Molecular Systematics of Fishes

Molecular Systematics of Fishes

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Molecular Systematics Fishes Edited by

Thomas D. Kocher Department of Zoology University of New Hampshire Durham, New Hampshire

Carol A. Stepien Department of Biology Case Western Reserve University Cleveland, Ohio

Academic Press San Diego London Boston New York Sydney Tokyo Toronto

This book is printed on acid-free paper. ( ~

Copyright 9 1997 by ACADEMIC PRESS All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. A c a d e m i c Press a division o f Harcourt Brace & Company

525 B Street, Suite 1900, San Diego, California 92101-4495, USA http://www.apnet.com Academic Press Limited 24-28 Oval Road, London NW 1 7DX, UK http://www.hbuk.co.uk/ap/ Library of Congress Cataloging-in-Publication Data Molecular systematics of fishes / edited by Thomas D. Kocher, Carol A. Stepien. p. cm. Includes bibliographical references and index. ISBN 0-12-417540-6 (alk. paper) 1. Fishes--Phylogeny. 2. Fishes--Molecular aspects. I. Kocher, Thomas D. II. Stepien, Carol A. QL618.2.M65 1997 96-49199 597.13'8--dc21 CIP

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Contents

Contributors Preface xi

ix

CHAPTER

3 CHAPTER

1 Molecules and Morphology in Studies of Fish Evolution Carol A. S tepien and Thomas D. Kocher

I. II. III. IV.

Introduction 1 History of Molecular Techniques 2 Controversy over Analytical Methods 5 Achievements and Failures of Molecular Systematics 7 V. Eight Promising Directions for Future Research 8 VI. A New Age of Synthesis 9 References 9

Molecular Systematics of a Rapidly Evolving Species Flock: The mbuna of Lake Malawi and the Search for Phylogenetic Signal Irv Kornfield and Alex Parker

I. Introduction 25 II. Molecular Investigations 26 III. Mitochondrial DNA and Ancestral Polymorphisms 26 IV. Alternate Molecular Approaches 27 V. Microsatellite Loci 28 VI. A Test of the Phylogenetic Potential of Microsatellites 29 VII. Materials and Methods 31 VIII. Results 32 IX. Discussion 33 X. Summary 35 References 35

CHAPTER

2

CHAPTER

Base Substitution in Fish Mitochondrial DNA: Patterns and Rates

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Thomas D. Kocher and Karen L. Carleton

Reconstruction of Cichlid Phylogeny Using Nuclear DNA Markers

I. II. III. IV.

Introduction 13 Simple Models of Substitution 13 Evolution of Real Sequences 15 Implications for Phylogenetic Reconstruction 19 V. Conclusions 23 References 24

Holger S~iltmann and Werner E. Mayer I. Introduction 39 II. Methods Used for Reconstructing Cichlid Phylogeny 40 III. Random Amplification of Polymorphic DNA (RAPD) 41

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CONTENTS

IV. Allele Size Frequencies at Dinucleotide Microsatellite Loci 45 V. Critical Evaluation Using RAPD and Microsatellite Allele Frequencies for the Reconstruction of Cichlid Fish Phylogeny References 49

CHAPTER

7 47

Phylogeographic Patterns in Populations of Cichlid Fishes from Rocky Habitats in Lake Tanganyika Christian Sturmbauer, Erik Verheyen, Lukas R~iber and Axel Meyer

CHAPTER

5 Biogeographic Analysis of Pacific Trout

(Oncorhynchusmykiss) in California and Mexico Based on Mitochondrial DNA and Nuclear Microsatellites Jennifer L. Nielsen, Monique C. Fountain and Jonathan M. Wright

I. Lake Tanganyika and Its Cichlid Species Flock 97 II. Speciation and DNA 98 III. From Patterns toward an Understanding of Processes 105 IV. Conclusions 109 References 109

CHAPTER

8 Fish Biogeography and Molecular Clocks: Perspectives from the Panamanian Isthmus

I. II. III. IV.

Introduction 53 Materials and Methods Results 57 Discussion 64 References 66 Appendices 70

Eldredge Bermingham, S. Shawn McCafferty and Andrew P. Martin

55

I. Introduction 113 II. Temporal Scaling: The Panama Isthmus and Molecular Clocks 114 III. Geographic Scaling: The Panama Isthmus and Caribbean Fish 119 IV. Geographic Scaling: The Panama Isthmus and the Circumtropical Abudefduf (Teleostei: Pomacentridae) Species Group 121 V. Geographic Scaling: The Panama Isthmus and Neotropical Freshwater Fishes 123 VI. Concluding Remarks 125 References 126

CHAPTER

6 Mitochondrial DNA Sequence Variation among the Sand Darters (Percidae: Teleostei) E. O. Wiley and Robert H. Hagen

I. II. III. IV. V. VI.

Introduction 75 Systematics of Sand Darters Methods and Materials 78 Results 78 Discussion 91 Summary 94 References 94 Appendices 96

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CHAPTER

9 The Utility of Mitochondrial DNA Control Region Sequences for Analyzing Phylogenetic Relationships among Populations, Species, and Genera of the Percidae Joseph E. Faber and Carol A. S tepien

I. Introduction 129 II. Materials and Methods

131

CONTENTS

III. Results 133 IV. Discussion 137 V. Material Examined References 140

140

vii

III. IV. V. VI. VII.

Allozymes and DNA 191 Fish Samples 191 DNA Sequences 191 Phylogenetic Relationships Conclusion 195 References 195

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CHAPTER

10 Phylogenetic Relationships among the Salmoninae Based on Nuclear and Mitochondrial DNA Sequences Ruth B. Phillips and Todd H. Oakley

CHAPTER

13 Interrelationships of Lamniform Sharks: Testing Phylogenetic Hypotheses with Sequence Data Gavin J. P. Naylor, Andrew P. Martin, Erik G. Mattison and Wesley M. Brown

I. Introduction 145 II. Conclusions 158 References 159

CHAPTER

11

I. Introduction 199 II. Materials and Methods III. Results and Discussion References 216 Appendix 218

Combining Molecular and Morphological Data in Fish Systematics: Examples from the Cyprinodontiformes

CHAPTER

14

Alex Parker

I. II. III. IV. v. VI. VII. VIII. IX.

Introduction 163 Analysis of Combined Data: Justification 164 Analysis of Combined Data: Methods 165 Consensus Approaches: Justification 166 Consensus Methods 166 Analysis of Cyprinodontiform Data 167 Methods 167 Results and Discussion 170 Conclusions 181 References 182 Appendices 184

202 204

Radiation of Characiform Fishes: Evidence from Mitochondrial and Nuclear DNA Sequences Guillermo Ortf

I. Introduction 219 II. Materials and Methods III. Results and Discussion References 240 Appendix 242

222 222

CHAPTER

15

CHAPTER

12 Molecular Phylogeny of the Fundulidae (Teleostei, Cyprinodontiformes) Based on the Cytochrome b Gene Giacomo Bernardi

I. Introduction 189 II. Morphology

190

The Evolution of Blennioid Fishes Based on an Analysis of Mitochondrial 12S rDNA Carol A. Stepien, Alison K. Dillon, Meriel J. Brooks, Kristen L. Chase and Allyson N. Hubers

I. II. III. IV.

Introduction 245 Materials and Methods Results 253 Discussion 258

250

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CONTENTS

V. Summary 267 References 268

VII. Conclusion 279 References 281

CHAPTER

CHAPTER

16

17

Major Histocompatibility Complex Genes in the Study of Fish Phylogeny

The Phylogenetic Utility of the Mitochondrial Cytochrome b Gene for Inferring Relationships among Actinopterygian Fishes

Jan Klein, Dagmar Klein, Felipe Figueroa, Akie Sato and Colin O'hUigin I. Introduction 271 II. Major Histocompatibility Complex (Mhc) Structure and Function 271 III. Mhc as a Source of Systematic Information 273 IV. Sequences as a Source of Phylogenetic and Systematic Information 273 V. Cladistic Analysis with Macromutations 275 VI. Mhc Gene Frequencies in Populations Undergoing Adaptive Radiation 276

Charles Lydeard and Kevin J. Roe I. Introduction 285 II. Materials and Methods III. Results and Discussion References 300 Taxonomic Index 305 Subject Index 311

288 289

Contributors

Numbers in parentheses indicate the pages on which the authors' contributions begin.

Allyson N. Hubers (245) Department of Biology, Case Western Reserve University, Cleveland, Ohio 44106.

Eldredge Bermingham (113) Smithsonian Tropical Research Institute, Balboa, Republic of Panama.

Dagmar Klein (271) Department of Microbiology and

Immunology, University of Miami School of Medicine, Miami, Florida 33136.

Giacomo Bernardi (189) Department of Biology, University of California, Santa Cruz, Santa Cruz, California 95064.

Jan Klein (271) Max-Planck-Institut ftir Biologie, Ab-

teilung Immungenetik, D-72076 Ttibingen, Germany and Department of Microbiology and Immunology, University of Miami School of Medicine, Miami, Florida 33136.

Meriel J. Brooks (245) Department of Science, Notre Dame College, South Euclid, Ohio 44121. Wesley M. Brown (199) Department of Biology, University of Michigan, Ann Arbor, Michigan 48109.

Thomas D. Kocher (1,13) Department of Zoology, University of New Hampshire, Durham, New Hampshire 03824.

Karen L. Carleton (13) Department of Zoology, University of New Hampshire, Durham, New Hampshire 03824.

Irv Kornfield (25) Department of Zoology and School of Marine Sciences, University of Maine, Orono, Maine 04469.

Kristen L. Chase (245) Department of Biology, Case Western Reserve University, Cleveland, Ohio 44106.

Western Reserve University, Cleveland, Ohio 44106.

Charles Lydeard (285) Aquatic Biology Program, University of Alabama, Department of Biological Sciences, Tuscaloosa, Alabama 35487.

Joseph E. Faber (129) Department of Biology, Case

Andrew P. Martin (113,199) Smithsonian Tropical Re-

Western Reserve University, Cleveland, Ohio 44106.

search Institute, Balboa, Republic of Panama and Department of Biological Sciences, University of Nevada Las Vegas, Las Vegas, Nevada 89154.

Alison K. Dillon (245) Department of Biology, Case

Felipe Figueroa (271) Max-Planck-Institut ftir Biologie, Abteilung Immungenetik, D-72076 Ttibingen, Germany.

Erik G. Mattison (199) Department of Biology, University of Michigan, Ann Arbor, Michigan 48109.

Monique C. Fountain (53) USDA Forest Service, Pa-

cific Southwest Research Station and Hopkins Marine Station, Department of Biology, Stanford University, Pacific Grove, California 93950.

Werner E. Mayer (39) Max-Planck-Institut ftir Bio-

Robert H. Hagan (75) Department of Entomology, University of Kansas, Lawrence, Kansas 66045.

S. Shawn McCafferty (113) Smithsonian Tropical Research Institute, Balboa, Republic of Panama.

logie, Abteilung Immungenetik, D-72076 Ttibingen, Germany.

ix

x

CONTRIBUTORS

Axel Meyer (97) Department of Ecology and Evolution, State University of New York at Stony Brook, Stony Brook, New York 11794.

Kevin J. Roe (285) Aquatic Biology Program, University of Alabama, Department of Biological Sciences, Tuscaloosa, Alabama 35487.

Gavin J. P. Naylor (199) Department of Biology, Osborn Memorial Laboratory, Yale University, New Haven, Connecticut 06520.

Lukas Riiber (97) Zoological Museum of the University of Zfirich, Switzerland.

Jennifer L. Nielsen (53) USDA Forest Service, Pacific Southwest Research Station and Hopkins Marine Station, Department of Biology, Stanford University, Pacific Grove, California 93950.

Akie Sato (271) Max-Planck-Institut ftir Biologie, Abteilung Immungenetik, D-72076 Ttibingen, Germany. Carol A. Stepien (1,129,245) Department of Biology, Case Western Reserve University, Cleveland, Ohio 44106.

Colm O'hUigin (271) Max-Planck-Institut ffir Biologie, Abteilung Immungenetik, D-72076 Tfibingen, Germany.

Christian Sturmbauer (97) Department of Zoology, University of Innsbruck, A-6020 Innsbruck Austria.

Todd H. Oakley (145) Department of Biological Sciences, University of Wisconsin- Milwaukee, Milwaukee, Wisconsin 53201.

I-Iolger Siiltmann (39) Max-Planck-Institut ftir Biologie, Abteilung Immungenetik, D-72076 Tfibingen, Germany.

Guillermo Orti (219) Department of Genetics, University of Georgia, Athens, Georgia 30602.

Erik Verheyen (97) Royal Belgium Institute of Natural Sciences, B-1000 Brussels, Belgium.

Alex Parker (25,163) Department of Zoology and School of Marine Sciences, University of Maine, Orono, Maine 04469.

E. O. Wiley (75) Museum of Natural History and Department of Systematics and Ecology, University of Kansas, Lawrence, Kansas 66045.

Ruth B. Phillips (145) Department of Biological Sciences, University of Wisconsin - Milwaukee, Milwaukee, Wisconsin 53201.

Jonathan M. Wright (53) Marine Gene Probe Laboratory, Department of Biology, Dalhousie University, Halifax, Nova Scotia B3H 4J1, Canada.

f , ce

ber, Allyson N. Hubers, Mark D. Chandler, Rachel A. Bartholomew, Rachael A. Callcut, and Gary R. Kutsikovich reviewed the entire volume at various stages. We owe special thanks to Rachel A. Bartholomew and Rachael A. Callcut for helping to prepare the indices, Karen L. Carleton for work on the references, and Craig Albertson for the artwork on the cover jacket. Our work on the molecular systematics of fishes has been generously funded by grants from the National Science Foundation, the Alfred Sloan Foundation, the National Geographic Society, the National Research Council, and the NOAA Sea Grant Program. We especially thank our families and students for their patience and understanding during the many periods that our work has required us to be elsewhere--in body or in thought. This volume is dedicated to our mentors (especially Richard Rosenblatt, David Hillis, Allan Wilson, and Jeff Mitton) who encouraged, critiqued, and shaped our ideas in molecular systematics. We hope that this volume will contribute to the preservation of fish species so that future generations will be able to wonder at the beauty and diversity of fishes in their natural habitats.

Fishes are the most diverse group of extant vertebrates, and yet our knowledge of the evolutionary relationships among them is largely incomplete. Over the past few years, molecular genetic methods, particularly PCR amplification and DNA sequencing, have become widely used to study the evolutionary history of fishes. Because of the strong tradition of morphological systematics of fishes, this group is uniquely suitable for testing and evaluating the efficacy of different approaches to elucidating the relationships among taxa. This book surveys the use of these new methods at many taxonomic levels, from the structure of local populations to the relationships among the deepest branches of the piscine family tree. The authors bring a diversity of experience and approaches to their analyses, and the result is a collective evaluation of the utility of these techniques for understanding evolutionary patterns and processes. Although this book focuses on fishes, the conclusions should be broadly applicable to the molecular systematics of other groups. We thank the authors for seeing this project through to completion. We are indebted to a host of anonymous individuals for constructive critical reviews of each chapter in manuscript form. In an increasingly busy world, it was a delight to see that many careful reviewers are still willing to take the time to coax a higher quality manuscript from their colleagues. In addition to these reviewers, Raymond R. Wilson, Joseph E. Fa-

Thomas D. Kocher, University of New Hampshire Carol A. Stepien, Case Western Reserve University

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C H A P T E R

1 Molecules and Morphology in Studies ofFish Evolution CAROL A. STEPIEN

T H O M A S D. KOCHER

Department of Biology Case Western Reserve University Cleveland, Ohio 44106

Department of Zoology University of New Hampshire Durham, New Hampshire 03824

I. I n t r o d u c t i o n

Fishes are the most diverse group of living vertebrates, with more than 24,600 extant species currently known (Nelson, 1994). For more than a century, systematists have sought to organize this diversity by studying aspects of their external and internal morphology. Their patient counting and dissection have achieved remarkable success in identifying groups of evolutionarily related species and provide the foundation and starting point for all current work on the systematics of fishes (for summaries of present status of morphological systematics of fishes see Nelson, 1994; Stiassny et al., 1996). The development of molecular techniques has helped invigorate studies of fish systematics. The realm of methods developed for molecular systematics (Hillis, et al., 1996; Ferraris and Palumbi, 1996) offer new suites of characters for analyzing relationships among fishes (Carvalho and Pitcher, 1995) and have been effectively applied from the level of populations to orders. It is hoped that this book illustrates the broad utility of molecular approaches for addressing fish systematic questions. Morphological studies have been especially successful in defining species and in organizing these species into genera. These groupings have usually been confirmed when examined with molecular approaches. Molecular characters have revealed some cryptic species (reviewed by Avise, 1994) and identified some inMOLECULAR SYSTEMATICS OF FISHES

correctly split groups (e.g., species in the clinid kelpfish genus Gibbonsia by Stepien and Rosenblatt, 1991; Stepien et al., Chapter 15). In general, the overall concordance between morphological and molecular studies has been good. Testing for congruence of relationships derived from independent data sets is a particularly robust approach to systematic problems (Miyamoto and Fitch, 1995). Although morphological studies have generally been successful in defining genera, it is rare to find studies which present a hypothesis of relationship above the level of the species comprising a genus, primarily due to a lack of congruence of characters. Fortunately, this is one of the strengths of molecular data, and inter- and intrageneric relationships are now being rapidly tested and elucidated. Molecular data are also the primary means used to assess the phylogeographic relationships among populations, examining questions of zoogeographic subdivision and relationships among areas (see Chapter 5 by Nielsen et al., Chapter 8 by Bermingham et al., and Chapter 9 by Faber and Stepien). Studies at these lower systematic levels are shedding more light on the mechanisms underlying the diversity of fishes. Both morphological and molecular studies have had particular difficulty discerning higher-level relationships. In both types of data, the central problems are identifying homologous characters and finding a sufficient number of synapomorphies to identify lineages with statistical confidence. Although great strides have Copyright 9 1997 by Academic Press. All rights of reproduction in any form reserved.

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CAROL A. STEPIEN A N D THOMAS D. KOCHER

been made in identifying appropriate molecules and refining analytical techniques, interpreting relationships among the deepest clades of the piscine phylogeny are still problematic. This book is arranged in approximate order of primary phylogenetic problems addressed, ranging from lower (relationships among populations and closely related species) to higher-level systematic questions. The first set of chapters primarily focus on discerning population and species level problems in relation to phylogeography and include Chapter 3 by Kornfield and Parker (mbuna species flock), Chapter 4 by S~iltmann and Mayer (cichlid adaptive radiation), Chapter 5 by Nielsen et al. (Pacific trout Oncorhynchus), Chapter 6 by Wiley and Hagen (sand darters Ammocrypta), Chapter 7 by Sturmbauer et al. (cichlids), and Chapter 8 by Bermingham et al. (biogeographic patterns involving fishes of the Panamanian Isthmus). The next set of chapters address resolution of DNA for testing middle-level systematic problems (species through family-level questions) and discriminating among morphology-based hypotheses, including Chapter 9 by Faber and Stepien (Percidae), Chapter 10 by Phillips and Oakley (Salmoninae), Chapter 11 by Parker (Cyprinodontiformes), and Chapter 12 by Bernardi (Fundulidae, Cyprinodontiformes). The final set of chapters focus on the resolution power of genes to address higher-level systematic questions and evaluating the level of maximum phylogenetic utility. These include Chapter 13 by Naylor et al. (lamniform sharks), Chapter 14 by Orti (Characiformes), Chapter 15 by Stepien et al. (Blennioidei), Chapter 16 by Klein et al. (Cichlidae), and Chapter 17 by Lydeard and Roe (Actinopterygii).

II. History of Molecular Techniques An increasingly sophisticated realm of techniques has been developed since the mid-1970s to study the molecular similarities of organisms. Although preceded by protein sequencing and immunology, the widespread use of molecular techniques in fish systematics really began with the discovery of allozyme polymorphisms. A. A l l o z y m e S t u d i e s

Allozyme/isozyme studies involve identifying protein polymorphisms by comparing their similarities and differences in net electric charge. Allozyme and isozyme studies have been one of the most popular approaches in examining population genetic and stock

divergence questions in fishes. They have also been especially useful in identifying cryptic species and in testing biogeographic hypotheses. Allozyme/isozyme electrophoresis has the advantage of being relatively rapid, cost effective, and efficient. Another advantage is that the sampling is spread over a variety of presumably independent gene loci. The chief disadvantage of using an allozyme approach is that bands (alleles) that have the same electric charge and migrate to the same point in the gel may not be homologous (i.e., evolutionary convergence). The scoring of gels is often somewhat subjective and bands are difficult to interpret when weak or close together. Variants have traditionally been assumed to be selectively neutral, enabling hypotheses of separation time to be tested. However, several studies have shown that some allozyme variants are not neutral markers and are under selection (Avise, 1994; Pogson et al., 1995; Powers and Shulte, 1996). Our view is that increasing evidence shows that most (if not all) "neutral" genetic markers, including allozymes, mtDNA, and microsatellites, are indeed subject to varying amounts of selective constraint. The possibility that loci are under selection does not eliminate their utility in systematics, however. For example, morphologists regularly utilize characters that are the products of selection. In this volume, Nielsen et al. (Chapter 5; Salmonidae) and Stepien et al. (Chapter 15; Blennioidei) examine the congruence of hypotheses derived from allozyme data with other molecular data sets. B. M i t o c h o n d r i a l D N A

The mitochondrial (rot) genome has many properties that make it useful for reconstructing recent phylogenetic history (reviewed by Wilson et al., 1985; Avise, 1994; Simon et al., 1994). The most important feature is its clonal inheritance. Fish mitochondrial genomes are haploid and apparently nonrecombining. The evolution of the molecule therefore corresponds exactly to the model of bifurcating evolutionary trees. Second, mtDNA evolves more quickly than most nuclear genes, allowing the identification of informative phylogenetic characters among even closely related species and populations. Two other features of mtDNA are typically listed as advantages for phylogenetic analysis. First, mtDNA is maternally inherited. Although it is true that mtDNA is predominantly maternally inherited, several instances of heteroplasmy of distinct mitochondrial lineages suggest that this is not strictly, or universally correct (Magoulas and Zouros, 1993). Second, it may no longer be appropriate to consider that substitutions in mtDNA accumulate according to a strictly neutral process.

1. Molecules and Morphology in Studies of Fish Evolution

Patterns of sequence differentiation suggest that selective sweeps may be common (Ballard and Kreitman, 1994), and laboratory experiments have suggested competitive differences among mitochondrial haplotypes (Hutter and Rand, 1995). Whether these departures from neutral evolution invalidate the concept of molecular clocks remains to be seen. Many studies of mtDNA have analyzed restriction fragment length polymorphisms (RFLPs). Whole mtDNA can be digested with specific endonucleases, and the products are then separated by size using gel electrophoresis. In the most comprehensive studies, restriction sites are mapped and their presence or absence (rather than mere sharing of fragment lengths) is scored (Dowling et al., 1990). RFLP studies have been a popular approach in quantifying the degree of divergence within and among populations. In applying this approach to species and higher-level systematic questions, the homology of restriction site characters becomes less certain. A better approach for these comparisons involves direct analysis of DNA sequences.

C. Polymerase Chain Reaction and DNA Sequencing Until the development of the polymerase chain reaction (PCR) (Saiki et al., 1988), sequencing of genes for phylogenetic analysis was rarely performed because of the huge investment required to clone homologous genes from multiple samples. The introduction of primer sequences with wide phylogenetic utility ("universal primers"; e.g., Kocher et al. 1989) allowed the rapid amplification of particular sequences from a large number of samples and helped create an explosion of studies using DNA sequences to examine phylogenetic questions. DNA sequence data have a number of inherent advantages over other kinds of systematic data. First, an essentially unlimited number of sequence characters are potentially available. Fish genomes typically contain on the order of a billion nucleotide pairs, each of which is potentially informative for phylogenetic analysis. Second, these characters are useful for studying relationships among both close and distant relatives. Each gene, as well as individual sites within a gene, evolves at a unique rate because of variation in the level of functional constraint. Slowly evolving genes such as nuclear 18S rDNA may be useful for discerning relationships among highly divergent groups (Hillis and Dixon, 1991). More rapidly evolving areas, such as the mtDNA control region, may be useful for discerning lower-level systematic relationships, such as among populations and species, as shown for percid relationships in the study by Faber and Stepien

(Chapter 9). In coding regions, the variation in DNA sequences may be evaluated among first, second, and third codon positions and at the amino acid level in order to increase potential phylogenetic utility at higher systematic levels. The relative strength of the phylogenetic signal with codon position and between the nucleotide and amino acid levels are critically evaluated by Naylor et al. (Chapter 13) and Lydeard and Roe (Chapter 17).

D. Mitochondrial DNA Sequence Regions Mitochondrial DNA regions have been well studied in fishes, and knowledge of universal primer sequences (e.g., Kocher et al., 1989; Meyer ef al., 1990, Simon et al., 1994; Palumbi, 1996) for amplification by PCR and sequencing has made them very accessible. As illustrated in this volume, they can be effectively used to address many different levels of taxonomic questions, depending on the region sequenced and the use of various correction factors for types and positions of substitutions. Silent sites of mitochondrial protein-coding genes and the nontranscribed control region are shown to be particularly useful for analyzing relationships of recently diverged taxa, such as among populations, species, and genera. In the case of higherlevel systematic questions, silent sites and rapidly evolving regions may have experienced multiple substitutions, obscuring phylogenetic signal. At higher taxonomic levels, more slowly evolving regions, such as the 12S and 16S ribosomal RNA genes may be useful. Alternatively, because substitutions in nonsynonymous nucleotide sites (which alter the encoded amino acids) occur more rarely, these changes may provide a higher signal/noise ratio for deep comparisons. The sequence evolution of mtDNA has been relatively well studied in fishes. Base substitution events occur relatively rapidly. MtDNA structure, gene order, and secondary structure are largely conserved in fishes, as well as in other vertebrates. It is inherited as a single unit and thus has been characterized as sampling a single gene, which is a possible disadvantage that may particularly affect population genetic studies. Because the evolutionary history of a single gene can be different from the average history of an entire genome (discussed by Avise, 1994), caution must be used in interpreting mitochondrial gene trees as reflecting the history of populations. The cytochrome b gene is probably the best-studied mitochondrial gene in fishes (e.g., Kocher et al., 1989; Meyer et al., 1990; Carr and Marshall, 1991; Block et al., 1993; Zhu et al., 1994; Carr et al., 1995). Like most mitochondrially encoded proteins, it is a transmembrane protein important in the respiratory chain of cellular

4

CAROL A. STEPIEN AND THOMAS D. KOCHER

metabolism. Although it has been widely used, some have questioned the ability of this sequence (especially short subsets of the gene) to resolve phylogenies (Martin et al., 1990; Graybeal, 1993; Meyer, 1994). In this volume, mtDNA sequences from the cytochrome b gene are used to analyze a variety of levels of relationships ranging from population genetics to higher-level systematics. For example, Bermingham et al. (Chapter 8) use cytochrome b data to assess population genetic and phylogeographic questions in tropical damselfishes of the Abudefduf saxatilis species group. Cytochrome b sequences are used to analyze relationships among species and groups of sand darters (family Percidae) (Wiley and Hagen, Chapter 6), among species of salmonids (Phillips and Oakley, Chapter 11), among members of the family Fundulidae (Cyprinodontiformes) (Bernardi, Chapter 12), and among lamniform sharks (Naylor et al., Chapter 13). At higher taxonomic levels, Lydeard and Roe (Chapter 17) test the use of cytochrome b to analyze relationships among actinopterygian fishes, revealing strong phylogenetic signal. By examining their data using different codon positions, Lydeard and Roe achieve greater utility at higher taxonomic levels than does Bernardi (Chapter 12). Mitochondrial ribosomal genes (12S and 16S rDNA subunits) are often used to study more distantly related taxa. Substitutions in the small subunit (12S) accumulate relatively slowly, approximating the average for the entire mitochondrial genome, whereas those in the large subunit (16S) evolve even more slowly (Simon et al., 1994). The 12S rDNA gene is used by Stepien et al. (Chapter 15) to examine relationships among species, genera, tribes, families, and suborders of blenniiform fishes, showing strong utility at these different levels and congruence with morphological-based hypotheses. Stepien (12S; Chapter 15), Orti (12S and 16S, Characiform fishes; Chapter 14), and Parker (16S, Cyprinodontiformes; Chapter 11) evaluate differences in the amount of phylogenetic signal among stem and loop regions of the ribosomal genes, reporting a greater retention of the phylogenetic signal at higher taxonomic levels in the more slowly evolving stem regions and more useful characters at lower taxonomic levels in the more rapidly changing loop regions. The mtDNA control region is involved in the control of mtDNA replication and RNA transcription. It is also called the displacement loop (D-loop) because one of the two strands of the helix is displaced by the synthesis of a new strand during replication. The highly variable left domain region has been believed to be largely selectively neutral, which may account for its very rapid rate of variation. In fishes, the control region is usually long (e.g., 888 to 1223 bp in percids; Faber and Stepien, Chapter 9) and often contains tandemly repeated segments. There is a set of conserved se-

quence blocks that are probably involved in controlling mtDNA replication and transcription, which may be useful for some systematic studies (see Attardi, 1985; Lee et al., 1995; Faber and Stepien, Chapter 9). The highly variable control region has thus been a popular sequence for examining population structure and relationships among closely related species of fishes (e.g., Meyer et al., 1990; Arnason and Rand, 1992; Sturmbauer and Meyer, 1992, 1993; Brown et al., 1993; Stepien, 1995; Lee et al., 1995). In this volume, Sturmbauer et al. (Chapter 7) employ sequence data from the control region to address phylogenetic questions and models of adaptive radiation and biogeography of cichlid fishes in Lake Tanganyika, Africa. Nielsen et al. (Chapter 5) utilize control region variation to discern patterns of geographic structure in the Pacific trout Oncorhynchus mykiss. The utility of control region sequences for discerning higher-level relationships is critically evaluated by Phillips and Oakley (Chapter 11) and by Faber and Stepien (Chapter 9). Although some areas of this rapidly evolving sequence are alignable even among distantly related fishes (see Lee et al., 1995), the high rate of evolution of this sequence appears to preclude analyses beyond the level of closely related species and perhaps genera. E. N u c l e a r

DNA Sequences

Several nuclear DNA regions have been used to address systematic questions among fishes. One of these is the major histocompatibility complex (MHC) used by Klein et al. (Chapter 16) to examine evolutionary hypotheses of the haplochromine flock of cichlids in Lake Victoria, East Africa. MHC molecules are believed to play a central role in the vertebrate immune system by presenting peptides to T lymphocytes, thereby initiating immune response cascades. Because MHC molecules are well known due to their role in the immune system and are highly variable, they also offer a wealth of potential systematic information. There are two classes of MHC molecules (I and II), which each consist of two polypeptide chains (a and b), but differ in structure and function (Bjorkman and Parham, 1990). Klein et al. (Chapter 16) use examples from classes I and II to test phylogenetic utility among recently diverged fish species as well as at higher phylogenetic levels. They also address whether selection causes sequence and allele frequency convergence in MHC genes. Stepien et al. (Chapter 15) compare sequence-based trees of blennioid fishes derived from the nuclear internal transcribed spacer (ITS)-1 region of the ribosomal array (Stepien et al., 1993) with trees produced from mitochondrial 12S rDNA gene sequences. A much greater number of variable characters is obtained using mtDNA 12S gene than was found from the nuclear

1. Molecules and Morphology in Studies ofFish Evolution

ITS-1 region (Stepien et al., 1993), suggesting that nuclear ITS sequences are best used for studying deeper divergences. In contrast, Phillips and Oakley (Chapter 10) find nuclear rDNA spacers to be most useful at lower taxonomic levels (interspecific and subspecific levels). These results suggest that the ITS-1 region may evolve at different rates in different fish groups. Other chapters explore the utility of new genes for phylogenetic analysis. Parker (Chapter 11) tests the relative degree of phylogenetic signal among first, second, and third codon positions of the nuclear tyrosine kinase gene X-src sequences for resolving relationships among the cyprinodontid killifishes. Orti (Chapter 14) compares nuclear DNA sequences from the protein-coding gene ependymin (a major glycoprotein component of the extracellular fluid in the brain of fishes) with mitochondrial 12S and 16S rDNA sequences to test the evolution of characiform fishes at various hierarchical levels. Much work remains in identifying a standard set of nuclear genes for phylogenetic analysis of fishes. F. O t h e r N u c l e a r Techniques

The introduction of PCR opened other avenues for the analysis of genome sequences. We touch here on two popular methods: randomly amplified polymorphic DNAs (RAPDs) and microsatellite polymorphisms. The RAPD method primarily detects sequence changes within the annealing sites of PCR primers, resulting in the presence or absence of amplification products from a particular locus. RAPD polymorphisms usually have a pattern of dominant inheritance (Williams et al., 1990) and can be used to screen for differences among individuals, populations, and species. Sultmann and Mayer (Chapter 4) employ RAPDs to identify polymorphic loci in cichlid groups, followed by locus-specific DNA amplification and sequence determination of the fragments. In this way, they avoid problems with determining homology of fragments among species. They find a large number of insertions and deletions (some of which are species specific) that can be treated as characters along with nucleotide substitutions. Their phylogenies show considerable congruence with morphological hypotheses and other molecular studies. They conclude that RAPDs are able to detect polymorphisms among closely related taxonomic groups, ranging from populations to genera. Microsatellite DNAs are highly variable, tandemly repeated DNA sequences with unit repeats one to six bases in length. Length polymorphisms arising from variation in the number of repeats are quantified by sizing PCR-amplified copies of the locus on a polyacrylamide gel. Microsatellites are abundantly distrib-

5

uted throughout the nuclear genome and are highly polymorphic. They follow a Mendelian codominant inheritance pattern. Microsatellites have been widely used to analyze mating systems and population genetic structure (Queller et al., 1993), despite the fact that their pattern of mutation is still poorly understood (Jarne and Lagoda, 1996). In Chapter 5, Nielsen et al. examine the biogeographic variation of nuclear microsatellite repeats in Pacific trout, O. mykiss, in comparison with mtDNA control region sequences. Although their mtDNA data show significant latitudinal and longitudinal correlations, microsatellite data are only weakly associated with longitude (and not at all with latitude). These differences suggest that the evolutionary processes resulting in phylogeographic patterns of genetic variation differentially affect the mitochondrial and nuclear genomes. Kornfield and Parker (Chapter 3) test the utility of microsatellite loci for examining relationships within a rapidly evolving species flock (the mbuna of Lake Malawi), in comparison with results from allozyme, mtDNA RFLP, mtDNA sequence, nuclear DNA sequence, and RAPDs data sets. They conclude that microsatellites are the first class of molecular markers to possess sufficient power to elucidate that level of evolutionary history. Sultman and Mayer (Chapter 4) compare microsatellite allele size frequencies among cichlid species from Lake Victoria. In total, these results suggest that microsatellite loci are applicable to species- and population-level work in rapidly evolving groups, as exemplified by the adaptive radiations of the Cichlidae. G. A L o o k to the Future

Although new kinds of polymorphisms will be identified as we come to understand the structure of genomes, there is some hope that the techniques used to study these polymorphisms have stabilized. Most investigators are now directly examining DNA sequence polymorphisms, the most fundamental unit of molecular variation. PCR and DNA sequencing will likely be the primary tools of molecular systematics in the foreseeable future. We anticipate that the major differences will be increases in length of sequence examined and the number of genetic loci scored.

III. Controversy over Analytical Methods Systematic biology is well known for its vigorous and highly polarized methodological debates. Although much of the acrimony has subsided, strong proponents of distance and cladistic approaches remain. This polarization is strongly correlated with the type of

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CAROL A. STEPIEN A N D THOMAS D. KOCHER

data sets studied by individual scientists. Morphologists have generally rejected distance approaches. Molecular systematists appear relatively flexible in the approaches taken to recover phylogenetic relationships from their data and have found that the evolution of sequences is often most easily modeled with distance methods. Still, character-state analyses of molecular data abound, and we should be careful not to equate molecular studies with distance analyses or morphological studies with cladistic analyses.

A. Cladistic Approaches The rise of cladistic methodology, as proposed by Hennig (1950, 1966) and popularized by Wiley (1981), has greatly contributed to the development of systematics from a collection of ad hoc procedures to a respectable science. Cladistics has markedly increased objectivity for interpreting the evolutionary history of characters and testing the relative strength of competing systematic hypotheses. This standard methodology has facilitated the comparison of hypotheses proposed by various investigators and support for different types of data sets. Examples of such comparisons occur in almost every chapter of this volume.

B. Distance Approaches Along with the development of molecular techniques, such as allozyme-isozyme electrophoresis, emerged the use of genetic distances and clustering algorithms which describe the degree of similarity or genetic relatedness among pairs of taxa and summarize this information in a "tree." Distance methods differ from cladistics in that they reduce the difference among each pair of taxa to a single number. Some workers argue that distance methods lose information inherent in the character-state matrix. Others argue that distance methods allow the evolution of the sequence to be more easily modeled. This allows accurate correction for unobserved multiple substitutions (homoplasy) in sequence data that is not possible with other methods. Like character-state methods, distance methods can be bootstrapped to evaluate the internal consistency of data. Recent theoretical work has focused on the calculation of standard errors of distances and branch lengths. Most types of distance trees are constructed with branch lengths that are proportional to the amount of divergence, making it possible to estimate relative times of separation.

C. Distance Corrections, Weighting,

and Clustering Genetic distances may be corrected for the effects of multiple substitutions per site. Methods for correcting

these include the Jukes-Cantor equation (Jukes and Cantor, 1969), which uses a Poisson model to calculate the probabilities of multiple substitutions, assuming equal probability of the type of substitution, no nucleotide bias (same proportions of G, A, T, and C), and that all sites along a sequence have an equal probability of change. Because some or all of these assumptions are violated by most DNA sequence data sets, additional correction factors are often used. The Kimura twoparameter method (Kimura, 1980) allows differential weighting of transition and transversion probabilities. Tamura and Nei's (1993) distance correction is based on the gamma distribution and corrects for nucleotide frequency differences, transition:transversion biases, and variation of substitution rate among different sites. Gamma distances are discussed at length by Kocher and Carleton (Chapter 2). Kumar et al. (1993) suggest that if various distance correction methods give similar results, then the simplest possible model should be used in order to minimize variance of the estimates. They suggest using the Jukes-Cantor or simple pairwise distances in cases when genetic distances are low, as long as substitution rates do not vary among lineages. Differential weighting of characters has been widely discussed (Wheeler, 1986; Swofford et al., 1996). It is clear that data for different nucleotide positions in coding regions, i.e., first, second, and third codon positions, should be analyzed separately because of their distinct patterns of selective constraint. Weighting is a relatively crude way to correct for the variation in rate among sites in noncoding sequences, especially as the pattern of selective constraint for these sequences is poorly understood. Weighting has also been used to model the relative frequency of different types of nucleotide substitution in parsimony analyses (Fitch and Ye, 1991). The advantage of this approach relative to the use of an appropriate distance method is not clear. Clustering algorithms have greatly improved in recent years. Neighbor joining (Saitou and Nei, 1987) is a widely used distance clustering algorithm that allows unequal rates of divergences among lineages. It is no longer necessary (or desirable) to assume that rates of sequence change are constant throughout a phylogeny.

D. Molecular Clocks Use of molecular characters has also been associated with the assumption of a "molecular clock," i.e., that mutations arise at relatively regular, predictable rates (Zuckerkandl and Pauling, 1962, 1965). Today, it is unlikely that any proponents of a universal clock, that ticks at a regular rate across all taxa, remain. Still, most workers accept the idea of local clockswthat rates of evolution within a particular group are relatively

1. Molecules and Morphology in Studies ofFish Evolution

similar. Clocks may be calibrated based on comparisons with taxa having known divergences, using wellcorroborated geological events (such as the linkage of the Isthmus of Panama as a barrier between the Atlantic and Pacific aquatic fauna; see Vawter et al, 1980; Grant, 1987; Stepien and Rosenblatt, 1996; Chapter 8 by Bermingham et al.), or with the fossil record. Dating divergences to the fossil record is complicated by the fact that the actual divergence usually predates its first fossil appearance by an unknown amount of time. Problems with clock calibration are discussed by Bermingham et al. (Chapter 8) and by Stepien et al. (Chapter 15).

E. Combining Data and Testing f o r Congruence There are two primary schools of thought among systematic biologists regarding combining morphological and molecular data. The first is the "total evidence" approach (Mickevich and Johnson, 1976; Kluge and Wolf, 1993) which states that phylogenetic analysis should be performed on a combined data set using all possible evidence. The null hypothesis for this approach is that there are no significant differences or partitions within the data set, i.e., that there is only one evolutionary history for the clade in question. Huelsenbeck et al. (1996) raise the point that estimates from total evidence have less sampling error as separate analyses of data partitions are based on fewer characters. It is advocated that total evidence tests should examine whether different sets of data have significantly different signals and these possible partitions should be tested against the combined data set (de Queiroz, 1993; Bull et al., 1993, Ballard, 1996). The other school of thought states that data sets should be analyzed separately (see Bull et al., 1993; Miyamoto and Fitch, 1995). Relationships among taxa that are congruent in separate analyses are regarded as strongly supported. In other words, the congruence of data from separate sources (such as separate analyses using different genes, or between morphological and molecular data sets) indicates increased support that the relationships are likely to be true. Miyamoto and Fitch (1995) suggest that relationships among taxa that are supported by different independent data sets are particularly robust, equivalent to obtaining independent verification of an experimental hypothesis from a different experimental source. This independent type of verification may be lost in combining data sets. An explicit assessment of congruence versus total evidence approaches is discussed in Chapter 11 by Parker. Parker analyzes problems in systematics of the Cyprinodontiformes by combining morphological characters from Parenti (1981, 1984) along with mo-

7

lecular data, including the nuclear tyrosine kinase gene X-src (Meyer and Lydeard, 1993) and mt16S rDNA sequences (Parker and Kornfield, 1995). He evaluates the methodology for combining data sets and comparing trees, including T-PTP (Faith, 1991) and bootstrap tests (Rodrigo et al., 1993). His conclusions argue for the utility of both combination and congruence approaches. Many of the authors in this volume compare taxonomic congruence between molecular-based and morphological-based hypotheses (e.g., Chapter 9 by Faber and Stepien, Chapter 10 by Phillips and Oakley, Chapter 12 by Bernardi, and Chapter 17 by Lydeard and Roe). Phillips and Oakley (Chapter 10) compare results from morphological and molecular studies of salmonid relationships and conclude that morphological traits suggesting one clade are unreliable. Bernardi (Chapter 12) discerns considerable concordance between molecular data and the definition of subgenera, but is unable to resolve higher-level relationships within the family. Lydeard and Roe (Chapter 17) also find greatest concordance of the two types of data at the lowest levels of the taxonomic hierarchy.

IV. Achievements and Failures of Molecular Systematics The greatest achievement of molecular systematics is the consistent and large set of characters generated for the analysis of phylogenies. The availability of these data has allowed the resolution of many intrageneric phylogenies that had not been previously addressed. Molecular studies have been spectacularly successful at the lowest taxonomic levels, particularly the analysis of relationships among populations or intraspecific phylogeography (Avise et al., 1987; see Chapters 3 through 9 of this volume). Molecular data offer an abundance of characters for studies at this level. Molecular studies have not yet fulfilled their promise for resolving deep relationships. There are two problems holding up progress in this area. First, it can become difficult to identify homology in highly diverged sequences. Alignments of characters becomes more difficult as the sequences diverge, particularly for hypervariable regions of rDNA genes. Hillis and Dixon (1991) have suggested that rDNA sequences beyond about 30% sequence difference should be discarded as unalignable. A better understanding of the relationship between rRNA structure and function would help in the identification of homologous sites. The second problem is "saturation": the equilibrium value of sequence difference that is reached when mul-

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tiple substitutions erase the record of previous substitutions at a site. For DNA sequence data there are only four nucleotide character states, G, A, T, and C, thus base substitutions at single nucleotide sites are often obscured by multiple substitutions at sites (multiple hits). As with morphological data sets, apparent synapomorphies may be the result of homoplastic convergence rather than shared common ancestry. Saturation is apparent in many molecular systematic studies. Claims that a group of taxa radiated rapidly at some time in the past should be scrutinized. It may be that molecular data are saturated and therefore uninformative as to the timing of particular branching events. This problem may be lessened either by examining more slowly evolving sites or by considering the codon as the character (rather than the individual nucleotides; Goldman and Yang, 1994; see Chapter 13 by Naylor et al. and Chapter 17 by Lydeard and Roe). Further studies of mutational processes, and the selective forces underlying variation in rate among sites, are needed. Alternatively, new kinds of data, such as the analysis of positional data, may be needed. Patterns of SINE insertion (Murata et al., 1993) or the order of homologous loci (Boore et al., 1995) provide another approach for resolving deep relationships. Molecular studies have also failed to resolve the phylogeny of some rapidly speciating groups. Even an accurate phylogeny of a gene may not be informative as to the relationships of the species under study. If the gene pools are isolated more rapidly than polymorphisms can be fixed in a lineage, then the reconstructed gene trees may not parallel the evolution of the species (Moran and Kornfield, 1993; Parker and Kornfield, 1997; Chapter 3 by Kornfield and Parker; Chapter 7 by Sturmbauer et al.). Instead, the polymorphisms may be carried through the speciation event and be randomly fixed in the descendant populations (see discussion by Avise, 1994). The solution of this problem may require brute force; the construction of many independent gene trees may uncover the relationships among populations.

1. Integration of Intraspecific Biogeographic Patterns with Studies of Speciation The study of the phylogenetic histories of populations in relation to biogeography has been termed "intraspecific phylogeography" (Avise et al., 1987). Several chapters in this volume specifically address testing these types of phylogeographic questions using fishes. Specifically, Wiley and Hagen (Chapter 6) test geographic distribution and likely histories of vicariance in a southeastern United States percid group, the sand darters. Faber and Stepien (Chapter 9) test for geographic relationship among spawning populations of walleye, Stizostedion vitreum, addressing whether gene flow is decreased due to natal homing. The evolution of species flocks, models of adaptive radiation, and biogeographic barriers are tested by Sturmbauer et al. (Chapter 7) for the cichlids of Lake Tanganyika, Africa. In studies of Panamanian freshwater fishes, Bermingham et al. (Chapter 8) describe very high levels of genetic divergence among populations, postulating that very high levels of phylogeographic structuring may be common in species exhibiting distributions that span large distances across physically isolated drainages. These studies are beginning to shed light on the role of geographic processes in speciation.

2. Reconstruction of Phylogenies among Congeners The now standard methodology of sequencing short stretches of the mitochondrial genome will continue to bear fruit in the analysis of relationships within genera. As outlined by Kocher and Carleton in Chapter 2, these efforts will be most successful for divergences within the last 5 million years. The steady accumulation of these sequences will allow the construction of intrageneric phylogenies for many groups of fishes and will lay the groundwork for studies attempting to understand relationships further back in time.

3. Reconstruction of Higher-Level Relationships Using Longer Sequences V. Eight Promising Directions for Future Research Molecular systematists have been working with DNA sequences for most of the last decade. The basic techniques of PCR and DNA sequencing are firmly established, but how will they be applied in the future? The following areas of molecular systematics may prove especially rewarding in the future.

Continuing advances in DNA sequencing technology suggest that it will be practical to analyze increasingly longer segments of DNA. Up to a point, longer sequences will allow the resolution of more ancient divergences. Hillis (1996) has suggested that sequences only 5000 bp long may be sufficient to accurately reconstruct even complex phylogenies. This seems a good intermediate goal, although additional complete mitochondrial sequences and many more nuclear sequences would be useful for some questions.

1. Molecules and Morphology in Studies ofFish Evolution

4. Analysis of Developmental Homologies at the Molecular Level Developmental biologists are beginning to focus on the analysis of fish development. A recent mutant hunt resulted in the isolation of more than 1500 mutations affecting development of the zebrafish (Haffter et al., 1996; Driever et al., 1996). We suspect that the genetic basis for many morphological differences will be revealed in the near future. Although the impact on the systematics of fishes is difficult to predict, the elucidation of molecular mechanisms generating morphological differences is sure to have an impact on the analysis of such characters. Where it is possible to cross species, it may be possible to identify the number of genes responsible for morphological differences (e.g., Doebley, 1992), quantifying for the first time the number of characters scored in morphological analyses.

5. Interpretation of Hybridization and Species Boundaries Using Abundant Nuclear Markers Habitat disturbance and continued introductions of exotic species will create new opportunities for the hybridization of species. The analysis of introgression in such hybrid swarms will be facilitated by the abundance of new genetic markers now available. Where the taxonomy of natural species has been in debate, these markers will provide new data on the extent of differentiation across the whole genome. The analysis of hybrids may also shed light on selective constraints and the interaction of genes (Kilpatrick and Rand, 1995; Rieseberg et al., 1996).

6. Analysis of the Evolution of Repetitive DNA Families Although most systematic analyses have focused on sequence variation in single-copy genes, there is some indication that repetitive DNA families offer new and useful tools for identifying relationships (Franck et al., 1994; Elder and Turner, 1994). Sequence variation in tandem and dispersed repetitive DNA may provide new insights in some groups.

9

8. Genomic Organization The increasing availability of genome maps, and even complete DNA sequences, is creating opportunities for the analysis of new characters. For example, Boore et al. (1995) used the pattern of gene arrangements in arthropod m t D N A to study arthropod relationships. O'Brien et al. (1993) proposed the use of a standard set of reference loci in the analysis of genomes, which would make it easy to identify such rearrangements in the nuclear genome. These types of characters may offer the best hope for resolving relationships among ancient lineages and need to be comprehensively addressed in fishes.

VI. A N e w Age of Synthesis Although morphological and molecular traditions have frequently collided in the past, we argue for a more synergistic approach that recognizes the peculiarities and limitations of each kind of data and in which there is an interplay between morphological and molecular studies. All inherited morphological characters have their origin in molecular characters. A record of the history of evolutionary change can be found in both the structure and the genes of organisms. At this point, analytical methods are rapidly increasing in sophistication, enabling us to better quantify rates of evolution and constraints on molecular changes through time. This understanding will lead to more accurate and consistent phylogenetic analyses. When combined with traditional approaches, these data promise to reveal much about the evolutionary forces that have produced the great diversity of modern fishes. This volume illustrates the beginning stages of this process, which is sweeping the field of fish systematics and paving the way to a new understanding of the interplay of genes, development, and selection. This new age of synthesis promises to continue to revolutionize systematics in the 21st century. References

7. Studies of the Molecular Clock in Fishes The mechanisms governing the speed and regularity of molecular clocks are poorly understood. The great diversity of habitat and life history among fishes, coupled with their excellent fossil record, makes this an excellent group with which to study molecular clocks. New insights will arise as rigorous accountings of substitution rate are made in groups of fishes varying in population size, environment, and life history.

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1. Molecules and Morphology in Studies ofFish Evolution

Mickevich, M. F., and Johnson, M. S. 1976. Congruence between morphological and allozyme data in evolutionary inference and character evolution. Syst. Zool. 25:260-270. Miyamoto, M. M., and Fitch, W. M. 1995. Testing species phylogenies and phylogenetic methods with congruence. Syst. Biol. 44: 64-76. Moran, P., and Kornfield, I. 1993. Were population bottlenecks associated with the radiation of the Mbuna species flock (Teleostei: Cichlidae) of Lake Malawi. Mol. Biol. Evol. 10:1015-1029. Murata, S., Takasaki, N., Saitoh, M., and Okada, N. 1993. Determination of the phylogenetic relationships among Pacific salmonids by using short interspersed elements (SINEs) as temporal landmarks of evolution. Proc. Natl. Acad. Sci. USA 90:6995-6999. Nelson, J. S. 1994. "Fishes of the World," 3rd. ed. Wiley, New York. O'Brien, S. J., Womack, J. E., Lyons, L. A., Moore, K. J., Jenkins, N. A., and Copeland, N. G. 1993. Anchored reference loci for comparative genome mapping in mammals. Nat. Genet. 3:103-112. Palumbi, S. R. 1996. Nucleic acids II. The polymerase chain reaction. In "Molecular Systematics" (D. M. Hillis, C. Moritz, and B. K. Mable, eds.), pp. 205-221. Sinauer Assoc., Sunderland, MA. Parenti, L. R. 1981. A phylogenetic and biogeographic analysis of cyprinodontiform fishes. Bull. Am. Mus. Nat. Hist. 1658:341-557. Parenti, L. R. 1984. A taxonomic revision of the Andean killifish genus Orestias. Bull. Am. Mus. Nat. Hist. 178:110-214. Parker, A., and Kornfield, I. 1995. A molecular perspective on evolution and zoogeography of cyprinodontid killifishes. Copeia 1995:8-21. Parker, A. and Kornfield, I. 1997. Evolution of the mitochondrial DNA control region in the mbuna (Cichlidae) species flock of Lake Malawi, East Africa. J. Mol. Evol. in press. Pogson, G. H., Mesa, K. A., and Boutilier, R. G. 1995. Genetic population structure and gene flow in the Atlantic cod Gadus morhua: A comparison of allozyme and nuclear RFLP loci. Genetics 139: 375-385. Powers, D. A., and Schulte, P. M. 1996. A molecular approach to the selectionist/neutralist controversy. In "Molecular Zoology" (J. D. Ferraris and S. R. Palumbi eds.), pp. 327-352. Wiley-Liss, New York. Queller, D. C., Strassmann, J. E., and Hughes, C. R. 1993. Microsatellites and kinship. Trends Ecol. Evol. 8:285-288. Rieseberg, L. H., Sinervo, B., Linder, C. R., Ungerer, M. C., and Arias, D. M. 1996. Role of gene interactions in hybrid speciation: Evidence from ancient and experimental hybrids. Science 272: 741-745. Rodrigo, A. G., Kelly-Borges, M., Bergquist, P. R., and Bergquist, P. L. 1993. A randomisation test of the null hypothesis that two cladograms are sample estimates of a parametric phylogenetic tree. New Zeal. J. Bot. 31:257-268. Saiki, R. K., Gelfand, D. H., Stoffel, S., Scharf, S. J., Higuchi, R., Horn, G. T., Mullis, K. B., and Erlich, H. A. 1988. Primer-directed enzymatic amplification of DNA with a thermostabile DNA polymerase. Science 239: 487-491. Saitou, N., and Nei, M. 1987. The neighbor-joining method: A new method reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406-425. Simon, C., Frati, F., Beckenbach, A., Crespi, B., Liu, H., and Flook, P. 1994. Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Ann. Entomol. Soc. Am. 87(6): 651-701.

11

Stepien, C. A. 1995. Population genetic divergence and geographic patterns from DNA sequences: Examples from marine and freshwater fishes. In "Evolution and the Aquatic Ecosystem: Defining Unique Units in Population Conservation" (J. Nielsen, ed.), pp. 263-287. American Fisheries Soc. Symposium, Bethesda, MD. Stepien, C. A. and Rosenblah, R. H. 1991. Patterns of gene flow and genetic divergence in the Northeastern Pacific Clinidae (Teleosteii Blennioidei), based on allozyme and morphological data. Copeia. 1991(4): 873-896. Stepien, C. A., Dixon, M. T., and Hillis, D. M. 1993. Evolutionary relationships of the blennioid fish families Clinidae, Labrisomidae, and Chaenopsidae: Congruence between DNA sequence and allozyme data. Bull. Mar. Sci. 52(1): 873-513. Stepien, C. A., and Rosenblatt, R. H. 1996. Genetic divergence in antitropical pelagic marine fishes (Trachurus, Merluccius, and Scomber) between North and South America. Copeia 1996(3): 586-598. Stiassny, M. L. J., Parenti, L. R., and Johnson, G. D. (eds.) 1996. "Interrelationships of Fishes." Academic Press, San Diego. Sturmbauer, C., and Meyer, A. 1992. Genetic divergence, speciation and morphological stasis in a lineage of African cichlid fishes. Nature 358:578-581. Sturmbauer, C., and Meyer, A. 1993. Mitochondrial phylogeny of the endemic mouthbrooding lineages of cichlid fishes of Lake Tanganyika, East Africa. Mol. Biol. Evol. 10: 751-768. Swofford, D. L., Olsen, G. J., Waddell, P. J., and Hillis, D. M. 1996. In "Molecular Systematics" (D. M. Hillis, C. Moritz, and B. K. Mable, eds.). 2nd Ed., pp. 407-514. Sinauer Assoc., Sunderland, MA. Tamura, K., and Nei, M. 1993. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol. Biol. Evol. 10:512-526. Vawter, A. T., Rosenblatt, R. H., and Gorman, G. C. 1980. Genetic divergence among fishes of the Eastern Pacific and the Caribbean: Support for the molecular clock. Evolution 34: 705m711. Wheeler, W. C. 1986. Character weighting and cladistic analysis. Syst. Zool. 35:102-109. Wiley, E. O. 1981. "Phylogenetics: The Theory and Practice of Phylogenetic Systematics." Wiley Interscience, New York. Williams, J. G. K., Kubelik, A. R., Livak, K. J., Rafalski, J. A., and Tingey, S. V. 1990. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res. 18: 6531-6535. Wilson, A. C., Cann, R. L., Carr, S. M., George, M., Jr., Gyllensten, B., Helm-Bychowski, K., Higuchi, R. C., Palumbi, S. R., Prager, E. M., Sage, R. D., and Stoneking, M. 1985. Mitochondrial DNA and two perspectives on evolutionary genetics. Biol. J. Linnean Soc. 26: 375-400. Zhu, D., Jamieson, B. G. M., Hugall, A., and Moritz, C. 1994. Sequence evolution and phylogenetic signal in control region and cytochrome b sequences of rainbowfishes (Melanotaeniidae). Mol. Biol. Evol. 11:672-683. Zuckerkandl, E. and Pauling, L. 1962. Molecular disease, evolution and genic heterogeneity. In "Horizons in Biochemistry" (M. Kasha and B. Pullman, eds.), pp. 189-225. Academic Press, New York. Zuckerkandl, E. and Pauling, L. 1965. Evolutionary divergence and convergence in proteins. In "Evolving Genes and Proteins" (V. Bryson and H. J. Vogel, eds.), pp. 97-166. Academic Press, New York.

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C H A P T E R

2 Base Substitution in Fish Mitochondrial DNA: Patterns and Rates THOMAS D. KOCHER and KAREN L. CARLETON Department of Zoology University of New Hampshire Durham, New Hampshire 03824

I. Introduction

differences can be observed in comparisons among species. Probably more is known about evolutionary patterns in animal mitochondrial genomes than for any other DNA sequence. Although some aspects of the substitutional pattern (e.g., the high proportion of transitions) are unique to animal mtDNA, this molecule is still an excellent model system to illustrate the analytic method needed to reconstruct phylogenies from DNA sequence data. This chapter focuses on patterns of mtDNA evolution in cichlid fishes. Examples are drawn from continuing studies of the sene encoding NADH dehydrogenase subunit 2 (ND2) in East African cichlids (Kocher et al., 1995). This data set is particularly useful because it includes a large number of closely related molecules which provide insights into the pattern of substitution usually obscured in comparisons among more highly diverged sequences.

Many of the authors in this volume use mitochondrial DNA (mtDNA) sequences because they are easily accessible, have high rates of evolution, and generally follow a clonal pattern of inheritance well suited to phylogenetic reconstruction (Wilson et al., 1985). This chapter is about the natural history of these sequences. Just as morphological systematists strive to analyze characters for which the pattern of development and effects of the environment are well known, so molecular systematists should begin by understanding the biology underlying the characters they use for inferring phylogenies. By understanding how changes accumulate in sequences, accurate models of substitution can be developed for use in phylogenetic inference. Molecular sequences are deceptively simple in structure. There are just four bases common in DNA. These bases appear to be freely interchangeable, but in fact, mutation interconverts some nucleotides more frequently than others. Selection and drift then act on this spectrum of mutations in such a way as to prevent most substitutions from becoming fixed in the population. Neither mutation nor selection is homogeneous along a sequence of nucleotides; close examination reveals important differences in the pattern of mutation and selective constraint among nucleotide sites. Additional

MOLECULAR SYSTEMATICS OF FISHES

II. S i m p l e M o d e l s of Substitution A. M u t a t i o n a l Models At the core of most phylogenetic reconstruction algorithms is a simplified mutational model of the sub-

13

Copyright 9 1997 by Academic Press. All rights of reproduction in any form reserved.

14

THOMAS D. KOCHER A N D KAREN L. CARLETON

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stitution process. The simplest model (Jukes and Cantor, 1969) assumes an equal probability of interconversion among all four nucleotides. A consequence of this model is a twofold excess of transversional change (purine ~ pyrimidine) because there are twice as many paths for transversions as for transitions. This model is not adequate for animal mtDNA because a much larger excess of transitions, relative to transversions, is typically observed. Kimura (1980) introduced a two parameter model to accommodate the higher rate of transitions (Fig. 1). This model is also inadequate, as it predicts that sequences at equilibrium will contain equal frequencies of all four nucleotides. A modified Kimura model (Felsenstein, 1986) adjusts the relative rates of transitions or transversions to accommodate the unequal frequency of bases seen in real sequences. More complex models are possible, but the need for a fully elaborated model, with a separate rate parameter for each of the 12 possible kinds of substitution, has not yet been demonstrated (but see Rzhetsky and Nei, 1995).

B. Multiple Hits and Saturation As mutations occur over time, a pair of homologous sequences will become increasingly different. The observed number of differences between these sequences accumulates almost linearly at first. Gradually, however, as some nucleotide sites experience more than one substitution, the observed sequence difference becomes a poor indicator of the actual divergence which has occurred. Eventually, the rate at which new differences arise is equal to the rate at which identical nucleotides arise by multiple substitution. At this point the sequences cannot display greater sequence difference (the sequences have reached "saturation"), even

though additional substitutions continue to occur. The true evolutionary rate is hidden by the occurrence of multiple substitutions at a site. Appropriate statistical corrections can be applied to transform the observed differences into a measure of the total number of changes that have occurred (total divergence, or evolutionary distance). These corrections can be derived for any of the mutational models, but are accurate only in the early stages of differentiation, before saturation has been closely approached. Furthermore, these corrections are accurate only if all of the nucleotide sites are evolving according to the same substitutional model.

C. Selectional Filter Although mutational models have been widely used to describe the process of substitution, they ignore the influence of selection, which may be the dominant force regulating change in real sequences. It is easy to show, by comparison of nucleotide substitution rates at silent and amino acid replacement sites, that selection filters out more than 90% of all mutations which occur in mtDNA. Any concordance between the predictions of mutational models and the evolution of real sequences is therefore fortuitous. Most simple models assume that substitutions occur randomly among sites following the Poisson distribution. Numerous demonstrations of the inadequacy of this model have been published (Fitch and Markowitz, 1970; Uzzell and Corbin, 1971; Kocher and Wilson, 1991). Substitutions do not occur with equal probability at each site. Instead, selection resists substitution at some sites, while allowing mutations at other sites to become fixed. A better model of this process uses a gamma distribution (Bliss and Fisher, 1953; Tamura and Nei, 1993), or a covarion model (Fitch and Markowitz, 1970; Miyamoto and Fitch, 1995), to allow rates of substitution to vary among nucleotide sites. The gamma distribution models have been mathematically formulated so that it is straightforward to correct distances for multiple hits (Tamura and Nei, 1993), but this is not yet possible for the covarion model. Few studies have attempted to estimate either the gamma parameter or the size and exchange rate of the covarion. It is important to remember that estimates of these parameters must be made from close relatives, as they provide the best information to quantify the process of substitution, free from the effects of multiple substitution. For protein-coding sequences, it is possible to classify sites a priori according to the known selective constraints of the coding function. At the very least, it is recognized that first, second, and third positions of co-

2. Base Substitution in Fish mtDNA dons evolve at different rates, because of the redundant structure of the genetic code, and the grouping of functionally similar amino acids according to the second base of the codon. Because the functional constraints on rRNA sequences are poorly understood, it is more difficult to assign sites to particular rate classes a priori. Models of evolution for these genes typically resort to a purely statistical representation of the sites.

III. Evolution of Real Sequences To evaluate which theoretical models provide the most appropriate basis for phylogenetic reconstruction, the evolution of real sequences must be quantified. Here we examine a set of 56 mitochondrially encoded NADH subunit 2 (ND2) sequences (348 codons) obtained from 45 species of cichlid fish, mostly from East Africa. The most divergent comparisons involve New World species which presumably diverged from the African lineages more than 60 million years (MY) ago. The most closely related sequences are intraspecific polymorphisms differing by just a few nucleotides. Those sequences not already reported in Kocher et al. (1995) are deposited in GenBank. Ideally, we would plot the divergence of molecules with respect to geologic times of divergence. For these fishes, however, few reliable divergence times are available. Instead we will use the proportion of third position sites which have experienced a transversion as a measure of divergence. Transversions occur relatively rarely and in a nearly Poisson fashion (Irwin et al., 1991). These divergences are corrected for multiple substitution using a two-state model [d = -0.5 in (1-2Q), where Q is the observed proportion of transversions].

A. Changes in the Third P o s i t i o n o f C o d o n s Many substitutions at the third positions of codons are synonymous (i.e., do not change the amino acid sequence of the encoded protein) and thus escape selection on protein structure. These sites therefore provide the most direct view of the mutational process. Although these sites are often thought to evolve according to a purely mutational model, some selective constraint does exist (Perna, 1996; Xia et al., 1996). While it would be inappropriate to equate substitutions at third positions with mutation, these sites approximate the underlying mutational spectrum more closely than the first or second positions. The dominant feature of mtDNA evolution is the high rate of transition substitutions relative to transver-

15

sions. At third positions the ratio of transition: transversion differences is at least 5:1 initially (Fig. 2), consistent with a strong transition bias in the underlying mutation process. As transitions begin to occur repeatedly at the same sites, the ratio of transitions: transversions observed in pairwise comparisons drops. At a 10% transversion difference, the ratio is only 2.5:1, and in the deepest comparisons it drops to 1:1. At a 10% transversion difference, the actual number of transition substitutions that have occurred is at least twice as great as the observed number of differences. The transition: transversion ratio is thus one way to quantify the degree of multiple substitution that has occurred since the common ancestor of two sequences. Base composition influences the maximum observed difference. Figure 3 shows the accumulation of the two kinds of transitions possible: those involving the purines (A and G) and those involving the pyrimidines (C and T). It is interesting to note that the initial rate of transitions is the same for the two types of nucleotides. The purines, however, show saturation at a lower level of divergence than the pyrimidines. This pattern arises because the frequencies of A and G are much more unequal than the frequencies of C and T. At third positions the proportions are A,G,C,T: 0.32, 0.05, 0.38, 0.26. The maximum divergence of two sequences is calculated as I - probability of chance identity. For the purines described earlier, where only two states are possible (e.g., A or G), this is calculated as

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16

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B. Changes in First and Second Positions and Amino Acid Substitution At the first and second position of codons, selection dominates the substitution process. This is apparent from the rate of transition substitution, which is 6and 15-fold slower at first and second positions, respectively, than the rate at third positions (Fig. 4). Because there is no reason to suspect a slower mutation rate at these sites, the difference must arise because selection prevents fixation of most mutations. Selection also constrains the maximum amount of difference that is observed between two sequences. Second positions plateau at approximately 3% transition differ-

ence, while first positions plateau at about 8%. The comparable value at third positions is 25%. Selective constraint has a strong effect on base composition, which differs among the three codon positions. First positions are relatively rich in GC because of the high leucine and alanine content of the ND2 protein. Second positions show a high proportion of T and C (37.9 and 30.4%, respectively), probably because hydrophobic amino acids required for this membranespanning protein are encoded by either C or T at the second position (Naylor et al., 1995). Probably the most important characteristic of selective constraint is that it varies from site to site along the molecule according to the structural function of the

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18

THOMAS D. KOCHER AND KAREN L. CARLETON

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encoded protein. Some positions in the protein can accept substitution relatively easily, whereas selection acts to prevent substitution at others. In ND2, this pattern of constraint can be visualized by plotting the proportion of variable sites along the molecule (Fig. 5). For many mitochondrially encoded proteins, the membrane-spanning helices of the protein experience high levels of substitution, whereas the turns between these helices appear relatively conserved (e.g., Irwin et al., 1991). The structure of ND2 is less well known, but it appears that regions of the protein outside the membrane may be constrained by selection for appropriate contacts with other proteins. If selection did not alter substitutional probabilities among sites we might expect to model the occurrence of multiple hits using a Poisson distribution. In fact, real molecules rarely fit a Poisson. Table I shows the number of changes per site estimated by parsimony over a tree for 10 closely related cichlids. The 72 inferred substitutions are distributed among just 53 of the 348 positions in the sequence. These data do not fit a model in which substitutions occur randomly along the sequence. Rather, the significant deviation from Poisson expectation demonstrates that the substitutions are clustered at a relatively small number of sites. It appears that selection is preventing substitutions at a large fraction of sites. Because the magnitude of selective constraint is likely to be a continuously distributed variable, it is most appropriate to model this variation as a gamma distribution. The gamma distribution uses an additional parameter to quantify the variance in rate among sites. Most real sequences can be modeled rather well with this distribution.

Fitch and Markowitz (1970) coined the term covarion to describe the set of "concomitantly variable codon positions." In their view, only a small proportion of the codons for a protein can experience an amino acid substitution at any given instant (the covarion). Substitution is thought to slowly alter the selective constraints so that the sites making up the covarion change over time (Fitch, 1971). The data in Table I can be made to fit a Poisson model, if it is assumed that the covarion con-

TABLE I Estimated Distribution of the N u m b e r of A m i n o Acid Substitutions per Site Estimated over a Parsimony Tree of 10 East African Cichlid Taxa a,b N u m b e r of changes per site over tree

Assuming 348 variable sites Observed Poisson expectation ,u = 22.32, p << 0.001 Assuming 100 variable sites Observed t ,2 = 0.1713, p > 0.9

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16 16.28

aThe 10 species and their assumed relationships are (((((Rhamphochromis sp., (Lethrinops aurita, Pseudotropheus zebra)), Gnathochromis pfefferi), (((Callochromis macrops, Opthalmotilapia ventralis) , Xenotilapia flavipinnus), Perissodus microlepis)), Limnochromis auritus), and Paracyprichromis brieni). bThe total length of the tree was 72 substitutions, including three sites that experienced at least 3 substitutions. Data fit a Poisson distribution of substitutions among sites, if it is assumed that only 100 of the 348 sites can accept a substitution.

2. BaseSubstitution in Fish mtDNA sists of only 100 of the amino acid sites. Selection may be acting to prevent subsitutions at the other 48 sites in the molecule. Miyamoto and Fitch (1995) demonstrate that the covarion model is more biologically correct than models based on the gamma distribution. It remains to be seen whether the difference between the covarion and the gamma models is important to phylogenetic analysis and whether the covarion model can be mathematically formulated for convenient use.

IV. Implications for Phylogenetic Reconstruction A. Choosing a Model There are two important decisions to be made when attempting to recover phylogenetic information from an analysis of molecular sequences. First, a substitutional model must be chosen which accurately models the evolution of the molecule under study, including whether rates vary among sites. Second, a particular tree-building algorithm must be selected. Although much has been written about the accuracy of various tree-construction algorithms, the choice of a substitutional model probably has a far greater impact on the phylogenetic conclusions. Since the pattern of evolution varies among genes (e.g., nuclear versus mitochondrial), it is important to adjust the substitution model for each analysis. Some tree-building algorithms allow this modeling more easily than others because the assumptions are more explicit or the model more easily adjusted. In general, it is easier to adjust the evolutionary model using methods which first calculate a distance statistic. Probably the best is the gamma distance developed by Tamura and Nei (1993), which incorporates transition/transversion bias, compositional inequalities, and variance in rate among sites. Once accurate distances are calculated, almost all tree algorithms will yield the correct topology (Huelsenbeck and Hillis, 1993). The neighborjoining algorithm (Saitou and Nei, 1987), for example, can construct trees from distance matrices calculated according to many different models. There are several advantages to focusing on the development of a distance matrix prior to initiating tree construction. First, calculation of the distance matrix focuses attention on the model of sequence evolution to be used. Second, it is usually more efficient to estimate topologies from a distance matrix than by searching for minimum evolution trees among a universe of possible topologies.

19

Third, it is easier to calculate standard errors for each divergence than to evaluate the support for nodes using a bootstrap approach. This is particularly true for sequences that are near saturation.

B. Power A n a l y s i s for m t D N A Phylogenetics Because of the heterogeneous nature of evolution along a DNA sequence, sites differ in the amount of information they carry about a particular phylogenetic relationship. It is important to determine which sites and classes of change give the greatest signal/noise ratio for testing a particular phylogenetic hypothesis. Characters must be chosen to match the time scale of the divergences being studied. An analysis using third position transitions to evaluate basal (60-80 MYBP) relationships in the Cichlidae would be fundamentally flawed, since these substitutions are completely saturated after about 10 MY of divergence (Fig. 2). Neither would it be appropriate to focus exclusively on third position transversions to recover relationships among close relatives because of the large amount of information that would be lost by not including transitions. We wish to know which characters from the ND2 sequence give the greatest power for resolving relationships among cichlids at various divergences. First, we must specify the model for the evolution of bases in the sequence. Because of the importance of both base composition and variance in rate among sites, the TamuraNei gamma-distance model is the most appropriate for these data. This model describes how sequences diverge through time by calculating the expected proportion of transitional differences for purines (P1) and pyrimidines (P2) and the expected proportion of transversional differences (Q). The mean values of these expected differences are used, assuming that rates vary among sites according to a gamma distribution [Tamura and Nei (1993) Eqs. (12-14)]:

12gAgG{ XR

gR --

[

a

q- gy ( ~2

]

__ a a + 2(gR ~1 + gy~)t a )a} a + 2~t

2gwgc{ _ [ a ] gy gY a + 2(gy a 2 -~-gR~)t

a

-Jr-XR( a + a2~t )a} I (a + a2~t )al'

-- 2gRgY 1 --

(2)

(3)

(4)

20

THOMAS D. KOCHER AND KAREN L. CARLETON

mulating during a time interval, At, from

~dPl dP2~ aP = \

B

C

1,

~

2,

3, or

(8)

dt + dt / a t

dQ A Q = -d-~ At .

IOMY

X

FIGURE 6 Hypothetical phylogeny used in the power analysis, Taxa B and C share a period of common ancestry (1, 2, 5, or 10 MY) after their divergence from taxon A. Subsequent analyses examine the power of different classes of mtDNA character to resolve this relationship after different periods of terminal divergence (x).

(9)

Typical parameters for vertebrate evolution can be obtained from the cichlid ND2 sequences as follows. Gene frequencies are determined from the sequence data. If we assume m

n

m

we can solve for a and fl using Eq. (5) plus Eq. (6) and Eq. (7) to get the following equations: where gA, go, gc, and gT are the nucleotide frequencies, a is the g a m m a parameter, C~l and ~2 are the rates for transitional changes for purines or pyrimidines, and fl is the rate for transversional change. These equations give the t i m e - d e p e n d e n t differences between two sequences. We use the equations for P and Q rather than s and v as they clearly represent data regarding the saturation of sequence differences resulting from multiple substitutions. We consider the power of the first, second, or third position transitions or transversions to identify a 1 MY period of shared ancestry between sequences B and C, after their divergence from sequence A (see Fig. 6), at various times in the past. This is done by first calculating the n u m b e r of sequence differences accumulating in that 1 MY interval, at various times in the past. In order to calculate the n u m b e r of differences, AP or AQ which accumulate within some time interval we need to calculate the derivatives of the previously described equations:

m

4gAge f ~(XR~I 4- gyfl) gR [

dP1 dt

[

a

a + 2(gR~l

]a+l

+ gyfl)t

_ -

[

gwfl

dt

a a + 2(gy~2 4- gR-fi)t

dQ dt = 4gRgYfl

--gRfl

[

a a 4- 2fit

a ]a+l} a + 2-fit

]al

"

and

Using Figs. 2 through 4, we can estimate d P / d t and d Q / d t at time t = 0. The parameters determined from the ND2 data are given in Table II. G a m m a values are taken from an analysis of m a m m a l i a n cytochrome b genes (Irwin et al., 1991). Figure 7 plots the n u m b e r of sequence differences accumulating in the 1 MY interval of interest at various times in the past. We have calculated the average value of Ap or AQ over the I MY time interval. Clearly, third position transitions contribute the greatest n u m b e r of changes in the first few million y e a r s m m o r e than all the other characters combined. With time and the effects of saturation, the accumulation of third position transition differences decreases. After only 5 MY, the combination of changes at first and second positions with third position transversions

a + 2 f- i t

__ [

]a+X

4(gAga + gwgc)

TABLE H

__ 4XTXCxy{(XY~2 4- XR~) [

=

dQ _ dt ( t = O) fl = . 4gRgY

Parameters for the Estimation of Expected Sequence Divergence and Associated Errors a

]a+l}a

(5) dP2

dP d t ( t = O)

(6) (7)

Based on these derivatives, we can calculate the n u m ber of transitional or transversional differences accu-

Parameter freq A, gA freq G, ga freq C, gc freq T, XT gamma, a dP/dt (t = 0) dQ/dt (t = 0) ]~

First position

Second position

Third position

0.295 0.196 0.331 0.178 0.4 1.7 0.5 3.64 0.50

0.160 0.113 0.354 0.373 0.25 0.7 0.2 1.17 0.25

0.318 0.048 0.377 0.257 5 10 1 22.3 1.08

aIn accordance with the Tamura-Nei gamma distance model discussed in the text.

2. Base Substitution in Fish mtDNA

netic signal uniting taxa B and C will be hidden by the variance associated with the long terminal branches. These crossing points have been calculated for various periods of common ancestry (1, 2, 5, and 10 MY) for data sets of various sizes (102 codons representing typical cytochrome b fragment data, 348 codons representing the cichlid ND2 data set, 1000 codons representing approximately three mitochondrial genes, and 3754 codons representing the complete coding regions for human mitochondrial DNA) as a function of the terminal branch length. Figure 9 summarizes the calculations in a format useful for planning phylogenetic studies. To use the figure, first determine the approximate time of divergence for the taxa under study (either through fossil evidence or by estimating third position transversion difference from a pilot study). Next, identify the curve associated with the desired degree of resolution (1, 2, 5, or 10 MY between divergences). Finally, read the number of codons which must be sequenced from the y-axis.

9 Total

<> l A P 9 1AQ 2AP | 2AQ 3AP

9

9 3AQ

15

Z 9

9 9

9

9

9

"".,-.:;;.......... 9

o

"

9

9

9

*"

|

~''

:

:

5

~ 10

15

21

20

40

--

35

--

30

--

Time (MYA)

FIGURE 7 The number of sequence differences accumulating in a 1 MY interval at various times in the past and observed at time zero. Third position transitions contribute the greatest n u m b e r of differences over the recent past, but the sum of transitions and transversions at first and second positions soon dominates.

AP

-"

G(P)

contributes a greater number of differences in a 1 MY interval than do third positions transitions. This plot represents only the signal, however. There will also be variability in the differences between the sequences resulting from the variance contributed by the differences estimates from the long terminal branches of the tree. This variability will contribute noise which, if large enough, will obscure the signal we hope to observe. The noise is determined from the standard deviation which is simply related to the variance. The binomial variance and standard deviations for P and Q are given by var(P) = var(Q) -

P(1

-

P)

Q(1 - Q)

o-(P) = )nP(1

-

25

t,., o

20

15

10

P) o

tr(Q) = )nQ(1 - Q)

~

0

I

I

I

I

J

2

4

6

8

10

Time(MYA)

Figure 8 plots both the number of changes contributed in a I MY interval at various times in the past and the standard deviation associated with differences accumulated on the terminal branches. The crossing points of the curves give an indication of when the phyloge-

FIGURE 8 The number of differences attributable to a 1 MY period of common ancestry ( 9 compared with the standard error associated with the changes on the terminal branches (el). The noise accumulated on the terminal branches will s w am p the signal arising from shared ancestry after only 2.5 MY. Plotted is 1.96 times the standard error for third position transition differences.

22

T H O M A S D. KOCHER A N D K A R E N L. C A R L E T O N

o //~

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FIGURE 9 Power analysis for mitochondrial sequence data. The situation considered is shown in Fig. 6. The n u m b e r of codons required to detect 1, 2, 5, or 10 MY periods of c o m m o n ancestry, at v a r i o u s times in the past. The base composition and rates of evolution of the cichlid ND2 gene (Table II) are assumed. The curves represent the n u m b e r of codons required so that I SD of the estimate of terminal branch length is equal to the m e a n n u m b e r of differences arising along the internal branch of the tree. Data are shown for transitions (AP) and transversions (AQ) in first (1), second (2), and third (3) positions. The x axis assumes a transversion divergence of 1% per million years. A spreadsheet is available from the authors for calculating crossing values for taxa with radically different base compositions or rate matrices.

2. Base Substitution in Fish mtDNA Several findings can be gleaned from these graphs. First, it is quite surprising that, even with the complete ND2 sequence, none of the characters have power to resolve a 1 MY difference beyond about 2.5 MY (only transitions at third positions are effective over this period). More slowly accumulating differences (e.g., changes at first and second positions), although not saturated (Fig. 4), are not effective in resolving the relationship because of the large variance associated with the small number of substitutions. Second, the greatest statistical power, even for deeply divergent lineages, is found in the third position transversion data. This is because third position transversions accumulate relatively rapidly and do so in a nearly Poisson fashion. The slower rates, and greater variation in rate among sites for other characters, sharply reduce their power. The third surprising finding is that mtDNA data have the potential to resolve rather deep divergences. Complete mitochondrial coding sequences should be able to resolve a 10% difference in divergence times, even 75 MY in the past. However, 100 codons give only coarse resolution for very recent events. We expect that this figure will be accurate for most vertebrate mtDNAs. Our preliminary examination of other taxa suggests that base composition is an important determinant of the power for resolving short time periods of shared ancestry. However, it is clear that a variation in rates among sites is the single most important factor affecting the performance of a given sequence in phylogenetic analysis. Differences in the assumed gamma parameter can have a dramatic effect on the accuracy of distance estimation.

V. Conclusions A. Choice o f m t D N A Sequence Characters It is well known that third position transitions, although useful for recent divergences, saturate rapidly. It is somewhat surprising that transversions at the third position outperform changes (both transitions and transversions) at the first and second codon positions. The advantage seems to arise because third position transversions approximate a Poisson distribution, whereas strong selection at first and second positions creates a large variance in substitution probability among sites.

B. Power Analysis Poor resolution of branching order deep in the tree is a common result in phylogenetic analyses. Investi-

23

gators frequently attribute this result to rapid radiation of the taxa in question. The alternative, that data are simply insufficient to resolve even moderately spaced speciation events, is rarely considered objectively. The graphs in Fig. 9 are a good tool for gauging the power of a particular data set to resolve closely spaced bifurcations. The steep slopes of the curves suggest that many published studies may have failed to gather sufficient data to detect even a 10% difference in divergence times.

C. A d e q u a c y o f M u t a t i o n a l Models Selection dominates the substitution process at almost all sites in the mitochondrial genome. It is therefore surprising that the models of sequence evolution most often used in phylogenetic analysis still focus on the mutation process. Use of mutation-based models is probably not appropriate for anything but third position transitions (Xia et al., 1996). Approaches that explicitly model the selection filter should be pursued, as they may allow modeling of sequence divergence further back in time.

D. Reality of Rate Variation Suggestions have been made that the rate of mitochondrial DNA evolution varies among lineages (e.g., Martin et al., 1992; Bermingham et al., 1997). Attention has begun to shift toward identifying physiological correlates which might account for this rate variation (Martin and Palumbi, 1993; Rand, 1994). While rate variation may well exist, the search for the causes of such variation may be premature. The rate of substitution is the result of a delicate interplay of forces, including mutation, selective constraints arising at both molecular and organismal levels, and population-level events. We should be careful not to jump from poorly supported correlations to hypotheses of causation. It is hoped that this chapter will promote the development of a consistent set of evolutionary rate estimates, incorporating corrections for both unequal base composition and patterns of selective constraint. When used in relative-rate tests, or well-substantiated absolute calibrations of evolution rate, these estimates may lead to new hypotheses on both the generality of mitochondrial clocks and the forces which regulate their ticking. A further benefit is that the refinement of substitution models will improve our ability to reconstruct phylogenetic relationships among species.

Acknowledgments Many thanks to those who helped focus our thinking, including N. Perna, and several classes of Zoology 715. This work was supported in part by NSF Grant BSR-9007015.

24

THOMAS D. KOCHER A N D KAREN L. CARLETON

References Bermingham, E., McCafferty, S. S., and Martin, A. P. 1997. Fish biogeography and molecular clocks: Perspectives from the Panamanian Isthmus. In "'Molecular Systematics of Fishes'" (T. D. Kocher and C. A. Stepien, eds.). Academic Press, San Diego. Bliss, C. I., and Fisher, R. A. 1953. Fitting the negative binomial distribution to biological data. Biometrics 9:176-200. Felsenstein, J. 1986. DNAML-DNA Maximum Likelihood Program. PHYLIP Manual, version 3.2. Department of Genetics, University of Washington, Seattle. Fitch, W. M. 1971b. The nonidentity of invariable positions in the cytochromes c of different species. Biochem. Genet. 5:231-241. Fitch, W. M., and Markowitz, E. 1970. An improved method for determining codon variability in a gene and its application to the rate of fixation of mutations in evolution. Biochem. Genet. 4:579-593. Huelsenbeck, J.P., and Hillis, D. M. 1993. Success of phylogenetic methods in the four-taxon case. Syst. Biol. 42:247-264. Irwin, D. M., Kocher, T. D., and Wilson, A. C. 1991. Evolution of the cytochrome b gene of mammals. J. Mol. Evol. 32:128-144. Jukes, T. H., and Cantor, C. R. 1969. Evolution of protein molecules. In "Mammalian Protein Metabolism" (H. N. Munro, ed.), Vol. III, pp. 21-132. Academic Press, New York. Kimura, M. 1980. A simple method for estimating evolutionary rate of base substitution through comparative studies of nucleotide sequences. J. Mol. Evol. 16:111-120. Kocher, T. D., Conroy, J. A., McKaye, K. R., Stauffer, J. R., and Lockwood, S. F. 1995. Evolution of the ND2 gene in East African cichlids. Mol. Phylogenet. Evol. 4: 420-432. Kocher, T. D., and Wilson, A. C. 1991. Sequence evolution of mitochondrial DNA in humans and chimpanzees: Control region and a protein-coding region. In "Evolution of Life: Fossils, Molecules, and Culture" (S. Osawa and T. Honjo, eds.), pp. 391-413. Springer-Verlag, Tokyo.

Martin, A. P., Naylor, G. J. P., and Palumbi, S. R. 1992. Rates of mitochondrial DNA evolution in sharks are slow compared with mammals. Nature 357:153-155. Martin, A. P., and Palumbi, S. R. 1993. Body size, metabolic rate, generation time, and the molecular clock. Proc. Natl. Acad. Sci. USA 90: 4087-4091. Miyamoto, M. M., and Fitch, W. M. 1995. Testing the covarion hypothesis of molecular evolution. MoI. Biol. Evol. 12:503-513. Naylor, G. J., Collins, T. M., and Brown, W. M. 1995. Hydrophobicity and phylogeny. Nature 373:565-566. Perna, N. T. 1996. Patterns of base composition within and between animal mitochondrial genomes. Ph.D. Thesis, University of New Hampshire. Rand, D. M. 1994. Thermal habit, metabolic rate and the evolution of mitochondrial DNA. Trends Ecol. Evol. 9:125-131. Rzhetsky, A., and Nei, M. 1995. Tests of applicability of several substitution models for DNA sequence data. Mol. Biol. Evol. 12: 131-151. Saitou, N., and Nei, M. 1987. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406 -425. Tamura, I., and Nei, M. 1993. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol. Biol. Evol. 10:512-526. Uzzell, T., and Corbin, K. W. 1971. Fitting discrete probability distributions to evolutionary events. Science 172:1089-1096. Wilson, A. C., Cann, R. L., Carr, S. M., George, M., Jr., Gyllensten, U. B., Helm-Bychowski, K. M., Higuchi, R. G., Palumbi, S. R., Prager, E. M., Sage, R. D., and Stoneking, M. 1985. Mitochondrial DNA and two perspectives on evolutionary genetics. Biol. J. Linn. Soc. 26:375-400. Xia, X., Hafner, M. S., and Sudman, P. D. 1996. On transition bias in mitochondrial genes of pocket gophers. J. Mol. Evol. 43:32-40.

C H A P T E R

3 Molecular Systematics of a Rapidly Evolving Species Flock: The mbuna of Lake Malawi and the Search for Phylogenetic Signal IRV KORNFIELD and ALEX PARKER Department of Zoology and School of Marine Sciences University of Maine Orono, Maine 04469

I. I n t r o d u c t i o n

Lake Malawi, an ecologically diverse assemblage of approximately 300 species, most still to be formally described. Geological studies (Scholz and Rosendahl, 1988; Gasse et al., 1989; Owen et al., 1990) and comparative molecular analyses (Kornfield, 1978; see later) strongly suggest that the mbuna are of extremely recent vintage. This chapter briefly describes the natural history of this endemic fauna, reviews previous molecular studies designed to understand relationships within the group, considers microsatellite markers, and evaluates their utility for exploration of mbuna interrelationships. Initial recognition of the special nature of the mbuna was made by Regan (1921) and Trewavas (1935), who defined numerous genera based on earlier collections made by Christy. The mbuna are a diverse assemblage of lithophilous, algae-grazing fishes, currently allocated among 13 genera (Moran and Kornfield, 1993). A general overview of the unique trophic attributes of some of these species was provided by Fryer (1959a,b) and later expanded by Fryer and Iles (1972) to include the first integrated evolutionary treatment of the fauna. Numerous workers have subsequently described new taxa, occasionally discussing variation within particular lineages (e.g., Marsh et al., 1981; Lewis, 1982; Rib-

One of the most difficult problems in phylogenetic analysis is the reconstruction of rapid radiations involving large numbers of taxa. If sequential speciation events occur quickly, even assuming that divergence occurs solely via bifurcation (versus, e.g., hybridization), only minimal signals or synapomorphic traces will be present. Given sufficient time, of course, independent lineages so created will become recognizable due to the acquisition of divergent character states. However, although derived diagnostic characters may be of taxonomic utility, as autapomorphies they are phylogenetically uninformative. Most difficult are those systems in which rapid radiation has occurred very recently; in such cases, even autapomorphies may be absent. Reconstruction of the phylogenetic history of several of the species flocks (Mayr, 1984) of Old World haplochromine cichlids presents precisely such a challenge. This chapter considers the mbuna 1 cichlid fauna of 1The Malawi rockfishes are known as mbuna (Chichewa) in the territorial waters of Malawi and Mozambique,and as vindongo (Swahili) in Tanzanianwaters.

MOLECULAR SYSTEMATICS OF FISHES

25

Copyright 9 1997 by Academic Press. All rights of reproduction in any form reserved.

26

IRV KORNFIELD A N D A L E X PARKER

bink et al., 1983a; Reinthal, 1990a). General understanding of evolutionary dynamics and ecology followed the detailed field studies of Ribbink et al. (1983b) who, for the first time, described the extent of lakewide variation present in putative conspecifics. Subsequent descriptive accounts by Konings (1990) and DeMason (1993) have suggested the presence of numerous additional taxa in previously unexplored regions of the lake. Although it is clear that they form a monophyletic group (Moran et al., 1994), few detailed phylogenetic hypotheses regarding relationships among mbuna have been articulated (Fryer and Iles, 1972; Oliver, 1984; Reinthal, 1987). The principal reasons for the absence of such hypotheses are the paucity of morphological synapomorphies (Reinthal, 1987) and the general propensity for convergent and/or parallel evolution among cichlids (Eccles and Trewavas, 1989; Lazzaro, 1991). A statistically robust phylogeny is critical to meaningful discussion of patterns of species diversification and ecological radiation in the mbuna; without such a phylogeny, all evolutionary patterns, and the mechanisms suggested to have engendered them (Liem, 1980; Dominey, 1984; Greenwood, 1984; Mayr, 1984; Turner, 1994), remain hypothetical. For example, homogeneity of coloration is taken by some authors to imply conspecificity among allopatric populations (see Lewis, 1981; Ribbink et al., 1983b); coloration, however, may be a convergent characteristic (Eccles and Trewavas, 1989; McElroy et al., 1991) or may be constrained by species packing in isolated communities (D. McElroy and I. Kornfield, unpublished observations). Similarly, many morphological correlates of trophic specialization (Reinthal, 1990a,b) may be convergent.

II. Molecular Investigations Reconstructing the evolutionary history of the mbuna by molecular means (Kornfield, 1991) has proved extremely difficult, due principally to the recency of their radiation. Isozyme analyses have provided compelling evidence of reproductive isolation among extremely similar forms (Kornfield, 1978; McKaye et al., 1982, 1984), but for a variety of reasons, allozymes cannot be used to reconstruct evolutionary relationships. In particular, the degree of variation present at individual loci is limited; most exhibit only a few electromorphs and no taxon-specific (diagnostic) alleles are present. Importantly, the limited number of characters provided by allozymes (as either loci or alleles) severely constrains objective statistical evaluation of these data.

III. Mitochondrial D N A and Ancestral Polymorphisms With the advent of mitochondrial DNA (mtDNA) analysis in evolutionary studies (reviewed in Avise, 1994), it was hoped that basic problems of cichlid phylogenetics would be resolved. This hope was founded on properties of mtDNA that were expected to allow greater resolution than previously achieved in molecular systematic studies; particularly important are high mutation rates (Brown et al., 1979) and selective neutrality or near-neutrality of many nucleotide positions (see Niki et al., 1989; Rand et al., 1994). Indeed, some systematic problems, intractable using allozyme analysis, yielded solutions with mtDNA (Avise et al., 1986; Seyoum and Kornfield, 1992a). Comparative studies of relationships within the Malawi cichlid fauna by restriction (Moran et al., 1994) and sequence analysis (Meyer et al., 1990) of mtDNA provided an unambiguous definition of portions of the endemic radiation. In particular, the basic dichotomy between mbuna and most of the remaining haplochromines was supported, as were the affinities of a few well-differentiated lineages (summarized in Meyer, 1993). Additionally, previously unsuspected relationships between the mbuna and some taxa of very divergent morphology and habitat (e.g., Alticorpus and Lethrinops) were revealed (Moran et al., 1994). Despite these successes, resolution of relationships within the mbuna remained problematic. Two major mtDNA lineages (or and/3), differing by 1.5% sequence divergence, were identified within the mbuna, but the affinities of the taxa involved appeared aberrant; several species were more closely related to taxa in other genera than to congeners. The solution to this problem was obtained when sample sizes were increased: the mbuna retained an ancestral mtDNA polymorphism (Moran and Kornfield, 1993). Comprehensive mtDNA restriction analysis demonstrated that both c~ and/3 mtDNA haplotypes were present in geographically defined populations of a number of common mbuna species. Thus, the relationships among these taxa based on mtDNA (Moran et al., 1994) represent a gene tree (Pamilo and Nei, 1988) in which lineage sorting (Avise et al., 1984) is incomplete; clearly these data should not be interpreted as a species tree. The extent of this polymorphism among the mbuna has been examined using sequence analysis of the dloop region (Parker and Kornfield, 1997). This study confirms the existence of the polymorphism and defines several divergent gene lineages based on site-specific transitions (Table I). With a few interesting exceptions (see later), most mbuna species are polymorphic. It is instructive to consider what the consequences

3. Molecular Systematics of mbuna Polymorphic Nucleotide Positions in the mtDNA Control Region of Six mbuna Species a

TABLE I.

Nucleotide position b

Pseudotropheus zebra "BB" 1 P. zebra "BB" 2 P. zebra "black dorsal" Labeotropheus trewavasae L. fuelleborni I L. fuelIeborni 2 Melanochromis auratus M. parallelus I M. parallelus 2

1

2

2

3

7 9

4 7

7 0

4 2

T C C C T C C C C

T C C C C C C T C

C T T T C T T C C

C T T T C T T C C

aFrom Parker and Kornfield, 1997. bN u m b e r i n g of nucleotide positions follows Bowers et al. (1994).

of complete lineage sorting would be for phylogenetic analysis of this fauna. Two species of mbuna possess only one of the major haplotype lineages: all studied individuals (n = 30) of Pseudotropheus zebra "black dorsal," an undescribed species endemic to the Maleri Islands, exhibit the ]~3 mtDNA haplotype (Moran and Kornfield, 1995; Parker and Kornfield, 1997, as do all individuals (n = 99) of Melanochromis auratus (Bowers et al., 1994; Parker and Kornfield, 1997). Both cr and ]~J3 mtDNA lineages are present in populations of Pseudotropheus tropheops "black" (Moran and Kornfield, 1993). If P. tropheops "black" were to lose the ]3 lineage, perhaps by genetic drift (Moran and Kornfield, 1995), subsequent mtDNA comparisons would unite M. auratus and P. zebra "black dorsal" to the exclusion of P. tropheops "black," resulting in a phylogenetic hypothesis entirely at odds with available morphological and ecological data. Thus, if lineage sorting was complete in the mbuna, the reconstructed tree would provide completely misleading results. McMillan and Palumbi (1995) reached a similar conclusion regarding Pacific butterflyfishes, suggesting that the random assortment of shared ancestral lineages may blur the evolutionary history of newly formed species. Additionally, variation in rates of population growth can generate significant differences in lineage diversity among taxa (Penny et al., 1995). For mtDNA to be phylogenetically informative in such cases, lineages must independently acquire new mutations in addition to simple reduction, via genetic drift, of the number of ancestral haplotypes present. Given the recent derivation of this fauna, and presumed rates of mtDNA mutation, such differentiation is unlikely within the mbuna.

27

IV. A l t e r n a t e M o l e c u l a r A p p r o a c h e s

If mtDNA cannot provide sufficient information to resolve relationships within the mbuna, are there other molecular systems that can be exploited? It is important, of course, that such alternate approaches provide information useful beyond simple taxonomic discrimination. At least three classes of molecular markers might potentially be so employed. Variation in randomly amplified polymorphic DNAs (RAPDs) (Williams et al., 1990) has been exploited to identify subspecies of Oreochromis niloticus by Bardakci and Skibinski (1994). These taxa can not be differentiated by allozyme analysis, but do possess diagnostic mtDNA restriction profiles (Seyoum and Kornfield, 1992a,b). Although both RAPDs and mtDNA provide diagnostic markers for subspecies, neither data set provides unambiguous statistical support for relationships among the taxa. The extent of sequence divergence between subspecies (Seyoum and Kornfield, 1992a) is about half of that observed between a and ~ lineages in the mbuna; it is thus possible that RAPDs could be used to infer relationships among mbuna species. This approach is compelling from a statistical perspective because the products of a large number of random primers can be characterized. However, the extent of RAPD variation within natural populations of cichlids has not yet been examined and may be considerably greater than that seen in the inbred aquaculture strains examined to date. Further, the technical problems associated with RAPD analysis (e.g., Ellsworth et al., 1993), as well as ambiguity of locus homology between more distantly related taxa, suggest a cautious approach to the use of such data. As an alternative, DNA sequences associated with individual RAPD primers can be characterized. However, an initial examination of such data suggests that the phylogenetic signal thus obtained may be limited in very closely related taxa such as mbuna (Sultmann et al., 1995). Extensive sequence variation has been demonstrated in mbuna at major histocompatibility complex (Mhc) loci (Klein et al., 1993; Ono et al., 1993). This extremely variable system has been useful in the population genetic analysis of mammalian taxa (Klein, 1986). Significant impediments exist, however, in applying this system to mbuna phylogenetics. As in mtDNA, some portion of Mhc variation can be thought of as a retained ancestral polymorphism; allelic variants are shared by multiple taxa and predate speciation. More importantly, because much of this variation may be maintained by selection (Hughes and Nei, 1989), polymorphism will be retained. Finally, sequence variation

28

IRV KORNFIELD A N D ALEX PARKER

will be evolutionarily interpretable only if Mhc loci can be distinguished individually; previous studies have identified up to eight alleles per individual (Klein et al., 1993; Ono et al., 1993), indicating coamplification of a minimum of four loci. Assuming identification of individual loci and examination of only selectively neutral (fourfold degenerate) codon positions, rates of substitution must still have been sufficiently high to outpace speciation, if they are to allow discrimination of mbuna interrelationships. At this time it is unknown whether the Mhc system will fulfill all of the necessary criteria. More generally, sequence variation in other portions of the nuclear genome could potentially provide information sufficient for phylogenetic analysis; mutational mechanisms and methods for analysis of DNA sequences are well understood for nuclear genes. Variation at protein coding genes would, in general, be expected to provide insufficient sensitivity for the examination of closely related species, given selective constraints on molecular function and the paucity of variation in structural gene products revealed by electrophoretic studies. Although exon sequences are thus expected to be conservative, intron sequences may potentially exhibit more informative variation. Phylogenetic examinations of intron sequences are few in number to date, but interspecific differentiation in introns may be limited among closely related taxa. For example, comparisons of intron variation among humpback whale populations, which have very distinctive mtDNAs, were noninformative (Palumbi and Baker, 1994). In Old World cichlids, sequence comparison of the second intron of the growth hormone gene in Old World cichlids enabled discrimination of the three major tilapiine genera, but provided no information relevant to relationships among congeners (I. Kornfield and R. Mulrenin, unpublished observations). Use of anonymous single-copy DNA markers constitutes an additional approach to capturing genetic variation (Karl et al., 1992). However, observed allelic variation has been limited, even in extensively studied populations (Karl and Avise, 1993), and substantial methodological difficulties (Hare et al., 1996) may compromise their routine application. More generally, it is not clear whether introns (or exons) of other nuclear genes possess the high rates of mutation required for successful phylogenetic analysis of closely related taxa like the mbuna. Indeed, because mbuna mtDNA retains ancestral polymorphisms as described earlier, it seems unlikely that autosomal nuclear loci, with fourfold greater effective population sizes (Avise, 1994), would have undergone allelic fixation within lineages. Various classes of repetitive DNA (Charlesworth et al., 1994) have been examined in cichlids to assess

their phylogenetic potential. In tilapiines, several families of minisatellite repeats make up a considerable portion of the nuclear genome (Wright, 1989) and exhibit sequence variation both within and among lineages (Franck et al., 1992). Again, however, the phylogenetic signal appears limited to lineages that are demonstrably divergent by conventional molecular methods (Franck et al., 1994). It would therefore seem improbable that this class of markers will offer sufficient sensitivity for phylogenetic analyses within the mbuna.

V. Microsatellite Loci More promising is variation at microsatellite loci. Such loci can exhibit extremely large numbers of alleles, differing in the number of a simple nucleotide repeat unit present (Queller et al., 1993). Allelic variation is thought to be generated by intraallelic polymerase slippage during DNA replication (Bruford and Wayne, 1993), but details of the exact mechanism are not well understood. The fundamental appeal of microsatellite loci for systematic studies of the mbuna is that mutation rates are extremely high, in the range of 10 -3-10-4 per locus per generation (Dallas, 1992; Edwards et al., 1992). Consequently, variation in microsatellite allele frequencies is strongly influenced by mutation, in addition to genetic drift. Thus mutation-driven variation in population allele frequencies can greatly augment that engendered by genetic drift. In contrast, mutations in other classes of polymorphic nuclear markers, such as allozymes or Mhc alleles, occur by the relatively slow process of nucleotide substitution, whereas interpopulation variation in allele or electromorph frequencies occurs principally as a result of genetic drift. In light of the fact that insufficient time has passed for genetic drift to produce complete lineage sorting in mtDNA and the fourfold larger effective population size of diploid, biparentally inherited nuclear genes (versus haploid, maternally inherited mtDNA), the potential for informative variation in these markers may be limited. Mutation of microsatellite alleles has been modeled as a stepwise process, in which an allele consisting of a given number of repeat units may change by either loss or gain of a single repeat (Valdes et al., 1993). This model implies that pairs of alleles differing by a small number of repeats share a more recent common ancestor than those which differ greatly in repeat number; this potential information on relatedness of alleles is utilized by a novel, microsatellite-specific metric of ge-

3. Molecular Systematics of mbuna

netic distance (see later). The stepwise mutation model (SMM) also illustrates the potential for convergent evolution of alleles, as there is no obvious way to determine whether an allele of a given size is descended from an ancestor possessing a greater or lesser number of repeat units. More recent studies, however, suggest that the SMM incompletely describes the mutational process at microsatellite loci. Using data on the human population of Sardinia, DiRienzo et al. (1994) demonstrated that observed allele frequency distributions are better explained by a two-phase model, incorporating infrequent mutational changes of two or more repeat units, than by a model including only single-step mutation. If multistep mutations are common, and microsatellite alleles are therefore often dissimilar in size to their immediate ancestors, than the infinite alleles model (IAM) may be more appropriate. A result consistent with this possibility was obtained by Estoup et al. (1995), who found that observed heterozygosities and allelic diversities in honeybee populations agreed more closely with IAM expectations than with the stepwise model. In contrast to the conclusions of DiRienzo et al. (1994), however, Estoup et al. (1995) suggested that their data deviated from stepwise expectations because most of the loci they studied consisted of complex repeats, whereas the SMM assumes that microsatellite loci are unbroken tracts of a single sequence motif. Determination of which model better describes variation at microsatellite loci has important implications for analysis. If the IAM is superior, then use of a classical measure of genetic distance, such as Nei's distance (Nei, 1987), would be appropriate. If the SMM realistically approximates microsatellite evolution, however, the implication is that there may be more information available in microsatellite data than is embodied in simple allele frequencies. Because closely related alleles are similar in repeat number under the SMM, it follows that the mean number of repeats at a locus should be more similar in recently isolated species or populations than in more distantly related ones. This observation motivated development of the delta-# distance statistic (Goldstein et al., 1995), which incorporates repeat number as well as frequency of alleles. Goldstein et al. (1995) showed analytically that an increase in delta-/~ is linear with time and independent of populations size, as long as populations are in mutation-drift equilibrium. They also empirically evaluated the behavior of delta-#, Nei's distance, and allele sharing in analysis of both human and primate relationships. Their results indicated that delta-/~ is superior for reconstruction of more distant evolutionary patterns (e.g., h u m a n chimpanzee-gorilla relationships), probably because it

29

remains linear over a greater range of divergence, but that the classical distance metrics better reconstructed more recent relationships [e.g., among human populations; see e.g., Bowcock et al. (1994)]. Regardless of the method employed, several characteristics of microsatellite loci may complicate analysis. Most importantly, because microsatellite loci appear to be bounded in size, exhibiting an upper limit in repeat number (Bowcock et al., 1994), any genetic distance metric will eventually reach an asymptote. For the human data considered by Goldstein et al. (1995), the average time to asymptotic distance was estimated to be approximately 20,000 generations; for any particular locus, the duration of linearity prior to the asymptote is proportional to the range of repeat numbers present. Additionally, Rubensztein et al. (1995) suggest that comparison of human microsatellite data to that for other primates reveals the presence of directional mutation pressure at some loci. Ellegren et al. (1995), however, have argued convincingly that this result instead reflects biases in sampling of loci. Finally, the potential presence of null (nonamplifying) alleles (Paetkau et al., 1995; Pemberton et al., 1995) may be problematic, although investigators who are aware of this possibility can take steps to minimize its influence (see later). Two studies have demonstrated the enormous utility of microsatellite variation for analysis of population biology of individual mbuna species (Kellogg et al., 1995; Parker and Kornfield, 1996). In these studies, genotypes at hypervariable microsatellite loci were used to examine the magnitude of polyandry in several species. Although allelic distributions can be used to discriminate among mbuna species (A. Parker and I. Kornfield, unpublished observations), it has not yet been experimentally demonstrated that microsatellite variation can be used for phylogenetic reconstruction in cichlid fishes. This idea is evaluated next.

VI. A Test of the Phylogenetic Potential of Microsatellites Before initiating investigations, it is critical to provide, a priori, a fair test of the ability of microsatellites to provide phylogenetic data relevant to the mbuna. Evolutionary trees can be generated using virtually any data set, so unless relationships among the taxa examined have previously been defined, any result might be viewed as a positive outcome. However, given the rapid mutation rate of this class of markers, it is improbable that their performance could be validated us-

30

IRV KORNFIELDAND ALEX PARKER

ing comparisons among taxonomic groups that have been successfully discriminated using other molecular methods. For example; significant divergence between the mbuna and the other major haplochromine clade of Lake Malawi is recognizable with mtDNA (Moran et al., 1994); these groups would be expected to also differ in microsatellite allele frequencies. However, a simple demonstration of differences does not constitute evidence of phylogenetic information, as microsatellite primers often amplify across very wide taxonomic spectra (Schl6tterer et al., 1991; Levin et al., 1995; P6pin et al., 1995; see later); the major Malawian haplochromine clades are likely far too divergent to retain signal in the form of differences in microsatellite allele frequency or composition. Similarly, comparisons between the major tilapiine lineages, or among species of Oreochromis with previously defined relationships, would probably provide diagnostic allele distributions but not phylogenetic information.

H y p o t h e s i s Formulation A conservative test is used to assess the potential significance of microsatellite variation for phylogenetic reconstruction in the mbuna. Although no explicit phylogeny is available, a number of lineages are unambiguously distinctive. Such lineages were originally recognized on the basis of substantive morphological differences and define the endemic genera (Regan, 1921; Trewavas, 1935). Three distinctive genera which have received considerable morphological and ecological study have been selected (Trewavas, 1935; Ribbink

et al., 1983a,b; Reinthal, 1990a,b): Labeotropheus Ahl, 1926; Melanochromis Trewavas, 1935; and Pseudotropheus Regan, 1921. The major features of these genera are summarized in Table II; representative species are illustrated in Fig. 1 (see color plate). In addition to dentition and osteological characters, note the well-defined differences in color patterns among these taxa; such characters are viewed as central in defining haplochromine lineages (Eccles and Trewavas, 1989). Given that these genera of mbuna are well defined, all contained species should be more similar to congeners than to species of any other mbuna genus. This forms the basis for our test of phylogenetic information content. From each of the three genera, two species were chosen for study: Labeotropheus fuelleborni Ahl, 1926; L. trewavasae Fryer, 1956; Melanochromis auratus (Boulenger, 1899); M. parallelus Burgess and Axelrod, 1976; Pseudotropheus zebra "BB" (Boulenger, 1899), and P. zebra "black dorsal." The two species of Melanochromis belong to the same infrageneric complex (Ribbink et al., 1983b). The genus Pseudotropheus contains a number of well-defined infrageneric complexes, some of them certainly worthy of generic rank (Ribbink et al., 1983b); the species of Pseudotropheus examined here are both members of the P. zebra species complex. P. zebra "BB" is the blue-barred form collected from Thumbi Island West, whereas P. zebra "black dorsal" is an undescribed taxon endemic to the Maleri Islands in southern Lake Malawi (Ribbink et al., 1983b; Konings, 1990). The null hypothesis tested is that all six taxa are equidistant from each other and form a "star" phylogeny (Fig. 2A). This situation would obtain if microsatellite

TABLE H Morphological and Ecological Characteristics of Three mbuna Genera a,b Pseudotropheus Regan, 1921 Oral dentition Ethmovomer Orientation Relative width Gut length (relative to SL) Mouth position Color pattern Feeding posture c Mean niche breadth (algae) Depth distribution Territoriality

Melanochromis Trewavas, 1935

Labeotropheus Ahl, 1927

Bicuspid

Bicuspid

Tricuspid

Horizontal Medium 4.5 + 0.8 Terminal Vertical b a r s Perpendicular 4.21 3-25 m Continuous

Horizontal Small 3.5 + 0.6 Terminal Horizontal stripes Acute 6.65 4-35 m Weak/intermittent

Vertical Medium 5.2 + 0.8 Subterminal Vertical bars Parallel 6.05 0-18 m Variable

The genus Pseudotropheus as currently defined includes a variety of morphologically distinct clades; several are worthy of generic status. Characters typical of the clade are presented, including P. zebra [see Reinthal (1987)for discussion]. bData compiled from Trewavas (1935),Fryer (1959b),Ribbink et al. (1983b),Reinthal (1987),I. Kornfield (personal observations). cBodyposition relative to rock surface when grazing on epilithic algae. a

3. Molecular Systematics of mbuna

A

maximum information content; clearly weaker alternatives could also be constructed.

R zebra 'black dorsal'

L. fuelleborni

31

R zebra "BB'

VII. Materials and Methods L. trewavasae

M. auratus M. parallelus

B

R zebra 'black dorsal'

L. fuelleborni

R zebra "BB'

L. trewavasae

M. auratus M. parallelus

C

R zebra 'black dorsal' R zebra "BB'

L. fuelleborni

L. trewavasae

M. auratus M. parallelus

FIGURE 2 Hypothetical and actual relationships among three congeneric pairs of mbuna. (A) The null hypothesis (H0): no definable relationships exist among the taxa. (B) The stringent alternative hypothesis (H1): all congeners unite in lineages distinct from other genera. (C) The relationships among six mbuna species based on neighbor-joining analysis of genetic distances inferred from two hypervariable microsatellite loci. Numbers indicate the percentage of bootstrap replicates (out of 100) in which associations were supported.

mutation rates are either excessive or insufficient to provide phylogenetic information. Alternatively, if a phylogenetic signal is present in microsatellite data, each pair of congeneric species should cluster to the exclusion of other tested taxa (Fig. 2B). This formulation of the alternative hypothesis is consistent with

Microsatellite Characterization

All specimens used were wild-caught fishes. Tissue samples of P. zebra "black dorsal" and P. zebra "BB" were collected in August 1988 and December 1990 and field frozen in liquid nitrogen (Moran and Kornfield, 1995); nuclear and mitochondrial DNAs were prepared by density gradient ultracentrifugation (Dowling et al., 1990). All other species were collected in September (L. fuelleborni, M. auratus; Chipoka) or November 1994 (L. trewavasae, M. parallelus; Nkhata Bay) and preserved in ethanol. DNA was prepared from muscle tissue of these specimens using proteinase K digestion followed by phenol/chloroform extraction and ethanol precipitation. Two microsatellite loci were examined in all individuals: UME002 and UME003 (GenBank accessions U14396 and U14397); these loci had been isolated previously from a P. zebra "gold" genomic library using conventional methods (Parker and Kornfield, 1996). These two loci are composed of complex repeats [allele 280 at locus UME002: (GT)12(93bp)(TCTA)19; allele 195 at locus UME003:(AT)6AAA(AT)2ACA(TG)6 (GCGT)13] and are hypervariable, each exhibiting greater than 23 alleles even in small population samples (see later discussion). Microsatellite genotypes for all individuals were determined from 32 P-labeled polymerase chain reaction products separated on 6% polyacrylamide sequencing gels; a 35S-labeled M13 sequencing ladder was used as a size standard on all gels. Allelic compositions for all species were examined for fit to Hardy-Weinberg expectations using a modified version of BIOSYS (Swofford and Selander, 1981; P. Moran, personal communication). Tests of genotypic homogeneity were conducted using the resampling programs of Zaykin and Pudovkin (1993). Genetic distances were calculated using the delta-/_t distance of Goldstein et al. (1995), allele sharing, and Nei's distance; all distance calculations were performed using MICROSAT vl.4 (Minch, 1995). Phylogenetic relationships were inferred from these distances using the neighbor-joining method (Saitou and Nei, 1987), implemented by PHYLIP v3.5 (Felsenstein, 1993); statistical support for elements of the resultant phylogenetic tree was estimated by resampling across individuals (Van Dongen, 1995).

32

IRV KORNFIELD A N D ALEX PARKER

VIII. Results Extensive variation was uncovered for all species at both loci. At UME002, samples of individual taxa possessed approximately 25 alleles, with 64 alleles detected in total (Fig. 3A); UME003 was almost as variable, with each species exhibiting approximately 21 of the total of 48 alleles observed (Fig. 3B). Frequency distributions were multimodal, with extensive gaps separating some size classes of alleles. Heterogeneity of genotypic frequencies among taxa was highly significant for both loci. After adjustment of significance criteria for multiple tests (Rice, 1989), two species deviated significantly from Hardy-Weinberg expectations at UME002 (M. parallelus and L. trewavasae), as did one at UME003 (M. parallelus). In M. parallelus, a null al-

mately 0.398 in M. parallelus. No presumptive homozygous null genotypes were observed at this locus for L. trewavasae, although the sampled population exhibited a large heterozygote deficiency. Although it is possible that this taxon also possesses a null allele, apparent heterozygote deficiencies are not implausible given the sample sizes employed (see later). The topology of the neighbor-joining tree obtained using the delta-/z statistic (Fig. 2C) allows the null hypothesis to be rejected and suggests that phylogenetic

signal is present in the microsatellite data. The pattern of relationship among species was neither a star nor a random combination of taxa. The Labeotropheus lineage was the most supported; the Pseudotropheus lineage had significant definition, but the two species of Melanochromis were not consistently united to the exclusion of other taxa. The same topology was recovered

lele(s) is suspected to be present at locus UME002; a number of individuals showed no amplification at

using allele sharing, but with reduced bootstrap support for both the Pseudotropheus and the Labeotropheus

UME002, but simultaneously expressed genotypes at UME003. Assuming Hardy-Weinberg equilibrium, the overall null allele frequency at UME002 is approxi-

clades. Using Nei's distance, only the Labeotropheus clade received bootstrap support in excess of 50% of replications. In light of the results of Goldstein et al.

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FIGURE 3 Allele frequency distributions at two hypervariable microsatellite loci in six mbuna species. Dashed lines enclose saltines separated by large gaps (see text). (A) Distribution of alleles at locus UME002. (B) Distribution of alleles at locus UME003.

i

,

3. Molecular Systematics of mbuna

(1995; see earlier), this suggests that the intergeneric comparison may be at the outer limit of phylogenetic utility for microsatellite data.

33

zygote deficiencies are observed in the absence of null homozygotes.

A. Sampling Considerations IX.

Discussion

This chapter has provided evidence that hypervariable microsatellite loci contain phylogenetic information potentially capable of resolving relationships within the mbuna. This is the first class of molecular markers shown to possess sufficient power to elucidate the evolutionary history of that fauna. The successful definition of relationships clearly depends on the number of loci studied; neither UME002 nor UME003 alone provided resolution equal to that obtained from the two loci considered together. This is consistent with the recommendations of Pamilo and Nei (1988) and with the results obtained by Bowcock et al. (1994), who produced a tree of human racial groups using 30 microsatellite loci; reanalysis using small subsets of these data does not result in consistent resolution (A. Parker and I. Kornfield, unpublished observations). Because the number of loci characterized was small, and the number of mbuna species examined was limited, it is not yet clear at what taxonomic level microsatellites will prove most useful in this assemblage, i.e., microsatellite loci may be of value for defining relationships among congeners or allopatric populations of conspecifics rather than relationships among genera. The current debate over appropriate models of microsatellite evolution (Shriver et al., 1993; Valdes et al., 1993) should not be viewed as a significant impediment to the phylogenetic application of these loci. For example, even if rate heterogeneity is present in the production of different classes of alleles, the relative relationships among taxa should be resolvable, even if absolute distances are biased. Further, the lack of consensus regarding appropriate methods to quantify divergence (Queller and Goodnight, 1989; Goldstein et al., 1995; Shriver et al., 1995; Van Dongen, 1995), and construct evolutionary trees (Swofford and Berlocher, 1987; Crother, 1990), should not proximately inhibit the use of microsatellite variation for phylogenetic study of the mbuna. The presence of null alleles at some loci should not compromise the validity of evolutionary inferences if data analysis is based on genotypic rather than allelic frequencies. When presumptive null homozygotes are observed, null allele frequencies may be estimated by maximum likelihood methods (Raymond and Rousset, 1995); it is at present unclear how allele frequencies should be estimated when hetero-

Of great practical importance is the number of microsatellite loci and individuals that must be sampled to provide reliable resolution of phylogenetic relationships. It is obvious from theoretical considerations (Pamilo and Nei, 1988; Weir, 1990) that resolution is improved as greater numbers of loci are examined; this is particularly true if loci exhibit only moderate levels of allelic diversity (and thus lower information content). The number of individuals that must be sampled depends principally on the number of alleles present at each locus. In addition, large sample sizes may be essential for the detection of outliers (see later). When allelic diversity is low, relatively few individuals need be examined. However, informative variation may exist principally at hypervariable loci, and it is here that large sample sizes are essential to the determination of allele frequencies with statistical confidence (Fig. 4). For example, with an average of 25 alleles per population at UME002 (Fig. 3A), simulations suggest that approximately 115 individuals should be examined from each population (A. Parker, unpublished data; see Fig. 4). These simulations involved iterative sampling of alleles with replacement from randomly generated frequency distributions, with sample-population identity (Nei's unbiased genetic identity; Nei, 1987) calculated after each additional allele was sampled. As individuals were added, sample-population identity was observed to increase rapidly to a value of approximately IN = 0.97, beyond which point improvement in identity was extremely gradual; thus this value (IN = 0.97) was inter-

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Simulation of sample size required to produce allele frequency estimates of similarity IN -->0.97 [Nei's unbiased genetic identity; Nei (1987)] to actual population allele frequencies (A. Parker, unpublished data). The empirical relationship derived from these simulations is: Sample Size = 1.5(N alleles)135. FIGURE 4

34

IRV KORNFIELD AND ALEX PARKER

preted to represent the point beyond which additional sampling effort is no longer worthwhile. In the present case, however, only 25 to 47 individuals were sampled per taxon. Thus, the resolution of relationships based on these two loci may be incomplete.

0.t3

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B. Evolutionary Signals in Microsatellites

011 0.05

There are three independent classes of phylogenetic information that can potentially be gleaned from microsatellite loci. The authors anticipate that these classes will be appropriate for examining relationships at different taxonomic levels. First, allele frequency distributions may be compared using genetic distance metrics based on the stepwise mutation model of microsatellite evolution (Slatkin, 1995; Goldstein et al., 1995). A second class of phylogenetic information, however, may be present in microsatellite allele frequency distributions. Major gaps in allele size distributions may signify unique mutational events. For example, in M. parallelus, alleles of size 150-180 bp are recognized at locus UME002 as representing expansion, via stepwise mutation, from a single allele produced by a distinct, saltatory mutational process (Fig. 3A). This class of alleles is separated from the next smallest allele by 75 bp; it thus conforms to the two-phase mutation model presented by DiRienzo et al. (1994), wherein divergent repeat classes are generated by infrequent large jumps. Machado-Joseph disease also conforms to this model; this pathology appears when a trinucleotide repeat increases by at least 75 bp to form a new allelic class (Maciel et al., 1995). As Maciel et al. (1995) noted, "clustering of expanded repeat sizes is also suggestive of a unique ancient founder mutation." A cladistic perspective, recognizing such novel classes of alleles as discrete characters, is adopted here; in light of the saltatory nature of the mutational events hypothesized to generate them, such characters are called saltines to distinguish them from standard patterns of microsatellite allele variation. Thus, the allelic class centered at 178 bp for UME002 in M. parallelus constitutes an autapomorphic saltine; if shared among independent lineages, saltines may be treated as synapomorphies. In this manner, some aspects of microsatellite allele distributions can be analyzed by standard cladistic methods (Swofford, 1990) rather than by distance approaches. Indeed, if a large number of loci were examined, it would be anticipated that saltines would permit construction of robust phylogenetic trees. However, like ancestral mtDNA polymorphisms, saltines can be retained or lost in multiple lineages. For example, in the human microsatellite data analyzed by Bowcock et al. (1994), locus ms164 has two

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Allelesize(bp) FIGURE 5 Distribution of alleles at human microsatellite locus

ms164 (E. Minch, personal communication);this locus was included in the study of Bowcocket al. (1994).The two divergentallelicclasses depicted are shared by a number of diverse human lineages. Aggregate sample size is 250.

allelic classes separated by 16 bp which are present in diverse human lineages (Fig. 5). Inspection of allele distributions at UME003 (Fig. 3B) reveals the presence of two major expansion classes centered around 149 and 201 bp; the smaller expansion class has probably been lost from both M. auratus and P. zebra. Genetic drift may play a major role in molding the distribution of rare expansion classes. If drift were to eliminate relatively infrequent alleles associated with major allelic clusters, e.g., the class centered around 300 bp at locus UME002 (Fig. 3A), such alleles could be regenerated rapidly by mutation. In contrast, if eliminated by drift, variation embodied in saltines would not be regenerated. For example, the absence of the saltatory class centered at 178 bp at UME002 from M. auratus could be due to drift. Indeed, mtDNA diversity is observed to be relatively low in this taxon (Bowers et al., 1994), consistent with the possibility of a recent population bottleneck. Note that it is critical that sample sizes be large enough to reliably detect the presence of saltines that occur at low absolute frequencies in some populations. To date, no one has exploited this class of information to construct phylogenetic trees. Finally, similar to saltines, the ability (or inability) of a given microsatellite primer pair to amplify DNAs from certain taxa can be treated as a cladistically informative binary character and forms a third potential information class. Again, such characters may constitute synapomorphies and can thus be used to infer relationships from a cladistic perspective, although no empirical information about the prevalence of these characters in cichlid fishes can be found. If null alleles are to be employed in this fashion, it is imperative that new flanking primers be designed and used to dem-

3. Molecular Systematics of mbuna

onstrate, by sequencing, that all observed null alleles are due to homologous changes in the original priming sites.

X. Summary The classical methods of molecular phylogenetic investigation, allozyme electrophoresis and mtDNA restriction or sequence analysis, have failed to resolve relationships among members of rapidly evolving species flocks such as the mbuna (Cichlidae) of Lake Malawi. Several classes of nuclear DNA markers may, however, provide greater resolution; most promising are microsatellite markers. The extremely high mutation rates at these loci render them fundamentally different from other nuclear DNA polymorphisms, as changes in allele frequency are influenced by mutation as well as genetic drift. Analysis of two microsatellite loci in three congeneric pairs of mbuna species strongly suggests that these markers can provide phylogenetic information relevant to these recently diverged taxa.

Acknowledgments We are exceedingly grateful to S. Grant, Salima, Malawi, for providing specimens and supporting our research. L. DeMason also supplied critical logistical support. E. Minch kindly shared unpublished human microsatellite data and provided a copy of his program to calculate delta-/z. A. Konings generously permitted reproduction of his mbuna photographs. M. Stiassay is inspirational. We are grateful to the editors and two anonymous referees who provided comments which helped improve this manuscript. This work was supported by NSF EHR91-08766 and NOAA Sea Grant NA36RG0110.

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C H A P T E R

4 Reconstruction of Cichlid Fish Phylogeny Using Nuclear DNA Markers ~176

H O L G E R S U L T M A N N and WERNER E. MAYER

Max-Planck-Institut fiir Biologie Abteilung Immungenetik D-72076 Tiibingen, Germany

some of which gave rise to more recent groups in lakes Malawi (Kocher et al., 1993) and Victoria. A comparatively large genetic divergence between species of the genus Tropheus from Lake Tanganyika was found to be accompanied by small morphological changes (Sturmbauer and Meyer, 1992). However, high morphological plasticity was found within the single New World species Cichlasoma managuense (Meyer, 1987). In addition, although some cichlid species from different lakes resemble each other morphologically, molecular data indicate that this similarity is due to convergent evolution (Kocher et al., 1993). Most of the cichlid species of Lakes Malawi and Victoria are endemic (Kornfield, 1978; Meyer et al., 1990; Greenwood, 1991) and monophyletic (Meyer et al., 1990; Meyer, 1993). Taking into account the estimated ages of 2 MY for Lake Malawi and less than 1 MY for Lake Victoria (Fryer and Iles, 1972), questions arise as to the speed and mode of speciation leading to hundreds of different species. It has been shown by allozyme variation that speciation in Lake Malawi occurred rapidly (Kornfield, 1978). Allopatric speciation might have been promoted by considerable fluctuation in the water levels of Lakes Malawi and Victoria (Livingstone, 1980; Owen et al., 1990). However, microallo-

I. I n t r o d u c t i o n

The family Cichlidae constitutes a monophyletic group in the order Perciformes (Kaufman and Liem, 1982). Monophyly of the cichlid family is indicated by the presence of at least nine synapomorphic morphological characters (Stiassny, 1991; Zihler, 1982; Gaemers, 1984). Since the distribution of cichlids ranges from South and Central America and Mexico to tropical Africa, Madagascar, southern India, and Sri Lanka (Ribbink, 1991), the cichlid family must have arisen before the separation of Africa, South America, and India by continental drift more than 100 million years (MY) ago. The morphology of cichlid species has been studied for almost 100 years and various classification schemes have been proposed (e.g., Pellegrin, 1904; Regan, 1906; Vandewalle, 1971; Trewavas, 1973, 1983; Poll, 1986; Greenwood, 1987; Cichocki, 1976; Stiassny, 1987, 1991; Oliver, 1984). The cichlid taxa in the Great Lakes of East Africa (Lakes Victoria, Malawi, and Tanganyika) are of special interest, having undergone recent explosive adaptive radiations leading to hundreds of different species. Lake Tanganyika, which is approximately 12 MY old (Cohen et al., 1993), provides an ancient reservoir of polyphyletic taxa (Nishida, 1991),

MOLECULAR SYSTEMATICS OF FISHES

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Copyright 9 1997 by Academic Press. All rights of reproduction in any form reserved.

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HOLGER SLILTMANN AND WERNER E. MAYER

patric or even sympatric speciation cannot be ruled out, particularly because habitats and niches are quite restricted for most of the species (Ribbink, 1991; Meyer, 1993). Before hypotheses regarding the speciation process can be postulated, the phylogenetic relationships among the various cichlid taxa must be elucidated. Two main difficulties have, however, hampered the reconstruction of cichlid phylogenies from morphological characters: paucity of synapomorphic characters, which hinders the recognition of taxonomic groups, and abundant parallelism, which makes it difficult to ascertain whether shared characters are synapomorphies or homoplasies. To circumvent these problems, molecular analyses have been initiated and used for the construction of phylogenies for cichlid species and species flocks (i.e., monophyletic groups of closely related species coexisting in the same area; Greenwood, 1984; Nishida, 1991; Sage et al., 1984).

II. Methods Used for Reconstructing Cichlid Phylogeny The present taxonomy of cichlids in the east African lakes is largely based on morphological characters, particularly the shape of the jaws and teeth as well as the trophic behavior (Greenwood, 1979, 1980). For a variety of allozymes, allelic frequencies have been estimated from the electrophoretic mobility patterns (Sage and Selander, 1975; Kornfield, 1978; Kornfield et al., 1979; McKaye et al., 1982; McAndrew and Majumdar, 1983, 1984; Sage et al., 1984; Nishida, 1991) and used to calculate genetic distances between sister groups of cichlids. These data allowed the subdivision of cichlids into genera and species flocks. For the Lake Victoria cichlids, however, despite their considerable morphological differences, genetic distances were too small (0.006 substitutions per locus; Sage et al., 1984) to evaluate interspecies relationships. The substitution rate at the mitochondrial control region and adjacent loci (cytochrome b and tRNA genes) has been shown to be higher than that of most nuclear DNA loci (Brown et al., 1979). Sequence analyses of mitochondrial DNA (mtDNA) (Meyer et al., 1990; Sturmbauer and Meyer, 1992, 1993; Kocher et al., 1993, 1995; Sturmbauer et al., 1994; Moran and Kornfield, 1993; Schliewen et al., 1994; Bowers et al., 1994) have extended the phylogenetic trees of the Lake Tanganyika and Malawi lineages and confirmed the monophyly of the Lake Victoria species flock. Discrep-

ancies between the restriction fragment length polymorphism (RFLP) pattern of mtDNA and the species tree based on morphological characters, however, led Moran and Kornfield (1993) to suggest an ancestral polymorphism in the founding populations of the Lake Malawi flocks, which hinders an accurate determination of their phylogenetic relationships. In addition to this problem of polymorphism predating species divergence, the low number of mtDNA markers available is a limiting factor. In contrast to the low genetic diversity among cichlids as revealed by allozyme data is the finding of high polymorphism at the Mhc (major histocompatibility complex) loci (Klein et al., 1993; Ono et al., 1993). Although some of this polymorphism is ancient (predating species divergence), the high number of different Mhc groups (loci) and alleles in cichlids might make the Mhc a useful genetic tool for studying cichlid phylogeny (Klein et al., 1997). The detection of a family of tandemly repeated satellite DNA elements in tilapia (Wright, 1989; Franck et al., 1992) has enabled Franck and co-workers (1994) to provide evidence for a close relationship of the mouthbrooding tilapiine genera Oreochromis and Sarotherodon in contrast to the substrate spawning genus Tilapia. In this report, nucleotide differences between the satellite consensus sequences for each genus were used for the construction of a phylogenetic tree. Using the molecular methods just described, the aim of elucidating the evolutionary history of cichlid species within the monophyletic groups of Lakes Malawi and Victoria has been achieved only partially, either because of the poor resolution achievable by the methods or because of the low number of polymorphic loci found. Thus, using more polymorphic nuclear DNA markers is the only means for making further progress in this field of research. The search for such new markers was greatly facilitated by the discovery of the polymerase chain reaction (PCR) (Saiki et al., 1988). This chapter describes and discusses the application of two PCR-based methods. First, S~iltmann et al. (1995) used the random amplification of the polymorphic DNA (RAPD) technique (Williams et al., 1990; Welsh and McClelland, 1990) to identify polymorphic genomic loci, followed by locus-specific DNA amplification and sequence determination of the fragments. In a second (unpublished) approach, locus-specific PCR primers were used to amplify microsatellite repetitive elements to determine allele size frequencies among cichlid species from Lake Victoria. Nucleotide substitutions and allele frequency differences between species were then used to calculate genetic distance matrices and to construct phylogenetic trees.

4. Reconstruction of Cichlid Phylogeny

III. Random Amplification of Polymorphic DNA (RAPD) The RAPD procedure (Welsh and McClelland, 1990; Williams et al., 1990) was originally developed as a method for fingerprinting genomes. PCR amplification is performed using a single oligonucleotide, typically a 10-mer primer, at low annealing temperatures (35-40 ~ Fig. 1A). Depending on its sequence, the primer randomly anneals to an unknown segment on one of the DNA strands. In some cases, another annealing site will be present on the complementary strand not too distant from the first site and amplification will occur. When two species, strains, or individuals are compared, polymorphism between them will be revealed on agarose or polyacrylamide electrophoresis gels by the presence or absence of an amplification product. This method has been applied to the discovery of genetic markers for mapping studies (Serikawa et al., 1992; Postlethwait et al., 1994) and to elucidate phylogenetic relationships between bacterial species and strains (Welsh and McClelland, 1990; Smith et al., 1994) and tilapiine cichlid species (Bardakci and Skibinski, 1994). In the latter case, three species of the genus Oreochromis and four subspecies of Oreochromis niloticus could be distinguished. However, analyses of the reaction conditions (Ellsworth et al., 1993; Muralidharan and Wakeland, 1993; Smith et al., 1994; Bowditch et al., 1994) have shown that RAPD is highly sensitive to a wide range of factors: the quality of the template DNA, minute contaminations of RNA, the primer/template ratio, and small changes of the magnesium concentration. In addition, it is prone to producing spurious fragment variation (as shown, for example, by comparison of F1 hybrid DNA with parental DNA; Ayliffe et al., 1994) and other artifacts. Therefore, the procedure has been supplemented by sequencing the differential RAPD fragment and designing primers for locus-specific amplification in standard PCR. Although the RAPD polymorphism is presumed to be located at the annealing site of the 10-mer primer, it has been shown that the primer-binding sites are often identical between two samples showing polymorphic bands (Bowditch et al., 1994). The most likely explanation for this is that the formation of different secondary structures of the DNA templates, due to nucleotide substitutions outside the annealing sites, affects the accessibility of the annealing sites. To examine variation at the RAPD primer annealing site, the "vectorette" technique described by Riley and co-workers (1990) was also applied. Genomic DNA was digested with restriction endonucleases, and so-

41

called vectorette linkers were ligated to all fragments (Fig. 1B). The vectorette linkers consisted of two oligonucleotides that were complementary to each other at their 5' and 3' ends, but contained a central mismatched region. In the subsequent PCR, the firststrand DNA synthesis primed by a locus-specific oligonucleotide was essential for the generation of the binding site of the so-called vectorette primer that specifically annealed to the complementary strand of the mismatched region of the vectorette linker. Thus, specific exponential amplification of the flanking region occurred. The PCR products were then cloned and sequenced by standard methods. Using two DNA samples (shown to be devoid of RNA by ethidium bromide staining) from Pseudotropheus zebra and Melanochromis auratus, the RAPD conditions that yielded the most reproducible results were determined and then these were kept constant in subsequent experiments. The conditions were as follows: 50-60% G +C content for the 10-mer primer (see Stiltmann et al., 1995), which was used at a concentration of 4/xM in the PCR (a combination of two 10-mer primers can also be used for the amplification); 100/xM each of dATP, dCTP, dGTP, and dTTP; 2.5 units of Taq polymerase; and 100 ng of template DNA in a total reaction volume of 25 #1 in 1• reaction buffer containing 1.5 mM magnesium chloride. The PCR program consisted of 45 sec at 93~ 15 sec annealing at 35-42~ and 10 min primer extension at 72 ~ followed by 35 to 45 cycles, each 15 sec at 93 ~ 15 sec annealing at 35 ~ 42~ and 3 min primer extension at 72~ The reaction was completed by a final primer extension step for 10 min at 72~ Only those cases which gave concordant banding patterns for two individuals of each species were examined further. Figure 2 shows an example of a typical result of the RAPD reaction where a polymorphic band of about 400 bp in size is present in P. zebra but absent from M. auratus. The fragments were subcloned in pUC18 or M13 vectors and sequenced (Sanger et al., 1977). From three of these sequences, specific primers for amplification were constructed. The corresponding loci were called DXTU1, DXTU2, and DXTU3 (for details, see Stiltmann et al., 1995). In the specific PCR, the following observations were made: 1. Polymorphism of locus-specific PCR products was frequently observed. The proportion of polymorphic versus monomorphic loci obtained by this procedure was estimated to be higher than 50%. 2. The applicability of the specific primers varied depending on the locus examined. At DXTU1, products were obtained from neotropical as well as from

42

HOLGER SfdLTMANN A N D WERNER E. M A Y E R

B

A

R

R

R

X

genomicDNA

10mer primer(X)

Restriction digest of genomic DNA

~ Denaturing, annealingat low stringency X

X

Species A

Species B

~

~

(RAPD) PCR underlow stringencyconditions

X

Ligation of vectorette linker containing a central mismatched segment

./"

Heat denaturation

no exponentialamplification fromspeciesA exponentiallyamplifiedDNA fragment from species B

~ Subcloning, Sequencing, Constructionof specific primersY andZ

1 st strand synthesis with target primer

~ StandardPCRusing manyspecies'DNA as templates

PCR with target and vectorette primers

"~LLLUdz

/

|

/

no priming

Z

~ Subcloning, Sequencing Phylogeneticanalysis

FIGURE I (A) Schematic outline of the RAPD method. See text for details. (B) Schematic outline of the vectorette approach. Genomic DNA is digested with a restriction enzyme (R). A vectorette linker, composed of two oligonucleotides that are complementary only at the ends and leave a central mismatched part, is ligated to the DNA fragments. In a PCR the synthesis of first-strand DNA is primed by an oligonucleotide specific for the target segment of a known sequence (shown as black box) and extended into the flankingparts and vectorette linker. This strand is used as a template in subsequent PCR cycles by the vectorette primer, which is located in the mismatched segment of the linker.

west and east African cichlid species, whereas at DXTU2, no products were found in cichlid species outside the Lake Victoria and Lake Malawi regions. These results are most likely due to different extents of conservation at the primer-binding sites. 3. Another notable feature of the specific PCR was the appearance of several by-products in addition to the band of the expected size. Since the possibility of amplification from multiple related loci (e.g., diversified repeats) could not be excluded in some cases, a third primer was used to prove the singularity of the amplified region in the cichlid genome. Sequence variability in the D N A fragments resulting from specific PCR can also be examined using single-stranded conformation polymorphism (SSCP;

Orita et al., 1989a,b) analysis. In this approach, distinct banding patterns of PCR products from different species indicate sequence differences between species at a single locus. The polymorphic locus DXTU1 was selected for a detailed sequence analysis using the GCG software package (Devereux and Haeberli, 1991) or the Clustal V program (Higgins et al., 1992). The following analysis of representative sequences at the DXTU1 locus is shown (contact author for raw data): 1. It is remarkable that insertions or deletions (indels) constitute about one-quarter of the total number of polymorphic sites found at the DXTU1 and the other genomic loci. Although nucleotide substitutions are commonly used in phylogenetic tree construction, in-

4. Reconstruction of Cichlid Phylogeny

12345

1358 bp 1078 bp 872 bp

-.91~

603 bp v

FIGURE 2 Products obtained by RAPD PCR with the 10-mer primer TU984 (5' GTGTGCCCCA3'). Products from Pseudotropheuszebra (lanes 1 and 2) and Melanochromisauratus (lanes 3 and 4) were separated on a 2% agarose gel. The left arrow indicates a 400-bp band present only in lanes I and 2. Lane 5 contains DNA size marker. The arrows on the right denote marker sizes.

(~ (~f

dels are normally excluded, yet the n u m b e r of possible ways by which nucleotides can be inserted, deleted, or rearranged is nearly unlimited, in contrast to the three possibilities by which nucleotides can be substituted at a single site. Thus, data could be analyzed by two different methods: the standard tree construction m e t h o d based on genetic distances and the neighbor-joining algorithm of Saitou and Nei (1987), and the cladistic analysis with the PAUP p r o g r a m version 3.1.1. (Swofford, 1993), in which shared indels were treated as synapomorphies. 2. There is considerable agreement between the distance tree (Fig. 3) and the cladogram (Fig. 4) based on the DXTU1 sequences. Although the evolutionary forces acting on the single loci m a y vary, the topologies of the neighbor-joining trees constructed for other loci than DXTU1 were congruent with the DXTU1 tree (see Stiltmann et al., 1995). However, low bootstrap values with respect to certain branching patterns in the neighbor-joining tree (e.g., the position of haplochromines in Lake Malawi, Fig. 3) suggest that longer sequences or more loci are required for a more precise

|

Cyphotilapia frontosa-143 L_ Cyphotilapia frontosa- 144

" ~ L a k e Tanganyika

~J

Cyphotilapia

Melanochromis auratus-1 Tyrranochromis macrostoma-1

~

Lake Malawi Haplochromis

Haplochromis xenognathus-ll4 Haplochromis velifer-602 ~'L-Hapl~176

~

Lake Victoria

~

~ _~ .

43

[ILCyrtocaramoorii-ZR216 L Pseudotropheus zebra- 1

Haplochromis ~

Lake Malawi

I,[

Haplochromis

(~ "-"

Lake Tanganyika genera

[ Neolamprologus brevis-63 ~ f Neolamprologus leleupi-135 ~ Julidochromis regani-60 Neolamprologus tretocephalus- 140 - - Astatoreochromis alluaudi-771 Alcolapia alcalicus-462 Oreochromis niloticus-LS7 Oreochromis urolepis-LSl O

Tylochromis leonensis-PR2 Thorichthys meeki-#55 Cichla-#15

non-endemic species Tilapiines from rivers and Lake Natron West African species ~

Neotropical species

Genetic distance I ! I I ! I I I 0.02 0.03 0.04 0.05 0.06 0.07 0 0.01 FIGURE 3 Neighbor-joining tree (Saitou and Nei, 1987) of the sequences at the DXTU1 locus. Genetic distances were calculated using Kimura's (1980) two-parameter method. The numbers at each node represent percentage recovery of the particular node in 1000 bootstrap replications.

44

HOLGER SCILTMANN AND WERNER E. MAYER

[

Melanochromis auratus-1 Pseudotropheus zebra- 1 Lake

Malawi

Haplochromis

Tyrannochromis macrostoma- 1 Cyrtocara moorii-ZR216 Haplochromis xenognathus-114

Lake Victoria

Haplochromis velifer-602

Haplochromis Haplochromis nigricans-268

Astatoreochromis alluaudi-771

non-endemic species

Cyphotilapia frontosa-143

Lake Tanganyika

Cyphotilapia frontosa-144

Cyphotilapia

Julidochromis regani-60

Lake Tanganyika

Neolamprologus leleupi-135

Julidochromis, Neolamprologus

Neolamprologus tretocephalus-140 Neolamprologus brevis-63 Alcolapia alcalicus-462

Oreochromis niloticus-LS7

Tilapiines

Oreochromis urolepis-LS l O

West African species

Tylochromis leonensis-PR2 Thorichthys meeki#55

~

Neotropicalspecies

Cichla#15 FIGURE 4 Cladogram of 20 representative taxa based on presence or absence of indels and substitutions at the DXTU1 locus. The tree resulted from 500 bootstrap replications using the heuristic search option of the PAUP program version 3.1.1 (Swofford, 1993). The numbers at each node represent percentage recovery of the particular branching order. Cichla No. 15 was used as an outgroup.

determination of species relationships. The trees (Figs. 3 and 4) of the DXTU1 sequences led to the following conclusions. First, the neotropical cichlid species Cichla sp. and Thorichthys meeki form a sister group to the African cichlids. The position of neotropical cichlids indicated by the molecular analysis is consistent with the results of morphological analysis (Cichocki, 1976; Oliver, 1984; Stiassny, 1991), which has revealed a set of derived characters uniting African cichlids (with the exception of Heterochromis) into a monophyletic group. Second, in the phylogram, the west African species Tylochromis leonensis is in a sister-group relationship with the east African species (the tilapiines, represented here by the genus Oreochromis from east African rivers and the Alcolapia alcalicus from Lake Natron; the Lake Tanganyika genera Neolamprologus, Julidochromis, and Cyphotilapia; and the Lake Malawi and Lake Vic-

toria species). In contrast, in the cladogram, Tylochromis appears as a sister group to the tilapiines. Third, the monophyly of the considered east African cichlids (tilapiines, haplochromines, and the Neolamprologus and Cyphotilapia genera of Lake Tanganyika) is indicated both by nucleotide substitution and by indel patterns. This branching order is also supported by mitochondrial DNA data (Meyer, 1993). Fourth, the tilapiines form a monophyletic sister group to the remaining east African Great Lake species and genera (haplochromines, Cyphotilapia, Astatoreochromis, and lamprologines). This result is concordant with morphological analyses (Regan, 1920; Trewavas, 1983) and other molecular studies (Kornfield et al., 1979; McAndrew and Majumdar, 1984; Seyoum, 1989; Sodsuk and McAndrew, 1991; Franck et al., 1994). Fifth, the species Astatoreochromis alluaudi, which is not endemic to Lake Victoria but is also found in other east African lakes and rivers, is a sister group of the

4. Reconstruction of Cichlid Phylogeny included east African lake genera. This result, as well as the sister-group placement of Julidochromis and Neolamprologus with respect to the Lake Malawi and Lake Victoria flocks, is also supported by mitochondrial DNA sequence data (Meyer et al., 1990). Sixth, the sister-group relationship of the Tanganyikan species Cyphotilapia frontosa to Lake Malawi haplochromines suggested by the NJ tree (Fig. 3) supports allozyme data (Kornfield, 1991), according to which Cyphotilapia is more closely related to the haplochromines of Lake Malawi than to those of Lake Tanganyika. This result further supports the polyphyletic structure of the Lake Tanganyika flocks. However, the cladogram (Fig. 4) favors Cyphotilapia in a sister group position to the Lake Malawi and Lake Victoria species on the one hand and the Lake Tanganyika Julidochromis and Neolamprologus genera on the other hand, thus supporting the sister group relationship of Cyphotilapia with other Lake Tanganyika cichlid flocks by using mtDNA control region data (Kocher et al., 1993). Finally, the monophyly of the endemic Lake Victoria haplochromines, as suggested by both trees, is consistent with the results of morphological studies (see Greenwood, 1978; Trewavas, 1983) and mitochondrial DNA analyses (Meyer et al., 1990; Sturmbauer and Meyer, 1992; Meyer, 1993; Moran and Kornfield, 1993). The finding of several indels, which are probably species specific, suggests that it may be possible to elucidate the relationships within species flocks using RAPD markers.

IV. Allele Size Frequencies at Dinucleotide Microsatellite Loci Microsatellites are tandemly repeated DNA sequences with repeat units of I to 6 bp in length and 10 to 100 units per locus (Charlesworth et al., 1994). They have been used for the construction of genetic maps in humans (Hearne et al., 1992; LeBlanc-Straceski et al., 1994) and other species. Variable repeat numbers have also been implicated in disease and cancer susceptibility (Wooster et al., 1994). The rate of mutations generating microsatellite repeat number variation is highest among all nuclear DNA markers; estimations for dinucleotide repeats range from 10 -2 to 10 -4 per generation (Jeffreys et al., 1988; Weber and Wong, 1993). This high mutation rate makes microsatellites a promising tool for population genetic analyses. Consequently, a number of studies have made use of microsatellites for determining relationships among populations of humans (Bowcock et al., 1994; Deka

45

et al., 1995), wolves (Roy et al., 1994), sheep (Buchanan et al., 1994), and toads (Scribner et al., 1994). Variability is believed to occur by the stepwise addition or subtraction of single repeat units after mispairing of the two DNA strands during the replication process (stepwise mutation model, SMM; Levinson and Gutman, 1987; Schl6tterer and Tautz, 1992). It has been shown, however (DiRienzo et al., 1994), that the SMM does not fully explain observed allele frequency distributions within populations: although allelic variation at dinucleotide repeat loci is predominantly due to single step mutations, rare changes of more than one repeat unit may occur as well. Furthermore, unequal crossing-over during meiosis may also contribute to the generation of polymorphism at the microsatellite loci. In cichlids, microsatellites have been used to study the mating behavior of Lake Malawi species (Kellogg et al., 1995). Cichlid fish phylogenies based on microsatellite data have not yet been published. However, the determination of allele size frequency distributions in distinct species from Lake Malawi and Lake Victoria, followed by the calculation of distance matrices, may provide the most promising means for reconstructing their phylogenies. In order to generate allele size data, subgenomic libraries with small insert sizes (200-1000 bp) from P. zebra (Lake Malawi) and Haplochromis nigricans (Lake Victoria) in the A gtl0 phage vector were constructed. The libraries were screened with the CA dinucleotide repeat-specific oligonucleotide (Ca)lsC, and hybridizing clones were isolated and sequenced (Sambrook et al., 1989). The clones contained stretches of CA(GT)repeated DNA with repeat numbers ranging from 8 to 90. Sequence-specific primers flanking the entire repetitive element at the particular locus were then taken for PCR amplification using genomic DNA from Lake Victoria cichlids as templates. One of the primers was labeled with fluorescein at its 5' end. The PCR products obtained from polymorphic loci were separated on a denaturing polyacrylamide gel in an automated sequencing apparatus. Bands were detected as fluorescence intensities of the labeled DNA strands, and their sizes were automatically determined by comparison with a size standard. From several microsatellite loci typed, this chapter shows the example of the DXTUCA15 locus. This locus was amplified from haplochromine genomic DNA with the primers MS16 (5' GCTGTGTAATCCCAAACTCC 3') and MS17 (5' GTATTTAGcTTTCCTCTG TGCT 3') by PCR with one 45-sec cycle at 93~ 15 sec at 55 ~ and 10 min at 72 ~ followed by 35 cycles, each 15 sec at 93~ 15 sec at 55~ and 1 min at 72~ The reaction was completed by a final primer extension

46

HOLGER S~ILTMANN AND WERNER E. MAYER

step for 10 min at 72~ As templates, genomic DNA samples from the Lake Victoria (and minor adjacent lakes like Lake Nabugabo, Kayugi, and Kayania) Haplochromis species H. beadlei (number of individuals, n = 12), H. cinctus (n = 19), H. laparogramma (n = 12),

H. nigricans (n = 15), H. nyererei (n = 40), H. plagiodon (n = 19), H. pyrrhocephalus (n = 43), H. sauvagei (n = 17), H. velifer (n = 81), and H. xenognathus (n = 29) were used. Individuals from each species were captured at two to six different locations in the wild. In the PCR, the primers amplified DNA fragments with sizes ranging from 75 to 93 bp. Size differences were due to variation of the number of CA repeat units, as determined by subcloning and sequencing random clones (data not shown). Although data are still preliminary, some interesting results have already been obtained from the specific amplification of cichlid microsatellite loci. First, in most of the amplifications, one or two products were visible (corresponding to homo- or heterozygosity of the individual at the particular locus). However, additional artifactual bands often appeared

Haplochromis beadlei

Haplochromislaparograrnrna

n=12

due to amplification at other loci. These by-products sometimes interfered with the precise determination of microsatellite size. Second, the size determination was also hampered by the occurrence of so-called "shadow bands" flanking the highest peak in a cluster of products. In the case of dinucleotide repeats, shadow bands usually differ by 2 bp in size. This observation suggests that they may have been generated by the insertion or deletion of repeat units during PCR amplification (Litt et al., 1993). Assuming that a similar mechanism generated shadow bands in different reactions, the largest peak area within a peak cluster for the determination of the allele size was used. Third, inhomogeneities within the polyacrylamide gel may lead to incorrect measurement of product sizes. In order to assess this possibility, the allele sizes at certain loci determined by gel electrophoresis were compared with those obtained by subcloning and sequencing of the same PCR products. From these data it was concluded that the error was no larger than one repeat unit. The summary of the allele size determination for each species is shown in Fig. 5. Allele frequencies (y

Haplochromis cinctus

n=12

Haplochromisnigricans

n=19

HapIochromis nyererei

n=15

n=40

0.4

g O.4 0.3

--e 0.3

0.3

0.2

0.2

0.2

0.3

0.2

o.111 I

0.1 o.,

8

9 10 11 12 13 14 15 16 17 repeat units

O.0

~

8

Hsplochromisplagiodon

~a 0.3

O 0

8

Hsplochromispyrrhocephalus

n=19

o>, 0.4 c

9 10 11 12 13 14 15 16 17 repeat units

0"0

9 10 11 12 13 14 15 1G 17 repeat units

8

Haplochromissauvagei

n=43

=-~. 04

o.,

-~ 0.3

.

.

.

.

.

.

.

.

O0

.

9 10 11 12 13 14 15 16 17 repeat units

8

Haplochromisvelifer

n=17

=~ o s]

.

0.1

Haplochromisxenognathus

n=81

n=29

~

0.41

Imi 9 10 11 12 13 14 15 16 17 repeat units

0.6

~0.5"

_== 0.4"

0.3 0.2 0.2 0.1

0.1

8

9 10 11 12 13 14 15 16 17 repeat units

0.0

8

9 10 11 12 13 14 15 16 17 repeat units

0.0

8

9 10 11 12 13 14 15 16 17 repeat units

8

9 10 11 12 13 14 15 16 17 repeat units

8

9 10 11 12 13 14 15 16 17 repeat units

FIGURE 5 Allele frequency distributions for 10 Haplochromis species from the Lakes Victoria, Kayugi, Kayania, and Nabugabo at the microsatellite locus DXTUCA15. Frequencies (y axis) are plotted against the number of repeat units (x axis) found in the fragment analysis (see text for details). The number of individuals included in each sample is given by n.

4. Reconstructionof Cichlid Phylogeny axis) are tabulated against the number of repeat units (x axis) calculated from the PCR product size by subtraction of the number of unique nucleotides in the fragment. Differences in frequency distributions between species are indicated by shape variations between the individual plots. Frequency data were used as the input for the microsat 1.4 computer program (written by Eric Minch; Goldstein et al., 1995), which calculates various distance measurements on the basis of allele frequencies (e.g., average squared difference in repeat numbers, Nei's identity; proportion of shared alleles). The basic assumption of the program is the validity of the stepwise mutation model (see also Valdes et al., 1993; Slatkin, 1995). It is important to note, however, that the algorithm is not dependent on the distribution of allele sizes within the species. Nei's identity method (Nei, 1972) was used for the calculation of a distance matrix (Fig. 6) which was then applied for the construction of a phylogenetic tree by the PHYLIP software package (Felsenstein, 1986-1993). The tree is shown in Fig. 7. It can be divided into two major branches, one of which is constituted by the Haplochro-

mis nyererei, H. nigricans, H. plagiodon, H. pyrrhocephalus, and H. laparogramma species, whereas H. beadlei, H. cinctus, H. sauvagei, and H. xenognathus appear on the second major branch. Haplochromis velifer is located at an intermediate position. An obstacle for a test of the reconstruction of the true phylogeny based on microsatellite allele frequencies in the closely related cichlid species from Lake Victoria is the low abundance of synapomorphic morphological characters. Most of the available studies have focused on the feeding habits, jaw morphology, and dentition (Greenwood, 1974, 1979, 1980; Witte and van Oijen, 1990). On the basis of these data, the species included in the phylogenetic tree (Fig. 7) can be subdivided into two major trophic groups (Witte and van Oijen, 1990), one of which is the planktivorous/algaeeating group Haplochromis cinctus (phytoplankton), H. laparogramma, H. pyrrhocephalus, H. nyererei (zoo-

i0

Habe Haci Hala Hani Hany Hapl Hapy Hasa Havl Haxe

-0.086 -0.030 -0.016 0.030 -0.050 0.088 -0.095 -0.008 0.072

0.051 0.088 0.158 0.024 0.117 -0.015 0.124 0.234

-0.078 -0.013 -0.079 -0.023 0.017 -0.018 0.248

-0.046 -0.078 0.040 0.009 -0.034 0.152

47

plankton), and H. nigricans (epilithic algae grazer). The other trophic group consists of the oral shell/mollusc crashers H. plagiodon, H. sauvagei, and H. xenognathus as well as H. beadlei, which is considered to be a sister species of Haplochromis plagiodon (Greenwood, 1980). In the phylogenetic tree generated by microsatellite data, this grouping is roughly reflected in the major branching pattern. The exceptions to this are H. plagiodon and cinctus, which are unexpectedly located on the opposite branches. Thus, data suggest that microsatellite data can be used to make a rough subdivision of some Lake Victoria cichlid species which corresponds to their feeding habits. Whether the congruence between phylogenetic position and trophic grouping is a rule for haplochromines in general remains to be examined. Certainly, multiple microsatellite loci will have to be analyzed in order to generate more reliable and independent data sets.

V. Critical Evaluation Using RAPD and Microsatellite Allele Frequencies for the Reconstruction of Cichlid Fish Phylogeny The recent adaptive radiation of cichlid fishes in Lake Malawi and Lake Victoria has produced closely related species flocks. The reconstruction of their phylogeny requires new methods capable of resolving genetic distances generated within short time spans. Because the available markers (mtDNA, allozymes, morphology) have achieved the goal of clarifying the Lake Victoria and Lake Malawi cichlid phylogeny only marginally, two different approaches that are both based on nuclear DNA markers were studied. The goal was to test the validity of current hypotheses on cichlid fish relationships. The RAPD-based sequence comparison requires relatively few samples from the species under consideration, and data collection and analysis are compara-

-0.029 0.157 0.023 -0.006 0.083

0.036 -0.024 -0.022 0.141

0.168 0.141 0.547

-0.001 0.033

0.i01

FIGURE 6 Distance matrix obtained with microsatellite allele frequency data for the 10 Haplochromis species shown in Fig. 5. Nei's identity method (Nei, 1972) was used for the generation of the matrix with the program microsat 1.4 (Goldstein et al., 1995).

48

HOLGER SfflLTMANN AND WERNER E. MAYER

Haplochromis laparogramma Haplochromis pyrrhocephalus Haplochromis plagiodon Haplochromis nigricans Haplochromis nyererei Haplochromis velifer I Haplochromis beadlei [ Haplochromis cinctus [ Haplochromis sauvagei

I I

I

Haplochromisxenognathus I

0 0.05 0.1 Relative length

I

0.15

FIGURE 7 Neighbor-joining tree (Saitou and Nei, 1987) constructed using the distance matrix from Fig. 6 as input data for the PHYLIP distance algorithm (Felsenstein, 1986 - 1993 ).

tively easy to carry out. The chance of finding interspecies variation in the set of random sequences is high. A prerequisite of the method as described here, however, is complete lineage sorting of the particular RAPD marker. To distinguish young species, therefore, frequency data are necessary. Subcloning and sequencing can be performed by established methods, but are time-consuming. Sequence data provide two types of characters, substitutions and indels, both of which can be used in separate phylogenetic analyses. The results obtained thus far agree well with previously reported molecular data and support the use of this method for molecular evolutionary studies of cichlid fishes. Yet, because some conflicting hypotheses (e.g., the position of Cyphotilapia with respect to the other east African Lake cichlids) could not be clearly resolved, the number of RAPD markers has to be increased in order to obtain phylogenetic trees with higher bootstrap support values. The likelihood of detecting synapomorphic characters between related species increases with the time that has passed since species separation. In this respect, the evolutionarily young (less than 2 MY) species flocks from Lake Malawi and Lake Vic-

toria, which are the interesting ones regarding the speciation process, will require many more nuclear DNA loci and sequencing. For the Lake Victoria haplochromines, the feasibility of obtaining such markers has been shown with the RAPD approach. The microsatellite approach makes use of the high mutation rate of short tandemly repeated sequences. Therefore, this method is more suitable for the determination of relationships between closely related species like the haplochromines of Lake Malawi and Lake Victoria. Once the polymorphic loci have been identified and the variation has been shown to be due to the repeat numbers, allele typing can be performed much quicker as compared to sequencing approaches. However, because the method employs frequency data, the requirement for large sample sizes per species may be a major obstacle to generating reliable data sets. It has been shown for di- to hexanucleotide microsatellite loci that the variance of the stepwise-weighted genetic distance does not change significantly when more than 25 individuals per species are used (Shriver et al., 1995). This number thus defines the preferred sample size. Two limiting factors hinder the use of microsatellite

4. Reconstruction of Cichlid Phylogeny

allele size typing: First, at oligomorphic loci the allele frequency distributions are similar in all species because the time for generation of variability has been too short or polymorphism has predated the speciation process. Second, in the case of convergence the allele frequency distributions of the species are similar because the process of generation of variability has reached an equilibrium state in all the species. In addition, to use the microsatellite approach effectively, several theoretical considerations have to be resolved: First, there is still uncertainty concerning the mechanism generating the variability (Schl6tterer and Tautz, 1992; DiRienzo et al., 1994). Thus, the available models might have to be refined once the mechanism of generation of repeat number variation has been elucidated. Second, the possibility of selection acting on microsatellite repeat number cannot be excluded and may lead to inconsistent results when loci are compared. Third, ignorance of interspecific hybridization events introduces a high degree of uncertainty concerning the topology of the phylogenetic tree. Fourth, errors due to inadequate sample size and possible kinships between cichlid fish taxa are difficult to evaluate and may bias the observed genetic distances between species. In general, RAPD and the microsatellite approach are both able to detect polymorphism between closely related taxonomic groups. With respect to cichlid phylogeny, RAPD can be primarily applied to genera under comparison. In contrast, the microsatellite method should be applied to the species and population level. Despite the unresolved problems with microsatellites, it is the authors' opinion that they are the best tool so far among all the available methods for studying cichlid phylogeny. Nonetheless, the search for additional polymorphic nuclear DNA markers should be continued because these will provide excellent markers for testing the validity of phylogenetic hypotheses.

Acknowledgments We thank Jan Klein for critical reading of the manuscript and helpful suggestions, Herbert Tichy for discussions on the cichlid species and providing the samples, Eric Minch from the Department of Genetics, Stanford University, for the microsat 1.4 program and help in getting it started, and Lynne Yakes for editorial assistance.

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evolutionary trees with polymorphic microsatellites. Nature 368: 455 -457. Bowditch, B. M., Albright, D. G., Williams, J. G. K., and Braun, M. J. 1994. Use of randomly amplified polymorphic DNA markers in comparative genome studies. Meth. Enzymol. 224:294-309. Bowers, N., Stauffer, J. R., and Kocher, T. D. 1994. Intra- and interspecific mitochondrial DNA sequence variation within two species of rock-dwelling cichlids (Teleostei: Cichlidae) from Lake Malawi, Africa. Mol. Phylogenet. Evol. 3(1):75-82. Brown, W.M., George, M., Jr., and Wilson, A.C. 1979. Rapid evolution of animal mitochondrial DNA. Proc. Natl. Acad. Sci. USA 76: 1967-1971. Buchanan, F. C., Adams, L. J., Littlejohn, R. P., Maddox, J. F., and Crawford, A. M. 1994. Determination of evolutionary relationships among sheep breeds using microsatellites. Genomics 22: 397-403. Charlesworth, B., Sniegowski, P., and Stephan, W. 1994. The evolutionary dynamics of repetitive DNA in eukaryotes. Nature 371: 215-220. Cichocki, F. P. 1976. "Cladistic History of Cichlid Fishes and Reproductive Strategies of the American Genera Acarichthys, Biotodoma and Geophagus," Vol. 1. Ph.D. thesis, University of Michigan, Ann Arbor, MI. Cohen, A. S., Soreghan, M. J., and Scholz, C A. 1993. Estimating the age of formation of lakes: An example from Lake Tanganyika, East African rift system. Geology 21:511-514. Deka, R., Jin, L., Shriver, M. D., Yu, L. M., Decroo, S., Hundrieser, J., Bunker, C. H., Ferrell, R. E., and Chakraborty, R. 1995. Population genetics of dinucleotide (dC-dA)n 9(dG-dT)n polymorphisms in world populations. Am. J. Hum. Genet. 56:461-474. Devereux, J., and Haeberli, P. 1991. "Genetics Computer Group, Program manual for the GCG package, Version 7," April 1991, Madison, WI. DiRienzo, A., Peterson, A. C., Garza, J. C., Valdes, A. M., Slatkin, M., and Freimer, N. B. 1994. Mutational processes of simple-sequence repeat loci in human populations. Proc. Natl. Acad. Sci. USA 91: 3166-3170. Ellsworth, D. L., Rittenhouse, K. D., and Honeycutt, R. L. 1993. Artifactual variation in randomly amplified polymorphic DNA banding patterns. Biotechniques 14:214-217. Felsenstein, J. 1986-1993. "PHYLIP: Phylogenetic Inference Package Version 3.5c." University of Washington. Franck, J. P. C., Kornfield, I., and Wright, J. M. 1994. The utility of SATA satellite DNA sequences for inferring phylogenetic relationships among the three major genera of tilapiine cichlid fishes. Mol. Phylogenet. Evol. 3:10-16. Franck, J. P. C., Wright, J. M., and McAndrew, B. J. 1992. Genetic variability in a family of satellite DNAs from tilapia (Pisces: Cichlidae). Genome 35: 719-725. Fryer, G., and Iles, T. D. 1972. "The Cichlid Fishes of the Great Lakes of Africa." Oliver and Boyd, Edinburgh. Gaemers, P. A. M. 1984. Taxonomic position of the Cichlidae as demonstrated by the morphology of their otoliths. Neth. J. Zool. 34: 566-595. Goldstein, D. B., Linares, A. R., Cavalli-Sforza, L. L., and Feldman, M. W. 1995. An evaluation of genetic distances for use with microsatellite loci. Genetics 139: 463-471. Greenwood, P. H. 1974. Cichlid fishes of Lake Victoria, East Africa: The biology and evolution of a species flock. Bull. Br. Mus. Nat. Hist. (Zool.) Suppl. 6:1-134. Greenwood, P. H. 1978. A review of the pharyngeal apophysis and its significance in the classification of African cichlid fishes. Bull. Br. Mus. Nat. Hist. (Zool.) 33:297-323. Greenwood, P. H. 1979. Towards a phyletic classification of the 'genus' Haplochromis (Pisces, Cichlidae) and related taxa. Bull. Br. Mus. Nat. Hist. (Zool.) 35:265-322.

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CHAPTER

5 Biogeographic Analysis of Pacific Trout (Oncorhynchus mykiss) in California and Mexico Based on Mitochondrial DNA and Nuclear Microsatellites JENNIFER L. NIELSEN and MONIQUE C. FOUNTAIN USDA Forest Service Pacific Southwest Research Station and Hopkins Marine Station Department of Biology Stanford University Pacific Grove, California 93950

rainbow trout). Genetic and morphological characters reported in many studies have confirmed the Pacific trout as true members of Oncorhynchus (PJehnke, 1968; Utter et al., 1973; Kendall and Behnke, 1984; Thomas et al., 1986; Stearley and Smith, 1993; Utter and Allendorf, 1994; see also Phillips and Oakley, 1997). The popular terms "salmon" and "trout" are now generally thought to refer to a flexibility in life history pattern .that has evolved independently among separate monophyletic groups, the Pacific Oncorhynchus [i.e., anadromous steelhead and freshwater rainbow trout O. mykiss; anadromous sockeye salmon (O nerka) and resident kokanee; sea-run and resident cutthroat trout O. clarki], and the Atlantic Salmo (i.e., anadromous and landlocked Atlantic salmon, S. salar; anadromous and resident brown trout, S. trutta). Similar trade-offs in life history traits are also found within Salvelinus (i.e., lacustrine and anadromous char, S. alpinus), suggesting that this flexibility in life history may

I. Introduction At the turn of the century, the Pacific basin trout were traditionally classified as members of the Atlantic lineage Salmo, based on analyses of morphology, life history characteristics, and iteroparity in the Pacific trout that were lacking in other Pacific salmon (Oncorhynchus spp.) The current reclassification of Pacific steelhead, cutthroat, and rainbow trout into the genus Oncorhynchus was based on new morphological characters and associations drawn from molecular genetic data (Smith and Stearley, 1989). As early as 1914, Regan had suggested that the Pacific trout were more closely related to the Pacific salmon (Oncorhynchus) than to the European Salmo. Based on osteological characters, Vladykov (1963) recognized that Pacific basin trout were separable from Atlantic basin Salmo, and Behnke (1965) first reported the near morphological identity of O. mykiss (Asiatic trout) and S. gairdnerii (North American

MOLECULAR SYSTEMATICS OF FISHES

JONATHAN M. WRIGHT Marine Gene Probe Laboratory Department of Biology Dalhousie University Halifax, Nova Scotia Canada B3H 4J1

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Copyright 9 1997 by Academic Press. All rights of reproduction in any form reserved.

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JENNIFER L. NIELSEN et al.

be a characteristic with roots ancestral to the split between Salmo and Oncorhynchus (Stearley and Smith, 1993; Foote et al., 1994). Genetic studies have revealed cryptic population structure due to behavior or life history variation that was not obvious from other types of analyses (Bowen et al., 1993; Bowcock et al., 1994). The reclassification of all Pacific anadromous steelhead and resident rainbow trout as O. mykiss has, therefore, led to significant controversy over the taxonomic status and genetic identity of the many subgroups of trout found throughout western North America (Behnke, 1992). Specific interest has evolved around the position of the California golden trout, the McCloud rainbow trout, Baja rainbow trout, the Eagle Lake rainbow trout, and the interior "redband" trout in the lineage of O. mykiss. The first genetic data used to support biogeographic separation of western trout into two major subgroups came from a study of allozymes via electrophoresis analyses conducted by Allendorf (1975). This study documented the geographical separation of western trout around the Cascade Crest (Pacific Crest), dividing O. mykiss into "inland" and "coastal" populations. Allendorf (1975) showed that allozyme allelic frequency differences separated inland and coastal groups of O. mykiss longitudinally over a broad geographic area throughout the western United States. Subsequent molecular studies conducted on the North American coastal distributions of O. mykiss supported genetic similarities between both resident (rainbow trout) and anadromous (steelhead) forms of coastal Pacific trout within geographically proximate locations (Utter et al., 1973; Okazaki, 1984; Parkinson, 1984; Currens et al., 1990; Gall et al., 1990; Reisenbichler et al., 1992). DNA analyses of the intraspecific genetic diversity in coastal O. mykiss confirmed the genetic similarity of resident and anadromous life history forms of trout from proximate geographic areas (Wilson et al., 1985; Thomas and Beckenbach, 1989)and have shown significant biogeographic structure at the southern extent of the range (Nielsen et al., 1994b). The latter study used mitochondrial DNA (mtDNA) and nuclear microsatellites to demonstrate a high degree of population differentiation and levels of genetic diversity that were unprecedented for this species. This unique level of genetic diversity found in southern steelhead has been confirmed by allozyme analyses of California coastal stocks by the National Marine Fisheries Service for their scientific status review resulting from a petition for Federal listing of the Pacific steelhead under the Endangered Species Act (Dr. R. Waples, personal communications, National Marine Fisheries Service, Seattle, WA).

DNA studies of Pacific salmonids initially concentrated on mitochondrial DNA markers due to the relatively rapid rate of evolution in this maternally inherited molecule, the ease of extraction and amplification of mtDNA, and a significant literature on the theory and application of mtDNA sequence analyses available to researchers by the end of the 1980s (Avise et al., 1987, and literature therein). Controversy has evolved over the degree and level of phylogenetic resolution available with mtDNA markers due to demonstrated variability in mutation rates for individual parts of the molecule among different taxa and possible saturation of base-point mutations in highly polymorphic regions (Avise et al., 1987, 1994b; Hillis, 1995). Despite such arguments, this molecule has played an important role in high-resolution analyses of population structure in closely related vertebrate groups (Moritz et al., 1987; Stoneking et al., 1991; Avise, 1994 and references therein; Avise et al., 1994a; Moritz et al., 1995). The development of simple protocols for the detection and amplification of short repetitive DNA sequences (i.e., microsatellites; Miklos, 1985; Tautz, 1989; Weber and May, 1989; Moore et al., 1991) provides access to new molecular tools derived from the nuclear genome with unusually high levels of intraspecific polymorphism. Short repetitive DNAs are common throughout the eukaryotic genome, have exceptionally high mutation rates, and generally provide large numbers of alleles useful for the reconstruction of closely related phylogenetic groups (Kelly et al., 1991; Henderson and Petes, 1992; Queller et al., 1993; Estoup et al., 1993; Bowcock et al., 1994). Polymerase chain reaction (PCR) amplification of microsatellites has provided an alternative molecular approach for the analysis of groups sharing recent evolutionary divergence (Burke et al., 1989; Bruford and Wayne, 1993; Queller et al., 1993; Ellegren, 1995). Nuclear microsatellite loci have, in general, provided a degree of analysis not previously available at the intraspecific level from mtDNA or allozymes (Bowcock et al., 1994; Goldstein et al., 1995; FitzSimmons et al., 1995; Nielsen, 1996). The function and biochemical mechanisms underlying mutation of simple sequence repeat loci, however, remain unknown and controversial (Long and David, 1980; Di Rienzo et al., 1994). One theoretical mechanism of mutation has been proposed for the microsatellite class of tandem repeats: a stepwise mutation process in which an allele mutates up or down by a small number of nucleotide repeat units (Schlotterer and Tautz, 1992). Variations on the stepwise mutation model underlie two recently developed genetic distance measures designed specifically for microsatellite loci (Goldstein et al., 1995; Slatkin, 1995). These dis-

5. mtDNA and Nuclear Microsatellites in Trout

tance measures are closely related in their analytical techniques, but are based on different conceptual interpretations of the stepwise mechanisms leading to repeat polymorphisms. Goldstein et al. (1995) used a strict (single-step) stepwise mutation model to analyze variation in the number of repeats found within a simple DNA sequence. Slatkin (1995), however, developed a two-phase mutation model introduced by Di Rienzo et al. (1994), which allows replication or deletion of more than one repeat unit as a single mutation event. Under the two-phase model, single-step mutations (involving only one repeat unit) are thought to be the most common elements of change, but events involving larger groups of repeat units, inserted or deleted as a single mutational element, are possible (Di Rienzo et al., 1994). Despite the fact that mutational mechanisms in repetitive DNA remain an open question, microsatellite markers have proven useful in many vertebrate population studies (Bruford and Wayne, 1993; Wright, 1993; Bowcock et al., 1994; Morin et al., 1994a,b; Nielsen et al., 1994b; Wright and Bentzen, 1994; Spencer et al., 1995; Gerloff et al., 1995). To date, however, no empirical studies have looked at the implications of the different analytical approaches to microsatellite distance data. Phylogenies based on single genes or short sequence loci, especially among closely related taxa, can be discordant with organismal phylogenies (Weller et al., 1994). Discrepancies between an individual gene tree and the true phylogeny of an organism can arise from lineage-sorting processes or allelic introgression between closely related groups (Neigel and Avise, 1986; Pamilo and Nei, 1988). The degree of phylogenetic congruence available among independent genetic markers has become an important issue in the interpretation of gene trees in relationship to organismal phylogenies (Birky et al., 1989; Bernatchez and Danzmann, 1993; Avise et al., 1994b; Bernatchez, 1995; Moritz et al., 1995). Phylogenetic results derived from several independent DNA regions provide a more robust perspective on the genetic history of an individual group or population than any one gene or nucleotide sequence alone (Avise, 1994; Cummings et al., 1995). It is important, however, that the chosen gene or sequence data used to test congruence among phylogenetic information are appropriately matched to the level or degree of phylogenetic divergence in question (Graybeal 1994). This chapter compares genetic diversity for mtDNA and three independent, highly polymorphic nuclear microsatellite markers in putative wild trout and steelhead populations from California and Mexico. DNA data on trout populations from interior as well as coastal locations are presented, and the intraspecific biogeographic resolution available for O. mykiss in

55

California and Mexico using both mtDNA and nuclear markers is addressed. Inferences available from these molecular data concerning the status of various populations of trout and steelhead are discussed.

II. Material and Methods A. Sampling Protocol

Coastal steelhead and interior trout (O. mykiss) were sampled noninvasively by taking fin clips (2-mm 2) from 354 live fish captured within riverine habitats in California and Mexico (Fig. 1). Tissues were sent as frozen or dried samples to the authors' laboratory from 1990 to 1995 and stored at -70~ until DNA extraction and amplifications were performed. O. mykiss were sampled from stream locations where wild stocks of steelhead and trout have been reported to have received a minimum of hatchery introductions since the mid-1930s [California Department of Fish and Game (CDFG) unpublished records and personal communications; Swift et al., 1993; Gall, 1995; Titus et al., in press]. Streams and rivers included in these analyses were divided into six general geographic localities to aid in the graphic depiction of data (see Appendix I). The northern and southern regions of California were separated at the San Francisco Bay and the interior and coastal populations were separated by the western boundary of the Klamath mountains and the great valley region in the north, the Sierra Nevada range throughout central California, and the transverse range in the south. All coastal steelhead and trout in California are currently classified as O. mykiss

Steelhead Eel River

/

Steelhead northcoast Eagle Lake

/.-~,.,~on,,~,~,,.,,,~/

rainbow~~~ ~~

Upper SacramentoRiver rainbow Steelhead RussianRiver

McCIoudRiver rainbow GoldenTroutCreek

Steelhead SF Bay

SF KernRivergoldentrout

Little Kerngoldentrout

Kern River rainbow

Central coast steelhead

Southern steelheadBig Sur Southern steelheadSanta YnezR.

/

Southern steelhead Malib~Cr.eek

Bajatrout

(,(~~___~tL./Rio Yaquitrout /.../~A~Mexico ,~,,,,

FIGURE 1 General location of DNA-sampling sites for steelhead and trout in California and Mexicoused in this study.

56

JENNIFERL. NIELSENet al.

irideus (after Behnke, 1992). The north interior collection of California trout included two putative subspecies of trout, the Eagle Lake trout (O. mykiss aquilarum) and the McCloud River redband trout (O. mykiss stonei), but probably contained a diverse mixture of populations with redband and coastal rainbow ancestry (Behnke, 1992). The south interior California trout collection was made up of three reported subspecies: the Kern River rainbow trout (O. mykiss gilberti), Little Kern River rainbow trout (O. mykiss whitei), and California golden trout from the South Fork Kern River (O. mykiss aquabonita). Mexican trout from Baja California Norte (O. mykiss nelsoni) were collected by G. Ruiz-Campos (Facultad de Ciencias, Universidad Aut6noma de Baja California). Fin clips taken from trout from the Rio Yaqui basin (an undefined subspecies of O. mykiss, R. R. Miller, personal communications) were sent to the authors' laboratory by B. L. Jensen (U. S. Fish and Wildlife Service, Dexter National Fish Hatchery and Technology Center, Dexter, NM) and by Jose Campoy Favela (Centro Ecologico de Sonora, Hermosillo, Sonora, Mexico). These samples were collected from a headwaters tributary of the Rio La Cueva, a tributary of the Rio Bavispe, which is a tributary of the Rio Yaqui. B. M i t o c h o n d r i a l DNA Total genomic DNA was extracted from fin clips using Chelex-100 resin (BioRad) following the methods of Nielsen et al. (1994a). Primers used in this study (S-phe and P2) were developed by W. K. Thomas (University of Missouri, Kansas City) in the late Allan Wilson's laboratory using the methods given in Kocher et al. (1989). These primers are known to amplify a highly variable segment of the mtDNA control region in salmonids. These primers permit amplification and sequencing of a segment containing 188 bp of the O. mykiss mtDNA control region and 5 bp of the adjacent phenyalanine tRNA gene. Primer sequences, amplification and sequencing protocols, and sequence of the entire region amplified by these primers in this species can be found in Nielsen et al. (1994a).

C. Microsatellites Three microsatellite loci [Omy77, Morris et al. (1996); Omy207, M. O'Connell, Marine Gene Probe Laboratory (MGPL), Dalhousie University, personal communications; and Ssa289, McConnell et al. (1995)] were chosen for this study based on their level of polymorphism in O. mykiss. Omy77 and Omy207 were developed specifically for O. mykiss at MGPL, Dalhousie

University. Ssa289 was developed by MGPL for Atlantic salmon. The sequence for primers amplifying these microsatellite loci appears in the respective literature or is available by request from MGPL. For each locus, primer B was labeled according to protocols given in Nielsen et al. (1994b). The methods of Nielsen et al. (1994b) were used except that each PCR reaction contained 3.75 ~1 doubledistilled H20, 0.625 #1 10• PCR buffer (670 ~1 1 M Tris, 67 #1 1 M MgCI2, 83 ~1 2 M AmSo4, 7/.~1 14 M ]3-mercaptoethanol, and 173 Izl double-distilled H20), 0.625 #1 10 mM dDNTPs, 0.625 #1 10/~M primer A, 0.32 ~1 1 #M primer B, 0.32/~1 labeled B primer, and 0.03 ~1 (0.15 units) Taq polymerase. PCR conditions were 30 cycles of 94 ~ for 40 sec, 50~ for 1 min, and 72~ for 2 min. Microsatellites were run out on a 6% polyacrylamide gel. Prior to loading the gel, 5/~1 of loading buffer [94% formamide, 4% 0.5 EDTA, 0.025% (w/v) both bromphenol blue and xylene cyanol FF) was added to each sample. The size of each microsatellite allele was determined by reference to the M13mp18 sequence, known DNA samples that were rerun on each gel, and a doublestranded reference marker showing the common alleles available for each microsatellite locus. Only unambiguous bands were scored, and in the case of multiple (shadow) bands, the darkest band was scored as the allele. The appearance of stutter bands which overlap between alleles was resolved by comparing the intensity and number of stutter bands for each individual at each locus (O'Reilly and Wright, 1995). To ensure consistency in both the PCR reactions and the scoring of microsatellites, 3.5% of all samples were rerun separately on different gels and scored independently by two people.

D. A n a l y t i c a l A p p r o a c h A pairwise distance matrix was constructed for sequences from the mtDNA control region segment amplified by S-Phe and P2, based on the two-parameter model of Kimura (1980). Phylogenetic analysis was performed on mtDNA data using the unrooted neighbor-joining (NJ) tree procedure from PHYLIP (Felsenstein, 1991) with 1000 bootstrap replicates (Felsenstein, 1985) to assess reproducibility of the NJ mtDNAbranching pattern. Previous studies have documented the biogeographic concordance associated with the mtDNA haplotypes in coastal steelhead (Nielsen et al., 1994b; Neeley, 1995). To test for differences in biogeographic distribution of genotypes using nuclear microsatellites, microsatellite data were pooled for individual trout by

5. mtDNA and Nuclear Microsatellites in Trout

known mtDNA haplotype and capture location, where the parenthetical mtDNA haplotype designation refers to the most common haplotype found in that particular geographic population (Appendix II). These geographic-haplotype groups then served as sample units for microsatellite genetic distance analyses and tree development for comparison with the mtDNA NJ tree, allowing the authors to discuss results available from microsatellite data in individual populations with documented mtDNA phylogeographic structures. The trees depicted in these analyses were not intended to reflect historic evolutionary associations among trout populations, but rather to test for genetic congruence in biogeographic data drawn from two independent molecular markers with potentially different evolutionary histories among these populations. Observed and expected values of heterozygotes were calculated for microsatellite data, and a test for Hardy-Weinberg (HW) equilibrium was performed for all populations combined according to the Fisher method described by Louis and Dempster (1987), which provided an estimate of the probability of rejecting the null hypothesis, i.e., HW equilibrium. A pairwise genetic distance matrix was calculated for allelic diversity using both the Slatkin (1995) and the Goldstein et al. (1995) methods for the three microsatellite loci combined. For the Goldstein et al. (1995) distance analyses, the authors used the program available from Dr. E. Minch, Department of Genetics, Stanford University. Rst analyses were performed using a Pascal program developed by M. C. F. that implemented Slatkin's stepwise model for distance analyses. Both distance measures assume a linear expectation of the average-squared distance for each locus (assuming no correlation between mutation rate and repeat score) and use the arithmetic average of mutation rates across loci. Statistics in both methods are equivalent to a general analysis of variance. Both methods compute an average sum of squares of the differences in allelic size within each population [Sw in Slatkin (1995); Do in Goldstein et al. (1995)] and the average squared difference between all possible pairs of populations (SB and D1 respectively) to obtain an estimate of variance in allele size in the total population. The basic difference between the two methods involves how they interpret the parameters of the mutation process. Slatkin's Rst [developed under the assumptions of the infinite allele model, Slatkin (1991)] used a ratio of combinations of the mean squared distance which cancels out all parameters of the mutation process [see formula 12 in Slatkin (1995)]. Goldstein et al. (1995) maintain an estimate of the mutation process under the expectation of a strict, single-step (one

57

repeat unit) shift for each mutation event. Distance data from both methods were used to generate a consensus neighbor-joining tree (PHYLIP, Felsenstein, 1991). One thousand bootstrap replicate trees were generated to assess the reproducibility of branching patterns found in each consensus tree. Analysis of variance (ANOVA) and factor analysis using principal components (PCA) were used to describe biogeographic associations between genotype (mtDNA or microsatellite allelic diversity) and sample location (longitude and latitude). Each factor represented a linear combination of actual mtDNA haplotype or microsatellite allelic frequencies (weighted for sample size) over all genotypes. Factor analyses were based on the variance-covariance matrix for all sampled populations such that the range of components was associated with the proportion of total variance over all locations. The first component was, therefore, associated with the greatest portion of the total variance for all genotypes over all locations, the second component had the second greatest proportion, etc. Least-squares multiple regression analyses were then used to regress the first principal component on latitude or longitude by genotype to graphically depict the correlation between sampling locality and genotype distributions.

III. Results A. Mitochondrial

DNA

Three previously unpublished mtDNA controlregion haplotypes, containing novel single base mutations, were found in this survey of trout populations from California and Mexico (MYS15, MYS16, and MYS18; Table I). MYS15 was found only in golden trout from Golden Trout Creek in the Kern River basin and in Taylor Creek, a tributary to the South Fork Kern River. MYS16 was found in two tributaries of the South Fork Kern River (Fay Creek, Manter Creek), in Ramshaw Meadows on the South Fork Kern River, in Golden Trout Creek, and in Eagle Lake rainbow trout. MYS18 was unique to the trout of the Rio Yaqui basin of northwestern Mexico. Twenty-seven trout from the San Pedro M~rtir basin in Baja California were monomorphic for mtDNA haplotype MYS1. All other mtDNA haplotypes found in freshwater trout samples taken from interior California rivers and streams carried identical control-region haplotypes to those previously reported in coastal anadromous populations (Nielsen et al., 1994b). The frequency distribution of the

58

JENNIFER L. NIELSEN et al.

TABLE I Mitochondrial Control Region Variable Sites and Nucleotide Changes Found in California Steelhead and Trout (Oncorhynchus mykiss) in 1990-1995 and in Two Populations of Mexican Trout from Baja California and the Rio Yaqui Base pair no.a mtDNA type

No.

1021

MYS1 MYS2 MYS3 MYS5 MYS6 MYS8 MYS12 MYS13 MYS15 MYS16 MYS18

99 17 108 20 7 25 7 8 7 45 11

T C T T T T T T T T T

1050

1086

1103

1104

1106

1109

1147

1149

T T T C C C C C T T T

A A A G G A A G A A A

G G G G G G G G A G G

A A A C C C C C A A A

G A A G G G G G A G G

G G G A A A G G G A G

C C C C C C C C C T C

T T T T C T T T T T C

"Base pair numbers follow those published by Digby et al. (1992). The number of fish sequenced for this study is given for each mtDNA type. Mitochondrial haplotypes MYS1-14 are equivalent to haplotypes ST1-14 previously reported in Nielsen et al. (1994b). ST4, ST7, ST9, ST10, ST11, and ST14 were represented by less than five confirmed samples each and were, therefore, not included in these analyses.

s o u t h e r n extent of the range, i.e., s o u t h of Point Conc e p t i o n (MYS5, MYS6, MYS8, a n d MYS13), a n d one n o r t h e r n California h a p l o t y p e (MYS12) s h o w e d significant u n i t y w i t h b o o t s t r a p v a l u e s > 50%. A 68% bootstrap v a l u e s u p p o r t e d u n i t y b e t w e e n coastal s t e e l h e a d (MYS3) a n d r e s i d e n t t r o u t f r o m the S a c r a m e n t o River (MYS3), the Little K e r n River (MYS3), a n d t w o g o l d e n t r o u t h a p l o t y p e p o p u l a t i o n s (MYS3 a n d MYS15). Genetic u n i t y b e t w e e n the Eagle Lake t r o u t a n d Califor-

11 u n i q u e m t D N A h a p l o t y p e s f o u n d in this s t u d y is g i v e n b y g e n e r a l g e o g r a p h i c location in Fig. 2. A n u n r o o t e d n e i g h b o r - j o i n i n g tree for controlr e g i o n m t D N A s e q u e n c e data s u m m e d for h a p l o t y p e p o p u l a t i o n s is d e p i c t e d in Fig. 3. This tree d i v i d e d the t r o u t - s t e e l h e a d a s s e m b l a g e into four g r o u p s supp o r t e d w i t h b o o t s t r a p v a l u e s > 50%, w h e n c o n s i d e r e d in r e l a t i o n s h i p to the Rio Yaqui trout. Steelhead m t D N A h a p l o t y p e s f o u n d m o s t f r e q u e n t l y at the

1

-

mtDNA Control Region

0.9 0.8 9 North Coast

0.7 o~

[ ] North Interior

0.6

Nil South Coast

0.s

L~ South Interior

~" 0.4

[ ] Mexico Coast

0.3

I~ Mexico Interior

0.2 O'

o

,' i 1

: 2

'," 3

I ' = =

5

6

l

', 8

12

13

15

16

18

mtDNA haplotype

Frequency distribution of Oncorhynchus mykiss mtDNA haplotypes given for six general geographic locations. Haplotype numbers are given by streams and geographic areas in Appendix I.

FIGURE 2

5. mtDNA and Nuclear Microsatellites in Trout

59

Sacramento rainbow trout (3) Little Kern R. golden trout (3) Kern River rainbow trout (3) CA steelhead (3)

35 68

CA golden trout (3) CA golden trout (15)

17 Rio Santo Domingo trout (1)

17

CA steelhead (1)

541 I

99

McCloud rainbow trout (1) CA steelhead (2)

83

Eagle Lake trout (16) CA golden trout (16) CA steelhead (6)

84 1 34

57 51

70

I I

I

CA steelhead (5) CA steelhead (13) CA steelhead (8) CA steelhead (12) Rio Yaqui trout (18)

FIGURE 3 Unrooted phylogenetic tree for a 188-bp mtDNA control region segment inferred from neighbor-joining analysis (PHYLIP) of pairwise distances calculated for 11 mtDNA haplotypes found in anadromous steelhead and resident trout in California and Mexico (19901995). For these analyses, parenthetical mtDNA haplotype designations represented the most common haplotype found in each particular population. Bootstrap (1000 replicates) probability values are given in percentages on the tree branches; values >50% are indicated in bold type.

nia golden trout, which shared identical m t D N A haplotypes (MSY16), was supported by a bootstrap value of 83%. B. N u c l e a r M i c r o s a t e l l i t e s

The three microsatellite loci used in this study contained dimeric repeats [Omy207 and Ssa289 poly(CA)poly(GT), and Omy77 poly(CT)-poly(GA)], found in tracts up to 74 repeat units long, with 10-33 alleles expressed per locus (Appendix II). Frequency distributions for microsatellite alleles are given by locus and geographic area in Fig. 4. The combined allelic distribution for the three loci was found to be in H a r d y Weinberg equilibrium over the total sample population (Fisher's exact p = 0.013). The microsatellites developed specifically for O. mykiss, i.e., Omy77 (27 alleles; range 77-141 bp) and Omy207 (33 alleles; range

76-148 bp), were significantly more polymorphic in California and Mexican trout and steelhead than the Ssa289 locus developed for Atlantic salmon (10 alleles; range 89-109 bp). All three loci conformed to the expectation of a single-step allele model, with gaps in the two-base repeat sequence occurring only in the largest alleles for Omy77 and Omy207. Genetic distance measures for the three microsatellite loci combined as calculated by Slatkin (1995) and Goldstein et al. (1995) are given by the haplotype population in Table II. Derived distance measures showed similar m e a n values for both models across all populations. Slatkin's m e a n Rst value was 0.207, whereas the m e a n Fst of Goldstein et al. was 0.205. The r of Goldstein et al. (expected duration of linearity of distance for the three loci combined) equaled 299,058 + 14,732 generations. Neighbor-joining trees developed from microsatellite distance data using both methods were

1

-r-

Locus - Omy77

0.9

i

0.8

North Coast

~] North Interior

0.7

I

0.6

South Coast South Interior

= 0.5 O"

[ ] Mexico Coast

n m

[ ] Mexico Interior

0.4 0.3 i

0.2 0.1

-

i

77-85

87-95

=

97-107

109-117

121-131

L

135-148

allele size range (bp)

0.9

Locus - O m y 2 0 7

0.8 0.7 0.6

i i

North Coast

[ ] North Interior

0.5

I

South Coast South Interior

0.4

[ ] Mexico Coast

0.3

E~ Mexico Interior 0.2 0.1 0 76-84

86-94

96-104

ii[

106-114

116-124

126-134

136-148

allele size range (bp)

Locus-

0.9

Ssa289

_.=

0.8

__=

0.7

i

-=

0.6

_=

___=

= 0.5 O" L

-

0.4

i

North Coast

[]

North Interior

i

South Coast

[ ] South Interior

~iiiii

[ ] Mexico Coast

0.3

I~ Mexico Interior

0.2

i

--=

0.1

1 89

91

93

9 95

97

~n 101

103

105

m 107

109

allele size (bp)

FIGURE 4 Frequency distributions of Oncorhynchus mykiss alleles from Omy77 (A),

60

Omy207 (B), and Ssa289 (C) microsatellite loci given by geographic area (see Appendix I for sample locations). Frequencies have been pooled by size class (each bin includes five sequential alleles) to aid in graphic resolution.

TABLE H

Genetic Distance Measures for Three Microsatellite Loci (Omy77, Omy207, Ssa289) from California and Mexican Trout Populations a

Population (haplotype) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

Rio Yaqui (18) CA steelhead (1) M c C l o u d (1) Rio Santo D o m i n g o (1) CA steelhead (2) CA g o l d e n (3) CA steelhead (3) Kern r a i n b o w (3) Little Kern River golden (3) Sacramento (3) CA steelhead (5) CA steelhead (6) CA steelhead (8) CA steelhead (12) CA steelhead (13) CA g o l d e n (15) CA golden (16) Eagle Lake (16)

1

2

3

m 23.10 41.05 94.92 25.96 32.10 35.46 22.46 56.43 7.28 44.09 11.68 42.67 28.43 55.70 13.39 10.00 11.53

0.40 m 4.93 109.53 0.25 15.32 7.79 45.41 64.87 36.89 8.51 3.64 10.00 1.22 34.91 12.20 11.70 31.80

0.42 0.04 ~ 91.92 3.19 11.36 2.96 47.06 53.29 50.56 3.24 9.03 3.61 3.21 21.37 14.44 16.64 37.19

4 0.90 0.59 0.59 ~ 106.21 73.58 69.52 35.31 6.08 79.73 84.11 81.47 73.11 108.65 29.47 60.25 68.54 45.57

5

6

7

8

9

10

11

12

13

14

15

16

17

18

0.33 0.03 0.04 0.59 ~ 12.67 6.67 44.46 62.38 37.98 7.52 3.89 8.75 0.48 32.46 11.51 11.45 31.85

0.63 0.22 0.09 0.71 0.07 -15.47 21.32 38.83 25.16 22.56 9.55 20.02 9.81 27.98 5.34 6.57 18.31

0.42 0.03 0.05 0.52 0.03 0.16 ~ 38.37 37.27 46.73 1.15 8.22 0.43 8.52 10.63 12.22 15.21 29.26

0.17 0.21 0.28 0.40 0.24 0.02 0.20 -15.21 9.56 52.65 23.75 46.01 44.15 32.80 10.79 11.83 1.98

0.59 0.40 0.34 0.34 0.34 0.41 0.26 0.02 m 46.23 49.41 43.24 41.12 64.09 13.24 28.12 34.02 20.42

0.30 0.27 0.29 0.60 0.21 0.32 0.28 0.04 0.36 ~ 60.04 18.94 56.06 37.59 59.33 12.16 9.29 5.48

0.44 0.05 0.05 0.57 0.04 0.17 0.00 0.27 0.31 0.33 ~ 12.77 0.40 9.87 15.12 20.01 23.17 41.30

0.00 0.10 0.14 0.63 0.10 0.14 0.14 0.18 0.26 0.11 0.13 ~ 12.11 4.80 26.95 3.01 2.63 13.94

0.43 0.03 0.05 0.50 0.05 0.20 0.00 0.23 0.27 0.30 0.02 0.20 ~ 10.95 10.75 17.24 20.78 36.31

0.11 0.07 0.01 0.59 0.03 0.31 0.00 0.23 0.22 0.05 0.00 0.00 0.06 -34.92 11.36 11.25 32.52

0.41 0.16 0.17 0.37 0.19 0.04 0.07 0.20 0.00 0.24 0.09 0.19 0.12 0.18 ~ 22.48 28.72 30.81

0.05 0.01 0.09 0.46 0.04 0.38 0.02 0.04 0.02 0.12 0.06 0.00 0.09 0.04 0.11 m 0.43 5.73

0.13 0.14 0.18 0.60 0.12 0.08 0.15 0.06 0.25 0.06 0.19 0.02 0.20 0.02 0.18 0.08 ~ 5.83

0.19 0.27 0.30 0.54 0.25 0.16 0.25 0.04 0.19 0.06 0.30 0.10 0.28 0.16 0.20 0.05 0.05

Distance measures (Rst) obtained according to the Slatkin (1995) m e t h o d using a stepwise m u t a t i o n process are given above the diagonal. Distance m e a s u r e s calculated according to Goldstein et al. (1995) using a one-step mutation model are given below the diagonal. a

62

JENNIFER L. NIELSEN et al. McCIoud r a i n b o w trout (1)

9

34 29

I

22 I

I

36

I

, C A steelhead (8) C A steelhead (5) C A steelhead ( 1 2) C A steelhead (1 3)

77

971 I

Rio Santo D o m i n g o trout (1) Little Kern R. golden trout (3) CA golden trout (1 6)

20

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CA steelhead (1)

CA golden trout (3) S a c r a m e n t o r a i n b o w trout (3)

4? r

44 31 !

I

Eagle Lake trout (16) Kern River r a i n b o w trout (3) CA golden trout (1 5) CA steelhead (6) Rio Yaqui trout (1 8)

FIGURE 5 Consensusunrooted phylogenetic tree for three microsatellite loci combined (Omy77, Omy207, and Ssa289) inferred from pairwise distances (Rst) resulting from mi-

crosatellite distance analysis based on Slatkin (1995) and using neighbor-joininganalysis (PHYLIP) of distance values to construct the tree. Bootstrap probability values based on 1000 replicate trees developed from bootstrapping of the original Rst distance data are given in percentages on the tree branches; values >50% are indicated in bold type.

not congruent for most haplotype populations (Figs. 5 and 6). Bootstrap values > 50% were rare among the microsatellite NJ branching units, making comparisons between the microsatellite and mtDNA trees difficult. No similar branching patterns were found by analyses of microsatellites that reflected the biogeographic associations developed from the authors' analyses of m t D N A haplotypes. The genetic similarity of the Rio Santo Domingo trout from Baja (MYS1), trout from the Little Kern River (MYS3), and a haplotype found only in southern steelhead (MYS13) was supported with > 50% bootstrap values in both microsatellite NJ trees. In both trees, close associations among the coastal steelhead populations (with the exception of haplotype MSY13)

and the McCloud River rainbow trout were supported. Only the Goldstein distance method, however, supported this association with bootstrap values 50%. Eagle Lake trout that shared a mtDNA haplotype with the South Fork Kern River golden trout (MYS16) were more closely associated with the Kern River and Sacramento River rainbow trout (both MYS3 haplotypes) using microsatellites. Neither tree supported these association with high bootstrap values. C. B i o g e o g r a p h i c

Concordance

A significant correlation was observed between mtDNA haplotype variation and both latitude (ANOVA F test < 0.001) and longitude (F test = 0.01), with lati-

5. m t D N A and Nuclear Microsatellites in Trout

63

McCloud rainbow trout (1) 11 22 [ 42

I

CA steelhead (1) CA steelhead (12)

38 /

CA Steelhead (2) 69

CA Steelhead (8)

55

CA steelhead (5)

59

CA Steelhead (3)

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CA steelhead (6) 21

CA golden trout (3) CA Steelhead (13)

58

21 21

s9 I I

Rio Santo Domingo trout (1) Little Kern golden trout (3) CA golden trout (15)

11 38 99

CA golden trout (16) Kern rainbow trout (3) Eagle Lake trout (16) Sacramento rainbow trout (3)

Rio Yaqui trout (18) FIGURE 6 Unrooted phylogenetic tree for three microsatellite loci combined (Omy77, Omy207, and Ssa289) inferred from pairwise distances resulting from microsatellite distance analysis based on the Goldstein et al. (1995) single-step distance model and using neighbor-joining analysis (PHYLIP) of distance values. Bootstrap (1000 replicates) probability values developed from the Goldstein el al. (1995) program are given in percentages on the tree branches; values >50% are indicated in bold type.

tude explaining 46% of the variance within haplotypes and longitude explaining 39% of the variance. Factor analysis of m t D N A haplotype frequency showed that the first principal component explained 72% of the variation across sampling areas, whereas the second factor explained 21% of the haplotype variance. Multiple regression of the m t D N A first principal component on latitude had the highest correlation 0 "2 - - 0.74; Fig. 7), with the m a x i m u m trend detected between populations above and below 37~ latitude (approximate location of Santa Cruz, CA). Regression of the first principal component on longitude gave 1,2 - - 0.62. The frequency distribution of microsatellite alleles, however, was weakly associated with longitude (F test = 0.05) and not at all with latitude (F test - 0.46). The

first principal component explained 33% of the variation in microsatellite allelic frequencies across all sampling areas, whereas the second factor contributed only 9% of the variance. Multiple regression analyses of the first principal component on longitude (1,2 = 0.55; Fig. 8) demonstrated a m a x i m u m trend in allelic variation around 121 ~ longitude (the approximate b o u n d a r y of the Sierra Nevada Crest in north-central California). Principal components analysis of genotype distributions using both m t D N A and microsatellite data combined found that the first principal component explained 68% of the variation in genotype frequency, whereas the second factor contributed 31% of the proportionate genotype variance. Factor axis loadings for

64

JENNIFER L. NIELSEN et at.

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mmm

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FIGURE 7 Regression of the first principal component derived from factor analysis of mtDNA haplotype diversity on latitude 0 .2 -0.74). The maximum trend was detected between populations above and below 37~ latitude (approximate location of Santa Cruz, CA).

mtDNA were -0.72 (factor one) and -0.09 (factor 2); for microsatellites, factor one and two axis loadings were 0.16 and 0.98, respectively.

IV.

Discussion

Biogeographic structure based on analyses of mtDNA and nuclear microsatellites proved to be non-

"9

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FIGURE 8 Regression of the first principal component derived

from factor analysis of microsatellite allelic frequency on longitude 0 .2 = 0.55). The maximumtrend was detected between populations east and west of 121~latitude (approximatelocationof SierraNevada Crest in north-central California).

congruent in this study, with no intraspecific phylogenetic relationships supported by both markers with significant bootstrap values. This noncongruence may be explained by the documented differences found between these genetic markers and geography. Mitochondrial DNA haplotypes showed significant correlation with both longitude and latitude. Nuclear microsatellites, however, correlated only weakly with longitude and not at all with latitude. Although it is widely understood that data from differents parts of the genome often evolve differently (Avise, 1994; Huelsenbeck et al., 1996), the influence different evolutionary processes may have on phylogeographic structure within closely related populations is not generally known. Three mtDNA haplotype bioregions for coastal steelhead were suggested in Nielsen et al. (1994b). Neeley (1995) confirmed these findings using additional mtDNA haplotype data and showed significant genetic subdivision in coastal trout at 38.7~ (just above the mouth of the Russian River on the north coast of California) and at 36.7~ at the Pajaro River in central California. The analyses of trout mtDNA diversity presented here included interior populations from the McCloud River, the upper Sacramento River, and the Kern River basin, as well as two southern populations from Mexico. These new results support a latitudinal cline in O. mykiss mtDNA haplotype variation, but suggest that the maximum difference in variation for inland and coastal populations occurs north and south of 37~ latitude. The resolution of mtDNA frequency distributions in interior trout populations from California would gain from the addition of samples from the San Joaquin River that were not available at the time of these analyses. One mtDNA haplotype (MSY3) was common in anadromous steelhead from the Russian River north of San Francisco Bay to the Carmel River just south of Monterey, California. This mtDNA haplotype was also found in dominant frequencies in resident trout from the upper Sacramento River, California golden trout from the South Fork Kern River at Ramshaw Meadows, Golden Trout Creek, and Johnson Creek, and in rainbow trout populations from the Kern River and the Little Kern River. These data imply an extensive geographic distribution of this haplotype in the interior populations and suggest a strong genetic relationship between resident and anadromous trout in the Sacramento River drainage and the trout of the Kern River basin. Behnke in his 1992 monograph on native trout suggests such a linkage between Sacramento River redband trout and the California golden trout based on coloration and other taxonomic characters, which would appear to support the mtDNA findings. Ac-

5. mtDNA and Nuclear Microsatellites in Trout cording to Behnke (1992), the most primitive redband trout found in the Sacramento River basin is represented by fish from an isolated population found in Sheepheaven Creek near the McCloud River. mtDNA was sequenced from 11 fin clips taken from trout from Sheepheaven Creek that were sent to the author's laboratory by the California Department of Fish and Game. These Sheepheaven Creek fish were monomorphic for mtDNA haplotype MYS1, as were all 54 McCloud River rainbow trout that were sequenced. Haplotype MYS1 was most frequently found in coastal steelhead from northern California. This haplotype has never been found in California golden trout. McCloud River redband trout had microsatellite alleles that have not been found in coastal steelhead groups. One notable example was the Omy77 allele (Omy77-79), which was common in the upper Sacramento River, Kern River, and Little Kern River rainbow trout, in Eagle Lake trout, and in California golden trout, but has been found in only one steelhead from the Carmel River. A second Omy77 allele (Omy77-121) dominated frequency in the McCloud trout populations and was rarely found in coastal steelhead. Two new mtDNA haplotypes (MYS15 and MYS16), never seen in coastal populations, were found among golden trout captured in Taylor, Fay and Manter Creeks, and in the South Fork Kern River at Ramshaw Meadows. Haplotype MYS16 was also found to be monomorphic in Eagle Lake trout. The isolated geographic distribution of this haplotype into this northern interior lake remains unclear. There have been no officially documented fish transfers from the South Fork Kern River to Eagle Lake in recent history (E. Gerstung, California Department of Fish and Game, personal communications). Microsatellite distance analyses did not link these two populations with any statistical rigor. A third unique mtDNA haplotype (MYS18) was found in the Rio Yaqui trout from northwestern Mexico. This group of fish had a significantly different genetic profile for both mtDNA and microsatellites when compared to the rest of O. mykiss. Several alleles that dominated the microsatellite frequency in the Rio Yaqui fish were found only rarely or not at all in California trout populations. The position of this group in the evolutionary history of Pacific trout has been speculated on in several early studies (Miller, 1950, 1972; Needham and Gard, 1964), but their taxonomic status remains undefined. These genetic findings support a unique identity for this group of trout which deserves further study. The mtDNA haplotype (MYS1), which dominated anadromous steelhead populations in northern California, was also found to be fixed in Rio Santo Domingo rainbow trout from Baja California. It has been

65

speculated that the Baja rainbow trout originated from the anadromous coastal steelhead of southern California (Ruiz-Campos and Pister, 1995). The rare, but ubiquitous, distribution of the MYS1 haplotype throughout southern California supports a possible historic connectivity between these anadromous stocks and the resident rainbow trout populations of Baja. In an earlier study using electrophoretic analyses of allozymes, Berg (1987) found a unique creatine kinase allele (Ck-2) in Baja trout that was not found in other coastal populations. Microsatellites also paint a different picture of biogeographic associations for the Baja trout. Microsatellite alleles (Omy77-77, Omy77-87, and Omy207-124) show a closer relationship between the Baja fish and trout populations in the Kern River and the South Fork Kern River. Omy77-87 was found in only one fish from Bull Frog Lake on the Little Kern River. Omy77-77 was found only in fish from Dry Meadows Creek on the Kern River. These associations demonstrate a possible evolutionary connection between the Baja trout and the Kern River basin, suggesting an alternate evolutionary path for these fish. Both analyses of microsatellite distance supported the unity of the Baja trout with the rainbow trout of the Little Kern River with high bootstrap values. This lack of congruence between mtDNA and microsatellite allelic frequencies argues against a single Pleistocene radiation for O. mykiss. An alternative hypothesis is two radiations from a Gulf of California refugium as suggested by Behnke (1992), with one contributing to the interior redband/golden trout complex and one to the coastal radiation of steelhead and coastal rainbow trout. It is interesting that three controversial trout populations, McCloud River's Sheepheaven Creek redband trout, the Eagle Lake trout, and the Baja trout, have demonstrable differences in interpretation of their evolutionary associations based on mtDNA and microsatellites. It is possible that these unique trout populations represent different ancestral nodes for both radiations. Another possible explanation for the lack of congruence between mtDNA phylogenetic structure and microsatellite data is male-mediated gene flow (Karl et al., 1992). This study found significant differences in population structure in nuclear vs mtDNA assays of sea turtles (Chelonia mydas) and attributed this finding to life history differences between males and females, where females alone demonstrated a strong natal site philopatry in rookery use. Male straying from natal streams during spawning migrations in anadromous salmon is thought to be more pervasive than straying in females (Flemming and Gross, 1994; Quinn and Foote, 1994). Similar behavior and male-mediated gene flow in resident rainbow trout, however, would be limited to

66

JENNIFERL. NIELSENet al.

straying among tributaries of the same river basin and would not seem to be a credible cause of the microsatellite allelic panmixia shown in this study across many interior river basins where there is currently no access to the ocean. The artificial transfer of trout from basin to basin could explain such a panmixia, but artificial stock transfers would not be limited strictly to male fish. A more likely mechanistic explanation for the lack of congruence among these molecular markers lies in the fact that microsatellites probably have diverged more rapidly than the mtDNA control region and may, therefore, not be useful in detecting phylogenetic relationships among closely related taxa due to a lack of lineage sorting in these markers. Our comparison of the Slatkin (1995) and Goldstein et al. (1995) distance measures gave no indication as to which of the two methods used for constructing distance matrices for microsatellites might more likely reflect trout phylogeny. The three microsatellite loci used in this study seem to fit the expectation of the singlestep allele model with the exception of a few large alleles in Omy77 and Omy207. The general results of the consensus trees were similar, with few significant branching patterns based on bootstrap analyses of 1000 trees. Analyses of additional polymorphic microsatellite loci may provide a more reliable signal for divergence of O. mykiss, but it is clear from these data that mtDNA control region sequence and microsatellites can give very different evolutionary signals for closely related groups. In a study that inferred phylogenetic trees from 10 vertebrate species, Cummings et al. (1995) suggested that a large number of genes and nucleotide sites are needed to exactly determine phylogenetic relationships. The selection of molecular markers used in phylogenetic studies is frequently made based on factors related to the historic use of the marker in systematic studies, the functional characteristics of the marker, the ease of extraction and amplification, but not on the relevance of that marker to the evolutionary history of the population. The conflicting results reported here for mtDNA sequence data and nuclear microsatellites confirm the need to draw phylogenetic inference from several independent markers before reaching conclusions that are presumed to represent the evolutionary history of the organism. In summary, the biogeographic results derived from mtDNA and microsatellites were not congruent for this study of trout and steelhead populations. The phylogeographic structure for mtDNA was significantly associated with both longitude and latitude in western trout populations. Unlike the conclusion drawn by Phillips and Oakley (1997), intraspecific mtDNA control region data retain significant biogeographic struc-

ture, suggesting that control region divergence can serve as a rigorous marker in the documentation of stock structure in this species. Only a weak association, however, was shown between longitude and the frequency of microsatellite alleles. The most significant separation for this marker occurred at the approximate boundary of the Sierra Nevada Crest, weakly supporting the biogeographic subdivision of O. mykiss previously reported by Allendorf (1975) for allozymes in trout. These data suggest that microsatellite, allozymes, and mtDNA data do not reflect the same evolutionary architecture in O. mykiss. Based on morphological data, Behnke (1992) suggested a Gulf of California refugium for Oncorhynchus during the mid-Pleistocene, approximately 250,000 years ago. With 4.5% mtDNA control region sequence divergence (Nielsen et al., 1994b), the female lineage of O. mykiss appears to have retained significant phylogenetic structure for a far longer period, assuming an expected substitution rate of around 4% per million years (Avise, 1994). Microsatellites, however, with only a weak geographic association between longitude and allelic frequency distributions, seem to represent population structure that has more recently diverged, perhaps during the mid to late Pleistocene (Bailey, 1966) when the Sierra Nevada area was strongly uplifted and tilted to the west. It is interesting, however, to note that factor analyses of the geographic range of samples and genetic data from both molecular markers showed that the first two factors could be used to explain 99% of the genetic variance reported in this study, suggesting that a combination of molecular markers reflecting independent evolutionary histories do a far better job of depicting phylogeography than either one alone.

Acknowledgments Numerous people were instrumental in collecting tissue from steelhead and trout for this project, clarifying our analytical approach, and editing difficult and cumbersome drafts of this paper. We express our special appreciationto MuriceCardenas, Cindy Carpanzano, Sara Chubb, Bill Cox, Karen Crow, Tom Dowling, Chris Gan, Eric Gerstung, Ed Henke, Buddy Jensen, Wendy Jones, Mat Lectner, Giles Manwaring, Bob Miller, Eric Minch, Steve Nettie, Steve Parmenter, Phil Pister, Dennis Powers, Mike Rode, Gorgonio Ruiz-Campos, Monty Slatkin, Kelley Thomas, Doug Tupper, Steve Turek, and Don Weidlein. We are grateful for the suggestions and corrections made in this manuscript by the editors and two anonymous reviewers.

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5. m t D N A and Nuclear Microsatellites in Trout

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Kocher, T. D., Thomas, W. K., and Meyer, A. 1989. Dynamics of mitochondrial DNA evolution in animals: Amplification and sequencing with conserved primers. Proc. Natl. Acad. Sci. USA 86: 6196-6200. Long, E. O. and David, I. B. 1980. Repeated genes in eukaryotes.Ann. Rev. Biochem. 49: 727- 764. Louis, E. J. and Dempster, E. R. 1987. An exact test for Hardy-Weinberg and multiple alleles. Biometrics 43:805-811. McConnell, S. K., O'Reilly, P., Hamilton, L., Wright, J. M., and Bentzen, P. 1995. Polymorphic microsatellite loci from Atlantic salmon (Salmo salar): Genetic differentiation of North American and European populations. Can. J. Fish. Aquat. Sci. 52:18631872. Miklos, G. L. G. 1985. Localized, highly repetitive DNA sequences in vertebrate and invertebrate genomes. In "Molecular Evolutionary Genetics" (R. J. MacIntyre, ed.), pp. 231-241 Plenum Press, New York. Miller, R. R. 1950. Notes on the cutthroat and rainbow trouts with the description of a new species from the Gila River, New Mexico. Occ. Pap. Mus. Zool. Univ. M1529 :1-42. Miller, R. R. 1972. Classification of the native trouts of Arizona, with the description of a new species, Salmo apache. Copeia 1972:401422. Moore, S. S., Sargent, L. L., King, T. J., Mattick, J. S., Georges, M., and Hetzel, D. J. S. 1991. The conservation of dinucleotide microsatellites among mammalian genomes allows the use of heterologous PCR primer pairs in closely related species. Genomics 10:654-660. Morin, P. A., Moore, J. J., Chakraborty, R., Jin, L., Goodall, J., and Woodruff, D. S. 1994a. Kin selection, social structure, gene flow, and the evolution of chimpanzees. Science 265:1193-1201. Morin, P. A., Wallis, J., Moore, J. J., and Woodruff, D. S. 1994b. Paternity exclusion in a community of wild chimpanzees using hypervariable simple sequence repeats. Mol. Ecol. 3:469-478. Moritz, C., Dowling, T. E., and Brown, W. M. 1987. Evolution of animal mitochondrial DNA: Relevance for population biology and systematics. Ann. Rev. Ecol. Syst. 18:269-292. Moritz, C., Lavery, S., and Slade, R. 1995. Using allele frequency and phylogeny to define units for conservation and management. In "Evolution and the Aquatic Ecosystem: Defining Unique Units in Population Conservation" (J. L. Nielsen, ed.), pp. 249-262. Am. Fish. Soc. Symposium No. 17, Bethesda, MD. Morris, D. B., Richard, K. R., and Wright, J. M. 1996. Microsatellites from rainbow trout (Oncorhynchus mykiss) and their use for genetic studies of salmonids. Can. J. Fish. Aquat. Sci. 53:120-126. Needham, P. R., and Gard, R. 1964. A new trout from central Mexico: Salmo chrysogaster, the Mexican golden trout. Copeia 1964:169173. Neeley, D. 1995. A statistical evaluation of coastal California steelhead genetic data gathered by J. L. Nielsen et al. and by Trihey and Associates. Prepared for S. P. Cramer & Asso. Submitted to Association of California Water Agencies, Sacramento, CA. Neigel, J. E., and Avise, J. C. 1986. Phylogenetic relationships of mitochondrial DNA under various demographic models of speciation. In "Evolutionary Processes and Theory" (E. Nevo and S. Karlin, eds.), pp. 515-534. Academic Press, New York. Nielsen, J. L. 1996. Molecular genetics and the conservation of salmonid biodiversity: Oncorhynchus at the edge of their range. In "'Molecular Genetic Approaches in Conservation" (T. Smith and R. Wayne, eds.) pp. 383-398. Oxford University Press, London. Nielsen, J. L., Gan, C. A., and Thomas, W. K. 1994a. Differences in genetic diversity for mtDNA between hatchery and wild populations of Oncorhynchus. Can. J. Fish Aquat. Sci. 51(Suppl. 1):290297. Nielsen, J. L. Gan, C. A., Wright, J. M., Morris, D. B., and Thomas, W. K. 1994b. Biogeographic distributions of mitochondrial and

nuclear markers for southern steelhead. Mol. Marine Bio. Biotech. 3:281-293. Okazaki, T. 1984. Genetic divergence and its zoogeographic implications in closely related species Salmo gairdneri and Salmo mykiss. Jap. J. Ichthyol. 31:297-310. O'Reilly, P., and Wright, J. M. 1995. The evolving technology of DNA fingerprinting and its application to fisheries and aquaculture. J. Fish. Biol. 47(Suppl. A) :29-55. Pamilo, P., and Nei, M. 1988. Relationships between gene trees and species trees. Mol. Biol. Evol. 5:568-583. Parkinson, E. A. 1984. Genetic variation in populations of steelhead (Salmo gairdneri) in British Columbia. Can. J. Fish. Aquat. Sci. 41: 1412-1420. Phillips, R. B., and Oakley, T. H. 1997. Phylogenetic relationships among the Salmonidae based on nuclear DNA and mitochondrial DNA sequences. In "Molecular Systematics of Fishes" (T. D. Kocher and C. A. Stepien, eds.). Academic Press, San Diego. Queller, D. C., Strassmann, J. E., and Hughs, C. R. 1993. Microsatellites and kinship. Trends Ecol. Evol. 8:285-288. Quinn, T. P., and Foote, C. J. 1994. The effects of body size and sexual dimorphism on the reproductive behavior of sockeye salmon (Oncorhynchus nerka). Anim. Behav. 48: 751-761. Regan, C. T. 1914. The systematic arrangement of the fishes of the family Salmonidae. Ann. Mag. Nat. Hist. 13(8):405-408. Reisenbichler, R. R., McIntyre, J. D., Solazzi, M. F., and Landing, S. W. 1992. Genetic variation in steelhead of Oregon and Northern California. Trans. Am. Fish. Soc. 121:158-169. Ruiz-Campos, G., and Pister, E. P. 1995. Distribution, habitat, and current status of the San Pedro Martir rainbow trout, Oncorhynchus mykiss nelsoni (Evermann). Bull. S. CA Acad. Sci. 94(2):131148. Schlotterer, C., and Tautz, D. 1992. Slippage synthesis of simple sequence DNA. Nucleic Acids Res. 20: 211-215. Slatkin, M. 1991. Inbreeding coefficients and coalescence times. Genet. Res. 58:167-175. Slatkin, M. 1995. A measure of population subdivision based on microsatellite allele frequencies. Genetics 139:457-462. Smith, G. R., and Stearley, R. F. 1989. The classification and scientific names of rainbow and cutthroat trouts. Fisheries 14:4-10. Spencer, P. B. S., Odorico, D. M., Jones, S. J., Marsh, H. D., and Miller, D. J. 1995. Highly variable microsatellites in isolated colonies of the rock-wallaby (Petrogale assimilis) Mol. Ecol. 4:523-525. Stearley, R. F., and Smith, G. R. 1993. Phylogeny of the Pacific trouts and salmon (Oncorhynchus) and genera of the family Salmonidae. Trans. Am. Fish. Soc. 122:1-33. Stoneking, M., Hedgecock, D., Higuchi, R. G., Vigilant, L., and Erlich, H. A. 1991. Population variation of human mtDNA control region sequence detected by enzymatic amplification and sequence-specific oligonucleotide probes. Am. J. Hum. Genet. 48:370-382. Swift, C. C., Haglund, T. R., Ruiz, M., and Fisher, R. N. 1993. The status and distribution of the freshwater fishes of southern California. Bull. South. Calif. Acad. Sci. 92(2): 101-167. Tautz, D. 1989. Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Res. 17: 6463-6471. Thomas, W. K., and Beckenbach, A. T. 1989. Variation in salmonid mitochondrial DNA: Evolutionary constraints and mechanisms of substitution. J. Mol. Evol. 29:233-245. Thomas, W. K., Withler, R. E., and Beckenbach, A. T. 1986. Mitochondrial DNA analysis of Pacific salmonid evolution. Can. J. Zool. 64:1058-1064. Titus, R. G., Erman, D. C., and Snider, W. M. History and status of steelhead in California coastal drainages south of San Francisco Bay. Hilgardia, in press.

5. m t D N A and Nuclear Microsatellites in Trout Utter, F. M., F. W. Allendorf, and H. O. Hodgins. 1973. Genetic variability and relationships in Pacific salmon and related trout based on protein variation. Syst. Zool. 22:257-270. Utter, F. M., and Allendorf, F. W. 1994. Phylogenetic relationships among species of Oncorhynchus: A consensus view. Conser. Biol. 8: 864- 867. Vladykov, V. 1963. A review of salmonid genera and their broad geographical distribution. Trans. Roy. Bd. Can. 1 (Ser. 4, Sect. 3): 459504. Weber, J., and May, P. 1989. Abundant class of human DNA polymorphisms which can be typed using the polymerase chain reaction. Am. J. Hum. Gene. 44:388-396. Weller, S. J., Pashley, D. P., Martin, J. A., and Constable, J. L. 1994.

69

Phylogeny of noctuoid moths and the utility of combining independent nuclear and mitochondrial genes. Syst. Biol. 43(2):194211. Wilson, G. M., Thomas, W. K., and Beckenbach, A. T. 1985. Intra- and inter-specific mitochondrial DNA sequence divergence in Salmo: Rainbow, steelhead, and cutthroat trouts. Can. J. Zool. 63:20882094. Wright, J. M. 1993. DNA fingerprinting in fishes. In "Biochemistry and Molecular Biology of Fishes" (P. W. Hochachka and T. Mommsen, eds.), Vol. 2, pp. 57-91. Elsevier Press, New York. Wright, J. M., and Bentzen, P. 1994. Microsatellites: Genetic markers for the future. In "Reviews in Fish Biology and Fisheries" (G. R. Carvalho and T. J. Pitcher, eds.). Chapman and Hill, London.

70

JENNIFER L. NIELSEN et at. APPENDIX I m t D N A haplotype Location North coast Van Duzen River Eel River Albion River Navarro River Gualala River Garcia River Russian River Salmon River Usal Creek Cottoneva Creek H o w a r d Creek Redwood Creek Lagunitas Creek North interior Sacramento River Mears Creek Soda Creek Dog Creek Slate Creek McCloud River Edson Creek Dry Creek Trout Creek Sheepheaven Creek Eagle Lake

1

2

5 10 7 2 1 1

1 10

3

6

8

12

13

15

16

18

Total

Total

8 25 8 2 1 1 2 4 3 3 3 5 3 68

Total

5 5 3 2 8 6 8 5 4 11 10 67

Total

4 4 6 15 9 6 6 5 7 6 9 77

2 2

3 1

1 2 1 3

6 8 5 4 11 10

South coast San Lorenzo River Zyante Creek Carmel River Santa Ynez River Morro Bay Scott Creek Waddell Creek Santa Rosa Creek Pico Creek Gaviota Creek Malibu Creek South interior Kern River Dry Meadows Creek Freeman Creek Little Kern River Bullfrog Lake Sheep Creek Willow Creek South Fork Kern River Fay Creek Manter Creek Ramshaw Meadows Taylor Creek Golden Trout Creek Johnson Creek

5

2 2 3 3

4

1 3 2 7

1

3 2

1 2

11 6 6

11 6 6

3 8 8 13 15 6

3 7 10

6 1

1 Total

13 15 9 6 9 10 98

5. mtDNA and Nuclear Microsatellites in Trout

71

APPENDIX ImContinued mtDNA.haplotype Location

1

Mexican coastal Rio Santo Domingo Arroyo San Rafael Arroyo San Antonio Arroyo La Zanja Arroyo E1 Potrero

12 6 4 3 2

2

3

5

6

8

12

13

15

16

Mexican interior Rio Yaqui Total

99

17

108

20

7

25

7

8

7

45

18

Total

Total

12 6 4 3 2 27

11

11

11

354

APPENDIX H Locus = O m y 77 Population (haplotype)

77

79

81

83

85

87

89

CA steelhead (1) M c C l o u d r a i n b o w (1) Rio Santo D o m i n g o (1)

91

93

95

97

101

103

105

107

109

2

1

1

14

5

5

4

3

4

117

6

CA steelhead (3) 6

Little Kern golden (3)

14

Sacramento r a i n b o w (3)

20

3 1

4

2 1

1

9

1 5

3

2

CA steelhead (6)

1 1

3

CA steelhead (12)

1

CA steelhead (13)

5

CA g o l d e n trout (15)

3 1

Eagle Lake r a i n b o w (16) Rio Yaqui trout (18)

12 2

5 30

1 2

10

8

2

2 2 11 1

1 3

5 2

16

5

3 2

3 2

1

CA steelhead (5) CA steelhead (8)

125

127

129

131

135

1

2

3

1

7

137

141 Total

1

2

1

1

1

6

2 1

5

3 1

2

4

1 1

4

1

3

1

1 1

4 3 6

1

2 1

3

1

4

2

1 2

32 38 1

3

2

1

1

1

2

3

4

10

1 1

1

3

32 14

3

56 1

2

14 16 14 18

1

3 20

44 16 38 46

1

11

2

1 1

2 4

2 5

2

2

7 10 3

1

1 4

54 32 20

14 3

2

121

24

CA g o l d e n t r o u t (3)

CA g o l d e n trout (16)

115

8

CA steelhead (2)

Kern River r a i n b o w (3)

111

20 22

2 Locus = O m y 207

76

CA steelhead (1)

78

80

82

84

86

88

90

4

5

1

1

1

5

92

M c C l o u d r a i n b o w (1)

94

96

98

100

6

2

1

9

2

Rio Santo D o m i n g o (1) CA steelhead (2) CA G o l d e n t r o u t (3)

104

106

4

1

1

14 1

1

1

1

2

2

CA steelhead (3)

2

2

1 2

3

2

2

1

10

1

7

1

1

1

108

110

112

4

116

118

2

1 8

1

3

124

1

1

1

1

2

1

7

6

4

10

122

126

128

130

132

134

136

138

148 Total

1

50

2

4 1

120

1

1 1

1 4

114

6 1

3

6

21 2

Kern River r a i n b o w (3) Little Kern g o l d e n (3)

102

20 6 2

19

30 30

1 1

38

1

1

5

1

1

3

1

38 1

2

3

1

16 36

Sacramento rainbow (3) CA steelhead (5) Kern River rainbow (5) CA steelhead (6) CA steelhead (8) Kern River rainbow (8) CA steelhead (12) CA steelhead (13) CA golden trout (15) CA golden trout (16) Eagle Lake rainbow (16) Rio Yaqui trout (18)

2

19 2

3

6

7

5 2

1

3

9 3 2 2 2

4 1

1

1

4 3

1 1

3

1

1

7

2 8

1

5

2

2

89

CA steelhead (1)

Y

91

93

95

97

2

30 8 16 14 2 17 3 22 10 12 5 9 3 6 3 14

3

4

2 11

1

1

4 5

1

2 4 14 2 4 14 14 1 1 36 2 1 4 5 12 22

3

2 1

2

9 5 3 1 2

6

2

6

1 2 1 6 2

4 4

5 27 3

2 2 2

1 3 1 3

2 3

4 1 4 1 3 1 4 2

4 4

5

3 2 1 6 1 4 1 3 4 1

1

1 1

2 2

3

4

1

1

2 1 1 2 6

101 103 105 107 109 Total

3 26 2 1

1

1

1 3

Locus = Ssa 289

McCloud rainbow (1) Rio Santo Doming0 (1) CA steelhead (2) CA golden trout (3) CA steelhead (3) Kern River rainbow (3) Little Kern golden (3) Sacramento rainbow (3) CA steelhead (5) Kern River rainbow (5) CA steelhead (6) CA steelhead (8) Kern River rainbow (8) CA steelhead (12) CA steelhead (13) CA golden trout (15) CA golden trout (16) Eagle Lake rainbow (16) Rio Yaqui trout (18)

1 2

50 34 20 32 34 44 16 36 44 32 14 14 54 10 14 16 14 20 20 22

1 1 1 2

4 2

46 30 12 12 36 10 14 16 14 20 20 20

This Page Intentionally Left Blank

C H A P T E R

6 Mitochondrial DNA Sequence Variation among the Sand Darters (Percidae: Teleostei) E. O. WILEY Museum of Natural History and Department of Systematics and Ecology University of Kansas Lawrence, Kansas 66045

time, developments in population genetic theory also have begun to provide bridges between disciplines (e.g., Slatkin and Maddison, 1989; Hudson, 1990; Templeton et al., 1992). In 1987, Avise and colleagues coined the term "intraspecific phylogeography" for the use of molecular data to reconstruct population histories in relation to geography. The essence of their approach is a threestage process. Molecular data are obtained from individuals sampled from geographically distinct populations. These data are next used to generate a tree showing genealogical relationships among individuals. Finally, the geographic distribution of individuals is compared with the tree. Avise et al. (1987) argued that patterns of concordance between genealogy and geography should reflect historical events responsible for current distribution of an organism. A fundamental assumption is that molecular data preserve a record of genealogy that is independent of the historical pattern of dispersal or vicariance among populations. Intraspecific phylogeography may offer significant insight into processes occurring at the interface between systematics and population genetics, but much work is still needed to refine methods. Since 1987, several authors have proposed methods that may allow

I. I n t r o d u c t i o n

The interface between population genetics and systematics remains one of the most challenging areas in evolutionary biology. Part of the difficulty arises from differing analytical approaches. The goal of most phylogenetic studies is to reconstruct historical (sister group) relationships among taxa through analysis of character distributions. Standard phylogenetic methods work best with characters that are monomorphic within species (Swofford et al., 1996). In contrast, the goals of most population genetic studies are to infer rates and directions of ongoing processes that affect relationships among individuals and populations through analysis of allele frequencies within and among populations. Standard population genetic methods do not include information about the historical relationship among different alleles (Weir, 1996). The contrasting emphases on monomorphic versus polymorphic characters, on character states versus alleles, and on historical versus contemporaneous processes have tended to create barriers between disciplines. However, since the mid-1980s, there has been increasing convergence in the types of data used for population genetic and systematic studies. At the same MOLECULAR SYSTEMATICS OF FISHES

ROBERT H. HAGEN Department of Entomology University of Kansas Lawrence, Kansas 66045

75

Copyright 9 1997 by Academic Press. All rights of reproduction in any form reserved.

76

E. O. WILEY AND ROBERT H. HAGEN

formal statistical assessment of inferences about population histories. The approaches can be divided into three categories: (1) extensions of the standard F statistics used in population genetic studies (Excoffier et al., 1992; Excoffier and Smouse, 1994); (2) extensions of spatial autocorrelation methods (Bertorelle and Barbujani, 1995); and (3) cladistically based tests of geographic associations (Slatkin and Maddison, 1989; Templeton et al., 1992, 1995). In addition to theoretical work, empirical studies are also needed to assess the utility and robustness of assumptions and methods. This chapter uses phylogenetic methods to address both inter- and intraspecific variation among sand darters within a single hierarchical framework. The chapter begins with a brief account of cytochrome b and its relevance to the study of inter- and intraspecific variation. The chapter then describes sand darters, a small group of North American percid fishes, before moving on to the results of the study.

A. Cytochrome b Analysis of mitochondrial DNA (mtDNA) sequence variation has become a well-established tool for studying fish evolution (reviewed in Meyer, 1994a). For this study, the authors chose to sequence a portion of the cytochrome b gene. Because the cytochrome b gene is a well-characterized gene that codes for an evolutionarily conservative protein, it has been used in a large number of systematic and population studies. The availability of polymerase chain reaction (PCR) primers that reliably amplify portions of the gene (Irwin et al., 1991), ease of aligning sequences from different species, and the ability to compare results from other studies all contribute to this popularity. Graybeal (1993) and Meyer (1994b) have issued cautions about the uncritical use of cytochrome b sequences in systematic studies. However, most of the difficulties appear at high levels of divergence, when widely separated taxa are included in the analyses. Krajewski and King (1996), using data from a series of phylogenetic studies on cranes (Gruidae), found that cytochrome b sequences yielded consistent results even with uncorrected divergences of up to 11%. Most studies have used cytochrome b sequences for studies at lower taxonomic levels, including studies not reviewed by Meyer (1994b) on Rivulus (Murphy and Collier, 1996) and Gambusia (Lydeard et al., 1995). The usefulness of cytochrome b sequences for intraspecific studies is more likely to be limited by lack of variation, although there is no obvious reason why the amount of variation should be less than for any other mitochondrial region. In a comparison of restriction fragment polymorphism with partial cytochrome b se-

quences, Birt et al. (1995) found comparable levels of mitochondrial variation within Mallotus villosus (Atlantic capelin) population samples from both techniques. Cytochrome b sequences have been used to detect intraspecific variation in five nominal species of rainbow fishes (Melanotaenia: Zhu et al., 1994), in three species of South American rodents (Patton et al., 1996), in the Atlantic cod (Gadus morhua: Carr et al., 1995), and in the Pacific sockeye salmon (Oncorhynchus nerka: Bickham et al., 1995).

II. Systematics of Sand Darters Percidae comprises some of the more familiar Eurasian and North American freshwater fishes, including the yellow perches (Perca), walleyes and saugers (Stizostedion), the ruffes (Gymnocephalus), the North American darters (Crystallaria, Percina, and Etheostoma), and two darter-like European genera (Zingel and Romanichthys). Darters are the largest percid group with approximately 164 described species distributed throughout eastern North America (Mayden et al., 1992). Sand darters consist of six species of small (a maximum of 50-60 mm standard length), translucent, insectivorous predators that live in clear streams, usually over sand bottoms. They typically bury into the sand and await their prey. Two typical species are shown in Fig. 1. Prior to Simons (1991, 1992) and Wiley (1992), seven species of percids were considered sand darters and placed in their own genus, Ammocrypta (Williams, 1975). One species, the crystal darter (Crystallaria asprella), was shown to be the sister group of Per-

FIGURE 1 Two members of Etheostoma (Ammocrypta): (a) E. beanii and (b) E. bifascia. From Williams (1975); reproduced with permission of the author and the Bulletin, Alabama Museum of Natural History.

T

77

6. mtDNA Sequence Variation among Sand Darters cina+Etheostoma (Simons, 1992; Wiley, 1992). The remaining species were shown to be related to species well embedded in Etheostoma (Simons, 1992), specifically to darters of the subgenera Ioa (monotypic: Etheostoma vitreum) and Boleosoma (five species including the common johnny darter, E. nigrum). Thus, Ammocrypta in the strict sense (s.s.) is now regarded as a subgenus of Etheostoma. Williams (1975) recognized two species groups within Ammocrypta s.s.; the E. beanii group and the E. pellucidum group (Fig. 2a). The E. beanii group comprised three species. Etheostoma beanii (Jordan) inhabits the Gulf Coastal Plain from the Hatchie River, southwest Tennessee, south along eastern tributaries of the Mississippi River to Lake Pontchartrain, Louisiana, and south and east to the Tombigbee and Alabama rivers of Alabama (Stauffer, 1980a; Fig. 3). Etheostoma bifascia (Williams) is distributed along Gulf Coast drainages in southern Alabama and western Florida from the Perdido River east to the Choctawhatchee, with possible introduction to the Apalachicola River (Stauffer et al., 1980; Fig. 3). Etheostoma clarum (Jordan and Meek) is sporadically distributed from the Neches and Sabine rivers in Texas north through the Mississippi Valley to Minnesota and Wisconsin, with populations in the Green and Cumberland river drainages of Kentucky (Stauffer, 1980b; Fig. 4). The E. pellucida group also comprised three species. Etheostoma pellucidum (Agassiz) was the northern species of the group and is found throughout the Ohio river basin south to western Kentucky and north to the southern margin of Lake Huron, around Lake Claire, and Lake Erie, with a disjunct population in the central tributaries of the St. Lawrence-Lake Champlain drainage (Hocutt, 1980b; Fig. 4). Etheostoma vivax (Hay) is

distributed from the Trinity River basin of eastern Texas, east to the Pascagoula River drainage of Mississippi, and north along the major tributaries of the Mississippi River to southern Missouri and western Tennessee and Kentucky (Stauffer and Hocutt, 1980; Fig. 4). Etheostoma meridianum (Williams) occupies the Tombigbee and Alabama rivers and their tributaries in Mississippi and Alabama, immediately adjacent to the southeastern range of E. vivax (Hocutt, 1980a; Fig. 4). William's (1975) recognition of two groups of sand darters was largely intuitive, i.e., not based on synapomorphic characters. Simons (1992) analyzed the relationships among members of the group with phylogenetic methods using a number of different morphological characters and arrived at a different hypothesis (Fig. 2b). He hypothesized that E. clarum was the basal member of the clade, removing it from the E. beanii group while maintaining the E. pellucidum group sensu Williams (1975). Although Simons (1992) hypothesized that E. meridianum and E. pellucidum were sister species, he acknowledged that support for this hypothesis was weak and that recognition of the three species as closest relatives rested on a single character. The most recent attempt to understand the relationships of sand darters was undertaken by Shaw et al., (1997) using morphology and allozyme data. They removed E. pellucidum to a more basal position, between E. clarum and the remaining four species (Fig. 2c), and hypothesized that E. vivax was the sister of E. beanii + E. bifascia. This chapter presents a new level of analysis of the sand darters, based on comparison of mitochondrial DNA sequences. Its objectives are threefold: (1) to further test the three different hypotheses of sand darter

t t<<,:t <<,.~

I

I

I

I

1o,+'

<4" <<,." <<,.'><<9

LIJ I

Io

FIGURE 2 Threeprevious hypotheses of the interrelationships of sand darters of Etheostoma(Ammocrypta): (a) Williams (1975),(b) Simons (1992),and (c) Shaw et al. (1997).

78

E. O. WILEYAND ROBERTH. HAGEN

relationships using molecular characters, (2) to test the utility of mitochondrial DNA sequence data for inferring relationships among populations of E. beanii and E. bifascia, and (3) to see how well the genetic structure of these populations corresponds to their geographic distribution and likely histories of vicariance. A less immediate objective is to explore the relationship between the species-level biogeography of southeastern fishes (Wiley and Mayden, 1985; Swift et al., 1986) and the intraspecific patterns of their component populations (e.g., Avise, 1992; Templeton et al., 1995).

Uncertain bases (marked "?") in individual sequences were assigned the same base found in other individuals of the same species or population. Because fewer than 2% of nucleotides were scored as uncertain, this conservative strategy had little to no effect on assignment of individuals to haplotype classes. Haplotypes were analyzed, alone and together, with morphological data taken from Shaw et al. (1997) using PAUP 3.1.1 (Swofford, 1993). A list of morphological characters, organized by species, is shown in Appendix II.

IV. Results III. Methods and Materials Specimens were collected in the field and immediately frozen in liquid nitrogen. Specimens examined are listed in Appendix I. Exact localities are available from E. O. Wiley. Tissues were stored at - 70 ~C until dissected. Approximately 0.1 g of tissue was dissected, and DNA was extracted from freshly frozen tissue by standard chloroform/phenol methods (Maniatis et al., 1982). PCR (Saiki, 1990) was used to amplify a 425-bp region that included approximately one-third of the N-terminal end of the mitochondrial cytochrome b gene and a portion of the adjacent glutamine tRNA gene (Irwin et al., 1991). Primers L14725 (5' CGAAGCTTGATATGAAAAACCATCGTTG 3') (Paabo, 1990) and H15149 (5' AAACTGCAGCCCCTAGAAATATTTGTCCTCA 3') (Kocher et al., 1989) were used. The thermal profile was 94~ sec, 55~ sec, and 70~ 2 min 30 sec, with a 4-sec extension for 30 cycles. Amplification products were separated by electrophoresis on NuSieve (FMC) agarose gels. The band containing the amplified DNA was excised from the gel, and the agarose was enzymatically digested with QiaQuick (Qiagen). The purified PCR product was manually sequenced with the fmol DNA-sequencing system (Promega) using the same primers used for amplification. Results were visualized by autoradiography and scored by visual inspection. Finally, the 250- 300-bp sequences obtained from each strand were aligned by eye, then spliced to produce a complete 422-bp sequence. Extensive overlap between sequences facilitated splicing and provided a partial check on the accuracy of individual sequence reads. The number of individual fishes sequenced was increased rather than using fewer fishes to obtain complete sequences from both strands. Sequences were deposited in GenBank, under accession numbers U90569-U90581. For phylogenetic and population-level analyses, DNA sequence data were reduced to haplotype data.

Mitochondrial DNA sequences were obtained from a total of 91 individual fish. Thirty-five of these were specimens of E. beanii from four river systems representing three drainages and 34 were E. bifascia from four river systems also representing three drainages. Eleven E. vivax from five drainages; four E. meridianum from its drainage; two specimens each of E. clarum, E. pellucidum, and E. vitreum; and one E. nigrum were also examined. The localities from which specimens of sand darters were taken are shown in Figs. 3 and 4. Complete sequences for haplotypes of each species are shown in Table I, aligned against E. nigrum [selected as the outgroup based on Simons (1992)]. Haplotypes for the four species represented by more than two fish (E. vivax, E. meridianum, E. beanii, and E. bifascia) are shown in Table II. To simplify comparisons, the invariant sites are omitted from Table II. Substitutions were identified at 116 of 422 sites (27%) of which 83 (72%) were transitions. The majority of the transitions (71%) were C ~ T changes. Among E. beanii and E. bifascia, only 21 of the 422 sites varied (5%) and the vast majority of changes (95%) were transitions. Of these, C ~ T transitions accounted for 70% (14) of the total. The sequenced region contains 402 base positions of the cytochrome b gene that code for 134 amino acids. Only 6 amino acid differences (4%) were found among all individuals. All amino acid substitutions were conservative, as would be expected for this highly constrained gene (Irwin et al., 1991). Three of the amino acid substitutions occurred in single individuals within two species (E. vivax and E. bifascia). The others occurred as presumed fixed differences supporting internodes on relatively deep branches of the tree (see Section IV, Table I, underlined codons and A). Silent substitutions occurred in 98 of the codons (73%) across all individuals. Among the recently diverged sister species E. beanii and E. bifascia, 17 codons contained si-

6. mtDNA Sequence Variation among Sand Darters

,

79

.~

E. beanfi

"

f,r"

/

E. bifascia

Distributions and localities sampled of Etheostoma beanii (west) and E. bifascia (east). Small and probably disjunct populations exist for each species (see map). Distributional data from Stauffer (1980a) and Stauffer et al. (1980). Drainage systems are numbered next to locality dots: 1, Yellow River; 2, Blackwater River; 3, Escambia River (one dot represents two collections); 4, Perdido River (two dots); 5, Alabama River (two dots); 6, Tombigbee River; 7, Escatawpa River; 8, Pascagoula River (two dots).

FIGURE 3

lent substitutions (13%). There were no obvious differences among codon or amino acid classes in the relative frequency of substitutions. Only minor differences were encountered in the phylogenetic analyses when differential weighting was employed (see below). The uncorrected frequency of nucleotide differences was used to estimate per site nucleotide substitution rates within species because of the overall low frequency of substitutions (Nei, 1987). Morphological data used in the total evidence phylogenetic analysis were taken from Simons (1992) and Shaw et al. (1997) and the constraints of those data are described in Appendix II. To save space, these data are presented in Appendix II as data for species, not haplotypes. Morphological data used in the analysis are presented in Table III in coded form organized by species. The numbering system duplicates that of the combined data matrix which is not presented. Characters

25, 27, 48, 50, and 52 of Shaw et al. (1997) were deleted because they were not relevant to elucidating relationships among species of Ammocrypta. Unfortunately, allozyme data reported by Shaw et al. (1997) are not combinable with the DNA data and were regretfully left out of the total evidence analysis.

A. PhylogeneticAnalyses Data derived from sequencing were reduced to haplotype vectors (Table II) and analyzed using PAUP 3.1.1 (Swofford, 1993). Four types of analyses were performed. One series of analyses consisted of DNA data and was performed with transversions and transitions equally weighted. Another series was performed in which transversions were weighted by a factor of three over transitions. A third series was performed using these data combined with morphological data. Finally,

80

E. 0. WILEY A N D ROBERT H. H A G E N 7-~.=&~r~:_,y2,.~:'.,.~,oY;, ?

\

;NC.>--H. ":, ' ,.. .-e'a~ .,,,,-~-

7;-.' ;o

te

."

i..'[t 9

~.,~

E. clarum

E. pellucidum

"9" ~

~ i ~.,~. D I(

9 ~ ~ :~,, " :?~,~" / !l~Vy_,, "7 .....~ ,,,':~. ~i,:,.~,-~>~,

..

E. meridianum

FIGURE 4 Distributions and localities sampled for four species of sand darters. The most northern population of E. pellucidum is thought to be disjunct. Distributional data are from Stauffer and Hocutt (1980), Stauffer (1980b), and Hocutt (1980a, b). Ranges are outlined. Localities sampled: black dots, E. meridianum; diagonal striped dots, E. vivax; horizontal striped dot, E. clarum; vertical striped dot, E. petlucidum.

a series of analyses was performed by subsampling individuals to see if sample size had an effect on the species-level tree. In each case, Etheostoma nigrum was designated as the outgroup species following Simons (1992).

1. Equally Weighted DNA Analyses A series of phylogenetic analyses were performed using the heuristic search option of PAUP 3.1.1. Each

analysis resulted in a group of equally parsimonious trees whose number equaled the maximum number of trees specified for the run. This resulted from the large number of polytomies encountered within E. vivax and within the E. beanii-E, bifascia complex. Exploration of varying numbers of the maximum trees setting showed that all analyses converged on two consensus tree topologies, both derived from 225 phylogenetic trees of 211 steps (CI = 0.678; RI = 0.891; RC = 0.604). The basal branches of each tree are shown in Figs. 5 and 6.

6. mtDNA Sequence Variation among Sand Darters

The relationships elucidated among the E. beanii and E. bifascia haplotypes are identical in both cases and are shown in Fig. 7. Tree 1 (Fig. 5) differs from tree 2 (Fig. 6) in the relationship between E. clarum and E. pellucidum. In tree 1, E. clarum is hypothesized as the sister species of all other Ammocrypta, with E. pellucidum as the next branch up the tree. In tree 2 these species are hypothesized as sister species. Both trees hypothesized similar relationships between haplotypes of E. vivax and E. meridianum, with E. vivax being unresolved. Both trees also hypothesize similar relationships among haplotypes of E. beanii and E. bifascia, portraying a complex mixture of within and between species haplotype relationships (Fig. 7). It should be noted that PAUP did not find both tree topologies; rather, a series of manual branch swaps using MacClade (Maddison and Maddison, 1992) were performed to examine likely alternative topologies, resulting in tree 1. If PAUP had found both topologies, a strict consensus analysis would have collapsed the appropriate nodes into a trichotomy. This final act of consensus was not performed because of results obtained in the total evidence analysis, as presented later. A final analysis was performed to determine the cost of grouping each haplotype within its own lineage (forcing the haplotypes to form a priori species-level lineages), resulting in a consensus tree derived from 100 phylogenetic trees of 214 steps (CI = 0.668; RI = 0.886; RC = 0.592). Thus a penalty of three steps is required in order to group E. beanii and E. bifascia haplotypes into their appropriate species-level lineages.

2. Transversion-Weighted Analyses Weighting transversions by a factor of three over transitions generated 100 equally parsimonious trees of 301 steps. The only difference between these trees and equally weighted trees is in the relationship of E. vivax and E. meridianum, where the haplotypes group into their "proper" species-level lineages (Fig. 8). The consensus topology of E. beanii and E. bifascia haplotype relationships was not affected by differential weighting.

3. Total Evidence Analyses Total evidence analyses were conducted using morphological data combined with the haplotype vectors for each haplotype. There are several caveats in this analysis. First, it was assumed that morphological data represent true species-level variation and that no significant geographic variation exists for these data that would fundamentally alter species-level characters.

81

Second, the authors have not examined the specimens from which they derived the DNA haplotype vectors for these morphological characters. Third, because E. beanii and E. bifascia share one haplotype (B1), this vector was duplicated and one vector was assigned the morphological data associated with E. beanii, (labeled "Bnl"), whereas the other was assigned morphological data associated with E. bifascia (labeled Bil). Fourth, the data matrix presented by Simons (1992) and modified by Shaw et al. (1997) was not designed to ferret out the autapomorphies of each species but to examine the relationships among species. As a result, the matrix is deficient in terminal autapomorphies that would presumably sort out lineages such as E. beanii and E. bifascia. Of course, each species is distinctive, with its own unique array of character differences. However, these have not been sorted out and phylogenetically argued, so they were not used here. For example, it is not clear if the two continuous dorsal fin stripes of E. bifascia are derived relative to the single stripe in E. beanii (Williams, 1975). It is clear, however, that E. beanii and E. bifascia form separate lineages. Thus, the differences between gene lineages and species relationships have not been interpreted as evidence that fewer species are involved in the analysis. Phylogenetic analyses were restricted to a maxim u m of 300 trees. One strict consensus tree (Fig. 9) was generated from 300 equally parsimonious trees of 241 steps (CI = 0.693; RI = 0.903; RC = 0.626). This tree corroborates the hypothesis that E. pellucidum is more closely related to other Ammocrypta than to E. clarum and that E. clarum is the basal member of the subgenus, i.e., the total evidence tree corroborates those relevant parts of the DNA-only tree 1 shown in Fig. 5 rather than tree 2 in Fig. 6. If the analysis is constrained to make E. pellucidum and E. clarum a monophyletic species pair, the result is a tree of 243 steps (CI = 0.687; RI = 0.901; RC = 0.619). The combined evidence consensus tree is identical with regard to the unweighted consensus topology of E. vivax and E. meridianum samples. The combined total evidence consensus tree has the effect of collapsing the relationships among E. beanii and E. bifascia haplotypes as shown in Fig. 7. The explanation for this is simple: there is a conflict between the morphological autapomorphy shared among individuals of E. beanii (character 138-1) and the history of haplotype evolution. This conflict is sufficient to erase all substructure shown in the DNA-only analyses except the basic grouping of B-17, B-18, and B-19, grouped by their unique array of three haplotypes and the pseudoconvergent morphological character 138-1, an autapomorphy of E. beanii.

Complete 422 b.p. Sequence for Etheostorna Speciesa

TABLE I

tRNA (glu)

<

t t

Etheostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150) clarum (KU 23145) clarum (KU 23145) vivax meridianum beanii and bifascia

-10

L

V

R

H

T

K

10

t

D

L

50

A

P

P

N

S

L

P

20

V

S

I

70

60

. . . . . . . . . . . . . . . . . . . . . . . .T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . . . .

L

K

A

I

30

N

N1

40

W

W

80

N

F

Z

90

G

S

L

100

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . . . . . . . . A . . C . . . . . C . A. . . . . . A . . . . . . . . A . . C . . . . . C . .A. . . . . . . . . . T . . . . . . . . C . . C . . A . . . . . . . . A . . C . . . . . C A. . T . . . . . . . . . . A . . . . . A . . . . . T . . . . . T . . C . . C . . A . . . . . . . . A . . C . . . . . AC . . T . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T . . . . . . . . C . . . T . . . . . . . . C . .

. . C C

. . . . . . . . w . . T . . y . . . . . T . . . . . . . . C . . C . . A . . G . . . . . A . . C . y . . . Cr . . . . . . . . . . . . . . . . . . . . . . . . . T . . . . . . . . C . . C . . A . . G . . . . . A . . C . . . . . C . . A. . . . . . . . . . . . . . T . . . . . y . T. . . . . . . . . C . . C . . T . . G . . . . . A . . C . . . . . C . . . . . . G

L

C

L

110

I

3

T

120

Q

I

L

130

T

G

L

140

F

L

A

M

150

H

Y

T

160

CTAGGTCTTTGCTTAATCACCCAGATCCTCACCGGACTCTTCTTGGCCATACACTATACC . . . . .C . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . . . . . TC . . . . T . . T . . . . . . . . G . . A . . C . . . . . T C . A . . . . . G . . . . . C . . . . . . . . C . . . . . TC . . . . T . . T . . . . . . . . G . . A . . C . . . . . T C . A . . . . . G . . . . . C . . . . . . . . . . . . . . . C . . . . T . . T . . . . . . T . A . . A . . C T . A . . . C . A . . . . . G . . . . . C . . . . . . . . . . . . . . .C . . . . T . . T . . . . . . T . A . . A . . C T . A . . . C . A . . . . . G . . . . . C . . . . . G . . m . . . . . y y . . . . y . . T . . A. . . . . . . . r . . C . . y . . y C .. A. . . . I . . . . . C . . . . . G . .m . . . . . T C . . . . T . . T . . A . . . . . . . . A . . C . . T . . . C . A . . . . . G . . . . . C . . . . .G. . C . . . . . y C . . G y y . . T . . A . . y . . y . . A . . T . . y . . . . . . . . . . . G . . . . . C . . .

A E theostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150)

L

GCACTTGTTGACCTCCCTGCCCCCTCAAATATTTCGGTATGATGGAATTTTGGTTCCCTT

L Etheostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150) clarum (KU 23145) clarum (KU 23145) vivax meridianum beanni and bifascia

>

S

TTCAACTACAAAAACCTCTA ATGGCAAGCCTCCGAAAAACCCACCCCTTACTAAAAATTGCAAACAAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . . . . . .G . . . . . . . . . . . . .G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . . . . . . G . . C . . . . . . . . . . . . . . . . .G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T . . . . . . . . . . . . . . . . . .C . . . . . . . . . . . . . . . . . G . . . . . . . . . . . . .G . . . . . y . .. . . . . . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . . . . . .G . y . . . G . . . . . . . G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . . . . . .G . . . . . . . . . . y . .~ . . y . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . C . C . . . . . . . . . . . . . . . G . . A

Etheostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150) clarum (KU 23145) clarum (KU 23145) vivax meridianum beanni and bifascia

Cytochrome B M A

170

GCCG . . . . . . . . . . A. . . A.

D

I

A 180

T

A

F

S 190

S

V

A 200

H

I

C 210

R

D

V

N

Y

G

220

ATATTGCCACAGCCTTTTCATCTGTTGCTCATATTTGCCGGGACGTAAACTACGGA . . . . . . . . . . . . . T . . . . . . . . . . . . . . . . . C . . . . . . . . A . . T . . . . . . . . G. . . . . . . . . . . . . . . T . . . . . G . . . . . . . . . . . C . . . . . . . . A . . T . . . . . . G. . . . . . C . . G . . C . . . . . C . . . . . A . . A . . A . . C . . C . . . . . . . . . . . . . .C . . . . . .C . . G . . C . . . . . C . . . . . A . . A . . A . . C . . C . ? . . ? . . . . . . . .C . .

. . . . . . . . . . . . .

clarum (KU 23145) clarum (KU 23145) vivux meridianurn beanni and bifascia

. . A. . . . . C . . A. . . . . C . . A. . y . .C . . A . . . . . C . . A. . . . . C

W

Etheostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150) clarum (KU 23145) clarum (KU 23145) vivax meridianurn beunni and bifasciu

230 T G A . . G . . G . . .

A A A A A

R

. . . . .

N

. . . . .

C . . . . . C . . . . . A . . A . . A . . C . . C . . . . . A . . . . . . . C . . . . . . . C . . . . . C . . . . . A . . A . . A . . C . . C . . . . . A . . . . . . . C . . . . . . . C . . . . . C . . . . . A . . A . . A . . . . . y . . . . . . . . y . . w . .C . . . . . . C . . . . . C . . . . . A . . A . . . . . . . . C . . . . . . . . . . . T C . . . . . . . . C . . . . . C . . G . . A . . A . . . . . C . . C . . . . . A . . . . . w . .C . . . . . .

I

4

H

A

N

G

A

S

F

F

F

I

C

I

Y

L

5

240 250 260 270 280 C T T A T C C G T A A T A T T C A T G C C A A C G G T G C A T C C T T T T T C T T C A T C T G C A T T T A C C T G

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . A . . T . . . . . C C . C . . . .. . . . . . . C . . . . . . . . . . . . . . . . . . . . . . . C . . TT . A . . . . . . . . T . . C . . C C . y . .. .. . . . . . . C . . . . . T . . C . . y . . . . . y . . . . . C . . T A . . . . . . . . . . T . . C . . C C . . . . . . . . . . . . . C . . . . .T . . C . . . . . . . . T . . . . . C . . T A . . . . . . . c .. T .. c .. c c . . . . . . . . . . . . . . . . . . . A . . C . . . . . . . . T . . T . . y . . T A . .

I

G

R

29 0

G

L

Y

300

Y

G

S

310

Y

L

Y

320

K

E

T

W

330

N

I

G

340

CACATTGGACGAGGCCTGTACTACGGGTCCTACCTTTATAAAGAAACATGAAATATTGGA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T . . . . . . . . C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T. . ? . . . . . C . . G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .G . . . . . . . .T . . C . . . . . . . . . . . . . . . . . G . . . . . . . . C . . . . . . . . . . . . . . . . . . . . A . . . . . . . . T . . C . . . . . . . . . . . . . . . . . G . . . . . . . . C . . . . . . . . . . . . . . . . . . . .G T . A . . . . . T . . C . . G . . T . . A . . C . . . . . G . . G . . . . . C . . . . . . . . . . . . . . . . . . . . G T . A. . . . . T . . C . . G . . T . . A . . C . . . . . G . . G . . . . . C . . . . . . . . T . . . . . . . . . . . r . . r . . y . . T . . y . . r . . . . . . . . . . . . . . r . . . . . r . . C . w . . . . . . T . . . . . . . . . . .GT . . . . . . .T . . C . . G . . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . T . . . . . . . . . . . r . . . . . . . . T . . C . . A . . . . . . . . . . . . . . . . . G . . . . .r C . . . . .

V

Etheostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150) clarum (KU23145) clarum (KU 23145) vivax meridianurn beanni and bifascia

I

. . . . .

. . . . . T . . C . . C C . C . .. .. . . . T . . C . . . . . . . . . . . . . . . . . . . . . .A. . . . . . . . . . . . . . . T . . C . . C C . C . .. .. . . . T . . C . . . . . . . . . . . . . . . . . . . . . .A . . . . . . . . . . . . A . . T . . . . . C C . C . . . .. . . . . . . C . . . . . . . . . . . . . . . . . . . . . . . C . . TT . A

H Etheostoma nigrum (KU2 3143) vitreum (KU 24389) vitreum (KU 23144) pellucidum (KU 23150) pellucidum (KU 23150) clarum (KU 23145) clarum (KU 23145) vivax meridianurn beanni and bifasciu

L

. . . . .

V6

L

L

350 360 G T A G T T C T T C T G C . . . . . . . . C . . C . . . . . . . . . C . . C . . . G . . G . . C . . C . . G . . G . . C . . C

. . C . .G . . . C . . G . . . . . .r . . . . . . G .

. . yr . C .

L

L

V

M

M

T

A

F

V

G

Y

V

L

P

370 380 390 400 T A C T A G T G A T A A T G A C C G C C T T T G T A G G G T A T G T T C T T C C C

. . T . . . . . . . . . . . . . . . . . . . . . . T . . A . . . . . . . . C . . . . . T . . . . . . . . . . . . . . . . . . . . . . T . . A . . . . . . . . C . . . . . . . . . . . A . . . . . . . . . . . . . . . . . T . . A . . C . . C . . G . . . . . . . . . . . A . . . . . . . . . . . . . . . . . T . . A . . C . . C . . G . . . . C . . C . . . . . . . . A . . . . . . . . . . . . . . . . . . . . A . . C . . . . . A . . . . C . . C . . . . . . . . A . . . . . . . . . . . . . . . . . . . . A . . C . . . . . A . . . . C . . C T . r . . . . . A . . . . . A . . . . . . . . . . . y . . A . . . . . y . . C . . . . A . . C T . G . . . . . A . . . . . A . . . . . . . . . . . C . . A . . . . . C . . C . . . . C . . C y . G. . . . . A . . . . . r . . . . . . . . . . . T . . r . . C . . . . . y . . .

Amino acid substitutions: (1) N D; (2) F S; (3) I V; (4)I L; (5) L M; (6) V I. aAmino acid translation of Cytochrome B partial sequence is given for E. nigrum; underlined codons and superscrips denote nonsynonymous substitutions in other species. For E. beunii, E. bifasciu, E. meridianurn, and E. vivux sequences lowercase letters denote intraspecific variation at that position. The complete list of haplotype variation for these 4 species is given in Table 11. Codes for intraspecific variation: y = C or T; r = A or G; w = A or T; s = G or C; m = A or C.

TABLE IZ Haplotypes Observed in E. vivax (V), E. mevidianum (M), E. beanii and E. bifascia (B) Position

Haplotypes

-17

-12

-9

-6

-3

24

48

57

60

63

66

98

108

114

120

121

125

126

135

138

141

147

150

159

174

201

207

v-1

A

C

G

C

C

T

C

T

T

C

T

T

G

C

T

C

T

T

C

C

G

T

C

G

T

A

T

v-2 v-3 v-4 v-5 V-6 v-7 V-8 M-1 M-2 B-1 B-2 B-3 B-4 B-5 8-6 B-7 B-8 B-9 B10 811 812 B13 B14 815 B16 B17 B18 B19

.

T

. .

'

G

.

G A

. C

G

C

T '

C C

T '

A

.

' .

C C

' '

' '

C C

' '

C

C

C

T

T

C

T

' .

. A A A A A . A A

A A A A A A A . A

. . . . C . .

T

T

C

T

. . C . .

T .

' T

.

.

.

A

T

.

C C C

. ' '

.

c

.

. C

' .

. . '

C

T

T

T

C

.

'

C

'

. ' .

. C C C

. . . . .

A A A A A

C C C . .

. .

A A

. .

C

A

C

C

.

T

.

. .

T T

. .

.

T

.

'

.

. . .

T T T

. . .

.

c

.

T ' ' '

.

' . . T

A A A .

G

C C C

. . . '

C C C C

. .

T T

C C

T

T

C

.

c

Position Haplotypes

216

219

246

270

276

282

303

304

306

309

315

318

333

339

348

351

352

354

357

361

363

375

387

390

396

399

V-1 V-2 V-3 V-4 V-5 V-6 V-7 V-8 M-1 M-2 B-1 B-2 B-3 B-4 B-5 B-6 B-7 B-8 B-9 B10 Bll B12 B13 B14 B15 B16 B17 B18 B19

T

T

T

C

T

C

A

C

G

C

C

A

A

G

A

A

G

G

C

T

G

A

C

A

C

C

A A A

T T T

T

C C C C

A

C C C C C

G

T

C

C C C C C

A

T

C

T

G G A

A A A

G

G 9

C C C

G

A A A A A

G

C

G G G

T T C

G

C

T T

C

A

A A A

9 T

G

T T T

9

C

G

C

A A C

T

G

G

T

A

T

A

Positions that did not v a r y a m o n g these h a p l o t y p e s are omitted; positions w i t h i n the sequence c o r r e s p o n d to those given in Table I.

A

9

A A A

T

A Matrix of Morphological Characters Organized by Species a

TABLE III Species E. nigrum E. vitreum E. clarum E. pellucidum E. vivax E. meridianum E. beanii E. bifascia

117 0 1 1 1 1 1 1 1

118 0 0 0 0 0 0 1 1

119 0 0 0 0 0 0 1 1

120 0 1 1 1 1 1 1 1

121 0 1 1 1 1 1 1 1

122 0 0 1 1 1 1 1 1

123 0 0 1 1 1 1 1 1

124 1 1 0 0 0 0 0 0

125 0 1 1 1 1 1 1 1

126 0 0 0 1 1 1 0 0

Species E. nigrum E. vitreum E. clarum E. pellucidum E. vivax E. meridianum E. beanii E. bifascia

131 1 1 0 0 0 0 0 0

132 1 1 0 0 0 0 0 0

133 0 1 1 1 1 1 1 1

134 0 0 1 1 1 1 1 1

135 0 1 1 1 1 1 1 1

136 0 0 0 0 0 0 1 1

137 0 0 0 0 0 0 1 1

138 0 0 0 0 0 0 1 0

139 0 0 1 0 0 0 1 1

140 0 0 1 0 1 0 1 1

127 0 0 1 1 1 1 1 1

128 0 0 0 1 1 1 1 1

129 0 0 0 0 0 0 1 1

130 0 0 0 1 1 1 1 1

"See Appendix II for a description of characters.

"T" +8

T

3

I'

LJ

L L! 13

E. bifascla

1 2

4

7

2

2

8

1

l 7

1

=4

~

1

1

10

4 1

I

I 52

4

13

3

7

LJ

5 18 10

'

t

1 5

~

1

11

=4 () 4

8 4

1

1

FIGURE 6 Basal part of tree 2 of two consensus trees generated by analysis of equally weighted D N A sequence data. See legend to Fig. 5 for definition of abbreviations.

00

I

O00

@ @ ID 0 0 0

0 0 0 0 0

r

III

f

9

9 @

I ..,

FIGURE 5 Basal part of tree I of two consensus trees generated by analysis of equally weighted D N A sequence data. The crown is shown in Fig. 7. In this and Figs. 6 - 9 , terminal units are haplotype vectors that represent one to several individuals. N, Etheostoma nigrum; Vt, E. vitreum; C, E. clarum; P, E. pellucidum; V, E. vivax; M, E. meridianum; B, E. beanii and E. bifascia. Dark bars are tagged with the n u m ber of transversions and transitions that show homoplasy along a particular internode. Open bars are tagged with the number of unique (CI = 1.0) transitions. Open circles are tagged with the number of unique transversions. A u t a p o m o r p h o u s characters are not plotted.

4 4 E. bifaseia E. beanii

FIGURE 7 Crown of D N A consensus trees 1 and 2. Relationships among haplotypes of E. beanii ( 9 and E. bifascia (o) are common to the consensus trees shown in Figs. 5 and 6. Note that the haplotypes do not sort into a priori species lineages.

6. mtDNA Sequence Variation among Sand Darters

I 1I

ried out on the sequence level and thus their contribution to the analyses would amount to using the same information twice. The authors note, however, that this class of changes includes amino acid substitutions that corroborate the monophyly of Ammocrypta [two nonsynonymous substitutions (Table I)] and the monophyly of E. vixax, E. meridianum, E. beanii, and E. bifascia [one nonsynonymous substitution (Table I)]. Three nonsynonymous substitutions were also found within species (Table I).

"3 =1 )1

3

t

87

8 1

5. Effects of Sampling Size

FIGURE 8 A portion of the topology of a consensus tree generated by weighting transversions three times transitions. Topologies (but not necessarily character distributions) of other parts of the tree are identical to those of consensus trees I and 2 shown in Figs. 5, 6, and 7.

4. Nonsynonymous Codon Substitutions This class of characters does not appear in any of the phylogenetic analyses because the analyses were car-

Because systematic studies using DNA sequencing are frequently undertaken using one or a few specimens for each taxon, the authors were interested in the effects of sample size on the phylogenetic results generated. To test these effects, 10 replicate phylogenetic analyses using a single individual for each of the ingroup taxa were performed. An exhaustive search was implemented. Tree lengths varied between 150 and 166

~, ~" ~, ~, ~, ~, ~, ~, ~, 138-1

8-1 4

4

'

-;12

"5

7

()4

"1

.

126-1

i

~

}

118..1 119,-1 120-1 136-1 137-1

138-1

8

4

1

26-1

14o-1

130-1

"" c-~

11 18 11

-----

--

122.1 123-1 124-o 125..1 131.o

132.o 134..1

FIGURE 9 A total evidence analysis using equally weighted DNA characters and morphological characters. Character annotations are similar to previous figures, except for the morphological characters. Dashes are labeled with the specific morphological character that was unique (CI = 1.0), whereas morphological characters found to be homoplasous are denoted with an "X."

TABLE IV

Distribution of Haplotypes among E. beanii and E. bifascia Samples Haplotype Sample

Species

beanii

Drainage

B-1

B-2

B-3

Pascagoula .

Tombigbee

3

Subtotal

.

9

3

0

Perdido

0

9

9

0

Yellow

1

Blackwater

2 3

2

9 9

2

1

1

0

9

1 9 0

9 0

B-16

B-17

0

0

0

1

3

.

.

.

1

3

0

0

0

3

2

2

6

9 16

11 1

1

35 11 12

.

.

.

6

9 0

size

6 9

9 1

1

.

. 9

3

B-19

. 9

1

.

3

B-18

12

4

1

3 4

B-15

.

9

10

B-14

12 .

.

0

B-13

. .

.

9

B-12

.

1

1

B-11

. .

10

2 .

1

B-10

1

9 9

B-9

.

2

0 .

B-8 .

. 9

. 9

B-7 .

. 9

Escambia

Total

B-6

.

.

Alabama

bifascia

B-5

.

Escatawpa

Subtotal

B-4

3

2

5 2

0

0

0

34 69

6. mtDNA Sequence Variation among Sand Darters steps whereas rescaled consistency indices varied between 0.765 and 0.816. Skewness (G1) varied between -1.44 and -1.63. Thus, one would judge all the results to carry a significant phylogenetic signal using the skewness criterion of Hillis (1991) and Hillis and Huelsenbeck (1992). The 10 replicates resulted in two tree topologies. Eight of the 10 replications found DNA tree 2 (Fig. 6) when all individuals were analyzed. Two of the replications found this tree plus an additional tree that asserts that E. meridianum is the sister species of the E. beanii-E, bifascia pair. None of the results duplicated the sequential basal positions of E. clarum and E. pellucidum shown in tree I (Fig. 5). Three additional analyses were produced using three randomly picked E. beanii and E. bifascia, and two each of the other members of the ingroup (because of haplotype diversity this amounted to all other members of the ingroup except E. vivax). Branch and bound analyses were employed to ensure that the most parsimonious tree or set of trees was found. All three replicates were consistent with the tree shown in Figs. 6 and 7, including one analysis that grouped an E. beanii with individual E. bifascia.

B. Intraspecific E v o l u t i o n

and Biogeography 1. E. beanii and E. bifascia A total of 19 mitochondrial haplotypes were detected among the 69 individual E. beanii and E. bifascia sequenced. There was very little overlap in the distribution of these haplotypes among drainages (Table IV). Only 3 haplotypes were found in more than one drainage system: among E. bifascia, haplotypes B-1 and B-9 appeared in the Yellow and Blackwater rivers; and among E. beanii, haplotype B-17 appeared in the Pascagoula and Escatawpa rivers. In both cases the rivers share a common estuary (Fig. 3, see numbers in legend to identify river drainages). The narrow geographic distribution of mitochondrial haplotypes among E. beanii and E. bifascia samples indicates that there is little contemporary gene flow between populations occupying separate river systems. Nucleotide diversities among these samples were estimated as 0.0033 for E. beanii and 0.0028 for E. bifascia using the formula of Nei (1987). These estimates are low, but within the range reported for other species and genes (Nei, 1987; Avise, 1994). Genetic distance between the two species, estimated from these diversities, was 0.0062. For the second level of analysis, genealogical relationships among haplotypes were added to geographic data. Haplotypes from both species were considered to-

89

gether. Genealogical relationships were inferred from patterns of sequence variation among haplotypes using two methods. The first was the parsimony-based phylogenetic analysis described earlier, which yielded the consensus tree shown in Fig. 7. The haplotypes found in E. beanii and E. bifascia were not separated on this tree. The most basal split occurred among the three haplotypes found only in the Escatawpa and Pascagoula rivers (B-17, B-18, and B-19), which were the westernmost drainages sampled, and all other haplotypes. The other resolved node within this section of the tree, comprising B-1 through B-11, has no obvious biogeographical interpretation: these haplotypes were found in rivers to the east of the Escatawpa and Pascagoula. Clearly, the interspecific phylogenetic tree lacks resolution at the intraspecific level for E. beanii and E. bifascia. For such closely related haplotypes, construction of an unrooted, minimum spanning network provides an alternative method for genealogical inference (Templeton et al. 1992; Excoffier and Smouse, 1994). In this approach, haplotypes are represented as nodes connected to one another by the minimum number of discrete mutational steps. A minimum spanning network for the E. beanii and E. bifascia haplotypes is shown in Fig. 10 (note figure legend for correct spatial relationships among drainages). The Escatawpa and Pascagoula haplotypes (B-17 through B-19) can be used as examples of the principles used in its construction. In this network, haplotypes B-18 and B-17 are connected by a single line segment which represents the single nucleotide substitution that distinguishes them (C ~ T at position 66; Table II). Haplotype B-19 differs from B-17 by two other substitutions (G ~ A at-9 and C ~ T at 399; Table II), which are represented by two line segments. The filled circle separating these two segments may be regarded as an unobserved intermediate haplotype. Together, the three line segments that separate haplotypes B-18 and B-19 represent the three nucleotide substitutions that distinguish this pair. An important distinction between the network shown in Fig. 10 and the tree shown in Fig. 7 is that extant haplotypes in the network, such as B-17, can serve as internal nodes and have multiple branches. These haplotypes may be interpreted as surviving ancestral haplotypes that may have spawned a series of descendant haplotypes. Although the network does not, by itself, imply any ancestor-descendant directionality, support for the basal status of B-17 relative to B18 and B-19 is provided by the observation that the root of the network, as shown by the phylogenetic tree, requires that B-17 be considered basal and by the fact that the substitutions found in the latter two haplo-

90

E. 0. WILEY A N D ROBERT H. HAGEN

Yellow & Blackwater

Escambia

"

\\

Perdido

"1

.

~

.

.

.

......:~i~i~!:i~~~i'~iiiiiiii i~i!i~:~~'"i.' i~ii}i Tombigbee

~ ~ " ~ \ ~ , , ~

~

\ , ~ , ~ \ . ~ ~_...~/'~\\>!"

~iil Alabama .....

\\\\

Perdido ~i~i~::~ii~::~::i~i~i~i ;i i i i i i~::i~::~:~::~i~i~i~::~::i~;~@~::~;~;@~f:~f:~@~@~~~ ::i::i::i~::F: i',i i i~i~

ii,i,iii',iiiii!ii!!!!iiii!i!ii!',!i,i',',i;;

i~;~i~i~iii~i~;~i~!~i~i~i~!ill~i~i~i

Escatawpa

I iiiiiiiiilE. beanii

!ii i ',',',i

& Pascagoula

~~

E. bifascia

FIGURE 10 A network of haplotypes observed in E. beanii and E. bifascia. Dots represent unobserved haplotypes one mutational step removed from other dots and/or observed haplotypes. The root occurs between haplotypes B-17 and B-12. Drainages from which haplotypes were observed are overlaid on the network. Note that for graphic reasons the geographic positions of drainages are not accurate. The actual spatial relationships among the drainages from west to east are: Pascagoula, Escatawpa, Tombigbee, Alabama (Tombigbee + Alabama = Mobile Bay drainage), Perdido, Escambia, Blackwater, Yellow rivers.

types are all unique within the set of E. beanii/E, bifascia haplotypes. The root of the entire E. beanii/E, bifascia clade lies between haplotypes B-17 and B-12, based on the reconstructed ancestral character state vector derived from the interspecific phylogenetic tree shown in Fig. 7. Of these two haplotypes, B-17 is one step from the ancestral node reconstructed by the parsimony analysis whereas B-12 is three steps removed. Another feature of the network in Fig. 10 is the closed loop connecting haplotypes B-1-B-3-B-2-B9. The presence of such loops indicates ambiguity among alternative, equally short, pathways connecting the

haplotypes (Excoffier and Smouse, 1994). Two circumstances could produce this condition: either one of the haplotypes arose from independent mutations in two different lineages (i.e., convergence) or one of the line segments represents a direct evolutionary path that did not actually occur (i.e., a case of back mutation resulting in character reversal at a particular site). As examples, haplotype B-2 may have been derived independently from B-9 and B-3 (convergence), or haplotypes B-1 and B-3 may differ by three mutations rather than one (transitions from C to T at positions 147 and 282, followed by reversal to C at 147; Table II). The rooted version of the network shown in Fig. 10 provides more biogeographic information than the haplotype tree. Haplotypes common to both species (B-l) or with descendants in both species (B-12) are near the middle of the network and have many descendants. Haplotypes represented by single individuals occur at the tips of the branches, as would be expected if these represent recent divergences. As in the tree, the three Escatawpa and Pascagoula haplotypes are clearly distinct, but co-occurring haplotypes in other drainages tend to be clustered on the network. There is an overall west-to-east pattern of haplotype distributions and most haplotypes are confined to single drainages (e.g., Perdido River populations) or drainages that share a common bay (e.g., Escatawpa and Pascagoula populations). This congruence would be expected of populations that have experienced little gene flow over a long period of time, sufficient for new haplotypes to evolve in situ. The authors note that while gene flow is lacking, the rooted network apparently does contain some haplotype relationships that imply historical connections between drainages. For example, the Escambia River is linked to both the Yellow and Blackwater and the Perdido through a series of ancestral/descendant haplotypes. Some of these relationships are probably younger than others. For example, the relationship between B-3 and B-11 suggests a relatively recent gene flow event because B-11 is far removed from any relationship with other Perdido haplotypes. 2. E. vivax and E. meridianum

Eight haplotypes were detected among 11 E. vivax individuals sequenced. The V-2 haplotype occurred in fish from the geographically close samples taken from the Mississippi and St. Francis rivers; the remaining haplotypes appeared only in single drainages. Two haplotypes were observed among th e four E. meridianum individuals sequenced (Table V). For these species, the phylogenetic trees based on equally weighted substitutions (Figs. 5 and 6) and the

6. mtDNA Sequence Variation among Sand Darters TABLE V

91

Distribution of Haplotypes among E. v i v a x and E. meridianum Samples Haplotype

Species

Drainage

M-1

M-2

V-1

V-2

V-3

V-4

V-5

V-6

V-7

V-8

meridianum Subtotal vivax

Tombigbee

3 3

1 1

0

0 1 1 .

0

0

0

0

0

0 1

1

1

1

Mississippi St. Francis Ouachita Pearl Sabine

1

9 2

0

Subtotal Total

0

1

minimum spanning network (Fig. 11) yield identical information. The eight E. vivax and two E. meridianum haplotypes resolve into five distinct haplotype lineages, none of which can be identified as basal. Each of the haplotype lineages are composed of individuals from the same or interconnected drainages. Greater divergence among haplotypes does limit the effectiveness of the network approach to genealogical reconstruction. When basal haplotypes are missing from the array (due to extinction or insufficient sampling), most of the network reduces to a tree,

2

1

1

1

2

2 2

1

Sample size 4 4 2 2 3 2 2 11 15

although information may still be obtained at the branch tips (Templeton et al., 1992). The small sample sizes representing these taxa limit the biogeographic analyses that can be made. The estimated nucleotide diversity among E. vivax was four times higher than for E. beanii and E. bifascia: 0.0142. However, the geographic area represented by these samples was also considerably larger, which could also account for the difference.

V. D i s c u s s i o n Ouachita

A. P h y l o g e n e t i c A n a l y s i s

....~:~:~!i!ii". ..... ................. ~ii!ii!iiiiii?

9 @

Tombigbee .................. ..:!iiiT

Sabine

. .........

Mississippi & St. Francis

Pearl

FIGURE 11 A network of haplotypes observed in E. vivax and E. meridianum. Dots represent unobserved haplotypes one mutational step removed from other dots a n d / o r observed haplotypes.

The major difference between the DNA-only analyses and those based on morphology and allozymes presented by Shaw et al. (1997) concerns the phylogenetic placement of E. pellucidum and the E. vivaxE. meridianum species pair. Shaw et al. (1996) hypothesized that E. pellucidum was the sister group of all Ammocrypta except E. clarum, a hypothesis identical to DNA tree 1 (Fig. 5), but not to DNA tree 2 (Fig. 6). If only a few individuals of each species had been sampled, the authors would have consistently drawn a conclusion at variance with the morphological and allozymic data unless they employed an approach minimally incorporating the DNA and morphological evidence. The authors' DNA-morphology tree favors the basal placement of E. clarum (Fig. 5) rather than a monophyletic group comprising E. clarum and E. pellucidum (Fig. 6). The authors consider this combined analysis tree (Fig. 9) to be their best estimate of the phylogenetic relationships among sand darters in this study because of the principle of total evidence (Kluge, 1989) and thus conclude that Shaw et al. (1997) correctly placed E. clarum and E. pellucidum. Regarding

92

E. O. WILEYAND ROBERTH. HAGEN

E. vivax and E. meridianum, the authors consistently arrived at the hypothesis that this species pair is monophyletic regardless of the data and weighting scheme used (Figs. 5, 6, and 9). Given that morphological data used by Shaw et al. (1996) as well as DNA data were used, the authors suggest that this is a more robust phylogenetic hypothesis than the alternative hypothesis that E. vivax is the sister to the E. beanii-E, bifascia pair. The biogeographic history implied by the total evidence phylogeny also provides some corroboration. A biogeographic pattern of a Mobile Bay drainage endemic being closely related to a species found west and north of the Mobile Bay is replicated in both the Hybopsis longirostris species group (Wiley and Titus, 1992) and the Lythrurus roseipinnis species group (Wiley and Siegel-Causey, 1994).

B. Biogeography of E. vivax and E. meridianum E. vivax is a relatively widespread species and it is not surprising that the populations sampled displayed a diversity of haplotypes. Although two of the E. vivax samples were geographically close (upper Pearl River drainage) to the samples of E. meridianum, they were not particularly close to that species in terms of sequence similarity. The authors hesitate to speculate as to the cause of the diversity observed in E. vivax haplotypes and suggest that a broader survey, including greater sample sizes and better geographic coverage, is needed.

C. Biogeography of E. beanii and E. bifascia

Despite the relative proximity of the rivers from which E. beanii and E. bifascia samples were collected, there was no indication of ongoing gene flow between populations within species as evidenced by haplotypes shared among drainages. The few exceptions were not sufficient to obscure the correlation. AMOVA analysis (Excoffier et al., 1992) does not contribute much additional information because there is little overlap among haplotype distributions. AMOVA may be more appropriate for situations where current gene flow plays a more significant role between populations within species. In contrast to clear differentiation among river drainage systems within species, relationships between the two species were obscure. Clearly, the gene tree shown through parsimony analysis and the haplotype network was not congruent with relationships on the species level, i.e., neither the gene tree nor the haplotype network supports the conclusion that E. beanii and

E. bifascia are separate species, but both morphological (Williams, 1975) and allozyme data (Shaw et al., 1996) leave no doubt that E. beanii and E. bifascia are separate lineages ("good" species). The authors suspect that this incongruence is due to the retention of ancestral haplotypes subsequent to speciation followed by mutational events derived from these haplotypes isolated in separate drainages. Such a scenario would not be expected to mirror evolution on the morphological or allozymic levels. This speculation is based on three lines of evidence. First, when the haplotype network was inspected, the authors observed that the haplotype shared by both species (B-l) is relatively far removed from the root of the network as shown by the phylogenetic analysis and that one found only in E. bifascia (B12) is between the shared haplotype (B-l) and the ancestral node (Fig. 10). Second, the shared haplotype is not found in geographically contiguous drainages, being found in the Tombigbee (E. beanii) and Yellow and Blackwater (E. bifascia) rivers. Given the lack of gene flow within species between drainages, it is unlikely that this shared haplotype is the result of gene flow. Third, the root of the network, as shown by the phylogenetic tree, is between the two major populations of E. beanii. Although the authors do not doubt that the Pascagoula/Escatawpa system is isolated from the Mobile Bay (Alabama-Tombigbee) drainage, it is believed that this occurred after the speciation event that separated E. beanii and E. bifascia. This is based on the general geologic history of the region, the monophyly of the species pair, and the distinctiveness of the two species which indicates that any split occurring between populations of E. beanii must have occurred after, not before, the origin of E. beanii and E. bifascia from their common ancestor. If this interpretation is accepted, then the historical gene flow patterns implied by the rooted network can be further resolved (Fig. 10). Older gene flow patterns are represented by haplotypes B-1 and B-12 and denote gene flow that occurred before the origin of either descendant species from their common ancestor. If so, then the ancestor/descendant patterns between these haplotypes and others found in both E. beanii and E. bifascia do not imply recent gene flow between these two species. Furthermore, they do not imply recent gene flow within E. bifascia relative to the relationship between the Blackwater and Yellow rivers on the one hand and the Escambia River on the other hand. Thus, the authors suggest that the mere presence of shared haplotypes cannot be automatically interpreted as evidence of gene flow. Rather, shared haplotypes are better interpreted within a historical context.

6. mtDNA Sequence Variation among Sand Darters Parts of the rooted network give indications of historical gene flow between drainages within species. There are two possible kinds of relationships within species between drainages. First, a haplotype might be shared between drainages. Haplotype B-l, as an ancestral haplotype, may not be indicative of a relationship between the Yellow and the Blackwater rivers, but B-9, a derived haplotype, probably is indicative of that relationship. Second, ancestor/descendant relationships among different haplotypes occupying different drainages might be indicative of a relationship. For example, however we resolve the loop B-l, B-9, B-2, B-3, the relationships of these haplotypes to other haplotypes in the Escambia, Yellow, and Blackwater rivers denotes historical gene flow exclusive to these drainages. The Perdido, highly isolated, shows some affinities to the contiguous Escambia through the B-3/B-11 haplotype relationship, but we must be cautious. Haplotype B-l, if interpreted as an ancestral haplotype, is not indicative of a close relationship among the Perdido, Escambia, Yellow, and Blackwater rivers. The link between B-1 and B-12 does not imply a close relationship among the Yellow, Blackwater and Perdido rivers. Just as shared haplotypes might not be indicative of a relationship between drainages, the link between ancestral and descendant haplotypes may be indications of more ancient rather than more recent gene flow.

D. Speciation and Biogeography E. beanii and E. bifascia are part of a larger story involving replicate speciation among several groups of fishes inhabiting the northern Gulf Coastal Plain. Wiley (1977) suggested that the speciation event involving two sister species of topminnows (Fundulidae), Fundulus nottii and F. escambiae, might be correlated with tectonic events occurring in the region that had apparently shifted drainage patterns from a northeastsouthwest direction to a north-south direction (Price and Whetstone, 1977). This event would have separated the Mobile Bay drainage basin (Alabama and Tombigbee rivers) from those immediately to the east (Perdido and Escambia rivers), producing the biogeographic pattern observed in the two species. Wiley and Mayden (1985) reviewed biogeographic distributions of a number of species groups of fresh and brackish water fishes, as well as selected other aquatic vertebrates and invertebrates. The same drainage boundaries corresponded to species limits for a number of groups. Wiley and Mayden (1985) identified six additional species pairs distributed in such a manner that one of the pair occupied the Mobile Bay basin and drainages to the west, whereas the sister species occupied the Perdido and Escambia river drainages and

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drainages to the east. These include two groups of topminnows (F. nottii-F, escambiae; F. confluentus-F, pulvereus), two species pairs of darters (E. chlorosomaE. davisoni; E. beanii-E, bifascia), two species pairs of minnows (L. roseipinnis-L, atripiculus; H. longirostrisHybopsis sp.), and three species pairs of snakes (Natrix rhombifera-N, taxispilota; N. cyclopion-N, floridans; Farencia reinwardti-F, abacura). Two apparent exceptions to this pattern, a group of Hybopsis minnows (the H. longirostris group) and a group of Lythrurus minnows (the L. roseipinnis group), were shown by subsequent phylogenetic analyses to conform to the pattern (Wiley and Titus, 1992; Wiley and Siegel-Causey, 1994). Additional groups that might be implicated in the pattern include subspecies of the pike Esox americanus (Crossman, 1966), species of the blenny genus Chasmodes (Williams, 1983), and the mosquito fishes Gambusia affinis and G. holbrooki (Wooten et al., 1988; Wooten and Lydeard, 1990; Scribner and Avise, 1993). What emerges from the phylogenetic studies is a pattern of vicariance. In the case of closely related and relatively recent species pairs such as E. beanii and E. bifascia, dispersal apparently has not altered the original vicariance pattern and it is relatively easy to correlate this pattern with geologic events. When one examines the patterns of the clades to which the various species pairs studied by Wiley and Mayden (1985) belong, it becomes quickly apparent that simple vicariance explanations of deeper nodes are difficult (Wiley and Mayden, 1985), but there is some trace among the fishes. The closest relatives of H. longirostris and Hybopsis sp. live in the Mobile Bay basin and in tributaries west to the Mississippi. The same is generally true of the relatives of L. roseipinnis and L. atripiculus: L. bellus, a Mobile Bay endemic, is the sister species of the pair whereas other relatives are found to the north and west (L. ardens and L. umbratilis). F. nottii and F. escambiae are a bit different in having an eastern sister species (F. lineolatus), but the three are related to two species that have more western distributions. Thus, finding that E. pellucidum is not, in fact, closely related to either E. vivax or E. meridianum (Shaw et al., 1997) brings the biogeography of the subgenus in closer agreement with what is known of the phylogeny and biogeography of fishes with similar distributions and presumably similar histories. Swift et al. (1986) suggest that the eastern Gulf Coast lowland fish fauna represented by such groups as the F. nottii group and, by extension, Ammocrypta colonized the coastal plain during the late Miocene during a period of low sea levels. Their time table of vicariance suggests a late Miocene-early Pliocene (4-5 mybp) event and certainly an event that happened no later than the late Pliocene [1-2 mybp: see Price and Whet-

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stone (1977) for geological evidence involving changes in drainage patterns]. In other groups, Pleistocene events are not correlated with speciation, but with geographic variation (Swift et al., 1986). Thus, differences within species among the various drainages along the Gulf Coastal Plain would be expected, but the authors conclude that they are younger than the vicariance events that produced the species observed in this study. If a relatively recent event (isolation of the Pascagoula/Escatawpa from the Mobile Bay within E. beanii) falls out at the base of a phylogenetic tree while a more ancient event (speciation of E. beanii and E. bifascia) does not, the most likely conclusion is that both species retained an array of haplotypes that were present in their common ancestor and that, given this, there is no expectation that the gene tree will reflect the species tree until such time as these ancestral haplotypes go extinct and more lineage-specific haplotypes emerge. Obviously, 2 - 4 million years has been insufficient time for this to occur.

VI. Summary DNA sequence data were obtained from the N-terminal end of the mitochondrial cytochrome b gene and a portion of the adjacent glutamine tRNA gene for 89 individuals representing six species of Etheostoma (Ammocrypta) and two closely related species, E. vitreum and E. nigrum. Substitutions were found at 27% of 422 sites and 71% of these were transitions. Six substitutions produce nonsynonymous codons out of the 134 cytochrome b codons included in the sequence. Among the recently diverged sister species E. beanii and E. bifascia, there were 21 substitutions (5%), none of which were fixed between species. Phylogenetic analyses of DNA data with haplotypes as terminal taxa were performed using equally weighted and transversionweighted matrices. A total evidence analysis was also performed that favored one of the DNA-only trees. In no case were the relationships among the haplotypes of E. beanii and E. bifascia resolved. Rather, some E. beanii haplotypes were basal relative to the remaining E. beanii and all E. bifascia haplotypes. A minimum spanning network of haplotypes was constructed. This network suggests that river drainage systems are isolated from each other and that haplotypes show high drainage system affinity. The placement of the root derived from the phylogenetic analysis onto the network suggests that there has been insufficient time for complete lineage sorting as E. beanii and E. bifascia diverged from their common ancestor. Despite this, the rooted network does suggest biogeographic relationships of populations from some of the drainages within E. bifascia.

Acknowledgments We thank Bob Cashner and Steve Stevenson (University of New Orleans), Rick Mayden, Berney Kahajda, and Andrew Simons (University of Alabama), Hank Bart (Tulane University), Doug SiegelCausey (University of Nebraska), Tim Schmidt (Wayne State University), George Harp (Arkansas State University), and Frank Cross and Kate Shaw (University of Kansas) for their help in collecting specimens in the field. Thanks to Larry Page (Illinois Natural History Survey) for specimens of E. pellucidum. Thanks to Bob Jenkins (Roanoke College) for specimens of E. vitreum. This project was generously supported by grants from the General Research Fund, University of Kansas (3208), and from the National Science Foundation (BSR 8722562 for field work and DEB 9207600 for data collecting and analysis).

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6. m t D N A Sequence Variation among Sand Darters

Kluge, A. G. 1989. A concern for evidence and a phylogenetic hypothesis of relationships among Epicrates (Boidae, Serpentes). Syst. Zool. 38: 7-25, Kocher, T. D., Meyer, W. K., et al. 1989. Dynamics of mitochondrial DNA evolution in animals. Proc. Natl. Acad. Sci. USA 86:61966200. Krajewski, C., and King, D. G. 1996. Molecular divergence and phylogeny: Rates and patterns of cytochrome b evolution in cranes. Mol. Biol. Evol. 13:21-30. Lydeard, C., Wooten, M. C. and Meyer, A. 1995. Cytochrome b sequence variation and a molecular phylogeny of the live-bearing fish genus Gambusia (Cyprinodontiformes: Poeciliidae). Can. J. Zool. 73:213-227. Maddison, W. P., and Maddison, D. R. 1992. "MacClade." Sinauer, Sunderland, MA. Magoulas, A., Tsimenides, N., and Zouros, E. 1996. Mitochondrial DNA phylogeny and the reconstruction of the population history of a species: The case of the European anchovy (Engraulis encrasicolus). Mol. Biol. Evol. 13:178-190. Maniatis, T., Fristch, E. F., and Sambrook, J. 1982. "Molecular Cloning: A Laboratory Manual." Cold Spring Harbor Laboratory, Cold Spring, NY. Mayden, R. L., B. M. Burr, L. M. Page, and R. R. Miller. 1992. The native freshwater fishes of North America. "Systematics, Historical Ecology and North American Freshwater Fishes" (R. L. Mayden, ed.), pp. 827-863. Stanford Univ. Press, Stanford, CA. Meyer, A. 1994a. DNA technology and phylogeny of fish. In "Genetics and Evolution of Aqauatic Organisms" (A. R. Beaumont, ed.), pp. 219-249. Chapman and Hall, London. Meyer, A. 1994b. Shortcomings of the cytochrome b gene as a molecular marker. Trends Ecol. Evol. 9:278-280. Murphy, W. J., and Collier, G. E. 1996. Phylogenetic relationships within the aplocheiloid fish genus Rivulus (Cyprinodontiformes, Rivulidae): Implications for Caribbean and Central American biogeography. Mol. Biol. Evol. 13:642-649. Nei, M. 1987. "Molecular Evolutionary Genetics." Columbia Univ. Press, New York. Paabo, S. 1990. Amplifying ancient DNA. In "PCR Protocols: A Guide to Methods and Applications" (M. A. Innes et al., eds.), pp. 159-166. Academic Press, San Diego. Patton, J. L., da Silva, M. N. F., and Malcolm, J. R. 1996. Hierarchical genetic structure and gene flow in three sypatric species of Amazonian rodent. Mol Ecol. 5: 229- 238. Price, R. C., and Whestone, K. N. 1977. Lateral stream migration as evidence for regional geologic structures in the eastern Gulf Coastal Plain. Southeast. Geol. 18(3):129-147. Saiki, R. K. 1990. Amplification of genomic DNA. In "PCR Protocols: A Guide to Methods and Applications" (M. A. Innis et al., eds.), pp. 13-20. Academic Press, San Diego. Scribner, K. T., and Avise, J. C. 1993. Cytonuclear genetic architecture in mosquitofish populations and the possible roles of introgressive hybridization. Mol. Ecol. 2:139-149. Shaw, K., Simons, A. M. and Wiley, E. O., 1997. A reexamination of the phylogenetic relationships of the sand darters (Teleostei: Percidae). Occas. Publ. Mus. Nat. Hist. Univ. Kansas. Submitted for publication. Simons, A. M. 1991. Phylogenetic relationships of the crystal darter, Crystallaria asprella. Copeia 1991:927- 936. Simons, A. M. 1992. Phylogenetic relationships of the Boleosoma species group (Percidae: Etheostoma). In "Systematics, Historical Ecology and North American Fireshwater Fishes" (R. L. Mayden, ed.), pp. 268-292. Stanford Univ. Press, Stanford, CA. Slatkin, M., and Maddison, W. P. 1989. A cladistic measure of gene flow inferred from the phylogenies of alleles. Genetics 123:603613. Stauffer, J. R. 1980a. Ammocrypta beani Jordan. In "Atlas of North

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American Freshwater Fishes" (D. S. Lee et al., eds.), p. 616. North Carolina St. Mus. Nat. Hist., Raleigh, NC. Stauffer, J. R. 1980b. Ammocrypta clara Jordan and Meek. In "Atlas of North American Freshwater Fishes" (D. S. Lee et al., eds.), p. 618. North Carolina St. Mus. Nat. Hist., Raleigh NC. Stauffer, J. R, and Hocutt, C. H. 1980. Ammocrypta vivax Hay. In "Atlas of North American Freshwater Fishes" (D. S. Lee et al., eds.), p. 621. North Carolina St. Mus. Nat. Hist., Raleigh, NC. Stauffer, J. R, Hocutt, C. H. and Gilbert, C. R. 1980. Ammocrypta bifascia Williams. In "Atlas of North American Freshwater Fishes" (D. S. Lee et al., eds.), p. 617. North Carolina St. Mus. Nat. Hist., Raleigh, NC. Swift, C. C., Gilbert, C. R. Bortone, S. A., Burgess, G. H., and Yeger, R. W. 1986. Zoogeography of the freshwater fishes of the southeastern United States: Savannah River to Lake Ponchartrain. In "The Zoogeography of North American Freshwater Fishes" (C. H. Hocutt and E. O. Wiley, eds.), pp. 213-265. WileyInterscience, New York. Swofford, D. L. 1993. PAUP 3.1.1. Computer Program distributed by the Illinois Natural History Survey, Champaign, IL. Swofford, D. L., Olsen, G. J., Waddell, P. J., and Hillis, D. M. 1996. Phylogenetic inference. In "Molecular Systematics" (D. M. Hillis, C. Moritz, and B. K. Mable, eds.), 2nd Ed., pp. 407-514. Sinauer Associates, Sunderland, MA. Templeton, A. R., Crandall, K. A., and Sing, C. F. 1992. A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. Genetics 132: 619-633. Templeton, A. R., Routman, E., and Phillips, C. A. 1995. Separating population structure from population history: A cladistic analysis of the geographical distribution of mitochondrial DNA haplotypes in the tiger salamander, Ambystoma tigrinum. Genetics 140: 767-782. Weir, B. S. 1996. Intraspecific differentiation. In "Molecular Systematics" (D. M. Hillis, C. Moritz, and B. K. Mable, eds.), 2nd Ed., pp. 385-406. Sinauer Associates, Sunderland, MA. Wiley, E. O. 1977. The phylogeny and systematics of the Fundulus nottii species group (Teleostei: Cyprinodontidae). Occ. Pap. Mus. Nat. Hist. Univ. Kansas. 67:1-31. Wiley, E. O. 1992. Phylogenetic relationships of the Percidae (Teleostei: Perciformes): A preliminary hypothesis. In "Systematics, Historical Ecology and North American Freshwater Fishes" (R. L. Mayden, ed.), pp. 247-267. Stanford University Press, Stanford, CA. Wiley, E. O., and Mayden, R. L. 1985. Species and speciation in phylogenetic systematics, with examples from the North American fish fauna. Ann. Missouri Bot. Gard. 72:596-635. Wiley, E. O., and Siegel-Causey, D. 1994. A phylogenetic analysis of the Lythrurus roseipinnis species group (Teleostei: Cyprinidae), with comments on the relationship of other Lythrurus. Occas. Pap. Mus. Nat. Hist. Univ. Kansas 171:1-20. Wiley, E. O., and Titus, T. A. 1992. Phylogenetic relationships among members of the Hybopsis dorsalis species group (Teleostei: Cyprinidae). Occas. Pap. Mus. Nat. Hist. Univ. Kansas 152:1-18. Williams, J. D. 1975. Systematics of the percid fishes of the subgenus Ammocrypta, genus Ammocrypta, with descriptions of two new species. Bull. Alabama Mus. Nat. Hist. 1:1-56. Williams, J. T. 1983. Taxonomy and ecology of the genus Chasmodes (Pisces: Blenniidae) with a discussion of its zoogeography. Bull. Florida St. Mus. Biol. Sci. 29(2): 1-100. Wooten, M. C., and Lydeard, C. 1990. Allozyme variation in a natural contact zone between Gambusia affinis and Gambusia holbrooki. Biochem. Syst. Ecol. 18(2/3): 169-173. Wooten, M. C., Scribner, K. T. and Smith, M. H. 1988. Genetic variation and systematics of Gambusia in the Southeastern United States. Copeia 1988(2):283-289.

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Zhu, D., Jamieson, B. G. M., Hugall, A., and Moritz, C. 1994. Sequence evolution and phylogenetic signal in control-regionand cytochrome-bsequences of rainbow fishes (Melanotaeniidae).Mot. Biol. Evol. 11(4):672-683.

A p p e n d i x h Specimens Examined

Specimens are presented by KU number (number of specimens), state, and major drainage. Exact localities are available from E. O. Wiley. Vouchered specimens are actual specimens used in this chapter, and the series may contain more specimens than analyzed. Etheostoma beanii: KU 22898 (6), Alabama, Esactawpa Dr. KU 24380 (5), Alabama, Tornbigbee Dr. KU 24382 (6), Alabama, Tombigbee Dr. KU 24381 (6), Alabama, Alabama Dr. KU 24383 (6), Mississippi, Pascagoula Dr. KU 24384 (6), Mississippi, Pascagoula Dr. Etheostoma bifascia: KU 24385 (6), Alabama, Perdido Dr. KU 24388 (5), Florida, Perdido Dr. KU 22146 (6), Florida, Escambia Dr. (1988 collection). KU 24387 (6), Florida, Escambia Dr. (1989 collection). KU 24386 (6), Alabama, Yellow Dr. KU 24862 (5), Florida, Blackwater Dr. Etheostoma clarum: KU 23145 (2), Arkansas, Strawberry Dr. Etheostoma meridianum: KU 23148 (2), Mississippi, Tombigbee Dr. KU 23149 (2), Misssippi, Tombigbee Dr. Etheostoma nigrum: KU 23143 (1), Kansas, Kansas Dr. Etheostoma pellucidum: KU 23150 (2), Indiana, Tippecanoe Dr. Etheostoma vitreum: KU 23144 (1), KU 24389 (1), Virginia. Blackwater Dr. Etheostoma vivax: KU 24390 (1), Missouri, Mississippi R. KU 23146 (2), Arkansas, St Francis Dr. KU 24391 (1), Louisiana, Ouachita Dr. KU 24392 (1), Louisiana, Ouachita Dr. KU 24393 (1), Louisiana, Sabine Dr. KU 24394 (1), Mississippi, Pearl Dr.

Appendix Ih Morphological Characters

The following characters are taken from Simons (1992) and Shaw et al. (1997). In each case, the observed attribute of individual specimens is considered a character, and homologous characters are organized into a transformation series (TS). Thus a transformation series is a column of data, and a cell in the matrix is the character observed for individuals of a species (see Wiley et al., 1991). This convention circumvents the usual (and inaccurate) convention of treating columns as "characters" and cells as "character states." TS 117: Ascending process of premaxilla perpen-

dicular to the alveolar process (0) or inclined posteriorly (1). TS 118: Premaxillary process of maxilla V-shaped (0) or U-shaped (1). TS 119: Notch laying posteroventral to the articular process of the quadrate shallow or absent (0) or deeply cut into the quadrate body (1). TS 120: Body of quadrate rounded (0) or rectangular (1). TS 121: Hyomandibular struts present as cruciform thickenings (0) or reduced to absent (1). TS 122: Descending process of the hyomandibular long and extending beyond the preopercular groove (0) or short and terminating at the end of the groove (1). TS 123: Hyomandibular spur absent (0) or present (1). TS 124: Ventral plate of the urohyal flattened (0) or curved (1). TS 125: Interhyal articular process of the posterior ceratohyal present (0) or absent (1). TS 126: Posterior margin of the preopercle smooth (0) or serrate (1). TS 127: Notch in the anterior angle of the preopercular roofing the articular facet for the interhyal present (0) or absent (1). TS 128: Opercular spine present (0) or absent (1). TS 129: Opercular strut extending from the hyomandibular articulatory facet strong (0) or greatly reduced (1). TS 130: Posterodorsal extension of the subopercle elongate (0) or truncated (1). TS 131: Mesethmoid thick and expanded anteriorly (0) or thin and not expanded (1). TS 132: Maxillary ligament inserted on two dorsomedial ridges of the mesethmoid (1), or inserted on two dorsolateral projections (0). Recoded from Shaw et al. (1996) three character transformation series. TS 133: Vomerine teeth present (0) or usually absent (1). TS 134: Membrane bone on the lateral margin of the nasal well developed (0) or present as a thin slip (1). TS 135: Remnant of the lateral line canal on the supracleithrum present (0) or absent (1). TS 136: Postcleithrum 2 present (0) or absent (1). TS 137: Longitudinal struts on the proximal anal pterygiophores present (0) or absent (1). TS 138: Processes for the insertion of the infracarinalis medius muscles on the anterior face of the first anal pterygiophore present (0) or absent (1). TS 139: Body scalation almost complete (0) or reduced laterally to a few scale rows (1). TS 140: Male anal fin breeding tubercles absent (0) or present (1).

C H A P T E R

7 Phylogeographic Patterns in Populations of Cichlid Fishesfrom Rocky Habitats in Lake Tanganyika CHRISTIAN STURMBAUER Department of Zoology University of Innsbruck A-6020 Innsbruck, Austria

ERIK VERHEYEN Royal Belgian Institute of Natural Sciences B-IO00 Brussels, Belgium

LUKAS ROBER Zoological Museum of the University of Z~rich Switzerland

AXEL MEYER Department of Ecology and Evolution State University of New York Stony Brook, New York 11794

I. Lake Tanganyika and Its Cichlid Species Flock

lake has reached its largest extension due to addition of a large tributary river, the Ruzizi in the northern edge of the lake. It was formed about 10,000 years ago by the formation of the Virunga volcano chain in Rwanda, blocking the formal connection of this area with the Nile system. The influx of the Ruzizi River also ended a long period of isolation from the Zaire River system and caused an overflow of Lake Tanganyika via the Lukuga into the Lualaba, the upper reaches of the Zaire River. Although the cichlid flock of Lake Victoria is considered to be monophyletic (Meyer et al., 1990), the Malawi and Tanganyika cichlid flocks are probably of polyphyletic origin (Greenwood, 1981; Nishida, 1991; Sturmbauer and Meyer, 1993; Moran et al., 1994; Sturmbauer et al., 1994; Kocher et al., 1993, 1995). Lake Malawi harbours a small sub-flock of five endemic species of Tilapiine cichlids (Eccles and Trewavas, 1989; Axelrod, 1993), in addition to its subflock of "haplochromines" which is considered monophyletic (Moran et al., 1994). The Lake Tanganyika cichlid flock is composed of several lineages, assigned to 12 tribes (Poll,

The cichlid species flocks of the great East African lakes represent the most diverse assemblages of freshwater fishes in the world. Lake Tanganyika is by far the oldest of the three major East African rift lakes with an estimated age of about 9 to 12 million years (Cohen et al., 1993). Its geological history is relatively well known (reviewed in Tiercelin and Mondeguer, 1991). The lake is formed of three basins which have been fused to one large lake about 5 to 6 million years ago. Seismic data show that about 200,000 (Tiercelin and Mondeguer, 1991) to 75,000 (Scholz and Rosendahl, 1988; C. A. Scholz personal communication) years ago the level of Lake Tanganyika dropped 600 m below its present level, possibly even splitting the lake into three sublakes for several tens of thousands of years. This vicariant event must have had severe effects on several habitats and their fish populations. After this period the lake level rose again with additional minor fluctuations in the more recent history. At present times the

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CHRISTIAN STURMBAUER et al.

1986). The ancestors of some tribes are likely to be older than the lake and probably have colonized the proto-lakes of Tanganyika to radiate in parallel into subflocks. The Victoria and Malawi cichlids are all, without exception, maternal mouthbrooders (females brood their eggs by buccal incubation; reviewed by Barlow, 1991; Keenleyside, 1991), and the Tanganyika flock contains several lineages of mouthbrooders as well as substrate breeders (Nishida, 1991; Sturmbauer et al., 1994; Kocher et al., 1995). The Tanganyikan cichlid fauna is morphologically, ecologically and behaviorally the most diverse species flock of the African lakes (Fryer and Iles, 1972; Greenwood, 1984). Due to its old age, the radiation may be in a highly advanced stage and the phylogeographic history of species and populations may reach back far in time compared to the cichlids of Lake Malawi and Lake Victoria. Several species are split into numerous populations which might have complex histories. Some are likely to be old, and therefore may have highly diversified genetically, to an extent that their history can be deduced from gene sequences.

sal and consequently the amount of gene flow among cichlid populations are ecological specialization and niche partitioning, e.g., habitat specifity, site fidelity or territoriality, homing behavior, and social organization (Fryer and Iles, 1972; McKaye and Gray, 1984; McElroy and Kornfield, 1990; Yanagisawa and Nishida, 1991; Hert, 1992; Sturmbauer and Dallinger, 1995). These species-specific characteristics may influence to which extent species will be split into distinct populations, to which extent populations will be isolated from each other, and also to which extent physical changes might affect their population structures. During periods of physical separation, genetic differences between populations will accumulate. Prezygotic isolation mechanisms might evolve as byproducts of genetic isolation, possibly driven by sexual selection on traits involved in social and/or reproductive behavior. This mechanism was suggested for color patterns of males being the decisive criterion of mate recognition and choice (Mayr, 1984; Dominey, 1984). Given the behavioral diversity in Tanganyikan mouthbrooders, the relative importance of sexual selection may also vary among species or lineages.

A. M o d e l i n g A d a p t i v e R a d i a t i o n

The Tanganyika cichlid species flock thus provides an excellent model system to elucidate the evolutionary mechanisms which induce and trigger explosive speciation events. An important aspect of understanding adaptive radiations is concerned with the mode of speciation which led to their diversification. Specifically, the relative importance of intrinsic biological characteristics such as ecology, anatomy, and behavior versus abiotic factors such as geological history, geographic structuring of the lake basin, barriers to gene flow, and fluctuations of the lake level is controversial. Although abiotic factors are thought to provide or prevent the opportunities for dispersal, biotic factors may define the dispersal capability of each species once an opportunity for gene flow is provided. Abiotic factors may thus be viewed as shape parameters of habitats in the lake ecosystem defining their location, size, and discontinuity in time and space. Changes in any abiotic parameter might reshape habitats, and existing barriers might be "torn down" at one time whereas others might arise at another. The degree of habitat change extends from small-scale fluctuations to vicariant events affecting almost all habitats and their species communities. Because abiotic factors most likely affect the whole species communities equally in their habitats, differences in the distribution patterns among species may primarily arise due to species-specific biological differences. Among biotic factors presumed to affect the disper-

II. Speciation and D N A The comparison of genetic patterns among species assemblages living sympatrically in geographically isolated populations is expected to provide insights into the dynamics of population histories and their evolutionary causes (e.g., reviewed in Avise, 1994). The amount of genetic divergence within and among populations, as well as frequencies and distributions of different genotypes, will provide information about their historical demography. By relating the observed patterns to ecology, habitat specificity and behavior, the decisive characteristics triggering the degree of isolation may be identified for several species on a comparative basis. Identifying the causes of isolation in various species is the goal of such an approach, and ultimately identifying possible patterns for various groups of species of similar biology. This chapter combines results of mitochondrial (mt)DNA sequence data presently available for three endemic Tanganyika cichlid lineages: Tropheus (Sturmbauer and Meyer, 1992), Simochromis (Meyer et al., 1996), and the members of the tribe Eretmodini (R(iber, 1994; Verheyen et al., 1996). MtDNA was shown to be a sensitive marker for population differentiation because it evolves 5 to 10 times faster than nuclear DNA (Avise, 1994). It is exclusively maternally transmitted in cichlids, making it more sensitive to population size fluc-

7. PhylogeographicPatterns of Cichlid Fishes tuations (reviewed in Meyer, 1993; Avise, 1994). This chapter focuses on results based on the mitochondrial control region because it is the most variable region of the entire genome (reviewed in Meyer, 1993, 1994) and thus most suitable in addressing phylogenetic questions at the population level. All species in this chapter inhabit rock and cobble shores along the lake where they often occur in sympatry. They all are epilithic algae feeders and are habitat specific to different degrees (Sturmbauer et al., 1992). For all three taxa, geographically distinct populations have been described, distinguishable only by minor, if any, morphological variation, but sometimes pronounced differences in coloration. DNA sequence data are available for populations of all three taxa along the central eastern coast of Lake Tanganyika. 1 This shoreline contains the major breakpoints which correspond to the locations of the three main basins of the lake and thus covers habitats in shallow water which are more strongly affected by fluctuations of lake level, as well as habitats situated at very steep shorelines which were probably not affected by periods of low lake level (Fig. 1A). Additional, yet unpublished, data were added to the Tropheus data set to increase geographical overlap with the data sets for Simochromis and the Eretmodini in the central eastern region of the lake. Species of the genus Tropheus are strictly confined to rock habitats for foraging and mating, and have a limited capacity for dispersal across open water (Brichard, 1989; Sturmbauer and Dallinger, 1995). Six nominal species are described (Poll, 1986), some of which have overlapping distribution (Snoeks et al., 1994), and more than 70 distinctly colored "races" have been reported (P. Schupke, personal communication). Samples of 23 localities are included in Fig. 1A. The genus Simochromis is closely related to Tropheus (Nishida, 1991; Sturmbauer and Meyer, 1992; Kocher et al., 1995) and both genera are classified within the same tribe, the Tropheini (Poll, 1986). The two Simochromis species studied so far, S. babaultii and S. diagramma, appear to be similar to Tropheus in their ecology, but they are typically less abundant. Their number of described geographical "races" is much smaller than Tropheus and some behavioral differences also exist between the taxa of the two genera. Although both sexes of Tropheus are highly sedentary, Simochromis species have been observed to move about in 1The nucleotide sequences in this chapter are available from EMBL/GenBankand are as follows:Z12047to Z12100and Z75694to Z75709 for Tropheus;X90593to X90638for the eretmodines; U40524 to U40532 for Simochromis babaultii; and U38808 and U38984 to U38995 for Simochromisdiagramma.

99

schools, and only dominant males keep territories (Brichard, 1989; C. Sturmbauer et al., unpublished observations). In contrast to Tropheus and to the Eretmodini, Simochromis is sexually dichromatic. Samples of 11 and 13 localities were analyzed for S. babaultii and S. diagramma, respectively. Species of the tribe Eretmodini are small, stenotopic cichlids and are the only group of cichlids that are adapted to living in shallow coastal areas, exposed to wave action. Three genera and four nominal species,

Eretmodus cyanostictus, Spathodus erythrodon, Spathodus marlieri, and Tanganicodus irsacae, have been described. Because eretmodines have a reduced swimbladder, they actually "sit" on the substrate, like the Gobiidae and the marine Blenniidae. The species differ in their ecology and dental morphology: three species were classified as epilithic algae feeders and one species (Tanganicodus) tends to feed on higher portions of invertebrates (Yamaoka et al., 1986). As in the case of Tropheus, numerous geographically isolated populations have been described for all four species, but color differences among populations are less pronounced than in Tropheus. Samples of 43 specimens from 32 localities were analyzed for the Eretmodini.

A. Genetic Variation in Tropheus Comparisons of the amount of sequence variation found within the genus Tropheus to that within the haplochromine species flocks of Lake Malawi and Lake Victoria suggested that Tropheus may be roughly twice the age of the whole Malawi species flock and six times the age of the Lake Victoria cichlid flock (Sturmbauer and Meyer, 1992). Tropheus duboisi is the most basal species in the genus, sister group to seven distinct lineages comprising the remaining five presently recognized species (Fig. lb). Although the average corrected sequence divergence among these seven different lineages amounted to 9.1% (standard deviation 1.6%), the average genetic divergence among populations of the same mitochondrial lineage was only 3.0% (standard deviation 1.1%). On the basis of the observed short branches and thus similar levels of genetic divergence defining the major mitochondrial lineages, and of similar levels among populations within each lineage, two successive radiations are hypothesized: in the primary radiation, Tropheus colonized rocky shores along the entire lake and the seven lineages originated. Relatively recently, each of those lineages underwent secondary radiations during which time geographically separated populations diversified to the patterns presently observed. The major fluctuation of the lake level was suggested as the trigger of the secondary radiations.

100

CHRISTIAN STURMBAUER et al.

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Tropheus duboisi FIGURE 1 Mitochondrial phylogeny and geographic distribution of the Tanganyikan genus Tropheus. Seventy-two individuals, assigned to six currently recognized species, were sequenced (Poll, 1986): Tropheus moorii, Boulenger, 1898; T. annectens, Boulenger, 1898; T. duboisi, Marlier, 1959; T. brichardi, Nelissen and Thys, 1976; T. kasabae, Nelissen, 1977; and T. polli, Axelrod, 1978. The populations are identified by the name of the nearest village (Brichard, 1989). (A) Map of Lake Tanganyika with localities of 23 Tropheus populations and distribution of the seven recognized major mitochondrial lineages. Stippled areas represent the hypothesized shoreline at a depth of 600 m, illustrating the locations of the three lake basins and the steepness of the shoreline. Numbers of individuals analyzed from each locality are given in parentheses if larger than one. Boxed genotype symbols indicate the presence of two mitochondrial genotypes assigned to different major lineages within a single geographical "race." (B) Molecular phylogeny of the genus Tropheus. The species names are given according to the current taxonomic assignments; a name in quotation marks refers to that used in the text. All populations from which species names are omitted are presently classified as T. moorii. The symbols indicate genetically distinct lineages based on the phylogenetic analysis of mitochondrial sequence data. The primary radiation and the succeeding more recent secondary radiations are indicated by stippled boxes. This phylogeny was obtained by parsimony analysis (using PAUP 3.1.1; Swofford, 1993). A bootstrap consensus tree (Felsenstein, 1985; 1000 replicates, 50% majority rule) based on 442 bp of the control region is shown. T. duboisi, identified as the closest living relative of all other Tropheus species (Sturmbauer and Meyer, 1992), was used as the outgroup. Transversions were weighted nine times over transitions based on the average observed frequency among taxa of up to 5% uncorrected sequence divergence. Three insertions were observed; each was weighted like a single transversion. This analysis included 20 representative taxa and resulted in three equally parsimonious trees [heuristic search with random addition of taxa and 20 replications; ACCTRANS option; weighted tree length, 393 steps; unweighted tree length, 172 base substitutions; consistency index excluding uninformative characters (Kluge and Farris, 1969), 0.50]. Bootstrap values are given on the branches.

B. Phylogeographic Patterns in Tropheus The distributions of six of the seven major genetic lineages show a clear phylogeographic pattern. Each

lineage is confined to discrete shore sections of a single basin, typically centering along steeply sloping habitats (see Fig. 2). Their genetic distances to each other suggest that these six lineages might have colonized

7. Phylogeographic Patterns of Cichlid Fishes

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O @ Wapembe II 1 Chaitika FIGURE 2 Mitochondrial phylogeny obtained by parsimony analysis and locations of Tropheus populations with geographically restricted distribution along the three major basins of Lake Tanganyika (indicated by stippled areas on the map). The populations are identified by the name of the nearest village (Brichard, 1989). Numbers of individuals analyzed from each locality are given in parentheses if larger than one. Boxed genotype symbols indicate the presence of two mitochondrial genotypes assigned to different major lineages within a single population. A bootstrap consensus tree (1000 replicates, 50% majority rule) is shown, based on 382 bp of the control region. Five individuals of a lineage from the northern shores (indicated by open triangle symbols) were used as the outgroup based on the analysis presented in Fig. lB. Transversions were weighted nine times over transitions based on the average observed frequency among taxa of up to 5% uncorrected sequence divergence. Three insertions were observed; each was weighted like a single transversion. This analysis included 22 representative taxa and resulted in 14 equally parsimonious trees (heuristic search with random addition of taxa and 20 replications; ACCTRANS option; weighted tree length, 312 steps; unweighted tree length, 128 base substitutions; consistency index excluding uninformative characters, 0.64). Bootstrap values are given on the branches. The symbols indicate genetically distinct lineages based on the phylogenetic analysis of mitochondrial sequence data. A split of the lake between the central and the southern basin during a period of low lake level, suggested by the distribution of closely related mitochondrial genotypes at opposite shores, is indicated on the map and connected to the relevant part of the phylogeny (lower box). The upper boxed section of the phylogeny indicates the presence of two distinct genotypes assigned to two major mitochondrial lineages in Tropheus "Kirschfleck."

their habitats during the primary radiation, well before the reported period of the low lake level. Due to the stability of their habitats, these lineages are likely to have survived the drop of the lake level intact. When the lake rose again, they did not seem to have significantly expanded their ranges during their secondary radiations. Only a single lineage (square symbols in Fig. 1B and Fig. 3) is widespread throughout the entire lake,

ranging from Bemba at the very northwestern end down to Mpulungu at the very south of Lake Tanganyika (Fig. 1B). Despite this, all members of the "square" lineage, even from distant populations, are genetically closely related, as closely as the populations within each primary lineage. Thus, the square lineage may have significantly expanded its range of distribution during its secondary radiation when the lake level rose after its low period.

102

CHRISTIAN STURMBAUER et al. ,

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FIGURE 3 Mitochondrial phylogeny based on 382 bp of the control region, obtained by parsimony analysis and neighbor joining (Saitou and Nei, 1987), and locations of Tropheus populations with geographically widespread distribution (termed "square lineage" in the text) along the three major basins of Lake Tanganyika are shown (indicated by stippled areas on the map). The populations are identified by the name of the nearest village (Brichard, 1989). The boxed genotype symbols at Wapembe indicate the presence of two mitochondrial genotypes assigned to different major lineages within a single population. A bootstrap consensus tree (1000 replicates in both, parsimony and neighbor joining) is shown in which all branches that were found in less than 50% of the replicates of both methods are collapsed. Five individuals of a lineage from the northern shores (indicated by open triangle symbols) were used as the outgroup based on the analysis presented in Fig. lB. Transversions and transitions were weighted equally, as all taxa of the ingroup are closely related. Three insertions were observed; each was weighted like a single base substitution. In neighbor joining, JukesCantor distances (Jukes, 1980) were used to correct for multiple substitutions. This analysis included 24 representative individuals and resulted in 50 equally parsimonious trees (heuristic search with random addition of taxa and 20 replications; ACCTRANS option; tree length, 97 base substitutions; consistency index excluding uninformative characters, 0.59). Bootstrap values above the branches are from parsimony, whereas those below the branches are from neighbor joining. A split of the lake between the northern and the central basin during a period of low lake level, suggested by this phylogenetic analysis, is indicated on the map and is connected to the relevant part of the phylogeny (boxed section).

In addition, the distribution of mitochondrial genotypes within and among populations of the "square lineage" does not suggest any obvious phylogeographic structure. Of 10 individuals sequenced from the population at Mpulungu at the southern end of the

lake, 8 different mitochondrial genotypes were identified, clustering with mitochondrial genotypes of several other localities of this lineage (three individuals were included in the analysis presented in Fig. 3). During their period of geographic expansion the

7. PhylogeographicPatterns of Cichlid Fishes members of the "square lineage" seem to have entered regions that were already colonized by other lineages. Data of a population near Wapembe at the southeastern shore of the lake suggest an introgression event in the history of this population between the indigenous lineage (from the primary radiation of Tropheus) and a second lineage of invaders. Among four individuals sequenced, all were different: three mitochondrial genotypes are assigned to the "square lineage" (square symbols in Figs. 1B and 3), whereas one individual represents a separate and heretoforth undescribed major mitochondrial lineage, in addition to the previously recognized lineages (hatched circle symbol in Figs. 1B and 2). This genotype may be a relict of the indigenous lineage from the primary radiation. The central eastern shore of Lake Tanganyika along the Mahale Mountain range (see Fig. 1A) represents a continuous, steeply sloping rock habitat. Its northern edge at Cape Kungwe is situated close to the border of the northern and the central basin, and its southern edge is at the border between the central and the southern basin. Along this range more than one taxon of Tropheus occurs in sympatry (Snoeks et al., 1994), pointing to high frequencies of secondary contact between multiple lineages at the junctions of the intermediate lake basins. At Cape Kungwe, the northern edge of the Mahale Mountain range, four sympatric Tropheus species were found: T. duboisi (the sister group of all other Tropheus), Tropheus "yellow," T. polli, and Tropheus "Kirschfleck." Tropheus "yellow" belongs to the "square lineage" with widespread distribution. Two of the three analyzed individuals appear to be most closely related to the individuals sampled at Kavalla and Kabimba on the western shore of the lake, exactly where the northern basin touches the current western shore line (see boxed section in Fig. 3), suggesting that Lake Tanganyika was actually split into sublakes between the northern and the central basin during the low period. Three species live sympatrically at the southern edge of the Mahale Mountain range at Cape Kibwesa. Two species, T. polli and T. "Kirschfleck," were also found at Cape Kungwe. The third sympatric Tropheus, Tropheus "Kibwesa" (black filled circle in Figs. I and 2), was only found at a stretch of some hundred meters around Cape Kibwesa. These individuals were resolved in a clade together with fish from two populations of the southwestern shore at Moba and Zongwe (see lower boxed section in Fig. 2). Because Tropheus is highly stenotopic and most probably unable to cross several kilometers of open water (Brichard, 1978; Yanagisawa and Nishida 1991; Sturmbauer and Dallinger, 1995), the observed phylogeographic affinities between populations at opposite shores suggest that Lake Tan-

103

ganyika was also split into sublakes between the central and the southern basin. T. polli, and Tropheus "Kirschfleck" occur in sympatry all along the shore of the Mahale Mountain range. Of the individuals sampled at Cape Kungwe, T. polli and Tropheus "Kirschfleck" have closely related genotypes which belong to the same mitochondrial lineage (open circles in Fig. 2). The amount of genetic divergence between these two species is in line with other genetic divergences of individuals of the same major genetic lineage which diversified during secondary radiations. However, this close genetic relationship is contrasted by their clearly expressed differences in coloration and in the shape of their caudal fins. The individuals of Tropheus "Kirschfleck" sampled at the southern edge of the Mahale Mountain range around Cape Kibwesa were genetically heterogeneous (see upper boxed section in Fig. 2). One genotype is almost identical to that sampled at Cape Kungwe and thus is also closely related to the genotypes found in T. polli. The second genotype belongs to a different major mitochondrial lineage and is closely related to populations at Lupota and Moliro at the southwestern shore of the lake (shaded circles in Figs. 1 and 2). Thus, one species, probably T. polli, may be indigenous and Tropheus "Kirschfleck" might have invaded the area from the opposite shoreline when the lake was split. Introgression or hybridization upon secondary contact between invading Tropheus might explain the observed distribution of genotypes. C. Genetic Variation in Eretmodines

The mitochondrial phylogeny is not fully concordant with the present taxonomy of the eretmodines, pointing to the existence of yet undescribed species and in a few cases, to hybridization among species on secondary contact. This chapter focuses on the phylogeography of mitochondrial genotypes and discusses the taxonomic heterogeneities only briefly, as a study including morphology, mtDNA, and nuclear markers is currently underway to adequately address these problems. Of the four presently recognized species,

Spathodus marlieri, Spathodus erythrodon, Eretmodus cyanostictus, and Tanganicodus irsacae, two major mitochondrial lineages have been identified (symbolized as A and B in Fig. 4), subdivided into seven clades. Because the average corrected sequence divergences between the two eretmodine lineages are similar to those found among the seven major lineages of the genus Tropheus (9.2%), the Eretmodini may have about the same age as the primary radiation of Tropheus (see Fig. 1B). Species occur widely sympatrically withTropheus and they also seem to have undergone succes-

104

CHRISTIAN STURMBAUER et al. I~- Ti (MJnago) Ec(40) EC (49) I1 ~--"Sm(Burundi) II ITi (1) ,_~ Lt~ EC(1) I r

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FIGURE 4 Mitochondrial phylogeny of the Eretmodini based on 336 bp of the control region obtained by neighbor joining (Saitou and Nei, 1987); locations of sampled populations are shown on the left map, and geographic distribution of mitochondrial lineages along the three major basins of Lake Tanganyika (indicated by stippled areas on the map) are shown on the center and right map. Populations are identified either by the name of the nearest village or by the number of the sample location during a collection in 1992. Bootstrap values are given on those branches that were obtained in more than 50% of the replications. Tropheus duboisi was used as the outgroup based on a phylogenetic analysis of several Tanganyikan mouthbrooders (Sturmbauer and Meyer, 1993). Kimura distances were used to correct for multiple substitutions (Kimura, 1980). This analysis included 43 representative individuals. Two major lineages (A and B) were defined on the basis of the phylogeny and the observed genetic distances among clades. Lineage A was subdivided into three clades (A1, A2, and A3) whereas lineage B was subdivided into four clades (B1 to B4). The lineages and clades were not only defined on the basis of the mitochondrial control region reported here, but also on the basis of cytochrome b (R~iber, 1994; Verheyen et at., 1996). The geographic distribution of lineage A is shown on the map in the center, whereas that of lineage B is shown on the right map. A split of the lake between the central and the southern basin during a period of low lake level, suggested by the distribution of clade B3, is indicated on the right map and the relevant section of the phylogeny is boxed. The species names are given according to the current taxonomic assignments: Ec, Eretmodus cyanostictus; Sm, Spathodus marlieri; Se, Spathodus erythrodon; and Ti, Tanganicodus irsacae. Locality names or numbers are given in parentheses. Ec (40)# of clade B4 indicates a morphologically and genetically distinct Eretmodus sympatric to another Eretmodus, Ec (40) of clade A1.

sive radiations. As in Tropheus, several habitats along the lake may have been colonized during a primary radiation establishing the two major mitochondrial lineages. Each lineage has then undergone secondary radiations, but in contrast to Tropheus, these secondary radiations did not proceed simultaneously in both lineages and may have been triggered by different causes. The Kimura distances between the clades within lineage A range from 3.1 to 3.4%, similar to the distances found in the secondary radiations of Tropheus (3.0%). The considerably higher Kimura distances (4.5 to 7.7%) observed among the four clades within lineage B indicate that their split is considerably older. The phylogram depicted in Fig. 4 also shows that the secondary

radiations within lineage A occurred much more recently than the clade formation within lineage B.

D. Phylogeographic Patterns in Eretmodines Lineage A is subdivided into three clades (A1, A2, and A3; see Fig. 4), each of which has limited distributions, so that the habitats of each subclade can be assigned to shores of one of the three lake basins. As depicted in the central map of Fig. 4, clade A1 ranges from Burundi to the northern edge of the Mahale Mountain range at Cape Kungwe. Surprisingly, individuals of different species clustered within clade A1.

7. PhylogeographicPatterns of Cichlid Fishes Clade A2 is restricted to the northern half of the Mahale Mountain range and is exclusively composed by E. cyanostictus. Clade A3 ranges from the southern part of the Mahale Mountain range to Cape Mpimbwe and is morphologically homogeneous, comprising only

E. cyanostictus. The individuals assigned to lineage B are subdivided into four clades. Lineages B1, B2, and B3 have restricted distributions (see the right map on Fig. 4). Lineage B1 is comprised exclusively of S. erythrodon and is limited to the northeastern shores of the northern basin (circle-triangle symbols in Fig. 4). Lineage B2, composed of T. irsacae, is found in the central basin, extending further to the north, to the southeastern shores of the northern basin. The distribution of lineage B3 seems to be restricted to the southern edge of the central basin and is found both on the eastern and on the western shores of the lake. Clade B4 is also morphologically heterogeneous and, like clade A1, contains individuals classified as Spathodus, Eretmodus, and Tanganicodus (filled circles in Fig. 4). In contrast to clades B1, B2, and B3, clade B4 it was found in more than one basin, at the southernmost Tanzanian localities, the southwestern shore at Kamakonde, and also in a single individual of E. cyanostictus on locality 40 in the northern basin [symbolized as Ec (40)# in Fig. 4]; this individual is morphologically and genetically distinct to a sympatric Eretmodus [Ec (40) of clade A1]. Individual Ec (40)# may also represent a "mitochondrial relict" genotype of a previously more widespread clade because this genotype was resolved on the basis of clade B4. Like the "square lineage" of Tropheus, lineage A seems to have undergone a secondary radiation during which three clades (A1, A2, and A3 in Fig. 4) were formed and the range of distribution was significantly expanded to shores of all three basins. During their spread, populations of clades A1, A2, and A3 may have reached secondary contact with populations of lineage B which seem to have spread and diversified earlier. At locality 40 (marked by # in the right map in Fig. 4), individuals of three clades (A1, B2, and B4) were found sympatrically.

E. Genetic Variation in Simochromis The two species analyzed, S. babaultii and S. diagramma, had an average genetic distance of 3.8% (standard deviation 0.6%). Thus, S. babaultii and S. diagramma would seem to be much younger species than most Tropheus and most eretmodines. They probably originated at about the same time when Tropheus and eretmodines underwent their secondary radiations.

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Among 25 sampled individuals of S. babaultii from 11 localities, nine mitochondrial genotypes were identified. The average genetic divergence among these nine genotypes was 0.9% (standard deviation 0.8%). Among 28 sampled individuals of S. diagramma from 13 localities, 13 genotypes with an average genetic distance of 1.2% (standard deviation 0.7%) were identified.

F. Phylogeographic Patterns in Simochromis The branching order among different haplotypes did not seem to reflect the geographic distribution of populations in either S. babaultii and S. diagramma in any obvious way, although in both species the two most ancestral haplotypes were found in the most southern populations. The geographic distribution of the mitochondrial genotypes observed in S. babaultii and S. diagramma was variable among haplotypes; however, when more than one individual was sampled from a given locality, both species tended to contain more than one haplotype per locality. Several genotypes were shared among geographically distant localities (Fig. 5) that did not correlate with the partitions of the lake according to the three basins.

III. From Patterns toward an Understanding of Processes

A. Habitat Characteristics, Lake L e v e l and Phylogeography The phylogeographic patterns of mtDNA variation show striking parallels in Tropheus and the Eretmodini in that both seem to have simultaneously undergone (at least) two consecutive radiations. The majority of these lineages are confined to small sections of a single basin (see Fig. 2 for Tropheus and Fig. 4 for the Eretmodini) and thus show a high degree of intralacustrine endemism (Snoeks et al., 1994). They all originated from a primary radiation, which occurred roughly at the same time in Tropheus and the Eretmodini. The lineages with restricted distribution are likely to have colonized their habitats before the period of the dramatically low lake level. Their habitats were situated at steeply sloping shore sections and may thus have in common that they were probably not wiped out by the drop of the lake level, but shifted along a continuous slope. After the lake rose again, the populations shifted back along the slope and did not seem to have expanded their ranges of distribution significantly.

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CHRISTIAN STURMBAUER et al. O DIA9 67

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FIGURE 5 Mitochondrial phylogeny of two species of the genus Simochromis based on 414 bp of the control region, locations of sampled populations, and the geographic distribution of mitochondrial genotypes along the three major basins of Lake Tanganyika (indicated by stippled areas on the maps). Populations are identified according to the number of the sample location during a collection in 1992. Parsimony analysis used equal weights for transversions and transitions, and Tropheus duboisi and Petrochromis trewawasae, both classified within the same tribe (Tropheini), were used as outgroups (Poll, 1986). A heuristic search resulted in minimum length trees of 64 substitutions and a consistency index of 0.79. A bootstrap consensus tree (1000 replicates, 50% majority rule) is shown with bootstrap values on the branches. This analysis included 25 individuals (nine mitochondrial haplotypes) for S. babaultii and 28 individuals (13 mitochondrial haplotypes) for S. diagramma. The geographic distribution of the nine identified haplotypes in S. babaultii is shown on the map on the left, whereas that of the 13 identified haplotypes in S. diagramma is shown on the right map.

As a second striking parallel, the "square lineage" in Tropheus and the A-lineage in the Eretmodini seem to have simultaneously expanded their distributions to all three basins of the lake because the average genetic divergences within the two groups are small and similar (around 3%). Clade B4 of the eretmodines might also have extended its range at about the same time because their members were found at both the eastern and the western shore of the southern basin and also at locality 40 in the northern basin (see the right map in Fig. 4) and because the average Kimura distances within clade B4 also amounted to 3.2%. It seems reasonable that the spread of all three groups was triggered by the same event, a substantial rise in the lake level. However, there are differences with respect to phylogeographic structuring among populations: no clear phylogeographic pattern emerged in the "square lineage" of Tropheus. If the ancestors of the square lineage

originally inhabited more shallow coasts, their populations must have been most severely affected when the lake level retreated. Several populations, previously spread over a wide stretch of shallow coastline, could have been fused into one large population for the period of the low lake level, which might explain the present genetic heterogeneity of this lineage. When the lake level rose after the low period the shallow bays were flooded again and quickly recolonized by the square lineage, which now contained several mitochondrial genotypes. The origin of the square lineage may be situated at the southern section of the northern basin and possibly at the western shore of the central basin; these are the only regions where no individuals with genotypes of the other lineages of limited distribution have been found. In contrast to the square lineage of Tropheus, the three clades of the A lineage of the Eretmodini do show strong phylogeographic structuring (Fig. 4, cen-

7. PhylogeographicPatterns of Cichlid Fishes ter map); all three clades are genetically and also geographically distinct, suggesting that their parental population may not have been as large and genetically heterogeneous as that of Tropheus and thus may not have originated from a shallow and unstable habitat. The heterogeneity in the genetic patterns of six versus a single lineage in Tropheus highlights the importance of intrinsic characteristics of species for their ability to disperse. The enormous success of the "square lineage" in colonizing newly available habitats, and even in replacing at least one original population after the vicariant event, strongly indicates significant differences in their ecology and/or behavior in comparison to the remaining lineages. One might assume that their occurrence in more unstable habitats in shallower regions of the lake, which were repeatedly affected, even by smaller lake level fluctuations, might have forced these populations to become more mobile than those populations situated at steeply sloping habitats which remained intact, regardless of the water level. It is also striking that the square lineage did not seem to be sucessful in colonizing the majority of stable habitats and in replacing indigenous lineages. This observation might point to the possibility that communities at equilibrium are resilient to invasion. S. babaultii and S. diagramma are likely to be much younger than Tropheus and the eretmodines. Because none of the genotypes were shared between the two species, lineage sorting may be complete, despite their young age. The genetic distances of about 3% to each other suggest that their origin might also be directly connected to the reported substantial drop of the lake level. The same vicariant event might thus have triggered both: speciation in Simochromis and secondary radiation in Tropheus and the Eretmodini. As suggested by the branching order in both, S. babaultii and S. diagramma, Simochromis might have speciated in the southern basin and then colonized habitats in the central and northern basin after the lake level of Tanganyika rose again. The second important observation is that both species of Simochromis lack any phylogeographic structure. This is in contrast to the findings for the six Tropheus lineages with limited distribution and the eretmodines. However, it is strikingly similar to the pattern found for the square lineage of Tropheus. Because none of the mitochondrial genotypes were shared among the two species, all identified genotypes are likely to have arisen after the speciation event, despite their lack of phylogeographic structure. This pattern might be explained by the fact that these genotypes were already present in the founder population, before they spread and colonized shores along all three basins. Populations remained genetically heterogene-

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ous due to the young age of these populations and the species. Moreover, the genetic heterogeneity may be caused by high rates of contemporary gene flow among populations all along the lake, even if they are separated from each other by large distances. This explanation is based on the assumption that Simochromis species are less sedentary than Tropheus and the Eretmodini. Ecological differences, combined with smallscale lake level fluctuations, may result in higher rates of gene flow among populations. In Simochromis, speciation may only occur as a consequence of vicariant events, such as an actual split of the lake, allowing for secondary contacts between more strictly isolated populations, such as those from opposite shores. Similarly, the lack of phylogeographic structure such as observed in the square lineage of Tropheus and Simochromis has also been reported for Malawi cichlids (Bowers et al., 1994; Moran and Kornfield, 1993). This parallel to Lake Malawi cichlids may be interesting because most Malawi species, particularly those found at the shallow and thus more unstable southern shore regions, are substantially younger, even than Simochromis. DNA sequences of such closely related species tend to differ from each other by too few point mutations and thus will not provide enough synapomorphies for phylogenetic analyses. Due to incomplete lineage sorting, mitochondrial genotypes may even still be shared by different species which can only be characterized genetically by different frequency patterns of mitochondrial RFLP haplotypes (Moran and Kornfield, 1995). Thus, more variable genetic markers, particularly microsatellites, may actually be more useful for phylogenetic analyses than DNA sequences (A. Parker and I. Kornfield, personal communication). A study on closely related Malawi cichlids has been undertaken by Kornfield and Parker (1997). As a future perspective, mtDNA sequences and those microsatellites used for extremely young Malawi species could be analyzed in parallel in Simochromis, allowing for a better understanding of the accumulation of homoplasy in microsatellite markers with an increasing time of divergence and to sort out maternal (mitochondrial) and nuclear (microsatellite DNA) perspectives on these issues.

B. Split of Lake Tanganyika In both Tropheus and the Eretmodini, closely related genotypes were found at opposite shorelines, despite their restricted dispersal ability through open water. Their low capability of dispersal has been demonstrated at a rock habitat near Rubiza in the northern Lake Tanganyika which emerged in the early seventies after a storm. This habitat was isolated from the next

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rock habitat by 15 km of sand shore (Brichard, 1978). Tropheus, Simochromis and the Eretmodini could not bridge 15 km of sand to colonize these new habitats; they appear to be too philopatric. Thus, it is highly unlikely that any of the three groups can cross several tens of kilometers of open water to colonize shores at opposite sides of the lake. The observation of closely related genotypes on opposite shores corroborates an actual split of Lake Tanganyika during the period of the extremely low lake level which was suggested on the basis of seismic data (Scholz and Rosendahl, 1988; Tiercelin and Mondeguer, 1991). Habitats at the border regions of the basins at either side may have been interconnected by newly forming shorelines through the lake, causing a connection of previously separate populations, so that even philopatric rock cichlids could have established secondary contact across the lake. The reported low stand of the lake level 200,000 to 75,000 years ago is likely to have severely impacted the present distributions of all three groups. However, the observed breakpoints among lineages, or among populations of the same lineage, are different. None of the lineages of the Eretmodini reached a lakewide distribution, indicating that their ability for dispersal is more similar to that of the six lineages of Tropheus with restricted distribution than to that of the "square lineage." The average genetic divergences of the lineages arising during the secondary radiations, especially the finding of closely related populations at both sides of the lake in the border regions of the lake basins, may be suitable to calibrate the rates of sequence divergence in cichlids as soon as more accurate datings of the dramatically low lake level and the split of Lake Tanganyika become available.

C. Secondary Contact, Hybridization, and Speciation According to the allopatric model of speciation, temporary geographic isolation is required to form reproductive barriers. Whenever two populations gain secondary contact, they may interbreed, depending on whether they still recognize each other as members of the same reproductive unit. Species tend to lose mobility with an increasing level of specialization (Fryer and Iles, 1972). Specialists may be subdivided into populations according to the discontinuous presence of habitats, such as rocky habitats that are interleaved by sandy shores. Data of Tropheus from Wapembe, where two genotypes of two major mitochondrial lineages were found in individuals of a single geographical "race," suggest a past hybridization event between an indigenous lineage and a second lineage of in-

vaders (see Fig. 1). The three individuals assigned to the "square lineage" may represent the descendants of the invaders, whereas the fourth individual seems to represent a separate and previously unidentified primary mitochondrial lineage, a relict of the indigenous lineage. A potential case of hybridization was found between T. polli and Tropheus "Kirschfleck" at the Mahale Mountain range (see upper boxed section of Fig. 2). One species, T. polli, may be indigenous and Tropheus "Kirschfleck" might have invaded the area from the opposite shore line when the lake was split. Introgression or hybridization upon secondary contact between invading Tropheus might explain the observed distribution of genotypes. Because both species remained separate and because the observed genetic distances correspond to the splits of the secondary radiations, hybridization may have only occured during the initial phase after secondary contact, and this potential hybrid zone is limited to this one locality. Prezygotic isolation mechanisms may have been perfected due to reinforcement after secondary contact, as was suggested by Butlin (1991). The second alternative, that hybridization may still be going on at very low frequencies so that species boundaries remain intact despite ongoing hybridization, seems less likely because the Kimura distances among heterospecific individuals found so far were always about 3%. As a third alternative, an ancient polymorphism may have persisted, as was shown for cichlid species of Lake Malawi (Moran and Kornfield, 1993). Which of the alternative scenarios is correct may become known when more representative samples become available and when nuclear markers are included in future analyses. Speciation without morphological change can be viewed as one of the characteristics of geographically separated sister species living in complex species communities of similar composition (Sturmbauer and Meyer, 1992). However, sympatry of four morphologically monomorphic species has only been reported for Tropheus so far (Snoeks et al., 1994; C. Sturmbauer et al., personal observations). Whenever sympatric, they are segregated by water depth (Kohda and Yanagisawa, 1992). One species is invariably found in the very upper water layer to a depth of about 2 m, whereas the other species shifts to a greater water depth of 2-6 m. For example, wherever T. polli and Tropheus "Kirschfleck" live sympatrically, T. polli always inhabits the upper zone and Tropheus "Kirschfleck" the deeper zone. The sympatric occurrences of Tropheus species that are virtually identical morphologically may point to the possibility that long-term coexistence may occur by depth segregation rather than morphological change. In the Eretmodini, which only inhabit the up-

7. PhylogeographicPatterns of Cichlid Fishes permost shore sections, sympatric taxa always seem to differ morphologically and hence, ecologically, pointing to the possibility that ecological diversification may be more important for the coexistence of two eretmodines than for two Tropheus. Most eretmodines (it has not been reported for S. marlieri) have a highly complicated system of mouthbrooding (Kuwamura et al., 1989). They are sexually monochromatic and live in permanent pairs. The female broods the eggs and transfers the newly hatched fry to the male which completes the mouthbrooding. In contrast, Tropheus forms temporary pairs in the territory of the male, and the female leaves the male's territory after spawning takes place (Yanagisawa and Nishida, 1991; Sturmbauer and Dallinger, 1995). Tropheus seems to live sedentarily in densely packed communities where both sexes are territorial (Yanagisawa and Nishida, 1991; Sturmbauer and Dallinger, 1995). Color patterns may play a much more important role in the social system of Tropheus and sexual selection may thus be more intense than in the eretmodines. Simochromis species have been observed to move about in schools, and only dominant males keep territories (Brichard, 1989; C. Sturmbauer et al., unpublished observations). In contrast to Tropheus and the Eretmodini, they are sexually dichromatic and more similar to the cichlids of Lake Victoria and Lake Malawi. They may be much more mobile than Tropheus and the eretmodines, which could also explain their lack of phylogeographic structure.

D. Evolutionary Characteristics of Mitochondrial DNA One of the major characteristics of mtDNA results from its one-dimensional path of coalescence, mtDNA phylogenies do not necessarily reflect the true species phylogenies. Sampling error among (maternally inherited) genotypes, hybridization upon secondary contact, differential extinction due to random genetic drift, or the retention of ancient polymorphisms can result in para- or polyphyly of mitochondrial genotypes in a single biological species. However, the paraphyletic placement of taxa does not necessarily imply that mitochondrial phylogenies are incorrect; paraphyly is an inevitable consequence of the evolution of a new species: if one out of several populations of a species undergoes speciation and the other populations remain reproductively compatible, the "older" species becomes paraphyletic. The possible paraphyletic placement of S. erythrodon in lineages B1 and B3 may thus represent a consequence of the speciation of Tanganicodus (in clade B2) within an originally conspecific assemblage (see Fig. 4). In conclusion, populations may

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have strikingly different histories. Although hybridization upon secondary contact may better explain the observed patterns in some populations (such as those along the break points of the lake basins), different alternatives may apply to other situations. Large-scale patterns of the most frequent genotypes are likely to be detected by small sample sizes. A more finely structured understanding of the history of populations, and also about underlying processes, will emerge with increasing sample sizes. The parallel analysis of mitochondrial and nuclear markers will add a second, nonlinear dimension to population studies, resulting from the genetics of nuclear DNA. Taking advantage of the information record in both genomes will be an important task for future studies.

IV. Conclusions The authors' comparative results emphasize the following hierarchy of factors influencing speciation: 1. Most lineages of Tropheus and of the eretmodines show a high degree of intralacustrine endemism. This observation has important implications for taxonomists and future taxonomic work should account for that. Genetic data should be incorporated into species descriptions. 2. A split of Lake Tanganyika during the period of a low lake level, suggested on the basis of seismic data, is independently corroborated by DNA sequences of Tropheus and the eretmodines. This major vicariant event affected the phylogeograpy of all investigated groups of rock-dwelling cichlids. 3. This general trend was overlayed by patterns resulting from specific characteristics of habitats which determine how severely abiotic factors act on each population and thus might explain some of the differences observed. 4. The degree of philopatry may be the dominating biological characteristic of a species, differentially affecting the phylogeographic structures among populations. 5. Finally, each population may adapt to living in specific habitats by evolving new ecological and behavioral characteristics which may also affect their dispersal ability.

References Avise, J. C. 1994. "Molecular Markers, Natural History and Evolution." Chapman and Hall, New York. Axelrod, H. R. 1993. "The Most Complete Colored Lexiconof Cichlids." T.F.H.,Neptune City, NJ. Barlow, G. W., 1991.Mating systems among cichlid fishes. In "Cich-

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Mayr, E. 1984. Evolution of fish species flocks: A commentary. In "Evolution of Fish Species Flocks" (A. A. Echelle and I. Kornfield, eds.), pp. 3-11. University of Maine at Orono Press, Orono. McElroy, D. M., and Kornfield, I. 1990. Sexual selection, reproductive behavior, and speciation in the Mbuna species flock of Lake Malawi (Pisces: Cichlidae). Environ. Biol. Fish. 28:273-284. McKaye, K. R., and Gray, W. N. 1984. Extrinsic barriers to gene flow in rock-dwelling cichlids of Lake Malawi: Macrohabitat heterogeneity and reef colonization. In "Evolution of Fish Species Flocks" (A. A. Echelle and I. Kornfield, eds.), pp. 169-183. University of Maine at Orono Press, Orono. Meyer, A. 1993. Evolution of mitochondrial DNA in fishes. In "Molecular Biology Frontiers, Biochemestry and Molecular Biology of Fishes" (P. W. Hochacka and T. P. Mommsen, eds.), Vol. 2, pp. 1-38. Elsevier, Amsterdam. Meyer, A. 1994. DNA technology and phylogeny of fish: Molecular phylogenetic studies of fish. In "Genetics and Evolution of Aquatic Organisms" (A. R. Beaumont, ed.), pp. 219-249. Chapman and Hall, London. Meyer, A., Knowles, L., and Verheyen, E. 1996. Widespread geographic distribution of mitochondrial haplotypes in Lake Tanganyika rock-dwelling fishes. Mot. Ecol. 5:341-350. Meyer, A., Kocher, T. D., Basasibwaki, P. and Wilson, A. C. 1990. Monophyletic origin of Lake Victoria cichlid fishes suggested by mitochondrial DNA sequences. Nature 347:550-553. Moran, P., and Kornfield, I. 1993. Retention of an ancestral polymorphism in the Mbuna species flock (Teleostei: Cichlidae) of Lake Malawi. Mol. Biol. Evol. 10:1015-1029. Moran, P., and Kornfield, I. 1995. Were population bottlenecks associated with the radiation of the Mbuna species flock (Teleostei: Cichlidae) of Lake Malawi? Mol. Biol. Evol. 12:1085-1093. Moran, P., Kornfield, I., and Reinthal, P. N. 1994. Molecular systematics and radiation of the haplochromine cichlids (Teleostei: Perciformes) from Lake Malawi. Copeia 1994:274-288. Nishida, M. 1991. Lake Tanganyika as an evolutionary reservoir of old lineages of East African cichlid fishes: Inferences from allozyme data. Experientia 47:974-979. Poll, M. 1986. Classification des cichlidae du lac Tanganika. Tribus, genres et aspeces. Acad. Roy. de Belg. Memories de la classe des sciences, Collection in - 8~ - 2~ serie, T. XLV--Fascicule 2:1 - 163. R~iber, L. 1994. "Phylogenetic and Phylogeographic Patterns in the Endemic Tanganyikan Cichlid Tribe Eretmodini, Inferred from mtDNA Sequences." Masters thesis, Zoological Museum of the University of Z~irich, Switzerland. Saitou, N., and Nei, M. 1987. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406-425. Scholz, C. A., and Rosendahl, B. R. 1988. Low lake stands in Lakes Malawi and Tanganyika, delineated with multifold seismic data. Science 240:1645-1648. Snoeks, J., R~iber, L., and Verheyen, E. 1994. The Tanganyika problem: Taxonomy and distribution of its ichthyofauna. In "Speciation in Ancient Lakes" (K. Martens, B. Goddeeris and G. Coulter, eds.), Adv. in Limnol. 44:357-374. Sturmbauer, C., and Dallinger, R. 1995. Diurnal variation of spacing and foraging behaviour in Tropheus moorii (Cichlidae) in Lake Tanganyika, eastern Africa. Neth. J. Zool. 45:386-401. Sturmbauer, C., Mark, W., and Dallinger, R. 1992. Ecophysiology of Aufwuchs-eating cichlids in Lake Tanganyika: Niche separation by trophic specialization. Environ. Biol. Fish. 35:283-290. Sturmbauer, C., and Meyer, A. 1992. Genetic divergence, speciation and morphological stasis in a lineage of African cichlid fishes. Nature 359:578-581. Sturmbauer, C., and Meyer, A. 1993. Mitochondrial phylogeny of the endemic mouthbrooding lineages of cichlid fishes of Lake Tanganyika, East Africa. Mol. Biol. Evol. 10: 751- 768.

7. Phylogeographic Patterns of Cichlid Fishes Sturmbauer, C, Verheyen, E., and Meyer, A. 1994. Mitochondrial phylogeny of the Lamprologini, the major substrate spawning lineage of cichlid fishes from Lake Tanganyika in eastern Africa. Mol. Biol. Evol. 11:691-703. Swofford, D. L. 1993. "Phylogenetic Analysis Using Parsimony (PAUP) Version 3.1.1." Smithsonian Institution, Washington, D.C. Tiercelin, J. J., and Mondeguer, A. 1991. The geology of the Tanganyika Trough. In "Lake Tanganyika and Its Life" (G. W. Coulter, ed.), pp. 7-48. Oxford University Press, London Oxford and New York.

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Verheyen, E., R(iber, L., Snoeks, J., and Meyer, A. 1996. Mitochondrial phylogeography of rock dwelling cichlid fishes reveals evolutionary influence of historic lake level fluctuations in Lake Tanganyika, Africa. Phil. Trans. Roy. Soc. Ser. B. 351:797-805. Yamaoka, K., Hori, M., and Kuratani, S. 1986. Ecomorphology of feeding in "goby-like" cichlid fishes in Lake Tanganyika. Physiol. Ecol. Jap. 23:17-29. Yanagisawa, Y., and Nishida, M. 1991. The social and mating system of the maternal mouthbrooder Tropheus moorii (Cichlidae) in Lake Tanganyika. Jap. J. Ichthyol. 38: 43- 50.

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8 Fish Biogeography and Molecular Clocks: Perspectives from the Panamanian Isthmus ELDREDGE B E R M I N G H A M S. SHAWN McCAFFERTY, and A N D R E W P. MARTIN Smithsonian Tropical Research Institute Balboa, Republic of Panama

through which the primary freshwater fishes of South America have invaded Central America. Bussing (1976, 1985) presented a more complete analysis of the origin of the region's freshwater fish fauna and supported an early Tertiary arrival in Central America for some characiform fishes. Nevertheless, he also recognized that the vast majority of primary freshwater fish reached Central America sometime in the Pliocene. Because the invasion of Central America by South American freshwater fish is believed recent, molecule-based biogeographic analyses provide one of the best opportunities to chronicle a major colonization episode and the subsequent assembly and diversification of a modern freshwater fish fauna. This chapter focuses on fish biogeography, particularly the geography of conspecific populations of tropical marine and freshwater fishes. At the core of this discussion lies the idea that molecule-based phylogenetic hypotheses are particularly useful for historical biogeographic analyses of recent earth history events (Bermingham et al., 1992). It is often the case that morphologically monotypic species with ranges that cross one or more centers of endemism exhibit molecular divergence. For example, mitochondrial DNA (mtDNA) phylogeography has demonstrated convincingly that differentiated conspecific populations can provide historical information about a region (Bermingham and

I. I n t r o d u c t i o n

Panama provides a rich landscape against which to study the evolution of fish and molecules. This is because roughly 3 million years ago part of Panama rose to complete the Central American fusion of the North and South American continents. In the process, a marine connection between the eastern Pacific Ocean and the Caribbean Sea was severed. Thus, the Pliocene rise of the Isthmus of Panama initiated, or perhaps continued, an evolutionary experiment of grand scale (Rubinoff and Leigh, 1990). Jordan (1908) developed his "law of geminate species" based on his observations of marine fish "sister" taxa found on either side of the Panamanian isthmus. Seventy years later Vawter and coworkers (1980) used Jordan's geminate taxa to test and support the "molecular clock" hypothesis. The Central American Isthmus has also played a prominent role in discussions pertaining to the dispersal and diversification of neotropical freshwater fishes. Darlington (1957) suggested that the South American freshwater fish fauna had been derived from Asian immigrants filtering through North and Central America, although several years later he began changing his view (Darlington, 1964). Myers (1966) and Miller (1966) formally recognized the importance of Panama's narrow isthmus as a terrestrial corridor along and MOLECULAR SYSTEMATICS OF FISHES

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Avise, 1986; Avise et al., 1987; Bermingham et al., 1992, 1996; Avise, 1994; Seutin et al., 1994; Joseph et al., 1995). Furthermore, to the extent that molecular clocks are reliable, one can establish the approximate chronology of branch points in molecular phylogenies (Bermingham et al., 1992; Page, 1991, 1993; Bermingham and Lessios, 1993; Knowlton et al., 1993). In turn, these chronologies can be used to test hypotheses related to geologically dated vicariant events (Sarich and Wilson, 1967; Beverly and Wilson, 1985; Bermingham et al., 1992; Joseph et al., 1995). Molecular data permit one to assess whether both the branching pattern and the general timing of speciation events conform to vicariant models of species diversification. Fishes collected in the marine and freshwater environments of Panama have provided opportunities to study fish molecular clocks and historical biogeography within a recent time frame of earth history. This time frame is appropriate to empirically document the role that historical contingency plays in the assembly and maintenance of biological communities. Such historical reconstructions help to convey the dynamics of evolutionary changes in species and of ecological changes in communities (Cornell and Lawton, 1992; Ricklefs and Schluter, 1993). It is already the case that studies of tropical species have documented levels of genetic divergence between geographic populations that are generally high in comparison to temperate species (Capparella, 1991; Hackett and Rosenberg, 1990; Escalante-Pliego, 1991; Patton and Smith, 1992; Peterson et al., 1992; daSilva and Patton, 1993; Seutin et al., 1993, 1994; Joseph et al., 1995; Brawn et al., 1996; Bermingham et al., 1996). At the very least, these results have important implications concerning our knowledge of species diversity and the conservation of tropical communities.

II. TemporalScaling: The Panama Isthmus and Molecular Clocks The first goal of this chapter is to provide insight into the mechanics and reliability of mitochondrial molecular clocks functioning across shallow spans of time. Generally speaking, we are interested in taxa that have diversified in the Miocene or forward. For the study of such recent speciation events one can only rarely rely on paleontological evidence to yield age estimates of taxic origins (Grande, 1985; Patterson, 1975). Temporal scaling of branch points in phylogenies is critically important for constraining hypotheses on correlation or causation between evolutionary and earth history events (Page, 1991, 1993; Lundberg, 1993) and strongly indicates an exaggerated role for molecular clocks in

studies of