Advances in
BOTANICAL RESEARCH Series Editors JEAN-CLAUDE KADER
Laboratoire Physiologie Cellulaire et Mole´culaire des Plantes, CNRS, Universite´ de Paris, Paris, France
MICHEL DELSENY
Laboratoire Ge´nome et De´veloppement des Plantes, CNRS IRD UP, Universite´ de Perpignan, Perpignan, France
Academic Press is an imprint of Elsevier 32 Jamestown Road, London NW17BY, UK 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2010 Copyright ß 2010, Elsevier Ltd. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher. Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email:
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CONTRIBUTORS TO VOLUME 56
J. AHMAD Proteomics & Bioinformatics Laboratory, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India H. BASHIR Proteomics & Bioinformatics Laboratory, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India NICHOLAS N. BOERSMA Department of Agronomy, Iowa State University, Ames, IA, USA MARK B. DAVID Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA FRANK G. DOHLEMAN Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA EMILY A. HEATON Department of Agronomy, Iowa State University, Ames, IA, USA M. IQBAL Molecular Ecology Laboratory, Department of Botany, Jamia Hamdard, New Delhi, India JOHN A. JUVIK Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA STEPHEN P. LONG Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA VERA LOZOVAYA Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA GREGORY F. MCISAAC Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA A. FERNANDO MIGUEZ Department of Agronomy, Iowa State University, Ames, IA, USA S. MUNEER Proteomics & Bioinformatics Laboratory, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India M. I. QURESHI Proteomics & Bioinformatics Laboratory, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India APICHART VANAVICHIT Rice Gene Discovery, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Kamphangsaen, Nakhonpathom, Thailand; Rice Science Center and Agronomy Department, Faculty of Agriculture, Kamphangsaen, Nakhonpathom, Thailand THOMAS B. VOIGT Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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CONTRIBUTORS
JACK WIDHOLM Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA TADACHI YOSHIHASHI Postharvest Science and Technology Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Ibaraki, Japan OLGA A. ZABOTINA Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, USA
CONTENTS OF VOLUMES 35–55 Series Editor (Volumes 35–44) J.A. CALLOW School of Biosciences, University of Birmingham, Birmingham, United Kingdom
Contents of Volume 35 Recent Advances in the Cell Biology of Chlorophyll Catabolism H. THOMAS, H. OUGHAM and S. HORTENSTEINER The Microspore: A Haploid Multipurpose Cell A. TOURAEV, M. PFOSSER and E. HEBERLE-BORS The Seed Oleosins: Structure Properties and Biological Role J. NAPIER, F. BEAUDOIN, A. TATHAM and P. SHEWRY Compartmentation of Proteins in the Protein Storage Vacuole: A Compound Organelle in Plant Cells L. JIANG and J. ROGERS Intraspecific Variation in Seaweeds: The Application of New Tools and Approaches C. MAGGS and R. WATTIER Glucosinolates and Their Degradation Products R. F. MITHEN
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Contents of Volume 36 PLANT VIRUS VECTOR INTERACTIONS Edited by R. Plumb Aphids: Non-Persistent Transmission T. P. PIRONE and K. L. PERRY Persistent Transmission of Luteoviruses by Aphids B. REAVY and M. A. MAYO Fungi M. J. ADAMS Whitefly Transmission of Plant Viruses J. K. BROWN and H. CZOSNEK Beetles R. C. GERGERICH Thrips as Vectors of Tospoviruses D. E. ULLMAN, R. MEIDEROS, L. R. CAMPBELL, A. E. WHITFIELD, J. L. SHERWOOD and T. L. GERMAN Virus Transmission by Leafhoppers, Planthoppers and Treehoppers (Auchenorrhyncha, Homoptera) E. AMMAR and L. R. NAULT Nematodes S. A. MacFARLANE, R. NEILSON and D. J. F. BROWN Other Vectors R. T. PLUMB
CONTENTS OF VOLUMES 35–55
Contents of Volume 37 ANTHOCYANINS IN LEAVES Edited by K. S. Gould and D. W. Lee Anthocyanins in Leaves and Other Vegetative Organs: An Introduction D. W. LEE and K. S. GOULD Le Rouge et le Noir: Are Anthocyanins Plant Melanins? G. S. TIMMINS, N. M. HOLBROOK and T. S. FEILD Anthocyanins in Leaves: History, Phylogeny and Development D. W. LEE The Final Steps in Anthocyanin Formation: A Story of Modification and Sequestration C. S. WINEFIELD Molecular Genetics and Control of Anthocyanin Expression B. WINKEL-SHIRLEY Differential Expression and Functional Significance of Anthocyanins in Relation to Phasic Development in Hedera helix L. W. P. HACKETT Do Anthocyanins Function as Osmoregulators in Leaf Tissues? L. CHALKER-SCOTT The Role of Anthocyanins for Photosynthesis of Alaskan Arctic Evergreens During Snowmelt S. F. OBERBAUER and G. STARR Anthocyanins in Autumn Leaf Senescence D. W. LEE A Unified Explanation for Anthocyanins in Leaves? K. S. GOULD, S. O. NEILL and T. C. VOGELMANN
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Contents of Volume 38 An Epidemiological Framework for Disease Management C. A. GILLIGAN Golgi-independent Trafficking of Macromolecules to the Plant Vacuole D. C. BASSHAM Phosphoenolpyruvate Carboxykinase: Structure, Function and Regulation R. P. WALKER and Z.-H. CHEN Developmental Genetics of the Angiosperm Leaf C. A. KIDNER, M. C. P. TIMMERMANS, M. E. BYRNE and R. A. MARTIENSSEN A Model for the Evolution and Genesis of the Pseudotetraploid Arabidopsis thaliana Genome Y. HENRY, A. CHAMPION, I. GY, A. PICAUD, A. LECHARNY and M. KREIS
Contents of Volume 39 Cumulative Subject Index Volumes 1–38
Contents of Volume 40 Starch Synthesis in Cereal Grains K. TOMLINSON and K. DENYER The Hyperaccumulation of Metals by Plants M. R. MACNAIR Plant Chromatin — Learning from Similarities and Differences J. BRZESKI, J. DYCZKOWSKI, S. KACZANOWSKI, P. ZIELENKIEWICZ and A. JERZMANOWSKI
CONTENTS OF VOLUMES 35–55
The Interface Between the Cell Cycle and Programmed Cell Death in Higher Plants: From Division unto Death D. FRANCIS The Importance of Extracellular Carbohydrate Production by Marine Epipelic Diatoms G. J. C. UNDERWOOD and D. M. PATERSON Fungal Pathogens of Insects: Cuticle Degrading Enzymes and Toxins A. K. CHARNLEY
Contents of Volume 41 Multiple Responses of Rhizobia to Flavonoids During Legume Root Infection JAMES E. COOPER Investigating and Manipulating Lignin Biosynthesis in the Postgenomic Era CLAIRE HALPIN Application of Thermal Imaging and Infrared Sensing in Plant Physiology and Ecophysiology HAMLYN G. JONES Sequences and Phylogenies of Plant Pararetroviruses, Viruses, and Transposable Elements CELIA HANSEN and J. S. HESLOP-HARRISON
Role of Plasmodesmata Regulation in Plant Development ARNAUD COMPLAINVILLE and MARTIN CRESPI
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Contents of Volume 42 Chemical Manipulation of Antioxidant Defences in Plants ROBERT EDWARDS, MELISSA BRAZIER-HICKS, DAVID P. DIXON and IAN CUMMINS The Impact of Molecular Data in Fungal Systematics P. D. BRIDGE, B. M. SPOONER and P. J. ROBERTS Cytoskeletal Regulation of the Plane of Cell Division: An Essential Component of Plant Development and Reproduction HILARY J. ROGERS Nitrogen and Carbon Metabolism in Plastids: Evolution, Integration, and Coordination with Reactions in the Cytosol ALYSON K. TOBIN and CAROLINE G. BOWSHER
Contents of Volume 43 Defensive and Sensory Chemical Ecology of Brown Algae CHARLES D. AMSLER and VICTORIA A. FAIRHEAD Regulation of Carbon and Amino Acid Metabolism: Roles of Sucrose Nonfermenting-1-Related Protein Kinase-1 and General Control Nonderepressible-2-Related Protein Kinase NIGEL G. HALFORD Opportunities for the Control of Brassicaceous Weeds of Cropping Systems Using Mycoherbicides AARON MAXWELL and JOHN K. SCOTT Stress Resistance and Disease Resistance in Seaweeds: The Role of Reactive Oxygen Metabolism MATTHEW J. DRING Nutrient Sensing and Signalling in Plants: Potassium and Phosphorus ANNA AMTMANN, JOHN P. HAMMOND, PATRICK ARMENGAUD and PHILIP J. WHITE
CONTENTS OF VOLUMES 35–55
Contents of Volume 44 Angiosperm Floral Evolution: Morphological Developmental Framework PETER K. ENDRESS Recent Developments Regarding the Evolutionary Origin of Flowers MICHAEL W. FROHLICH Duplication, Diversification, and Comparative Genetics of Angiosperm MADS-Box Genes VIVIAN F. IRISH Beyond the ABC-Model: Regulation of Floral Homeotic Genes LAURA M. ZAHN, BAOMIN FENG and HONG MA Missing Links: DNA-Binding and Target Gene Specificity of Floral Homeotic Proteins RAINER MELZER, KERSTIN KAUFMANN ¨ NTER THEIßEN and GU Genetics of Floral Development in Petunia ANNEKE RIJPKEMA, TOM GERATS and MICHIEL VANDENBUSSCHE Flower Development: The Antirrhinum Perspective BRENDAN DAVIES, MARIA CARTOLANO and ZSUZSANNA SCHWARZ-SOMMER Floral Developmental Genetics of Gerbera (Asteraceae) TEEMU H. TEERI, MIKA KOTILAINEN, ANNE UIMARI, SATU RUOKOLAINEN, YAN PENG NG, URSULA MALM, ¨ NEN, SUVI BROHOLM, ROOSA LAITINEN, ¨ LLA EIJA PO PAULA ELOMAA and VICTOR A. ALBERT Gene Duplication and Floral Developmental Genetics of Basal Eudicots ELENA M. KRAMER and ELIZABETH A. ZIMMER
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Genetics of Grass Flower Development CLINTON J. WHIPPLE and ROBERT J. SCHMIDT Developmental Gene Evolution and the Origin of Grass Inflorescence Diversity SIMON T. MALCOMBER, JILL C. PRESTON, RENATA REINHEIMER, JESSIE KOSSUTH and ELIZABETH A. KELLOGG Expression of Floral Regulators in Basal Angiosperms and the Origin and Evolution of ABC-Function PAMELA S. SOLTIS, DOUGLAS E. SOLTIS, SANGTAE KIM, ANDRE CHANDERBALI and MATYAS BUZGO The Molecular Evolutionary Ecology of Plant Development: Flowering Time in Arabidopsis thaliana KATHLEEN ENGELMANN and MICHAEL PURUGGANAN A Genomics Approach to the Study of Ancient Polyploidy and Floral Developmental Genetics JAMES H. LEEBENS-MACK, KERR WALL, JILL DUARTE, ZHENGUI ZHENG, DAVID OPPENHEIMER and CLAUDE DEPAMPHILIS Series Editors (Volume 45– ) JEAN-CLAUDE KADER Laboratoire Physiologie Cellulaire et Mole´culaire des Plantes, CNRS, Universite´ de Paris, Paris, France MICHEL DELSENY Laboratoire Ge´nome et De´veloppement des Plantes, CNRS IRD UP, Universite´ de Perpignan, Perpignan, France
Contents of Volume 45 RAPESEED BREEDING History, Origin and Evolution S. K. GUPTA and ADITYA PRATAP
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Breeding Methods B. RAI, S. K. GUPTA and ADITYA PRATAP The Chronicles of Oil and Meal Quality Improvement in Oilseed Rape ABHA AGNIHOTRI, DEEPAK PREM and KADAMBARI GUPTA Development and Practical Use of DNA Markers KATARZYNA MIKOLAJCZYK Self-Incompatibility RYO FUJIMOTO and TAKESHI NISHIO Fingerprinting of Oilseed Rape Cultivars ´ ˇ URN and JANA ZˇALUDOVA VLADISLAV C Haploid and Doubled Haploid Technology L. XU, U. NAJEEB, G. X. TANG, H. H. GU, G. Q. ZHANG, Y. HE and W. J. ZHOU Breeding for Apetalous Rape: Inheritance and Yield Physiology LIXI JIANG Breeding Herbicide-Tolerant Oilseed Rape Cultivars PETER B. E. MCVETTY and CARLA D. ZELMER Breeding for Blackleg Resistance: The Biology and Epidemiology W. G. DILANTHA FERNANDO, YU CHEN and KAVEH GHANBARNIA Development of Alloplasmic Rape MICHAL STARZYCKI, ELIGIA STARZYCKI and JAN PSZCZOLA Honeybees and Rapeseed: A Pollinator–Plant Interaction D. P. ABROL
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Genetic Variation and Metabolism of Glucosinolates NATALIA BELLOSTAS, ANNE DORTHE SØRENSEN, JENS CHRISTIAN SØRENSEN and HILMER SØRENSEN Mutagenesis: Generation and Evaluation of Induced Mutations SANJAY J. JAMBHULKAR Rapeseed Biotechnology VINITHA CARDOZA and C. NEAL STEWART, JR. Oilseed Rape: Co-existence and Gene Flow from Wild Species RIKKE BAGGER JØRGENSEN Evaluation, Maintenance, and Conservation of Germplasm RANBIR SINGH and S. K. SHARMA Oil Technology ¨ US BERTRAND MATTHA
Contents of Volume 46 INCORPORATING ADVANCES IN PLANT PATHOLOGY Nitric Oxide and Plant Growth Promoting Rhizobacteria: Common Features Influencing Root Growth and Development ´ NICA CREUS, MARI´A CELESTE MOLINA-FAVERO, CECILIA MO LUCIANA LANTERI, NATALIA CORREA-ARAGUNDE, MARI´A CRISTINA LOMBARDO, CARLOS ALBERTO BARASSI and LORENZO LAMATTINA How the Environment Regulates Root Architecture in Dicots ´ RIE LEFEBVRE, PHILIPPE MARIANA JOVANOVIC, VALE LAPORTE, SILVINA GONZALEZ-RIZZO, CHRISTINE LELANDAIS-BRIE`RE, FLORIAN FRUGIER, CAROLINE HARTMANN and MARTIN CRESPI
CONTENTS OF VOLUMES 35–55
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Aquaporins in Plants: From Molecular Structure to Integrated Functions OLIVIER POSTAIRE, LIONEL VERDOUCQ and CHRISTOPHE MAUREL Iron Dynamics in Plants JEAN-FRANC ¸ OIS BRIAT Plants and Arbuscular Mycorrhizal Fungi: Cues and Communication in the Early Steps of Symbiotic Interactions VIVIENNE GIANINAZZI-PEARSON, NATHALIE SE´JALON-DELMAS, ANDREA GENRE, SYLVAIN JEANDROZ and PAOLA BONFANTE Dynamic Defense of Marine Macroalgae Against Pathogens: From Early Activated to Gene-Regulated Responses AUDREY COSSE, CATHERINE LEBLANC and PHILIPPE POTIN
Contents of Volume 47 INCORPORATING ADVANCES IN PLANT PATHOLOGY The Plant Nucleolus ´ EZ-VA ´ SQUEZ AND FRANCISCO JAVIER MEDINA JULIO SA Expansins in Plant Development DONGSU CHOI, JEONG HOE KIM AND YI LEE Molecular Biology of Orchid Flowers: With Emphasis on Phalaenopsis WEN-CHIEH TSAI, YU-YUN HSIAO, ZHAO-JUN PAN, CHIACHI HSU, YA-PING YANG, WEN-HUEI CHEN AND HONG-HWA CHEN
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Molecular Physiology of Development and Quality of Citrus ´ S, JOSE´ M. FRANCISCO R. TADEO, MANUEL CERCO COLMENERO-FLORES, DOMINGO J. IGLESIAS, MIGUEL A. NARANJO, GABINO RI´OS, ESTHER CARRERA, OMAR RUIZ-RIVERO, IGNACIO LLISO, RAPHAE¨ L MORILLON, PATRICK OLLITRAULT AND MANUEL TALON Bamboo Taxonomy and Diversity in the Era of Molecular Markers MALAY DAS, SAMIK BHATTACHARYA, PARAMJIT SINGH, TARCISO S. FILGUEIRAS AND AMITA PAL
Contents of Volume 48 Molecular Mechanisms Underlying Vascular Development JAE-HOON JUNG, SANG-GYU KIM, PIL JOON SEO AND CHUNG-MO PARK Clock Control Over Plant Gene Expression ANTOINE BAUDRY AND STEVE KAY Plant Lectins ELS J. M. VAN DAMME, NAUSICAA LANNOO AND WILLY J. PEUMANS Late Embryogenesis Abundant Proteins MING-DER SHIH, FOLKERT A. HOEKSTRA AND YUE-IE C. HSING
Contents of Volume 49 Phototropism and Gravitropism in Plants MARIA LIA MOLAS AND JOHN Z. KISS
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Cold Signalling and Cold Acclimation in Plants ERIC RUELLAND, MARIE-NOELLE VAULTIER, ALAIN ZACHOWSKI AND VAUGHAN HURRY Genome Evolution in Plant Pathogenic and Symbiotic Fungi GABRIELA AGUILETA, MICHAEL E. HOOD, GUISLAINE REFRE´GIER AND TATIANA GIRAUD
Contents of Volume 50 Aroma Volatiles: Biosynthesis and Mechanisms of Modulation During Fruit Ripening BRUNO G. DEFILIPPI, DANIEL MANRI´QUEZ, ´ LEZ-AGU ¨ ERO KIETSUDA LUENGWILAI AND MAURICIO GONZA Jatropha curcas: A Review NICOLAS CARELS You are What You Eat: Interactions Between Root Parasitic Plants and Their Hosts LOUIS J. IRVING AND DUNCAN D. CAMERON Low Oxygen Signaling and Tolerance in Plants FRANCESCO LICAUSI AND PIERDOMENICO PERATA Roles of Circadian Clock and Histone Methylation in the Control of Floral Repressors RYM FEKIH, RIM NEFISSI, KANA MIYATA, HIROSHI EZURA AND TSUYOSHI MIZOGUCHI
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Contents of Volume 51 PAMP-Triggered Basal Immunity in Plants ¨ RNBERGER AND BIRGIT KEMMERLING THORSTEN NU Plant Pathogens as Suppressors of Host Defense ´ TRAUX, ROBERT WILSON JACKSON, JEAN-PIERRE ME ESTHER SCHNETTLER AND ROB W. GOLDBACH From Nonhost Resistance to Lesion-Mimic Mutants: Useful for Studies of Defense Signaling ANDREA LENK AND HANS THORDAL-CHRISTENSEN Action at a Distance: Long-Distance Signals in Induced Resistance MARC J. CHAMPIGNY AND ROBIN K. CAMERON Systemic Acquired Resistance R. HAMMERSCHMIDT Rhizobacteria-Induced Systemic Resistance ¨ FTE DAVID DE VLEESSCHAUWER AND MONICA HO Plant Growth-Promoting Actions of Rhizobacteria STIJN SPAEPEN, JOS VANDERLEYDEN AND YAACOV OKON Interactions Between Nonpathogenic Fungi and Plants M. I. TRILLAS AND G. SEGARRA Priming of Induced Plant Defense Responses UWE CONRATH Transcriptional Regulation of Plant Defense Responses MARCEL C. VAN VERK, CHRISTIANE GATZ AND HUUB J. M. LINTHORST
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Unexpected Turns and Twists in Structure/Function of PR-Proteins that Connect Energy Metabolism and Immunity MEENA L. NARASIMHAN, RAY A. BRESSAN, MATILDE PAINO D’URZO, MATTHEW A. JENKS AND TESFAYE MENGISTE Role of Iron in Plant–Microbe Interactions P. LEMANCEAU, D. EXPERT, F. GAYMARD, P. A. H. M. BAKKER AND J.-F. BRIAT Adaptive Defense Responses to Pathogens and Insects LINDA L. WALLING Plant Volatiles in Defence MERIJN R. KANT, PETRA M. BLEEKER, MICHIEL VAN WIJK, ROBERT C. SCHUURINK AND MICHEL A. HARING Ecological Consequences of Plant Defence Signalling MARTIN HEIL AND DALE R. WALTERS
Contents of Volume 52 Oxidation of Proteins in Plants—Mechanisms and Consequences LEE J. SWEETLOVE AND IAN M. MØLLER Reactive Oxygen Species: Regulation of Plant Growth and Development HYUN-SOON KIM, YOON-SIK KIM, KYU-WOONG HAHN, HYOUK JOUNG AND JAE-HEUNG JEON Ultraviolet-B Induced Changes in Gene Expression and Antioxidants in Plants S. B. AGRAWAL, SURUCHI SINGH AND MADHOOLIKA AGRAWAL
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Roles of -Glutamyl Transpeptidase and -Glutamyl Cyclotransferase in Glutathione and Glutathione-Conjugate Metabolism in Plants NAOKO OHKAMA-OHTSU, KEIICHI FUKUYAMA AND DAVID J. OLIVER The Redox State, a Referee of the Legume–Rhizobia Symbiotic Game DANIEL MARINO, CHIARA PUCCIARIELLO, ALAIN PUPPO AND PIERRE FRENDO
Contents of Volume 53 Arabidopsis Histone Lysine Methyltransferases FRE´DE´ RIC PONTVIANNE, TODD BLEVINS, AND CRAIG S. PIKAARD Advances in Coffea Genomics ALEXANDRE DE KOCHKO, SE´LASTIQUE AKAFFOU, ALAN ANDRADE, CLAUDINE CAMPA, DOMINIQUE CROUZILLAT, ROMAIN GUYOT, PERLA HAMON, RAY MING, LUKAS A. MUELLER, VALE´RIE PONCET, CHRISTINE TRANCHANTDUBREUIL, AND SERGE HAMON Regulatory Components of Shade Avoidance Syndrome JAIME F. MARTI´NEZ-GARCI´A, ANAHIT GALSTYAN, ´ S CIFUENTES-ESQUIVEL, MERCE`SALLA-MARTRET, NICOLA ´ MARC¸ AL GALLEMI, AND JORDI BOU-TORRENT Responses of Halophytes to Environmental Stresses with Special Emphasis to Salinity KSOURI RIADH, MEGDICHE WIDED, KOYRO HANS-WERNER, AND ABDELLY CHEDLY Plant Nematode Interaction: A Sophisticated Dialogue PIERRE ABAD AND VALERIE M. WILLIAMSON
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Optimization of Nutrition in Soilless Systems: A Review ´ NGELES CALATAYUD ELISA GORBE AND A
Contents of Volume 54 Pollen Germination and Tube Growth HUEI-JING WANG, JONG-CHIN HUANG, AND GUANG-YUH JAUH Molecular Mechanisms of Sex Determination in Monoecious and Dioecious Plants GEORGE CHUCK The Evolution of Floral Symmetry HE´LE`NE CITERNE, FLORIAN JABBOUR, SOPHIE NADOT, AND CATHERINE DAMERVAL Protein Turnover in Grass Leaves LOUIS JOHN IRVING, YUJI SUZUKI, HIROYUKI ISHIDA, AND AMANE MAKINO
Contents of Volume 55 Carpel Development ´ NDIZ, CHLOE´ FOURQUIN, CRISTINA FERRA NATHANAEL PRUNET, CHARLIE P. SCUTT, EVA SUNDBERG, CHRISTOPHE TREHIN, AND AURE´LIE C. M. VIALETTE-GUIRAUD Root System Architecture PAUL A. INGRAM AND JOCELYN E. MALAMY
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Functional Genomics of Cacao FABIENNE MICHELI, MARK GUILTINAN, KARINA PERES GRAMACHO, MIKE J. WILKINSON, ANTONIO VARGAS DE ´ LIO CE´ZAR DE MATTOS CASCARDO, OLIVEIRA FIGUEIRA, JU SIELA MAXIMOVA, AND CLAIRE LANAUD The Ecological Water-Use Strategies of Succulent Plants R. MATTHEW OGBURN AND ERIKA J. EDWARDS
Nodule Physiology and Proteomics of Stressed Legumes
M. I. QURESHI,*,1 S. MUNEER,* H. BASHIR,* J. AHMAD* AND M. IQBAL{
*Proteomics & Bioinformatics Laboratory, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India { Molecular Ecology Laboratory, Department of Botany, Jamia Hamdard, New Delhi, India
I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Plant–Microbe Interaction and Specificity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Infection and Nodulation Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Role of Flotillins and Flavonoids........................................... B. Peribacteroid Membrane ..................................................... C. Gene Regulation in Nodules................................................. IV. Nodule Proteomics: Wet Laboratory and Bioinformatics Procedures . . . . A. Nodule Cultivation and Harvesting ........................................ B. 2DE: IEF and SDS-PAGE................................................... V. Proteomic Response of Nodule to Different Stresses . . . . . . . . . . . . . . . . . . . . . . A. Oxidative Stress-Related Proteins in Nodules............................. B. Pathogenesis-Related Proteins............................................... C. Abiotic Stresses and Identified Proteins in Nodule....................... VI. Applications of Nodule Proteomics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Corresponding author: E-mail:
[email protected]
Advances in Botanical Research, Vol. 56 Copyright 2010, Elsevier Ltd. All rights reserved.
0065-2296/10 $35.00 DOI: 10.1016/S0065-2296(10)56001-4
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ABSTRACT Symbiotic bacteria are harboured in the nodules of the nitrogen-fixing plants. The bacteria, collectively termed rhizobia, include genera such as Rhizobium, Sinorhizobium, Bradyrhizobium, Mesorhizobium and Azorhizobium, and form specialised organs within the plant. Nitrogen fixation occurs via the conversion of N2 into NH3 by bacterial nitrogenases. Knowledge of protein profile (structural and soluble) of bacteria and host may provide information useful in understanding the bacteria–host relationship and improving N2-fixation efficiency in leguminous plants. Although the majority of nitrogen-fixing plants belong to the family Fabaceae, a few non-leguminous plants (like actinorhizal plants) can also fix nitrogen. Proteomics is an ideal tool to study the protein profile and its correlation with nodule-associated metabolic and symbiotic processes. N2-fixing symbioses are well studied but not in terms of proteomic response to abiotic stress. Data obtained in some proteomic studies on Medicago trancatula and few other leguminous plants provide useful information on root nodules, their symbiotic bacteria and the proteins produced by both partners during their constant signal exchange and growth. Mass spectrometric analysis has helped in identifying several proteins, including those associated with molecular regulation, respiration and leghaemoglobin, proteases in the nodule. Differential expression of proteins under different abiotic stresses such as temperature, drought, salinity and toxic metals that affect the profile of nodule proteome is believed to be due to the production of oxidative stress, osmotic imbalance and other direct or secondary consequences of stress. However, nutrient stress also affects proteome profile as in iron deficiency. Iron-containing proteins play a key role in symbiotic nitrogen fixation (SNF) that occurs in the nodule. Several proteins like those related to SNF, predominant components of nitrogenase complexes such as nifD, nifH, nifK, nitrogen regulatory protein II (GlnB) and PIIA (PtsN) and urease accessory protein (UreE) are known to be affected by abiotic stress. Nodules are well equipped with antioxidant enzymes (superoxide dismutase, ascorbate peroxidase and glutathione reductase, etc.) which respond to stress conditions. This review introduces nodule physiology and examines critically the recent developments in the field of nodule proteomics, emphasising, in particular, upon changes brought about by abiotic stresses to the nodule proteome, provides up-to-date information on key metabolic proteins that help to combat stress and discusses the prospects of nodule proteomics.
ABBREVIATIONS NFB SOD APX GR PR SNF ESI CBBR
nitrogen-fixing bacteria superoxide dismutase ascorbate peroxidase glutathione reductase pathogenesis-related proteins symbiotic nitrogen fixation electrospray ionisation coomassie brilliant blue-R
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I. INTRODUCTION Even though nitrogen (N) is among the most abundant elements on the Earth and a major constituent of air, it is the critical limiting element for growth of most plants due to its non-availability (Graham and Vance, 2000; Smil, 1999; Socolow, 1999). Since proteins form structural and regulatory network of life, their production solely depends on availability of sufficient N. Plants acquire N from (a) the soil through mineralisation of organic matter and (b) the atmosphere through symbiotic N2 fixation. The entire amount of nutritional N required by humans is obtained directly or indirectly from plants. However, since the 1970s, management of N inputs into agricultural systems has become a contentious issue (Den Herder et al., 2007). Plant root nodules are the knob-like structures formed especially on and from roots of leguminous plants, as a result of symbiotic infection by nitrogen-fixing bacteria such as Rhizobium. The components of a typical nodule include host-plant tissue and N2-fixing bacteria. The N2-fixing organisms are prokaryotic in nature; some eubacteria and a few archaebacteria are capable of N2-fixation, but no eukaryotic cells can do this. Some N2-fixing bacteria are free-living, whereas others form symbiotic associations with plants. Seeds (Maj et al., 2010) during germination or when the leguminous plants attain a certain age, their roots secrete flavonoids, which interact with bacterial proteins of the NodD family (Cesco et al., 2010). For a recent review on flavonoids, see Buer et al. (2010). When NodD binds a flavonoid, it activates the other nodulation genes. Some of the nod genes code for enzymes that produce Nod factors, short oligosaccharides made of three to six molecules of N-acetyl glucosamine plus other sugars such as fucose and with attached fatty acids. These in turn are recognised by the plant. There are many types of flavonoids and Nod factors with variety varying to host and rhizobia. Other mechanisms of interactions between plant and bacteria also operate and vary with species and growth condition (Samac and Graham, 2007). For example, a carbohydrate-binding protein (lectin) on the surface of root cells of clover (Trifolium) specifically binds to lipopolysaccharide of Rhizobium leguminosarum bv. trifolii, which contains 2-deoxyglucose. The bacteria then enter the cell and produce cytokinins that promote plant-cell division and ultimately form nodules. The bacteria lose their outer membranes and become irregular in shape to form the ‘‘bacteroids’’. Being a rich source of proteins, legumes are the staple food for millions of humans and animals. Nitrogen-fixing ability of legumes (in nodules), from physiologically non-available molecular dinitrogen (N2) to available forms, makes them very special in terms of providing nitrogen skeleton to different life forms. Legume growth, development and productivity are directly
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associated with a special type of root-borne organ called ‘‘nodule (symbiosome)’’ which contains several types of proteins associated with N2-fixation such as nifH, nifD, nifK and so on (Souza et al., 2010). One of the beststudied N2-fixing symbioses is one established between certain members of Leguminosae and soil bacteria, collectively termed rhizobia. This symbiotic interaction results in the formation of a unique plant organ, the root nodule, to which the plant supplies reduced carbon for the bacteroids (differentiated form of bacteria) in exchange for fixed nitrogen (Larrainzar et al., 2007). Besides harbouring N2-fixing bacteria and mycorrhiza, nodules are characterised by the presence of leghaemoglobin, ferritin, nitrogenase and specific proteases. Abiotic stresses may significantly alter the protein profile and associated metabolism in leguminous plants that harbour N2-fixing machinery (Willey et al., 2008). Nodule defence against stress is also constituted by protein and non-protein components. Proteins control the regulation of their own and non-protein components in terms of synthesis and function. It becomes crucial to study the nodule-associated metabolism, growth and physiochemistry, to understand all proteomic components and their interactions, and the factors influencing N2-fixing which would help in developing strategies for a better symbiotic association. Proteomics is an ideal tool to study the interaction between root nodules and their symbiotic bacteria, as it provides a broad overview of proteins produced by both partners during their signal exchange and growth of symbiome. It also allows the comparative analysis, in terms of differential protein expression, of leguminous plants under control and stress conditions, indicating changes in metabolic and functioning parameters. Recent advances in proteomics, mass spectrometry (MS) and bioinformatics are greatly helpful in the study of protein expression in biological systems including symbiotic associations (Djordjevic, 2004; Mastronunzio et al., 2009; Natera et al., 2000; Van Wijk, 2001). With the help of the proteomic approach, hundreds of proteins have been identified with the development and functioning of rhizobial symbiosis (Bestel-Corre et al., 2002, 2004; Rolfe et al., 2003; Trevaskis et al., 2002). Proteomics at the level of nodule provides information about the variety of proteins, including proteins of host plant and N2-fixing bacterium; proteins that might be structural, soluble such as in the form of enzymes and their isoforms and expressed at different growth stages and under specific physiological conditions at a given time can also be revealed. The study of nodules at the molecular level provides novel possibilities to address numerous biological questions associated with nodule metabolism and symbiotic association. In fact, the large-scale screening approach of nodule proteomics enables protein-expression studies of both plant and bacteria. This was not possible with the classical molecular biology
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techniques in which the expression of only one or few proteins can usually be studied at a time. Using the high-throughput proteomic technologies, hundreds of proteins may be analysed simultaneously, at the cellular or subcellular level. The strength of the proteomic approach is that no limitations are set for the proteins analysed on cellular function, for example, protein with a role in symbiotic interaction or specific signal transduction pathway. Therefore, this approach helps in the investigation of protein populations that are not previously expected and might be linked to any physiological conditions. In addition, proteomic investigations are not limited to proteins that are already identified and characterised. Furthermore, differential display of expression levels of proteins already identified is also of significant use to understand the molecular mechanisms. They may help to establish links between physiological conditions and with novel or already identified proteins; obtained amino acid sequences are then deduced from nucleic acid sequence of corresponding plant genes using advance software. At certain steps (protein database match and protein–DNA database match), bioinformatics plays a great role in protein and respective gene identification. Recent advancements in staining and MS techniques have aided to high sensitivity of proteomic technologies thus allowing for large-scale screening studies utilising only a minimal amount of protein. Moreover, comparative analysis of protein maps allows for detection of differential expression patterns under different growth conditions, protein residues phosphorylation and even mutation in corresponding genes (Mathesius, 2009). This review aims at evaluating the literature available on the initiation and progression of nodulation with mechanism including formation, establishment and functioning of symbiotic association. This will also present a comprehensive account of changes in nodule-protein profile in response to abiotic stress, and details of nodule proteomic methodology, its applications and benefits.
II. PLANT–MICROBE INTERACTION AND SPECIFICITY The bacteria associated with conversion of atmospheric nitrogen to ammonia, such as Rhizobium, Bradyrhizobium and Azorhizobium (collectively referred to as rhizobia), elicit on their leguminous hosts the formation of specialised organs, the nodules. These structures originate from stem or root and develop as a site of bacterial conversion of atmospheric nitrogen into ammonia, which is used by the plant as a nitrogen source (Van Rhijn and Vanderleyden, 1995). The association of bacterium with a host is specific as
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TABLE I A List of Some Rhizobium Species and Their Corresponding Hosts Rhizobium species Bradyrhizobium japanicum Rhizobium fredii R. phaseoli S. meliloti Rhizobium leguminosarum bv. trifolii R. Ieguminosarum ‘‘Cowpea rhizobia’’ group or Rhizobium sp.
Azorhizobium caulinodans
Host plants Glycine max (soybean) Glycine max (soybean) Phaseolus vulgaris (common bean) Medicago sativa (alfalfa) Melilotus sp. (sweet clovers) Trifolium sp. (clovers) Pisum sativum (peas) Vicia faba (broad bean) Vigna unguiculata (cowpea), Arachis hypogaea (peanut), Vigna subterranea (Bambara groundnut) Leucaena sp., Albizia sp., Sesbania sp. Sesbania rostrata (stem nodulating)
Source: http://www.fao.org/wairdocs/ilri/x5546e/x5546e05.htm.
mentioned in Table I. The plant species very specifically accommodates Rhizobium species in the nodule. For example, Medicago sativa could harbour only Sinorhizobium meliloti; however, S. meliloti can also be harboured by Melilotus and Trifolium spp. Within the nodule, bacterial colonisation results in the formation of bacteroids. All nitrogen-fixing bacteroids within the legume root-nodule cells are surrounded by a host-derived peribacteroid membrane (PBM). Components of this membrane are supplied directly by the endoplasmic reticulum and golgi of the host cell. The peribacteroid space lies between the peribacteroid and bacteroid membranes and contains several activities typically found in vacuoles, namely protease, acid trehalase, -mannosidase isoenzyme II and protein protease inhibitor. Thus, bacteroids inhabit an environment that fulfils the definition of a lysosome. Since the endosymbiotic organelles are morphologically different from the lytic compartment normally present in a root-cortex cell (the central vacuole), it is proposed that they represent organ-specific modifications of lysosomes, analogous to the protein bodies of seeds (see Mellor, 1989).
III. INFECTION AND NODULATION MECHANISMS Nitrogen-fixing ability of legume–rhizobial symbioses has a great potential to improve crop yields even at reduced usage of nitrogenous fertilisers. Unfortunately, the nitrogen-fixing efficiency of many legume–rhizobial
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combinations is low. The nodule efficiency has very much been associated with signal exchange within mature nodules (Schumpp and Deakin, 2010). Furthermore, the mechanism for rhizobial growth suppression but with long persistence of rhizobium in plant cell is largely unknown. It has been suggested recently that defence responses are disabled in mature nodules and superseded by specialised mechanisms of bacterial population control (Schumpp and Deakin, 2010). There might also be other reasons for the differential degree of bacterial infection to legume root, nodule growth rate and physiochemical properties, and function such as texture and physiochemical properties of the soil, availability of non-specific or inefficient strains of bacteria. A careful examination has resulted in the identification of plant flotillins as a factor responsible for causing root infection by N2-fixing bacteria (Haney and Long, 2010). Earlier, flotillins [also called Reggies (Schulte et al., 1997)] were often used as markers for cholesterolrich, detergent-resistant, membrane microdomains called ‘‘lipid rafts’’ and are now known to define a clathrin-independent, caveolin-independent endocytic pathway required for endocytosis of cholera toxin (Glebov et al., 2006). By interacting with effectors that can bind actin, flotillins mediate membrane-shaping events including membrane budding, actin-mediated neuronal differentiation and filopodia formation (Haney and Long, 2010). Wang et al. (2010) identified the DNF1 gene as encoding a subunit of a signal peptidase complex that is highly expressed in nodules. It has also been suggested that nodule-specific cystein-rich peptides govern the terminal differentiation of bacteria in symbiosis (Van de Velde et al., 2010). By analysing data from whole-genome expression analysis, they proposed that the correct symbiosome development in Medicago truncatula requires orderly secretion of protein constituents through coordinated up-regulation of a nodule-specific pathway exemplified by DNF1. A. ROLE OF FLOTILLINS AND FLAVONOIDS
For a successful establishment of compatible rhizobial–legume symbioses, plant roots should support bacterial infection via facilitation of progression of infection threads (ITs). Formation of IT further leads to formation of functional N2-fixing nodules, as a result of a series of molecular and physiochemical events (Freiberg et al., 1997). Haney and Long (2010) have reported requirement of plant flotillin-like genes (FLOTs) expressed during S. meliloti infection by its host legume M. truncatula. Earlier, flotillins have been reported in other organisms playing roles in viral pathogenesis, endocytosis and membrane shaping. Haney and Long (2010) identified seven FLOT genes in the M. truncatula genome and showed that two, FLOT2 and
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Fold change of FLOT expression
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FLOT1
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FLOT2
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FLOT3
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FLOT4
5 4 3 2 1 0 0
5
10
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20
Days post inoculation (dpi)
Fig. 1. Demonstration of expression of FLOTs which is up-regulated during nodulation, and this regulation depends on the Nod factor. Expression of individual FLOT genes was measured by quantitative RT-PCR. Each FLOT expression level was normalised to an internal actin control. Study was done in wild-type S. meliloti Rm1021.Reproduced from Haney and Long, 2010 with permission.
FLOT4, are strongly up-regulated during early symbiotic events (Fig. 1). The rate of up-regulation depends on bacterial Nod factor and the plant’s ability to perceive the Nod factor. Data from microscopy suggest that M. truncatula FLOT2 and FLOT4 localise to membrane microdomains. Upon rhizobial inoculation, FLOT4 uniquely becomes localised to the tips of elongating root hairs. Silencing FLOT2 and FLOT4 gene expression reveals a non-redundant requirement for both genes in IT initiation and nodule formation. FLOT4 is uniquely required for IT elongation, and FLOT4 localises to IT membranes. Thus, the work of Haney and Long (2010) reveals a critical role of plant flotillins in symbiotic bacterial infection. A complex signal exchange between macrosymbiont and microsymbiont initiates the nodulation process (Den Herder et al., 2007; Jones et al., 2007): upon perception of flavonoids exuded by host roots, rhizobia switch on their nodulation genes (Cooper, 2007), thus forming lipochitooligosaccharide molecules, designated as nodulation factors (NFs; Deakin and Broughton, 2009; D’Haeze and Holesters, 2002). NFs are essential for bacterial invasion and induction of cortical cell division to form nodule organs (Geurts and Bisseling, 2002). In fact, root infection by rhizobia is a multi-step process. It is initiated by certain pre-infection events occurring in the rhizosphere and progresses further under control of several factors and genes (Fig. 2). Plant root secretes exudates to which rhizobia respond by positive chemotaxis and move towards localised sites on the legume roots (Barbour et al., 1991;
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Flotillin genes/nodule growth genes
HO
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O HO
Nod genes Transporter proteins
O
OH
Flavonoids Nod biosynthesis
Nod factors Nod receptors
Rhizobium
Legume root hair
FLOT4, FLOT4?..nodulation? Physical structure to bacteroid?
Fig. 2. Schematic representation of the interaction between Rhizobium species and legume roots. Plant secretes flavonoids which induces nod genes in Rhizobium. Nod factors induce root-hair activation, cortical cell division, facilitation of infection process, increased flavonoid production and flotillins.
Caetano-Annole´s and Gresshoff, 1991). Both Bradyrhizobium and Sinorhizobium spp. are attracted by amino acids, dicarboxylic acids and very low concentrations of excreted components such as flavonoids present in the exudates (Peters and Verma, 1990). Physiological conditions have been found to influence the attachment capacity of R. leguminosarum bv. viciae to pea root hairs (Smit et al., 1989). However, lectins are also involved in the rhizobial attachment (Kijne et al., 1988; Kijne, 1992). For R. leguminosarum bv. viciae, a Ca2þ-dependent adhesin, called rhicadhesin, mediates the initial direct attachment to pea root-hair surfaces (Vesper et al., 1987). For cap
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formation, the firm attachment step, fibrillous appendages of (brady)rhizobia appear to be involved. These appendages can be cellulose fibrils (R. leguminosarum) or proteinous fimbriae (Bradyrhizobium japonicum) (Ho et al., 1990). Other non-protein bacterial macromolecules might also be involved. In all Rhizobium–plant interactions studied so far, the active substances have been identified as lipooligosaccharides, also called Nod factors. These Nod factors are synthesised by some of the nodulation genes (Spaink et al., 1991; Truchet et al., 1991). It has been shown that Medicago GRAStype protein-nodulation signalling pathway 1 (NSP1; Smit et al., 2005) and 2 (NSP2; Kalo et al., 2005), which are essential for all known Nod factorinduced changes in gene expression, are involved. NSP1 is constitutively expressed, and so it acts as a primary transcriptional regulator mediating all known Nod factor-induced transcriptional responses; it is therefore named as Nod factor response (Smit et al., 2005). NSP2 encodes a GRAS protein essential for Nod factor signalling. NSP2 functions downstream of Nod factor-induced calcium spiking and a calcium/calmodulin-dependent protein kinase. The host plant reacts by depositing new cell wall material around the lesion made by Rhizobium infection in the form of an inwardly growing tube. The tube is filled with proliferating bacteria surrounded by a matrix and becomes an IT. The IT grows towards the inner tangential wall of the root-hair cell tip by a process of tip growth. Concomitant with formation of the IT, particular cortical cells divide to form a nodule primordium and the IT grows towards these primordia (Wood and Newcomb, 1989). While the meristem is active, rhizobia are released from the ITs into the plant-cell cytoplasm (Brewin, 1991; Hirsch, 1992); in tropical legumes (e.g. soybean), a nodule meristem is induced in the root outer cortex, and the bacteria are released into actively dividing meristematic cells, with each daughter cell receiving rhizobia (Newcomb, 1981). Den Herder et al. (2007) have reviewed other mechanisms of infection. A protein, remorin, has been shown to interact with symbiotic receptors and regulate bacterial infections (Lefebvre et al., 2010). Intercellular bacterial microcolonies or infection pockets (IPs) are created in the outer cortex, from where ITs guide the bacteria towards the nodule primordium (Den Herder et al., 2006). Oxidative burst-like phenomena have been observed as a primary response in the interaction of S. meliloti with alfalfa (M. sativa) where superoxide and H2O2 are produced (Santos et al., 2001). In alfalfa roots, recognition of compatible NFs rapidly stimulates localised production of superoxide. This response is absent in the non-nodulating plant mutant and does not make infections1-1 (dmi1-1), which is impaired in the NF signal-transduction pathway (Ramu et al., 2002). Symbiotic bacteria overcome the plant’s defence by activating antioxidant enzymes (Jamet et al., 2003; Santos et al.,
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1999, 2000). Also, several plant genes related to protection against oxidative stress are differentially expressed during nodulation. After successful establishment of bacteroids in the nodules, symbiotic nitrogen fixation (SNF) takes place in specialised bacterial cells with the help of bacterial enzyme nitrogenase which catalyses the following reaction: N2 þ 8Hþ þ 8e þ 16Mg ATP ¼ 2NH3 þ H2 þ 16Mg ADP þ 16Pi Nitrogenase consists of two components, the homodimeric Fe protein, encoded by nifH, and the tetrameric molybdenum–iron (Mo–Fe) protein, encoded by nifD and nifK, which contains the Mo–Fe cofactor. In symbiosis, ammonium is exported to and assimilated in the plant, which in turn supplies the bacteria with carbon sources to provide energy for the nitrogenase reaction. The structure of a mature nodule develops to meet the requirements set by this nutrient exchange between both the symbiotic partners. B. PERIBACTEROID MEMBRANE
Plant-derived PBM serves as a interface for signal and metabolite exchange between host plant cell and intercellular bacteria (see Mylona et al., 1995). It also prevents a defence response by the plant against the ‘‘intracellular’’ bacteria (Nap and Bisseling, 1990; Verma, 1992). The PBM contains several nodulins and may also have rhizobial proteins (Fortin et al., 1985; Miao et al., 1992). Within the peribacteroid space between the bacteroids and the PBM, several proteins are present that are also found in vacuoles including proteases (Sarma et al., 2007) and thus, the PBM may have adopted some properties of the tonoplast membrane, forming a lytic compartment continuously being neutralised by ammonia exported by the bacteroids (Kannenberg and Brewin, 1989). By using an antisense strategy in combination with nodule-specific promoters, it has been shown that homologues of the Yptl protein (Schmitt et al., 1986), which controls membrane biosynthesis in yeast, are involved in PBM biosynthesis in soybean nodules (Cheon et al., 1993). In nodules expressing antisense RNA of such a homolog, the number of bacteroids per cell was reduced and the infected cells did not expand. Bacteroids express a dicarboxylic acid uptake system, isolated bacteroids take up dicarboxylic acids and mutants in this uptake are symbiotically ineffective (Werner, 1992); all of which indicate that dicarboxylic acids are likely to be the carbon source supplied by the plant to the intracellular bacteria. It has been suggested that nodulin-26 transports the dicarboxylic acids to the bacteroids (Ouyang et al., 1991). However, its low substrate specificity in vitro indicates that it is more likely to form a pore responsible for the uptake of ions or small metabolites in general (Weaver et al., 1994).
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For elucidation of function, it has been reported that PBM in the nitrogenfixing cells of yellow lupine (Lupinus luteus L.) and broad bean (Vicia faba L.) is endowed with a calcium-translocating ATPase that pumps Ca2þ into the symbiosome. This pumping ensures, on the one hand, calcium homeostasis in the cytosol of infected plant cells and, on the other hand, it optimises Ca2þ level in symbiosomes, first of all in the bacteroids, because Ca2þ is one of the main factors controlling their nitrogenase activity. The balance between the symbiotic partners and the maintenance of optimal Ca2þ level in the bacteroids also depends on passive Ca2þ efflux from symbiosomes to the plant-cell cytosol via calcium channels (Izmailov, 2003). C. GENE REGULATION IN NODULES
Signalling between legume and its bacterial symbiont is essential for the coordinate expression of both plant and bacterial genes. The bacterial nodulation genes (nod, nol, noe) encode a key set of proteins involved in the establishment of this symbiotic relationship. The nod genes are expressed specifically in response to plant-produced flavonoid compounds. Central to the regulation of the nod genes is NodD, a LysR-type regulator, which activates nod gene expression only in the presence of the flavonoid inducer (Loh and Stacey, 2003). Furthermore, in the process of maturation, triggering and maintenance of functionality of nitrogen-fixing root nodules, several genes of both symbionts are specifically induced and/or up- and downregulated (Mylona et al., 1995). The use of reporter genes as well as in situ hybridisation studies has provided detailed insights into the spatial and temporal regulation of such genes in indeterminate nodules. In such nodules, major, sudden developmental changes occur at the transition of the prefixation zone to the interzone: starch is deposited in the plastids of the infected cells, and the bacteroid morphology alters (Vasse et al., 1990). These events are accompanied by changes in bacterial gene expression: transcription of bacterial nif genes, which encode enzymes involved in the nitrogen-fixation process, is induced, whereas expression of the bacterial outer-membraneprotein gene ropA is dramatically reduced (De Maagd et al., 1994; Yang et al., 1991). All these events, together with sudden changes in plant gene expression, take place within a single cell layer. To investigate plant factors causing this rapid change in bacterial differentiation, rhizobial nif gene regulation has been studied extensively and found to be induced generally by microaerobic conditions (see Fischer, 1994; Merrick, 1992). Transcription of S. meliloti nitrogen-fixation (nif/fix) genes is controlled either by the transcriptional activator NifA together with the sigma factor RpoN (Gusslin et al., 1986; Morett and Buck, 1989) or, for some genes, by the
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transcriptional activator FixK. NifA activity is under oxygen control at two levels: the NifA protein itself is oxygen sensitive (Krey et al., 1992), and its transcription, together with that of fixK, is induced under microaerobic conditions by the transcriptional activator FixJ (David et al., 1988). FixJ is part of a two-component system that includes the oxygen-sensing haemoprotein FixL. FixJ is activated by FixL by phosphorylation upon microaerobiosis (Da Re et al., 1994; David et al., 1988; Gilles-Gonzalez et al., 1991). It is the activated FixJ protein that in turn induces the transcription of nifA and fixK (Batut et al., 1989). Although microaerobic conditions are essential for rhizobial nif gene transcription in symbiosis, it has long been debated whether the reduction of oxygen concentration is the sole regulatory factor for the induction of nif gene expression in the interzone. Some results (Soupe´ne et al., 1995) have shown that S. meliloti nif gene expression in plants can be modified by changing the external oxygen concentration: in nodules immersed in agar, nif gene expression is extended to a younger part of the nodule and now also occurs in the prefixation zone. This effect is controlled by the FixLJ system, because the same result is obtained by nodulation with a strain carrying a constitutively active mutant form of FixJ (FixJ*). Thus, oxygen concentration seems to be a major factor in controlling symbiotic nif gene transcription during symbiosis. In contrast, ropA expression is not under oxygen control in free-living bacteria, and ropA repression can even be uncoupled from nif gene induction in the same cell layer. In mutant nodules induced by a Rhizobium strain whose host range had been manipulated, rop4 mRNA distribution was equal to that in wildtype nodules, whereas bacteroid differentiation and nif gene induction did not take place (De Maagd et al., 1994). Therefore, further analyses are required to determine the other regulatory factors responsible for changes in bacterial gene expression in the first cell layer of the interzone. The expression of several plant genes is also controlled at the transition of the prefixation zone to the interzone as well as in other zones of the central tissue (Kardailsky et al., 1993; Matvlienko et al., 1994; Scheres et al., 1990a,b; Yang et al., 1991). However, the expression of these genes seems not to be controlled by the oxygen tension (Govers et al., 1986) but rather to be under developmental control. To analyse the regulators of plant nodulin gene expression, the expression of nodulin promoter--glucuronidase fusions has been studied in heterologous legumes (Brears et al., 1991; Forde et al., 1990; Szabados et al., 1990). The most extensive studies have been performed on the leghaemoglobin genes. So far, promoter analysis of these genes has led to the identification of a so-called organ-specific cis-acting element (OSE; Ramlov et al., 1993), also called the nodule-infecting cell-specific element (NICE; Szczyglowski et al., 1994), which has also been found in the promoter
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of the nodule-specific haemoglobin gene of the actinorhizal plant Casuarina glauca (Jacobsen-Lyon et al., 1995). A C. glauca haemoglobin promoter-glucuronidase fusion is expressed in the infected cells of Rhizobium-induced nodules from Lotus cornicularus (Jacobsen-Lyon et al., 1995), which implies that similar regulatory factors are involved in both the legume and actinorhizal systems. However, the corresponding transcription factors that bind to these promoter elements have yet to be identified. Although genetic analyses of plant symbiotic mutants have led to the identification of key genes involved in Rhizobium–legume communication as well as in the development and function of nitrogen-fixing root nodules, the impact of these genes in coordinating the transcriptional programmes of nodule development has been evaluated only in limited and isolated studies. A recent review by Loh and Stacey (2003) describes the events of gene regulation in the nodule of B. japonicum. According to them, multiple mechanisms regulate and fine-tune B. japonicum nod gene expression. This regulation involves members of three global regulatory families (i.e. MerR, two-component and LysR). In a study, null mutations in S. meliloti exoS and chvI demonstrate the importance of this two-component regulatory system for symbiosis (Belanger et al., 2009).
IV. NODULE PROTEOMICS: WET LABORATORY AND BIOINFORMATICS PROCEDURES Two-dimensional gel electrophoresis (2DE) with immobilised pH gradients (IPGs) combined for protein identification with MS is currently the workhorse for proteomics (Go¨rg et al., 2004). A number of promising alternatives or complementary technologies, such as multidimensional protein identification technology, stable isotope labelling, protein or antibody arrays are available but 2DE has emerged as the only technique that is being routinely applied for parallel quantitative expression profiling of large sets of complex protein mixtures such as the whole-cell lysates. It is also an ideal tool for analysing proteins localised to bacteroid or PBM or cell organelles. 2DE, besides resolving complex mixtures of proteins on the basis of isoelectric point (pI), molecular mass (Mr), solubility and relative abundance, enables to obtain proteome maps of intact proteins up to detectable limit. In addition to identification of proteins, a comparative study reflects changes in proteinexpression level, isoforms or post-translational modifications. Advanced 2DE technology with IPGs (Go¨rg et al., 2000, 2004) is more efficient with respect to reproducibility, handling, resolution and separation of very acidic and/or basic proteins. In extension to 2D, principally similar 3DE has further helped in resolution of highly hydrophobic proteins (D’Amici et al., 2008;
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Qureshi et al., 2010) of thylakoid complexes; however, nodule studies have yet to be done using this approach. The range of IPG strips (wide scale, pH 2.5–12) and narrow scale has enabled the separation of very alkaline proteins with increased resolution (delta pI ¼ 0.001). Gel images obtained from SDSPAGE of the corresponding IPG strips resulted in the development of huge databases of 2D gels. Depending on the size and pH gradient of IPG strip and corresponding SDS-PAGE gel, 2DE can resolve more than 5000 proteins simultaneously ( 2000 proteins routinely), and detect and quantify < 1 ng of protein per spot (Go¨rg et al., 2004). Furthermore, genetic and physiochemical studies could not give a clear picture of plant nodules such as of symbiotic association, regulation of growth of all partners and their interaction, PBM-dependent signal transduction and profile of proteins expressed at any specific growth stage or in response to any physiological conditions, including abiotic stresses. Even the huge data obtained by DNA sequencing could not provide any important information related to the regulatory, structural and functional aspects of nodules and symbiosome. However, with the recent developments in proteomics, MS and bioinformatics, very important facts have been discovered or are being investigated. Since proteomics provides a global picture of the types of proteins resolved using isoelectric focusing (IEF) and denatured SDSPAGE, the huge data obtained (Table II) help in understanding the overall scenario in the nodule or symbiosome. The available gene databanks are of great help in the identification of encoding genes. At certain stages during the proteomic procedure, bioinformatics softwares not only serve to calculate the level of significance (biostatistics-based analysis) but also it is important as an interface between 2D gel images to protein spot identification (image analysis software), role in recognition of signals to identify peptides during peptide-mass fingerprinting (PMF) and in a match of obtained PMF data with protein databank to identify homology with already existing or identified protein. Furthermore, protein–nucleic acid match software helps in identification of genes that encode the individual proteins. Image analysis software helps in estimating the change in expression level of a number of proteins in a single operation that also includes proteins that are newly induced, overexpressed and those or put at silence. This part would highlight details of how nodules are grown under experimental conditions, harvested and used to extract proteins. Protein sample preparation for 2DE; IEF and denaturing SDS-PAGE will be discussed thoroughly followed by image analysis, identification of protein spots of interest and tryptic digestion of excised protein spots. The last part of proteomic methodology will deal with the techniques of PMF and identification of proteins by a match with public protein database/databank.
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TABLE II Plant Protein Identification in Medicago truncatula Root Nodules S. no. 1.
2.
3.
Metabolic category and name of identified proteins Amino acid metabolism ARD-like protein, 2-oxoglutarate dehydrogenase E2 subunit, 3-isopropylmalate dehydrogenase, 3-ketoacyl-CoA thiolase, adenosylhomocysteinase, adenosylhomocysteinase, argininosuccinate synthase, chloroplast precursor, asparagine synthase, aspartate aminotransferase, ATP sulfurylase, putative aspartate aminotransferase, -cyanoalanine synthase, cytosolic acetoacetyl-coenzyme A, thiolase, orotein identification, cysteine desulfurase, F22O13.11 similar to L-allothreonine aldolase, -aminobutyrate transaminase subunit isozyme 1, glutamate dehydrogenase 1, glutamine synthetase, glutathione S-transferase GST 15, glutathione S-transferase GST 22, glycine dehydrogenase (decarboxylating), mitochondrial precursor, glyoxalase I, histidinol-phosphate aminotransferase, hydroxyacylglutathione hydrolase cytoplasmic (Glyoxalase II) (Glx II), ketol-acid reductoisomerase, lactoylglutathione lyase (methylglyoxalase) (aldoketomutase), (Glyoxalase I), methionine synthase, NADH-dependent glutamate synthase, ornithine carbamoyltransferase, phosphoserine aminotransferase, plastidic cysteine synthase 1, S-adenosyl-L-methionine synthetase, S-adenosylmethionine synthetase, S-adenosylmethionine synthetase 3, similar to AT4g32520/F8B4_220, similar to urease accessory protein UREG, similar to histidinol dehydrogenase, similar to cysteine synthase, thiosulphate sulphurtransferase Protein degradation 26S protease regulatory subunit 6B homologue, 26S proteasome regulatory subunit S2, arginyl-tRNA synthetase, aspartyl aminopeptidase, glutaminyl-tRNA synthetase, guanine nucleotide-binding protein -subunit-like protein, Kunitz proteinase inhibitor-1, Lysyl-tRNA synthetase, mitochondrial processing peptidase -subunit, multifunctional aminoacyl-tRNA ligase-like protein, neutral leucine aminopeptidase preprotein, non-cell-autonomous heat shock cognate protein 70, oligopeptidase A, protein identification, serine/threonine protein phosphatase PP2A catalytic subunit, similar to cell death-related protein SPL11, similar to CDC48-interacting UBX-domain protein, thiolprotease, ubiquitin-conjugating enzyme E2 variant 1, Xaa-Pro aminopeptidase 2 Protein synthesis 23S ribosomal RNA, 30S ribosomal protein S18, 40S ribosomal protein S2, S3, S5, S8, S9, S19, SA, DEAD box RNA helicase, eukaryotic initiation factor 4, eukaryotic initiation factor 4A-11, protein identification, eukaryotic initiation factor 4B, eukaryotic translation initiation factor 5A-2, ribosomal protein L2, signal recognition particle 19 kDa protein, similar to seryl-tRNA synthetase, translational elongation factor 1B -subunit, translational elongation factor 1B -subunit, translational elongation factor Tu, ubiquitin/ribosomal protein S27A fusion protein (continues)
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Table II S. no. 4.
5.
6.
7.
8.
17
(continued )
Metabolic category and name of identified proteins Major carbohydrate metabolism Alpha-glucan phosphorylase, H isozyme, fructokinase, hexokinase-related protein 1, putative -fructofuranosidase/alkaline invertase, sucrose synthase, chalcone reductase, similar to NAD(P)H dependent 60 -deoxychalcone synthase, 2,3-bisphosphoglycerate-independent phosphoglycerate mutase, cytosolic phosphoglycerate kinase, enolase, fructosebisphosphate aldolase, fructose-bisphosphate aldolase-like protein, glucose-6-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, phosphoenolpyruvate carboxylase, phosphoglucomutase, phosphoglucomutase, chloroplast precursor, phosphoglycerate kinase, pyrophosphatedependent phosphofructokinase -subunit, pyrophosphatefructose 6-phosphate 1-phosphotransferase -subunit, pyruvate kinase-like protein, triosephosphate isomerase, UDP-glucose pyrophosphorylase TCA Aconitate hydratase, aconitate hydratase, carbonic anhydrase, citrate synthase, cytosolic malate dehydrogenase, dihydrolipoyl dehydrogenase, fumarate hydratase 1, malate dehydrogenase, pyruvate dehydrogenase E1 component -subunit, pyruvate dehydrogenase E1 component -subunit, similar to Isocitrate dehydrogenase (NADþ) precursor, similar to NAD-dependent isocitrate dehydrogenase, similar to NADP-dependent malic enzyme, succinate dehydrogenase subunit 3, succinate dehydrogenase (ubiquinone) flavoprotein subunit, succinyl-CoA ligase (GDP-forming) -chain, succinyl-CoA ligase -subunit Redox Heme oxygenase 1, catalase, dehydroascorbate reductase, glutamate-cysteine ligase, glutaredoxin, glutathione reductase, L-ascorbate peroxidase, leghaemoglobin (types 1, 2, 29), mitochondrial peroxiredoxin, 2-on-2 haemoglobin, monodehydroascorbate reductase, peroxiredoxin-like protein, probable protein disulphide-isomerase A6, protein disulphideisomerase, thioredoxin h, superoxide dismutase (Mn) precursor, thioredoxin reductase 2, thioredoxin H, thioredoxin-dependent peroxidase Stress NBS-LRR resistance protein RGH1, late embryogenesis-like protein, Bax inhibitor, chaperone HSP90-2, chitinase, class 10 PR protein, DNAK-type molecular chaperone, fibre protein Fb19, heat shock 70 kDa protein, heat shock protein 70-3, Pathogenesisrelated protein-like protein, PPRG2 pathogen-related protein (PR-10 family), peroxidase (type 2, 1B), similar to trypsin protein inhibitor 3, glycine-rich protein 2 (partial 45% similarity), stressinduced protein sti1-like protein Oxidative pentose pathway 6-Phosphogluconate dehydrogenase, ferredoxin-NADP reductase, -hydroxybutyrate dehydrogenaselike protein, ribose-5-phosphate isomerase, Si6phosphogluconolactonase-like protein, transaldolase ToTAL, transaldolase, transketolase-like protein (continues)
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Table II S. no. 9.
10.
11. 12.
13.
14.
15. 16.
17.
(continued )
Metabolic category and name of identified proteins Secondary metabolism Betaine-aldehyde dehydrogenase, caffeic acid 3-O-methyltransferase, caffeoyl-coa O-methyltransferase, chalcone–flavonone isomerase 1, cinnamoyl-CoA reductase-like protein, cinnamyl alcohol dehydrogenase, flavanone 3 -hydroxylase, isoflavone reductase homologue 1, isopentenyl pyrophosphate isomerase, O-diphenol-O-methyl transferase, phenylalanine ammonia-lyase, weakly similar to orcinol O-methyltransferase Signalling Calmodulin-like protein 2, calmodulin-like protein 6b, calreticulin, GDP dissociation inhibitor, GTP-binding protein, lectin, mitochondrial srRNA, weakly similar to inositol 1,3,4-trisphosphate 5/6-kinase Hormone metabolism Carboxymethylenebutenolidase I, ENOD18 protein, lipoxygenase, lipoxygenase Loxn3, methylesterase Transport ATP synthase- chain, electron transfer flavoprotein -subunit-like, F1 ATPase, porin por1, probable Hþ-transporting ATPase, similar to potential copper-transporting ATPase 3, vacuolar ATP synthase subunit C Nucleotide metabolism Adenylate kinase B, Bac19.7, bifunctional UMP synthase, cytidine deaminase 4, inorganic pyrophosph9ataselike protein, kinase 2 (AK 2) (adenosine 50 -phosphotransferase 2), nucleoside diphosphate kinase II, Pndkn1, ribonucleotide reductase large subunit A, uricase (nod-35) RNA regulation CCCH-type zinc finger protein, glycine-rich RNA binding protein (type 7, GRP2A, PSGRBP), nucleoid DNAbinding-like protein, poly(A)-binding protein, single-stranded nucleic acid binding protein, transcription factor EREBP-like protein Metal handling Arg10, basic blue protein, copper chaperone, ferritin, ferritin 2, selenium binding protein, similar to ATFP3 Cell wall/cell organisation Actin, actin 11, -tubulin, -tubulin R2242, cell division cycle protein 48 homologue, cyclophilin, Cyp1, DTDPglucose 4-6-dehydratase homologue D18, DTDP-glucose 4-6dehydratase, endosperm-specific protein-like protein, fasciclin-like arabinogalactan protein 1, pectinesterase, protein identification, plastid-lipid-associated protein, reversibly glycosylated protein, tubulin -chain, tubulin -3/-5 chain, tubulin beta chain, tubulin -2 chain, tubulin -8 chain Miscellaneous 1,4-Benzoquinone reductase-like, 5,10-methylenetetrahydrofolate dehydrogenase, 5-formyltetrahydrofolate cycloligase, acid phosphatase, acyl-peptide hydrolase-like, alcohol dehydrogenase 1, alcohol dehydrogenase class III, aldehyde dehydrogenase, aldehyde dehydrogenase (NADþ), allyl alcohol dehydrogenase, -L-arabinofuranosidase, -glucosidase-like protein, CBS domaincontaining protein-like, coproporphyrinogen oxidase, dolichylphosphate -glucosyltransferase homologue, early nodule-specific protein, protein identification, early nodulin-like protein 2 precursor, early tobacco anther 1, enoyl-ACP reductase, epoxide hydrolase, (continues)
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Table II S. no.
19
(continued )
Metabolic category and name of identified proteins epoxide hydrolase, globulin-like protein, glycogenin-like starch initiation protein, putative nodule membrane protein, 1,4benzoquinone reductase-like, lectin-related polypeptide, luminal binding protein 4, lysophospholipase homologue, methylenetetrahydrofolate reductase, methylthioadenosine/Sadenosyl homocysteine nucleosidase, Mtn13 protein, O-linked Nacetyl glucosamine transferase, protein identification, phosphoglucomutase, ribonucleoprotein-like, SGRP-1 protein, similar to late embryogenesis abundant proteins, sure stationaryphase survival protein, partially similar to cytochrome P450, partial (21% similarity)
List of identified plant nodule proteins using two-dimensional liquid chromatography coupled to mass spectrometry (2D-LC/MS/MS). Tentative consensus sequences were retrieved from the Medicago Gene Index from The Institute for Genomic Research Release 8.0 (January 19, 2005) (now located at http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb¼medicago). Proteins are sorted based on their functional classification as given by the Mapman program, based on Gene Ontology Consortium (GOC) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) databases (adopted and modified from Larrainzar et al., 2007 with permission).
A. NODULE CULTIVATION AND HARVESTING
A primary need for starting a N2-fixing organ proteomics is the availability of the nodule sample, the starting material, in sufficient amounts. Methodologies adopted may differ depending on the type of legume and experimentation. Sometimes, legumes are grown in the soil (field plots or pots) where nodulation starts due to the bacteria present in the soil. Pre-inoculation of seeds that help in immediate infection of roots as they emerge is also practised. The species of symbiotic N2-fixing bacteria is isolated from nodule bacteroids and cultured in vitro or in fermenter. A variety of nutrient culture media such as diluted sugarcane molasses and modified Hoagland nutrient solution are used. Growth of bacteria is monitored spectrophotometrically. The cultured media serve as ‘‘master culture’’ which is used to inoculate for nodule induction in the root. These days, legumes are very often grown in hydroponics and a part of master bacterial culture is added to the hydroponic culture. These bacteria are thus available in hydroponic culture (D’Haeze et al. 2000) or in vitro (Innes, 1998) to infect the roots of legumes. Once nodules are borne on the roots of legume plants or attain the desired level of growth, harvesting of nodules is carried. Roots bearing nodules are washed and blot-dried, followed by the weighing measurements. The weighed and estimated amount of nodules is frozen immediately in liquid N2 and immediately used for sample preparation or stored at 80 8C until further use.
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M. I. QURESHI ET AL. B. 2DE: IEF AND SDS-PAGE
For 2D separation of nodule proteomics, good quality protein sample is a primary requisite. Depending upon the type of tissue, location and experimental set-up, protein extraction protocols may differ considerably. For extraction of proteins from nodules, various combinations are tried; different protocols have been used for nodule phosphoproteome (Grimsrud et al., 2010) and whole nodule proteome (Larrainzar et al., 2007). Using the latter approach, Larrainzar et al. (2007) identified more than 300 proteins in the M. trancatula nodule proteome (Table II) which were further functionally classified into different metabolic groups (Fig. 3). 1. Protein extraction and sample preparation There are certain methods for extraction of proteins from any part of the plant. In order to study the interactive changes in proteomes after infections of root hairs by B. japonicum, Wan et al. (2005) conducted a large-scale
Signalling and hormone metabolism 7% Secondary metabolism 3%
Transport 2%
Amino acid metabolism 12% Cell wall and organisation 5%
RNA regulation 2%
CHO metabolism 3%
Redox and stress 12%
Glycolysis/TCA 12% Protein synthesis and degradation 13%
Metal handling 2% OPP 2% Nucleotide metabolism 3%
Miscellaneous 22%
Fig. 3. Functional classification of the identified proteins in the 2D-LC/MS/MS analysis of M. truncatula nodule plant fraction. Reproduced from Larrainzar et al., 2007 with permission.
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proteomics and identified several proteins. For protein extraction and 2D analysis, they developed good 2D gels which assisted well in tandem MS/ MALDI; similar protocols have been applied to nodules by other authors. In general, two methods, (i) phenol extraction method (Dumas-Gaudot et al., 2004) and (ii) trichloroacetic acid (TCA)–acetone precipitation method (Chen et al., 2009), are used for protein extraction on a routine basis. Frozen nodules are ground in chilled pestle and mortar to a fine powder, making a homogenate with appropriate concentrations/values of homogenisation buffer such as 40 mM Tris–HCl, pH 7.5, 2 mM EDTA, 0.07% -mercaptoethanol, 2% PVP, 1% Triton X-100, 6 M urea, 2 M thiourea and 4% CHAPS; some partial modifications are usually done for protein extraction (Komatsu and Ahsan, 2009) as per requirements. However, there are also reports of protein extraction by direct addition of chilled 10% TCA prepared in acetone (w/v). When extraction is done in extraction buffer, the homogenate is centrifuged at approximately 30,000 rpm for 60 min at 4 8C. The supernatant is separated and incubated with chilled 10% TCA (w/v) þ 0.07% -mercaptoethanol (v/v) prepared in acetone and left overnight at 20 8C. In the latter method of protein extraction, as discussed above, nodule powder þ acetone (10% TCA) is left overnight and centrifuged at approximately 8000 rpm. The supernatant is discarded and the pellet, which contained cellular debris and proteins, is collected. Thus, the pellet, obtained at this stage or by the former method using the TCA–acetone precipitation method, is dried by vacuum infiltration at low temperature and stored below freezing point. For preparation of the sample, the pellet is solubilised in a solubilisation-cocktail buffer containing 6–9 M urea (w/v), 2 M thiourea (w/ v), 30 mM Tris–HCl (w/v), 1–2% Triton X-100 (v/v), 2–6% CHAPS (w/v), 0.2% ampholytes (v/v) and 50-mM dithiothreitol (DTT) (w/v). TBP has also been used in modified methods (Herbert et al., 2005). A vigorous mixing is followed by centrifugation at approximately 12,000 rpm for approximately 15 min. The supernatant collected which contains proteins is retained and any pellet that might contain unsolubilised proteins is discarded. The concentration of protein is estimated at this stage against the standard curve of bovine serum albumin for which different methods are used. Bradford reagent or Lowry method and the biuret method are quite common. The desired concentration of protein per microlitre is 5–10 g or up to the level of saturation in solubilisation-cocktail. Protein concentration can then be diluted as per the requirement. Sometimes, this sample is used for SDS-PAGE to see the quality of proteins prior to 2D analysis. Experience, precautionary measures [good laboratory practices (GLP)] and development of confidence lead to good quality 2D analysis with better reproducibility.
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2. Protein focusing (first-dimensional run) Once the sample is ready with proteins, separation can be done by IEF on the basis of their pI. IEF, also known as electrofocusing, is a technique for separating different molecules, here protein, on the basis of their electric charge differences. It is a type of protein electrophoresis usually performed in a gel with linear gradient of pH dispersed through its length. Commercial competition among companies in the field of life sciences/biochemistry has resulted in development and further refinement of products used in proteomics including gel strips with pH gradient, IPG. Now, commercially available IPG strips from leading companies are preferred over the laboratory-made pH gradient gels and capillary gels. These IPG strips are available in a variety of sizes, pH ranges and patterns of pH distribution such as in linear (LN) or non-linear (NL) fashion. The size of IPG strip may start with few centimetre (7 cm very common) to tens of centimetre; the range of pH may be 3–10, 4–7, 5–8 and many more combinations. In LN IPG strip’s pH on gel length is distributed with a uniform gradient, whereas in NL IPG strip’s pH, the distribution is narrow or compressed at the ends and expanded in the centre. Thus, a scientist has great liberty to choose IPG strips as per the experimental design. The known and desired amount of proteins present in pre-estimated (depending on the size of IPG strip) quantity of solubilisation cocktail (rehydration buffer) and IPG strip is rehydrated either actively (under the influence of electric current) or passively. According to another method, IPG strips are rehydrated with rehydration buffer followed by protein focusing. In this method, protein is loaded onto the IPG strip using a loading cup (Bodzon-Kulakowska et al., 2007). Loaded with sample buffer and proteins, IPG strips are subjected to IEF as a first-dimensional run. The duration and the amount of electric current is estimated in terms of volts hours (V h) which varies with the type of protein nature, degree of resolution and the size of the IPG strip. For example, the value of V h for IEF of proteins may start from few thousands (8000 V h, 7 cm IPG strip) to several thousands of V h (75,000 V h, 17 cm IPG strip). Furthermore, the pattern of passing the electric current to the equipment used for protein focusing (IEF cell) can vary. The passage of current might be provided with different ramping modes (slow, linear or rapid ramping). In general, the current limit is set between 50 and 90 A per strip. The factor that determines the time to reach the maximum voltage set by the user is the composition of the sample solution. A sample with high salt concentration including ampholytes and high sample loads requires a long time to attain the steady state. After completion of the protein-focusing run, the IPG strip may be stored at 20 8C for a long time.
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3. IPG strip equilibration The focused IPG strip has proteins in native form and need to get reduced and alkylate so as to get charged with SDS for proper running in the second dimension. It is necessary to equilibrate focused strips in SDS-containing buffers. Equilibration of proteins in IPG strips can be done in two steps: (i) reduction of sulfhydryl groups using 2% (w/v) DTT and (ii) alkylation of sulphohydryl groups using 2.5% (w/v) iodoacetamide (IAA). Both DTT and IAA may be prepared separately in a buffer of similar chemical composition [6 M urea, 2% SDS, 0.05 M Tris–HCl, pH 8.8, 20% glycerol and rest ultra-pure (milliQ) water in respect to final volume]. 4. SDS-PAGE (second-dimensional run) Equilibrated strips are loaded onto the gels containing SDS. The size of the second-dimensional gel is set in accordance with the size of the IPG strip, and the percent acrylamide concentration depends on the molecular weight of the protein. Sometimes, the gradient in the gel is also used. Likewise, in the traditional single-dimensional SDS gel in two divisions, stacking and resolving gels are also used; a protein standard/protein ladder with known molecular-weight proteins accompanies this run. These days, pre-cast gels are available commercially which save time and provide high quality and reproducibility. The second-dimensional run is initiated by passing the electric current (low e.g. 20 V during protein run through a stacking gel but higher, e.g. 100 V during protein run through a resolving gel) under cool conditions with a dual buffer system, namely the lower tank and upper tank buffers, with the major difference being that the upper tank buffer contains SDS to continuously provide a negative charge to proteins. The tracking dye indicates the progression and completion of the run. 5. Gel staining for protein visualisation At the completion of the SDS-gel (second-dimensional) run, the gel is stained using stains such as fluorescent (ruthenium stain; Rabilloud et al., 2001) and silver. Depending on the amount of proteins on the gel, MS-compatibility and ease of user, the stain is selected for visualisation of the proteins on the 2D gel. Traditionally, Coomassie Brilliant Blue R-250 stain was in common practice. Being highly sensitive (10–50-fold over CBBR), silver stain (Merril et al., 1981) with a detectable range of 0.1 ng protein/mm2 was a method of choice but facing a drawback, not MS friendly, some modifications were done later. Another dye, SYPRO Ruby, is also used to stain the proteins in the gel, but it has a demerit of becoming visible on UV or blue light box and can be scanned with specifically provided gel-documentation systems.
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Recently, a very sensitive (between CBBR-250 and silver stain) staining method was introduced (Candiano et al., 2004), which uses colloidal Coomassie Blue G-250 stain (modified from Neuhoff’s colloidal Coomassie Blue G-250 stain). Because of its high sensitivity, it is known as the blue silver stain, a complement from silver stain. The merit of this stain lies in that, besides being highly sensitive, it does not require organic solvents in large amounts. Spots start becoming visible within few minutes of exposure; destaining is done with water. 6. Gel imaging and image analysis After staining the gels of the second dimension, the image of the same is recorded in the form of electronic data, and therefore, images can be loaded easily on to image analysis software and sometimes to image editing software, for example, in case of a broken gel, for image editing. A number of excellent image analysis softwares are available from Bio-Rad, Non-linear Dynamics, and Delta-2D, among others. These bioinformatics softwares have revolutionised the field of proteomic research due to their high-quality image-analysis property, comparing thousands of protein spots simultaneously. By a comparative analysis of data obtained in terms of proteinspot intensities, it is possible to estimate the relative changes in the expression levels of proteins (whether suppressed, induced, over- or under-expressed) and also the phosphorylation in proteins simply by analysing the pI shift. Thus, at this step, proteins of interest may be selected and get excised (trapped in gel pieces) from the main gel for in-gel digestion followed by PMF. Furthermore, the bioinformatics software provides an opportunity to present data in a number of ways (Gehlenborg et al., 2010; Hoogland et al., 2008). 7. In-gel protease digestion of protein and PMF After identification of a set of differentially expressed spots and other proteins of interest from a series of 2D gels by any image-analysis software, the next step is typically to perform PMF (Larrainzar et al., 2007). In-gel protease (mostly trypsin) digestion, Coomassie Brilliant Blue- or silver stainvisualised protein spots are manually or with the help of an automated spot cutter excised as small (e.g. 1.5- or 3.0-mm diameter) plugs depending on the relative abundance of the spot. Gel plugs are transferred to either microtubes or polypropylene 96-well plates, sealed and stored at 80 8C until further processing. To each well of the latter, 25 l of a 1:1 (v/v) solution of 50-mM ammonium bicarbonate and acetonitrile (ACN) are added, and the mixtures are incubated at room temperature for 15 min. This process is repeated until all the gel spots are completely destained. The spots are then dehydrated with
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25 l of ACN for 15 min at room temperature. After ACN removal, the spots are dried under vacuum and rehydrated in 20 l of sequencing-grade modified bovine trypsin (10 ng/l in 25-mM ammonium bicarbonate). After rehydration for 20 min, excess trypsin solution is removed, and 15 l of 25 mM ammonium bicarbonate is added to each well to prevent dehydration during incubation. Proteolysis is allowed to continue overnight at 37 8C and stopped by adding 15 l of 10% formic acid. The supernatant is recovered, and the plug-proteins are extracted twice with 25 l of a 1:1 (v/v) solution of ACN and 25-mM ammonium bicarbonate and once more with 25 l of ACN. The extracts are then combined/pooled and concentrated under vacuum to a final volume of 25 l.
8. Liquid chromatography and mass spectrometric analyses In the recent past, there has been a rapid development in liquid chromatographic and mass spectrometric techniques. This combination of liquid chromatography and MS is a perfect match for conducting PMF (peptidemass-map analysis using MS), peptide-fragment fingerprinting (MS/MS ion search analysis) using tandem MS or intact molecular mass determination by electrospray ionisation mass spectrometry (ESI-MS) or matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS). Among the various MS-based techniques, LC/MS/MS-separations of protein digests may be achieved using a nanoscale high performance liquid chromatography (HPLC) system consisting of an autosampler, a precolumn switching device and an HPLC-pump system. In general, samples (5 l) are ˚, loaded onto a C18 precolumn (0.3-mm inner diameter 1.0 mm, 100 A PepMap C18, LC Packings) for desalting and concentrating at a flow rate of 50 l/min, using the mobile phase A (5% ACN and 95% water containing 0.1% formic acid). Peptides are then eluted from the precolumn and separated on a nanoanalytical C18 column (75-m inner diameter 15 cm, ˚ , PepMap C18, LC Packings) at a flow rate of 200 nl/min. Peptides 100 A are eluted with a linear gradient of 5–40% mobile phase B (95% ACN and 5% water containing 0.08% formic acid) over 40 min. The separated peptides are directly analysed with an ABI QSTAR Pulsar I hybrid Q-TOF mass spectrometer equipped with a nanoelectrospray ionisation source. The nanoelectrospray is generated using a PicoTip needle (10-m inner diameter) maintained at a voltage of 2400 V. TOF-MS and tandem mass spectral data are acquired using information-dependent acquisition (IDA), chargestate selection from 2 to 5, an intensity threshold of 10 counts/s and a collision energy setting automatically determined by the IDA based on the m/z values of each precursor ion. Following IDA data acquisition, precursor
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M. I. QURESHI ET AL.
ions were excluded for 90 s using a window of 6 amu to minimise the redundancy in tandem mass spectra. 9. Database queries and protein identification In very common, the acquired mass spectral data are queried against a custom legume protein database using the MASCOT (version 1.8.0, Matrix Science Ltd., London, UK) search engine (Creasy and Cottrell, 2002; Lei et al., 2005), with a mass tolerance of 150 ppm, and allowance for up to one trypsin miscleavage and variable amino acid modifications consisting of methionine oxidation and cysteine carbamidomethylation. The custom legume protein database has been generated from tentative consensus sequences compiled as gene indices by the Institute for Genomic Research (www.tigr.org/tdb/tgi.shtml). These sequences included thousands of records for M. truncatula, Glycine max and Lotus japonicus. The nucleotide sequences may then be translated into amino acid sequences and annotated using EST Analyzer (www.bioinfo.noble.org/). For a given sequence, EST Analyzer searches the National Center for Biotechnology non-redundant (NCBInr) protein dataset to identify a homologous protein (the best hit of BLASTX search), which is used to annotate the query sequence. Based on the alignment between the query sequence and template, frameshift errors are also detected and corrected, if possible. All possible protein sequences are annotated, given pseudo-GI numbers, formatted conforming to NCBInr to allow queries by MASCOT and compiled as a plant–protein database. Only protein identifications with a molecular-weight search (MOWSE) score greater than two times the generally accepted significant threshold (determined at 95% confidence level as calculated by MASCOT) and with at least more than two peptides matched are considered good. MASCOT is a software coupled to mass spectrometers, which facilitates protein identification and structural analysis and provides instant online bridge between mass spectra and public sequence databases (Aebersold and Mann, 2003; Ferguson and Smith, 2003; Lin et al., 2003). Each PMF is usually a viable means of assigning identity to a specific protein, as a result of variability in amino acid sequences and of the relative distribution of protease-cleavage sites between proteins (GodovacZimmermann et al., 2005); members of protein families with a high degree of sequence similarity can also result in effectively indistinguishable PMFs. This problem is exacerbated by the fact that it is unusual for the full complement of peptides for any given protein to be ionised and detected experimentally by MALDI-TOF. By using this approach, different proteins have been found to be up-regulated under the corresponding abiotic stresses, so as to give a comparative overview of the proteins. Proteins associated with nitrogen and
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sulphur metabolism, as detected by using proteomic tools, have also been mentioned. Figure 4 presents an overview of the proteomic analysis of nodules.
V. PROTEOMIC RESPONSE OF NODULE TO DIFFERENT STRESSES Differential expression of proteins takes place under a variety of stress. The degree of expression varies with the type of stress the legume is exposed to. Proteome of nodule can be displayed on 2D SDS-PAGE, which is digitally recorded in high resolution by using a scanner or a high-quality digital camera or gel-documentation systems attached to computers. Changes in the volume of each protein visible in gels are computed by image-analysis software, and this analysis is done on the basis of the area occupied and the visible intensity of the individual protein spots. Image analysis software provides data in tabular or graphic (huge variety such as pie, bar, line graphs) form with changes in comparison with controls. Once the data of PMF are received and identified by performing a match to several proteomic databases/databanks, protein spots on the gel image and in tables are assigned names with identified or closest match. Although enough has been done to identify the protein of nodules (De-laPen˜a et al., 2008; Larrainzar et al., 2007; Lei et al., 2005; Siria et al., 2000), unambiguous understanding of changes in proteome of nodules under stress is yet to be achieved. The few studies dealing with nodules in response to different stressors are discussed below. A. OXIDATIVE STRESS-RELATED PROTEINS IN NODULES
There are certain edaphic, climatic and biological factors that limit the biological nitrogen fixation. Edaphic factors include excessive soil moisture, drought, soil acidity, P deficiency, excess mineral N and deficiency of Ca, MO, CO and B. Among climatic factors, biuret, light and temperature are of great significance, whereas biotic factors include excessive defoliation of host plant, crop competition and insects and nematodes. Under stress conditions, plants have an outburst of oxidative stress producing a mixture of superoxide radicals, hydrogen peroxide and N2O molecules (Kav et al., 2007), along with the other responses. The legume nodules operate various antioxidant mechanisms, including ascorbate–glutathione cycle, in order to mitigate the oxidative stress so as to maintain metabolic pathways near normal (Fig. 5; Matamoros et al., 2003).
SDS PAGE/ MW
IPGs
Root (gel1)
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IEF/pI SDS PAGE/ MW
Stress
Nodule proteome (control, gel3)
In-gel proteins excised from 2D gels (gel1, gel2, gel3 and/or gel4; selection assisted by image analysis software
Protein digestion, MS, databank queries, identification
IEF/pI Proteomes
Nodulation and developmental stages
Root cell/hair
Protein extraction, sample preparation, focusing, SDS-PAGE, gel documentation
Rhizobium
Gel documentation
Protease (trypsin) digestion of proteins
LC-MS/MS/QTOF spectra
MALDI-TOF/TOF-MS Tandem mass spectrometry Stress 1
Mapman analysis
L.S. Nodule Stress 2
IEF SDS PAGE/ MW
Stressed nodule
Nodule proteome (stressed, gel4)
Stress 3
Data analysis
Mascot search result for protein identification by database match
Image analysis (comparative), spot numbering, selection of proteins of interest
Fig. 4. Diagrammatic representation of strategy for proteomics of individual organisms of nodule or complete nodule, under normal or stressed conditions.
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Peroxisome ox met
n
H2O
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MDHA
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D SO Mn
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gEC
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(h)GSSG ROH FeSOD CuZnSODp
+
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GSH-PX
H2O2 APX
DR
Cu
id
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st Pla
Mi toc ho
MR H2O2
Glu + Cys g ECS
ETC
− MnSOD
O2
g ECS
H2O2 gEC
CAT
GSHS
H2O
GSH
Bacteroid
Fig. 5. Antioxidant enzymes of legume nodules localised in different organelles and bacteroid. ASC, ascorbate; CAT, catalase; CuZnSODc, cytosol CuZnSOD; CuZnSODp, plastid CuZnSOD; DHA, dehydroascorbate; DR, dehydroascorbate reductase; EC, Glu-Cys; ECS, -glutamylcysteine synthetase; ETC, electron transport chain; GL, L-galactono--lactone; GLDH, L-galactono--lactone dehydrogenase; GR, glutathione reductase; (h)GSH, (homo)glutathione, reduced form; (h)GSHS, (homo)glutathione synthetase; (h)GSSG, (homo)glutathione, oxidised form; Lb, leghaemoglobin; MDHA, monodehydroascorbate; MR, monodehydroascorbate reductase; Ox met, oxidative metabolism. Reproduced from Matamoros et al., 2003 with permission.
Synthesis as well as degradation of proteins in the root nodules is equally important for normal metabolism, growth, development, homeostasis and cell death, thus making the proteome very dynamic, enabling continuous changes in protein patterns including various cellular compartments (Feller et al., 2008). Therefore, equilibrium between proteolysis and protein synthesis is an important process in maintaining homeostasis of plant cell under optimal and stress conditions. Recent advances in nodule-proteome analysis have revealed various stress-induced and suppressed proteins that are involved in maintaining and regulating the internal metabolism of plants against various environmental stresses. It has been reported that the main proteins of root nodules (nif proteins) may also be non-enzymatically cleaved by the reactive oxygen species (ROS). These ROS may directly cleave the nodule protein or modify it in such a way that it becomes more susceptible to
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proteolytic cleavage. Induction of increased levels of ROS has been demonstrated in response to abiotic stress caused by high light at low temperatures (Nakano et al., 2006), and exposure to heavy metals. Continuous exposure of root nodule to abiotic stress increases the level of several metabolites, proteins with known enzymatic or structural functions and regulatory proteins that may provide a certain degree of tolerance. Stress-induced proteins include key enzymes for osmolytes (proline, betains, sugars such as trehalose and polyamines) biosynthesis, detoxification enzymes, water channel and transport proteins and these may be targeted as the active components available for manipulation. Identification of the precise physiological roles of most stress genes/proteins has proved to be a challenging task. There is a need to eliminate effectively the ROS generated as a result of environmental stresses in aerobic organisms. However, ROS are also generated in nodules during normal metabolic processes such as respiration. Depending on the nature of the ROS, some are highly toxic and need to be rapidly detoxified. In order to control the level of ROS and protect the cells from oxidative injury, nodules develop a complex antioxidant defence system to scavenge the ROS. These systems include various enzymes and non-enzymatic metabolites that may play a significant role in ROS signalling within the cell and between organisms of the nodule symbiosome. Enzymes involved in oxidative protection, such as glutathione peroxidase (GPX), superoxide dismutase (SOD), ascorbate peroxidases (APX) and glutathione reductase (GR), and finally proteins involved in regulatory functions and in signal transduction, including protein kinases and transcriptional factors, have a broader role in governing plant responses to stress (Fig. 5; Matamoros et al., 2003; Scharf et al., 1998; Shinozaki and Yamaguchi-Shinozaki, 1997). SOD is a group of metalloenzymes that alter its activity under different environmental conditions. It is a highly efficient catalyst mediating a pivotal reaction in the antioxidant pathway (Foyer et al., 1994). An SOD isoform acts with APX, monodehydroascorbate reductase (MDAR) and GR in order to ensure maximum protection to the cell. In this scheme, APX reduces the H2O2 generated by SOD activity into H2O (Bowler et al., 1992). In proteomic studies, catalase was found increased under high temperature in wheat leaf (Majoul et al., 2004), but nothing can be predicted about its level under stress until more studies come forward. Moreover, the behaviour of nodule catalase is yet to be demonstrated. One of the most extensively studied alkaline proteins that accumulated in response to salt adaptation is osmotin, which was first identified in salt-adapted tobacco cells. Tobacco contains at least three isoforms of osmotin, all of which are cationic. The 26-kDa mature protein is localised to the vacuole. Osmotin is classified as a pathogenesisrelated (PR) protein, because in early studies, it was found to accumulate
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after pathogen infection. Hajheidari et al. (2005) and his associates observed, using the proteomic approach, an osmotin-like protein up-regulated in drought conditions. Similar types of protein, however, have been described in the nodules of M. truncatula (Gamas et al., 1998). B. PATHOGENESIS-RELATED PROTEINS
Pathogen-responsive proteins involved in defence mechanism in root nodules against abiotic stress account up to approximately 12% of all proteins identified in pea roots. These proteins, protecting plants against pathogenic fungi, bacteria and viruses as well as adverse environmental conditions, are induced by a variety of biotic and abiotic stimuli such as wounding, pathogen infection or environmental stress (Kav et al., 2007). In an experiment, the most abundant protein in the 2DE proteome-reference map has been identified as an abscisic acid-responsive protein with a high MOWSE score (783). The photosynthetic carbon-fixation enzyme, ribulose-bisphosphate carboxylase, is the most abundant protein found in roots and root-derived cell cultures. It has been found that of the five most abundant proteins in the root-nodule cultures, that is ABR-17, thaumalin-like proteins PR-5b, 1,3-glucanase, calmodulin and in 2-1 protein, all are PR and stress-related proteins, although calmodulin is generally thought to be involved in signal transduction (Larrainzar et al., 2007). The most abundant proteins in nodules are the common metabolic enzymes and transport proteins. The preponderance of disease- or stress-related proteins in nodule-suspension cell cultures has been attributed to the stress associated with the growth of cells in culture. In fact, some PR proteins have been demonstrated to be induced by the culture process. Classes of defence/stress-related identified proteins include protease inhibitors peroxidase, proteomase and carboxylase. Many unique nodule proteins have been revealed for the first time (Wienkoop and Saalbach, 2003). Some proteins are not under the influence of signalling pathways such as activation of MMP2 protein is not dependent on salicylic acid or jasmonic acid (JA) signalling pathways. Proteins not identified in the previous proteomic studies of nodules include halo acid dehalogenase-like family, which has a sequence similar to sucrose-6-phosphate phosphohydrolase and a sequence from Arabidopsis that has halo acid dehalogenase-like domain, osmotin-like protein precursor, UVB resistance protein-like protein, thaumatin-like protein PR-5b and MHN13. The last one (MHN13), identified in M. trancatula (Gamas et al., 1998), is closely related to the PR10 family unlike some other members of the PR10 family found in M. trancatula, such as MtPR10-1, which is constitutively expressed in roots and pathogens inducible in leaves;
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MtN13 has been reported to express exclusively in roots during nodulation and occur specifically in the nodule outer cortex. However, recent work related to the high expression of MtN13 transcripts in alfalfa trichomes may be a portion of the gene expression pattern of the tissue from which they were derived. Some proteins that are induced or regulated (up-regulation or down-regulation) have been found by proteomic techniques and bioinformatics tools as being associated with nutrient stress. C. ABIOTIC STRESSES AND IDENTIFIED PROTEINS IN NODULE
The stresses discussed above are of great concern as these pose serious threats to the productivity of legumes. Since the productivity of legumes directly depends on the health of nodules, proteomic profile of nodules may provide a broad view of proteins present in nodule-based symbiome. This will significantly help in designing and developing strategies to combat stress and improve legume productivity with their least affected N2-fixing efficiency. The literature is not that rich in protein data obtained from nodules. Furthermore, there are only few reports focusing on nodules for analysis of protein profile altered in response to abiotic stress. Several proteins and some related to SNF, such as nifD, nifK, nifH and nitrogen regulatory protein II (GlnB) and PIIA (PtsN) and urease accessory proteins (UreEs), have been found to be affected by different stresses. A number of proteins identified in nodules of a model legume have been listed in Table II. The effect of major individual stresses is discussed below. 1. Drought stress Drought is one of the major environmental factors adversely affecting crop production. SNF gives early response to drought stress, and related proteins are expressed in the nodules of legumes. One of the most important legumes studied for the proteomics of N2-fixation under drought is M. truncatula (Bestel-Corre et al., 2002; Grimsrud et al., 2010; Larrainzar et al., 2007; Mathesius, 2009). About four proteins induced flavonoid elicitors in R. leguminosarum, nodB, nodE and other low molecular mass proteins, with no homology to known proteins having been identified. Chen et al. (2000, 2005) identified 59 upregulated and down-regulated proteins from nolR mutation having different functions like basic metabolism, heat shock, protein synthesis, translation, oxidative stress and cell growth in S. meliloti. Other proteins including MyK15 have been identified in relation to drought stress (Fester and Strack, 2003). Furthermore, proteins involved in signalling processes in nitrogen-fixing nodules have been analysed. Two calmodulin-like proteins (CaML) have been
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identified corresponding to proteins CaML2 and 6b. A third protein, CaML4, has also been detected in M. trancatula (Larrainzar et al., 2007). Some other proteins related to SNF, predominantly the components of the nitrogenase complexes, such as nifD, nifH and nifK, and other nitrogen regulatory proteins PII (GlnB), PIIA (PtsN) and UreEs that are essential for nitrogen fixation in legumes have been identified in the root nodules. With the genomic approach, new gene up-regulation has been reported in the nodules of L. japonicus (Asamizu et al., 2005) and soybean (Clement et al., 2008). 2. Salinity stress Marginal agricultural and irrigated lands are buffering with high salt concentration predominant with NaCl. Root nodules of legumes in alkaline soils and semi-arid regions have been affected adversely (Shamseldin and Werner, 2006). Since the nodules take their nitrogen for growth and development from the soil, the rate of growth becomes highly retarded in saline conditions. There are only few reports on salt stress proteomics carried on root-nodule showing up-regulation and down-regulation of proteins that have been identified (Kav et al., 2007; Shamseldin and Werner, 2006). In salt-tolerant Rhizobium etli, 35 proteins decreased and 14 increased in concentration after exposure to salt stress. In S. meliloti, several proteins have been identified under salt stress, including the overexpressed proteins hypothetically exported protein from cellular periplasmic space and belonging to a protein family of extracytoplasmic solute receptors. Other proteins were carboxynospermidin decarboxylase, involved in the biosynthesis of spermidine via decarboxylation of ornithine and arginine. Six other proteins found downregulated belong to ABC transporters (Shamseldin and Werner, 2006). However, it is still to be mapped how legume proteins change their level of expression while responding to salinity and how these proteins are linked together in a signal pathway of salt-stress adaptation. 3. Temperature stress Stress may be caused by low (10 8C or less) or high (e.g. 35 8C or more) temperature extremes. Plants are facing high temperature stress due to annual temperature rise because of greenhouse gas emission. The worldwide extensive agricultural losses are attributed to heat, often in combination with drought or other stresses. Legumes growing in tropical areas face both high and low temperatures. As in numerous non-leguminous plants (see Qureshi et al., 2007; Timperio et al., 2008), HSPs overexpress in legume nodules (Panter et al., 2000). The HSPs and their homologues must perform many essential functions in both normal and stressed cells. According to current
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understanding, HSP60, HSP70 and HSP90 function to establish the conformation or assembly of other protein structures. A number of stress-protein families, including HSP90, HSP70, chaperonin 60, HSP40, the LMW stress proteins and ubiquitin, have been identified in diverse phyla (Lewis et al., 1999). Under normal conditions, several of the major stress proteins are present at low levels and function as ‘‘molecular chaperones’’, with key components contributing to cellular homoeostasis in cells under both optimal and adverse growth conditions (Wang et al., 2004). Several proteins under low and high temperatures show up-regulation or down-regulation, 19 proteins were induced and 12 de novo and 7 others were clearly up-regulated. Several other heat shock proteins have been identified under temperature stress but in B. japonicum grown in vitro outside the nodule (Mu¨nchbach et al., 1999). The heat shock-induced proteins that have been identified fall into four classes: known sHsp, novel sHsp homologues, GroESL/DnaK and unknown proteins. Of the 10 sHsp, two, HspA and F, have not been observed under temperature stress (Mu¨nchbach et al., 1999). In a study conducted by Panter et al. (2000), soybean PBM proteins were isolated from nitrogen-fixing root nodules and subjected to N-terminal sequencing. Sequence data from 17 putative PBM proteins were obtained, 6 of them being homologous to proteins of known function. These include three chaperones (HSP60, BiP [HSP70], a PDI and two proteases (a serine and a thiol protease), all of them being associated with some aspect of protein processing in plants. The PBM homologues of these proteins were speculated to play roles in protein translocation, folding, maturation or degradation in symbiosomes. Two proteins are homologous to known, nodule-specific proteins from soybean, nodulin 53b and nodulin 26B. Although the function of these nodulins is unknown, nodulin 53b is independently associated with the PBM. All of the eight proteins with identifiable homologues are likely to be peripheral rather than integral membrane proteins. The identification of homologues of HSP70 and HSP60 associated with the PBM was the first evidence that the molecular machinery for co- or post-translational import of cytoplasmic proteins is present in symbiosomes (Panter et al., 2000). This has important implications for the biogenesis of this unique, nitrogen-fixing organelle. The existing proteomic data on nodules are yet deficient to have a complete understanding of metabolism and related heat shock proteins and protein interactions. There is still a gap in understanding of molecular heat responses of rhizobia, including mechanisms for acquired thermotolerance, and the effects of heat on nodulation and symbiotic gene expression and also on proteome profile, including enzymes involved in nodulation and nitrogen fixation at high temperatures under field conditions.
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4. Metal stresses Plants respond to heavy metal toxicity in a variety of ways (Aghaei et al., 2009; Qadir et al., 2004) that include immobilisation, exclusion, chelation and compartmentalisation of the metal ions, formation of peptide metalbinding ligand PCs (Grill et al., 1985) and MTs (Cobbett and Goldsbrough, 2002) and expression of more common reactions such as formation of ethylene and stress proteins. A large number of stress proteins are induced by heavy metal stress with a molecular mass of 10,000–70,000 kDa in the leaves of different plant species. Ahsan et al. (2009) reviewed recent developments in plant proteomic responses to metals. For a better understanding of the global changes in the proteomic profile of symbiotic partners or symbiosome in response to metal stresses, we still have to go a long way. a. Cadmium stress. Only few studies have been conducted on the proteomics of nodules under heavy metal stress. Chen et al. (2003) observed a decline due to cadmium stress in the process of nodulation and N2-fixation in soybean together with ultrastructural changes in the nodules. Cadmium has also been shown to affect the interaction between legume and rootnodule bacteria (Ausili et al., 2002) and induce senescence in the soybean nodules (Balestrasse et al., 2004). Induction of oxidative stress in the nodules by the accumulation of -aminolevulinic acid (Noriega et al., 2007) may be one of the reasons. However, flavodoxin overexpression reduces the cadmium-induced damage in alfalfa root nodules (Shvaleva et al., 2010). The proteins identified by 2D analysis in root nodules such as in peribacteroid membrane include HSP60, BiP, protein disulfide isomerase, thiol isomerase, two functional unknown nodule-specific proteins and subtilisin-like serine protease (Panter et al., 2000), but no study has shown the impact of Cd on most of the proteins identified in the nodules. A recent review by Mathesius (2009) catalogues the identified proteins from the N2-fixing symbiosome. b. Arsenic stress. Arsenic is another non-essential element, which is highly soluble, hence available and occurs naturally in ground state. This is considered to be toxic for both plants and animals. Arsenic is present in soils in the form of arsenate and arsenite (see Smith et al., 2009). Arsenic is extensively studied for its impact on plant species (Ahsan et al., 2010; Gunes et al., 2009; Panda et al. 2010; Singh et al. 2006), but little is known about its effects on root nodules on the proteomic level (Mandal et al., 2009). The impact of arsenic on proteome in plants has been studied in the leaves and roots of maize (Requejo and Tena, 2005, 2006). Rhizobium VMA301 has been isolated from the root nodules of Vigna mungo, grown in arsenic-contaminated field.
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Sixteen differentially expressed proteins have been identified using RP-HPLC and MALDI-TOF-MS from arsenite-induced whole-cell-lysate-soluble proteins. Nine proteins were up-regulated and seven proteins were downregulated in comparison with the control group (cells grown without arsenite) in V. mungo. These differential protein expressions have been suggested to mitigate the toxic effect of arsenite and stimulate the detoxification process (Mandal et al., 2009). The proteins identified are functionally involved in cell signalling, stress and detoxification, defence and development and protein biosynthesis. It is possible that arsenic stress generates ROS, triggering signal molecules such as JA and S-adenosyl-methione (SAM), and activating the detoxification process, which mainly involves glutathione/PC biosynthesis. Further studies have yet to be carried out within root nodules under arsenic stress. c. Aluminium stress. Aluminium is the third most abundant element in soils after oxygen and silicon; plants are therefore exposed to some of Al in soils (Ma et al., 2001). Al solubilises in the form of its toxic trivalent cation (Al3þ), which can subsequently accumulate in high concentrations in the soil. To our knowledge, there are only few reports on proteomic responses of plants to Al stress; these are related to rice (Yang et al., 2007), tomato (Zhou et al., 2009) and soybean (Zhen et al., 2007). More than 1200 root proteins of soybean BX10 seedlings were reproducibly resolved on gels. A total of 39 differentially expressed spots in abundance were identified by MS, with 21 up-regulated, 13 newly induced and 5 down-regulated ones. The heat shock proteins, glutathione S-transferase, chalcone-related synthetase, GTP-binding protein and ABC transporter ATP-binding protein, have been detected at the transcriptional or translational level in other plants. Other proteins, identified by Zhen et al. (2007), are new Al-induced proteins. Soybean BX10 roots under aluminium stress could be characterised by the cellular activities involved in stress/defence, signal transduction, transport, protein folding, gene regulation and primary metabolisms, which are critical for plant survival under Al toxicity.
VI. APPLICATIONS OF NODULE PROTEOMICS Legumes are unique in their ability to fix atmospheric nitrogen through symbiotic relationships with rhizobia, resulting in accumulation of high protein content in the host plants and the portioning of nitrogen in the soil (Lei et al., 2007). In the current global environmental scenario, these are only legumes that can supply dietary protein needed by millions of mouth. Unfortunately, commercial legumes, such as soybean and alfalfa, have large
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complex genomes that make the direct molecular and genetic study of these species a bit more challenging. As a result, M. truncatula has been adopted as a model species for studying legume biology. Even when the genome of this species is fully sequenced, it will require availability of protein sequences to provide genomic data a meaning. The nodule-based proteomics has yet to explore symbiotic proteome and its dynamism under various growth conditions. Despite the availability of the literature on the mechanism of symbiosome induction, maintenance and regulation, it is yet to be revealed how these parameters are affected by environmental factors. Symbiosome researchers would then be assisted with better tools to develop strategies for improved rate of nodule induction, growth, development and functioning; and more importantly for conversion of non-N2-fixing plants to N2-fixing plants. Proteomics may be used for individual organism of symbiosome proteome analyses, nodule proteome (symbiosome), systematic identification of specific proteins, proteins that attract rhizobium towards host roots, proteins involved in nodulation and its progression and proteins regulating the nodule metabolism. Application of proteomics associated with N2-fixing root nodules in modern biology is growing fast so as to sustain challenges for the prospective harsh environmental conditions such as increasing pollution, global warming and nutrient imbalance. Significantly, proteomics helps to understand the proteins of root nodules which are involved in nitrogen metabolism, carbon metabolism and cell-division processes (Natera et al., 2000), and the way in which their metabolism and regulation operate. Several bacterial proteins involved in plant–microbe interactions allow for knowing the actual mechanism of the symbiotic relationship of host and pathogens. Obtaining the data of protein sequencing, proteins seem to play key role in response to abiotic stress may be focused to understand the functions of identified proteins/genes. Nodule-specific proteins may serve as physiological markers of tissue-specific protein expression. Putative unique proteins may provide a valuable insight into the specialised physiological function of leaves. Tissue-specific SDS-PAGE/2DE protein profiles will provide reference maps for future proteomic comparisons of wild-type, genetic mutants and biotically or abiotically stressed plants. Proteomic analysis also gives an idea where, when and at what level a messenger will be translated and the corresponding protein will accumulate. Proteomics of nodules further helps in the study of post-translational modifications (such as cutting of signal peptide, phosphorylation, glycosylation). It is clear that the proteomic strategy has been responsible for the discovery of numerous new proteins and for cataloguing previously unknown cellular and sub-cellular protein compliments (Rampitsch and Srinivasan, 2006). Proteomic data will enable investigation of proteins/genes for crop improvement in an effective manner.
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VII. CONCLUSIONS It can be concluded that proteomics in root nodules under abiotic stress allows for the characterisation of different novel nodule proteins and understanding their corresponding functions which would help in development of better crops. Development of a similar approach in legume resistance to parasitic plant infection may reveal new, unexpected pathways and help to understand the specific early resistance mechanisms involved, if any. By obtaining data on protein sequencing, proteins playing a key role against abiotic stress may be focused apart from understanding the functions of identified proteins/genes. It will unravel the actual mechanism of the symbiotic relationship between host and pathogens. Identification of several genes provides better information for combating the stresses. However, studies conducted on Indian mustard [unpublished data of the TMOP&M/CSIR (Government of India)-sponsored research project] have shown that the productivity of mustard was significantly enhanced when seeds were inoculated with Rhizobium spp. prior to sowing. But no study has been conducted to examine whether any relation by rhizobium was established in the host plant. Efforts are in progress to convert C3 plants to C4 plants for a better photosynthesis rate. At a time when excessive use of N-fertilisers poses a potential threat to the environment (Singer, 2009), scientists also have a responsibility to convert non-N2-fixing plants to N2-fixing ones for ensuring a cleaner environment, enhanced productivity of crops and cost-effective availability of nitrogen fertilisers.
ACKNOWLEDGEMENTS This study is supported by the University Grants Commission and the Department of Science & Technology, Government of India through extramural research funding to M. I. Qureshi and UGC fellowships to other authors, except Muhammad Iqbal.
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Molecular Aspects of Fragrance and Aroma in Rice
APICHART VANAVICHIT*,{,1 AND TADACHI YOSHIHASHI{
*Rice Gene Discovery, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Kamphangsaen, Nakhonpathom, Thailand { Rice Science Center and Agronomy Department, Faculty of Agriculture, Kamphangsaen, Nakhonpathom, Thailand { Postharvest Science and Technology Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Ibaraki, Japan
I. 2-Acetyl-1-Pyrroline, a Potent Flavour Component of Aromatic Rice. . . . II. Aromatic Gene Discovery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Mendelian Genetics of Grain Aroma ...................................... B. Genetic Mapping of Grain Aroma ......................................... C. QTL Mapping of 2AP ........................................................ D. Map-Based Cloning of the Gene Controlling Grain 2AP............... III. Molecular Mechanisms Regulating 2AP Biosynthesis . . . . . . . . . . . . . . . . . . . . . A. Isogenic Lines Revealed the Absence of the Os2AP Transcript........ B. Suppressing Os2AP by RNAi Makes Rice Aromatic.................... C. Overexpression of Os2AP Turns Aromatic Rice to Non-Aromatic Rice ........................................................... D. Alternative Mechanism of Regulating 2AP Biosynthesis ............... IV. Biochemical Functions of Os2AP and BADH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. The Os2AP Protein is an AMADH ........................................ B. Kinetic and Affinity Studies of Isolated Enzymes, Os2AP and BADH ......................................................... V. Formation Pathway of 2AP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Chemistry Behind 2-AP Formation ........................................
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Corresponding author: E-mail:
[email protected]
Advances in Botanical Research, Vol. 56 Copyright 2010, Elsevier Ltd. All rights reserved.
0065-2296/10 $35.00 DOI: 10.1016/S0065-2296(10)56002-6
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B. Source of Nitrogen in 2AP ................................................... C. Source of Acetyl Group in 2AP ............................................. D. Metabolic Disorder Makes Rice More Aromatic ........................ VI. Genetic Diversity and Origin of the Aromatic Gene. . . . . . . . . . . . . . . . . . . . . . . A. Genetic Diversity of the Aromatic Rice.................................... B. Naturally Occurring Allelic Variation of the Aromatic Gene .......... C. Origin of the Aromatic Gene ................................................ D. Ancestors of the Aromatic Gene ............................................ E. Evolutionary Relationship Among Plant BADH/AMADH Family ............................................... F. Deficiency in AMADH Makes Aromatic Plants ......................... VII. Environmental Adaptability of Aromatic Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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ABSTRACT Grain aroma is the most attractive characteristic of high-quality rice, and demand for it is not only increasing in the Asian market but is also widely recognized in Europe and all over the world. Aromatic rice is rare and so precious that in some countries, it is considered a national asset and pride. The aromatic compound, 2-acetyl-1pyrroline (2AP) was discovered in rice in 1983 [Buttery, R. G., Ling, L. C., Juliano, B. O., and Turnbauhg, J. G. (1983). Cooked rice aroma and 2-acetyl-1-pyrroline. Journal of Agricultural and Food Chemistry, 823–826.], but the gene controlling the accumulation of 2AP has only recently been identified by map-based cloning (Os2AP). The molecular genetics, biochemistry, and evolution of the aromatic gene have been elucidated in recent years as a consequence of the gene discovery. Aromatic rice has accumulated several natural mutations in an amino aldehyde dehydrogenase (AMADH) that oxidizes -amino butylaldehyde to -amino butyric acid (GABA). RNA interference against the cloned Os2AP generated aromatic from non-aromatic rice plants. A similar technique was used to achieve new aromatic soybean. Aromatic gene also shed new light on evolutionary and domestication aspects of the most important cereal of mankind. The time has come to review past achievements in the light of the recent discovery of the functions of aromatic genes in rice and other plant species.
I. 2-ACETYL-1-PYRROLINE, A POTENT FLAVOUR COMPONENT OF AROMATIC RICE The fragrance of cooked rice consists of more than 200 volatile compounds such as hydrocarbons, alcohols, aldehydes, ketones, acids, esters, phenols, pyridines, pyrazines, and other compounds (Maga, 1984; Paule and Power, 1989; Tsugita et al., 1980; Yajima et al., 1978). A comparative study of the volatile components of aromatic and non-aromatic rice varieties showed that 2-acetyl-1-pyrroline (2AP), which contributed to specific flavour in aromatic rice and has comparably lower odour threshold among rice volatiles, occurs at higher levels in aromatic rice varieties and at significantly lower levels in
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non-aromatic rice varieties (Buttery et al., 1983). Numerous studies have shown that 2AP is the only volatile compound in which the relationship between its concentration in rice and sensory intensity has been established (Maga, 1984; Paule and Powers, 1989; Tsugita et al., 1980; Yajima et al., 1978). The compound 2AP, usually described as a ‘‘pop-corn’’ or ‘‘roasted’’ flavour compound, was also identified as an important attribute of processed foods such as wheat bread crust, rye bread (Buttery et al., 1982, 1983), popcorn (Schieberle, 1991), and wet milled millet (Seitz et al., 1993). Interestingly, 2AP was also identified in other plants and microbes, including pandan leaves (Pandanus amaryllifolius Roxb.) (Buttery et al., 1983), bread flowers (Vallaris glabra Ktze.) (Wongpornchai et al., 2003), soybean (Fushimi and Masuda, 2001), Bacillus cereus (Romanczyk et al., 1995), Lactobacillus hilgardii (Costello and Henschke, 2002), and fungi (Nagsuk et al., 2003).
II. AROMATIC GENE DISCOVERY A. MENDELIAN GENETICS OF GRAIN AROMA
Grain aroma was reported to be governed by a single recessive nuclear gene (Huang et al., 1994; Sood and Siddiq, 1978), with a few exceptions. So far, the inheritance of grain aroma has been reported to depend on the genetic background of the materials being studied. Grain aroma has also been reported to be governed by a dominant gene (Jodon, 1944), or found to be di- or trigenic (Dhulappanavar, 1976; Kadam and Patankar, 1938; Nagaraju et al., 1975; Reddy and Sathyanarayanaiah, 1980).
B. GENETIC MAPPING OF GRAIN AROMA
Several aromatic rice varieties were used for genetic mapping; some examples are aromatic japonicas including Della (Ahn et al., 1992), Azucena (Bourgis et al., 2008; Lorieux et al., 1996), Suyunuo (Chen et al., 2006; Shi et al., 2008), and Wuxianjing (Chen et al., 2006). Quantitative trait locus (QTL) mapping was also performed in such aromatic indica rice as Jasmine (KDML105) (Lanceras et al., 2000; Tragoonrung et al., 1996), Kyeema (Bradbury et al., 2005), and Wuxiangxian (Chen et al., 2006). Those results produced the consensus genetic map that confined grain aroma within 3.5–4.5 cM; this region was flanked by two polymorphic SSR markers on chromosome 8.
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A. VANAVICHIT AND T. YOSHIHASHI C. QTL MAPPING OF 2AP
Genetic mappings of grain aroma were reported as a qualitative trait based on sensory tests. However, volatile compounds of different aromatic rice varieties, particularly the amount of 2AP, varied quantitatively (Fitzgerald et al., 2008; Goufo et al., 2010; Hein et al., 2006; Itani et al., 2004). Due to costly analysis of 2AP, only limited QTL mapping experiments for grain 2AP content were reported so far. The grain 2AP-density was identified in three map locations (Lorieux et al., 1996). The major QTL mapped on chromosome 8 coincided with the consensus genetic map based on sensory test on chromosome 8 (Chen et al. 2006; Lorieux et al., 1996). In addition, two minor QTLs were localized on chromosomes 4 and 12 (Lorieux et al., 1996). Therefore, the 4.5 cM map interval between RG1 and RG28 on the chromosome 8 was considered a critical region for map-based cloning.
D. MAP-BASED CLONING OF THE GENE CONTROLLING GRAIN 2AP
The first mapping of grain aroma took place in 1992 (Ahn et al., 1992), and the gene responsible for grain aroma was identified 12 years later, with the first and only successful map-based cloning of the gene controlling 2AP (Fig. 1; Vanavichit et al, 2004, 2005). By taking advantage of within-family segregation for 2AP from the F6 to the F13 generations of the cross between Jasmine rice and a non-aromatic rice, the original 1.13-Mb region flanked by RG1 and RG28 was effectively narrowed down to 82.8 kb, where three KDML105 Bacterial Artificial Chromosome (BAC) clones were shotgun sequenced, and three candidate genes were identified (Vanavichit et al., 2005). ORF3, later named Os2AP, was determined to be responsible for grain aroma in aromatic rice, because double recombinations within ORF3 resulted in the disappearance of 2AP. Comparative sequence analysis of ORF3 between KDML105 and Nipponbare revealed that the 4.5-kb genomic sequence contained 15 exons of the 1512-bp coding sequence that translated into the 503 amino acid sequence in non-aromatic Nipponbare. In aromatic KDML105 and within the exon 7 of Os2AP, two important mutation events were found at positions 730 (A to T) and 732 (T to A), followed by the 8-bp deletion ‘‘GATTAGGC’’ starting at position 734 (Fig. 1). A second map-based cloning approach was also reported; in a cross between aromatic Kyeema and a cultivar of non-aromatic rice, grain aroma was mapped on chromosome 8 between the SSR markers RM515 and SSRJ07 (Bradbury et al., 2005). The in silico physical map consisted of four Nipponbare BAC clones spanning the 386 -kb flanked SSR markers RM515 and SSRJ07. Re-sequencing one of the BAC clones revealed 17 genes. However,
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Fig. 1. Map-based cloning of the aromatic gene in rice: (A) fine-scale mapping in the 700-kb region spanned by a KD BAC contig. Three KD BAC clones spanning a 170-kb region where the aromatic gene was expected were shotgun sequenced (B) high density mapping using 1116 F12 plants derived from a single F6 plant to narrow down the critical region to 27 kb in a single BAC. Six segregating F12 ISLs were graphically genotyped in the 82.8-kb region enriched by specific indel markers, (C) annotation of the genomic sequence of the KD BAC 68L13 found three ORFs similar to methyl crotonyl CoA lyase, hypothetical protein, the AMADH called Os2AP, a candidate
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significant sequence variation was identified in only one clone, which was later identified as BAD2, a betaine aldehyde dehydrogenase (BADH) homologue. In the screening of 14 diverse fragrant and 64 non-fragrant rice varieties, the sequence variation of exon 7 was perfectly matched with grain aroma, but no transgenic evidence was provided. Based on their similarity at both the nucleotide and amino acid levels, Os2AP and BAD2 were considered the same gene. A third map-based cloning effort was reported using in silico physical mapping within the critical region by comparing only genomic BAC-end sequences of Nipponbare (Wanchana et al., 2005) and by comparing genomic sequences between Nipponbare and 93-11 (Chen et al., 2008). The restriction map surrounding the region of the three candidate genes, carbonic anhydrase (CA), methylcrotonyl CoA carboxylase (MCC), and aldehyde dehydrogenase (Os2AP), was used to screen BAC clones of a local Chinese aromatic japonica rice cv. Suyunuo and a Chinese non-aromatic indica rice cv. Nanjing11; three subclones of each candidate gene were used for functional analysis. The conclusion that BAD2 was the best aroma candidate locus identified in the Azucena japonica cultivar was also reached using fine-scale mapping using Azucena IR64 (Bourgis et al., 2008). Once the gene regulating 2AP content in rice was cloned, the next step was to understand its functions and the regulation of 2AP accumulation.
III. MOLECULAR MECHANISMS REGULATING 2AP BIOSYNTHESIS A. ISOGENIC LINES REVEALED THE ABSENCE OF THE OS2AP TRANSCRIPT
Grain aroma is recessive to non-aroma. The 8-bp deletion in exon 7 found in aromatic rice varieties all over the world is the functional marker of aromatic rice. The first approach investigating how the aromatic gene functions was achieved by comparing the isogenic lines A117 and NA10, which differ only in the 27-kb genomic region containing the aromatic gene Os2AP (Vanavichit et al., 2005). Transcription analysis of the Os2AP and flanking candidate genes revealed the differential expression of Os2AP in all parts of the rice plant. The compound 2AP is naturally expressed starting from young
gene controlling 2-acetyl-pyrroline, (D) gene models of Os2AP showing a double recombinants identified in 177 F6 plants from the cross between KD and JHN that knock-out the gene function and as a result generating 2AP and (E) the sequence part of the exon 7 where 8 bp deletion causes the early stop codon that disrupts the gene function.
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seedling to the grain-filling period and accumulates in mature grains. The pattern of 2AP expression was consistent with the constitutive expression of functional Os2AP in all plant organs. However, one exception was in the roots, where some researchers have reported no expression (Chen et al., 2008). Other researchers detected 2AP and Os2AP transcripts at low levels from rice roots and culture media (Vanavichit et al., 2005). This inconsistent expression result needs detailed studies to explain how the nonsense mutation causes suppressive expression in the different plant parts. The reduction of Os2AP transcripts was highly significant from 10 to 20 days after pollination (DAP) (Vanavichit et al., 2005; Fig. 2). In our laboratory, we illustrated the effect of reduced expression of Os2AP at the whole-genome level using the isogenic lines A117 and NA10 in the rice oligoarray version II Rice Array Database, http://www.ricearray.org/nsfarray/nsfarray.shtml, containing 20,190 unique gene-specific probes against total RNA isolated from plants harvested at 10–20 DAP (Fig. 3). The results confirmed that Os2AP was overexpressed fivefold, along with 72 other genes, in the non-aromatic NA10. On the other hand, only 17 genes were overexpressed in the aromatic line A117. In connection with the 8-bp deletion in exon 7 of the aromatic allele, the suppressive expression of Os2AP resulted from a premature stop codon at position 753, which shortened the full-length peptide to 252 amino acids in aromatic rice (Bradbury et al., 2005; Vanavichit et al., 2005). This short, incomplete peptide was reported to trigger nonsense-mediated decay (NMD) in several cases (Chang et al., 2007). The hypothesis postulated that NMD was operative in aromatic isogenic lines and in all aromatic rice.
B. SUPPRESSING OS2AP BY RNAI MAKES RICE AROMATIC
To confirm if the reduced expression of Os2AP was the genetic basis for 2AP accumulation, two transgenic approaches were applied. First, RNA interference (RNAi) was used to reduce the expression of the non-aromatic allele of Os2AP. The RNAi was constructed from the genomic sequence spanning exons 6 to 8 in the opposite direction from the corresponding cDNA. This allowed the transcript to create double-stranded RNA, resulting in NMD and aromatic Nipponbare that could accumulate 2AP in a range of 0.05– 0.20 ppm (Vanavichit et al., 2005). In this experiment, the strongest RNAi expression gave the strongest suppression and the highest accumulation of 2AP, comparable to the 2AP content in Jasmine rice (Vanavichit et al., 2005). In an independent study, transgenic rice containing RNAi by an inverted repeat of cDNA encoding Os2AP accumulated 2AP in considerable amounts (Niu et al., 2008).
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Fig. 2. (A) Expression analysis of the Os2AP and other predicted coding sequences from the genomic sequence of KD. Total RNAs were isolated from 10, 15 and 20 days after pollination (DAP), from aromatic versus non-aromatic ISLs. (B) Expression analysis of the Os2AP and actin between the aromatic ISL versus nonaromatic ISL where the total RNAs were isolated from stems, roots, leaves and seeds, 15 DAP.
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Fig. 3. Differential expression profiling using 21K oligonucleotide array (TIGR, 2005) against total RNA isolated during 10–20 days after pollination. Significant upregulated genes detected from both isogenic lines were compared. All raw data were listed in http://rice.kps.ku.ac.th/aroma-rice.html.
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A. VANAVICHIT AND T. YOSHIHASHI C. OVEREXPRESSION OF OS2AP TURNS AROMATIC RICE TO NON-AROMATIC RICE
While RNAi against Os2AP allows non-aromatic rice to accumulate significantly more 2AP, the question remained whether the overexpression of Os2AP would revert the aromatic to non-aromatic rice. The overexpression of various constructs of Os2AP, driven by a CaMV35S promoter, was compared in the transgenic aromatic rice cv. Wuxiangjing 9 (Chen et al., 2008). When comparing partial constructs of Os2AP, only overexpression from the intact one significantly suppressed the accumulation of 2AP in plantlets (Chen et al., 2008). This suggests that the reduced expression of the Os2AP is the key regulatory step for 2AP accumulation. Therefore, the results from both the RNAi and overexpression of Os2AP confirmed that Os2AP determines the accumulation of 2AP in rice. D. ALTERNATIVE MECHANISM OF REGULATING 2AP BIOSYNTHESIS
Some aromatic rice lines from isozyme Groups I and V in our laboratory did not show the 8-bp deletion. These aromatic rice lines have half the amount of grain 2AP compared to those with the 8-bp deleted lines. A multiple genomic sequence alignment among these aromatic lines identified a 3-bp addition in exon 13. This insertion is in frame with translation and adds a tyrosine into the peptide. In contrast to those 8-bp deleted aromatic lines, in these lines, Os2AP is expressed normally during seed development. The predicted threedimensional structure revealed that the additional tyrosine is perfectly situated in the NAD-binding pocket of the NAD-binding domain. To understand the effect of tyrosine addition, a full-length cDNA of the new aromatic allele was overexpressed in Escherichia coli for kinetic and binding studies. The isolated enzymes had lower enzyme activities than the wild type, perhaps because the proximity of the tyrosine addition may interfere with NAD binding. The two mutations, however, made the substrate 1-pyrroline more available for 2AP biosynthesis.
IV. BIOCHEMICAL FUNCTIONS OF OS2AP AND BADH A. THE OS2AP PROTEIN IS AN AMADH
The Os2AP protein was localized immunologically in the cytoplasm with the C-terminal serine-lysine-leucine (SKL) signal peptide specific for targeting to the peroxisome (Chen et al., 2008). Western blot analysis using immunodetection against the Os2AP peptide revealed a 55-kDa peptide in all
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non-aromatic rice varieties that was absent in all aromatic rice varieties. Once again, this result confirmed that the instability of the Os2AP transcript affects the protein stability at the post-transcriptional level in aromatic rice. The in vitro prediction of the two Os2AP alleles revealed the intact 55-kDa peptide in the non-aromatic allele, while 252 C-terminal residues were deleted in the aromatic allele. The significance of the C-terminus was predicted to be the entire substrate binding and oligomerization domains of the Os2AP protein (Bradbury et al., 2005; Chen et al., 2008; Vanavichit et al., 2005). To understand the roles of the missing null allele in 2AP biosynthesis, the enzymatic activities and substrate specificity were studied by native gel electrophoresis. Extracts from aromatic rice gave only one band at 55 kDa, while those from non-aromatic lines gave two major bands at 54 and 55 kDa (Unpublished data). The partial amino acid sequences revealed the lower band to be amino aldehyde dehydrogenase (AMADH), the product of Os2AP; the upper band was the product of BADH, that is the orthologue of Os2AP located on chromosome 4. The activity gel confirmed that the 54kDa Os2AP was more specific to the -amino butylaldehyde ABL substrate, whereas the BADH had a broader specificity. It is interesting that the two orthologues both play roles in 2AP accumulation in rice. Substrate specificity was one of the major differences between the Os2AP and BADH, as revealed by activity gel electrophoresis. In the activity gel where Abal and Betald were used as substrates, the 54-kDa band showed only AMADH activity, while the 55-kDa band showed AMADH and BADH activities. As a result, the author suggested that BADH2 be renamed AMADH based on the specificity, because these results were confirmed by the partial amino acid sequence. These conclusions were in contrast with the Western blot results, which showed that the 55-kDa band was the product of Os2AP (Chen et al., 2008). However, all the non-aromatic rice varieties showed two faint bands similar to the activity gel; the upper band was common among several rice varieties. Considering the broader specificity of the enzyme, BADH could play important roles in interfering with 2AP accumulation in aromatic rice. To test this possibility, RNAi against BADH in either the aromatic or the non-aromatic background must be developed. B. KINETIC AND AFFINITY STUDIES OF ISOLATED ENZYMES, OS2AP AND BADH
To obtain insights into the kinetics of both enzymes, the overexpression of the cloned Os2AP and BADH in E. coli was reported (Bradbury et al., 2008). The overexpressed Os2AP in E. coli showed moderate affinity towards Betald but higher affinity towards ABald (Bradbury et al., 2008).
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Surprisingly, the BADH showed no affinity towards Betald but moderate affinity towards ABald (Bradbury et al., 2008). Similar results were reported on the low affinity of both Os2AP and BADH towards Betald, while the affinity towards ABald was higher. However, the in vitro and in vivo enzyme specificities were quite different. From the native gel activities, the 54 kDa Os2AP was expressed only in non-aromatic varieties, and Os2AP bound only to ABald. Trossat et al. (1997) (21) reported that transgenically expressed BADH from Beta vulgaris showed AMADH activity, and they suggested that AMADH from Avena sativa, Pisum sativum, Setaria italica, and Vicia faba should be the same enzyme as BADH. However, recent studies demonstrated that a homogenous AMADH showed no BADH activity (Sebela et al., 2000); overexpressed BADH also showed no AMADH activity in higher plants (Hibino et al., 2001). Since BADH and AMADH share a high level of similarity at the genomic and amino acid levels, AMADH could have been misidentified as BADH even though their substrate specificities were different. The differences between in vitro and in vivo enzyme specificities must be studied further. One possible experiment would be creating a post-transcriptional modification to interfere with the substrate binding site.
V. FORMATION PATHWAY OF 2AP A. CHEMISTRY BEHIND 2-AP FORMATION
The compound 2AP was isolated and characterized from the basic fraction of a steam distillation extract of aromatic rice. Thus, 2AP should be considered a basic compound. Its six-membered ring analogue, 6-acetyl-1,2,3,4tetrahydropyridine (6-ATHP), which has organoleptic properties similar to those of 2AP, is known as its tautomer and is shown in Fig. 4A. Grimm et al. (2001) and Yoshihashi (2002) also reported similar tautomerism of 2AP, by the observation of a tautomer peak in a GC chromatogram. The compounds 4-aminobutanal and 1-pyrroline, which are considered biological intermediates of 2AP by Os2AP disruption, are in equilibrium and can interconvert spontaneously Fig. 4(C). The compound 1-pyrroline was reported as 1-pyrroline trimer in neat form; however, it was also reported as 1-pyrroline in the gas phase by GC-FTIR analysis (Baker et al., 1992). Due to the prototropic tautomerism of these compounds, the tautomeric equilibria could affect the results of analysis, especially in aqueous solution. Thus, the quantification of these compounds must be carefully investigated, as a result could be influenced by a strong matrix effect of these
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B N
N H
N
N H
O
O
O
O
C −H2O H2N
CHO
N
+H2O
N
N
N
TCA cycle 2-Oxoglutarate
Succinate
Proline biosynthesis Glutamate
Succinate semialdehyde
AMADH 2AP
P5C
GABA
GABA shunt
Aromatic varieties
(Os2AP)
?? Proline
4-aminobutanal
Putrescine
Spermidine
Ornithine
Arginine
Polyamine synthesis and catabolism
Fig. 4. Tautomeric equilibria of 6-ATHP (A), 2AP (B) and 4-aminobutanal (C). Formation pathway of 2AP in aromatic rice. The pathway drawing is based on the literature cited. The detailed pathway from P5C to 4-aminobutanal was not reported yet. Aromatic varieties lack AMADH enzyme activity, which convert 4-aminobutanal to GABA, to yield 2AP.
equilibria. Another problem was the extraction method, as mentioned by Adams and De Kimpe (2006) regarding 2AP in B. cereus; they reported that ‘‘the use of a non-thermal extraction method is essential to obtain
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reliable results on the biological formation of these Maillard flavour compounds’’. Therefore, the interpretation of the results must consider these constraints. B. SOURCE OF NITROGEN IN 2AP
Yoshihashi (2002) reported that additions of glutamate and its related amino acids ornithine and proline induced 2AP formation in rice calli of an aromatic rice variety, Khao Dawk Mali 105; the addition of proline dramatically increased the 2AP content. From tracer experiments with 15N-labelled proline, it was also concluded that the pyrroline ring of 2AP originated from proline. Native AMADH, which is encoded by the Os2AP gene, was considered to act in polyamine catabolism because of its substrate specificity. The enzyme commonly converts 4-aminobutanal into 4-aminobutyrate (GABA); however, this catabolic reaction did not occur in aromatic rice varieties, and 4-aminobutanal was accumulated. The 4-aminobutanal was formed through the oxidation of putrescine by Cu-diamine oxidase via a non-reversible reaction. Yoshihashi et al. (2002) reported that the 4-aminobutanal content observed by GC–MS for aromatic rice callus content was stable even when proline was added. Since only 4-aminobutanal was observed as 1-pyrroline from the GC analysis, the non-enzymatic formation of 2AP in aromatic rice could arise from 4-aminobutanal. Huang et al. (2008) reported the formation of 2AP from pyrroline-5-carboxylic acid (P5C) by the up-regulation of P5C synthase 1 and 2 (P5CS1 and 2). They mentioned 1-pyrroline as the intermediate to 2AP formation although the detailed formation pathway from P5C to 1-pyrroline was not then described. QTL analysis of 2AP (Lorieux et al., 1996) determined not only that Os2AP is located on chromosome 8 but also that other loci could be related to 2AP formation. Therefore, it can be hypothesized that P5CS1 and 2 were the genes controlling 2AP formation by controlling the 4-aminobutanal content. In conclusion, both studies of nitrogen source point to 4-aminobutanal or 1-pyrroline as the source of the pyrroline ring of 2AP in aromatic rice. C. SOURCE OF ACETYL GROUP IN 2AP
Yoshihashi (2002) also performed a tracer experiment using 1-13C labelled proline and concluded that the acetyl group of 2AP did not originate from proline. Model studies on the thermal formation of 2AP with proline and ornithine revealed that the acetyl group of 2AP originated from 2-oxopropanal, which is a sugar degradation product of a deformylation reaction (Schieberle, 1995). Further model studies with isotopically labelled
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compounds also showed that 2-acetylpyrrolidine could be the intermediate of 1-pyrroline and 2-oxopropanal; however, the reaction also resulted in 6-ATHP (Hofmann and Schieberle, 1998). The compound 2-oxopropanal could react with ornithine and proline under thermal conditions and produce 2AP and 2AP and 6-ATHP, respectively. Detailed analysis of 2AP formation in L. hilgardii DSM 20176 showed that the catabolism of lysine and ornithine led to the formation of 2,3,4,5-tetrahydropyridine and 1-pyrroline, which then served to form 6-ATHP and 2AP, respectively (Costello and Henschke, 2002). Thus, acetyl-CoA or acetoaldehyde was proposed to induce the acylation of these intermediates to yield 6-ATHP and 2AP. However, 6-ATHP was not reported or observed in aromatic rice flavour; therefore, detailed studies of the introduction of the acetyl group into 4-aminobutanal are required to understand 2AP formation. In addition, Huang et al. (2008) proposed 2-oxopropanal as the precursor of the acetyl group, even in nonthermal conditions. In organisms, 2-oxopropanal is common because it is the intermediate of glycolysis; the reaction of 4-aminobutanal always produces 6-ATHP. It is not clear whether the same pathway as thermal formation occurred in aromatic rice. We should also mention that 2-oxopropanal is known for its high cytotoxicity and high reactivity and also as the most important glycation agent to DNA and proteins. D. METABOLIC DISORDER MAKES RICE MORE AROMATIC
The AMADH disorder in aromatic rice disrupts Os2AP and results in the formation of 2AP through the accumulation of 4-aminobutanal (Fig. 4B). This metabolic disorder in polyamine catabolism can be considered to improve rice quality. The product of the AMADH reaction, GABA, is accumulated in plants under stress conditions such as drought, cold, and salinity (Aurisano et al., 1995; Kinnersley and Turano, 2000). The accumulation pathway, consisting of glutamate decarboxylase (EC 4.1.1.15), GABA transaminase (EC 2.6.1.19), and succinate semialdehyde dehydrogenase (EC 1.2.1.16 or 24), is known as the GABA shunt (Fig. 4B), and it bypasses two steps of the TCA cycle. The accumulation of GABA through the GABA shunt is predominant; however, Turano et al. (1997) reported significant GABA flux from putrescine through AMADH. Since rice AMADH did not accept betaine aldehyde as its substrate in the native state, aromatic rice varieties under stressed conditions could enhance their polyamine content, resulting in a higher 2AP content. Yoshihashi et al. (2004) analyzed the 2AP content of various aromatic rice samples from Thailand and found that samples from irrigated areas had a lower 2AP content than those from drought-stricken and rain-fed areas. The Os2AP disruption and the
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‘‘aromatic’’ phenotype could be a genetic predisposition, but the formation of 2AP as a phenotype could also be regulated by environmental conditions. The genetic difference in Os2AP may be beneficial for breeding new aromatic rice varieties. However, detailed studies on environmental conditions, especially on stress conditions with potential effects on GABA formation through AMADH, are needed to improve the quality of aromatic rice from paddy fields.
VI. GENETIC DIVERSITY AND ORIGIN OF THE AROMATIC GENE A. GENETIC DIVERSITY OF THE AROMATIC RICE
Traditional aromatic rice varieties are classified into three isozyme groups, namely Group I (indica), Group V (indica), and Group VI (tropical japonica) (Glaszmann, 1987). The aromatic cultivars belonging to Group I are Jasmine and include several cultivars from Thailand, Cambodia, Vietnam, and Southern China; those in Group V are Basmati and comprise several cultivars from India, Myanmar, Iran, Pakistan, Afghanistan, Bangladesh, and China; and those in Group VI are Azucena and encompass several cultivars from Indonesia and the Philippines (Khush, 2000). To investigate the allelic variation among these diverse aromatic germplasms, 478 aromatic rice varieties were assessed for variation in the 8-bp deletion in exon 7 and grain 2AP content (Fitzgerald et al., 2008). The majority of the aromatic lines contained the 8-bp deletion, with approximately 10% of aromatic varieties accumulating significant amounts of 2AP containing no 8-bp deletion (Fitzgerald et al., 2008). The possibility that the other loci control 2AP accumulation was reported in two QTL mapping experiments (Amarawathi et al., 2008; Lorieux et al., 1996). The most likely location of the second QTL was reported on chromosome 4 but showed a much smaller effect. Data mining into the QTL ch4 localized the Os2AP ortholog, BADH, within the region (Lorieux et al., 1996). Additional small QTLs were found on chromosomes 3 (Amarawathi et al., 2008) and 12 (Lorieux et al., 1996). So far, no genetic validation has been reported for the existence and roles of these smaller QTLs in the biosynthesis and accumulation of 2AP. The discovery of other naturally occurring mutations in Os2AP has also been explored recently.
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B. NATURALLY OCCURRING ALLELIC VARIATION OF THE AROMATIC GENE
To explore allelic variation in Os2AP, a large collection of aromatic and nonaromatic rice with distinct geographic and genetic origins was analyzed for Single Nucleotide Polymorphism (SNP) variation within the Os2AP region (55 SNP) and across 5.3 Mb (78 SNP) of the flanking region (Kovach et al., 2009). The diverse germplasm pool consisted of 280 accessions of Oryza rufipogon, 242 cultivated accessions collected from 38 countries, and 26 aromatic accessions lacking the 8-bp deletion (Fitzgerald et al., 2008). Based on gene-specific SNP variations, the rice germplasm was classified into 10 haplotypes, where the badh 2.1 haplotype and the 8-bp delection in exon 7 were the most common aromatic haplotype (Kovach et al., 2009). The less frequent haplotype groups consisted of exon 14 insertions (badh 2.7) and exon 13 SNP (badh 2.8) and associated with the highest 2AP content. Four out of eight mutations were predicted to cause truncated Os2AP transcripts and abolish protein functionality (Kovach et al., 2009). Interestingly, three other mutations in found in rice from Bangladesh (Group I) and Myanmar (Group V) resulted in one amino acid addition (Kovach et al., 2009). Despite several reports of mutations in Os2AP, two other rice varieties exhibiting elevated 2AP levels lacked any known non-functional allele. In addition, SNP haplotypes were found in BADH gene and it seems to be associated with quantitative variation of 2AP content (Singh et al., 2010). Until the new gene is found, Os2AP remains the only known major regulator of 2AP in aromatic rice. C. ORIGIN OF THE AROMATIC GENE
More aromatic alleles were found in Group V than in any other rice variety, indicating that aromatic rice may originate from Group V and might have been transmitted to other indica varieties via cross-hybridization. Identifying the donor of the aromatic gene to traditional aromatic rice would be very interesting. (The presence of MITE at position 51 was associated with fragrant japonicas and indicas; Bourgis et al., 2008.) D. ANCESTORS OF THE AROMATIC GENE
Annual wild rice species such as O. rufipogon, Oryza nivara, and Oryza spontaneous are believed to be the ancestors of cultivated rice. It may be that aromatic gene can be transmitted to cultivated rice. If it is true that these are the ancestors and that the aromatic gene came from this source In that case, aromatic wild species must be found in natural habitats. Eleven wild
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rice species sampled from a germplasm bank were analyzed for the 8-bp deletion in Os2AP. The aromatic wild species were first identified in our laboratory using the 8-bp functional marker for screening (Vutiyano, 2009). However, the aromatic marker allele was found in only two wild species, O. rufipogon and O. nivara. Moreover, the 8-bp aromatic allele was also identified at a low frequency (0.23) in 229 natural wild rice accessions, of O. rufipogon, collected in Thailand (Prathepha, 2008). From the latter study, the author concluded that the aromatic allele already existed in wild rice. However, in 280 accessions of the wild rice species O. rufipogon and O. nivara, the 8-bp deletion was mostly absent, but one sample was heterozygous (Kovach et al., 2009). Because the heterozygous wild rice exhibited several characteristics of cultivated species, the author concluded that the aromatic allele did not originate from the wild species themselves but from a recent introgression of the aromatic allele from cultivated rice. The authors concluded that the aromatic gene was first domesticated within japonica-type cultivars before it was transmitted through indica-type cultivars; this was in line with their SNP diversity survey over the 5.8 kb across the Os2AP. To test this hypothesis, several hundred aromatic rice varieties from the Southeastern Asia Greater Mekong Subregion including Myanmar, Thailand, Cambodia, and Laos were collected.
E. EVOLUTIONARY RELATIONSHIP AMONG PLANT BADH/AMADH FAMILY
Rice is not the only plant producing 2AP. Pandan, breadflower, soybean, coconut, etc., are among well-known aromatic plants. Identification of aromatic gene in rice emerged as a new tool to create desirable aromatic plants. Phylogenic relationship among orthologous sequences related to Os2AP (AMADH) and BADH plants was recently reported (Arikit et al., 2010). Os2AP/BADH homologous sequences retrieved from several dicots, monocots, and non-flowering plant genomes were analyzed and shown in Fig. 5. Two distinct clades, the monocot and dicot, were clearly defined in flowering plant genomes (Fig. 5). Within the monocot clade, two orthologous subgroups were distinctively defined as Os2AP-like or BADH-like sequences. For most of the dicot clade, two distinct paralogous subgroups were defined after speciation. These results suggested a gene duplication event in the monocot. Analysis of NAD-dependent aldehyde dehydrogenase protein domain, an aldehyde dehydrogenase cysteine active site, revealed two major groups according to two concensus domains (Fig. 6).
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Monocot BADH-like
Monocot Os2AP-like
Dicot AMADH
Fig. 5. BADH gene family was analyzed following a phylogenomic approach. A set of protein sequences homologous to rice Os2AP was obtained by FlowerPower tool (http://phylogenomics.berkeley.edu/cgi-bin/flowerpower/input_flowerpower.py) using Uniprot proteins as database (http://www.pir.uniprot.org). The homologous proteins were aligned following multiple sequence alignments using MUSCLE program (http://phylogenomics.berkeley.edu/muscle/). A phylogenetic tree was constructed according to the multiple sequence alignments by using SCI-PHY tool (http://phylogenomics.berkeley.edu/cgi-bin/SCI-PHY/input_SCI-PHY.py). Protein domains of these homologous proteins were predicted by Prosite program (http:// au.expasy.org/prosite/). Sequences of rice BADH (SwissProt O24174), Os2AP (SwissProt Q84LK3) and E. coli (SwissProt P77674) were used. The BLAST 2 (BLOSUM 62 matrix) search engine was used to create sequence alignments, whereas Clustal W1.83 enabled the alignment of multiple sequences.
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A Rice BADH
E. coli BADH
Rice AMADH/Os2AP
B BADH (rice) Q6BD95 (Zoysia tenuifolia) Q6BD93 (turf grass) Q94IC0 (barley) BADH (barley) Q5KSN8 (leymus) Q43829 (Sorghum)
FaNAGQVCSATS FaNGGQVCSATS FaNGGQVCSATS FfNGGQVCSATS FfNGGQVCSATS FfNGGQVCSATS LpNAGQVCSAAS
Os2AP (rice) BADH (spinach) Q6BD3 (turf grass) Q6BD88 (turf grass) Q94IC1 (barley) Q53CF4 (maize) Q6BD99 (zoysia tenuifolia) Q8LGQ9 (wheat) Q4H1G7 (sugar beet) BADH (sugar beet) O9STS1 (Arabidopsis)
FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS FwTNGQICSATS
[FYLVA] . x . {GVEP} . {DILV} . G . [QE] . {LPYG} . C . [LIVMGSTANC] . [AGCN] . {HE} . [GSTADNEKR]
Fig. 6. Homology modelling of the BADH and Os2AP protein structure and comparison of structures. The three-dimensional structure of the rice BADH enzyme and Os2AP enzyme were modelled by comparative protein modelling methods using the program SWISS-MODEL in the optimized mode. The structure of the enzyme was modelled on the basis of its structural similarity with the E. coli BADH (Protein Data Bank entry 1WNB). The degree of identity between the template and the E. coli BADH sequence were 37.23% and 38.65%, respectively, which enabled a preliminary model to be generated by SWISS-MODEL. The sequence alignment was then improved manually; Swiss-PdbViewer 3.7 was used to produce a structure-based alignment and SWISS-MODEL was used in the optimized mode to minimize energy. The final model was evaluated with PROCHECK, and Swiss-PdbViewer 3.7 was then used to analyze and visualize the structures.
F. DEFICIENCY IN AMADH MAKES AROMATIC PLANTS
As a result of high homology in the protein sequences, it is possible that all 2AP accumulators may utilize similar mechanism as rice. To prove the concept, natural aromatic soybean was used as a case study. Several aromatic soybeans such as Yuagari musume and Kaori hime accumulated seed 2AP in a range of 300–500 ppb. In aromatic soybean, loss of GmAMADH2 activity was detected in maturing seeds (Arikit et al., 2010). This suggested that
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similar suppressive mechanism is similar to rice. The GmAMADH2-RNAi was transformed into two non-aromatic soybean varieties, CM60 and Jack. The result showed that the expression of GmAMADH1 was not affected by GmAMADH2-RNAi. Contents of 2AP in CM60-RNAi and Jack-RNAi were detected in a range of 324–350 ppb. In conclusion, it is possible to generate aromatic plant varieties by suppressing seed-specific Os2AP-like gene (Fig. 5).
VII. ENVIRONMENTAL ADAPTABILITY OF AROMATIC RICE Most types of aromatic rice, such as Jasmine, Basmati, and Azucena, are landrace varieties. Breeding high-yielding aromatic rice has been attempted in many countries, but with little success. So far, the high-yielding aromatic rice cultivars developed have shown less intensity of the aromatic compound 2AP than the traditional ones. Is aromatic rice less productive than nonaromatic rice? In light of the biosynthesis of 2AP (Fig. 2), 2AP is the end product of the polyamine pathway in aromatic rice. In non-aromatic rice, -aminobutyraldehyde is converted to GABA and subsequently back to the TCA cycle via succinate. Considering the loss of two nitrogen atoms from a molecule of -aminoaldehyde for the biosynthesis of one molecule of 2AP, aromatic rice seems plausibly less productive than non-aromatic rice, especially under stress conditions. To investigate the latter phenomenon, RNAi and wild-type rice were compared for traits related to productivity (Niu et al., 2008). The results showed reduction of plant height, 1000-grain weight, and overall productivity in aromatic RNAi rice compared to the wild type. Under high-salinity conditions, seedling growth rates were more severely affected by different salt concentrations compared to the wild type. However, the germination of aromatic rice seedlings was unaffected by various salt-stressed conditions. To further investigate salt sensitivity, several aromatic and non-aromatic cultivars were compared for productivity when grown under 22-mM salt solution from 11 weeks post-planting (Fitzgerald et al., 2010). The seed set was severely affected by such salinity conditions in aromatic rice. The authors concluded that Os2AP plays important roles in resistance to salt stresses. However, under salt stress conditions, the ratio of BADH to Os2AP transcripts was high, suggesting that BADH, and not Os2AP, was responsible for salt responses from a molecule of -aminoaldehyde (Fitzgerald et al., 2008). At this end, it is a beginning of new chapters for understanding functional roles of aromatic gene.
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Fitzgerald, M. A., Hamilton, N. R. S., Calingacion, M. N., Verhoeven, H. A. and Butardo, V. M. (2008). Is there a second fragrance gene in rice? Plant Biotechnology Journal 6, 416–423. Fitzgerald, T. L., Waters, D. L. E., Brooks, L. O. and Henry, R. J. (2010). Fragrance in rice (Oryza sativa) is associated with reduced yield under salt treatment. Environmental and Experimental Botany 68(3), 292–300. Glaszmann, J. C. (1987). Isozymes and classification of rice varieties. Theoretical and Applied Genetics 74, 21–30. Goufo, P., Wongpornchai, S. and Tang, X. (2010). Decrease in rice aroma after application of growth regulators. Agronomy for Sustainable Development doi:10.1051/agro/2010011. Grimm, C. C., Bergman, C., Delgado, J. and Bryant, R. (2001). Screening for 2-acetyl-1-pyrroline in the headspace of rice using SPME/GC-MS. Journal of Agricultural and Food Chemistry 49, 245–249. Hein, N. L., Yoshihashi, T., Sarhadi, W. A. and Hirata, Y. (2006). Sensory test for aroma and quantitative analysis of 2-acetyl-1-pyrroline in Asian aromatic rice varieties. Plant Production Science 9(3), 294–297. Hibino, T., Meng, Y., Kawamitsu, Y., Uehara, N., Matsuda, N., Tanaka, Y., Ishikawa, H., Baba, S., Takabe, T., Wada, K., Ishii, T. and Takabe, T. (2001). Molecular cloning and functional characterization of two kinds of betaine aldehyde dehydrogenase in betaine accumulating mangrove Avicennia marina (Forsk.) Vierh. Plant Molecular Biology 45, 353–363. Hofmann, T. and Schieberle, P. (1998). 2-Oxopropanal, hydroxy-2-propanone, and 1-pyrrolines important intermediates in the generation of the roast- smelling food flavor compounds 2-acetyl-1-pyrroline and 2-acetyltetrahydropyridine. Journal of Agricultural and Food Chemistry 46, 2270–2277. Huang, N., McCouch, S. R., Mew, T., Parco, A. and Guiderdoni, E. (1994). A rapid technique for scent determination in rice. Rice Genetics Newsletter 11, 134–137. Huang, T. C., Teng, C. S., Chang, J. L., Chuang, H. S., Ho, C. T. and Wu, M. L. (2008). Biosynthetic mechanism of 2-acetyl-1-pyrroline and its relationship with 1-pyrroline-5-carboxylic acid and methylglyoxal in aromatic rice (Oryza sativa L.) callus. Journal of Agricultural and Food Chemistry 56, 7399–7404. Itani, T., Tamaki, M., Hayata, Y., Fushimi, T. and Hashizume, K. (2004). Variation of 2-acetyl-1-pyrroline concentration in aromatic rice grains collected in the same region in Japan and factors affecting its concentration. Plant Production Science 7(2), 178–183. Jodon, N. E. (1944). The inheritance of flower fragrance and other character in rice. Journal of American Society Agronomy 27, 910–921. Kadam, B. S. and Patankar, V. K. (1938). Inheritance of aroma in rice. Indian Journal of Genetics and Breeding 40, 327–329. Khush, G. S. (2000). Taxonomy and origin of rice. In Aromatic Rices, (R. K. Singh, U. S. Singh and G. H. Khush, eds.), pp. 5–13. Oxford and IBH Publishing Co. Pvt. Ltd, New Delhi, Calcutta. Kinnersley, A. M. and Turano, F. J. (2000). Gamma aminobutyric acid (GABA) and plant responses to stress. Critical Reviews in Plant Sciences 19, 479–509. Kovach, M. J., Calingacion, M. N., Fitzgerald, M. A. and McCouch, S. R. (2009). The origin and evolution of fragrance in rice (Oryza sativa L.). PNAS 106 (34), 14444–14449. Lanceras, J. C., Huang, Z. L., Naivikul, O., Vanavichit, A., Ruanjaichon, V. and Tragoonrung, S. (2000). Mapping of genes for cooking and eating qualities in Thai jasmine rice (KDML 105). DNA Research 7, 93–101.
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Lorieux, M., Petrov, M., Huang, N., Guiderdoni, E. and Ghesquiere, A. (1996). Aroma in rice: Genetic analysis of a quantitative trait. Theoretical and Applied Genetics 93, 1145–1151. Fushimi, T. and Masuda, R. (2001). 2-acetyl-1-pyrroline concentration of the aromatic vegetable soybean ‘‘Dadacha-mame’’. In Proceedings of the Second International Vegetable Soybean Conference, (T. A. Lumpkin and S. Shanmugasundaram, eds.). Washington State University, Pullman, Washington, USAp. 39. Maga, J. A. (1984). Rice product volatile: A review. Journal of Agricultural and Food Chemistry 32, 924–970. Nagaraju, M., Choudhary, D. and Balakrishna Rao, M. J. (1975). A simple technique to identify scent in rice and inheritance pattern of scent. Current Science 44, 599. Nagsuk, A., Winichphol, N. and Rungsarthong, V. (2003). Identification of 2-acetyl1-pyrroline, the principal aromatic rice flavor compound, in fungus cultures. In Proceedings of the 2nd International Conference on Medicinal Mushrooms & International Conference on Biodiversity and Bioactive Compounds, pp. 395–400. Pattaya Exhibition Center, Cholburi, Thailand. Niu, X., Tang, W., Huang, W., Ren, G., Wang, Q., Luo, D., Xiao, Y., Yang, S., Wang, F., Lu, B.-R., Gao, F., Lu, T. and Liu, Y. (2008). RNAi- directed downregulation of OsBADH2 results in aroma (2-acetyl-1-pyrroline) production in rice (Oryza sativa L.). BMC Plant Biology 8, 100. Paule, C. M. and Powers, J. J. (1989). Sensory and chemical examination of aromatic and nonaromatic rices. Journal of Food Science 54, 343–346. Prathepha, P. (2009). The fragrance (fgr) gene in natural populations of wild rice (Oryza rufipogon Griff.). Genetic Resources and Crop Evolution 56, 13–18. Reddy, P. R. and Sathyanarayanaiah, K. (1980). Inheritance of aroma in rice. Indian Journal of Plant Breeding 40, 327. Romanczyk, J. R. L. J., McClelland, C. A., Post, L. S. and Aitken, W. M. (1995). Formation of 2-acetyl-1-pyrroline by several Bacillus cereus strains isolated from cocao fermentation boxes. Journal of Agricultural and Food Chemistry 43(2), 469–475. Schieberle, P. (1991). Primary odorants in popcorn. Journal of Agricultural and Food Chemistry 39(6), 1141–1144. Schieberle, P. (1995). Quantitation of important roast-smelling odorants in popcorn by stable-isotope dilution assays and model studies on flavor formation during popping. Journal of Agricultural and Food Chemistry 50, 2442–2448. Sebela, M., Brauner, F., Radova, A., Jacobsen, S., Havlis, J., Galuszka, P. and Pec, P. (2000). Characterisation of homogeneous plant aminoaldehyde dehydrogenase. Biochimica et Biophysica Acta 1480, 329–341. Seitz, L. M., Wright, R. L., Waniska, R. D. and Rooney, L. W. (1993). Contribution of 2-acetyl-1-pyrroline to odors from wetted ground pearl millet. Journal of Agricultural and Food Chemistry 41(6), 955–958. Shi, W., Yang, Y., Chen, S. and Xu, M. (2008). Discovery of a new fragrance allele and the development of functional markers for the breeding of fragrant rice varieties. Molecular Breeding 22, 185–192. Singh, A., Singh, P. K., Singh, R., Pandit, A., Mahato, A. K., Gupta, D. K., Tyagi, K., Singh, A. K., Singh, N. K. and Sharma, T. R. (2010). SNP haplotypes of the BADH1 gene and their association with aroma in rice (Oryza sativa L.). Molecular Breeding 26, 325–338. Sood, B. G. and Siddiq, E. A. (1978). A rapid technique for scent determination in rice. Indian Journal of Genetics and Plant Breeding 38, 268–271.
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Tragoonrung, S., Sheng, J. Q. and Vanavichit, A. (1996). Tagging an aromatic gene in lowland rice using bulk segregant analysis. Rice Genetics III, IRRI, pp. 613–618. Trossat, C., Rathinasabapathi, B. and Hanson, A. D. (1997). Transgenically expressed betaine aldehyde dehydrogenase efficiently catalyzes oxidation of dimethylsulfoniopropionaldehyde and !-aminoaldehydes. Plant Physiology 113, 1457–1461. Tsugita, T., Kurata, T. and Kato, H. (1980). Volatile components after cooking rice milled to different degrees. Agricultural and Biological Chemistry 44, 835–840. Turano, F. J., Thakkar, S. S., Fang, T. and Weisemann, J. M. (1997). Characterization and expression of NAD(H)-dependent glutamate dehydrogenase genes in Arabidopsis. Plant Physiology 113, 1329–1341. Vanavichit, A., Kamolsukyurnyong, W., Wanchana, S., Wongpornchai, S., Ruengphayak, S., Toojinda, T. and Tragoonrung, S. (2004). Discovering genes for rice grain aroma. In Proceedings of the 1st International Conference on Rice for the Future, 31 August–3 September, 2004, pp. 71–80. Kasetsart University, Bangkok, Thailand. Vanavichit, A., Tragoonrung, S., Theerayut, T., Wanchana, S., Kamolsukyunyong, W. (2005). Transgenic rice plants with reduced expression of Os2AP and elevated levels of 2-acetyl-1-pyrroline. United States Patent, Patent No. US 7,319,181 B2 Vutiyano, C. (2009). Identification of wild species carrying aromatic allele in rice (Oryza spp.) Kasetsat University, Thailand: Ph.D. Thesis in Philosophy (Tropical Agriculture). Wanchana, S., Kamolsukyunyong, W., Ruengphayak, S., Toojinda, T., Tragoonrung, S. and Vanavichit, A. (2005). A rapid construction of a physical contig across a 4.5 cM region for rice grain aroma facilitates marker enrichment for positional cloning. Science Asia 31, 299–306. Wongpornchai, S., Sriseadka, T. and Choonvisase, S. (2003). Identification and quantitation of the rice aroma compound, 2-acetyl-1-pyrroline, in bread flowers (Vallaris glabra Ktze). Journal of Agricultural and Food Chemistry 51, 457–462. Yajima, I., Yanai, T. and Nakamura, M. (1978). Volatile flavor components of cooked rice. Agricultural and Biological Chemistry 42, 1229. Yoshihashi, T. (2002). Quantitative analysis on 2-acetyl-1-pyrroline of aromatic rice by stable isotope dilution method and model studies on its formation during cooking. Journal of Food Science 67(2), 619–622. Yoshihashi, T., Nguyen, H. T. T. and Inatomi, H. (2002). Precursors of 2-acetyl-1pyrroline, a potent flavor compound of an aromatic rice variety. Journal of Agricultural and Food Chemistry 50, 2001–2004. Yoshihashi, T., Nguyen, H. T. T. and Kabaki, N. (2004). Area dependency of 2-acetyl-1-pyrroline content in an aromatic rice variety, Khao Dawk Mali 105. Japan Agricultural Research Quarterly 38, 105–109.
Miscanthus: A Promising Biomass Crop
EMILY A. HEATON,*,1 FRANK G. DOHLEMAN,{,2 A. FERNANDO MIGUEZ,* JOHN A. JUVIK,{ VERA LOZOVAYA,{ JACK WIDHOLM,{ OLGA A. ZABOTINA,} GREGORY F. MCISAAC,k MARK B. DAVID,k THOMAS B. VOIGT,{ NICHOLAS N. BOERSMA* AND STEPHEN P. LONG{
*Department of Agronomy, Iowa State University, Ames, IA, USA { Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA { Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA } Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, USA k Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. A Role for Biomass Crops .................................................... B. Food Versus Fuel and the Case for High-Yielding Crops ............... C. A Role for Miscanthus Giganteus ......................................... D. Structure of this Review ....................................................... II. Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. European and US Trials....................................................... B. Crop Modelling .................................................................
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Corresponding author. E-mail:
[email protected] Current address: Monsanto Company, St. Louis, MO, USA.
2
Advances in Botanical Research, Vol. 56 Copyright 2010, Elsevier Ltd. All rights reserved.
0065-2296/10 $35.00 DOI: 10.1016/S0065-2296(10)56003-8
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III. Physiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Physiological Basis for M. Giganteus Productivity ..................... B. Nutrient Cycling in M. Giganteus ......................................... IV. Breeding, Genomics and Genetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Taxonomy and Origins ........................................................ B. Miscanthus Species Genetic Improvement .................................. C. Breeding.......................................................................... D. Genomics ........................................................................ E. Micropropagation, Genetic Engineering and Chromosome Doubling ..................................................... V. Environmental Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Water ............................................................................. B. Nitrate Leaching................................................................ C. Summary and Implications for Research Needs........................... VI. Technical Challenges to Commercial Production. . . . . . . . . . . . . . . . . . . . . . . . . . . A. Propagation, Rhizome Storage and Establishment ....................... B. Agronomy ....................................................................... C. New Varieties ................................................................... Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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ABSTRACT The C4 grass Miscanthus giganteus is of increasing interest as a biomass feedstock for renewable fuel production. This review describes what is known to date on M. giganteus from extensive research in Europe and more recently in the US. Research trials have shown that M. giganteus productivity is among the highest recorded within temperate climates. The crop’s high productivity results from greater levels of seasonal carbon fixation than other C4 crops during the growing season. Genetic sequencing of M. giganteus has identified close homology with related crop species such as sorghum (Sorghum bicolor (L.) Moench) and sugarcane (Saccharum officinarum L.), and breeding of new varieties is underway. Miscanthus giganteus has high water use efficiency; however, its exceptional productivity causes higher water use than other arable crops, potentially causing changes in hydrology in agricultural areas. Nitrogen use patterns are inconsistent and may indicate association with N fixing microorganisms. Miscanthus giganteus has great promise as an economically and ecologically viable biomass crop; however, there are still challenges to widespread commercial development.
I. INTRODUCTION A. A ROLE FOR BIOMASS CROPS
Increasing the share of world energy that comes from renewable sources is critical to stabilizing the global climate (IPCC, 2007). Among renewable energy sources, only biomass can provide fuel and electricity in a form and scale that is compatible with existing transportation and power generation infrastructure (DOE, 2006). Unlike wind and solar energy, biomass can be converted directly
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into liquid fuel by a variety of conversion routes, as is current practice with petroleum, or it can be stored to generate electricity on-demand, as is the current practice with coal. It also provides raw material for renewable alternatives to fossil-based products. Biomass is also the only available source of renewable carbon for products currently made from fossil carbon sources. How much biomass is needed? Of the 105 exajoules (EJ, 1018 J) of energy consumed in the US in 2008, only 4% or 4.1 EJ came from biomass sources, mainly from combustion of wood residues for heat and power by paper manufacturers (DOE, 2009). Energy consumption is expected to increase by 14% by 2034, to 120.8 EJ (DOE, 2010). Multiple acts of legislation currently under consideration in the US could further increase renewable energy demand 10–40%, leading it to comprise 14% of the total US energy demand, or 17 EJ y 1, by 2035 (DOE, 2010). Over 900 million Mg of biomass per year is needed to produce 17 EJ y 1, assuming biomass to contain 18 MJ kg 1 (Jenkins et al., 1998) and energy conversion to be 100% efficient. Of course, conversion of biomass energy into useful forms like liquid fuels or electricity is not 100% efficient, and typical efficiencies range between 30% and 70%, depending on methods and accounting (Brown, 2003; Jenkins et al., 1998; Mohan et al., 2006). Assuming an average conversion efficiency of 50%, the US will require more than 1.8 billion Mg of biomass per year to meet renewable energy demands through bioenergy, or a little more than 50% of the entire US maize crop in 2009 (NASS, 2010). Even if only a portion of US renewable energy comes from biomass, it will still have a major impact on cultivated and natural lands. The feasibility and impact of large-scale biomass production have been intensely debated and investigated in recent years (Dohleman et al., 2010; Dornburg et al., 2010; Fargione et al., 2008; Hertel et al., 2010; Hill et al., 2009; Kim et al., 2009; Levasseur et al., 2010; Reijnders, 2010; Smeets and Faaij, 2010; Solomon, 2010; Taheripour et al., 2010). Despite a wide range of conclusions, it is generally agreed that (1) resources are limited and (2) future agricultural systems must be sustainable. B. FOOD VERSUS FUEL AND THE CASE FOR HIGH-YIELDING CROPS
It is reasonable to propose that crops that produce high biomass yields per unit land area be used to meet bioenergy demand, since they will require less land than low-yielding crops, and this is a key principle of biomass crop development (Heaton et al., 2008b). For example, the high-yielding perennial Miscanthus giganteus could require 87% less land to produce the same amount of biomass as a low-input, high-diversity mixture of prairie species,
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because the yield of the M. giganteus monoculture is nearly eightfold greater (Heaton et al., 2008a). However, while yield might be a driving selection criterion, it is not the only one, and future crop systems must be evaluated on their environmental and social functions, in addition to traditionally valued economic functions (Boody et al., 2005; Schulte et al., 2006). Diverse cropping systems that fill all available environmental niches can provide more ecosystem services such as nutrient cycling, water retention and filtration and biodiversity than annual monocultures, but they are inherently more difficult to manage for biomass production because each species prefers different conditions in a given year (Russelle et al., 2007; Tilman et al., 2006). High-yielding perennials that are on the field for most of the year can offer a compromise by simplifying crop management over diverse mixtures while still providing ecosystem services (Heaton et al., 2004b; Schmer et al., 2008). 1. Sustainability ‘Sustainable’ has many definitions, most of them contentious with reference to agriculture. A useful metaphor to discuss sustainability is the ‘sustainability stool’. The legs of the stool are environmental, economic and social sustainability; if an agricultural system has inadequate performance in any of the three areas, the system will eventually collapse (Douglass, 1984). Perennial energy crops potentially can provide a solid foundation for sustainability with performance that is equal to or improved over that of annual arable crops. a. Economic sustainability. Of the three legs of the sustainability stool, economic sustainability of agriculture receives the most attention. Globally, there has been a trend away from diverse crop rotation to simplified annual crop systems that has been accompanied by increases in yield and farm labour productivity, made possible through increased reliance on synthetic fertilizer, pesticides and subsidy payments for crops in surplus (Bullock, 1992; Malezieux et al., 2009; Schulte et al., 2006; Tegtmeier and Duffy, 2004). Beginning with the Soil Conservation Act of 1935, the US government has, like many developed countries, paid farmers to set aside land from arable cropping, and instead plant it to perennials as a soil conservation tool. As demand grows for highly productive land to produce food, feed, fibre and now fuel, however, the value of these government programmes fades in comparison to what a farmer can earn by producing a subsidy-protected grain crop. Traditionally, it has been difficult and nebulous to value the ecosystem services provided by perennial agriculture (Farber et al., 2002; Liu et al., 2010; Porter et al., 2009), and without a harvested product for sale,
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perennials usually lose against annual crops in the marketplace. With the advent of a clear demand for energy from perennial biomass, farmers and conservationists may have their cake and eat it too, as the crops grown can be harvested and sold for a profit while still providing ecosystem services similar to those from set-aside land. How does the economic return of biomass crops compare to that of traditional arable crops in the US? James et al. (2010) calculated the breakeven price for a farmer in the Midwestern US to switch to a range of perennial energy crops and found that currently, none was economically viable against continuous maize production on highly fertile land. However, they evaluated M. giganteus using current prices for rhizomes ($1.80 ea) and a future price anticipating improved production practices ($0.05 ea) and found that of all the crops evaluated, future M. giganteus is more profitable than continuous maize, with a break-even price of only $45 Mg 1 (James et al., 2010). In on-farm trials with co-operators in Nebraska, South Dakota and North Dakota, Perrin et al. (2008) found that switchgrass could be grown at a commercial scale for about $50 Mg 1. By comparison, the costs for continuous maize production on prime farmland in Iowa are about $150 Mg 1 in 2010 (Duffy, 2010), suggesting that perennial crops are profitable and will be economically sustainable even on prime farmland in the US. b. Environmental sustainability. Perennial plants have long been associated with good environmental performance and improved ecosystem health. Without the disturbance of annual soil tillage above- and below-ground biomass accumulates, perennials protect and hold the soil against wind and water erosion while increasing soil quality and organic matter (BlancoCanqui, 2010; Luo et al., 2010). An increased proportion of perennials in the landscape are also associated with an increase in biodiversity, as perennials provide habitat for animals and insects (Malezieux et al., 2009; Schulte et al., 2006). Additionally, perennial crops can increase the quantity and diversity of mineral nutrients available in the rhizosphere by establishing complex and often long-term relationships with the microbial community (Davis et al., 2010; Nehls et al., 2010). The larger and active root system of perennial grasses is particularly effective at scavenging available nutrients and preventing them from leaching with draining water where they may act as pollutants (Allan, 2004; Randall et al., 1997). In the US Environmental Protection Agency’s recent Science Advisory Board report on hypoxia in the Gulf of Mexico, the high losses of nitrate from current corn–soybean production systems on tile-drained landscapes in the Mississippi River Basin were clearly identified as a major source of the nutrients causing hypoxia (EPA, 2008). These losses occurred even
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when best management practices were applied. In that report, it was suggested that perennials were the best option to substantially reduce nitrate losses, but such a shift was unlikely, given current agricultural policies. In a more specific example of how nitrate losses from current production systems could be reduced using perennials, Hatfield et al. (2009) evaluated a watershed in central Iowa. They observed that mean annual NO3–N concentrations in water have been increasing since 1970 in spite of no significant change in N fertilizer use for the past 15 years, and a decrease in cattle and hog production in the watershed. Upon evaluation of regional crop yields, land-use change and precipitation, they found that an increase in land planted to maize and soybean, at the expense of perennial pasture, were highly correlated with the increase in NO3–N concentrations. The authors concluded that the narrow window of nutrient uptake in maize–soy systems allowed more nutrients to leave the system, even though the amount of fertilizer applied was steady and crop yields were increasing. One suggested solution to reduce nutrient loading in the watershed was to plant more perennials with water use patterns that complement those of maize–soy (Hatfield et al., 2009). c. Social sustainability. Biomass energy may help revitalize languishing rural economies (Solomon, 2010). Even as industrial agriculture has delivered record crop yields and gross revenue in the past 50 years, farmer employment and profit have deteriorated (Fig. 1). The US Department of Agriculture (USDA) reports that a rural society that used to be characterized by small farms supported by farm sales has changed to large, concentrated farms, and over 40% of documented farms are in the ‘residential/lifestyle’ category. While the majority of US farms are still small farms, over 50% of their operators are retired or rely on another job as their principal occupation (NASS, 2007). Conversely, large farms, that is, those with revenue over $100,000 per year, comprise only 15% of all US farms, yet account for 88% of sales. In short, only a fraction of farmers can still make a living from farming (Duffy, 2008), and this is reflected in the steady decline of rural populations (US Census Bureau, 1990). Job creation in the renewable energy economy supports the social sustainability of biomass cropping systems. A review of clean energy finance by the Pew Charitable Trust found global investment up by 230% since 2005, despite the largest economic downturn in at least 50 years, and clean energy investments are expected to grow to $200 billion by 2010 (The Pew Charitable Trusts, 2010). ‘Green jobs’ have been touted as the solution to the economic and environmental woes of many countries, and have received priority in economic recovery spending. Despite inconsistent government
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400 Total production expenses Value of agricultural sector production Net farm income Direct government payments
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Fig. 1. The value of U.S. agricultural production, total production expenses, net farm income and direct payments from the government, that is, subsidies, from 1949 through 2008 (USDA/ERS, 2010).
support, there are already more green jobs than biotechnology-related jobs, though biotech has seen steady government support (Fig. 2) (The Pew Charitable Trusts, 2009). The low bulk density of biomass makes it inherently inefficient to transport (Fales et al., 2007; Rentizelas et al., 2009; Shinners and Binversie, 2007), necessitating local processing and handling, thus ensuring distributed jobs within regions irrespective of the fuel produced. In an analysis of case studies in Brazil and the Ukraine, Smeets and Faaij (2010) found that instilling a ‘strict’ set of sustainability criteria, for example, restriction of child labour, education of the workforce and mandatory healthcare, had positive community impacts with only a limited effect on the cost of bioenergy production from perennials. This was largely attributed to the reduced costs of perennial agriculture compared to annual row cropping systems. C. A ROLE FOR MISCANTHUS GIGANTEUS
1. Origins and uses Miscanthus is a genus comprising 14–20 species of perennial, C4 grasses native to eastern Asia, N. India and Africa (Clayton et al., 2008; Hodkinson et al., 2002a; Scally et al., 2001). As described in a review by
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Job sector
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Fig. 2. Number of U.S. jobs in biotechnology, clean energy and traditional energy industries in 2007 (Pew Charitable Trust, 2009).
Stewart et al. (2009), Miscanthus species have long been used for grazing and structural materials in China and Japan and have only recently become of interest for energy. Long recognized for their ornamental value, and as a germplasm source of stress tolerance in sugarcane breeding, Miscanthus species are now found and commonly naturalized in North and South America as well as in Europe, Africa, Asia and Europe (Clayton et al., 2008; Scally et al., 2001). In 1935, Aksel Olsen brought a sterile Miscanthus hybrid that was of horticultural interest back from Yokohama, Japan to Denmark, where it was cultivated by Karl Foerster and observed to have vigorous growth (Lewandowski et al., 2000; Linde-Laursen, 1993; Scally et al., 2001). Originally named Miscanthus sinensis ‘Giganteus’ hort. (Greef and Deuter, 1993), it has gone by many names, including M. giganteus, M. sinensis Anderss. ‘Giganteus’ and M. ogiformis Honda (Hodkinson et al., 2002c). By using DNA sequencing, AFLP and fluorescent in situ DNA hybridization, Hodkinson et al. (2002c) confirmed suspicions that it was an allotriploid (2n ¼ 3x ¼ 57) hybrid of M. sinensis and Miscanthus sacchariflorus and subsequently formally classified it with the Royal Botanic Gardens, Kew in the UK as M. giganteus (Greef & Deuter ex Hodkinson & Renvoize) (Hodkinson et al., 2002b). Following concern over fossil fuel dependence beginning in the 1970s, M. giganteus was evaluated along with several other species for potential as a bioenergy crop. The sterile clone from trials in Hornum, Denmark was
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spread across Europe, and included in both public and private trials (Jorgensen and Schwarz, 2000; Lewandowski et al., 2000). 2. Overview of Miscanthus research history Miscanthus giganteus has been studied across Europe since 1983 under a multitude of national and EU programmes (Jones and Walsh, 2001a; Lewandowski et al., 2000). Two EU-wide projects, the Miscanthus Productivity Network (MPN) and the European Miscanthus Improvement (EMI), have been particularly influential on the availability of Miscanthus data today (Fig. 3). In 1992, the 3-year MPN began as part of the European Agro-Industry Research programme (contract no. AIR1-CT92-0294). With 17 partners in 10 countries, the MPN aimed to ‘. . .generate information on the potential of Miscanthus as a non-food crop in Europe’, (Jones and Walsh, 2001b). Most trials used similar methods to assess potential productivity associated with water, nitrogen and low temperature limitation across different environments. Harvest, storage and utilization of biomass were also studied, along with genotype screening of other Miscanthus species. Generally, the MPN found M. giganteus to be broadly adapted to a wide range of growing
1935
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M. x giganteus evaluated in Hornum, Denmark
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EMI project UK EU funded tests 15 network genotypes Private EMN network at 5 sites sector 18 sites investment
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Activity = people x resources
M. x giganteus imported to Europe
German miscanthus biomass programme starts with Veba ÖI
First US field trial results in Illinois Field trials start Bical Ltd. across US starts in
2010 DEFRA funds breeding programme at IBERS, UK; BP funds Energy Biosciences Institute in Illinois and California
Fig. 3. Timeline of key activities in the investigation of Miscanthus as a biomass crop, adapted courtesy of J. Clifton-Brown.
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conditions, but was not the optimal choice in all locations tested (McCarthy, 1992). For a complete description of MPN results, see Jones and Walsh (2001a). Following on from the MPN, the EMI project began in 1997 to address the limitations imposed by a narrow genetic base within M. giganteus clones and better match genotypes with environments (Lewandowski and CliftonBrown, 1997). Similar in structure to the MPN, EMI focused on crop improvement by developing breeding methods and assessing the genotype environment interaction of 15 selected Miscanthus genotypes in five countries (Clifton-Brown et al., 2001a). The EMI project successfully identified genotypic variation in environmental performance among Miscanthus genotypes and has paved the way for current private and public breeding programmes in the US and Europe (Clifton-Brown et al., 2008). In contrast to Europe, Miscanthus species were not included in initial screening of potential biomass crops in the US. There, research, supported primarily by the US Department of Energy (DOE), focused on switchgrass (Panicum virgatum L.) as a model herbaceous species beginning in the 1980s (McLaughlin, 1992; Parrish and Fike, 2005; Sanderson et al., 1996). In fact, it was not until 2004 that Heaton et al. (2004b) used the model MISCANMOD, developed by Clifton-Brown et al. (2000) in Ireland, to project potential M. giganteus productivity in the US. Following promising modelled productivity, Heaton et al. (2004a)Heaton et al. went on to show that M. giganteus was likely to produce more biomass per unit input of water, nitrogen or heat, than would switchgrass under the same conditions, and thus field research in the US was warranted. Superior yield of M. giganteus over switchgrass was later confirmed in the first replicated trials of M. giganteus in the US, at three sites in Illinois where measured yields of M. giganteus were two- to fourfold higher than those of switchgrass, var. Cave-In-Rock (Heaton et al., 2008a). D. STRUCTURE OF THIS REVIEW
Following promising initial results, a Strategic Research Initiative (SRI) was initiated at the University of Illinois at Urbana-Champaign to further investigate M. giganteus in Illinois. Initial work by 14 investigators focused on a clone of M. giganteus collected by the Chicago Botanic Garden and brought to the Urbana, Illinois campus in 1988 where it had thrived in a demonstration planting (Heaton et al., 2008a). This review will highlight research areas addressed by the SRI through support from the Illinois Council on Food and Agriculture Research from 2004 to 2009 (award 04-SRI-036) (Long, 2005). Research in Illinois has expanded exponentially
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in recent years, and has been the provenance of work on Miscanthus in the US, which has grown from non-existence 10 years ago to being underway in nearly every state today. Focusing on M. giganteus, this review will address modelled and observed productivity (Section II), the physiological basis for that productivity (Section III), breeding and genetic engineering efforts (Section IV), the environmental impacts of production (Section V) and the technical challenges to commercial production (Section VI).
II. PRODUCTIVITY A. EUROPEAN AND US TRIALS
Here, we review the biomass production of M. giganteus reported from trials over a wide geographic range, with emphasis on how yield varies with precipitation, temperature and soil conditions. While other reviews of Miscanthus productivity and suitability can be a good source of data that might be otherwise difficult to find (Jones and Walsh, 2001a; Lewandowski et al., 2000; Miguez et al., 2008; Smeets et al., 2009; Zub and Brancourt-Hulmel, 2010), our goal here is to provide an overview of M. giganteus productivity, key factors that influence it and how it may be modelled and predicted. Productivity of M. giganteus has been tested in field trials across Europe since 1983 under a multitude of national and EU programmes (Lewandowski et al., 2003b). Only a portion of the numerous academic and industrial field trials that have been conducted is reported in English and published in easily accessed, peer-reviewed publications. Most studies cover a 2–5-year growth period, even though the lifetime of a M. giganteus stand can range from 15 to 30 years (Hastings et al., 2009a; Heaton et al., 2004b), and only a few studies have followed M. giganteus growth over a longer term, for example, 10 or more years (Christian et al., 2008; Clifton-Brown et al., 2007). Miscanthus giganteus is not typically harvested in the year, it is planted because of low yields and possible negative impacts on survival during the crop’s critical first winter. Generally, winter kill is only a problem in the first season; if a plant makes it through the first winter, it will nearly always survive subsequent winters, even if they are much harsher (Clifton-Brown et al., 2001b; Heaton et al., 2008a; Lewandowski et al., 2000). A typical growing season for a mature stand of M. giganteus is shown in Fig. 4. Shoots emerge from the rhizomes in early spring when soil temperatures are between 6 and 10 8C. Though leaves can extend at lower temperatures, 10 8C is considered the standard for consistent leaf extension (Clifton-Brown and
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April
May
August/ September
November
December
Emergence
Canopy closure
Maximum biomass
Senescence Dry down
February
Over winter
Fig. 4. Annual growth cycle of a mature M. giganteus stand. Typically 30% of peak biomass can be lost during senescence and overwintering as leaves drop and nutrients are remobilized to rhizomes.
Jones, 1997; Hastings et al., 2009a; Zub and Brancourt-Hulmel, 2010). Biomass rapidly accumulates through summer, peaking around September (Beale and Long, 1997; Heaton et al., 2008a). Though biomass yields are highest in late summer, so are moisture contents and nutrient take-off rates. The crop is typically harvested after senescence and associated nutrient remobilization and crop drying have occurred, that is, in the period after a killing frost but prior to spring growth. For example, the harvest window in Illinois is between November and March, depending on the demand for feedstock and ability to access the field under snowy winter conditions. During senescence, 30–50% of harvestable dry matter can be lost as leaves drop (Clifton-Brown et al., 2007; Heaton et al., 2008a) and nutrient reserves are translocated to the perennating rhizomes (Section III) (Beale and Long, 1997; Dohleman, 2009). Efficient translocation not only helps to ensure adequate nutrient supply for growth in the following season, thus reducing the need for additional fertiliser (Himken et al., 1997; Lewandowski and Kicherer, 1997), it also minimises the inorganic compounds in the harvested feedstock that could become pollutants in fuel (Jenkins et al., 1998).
1. Productivity overview Overall, studies show that the range of harvestable M. giganteus yields to be between 5 and 55 Mg ha 1 (Fig. 5), making it one of, if not the most, productive land plants in temperate climates. The underlying physiologic basis of this exceptional productivity is discussed in the next section (Section III); here, we outline the results of geographically diverse yield trials.
Miscanthus production Europe and Unites States
DENMARK.2 15-15'
IRELAND5 4-20' U.K11 8-30’
ILLINOIS15
NETH.3 15-15'
BELGIUM4
14-44'
KANSAS1 12-12' GERMANY9 4-30'
15-16'
MISSISSIPPI17
25-56'
FRANCE16 AUSTRIA6 42-49' SWITZERLAND7 22-22' 13-25' ITALY12 30-32'
PORTUGAL10 24-30'
SPAIN13 14-34' TURKEY8 12-28' 14
GREECE 26-44'
Miscanthus production High (>30 Mg ha−1) Medium (21-30 Mg ha−1) Low (<20 Mg ha−1)
1
7
Propheter et al. (2010); Scott Staggenborg, unpublished data. Lewandowski et al. (2000) 8 Lewandowski et al. (2004); Acaroglu and Aksoy (2005) Lewandowski et al. (2000) 3 9 Clifton-Brown et al. (2000); Clifton-Brown et al. (2004) Lewandowski et al. (2000) 10 4 Clifton-Brown et al. (2000); Clifton-Brown et al, (2004) Clifton-Brown et al. (2000) 11 5 Beale and Long (1997) Clifton-Brown et al. (2007) 6 12 Lewandowski et al. (2000) Lewandowski et al. (2000), Mantineo et al. (2009) 2
Fig. 5.
13
Lewandowski et al. (2000) Lewandowski et al. (2000) 15 Heaton et al. (2008) 16 Tayot et al. (1995); Clifton-Brown et al. (2004) 17 Batchelor and Steele (2009) 14
Map of M. giganteus trials and the range of biomass yields reported in the peer-reviewed scientific literature.
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Numerous studies have evaluated M. giganteus in England and Ireland. Beale and Long (1997) measured above- and below-ground productivity of 3–4-year-old stands of M. giganteus and another C4 perennial grass, Spartina cynosuroides in England at 518 N latitude. The above-ground biomass of M. giganteus peaked at 30 Mg ha 1 in mid-September, then declined to about 20 Mg ha 1 by February, while S. cynosuroides reached peak production in August ( 20 Mg ha 1) but maintained that level throughout the fall and early winter as leaves were retained in the aerial biomass instead of dropping as in M. giganteus. Below the ground, the biomass of rhizomes and roots extracted from a 20-cm depth was found to vary over the course of the year in a pattern suggestive of nutrient mobilization, with depletion of biomass in the late spring and early summer, followed by increases that peaked around the end of the growing season in early November (Beale and Long, 1997). This pattern has also been observed in M. giganteus in Germany (Himken et al., 1997) and the US (Dohleman, 2009). Two of the rare longer-term trials of M. giganteus productivity were conducted in England at the Rothamsted Research Farm (518480 N) and in Cashel Co., Ireland (528390 N). In the cool climates at both locations, harvestable biomass continued to increase during the first 5 years of growth (Christian et al., 2008; Clifton-Brown et al., 2007). This is in contrast to warmer locations where ceiling yields were achieved in 2–3 years (CliftonBrown et al., 2001a; Heaton et al., 2008a). Changes in harvestable biomass following achievement of plateau yields were attributed to annual weather conditions, namely moisture availability, and possibly to K deficiencies, as K take-off rates were high in both fertilized and unfertilized treatments. In Ireland, soil and tissue analysis indicated K to contribute more to observed yield increases than N or P fertilizer (Clifton-Brown et al., 2007), which showed no significant impact at either location. Germany was the home to some of the largest plantations of M. giganteus in the 1990s, though losses of micropropagated plants during the first winter (Jorgensen and Schwarz, 2000) tempered enthusiasm and slowed M. giganteus adoption across the country. Multiple trials in Germany have shown good potential for M. giganteus as well as M. sinensis varieties for biomass production (Clifton-Brown and Lewandowski, 2002; Clifton-Brown et al., 1998; Clifton-Brown et al., 2001a) with efficiencies of nutrient and energy use that are comparable to or better than willow (Salix spp.), switchgrass, reed canary grass (Phalaris arundinacea) and maize (Boehmel et al., 2008; Lewandowski and Schmidt, 2006). In the warmer, drier climates of Italy, Greece, Portugal and Turkey, M. giganteus has produced > 35 Mg ha 1 under irrigation and N fertilization. Such locations present the best documentation of M. giganteus yield
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response to N fertilizer (Acaroglu and Aksoy, 2005; Ercoli et al., 1999), though the response is still not consistent (Danalatos et al., 2007; Mantineo et al., 2009), as reviewed by Miguez et al. (2008). Without irrigation, M. giganteus is not likely to be viable in dry Mediterranean climates, though some types of M. sinensis are promising (Clifton-Brown et al., 2001a; Danalatos et al., 2007). Yield trials of M. giganteus started much later in the US, where the focus was on switchgrass instead of M. giganteus as a model herbaceous energy crop (Heaton et al., 2004b). The first replicated trials were conducted in the Midwestern US where trials at three locations in Illinois (378450 N–418850 N) demonstrated some of the highest productivity on record, with average harvestable yields of 30 Mg ha 1 without irrigation and only 25 kg ha 1 of N fertilizer applied in one season (Heaton et al., 2008a). Such high yields, 2–4 times those of the regionally adapted Cave-In-Rock switchgrass, even under a low-input management scheme, stimulated considerable interest in M. giganteus in the US. Furthermore, the sterile nature of this clone is considered particularly advantageous in of light invasion potential from new biomass crops (Barney and Ditomaso, 2008; Jakob et al., 2009). Dohleman and Long (2009) demonstrated that M. giganteus is 60% more productive than maize, even in the heart of the US ‘Corn Belt’. How is this possible? Even though maize had higher light-saturated photosynthetic rates as well as higher rates of primary carboxylation and substrate regeneration, M. giganteus had more leaf area and a longer canopy duration, allowing it to assimilate more carbon into biomass over the entire growing season (Dohleman and Long, 2009). A similar result has been observed in Kansas, where M. giganteus has yielded more than maize (12.8 Mg ha 1 vs. 10.1 Mg ha 1), though yields of both crops were half of those realized by the photoperiod-sensitive S. bicolor (Propheter et al., 2010). Why has such large variation been observed in such genetically similar material? In the following sections, we explore the relationship of biomass yield to environmental factors that might limit it. 2. Water As a C4 crop, M. giganteus has a high efficiency of water use, typically requiring between 100 and 300 l of water to produce 1 kg of biomass (Beale et al., 1999; Lewandowski et al., 2000; Mantineo et al., 2009) For comparison, typical values for an annual maize or sorghum crop are near the upper end of this range, around 300 l kg 1 (Hanson and Hitz, 1983; Howell et al., 1998). At high yields, efficient use of water does not necessarily confer low water use overall, and there is some concern that water availability will limit the use of M. giganteus (Richter et al., 2008). For instance, an
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M. giganteus crop of 25 Mg ha 1 at an average water use efficiency would require 200 l kg 1 25,000 kg ¼ 5,000,000 l or the equivalent of 500 mm of rainfall during the growing season. More information on water use by M. giganteus can be found in Section V. While M. giganteus has been shown to have a root–shoot ratio of approximately 1 to 1 (Dohleman, 2009) and roots that extend down at least 2 m (Neukirchen et al., 1999), it does not appear that M. giganteus draws water from this entire depth. Studies of soil water depletion in England and Italy show that M. giganteus obtains most of its water from the top 1.5 m of the soil profile, leading Finch and Riche (2008) to suggest that 1.7 m should be considered the ‘effective maximum rooting depth’ concerning soil moisture (Beale et al., 1999; Finch and Riche, 2008; Monti and Zatta, 2009). Beale et al. (1999) found that M. giganteus grown in southern England extracted most of its water from the first 0.8 m of the soil profile and 90% of the root biomass was found in the first 0.5 m of the soil profile. In this study, the water use efficiency of M. giganteus was higher than another C4 grass, S. cynosuroides, but the higher productivity of M. giganteus was mainly due to its extended growing period, since the flowering of S. cynosuroides commenced in early July and M. giganteus remained vegetative until September, reaching 29 Mg ha 1 of dry biomass in an irrigated field. In a container experiment, Clifton-Brown and Lewandowski (2000b) found M. sacchariflorus to have the highest water use efficiency (4.1 g DM kg 1 H2O) when compared to M. sinensis and M. giganteus. They concluded that M. sinensis would be more suitable to drier environments than the other two genotypes since it responded early to drought stress by reducing stomatal conductance and leaf growth (Clifton-Brown and Lewandowski, 2000b). Quantification of the impact of soil moisture deficit on biomass yield has been attempted within single experiments, but is perhaps best summarized by the inputs into MISCANFOR, a crop growth model developed for M. giganteus and a stress-tolerant M. sinensis variety (Hastings et al., 2009a,b). MISCANFOR calculates the actual evapotranspiration (ET) a simulated crop would experience using a three-step process and available meteorological data. First, it considers evaporation of rainfall intercepted by the canopy, then leaf transpiration, which is in turn related to the leaf area index of the canopy and the limitation of available soil moisture, and finally, evaporation from the soil through diffusion from soil pores (Hastings et al., 2009a). This process is more holistic than other approaches in that it considers the soil moisture holding capacity of soils in addition to precipitation/irrigation and ET, and has been used to estimate the likely growing range and productivity of M. giganteus in Europe (Hastings et al., 2009b).
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3. Temperature a. Seasonal growth. Typically, M. giganteus begins to grow from dormant rhizomes when soil temperatures reach 10–12 8C, while leaves begin expanding after air temperatures average 5–10 8C (Clifton-Brown and Jones, 1997; Farrell et al., 2006; Lewandowski et al., 2000). Though chilling temperatures (below 12 8C) frequently limit productivity of C4 crops (Long, 1999), M. giganteus has proved an exception to this trend by remaining productive and with high quantum efficiencies of CO2 assimilation, even at cool temperatures in the field (Beale and Long, 1995; Beale et al., 1996; Dohleman et al., 2009). When evaluating growth rates of different genotypes under low temperature in a controlled environment, Clifton-Brown and Jones (1997) found that M. giganteus was also able to expand leaves more rapidly between 10 and 20 8C, allowing it to close canopy faster and yield more biomass, while Farrell et al. found genetic variation in temperature thresholds for emergence that should allow some genotypes to begin growing earlier in the season. b. Overwinter survival. One of the major limitations to the production of M. giganteus in temperate climates is consistent overwinter survival, particularly in the establishment year (Clifton-Brown and Lewandowski, 2000a; Farrell et al., 2006; Heaton et al., 2004b; Lewandowski et al., 2000, 2003b). Currently, it is generally accepted that temperatures less than 3.4 8C are lethal to M. giganteus, thus, this is the lower limit used to determine its potential distribution and productivity (Hastings et al., 2009a,b). Although Clifton-Brown and Lewandowski (2000a) identified 3.4 8C as sufficient to kill rhizomes removed from the field in an artificial freezing test, this temperature is not consistent with the observations in the US, where established M. giganteus has regularly survived soil temperatures below 6 8C at a 10-cm depth (E. Heaton, unpublished data). Little work has yet to be done on the importance of cold acclimation to overwinter survival in Miscanthus species, but it is likely to be as important as it is in other cool-season perennial grasses, where a distinction is made between cold acclimation and freezing tolerance (e.g. Hulke et al., 2008; Stier et al., 2003; Zhou and Zhao, 2004). 4. Soil conditions Generally, M. giganteus performs well over a range of soil conditions when water is not limiting. Under water-limited conditions, it has performed best when planted in clay soils and worse when planted in sandy soils, likely to do with the higher water holding capacity of clay soils. Christian and Haase
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(2001) report on Austrian trials aimed at testing the influence of soil type on the yield and stem number of M. giganteus, where it was found that a good soil aggregate structure, as indicated by pore volume and size distribution, was more important than the soil type or pH. The authors concluded that the most suitable soils for M. giganteus have an intermediate texture that allows good air movement, a high water holding capacity and high organic matter content (Christian and Haase, 2001). While they also assert that shallow soils reduce potential productivity, Clifton-Brown et al. (2007) found that M. giganteus still produced 15–20 Mg ha 1 y 1 even when grown on marginal soil that had an effective rooting depth of 40 cm. Over a period of 15 years, productivity declined at this site, but was attributed to potassium deficiency and thus considered manageable. Heavy, waterlogged soils have also been shown to reduce plant height and delay achievement of plateau yields from 2 to 5 years in M. giganteus (Christian and Haase, 2001). In Germany, M. giganteus was grown on two sandy soils, a silt-dominated soil and a clay-dominated soil. Above- and below-ground biomass was highest at the site with the silt soil, and M. giganteus cropping was found to influence the soil organic matter (SOM) composition at all locations (Kahle et al., 2001). Pre-harvest losses and harvest residues supplied 2.2–5 Mg C per year to the soil and lead to an increase of 0.5–1.2 g kg 1 SOM per year, with higher contributions on the sandier soils. Further, it was found that M. giganteus disproportionately enriched lipids, sterols and fatty acids in SOM that are less available for decomposition by soil microorganisms, thus increasing the hydrophobic components of SOM that are important for soil aggregation and stability and improving soil quality (Kahle et al., 2001). B. CROP MODELLING
1. Productivity modelling The potential of M. giganteus as a dedicated bioenergy crop, as evidenced from the extensive network of European field trials (e.g. MPN), has been extended throughout the rest of Europe using semi-mechanistic crop models (Clifton-Brown et al., 2000, 2004; Hastings et al., 2009a; Miguez et al., 2009; Price, 2004). Initially, Clifton-Brown et al. (2000), using a simple model based on radiation use efficiency (RUE), simulated potential productivity of M. giganteus for Ireland with yields ranging from 16 Mg ha 1 in northern Ireland to 26 Mg ha 1 in southern Ireland, where the total annual solar radiation and the length of the growing season are longer (Clifton-Brown et al., 2000, 2001b). These predictions, however, were only based on radiation and temperature and ignored limitations due to water and nutrient
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stress. Price (2004), using a similar approach that included effects due to water stress, estimated yields in the range 7–24 Mg ha 1 for England and Wales. An important consideration that can be explored using crop models is the yearto-year variability in yields, which Price (2004) estimated to be 10–25%. This variability, which is typically poorly estimated from short-duration field trials, is a crucial component in planning for feedstock availability for a biorefinery. Incorporating site-specific information about soil water availability and improving upon the previous version of the model, Clifton-Brown et al. (2004) showed that the water-limited potential for M. giganteus biomass production in Europe ranged from 17 Mg ha 1 in Sweden to 41 Mg ha 1 in Portugal. Under non-limiting conditions, the highest estimated peak yield was of 60 Mg ha 1, which reflects the maximum potential of M. giganteus, and it is close to the highest values measured in Italy and Greece (50 and 54 Mg ha 1, respectively). However, another important consideration in M. giganteus productivity is the inevitable reduction in harvestable biomass between the peak biomass in the fall to that of late winter. Clifton-Brown et al. (2004) estimated this to be 0.36% loss per day and an average total of 33% by the late winter harvest. Simple models, such as MISCANMOD, are valuable for assessing the potential of M. giganteus productivity outside the range where it has been cultivated. However, there are limitations in its ability to extrapolate to other regions since the model strongly depends on a parameter that describes the efficiency of the crop in converting radiation to biomass (RUE, g MJ 1). Although in this model, RUE has been treated as a constant, Clifton-Brown et al. (2000, 2004) reported that the value of ec for M. giganteus ranged from 2.4 to 4.2 g MJ 1 PAR in different environments. These authors recognized that the model depends strongly on RUE and that a more mechanistic model would be more appropriate (CliftonBrown et al., 2001b). Empirical models are appealing due to simplicity, but by their design, they cannot provide insights into the physiological basis of RUE variation, or growth and the physiology of water use. The model MISCANMOD has been further refined and renamed MISCANFOR (Hastings et al., 2009a), with improved descriptions of the relationship between potential and actual ET, which impacts calculation of water stress; variable RUE which depends on temperature, nutrient and water stress; and additional modifications that reflect recent findings in M. giganteus physiology such as photoperiod sensitivity. Their results suggest that although M. giganteus can be highly productive in southern Europe, a 20% variability in biomass productivity should be expected due to year-to-year fluctuations in weather patterns (Hastings et al., 2009a).
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To make more detailed predictions of M. giganteus physiology and growth, a different type of model with a higher degree of mechanism is needed. WIMOVAC (Windows Intuitive Model of Vegetation response to Atmospheric and Climate Change) is a more suitable model as a guide to future experiments and breeding (Humphries and Long, 1995). It was shown that theoretically, M. giganteus can increase its productivity by 4 Mg ha 1 if the threshold temperature for growth could be lowered by 2 8C and degreeday requirements were increased so that flowering occurred uniformly (Clifton-Brown et al., 2001b). Miguez et al. (2009) also showed that in addition to peak productivity, WIMOVAC was able to accurately simulate plant CO2 uptake, leaf area index and biomass partitioning among leaf, stem, root and rhizome; this last part being limited by available data. Although results from models are useful for evaluating the biomass potential of M. giganteus in different regions, it is also important for crop models to integrate new information on plant growth and physiology generated in recent laboratory and field experiments. In addition, crop models can be used as an aid in breeding programmes if appropriate connections can be made between relevant traits that can be quickly phenotyped, included in crop models and evaluated for productivity (Boote et al., 1996). Crop models are also the only tool available to produce estimates of M. giganteus performance under future projected climate change scenarios or to evaluate the impact of increasing the land use devoted to bioenergy crops on carbon sequestration and reduction in greenhouse gas emissions (Clifton-Brown et al., 2007; Davis et al., 2010; Tuck et al., 2006). 2. Modelling for crop improvement Crop models can also be used as a guide for breeding programmes or as a means to envision a crop ideotype (Boote et al., 1996). While simulation models can be used to predict appropriate trait phenotypes and selection protocols in breeding programmes to achieve ideotypes (Boote et al., 1996), for a true integration of crop models and breeding, the inheritance of model parameters is required (Yin et al., 2003). One objective that can be pursued in a breeding programme is to optimize plant carbon allocation among plant components (i.e. leaf, stem, rhizome and root), which requires at least (1) phenotypic and genotypic data, and (2) a crop model that can capture the impact of different carbon allocation schemes on growth and biomass production. This approach can be used to study the effects of genotypes with different biomass partitioning schemes. However, there is clearly a balance between the support and nutrient acquisition provided by rhizomes and roots and the benefit of partitioning more biomass to above-ground organs that can be
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harvested. One factor that is likely to have a major impact on carbon allocation is the manipulation of flowering time (Sticklen, 2007). By reducing the energy invested in reproductive structures, the proportion of biomass available for harvest can be increased (Ragauskas et al., 2006) and optimized to develop cultivars adapted to particular regions. For example, an improved carbon allocation scheme can result in reduced leaf area by increasing the number of stems and/or their thickness. In addition, maintaining leaf area index at optimum values (Hay and Porter, 2006) also has the potential of reducing crop transpiration and thus improve water use efficiency which can be especially important for biomass production in dry environments (Richards et al., 2002). This reduction in leaf area index will be most beneficial if it does not impact on the timing of canopy closure and maximum light interception. It should also be considered that flowering is an important component in triggering senescence processes which, in perennial crops, initiate translocation of nutrients and carbohydrates to below-ground storage (Heaton et al., 2009). If delayed flowering prevents this from happening, the nutrient use efficiency will decrease, impacting the sustainability of the cropping system, since synthetic fertilizers need to be added and the excess N in the exported biomass needs to removed or treated (Beale and Long, 1997).
III. PHYSIOLOGY As reviewed in the previous section, M. giganteus has proved to be one of the most, if not the most, productive terrestrial plants in mid-latitude northern climates (35–608 N). The first replicated trials of this crop in the US showed yields of 30–40 Mg ha 1 y 1 across three sites in Illinois (Heaton et al., 2008a). In central Illinois, where some of the highest yields of maize in the world are recorded, M. giganteus yielded 60% more shoot biomass, even though the maize crop was heavily fertilized and no fertilizer added to M. giganteus during the comparison (Dohleman and Long, 2009). In E. England at 528 N, dry matter yield in similar replicated trials was 20 Mg ha 1 with a peak biomass of 30 Mg ha 1. These are the highest annual dry matter yields for any crop in the UK (Beale and Long, 1995, 1997). Taking account of the large amount of root and rhizome simultaneously produced, the efficiency of conversion of visible sunlight energy intercepted by the leaves into total biomass energy was 7.8%, again one of the highest conversion efficiencies recorded and equal to that obtained by the Amazonian grass Echinochola polystachya which holds the record annual dry matter yield for any terrestrial vegetation (Beale and Long, 1995; Piedade et al., 1991). This
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represents 65% of the theoretical maximum efficiency of C4 photosynthesis, that is, 12% of visible sunlight (Zhu et al., 2008). The potentially higher water and nitrogen use efficiencies associated with C4 photosynthesis are also realized (Beale and Long, 1997; Beale et al., 1999). This section analyses the possible physiological basis of this exceptional productivity and resource use efficiency. A. PHYSIOLOGICAL BASIS FOR M. GIGANTEUS PRODUCTIVITY
Why is M. giganteus so high yielding? Crop yield is determined by the product of total incident solar radiation (Qtot), the efficiency of radiation interception (Ei), the efficiency of conversion of intercepted radiation to above-ground biomass (Eca) and the efficiency of partitioning biomass to harvested material (; e.g. the grain in most crop plants). In biomass crops, all above-ground biomass is harvested, making close to unity, therefore Ei and Eca are crucial to the final yield. Miscanthus giganteus is an inter-specific hybrid, so one hypothesis would be that its exceptional yield is a result of hybrid vigour. However, side-byside trials in Europe have shown that cultivars of one of the parent species, M. sinensis, achieve similarly high yields (Clifton-Brown et al., 2001a, 2004). A second factor is that its parent species, in their native habitat, are primary colonizers (Stewart et al., 2009). Many primary colonizers have proved to be highly productive; this may be a feature selected in evolution, since to colonize sites where other plants have not previously grown, high productivity may be crucial to gaining a foothold, as shown by the highly productive species E. polystachya (100 Mg ha 1 y 1; Piedade et al., 1991) and Spartina alterniflora (64 Mg ha 1 y 1; Long and Mason, 1983). Thirdly, M. giganteus uses C4 photosynthesis, as apparently do all genera of the grass tribe Andropogoneae which includes Sorghum, Zea, Saccharum and Andropogon (Kellogg, 1998). C4 photosynthesis has an inherently higher efficiency of conversion of sunlight energy into carbohydrate because it avoids photorespiration. Photorespiration occurs in other plants (C3) because the primary carboxylase (Rubisco) catalyses both a carboxylation and an oxygenation reaction. The oxygenation reaction catabolizes recently formed carbohydrate back to CO2, and so imposes an average 30% yield penalty on C3 crops, a penalty that increases with temperature (Long, 1991). C4 photosynthesis has evolved independently from the more ancient and ubiquitous C3 photosynthesis at least 45 times (Sage et al., 1999). The elimination of photorespiration in C4 species does come at a cost. More energy is required for each CO2 assimilated, although it is less than the energy lost to photorespiration when
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temperature exceeds 25 8C. In high light environments where photosynthesis is light-saturated, additional energy requirements are, by definition, irrelevant. Because of the higher efficiency of carboxylation in C4 plants, intercellular CO2 concentration is lower and typically only about 60% of that in C3 leaves. As a result, a C4 leaf in the same environment as a C3 leaf will lose only 60% of the water lost by a C3 leaf in assimilating a given amount of CO2. Because of the advantages that C4 photosynthesis has under high temperature, high light and low moisture conditions, it evolved mostly in low-latitude and relatively arid regions (Sage et al., 1999). It has been hypothesized that the process of C4 photosynthesis is intrinsically limited to warm climates, and that its efficiency of light use will be intrinsically less efficient at low temperatures (Sage and Kubien, 2007). Miscanthus giganteus is proof that this is not the case. It is able to form and maintain leaves with high photosynthetic rates at temperatures about 6 8C cooler than maize cultivars bred for cool temperate climates. Even compared to other C4 plants native to cool climates, M. giganteus appears exceptional (Long, 1999). How does M. giganteus differ? Gene sequences of Rubisco and the enzymes of the C4 dicarboxylate cycle show 99% homology with its very close relative sugarcane (S. officinarum), and the few single nucleotide polymorphisms (SNPs) give no clue of any changes that would make these enzymes more cold-tolerant. This is supported by the observation that there appear to be no differences in the temperature dependence of the kinetics of the recombinant enzymes from these two species in vitro (Wang et al., 2008a,b). Metabolic control analysis suggests that two enzymes limit the rate of photosynthesis in C4 plants: Rubisco and PPDK. When maize and M. giganteus are transferred from a growth temperature of 25 to 14 8C, photosynthetic rates in both species decline over the first 2 days, but in M. giganteus, it then recovers while continuing to decline without recovery in maize. What underlies this difference? In maize, amounts of Rubisco and PPDK decline continuously, while in M. giganteus, the amount of Rubisco is unchanged and the amount of PPDK more than doubles. This corresponds to a large increase in the amount of mRNA coding for PPDK, suggesting an up-regulation of gene expression. In vitro, PPDK is cold-labile, dissociating into its monomers at 10–12 8C. Concentration of the enzyme in vitro, however, suppresses this dissociation, which might explain the ability of C4 photosynthesis to continue functioning at much lower temperatures in M. giganteus (Wang et al., 2008b). C4 plants are also strongly affected by photoinhibition at low temperatures. Decreased ability to use absorbed light energy in carbon metabolism leads to oxidative inhibition and damage to the photosynthetic apparatus.
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Even compared to the UK native C4 plant, Cyperus longus, M. giganteus has a significant advantage here. While the efficiency of use of electrons utilized in CO2 assimilation declines significantly with decrease in temperature from 25 to 17 8C in C. longus, this efficiency did not decline in M. giganteus until 10 8C (Farage et al., 2006). How is this achieved? First, M. giganteus maintains high rates of photosynthetic carbon metabolism down to 10 8C, allowing it to utilize more of the absorbed light energy. Secondly, the xanthophylls Zeaxanthin, which facilitates heat dissipation of excess absorbed light energy in the photosynthetic apparatus, increased some 20-fold from 0.8 mol m 2 in M. giganteus grown at 25 8C to 16.8 mol m 2 when grown at 10 8C (Farage et al., 2006). How do these biochemical advantages lead to increases in yield in the field? In trials in the Corn Belt of the Midwestern US, M. giganteus has an annual Ei that is 60% higher than maize, the major factor accounting for its higher productivity. This is due to the perenniality of M. giganteus and also its ability to produce photosynthetically viable leaves during the cooler periods at the ends of the growing season within the temperate environment (Dohleman and Long, 2009). Estimates of canopy photosynthesis show that M. giganteus is able to produce active leaves early in the spring, allowing for a great deal of net canopy photosynthesis near the summer solstice, when the maximum amount of solar radiation is available. Furthermore, a great deal of CO2 assimilation occurs in the autumn, after the maize crop has completely senesced (Fig. 6). Miscanthus giganteus is exceptionally productive when compared to other perennials as well, with the advantage compared to those species driven by a greater Eca. Miscanthus giganteus was able to produce a closed canopy within one month and maintain it for 5 months even at the high latitude of 528 N, and also have a 60% higher Eca than S. cynosuroides (Beale and Long, 1995). Miscanthus giganteus has been shown to have a substantially higher Eca than the regionally adapted perennial switchgrass. When integrated over two full growing seasons, the leaf-level photosynthesis of M. giganteus was 33% higher than that of switchgrass (Dohleman et al., 2009). This increased carbon assimilation came at a price, however, as stomatal conductance was also 25% higher in M. giganteus and could explain why switchgrass tends to remain more productive under dry conditions (Heaton et al., 2004a). High productivity in cool environments is not simply a function of capacity to maintain high leaf photosynthetic efficiency at low temperature, but also the ability of the perennating organ, the rhizome, to survive sub-zero winter temperatures. Established stands of M. giganteus and the parent species have survived for decades in botanical gardens where winter temperatures can drop below 25 8C. For example, the clone planted in
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Estimates of canopy-level carbon assimilation for M. x giganteus and Z. mays
Daily canopy level CO2 assimilation (mol CO2 m−2 ground area day−1)
4 M.x giganteus Z.mays 3
2
1
0 Jan
Feb
Mar
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Fig. 6. Seasonal carbon accumulation for the perennial crop M. giganteus and annual row crop Z. mays. While Z. mays is able to assimilate more carbon in the middle portion of the growing season, the extended growing season allows for 60% greater biomass accumulation in M. giganteus (modified from Dohleman and Long, 2009).
the Illinois trials has survived without any evidence of winter loss in Urbana since 1988 and Chicago Botanical Gardens since 1970. This includes survival through the coldest winter temperature ever recorded in Chicago, 33 8C in January 1985 (Heaton et al., 2008a). However, Miscanthus appears more vulnerable to low temperature during the first year after planting. Artificial freezing tests with rhizomes removed from the field showed that the lethal temperature at which 50% were killed (LT50) for M. giganteus and M. sacchariflorus genotypes was only 3.4 8C (Clifton-Brown and Lewandowski, 2000a). This represents a high risk for losses after planting of rhizomes or in the establishment of stands from seed. However, LT50 in one of the M. sinensis genotypes tested was 6.5 8C, showing significant potential for selection of improved tolerance. Interestingly, among the genotypes, increased tolerance to freezing temperatures was not related to earliness in autumn shoot senescence or associated with size. This last point may be critical, since while M. giganteus partitioned 35–40% of its biomass in rhizomes, the most cold-tolerant genotype partitioned only about 20% of its biomass into rhizomes (Clifton-Brown and Lewandowski, 2000a). This is
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important, since if there is no over-wintering penalty for investing less in rhizomes, then it indicates the potential to select for lines which partition a higher proportion of photosynthate into stems. This will have the double benefit of accelerating shoot growth and harvestable biomass. The clone(s) of M. giganteus that have so far been examined in Europe and the US are thought to have been collected from Honshu island of Japan (Stewart et al., 2009). The parent species, M. sinensis and M. sacchariflorus, range from the tropics to southern Siberia, so it is unlikely that results for this clone represent the limits to cold temperature tolerance, and there should be breeding resources available to improve the cold-tolerance of Miscanthus rhizomes. B. NUTRIENT CYCLING IN M. GIGANTEUS
One of the touted advantages of perennial grasses in general and M. giganteus in particular is the ability to internally cycle or remobilize nutrients between above- and below-ground tissues. Himken et al. (1997) in Germany and Beale and Long (1997) in England independently documented a seasonal pattern in biomass and nutrient accumulation in shoots and rhizomes of M. giganteus, with rhizome biomass peaking after 80% of above-ground dry matter had accumulated in the late summer/early autumn, then staying constant or decreasing slightly over the winter. Rhizome biomass then declined dramatically during shoot emergence in the spring, presumably as mobile carbohydrates and nutrients were translocated to the actively growing shoot tissue. The concentrations of N and P in plant tissues generally mirrored the seasonal trends in biomass allocation, but K showed less fluctuation in below-ground tissues, possibly because more of the monovalent anion leached from senescing shoots before it could be remobilized to the rhizome (Beale and Long, 1997; Clifton-Brown et al., 2007). Further, crop removal rates of K were higher and tissue and soil concentrations lower in long-term trials of M. giganteus in England and Ireland (Christian et al., 2008; Clifton-Brown et al., 2007), suggesting that K is not translocated as efficiently as N and P and thus K may limit growth before other macronutrients do. It is important to be aware that the addition of K fertilizer is frequently achieved through application of KCl fertilizer, leading to complementary uptake of Cl (Lewandowski and Kicherer, 1997; Lewandowski et al., 2003a) which leads to production of HCl during combustion of the feedstock. HCl can have negative environmental and economic consequences for energy producers, leading to emission of the poison dioxin, as well as corroding steam boilers (Lewandowski and Heinz, 2003). Mineral nutrients are
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undesirable in biomass feedstock because they can ultimately become atmospheric pollutants that must be mitigated irrespective of the type of fuel that is produced. Crop senescence and harvest time can dramatically impact the amount of nutrients removed from the field with short-term impacts on fuel quality and long-term impacts on environmental and economic sustainability. Green M. giganteus shoot tissue typically has N, P and K concentrations of about 20, 2 and 20 mg g 1, respectively (Beale and Long, 1997; Heaton et al., 2009; Himken et al., 1997). Concentrations are highest during shoot emergence and become diluted as biomass rapidly accumulates in the first few months of growth. By winter, the concentrations of N, P and K have dropped by an order of magnitude, to 1–5 mg g 1. Nutrient budgets have shown that the shoots obtain some of their nutrients from the soil, and not all of the nutrients are taken off by the harvested crop or put back in the rhizome, and therefore, some are lost back to the soil every year (Beale and Long, 1997), though the impact of nutrient movement among plant, soil and detritus pools has not been thoroughly evaluated. The N demands of a high-yielding M. giganteus crop seem impossible to satisfy without external fertilizer or serious depletion of soil reserves: Heaton et al. (2009) found that M. giganteus was capable of removing nearly 300 kg ha 1 of N, despite only a single application of 25 kg ha 1 N during the preceding 3 years. What is the source of this N? Even in fertile soils with high mineralization rates, balancing the N budget in Illinois was only possible when N fixation was included in the analysis (Davis et al., 2010). N fixation may be a plausible explanation given that nitrogenase activity was found via acetylene reduction in rhizomes and in bacteria isolated from the rhizosphere. Agricultural producers are faced with a difficult decision when it comes to choosing the best time to harvest M. giganteus: harvest in the late summer when yields are highest, or wait until the first frost and lose 30–50% of biomass to leaf drop and weather? Multiple studies have examined this question (Heaton et al., 2009; Huisman et al., 1997; Lewandowski and Heinz, 2003; Lewandowski et al., 2003a) and generally conclude that it is better to wait and harvest after nutrient concentrations have decreased than to harvest feedstock of reduced quality and be forced to apply costly and greenhouse gas-intensive fertilizer. Further, the biomass ‘lost’ due to leaf drop actually contributes to the SOM pool and could be valued in a carbon credit market. Because N is remobilized to the rhizome, the C:N ratio of standing biomass increases dramatically (Heaton et al., 2009), making the remaining litter recalcitrant to microbial decomposition (Kahle et al., 2001) and contributing to soil organic carbon (Kahle et al., 2002).
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IV. BREEDING, GENOMICS AND GENETICS A. TAXONOMY AND ORIGINS
The tribe Andropogoneae within the family Poaceae includes several species of natural and agricultural value, including the C4 grasses sorghum (S. bicolor L. Moench), maize (Zea mays L.) and sugarcane (S. officinarum L.). The subtribe Saccharinae includes the genera Saccharum L. and Miscanthus Anderss., species of which are currently under consideration as potential biomass crops for renewable energy production (Hodkinson et al., 2002a). These two genera are closely related with evidence suggesting occasional inter-generic hybridization (Sobral et al., 1994). Morphologically, Miscanthus species differ from Saccharum by their tough inflorescence rachis, with both spikelets of a pair being pedicellate (Hodkinson et al., 2002a). The taxonomic status of the genus Miscanthus is in a state of flux, with relatively little information available about identity and inter-relationships of its species. According to Clayton and Renvoize (1986), the genus consists of approximately 20 species, most of which are endemic to eastern or southeastern Asia (China, Taiwan, Japan, Korea and south), with two species found in the Himalayas and four in sub-Saharan Africa. Of particular relevance to this review are the species of Miscanthus endemic to southeastern Asia touted as potential dedicated bioenergy crops including Miscanthus floridulus, Miscanthus lutarioriparium, M. sacchariflorus, M. sinensis and the triploid inter-specific hybrid M. giganteus. The basic chromosome number of these species is 19 (Adati and Shiotani, 1962), with most accessions being diploids, although some of the strongly rhizomatous species (M. sacchariflorus and M. lutarioriparium) include accessions that are triploid or tetraploid (Hirayoshi et al., 1955; Hodkinson et al., 2001). Miscanthus sinensis is endemic to East Asia ranging from New Guinea through Indonesia, north through Southeast Asia into China, Taiwan, Japan, Korea and Russia. The native distribution of M. sacchariflorus is limited to Northern China, Korea, Russia and Japan (Hodkinson et al., 2002c). These species, particularly M. sinensis, have populations that have evolved to adapt to a broad range of environments and show substantial genetic diversity (Hodkinson et al., 2002a). All of these species are perennial rhizomatous grasses with obligate out-crossing due to self-incompatibility and with the possible exception that M. floridulus can survive winters in temperate climates. DNA evidence suggests that M. giganteus (3n ¼ 57) is an allotriploid hybrid generated from a rare natural cross between diploid M. sinensis (2n ¼ 38) and a tetraploid M. sacchariflorus (4n ¼ 76) (Hirayoshi et al., 1960; Lafferty and Lelley, 1994; Rayburn et al., 2009) that occurred in
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Japan and via clonal propagation transported in 1935 to Europe and later to North America by commercial nurserymen (Linde-Laursen, 1993). The University of Illinois clone was originally procured from the Chicago Botanic Garden, which in turn acquired their specimen from Europe. This clone shares genetic identity with the widely propagated M. giganteus genotype grown throughout Great Britain (J. Clifton-Brown, personal communication). Miscanthus giganteus is a sterile allotriploid and so does not produce viable seed, reducing its potential as an invasive species (Hodkinson et al., 2002a). Much of the evidence as to the putative parents of M. giganteus is based on morphological observations. Data obtained by Hodkinson et al. (2002b) using variation in the internal transcribed spacer (ITS) region of nuclear ribosomal DNA (nrDNA) supported the hypothesis that M. sinensis and M. sacchariflorus were the parents of M. giganteus and that one species contributed two genomes while the other species contributed only one. The study was unable to elucidate which species contributed two genomes. Calculation of the nuclear genome size using flow cytometry suggests that the M. giganteus accession at the University of Illinois comprises two genomes of M. sinensis and one of M. sacchariflorus (Rayburn et al., 2009). B. MISCANTHUS SPECIES GENETIC IMPROVEMENT
1. Rationale All Miscanthus species are presently genetically unimproved so one would expect that improvement in a number of key traits could be made using breeding and genetic engineering tools. The use of transformation technology is especially important in the case of M. giganteus, which is sterile, thus seed is not produced and crosses cannot be made to generate variability. There also appear to be very few independently derived lines, again indicating little variation. Initial reports indicated that M. giganteus had few pests and diseases, but more recent work has shown that indeed insects, nematodes and pathogens do attack the plants (see Section VI). Thus, it is likely that large plantings of genetically uniform unimproved clones will be subjected to the usual pests and diseases that can affect most crops. 2. Traits to improve Overall yield is one of the most important traits for biomass crops and this is controlled by many factors, including growth rate and duration, and environmental limitations such as water, heat, cold, nutrient, pests and disease. One would expect photosynthetic efficiency to be very important for yield, but Miscanthus species already have the C4 pathway and very efficient
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photosynthesis (Section III). Populations of M. sacchariflorus endemic to Eastern Asia are found as far north as the Amur River Valley in Western Russia. Accessions from these species in Russia and Northern China have adapted to severe winter conditions and represent sources of cold-tolerant germplasm. If flowering is prevented, the active growth period can be increased, so delaying or preventing flowering by decreasing expression of the indeterminate gametophyte gene might be useful (Colasanti et al., 1998). The growth rate might also be increased by increasing gibberillin levels (Eriksson et al., 2000). There are also known genes that have shown promise for alleviating many biotic and abiotic stresses that affect plant performance (Allen, 2010; Datta, 2002). Another trait that is most important to alter is composition of the cell walls. The bulk of mature plant biomass represents secondary cell walls consisting mainly of a complex polysaccharide framework, several types of highly glycosylated proteins and complex polymers of phenylpropanoid units, that is, lignin, the hydrophobic filler that provides physical strength to the cell wall. Various structural and chemical characteristics of plant cell walls that act as the first barrier between plant and environment have evolved in order to resist external stresses from pathogen attack, wounding or mechanical stimuli. These cell wall properties make it difficult to disassemble biomass when it is used for liquid biofuel production; however, high lignin can be advantageous for burning since it has a higher energy content than carbohydrate. Miscanthus species, as all gramineous plants, have type II cell walls with a high content of arabinoxylans and 1,3:1,4--glucans (b-glucans) and a low content of pectic polymers and xyloglucans, which predominate in the matrix of type I cell walls found in dicotyledons and other monocotyledons (Carpita, 1996). Another feature of gramineous cell walls is a high content of hydroxycinnamic acids, such as ferulic acid and p-coumaric acid, which are ester-linked to structural polysaccharides such as different arabinoxylans (Smith and Hartley, 1983). Glucuronoarabinoxylan, arabinoxylans and other xylan-rich hemicelluloses are the dominant hemicelluloses in the cell walls of different tissues of grasses, including their lignified supporting tissues. The amounts of lignin and cell wall-bound ferulic and diferulic acids as well as the composition of wall polysaccharides determine the gramineous plant cell wall rigidity, extensibility and digestibility (Grabber et al., 2004). Information on Miscanthus biomass composition is very limited at present, and the contents of main biomass constituents greatly vary in different publications. Thus, it was reported that dried biomass contains 18.30–
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20.99% lignin and 69.78–78.63% holocellulose in M. sacchariflorus (Visser and Pignatelli, 2001), 38% cellulose, 24% hemicellulose and 25% Klason lignin in M. giganteus (de Vrije et al., 2002) and 41.9% cellulose, 26.6% hemicellulose and only 13.3% lignin determined as acid lignin fibre in M. ogiformis (analogous species to M. giganteus) (Magid et al., 2004). The reported different estimates of lignin concentrations could result from the application of various analytical procedures which do not give consistent results. We tested the biomass characteristics of several Miscanthus accessions from the germplasm collection grown on the University of Illinois experimental farm that were harvested at the end of the growing season applying the acetyl bromide method which was recommended for the prediction of biomass digestibility based on lignin levels (Fukushima and Hatfield, 2004). The results showed large variations across genotypes selected in major cell wall constituents which can have an influence on biomass biodegradability, with about 26% lignin, 40% cellulose and 20% xylan being typical (Fig. 7). There was a negative correlation between the lignin and etherbound phenolic contents and sugar released by both enzymatic hydrolysis alone and that after acid pre-treatment (Fig. 8; A.V. Lygin, unpublished data) when saccharification of selected plant biomass and composition was carried out, as described by Chen and Dixon (2007). For biochemical conversion to fuel, cost-effective pre-treatment (mechanical, physical, chemical or most promising enzymatic) of biomass is usually required. Pre-treatment can modify or remove unwanted by-products, such as lignin, to reduce cellulose crystallinity, and increase the porosity, thus improving hydrolysis (McMillan, 1994). As a consequence of these pre-treatments, cellulose is made accessible for hydrolysis to glucose and fermentation to alcohols. Using genetic engineering for the expression of glycosyl hydrolases that cleave only side chains in branched polysaccharides will give the possibility for fine modification of these polysaccharides, without complete breakdown, that can increase polysaccharide accessibility to enzymatic treatment during biomass conversion. Transgenic expression of glycosyl hydrolases with a well-characterized specificity provides a direct approach for post-synthetic modification of specific polymeric constituents in plant cell walls (Sticklen, 2007). On account of rapid advancements in the characterization of microbial hydrolases, the currently available number of these enzymes is sufficient to deconstruct cell wall polysaccharides completely. Thus, generating transgenic plants with decreased cross-linking levels in cell walls and less lignin should result in higher efficiency of biochemical biomass conversion to fuel, while genotypes with high lignin would be ideal for burning.
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A
Cell wall (CW) components 60 Lignin Cellulose Xylan
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Gracillius nana
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Enzymatic saccharification with acid pretreatment 60 50 40 30 20 Mxg
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Fig. 7. Biomass characteristics of several Miscanthus genotypes (Miscanthus giganteus—M g and four M. sinensis accessions: ‘‘Grosse Fontaine’’, ‘‘Adagio’’, ‘‘Gracillius Nana’’ and ‘‘Alegro’’): (A) acetyl bromide lignin, cellulose and xylan concentrations in cell walls of dried mature tillers harvested in February 2010. Cellulose was estimated by treatment of CW with acetic-nitric reagent followed by phenol-sulfuric assay with glucose as a standard. Xylan was calculated using data from monosaccharide composition of hemicelluloses; (B) sugars (as glucose equivalent) released from grass cell walls by enzymatic hydrolysis (with cellulase and cellobiase for 72 h) without pretreatment and (C) with acid pretreatment. (Vertical bars represent the SD).
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A 29
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27 26 y = −0.7563x + 53.845 R2 = 0.9045
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Fig. 8. Relationships between the lignin contents and saccharification of Miscanthus biomass. Each point represents an individual accession. Stem material was treated with cellulase and cellobiase for 72 h. Total sugar released is presented as a function of lignin content of untreated stems (A) or lignin content of acid pretreated stems (B).
C. BREEDING
Genetic improvement of Miscanthus species as dedicated bioenergy crops is in its infancy. Introductions of Miscanthus accessions into Europe and North America from Southeast Asia were made in the late nineteenth and throughout the twentieth century. Until recently Kew Gardens in England had one of the most extensive collections. These collections represent much of the currently available germplasm for Miscanthus crop improvement. Increased interest and use of ornamental grasses in urban landscapes in the 1970s and 1980s lead to the propagation and commercial sale of Miscanthus accessions (primarily M. sinensis) by nurseries in Europe and North America. These
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horticultural varieties were sold as vegetatively propagated clones and tended to have reduced stature, early flowering and showy inflorescences. The oil embargoes of the 1970s and increasing crude oil costs initiated efforts in Europe and North America to investigate alternative and renewable sources of energy. This leads to the creation of the EU’s MPN and the EMI programmes described earlier and ultimately to the formation of Tinplant Biotechnik und Pflanzenvermehrung GmbH in 1992, a commercial company partially dedicated to Miscanthus breeding in Germany. For 15 years, Tinplant conducted hybridizations and selection for improved accessions of M. sinensis, M. sacchariflorus and M. giganteus for sale to the ornamental nursery industry and for enhanced biomass. Tinplant was acquired in 2007 by Mendel Biotechnology, Inc. of California, who has expanded the Miscanthus breeding programme. In addition, in 2004, the United Kingdom Department for Environment, Food and Rural Affairs initiated support for a Miscanthus breeding programme in Aberystwyth, Wales where they have acquired the Kew Garden collections and some materials from Tinplant and Southeast Asia (Clifton-Brown et al., 2008). Miscanthus breeding efforts have recently been initiated at several other institutions, including the University of Illinois’ Energy Biosciences Institute. Current efforts by both private and public programmes are focused on the collection of Miscanthus genetic resources primarily from countries in Southeast Asia. Collection of germplasm from foreign countries requires compliance with the Convention on Biological Diversity (United Nations Environment Programme, 1993), which gives sovereignty to each country over its genetic resources and requires arrangement of formal partnerships before collection and export of germplasm to another country. Another factor that influences collection involves compliance with issues of plant quarantine where Miscanthus germplasm (seeds or propagules) must be tested and inspected by a government-approved plant pathologist before release. The collection and use of diverse germplasm is a crucial factor in Miscanthus crop improvement programmes. While significant genetic variability has been found among the parental species (M. sinensis and M. sacchariflorus) (Jorgensen and Muhs, 2001), the few (3 or 4) existing triploid M. giganteus accessions generated from inter-specific hybridization display very low levels (Greef et al., 1997; Hodkinson et al., 2002a). Miscanthus giganteus displays remarkable heterosis for vegetative growth when compared to its putative parental species, although in competitive European trials, some accessions of M. sinensis produced up to 70% of the biomass of M. giganteus (Clifton-Brown et al., 2001a). Breeding efforts with M. giganteus are hindered by difficulties in re-synthesizing new
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accessions of triploid M. giganteus due to incompatibility between the parents and the sterility associated with the triploid genome. The requirement of labour-intensive and costly vegetative propagation for potential commercial production of triploid M. giganteus germplasm favours the development of improved vegetative propagation techniques that result in higher multiplication rates and hardy propagules. The inherently high cost of vegetative propagation, however, also favours the development of Miscanthus genotypes that are fertile and bear seeds to facilitate planting and production. The recent creation of hexaploid M. giganteus plants (Yu et al., 2009) presents potential opportunities for the development of fertile germplasm and new breeding opportunities by conducting hybridizations between hexaploids or between hexaploids and diploid M. sinensis and M. sacchariflorus accessions that could generate viable seed. Early emphasis in public and private breeding programmes is on creation and selection within diploid M. sinensis, M. sacchariflorus and hybrid M. sinensis M. sacchariflorus populations. These populations will be used to generate linkage maps for diploid M. sinensis and M. sacchariflorus and for associating the genome with beneficial phenotypic traits. DNA markersaturated linkage maps of the Miscanthus genome will allow for association mapping and marker-assisted breeding. It must be cautioned that though seeded Miscanthus is highly favourable from an economic perspective, a thorough investigation about the invasive potential of fertile Miscanthus is critical prior to mass plantation of these species. D. GENOMICS
One aim of the current Feedstocks Genomics Programme within the Energy Biosciences Institute at the University of Illinois is to generate resources that will enable genomics-directed improvement of Miscanthus germplasm. The genome of M. giganteus is very large, estimated to be 7.0 Gbp by flow cytometry (Rayburn et al., 2009). Using new generation genomic tools, 1 skim sequencing of M. giganteus DNA revealed that much of the genome consists of major repeated sequences with only 2% or about 165 Mbp as ‘genespace’, and the recently sequenced S. bicolor is a useful reference genome (Swaminathan et al., 2010). Deep sequencing of the M. sinensis, M. sacchariflorus and M. giganteus transcriptome found that contigs matched 29,000 of the estimated 36,000 Sorghum genes. This sequence information will be used to generate SNPs, single sequence repeats (SSRs) and PCR-based markers that will be made available to the public for linkage studies, association mapping and marker-assisted breeding. We are in the process of identifying the most informative SNPs across
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the transcriptome of these species to generate a Goldengate SNP array to apply to M. sinensis and M. sinensis M. sacchariflorus hybrid segregating populations. This will provide genetic linkage maps for these species and be used to identify QTL and genes associated with desired phenotypes. These SNP arrays will be made available to the public, while the transcript and genomic sequences the programme generates will be available to online browsers by 2011.
E. MICROPROPAGATION, GENETIC ENGINEERING AND CHROMOSOME DOUBLING
1. Micropropagation Methods have been developed using several tissues of the M. giganteus plant, most efficiently immature inflorescences, to initiate cultures that then can be multiplied and regenerated into whole plants (Holmes and Petersen, 1996; Kim et al., 2010). These methods can be used for micropropagation for large-scale planting and also would be important for genetic transformation, since the genes are, in most cases, inserted into cultured cells.
2. Genetic engineering While breeding may be able to manipulate a number of traits for Miscanthus species, there is very little presently known about what traits are available in the germplasm, and breeding systems are just being developed. Because M. giganteus is sterile and breeding cannot be readily accomplished, being able to directly insert genes appears to have some real importance. Most plant transformation utilizes tissue culture, and methods have been published for culture initiation, maintenance and plant regeneration as stated earlier (Holmes and Petersen, 1996; Kim et al., 2010). Usually, the gene of interest and selectable marker gene are inserted into cells by particle bombardment or Agrobacterium tumefaciens co-cultivation. The transformed cells are selected using a selective agent that kills untransformed cells, but not those expressing the selectable marker gene, such as antibiotic resistance. Plants are then regenerated. To date, the only published report of Miscanthus transformation is with M. sinensis using tissue cultures initiated from immature spiklets or germinating seeds and A. tumefaciens (Engler and Chen, 2009). Selection was carried out using the antibiotic G-418 with the nptII selectable marker gene and plants were generated from the selected callus.
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3. Chromosome doubling It is possible that doubling the chromosome number of the sterile triploid M. giganteus could generate fertile hexaploids that could enable seed production and breeding. Since the cell size would also increase, it is possible that biomass production could increase and the cell wall composition change. We have applied methods that were used to double the chromosome number in maize callus (Wan et al., 1991) to regenerable M. giganteus callus and did produce chromosome-doubled plants (Yu et al., 2009). Preliminary results indicate that the pollen is more viable, as shown by triphenyltetrazolium chloride staining, than that produced by the triploid (W.B. Chae, unpublished data). No seed was produced, but there may be a problem of self-incompatibility as seen with Miscanthus species.
V. ENVIRONMENTAL IMPACTS Compared to annually cultivated crops, perennial grasses are often considered environmentally favourable because the more dense and continuous vegetative cover provides protection to the soil against erosion, may reduce runoff and nutrient loss and sequester carbon in the soil (Blanco-Canqui, 2010). Because perennials begin growth earlier in the year than annuals, perennial grasses are thought to be more synchronous with soil nutrient availability (mineralization) and plant uptake throughout the growing season, which may limit nutrient losses. The degree to which these benefits are realized in practice depends on the specific management practices employed, in addition to past management and the environmental context. Reduced runoff may be beneficial in settings where erosion or downstream flooding is problematic. However, in some settings, runoff and drainage from agricultural cropland are important sources of water for human communities and aquatic ecosystems. In these situations, reduced runoff or drainage may be considered detrimental, especially during droughts. Thus, understanding and assessing the environmental impacts of M. giganteus require some attention to specific management practices and the likely impacts in the various places it will be grown. Unfortunately, there has been relatively little research on the environmental impacts of M. giganteus to date across the range of environmental conditions where it might be grown. Several biofuel crops have been reviewed for possible impacts on water use and nutrient loss (Powlson et al., 2005), but more recent studies are now available on M. giganteus.
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Although M. giganteus is considered an efficient crop in terms of water use per unit of biomass produced (Beale et al., 1999), its high productivity may lead to high water use compared to other crops. Empirical evidence from the US and Germany (Boelcke et al., 1998) is consistent with this view, but a simulation study of the southern UK (Finch et al., 2004) suggested less water use from M. giganteus than from the existing land cover, which was largely a mixture of annual crops and perennial grasses. At two locations in Germany, Boelcke et al. (1998) measured soil moisture in mature (4–6 years old) stands of M. giganteus for a 4-year period. They concluded that soil moisture supply was limiting the biomass yield. They used soil moisture data to calibrate the model LEACHW, and used the model to estimate ET and drainage. The model simulations indicated that M. giganteus provided significantly less groundwater recharge compared to a rotation of winter rye-phacelia-potato. Finch et al. (2004) used a mechanistic model to predict long-term changes in ET resulting from increased plantings of M. giganteus, switchgrass and short rotation willow coppice in the UK. Their modelling predicted that M. giganteus and switchgrass would reduce ET by approximately 50 mm y 1 compared to the existing mixture of cereal crops (e.g. wheat) and C3 grasses, largely because the existing vegetation had a lower temperature threshold for photosynthesis which results in a longer growing season. Model parameterization was partly based on measured characteristics of the plants. The cultivar of switchgrass and the age of the stands were not mentioned, but they measured greater leaf area index in switchgrass than M. giganteus, which is opposite of the results reported by Heaton et al. (2008a) who compared M. giganteus to Cave-in-Rock switchgrass. Finch et al. (2004) also reported that soil moisture under M. giganteus tended to be lower than soil moisture under switchgrass during the later stages of the growing season. The soil moisture comparison was made at two sites over 2 years using replicate plots, but no statistical analysis of the differences was presented. The soil moisture measurements were used to calibrate the model they used to predict the hydrologic impact of the grasses. Finch et al. (2004) acknowledged a need for more data collection on energy grasses to confirm their results. Richter et al. (2008) reaffirmed this need for more data collection to verify the results of Finch et al. (2004). Richter et al. (2008) presented an analysis of existing biomass yields of M. giganteus in the UK, and concluded that soil water availability appeared to be the single most important factor in limiting biomass yield. Finch and Riche (2008) reported that the depth of soil water depletion under
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M. giganteus (1.7 m) was greater than under most crops grown in the UK, even though they estimated that stomatal conductance was lower than most crops. Finch and Riche (2010) also reported that approximately 20% of the precipitation falling on M. giganteus from September till harvest was evaporated from the leaves and stem. This quantity of interception in the fall during winter is more typical of a forest than an agricultural crop, and may partly explain the greater depletion of soil moisture. In the US, McIsaac et al. (in press) measured soil moisture to a depth of 90 cm under M. giganteus, switchgrass (Cave-In-Rock cultivar) and a maize–soybean rotation (the predominant land use in the region) over four growing seasons (2005–2008) in central Illinois. At the end of the growing season, soil moisture under M. giganteus was statistically less than under either switchgrass or maize–soybean. Based on simple water budget calculations, they estimated that the ET of M. giganteus was on average 104 mm y 1 greater than maize–soybean and 140 mm y 1 greater than switchgrass (McIsaac et al., in press). An increase of 104 mm y 1 in ET could reduce surface water flows by 32% in the central Illinois region. Both switchgrass and the M. giganteus were harvested in winter and neither received N fertilizer in this experiment. Cave-In-Rock is not the most productive variety of switchgrass. Higher yielding varieties of switchgrass, treated with appropriate quantities of N fertilizer, would likely be more productive and consequently may use more water than reported in this study (Kiniry et al., 2008; Vogel, 2004). Hickman et al. (2010) used a micrometeorological residual energy budget method to estimate ET from M. giganteus, switchgrass and maize in one growing season (2007). According to their estimates, ET from switchgrass and maize was similar (764 mm) over the 166-day growing season, while water use by M. giganteus was about 190 mm greater. This study was conducted in a subset of the plots used by McIsaac et al. (in press), who estimated M giganteus used 109 mm more water than maize and 69 mm more than switchgrass during this growing season. Although both studies indicate substantially greater ET from M. giganteus compared to the other two crops, differences in magnitude may reflect limitations of the measurement approaches used, as well as somewhat different time periods of observation during the growing season. If the results of Hickman et al. (2010) are more accurate and representative, the impact of M. giganteus could reduce surface water flows in the region by 58%. In a modelling study of the Raccoon River watershed in Iowa, US, Schilling et al. (2008) estimated that converting corn–soybeans to perennial grasses would increase ET by 47 or 58 mm y 1, depending on whether warmseason or cool-season grasses were planted, and this would reduce annual
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water yields (annual stream flow per ha) by 46 and 54 mm y 1, respectively. Compared to a baseline water yield of 193 mm y 1, these values represent reductions in water yield of 24% and 28%, respectively. Modelling of warmseason grasses was based on characteristics of switchgrass, while cool-season grasses were modelled on the basis of fescue. M. giganteus was not modelled because of lack of information about its physiological characteristics (Schilling et al., 2008). Given the higher productivity of M. giganteus and the greater soil moisture depletion, as demonstrated by McIsaac et al. (in press), it seems reasonable to expect that conversion to M. giganteus could lead to greater reductions in water yield in Iowa than modelled by Schilling et al. (2008). B. NITRATE LEACHING
Christian (1994) and Christian and Riche (1998) reported that nitrate leaching losses from plots of M. giganteus grown in silty clay loam soil at Rothamstead Farm in the UK. Fertilizer treatments were 0, 60 and 120 kg N ha 1 y 1 applied in the spring. They measured soil water nitrate concentrations in water extracted using porous ceramic cups and estimated leaching from the drainage measured from separate soil monoliths during the dormant season. During the establishment year, they reported 154, 187 and 228 kg N ha 1 leached, respectively, from the 0, 60 and 120 kg N ha 1 fertilizer treatments (Christian, 1994; Christian and Riche, 1998). These high values were partly attributed to the prior cropping system, and to precipitation being 200 mm above average. In the second and third years of the experiment, precipitation was 37 mm above and 37 mm below normal, respectively, and the average nitrate leached in those 2 years was 5.5, 17.5 and 58.5 kg N ha 1 y 1. Christian and Riche (1998) reported that there were no biomass yield differences among the N fertilizer treatments. Thus, under optimal N management in that setting (0 N fertilizer), nitrate leaching appears to be relatively low. Christian and Riche (1998) used porous cup lysimeters to obtain soil solution nitrate concentrations and then estimated leaching flux by combining these concentration data with a separate measurement of drainage flux. Tension lysimeter data may not always reflect drainage water concentration, which adds uncertainty to the overall flux estimate; see Fares et al. (2009) for review. Curley et al. (2009) also used suction lysimeters to monitor nitrate concentrations in the soil under second and third year M. giganteus in Ireland that had been treated with cattle manure slurry with N rates of 0, 60 and 120 kg N ha 1 y 1. In the first year of their observations, they reported an increase in soil water nitrate with increasing N application rate, although
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mean concentrations were relatively low, ranging from 3.1 to 4.5 mg N l 1. During the second year of observations, concentrations were lower than in the first year and there was no statistical difference among the three original treatments. However, a fourth treatment was added (180 kg N ha 1) and the mean concentration in this treatment was statistically greater than the others (4.8 mg N l 1) (Curley et al., 2009). Curley et al. (2009) did not report on actual leaching losses or whether biomass yields were influenced by the different N treatments, nor did they indicate the portion of the manure N that was in an inorganic form when applied. If the quantity of drainage water was not affected by the treatments, then the quantity of nitrate leached would be proportional to the soil water nitrate concentrations. C. SUMMARY AND IMPLICATIONS FOR RESEARCH NEEDS
Empirical evidence from the central US, Germany and the UK indicates that ET from M. giganteus is greater than from typical annual crops and thus has the potential to reduce surface water flows and groundwater recharge where it replaces these annual crops on a large scale. A simulation study of the southern UK suggests that large-scale plantings of M. giganteus may result in a reduction of ET (and thus more groundwater recharge and surface flows) if it were to replace C3 grasses and annual crops. More work needs to be done to quantify water use of M. giganteus under a wide variety of conditions in order to establish relationships that will be useful for modelling the impacts in areas where production appears most economically feasible. It would also be useful to monitor the hydrology of small watersheds with substantial M. giganteus plantings, to verify the scaling up of models based on plot and field observations. Where M. giganteus can be grown with little or no N fertilizer, nitrate leaching losses will likely be low compared to crops such as maize that have a high N requirement. However, because M. giganteus is slow to establish, large losses of nitrate to leaching are possible during the establishment year, although the quantity will likely depend on weather and prior land use. More research is needed to quantify the N leaching and N2O emissions for a variety of N fertilizer rates and timings in settings where M. giganteus responds to N fertilizer application. Additionally, the possibility of using cover crops in the establishment year to minimize N losses without inhibiting M. giganteus establishment deserves investigation (Fig. 9). Miscanthus giganteus is also likely to sequester carbon, alter wildlife habitats and have other environmental consequences. Although M. giganteus provides an economic advantage by producing high biomass per unit area and per unit of water transpired, the environmental costs and
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benefits of large-scale plantings will depend on local conditions and the fraction of the landscape planted to M. giganteus. The relative costs and benefits of reduced surface water flows or nitrate leaching, or other effects will vary in different contexts. Landowners, policy makers and citizens need reliable and locally relevant information about these impacts in order to make informed decisions about land management and policy alternatives. Since these consequences may occur over decades, mechanistic models based on empirical research are needed to provide reasonable projections of the impacts in a wide range of settings.
VI. TECHNICAL CHALLENGES TO COMMERCIAL PRODUCTION Even though European researchers have studied M. giganteus as a biomass feedstock since the early 1980s, and Illinois researchers have studied its use since the early 2000s, barriers remain to the commercial production of the grass. Given that the biomass potential of M. giganteus is great for
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some temperate areas in North America, it is important that these hurdles be overcome in a timely fashion in order to avoid being unprepared should an energy crisis occur. These challenges occur in the grass’ propagation and establishment, agronomy, pest and pest controls, and genetics.
A. PROPAGATION, RHIZOME STORAGE AND ESTABLISHMENT
1. Propagation Because it is sterile, asexual propagation, such as rhizome divisions or micropropagation, must be used to multiply M. giganteus into commercial quantities. Overall, propagating this grass is a relatively simple horticultural exercise; conversely, propagating large commercial quantities is less so. Propagating M. giganteus using rhizome divisions entails separating a rhizome mass into small pieces for replanting. This can be done with potted plants growing in greenhouses and can also be conducted using field-grown plants. University of Illinois experience has determined that the potted M. giganteus can often be divided every 4–8 weeks (Pyter et al., 2009) when grown in greenhouses under 12 h per day artificial light during winter using 10 cm square pots and an artificial, soil-less potting mix. Small rhizome segments can also be used to produce plantlets or plugs by dividing rhizomes into very small, two-to-three node segments, potting the segments and growing these rhizome segments into small plants. This technique is being used commercially with success to produce large numbers of plants using relatively small amounts of rhizomes. This is a likely method for planting commercial acreages where irrigation or reliable natural precipitation is available to ensure that the small plants will become established (Fig. 10). Miscanthus giganteus rhizomes can also be field-planted, grown into established plants and harvested after one or two growing seasons. Mechanical rhizome lifters are available (e.g. Tomax, Ltd., Waterford, Ireland) which can be used to improve harvest efficiency and yields. By observation, most of the mechanically harvested rhizomes pieces are 10–25 g. Pyter et al. (in press) found that 20–25 g rhizome pieces produced statistically similar end-of-season biomass as rhizomes pieces of 40 g. Pyter et al. (2009) reported hand-harvested yields of 7–10 rhizome pieces from 1-year clumps and 25–30 rhizome pieces from 2-year clumps. Mechanical harvesting likely yields greater numbers of the smaller rhizome pieces. In 2010, a mechanically harvested 0.4 ha field of 1-year plants yielded enough rhizomes to replant approximately 3.6 ha, representing a ninefold multiplication factor (Pyter et al., in press).
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A
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Fig. 10. (A) Greenhouse grown ‘‘plug’’ of M. giganteus. (B) Field dug M. giganteus rhizome. Photo credits N. Boersma and E. Heaton, respectively.
Micropropagated M. giganteus plants are commercially available in the US, but are expensive. In addition, in Denmark and Clifton-Brown et al. (2007) in Ireland found that rhizome-produced M. giganteus plants survived the first winter, while plants directly regenerated using micropropagation died the first winter after planting (Clifton-Brown, 1997). 2. Rhizome storage Currently, research is being conducted in Illinois in an attempt to identify the physiological condition of rhizomes necessary for survival. In one Illinois study, Pyter et al. (in press) found that rhizomes can be successfully stored at 4 8C for up to 4 months in moist sand. In an ongoing 2010 study, rhizomes have been shown to require a moisture content of at least 50% to regrow after planting. When improperly stored, rhizomes can dry below this level and not survive planting. Additional work is being conducted to measure carbohydrate levels within rhizomes harvested at different times of the year to identify conditions that can limit establishment success. 3. Planting and establishment Mechanical nursery or vegetable transplanters have been successfully used to plant M. giganteus rhizomes and plugs. Rhizomes planted to 10 cm produced the greatest amount of biomass at the end of the first season’s growth
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in Illinois (Pyter et al., in press). Planting densities have varied, with successful plantings occurring at densities of 10,000–12,000 ha 1 (Pyter et al., 2009). As small rhizome segments and plugs are used, planting densities may increase to 20,000–25,000 ha 1 to reduce gaps in plantings due to low rhizome emergence rates. Emergence rates have ranged from as low as 50% to 98% depending on rhizome size and storage conditions (Huisman and Kortleve, 1994) in Europe. Pyter et al. (2009) reported 60–70% of the rhizomes sprouting in an Illinois planting. Plugs comprising small plants, growing in a small amount of horticultural potting mix can be produced using micropropagated plantlets, rhizome pieces or rooted stem cuttings and can be an outstanding substitute for planting rhizomes (Atkinson, 2009). The main limitation to planting plugs is the probable need for irrigation during establishment. Plugs can be well established and relatively drought-tolerant in less than a growing season, but during the establishment period, a prolonged period of droughty weather can compromise plug survival without the availability of water to supplement natural precipitation. While established M. giganteus have survived winter air temperatures as low as 208 C in Illinois (Pyter et al., 2009), there have been situations where first year M. giganteus crops have been damaged or killed during the first winter after planting. Clifton-Brown and Lewandowski (2000a) and CliftonBrown et al. (2001a) reported that M. giganteus, especially first year plantings, is at risk when soil temperatures at 5 cm drop below 3 8C. During the 2008–2009 winter, 2008 plantings in portions of the US Midwest were severely damaged; 6.5 ha in Illinois were thinned during that winter to the degree that the replanting was necessary. Concerns over first year winter damage can obviously limit where M. giganteus can be commercially produced. In December 2009, in a Decatur, Illinois, US demonstration planting, daily soil temperatures at a 5-cm depth were as much as 4 8C colder under first year plants than under third year plants. A small, little-developed rhizome mass, along with virtually no insulating leaf litter on the soil surface may combine to explain the susceptibility of winter damage in first year plants. Also, Lewandowski (1998) speculated that M. giganteus is more tolerant of cold when the temperature decline is slow and steady, rather than sudden. She also indicated that cold damage may occur when temperatures vary above and below freezing, writing that M. giganteus may sprout during warm stretches, only to be damaged when temperatures drop, because it is susceptible to cold damage (Lewandowski, 1998). These hypotheses require further study for confirmation. Commercial barriers caused by a lack of propagation and planting information or by inconsistent research findings require that additional work be
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completed prior to successful large-scale planting. Research that identifies efficient methods and equipment designed for low-cost propagation and planting with guaranteed establishment are necessary prior to commercial acceptance of M. giganteus as a biomass feedstock.
B. AGRONOMY
1. Fertility It is not clear whether fertilizer applications will increase the harvestable yields of M. giganteus (Heaton et al., 2010; Miguez et al., 2008). Experiments in Europe have shown contrasting responses of M. giganteus to N fertilizer. For example, in Austria, Schwarz et al. (1994) reported an increase of only 1 Mg ha 1 in dry biomass (from 20.6 to 21.6 Mg ha 1) with an increase in N level from 0 to 180 kg N ha 1 in a 3-year-old crop. However, the authors hypothesize that because the soil had a high capacity for nutrient delivery, the lack of N response can be attributed, at least in this case, to the combined effect of optimal initial nutrient supply and the fact that only the second and third growing seasons were reported (Schwarz et al., 1994). Similarly, in Germany, Himken et al. (1997) did not observe a significant N fertilization effect on above-ground or rhizome dry biomass, possibly because the soil supplied the N needed for the yield levels at this location. Moreover, this study measured above-ground biomass as well as belowground biomass and showed that the rhizome biomass can exceed 15 Mg ha 1 for a crop that achieved a peak dry biomass of 30 Mg ha 1 in September (Himken et al., 1997). Finally, at Rothamsted Research Farm, in England, biomass yields from a 14-year planting of M. giganteus did not respond to N application (Christian et al., 2008). The authors wrote that this was likely the result of the soil type at the research site, the management of the previous crop produced on the research site and the efficient resource utilization of the C4 grass including the natural recycling of N and other minerals within the plant. Conversely, increasing levels of nitrogen increased yields in an Italian study (Ercoli et al., 1999). These authors found an interaction between irrigation and N fertilization. With 100 kg N ha 1 of fertilizer, irrigation increased dry biomass by 3.7 Mg ha 1, and with 200 kg N ha 1, irrigation increased dry biomass by 9.8 Mg ha 1. Other minerals may play a role in M. giganteus biomass yields. In a 15-year M. giganteus study in Ireland, Clifton-Brown et al. (2007) showed an increased yield with nitrogen in some years, but not in others. This study also showed a yield increase with an application of K, indicating the need to study fertilization regimes beyond nitrogen.
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Given the inconsistent results of these studies, a simplistic explanation of M. giganteus response to fertilizer remains difficult. It is likely that the response of M. giganteus to fertilization is due to the interactions of weather conditions, soil type and agronomic management. Thus, yield response to fertilization may change from field to field or even change within the same field from year to year. Moreover, predicting an exact response of M. giganteus to fertilization is also difficult, making it problematical for agronomists to make accurate fertilization recommendations when managing M. giganteus. 2. Weeds, insects and diseases in M. giganteus a. Weed control. Weed control during the first year, and sometimes the second year, is necessary to produce a successful M. giganteus crop (Christian and Haase, 2001; Lewandowski et al., 1995, 2000). Several researchers have evaluated post-planting tillage and cover crops as weed controls with varying success (Buhler et al., 1998; Bullard et al., 1995; Schwarz et al., 1994; Venturi et al., 1999). More consistent weed control, however, is likely to be accomplished through the use of herbicides. Unfortunately, the herbicides registered for M. giganteus are limited to applications to landscape ornamentals. Both pre-emergence and post-emergence herbicides have been used in Europe; researchers generally found that herbicides that are safe for application to corn can be safely applied to M. giganteus (Bullard et al., 1995; Serafin and Ammon 1995, as cited in Lewandowski et al., 2000). Buhler et al. (1998) reported that metolachlor appeared to be safe on various warm-season perennial grasses, and Huisman et al. (1997) recommended applications of atrazine to control weeds. In Illinois experiments that applied herbicides at typical corn rates, Pyter et al. (2009) reported that M. giganteus was tolerant of pre-emergence applications of pendimethalin, pendimethalin þ atrazine, S-metolachlor and S-metolachlor þ atrazine, and post-emergence applications of 2,4- D ester and dicamba. More recently, Anderson et al. (in press) found in field studies that herbicides, in general, that are applied to control weeds in maize were safe to apply to M. giganteus and included atrazine, pendimethalin and S-metolachlor applied as pre-emergence herbicides, and bromoxynil, dicamba and mesotrione þ atrazine applied as post-emergence herbicides. b. Insect and disease control. Huggett et al. (1999) found that the corn leaf aphid (Rhopalosiphum maidis) survived, was highly fecund and able to transmit barley yellow dwarf virus (BYDV) which is a concern because Miscanthus spp. can carry the virus with or without showing symptoms.
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In the US, Bradshaw et al. (2010) also reported corn leaf aphid and yellow sugarcane aphid (Sipha flava) on field-grown M. giganteus in four states. Christian et al. (1997) observed larvae of the common rustic moth (Mesapamea secalis) feeding on M. giganteus tissues in the spring, but harvestable stem density did not appear to be affected. In Illinois, Spencer and Raghu (2009) reported M. giganteus to be a site of oviposition and emergence of the Western Corn Rootworm (Diabrotica virgifera virgifera), a major pest of maize. Finally, Prasifka et al. (2009) noted that fall armyworm (Spodoptera frugiperda) infested field plots of M. giganteus and fed on its leaves in laboratory studies. While Christian and Haase (2001) report that no diseases greatly affect M. giganteus production, several pathogens have been found on the grass. Fusarium spp. (Thinggaard 1997, as cited in Lewandowski et al., 2000), BYDV (Bullard et al., 1995; Christian et al., 1994) and Miscanthus blight (Leptosphaeria spp.) (O’Neill and Farr, 1996) can affect M. giganteus. At several Midwestern US sites, nematodes, including two species of Xiphinema and one species of Longidorus (Longidorus breviannulatus), were found in soils surrounding M. giganteus roots (Mekete et al., 2009). They also reported that great numbers of L. breviannulatus appeared to destroy fibrous roots and stunt lateral roots (Mekete et al., 2009). Ahonsi et al. (2010) reported occurrences of the leaf blight, Pithomyces chartarum, in Kentucky.
3. Harvesting technology At the conclusion of the growing season, M. giganteus usually drops most of its leaves as it senesces, and the senesced stems are typically harvested during the winter, from November through the end of March in temperate areas, depending on snow cover and access to fields. US companies are evaluating different equipment for cutting, conditioning, windrowing and baling the stems to determine efficient and effective methods. Traditional hay equipment works, but it is a slow process given the toughness and large number of harvestable stems. The harvest goal is to cut at 5–10 cm, but in past evaluations, some ill-suited equipment left M. giganteus stems of more than 30 cm. Leaving biomass in the field unharvested is a concern that equipment manufacturers must consider; more than 2 t ha 1 of biomass remained in an Illinois field following a 2010 harvest. Baling machines have successfully produced variously sized round and rectangular bales of M. giganteus in the past. Moisture levels of the biomass tend to vary with harvest time. Heaton (2006) reports moisture levels from 50% in an October harvest down to less than 10% in a February harvest. Under cover, the stored bales have remained intact and in good
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condition for at least 3 years without excessive breakdown or attracting rodent or insect pests. Existing technology allows M. giganteus to be cut, baled and stored for later use. At present, however, the challenges to commercial production are the inefficiencies of equipment designed for hay and straw crops, not for heavier-stemmed biomass crops. It is very likely that technology that combines woody plant harvest with hay and straw crop harvest will be suitable for biomass crops. 4. Eradicating M. Giganteus Eradicating M. giganteus in order to convert a planting to another biomass feedstock or to a row crop has also been studied. Anderson (2010) found that tillage combined with glyphosate applications can control mature M. giganteus, but treatments will likely need to be repeated in a second growing season for complete eradication. In another experiment, Anderson et al. (2010) examined planting glyphosate-resistant soybeans directly into a mature stand of M. giganteus and found that soybean yield was not reduced when either one or two sequential glyphosate applications were made in-crop compared with a weed-free control. The following year, this field was rotated into glyphosate-resistant corn, and corn yields were similar to the weed-free control following one or two sequential applications of glyphosate. While glyphosate applications kept the M. giganteus from reducing yields, Anderson (2010) speculated that it will likely take more than two growing seasons to completely eradicate the biomass grass. Overcoming agronomic challenges are paramount to successful commercial production of M. giganteus. Some of this research will be, by necessity, local and continuous, given the probability of local responses to fertility and pest problems, along with the evolution of pests and Miscanthus genetics. Improved harvesting technologies, however, are likely to be useful throughout the entire geographic area where M. giganteus is commercially grown. C. NEW VARIETIES
The M. giganteus clone used in University of Illinois feedstock research originated from rhizomes obtained from the Chicago Botanic Gardens (Glencoe, Illinois) in 1988 (Pyter et al., 2009) and has been part of a landscape demonstration planting at the University since that time. In addition to this common landscape clone, there are other M. giganteus types being developed and marketed specifically for biomass production. For example, ‘Freedom’ Giant Miscanthus was developed at Mississippi State University and is being produced for commercial planting by SunBelt Biofuels (http://
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www.extension.org/pages/‘‘Freedom’’_Giant_Miscanthus_is_Viable_ Biofuel_Feedstock; http://www.biomassmagazine.com/article.jsp?article_ id¼3536). New Energy Farms of Canada (http://www.newenergyfarms.net/ pricing.aspx) lists ‘Amuri’ and ‘Nagara’ as very cold-tolerant, high-yielding Miscanthus. Biotechnology firms such as Ceres, Inc. and Mendel Bioenergy Seeds are evaluating additional forms of Miscanthus to determine biomass potential. Additional M. giganteus genotypes present growers with options when producing this crop that will allow for selection from a pallet of grasses for different locations and environments in order to produce the most productive and least input-dependent grass for an area. Moreover, it is likely that additional genotypes will be developed in the future, which offers additional opportunities to fine-tune planting choices such as disease and/or insect resistance. The barrier to commercial production of these new genotypes is the need to conduct research so that agronomists can direct growers to make the best choices for a biomass production scheme.
ACKNOWLEDGEMENTS This work was primarily supported by the Illinois Council on Food and Agriculture Research (Award 04-SRI-036). Additional support was provided by the Energy Biosciences Institute at the University of Illinois and the Iowa State University Department of Agronomy. The authors thank Dustin Schau for reviewing this manuscript.
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AUTHOR INDEX
A Abdin, M.Z., 35 Abdollahian-Noghabi, M., 31 Acaroglu, M., 87, 89 Adams, A., 61 Adati, S., 102 Aebersold, R., 26 Aghaei, K., 35 Agindotan, B.O., 122 Ahmad, J., 1 Ahn, S.N., 51–52 Ahonsi, M.O., 122 Ahsan, N., 21, 35 Aiking, H., 77 Aitken, W.M., 51 Aksoy, A.S., 87, 89 Alabady, M.S., 109 Alam, I., 35 Allan, J.D., 79 Allen, R.D., 104 Altman, A., 34 Amabile, I., 51, 54, 65 Amarawathi, Y., 64 Amiour, N., 21 Ammon, H.-U., 121 Anders, I., 29 Anderson, E.K., 123 Anderson, J.L., 79 Andersson, B., 84, 88–89, 96, 100–101, 108 Andow, D.A., 78 Ane´, J.M., 20 Appel, R.D., 24 Archontoulis, S.V., 89 Arikit, S., 66, 68 Arrese-Igor, C., 4, 19–20, 24, 27, 31–33 Arundale, R., 122 Asamizu, E., 33 Asbjornsen, H., 78–79 Askari, H., 31 Atkinson, C.J., 119 Aurisano, N., 63 Ausili, P., 35 Ausubel, F.M., 12 B Baba, S., 60 Bairoch, A., 7 Baker, J.D., 60 Baker, J.M., 78 Baker, N.R., 98
Bal, A.K., 11 Balakrishna Rao, M.J., 51 Balestrasse, K.B., 35 Baliga, N.S., 24 Bancel, E., 30 Banse, M., 77 Barbour, W.M., 8 Barney, J.N., 89 Barriere, Y., 104 Basch, G., 84, 88–89, 96, 100–101, 108 Bashir, H., 1 Batlle, A., 35 Batut, J., 13 Bauer, W.D., 9 Baxter, L.L., 77, 86 Beale, C.V., 86–91, 95–96, 98, 100–101, 112 Becana, M., 27, 29–30 Beckman, J.F., 77 Belanger, L., 14 Belau, L., 101 Ben Hamida, J., 30 Bennett, M.D., 82, 102 Benson, D.R., 4 Bergman, C., 60 Bernacchi, C.J., 113 Bertagnoli, S., 13 Bertani, A., 63 Bestel-Corre, G., 4, 21, 32 Beuch, S., 92, 101 Bierczynska-Krzysik, A., 22 Billinghurst, Z., 34 Bint, D.A., 91 Binversie, B.N., 81 Birur, D.K., 77 Bisseling, T., 7–8, 10–13 Bittencourt-Silvestre, J., 10 Blade, S.F., 27 Blanco-Canqui, H., 79, 111 Blowers, D., 98 Bocquet, S., 10–11 Bodulovic, G., 21 Bodzon-Kulakowska, A., 22 Boehmel, C., 88 Boelcke, B., 92, 101, 112 Boersma, N.N., 75, 120 Boguth, G., 14 Boistard, P., 13 Bollero, G.A., 82, 85, 89, 92, 94, 96, 100, 120, 123 Bollich, C.N., 51–52 Bonari, E., 89, 120
140
AUTHOR INDEX
Boncompagni, E., 33 Bonta, D., 77 Boody, G., 78 Boote, K., 94 Borisov, A., 35 Bouchet, G., 24 Bourgis, F., 51, 54, 65 Bowler, C., 30 Bradbury, L.M.T., 51–52, 55, 59–60 Bradley, C.A., 122 Bradshaw, J.D., 122 Braga, D.P.V., 102 Brancourt-Hulmel, M., 85–86 Branlard, G., 30 Brauner, F., 60 Brears, T., 13 Breuer, J., 85–88, 92, 94, 100, 118, 120 Brewin, N.J., 10–11 Bright, N.A., 7 Britovsek, G., 95 Brooks, L.O., 69 Broughton, W.J., 7–8 Brown, L.R., 26 Brown, R.C., 77 Bruschi, M., 24 Brushett, D.J., 59–60 Bryant, R., 60 Buck, M., 12 Buech, S., 112 Buer, C.S., 3 Buhler, D.D., 121 Bullard, M.J., 121–122 Bullock, D.G., 78 Butardo, V.M., 52, 64–65, 69 Buttery, R.G., 51 C Caetano-Anolle´s, G., 9 Cairney, J., 95 Calingacion, M.N., 52, 64–66, 69 Camut, S., 10, 12 Candiano, G., 24 Carnemolla, B., 24 Carpita, N.C., 104 Casler, M.D., 113 Caveny, J.D., 120 Cesco, S., 3 Chang, J.L., 62–63 Chang, Y.F., 55 Charles, T.C., 14 Chase, M.W., 81–82, 102–103, 108 Chen, F., 105 Cheng, Z., 54–55, 58–59 Chen, H.C., 21, 32 Chen, J., 110 Chen, S., 51–52, 54–55, 58–59 Chen, Y.X., 35 Cheon, C.I., 11
Chiang, Y.-C., 84, 108 Choonvisase, S., 51 Choudhary, D., 51 Christian, D.G., 84–85, 88–89, 91–92, 96, 100–101, 108, 112, 114, 120–122 Christou, M., 85, 91 Chuang, H.S., 62–63 Chubatsu, L.S., 4 Claassen, P.A.M., 105 Clark, D.B., 112 Claupein, W., 88 Clayton, W.D., 81–82, 102 Clemente, M.R., 27, 29–30 Clement, M., 33 Clifton-Brown, J.C., 78, 82–94, 96, 99–101, 108, 118, 120–122 Cobbett, C.S., 35 Colasanti, J., 104 Colebatch, G., 4 Condon, A.G., 95 Conger, B.V., 84 Cook, D.R., 10 Coon, J.J., 20 Cooper, J.E., 8 Copani, V., 87, 89 Cordi, B., 34 Coruui, G.M., 13 Cosentino, S.L., 87, 89 Costanza, R., 78 Costello, P.J., 51, 63 Cottrell, J.S., 26 Crawford, J., 102–103, 109 Creasy, D.M., 26 Crow, T.R., 78–79 Crozat, Y., 78–79, 87, 89 Curley, E.M., 114–115 Czypionka Krause, U., 90 Czypionka, K.U., 86, 88, 100–101, 120 D D’Agosta, G.M., 87, 89 DaGue, B.B., 20 Dailey, A.G., 89, 112 Dainese, P., 34 Dale, B.E., 77 Dalton, D.A., 27, 29–30 D’Amici, G.M., 14–15 Danalatos, N.G., 89 Da Re, S., 13 Das, A.K., 35–36 Datta, S.K., 104 Daveran-Mlngot, M.L., 13 David, G., 21 David, M.B., 13, 75, 113–114, 116 Davies, B.W., 8 Davies, H.N., 112
AUTHOR INDEX Davison, B., 95 Davis, S.C., 79, 94, 101 Day, D.A., 11 Deakin, W.J., 7–8 Debelle´, F., 10 de Billy, F., 10, 12, 31 Debreczeny, M., 7 de Bruijn, F.J., 13 de Bruxelles, G., 33–35 Deb, S.K., 114 Dedieu, A., 13 de Haas, G.G., 105 De Kimpe, N., 61 de-la-Pen˜a, C., 27 de la Pen˜a, T.C., 35 Delgado, J., 60 Del Grosso, S., 79, 94, 101 Delhaize, E., 36 Delseny, M., 51, 54, 65 DeLucia, E.H., 79, 94, 101 De Maagd, R.A., 12–13 Demirevska, K., 29 De´narie´, J., 10 Den Herder, G., 10 Den Herder, J.D., 3, 8, 10 Dennls, E.S., 14 De Paoli, E., 109 Depledge, M.H., 34 Desbrosses, G., 4 Deschenes, L., 77 Deslandes, L., 10 de Tourdonnet, S., 78–79, 87, 89 Deuter, M., 82, 108 de Vrije, T., 105 D’Haeze, W.D., 8, 19 Dhulappanavar, C.V., 51 Diaz, C.L., 9 Dietz, S., 79 Dietz, W.B., 4 Dimmick, K.A., 14 Ditomaso, J.M., 89 Ditta, G.S., 13 Dixon, R.A., 26–27, 105 Djordjevic, M.A., 3–4, 21, 27 Djordjevic, N.A., 4, 37 Dohleman, F.G., 75, 77–79, 84–86, 88–91, 94–95, 98–99, 101, 105, 113, 117, 119–121, 123 Domergue, O., 13 Dornburg, V., 77 Douglass, G.K., 78 Drabik, A., 22 Drukier, A.K., 26 Duffy, M.D., 78–80 Dumas-Gaudot, E., 4, 21, 32 Dunau, M.L., 23 Duncan, D.R., 111 Dunn, M.J., 14–15
Dupraz, C., 78–79, 87, 89 Dylag, T., 22 E Eckert, C., 95 Edidi, M.G., 33 Edwards, A., 10 Ehlke, N.J., 91 Ehrendorfer, K., 120–121 Ehsanpour, A.A., 35 Elmer, A.M., 26–27 Emerich, D.W., 11 Engler, D., 110 Ercoli, L., 89, 120 Eriksson, M.E., 104 Evett, S.R., 89 F Faaij, A.P.C., 77, 81, 85 Fagioni, M., 15 Fales, S.L., 81 Fang, T., 63 Farage, P.K., 98 Farber, S.C., 78 Fares, A., 114 Fares, S., 114 Fargione, J., 77 Farkas, A., 7 Farr, D.F., 122 Farrell, A.D., 91 Fedorova, E., 7 Fellay, R., 7 Feller, U., 29 Ferguson, P.L., 26 Fernandez, F.G., 82, 96, 100 Fester, T.M.K., 32 Fike, J.H., 84 Filiault, D.L., 91 Finch, J.W., 90, 112–113 Fischer, H.M., 12 Fitzgerald, M.A., 52, 64–66, 69 Fitzgerald, T.L., 51–52, 55, 59, 69 Flavell, R.B., 77 Fleming, J.S., 14 Forde, B.G., 13 Forde, S.M.D., 122 Fortin, M.G., 11 Fourment, J., 13 Foussard, M., 13 Foyer, C.H., 30 Franssen, H., 13 Frederick, W., 95 Freeman, J., 13 Freiberg, C., 7 Fuchs, D.J., 79 Fujimoto, S.Y., 13
141
142
AUTHOR INDEX
Fukushima, R.S., 105 Fushimi, T., 51–52 G Gallego, S.M., 35 Gallwitz, D., 11 Galuszka, P., 60 Gamas, P., 31 Ganapathy, A., 20 Gao, F., 55, 69 Garcı´a de la Torre, V.S., 35 Garnerone, A.M., 13 Gassman, P.W., 78, 113–114 Gavin, A.C., 24 Gehlenborg, N., 24 Geiger, O., 10 Geurts, R., 8, 10 Gezan, S.A., 89, 112 Ghai, J., 13 Gherbi, H., 51, 54, 65 Ghesquie`re, A., 51–52, 54, 62, 64–65 Ghiggeri, G.M., 24 Gianinazzi-Pearson, V., 21 Gianinazzi, S., 4, 21 Gigler, J.K., 121 Gilles-Gonzalez, M.A., 13 Gillies, S.A., 59–60 Glaszmann, J.C., 64 Gleason, C., 10 Glebov, O.O., 7 Glendining, M., 94 Gloudemans, T., 13 Glushka, J., 10 Godiard, L., 10 Godovac-Zimmermann, J., 26 Goesmann, A., 24 Gohringer, F., 79 Goldman, D., 23 Goldsbrough, P., 35 Gonza´lez, E.M., 4, 19–20, 24, 27, 31–33 Goonewardene, L., 27 Goormachtig, S., 3, 10 Goosen-De Roo, L., 12–13 Go¨rg, A., 14–15 Gosh, A.K., 35–36 Goufo, P., 52 Gough, C., 10 Govers, G., 13 Grabber, J.H., 104 Graham, M.A., 3 Graham, P.H., 3 Gray, M.E., 92, 94, 122 Greef, J.M., 82, 108 Greene, N., 113 Gresshoff, P.M., 9 Griffitts, J., 7 Grill, E., 35 Grimm, C.C., 60
Grimsrud, P.A., 20, 32 Grunenberg, B., 13 Guerreiro, N., 4, 37 Guiderdoni, E., 51–52, 62, 64 Gunes, A., 35 Gupta, D.K., 65 Gusslin, G.N., 12 Guyot, R., 51, 54, 65 H Haase, E., 91–92, 121–122 Hager, A.G., 123 Hajheidari, M., 31 Hakura, A., 102 Hallett, J., 95 Hall, P.J., 21 Hall, R.L., 112 Hamilton, N.R.S., 52, 64–65, 69 Handy, R.B., 34 Haney, C.H., 7–8 Hanson, A.D., 60, 89 Harder, A., 14 Harman, K.T., 81–82 Hartley, R.D., 104 Hartzler, R.G., 121 Hashizume, K., 52 Hastings, A., 85–86, 90–93 Hatfield, J.L., 80 Hatfield, R.D., 105 Hattermann, D.R., 8 Havlis, J., 60 Hawthorne, P., 77 Hayata, Y., 52 Hay, R., 95 Heath, M.C., 121–122 Heath, R.R., 60 Heaton, E.A., 75, 77–78, 84–89, 91, 95, 98–99, 101, 112, 117, 119–123 He, F., 54–55, 58–59 Hein, N.L., 52 Heinz, A., 100–101 Hellnski, D.R., 13 Henry, R.J., 51–52, 55, 59–60, 69 Henschke, P.A., 51, 63 Herbert, B., 21 He´rouart, D., 10–11, 33 Hertel, T.W., 77 Hertig, C., 13 Herve´, C., 10 Herwaarden, A.F.V., 95 Hess, J.R., 81 He, Y.F., 35 Hibbs, M.A., 24 Hibino, T., 60 Hickman, G.C., 113 Higgins, J., 32 Higgins, T.J.V., 21 Hill, J., 77
AUTHOR INDEX Himken, M., 86, 88, 90, 100–101, 120 Hirata, Y., 52 Hirayoshi, I., 102 Hirsch, A.M., 10 Hitz, W.D., 89 Hocart, C., 4 Ho, C.T., 62–63 Hodkinson, T.R., 81–82, 84, 102–103, 108 Hofmann, T., 63 Hohfeld, I., 30 Ho, I., 109 Holesters, M., 3, 8, 10, 19 Holmes, L.B., 110 Hong, Z., 11 Hontelez, J., 12–13 Hoogland, C., 24 Hooymans, J., 13 Hopkins, A.A., 84 Horvath, B., 12–13 Ho, S.C., 10 House, J., 94 Howell, T.A., 89 Huang, N., 51–52, 62, 64 Huang, T.C., 62–63 Huang, W., 55, 69 Huang, Y., 4 Huang, Z.L., 51 Huggett, D.A.J., 121 Huggins, D.R., 79 Huisman, S.A., 119 Huisman, W., 82–83, 85, 87, 89, 91, 101, 121–122 Hulke, B.S., 91 Humphries, S., 92, 94 Huo, H., 77 Huong, N.T.T., 66, 68 Hussey, M.A., 84 I Imin, N., 3 Inal, A., 35 Inatomi, H., 60, 62 Innes, R.W., 19 Invitti, A.L., 4 Inze, D., 30 Iqbal, M., 1 Ishihara, H., 7 Ishii, T., 60 Ishikawa, H., 60 Israelsson, M., 104 Itani, T., 52 Ivanov, S., 7 Izmailov, S.F., 12 J Jacobsen-Lyon, K., 14 Jacobsen, S., 60
Jacobs, J., 13 Jakob, K., 89 James, L.K., 79 James, P., 34 Jamet, A., 10 Jarzebinska, J., 22 Javed, S., 35 Jenkins, B.M., 77, 86 Jensen, E.O., 14 Jha, M.K., 78, 113–114 Jin, Q., 51–52, 55, 59 Ji, Q., 54–55, 58–59 Jodon, N.E., 51 Joergensen, J.E., 14 Johnson, M.V.V., 113 Jones, C.S., 80 Jones, J., 94 Jones, K.M., 8 Jones, M.B., 78, 81–89, 91–94, 96, 100–101, 118, 120 Jorgensen, U., 83–85, 88–89, 92, 94, 96, 100–101, 108 Juhasz, A.L., 35 Juliano, B.O., 51 Juliano, O.B., 51 Jung, C., 108 Jung, H.-J.G., 78 Junk, W.J., 95–96 Juvik, J.A., 75, 102–103, 105, 109–111 K Kabaki, N., 63 Kadam, B.S., 51 Kahle, P., 92, 101 Kahn, D., 13 Kalo, P., 10 Kamolsukyunyong, W., 52, 54–55, 59 Kannenberg, E.L., 11 Kardailsky, I., 13 Kato, H., 50–51 Kato, R., 102 Kav, N.N.V., 27, 31, 33 Kawamitsu, Y., 60 Keijsers, E.R.P., 105 Keim, P., 102 Kellogg, E., 96 Kennedy, E.P., 10 Kent, A.D., 79, 94, 101 Kevei, Z., 7 Khush, G.S., 64 Kicherer, A., 86, 100, 121 Kijne, J.W., 9 Kilpatrick, J.B., 121–122 Kim, H.S., 77, 109–111 Kim, K.-H., 35 Kim, S., 77 Kiniry, J.R., 113 Kinnersley, A.M., 63
143
144
AUTHOR INDEX
Kitagawa, M., 102 Kitano, H., 24 Kjeldsen, J.B., 84, 88–89, 96, 108 Klassen, G., 4 Klausa, D., 10 Kleiner, O., 26 Klipp, W., 13 Knops, J.M.H., 78 Kobayashi, H., 8 Kohlbacher, O., 24 Komatsu, S., 21, 35 Kondorosi, E., 32 Kortleve, W.J., 119 Kovach, M.J., 65–66 Krey, R., 13 Krinke, M., 78 Kropff, M.J., 94 Kubien, D.S., 97 Kunert, K.K.J., 30 Kurata, T., 50–51 L Ladrera, R., 4, 19–20, 24, 27, 31–33 Laessing, U., 7 Lafferty, J., 102 LaHood, E.S., 102 Lambert, A., 33 Lammel, J., 86, 88, 90, 100–101, 120 Lamptey, J.N.L., 122 Lanceras, J.C., 51 Langeveld, H., 77 Lapierre, C., 104 Larrainzar, E., 4, 19–20, 24, 27, 31–33 Laser, M.S., 113 Laurans, M., 78–79, 87, 89 Laursen, N.G., 13 Laver, D., 33–35 Leak, D., 95 Leakey, A.D.B., 91, 98 Leather, S.R., 121 Lee, B.-H., 35 Lee, D.-G., 35 Lee, H., 35 Lee, K.-W., 35 Lee, N.G., 11 Lee, S.-H., 35 Lefebvre, B., 10 Leinweber, P., 92, 101 Leitch, I.J., 82, 102 Lei, Z., 26–27, 36 Lelley, T., 102 Lenandair, M., 30 Lenogue, S., 21 Lerouge, P., 10 Lesage, P., 77 Levasseur, A., 77 Lewandowski, I.M., 82–93, 96, 99–101, 108, 119, 121–122
Lewis, R.D., 34 Liebhard, P., 120–121 Liebman, M., 78–79 Lievens, S., 3 Limpens, E., 7 Li, M.R., 96–97 Lin, D., 26 Lindblad, P., 35 Linde-Laursen, I., 82, 103 Lindvall, E., 85, 91 Ling, L.C., 51 Liotta, C., 95 Lisacek, F., 24 Liu, S., 78 Liu, X., 54–55, 58–59 Liu, Y., 55, 69 Lledo, M.D., 81, 102–103, 108 Loh, J., 12, 14 Londo, M., 77 Long, S.P., 75, 77–78, 84–92, 94–101, 112, 117, 119–121, 123 Long, S.R., 7 Lorieux, M., 51–52, 54, 62, 64–65 Lottspeich, F., 7 Louis, C.F., 11 Lozovaya, V., 75 Lozovaya, V.V., 75, 105 Lu, B.-R., 55, 69 Lucas, M.M., 35 Luche, S., 23 Ludwig, L., 77 Lugtenberg, B.J.J., 9–10, 12–13 Lunardi, J., 23 Luo, D., 55, 69 Luo, Y.M., 35 Luo, Z.K., 79 Lu, T., 55, 69 Luxhoi, J., 105 Lygin, A.V., 105 Lynd, L., 113 Lyshede, O.B., 105 M Maga, J.A., 50–51 Magid, J., 105 Mahato, A.K., 65 Maj, D., 3 Ma, J.F., 36 Majoul, T., 30 Makowski, D., 78–79, 87, 89 Malezieux, E., 78–79, 87, 89 Malik, S.A., 9 Ma, L.Q., 35 Mandal, M., 35–36 Mandal, S.M., 35–36 Mann, M., 26 Mantineo, M., 87, 89 Marcker, K.A., 13–14
AUTHOR INDEX Marek-Kozaczuk, M., 3 Margni, M., 77 Mariotti, M., 89, 120 Marsh, J., 10 Marsh, T.J., 112 Ma˜rtensson, A., 35 Mascia, P.N., 77 Masoni, A., 89, 120 Mastronunzio, J.E., 4 Masuda, R., 51 Matamoros, M.A., 27, 29–30 Mathesius, U., 4–5, 32, 35 Matsuda, N., 60 Matvlienko, M., 13 Mbengue, M., 10 McCarthy, S., 84 McClelland, C.A., 51 McCouch, S.R., 51, 65–66 McDonnell, K.P., 114–115 McIsaac, G.F., 75, 113–114, 116 McLaughlin, S.B., 84 McMillan, J.D., 105 McMullan, L.D., 80 Meagher, R.L., 122 Meeusen, M., 77 Mekete, T., 92, 94, 122 Mellor, R., 6 Mendes, P.J., 26–27 Meng, Y., 60 Mergaert, P., 19 Merrick, M.J., 12 Merril, C.R., 23 Mew, T., 51 Meyers, B.C., 30 Miao, G.-H., 11 Mielenz, J., 95 Miguez, A.F., 75 Miguez, F.E., 85, 89, 92, 94, 120 Mikulass, K., 7 Miles, T.R., 77, 86 Millar, J.G., 60 Mitchell, C.A., 113–114, 116 Mitchell, C.P., 85–86, 90–93 Mitchell, R.B., 79 Mitra, R.M., 10 Mitsios, I., 89 Moerman, M., 13 Mohan, D., 77 Mohapatra, T., 64 Molenaar, J., 101, 121 Monson, R.K., 96–97 Montagu, M.V., 30 Monteiro, R.A., 4 Monti, A., 90 Mooney, B., 20 Moore, A., 21 Moose, S.P., 97 Morcillo, C.N., 35 Moreau, S., 10
145
Morett, E., 12 Morey, V.R., 78 Morison, J.I.L., 89–90, 96, 112 Moritz, T., 104 Mortensen, J.V., 84, 88–89, 96, 108 Mostaguir, K., 24 Mozaffarian, H., 77 Muenchbach, M., 34 Muhs, H.-J., 108 Mulders, I.H.M., 12–13 Muneer, S., 1 Murphy, R., 95 Musante, L., 24 Mylona, P., 11–12 N Nagaraj, S., 36 Nagaraju, M., 51 Nagoshi, R.N., 122 Nagsuk, A., 51 Nagy, A., 7 Naidu, S.L., 97 Naivikul, O., 51 Nakamura, M., 50–51 Nakamura, Y., 33 Nakano, M., 30 Nap, J.-P., 11 Narberhaus, F., 34 Natera Guerreiro, N., 27 Natera, S.H.A., 4, 37 Nath, S., 35 Nehls, U., 79 Neilson, B., 84, 87, 92–93 Nelson, E., 77 Nelson, W.W., 79 Netzer, D.A., 121 Neukirchen, D., 86, 88, 90, 100–101, 120 Neumann, G., 3 Neumann, J., 77 Neuweger, H., 24 Newcomb, W., 10 Nguyen, H.T.T., 60, 62–63 Niblack, T.L., 92, 94, 122 Nichols, B.J., 7 Nishikawa, K., 102 Nishiwaki, A., 82, 96, 100 Niu, X., 55, 69 Nixon, P.M.I., 121–122 Nobuta, K., 30 Noga, M., 22 Noriega, G.O., 35 Nover, L., 30 O Obermaier, C., 14 Ocumpaugh, W.R., 84 O’Donoghue, S.I., 24
146 Oehrle, N.W., 11 O’Flynn, M.G., 114–115 Olfs, H.W., 86, 88, 90, 100–101, 120 Ollver, J.E., 13 Olsson, O., 104 O’Neill, N.R., 122 Orecchia, P., 24 Oresnik, I.J., 32 Ort, D.R., 96 Os, D.D., 20 Ouyang, L.J., 11 Ozier-Lafontaine, H., 78–79, 87, 89 P Palagi, P.M., 24 Palta, J.P., 91 Panda, S.K., 35 Pandit, A., 65 Panter, S., 33–35 Parco, A., 51 Parrish, D.J., 84 Parton, W.J., 79, 94, 101 Paschke, K.A., 7 Patane, C., 87, 89 Patankar, V.K., 51 Paterson, A.H., 89 Pati, B.R., 35–36 Paule, C.M., 50–51 Pawlowski, K., 11–12 Peacock, W.J., 14 Pec, P., 60 Pedrosa, F.O., 4 Peng, H.-M., 10 Perret, X., 7 Perrin, R.K., 79 Petersen, K.K., 110 Peters, N.K., 9 Petolino, J.F., 111 Petrov, M., 51–52, 62, 64 Pfaff, E., 11 Pickering, N., 94 Piedade, M.T.F., 95–96 Pignatelli, V., 105 Pilbeam, D.J., 35 Pinton, R., 3 Pittman, C.U., 77 Plneda, M., 13 Plumb, R.T., 122 Poinsot, V., 4, 32 Polasky, S., 77 Porter, J., 78, 95 Porter, P.M., 78 Portis, A.R., 97 Portyanko, V., 10 Post, L.S., 51 Powers, J.J., 50–51 Powlson, D.S., 89, 111–112 Prasifka, J.R., 122
AUTHOR INDEX Prathepha, P., 66 Price, L., 92–93 Prome´, J.-C., 10, 19 Propheter, J.L., 87, 89 Pueyo, J.J., 35 Pu¨hler, A., 13 Puppo, A., 10–11 Pyter, R., 117, 119, 121, 123 Q Qadir, S., 33, 35 Qi, J.L., 36 Qureshi, M.I., 1, 15, 33, 35 R Rabilloud, T., 23 Radova, A., 60 Raedts, J., 10 Ragauskas, A., 95 Raghu, S., 122 Ralph, J., 104 Ramlov, K.B., 13 Ramos, J., 27, 29–30 Rampitsch, C., 37 Ramu, S.K., 10 Randall, G.W., 79 Rapidel, B., 78–79, 87, 89 Ratet, P., 13 Rathinasabapathi, B., 35, 60 Rayan, P.R., 36 Rayburn, A.L., 102–103, 109, 111 Rayburn, C.M., 102–103, 109 Read, J.C., 84 Rebetzke, G.J., 95 Reddy, P.R., 51 Reed, R.L., 84 Reggiani, R., 63 Rego, F.G., 4 Reich, P.B., 78 Reijnders, L., 77 Reinhold, V.N., 10 Renaut, J., 35 Ren, G., 55, 69 Rentizelas, A.A., 81 Renvoize, S.A., 81–82, 102–103, 108 Requejo, R., 35 Reyrat, J.M., 13 Richards, R.A., 95 Riche, A.B., 84–85, 88–90, 96, 100–101, 108, 111–114, 120 Richter, G.M., 89, 112 Riemenschneider, D.E., 121 Righetti, P.G., 24 Rigo, L.U., 4 Rinalducci, S., 15 Rinco´n, A., 35 Roberts, D.M., 11
AUTHOR INDEX Roberts, J.M., 112 Robin, X., 24 Roche, P., 10 Roest, H.P., 12–13 Rokhsar, D.S., 109 Rolfe, B.G., 4, 21 Romanczyk, J.R.L.J., 51 Rombauts, S., 3 Ronson, C.W., 12 Rooney, L.W., 51 Rosenthal, A., 7 Rosier, P.T.W., 112 Ros, J., 77 Ruanjaichon, V., 51 Rubio, M.C., 27, 29–30 Ruckenbauer, P., 120–121 Ruengphayak, S., 52, 54 Rungsarthong, V., 51 Russelle, M.P., 78–79 S Saadi, I.J., 55 Saalbach, G., 4, 31 Sage, R.F., 96–97 Salamin, N., 81, 102–103, 108 Salse, J., 51, 54, 65 Samac, D.A., 3 Samson, R., 77 Sanderson, M.A., 84 Sandhu, H., 78 Santos, R., 10–11 Santucci, L., 24 Sarhadi, W.A., 52 Sarma, A.D., 11 Sathyanarayanaiah, K., 51 Satinder, A., 21 Sato, S., 33 Sauve´, R., 36 Scally, L., 81–82 Schapendonk, A., 94 Scharf, K.D., 30 Scheibe, B., 14 Scheres, B., 13 Schieberle, P., 51, 62–63 Schilling, K.E., 78, 113–114 Schindler, M., 10 Schmer, M.R., 79 Schmidt, U., 88 Schmitt, H.D., 11 Schneide, R., 24 Schneider, A.D., 89 Schneider, S., 88 Schondelmaier, J., 108 Schroeyers, K., 10 Schulte, L.A., 78–79 Schulten, H.R., 92, 101 Schulte, T., 7 Schumpp, O., 7
Schwartz, D., 20 Schwarz, H., 120–121 Schwarz, K.-U., 83–84, 88–89, 96, 100–101, 108 Scurlock, J.M.O., 82–83, 85, 87, 89, 91, 121–122 Sebela, M., 60 Seitz, L.M., 51 Serafin, F., 121 Shah, A.H., 35 Shamseldin, A., 33 Sharma, T.R., 64–65 Sheeley, D.M., 10 Sheng, J.Q., 51 Sherwood, L.M., 4 Shield, I., 111 Shinners, K.J., 81 Shinozaki, K., 30 Shiotani, I., 102 Shi, W., 36, 51–52, 54–55, 58–59 Shoseyov, O., 34 Shower, N.H., 11 Shvaleva, A., 35 Siddiq, E.A., 51 Siddique, A.B.M., 11 Sigaud, S., 10 Sigsgaard, L., 78 Silberring, J., 22 Silver, D., 13 Singer, M., 38 Singh, A.K., 64–65 Singh, N.K., 35, 64–65 Singh, P.K., 65 Singh, R., 64–65 Singh, V.P., 64 Siria, H.A., 27 Skogen, J.W., 30 Skorupska, A., 3 Smeets, E.M.W., 77, 81, 85 Smil, V., 3 Smit, G., 9 Smith, C.M., 79, 94, 101 Smith, E., 35 Smith, M.M., 104 Smith, P., 85–86, 90–94 Smith, R.D., 26 Smit, P., 10 Sobral, B.W.S., 102 Socolow, R.H., 3 Solomon, B.D., 77, 80 Sood, B.G., 51 Soupe´ne, E., 13 Souza, A.L., 4 Souza, E.M., 4 Spaink, H.P., 10, 12–13 Speller, C.S., 121–122 Spencer, J.L., 122 Srinivasan, M., 37 Sriseadka, T., 51
147
148
AUTHOR INDEX
Srivastava, M., 35 Srivastava, S., 27 Stacey, G., 8, 12, 14, 20 Staggenborg, S.A., 87, 89 Stam, P., 94 Stampfl, P.F., 87, 90–93, 96 Starker, C., 7 Staudenmann, W., 34 Steele, P.H., 77 Steffey, K.L., 122 Stewart, J.R., 82, 96, 100 Sticklen, M., 95, 105 Stier, J.C., 91 Stougaard, J., 13 Strack, D., 32 Stratford, C., 112 Strub, J.M., 23 Stuermer, C.A., 7 Suder, P., 22 Su, J., 36 Sumner, L.W., 26–27, 36 Sundaresan, V., 104 Sun, O.J., 79 Sussman, M.R., 20 Swaminathan, S., 109 Swaney, D.L., 20 Swinton, S.M., 79 Swinton, S. M., 79 Szabados, L., 13 Szatmari, A., 7 Szczyglowski, K., 13 T Tabata, S., 33 Tabb, D.L., 26 Taga, M.E., 8 Taheripour, F., 77 Tailliez, E., 51, 54, 65 Takabe, T., 60 Takahashi, C., 82, 102 Tak, T., 10 Taliaferro, C., 84 Tamaki, M., 52 Tanaka, Y., 60 Tan, G.B., 105 Tang, W., 55, 69 Tang, X., 52 Tanksley, S.D., 51–52 Tatsiopoulos, I.P., 81 Tayebi, K., 84, 88–89, 96, 100–101, 108 Tayot, 87 Tegtmeier, E.M., 78 Teixeira, F., 84, 88–89, 96, 100–101, 108 Tej, S.S., 30 Tena, M., 35 Tenenbaum, D., 24 Teng, C.S., 62–63 Thakkar, S.S., 63
Thannhauser, T.W., 36 Theerayut, T., 52, 54–55, 59 Thelen, J., 20 Thelen, K.D., 79 Thinggaard, K., 122 Thomas, S.R., 77 Thomson, R., 33–35 Tian, G.M., 35 Tilman, D., 77–78 Timmers, T., 10 Timperio, A.M., 14, 33 Tiricz, H., 7 Tolis, A.J., 81 Tolk, J.A., 89 Tomaro, M.L., 35 Tomasi, N., 3 Toma, Y., 82, 96, 100 Toojinda, T., 52, 54 Torres, M., 20 To´th, K., 10 Touati, D., 10–11 Tragoonrung, S., 51–52, 54–55, 59 Trevaskis, B., 4, 33–35 Triboi, E., 30 Trossat, C., 60 Troy, A., 78 Truchet, G., 10, 12–13, 31 Tsugita, T., 50–51 Tuck, G., 94 Turano, F.J., 63 Turnbauhg, J.G., 51 Tyagi, K., 65 Tyner, W.E., 77 U Udvardi, M., 4, 33–35 Uehara, N., 60 Upadhyay, R.K., 35 Upton, J., 105 Uyen, T.T., 66, 68 V Valantin-Morison, M., 78–79, 87, 89 Valot, B., 21 Vanavichit, A., 49, 51–52, 54–55, 59, 66, 68 van Brussel, A.A.N., 10 Vance, C.P., 3 van den Born, G.J., 77 van der Knaap, E., 13 Vanderleyden, J., 5 van de Sande, K., 13 Van de Sype, G., 10 Van de Velde, W., 7 van de Ven, G., 77 van de Wiel, C., 13 van Dorsselaer, A., 23 van Eck, H., 13
AUTHOR INDEX van Engelen, F., 13 van Kammen, A., 12–13 VanLoocke, A., 113 van Oorschot, M., 77 Van Rhijn, P., 5 van Vuuren, D., 77 Van Wijk, K., 4 Varala, K., 109 Vasse, J., 10, 12 Vemaraju, K., 30 Venturi, P., 101, 121 Verhoeven, H. A., 52, 64–65, 69 Verma, D.P.S., 9, 11 Vesper, S.J., 9 Villamil, M.B., 85, 89, 120 Vinocur, B., 34 Visser, P., 105 Vivanco, J.M., 27 Vogel, K.P., 79, 113 Voigt, T.B., 75, 78, 84–85, 89, 91, 98–99, 112, 117, 119–123 Vondracek, B., 78 Vonier, P., 121 Vutiyano, C., 66 W Wada, K., 60 Wagner, P., 11 Walker, E.L., 13 Walker, G.C., 8 Walsh, M., 83–85 Walters, K.F.A., 121 Walther, D., 24 Wanchana, S., 52, 54–55, 59, 66, 68 Wang, D.F., 7, 87, 89, 97 Wang, E.L., 79 Wang, F., 55, 69 Wang, J.L., 10 Wang, Q., 55, 69 Wang, S.S., 36 Wang, W., 34 Wang, Y., 36 Waniska, R.D., 51 Wan, J., 20 Wanrey, M., 4 Wan, Y., 111 Waters, D.L.E., 51–52, 55, 59–60, 69 Watkins, E., 91 Watson, B.S., 26–27, 36 Wattenbach, M., 85–86, 90–94 Weaver, C.D., 11 Weber, J., 35 Weckwerth, W., 4, 19–20, 24, 27, 31–33 Weidmann, S., 21 Weiller, G., 4 Weinman, J., 4 Weisemann, J.M., 63 Weisskopf, L., 3
149
Weiss, W., 14–15 Welle, P., 78 Wenger, C.D., 20 Werner, D., 11, 33 Westra, J., 78 Whelan, J., 11 Widholm, J.M., 75, 105, 109–111 Wielbo, J., 3 Wienkoop, S., 4, 19–20, 24, 27, 31–33 Wildgruber, R., 14 Wilhelm, W.W., 81 Wilkins, C., 122 Wilkinson, M.F., 55 Willey, J.M., 4 Williams, C., 95 Williams, D.W., 122 Williamson, H., 81–82 Wilson, M.A., 78 Winichphol, N., 51 Winnacker, E.-L., 35 Wisniewski, M., 91 Wittulsky, S., 79 Wolf, D.D., 84 Wolter, C.F., 78, 113–114 Wolters, A.M., 13 Wong, M.H., 35 Wongpornchai, S., 51–52, 66, 68 Wood, S.M., 10 Woolverton, C.J., 4 Wratten, S., 78 Wright, R.L., 51 Wu, J., 51–52 Wullschleger, S.D., 84 Wu, M.L., 62–63 Wu, X., 87, 89 Wyse, D.L., 91 X Xiao, Y., 55, 69 Xu, D., 20 Xu, M., 51–52, 54–55, 58–59 Y Yajima, I., 50–51 Yamada, T., 82, 96, 100 Yamaguchi-Shinozaki, K., 30 Yanai, T., 50–51 Yang, Q., 36 Yang, S., 55, 69 Yang, W.C., 12–13 Yang, Y., 35, 51–52, 54–55, 58–59 Yates, I.J.R., 26 Yates, N.E., 85, 88, 100, 120 Yin, X., 94 York, W.S., 10 Yoshihashi, T., 49, 52, 60, 62–63, 66, 68 Yuan, Z., 104
150 Yu, T.Y., 109, 111 Yu, Y.L., 35 Z Zabotina, O.A., 75, 105 Zacharias, S., 112 Zalensky, A., 13 Zardi, L., 24 Zatta, A., 90 Zechelowska, M., 11 Zehirov, G., 7 Zenk, M.H., 35 Zhang,G., 110 Zhang, J., 36
AUTHOR INDEX Zhang, Y.-K., 78, 113–114 Zhang, Z., 54–55, 58–59 Zhao, H.L., 91 Zheng, H.C., 77 Zheng, S.J., 35 Zhen, Y., 36 Zhou, F.S., 89 Zhou, R.L., 91 Zhou, S., 36 Zhu, X.-J., 92, 94, 96 Zimmerman, J., 78 Zolla, L., 14–15, 33 Zub, H.W., 85–86 Zwartkruis, F., 13
SUBJECT INDEX
A Abiotic stress drought stress, 32–33 metal stress aluminium, 36 arsenic, 35–36 cadmium, 35 salinity stress, 33 temperature stress, 33–34 Acetonitrile (ACN), 24 2-Acetyl-1-pyrroline (2AP) 2AP biosynthesis, regulation non-aromatic rice, Os2AP overexpression, 58 Os2AP suppression, RNAi, 55 transcription analysis, Os2AP, 54–57 tyrosine, 58 biochemical functions, Os2AP and BADH, 59–60 formation of acetyl group, 62–63 metabolic disorder, 63–64 nitrogen source, 62 tautomeric equilibria, 60–62 pop-corn/roasted flavour, 51 QTL mapping, 52 volatile compound, aromatic rice, 50 Amino aldehyde dehydrogenase (AMADH) deficiency, aromatic plants, 68 disorder, aromatic rice, 63–64 Os2AP (see Os2AP protein) phylogenetic relationship, 66–67 4-Aminobutanal, 63 Aromatic rice allelic variation, 65 AMDH deficiency, 68 ancestors of, 65–66 2AP biosynthesis, regulation (see also 2-Acetyl-1-pyrroline (2AP)) non-aromatic rice, Os2AP overexpression, 58 Os2AP suppression, RNAi, 55 transcription analysis, Os2AP, 54–57 biochemical functions, Os2AP and BADH, 59–60 environmental adaptability, 69 gene discovery gene mapping, 51–52 map-based cloning, 52–54 mendelian genetics, 51 QTL mapping, 52
genetic diversity, 64 origin, 65 phylogenetic relationship, BADH gene family, 66–67 Ascorbate peroxidases (APX), 30 B Bacterial artificial chromosome (BAC) clones, 52 Bacteroids, 3 Betaine aldehyde dehydrogenase (BADH) biochemical functions, 59–60 gene family, 66–67 protein structure, 68 Biomass. See also Miscanthus giganteus above-ground, 92, 96 below-ground, 92 C4 grasses, 102 characteristics, Miscanthus genotypes, 105–106 crops, 76–77 energy consumption, 77 high-yielding perennial economic sustainability, 78–79 environmental sustainability, 79–80 social sustainability, 80–81 lignin vs. saccharification, 105, 107 renewable sources, 76–77 rhizome, 100 C Calmodulin-like proteins (CaML), 32–33 Chromosome doubling, 111 C4 plants. See also Miscanthus giganteus grass, 102 metabolic control analysis, 97 photoinhibition, 97–98 photosynthesis, 96–97 D Drought stress, leguminous nodule, 32–33 E Echinochola polystachya, 95 Electrospray ionisation mass spectrometry (ESI-MS), 25 Environmental niche, 78
152
SUBJECT INDEX
European Miscanthus improvement (EMI), 83 Evapotranspiration (ET), 90 F Flotillins and flavonoids FLOT gene expression, 7–8 infection threads, 7 nodulation factors, 8 root infection, rhizobia, 8–9 symbiotic bacterial infection, 8 Freedom Giant Miscanthus, 123–124 G Giant Miscanthus. See Miscanthus giganteus
-aminobutyric acid (GABA), 63–64 Gene mapping, 51–52 Gene regulation, legume nodules NifA/FixK, transcriptional activator, 12–13 nif gene, nitrogen-fixation process, 12 nod gene expression, 12 organ-specific cis-acting element (OSE), 13–14 Genetic engineering, 110 Grain aroma. See Aromatic rice H High performance liquid chromatography (HPLC) differentially expressed proteins, 36 protein separation, 25–26 I Immobilised pH gradient (IPG) equilibration, 23 two-dimensional gel electrophoresis with, 14–15 Isoelectric focusing (IEF), 15 L Lipooligosaccharides, 10 M Map-based cloning, 52–54 MASCOT software, 26 Mass spectrometric analyses, 25 Medicago truncatula, 7 Micropropagation, 110 MISCANFOR model, 90 MISCANMOD model, 93 Miscanthus giganteus
Amuri, 124 biomass (see Biomass) breeding accessions, 107 collection and use, germplasm, 108 programme, 108 vegetative propagation technique, 109 chromosome doubling, 111 energy consumption, 77 environmental impact annual leaching fluxes, 115–116 nitrate leaching, 114–115 specific management practice, 111 water, 112–114 Freedom Giant Miscanthus, 123–124 genetic engineering, 110 genetic improvement rationale, 103 traits, 103–107 genomics, 109–110 high-yielding perennial economic sustainability, 78–79 environmental sustainability, 79–80 social sustainability, 80–81 in Illinois, 84–85 micropropagation, 110 Nagara, 124 origin, 81–83 physiology annual dry matter yield, 95 artificial freezing test, rhizome, 99–100 carbon accumulation, 98–99 clone(s), 100 C4 photosynthesis, 96–97 nutrient cycle, 100–101 photoinhibition, 97–98 productivity vs. cool environments, 97 replicated trials, 95 productivity annual growth cycle, 85–86 field trials, 85 geographically diverse yield trials, 86–89 modelling, 92–95 overwinter survival, 91 seasonal growth, 91 soil conditions, 91–92 water use efficiency, 89–90 renewable sources, 76–77 research, 83–84 technical challenges, commercial production eradication, 123 harvesting technology, 122–123 insect and disease control, 121–122 planting and establishment, 118–120 propagation, 117–118 rhizome storage, 118
SUBJECT INDEX soil fertility, 120–121 weed control, 121 Miscanthus productivity network (MPN), 83 Miscanthus sinensis, 82 Molecular-weight search (MOWSE) score, 26 N Nipponbare, 52 Nitrate leaching, 114–115 Nitrogen-fixing bacteria, rhizobium, 3 Nod factors, 10 Nodule, stressed legumes infection and nodulation mechanism flotillins and flavonoids, 7–11 gene regulation, 12–14 peribacteroid membrane, 11–12 N2-fixing bacteria, 3 plant-microbe interaction and specificity, 5–6 proteomics applications, 36–37 cultivation and harvesting, 19 database queries and identification, 26–27 gel imaging and image analysis, 24 gel staining, protein visualisation, 23–24 image analysis software, 15 in-gel protease digestion and PMF, 24–25 IPG strip equilibration, 23 liquid chromatography, 25–26 mass spectrometric analyses, 25 protein extraction and sample preparation, 20–21 protein focusing, 22–23 protein identified, Medicago truncatula, 16–19 protein-nucleic acid match software, 15 SDS-PAGE, 23 two-dimensional gel electrophoresis, 14–15 stress abiotic stress, 32–36 oxidative stress-related proteins, 27–31 pathogenesis-related proteins, 31–32 Nutrient cycle, 100–101 O Os2AP protein allelic variation, 65 amino aldehyde dehyrogenase, 59 aromatic rice
153
non-aromatic, overexpression of, 58 suppression, RNAi, 55 and BADH, 59–60 differential expression, 55, 57 kinetic and affinities, 59–60 protein structure, 68 transcription analysis, 54–56 Western blot analysis, 58–59 Osmotin, pathogenesis-related protein, 30 P Pathogenesis-related proteins, 31–32 PBM. See Peribacteroid membrane Peptide-mass fingerprinting (PMF), 15 Peribacteroid membrane (PBM), 11–12 Plant-microbe interaction, 5–6 PMF. See Peptide-mass fingerprinting Proteomics, nodule application, 36–37 cultivation and harvesting, 19 database queries and identification, 26–27 gel imaging and image analysis, 24 gel staining, protein visualisation, 23–24 image analysis software, 15 in-gel protease digestion and PMF, 24–25 IPG strip equilibration, 23 liquid chromatography, 25–26 mass spectrometric analyses, 25 protein extraction and sample preparation, 20–21 protein focusing, 22–23 protein identified, Medicago truncatula, 16–19 protein-nucleic acid match software, 15 SDS-PAGE, 23 two-dimensional gel electrophoresis, 14–15 Pyrroline-5-carboxylic acid (P5C), 62 Q Quantitative trait locus (QTL), 51 R Radiation use efficiency (RUE), 92 Reactive oxygen species (ROS), 29 Remorin, 10 Rhicadhesin, 9 Rhizobium. See also Nodule, stressed legumes infection, 10 legume roots interactions, 8–9 nitrogen-fixing bacteria, 3 R. leguminosarum bv. trifolii, 3 strain, 13 various species, 6
154
SUBJECT INDEX
Rhizome, Miscanthus giganteus artificial freezing test, 99 biomass, below-ground, 88 storage, technical challenge, 118 Rhopalosiphum maidis, 121 Rice. See Aromatic rice S Salinity stress, 33 SDS-PAGE, 23 Single nucleotide polymorphism (SNP), 65 Sipha flava, 122 Strategic Research Initiative (SRI), 84 Stress abiotic stress (see Abiotic stress) oxidative stress-related proteins antioxidant mechanism, 27, 29 ascorbate peroxidases, 30 osmotin, 30–31 reactive oxygen species, 29–30 SOD, 30 pathogenesis-related proteins, 31–32 Superoxide dismutase (SOD), 30 Sustainability definition, 78 economic sustainability, 78–79 environmental sustainability, 79–80
social sustainability, 80–81 Symbiotic nitrogen fixation (SNF), 4, 11 T Temperature stress, 33–34 Two-dimensional gel electrophoresis (2DE) IEF and SDS-PAGE gel imaging and image analysis, 24 gel-staining, 23–24 in-gel protease digestion and PMF, 24–25 IPG strip equilibration, 23 liquid chromatography, 25–26 mass spectrometric analyses, 25 protein extraction and sample preparation, 20–21 protein focusing, 22 SDS-PAGE, 23 IPG strips, 14–15 W Western blot analysis, 58–59 Windows Intuitive Model of Vegetation response to Atmospheric and Climate Change (WIMOVAC), 94
