Free ebooks ==> www.Ebook777.com Omics Technologies and Crop Improvement www.Ebook777.com Free ebooks ==> www.Ebook777.com www.Ebook777.com Free ebooks ==> www.Ebook777.com Omics Technologies and Crop Improvement EDITED BY N o u re d d in e Be n ke b lia Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business www.Ebook777.com Free ebooks ==> www.Ebook777.com CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2015 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S Government works Version Date: 20140620 International Standard Book Number-13: 978-1-4665-8669-7 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint Except as permitted under U.S Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers For permission to photocopy or use material electronically from this work, please access www.copyright.com (http:// www.copyright.com/) or contact the Copyright Clearance Center, Inc (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400 CCC is a not-for-profit organization that provides licenses and registration for a variety of users For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com www.Ebook777.com Free ebooks ==> www.Ebook777.com Contents Preface vii Editor .ix Contributors .xi Chapter Omics Databases and Gene Expression Networks in Plant Sciences .1 Masaaki Kobayashi, Hajime Ohyanagi, and Kentaro Yano Chapter Foodomics Strategies for the Analysis of Genetically Modified Crops 15 Alberto Valdés, Alejandro Cifuentes, and Virginia García-Cas Chapter Genomics in Hardwood Tree Improvement: Applications of a Growing Resource 45 Lisa W Alexander and Shaneka S Lawson Chapter MicroRNA Omics Approaches to Investigate Abiotic and Biotic Stress Responses in Plants 105 Shiv S Verma, Swati Megha, Muhammad H Rahman, Nat N V Kav, and Urmila Basu Chapter Genome-Wide View of the Expression Profiles of NAC-Domain Genes in Response to Infection by Rice Viruses 127 Shoshi Kikuchi Chapter Plant Molecular Breeding: Perspectives from Plant Biotechnology and Marker-Assisted Selection 153 Ashwani Kumar, Manorma Sharma, Saikat Kumar Basu, Muhammad Asif, Xian Ping Li, and Xiuhua Chen Chapter A Comprehensive Forage Development Model for Advancing the Agricultural and Rural Economy of Pakistan through Integration of Agronomic and Omics Approaches 169 Mukhtar Ahmed, Muhammad Asif, Muhammad Kausar Nawaz Shah, Arvind H Hirani, Muhammad Sajad, Fayyaz-ul-Hassan, and Saikat Kumar Basu v www.Ebook777.com Free ebooks ==> www.Ebook777.com vi Contents Chapter New Approaches for Detection of Unique Qualities of Small Fruits 187 Teodora Dzhambazova, Ilian Badjakov, Ivayla Dincheva, Maria Georgieva, Ivan Tsvetkov, Atanas Pavlov, Andrey Marchev, Kiril Mihalev, Galin Ivanov, Violeta Kondakova, Rossitza Batchvarova, and Atanas Atanassov Chapter Marker-Assisted Selection in Coffee 209 Sarada Krishnan Chapter 10 Advances in Papaya Genomics 219 Savarni Tripathi, Luz Castro, Gustavo Fermin, and Paula Tennant Chapter 11 Advances in Omics for Improved Onion and Potato Quality 253 Noureddine Benkeblia Chapter 12 Omics-Based Approaches for Improvement of the Common Bean 271 Sajad Majeed Zargar, Chumki Bhattacharjee, Rashmi Rai, Muslima Nazir, Yoichiro Fukao, Ganesh Kumar Agrawal, and Randeep Rakwal Chapter 13 Genomics, Transcriptomics, and Molecular Breeding for Improving Cereals 303 Arvind H Hirani, Muhammad Asif, Manorma Sharma, Saikat K Basu, Muhammad Iqbal, and Muhammad Sajad Chapter 14 Next-Generation Sequencing: Principle and Applications to Crops 323 Pradeep K Jain, Pooja Choudhary Taxak, Prasanta K Dash, Kishor Gaikwad, Rekha Kansal, and Vijay K Gupta Chapter 15 Linking Plant Amino Acids with Energy and Stress: A Systems Biology Perspective 343 Jedrzej Szymanski and Gad Galili Index 359 www.Ebook777.com Free ebooks ==> www.Ebook777.com Preface “Generosity is not what comes from hand, but what comes from heart Someone can never be better with his knowledge or his wealth, but could be with his value and attitude.” The question that was raised from the end of the twentieth century was how to feed a world population that will likely be ca billion by 2050, especially considering scientific studies reporting that some yields will probably drop The main challenge is to address this issue by finding opportunities to improve yields of the main crops of cereals, roots and tubers, and grasses In the last three decades, the development of analytical techniques and new emerging technologies such as genomics, transcriptomics, proteomics, metabolomics, and other food-omics has provided promising possibilities for the analysis of crop productivity and possible ways of improving yield and productivity, limiting the land needed to produce this quantity of food, and finally improving the efficiency of resource use, insuring sustainable improvements in crop productivity These improvements will doubtless lead to improvement in the nutritional, processing, and safety qualities of crops In addition, these improvements will also have positive impacts on the environment by reducing pollution and the use of fertilizers, pesticides and other chemicals, and water To achieve these goals, different approaches are suggested such as generating fully sequenced crop genomes or metabolic profiling of these crops This book provides additional information on how crops can be improved and how these improvements would be beneficial to humans, environmentally friendly, and socioeconomically sustainable Noureddine Benkeblia University of the West Indies vii www.Ebook777.com Free ebooks ==> www.Ebook777.com www.Ebook777.com Free ebooks ==> www.Ebook777.com Editor Noureddine Benkeblia is a professor of crop science involved in food science, focusing on food-plants biochemistry and physiology His work is mainly devoted to pre- and postharvest metabolism in crops A few years ago, he introduced a new concept in systems biology—metabolomics—to investigate the mechanisms of biosynthesis and accumulation of fructans in liliaceous plants Professor Benkeblia received his BSc, MPhil, and Doctor in Food Sciences from the Institut National Agronomique (Algeria) and Doctor in Agriculture (PhD) from Kagoshima University (Japan) After a few years of teaching in Algeria, he joined the Institut National de la Recherche Agronomique, Avignon, France, as a postdoctoral scientist from 2000 From 2002 to 2007, he worked as a visiting professor at the University of Rakuno Gakuen, Ebetsu, Japan, and research associate at Hokaido University Professor Benkeblia joined the Department of Life Sciences, the University of the West Indies, Jamaica, in 2008, continuing his work on the physiology, biochemistry, and metabolomics of fructan-containing plants in Jamaica He also works on the postharvest physiology and biochemistry of local fruits Professor Benkeblia has published over 150 papers, over 37 books and book chapters, and has been the recipient of many awards, including the University of the West Indies Award for the Most Outstanding Researcher in 2011 and 2013 ix www.Ebook777.com Free ebooks ==> www.Ebook777.com www.Ebook777.com Free ebooks ==> www.Ebook777.com 364 Index HILIC, see Hydrophilic interaction liquid chromatography (HILIC) Hordeum vulgare, 286 Horovitzia, 220 Horseradish tissue culture, 157 HPD, see p-hydroxyphenylpyruvate dioxygenase (HPD) HPLC, see High-performance liquid chromatography (HPLC) HSF, see Heat shock transcription factor (HSF) HS-SPME, see Headspace solid-phase microextraction (HS-SPME) Ht-SuperSAGE analysis, 227 Human Genome Project (HGP), 325 Hybrid chestnut reintroduction, monitoring, 79 interactions between resistant and native chestnuts, 82 linkage disequilibrium, 82–84 local adaptation and long-term fitness of reintroduced populations, 84–85 population management, markers for, 79 chloroplast markers, 79–80 morphological, physiological, and phenological traits, 81–82 nuclear markers, 80–81 Hydrophilic interaction liquid chromatography (HILIC), 33 4-Hydroxy-L-threonine, 33 p-Hydroxyphenylpyruvate dioxygenase (HPD), 226 HYL1, see Hyponastic Leaves (HYL1) Hyponastic Leaves (HYL1), 107 Hypovirulence, 71 I ICAT, see Isotope-coded affinity tag (ICAT) Illumina/Solexa genome analyzer, 327 Imaging processing, 19 Immobilized pH gradients (IPGs), 288 Inositol, 35 INSDC, see International Nucleotide Sequence Database Collaboration (INSDC) Insect-resistant cotton events, 16 Insect-resistant maize events, 16 International Nucleotide Sequence Database Collaboration (INSDC), 2–3 In vitro propagation of small fruits, 196–200 Ionomics-based approaches, for common bean, 291 Ion Personal Genome Machine, 327 Ion Personal Genome Machine by Life Technologies, 327 Ion trap (IT) mass analyzer, 28 IPGs, see Immobilized pH gradients (IPGs) Isobaric tags for relative and absolute quantitation (iTRAQ), 25, 29, 288 IsomiRs, 111 Isotope-coded affinity tag (ICAT), 288 IT mass analyzer, see Ion trap (IT) mass analyzer iTRAQ, see Isobaric tags for relative and absolute quantitation (iTRAQ) J JA, see Jasmonic acid (JA) JA biosynthetic enzymes, genes encoding, 137 Jarilla, 220 Jasmonic acid (JA), 350–351 Juglans cinera, 86 Juglans nigra, 86 K Kale (Brassica oleracea L.), 178–179 KEGG, see Kyoto Encyclopedia of Genes and Genomes (KEGG) KMD rice, 25 Knop’s salt solution, 155 Kyoto Encyclopedia of Genes and Genomes (KEGG), L Large-scale expression data, 10 Late embryogenesis abundant proteins (LEA), 286 LC–MS, see Liquid chromatography–mass spectrometry (LC–MS) LC-TOF MS analysis, 28 LD, see Linkage disequilibrium (LD) LEA, see Late embryogenesis abundant proteins (LEA) Legume forages, in Pakistan, 175 Berseem/Egyptian clover (Trifolium alexandrinum L), 176–177 fenugreek/methi (Trigonella foenum-graecum L.), 177 lucerne/alfalfa (Medicago sativa L.), 175–176 mungbean (Vigna radiata [L.] Wilczek), 177 Persian clover or shaftal (Trifolium resupinatum L.), 177 Legumes, 271 as integration model to maintain agricultural sustainability, 174–175 bulk, 175 high fiber, 175 minerals, 175 proteins, 175 vitamins, 175 principle constituents, variation in, 273–275 Leguminosea, 271 Leptoglossus occidentalis Heidemann, 158 Leuce Duby, 49 Leucoides, 49 LGs, see Linkage groups (LGs) Library information management system (LIMS), 327 Life Technologies Ion Torrent, 333–334 LIMS, see Library information management system (LIMS) Lin4 RNAs, 105 Linkage disequilibrium (LD), 47–48, 54, 66, 82–84 Linkage drag, 82 Linkage groups (LGs), 47, 48, 53, 64, 76 Linkage maps, see Genetic maps Liquid chromatography (LC), 25, 28 Liquid chromatography–mass spectrometry (LC–MS), 28, 32–33, 229 Livestock production practices in Pakistan, 172–173 Llumina Genome analyzer, 332 www.Ebook777.com Free ebooks ==> www.Ebook777.com Index 365 LMW-GS, see Low-molecular-weight glutenin subunit (LMW-GS) Lotus japonicus, 345 Low-molecular-weight glutenin subunit (LMW-GS), 36 Lucerne/alfalfa (Medicago sativa L.), 175–176 M Maize, 307 transcriptomics in, 315–316 MALDI, see Matrix-assisted laser desorption/ionization (MALDI) MALDI-TOF-MS, see Matrix-assisted laser desorption/ ionization-time-of flight-mass spectrometry (MALDI-TOF-MS) MALDI-TOF MS techniques, 35 Malformed top disease (MTD), 225 MAPK, see Mitogen-activated protein kinase (MAPK) Marker-assisted selection (MAS), 47, 155, 190, 210 biochemical markers, 156–158 future insight, 163 molecular markers, 158 amplified fragment length polymorphism (AFLP), 163–164 randomly amplified polymorphic DNA (RAPD), 161–162 restriction fragment length polymorphism (RFLP), 159–160 simple sequence repeats (SSRs), 162–163 morphological markers, 156 Markers, development of, 337 MAS, see Marker-assisted selection (MAS) Mass spectrometry, 25, 29, 288 Mass spectrophotometry, 228 Matrix-assisted laser desorption/ionization (MALDI), 26 Matrix-assisted laser desorption/ionizationtime-of flight-mass spectrometry (MALDI-TOF-MS), 288 Medicago truncatula, 176, 232 miRNAs in, 117 Meloidogyne spp., 213–214 Metabolic pools, interactions between, 351–352 Metabolic profiling analysis, 30 Metabolite profiling, 29–35 Metabolomics, 29, 188, 192–195, 308, 315 -based approaches, for common bean, 291 Metagenomics, 336–337 Metal stress, miRNAs and, 117 1-Methylcyclopropene (1-MCP), 228 Microarray technology, 19, 21 MicroRNA omics approaches, 105–106 future perspectives, 118 miRNA biogenesis pathway, 107 miRNA profiling technologies, 107 degradome sequencing, 111–112 next-generation sequencing, 109–111 miRNAs and biotic stress, 118 in plant growth and development, 112–113 plant miRNAs and abiotic stress, 113 metal stress, 117 miRNAs in response to drought and salt stress, 114–115 nutrient stress, 116–117 temperature stress, 115–116 MicroRNAs (miRNAs), 232, 337 Microsatellites, see Simple sequence repeats (SSRs) micTarBase, 110 miR393 expression, 18 miR399 expression, 116 miRanda-microRNA.org, 109 miRBase, 109 miRCURY Locked-Nucleic-Acid array technology, 109 miRDB, 110 miRecords, 110 miRGator, 110 miRGen 2.0, 109 miRNA159, 112 miRNA databases, 109 miRNAMap, 109, 110 miRNA microarrays, 108, 109 miRNAs, see MicroRNAs (miRNAs) miRU, psRNA target, 110 miRwalk, 110 Mitogen-activated protein kinase (MAPK), 287 Molecular farming, 154 Molecular markers, 158 amplified fragment length polymorphism (AFLP), 163–164 randomly amplified polymorphic DNA (RAPD), 161–162 restriction fragment length polymorphism (RFLP), 159–160 simple sequence repeats (SSRs), 162–163 Molecular profiling, 18 MON810 maize event, 25 Morel, George, 155 Morphological markers, 156 MRM, see Multiple reaction monitoring assay (MRM) MRNA-Seq, bioinformatics for, assembly, expression profiling, mapping, new technologies for, preprocessing, MTD, see Malformed top disease (MTD) Multicropping techniques, 175 Multidimensional protein identification technology (MudPit), 288 Multiple reaction monitoring assay (MRM), 288 Mungbean (Vigna radiata [L.] Wilczek), 177 Myeloblastosis (MYB) transcription factor genes, 112 N NAC genes, expression of in response to four viral infections, 143–149 NAC proteins and virally encoded gene products, interactions between, 132 www.Ebook777.com Free ebooks ==> www.Ebook777.com 366 Index NAC transcription factors, 127 host NAC and viral proteins, interaction between, 131 structure and phylogenic classification, 128–130 Next-generation sequencing (NGS), 1, 5, 323 comparative profiles of, 326 current sequencing technologies to crops, applications of, 335–336 deep transcriptome investigations, 337 development of markers, 337 mapping the epigenome, 338 metagenomics, 336–337 protein–DNA interactions, study of, 338 sequencing of whole genomes, 336 for miRNA profiling, 109–111 mRNA-Seq, bioinformatics for, assembly, expression profiling, mapping, new technologies for, preprocessing, PCR-based next-generation sequencing platforms, 331 Applied Biosystems SOLiD analyzer, 332–333 Life Technologies Ion Torrent, 333–334 llumina Genome analyzer, 332 Roche/454 FLX pyrosequencer, 331–332 RPKM and FPKM, sequencing and imaging, 329 cyclic reversible termination (CRT), 329–330 real-time sequencing, 330–331 sequencing by ligation (SBL), 330 single-nucleotide addition, 330 single-molecule DNA sequencing platforms, 334 Helicos BioSciences HeliScope, 335 Pacific Biosciences SMRT DNA sequencer, 334–335 template preparation, 327 clonally amplified templates, 328 single-molecule templates, 328–329 NGS, see Next-generation sequencing (NGS) Nitrate reductase (NR), 260 NMR, see Nuclear magnetic resonance (NMR) Northern red oak (Quercus rubra), 59, 87 NR, see Nitrate reductase (NR) Nuclear magnetic resonance (NMR), 30, 193 Nuclear markers, 80–81 NUE, see N-use efficiency (NUE) N-use efficiency (NUE), 260 Nutrient stress, miRNAs in, 116–117 Nutrigenomics, 195–196 O Oak genomics, 65 Oat (Avena sativa L.), 177–178 OECD, see Organisation of Economic Co-operation and Development (OECD) Oilseed rape (Brassica napus), 345 OMAP, see Oryza Map Alignment Project (OMAP) Omics and crops improvement, 254–255 Omics approaches, 308 Organisation of Economic Co-operation and Development (OECD), 18 Oryza, genetic variation, 312 OryzaExpress, Oryza Map Alignment Project (OMAP), Os01g0816100, 148 Os02g0555300, 148 Os07g37920-RNAi rice plants, 147 Os11g0126900, 147 Os12g0123700, 147 Osmolites, 304 Osmoprotectant, 304 Ostil1 gene, 148 P P-35S, 17 PacBio RS single-molecule real-time (SMRT) system, 327 Pacific Biosciences PacBio RS SMRT system, 327 Pacific Biosciences SMRT DNA sequencer, 334–335 Pakistan’ agriculture, forage development in, see Forage development in Pakistan’ agriculture Papain, 220 Papaya (Carica papaya L.), 219 computational genomics, 230 analysis of gene families, 230–231 circadian expression and regulation, 235–236 defense and signaling, 231–232 evolutionary genomics, 236 flower and fruit development, 233–235 genome evolution, 236–237 growth and development, 232–233 sex chromosome evolution, 237–240 experimentally based functional genomics, 221 genetic approaches, 221 marker-based approaches, 221–224 mutagenesis, 224–225 transgenic technology, 225–226 genome to breeding and beyond, 240–242 genomics, advances in, 219 omics approaches, 226 metabolite profiling, 229–230 protein profiling, 228–229 transcriptome sequencing, 226–228 transcript profiling, 226–228 Papaya meleira virus (PeMV), 229 Papaya ringspot virus (PRSV), 221 Papilionoideae, 271 PAR, see Pseudoautosomal region (PAR) Parallel analysis of RNA ends (PARE), 111 PARE, see Parallel analysis of RNA ends (PARE) Partial least squares discriminant analysis (PLS-DA), 33 Partial Pearson correlation coefficient (PPC), 350 PCA, see Principal component analysis (PCA) PCC, see Pearson correlation coefficient (PCC) PCR, see Polymerase chain reaction (PCR) PCR-based next-generation sequencing platforms, 331 Applied Biosystems SOLiD analyzer, 332–333 Life Technologies Ion Torrent, 333–334 www.Ebook777.com Free ebooks ==> www.Ebook777.com Index 367 llumina Genome analyzer, 332 Roche/454 FLX pyrosequencer, 331–332 Pearson correlation coefficient (PCC), 8, Pectolytic enzymes, 201 Pedunculate oak, 59 PeMV, see Papaya meleira virus (PeMV) Peronospora parasitica, 156 Peroxidase, 157 Persian clover or shaftal (Trifolium resupinatum L.), 177 PGM, see Phosphoglucomutase activity (PGM) Phaseoli, 271 Phaseolus aureus, 289 Phaseolus vulgaris salt stress, 115 Phaseolus vulgaris L., see Common bean Phenological traits, 66 Phenomics, 308 Phosphoglucomutase activity (PGM), 223 Phosphorus, for plant growth, 116 Phytomonas, 158 Phytophthera, 85 Phytophthora, 226 PIC, see Polymorphic information content (PIC) Picea, 46 PICME, see Platform for Integrated Clone Management (PICME) PicTar, 110 Pinus, 46, 47 PITA, 110 Plant Expression Database (PLEXdb), Plant Markers, 190 Plant mechanisms to cope with stresses, 305–308 Plant MetGenMAP, 25 Plant miRNAs and abiotic stress, 113 metal stress, 117 miRNAs in response to drought and salt stress, 114–115 nutrient stress, 116–117 temperature stress, 115–116 Plant molecular breeding, 153 future insight, 163 marker-assisted selection (MAS), 155 biochemical markers, 156–158 molecular markers, 158 morphological markers, 156 plant breeding, 154–155 plant tissue culture, 155 Platform for Integrated Clone Management (PICME), 65 PLEXdb, see Plant Expression Database (PLEXdb) PLS-DA, see Partial least squares discriminant analysis (PLS-DA) PMRD, 109 Polymerase chain reaction (PCR), 17 Polymorphic information content (PIC), 277 Polyvinylphosphonic acid (PVPA), 334 Populus, 47, 49, 50, 290 breeding for drought resistance in (case study), 55–57 cold stress, 116 gene discovery, 55 leaves as engineering targets (case study), 57–59 linkage mapping and QTL discovery, 53–55 mapping populations, 52–53 sequence data, 51–52 Populus balsamifera, 52 Populus canadensis, 51 Populus deltoides, 52 Populus euphratica, 58 Populus maximowiczii, 52 Populus nigra, 52 Populus tomentosa, 116 Populus trichocarpa, 49, 52 salt stress, 115 Posttranslational modifications (PTMs), 287 Potato (Solanum tuberosum L.), 255 breeding, 258 domesticated varieties, 255 diseases, 257 growing issues, 256–257 pests of potato, 257–258 water deficiency, 255–256 history of, 255 omics improvement goals, 259 low acrylamide-forming potential, 262–263 nitrogen-use efficiency, increasing, 260 nutritional attributes, enhancing, 262 pesticides, 261–262 salinity, tolerance to, 261 water-use efficiency, increasing, 260–261 perspectives, 263 transgenic potato, 258–259 Potato virus A (PVA), 257 Potato yellow dwarf virus (PYDV), 257 PPC, see Partial Pearson correlation coefficient (PPC) Praline, 157 Pre-miRNA, 107 Principal component analysis (PCA), 25, 30, 33, 35 Proline (Pro), 261 Protein–DNA interactions, study of, 338 Protein profiling, 26–29 Proteomics, 187–188, 191–192, 308, 315 Proteomics approach, for common bean, 287 in beans, 289 need for, 287–288 subproteomic analyses, 290–291 technological update, 288–289 PRSV, see Papaya ringspot virus (PRSV) Pseudoautosomal region (PAR), 239 Pseudocercospora griseola, 283 Pseudomonas syringae, 232, 283 Pseudotsuga, 46 Pseudotsuga menziesii, 84 PsRNATarget, 115 PTMs, see Posttranslational modifications (PTMs) P tomentosa plantlets, salt-treated, 115 PVA, see Potato virus A (PVA) PVPA, see Polyvinylphosphonic acid (PVPA) PYDV, see Potato yellow dwarf virus (PYDV) Pyrosequencing, 330 www.Ebook777.com Free ebooks ==> www.Ebook777.com 368 Index Q qRT-PCR, see Quantitative real-time PCR (qRT-PCR) QTL, see Quantitative trait loci (QTL) Quantitative real-time PCR (qRT-PCR), 108, 10–111 Quantitative trait loci (QTL), 47, 53, 64, 158 in forage crop species, 180–181 Quercus, 47 Quercus, genomics of adaptive traits in, 59 adaptive trait variation (case studies), 66–68 BAC libraries and physical mapping, 64–65 gene sequences, 60–61 linkage mapping and QTL analysis, 62–64 mapping populations, 62 population differentiation in northern red oak (case studies), 68–69 Quercus alba, 61, 87 Quercus petraea, 59, 60, 62, 66, 67 Quercus Portal, 88–89 Quercus robur, 59, 60, 62, 64 Quercus rubra, 59, 61, 66, 87 R RACE, see 5′-Rapid amplification of cDNA ends (RACE) Rainfed forage crops, rotation research for, 173–174 RALF, see Rapid Alkalinization Factors (RALF) Ralstonia solanacearum, 257 Random amplified polymorphic DNA (RAPD), 47, 161–162, 190, 213, 221, 276 RAPD, see Random amplified polymorphic DNA (RAPD) Rape (Brassica napus L.), 179 Rapid Alkalinization Factors (RALF), 140 5′-Rapid amplification of cDNA ends (RACE), 111 Raspberry, breeding in, 191 RDV, see Rice dwarf virus (RDV) Reactive oxygen intermediates (ROI), 306–307 Reactive oxygen species (ROS) accumulation, 344 Reads per kilobase of exon model per million mapped reads (RPKM), Real-time sequencing, 330–331 Reference genome sequences, Reintroduced populations local adaptation and long-term fitness of, 84–85 RepTar, 110 Resistance genes, 76 Resistant and native chestnuts, interactions between, 82 Restriction fragment length polymorphism (RFLP), 159–160, 276 Reverse-phase high-performance liquid chromatography (RP-HPLC), 288 RFLP, see Restriction fragment length polymorphism (RFLP) RGSV, see Rice grassy stunt virus (RGSV) Rhizobium etli, 290 Ribulose-1,5-bisphosphate carboxylase oxygenase (RuBiSCO), 260 Rice, 307 gene expression networks in, 4–5 NAC genes, 134–136 NAC transcription factors, 130 transcriptomics in, 314 Rice crops, transcriptome profiling of, 21 RiceCyc, Rice dwarf virus (RDV), 131–137, 138 Rice Expression Profile Database (RiceXPro), RiceFREND, Rice grassy stunt virus (RGSV), 140, 143, 147 Rice NAC gene response to rice viral infection, 131 rice dwarf virus (RDV), 131–137, 138 rice grassy stunt virus (RGSV), 140, 143 rice stripe virus (RSV), 137, 139 rice tungro spherical virus (RTSV), 137, 140, 141 Rice Oligonucleotide Array Database (ROAD), Rice stripe virus (RSV), 137, 139, 147 Rice tungro bacilliform virus (RTBV), 137, 140 Rice tungro spherical virus (RTSV), 137, 140, 141 RiceXPro, see Rice Expression Profile Database (RiceXPro) RIM1 gene, 147 RITA® system, 197–200 RNA22, 110 RNA hybrid, 110 RNAi, 313 RNA polymerase II (pol II), 107 ROAD, see Rice Oligonucleotide Array Database (ROAD) Roche/454 FLX pyrosequencer, 331–332 Roche 454 GS FLX sequencer, 327 Roche GS FLX 454 sequencer, 327 ROI, see Reactive oxygen intermediates (ROI) Root-knot nematode (Meloidogyne spp.), 213–214 ROS accumulation, see Reactive oxygen species (ROS) accumulation RP-HPLC, see Reverse-phase high-performance liquid chromatography (RP-HPLC) RPKM, see Reads per kilobase of exon model per million mapped reads (RPKM) RSV, see Rice stripe virus (RSV) RTBV, see Rice tungro bacilliform virus (RTBV) RTSV, see Rice tungro spherical virus (RTSV) RuBiSCO, see Ribulose-1,5-bisphosphate carboxylase oxygenase (RuBiSCO) Rubus (raspberry, blackberry), 189 Rubus idaeus, 191 S SA, see Salicylic acid (SA) S-adenosyl methionine (SAM), 350 Safety evaluation of GMOs, 18 Safflower (Carthamus tinctorius L.), 179 SAGE, see Serial analysis of gene expression (SAGE) Salicylic acid (SA), 350 Salinity, potato crop sensitivity to, 261 Salinity-impacted areas, forage production in, 179–180 Salt stress, 304 SAM, see S-adenosyl methionine (SAM) Sanger-454 unigene set, 68 SBL, see Sequencing by ligation (SBL) SBS, see Sequencing-by-synthesis (SBS) www.Ebook777.com Free ebooks ==> www.Ebook777.com Index 369 Scanning tunneling microscope (TEM), 327 SCAR, see Sequence-characterized amplified region (SCAR) SDS-PAGE, see Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) SELDI, see Surface-enhanced laser desorption/ionization (SELDI) Sequence-characterized amplified region (SCAR), 222 Sequence Read Archive (SRA), Sequence-related amplified polymorphism (SRAP) genetic linkage maps, 53 Sequencing and imaging, 329 cyclic reversible termination (CRT), 329–330 real-time sequencing, 330–331 sequencing by ligation (SBL), 330 single-nucleotide addition: pyrosequencing, 330 Sequencing by ligation (SBL), 330 Sequencing-by-synthesis (SBS), 331 Serial analysis of gene expression (SAGE), 337 Sessile oak, 59 Short tandem repeats (STRs), see Simple sequence repeats (SSRs) Shotgun protein analysis, 29 SILAC, see Stable isotope labeling by amino acids in cell culture (SILAC) Silene latifolia, 239 Simple sequence repeats (SSRs), 47, 52, 53, 162–163, 189, 190, 221, 276 Single-molecule DNA sequencing platforms, 334 Helicos BioSciences HeliScope, 335 Pacific Biosciences SMRT DNA sequencer, 334–335 Single-molecule sequencing (SMS), 335 Single-molecule templates, 328–329 Single-nucleotide addition (SNA), 327, 330 Single nucleotide polymorphisms (SNPs), 1–2, 47, 67, 190, 277, 335 siRNAs, see Small interfering RNAs (siRNAs) SLA, see Specific leaf area (SLA) Small fruits berry polyphenols processing and food matrix effects, 201–202 detection of unique qualities of, 188 genomics, 189–191 metabolomics, 192–195 nutrigenomics, 195–196 proteomics, 191–192 in vitro propagation of, 196–200 phytochemical studies of, 188 Small interfering RNAs (siRNAs), 241, 337 SMRT system, see PacBio RS single-molecule real-time (SMRT) system SMS, see Single-molecule sequencing (SMS) SNA, see Single-nucleotide addition (SNA) SNP, see Sodium nitroprusside (SNP) SNPs, see Single nucleotide polymorphisms (SNPs) SOD, see Superoxide dismutase (SOD) Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE), 157 Sodium nitroprusside (SNP), 289 Solanum, 258 Solexa sequencing, 109 Solid-phase amplification, 328 SOLiD sequencing technology, 227 Sorghum (Sorghum bicolor L.), 178 Southern hybridization, 159 Specific leaf area (SLA), 58 SRA, see Sequence Read Archive (SRA) SRAP genetic linkage maps, see Sequence-related amplified polymorphism (SRAP) genetic linkage maps SSA, see Succinic semialdehyde (SSA) SSADH, see Succinic semialdehyde dehydrogenase (SSADH) SSRs, see Simple sequence repeats (SSRs) Stable isotope labeling by amino acids in cell culture (SILAC), 288 starBase, 110 Strawberries, 195 Stress, amino acids in, 343–344 Stress recovery, 349 Structural genomics, 309 Subproteomic analyses, 290–291 “Substantial equivalence,” 16 Succinic semialdehyde (SSA), 349 Succinic semialdehyde dehydrogenase (SSADH), 349 Sucrose-enriched Knop’s salt solution, 155 Sulfur, for plants, 116 Sunflower (Helianthus annuus), 345 Superoxide dismutase (SOD), 117, 307 Surface-enhanced laser desorption/ionization (SELDI), 288 T Tacamahaca, 49 TACF, see The American Chestnut Foundation (TACF) TAIR, see The Arabidopsis Information Resource (TAIR) Tandem affinity purification (TAP), 288 TAP, see Tandem affinity purification (TAP) TaqMan miRNA assays, 109 TarBase, 110 Targeting-induced local lesions in genomes (TILLING), 313–314 TargetScan, 110 TCA cycle, see Tricarboxylic acid (TCA) cycle TEM, see Scanning tunneling microscope (TEM) Temperature stress, miRNAs in, 115–116 Template preparation, 327 clonally amplified templates, 328 emulsion PCR, 328 solid-phase amplification, 328 single-molecule templates, 328–329 TFs, see Transcription factors (TFs) The American Chestnut Foundation (TACF), 77–79 The Arabidopsis Information Resource (TAIR), TILLING, see Targeting-induced local lesions in genomes (TILLING) Tissue culture, in plant breeding, 155 T-nos, 17 γ-Tocopherol, 35 Totipotency, 155 TPS, see True potato seed (TPS) Transcript and metabolic data, integration of, 352–353 www.Ebook777.com Free ebooks ==> www.Ebook777.com 370 Index Transcription factors (TFs), 128, 226 Transcriptome profiling of rice crops, 21 Transcriptomics, 314 in barley, 315 in maize, 315–316 in rice, 314 in wheat, 314–315 Transcript profiling, 227 Transgenic potato, 258–259 Transgenic rice, 29 Tree breeding, 46 TreeGenes Database, 86–87 Tricarboxylic acid (TCA) cycle, 343 Triticum aestivum, 312 Triticum duram, 312 True potato seed (TPS), 258 True seed potatoes (TSP), 256 Trypanosomatids (kinetoplastid protozoa), 158 TSP, see True seed potatoes (TSP) Tsuga canadensis, 86 Tuberization, of potato, 256 Turanga, 49 Turnip (Brassica rapa L.), 179 TW16, 140 Two-dimensional differential gel electrophoresis (2-D DIGE), 228 Two-dimensional gel electrophoresis (2-DGE), 26, 35 2-D liquid chromatography (2D-LC), 289 2n gametes, 53 U Unintended effects, 16 Uromyces appendiculatus, 283 V Vaccinium (blueberry, lingonberry), 189 Vaccinium vitis-idaea L., 197–200 Vanuxem, 76 Vasconcellea, 238 Vasconcellea heilbornii, 228 VitisNet, 192 Vitis vinifera L., 188 W Water deficit stress, 305 Water-use efficiency (WUE), 55, 81, 260–261 Web resources, information on, databases for gene expression profiling by NGS, databases for microarray gene expression profiling, 2–3 reference genome sequences, Western conifer seed bug, 158 Wheat transcriptomics in, 314–315 Wheat seed storage proteins, 157 White oak (Quercus alba), 87 Whole-genome sequencing, 309–310, 336 Whole plant system response, 232 WUE, see Water-use efficiency (WUE) Z ZDS, see ξ-carotene desaturase (ZDS) Zea mays, 115 Zero-mode waveguide detectors (ZMW), 331 Zma-miR168, expression of, 115 ZMW, see Zero-mode waveguide detectors (ZMW) www.Ebook777.com 75 70 65 x-CoA C +G LC C+ LC 80 CE HCN CE PC2 (28%) 10 85 G Coverage (%) Free ebooks ==> www.Ebook777.com LycoCyc GC LC CE EtO –5 PC1(51%) 10 Figure 2.4 Evaluation of the achieved coverage PCA was performed on the predicted physicochemical properties of the detected metabolites and the metabolites in the LycoCyc database The score plots show that the distribution of the detected metabolites occupies a similar space as the reference metabolites (Reprinted from Kusano, M., H Redestig, T Hirai et  al 2011 Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment PLoS ONE 16: e16989.) www.Ebook777.com Free ebooks ==> www.Ebook777.com P1 P2 × F1 Many generations ⊗ F2 (a) (b) Figure 3.1 A schematic representation of traditional QTL mapping (a) and association mapping (b) QTL mapping can suffer from low resolution as single markers are typically in LD with large genomic regions In association mapping, higher resolution is obtained because markers are in LD with much smaller genomic regions, primarily due to many generations of recombination and high genetic diversity in large, unstructured populations A mutated allele (gold diamond) will be in LD only with closely located markers (Reprinted with permission from Zhu, C., Gore, M., Buckler, E.S., and Yu, J., Plant Genome, 1, 5–20, 2008.) (a) (b) (c) Figure 3.6 (a) Chestnut trees are cork-borer inoculated with three different strains of chestnut blight: a mildly virulent strain at the top, a moderately virulent strain in the middle, and a highly virulent strain at the bottom (b) Blight infections on a resistant tree are characterized by fungal cankers having defined margins of swollen calluses and living tissue (c) Blight-susceptible trees show sunken cankers with necrotic tissue at the margins, which quickly girdle and kill the infected stem (Photo by J Hill Craddock.) www.Ebook777.com Free ebooks ==> www.Ebook777.com Cytoplasm Nucleus Mir locus Polll? Pri-miRNA Chromatin changes DCL1? Other? HEN1 Pre-miRNA AGO4 miRNA duplex Systemic signal? HYL1 DCL1 RISC AGO miRNA in RISC complex AAAAAA XRN4 siRNA Exportin-5 HST? RdRp (SDE1) miRNA duplex AAAAAA PAZ AAAAAA PIWI AAAAAA Translational inhibition RISC AGO mRNA cleavage AGO Figure 4.2 Model for miRNA biogenesis and activity in plants (Reprinted from Curr Opin Plant Bio, 8, Kidner, C A and R A Martienssen The developmental role of microRNA in plants, 38–44 Copyright 2005, with permission from Elsevier.) www.Ebook777.com Free ebooks ==> www.Ebook777.com I ONAC2 II ONAC3 III ONAC5 IV ONAC6 V NAM(CUC3) VI NAC1 VII NAC22 VIII SND IX TIP X ANAC34 XI SNAC XII NEO XIII ONAC7 XIV ONAC1 XV ONAC4 XVI OMNAC XVII XVIII Figure 5.2 An unrooted phylogenetic tree of the NAC transcription factors of rice and Arabidopsis classified into 18 groups The amino acid sequences of the NAC domain of 135 rice NAC-family proteins and 117 Arabidopsis NAC proteins were aligned by Clustal W, and a phylogenetic tree was constructed using MEGA4.0 and the NJ method Bootstrap values from 1000 replicates were used to assess the robustness of the trees (The classification by Nuruzzaman et al (2010) is indicated in parentheses.) (Reprinted from Gene 465, Nuruzzaman, M., R Manimekalai, and A M Sharoni et al Genome-wide analysis of NAC transcription factor family in rice 30–44, Copyright 2010, with permission from Elsevier.) www.Ebook777.com Free ebooks ==> www.Ebook777.com Figure 8.2 Vaccinium vitis-idaea L plantlets at the end of their growth cycle in a RITA temporary immersion system www.Ebook777.com Free ebooks ==> www.Ebook777.com Tolerant sample Protein extraction Sensitive sample Protein separation by 2-DGE Protein visualization by CBB/silver stain/dye and image analysis In-gel enzymatic digestion and MS analysis of the spots of interest Database searching and protein identification Database searching System-level approach, evaluation Regulatory network Identification of key regulators Manipulation of key regulator for crop improvement (common bean) Figure 12.3 Proteomics approach for identification of novel proteins in the common bean A gel-based proteomics approach can be used to identify the differentially expressed proteins among tolerant and susceptible cultivars Identification of these novel proteins will help in revealing the metabolic pathways involved in inducing tolerance www.Ebook777.com Free ebooks ==> www.Ebook777.com Phenotypes/phenomics Metabolomics Reverse genetics Proteomics Forward genetics Transcriptomics Genomics Sequence information of gene/genes Figure 13.3 Flowchart of omic tools and strategies in forward and reverse genetic approaches www.Ebook777.com Free ebooks ==> www.Ebook777.com Asp (1) Cytosol (16) (16, 17) (2) Mitochondrion Acetyl-CoA (18) Thr OAA (3-7) (19-21) (22 -25) Malate Fumarate (26, 23-25) Met Lys TCA cycle Ile Leu GABA Val (2) Succ (8-10) Glu Glu ETFOX ETFRED (14-15) (a) Acetyl-CoA (28) (29-30) (13) (Ile) Propionyl-CoA Acetyl-CoA (Leu) Acetyl-CoA Acetoacetate (3) CO2 Glu + (4) 2-OG + NADH + NH4 ↔ Glu+ NAD + H2O (5) 2-OG + Ala ↔ Glu + pyruvate (6) 2-OG + Asp ↔ Glu + OAA (7) 2-OG + Ile ↔ Glu + 2-keto-3-methyl-valerate (7) 2-OG + Leu ↔ Glu+ 2-keto-iso-caproate (8) 2-OG + Tyr ↔ Glu + p-hydroxyphenylpyruvate (7) 2-OG + Val ↔ Glu + 2-keto-isovalerate (9) 2-OG + Orn ↔ Glu + Glu-γ-semialdehyde (10) 2-OG + arogenate ← Glu+ prephenate (11) 2-OG + histigdinol phosphate ← Glu+ IAP (12) 2-OG + 3-phosphoserine ← Glu + 3-PHP (13) Fumarate + Arg ← arginino-succinate (14) Malate+ CoA ← acetylCoA+ H2O + glyoxylate 2-OG (25) ETFOX ETFRED (12) Glu SSA + (27) 2-OG (11) (1) 2-OG GABA (Val) Propionyl-CoA (b) Figure 15.1 (a) Catabolic pathways of aspartate family and branched-chain amino acids Black arrows represent single biochemical reactions Red dotted arrows represent protein degradation Involved enzymes: (1) monofunctional Asp kinase AK1; (2) Asp-semialdehyde dehydrogenase ASD; (3) dihydrodipicolinate synthase DHDPS1; (4) dihydrodipicolinate reductase DHDPR; (5) L,L-diaminopimelate aminotransferase AGD2; (6) diaminopimelate epimerase DAPE; (7) diaminopimelate decarboxylase DAPD; (8) Lys-ketoglutarate reductase/saccharopine dehydrogenase LKR/SDH; (9) saccharopine dehydrogenase SDH; (10) 3-chloroallyl aldehyde dehydrogenase ALDH; (11) NA; (12) NA; (13) NA; (14) enoyl-CoA hydratase MFP2; (15) acetoacetyl-CoA thiolase AACT1; (16) Asp kinase/homo-Ser dehydrogenase AK/HSDH; (17) homo-Ser kinase HSK; (18) Thr synthase TS; (19) cystathionine g-synthase CGS; (20) cystathionine b-lyase CBL; (21) Met synthase MS; (22) Thr deaminase TD; (23) acetolactate synthase AHASS; (24) ketol acid reductoisomerase KARI; (25) branched-chain amino acid aminotransferase BCAT; (26) Met g-lyase MGL; (27) branched-chain keto-acid dehydrogenase BCE2/LPD2; (28) NA; (29) enoyl-CoA hydratase MFP2; (30) acetoacetyl-CoA thiolase AACT1 (b) TCA cycle scheme, GABA shunt, and basic reactions of TCA intermediates involving amino acids and AA-derived acetyl-CoA Enzymes involved: (1) GABA transaminase; (2) succinic semialdehyde dehydrogenase; (3) glutamate decarboxylase; (4) glutamate dehydrogenase; (5) alanine transaminase; (6) aspartate transaminase; (7) branched-chain amino acid transaminase; (8) aromatic amino acid transaminase; (9) ornithine transaminase; (10) glutamate-prephenate aminotransferase; (11) histidinol-phosphate transaminase; and (12) phosphoserine aminotransferase; (13) arginosuccinate lyase; (14) malate synthase Metabolite abbreviations: IAP, imidazole acetol-phosphate; 3-PHP, 3-phosphohydroxypyruvate The list of the enzymatic reactions indicated in the bottom of panel b was principally based on a previous review (Sweetlove, L J., K F Beard, A Nunes-Nesi, A R Fernie, and R G Ratcliffe 2010 Not just a circle: flux modes in the plant TCA cycle Trends Plant Sci 15: 462–70.) www.Ebook777.com ... main crops of cereals, roots and tubers, and grasses In the last three decades, the development of analytical techniques and new emerging technologies such as genomics, transcriptomics, proteomics,...Free ebooks ==> www.Ebook777.com www.Ebook777.com Free ebooks ==> www.Ebook777.com Omics Technologies and Crop Improvement EDITED BY N o u re d d in e Be n ke b lia Boca Raton London New York... such as genomics, transcriptomics, proteomics, metabolomics, and other food -omics has provided promising possibilities for the analysis of crop productivity and possible ways of improving yield