413P. K. Gupta and R. K. Varshney (eds.), Cereal Genomics II, DOI: 10.1007/978-94-007-6401-9, © Springer Science+Business Media Dordrecht 2013

Appendix IContributors

EDUARD AKHUNOV

Department of Plant Pathology, Kansas State University, Manhattan KS 66502 USA

ALINA AKHUNOVA

Integrated Genomics Facility, Kansas State University, Manhattan KS 66502 USA

VINDHYA AMARASINGHE

Department of Botany and Plant Pathology, 2082 Cordley Hall, Oregon State University, Corvallis, OR, 97331-2902, USA

JOSE L. ARAUS

Unitat de Fisiologia Vegetal, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain; International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco, Mexico 56130, Mexico

JAN P. BUCHMANN

Institute of Plant Biology, University of Zurich, Zollikerstrasse 107, CH-8008 Zürich, Switzerland

JILL E. CAIRNS

International Maize and Wheat Improvement Center (CIMMYT), P.O. Box MP 163, Mount Pleasant, Harare, Zimbabwe

JOSE CROSSA

International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco, Mexico 56130, Mexico

414 Appendix I: Contributors

BISWANATH DAS

International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations Avenue, Gigiri, Nairobi 00621, Kenya

PALITHA DHARMAWARDHANA

Department of Botany and Plant Pathology, 2082 Cordley Hall, Oregon State University, Corvallis, OR, 97331-2902, USA

DAVID EDWARDS

University of Queensland, Brisbane, QLD, 4072, Australia

JUSTIN ELSER

Department of Botany and Plant Pathology, 2082 Cordley Hall, Oregon State University, Corvallis, OR, 97331-2902, USA

BIKRAM S. GILL

Wheat Genetic and Genomic Resources Center and Department of Plant Pathology, Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506-5502, USA; King Abdulaziz University, Faculty of Science, Genomics and Biotechnology Section, Department of Biological Sciences, Jeddah 21589 Saudi Arabia

PUSHPENDRA K. GUPTA

Department of Genetics and Plant Breeding, CCS University, Meerut 250004, India

ZHONGHU HE

Institute of Crop Sciences/International Maize and Wheat Improvement Center (CIMMYT), Chinese Academy of Agricultural Sciences, 12 South Zhongguancun St., Beijing 100081, China

PANKAJ JAISWAL

Department of Botany and Plant Pathology, 2082 Cordley Hall, Oregon State University, Corvallis, OR, 97331-2902, USA

BEAT KELLER

Institute of Plant Biology, University of Zurich, Zollikerstrasse 107, CH-8008 Zürich, Switzerland

SEIFOLLAH KIANI

Department of Plant Pathology, Kansas State University, Manhattan KS 66502 USA

415Appendix I: Contributors

NATALIYA KOVALCHUK

Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, Waite Campus, Urrbrae, South Australia

PAWAN L. KULWAL

State Level Biotechnology Centre, Mahatma Phule Agricultural University, Rahuri, Ahmednagar (MS), 413722, India

BARBARA LADDOMADA

Wheat Genetic and Genomic Resources Center and Department of Plant Pathology, Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506-5502, USA; Istituto di Scienze delle Produzioni Alimentari, Consiglio Nazionale delle Ricerche (ISPA-CNR), Via Monteroni 73100 Lecce, Italy

PETER LANGRIDGE

Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, Waite Campus, Urrbrae, South Australia

JIAYANG LI

State Key Laboratory of Plant Genomics and National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China

MING LI

Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, Waite Campus, Urrbrae, South Australia

SERGIY LOPATO

Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, Waite Campus, Urrbrae, South Australia

COSMOS MAGOROKOSHO

International Maize and Wheat Improvement Center (CIMMYT), P.O. Box MP 163, Mount Pleasant, Harare, Zimbabwe

REYAZUL R. MIR

Division of Plant Breeding & Genetics, Shere-Kashmir University of Agricultural Sciences & Technology of Jammu (SKUAST-J),Chatha-180 009, Jammu, India

NATALIA PALACIOS

International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco, Mexico 56130, Mexico

416 Appendix I: Contributors

ANDREW H. PATERSON

Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA

BODDUPALLI M. PRASANNA

International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations Avenue, Gigiri, Nairobi 00621, Kenya

NIDHI RAWAT

Wheat Genetic and Genomic Resources Center and Department of Plant Pathology, Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506-5502, USA

SACHIN RUSTGI

Washington State University, Pullman- 99164, W.A., USA

TAO SANG

State Key Laboratory of Systematic and Evolutionary Botany, Key Laboratory of Plant Resources and Beijing Botanical Garden, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China

NESE SREENIVASULU

Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Interdiciplinary Center for Crop Plant Research (IZN) Research Group Stress Genomics, Corrensstraße 3, 06466 Gatersleben, Germany

PALAKOLANU S. REDDY

Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Interdiciplinary Center for Crop Plant Research (IZN) Research Group Stress Genomics, Corrensstraße 3, 06466 Gatersleben, Germany

RAJEEV K. VARSHNEY

Center of Excellence in Genomics (CEG), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India; CGIAR Generation Challenge Programme (GCP), c/o CIMMYT, 06600 Mexico DF, Mexico

JIANMIN WAN

Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 South Zhongguancun St., Beijing 100081, China

417Appendix I: Contributors

XI-YIN WANG

Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA; Center for Genomics and Computational Biology, School of Life Sciences, and School of Sciences, Hebei United University, Tangshan, Hebei 063009, China

THOMAS WICKER

Institute of Plant Biology, University of Zurich, Zollikerstrasse 107, CH-8008 Zürich, Switzerland

YUNBIXU

Institute of Crop Sciences/International Maize and Wheat Improvement Center (CIMMYT), Chinese Academy of Agricultural Sciences, 12 South Zhongguancun St., Beijing 100081, China

419P. K. Gupta and R. K. Varshney (eds.), Cereal Genomics II, DOI: 10.1007/978-94-007-6401-9, © Springer Science+Business Media Dordrecht 2013

Andrew K. Borrell, University of Queensland, Brisbane, AustraliaDave Edwards, University of Queensland, Brisbane, AustraliaBikram Gill, Kansas State University, Manhattan, USAMukesh Jain, National Institute of Plant Genome Research, New Delhi, India Takao Komatsuda, National Institute of Crop Science, Ibaraki, JapanVasudev Kumanduri, European Bioinformatics Institute, Cambridge, UKJianxin Ma, Purdue University, Indiana, USAReyazul R. Mir, Shere-Kashmir University of Agricultural Sciences & Technology of Jammu (SKUAST-J), Jammu, IndiaEviatar Nevo, University of Haifa, Haifa, IsraelManish Pandey, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, IndiaSaurabh Raghuvanshi, Delhi University – South Campus, Delhi, IndiaHeike U. Schneider, Forschungszentrum Jülich, Jülich, GermanyTrushar Shah, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, IndiaNils Stein, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanyMahendar Thudi, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, IndiaRoberto Tuberosa, University of Bologna, Bologna, ItalyRobbie Waugh, The James Hutton Institute, Dundee, UK

Appendix II Reviewers

421P. K. Gupta and R. K. Varshney (eds.), Cereal Genomics II, DOI: 10.1007/978-94-007-6401-9, © Springer Science+Business Media Dordrecht 2013

421

genes and alleles, 395GWAS, 384in a crop species, 384in wheat, 386–387phenotypic variance, 184–185

AL. See Aleurone layerAL1 gene, 228–229Aleurone layer (AL), 216, 223, 225–226

alpha-gliadin promoter, 2361 Cys-Prx promoter, 237

Allergens, 236Alpha-tocopherol, 262AM. See Association mappingAmplification refractory mutation system

(ARMS), 22Amplified fragment length polymorphism

(AFLP), 5, 62AMPRIL. See Arabidopsis multiparent RILAmylopectin, 253Amylose, 229, 253–255Ancestral polyploidy

genome size variation, 108large-scale genomic repatterning rules,

107–108paleogenomic exploration, 105–107recursive polyploidizations, 105

Animal proteins, 235, 237Anthocyanin biosynthesis, 327Anti-nutrients, 234APPF. See Australian Plant Phenomics

FacilityAquaporins, 356Arabidopsis, 23, 132, 198

ABF3 and ABF4, 198endosperm, 222genomes, 105

0–91-FFT. See Fructan 1-fructosyltransferase1-SST. See Sucrose 1-fructosyltransferase2,4-dihydroxy-7-methoxy-1,4-benzoxazin-

3-one (DIMBOA), 2585-methyl-cytosene sensitive restriction

enzymes (MCS restriction enzymes), 62

6-FEH. See Fructan 6-exohydrolase15-cis-phytoene, 260

AAb initio gene prediction, 157AB-QTL analysis, 290–291, 395ABA. See Abscisic acidABA-dependent signaling pathway, 191–192ABA-independent signaling pathway, 191–192Abscisic acid (ABA), 192

accumulation, 288signaling pathways, 191–192

Ac. See ActivatoraCGH. See Array-based comparative genomic

hybridizationACPFG. See Australian Centre for Plant

Functional GenomicsActivator (Ac), 131

gene trap approach, 146transposon, 145

Affymetrix chips, 16, 39, 40t, 41t, 186AFLP. See Amplified fragment length

polymorphismAgilent technologies, 18Agronomic traits, 395

AM and JLAM in major cereals, 296tAM and JLAM in major cereal, 296t

Index

Note: Page numbers followed by f or t indicate figure or table, respectively

Index422422

phenomics project, 381Sanger technology, 59

Arabidopsis multiparent RIL (AMPRIL), 280Arabinoxylans (AX), 252

GT43 and GT47 family genes, 253Xylp, 252

ARMS. See Amplification refractory mutation system

Array-based comparative genomic hybridiza-tion aCGH), 13, 18, 26, 70

DNA chips/microarrays, 15whole-genome, 43

Array-based genotyping platformsCNVs and PAVs, 43DArT markers, 32–39high-throughput SNP, 23–31RAD, 42–43Sequenom MassARRAY system, 39–42SFP, 39, 40– 41t

Array-based high-throughput SNP genotyping platforms

Fluidigm SNP genotyping, 31Illumina’s goldengate assay, 24–26Illumina’s infinium assays, 26–31KASPar assays, 31

Association mapping (AM), 295, 382LD-based, 276, 295in plants, 295

Australian Centre for Plant Functional Genomics (ACPFG), 6

Australian Plant Phenomics Facility (APPF), 192

AX. See Arabinoxylans

BB. distachyon. See Brachypodium dystachionBAC. See Bacterial artificial chromosomeBackcross (BC1) populations, 277Backcross introgression line (BIL), 377Bacterial artificial chromosome (BAC), 103,

180, 181Bacterial blight (BB), 396Barley (Hordeum vulgare L.), 184

digital models of developing, 224free-threshing trait, 332free-threshing wheat, 332grains, transverse and longitudinal sections

of, 216fmap-based QTL cloning, 331orthologous genes, 332

Basal endosperm transfer layer (BETL), 223, 226–229

BETL1-4, 227END1 transcripts, 227mni1 gene, 227, 228rgf1 mutation, 228transcription factors, 228, 229transfer-cell mediated uptake mechanism,

226, 227Basal Endosperm Transfer Layer1-4 (BETL1-

4), 227Basic-Helix-Loop-Helix (bHLH), 259BB. See Bacterial blightBC1. See BackcrossBead array technology, 17β-D-xylopyranosyl (Xylp), 252β-D-glucans, 251Beta glucans

grasses, cell walls, 251microarray analysis, 252

BETL. See Basal endosperm transfer layerBETL1-4. See Basal Endosperm Transfer

Layer1-4bHLH. See Basic-Helix-Loop-HelixBIL. See Backcross introgression lineBioactive compounds

See alsoCereal-based functional food genomics

carotenoids, 260–262polyphenols, 256–260tocopherols, 262–264tocotrienols, 262–264

Bioinformatics resources and tools, 120Biological process (BP), 170Biology/omics approach, 178BP. See Biological processBrachypodium dystachion (B. distachyon), 103

genome size, 132, 181BrachyTAG program, 181, 196–197Brassinosteroids, 192Breeding, 381Breeding populations, 377–378Bulk segregant analysis, 282–283Burrows-Wheeler (BW), 81Burrows-Wheeler transform (BWT), 81BW. See Burrows-WheelerBWT. See Burrows-Wheeler transform

CCAAS. See Chinese Academy of Agricultural

SciencesCaMV. See Cauliflower mosaic virusCapillary Electrophoresis-Mass Spectroscopy

(CE-MS), 365

Index 423423

Carbohydrate-based functional food components

arabinoxylans, 252–253beta glucans, 251–252inulin, 255–256resistant starch, 253–255

Carotenoidsβ-carotene synthesis pathway, 261carotenoid biosynthesis pathway, 261f

isoprenoid compounds, 260psy1-A and psy1-B1 genes, 262

Cauliflower mosaic virus (CaMV), 260, 264CC. See Cellular componentCE-MS. See Capillary Electrophoresis-Mass

SpectroscopyCellular component (CC), 170Cellulose synthase genes (CesA genes), 251Cellulose synthase-like genes (Csl genes),

251, 252Central starchy endosperm (CSE), 223, 229

Floury2, 230maize mutants, 230O2, 229–230O7 gene, 230–231starchy endosperm sources, 231storage proteins, 229Zein protein synthesis, 230

Cereal breeding programsagro-ecologies, 341cereal-growing regions, 341–342for generating high-quality data, 346–351high throughput programs, need for, 343,

345HTPP, 341–342modern breeding, 342

Cereal genomics, 1, 3–4tbioinformatics analysis capabilities, 58cereal grain production, 1, 2fcereals functional genomics, 6complex polygenic traits, 57germplasm characterization, 57high-throughput sequencing, 58molecular marker technologies, 57molecular markers, 5–6, 58NGS technologies, 5, 58organization and evolution, 6QTL analysis, 7Sanger’s dideoxynucleotide synthetic

method, 58Cereal seed genomics

See also Seed development in cerealsembryo culture, 219embryo rescue, 219

endosperm cultures, 220IVF, 218micro-dissection, 217NTT system, 218somatic embryogenesis, 219Y1H system, 217–218Y2H system, 218

Cereal-based functional food genomics, 247See also Bioactive compoundscarbohydrate-based functional food com-

ponents, 251–256cereals, 248functional foods, 247, 264tissue distribution, 249–250t

Cereals, 177, 248domestication list QTLs/genes cloned in,

294tenvironmental adaptability, 376functional genomics, 6high-throughput and precision phenotyp-

ing, 375MABC platform, 376–387marker-assisted selection application,

395–401marker-assisted selection methodologies,

387–391strategies for marker-assisted selection,

391–395CesA genes. See Cellulose synthase genesCGH. See Comparative genomic

hybridizationChalcone synthase (CHS), 259Characterizing and controlling site variation

experimental design, 349–350phenotypic variation, 346phenotyping environment role, 346signal-to-noise ratio, 346site characterization, 347, 348, 349soil texture, 346soils, 346spatial analyses, 350–351topography, 346water content as volume fraction, 347t

Chinese Academy of Agricultural Sciences (CAAS), 400

Chloridoid and arundinoid grasses, 104Chromosome segment substitution line

(CSSL), 377, 395CHS. See Chalcone synthaseCIM. See Composite interval mappingCIMMYT. See Coworkers from International

Maize and Wheat Improvement CenterCNVs. See Copy number variations

Index424424

Colinearity, 129, 141Comparative genomic hybridization (CGH),

18, 19, 22, 26Comparative genomics research

C4 photosynthetic pathway, 117CA genes, 117whole-genome duplication, 116

Complexity reduction of polymorphic sequences (CRoPS), 62, 380

Component grain tissue developmentSee also Seed development in cerealsaleurone layer, 225–226basal endosperm transfer layer,

226–229CSE, 229–231embryo development, 220–221endosperm development, 221–225ESR, 231–232maternal tissues, 232–233

Composite interval mapping (CIM), 283–284, 288

comparison285tsoftware, 301t

Computer software for QTL mappingsoftware availability, 301tstatistical analyses, 302

Conventional breeding, 341, 343, 376, 399Copy number variations (CNVs), 5, 21–22,

69, 70in maize, 43in rice, 43wheat exonic sequence alignments, 87

Cot analysis, 131Coworkers from International Maize

and Wheat Improvement Center (CIMMYT), 7

Global Maize Program, 342MABC program, 397tropical maize on rows, 362t

Crop domestication, 293domestication QTLs/genes cloned in

cereals, 294tevolutionary mechanisms, 322genetics, 333grasses, 335theories and hypotheses, 320

CRoPS. See Complexity reduction of polymorphic sequences

CSE. See Central starchy endospermCsl genes. See Cellulose synthase-like

genesCSSL. See Chromosome segment

substitution line

DDAA. See Days after anthesisDAP. See Days after pollinationDArT. See Diversity array technologyDays after anthesis (DAA), 236Days after pollination (DAP), 223DB. See DNA bindingDeB30. See Defective endosperm B30Decision support tools, 387, 402Defective endosperm B30 (DeB30), 230Degree of polymerization (DP), 251Deoxnivelanol (DON), 363Deutsches Pflanzen Phänotypisierungs

Netzwerk (DPPN), 192DH. See Doubled haploidDietary fibre, 235DIMBOA. See 2,4-dihydroxy-7-methoxy-1Diploid zygote, 220–221Discolored 1. See Dsc1Disease and insect-pest phenotyping

diagrammatic scales, 362digital imaging systems, 362–363non-destructive methods, 363remote sensing, 363tools for, 361tropical maize thermal images, 362f

Dissociator (Ds), 131Diversity array technology (DArT), 5, 19, 21,

32f, 295, 378in breeding for cereal crops, 33–38, 34–37tcost-effectiveness, 38–39nature, 33

DNA binding (DB), 228DNA chips

gene-based microarrays, 16high-density oligonucleotide arrays, 14microarrays for SNP genotyping, 17whole genome high density resequencing

microarrays, 15–16DNA elements, repetitive, 156DNA sequence variation detection

bioinformatical tools, 81genetic variation analysis, 80–81genotype methods and SNP calling, 83non-commercial NGS alignment software,

82tDNA-based molecular markers, 11DNA-intercalating dye, 23Domestication related QTLs in cereals, 293Domestication syndrome, 320

cereal crops, 319domestication of cereals, 319–320domestication transition, 321

Index 425425

gene evolution and domestication processes, 328

genes underlying, 322and genetic analyses, 320–322grain/seed cover, size, and coloration,

326–328inflorescence structure, 321, 325, 326plant and animal domestication, 319plant architecture, 325, 326recent advancements, 334–335seed dormancy, 321shattering and threshing, 322–325stony fruitcases, 321top-down approach, 321

DON. See DeoxnivelanolDouble-strand break (DSB), 143Doubled haploid (DH), 277, 342, 377DP. See Degree of polymerizationDPPN. See Deutsches Pflanzen

Phänotypisierungs NetzwerkDs. See DissociatorDSB. See Double-strand breakDsc1 (Discolored 1), 230

EEC. See Enzyme commissionEffective Use of Water (EUW), 352, 353ELP. See Expression level polymorphismEM. See Expectation-maximizationEmbryo surrounding region (ESR), 216, 223,

231–232Emp2 (Empty pericarp2), 230Empirical evidence-based methods, 157Empty pericarp2. See Emp2END1 transcripts. See ENDOSPERM1

transcriptsEndosperm development, 221

cell plate formation, 223cellular, 221digital models of developing barley

grains, 224endosperm cells, 216free-growing anticlinal walls, 222free-nuclear divisions, 222, 223grain specific promoter activity, 224fhelobial, 221nuclear, 221–222syncytial and cellularization phases,

222tissue types, 225wheat endosperm cellularization process,

223

Endosperm transfer cells (ETC), 216, 232–233

promoters, 237transgenic wheat and rice plants, 227

ENDOSPERM1 transcripts (END1 tran-scripts), 227

Enzyme commission (EC), 169EPPN. See European Plant Phenotyping

NetworkeQTLs. See Expression QTLsESR. See Embryo surrounding regionEST. See Expressed sequence tagETC. See Endosperm transfer cellsEuropean Plant Phenotyping Network (EPPN),

192EUW. See Effective Use of WaterExpectation-maximization (EM), 283Experimental design

options, 349f, 350fRCBD, 350soil heterogeneity, 349spatial variability, 349

Expressed sequence tag (EST), 157Expression level polymorphism (ELP), 19Expression QTLs (eQTLs), 287Extra cell layers 1 (xcl1), 226

FF3H gene. See Flavanone 3-hydroxylase geneFalse discovery rate (FDR), 173FAST CornTM, 344FDR. See False discovery rateFEH. See Fructan exohydrolaseFGENESH software, 157–158FHB. See Fusarium head blightField phenotyping

characterizing and controlling site varia-tion, 346–351

data generation from, 345selection strategies, 351–353

Field-based phenotyping, 345, 381FISH. See Fluorescence in situ hybridizationFl2. See Floury2Flavanone 3-hydroxylase gene (F3H gene),

259Flavonoids, 259

endosperm-specific promoter, 260low-molecular-weight phenolics, 259

Floury2 (Fl2), 230Fluidigm Dynamic Arrays, 14Fluorescence in situ hybridization

(FISH), 70

Index426426

Fluorescence Resonance Energy Transfer detection system (FRET detection system), 22, 31

Fluxome, 190, 190–191FNB. See Food and Nutrition BoardFood and Nutrition Board (FNB), 247Food for Specific Health Use (FOSHU), 247FOSHU. See Food for Specific Health UseFourier transform-infrared spectrometer (FT-

IR), 189FOX hunting system, 197Foxtail millet (Setaria italic), 103

cereal genomes, 333whole-genome sequences, 104t

Free-threshing, 324–325development, 326QTL, 332

FRET detection system. See Fluorescence Resonance Energy Transfer detection system

Fructan 1-fructosyltransferase (1-FFT), 255Fructan 6-exohydrolase (6-FEH), 256Fructan biosynthesis, 255Fructan exohydrolase (FEH), 255, 256FT-IR. See Fourier transform-infrared

spectrometerFull-length collagen type I alpha1 (rCIa1), 235Functional annotation of genomes

See also GO enrichment analysisusing gene ontology assignments, 169, 170GO assignments, 170–171protein signature identification, 163–169

Functional foods, 247prebiotic components, 251whole grain cereals, 248wild germplasm, 265

Fusarium head blight (FHB), 288, 301, 385MAS, 401meta-QTL analysis studies, 292tin southern and northern leaf blights, 290in wheat, 290, 398

GGA. See Gibberellic acidGas chromatography (GC), 363, 365Gas chromatography-mass spectroscopy (GC–

MS), 189, 365GBS. See Genotyping-by-sequencingGBS libraries, 380GBSS-I. See Granule Bound Starch

Synthase-IGC. See Gas chromatographyGC–MS. See Gas chromatography-mass

spectroscopy

GDUSHD. See Growing degree day heat units to pollen shedding

GEBV. See Genomic estimated breeding values

GEI. See Genotype by environment interactions

GEM. See Gene expression markerGene collinearity facilitated paleogenomic

explorationadditional polyploidization, 106–107DNA segments, 106gene collinearity between chromosomes, 106fgene synteny characterization, 105whole-genome duplication, 107

Gene evolution and domestication processesbarley and wheat, 331–332generalization, 332–333maize, 331rice, 328–330

Gene expression marker (GEM), 19Gene groups in grasses

biased base substitutions, 119elevation in GC content, 119–120GC content in grass genes, 118fprominently elevated GC content, 117–118

Gene homology analysis, 158functional orthologs, 158–159InParanoid gene orthology analysis,

159–162OrthoMCL scalable method, 162–163

Gene introgression, 395–396Gene movement, molecular mechanism for,

141diagnostic sequence motifs, 143DSBs, 143foreign gene duplication, 142flarge gene-containing fragments, 142patching up process, 143synteny and colinearity, 141

Gene ontology (GO), 164, 170consortium website lists, 172enrichment analysis, 173tfunctional annotation using, 169–171

Gene predictionab initio gene prediction, 157empirical evidence-based methods, 157FGENESH software, 157–158

Gene pyramidingfor complex traits, 398–399for major genes, 398

Gene transferalleles of Azucena, 397BB resistance genes, 396FHB resistance, 397QPM lines, 397

Index 427427

Gene-based microarrays, 16Generalization

See also Domestication syndromecritical domestication, 333critical domestication transition, 332domestication allele, 332–333domestication-related genes, 333one-gene, one-trait hypothesis, 332

Genetic blueprint. See Genome sequenceGenetic diversity analysis application

DNA sequence variation detection, 80–83genetic variation analysis, 77–78molecular variation genome-wide study, 77next-generation sequencing technologies,

78–80Genetic variation genome-level analysis

See also Genetic diversity analysis application

reduced representation sequencing, 87–90targeted sequence capture, 85–87transcriptome-based analysis, 83–85whole genome re-sequencing, 90–94

Genetical genomics, 276, 287Genome, gene-rich regions, 293Genome annotation

functional annotation of genomes, 163–171

gene homology analysis, 158–163GO annotation use, 171–174stages, 156structural annotation, 156–158

Genome contraction through DNA deletion, 136

analysis of orthologous regions, 136, 138fgenome expansion through TE insertions,

137fgenome size reduction mechanisms, 139fgenomic turnover, 140illegitimate recombination, 139–140LTR retrotransposon surveys, 140random deletions, 138, 139solo-LTR generation, 137, 138

Genome evolutionSee also Plant genomesBAC-by-BAC approach, 127WGS approach, 127–128

Genome sequence, 128, 178See also Seed development in cerealsancestral polyploidy, 105–108availability from grass genomes, 129barley, 184biofuel production, 101, 102bioinformatics resources and tools, 120Brachypodium, 103, 181candidate gene identification, 197–198

categories, 128cereals phylogeny, 102fchloridoid and arundinoid grasses, 104comparative genomics research, 116–117foxtail millet, 103gene groups, 117genetic novelties and species diversifica-

tion, 108–111genomes, 103grass chromosomes evolution, 111–116grasses, 101, 104tmaize, 103, 180–181omics related resources, 182–183tprojects in cereals, 178, 179trice, 102, 178, 180sugarcane, 101transcriptome, 104tribe Saccharinae, 103wheat, 184–185

Genome size of plants, 131, 133tdynamic equilibrium of, 141gene numbers133tphylogenetic relationships and, 132freduction mechanisms, 139fTE determination of, 133–134

Genome–wide association studies (GWAS), 5, 57, 67, 295, 384

Genome-specific sites (GSS), 86, 87Genome-wide association (GWA), 381Genome-wide selection (GWS), 303, 342Genome-wide transcriptome profiling, 186Genomic estimated breeding values (GEBV),

57– 58, 388, 391Genomic selection (GS), 57, 389

GEBVs, 388GS, 389–390methodologies for marker-assisted

breeding, 389fstrategies for marker-assisted breeding,

390fviable MAS approach, 390

Genomic turnover, 140, 141Genotype by environment interactions (GEI),

292Genotyping platforms, 380Genotyping-by-sequencing (GBS), 70, 89,

298 , 304, 380Geranyl geranyl diphosphate (GGPP), 260Germplasm, 400–401GGPP. See Geranyl geranyl diphosphateGibberellic acid (GA), 225Gibberellins, 192Glutelin (Gt1), 260Glycosyl transferases (GT), 252GO. See Gene Ontology

Index428428

GO assignmentsbased on gene homology, 170–171based on InterPro assignments, 170

GO enrichment analysis, 171, 172, 173fSee also GO enrichment analysisBinGO calculation, 173, 174BinGO tabular output, 171fexperiment on circadian control in rice,

172GO annotation, 172methods, 172against reference set, 172–173

Goat grass (Aegilops tauschii), 67Grain/seed cover and coloration

anthocyanin biosynthesis, 327hull colors, 327inflorescence meristem, 327molecular characterization, 328molecular cloning, 328polyphenol oxidase, 327teosinte, 326–327wild progenitors, 327wild-type allele, 327

Granule Bound Starch Synthase-I (GBSS-I), 253

Grass chromosome evolution, 111high intragenomic similarity and diver-

gence, 114homoeologous recombination, 114–116long-lasting illegitimate recombination,

112–114orthologous chromosome, 112pan-grass polyploidization, 111

Grass genomesSee also Transposable elements (TE)comparative analysis of, 129, 130crop circle genetic resolution, 130genome sequences availability from, 129molecular mechanism for gene movement,

141–143RFLP marker, 129

Growing degree day heat units to pollen shed-ding (GDUSHD), 281

Growth maintenanceaquaporins, 356osmotic adjustment, 356stress avoidance mechanism, 355–356water deficit, 355

GS. See Genomic selectionGSS. See Genome-specific sitesGT. See Glycosyl transferasesGt1. See GlutelinGWA. See Genome-wide association

GWAS. See Genome wide association studiesGWS. See Genome-wide selection

HHAF. See Hour after fertilizationHAP. See Hour after pollinationHaplotype map (HapMap), 379Hetero-fertilization frequencies, 394Heterosis, 355

components, 90in maize, 355, 359PAV and SNP, 93

HGA. See Homogentisic acidHidden Markov Models (HMM), 157,

167–168tHigh performance liquid chromatography

(HPLC), 363, 364High throughput phenotyping platforms

(HTPP), 343, 345breeding perspective, 381establishment, 344example companies, 344NIEs concept, 381operations, 343precision phenotyping, 381quantitative phenotypes, 381stress environment effect, 381–382

High-molecular-weight glutenin subunits (HMW-GS), 236, 386

High-resolution melting (HRM), 19curve analysis, 22–23

HMM. See Hidden Markov ModelsHMPR. See Hypomethylated partial

restrictionHMW-GS. See High-molecular-weight glute-

nin subunitsHomoeologous recombination

See also Illegitimate recombination in grasses

andromonecious dwarf phenotype, 115elevated gene loss rates, 115homoeologous chromosomes pair, 114resistance genes distribution, 116frice floral organs, 115telomere bouquet, 115

Homogentisic acid (HGA), 264Homologue gene cluster creation, 160Hour after fertilization (HAF), 221Hour after pollination (HAP), 223HPLC. See High performance liquid

chromatographyHPP. See p-hydroxyphenylpyruvic acid

Index 429429

HPPD. See p-hydroxyphenylpyruvic acid dioxygenase

HRM. See High-resolution meltingHTPP. See High throughput phenotyping

platformsHydroxycinnamic acids, 258Hypomethylated partial restriction (HMPR),

62

IIBSC. See International Barley Sequencing

ConsortiumICIM. See Inclusive composite interval

mappingIDP. See Insertion/deletion polymorphismIllegitimate recombination in grasses

genetic recombination, 108–109genome duplication and conversion pat-

tern, 109fhomoeologous recombination, 109–110pan genome dynamics, 110pericentromeric regions, 110polyploidization, 109

IM. See Interval mappingImmortal populations, 377Immortalized F2 population, 279In vitro fertilization (IVF), 218Inclusive composite interval mapping (ICIM),

283, 303InDels. See Insertions/deletionsInParanoid gene orthology analysis, 159

confidence values, 160gene families, 161fhomologue gene cluster creation, 160InParanoid implementation, 160–161MultiParanoid cluster, 162pairwise similarity comparisons, 159super cluster creation, 161, 162

Insertion site-based polymorphism (ISBP), 5, 23, 58, 69

Insertion/deletion polymorphism (IDP), 23Insertions/deletions (InDels), 13, 19, 21, 33,

43, 262Integrated resource of Protein Domains and

Functional sites (InterPro), 163–164GO assignments based on InterPro assign-

ments, 170implementation, 165InterProScan web interface, 165, 166f,

168frelationships between InterPro entries, 165retrieving InterPro results, 166, 168–169

signature recognition approaches, 167–168t

types, 164tIntegrative systems biology, 193

See also Genome sequenceBrachyTAG program, 196–197FOX hunting system, 197metabolic network reconstructions,

194–195omics integration pipeline, 194fpreselected set of genes, 196reverse engineering, 194top-down systems biology, 193, 194transcriptome co-expression analysis,

195–196International Barley Sequencing Consortium

(IBSC), 184International Plant Phenomics Network

(IPPN), 192, 381International Rice Genome Sequencing Project

(IRGSP), 102–103plant genome sizes and gene

numbers, 133trice, 328–330scaffolds and gaps, 128twhole genome sequencing projects, 179t

International wheat genome sequencing consortium (IWGSC), 184–185

InterPro. See Integrated resource of Protein Domains and Functional sites

InterProScan, 165analysis, 169frice protein, 168fsignature recognition approaches,

167–168tweb interface, 165, 166f

Interval mapping (IM), 284Inulin

biosynthesis model, 255gene clone, 255–256long-chain inulin molecules, 256QTL mapping, 256

IPP. See Isopentyl diphosphateIPPN. See International Plant Phenomics

NetworkIRGSP. See International Rice Genome

Sequencing ProjectISBP. See Insertion site-based

polymorphismIsopentyl diphosphate (IPP), 260IVF. See In vitro fertilizationIWGSC. See International wheat genome

sequencing consortium

Index430430

JJoint-linkage association mapping (JLAM),

276, 298, 303in cereals, 296–297t

Junk DNA, 131

KKBioscience competitive allele‐specific PCR

(KASPar), 22, 24, 31genotyping assay conversion rate, 84SNP, 67, 84

LLateral spikelets, 326LC–MS. See Liquid chromatography-mass

spectrometryLD. See Linkage disequilibriumLDRs. See Levels of diversityLemnatech scan analyzer 3D. See Plant

AcceleratorLeucine-rich repeat domain (LRR domain),

140Levels of diversity (LDRs), 94Likelihood ratio (LR), 283LINE. See Long interspersed nuclear elementLinkage disequilibrium (LD), 57, 276, 295,

378AM in cereals, 296–297JLAM in cereals, 296–297MLM, 295natural population for, 378QTL mapping based on, 295

Linkage-based QTL mapping methods, 282advanced backcross QTL analysis,

290–291Bayesian approach for, 286–287bulk segregant analysis, 282–283CIM, 283–284comparison between different methods of,

285tfor dynamic traits, 288–289EM algorithm, 283eQTLs, 287genetical genomics and expression, 287high density linkage maps, 283interacting epistatic QTLs, 284MAYG, 291meta-QTL analysis, 291–292mixed-model analysis, 292–293mQTL, 288multi-trait mapping, 284, 286for ordinal traits, 289

pQTLs, 287–288QTL analysis, 290

Lipoxynase (LOX), 387Liquid chromatography-mass spectrometry

(LC–MS), 189, 365LMW-GS. See Low-molecular-weight glute-

nin subunitsLong interspersed nuclear element (LINE),

144, 156Long terminal repeat retrotransposons (LTR

retrotransposons), 108, 134, 144activity, 136genome-wide surveys, 140sequences, 140

Long-lasting illegitimate recombinationhomoeologous chromosome pair, 112homoeologs, 112homology pattern and evolutionary model

of chromosomes, 112frice-sorghum divergence, 113–114

Low-molecular-weight glutenin subunits (LMW-GS), 387

LOX. See LipoxynaseLR. See Likelihood ratioLRR domain. See Leucine-rich repeat domainLTR retrotransposons. See Long terminal

repeat retrotransposonsLutein, 261

MMABC. See Marker-assisted backcrossingMADS box family member, 233MAGIC. See Multiparent advanced genera-

tion intercrossMAGIs. See Maize assembled genomic

islandsMaize (Zea mays), 66, 103, 180–181

causal mutation, 331genetic diversity, 379maize domestication, 331phylogenetic analyses, 331single nonsynonymous substitution, 331

Maize assembled genomic islands (MAGIs), 83

Mapping As You Go (MAYG), 291Mapping populations, 378

advanced generation populations, 279backcross population, 279bi-parental, 277in cereals, 277DH populations, 278F2 population, 278gene effects for heterosis breeding, 279

Index 431431

immortalized F2, 279mapping population comparison, 278fNC III design populations, 279next-generation multi-parental, 281–282

Maps. See Markers and mapsMarker development and validation

C to A mutation, 386marker-trait association, 386MAS-based breeding programs, 385PCR-based markers, 386pleiotropic effects, 386

Marker systems, array-based, 12–13aCGH, 18classification, 19DArT markers, 17DNA chips, 14–17Fluidigm dynamic arrays, 14genotyping platforms, 23–43high density arrays-based resequencing, 23microarrays, 13platforms genotyping, 13fprinciples and methods, 20–23TAM, 17–18

Marker-assisted backcrossing (MABC), 342, 376

decision support tools, 387genotyping platforms, 379–380integrating MAS in breeding strategies,

376marker development and validation,

385–387marker-trait association analysis, 382–385markers and maps, 378–379precision and high-throughput phenotyp-

ing, 381–382trait genetics and breeding populations

Marker-assisted breedingagronomic characters, 401breeding programs, 400conventional breeding, 399conventional genetic enhancement, 401germplasm, 400marker-assisted transfer, 400MAS-derived varieties, 399sorghum, 401

Marker-assisted recurrent selection (MARS), 342, 376, 388, 399

Marker assisted selection (MAS), 57, 342, 376

application in cereals, 395gene introgression, 395–396gene pyramiding selection, 398, 399gene transfer, 396–398genomic selection, 388–391

increasing scale and efficiency, 393, 394integration in breeding strategies, 376marker-assisted breeding, 399–401marker-assisted breeding platform compo-

nents, 377fMARS, 388MAS-based breeding programs, 385methodologies, 387multiple targets, 398, 399pyramiding multiple loci, 392reducing costs, 393, 394scheme optimization, 394–395selection for multiple traits, 392–393selection strategies, 391traits for gene selection, 391

Marker-trait association (MTA), 12, 57, 295, 386

association mapping, 382genetic and breeding materials, 384haplotype-based mapping, 383high-density genetic maps, 384high-density SNP data, 384joint linkage-LD mapping strategy, 383meta and in silico analyses, 385parallel mapping, 383specific mapping population, 385specific traits, 382statistical approaches, 382, 383

MarkersRAD, 87real-time detection based, 22recombination bins as, 70

Markers and mapsHapMap, 379maize genetic diversity, 379molecular markers, 378SNPs, 378–379

MARS. See Marker-assisted recurrent selection

MAS. See Marker assisted selectionMasking repetitive DNA, 156Maternal pericarp, 227, 233Maternal tissues, 232–233Maternally expressed gene 1 (Meg1), 228Maximum likelihood (ML) approach, 282, 283

restricted maximum likelihood (REML) single-locus method, 286

of SNP calls, 92MAYG. See Mapping As You GoMb. See MegabaseMCS restriction enzymes. See 5-methyl-

cytosene sensitive restriction enzymesMeg1. See Maternally expressed gene1Megabase (Mb), 180

Index432432

Meta-QTL analysis, 291–292Metabolic flux balance analysis (MFA),

190–191Metabolite profiling, 189, 364–365Metabolite QTL (mQTL), 276, 288, 385Metabolomics, 189

metabolic regulation, 189metabolomic research, 190plant response to stresses, 189–190

MF. See Molecular functionMFA. See Metabolic flux balance analysisMicroarray analysis, 186, 252Microarray-based markers

CNVs and PAVs, 21–22DArT, 21TAM, 21TDM, 20

Micronutrients, 233, 234, 263–264Miniature1 gene (mni1 gene), 227MIPS-REdat, 156Mismatch (MM), 16Mixed-model analysis, 292–293ML. See Maximum likelihoodMM. See Mismatchmni1 gene. See Miniature1 geneModern breeding, 342

conventional breeding, 343high throughput genotyping, 343uses within breeding pipelines, 342

Modern breeding in phenotypingmolecular breeding, 342molecular techniques use, 342specific target traits, 342

Modified grain composition, 233–234See also Seed development in cerealsallergens, 236animal proteins, 235cell walls, 235dietary fibre, 235micronutrients, 234oil content, 234–235seed-specific promoters, 236–238SSPs, 235starch composition, 234

Molecular breeding, 7, 342DArT marker assays, 39GoldenGate (GG) assay for, 30–31

Molecular cloning, 328Molecular function (MF), 170mQTL. See Metabolite QTLMTA. See Marker-trait associationMultiParanoid cluster, 162Multiparent advanced generation intercross

(MAGIC), 280, 378

NNA. See NicotianamineNAM. See Nested association mappingNARS. See National agricultural research

systemsNational agricultural research systems

(NARS), 376Natural population, 378NB-ARC. See Nucleotide-binding adaptors

shared by R proteinsNC III design population, 279NCD. See Nuclear cytoplasmic domainNCIII. See North Carolina IIINDVI. See Normalized Difference Vegetation

IndexNear infrared reflectance spectroscopy

(NIRS), 359, 363, 364Near iso-environment (NIE), 381–382Near-isogenic lines (NILs), 377, 378Nested association mapping (NAM), 89,

280–281, 378Next generation sequencing (NGS), 5, 6, 58Next generation sequencing technologies

(NGS technologies), 12, 33fluorescently real-time detection, 80Ion PGM sequencer, 80NGS platforms, 78re-sequencing projects, 80sequencing platform comparison, 79tfor SNP discovery and genotyping, 60, 62

Next-generation multi-parental mapping populations

multiline cross inbred lines, 281phenotypic data, 281recombinant inbred advanced intercross

lines, 282NGS. See Next generation sequencingNGS technologies. See Next generation

sequencing technologiesNGS-based SNP discovery, tools for, 64

SNPs and sequencing errors, 64–66software for SNP discovery in cereals, 64

Nicotiana plumbaginifolia (N. plumbaginifo-lia), 255

Nicotianamine (NA), 234NIE. See Near iso-environmentNILs. See Near-isogenic linesNIRS. See Near infrared reflectance

spectroscopyNMR. See Nuclear magnetic resonanceNon-redundant database (NR database), 157Normalized Difference Vegetation Index

(NDVI), 348, 349, 357tNorth Carolina III (NCIII), 279

Index 433433

NPTC. See Nucellar projection transfer cellsNR database. See Non-redundant databaseNTT system. See Nuclear transportation trap

systemNucellar projection transfer cells (NPTC),

232–233Nuclear cytoplasmic domain (NCD), 222Nuclear magnetic resonance (NMR), 189,

365Nuclear transportation trap system (NTT

system), 218Nucleotide sequences, 155–156Nucleotide-binding adaptors shared by R

proteins (NB-ARC), 93Nutritional trait phenotyping

breeding programs in cereals, 364–365grain quality, 363macronutrients, 363metabolite profiling, 365metabolomics, 365microplate-based colorimetric

assays, 364NIR, 364NIRS, 364

OO2 modifiers (Opm), 230O2. See Opaque 2o7. See Opaque7O7 gene, 230–231Oil content, 234–235OMAP. See Oryza Map Alignment ProjectOmics revolution by high-throughput

techniques, 185–186See also Genome sequencefluxome, 190–191hormone role, 191–192metabolomics, 189–190phenomics, 192–193proteomics, 187–189transcriptomics, 186–187

Opaque 2 (O2), 229–230Opaque7 (o7), 230–231Open Reading Frame (ORF), 157, 163, 165Opm. See O2 modifiersOregon Wolfe Barley (OWB), 88ORF. See Open Reading FrameOrganism databases, 170Orthologous chromosome, 112OrthoMCL scalable method, 162–163Oryza Map Alignment Project (OMAP), 60Oryza sativa SSIIIa mutations (OsSSIIIa

mutations), 254

OryzaPG-DB, 188–189Osmotic adjustment, 356OWB. See Oregon Wolfe BarleyOxalate oxidase (OxO), 258

Pp-hydroxyphenylpyruvic acid (HPP), 264p-hydroxyphenylpyruvic acid dioxygenase

(HPPD), 264PAL. See Phenylalanine ammonia-lyasePan-grass polyploidization, 111Patching up process, 143PAVs. See Presence and absence variationsPCR-based markers, 386PDA. See Personal Digital AssistantPDS. See Phytoene desaturasePerfect match (PF), 16Personal Digital Assistant (PDA), 366PF. See Perfect matchPFANTOM. See Plant protein family

information-based predictor for endomembrane

PhenoFabTM, 344Phenolic acids, 258Phenomics, 192–193PHENOPSIS, 344Phenylalanine ammonia-lyase (PAL), 258Photosynthetic-driven plant biomass

accumulation, 352–353Phytoene desaturase (PDS), 261, 262Phytoene synthase gene (psy gene), 260, 261Pichia pastoris (P. pastoris), 256Plant Accelerator, 192–193, 344Plant genomes

See also Transposable elements (TE)genome contraction, 136–140scaffolds and gaps in selection of, 128fTE in, 130TE-driven genome expansion, 134–136

Plant protein family information-based predic-tor for endomembrane (PFANTOM), 253

Plant root monitoring platform (PlaRoM), 354Plants

abiotic stress effect, 177–178architecture, 325, 326life-cycle, 192phenotypes, 343

PlaRoM. See Plant root monitoring platformPolyphenol oxidase (PPO), 387Polyphenols, 256–260

flavonoids, 259–260hydroxyl groups, 256

Index434434

phenolic acids, 258phenylpropanoid pathway, 257fpolyphenol accumulation and composi-

tion, 257Post-translational modification (PTM), 164PPO. See Polyphenol oxidasepQTLs. See Protein Quantity LociPrecision field phenotyping

photosynthetic-driven plant biomass accu-mulation, 352–353

yield potential vs. stress adaptation, 351–352

Precision phenotypingbreeding perspective, 381NIEs concept, 381precision phenotyping, 381quantitative phenotypes, 381stress environment effect, 381–382

Presence and absence variations (PAVs), 5, 21–22, 69, 70

in maize, 43in rice, 43wheat exonic sequence alignments, 87

Protein Quantity Loci (pQTLs), 287–288Protein signature identification, 163

implementation, 165InterPro, 163–164InterPro entries, relationships between, 165InterProScan web interface, 165, 166f,

168fInterPro results, retrieving, 166, 168–169signature recognition approaches,

167–168tProteomics, 187

implication of proteomic studies, 188OryzaPG-DB, 188–189RIPP-DB, 188

Pseudomolecules, 128psy gene. See Phytoene synthase genePTM. See Post-translational modification

QQDs. See Quantum dotsQM. See QTL mappingQPM. See Quality protein maizeQTL. See Quantitative trait lociQTL mapping (QM), 276

based on LD, 295–297computer software for, 301–302joint linkage and AM, 298limitations, 302linkage-based methods, 282–291

mapping populations in cereals, 277–282MAYG, 291methodology and applications in cereal

breeding, 275–277QTLs cloning. See QTLs, cloning ofsystematic representation involved in, 226f

QTLs, cloning of, 298, 299biparental mapping populations, 299in cereals, 300tmapping and functional genomics, 298positional cloning, 299transgenics production, 300–301

QTs. See Quantitative traitsQuality protein maize (QPM), 230, 397, 400Quantitative trait loci (QTL), 251, 275, 321,

366Quantitative traits (QTs), 275Quantum dots (QDs), 14

RRAD. See Restriction site-associated DNARAD-seq. See Restriction-site associated

DNA sequencingRadial-microtubule systems (RMS), 222Randomized complete block design (RCBD),

350RBIP. See Retrotransposon-based insertion

polymorphismRCBD. See Randomized complete block

designrCIa1. See Full-length collagen type I alpha1RDA. See Recommended dietary allowanceRecent advancements

cloning domestication QTLs, 334rapid genome resequencing, 334reference genome for crop system, 334sampling strategies, 334stochastic factors, 334taxonomic sampling strategy, 335

Recombinant inbred advanced intercross lines (RIAILs), 278f, 280, 282

Recombinant inbred lines (RILs), 89, 277, 377–378t

development, 278population, 90, 91QTL analysis, 384

Recombination bins as markers, 58, 70Recommended dietary allowance (RDA), 260Reduced grain filling (rgf1), 228Reduced representation libraries (RRLs), 62Reduced representation sequencing, 62

complexity reduction approach, 89–90complexity-reduced libraries, 88–89

Polyphenols (cont.)

Index 435435

CRoPS, 62GBS, 89low coverage genotyping, 63–64OWB libraries, 88RAD markers, 87RAD method, 88RAD-seq, 62–63RNA-seq for SNP discovery, 63RRLs library, 62small gene-enriched fragments, 62targeted region-capture, 63

Resistant starchGBSS-I, 253OsSSIIIa, 254SBEIIa and SBEIIb, 255starch synthesis in cereals, 254f

Restriction fragment length polymorphism (RFLP), 5, 129, 378

Restriction site-associated DNA (RAD), 5, 87

markers, 42Restriction-site associated DNA sequencing

(RAD-seq), 62Retrotransposon-based insertion polymor-

phism (RBIP), 18, 21RFLP. See Restriction fragment length

polymorphismrgf1. See Reduced grain fillingRhizotrons, 354RIAILs. See Recombinant inbred advanced

intercross linesRice (Oryza sativa), 67, 178, 180

domestication alleles, rapid fixation, 330domestication genes cloning, 329FOX gene hunting system, 180loss-of-function mutations, 330phylogenetic and population genetic

analysis, 330reconciliation, 329rice domestication, 329rice domestication rate, 330

Rice Strata (RS), 112RIKEN Plant Phosphoproteome Database

(RIPP-DB), 188RILs. See Recombinant inbred linesRIPP-DB. See RIKEN Plant

Phosphoproteome DatabaseRLD. See Root length densityRMS. See Radial-microtubule systemsRoche NimbleGen, 18Root length density (RLD), 353–357Root system architecture (RSA), 353

heterosis, 355plant root system, 353

PlaRoM, 354rhizotronic facility with maize genotypes,

355frhizotrons, 354roots spatial distribution, 353–354screening techniques, 354shovelomics, 354

RRLs. See Reduced representation librariesRS. See Rice StrataRSA. See Root system architectureRye (Secale cereale), 67

SSBEIIa. See Starch branching enzymes of

class IIScanAlyzer, 344SCFAs. See Short chain fatty acidsSE. See Starchy endospermSecond generation sequencing

reduced representation sequencing, 62restriction enzyme based NGS for SNP,

60, 62restriction site-associated DNA, 62–63sequencing-based development, 61tSGSautoSNP, 64SNPs based on, 60

Seed abortioncarbon metabolism and carbon transport,

358effective seed number, 357sugar hunger, 358

Seed development in cereals, 215cereal seed structure, 216grain yield, 215sections of barley grain, 216f

Seed storage protein (SSP), 235Seed-specific promoters, 236

See also Seed development in cerealsHD-Zip IV transcription factor promoters,

237, 238HMW subunit gene, 236LTP gene promoters, 237

Selfish DNA, 131Semi-random (SR) library, 88Sequence based DNA markers

CNVs and PAVs, 69–70ISBP, 69recombination bins as markers, 70simple sequence repeats, 68–69single nucleotide polymorphisms, 59–67

Sequence capture methoddirect whole-genome sequencing, 85EST/cDNA sequences, 87

Index436436

liquid-phase sequence, 86oligonucleotide probes pool, 85OWB libraries, 88sequence capture methods, 85–86variable sites, 86fwheat exonic sequence alignments, 87

Sequenom MassARRAY system, 39–42SFP. See Single feature polymorphismShattering

genes controlling domestication traits, 323t

homeobox gene, 324non-brittle phenotype, 324non-brittle rachis, 324non-shattering phenotype, 324recessive mutation, 325reduction in shattering, 322

Short chain fatty acids (SCFAs), 256Shovelomics, 354Simple sequence repeat (SSR), 5, 58, 378

first generation sequence data, 68NGS data, 68–69

Single feature polymorphism (SFP), 19, 39Single nucleotide polymorphism (SNP), 5,

15, 58, 59, 77, 262, 295array-based SNPs vs. NGS

based-SNPs, 59co-segregation, 65–66first generation sequencing, 59–60genotype-specific SNP alleles, 66genotyping microarrays, 17in goat grass, 67in maize, 66NGS-based SNP discovery, tools for,

64–66redundancy score, 65in rice, 67in rye, 67second generation sequencing, 60–64and sequencing errors, 64–65sequence quality, 65in wheat, 67

SNP. See Single nucleotide polymorphismSoil texture, 346Soils, 346Sorghum bicolor (Sorghum), 103, 401Sorghum Strata (SS), 112Spikelets, 326SR. See Semi-randomSS. See Sorghum StrataSSP. See Seed storage proteinSSR. See Simple sequence repeat

Stable isotopes and low cost surrogatesash content of hybrids vs. inbreeds, 359f,

360fheterosis in maize, 359mineral accumulation, 359NIRS technique, 359oxygen and hydrogen isotope composition,

361thermal imaging, 361transpiration time-integrative indicator, 358

Starch Branching Enzymes (SBE) I-II, 253Starch branching enzymes of class II

(SBEIIa), 234Starch composition, 234Starch Synthase (SS) I–IV, 253Starchy endosperm (SE), 216Stay-green, 356

and delayed senescence, 357portable spectroradiometer use, 357fslow leaf growth rate, 356stay-green expression, 356, 357

Structural annotationgene prediction, 157–158masking repetitive DNA, 156

Structural variation (SV), 13, 19, 58, 69–70Sucrose 1-fructosyltransferase (1-SST), 255Super cluster creation, 161, 162Synteny, 141–142

TTagged array marker (TAM), 17, 21Tandem Repeat Finder (TRF), 156Targeting induced Local Lesions in Genome

(TILLING), 252, 264TaRSZ38, 218TCS. See Two-component systemTd. See Triticum dicoccoidesTDMs. See Transcript-derived markersTE. See Transposable elementsTE-driven genome expansion

classification system for TE, 135fLTR retrotransposons, 134, 136

Teosinte, 326–327Thick aleurone1 (thk1), 225Thin-layer chromatography (TLC), 363thk1. See Thick aleurone1Threshing

ability to, 322free-threshing, 324genes controlling domestication traits, 323thomeobox gene, 324non-brittle phenotype, 324

Sequence capture method (cont.)

Index 437437

non-brittle rachis, 324recessive mutation, 325

TILLING. See Targeting induced Local Lesions in Genome

Time-related mapping (TRM), 288–289TL. See Transfer cell layerTLC. See Thin-layer chromatography, Tocopherol synthesis, 263t, 264Tocotrienols, 262Tos17 retrotransposon, 146–147Trait genetics, 377, 378Traits and tools

See also Cereal breeding programsgrowth maintenance, 355–356metabolite profiling, 365novel tools for disease and insect-pest,

361–363nutritional trait phenotyping, 363–365organization and analysis, 365–366root system architecture and efficiency,

353–355seed abortion and early seed growth,

357–358stable isotopes and low cost surrogates,

358–361stay-green, 356–357

Transcript-derived markers (TDMs), 16, 19, 20

Transcriptome, 104Transcriptome-based analysis

alternative sequencing technology, 84B73 MAGI genomic assemblies, 84RNA-Seq, 83single-base resolution analysis, 84–85SNP discovery efforts, 83stringent filtering criterion, 83

Transcriptomics, 186–187Transfer cell layer (TL), 223, 232Transposable elements (TE), 130

adaptive value of, 144classification system for, 135fcrop plant maize, 145as evolutionary force, 143–144genome size determination, 133–134LINE retrotransposon activity, 144

TransposonsSee also Plant genomesAc/Ds elements, 145–146crop plant maize, 145in plants, 130–131Tos17 retrotransposon, 146–147transposon insertion mutant collections,

146

uses, for functional studies, 145TRF. See Tandem Repeat FinderTriticum dicoccoides (Td), 86TRM. See Time-related mappingTwo-component system (TCS), 228

UUltra-high-throughput nano-arrays/nano-chips,

14Ultra-Performance Liquid Chromatography

(UPLC), 364URLs links, omics related resources in cereals,

182–183tUV-B-mediated responses in maize, 196

VVariant detector array (VDA), 17Vitamin-E-defective (VTE3) enzyme, 262

WWater use efficiency (WUE), 352–353WGS approach. See Whole-genome shotgun

approachWheat (Triticum aestivum), 67, 184–185

free-threshing trait, 332free-threshing wheat, 332map-based QTL cloning, 331orthologous genes, 332

Whole genome re-sequencingB73 genome, 93bioinformatically challenging, 90deep whole-genome sequencing, 91heterosis hypotheses, 92high density resequencing microarrays,

15, 16finitiation methionine residue, 92large-effect SNPs, 93low-pass whole-genome, 93maize domestication, 94NGS shotgun sequencing, 92polymorphic genes, 92–93RIL population, 90–91selfing effect, 94SNP error rate, 91whole-genome sequencing studies, 90

Whole-genome shotgun approach (WGS approach), 127–128, 180

Wild progenitors, 327Wild-type allele, 327WUE. See Water use efficiency

Index438438

ζ-carotene desaturase genes (ZDS genes), 262Zinc-finger nuclear transcription factor, 325ZmAE1. See Zea mays androgenic embryo1ZmCR4 gene, 226ZmMRP-1 transcription factor, 228zmsmu2-1 mutants, 230zmsmu2-3 mutants, 230ZmTCRR-1 transcription factor, 228ZmTCRR-2 transcription factor, 228

Xxcl1. See extra cell layers 1Xylp. See β-D-xylopyranosyl

YYeast one-hybrid system (Y1H system),

217–218Yellow pigment content (YPC), 387

ZZea mays androgenic embryo1 (ZmAE1), 231Zero-mode waveguide (ZMW), 80