Quantitative Genetics, Genomics and Plant Breeding

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Quantitative Genetics, Genomics and Plant Breeding
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Contents
Contributors
Foreword
Preface
1 Vignettes of the History of Genetics
	Mendelism
	Why Genetics was a Late Bloomer
	The Rise of Drosophila and Cytogenetics
	Mutation
	Non-nuclear Inheritance
	Pleiotropy
	Definition of the Gene
	Gene Numbers
	Transformation
	The Future of Genetics
	References
Section I:Quantitative Genetics: Plant Breeding, Bioinformatics, Genome Editing and G×E Interaction
	2 Food and Health: The Role of Plant Breeding
		Introduction
		Diet Diversity and Crop Uniformity
		Seeds, Food and Health
		How Consumers Defend Themselves
		What Can Plant Breeding Do?
		Summary and Conclusions
		References
	3 The Importance of Plant Pan-genomes in Breeding
		Introduction
		Plant Pan-genomes
		Importance of Pan-genomes in Plant Breeding
			Detection of single nucleotide polymorphisms within a pan-genome
			Understanding structural variations of resistance genes within a plant pan-genome
		Summary and Conclusions
		References
	4 Genome Editing Technologies for Crop Improvement
		Introduction
		Plant Disease Resistance
			CRISPR/Cas9 for resistance to plant viruses
			CRISPR/Cas9 for developing bacterial resistance
		Genome Modification for Nutritional Improvement
		Yield of Crop Plants
		Plant Domestication
		Medicinal Plants
		Some Advantages of CRISPR/Cas9 for Genome Editing in Plants
		Some Disadvantages of CRISPR/Cas9 for Plant Genetic Improvement
		Conclusion
		References
	5 Epigenome Editing in Crop Improvement
		Introduction
		Epigenetic Changes
			DNA methylation
			De novo DNA methylation
			Maintenance of DNA methylation
			Histone modifications
		Epigenome Modifications in Plants
		Epigenome Diversity Useful for Crop Breeding
			Non-targeted epigenetic diversity
			Targeted epigenetic diversity
		Genome Editing to Epigenome Editing
		Why Go for Epigenome Editing?
		Strategies of Epigenome Editing
		Prerequisites for Epigenome Editing
		Epigenetic Profiling of Target Region Related to Target Trait
		Non-coding RNAs and their Genome-wide Profiling in Plants
		Identifying the Role of ncRNAs in Plants
			siRNAs identification
			lncRNAs identification
		Epigenome Editing Approaches
			Random epigenome editing methods
			Epigenome editing through antimetabolite inhibitors
			Epigenome editing through tissue culture
			Overexpression of epigenetic effector/modifiers
		Precise Epigenome Editing Methods
			Targeting of siRNAs
			Targeting of lncRNAs
			Engineered DNA-binding domains fused with effector molecules
				Zinc finger protein-based epigenome editing tools
				Transcription activator-like effector-based epigenome editing tools
				CRISPR/dCas9-based epigenome editing tools
		Targeted Epigenome Editing Procedures in Plants
		Allele-specific Epigenome Editing
		General Applications of Epigenome Editing
		Limitations of Epigenome Editing Technology
		Future Prospects of Epigenome Editing in Crop Improvement
		References
	6 Bioinformatics and Plant Breeding
		Introduction
		Genetics and Molecular Markers
		Genomics and Pan-genomics
		Application of Molecular Markers in Plant Breeding
			Marker-assisted selection
			Genomic selection
			Genome editing
		Future Directions
			Real-time genotyping in the field
			Deep learning and crop breeding
		Summary
		References
	7 Bioinformatics Approaches for Pathway Reconstruction in Orphan Crops – A New Paradigm
		Introduction
		The Genome Assembly and Annotation Process
			The situation for orphan crops and species
			Sugarcane
			Miscanthus
			Miscanes
			White fonio ( Digitaria exilis)
			Lignin
			Conclusion
		Approaches to Assembling and Annotating Genes/Transcripts in Orphan Species
			The orphan species gene/transcript assembly problem
			The functional gene annotation problem
				The Gene Ontology
				The MapMan BIN Ontology
				The Planteome
			The plant interactome
			Plant pathway databases
				Plant Reactome
				KEGG
				PlantCyc
			Structural modelling
			Domain mapping
			Understanding biological function
			The importance of phylogenetics
			Natural language processing
				Implementing NLP for gene annotation
			The ‘annotatable gene space’
		The Sugarcane, Miscanthus and Fonio Blanc Lignin Pathways
			Transcript sequence confirmation by sequencing
			Regulation of the lignin pathway
			Extending the lignin pathway: an improved understanding of lignification
			Applications – quantitative PCR and expression microarrays
		Conclusion
		References
	8 Advances in QTL Mapping and Cloning
		Contemporary History of Quantitative Genetics
		Molecular Markers: A New Dimension in QTL Mapping
		Principles of QTL Mapping
		Methods of QTL Analysis
		Advances in High-throughput Genotyping
		Advances in High-throughput Phenotyping
		Advances in Mapping QTL
			Modified BSA strategies for mapping QTL
				QTL-Seq: an extension of BSA
				MutMap
				MutMap-Gap
				BSR-seq
			Genome-wide association: mapping QTL in natural population
			Consensus QTL detection using meta QTL analysis
			Positional cloning of QTL
			Homology-based cloning of QTL
		Future Research Priorities in QTL Mapping and Cloning
		References
	9 Genotype–Environment Interaction and Stability Analyses: An Update
		Introduction
		Crossover and Non-crossover Interactions
			Crossover or qualitative interaction
			Non-crossover or quantitative interaction
		Importance of GEI
		Achievements
		Causes of Genotype–Environment Interaction
			Environmental effect on the genome
			Biotic stresses
			Abiotic stresses
				Responses to temperature
				Oxidative stress
		How to Deal with GEI
			Concepts of stability
			Stability statistics
			Simultaneous selection for yield and stability
			Covariates and stability
			Stability variance for unbalanced data
		Testing and Breeding Strategies
			Breeding for resistance/tolerance to stresses
			Breeding for stability/reliability of performance
			Measure interaction at intermediate growth stages
			Early multi-environment testing
			Optimal resource allocation
		Outlook
		References
	10 Biplot Analysis of Multi-environment Trial Data
		Introduction
			Multi-environment trial data analysis
			Visualization of multi-environment trial data
		The GGE-biplot Methodology
			The concept of biplot
			Approximation of any two-way table using a rank-two matrix
			The concept of GGE
			Models for constructing a GGE biplot
				Singular value decomposition of environment-centred data
				Singular value decomposition of within- environment standard deviation-scaled data
		Biplot Analysis of Multi-environment Trial Data: An Example
			The steps in biplot analysis
			Visualizing the performance of different genotypes in a given environment
			Visualizing the relative adaptation of a given genotype in different environments
			Visual comparison of two genotypes in different environments
			Visual identification of the best genotype(s) for each environment
			Visualizing groups of environments
			Visualizing the mean performance and stability of genotypes
			Visualizing the discriminating ability and representativeness of environments
			Strength of the GGE-biplot approach
			Constraints of the GGE-biplot approach
			Other applications of the GGE-biplot approach
		New Developments Regarding GGE-biplot Analysis Since 2002
			Heritability-enriched GGE biplot for test environment evaluation
			GGE-GGL biplot to identify repeatable GEI
			LG biplot for mega-environments analysis
			GYT biplot for genotype evaluation based on multiple traits
		Acknowledgements
		References
	11 Design and Analysis of Multi-year Field Trials for Annual Crops
		Introduction
		Design of Field Trials
			Within-field design
				Lattices and alpha-designs
				Row–column designs
				Latinized rows and columns
				Repeated checks
			Across-fields design
				Within years
				Across years
		Analysis of Field Trials
			Single-field analysis
			Combined analysis across fields
				Estimating genotype performance: a mixed-model approach
				Estimating genotype performance: genotype-by-environment interaction
				Estimating variance components: single-year versus multi-year analysis
		Description, Presentation and Summarization
			Presentation of the results from spatial analysis of single fields (first-stage)
			Graphical presentation of combined analysis across fields
				Graphical representation of two-way two-mode tables
				Graphical representation of three-way, three-mode arrays
		Conclusion
		References
	12 Advances in the Definition of Adaptation Strategies and Yield-stability Targets in Plant Breeding
		Introduction
		Adaptation and Yield Stability
		An Analytical Flow Chart
		Analysis of Adaptation
		Comparison of Wide- versus Specific-adaptation Strategies
		Definition of Selection Environments
		Climate Change and Genotype– environment Interactions
		Conclusions and Perspectives
		Acknowledgements
		References
Section II:Intersection of Breeding, Genetics and Genomics: Crop Examples
	13 Prediction with Big Data in the Genomic and High-throughput Phenotyping Era: A Case Study with Wheat Data
		Introduction
		Materials and Methods
			Phenotypic data
			Markers
			Pedigree
			Statistical models
				Model 1: genomic G×E interaction using markers
				Model 2: pedigree G×E interaction
				Model 3: item-based collaborative filtering (IBCF)
			Assessing prediction accuracy
		Results
		Discussion
		Summary and Concluding Remarks
		References
		Appendix
	14 Quantitative Genetics in Improving Root and Tuber Crops
		Introduction
		Breeding Methods, Inbreeding Depression, Epistasis and Heterosis in RTBs
			Heterosis
			Inbreeding
			Epistasis
			Advantages of inbreeding
		Assessing Epistasis in Diallel Crosses in RTB Crops
			Statistical model
			Results
		References
	15 Genomic Selection in Rice: Empirical Results and Implications for Breeding
		Introduction
		Factors Affecting the Predictive Ability of Genomic Prediction in Rice
			Characteristics of the training population
			Effect of trait characteristics
			Effect of characteristics of genotypic data (marker density, linkage disequilibrium and minor allele frequency)
			Effect of prediction methods
		Designing Training Population for Pedigree Breeding
		Integrating Trait-specific Marker Selection
		Accounting for GEI to Breed for Tolerance to Abiotic Stresses
		Implications for Breeding Rice
		Summary
		References
	16 Novel Breeding Approaches for Developing Climate-resilient Rice
		Introduction
		Abiotic Stresses and Tolerance Mechanisms in Rice
		Conventional and Mutation Breeding
		Novel Approaches to Improve Abiotic Stress Tolerance in Rice
			Genomics
				QTL mapping
				Genome-wide association studies
				Marker-assisted selection
				Genomic selection
			Transcriptomics
			Proteomics
			Metabolomics
			Phenomics
			Transgenic approach
			Genome editing
		Conclusion and Future Prospects
		References
	17 Quantitative Genetics, Molecular Techniques and Agronomic Performance of Provitamin A Maize in Sub-Saharan Africa
		Introduction
		Quantitative Genetics of Maize Provitamin A
			Screening maize germplasm collection at the International Institute of Tropical Agriculture for provitamin A
			Genetic diversity/variation for provitamin A content in the maize germplasm
			Laboratory screening methods
			Genetic variability for provitamin A and its components
			Mode of inheritance and heritability estimates
			Genotype-by-environment interactions for carotenoid concentrations
			Population improvement and development of open-pollinated varieties
		Molecular Approaches to Provitamin A Enhancement in Maize
		Agronomic Performance of Provitamin A Maize in Sub-Saharan Africa
			Development of varieties, inbreds and hybrids with enhanced provitamin A content and tolerance to multiple stresses
			Evaluation of maize inbred lines and hybrids – GCA, SCA, testers and heterotic groupings of early and extra-early PVA inbred lines at IITA
			Combining ability and heterotic patterns of the International Institute of Tropical Agriculture’s extra-early and early provitamin A inbred lines
				Extra-early inbred lines
				Early inbred lines
			Interrelationships among traits of extra-early provitamin A maize hybrids under drought and Striga -infested environments
		Summary and Conclusions
		Acknowledgements
		References
	18 Developments in Genomics Relative to Abiotic Stress-tolerance Breeding in Maize During the Past Decade
		Introduction
		Maize Phenotyping
		The Advent of Genomics in Plant Breeding
		Marker-assisted Recurrent Selection
		Genome-wide Association Studies
			Genome-wide association mapping in maize
			Genomic selection
			Genomic selection in maize stress-tolerance breeding
			Statistical models in genomic selection
		Genotyping by Sequencing
		Resequencing
		Genome Editing
		Conclusions
		References
	19 Exploiting Alien Genetic Variation for Germplasm Enhancement in Brassica Oilseeds
		Introduction
		Family Brassicaceae
			Brassica coenospecies
		Wide Hybridization
			Constraints and amendments for alien gene transfer
				Sexual incongruity
			Genetic conduits for alien gene transfer
				Interspecific or intergeneric hybridization
				Synthetic amphidiploids
				Monosomic and disomic alien addition lines
				Chromosome substitution lines
				Alien introgression lines
		Cytogenetic and Molecular Characterization of Wide Hybrids and Backcross Derivatives
		Case Studies for Successful Use of Brassica Wild Relatives for Germplasm Enhancement
			Development of CMS (cytoplasmic male-sterile) and fertility restorer lines
			Disease resistance
			Pest resistance
			Resistance to abiotic stresses
			Genes for quality traits
		Summary
		References
	20 Biofortified Pearl Millet Cultivars Offer Potential Solution to Tackle Malnutrition in India
		Introduction
		Why Biofortify Pearl Millet?
		Breeding Target for Biofortified Pearl Millet
		Improved Phenotyping Protocol
		Cultivar Development Strategy
		Current Status and Future Prospects for Biofortified Pearl Millet Cultivars
		Biofortified Cultivar Release Policy
		Nutritional Bioavailability and Efficacy Evidence
		The Way Forward to Eradicate Malnutrition in India
		Summary and Conclusions
		References
Index
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