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This detailed collection explores genome-wide association studies (GWAS), which have revolutionized the investigation of complex traits over the past decade and have unveiled numerous useful genotype-phenotype associations in plants. The book describes the key concepts and methods underlying GWAS, including the genetic architecture underlying variation for phenotypic traits, the structure of genetic variation in plants, technologies for capturing genetic information, study designs, and the statistical models and bioinformatics tools used for data analysis. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of invaluable implementation advice that leads to the most fruitful research results.
Authoritative and practical, Genome-Wide Association Studies serves as an extremely valuable resource for the plant research community by rendering GWAS analysis less challenging and more accessible to a broader group of users.
List of contents
Designing a Genome-Wide Association Study: Main Steps and Critical Decisions.- Preparation and Curation of Phenotypic Datasets.- Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerations.- Genome-Wide Association Study Statistical Models: A Review.- Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies.- Preparation and Curation of Multi-Year, Multi-Location, Multi-Trait Datasets.- Development, Preparation, and Curation of High-Throughput Phenotypic Data for Genome-Wide Association Studies: A Sample Pipeline in R.- Preparation and Curation of Omics Data for Genome-Wide Association Studies.- Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies.- A Practical Guide to Using Structural Variants for Genome-Wide Association Studies.- Data Integration, Imputation, and Meta-Analysis for Genome-Wide Association Studies.- Population Structure and Relatedness for Genome-Wide AssociationStudies.- Performing Genome-Wide Association Studies with Multiple Models Using GAPIT.- Performing Genome-Wide Association Studies Using rMVP.- Identification and Validation of Candidate Genes from Genome-Wide Association Studies.- Biparental Crossing and QTL Mapping for Genome-Wide Association Studies Validation.- Development of Breeder Friendly KASP Markers from Genome-Wide Association Studies Results.- Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies.- GWAS Case Studies in Wheat.- Plant Microbiome-Based Genome-Wide Association Studies.
