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Identification and Validation of Candidate Genes from Genome-Wide Association Studies

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Genome-Wide Association Studies

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2481))

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Abstract

Exploiting the statistical associations coming out from a GWAS experiment to identify and validate candidate genes may be potentially difficult and time consuming. To fill the gap between the identification of candidate genes toward their functional validation onto the trait performance, the prioritization of variants underlying the GWAS-associated regions is necessary. In parallel, recent developments in genomics and statistical methods have been achieved notably in human genetic and they are accordingly being adopted in plant breeding toward the study of the genetic architecture of traits to sustain genetic gains. In this chapter, we aim at providing both theoretical and practical aspects underlying three main options including (1) the MetaGWAS analysis, (2) the statistical fine map** and (3) the integration of functional data toward the identification and validation of candidate genes from a GWAS experiment.

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Authors and Affiliations

  1. Syngenta SAS France, Saint Sauveur, France

    Elise Albert & Christopher Sauvage

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  1. Elise Albert
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  2. Christopher Sauvage
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Editors and Affiliations

  1. Département de Phytologie, Université Laval, Quebec City, QC, Canada

    Davoud Torkamaneh

  2. Institut de biologie intégrative et des systems, Université Laval, Québec, QC, Canada

    François Belzile

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Albert, E., Sauvage, C. (2022). Identification and Validation of Candidate Genes from Genome-Wide Association Studies. In: Torkamaneh, D., Belzile, F. (eds) Genome-Wide Association Studies. Methods in Molecular Biology, vol 2481. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2237-7_15

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  • DOI: https://doi.org/10.1007/978-1-0716-2237-7_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2236-0

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