A Guide to Genome-Wide Association Mapping in Plants

Liana T. Burghardt, Nevin D. Young, Peter Tiffin

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

Genome-wide association studies (GWAS) have developed into a valuable approach for identifying the genetic basis of phenotypic variation. In this article, we provide an overview of the design, analysis, and interpretation of GWAS. First, we present results from simulations that explore key elements of experimental design as well as considerations for collecting the relevant genomic and phenotypic data. Next, we outline current statistical methods and tools used for GWA analyses and discuss the inclusion of covariates to account for population structure and the interpretation of results. Given that many false positive associations will occur in any GWA analysis, we highlight strategies for prioritizing GWA candidates for further statistical and empirical validation. While focused on plants, the material we cover is also applicable to other systems.

Original languageEnglish (US)
Pages (from-to)22-38
Number of pages17
JournalCurrent protocols in plant biology
Volume2
Issue number1
DOIs
StatePublished - Mar 1 2017

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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