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Wild GWAS—association mapping in natural populations
Author(s) -
Santure Anna W.,
Garant Dany
Publication year - 2018
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12901
Subject(s) - biology , genome wide association study , association mapping , epistasis , genotyping , genetic association , evolutionary biology , quantitative trait locus , genetics , identification (biology) , population , trait , computational biology , genotype , single nucleotide polymorphism , ecology , gene , demography , sociology , computer science , programming language
The increasing affordability of sequencing and genotyping technologies has transformed the field of molecular ecology in recent decades. By correlating marker variants with trait variation using association analysis, large‐scale genotyping and phenotyping of individuals from wild populations has enabled the identification of genomic regions that contribute to phenotypic differences among individuals. Such “gene mapping” studies are enabling us to better predict evolutionary potential and the ability of populations to adapt to challenges, such as changing environment. These studies are also allowing us to gain insight into the evolutionary processes maintaining variation in natural populations, to better understand genotype‐by‐environment and epistatic interactions and to track the dynamics of allele frequency change at loci contributing to traits under selection. Gene mapping in the wild using genomewide association scans ( GWAS ) do, however, come with a number of methodological challenges, not least the population structure in space and time inherent to natural populations. We here provide an overview of these challenges, summarize the exciting methodological advances and applications of association mapping in natural populations reported in this special issue and provide some guidelines for future “wild GWAS ” research.