Detecting polygenic selection in marine populations by combining population genomics and quantitative genetics approaches

Pierre-Alexandre Gagnaire, Oscar Eduardo Gaggiotti

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)


Highly fecund marine species with dispersive life-history stages often display large population sizes and wide geographic distribution ranges. Consequently, they are expected to experience reduced genetic drift, efficient selection fueled by frequent adaptive mutations, and high migration loads. This has important consequences for understanding how local adaption proceeds in the sea. A key issue in this regard, relates to the genetic architecture underlying fitness traits. Theory predicts that adaptation may involve many genes but with a high variance in effect size. Therefore, the effect of selection on allele frequencies may be substantial for the largest effect size loci, but insignificant for small effect genes. In such a context, the performance of population genomic methods to unravel the genetic basis of adaptation depends on the fraction of adaptive genetic variance explained by the cumulative effect of outlier loci. Here, we address some methodological challenges associated with the detection of local adaptation using molecular approaches. We provide an overview of genome- scan methods to detect selection, including those assuming complex demographic models that better describe spatial population structure. We then focus on quantitative genetics approaches that search for genotype-phenotype associations at different genomic scales, including genome-wide methods evaluating the cumulative effect of variants. We argue that the limited power of single locus tests can be alleviated by the use of polygenic scores to estimate the joint contribution of candidate variants to phenotypic variation.
Original languageEnglish
Pages (from-to)603-616
Number of pages14
JournalCurrent Zoology
Issue number6
Early online date23 Aug 2016
Publication statusPublished - Dec 2016


  • Local adaptation
  • Genome scans
  • Quantitative genetics
  • Genotype-phenotype association
  • Polygenic scores


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