Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions

Abstract

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species’ demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Breaking RAD: An evaluation of the utility of restriction site associated DNA sequencing for genome scans of adaptation

“…Some missing data and artefacts are caused by structural differences (insertions, deletions, inversions, etc. ) between resequenced individuals and the reference genome to which they are aligned (Tiffin & Ross-Ibarra 2014;Hoban et al 2016). Finally, it is important that researchers retain invariant sites in their data sets to accurately calculate population genetic summary statistics and demographic parameters.…”

“…Other reviews have outlined these problems, which include the confounding effects of population structure, demographic history and issues with analytical methods (Lotterhos & Whitlock 2014;Tiffin & Ross-Ibarra 2014;Rellstab et al 2015;Hoban et al 2016). However, the problem with RADseq is with the marker data sets themselves, which are often far too sparse to have a reasonable chance of detecting the loci involved in adaptation.…”

Recent advances in conservation and population genomics data analysis

“…Technological and analytical advances now allow us to use many thousands of loci, gene expression, or epigenetics to address basic questions of relevance for conservation, such as identifying loci associated with local adaptation or adaptive potential in species face changing environments (Bernatchez, 2016; Flanagan, Forester, Latch, Aitken, & Hoban, 2017; Harrisson et al., 2014; Hoban et al., 2016; Hoffmann et al., 2015; Jensen, Foll, & Bernatchez, 2016; Le Luyer et al., 2017; Wade et al., 2016). As conservation genomics matures, new challenges are arising.…”

‘Intentional Genetic Manipulation’ as a conservation threat

“…There is an urgent need to understand the underlying genetic basis of the traits that are currently being selected on wildlife ranches and to determine how allele frequencies differ between ranched and wild populations. This knowledge can be achieved through analysis of candidate genes, experiments and/or by using shared records on breeding outcomes from the ranchers, though we recognise that the genetic basis of some traits will be more difficult than others to document (Hoban et al 2016). There is now a broader knowledge base on the genetic underpinning of coat colour in wild and domestic animals (e.g.…”