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

By Sean M. Hoban, Joanna L. Kelley, K. Lotterhos, M. Antolin, Gideon Bradburd, D. Lowry, M. Poss, Laura K. Reed, Andrew Storfer, M. Whitlock. American Naturalist, 2016

736 citations recorded by the source corpus.

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.

Subfields: Genetics

View Paper: https://www.semanticscholar.org/paper/6b203399d917097d6e897b0bc4f628f8453d0419

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In Genetics

Citations in the corpus

The genomics of local adaptation in trees: are we out of the woods yet? (2017, background): “…size, type, location, expression, pleiotropic effect, environmental influence, and interaction of underlying loci), which is generally not known a priori (Stinchcombe & Hoekstra 2008; Rellstab et al. 2015; Savolainen et al. 2013; Hoban et al. 2016; Burghardt et al. 2017; Wadgymar et al. 2017).”
Identifying targets and agents of selection: innovative methods to evaluate the processes that contribute to local adaptation (2017, background): “In those cases, two types of studies involving genome-wide or candidate gene resequencing can illuminate mutations underlying local adaptation: (i) genome scans and (ii) genotype–environment association studies (Rellstab et al. 2015; Hoban et al. 2016).”
Advances in the Application of Genetics in Marine Turtle Biology and Conservation (2017, background): “Additionally, SNPs in coding regions can be used to understand genotype and phenotype linkages and identify loci under selection if adequate genomic and budget resources are available (Hoban et al., 2016; Todd et al., 2016).”
Landscape Genomics: Understanding Relationships Between Environmental Heterogeneity and Genomic Characteristics of Populations (2017, background): “For example, several very helpful studies already exist that compare different approaches for identifying adaptive genetic variation in landscape genomics (e.g., Rellstab et al. 2015; Forester et al. 2016; Hoban et al. 2016; Rajora et al. 2016) and that highlight issues with some of the more promine”
Lessons on Evolution from the Study of Edaphic Specialization (2017, background): “Genome scans, when combined with candidate gene approaches, comparative transcriptomics, QTL mapping, functional analysis, and experimental manipulation, can reveal loci with high levels of differentiation between edaphically divergent populations, enabling the discovery of genes driving adaptation ”