Distinguishing Among Modes of Convergent Adaptation Using Population Genomic Data

Abstract

Geographically separated populations can convergently adapt to the same selection pressure. Convergent evolution at the level of a gene may arise via three distinct modes. The selected alleles can (1) have multiple independent mutational origins, (2) be shared due to shared ancestral standing variation, or (3) spread throughout subpopulations via gene flow. We present a model-based, statistical approach that utilizes genomic data to detect cases of convergent adaptation at the genetic level, identify the loci involved and distinguish among these modes. To understand the impact of convergent positive selection on neutral diversity at linked loci, we make use of the fact that hitchhiking can be modeled as an increase in the variance in neutral allele frequencies around a selected site within a population. We build on coalescent theory to show how shared hitchhiking events between subpopulations act to increase covariance in allele frequencies between subpopulations at loci near the selected site, and extend this theory under different models of migration and selection on the same standing variation. We incorporate this hitchhiking effect into a multivariate normal model of allele frequencies that also accounts for population structure. Based on this theory, we present a composite-likelihood-based approach that utilizes genomic data to identify loci involved in convergence, and distinguishes among alternate modes of convergent adaptation. We illustrate our method on genome-wide polymorphism data from two distinct cases of convergent adaptation. First, we investigate the adaptation for copper toxicity tolerance in two populations of the common yellow monkey flower, We show that selection has occurred on an allele that has been standing in these populations prior to the onset of copper mining in this region. Lastly, we apply our method to data from four populations of the killifish,, that show very rapid convergent adaptation for tolerance to industrial pollutants. Here, we identify a single locus at which both independent mutation events and selection on an allele shared via gene flow, either slightly before or during selection, play a role in adaptation across the species' range.

Parallel and nonparallel genomic responses contribute to herbicide resistance in Ipomoea purpurea, a common agricultural weed

“…We sought to determine the most likely model for genomic convergence by determining whether potential selected alleles within regions exhibited multiple independent origins, were spread among populations via gene flow, or were shared among populations due to ancestral standing variation. To do so, we applied the inference method of Lee and Coop [33] which builds on coalescent theory to show how shared hitchhiking events influence the covariance structure of allele frequencies between populations at loci near the selected site. We first focused our formal tests of convergence on the enriched region of chromosome 10 given that it exhibited the strongest signature of differentiation between resistant and susceptible populations, and that the same haplotype was shared with the majority of individuals from resistant populations.…”

Beyond parallel evolution: when several species colonize the same environmental gradient

“…Therefore, identifying a relevant framework with replicates of ecological divergence with independent genetic backgrounds (i.e. isolated species with complete allelic sorting) is still essential to disentangle the effects of selection in response to the environment from other evolutionary mechanisms (Foote, 2018;Lee and Coop, 2017). The repeated colonization of the same environmental gradient by several species thus provides a third approach to study independent replicates of ecological divergence.…”

Genomics of Long- and Short-Term Adaptation in Maize and Teosintes

“…Recently, a new method has been developed to infer modes of convergence [118], using covariance of allele frequencies in windows around a selected site to explicitly compare different models of origin for a selected variant. This novel method should give a better insight on the genetic mechanisms underlying convergence.…”