Genomic signatures of climate adaptation in bank voles

Abstract

Evidence for spatially varying selection and adaptive variation can provide insight into a species’ ability to adapt to different environments. However, despite recent advances in genomics, it remains difficult to detect footprints of spatially varying selection in natural populations. Here we analysed ddRAD sequencing data (21,892 SNPs) in conjunction with geographic climate variation to search for signatures of adaptive differentiation in twelve populations of the bank vole (Myodes/Clethrionomys glareolus) distributed across Europe. To identify the loci subject to spatially varying selection and associated with climate variation, we applied multiple genotype-environment association (GEA) methods, two univariate and one multivariate, and controlled for the effect of population structure. In total, we identified 213 candidate adaptive loci, 74 of which were located within genes. In particular, we identified signatures of selection in candidate genes with functions related to lipid metabolism and the immune system. Using the results of redundancy analysis (RDA), we demonstrated that population history and climate have joint effects on the genetic variation in the pan-European metapopulation. Furthermore, by examining only candidate loci, we found that annual mean temperature is an important factor shaping adaptive genetic variation in the bank vole. By combining landscape genomic approaches, our study sheds light on genome-wide adaptive differentiation and the spatial distribution of variants underlying adaptive variation in bank voles that are influenced by local climate.

iHDSel software: The Price equation and the population stability index to detect genomic patterns compatible with selective sweeps. An example with SARS-CoV-2.

“…Finally, some genomic patterns of selection correlate with environmental variables, making it difficult to separate both effects (Folkertsma et al 2024). The method proposed here could be combined with other methods that take this correlation into account.…”

“…Therefore, if we use two samples to compare the effect of the sweep, they can be separated by time or space. Detecting the footprint of natural selection in genomes in general, and specifically divergent selection, is important for studying speciation processes (Galindo et al 2021) and climate adaptation (Folkertsma et al 2024), but also for more immediate effects such as resistance to infections in commercially important marine species (Pampín et al 2023; Vera et al 2023).…”