Genomic signatures of climate adaptation in bank voles
收藏NIAID Data Ecosystem2026-05-01 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.1c59zw42p
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Evidence for divergent selection and adaptive variation across the landscape 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 climate mediated 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 (Clethrionomys glareolus) distributed across Europe. To identify the loci subject to selection 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 loci for adaptation, 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 influenced by local climate in bank voles.
Methods
We investigate genomic adaptations in a small mammal distributed throughout Europe (3,200 km) using a multivariate and multimethod approach. We sampled 12 populations and 276 individuals using a ddRAD sequencing approach. We found strong spatial structuring of populations, and identified candidate genes for climate adaptation using genotype-environmental association methods.
创建时间:
2024-02-19



