Population genomics of rapid evolution in natural populations: Polygenic selection in response to power station thermal effluents

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Abstract

Background: Examples of rapid evolution are common in nature but difficult to account for with the standard population genetic model of adaptation. Instead, selection from the standing genetic variation permits rapid adaptation via soft sweeps or polygenic adaptation. Empirical evidence of this process in nature is currently limited but accumulating. Results: We provide genome-wide analyses of rapid evolution in Fundulus heteroclitus populations subjected to recently elevated temperatures due to coastal power station thermal effluents using 5449 SNPs across two effluent-affected and four reference populations. Bayesian and multivariate analyses of population genomic structure reveal a substantial portion of genetic variation that is most parsimoniously explained by selection at the site of thermal effluents. An FST outlier approach in conjunction with additional conservative requirements identify significant allele frequency differentiation that exceeds neutral expectations among exposed and closely related reference populations. Genomic variation patterns near these candidate loci reveal that individuals living near thermal effluents have rapidly evolved from the standing genetic variation through small allele frequency changes at many loci in a pattern consistent with polygenic selection on the standing genetic variation. Conclusions: While the ultimate trajectory of selection in these populations is unknown and we survey only a minority of genomic loci, our findings suggest that polygenic models of adaptation may play important roles in large, natural populations experiencing recent selection due to environmental changes that cause broad physiological impacts.

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Dayan, D. I., Du, X., Baris, T. Z., Wagner, D. N., Crawford, D. L., & Oleksiak, M. F. (2019). Population genomics of rapid evolution in natural populations: Polygenic selection in response to power station thermal effluents. BMC Evolutionary Biology, 19(1). https://doi.org/10.1186/s12862-019-1392-5

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