Modern genomics in studying the problems of human adaptation to climate in north Siberia
Background: Indigenous people of north Siberia live in some of the harshest natural conditions on Earth, experiencing prolonged exposure to cold, large fluctuations in the length of daylight, and a limited diet. It is obvious that the successful occupation of such extremely difficult territories is connected not only with cultural but also with genetic adaptation. However, specific mechanisms of genetic adaptation to the cold climate and animal fat-rich diet still remain poorly understood. The aim of the study: To explore markers of polygenic selection for fat-rich diet and climate stress in the high northern latitudes. Materials and methods: The study consisted of three stages. At the first stage, we performed selection scans on whole exome and genome-wide single nucleotide polymorphism array data from the populations of Nganasans (N=21) and Yakuts (N=21). At the second stage, in the tails of empirical distributions, candidate genes associated with biological processes and phenotypes related to adaptation in circumpolar groups were revealed. At the third stage, the best candidates were genotyped in additional Siberian populations to determine the spatial distribution of allele frequencies and their associations with climatic variables. Results: We have identified several candidate genes, the most relevant being PLA2G2A, PLIN1, and ANGPTL8 genes involved in lipid metabolism and related to brown adipose tissue. Missense mutations in these genes exhibit spatial patterns consistent with selection for cold climate and/or diet. Conclusion: The results support the hypothesis that indigenous populations in Siberia have genetically adapted to harsh environments by selection on multiple genes related mostly to fat metabolism.
Osipova LP, Lichman DV, Hallmark B, et al. Modern genomics in studying the problems of human adaptation to climate in north Siberia. Research Results in Biomedicine. 2020;6(3):323-337. Russian. DOI:10.18413/2658-6533-2020- 6-3-0-4
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Authors was supported by RSF, according to the research project No. 19-15-00219 (grant No. 19-15-00219)