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Mapping and annotating genomic loci to prioritize genes and implicate distinct polygenic adaptations for skin color

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Authors

Kim, Beomsu; Kim, Dan Say; Shin, Joong-Gon; Leem, Sangseob; Cho, Minyoung; Kim, Hanji; Gu, Ki-Nam; Seo, Jung Yeon; You, Seung Won; Martin, Alicia R.; Park, Sun Gyoo; Kim, Yunkwan; Jeong, Choongwon; Kang, Nae Gyu; Won, Hong-Hee

Issue Date
2024-06
Publisher
Nature Publishing Group
Citation
Nature Communications, Vol.15 No.1, p. 4874
Abstract
Evidence for adaptation of human skin color to regional ultraviolet radiation suggests shared and distinct genetic variants across populations. However, skin color evolution and genetics in East Asians are understudied. We quantified skin color in 48,433 East Asians using image analysis and identified associated genetic variants and potential causal genes for skin color as well as their polygenic interplay with sun exposure. This genome-wide association study (GWAS) identified 12 known and 11 previously unreported loci and SNP-based heritability was 23-24%. Potential causal genes were determined through the identification of nonsynonymous variants, colocalization with gene expression in skin tissues, and expression levels in melanocytes. Genomic loci associated with pigmentation in East Asians substantially diverged from European populations, and we detected signatures of polygenic adaptation. This large GWAS for objectively quantified skin color in an East Asian population improves understanding of the genetic architecture and polygenic adaptation of skin color and prioritizes potential causal genes. Here, the authors perform a large GWAS for objectively quantified skin color in an East Asian population (N = 48,433), identifying potential causal genes, polygenic adaptations, and interaction between genetic variants and sun-exposure at polygenic level.
ISSN
2041-1723
URI
https://hdl.handle.net/10371/204939
DOI
https://doi.org/10.1038/s41467-024-49031-4
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  • College of Natural Sciences
  • School of Biological Sciences
Research Area Bioinformatics, Ecology, Evolutionary Biology, 생물정보학, 생태학, 유전체

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