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Wide Distribution and Altitude Correlation of an Archaic High-altitude-adaptive EPAS1 Haplotype in the Himalayas

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Journal Hum Genet
Specialty Genetics
Date 2016 Feb 18
PMID 26883865
Citations 28
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Abstract

High-altitude adaptation in Tibetans is influenced by introgression of a 32.7-kb haplotype from the Denisovans, an extinct branch of archaic humans, lying within the endothelial PAS domain protein 1 (EPAS1), and has also been reported in Sherpa. We genotyped 19 variants in this genomic region in 1507 Eurasian individuals, including 1188 from Bhutan and Nepal residing at altitudes between 86 and 4550 m above sea level. Derived alleles for five SNPs characterizing the core Denisovan haplotype (AGGAA) were present at high frequency not only in Tibetans and Sherpa, but also among many populations from the Himalayas, showing a significant correlation with altitude (Spearman's correlation coefficient = 0.75, p value 3.9 × 10(-11)). Seven East- and South-Asian 1000 Genomes Project individuals shared the Denisovan haplotype extending beyond the 32-kb region, enabling us to refine the haplotype structure and identify a candidate regulatory variant (rs370299814) that might be interacting in an additive manner with the derived G allele of rs150877473, the variant previously associated with high-altitude adaptation in Tibetans. Denisovan-derived alleles were also observed at frequencies of 3-14% in the 1000 Genomes Project African samples. The closest African haplotype is, however, separated from the Asian high-altitude haplotype by 22 mutations whereas only three mutations, including rs150877473, separate the Asians from the Denisovan, consistent with distant shared ancestry for African and Asian haplotypes and Denisovan adaptive introgression.

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References
1.
Samaja M, Veicsteinas A, Cerretelli P . Oxygen affinity of blood in altitude Sherpas. J Appl Physiol Respir Environ Exerc Physiol. 1979; 47(2):337-41. DOI: 10.1152/jappl.1979.47.2.337. View

2.
Auton A, Brooks L, Durbin R, Garrison E, Kang H, Korbel J . A global reference for human genetic variation. Nature. 2015; 526(7571):68-74. PMC: 4750478. DOI: 10.1038/nature15393. View

3.
Bandelt H, Forster P, Rohl A . Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999; 16(1):37-48. DOI: 10.1093/oxfordjournals.molbev.a026036. View

4.
Stephens M, Scheet P . Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet. 2005; 76(3):449-62. PMC: 1196397. DOI: 10.1086/428594. View

5.
Peng B, Kimmel M . simuPOP: a forward-time population genetics simulation environment. Bioinformatics. 2005; 21(18):3686-7. DOI: 10.1093/bioinformatics/bti584. View