Affiliations 

  • 1 Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
  • 2 Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 200031, China
  • 3 State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
  • 4 School of Medicine, Xizang University for Nationalities, Xianyang 712082, Shaanxi, China
  • 5 Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University, Urumqi 830011, China
  • 6 Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Faculty of Medicine and Health Sciences, UCSI University, Kualal Lumpur Campus, Jalan Choo Lip Kung, Taman Taynton View, 56000 Cheras, Kuala Lumpur, Malaysia
  • 7 Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seocho-gu, Seoul 137-701, Korea
  • 8 State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
  • 9 Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 200031, China; Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China. Electronic address: xushua@picb.ac.cn
Am J Hum Genet, 2015 Jul 02;97(1):54-66.
PMID: 26073780 DOI: 10.1016/j.ajhg.2015.05.005

Abstract

Tibetan high-altitude adaptation (HAA) has been studied extensively, and many candidate genes have been reported. Subsequent efforts targeting HAA functional variants, however, have not been that successful (e.g., no functional variant has been suggested for the top candidate HAA gene, EPAS1). With WinXPCNVer, a method developed in this study, we detected in microarray data a Tibetan-enriched deletion (TED) carried by 90% of Tibetans; 50% were homozygous for the deletion, whereas only 3% carried the TED and 0% carried the homozygous deletion in 2,792 worldwide samples (p < 10(-15)). We employed long PCR and Sanger sequencing technologies to determine the exact copy number and breakpoints of the TED in 70 additional Tibetan and 182 diverse samples. The TED had identical boundaries (chr2: 46,694,276-46,697,683; hg19) and was 80 kb downstream of EPAS1. Notably, the TED was in strong linkage disequilibrium (LD; r(2) = 0.8) with EPAS1 variants associated with reduced blood concentrations of hemoglobin. It was also in complete LD with the 5-SNP motif, which was suspected to be introgressed from Denisovans, but the deletion itself was absent from the Denisovan sequence. Correspondingly, we detected that footprints of positive selection for the TED occurred 12,803 (95% confidence interval = 12,075-14,725) years ago. We further whole-genome deep sequenced (>60×) seven Tibetans and verified the TED but failed to identify any other copy-number variations with comparable patterns, giving this TED top priority for further study. We speculate that the specific patterns of the TED resulted from its own functionality in HAA of Tibetans or LD with a functional variant of EPAS1.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.