Genome-wide detection and characterization of positive selection in human populations

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With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2)1. We used ‘long-range haplotype’ methods, which were developed to identify alleles segregating in a population that have undergone recent selection2, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus3, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation4,5, in Europe; and EDAR and EDA2R, both involved in development of hair follicles6, in Asia.

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Figure 1: Localizing SLC24A5 and EDAR signals of selection.
Figure 2: Global distribution of SLC24A5 A111T and EDAR V370A.
Figure 3: Structural model of the EDAR death domain.


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P.C.S. is funded by a Burroughs Wellcome Career Award in the Biomedical Sciences and has been funded by the Damon Runyon Cancer Fellowship and the L’Oreal for Women in Science Award. We thank A. Schier, B. Voight, R. Roberts, M. Kreiger, A. Abzhanov, D. Degusta, M. Burnette, E. Lieberman, M. Daly, D. Altshuler, D. Reich, D. Lieberman and I. Woods for helpful discussions on our analysis and results. We also thank L. Ziaugra, D. Tabbaa and T. Rachupka for experimental assistance. This work was funded in part by grants from the National Human Genome Research Institute (to E.S.L.) and from the Broad Institute of MIT and Harvard.

Author Contributions P.C.S., P.V., B.F. and E.S.L. initiated the project. P.V., B.F. and P.C.S. developed key software. P.C.S., P.V., B.F., S.F.S., J.L., E.H., C.C., X.X., E.B., S.A.McC. and R.G. performed analysis. P.C.S., E.B. and E.H. performed experiments. P.C.S., E.S.L., P.V. and S.F.S. wrote the manuscript.

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Supplementary Information

The file contains Supplementary Methods, Supplementary Figures S1-S10 with Legends and Supplementary Tables 1-11. Supplementary Methods give details of LRH, iHS, XP-EHH, and localization analysis, including simulations and power calculations, Sweep software, ruling out confounders and details of identification of functional elements in the top candidates. Supplementary Tables illustrate power calculations for LRH, iHS, and XP-EHH, candidate regions and polymorphisms found from several analysis, fraction of SNPs predicted to be in the HapMap and dbSNP, as well as locations of copy number variants in the top candidates. Supplementary Figures show schematic of localization heuristic, power of LRH, iHS, and XP-EHH, top XP-EHH candidate,. localization of signal in LCT region, conservation, protein sequence and structure prediction, global variation, and examination of copy number variants for SLC24A5 and EDAR. (PDF 1482 kb)

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