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Molecular Phylogeography of a Human Autosomal Skin Color Locus Under Natural Selection

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      Abstract

      Divergent natural selection caused by differences in solar exposure has resulted in distinctive variations in skin color between human populations. The derived light skin color allele of the SLC24A5 gene, A111T, predominates in populations of Western Eurasian ancestry. To gain insight into when and where this mutation arose, we defined common haplotypes in the genomic region around SLC24A5 across diverse human populations and deduced phylogenetic relationships between them. Virtually all chromosomes carrying the A111T allele share a single 78-kb haplotype that we call C11, indicating that all instances of this mutation in human populations share a common origin. The C11 haplotype was most likely created by a crossover between two haplotypes, followed by the A111T mutation. The two parental precursor haplotypes are found from East Asia to the Americas but are nearly absent in Africa. The distributions of C11 and its parental haplotypes make it most likely that these two last steps occurred between the Middle East and the Indian subcontinent, with the A111T mutation occurring after the split between the ancestors of Europeans and East Asians.

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      An integrated map of genetic variation from 1,092 human genomes

      Summary Through characterising the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help understand the genetic contribution to disease. We describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methodologies to integrate information across multiple algorithms and diverse data sources we provide a validated haplotype map of 38 million SNPs, 1.4 million indels and over 14 thousand larger deletions. We show that individuals from different populations carry different profiles of rare and common variants and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways and that each individual harbours hundreds of rare non-coding variants at conserved sites, such as transcription-factor-motif disrupting changes. This resource, which captures up to 98% of accessible SNPs at a frequency of 1% in populations of medical genetics focus, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.
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        A new statistical method for haplotype reconstruction from population data.

        Current routine genotyping methods typically do not provide haplotype information, which is essential for many analyses of fine-scale molecular-genetics data. Haplotypes can be obtained, at considerable cost, experimentally or (partially) through genotyping of additional family members. Alternatively, a statistical method can be used to infer phase and to reconstruct haplotypes. We present a new statistical method, applicable to genotype data at linked loci from a population sample, that improves substantially on current algorithms; often, error rates are reduced by > 50%, relative to its nearest competitor. Furthermore, our algorithm performs well in absolute terms, suggesting that reconstructing haplotypes experimentally or by genotyping additional family members may be an inefficient use of resources.
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          A second generation human haplotype map of over 3.1 million SNPs.

          We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.
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            Author and article information

            Affiliations
            [* ]Department of Pharmacology, Penn State College of Medicine, Hershey, Pennsylvania 17033
            []Penn State Cancer Institute, Penn State College of Medicine, Hershey, Pennsylvania 17033
            []Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania 17033
            [§ ]Jake Gittlen Cancer Research Foundation, Penn State College of Medicine, Hershey, Pennsylvania 17033
            [** ]Division of Experimental Pathology, Penn State College of Medicine, Hershey, Pennsylvania 17033
            [†† ]School of Anthropology and Museum Ethnography, Oxford University, Oxford, OX2 6PE, UK
            Author notes

            Supporting information is available online at http://www.g3journal.org/lookup/suppl/doi:10.1534/g3.113.007484/-/DC1

            [1 ]Corresponding authors: Department of Pharmacology, R130, Penn State College of Medicine, 500 University Drive, Hershey, PA 17033. E-mail: vcanfield@ 123456gmail.com ; and Jake Gittlen Cancer Research Foundation, Penn State College of Medicine, 500 University Drive, Hershey, PA 17033. E-mail: kcheng76@ 123456gmail.com
            Journal
            G3 (Bethesda)
            Genetics
            G3: Genes, Genomes, Genetics
            G3: Genes, Genomes, Genetics
            G3: Genes, Genomes, Genetics
            G3: Genes|Genomes|Genetics
            Genetics Society of America
            2160-1836
            1 November 2013
            November 2013
            : 3
            : 11
            : 2059-2067
            24048645
            3815065
            GGG_007484
            10.1534/g3.113.007484
            Copyright © 2013 Canfield et al.

            This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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            Pages: 9
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            Investigations
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            v1

            Genetics

            natural selection, skin color, slc24a5, haplotype, recombination

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