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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-10-31

AUTHORS

Gil A. McVean, David M. Altshuler (Co-Chair), Richard M. Durbin (Co-Chair), Gonçalo R. Abecasis, David R. Bentley, Aravinda Chakravarti, Andrew G. Clark, Peter Donnelly, Evan E. Eichler, Paul Flicek, Stacey B. Gabriel, Richard A. Gibbs, Eric D. Green, Matthew E. Hurles, Bartha M. Knoppers, Jan O. Korbel, Eric S. Lander, Charles Lee, Hans Lehrach, Elaine R. Mardis, Gabor T. Marth, Gil A. McVean, Deborah A. Nickerson, Jeanette P. Schmidt, Stephen T. Sherry, Jun Wang, Richard K. Wilson

ABSTRACT

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here 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 methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 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 contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. More... »

PAGES

56-65

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  • Journal

    TITLE

    Nature

    ISSUE

    7422

    VOLUME

    491

    Author Affiliations

  • Department of Statistics, Oxford University, OX1 3TG, Oxford, UK
  • Department of Genetics, Harvard Medical School, 02142, Cambridge, Massachusetts, USA
  • Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, CB10 1SA, Cambridge, UK
  • Center for Statistical Genetics, Biostatistics, University of Michigan, 48109, Ann Arbor, Michigan, USA
  • Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Near Saffron Walden, Essex CB10 1XL, UK.
  • McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 21205, Baltimore, Maryland, USA
  • Center for Comparative and Population Genomics, Cornell University, 14850, Ithaca, New York, USA
  • Department of Genome Sciences, University of Washington School of Medicine and Howard Hughes Medical Institute, 98195, Seattle, Washington, USA
  • European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD, Cambridge, UK
  • The Broad Institute of MIT and Harvard, 7 Cambridge Center, 02142, Cambridge, Massachusetts, USA
  • Baylor College of Medicine, Human Genome Sequencing Center, 77030, Houston, Texas, USA
  • US National Institutes of Health, National Human Genome Research Institute, 31 Center Drive, Bethesda, Maryland 20892, USA.
  • Centre of Genomics and Policy, McGill University, Montréal, H3A 1A4, Québec, Canada
  • European Molecular Biology Laboratory, Genome Biology Research Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.
  • Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
  • Dahlem Centre for Genome Research and Medical Systems Biology, D-14195, Berlin-Dahlem, Germany
  • The Genome Center, Washington University School of Medicine, 63108, St Louis, Missouri, USA
  • Department of Biology, Boston College, 02467, Chestnut Hill, Massachusetts, USA
  • Department of Genome Sciences, University of Washington School of Medicine, 98195, Seattle, Washington, USA
  • Affymetrix, Inc., Santa, 95051, Clara, California, USA
  • US National Institutes of Health, National Center for Biotechnology Information, 45 Center Drive, Bethesda, Maryland 20892, USA.
  • Department of Biology, University of Copenhagen, DK-2100, Copenhagen, Denmark
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nature11632

    DOI

    http://dx.doi.org/10.1038/nature11632

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1000661742

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/23128226


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