Recombination rates in admixed individuals identified by ancestry-based inference View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-09

AUTHORS

Daniel Wegmann, Darren E Kessner, Krishna R Veeramah, Rasika A Mathias, Dan L Nicolae, Lisa R Yanek, Yan V Sun, Dara G Torgerson, Nicholas Rafaels, Thomas Mosley, Lewis C Becker, Ingo Ruczinski, Terri H Beaty, Sharon L R Kardia, Deborah A Meyers, Kathleen C Barnes, Diane M Becker, Nelson B Freimer, John Novembre

ABSTRACT

Studies of recombination and how it varies depend crucially on accurate recombination maps. We propose a new approach for constructing high-resolution maps of relative recombination rates based on the observation of ancestry switch points among admixed individuals. We show the utility of this approach using simulations and by applying it to SNP genotype data from a sample of 2,565 African Americans and 299 African Caribbeans and detecting several hundred thousand recombination events. Comparison of the inferred map with high-resolution maps from non-admixed populations provides evidence of fine-scale differentiation in recombination rates between populations. Overall, the admixed map is well predicted by the average proportion of admixture and the recombination rate estimates from the source populations. The exceptions to this are in areas surrounding known large chromosomal structural variants, specifically inversions. These results suggest that outside of structurally variable regions, admixture does not substantially disrupt the factors controlling recombination rates in humans. More... »

PAGES

847

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ng.894

    DOI

    http://dx.doi.org/10.1038/ng.894

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1017626770

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/21775992


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    436 schema:name Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.
    437 Department of Medicine, University of Chicago, Chicago, Illinois, USA.
    438 Department of Statistics, University of Chicago, Chicago, Illinois, USA.
    439 For the Chicago Asthma Genetics (CAG) and Collaborative Study on the Genetics of Asthma (CSGA) consortium.
    440 For the Severe Asthma Research Program (SARP) consortium.
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    443 schema:name Department of Epidemiology, Emory University, Atlanta, Georgia, USA.
    444 Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA.
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    448 schema:name Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, California, USA.
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    450 Interdepartmental Program in Bioinformatics, University of California, Los Angeles, California, USA.
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    453 schema:name Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
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    456 For the Genetic Research on Asthma in the African Diaspora (GRAAD) consortium.
    457 For the Genetic Study of Atherosclerosis Risk (GeneSTAR) consortium.
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    464 schema:name Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
    465 For the Severe Asthma Research Program (SARP) consortium.
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    467 https://www.grid.ac/institutes/grid.251313.7 schema:alternateName University of Mississippi
    468 schema:name Department of Medicine, University of Mississippi, Jackson, Mississippi, USA.
    469 For the Genetic Epidemiology Network of Arteriopathy (GENOA) consortium.
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