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Genome-wide patterns of population structure and admixture in West Africans and African Americans
Edited by Mary-Claire King, University of Washington, Seattle, WA and approved November 19, 2009(received for review August 25, 2009)
↵1S.A.T. and C.D.B. contributed equally to this work.

Abstract
Quantifying patterns of population structure in Africans and African Americans illuminates the history of human populations and is critical for undertaking medical genomic studies on a global scale. To obtain a fine-scale genome-wide perspective of ancestry, we analyze Affymetrix GeneChip 500K genotype data from African Americans (n = 365) and individuals with ancestry from West Africa (n = 203 from 12 populations) and Europe (n = 400 from 42 countries). We find that population structure within the West African sample reflects primarily language and secondarily geographical distance, echoing the Bantu expansion. Among African Americans, analysis of genomic admixture by a principal component-based approach indicates that the median proportion of European ancestry is 18.5% (25th–75th percentiles: 11.6–27.7%), with very large variation among individuals. In the African-American sample as a whole, few autosomal regions showed exceptionally high or low mean African ancestry, but the X chromosome showed elevated levels of African ancestry, consistent with a sex-biased pattern of gene flow with an excess of European male and African female ancestry. We also find that genomic profiles of individual African Americans afford personalized ancestry reconstructions differentiating ancient vs. recent European and African ancestry. Finally, patterns of genetic similarity among inferred African segments of African-American genomes and genomes of contemporary African populations included in this study suggest African ancestry is most similar to non-Bantu Niger-Kordofanian-speaking populations, consistent with historical documents of the African Diaspora and trans-Atlantic slave trade.
Footnotes
- 2To whom correspondence may be addressed at: Departments of Biology and Genetics, 428 Clinical Research Building, 415 Curie Boulevard, University of Pennsylvania, Philadelphia, PA 19104–6145. E-mail: tishkoff{at}mail.med.upenn.edu.
- 3To whom correspondence may be addressed at: Department of Biological Statistics, Computational Biology, 102J Weill Hall, Cornell University, Ithaca, NY 14853. E-mail: cdb28{at}cornell.edu.
Author contributions: K.B., S.A.T., and C.D.B. designed research; K.B., A.A., S.A.T., and C.D.B. performed research; K.B., M.R.N., J.R.O., S.L.H., S.W., A.F., J.-M.B., C.W., S.A.T., and C.D.B. contributed new reagents/analytic tools; K.B., A.A., M.R.N., S.A.T., and C.D.B. analyzed data; K.B., A.A., S.A.T., and C.D.B. wrote the paper; and S.A.T. and C.D.B. co-supervised the project.
Conflict of interest statement: The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0909559107/DCSupplemental.
Freely available online through the PNAS open access option.
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