A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations
Studies of large sets of single nucleotide polymorphism (SNP) data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2841 SNPs in 12 sub-Saharan African populations, including a previously unsampled region of southeastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the southeastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region.
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Format: | artículo biblioteca |
Language: | English |
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Nature Publishing Group
2011
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Subjects: | Population genetics, Africa, Population history, |
Online Access: | http://hdl.handle.net/10261/43220 |
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dig-ibe-es-10261-432202021-12-28T16:50:32Z A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations Sikora, Martin Laayouni, Hafid Calafell, Francesc Comas, David Bertranpetit, Jaume Population genetics Africa Population history Studies of large sets of single nucleotide polymorphism (SNP) data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2841 SNPs in 12 sub-Saharan African populations, including a previously unsampled region of southeastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the southeastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region. Esta investigación ha sido financiada por la Dirección General de Investigación, Ministerio de Ciencia y Tecnología, España (becas SAF2007-63.171, BFU2007-63657) y la Direcció General de Recerca de la Generalitat de Catalunya (2009 SGR 1101). MS fue financiado por una beca de doctorado del Programa de becas FPU del Ministerio de Educación y Ciencia, España (AP2005-3982). Peer reviewed 2011-12-12T12:12:17Z 2011-12-12T12:12:17Z 2011 artículo http://purl.org/coar/resource_type/c_6501 European Journal of Human Genetics 19(1): 84-88 (2011) 1018-4813 http://hdl.handle.net/10261/43220 10.1038/ejhg.2010.141 1476-5438 20736976 en http://dx.doi.org/10.1038/ejhg.2010.141 Sí none Nature Publishing Group |
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Population genetics Africa Population history Population genetics Africa Population history Sikora, Martin Laayouni, Hafid Calafell, Francesc Comas, David Bertranpetit, Jaume A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations |
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Studies of large sets of single nucleotide polymorphism (SNP) data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2841 SNPs in 12 sub-Saharan African populations, including a previously unsampled region of southeastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the southeastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region. |
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artículo |
topic_facet |
Population genetics Africa Population history |
author |
Sikora, Martin Laayouni, Hafid Calafell, Francesc Comas, David Bertranpetit, Jaume |
author_facet |
Sikora, Martin Laayouni, Hafid Calafell, Francesc Comas, David Bertranpetit, Jaume |
author_sort |
Sikora, Martin |
title |
A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations |
title_short |
A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations |
title_full |
A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations |
title_fullStr |
A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations |
title_full_unstemmed |
A genomic analysis identifies a novel component in the genetic structure of sub-Saharan African populations |
title_sort |
genomic analysis identifies a novel component in the genetic structure of sub-saharan african populations |
publisher |
Nature Publishing Group |
publishDate |
2011 |
url |
http://hdl.handle.net/10261/43220 |
work_keys_str_mv |
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