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      Whole-genome sequencing for an enhanced understanding of genetic variation among South Africans

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          Abstract

          The Southern African Human Genome Programme is a national initiative that aspires to unlock the unique genetic character of southern African populations for a better understanding of human genetic diversity. In this pilot study the Southern African Human Genome Programme characterizes the genomes of 24 individuals (8 Coloured and 16 black southeastern Bantu-speakers) using deep whole-genome sequencing. A total of ~16 million unique variants are identified. Despite the shallow time depth since divergence between the two main southeastern Bantu-speaking groups (Nguni and Sotho-Tswana), principal component analysis and structure analysis reveal significant ( p < 10 −6) differentiation, and F ST analysis identifies regions with high divergence. The Coloured individuals show evidence of varying proportions of admixture with Khoesan, Bantu-speakers, Europeans, and populations from the Indian sub-continent. Whole-genome sequencing data reveal extensive genomic diversity, increasing our understanding of the complex and region-specific history of African populations and highlighting its potential impact on biomedical research and genetic susceptibility to disease.

          Abstract

          African populations show a high level of genetic diversity and extensive regional admixture. Here, the authors sequence the whole genomes of 24 South African individuals of different ethnolinguistic origin and find substantive genomic divergence between two southeastern Bantu-speaking groups.

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          The genetic structure and history of Africans and African Americans.

          Africa is the source of all modern humans, but characterization of genetic variation and of relationships among populations across the continent has been enigmatic. We studied 121 African populations, four African American populations, and 60 non-African populations for patterns of variation at 1327 nuclear microsatellite and insertion/deletion markers. We identified 14 ancestral population clusters in Africa that correlate with self-described ethnicity and shared cultural and/or linguistic properties. We observed high levels of mixed ancestry in most populations, reflecting historical migration events across the continent. Our data also provide evidence for shared ancestry among geographically diverse hunter-gatherer populations (Khoesan speakers and Pygmies). The ancestry of African Americans is predominantly from Niger-Kordofanian (approximately 71%), European (approximately 13%), and other African (approximately 8%) populations, although admixture levels varied considerably among individuals. This study helps tease apart the complex evolutionary history of Africans and African Americans, aiding both anthropological and genetic epidemiologic studies.
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            Genomics for the world.

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              Genomic patterns of homozygosity in worldwide human populations.

              Genome-wide patterns of homozygosity runs and their variation across individuals provide a valuable and often untapped resource for studying human genetic diversity and evolutionary history. Using genotype data at 577,489 autosomal SNPs, we employed a likelihood-based approach to identify runs of homozygosity (ROH) in 1,839 individuals representing 64 worldwide populations, classifying them by length into three classes-short, intermediate, and long-with a model-based clustering algorithm. For each class, the number and total length of ROH per individual show considerable variation across individuals and populations. The total lengths of short and intermediate ROH per individual increase with the distance of a population from East Africa, in agreement with similar patterns previously observed for locus-wise homozygosity and linkage disequilibrium. By contrast, total lengths of long ROH show large interindividual variations that probably reflect recent inbreeding patterns, with higher values occurring more often in populations with known high frequencies of consanguineous unions. Across the genome, distributions of ROH are not uniform, and they have distinctive continental patterns. ROH frequencies across the genome are correlated with local genomic variables such as recombination rate, as well as with signals of recent positive selection. In addition, long ROH are more frequent in genomic regions harboring genes associated with autosomal-dominant diseases than in regions not implicated in Mendelian diseases. These results provide insight into the way in which homozygosity patterns are produced, and they generate baseline homozygosity patterns that can be used to aid homozygosity mapping of genes associated with recessive diseases. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Michele.ramsay@wits.ac.za
                michael.pepper@up.ac.za
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                12 December 2017
                12 December 2017
                2017
                : 8
                : 2062
                Affiliations
                [1 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, , University of the Witwatersrand, ; Johannesburg, 2193 South Africa
                [2 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, Division of Human Genetics, School of Pathology, Faculty of Health Sciences, , University of the Witwatersrand, ; Johannesburg, 2000 South Africa
                [3 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, School of Electrical and Information Engineering, , University of the Witwatersrand, ; Johannesburg, 2050 South Africa
                [4 ]ISNI 0000 0001 2214 904X, GRID grid.11956.3a, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, , Stellenbosch University, ; Tygerberg, 7505 South Africa
                [5 ]ISNI 0000 0004 1937 1151, GRID grid.7836.a, Computational Biology Division, Department of Integrative Biomedical Sciences, IDM, , University of Cape Town, ; Cape Town, 7925 South Africa
                [6 ]ISNI 0000 0004 1937 1151, GRID grid.7836.a, Division of Human Genetics, Department of Pathology, IDM, Faculty of Health Sciences, , University of Cape Town, ; Cape Town, 7925 South Africa
                [7 ]ISNI 0000 0001 2156 8226, GRID grid.8974.2, South African MRC Bioinformatics Unit, South African National Bioinformatics Institute, , University of the Western Cape, ; Bellville, 7925 South Africa
                [8 ]ISNI 0000 0001 2107 2298, GRID grid.49697.35, Department of Biochemistry and Genomics Research Institute, Centre for Bioinformatics and Computational Biology, , University of Pretoria, ; Pretoria, 0083 South Africa
                [9 ]ISNI 0000 0001 2173 1003, GRID grid.428711.9, Agricultural Research Council, ; Pretoria, 0184 South Africa
                [10 ]ISNI 0000 0001 2105 2799, GRID grid.411732.2, Department of Preclinical Sciences, School of Health Care Sciences, Faculty of Health Sciences, , University of Limpopo, ; Mankweng, 0727 South Africa
                [11 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, , University of the Witwatersrand, ; Johannesburg, 2000 South Africa
                [12 ]ISNI 0000 0001 2105 2799, GRID grid.411732.2, Department of Medical Sciences, School of Health Sciences, Faculty of Health Sciences, , University of Limpopo, ; Mankweng, 0727 South Africa
                [13 ]ISNI 0000 0001 2214 904X, GRID grid.11956.3a, Department of Genetics, , Stellenbosch University, ; Stellenbosch, 7600 South Africa
                [14 ]ISNI 0000 0001 2107 2298, GRID grid.49697.35, Institute for Cellular and Molecular Medicine, Department of Immunology, Faculty of Health Sciences, , University of Pretoria, ; Pretoria, 0084 South Africa
                Author information
                http://orcid.org/0000-0001-7614-1887
                Article
                663
                10.1038/s41467-017-00663-9
                5727231
                29233967
                169ca23c-89a1-404a-9baa-f3b4dcf1e0d9
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 September 2016
                : 17 July 2017
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