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      Genetic variation and population structure of Botswana populations as identified with AmpFLSTR Identifiler short tandem repeat (STR) loci

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          Abstract

          Population structure was investigated in 990 Botswana individuals according to ethno-linguistics, Bantu and Khoisan, and geography (the nine administrative districts) using the Identifiler autosomal microsatellite markers. Genetic diversity and forensic parameters were calculated for the overall population, and according to ethno-linguistics and geography. The overall combined power of exclusion (CPE) was 0.9999965412 and the combined match probability 6,28 × 10 −19. CPE was highest for the Khoisan Tuu ethnolinguistic group and the Northeast District at 0.9999582029 and 0.9999922652 respectively. CMP ranged from 6.28 × 10 −19 (Khoisan Tuu) to 1,02 × 10 −18 (Northwest district). Using pairwise genetic distances (F ST), analysis of molecular variance (AMOVA), factorial correspondence analysis (FCA), and the unsupervised Bayesian clustering method found in STRUCTURE and TESS, ethno-linguistics were found to have a greater influence on population structure than geography. FCA showed clustering between Bantu and Khoisan, and within the Bantu. This Bantu sub-structuring was not seen with STRUCTURE and TESS, which detected clustering only between Bantu and Khoisan. The patterns of population structure revealed highlight the need for regional reference databases that include ethno-linguistic and geographic location information. These markers have important potential for bio-anthropological studies as well as for forensic applications.

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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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            Farmers and their languages: the first expansions.

            The largest movements and replacements of human populations since the end of the Ice Ages resulted from the geographically uneven rise of food production around the world. The first farming societies thereby gained great advantages over hunter-gatherer societies. But most of those resulting shifts of populations and languages are complex, controversial, or both. We discuss the main complications and specific examples involving 15 language families. Further progress will depend on interdisciplinary research that combines archaeology, crop and livestock studies, physical anthropology, genetics, and linguistics.
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              Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study

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                Author and article information

                Contributors
                medamato@uwc.ac.za
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                28 July 2017
                28 July 2017
                2017
                : 7
                : 6768
                Affiliations
                [1 ]ISNI 0000 0001 2156 8226, GRID grid.8974.2, , University of the Western Cape, Department of Biotechnology, Forensic DNA Laboratory, ; Private Bag X17, 7535 Bellville, Cape Town South Africa
                [2 ]Botswana Police Service, Forensic Science Laboratory, Private Bag 0400, Gaborone, Botswana
                [3 ]ISNI 0000 0004 0635 5486, GRID grid.7621.2, , University of Botswana, Biological Sciences Department, ; Private Bag 00704, Gaborone, Botswana
                Author information
                http://orcid.org/0000-0003-0147-1819
                Article
                6365
                10.1038/s41598-017-06365-y
                5533702
                28754995
                c38aca31-f241-4850-a759-8d4b7d6c0107
                © 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/.

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                : 11 May 2016
                : 14 June 2017
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