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      Migration and Interaction in a Contact Zone: mtDNA Variation among Bantu-Speakers in Southern Africa

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          Abstract

          Bantu speech communities expanded over large parts of sub-Saharan Africa within the last 4000–5000 years, reaching different parts of southern Africa 1200–2000 years ago. The Bantu languages subdivide in several major branches, with languages belonging to the Eastern and Western Bantu branches spreading over large parts of Central, Eastern, and Southern Africa. There is still debate whether this linguistic divide is correlated with a genetic distinction between Eastern and Western Bantu speakers. During their expansion, Bantu speakers would have come into contact with diverse local populations, such as the Khoisan hunter-gatherers and pastoralists of southern Africa, with whom they may have intermarried. In this study, we analyze complete mtDNA genome sequences from over 900 Bantu-speaking individuals from Angola, Zambia, Namibia, and Botswana to investigate the demographic processes at play during the last stages of the Bantu expansion. Our results show that most of these Bantu-speaking populations are genetically very homogenous, with no genetic division between speakers of Eastern and Western Bantu languages. Most of the mtDNA diversity in our dataset is due to different degrees of admixture with autochthonous populations. Only the pastoralist Himba and Herero stand out due to high frequencies of particular L3f and L3d lineages; the latter are also found in the neighboring Damara, who speak a Khoisan language and were foragers and small-stock herders. In contrast, the close cultural and linguistic relatives of the Herero and Himba, the Kuvale, are genetically similar to other Bantu-speakers. Nevertheless, as demonstrated by resampling tests, the genetic divergence of Herero, Himba, and Kuvale is compatible with a common shared ancestry with high levels of drift, while the similarity of the Herero, Himba, and Damara probably reflects admixture, as also suggested by linguistic analyses.

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          New approaches for unravelling reassortment pathways

          Background Every year the human population encounters epidemic outbreaks of influenza, and history reveals recurring pandemics that have had devastating consequences. The current work focuses on the development of a robust algorithm for detecting influenza strains that have a composite genomic architecture. These influenza subtypes can be generated through a reassortment process, whereby a virus can inherit gene segments from two different types of influenza particles during replication. Reassortant strains are often not immediately recognised by the adaptive immune system of the hosts and hence may be the source of pandemic outbreaks. Owing to their importance in public health and their infectious ability, it is essential to identify reassortant influenza strains in order to understand the evolution of this virus and describe reassortment pathways that may be biased towards particular viral segments. Phylogenetic methods have been used traditionally to identify reassortant viruses. In many studies up to now, the assumption has been that if two phylogenetic trees differ, it is because reassortment has caused them to be different. While phylogenetic incongruence may be caused by real differences in evolutionary history, it can also be the result of phylogenetic error. Therefore, we wish to develop a method for distinguishing between topological inconsistency that is due to confounding effects and topological inconsistency that is due to reassortment. Results The current work describes the implementation of two approaches for robustly identifying reassortment events. The algorithms rest on the idea of significance of difference between phylogenetic trees or phylogenetic tree sets, and subtree pruning and regrafting operations, which mimic the effect of reassortment on tree topologies. The first method is based on a maximum likelihood (ML) framework (MLreassort) and the second implements a Bayesian approach (Breassort) for reassortment detection. We focus on reassortment events that are found by both methods. We test both methods on a simulated dataset and on a small collection of real viral data isolated in Hong Kong in 1999. Conclusions The nature of segmented viral genomes present many challenges with respect to disease. The algorithms developed here can effectively identify reassortment events in small viral datasets and can be applied not only to influenza but also to other segmented viruses. Owing to computational demands of comparing tree topologies, further development in this area is necessary to allow their application to larger datasets.
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            Origin and evolution of Native American mtDNA variation: a reappraisal.

            The timing and number of prehistoric migrations involved in the settlement of the American continent is subject to intense debate. Here, we reanalyze Native American control region mtDNA data and demonstrate that only an appropriate phylogenetic analysis accompanied by an appreciation of demographic factors allows us to discern different migrations and to estimate their ages. Reappraising 574 mtDNA control region sequences from aboriginal Siberians and Native Americans, we confirm in agreement with linguistic, archaeological and climatic evidence that (i) the major wave of migration brought one population, ancestral to the Amerinds, from northeastern Siberia to America 20,000-25,000 years ago and (ii) a rapid expansion of a Beringian source population took place at the end of the Younger Dryas glacial phase approximately 11,300 years ago, ancestral to present Eskimo and Na-Dene populations.
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              Harvesting the fruit of the human mtDNA tree.

              Human mitochondrial DNA (mtDNA) studies have entered a new phase since the blossoming of complete genome analyses. Sequencing complete mtDNAs is more expensive and more labour intensive than restriction analysis or simply sequencing the control region of the molecule. But the efforts are paying off, as the phylogenetic resolution of the mtDNA tree has been greatly improved, and, in turn, phylogeographic interpretations can be given correspondingly greater precision in terms of the timing and direction of human dispersals. Therefore, despite mtDNA being only a fraction of our total genome, the deciphering of its evolution is profoundly changing our perception about how modern humans spread across our planet. Here we illustrate the phylogeographic approach with two case studies: the initial dispersal out of Africa, and the colonization of Europe.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                5 June 2014
                : 9
                : 6
                : e99117
                Affiliations
                [1 ]Department of Evolutionary Genetics, MPI for Evolutionary Anthropology, Leipzig, Germany
                [2 ]Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology, University of Bologna, Bologna, Italy
                [3 ]CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto, Vairão, Portugal
                [4 ]STAB VIDA, Investigação e Serviços em Ciências Biológicas, Lda, Oeiras, Portugal
                [5 ]Departamento de Biologia, Faculdade de Ciências da Universidade do Porto, Porto, Portugal
                [6 ]Department of African Languages and Cultures, Ghent University, KongoKing Research Group, Ghent, Belgium
                [7 ]Université libre de Bruxelles, Faculté de Philosophie et Lettres, Brussels, Belgium
                [8 ]Laboratoire Dynamique du Langage, UMR5596, CNRS and Université Lyon Lumière 2, Lyon, France
                University of Perugia, Italy
                Author notes

                Competing Interests: MV was supported by STAB VIDA, Investigação e Serviços em Ciências Biológicas, Lda. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: CB JR MS BP. Performed the experiments: MV. Analyzed the data: CB MV SO. Contributed reagents/materials/analysis tools: JR MS BP. Wrote the paper: CB KB JR MS BP. Provided input on writing the manuscript: MV SO.

                [¤]

                Current address: Division of Biological Anthropology, University of Cambridge, Cambridge, United Kingdom

                Article
                PONE-D-14-06940
                10.1371/journal.pone.0099117
                4047067
                24901532
                0b53c88a-d18b-47ef-9494-6e6d38f65993
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 March 2014
                : 11 May 2014
                Page count
                Pages: 14
                Funding
                This work was funded by the Max Planck Society, by FCT Project Grant PTDC/BIA-EVF/2907/2012, by the EU FP7 REGPOT grant CIBIO-New-Gen-28643, and by the “Genomics and Evolutionary Biology” project co-financed by the North Portugal Regional Operational Programme 2007/2013 (ON.2– O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF); CB was supported by the European Research Council ERC-2011-AdG 295733 grant (Langelin); MV was supported by STAB VIDA, Investigação e Serviços em Ciências Biológicas, Lda; MV and SO were supported by the Portuguese Ministry for Science, Technology and Higher Education through PhD grants SFRH/BDE/51828/2012 and SFRH/BD/85776/2012, respectively. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Evolutionary Ecology
                Evolutionary Biology
                Population Genetics
                Gene Flow
                Haplotypes
                Evolutionary Genetics
                Genetics
                People and Places
                Population Groupings
                Ethnicities
                Social Sciences
                Anthropology
                Cultural Anthropology
                Linguistic Anthropology

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