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      Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula

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          Abstract

          The Iberian Peninsula is linguistically diverse and has a complex demographic history, including a centuries-long period of Muslim rule. Here, we study the fine-scale genetic structure of its population, and the genetic impacts of historical events, leveraging powerful, haplotype-based statistical methods to analyse 1413 individuals from across Spain. We detect extensive fine-scale population structure at extremely fine scales (below 10 Km) in some regions, including Galicia. We identify a major east-west axis of genetic differentiation, and evidence of historical north to south population movement. We find regionally varying fractions of north-west African ancestry (0–11%) in modern-day Iberians, related to an admixture event involving European-like and north-west African-like source populations. We date this event to 860–1120 CE, implying greater genetic impacts in the early half of Muslim rule in Iberia. Together, our results indicate clear genetic impacts of population movements associated with both the Muslim conquest and the subsequent Reconquista.

          Abstract

          The Iberian Peninsula has a complex history. Here, the authors analyse the genetic structure of the modern Iberian population at fine scale, revealing historical population movements associated with the time of Muslim rule.

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          Ancient human genomes suggest three ancestral populations for present-day Europeans

          We sequenced genomes from a $\sim$7,000 year old early farmer from Stuttgart in Germany, an $\sim$8,000 year old hunter-gatherer from Luxembourg, and seven $\sim$8,000 year old hunter-gatherers from southern Sweden. We analyzed these data together with other ancient genomes and 2,345 contemporary humans to show that the great majority of present-day Europeans derive from at least three highly differentiated populations: West European Hunter-Gatherers (WHG), who contributed ancestry to all Europeans but not to Near Easterners; Ancient North Eurasians (ANE), who were most closely related to Upper Paleolithic Siberians and contributed to both Europeans and Near Easterners; and Early European Farmers (EEF), who were mainly of Near Eastern origin but also harbored WHG-related ancestry. We model these populations' deep relationships and show that EEF had $\sim$44% ancestry from a "Basal Eurasian" lineage that split prior to the diversification of all other non-African lineages.
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            A genetic atlas of human admixture history.

            Modern genetic data combined with appropriate statistical methods have the potential to contribute substantially to our understanding of human history. We have developed an approach that exploits the genomic structure of admixed populations to date and characterize historical mixture events at fine scales. We used this to produce an atlas of worldwide human admixture history, constructed by using genetic data alone and encompassing over 100 events occurring over the past 4000 years. We identified events whose dates and participants suggest they describe genetic impacts of the Mongol empire, Arab slave trade, Bantu expansion, first millennium CE migrations in Eastern Europe, and European colonialism, as well as unrecorded events, revealing admixture to be an almost universal force shaping human populations.
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              Differential confounding of rare and common variants in spatially structured populations

              Well-powered genome-wide association studies, now possible through advances in technology and large-scale collaborative projects, promise to reveal the contribution of rare variants to complex traits and disease. However, while population structure is a known confounder of association studies, it is unknown whether methods developed to control stratification are equally effective for rare variants. Here we demonstrate that rare variants can show a systematically different and typically stronger stratification than common variants, and that this is not necessarily corrected by existing methods. We show that the same process leads to inflation for load-based tests and can obscure signals at truly associated variants. We show that populations can display spatial structure in rare variants even when FST is low, but that allele-frequency dependent metrics of allele sharing can reveal localized stratification. These results underscore the importance of collecting and integrating spatial information in the genetic analysis of complex traits.
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                Author and article information

                Contributors
                myers@stats.ox.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                1 February 2019
                1 February 2019
                2019
                : 10
                : 551
                Affiliations
                [1 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Wellcome Trust Centre for Human Genetics, , University of Oxford, ; Oxford, OX3 7BN UK
                [2 ]Fundación Pública Galega de Medicina Xenómica- CIBERER-IDIS, Santiago de Compostela, A Coruña, Spain
                [3 ]ISNI 0000000109410645, GRID grid.11794.3a, Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB2-ISCIII), , Universidade de Santiago de Compostela, ; A Coruña, Spain
                [4 ]ISNI 0000000109410645, GRID grid.11794.3a, Institute of Forensic Sciences., , University of Santiago de Compostela, ; A Coruña, Spain
                [5 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Statistics, , University of Oxford, ; Oxford, OX1 3LB UK
                Author information
                http://orcid.org/0000-0002-1139-0732
                http://orcid.org/0000-0001-9495-3408
                Article
                8272
                10.1038/s41467-018-08272-w
                6358624
                30710075
                f858868a-742f-4b29-9634-92c9156a2f8b
                © The Author(s) 2019

                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
                : 24 May 2018
                : 7 December 2018
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