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      The Origins of Ashkenaz, Ashkenazic Jews, and Yiddish

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          Abstract

          Recently, the geographical origins of Ashkenazic Jews (AJs) and their native language Yiddish were investigated by applying the Geographic Population Structure (GPS) to a cohort of exclusively Yiddish-speaking and multilingual AJs. GPS localized most AJs along major ancient trade routes in northeastern Turkey adjacent to primeval villages with names that resemble the word “Ashkenaz.” These findings were compatible with the hypothesis of an Irano-Turko-Slavic origin for AJs and a Slavic origin for Yiddish and at odds with the Rhineland hypothesis advocating a Levantine origin for AJs and German origins for Yiddish. We discuss how these findings advance three ongoing debates concerning (1) the historical meaning of the term “Ashkenaz;” (2) the genetic structure of AJs and their geographical origins as inferred from multiple studies employing both modern and ancient DNA and original ancient DNA analyses; and (3) the development of Yiddish. We provide additional validation to the non-Levantine origin of AJs using ancient DNA from the Near East and the Levant. Due to the rising popularity of geo-localization tools to address questions of origin, we briefly discuss the advantages and limitations of popular tools with focus on the GPS approach. Our results reinforce the non-Levantine origins of AJs.

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          Most cited references56

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          Genomic insights into the origin of farming in the ancient Near East

          We report genome-wide ancient DNA from 44 ancient Near Easterners ranging in time between ~12,000-1,400 BCE, from Natufian hunter-gatherers to Bronze Age farmers. We show that the earliest populations of the Near East derived around half their ancestry from a ‘Basal Eurasian’ lineage that had little if any Neanderthal admixture and that separated from other non-African lineages prior to their separation from each other. The first farmers of the southern Levant (Israel and Jordan) and Zagros Mountains (Iran) were strongly genetically differentiated, and each descended from local hunter-gatherers. By the time of the Bronze Age, these two populations and Anatolian-related farmers had mixed with each other and with the hunter-gatherers of Europe to drastically reduce genetic differentiation. The impact of the Near Eastern farmers extended beyond the Near East: farmers related to those of Anatolia spread westward into Europe; farmers related to those of the Levant spread southward into East Africa; farmers related to those from Iran spread northward into the Eurasian steppe; and people related to both the early farmers of Iran and to the pastoralists of the Eurasian steppe spread eastward into South Asia.
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            Interpreting principal component analyses of spatial population genetic variation.

            Nearly 30 years ago, Cavalli-Sforza et al. pioneered the use of principal component analysis (PCA) in population genetics and used PCA to produce maps summarizing human genetic variation across continental regions. They interpreted gradient and wave patterns in these maps as signatures of specific migration events. These interpretations have been controversial, but influential, and the use of PCA has become widespread in analysis of population genetics data. However, the behavior of PCA for genetic data showing continuous spatial variation, such as might exist within human continental groups, has been less well characterized. Here, we find that gradients and waves observed in Cavalli-Sforza et al.'s maps resemble sinusoidal mathematical artifacts that arise generally when PCA is applied to spatial data, implying that the patterns do not necessarily reflect specific migration events. Our findings aid interpretation of PCA results and suggest how PCA can help correct for continuous population structure in association studies.
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              A model-based approach for analysis of spatial structure in genetic data.

              Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                21 June 2017
                2017
                : 8
                : 87
                Affiliations
                [1] 1Manipal Centre for Natural Sciences, Manipal University Manipal, India
                [2] 2Department of Linguistics, Tel Aviv University Tel-Aviv, Israel
                [3] 3Department of Psychiatry and Behavioral Sciences, Johns Hopkins University Baltimore, MD, United States
                [4] 4Department of Animal and Plant Sciences, University of Sheffield Sheffield, United Kingdom
                Author notes

                Edited by: Stéphane Joost, École Polytechnique Fédérale de Lausanne, Switzerland

                Reviewed by: Pavel Flegontov, University of Ostrava, Czechia; Lounès Chikhi, Centre National de la Recherche Scientifique (CNRS), France; Erika Hagelberg, University of Oslo, Norway

                *Correspondence: Eran Elhaik e.elhaik@ 123456sheffield.ac.uk

                This article was submitted to Evolutionary and Population Genetics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2017.00087
                5478715
                28680441
                0866698d-f716-4c8f-a9dc-761f4e490448
                Copyright © 2017 Das, Wexler, Pirooznia and Elhaik.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 October 2016
                : 07 June 2017
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 61, Pages: 8, Words: 6448
                Funding
                Funded by: Royal Society for the Prevention of Cruelty to Animals 10.13039/100009478
                Award ID: IE140020
                Funded by: Medical Research Council 10.13039/501100000265
                Award ID: MC_PC_14115
                Funded by: National Youth Science Foundation 10.13039/100007515
                Award ID: DEB-1456634
                Categories
                Genetics
                Perspective

                Genetics
                yiddish,ashkenazic jews,ashkenaz,geographic population structure (gps),archaeogenetics,rhineland hypothesis,ancient dna

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