Contemporary Jews comprise an aggregate of ethno-religious communities whose worldwide members identify with each other through various shared religious, historical and cultural traditions1,2. Historical evidence suggests common origins in the Middle East, followed by migrations leading to the establishment of communities of Jews in Europe, Africa and Asia, in what is termed the Jewish Diaspora3,4,5. This complex demographic history imposes special challenges in attempting to address the genetic structure of the Jewish people6. Although many genetic studies have shed light on Jewish origins and on diseases prevalent among Jewish communities, including studies focusing on uniparentally and biparentally inherited markers7,8,9,10,11,12,13,14,15,16, genome-wide patterns of variation across the vast geographic span of Jewish Diaspora communities and their respective neighbours have yet to be addressed. Here we use high-density bead arrays to genotype individuals from 14 Jewish Diaspora communities and compare these patterns of genome-wide diversity with those from 69 Old World non-Jewish populations, of which 25 have not previously been reported. These samples were carefully chosen to provide comprehensive comparisons between Jewish and non-Jewish populations in the Diaspora, as well as with non-Jewish populations from the Middle East and north Africa. Principal component and structure-like analyses identify previously unrecognized genetic substructure within the Middle East. Most Jewish samples form a remarkably tight subcluster that overlies Druze and Cypriot samples but not samples from other Levantine populations or paired Diaspora host populations. In contrast, Ethiopian Jews (Beta Israel) and Indian Jews (Bene Israel and Cochini) cluster with neighbouring autochthonous populations in Ethiopia and western India, respectively, despite a clear paternal link between the Bene Israel and the Levant. These results cast light on the variegated genetic architecture of the Middle East, and trace the origins of most Jewish Diaspora communities to the Levant.

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Primary accessions

Gene Expression Omnibus

Data deposits

The array data described in this paper are deposited in the Gene Expression Omnibus under accession number GSE21478.


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We thank the individuals who provided DNA samples for this study, including the National Laboratory for the Genetics of Israeli Populations; Mari Nelis, Georgi Hudjashov and Viljo Soo for conducting the autosomal genotyping; Lauri Anton for computational help. R.V. and D.M.B. thank the European Commission, Directorate-General for Research for FP7 Ecogene grant 205419. R.V. thanks the European Union, Regional Development Fund through a Centre of Excellence in Genomics grant and the Swedish Collegium for Advanced Studies for support during the initial stage of this study. E.M. and Si.R. thank the Estonian Science Foundation for grants 7858 and 7445, respectively. K.S. thanks the Arthur and Rosalinde Gilbert Foundation fund of the American Technion Society. Sa.R. thanks the European Union for Marie Curie International Reintegration grant CT-2007-208019, and the Israeli Science Foundation for grant 1227/09. IPATIMUP is an Associate Laboratory of the Portuguese Ministry of Science, Technology and Higher Education and is partly supported by Fundação para a Ciência ea Tecnologia, the Portuguese Foundation for Science and Technology.

Author information

Author notes

    • Doron M. Behar
    • , Bayazit Yunusbayev
    •  & Mait Metspalu

    These authors contributed equally to this work.


  1. Molecular Medicine Laboratory, Rambam Health Care Campus, Haifa 31096, Israel

    • Doron M. Behar
    • , Guennady Yudkovsky
    •  & Karl Skorecki
  2. Estonian Biocentre and Department of Evolutionary Biology, University of Tartu, Tartu 51010, Estonia

    • Doron M. Behar
    • , Bayazit Yunusbayev
    • , Mait Metspalu
    • , Ene Metspalu
    • , Jüri Parik
    • , Siiri Rootsi
    • , Gyaneshwer Chaubey
    • , Ildus Kutuev
    •  & Richard Villems
  3. Institute of Biochemistry and Genetics, Ufa Research Center, Russian Academy of Sciences, Ufa 450054, Russia

    • Bayazit Yunusbayev
    • , Ildus Kutuev
    •  & Elza K. Khusnutdinova
  4. Department of Statistics and Operations Research, School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel

    • Saharon Rosset
  5. Rappaport Faculty of Medicine and Research Institute, Technion – Israel Institute of Technology, Haifa 31096, Israel

    • Guennady Yudkovsky
    •  & Karl Skorecki
  6. Research Centre for Medical Genetics, Russian Academy of Medical Sciences, Moscow 115478, Russia

    • Oleg Balanovsky
  7. Dipartimento di Genetica e Microbiologia, Università di Pavia, Pavia 27100, Italy

    • Ornella Semino
  8. Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto 4200-465, Portugal

    • Luisa Pereira
  9. Faculdade de Medicina, Universidade do Porto, Porto 4200-319, Portugal

    • Luisa Pereira
  10. Institute of Evolutionary Biology (CSIC-UPF), CEXS-UPF-PRBB and CIBER de Epidemiología y Salud Pública, Barcelona 08003, Spain

    • David Comas
  11. Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel

    • David Gurwitz
    •  & Batsheva Bonne-Tamir
  12. Department of the Languages and Cultures of the Near and Middle East, Faculty of Languages and Cultures, School of Oriental and African Studies (SOAS), University of London, London WC1H 0XG, UK

    • Tudor Parfitt
  13. ARL Division of Biotechnology, University of Arizona, Tucson, Arizona 85721, USA

    • Michael F. Hammer


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D.M.B. and R.V. conceived and designed the study. B.B.T., D.C., D.G., D.M.B., E.K.K., G.C., I.K., L.P., M.F.H., O.B., O.S., T.P. and R.V. provided DNA samples to this study. E.M., J.P. and G.Y. screened and prepared the samples for the autosomal genotyping. D.M.B., E.M., G.C., M.F.H. and Si.R. generated and summarized the database for the uniparental analysis. B.Y., M.M. and Sa.R. designed and applied the modelling methodology and statistical analysis. T.P. provided expert input regarding the relevant historical aspects. B.Y., D.M.B., K.S., M.F.H., M.M., R.V. and Sa.R. wrote the paper. B.Y., D.M.B. and M.M. contributed equally to the paper. All authors discussed the results and commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Doron M. Behar or Karl Skorecki or Richard Villems.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Notes 1-6, References and Supplementary Tables 1-5.

  2. 2.

    Supplementary Figures

    This file contains Supplementary Figures 1 and 3-6 and legends for Supplementary Figures 1-6 (see separate file for Supplementary Figure 2)

  3. 3.

    Supplementary Figure 2

    This file shows the Principal Component Analysis of the Old World High-Density Array Data. a, Scatter plot of Old World individuals, showing the first two principal components. Here, the first PC (4.2% of variation, vertical axis) captures primarily differences between sub-Saharan Africans and the rest of the Old World. The second PC (3.4% of variation, horizontal axis) differentiates West Eurasians from South and East Asians. Axes of variation were scaled according to eigenvalues. Each letter code (Supplementary Table 1) corresponds to one individual and the colour indicates population origin. b, Scatter plot of Old World individuals, showing PC1 and PC3. c, Scatter plot of Old World individuals, showing PC1 and PC4. Note that eigenvalues for PC3 and PC4 are ~8 times smaller than for PC1 and 2.

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