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Nature
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The genome-wide structure of the Jewish people

Naturevolume 466pages238–242 (2010)Cite this article

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Abstract

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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Figure 1:PCA of high-density array data.
Figure 2:PCA of west Eurasian high-density array data.
Figure 3:Population structure inferred by ADMIXTURE analysis.

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Accession codes

Primary accessions

Gene Expression Omnibus

Data deposits

The array data described in this paper are deposited in the Gene Expression Omnibus under accession numberGSE21478.

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Acknowledgements

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
  1. Doron M. Behar, Bayazit Yunusbayev and Mait Metspalu: These authors contributed equally to this work.

Authors and Affiliations

  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

Authors
  1. Doron M. Behar
  2. Bayazit Yunusbayev
  3. Mait Metspalu
  4. Ene Metspalu
  5. Saharon Rosset
  6. Jüri Parik
  7. Siiri Rootsi
  8. Gyaneshwer Chaubey
  9. Ildus Kutuev
  10. Guennady Yudkovsky
  11. Elza K. Khusnutdinova
  12. Oleg Balanovsky
  13. Ornella Semino
  14. Luisa Pereira
  15. David Comas
  16. David Gurwitz
  17. Batsheva Bonne-Tamir
  18. Tudor Parfitt
  19. Michael F. Hammer
  20. Karl Skorecki
  21. Richard Villems

Contributions

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.

Corresponding authors

Correspondence toDoron M. Behar,Karl Skorecki orRichard Villems.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Notes 1-6, References and Supplementary Tables 1-5. (PDF 1143 kb)

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) (PDF 6701 kb)

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. (PDF 1892 kb)

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Behar, D., Yunusbayev, B., Metspalu, M.et al. The genome-wide structure of the Jewish people.Nature466, 238–242 (2010). https://doi.org/10.1038/nature09103

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Comments

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  1. Jihad Orabi

    Jews Yemenite samples are located closer to Saudi and Bedouins populations i.e. same geographical area. Similarly, Ashkenazi and Georgian Jew cluster closer to the Georgian and Armenian population, i. e. same geographical area. Even the Moroccan Jews cluster outside of the Levant populations. From PCA it is clear that Jews outside Levant cluster closer to their native population rather than to the Jews or non Jews from Levant.

  2. Otero Hector Horacio

    In my hypothesis, the "L2" mtDNA marker is present in the two populations also the derived and sibling mtDNA Hg "M" and "N", as well as the Y markers Hg E3b and 4s too, all of this from East Africa and so. They belong respectively at one of the three nucleous or center jewish ancient populations, that evolving the called "Syrian-European nucleous"(helenistic and Roman times).
    The oldest center <del>Ethiopians belong these</del> were that developed in Napata and Elephantine (Kush) and whose nucleous or center was after Alexandria, and I called "Coptic Nucleous" derived in two bias, and split forwards the North via Europe <del>intermixed with the Syrian Europe nucleous</del> or the South, via Nile and the Horn Of Africa.
    The "Babilonian and Persian nucleous" is other of the above three mentioned centers and included Bukara, Iranian and Iraki mainly.
    All of this Nucleous take Judaea and Israel like a axis and pendulo.
    Another fourth Nucleous or center I call "East Europe" <del>not mainly conected with ME</del>, is not ancient like the three others and was the Jewish Khazar Empire stiring into Askenazy current population and others. All of this events were naturaly intrajewish asimilations in all jews current populations.
    The Ashkenazim hyperhaploydia is explained by the superposition and overlay of diverse fount or source population , that are all of this of Jewish origin (that consider converted into intraJewish assimilations) , one coming from the ?Syrian European nucleous? ? that Sephardic as well as preAshenazim bring inside -. The other convergence were the ?Coptic Jewish nucleous?, coming from Alexandria, the main and largest Judaic center in ancient times ? the buried and graves in Jewish graveyards and catacombs of Tuscan, and Alsace as too Rhineland cities take a lot of Egyptian ornaments and display figures from these, as well as Y and mtDNA markers - . The great Jews migration from Egypt beginning after the Muslim invaders from Arabia in the VII AE century. The ?Babylonian and Persian nucleous? take place and contacts newly with and when the ?preAshenazim second fase? were migrating to the East Europe. A remarkable contact was with the fourth ?East Europe Jews nucleous?<del>not related or little related with ME</del>, with the descendant of the Jews Khazarians ones, spreading every where and carrying a lot of East Europe and Eurasian markers. That happen between the XI and XII century AE.
    The Tuscan host populations come from Anatolia like infers mtDNA markers, and others, yet present today ? a thread Etruscan link &#8211 and are so common in South East Basin like Albanian, Grecian, Tunisian and Anatolian , as well as the entirely Italy and some South France spots, practical absent in central or North Europa or East Asia. If we compare Ashkenazy jews with this South European Tuscan population will see a more European genes pool coming from Europe than if we compare with Central and North European population.

    Dr Hector H. Otero C.
    Argentina.

    See too:
    http://www.nature.com/news/...
    See, my comment 11149 and 12952 in the above Html, with table 1 <del>partial</del>, remember that the sibling Hg "M" and "N" <del>from "L3"</del> too correspond to East African origin, and are not included at all-see complete table 1, in reference-.

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Editorial Summary

The Jewish line

A comparison of genomic data from 14 Jewish communities across the world with data from 69 non-Jewish populations reveals a close relationship between most of today's Jews and non-Jewish populations from the Levant. This fits in with the idea that most contemporary Jews are descended from ancient Hebrew and Israelite residents of the Levant. By contrast, the Ethiopian and Indian Jewish communities cluster with neighbouring non-Jewish populations in Ethiopia and western India, respectively. This may be partly because a greater degree of genetic, religious and cultural crossover took place when the Jewish communities in these areas became established.

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