137 ancient human genomes from across the Eurasian steppes (original) (raw)

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• 30 August 2018

with In this Article, Angela M. Taravella and Melissa A. Wilson Sayres have been added to the author list (associated with: School of Life Sciences, Center for Evolution and Medicine, The Biodesign Institute, Arizona State University, Tempe, AZ, USA). The author list and Author Information section have been corrected online.

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Acknowledgements

We thank K. Magnussen, L. Petersen, C. Mortensen and A. Seguin-Orlando at the Danish National Sequencing Centre for producing the analysed sequences; P. Reimer and S. Hoper at the 14Chrono Center Belfast for providing accelerator mass spectrometry dating; S. Hackenbeck for discussing palaeodietary reconstructions; D. Christiansen Appelt, B. Heyerdahl, the Explico Foundation team, J. Isakova, B. Daulet, A. Tairov, N. Abduov, B. Tudiyarov, V. Volkov, M. Akchurin, I. Baimukhan, N. Namdakov, Y. Yusupov, E. Ramankulov, A. Nurgaziyev and A. Kusaev for important assistance in fieldwork; J. Stenderup, P. V. Olsen and T. Brand for technical assistance in the laboratory; all involved archaeologists, historians and geographers from Kazakhstan: A. Suslov, I. Erofeeva, E. Nurmaganbetov, B. Kozhakhmetov, N. Loman, Y. Parshin, S. Ladunskiy, M. Bedelbaeva, A. Marcsik, O. Gábor, M. Půlpán, Y. Kubeev, R. Zhumashev, K. Omarov, S. Kasymov and U. Akimbayeva; P. Rodzianko for creating the initial contact between P.d.B.D., S.E. and E.U.; and S. Jacobsen and J. O’Brien for translating and proofreading Russian contributions. E.W. thanks St. John’s College, Cambridge for support and for providing an environment facilitating scientific discussions. B.Boldg. thanks the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology. The project was funded by the Danish National Research Foundation (E.W.), the Lundbeck Foundation (E.W.) and KU2016 (E.W.).

Reviewer information

Nature thanks T. Higham, D. Anthony, B. Shapiro, R. Dennell and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

1. Kasper Nielsen
   Present address: Carlsberg Research Laboratory, Copenhagen, Denmark

Authors and Affiliations

1. Center for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
   Peter de Barros Damgaard, Gabriel Renaud, Thorfinn Korneliussen, J. Víctor Moreno-Mayar, Ashot Margaryan, Morten E. Allentoft, Ludovic Orlando, Rasmus Nielsen, Martin Sikora & Eske Willerslev
2. Eco-anthropologie et Ethnobiologie, Muséum national d’Histoire naturelle, CNRS, Université Paris Diderot, Paris, France
   Nina Marchi & Evelyne Heyer
3. Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark
   Simon Rasmussen, Anders Gorm Pedersen & Kasper Nielsen
4. Leiden University Centre for Linguistics, Leiden University, Leiden, The Netherlands
   Michaël Peyrot
5. Department of Zoology, University of Cambridge, Cambridge, UK
   Thorfinn Korneliussen, Mikkel Winther Pedersen & Eske Willerslev
6. Department of Biology, Stanford University, Stanford, CA, USA
   Amy Goldberg
7. Buketov Karaganda State University, Saryarka Archaeological Institute, Karaganda, Kazakhstan
   Emma Usmanova, Valeriy Loman, Evgeniy Dmitriev, Valeriy Evdokimov, Alexey Kukushkin, Igor Kukushkin & Victor Varfolomeev
8. Shejire DNA, Almaty, Kazakhstan
   Nurbol Baimukhanov & Gabit Baimbetov
9. Department of Archaeology, Conservation and History, University of Oslo, Oslo, Norway
   Lotte Hedeager
10. Department of Theory and Methods, Institute of Archaeology Russian Academy of Sciences, Moscow, Russia
    Gennady Afanasiev
11. Department of History, Kyrgyzstan-Turkey Manas University, Bishkek, Kyrgyzstan
    Kunbolot Akmatov, Ashyk Alpaslan & Tabaldiev Kubatbek
12. National Academy of Sciences of Kyrgyzstan, Bishkek, Kyrgyzstan
    Almaz Aldashev
13. Department of History, Irkutsk State University, Irkutsk, Russia
    Vladimir I. Bazaliiskii
14. A. Kh. Margulan Institute of Archaeology, Almaty, Kazakhstan
    Arman Beisenov & Egor Kitov
15. Laboratory of Virology, Institute of Veterinary Medicine, Mongolian University of Life Sciences, Ulaanbaatar, Mongolia
    Bazartseren Boldbaatar
16. Department of Biology, School of Arts and Sciences, National University of Mongolia, Ulaanbaatar, Mongolia
    Bazartseren Boldgiv & Sainbileg Undrakhbold
17. Departament of Biology and Ecology, Tuvan State University, Kyzyl, Russia
    Choduraa Dorzhu
18. The Explico Foundation, Floro, Norway
    Sturla Ellingvag
19. Department of Archaeology, Ulaanbaatar State University, Ulaanbaatar, Mongolia
    Diimaajav Erdenebaatar & Enkhbayar Mijiddorj
20. Department of Biology and Biotechnology, Hashemite University, Zarqa, Jordan
    Rana Dajani
21. Radcliffe Institute for Advanced Study, Harvard University, Cambridge, MA, USA
    Rana Dajani
22. Unit for Environmental Archaeology and Materials Science, National Museum of Denmark, Copenhagen, Denmark
    Karin M. Frei
23. Peter the Great Museum of Anthropology and Ethnography (Kunstkamera) RAS, St. Petersburg, Russia
    Andrey Gromov & Vyacheslav Moiyesev
24. Archaeological Expertise LLC, Almaty, Kazakhstan
    Alexander Goryachev & Dmitriy Voyakin
25. Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
    Hakon Hakonarson
26. Republican Scientific Center of Immunology, Ministry of Public Health, Tashkent, Uzbekistan
    Tatyana Hegay
27. Department of Bioengineering, Bioinformatics and Molecular Biology, Russian-Armenian University, Yerevan, Armenia
    Zaruhi Khachatryan & Levon Yepiskoposyan
28. Complex Research Institute of the Russian Academy of Sciences, Grozny, Russia
    Ruslan Khaskhanov
29. Institute of Ethnology and Anthropology, Russian Academy of Science, Moscow, Russia
    Egor Kitov
30. Kostanay Regional Local History Museum, Kostanay, Kazakhstan
    Alina Kolbina
31. Centre for Baltic and Scandinavian Archaeology, Schleswig, Germany
    Nina Lau
32. Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan, Armenia
    Ashot Margaryan
33. Saxo-Institute, University of Copenhagen, Copenhagen, Denmark
    Inga Merkyte
34. Center for Archaeological Research, S. Toraighyrov Pavlodar State University, Pavlodar, Kazakhstan
    Ilya V. Mertz & Viktor K. Mertz
35. The State Historical and Cultural Reserve-Museum (ISSYK), Almaty, Kazakhstan
    Gulmira Mukhtarova, Bekmukhanbet Nurmukhanbetov & Turaly Tulegenov
36. Institute of Archeology and Ethnography of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
    Z. Orozbekova
37. University of Arizona, Laboratory of Tree-Ring Research, Tucson, AZ, USA
    Irina Panyushkina
38. Institute of Archaeology of the Slovak Academy of Sciences, Nitra, Slovakia
    Karol Pieta & Tereza Štolcová
39. Institute for History of Medicine and Foreign Languages, First Faculty of Medicine, Charles University, Prague, Czech Republic
    Václav Smrčka
40. Archaeological Laboratory, Kostanay State University, Kostanay, Kazakhstan
    Irina Shevnina & Andrey Logvin
41. Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
    Karl-Göran Sjögren & Kristian Kristiansen
42. Institute of History and Cultural Heritage of National Academy of Sciences, Bishkek, Kyrgyzstan
    Kadicha Tashbaeva
43. Institute of Problems Development of the North Siberian Branch of the Russian Academy of Sciences, Tyumen, Russia
    Alexander Tkachev
44. Department of Anthropology, University of Alberta, Edmonton, Alberta, Canada
    Andrzej Weber
45. Institute of History, Archaeology and Ethnology, Far-Eastern Branch of the Russian Academy of Sciences, Ulan-Ude, Russia
    Nikolay Kradin
46. Institute of Mongolian, Buddhist, and Tibetan Studies, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude, Russia
    Nikolay Kradin
47. Laboratoire d’Anthropobiologie Moléculaire et d’Imagerie de Synthèse, Université de Toulouse, Université Paul Sabatier, Toulouse, France
    Ludovic Orlando
48. Departments of Integrative Biology and Statistics, University of Berkeley, Berkeley, CA, USA
    Rasmus Nielsen
49. Wellcome Trust Sanger Institute, Hinxton, UK
    Eske Willerslev
50. School of Life Sciences, Center for Evolution and Medicine, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
    Angela M. Taravella & Melissa A. Wilson Sayres

Authors

1. Peter de Barros Damgaard
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2. Nina Marchi
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3. Simon Rasmussen
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4. Michaël Peyrot
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5. Gabriel Renaud
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6. Thorfinn Korneliussen
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7. J. Víctor Moreno-Mayar
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8. Mikkel Winther Pedersen
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9. Amy Goldberg
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10. Emma Usmanova
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11. Nurbol Baimukhanov
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12. Valeriy Loman
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13. Lotte Hedeager
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14. Anders Gorm Pedersen
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15. Kasper Nielsen
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16. Gennady Afanasiev
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17. Kunbolot Akmatov
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18. Almaz Aldashev
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19. Ashyk Alpaslan
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20. Gabit Baimbetov
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21. Vladimir I. Bazaliiskii
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22. Arman Beisenov
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23. Bazartseren Boldbaatar
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24. Bazartseren Boldgiv
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25. Choduraa Dorzhu
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26. Sturla Ellingvag
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27. Diimaajav Erdenebaatar
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28. Rana Dajani
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29. Evgeniy Dmitriev
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30. Valeriy Evdokimov
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31. Karin M. Frei
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32. Andrey Gromov
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33. Alexander Goryachev
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34. Hakon Hakonarson
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35. Tatyana Hegay
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36. Zaruhi Khachatryan
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37. Ruslan Khaskhanov
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38. Egor Kitov
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39. Alina Kolbina
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40. Tabaldiev Kubatbek
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41. Alexey Kukushkin
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42. Igor Kukushkin
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43. Nina Lau
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44. Ashot Margaryan
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46. Ilya V. Mertz
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48. Enkhbayar Mijiddorj
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49. Vyacheslav Moiyesev
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50. Gulmira Mukhtarova
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51. Bekmukhanbet Nurmukhanbetov
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52. Z. Orozbekova
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53. Irina Panyushkina
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54. Karol Pieta
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55. Václav Smrčka
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56. Irina Shevnina
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57. Andrey Logvin
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58. Karl-Göran Sjögren
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59. Tereza Štolcová
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60. Angela M. Taravella
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61. Kadicha Tashbaeva
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62. Alexander Tkachev
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63. Turaly Tulegenov
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64. Dmitriy Voyakin
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65. Levon Yepiskoposyan
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66. Sainbileg Undrakhbold
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67. Victor Varfolomeev
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68. Andrzej Weber
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69. Melissa A. Wilson Sayres
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70. Nikolay Kradin
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71. Morten E. Allentoft
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76. Kristian Kristiansen
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77. Eske Willerslev
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Contributions

E.W. initiated and led the study. P.d.B.D., E.W., E.U. and E.H. designed the study. P.d.B.D. and N.M. produced the data. P.d.B.D., N.M., S.R., M.S., G.R., T.Ko., A.Gol., M.W.P., A.G.P. and K.N. analysed or assisted in analysis of data. A.M.T. and M.A.W.S. provided an overview of major Y-chromosomal haplogroups in Supplementary Information Section 8. P.d.B.D., E.W. and K.K. interpreted results with considerable input from M.S., R.N., M.P., N.K., S.R., L.O., M.E.A. and J.V.M.-M. P.d.B.D., E.W., K.K., M.P. and S.R. wrote the manuscript with considerable input from N.K., L.H., M.S., R.N., M.E.A., L.O. and J.V.M.-M., with contributions from all authors. P.d.B.D., M.E.A., L.O., E.U., N.B., V.L., G.A., K.A., A.Ald., A.Alp., G.B., V.I.B., A.B., B.Boldb., B.Boldg., C.D., S.E., D.E., R.D., E.D., V.E., K.M.F., A.Gor., A.Gr., H.H., T.H., Z.K., R.K., E.K., A.Ko., T.Ku., A.Ku., I.K., N.L., A.M., V.K.M., I.V.M., I.M., E.M., V.M., G.M., B.N., Z.O., I.P., K.P., V.S., I.S., A.L., K.-G.S., T.S., K.T., A.T., T.T., D.V., L.Y., S.U., V.V., A.W. and E.H. excavated, curated, sampled and/or described analysed skeletons; all authors contributed to final interpretation of data.

Corresponding author

Correspondence toEske Willerslev.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Analyses of Iron Age clusters.

a, PCA of Iron Age nomads and ancestral sources, explaining the diversity between them using 74 individuals at 242,406 autosomal single nucleotide polymorphism (SNP) positions. b, PCA of Iron Age nomads alone using 29 individuals at 242,406 autosomal SNP positions. c, PCA of Xiongnu, ‘Western’ Xiongnu, Tian Shan Huns, Nomads Hun Period, and Tian Shan Sakas, using 39 individuals at 242,406 autosomal SNP positions. d, Model-based clustering at K = 7 illustrating differences in ancestral proportions. Labelled individuals: A, Andronovo; B, Neolithic European (Europe_EN, in a); C, Baikal hunter-gatherers; D, Neolithic Iranian (Iran_N, in a). Here we illustrate the admixture analyses with K = 7 as it approximately identifies the major component of relevance (Anatolian/European farmer component, Caucasian ancestry, EHG-related ancestry and East Asian ancestry). The asterisk indicates an individual flagged as a genetic outlier. d, e, Results for model-based clustering analysis at K = 7. Here we illustrate the admixture analyses with K = 7 as it approximately identifies the major component of relevance (Anatolian/European farmer component, Caucasian ancestry, EHG-related ancestry and East Asian ancestry). Panel d is focused on the Iron Age, while e is focused on the transition to the Hun period.

Extended Data Fig. 2 Illustration of shared ancestry between Neolithic farmers and Iron Age nomads.

Results for model-based clustering analysis at K = 7, plotting only one individual from relevant groups, to illustrate shared ancestry between Neolithic farmers from Europe, Late Bronze Age nomads and Iron Age nomads, not shared with Early Bronze Age nomads. MBLA, Middle-to-Late Bronze Age; Neo, Neolithic.

Extended Data Fig. 3 Illustration of gene flow into Hungarian Scythians.

We represent all D(Test, Mbuti; Andronovo, Hungarian Scythians) that deviate significantly from 0 (that is, higher than 3× the standard errors). The reported numbers are the _D_-statistics and the 3 standard errors were plotted as error bars. The number of individuals per population can be found in Supplementary Tables 3, 4.

Extended Data Fig. 4 Illustration of negative admixture _f_3 statistics for Iron Age populations.

Plot shows _f_3(Bronze Age Test 1, Bronze Age Test 2; Iron Age Test). The reported numbers are of the _f_3 statistics, and the 3 standard errors were plotted as errors bars. The number of individuals per population can be found in Supplementary Table 3.

Extended Data Fig. 5 Illustration of West Eurasian gene flow into groups forming the Xiongnu culture.

We represent all D(Test, Mbuti; ‘Western’ Xiongnu, Xiongnu) that deviate significantly from 0 (that is, higher than 3× the standard errors). The reported numbers are the _D_-statistics and the 3 standard errors were plotted as error bars. The number of individuals per population can be found in Supplementary Tables 3, 4.

Extended Data Fig. 6 Illustration of West Eurasian ancestry in early Tian Shan Huns.

We represent all D(Test, Mbuti; Tian Shan Huns, Xiongnu) that deviate significantly from 0 (that is, higher than 3× the standard errors). The reported numbers are the _D_-statistics and the 3 standard errors were plotted as error bars. The number of individuals per population can be found in Supplementary Tables 3, 4.

Extended Data Fig. 7 Analyses of Xiongnu and Hun period population clusters.

a, PCA of Xiongnu, ‘Western’ Xiongnu, Tian Shan Huns, Hun-period nomads, Tian Shan Sakas, Kangju and Wusun, including 49 individuals analysed at 242,406 autosomal SNP positions. b, Results for model-based clustering analysis at K = 7. Here we illustrate the admixture analyses with K = 7 as it approximately identifies the major component of relevance (Anatolian/European farmer component, Caucasian ancestry, EHG-related ancestry and East Asian ancestry). Individual A is a southern Siberian individual associated with the Andronovo culture.

Extended Data Fig. 8 Analyses of Turk- and Medieval-period population clusters.

a, PCA of Tian Shan Hun, Turk, Kimak, Kipchack, Karakhanid and Golden Horde, including 28 individuals analysed at 242,406 autosomal SNP positions. b, Results for model-based clustering analysis at K = 7. Here we illustrate the admixture analyses with K = 7 as it approximately identifies the major component of relevance (Anatolian/European farmer component, Caucasian ancestry, EHG-related ancestry and East Asian ancestry).

Extended Data Fig. 9 Maximum likelihood phylogenetic reconstruction of Y. pestis.

This tree reveals the basal position of the Tian Shan sample (0.ANT5, DA101, ad 186) compared to the Justinian plague sample (0.ANT4, A120, ad 536). These two samples are shown in orange italics. Other ancient plague samples included in the tree are Bronze Age samples (0.PRE1 and 0.PRE2) and a Black Death sample (1.PRE1). Numbers on nodes indicate bootstrap support (not all of which are shown, for clarity) and certain branches have been collapsed for clarity. Branch lengths are substitutions per site.

Extended Data Fig. 10 Analyses of sex-specific contributions to Iron Age populations.

Estimates of the male and female contributions from each source populations (left column) to each of the four admixed populations (right column) using a previously published method40. For each admixed population, we compared the observed mean autosomal and X-chromosomal ancestry, estimated in qpAdm, to that calculated under a constant admixture model on a grid of sex-specific contribution parameters ranging from 0 to 1 in 0.025 increments using a Euclidean distance. The logarithms of the ratio of male to female contribution parameters that produce the smallest 0.1% of distances from the data are plotted, with the full range of parameter values in grey, the middle 50% in black, and the median value in red. The dashed line indicates equal male and female contributions.

Supplementary information

Supplementary Information

This files contains Section 1 (Archaeological background for Iron Age to Medieval steppe cultures), Section 2 (Linguistic history of the steppe), Section 3 (Data generation and analyses), Section 4 (Site descriptions and individual outgroup-f3 statistics), Section 5 (Modern dataset), Section 6 (Comparing ancient DNA preservation in the mineral and organic phases of tooth cementum), Section 7 (Plague genome reconstructions), Section 8 (Y-chromosomal analyses), Section 9 (Sarmatians and Alan), Section 10 (Mitogenomes) and Section 11 (Radiocarbon dating)

Reporting Summary

Supplementary Table 1

Basic mapping statistics

Supplementary Table 2

Overview of ancient samples. This table includes radiocarbon dating and calibration, geographical coordinates and genetic gender.

Supplementary Table 3

Population label and sample size overview. This table provides a fast contextualization of population labels used here.

Supplementary Table 4

Information on present-day dataset. This includes geographical coordinates coupled to the full presentation of ancestral proportions estimated using qpAdm with a set of 5 outgroups: Mbuti, Ust'Ishim, Clovis, Kostenki14 and Switzerland HG. Number of individuals per modelled population can be found in Supplementary Table 3. See Supplementary Information section 3 for description of qpAdm analyses.

Supplementary Table 5

QpAdm modelling of Iron Age Scythians. We here compare different sets of sources, ie. Andronovo, Sintashta and Yamnaya and a set of 7 outgroups (Mbuti, Ust'Ishim, Clovis, Kostenki14, Switzerland_HG, Natufian and MA1). Red colors reflect a failed model. Note that for Tagar where MA1 was used a source, the outgroup was replaced with EHG. Number of individuals per modelled population can be found in Supplementary Table 3. See Supplementary Section 3 for description of qpAdm analyses.

Supplementary Table 6

Fst values between the Iron Age Scythian groups. Number of individuals per modelled population can be found in Supplementary Table 3.

Supplementary Table 7

QpAdm modelling of Kangju and Wusun. We here use a set of 7 outgroups (Mbuti, Ust'Ishim, Clovis, Kostenki14, Switzerland_HG, Natufian and MA1). Number of individuals per modelled population can be found in Supplementary Table 3. See Supplementary Information section 3 for description of qpAdm analyses.

Supplementary Table 8

Authentication assessment. Damage parameters, contamination estimates and mitogenome haplogroup assignment. See Supplementary Information sections 3 and 10 for exhaustive description of sample analyses.

Supplementary Table 9

Confident Y-chromosomal haplogroup assignment.

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Damgaard, P.d.B., Marchi, N., Rasmussen, S. et al. 137 ancient human genomes from across the Eurasian steppes.Nature 557, 369–374 (2018). https://doi.org/10.1038/s41586-018-0094-2

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• Received: 18 April 2017
• Accepted: 03 April 2018
• Published: 09 May 2018
• Issue Date: 17 May 2018
• DOI: https://doi.org/10.1038/s41586-018-0094-2