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Population genomics of Bronze Age Eurasia

Abstract

The Bronze Age of Eurasia (around 3000–1000 BC) was a period of major cultural changes. However, there is debate about whether these changes resulted from the circulation of ideas or from human migrations, potentially also facilitating the spread of languages and certain phenotypic traits. We investigated this by using new, improved methods to sequence low-coverage genomes from 101 ancient humans from across Eurasia. We show that the Bronze Age was a highly dynamic period involving large-scale population migrations and replacements, responsible for shaping major parts of present-day demographic structure in both Europe and Asia. Our findings are consistent with the hypothesized spread of Indo-European languages during the Early Bronze Age. We also demonstrate that light skin pigmentation in Europeans was already present at high frequency in the Bronze Age, but not lactose tolerance, indicating a more recent onset of positive selection on lactose tolerance than previously thought.

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Figure 1: Distribution maps of ancient samples.
Figure 2: Genetic structure of ancient Europe and the Pontic-Caspian steppe.
Figure 3: Genetic structure of Bronze Age Asia.
Figure 4: Allele frequencies for putatively positively selected SNPs.

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Primary accessions

European Nucleotide Archive

Data deposits

DNA sequence alignments are available from the European Nucleotide Archive (http://www.ebi.ac.uk/ena) under accession number PRJEB9021.

References

  1. Fu, Q. et al. Genome sequence of a 45,000-year-old modern human from western Siberia. Nature 514, 445–449 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  2. Seguin-Orlando, A. et al. Genomic structure in Europeans dating back at least 36,200 years. Science 346, 1113–1118 (2014)

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Rasmussen, M. et al. An Aboriginal Australian genome reveals separate human dispersals into Asia. Science 334, 94–98 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  4. Raghavan, M. et al. Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans. Nature 505, 87–91 (2014)

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Raghavan, M. et al. The genetic prehistory of the New World Arctic. Science 345, 1255832 (2014)

    Article  PubMed  CAS  Google Scholar 

  6. Rasmussen, M. et al. The genome of a Late Pleistocene human from a Clovis burial site in western Montana. Nature 506, 225–229 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bramanti, B. et al. Genetic discontinuity between local hunter-gatherers and Central Europe’s first farmers. Science 326, 137–140 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  8. Malmström, H. et al. Ancient DNA reveals lack of continuity between Neolithic hunter-gatherers and contemporary Scandinavians. Curr. Biol. 19, 1758–1762 (2009)

    Article  PubMed  CAS  Google Scholar 

  9. Skoglund, P. et al. Origins and genetic legacy of Neolithic farmers and hunter-gatherers in Europe. Science 336, 466–469 (2012)

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Lazaridis, I. et al. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Haak, W. et al. Ancient DNA from European early Neolithic farmers reveals their Near Eastern affinities. PLoS Biol. 8, e1000536 (2010)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Gamba, C. et al. Genome flux and stasis in a five millennium transect of European prehistory. Nature Commun. 5, 5257 (2014)

    Article  ADS  CAS  Google Scholar 

  13. Kristiansen, K. in The World System and the Earth System. Global Socioenvironmental Change and Sustainability Since the Neolithic (eds Hornborg, B. & Crumley, C.) (Left Coast Press, 2007)

    Google Scholar 

  14. Shishlina, N. Reconstruction of the Bronze Age of the Caspian Steppes. Life Styles and Life Ways of Pastoral Nomads. Vol. 1876 (Archaeopress, 2008)

    Google Scholar 

  15. Anthony, D. The Horse, The Wheel and Language. How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World (Princeton Univ. Press, 2007)

    Google Scholar 

  16. Harrison, R. & Heyd, V. The Transformation of Europe in the third millennium BC: the example of ‘Le Petit-Chasseur I + III’ (Sion, Valais, Switzerland). Praehistorische Zeitschrift. 82, 129–214 (2007)

    Article  Google Scholar 

  17. Vandkilde, H. Culture and Change in the Central European Prehistory, 6th to 1st millennium BC (Aarhus Univ. Press, 2007)

    Google Scholar 

  18. Kristiansen, K. & Larsson, T. The Rise of Bronze Age Society. Travels, Transmissions and Transformations (Cambridge Univ. Press, 2005)

    Google Scholar 

  19. Hanks, B. K., Epimakhov, A. V. & Renfrew, A. C. Towards a refined chronology for the Bronze Age of the southern Urals, Russia. Antiquity 81, 353–367 (2007)

    Article  Google Scholar 

  20. Kuznetsov, P. F. The emergence of Bronze Age chariots in Eastern Europe. Antiquity 80, 638–645 (2006)

    Article  Google Scholar 

  21. Koryakova, L. & Epimakhov, A. V. The Urals and Western Siberia in the Bronze and Iron Ages (Cambridge Univ. Press, 2007)

    Book  Google Scholar 

  22. Rasmussen, M. et al. Ancient human genome sequence of an extinct Palaeo-Eskimo. Nature 463, 757–762 (2010)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  23. Carpenter, M. L. et al. Pulling out the 1%: whole-genome capture for the targeted enrichment of ancient DNA sequencing libraries. Am. J. Hum. Genet. 93, 852–864 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Barros Damgaard, P. d. et al. Improving access to endogenous DNA in ancient bones and teeth. Preprint at bioRxivhttp://dx.doi.org/10.1101/014985 (2015)

  25. Adler, C. J., Haak, W., Donlon, D., Cooper, A. & The Genographic Consortium Survival and recovery of DNA from ancient teeth and bones. J. Archaeol. Sci. 38, 956–964 (2011)

    Article  Google Scholar 

  26. Orlando, L. et al. True single-molecule DNA sequencing of a Pleistocene horse bone. Genome Res. 21, 1705–1719 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Olalde, I. & Lalueza-Fox, C. Modern humans’ paleogenomics and the new evidences on the European prehistory. Science and Technology of Archaeological Research 1, http://dx.doi.org/10.1179/2054892315Y.0000000002 (2015)

  28. Grigoriev, S. Ancient Indo-Europeans (Charoid, 2002)

    Google Scholar 

  29. Bendezu-Sarmiento, J. De l’Âge du Bronze et lÂge du Fer au Kazakkstan, gestes funéraires et paramètres biologiques. Identités culturelles des population Andronovo et Saka (De Boccard, 2007)

    Google Scholar 

  30. Kozintsev, A. G., Gromov, A. V. & Moiseyev, V. G. Collateral relatives of American Indians among the Bronze Age populations of Siberia? Am. J. Phys. Anthropol. 108, 193–204 (1999)

    Article  CAS  PubMed  Google Scholar 

  31. Kristiansen, K. in Becoming European. The transformation of third millennium Northern and Western Europe (eds Prescott, C. & Glørstad, H.) (Oxbow Books, 2012)

    Google Scholar 

  32. Haak, W. et al. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature http://dx.doi.org/10.1038/nature14317 (this issue)

  33. Olalde, I. et al. Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic European. Nature 507, 225–228 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  34. Itan, Y., Powell, A., Beaumont, M. A., Burger, J. & Thomas, M. G. The origins of lactase persistence in Europe. PLoS Computational Biol. 5, e1000491 (2009)

    Article  ADS  MathSciNet  CAS  Google Scholar 

  35. Mallory, J. In Search of the Indo-Europeans. Language, Archaeology and Myth (Thames & Hudson, 1987)

    Google Scholar 

  36. Renfrew, A. C. Archaeology and Language. The Puzzle of Indo-European Origins (Penguin, 1987)

    Google Scholar 

  37. Mallory, J. & Mair, V. The Tarim Mummies. Ancient China and the Mystery of the Earliest People from the West (Thames & Hudson, 2000)

    Google Scholar 

  38. Keyser, C. et al. Ancient DNA provides new insights into the history of south Siberian Kurgan people. Hum. Genet. 126, 395–410 (2009)

    Article  CAS  PubMed  Google Scholar 

  39. Meyer, M. & Kircher, M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protocols (2010)

  40. Orlando, L. et al. Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse. Nature 499, 74–78 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  41. Malaspinas, A.-S. et al. Two ancient human genomes reveal Polynesian ancestry among the indigenous Botocudos of Brazil. Curr. Biol. 24, R1035–R1037 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Willerslev, E. & Cooper, A. Ancient DNA. Proc. Royal Soc. B 272, 3–16 (2005)

    Article  CAS  Google Scholar 

  43. Briggs, A. W. et al. Patterns of damage in genomic DNA sequences from a Neandertal. Proc. Natl Acad. Sci. USA 104, 14616–14621 (2007)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  44. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Schubert, M. et al. Improving ancient DNA read mapping against modern reference genomes. BMC Genomics 13, 178 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Jónsson, H., Ginolhac, A., Schubert, M., Johnson, P. & Orlando, L. mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters. Bioinformatics (2013)

  49. Fu, Q. et al. DNA analysis of an early modern human from Tianyuan Cave, China. Proc. Natl Acad. Sci. USA 110, 2223–2227 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  50. Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: analysis of next generation sequencing data. BMC Bioinformatics 15, (2014)

  51. Patterson, N., Price, A. L. & Reich, D. Population structure and Eigenanalysis. PLoS Genet. 2, e190 (2006)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Patterson, N. et al. Ancient admixture in human history. Genetics 192, 1065–1093 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  54. Weir, B. S. & Hill, W. Estimating F-statistics. Annu. Rev. Genet. 36, 721–750 (2002)

    Article  CAS  PubMed  Google Scholar 

  55. Nyström, V. et al. Microsatellite genotyping reveals end-Pleistocene decline in mammoth autosomal genetic variation. Mol. Ecol. 21, 3391–3402 (2012)

    Article  PubMed  CAS  Google Scholar 

  56. Browning, S. R. & Browning, B. L. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am. J. Hum. Genet. 81, 1084–1097 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank K. Magnussen, L. A. Petersen, C. D. Mortensen and A. Seguin-Orlando at the Danish National Sequencing Centre for help with the sequencing. We thank C. G. Zacho for technical assistance. The project was funded by The European Research Council (FP/2007-2013, grant no. 269442, The Rise), The University of Copenhagen (KU2016 programme), Marie Curie Actions of the European Union (FP7/2007-2013, grant no. 300554), The Villum Foundation (Young Investigator Programme, grant no. 10120), Frederik Paulsen, The Miller Institute, University of California, Berkeley, The Lundbeck Foundation, and The Danish National Research Foundation.

Author information

Authors and Affiliations

Authors

Contributions

E.W. and K.K. initiated and led the study. M.E.A., J.S., L.V., H.S., P.B.D., A.M., M.R., L.S. performed the DNA laboratory work. M.Si., S.R., M.E.A., A.-S.M., P.B.D., A.M. analysed the genetic data. K.-G.S., T.A., N.L., L.H., J.B., P.D.C., P.D., P.R.D., A.E., A.V.E., K.F., M.F., G.G., T.G., A.G., S.G., T.H., R.J., J.K., V.K., A.K., V.K., A.K., I.L., C.L., A.M., G.M., I.M., M.M., R.M., V.M., D.Po., G.P., L.P., D.Pr., L.P., M.Sa., N.S., V.Sm., V.Sz., V.I.S., G.T., S.V.T., L.V., M.V., L.Y., V.Z. collected the samples and/or provided input to the archaeological interpretations. T.H. and D.C. conducted radiocarbon dating. T.S.-P., L.O., S.B., R.N. provided input to the genetic analyses. E.W., K.K., M.E.A., M.Si., K.-G.S. wrote the paper with input from all co-authors.

Corresponding author

Correspondence to Eske Willerslev.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Principal component analysis of ancient genomes.

a, b, Principal component analysis of ancient individuals projected onto contemporary individuals from non-African populations (a), Europe, West Asia and the Caucasus (b). Grey labels represent population codes indicating coordinates for individuals (small) and median of the population (large). Coloured labels indicate positions for ancient individuals (small) and median for ancient groups (large). Ancient individuals within a group are connected to the respective median position by coloured lines.

Extended Data Figure 2 Pairwise outgroup f3 statistics.

Panels depict pairwise plots of outgroup f3 statistics of the form f3(Ju’hoan North;Population1, Population2), showing the correlation of the amount of shared genetic drift for a pair of ancient groups (Population1) with all modern populations (Population2) in the Human Origins data set (panel A). Closely related ancient groups are expected to show highly correlated statistics. a, Sintashta/Corded Ware. b, Yamnaya/Afanasievo. c, Sintashta/Andronovo. d, Okunevo/Mal’ta. Coloured circles indicate modern populations; error bars indicate ± 1 standard error from the block jackknife.

Extended Data Figure 3 Yamnaya ancestry mirrors Mal’ta ancestry in present-day Europeans and Caucasians.

Panels show pairwise plots of D-statistics D(Outgroup, Ancient)(Bedouin, Modern), contrasting Mal’ta (MA1) and Hunter-gatherers (a), and MA1 and Yamnaya (b). Coloured labels indicate modern populations, with lines corresponding to ± 1 standard error of the respective D-statistic from block jacknife. Text away from the diagonal line indicates an ancient group with relative increase in allele sharing with the respective modern populations.

Extended Data Figure 4 Genetic differentiation between ancient and modern groups in Human Origins data set.

Panels show FST between pairs of modern and ancient groups (coloured lines) for subsets of ancient groups, with results for the remaining groups in the background (grey). Top, early Europeans. Middle, Bronze Age Europeans and steppe/Caucasus. Bottom, Bronze Age Asians. Results based on Human Origins data set (panel A).

Extended Data Figure 5 Genetic differentiation between ancient and modern groups in 1000 Genomes data set.

Matrix of pairwise FST values between modern and ancient groups in the 1000 Genomes data set (panel B).

Extended Data Figure 6 Distribution of uniparental lineages in Bronze Age Eurasians.

a, b, Barplots showing the relative frequency of Y chromosome (a) and mitochondrial DNA lineages (b) in different Bronze Age groups. Top row shows overall frequencies for all individuals combined.

Extended Data Figure 7 Derived allele frequencies for lactase persistence in modern and ancient groups.

Derived allele frequency of rs4988235 in the LCT gene inferred from imputation of ancient individuals. Numbers indicate the total number of chromosomes for each group.

Extended Data Table 1 Selected D-test results from 1000 Genomes data set (panel B)
Extended Data Table 2 f3 statistic results for ancient groups

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Supplementary information

Supplementary Information

This file contains Supplementary Information sections 1-6. Section 1: An introduction to the sampled cultures and their dating. Section 2: Brief description of the samples (including Supplementary Tables 1-3). Section 3: Laboratory work and sample selection (including Supplementary Tables 4-5, and Supplementary Figure 1). Section 4: Radiocarbon dating. Section 5: Bioinformatics and DNA authentication. Section 6: Population genomics (including Supplementary Table 9 and Supplementary Figures 2-6). (PDF 4331 kb)

Supplementary Table 6

This table contains sequencing summary statistics. (XLSX 20 kb)

Supplementary Table 7

This table contains an overview of aDNA damage statistics. (XLS 44 kb)

Supplementary Table 8

This table contains results of DNA contamination tests. (XLSX 18 kb)

Supplementary Table 10

This table contains D-test for all combinations D(Outgroup,Ancient1)(Ancient2)(Ancient3); 1000 Genomes dataset. (XLSX 1915 kb)

Supplementary Table 11

This table contains “Outgroup” f3-statistics for all combinations of ancient and modern groups; Human Origins dataset. (XLSX 748 kb)

Supplementary Table 12

This table contains all-pair “admixture” f3-statistics; 1000 Genomes dataset. (XLSX 3921 kb)

Supplementary Table 13

This table contains derived allele frequencies of 104 SNP catalogue for putative selection; 1000 Genomes dataset. (XLSX 63 kb)

Supplementary Table 14

This table contains an overview of mtDNA haplogroups and identified variants. (XLS 97 kb)

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Allentoft, M., Sikora, M., Sjögren, KG. et al. Population genomics of Bronze Age Eurasia. Nature 522, 167–172 (2015). https://doi.org/10.1038/nature14507

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