The genetic history of Ice Age Europe

Journal name:
Nature
Volume:
534,
Pages:
200–205
Date published:
DOI:
doi:10.1038/nature17993
Received
Accepted
Published online

Abstract

Modern humans arrived in Europe ~45,000 years ago, but little is known about their genetic composition before the start of farming ~8,500 years ago. Here we analyse genome-wide data from 51 Eurasians from ~45,000–7,000 years ago. Over this time, the proportion of Neanderthal DNA decreased from 3–6% to around 2%, consistent with natural selection against Neanderthal variants in modern humans. Whereas there is no evidence of the earliest modern humans in Europe contributing to the genetic composition of present-day Europeans, all individuals between ~37,000 and ~14,000 years ago descended from a single founder population which forms part of the ancestry of present-day Europeans. An ~35,000-year-old individual from northwest Europe represents an early branch of this founder population which was then displaced across a broad region, before reappearing in southwest Europe at the height of the last Ice Age ~19,000 years ago. During the major warming period after ~14,000 years ago, a genetic component related to present-day Near Easterners became widespread in Europe. These results document how population turnover and migration have been recurring themes of European prehistory.

At a glance

Figures

  1. Location and age of the 51 ancient modern humans.
    Figure 1: Location and age of the 51 ancient modern humans.

    Each bar corresponds to an individual, the colour code designates the genetically defined cluster of individuals, and the height is proportional to age (the background grid shows a projection of longitude against age). To help in visualization, we add jitter for sites with multiple individuals from nearby locations. Four individuals from Siberia are plotted at the far eastern edge of the map. ka, thousand years ago.

  2. Decrease of Neanderthal ancestry over time.
    Figure 2: Decrease of Neanderthal ancestry over time.

    Plot of radiocarbon date against Neanderthal ancestry for individuals with at least 200,000 SNPs covered, along with present-day Eurasians (standard errors are from a block jackknife). The least squares fit (grey) excludes the data from Oase1 (an outlier with recent Neanderthal ancestry) and three present-day European populations (known to have less Neanderthal ancestry than east Asians). The slope is significantly negative for all eleven subsets of individuals we analysed (10−29 < P < 10−11 based on a block jackknife) (Extended Data Table 3). BP, before present.

  3. Genetic clustering of the ancient modern humans.
    Figure 3: Genetic clustering of the ancient modern humans.

    a, Shared genetic drift measured by f3(X,Y; Mbuti) among individuals with at least 30,000 SNPs covered (for AfontovaGora3, ElMiron, Falkenstein, GoyetQ-2, GoyetQ53-1, HohleFels49, HohleFels79, LesCloseaux13, Ofnet, Ranchot88 and Rigney1, we use all sequences for higher resolution). Lighter colours indicate more shared drift. b, Multi-dimensional scaling (MDS) analysis, computed using the R software cmdscale package, highlights the main genetic groupings analysed in this study: Věstonice Cluster (brown), Mal’ta Cluster (pink), El Mirón Cluster (yellow), Villabruna Cluster (light green), and Satsurblia Cluster (dark purple). The affinity of GoyetQ116-1 (dark green) to the El Mirón Cluster is evident in both views of the data.

  4. Population history inferences.
    Figure 4: Population history inferences.

    a, Admixture graph relating selected high coverage individuals. Dashed lines show inferred admixture events; the estimated mixture proportions fitted using the ADMIXTUREGRAPH software are labelled28(the estimated genetic drift on each branch is given in a version of this graph shown in Supplementary Information section 6). The individuals are positioned vertically based on their radiocarbon date, but we caution that the population split times are not accurately known. Colour is used to highlight important early branches of the European founder population: the Kostenki14 lineage is modelled as the predominant contributor to the Věstonice Cluster (green); the GoyetQ116-1 lineage as the predominant contributor to the El Mirón Cluster (red); and the Villabruna lineage as broadly represented across many clusters. b, Drawing together of European and Near Eastern populations ~14,000 years ago. Plot of affinity of each pre-Neolithic European population X to non-Africans outside Europe Y moving forward in time, comparing to Kostenki14 as a baseline; values Z < −3 standard errors below zero are indicated with filled symbols (we restricted to individuals with >50,000 SNPs). We observe an affinity to Near Easterners beginning with the Villabruna Cluster, and another to east Asians that affects a subset of the Villabruna Cluster.

  5. A decrease in Neanderthal ancestry in the last 45,000 years.
    Extended Data Fig. 1: A decrease in Neanderthal ancestry in the last 45,000 years.

    This is similar to Fig. 2, except we use ancestry estimates from rates of alleles matching to Neanderthal rather than f4-ratios, as described in Supplementary Information section 3. The least-squares fit excludes Oase1 (as an outlier with recent Neanderthal ancestry) and Europeans (known to have reduced Neanderthal ancestry). The regression slope is significantly negative (P = 0.00004, Extended Data Table 3).

  6. Heat matrix of pairwise f3(X, Y; Mbuti) for selected ancient individuals.
    Extended Data Fig. 2: Heat matrix of pairwise f3(X, Y; Mbuti) for selected ancient individuals.

    Only individuals with at least 30,000 SNPs covered at least once are analysed.

  7. Studying how the relatedness of non-European populations to pairs of European hunter-gatherers changes over time.
    Extended Data Fig. 3: Studying how the relatedness of non-European populations to pairs of European hunter-gatherers changes over time.

    Statistics were examined of the form D(W, X; Y, Mbuti), with the Z-score given on the y axis, where W is an early European hunter-gatherer, X is another European hunter-gatherer (in chronological order on the x axis), and Y is a non-European population (see legend). a, W = Kostenki14. b, W = GoyetQ116-1. c, W = Vestonice16. d, W = ElMiron. |Z| > 3 scores are considered statistically significant (horizontal line). The similar Fig. 4b gives absolute D-statistic values rather than Z-scores (for W = Kostenki14) and uses pooled regions rather than individual populations Y.

  8. Three admixture graph models that fit the data for Satsurblia, an Upper Palaeolithic individual from the Caucasus.
    Extended Data Fig. 4: Three admixture graph models that fit the data for Satsurblia, an Upper Palaeolithic individual from the Caucasus.

    These models use 127,057 SNPs covered in all populations. Estimated genetic drifts are given along the solid lines in units of f2-distance (parts per thousand), and estimated mixture proportions are given along the dotted lines. All three models provide a fit to the allele frequency correlation data among Mbuti, Ust’-Ishim, Kostenki14, Vestonice16, Malta1, ElMiron and Satsurblia to within the limits of our resolution, in the sense that all empirical f2-, f3- and f4-statistics relating the individuals are within three standard errors of the expectation of the model. Models in which Satsurblia is treated as unadmixed cannot be fit.

Tables

  1. The 51 ancient modern humans analysed in this study
    Extended Data Table 1: The 51 ancient modern humans analysed in this study
  2. Estimated proportion of Neanderthal ancestry
    Extended Data Table 2: Estimated proportion of Neanderthal ancestry
  3. Significant correlation of Neanderthal ancestry estimate with specimen age
    Extended Data Table 3: Significant correlation of Neanderthal ancestry estimate with specimen age
  4. Sex determination for newly reported individuals
    Extended Data Table 4: Sex determination for newly reported individuals
  5. Allele counts at SNPs affected by selection in individuals with >1-fold coverage
    Extended Data Table 5: Allele counts at SNPs affected by selection in individuals with >1-fold coverage
  6. All European hunter-gatherers beginning with Kostenki14 share genetic drift with present-day Europeans
    Extended Data Table 6: All European hunter-gatherers beginning with Kostenki14 share genetic drift with present-day Europeans

Accession codes

Primary accessions

European Nucleotide Archive

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Author information

  1. These authors contributed equally to this work.

    • Cosimo Posth &
    • Mateja Hajdinjak
  2. These authors jointly supervised this work.

    • Johannes Krause,
    • Svante Pääbo &
    • David Reich

Affiliations

  1. Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, IVPP, CAS, Beijing 100044, China

    • Qiaomei Fu
  2. Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA

    • Qiaomei Fu,
    • Swapan Mallick,
    • Nadin Rohland,
    • Iosif Lazaridis,
    • Mark Lipson,
    • Iain Mathieson,
    • Pontus Skoglund &
    • David Reich
  3. Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany

    • Qiaomei Fu,
    • Mateja Hajdinjak,
    • Martin Petr,
    • Matthias Meyer,
    • Birgit Nickel,
    • Viviane Slon,
    • Janet Kelso &
    • Svante Pääbo
  4. Institute for Archaeological Sciences, Archaeo- and Palaeogenetics, University of Tübingen, 72070 Tübingen, Germany

    • Cosimo Posth,
    • Anja Furtwängler,
    • Alissa Mittnik,
    • Alexander Peltzer &
    • Johannes Krause
  5. Department of Archaeogenetics, Max Planck Institute for the Science of Human History, 07745 Jena, Germany

    • Cosimo Posth,
    • Wolfgang Haak,
    • Alissa Mittnik,
    • Stephan Schiffels &
    • Johannes Krause
  6. Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA

    • Swapan Mallick,
    • Nick Patterson &
    • David Reich
  7. Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA

    • Swapan Mallick &
    • David Reich
  8. School of Archaeology and Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland

    • Daniel Fernandes &
    • Ron Pinhasi
  9. CIAS, Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, Portugal

    • Daniel Fernandes
  10. Australian Centre for Ancient DNA, School of Biological Sciences, The University of Adelaide, SA-5005 Adelaide, Australia

    • Wolfgang Haak
  11. Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany

    • Sahra Talamo,
    • Stefano Benazzi,
    • Marcello A. Mannino &
    • Michael P. Richards
  12. Institute of Archaeology and Ethnography, Russian Academy of Sciences, Siberian Branch, 17 Novosibirsk, RU-630090, Russia

    • Anatoly P. Derevianko,
    • Nikolai Drozdov,
    • Vyacheslav Slavinsky &
    • Alexander Tsybankov
  13. Altai State University, Barnaul, RU-656049, Russia

    • Anatoly P. Derevianko
  14. Dipartimento di Civiltà e Forme del Sapere, Università di Pisa, 56126 Pisa, Italy

    • Renata Grifoni Cremonesi
  15. Department of Biology, University of Pisa, 56126 Pisa, Italy

    • Francesco Mallegni
  16. Direction régionale des affaires culturelles Rhône-Alpes, 69283 Lyon, Cedex 01, France

    • Bernard Gély
  17. Dipartimento di Biologia, Università degli Studi di Bari ‘Aldo Moro’, 70125 Bari, Italy

    • Eligio Vacca
  18. Instituto Internacional de Investigaciones Prehistóricas, Universidad de Cantabria, 39005 Santander, Spain

    • Manuel R. González Morales &
    • Lawrence G. Straus
  19. Department of Anthropology, MSC01 1040, University of New Mexico, Albuquerque, New Mexico 87131-0001, USA

    • Lawrence G. Straus
  20. Quaternary Archaeology, Institute for Oriental and European Archaeology, Austrian Academy of Sciences, 1010 Vienna, Austria

    • Christine Neugebauer-Maresch
  21. Department of Anthropology, Natural History Museum Vienna, 1010 Vienna, Austria

    • Maria Teschler-Nicola
  22. Department of Anthropology, University of Vienna, 1090 Vienna, Austria

    • Maria Teschler-Nicola
  23. “Emil Racoviţă” Institute of Speleology, 010986 Bucharest 12, Romania

    • Silviu Constantin
  24. “Emil Racoviţă” Institute of Speleology, Cluj Branch, 400006 Cluj, Romania

    • Oana Teodora Moldovan
  25. Department of Cultural Heritage, University of Bologna, 48121 Ravenna, Italy

    • Stefano Benazzi
  26. Sezione di Scienze Preistoriche e Antropologiche, Dipartimento di Studi Umanistici, Università di Ferrara, 44100 Ferrara, Italy

    • Marco Peresani
  27. Università degli Studi di Bari ‘Aldo Moro’, 70125 Bari, Italy

    • Donato Coppola
  28. Museo di “Civiltà preclassiche della Murgia meridionale”, 72017 Ostuni, Italy

    • Donato Coppola
  29. Dipartimento di Biologia, Università di Firenze, 50122 Florence, Italy

    • Martina Lari &
    • David Caramelli
  30. Dipartimento di Scienze Fisiche, della Terra e dell’Ambiente, U.R. Preistoria e Antropologia, Università degli Studi di Siena, 53100 Siena, Italy

    • Stefano Ricci &
    • Annamaria Ronchitelli
  31. CNRS/UMR 7041 ArScAn MAE, 92023 Nanterre, France

    • Frédérique Valentin
  32. INRAP/UMR 8215 Trajectoires 21, 92023 Nanterre, France

    • Corinne Thevenet
  33. Ulmer Museum, 89073 Ulm, Germany

    • Kurt Wehrberger
  34. University of Bucharest, Faculty of Geology and Geophysics, Department of Geology, 01041 Bucharest, Romania

    • Dan Grigorescu
  35. Department of Anthropology, California State University Northridge, Northridge, California 91330-8244, USA

    • Hélène Rougier
  36. Université de Bordeaux, CNRS, UMR 5199-PACEA, 33615 Pessac Cedex, France

    • Isabelle Crevecoeur
  37. TRACES – UMR 5608, Université Toulouse Jean Jaurès, Maison de la Recherche, 31058 Toulouse Cedex 9, France

    • Damien Flas
  38. Royal Belgian Institute of Natural Sciences, 1000 Brussels, Belgium

    • Patrick Semal
  39. Department of Archaeology, School of Culture and Society, Aarhus University, 8270 Højbjerg, Denmark

    • Marcello A. Mannino
  40. Service Régional d’Archéologie de Franche-Comté, 25043 Besançon Cedex, France

    • Christophe Cupillard
  41. Laboratoire Chronoenvironnement, UMR 6249 du CNRS, UFR des Sciences et Techniques, 25030 Besançon Cedex, France

    • Christophe Cupillard
  42. Department of Geosciences, Biogeology, University of Tübingen, 72074 Tübingen, Germany

    • Hervé Bocherens &
    • Dorothée G. Drucker
  43. Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, 72072 Tübingen, Germany

    • Hervé Bocherens,
    • Nicholas J. Conard,
    • Katerina Harvati &
    • Johannes Krause
  44. Department of Early Prehistory and Quaternary Ecology, University of Tübingen, 72070 Tübingen, Germany

    • Nicholas J. Conard
  45. Institute for Archaeological Sciences, Paleoanthropology, University of Tübingen, 72070 Tübingen, Germany

    • Katerina Harvati
  46. Museum of Anthropology and Ethnography, Saint Petersburg 34, Russia

    • Vyacheslav Moiseyev
  47. Department of Anthropology, Faculty of Science, Masaryk University, 611 37 Brno, Czech Republic

    • Jiří Svoboda
  48. Institute of Archaeology at Brno, Academy of Science of the Czech Republic, 69129 Dolní Vĕstonice, Czech Republic

    • Jiří Svoboda
  49. Department of Archaeology, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada

    • Michael P. Richards

Contributions

J.Kr, S.P. and D.R. conceived the idea for the study. Q.F., C.P., M.H., W.H., M.Me, V.Slo, R.G.C., A.P.D., N.D., V.Sla, A.T., F.M., B.G., E.V., M.R.G.M., L.G.S., C.N.-M., M.T.-N., S.C., O.T.M., S.B., M.Per, D.Co, M.La, S.R., A.R., F.V., C.T., K.W., D.G., H.R., I.C., D.Fl, P.Se, M.A.M., C.C., H.B., N.J.C., K.H., V.M., D.G.D., J.S., D.Ca, R.P., J.Kr, S.P. and D.R. assembled archaeological material. Q.F., C.P., M.H., D.Fe, A.F., W.H., M.Me, A.M., B.N., N.R., V.Slo, S.T., H.B., D.G.D., M.P.R., R.P., J.Kr, S.P. and D.R. performed or supervised wet laboratory work. Q.F., C.P., M.H., M.Pet, S.M., A.P., I.L., M.Li, I.M., S.S., P.Sk, J.Ke, N.P. and D.R. analysed data. Q.F., C.P., M.H., M.Pet, J.Ke, S.P. and D.R. wrote the manuscript and supplements.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

The aligned sequences are available through the European Nucleotide Archive under accession number PRJEB13123.

Reviewer Information Nature thanks C. Lalueza-Fox and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author details

Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: A decrease in Neanderthal ancestry in the last 45,000 years. (127 KB)

    This is similar to Fig. 2, except we use ancestry estimates from rates of alleles matching to Neanderthal rather than f4-ratios, as described in Supplementary Information section 3. The least-squares fit excludes Oase1 (as an outlier with recent Neanderthal ancestry) and Europeans (known to have reduced Neanderthal ancestry). The regression slope is significantly negative (P = 0.00004, Extended Data Table 3).

  2. Extended Data Figure 2: Heat matrix of pairwise f3(X, Y; Mbuti) for selected ancient individuals. (332 KB)

    Only individuals with at least 30,000 SNPs covered at least once are analysed.

  3. Extended Data Figure 3: Studying how the relatedness of non-European populations to pairs of European hunter-gatherers changes over time. (525 KB)

    Statistics were examined of the form D(W, X; Y, Mbuti), with the Z-score given on the y axis, where W is an early European hunter-gatherer, X is another European hunter-gatherer (in chronological order on the x axis), and Y is a non-European population (see legend). a, W = Kostenki14. b, W = GoyetQ116-1. c, W = Vestonice16. d, W = ElMiron. |Z| > 3 scores are considered statistically significant (horizontal line). The similar Fig. 4b gives absolute D-statistic values rather than Z-scores (for W = Kostenki14) and uses pooled regions rather than individual populations Y.

  4. Extended Data Figure 4: Three admixture graph models that fit the data for Satsurblia, an Upper Palaeolithic individual from the Caucasus. (127 KB)

    These models use 127,057 SNPs covered in all populations. Estimated genetic drifts are given along the solid lines in units of f2-distance (parts per thousand), and estimated mixture proportions are given along the dotted lines. All three models provide a fit to the allele frequency correlation data among Mbuti, Ust’-Ishim, Kostenki14, Vestonice16, Malta1, ElMiron and Satsurblia to within the limits of our resolution, in the sense that all empirical f2-, f3- and f4-statistics relating the individuals are within three standard errors of the expectation of the model. Models in which Satsurblia is treated as unadmixed cannot be fit.

Extended Data Tables

  1. Extended Data Table 1: The 51 ancient modern humans analysed in this study (327 KB)
  2. Extended Data Table 2: Estimated proportion of Neanderthal ancestry (477 KB)
  3. Extended Data Table 3: Significant correlation of Neanderthal ancestry estimate with specimen age (205 KB)
  4. Extended Data Table 4: Sex determination for newly reported individuals (485 KB)
  5. Extended Data Table 5: Allele counts at SNPs affected by selection in individuals with >1-fold coverage (285 KB)
  6. Extended Data Table 6: All European hunter-gatherers beginning with Kostenki14 share genetic drift with present-day Europeans (623 KB)

Supplementary information

PDF files

  1. Supplementary Information (7.8 MB)

    This file contains Supplementary Text and Data, Supplementary Tables, Supplementary Figures and additional references (see Contents for more details).

Additional data