Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Ancient gene flow from early modern humans into Eastern Neanderthals

Abstract

It has been shown that Neanderthals contributed genetically to modern humans outside Africa 47,000–65,000 years ago. Here we analyse the genomes of a Neanderthal and a Denisovan from the Altai Mountains in Siberia together with the sequences of chromosome 21 of two Neanderthals from Spain and Croatia. We find that a population that diverged early from other modern humans in Africa contributed genetically to the ancestors of Neanderthals from the Altai Mountains roughly 100,000 years ago. By contrast, we do not detect such a genetic contribution in the Denisovan or the two European Neanderthals. We conclude that in addition to later interbreeding events, the ancestors of Neanderthals from the Altai Mountains and early modern humans met and interbred, possibly in the Near East, many thousands of years earlier than previously thought.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Divergence and heterozygosity in the Altai Neanderthal and Denisovan genomes.
Figure 2: Distinguishing between two scenarios of introgression into archaic humans.
Figure 3: Refined demography of archaic and modern humans.
Figure 4: Homozygous segments on chromosome 21.

Similar content being viewed by others

Accession codes

Primary accessions

European Nucleotide Archive

Data deposits

Sequence data are available in the European Nucleotide Archive (ENA) under accession number PRJEB11828.

References

  1. Arsuaga, J. L. et al. Neandertal roots: Cranial and chronological evidence from Sima de los Huesos. Science 344, 1358–1363 (2014)

    Article  ADS  CAS  Google Scholar 

  2. Prüfer, K. et al. The complete genome sequence of a Neanderthal from the Altai Mountains. Nature 505, 43–49 (2014)

    Article  ADS  Google Scholar 

  3. Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010)

    Article  ADS  CAS  Google Scholar 

  4. 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  Google Scholar 

  5. Fu, Q. et al. An early modern human from Romania with a recent Neanderthal ancestor. Nature (2015)

  6. Reich, D. et al. Genetic history of an archaic hominin group from Denisova Cave in Siberia. Nature 468, 1053–1060 (2010)

    Article  ADS  CAS  Google Scholar 

  7. Meyer, M. et al. A high-coverage genome sequence from an archaic Denisovan individual. Science 338, 222–226 (2012)

    Article  ADS  CAS  Google Scholar 

  8. The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015)

  9. Pickrell, J. K. et al. Ancient west Eurasian ancestry in southern and eastern Africa. Proc. Natl Acad. Sci. USA 111, 2632–2637 (2014)

    Article  ADS  CAS  Google Scholar 

  10. Llorente, M. G. et al. Ancient Ethiopian genome reveals extensive Eurasian admixture throughout the African continent. Science 350, 820–822 (2015)

    Article  ADS  CAS  Google Scholar 

  11. Gronau, I., Hubisz, M. J., Gulko, B., Danko, C. G. & Siepel, A. Bayesian inference of ancient human demography from individual genome sequences. Nature Genet. 43, 1031–1034 (2011)

    Article  CAS  Google Scholar 

  12. Sankararaman, S., Patterson, N., Li, H., Paabo, S. & Reich, D. The date of interbreeding between Neandertals and modern humans. PLoS Genet. 8, e1002947 (2012)

    Article  CAS  Google Scholar 

  13. Rasmussen, M. D., Hubisz, M. J., Gronau, I. & Siepel, A. Genome-wide inference of ancestral recombination graphs. PLoS Genet. 10, e1004342 (2014)

    Article  Google Scholar 

  14. Burbano, H. A. et al. Targeted investigation of the Neandertal genome by array-based sequence capture. Science 328, 723–725 (2010)

    Article  ADS  CAS  Google Scholar 

  15. 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  Google Scholar 

  16. Rausa, F. M., Galarneau, L., Bélanger, L. & Costa, R. H. The nuclear receptor fetoprotein transcription factor is coexpressed with its target gene HNF-3β in the developing murine liver intestine and pancreas. Mech. Dev. 89, 185–188 (1999)

    Article  CAS  Google Scholar 

  17. Enard, W. FOXP2 and the role of cortico-basal ganglia circuits in speech and language evolution. Curr. Opin. Neurobiol. 21, 415–424 (2011)

    Article  CAS  Google Scholar 

  18. McVicker, G., Gordon, D., Davis, C. & Green, P. Widespread genomic signatures of natural selection in hominid evolution. PLoS Genet. 5, e1000471 (2009)

    Article  Google Scholar 

  19. Veeramah, K. R., Gutenkunst, R. N., Woerner, A. E., Watkins, J. C. & Hammer, M. F. Evidence for increased levels of positive and negative selection on the X chromosome versus autosomes in humans. Mol. Biol. Evol. 31, 2267–2282 (2014)

    Article  CAS  Google Scholar 

  20. Sankararaman, S. et al. The genomic landscape of Neanderthal ancestry in present-day humans. Nature 507, 354–357 (2014)

    Article  ADS  CAS  Google Scholar 

  21. Pemberton, T. J. et al. Genomic patterns of homozygosity in worldwide human populations. Am. J. Hum. Genet. 91, 275–292 (2012)

    Article  CAS  Google Scholar 

  22. Siepel, A. et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15, 1034–1050 (2005)

    Article  CAS  Google Scholar 

  23. Castellano, S. et al. Patterns of coding variation in the complete exomes of three Neandertals. Proc. Natl Acad. Sciences USA 111, 6666–6671 (2014)

    Article  ADS  CAS  Google Scholar 

  24. Hublin, J. J. in Neandertals and Modern Humans in Western Asia (eds Akazawa, T., Aoki, K. & Bar-Yosef, O. ) (Kluwer Academic Publishers, 1998)

  25. Mercier, N. H. V., Bar-Yosef, O., Vandermeersch B., Stringer, C. & Joron, J.-L. Thermoluminescence date for the Mousterian burial site of Es-Skhul, Mt. Carmel. J. Archaeol. Sci. 20, 169–174 (1993)

    Article  Google Scholar 

  26. Grün, R. et al. U-series and ESR analyses of bones and teeth relating to the human burials from Skhul. J. Hum. Evol. 49, 316–334 (2005)

    Article  Google Scholar 

  27. Armitage, S. J. et al. The southern route “Out of Africa”: evidence for an early expansion of modern humans into Arabia. Science 331, 453–456 (2011)

    Article  ADS  CAS  Google Scholar 

  28. Rose, J. I. A. & Marks, A. E. “Out of Arabia” and the Middle–Upper Palaeolithic transition in the southern Levant. Quartär 61, 49–85 (2014)

  29. Liu, W. et al. The earliest unequivocally modern humans in southern China. Nature 526, 696–699 (2015)

    Article  ADS  CAS  Google Scholar 

  30. Rohland, N. & Hofreiter, M. Comparison and optimization of ancient DNA extraction. Biotechniques 42, 343–352 (2007)

    Article  CAS  Google Scholar 

  31. Meyer, M. & Kircher, M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protocols 2010, http://dx.doi.org/10.1101/pdb.prot5448 (2010)

  32. Kircher, M., Sawyer, S. & Meyer, M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 40, e3 (2012)

    Article  CAS  Google Scholar 

  33. Briggs, A. W. et al. Removal of deaminated cytosines and detection of in vivo methylation in ancient DNA. Nucleic Acids Res. 38, e87 (2010)

    Article  Google Scholar 

  34. Gnirke, A. et al. Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nature Biotechnol. 27, 182–189 (2009)

    Article  CAS  Google Scholar 

  35. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010)

    Article  CAS  Google Scholar 

  36. Paten, B., Herrero, J., Beal, K., Fitzgerald, S. & Birney, E. Enredo and Pecan: genome-wide mammalian consistency-based multiple alignment with paralogs. Genome Res. 18, 1814–1828 (2008)

    Article  CAS  Google Scholar 

  37. Hudson, R. R. Generating samples under a Wright–Fisher neutral model of genetic variation. Bioinformatics 18, 337–338 (2002)

    Article  CAS  Google Scholar 

  38. Roach, J. C. et al. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 328, 636–639 (2010)

    Article  ADS  CAS  Google Scholar 

  39. Fenner, J. N. Cross-cultural estimation of the human generation interval for use in genetics-based population divergence studies. Am. J. Phys. Anthropol. 128, 415–423 (2005)

    Article  Google Scholar 

  40. Freedman, A. H. et al. Genome sequencing highlights the dynamic early history of dogs. PLoS Genet. 10, e1004016 (2014)

    Article  Google Scholar 

  41. Gravel, S. et al. Demographic history and rare allele sharing among human populations. Proc. Natl Acad. Sci. USA 108, 11983–11988 (2011)

    Article  ADS  CAS  Google Scholar 

  42. Prado-Martinez, J. et al. Great ape genetic diversity and population history. Nature 499, 471–475 (2013)

    Article  ADS  CAS  Google Scholar 

  43. Durinck, S. et al. BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics 21, 3439–3440 (2005)

    Article  CAS  Google Scholar 

  44. Arbiza, L. et al. Genome-wide inference of natural selection on human transcription factor binding sites. Nature Genet. 45, 723–729 (2013)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank M. Slatkin, F. Racimo, J. Kelso, K. Prüfer, M. Stoneking and D. Reich for comments; the MPI-EVA sequencing group, B. Nickel and R. Schultz for technical support; A. Heinze, S. Sawyer and J. Dabney for sequencing library preparation; U. Stenzel and G. Renaud for help with sequence processing. M.J.H. was supported by the National Science Foundation Graduate Research Fellowship under grant DGE-1144153. Q.F. was funded in part by the Special Foundation of the President of the Chinese Academy of Sciences. T.M-B. was supported by ICREA, EMBO YIP 2013 and Fundació Barcelona Zoo. The Max Planck Society, the Krekeler Foundation, MINECO (grants BFU2014-55090-P FEDER, BFU2015-7116-ERC and BFU2015-6215-ERC to T.M-B. and BFU2012-34157 FEDER to C.L.-F.) and the US National Institutes of Health (grant GM102192 to A.S. and U01 MH106874 to T.M-B.) provided financial support.

Author information

Authors and Affiliations

Authors

Contributions

M.M. and Q.F. performed experiments; M.Ku., I.Gr., M.J.H., C.d.F., J.P.-M., M.Ki, Q.F., H.A.B., T.M.-B., A.M.A., S.P., M.M., A.S. and S.C. analysed genetic data; C.L.-F., M.d.l.R., A.R., P.R., D.B., Ž.,K., I.Gu. and B.V. analysed anthropological data; M.Ku., I.Gr., M.J.H., B.V., S.P., A.S. and S.C. wrote the manuscript.

Corresponding authors

Correspondence to Adam Siepel or Sergi Castellano.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Migration rates in preliminary demographic inference.

Total migration rates estimated for 22 directional migration bands in five separate preliminary G-PhoCS runs. Rows correspond to source populations and columns to the target populations. The 20 migration bands between modern and archaic populations were considered in five separate runs, each containing the four bands associated with a different modern human population (Supplementary Fig. 15A). The two migration bands between the Denisovan and the Altai Neanderthal populations were considered in all five runs, and the values shown here correspond to an aggregate of all five runs. The estimates are as shown in Supplementary Fig. 15B. Shade indicates the posterior mean total migration rate (legend), which approximates the probability that a lineage in the target population originated in the source population. The 95% Bayesian credible intervals from 2,000 MCMC replicates are indicated for migration bands whose upper credible interval bound is above 0.3%. We identified four clusters of migration bands, corresponding to what were likely at least four different cases of introgression between populations: (1) Neanderthals into non-African modern humans (red box), (2) Denisovans into Oceanians (green box), (3) between Neanderthals and Denisovans (magenta), and (4) modern humans into Neanderthals (blue box). Alt, Altai Neanderthal; Chi, Chinese; Den, Denisovan; Fre, French; Pap, Papuan; Yor, Yoruba.

Extended Data Figure 2 Demographic inference on simulated data.

Simulated data were generated under the demographic model as inferred by G-PhoCS (Supplementary Table 13). Each simulated data set consisted of 10,000 loci of 1 kb length. We simulated the Altai Neanderthal, the Denisovan, and three modern human populations corresponding to the San, Yoruba, and French, with modern human demography consistent with recent studies (Supplementary information section 8). Three migration bands were simulated: (1) from the Altai Neanderthal to the Denisovan, (2) from a population that diverged from the ancestors of all present-day humans 300,000 years ago into the Altai Neanderthal, and (3) from a population that diverged from the ancestors of all modern and archaic humans roughly 2.6 million years ago into the Denisovan. a, Estimates of effective population sizes (theta, θ), population divergence times (tau, τ) and migration rates (m) from three G-PhoCS runs on data simulated with gene flow from modern humans into the Altai Neanderthal lineage. Each run analyses an individual from a different present-day population, using the exact same setup used in our main analysis (Supplementary Fig. 15A). Parameters are typically estimated accurately, with 95% Bayesian credible intervals containing the values used in simulations (horizontal red lines). Rates of archaic gene flow into Denisovan appear to be somewhat overestimated, and differences between analyses of African and non-African populations are consistent with those observed in the data analysis (Supplementary Fig. 15B). b, Similar analysis done on data simulated without gene flow from modern humans into the Altai Neanderthal lineage. Accurate estimates are obtained for all model parameters, and no gene flow is inferred from modern humans into the ancestors of the Altai Neanderthal. Error bars represent the 95% Bayesian credible intervals from 2,000 MCMC replicates.

Extended Data Figure 3 Simulation of different source populations for modern introgression into Neanderthals.

Estimated rates of migration from the modern human population to the Altai Neanderthal population obtained from 15 G-PhoCS runs on five simulated data sets. All demographic parameters are set according to the values inferred by G-PhoCS in our data analysis (Supplementary Table 13), and the five data sets differ by the source population for migration: no migration (none), population ancestral to all present-day humans (ancestral), population ancestral to Yoruba and Europeans (Yoruba), San population (San), and European population (European). The first two sets are the ones analysed in Extended Data Fig. 2. Each data set is analysed three times, using different present-day samples: European (French), Yoruba, or San. Significant differences in estimates are observed between the data sets with and without gene flow and the data set with gene flow from a source population related to Europeans. Only minor differences were observed between values inferred for the three data sets with source population diverging from African populations (San, Yoruba, and ancestral). We conclude from this that the source population likely diverged from an African human population before the divergence of present-day Eurasians. The shaded circle in Fig. 3a represents this conclusion. Error bars represent the 95% Bayesian credible intervals from 2,000 MCMC replicates.

Extended Data Figure 4 Simulation of present-day human contamination.

Simulated windows of 100 kb for the Altai Neanderthal and Denisovan genomes with present-day human contamination of 5% at the genotype level. Windows are binned by their minimum divergence to Africans using derived alleles at >0.9 frequency in the simulated African population. The x and y axis as in Fig. 1. a, Gene flow from a deeply divergent archaic hominin into the Denisovan lineage (1%) and Altai Neanderthal gene flow into the Denisovan lineage (0.65%). b, Gene flow from a deeply divergent archaic hominin into the Denisovan lineage, Altai Neanderthal gene flow into the Denisovan lineage and modern human gene flow into the Altai Neanderthal lineage (1.8%). Error bars represent the 95% confidence intervals from 1,000 bootstrap replicates.

Extended Data Figure 5 Haplotype ages inferred by ARGweaver on simulated data.

a, Distribution of ‘African’ haplotype ages in sequences simulated with introgression into the Altai Neanderthal lineage from modern humans 100,000 years ago. ‘African’ haplotypes are identified as in Fig. 2. Error bars represent the 95% Bayesian credible intervals from 302 MCMC replicates. b, Distribution of true haplotype ages for each of the estimated ages. The horizontal dotted lines show the estimated age. The plot is divided into four quadrants; the lower half represents ‘African’ haplotypes having true ages between 100,000 and 620,000 years ago (the divergence time between archaic and present-day humans), which are necessarily due to post-divergence gene flow from modern humans. The left side of the plot represents regions that would be identified as introgressed based on a threshold of ≤ 234,000 years. The counts in each quadrant are for Altai Neanderthal (red) and Denisovan (blue), respectively. The counts for the Denisovan in the lower two quadrants are zero because there was no simulated migration from modern humans into the Denisovan lineage. Note that this is a somewhat nonstandard plot of true age versus estimated age; a more standard, reversed view is given in Supplementary Fig. 33 and demonstrates that the estimated ages are largely unbiased. Error bars as in the standard Tukey box plot (R boxplot function).

Extended Data Figure 6 Main G-PhoCS demographic inference.

Summary of the main demographic inference using G-PhoCS in a model with four archaic populations and one modern human population. a, The population phylogeny assumed in each of the G-PhoCS runs. Labels on internal edges indicate names of the four ancestral populations: population ancestral to the two Western Neanderthals (W.NEA), population ancestral to all three Neanderthals (NEA), population ancestral to all four archaic individuals (ARC), and population ancestral to all human samples (HUM). We augmented the phylogeny with 14 directional migration bands (arrows) between all pairs of sampled populations except for the pairs of Neanderthal populations. In one of the runs we added an unknown ‘ghost’ population and a migration band from that population into the Denisovan population. b, Parameter estimates obtained by G-PhoCS in six separate runs analysing 13,754 neutral and loosely linked loci, substituting samples in the ‘Modern’ population with pairs of present-day humans from five different modern populations (Supplementary Table 11). The last run has gene flow from the ‘ghost’ population and uses two Yoruba individuals in the modern human population. Bar heights indicate posterior mean and error bars correspond to 95% Bayesian credible intervals. Estimates of divergence times (τ) and effective population sizes (θ) are given in raw form, scaled by number of mutations per 10 kb (left axis), and calibrated to absolute units, 1,000 years for time, and 1,000 individuals for effective population size, (right axis) assuming an average mutation rate of 0.5 × 10−9 mutations per year per bp and an average generation time of 29 years. For each of the 14 migration bands, we are showing the estimated total migration rates (m). See Supplementary Information section 8 for more information on parameter calibration and setup for G-PhoCS. A graphical summary of these estimates is given in Fig. 3.

Extended Data Figure 7 Migration rates in main demographic inference.

Total migration rates estimated for 46 directional migration bands in five separate G-PhoCS runs. Rows correspond to source populations and columns to the target populations. The 40 migration bands between modern (present-day) and archaic populations were considered in five separate runs, each containing the eight bands associated with a different modern human population (Extended Data Fig. 6a). The six migration bands between the Denisovan population and the three Neanderthal populations were considered in all six runs, and the values shown here were estimated as an aggregate of all five runs. The estimates are as shown in Extended Data Fig. 6. Shade indicates the posterior mean total migration rate (legend), which approximates the probability that a lineage in the target population originated in the source population. The 95% Bayesian credible intervals from 2,000 MCMC replicates are indicated for migration bands whose upper credible interval bound is above 0.3%. We identified four clusters of migration bands, corresponding to what were likely at least four different cases of introgression between populations: (1) Western (European) Neanderthals into non-African modern humans (red box), (2) Denisovans into East Asian and Oceanians (green box), (3) Neanderthals into Denisovans (magenta), and (4) modern humans into Eastern Neanderthals (blue box). Directed arrows in Fig. 3a depict these introgression events. Sid, El Sidrón Neanderthal; Vin, Vindija Neanderthal.

Extended Data Figure 8 Principal component analysis.

The putatively introgressed segments in the Altai Neanderthal genome, defined by derived alleles in two individuals from the San, Yoruba, Mbuti, Dinka or Mandenka populations. The introgressed segments show no clear affinity to one present-day African population. A, Altai Neanderthal; S, San; M, Mbuti; Y, Yoruba; D, Dinka; N, Mandenka.

Extended Data Figure 9 Natural selection in chromosome 21.

Ratio of functional (putatively deleterious) to neutral polymorphism in archaic and present-day humans (Supplementary Information section 7). TFBS, transcription factor binding sites; upstream refers to 5 kb before the transcription start site of genes; UTRs, untranslated regions (in the mRNA). PhastCons ≥ 0.9 for a site to be used. Ne, Neanderthals; Af, Africans; As, Asians; Am, Americans.

Extended Data Table 1 Shared derived alleles

Related audio

Supplementary information

Supplementary Information

This file contains Supplementary Text 1-11, Supplementary Tables 1-19, Supplementary Figures 1-34 and additional references (see Contents). (PDF 10378 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kuhlwilm, M., Gronau, I., Hubisz, M. et al. Ancient gene flow from early modern humans into Eastern Neanderthals. Nature 530, 429–433 (2016). https://doi.org/10.1038/nature16544

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature16544

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing