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Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic European


Ancient genomic sequences have started to reveal the origin and the demographic impact of farmers from the Neolithic period spreading into Europe1,2,3. The adoption of farming, stock breeding and sedentary societies during the Neolithic may have resulted in adaptive changes in genes associated with immunity and diet4. However, the limited data available from earlier hunter-gatherers preclude an understanding of the selective processes associated with this crucial transition to agriculture in recent human evolution. Here we sequence an approximately 7,000-year-old Mesolithic skeleton discovered at the La Braña-Arintero site in León, Spain, to retrieve a complete pre-agricultural European human genome. Analysis of this genome in the context of other ancient samples suggests the existence of a common ancient genomic signature across western and central Eurasia from the Upper Paleolithic to the Mesolithic. The La Braña individual carries ancestral alleles in several skin pigmentation genes, suggesting that the light skin of modern Europeans was not yet ubiquitous in Mesolithic times. Moreover, we provide evidence that a significant number of derived, putatively adaptive variants associated with pathogen resistance in modern Europeans were already present in this hunter-gatherer.

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Figure 1: Geographic location and genetic affinities of the La Braña 1 individual.
Figure 2: Ancestral variants around the SLC45A2 (rs16891982, above) and SLC24A5 (rs1426654, below) pigmentation genes in the Mesolithic genome.

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Accession codes


Sequence Read Archive

Data deposits

Alignment data are available through the Sequence Read Archive (SRA) under accession numbers PRJNA230689 and SRP033596.


  1. Keller, A. et al. New insights into the Tyrolean Iceman’s origin and phenotype as inferred by whole-genome sequencing. Nature Commun. 3, 698 (2012)

    Article  ADS  Google Scholar 

  2. Sánchez-Quinto, F. et al. Genomic affinities of two 7,000-year-old Iberian hunter-gatherers. Curr. Biol. 22, 1494–1499 (2012)

    Article  PubMed  Google Scholar 

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

    Article  CAS  ADS  PubMed  Google Scholar 

  4. Laland, K. N., Odling-Smee, J. & Myles, S. How culture shaped the human genome: bringing genetics and the human sciences together. Nature Rev. Genet. 11, 137–148 (2010)

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  7. Vidal Encinas, J. M. & Prada Marcos, M. E. Los hombres mesolíticos de La Braña-Arintero (Valdelugueros, León) (León: Junta de Castilla y León, 2010)

    Google Scholar 

  8. Overballe-Petersen, S., Orlando, L. & Willerslev, E. Next-generation sequencing offers new insights into DNA degradation. Trends Biotechnol. 30, 364–368 (2012)

    Article  CAS  PubMed  Google Scholar 

  9. Allentoft, M. E. et al. The half-life of DNA in bone: measuring decay kinetics in 158 dated fossils. Proc. R. Soc. B Biol. Sci. 279, 4824–4733 (2012)

    Article  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  11. Nelson, M. R. et al. The population reference sample, POPRES: a resource for population, disease, and pharmacological genetics research. Am. J. Hum. Genet. 83, 347–358 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Novembre, J. et al. Genes mirror geography within Europe. Nature 456, 98–101 (2008)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  13. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012)

  14. Surakka, I. et al. Founder population-specific HapMap panel increases power in GWA studies through improved imputation accuracy and CNV tagging. Genome Res. 20, 1344–1351 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  ADS  PubMed  Google Scholar 

  16. Reich, D., Thangaraj, K., Patterson, N., Price, A. L. & Singh, L. Reconstructing Indian population history. Nature 461, 489–494 (2009)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  18. Perry, G. H. et al. Diet and the evolution of human amylase gene copy number variation. Nature Genet. 39, 1256–1260 (2007)

    Article  CAS  PubMed  Google Scholar 

  19. Grossman, S. R. et al. Identifying recent adaptations in large-scale genomic data. Cell 152, 703–713 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lamason, R. L. et al. SLC24A5, a putative cation exchanger, affects pigmentation in zebrafish and humans. Science 310, 1782–1786 (2005)

    Article  CAS  ADS  PubMed  Google Scholar 

  21. Norton, H. L. et al. Genetic evidence for the convergent evolution of light skin in Europeans and East Asians. Mol. Biol. Evol. 24, 710–722 (2007)

    Article  CAS  PubMed  Google Scholar 

  22. Sturm, R. A. & Duffy, D. L. Human pigmentation genes under environmental selection. Genome Biol. 13, 248 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sturm, R. A. et al. A single SNP in an evolutionary conserved region within intron 86 of the HERC2 gene determines human blue-brown eye color. Am. J. Hum. Genet. 82, 424–431 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Walsh, S. et al. The HIrisPlex system for simultaneous prediction of hair and eye colour from DNA. Forensic Sci. Int. Genet. 7, 98–115 (2013)

    Article  CAS  PubMed  Google Scholar 

  25. Aoshi, T., Koyama, S., Kobiyama, K., Akira, S. & Ishii, K. J. Innate and adaptive immune responses to viral infection and vaccination. Curr. Opin. Virol. 1, 226–232 (2011)

    Article  CAS  PubMed  Google Scholar 

  26. Moresco, E. M. Y., LaVine, D. & Beutler, B. Toll-like receptors. Curr. Biol. 21, R488–R493 (2011)

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Huson, D. H., Mitra, S., Ruscheweyh, H.-J., Weber, N. & Schuster, S. C. Integrative analysis of environmental sequences using MEGAN4. Genome Res. 21, 1552–1560 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Jónsson, H., Ginolhac, A., Schubert, M., Johnson, P. L. F. & Orlando, L. mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters. Bioinformatics 29, 1682–1684 (2013)

    PubMed  PubMed Central  Google Scholar 

  30. 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  PubMed  PubMed Central  Google Scholar 

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The authors thank L. A. Grau Lobo (Museo de León) for access to the La Braña specimen, M. Rasmussen and H. Schroeder for valid input into the experimental work, and M. Raghavan for early access to Mal'ta genome data. Sequencing was performed at the Danish National High-Throughput DNA-Sequencing Centre, University of Copenhagen. The POPRES data were obtained from dbGaP (accession number 2038). The authors are grateful for financial support from the Danish National Research Foundation, ERC Starting Grant (260372) to TM-B, and (310372) to M.G.N., FEDER and Spanish Government Grants BFU2012-38236, the Spanish Multiple Sclerosis Netowrk (REEM) of the Instituto de Salud Carlos III (RD12/0032/0011) to A.N., BFU2011-28549 to T.M.-B., BFU2012-34157 to C.L.-F., ERC (Marie Curie Actions 300554) to M.E.A., NIH NRSA postdoctoral fellowship (F32GM106656) to C.W.K.C., NIH (R01-HG007089) to J.N., NSF postdoctoral fellowship (DBI-1103639) to M.D., the Australian NHMRC to R.A.S. and a predoctoral fellowship from the Basque Government (DEUI) to I.O.

Author information

Authors and Affiliations



C.L.-F. and E.W. conceived and lead the project. M.E.P. and J.M.V.E. provided anthropological and archaeological information. O.R. and M.E.A. performed the ancient extractions and library construction, respectively. I.O., M.E.A., F.S.-Q., J.P.-M., S.R., O.R., M.F.-C. and T.M.-B. performed mapping, SNP calling, mtDNA assembly, contamination estimates and different genomic analyses on the ancient genome. I.O., F.S.-Q., G.S., C.W.K.C., M.D., J.A.R., J.Q., O.R., U.M.M. and A.N. performed functional, ancestry and population genetic analyses. R.N. and J.N. coordinated the ancestry analyses. M.G.N., R.A.S. and P.S. coordinated the immunological, pigmentation and selection analyses, respectively. I.O., M.E.A., T.M.-B., E.W. and C.L.-F. wrote the majority of the manuscript with critical input from R.N., M.G.N., J.N., R.A.S., P.S. and A.N.

Corresponding authors

Correspondence to Eske Willerslev or Carles Lalueza-Fox.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Alignment and coverage statistics of the La Braña 1 genome.

a, Alignment summary of the La Braña 1 sequence data to hg19 assembly. b, Coverage statistics per chromosome. The percentage of the chromosome covered by at least one read is shown, as well as the mean read depth of all positions and positions covered by at least one read. c, Percentage of the genome covered at different minimum read depths.

Extended Data Figure 2 Damage pattern of La Braña 1 sequenced reads.

a, b, Frequencies of C to T (red) and G to A (blue) misincorporations at the 5′ end (left) and 3′ end (right) are shown for the nuclear DNA (nuDNA) (a) and mtDNA (b). c, d, Fragment length distribution of reads mapping to the nuclear genome (c) and mtDNA genome (d). Coefficients of determination (R2) for an exponential decline are provided for the four different data sets. The exponential coefficients for the four data sets correspond to the damage fraction (λ); e is the base of the natural logarithm.

Extended Data Figure 3 Genetic affinities of the La Braña 1 genome.

a, PCA of the La Braña 1 SNP data and the 1000 Genomes Project European individuals. b, PCA of La Braña 1 versus world-wide data genotyped with the Illumina Omni 2.5M array. Continental terms make reference to each Omni population grouping as follows: Africans, Yoruba and Luyha; Asians, Chinese (Beijing, Denver, South, Dai), Japanese and Vietnamese; Europeans, Iberians, Tuscans, British, Finns and CEU; and Indian Gujarati from Texas. c, Each panel shows PC1 and PC2 based on the PCA of one of the ancient samples with the merged POPRES+FINHM sample, before Procrustes transformation. The ancient samples include the La Braña 1 sample and four Neolithic samples from refs 1 and 3.

Extended Data Figure 4 Allele-sharing analysis.

Each panel shows the allele-sharing of a particular Neolithic sample from refs 1 and 3 with La Braña 1 sample. The sample IDs are presented in the upper left of each panel (Ajv52, Ajv70, Ire8, Gok4 and Ötzi). In the upper right of each panel, the Pearson’s correlation coefficient is given with the associated P value.

Extended Data Figure 5 Pairwise outgroup f3 statistics.

a, Sardinian versus Karitiana. b, Sardinian versus Han. c, La Braña 1 versus Mal’ta. d, Sardinian versus Mal’ta. e, La Braña 1 versus Karitiana. The solid line represents y = x.

Extended Data Figure 6 Analysis of heterozygosity.

a, Heterozygosity distributions of La Braña 1 and modern individuals with similar coverage from the 1000 Genomes Project (using 1-Mb windows with 200 kb overlap). CEU, northern- and western-European ancestry. CHB, Han Chinese; FIN, Finns; GBR, Great Britain; IBS, Iberians; JPT, Japanese; LWK, Luhya; TSI, Tuscans; YRI, Yorubans. b, Heterozygosity values in 1-Mb windows (with 200 kb overlap) across each chromosome.

Extended Data Figure 7 Amylase copy-number analysis.

a, Size distribution of diploid control regions. b, AMY1 gene copy number in La Braña 1. CN, copy number; DGV, Database of Genomic Variation. c, La Braña 1 AMY1 gene copy number in the context of low- and high-starch diet populations. d, Classification of low- and high-starch diet individuals based on AMY1 copy number. Using data from ref. 18, individuals were classified as in low-starch (less or equal than) or high-starch (higher than) categories and the fraction of correct predictions was calculated. In addition, we calculated the random expectation and 95% limit of low-starch-diet individuals classified correctly at each threshold value.

Extended Data Figure 8 Neighbouring variants for three diagnostic SNPs related to immunity.

a, rs2745098 (PTX4 gene). b, rs11755393 (UHRF1BP1 gene). c, rs10421769 (GPATCH1 gene). For PTX4, UHRF1BP1 and GPATCH1, La Braña 1 displays the derived allele and the European-specific haplotype, indicating that the positive-selection event was already present in the Mesolithic. Blue, ancestral; red, derived.

Extended Data Figure 9 Metagenomic analysis of the non-human reads.

a, Domain attribution of the reads that did not map to hg19. b, Proportion of different Bacteria groups. c, Proportion of different types of Proteobacteria. d, Microbial attributes of the microbes present in the La Braña 1 sample.

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

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