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

Accession codes

Accessions

Sequence Read Archive

Data deposits

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

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Acknowledgements

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

Author notes

  1. Iñigo Olalde and Morten E. Allentoft: These authors contributed equally to this work.

Authors and Affiliations

  1. Institut de Biologia Evolutiva, CSIC-UPF, Barcelona 08003, Spain,
    Iñigo Olalde, Federico Sánchez-Quinto, Gabriel Santpere, Javier Prado-Martinez, Juan Antonio Rodríguez, Javier Quilez, Oscar Ramírez, Urko M. Marigorta, Marcos Fernández-Callejo, Tomàs Marquès-Bonet, Arcadi Navarro & Carles Lalueza-Fox
  2. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen K, Denmark,
    Morten E. Allentoft & Eske Willerslev
  3. Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 90095, California, USA
    Charleston W. K. Chiang
  4. Department of Integrative Biology, University of California, Berkeley, 94720, California, USA
    Michael DeGiorgio
  5. Department of Biology, Pennsylvania State University, 502 Wartik Laboratory, University Park, 16802, Pennsylvania, USA
    Michael DeGiorgio
  6. Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark,
    Simon Rasmussen
  7. I.E.S.O. 'Los Salados', Junta de Castilla y León, E-49600 Benavente, Spain,
    María Encina Prada
  8. Junta de Castilla y León, Servicio de Cultura de León, E-24071 León, Spain,
    Julio Manuel Vidal Encinas
  9. Center for Theoretical Evolutionary Genomics, University of California, Berkeley, 94720, California, USA
    Rasmus Nielsen
  10. Department of Medicine and Nijmegen Institute for Infection, Inflammation and Immunity, Radboud University Nijmegen Medical Centre, 6500 Nijmegen, The Netherlands,
    Mihai G. Netea
  11. Department of Human Genetics, University of Chicago, 60637, Illinois, USA
    John Novembre
  12. Institute for Molecular Bioscience, Melanogenix Group, The University of Queensland, Brisbane, 4072, Queensland, Australia
    Richard A. Sturm
  13. Department of Organismic and Evolutionary Biology, Center for Systems Biology, Harvard University, Cambridge, 02138, Massachusetts, USA
    Pardis Sabeti
  14. Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, 02142, Massachusetts, USA
    Pardis Sabeti
  15. Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Catalonia, Spain,
    Tomàs Marquès-Bonet & Arcadi Navarro
  16. Centre de Regulació Genòmica (CRG), Barcelona 08003, Catalonia, Spain,
    Arcadi Navarro
  17. National Institute for Bioinformatics (INB), Barcelona 08003, Catalonia, Spain,
    Arcadi Navarro

Authors

  1. Iñigo Olalde
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  2. Morten E. Allentoft
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  3. Federico Sánchez-Quinto
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  4. Gabriel Santpere
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  5. Charleston W. K. Chiang
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  6. Michael DeGiorgio
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  7. Javier Prado-Martinez
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  8. Juan Antonio Rodríguez
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  9. Simon Rasmussen
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  10. Javier Quilez
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  11. Oscar Ramírez
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  12. Urko M. Marigorta
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  13. Marcos Fernández-Callejo
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  14. María Encina Prada
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  15. Julio Manuel Vidal Encinas
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  16. Rasmus Nielsen
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  17. Mihai G. Netea
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  18. John Novembre
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  19. Richard A. Sturm
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  20. Pardis Sabeti
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  21. Tomàs Marquès-Bonet
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  22. Arcadi Navarro
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  23. Eske Willerslev
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  24. Carles Lalueza-Fox
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Contributions

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 toEske 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 (_R_2) 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 _f_3 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.

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). https://doi.org/10.1038/nature12960

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