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.

  • Article
  • Published:

Pervasive introgression facilitated domestication and adaptation in the Bos species complex

Abstract

Species of the Bos genus, including taurine cattle, zebu, gayal, gaur, banteng, yak, wisent and bison, have been domesticated at least four times and have been an important source of meat, milk and power for many human cultures. We sequence the genomes of gayal, gaur, banteng, wisent and bison, and provide population genomic sequencing of an additional 98 individuals. We use these data to determine the phylogeny and evolutionary history of these species and show that the threatened gayal is an independent species or subspecies. We show that there has been pronounced introgression among different members of this genus, and that it in many cases has involved genes of considerable adaptive importance. For example, genes under domestication selection in cattle (for example, MITF) were introgressed from domestic cattle to yak. Also, genes in the response-to-hypoxia pathway (for example, EGLN1, EGLN2 and HIF3a) have been introgressed from yak to Tibetan cattle, probably facilitating their adaptation to high altitude. We also validate that there is an association between the introgressed EGLN1 allele and haemoglobin and red blood cell concentration. Our results illustrate the importance of introgression as a source of adaptive variation and during domestication, and suggest that the Bos genus evolves as a complex of genetically interconnected species with shared evolutionary trajectories.

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

Access options

Buy this article

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

Fig. 1: Phylogenetic tree and genetic introgression of species in the Bos genus.
Fig. 2: Distribution of regions in the genome where introgression occurred between Tibetan cattle and yak.
Fig. 3: Genetic introgression of EGLN1 from yak to Tibetan cattle.

Similar content being viewed by others

References

  1. Soubrier, J. et al. Early cave art and ancient DNA record the origin of European bison. Nat. Commun. 7, 13158 (2014).

    Google Scholar 

  2. Gautier, M. et al. Deciphering the wisent demographic and adaptive histories from individual whole-genome sequences. Mol. Biol. Evol. 33, 2801–2814 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Wang, K. et al. The genome sequence of the wisent (Bison bonasus). GigaScience 6, 1–5 (2017).

    PubMed  PubMed Central  Google Scholar 

  4. Qiu, Q. et al. Yak whole-genome resequencing reveals domestication signatures and prehistoric population expansions. Nat. Commun. 6, 10283 (2015).

    CAS  PubMed  Google Scholar 

  5. Medugorac, I. et al. Whole-genome analysis of introgressive hybridization and characterization of the bovine legacy of Mongolian yaks. Nat. Genet. 49, 470–475 (2017).

    CAS  PubMed  Google Scholar 

  6. Daetwyler, H. D. et al. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle. Nat. Genet. 46, 858–865 (2014).

    CAS  PubMed  Google Scholar 

  7. Qiu, Q. et al. The yak genome and adaptation to life at high altitude. Nat. Genet. 44, 946–949 (2012).

    CAS  PubMed  Google Scholar 

  8. Newman, J. H. et al. Increased prevalence of EPAS1 variant in cattle with high-altitude pulmonary hypertension. Nat. Commun. 6, 6863 (2015).

    CAS  PubMed  Google Scholar 

  9. Decker, J. E. et al. Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics. Proc. Natl Acad. Sci. USA 106, 18644–18649 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Hassanin, A., An, J., Ropiquet, A., Nguyen, T. T. & Couloux, A. Combining multiple autosomal introns for studying shallow phylogeny and taxonomy of Laurasiatherian mammals: application to the tribe Bovini (Cetartiodactyla, Bovidae). Mol. Phylogenet. Evol. 66, 766–775 (2013).

    PubMed  Google Scholar 

  11. Buntjer, J. B., Otsen, M., Nijman, I. J., Kuiper, M. T. R. & Lenstra, J. A. Phylogeny of bovine species based on AFLP fingerprinting. Heredity 88, 46–51 (2002).

    CAS  PubMed  Google Scholar 

  12. Ma, G. et al. Phylogenetic relationships and status quo of colonies for gayal based on analysis of cytochrome b gene partial sequences. J. Genet. Genom. 34, 413–419 (2007).

    CAS  Google Scholar 

  13. Baig, M. et al. Mitochondrial DNA diversity and origin of Bos frontalis. Curr. Sci. 104, 115–120 (2013).

    CAS  Google Scholar 

  14. Gou, X., Wang, Y., Yang, S., Deng, W. & Mao, H. Genetic diversity and origin of gayal and cattle in Yunnan revealed by mtDNA control region and SRY gene sequence variation. J. Anim. Breed. Genet. 127, 154–160 (2010).

    CAS  PubMed  Google Scholar 

  15. Mei, C. et al. Whole-genome sequencing of the endangered bovine species gayal (Bos frontalis) provides new insights into its genetic features. Sci. Rep. 6, 19787 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Nielsen, R. et al. Tracing the peopling of the world through genomics. Nature 541, 302–310 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Mirarab, S. et al. ASTRAL: genome-scale coalescent-based species tree estimation. Bioinformatics 30, i541–i548 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Liu, L., Yu, L. & Edwards, S. V. A maximum pseudo-likelihood approach for estimating species trees under the coalescent model. BMC Evol. Biol. 10, 302 (2010).

    PubMed  PubMed Central  Google Scholar 

  21. Verkaar, E. L. C., Nijman, I. J., Beeke, M., Hanekamp, E. & Lenstra, J. A. Maternal and paternal lineages in cross-breeding bovine species. Has wisent a hybrid origin?. Mol. Biol. Evol 21, 1165–1170 (2004).

    CAS  PubMed  Google Scholar 

  22. Hobolth, A., Christensen, O. F., Mailund, T. & Schierup, M. H. Genomic relationships and speciation times of human, chimpanzee, and gorilla inferred from a coalescent hidden Markov model. PLoS Genet. 3, e7 (2007).

    PubMed  PubMed Central  Google Scholar 

  23. Hedges, S. B., Marin, J., Suleski, M., Paymer, M. & Kumar, S. Tree of life reveals clock-like speciation and diversification. Mol. Biol. Evol. 32, 835–845 (2014).

    Google Scholar 

  24. Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Wecek, K. et al. Complex admixture preceded and followed the extinction of wisent in the wild. Mol. Biol. Evol. 34, 598–612 (2017).

    CAS  PubMed  Google Scholar 

  26. Durand, E. Y., Patterson, N., Reich, D. & Slatkin, M. Testing for ancient admixture between closely related populations. Mol. Biol. Evol. 28, 2239–2252 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Bosse, M. et al. Genomic analysis reveals selection for Asian genes in European pigs following human-mediated introgression. Nat. Commun. 5, 4392 (2014).

    CAS  PubMed  Google Scholar 

  29. Hofer, E., Sobanov, Y., Brostjan, C., Lehrach, H. & Düchler, M. The centromeric part of the human natural killer (NK) receptor complex: lectin-like receptor genes expressed in NK, dendritic and endothelial cells. Immunol. Rev. 181, 5–19 (2001).

    CAS  PubMed  Google Scholar 

  30. Kao, H.-T. et al. A third member of the synapsin gene family. Proc. Natl Acad. Sci. USA 95, 4667–4672 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Porton, B. et al. Mice lacking synapsin III show abnormalities in explicit memory and conditioned fear. Genes Brain Behav. 9, 257–268 (2009).

    PubMed  PubMed Central  Google Scholar 

  32. Per, J. Behavior genetics and the domestication of animals. Annu. Rev. Anim. Biosci. 2, 85–104 (2014).

    Google Scholar 

  33. Driscoll, C. A., Macdonald, D. W. & O’Brien, S. J. From wild animals to domestic pets, an evolutionary view of domestication. Proc. Natl Acad. Sci. USA 106, 9971–9978 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Suzuki, G. et al. Sept5 deficiency exerts pleiotropic influence on affective behaviors and cognitive functions in mice. Hum. Mol. Genet. 18, 1652–1660 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Carneiro, M. et al. The genomic architecture of population divergence between subspecies of the European rabbit. PLoS Genet. 10, e1003519 (2014).

    PubMed  PubMed Central  Google Scholar 

  36. Li, Y. et al. Artificial selection on brain-expressed genes during the domestication of dog. Mol. Biol. Evol. 30, 1867–1876 (2013).

    CAS  PubMed  Google Scholar 

  37. Wang, G.-d. et al. The genomics of selection in dogs and the parallel evolution between dogs and humans. Nat. Commun. 4, 1860 (2013).

    PubMed  Google Scholar 

  38. The-Bovine-HapMap-Consortium Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science 324, 528–532 (2009).

    PubMed Central  Google Scholar 

  39. Maples, B. K., Gravel, S., Kenny, E. E. & Bustamante, C. D. RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference. Am. J. Hum. Genet. 93, 278–288 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Huerta-Sánchez, E. et al. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature 512, 194–197 (2014).

    PubMed  PubMed Central  Google Scholar 

  41. Lorenzo, F. R. et al. A genetic mechanism for Tibetan high-altitude adaptation. Nat. Genet. 46, 951–956 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Bigham, A. W. & Lee, F. S. Human high-altitude adaptation: forward genetics meets the HIF pathway. Genes Dev. 28, 2189–2204 (2014).

    PubMed  PubMed Central  Google Scholar 

  43. Storz, J. F., Scott, G. R. & Cheviron, Z. A. Phenotypic plasticity and genetic adaptation to high-altitude hypoxia in vertebrates. J. Exp. Biol. 213, 4125–4136 (2010).

    PubMed  PubMed Central  Google Scholar 

  44. Chen, F. H. et al. Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 B.P. Science 347, 248–250 (2015).

    CAS  PubMed  Google Scholar 

  45. Miao, B., Wang, Z. & Li, Y. Genomic analysis reveals hypoxia adaptation in the Tibetan mastiff by introgression of the gray wolf from the Tibetan Plateau. Mol. Biol. Evol. 34, 734–743 (2017).

    CAS  PubMed  Google Scholar 

  46. Hsiao, J. J. & Fisher, D. E. The roles of microphthalmia transcription factor and pigmentation in melanoma. Arch. Biochem. Biophys. 563, 28–34 (2015).

    Google Scholar 

  47. Kim, J. et al. The genome landscape of indigenous African cattle. Genome Biol. 18, 34 (2017).

    PubMed  PubMed Central  Google Scholar 

  48. Qanbari, S. et al. Classic selective sweeps revealed by massive sequencing in cattle. PLoS Genet. 10, e1004148 (2012).

    Google Scholar 

  49. Hayes, B. J., Pryce, J., Chamberlain, A. J., Bowman, P. J. & Goddard, M. E. Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits. PLoS Genet. 6, e1001139 (2010).

    PubMed  PubMed Central  Google Scholar 

  50. Kong, Y. Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics 98, 152–153 (2011).

    CAS  PubMed  Google Scholar 

  51. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).

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

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Popescu, A.-A., Huber, K. T. & Paradis, E. ape 3.0: new tools for distance-based phylogenetics and evolutionary analysis in R. Bioinformatics 28, 1536–1537 (2012).

    CAS  PubMed  Google Scholar 

  54. Mailund, T. et al. A new isolation with migration model along complete genomes infers very different divergence processes among closely related great ape species. PLoS Genet. 8, e1003125 (2012).

    PubMed  PubMed Central  Google Scholar 

  55. Mailund, T., Dutheil, J. Y., Hobolth, A., Lunter, G. & Schierup, M. H. Estimating divergence time and ancestral effective population size of Bornean and Sumatran orangutan subspecies using a coalescent hidden Markov model. PLoS Genet. 7, e1001319 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Kumar, S. & Subramanian, S. Mutation rates in mammalian genomes. Proc. Natl Acad. Sci. USA 99, 803–808 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Browning, B. L. & Browning, S. R. Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194, 459–471 (2013).

    PubMed  PubMed Central  Google Scholar 

  58. Maples, B. K., Gravel, S., Kenny, E. E. & Bustamante, C. D. RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference. Am. J. Hum. Genet. 93, 278–288 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Tamura, K., Stecher, G., Peterson, D., Filipski, A. & Kumar, S. MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0. Mol. Biol. Evol. 30, 2725–2729 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Reimand, J. et al. g:Profiler—a web server for functional interpretation of gene lists (2016 update). Nucleic Acids Res. 44, W83–W89 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2008).

    Google Scholar 

  63. Eden, E., Navon, R., Steinfeld, I., Lipson, D. & Yakhini, Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10, 48 (2009).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No XDB13020600), National Natural Science Foundation of China (91731304, 31321002, 31272418, 31561143010), the Chinese 973 program (2013CB835204), Animal Branch of the Germplasm Bank of Wild Species (GBOWS) and the Program for Changjiang Scholar and Innovation Research Team in University (IRT_15R621). D.-D.W. was supported by the Youth Innovation Promotion Association, Chinese Academy of Sciences.

Author information

Authors and Affiliations

Authors

Contributions

Y.-P.Z., D.-D.W., R.N. and Q.Z. lead the project, and designed and conceived the study. D.-D.W., S.W., X.-D.D. and R.N. prepared the manuscript. D.-D.W., S.W., X.-D.D., Y. Z., Y.L. and M.-S.W. performed the data analysis. J.M.W., M.T. and O.F. performed some sampling and experiments. All authors read the manuscript.

Corresponding authors

Correspondence to Dong-Dong Wu, Rasmus Nielsen, Qin Zhang or Ya-Ping Zhang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figures and tables 1–4

Reporting Summary

Supplementary table 5

Genetic introgression between gayal and zebu

Supplementary table 6

Genetic introgression between bali cattle and zebu

Supplementary table 7

Gene enrichment analysis genes within regions showing genetic introgression between zebu and gayal

Supplementary table 8

Gene enrichment analysis genes within regions showing genetic introgression between zebu and bali cattle

Supplementary table 9

Genetic introgression between yak and Tibetan cattle

Supplementary table 10

Gene enrichment analysis genes within regions showing genetic introgression between yak and Tibetan cattle

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, DD., Ding, XD., Wang, S. et al. Pervasive introgression facilitated domestication and adaptation in the Bos species complex. Nat Ecol Evol 2, 1139–1145 (2018). https://doi.org/10.1038/s41559-018-0562-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41559-018-0562-y

This article is cited by

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