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Whole-genome analysis of introgressive hybridization and characterization of the bovine legacy of Mongolian yaks

Nature Genetics volume 49, pages 470475 (2017) | Download Citation

Abstract

The yak is remarkable for its adaptation to high altitude and occupies a central place in the economies of the mountainous regions of Asia. At lower elevations, it is common to hybridize yaks with cattle to combine the yak's hardiness with the productivity of cattle. Hybrid males are sterile, however, preventing the establishment of stable hybrid populations, but not a limited introgression after backcrossing several generations of female hybrids to male yaks. Here we inferred bovine haplotypes in the genomes of 76 Mongolian yaks using high-density SNP genotyping and whole-genome sequencing. These yaks inherited 1.3% of their genome from bovine ancestors after nearly continuous admixture over at least the last 1,500 years. The introgressed regions are enriched in genes involved in nervous system development and function, and particularly in glutamate metabolism and neurotransmission. We also identified a novel mutation associated with a polled (hornless) phenotype originating from Mongolian Turano cattle. Our results suggest that introgressive hybridization contributed to the improvement of yak management and breeding.

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References

  1. 1.

    Hybridization as an invasion of the genome. Trends Ecol. Evol. 20, 229–237 (2005).

  2. 2.

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

  3. 3.

    & Resurrecting surviving Neandertal lineages from modern human genomes. Science 343, 1017–1021 (2014).

  4. 4.

    et al. The genomic signature of crop–wild introgression in maize. PLoS Genet. 9, e1003477 (2013).

  5. 5.

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

  6. 6.

    , , , & Assessment of cattle genetic introgression into domestic yak populations using mitochondrial and microsatellite DNA markers. Anim. Genet. 41, 242–252 (2010).

  7. 7.

    , & The genetics of brown coat color and white spotting in domestic yaks (Bos grunniens). Anim. Genet. 45, 652–659 (2014).

  8. 8.

    et al. Serial translocation by means of circular intermediates underlies colour sidedness in cattle. Nature 482, 81–84 (2012).

  9. 9.

    et al. Bovine polledness—an autosomal dominant trait with allelic heterogeneity. PLoS One 7, e39477 (2012).

  10. 10.

    et al. Novel insights into the bovine polled phenotype and horn ontogenesis in Bovidae. PLoS One 8, e63512 (2013).

  11. 11.

    et al. The 80-kb DNA duplication on BTA1 is the only remaining candidate mutation for the polled phenotype of Friesian origin. Genet. Sel. Evol. 46, 44 (2014).

  12. 12.

    et al. Associations of single nucleotide polymorphisms in candidate genes with the polled trait in Datong domestic yaks. Anim. Genet. 45, 138–141 (2014).

  13. 13.

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

  14. 14.

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

  15. 15.

    , , & RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference. Am. J. Hum. Genet. 93, 278–288 (2013).

  16. 16.

    , & The Yak (FAO Regional Office for Asia and the Pacific, 2003).

  17. 17.

    Sex chromosomes and speciation in Drosophila. Trends Genet. 24, 336–343 (2008).

  18. 18.

    & Climatic changes during the past 1300 years as deduced from the sediments of Lake Nakatsuna, central Japan. Limnology 2, 157–168 (2001).

  19. 19.

    China Marches West: The Qing Conquest of Central Eurasia (Harvard University Press, 2009).

  20. 20.

    et al. Rabbit genome analysis reveals a polygenic basis for phenotypic change during domestication. Science 345, 1074–1079 (2014).

  21. 21.

    et al. Prehistoric genomes reveal the genetic foundation and cost of horse domestication. Proc. Natl. Acad. Sci. USA 111, E5661–E5669 (2014).

  22. 22.

    et al. Refinement of chromosome 3p22.3 region and identification of a susceptibility gene for bipolar affective disorder. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 162B, 163–168 (2013).

  23. 23.

    & Novel neurotransmitters and their neuropsychiatric relevance. Am. J. Psychiatry 157, 1738–1751 (2000).

  24. 24.

    , & Integrated sphingosine-1 phosphate signaling in the central nervous system: from physiological equilibrium to pathological damage. Pharmacol. Res. 104, 156–164 (2016).

  25. 25.

    & Behavioral genetics of affective and anxiety disorders. in Behavioral Neurogenetics (eds. Cryan, F.J. & Reif, A.) 463–502 (Springer, 2012).

  26. 26.

    et al. Identification of pathways for bipolar disorder: a meta-analysis. JAMA Psychiatry 71, 657–664 (2014).

  27. 27.

    et al. Genome-wide genetic association of complex traits in heterogeneous stock mice. Nat. Genet. 38, 879–887 (2006).

  28. 28.

    , , & Genetical genomics of behavior: a novel chicken genomic model for anxiety behavior. Genetics 202, 327–340 (2016).

  29. 29.

    , & Genetic mapping of canine fear and aggression. BMC Genomics 17, 572 (2016).

  30. 30.

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

  31. 31.

    The physiology of horn growth: a study of the morphogenesis, the interaction of tissues, and the evolutionary processes of a mendelian recessive character by means of transplantation of tissues. J. Exp. Zool. 69, 347–405 (1935).

  32. 32.

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

  33. 33.

    et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

  34. 34.

    , , , & Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 25, 2865–2871 (2009).

  35. 35.

    , & Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

  36. 36.

    , & CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994).

  37. 37.

    , , , & MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol. Biol. Evol. 30, 2725–2729 (2013).

  38. 38.

    & The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425 (1987).

  39. 39.

    Confidence-limits on phylogenies: an approach using the bootstrap. Evolution 39, 783–791 (1985).

  40. 40.

    & Efficient multilocus association testing for whole genome association studies using localized haplotype clustering. Genet. Epidemiol. 31, 365–375 (2007).

  41. 41.

    , , & Inference of population structure using dense haplotype data. PLoS Genet. 8, e1002453 (2012).

  42. 42.

    et al. A genetic atlas of human admixture history. Science 343, 747–751 (2014).

  43. 43.

    et al. The fine-scale genetic structure of the British population. Nature 519, 309–314 (2015).

  44. 44.

    et al. Recovery of native genetic background in admixed populations using haplotypes, phenotypes, and pedigree information—using Cika cattle as a case breed. PLoS One 10, e0123253 (2015).

  45. 45.

    et al. High resolution of human evolutionary trees with polymorphic microsatellites. Nature 368, 455–457 (1994).

  46. 46.

    & Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23, 254–267 (2006).

  47. 47.

    et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

  48. 48.

    et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).

  49. 49.

    , & Reconciling the analysis of IBD and IBS in complex trait studies. Nat. Rev. Genet. 11, 800–805 (2010).

  50. 50.

    & Prediction of identity by descent probabilities from marker-haplotypes. Genet. Sel. Evol. 33, 605–634 (2001).

  51. 51.

    & Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution. Genetics 174, 1009–1016 (2006).

  52. 52.

    , , , & Fine mapping of a quantitative trait locus for twinning rate using combined linkage and linkage disequilibrium mapping. Genetics 161, 373–379 (2002).

  53. 53.

    et al. Fine mapping of milk production QTL on BTA6 by combined linkage and linkage disequilibrium analysis. J. Dairy Sci. 87, 690–698 (2004).

  54. 54.

    et al. Whole-genome resequencing shows numerous genes with nonsynonymous SNPs in the Japanese native cattle Kuchinoshima-Ushi. BMC Genomics 12, 103 (2011).

  55. 55.

    et al. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28, i333–i339 (2012).

  56. 56.

    Multiple sequence alignment with hierarchical clustering. Nucleic Acids Res. 16, 10881–10890 (1988).

  57. 57.

    , , & WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004).

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Acknowledgements

A.C. acknowledges P. Boudinot and D. Boichard for interesting discussions about the major histocompatibility complex and the recombination rate in cattle, respectively; M. Boussaha, Y. Djari and C. Klopp for introducing him to the use of SAMtools and Pindel software; and M.-C. Deloche, C. Escouflaire and A. Michenet for their punctual assistance. The authors acknowledge the Zoologischer Garten Berlin, Tierpark Cottbus and Tierpark Hellabrunn Munich (Germany), as well as the Jardin des Plantes de Paris (France) and all the breeders in Europe and Asia for generously providing samples and phenotypes. Apis-Gène is acknowledged for funding the AKELOS research project. LAFUGA is funded by the LMU excellence program.

Author information

Affiliations

  1. Chair of Animal Genetics and Husbandry, Ludwig Maximilians University Munich, Munich, Germany.

    • Ivica Medugorac
    •  & Sophie Rothammer
  2. Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University Munich, Munich, Germany.

    • Alexander Graf
    • , Helmut Blum
    •  & Stefan Krebs
  3. GABI, INRA, AgroParisTech, Université Paris–Saclay, Jouy-en-Josas, France.

    • Cécile Grohs
    •  & Aurélien Capitan
  4. Mongolian Jak Society, Sum, Ulan Bator, Mongolia.

    • Yondon Zagdsuren
  5. Center of Biotechnology and Molecular Diagnostics of the L.K. Ernst Institute of Animal Husbandry, Moscow region, Russian Federation.

    • Elena Gladyr
    •  & Natalia Zinovieva
  6. INRA, UMR 1388 Génétique, Physiologie et Systèmes d'Elevage GeT-PlaGe Genomic Facility, Castanet-Tolosan, France.

    • Johanna Barbieri
  7. Université de Toulouse, INPT, ENSAT, UMR 1388 Génétique, Physiologie et Systèmes d'Elevage, Castanet-Tolosan, France.

    • Johanna Barbieri
  8. Tierzuchtforschung e.V. München, Grub, Germany.

    • Doris Seichter
    •  & Ingolf Russ
  9. AgriGenomics, Illumina, San Diego, California, USA.

    • André Eggen
  10. Genetics Institute, Faculty of Life Sciences, University College London, London, UK.

    • Garrett Hellenthal
  11. Institute of Animal Breeding and Genetics, Department for Biomedical Sciences, University of Veterinary Medicine, Vienna, Austria.

    • Gottfried Brem
  12. ALLICE, Paris, France.

    • Aurélien Capitan

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Contributions

A.C. and I.M. conceived and coordinated the study. A.C., I.M. and S.K. designed the study. I.M. mapped the POLLED locus and performed introgression analysis using SNP chip genotyping data, simulation analyses and neighbor-joining phylogenetic analyses. A.C. performed variant calling, annotation and screening for candidate mutations, analysis of sequence conservation, annotation of the gene content of the introgressed intervals and gene set enrichment analyses. S.K., A.G. and I.M. performed introgression analysis based on WGS data, determination of ancestral alleles, genome and capture sequencing, and R graphics. C.G., S.R. and A.C. performed PCR for Sanger sequencing and for genotyping by PCR and electrophoresis or PCR and Sanger sequencing. J.B. performed WGS. D.S. and I.R. performed SNP chip genotyping and WGS. Y.Z., E.G., N.Z. and G.B. provided samples and phenotypes. H.B. provided sequencing and bioinformatics facilities. A.E. provided Illumina BovineHD SNP chip genotyping data. G.H. provided software and expertise in admixture analysis. A.C., I.M., S.K. and A.G. contributed to writing the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ivica Medugorac or Aurélien Capitan.

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DOI

https://doi.org/10.1038/ng.3775

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