Article | Published:

Variation and constraints in hybrid genome formation

Nature Ecology & Evolutionvolume 2pages549556 (2018) | Download Citation


Hybridization is an important source of variation; it transfers adaptive genetic variation across species boundaries and generates new species. Yet, the limits to viable hybrid genome formation are poorly understood. Here we investigated to what extent hybrid genomes are free to evolve by sequencing the genomes of four island populations of the homoploid hybrid Italian sparrow Passer italiae. We report that a variety of novel and fully functional hybrid genomic combinations are likely to have arisen independently on Crete, Corsica, Sicily and Malta, with differentiation in candidate genes for beak shape and plumage colour. However, certain genomic regions are invariably inherited from the same parent species, limiting variation. These regions are over-represented on the Z chromosome and harbour candidate incompatibility loci, including DNA-repair and mitonuclear genes. These gene classes may contribute to the general reduction of introgression on sex chromosomes. This study demonstrates that hybrid genomes may vary, and identifies new candidate reproductive isolation genes.

  • Subscribe to Nature Ecology & Evolution for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Additional information

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


  1. 1.

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

  2. 2.

    Abbott, R. et al. Hybridization and speciation. J. Evol. Biol. 26, 229–246 (2013).

  3. 3.

    Seehausen, O. Hybridization and adaptive radiation. Trends Ecol. Evol. 19, 198–207 (2004).

  4. 4.

    The Heliconius Genome Sequencing Consortium. Butterfly genome reveals promiscuous exchange of mimicry adaptations among species. Nature 487, 94–98 (2012).

  5. 5.

    Rieseberg, L. H. Major ecological transitions in wild sunflowers facilitated by hybridization. Science 301, 1211–1216 (2003).

  6. 6.

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

  7. 7.

    Fontaine, M. C. et al. Extensive introgression in a malaria vector species complex revealed by phylogenomics. Science 347, 1258524 (2015).

  8. 8.

    Baack, E. J. & Rieseberg, L. H. A genomic view of introgression and hybrid speciation. Curr. Opin. Genet. Dev. 17, 513–518 (2007).

  9. 9.

    Trier, C. N., Hermansen, J. S., Sætre, G.-P. & Bailey, R. I. Evidence for mito-nuclear and sex-linked reproductive barriers between the hybrid Italian sparrow and its parent species. PLoS Genet. 10, e1004075 (2014).

  10. 10.

    Martin, S. H. et al. Genome-wide evidence for speciation with gene flow in Heliconius butterflies. Genome Res. 23, 1817–1828 (2013).

  11. 11.

    Qvarnström, A. & Bailey, R. I. Speciation through evolution of sex-linked genes. Heredity 102, 4–15 (2008).

  12. 12.

    Hermansen, J. S. et al. Hybrid speciation in sparrows I: phenotypic intermediacy, genetic admixture and barriers to gene flow. Mol. Ecol. 20, 3812–3822 (2011).

  13. 13.

    Elgvin, T. O. et al. The genomic mosaicism of hybrid speciation. Sci. Adv. 3, 1–15 (2017).

  14. 14.

    Hermansen, J. S. et al. Hybrid speciation through sorting of parental incompatibilities in Italian sparrows. Mol. Ecol. 23, 5831–5842 (2014).

  15. 15.

    Saetre, G. P. et al. Single origin of human commensalism in the house sparrow. J. Evol. Biol. 25, 788–796 (2012).

  16. 16.

    Bache-Mathiesen, L. The Evolutionary Potential of Male Plumage Color in a Hybrid Sparrow Species. MSc thesis, University of Oslo (2015);

  17. 17.

    Meier, J. I. et al. Ancient hybridization fuels rapid cichlid fish adaptive radiations. Nat. Commun. 8, 1–11 (2017).

  18. 18.

    Burri, R. et al. Linked selection and recombination rate variation drive the evolution of the genomic landscape of differentiation across the speciation continuum of Ficedula flycatchers. Genome Res. 25, 1656–1665 (2015).

  19. 19.

    Hill, W. G. & Robertson, A. The effect of linkage on limits to artificial selection. Genet. Res. 8, 269–294 (1966).

  20. 20.

    Laine, V. N. et al. Evolutionary signals of selection on cognition from the great tit genome and methylome. Nat. Commun. 7, 1–9 (2016).

  21. 21.

    Lamichhaney, S. et al. Evolution of Darwin’s finches and their beaks revealed by genome sequencing. Nature 518, 371–375 (2015).

  22. 22.

    Eroukhmanoff, F., Hermansen, J. S., Bailey, R. I., Sæther, S. A. & Sætre, G.-P. S. Local adaptation within a hybrid species. Heredity 111, 286–292 (2013).

  23. 23.

    Noramly, S., Freeman, A. & Morgan, B. A. Beta-catenin signaling can initiate feather bud development. Development 126, 3509–3521 (1999).

  24. 24.

    Guo, H. et al Wnt/beta-catenin signaling pathway activates melanocyte stem cells in vitro and in vivo. J. Dermatol. Sci. 83, 45–51 (2016).

  25. 25.

    Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595 (1989).

  26. 26.

    Mank, J. E., Nam, K. & Ellegren, H. Faster-Z evolution is predominantly due to genetic drift. Mol. Biol. Evol. 27, 661–670 (2010).

  27. 27.

    Charlesworth, B., Coyne, J. A. & Barton, N. H. The relative rates of evolution of sex chromosomes and autosomes. Am. Nat. 130, 113–146 (2016).

  28. 28.

    Charlesworth, B. & Charlesworth, D. The degeneration of Y chromosomes. Philos. Trans. R. Soc. Lond. B 355, 1563–1572 (2000).

  29. 29.

    Poelstra, J. W., Vijay, N., Hoeppner, M. P. & Wolf, J. B. W. Transcriptomics of colour patterning and coloration shifts in crows. Mol. Ecol. 24, 4617–4628 (2015).

  30. 30.

    Tomarev, S. I. & Nakaya, N. Olfactomedin domain-containing proteins: possible mechanisms of action and functions in normal development and pathology. Mol. Neurobiol. 40, 122–138 (2009).

  31. 31.

    David, W. M., Mitchell, D. L. & Walter, R. B. DNA repair in hybrid fish of the genus Xiphophorus. Comp. Biochem. Physiol. C. 138, 301–309 (2004).

  32. 32.

    Greig, D., Travisano, M., Louis, E. J. & Borts, R. H. A role for the mismatch repair system during incipient speciation in Saccharomyces. J. Evol. Biol. 16, 429–437 (2003).

  33. 33.

    Schumer, M. & Brandvain, Y. Determining epistatic selection in admixed populations. Mol. Ecol. 25, 2577–2591 (2016).

  34. 34.

    Barton, N. H. The role of hybridization in evolution. Mol. Ecol. 10, 551–568 (2001).

  35. 35.

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

  36. 36.

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

  37. 37.

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

  38. 38.

    Van der Auwera, G. A. et al. From FastQ data to high-confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinforma. 11, 1–33 (2013).

  39. 39.

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

  40. 40.

    Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: Analysis of Next Generation Sequencing Data. BMC Bioinforma. 15, 356 (2014).

  41. 41.

    Fumagalli, M., Vieira, F. G., Linderoth, T. & Nielsen, R. ngsTools: methods for population genetics analyses from next-generation sequencing data. Bioinformatics 30, 1486–1487 (2014).

  42. 42.

    Fumagalli, M. et al. Quantifying population genetic differentiation from next-generation sequencing data. Genetics 195, 979–992 (2013).

  43. 43.

    Martin, S. H., Davey, J. W. & Jiggins, C. D. Evaluating the use of ABBA–BABA statistics to locate introgressed loci. Mol. Biol. Evol. 32, 244–257 (2014).

  44. 44.

    Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).

  45. 45.

    Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

  46. 46.

    Zamani, N. et al. Unsupervised genome-wide recognition of local relationship patterns. BMC Genom. 14, 1–11 (2013).

  47. 47.

    Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, e1003537 (2014).

  48. 48.

    O’Connell, J. et al. A general approach for haplotype phasing across the full spectrum of relatedness. PLoS Genet. 10, e1004234 (2014).

  49. 49.

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

  50. 50.

    Bruen, T. C., Philippe, H. & Bryant, D. A simple and robust statistical test for detecting the presence of recombination. Genetics 172, 2665–2681 (2006).

  51. 51.

    Yule, U. G. A mathematical theory of evolution, based on the conclusions of Dr. J. C. Willis, F.R.S. Phil. Trans. R. Soc. Lond. B 213, 21–87 (1925).

  52. 52.

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

  53. 53.

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

  54. 54.

    Matschiner, M. Fitchi: haplotype genealogy graphs based on the Fitch algorithm. Bioinformatics 32, 1250–1252 (2016).

  55. 55.

    Burri, R. et al. Linked selection and recombination rate variation drive the evolution of the genomic landscape of differentiation across the speciation continuum of Ficedula flycatchers. Genome Res. 25, 1656–1665 (2015).

  56. 56.

    Beissbarth, T. & Speed, T. P. GOstat: find statistically overrepresented gene ontologies within a group of genes. Bioinformatics 20, 1464–1465 (2004).

  57. 57.

    Smith, A. C., Blackshaw, J. A. & Robinson, A. J. MitoMiner: a data warehouse for mitochondrial proteomics data. Nucleic Acids Res. 40, D1160–D1167 (2011).

  58. 58.

    Benjamini, Y. Simultaneous and selective inference: current successes and future challenges. Biom. J. 52, 708–721 (2010).

  59. 59.

    Pfeifer, B., Wittelsbürger, U., Ramos-Onsins, S. E. & Lercher, M. J. PopGenome: an efficient Swiss army knife for population genomic analyses in R. Mol. Biol. Evol. 31, 1929–1936 (2014).

Download references


We thank M. Tesaker and BirdLife Malta for help with field work, L. Piñeiro and L. Bache-Mathiesen for providing morphological data, and A. Nilsson for comments on the manuscript. This work was funded by a Swedish Research Council post doctoral grant and a Wenner-Gren Fellowship to A.R. and a Norwegian Science Foundation grant to G-P.S. and A.R.

Author information


  1. Department of Biosciences, Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway

    • Anna Runemark
    • , Cassandra N. Trier
    • , Fabrice Eroukhmanoff
    • , Jo S. Hermansen
    • , Michael Matschiner
    • , Mark Ravinet
    • , Tore O. Elgvin
    •  & Glenn-Peter Sætre


  1. Search for Anna Runemark in:

  2. Search for Cassandra N. Trier in:

  3. Search for Fabrice Eroukhmanoff in:

  4. Search for Jo S. Hermansen in:

  5. Search for Michael Matschiner in:

  6. Search for Mark Ravinet in:

  7. Search for Tore O. Elgvin in:

  8. Search for Glenn-Peter Sætre in:


A.R. conceived the study, carried out field work and laboratory work, designed analyses, analysed data and wrote the manuscript. C.N.T. helped design analyses, and provided scripts, F.E. carried out field work and the gene ontology analyses, J.S.H. carried out field work and the final touches in figure preparation, M.M. performed the BEAST and Saguaro analyses and M.R. performed the recombination rate analyses and principal component analysis. T.O.E. provided the house sparrow reference genome, and G.P.S. identified the study system, designed the sampling strategy and carried out field work. All co-authors commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Anna Runemark.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–10, Supplementary Tables 1–23

  2. Life Sciences Reporting Summary

About this article

Publication history





Rights and permissions

To obtain permission to re-use content from this article visit RightsLink.