Abstract

Males and females share many traits that have a common genetic basis; however, selection on these traits often differs between the sexes, leading to sexual conflict1,2. Under such sexual antagonism, theory predicts the evolution of genetic architectures that resolve this sexual conflict2,3,4,5. Yet, despite intense theoretical and empirical interest, the specific loci underlying sexually antagonistic phenotypes have rarely been identified, limiting our understanding of how sexual conflict impacts genome evolution3,6 and the maintenance of genetic diversity6,7. Here we identify a large effect locus controlling age at maturity in Atlantic salmon (Salmo salar), an important fitness trait in which selection favours earlier maturation in males than females8, and show it is a clear example of sex-dependent dominance that reduces intralocus sexual conflict and maintains adaptive variation in wild populations. Using high-density single nucleotide polymorphism data across 57 wild populations and whole genome re-sequencing, we find that the vestigial-like family member 3 gene (VGLL3) exhibits sex-dependent dominance in salmon, promoting earlier and later maturation in males and females, respectively. VGLL3, an adiposity regulator associated with size and age at maturity in humans, explained 39% of phenotypic variation, an unexpectedly large proportion for what is usually considered a highly polygenic trait. Such large effects are predicted under balancing selection from either sexually antagonistic or spatially varying selection9,10. Our results provide the first empirical example of dominance reversal allowing greater optimization of phenotypes within each sex, contributing to the resolution of sexual conflict in a major and widespread evolutionary trade-off between age and size at maturity. They also provide key empirical evidence for how variation in reproductive strategies can be maintained over large geographical scales. We anticipate these findings will have a substantial impact on population management in a range of harvested species where trends towards earlier maturation have been observed.

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Accessions

Primary accessions

European Nucleotide Archive

Data deposits

Details of the SNPs used in the study have been deposited in dbSNP (http://www.ncbi.nlm.nih.gov/SNP/) under accession numbers ss1867919552–ss1868858426, and re-sequencing data have been deposited in EMBL Nucleotide Sequence Database (European Nucleotide Archive) under accession number PRJEB10744. SNP genotype and phenotype data and detailed DNA sequence information of the main candidate gene regions are available in Dryad (http://dx.doi.org/10.5061/dryad. 23h4q).

References

  1. 1.

    & Intralocus sexual conflict. Trends Ecol. Evol. 24, 280–288 (2009)

  2. 2.

    Sexual dimorphism, sexual selection, and adaptation in polygenic characters. Evolution 34, 292–305 (1980)

  3. 3.

    Sex chromosomes and the evolution of sexual dimorphism. Evolution 38, 1416–1424 (1984)

  4. 4.

    The Genetical Theory of Natural Selection 139–142 (Oxford Univ. Press, 1930)

  5. 5.

    Intralocus sexual conflict. Ann. NY Acad. Sci . 1168, 52–71 (2009)

  6. 6.

    The genomic location of sexually antagonistic variation: some cautionary comments. Evolution 64, 1510–1516 (2010)

  7. 7.

    & Polygenic variation maintained by balancing selection: pleiotropy, sex-dependent allelic effects and G × E interactions. Genetics 166, 1053–1079 (2004)

  8. 8.

    in Evolution Illuminated: Salmon and Their Relatives (eds & ) 20–51 (Oxford Univ. Press, 2004)

  9. 9.

    & Balancing selection in species with separate sexes: insights from Fisher’s geometric model. Genetics 197, 991–1006 (2014)

  10. 10.

    , & Ecological genomics of local adaptation. Nature Rev. Genet. 14, 807–820 (2013)

  11. 11.

    A review of some fundamental concepts and problems of population genetics. Cold Spring Harb. Symp. Quant. Biol. 20, 1–15 (1955)

  12. 12.

    et al. Negative frequency-dependent selection of sexually antagonistic alleles in Myodes glareolus. Science 334, 972–974 (2011)

  13. 13.

    , , & Heterozygote advantage as a natural consequence of adaptation in diploids. Proc. Natl Acad. Sci. USA 108, 20666–20671 (2011)

  14. 14.

    & Evolutionary inevitability of sexual antagonism. Proc. R. Soc. Lond. B 281, 20132123 (2014)

  15. 15.

    , , & Regions of stable equilibria for models of differential selection in the two sexes under random mating. Genetics 85, 171–183 (1977)

  16. 16.

    & Two sexes, one genome: the evolutionary dynamics of intralocus sexual conflict. Ecol. Evol . 3, 1819–1834 (2013)

  17. 17.

    Life history evolution: successes, limitations, and prospects. Naturwissenschaften 87, 476–486 (2000)

  18. 18.

    & in Atlantic Salmon Ecology 33–65 (Wiley-Blackwell, 2011)

  19. 19.

    & Life history variation and growth rate thresholds for maturity in Atlantic salmon, Salmo salar. Can. J. Fish. Aquat. Sci . 55 (Suppl. 1), 22–47 (1998)

  20. 20.

    , , & Vestigial-like 3 is an inhibitor of adipocyte differentiation. J. Lipid Res. 54, 473–481 (2013)

  21. 21.

    et al.; Australian Ovarian Cancer Study; GENICA Network; kConFab; LifeLines Cohort Study; InterAct Consortium; Early Growth Genetics (EGG) Consortium. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 514, 92–97 (2014)

  22. 22.

    et al.; ReproGen Consortium; Early Growth Genetics (EGG) Consortium. Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity. Hum. Mol. Genet. 22, 2735–2747 (2013)

  23. 23.

    et al. Control of puberty in farmed fish. Gen. Comp. Endocrinol. 165, 483–515 (2010)

  24. 24.

    , , & Modelling the proximate basis of salmonid life-history variation, with application to Atlantic salmon, Salmo salar L. Evol. Ecol. 12, 581–599 (1998)

  25. 25.

    et al. Localization of a novel human A-kinase-anchoring protein, hAKAP220, during spermatogenesis. Dev. Biol. 223, 194–204 (2000)

  26. 26.

    et al. Direct transcriptional regulation of Six6 is controlled by SoxB1 binding to a remote forebrain enhancer. Dev. Biol. 366, 393–403 (2012)

  27. 27.

    & (eds) Mechanisms of Life History Evolution: The Genetics and Physiology of Life History Traits and Trade-Offs (Oxford Univ. Press, 2011)

  28. 28.

    et al. Comparative genome analysis of the primary sex-determining locus in salmonid fishes. Genome Res. 13, 272–280 (2003)

  29. 29.

    Overview of the status of Atlantic salmon (Salmo salar) in the North Atlantic and trends in marine mortality. ICES J. Mar. Sci. 69, 1538–1548 (2012)

  30. 30.

    & Human-induced evolution caused by unnatural selection through harvest of wild animals. Proc. Natl Acad. Sci. USA 106 (Suppl. 1), 9987–9994 (2009)

  31. 31.

    et al. SNP-array reveals genome-wide patterns of geographical and potential adaptive divergence across the natural range of Atlantic salmon (Salmo salar). Mol. Ecol. 22, 532–551 (2013)

  32. 32.

    , , & A standardized method for quantifying unidirectional genetic introgression. Ecol. Evol . 4, 3256–3263 (2014)

  33. 33.

    et al. Low but significant genetic differentiation underlies biologically meaningful phenotypic divergence in a large Atlantic salmon population. Mol. Ecol. 24, 5158–5174 (2015)

  34. 34.

    et al. Genome-wide SNP analysis reveals a genetic basis for sea-age variation in a wild population of Atlantic salmon (Salmo salar). Mol. Ecol. 23, 3452–3468 (2014)

  35. 35.

    et al. The sexually dimorphic on the Y-chromosome gene (sdY) is a conserved male-specific Y-chromosome sequence in many salmonids. Evol. Appl . 6, 486–496 (2013)

  36. 36.

    & Marine post-smolt growth and age at maturity of Atlantic salmon. J. Fish Biol. 48, 1–15 (1996)

  37. 37.

    & Spacing of scale circuli versus growth-rate in young Coho salmon. Fish Bull. 88, 637–643 (1990)

  38. 38.

    ICES. Report of the Workshop on Age Determination of Salmon (WKADS). Report CM 2011/ACOM:44 (ICES, 2011)

  39. 39.

    , & Growth rate correlations across life-stages in female Atlantic salmon. J. Fish Biol. 60, 780–784 (2002)

  40. 40.

    & Sea growth, smolt age and age at sexual maturation in Atlantic salmon. J. Fish Biol. 71, 245–252 (2007)

  41. 41.

    , & Genetic origin of Norwegian farmed Atlantic salmon. Aquaculture 98, 41–50 (1991)

  42. 42.

    GenABEL Project Developers. GenABEL: genome-wide SNP association analysis. R package version 1.8-0 (2013)

  43. 43.

    R Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2014)

  44. 44.

    B. ordinal - regression models for ordinal data. R package version 2015.1-21 (2015)

  45. 45.

    , , , & Adjusting for heritable covariates can bias effect estimates in genome-wide association studies. Am. J. Hum. Genet. 96, 329–339 (2015)

  46. 46.

    et al. Detecting selection in population trees: the Lewontin and Krakauer test extended. Genetics 186, 241–262 (2010)

  47. 47.

    & Evaluation of demographic history and neutral parameterization on the performance of FST outlier tests. Mol. Ecol. 23, 2178–2192 (2014)

  48. 48.

    , , & Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, v067.i01 (2015)

  49. 49.

    & Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010)

  50. 50.

    & Haplotype-based variant detection from short-read sequencing. Preprint at (2012)

  51. 51.

    et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012)

  52. 52.

    et al. A method and server for predicting damaging missense mutations. Nature Methods 7, 248–249 (2010)

  53. 53.

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

  54. 54.

    et al. Detecting recent positive selection in the human genome from haplotype structure. Nature 419, 832–837 (2002)

  55. 55.

    & rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure. Bioinformatics 28, 1176–1177 (2012)

  56. 56.

    , , & A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006)

  57. 57.

    & Detecting balancing selection in genomes: limits and prospects. Mol. Ecol. 24, 3529–3545 (2015)

  58. 58.

    & Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol. Evol. 28, 659–669 (2013)

  59. 59.

    , , & On detecting incomplete soft or hard selective sweeps using haplotype structure. Mol. Biol. Evol. 31, 1275–1291 (2014)

  60. 60.

    , , & Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps. PLoS Genet. 11, e1005004 (2015)

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Acknowledgements

We thank L. Andersson, T. F. Hansen and H. Granroth-Wilding for commenting on earlier drafts of the manuscript. We also acknowledge the numerous fishers who contributed scales and phenotypic information. We thank J. Haantie, J. G. Jensås, J. Kuusela, I. Torvi and G. Østborg for scale measurements, T. Andersstuen, T. Balstad, L. Birkeland Eriksen, S. Karoliussen, J. Kuismin, M. Lindqvist, T. Pajula, K. Salminen, K. Sõstar, M. Spets and K. Vagonyte-Hallan for laboratory assistance, M. Ellmen, O. Guttorm, T. Kanniainen, A. Koskinen, T. Pöyhönen and S. Uusi-Heikkilä for sampling assistance, and T. Mulugeta for informatics support. Bioinformatic analyses used resources at the Finnish Centre for Scientific Computing, the Abel Cluster, owned by the University of Oslo and the Norwegian Metacenter for High Performance Computing, and operated by the Department for Research Computing at the University of Oslo IT Department and the Orion Computing Cluster at CIGENE. This study was funded by the Finnish Academy (grants 137710, 141231, 272836, 284941), the Research Council of Norway (QuantEscape, grant 216105 and RCN-project 221734/O30) and by AquaGen (SNP array development).

Author information

Author notes

    • Nicola J. Barson
    •  & Tutku Aykanat

    These authors contributed equally to this work.

Affiliations

  1. Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, NO-1432 Ås, Norway

    • Nicola J. Barson
    • , Matthew Kent
    • , Torfinn Nome
    •  & Sigbjørn Lien
  2. Department of Biology, University of Turku, FI-20014, Finland

    • Tutku Aykanat
    •  & Craig R. Primmer
  3. Norwegian Institute for Nature Research (NINA), NO-7485 Trondheim, Norway

    • Kjetil Hindar
    • , Geir H. Bolstad
    • , Peder Fiske
    • , Arne J. Jensen
    • , Sten Karlsson
    •  & Tor F. Næsje
  4. Nofima - Norwegian Institute of Food, Fisheries and Aquaculture Research, NO-1431 Ås, Norway

    • Matthew Baranski
    •  & Céleste Jacq
  5. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK

    • Susan E. Johnston
  6. AquaGen, NO-7462 Trondheim, Norway

    • Thomas Moen
  7. Natural Resources Institute Finland, Oulu, FI-90014, Finland

    • Eero Niemelä
    • , Panu Orell
    • , Atso Romakkaniemi
    •  & Jaakko Erkinaro
  8. Radgivende Biologer, NO-5003 Bergen, Norway

    • Harald Sægrov
    •  & Kurt Urdal

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Contributions

C.R.P., S.L., N.J.B., T.A. and K.H. conceived the study. C.R.P., S.L., N.J.B., T.A., K.H., C.J., S.K. and S.E.J. designed the experiments. T.M. led the development of the 220K SNP array, and M.K. and T.N. generated and conducted bioinformatics on the molecular data. K.H., P.F., A.J.J., T.F.N., H.S., K.U., J.E., P.O., A.R. and E.N. coordinated the collection of phenotypic data. T.A., N.J.B., M.B., G.H.B., S.K. and C.J. analysed the data. N.J.B., T.A. and C.R.P. wrote the manuscript. All authors read and commented on the manuscript. C.R.P. and S.L. contributed equally as senior authors.

Corresponding authors

Correspondence to Sigbjørn Lien or Craig R. Primmer.

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    Supplementary Information

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DOI

https://doi.org/10.1038/nature16062

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