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Genomic evidence consistent with antagonistic pleiotropy may help explain the evolutionary maintenance of same-sex sexual behaviour in humans

An Author Correction to this article was published on 13 September 2021

This article has been updated


Human same-sex sexual behaviour (SSB) is heritable, confers no immediately obvious direct reproductive or survival benefit and can divert mating effort from reproductive opportunities. This presents a Darwinian paradox: why has SSB been maintained despite apparent selection against it? We show that genetic effects associated with SSB may, in individuals who only engage in opposite-sex sexual behaviour (OSB individuals), confer a mating advantage. Using results from a recent genome-wide association study of SSB and a new genome-wide association study on number of opposite-sex sexual partners in 358,426 individuals, we show that, among OSB individuals, genetic effects associated with SSB are associated with having more opposite-sex sexual partners. Computer simulations suggest that such a mating advantage for alleles associated with SSB could help explain how it has been evolutionarily maintained. Caveats include the cultural specificity of our UK and US samples, the societal regulation of sexual behaviour in these populations, the difficulty of measuring mating success and the fact that measured variants capture a minority of the total genetic variation in the traits.

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Fig. 1: Evolutionary simulations.
Fig. 2: Per-chromosome SNP-based heritability.

Data availability

This research was conducted using data from the UK Biobank resource (application number 25995). UK Biobank data can be accessed on request once a research project has been submitted and approved by the UK Biobank committee ( Data from The National Longitudinal Study of Adolescent to Adult Health (Add Health) can also be applied for (see for details). GWAS summary statistics of the number of opposite sex sexual partners among OSB individuals in UK-Biobank are available at GWAS Catalog (, study accession IDs: GCST90026480, GCST90026481, and GCST90026482). Source data are provided with this paper.

Code availability

Custom code used for statistical analyses is available from the corresponding author upon request. Source data are provided with this paper.

Change history


  1. ACSF investigators. AIDS and sexual behaviour in France. Nature 360, 407 (1992).

    Article  Google Scholar 

  2. Melbye, M. & Biggar, R. J. Interactions between persons at risk for AIDS and the general population in Denmark. Am. J. Epidemiol. 135, 593–602 (1992).

    CAS  PubMed  Article  Google Scholar 

  3. Semenyna, S. W., VanderLaan, D. P., Petterson, L. J. & Vasey, P. L. Familial patterning and prevalence of male androphilia in Samoa. J. Sex. Res. 54, 1077–1084 (2017).

    PubMed  Article  Google Scholar 

  4. Bailey, J. M. et al. Sexual orientation, controversy, and science. Psychol. Sci. Public Interest 17, 45–101 (2016).

    PubMed  Article  Google Scholar 

  5. Pillard, R. C. & Bailey, J. M. Human sexual orientation has a heritable component. Hum. Biol. 70, 347–365 (1998).

    CAS  PubMed  Google Scholar 

  6. Langstrom, N., Rahman, Q., Carlstrom, E. & Lichtenstein, P. Genetic and environmental effects on same-sex sexual behavior: a population study of twins in Sweden. Arch. Sex. Behav. 39, 75–80 (2010).

    PubMed  Article  Google Scholar 

  7. Bailey, N. W. & Zuk, M. Same-sex sexual behavior and evolution. Trends Ecol. Evol. 24, 439–446 (2009).

    PubMed  Article  Google Scholar 

  8. Clive, J., Flintham, E. & Savolainen, V. Understanding same-sex sexual behaviour requires thorough testing rather than reinvention of theory. Nat. Ecol. Evol. 4, 784–785 (2020).

    PubMed  Article  Google Scholar 

  9. Hutchinson, G. E. A speculative consideration of certain possible forms of sexual selection in man. Am. Nat. 93, 81–91 (1959).

    Article  Google Scholar 

  10. McKnight, J. Straight Science?: Homosexuality, Evolution and Adaptation (Routledge, 1997).

  11. Wilson, E. O. Sociobiology: The New Synthesis (Harvard Univ. Press, 1975).

  12. Camperio-Ciani, A., Corna, F. & Capiluppi, C. Evidence for maternally inherited factors favouring male homosexuality and promoting female fecundity. Proc. R. Soc. Lond. Ser. B 271, 2217–2221 (2004).

    Article  Google Scholar 

  13. Zietsch, B. P. et al. Genetic factors predisposing to homosexuality may increase mating success in heterosexuals. Evol. Hum. Behav. 29, 424–433 (2008).

    Article  Google Scholar 

  14. Vasey, P. L., Pocock, D. S. & VanderLaan, D. P. Kin selection and male androphilia in Samoan fa’afafine. Evol. Hum. Behav. 28, 159–167 (2007).

    Article  Google Scholar 

  15. Rice, W. R., Friberg, U. & Gavrilets, S. Homosexuality as a consequence of epigenetically canalized sexual development. Q. Rev. Biol. 87, 343–368 (2012).

    PubMed  Article  Google Scholar 

  16. Hoskins, J. L., Ritchie, M. G. & Bailey, N. W. A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour. Proc. R. Soc. B 282, 20150429 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  17. Monk, J. D., Giglio, E., Kamath, A., Lambert, M. R. & McDonough, C. E. An alternative hypothesis for the evolution of same-sex sexual behaviour in animals. Nat. Ecol. Evol. 3, 1622–1631 (2019).

    PubMed  Article  Google Scholar 

  18. Schwartz, G., Kim, R. M., Kolundzija, A. B., Rieger, G. & Sanders, A. R. Biodemographic and physical correlates of sexual orientation in men. Arch. Sex. Behav. 39, 93–109 (2010).

    PubMed  Article  Google Scholar 

  19. Ganna, A. et al. Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior. Science 365, eaat7693 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. Bell, A. P. & Weinberg, M. Homosexualities: A Study of Diversity among Men and Women (Simon and Schuster, 1978).

  21. Nila, S., Barthes, J., Crochet, P.-A., Suryobroto, B. & Raymond, M. Kin selection and male homosexual preference in Indonesia. Arch. Sex. Behav. 47, 2455–2465 (2018).

    PubMed  Article  Google Scholar 

  22. Vasey, P. L., Parker, J. L. & VanderLaan, D. P. Comparative reproductive output of androphilic and gynephilic males in Samoa. Arch. Sex. Behav. 43, 363–367 (2014).

    PubMed  Article  Google Scholar 

  23. Miller, E. M. Homosexuality, birth order, and evolution: toward an equilibrium reproductive economics of homosexuality. Arch. Sex. Behav. 29, 1–34 (2000).

    PubMed  Article  Google Scholar 

  24. Carter, A. J. & Nguyen, A. Q. Antagonistic pleiotropy as a widespread mechanism for the maintenance of polymorphic disease alleles. BMC Med. Genet. 12, 160 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  25. Hamer, D. H., Hu, S., Magnuson, V. L., Hu, N. & Pattatucci, A. M. L. A linkage between DNA markers on the X-chromosome and male sexual orientation. Science 261, 321–327 (1993).

    CAS  PubMed  Article  Google Scholar 

  26. Sanders, A. R. et al. Genome-side association study of male sexual orientation. Sci. Rep. 7, 16950 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  27. Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. Vilhjálmsson, B. J. et al. Modeling linkage disequilibrium increases accuracy of polygenic risk scores. Am. J. Hum. Genet. 97, 576–592 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  29. McQueen, M. B. et al. The national longitudinal study of adolescent to adult health (Add Health) sibling pairs genome-wide data. Behav. Genet. 45, 12–23 (2015).

    PubMed  Article  Google Scholar 

  30. Grotzinger, A. D. et al. Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits. Nat. Hum. Behav. 3, 513–525 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  31. Schmitt, D. P. Sociosexuality from Argentina to Zimbabwe: a 48-nation study of sex, culture, and strategies of human mating. Behav. Brain Sci. 28, 247–275 (2005).

    PubMed  Article  Google Scholar 

  32. Wainschtein, P. et al. Recovery of trait heritability from whole genome sequence data. Preprint at bioRxiv (2019).

  33. Rose, M. R. Antagonistic pleiotropy, dominance, and genetic variation. Heredity 48, 63–78 (1982).

    Article  Google Scholar 

  34. Gimelfarb, A. Additive variation maintained under stabilizing selection: a two-locus model for pleiotropy for two quantitative characters. Genetics 112, 717–725 (1986).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. Zhivotovsky, L. A. & Gavrilets, S. Quantitative variability and multilocus polymorphism under epistatic selection. Theor. Popul. Biol. 42, 254–283 (1992).

    CAS  PubMed  Article  Google Scholar 

  36. Hedrick, P. W. Antagonistic pleiotropy and genetic polymorphism: a perspective. Heredity 82, 126–133 (1999).

    Article  Google Scholar 

  37. Connallon, T. & Clark, A. G. Antagonistic versus nonantagonistic models of balancing selection: characterising the relative timescales and hitchhiking effects of partial selective sweeps. Evolution 67, 908–917 (2013).

    PubMed  Article  Google Scholar 

  38. Simons, Y. B., Bullaughey, K., Hudson, R. R. & Sella, G. A population genetic interpretation of GWAS findings for human quantitative traits. PLoS Biol. 16, e2002985 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  39. Barban, N. et al. Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nat. Genet. 48, 1462–1472 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. Camperio Ciani, A., Cermelli, P. & Zanzotto, G. Sexually antagonistic selection in human male homosexuality. PLoS ONE 3, e2282 (2008).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  41. Gavrilets, S. & Rice, W. R. Genetic models of homosexuality: generating testable predictions. Proc. R. Soc. B 273, 3031–3038 (2006).

    PubMed  PubMed Central  Article  Google Scholar 

  42. Altman, D. G. & Bland, J. M. Statistics notes: the normal distribution. Br. Med. J. 310, 298 (1995).

    CAS  Article  Google Scholar 

  43. Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  44. Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  45. Fry, A. et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am. J. Epidemiol. 186, 1026–1034 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  46. Harris, K. M., Halpern, C. T., Haberstick, B. C. & Smolen, A. The national longitudinal study of adolescent health (Add Health) sibling pairs data. Twin Res. Hum. Genet. 16, 391–398 (2013).

    PubMed  Article  Google Scholar 

  47. Lee, A. J. et al. Genetic factors that increase male facial masculinity decrease facial attractiveness of female relatives. Psychol. Sci. 25, 476–484 (2014).

    PubMed  Article  Google Scholar 

  48. McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  50. Loh, P. R. et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat. Genet. 47, 284–290 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  51. Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  52. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  53. 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).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. de Moor, M. H. M. et al. Meta-analysis of genome-wide association studies for personality. Mol. Psychiatry 17, 337–349 (2012).

    PubMed  Article  CAS  Google Scholar 

  55. Lo, M. T. et al. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat. Genet. 49, 152–156 (2017).

    CAS  PubMed  Article  Google Scholar 

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This research was conducted using the UK Biobank Resource under applications 25995. We thank all cohort participants for making this study possible. A.R.S. received funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development specifically to investigate the genetics of sexual orientation: R01HD041563 (A.R.S. PI) and R21HD080410 (A.R.S., E.R.M. MPI). E.R.M., G.W.B. and S.G. are also supported by R21HD080410. No other member of the group received funding specifically for this study, but members of our team received salary funding from organizations as well as their own universities. B.P.Z. received funding from The Australian Research Council (FT160100298). A.A. is supported by ZonMw grant 849200011 from The Netherlands Organisation for Health Research and Development. Study-specific acknowledgements: This research uses data from Add Health, a programme project directed by K.M. Harris (PI) and designed by J.R. Udry, P.S. Bearman and K.M. Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD031921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Information on how to obtain the Add Health data files is available on the Add Health website ( This research uses Add Health GWAS data funded by Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) grants R01 HD073342 to K. M. Harris (PI) and R01 HD060726 to K.M. Harris, J.D. Boardman and M.B. McQueen (MPIs). The authors thank A. Ganna and M. Nivard for analysis work, A. Ganna, J. Perry, M. Nivard, B. Neale, R. Wedow and M. Keller for extensive discussion, and B. von Hippel, F. Barlow, F. Sathirapongsasuti, A. Auton and J. McCreight for comments on manuscript drafts. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations



B.P.Z. and K.J.H.V. conceived and designed the study. M.S., A.A. and R.M. analysed the data and produced the figures. B.P.Z., M.S. and K.J.H.V. wrote the manuscript. A.A., R.M., J.N.L., S.G., G.W.B., E.R.M. and A.R.S. provided significant feedback on the analyses and the manuscript.

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Correspondence to Brendan P. Zietsch.

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The authors declare no competing interests.

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Peer review information Primary Handling Editors: Charlotte Payne and Stavroula Kousta.

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Supplementary information

Supplementary Information

I. Evolutionary simulations. II. Notes on the use of lifetime number of sex partners to index mating advantage. III. Overview of GWAS results for number of opposite-sex sexual partners in heterosexuals; (A) QQ plot, (B) Manhattan plot and (C) list of significant SNPs. IV. Further discussion of evolutionary possibilities regarding SSB. V. Pre-registration and changes to the pre-registered plan. VI. Genomic SEM model used to test potential mediating effects of personality traits. VII. 24 VII. General summary and frequently asked questions. Supplementary references. The Supplementary Information includes Supplementary Figs. 1–7 and Tables 1 and 2.

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Zietsch, B.P., Sidari, M.J., Abdellaoui, A. et al. Genomic evidence consistent with antagonistic pleiotropy may help explain the evolutionary maintenance of same-sex sexual behaviour in humans. Nat Hum Behav 5, 1251–1258 (2021).

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