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.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

Abstract

The genetic architecture of human reproductive behavior—age at first birth (AFB) and number of children ever born (NEB)—has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Manhattan plots of SNPs for age at first birth and number of children ever born in single-genomic-control meta-analysis.
Figure 2: Quantile–quantile plots.
Figure 3: Genetic overlap between AFB or NEB and other related traits.

Similar content being viewed by others

References

  1. Elks, C.E. et al. Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies. Nat. Genet. 42, 1077–1085 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Perry, J.R.B. et al. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 514, 92–97 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Rahmioglu, N. et al. Genetic variants underlying risk of endometriosis: insights from meta-analysis of eight genome-wide association and replication datasets. Hum. Reprod. Update 20, 702–716 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Day, F.R. et al. Causal mechanisms and balancing selection inferred from genetic associations with polycystic ovary syndrome. Nat. Commun. 6, 8464 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Mehta, D. et al. Evidence for genetic overlap between schizophrenia and age at first birth in women. JAMA Psychiatry 73, 497–505 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Mills, M.C. & Tropf, F.C. The biodemography of fertility: a review and future research frontiers. Kolner Z. Soz. Sozpsychol. 67 (Suppl. 1), 397–424 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Mills, M., Rindfuss, R.R., McDonald, P. & te Velde, E. Why do people postpone parenthood? Reasons and social policy incentives. Hum. Reprod. Update 17, 848–860 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Boivin, J., Bunting, L., Collins, J.A. & Nygren, K.G. International estimates of infertility prevalence and treatment-seeking: potential need and demand for infertility medical care. Hum. Reprod. 22, 1506–1512 (2007).

    Article  PubMed  Google Scholar 

  9. Mascarenhas, M.N., Flaxman, S.R., Boerma, T., Vanderpoel, S. & Stevens, G.A. National, regional, and global trends in infertility prevalence since 1990: a systematic analysis of 277 health surveys. PLoS Med. 9, e1001356 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Venkatesh, T., Suresh, P.S. & Tsutsumi, R. New insights into the genetic basis of infertility. Appl. Clin. Genet. 7, 235–243 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Day, F.R. et al. Physical and neurobehavioral determinants of reproductive onset and success. Nat. Genet. 48, 617–623 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Balbo, N., Billari, F.C. & Mills, M.C. Fertility in advanced societies: a review of research. Eur. J. Popul. 29, 1–38 (2012).

    Article  PubMed  Google Scholar 

  13. Tropf, F.C. et al. Human fertility, molecular genetics, and natural selection in modern societies. PLoS One 10, e0126821 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Fisher, R.A. The Genetical Theory of Natural Selection (Oxford University Press, 1930).

  15. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    CAS  PubMed  Google Scholar 

  16. van der Most, P.J. et al. QCGWAS: a flexible R package for automated quality control of genome-wide association results. Bioinformatics 30, 1185–1186 (2014).

    Article  CAS  PubMed  Google Scholar 

  17. Winkler, T.W. et al. Quality control and conduct of genome-wide association meta-analyses. Nat. Protoc. 9, 1192–1212 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Lango Allen, H. et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467, 832–838 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. 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  Google Scholar 

  20. Wood, A.R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173–1186 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Purcell, S.M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

    Article  CAS  PubMed  Google Scholar 

  22. Liu, J.Z. et al. A versatile gene-based test for genome-wide association studies. Am. J. Hum. Genet. 87, 139–145 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mishra, A. & Macgregor, S. VEGAS2: software for more flexible gene-based testing. Twin Res. Hum. Genet. 18, 86–91 (2015).

    Article  PubMed  Google Scholar 

  24. Vaez, A. et al. In silico post genome-wide association studies analysis of C-reactive protein loci suggests an important role for interferons. Circ Cardiovasc Genet 8, 487–497 (2015).

    Article  CAS  PubMed  Google Scholar 

  25. ENCODE Project Consortium. ENCODE (ENCyclopedia Of DNA Elements) Project. Science 306, 636–640 (2004).

  26. Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Boyle, A.P. et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22, 1790–1797 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zhernakova, D. et al. Hypothesis-free identification of modulators of genetic risk factors. Preprint at bioRxiv http://dx.doi.org/10.1101/033217 (2015).

  29. Bonder, M.J. et al. Disease variants alter transcription factor levels and methylation of their binding sites. Preprint at bioRxiv http://dx.doi.org/10.1101/033084 (2015).

  30. Tranchevent, L.C. et al. ENDEAVOUR update: a web resource for gene prioritization in multiple species. Nucleic Acids Res. 36, W377–W384 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pers, T.H., Dworzyn´ski, P., Thomas, C.E., Lage, K. & Brunak, S. MetaRanker 2.0: a web server for prioritization of genetic variation data. Nucleic Acids Res. 41, W104–W108 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Chen, J., Bardes, E.E., Aronow, B.J. & Jegga, A.G. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res. 37, W305–W311 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Pers, T.H. et al. Biological interpretation of genome-wide association studies using predicted gene functions. Nat. Commun. 6, 5890 (2015).

    Article  CAS  PubMed  Google Scholar 

  34. Euesden, J., Lewis, C.M. & O'Reilly, P.F. PRSice: Polygenic Risk Score software. Bioinformatics 31, 1466–1468 (2015).

    Article  CAS  PubMed  Google Scholar 

  35. Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Willer, C.J. et al. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45, 1274–1283 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Locke, A.E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Rietveld, C.A. et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc. Natl. Acad. Sci. USA 111, 13790–13794 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Day, F.R. et al. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. Nat. Genet. 47, 1294–1303 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Perry, J.R. et al. A genome-wide association study of early menopause and the combined impact of identified variants. Hum. Mol. Genet. 22, 1465–1472 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Fang, W.-L. et al. CREB coactivator CRTC2/TORC2 and its regulator calcineurin crucially mediate follicle-stimulating hormone and transforming growth factor β1 upregulation of steroidogenesis. J. Cell. Physiol. 227, 2430–2440 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. Cao, G. et al. Molecular cloning and characterization of a novel human cAMP response element–binding (CREB) gene (CREB4). J. Hum. Genet. 47, 373–376 (2002).

    Article  CAS  PubMed  Google Scholar 

  44. El-Alfy, M. et al. Stage-specific expression of the Atce1/Tisp40α isoform of CREB3L4 in mouse spermatids. J. Androl. 27, 686–694 (2006).

    Article  CAS  PubMed  Google Scholar 

  45. Adham, I.M. et al. Reduction of spermatogenesis but not fertility in Creb3l4-deficient mice. Mol. Cell. Biol. 25, 7657–7664 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. McAllister, J.M. et al. Overexpression of a DENND1A isoform produces a polycystic ovary syndrome theca phenotype. Proc. Natl. Acad. Sci. USA 111, E1519–E1527 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. O'Bryan, M.K. et al. RBM5 is a male germ cell splicing factor and is required for spermatid differentiation and male fertility. PLoS Genet. 9, e1003628 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Tsukamoto, S. et al. Functional analysis of lysosomes during mouse preimplantation embryo development. J. Reprod. Dev. 59, 33–39 (2013).

    CAS  PubMed  Google Scholar 

  49. Szucs, M., Osvath, P., Laczko, I. & Jakab, A. Adequacy of hyaluronan binding assay and a new fertility index derived from it for measuring of male fertility potential and the efficacy of supplement therapy. Andrologia 47, 519–524 (2015).

    Article  CAS  PubMed  Google Scholar 

  50. Buensuceso, A.V. et al. Ephrin-A5 is required for optimal fertility and a complete ovulatory response to gonadotropins in the female mouse. Endocrinology 157, 942–955 (2016).

    Article  CAS  Google Scholar 

  51. Jisa, E. & Jungbauer, A. Kinetic analysis of estrogen receptor homo- and heterodimerization in vitro. J. Steroid Biochem. Mol. Biol. 84, 141–148 (2003).

    Article  CAS  PubMed  Google Scholar 

  52. O'Donnell, L., Robertson, K.M., Jones, M.E. & Simpson, E.R. Estrogen and spermatogenesis. Endocr. Rev. 22, 289–318 (2001).

    Article  CAS  PubMed  Google Scholar 

  53. Ly-Huynh, J.D. et al. Importin α2–interacting proteins with nuclear roles during mammalian spermatogenesis. Biol. Reprod. 85, 1191–1202 (2011).

    Article  CAS  PubMed  Google Scholar 

  54. Varshney, G.K. et al. CRISPRz: a database of zebrafish validated sgRNAs. Nucleic Acids Res. 44, D1, D822–D826 (2016).

    Article  CAS  Google Scholar 

  55. Menken, J. Age and fertility: how late can you wait? Demography 22, 469–483 (1985).

    Article  CAS  PubMed  Google Scholar 

  56. Manolio, T.A., Brooks, L.D. & Collins, F.S. A HapMap harvest of insights into the genetics of common disease. J. Clin. Invest. 118, 1590–1605 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362–9367 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Okkelman, I.A., Sukaeva, A.Z., Kirukhina, E.V., Korneenko, T.V. & Pestov, N.B. Nuclear translocation of lysyl oxidase is promoted by interaction with transcription repressor p66β. Cell Tissue Res. 358, 481–489 (2014).

    Article  CAS  PubMed  Google Scholar 

  59. Joshi, N.R. et al. Altered expression of microRNA-451 in eutopic endometrium of baboons (Papio anubis) with endometriosis. Hum. Reprod. 30, 2881–2891 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Franklin, R.B. et al. Human ZIP1 is a major zinc uptake transporter for the accumulation of zinc in prostate cells. J. Inorg. Biochem. 96, 435–442 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Lisle, R.S., Anthony, K., Randall, M.A. & Diaz, F.J. Oocyte–cumulus cell interactions regulate free intracellular zinc in mouse oocytes. Reproduction 145, 381–390 (2013).

    Article  CAS  PubMed  Google Scholar 

  62. Shan, B. et al. Association of DENND1A gene polymorphisms with polycystic ovary syndrome: a meta-analysis. J. Clin. Res. Pediatr. Endocrinol. 8, 135–143 (2016).

    Article  Google Scholar 

  63. Impera, L. et al. A novel fusion 5′AFF3/3′BCL2 originated from a t(2;18)(q11.2;q21.33) translocation in follicular lymphoma. Oncogene 27, 6187–6190 (2008).

    Article  CAS  PubMed  Google Scholar 

  64. Urano, A. et al. Infertility with defective spermiogenesis in mice lacking AF5q31, the target of chromosomal translocation in human infant leukemia. Mol. Cell. Biol. 25, 6834–6845 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Reese, K.L. et al. Acidic hyaluronidase activity is present in mouse sperm and is reduced in the absence of SPAM1: evidence for a role for hyaluronidase 3 in mouse and human sperm. Mol. Reprod. Dev. 77, 759–772 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Heath, E., Sablitzky, F. & Morgan, G.T. Subnuclear targeting of the RNA-binding motif protein RBM6 to splicing speckles and nascent transcripts. Chromosome Res. 18, 851–872 (2010).

    Article  CAS  PubMed  Google Scholar 

  67. Kamura, T. et al. Cytoplasmic ubiquitin ligase KPC regulates proteolysis of p27Kip1 at G1 phase. Nat. Cell Biol. 6, 1229–1235 (2004).

    Article  CAS  PubMed  Google Scholar 

  68. Kato, J.Y., Matsuoka, M., Polyak, K., Massagué, J. & Sherr, C.J. Cyclic AMP–induced G1 phase arrest mediated by an inhibitor (p27Kip1) of cyclin-dependent kinase 4 activation. Cell 79, 487–496 (1994).

    Article  CAS  PubMed  Google Scholar 

  69. Bagley, D.C., Paradkar, P.N., Kaplan, J. & Ward, D.M. Mon1a protein acts in trafficking through the secretory apparatus. J. Biol. Chem. 287, 25577–25588 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Sakamoto, O. et al. Role of macrophage-stimulating protein and its receptor, RON tyrosine kinase, in ciliary motility. J. Clin. Invest. 99, 701–709 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Zhang, C. et al. Molecular mechanisms that drive estradiol-dependent burst firing of Kiss1 neurons in the rostral periventricular preoptic area. Am. J. Physiol. Endocrinol. Metab. 305, E1384–E1397 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Ponglikitmongkol, M., Green, S. & Chambon, P. Genomic organization of the human oestrogen receptor gene. EMBO J. 7, 3385–3388 (1988).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. de Mattos, C.S. et al. ESR1 and ESR2 gene polymorphisms are associated with human reproduction outcomes in Brazilian women. J. Ovarian Res. 7, 114 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Lamp, M. et al. Polymorphisms in ESR1, ESR2 and HSD17B1 genes are associated with fertility status in endometriosis. Gynecol. Endocrinol. 27, 425–433 (2011).

    Article  CAS  PubMed  Google Scholar 

  75. Chiu, Y.-C. et al. Foxp2 regulates neuronal differentiation and neuronal subtype specification. Dev. Neurobiol. 74, 723–738 (2014).

    Article  CAS  PubMed  Google Scholar 

  76. Alves, M.G. et al. Metabolic fingerprints in testicular biopsies from type 1 diabetic patients. Cell Tissue Res. 362, 431–440 (2015).

    Article  CAS  PubMed  Google Scholar 

  77. Mojiminiyi, O.A., Safar, F.H., Al Rumaih, H. & Diejomaoh, M. Variations in alanine aminotransferase levels within the normal range predict metabolic and androgenic phenotypes in women of reproductive age. Scand. J. Clin. Lab. Invest. 70, 554–560 (2010).

    Article  CAS  PubMed  Google Scholar 

  78. Van Maldergem, L. et al. Revisiting the craniosynostosis-radial ray hypoplasia association: Baller–Gerold syndrome caused by mutations in the RECQL4 gene. J. Med. Genet. 43, 148–152 (2016).

    Google Scholar 

  79. Ruan, Y., Cheng, M., Ou, Y., Oko, R. & van der Hoorn, F.A. Ornithine decarboxylase antizyme Oaz3 modulates protein phosphatase activity. J. Biol. Chem. 286, 29417–29427 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Zhu, Z. et al. Dominance genetic variation contributes little to the missing heritability for human complex traits. Am. J. Hum. Genet. 96, 377–385 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Shen, X. et al. Simple multi-trait analysis identifies novel loci associated with growth and obesity measures. Preprint at bioRxiv http://dx.doi.org/10.1101/022269 (2015).

  84. Okbay, A. et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat. Genet. 48, 624–633 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Winkler, T.W. et al. EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data. Bioinformatics 31, 259–261 (2015).

    Article  CAS  PubMed  Google Scholar 

  86. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  87. Mostafavi, S., Ray, D., Warde-Farley, D., Grouios, C. & Morris, Q. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function. Genome Biol. 9 (Suppl. 1), S4 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Saito, R. et al. A travel guide to Cytoscape plugins. Nat. Methods 9, 1069–1076 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Montojo, J. et al. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics 26, 2927–2928 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Kohler, H.-P., Rodgers, J.L. & Christensen, K. Is fertility behavior in our genes? Findings from a Danish twin study. Popul. Dev. Rev. 25, 253–288 (1999).

    Article  Google Scholar 

  92. Tropf, F.C., Barban, N., Mills, M.C., Snieder, H. & Mandemakers, J.J. Genetic influence on age at first birth of female twins born in the UK, 1919–68. Popul. Stud. (Camb.) 69, 129–145 (2015).

    Article  Google Scholar 

  93. Voight, B.F., Kudaravalli, S., Wen, X. & Pritchard, J.K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

For full acknowledgments, see the Supplementary Note. Funding to lead this consortium was provided by grants awarded to M.C.M.: ERC Consolidator Grant SOCIOGENOME (615603), a Dutch Science Foundation (NWO) grant (VIDI grant 452-10-012), a UK ESRC/NCRM SOCGEN grant (ES/N011856/1), the European Union's FP7 Families And Societies project (320116), and the Wellcome Trust ISSF and John Fell Fund. M.d.H. was supported by grants from the Swedish Research Council (2015-03657) and the Swedish Heart-Lung Foundation (20140543). Research was carried out in collaboration with the Social Science Genetic Association Consortium (SSGAC), with funding from the US National Science Foundation (EAGER: 'Workshop for the Formation of a Social Science Genetic Association Consortium'), a Supplementary grant from the National Institutes of Health Office of Behavioral and Social Science Research, the Ragnar Söderberg Foundation (E9/11), the Swedish Research Council (421-2013-1061), the Jan Wallander and Tom Hedelius Foundation, an ERC Consolidator Grant (647648 EdGe), the Pershing Square Fund of the Foundations of Human Behavior and the NIA/NIH through grants P01-AG005842, P01-AG005842-20S2, P30-AG012810 and T32-AG000186-23 to NBER and R01-AG042568-02 to the University of Southern California. X.S. was supported by a grant from the Swedish Research Council (537-2014-371). We thank X. Ding for research assistance, N. Pirastu, K. Coward and L. Layman for valuable comments, and the University of Oxford Advanced Research Computing (ARC) facility (http://dx.doi.org/10.5281/zenodo.22558). This research has been conducted using the UK Biobank Resource.

Author information

Authors and Affiliations

Authors

Consortia

Contributions

Senior investigators who led writing, analysis and study design: M.C.M., H. Snieder and M.d.H. Senior investigators who participated in study design: P.D.K., D.J.B. and D.C. Junior investigator who contributed to the study design and management: N. Barban. Population stratification: N. Barban and F.C.T. Genetic correlations and polygenic score prediction: N. Barban. Meta-analysis and quality control: N. Barban, R.d.V., J.J.M. and I.M.N. Biological annotation: R.J., M.d.H. and A.V. Sex-specific genetic effects: N. Barban and F.C.T. Bivariate and conditional analysis of the two fertility traits: X.S., J.F.W. and D.I.C. Gene-based analysis V.T. and S.W.v.d.L. Authors not listed contributed to recruitment, genotyping or data processing for the meta-analysis (Supplementary Table 43).

Corresponding authors

Correspondence to Nicola Barban, Marcel den Hoed, Harold Snieder or Melinda C Mills.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–37 and Supplementary Note. (PDF 11303 kb)

Supplementary Tables 1–43

Supplementary Tables 1–43. (XLS 12508 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Barban, N., Jansen, R., de Vlaming, R. et al. Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nat Genet 48, 1462–1472 (2016). https://doi.org/10.1038/ng.3698

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3698

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