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Imprint of assortative mating on the human genome


Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1,2,3,4,5 and has evolutionary consequences6,7,8. Under Fisher's classical theory6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes.

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Fig. 1: Schematic of the effect of assortative mating on the correlation between trait-associated alleles.
Fig. 2: Estimates of assortative mating-induced GPD among TIAs in three independent cohorts.
Fig. 3: Correlation of genetic predictors of 32 complex traits and diseases in 18,984 mates pairs as function of within-individual estimates of GPD in alleles associated with these traits.

Data availability

We used genotypic data from the Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA: dbGaP phs000674.v2.p2), genotypic and phenotypic data from the Health and Retirement Study (HRS: dbGaP phs000428.v1.p1), and genotypic and phenotypic data from the UKB under project 12505.


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This research was supported by the Australian Research Council (DP130102666, DP160103860 and DP160102400), Australian National Health and Medical Research Council (1078037, 1078901, 1103418, 1107258, 1127440 and 1113400), National Institutes of Health (grants R01AG042568, P01GM099568 and R01MH100141) and Sylvia and Charles Viertel Charitable Foundation. The GERA study was supported by grant RC2 AG036607 from the National Institutes of Health, and grants from the Robert Wood Johnson Foundation, Ellison Medical Foundation, Wayne and Gladys Valley Foundation and Kaiser Permanente. The authors thank members of the Kaiser Permanente Medical Care Plan, Northern California Region who generously agreed to participate in the Kaiser Permanente Research Program on Genes, Environment and Health. This research has been conducted using the UKB Resource under project 12505. We thank B. Hill for helpful comments and suggestions on the manuscript. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information




P.M.V., L.Y., M.R.R., J.Y. and M.E.G. conceived and designed the study. L.Y., M.T. and N.R.W. curated the summary statistics. L.Y. and P.M.V. derived the theory. Y.Y., M.T., J.G., K.E.K. and L.Y. performed the mate pairs analyses. M.C.K., P.T., D.J.B. and D.C. helped to develop the methodology and interpret the results. P.M.V., N.R.W., M.R.R. and L.Y. performed the sibling pairs analyses. K.E.K. and L.Y. performed quality control of the UKB data. L.Y. and M.R.R. performed statistical analyses and simulations. L.Y. and P.M.V. wrote the manuscript with the participation of all authors.

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Correspondence to Loic Yengo or Peter M. Visscher.

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Supplementary Tables 1–3, Supplementary Figures 1–5, Supplementary Notes 1–4

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Yengo, L., Robinson, M.R., Keller, M.C. et al. Imprint of assortative mating on the human genome. Nat Hum Behav 2, 948–954 (2018).

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