Imprint of assortative mating on the human genome

Loic Yengo (), Matthew R. Robinson, Matthew C. Keller, Kathryn E. Kemper, Yuanhao Yang, Maciej Trzaskowski, Jacob Gratten, Patrick Turley, David Cesarini, Daniel J. Benjamin, Naomi R. Wray, Michael E. Goddard, Jian Yang and Peter M. Visscher ()
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Loic Yengo: The University of Queensland
Matthew R. Robinson: The University of Queensland
Matthew C. Keller: University of Colorado at Boulder
Kathryn E. Kemper: The University of Queensland
Yuanhao Yang: The University of Queensland
Maciej Trzaskowski: The University of Queensland
Jacob Gratten: The University of Queensland
Patrick Turley: Massachusetts General Hospital
Daniel J. Benjamin: National Bureau of Economic Research
Naomi R. Wray: The University of Queensland
Michael E. Goddard: University of Melbourne
Jian Yang: The University of Queensland
Peter M. Visscher: The University of Queensland

Nature Human Behaviour, 2018, vol. 2, issue 12, 948-954

Abstract: Abstract Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1–5 and has evolutionary consequences6–8. 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.

Date: 2018
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DOI: 10.1038/s41562-018-0476-3

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