Assortative mating biases marker-based heritability estimators

Richard Border; Sean O’Rourke; Teresa de Candia; Michael E. Goddard; Peter M. Visscher; Loic Yengo; Matt Jones; Matthew C. Keller

doi:10.1038/s41467-022-28294-9

Nature Communications (Feb 2022)

Assortative mating biases marker-based heritability estimators

Richard Border,
Sean O’Rourke,
Teresa de Candia,
Michael E. Goddard,
Peter M. Visscher,
Loic Yengo,
Matt Jones,
Matthew C. Keller

Affiliations

Richard Border: Departments of Neurology and Computer Science, University of California
Sean O’Rourke: Department of Mathematics, University of Colorado Boulder
Teresa de Candia: Institute for Behavioral Genetics, University of Colorado Boulder
Michael E. Goddard: Faculty of Veterinary and Agricultural Science, University of Melbourne
Peter M. Visscher: Institute for Molecular Bioscience, University of Queensland
Loic Yengo: Institute for Molecular Bioscience, University of Queensland
Matt Jones: Department of Psychology and Neuroscience, University of Colorado Boulder
Matthew C. Keller: Institute for Behavioral Genetics, University of Colorado Boulder

DOI: https://doi.org/10.1038/s41467-022-28294-9
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 10

Abstract

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Methods for estimating heritability, the fraction of variance attributable to genetic factors, assume random mating. Here, the authors show that under assortative mating, when mate choice reflects phenotypic similarity, these methods produce overestimates.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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