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Evidence of directional and stabilizing selection in contemporary humans
Edited by Aravinda Chakravarti, Johns Hopkins University School of Medicine, Baltimore, MD, and approved November 3, 2017 (received for review May 1, 2017)
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Significance
Combining high-throughput molecular genetic data with extensive phenotyping enables the direct study of natural selection in humans. We see firsthand how and at what rates contemporary human populations are evolving. Here we demonstrate that the genetic variants associated with several traits, including age at first birth in females and body-mass index in males, are also associated with reproductive success. In addition, for several traits, we demonstrate that individuals at either extreme of the phenotypic range have reduced fitness—the hallmark of stabilizing selection. Overall, the data are indicative of a moving optimum model for contemporary evolution of human quantitative traits.
Abstract
Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.
Footnotes
- ↵1To whom correspondence should be addressed. Email: peter.visscher{at}uq.edu.au.
Author contributions: J.S.S., M.R.R., K.R.T., and P.M.V. designed research; J.S.S. and J.S. performed research; J.S.S. and J.S. analyzed data; and J.S.S. and P.M.V. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1707227114/-/DCSupplemental.
Published under the PNAS license.