Polygenic adaptation after a sudden change in environment

Abstract
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Abstract

Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Notably, we describe the two phases of the allele dynamics: The first is a rapid phase, in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, ultimately leading to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, key results should hold in more general settings, and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.

Data availability

No new data was collected for this study. Data for this study were generated by computer simulations run by the authors. These simulations output summaries of several quantities of interest, as well as the standard error of these quantities. Source data files with the results of these simulations have been provided for Figs. 2B-C, 4, 5, 7A and 8.

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Author details

Laura Katharine Hayward

Institute of Science and Technology Austria, Maria Gugging, Austria

For correspondence
lauhayward@gmail.com

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-4445-8067
Guy Sella

Department of Biological Sciences, Columbia University, New York, United States

For correspondence
gs2747@columbia.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-5239-7930

Funding

National Institutes of Health (GM115889)

Guy Sella

National Institutes of Health (GM115889)

Laura Katharine Hayward

National Institutes of Health (GM121372)

Laura Katharine Hayward

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.