Polygenic adaptation after a sudden change in environment

  1. Laura Katharine Hayward  Is a corresponding author
  2. Guy Sella  Is a corresponding author
  1. Institute of Science and Technology Austria, Austria
  2. Columbia University, United States

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.

Article and author information

Author details

  1. 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.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4445-8067
  2. 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.
    ORCID icon "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.

Reviewing Editor

  1. Graham Coop, University of California, Davis, United States

Version history

  1. Preprint posted: October 3, 2019 (view preprint)
  2. Received: January 19, 2021
  3. Accepted: July 18, 2022
  4. Accepted Manuscript published: September 26, 2022 (version 1)
  5. Accepted Manuscript updated: September 27, 2022 (version 2)
  6. Version of Record published: November 23, 2022 (version 3)

Copyright

© 2022, Hayward & Sella

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.

Metrics

  • 1,871
    Page views
  • 422
    Downloads
  • 15
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Laura Katharine Hayward
  2. Guy Sella
(2022)
Polygenic adaptation after a sudden change in environment
eLife 11:e66697.
https://doi.org/10.7554/eLife.66697

Share this article

https://doi.org/10.7554/eLife.66697

Further reading

    1. Evolutionary Biology
    Jordan Little, Maria Chikina, Nathan L Clark
    Research Article

    Co-functional proteins tend to have rates of evolution that covary over time. This correlation between evolutionary rates can be measured over the branches of a phylogenetic tree through methods such as evolutionary rate covariation (ERC), and then used to construct gene networks by the identification of proteins with functional interactions. The cause of this correlation has been hypothesized to result from both compensatory coevolution at physical interfaces and nonphysical forces such as shared changes in selective pressure. This study explores whether coevolution due to compensatory mutations has a measurable effect on the ERC signal. We examined the difference in ERC signal between physically interacting protein domains within complexes compared to domains of the same proteins that do not physically interact. We found no generalizable relationship between physical interaction and high ERC, although a few complexes ranked physical interactions higher than nonphysical interactions. Therefore, we conclude that coevolution due to physical interaction is weak, but present in the signal captured by ERC, and we hypothesize that the stronger signal instead comes from selective pressures on the protein as a whole and maintenance of the general function.

    1. Computational and Systems Biology
    2. Evolutionary Biology
    Roee Ben Nissan, Eliya Milshtein ... Ron Milo
    Research Article

    Synthetic autotrophy is a promising avenue to sustainable bioproduction from CO2. Here, we use iterative laboratory evolution to generate several distinct autotrophic strains. Utilising this genetic diversity, we identify that just three mutations are sufficient for Escherichia coli to grow autotrophically, when introduced alongside non-native energy (formate dehydrogenase) and carbon-fixing (RuBisCO, phosphoribulokinase, carbonic anhydrase) modules. The mutated genes are involved in glycolysis (pgi), central-carbon regulation (crp), and RNA transcription (rpoB). The pgi mutation reduces the enzyme’s activity, thereby stabilising the carbon-fixing cycle by capping a major branching flux. For the other two mutations, we observe down-regulation of several metabolic pathways and increased expression of native genes associated with the carbon-fixing module (rpiB) and the energy module (fdoGH), as well as an increased ratio of NADH/NAD+ - the cycle’s electron-donor. This study demonstrates the malleability of metabolism and its capacity to switch trophic modes using only a small number of genetic changes and could facilitate transforming other heterotrophic organisms into autotrophs.