Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments
Abstract
Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in “non-home” environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.
Data availability
All underlying sequencing data for both barcode sequencing and whole genome sequencing are available from the short read archive (SRA) under accession number PRJNA912754.
Article and author information
Author details
Funding
National Institute of General Medical Sciences (R35 GM131824)
- Gavin Sherlock
National Institute of General Medical Sciences (R35 GM118165)
- Dmitri A Petrov
National Institute of General Medical Sciences (R01 GM104239)
- Michael M Desai
National Science Foundation (PHY-1914916)
- Michael M Desai
National Science Foundation (DMS-1764269)
- Michael M Desai
National Science Foundation
- Milo S Johnson
National Institute of General Medical Sciences (R01 GM110275)
- Gavin Sherlock
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, Chen et al.
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.
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