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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Further reading
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- Evolutionary Biology
Gene duplication drives evolution by providing raw material for proteins with novel functions. An influential hypothesis by Ohno (1970) posits that gene duplication helps genes tolerate new mutations and thus facilitates the evolution of new phenotypes. Competing hypotheses argue that deleterious mutations will usually inactivate gene duplicates too rapidly for Ohno’s hypothesis to work. We experimentally tested Ohno’s hypothesis by evolving one or exactly two copies of a gene encoding a fluorescent protein in Escherichia coli through several rounds of mutation and selection. We analyzed the genotypic and phenotypic evolutionary dynamics of the evolving populations through high-throughput DNA sequencing, biochemical assays, and engineering of selected variants. In support of Ohno’s hypothesis, populations carrying two gene copies displayed higher mutational robustness than those carrying a single gene copy. Consequently, the double-copy populations experienced relaxed purifying selection, evolved higher phenotypic and genetic diversity, carried more mutations and accumulated combinations of key beneficial mutations earlier. However, their phenotypic evolution was not accelerated, possibly because one gene copy rapidly became inactivated by deleterious mutations. Our work provides an experimental platform to test models of evolution by gene duplication, and it supports alternatives to Ohno’s hypothesis that point to the importance of gene dosage.
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