Ethanol stress induces siRNA-mediated epimutations and phenotypic variability in fission yeast
Villalba de la Pena, M.; Sarkies, P.
Show abstract
Epigenetic information is required for the maintenance of gene expression states through cell division. Some epigenetic information can also persist through generations, raising the possibility that epigenetic differences may arise in populations and contribute to evolutionary processes such as drift and natural selection. Evaluating this requires characterising the properties of such epimutations, so that their rate, stability and genome-wide distribution can be assessed. Recent experiments in many organisms have demonstrated that epimutations occur, but have limited stability relative to DNA sequence mutations. However, the extent to which epimutations contribute to evolution is still unclear, in part because it is not clear whether epimutations respond dynamically to environmental conditions. Here, we use the fission yeast S. pombe, in which evolutionarily relevant epimutations have been observed, but not yet systematically characterised, to test whether a physiologically relevant stress, ethanol exposure, leads to changes in the properties of epimutations. Using laboratory evolution experiments with repeated population bottlenecks to minimise selection, we show that epimutations associated with changes in small interfering (si)RNAs occur at a greater rate in ethanol. Ethanol-induced epimutations are enriched at transposable element loci and correlate with changes in transposon expression. Ethanol exposure also increases gene expression noise genome-wide and variability in growth rate; importantly, both these increases are suppressed in mutants lacking siRNAs. Together, these results demonstrate that stress can alter the generation of heritable epigenetic information, and suggest that siRNAs may have a role in promoting phenotypic variability in response to environmental stress.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Phenotypic and genotypic consequences of CRISPR/Cas9 editing of the replication origins in the rDNA of Saccharomyces cerevisiae 94%
- Contrasting mutation patterns in haploid and diploid cells from two yeast species 93%
- Hotspot of de novo telomere addition stabilizes linear amplicons in yeast grown in sulfate-limiting conditions 93%
Similar papers in this journal
- SSD1 suppresses phenotypes induced by the lack of Elongator-dependent tRNA modifications 93%
- Temperature preference biases parental genome retention during hybrid evolution 93%
- Aneuploidy alleviates the cell proliferation defect caused by mutations affecting origin licensing in Saccharomyces cerevisiae 93%
Similar papers in this journal
- Strength of selection potentiates distinct adaptive responses in an evolution experiment with outcrossing yeast 93%
- Directed evolution for cell separation in natural isolates of budding yeast reveals selection to deactivate AMN1 and the Rim101 pathway in haploids and selection in favor of Hawthorne's deletion in diploids 92%
- Genetic suppression interactions are highly conserved across genetic backgrounds 92%
Similar papers in this journal
- Population selection and sequencing of C. elegans wild isolates identifies a region on chromosome III affecting starvation resistance 91%
- Genome Profiling for Aflatoxin B1 Resistance in Saccharomyces cerevisiae Reveals a Role for the CSM2/SHU Complex in Tolerance of Aflatoxin B1-associated DNA Damage 90%
- Complex pleiotropic genetic architecture of evolved heat stress and oxidative stress resistance in the nematode Caenorhabditis remanei 90%
Similar papers in this journal
- Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae 92%
- The environmental stress response causes ribosome loss in aneuploid yeast cells. 91%
- Gene loss, repression, amplification, and horizontal acquisition shape galactose/melibiose metabolism in fission yeast 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.