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Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments
Understanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a stron...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321538/ https://www.ncbi.nlm.nih.gov/pubmed/33749796 http://dx.doi.org/10.1093/molbev/msab087 |
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author | Vignogna, Ryan C Buskirk, Sean W Lang, Gregory I |
author_facet | Vignogna, Ryan C Buskirk, Sean W Lang, Gregory I |
author_sort | Vignogna, Ryan C |
collection | PubMed |
description | Understanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a strong positive genetic interaction between specific mutations in KEL1 (P344T) and HSL7 (A695fs) that arose in an experimentally evolved Saccharomyces cerevisiae population. Because this genetic interaction is not phenocopied by gene deletion, it was previously unknown. Using “evolutionary replay” experiments, we identified additional mutations that have positive genetic interactions with the kel1-P344T mutation. We replayed the evolution of this population 672 times from six timepoints. We identified 30 populations where the kel1-P344T mutation reached high frequency. We performed whole-genome sequencing on these populations to identify genes in which mutations arose specifically in the kel1-P344T background. We reconstructed mutations in the ancestral and kel1-P344T backgrounds to validate positive genetic interactions. We identify several genetic interactors with KEL1, we validate these interactions by reconstruction experiments, and we show these interactions are not recapitulated by loss-of-function mutations. Our results demonstrate the power of experimental evolution to identify genetic interactions that are positive, allele specific, and not readily detected by other methods, shedding light on an underexplored region of the yeast genetic interaction network. |
format | Online Article Text |
id | pubmed-8321538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83215382021-07-30 Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments Vignogna, Ryan C Buskirk, Sean W Lang, Gregory I Mol Biol Evol Discoveries Understanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a strong positive genetic interaction between specific mutations in KEL1 (P344T) and HSL7 (A695fs) that arose in an experimentally evolved Saccharomyces cerevisiae population. Because this genetic interaction is not phenocopied by gene deletion, it was previously unknown. Using “evolutionary replay” experiments, we identified additional mutations that have positive genetic interactions with the kel1-P344T mutation. We replayed the evolution of this population 672 times from six timepoints. We identified 30 populations where the kel1-P344T mutation reached high frequency. We performed whole-genome sequencing on these populations to identify genes in which mutations arose specifically in the kel1-P344T background. We reconstructed mutations in the ancestral and kel1-P344T backgrounds to validate positive genetic interactions. We identify several genetic interactors with KEL1, we validate these interactions by reconstruction experiments, and we show these interactions are not recapitulated by loss-of-function mutations. Our results demonstrate the power of experimental evolution to identify genetic interactions that are positive, allele specific, and not readily detected by other methods, shedding light on an underexplored region of the yeast genetic interaction network. Oxford University Press 2021-03-22 /pmc/articles/PMC8321538/ /pubmed/33749796 http://dx.doi.org/10.1093/molbev/msab087 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Discoveries Vignogna, Ryan C Buskirk, Sean W Lang, Gregory I Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments |
title | Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments |
title_full | Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments |
title_fullStr | Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments |
title_full_unstemmed | Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments |
title_short | Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments |
title_sort | exploring a local genetic interaction network using evolutionary replay experiments |
topic | Discoveries |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321538/ https://www.ncbi.nlm.nih.gov/pubmed/33749796 http://dx.doi.org/10.1093/molbev/msab087 |
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