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• W2897828290 abstract "Genome shuffling (GS) is a widely adopted methodology for the evolutionary engineering of desirable traits in industrially relevant microorganisms. We have previously used genome shuffling to generate a strain of Saccharomyces cerevisiae that is tolerant to the growth inhibitors found in a lignocellulosic hydrolysate. In this study, we expand on previous work by performing a population-wide genomic survey of our genome shuffling experiment and dissecting the molecular determinants of the evolved phenotype. Whole population whole-genome sequencing was used to survey mutations selected during the experiment and extract allele frequency time series. Using growth curve assays on single point mutants and backcrossed derivatives, we explored the genetic architecture of the selected phenotype and detected examples of epistasis. Our results reveal cohorts of strongly correlated mutations, suggesting prevalent genetic hitchhiking and the presence of pre-existing founder mutations. From the patterns of apparent selection and the results of direct phenotypic assays, our results identify key driver mutations and deleterious hitchhikers. We use these data to propose a model of inhibitor tolerance in our GS mutants. Our results also suggest a role for compensatory evolution and epistasis in our genome shuffling experiment and illustrate the impact of historical contingency on the outcomes of evolutionary engineering." @default.
• W2897828290 created "2018-10-26" @default.
• W2897828290 creator A5028043748 @default.
• W2897828290 creator A5030960608 @default.
• W2897828290 creator A5056690786 @default.
• W2897828290 creator A5067764241 @default.
• W2897828290 date "2018-10-16" @default.
• W2897828290 modified "2023-10-18" @default.
• W2897828290 title "Determinants of selection in yeast evolved by genome shuffling" @default.
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• W2897828290 doi "https://doi.org/10.1186/s13068-018-1283-9" @default.
• W2897828290 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6190656" @default.
• W2897828290 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30356826" @default.
• W2897828290 hasPublicationYear "2018" @default.
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