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Seamless site-directed mutagenesis of the Saccharomyces cerevisiae genome using CRISPR-Cas9.

Author(s): Biot-Pelletier D, Martin VJ

J Biol Eng. 2016;10:6 Authors: Biot-Pelletier D, Martin VJ

Article GUID: 27134651

Determinants of selection in yeast evolved by genome shuffling.

Author(s): Biot-Pelletier D, Pinel D, Larue K, Martin VJJ

Biotechnol Biofuels. 2018;11:282 Authors: Biot-Pelletier D, Pinel D, Larue K, Martin VJJ

Article GUID: 30356826


Title:Determinants of selection in yeast evolved by genome shuffling.
Authors:Biot-Pelletier DPinel DLarue KMartin VJJ
Link:https://www.ncbi.nlm.nih.gov/pubmed/30356826?dopt=Abstract
DOI:10.1186/s13068-018-1283-9
Category:Biotechnol Biofuels
PMID:30356826
Dept Affiliation: GENOMICS
1 1Department of Biology, Centre for Structural and Functional Genomics, Centre for Applied Synthetic Biology, Concordia University, 7141 Sherbrooke Street West, Montreal, QC H4B 1R6 Canada.
2 2Present Address: Lallemand Inc., Montréal, QC H4P 2R2 Canada.
3 3Present Address: Amyris Inc, Emeryville, CA 94608 USA.
4 Present Address: Charles River Laboratories, Senneville, QC H9X 3R3 Canada.

Description:

Determinants of selection in yeast evolved by genome shuffling.

Biotechnol Biofuels. 2018;11:282

Authors: Biot-Pelletier D, Pinel D, Larue K, Martin VJJ

Abstract

Background: 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.

Results: 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.

Conclusions: 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.

PMID: 30356826 [PubMed]