Determinants of selection in yeast evolved by genome shuffling

Damien Biot-Pelletier,Kane Larue,Dominic Pinel,Vincent J J Martin

doi:10.1186/s13068-018-1283-9

Abstract

BackgroundGenome 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.ResultsWhole 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.ConclusionsWe 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.

Highlights

Genome shuffling (GS) is a widely adopted methodology for the evolutionary engineering of desirable traits in industrially relevant microorganisms
Haploid mutants with tolerance above wild-type levels were selected on gradient plates, which consist in dishes of agar medium displaying increasing concentration of hydrolysate from one end to the other
Descriptive model of evolutionary dynamics in the genome shuffling experiment Based on the proposed model of spent sulfite liquor (SSL) tolerance and on the allele frequency time series obtained from population sequencing (Fig. 2), we propose a model to describe the evolutionary dynamics of our genome shuffling experiment

Summary

Introduction

Genome shuffling (GS) is a widely adopted methodology for the evolutionary engineering of desirable traits in industrially relevant microorganisms. Genome shuffling (GS) is an evolutionary engineering method based on recursive recombination and selection in populations of mutants (Fig. 1) It aims to speed the rate of evolution of desired traits by exploiting sexual, parasexual or artificial recombination to promote purifying selection, positive epistasis, and the accumulation of beneficial mutations, while reducing clonal interference. It has been widely and successfully adopted for the evolutionary engineering of industrial traits in microbes [1]. System-level approaches, like array-comparative genome hybridization [5], RNAseq [5, 6], and whole genome sequencing [6,7,8], as well as proteomics methods [9,10,11] have been used to investigate the complex genetic architecture of strains derived from GS experiments

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