An upsurge in the bioeconomy drives the need for engineering microorganisms with increasingly complex phenotypes. Gains in productivity of industrial microbes depend on the development of improved strains. Classical strain improvement programmes for the generation, screening and isolation of such mutant strains have existed for several decades. An alternative to traditional strain improvement methods, genome shuffling, allows the directed evolution of whole organisms via recursive recombination at the genome level. This review deals chiefly with the technical aspects of genome shuffling. It first presents the diversity of organisms and phenotypes typically evolved using this technology and then reviews available sources of genetic diversity and recombination methodologies. Analysis of the literature reveals that genome shuffling has so far been restricted to microorganisms, both prokaryotes and eukaryotes, with an overepresentation of antibiotics- and biofuel-producing microbes. Mutagenesis is the main source of genetic diversity, with few studies adopting alternative strategies. Recombination is usually done by protoplast fusion or sexual recombination, again with few exceptions. For both diversity and recombination, prospective methods that have not yet been used are also presented. Finally, the potential of genome shuffling for gaining insight into the genetic basis of complex phenotypes is also discussed.

CRISPR assisted homology directed repair enables the introduction of virtually any modification to the Saccharomyces cerevisiae genome. Of obvious interest is the marker-free and seamless introduction of point mutations. To fulfill this promise, a strategy that effects single nucleotide changes while preventing repeated recognition and cutting by the gRNA/Cas9 complex is needed. We demonstrate a two-step method to introduce point mutations at 17 positions in the S. cerevisiae genome. We show the general applicability of the method, enabling the seamless introduction of single nucleotide changes at any location, including essential genes and non-coding regions. We also show a quantifiable phenotype for a point mutation introduced in gene GSH1. The ease and wide applicability of this general method, combined with the demonstration of its feasibility will enable genome editing at an unprecedented level of detail in yeast and other organisms.

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.Electronic supplementary materialThe online version of this article (10.1186/s13068-018-1283-9) contains supplementary material, which is available to authorized users.

Critical mitochondrial functions, including cellular respiration, rely on frequently interacting components expressed from both the mitochondrial and nuclear genomes. The fitness of eukaryotic organisms depends on a tight collaboration between both genomes. In the face of an elevated rate of evolution in the mitochondrial genome, current models predict that maintenance of mitonuclear compatibility relies on compensatory evolution of the nuclear genome. Mitonuclear interactions would therefore exert a strong influence on evolutionary trajectories. One prediction from this model is that the same nuclear genomes but evolving with different mitochondrial haplotypes would follow distinct molecular paths towards higher fitness peaks. To test this prediction, we submitted 1344 populations derived from seven mitonuclear genotypes of Saccharomyces cerevisiae to more than 300 generations of experimental evolution in conditions that either select for a mitochondrial function, or that do not strictly require this organelle for survival. Performing high-throughput phenotyping and whole-genome sequencing on independently evolved individuals isolated from endpoint populations, we identified numerous examples of gene-level evolutionary convergence among populations with the same mitonuclear background. We recapitulated a subset of prominent loss-of-function alleles in the ancestral backgrounds. This confirmed a generalized pattern of mitonuclear-specific and highly epistatic fitness effects. Together, these results demonstrate how mitonuclear interactions can dictate evolutionary divergence of populations with identical starting nuclear genotypes.