Spontaneous duplications in diploid Saccharomyces cerevisiae cells

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values. Copy number variants (CNVs) are a pervasive source of heritable variation that can facilitate rapid adaptive evolution. Previously, we developed a locus-specific fluorescent CNV reporter to quantify CNV dynamics in evolving populations maintained in nutrient-limiting conditions using chemostats. Here, we use CNV adaptation dynamics to estimate the rate at which beneficial CNVs are introduced through de novo mutation and their fitness effects using simulation-based likelihood-free inference approaches. We tested the suitability of 2 evolutionary models: a standard Wright-Fisher model and a chemostat model. We evaluated 2 likelihood-free inference algorithms: the well-established Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC) algorithm, and the recently developed Neural Posterior Estimation (NPE) algorithm, which applies an artificial neural network to directly estimate the posterior distribution. By systematically evaluating the suitability of different inference methods and models, we show that NPE has several advantages over ABC-SMC and that a Wright-Fisher evolutionary model suffices in most cases. Using our validated inference framework, we estimate the CNV formation rate at the GAP1 locus in the yeast Saccharomyces cerevisiae to be 10-4.7 to 10-4 CNVs per cell division and a fitness coefficient of 0.04 to 0.1 per generation for GAP1 CNVs in glutamine-limited chemostats. We experimentally validated our inference-based estimates using 2 distinct experimental methods-barcode lineage tracking and pairwise fitness assays-which provide independent confirmation of the accuracy of our approach. Our results are consistent with a beneficial CNV supply rate that is 10-fold greater than the estimated rates of beneficial single-nucleotide mutations, explaining the outsized importance of CNVs in rapid adaptive evolution. More generally, our study demonstrates the utility of novel neural network-based likelihood-free inference methods for inferring the rates and effects of evolutionary processes from empirical data with possible applications ranging from tumor to viral evolution.

Pathways and Mechanisms that Prevent Genome Instability in Saccharomyces cerevisiae

Genome rearrangements result in mutations that underlie many human diseases, and ongoing genome instability likely contributes to the development of many cancers. The tools for studying genome instability in mammalian cells are limited, whereas model organisms such as Saccharomyces cerevisiae are more amenable to these studies. Here, we discuss the many genetic assays developed to measure the rate of occurrence of Gross Chromosomal Rearrangements (called GCRs) in S. cerevisiae. These genetic assays have been used to identify many types of GCRs, including translocations, interstitial deletions, and broken chromosomes healed by de novo telomere addition, and have identified genes that act in the suppression and formation of GCRs. Insights from these studies have contributed to the understanding of pathways and mechanisms that suppress genome instability and how these pathways cooperate with each other. Integrated models for the formation and suppression of GCRs are discussed.

Genome Diversity and Evolution in the Budding Yeasts (Saccharomycotina)

Considerable progress in our understanding of yeast genomes and their evolution has been made over the last decade with the sequencing, analysis, and comparisons of numerous species, strains, or isolates of diverse origins. The role played by yeasts in natural environments as well as in artificial manufactures, combined with the importance of some species as model experimental systems sustained this effort. At the same time, their enormous evolutionary diversity (there are yeast species in every subphylum of Dikarya) sparked curiosity but necessitated further efforts to obtain appropriate reference genomes. Today, yeast genomes have been very informative about basic mechanisms of evolution, speciation, hybridization, domestication, as well as about the molecular machineries underlying them. They are also irreplaceable to investigate in detail the complex relationship between genotypes and phenotypes with both theoretical and practical implications. This review examines these questions at two distinct levels offered by the broad evolutionary range of yeasts: inside the best-studied Saccharomyces species complex, and across the entire and diversified subphylum of Saccharomycotina. While obviously revealing evolutionary histories at different scales, data converge to a remarkably coherent picture in which one can estimate the relative importance of intrinsic genome dynamics, including gene birth and loss, vs. horizontal genetic accidents in the making of populations. The facility with which novel yeast genomes can now be studied, combined with the already numerous available reference genomes, offer privileged perspectives to further examine these fundamental biological questions using yeasts both as eukaryotic models and as fungi of practical importance.

Gene copy-number variation in haploid and diploid strains of the yeast Saccharomyces cerevisiae

The increasing ability to sequence and compare multiple individual genomes within a species has highlighted the fact that copy-number variation (CNV) is a substantial and underappreciated source of genetic diversity. Chromosome-scale mutations occur at rates orders of magnitude higher than base substitutions, yet our understanding of the mechanisms leading to CNVs has been lagging. We examined CNV in a region of chromosome 5 (chr5) in haploid and diploid strains of Saccharomyces cerevisiae. We optimized a CNV detection assay based on a reporter cassette containing the SFA1 and CUP1 genes that confer gene dosage-dependent tolerance to formaldehyde and copper, respectively. This optimized reporter allowed the selection of low-order gene amplification events, going from one copy to two copies in haploids and from two to three copies in diploids. In haploid strains, most events involved tandem segmental duplications mediated by nonallelic homologous recombination between flanking direct repeats, primarily Ty1 elements. In diploids, most events involved the formation of a recurrent nonreciprocal translocation between a chr5 Ty1 element and another Ty1 repeat on chr13. In addition to amplification events, a subset of clones displaying elevated resistance to formaldehyde had point mutations within the SFA1 coding sequence. These mutations were all dominant and are proposed to result in hyperactive forms of the formaldehyde dehydrogenase enzyme.

Ploidy influences cellular responses to gross chromosomal rearrangements in Saccharomyces cerevisiae

Background

Gross chromosomal rearrangements (GCRs) such as aneuploidy are key factors in genome evolution as well as being common features of human cancer. Their role in tumour initiation and progression has not yet been completely elucidated and the effects of additional chromosomes in cancer cells are still unknown. Most previous studies in which Saccharomyces cerevisiae has been used as a model for cancer cells have been carried out in the haploid context. To obtain new insights on the role of ploidy, the cellular effects of GCRs were compared between the haploid and diploid contexts.

Results

A total number of 21 haploid and diploid S. cerevisiae strains carrying various types of GCRs (aneuploidies, nonreciprocal translocations, segmental duplications and deletions) were studied with a view to determining the effects of ploidy on the cellular responses. Differences in colony and cell morphology as well as in the growth rates were observed between mutant and parental strains. These results suggest that cells are impaired physiologically in both contexts. We also investigated the variation in genomic expression in all the mutants. We observed that gene expression was significantly altered. The data obtained here clearly show that genes involved in energy metabolism, especially in the tricarboxylic acid cycle, are up-regulated in all these mutants. However, the genes involved in the composition of the ribosome or in RNA processing are down-regulated in diploids but up-regulated in haploids. Over-expression of genes involved in the regulation of the proteasome was found to occur only in haploid mutants.

Conclusion

The present comparisons between the cellular responses of strains carrying GCRs in different ploidy contexts bring to light two main findings. First, GCRs induce a general stress response in all studied mutants, regardless of their ploidy. Secondly, the ploidy context plays a crucial role in maintaining the stoichiometric balance of the proteins: the translation rates decrease in diploid strains, whereas the excess protein synthesized is degraded in haploids by proteasome activity.