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Transposable elements (TEs) are major contributors to structural genomic variation by creating interspersed duplications of themselves. In return, structural variants (SVs) can affect the genomic distribution of TE copies and shape their load. One long-standing hypothesis states that hybridization could trigger TE mobilization and thus increase TE load in hybrids. We previously tested this hypothesis by performing a large-scale evolution experiment by mutation accumulation (MA) on multiple hybrid genotypes within and between wild populations of the yeastsSaccharomyces paradoxusandSaccharomyces cerevisiae. Using aggregate measures of TE load with short-read sequencing, we found no evidence for TE load increase in hybrid MA lines. Here, we resolve the genomes of the hybrid MA lines with long-read phasing and assembly to precisely characterize the role of SVs in shaping the TE landscape. Highly contiguous phased assemblies of 127 MA lines revealed that SV types like polyploidy, aneuploidy and loss of heterozygosity have large impacts on the TE load. We characterized 18 de novo TE insertions, indicating that transposition only has a minor role in shaping the TE landscape in MA lines. Because the scarcity of TE mobilization in MA lines provided insufficient resolution to confidently dissect transposition rate variation in hybrids, we adapted an in vivo assay to measure transposition rates in variousS. paradoxushybrid backgrounds. We found that transposition rates are not increased by hybridization, but are modulated by many genotype-specific factors including initial TE load, TE sequence variants and mitochondrial DNA inheritance. Our results show the multiple scales at which TE load is shaped in hybrid genomes, being highly impacted by SV dynamics and finely modulated by genotype-specific variation in transposition rates.

Pathogenic fungi are a cause of growing concern. Developing an efficient and safe antifungal is challenging because of the similar biological properties of fungal and host cells. Consequently, there is an urgent need to better understand the mechanisms underlying antifungal resistance to prolong the efficacy of current molecules. A major step in this direction would be to be able to predict or even prevent the acquisition of resistance. We leverage the power of experimental evolution to quantify the diversity of paths to resistance to the antifungal 5-fluorocytosine (5-FC), commercially known as flucytosine. We generated hundreds of independent 5-FC resistant mutants derived from two genetic backgrounds from wild isolates ofSaccharomyces cerevisiae. Through automated pin-spotting, whole-genome and amplicon sequencing, we identified the most likely causes of resistance for most strains. Approximately a third of all resistant mutants evolved resistance through the pleiotropic drug response, a potentially novel mechanism in response to 5-FC, marked by cross-resistance to fluconazole. For the majority of the remaining two thirds, resistance was acquired through loss-of-function mutations inFUR1, which encodes an important enzyme in the metabolism of 5-FC. We describe conditions in which mutations affecting this particular step of the metabolic pathway are favored over known resistance mutations affecting a step upstream, such as the well-known target cytosine deaminase encoded byFCY1. This observation suggests that ecological interactions may dictate the identity of resistance hotspots.

Yeasts are ubiquitous in temperate forests. While this broad habitat is well-defined, the yeasts inhabiting it and their life cycles, niches, and contributions to ecosystem functioning are less understood. Yeasts are present on nearly all sampled substrates in temperate forests worldwide. They associate with soils, macroorganisms, and other habitats and no doubt contribute to broader ecosystem-wide processes. Researchers have gathered information leading to hypotheses about yeasts' niches and their life cycles based on physiological observations in the laboratory as well as genomic analyses, but the challenge remains to test these hypotheses in the forests themselves. Here, we summarize the habitat and global patterns of yeast diversity, give some information on a handful of well-studied temperate forest yeast genera, discuss the various strategies to isolate forest yeasts, and explain temperate forest yeasts' contributions to biotechnology. We close with a summary of the many future directions and outstanding questions facing researchers in temperate forest yeast ecology. Yeasts present an exciting opportunity to better understand the hidden world of microbial ecology in this threatened and global habitat.

Protein-protein interactions (PPIs) drive many cellular processes. Some PPIs are directed by Src homology 3 (SH3) domains that bind proline-rich motifs on other proteins. The evolution of the binding specificity of SH3 domains is not completely understood, particularly following gene duplication. Paralogous genes accumulate mutations that can modify protein functions and, for SH3 domains, their binding preferences. Here, we examined how the binding of the SH3 domains of two paralogous yeast type I myosins, Myo3 and Myo5, evolved following duplication. We found that the paralogs have different SH3-dependent interaction profiles. However, by swapping SH3 domains between the paralogs and by characterizing the SH3 domains freed from their protein context, we find that very few of the differences in interactions, if any, depend on the SH3 domains themselves. We used ancestral sequence reconstruction to resurrect the pre-duplication SH3 domains and examined, moving back in time, how the binding preference changed. Although the closest ancestor of the two domains had a very similar binding preference as the extant ones, older ancestral domains displayed a gradual loss of interaction with the modern interaction partners when inserted in the extant paralogs. Molecular docking and experimental characterization of the free ancestral domains showed that their affinity with the proline motifs is likely not the cause for this loss of binding. Taken together, our results suggest that intramolecular interaction between a SH3 and its host protein evolves through time, making domains not functionally equivalent even when they have the same binding specificity.

Morphological profiling is a combination of established optical microscopes and cutting-edge machine vision technologies, which stacks up successful applications in high-throughput phenotyping. One major question is how much information can be extracted from an image to identify genetic differences between cells. While fluorescent microscopy images of specific organelles have been broadly used for single-cell profiling, the potential ability of bright-field (BF) microscopy images of label-free cells remains to be tested. Here, we examine whether single-gene perturbation can be discriminated based on BF images of label-free cells using a machine learning approach. We acquired hundreds of BF images of single-gene mutant cells, quantified single-cell profiles consisting of texture features of cellular regions, and constructed a machine learning model to discriminate mutant cells from wild-type cells. Interestingly, the mutants were successfully discriminated from the wild type (area under the receiver operating characteristic curve = 0.773). The features that contributed to the discrimination were identified, and they included those related to the morphology of structures that appeared within cellular regions. Furthermore, functionally close gene pairs showed similar feature profiles of the mutant cells. Our study reveals that single-gene mutant cells can be discriminated from wild-type cells based on BF images, suggesting the potential as a useful tool for mutant cell profiling.

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 an 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 ofSaccharomyces cerevisiaeto more than 300 generations of experimental evolution in conditions that either select for a mitochondrial function, or that do not strictly require respiration 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. Phenotypic and genotypic data on strains derived from this evolution experiment identify the nuclear genome and the environment as the main determinants of evolutionary divergence, but also show a modulating role for the mitochondrial genome exerted both directly and via interactions with the two other components. We finally recapitulated a subset of prominent loss-of-function alleles in the ancestral backgrounds and 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.

SummaryFungi have a wide range of lifestyles and hosts. We still know little about the impact of lifestyles on their genome architecture. Here, we combined and annotated 562 fungal genomes from the class Sordariomycetes and examined the coevolution between 12 genomic and two lifestyle traits: pathogenicity and insect association. We found that many pathogens tend to evolve a larger number of protein-coding genes, tRNA genes, and have larger non-repetitive genome sizes than non-pathogenic species. In contrast, species with a pathogenic or symbiotic relationship with insects have smaller genome sizes and genes with longer exons; they also have fewer genes if they are vectored by insects, compared to species not associated with insects. Our study demonstrates that pathogen genome size and complexity are the result of an interplay between drift, imposed by symbiosis and small effective population size, which leads to genome contraction, and the adaptive role of gene amplification, which leads to genome expansion.

The biophysical properties of the cytoplasm are major determinants of key cellular processes and adaptation. Many yeasts produce dormant spores that can withstand extreme conditions. We show that spores ofSaccharomyces cerevisiæexhibit extraordinary biophysical properties, including a highly viscous and acidic cytosol. These conditions alter the solubility of more than 100 proteins such as metabolic enzymes that become more soluble as spores transit to active cell proliferation upon nutrient repletion. A key regulator of this transition is the heat shock protein Hsp42, which shows transient solubilization and phosphorylation, and is essential for the transformation of the cytoplasm during germination. Germinating spores therefore return to growth through the dissolution of protein assemblies, orchestrated in part by Hsp42 activity. The modulation of spores’ molecular properties are likely key adaptive features of their exceptional survival capacities.

With the current COVID-19 pandemic, we all realized how important interactions are. Interactions are everywhere. At the cellular level, protein interactions play a key role and their ensemble, also called interactome, is often referred as the basic building blocks of life. Given its importance, the maintenance of the integrity of the interactome is a real challenge in the cell. Many events during evolution can disrupt interactomes and potentially result in different characteristics for the organisms. However, the molecular underpinnings of changes in interactions at the cellular level are still largely unexplored. Among the perturbations, hybridization puts in contact two different interactomes, which may lead to many changes in the protein interaction network of the hybrid, including gains and losses of interactions. We recently investigated the fate of the interactomes after hybridization between yeast species using a comparative proteomics approach. A large-scale conservation of the interactions was observed in hybrids, but we also noticed the presence of proteostasis-related changes. This suggests that, despite a general robustness, small differences may accumulate in hybrids and perturb their protein physiology. Here, we summarize our work with a broader perspective on the importance of interactions.

Protein–protein interactions (PPIs) between modular binding domains and their target peptide motifs are thought to largely depend on the intrinsic binding specificities of the domains. The large family of SRC Homology 3 (SH3) domains contribute to cellular processes via their ability to support such PPIs. While the intrinsic binding specificities of SH3 domains have been studied in vitro, whether each domain is necessary and sufficient to define PPI specificity in vivo is largely unknown. Here, by combining deletion, mutation, swapping and shuffling of SH3 domains and measurements of their impact on protein interactions in yeast, we find that most SH3s do not dictate PPI specificity independently from their host protein in vivo. We show that the identity of the host protein and the position of the SH3 domains within their host are critical for PPI specificity, for cellular functions and for key biophysical processes such as phase separation. Our work demonstrates the importance of the interplay between a modular PPI domain such as SH3 and its host protein in establishing specificity to wire PPI networks. These findings will aid understanding how protein networks are rewired during evolution and in the context of mutation-driven diseases such as cancer., The SRC Homology 3 (SH3) domains mediate protein–protein interactions (PPIs). Here, the authors assess the SH3-mediated PPIs in yeast, and show that the identity of the protein itself and the position of the SH3 both affect the interaction specificity and thus the PPI-dependent cellular functions.

Cells evolve in a space of parameter values set by physical and chemical forces. These constraints create associations among cellular properties. A particularly strong association is the negative correlation between the rate of evolution of proteins and their abundance in the cell. Highly expressed proteins evolve slower than lowly expressed ones. Multiple hypotheses have been put forward to explain this relationship, including, for instance, the requirement for higher mRNA stability, misfolding avoidance, and misinteraction avoidance for highly expressed proteins. Here, we review some of these hypotheses, their predictions, and how they are supported to finally discuss recent experiments that have been performed to test these predictions.

Deep mutational scanning (DMS) generates mutants of a protein of interest in a comprehensive manner. CRISPR-Cas9 technology enables large-scale genome editing with high efficiency. Using both DMS and CRISPR-Cas9 therefore allows us to investigate the effects of thousands of mutations inserted directly in the genome. Combined with protein-fragment complementation assay (PCA), which enables the quantitative measurement of protein-protein interactions (PPIs) in vivo, these methods allow for the systematic assessment of the effects of mutations on PPIs in living cells. Here, we describe a method leveraging DMS, CRISPR-Cas9, and PCA to study the effect of point mutations on PPIs mediated by protein domains in yeast.

Base editing is a CRISPR-Cas9 genome engineering tool that allows programmable mutagenesis without the creation of double-stranded breaks. Here, we describe the design and execution of large-scale base editing screens using the Target-AID base editor in yeast. Using this approach, thousands of sites can be mutated simultaneously. The effects of these mutations on fitness can be measured using a pooled growth competition assay followed by DNA sequencing of gRNAs as barcodes.

Mitochondrial DNA (mtDNA) is a cytoplasmic genome that is essential for respiratory metabolism. While uniparental mtDNA inheritance is most common in animals and plants, distinct mtDNA haplotypes can coexist in a state of heteroplasmy, either because of paternal leakage or de novo mutations. MtDNA integrity and the resolution of heteroplasmy have important implications, notably for mitochondrial genetic disorders, speciation and genome evolution in hybrids. However, the impact of genetic variation on the transition to homoplasmy from initially heteroplasmic backgrounds remains largely unknown. Here, we useSaccharomycesyeasts, fungi with constitutive biparental mtDNA inheritance, to investigate the resolution of mtDNA heteroplasmy in a variety of hybrid genotypes. We previously designed 11 crosses along a gradient of parental evolutionary divergence using undomesticated isolates ofSaccharomyces paradoxusandSaccharomyces cerevisiae. Each cross was independently replicated 48 to 96 times, and the resulting 864 hybrids were evolved under relaxed selection for mitochondrial function. Genome sequencing of 446 MA lines revealed extensive mtDNA recombination, but recombination rate was not predicted by parental divergence level. We found a strong positive relationship between parental divergence and the rate of large-scale mtDNA deletions, which lead to the loss of respiratory metabolism. We also uncovered associations between mtDNA recombination, mtDNA deletion, and genome instability that were genotype-specific. Our results show that hybridization in yeast induces mtDNA degeneration through large-scale deletion and loss of function, with deep consequences for mtDNA evolution, metabolism and the emergence of reproductive isolation.

Recent evidence suggests that the coding potential of the mitogenome is underestimated. We found a downstream alternative ATG initiation codon in the +3 reading frame of the human mitochondrial nd4 gene. This newly characterized alternative open reading frame (altORF) encodes a 99-amino acids long polypeptide, MTALTND4, which is conserved in primates. This small protein is localized in mitochondria and cytoplasm and is also found in the plasma, and it impacts mitochondrial physiology. Alternative mitochondrial peptides such as MTALTND4 may offer a new framework for the investigation of mitochondrial functions and diseases.

Species is the fundamental unit to quantify biodiversity. In recent years, the model yeast Saccharomyces cerevisiae has seen an increased number of studies related to its geographical distribution, population structure, and phenotypic diversity. However, seven additional species from the same genus have been less thoroughly studied, which has limited our understanding of the macroevolutionary events leading to the diversification of this genus over the last 20 million years. Here, we show the geographies, hosts, substrates, and phylogenetic relationships for approximately 1,800 Saccharomyces strains, covering the complete genus with unprecedented breadth and depth. We generated and analyzed complete genome sequences of 163 strains and phenotyped 128 phylogenetically diverse strains. This dataset provides insights about genetic and phenotypic diversity within and between species and populations, quantifies reticulation and incomplete lineage sorting, and demonstrates how gene flow and selection have affected traits, such as galactose metabolism. These findings elevate the genus Saccharomyces as a model to understand biodiversity and evolution in microbial eukaryotes., Some computations were performed on Tirant III of the Spanish Supercomputing Network (“Servei d’Informàtica de la Universitat de València”) under the project BCV-2021-1-0001 granted to DP, while others were performed at the Wisconsin Energy Institute and the Center for High-Throughput Computing of the University of Wisconsin–Madison. During a portion of this project, DP was a researcher funded by the European Union’s Horizon 2020 research and innovation program Marie Sklodowska-Curie, grant agreement No. 747775, the Research Council of Norway (RCN) grant Nos. RCN 324253 and 274337, and the Generalitat Valenciana plan GenT grant No. CIDEGENT/2021/039. D.P. is a recipient of an Illumina Grant for Illumina Sequencing Saccharomyces strains in this study. Q.K.L. was supported by the National Science Foundation under Grant No. DGE-1256259 (Graduate Research Fellowship) and the Predoctoral Training Program in Genetics, funded by the National Institutes of Health (5T32GM007133). This material is based upon work supported in part by the Great Lakes Bioenergy Research Center, Office of Science, Office of Biological and Environmental Research under Award Numbers DE-SC0018409 and DE-FC02-07ER64494; the National Science Foundation under Grant Nos. DEB-1253634, DEB−1442148, and DEB-2110403; and the USDA National Institute of Food and Agriculture Hatch Project Number 1020204. C.T.H. is an H. I. Romnes Faculty Fellow, supported by the Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation. QMW was supported by the National Natural Science Foundation of China (NSFC) under Grant Nos. 31770018 and 31961133020. C.R.L. holds the Canada Research Chair in Cellular Systems and Synthetic Biology, and his research on wild yeast is supported by an NSERC Discovery Grant.

The genome sequences of archeological Saccharomyces cerevisiae isolates can reveal insights about the history of human baking, brewing and winemaking activities. A yeast strain called Jean-Talon was recently isolated from the vaults of the Intendant’s Palace of Nouvelle France on a historical site in Québec City. This site was occupied by breweries from the end of the 17th century until the middle of the 20th century when poisoning caused by cobalt added to the beer led to a shutdown of brewing activities. We sequenced the genome of the Jean-Talon strain and reanalyzed the genomes of hundreds of strains to determine how it relates to other domesticated and wild strains. The Jean-Talon strain is most closely related to industrial beer strains from the beer and bakery genetic groups from the United Kingdom and Belgium. It has numerous aneuploidies and Copy Number Variants (CNVs), including the main gene conferring cobalt resistance in yeast. The Jean-Talon strain has indeed higher tolerance to cobalt compared to other yeast strains, consistent with adaptation to the most recent brewing activities on the site. We conclude from this that the Jean-Talon strain most likely derives from recent brewing activities and not from the original breweries of Nouvelle France on the site.

Hybridization and the resulting introgression can drive the success of invasive species via the rapid acquisition of adaptive traits. The Dutch elm disease pandemics in the past 100 years were caused by three fungal lineages with permeable reproductive barriers: Ophiostoma ulmi, Ophiostoma novo-ulmi subspecies novo-ulmi and Ophiostoma novo-ulmi subspecies americana. Using whole-genome sequences and growth phenotyping of a worldwide collection of isolates, we show that introgression has been the main driver of genomic diversity and that it impacted fitness-related traits. Introgressions contain genes involved in host–pathogen interactions and reproduction. Introgressed isolates have enhanced growth rate at high temperature and produce different necrosis sizes on an in vivo model for pathogenicity. In addition, lineages diverge in many pathogenicity-associated genes and exhibit differential mycelial growth in the presence of a proxy of a host defence compound, implying an important role of host trees in the molecular and functional differentiation of these pathogens. Genome analysis of fungi responsible for Dutch elm disease shows that introgression has contributed to genomic diversity and has impacted fitness-related traits in these pathogens.

The ability to measure microbial fitness directly in natural conditions and in interaction with other microbes is a challenge that needs to be overcome if we want to gain a better understanding of microbial fitness determinants in nature. Here we investigate the influence of the natural microbial community on the relative fitness of the North American populations SpB, SpC and SpC* of the wild yeast Saccharomyces paradoxus using DNA barcodes and a soil microcosm derived from soil associated with oak trees. We find that variation in fitness among these genetically distinct groups is influenced by the microbial community. Altering the microbial community load and diversity with an irradiation treatment significantly diminishes the magnitude of fitness differences among populations. Our findings suggest that microbial interactions could affect the evolution of yeast lineages in nature by modulating variation in fitness.

The assembly of complexes following the detection of extracellular signals is often controlled by signaling proteins comprising multiple peptide binding modules. The SRC homology (SH)3 family represents the archetypical modular protein interaction module, with ~300 annotated SH3 domains in humans that regulate an impressive array of signaling processes. We review recent findings regarding the allosteric contributions of SH3 domains host protein context, their phosphoregulation, and their roles in phase separation that challenge the simple model in which SH3s are considered to be portable domains binding to specific proline-rich peptide motifs.

Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein–protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, dihydrofolate reductase protein-fragment complementation assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11 000 bait-prey pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.