With the rise of high-throughput sequencing technologies, a holistic view of genetic variation within populations—through population genomics studies—appears feasible, although it remains an ongoing effort. Genetic variation arises from a diverse range of evolutionary forces, with mutation and recombination being key drivers in shaping genomes. Studying genetic variation within a population represents a crucial first step in understanding the relationship between genotype and phenotype and the evolutionary history of species. In this context, the budding yeast Saccharomyces cerevisiae has been at the forefront of population genomic studies. In addition, it has a complex history that involves adaptation to a wide range of wild and human-related ecological niches. Although to date more than 3,000 diverse isolates have been sequenced, there is currently a lack of a resource bringing together sequencing data and associated metadata for all sequenced isolates. To perform a comprehensive analysis of the population structure of S. cerevisiae, we collected genome sequencing data from 3,034 natural isolates and processed the data uniformly. We determined ploidy levels, identified single nucleotide polymorphisms (SNPs), small insertion–deletions (InDels), copy number variations (CNVs), and aneuploidies across the population, creating a publicly accessible resource for the yeast research community. Interestingly, we showed that this population captures ∼93% of the species diversity. Using neighbor-joining and Bayesian methods, we redefined the populations, revealing clustering patterns primarily based on ecological origin. This work represents a valuable resource for the community and efforts have been made to make it evolvable and integrable to future yeast population studies.

Meiotic recombination is essential for the accurate chromosome segregation and the generation of genetic diversity through crossover and gene conversion events. Although this process has been studied extensively in a few selected model species, understanding how its properties vary across species remains limited. For instance, the ancestral ZMM pathway that generates interference-dependent crossovers has undergone multiple losses throughout evolution, suggesting variations in the regulation of crossover formation. In this context, we first characterized the meiotic recombination landscape and properties of the Kluyveromyces lactis budding yeast. We then conducted a comprehensive analysis of 29,151 recombination events (19, 212 COs and 9, 939 NCOs) spanning 577 meioses in the five budding yeast species Saccharomyces cerevisiae, Saccharomyces paradoxus, Lachancea kluyveri, Lachancea waltii and K. lactis. Eventually, we found that the Saccharomyces yeasts displayed higher recombination rates compared to the non-Saccharomyces yeasts. In addition, bona fide crossover interference and associated crossover homeostasis were detected in the Saccharomyces species only, adding L. kluyveri and K. lactis to the list of budding yeast species that lost crossover interference. Finally, recombination hotspots, although highly conserved within the Saccharomyces yeasts are not conserved beyond the Saccharomyces genus. Overall, these results highlight great variability in the recombination landscape and properties through budding yeasts evolution.

Accessing the natural genetic diversity of species unveils hidden genetic traits, clarifies gene functions and allows the generalizability of laboratory findings to be assessed. One notable discovery made in natural isolates of Saccharomyces cerevisiae is that aneuploidy—an imbalance in chromosome copy numbers—is frequent (around 20%), which seems to contradict the substantial fitness costs and transient nature of aneuploidy when it is engineered in the laboratory. Here we generate a proteomic resource and merge it with genomic and transcriptomic data for 796 euploid and aneuploid natural isolates. We find that natural and lab-generated aneuploids differ specifically at the proteome. In lab-generated aneuploids, some proteins—especially subunits of protein complexes—show reduced expression, but the overall protein levels correspond to the aneuploid gene dosage. By contrast, in natural isolates, more than 70% of proteins encoded on aneuploid chromosomes are dosage compensated, and average protein levels are shifted towards the euploid state chromosome-wide. At the molecular level, we detect an induction of structural components of the proteasome, increased levels of ubiquitination, and reveal an interdependency of protein turnover rates and attenuation. Our study thus highlights the role of protein turnover in mediating aneuploidy tolerance, and shows the utility of exploiting the natural diversity of species to attain generalizable molecular insights into complex biological processes.

Gene expression is an essential step in the translation of genotypes into phenotypes. However, little is known about the transcriptome architecture and the underlying genetic effects at the species level. Here we generated and analyzed the pan-transcriptome of ~1,000 yeast natural isolates across 4,977 core and 1,468 accessory genes. We found that the accessory genome is an underappreciated driver of transcriptome divergence. Global gene expression patterns combined with population structure showed that variation in heritable expression mainly lies within subpopulation-specific signatures, for which accessory genes are overrepresented. Genome-wide association analyses consistently highlighted that accessory genes are associated with proportionally more variants with larger effect sizes, illustrating the critical role of the accessory genome on the transcriptional landscape within and between populations.

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype–phenotype relationship.

Meiotic recombination shows broad variations across species and along chromosomes and is often suppressed at and around genomic regions determining sexual compatibility such as mating type loci in fungi. Here, we show that the absence of Spo11-DSBs and meiotic recombination on Lakl0C-left, the chromosome arm containing the sex locus of the Lachancea kluyveri budding yeast, results from the absence of recruitment of the two chromosome axis proteins Red1 and Hop1, essential for proper Spo11-DSBs formation. Furthermore, cytological observation of spread pachytene meiotic chromosomes reveals that Lakl0C-left does not undergo synapsis. However, we show that the behavior of Lakl0C-left is independent of its particularly early replication timing and is not accompanied by any peculiar chromosome structure as detectable by Hi-C in this yet poorly studied yeast. Finally, we observed an accumulation of heterozygous mutations on Lakl0C-left and a sexual dimorphism of the haploid meiotic offspring, supporting a direct effect of this absence of meiotic recombination on L. kluyveri genome evolution and fitness. Because suppression of meiotic recombination on sex chromosomes is widely observed across eukaryotes, the mechanism for recombination suppression described here may apply to other species, with the potential to impact sex chromosome evolution.

Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level.

Gene expression is known to vary among individuals, and this variability can impact the phenotypic diversity observed in natural populations. While the transcriptome and proteome have been extensively studied, little is known about the translation process itself. Here, we therefore performed ribosome and transcriptomic profiling on a genetically and ecologically diverse set of natural isolates of the Saccharomyces cerevisiae yeast. Interestingly, we found that the Euclidean distances between each profile and the expression fold changes in each pairwise isolate comparison were higher at the transcriptomic level. This observation clearly indicates that the transcriptional variation observed in the different isolates is buffered through a phenomenon known as post-transcriptional buffering at the translation level. Furthermore, this phenomenon seemed to have a specific signature by preferentially affecting essential genes as well as genes involved in complex-forming proteins, and low transcribed genes. We also explored the translation of the S. cerevisiae pangenome and found that the accessory genes related to introgression events displayed similar transcription and translation levels as the core genome. By contrast, genes acquired through horizontal gene transfer events tended to be less efficiently translated. Together, our results highlight both the extent and signature of the post-transcriptional buffering.

Assessing the complexity and expressivity of traits at the species level is an essential first step to better dissect the genotype-phenotype relationship. As trait complexity behaves dynamically, the classic dichotomy between monogenic and complex traits is too simplistic. However, no systematic assessment of this complexity spectrum has been carried out on a population scale to date. In this context, we generated a large diallel hybrid panel composed of 190 unique hybrids coming from 20 natural isolates representative of the S. cerevisiae genetic diversity. For each of these hybrids, a large progeny of 160 individuals was obtained, leading to a total of 30,400 offspring individuals. Their mitotic growth was evaluated on 38 conditions inducing various cellular stresses. We developed a classification algorithm to analyze the phenotypic distributions of offspring and assess the trait complexity. We clearly found that traits are mainly complex at the population level. On average, we found that 91.2% of cross/trait combinations exhibit high complexity, while monogenic and oligogenic cases accounted for only 4.1% and 4.7%, respectively. However, the complexity spectrum is very dynamic, trait specific and tightly related to genetic backgrounds. Overall, our study provided greater insight into trait complexity as well as the underlying genetic basis of its spectrum in a natural population.

Gene expression variation, an essential step between genotype and phenotype, is collectively controlled by local (cis) and distant (trans) regulatory changes. Nevertheless, how these regulatory elements differentially influence gene expression variation remains unclear. Here, we bridge this gap by analyzing the transcriptomes of a large diallel panel consisting of 323 unique hybrids originating from genetically divergent Saccharomyces cerevisiae isolates. Our analysis across 5,087 transcript abundance traits showed that non-additive components account for 36% of the gene expression variance on average. By comparing allele-specific read counts in parent-hybrid trios, we found that trans-regulatory changes underlie the majority of gene expression variation in the population. Remarkably, most cis-regulatory variations are also exaggerated or attenuated by additional trans effects. Overall, we showed that the transcriptome is globally buffered at the genetic level mainly due to trans-regulatory variation in the population.

Pangenomes provide access to an accurate representation of the genetic diversity of species, both in terms of sequence polymorphisms and structural variants (SVs). Here we generated the Saccharomyces cerevisiae Reference Assembly Panel (ScRAP) comprising reference-quality genomes for 142 strains representing the species’ phylogenetic and ecological diversity. The ScRAP includes phased haplotype assemblies for several heterozygous diploid and polyploid isolates. We identified circa (ca.) 4,800 nonredundant SVs that provide a broad view of the genomic diversity, including the dynamics of telomere length and transposable elements. We uncovered frequent cases of complex aneuploidies where large chromosomes underwent large deletions and translocations. We found that SVs can impact gene expression near the breakpoints and substantially contribute to gene repertoire evolution. We also discovered that horizontally acquired regions insert at chromosome ends and can generate new telomeres. Overall, the ScRAP demonstrates the benefit of a pangenome in understanding genome evolution at population scale.

Copy number variants (CNVs), duplications and deletions of genomic sequences, contribute to evolutionary adaptation but can also confer deleterious effects and cause disease. Whereas the effects of amplifying individual genes or whole chromosomes (i.e., aneuploidy) have been studied extensively, much less is known about the genetic and functional effects of CNVs of differing sizes and structures. Here, we investigated Saccharomyces cerevisiae (yeast) strains that acquired adaptive CNVs of variable structures and copy numbers following experimental evolution in glutamine-limited chemostats. Although beneficial in the selective environment, CNVs result in decreased fitness compared with the euploid ancestor in rich media. We used transposon mutagenesis to investigate mutational tolerance and genome-wide genetic interactions in CNV strains. We find that CNVs increase mutational target size, confer increased mutational tolerance in amplified essential genes, and result in novel genetic interactions with unlinked genes. We validated a novel genetic interaction between different CNVs and BMH1 that was common to multiple strains. We also analyzed global gene expression and found that transcriptional dosage compensation does not affect most genes amplified by CNVs, although gene-specific transcriptional dosage compensation does occur for ∼12% of amplified genes. Furthermore, we find that CNV strains do not show previously described transcriptional signatures of aneuploidy. Our study reveals the extent to which local and global mutational tolerance is modified by CNVs with implications for genome evolution and CNV-associated diseases, such as cancer.

Gene expression variation can provide an overview of the changes in regulatory networks that underlie phenotypic diversity. Certain evolutionary trajectories such as polyploidization events can have an impact on the transcriptional landscape. Interestingly, the evolution of the yeast species Brettanomyces bruxellensis has been punctuated by diverse allopolyploidization events leading to the coexistence of a primary diploid genome associated with various haploid acquired genomes. To assess the impact of these events on gene expression, we generated and compared the transcriptomes of a set of 87 B. bruxellensis isolates, selected as being representative of the genomic diversity of this species. Our analysis revealed that acquired subgenomes strongly impact the transcriptional patterns and allow discrimination of allopolyploid populations. In addition, clear transcriptional signatures related to specific populations have been revealed. The transcriptional variations observed are related to some specific biological processes such as transmembrane transport and amino acids metabolism. Moreover, we also found that the acquired subgenome causes the overexpression of some genes involved in the production of flavor-impacting secondary metabolites, especially in isolates of the beer population.

DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis

Théo Aspert, Didier Hentsch, Gilles Charvin. eLife, (2022) - DOI: 10.7554/eLife.79519

The process of domestication has variable consequences on genome evolution leading to different phenotypic signatures. Access to the complete genome sequences of a large number of individuals makes it possible to explore the different facets of this domestication process. Here, we sought to explore the genome evolution of Kluyveromyces lactis, a yeast species well-known for its involvement in dairy processes but also present in natural environments. Using a combination of short and long-read sequencing strategies, we investigated the genomic variability of 41 K. lactis isolates and found that the overall genetic diversity of this species is very high (θw = 3.3 × 10−2) compared to other species such as Saccharomyces cerevisiae (θw = 1.6 × 10−2). However, the domesticated dairy population shows a reduced level of diversity (θw = 1 × 10−3), probably due to a domestication bottleneck. In addition, this entire population is characterized by the introgression of the LAC4 and LAC12 genes, responsible for lactose fermentation and coming from the closely related species, Kluyveromyces marxianus, as previously described. Our results also highlighted that the LAC4/LAC12 gene cluster was acquired through multiple and independent introgression events. Finally, we also identified several genes that could play a role in adaptation to dairy environments through copy number variation. These genes are involved in sugar consumption, flocculation and drug resistance, and may play a role in dairy processes. Overall, our study illustrates contrasting genomic evolution and sheds new light on the impact of domestication processes on it.

Meiotic recombination is a driving force for genome evolution, deeply characterized in a few model species, notably in the budding yeast Saccharomyces cerevisiae. Interestingly, Zip2, Zip3, Zip4, Spo16, Msh4, and Msh5, members of the so-called ZMM pathway that implements the interfering meiotic crossover pathway in S. cerevisiae, have been lost in Lachancea yeast species after the divergence of Lachancea kluyveri from the rest of the clade. In this context, after investigating meiosis in L. kluyveri, we determined the meiotic recombination landscape of Lachancea waltii. Attempts to generate diploid strains with fully hybrid genomes invariably resulted in strains with frequent whole-chromosome aneuploidy and multiple extended regions of loss of heterozygosity (LOH), which mechanistic origin is so far unclear. Despite the lack of multiple ZMM pro-crossover factors in L. waltii, numbers of crossovers and noncrossovers per meiosis were higher than in L. kluyveri but lower than in S. cerevisiae, for comparable genome sizes. Similar to L. kluyveri but opposite to S. cerevisiae, L. waltii exhibits an elevated frequency of zero-crossover bivalents. Lengths of gene conversion tracts for both crossovers and non-crossovers in L. waltii were comparable to those observed in S. cerevisiae and shorter than in L. kluyveri despite the lack of Mlh2, a factor limiting conversion tract size in S. cerevisiae. L. waltii recombination hotspots were not shared with either S. cerevisiae or L. kluyveri, showing that meiotic recombination hotspots can evolve at a rather limited evolutionary scale within budding yeasts. Finally, L. waltii crossover interference was reduced relative to S. cerevisiae, with interference being detected only in the 25 kb distance range. Detection of positive inference only at short distance scales in the absence of multiple ZMM factors required for interference-sensitive crossovers in other systems likely reflects interference between early recombination precursors such as DSBs.