Gain- and loss-of-function alleles within signaling pathways lead to phenotypic diversity among individuals.

Understanding how phenotypic diversity is generated is an important question in biology. We explored phenotypic diversity among wild yeast isolates (Saccharomyces cerevisiae) and found variation in the activity of MAPK signaling pathways as a contributing mechanism. To uncover the genetic basis of this mechanism, we identified 1957 SNPs in 62 candidate genes encoding signaling proteins from a MAPK signaling module within a large collection of yeast (>1500 individuals). Follow-up testing identified functionally relevant variants in key signaling proteins. Loss-of-function (LOF) alleles in a PAK kinase impacted protein stability and pathway specificity decreasing filamentous growth and mating phenotypes. In contrast, gain-of-function (GOF) alleles in G-proteins that were hyperactivating induced filamentous growth. Similar amino acid substitutions in G-proteins were identified in metazoans that in some cases were fixed in multicellular lineages including humans, suggesting hyperactivating GOF alleles may play roles in generating phenotypic diversity across eukaryotes. A mucin signaler that regulates MAPK activity was also found to contain a prevalance of presumed GOF alleles amoung individuals based on changes in mucin repeat numbers. Thus, genetic variation in signaling pathways may act as a reservoir for generating phenotypic diversity across eukaryotes.

Building pangenome graphs.

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder, a pipeline for constructing pangenome graphs without bias or exclusion. The PanGenome Graph Builder uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events and infer phylogenetic relationships.

An integrative taxonomy approach reveals Saccharomyces chiloensis sp. nov. as a newly discovered species from Coastal Patagonia.

Species delineation in microorganisms is challenging due to the limited markers available for accurate species assignment. Here, we applied an integrative taxonomy approach, combining extensive sampling, whole-genome sequence-based classification, phenotypic profiling, and assessment of interspecific reproductive isolation. Our work reveals the presence of a distinct Saccharomyces lineage in Nothofagus forests of coastal Patagonia. This lineage, designated Saccharomyces chiloensis sp. nov., exhibits 7% genetic divergence from its sister species S. uvarum, as revealed by whole-genome sequencing and population analyses. The South America-C (SA-C) coastal Patagonia population forms a unique clade closely related to a previously described divergent S. uvarum population from Oceania (AUS, found in Australia and New Zealand). Our species reclassification is supported by a low Ortho Average Nucleotide Identity (OANI) of 93% in SA-C and AUS relative to S. uvarum, which falls below the suggested species delineation threshold of 95%, indicating an independent evolutionary lineage. Hybrid spore viability assessment provided compelling evidence that SA-C and AUS are reproductively isolated from S. uvarum. In addition, we found unique structural variants between S. chiloensis sp. nov. lineages, including large-scale chromosomal translocations and inversions, together with a distinct phenotypic profile, emphasizing their intraspecies genetic distinctiveness. We suggest that S. chiloensis sp. nov diverged from S. uvarum in allopatry due to glaciation, followed by post-glacial dispersal, resulting in distinct lineages on opposite sides of the Pacific Ocean. The discovery of S. chiloensis sp. nov. illustrates the uniqueness of Patagonia's coastal biodiversity and underscores the importance of adopting an integrative taxonomic approach in species delineation to unveil cryptic microbial species. The holotype of S. chiloensis sp. nov. is CBS 18620T.

Natural proteome diversity links aneuploidy tolerance to protein turnover.

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 frequent1,2 (around 20%), which seems to contradict the substantial fitness costs and transient nature of aneuploidy when it is engineered in the laboratory3-5. Here we generate a proteomic resource and merge it with genomic1 and transcriptomic6 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.

Ancient and recent origins of shared polymorphisms in yeast.

Shared genetic polymorphisms between populations and species can be ascribed to ancestral variation or to more recent gene flow. Here, we mapped shared polymorphisms in Saccharomyces cerevisiae and its sister species Saccharomyces paradoxus, which diverged 4-6 million years ago. We used a dense map of single-nucleotide diagnostic markers (mean distance 15.6 base pairs) in 1,673 sequenced S. cerevisiae isolates to catalogue 3,852 sequence blocks (≥5 consecutive markers) introgressed from S. paradoxus, with most being recent and clade-specific. The highly diverged wild Chinese S. cerevisiae lineages were depleted of introgressed blocks but retained an excess of individual ancestral polymorphisms derived from incomplete lineage sorting, perhaps due to less dramatic population bottlenecks. In the non-Chinese S. cerevisiae lineages, we inferred major hybridization events and detected cases of overlapping introgressed blocks across distinct clades due to either shared histories or convergent evolution. We experimentally engineered, in otherwise isogenic backgrounds, the introgressed PAD1-FDC1 gene pair that independently arose in two S. cerevisiae clades and revealed that it increases resistance against diverse antifungal drugs. Overall, our study retraces the histories of divergence and secondary contacts across S. cerevisiae and S. paradoxus populations and unveils a functional outcome.

Engineering heterothallic strains in fission yeast.

In poor nitrogen conditions, fission yeast cells mate, undergo meiosis and form spores that are resistant to deleterious environments. Natural isolates of Schizosaccharomyces pombe are homothallic. This allows them to naturally switch between the two h- and h+ mating types with a high frequency, thereby ensuring the presence of both mating partners in a population of cells. However, alteration of the mating type locus can abolish mating type switching or reduce it to a very low frequency. Such heterothallic strains have been isolated and are common in research laboratories due to the simplicity of their use for Mendelian genetics. In addition to the standard laboratory strains, a large collection of natural S. pombe isolates is now available, representing a powerful resource for investigating the genetic diversity and biology of fission yeast. However, most of these strains are homothallic, and only tedious or mutagenic strategies have been described to obtain heterothallic cells from a homothallic parent. Here, we describe a simple approach to generate heterothallic strains. It takes advantage of an alteration of the mating type locus that was previously identified in a mating type switching-deficient strain and the CRISPR-Cas9 editing tool, allowing for a one-step engineering of heterothallic cells with high efficiency.

Genome instability footprint under rapamycin and hydroxyurea treatments.

The mutational processes dictating the accumulation of mutations in genomes are shaped by genetic background, environment and their interactions. Accurate quantification of mutation rates and spectra under drugs has important implications in disease treatment. Here, we used whole-genome sequencing and time-resolved growth phenotyping of yeast mutation accumulation lines to give a detailed view of the mutagenic effects of rapamycin and hydroxyurea on the genome and cell growth. Mutation rates depended on the genetic backgrounds but were only marginally affected by rapamycin. As a remarkable exception, rapamycin treatment was associated with frequent chromosome XII amplifications, which compensated for rapamycin induced rDNA repeat contraction on this chromosome and served to maintain rDNA content homeostasis and fitness. In hydroxyurea, a wide range of mutation rates were elevated regardless of the genetic backgrounds, with a particularly high occurrence of aneuploidy that associated with dramatic fitness loss. Hydroxyurea also induced a high T-to-G and low C-to-A transversion rate that reversed the common G/C-to-A/T bias in yeast and gave rise to a broad range of structural variants, including mtDNA deletions. The hydroxyurea mutation footprint was consistent with the activation of error-prone DNA polymerase activities and non-homologues end joining repair pathways. Taken together, our study provides an in-depth view of mutation rates and signatures in rapamycin and hydroxyurea and their impact on cell fitness, which brings insights for assessing their chronic effects on genome integrity.

phyBWT2: phylogeny reconstruction via eBWT positional clustering.

BACKGROUND: Molecular phylogenetics studies the evolutionary relationships among the individuals of a population through their biological sequences. It may provide insights about the origin and the evolution of viral diseases, or highlight complex evolutionary trajectories. A key task is inferring phylogenetic trees from any type of sequencing data, including raw short reads. Yet, several tools require pre-processed input data e.g. from complex computational pipelines based on de novo assembly or from mappings against a reference genome. As sequencing technologies keep becoming cheaper, this puts increasing pressure on designing methods that perform analysis directly on their outputs. From this viewpoint, there is a growing interest in alignment-, assembly-, and reference-free methods that could work on several data including raw reads data. RESULTS: We present phyBWT2, a newly improved version of phyBWT (Guerrini et al. in 22nd International Workshop on Algorithms in Bioinformatics (WABI) 242:23-12319, 2022). Both of them directly reconstruct phylogenetic trees bypassing both the alignment against a reference genome and de novo assembly. They exploit the combinatorial properties of the extended Burrows-Wheeler Transform (eBWT) and the corresponding eBWT positional clustering framework to detect relevant blocks of the longest shared substrings of varying length (unlike the k-mer-based approaches that need to fix the length k a priori). As a result, they provide novel alignment-, assembly-, and reference-free methods that build partition trees without relying on the pairwise comparison of sequences, thus avoiding to use a distance matrix to infer phylogeny. In addition, phyBWT2 outperforms phyBWT in terms of running time, as the former reconstructs phylogenetic trees step-by-step by considering multiple partitions, instead of just one partition at a time, as previously done by the latter. CONCLUSIONS: Based on the results of the experiments on sequencing data, we conclude that our method can produce trees of quality comparable to the benchmark phylogeny by handling datasets of different types (short reads, contigs, or entire genomes). Overall, the experiments confirm the effectiveness of phyBWT2 that improves the performance of its previous version phyBWT, while preserving the accuracy of the results.

Telomere-to-telomere assemblies of 142 strains characterize the genome structural landscape in Saccharomyces cerevisiae.

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.

Single nucleotide polymorphisms associated with wine fermentation and adaptation to nitrogen limitation in wild and domesticated yeast strains.

For more than 20 years, Saccharomyces cerevisiae has served as a model organism for genetic studies and molecular biology, as well as a platform for biotechnology (e.g., wine production). One of the important ecological niches of this yeast that has been extensively studied is wine fermentation, a complex microbiological process in which S. cerevisiae faces various stresses such as limited availability of nitrogen. Nitrogen deficiencies in grape juice impair fermentation rate and yeast biomass production, leading to sluggish or stuck fermentations, resulting in considerable economic losses for the wine industry. In the present work, we took advantage of the "1002 Yeast Genomes Project" population, the most complete catalogue of the genetic variation in the species and a powerful resource for genotype-phenotype correlations, to study the adaptation to nitrogen limitation in wild and domesticated yeast strains in the context of wine fermentation. We found that wild and domesticated yeast strains have different adaptations to nitrogen limitation, corroborating their different evolutionary trajectories. Using a combination of state-of-the-art bioinformatic (GWAS) and molecular biology (CRISPR-Cas9) methodologies, we validated that PNP1, RRT5 and PDR12 are implicated in wine fermentation, where RRT5 and PDR12 are also involved in yeast adaptation to nitrogen limitation. In addition, we validated SNPs in these genes leading to differences in fermentative capacities and adaptation to nitrogen limitation. Altogether, the mapped genetic variants have potential applications for the genetic improvement of industrial yeast strains.

Building pangenome graphs.

Pangenome graphs can represent all variation between multiple genomes, but existing methods for constructing them are biased due to reference-guided approaches. In response, we have developed PanGenome Graph Builder (PGGB), a reference-free pipeline for constructing unbi-ased pangenome graphs. PGGB uses all-to-all whole-genome alignments and learned graph embeddings to build and iteratively refine a model in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

Spontaneous Mutation Rates and Spectra of Respiratory-Deficient Yeast.

The yeast petite mutant was first discovered in the yeast Saccharomyces cerevisiae, which shows growth stress due to defects in genes encoding the respiratory chain. In a previous study, we described that deletion of the nuclear-encoded gene MRPL25 leads to mitochondrial genome (mtDNA) loss and the petite phenotype, which can be rescued by acquiring ATP3 mutations. The mrpl25Δ strain showed an elevated SNV (single nucleotide variant) rate, suggesting genome instability occurred during the crisis of mtDNA loss. However, the genome-wide mutation landscape and mutational signatures of mitochondrial dysfunction are unknown. In this study we profiled the mutation spectra in yeast strains with the genotype combination of MRPL25 and ATP3 in their wildtype and mutated status, along with the wildtype and cytoplasmic petite rho0 strains as controls. In addition to the previously described elevated SNV rate, we found the INDEL (insertion/deletion) rate also increased in the mrpl25Δ strain, reinforcing the occurrence of genome instability. Notably, although both are petites, the mrpl25Δ and rho0 strains exhibited different INDEL rates and transition/transversion ratios, suggesting differences in the mutational signatures underlying these two types of petites. Interestingly, the petite-related mutagenesis effect disappeared when ATP3 suppressor mutations were acquired, suggesting a cost-effective mechanism for restoring both fitness and genome stability. Taken together, we present an unbiased genome-wide characterization of the mutation rates and spectra of yeast strains with respiratory deficiency, which provides valuable insights into the impact of respiratory deficiency on genome instability.

Telomeres are shorter in wild Saccharomyces cerevisiae isolates than in domesticated ones.

Telomeres are ribonucleoproteins that cap chromosome-ends and their DNA length is controlled by counteracting elongation and shortening processes. The budding yeast Saccharomyces cerevisiae has been a leading model to study telomere DNA length control and dynamics. Its telomeric DNA is maintained at a length that slightly varies between laboratory strains, but little is known about its variation at the species level. The recent publication of the genomes of over 1,000 S. cerevisiae strains enabled us to explore telomere DNA length variation at an unprecedented scale. Here, we developed a bioinformatic pipeline (YeaISTY) to estimate telomere DNA length from whole-genome sequences and applied it to the sequenced S. cerevisiae collection. Our results revealed broad natural telomere DNA length variation among the isolates. Notably, telomere DNA length is shorter in those derived from wild rather than domesticated environments. Moreover, telomere DNA length variation is associated with mitochondrial metabolism, and this association is driven by wild strains. Overall, these findings reveal broad variation in budding yeast's telomere DNA length regulation, which might be shaped by its different ecological life-styles.

Evolution of yeast hybrids by aborted meiosis.

Sterile hybrids are broadly considered evolutionary dead-ends because of their faulty sexual reproduction. While sterility in obligate sexual organisms is a clear constraint in perpetuating the species, some facultative sexual microbes such as yeasts can propagate asexually and maintain genome plasticity. Moreover, incomplete meiotic pathways in yeasts represent alternative routes to the standard meiosis that generates genetic combinations in the population and fuel adaptation. Here, we review how aborting meiosis promotes genome-wide allele shuffling in sterile Saccharomyces hybrids and describe approaches to identify evolved clones in a cell population. We further discuss possible implications of this process in generating phenotypic novelty and report cases of abortive meiosis across yeast species.

Genetically controlled mtDNA deletions prevent ROS damage by arresting oxidative phosphorylation.

Deletion of mitochondrial DNA in eukaryotes is currently attributed to rare accidental events associated with mitochondrial replication or repair of double-strand breaks. We report the discovery that yeast cells arrest harmful intramitochondrial superoxide production by shutting down respiration through genetically controlled deletion of mitochondrial oxidative phosphorylation genes. We show that this process critically involves the antioxidant enzyme superoxide dismutase 2 and two-way mitochondrial-nuclear communication through Rtg2 and Rtg3. While mitochondrial DNA homeostasis is rapidly restored after cessation of a short-term superoxide stress, long-term stress causes maladaptive persistence of the deletion process, leading to complete annihilation of the cellular pool of intact mitochondrial genomes and irrevocable loss of respiratory ability. This shows that oxidative stress-induced mitochondrial impairment may be under strict regulatory control. If the results extend to human cells, the results may prove to be of etiological as well as therapeutic importance with regard to age-related mitochondrial impairment and disease.

Resistance to Arsenite and Arsenate in Saccharomyces cerevisiae Arises through the Subtelomeric Expansion of a Cluster of Yeast Genes.

Arsenic is one of the most prevalent toxic elements in the environment, and its toxicity affects every organism. Arsenic resistance has mainly been observed in microorganisms, and, in bacteria, it has been associated with the presence of the Ars operon. In Saccharomyces cerevisiae, three genes confer arsenic resistance: ARR1, ARR2, and ARR3. Unlike bacteria, in which the presence of the Ars genes confers per se resistance to arsenic, most of the S. cerevisiae isolates present the three ARR genes, regardless of whether the strain is resistant or sensitive to arsenic. To assess the genetic features that make natural S. cerevisiae strains resistant to arsenic, we used a combination of comparative genomic hybridization, whole-genome sequencing, and transcriptomics profiling with microarray analyses. We observed that both the presence and the genomic location of multiple copies of the whole cluster of ARR genes were central to the escape from subtelomeric silencing and the acquisition of resistance to arsenic. As a result of the repositioning, the ARR genes were expressed even in the absence of arsenic. In addition to their relevance in improving our understanding of the mechanism of arsenic resistance in yeast, these results provide evidence for a new cluster of functionally related genes that are independently duplicated and translocated.

miRNAs Copy Number Variations Repertoire as Hallmark Indicator of Cancer Species Predisposition.

Aging is one of the hallmarks of multiple human diseases, including cancer. We hypothesized that variations in the number of copies (CNVs) of specific genes may protect some long-living organisms theoretically more susceptible to tumorigenesis from the onset of cancer. Based on the statistical comparison of gene copy numbers within the genomes of both cancer-prone and -resistant species, we identified novel gene targets linked to tumor predisposition, such as CD52, SAT1 and SUMO. Moreover, considering their genome-wide copy number landscape, we discovered that microRNAs (miRNAs) are among the most significant gene families enriched for cancer progression and predisposition. Through bioinformatics analyses, we identified several alterations in miRNAs copy number patterns, involving miR-221, miR-222, miR-21, miR-372, miR-30b, miR-30d and miR-31, among others. Therefore, our analyses provide the first evidence that an altered miRNAs copy number signature can statistically discriminate species more susceptible to cancer from those that are tumor resistant, paving the way for further investigations.

Extensive simulations assess the performance of genome-wide association mapping in various Saccharomyces cerevisiae subpopulations.

With the advent of high throughput sequencing technologies, genome-wide association studies (GWAS) have become a powerful paradigm for dissecting the genetic origins of the observed phenotypic variation. We recently completely sequenced the genome of 1011 Saccharomyces cerevisiae isolates, laying a strong foundation for GWAS. To assess the feasibility and the limits of this approach, we performed extensive simulations using five selected subpopulations as well as the total set of 1011 genomes. We measured the ability to detect the causal genetic variants involved in Mendelian and more complex traits using a linear mixed model approach. The results showed that population structure is well accounted for and is not the main problem when the sample size is high enough. While the genetic determinant of a Mendelian trait is easily mapped in all studied subpopulations, discrepancies are seen between datasets when performing GWAS on a complex trait in terms of detection, false positive and false negative rate. Finally, we performed GWAS on the different defined subpopulations using a real quantitative trait (resistance to copper sulfate) and showed the feasibility of this approach. The performance of each dataset depends simultaneously on several factors such as sample size, relatedness and population evolutionary history. This article is part of the theme issue 'Genetic basis of adaptation and speciation: from loci to causative mutations'.

RecombineX: A generalized computational framework for automatic high-throughput gamete genotyping and tetrad-based recombination analysis.

Meiotic recombination is an essential biological process that ensures faithful chromosome segregation and promotes parental allele shuffling. Tetrad analysis is a powerful approach to quantify the genetic makeups and recombination landscapes of meiotic products. Here we present RecombineX (https://github.com/yjx1217/RecombineX), a generalized computational framework that automates the full workflow of marker identification, gamete genotyping, and tetrad-based recombination profiling based on any organism or genetic background with batch processing capability. Aside from conventional reference-based analysis, RecombineX can also perform analysis based on parental genome assemblies, which facilitates analyzing meiotic recombination landscapes in their native genomic contexts. Additional features such as copy number variation profiling and missing genotype inference further enhance downstream analysis. RecombineX also includes a dedicate module for simulating the genomes and reads of recombinant tetrads, which enables fine-tuned simulation-based hypothesis testing. This simulation module revealed the power and accuracy of RecombineX even when analyzing tetrads with very low sequencing depths (e.g., 1-2X). Tetrad sequencing data from the budding yeast Saccharomyces cerevisiae and green alga Chlamydomonas reinhardtii were further used to demonstrate the accuracy and robustness of RecombineX for organisms with both small and large genomes, manifesting RecombineX as an all-around one stop solution for future tetrad analysis. Interestingly, our re-analysis of the budding yeast tetrad sequencing data with RecombineX and Oxford Nanopore sequencing revealed two unusual structural rearrangement events that were not noticed before, which exemplify the occasional genome instability triggered by meiosis.