Dissection of quantitative traits by bulk segregant mapping in a protoploid yeast species

Rapid evolutionary repair by secondary perturbation of a primary disrupted transcriptional network

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict-free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss-of-function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade-off phenotypes. The trade-offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population.

Overdominant and partially dominant mutations drive clonal adaptation in diploid Saccharomyces cerevisiae

Identification of adaptive targets in experimental evolution typically relies on extensive replication and genetic reconstruction. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of evolved mutations. Here, we apply this method to six Saccharomyces cerevisiae clones isolated from four diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains 17-26 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of the evolved clones to a barcoded haploid version of the ancestor. We competed the resulting barcoded diploids en masse and quantified fitness in the experimental and alternative environments by barcode sequencing. We estimated average fitness effects of evolved mutations using barcode-based fitness assays and whole genome sequencing for a subset of segregants. In contrast to our previous work with haploid evolved clones, we find that diploids carry fewer beneficial mutations, with modest fitness effects (up to 5.4%) in the environment in which they arose. In agreement with theoretical expectations, reconstruction experiments show that all mutations with a detectable fitness effect manifest some degree of dominance over the ancestral allele, and most are overdominant. Genotypes with lower fitness effects in alternative environments allowed us to identify conditions that drive adaptation in our system.

Dissection of quantitative trait loci in the Lachancea waltii yeast species highlights major hotspots

Dissecting the genetic basis of complex trait remains a real challenge. The budding yeast Saccharomyces cerevisiae has become a model organism for studying quantitative traits, successfully increasing our knowledge in many aspects. However, the exploration of the genotype-phenotype relationship in non-model yeast species could provide a deeper insight into the genetic basis of complex traits. Here, we have studied this relationship in the Lachancea waltii species which diverged from the S. cerevisiae lineage prior to the whole-genome duplication. By performing linkage mapping analyses in this species, we identified 86 quantitative trait loci (QTL) impacting the growth in a large number of conditions. The distribution of these loci across the genome has revealed two major QTL hotspots. A first hotspot corresponds to a general growth QTL, impacting a wide range of conditions. By contrast, the second hotspot highlighted a trade-off with a disadvantageous allele for drug-free conditions which proved to be advantageous in the presence of several drugs. Finally, a comparison of the detected QTL in L. waltii with those which had been previously identified for the same trait in a closely related species, Lachancea kluyveri was performed. This analysis clearly showed the absence of shared QTL across these species. Altogether, our results represent a first step toward the exploration of the genetic architecture of quantitative trait across different yeast species.

Pervasive Phenotypic Impact of a Large Nonrecombining Introgressed Region in Yeast

To explore the origin of the diversity observed in natural populations, many studies have investigated the relationship between genotype and phenotype. In yeast species, especially in Saccharomyces cerevisiae, these studies are mainly conducted using recombinant offspring derived from two genetically diverse isolates, allowing to define the phenotypic effect of genetic variants. However, large genomic variants such as interspecies introgressions are usually overlooked even if they are known to modify the genotype–phenotype relationship. To have a better insight into the overall phenotypic impact of introgressions, we took advantage of the presence of a 1-Mb introgressed region, which lacks recombination and contains the mating-type determinant in the Lachancea kluyveri budding yeast. By performing linkage mapping analyses in this species, we identified a total of 89 loci affecting growth fitness in a large number of conditions and 2,187 loci affecting gene expression mostly grouped into two major hotspots, one being the introgressed region carrying the mating-type locus. Because of the absence of recombination, our results highlight the presence of a sexual dimorphism in a budding yeast for the first time. Overall, by describing the phenotype–genotype relationship in the Lachancea kluyveri species, we expanded our knowledge on how genetic characteristics of large introgression events can affect the phenotypic landscape.

QTL analysis of natural Saccharomyces cerevisiae isolates reveals unique alleles involved in lignocellulosic inhibitor tolerance

Decoding the genetic basis of lignocellulosic inhibitor tolerance in Saccharomyces cerevisiae is crucial for rational engineering of bioethanol strains with enhanced robustness. The genetic diversity of natural strains present an invaluable resource for the exploration of complex traits of industrial importance from a pan-genomic perspective to complement the limited range of specialised, tolerant industrial strains. Natural S. cerevisiae isolates have lately garnered interest as a promising toolbox for engineering novel, genetically encoded tolerance phenotypes into commercial strains. To this end, we investigated the genetic basis for lignocellulosic inhibitor tolerance of natural S. cerevisiae isolates. A total of 12 quantitative trait loci underpinning tolerance were identified by next-generation sequencing linked bulk-segregant analysis of superior interbred pools. Our findings corroborate the current perspective of lignocellulosic inhibitor tolerance as a multigenic, complex trait. Apart from a core set of genetic variants required for inhibitor tolerance, an additional genetic background-specific response was observed. Functional analyses of the identified genetic loci revealed the uncharacterised ORF, YGL176C and the bud-site selection XRN1/BUD13 as potentially beneficial alleles contributing to tolerance to a complex lignocellulosic inhibitor mixture. We present evidence for the consideration of both regulatory and coding sequence variants for strain improvement.

PyBSASeq: a simple and effective algorithm for bulked segregant analysis with whole-genome sequencing data

BACKGROUND

Bulked segregant analysis (BSA), coupled with next-generation sequencing, allows the rapid identification of both qualitative and quantitative trait loci (QTL), and this technique is referred to as BSA-Seq here. The current SNP index method and G-statistic method for BSA-Seq data analysis require relatively high sequencing coverage to detect significant single nucleotide polymorphism (SNP)-trait associations, which leads to high sequencing cost.

RESULTS

We developed a simple and effective algorithm for BSA-Seq data analysis and implemented it in Python; the program was named PyBSASeq. Using PyBSASeq, the significant SNPs (sSNPs), SNPs likely associated with the trait, were identified via Fisher's exact test, and then the ratio of the sSNPs to total SNPs in a chromosomal interval was used to detect the genomic regions that condition the trait of interest. The results obtained this way are similar to those generated via the current methods, but with more than five times higher sensitivity. This approach was termed the significant SNP method here.

CONCLUSIONS

The significant SNP method allows the detection of SNP-trait associations at much lower sequencing coverage than the current methods, leading to ~ 80% lower sequencing cost and making BSA-Seq more accessible to the research community and more applicable to the species with a large genome.

Correlating Genotype and Phenotype in the Asexual Yeast Candida orthopsilosis Implicates ZCF29 in Sensitivity to Caffeine

Candida orthopsilosis is diploid asexual yeast that causes human disease. Most C. orthopsilosis isolates arose from at least four separate hybridizations between related, but not identical, parents. Here, we used population genomics data to correlate genotypic and phenotypic variation in 28 C. orthopsilosis isolates. We used cosine similarity scores to identify 65 variants with potential high-impact (deleterious effects) that correlated with specific phenotypes. Of these, 19 were Single Nucleotide Polymorphisms (SNPs) that changed stop or start codons, or splice sites. One variant resulted in a premature stop codon in both alleles of the gene ZCF29 in C. orthopsilosis isolate 185, which correlated with sensitivity to nystatin and caffeine. We used CRISPR-Cas9 editing to introduce this polymorphism into two resistant C. orthopsilosis isolates. Introducing the stop codon resulted in sensitivity to caffeine and to ketoconazole, but not to nystatin. Our analysis shows that it is possible to associate genomic variants with phenotype in asexual Candida species, but that only a small amount of genomic variation can be easily explored.

Sources of Fungal Genetic Variation and Associating It with Phenotypic Diversity

The first eukaryotic genome to be sequenced was fungal, and there continue to be more sequenced genomes in the kingdom Fungi than in any other eukaryotic kingdom. Comparison of these genomes reveals many sources of genetic variation, from single nucleotide polymorphisms to horizontal gene transfer and on to changes in the arrangement and number of chromosomes, not to mention endofungal bacteria and viruses. Population genomics shows that all sources generate variation all the time and implicate natural selection as the force maintaining genome stability. Variation in wild populations is a rich resource for associating genetic variation with phenotypic variation, whether through quantitative trait locus mapping, genome-wide association studies, or reverse ecology. Subjects of studies associating genetic and phenotypic variation include model fungi, e.g., Saccharomyces and Neurospora, but pioneering studies have also been made with fungi pathogenic to plants, e.g., Pyricularia (= Magnaporthe), Zymoseptoria, and Fusarium, and to humans, e.g., Coccidioides, Cryptococcus, and Candida.

Variation of the meiotic recombination landscape and properties over a broad evolutionary distance in yeasts

Meiotic recombination is a major factor of genome evolution, deeply characterized in only a few model species, notably the yeast Saccharomyces cerevisiae. Consequently, little is known about variations of its properties across species. In this respect, we explored the recombination landscape of Lachancea kluyveri, a protoploid yeast species that diverged from the Saccharomyces genus more than 100 million years ago and we found striking differences with S. cerevisiae. These variations include a lower recombination rate, a higher frequency of chromosomes segregating without any crossover and the absence of recombination on the chromosome arm containing the sex locus. In addition, although well conserved within the Saccharomyces clade, the S. cerevisiae recombination hotspots are not conserved over a broader evolutionary distance. Finally and strikingly, we found evidence of frequent reversal of commitment to meiosis, resulting in return to mitotic growth after allele shuffling. Identification of this major but underestimated evolutionary phenomenon illustrates the relevance of exploring non-model species.

Meiotic recombination promotes accurate chromosome segregation and genetic diversity. To date, the mechanisms and rules lying behind recombination were dissected using model organisms such as the budding yeast Saccharomyces cerevisiae. To assess the conservation and variation of this process over a broad evolutionary distance, we explored the meiotic recombination landscape in Lachancea kluyveri, a budding yeast species that diverged from S. cerevisiae more than 100 million years ago. The meiotic recombination map we generated revealed that the meiotic recombination landscape and properties significantly vary across distantly related yeast species, raising the yet to confirm possibility that recombination hotspots conservation across yeast species depends on synteny conservation. Finally, the frequent meiotic reversions we observed led us to re-evaluate their evolutionary importance.