Trait variation in yeast is defined by population history

Evolution of ecological dominance of yeast species in high-sugar environments

In budding yeasts, fermentation in the presence of oxygen evolved around the time of a whole genome duplication (WGD) and is thought to confer dominance in high-sugar environments because ethanol is toxic to many species. Although there are many fermentative yeast species, only Saccharomyces cerevisiae consistently dominates wine fermentations. In this study, we use coculture experiments and intrinsic growth rate assays to examine the relative fitness of non-WGD and WGD yeast species across environments to assess when S. cerevisiae's ability to dominate high-sugar environments arose. We show that S. cerevisiae dominates nearly all other non-WGD and WGD species except for its sibling species S. paradoxus in both grape juice and a high-sugar rich medium. Of the species we tested, S. cerevisiae and S. paradoxus have evolved the highest ethanol tolerance and intrinsic growth rate in grape juice. However, the ability of S. cerevisiae and S. paradoxus to dominate certain species depends on the temperature and the type of high-sugar environment. Our results indicate that dominance of high-sugar environments evolved much more recently than the WGD, most likely just prior to or during the differentiation of Saccharomyces species, and that evolution of multiple traits contributes to S. cerevisiae's ability to dominate wine fermentations.

Diversity and adaptive evolution of Saccharomyces wine yeast: a review

Saccharomyces cerevisiae and related species, the main workhorses of wine fermentation, have been exposed to stressful conditions for millennia, potentially resulting in adaptive differentiation. As a result, wine yeasts have recently attracted considerable interest for studying the evolutionary effects of domestication. The widespread use of whole-genome sequencing during the last decade has provided new insights into the biodiversity, population structure, phylogeography and evolutionary history of wine yeasts. Comparisons between S. cerevisiae isolates from various origins have indicated that a variety of mechanisms, including heterozygosity, nucleotide and structural variations, introgressions, horizontal gene transfer and hybridization, contribute to the genetic and phenotypic diversity of S. cerevisiae. This review will summarize the current knowledge on the diversity and evolutionary history of wine yeasts, focusing on the domestication fingerprints identified in these strains.

This review summarizes current knowledge and recent advances on the diversity and evolutionary history of Saccharomyces cerevisiae wine yeasts, focusing on the domestication fingerprints identified in these strains.

Breeding Strategy To Generate Robust Yeast Starter Cultures for Cocoa Pulp Fermentations

Cocoa pulp fermentation is a spontaneous process during which the natural microbiota present at cocoa farms is allowed to ferment the pulp surrounding cocoa beans. Because such spontaneous fermentations are inconsistent and contribute to product variability, there is growing interest in a microbial starter culture that could be used to inoculate cocoa pulp fermentations. Previous studies have revealed that many different fungi are recovered from different batches of spontaneous cocoa pulp fermentations, whereas the variation in the prokaryotic microbiome is much more limited. In this study, therefore, we aimed to develop a suitable yeast starter culture that is able to outcompete wild contaminants and consistently produce high-quality chocolate. Starting from specifically selected Saccharomyces cerevisiae strains, we developed robust hybrids with characteristics that allow them to efficiently ferment cocoa pulp, including improved temperature tolerance and fermentation capacity. We conducted several laboratory and field trials to show that these new hybrids often outperform their parental strains and are able to dominate spontaneous pilot scale fermentations, which results in much more consistent microbial profiles. Moreover, analysis of the resulting chocolate showed that some of the cocoa batches that were fermented with specific starter cultures yielded superior chocolate. Taken together, these results describe the development of robust yeast starter cultures for cocoa pulp fermentations that can contribute to improving the consistency and quality of commercial chocolate production.

Population structure of mitochondrial genomes in Saccharomyces cerevisiae

Background

Rigorous study of mitochondrial functions and cell biology in the budding yeast, Saccharomyces cerevisiae has advanced our understanding of mitochondrial genetics. This yeast is now a powerful model for population genetics, owing to large genetic diversity and highly structured populations among wild isolates. Comparative mitochondrial genomic analyses between yeast species have revealed broad evolutionary changes in genome organization and architecture. A fine-scale view of recent evolutionary changes within S. cerevisiae has not been possible due to low numbers of complete mitochondrial sequences.

Results

To address challenges of sequencing AT-rich and repetitive mitochondrial DNAs (mtDNAs), we sequenced two divergent S. cerevisiae mtDNAs using a single-molecule sequencing platform (PacBio RS). Using de novo assemblies, we generated highly accurate complete mtDNA sequences. These mtDNA sequences were compared with 98 additional mtDNA sequences gathered from various published collections. Phylogenies based on mitochondrial coding sequences and intron profiles revealed that intraspecific diversity in mitochondrial genomes generally recapitulated the population structure of nuclear genomes. Analysis of intergenic sequence indicated a recent expansion of mobile elements in certain populations. Additionally, our analyses revealed that certain populations lacked introns previously believed conserved throughout the species, as well as the presence of introns never before reported in S. cerevisiae.

Conclusions

Our results revealed that the extensive variation in S. cerevisiae mtDNAs is often population specific, thus offering a window into the recent evolutionary processes shaping these genomes. In addition, we offer an effective strategy for sequencing these challenging AT-rich mitochondrial genomes for small scale projects.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1664-4) contains supplementary material, which is available to authorized users.

Comparative genomics of Saccharomyces cerevisiae natural isolates for bioenergy production

Lignocellulosic plant material is a viable source of biomass to produce alternative energy including ethanol and other biofuels. However, several factors—including toxic byproducts from biomass pretreatment and poor fermentation of xylose and other pentose sugars—currently limit the efficiency of microbial biofuel production. To begin to understand the genetic basis of desirable traits, we characterized three strains of Saccharomyces cerevisiae with robust growth in a pretreated lignocellulosic hydrolysate or tolerance to stress conditions relevant to industrial biofuel production, through genome and transcriptome sequencing analysis. All stress resistant strains were highly mosaic, suggesting that genetic admixture may contribute to novel allele combinations underlying these phenotypes. Strain-specific gene sets not found in the lab strain were functionally linked to the tolerances of particular strains. Furthermore, genes with signatures of evolutionary selection were enriched for functional categories important for stress resistance and included stress-responsive signaling factors. Comparison of the strains’ transcriptomic responses to heat and ethanol treatment—two stresses relevant to industrial bioethanol production—pointed to physiological processes that were related to particular stress resistance profiles. Many of the genotype-by-environment expression responses occurred at targets of transcription factors with signatures of positive selection, suggesting that these strains have undergone positive selection for stress tolerance. Our results generate new insights into potential mechanisms of tolerance to stresses relevant to biofuel production, including ethanol and heat, present a backdrop for further engineering, and provide glimpses into the natural variation of stress tolerance in wild yeast strains.

Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype

Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants’ effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage of analyzing allele-specific transcriptional dynamics of mediating genes. Applications in higher eukaryotes can be valuable for inferring causal molecular pathways underlying complex dynamic processes, such as development, physiology and disease progression.

The causal path from a genetic variant to a complex phenotype such as disease progression is often not known. Studying gene expression variation is one approach to identify the mediating genes, however, it is difficult to distinguish causative from correlative genes. This becomes a challenge especially when studying developmental and physiological traits, since they involve dynamic processes contributing to the variation and only single static expression profiling is performed. As a proof of concept, we addressed this challenge here in yeast, by studying genome-wide gene expression in the presence of the causative polymorphism of MKT1 as the sole genetic variant, during the time phase when it contributes to sporulation efficiency variation. Our analysis during early sporulation identified mitochondrial retrograde signaling and nitrogen starvation as novel regulators, acting additively to regulate sporulation efficiency. Furthermore, we showed that PUF3, a known interactor of MKT1 had an independent role in sporulation. Our results highlight the role of differential mitochondrial signaling for efficient meiosis, providing insights into the factors regulating infertility. In addition, our study has implications for characterizing the molecular effects of causal genetic variants on dynamic biological processes during development and disease progression.

Ecological and Genetic Barriers Differentiate Natural Populations of Saccharomyces cerevisiae

How populations that inhabit the same geographical area become genetically differentiated is not clear. To investigate this, we characterized phenotypic and genetic differences between two populations of Saccharomyces cerevisiae that in some cases inhabit the same environment but show relatively little gene flow. We profiled stress sensitivity in a group of vineyard isolates and a group of oak-soil strains and found several niche-related phenotypes that distinguish the populations. We performed bulk-segregant mapping on two of the distinguishing traits: The vineyard-specific ability to grow in grape juice and oak-specific tolerance to the cell wall damaging drug Congo red. To implicate causal genes, we also performed a chemical genomic screen in the lab-strain deletion collection and identified many important genes that fell under quantitative trait loci peaks. One gene important for growth in grape juice and identified by both the mapping and the screen was SSU1, a sulfite-nitrite pump implicated in wine fermentations. The beneficial allele is generated by a known translocation that we reasoned may also serve as a genetic barrier. We found that the translocation is prevalent in vineyard strains, but absent in oak strains, and presents a postzygotic barrier to spore viability. Furthermore, the translocation was associated with a fitness cost to the rapid growth rate seen in oak-soil strains. Our results reveal the translocation as a dual-function locus that enforces ecological differentiation while producing a genetic barrier to gene flow in these sympatric populations.

The 100-genomes strains, an S. cerevisiae resource that illuminates its natural phenotypic and genotypic variation and emergence as an opportunistic pathogen

Saccharomyces cerevisiae, a well-established model for species as diverse as humans and pathogenic fungi, is more recently a model for population and quantitative genetics. S. cerevisiae is found in multiple environments—one of which is the human body—as an opportunistic pathogen. To aid in the understanding of the S. cerevisiae population and quantitative genetics, as well as its emergence as an opportunistic pathogen, we sequenced, de novo assembled, and extensively manually edited and annotated the genomes of 93 S. cerevisiae strains from multiple geographic and environmental origins, including many clinical origin strains. These 93 S. cerevisiae strains, the genomes of which are near-reference quality, together with seven previously sequenced strains, constitute a novel genetic resource, the “100-genomes” strains. Our sequencing coverage, high-quality assemblies, and annotation provide unprecedented opportunities for detailed interrogation of complex genomic loci, examples of which we demonstrate. We found most phenotypic variation to be quantitative and identified population, genotype, and phenotype associations. Importantly, we identified clinical origin associations. For example, we found that an introgressed PDR5 was present exclusively in clinical origin mosaic group strains; that the mosaic group was significantly enriched for clinical origin strains; and that clinical origin strains were much more copper resistant, suggesting that copper resistance contributes to fitness in the human host. The 100-genomes strains are a novel, multipurpose resource to advance the study of S. cerevisiae population genetics, quantitative genetics, and the emergence of an opportunistic pathogen.

Protocols and programs for high-throughput growth and aging phenotyping in yeast

In microorganisms, and more particularly in yeasts, a standard phenotyping approach consists in the analysis of fitness by growth rate determination in different conditions. One growth assay that combines high throughput with high resolution involves the generation of growth curves from 96-well plate microcultivations in thermostated and shaking plate readers. To push the throughput of this method to the next level, we have adapted it in this study to the use of 384-well plates. The values of the extracted growth parameters (lag time, doubling time and yield of biomass) correlated well between experiments carried out in 384-well plates as compared to 96-well plates or batch cultures, validating the higher-throughput approach for phenotypic screens. The method is not restricted to the use of the budding yeast Saccharomyces cerevisiae, as shown by consistent results for other species selected from the Hemiascomycete class. Furthermore, we used the 384-well plate microcultivations to develop and validate a higher-throughput assay for yeast Chronological Life Span (CLS), a parameter that is still commonly determined by a cumbersome method based on counting "Colony Forming Units". To accelerate analysis of the large datasets generated by the described growth and aging assays, we developed the freely available software tools GATHODE and CATHODE. These tools allow for semi-automatic determination of growth parameters and CLS behavior from typical plate reader output files. The described protocols and programs will increase the time- and cost-efficiency of a number of yeast-based systems genetics experiments as well as various types of screens.

The fascinating and secret wild life of the budding yeast S. cerevisiae

The budding yeast Saccharomyces cerevisiae has been used in laboratory experiments for over a century and has been instrumental in understanding virtually every aspect of molecular biology and genetics. However, it wasn't until a decade ago that the scientific community started to realise how little was known about this yeast's ecology and natural history, and how this information was vitally important for interpreting its biology. Recent large-scale population genomics studies coupled with intensive field surveys have revealed a previously unappreciated wild lifestyle of S. cerevisiae outside the restrictions of human environments and laboratories. The recent discovery that Chinese isolates harbour almost twice as much genetic variation as isolates from the rest of the world combined suggests that Asia is the likely origin of the modern budding yeast.

DOI:http://dx.doi.org/10.7554/eLife.05835.001

AGAPE (Automated Genome Analysis PipelinE) for pan-genome analysis of Saccharomyces cerevisiae

The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community.

The genomic and phenotypic diversity of Schizosaccharomyces pombe

Natural variation within species reveals aspects of genome evolution and function. The fission yeast Schizosaccharomyces pombe is an important model for eukaryotic biology, but researchers typically use one standard laboratory strain. To extend the usefulness of this model, we surveyed the genomic and phenotypic variation in 161 natural isolates. We sequenced the genomes of all strains, finding moderate genetic diversity (π = 3 × 10(-3) substitutions/site) and weak global population structure. We estimate that dispersal of S. pombe began during human antiquity (∼340 BCE), and ancestors of these strains reached the Americas at ∼1623 CE. We quantified 74 traits, finding substantial heritable phenotypic diversity. We conducted 223 genome-wide association studies, with 89 traits showing at least one association. The most significant variant for each trait explained 22% of the phenotypic variance on average, with indels having larger effects than SNPs. This analysis represents a rich resource to examine genotype-phenotype relationships in a tractable model.

A Boolean gene regulatory model of heterosis and speciation

BACKGROUND

Modelling genetic phenomena affecting biological traits is important for the development of agriculture as it allows breeders to predict the potential of breeding for certain traits. One such phenomenon is heterosis or hybrid vigor: crossing individuals from genetically distinct populations often results in improvements in quantitative traits, such as growth rate, biomass production and stress resistance. Heterosis has become a very useful tool in global agriculture, but its genetic basis remains controversial and its effects hard to predict. We have taken a computational approach to studying heterosis, developing a simulation of evolution, independent reassortment of alleles and hybridization of Gene Regulatory Networks (GRNs) in a Boolean framework. These artificial regulatory networks exhibit topological properties that reflect those observed in biology, and fitness is measured as the ability of a network to respond to external inputs in a pre-defined way.

RESULTS

Our model reproduced common experimental observations on heterosis using only biologically justified parameters, such as mutation rates. Hybrid vigor was observed and its extent was seen to increase as parental populations diverged, up until a point of sudden collapse of hybrid fitness. Thus, the model also describes a process akin to speciation due to genetic incompatibility of the separated populations. We also reproduce, for the first time in a model, the fact that hybrid vigor cannot easily be fixed by within a breeding line, currently an important limitation of the use of hybrid crops. The simulation allowed us to study the effects of three standard models for the genetic basis of heterosis: dominance, over-dominance, and epistasis.

CONCLUSION

This study describes the most detailed simulation of heterosis using gene regulatory networks to date and reproduces several phenomena associated with heterosis for the first time in a model. The level of detail in our model allows us to suggest possible warning signs of the impending collapse of hybrid vigor in breeding. In addition, the simulation provides a framework that can be extended to study other aspects of heterosis and alternative evolutionary scenarios.

Differential regulation of antagonistic pleiotropy in synthetic and natural populations suggests its role in adaptation

Antagonistic pleiotropy (AP), the ability of a gene to show opposing effects in different phenotypes, has been identified in various life history traits and complex disorders, indicating its fundamental role in balancing fitness over the course of evolution. It is intuitive that natural selection might maintain AP to allow organisms phenotypic flexibility in different environments. However, despite several attempts, little evidence exists for its role in adaptation. We performed a meta-analysis in yeast to identify the genetic basis of AP in bi-parental segregants, natural isolates, and a laboratory strain genome-wide deletion collection, by comparing growth in favorable and stress conditions. We found that whereas AP was abundant in the synthetic populations, it was absent in the natural isolates. This finding indicated resolution of trade-offs, i.e., mitigation of trade-offs over evolutionary history, probably through accumulation of compensatory mutations. In the deletion collection, organizational genes showed AP, suggesting ancient resolutions of trade-offs in the basic cellular pathways. We find abundant AP in the segregants, greater than estimated in the deletion collection or observed in previous studies, with IRA2, a negative regulator of the Ras/PKA signaling pathway, showing trade-offs across diverse environments. Additionally, IRA2 and several other Ras/PKA pathway genes showed balancing selection in isolates of S. cerevisiae and S. paradoxus, indicating that multiple alleles maintain AP in this pathway in natural populations. We propose that during AP resolution, retaining the ability to vary signaling pathways such as Ras/PKA, may provide organisms with phenotypic flexibility. However, with increasing organismal complexity AP resolution may become difficult. A partial resolution of AP could manifest as complex human diseases, and the inability to resolve AP may play a role in speciation. Our findings suggest that testing a universal phenomenon like AP across multiple experimental systems may elucidate mechanisms underlying its regulation and evolution.

Metabolic variation in natural populations of wild yeast

Ecological diversification depends on the extent of genetic variation and on the pattern of covariation with respect to ecological opportunities. We investigated the pattern of utilization of carbon substrates in wild populations of budding yeast Saccharomyces paradoxus. All isolates grew well on a core diet of about 10 substrates, and most were also able to grow on a much larger ancillary diet comprising most of the 190 substrates we tested. There was substantial genetic variation within each population for some substrates. We found geographical variation of substrate use at continental, regional, and local scales. Isolates from Europe and North America could be distinguished on the basis of the pattern of yield across substrates. Two geographical races at the North American sites also differed in the pattern of substrate utilization. Substrate utilization patterns were also geographically correlated at local spatial scales. Pairwise genetic correlations between substrates were predominantly positive, reflecting overall variation in metabolic performance, but there was a consistent negative correlation between categories of substrates in two cases: between the core diet and the ancillary diet, and between pentose and hexose sugars. Such negative correlations in the utilization of substrate from different categories may indicate either intrinsic physiological trade-offs for the uptake and utilization of substrates from different categories, or the accumulation of conditionally neutral mutations. Divergence in substrate use accompanies genetic divergence at all spatial scales in S. paradoxus and may contribute to race formation and speciation.

Genetic mapping of MAPK-mediated complex traits Across S. cerevisiae

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.

Wild yeast strains differ in phenotypes that are controlled by highly conserved signaling pathways. Yet it remains unknown how naturally occurring genetic variants influence signaling pathways in yeast. We have developed an approach to facilitate the mapping of genetic variants that underlie these phenotypic differences in a set of wild strain. Our mapping approach requires minimal strain engineering and enables the rapid isolation of mapping populations from any strain background. In particular, we have mapped genetic variants in twelve highly diverse yeast strains. Further, we demonstrate how the mapping results from these twelve strains can be used jointly to narrow the number of genetic variants identified to a set of putative causal variants. We identify genetic variants in genes with various roles in cell signaling. Our results illustrate the interplay of different signaling pathways and which signaling genes are more likely to contain variants of large phenotypic impact.

The ecology and evolution of non-domesticated Saccharomyces species

Yeast researchers need model systems for ecology and evolution, but the model yeast Saccharomyces cerevisiae is not ideal because its evolution has been affected by domestication. Instead, ecologists and evolutionary biologists are focusing on close relatives of S. cerevisiae, the seven species in the genus Saccharomyces. The best-studied Saccharomyces yeast, after S. cerevisiae, is S. paradoxus, an oak tree resident throughout the northern hemisphere. In addition, several more members of the genus Saccharomyces have recently been discovered. Some Saccharomyces species are only found in nature, while others include both wild and domesticated strains. Comparisons between domesticated and wild yeasts have pinpointed hybridization, introgression and high phenotypic diversity as signatures of domestication. But studies of wild Saccharomyces natural history, biogeography and ecology are only beginning. Much remains to be understood about wild yeasts' ecological interactions and life cycles in nature. We encourage researchers to continue to investigate Saccharomyces yeasts in nature, both to place S. cerevisiae biology into its ecological context and to develop the genus Saccharomyces as a model clade for ecology and evolution.

Concerted evolution of life stage performances signals recent selection on yeast nitrogen use

Exposing natural selection driving phenotypic and genotypic adaptive differentiation is an extraordinary challenge. Given that an organism's life stages are exposed to the same environmental variations, we reasoned that fitness components, such as the lag, rate, and efficiency of growth, directly reflecting performance in these life stages, should often be selected in concert. We therefore conjectured that correlations between fitness components over natural isolates, in a particular environmental context, would constitute a robust signal of recent selection. Critically, this test for selection requires fitness components to be determined by different genetic loci. To explore our conjecture, we exhaustively evaluated the lag, rate, and efficiency of asexual population growth of natural isolates of the model yeast Saccharomyces cerevisiae in a large variety of nitrogen-limited environments. Overall, fitness components were well correlated under nitrogen restriction. Yeast isolates were further crossed in all pairwise combinations and coinheritance of each fitness component and genetic markers were traced. Trait variations tended to map to quantitative trait loci (QTL) that were private to a single fitness component. We further traced QTLs down to single-nucleotide resolution and uncovered loss-of-function mutations in RIM15, PUT4, DAL1, and DAL4 as the genetic basis for nitrogen source use variations. Effects of SNPs were unique for a single fitness component, strongly arguing against pleiotropy between lag, rate, and efficiency of reproduction under nitrogen restriction. The strong correlations between life stage performances that cannot be explained by pleiotropy compellingly support adaptive differentiation of yeast nitrogen source use and suggest a generic approach for detecting selection.

Unveiling nonessential gene deletions that confer significant morphological phenotypes beyond natural yeast strains

BACKGROUND

Phenotypes are variable within species, with high phenotypic variation in the fitness and cell morphology of natural yeast strains due to genetic variation. A gene deletion collection of yeast laboratory strains also contains phenotypic variations, demonstrating the involvement of each gene and its specific function. However, to date, no study has compared the phenotypic variations between natural strains and gene deletion mutants in yeast.

RESULTS

The morphological variance was compared between 110 most distinct gene deletion strains and 36 typical natural yeast strains using a generalized linear model. The gene deletion strains had higher morphological variance than the natural strains. Thirty-six gene deletion mutants conferred significant morphological changes beyond that of the natural strains, revealing the importance of the genes with high genetic interaction and specific cellular functions for species conservation.

CONCLUSION

Based on the morphological analysis, we discovered gene deletion mutants whose morphologies were not seen in nature. Our multivariate approach to the morphological diversity provided a new insight into the evolution and species conservation of yeast.

Acquisition of the ability to assimilate mannitol by Saccharomyces cerevisiae through dysfunction of the general corepressor Tup1-Cyc8

Saccharomyces cerevisiae normally cannot assimilate mannitol, a promising brown macroalgal carbon source for bioethanol production. The molecular basis of this inability remains unknown. We found that cells capable of assimilating mannitol arose spontaneously from wild-type S. cerevisiae during prolonged culture in mannitol-containing medium. Based on microarray data, complementation analysis, and cell growth data, we demonstrated that acquisition of mannitol-assimilating ability was due to spontaneous mutations in the genes encoding Tup1 or Cyc8, which constitute a general corepressor complex that regulates many kinds of genes. We also showed that an S. cerevisiae strain carrying a mutant allele of CYC8 exhibited superior salt tolerance relative to other ethanologenic microorganisms; this characteristic would be highly beneficial for the production of bioethanol from marine biomass. Thus, we succeeded in conferring the ability to assimilate mannitol on S. cerevisiae through dysfunction of Tup1-Cyc8, facilitating production of ethanol from mannitol.

Extensive heterosis in growth of yeast hybrids is explained by a combination of genetic models

Heterosis, also known as hybrid vigor, is the superior performance of a heterozygous hybrid relative to its homozygous parents. Despite the scientific curiosity of this phenotypic phenomenon and its significance for food production in agriculture, its genetic basis is insufficiently understood. Studying heterosis in yeast can potentially yield insights into its genetic basis, can allow one to test the different hypotheses that have been proposed to explain the phenomenon and allows better understanding of how to take advantage of this phenomenon to enhance food production. We therefore crossed 16 parental yeast strains to form 120 yeast hybrids, and measured their growth rates under five environmental conditions. A considerable amount of dominant genetic variation was found in growth performance, and heterosis was measured in 35% of the hybrid-condition combinations. Despite previous reports of correlations between heterosis and measures of sequence divergence between parents, we detected no such relationship. We used several analyses to examine which genetic model might explain heterosis. We found that dominance complementation of recessive alleles, overdominant interactions within loci and epistatic interactions among loci each contribute to heterosis. We concluded that in yeast heterosis is a complex phenotype created by the combined contribution of different genetic interactions.

Phenotypic evaluation of natural and industrial Saccharomyces yeasts for different traits desirable in industrial bioethanol production

Saccharomyces cerevisiae is the organism of choice for many food and beverage fermentations because it thrives in high-sugar and high-ethanol conditions. However, the conditions encountered in bioethanol fermentation pose specific challenges, including extremely high sugar and ethanol concentrations, high temperature, and the presence of specific toxic compounds. It is generally considered that exploring the natural biodiversity of Saccharomyces strains may be an interesting route to find superior bioethanol strains and may also improve our understanding of the challenges faced by yeast cells during bioethanol fermentation. In this study, we phenotypically evaluated a large collection of diverse Saccharomyces strains on six selective traits relevant for bioethanol production with increasing stress intensity. Our results demonstrate a remarkably large phenotypic diversity among different Saccharomyces species and among S. cerevisiae strains from different origins. Currently applied bioethanol strains showed a high tolerance to many of these relevant traits, but several other natural and industrial S. cerevisiae strains outcompeted the bioethanol strains for specific traits. These multitolerant strains performed well in fermentation experiments mimicking industrial bioethanol production. Together, our results illustrate the potential of phenotyping the natural biodiversity of yeasts to find superior industrial strains that may be used in bioethanol production or can be used as a basis for further strain improvement through genetic engineering, experimental evolution, or breeding. Additionally, our study provides a basis for new insights into the relationships between tolerance to different stressors.

The effect of hybrid transgression on environmental tolerance in experimental yeast crosses

Evidence is rapidly accumulating that hybridization generates adaptive variation. Transgressive segregation in hybrids could promote the colonization of new environments. Here, we use an assay to select hybrid genotypes that can proliferate in environmental conditions beyond the conditions tolerated by their parents, and we directly compete them against parental genotypes in habitats across environmental clines. We made 45 different hybrid swarms by crossing yeast strains (both Saccharomyces cerevisiae and S. paradoxus) with different genetic and phenotypic divergence. We compared the ability of hybrids and parents to colonize seven types of increasingly extreme environmental clines, representing both natural and novel challenges (mimicking pollution events). We found that a significant majority of hybrids had greater environmental ranges compared to the average of both their parents' ranges (mid-parent transgression), but only a minority of hybrids had ranges exceeding their best parent (best-parent transgression). Transgression was affected by the specific strains involved in the cross and by the test environment. Genetic and phenotypic crossing distance predicted the extent of transgression in only two of the seven environments. We isolated a set of potentially transgressive hybrids selected at the extreme ends of the clines and found that many could directly outcompete their parents across whole clines and were between 1.5- and 3-fold fitter on average. Saccharomyces yeast is a good model for quantitative and replicable experimental speciation studies, which may be useful in a world where hybridization is becoming increasingly common due to the relocation of plants and animals by humans.

Hybridization facilitates evolutionary rescue

The resilience of populations to rapid environmental degradation is a major concern for biodiversity conservation. When environments deteriorate to lethal levels, species must evolve to adapt to the new conditions to avoid extinction. Here, we test the hypothesis that evolutionary rescue may be enabled by hybridization, because hybridization increases genetic variability. Using experimental evolution, we show that interspecific hybrid populations of Saccharomyces yeast adapt to grow in more highly degraded environments than intraspecific and parental crosses, resulting in survival rates far exceeding those of their ancestors. We conclude that hybridization can increase evolutionary responsiveness and that taxa able to exchange genes with distant relatives may better survive rapid environmental change.

Large-scale selection and breeding to generate industrial yeasts with superior aroma production

The concentrations and relative ratios of various aroma compounds produced by fermenting yeast cells are essential for the sensory quality of many fermented foods, including beer, bread, wine, and sake. Since the production of these aroma-active compounds varies highly among different yeast strains, careful selection of variants with optimal aromatic profiles is of crucial importance for a high-quality end product. This study evaluates the production of different aroma-active compounds in 301 different Saccharomyces cerevisiae, Saccharomyces paradoxus, and Saccharomyces pastorianus yeast strains. Our results show that the production of key aroma compounds like isoamyl acetate and ethyl acetate varies by an order of magnitude between natural yeasts, with the concentrations of some compounds showing significant positive correlation, whereas others vary independently. Targeted hybridization of some of the best aroma-producing strains yielded 46 intraspecific hybrids, of which some show a distinct heterosis (hybrid vigor) effect and produce up to 45% more isoamyl acetate than the best parental strains while retaining their overall fermentation performance. Together, our results demonstrate the potential of large-scale outbreeding to obtain superior industrial yeasts that are directly applicable for commercial use.

Improving industrial yeast strains: exploiting natural and artificial diversity

Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as 'global transcription machinery engineering' (gTME), to induce genetic variation, providing a new source of yeast genetic diversity.

Metagenomics reveals that detoxification systems are underrepresented in marine bacterial communities

BACKGROUND

Environmental shotgun sequencing (metagenomics) provides a new way to study communities in microbial ecology. We here use sequence data from the Global Ocean Sampling (GOS) expedition to investigate toxicant selection pressures revealed by the presence of detoxification genes in marine bacteria. To capture a broad range of potential toxicants we selected detoxification protein families representing systems protecting microorganisms from a variety of stressors, such as metals, organic compounds, antibiotics and oxygen radicals.

RESULTS

Using a bioinformatics procedure based on comparative analysis to finished bacterial genomes we found that the amount of detoxification genes present in marine microorganisms seems surprisingly small. The underrepresentation is particularly evident for toxicant transporters and proteins involved in detoxifying metals. Exceptions are enzymes involved in oxidative stress defense where peroxidase enzymes are more abundant in marine bacteria compared to bacteria in general. In contrast, catalases are almost completely absent from the open ocean environment, suggesting that peroxidases and peroxiredoxins constitute a core line of defense against reactive oxygen species (ROS) in the marine milieu.

CONCLUSIONS

We found no indication that detoxification systems would be generally more abundant close to the coast compared to the open ocean. On the contrary, for several of the protein families that displayed a significant geographical distribution, like peroxidase, penicillin binding transpeptidase and divalent ion transport protein, the open ocean samples showed the highest abundance. Along the same lines, the abundance of most detoxification proteins did not increase with estimated pollution. The low level of detoxification systems in marine bacteria indicate that the majority of marine bacteria have a low capacity to adapt to increased pollution. Our study exemplifies the use of metagenomics data in ecotoxicology, and in particular how anthropogenic consequences on life in the sea can be examined.

Ploidy-regulated variation in biofilm-related phenotypes in natural isolates of Saccharomyces cerevisiae

The ability of yeast to form biofilms contributes to better survival under stressful conditions. We see the impact of yeast biofilms and “flocs” (clumps) in human health and industry, where forming clumps enables yeast to act as a natural filter in brewing and forming biofilms enables yeast to remain virulent in cases of fungal infection. Despite the importance of biofilms in yeast natural isolates, the majority of our knowledge about yeast biofilm genetics comes from work with a few tractable laboratory strains. A new collection of sequenced natural isolates from the Saccharomyces Genome Resequencing Project enabled us to examine the breadth of biofilm-related phenotypes in geographically, ecologically, and genetically diverse strains of Saccharomyces cerevisiae. We present a panel of 31 haploid and 24 diploid strains for which we have characterized six biofilm-related phenotypes: complex colony morphology, complex mat formation, flocculation, agar invasion, polystyrene adhesion, and psuedohyphal growth. Our results show that there is extensive phenotypic variation between and within strains, and that these six phenotypes are primarily uncorrelated or weakly correlated, with the notable exception of complex colony and complex mat formation. We also show that the phenotypic strength of these strains varies significantly depending on ploidy, and the diploid strains demonstrate both decreased and increased phenotypic strength with respect to their haploid counterparts. This is a more complex view of the impact of ploidy on biofilm-related phenotypes than previous work with laboratory strains has suggested, demonstrating the importance and enormous potential of working with natural isolates of yeast.

Colony-live--a high-throughput method for measuring microbial colony growth kinetics--reveals diverse growth effects of gene knockouts in Escherichia coli

Background

Precise quantitative growth measurements and detection of small growth changes in high-throughput manner is essential for fundamental studies of bacterial cell. However, an inherent tradeoff for measurement quality in high-throughput methods sacrifices some measurement quality. A key challenge has been how to enhance measurement quality without sacrificing throughput.

Results

We developed a new high-throughput measurement system, termed Colony-live. Here we show that Colony-live provides accurate measurement of three growth values (lag time of growth (LTG), maximum growth rate (MGR), and saturation point growth (SPG)) by visualizing colony growth over time. By using a new normalization method for colony growth, Colony-live gives more precise and accurate growth values than the conventional method. We demonstrated the utility of Colony-live by measuring growth values for the entire Keio collection of Escherichia coli single-gene knockout mutants. By using Colony-live, we were able to identify subtle growth defects of single-gene knockout mutants that were undetectable by the conventional method quantified by fixed time-point camera imaging. Further, Colony-live can reveal genes that influence the length of the lag-phase and the saturation point of growth.

Conclusions

Measurement quality is critical to achieving the resolution required to identify unique phenotypes among a diverse range of phenotypes. Sharing high-quality genome-wide datasets should benefit many researchers who are interested in specific gene functions or the architecture of cellular systems. Our Colony-live system provides a new powerful tool to accelerate accumulation of knowledge of microbial growth phenotypes.

Stochastic galactokinase expression underlies GAL gene induction in a GAL3 mutant of Saccharomyces cerevisiae

GAL1 and GAL3 are paralogous signal transducers that functionally inactivate Gal80p to activate the Gal4p-dependent transcriptional activation of GAL genes in Saccharomyces cerevisiae in response to galactose. Unlike a wild-type strain, the gal3∆ strain shows delayed growth kinetics as a result of the signaling function of GAL1. The mechanism ensuring that GAL1 is eventually expressed to turn on the GAL switch in the gal3∆ strain remains a paradox. Using galactose and histidine growth complementation assays, we demonstrate that 0.3% of the gal3∆ cell population responds to galactose. This is corroborated by flow cytometry and microscopic analysis. The galactose responders and nonresponders isolated from the galactose-adapted population attain the original bimodal state and this phenotype is found to be as hard wired as a genetic trait. Computational analysis suggests that the log-normal distribution in GAL4 synthesis can lead to bimodal expression of GAL80, resulting in the bimodal expression of GAL genes. Heterozygosity at the GAL80 but not at the GAL1, GAL2 or GAL4 locus alters the extent of bimodality of the gal3∆ cell population. We suggest that the asymmetric expression pattern between GAL1 and GAL3 results in the ability of S. cerevisiae to activate the GAL pathway by conferring nongenetic heterogeneity.

A Gondwanan imprint on global diversity and domestication of wine and cider yeast Saccharomyces uvarum

In addition to Saccharomyces cerevisiae, the cryotolerant yeast species S. uvarum is also used for wine and cider fermentation but nothing is known about its natural history. Here we use a population genomics approach to investigate its global phylogeography and domestication fingerprints using a collection of isolates obtained from fermented beverages and from natural environments on five continents. South American isolates contain more genetic diversity than that found in the Northern Hemisphere. Moreover, coalescence analyses suggest that a Patagonian sub-population gave rise to the Holarctic population through a recent bottleneck. Holarctic strains display multiple introgressions from other Saccharomyces species, those from S. eubayanus being prevalent in European strains associated with human-driven fermentations. These introgressions are absent in the large majority of wild strains and gene ontology analyses indicate that several gene categories relevant for wine fermentation are overrepresented. Such findings constitute a first indication of domestication in S. uvarum.

Computational models reveal genotype-phenotype associations in Saccharomyces cerevisiae

Genome sequencing is essential to understand individual variation and to study the mechanisms that explain relations between genotype and phenotype. The accumulated knowledge from large-scale genome sequencing projects of Saccharomyces cerevisiae isolates is being used to study the mechanisms that explain such relations. Our objective was to undertake genetic characterization of 172 S. cerevisiae strains from different geographical origins and technological groups, using 11 polymorphic microsatellites, and computationally relate these data with the results of 30 phenotypic tests. Genetic characterization revealed 280 alleles, with the microsatellite ScAAT1 contributing most to intrastrain variability, together with alleles 20, 9 and 16 from the microsatellites ScAAT4, ScAAT5 and ScAAT6. These microsatellite allelic profiles are characteristic for both the phenotype and origin of yeast strains. We confirm the strength of these associations by construction and cross-validation of computational models that can predict the technological application and origin of a strain from the microsatellite allelic profile. Associations between microsatellites and specific phenotypes were scored using information gain ratios, and significant findings were confirmed by permutation tests and estimation of false discovery rates. The phenotypes associated with higher number of alleles were the capacity to resist to sulphur dioxide (tested by the capacity to grow in the presence of potassium bisulphite) and the presence of galactosidase activity. Our study demonstrates the utility of computational modelling to estimate a strain technological group and phenotype from microsatellite allelic combinations as tools for preliminary yeast strain selection.

Genome-wide mapping of cellular traits using yeast

Yeast has long enjoyed superiority as a genetic model because of its short generation time and ease of generating alleles for genetic analysis. However, recent developments of guided nucleases for genome editing in higher eukaryotes, and funding pressures for translational findings, force all model organism communities to reaffirm and rearticulate the advantages of their chosen creature. Here I examine the utility of budding yeast for understanding the genetic basis of cellular traits, using natural variation as well as classical genetic perturbations, and its future prospects compared to undertaking the work in human cell lines. Will yeast remain central, or will it join the likes of phage as an early model that is no longer widely used to answer the pressing questions?

Heritability and genetic basis of protein level variation in an outbred population

The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the population’s average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance.

A high-definition view of functional genetic variation from natural yeast genomes

The question of how genetic variation in a population influences phenotypic variation and evolution is of major importance in modern biology. Yet much is still unknown about the relative functional importance of different forms of genome variation and how they are shaped by evolutionary processes. Here we address these questions by population level sequencing of 42 strains from the budding yeast Saccharomyces cerevisiae and its closest relative S. paradoxus. We find that genome content variation, in the form of presence or absence as well as copy number of genetic material, is higher within S. cerevisiae than within S. paradoxus, despite genetic distances as measured in single-nucleotide polymorphisms being vastly smaller within the former species. This genome content variation, as well as loss-of-function variation in the form of premature stop codons and frameshifting indels, is heavily enriched in the subtelomeres, strongly reinforcing the relevance of these regions to functional evolution. Genes affected by these likely functional forms of variation are enriched for functions mediating interaction with the external environment (sugar transport and metabolism, flocculation, metal transport, and metabolism). Our results and analyses provide a comprehensive view of genomic diversity in budding yeast and expose surprising and pronounced differences between the variation within S. cerevisiae and that within S. paradoxus. We also believe that the sequence data and de novo assemblies will constitute a useful resource for further evolutionary and population genomics studies.

Phenotypic characterisation of Saccharomyces spp. yeast for tolerance to stresses encountered during fermentation of lignocellulosic residues to produce bioethanol

Background

During industrial fermentation of lignocellulose residues to produce bioethanol, microorganisms are exposed to a number of factors that influence productivity. These include inhibitory compounds produced by the pre-treatment processes required to release constituent carbohydrates from biomass feed-stocks and during fermentation, exposure of the organisms to stressful conditions. In addition, for lignocellulosic bioethanol production, conversion of both pentose and hexose sugars is a pre-requisite for fermentative organisms for efficient and complete conversion. All these factors are important to maximise industrial efficiency, productivity and profit margins in order to make second-generation bioethanol an economically viable alternative to fossil fuels for future transport needs.

Results

The aim of the current study was to assess Saccharomyces yeasts for their capacity to tolerate osmotic, temperature and ethanol stresses and inhibitors that might typically be released during steam explosion of wheat straw. Phenotypic microarray analysis was used to measure tolerance as a function of growth and metabolic activity. Saccharomyces strains analysed in this study displayed natural variation to each stress condition common in bioethanol fermentations. In addition, many strains displayed tolerance to more than one stress, such as inhibitor tolerance combined with fermentation stresses.

Conclusions

Our results suggest that this study could identify a potential candidate strain or strains for efficient second generation bioethanol production. Knowledge of the Saccharomyces spp. strains grown in these conditions will aid the development of breeding programmes in order to generate more efficient strains for industrial fermentations.

Heterosis is prevalent among domesticated but not wild strains of Saccharomyces cerevisiae

Crosses between inbred but unrelated individuals often result in an increased fitness of the progeny. This phenomenon is known as heterosis and has been reported for wild and domesticated populations of plants and animals. Analysis of heterosis is often hindered by the fact that the genetic relatedness between analyzed organisms is only approximately known. We studied a collection of Saccharomyces cerevisiae isolates from wild and human-created habitats whose genomes were sequenced and thus their relatedness was fully known. We reasoned that if these strains accumulated different deleterious mutations at an approximately constant rate, then heterosis should be most visible in F1 heterozygotes from the least related parents. We found that heterosis was substantial and positively correlated with sequence divergence, but only in domesticated strains. More than 80% of the heterozygous hybrids were more fit than expected from the mean of their homozygous parents, and approximately three-quarters of those exceeded even the fittest parent. Our results support the notion that domestication brings about relaxation of selection and accumulation of deleterious mutations. However, other factors may have contributed as well. In particular, the observed build-up of genetic load might be facilitated by a decrease, and not increase, in the rate of inbreeding.

Yeast growth plasticity is regulated by environment-specific multi-QTL interactions

For a unicellular, non-motile organism like Saccharomyces cerevisiae, carbon sources act both as nutrients and as signaling molecules and consequently affect various fitness parameters including growth. It is therefore advantageous for yeast strains to adapt their growth to carbon source variation. The ability of a given genotype to manifest different phenotypes in varying environments is known as phenotypic plasticity. To identify quantitative trait loci (QTL) that drive plasticity in growth, two growth parameters (growth rate and biomass) were measured in a published dataset from meiotic recombinants of two genetically divergent yeast strains grown in different carbon sources. To identify QTL contributing to plasticity across pairs of environments, gene–environment interaction mapping was performed, which identified several QTL that have a differential effect across environments, some of which act antagonistically across pairs of environments. Multi-QTL analysis identified loci interacting with previously known growth affecting QTL as well as novel two-QTL interactions that affect growth. A QTL that had no significant independent effect was found to alter growth rate and biomass for several carbon sources through two-QTL interactions. Our study demonstrates that environment-specific epistatic interactions contribute to the growth plasticity in yeast. We propose that a targeted scan for epistatic interactions, such as the one described here, can help unravel mechanisms regulating phenotypic plasticity.

Mapping genetic variants underlying differences in the central nitrogen metabolism in fermenter yeasts

Different populations within a species represent a rich reservoir of allelic variants, corresponding to an evolutionary signature of withstood environmental constraints. Saccharomyces cerevisiae strains are widely utilised in the fermentation of different kinds of alcoholic beverages, such as, wine and sake, each of them derived from must with distinct nutrient composition. Importantly, adequate nitrogen levels in the medium are essential for the fermentation process, however, a comprehensive understanding of the genetic variants determining variation in nitrogen consumption is lacking. Here, we assessed the genetic factors underlying variation in nitrogen consumption in a segregating population derived from a cross between two main fermenter yeasts, a Wine/European and a Sake isolate. By linkage analysis we identified 18 main effect QTLs for ammonium and amino acids sources. Interestingly, majority of QTLs were involved in more than a single trait, grouped based on amino acid structure and indicating high levels of pleiotropy across nitrogen sources, in agreement with the observed patterns of phenotypic co-variation. Accordingly, we performed reciprocal hemizygosity analysis validating an effect for three genes, GLT1, ASI1 and AGP1. Furthermore, we detected a widespread pleiotropic effect on these genes, with AGP1 affecting seven amino acids and nine in the case of GLT1 and ASI1. Based on sequence and comparative analysis, candidate causative mutations within these genes were also predicted. Altogether, the identification of these variants demonstrate how Sake and Wine/European genetic backgrounds differentially consume nitrogen sources, in part explaining independently evolved preferences for nitrogen assimilation and representing a niche of genetic diversity for the implementation of practical approaches towards more efficient strains for nitrogen metabolism.

Genetics of single-cell protein abundance variation in large yeast populations

Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or multiple genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL) ¹. Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power ^2–6. Consequently, many eQTL are likely missed, especially those with smaller effects ⁷. Further, most studies use mRNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics ^8–13 reported surprising differences between eQTL and protein QTL (pQTL) for the same genes ^9,10, but these studies have been even more limited in scope. Here, we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyes cerevisiae. We measure single-cell protein abundance through the use of green-fluorescent-protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high vs. low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci cluster at hotspot locations that influence multiple proteins—in some cases, more than half of those examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.

The fitness advantage of commercial wine yeasts in relation to the nitrogen concentration, temperature, and ethanol content under microvinification conditions

The effect of the main environmental factors governing wine fermentation on the fitness of industrial yeast strains has barely received attention. In this study, we used the concept of fitness advantage to measure how increasing nitrogen concentrations (0 to 200 mg N/liter), ethanol (0 to 20%), and temperature (4 to 45°C) affects competition among four commercial wine yeast strains (PDM, ARM, RVA, and TTA). We used a mathematical approach to model the hypothetical time needed for the control strain (PDM) to out-compete the other three strains in a theoretical mixed population. The theoretical values obtained were subsequently verified by competitive mixed fermentations in both synthetic and natural musts, which showed a good fit between the theoretical and experimental data. Specifically, the data show that the increase in nitrogen concentration and temperature values improved the fitness advantage of the PDM strain, whereas the presence of ethanol significantly reduced its competitiveness. However, the RVA strain proved to be the most competitive yeast for the three enological parameters assayed. The study of the fitness of these industrial strains is of paramount interest for the wine industry, which uses them as starters of their fermentations. Here, we propose a very simple method to model the fitness advantage, which allows the prediction of the competitiveness of one strain with respect to different abiotic factors.

An evaluation of high-throughput approaches to QTL mapping in Saccharomyces cerevisiae

Dissecting the molecular basis of quantitative traits is a significant challenge and is essential for understanding complex diseases. Even in model organisms, precisely determining causative genes and their interactions has remained elusive, due in part to difficulty in narrowing intervals to single genes and in detecting epistasis or linked quantitative trait loci. These difficulties are exacerbated by limitations in experimental design, such as low numbers of analyzed individuals or of polymorphisms between parental genomes. We address these challenges by applying three independent high-throughput approaches for QTL mapping to map the genetic variants underlying 11 phenotypes in two genetically distant Saccharomyces cerevisiae strains, namely (1) individual analysis of >700 meiotic segregants, (2) bulk segregant analysis, and (3) reciprocal hemizygosity scanning, a new genome-wide method that we developed. We reveal differences in the performance of each approach and, by combining them, identify eight polymorphic genes that affect eight different phenotypes: colony shape, flocculation, growth on two nonfermentable carbon sources, and resistance to two drugs, salt, and high temperature. Our results demonstrate the power of individual segregant analysis to dissect QTL and address the underestimated contribution of interactions between variants. We also reveal confounding factors like mutations and aneuploidy in pooled approaches, providing valuable lessons for future designs of complex trait mapping studies.

Trx2p-dependent regulation of Saccharomyces cerevisiae oxidative stress response by the Skn7p transcription factor under respiring conditions

The whole genome analysis has demonstrated that wine yeasts undergo changes in promoter regions and variations in gene copy number, which make them different to lab strains and help them better adapt to stressful conditions during winemaking, where oxidative stress plays a critical role. Since cytoplasmic thioredoxin II, a small protein with thiol-disulphide oxidoreductase activity, has been seen to perform important functions under biomass propagation conditions of wine yeasts, we studied the involvement of Trx2p in the molecular regulation of the oxidative stress transcriptional response on these strains. In this study, we analyzed the expression levels of several oxidative stress-related genes regulated by either Yap1p or the co-operation between Yap1p and Skn7p. The results revealed a lowered expression for all the tested Skn7p dependent genes in a Trx2p-deficient strain and that Trx2p is essential for the oxidative stress response during respiratory metabolism in wine yeast. Additionally, activity of Yap1p and Skn7p dependent promoters by β-galactosidase assays clearly demonstrated that Skn7p-dependent promoter activation is affected by TRX2 gene deficiency. Finally we showed that deleting the TRX2 gene causes Skn7p hyperphosphorylation under oxidative stress conditions. We propose Trx2p to be a new positive efector in the regulation of the Skn7p transcription factor that controls phosphorylation events and, therefore, modulates the oxidative stress response in yeast.

Divergence of iron metabolism in wild Malaysian yeast

Comparative genomic studies have reported widespread variation in levels of gene expression within and between species. Using these data to infer organism-level trait divergence has proven to be a key challenge in the field. We have used a wild Malaysian population of S. cerevisiae as a test bed in the search to predict and validate trait differences based on observations of regulatory variation. Malaysian yeast, when cultured in standard medium, activated regulatory programs that protect cells from the toxic effects of high iron. Malaysian yeast also showed a hyperactive regulatory response during culture in the presence of excess iron and had a unique growth defect in conditions of high iron. Molecular validation experiments pinpointed the iron metabolism factors AFT1, CCC1, and YAP5 as contributors to these molecular and cellular phenotypes; in genome-scale sequence analyses, a suite of iron toxicity response genes showed evidence for rapid protein evolution in Malaysian yeast. Our findings support a model in which iron metabolism has diverged in Malaysian yeast as a consequence of a change in selective pressure, with Malaysian alleles shifting the dynamic range of iron response to low-iron concentrations and weakening resistance to extreme iron toxicity. By dissecting the iron scarcity specialist behavior of Malaysian yeast, our work highlights the power of expression divergence as a signpost for biologically and evolutionarily relevant variation at the organismal level. Interpreting the phenotypic relevance of gene expression variation is one of the primary challenges of modern genomics.

Genomic sequence diversity and population structure of Saccharomyces cerevisiae assessed by RAD-seq

The budding yeast Saccharomyces cerevisiae is important for human food production and as a model organism for biological research. The genetic diversity contained in the global population of yeast strains represents a valuable resource for a number of fields, including genetics, bioengineering, and studies of evolution and population structure. Here, we apply a multiplexed, reduced genome sequencing strategy (restriction site-associated sequencing or RAD-seq) to genotype a large collection of S. cerevisiae strains isolated from a wide range of geographical locations and environmental niches. The method permits the sequencing of the same 1% of all genomes, producing a multiple sequence alignment of 116,880 bases across 262 strains. We find diversity among these strains is principally organized by geography, with European, North American, Asian, and African/S. E. Asian populations defining the major axes of genetic variation. At a finer scale, small groups of strains from cacao, olives, and sake are defined by unique variants not present in other strains. One population, containing strains from a variety of fermentations, exhibits high levels of heterozygosity and a mixture of alleles from European and Asian populations, indicating an admixed origin for this group. We propose a model of geographic differentiation followed by human-associated admixture, primarily between European and Asian populations and more recently between European and North American populations. The large collection of genotyped yeast strains characterized here will provide a useful resource for the broad community of yeast researchers.