Advances in quantitative trait analysis in yeast

Saccharomyces cerevisiae strains for second-generation ethanol production: from academic exploration to industrial implementation

The recent start-up of several full-scale 'second generation' ethanol plants marks a major milestone in the development of Saccharomyces cerevisiae strains for fermentation of lignocellulosic hydrolysates of agricultural residues and energy crops. After a discussion of the challenges that these novel industrial contexts impose on yeast strains, this minireview describes key metabolic engineering strategies that have been developed to address these challenges. Additionally, it outlines how proof-of-concept studies, often developed in academic settings, can be used for the development of robust strain platforms that meet the requirements for industrial application. Fermentation performance of current engineered industrial S. cerevisiae strains is no longer a bottleneck in efforts to achieve the projected outputs of the first large-scale second-generation ethanol plants. Academic and industrial yeast research will continue to strengthen the economic value position of second-generation ethanol production by further improving fermentation kinetics, product yield and cellular robustness under process conditions.

Budding Yeast Strains and Genotype-Phenotype Mapping

A small number of well-studied laboratory strains of Saccharomyces cerevisiae, mostly derived from S288C, are used in yeast research. Although powerful, studies for understanding S288C do not always capture the phenotypic essence or the genetic complexity of S. cerevisiae biology. This is particularly problematic for multilocus phenotypes identified in laboratory strains because these loci have never been jointly exposed to natural selection and the corresponding phenotypes do not represent optimization for any particular purpose or environment. Isolation and sequencing of new natural yeast strains also reveal that the total sequence diversity of the S. cerevisiae global population is poorly sampled in common laboratory strains. Here we discuss methodologies required for using the natural genetic variation in yeast to complete a genotype-phenotype map.

Natural variation in a single amino acid substitution underlies physiological responses to topoisomerase II poisons

Many chemotherapeutic drugs are differentially effective from one patient to the next. Understanding the causes of this variability is a critical step towards the development of personalized treatments and improvements to existing medications. Here, we investigate sensitivity to a group of anti-neoplastic drugs that target topoisomerase II using the model organism Caenorhabditis elegans. We show that wild strains of C. elegans vary in their sensitivity to these drugs, and we use an unbiased genetic approach to demonstrate that this natural variation is explained by a methionine-to-glutamine substitution in topoisomerase II (TOP-2). The presence of a non-polar methionine at this residue increases hydrophobic interactions between TOP-2 and its poison etoposide, as compared to a polar glutamine. We hypothesize that this stabilizing interaction results in increased genomic instability in strains that contain a methionine residue. The residue affected by this substitution is conserved from yeast to humans and is one of the few differences between the two human topoisomerase II isoforms (methionine in hTOPIIα and glutamine in hTOPIIβ). We go on to show that this amino acid difference between the two human topoisomerase isoforms influences cytotoxicity of topoisomerase II poisons in human cell lines. These results explain why hTOPIIα and hTOPIIβ are differentially affected by various poisons and demonstrate the utility of C. elegans in understanding the genetics of drug responses.

The severe cytotoxic effects associated with anti-neoplastic treatment regimens make it difficult to assess the contributions of genetic variation on treatment responses in clinical settings. Therefore, we leveraged genetic diversity present in the metazoan model nematode Caenorhabditis elegans to identify genetic variants that contribute to differential susceptibility to a broadly administered class of anti-neoplastic compounds that poison the activity of topoisomerase II enzymes. We show that wild C. elegans isolates contain either glutamine or methionine at a highly conserved residue of the topoisomerase II (TOP-2) protein and that this substitution is predictive of animal responses to the topoisomerase II poisons etoposide, teniposide, dactinomycin, and XK469. Interestingly, the two human versions of this protein, hTOPIIα and hTOPIIβ, contain a methionine or glutamine at the corresponding residue, respectively. We show that this difference between the two human topoisomerase II isoforms contributes to the differential cytotoxicity induced by these drugs. Taken together, our results highlight the power of studying the effects of natural genetic variation on drug responses in a model organism and propose methods to develop new drugs that have increased affinity for the desired hTOPIIα isoform expressed in tumor cells.

Identification of Nitrogen Consumption Genetic Variants in Yeast Through QTL Mapping and Bulk Segregant RNA-Seq Analyses

Saccharomyces cerevisiae is responsible for wine must fermentation. In this process, nitrogen represents a limiting nutrient and its scarcity results in important economic losses for the wine industry. Yeast isolates use different strategies to grow in poor nitrogen environments and their genomic plasticity enables adaptation to multiple habitats through improvements in nitrogen consumption. Here, we used a highly recombinant S. cerevisiae multi-parent population (SGRP-4X) derived from the intercross of four parental strains of different origins to identify new genetic variants responsible for nitrogen consumption differences during wine fermentation. Analysis of 165 fully sequenced F12 segregants allowed us to map 26 QTL in narrow intervals for 14 amino acid sources and ammonium, the majority of which represent genomic regions previously unmapped for these traits. To complement this strategy, we performed Bulk segregant RNA-seq (BSR-seq) analysis in segregants exhibiting extremely high and low ammonium consumption levels. This identified several QTL overlapping differentially expressed genes and refined the gene candidate search. Based on these approaches, we were able to validate ARO1, PDC1, CPS1, ASI2, LYP1, and ALP1 allelic variants underlying nitrogen consumption differences between strains, providing evidence of many genes with small phenotypic effects. Altogether, these variants significantly shape yeast nitrogen consumption with important implications for evolution, ecological, and quantitative genomics.

Genome Diversity and Evolution in the Budding Yeasts (Saccharomycotina)

Considerable progress in our understanding of yeast genomes and their evolution has been made over the last decade with the sequencing, analysis, and comparisons of numerous species, strains, or isolates of diverse origins. The role played by yeasts in natural environments as well as in artificial manufactures, combined with the importance of some species as model experimental systems sustained this effort. At the same time, their enormous evolutionary diversity (there are yeast species in every subphylum of Dikarya) sparked curiosity but necessitated further efforts to obtain appropriate reference genomes. Today, yeast genomes have been very informative about basic mechanisms of evolution, speciation, hybridization, domestication, as well as about the molecular machineries underlying them. They are also irreplaceable to investigate in detail the complex relationship between genotypes and phenotypes with both theoretical and practical implications. This review examines these questions at two distinct levels offered by the broad evolutionary range of yeasts: inside the best-studied Saccharomyces species complex, and across the entire and diversified subphylum of Saccharomycotina. While obviously revealing evolutionary histories at different scales, data converge to a remarkably coherent picture in which one can estimate the relative importance of intrinsic genome dynamics, including gene birth and loss, vs. horizontal genetic accidents in the making of populations. The facility with which novel yeast genomes can now be studied, combined with the already numerous available reference genomes, offer privileged perspectives to further examine these fundamental biological questions using yeasts both as eukaryotic models and as fungi of practical importance.

Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth

In all organisms, the majority of traits vary continuously between individuals. Explaining the genetic basis of quantitative trait variation requires comprehensively accounting for genetic and nongenetic factors as well as their interactions. The growth of microbial cells can be characterized by a lag duration, an exponential growth phase, and a stationary phase. Parameters that characterize these growth phases can vary among genotypes (phenotypic variation), environmental conditions (phenotypic plasticity), and among isogenic cells in a given environment (phenotypic variability). We used a high-throughput microscopy assay to map genetic loci determining variation in lag duration and exponential growth rate in growth rate-limiting and nonlimiting glucose concentrations, using segregants from a cross of two natural isolates of the budding yeast, Saccharomyces cerevisiae We find that some quantitative trait loci (QTL) are common between traits and environments whereas some are unique, exhibiting gene-by-environment interactions. Furthermore, whereas variation in the central tendency of growth rate or lag duration is explained by many additive loci, differences in phenotypic variability are primarily the result of genetic interactions. We used bulk segregant mapping to increase QTL resolution by performing whole-genome sequencing of complex mixtures of an advanced intercross mapping population grown in selective conditions using glucose-limited chemostats. We find that sequence variation in the high-affinity glucose transporter HXT7 contributes to variation in growth rate and lag duration. Allele replacements of the entire locus, as well as of a single polymorphic amino acid, reveal that the effect of variation in HXT7 depends on genetic, and allelic, background. Amplifications of HXT7 are frequently selected in experimental evolution in glucose-limited environments, but we find that HXT7 amplifications result in antagonistic pleiotropy that is absent in naturally occurring variants of HXT7 Our study highlights the complex nature of the genotype-to-phenotype map within and between environments.

Polymorphisms in the yeast galactose sensor underlie a natural continuum of nutrient-decision phenotypes

In nature, microbes often need to "decide" which of several available nutrients to utilize, a choice that depends on a cell's inherent preference and external nutrient levels. While natural environments can have mixtures of different nutrients, phenotypic variation in microbes' decisions of which nutrient to utilize is poorly studied. Here, we quantified differences in the concentration of glucose and galactose required to induce galactose-responsive (GAL) genes across 36 wild S. cerevisiae strains. Using bulk segregant analysis, we found that a locus containing the galactose sensor GAL3 was associated with differences in GAL signaling in eight different crosses. Using allele replacements, we confirmed that GAL3 is the major driver of GAL induction variation, and that GAL3 allelic variation alone can explain as much as 90% of the variation in GAL induction in a cross. The GAL3 variants we found modulate the diauxic lag, a selectable trait. These results suggest that ecological constraints on the galactose pathway may have led to variation in a single protein, allowing cells to quantitatively tune their response to nutrient changes in the environment.

The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae

Background

Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci.

Results

In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions’ adaptive nature.

Conclusions

The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3572-2) contains supplementary material, which is available to authorized users.

Genetic Causes of Phenotypic Adaptation to the Second Fermentation of Sparkling Wines in Saccharomyces cerevisiae

Hybridization is known to improve complex traits due to heterosis and phenotypic robustness. However, these phenomena have been rarely explained at the molecular level. Here, the genetic determinism of Saccharomyces cerevisiae fermentation performance was investigated using a QTL mapping approach on an F1-progeny population. Three main QTL were detected, with positive alleles coming from both parental strains. The heterosis effect found in the hybrid was partially explained by three loci showing pseudooverdominance and dominance effects. The molecular dissection of those QTL revealed that the adaptation to second fermentation is related to pH, lipid, or osmotic regulation. Our results suggest that the stressful conditions of second fermentation have driven the selection of rare genetic variants adapted to maintain yeast cell homeostasis and, in particular, to low pH conditions.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Experimental evolution in fungi: An untapped resource

Historically, evolutionary biology has been considered an observational science. Examining populations and inferring evolutionary histories mold evolutionary theories. In contrast, laboratory evolution experiments make use of the amenability of traditional model organisms to study fundamental processes underlying evolution in real time in simple, but well-controlled, environments. With advances in high-throughput biology and next generation sequencing, it is now possible to propagate hundreds of parallel populations over thousands of generations and to quantify precisely the frequencies of various mutations over time. Experimental evolution combines the ability to simultaneously monitor replicate populations with the power to vary individual parameters to test specific evolutionary hypotheses, something that is impractical or infeasible in natural populations. Many labs are now conducting laboratory evolution experiments in nearly all model systems including viruses, bacteria, yeast, nematodes, and fruit flies. Among these systems, fungi occupy a unique niche: with a short generation time, small compact genomes, and sexual cycles, fungi are a particularly valuable and largely untapped resource for propelling future growth in the field of experimental evolution. Here, we describe the current state of fungal experimental evolution and why fungi are uniquely positioned to answer many of the outstanding questions in the field. We also review which fungal species are most well suited for experimental evolution.

EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis

Identification of genomic regions associated with a phenotype of interest is a fundamental step toward solving questions in biology and improving industrial research. Bulk segregant analysis (BSA) combined with high-throughput sequencing is a technique to efficiently identify these genomic regions associated with a trait of interest. However, distinguishing true from spuriously linked genomic regions and accurately delineating the genomic positions of these truly linked regions requires the use of complex statistical models currently implemented in software tools that are generally difficult to operate for non-expert users. To facilitate the exploration and analysis of data generated by bulked segregant analysis, we present EXPLoRA-web, a web service wrapped around our previously published algorithm EXPLoRA, which exploits linkage disequilibrium to increase the power and accuracy of quantitative trait loci identification in BSA analysis. EXPLoRA-web provides a user friendly interface that enables easy data upload and parallel processing of different parameter configurations. Results are provided graphically and as BED file and/or text file and the input is expected in widely used formats, enabling straightforward BSA data analysis. The web server is available at http://bioinformatics.intec.ugent.be/explora-web/.

Exploiting budding yeast natural variation for industrial processes

For the last two decades, the natural variation of the yeast Saccharomyces cerevisiae has been massively exploited with the aim of understanding ecological and evolutionary processes. As a result, many new genetic variants have been uncovered, providing a large catalogue of alleles underlying complex traits. These alleles represent a rich genetic resource with the potential to provide new strains that can cope with the growing demands of industrial fermentation processes. When surveyed in detail, several of these variants have proven useful in wine and beer industries by improving nitrogen utilisation, fermentation kinetics, ethanol production, sulphite resistance and aroma production. Here, I illustrate how allele-specific expression and polymorphisms within the coding region of GDB1 underlie fermentation kinetic differences in synthetic wine must. Nevertheless, the genetic basis of how GDB1 variants and other natural alleles interact in foreign genetic backgrounds remains unclear. Further studies in large sets of strains, recombinant hybrids and multiple parental pairs will broaden our knowledge of the molecular and genetic basis of trait adaptation for utilisation in applied and industrial processes.

An interaction quantitative trait loci tool implicates epistatic functional variants in an apoptosis pathway in smallpox vaccine eQTL data

Expression quantitative trait loci (eQTL) studies have functionalized nucleic acid variants through the regulation of gene expression. Although most eQTL studies only examine the effects of single variants on transcription, a more complex process of variant-variant interaction (epistasis) may regulate transcription. Herein, we describe a tool called interaction QTL (iQTL) designed to efficiently detect epistatic interactions that regulate gene expression. To maximize biological relevance and minimize the computational and hypothesis testing burden, iQTL restricts interactions such that one variant is within a user-defined proximity of the transcript (cis-regulatory). We apply iQTL to a data set of 183 smallpox vaccine study participants with genome-wide association study and gene expression data from unstimulated samples and samples stimulated by inactivated vaccinia virus. While computing only 0.15% of possible interactions, we identify 11 probe sets whose expression is regulated through a variant-variant interaction. We highlight the functional epistatic interactions among apoptosis-related genes, DIABLO, TRAPPC4 and FADD, in the context of smallpox vaccination. We also use an integrative network approach to characterize these iQTL interactions in a posterior network of known prior functional interactions. iQTL is an efficient, open-source tool to analyze variant interactions in eQTL studies, providing better understanding of the function of epistasis in immune response and other complex phenotypes.

Genomic saturation mutagenesis and polygenic analysis identify novel yeast genes affecting ethyl acetate production, a non-selectable polygenic trait

Isolation of mutants in populations of microorganisms has been a valuable tool in experimental genetics for decades. The main disadvantage, however, is the inability of isolating mutants in non-selectable polygenic traits. Most traits of organisms, however, are non-selectable and polygenic, including industrially important properties of microorganisms. The advent of powerful technologies for polygenic analysis of complex traits has allowed simultaneous identification of multiple causative mutations among many thousands of irrelevant mutations. We now show that this also applies to haploid strains of which the genome has been loaded with induced mutations so as to affect as many non-selectable, polygenic traits as possible. We have introduced about 900 mutations into single haploid yeast strains using multiple rounds of EMS mutagenesis, while maintaining the mating capacity required for genetic mapping. We screened the strains for defects in flavor production, an important non-selectable, polygenic trait in yeast alcoholic beverage production. A haploid strain with multiple induced mutations showing reduced ethyl acetate production in semi-anaerobic fermentation, was selected and the underlying quantitative trait loci (QTLs) were mapped using pooled-segregant whole-genome sequence analysis after crossing with an unrelated haploid strain. Reciprocal hemizygosity analysis and allele exchange identified PMA1 and CEM1 as causative mutant alleles and TPS1 as a causative genetic background allele. The case of CEM1 revealed that relevant mutations without observable effect in the haploid strain with multiple induced mutations (in this case due to defective mitochondria) can be identified by polygenic analysis as long as the mutations have an effect in part of the segregants (in this case those that regained fully functional mitochondria). Our results show that genomic saturation mutagenesis combined with complex trait polygenic analysis could be used successfully to identify causative alleles underlying many non-selectable, polygenic traits in small collections of haploid strains with multiple induced mutations.

RIM15 antagonistic pleiotropy is responsible for differences in fermentation and stress response kinetics in budding yeast

Different natural yeast populations have faced dissimilar selective pressures due to the heterogeneous fermentation substrates available around the world; this increases the genetic and phenotypic diversity in Saccharomyces cerevisiae In this context, we expect prominent differences between isolates when exposed to a particular condition, such as wine or sake musts. To better comprehend the mechanisms underlying niche adaptation between two S. cerevisiae isolates obtained from wine and sake fermentation processes, we evaluated fermentative and fungicide resistance phenotypes and identify the molecular origin of such adaptive variation. Multiple regions were associated with fermentation rate under different nitrogen conditions and fungicide resistance, with a single QTL co-localizing in all traits. Analysis around this region identified RIM15 as the causative locus driving fungicide sensitivity, together with efficient nitrogen utilization and glycerol production in the wine strain. A null RIM15 variant confers a greater fermentation rate through the utilization of available glucose instead of its storage. However, this variant has a detrimental effect on fungicide resistance since complex sugars are not synthesized and transported into the membrane. Together, our results reveal the antagonist pleiotropic nature of a RIM15 null variant, positively affecting a series of fermentation related phenotypes, but apparently detrimental in the wild.

An Energy-Independent Pro-longevity Function of Triacylglycerol in Yeast

Intracellular triacylglycerol (TAG) is a ubiquitous energy storage lipid also involved in lipid homeostasis and signaling. Comparatively, little is known about TAG’s role in other cellular functions. Here we show a pro-longevity function of TAG in the budding yeast Saccharomyces cerevisiae. In yeast strains derived from natural and laboratory environments a correlation between high levels of TAG and longer chronological lifespan was observed. Increased TAG abundance through the deletion of TAG lipases prolonged chronological lifespan of laboratory strains, while diminishing TAG biosynthesis shortened lifespan without apparently affecting vegetative growth. TAG-mediated lifespan extension was independent of several other known stress response factors involved in chronological aging. Because both lifespan regulation and TAG metabolism are conserved, this cellular pro-longevity function of TAG may extend to other organisms.

Triacylglycerol (TAG) is a ubiquitous lipid species well-known for its roles in storing surplus energy, providing insulation, and maintaining cellular lipid homeostasis. Here we present evidence for a novel pro-longevity function of TAG in the budding yeast, a model organism for aging research. Yeast cells that are genetically engineered to store more TAG live significantly longer without suffering obvious growth defects, whereas those lean cells that are depleted of TAG die early. Yeast strains isolated from the wild in general contain more fat and also display longer lifespan. One of the approaches taken here to force the increase of intracellular TAG is to delete lipases responsible for lipid hydrolysis. Energy extraction from TAG thus is unlikely an underlying cause of the observed lifespan extension. Our results are reminiscent of certain animal studies linking higher body fat to longer lifespan. Potential mechanisms for the connection of TAG and yeast lifespan regulation are discussed.

Extensive Recombination of a Yeast Diploid Hybrid through Meiotic Reversion

In somatic cells, recombination between the homologous chromosomes followed by equational segregation leads to loss of heterozygosity events (LOH), allowing the expression of recessive alleles and the production of novel allele combinations that are potentially beneficial upon Darwinian selection. However, inter-homolog recombination in somatic cells is rare, thus reducing potential genetic variation. Here, we explored the property of S. cerevisiae to enter the meiotic developmental program, induce meiotic Spo11-dependent double-strand breaks genome-wide and return to mitotic growth, a process known as Return To Growth (RTG). Whole genome sequencing of 36 RTG strains derived from the hybrid S288c/SK1 diploid strain demonstrates that the RTGs are bona fide diploids with mosaic recombined genome, derived from either parental origin. Individual RTG genome-wide genotypes are comprised of 5 to 87 homozygous regions due to the loss of heterozygous (LOH) events of various lengths, varying between a few nucleotides up to several hundred kilobases. Furthermore, we show that reiteration of the RTG process shows incremental increases of homozygosity. Phenotype/genotype analysis of the RTG strains for the auxotrophic and arsenate resistance traits validates the potential of this procedure of genome diversification to rapidly map complex traits loci (QTLs) in diploid strains without undergoing sexual reproduction.

On the Mapping of Epistatic Genetic Interactions in Natural Isolates: Combining Classical Genetics and Genomics

Genetic variation within species is the substrate of evolution. Epistasis, which designates the non-additive interaction between loci affecting a specific phenotype, could be one of the possible outcomes of genetic diversity. Dissecting the basis of such interactions is of current interest in different fields of biology, from exploring the gene regulatory network, to complex disease genetics, to the onset of reproductive isolation and speciation. We present here a general workflow to identify epistatic interactions between independently evolving loci in natural populations of the yeast Saccharomyces cerevisiae. The idea is to exploit the genetic diversity present in the species by evaluating a large number of crosses and analyzing the phenotypic distribution in the offspring. For a cross of interest, both parental strains would have a similar phenotypic value, whereas the resulting offspring would have a bimodal distribution of the phenotype, possibly indicating the presence of epistasis. Classical segregation analysis of the tetrads uncovers the penetrance and complexity of the interaction. In addition, this segregation could serve as the guidelines for choosing appropriate mapping strategies to narrow down the genomic regions involved. Depending on the segregation patterns observed, we propose different mapping strategies based on bulk segregant analysis or consecutive backcrosses followed by high-throughput genome sequencing. Our method is generally applicable to all systems with a haplodiplobiontic life cycle and allows high resolution mapping of interacting loci that govern various DNA polymorphisms from single nucleotide mutations to large-scale structural variations.

Population perspectives on functional genomic variation in yeast

Advances in high-throughput sequencing have facilitated large-scale surveys of genomic variation in the budding yeast,Saccharomyces cerevisiae These surveys have revealed extensive sequence variation between yeast strains. However, much less is known about how such variation influences the amount and nature of variation for functional genomic traits within and between yeast lineages. We review population-level studies of functional genomic variation, with a particular focus on how population functional genomic approaches can provide insights into both genome function and the evolutionary process. Although variation in functional genomics phenotypes is pervasive, our understanding of the consequences of this variation, either in physiological or evolutionary terms, is still rudimentary and thus motivates increased attention to appropriate null models. To date, much of the focus of population functional genomic studies has been on gene expression variation, but other functional genomic data types are just as likely to reveal important insights at the population level, suggesting a pressing need for more studies that go beyond transcription. Finally, we discuss how a population functional genomic perspective can be a powerful approach for developing a mechanistic understanding of the processes that link genomic variation to organismal phenotypes through gene networks.

Defining Molecular Basis for Longevity Traits in Natural Yeast Isolates

The budding yeast has served as a useful model organism in aging studies, leading to the identification of genetic determinants of longevity, many of which are conserved in higher eukaryotes. However, factors that promote longevity in laboratory setting often have severe fitness disadvantage in the wild. Here, to obtain an unbiased view on longevity regulation we analyzed how replicative lifespan is shaped by transcriptional, translational, metabolic, and morphological factors across 22 wild-type Saccharomyces cerevisiae isolates. We observed significant differences in lifespan across these strains and found that their longevity is strongly associated with up-regulation of oxidative phosphorylation and respiration and down-regulation of amino acid and nitrogen compound biosynthesis. Since calorie restriction and TOR signaling also extend lifespan by adjusting many of the identified pathways, the data suggest that natural plasticity of yeast lifespan is shaped by processes that not only do not impose cost on fitness, but are amenable to dietary intervention.

Analysis of Polygenic Mutants Suggests a Role for Mediator in Regulating Transcriptional Activation Distance in Saccharomyces cerevisiae

Studies of natural populations of many organisms have shown that traits are often complex, caused by contributions of mutations in multiple genes. In contrast, genetic studies in the laboratory primarily focus on studying the phenotypes caused by mutations in a single gene. However, the single mutation approach may be limited with respect to the breadth and degree of new phenotypes that can be found. We have taken the approach of isolating complex, or polygenic mutants in the lab to study the regulation of transcriptional activation distance in yeast. While most aspects of eukaryotic transcription are conserved from yeast to human, transcriptional activation distance is not. In Saccharomyces cerevisiae, the upstream activating sequence (UAS) is generally found within 450 base pairs of the transcription start site (TSS) and when the UAS is moved too far away, activation no longer occurs. In contrast, metazoan enhancers can activate from as far as several hundred kilobases from the TSS. Previously, we identified single mutations that allow transcription activation to occur at a greater-than-normal distance from the GAL1 UAS. As the single mutant phenotypes were weak, we have now isolated polygenic mutants that possess strong long-distance phenotypes. By identification of the causative mutations we have accounted for most of the heritability of the phenotype in each strain and have provided evidence that the Mediator coactivator complex plays both positive and negative roles in the regulation of transcription activation distance.

Auxotrophic Mutations Reduce Tolerance of Saccharomyces cerevisiae to Very High Levels of Ethanol Stress

Very high ethanol tolerance is a distinctive trait of the yeast Saccharomyces cerevisiae with notable ecological and industrial importance. Although many genes have been shown to be required for moderate ethanol tolerance (i.e., 6 to 12%) in laboratory strains, little is known of the much higher ethanol tolerance (i.e., 16 to 20%) in natural and industrial strains. We have analyzed the genetic basis of very high ethanol tolerance in a Brazilian bioethanol production strain by genetic mapping with laboratory strains containing artificially inserted oligonucleotide markers. The first locus contained the ura3Δ0 mutation of the laboratory strain as the causative mutation. Analysis of other auxotrophies also revealed significant linkage for LYS2, LEU2, HIS3, and MET15. Tolerance to only very high ethanol concentrations was reduced by auxotrophies, while the effect was reversed at lower concentrations. Evaluation of other stress conditions showed that the link with auxotrophy is dependent on the type of stress and the type of auxotrophy. When the concentration of the auxotrophic nutrient is close to that limiting growth, more stress factors can inhibit growth of an auxotrophic strain. We show that very high ethanol concentrations inhibit the uptake of leucine more than that of uracil, but the 500-fold-lower uracil uptake activity may explain the strong linkage between uracil auxotrophy and ethanol sensitivity compared to leucine auxotrophy. Since very high concentrations of ethanol inhibit the uptake of auxotrophic nutrients, the active uptake of scarce nutrients may be a major limiting factor for growth under conditions of ethanol stress.

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.

Natural yeast promoter variants reveal epistasis in the generation of transcriptional-mediated noise and its potential benefit in stressful conditions

The increase in phenotypic variability through gene expression noise is proposed to be an evolutionary strategy in selective environments. Differences in promoter-mediated noise between Saccharomyces cerevisiae strains could have been selected for thanks to the benefit conferred by gene expression heterogeneity in the stressful conditions, for instance, those experienced by industrial strains. Here, we used a genome-wide approach to identify promoters conferring high noise levels in the industrial wine strain EC1118. Many promoters of genes related to environmental factors were identified, some of them containing genetic variations compared with their counterpart in the laboratory strain S288c. Each variant of eight promoters has been fused to yeast-Enhanced Green Fluorescent Protein and integrated in the genome of both strains. Some industrial variants conferred higher expression associated, as expected, with lower noise, but other variants either increased or decreased expression without modifying variability, so that they might exhibit different levels of transcriptional-mediated noise at equal mean. At different induction conditions giving similar expression for both variants of the CUP1 promoter, we indeed observed higher noise with the industrial variant. Nevertheless, this difference was only observed in the industrial strain, revealing epistasis in the generation of promoter-mediated noise. Moreover, the increased expression variability conferred by this natural yeast promoter variant provided a clear benefit in the face of an environmental stress. Thus, modulation of gene expression noise by a combination of promoter modifications and trans-influences might be a possible adaptation mechanism in yeast.

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.

Genetic architecture of natural variation of telomere length in Arabidopsis thaliana

Telomeres represent the repetitive sequences that cap chromosome ends and are essential for their protection. Telomere length is known to be highly heritable and is derived from a homeostatic balance between telomeric lengthening and shortening activities. Specific loci that form the genetic framework underlying telomere length homeostasis, however, are not well understood. To investigate the extent of natural variation of telomere length in Arabidopsis thaliana, we examined 229 worldwide accessions by terminal restriction fragment analysis. The results showed a wide range of telomere lengths that are specific to individual accessions. To identify loci that are responsible for this variation, we adopted a quantitative trait loci (QTL) mapping approach with multiple recombinant inbred line (RIL) populations. A doubled haploid RIL population was first produced using centromere-mediated genome elimination between accessions with long (Pro-0) and intermediate (Col-0) telomere lengths. Composite interval mapping analysis of this population along with two established RIL populations (Ler-2/Cvi-0 and Est-1/Col-0) revealed a number of shared and unique QTL. QTL detected in the Ler-2/Cvi-0 population were examined using near isogenic lines that confirmed causative regions on chromosomes 1 and 2. In conclusion, this work describes the extent of natural variation of telomere length in A. thaliana, identifies a network of QTL that influence telomere length homeostasis, examines telomere length dynamics in plants with hybrid backgrounds, and shows the effects of two identified regions on telomere length regulation.

Genetic basis of haloperidol resistance in Saccharomyces cerevisiae is complex and dose dependent

The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain) and RM11_1a (a vineyard strain), to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance.

Variation in response to a drug can be determined by many factors. In the model organism baker's yeast, many studies of chemical resistance traits have uncovered a complex genetic basis of such resistance. However, an in-depth study of how drug dose alters the effects of underlying genetic factors is lacking. Here, we employed linkage analysis to map the specific genetic loci underlying response to haloperidol, a small molecule therapeutic drug, using a large panel of segregants from a cross between two genetically divergent yeast strains BY (a laboratory strain) and RM (a vineyard strain). We found that loci associated with haloperidol resistance are dose-dependent. We also showed that variants in the oxysterol-binding-protein-like domain of the gene SWH1 underlie the major locus detected at all doses of haloperidol. Genetic interactions among genes SWH1, MKT1, and IRA2 in the RM background contribute to the differential response at high concentrations of haloperidol.

Natural genetic variation impacts expression levels of coding, non-coding, and antisense transcripts in fission yeast

Our current understanding of how natural genetic variation affects gene expression beyond well-annotated coding genes is still limited. The use of deep sequencing technologies for the study of expression quantitative trait loci (eQTLs) has the potential to close this gap. Here, we generated the first recombinant strain library for fission yeast and conducted an RNA-seq-based QTL study of the coding, non-coding, and antisense transcriptomes. We show that the frequency of distal effects (trans-eQTLs) greatly exceeds the number of local effects (cis-eQTLs) and that non-coding RNAs are as likely to be affected by eQTLs as protein-coding RNAs. We identified a genetic variation of swc5 that modifies the levels of 871 RNAs, with effects on both sense and antisense transcription, and show that this effect most likely goes through a compromised deposition of the histone variant H2A.Z. The strains, methods, and datasets generated here provide a rich resource for future studies.

Tiled ChrI RHS collection: a pilot high-throughput screening tool for identification of allelic variants

Reciprocal hemizygosity analysis is a genetic technique that allows phenotypic determination of the allelic effects of a gene in a genetically uniform background. Expanding this single gene technique to generate a genome-wide collection is termed as reciprocal hemizygosity scanning (RHS). The RHS collection should circumvent the need for linkage mapping and provide the power to identify all possible allelic variants for a given phenotype. However, the published RHS collections based on the existing genome-wide haploid deletion library reported a high rate of false positives. In this study, we report de novo construction of a RHS collection that is not based on the yeast deletion library. This collection has been constructed for the shortest yeast chromosome, ChrI. Using this ChrI RHS collection, we identified 13 allelic variants for the previously mapped loci and novel allelic variants for the growth differences in different environments. A few of these novel variants, which were fine mapped to a gene level, identified novel genetic variation for the previously studied environmental conditions. The availability of a genome-wide RHS collection would thus help us uncover a comprehensive list of allelic variants and better our understanding of the molecular pathways modulating a quantitative trait.

Identification of loci that cause phenotypic variation in diverse species with the reciprocal hemizygosity test

The reciprocal hemizygosity test is a straightforward genetic test that can positively identify genes that have evolved to contribute to a phenotypic difference between strains or between species. The test involves a comparison between hybrids that are genetically identical throughout the genome except at the test locus, which is rendered hemizygous for alternative alleles from the two parental strains. If the two reciprocal hemizygotes display different phenotypes, then the two parental alleles must have evolved. New methods for targeted mutagenesis will allow application of the reciprocal hemizygosity test in many organisms. This review discusses the principles, advantages, and limitations of the test.

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.

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?

Single nucleotide variants in transcription factors associate more tightly with phenotype than with gene expression

Mapping the polymorphisms responsible for variation in gene expression, known as Expression Quantitative Trait Loci (eQTL), is a common strategy for investigating the molecular basis of disease. Despite numerous eQTL studies, the relationship between the explanatory power of variants on gene expression versus their power to explain ultimate phenotypes remains to be clarified. We addressed this question using four naturally occurring Quantitative Trait Nucleotides (QTN) in three transcription factors that affect sporulation efficiency in wild strains of the yeast, Saccharomyces cerevisiae. We compared the ability of these QTN to explain the variation in both gene expression and sporulation efficiency. We find that the amount of gene expression variation explained by the sporulation QTN is not predictive of the amount of phenotypic variation explained. The QTN are responsible for 98% of the phenotypic variation in our strains but the median gene expression variation explained is only 49%. The alleles that are responsible for most of the variation in sporulation efficiency do not explain most of the variation in gene expression. The balance between the main effects and gene-gene interactions on gene expression variation is not the same as on sporulation efficiency. Finally, we show that nucleotide variants in the same transcription factor explain the expression variation of different sets of target genes depending on whether the variant alters the level or activity of the transcription factor. Our results suggest that a subset of gene expression changes may be more predictive of ultimate phenotypes than the number of genes affected or the total fraction of variation in gene expression variation explained by causative variants, and that the downstream phenotype is buffered against variation in the gene expression network.

Mapping small effect mutations in Saccharomyces cerevisiae: impacts of experimental design and mutational properties

Genetic variants identified by mapping are biased toward large phenotypic effects because of methodologic challenges for detecting genetic variants with small phenotypic effects. Recently, bulk segregant analysis combined with next-generation sequencing (BSA-seq) was shown to be a powerful and cost-effective way to map small effect variants in natural populations. Here, we examine the power of BSA-seq for efficiently mapping small effect mutations isolated from a mutagenesis screen. Specifically, we determined the impact of segregant population size, intensity of phenotypic selection to collect segregants, number of mitotic generations between meiosis and sequencing, and average sequencing depth on power for mapping mutations with a range of effects on the phenotypic mean and standard deviation as well as relative fitness. We then used BSA-seq to map the mutations responsible for three ethyl methanesulfonate−induced mutant phenotypes in Saccharomyces cerevisiae. These mutants display small quantitative variation in the mean expression of a fluorescent reporter gene (−3%, +7%, and +10%). Using a genetic background with increased meiosis rate, a reliable mating type marker, and fluorescence-activated cell sorting to efficiently score large segregating populations and isolate cells with extreme phenotypes, we successfully mapped and functionally confirmed a single point mutation responsible for the mutant phenotype in all three cases. Our simulations and experimental data show that the effects of a causative site not only on the mean phenotype, but also on its standard deviation and relative fitness should be considered when mapping genetic variants in microorganisms such as yeast that require population growth steps for BSA-seq.

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.

Exploiting the extraordinary genetic polymorphism of ciona for developmental genetics with whole genome sequencing

Studies in tunicates such as Ciona have revealed new insights into the evolutionary origins of chordate development. Ciona populations are characterized by high levels of natural genetic variation, between 1 and 5%. This variation has provided abundant material for forward genetic studies. In the current study, we make use of deep sequencing and homozygosity mapping to map spontaneous mutations in outbred populations. With this method we have mapped two spontaneous developmental mutants. In Ciona intestinalis we mapped a short-tail mutation with strong phenotypic similarity to a previously identified mutant in the related species Ciona savignyi. Our bioinformatic approach mapped the mutation to a narrow interval containing a single mutated gene, α-laminin3,4,5, which is the gene previously implicated in C. savignyi. In addition, we mapped a novel genetic mutation disrupting neural tube closure in C. savignyi to a T-type Ca(2+) channel gene. The high efficiency and unprecedented mapping resolution of our study is a powerful advantage for developmental genetics in Ciona, and may find application in other outbred species.

QTL dissection of Lag phase in wine fermentation reveals a new translocation responsible for Saccharomyces cerevisiae adaptation to sulfite

Quantitative genetics and QTL mapping are efficient strategies for deciphering the genetic polymorphisms that explain the phenotypic differences of individuals within the same species. Since a decade, this approach has been applied to eukaryotic microbes such as Saccharomyces cerevisiae in order to find natural genetic variations conferring adaptation of individuals to their environment. In this work, a QTL responsible for lag phase duration in the alcoholic fermentation of grape juice was dissected by reciprocal hemizygosity analysis. After invalidating the effect of some candidate genes, a chromosomal translocation affecting the lag phase was brought to light using de novo assembly of parental genomes. This newly described translocation (XV-t-XVI) involves the promoter region of ADH1 and the gene SSU1 and confers an increased expression of the sulfite pump during the first hours of alcoholic fermentation. This translocation constitutes another adaptation route of wine yeast to sulfites in addition to the translocation VIII-t-XVI previously described. A population survey of both translocation forms in a panel of domesticated yeast strains suggests that the translocation XV-t-XVI has been empirically selected by human activity.

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.

The molecular basis of phenotypic variation in yeast

The power of yeast genetics has now been extensively applied to phenotypic variation among strains of Saccharomyces cerevisiae. As a result, over 100 genes and numerous sequence variants have been identified, providing us with a general characterization of mutations underlying quantitative trait variation. Most quantitative trait alleles exert considerable phenotypic effects and alter conserved amino acid positions within protein coding sequences. When examined, quantitative trait alleles influence the expression of numerous genes, most of which are unrelated to an allele's phenotypic effect. The profile of quantitative trait alleles has proven useful to reverse quantitative genetics approaches and supports the use of systems genetics approaches to synthesize the molecular basis of trait variation across multiple strains.

Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis

Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.

High-resolution mapping of complex traits with a four-parent advanced intercross yeast population

A large fraction of human complex trait heritability is due to a high number of variants with small marginal effects and their interactions with genotype and environment. Such alleles are more easily studied in model organisms, where environment, genetic makeup, and allele frequencies can be controlled. Here, we examine the effect of natural genetic variation on heritable traits in a very large pool of baker's yeast from a multiparent 12th generation intercross. We selected four representative founder strains to produce the Saccharomyces Genome Resequencing Project (SGRP)-4X mapping population and sequenced 192 segregants to generate an accurate genetic map. Using these individuals, we mapped 25 loci linked to growth traits under heat stress, arsenite, and paraquat, the majority of which were best explained by a diverging phenotype caused by a single allele in one condition. By sequencing pooled DNA from millions of segregants grown under heat stress, we further identified 34 and 39 regions selected in haploid and diploid pools, respectively, with most of the selection against a single allele. While the most parsimonious model for the majority of loci mapped using either approach was the effect of an allele private to one founder, we could validate examples of pleiotropic effects and complex allelic series at a locus. SGRP-4X is a deeply characterized resource that provides a framework for powerful and high-resolution genetic analysis of yeast phenotypes and serves as a test bed for testing avenues to attack human complex traits.

Predicting complex phenotype-genotype interactions to enable yeast engineering: Saccharomyces cerevisiae as a model organism and a cell factory

There is an increasing use of systems biology approaches in both "red" and "white" biotechnology in order to enable medical, medicinal, and industrial applications. The intricate links between genotype and phenotype may be explained through the use of the tools developed in systems biology, synthetic biology, and evolutionary engineering. Biomedical and biotechnological research are among the fields that could benefit most from the elucidation of this complex relationship. Researchers have studied fitness extensively to explain the phenotypic impacts of genetic variations. This elaborate network of dependencies and relationships so revealed are further complicated by the influence of environmental effects that present major challenges to our achieving an understanding of the cellular mechanisms leading to healthy or diseased phenotypes or optimized production yields. An improved comprehension of complex genotype-phenotype interactions and their accurate prediction should enable us to more effectively engineer yeast as a cell factory and to use it as a living model of human or pathogen cells in intelligent screens for new drugs. This review presents different methods and approaches undertaken toward improving our understanding and prediction of the growth phenotype of the yeast Saccharomyces cerevisiae as both a model and a production organism.

QTL analysis of high thermotolerance with superior and downgraded parental yeast strains reveals new minor QTLs and converges on novel causative alleles involved in RNA processing

Revealing QTLs with a minor effect in complex traits remains difficult. Initial strategies had limited success because of interference by major QTLs and epistasis. New strategies focused on eliminating major QTLs in subsequent mapping experiments. Since genetic analysis of superior segregants from natural diploid strains usually also reveals QTLs linked to the inferior parent, we have extended this strategy for minor QTL identification by eliminating QTLs in both parent strains and repeating the QTL mapping with pooled-segregant whole-genome sequence analysis. We first mapped multiple QTLs responsible for high thermotolerance in a natural yeast strain, MUCL28177, compared to the laboratory strain, BY4742. Using single and bulk reciprocal hemizygosity analysis we identified MKT1 and PRP42 as causative genes in QTLs linked to the superior and inferior parent, respectively. We subsequently downgraded both parents by replacing their superior allele with the inferior allele of the other parent. QTL mapping using pooled-segregant whole-genome sequence analysis with the segregants from the cross of the downgraded parents, revealed several new QTLs. We validated the two most-strongly linked new QTLs by identifying NCS2 and SMD2 as causative genes linked to the superior downgraded parent and we found an allele-specific epistatic interaction between PRP42 and SMD2. Interestingly, the related function of PRP42 and SMD2 suggests an important role for RNA processing in high thermotolerance and underscores the relevance of analyzing minor QTLs. Our results show that identification of minor QTLs involved in complex traits can be successfully accomplished by crossing parent strains that have both been downgraded for a single QTL. This novel approach has the advantage of maintaining all relevant genetic diversity as well as enough phenotypic difference between the parent strains for the trait-of-interest and thus maximizes the chances of successfully identifying additional minor QTLs that are relevant for the phenotypic difference between the original parents.

Most traits of organisms are determined by an interplay of different genes interacting in a complex way. For instance, nearly all industrially-important traits of the yeast Saccharomyces cerevisiae are complex traits. We have analyzed high thermotolerance, which is important for industrial fermentations, reducing cooling costs and sustaining higher productivity. Whereas genetic analysis of complex traits has been cumbersome for many years, the development of pooled-segregant whole-genome sequence analysis now allows successful identification of underlying genetic loci with a major effect. On the other hand, identification of loci with a minor contribution remains a challenge. We now present a methodology for identifying minor loci, which is based on the finding that the inferior parent usually also harbours superior alleles. This allowed construction for the trait of high thermotolerance of two ‘downgraded parent strains’ by replacing in each parent a superior allele by the inferior allele from the other parent. Subsequent mapping with the downgraded parents revealed new minor loci, which we validated by identifying the causative genes. Hence, our results illustrate the power of this methodology for successfully identifying minor loci determining complex traits and with a high chance of being co-responsible for the phenotypic difference between the original parents.

Genetic and nongenetic determinants of cell growth variation assessed by high-throughput microscopy

In microbial populations, growth initiation and proliferation rates are major components of fitness and therefore likely targets of selection. We used a high-throughput microscopy assay, which enables simultaneous analysis of tens of thousands of microcolonies, to determine the sources and extent of growth rate variation in the budding yeast (Saccharomyces cerevisiae) in different glucose environments. We find that cell growth rates are regulated by the extracellular concentration of glucose as proposed by Monod (1949), but that significant heterogeneity in growth rates is observed among genetically identical individuals within an environment. Yeast strains isolated from different geographic locations and habitats differ in their growth rate responses to different glucose concentrations. Inheritance patterns suggest that the genetic determinants of growth rates in different glucose concentrations are distinct. In addition, we identified genotypes that differ in the extent of variation in growth rate within an environment despite nearly identical mean growth rates, providing evidence that alleles controlling phenotypic variability segregate in yeast populations. We find that the time to reinitiation of growth (lag) is negatively correlated with growth rate, yet this relationship is strain-dependent. Between environments, the respirative activity of individual cells negatively correlates with glucose abundance and growth rate, but within an environment respirative activity and growth rate show a positive correlation, which we propose reflects differences in protein expression capacity. Our study quantifies the sources of genetic and nongenetic variation in cell growth rates in different glucose environments with unprecedented precision, facilitating their molecular genetic dissection.

Genome wide association identifies novel loci involved in fungal communication

Understanding how genomes encode complex cellular and organismal behaviors has become the outstanding challenge of modern genetics. Unlike classical screening methods, analysis of genetic variation that occurs naturally in wild populations can enable rapid, genome-scale mapping of genotype to phenotype with a medium-throughput experimental design. Here we describe the results of the first genome-wide association study (GWAS) used to identify novel loci underlying trait variation in a microbial eukaryote, harnessing wild isolates of the filamentous fungus Neurospora crassa. We genotyped each of a population of wild Louisiana strains at 1 million genetic loci genome-wide, and we used these genotypes to map genetic determinants of microbial communication. In N. crassa, germinated asexual spores (germlings) sense the presence of other germlings, grow toward them in a coordinated fashion, and fuse. We evaluated germlings of each strain for their ability to chemically sense, chemotropically seek, and undergo cell fusion, and we subjected these trait measurements to GWAS. This analysis identified one gene, NCU04379 (cse-1, encoding a homolog of a neuronal calcium sensor), at which inheritance was strongly associated with the efficiency of germling communication. Deletion of cse-1 significantly impaired germling communication and fusion, and two genes encoding predicted interaction partners of CSE1 were also required for the communication trait. Additionally, mining our association results for signaling and secretion genes with a potential role in germling communication, we validated six more previously unknown molecular players, including a secreted protease and two other genes whose deletion conferred a novel phenotype of increased communication and multi-germling fusion. Our results establish protein secretion as a linchpin of germling communication in N. crassa and shed light on the regulation of communication molecules in this fungus. Our study demonstrates the power of population-genetic analyses for the rapid identification of genes contributing to complex traits in microbial species.

Many phenotypes of interest are controlled by multiple loci, and in biological systems identifying determinants of such complex traits is challenging. Here, we genotyped 112 wild isolates of Neurospora crassa and used this resource to identify genes that mediate a fundamental but poorly-understood attribute of this filamentous fungus: the ability of germinating spores to sense each other at a distance, extend projections toward one another, and fuse. Inheritance at a secretion gene, cse-1, was associated strongly with germling communication across wild strains; this association was validated in experiments showing reduced communication in a cse-1 deletion strain. By testing interacting partners of CSE1, and by assessing additional secretion and signaling factors whose inheritance associated more modestly with germling communication in wild strains, we identified eight other novel determinants of this phenotype. Our population of genotyped wild isolates provides a flexible and powerful community resource for the rapid identification of any varying, complex phenotype in N. crassa. The success of our approach, which used a phenotyping scheme far more tractable than would be required in a screen of the entire N. crassa gene deletion collection, serves as a proof of concept for association studies of wild populations for any organism.