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

QTL mapping reveals novel genes and mechanisms underlying variations in H2S production during alcoholic fermentation in Saccharomyces cerevisiae

Saccharomyces cerevisiae requirement for reduced sulfur to synthesize methionine and cysteine during alcoholic fermentation, is mainly fulfilled through the sulfur assimilation pathway. Saccharomyces cerevisiae reduces sulfate into sulfur dioxide (SO2) and sulfide (H2S), whose overproduction is a major issue in winemaking, due to its negative impact on wine aroma. The amount of H2S produced is highly strain-specific and also depends on SO2 concentration, often added to grape must. Applying a bulk segregant analysis to a 96-strain-progeny derived from two strains with different abilities to produce H2S, and comparing allelic frequencies along the genome of pools of segregants producing contrasting H2S quantities, we identified two causative regions involved in H2S production in the presence of SO2. A functional genetic analysis allowed the identification of variants in four genes able to impact H2S formation, viz; ZWF1, ZRT2, SNR2, and YLR125W, and involved in functions and pathways not associated with sulfur metabolism until now. These data point out that, in wine fermentation conditions, redox status, and zinc homeostasis are linked to H2S formation while providing new insights into the regulation of H2S production, and a new vision of the interplay between the sulfur assimilation pathway and cell metabolism.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene overexpression, revealing that the fitness costs of copy-number variation can vary substantially with genetic background in a common-garden environment. But the interplay between copy-number variation tolerance and environment remains unexplored on a genomic scale. Here, we measured the tolerance to gene overexpression in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride stress. Overexpressed genes that are commonly deleterious during sodium chloride stress recapitulated those commonly deleterious under standard conditions. However, sodium chloride stress uncovered novel differences in strain responses to gene overexpression. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to sodium chloride stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to overexpression of specific genes. Although most genes were deleterious, hundreds were beneficial when overexpressed-remarkably, most of these effects were strain specific. Few beneficial genes were shared between the sodium chloride-sensitive isolates, implicating mechanistic differences behind their sodium chloride sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural copy-number variation of a sodium export pump that likely contributes to strain-specific responses to overexpression of other genes. Our results reveal extensive strain-by-environment interactions in the response to gene copy-number variation, raising important implications for the accessibility of copy-number variation-dependent evolutionary routes under times of stress.

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation (CNV) provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene over-expression (OE), revealing that the fitness costs of CNV can vary substantially with genetic background in a common-garden environment. But the interplay between CNV tolerance and environment remains unexplored on a genomic scale. Here we measured the tolerance to gene OE in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride (NaCl) stress. OE genes that are commonly deleterious during NaCl stress recapitulated those commonly deleterious under standard conditions. However, NaCl stress uncovered novel differences in strain responses to gene OE. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to NaCl stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to gene OE. Although most genes were deleterious, hundreds were beneficial when overexpressed - remarkably, most of these effects were strain specific. Few beneficial genes were shared between the NaCl-sensitive isolates, implicating mechanistic differences behind their NaCl sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural CNV of a sodium export pump that likely contributes to strain-specific responses to OE of other genes. Our results reveal extensive strain-by-environment interaction in the response to gene CNV, raising important implications for the accessibility of CNV-dependent evolutionary routes under times of stress.

Identification of genetic variants of the industrial yeast Komagataella phaffii (Pichia pastoris) that contribute to increased yields of secreted heterologous proteins

The yeast Komagataella phaffii (formerly called Pichia pastoris) is used widely as a host for secretion of heterologous proteins, but only a few isolates of this species exist and all the commonly used expression systems are derived from a single genetic background, CBS7435 (NRRL Y-11430). We hypothesized that other genetic backgrounds could harbor variants that affect yields of secreted proteins. We crossed CBS7435 with 2 other K. phaffii isolates and mapped quantitative trait loci (QTLs) for secretion of a heterologous protein, β-glucosidase, by sequencing individual segregant genomes. A major QTL mapped to a frameshift mutation in the mannosyltransferase gene HOC1, which gives CBS7435 a weaker cell wall and higher protein secretion than the other isolates. Inactivation of HOC1 in the other isolates doubled β-glucosidase secretion. A second QTL mapped to an amino acid substitution in IRA1 that tripled β-glucosidase secretion in 1-week batch cultures but reduced cell viability, and its effects are specific to this heterologous protein. Our results demonstrate that QTL analysis is a powerful method for dissecting the basis of biotechnological traits in nonconventional yeasts, and a route to improving their industrial performance.

A widespread inversion polymorphism conserved among Saccharomyces species is caused by recurrent homogenization of a sporulation gene family

Saccharomyces genomes are highly collinear and show relatively little structural variation, both within and between species of this yeast genus. We investigated the only common inversion polymorphism known in S. cerevisiae, which affects a 24-kb 'flip/flop' region containing 15 genes near the centromere of chromosome XIV. The region exists in two orientations, called reference (REF) and inverted (INV). Meiotic recombination in this region is suppressed in crosses between REF and INV orientation strains such as the BY x RM cross. We find that the inversion polymorphism is at least 17 million years old because it is conserved across the genus Saccharomyces. However, the REF and INV isomers are not ancient alleles but are continually being re-created by re-inversion of the region within each species. Inversion occurs due to continual homogenization of two almost identical 4-kb sequences that form an inverted repeat (IR) at the ends of the flip/flop region. The IR consists of two pairs of genes that are specifically and strongly expressed during the late stages of sporulation. We show that one of these gene pairs, YNL018C/YNL034W, codes for a protein that is essential for spore formation. YNL018C and YNL034W are the founder members of a gene family, Centroid, whose members in other Saccharomycetaceae species evolve fast, duplicate frequently, and are preferentially located close to centromeres. We tested the hypothesis that Centroid genes are a meiotic drive system, but found no support for this idea.

High-throughput approaches to functional characterization of genetic variation in yeast

Expansion of sequencing efforts to include thousands of genomes is providing a fundamental resource for determining the genetic diversity that exists in a population. Now, high-throughput approaches are necessary to begin to understand the role these genotypic changes play in affecting phenotypic variation. Saccharomyces cerevisiae maintains its position as an excellent model system to determine the function of unknown variants with its exceptional genetic diversity, phenotypic diversity, and reliable genetic manipulation tools. Here, we review strategies and techniques developed in yeast that scale classic approaches of assessing variant function. These approaches improve our ability to better map quantitative trait loci at a higher resolution, even for rare variants, and are already providing greater insight into the role that different types of mutations play in phenotypic variation and evolution not just in yeast but across taxa.

QTL mapping of a Brazilian bioethanol strain links the cell wall protein-encoding gene GAS1 to low pH tolerance in S. cerevisiae

BACKGROUND

Saccharomyces cerevisiae is largely applied in many biotechnological processes, from traditional food and beverage industries to modern biofuel and biochemicals factories. During the fermentation process, yeast cells are usually challenged in different harsh conditions, which often impact productivity. Regarding bioethanol production, cell exposure to acidic environments is related to productivity loss on both first- and second-generation ethanol. In this scenario, indigenous strains traditionally used in fermentation stand out as a source of complex genetic architecture, mainly due to their highly robust background-including low pH tolerance.

RESULTS

In this work, we pioneer the use of QTL mapping to uncover the genetic basis that confers to the industrial strain Pedra-2 (PE-2) acidic tolerance during growth at low pH. First, we developed a fluorescence-based high-throughput approach to collect a large number of haploid cells using flow cytometry. Then, we were able to apply a bulk segregant analysis to solve the genetic basis of low pH resistance in PE-2, which uncovered a region in chromosome X as the major QTL associated with the evaluated phenotype. A reciprocal hemizygosity analysis revealed the allele GAS1, encoding a β-1,3-glucanosyltransferase, as the casual variant in this region. The GAS1 sequence alignment of distinct S. cerevisiae strains pointed out a non-synonymous mutation (A631G) prevalence in wild-type isolates, which is absent in laboratory strains. We further showcase that GAS1 allele swap between PE-2 and a low pH-susceptible strain can improve cell viability on the latter of up to 12% after a sulfuric acid wash process.

CONCLUSION

This work revealed GAS1 as one of the main causative genes associated with tolerance to growth at low pH in PE-2. We also showcase how GAS1PE-2 can improve acid resistance of a susceptible strain, suggesting that these findings can be a powerful foundation for the development of more robust and acid-tolerant strains. Our results collectively show the importance of tailored industrial isolated strains in discovering the genetic architecture of relevant traits and its implications over productivity.

Pleiotropy and epistasis within and between signaling pathways defines the genetic architecture of fungal virulence

Cryptococcal disease is estimated to affect nearly a quarter of a million people annually. Environmental isolates of Cryptococcus deneoformans, which make up 15 to 30% of clinical infections in temperate climates such as Europe, vary in their pathogenicity, ranging from benign to hyper-virulent. Key traits that contribute to virulence, such as the production of the pigment melanin, an extracellular polysaccharide capsule, and the ability to grow at human body temperature have been identified, yet little is known about the genetic basis of variation in such traits. Here we investigate the genetic basis of melanization, capsule size, thermal tolerance, oxidative stress resistance, and antifungal drug sensitivity using quantitative trait locus (QTL) mapping in progeny derived from a cross between two divergent C. deneoformans strains. Using a "function-valued" QTL analysis framework that exploits both time-series information and growth differences across multiple environments, we identified QTL for each of these virulence traits and drug susceptibility. For three QTL we identified the underlying genes and nucleotide differences that govern variation in virulence traits. One of these genes, RIC8, which encodes a regulator of cAMP-PKA signaling, contributes to variation in four virulence traits: melanization, capsule size, thermal tolerance, and resistance to oxidative stress. Two major effect QTL for amphotericin B resistance map to the genes SSK1 and SSK2, which encode key components of the HOG pathway, a fungal-specific signal transduction network that orchestrates cellular responses to osmotic and other stresses. We also discovered complex epistatic interactions within and between genes in the HOG and cAMP-PKA pathways that regulate antifungal drug resistance and resistance to oxidative stress. Our findings advance the understanding of virulence traits among diverse lineages of Cryptococcus, and highlight the role of genetic variation in key stress-responsive signaling pathways as a major contributor to phenotypic variation.

History and Domestication of Saccharomyces cerevisiae in Bread Baking

The yeast Saccharomyces cerevisiae has been instrumental in the fermentation of foods and beverages for millennia. In addition to fermentations like wine, beer, cider, sake, and bread, S. cerevisiae has been isolated from environments ranging from soil and trees, to human clinical isolates. Each of these environments has unique selection pressures that S. cerevisiae must adapt to. Bread dough, for example, requires S. cerevisiae to efficiently utilize the complex sugar maltose; tolerate osmotic stress due to the semi-solid state of dough, high salt, and high sugar content of some doughs; withstand various processing conditions, including freezing and drying; and produce desirable aromas and flavors. In this review, we explore the history of bread that gave rise to modern commercial baking yeast, and the genetic and genomic changes that accompanied this. We illustrate the genetic and phenotypic variation that has been documented in baking strains and wild strains, and how this variation might be used for baking strain improvement. While we continue to improve our understanding of how baking strains have adapted to bread dough, we conclude by highlighting some of the remaining open questions in the field.

A natural variant of the essential host gene MMS21 restricts the parasitic 2-micron plasmid in Saccharomyces cerevisiae

Antagonistic coevolution with selfish genetic elements (SGEs) can drive evolution of host resistance. Here, we investigated host suppression of 2-micron (2μ) plasmids, multicopy nuclear parasites that have co-evolved with budding yeasts. We developed SCAMPR (Single-Cell Assay for Measuring Plasmid Retention) to measure copy number heterogeneity and 2μ plasmid loss in live cells. We identified three S. cerevisiae strains that lack endogenous 2μ plasmids and reproducibly inhibit mitotic plasmid stability. Focusing on the Y9 ragi strain, we determined that plasmid restriction is heritable and dominant. Using bulk segregant analysis, we identified a high-confidence Quantitative Trait Locus (QTL) with a single variant of MMS21 associated with increased 2μ instability. MMS21 encodes a SUMO E3 ligase and an essential component of the Smc5/6 complex, involved in sister chromatid cohesion, chromosome segregation, and DNA repair. Our analyses leverage natural variation to uncover a novel means by which budding yeasts can overcome highly successful genetic parasites.

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

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

Two Synthetic 18-Way Outcrossed Populations of Diploid Budding Yeast with Utility for Complex Trait Dissection

Advanced-generation multiparent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than genome-wide association studies to detect rare variants and higher resolution than F2 linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from 18 genetically diverse founding strains. We carried out de novo assemblies of the genomes of the 18 founder strains, such that virtually all variation segregating between these strains is known, and represented those assemblies as Santa Cruz Genome Browser tracks. We discovered complex patterns of structural variation segregating among the founders, including a large deletion within the vacuolar ATPase VMA1, several different deletions within the osmosensor MSB2, a series of deletions and insertions at PRM7 and the adjacent BSC1, as well as copy number variation at the dehydrogenase ALD2 Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66 kb, demonstrating that the population is highly recombined. We pool-sequenced the two MPPs to 3270× and 2226× coverage and demonstrated that we can accurately estimate local haplotype frequencies using pooled data. We further downsampled the pool-sequenced data to ∼20-40× and showed that local haplotype frequency estimates remained accurate, with median error rates 0.8 and 0.6% at 20× and 40×, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that 10 or more founders are present at a detectable frequency for > 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

Exploiting strain diversity and rational engineering strategies to enhance recombinant cellulase secretion by Saccharomyces cerevisiae

Consolidated bioprocessing (CBP) of lignocellulosic material into bioethanol has progressed in the past decades; however, several challenges still exist which impede the industrial application of this technology. Identifying the challenges that exist in all unit operations is crucial and needs to be optimised, but only the barriers related to the secretion of recombinant cellulolytic enzymes in Saccharomyces cerevisiae will be addressed in this review. Fundamental principles surrounding CBP as a biomass conversion platform have been established through the successful expression of core cellulolytic enzymes, namely β-glucosidases, endoglucanases, and exoglucanases (cellobiohydrolases) in S. cerevisiae. This review will briefly address the challenges involved in the construction of an efficient cellulolytic yeast, with particular focus on the secretion efficiency of cellulases from this host. Additionally, strategies for studying enhanced cellulolytic enzyme secretion, which include both rational and reverse engineering approaches, will be discussed. One such technique includes bio-engineering within genetically diverse strains, combining the strengths of both natural strain diversity and rational strain development. Furthermore, with the advancement in next-generation sequencing, studies that utilise this method of exploiting intra-strain diversity for industrially relevant traits will be reviewed. Finally, future prospects are discussed for the creation of ideal CBP strains with high enzyme production levels.Key Points• Several challenges are involved in the construction of efficient cellulolytic yeast, in particular, the secretion efficiency of cellulases from the hosts.• Strategies for enhancing cellulolytic enzyme secretion, a core requirement for CBP host microorganism development, include both rational and reverse engineering approaches.• One such technique includes bio-engineering within genetically diverse strains, combining the strengths of both natural strain diversity and rational strain development.

Mapping Ethanol Tolerance in Budding Yeast Reveals High Genetic Variation in a Wild Isolate

Ethanol tolerance, a polygenic trait of the yeast Saccharomyces cerevisiae, is the primary factor determining industrial bioethanol productivity. Until now, genomic elements affecting ethanol tolerance have been mapped only at low resolution, hindering their identification. Here, we explore the genetic architecture of ethanol tolerance, in the F6 generation of an Advanced Intercrossed Line (AIL) mapping population between two phylogenetically distinct, but phenotypically similar, S. cerevisiae strains (a common laboratory strain and a wild strain isolated from nature). Under ethanol stress, 51 quantitative trait loci (QTLs) affecting growth and 96 QTLs affecting survival, most of them novel, were identified, with high resolution, in some cases to single genes, using a High-Resolution Mapping Package of methodologies that provided high power and high resolution. We confirmed our results experimentally by showing the effects of the novel mapped genes: MOG1, MGS1, and YJR154W. The mapped QTLs explained 34% of phenotypic variation for growth and 72% for survival. High statistical power provided by our analysis allowed detection of many loci with small, but mappable effects, uncovering a novel “quasi-infinitesimal” genetic architecture. These results are striking demonstration of tremendous amounts of hidden genetic variation exposed in crosses between phylogenetically separated strains with similar phenotypes; as opposed to the more common design where strains with distinct phenotypes are crossed. Our findings suggest that ethanol tolerance is under natural evolutionary fitness-selection for an optimum phenotype that would tend to eliminate alleles of large effect. The study provides a platform for development of superior ethanol-tolerant strains using genome editing or selection.

Natural allelic variations of Saccharomyces cerevisiae impact stuck fermentation due to the combined effect of ethanol and temperature; a QTL-mapping study

BACKGROUND

Fermentation completion is a major prerequisite in many industrial processes involving the bakery yeast Saccharomyces cerevisiae. Stuck fermentations can be due to the combination of many environmental stresses. Among them, high temperature and ethanol content are particularly deleterious especially in bioethanol and red wine production. Although the genetic causes of temperature and/or ethanol tolerance were widely investigated in laboratory conditions, few studies investigated natural genetic variations related to stuck fermentations in high gravity matrixes.

RESULTS

In this study, three QTLs linked to stuck fermentation in winemaking conditions were identified by using a selective genotyping strategy carried out on a backcrossed population. The precision of mapping allows the identification of two causative genes VHS1 and OYE2 characterized by stop-codon insertion. The phenotypic effect of these allelic variations was validated by Reciprocal Hemyzygous Assay in high gravity fermentations (> 240 g/L of sugar) carried out at high temperatures (> 28 °C). Phenotypes impacted were mostly related to the late stage of alcoholic fermentation during the stationary growth phase of yeast.

CONCLUSIONS

Our findings illustrate the complex genetic determinism of stuck fermentation and open new avenues for better understanding yeast resistance mechanisms involved in high gravity fermentations.

Signatures of directional selection in a hybrid yeast population

Meiotic recombination is a fundamental biological process that leads to crossover and gene conversion. High resolution maps of meiotic recombination have been reported in several model organisms. However, few studies have studied how rapidly selection affects the products of meiotic recombination. Here we constructed and sequenced a yeast population of 38 haploid strains derived from hybridizations of two common used strains S288c and YJM789. We identified 20 regions with strong biased allele frequency across the genome, revealing signatures of selection in a rather short period. These regions harbor ample crossovers and gene conversions, which enable us to trace how selection works on the genomic fragments after meiosis. The total length of such regions under selection accounts for 5% of the entire genome, and those regions contain many functional-related genes. In addition, recombination breaks down linkage disequilibrium to half of its maximum within 42 kb and reduces nucleotide diversity significantly in selected regions. Our study thus provides details of directional selection on the outcomes of meiotic recombination using experimental approaches, and will shed light on our understanding of the fast reshaping of population structure by selection, as well as the important roles of recombination.

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

A central goal of modern genetics is to understand how and why organisms in the wild differ in phenotype. To date, the field has advanced largely on the strength of linkage and association mapping methods, which trace the relationship between DNA sequence variants and phenotype across recombinant progeny from matings between individuals of a species. These approaches, although powerful, are not well suited to trait differences between reproductively isolated species. Here we describe a new method for genome-wide dissection of natural trait variation that can be readily applied to incompatible species. Our strategy, RH-seq, is a genome-wide implementation of the reciprocal hemizygote test. We harnessed it to identify the genes responsible for the striking high temperature growth of the yeast Saccharomyces cerevisiae relative to its sister species S. paradoxus. RH-seq utilizes transposon mutagenesis to create a pool of reciprocal hemizygotes, which are then tracked through a high-temperature competition via high-throughput sequencing. Our RH-seq workflow as laid out here provides a rigorous, unbiased way to dissect ancient, complex traits in the budding yeast clade, with the caveat that resource-intensive deep sequencing is needed to ensure genomic coverage for genetic mapping. As sequencing costs drop, this approach holds great promise for future use across eukaryotes.

Quantitative Trait Nucleotides Impacting the Technological Performances of Industrial Saccharomyces cerevisiae Strains

The budding yeast Saccharomyces cerevisiae is certainly the prime industrial microorganism and is related to many biotechnological applications including food fermentations, biofuel production, green chemistry, and drug production. A noteworthy characteristic of this species is the existence of subgroups well adapted to specific processes with some individuals showing optimal technological traits. In the last 20 years, many studies have established a link between quantitative traits and single-nucleotide polymorphisms found in hundreds of genes. These natural variations constitute a pool of QTNs (quantitative trait nucleotides) that modulate yeast traits of economic interest for industry. By selecting a subset of genes functionally validated, a total of 284 QTNs were inventoried. Their distribution across pan and core genome and their frequency within the 1,011 Saccharomyces cerevisiae genomes were analyzed. We found that 150 of the 284 QTNs have a frequency lower than 5%, meaning that these variants would be undetectable by genome-wide association studies (GWAS). This analysis also suggests that most of the functional variants are private to a subpopulation, possibly due to their adaptive role to specific industrial environment. In this review, we provide a literature survey of their phenotypic impact and discuss the opportunities and the limits of their use for industrial strain selection.

Detecting genetic interactions using parallel evolution in experimental populations

Eukaryotic genomes contain thousands of genes organized into complex and interconnected genetic interaction networks. Most of our understanding of how genetic variation affects these networks comes from quantitative-trait loci mapping and from the systematic analysis of double-deletion (or knockdown) mutants, primarily in the yeast Saccharomyces cerevisiae. Evolve and re-sequence experiments are an alternative approach for identifying novel functional variants and genetic interactions, particularly between non-loss-of-function mutations. These experiments leverage natural selection to obtain genotypes with functionally important variants and positive genetic interactions. However, no systematic methods for detecting genetic interactions in these data are yet available. Here, we introduce a computational method based on the idea that variants in genes that interact will co-occur in evolved genotypes more often than expected by chance. We apply this method to a previously published yeast experimental evolution dataset. We find that genetic targets of selection are distributed non-uniformly among evolved genotypes, indicating that genetic interactions had a significant effect on evolutionary trajectories. We identify individual gene pairs with a statistically significant genetic interaction score. The strongest interaction is between genes TRK1 and PHO84, genes that have not been reported to interact in previous systematic studies. Our work demonstrates that leveraging parallelism in experimental evolution is useful for identifying genetic interactions that have escaped detection by other methods. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data

BACKGROUND

Quantitative trait locus (QTL) mapping using bulk segregants is an effective approach for identifying genetic variants associated with phenotypes of interest in model organisms. By exploiting next-generation sequencing technology, the QTL mapping accuracy can be improved significantly, providing a valuable means to annotate new genetic variants. However, setting up a comprehensive analysis framework for this purpose is a time-consuming and error-prone task, posing many challenges for scientists with limited experience in this domain.

RESULTS

Here, we present BSA4Yeast, a comprehensive web application for QTL mapping via bulk segregant analysis of yeast sequencing data. The software provides an automated and efficiency-optimized data processing, up-to-date functional annotations, and an interactive web interface to explore identified QTLs.

CONCLUSIONS

BSA4Yeast enables researchers to identify plausible candidate genes in QTL regions efficiently in order to validate their genetic variations experimentally as causative for a phenotype of interest. BSA4Yeast is freely available at https://bsa4yeast.lcsb.uni.lu.

Dissection of the molecular bases of genotype x environment interactions: a study of phenotypic plasticity of Saccharomyces cerevisiae in grape juices

Background

The ability of a genotype to produce different phenotypes according to its surrounding environment is known as phenotypic plasticity. Within different individuals of the same species, phenotypic plasticity can vary greatly. This contrasting response is caused by gene-by-environment interactions (GxE). Understanding GxE interactions is particularly important in agronomy, since selected breeds and varieties may have divergent phenotypes according to their growing environment. Industrial microbes such as Saccharomyces cerevisiae are also faced with a large range of fermentation conditions that affect their technological properties. Finding the molecular determinism of such variations is a critical task for better understanding the genetic bases of phenotypic plasticity and can also be helpful in order to improve breeding methods.

Results

In this study we implemented a QTL mapping program using two independent cross (~ 100 progeny) in order to investigate the molecular basis of yeast phenotypic response in a wine fermentation context. Thanks to whole genome sequencing approaches, both crosses were genotyped, providing saturated genetic maps of thousands of markers. Linkage analyses allowed the detection of 78 QTLs including 21 with significant interaction with the environmental conditions. Molecular dissection of a major QTL demonstrated that the sulfite pump Ssu1p has a pleiotropic effect and impacts the phenotypic plasticity of several traits.

Conclusions

The detection of QTLs and their interactions with environment emphasizes the complexity of yeast industrial traits. The validation of the interaction of SSU1 allelic variants with the nature of the fermented juice increases knowledge about the impact of the sulfite pump during fermentation. All together these results pave the way for exploiting and deciphering the genetic determinism of phenotypic plasticity.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5145-4) contains supplementary material, which is available to authorized users.

Genetic dissection of interspecific differences in yeast thermotolerance

Some of the most unique and compelling survival strategies in the natural world are fixed in isolated species1. To date, molecular insight into these ancient adaptations has been limited, as classic experimental genetics has focused on interfertile individuals in populations2. Here we use a new mapping approach, which screens mutants in a sterile interspecific hybrid, to identify eight housekeeping genes that underlie the growth advantage of Saccharomyces cerevisiae over its distant relative S. paradoxus at high temperature. Pro-thermotolerance alleles at these mapped loci were required for the adaptive trait in S. cerevisiae and sufficient for its partial reconstruction in S. paradoxus. The emerging picture is one in which S. cerevisiae improved the heat resistance of multiple components of the fundamental growth machinery in response to selective pressure. Our study lays the groundwork for the mapping of genotype to phenotype in clades of sister species across Eukarya.

Rapid Identification of Major QTLS Associated With Near- Freezing Temperature Tolerance in Saccharomyces cerevisiae

Temperatures had a strong effect on many life history traits, including growth, development and reproduction. At near-freezing temperatures (0–4°C), yeast cells could trigger series of biochemical reactions to respond and adapt to the stress, protect them against sever cold and freeze injury. Different Saccharomyces cerevisiae strains vary greatly in their ability to grow at near-freezing temperatures. However, the molecular mechanisms that allow yeast cells to sustain this response are not yet fully understood and the genetic basis of tolerance and sensitivity to near-freeze stress remains unclear. Uncovering the genetic determinants of this trait is, therefore, of is of significant interest. In order to investigate the genetic basis that underlies near-freezing temperature tolerance in S. cerevisiae, we mapped the major quantitative trait loci (QTLs) using bulk segregant analysis (BSA) in the F₂ segregant population of two Chinese indigenous S. cerevisiae strains with divergent tolerance capability at 4°C. By genome-wide comparison of single-nucleotide polymorphism (SNP) profiles between two bulks of segregants with high and low tolerance to near-freezing temperature, a hot region located on chromosome IV was identified tightly associated with the near-freezing temperature tolerance. The Reciprocal hemizygosity analysis (RHA) and gene deletion was used to validate the genes involved in the trait, showed that the gene NAT1 plays a role in the near-freezing temperature tolerance. This study improved our understanding of the genetic basis of the variability of near-freezing temperature tolerance in yeasts. The superior allele identified could be used to genetically improve the near-freezing stress adaptation of industrial yeast strains.

Structure based drug design and in vitro metabolism study: Discovery of N-(4-methylthiophenyl)-N,2-dimethyl-cyclopenta[d]pyrimidine as a potent microtubule targeting agent

We report a series of tubulin targeting agents, some of which demonstrate potent antiproliferative activities. These analogs were designed to optimize the antiproliferative activity of 1 by varying the heteroatom substituent at the 4'-position, the basicity of the 4-position amino moiety, and conformational restriction. The potential metabolites of the active compounds were also synthesized. Some compounds demonstrated single digit nanomolar IC₅₀ values for antiproliferative effects in MDA-MB-435 melanoma cells. Particularly, the S-methyl analog 3 was more potent than 1 in MDA-MB-435 cells (IC₅₀ = 4.6 nM). Incubation of 3 with human liver microsomes showed that the primary metabolite of the S-methyl moiety of 3 was the methyl sulfinyl group, as in analog 5. This metabolite was equipotent with the lead compound 1 in MDA-MB-435 cells (IC₅₀ = 7.9 nM). Molecular modeling and electrostatic surface area were determined to explain the activities of the analogs. Most of the potent compounds overcome multiple mechanisms of drug resistance and compound 3 emerged as the lead compound for further SAR and preclinical development.

Gene-gene and gene-environment interactions in complex traits in yeast

One of the fundamental questions in biology is how the genotype regulates the phenotype. An increasing number of studies indicate that, in most cases, the effect of a genetic locus on the phenotype is context-dependent, i.e. it is influenced by the genetic background and the environment in which the phenotype is measured. Still, the majority of the studies, in both model organisms and humans, that map the genetic regulation of phenotypic variation in complex traits primarily identify additive loci with independent effects. This does not reflect an absence of the contribution of genetic interactions to phenotypic variation, but instead is a consequence of the technical limitations in mapping gene-gene interactions (GGI) and gene-environment interactions (GEI). Yeast, with its detailed molecular understanding, diverse population genomics and ease of genetic manipulation, is a unique and powerful resource to study the contributions of GGI and GEI in the regulation of phenotypic variation. Here we review studies in yeast that have identified GGI and GEI that regulate phenotypic variation, and discuss the contribution of these findings in explaining missing heritability of complex traits, and how observations from these GGI and GEI studies enhance our understanding of the mechanisms underlying genetic robustness and adaptability that shape the architecture of the genotype-phenotype map.

PHENOS: a high-throughput and flexible tool for microorganism growth phenotyping on solid media

Background

Microbial arrays, with a large number of different strains on a single plate printed with robotic precision, underpin an increasing number of genetic and genomic approaches. These include Synthetic Genetic Array analysis, high-throughput Quantitative Trait Loci (QTL) analysis and 2-hybrid techniques. Measuring the growth of individual colonies within these arrays is an essential part of many of these techniques but is useful for any work with arrays. Measurement is typically done using intermittent imagery fed into complex image analysis software, which is not especially accurate and is challenging to use effectively. We have developed a simple and fast alternative technique that uses a pinning robot and a commonplace microplate reader to continuously measure the thickness of colonies growing on solid agar, complemented by a technique for normalizing the amount of cells initially printed to each spot of the array in the first place. We have developed software to automate the process of combining multiple sets of readings, subtracting agar absorbance, and visualizing colony thickness changes in a number of informative ways.

Results

The “PHENOS” pipeline (PHENotyping On Solid media), optimized for Saccharomyces yeasts, produces highly reproducible growth curves and is particularly sensitive to low-level growth. We have empirically determined a formula to estimate colony cell count from an absorbance measurement, and shown this to be comparable with estimates from measurements in liquid. We have also validated the technique by reproducing the results of an earlier QTL study done with conventional liquid phenotyping, and found PHENOS to be considerably more sensitive.

Conclusions

“PHENOS” is a cost effective and reliable high-throughput technique for quantifying growth of yeast arrays, and is likely to be equally very useful for a range of other types of microbial arrays. A detailed guide to the pipeline and software is provided with the installation files at https://github.com/gact/phenos.

Electronic supplementary material

The online version of this article (10.1186/s12866-017-1143-y) contains supplementary material, which is available to authorized users.

Wine yeast phenomics: A standardized fermentation method for assessing quantitative traits of Saccharomyces cerevisiae strains in enological conditions

This work describes the set up of a small scale fermentation methodology for measuring quantitative traits of hundreds of samples in an enological context. By using standardized screw cap vessels, the alcoholic fermentation kinetics of Saccharomyces cerevisiae strains were measured by following their weight loss over the time. This dispositive was coupled with robotized enzymatic assays for measuring metabolites of enological interest in natural grape juices. Despite the small volume used, kinetic parameters and fermentation end products measured are similar with those observed in larger scale vats. The vessel used also offers the possibility to assay 32 volatiles compounds using a headspace solid-phase micro-extraction coupled to gas chromatography and mass spectrometry. The vessel shaking applied strongly impacted most of the phenotypes investigated due to oxygen transfer occuring in the first hours of the alcoholic fermentation. The impact of grape must and micro-oxygenation was investigated illustrating some relevant genetic x environmental interactions. By phenotyping a wide panel of commercial wine starters in five grape juices, broad phenotypic correlations between kinetics and metabolic end products were evidentiated. Moreover, a multivariate analysis illustrates that some grape musts are more able than others to discriminate commercial strains since some are less robust to environmental changes.

Natural Variation in SER1 and ENA6 Underlie Condition-Specific Growth Defects in Saccharomyces cerevisiae

Despite their ubiquitous use in laboratory strains, naturally occurring loss-of-function mutations in genes encoding core metabolic enzymes are relatively rare in wild isolates of Saccharomyces cerevisiae. Here, we identify a naturally occurring serine auxotrophy in a sake brewing strain from Japan. Through a cross with a honey wine (white tecc) brewing strain from Ethiopia, we map the minimal medium growth defect to SER1, which encodes 3-phosphoserine aminotransferase and is orthologous to the human disease gene, PSAT1. To investigate the impact of this polymorphism under conditions of abundant external nutrients, we examine growth in rich medium alone or with additional stresses, including the drugs caffeine and rapamycin and relatively high concentrations of copper, salt, and ethanol. Consistent with studies that found widespread effects of different auxotrophies on RNA expression patterns in rich media, we find that the SER1 loss-of-function allele dominates the quantitative trait locus (QTL) landscape under many of these conditions, with a notable exacerbation of the effect in the presence of rapamycin and caffeine. We also identify a major-effect QTL associated with growth on salt that maps to the gene encoding the sodium exporter, ENA6. We demonstrate that the salt phenotype is largely driven by variation in the ENA6 promoter, which harbors a deletion that removes binding sites for the Mig1 and Nrg1 transcriptional repressors. Thus, our results identify natural variation associated with both coding and regulatory regions of the genome that underlie strong growth phenotypes.

Identification of Novel Alleles Conferring Superior Production of Rose Flavor Phenylethyl Acetate Using Polygenic Analysis in Yeast

Flavor compound metabolism is one of the last areas in metabolism where multiple genes encoding biosynthetic enzymes are still unknown. A major challenge is the involvement of side activities of enzymes having their main function in other areas of metabolism. We have applied pooled-segregant whole-genome sequence analysis to identify novel Saccharomyces cerevisiae genes affecting production of phenylethyl acetate (2-PEAc). This is a desirable flavor compound of major importance in alcoholic beverages imparting rose- and honey-like aromas, with production of high 2-PEAc levels considered a superior trait. Four quantitative trait loci (QTLs) responsible for high 2-PEAc production were identified, with two loci each showing linkage to the genomes of the BTC.1D and ER18 parents. The first two loci were investigated further. The causative genes were identified by reciprocal allele swapping into both parents using clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9. The superior allele of the first major causative gene, FAS2, was dominant and contained two unique single nucleotide polymorphisms (SNPs) responsible for high 2-PEAc production that were not present in other sequenced yeast strains. FAS2 encodes the alpha subunit of the fatty acid synthetase complex. Surprisingly, the second causative gene was a mutant allele of TOR1, a gene involved in nitrogen regulation. Exchange of both superior alleles in the ER18 parent strain increased 2-PEAc production 70%, nearly to the same level as in the best superior segregant. Our results show that polygenic analysis combined with CRISPR/Cas9-mediated allele exchange is a powerful tool for identification of genes encoding missing metabolic enzymes and for development of industrial yeast strains generating novel flavor profiles in alcoholic beverages.IMPORTANCE Multiple reactions in flavor metabolism appear to be catalyzed by side activities of other enzymes that have been difficult to identify. We have applied genetic mapping of quantitative trait loci in the yeast Saccharomyces cerevisiae to identify mutant alleles of genes determining the production of phenylethyl acetate, an important flavor compound imparting rose- and honey-like aromas to alcoholic beverages. We identified a unique, dominant allele of FAS2 that supports high production of phenylethyl acetate. FAS2 encodes a subunit of the fatty acid synthetase complex and apparently exerts an important side activity on one or more alternative substrates in flavor compound synthesis. The second mutant allele contained a nonsense mutation in TOR1, a gene involved in nitrogen regulation of growth. Together the two alleles strongly increased the level of phenylethyl acetate. Our work highlights the potential of genetic mapping of quantitative phenotypic traits to identify novel enzymes and regulatory components in yeast metabolism, including regular metabolic enzymes with unknown side activities responsible for biosynthesis of specific flavor compounds. The superior alleles identified can be used to develop industrial yeast strains generating novel flavor profiles in alcoholic beverages.

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.

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.

Omics analysis of acetic acid tolerance in Saccharomyces cerevisiae

Acetic acid is an inhibitor in industrial processes such as wine making and bioethanol production from cellulosic hydrolysate. It causes energy depletion, inhibition of metabolic enzyme activity, growth arrest and ethanol productivity losses in Saccharomyces cerevisiae. Therefore, understanding the mechanisms of the yeast responses to acetic acid stress is essential for improving acetic acid tolerance and ethanol production. Although 329 genes associated with acetic acid tolerance have been identified in the Saccharomyces genome and included in the database ( http://www.yeastgenome.org/observable/resistance_to_acetic_acid/overview ), the cellular mechanistic responses to acetic acid remain unclear in this organism. Post-genomic approaches such as transcriptomics, proteomics, metabolomics and chemogenomics are being applied to yeast and are providing insight into the mechanisms and interactions of genes, proteins and other components that together determine complex quantitative phenotypic traits such as acetic acid tolerance. This review focuses on these omics approaches in the response to acetic acid in S. cerevisiae. Additionally, several novel strains with improved acetic acid tolerance have been engineered by modifying key genes, and the application of these strains and recently acquired knowledge to industrial processes is also discussed.

Quantitative Trait Loci (QTL)-Guided Metabolic Engineering of a Complex Trait

Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.

The Genomic Architecture of Interactions Between Natural Genetic Polymorphisms and Environments in Yeast Growth

Gene-environment interaction (G×E) refers to the phenomenon that the same mutation has different phenotypic effects in different environments. Although quantitative trait loci (QTLs) exhibiting G×E have been reported, little is known about the general properties of G×E, and those of its underlying QTLs. Here, we use the genotypes of 1005 segregants from a cross between two Saccharomyces cerevisiae strains, and the growth rates of these segregants in 47 environments, to identify growth rate QTLs (gQTLs) in each environment, and QTLs that have different growth effects in each pair of environments (g×eQTLs) . The average number of g×eQTLs identified between two environments is 0.58 times the number of unique gQTLs identified in these environments, revealing a high abundance of G×E. Eighty-seven percent of g×eQTLs belong to gQTLs, supporting the practice of identifying g×eQTLs from gQTLs. Most g×eQTLs identified from gQTLs have concordant effects between environments, but, as the effect size of a mutation in one environment enlarges, the probability of antagonism in the other environment increases. Antagonistic g×eQTLs are enriched in dissimilar environments. Relative to gQTLs, g×eQTLs tend to occur at intronic and synonymous sites. The gene ontology (GO) distributions of gQTLs and g×eQTLs are significantly different, as are those of antagonistic and concordant g×eQTLs. Simulations based on the yeast data showed that ignoring G×E causes substantial missing heritability. Together, our findings reveal the genomic architecture of G×E in yeast growth, and demonstrate the importance of G×E in explaining phenotypic variation and missing heritability.

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.

The Modular Adaptive Ribosome

The ribosome is an ancient machine, performing the same function across organisms. Although functionally unitary, recent experiments suggest specialized roles for some ribosomal proteins. Our central thesis is that ribosomal proteins function in a modular fashion to decode genetic information in a context dependent manner. We show through large data analyses that although many ribosomal proteins are essential with consistent effect on growth in different conditions in yeast and similar expression across cell and tissue types in mice and humans, some ribosomal proteins are used in an environment specific manner. The latter set of variable ribosomal proteins further function in a coordinated manner forming modules, which are adapted to different environmental cues in different organisms. We show that these environment specific modules of ribosomal proteins in yeast have differential genetic interactions with other pathways and their 5’UTRs show differential signatures of selection in yeast strains, presumably to facilitate adaptation. Similarly, we show that in higher metazoans such as mice and humans, different modules of ribosomal proteins are expressed in different cell types and tissues. A clear example is nervous tissue that uses a ribosomal protein module distinct from the rest of the tissues in both mice and humans. Our results suggest a novel stratification of ribosomal proteins that could have played a role in adaptation, presumably to optimize translation for adaptation to diverse ecological niches and tissue microenvironments.

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.

Comprehensive Analysis of the SUL1 Promoter of Saccharomyces cerevisiae

In the yeast Saccharomyces cerevisiae, beneficial mutations selected during sulfate-limited growth are typically amplifications of the SUL1 gene, which encodes the high-affinity sulfate transporter, resulting in fitness increases of >35% . Cis-regulatory mutations have not been observed at this locus; however, it is not clear whether this absence is due to a low mutation rate such that these mutations do not arise, or they arise but have limited fitness effects relative to those of amplification. To address this question directly, we assayed the fitness effects of nearly all possible point mutations in a 493-base segment of the gene's promoter through mutagenesis and selection. While most mutations were either neutral or detrimental during sulfate-limited growth, eight mutations increased fitness >5% and as much as 9.4%. Combinations of these beneficial mutations increased fitness only up to 11%. Thus, in the case of SUL1, promoter mutations could not induce a fitness increase similar to that of gene amplification. Using these data, we identified functionally important regions of the SUL1 promoter and analyzed three sites that correspond to potential binding sites for the transcription factors Met32 and Cbf1 Mutations that create new Met32- or Cbf1-binding sites also increased fitness. Some mutations in the untranslated region of the SUL1 transcript decreased fitness, likely due to the formation of inhibitory upstream open reading frames. Our methodology-saturation mutagenesis, chemostat selection, and DNA sequencing to track variants-should be a broadly applicable approach.

Polygenic analysis and targeted improvement of the complex trait of high acetic acid tolerance in the yeast Saccharomyces cerevisiae

BACKGROUND

Acetic acid is one of the major inhibitors in lignocellulose hydrolysates used for the production of second-generation bioethanol. Although several genes have been identified in laboratory yeast strains that are required for tolerance to acetic acid, the genetic basis of the high acetic acid tolerance naturally present in some Saccharomyces cerevisiae strains is unknown. Identification of its polygenic basis may allow improvement of acetic acid tolerance in yeast strains used for second-generation bioethanol production by precise genome editing, minimizing the risk of negatively affecting other industrially important properties of the yeast.

RESULTS

Haploid segregants of a strain with unusually high acetic acid tolerance and a reference industrial strain were used as superior and inferior parent strain, respectively. After crossing of the parent strains, QTL mapping using the SNP variant frequency determined by pooled-segregant whole-genome sequence analysis revealed two major QTLs. All F1 segregants were then submitted to multiple rounds of random inbreeding and the superior F7 segregants were submitted to the same analysis, further refined by sequencing of individual segregants and bioinformatics analysis taking into account the relative acetic acid tolerance of the segregants. This resulted in disappearance in the QTL mapping with the F7 segregants of a major F1 QTL, in which we identified HAA1, a known regulator of high acetic acid tolerance, as a true causative allele. Novel genes determining high acetic acid tolerance, GLO1, DOT5, CUP2, and a previously identified component, VMA7, were identified as causative alleles in the second major F1 QTL and in three newly appearing F7 QTLs, respectively. The superior HAA1 allele contained a unique single point mutation that significantly improved acetic acid tolerance under industrially relevant conditions when inserted into an industrial yeast strain for second-generation bioethanol production.

CONCLUSIONS

This work reveals the polygenic basis of high acetic acid tolerance in S. cerevisiae in unprecedented detail. It also shows for the first time that a single strain can harbor different sets of causative genes able to establish the same polygenic trait. The superior alleles identified can be used successfully for improvement of acetic acid tolerance in industrial yeast strains.

The complex genetic and molecular basis of a model quantitative trait

Sixty‐four genomic loci and seven genes that contribute to heritable variation in a model quantitative trait—resistance to oxidative stress—are identified across three yeast strains. The high‐resolution understanding of this phenotype provides new insight into the genetic and molecular basis of quantitative traits.

Quantitative traits are often influenced by many loci with small effects. Identifying most of these loci and resolving them to specific genes or genetic variants is challenging. Yet, achieving such a detailed understanding of quantitative traits is important, as it can improve our knowledge of the genetic and molecular basis of heritable phenotypic variation. In this study, we use a genetic mapping strategy that involves recurrent backcrossing with phenotypic selection to obtain new insights into an ecologically, industrially, and medically relevant quantitative trait—tolerance of oxidative stress, as measured based on resistance to hydrogen peroxide. We examine the genetic basis of hydrogen peroxide resistance in three related yeast crosses and detect 64 distinct genomic loci that likely influence the trait. By precisely resolving or cloning a number of these loci, we demonstrate that a broad spectrum of cellular processes contribute to hydrogen peroxide resistance, including DNA repair, scavenging of reactive oxygen species, stress-induced MAPK signaling, translation, and water transport. Consistent with the complex genetic and molecular basis of hydrogen peroxide resistance, we show two examples where multiple distinct causal genetic variants underlie what appears to be a single locus. Our results improve understanding of the genetic and molecular basis of a highly complex, model quantitative trait.

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.

The genomics of microbial domestication in the fermented food environment

Shortly after the agricultural revolution, the domestication of bacteria, yeasts, and molds, played an essential role in enhancing the stability, quality, flavor, and texture of food products. These domestication events were probably the result of human food production practices that entailed the continual recycling of isolated microbial communities in the presence of abundant agricultural food sources. We suggest that within these novel agrarian food niches the metabolic requirements of those microbes became regular and predictable resulting in rapid genomic specialization through such mechanisms as pseudogenization, genome decay, interspecific hybridization, gene duplication, and horizontal gene transfer. The ultimate result was domesticated strains of microorganisms with enhanced fermentative capacities.

Negative feedback buffers effects of regulatory variants

Mechanisms conferring robustness against regulatory variants have been controversial. Previous studies suggested widespread buffering of RNA misexpression on protein levels during translation. We do not find evidence that translational buffering is common. Instead, we find extensive buffering at the level of RNA expression, exerted through negative feedback regulation acting in trans, which reduces the effect of regulatory variants on gene expression. Our approach is based on a novel experimental design in which allelic differential expression in a yeast hybrid strain is compared to allelic differential expression in a pool of its spores. Allelic differential expression in the hybrid is due to cis-regulatory differences only. Instead, in the pool of spores allelic differential expression is not only due to cis-regulatory differences but also due to local trans effects that include negative feedback. We found that buffering through such local trans regulation is widespread, typically compensating for about 15% of cis-regulatory effects on individual genes. Negative feedback is stronger not only for essential genes, indicating its functional relevance, but also for genes with low to middle levels of expression, for which tight regulation matters most. We suggest that negative feedback is one mechanism of Waddington's canalization, facilitating the accumulation of genetic variants that might give selective advantage in different environments.

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.

Allelic variation, aneuploidy, and nongenetic mechanisms suppress a monogenic trait in yeast

Clinically relevant features of monogenic diseases, including severity of symptoms and age of onset, can vary widely in response to environmental differences as well as to the presence of genetic modifiers affecting the trait's penetrance and expressivity. While a better understanding of modifier loci could lead to treatments for Mendelian diseases, the rarity of individuals harboring both a disease-causing allele and a modifying genotype hinders their study in human populations. We examined the genetic architecture of monogenic trait modifiers using a well-characterized yeast model of the human Mendelian disease classic galactosemia. Yeast strains with loss-of-function mutations in the yeast ortholog (GAL7) of the human disease gene (GALT) fail to grow in the presence of even small amounts of galactose due to accumulation of the same toxic intermediates that poison human cells. To isolate and individually genotype large numbers of the very rare (∼0.1%) galactose-tolerant recombinant progeny from a cross between two gal7Δ parents, we developed a new method, called "FACS-QTL." FACS-QTL improves upon the currently used approaches of bulk segregant analysis and extreme QTL mapping by requiring less genome engineering and strain manipulation as well as maintaining individual genotype information. Our results identified multiple distinct solutions by which the monogenic trait could be suppressed, including genetic and nongenetic mechanisms as well as frequent aneuploidy. Taken together, our results imply that the modifiers of monogenic traits are likely to be genetically complex and heterogeneous.

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.