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

Genomic approachesidentifySTT4 as a new component in glucose-induced activation of yeast plasma membrane H+-ATPase

Many studies have focused on identifying the signaling pathway by which addition of glucose triggers post-translational activation of the plasma membrane H+-ATPase in yeast. They have revealed that calcium signaling is involved in the regulatory pathway, supported for instance by the phenotype of mutants inARG82 that encodes an inositol kinase that phosphorylates inositol triphosphate (IP3). Strong glucose-induced calcium signaling, and high glucose-induced plasma membrane H+-ATPase activation have been observed in a specific yeast strain with the PJ genetic background. In this study, we have applied pooled-segregant whole genome sequencing, QTL analysis and a new bioinformatics methodology for determining SNP frequencies to identify the cause of this discrepancy and possibly new components of the signaling pathway. This has led to the identification of an STT4 allele with 6 missense mutations as a major causative allele, further supported by the observation that deletion of STT4 in the inferior parent caused a similar increase in glucose-induced plasma membrane H+-ATPase activation. However, the effect on calcium signaling was different indicating the presence of additional relevant genetic differences between the superior and reference strains. Our results suggest that phosphatidylinositol-4-phosphate might play a role in the glucose-induced activation of plasma membrane H+-ATPase by controlling intracellular calcium release through the modulation of the activity of phospholipase C.

Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes.

Polygenic Analysis of Tolerance to Carbon Dioxide Inhibition of Isoamyl Acetate "Banana" Flavor Production in Yeast Reveals MDS3 as Major Causative Gene

The introduction in modern breweries of tall cylindroconical fermentors, replacing the traditional open fermentation vats, unexpectedly revealed strong inhibition of flavor production by the high CO₂ pressure in the fermentors. We have screened our collection of Saccharomyces cerevisiae strains for strains displaying elevated tolerance to inhibition of flavor production by +0.65 bar CO₂, using a laboratory scale CO₂ pressurized fermentation system. We focused on the production of isoamyl acetate, a highly desirable flavor compound conferring fruity banana flavor in beer and other alcoholic beverages, from its precursor isoamyl alcohol (IAAc/Alc ratio). We selected the most tolerant Saccharomyces cerevisiae strain, saké yeast Kyokai no. 1, isolated a stable haploid segregant seg63 with the same high IAAc/Alc ratio under CO₂ pressure, crossed seg63 with the unrelated inferior strain ER7A and phenotyped 185 haploid segregants, of which 28 displaying a high IAAc/Alc ratio were pooled. Mapping of Quantitative Trait Loci (QTLs) by whole-genome sequence analysis based on SNP variant frequency revealed two QTLs. In the major QTL, reciprocal hemizygosity analysis identified MDS3 as the causative mutant gene, a putative member of the TOR signaling pathway. The MDS3^Seg.63 allele was dominant and contained a single causative point mutation, T2171C, resulting in the F274S substitution. Introduction of MDS3^Seg.63 in an industrial tetraploid lager yeast with CRISPR/Cas9 enhanced isoamyl acetate production by 145% under CO₂ pressure. This work shows the strong potential of polygenic analysis and targeted genetic modification for creation of cisgenic industrial brewer's yeast strains with specifically improved traits.

IMPORTANCE The upscaling of fermentation to very tall cylindroconical tanks is known to negatively impact beer flavor. Most notably, the increased CO₂ pressure in such tanks compromises production by the yeast of the desirable fruity “banana” flavor (isoamyl acetate). The cause of the CO₂ inhibition of yeast flavor production has always remained enigmatic. Our work has brought the first insight into its molecular-genetic basis and provides a specific gene tool for yeast strain improvement. We first identified a yeast strain with superior tolerance to CO₂ inhibition of flavor production, and applied polygenic analysis to identify the responsible gene. We narrowed down the causative element to a single nucleotide difference, MDS3^T2171C, and showed that it can be engineered into brewing yeast to obtain strains with superior flavor production in high CO₂ pressure conditions, apparently without affecting other traits relevant for beer brewing. Alternatively, such a strain could be obtained through marker-assisted breeding.

Genome-wide effect of non-optimal temperatures under anaerobic conditions on gene expression in Saccharomyces cerevisiae

Understanding of thermal adaptation mechanisms in yeast is crucial to develop better-adapted strains to industrial processes, providing more economical and sustainable products. We have analyzed the transcriptomic responses of three Saccharomyces cerevisiae strains, a commercial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and a commercial bioethanol strain, Ethanol Red, grown at non-optimal temperatures under anaerobic chemostat conditions. Transcriptomic analysis of the three strains revealed a huge complexity of cellular mechanisms and responses. Overall, cold exerted a stronger transcriptional response in the three strains comparing with heat conditions, with a higher number of down-regulating genes than of up-regulating genes regardless the strain analyzed. The comparison of the transcriptome at both sub- and supra-optimal temperatures showed the presence of common genes up- or down-regulated in both conditions, but also the presence of common genes up- or down-regulated in the three studied strains. More specifically, we have identified and validated three up-regulated genes at sub-optimal temperature in the three strains, OPI3, EFM6 and YOL014W. Finally, the comparison of the transcriptomic data with a previous proteomic study with the same strains revealed a good correlation between gene activity and protein abundance, mainly at low temperature. Our work provides a global insight into the specific mechanisms involved in temperature adaptation regarding both transcriptome and proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

Production of Bioethanol—A Review of Factors Affecting Ethanol Yield

Fossil fuels are a major contributor to climate change, and as the demand for energy production increases, alternative sources (e.g., renewables) are becoming more attractive. Biofuels such as bioethanol reduce reliance on fossil fuels and can be compatible with the existing fleet of internal combustion engines. Incorporation of biofuels can reduce internal combustion engine (ICE) fleet carbon dioxide emissions. Bioethanol is typically produced via microbial fermentation of fermentable sugars, such as glucose, to ethanol. Traditional feedstocks (e.g., first-generation feedstock) include cereal grains, sugar cane, and sugar beets. However, due to concerns regarding food sustainability, lignocellulosic (second-generation) and algal biomass (third-generation) feedstocks have been investigated. Ethanol yield from fermentation is dependent on a multitude of factors. This review compares bioethanol production from a range of feedstocks, and elaborates on available technologies, including fermentation practices. The importance of maintaining nutrient homeostasis of yeast is also examined. The purpose of this review is to provide industrial producers and policy makers insight into available technologies, yields of bioethanol achieved by current manufacturing practices, and goals for future innovation.

Stress modulation as a means to improve yeasts for lignocellulose bioconversion

The second-generation (2G) fermentation environment for lignocellulose conversion presents unique challenges to the fermentative organism that do not necessarily exist in other industrial fermentations. While extreme osmotic, heat, and nutrient starvation stresses are observed in sugar- and starch-based fermentation environments, additional pre-treatment-derived inhibitor stress, potentially exacerbated by stresses such as pH and product tolerance, exist in the 2G environment. Furthermore, in a consolidated bioprocessing (CBP) context, the organism is also challenged to secrete enzymes that may themselves lead to unfolded protein response and other stresses. This review will discuss responses of the yeast Saccharomyces cerevisiae to 2G-specific stresses and stress modulation strategies that can be followed to improve yeasts for this application. We also explore published -omics data and discuss relevant rational engineering, reverse engineering, and adaptation strategies, with the view of identifying genes or alleles that will make positive contributions to the overall robustness of 2G industrial strains. KEYPOINTS: • Stress tolerance is a key driver to successful application of yeast strains in biorefineries. • A wealth of data regarding stress responses has been gained through omics studies. • Integration of this knowledge could inform engineering of fit for purpose strains.

Random Transfer of Ogataea polymorpha Genes into Saccharomyces cerevisiae Reveals a Complex Background of Heat Tolerance

Horizontal gene transfer, a process through which an organism acquires genes from other organisms, is a rare evolutionary event in yeasts. Artificial random gene transfer can emerge as a valuable tool in yeast bioengineering to investigate the background of complex phenotypes, such as heat tolerance. In this study, a cDNA library was constructed from the mRNA of a methylotrophic yeast, Ogataea polymorpha, and then introduced into Saccharomyces cerevisiae. Ogataea polymorpha was selected because it is one of the most heat-tolerant species among yeasts. Screening of S. cerevisiae populations expressing O. polymorpha genes at high temperatures identified 59 O. polymorpha genes that contribute to heat tolerance. Gene enrichment analysis indicated that certain S. cerevisiae functions, including protein synthesis, were highly temperature-sensitive. Additionally, the results confirmed that heat tolerance in yeast is a complex phenotype dependent on multiple quantitative loci. Random gene transfer would be a useful tool for future bioengineering studies on yeasts.

Whole-Genome Transformation Promotes tRNA Anticodon Suppressor Mutations under Stress

tRNAs are encoded by a large gene family, usually with several isogenic tRNAs interacting with the same codon. Mutations in the anticodon region of other tRNAs can overcome specific tRNA deficiencies. Phylogenetic analysis suggests that such mutations have occurred in evolution, but the driving force is unclear. We show that in yeast suppressor mutations in other tRNAs are able to overcome deficiency of the essential TRT2-encoded tRNAThrCGU at high temperature (40°C). Surprisingly, these tRNA suppressor mutations were obtained after whole-genome transformation with DNA from thermotolerant Kluyveromyces marxianus or Ogataea polymorpha strains but from which the mutations did apparently not originate. We suggest that transient presence of donor DNA in the host facilitates proliferation at high temperature and thus increases the chances for occurrence of spontaneous mutations suppressing defective growth at high temperature. Whole-genome sequence analysis of three transformants revealed only four to five nonsynonymous mutations of which one causing TRT2 anticodon stem stabilization and two anticodon mutations in non-threonyl-tRNAs, tRNALysCUU and tRNAeMetCAU, were causative. Both anticodon mutations suppressed lethality of TRT2 deletion and apparently caused the respective tRNAs to become novel substrates for threonyl-tRNA synthetase. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) data could not detect any significant mistranslation, and reverse transcription-quantitative PCR results contradicted induction of the unfolded protein response. We suggest that stress conditions have been a driving force in evolution for the selection of anticodon-switching mutations in tRNAs as revealed by phylogenetic analysis.IMPORTANCE In this work, we have identified for the first time the causative elements in a eukaryotic organism introduced by applying whole-genome transformation and responsible for the selectable trait of interest, i.e., high temperature tolerance. Surprisingly, the whole-genome transformants contained just a few single nucleotide polymorphisms (SNPs), which were unrelated to the sequence of the donor DNA. In each of three independent transformants, we have identified a SNP in a tRNA, either stabilizing the essential tRNAThrCGU at high temperature or switching the anticodon of tRNALysCUU or tRNAeMetCAU into CGU, which is apparently enough for in vivo recognition by threonyl-tRNA synthetase. LC-MS/MS analysis indeed indicated absence of significant mistranslation. Phylogenetic analysis showed that similar mutations have occurred throughout evolution and we suggest that stress conditions may have been a driving force for their selection. The low number of SNPs introduced by whole-genome transformation may favor its application for improvement of industrial yeast strains.

Thermo-adaptive evolution to generate improved Saccharomyces cerevisiae strains for cocoa pulp fermentations

Cocoa pulp fermentation is a consequence of the succession of indigenous yeasts, lactic acid bacteria and acetic acid bacteria that not only produce a diversity of metabolites, but also cause the production of flavour precursors. However, as such spontaneous fermentations are less reproducible and contribute to produce variability, interest in a microbial starter culture is growing that could be used to inoculate cocoa pulp fermentations. This study aimed to generate robust S. cerevisiae strains by thermo-adaptive evolution that could be used in cocoa fermentation. We evolved a cocoa strain in a sugary defined medium at high temperature to improve both fermentation and growth capacity. Moreover, adaptive evolution at high temperature (40 °C) also enabled us to unveil the molecular basis underlying the improved phenotype by analysing the whole genome sequence of the evolved strain. Adaptation to high-temperature conditions occurred at different genomic levels, and promoted aneuploidies, segmental duplication, and SNVs in the evolved strain. The lipid profile analysis of the evolved strain also evidenced changes in the membrane composition that contribute to maintain an appropriate cell membrane state at high temperature. Our work demonstrates that experimental evolution is an effective approach to generate better-adapted yeast strains at high temperature for industrial processes.

Polygenic analysis of very high acetic acid tolerance in the yeast Saccharomyces cerevisiae reveals a complex genetic background and several new causative alleles

BACKGROUND

High acetic acid tolerance is of major importance in industrial yeast strains used for second-generation bioethanol production, because of the high acetic acid content of lignocellulose hydrolysates. It is also important in first-generation starch hydrolysates and in sourdoughs containing significant acetic acid levels. We have previously identified snf4 ^E269* as a causative allele in strain MS164 obtained after whole-genome (WG) transformation and selection for improved acetic acid tolerance.

RESULTS

We have now performed polygenic analysis with the same WG transformant MS164 to identify novel causative alleles interacting with snf4 ^E269* to further enhance acetic acid tolerance, from a range of 0.8-1.2% acetic acid at pH 4.7, to previously unmatched levels for Saccharomyces cerevisiae. For that purpose, we crossed the WG transformant with strain 16D, a previously identified strain displaying very high acetic acid tolerance. Quantitative trait locus (QTL) mapping with pooled-segregant whole-genome sequence analysis identified four major and two minor QTLs. In addition to confirmation of snf4 ^E269* in QTL1, we identified six other genes linked to very high acetic acid tolerance, TRT2, MET4, IRA2 and RTG1 and a combination of MSH2 and HAL9, some of which have never been connected previously to acetic acid tolerance. Several of these genes appear to be wild-type alleles that complement defective alleles present in the other parent strain.

CONCLUSIONS

The presence of several novel causative genes highlights the distinct genetic basis and the strong genetic background dependency of very high acetic acid tolerance. Our results suggest that elimination of inferior mutant alleles might be equally important for reaching very high acetic acid tolerance as introduction of rare superior alleles. The superior alleles of MET4 and RTG1 might be useful for further improvement of acetic acid tolerance in specific industrial yeast strains.

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.

Selection and subsequent physiological characterization of industrial Saccharomyces cerevisiae strains during continuous growth at sub- and- supra optimal temperatures

A phenotypic screening of 12 industrial yeast strains and the well-studied laboratory strain CEN.PK113-7D at cultivation temperatures between 12 °C and 40 °C revealed significant differences in maximum growth rates and temperature tolerance. From those 12, two strains, one performing best at 12 °C and the other at 40 °C, plus the laboratory strain, were selected for further physiological characterization in well-controlled bioreactors. The strains were grown in anaerobic chemostats, at a fixed specific growth rate of 0.03 h-1 and sequential batch cultures at 12 °C, 30 °C, and 39 °C. We observed significant differences in biomass and ethanol yields on glucose, biomass protein and storage carbohydrate contents, and biomass yields on ATP between strains and cultivation temperatures. Increased temperature tolerance coincided with higher energetic efficiency of cell growth, indicating that temperature intolerance is a result of energy wasting processes, such as increased turnover of cellular components (e.g. proteins) due to temperature induced damage.

Unique genetic basis of the distinct antibiotic potency of high acetic acid production in the probiotic yeast Saccharomyces cerevisiae var. boulardii

The yeast Saccharomyces boulardii has been used worldwide as a popular, commercial probiotic, but the basis of its probiotic action remains obscure. It is considered conspecific with budding yeast Saccharomyces cerevisiae, which is generally used in classical food applications. They have an almost identical genome sequence, making the genetic basis of probiotic potency in S. boulardii puzzling. We now show that S. boulardii produces at 37°C unusually high levels of acetic acid, which is strongly inhibitory to bacterial growth in agar-well diffusion assays and could be vital for its unique application as a probiotic among yeasts. Using pooled-segregant whole-genome sequence analysis with S. boulardii and S. cerevisiae parent strains, we succeeded in mapping the underlying QTLs and identified mutant alleles of SDH1 and WHI2 as the causative alleles. Both genes contain a SNP unique to S. boulardii (sdh1^F317Y and whi2^S287*) and are fully responsible for its high acetic acid production. S. boulardii strains show different levels of acetic acid production, depending on the copy number of the whi2^S287* allele. Our results offer the first molecular explanation as to why S. boulardii could exert probiotic action as opposed to S. cerevisiae. They reveal for the first time the molecular-genetic basis of a probiotic action-related trait in S. boulardii and show that antibacterial potency of a probiotic microorganism can be due to strain-specific mutations within the same species. We suggest that acquisition of antibacterial activity through medium acidification offered a selective advantage to S. boulardii in its ecological niche and for its application as a probiotic.

Mitigating stress in industrial yeasts

The yeast, Saccharomyces cerevisiae, is the premier fungal cell factory exploited in industrial biotechnology. In particular, ethanol production by yeast fermentation represents the world's foremost biotechnological process, with beverage and fuel ethanol contributing significantly to many countries economic and energy sustainability. During industrial fermentation processes, yeast cells are subjected to several physical, chemical and biological stress factors that can detrimentally affect ethanol yields and overall production efficiency. These stresses include ethanol toxicity, osmostress, nutrient starvation, pH and temperature shock, as well as biotic stress due to contaminating microorganisms. Several cell physiological and genetic approaches to mitigate yeast stress during industrial fermentations can be undertaken, and such approaches will be discussed with reference to stress mitigation in yeasts employed in Brazilian bioethanol processes. This article will highlight the importance of furthering our understanding of key aspects of yeast stress physiology and the beneficial impact this can have more generally on enhancing industrial fungal bioprocesses.

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.

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.

Experimental Evolution of Yeast for High-Temperature Tolerance

Thermotolerance is a polygenic trait that contributes to cell survival and growth under unusually high temperatures. Although some genes associated with high-temperature growth (Htg+) have been identified, how cells accumulate mutations to achieve prolonged thermotolerance is still mysterious. Here, we conducted experimental evolution of a Saccharomyces cerevisiae laboratory strain with stepwise temperature increases for it to grow at 42 °C. Whole genome resequencing of 14 evolved strains and the parental strain revealed a total of 153 mutations in the evolved strains, including single nucleotide variants, small INDELs, and segmental duplication/deletion events. Some mutations persisted from an intermediate temperature to 42 °C, so they might be Htg+ mutations. Functional categorization of mutations revealed enrichment of exonic mutations in the SWI/SNF complex and F-type ATPase, pointing to their involvement in high-temperature tolerance. In addition, multiple mutations were found in a general stress-associated signal transduction network consisting of Hog1 mediated pathway, RAS-cAMP pathway, and Rho1-Pkc1 mediated cell wall integrity pathway, implying that cells can achieve Htg+ partly through modifying existing stress regulatory mechanisms. Using pooled segregant analysis of five Htg+ phenotype-orientated pools, we inferred causative mutations for growth at 42 °C and identified those mutations with stronger impacts on the phenotype. Finally, we experimentally validated a number of the candidate Htg+ mutations. This study increased our understanding of the genetic basis of yeast tolerance to high temperature.

QTL analysis reveals genomic variants linked to high-temperature fermentation performance in the industrial yeast

BACKGROUND

High-temperature fermentation is desirable for the industrial production of ethanol, which requires thermotolerant yeast strains. However, yeast thermotolerance is a complicated quantitative trait. The understanding of genetic basis behind high-temperature fermentation performance is still limited. Quantitative trait locus (QTL) mapping by pooled-segregant whole genome sequencing has been proved to be a powerful and reliable approach to identify the loci, genes and single nucleotide polymorphism (SNP) variants linked to quantitative traits of yeast.

RESULTS

One superior thermotolerant industrial strain and one inferior thermosensitive natural strain with distinct high-temperature fermentation performances were screened from 124 Saccharomyces cerevisiae strains as parent strains for crossing and segregant isolation. Based on QTL mapping by pooled-segregant whole genome sequencing as well as the subsequent reciprocal hemizygosity analysis (RHA) and allele replacement analysis, we identified and validated total eight causative genes in four QTLs that linked to high-temperature fermentation of yeast. Interestingly, loss of heterozygosity in five of the eight causative genes including RXT2, ECM24, CSC1, IRA2 and AVO1 exhibited positive effects on high-temperature fermentation. Principal component analysis (PCA) of high-temperature fermentation data from all the RHA and allele replacement strains of those eight genes distinguished three superior parent alleles including VPS34, VID24 and DAP1 to be greatly beneficial to high-temperature fermentation in contrast to their inferior parent alleles. Strikingly, physiological impacts of the superior parent alleles of VPS34, VID24 and DAP1 converged on cell membrane by increasing trehalose accumulation or reducing membrane fluidity.

CONCLUSIONS

This work revealed eight novel causative genes and SNP variants closely associated with high-temperature fermentation performance. Among these genes, VPS34 and DAP1 would be good targets for improving high-temperature fermentation of the industrial yeast. It also showed that loss of heterozygosity of causative genes could contribute to the improvement of high-temperature fermentation capacities. Our findings would provide guides to develop more robust and thermotolerant strains for the industrial production of ethanol.

Genetic Basis of Variation in Heat and Ethanol Tolerance in Saccharomyces cerevisiae

Saccharomyces cerevisiae has the capability of fermenting sugar to produce concentrations of ethanol that are toxic to most organisms. Other Saccharomyces species also have a strong fermentative capacity, but some are specialized to low temperatures, whereas S. cerevisiae is the most thermotolerant. Although S. cerevisiae has been extensively used to study the genetic basis of ethanol tolerance, much less is known about temperature dependent ethanol tolerance. In this study, we examined the genetic basis of ethanol tolerance at high temperature among strains of S. cerevisiae. We identified two amino acid polymorphisms in SEC24 that cause strong sensitivity to ethanol at high temperature and more limited sensitivity to temperature in the absence of ethanol. We also identified a single amino acid polymorphism in PSD1 that causes sensitivity to high temperature in a strain dependent fashion. The genes we identified provide further insight into genetic variation in ethanol and temperature tolerance and the interdependent nature of these two traits in S. cerevisiae.

Estimation of QTL heritability based on pooled sequencing data

Motivation

Bulked segregant analysis combined with next generation sequencing has proven to be a simple and efficient approach for fast mapping of quantitative trait loci (QTLs). However, how to estimate the proportion of phenotypic variance explained by a QTL (or termed QTL heritability) in such pooled QTL mapping is an unsolved problem.

Results

In this paper, we propose a method called PQHE to estimate QTL heritability using pooled sequencing data obtained under different experimental designs. Simulation studies indicated that our method is correct and feasible. Four practical examples from rice and yeast are demonstrated, each representing a different situation.

Availability and implementation

The R scripts of our method are open source under GPLv3 license at http://genetics.fafu.edu.cn/PQHE or https://github.com/biotangweiqi/PQHE. The R scripts require the R package rootSolve.

Contact

wuwr@fafu.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Enhancing Yeast Alcoholic Fermentations

The production of ethanol by yeast fermentation represents the largest of all global biotechnologies. Consequently, the yeast Saccharomyces cerevisiae is the world's premier industrial microorganism, which is responsible not only for the production of alcoholic beverages, including beer, wine, and distilled spirits, but also for the billions of liters of bioethanol produced annually for use as a renewable transportation fuel. Although humankind has exploited the fermentative activities of yeasts for millennia, many aspects of alcohol fermentation remain poorly understood. This chapter will review some of the key considerations in optimizing industrial alcohol fermentations with a particular emphasis on enhancement opportunities involving cell physiology and strain engineering of the major microbial ethanologen, the yeast S. cerevisiae.

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.

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.

Engineering tolerance to industrially relevant stress factors in yeast cell factories

The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way.

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.

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.

Dynamics in the Strawberry Rhizosphere Microbiome in Response to Biochar and Botrytis cinerea Leaf Infection

Adding biochar, the solid coproduct of biofuel production, to peat can enhance strawberry growth, and disease resistance against the airborne fungal pathogen Botrytis cinerea. Additionally, biochar can induce shifts in the strawberry rhizosphere microbiome. However, the moment that this biochar-mediated shift occurs in the rhizosphere is not known. Further, the effect of an above-ground infection on the strawberry rhizosphere microbiome is unknown. In the present study we established two experiments in which strawberry transplants (cv. Elsanta) were planted either in peat or in peat amended with 3% biochar. First, we established a time course experiment to measure the effect of biochar on the rhizosphere bacterial and fungal communities over time. In a second experiment, we inoculated the strawberry leaves with B. cinerea, and studied the impact of the infection on the rhizosphere bacterial community. The fungal rhizosphere community was stabilized after 1 week, except for the upcoming Auriculariales, whereas the bacterial community shifted till 6 weeks. An effect of the addition of biochar to the peat on the rhizosphere microbiome was solely measured for the bacterial community from week 6 of plant growth onwards. When scoring the plant development, biochar addition was associated with enhanced root formation, fruit production, and postharvest resistance of the fruits against B. cinerea. We hypothesize that the bacterial rhizosphere microbiome, but also biochar-mediated changes in chemical substrate composition could be involved in these events. Infection of the strawberry leaves with B. cinerea induced shifts in the bacterial rhizosphere community, with an increased bacterial richness. This disease-induced effect was not observed in the rhizospheres of the B. cinerea-infected plants grown in the biochar-amended peat. The results show that an above-ground infection has its effect on the strawberry rhizosphere microbiome, changing the bacterial interactions in the root-substrate interface. This infection effect on the bacterial rhizosphere microbiome seems to be comparable to, but less pronounced than the effect of biochar-addition to the peat. The biological meaning of these observations needs further research, but this study indicates that biochar and an above-ground pathogen attack help the plant to recruit rhizosphere microbes that may aid them in their plant growth and health.

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.

Seasonal habitat suitability modeling and factors affecting the distribution of Asian Houbara in East Iran

In this study, maximum entropy models were developed in four seasons to evaluate habitat suitability and factors affecting Asian Houbara in Iran. Environmental variables used in modeling consisted of 42 environmental and climate variables for Nayband wildlife refuge and 36 environmental and climate variables for Petregan protected area. Also, seasonal overlap area were obtained using the ENM TOOLS software. The results showed that the most important factors affecting habitat suitability of the Asian Houbara in all seasons included the ratio of distance to hill, the type of Artemisia-Gymnocarpus, distance to the slope (8-12%) in the Nayband wildlife refuge, distance to the type of Artemisia aucheri, distance to the Land Passion, and distance to the dry land farming in the Petregan region. In summer, the most suitable habitat is Nayband but is Petergan during fall-winter. there is maximum overlap in summer, and the least overlap in the spring these areas. The results of this study can be used as a valuable tool in implementing conservation and management strategies, in order to increase desirable habitats in the eastern part of Iran.

Gene-Environment Interactions in Stress Response Contribute Additively to a Genotype-Environment Interaction

How combinations of gene-environment interactions collectively give rise to genotype-environment interactions is not fully understood. To shed light on this problem, we genetically dissected an environment-specific poor growth phenotype in a cross of two budding yeast strains. This phenotype is detectable when certain segregants are grown on ethanol at 37°C (‘E37’), a condition that differs from the standard culturing environment in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). Using recurrent backcrossing with phenotypic selection, we identified 16 contributing loci. To examine how these loci interact with each other and the environment, we focused on a subset of four loci that together can lead to poor growth in E37. We measured the growth of all 16 haploid combinations of alleles at these loci in all four possible combinations of carbon source (ethanol or glucose) and temperature (30 or 37°C) in a nearly isogenic population. This revealed that the four loci act in an almost entirely additive manner in E37. However, we also found that these loci have weaker effects when only carbon source or temperature is altered, suggesting that their effect magnitudes depend on the severity of environmental perturbation. Consistent with such a possibility, cloning of three causal genes identified factors that have unrelated functions in stress response. Thus, our results indicate that polymorphisms in stress response can show effects that are intensified by environmental stress, thereby resulting in major genotype-environment interactions when multiple of these variants co-occur.

Determining the genetic and molecular mechanisms that give rise to genotype-environment interaction (‘GxE’) is important for many areas of biology, including agriculture, evolution, and medicine. To help advance knowledge regarding this topic, we dissect the genetic basis of an example of GxE in which certain Saccharomyces cerevisiae cross progeny show extremely poor growth specifically on ethanol at 37°C. This environment differs from the standard condition used for culturing budding yeast in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). We provide evidence that poor growth on ethanol at 37°C is caused by a number of predominantly additive loci that individually exhibit gene-environment interactions with both carbon source and temperature. These loci show their largest effects when carbon source and temperature are simultaneously modified, indicating their effect magnitudes may be influenced by the severity of environmental stress. Consistent with this possibility, we clone three causal genes and find they encode functionally unrelated components of stress response. Our work suggests that polymorphisms in stress response can contribute additively to genotype-environment interactions that vary in intensity across conditions in a stress level-dependent manner.

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.

Reduced Glucose Sensation Can Increase the Fitness of Saccharomyces cerevisiae Lacking Mitochondrial DNA

Damage to the mitochondrial genome (mtDNA) can lead to diseases for which there are no clearly effective treatments. Since mitochondrial function and biogenesis are controlled by the nutrient environment of the cell, it is possible that perturbation of conserved, nutrient-sensing pathways may successfully treat mitochondrial disease. We found that restricting glucose or otherwise reducing the activity of the protein kinase A (PKA) pathway can lead to improved proliferation of Saccharomyces cerevisiae cells lacking mtDNA and that the transcriptional response to mtDNA loss is reduced in cells with diminished PKA activity. We have excluded many pathways and proteins from being individually responsible for the benefits provided to cells lacking mtDNA by PKA inhibition, and we found that robust import of mitochondrial polytopic membrane proteins may be required in order for cells without mtDNA to receive the full benefits of PKA reduction. Finally, we have discovered that the transcription of genes involved in arginine biosynthesis and aromatic amino acid catabolism is altered after mtDNA damage. Our results highlight the potential importance of nutrient detection and availability on the outcome of mitochondrial dysfunction.

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.

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.

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.

ATG18 and FAB1 are involved in dehydration stress tolerance in Saccharomyces cerevisiae

Recently, different dehydration-based technologies have been evaluated for the purpose of cell and tissue preservation. Although some early results have been promising, they have not satisfied the requirements for large-scale applications. The long experience of using quantitative trait loci (QTLs) with the yeast Saccharomyces cerevisiae has proven to be a good model organism for studying the link between complex phenotypes and DNA variations. Here, we use QTL analysis as a tool for identifying the specific yeast traits involved in dehydration stress tolerance. Three hybrids obtained from stable haploids and sequenced in the Saccharomyces Genome Resequencing Project showed intermediate dehydration tolerance in most cases. The dehydration resistance trait of 96 segregants from each hybrid was quantified. A smooth, continuous distribution of the anhydrobiosis tolerance trait was found, suggesting that this trait is determined by multiple QTLs. Therefore, we carried out a QTL analysis to identify the determinants of this dehydration tolerance trait at the genomic level. Among the genes identified after reciprocal hemizygosity assays, RSM22, ATG18 and DBR1 had not been referenced in previous studies. We report new phenotypes for these genes using a previously validated test. Finally, our data illustrates the power of this approach in the investigation of the complex cell dehydration phenotype.

Efficient Multiplexed Integration of Synergistic Alleles and Metabolic Pathways in Yeasts via CRISPR-Cas

CRISPR-Cas genome engineering in yeast has relied on preparation of complex expression plasmids for multiplexed gene knockouts and point mutations. Here we show that co-transformation of a single linearized plasmid with multiple PCR-generated guide RNA (gRNA) and donor DNA cassettes facilitates high-efficiency multiplexed integration of point mutations and large constructs. This technique allowed recovery of marker-less triple-engineering events with 64% efficiency without selection for expression of all gRNAs. The gRNA cassettes can be easily made by PCR and delivered in any combination. We employed this method to rapidly phenotype up to five specific allele combinations and identify synergistic effects. To prototype a pathway for the production of muconic acid, we integrated six DNA fragments totaling 24 kb across three loci in naive Saccharomyces cerevisiae in a single transformation. With minor modifications, we integrated a similar pathway in Kluyveromyces lactis. The flexibility afforded by combinatorial gRNA delivery dramatically accelerates complex strain engineering for basic research and industrial fermentation.

Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance

BACKGROUND

During the final phases of bioethanol fermentation, yeast cells face high ethanol concentrations. This stress results in slower or arrested fermentations and limits ethanol production. Novel Saccharomyces cerevisiae strains with superior ethanol tolerance may therefore allow increased yield and efficiency. Genome shuffling has emerged as a powerful approach to rapidly enhance complex traits including ethanol tolerance, yet previous efforts have mostly relied on a mutagenized pool of a single strain, which can potentially limit the effectiveness. Here, we explore novel robot-assisted strategies that allow to shuffle the genomes of multiple parental yeasts on an unprecedented scale.

RESULTS

Screening of 318 different yeasts for ethanol accumulation, sporulation efficiency, and genetic relatedness yielded eight heterothallic strains that served as parents for genome shuffling. In a first approach, the parental strains were subjected to multiple consecutive rounds of random genome shuffling with different selection methods, yielding several hybrids that showed increased ethanol tolerance. Interestingly, on average, hybrids from the first generation (F1) showed higher ethanol production than hybrids from the third generation (F3). In a second approach, we applied several successive rounds of robot-assisted targeted genome shuffling, yielding more than 3,000 targeted crosses. Hybrids selected for ethanol tolerance showed increased ethanol tolerance and production as compared to unselected hybrids, and F1 hybrids were on average superior to F3 hybrids. In total, 135 individual F1 and F3 hybrids were tested in small-scale very high gravity fermentations. Eight hybrids demonstrated superior fermentation performance over the commercial biofuel strain Ethanol Red, showing a 2 to 7% increase in maximal ethanol accumulation. In an 8-l pilot-scale test, the best-performing hybrid fermented medium containing 32% (w/v) glucose to dryness, yielding 18.7% (v/v) ethanol with a productivity of 0.90 g ethanol/l/h and a yield of 0.45 g ethanol/g glucose.

CONCLUSIONS

We report the use of several different large-scale genome shuffling strategies to obtain novel hybrids with increased ethanol tolerance and fermentation capacity. Several of the novel hybrids show best-parent heterosis and outperform the commonly used bioethanol strain Ethanol Red, making them interesting candidate strains for industrial production.

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.

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.

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.

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.

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

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

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.