Identification of novel causative genes determining the complex trait of high ethanol tolerance in yeast using pooled-segregant whole-genome sequence analysis

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.

Optimal trade-off between boosted tolerance and growth fitness during adaptive evolution of yeast to ethanol shocks

BACKGROUND

The selection of Saccharomyces cerevisiae strains with higher alcohol tolerance can potentially increase the industrial production of ethanol fuel. However, the design of selection protocols to obtain bioethanol yeasts with higher alcohol tolerance poses the challenge of improving industrial strains that are already robust to high ethanol levels. Furthermore, yeasts subjected to mutagenesis and selection, or laboratory evolution, often present adaptation trade-offs wherein higher stress tolerance is attained at the expense of growth and fermentation performance. Although these undesirable side effects are often associated with acute selection regimes, the utility of using harsh ethanol treatments to obtain robust ethanologenic yeasts still has not been fully investigated.

RESULTS

We conducted an adaptive laboratory evolution by challenging four populations (P1-P4) of the Brazilian bioethanol yeast, Saccharomyces cerevisiae PE-2_H4, through 68-82 cycles of 2-h ethanol shocks (19-30% v/v) and outgrowths. Colonies isolated from the final evolved populations (P1c-P4c) were subjected to whole-genome sequencing, revealing mutations in genes enriched for the cAMP/PKA and trehalose degradation pathways. Fitness analyses of the isolated clones P1c-P3c and reverse-engineered strains demonstrated that mutations were primarily selected for cell viability under ethanol stress, at the cost of decreased growth rates in cultures with or without ethanol. Under this selection regime for stress survival, the population P4 evolved a protective snowflake phenotype resulting from BUD3 disruption. Despite marked adaptation trade-offs, the combination of reverse-engineered mutations cyr1A1474T/usv1Δ conferred 5.46% higher fitness than the parental PE-2_H4 for propagation in 8% (v/v) ethanol, with only a 1.07% fitness cost in a culture medium without alcohol. The cyr1A1474T/usv1Δ strain and evolved P1c displayed robust fermentations of sugarcane molasses using cell recycling and sulfuric acid treatments, mimicking Brazilian bioethanol production.

CONCLUSIONS

Our study combined genomic, mutational, and fitness analyses to understand the genetic underpinnings of yeast evolution to ethanol shocks. Although fitness analyses revealed that most evolved mutations impose a cost for cell propagation, combination of key mutations cyr1A1474T/usv1Δ endowed yeasts with higher tolerance for growth in the presence of ethanol. Moreover, alleles selected for acute stress survival comprising the P1c genotype conferred stress tolerance and optimal performance under conditions simulating the Brazilian industrial ethanol production.

MKT1 alleles regulate stress responses through posttranscriptional modulation of Puf3 targets in budding yeast

MKT1 is a pleiotropic stress response gene identified by several quantitative trait studies with MKT189G as a causal variant, contributing to growth advantage in multiple stress environments. MKT1 has been shown to regulate HO endonuclease posttranscriptionally via the Pbp1-Pab1 complex. RNA-binding protein Puf3 modulates a set of nuclear-encoded mitochondrial transcripts whose expression was found to be affected by MKT1 alleles. This study attempts to relate the MKT1 allele-derived growth advantage with the stability of Puf3 targets during stress and elucidate the roles of Pbp1 and Puf3 in this mechanism. Our results showed that the growth advantage of the MKT189G allele in cycloheximide and H2 O2 was PBP1-dependent, whereas in 4-nitroquinoline 1-oxide, the growth advantage was dependent on both PUF3 and PBP1. We compared the messenger RNA decay kinetics of a set of Puf3 targets in multiple stress environments to understand the allele-specific regulation by MKT1. In oxidative stress, the MKT189G allele modulated the differential expression of nuclear-encoded mitochondrial genes in a PBP1- and PUF3-dependent manner. Additionally, MKT189G stabilised Puf3 targets, namely, COX17, MRS1 and RDL2, in an allele and stress-specific manner. Our results showed that COX17, MRS1 and RDL2 had a stress-specific response in stress environments, with the MKT189G allele contributing to better growth; this response was both PBP1- and PUF3-dependent. Our results indicate that the common allele, MKT189G , regulates stress responses by differentially stabilising Puf3-target mitochondrial genes, which allows for the strain's better growth in stress environments.

From Saccharomyces cerevisiae to Ethanol: Unlocking the Power of Evolutionary Engineering in Metabolic Engineering Applications

Increased human population and the rapid decline of fossil fuels resulted in a global tendency to look for alternative fuel sources. Environmental concerns about fossil fuel combustion led to a sharp move towards renewable and environmentally friendly biofuels. Ethanol has been the primary fossil fuel alternative due to its low carbon emission rates, high octane content and comparatively facile microbial production processes. In parallel to the increased use of bioethanol in various fields such as transportation, heating and power generation, improvements in ethanol production processes turned out to be a global hot topic. Ethanol is by far the leading yeast output amongst a broad spectrum of bio-based industries. Thus, as a well-known platform microorganism and native ethanol producer, baker's yeast Saccharomyces cerevisiae has been the primary subject of interest for both academic and industrial perspectives in terms of enhanced ethanol production processes. Metabolic engineering strategies have been primarily adopted for direct manipulation of genes of interest responsible in mainstreams of ethanol metabolism. To overcome limitations of rational metabolic engineering, an alternative bottom-up strategy called inverse metabolic engineering has been widely used. In this context, evolutionary engineering, also known as adaptive laboratory evolution (ALE), which is based on random mutagenesis and systematic selection, is a powerful strategy to improve bioethanol production of S. cerevisiae. In this review, we focus on key examples of metabolic and evolutionary engineering for improved first- and second-generation S. cerevisiae bioethanol production processes. We delve into the current state of the field and show that metabolic and evolutionary engineering strategies are intertwined and many metabolically engineered strains for bioethanol production can be further improved by powerful evolutionary engineering strategies. We also discuss potential future directions that involve recent advancements in directed genome evolution, including CRISPR-Cas9 technology.

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.

CRISPR/Cas9-mediated point mutations improve α-amylase secretion in Saccharomyces cerevisiae

The rapid expansion of the application of pharmaceutical proteins and industrial enzymes requires robust microbial workhorses for high protein production. The budding yeast Saccharomyces cerevisiae is an attractive cell factory due to its ability to perform eukaryotic post-translational modifications and to secrete proteins. Many strategies have been used to engineer yeast platform strains for higher protein secretion capacity. Herein, we investigated a line of strains that have previously been selected after UV random mutagenesis for improved α-amylase secretion. A total of 42 amino acid altering point mutations identified in this strain line were reintroduced into the parental strain AAC to study their individual effects on protein secretion. These point mutations included missense mutations (amino acid substitution), nonsense mutations (stop codon generation), and frameshift mutations. For comparison, single gene deletions for the corresponding target genes were also performed in this study. A total of 11 point mutations and seven gene deletions were found to effectively improve α-amylase secretion. These targets were involved in several bioprocesses, including cellular stresses, protein degradation, transportation, mRNA processing and export, DNA replication, and repair, which indicates that the improved protein secretion capacity in the evolved strains is the result of the interaction of multiple intracellular processes. Our findings will contribute to the construction of novel cell factories for recombinant protein secretion.

Use of Bulk Segregant Analysis for Determining the Genetic Basis of Azole Resistance in the Opportunistic Pathogen Aspergillus fumigatus

A sexual cycle was described in 2009 for the opportunistic fungal pathogen Aspergillus fumigatus, opening up for the first time the possibility of using techniques reliant on sexual crossing for genetic analysis. The present study was undertaken to evaluate whether the technique 'bulk segregant analysis' (BSA), which involves detection of differences between pools of progeny varying in a particular trait, could be applied in conjunction with next-generation sequencing to investigate the underlying basis of monogenic traits in A. fumigatus. Resistance to the azole antifungal itraconazole was chosen as a model, with a dedicated bioinformatic pipeline developed to allow identification of SNPs that differed between the resistant progeny pool and resistant parent compared to the sensitive progeny pool and parent. A clinical isolate exhibiting monogenic resistance to itraconazole of unknown basis was crossed to a sensitive parent and F1 progeny used in BSA. In addition, the use of backcrossing and increasing the number in progeny pools was evaluated as ways to enhance the efficiency of BSA. Use of F1 pools of 40 progeny led to the identification of 123 candidate genes with SNPs distributed over several contigs when aligned to an A1163 reference genome. Successive rounds of backcrossing enhanced the ability to identify specific genes and a genomic region, with BSA of progeny (using 40 per pool) from a third backcross identifying 46 genes with SNPs, and BSA of progeny from a sixth backcross identifying 20 genes with SNPs in a single 292 kb region of the genome. The use of an increased number of 80 progeny per pool also increased the resolution of BSA, with 29 genes demonstrating SNPs between the different sensitive and resistant groupings detected using progeny from just the second backcross with the majority of variants located on the same 292 kb region. Further bioinformatic analysis of the 292 kb region identified the presence of a cyp51A gene variant resulting in a methionine to lysine (M220K) change in the CYP51A protein, which was concluded to be the causal basis of the observed resistance to itraconazole. The future use of BSA in genetic analysis of A. fumigatus is discussed.

Fine Mapping and Functional Analysis of the Gene PcTYR, Involved in Control of Cap Color of Pleurotus cornucopiae

Oyster mushrooms have a high biological efficiency and are easy to cultivate, which is why they are produced all over the world. Cap color is an important commercial trait for oyster mushrooms. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. In this study, a 0.8-Mb major quantitative trait locus (QTL) region controlling cap color in the oyster mushroom Pleurotus cornucopiae was mapped on chromosome 7 through bulked-segregant analysis sequencing (BSA-seq) and extreme-phenotype genome-wide association studies (XP-GWAS). Candidate genes were further selected by comparative transcriptome analysis, and a tyrosinase gene (PcTYR) was identified as the highest-confidence candidate gene. Overexpression of PcTYR resulted in a significantly darker cap color, while the cap color of RNA interference (RNAi) strains for this gene was significantly lighter than that of the wild-type (WT) strains, suggesting that PcTYR plays an essential role in cap color formation. This is the first report about fine mapping and functional verification of a gene controlling cap color in oyster mushrooms. This will enhance our understanding of the genetic basis for cap color formation in oyster mushrooms and will facilitate molecular breeding for cap color. IMPORTANCE Oyster mushrooms are widely cultivated and consumed over the world for their easy cultivation and high biological efficiency (mushroom fresh weight/substrate dry weight × 100%). Fruiting bodies with dark caps are more and more popular according to consumer preferences, but dark varieties are rarely seen on the market. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. A major QTL of cap color in oyster mushroom P. cornucopiae was fine mapped by using bulked-segregant analysis (BSA) and extreme-phenotype genome-wide association study (XP-GWAS) analysis. A candidate gene PcTYR coding tyrosinase was further identified with the help of comparative transcriptome analysis. qPCR analysis and genetic transformation tests proved that PcTYR played an essential role in cap color formation. This study will contribute to revealing the genetic mechanism of cap color formation in mushrooms, thereby facilitating molecular breeding for cap color trait.

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.

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.

Massive QTL analysis identifies pleiotropic genetic determinants for stress resistance, aroma formation, and ethanol, glycerol and isobutanol production in Saccharomyces cerevisiae

BACKGROUND

The brewer's yeast Saccharomyces cerevisiae is exploited in several industrial processes, ranging from food and beverage fermentation to the production of biofuels, pharmaceuticals and complex chemicals. The large genetic and phenotypic diversity within this species offers a formidable natural resource to obtain superior strains, hybrids, and variants. However, most industrially relevant traits in S. cerevisiae strains are controlled by multiple genetic loci. Over the past years, several studies have identified some of these QTLs. However, because these studies only focus on a limited set of traits and often use different techniques and starting strains, a global view of industrially relevant QTLs is still missing.

RESULTS

Here, we combined the power of 1125 fully sequenced inbred segregants with high-throughput phenotyping methods to identify as many as 678 QTLs across 18 different traits relevant to industrial fermentation processes, including production of ethanol, glycerol, isobutanol, acetic acid, sulfur dioxide, flavor-active esters, as well as resistance to ethanol, acetic acid, sulfite and high osmolarity. We identified and confirmed several variants that are associated with multiple different traits, indicating that many QTLs are pleiotropic. Moreover, we show that both rare and common variants, as well as variants located in coding and non-coding regions all contribute to the phenotypic variation.

CONCLUSIONS

Our findings represent an important step in our understanding of the genetic underpinnings of industrially relevant yeast traits and open new routes to study complex genetics and genetic interactions as well as to engineer novel, superior industrial yeasts. Moreover, the major role of rare variants suggests that there is a plethora of different combinations of mutations that can be explored in genome editing.

Quantitative Trait Loci Controlling Agronomic and Biochemical Traits in Cannabis sativa

Understanding the genetic basis of complex traits is a fundamental goal of evolutionary genetics. Yet, the genetics controlling complex traits in many important species such as hemp (Cannabis sativa) remain poorly investigated. Because hemp’s change in legal status with the 2014 and 2018 U.S. Federal Farm Bills, interest in the genetics controlling its numerous agriculturally important traits has steadily increased. To better understand the genetics of agriculturally important traits in hemp, we developed an F₂ population by crossing two phenotypically distinct hemp cultivars (Carmagnola and USO31). Using whole-genome sequencing, we mapped quantitative trait loci (QTL) associated with variation in numerous agronomic and biochemical traits. A total of 69 loci associated with agronomic (34) and biochemical (35) trait variation were identified. We found that most QTL co-localized, suggesting that the phenotypic distinctions between Carmagnola and USO31 are largely controlled by a small number of loci. We identified TINY and olivetol synthase as candidate genes underlying co-localized QTL clusters for agronomic and biochemical traits, respectively. We functionally validated the olivetol synthase candidate by expressing the alleles in yeast. Gas chromatography-mass spectrometry assays of extracts from these yeast colonies suggest that the USO31 olivetol synthase is functionally less active and potentially explains why USO31 produces lower cannabinoids compared to Carmagnola. Overall, our results help modernize the genomic understanding of complex traits in hemp.

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.

A Major Effect Gene Controlling Development and Pathogenicity in Botrytis cinerea Identified Through Genetic Analysis of Natural Mycelial Non-pathogenic Isolates

Botrytis cinerea is a necrotrophic plant pathogenic fungus with a wide host range. Its natural populations are phenotypically and genetically very diverse. A survey of B. cinerea isolates causing gray mold in the vineyards of Castilla y León, Spain, was carried out and as a result eight non-pathogenic natural variants were identified. Phenotypically these isolates belong to two groups. The first group consists of seven isolates displaying a characteristic mycelial morphotype, which do not sporulate and is unable to produce sclerotia. The second group includes one isolate, which sporulates profusely and does not produce sclerotia. All of them are unresponsive to light. Crosses between a representative mycelial non-pathogenic isolate and a highly aggressive field isolate revealed that the phenotypic differences regarding pathogenicity, sporulation and production of sclerotia cosegregated in the progeny and are determined by a single genetic locus. By applying a bulked segregant analysis strategy based on the comparison of the two parental genomes the locus was mapped to a 110 kb region in chromosome 4. Subcloning and transformation experiments revealed that the polymorphism is an SNP affecting gene Bcin04g03490 in the reference genome of B. cinerea. Genetic complementation analysis and sequencing of the Bcin04g03490 alleles demonstrated that the mutations in the mycelial isolates are allelic and informed about the nature of the alterations causing the phenotypes observed. Integration of the allele of the pathogenic isolate into the non-pathogenic isolate fully restored the ability to infect, to sporulate and to produce sclerotia. Therefore, it is concluded that a major effect gene controlling differentiation and developmental processes as well as pathogenicity has been identified in B. cinerea. It encodes a protein with a GAL4-like Zn(II)2Cys6 binuclear cluster DNA binding domain and an acetyltransferase domain, suggesting a role in regulation of gene expression through a mechanism involving acetylation of specific substrates.

Identification of novel genes involved in neutral lipid storage by quantitative trait loci analysis of Saccharomyces cerevisiae

BACKGROUND

The accumulation of intracellular fat depots is a polygenic trait. Therefore, the extent of lipid storage in the individuals of a species covers a broad range and is determined by many genetic factors. Quantitative trait loci analysis can be used to identify those genetic differences between two strains of the same species that are responsible for the differences in a given phenotype. We used this method and complementary approaches to identify genes in the yeast Saccharomyces cerevisiae that are involved in neutral lipid storage.

RESULTS

We selected two yeast strains, the laboratory strain BY4741 and the wine yeast AWRI1631, with a more than two-fold difference in neutral lipid content. After crossing, sporulation and germination, we used fluorescence activated cell sorting to isolate a subpopulation of cells with the highest neutral lipid content from the pool of segregants. Whole genome sequencing of this subpopulation and of the unsorted pool of segregants implicated several loci that are involved in lipid accumulation. Three of the identified genes, PIG1, PHO23 and RML2, were investigated in more detail. Deletions of these genes and the exchange of the alleles between the two parental strains confirmed that the encoded proteins contribute to neutral lipid storage in S. cerevisiae and that PIG1, PHO23 and RML2 are the major causative genes. Backcrossing of one of the segregants with the parental strains for seven generations revealed additional regions in the genomes of both strains with potential causative genes for the high lipid accumulation phenotype.

CONCLUSIONS

We identified several genes that contribute to the phenotype of lipid accumulation in an allele-specific manner. Surprisingly, no allelic variations of genes with known functions in lipid metabolism were found, indicating that the level of storage lipid accumulation is determined by many cellular processes that are not directly related to lipid metabolism.

Transcriptional Regulatory Networks Involved in C3-C4 Alcohol Stress Response and Tolerance in Yeast

Alcohol toxicity significantly impacts the titer and productivity of industrially produced biofuels. To overcome this limitation, we must find and use strategies to improve stress tolerance in production strains. Previously, we developed a multiplex navigation of a global regulatory network (MINR) library that targeted 25 regulatory genes that are predicted to modify global regulation in yeast under different stress conditions. In this study, we expanded this concept to target the active sites of 47 transcriptional regulators using a saturation mutagenesis library. The 47 targeted regulators interact with more than half of all yeast genes. We then screened and selected for C3-C4 alcohol tolerance. We identified specific mutants that have resistance to isopropanol and isobutanol. Notably, the WAR1_K110N variant improved tolerance to both isopropanol and isobutanol. In addition, we investigated the mechanisms for improvement of isopropanol and isobutanol stress tolerance and found that genes related to glycolysis play a role in tolerance to isobutanol, while changes in ATP synthesis and mitochondrial respiration play a role in tolerance to both isobutanol and isopropanol. Overall, this work sheds light on basic mechanisms for isopropanol and isobutanol toxicity and demonstrates a promising strategy to improve tolerance to C3-C4 alcohols by perturbing the transcriptional regulatory network.

Yeast Cellular Stress: Impacts on Bioethanol Production

Bioethanol is the largest biotechnology product and the most dominant biofuel globally. Saccharomyces cerevisiae is the most favored microorganism employed for its industrial production. However, obtaining maximum yields from an ethanol fermentation remains a technical challenge, since cellular stresses detrimentally impact on the efficiency of yeast cell growth and metabolism. Ethanol fermentation stresses potentially include osmotic, chaotropic, oxidative, and heat stress, as well as shifts in pH. Well-developed stress responses and tolerance mechanisms make S. cerevisiae industrious, with bioprocessing techniques also being deployed at industrial scale for the optimization of fermentation parameters and the effective management of inhibition issues. Overlap exists between yeast responses to different forms of stress. This review outlines yeast fermentation stresses and known mechanisms conferring stress tolerance, with their further elucidation and improvement possessing the potential to improve fermentation efficiency.

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.

Destressing Yeast for Higher Biofuel Yields: Can Excess Chaotropicity Be Mitigated?

Biofuels have the capacity to contribute to carbon dioxide emission reduction and to energy security as oil reserves diminish and/or become concentrated in politically unstable regions. However, challenges exist in obtaining the maximum yield from industrial fermentations. One challenge arises from the nature of alcohols. These compounds are chaotropic (i.e. causes disorder in the system) which causes stress in the microbes producing the biofuel. Brewer's yeast (Saccharomyces cerevisiae) typically cannot grow at ethanol concentration much above 17% (v/v). Mitigation of these properties has the potential to increase yield. Previously, we have explored the effects of chaotropes on model enzyme systems and attempted (largely unsuccessfully) to offset these effects by kosmotropes (compounds which increase the order of the system, i.e. the "opposite" of chaotropes). Here we present some theoretical results which suggest that high molecular mass polyethylene glycols may be the most effective kosmotropic additives in terms of both efficacy and cost. The assumptions and limitations of these calculations are also presented. A deeper understanding of the effects of chaotropes on biofuel-producing microbes is likely to inform improvements in bioethanol yields and enable more rational approaches to the "neutralisation" of chaotropicity.

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.

BSA-Seq Discovery and Functional Analysis of Candidate Hessian Fly (Mayetiola destructor) Avirulence Genes

The Hessian fly (HF, Mayetiola destructor) is a plant-galling parasite of wheat (Triticum spp.). Seven percent of its genome is composed of highly diversified signal-peptide-encoding genes that are transcribed in HF larval salivary glands. These observations suggest that they encode effector proteins that are injected into wheat cells to suppress basal wheat immunity and redirect wheat development towards gall formation. Genetic mapping has determined that mutations in four of these genes are associated with HF larval survival (virulence) on plants carrying four different resistance (R) genes. Here, this line of investigation was pursued further using bulked-segregant analysis combined with whole genome resequencing (BSA-seq). Virulence to wheat R genes H6, Hdic, and H5 was examined. Mutations associated with H6 virulence had been mapped previously. Therefore, we used H6 to test the capacity of BSA-seq to map virulence using a field-derived HF population. This was the first time a non-structured HF population had been used to map HF virulence. Hdic virulence had not been mapped previously. Using a structured laboratory population, BSA-seq associated Hdic virulence with mutations in two candidate effector-encoding genes. Using a laboratory population, H5 virulence was previously positioned in a region spanning the centromere of HF autosome 2. BSA-seq resolved H5 virulence to a 1.3 Mb fragment on the same chromosome but failed to identify candidate mutations. Map-based candidate effectors were then delivered to Nicotiana plant cells via the type III secretion system of Burkholderia glumae bacteria. These experiments demonstrated that the genes associated with virulence to wheat R genes H6 and H13 are capable of suppressing plant immunity. Results are consistent with the hypothesis that effector proteins underlie the ability of HFs to survive on wheat.

Effects of a high-cultivation temperature on the physiology of three different Yarrowia lipolytica strains

Despite the increasing relevance, ranging from academic research to industrial applications, only a limited number of non-conventional, oleaginous Yarrowia lipolytica strains are characterized in detail. Therefore, we analyzed three strains in regard to their metabolic and physiological properties, especially with respect to important characteristics of a production strain. By investigating different cultivation conditions and media compositions, similarities and differences between the distinct strain backgrounds could be derived. Especially sugar alcohol production, as well as an agglomeration of cells were found to be connected with growth at high temperatures. In addition, sugar alcohol production was independent of high substrate concentrations under these conditions. To investigate the genotypic basis of particular traits, including growth characteristics and metabolite concentrations, genomic analysis were performed. We found sequence variations for one third of the annotated proteins but no obvious link to all phenotypic features.

The RNA-associated proteins MKT1 and MKT1L form alternative PBP1-containing complexes in Trypanosoma brucei

Control of gene expression in kinetoplastids such as trypanosomes depends heavily on RNA-binding proteins that influence mRNA decay and translation. We previously showed that the trypanosome protein MKT1 forms a multicomponent protein complex: MKT1 interacts with PBP1, which in turn recruits LSM12 and poly(A)-binding protein. MKT1 is recruited to mRNAs by sequence-specific RNA-binding proteins, resulting in stabilization of the bound mRNA. We here show that PBP1, LSM12, and a 117-residue protein, XAC1 (Tb927.7.2780), are present in complexes that contain either MKT1 or an MKT1-like protein, MKT1L (Tb927.10.1490). All five proteins are present predominantly in the complexes, and we found evidence for a minor subset of complexes containing both MKT1 and MKT1L. XAC1-containing complexes reproducibly contained RNA-binding proteins that were previously found associated with MKT1. Moreover, XAC1- or MKT1-containing complexes specifically recruited one of the two poly(A)-binding proteins, PABP2, and one of the six cap-binding translation initiation complexes, EIF4E6-EIF4G5. Yeast two-hybrid assay results indicated that MKT1 directly interacts with EIF4G5. MKT1-PBP1 complexes can therefore interact with mRNAs via their poly(A) tails and caps, as well as through sequence-specific RNA-binding proteins. Correspondingly, MKT1 is associated with many mRNAs, although not with those encoding ribosomal proteins. Meanwhile, MKT1L resembles MKT1 at the C terminus but additionally features an N-terminal extension with low-complexity regions. Although MKT1L depletion inhibited cell proliferation, we found no evidence that it specifically interacts with RNA-binding proteins or mRNA. We speculate that MKT1L may compete with MKT1 for PBP1 binding and thereby modulate the function of MKT1-containing complexes.

The roles and applications of chaotropes and kosmotropes in industrial fermentation processes

Chaotropicity has long been recognised as a property of some compounds. Chaotropes tend to disrupt non-covalent interactions in biological macromolecules (e.g. proteins and nucleic acids) and supramolecular assemblies (e.g. phospholipid membranes). This results in the destabilisation and unfolding of these macromolecules and assemblies. Unsurprisingly, these compounds are typically harmful to living cells since they act against multiple targets, comprising cellular integrity and function. Kosmotropes are the opposite of chaotropes and these compounds promote the ordering and rigidification of biological macromolecules and assemblies. Since many biological macromolecules have optimum levels of flexibility, kosmotropes can also inhibit their activity and can be harmful to cells. Some products of industrial fermentations, most notably alcohols, are chaotropic. This property can be a limiting factor on rates of production and yields. It has been hypothesised that the addition of kosmotropes may mitigate the chaotropicity of some fermentation products. Some microbes naturally adapt to chaotropic environments by producing kosmotropic compatible solutes. Exploitation of this in industrial fermentations has been hampered by scientific and economic issues. The cost of the kosmotropes and their removal during purification needs to be considered. We lack a complete understanding of the chemistry of chaotropicity and a robust, quantitative framework for estimating overall chaotropicities of mixtures. This makes it difficult to predict the amount of kosmotrope required to neutralise the chaotropicity. This review considers examples of industrial fermentations where chaotropicity is an issue and suggests possible mitigations.

A tps1Δ persister-like state in Saccharomyces cerevisiae is regulated by MKT1

Trehalose metabolism in yeast has been linked to a variety of phenotypes, including heat resistance, desiccation tolerance, carbon-source utilization, and sporulation. The relationships among the several phenotypes of mutants unable to synthesize trehalose are not understood, even though the pathway is highly conserved. One of these phenotypes is that tps1Δ strains cannot reportedly grow on media containing glucose or fructose, even when another carbon source they can use (e.g. galactose) is present. Here we corroborate the recent observation that a small fraction of yeast tps1Δ cells do grow on glucose, unlike the majority of the population. This is not due to a genetic alteration, but instead resembles the persister phenotype documented in many microorganisms and cancer cells undergoing lethal stress. We extend these observations to show that this phenomenon is glucose-specific, as it does not occur on another highly fermented carbon source, fructose. We further demonstrate that this phenomenon appears to be related to mitochondrial complex III function, but unrelated to inorganic phosphate levels in the cell, as had previously been suggested. Finally, we found that this phenomenon is specific to S288C-derived strains, and is the consequence of a variant in the MKT1 gene.

Repeated batches as a strategy for high 2G ethanol production from undetoxified hemicellulose hydrolysate using immobilized cells of recombinant Saccharomyces cerevisiae in a fixed-bed reactor

BACKGROUND

The search for sustainable energy sources has become a worldwide issue, making the development of efficient biofuel production processes a priority. Immobilization of second-generation (2G) xylose-fermenting Saccharomyces cerevisiae strains is a promising approach to achieve economic viability of 2G bioethanol production from undetoxified hydrolysates through operation at high cell load and mitigation of inhibitor toxicity. In addition, the use of a fixed-bed reactor can contribute to establish an efficient process because of its distinct advantages, such as high conversion rate per weight of biocatalyst and reuse of biocatalyst.

RESULTS

This work assessed the influence of alginate entrapment on the tolerance of recombinant S. cerevisiae to acetic acid. Encapsulated GSE16-T18SI.1 (T18) yeast showed an outstanding performance in repeated batch fermentations with cell recycling in YPX medium supplemented with 8 g/L acetic acid (pH 5.2), achieving 10 cycles without significant loss of productivity. In the fixed-bed bioreactor, a high xylose fermentation rate with ethanol yield and productivity values of 0.38 gethanol/gsugars and 5.7 g/L/h, respectively were achieved in fermentations using undetoxified sugarcane bagasse hemicellulose hydrolysate, with and without medium recirculation.

CONCLUSIONS

The performance of recombinant strains developed for 2G ethanol production can be boosted strongly by cell immobilization in alginate gels. Yeast encapsulation allows conducting fermentations in repeated batch mode in fixed-bed bioreactors with high xylose assimilation rate and high ethanol productivity using undetoxified hemicellulose hydrolysate.

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.

Mkt1 is required for RNAi-mediated silencing and establishment of heterochromatin in fission yeast

Constitutive domains of repressive heterochromatin are maintained within the fission yeast genome through self-reinforcing mechanisms involving histone methylation and small RNAs. Non-coding RNAs generated from heterochromatic regions are processed into small RNAs by the RNA interference pathway, and are subject to silencing through both transcriptional and post-transcriptional mechanisms. While the pathways involved in maintenance of the repressive heterochromatin state are reasonably well understood, less is known about the requirements for its establishment. Here, we describe a novel role for the post-transcriptional regulatory factor Mkt1 in establishment of heterochromatin at pericentromeres in fission yeast. Loss of Mkt1 does not affect maintenance of existing heterochromatin, but does affect its recovery following depletion, as well as de novo establishment of heterochromatin on a mini-chromosome. Pathway dissection revealed that Mkt1 is required for RNAi-mediated post-transcriptional silencing, downstream of small RNA production. Mkt1 physically associates with pericentromeric transcripts, and is additionally required for maintenance of silencing and heterochromatin at centromeres when transcriptional silencing is impaired. Our findings provide new insight into the mechanism of RNAi-mediated post-transcriptional silencing in fission yeast, and unveil an important role for post-transcriptional silencing in establishment of heterochromatin that is dispensable when full transcriptional silencing is imposed.

Trait mapping in diverse arthropods by bulked segregant analysis

Bulked segregant analysis (BSA) is a cross-based method for genetic mapping in sexually reproducing organisms. The method's use of bulked (pooled) samples markedly reduces the genotyping effort associated with traditional linkage mapping studies. Further, it can be applied to species with life histories or physical attributes (as for micro-insects) that render genetic mapping with other methods impractical. Recent studies in both insects and mites have revealed that advanced BSA experimental designs can resolve causal loci to narrow genomic intervals, facilitating follow-up investigations. As high-quality genomes become more widely available, BSA methods are poised to become an increasingly important tool for the rapid mapping of both monogenic and polygenic traits in diverse arthropod species.

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.

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.

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.

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.

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.

NaCl-saturated brines are thermodynamically moderate, rather than extreme, microbial habitats

NaCl-saturated brines such as saltern crystalliser ponds, inland salt lakes, deep-sea brines and liquids-of-deliquescence on halite are commonly regarded as a paradigm for the limit of life on Earth. There are, however, other habitats that are thermodynamically more extreme. Typically, NaCl-saturated environments contain all domains of life and perform complete biogeochemical cycling. Despite their reduced water activity, ∼0.755 at 5 M NaCl, some halophiles belonging to the Archaea and Bacteria exhibit optimum growth/metabolism in these brines. Furthermore, the recognised water-activity limit for microbial function, ∼0.585 for some strains of fungi, lies far below 0.755. Other biophysical constraints on the microbial biosphere (temperatures of >121°C; pH > 12; and high chaotropicity; e.g. ethanol at >18.9% w/v (24% v/v) and MgCl2 at >3.03 M) can prevent any cellular metabolism or ecosystem function. By contrast, NaCl-saturated environments contain biomass-dense, metabolically diverse, highly active and complex microbial ecosystems; and this underscores their moderate character. Here, we survey the evidence that NaCl-saturated brines are biologically permissive, fertile habitats that are thermodynamically mid-range rather than extreme. Indeed, were NaCl sufficiently soluble, some halophiles might grow at concentrations of up to 8 M. It may be that the finite solubility of NaCl has stabilised the genetic composition of halophile populations and limited the action of natural selection in driving halophile evolution towards greater xerophilicity. Further implications are considered for the origin(s) of life and other aspects of astrobiology.

Whole Genome Resequencing from Bulked Populations as a Rapid QTL and Gene Identification Method in Rice

Most Quantitative Trait Loci (QTL) and gene isolation approaches, such as positional- or map-based cloning, are time-consuming and low-throughput methods. Understanding and detecting the genetic material that controls a phenotype is a key means to functionally analyzing genes as well as to enhance crop agronomic traits. In this regard, high-throughput technologies have great prospects for changing the paradigms of DNA marker revealing, genotyping, and for discovering crop genetics and genomic study. Bulk segregant analysis, based on whole genome resequencing approaches, permits the rapid isolation of the genes or QTL responsible for the causative mutation of the phenotypes. MutMap, MutMap Gap, MutMap+, modified MutMap, and QTL-seq methods are among those approaches that have been confirmed to be fruitful gene mapping approaches for crop plants, such as rice, irrespective of whether the characters are determined by polygenes. As a result, in the present study we reviewed the progress made by all these methods to identify QTL or genes in rice.

Genotype-by-Environment-by-Environment Interactions in the Saccharomyces cerevisiae Transcriptomic Response to Alcohols and Anaerobiosis

Next generation biofuels including longer-chain alcohols such as butanol are attractive as renewable, high-energy fuels. A barrier to microbial production of butanols is the increased toxicity compared to ethanol; however, the cellular targets and microbial defense mechanisms remain poorly understood, especially under anaerobic conditions used frequently in industry. Here we took a comparative approach to understand the response of Saccharomyces cerevisiae to 1-butanol, isobutanol, or ethanol, across three genetic backgrounds of varying tolerance in aerobic and anaerobic conditions. We find that strains have different growth properties and alcohol tolerances with and without oxygen availability, as well as unique and common responses to each of the three alcohols. Our results provide evidence for strain-by-alcohol-by-oxygen interactions that moderate how cells respond to alcohol stress.

The Genetic Basis of Mutation Rate Variation in Yeast

Mutations are the root source of genetic variation and underlie the process of evolution. Although the rates at which mutations occur vary considerably between species, little is known about differences within species, or the genetic and molecular basis of these differences. Here, we leveraged the power of the yeast Saccharomyces cerevisiae as a model system to uncover natural genetic variants that underlie variation in mutation rate. We developed a high-throughput fluctuation assay and used it to quantify mutation rates in seven natural yeast isolates and in 1040 segregant progeny from a cross between BY, a laboratory strain, and RM, a wine strain. We observed that mutation rate varies among yeast strains and is heritable (H² = 0.49). We performed linkage mapping in the segregants and identified four quantitative trait loci underlying mutation rate variation in the cross. We fine-mapped two quantitative trait loci to the underlying causal genes, RAD5 and MKT1, that contribute to mutation rate variation. These genes also underlie sensitivity to the DNA-damaging agents 4NQO and MMS, suggesting a connection between spontaneous mutation rate and mutagen sensitivity.

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.

GPD1 and ADH3 Natural Variants Underlie Glycerol Yield Differences in Wine Fermentation

Glycerol is one of the most important by-products of alcohol fermentation, and depending on its concentration it can contribute to wine flavor intensity and aroma volatility. Here, we evaluated the potential of utilizing the natural genetic variation of non-coding regions in budding yeast to identify allelic variants that could modulate glycerol phenotype during wine fermentation. For this we utilized four Saccharomyces cerevisiae strains (WE - Wine/European, SA – Sake, NA – North American, and WA – West African), which were previously profiled for genome-wide Allele Specific Expression (ASE) levels. The glycerol yields under Synthetic Wine Must (SWM) fermentations differed significantly between strains; WA produced the highest glycerol yields while SA produced the lowest yields. Subsequently, from our ASE database, we identified two candidate genes involved in alcoholic fermentation pathways, ADH3 and GPD1, exhibiting significant expression differences between strains. A reciprocal hemizygosity assay demonstrated that hemizygotes expressing GPD1^WA, GPD1^SA, ADH3^WA and ADH3^SA alleles had significantly greater glycerol yields compared to GPD1^WE and ADH3^WE. We further analyzed the gene expression profiles for each GPD1 variant under SWM, demonstrating that the expression of GPD1^WE occurred earlier and was greater compared to the other alleles. This result indicates that the level, timing, and condition of expression differ between regulatory regions in the various genetic backgrounds. Furthermore, promoter allele swapping demonstrated that these allele expression patterns were transposable across genetic backgrounds; however, glycerol yields did not differ between wild type and modified strains, suggesting a strong trans effect on GPD1 gene expression. In this line, Gpd1 protein levels in parental strains, particularly Gpd1p^WE, did not necessarily correlate with gene expression differences, but rather with glycerol yield where low Gpd1p^WE levels were detected. This suggests that GPD1^WE is influenced by recessive negative post-transcriptional regulation which is absent in the other genetic backgrounds. This dissection of regulatory mechanisms in GPD1 allelic variants demonstrates the potential to exploit natural alleles to improve glycerol production in wine fermentation and highlights the difficulties of trait improvement due to alternative trans-regulation and gene-gene interactions in the different genetic background.

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.

Incorporating comparative genomics into the design-test-learn cycle of microbial strain engineering

Engineering microbes with new properties is an important goal in industrial engineering, to establish biological factories for production of biofuels, commodity chemicals and pharmaceutics. But engineering microbes to produce new compounds with high yield remains a major challenge toward economically viable production. Incorporating several modern approaches, including synthetic and systems biology, metabolic modeling and regulatory rewiring, has proven to significantly advance industrial strain engineering. This review highlights how comparative genomics can also facilitate strain engineering, by identifying novel genes and pathways, regulatory mechanisms and genetic background effects for engineering. We discuss how incorporating comparative genomics into the design-test-learn cycle of strain engineering can provide novel information that complements other engineering strategies.

Combining QTL-seq and linkage mapping to fine map a wild soybean allele characteristic of greater plant height

BACKGROUND

Plant height (PH) is an important agronomic trait and is closely related to yield in soybean [Glycine max (L.) Merr.]. Previous studies have identified many QTLs for PH. Due to the complex genetic background of PH in soybean, there are few reports on its fine mapping.

RESULTS

In this study, we used a mapping population derived from a cross between a chromosome segment substitution line CSSL3228 (donor N24852 (G. Soja), a receptor NN1138-2 (G. max)) and NN1138-2 to fine map a wild soybean allele of greater PH by QTL-seq and linkage mapping. We identified a QTL for PH in a 1.73 Mb region on soybean chromosome 13 through QTL-seq, which was confirmed by SSR marker-based classical QTL mapping in the mapping population. The linkage analysis showed that the QTLs of PH were located between the SSR markers BARCSOYSSR_13_1417 and BARCSOYSSR_13_1421 on chromosome 13, and the physical distance was 69.3 kb. RT-PCR and sequence analysis of possible candidate genes showed that Glyma.13 g249400 revealed significantly higher expression in higher PH genotypes, and the gene existed 6 differences in the amino acids encoding between the two parents.

CONCLUSIONS

Data presented here provide support for Glyma.13 g249400 as a possible candidate genes for higher PH in wild soybean line N24852.

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations

Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well.

Genome-wide association across Saccharomyces cerevisiae strains reveals substantial variation in underlying gene requirements for toxin tolerance

Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 Saccharomyces cerevisiae strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement.

Understanding the genetic architecture of complex traits is important for elucidating the genotype-phenotype relationship. Many studies have sought genetic variants that underlie phenotypic variation across individuals, both to implicate causal variants and to inform on architecture. Here we used genome-wide association analysis to identify genes and processes involved in tolerance of toxins found in plant-biomass hydrolysate, an important substrate for sustainable biofuel production. We found substantial variation in whether or not individual genes were important for tolerance across genetic backgrounds. Whether or not a gene was important in a given strain background explained more variation than the alleleic differences in the gene. These results suggest substantial variation in gene contributions, and perhaps underlying mechanisms, of toxin tolerance.

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.