Computational Models for Prediction of Yeast Strain Potential for Winemaking from Phenotypic Profiles

Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain''s potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40°C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain''s technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection procedures.     

Prediction of yeast protein-protein interaction network: insights from the Gene Ontology and annotations

A map of protein–protein interactions provides valuable insight into the cellular function and machinery of a proteome. By measuring the similarity between two Gene Ontology (GO) terms with a relative specificity semantic relation, here, we proposed a new method of reconstructing a yeast protein–protein interaction map that is solely based on the GO annotations. The method was validated using high-quality interaction datasets for its effectiveness. Based on a Z-score analysis, a positive dataset and a negative dataset for protein–protein interactions were derived. Moreover, a gold standard positive (GSP) dataset with the highest level of confidence that covered 78% of the high-quality interaction dataset and a gold standard negative (GSN) dataset with the lowest level of confidence were derived. In addition, we assessed four high-throughput experimental interaction datasets using the positives and the negatives as well as GSPs and GSNs. Our predicted network reconstructed from GSPs consists of 40753 interactions among 2259 proteins, and forms 16 connected components. We mapped all of the MIPS complexes except for homodimers onto the predicted network. As a result, ~35% of complexes were identified interconnected. For seven complexes, we also identified some nonmember proteins that may be functionally related to the complexes concerned. This analysis is expected to provide a new approach for predicting the protein–protein interaction maps from other completely sequenced genomes with high-quality GO-based annotations.     

Genetic Control of Cell Growth and Development in the YeastSaccharomyces cerevisiae: I. Phenotypic Selection of Mutants among Strains of the Peterhof Genetic Collection

Results of identifying phenotypes intrinsic to mutations of genes that regulate the activity of the signal transduction pathway of RAS-cyclic adenosinemonophosphate in six strains belonging to the Peterhof genetic collection of the yeast Saccharomyces cerevisiaeare presented: an increase or decrease in the amount of the accumulated glycogen, resistance or sensitivity to heat shock and nitrogen starvation, and the growth and viability in media containing unfermentable carbon sources (potassium acetate, ethanol, and glycerol) at temperatures 30 and 70°C. Collectively these phenotypic characteristics in five examined yeast strains can be interpreted as indicating disturbances in the activity of the RAS/cAMP pathway. However, the discrepancies revealed between cellular phenotypes in these strains and in the strains with a decreased or increased activity of the RAS/cAMP pathway did not allow them to be assigned to a particular functional activity group. The inconsistencies between phenotypes detected in this study may be prerequisites for the identification of new genes responsible for this signal transduction pathway or new mutations in the known genes that determine other phenotypic combinations.     

Integrating comprehensive functional annotations to boost power and accuracy in gene-based association analysis

Gene-based association tests aggregate genotypes across multiple variants for each gene, providing an interpretable gene-level analysis framework for genome-wide association studies (GWAS). Early gene-based test applications often focused on rare coding variants; a more recent wave of gene-based methods, e.g. TWAS, use eQTLs to interrogate regulatory associations. Regulatory variants are expected to be particularly valuable for gene-based analysis, since most GWAS associations to date are non-coding. However, identifying causal genes from regulatory associations remains challenging and contentious. Here, we present a statistical framework and computational tool to integrate heterogeneous annotations with GWAS summary statistics for gene-based analysis, applied with comprehensive coding and tissue-specific regulatory annotations. We compare power and accuracy identifying causal genes across single-annotation, omnibus, and annotation-agnostic gene-based tests in simulation studies and an analysis of 128 traits from the UK Biobank, and find that incorporating heterogeneous annotations in gene-based association analysis increases power and performance identifying causal genes.     

The uses of genome-wide yeast mutant collections

We assess five years of usage of the major genome-wide collections of mutants from Saccharomyces cerevisiae: single deletion mutants, double mutants conferring 'synthetic' lethality and the 'TRIPLES' collection of mutants obtained by random transposon insertion. Over 100 experimental conditions have been tested and more than 5,000 novel phenotypic traits have been assigned to yeast genes using these collections.     

Genetic complexity and quantitative trait loci mapping of yeast morphological traits

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes.     

The SIT4 protein phosphatase functions in late G1 for progression into S phase.

Saccharomyces cerevisiae strains containing temperature-sensitive mutations in the SIT4 protein phosphatase arrest in late G1 at the nonpermissive temperature. Order-of-function analysis shows that SIT4 is required in late G1 for progression into S phase. While the levels of SIT4 do not change in the cell cycle, SIT4 associates with two high-molecular-weight phosphoproteins in a cell-cycle-dependent fashion. In addition, we have identified a polymorphic gene, SSD1, that in some versions can suppress the lethality due to a deletion of SIT4 and can also partially suppress the phenotypic defects due to a null mutation in BCY1. The SSD1 protein is implicated in G1 control and has a region of similarity to the dis3 protein of Schizosaccharomyces pombe. We have also identified a gene, PPH2alpha, that in high copy number can partially suppress the growth defect of sit4 strains. The PPH2 alpha gene encodes a predicted protein that is 80% identical to the catalytic domain of mammalian type 2A protein phosphatases but also has an acidic amino-terminal extension not present in other phosphatases.     

Acetaldehyde addition throughout the growth phase alleviates the phenotypic effect of zinc deficiency in Saccharomyces cerevisiae

During experiments to determine the effects of exogenously added acetaldehyde on pure cultures of various yeast strains, we discovered that an early acetaldehyde perfusion during the growth phase allowed several yeasts to partially overcome the phenotypic effects of zinc depletion during alcoholic fermentation. We, therefore, performed genome-wide expression and proteomic analysis on an industrial Saccharomyces cerevisiae yeast strain (VL1) growing in zinc-replete or zinc-depleted conditions in the presence of perfused acetaldehyde to identify molecular markers of this effect. Zinc depletion severely affects ethanol production and therefore nicotinamide adenine dinucleotide (NAD) regeneration, although we observed partial compensation by the upregulation of the poorly efficient Fe-dependent Adh4p in our conditions. A coordinate metabolic response was indeed observed in response to the early acetaldehyde perfusion, and particularly of the lower part of glycolysis, leading to the cellular replenishment of NAD cofactor. These various findings suggest that acetaldehyde exchange between strains may inhibit the growth of some yeast strains while encouraging the growth of others. This phenomenon could be particularly important for understanding the ecology of colonization of complex fermentation media by S. cerevisiae after elimination of non-Saccharomyces yeasts.     

MKK1 and MKK2, which encode Saccharomyces cerevisiae mitogen-activated protein kinase-kinase homologs, function in the pathway mediated by protein kinase C.

The PKC1 gene of Saccharomyces cerevisiae encodes a homolog of mammalian protein kinase C that is required for normal growth and division of yeast cells. We report here the isolation of the yeast MKK1 and MKK2 (for mitogen-activated protein [MAP] kinase-kinase) genes which, when overexpressed, suppress the cell lysis defect of a temperature-sensitive pkc1 mutant. The MKK genes encode protein kinases most similar to the STE7 product of S. cerevisiae, the byr1 product of Schizosaccharomyces pombe, and vertebrate MAP kinase-kinases. Deletion of either MKK gene alone did not cause any apparent phenotypic defects, but deletion of both MKK1 and MKK2 resulted in a temperature-sensitive cell lysis defect that was suppressed by osmotic stabilizers. This phenotypic defect is similar to that associated with deletion of the BCK1 gene, which is thought to function in the pathway mediated by PCK1. The BCK1 gene also encodes a predicted protein kinase. Overexpression of MKK1 suppressed the growth defect caused by deletion of BCK1, whereas an activated allele of BCK1 (BCK1-20) did not suppress the defect of the mkk1 mkk2 double disruption. Furthermore, overexpression of MPK1, which encodes a protein kinase closely related to vertebrate MAP kinases, suppressed the defect of the mkk1 mkk2 double mutant. These results suggest that MKK1 and MKK2 function in a signal transduction pathway involving the protein kinases encoded by PKC1, BCK1, and MPK1. Genetic epistasis experiments indicated that the site of action for MKK1 and MKK2 is between BCK1 and MPK1.     

Genetic control of growth and development of yeast Saccharomyces cerevisiae cells. Phenotypic selection of mutants among strains of the Peterhof genetic collection

Results of identifying phenotypes intrinsic to mutations of genes that regulate the activity of the signal transduction pathway of RAS-cyclic adenosinemonophosphate in six strains belonging to the Peterhof genetic collection of the yeast Saccharomyces cerevisiae are presented: an increase or decrease in the amount of the accumulated glycogen, resistance or sensitivity to heat shock and nitrogen starvation, and the growth and viability in media containing unfermentable carbon sources (potassium acetate, ethanol, and glycerol) at temperatures 30 and 70 degrees C. Collectively these phenotypic characteristics in five examined yeast strains can be interpreted as indicating disturbances in the activity of the RAS/cAMP pathway. However, the discrepancies revealed between cellular phenotypes in these strains and in the strains with a decreased or increased activity of the RAS/cAMP pathway did not allow them to be assigned to a particular functional activity group. The inconsistencies between phenotypes detected in this study may be prerequisites for the identification of new genes responsible for this signal transduction pathway or new mutations in the known genes that determine other phenotypic combinations.     

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

Background

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

Results

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

Conclusion

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

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-932) contains supplementary material, which is available to authorized users.     

Masking and purging mutations following EMS treatment in haploid, diploid and tetraploid yeast (Saccharomyces cerevisiae)

The yeast, Saccharomyces cerevisiae, was used as a model to investigate theories of ploidy evolution. Mutagenesis experiments using the alkylating agent EMS (ethane methyl sulphonate) were conducted to assess the relative importance that masking of deleterious mutations has on response to and recovery from DNA damage. In particular, we tested whether cells with higher ploidy levels have relatively higher fitnesses after mutagenesis, whether the advantages of masking are more pronounced in tetraploids than in diploids, and whether purging of mutations allows more rapid recovery of haploid cells than cells with higher ploidy levels. Separate experiments were performed on asexually propagating stationary phase cells using (1) prototrophic haploid (MAT alpha) and diploid (MATa/alpha) strains and (2) isogenic haploid, diploid and tetraploid strains lacking a functional mating type locus. In both sets of experiments, haploids showed a more pronounced decrease in apparent growth rate than diploids, but both haploids and diploids appeared to recover very rapidly. Tetraploids did not show increased benefits of masking compared with diploids but volume measurements and FACScan analyses on the auxotrophic strains indicated that all treated tetraploid strains decreased in ploidy level and that some of the treated haploid lines increased in ploidy level. Results from these experiments confirm that while masking deleterious mutations provides an immediate advantage to higher ploidy levels in the presence of mutagens, selection is extremely efficient at removing induced mutations, leading growth rates to increase rapidly over time at all ploidy levels. Furthermore, ploidy level is itself a mutable trait in the presence of EMS, with both haploids and tetraploids often evolving towards diploidy (the ancestral state of S. cerevisiae) during the course of the experiment.     

Genetic dissection of ethanol tolerance in the budding yeast Saccharomyces cerevisiae

Uncovering genetic control of variation in ethanol tolerance in natural populations of yeast Saccharomyces cerevisiae is essential for understanding the evolution of fermentation, the dominant lifestyle of the species, and for improving efficiency of selection for strains with high ethanol tolerance, a character of great economic value for the brewing and biofuel industries. To date, as many as 251 genes have been predicted to be involved in influencing this character. Candidacy of these genes was determined from a tested phenotypic effect following gene knockout, from an induced change in gene function under an ethanol stress condition, or by mutagenesis. This article represents the first genomics approach for dissecting genetic variation in ethanol tolerance between two yeast strains with a highly divergent trait phenotype. We developed a simple but reliable experimental protocol for scoring the phenotype and a set of STR/SNP markers evenly covering the whole genome. We created a mapping population comprising 319 segregants from crossing the parental strains. On the basis of the data sets, we find that the tolerance trait has a high heritability and that additive genetic variance dominates genetic variation of the trait. Segregation at five QTL detected has explained approximately 50% of phenotypic variation; in particular, the major QTL mapped on yeast chromosome 9 has accounted for a quarter of the phenotypic variation. We integrated the QTL analysis with the predicted candidacy of ethanol resistance genes and found that only a few of these candidates fall in the QTL regions.     

Mutability of demographic noise in microbial range expansions

Demographic noise, the change in the composition of a population due to random birth and death events, is an important driving force in evolution because it reduces the efficacy of natural selection. Demographic noise is typically thought to be set by the population size and the environment, but recent experiments with microbial range expansions have revealed substantial strain-level differences in demographic noise under the same growth conditions. Many genetic and phenotypic differences exist between strains; to what extent do single mutations change the strength of demographic noise? To investigate this question, we developed a high-throughput method for measuring demographic noise in colonies without the need for genetic manipulation. By applying this method to 191 randomly-selected single gene deletion strains from the E. coli Keio collection, we find that a typical single gene deletion mutation decreases demographic noise by 8% (maximal decrease: 81%). We find that the strength of demographic noise is an emergent trait at the population level that can be predicted by colony-level traits but not cell-level traits. The observed differences in demographic noise from single gene deletions can increase the establishment probability of beneficial mutations by almost an order of magnitude (compared to in the wild type). Our results show that single mutations can substantially alter adaptation through their effects on demographic noise and suggest that demographic noise can be an evolvable trait of a population.Subject terms: Bacterial evolution, Population genetics, Population dynamics, Population genetics, Biofilms     

Need-Based Up-Regulation of Protein Levels in Response to Deletion of Their Duplicate Genes

Many duplicate genes maintain functional overlap despite divergence over long evolutionary time scales. Deleting one member of a paralogous pair often has no phenotypic effect, unless its paralog is also deleted. It has been suggested that this functional compensation might be mediated by active up-regulation of expression of a gene in response to deletion of its paralog. However, it is not clear how prevalent such paralog responsiveness is, nor whether it is hardwired or dependent on feedback from environmental conditions. Here, we address these questions at the genomic scale using high-throughput flow cytometry of single-cell protein levels in differentially labeled cocultures of wild-type and paralog-knockout Saccharomyces cerevisiae strains. We find that only a modest fraction of proteins (22 out of 202) show significant up-regulation to deletion of their duplicate genes. However, these paralog-responsive proteins match almost exclusively duplicate pairs whose overlapping function is required for growth. Moreover, media conditions that add or remove requirements for the function of a duplicate gene pair specifically eliminate or create paralog responsiveness. Together, our results suggest that paralog responsiveness in yeast is need-based: it appears only in conditions in which the gene function is required. Physiologically, such need-based responsiveness could provide an adaptive mechanism for compensation of genetic, environmental, or stochastic perturbations in protein abundance.     

Total ancestry measure: quantifying the similarity in tree-like classification, with genomic applications

MOTIVATION: Many classifications of protein function such as Gene Ontology (GO) are organized in directed acyclic graph (DAG) structures. In these classifications, the proteins are terminal leaf nodes; the categories 'above' them are functional annotations at various levels of specialization and the computation of a numerical measure of relatedness between two arbitrary proteins is an important proteomics problem. Moreover, analogous problems are important in other contexts in large-scale information organization--e.g. the Wikipedia online encyclopedia and the Yahoo and DMOZ web page classification schemes. RESULTS: Here we develop a simple probabilistic approach for computing this relatedness quantity, which we call the total ancestry method. Our measure is based on counting the number of leaf nodes that share exactly the same set of 'higher up' category nodes in comparison to the total number of classified pairs (i.e. the chance for the same total ancestry). We show such a measure is associated with a power-law distribution, allowing for the quick assessment of the statistical significance of shared functional annotations. We formally compare it with other quantitative functional similarity measures (such as, shortest path within a DAG, lowest common ancestor shared and Azuaje's information-theoretic similarity) and provide concrete metrics to assess differences. Finally, we provide a practical implementation for our total ancestry measure for GO and the MIPS functional catalog and give two applications of it in specific functional genomics contexts. AVAILABILITY: The implementations and results are available through our supplementary website at: http://gersteinlab.org/proj/funcsim. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Clustering of gene expression data using a local shape-based similarity measure

MOTIVATION: Microarray technology enables the study of gene expression in large scale. The application of methods for data analysis then allows for grouping genes that show a similar expression profile and that are thus likely to be co-regulated. A relationship among genes at the biological level often presents itself by locally similar and potentially time-shifted patterns in their expression profiles. RESULTS: Here, we propose a new method (CLARITY; Clustering with Local shApe-based similaRITY) for the analysis of microarray time course experiments that uses a local shape-based similarity measure based on Spearman rank correlation. This measure does not require a normalization of the expression data and is comparably robust towards noise. It is also able to detect similar and even time-shifted sub-profiles. To this end, we implemented an approach motivated by the BLAST algorithm for sequence alignment.We used CLARITY to cluster the times series of gene expression data during the mitotic cell cycle of the yeast Saccharomyces cerevisiae. The obtained clusters were related to the MIPS functional classification to assess their biological significance. We found that several clusters were significantly enriched with genes that share similar or related functions.     

Demethoxy-Q, an intermediate of coenzyme Q biosynthesis, fails to support respiration in Saccharomyces cerevisiae and lacks antioxidant activity

Caenorhabditis elegans clk-1 mutants cannot produce coenzyme Q(9) and instead accumulate demethoxy-Q(9) (DMQ(9)). DMQ(9) has been proposed to be responsible for the extended lifespan of clk-1 mutants, theoretically through its enhanced antioxidant properties and its decreased function in respiratory chain electron transport. In the present study, we assess the functional roles of DMQ(6) in the yeast Saccharomyces cerevisiae. Three mutations designed to mirror the clk-1 mutations of C. elegans were introduced into COQ7, the yeast homologue of clk-1: E233K, predicted to disrupt the di-iron carboxylate site considered essential for hydroxylase activity; L237Stop, a deletion of 36 amino acid residues from the carboxyl terminus; and P175Stop, a deletion of the carboxyl-terminal half of Coq7p. Growth on glycerol, quinone content, respiratory function, and response to oxidative stress were analyzed in each of the coq7 mutant strains. Yeast strains lacking Q(6) and producing solely DMQ were respiratory deficient and unable to support (6)either NADH-cytochrome c reductase or succinate-cytochrome c reductase activities. DMQ(6) failed to protect cells against oxidative stress generated by H(2)O(2) or linolenic acid. Thus, in the yeast model system, DMQ does not support respiratory activity and fails to act as an effective antioxidant. These results suggest that the life span extension observed in the C. elegans clk-1 mutants cannot be attributed to the presence of DMQ per se.