Quantitative maps of genetic interactions in yeast - Comparative evaluation and integrative analysis

Background  

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms.     

Small fitness effects and weak genetic interactions between deleterious mutations in heterozygous loci of the yeast Saccharomyces cerevisiae

Rare, random mutations were induced in budding yeast by ethyl methanesulfonate (EMS). Clones known to bear a single non-neutral mutation were used to obtain mutant heterozygotes and mutant homozygotes that were later compared with wild-type homozygotes. The average homozygous effect of mutation was an approximately 2% decrease in the growth rate. In heterozygotes, the harmful effect of these relatively mild mutations was reduced approximately fivefold. In a test of epistasis, two heterozygous mutant loci were paired at random. Fitness of the double mutants was best explained by multiplicative action of effects at single loci, with little evidence for epistasis and essentially excluding synergism. In other experiments, the same mutations in haploid and heterozygous diploid clones were compared. Regardless of the haploid phenotypes, mildly deleterious or lethal, fitness of the heterozygotes was decreased by less than half a per cent on average. In general, the results presented here suggest that most mutations tend to exhibit small and weakly interacting effects in heterozygous loci regardless of how harmful they are in haploids or homozygotes.     

Exploring genetic interactions and networks with yeast

The development and application of genetic tools and resources has enabled a partial genetic-interaction network for the yeast Saccharomyces cerevisiae to be compiled. Analysis of the network, which is ongoing, has already provided a clear picture of the nature and scale of the genetic interactions that robustly sustain biological systems, and how cellular buffering is achieved at the molecular level. Recent studies in yeast have begun to define general principles of genetic networks, and also pave the way for similar studies in metazoan model systems. A comparative understanding of genetic-interaction networks promises insights into some long-standing genetic problems, such as the nature of quantitative traits and the basis of complex inherited disease.     

The genetic map of the mitochondrial genome in yeast

Summary An approach for the screening of mit^- mutants, the isolation and preliminary classification of a series of such mutants is reported. Loss and retention of 8 mit^- and 6 drug^r markers in mitDNA was analyzed in populations of rho^- clones derived from four yeast strains. The populations studied constitute a representative fraction of the rho^- petites formed during growth at 35° C under the influence of mutation tsp-25 which is in common to the four strains. The majority of the rho^- clones retained several of the markers studied. Depending on the marker regarded retention frequencies between 15% (oxi3) and 45% (oli1, cob) were observed. Loss of one and retention of the other of a pair of markers was determined in all rho^- clones of the four populations. The frequencies of marker separation by rho^- deletion thus obtained are assumed to reflect the distance between markers on the mitochondrial genome: the higher the frequency of separation the longer the distance between two markers. Based on these frequencies a unique order of markers on a circular map was determined. Positions of markers on a scale from 0 to 100 were found to be: cap/ery (0) — olil (16) — cob1-1354 (21) — ana101 (22) — cob2-1625 (24) — oli2 (35) — pho1 (40) — oxi3-2501 (44) — oxi3-3771 (47) — par (65) — oxi2 (79) — oxil (87) tms8 (93) —cap (100). The relevance of this map as to the faithful representation of the topology of gene loci on mitDNA is discussed. Correlation of retention frequencies of markers to their map positions reveals a pronounced polarity: mitDNA segments carrying the cob-oli1 segment prevail whereas segments retaining oxi3 are the least frequent.     

Structure-function analysis and genetic interactions of the yeast branchpoint binding protein Msl5

Saccharomyces cerevisiae Msl5 (branchpoint binding protein) orchestrates spliceosome assembly by binding the branchpoint sequence 5'-UACUAAC and establishing cross intron-bridging interactions with other components of the splicing machinery. Reciprocal tandem affinity purifications verify that Msl5 exists in vivo as a heterodimer with Mud2 and that the Msl5-Mud2 complex is associated with the U1 snRNP. By gauging the ability of mutants of Msl5 to complement msl5Δ, we find that the Mud2-binding (amino acids 35-54) and putative Prp40-binding (PPxY(100)) elements of the Msl5 N-terminal domain are inessential, as are the C-terminal proline-rich domain (amino acids 382-476) and two zinc-binding CxxCxxxxHxxxxC motifs (amino acids 273-286 and 299-312). A subset of conserved branchpoint RNA-binding amino acids in the central KH-QUA2 domain (amino acids 146-269) are essential pairwise (Ile198-Arg190; Leu256-Leu259) or in trios (Leu169-Arg172-Leu176), whereas other pairs of RNA-binding residues are dispensable. We used our collection of viable Msl5 mutants to interrogate synthetic genetic interactions, in cis between the inessential structural elements of the Msl5 polypeptide and in trans between Msl5 and yeast splicing factors (Mud2, Nam8 and Tgs1) that are optional for vegetative growth. The results suggest a network of important but functionally buffered protein-protein and protein-RNA interactions between the Mud2-Msl5 complex at the branchpoint and the U1 snRNP at the 5' splice site.     

A molecular interpretation of genetic interactions in yeast

Gene deletion studies in yeast have shown that only approximately 18% of its genes are essential for survival under standard laboratory conditions. This unexpectedly high fraction of genes with apparently no deletion effect has many practical and fundamental implications, and it is subject of considerable interest. Here, we briefly review some of the complementary models proposed to explain the robustness observed in biological networks. We also present and analyse a collection of well-documented cases of gene pairs with capacity to compensate the deleterious effects caused by the inactivation of one of the partner genes, and suggest the molecular bases of how these functional compensations might occur at the protein level.     

Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference

Biological processes are highly dynamic but the current representation of molecular networks is static and largely qualitative. To investigate the dynamic property of genetic networks, a novel quantitative high-throughput method based on RNA interference and capable of calculating the relevance of each interaction, was developed. With this approach, it will be possible to identify not only the components of a network, but also to investigate quantitatively how network and biological processes react to perturbations. As a first application of this method, the genetic interactions of a weak loss-of-function mutation in the gene efl-1/E2F with all the genes of chromosome III were investigated during embryonic development of Caenorhabditis elegans. Fifteen synthetic genetic interactions of efl-1/E2F with the genes of chromosome III were detected, measured and ranked by statistical relevance.     

Functional analysis of the yeast genome

Just as Saccharomyces cerevisiae itself provides a model for so many processes essential to eukaryotic life, we anticipate that the methods and the mindset that have moved yeast biological research "beyond the genome" provide a prototype for making similar progress in other organisms. In this review I describe the experimental processes, results and utility of the current large-scale experimental approaches that use genomic data to provide a functional analysis of the yeast genome. Electronic Publication     

Functional analysis of the yeast genome

The release of the complete genome sequence of the yeast Saccharomyces cerevisiae has ushered in a new phase of genome research in which sequence function will be assigned. The goal is to determine the biological function of each of the >6,000 open reading frames in the yeast genome. Innovative approaches have been developed that exploit the sequence data and yield information about gene expression levels, protein levels, subcellular localization and gene function for the entire genome.     

Spatial interactions within modular organisms: genetic heterogeneity and organism fitness

Modular organisms are composed of iterated units of construction that vary in their spatial arrangement. This variation is expected to affect the fitness of modular organisms due to interactions among neighboring modules and the potential for such organisms to be genetically heterogeneous. We devise a spatially explicit model to investigate how spatial interactions among neighboring modules affect organism fitness. We show that fitness is strongly dependent on the spatial arrangement of modules in both genetically homogeneous and heterogeneous organisms, and that the magnitude of the variation is dependent on the strength of interactions among modules. Organism fitness is more variable with interactions among modules that are symmetrical (each affects each other in the same directions) than with asymmetrical interactions (neighbors affect each other in different directions). We conclude by discussing potential extension of the present framework to a general dynamic model of spatially structured organism development.     

Selection in yeast I: Assessing genetic stability and relative fitness of commercial yeasts

Summary The potential for changes in allele frequencies in yeast populations by selection was examined. Cells from the wine yeastSaccharomyces cerevisiae (strain Montrachet) were grown over a large number of generations using two different culturing techniques, each with two variations: serial transfers on WLN agar plates with and without UV irradiation, and continuous culture in autoclaved and in filter-sterilized grape must. A low frequency of variant isozyme patterns was found in samples taken at the end of the experiment. Growth rates in must and on agar plates were also examined, and it was found that all samples were faster-growing than the original strain, to varying degrees. Applications for the selection system developed are discussed.     

Modeling cancer metabolism on a genome scale

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome‐scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network‐level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field.     

Slow fitness recovery in a codon-modified viral genome

Extensive synonymous codon modification of viral genomes appears to be an effective way of attenuating strains for use as live vaccines. An assumption of this method is that codon changes have individually small effects, such that codon-attenuated viruses will be slow to evolve back to high fitness (and thus to high virulence). The major capsid gene of the bacterial virus T7 was modified to have varying levels of suboptimal synonymous codons in different constructs, and fitnesses declined linearly with the number of changes. Adaptation of the most extreme design, with 182 codon changes, resulted in a slow fitness recovery by standards of previous experimental evolution with this virus, although fitness effects of substitutions were higher than expected from the average effect of an engineered codon modification. Molecular evolution during recovery was modest, and changes evolved both within the modified gene and outside it. Some changes within the modified gene evolved in parallel across replicates, but with no obvious explanation. Overall, the study supports the premise that codon-modified viruses recover fitness slowly, although the evolution is substantially more rapid than expected from the design principle.     

Quantitative evidence for early life fitness defects from 32 longevity-associated alleles in yeast

Reduced fecundity has been associated with some alleles that enhance longevity in invertebrate and mammalian models. This observation has been suggested to support the antagonistic pleiotropy theory of aging, which predicts that alleles of some genes promoting fitness early in life have detrimental effects later in life that limit survival. In only a few cases, however, has the relative fitness of long-lived mutants been quantified through direct competition with the wild type genotype. Here we report the first comprehensive analysis of longevity/fitness trade-offs by measuring the relative fitness of 49 long-lived yeast variants in a direct competition assay with wild type cells. We find that 32 (65%) of these variants show a significant defect in fitness in this competition assay. In 26 (81%) of these cases, this reduction in fitness can be partially accounted for by reduced maximal growth rate during early life, usually resulting from a G0/G1-specific cell cycle defect. A majority of the less fit longevity-enhancing variants are associated with reduced mRNA translation. These findings are therefore consistent with the idea that enhanced longevity often comes with a fitness cost and suggest that this cost is often associated with variation in a subset of longevity factors, such as those regulating mRNA translation, growth, and reproduction.     

Quantitative evidence for early life fitness defects from 32 longevity-associated alleles in yeast

Reduced fecundity has been associated with some alleles that enhance longevity in invertebrate and mammalian models. This observation has been suggested to support the antagonistic pleiotropy theory of aging, which predicts that alleles of some genes promoting fitness early in life have detrimental effects later in life that limit survival. In only a few cases, however, has the relative fitness of long-lived mutants been quantified through direct competition with the wild type genotype. Here we report the first comprehensive analysis of longevity/fitness trade-offs by measuring the relative fitness of 49 long-lived yeast variants in a direct competition assay with wild type cells. We find that 32 (65%) of these variants show a significant defect in fitness in this competition assay. In 26 (81%) of these cases, this reduction in fitness can be partially accounted for by reduced maximal growth rate during early life, usually resulting from a G₀/G₁-specific cell cycle defect. A majority of the less fit longevity-enhancing variants are associated with reduced mRNA translation. These findings are therefore consistent with the idea that enhanced longevity often comes with a fitness cost and suggest that this cost is often associated with variation in a subset of longevity factors, such as those regulating mRNA translation, growth and reproduction.Key words: yeast, aging, antagonistic pleiotropy, fitness, translation, longevity, evolution     

Differential genetic interactions of yeast stress response MAPK pathways

Genetic interaction screens have been applied with great success in several organisms to study gene function and the genetic architecture of the cell. However, most studies have been performed under optimal growth conditions even though many functional interactions are known to occur under specific cellular conditions. In this study, we have performed a large‐scale genetic interaction analysis in Saccharomyces cerevisiae involving approximately 49 × 1,200 double mutants in the presence of five different stress conditions, including osmotic, oxidative and cell wall‐altering stresses. This resulted in the generation of a differential E‐MAP (or dE‐MAP) comprising over 250,000 measurements of conditional interactions. We found an extensive number of conditional genetic interactions that recapitulate known stress‐specific functional associations. Furthermore, we have also uncovered previously unrecognized roles involving the phosphatase regulator Bud14, the histone methylation complex COMPASS and membrane trafficking complexes in modulating the cell wall integrity pathway. Finally, the osmotic stress differential genetic interactions showed enrichment for genes coding for proteins with conditional changes in phosphorylation but not for genes with conditional changes in gene expression. This suggests that conditional genetic interactions are a powerful tool to dissect the functional importance of the different response mechanisms of the cell.     

Time scale and dimension analysis of a budding yeast cell cycle model

Background  

The progress through the eukaryotic cell division cycle is driven by an underlying molecular regulatory network. Cell cycle progression can be considered as a series of irreversible transitions from one steady state to another in the correct order. Although this view has been put forward some time ago, it has not been quantitatively proven yet. Bifurcation analysis of a model for the budding yeast cell cycle has identified only two different steady states (one for G1 and one for mitosis) using cell mass as a bifurcation parameter. By analyzing the same model, using different methods of dynamical systems theory, we provide evidence for transitions among several different steady states during the budding yeast cell cycle.     

An inclusive fitness analysis of synergistic interactions in structured populations

We study the evolution of a pair of competing behavioural alleles in a structured population when there are non-additive or ‘synergistic’ fitness effects. Under a form of weak selection and with a simple symmetry condition between a pair of competing alleles, Tarnita et al. provide a surprisingly simple condition for one allele to dominate the other. Their condition can be obtained from an analysis of a corresponding simpler model in which fitness effects are additive. Their result uses an average measure of selective advantage where the average is taken over the long-term—that is, over all possible allele frequencies—and this precludes consideration of any frequency dependence the allelic fitness might exhibit. However, in a considerable body of work with non-additive fitness effects—for example, hawk–dove and prisoner''s dilemma games—frequency dependence plays an essential role in the establishment of conditions for a stable allele-frequency equilibrium. Here, we present a frequency-dependent generalization of their result that provides an expression for allelic fitness at any given allele frequency p. We use an inclusive fitness approach and provide two examples for an infinite structured population. We illustrate our results with an analysis of the hawk–dove game.