Genetic background and mistranslation frequency determine the impact of mistranslating tRNASerUGG.

Transfer RNA variants increase the frequency of mistranslation, the misincorporation of an amino acid not specified by the "standard" genetic code, to frequencies approaching 10% in yeast and bacteria. Cells cope with these variants by having multiple copies of each tRNA isodecoder and through pathways that deal with proteotoxic stress. In this study, we define the genetic interactions of the gene encoding tRNASerUGG,G26A, which mistranslates serine at proline codons. Using a collection of yeast temperature-sensitive alleles, we identify negative synthetic genetic interactions between the mistranslating tRNA and 109 alleles representing 91 genes, with nearly half of the genes having roles in RNA processing or protein folding and turnover. By regulating tRNA expression, we then compare the strength of the negative genetic interaction for a subset of identified alleles under differing amounts of mistranslation. The frequency of mistranslation correlated with the impact on cell growth for all strains analyzed; however, there were notable differences in the extent of the synthetic interaction at different frequencies of mistranslation depending on the genetic background. For many of the strains, the extent of the negative interaction with tRNASerUGG,G26A was proportional to the frequency of mistranslation or only observed at intermediate or high frequencies. For others, the synthetic interaction was approximately equivalent at all frequencies of mistranslation. As humans contain similar mistranslating tRNAs, these results are important when analyzing the impact of tRNA variants on disease, where both the individual's genetic background and the expression of the mistranslating tRNA variant need to be considered.

The amino acid substitution affects cellular response to mistranslation.

Mistranslation, the misincorporation of an amino acid not specified by the "standard" genetic code, occurs in all organisms. tRNA variants that increase mistranslation arise spontaneously and engineered tRNAs can achieve mistranslation frequencies approaching 10% in yeast and bacteria. Interestingly, human genomes contain tRNA variants with the potential to mistranslate. Cells cope with increased mistranslation through multiple mechanisms, though high levels cause proteotoxic stress. The goal of this study was to compare the genetic interactions and the impact on transcriptome and cellular growth of two tRNA variants that mistranslate at a similar frequency but create different amino acid substitutions in Saccharomyces cerevisiae. One tRNA variant inserts alanine at proline codons whereas the other inserts serine for arginine. Both tRNAs decreased growth rate, with the effect being greater for arginine to serine than for proline to alanine. The tRNA that substituted serine for arginine resulted in a heat shock response. In contrast, heat shock response was minimal for proline to alanine substitution. Further demonstrating the significance of the amino acid substitution, transcriptome analysis identified unique up- and down-regulated genes in response to each mistranslating tRNA. Number and extent of negative synthetic genetic interactions also differed depending upon type of mistranslation. Based on the unique responses observed for these mistranslating tRNAs, we predict that the potential of mistranslation to exacerbate diseases caused by proteotoxic stress depends on the tRNA variant. Furthermore, based on their unique transcriptomes and genetic interactions, different naturally occurring mistranslating tRNAs have the potential to negatively influence specific diseases.

Environmental robustness of the global yeast genetic interaction network.

Phenotypes associated with genetic variants can be altered by interactions with other genetic variants (GxG), with the environment (GxE), or both (GxGxE). Yeast genetic interactions have been mapped on a global scale, but the environmental influence on the plasticity of genetic networks has not been examined systematically. To assess environmental rewiring of genetic networks, we examined 14 diverse conditions and scored 30,000 functionally representative yeast gene pairs for dynamic, differential interactions. Different conditions revealed novel differential interactions, which often uncovered functional connections between distantly related gene pairs. However, the majority of observed genetic interactions remained unchanged in different conditions, suggesting that the global yeast genetic interaction network is robust to environmental perturbation and captures the fundamental functional architecture of a eukaryotic cell.

Natural variants suppress mutations in hundreds of essential genes.

The consequence of a mutation can be influenced by the context in which it operates. For example, loss of gene function may be tolerated in one genetic background, and lethal in another. The extent to which mutant phenotypes are malleable, the architecture of modifiers and the identities of causal genes remain largely unknown. Here, we measure the fitness effects of ~ 1,100 temperature-sensitive alleles of yeast essential genes in the context of variation from ten different natural genetic backgrounds and map the modifiers for 19 combinations. Altogether, fitness defects for 149 of the 580 tested genes (26%) could be suppressed by genetic variation in at least one yeast strain. Suppression was generally driven by gain-of-function of a single, strong modifier gene, and involved both genes encoding complex or pathway partners suppressing specific temperature-sensitive alleles, as well as general modifiers altering the effect of many alleles. The emerging frequency of suppression and range of possible mechanisms suggest that a substantial fraction of monogenic diseases could be managed by modulating other gene products.

Timer-based proteomic profiling of the ubiquitin-proteasome system reveals a substrate receptor of the GID ubiquitin ligase.

Selective protein degradation by the ubiquitin-proteasome system (UPS) is involved in all cellular processes. However, the substrates and specificity of most UPS components are not well understood. Here we systematically characterized the UPS in Saccharomyces cerevisiae. Using fluorescent timers, we determined how loss of individual UPS components affects yeast proteome turnover, detecting phenotypes for 76% of E2, E3, and deubiquitinating enzymes. We exploit this dataset to gain insights into N-degron pathways, which target proteins carrying N-terminal degradation signals. We implicate Ubr1, an E3 of the Arg/N-degron pathway, in targeting mitochondrial proteins processed by the mitochondrial inner membrane protease. Moreover, we identify Ylr149c/Gid11 as a substrate receptor of the glucose-induced degradation-deficient (GID) complex, an E3 of the Pro/N-degron pathway. Our results suggest that Gid11 recognizes proteins with N-terminal threonines, expanding the specificity of the GID complex. This resource of potential substrates and relationships between UPS components enables exploring functions of selective protein degradation.

The budding yeast RSC complex maintains ploidy by promoting spindle pole body insertion.

Ploidy is tightly regulated in eukaryotic cells and is critical for cell function and survival. Cells coordinate multiple pathways to ensure replicated DNA is segregated accurately to prevent abnormal changes in chromosome number. In this study, we characterize an unanticipated role for the Saccharomyces cerevisiae "remodels the structure of chromatin" (RSC) complex in ploidy maintenance. We show that deletion of any of six nonessential RSC genes causes a rapid transition from haploid to diploid DNA content because of nondisjunction events. Diploidization is accompanied by diagnostic changes in cell morphology and is stably maintained without further ploidy increases. We find that RSC promotes chromosome segregation by facilitating spindle pole body (SPB) duplication. More specifically, RSC plays a role in distributing two SPB insertion factors, Nbp1 and Ndc1, to the new SPB. Thus, we provide insight into a role for a SWI/SNF family complex in SPB duplication and ploidy maintenance.

Systematic analysis of complex genetic interactions.

To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.

Genome-Scale Networks Link Neurodegenerative Disease Genes to α-Synuclein through Specific Molecular Pathways.

Numerous genes and molecular pathways are implicated in neurodegenerative proteinopathies, but their inter-relationships are poorly understood. We systematically mapped molecular pathways underlying the toxicity of alpha-synuclein (α-syn), a protein central to Parkinson's disease. Genome-wide screens in yeast identified 332 genes that impact α-syn toxicity. To "humanize" this molecular network, we developed a computational method, TransposeNet. This integrates a Steiner prize-collecting approach with homology assignment through sequence, structure, and interaction topology. TransposeNet linked α-syn to multiple parkinsonism genes and druggable targets through perturbed protein trafficking and ER quality control as well as mRNA metabolism and translation. A calcium signaling hub linked these processes to perturbed mitochondrial quality control and function, metal ion transport, transcriptional regulation, and signal transduction. Parkinsonism gene interaction profiles spatially opposed in the network (ATP13A2/PARK9 and VPS35/PARK17) were highly distinct, and network relationships for specific genes (LRRK2/PARK8, ATXN2, and EIF4G1/PARK18) were confirmed in patient induced pluripotent stem cell (iPSC)-derived neurons. This cross-species platform connected diverse neurodegenerative genes to proteinopathy through specific mechanisms and may facilitate patient stratification for targeted therapy.

Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae.

BACKGROUND: Transcriptome studies have revealed that many eukaryotic genomes are pervasively transcribed producing numerous long non-coding RNAs (lncRNAs). However, only a few lncRNAs have been ascribed a cellular role thus far, with most regulating the expression of adjacent genes. Even less lncRNAs have been annotated as essential hence implying that the majority may be functionally redundant. Therefore, the function of lncRNAs could be illuminated through systematic analysis of their synthetic genetic interactions (GIs). RESULTS: Here, we employ synthetic genetic array (SGA) in Saccharomyces cerevisiae to identify GIs between long intergenic non-coding RNAs (lincRNAs) and protein-coding genes. We first validate this approach by demonstrating that the telomerase RNA TLC1 displays a GI network that corresponds to its well-described function in telomere length maintenance. We subsequently performed SGA screens on a set of uncharacterised lincRNAs and uncover their connection to diverse cellular processes. One of these lincRNAs, SUT457, exhibits a GI profile associating it to telomere organisation and we consistently demonstrate that SUT457 is required for telomeric overhang homeostasis through an Exo1-dependent pathway. Furthermore, the GI profile of SUT457 is distinct from that of its neighbouring genes suggesting a function independent to its genomic location. Accordingly, we show that ectopic expression of this lincRNA suppresses telomeric overhang accumulation in sut457Δ cells assigning a trans-acting role for SUT457 in telomere biology. CONCLUSIONS: Overall, our work proposes that systematic application of this genetic approach could determine the functional significance of individual lncRNAs in yeast and other complex organisms.

Exploring genetic suppression interactions on a global scale.

Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.

A global genetic interaction network maps a wiring diagram of cellular function.

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.

Mapping the functional yeast ABC transporter interactome.

ATP-binding cassette (ABC) transporters are a ubiquitous class of integral membrane proteins of immense clinical interest because of their strong association with human disease and pharmacology. To improve our understanding of these proteins, we used membrane yeast two-hybrid technology to map the protein interactome of all of the nonmitochondrial ABC transporters in the model organism Saccharomyces cerevisiae and combined this data with previously reported yeast ABC transporter interactions in the BioGRID database to generate a comprehensive, integrated 'interactome'. We show that ABC transporters physically associate with proteins involved in an unexpectedly diverse range of functions. We specifically examine the importance of the physical interactions of ABC transporters in both the regulation of one another and in the modulation of proteins involved in zinc homeostasis. The interaction network presented here will be a powerful resource for increasing our fundamental understanding of the cellular role and regulation of ABC transporters.

Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.

Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single- and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles.

The genetic landscape of a cell.

A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.

The extensive and condition-dependent nature of epistasis among whole-genome duplicates in yeast.

Since complete redundancy between extant duplicates (paralogs) is evolutionarily unfavorable, some degree of functional congruency is eventually lost. However, in budding yeast, experimental evidence collected for duplicated metabolic enzymes and in global physical interaction surveys had suggested widespread functional overlap between paralogs. While maintained functional overlap is thought to confer robustness against genetic mutation and facilitate environmental adaptability, it has yet to be determined what properties define paralogs that can compensate for the phenotypic consequence of deleting a sister gene, how extensive this epistasis is, and how adaptable it is toward alternate environmental states. To this end, we have performed a comprehensive experimental analysis of epistasis as indicated by aggravating genetic interactions between paralogs resulting from an ancient whole-genome duplication (WGD) event occurring in the budding yeast Saccharomyces cerevisiae, and thus were able to compare properties of large numbers of epistatic and non-epistatic paralogs with identical evolutionary times since divergence. We found that more than one-third (140) of the 399 examinable WGD paralog pairs were epistatic under standard laboratory conditions and that additional cases of epistasis became obvious only under media conditions designed to induce cellular stress. Despite a significant increase in within-species sequence co-conservation, analysis of protein interactions revealed that paralogs epistatic under standard laboratory conditions were not more functionally overlapping than those non-epistatic. As experimental conditions had an impact on the functional categorization of paralogs deemed epistatic and only a fraction of potential stress conditions have been interrogated here, we hypothesize that many epistatic relationships remain unresolved.