Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.
Wild yeast strains differ in phenotypes that are controlled by highly conserved signaling pathways. Yet it remains unknown how naturally occurring genetic variants influence signaling pathways in yeast. We have developed an approach to facilitate the mapping of genetic variants that underlie these phenotypic differences in a set of wild strain. Our mapping approach requires minimal strain engineering and enables the rapid isolation of mapping populations from any strain background. In particular, we have mapped genetic variants in twelve highly diverse yeast strains. Further, we demonstrate how the mapping results from these twelve strains can be used jointly to narrow the number of genetic variants identified to a set of putative causal variants. We identify genetic variants in genes with various roles in cell signaling. Our results illustrate the interplay of different signaling pathways and which signaling genes are more likely to contain variants of large phenotypic impact.
Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or multiple genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL) 1. Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power 2–6. Consequently, many eQTL are likely missed, especially those with smaller effects 7. Further, most studies use mRNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics 8–13 reported surprising differences between eQTL and protein QTL (pQTL) for the same genes 9,10, but these studies have been even more limited in scope. Here, we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyes cerevisiae. We measure single-cell protein abundance through the use of green-fluorescent-protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high vs. low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci cluster at hotspot locations that influence multiple proteins—in some cases, more than half of those examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.
The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain) and RM11_1a (a vineyard strain), to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance.
Variation in response to a drug can be determined by many factors. In the model organism baker's yeast, many studies of chemical resistance traits have uncovered a complex genetic basis of such resistance. However, an in-depth study of how drug dose alters the effects of underlying genetic factors is lacking. Here, we employed linkage analysis to map the specific genetic loci underlying response to haloperidol, a small molecule therapeutic drug, using a large panel of segregants from a cross between two genetically divergent yeast strains BY (a laboratory strain) and RM (a vineyard strain). We found that loci associated with haloperidol resistance are dose-dependent. We also showed that variants in the oxysterol-binding-protein-like domain of the gene SWH1 underlie the major locus detected at all doses of haloperidol. Genetic interactions among genes SWH1, MKT1, and IRA2 in the RM background contribute to the differential response at high concentrations of haloperidol.
Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.
Individuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic—it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called “ribosome profiling” to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.
For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this “missing heritability” have been proposed1. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to approximately 50%. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits.
Metabolism, the conversion of nutrients into usable energy and biochemical building blocks, is an essential feature of all cells. The genetic factors responsible for inter-individual metabolic variability remain poorly understood. To investigate genetic causes of metabolome variation, we measured the concentrations of 74 metabolites across 100 segregants from a Saccharomyces cerevisiae cross by liquid chromatography-tandem mass spectrometry. We found 52 quantitative trait loci for 34 metabolites. These included linkages due to overt changes in metabolic genes, e.g., linking pyrimidine intermediates to the deletion of ura3. They also included linkages not directly related to metabolic enzymes, such as those for five central carbon metabolites to ira2, a Ras/PKA pathway regulator, and for the metabolites, S-adenosyl-methionine and S-adenosyl-homocysteine to slt2, a MAP kinase involved in cell wall integrity. The variant of ira2 that elevates metabolite levels also increases glucose uptake and ethanol secretion. These results highlight specific examples of genetic variability, including in genes without prior known metabolic regulatory function, that impact yeast metabolism.
Many traits, from human height to E. coli growth rate, quantitatively vary across members of a species. Among the most medically and agriculturally important traits are levels of cellular metabolites, such as cholesterol levels in humans or starch in food crops. Metabolic variation in yeast also holds practical importance with some Saccharomyces strains better suited to making ethanol for biofuel and others tailored to making flavorful wine. This metabolic heterogeneity can be used to gain insight into general principles of metabolic regulation which effect metabolite abundance in eukaryotes. To this end, we examined inter-strain differences in metabolism in over 100 closely related S. cerevisiae strains. We identified over 50 genetic loci that control the levels of specific metabolites, including not only loci that encode metabolic enzymes, but also those that encode global cellular regulators. For example, differences in the sequence of ira2, an inhibitor of Ras, lead to differences in central carbon metabolite levels, and polymorphisms in slt2, a poorly characterized MAP kinase, alter levels of sulfur-containing metabolites. These findings provide insights into the mechanisms cells use to control metabolite concentrations.
The mechanistic basis for how genetic variants cause differences in phenotypic traits is often elusive. We identified a quantitative trait locus in Caenorhabditis elegans that affects three seemingly unrelated phenotypic traits: lifetime fecundity, adult body size, and susceptibility to the human pathogen Staphyloccus aureus. We found a QTL for all three traits arises from variation in the neuropeptide receptor gene npr-1. Moreover, we found that variation in npr-1 is also responsible for differences in 247 gene expression traits. Variation in npr-1 is known to determine whether animals disperse throughout a bacterial lawn or aggregate at the edges of the lawn. We found that the allele that leads to aggregation is associated with reduced growth and reproductive output. The altered gene expression pattern caused by this allele suggests that the aggregation behavior might cause a weak starvation state, which is known to reduce growth rate and fecundity. Importantly, we show that variation in npr-1 causes each of these phenotypic differences through behavioral avoidance of ambient oxygen concentrations. These results suggest that variation in npr-1 has broad pleiotropic effects mediated by altered exposure to bacterial food.
Using the nematode roundworm Caenorhabditis elegans, we identified differences in lifetime fecundity, adult body size, and susceptibility to the human pathogen Staphyloccus aureus between the laboratory strain (N2) from Bristol, England and a wild strain (CB4856) from Hawaii, USA. Using linkage mapping and other genetic tests, we found a QTL for all three traits arises from variation in the neuropeptide receptor gene npr-1. Moreover, we found that variation in npr-1 is also responsive for differences in 247 gene expression traits. Variation in npr-1 is known to determine whether animals disperse throughout a bacterial lawn or aggregate at the edges of the lawn. We found that the allele that leads to aggregation is associated with reduced growth and reproductive output likely caused by a weak chronic starvation state. These results suggest that variation in npr-1 has broad effects on the phenotype of an organism mediated by altered exposure to bacterial food.
A strain of Halomonas bacteria, GFAJ-1, has been reported to be able to use arsenate as a nutrient when phosphate is limiting, and to specifically incorporate arsenic into its DNA in place of phosphorus. However, we have found that arsenate does not contribute to growth of GFAJ-1 when phosphate is limiting and that DNA purified from cells grown with limiting phosphate and abundant arsenate does not exhibit the spontaneous hydrolysis expected of arsenate ester bonds. Furthermore, mass spectrometry showed that this DNA contains only trace amounts of free arsenate and no detectable covalently bound arsenate.
High concentrations of ammonium at physiological concentrations of potassium are toxic for the standard laboratory strain of Saccharomyces cerevisiae. In the original description of this metabolic phenotype, we focused on the standard laboratory strains of Saccharomyces. In this study, we screened a large collection of S. cerevisiae natural isolates and identified one strain that is resistant to high concentrations of ammonium. This strain, K12, was isolated in sake breweries. When the K12 strain was crossed to the standard laboratory strain (FY4), the resulting tetrads displayed 2:2 segregation of the resistance phenotype, suggesting a single gene trait. Using a bulk segregant analysis strategy, we mapped this trait to a 150-kb region on chromosome X containing the TRK1 gene. This gene encodes a transporter required for high-affinity potassium transport in S. cerevisiae. Data from reciprocal hemizygosity experiments with TRK1 deletion strains in K12 and BY backgrounds, as well as analysis of the deletion of this gene in the K12 strain, demonstrate that the K12 allele of TRK1 is responsible for ammonium toxicity resistance. Furthermore, we determined the minimal amount of potassium required for both the K12 and laboratory strain needed for growth. These results demonstrate that the gene encoded by the K12 allele of TRK1 has a greater affinity for potassium than the standard allele of TRK1 found in Saccharomyces strains. We hypothesize that this greater-affinity allele of the potassium transporter reduces the flux of ammonium into the yeast cells under conditions of ammonium toxicity. These findings further refine our understanding of ammonium toxicity in yeast and provide an example of using natural variation to understand cellular processes.
Aging and longevity are complex traits influenced by genetic and environmental factors. To identify quantitative trait loci (QTLs) that control replicative lifespan, we employed an outbred Saccharomyces cerevisiae model, generated by crossing a vineyard and a laboratory strain. The predominant QTL mapped to the rDNA, with the vineyard rDNA conferring a lifespan increase of 41%. The lifespan extension was independent of Sir2 and Fob1, but depended on a polymorphism in the rDNA origin of replication from the vineyard strain that reduced origin activation relative to the laboratory origin. Strains carrying vineyard rDNA origins have increased capacity for replication initiation at weak plasmid and genomic origins, suggesting that inability to complete genome replication presents a major impediment to replicative lifespan. Calorie restriction, a conserved mediator of lifespan extension that is also independent of Sir2 and Fob1, reduces rDNA origin firing in both laboratory and vineyard rDNA. Our results are consistent with the possibility that calorie restriction, similarly to the vineyard rDNA polymorphism, modulates replicative lifespan through control of rDNA origin activation, which in turn affects genome replication dynamics.
Although many aging regulators have been discovered, we are still uncovering how each contributes to the basic biology underlying cell lifespan and how certain longevity-promoting regimens, such as calorie restriction, manipulate the aging process across species. Since many cellular aging processes between human cells and budding yeast are related, we examined a collection of genetically diverse yeast and discovered that a genetic variant in vineyard yeast confers a 41% lifespan increase. The responsible sequence in the vineyard yeast reduces the amount of DNA replication that initiates at the ribosomal DNA (rDNA) locus, a chromosome-sized region of the genome that is dedicated to the production of ribosomal RNA required for protein synthesis and growth. Strikingly, we find that calorie restriction conditions also reduce rDNA replication, potentially promoting longevity by the same mechanism. While the rDNA has been previously linked to lifespan control, how this single locus affects global cell function has remained elusive. We find that a weakly replicating rDNA promotes DNA replication across the rest of the cell's genome, perhaps through the re-allocation of replication resources from decreased rDNA demand. Our findings suggest that the cell's inability to complete genome replication is one of the major impediments to yeast longevity.
Aggregation is a social behavior that varies between and within species, providing a model to study the genetic basis of behavioral diversity. In the nematode Caenorhabditis elegans, aggregation is regulated by environmental context and by two neuromodulatory pathways, one dependent on the neuropeptide receptor NPR-1 and one dependent on the TGF-β family protein DAF-7. To gain further insight into the genetic regulation of aggregation, we characterize natural variation underlying behavioral differences between two wild-type C. elegans strains, N2 and CB4856. Using quantitative genetic techniques, including a survey of chromosome substitution strains and QTL analysis of recombinant inbred lines, we identify three new QTLs affecting aggregation in addition to the two known N2 mutations in npr-1 and glb-5. Fine-mapping with near-isogenic lines localized one QTL, accounting for 5%–8% of the behavioral variance between N2 and CB4856, 3′ to the transcript of the GABA neurotransmitter receptor gene exp-1. Quantitative complementation tests demonstrated that this QTL affects exp-1, identifying exp-1 and GABA signaling as new regulators of aggregation. exp-1 interacts genetically with the daf-7 TGF-β pathway, which integrates food availability and population density, and exp-1 mutations affect the level of daf-7 expression. Our results add to growing evidence that genetic variation affecting neurotransmitter receptor genes is a source of natural behavioral variation.
In both animals and humans, normal individuals can behave differently in the same environment. Natural variation in behavior is partly due to genetic differences between individuals and partly due to experience. Mapping studies have demonstrated that the genetic component of natural behavioral variation is complex, with many genes that each contribute a small amount to the observed behavior. This complexity has made it difficult to identify the causative genes for individual differences. Here we use the nematode worm C. elegans to dissect a social behavioral trait, the propensity to aggregate with other animals in the presence of food. We find that the behavioral differences between two wild-type worm strains result from at least five genetic differences between the strains, two of which were previously known. One of the three new loci affects a receptor for the neurotransmitter GABA, which regulates excitability in the brain. In the context of previous work, we suggest that a significant number of genes that generate behavioral variation encode neurotransmitter receptors. This analysis in a model animal may help guide discoveries of the genetic variants that affect common human behavioral traits by suggesting classes of genes to examine closely.
Responding to noxious stimuli by invoking an appropriate escape response is critical for survival of an organism. The sensations of small and large changes in temperature in most organisms have been studied separately in the context of thermotaxis and nociception, respectively. Here we use the nematode C. elegans to address the neurogenetic basis of responses to thermal stimuli over a broad range of intensities.
C. elegans responds to aversive temperature by eliciting a stereotypical behavioral sequence. Upon sensation of the noxious stimulus, it moves backwards, turns and resumes forward movement in a new direction. In order to study the response of C. elegans to a broad range of noxious thermal stimuli, we developed a novel assay that allows simultaneous characterization of multiple aspects of escape behavior elicited by thermal pulses of increasing amplitudes. We exposed the laboratory strain N2, as well as 47 strains with defects in various aspects of nervous system function, to thermal pulses ranging from ΔT = 0.4°C to 9.1°C and recorded the resulting behavioral profiles.
Through analysis of the multidimensional behavioral profiles, we found that the combinations of molecules shaping avoidance responses to a given thermal pulse are unique. At different intensities of aversive thermal stimuli, these distinct combinations of molecules converge onto qualitatively similar stereotyped behavioral sequences.
Nociception; dimensionality reduction; ethology; thermal sensation
The nematode Caenorhabditis elegans is central to research in molecular, cell, and developmental biology, but nearly all of this research has been conducted on a single strain. Comparatively little is known about the population genomic and evolutionary history of this species. We characterized C. elegans genetic variation by high-throughput selective sequencing of a worldwide collection of 200 wild strains, identifying 41,188 single nucleotide polymorphisms. Unexpectedly, C. elegans genome variation is dominated by a set of commonly shared haplotypes on four of the six chromosomes, each spanning many megabases. Population-genetic modeling shows that this pattern was generated by chromosome-scale selective sweeps that have reduced variation worldwide; at least one of these sweeps likely occurred in the past few hundred years. These sweeps, which we hypothesize to be a result of human activity, have dramatically reshaped the global C. elegans population in the recent past.
A novel strategy for the quantitative measurement of allele-specific protein expression is used to infer the contributions of cis- and trans-acting factors influencing the divergence of protein levels between yeast species.
Rigorous experimental controls and analyses confirm the accuracy of the new strategy for the quantitative measurement of allele-specific protein expression by high-throughput mass spectrometry.Analysis of allele-specific protein expression in an interspecies yeast hybrid and protein expression differences between species reveals that both cis-effects and trans-effects contribute to protein expression divergence between two yeast species, Saccharomyces cerevisiae and Saccharomyces bayanus.
Understanding the genetic basis of gene regulatory variation is a key goal of evolutionary and medical genetics. Regulatory variation can act in an allele-specific manner (cis-acting) or it can affect both alleles of a gene (trans-acting). Differential allele-specific expression (ASE), in which the expression of one allele differs from another in a diploid, implies the presence of cis-acting regulatory variation. While microarrays and high-throughput sequencing have enabled genome-wide measurements of transcriptional ASE, methods for measurement of protein ASE (pASE) have lagged far behind. We describe a flexible, accurate, and scalable strategy for measurement of pASE by liquid chromatography-coupled mass spectrometry (LC-MS). We apply this approach to a hybrid between the yeast species Saccharomyces cerevisiae and Saccharomyces bayanus. Our results provide the first analysis of the relative contribution of cis-acting and trans-acting regulatory differences to protein expression divergence between yeast species.
allele specific; divergence; mass spectrometry; protein expression; proteomics
Resistance of nematodes to anthelmintics such as avermectins has emerged as a major global health and agricultural problem, but genes conferring natural resistance to avermectins are unknown. We show that a naturally occurring four amino-acid deletion in the ligand-binding domain of GLC-1, the alpha-subunit of a glutamate-gated chloride channel, confers resistance to avermectins in the model nematode Caenorhabditis elegans. We also find that the same variant confers resistance to the avermectin-producing bacterium Streptomyces avermitilis. Population-genetic analyses identified two highly divergent haplotypes at the glc-1 locus that have been maintained at intermediate frequencies by long-term balancing selection. These results implicate variation in glutamate-gated chloride channels in avermectin resistance and provide a mechanism by which such resistance can be maintained.
Many questions about the genetic basis of complex traits remain unanswered. This is in part due to the low statistical power of traditional genetic mapping studies. We used a statistically powerful approach, extreme QTL mapping (X-QTL), to identify the genetic basis of resistance to 13 chemicals in all 6 pairwise crosses of four ecologically and genetically diverse yeast strains, and we detected a total of more than 800 loci. We found that the number of loci detected in each experiment was primarily a function of the trait (explaining 46% of the variance) rather than the cross (11%), suggesting that the level of genetic complexity is a consistent property of a trait across different genetic backgrounds. Further, we observed that most loci had trait-specific effects, although a small number of loci with effects in many conditions were identified. We used the patterns of resistance and susceptibility alleles in the four parent strains to make inferences about the allele frequency spectrum of functional variants. We also observed evidence of more complex allelic series at a number of loci, as well as strain-specific signatures of selection. These results improve our understanding of complex traits in yeast and have implications for study design in other organisms.
Most heritable traits of agricultural, evolutionary, and medical significance are specified by multiple genetic loci. Despite decades of research, we have only a limited understanding of the genetic basis of such complex traits. Studies in model organisms have the potential to provide fundamental insights into this research area, but most genetic mapping studies in these species have had low statistical power to detect multiple loci with small effects. Using a technique in which we employed millions of cross progeny in genetic mapping, we previously showed that resistance to chemicals has a highly complex genetic basis in a cross of a lab strain and a wine strain of the budding yeast Saccharomyces cerevisiae. Because we only examined a single cross, it was unclear how general our findings were. Here, we expand our work to all six possible crosses of four strains—the two isolates we used in our last study, as well as an isolate from an immunocompromised human being and an isolate from the sap of an oak tree. Our results based on these four ecologically and genetically distinct S. cerevisiae strains suggest that resistance to chemicals commonly exhibits a highly complex genetic basis among yeast isolates.
Eukaryotic release factors 1 and 3, encoded by SUP45 and SUP35, respectively, in Saccharomyces cerevisiae, are required for translation termination. Recent studies have shown that, besides these two key factors, several genetic and epigenetic mechanisms modulate the efficiency of translation termination. These mechanisms, through modifying translation termination fidelity, were shown to affect various cellular processes, such as mRNA degradation, and in some cases could confer a beneficial phenotype to the cell. The most studied example of such a mechanism is [PSI+], the prion conformation of Sup35p, which can have pleiotropic effects on growth that vary among different yeast strains. However, genetic loci underlying such readthrough-dependent, background-specific phenotypes have yet to be identified. Here, we used sup35C653R, a partial loss-of-function allele of the SUP35 previously shown to increase readthrough of stop codons and recapitulate some [PSI+]-dependent phenotypes, to study the genetic basis of phenotypes revealed by increased translational readthrough in two divergent yeast strains: BY4724 (a laboratory strain) and RM11_1a (a wine strain). We first identified growth conditions in which increased readthrough of stop codons by sup35C653R resulted in different growth responses between these two strains. We then used a recently developed linkage mapping technique, extreme QTL mapping (X-QTL), to identify readthrough-dependent loci for the observed growth differences. We further showed that variation in SKY1, an SR protein kinase, underlies a readthrough-dependent locus observed for growth on diamide and hydrogen peroxide. We found that the allelic state of SKY1 interacts with readthrough level and the genetic background to determine growth rate in these two conditions.
Proper termination is an important step in a successful mRNA translation event. Many factors, employing genetic and epigenetic mechanisms, are involved in modifying translation termination efficiency in the budding yeast, Saccharomyces cerevisiae. [PSI+], the prion conformation of Sup35p, one of the translation termination factors in yeast, provides an example of such mechanisms. [PSI+] increases readthrough of stop codons. This has the potential to unveil hidden genetic variation that may enhance growth in some yeast strains in certain environments. The specific details of readthrough-dependent phenotypes, however, have remained poorly understood. Here, we used a partial loss-of-function allele of SUP35, which increases readthrough of stop codons, and a recently developed linkage mapping technique, X-QTL, to map loci underlying readthrough-dependent growth phenotypes in two divergent yeast strains, BY (a laboratory strain) and RM (a wine strain). We found that readthrough-dependent growth phenotypes are often complex, with multiple loci influencing growth. We also showed that variants in the gene SKY1 underlie one of the loci detected for readthrough-dependent growth phenotypes in the presence of two chemicals that induce oxidative stress.
In quantitative mass spectrometry-based proteomics, the metabolic incorporation of a single source of 15N-labeled nitrogen has many advantages over using stable isotope-labeled amino acids. However, the lack of a robust computational framework for analyzing the resulting spectra has impeded wide use of this approach. We have addressed this challenge by introducing a new computational methodology for analyzing 15N spectra in which quantification is integrated with identification. Application of this method to an Escherichia coli growth transition reveals significant improvement in quantification accuracy over previous methods.
Innate behaviours are flexible: they change rapidly in response to transient environmental conditions, and are modified slowly by changes in the genome. A classical flexible behaviour is the exploration-exploitation decision, which describes the time at which foraging animals choose to abandon a depleting food supply. Here we use quantitative genetic analysis to examine the decision to leave a food patch in Caenorhabditis elegans. We find that patch-leaving is a multigenic trait regulated in part by naturally-occurring noncoding polymorphisms in tyra-3, which encodes a G protein-coupled catecholamine receptor related to vertebrate adrenergic receptors. tyra-3 acts in sensory neurons that detect food-related cues, suggesting that the internal catecholamines detected by tyra-3 regulate responses to external conditions. These results indicate that genetic variation and environmental cues can converge on common circuits to regulate behaviour, and suggest that catecholamines have an ancient role in regulating behavioural decisions.
Variation in the levels of co-regulated proteins that function within networks in an outbred yeast population is not driven by variation in the corresponding transcripts.
Networks of co-regulated transcripts in genetically diverse populations have been studied extensively, but little is known about the degree to which these networks cause similar co-variation at the protein level. We quantified 354 proteins in a genetically diverse population of yeast segregants, which allowed for the first time construction of a coherent protein co-variation matrix. We identified tightly co-regulated groups of 36 and 93 proteins that were made up predominantly of genes involved in ribosome biogenesis and amino acid metabolism, respectively. Even though the ribosomal genes were tightly co-regulated at both the protein and transcript levels, genetic regulation of proteins was entirely distinct from that of transcripts, and almost no genes in this network showed a significant correlation between protein and transcript levels. This result calls into question the widely held belief that in yeast, as opposed to higher eukaryotes, ribosomal protein levels are regulated primarily by regulating transcript levels. Furthermore, although genetic regulation of the amino acid network was more similar for proteins and transcripts, regression analysis demonstrated that even here, proteins vary predominantly as a result of non-transcriptional variation. We also found that cis regulation, which is common in the transcriptome, is rare at the level of the proteome. We conclude that most inter-individual variation in levels of these particular high abundance proteins in this genetically diverse population is not caused by variation of their underlying transcripts.
The level of protein produced by each gene corresponds approximately to the level of mRNA transcript produced by that gene: so high-abundance proteins, like those involved in protein synthesis, are represented by high-abundance transcripts, whereas low-abundance proteins, like those involved in signaling pathways, are represented by low-abundance transcripts. Furthermore, genetic variation can cause variation in transcript levels for the same gene between different individuals. These two observations have led to the assumption that inter-individual variation in transcript levels for any particular gene causes corresponding variation in protein levels. However, this need not be the case, because protein levels could be controlled not only by regulating transcript levels but also by regulating protein translation and stability. Because inter-individual variation in the levels of the transcript for any particular gene is typically less than 3-fold, rather than orders of magnitude, it is possible that the predominant cause of inter-individual variation in levels of any particular protein is transcription-independent regulation of protein levels. Here, we look in a genetically diverse population of 95 yeast strains at the genetic variation that leads in turn to variation in levels of 354 proteins that function within co-regulated networks. We find that the between-strain variation predominantly reflects transcription-independent mechanisms. If this result is typical of the proteome as a whole, it suggests that protein levels in genetically diverse populations cannot be accurately inferred from levels of their underlying transcripts.
Aging and longevity are considered to be highly complex genetic traits. In order to gain insight into aging as a polygenic trait, we employed an outbred Saccharomyces cerevisiae model, generated by crossing a vineyard strain RM11 and a laboratory strain S288c, to identify quantitative trait loci that control chronological lifespan. Among the major loci that regulate chronological lifespan in this cross, one genetic linkage was found to be congruent with a previously mapped locus that controls telomere length variation. We found that a single nucleotide polymorphism in BUL2, encoding a component of an ubiquitin ligase complex involved in trafficking of amino acid permeases, controls chronological lifespan and telomere length as well as amino acid uptake. Cellular amino acid availability changes conferred by the BUL2 polymorphism alter telomere length by modulating activity of a transcription factor Gln3. Among the GLN3 transcriptional targets relevant to this phenotype, we identified Wtm1, whose upregulation promotes nuclear retention of ribonucleotide reductase (RNR) components and inhibits the assembly of the RNR enzyme complex during S-phase. Inhibition of RNR is one of the mechanisms by which Gln3 modulates telomere length. Identification of a polymorphism in BUL2 in this outbred yeast population revealed a link among cellular amino acid availability, chronological lifespan, and telomere length control.
Dietary restriction promotes longevity in many species, ranging from yeast to primates, and delays aging-related pathologies including cancer in rodent models. There is considerable interest in understanding how nutrient limitation mediates these beneficial effects. Much of what we have learned about the genetics of aging comes from studying isogenic model organisms, where the effects of single gene changes can be examined independently of other genetic alterations. In order to explore a broader spectrum of genetic variation and to gain insight into aging-related phenotypes as polygenic traits, we analyzed the chronological lifespan of 122 S. cerevisiae strains derived from a cross between laboratory and vineyard yeast strains. The major genetic locus controlling chronological lifespan was found to be identical to a previously mapped locus that controls telomere length. Identification of the responsible polymorphism in BUL2, a gene involved in controlling amino acid permeases, allowed us to establish a previously unrecognized link among cellular amino acid intake, chronological aging, and telomere maintenance. While human epidemiological studies have linked shortened telomeres with increased mortality, it is unclear how these processes are connected. Our results suggest that, in yeast, reduced amino acid uptake and consequent reduced nutrient signaling extend chronological lifespan but reduce telomere length.
Translation termination is a highly controlled process in the cell. In Saccharomyces cerevisiae, various regulatory factors employ genetic and epigenetic mechanisms to control this process. We used a quantitative dual luciferase reporter assay to demonstrate a difference in translation termination efficiency between two different yeast strains, BY4724 and RM11-1a. We then used a recently developed linkage mapping technique, extreme QTL mapping (X-QTL), to show that this difference is largely explained by a coding polymorphism in TRM10 (which encodes a tRNA–methylating enzyme) and a regulatory polymorphism in SUP45 (which encodes one of the yeast translation termination factors). BY and RM carry variants of TRM10 and SUP45 with opposite effects on translation termination efficiency. These variants are common among 63 diverse S. cerevisiae strains and are in strong linkage disequilibrium with each other. This observation suggests that selection may have favored allelic combinations of the two genes that maintain an intermediate level of translation termination efficiency. Our results also provide genetic evidence for a new role of Trm10p in translation termination efficiency.
Translation, the process of protein synthesis from messenger RNA (mRNA), cannot be successfully completed without proper termination. The ends of the mRNA coding regions are marked by one of the three stop codons, which are recognized by termination factors rather than by the transfer RNAs (tRNAs) that match amino acids to the corresponding codons. Like most biological processes, translation termination is not perfect. Occasionally, tRNAs bind to stop codons, resulting in polypeptides with additional amino acids beyond the normal stop position—a phenomenon known as readthrough. Perturbations that affect the balance between termination factors and tRNAs will change readthrough. Here we demonstrate the effect of two perturbations on translation termination efficiency in the context of natural genetic variation. We show that a difference in readthrough between a laboratory and a vineyard strain of yeast is largely due to two genetic variants. One variant affects the expression level of a key translation termination factor; the other modifies the activity of a tRNA–methylating enzyme. We also show that natural selection has favored an intermediate level of readthrough.
A sperm-delivered toxin and an embryo-expressed antidote form a co-adapted gene complex in C. elegans that promotes its own transmission to the detriment of organisms carrying it.
The evolutionary fate of an allele ordinarily depends on its contribution to host fitness. Occasionally, however, genetic elements arise that are able to gain a transmission advantage while simultaneously imposing a fitness cost on their hosts. We previously discovered one such element in C. elegans that gains a transmission advantage through a combination of paternal-effect killing and zygotic self-rescue. Here we demonstrate that this element is composed of a sperm-delivered toxin, peel-1, and an embryo-expressed antidote, zeel-1. peel-1 and zeel-1 are located adjacent to one another in the genome and co-occur in an insertion/deletion polymorphism. peel-1 encodes a novel four-pass transmembrane protein that is expressed in sperm and delivered to the embryo via specialized, sperm-specific vesicles. In the absence of zeel-1, sperm-delivered PEEL-1 causes lethal defects in muscle and epidermal tissue at the 2-fold stage of embryogenesis. zeel-1 is expressed transiently in the embryo and encodes a novel six-pass transmembrane domain fused to a domain with sequence similarity to zyg-11, a substrate-recognition subunit of an E3 ubiquitin ligase. zeel-1 appears to have arisen recently, during an expansion of the zyg-11 family, and the transmembrane domain of zeel-1 is required and partially sufficient for antidote activity. Although PEEL-1 and ZEEL-1 normally function in embryos, these proteins can act at other stages as well. When expressed ectopically in adults, PEEL-1 kills a variety of cell types, and ectopic expression of ZEEL-1 rescues these effects. Our results demonstrate that the tight physical linkage between two novel transmembrane proteins has facilitated their co-evolution into an element capable of promoting its own transmission to the detriment of organisms carrying it.
Natural selection typically favors only those genetic variants that increase the overall fitness of the organism. Occasionally, however, variants arise that are able to increase their representation in future generations, while simultaneously reducing the fertility or fecundity of their hosts. Although such variants occur in a wide variety of taxa, their genetic bases and molecular mechanisms remain poorly understood. Here we demonstrate that one such variant in the roundworm C. elegans is composed of two adjacent genes: a sperm-delivered toxin and an embryo-expressed antidote. The toxin protein is expressed in sperm and delivered to the embryo upon fertilization. In the presence of the toxin, embryos that don't inherit the antidote gene die during late embryogenesis, whereas those that do develop normally. Both the toxin and the antidote genes encode transmembrane proteins, and both are evolutionarily novel. Our results imply that the tight physical linkage between these two novel genes has facilitated their evolution into a co-adapted gene complex capable of promoting its own transmission to the detriment of host fitness.
Mutation generates the heritable variation that genetic drift and natural selection shape. In classical quantitative genetic models, drift is a function of the effective population size and acts uniformly across traits, while mutation and selection act trait-specifically. We identified thousands of quantitative trait loci (QTL) influencing transcript abundance traits in a cross of two C. elegans strains; although trait-specific mutation and selection explained some of the observed pattern of QTL distribution, the pattern was better explained by trait-independent variation in the intensity of selection on linked sites. Our results suggest that traits in C. elegans exhibit different levels of variation less because of their own attributes than because of differences in the effective population sizes of the genomic regions harboring their underlying loci.