The complex genetic and molecular basis of a model quantitative trait

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

The complex role of genetic background in shaping the effects of spontaneous and induced mutations

Spontaneous and induced mutations frequently show different phenotypic effects across genetically distinct individuals. It is generally appreciated that these background effects mainly result from genetic interactions between the mutations and segregating loci. However, the architectures and molecular bases of these genetic interactions are not well understood. Recent work in a number of model organisms has tried to advance knowledge of background effects both by using large‐scale screens to find mutations that exhibit this phenomenon and by identifying the specific loci that are involved. Here, we review this body of research, emphasizing in particular the insights it provides into both the prevalence of background effects across different mutations and the mechanisms that cause these background effects.

A large fraction of mutations show different effects in distinct individuals.

These background effects are mainly caused by epistasis with segregating loci.

Mapping studies show a diversity of genetic architectures can be involved.

Genetically complex changes in gene expression are often, but not always, causative.

Identification of Suppressor of Clathrin Deficiency-1 (SCD1) and Its Connection to Clathrin-Mediated Endocytosis in Saccharomyces cerevisiae

Clathrin is a major coat protein involved in vesicle formation during endocytosis and transport in the endosomal/trans Golgi system. Clathrin is required for normal growth of yeast (Saccharomyces cerevisiae) and in some genetic backgrounds deletion of the clathrin heavy chain gene (CHC1) is lethal. Our lab defined a locus referred to as “suppressor of clathrin deficiency” (SCD1). In the presence of the scd1-v allele (“v” – viable), yeast cells lacking clathrin heavy chain survive but grow slowly, are morphologically abnormal and have many membrane trafficking defects. In the presence of scd1-i (“i”- inviable), chc1∆ causes lethality. As a strategy to identify SCD1, we used pooled linkage analysis and whole genome sequencing. Here, we report that PAL2 (YHR097C) is the SCD1 locus. pal2∆ is synthetic lethal with chc1∆; whereas a deletion of its paralog, PAL1, is not synthetic lethal with clathrin deficiency. Like Pal1, Pal2 has two NPF motifs that are potential binding sites for EH domain proteins such as the early endocytic factor Ede1, and Pal2 associates with Ede1. Also, GFP-tagged Pal2p localizes to cortical patches containing other immobile phase endocytic coat factors. Overall, our data show that PAL2 is the SCD1 locus and the Pal2 protein has characteristics of an early factor involved in clathrin-mediated endocytosis.

Linkage mapping of yeast cross protection connects gene expression variation to a higher-order organismal trait

Gene expression variation is extensive in nature, and is hypothesized to play a major role in shaping phenotypic diversity. However, connecting differences in gene expression across individuals to higher-order organismal traits is not trivial. In many cases, gene expression variation may be evolutionarily neutral, and in other cases expression variation may only affect phenotype under specific conditions. To understand connections between gene expression variation and stress defense phenotypes, we have been leveraging extensive natural variation in the gene expression response to acute ethanol in laboratory and wild Saccharomyces cerevisiae strains. Previous work found that the genetic architecture underlying these expression differences included dozens of “hotspot” loci that affected many transcripts in trans. In the present study, we provide new evidence that one of these expression QTL hotspot loci affects natural variation in one particular stress defense phenotype—ethanol-induced cross protection against severe doses of H₂O₂. A major causative polymorphism is in the heme-activated transcription factor Hap1p, which we show directly impacts cross protection, but not the basal H₂O₂ resistance of unstressed cells. This provides further support that distinct cellular mechanisms underlie basal and acquired stress resistance. We also show that Hap1p-dependent cross protection relies on novel regulation of cytosolic catalase T (Ctt1p) during ethanol stress in a wild oak strain. Because ethanol accumulation precedes aerobic respiration and accompanying reactive oxygen species formation, wild strains with the ability to anticipate impending oxidative stress would likely be at an advantage. This study highlights how strategically chosen traits that better correlate with gene expression changes can improve our power to identify novel connections between gene expression variation and higher-order organismal phenotypes.

A major goal in genetics is to understand how individuals with different genetic makeups respond to their environment. Understanding these “gene-environment interactions” is important for the development of personalized medicine. For example, gene-environment interactions can explain why some people are more sensitive to certain drugs or are more likely to get certain cancers. While the underlying causes of gene-environment interactions are unclear, one possibility is that differences in gene expression across individuals are responsible. In this study, we examined that possibility using baker’s yeast as a model. We were interested in a phenomenon called acquired stress resistance, where cells exposed to a mild dose of one stress can become resistant to an otherwise lethal dose of severe stress. This response is observed in diverse organisms ranging from bacteria to humans, though the specific mechanisms governing acquisition of higher stress resistance are poorly understood. To understand the differences between yeast strains with and without the ability to acquire further stress resistance, we employed genetic mapping. We found that part of the variation in acquired stress resistance was due to sequence differences in a key regulatory protein, thus providing new insight into how different individuals respond to acute environmental change.

The Stress-Inducible Peroxidase TSA2 Underlies a Conditionally Beneficial Chromosomal Duplication in Saccharomyces cerevisiae

Although chromosomal duplications are often deleterious, in some cases they enhance cells’ abilities to tolerate specific genetic or environmental challenges. Identifying the genes that confer these conditionally beneficial effects to particular chromosomal duplications can improve our understanding of the genetic and molecular mechanisms that enable certain aneuploidies to persist in cell populations and contribute to disease and evolution. Here, we perform a screen for spontaneous mutations that improve the tolerance of haploid Saccharomyces cerevisiae to hydrogen peroxide. Chromosome IV duplication is the most frequent mutation, as well as the only change in chromosomal copy number seen in the screen. Using a genetic mapping strategy that involves systematically deleting segments of a duplicated chromosome, we show that the chromosome IV’s duplication effect is largely due to the generation of a second copy of the stress-inducible cytoplasmic thioredoxin peroxidase TSA2. Our findings add to a growing body of literature that shows the conditionally beneficial effects of chromosomal duplication are typically mediated by a small number of genes that enhance tolerance to specific stresses when their copy numbers are increased.

Naturally Segregating Variation at Ugt86Dd Contributes to Nicotine Resistance in Drosophila melanogaster

Identifying the sequence polymorphisms underlying complex trait variation is a key goal of genetics research, since knowing the precise causative molecular events allows insight into the pathways governing trait variation. Genetic analysis of complex traits in model systems regularly starts by constructing QTL maps, but generally fails to identify causative sequence polymorphisms. Previously we mapped a series of QTL contributing to resistance to nicotine in a Drosophila melanogaster multiparental mapping resource and here use a battery of functional tests to resolve QTL to the molecular level. One large-effect QTL resided over a cluster of UDP-glucuronosyltransferases, and quantitative complementation tests using deficiencies eliminating subsets of these detoxification genes revealed allelic variation impacting resistance. RNAseq showed that Ugt86Dd had significantly higher expression in genotypes that are more resistant to nicotine, and anterior midgut-specific RNA interference (RNAi) of this gene reduced resistance. We discovered a segregating 22-bp frameshift deletion in Ugt86Dd, and accounting for the InDel during mapping largely eliminates the QTL, implying the event explains the bulk of the effect of the mapped locus. CRISPR/Cas9 editing of a relatively resistant genotype to generate lesions in Ugt86Dd that recapitulate the naturally occurring putative loss-of-function allele, leads to a large reduction in resistance. Despite this major effect of the deletion, the allele appears to be very rare in wild-caught populations and likely explains only a small fraction of the natural variation for the trait. Nonetheless, this putatively causative coding InDel can be a launchpad for future mechanistic exploration of xenobiotic detoxification.

Variability of DNA Methylation within Schizophrenia Risk Loci across Subregions of Human Hippocampus

Identification of 108 genomic regions significantly associated with schizophrenia risk by the Psychiatric Genomics Consortium was a milestone for the field, and much work is now focused on determining the mechanism of risk associated with each locus. Within these regions, we investigated variability of DNA methylation, a low-level cellular phenotype closely linked to genotype, in two highly similar cellular populations sampled from the human hippocampus, to draw inferences about the elaboration of genotype to phenotype within these loci enriched for schizophrenia risk. DNA methylation was assessed with the Illumina HumanMethylation450 BeadArray in tissue laser-microdissected from the stratum oriens of subfield CA1 or CA2/3, regions having unique connectivity with intrinsic and extrinsic fiber systems within the hippocampus. Samples consisted of postmortem human hippocampus tissue from eight schizophrenia patients, eight bipolar disorder patients, and eight healthy control subjects. Within these genomic regions, we observed far greater difference in methylation patterns between circuit locations within subjects than in a single subregion between subjects across diagnostic groups, demonstrating the complexity of genotype to phenotype elaboration across the diverse circuitry of the human brain.

The Saccharomyces cerevisiae Cdk8 Mediator Represses AQY1 Transcription by Inhibiting Set1p-Dependent Histone Methylation

In the budding yeast Saccharomyces cerevisiae, nutrient depletion induces massive transcriptional reprogramming that relies upon communication between transcription factors, post-translational histone modifications, and the RNA polymerase II holoenzyme complex. Histone H3Lys4 methylation (H3Lys4 me), regulated by the Set1p-containing COMPASS methyltransferase complex and Jhd2p demethylase, is one of the most well-studied histone modifications. We previously demonstrated that the RNA polymerase II mediator components cyclin C-Cdk8p inhibit locus-specific H3Lys4 3me independently of Jhd2p. Here, we identify loci subject to cyclin C- and Jhd2p-dependent histone H3Lys4 3me inhibition using chromatin immunoprecipitation (ChIP)-seq. We further characterized the independent and combined roles of cyclin C and Jhd2p in controlling H3Lys4 3me and transcription in response to fermentable and nonfermentable carbon at multiple loci. These experiments suggest that H3Lys4 3me alone is insufficient to induce transcription. Interestingly, we identified an unexpected role for cyclin C-Cdk8p in repressing AQY1 transcription, an aquaporin whose expression is normally induced during nutrient deprivation. These experiments, combined with previous work in other labs, support a two-step model in which cyclin C-Cdk8p mediate AQY1 transcriptional repression by stimulating transcription factor proteolysis and preventing Set1p recruitment to the AQY1 locus.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Gene-Environment Interactions in Stress Response Contribute Additively to a Genotype-Environment Interaction

How combinations of gene-environment interactions collectively give rise to genotype-environment interactions is not fully understood. To shed light on this problem, we genetically dissected an environment-specific poor growth phenotype in a cross of two budding yeast strains. This phenotype is detectable when certain segregants are grown on ethanol at 37°C (‘E37’), a condition that differs from the standard culturing environment in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). Using recurrent backcrossing with phenotypic selection, we identified 16 contributing loci. To examine how these loci interact with each other and the environment, we focused on a subset of four loci that together can lead to poor growth in E37. We measured the growth of all 16 haploid combinations of alleles at these loci in all four possible combinations of carbon source (ethanol or glucose) and temperature (30 or 37°C) in a nearly isogenic population. This revealed that the four loci act in an almost entirely additive manner in E37. However, we also found that these loci have weaker effects when only carbon source or temperature is altered, suggesting that their effect magnitudes depend on the severity of environmental perturbation. Consistent with such a possibility, cloning of three causal genes identified factors that have unrelated functions in stress response. Thus, our results indicate that polymorphisms in stress response can show effects that are intensified by environmental stress, thereby resulting in major genotype-environment interactions when multiple of these variants co-occur.

Determining the genetic and molecular mechanisms that give rise to genotype-environment interaction (‘GxE’) is important for many areas of biology, including agriculture, evolution, and medicine. To help advance knowledge regarding this topic, we dissect the genetic basis of an example of GxE in which certain Saccharomyces cerevisiae cross progeny show extremely poor growth specifically on ethanol at 37°C. This environment differs from the standard condition used for culturing budding yeast in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). We provide evidence that poor growth on ethanol at 37°C is caused by a number of predominantly additive loci that individually exhibit gene-environment interactions with both carbon source and temperature. These loci show their largest effects when carbon source and temperature are simultaneously modified, indicating their effect magnitudes may be influenced by the severity of environmental stress. Consistent with this possibility, we clone three causal genes and find they encode functionally unrelated components of stress response. Our work suggests that polymorphisms in stress response can contribute additively to genotype-environment interactions that vary in intensity across conditions in a stress level-dependent manner.