Correction: Genetic and metabolomic architecture of variation in diet restriction-mediated lifespan extension in Drosophila.

[This corrects the article DOI: 10.1371/journal.pgen.1008835.].

Natural trait variation across Saccharomycotina species.

Among molecular biologists, the group of fungi called Saccharomycotina is famous for its yeasts. These yeasts in turn are famous for what they have in common-genetic, biochemical, and cell-biological characteristics that serve as models for plants and animals. But behind the apparent homogeneity of Saccharomycotina species lie a wealth of differences. In this review, we discuss traits that vary across the Saccharomycotina subphylum. We describe cases of bright pigmentation; a zoo of cell shapes; metabolic specialties; and species with unique rules of gene regulation. We discuss the genetics of this diversity and why it matters, including insights into basic evolutionary principles with relevance across Eukarya.

Joint effects of genes underlying a temperature specialization tradeoff in yeast.

A central goal of evolutionary genetics is to understand, at the molecular level, how organisms adapt to their environments. For a given trait, the answer often involves the acquisition of variants at unlinked sites across the genome. Genomic methods have achieved landmark successes in pinpointing these adaptive loci. To figure out how a suite of adaptive alleles work together, and to what extent they can reconstitute the phenotype of interest, requires their transfer into an exogenous background. We studied the joint effect of adaptive, gain-of-function thermotolerance alleles at eight unlinked genes from Saccharomyces cerevisiae, when introduced into a thermosensitive sister species, S. paradoxus. Although the loci damped each other's beneficial impact (that is, they were subject to negative epistasis), most boosted high-temperature growth alone and in combination, and none was deleterious. The complete set of eight genes was sufficient to confer ~15% of the S. cerevisiae thermotolerance phenotype in the S. paradoxus background. The same loci also contributed to a heretofore unknown advantage in cold growth by S. paradoxus. Together, our data establish temperature resistance in yeasts as a model case of a genetically complex evolutionary tradeoff, which can be partly reconstituted from the sequential assembly of unlinked underlying loci.

Genetic and metabolomic architecture of variation in diet restriction-mediated lifespan extension in Drosophila.

In most organisms, dietary restriction (DR) increases lifespan. However, several studies have found that genotypes within the same species vary widely in how they respond to DR. To explore the mechanisms underlying this variation, we exposed 178 inbred Drosophila melanogaster lines to a DR or ad libitum (AL) diet, and measured a panel of 105 metabolites under both diets. Twenty four out of 105 metabolites were associated with the magnitude of the lifespan response. These included proteinogenic amino acids and metabolites involved in α-ketoglutarate (α-KG)/glutamine metabolism. We confirm the role of α-KG/glutamine synthesis pathways in the DR response through genetic manipulations. We used covariance network analysis to investigate diet-dependent interactions between metabolites, identifying the essential amino acids threonine and arginine as "hub" metabolites in the DR response. Finally, we employ a novel metabolic and genetic bipartite network analysis to reveal multiple genes that influence DR lifespan response, some of which have not previously been implicated in DR regulation. One of these is CCHa2R, a gene that encodes a neuropeptide receptor that influences satiety response and insulin signaling. Across the lines, variation in an intronic single nucleotide variant of CCHa2R correlated with variation in levels of five metabolites, all of which in turn were correlated with DR lifespan response. Inhibition of adult CCHa2R expression extended DR lifespan of flies, confirming the role of CCHa2R in lifespan response. These results provide support for the power of combined genomic and metabolomic analysis to identify key pathways underlying variation in this complex quantitative trait.

A role for worm cutl-24 in background- and parent-of-origin-dependent ER stress resistance.

BACKGROUND: Organisms in the wild can acquire disease- and stress-resistance traits that outstrip the programs endogenous to humans. Finding the molecular basis of such natural resistance characters is a key goal of evolutionary genetics. Standard statistical-genetic methods toward this end can perform poorly in organismal systems that lack high rates of meiotic recombination, like Caenorhabditis worms. RESULTS: Here we discovered unique ER stress resistance in a wild Kenyan C. elegans isolate, which in inter-strain crosses was passed by hermaphrodite mothers to hybrid offspring. We developed an unbiased version of the reciprocal hemizygosity test, RH-seq, to explore the genetics of this parent-of-origin-dependent phenotype. Among top-scoring gene candidates from a partial-coverage RH-seq screen, we focused on the neuronally-expressed, cuticlin-like gene cutl-24 for validation. In gene-disruption and controlled crossing experiments, we found that cutl-24 was required in Kenyan hermaphrodite mothers for ER stress tolerance in their inter-strain hybrid offspring; cutl-24 was also a contributor to the trait in purebred backgrounds. CONCLUSIONS: These data establish the Kenyan strain allele of cutl-24 as a determinant of a natural stress-resistant state, and they set a precedent for the dissection of natural trait diversity in invertebrate animals without the need for a panel of meiotic recombinants.

Transposon insertional mutagenesis in Saccharomyces uvarum reveals trans-acting effects influencing species-dependent essential genes.

To understand how complex genetic networks perform and regulate diverse cellular processes, the function of each individual component must be defined. Comprehensive phenotypic studies of mutant alleles have been successful in model organisms in determining what processes depend on the normal function of a gene. These results are often ported to newly sequenced genomes by using sequence homology. However, sequence similarity does not always mean identical function or phenotype, suggesting that new methods are required to functionally annotate newly sequenced species. We have implemented comparative analysis by high-throughput experimental testing of gene dispensability in Saccharomyces uvarum, a sister species of Saccharomyces cerevisiae. We created haploid and heterozygous diploid Tn7 insertional mutagenesis libraries in S. uvarum to identify species-dependent essential genes, with the goal of detecting genes with divergent functions and/or different genetic interactions. Comprehensive gene dispensability comparisons with S. cerevisiae predicted diverged dispensability at 12% of conserved orthologs, and validation experiments confirmed 22 differentially essential genes. Despite their differences in essentiality, these genes were capable of cross-species complementation, demonstrating that trans-acting factors that are background-dependent contribute to differential gene essentiality. This study shows that direct experimental testing of gene disruption phenotypes across species can inform comparative genomic analyses and improve gene annotations. Our method can be widely applied in microorganisms to further our understanding of genome evolution.

Polygenic evolution of a sugar specialization trade-off in yeast.

The evolution of novel traits can involve many mutations scattered throughout the genome. Detecting and validating such a suite of alleles, particularly if they arose long ago, remains a key challenge in evolutionary genetics. Here we dissect an evolutionary trade-off of unprecedented genetic complexity between long-diverged species. When cultured in 1% glucose medium supplemented with galactose, Saccharomyces cerevisiae, but not S. bayanus or other Saccharomyces species, delayed commitment to galactose metabolism until glucose was exhausted. Promoters of seven galactose (GAL) metabolic genes from S. cerevisiae, when introduced together into S. bayanus, largely recapitulated the delay phenotype in 1% glucose-galactose medium, and most had partial effects when tested in isolation. Variation in GAL coding regions also contributed to the delay when tested individually in 1% glucose-galactose medium. When combined, S. cerevisiae GAL coding regions gave rise to profound growth defects in the S. bayanus background. In medium containing 2.5% glucose supplemented with galactose, wild-type S. cerevisiae repressed GAL gene expression and had a robust growth advantage relative to S. bayanus; transgenesis of S. cerevisiae GAL promoter alleles or GAL coding regions was sufficient for partial reconstruction of these phenotypes. S. cerevisiae GAL genes thus encode a regulatory program of slow induction and avid repression, and a fitness detriment during the glucose-galactose transition but a benefit when glucose is in excess. Together, these results make clear that genetic mapping of complex phenotypes is within reach, even in deeply diverged species.

S1PR3 Mediates Itch and Pain via Distinct TRP Channel-Dependent Pathways.

Sphingosine 1-phosphate (S1P) is a bioactive signaling lipid associated with a variety of chronic pain and itch disorders. S1P signaling has been linked to cutaneous pain, but its role in itch has not yet been studied. Here, we find that S1P triggers itch and pain in male mice in a concentration-dependent manner, with low levels triggering acute itch alone and high levels triggering both pain and itch. Ca2+ imaging and electrophysiological experiments revealed that S1P signals via S1P receptor 3 (S1PR3) and TRPA1 in a subset of pruriceptors and via S1PR3 and TRPV1 in a subset of heat nociceptors. Consistent with these findings, S1P-evoked itch behaviors are selectively lost in mice lacking TRPA1, whereas S1P-evoked acute pain and heat hypersensitivity are selectively lost in mice lacking TRPV1. We conclude that S1P acts via different cellular and molecular mechanisms to trigger itch and pain. Our discovery elucidates the diverse roles that S1P signaling plays in somatosensation and provides insight into how itch and pain are discriminated in the periphery.SIGNIFICANCE STATEMENT Itch and pain are major health problems with few effective treatments. Here, we show that the proinflammatory lipid sphingosine 1-phosphate (S1P) and its receptor, S1P receptor 3 (S1PR3), trigger itch and pain behaviors via distinct molecular and cellular mechanisms. Our results provide a detailed understanding of the roles that S1P and S1PR3 play in somatosensation, highlighting their potential as targets for analgesics and antipruritics, and provide new insight into the mechanistic underpinnings of itch versus pain discrimination in the periphery.

Predicting Responses to Contemporary Environmental Change Using Evolutionary Response Architectures.

Rapid environmental change currently presents a major threat to global biodiversity and ecosystem functions, and understanding impacts on individual populations is critical to creating reliable predictions and mitigation plans. One emerging tool for this goal is high-throughput sequencing technology, which can now be used to scan the genome for signs of environmental selection in any species and any system. This explosion of data provides a powerful new window into the molecular mechanisms of adaptation, and although there has been some success in using genomic data to predict responses to selection in fields such as agriculture, thus far genomic data are rarely integrated into predictive frameworks of future adaptation in natural populations. Here, we review both theoretical and empirical studies of adaptation to rapid environmental change, focusing on areas where genomic data are poised to contribute to our ability to estimate species and population persistence and adaptation. We advocate for the need to study and model evolutionary response architectures, which integrate spatial information, fitness estimates, and plasticity with genetic architecture. Understanding how these factors contribute to adaptive responses is essential in efforts to predict the responses of species and ecosystems to future environmental change.

Cross-phenotype association tests uncover genes mediating nutrient response in Drosophila.

BACKGROUND: Obesity-related diseases are major contributors to morbidity and mortality in the developed world. Molecular diagnostics and targets of therapies to combat nutritional imbalance are urgently needed in the clinic. Invertebrate animals have been a cornerstone of basic research efforts to dissect the genetics of metabolism and nutrient response. We set out to use fruit flies reared on restricted and nutrient-rich diets to identify genes associated with starvation resistance, body mass and composition, in a survey of genetic variation across the Drosophila Genetic Reference Panel (DGRP). RESULTS: We measured starvation resistance, body weight and composition in DGRP lines on each of two diets and used several association mapping strategies to harness this panel of phenotypes for molecular insights. We tested DNA sequence variants for a relationship with single metabolic traits and with multiple traits at once, using a scheme for cross-phenotype association mapping; we focused our association tests on homologs of human disease genes and common polymorphisms; and we tested for gene-by-diet interactions. The results revealed gene and gene-by-diet associations between 17 variants and body mass, whole-body triglyceride and glucose content, or starvation resistance. Focused molecular experiments validated the role in body mass of an uncharacterized gene, CG43921 (which we rename heavyweight), and previously unknown functions for the diacylglycerol kinase rdgA, the huntingtin homolog htt, and the ceramide synthase schlank in nutrient-dependent body mass, starvation resistance, and lifespan. CONCLUSIONS: Our findings implicate a wealth of gene candidates in fly metabolism and nutrient response, and ascribe novel functions to htt, rdgA, hwt and schlank.

Genome wide association identifies novel loci involved in fungal communication.

Understanding how genomes encode complex cellular and organismal behaviors has become the outstanding challenge of modern genetics. Unlike classical screening methods, analysis of genetic variation that occurs naturally in wild populations can enable rapid, genome-scale mapping of genotype to phenotype with a medium-throughput experimental design. Here we describe the results of the first genome-wide association study (GWAS) used to identify novel loci underlying trait variation in a microbial eukaryote, harnessing wild isolates of the filamentous fungus Neurospora crassa. We genotyped each of a population of wild Louisiana strains at 1 million genetic loci genome-wide, and we used these genotypes to map genetic determinants of microbial communication. In N. crassa, germinated asexual spores (germlings) sense the presence of other germlings, grow toward them in a coordinated fashion, and fuse. We evaluated germlings of each strain for their ability to chemically sense, chemotropically seek, and undergo cell fusion, and we subjected these trait measurements to GWAS. This analysis identified one gene, NCU04379 (cse-1, encoding a homolog of a neuronal calcium sensor), at which inheritance was strongly associated with the efficiency of germling communication. Deletion of cse-1 significantly impaired germling communication and fusion, and two genes encoding predicted interaction partners of CSE1 were also required for the communication trait. Additionally, mining our association results for signaling and secretion genes with a potential role in germling communication, we validated six more previously unknown molecular players, including a secreted protease and two other genes whose deletion conferred a novel phenotype of increased communication and multi-germling fusion. Our results establish protein secretion as a linchpin of germling communication in N. crassa and shed light on the regulation of communication molecules in this fungus. Our study demonstrates the power of population-genetic analyses for the rapid identification of genes contributing to complex traits in microbial species.

Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation.

Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Small-molecule metabolites are one category of critical cellular intermediates that can influence as well as be a target of cellular regulations. Because metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. Here we develop and apply a network reconstruction approach that simultaneously integrates six different types of data: endogenous metabolite concentration, RNA expression, DNA variation, DNA-protein binding, protein-metabolite interaction, and protein-protein interaction data, to construct probabilistic causal networks that elucidate the complexity of cell regulation in a segregating yeast population. Because many of the metabolites are found to be under strong genetic control, we were able to employ a causal regulator detection algorithm to identify causal regulators of the resulting network that elucidated the mechanisms by which variations in their sequence affect gene expression and metabolite concentrations. We examined all four expression quantitative trait loci (eQTL) hot spots with colocalized metabolite QTLs, two of which recapitulated known biological processes, while the other two elucidated novel putative biological mechanisms for the eQTL hot spots.

Genetics and regulatory impact of alternative polyadenylation in human B-lymphoblastoid cells.

Gene expression varies widely between individuals of a population, and regulatory change can underlie phenotypes of evolutionary and biomedical relevance. A key question in the field is how DNA sequence variants impact gene expression, with most mechanistic studies to date focused on the effects of genetic change on regulatory regions upstream of protein-coding sequence. By contrast, the role of RNA 3'-end processing in regulatory variation remains largely unknown, owing in part to the challenge of identifying functional elements in 3' untranslated regions. In this work, we conducted a genomic survey of transcript ends in lymphoblastoid cells from genetically distinct human individuals. Our analysis mapped the cis-regulatory architecture of 3' gene ends, finding that transcript end positions did not fall randomly in untranslated regions, but rather preferentially flanked the locations of 3' regulatory elements, including miRNA sites. The usage of these transcript length forms and motifs varied across human individuals, and polymorphisms in polyadenylation signals and other 3' motifs were significant predictors of expression levels of the genes in which they lay. Independent single-gene experiments confirmed the effects of polyadenylation variants on steady-state expression of their respective genes, and validated the regulatory function of 3' cis-regulatory sequence elements that mediated expression of these distinct RNA length forms. Focusing on the immune regulator IRF5, we established the effect of natural variation in RNA 3'-end processing on regulatory response to antigen stimulation. Our results underscore the importance of two mechanisms at play in the genetics of 3'-end variation: the usage of distinct 3'-end processing signals and the effects of 3' sequence elements that determine transcript fate. Our findings suggest that the strategy of integrating observed 3'-end positions with inferred 3' regulatory motifs will prove to be a critical tool in continued efforts to interpret human genome variation.

Negative feedback confers mutational robustness in yeast transcription factor regulation.

Organismal fitness depends on the ability of gene networks to function robustly in the face of environmental and genetic perturbations. Understanding the mechanisms of this stability is one of the key aims of modern systems biology. Dissecting the basis of robustness to mutation has proven a particular challenge, with most experimental models relying on artificial DNA sequence variants engineered in the laboratory. In this work, we hypothesized that negative regulatory feedback could stabilize gene expression against the disruptions that arise from natural genetic variation. We screened yeast transcription factors for feedback and used the results to establish ROX1 (Repressor of hypOXia) as a model system for the study of feedback in circuit behaviors and its impact across genetically heterogeneous populations. Mutagenesis experiments revealed the mechanism of Rox1 as a direct transcriptional repressor at its own gene, enabling a regulatory program of rapid induction during environmental change that reached a plateau of moderate steady-state expression. Additionally, in a given environmental condition, Rox1 levels varied widely across genetically distinct strains; the ROX1 feedback loop regulated this variation, in that the range of expression levels across genetic backgrounds showed greater spread in ROX1 feedback mutants than among strains with the ROX1 feedback loop intact. Our findings indicate that the ROX1 feedback circuit is tuned to respond to perturbations arising from natural genetic variation in addition to its role in induction behavior. We suggest that regulatory feedback may be an important element of the network architectures that confer mutational robustness across biology.

Inferring evolutionary histories of pathway regulation from transcriptional profiling data.

One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolution-based methods to infer evidence for natural selection from expression data are at a premium in the field, and to date, phylogenetic approaches have not been well-suited to address the question in the small sets of taxa profiled in standard surveys of gene expression. We have developed a strategy to infer evolutionary histories from expression profiles by analyzing suites of genes of common function. In a manner conceptually similar to molecular evolution models in which the evolutionary rates of DNA sequence at multiple loci follow a gamma distribution, we modeled expression of the genes of an a priori-defined pathway with rates drawn from an inverse gamma distribution. We then developed a fitting strategy to infer the parameters of this distribution from expression measurements, and to identify gene groups whose expression patterns were consistent with evolutionary constraint or rapid evolution in particular species. Simulations confirmed the power and accuracy of our inference method. As an experimental testbed for our approach, we generated and analyzed transcriptional profiles of four Saccharomyces yeasts. The results revealed pathways with signatures of constrained and accelerated regulatory evolution in individual yeasts and across the phylogeny, highlighting the prevalence of pathway-level expression change during the divergence of yeast species. We anticipate that our pathway-based phylogenetic approach will be of broad utility in the search to understand the evolutionary relevance of regulatory change.

Population genomics and local adaptation in wild isolates of a model microbial eukaryote.

Elucidating the connection between genotype, phenotype, and adaptation in wild populations is fundamental to the study of evolutionary biology, yet it remains an elusive goal, particularly for microscopic taxa, which comprise the majority of life. Even for microbes that can be reliably found in the wild, defining the boundaries of their populations and discovering ecologically relevant phenotypes has proved extremely difficult. Here, we have circumvented these issues in the microbial eukaryote Neurospora crassa by using a "reverse-ecology" population genomic approach that is free of a priori assumptions about candidate adaptive alleles. We performed Illumina whole-transcriptome sequencing of 48 individuals to identify single nucleotide polymorphisms. From these data, we discovered two cryptic and recently diverged populations, one in the tropical Caribbean basin and the other endemic to subtropical Louisiana. We conducted high-resolution scans for chromosomal regions of extreme divergence between these populations and found two such genomic "islands." Through growth-rate assays, we found that the subtropical Louisiana population has a higher fitness at low temperature (10 °C) and that several of the genes within these distinct regions have functions related to the response to cold temperature. These results suggest the divergence islands may be the result of local adaptation to the 9 °C difference in average yearly minimum temperature between these two populations. Remarkably, another of the genes identified using this unbiased, whole-genome approach is the well-known circadian oscillator frequency, suggesting that the 2.4°-10.6° difference in latitude between the populations may be another important environmental parameter.

Stem cell transcriptional profiles from mouse subspecies reveal cis-regulatory evolution at translation genes.

A key goal of evolutionary genomics is to harness molecular data to draw inferences about selective forces that have acted on genomes. The field progresses in large part through the development of advanced molecular-evolution analysis methods. Here we explored the intersection between classical sequence-based tests for selection and an empirical expression-based approach, using stem cells from Mus musculus subspecies as a model. Using a test of directional, cis-regulatory evolution across genes in pathways, we discovered a unique program of induction of translation genes in stem cells of the Southeast Asian mouse M. m. castaneus relative to its sister taxa. As a complement, we used sequence analyses to find population-genomic signatures of selection in M. m. castaneus, at the upstream regions of the translation genes, including at transcription factor binding sites. We interpret our data under a model of changes in lineage-specific pressures across Mus musculus in stem cells with high translational capacity. Together, our findings underscore the rigor of integrating expression and sequence-based methods to generate hypotheses about evolutionary events from long ago.

OXR1 maintains the retromer to delay brain aging under dietary restriction.

Dietary restriction (DR) delays aging, but the mechanism remains unclear. We identified polymorphisms in mtd, the fly homolog of OXR1, which influenced lifespan and mtd expression in response to DR. Knockdown in adulthood inhibited DR-mediated lifespan extension in female flies. We found that mtd/OXR1 expression declines with age and it interacts with the retromer, which regulates trafficking of proteins and lipids. Loss of mtd/OXR1 destabilized the retromer, causing improper protein trafficking and endolysosomal defects. Overexpression of retromer genes or pharmacological restabilization with R55 rescued lifespan and neurodegeneration in mtd-deficient flies and endolysosomal defects in fibroblasts from patients with lethal loss-of-function of OXR1 variants. Multi-omic analyses in flies and humans showed that decreased Mtd/OXR1 is associated with aging and neurological diseases. mtd/OXR1 overexpression rescued age-related visual decline and tauopathy in a fly model. Hence, OXR1 plays a conserved role in preserving retromer function and is critical for neuronal health and longevity.

Evolution of a membrane protein regulon in Saccharomyces.

Expression variation is widespread between species. The ability to distinguish regulatory change driven by natural selection from the consequences of neutral drift remains a major challenge in comparative genomics. In this work, we used observations of mRNA expression and promoter sequence to analyze signatures of selection on groups of functionally related genes in Saccharomycete yeasts. In a survey of gene regulons with expression divergence between Saccharomyces cerevisiae and S. paradoxus, we found that most were subject to variation in trans-regulatory factors that provided no evidence against a neutral model. However, we identified one regulon of membrane protein genes controlled by unlinked cis- and trans-acting determinants with coherent effects on gene expression, consistent with a history of directional, nonneutral evolution. For this membrane protein group, S. paradoxus alleles at regulatory loci were associated with elevated expression and altered stress responsiveness relative to other yeasts. In a phylogenetic comparison of promoter sequences of the membrane protein genes between species, the S. paradoxus lineage was distinguished by a short branch length, indicative of strong selective constraint. Likewise, sequence variants within the S. paradoxus population, but not across strains of other yeasts, were skewed toward low frequencies in promoters of genes in the membrane protein regulon, again reflecting strong purifying selection. Our results support a model in which a distinct expression program for the membrane protein genes in S. paradoxus has been preferentially maintained by negative selection as the result of an increased importance to organismal fitness. These findings illustrate the power of integrating expression- and sequence-based tests of natural selection in the study of evolutionary forces that underlie regulatory change.

Polygenic and directional regulatory evolution across pathways in Saccharomyces.

The search to understand how genomes innovate in response to selection dominates the field of evolutionary biology. Powerful molecular evolution approaches have been developed to test individual loci for signatures of selection. In many cases, however, an organism's response to changes in selective pressure may be mediated by multiple genes, whose products function together in a cellular process or pathway. Here we assess the prevalence of polygenic evolution in pathways in the yeasts Saccharomyces cerevisiae and S. bayanus. We first established short-read sequencing methods to detect cis-regulatory variation in a diploid hybrid between the species. We then tested for the scenario in which selective pressure in one species to increase or decrease the activity of a pathway has driven the accumulation of cis-regulatory variants that act in the same direction on gene expression. Application of this test revealed a variety of yeast pathways with evidence for directional regulatory evolution. In parallel, we also used population genomic sequencing data to compare protein and cis-regulatory variation within and between species. We identified pathways with evidence for divergence within S. cerevisiae, and we detected signatures of positive selection between S. cerevisiae and S. bayanus. Our results point to polygenic, pathway-level change as a common evolutionary mechanism among yeasts. We suggest that pathway analyses, including our test for directional regulatory evolution, will prove to be a relevant and powerful strategy in many evolutionary genomic applications.