Variation in behaviors in natural populations arises from complex networks of multiple segregating polymorphic alleles whose expression can be modulated by the environment. Since behaviors reflect dynamic interactions between organisms and their environments, they are central targets for adaptive evolution. Drosophila melanogaster presents a powerful system for dissecting the genetic basis of behavioral phenotypes, since both the genetic background and environmental conditions can be controlled and behaviors accurately quantified. Single gene mutational analyses can identify the roles of individual genes within cellular pathways, whereas systems genetic approaches that exploit natural variation can construct genetic networks that underlie phenotypic variation. Combining these approaches with emerging technologies, such as genome editing, is likely to yield a comprehensive understanding of the neurogenetic underpinnings that orchestrate the manifestation of behaviors.
The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.
Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.
Pigmentation varies within and between species and is often adaptive. The amount of pigmentation on the abdomen of Drosophila melanogaster is a relatively simple morphological trait, which serves as a model for mapping the genetic basis of variation in complex phenotypes. Here, we assessed natural variation in female abdominal pigmentation in 175 sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel, derived from the Raleigh, NC population. We quantified the proportion of melanization on the two most posterior abdominal segments, tergites 5 and 6 (T5, T6). We found significant genetic variation in the proportion of melanization and high broad-sense heritabilities for each tergite. Genome-wide association studies identified over 150 DNA variants associated with the proportion of melanization on T5 (84), T6 (34), and the difference between T5 and T6 (35). Several of the top variants associated with variation in pigmentation are in tan, ebony, and bric-a-brac1, genes known to affect D. melanogaster abdominal pigmentation. Mutational analyses and targeted RNAi-knockdown showed that 17 out of 28 (61%) novel candidate genes implicated by the genome-wide association study affected abdominal pigmentation. Several of these genes are involved in developmental and regulatory pathways, chitin production, cuticle structure, and vesicle formation and transport. These findings show that genetic variation may affect multiple steps in pathways involved in tergite development and melanization. Variation in these novel candidates may serve as targets for adaptive evolution and sexual selection in D. melanogaster.
Body pigmentation contributes to the spectacular biodiversity present in nature and mediates mate choice, mimicry, and physiological functions such as thermoregulation and UV resistance. Thus, pigmentation is a significant contributor to fitness. In order to understand how complex traits such as pigmentation evolve, we must first identify the genetic variants underlying phenotypic variation. We used the Drosophila melanogaster Genetic Reference Panel, a wild derived population of fully sequenced inbred fly lines, to identify the contributions of both known and novel genetic variants to natural variation in abdominal pigmentation in female flies. Our results show that genetic variation within many biological pathways contributes to variation in D. melanogaster pigmentation.
Little is known about the genetic basis of naturally occurring variation for sexually selected behavioral traits. Drosophila melanogaster, with its rich repertoire of courtship behavior and genomic and genetic resources, is an excellent model organism for addressing this question. We assayed a genetically diverse panel of lines with full genome sequences, the Drosophila Genetic Reference Panel, to assess the heritability of variation in courtship behavior and mating progression. We subsequently used these data to quantify natural variation in transition probabilities between courtship behaviors. We found heritable variation along the expected trajectory for courtship behaviors, including the tendency to initiate courtship and rate of progression through courtship, suggesting a genetic basis to male modulation of courtship behavior based on feedback from unrelated, outbred, and genetically identical females. We assessed the genetic basis of variation of the transition with the greatest heritability—from copulation to no engagement with the female—and identified variants in Serrate and Furin 1 as well as many other polymorphisms on the chromosome 3R associated with this transition. Our findings suggest that courtship is a highly dynamic behavior with both social and genetic inputs, and that males may play an important role in courtship initiation and duration.
ethogram; quantitative genetics; behavior; DGRP; GWAS
Methylmercury (MeHg) is a persistent environmental toxin present in seafood that can compromise the developing nervous system in humans. The effects of MeHg toxicity varies among individuals, despite similar levels of exposure, indicating that genetic differences contribute to MeHg susceptibility. To examine how genetic variation impacts MeHg tolerance, we assessed developmental tolerance to MeHg using the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP). We found significant genetic variation in the effects of MeHg on development, measured by eclosion rate, giving a broad sense heritability of 0.86. To investigate the influence of dietary factors, we measured MeHg toxicity with caffeine supplementation in the DGRP lines. We found that caffeine counteracts the deleterious effects of MeHg in the majority of lines, and there is significant genetic variance in the magnitude of this effect, with a broad sense heritability of 0.80. We performed genome-wide association (GWA) analysis for both traits, and identified candidate genes that fall into several gene ontology categories, with enrichment for genes involved in muscle and neuromuscular development. Overexpression of glutamate-cysteine ligase, a MeHg protective enzyme, in a muscle-specific manner leads to a robust rescue of eclosion of flies reared on MeHg food. Conversely, mutations in kirre, a pivotal myogenic gene identified in our GWA analyses, modulate tolerance to MeHg during development in accordance with kirre expression levels. Finally, we observe disruptions of indirect flight muscle morphogenesis in MeHg-exposed pupae. Since the pathways for muscle development are evolutionarily conserved, it is likely that the effects of MeHg observed in Drosophila can be generalized across phyla, implicating muscle as an additional hitherto unrecognized target for MeHg toxicity. Furthermore, our observations that caffeine can ameliorate the toxic effects of MeHg show that nutritional factors and dietary manipulations may offer protection against the deleterious effects of MeHg exposure.
We determined female genome sizes using flow cytometry for 211 Drosophila melanogaster sequenced inbred strains from the Drosophila Genetic Reference Panel, and found significant conspecific and intrapopulation variation in genome size. We also compared several life history traits for 25 lines with large and 25 lines with small genomes in three thermal environments, and found that genome size as well as genome size by temperature interactions significantly correlated with survival to pupation and adulthood, time to pupation, female pupal mass, and female eclosion rates. Genome size accounted for up to 23% of the variation in developmental phenotypes, but the contribution of genome size to variation in life history traits was plastic and varied according to the thermal environment. Expression data implicate differences in metabolism that correspond to genome size variation. These results indicate that significant genome size variation exists within D. melanogaster and this variation may impact the evolutionary ecology of the species. Genome size variation accounts for a significant portion of life history variation in an environmentally dependent manner, suggesting that potential fitness effects associated with genome size variation also depend on environmental conditions.
Genome size evolution is ubiquitous, and–even after decades of research–mysterious. There are two major classes of hypotheses regarding genome size evolution, those that attribute its causes to evolutionarily neutral processes and those that suggest a role for selection. Numerous correlations between genome size and fitness-related phenotypes have been documented, suggesting selection could play a role in genome size evolution. Unfortunately, many of the effects in those studies are confounded with factors that could provide alternative explanations. Here, we show that 211 inbred strains of Drosophila melanogaster exhibit abundant variation in genome size, which correlates with life history traits in a temperature-dependent manner. Gene expression analyses suggest a role for differences in metabolism between strains with large and small genomes. Thus, there is genetic variation in genome size within D. melanogaster, and this variation is connected to variation in environmentally dependent life history traits. These observations indicate that selection is indeed a potential mechanism by which genome size can evolve. Our results also suggest that higher levels of genetic architecture may explain some of the genetic contribution to biologically important complex traits and raise the possibility that nucleotide quantity can contribute to phenotype in addition to quality.
The role of epistasis in the genetic architecture of quantitative traits is controversial, despite the biological plausibility that non-linear molecular interactions underpin the genotype-phenotype map. This controversy arises because most genetic variation for quantitative traits is additive. However, additive variance is consistent with pervasive epistatic gene action. Here, I discuss experimental designs to detect the contribution of epistasis to quantitative trait phenotypes in model organisms. These studies indicate that epistatic gene action is common, and that additivity can be an emergent property of underlying genetic interaction networks. Epistasis causes hidden quantitative genetic variation in natural populations and could be responsible for the small additive effects, missing heritability and lack of replication typically observed for human complex traits.
Predicting functional gene annotations remains a significant challenge, even in well-annotated genomes such as yeast and Drosophila. One promising, high-throughput method for gene annotation is to use correlated gene expression patterns to annotate target genes based on the known function of focal genes. The Drosophila melanogaster transcriptome varies genetically among wild derived inbred lines, with strong genetic correlations among the transcripts. Here, we leveraged the genetic correlations in gene expression among known seminal fluid protein (SFP) genes and the rest of the genetically varying transcriptome to identify 176 novel candidate SFPs (cSFPs). We independently validated the correlation in gene expression between seven of the cSFPs and a known SFP gene, as well as expression in male reproductive tissues. We argue that this method can be extended to other systems for which information on genetic variation in gene expression is available.
Limited lifespan and senescence are quantitative traits, controlled by many interacting genes with individually small and environmentally plastic effects, complicating genetic analysis. We performed genome wide analysis of gene expression for two Drosophila melanogaster lines selected for postponed senescence and one control, unselected line to identify candidate genes affecting lifespan as well as variation in lifespan. We obtained gene expression profiles for young flies of all lines, all lines at the time only 10% of the control lines survived, and the time at which 10% of the selected lines survived. Transcriptional responses to aging involved 19% of the genome. The transcriptional signature of aging involved the down-regulation of genes affecting proteolysis, metabolism, oxidative phosphorylation, and mitochrondrial function; and the up-regulation of genes affecting protein synthesis, immunity, defense responses, and the detoxification of xenobiotic substances. The transcriptional signature of postponed senescence involved the up-regulation of proteases and phosphatases and genes affecting detoxification of xenobiotics; and the down-regulation of genes affecting immunity, defense responses, metabolism and muscle function. Functional tests of 17 mutations confirmed 12 novel genes affecting Drosophila lifespan. Identification of genes affecting longevity by analysis of gene expression changes in lines selected for postponed senescence thus complements alternative genetic approaches.
aging; postponed senescence; gene expression; candidate genes; artificial selection
Alcohol abuse and alcoholism incur a heavy socioeconomic cost in many countries. Both genetic and environmental factors contribute to variation in the inebriating effects of alcohol and alcohol addiction among individuals within and across populations. From a genetics perspective, alcohol sensitivity is a quantitative trait determined by the cumulative effects of multiple segregating genes and their interactions with the environment. This review summarizes insights from model organisms as well as human populations that represent our current understanding of the genetic and genomic underpinnings that govern alcohol metabolism and the sedative and addictive effects of alcohol on the nervous system.
Electronic supplementary material
The online version of this article (doi:10.1007/s00438-013-0808-y) contains supplementary material, which is available to authorized users.
Addiction; Behavioral genetics; Genome-wide association; Quantitative trait loci; Meta-analysis
A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.
Understanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals.
One of the principal challenges in current biology is to understand the relationship between genetic and phenotypic variation. The increasing availability of genomic variation maps of human as well as of model organism populations (mouse and Arabidopsis) constitutes an important step towards meeting this challenge. However, despite its excellent track record as a premier model to understand genome function, no genome-wide variation data beyond single-nucleotide variants and microsatellites are currently available for D. melanogaster. Here, we present a comprehensive, nucleotide-resolution catalogue of variants of various types (single-nucleotide, multi-nucleotide, and structural variants) for 39 wild-derived inbred D. melanogaster lines based on high-throughput sequencing. This catalogue confirms that non–SNP variants account for more than half of genomic variation, allowing us to provide new insights into the non-random distribution of variants in the Drosophila genome. We further present genome-wide cis-associations with gene expression based on whole adult fly microarray data, revealing significant associations for about 2,000 genes. Most associations are sex-specific, providing evidence for a decoupling of the genomic, regulatory architecture between males and females.
Reactive oxygen species (ROS) are a common byproduct of mitochondrial energy metabolism, and can also be induced by exogenous sources, including UV light, radiation, and environmental toxins. ROS generation is essential for maintaining homeostasis by triggering cellular signaling pathways and host defense mechanisms. However, an imbalance of ROS induces oxidative stress and cellular death and is associated with human disease, including age-related locomotor impairment. To identify genes affecting sensitivity and resistance to ROS-induced locomotor decline, we assessed locomotion of aged flies of the sequenced, wild-derived lines from the Drosophila melanogaster Genetics Reference Panel on standard medium and following chronic exposure to medium supplemented with 3 mM menadione sodium bisulfite (MSB). We found substantial genetic variation in sensitivity to oxidative stress with respect to locomotor phenotypes. We performed genome-wide association analyses to identify candidate genes associated with variation in sensitivity to ROS-induced decline in locomotor performance, and confirmed the effects for 13 of 16 mutations tested in these candidate genes. Candidate genes associated with variation in sensitivity to MSB-induced oxidative stress form networks of genes involved in neural development, immunity, and signal transduction. Many of these genes have human orthologs, highlighting the utility of genome-wide association in Drosophila for studying complex human disease.
Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP–based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.
The ability to accurately predict values of complex phenotypes from genotype data will revolutionize plant and animal breeding, personalized medicine, and evolutionary biology. To date, genomic prediction has utilized high-density single-nucleotide polymorphism (SNP) genotyping arrays, but the availability of sequence data opens new frontiers for genomic prediction methods. This article is the first application of genomic phenotype prediction using whole-genome sequence data in a substantial sample of a higher eukaryote. We use ∼2.5 million SNPs with minor allele frequency greater than 2.5% derived from genomic sequences of the “Drosophila Genetic Reference Panel” to predict phenotypes for two traits, starvation resistance and startle-induced locomotor behavior. We systematically address prediction within versus across sexes, genomic best linear unbiased prediction (GBLUP) versus a Bayesian approach, and the effect of SNP density. We find that (i) genomic prediction can be efficiently implemented using sequence data via GBLUP, (ii) there is little gain in predictive ability if the number of SNPs is increased above 150,000, and (iii) neither implicit nor explicit marker selection substantially improves the predictive ability. Although the findings must be seen against the background of small sample sizes, the results illustrate both the potential of the approach and the challenges ahead.
Aerobic organisms are susceptible to damage by reactive oxygen species. Oxidative stress resistance is a quantitative trait with population variation attributable to the interplay between genetic and environmental factors. Drosophila melanogaster provides an ideal system to study the genetics of variation for resistance to oxidative stress.
Methods and Findings
We used 167 wild-derived inbred lines of the Drosophila Genetic Reference Panel for a genome-wide association study of acute oxidative stress resistance to two oxidizing agents, paraquat and menadione sodium bisulfite. We found significant genetic variation for both stressors. Single nucleotide polymorphisms (SNPs) associated with variation in oxidative stress resistance were often sex-specific and agent-dependent, with a small subset common for both sexes or treatments. Associated SNPs had moderately large effects, with an inverse relationship between effect size and allele frequency. Linear models with up to 12 SNPs explained 67–79% and 56–66% of the phenotypic variance for resistance to paraquat and menadione sodium bisulfite, respectively. Many genes implicated were novel with no known role in oxidative stress resistance. Bioinformatics analyses revealed a cellular network comprising DNA metabolism and neuronal development, consistent with targets of oxidative stress-inducing agents. We confirmed associations of seven candidate genes associated with natural variation in oxidative stress resistance through mutational analysis.
We identified novel candidate genes associated with variation in resistance to oxidative stress that have context-dependent effects. These results form the basis for future translational studies to identify oxidative stress susceptibility/resistance genes that are evolutionary conserved and might play a role in human disease.
Phenotypic plasticity is the ability of a single genotype to produce different phenotypes in response to changing environments. We assessed variation in genome-wide gene expression and four fitness-related phenotypes of an outbred Drosophila melanogaster population under 20 different physiological, social, nutritional, chemical, and physical environments; and we compared the phenotypically plastic transcripts to genetically variable transcripts in a single environment. The environmentally sensitive transcriptome consists of two transcript categories, which comprise ∼15% of expressed transcripts. Class I transcripts are genetically variable and associated with detoxification, metabolism, proteolysis, heat shock proteins, and transcriptional regulation. Class II transcripts have low genetic variance and show sexually dimorphic expression enriched for reproductive functions. Clustering analysis of Class I transcripts reveals a fragmented modular organization and distinct environmentally responsive transcriptional signatures for the four fitness-related traits. Our analysis suggests that a restricted environmentally responsive segment of the transcriptome preserves the balance between phenotypic plasticity and environmental canalization.
Unlike Mendelian traits, where the genotype allows a direct prediction of the phenotype, predicting phenotypic values is not straightforward for complex traits, which arise from multiple segregating genes and their interactions with the environment. Here, a single genotype can often express different phenotypes in different environments. Such phenotypic plasticity is the counterpoint to “environmental canalization,” whereby genotypes produce the same phenotype in different environments. Whereas phenotypic plasticity allows organisms to respond rapidly to changing environments, environmental canalization buffers phenotypes against environmental perturbations. The balance between plasticity and robustness is crucial for optimal fitness, but the genetic basis for phenotypic plasticity is poorly defined. Here, we present the most comprehensive analysis to date of variation in genome-wide gene expression of an outbred Drosophila melanogaster population under 20 different environments. We find that a restricted environmentally responsive segment of the transcriptome (∼15%) preserves the balance between phenotypic plasticity and environmental canalization. Environmentally plastic transcripts can be grouped into two categories. Class I transcripts are genetically variable and associated with detoxification, metabolism, proteolysis, heat shock proteins, and transcriptional regulation. Class II transcripts have low genetic variance and show sexually dimorphic expression enriched for reproductive functions. Despite low genetic variance these transcripts evolve rapidly.
A central issue in evolutionary quantitative genetics is to understand how genetic variation for quantitative traits is maintained in natural populations. Estimates of genetic variation and of genetic correlations and pleiotropy among multiple traits, inbreeding depression, mutation rates for fitness and quantitative traits and of the strength and nature of selection are all required to evaluate theoretical models of the maintenance of genetic variation. Studies in Drosophila melanogaster have shown that a substantial fraction of segregating variation for fitness-related traits in Drosophila is due to rare deleterious alleles maintained by mutation–selection balance, with a smaller but significant fraction attributable to intermediate frequency alleles maintained by alleles with antagonistic pleiotropic effects, and late-age-specific effects. However, the nature of segregating variation for traits under stabilizing selection is less clear and requires more detailed knowledge of the loci, mutation rates, allelic effects and frequencies of molecular polymorphisms affecting variation in suites of pleiotropically connected traits. Recent studies in D. melanogaster have revealed unexpectedly complex genetic architectures of many quantitative traits, with large numbers of pleiotropic genes and alleles with sex-, environment- and genetic background-specific effects. Future genome wide association analyses of many quantitative traits on a common panel of fully sequenced Drosophila strains will provide much needed empirical data on the molecular genetic basis of quantitative traits.
maintenance of quantitative genetic variation; mutation–selection balance; balancing selection; pleiotropy; context-dependent effects; genetic architecture
Understanding the genetic and environmental factors that affect variation in life span and senescence is of major interest for human health and evolutionary biology. Multiple mechanisms affect longevity, many of which are conserved across species, but the genetic networks underlying each mechanism and cross-talk between networks are unknown. We report the results of a screen for mutations affecting Drosophila life span. One third of the 1,332 homozygous P–element insertion lines assessed had quantitative effects on life span; mutations reducing life span were twice as common as mutations increasing life span. We confirmed 58 mutations with increased longevity, only one of which is in a gene previously associated with life span. The effects of the mutations increasing life span were highly sex-specific, with a trend towards opposite effects in males and females. Mutations in the same gene were associated with both increased and decreased life span, depending on the location and orientation of the P–element insertion, and genetic background. We observed substantial—and sex-specific—epistasis among a sample of ten mutations with increased life span. All mutations increasing life span had at least one deleterious pleiotropic effect on stress resistance or general health, with different patterns of pleiotropy for males and females. Whole-genome transcript profiles of seven of the mutant lines and the wild type revealed 4,488 differentially expressed transcripts, 553 of which were common to four or more of the mutant lines, which include genes previously associated with life span and novel genes implicated by this study. Therefore longevity has a large mutational target size; genes affecting life span have variable allelic effects; alleles affecting life span exhibit antagonistic pleiotropy and form epistatic networks; and sex-specific mutational effects are ubiquitous. Comparison of transcript profiles of long-lived mutations and the control line reveals a transcriptional signature of increased life span.
Recent advances in medical science as well as vastly improved living conditions have resulted in a steady increase in human life span, with a concomitant increase in health issues associated with aging. In addition, understanding life history evolution requires that we know why organisms age and why there is variation in aging and senescence. To identify genes involved in aging, we assessed longevity in a collection of over 1,300 Drosophila lines homozygous for a single P transposable element mutation. We found 58 mutations in novel loci that increase life span by up to 33%. Most mutations had different effects on male and female life span, and for some the effects were opposite between the sexes. Effects of these mutations on starvation resistance, chill coma recovery, and climbing ability varied, but all had a deleterious effect on at least one other trait. A sample of ten mutations with increased life span formed genetic interaction networks, but the genetic interactions were different, and sometimes in opposite directions, in males and females. Transcript profiles of seven long-lived mutations and the control line reveal a core transcriptional signature of increased life span involving novel candidate genes for future analysis.
Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
For most organisms, chemosensation is critical for survival and is mediated by large families of chemoreceptor proteins, whose expression must be tuned appropriately to changes in the chemical environment. We asked whether expression of chemoreceptor genes that are clustered in the genome would be regulated independently; whether expression of certain chemoreceptor genes would be especially sensitive to environmental changes; whether groups of chemoreceptor genes undergo coordinated rexpression; and how plastic the expression of chemoreceptor genes is with regard to sex, development, reproductive state, and social context. To answer these questions we used Drosophila melanogaster, because its chemosensory systems are well characterized and both the genotype and environment can be controlled precisely. Using customized cDNA microarrays, we showed that chemoreceptor genes that are clustered in the genome undergo independent transcriptional regulation at different developmental stages and between sexes. Expression of distinct subgroups of chemoreceptor genes is sensitive to reproductive state and social interactions. Furthermore, exposure of flies only to odor of the opposite sex results in altered transcript abundance of chemoreceptor genes. These genes are distinct from those that show transcriptional plasticity when flies are allowed physical contact with same or opposite sex members. We analyzed covariance in transcript abundance of chemosensory genes across all environmental conditions and found that they segregated into 20 relatively small, biologically relevant modules of highly correlated transcripts. This finely pixilated modular organization of the chemosensory subgenome enables fine tuning of the expression of the chemoreceptor repertoire in response to ecologically relevant environmental and physiological conditions.
Rapid adaptation and phenotypic plasticity to the chemical environment are essential prerequisites for survival; and, consequently, large families of genes that mediate the recognition of olfactory and gustatory cues have evolved. We asked how flexible the expression of these genes is in the face of rapidly changing conditions encountered during an individual's lifetime. We used the fruit fly, Drosophila melanogaster, to address this question, since both the genetic composition and environmental rearing conditions can be controlled precisely in this experimentally amenable model organism. By measuring expression levels of all chemosensory genes simultaneously, we identified genes that show altered expression at different developmental stages, during aging, in males and females, following mating, and in different social conditions. We asked whether chemosensory genes are regulated independently or whether their regulation is structured. We found that chemosensory genes that are located in close proximity to one another on the chromosome are often regulated independently. However, statistical analysis showed that groups of chemosensory genes are coordinately expressed in response to a range of environmental conditions, revealing an underlying modular organization of the phenotypic plasticity of the chemosensory receptor repertoire.
Determining the genetic architecture of complex traits is challenging because phenotypic variation arises from interactions between multiple, environmentally sensitive alleles. We quantified genome-wide transcript abundance and phenotypes for six ecologically relevant traits in D. melanogaster wild-derived inbred lines. We observed 10,096 genetically variable transcripts and high heritabilities for all organismal phenotypes. The transcriptome is highly genetically inter-correlated, forming 241 transcriptional modules. Modules are enriched for transcripts in common pathways, gene ontology categories, tissue-specific expression, and transcription factor binding sites. The high transcriptional connectivity allows us to infer genetic networks and the function of predicted genes based on annotations of other genes in the network. Regressions of organismal phenotypes on transcript abundance implicate several hundred candidate genes that form modules of biologically meaningful correlated transcripts affecting each phenotype. Overlapping transcripts in modules associated with different traits provides insight into the molecular basis of pleiotropy between complex traits.
Sleep disorders are common in humans, and sleep loss increases the risk of obesity and diabetes1. Studies in Drosophila2, 3 have revealed molecular pathways4–7 and neural tissues8–10 regulating sleep; however, genes that maintain genetic variation for sleep in natural populations are unknown. Here, we characterized sleep in 40 wild-derived Drosophila lines and observed abundant genetic variation in sleep architecture. We associated sleep with genome-wide variation in gene expression11 to identify candidate genes. We independently confirmed that molecular polymorphisms in Catecholamines up are associated with variation in sleep; and that P-element mutations in four candidate genes affect sleep and gene expression. Transcripts associated with sleep grouped into biologically plausible genetically correlated transcriptional modules. We confirmed co-regulated gene expression using P-element mutants. Genes associated with sleep duration are evolutionarily conserved. Quantitative genetic analysis of natural phenotypic variation is an efficient method for revealing candidate genes and pathways.
Glaucoma is the world's second leading cause of bilateral blindness with progressive loss of vision due to retinal ganglion cell death. Myocilin has been associated with congenital glaucoma and 2–4% of primary open angle glaucoma (POAG) cases, but the pathogenic mechanisms remain largely unknown. Among several hypotheses, activation of the unfolded protein response (UPR) has emerged as a possible disease mechanism.
Methodology / Principal Findings
We used a transgenic Drosophila model to analyze whole-genome transcriptional profiles in flies that express human wild-type or mutant MYOC in their eyes. The transgenic flies display ocular fluid discharge, reflecting ocular hypertension, and a progressive decline in their behavioral responses to light. Transcriptional analysis shows that genes associated with the UPR, ubiquitination, and proteolysis, as well as metabolism of reactive oxygen species and photoreceptor activity undergo altered transcriptional regulation. Following up on the results from these transcriptional analyses, we used immunoblots to demonstrate the formation of MYOC aggregates and showed that the formation of such aggregates leads to induction of the UPR, as evident from activation of the fluorescent UPR marker, xbp1-EGFP.
Conclusions / Significance
Our results show that aggregation of MYOC in the endoplasmic reticulum activates the UPR, an evolutionarily conserved stress pathway that culminates in apoptosis. We infer from the Drosophila model that MYOC-associated ocular hypertension in the human eye may result from aggregation of MYOC and induction of the UPR in trabecular meshwork cells. This process could occur at a late age with wild-type MYOC, but might be accelerated by MYOC mutants to account for juvenile onset glaucoma.