Drosophila Genetic Reference Panel Research Articles

Drosophila Toxicogenomics: genetic variation and sexual dimorphism in susceptibility to 4-Methylimidazole

Background4-methylimidazole is a ubiquitous and potentially carcinogenic environmental toxicant. Genetic factors that contribute to variation in susceptibility to its toxic effects are challenging to assess in human populations. We used the Drosophila melanogaster Genetic Reference Panel (DGRP), a living library of natural genetic variation, to identify genes with human orthologs associated with variation in susceptibility to 4-methylimidazole.ResultsWe screened 204 DGRP lines for survival following 24-hour exposure to 4-methylimidazole. We found extensive genetic variation for survival, with a broad sense heritability of 0.82; as well as genetic variation in sexual dimorphism, with a cross-sex genetic correlation of 0.59. Genome-wide association analyses identified a total of 241 candidate molecular polymorphisms in or near 273 unique genes associated with survival. These polymorphisms had either sex-specific or sex-antagonistic effects, and most had putative regulatory effects. We generated interaction networks using these candidate genes as inputs and computationally recruited genes with known physical or genetic interactions. The network genes were significantly over-represented for gene ontology terms involving all aspects of development (including nervous system development) and cellular and organismal functions as well as canonical signaling pathways, and most had human orthologs.ConclusionsThe genetic basis of variation in sensitivity to acute exposure to 4-methylimidazole in Drosophila is attributable to variation in genes and networks of genes known for their effects on multiple developmental and cellular processes, including possible neurotoxicity. Given evolutionary conservation of the underlying genes and pathways, these insights may be applicable to humans.

Systems biology approaches identify metabolic signatures of dietary lifespan and healthspan across species

Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabolites as markers to reveal how different genotypes respond to diet to influence longevity and healthspan traits. We analyzed data from Drosophila Genetic Reference Panel (DGRP) strains raised under AL and DR conditions, combining metabolomic, phenotypic, and genome-wide information. We employed two computational and complementary methods across species—random forest modeling within the DGRP as our primary analysis and Mendelian randomization in human cohorts as a secondary analysis. We pinpointed key traits with cross-species relevance as well as underlying heterogeneity and pleiotropy that influence lifespan and healthspan. Notably, orotate was linked to parental age at death in humans and blocked the DR lifespan extension in flies, while threonine supplementation extended lifespan, in a strain- and sex-specific manner. Thus, utilizing natural genetic variation data from flies and humans, we employed a systems biology approach to elucidate potential therapeutic pathways and metabolomic targets for diet-dependent changes in lifespan and healthspan.

DGRPool, a web tool leveraging harmonized Drosophila Genetic Reference Panel phenotyping data for the study of complex traits

Genome-wide association studies have advanced our understanding of complex traits, but studying how a GWAS variant can affect a specific trait in the human population remains challenging due to environmental variability. Drosophila melanogaster is in this regard an excellent model organism for studying the relationship between genetic and phenotypic variation due to its simple handling, standardized growth conditions, low cost, and short lifespan. The Drosophila Genetic Reference Panel (DGRP) in particular has been a valuable tool for studying complex traits, but proper harmonization and indexing of DGRP phenotyping data is necessary to fully capitalize on this resource. To address this, we created a web tool called DGRPool (dgrpool.epfl.ch), which aggregates phenotyping data of 1034 phenotypes across 135 DGRP studies in a common environment. DGRPool enables users to download data and run various tools such as genome-wide (GWAS) and phenome-wide (PheWAS) association studies. As a proof-of-concept, DGRPool was used to study the longevity phenotype and uncovered both established and unexpected correlations with other phenotypes such as locomotor activity, starvation resistance, desiccation survival, and oxidative stress resistance. DGRPool has the potential to facilitate new genetic and molecular insights of complex traits in Drosophila and serve as a valuable, interactive tool for the scientific community.

DGRPool, a web tool leveraging harmonized Drosophila Genetic Reference Panel phenotyping data for the study of complex traits.

Genome-wide association studies have advanced our understanding of complex traits, but studying how a GWAS variant can affect a specific trait in the human population remains challenging due to environmental variability. Drosophila melanogaster is in this regard an excellent model organism for studying the relationship between genetic and phenotypic variation due to its simple handling, standardized growth conditions, low cost, and short lifespan. The Drosophila Genetic Reference Panel (DGRP) in particular has been a valuable tool for studying complex traits, but proper harmonization and indexing of DGRP phenotyping data is necessary to fully capitalize on this resource. To address this, we created a web tool called DGRPool (dgrpool.epfl.ch), which aggregates phenotyping data of 1034 phenotypes across 135 DGRP studies in a common environment. DGRPool enables users to download data and run various tools such as genome-wide (GWAS) and phenome-wide (PheWAS) association studies. As a proof-of-concept, DGRPool was used to study the longevity phenotype and uncovered both established and unexpected correlations with other phenotypes such as locomotor activity, starvation resistance, desiccation survival, and oxidative stress resistance. DGRPool has the potential to facilitate new genetic and molecular insights of complex traits in Drosophila and serve as a valuable, interactive tool for the scientific community.

The Impact of the Angiotensin-Converting Enzyme Inhibitor Lisinopril on Metabolic Rate in Drosophila melanogaster.

Evidence suggests that angiotensin-converting enzyme inhibitors (ACEIs) may increase metabolic rate by promoting thermogenesis, potentially through enhanced fat oxidation and improved insulin. More research is, however, needed to understand this intricate process. In this study, we used 22 lines from the Drosophila Genetic Reference Panel to assess the metabolic rate of virgin female and male flies that were either fed a standard medium or received lisinopril for one week or five weeks. We demonstrated that lisinopril affects the whole-body metabolic rate in Drosophila melanogaster in a genotype-dependent manner. However, the effects of genotypes are highly context-dependent, being influenced by sex and age. Our findings also suggest that lisinopril may increase the Drosophila metabolic rate via the accumulation of a bradykinin-like peptide, which, in turn, enhances cold tolerance by upregulating Ucp4b and Ucp4c genes. Finally, we showed that knocking down Ance, the ortholog of mammalian ACE in Malpighian/renal tubules and the nervous system, leads to opposite changes in metabolic rate, and that the effect of lisinopril depends on Ance in these systems, but in a sex- and age-specific manner. In conclusion, our results regarding D. melanogaster support existing evidence of a connection between ACEI drugs and metabolic rate while offering new insights into this relationship.

Larval density can be used to predict genetic modifiers of glucagon signaling in Drosophila melanogaster.

Obesity is a growing concern. 42.3% of people in the U.S were considered obese between 2017-2018. Much is still unknown about the genetic components that contribute to weight gain. In humans, the hormone glucagon is a major contributor to the body's energy regulation as it signals for the breakdown of lipids. Treatments targeting the glucagon pathway have helped patients with both weight loss and appetite suppression. Understanding the genetic modifiers of glucagon signaling and its downstream pathways could enable the development of a wider variety of effective therapeutics. In this study, we blocked the glucagon pathway in Drosophila melanogaster by reducing the expression of the fly ortholog of the glucagon receptor (AKHR). We then crossed our model to the Drosophila Genetic Reference Panel (DGRP) and looked for natural variation in fat content. We used variation in larval density to identify candidate modifier genes through a genome-wide association study. We then tested these modifier genes by increasing or decreasing their expression in the AKHR model. We screened these candidates initially with the same density assay used in the original study to narrow down to four candidate genes that substantially impacted the density of the larvae: THADA, AmyD, GluRIIC, and CG9826. We further characterized these candidates using biochemical assays to analyze stored metabolites such as triglycerides, glucose, glycogen, and protein under control, high sugar, and high fat conditions to see if the larvae are resistant to environmental changes. Our results indicate consistency between the results of the density assay and direct measurement of metabolite levels. In particular, THADA and AmyD are highlighted as interesting genes for additional study. We hope to improve our understanding of the glucagon signaling pathway, obesity, and lipid metabolism. We also aim to provide candidate genes that can be regarded as future therapeutic targets.

Genome-Wide Association Study and transcriptome analysis reveals a complex gene network that regulates opsin gene expression and cell fate determination in Drosophila R7 photoreceptor cells.

An animal's ability to discriminate between differing wavelengths of light (i.e., color vision) is mediated, in part, by a subset of photoreceptor cells that express opsins with distinct absorption spectra. In Drosophila R7 photoreceptors, expression of the rhodopsin molecules, Rh3 or Rh4, is determined by a stochastic process mediated by the transcription factor spineless. The goal of this study was to identify additional factors that regulate R7 cell fate and opsin choice using a Genome Wide Association Study (GWAS) paired with transcriptome analysis via RNA-Seq. We examined Rh3 and Rh4 expression in a subset of fully-sequenced inbred strains from the Drosophila Genetic Reference Panel and performed a GWAS to identify 42 naturally-occurring polymorphisms-in proximity to 28 candidate genes-that significantly influence R7 opsin expression. Network analysis revealed multiple potential interactions between the associated candidate genes, spineless and its partners. GWAS candidates were further validated in a secondary RNAi screen which identified 12 lines that significantly reduce the proportion of Rh3 expressing R7 photoreceptors. Finally, using RNA-Seq, we demonstrated that all but four of the GWAS candidates are expressed in the pupal retina at a critical developmental time point and that five are among the 917 differentially expressed genes in sevenless mutants, which lack R7 cells. Collectively, these results suggest that the relatively simple, binary cell fate decision underlying R7 opsin expression is modulated by a larger, more complex network of regulatory factors. Of particular interest are a subset of candidate genes with previously characterized neuronal functions including neurogenesis, neurodegeneration, photoreceptor development, axon growth and guidance, synaptogenesis, and synaptic function.

Natural variation in starvation sensitivity maps to a point mutation in phospholipase IPLA2-VIA in Drosophila melanogaster.

Resistance to starvation is a classic complex trait, where genetic and environmental variables can greatly modify an animal's ability to survive without nutrients. In this study, we investigate the genetic basis of starvation resistance using complementary quantitative and classical genetic mapping in Drosophila melanogaster. Using the Drosophila Genetics Reference Panel (DGRP) as a starting point, we queried the genetic basis of starvation sensitivity in one of the most sensitive DGRP lines. We localize a major effect locus modifying starvation resistance to the phospholipase iPLA2-VIA. This finding is consistent with the work of others which demonstrate the importance of lipid regulation in starvation stress. Furthermore, we demonstrate that iPLA2-VIA plays a role in the maintenance of sugar reserves post-starvation, which highlights a key dynamic between lipid remodeling, sugar metabolism and resistance to starvation stress.

A genome-wide association study implicates the olfactory system in Drosophila melanogaster diapause-associated lifespan extension and fecundity.

The effects of environmental stress on animal life are gaining importance with climate change. Diapause is a dormancy program that occurs in response to an adverse environment, followed by resumption of development and reproduction upon the return of favorable conditions. Diapause is a complex trait, so we leveraged the Drosophila genetic reference panel (DGRP) lines and conducted a Genome-Wide Association Study (GWAS) to characterize the genetic basis of diapause. We assessed post-diapause and non-diapause fecundity across 193 DGRP lines. GWAS revealed 546 genetic variants, encompassing single nucleotide polymorphisms, insertions and deletions associated with post-diapause fecundity. We identified 291 candidate diapause-associated genes, 40 of which had previously been associated with diapause. 89 of the candidates were associated with more than one SNP. Gene network analysis indicated that the diapause-associated genes were primarily linked to neuronal and reproductive system development. Similarly, comparison with results from other fly GWAS revealed the greatest overlap with olfactory-behavior-associated and fecundity-and-lifespan-associated genes. An RNAi screen of the top candidates identified two neuronal genes, Dip-γ and Scribbler, to be required during recovery for post-diapause fecundity. We complemented the genetic analysis with a test of which neurons are required for successful diapause. We found that although amputation of the antenna had little to no effect on non-diapause lifespan, it reduced diapause lifespan and postdiapause fecundity. We further show that olfactory receptor neurons and temperature-sensing neurons are required for successful recovery from diapause. Our results provide insights into the molecular, cellular, and genetic basis of adult reproductive diapause in Drosophila .

Comparing statistical learning methods for complex trait prediction from gene expression.

Accurate prediction of complex traits is an important task in quantitative genetics that has become increasingly relevant for personalized medicine. Genotypes have traditionally been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regressions, dimension reductions, and machine learning methods. Recent studies have shown that gene expression levels can produce higher prediction accuracy than genotypes. However, only a few prediction methods were used in these studies. Thus, a comprehensive assessment of methods is needed to fully evaluate the potential of gene expression as a predictor of complex trait phenotypes. Here, we used data from the Drosophila Genetic Reference Panel (DGRP) to compare the ability of several existing statistical learning methods to predict starvation resistance from gene expression in the two sexes separately. The methods considered differ in assumptions about the distribution of gene effect sizes - ranging from models that assume that every gene affects the trait to more sparse models - and their ability to capture gene-gene interactions. We also used functional annotation (i.e., Gene Ontology (GO)) as an external source of biological information to inform prediction models. The results show that differences in prediction accuracy between methods exist, although they are generally not large. Methods performing variable selection gave higher accuracy in females while methods assuming a more polygenic architecture performed better in males. Incorporating GO annotations further improved prediction accuracy for a few GO terms of biological significance. Biological significance extended to the genes underlying highly predictive GO terms with different genes emerging between sexes. Notably, the Insulin-like Receptor (InR) was prevalent across methods and sexes. Our results confirmed the potential of transcriptomic prediction and highlighted the importance of selecting appropriate methods and strategies in order to achieve accurate predictions.

Diurnal variation in genetic parameters for locomotor activity in Drosophila melanogaster assessed under natural thermal conditions.

In nature, organisms are exposed to variable and occasionally stressful environmental conditions. Responses to diurnal and seasonal fluctuations, such as temperature and food accessibility, involve adaptive behavioural and physiological changes. While much work has been done on understanding the genetic architecture and evolutionary potential of stress tolerance traits under constant thermal conditions, there has been less focus on the quantitative genetic background in variable environments. In this study, we use the Drosophila Genetic Reference Panel (DGRP) to investigate the locomotor activity, a key behavioural trait, under variable natural thermal conditions during the summer in a temperate environment. Male flies from 100 DGRP lines were exposed to natural thermal and light conditions in Drosophila activity monitors across three experimental days. We found that activity was highly temperature and time dependent and varied between lines both within and between days. Furthermore, we observed variation in genetic and environmental variance components, with low to moderate estimates of the heritability for locomotor activity, consistently peaking in the afternoons. Moreover, we showed that the estimated genetic correlations of locomotor activity between two time points decreased, as the absolute differences in ambient temperature increased. In conclusion, we find that the genetic background for locomotor activity is environment specific, and we conclude that more variable and unpredictable future temperatures will likely have a strong impact on the evolutionary trajectories of behavioural traits in ectotherms.

Pleiotropic fitness effects across sexes and ages in the Drosophila genome and transcriptome.

Selection varies between categories of individuals, with far-reaching ramifications: Sex-specific selection can impede or accelerate adaptation, and differences in selection between young and old individuals are ultimately responsible for senescence. Here, we measure early- and late-life fitness in adults of both sexes from the Drosophila genetic reference panel and perform quantitative genetic and transcriptomic analyses. Fitness was heritable, showed positive pleiotropy across sexes and age classes, and appeared to be influenced by very large numbers of loci with small effects plus a smaller number with moderate effects. Most loci affected male and female fitness in the same direction; relatively few candidate sexually antagonistic loci were found, though these were enriched on the X chromosome as predicted by theory. The expression level of many genes showed an opposite correlation with fitness in males and females, consistent with unresolved sexual conflict over transcription. The load of deleterious mutations correlated negatively with fitness across genotypes, and we found some evidence for the mutation accumulation (but not the antagonistic pleiotropy) theory of aging.

A predominant role of genotypic variation in both expression of sperm competition genes and paternity success in Drosophila melanogaster.

Sperm competition is a crucial aspect of male reproductive success in many species, including Drosophila melanogaster, and seminal fluid proteins (Sfps) can influence sperm competitiveness. However, the combined effect of environmental and genotypic variation on sperm competition gene expression remains poorly understood. Here, we used Drosophila Genetic Reference Panel (DGRP) inbred lines and manipulated developmental population density (i.e. larval density) to test the effects of genotype, environment and genotype-by-environment interactions (GEI) on the expression of the known sperm competition genes Sex Peptide, Acp36DE and CG9997. High larval density resulted in reduced adult body size, but expression of sperm competition genes remained unaffected. Furthermore, we found no significant GEI but genotypic effects in the expression of SP and Acp36DE. Our results also revealed GEI for relative competitive paternity success (second male paternity; P2), with genes' expression positively correlated with P2. Given the effect of genotype on the expression of genes, we conducted a genome-wide association study (GWAS) and identified polymorphisms in putative cis-regulatory elements as predominant factors regulating the expression of SP and Acp36DE. The association of genotypic variation with sperm competition outcomes, and the resilience of sperm competition genes' expression against environmental challenges, demonstrates the importance of genome variation background in reproductive fitness.

Basidiomycota species in Drosophila gut are associated with host fat metabolism

The importance of bacterial microbiota on host metabolism and obesity risk is well documented. However, the role of fungal microbiota on host storage metabolite pools is largely unexplored. We aimed to investigate the role of microbiota on D. melanogaster fat metabolism, and examine interrelatedness between fungal and bacterial microbiota, and major metabolic pools. Fungal and bacterial microbiota profiles, fat, glycogen, and trehalose metabolic pools are measured in a context of genetic variation represented by whole genome sequenced inbred Drosophila Genetic Reference Panel (DGRP) samples. Increasing Basidiomycota, Acetobacter persici, Acetobacter pomorum, and Lactobacillus brevis levels correlated with decreasing triglyceride levels. Host genes and biological pathways, identified via genome-wide scans, associated with Basidiomycota and triglyceride levels were different suggesting the effect of Basidiomycota on fat metabolism is independent of host biological pathways that control fungal microbiota or host fat metabolism. Although triglyceride, glycogen and trehalose levels were highly correlated, microorganisms’ effect on triglyceride pool were independent of glycogen and trehalose levels. Multivariate analyses suggested positive interactions between Basidiomycota, A. persici, and L. brevis that collectively correlated negatively with fat and glycogen pools. In conclusion, fungal microbiota can be a major player in host fat metabolism. Interactions between fungal and bacterial microbiota may exert substantial control over host storage metabolite pools and influence obesity risk.

A Parallel Computing Approach to Gene Expression and Phenotype Correlation for Identifying Retinitis Pigmentosa Modifiers in Drosophila

As a genetic eye disorder, retinitis pigmentosa (RP) has been a focus of researchers to find a diagnosis through either genome-wide association (GWA) or RNAseq analysis. In fact, GWA and RNAseq are considered two complementary approaches to gaining a more comprehensive understanding of the genetics of different diseases. However, RNAseq analysis can provide information about the specific mechanisms underlying the disease and the potential targets for therapy. This research proposes a new approach to differential gene expression (DGE) analysis, which is the heart of the core-analysis phase in any RNAseq study. Based on the Drosophila Genetic Reference Panel (DGRP), the gene expression dataset is computationally analyzed in light of eye-size phenotypes. We utilized the foreach and the doParallel R packages to run the code on a multicore machine to reduce the running time of the original algorithm, which exhibited an exponential time complexity. Experimental results showed an outstanding performance, reducing the running time by 95% while using 32 processes. In addition, more candidate modifier genes for RP were identified by increasing the scope of the analysis and considering more datasets that represent different phenotype models.

The genetic basis of adaptation to copper pollution in Drosophila melanogaster.

Introduction: Heavy metal pollutants can have long lasting negative impacts on ecosystem health and can shape the evolution of species. The persistent and ubiquitous nature of heavy metal pollution provides an opportunity to characterize the genetic mechanisms that contribute to metal resistance in natural populations. Methods: We examined variation in resistance to copper, a common heavy metal contaminant, using wild collections of the model organism Drosophila melanogaster. Flies were collected from multiple sites that varied in copper contamination risk. We characterized phenotypic variation in copper resistance within and among populations using bulked segregant analysis to identify regions of the genome that contribute to copper resistance. Results and Discussion: Copper resistance varied among wild populations with a clear correspondence between resistance level and historical exposure to copper. We identified 288 SNPs distributed across the genome associated with copper resistance. Many SNPs had population-specific effects, but some had consistent effects on copper resistance in all populations. Significant SNPs map to several novel candidate genes involved in refolding disrupted proteins, energy production, and mitochondrial function. We also identified one SNP with consistent effects on copper resistance in all populations near CG11825, a gene involved in copper homeostasis and copper resistance. We compared the genetic signatures of copper resistance in the wild-derived populations to genetic control of copper resistance in the Drosophila Synthetic Population Resource (DSPR) and the Drosophila Genetic Reference Panel (DGRP), two copper-naïve laboratory populations. In addition to CG11825, which was identified as a candidate gene in the wild-derived populations and previously in the DSPR, there was modest overlap of copper-associated SNPs between the wild-derived populations and laboratory populations. Thirty-one SNPs associated with copper resistance in wild-derived populations fell within regions of the genome that were associated with copper resistance in the DSPR in a prior study. Collectively, our results demonstrate that the genetic control of copper resistance is highly polygenic, and that several loci can be clearly linked to genes involved in heavy metal toxicity response. The mixture of parallel and population-specific SNPs points to a complex interplay between genetic background and the selection regime that modifies the effects of genetic variation on copper resistance.

Genome-wide analysis reveals novel regulators of synaptic maintenance in Drosophila.

Maintaining synaptic communication is required to preserve nervous system function as an organism ages. While much work has been accomplished to understand synapse formation and development, we understand relatively little regarding maintaining synaptic integrity throughout aging. To better understand the mechanisms responsible for maintaining synaptic structure and function, we performed an unbiased forward genetic screen to identify genes required for synapse maintenance of adult Drosophila neuromuscular junctions. Using flight behavior as a screening tool, we evaluated flight ability in 198 lines from the Drosophila Genetic Reference Panel to identify single nucleotide polymorphisms (SNPs) that are associated with a progressive loss of flight ability with age. Among the many candidate genes identified from this screen, we focus here on 10 genes with clear human homologs harboring SNPs that are most highly associated with synaptic maintenance. Functional validation of these genes using mutant alleles revealed a progressive loss of synaptic structural integrity. Tissue-specific knockdown of these genes using RNA interference (RNAi) uncovered important roles for these genes in either presynaptic motor neurons, postsynaptic muscles, or associated glial cells, highlighting the importance of each component of tripartite synapses. These results offer greater insight into the mechanisms responsible for maintaining structural and functional integrity of synapses with age.

Galbut Virus Infection Minimally Influences Drosophila melanogaster Fitness Traits in a Strain and Sex-Dependent Manner.

Galbut virus (family Partitiviridae) infects Drosophila melanogaster and can be transmitted vertically from infected mothers or infected fathers with near perfect efficiency. This form of super-Mendelian inheritance should drive infection to 100% prevalence, and indeed, galbut virus is ubiquitous in wild D. melanogaster populations. However, on average, only about 60% of individual flies are infected. One possible explanation for this is that a subset of flies are resistant to infection. Although galbut virus-infected flies appear healthy, infection may be sufficiently costly to drive selection for resistant hosts, thereby decreasing overall prevalence. To test this hypothesis, we quantified a variety of fitness-related traits in galbut virus-infected flies from two lines from the Drosophila Genetic Reference Panel (DGRP). Galbut virus-infected flies had no difference in average lifespan and total offspring production compared to their uninfected counterparts. Galbut virus-infected DGRP-517 flies pupated and eclosed faster than their uninfected counterparts. Some galbut virus-infected flies exhibited altered sensitivity to viral, bacterial, and fungal pathogens. The microbiome composition of flies was not measurably perturbed by galbut virus infection. Differences in phenotype attributable to galbut virus infection varied as a function of fly sex and DGRP strain, and differences attributable to infection status were dwarfed by larger differences attributable to strain and sex. Thus, galbut virus infection does produce measurable phenotypic changes, with changes being minor, offsetting, and possibly net-negative.

Dietary Stimuli, Intestinal Bacteria and Peptide Hormones Regulate Female Drosophila Defecation Rate

Peptide hormones control Drosophila gut motility, but the intestinal stimuli and the gene networks coordinating this trait remain poorly defined. Here, we customized an assay to quantify female Drosophila defecation rate as a proxy of intestinal motility. We found that bacterial infection with the human opportunistic bacterial pathogen Pseudomonas aeruginosa (strain PA14) increases defecation rate in wild-type female flies, and we identified specific bacteria of the fly microbiota able to increase defecation rate. In contrast, dietary stress, imposed by either water-only feeding or high ethanol consumption, decreased defecation rate and the expression of enteroendocrine-produced hormones in the fly midgut, such as Diuretic hormone 31 (Dh31). The decrease in defecation due to dietary stress was proportional to the impact of each stressor on fly survival. Furthermore, we exploited the Drosophila Genetic Reference Panel wild type strain collection and identified strains displaying high and low defecation rates. We calculated the narrow-sense heritability of defecation rate to be 91%, indicating that the genetic variance observed using our assay is mostly additive and polygenic in nature. Accordingly, we performed a genome-wide association (GWA) analysis revealing 17 candidate genes linked to defecation rate. Downregulation of four of them (Pmp70, CG11307, meso18E and mub) in either the midgut enteroendocrine cells or in neurons reduced defecation rate and altered the midgut expression of Dh31, that in turn regulates defecation rate via signaling to the visceral muscle. Hence, microbial and dietary stimuli, and Dh31-controlling genes, regulate defecation rate involving signaling within and among neuronal, enteroendocrine, and visceral muscle cells.

Early-life nutrition interacts with developmental genes to shape the brain and sleep behavior in Drosophila melanogaster.

The mechanisms by which the genotype interacts with nutrition during development to contribute to the variation of complex behaviors and brain morphology of adults are not well understood. Here we use the Drosophila Genetic Reference Panel to identify genes and pathways underlying these interactions in sleep behavior and mushroom body morphology. We show that early-life nutritional restriction effects on sleep behavior and brain morphology depends on the genotype. We mapped genes associated with sleep sensitivity to early-life nutrition, which were enriched for protein-protein interactions responsible for translation, endocytosis regulation, ubiquitination, lipid metabolism, and neural development. By manipulating the expression of candidate genes in the mushroom bodies (MBs) and all neurons, we confirm that genes regulating neural development, translation and insulin signaling contribute to the variable response of sleep and brain morphology to early-life nutrition. We show that the interaction between differential expression of candidate genes with nutritional restriction in early life resides in the MBs or other neurons and that these effects are sex-specific. Natural variations in genes that control the systemic response to nutrition and brain development and function interact with early-life nutrition in different types of neurons to contribute to the variation of brain morphology and adult sleep behavior.