Genome-wide association study of sleep in Drosophila melanogaster

BACKGROUND: Sleep is a highly conserved behavior, yet its duration and pattern vary extensively among species and between individuals within species. The genetic basis of natural variation in sleep remains unknown. RESULTS: We used the Drosophila Genetic Reference Panel (DGRP) to perform a genome-wide association (GWA) study of sleep in D. melanogaster. We identified candidate single nucleotide polymorphisms (SNPs) associated with differences in the mean as well as the environmental sensitivity of sleep traits; these SNPs typically had sex-specific or sex-biased effects, and were generally located in non-coding regions. The majority of SNPs (80.3%) affecting sleep were at low frequency and had moderately large effects. Additive models incorporating multiple SNPs explained as much as 55% of the genetic variance for sleep in males and females. Many of these loci are known to interact physically and/or genetically, enabling us to place them in candidate genetic networks. We confirmed the role of seven novel loci on sleep using insertional mutagenesis and RNA interference. CONCLUSIONS: We identified many SNPs in novel loci that are potentially associated with natural variation in sleep, as well as SNPs within genes previously known to affect Drosophila sleep. Several of the candidate genes have human homologues that were identified in studies of human sleep, suggesting that genes affecting variation in sleep are conserved across species. Our discovery of genetic variants that influence environmental sensitivity to sleep may have a wider application to all GWA studies, because individuals with highly plastic genotypes will not have consistent phenotypes

Phenotypic and transcriptional response to selection for alcohol sensitivity in Drosophila melanogaster

Gene-expression profiling combined with selection for genetically divergent Drosophila lines either highly sensitive or resistant to ethanol exposure has been used to identify candidate genes that affect alcohol sensitivity, including 23 novel genes that have human orthologs

Transcriptional response to alcohol exposure in Drosophila melanogaster

BACKGROUND: Alcoholism presents widespread social and human health problems. Alcohol sensitivity, the development of tolerance to alcohol and susceptibility to addiction vary in the population. Genetic factors that predispose to alcoholism remain largely unknown due to extensive genetic and environmental variation in human populations. Drosophila, however, allows studies on genetically identical individuals in controlled environments. Although addiction to alcohol has not been demonstrated in Drosophila, flies show responses to alcohol exposure that resemble human intoxication, including hyperactivity, loss of postural control, sedation, and exposure-dependent development of tolerance. RESULTS: We assessed whole-genome transcriptional responses following alcohol exposure and demonstrate immediate down-regulation of genes affecting olfaction, rapid upregulation of biotransformation enzymes and, concomitant with development of tolerance, altered transcription of transcriptional regulators, proteases and metabolic enzymes, including biotransformation enzymes and enzymes associated with fatty acid biosynthesis. Functional tests of P-element disrupted alleles corresponding to genes with altered transcription implicated 75% of these in the response to alcohol, two-thirds of which have human orthologues. CONCLUSION: Expression microarray analysis is an efficient method for identifying candidate genes affecting complex behavioral and physiological traits, including alcohol abuse. Drosophila provides a valuable genetic model for comparative genomic analysis, which can inform subsequent studies in human populations. Transcriptional analyses following alcohol exposure in Drosophila implicate biotransformation pathways, transcriptional regulators, proteolysis and enzymes that act as metabolic switches in the regulation of fatty acid metabolism as important targets for future studies of the physiological consequences of human alcohol abuse

Quantitative genomics of starvation stress resistance in Drosophila

BACKGROUND: A major challenge of modern biology is to understand the networks of interacting genes regulating complex traits, and the subset of these genes that affect naturally occurring quantitative genetic variation. Previously, we used P-element mutagenesis and quantitative trait locus (QTL) mapping in Drosophila to identify candidate genes affecting resistance to starvation stress, and variation in resistance to starvation stress between the Oregon-R (Ore) and 2b strains. Here, we tested the efficacy of whole-genome transcriptional profiling for identifying genes affecting starvation stress resistance. RESULTS: We evaluated whole-genome transcript abundance for males and females of Ore, 2b, and four recombinant inbred lines derived from them, under control and starved conditions. There were significant differences in transcript abundance between the sexes for nearly 50% of the genome, while the transcriptional response to starvation stress involved approximately 25% of the genome. Nearly 50% of P-element insertions in 160 genes with altered transcript abundance during starvation stress had mutational effects on starvation tolerance. Approximately 5% of the genome exhibited genetic variation in transcript abundance, which was largely attributable to regulation by unlinked genes. Genes exhibiting variation in transcript abundance among lines did not cluster within starvation resistance QTLs, and none of the candidate genes affecting variation in starvation resistance between Ore and 2b exhibited significant differences in transcript abundance between lines. CONCLUSIONS: Expression profiling is a powerful method for identifying networks of pleiotropic genes regulating complex traits, but the relationship between variation in transcript abundance among lines used to map QTLs and genes affecting variation in quantitative traits is complicated

Quantitative genomics of locomotor behavior in Drosophila melanogaster

The locomotor behavior of Drosophila melanogaster was quantified in a large population of inbred lines derived from a single natural population, showing that many pleiotropic genes show correlated transcriptional responses to multiple behaviors

Mutations in many genes affect aggressive behavior in Drosophila melanogaster

BACKGROUND: Aggressive behavior in animals is important for survival and reproduction. Identifying the underlying genes and environmental contexts that affect aggressive behavior is important for understanding the evolutionary forces that maintain variation for aggressive behavior in natural populations, and to develop therapeutic interventions to modulate extreme levels of aggressive behavior in humans. While the role of neurotransmitters and a few other molecules in mediating and modulating levels of aggression is well established, it is likely that many additional genetic pathways remain undiscovered. Drosophila melanogaster has recently been established as an excellent model organism for studying the genetic basis of aggressive behavior. Here, we present the results of a screen of 170 Drosophila P-element insertional mutations for quantitative differences in aggressive behavior from their co-isogenic control line. RESULTS: We identified 59 mutations in 57 genes that affect aggressive behavior, none of which had been previously implicated to affect aggression. Thirty-two of these mutants exhibited increased aggression, while 27 lines were less aggressive than the control. Many of the genes affect the development and function of the nervous system, and are thus plausibly relevant to the execution of complex behaviors. Others affect basic cellular and metabolic processes, or are mutations in computationally predicted genes for which aggressive behavior is the first biological annotation. Most of the mutations had pleiotropic effects on other complex traits. We characterized nine of these mutations in greater detail by assessing transcript levels throughout development, morphological changes in the mushroom bodies, and restoration of control levels of aggression in revertant alleles. All of the P-element insertions affected the tagged genes, and had pleiotropic effects on brain morphology. CONCLUSION: This study reveals that many more genes than previously suspected affect aggressive behavior, and that these genes have widespread pleiotropic effects. Given the conservation of aggressive behavior among different animal species, these are novel candidate genes for future study in other animals, including humans

A transcriptional network associated with natural variation in Drosophila aggressive behavior

A genome-wide screen of inbred Drosophila lines together with transcriptional network modeling reveals insights into the genetic bases of heritable aggression

Systems genetics analysis of body weight and energy metabolism traits in Drosophila melanogaster

<p>Abstract</p> <p>Background</p> <p>Obesity and phenotypic traits associated with this condition exhibit significant heritability in natural populations of most organisms. While a number of genes and genetic pathways have been implicated to play a role in obesity associated traits, the genetic architecture that underlies the natural variation in these traits is largely unknown. Here, we used 40 wild-derived inbred lines of <it>Drosophila melanogaster </it>to quantify genetic variation in body weight, the content of three major metabolites (glycogen, triacylglycerol, and glycerol) associated with obesity, and metabolic rate in young flies. We chose these lines because they were previously screened for variation in whole-genome transcript abundance and in several adult life-history traits, including longevity, resistance to starvation stress, chill-coma recovery, mating behavior, and competitive fitness. This enabled us not only to identify candidate genes and transcriptional networks that might explain variation for energy metabolism traits, but also to investigate the genetic interrelationships among energy metabolism, behavioral, and life-history traits that have evolved in natural populations.</p> <p>Results</p> <p>We found significant genetically based variation in all traits. Using a genome-wide association screen for single feature polymorphisms and quantitative trait transcripts, we identified 337, 211, 237, 553, and 152 novel candidate genes associated with body weight, glycogen content, triacylglycerol storage, glycerol levels, and metabolic rate, respectively. Weighted gene co-expression analyses grouped transcripts associated with each trait in significant modules of co-expressed genes and we interpreted these modules in terms of their gene enrichment based on Gene Ontology analysis. Comparison of gene co-expression modules for traits in this study with previously determined modules for life-history traits identified significant modular pleiotropy between glycogen content, body weight, competitive fitness, and starvation resistance.</p> <p>Conclusions</p> <p>Combining a large phenotypic dataset with information on variation in genome wide transcriptional profiles has provided insight into the complex genetic architecture underlying natural variation in traits that have been associated with obesity. Our findings suggest that understanding the maintenance of genetic variation in metabolic traits in natural populations may require that we understand more fully the degree to which these traits are genetically correlated with other traits, especially those directly affecting fitness.</p

Genetic basis of transcriptome diversity in Drosophila melanogaster

Understanding how DNA sequence variation is translated into variation for complex phenotypes has remained elusive but is essential for predicting adaptive evolution, for selecting agriculturally important animals and crops, and for personalized medicine. Gene expression may provide a link between variation in DNA sequence and organismal phenotypes, and its abundance can be measured efficiently and accurately. Here we quantified genomewide variation in gene expression in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP), increasing the annotated Drosophila transcriptome by 11%, including thousands of novel transcribed regions (NTRs). We found that 42%of the Drosophila transcriptome is genetically variable in males and females, including the NTRs, and is organized into modules of genetically correlated transcripts. We found that NTRs often were negatively correlated with the expression of protein-coding genes, which we exploited to annotate NTRs functionally. We identified regulatory variants for the mean and variance of gene expression, which have largely independent genetic control. Expression quantitative trait loci (eQTLs) for the mean, but not for the variance, of gene expression were concentrated near genes. Notably, the variance eQTLs often interacted epistatically with local variants in these genes to regulate gene expression. This comprehensive characterization of population-scale diversity of transcriptomes and its genetic basis in the DGRP is critically important for a systems understanding of quantitative trait variation