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Malathion is an organophosphate pesticide commonly used on field crops, fruit trees, livestock, agriculture, and for mosquito and medfly control. Aerial applications can result in solubilized malathion in swimming pools and other recreational waters that may come into contact with human skin. To evaluate the human skin absorption of malathion for the assessment of risk associated with human exposures to aqueous solutions, human volunteers were selected and exposed to aqueous solutions of malathion. Participants submerged their arms and hands in twenty liters of dilute malathion solution in either a stagnant or stirred state. The "disappearance method" was applied by measuring malathion concentrations in the water before and after human exposure for various periods of time. No measurable skin absorption was detected in 42% of the participants; the remaining 58% of participants measured minimal absorbed doses of malathion. Analyzing these results through the Hazard Index model for recreational swimmer and bather exposure levels typically measured in contaminated swimming pools and surface waters after bait application indicated that these exposures are an order of magnitude less than a minimal dose known to result in a measurable change in acetylcholinesterase activity. It is concluded that exposure to aqueous malathion in recreational waters following aerial bait applications is not appreciably absorbed, does not result in an effective dose, and therefore is not a public health hazard.

Model organisms such as Drosophila are powerful tools to study the genetic basis of sleep. Previously, we identified the genes pointed and Arginine kinase 1 using selective breeding for long and short sleep duration in an outbred population of Drosophila . pointed is a transcription factor that is part of the epidermal growth factor receptor signaling pathway, while Arginine kinase 1 is involved in proline and arginine metabolism. Conserved orthologs of these genes exist in mice, leading us to hypothesize that they would also impact sleep in a murine model. We generated mutations in the murine orthologs Ets1 and Ckm using CRISPR in a C57BL/6N background and used video analysis to measure sleep in the mice. Both mutations affected sleep parameters, and the effects were observed predominantly in female mice, with males showing fewer differences from littermate controls. The study of natural populations in flies therefore leads to candidate genes with functional conservation on sleep in mammals., (Published by Oxford University Press on behalf of Sleep Research Society 2024.)

Sleep latency, the amount of time that it takes an individual to fall asleep, is a key indicator of sleep need. Sleep latency varies considerably both among and within species and is heritable, but lacks a comprehensive description of its underlying genetic network. Here we conduct a genome-wide association study of sleep latency. Using previously collected sleep and activity data on a wild-derived population of flies, we calculate sleep latency, confirming significant, heritable genetic variation for this complex trait. We identify 520 polymorphisms in 248 genes contributing to variability in sleep latency. Tests of mutations in 23 candidate genes and additional putative pan-neuronal knockdown of 9 of them implicated CG44153, Piezo, Proc-R and Rbp6 in sleep latency. Two large-effect mutations in the genes Proc-R and Piezo were further confirmed via genetic rescue. This work greatly enhances our understanding of the genetic factors that influence variation in sleep latency., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Previous studies of natural variants in Drosophila melanogaster implicated the Wnt signaling receptor frizzled in sleep. Given that the Wnt signaling pathway is highly conserved across species, we hypothesized that frizzled class receptor 1 ( Fzd1 ), the murine homolog of frizzled , would also have a role in sleep. Using a CRISPR transgenic approach, we removed most of the Fzd1 coding region from C57BL/6N mice. We used a video assay to measure sleep characteristics in Fzd1 -deficient mice. As Wnt signaling is known to affect visuospatial memory, we also examined the impact of the deletion on learning and memory using the novel object recognition (NOR) paradigm. Fzd1 -deficient mice had altered sleep compared to littermate controls. The mice did not respond differently to the NOR paradigm compared to controls but did display anxiety-like behavior. Our strategy demonstrates that the study of natural variation in Drosophila sleep translates into candidate genes for sleep in vertebrate species such as the mouse., (Published by Oxford University Press on behalf of Sleep Research Society 2023. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

All but the simplest phenotypes are believed to result from interactions between two or more genes forming complex networks of gene regulation. Sleep is a complex trait known to depend on the system of feedback loops of the circadian clock, and on many other genes; however, the main components regulating the phenotype and how they interact remain an unsolved puzzle. Genomic and transcriptomic data may well provide part of the answer, but a full account requires a suitable quantitative framework. Here we conducted an artificial selection experiment for sleep duration with RNA-seq data acquired each generation. The phenotypic results are robust across replicates and previous experiments, and the transcription data provides a high-resolution, time-course data set for the evolution of sleep-related gene expression. In addition to a Hierarchical Generalized Linear Model analysis of differential expression that accounts for experimental replicates we develop a flexible Gaussian Process model that estimates interactions between genes. 145 gene pairs are found to have interactions that are different from controls. Our method appears to be not only more specific than standard correlation metrics but also more sensitive, finding correlations not significant by other methods. Statistical predictions were compared to experimental data from public databases on gene interactions. Mutations of candidate genes implicated by our results affected night sleep, and gene expression profiles largely met predicted gene-gene interactions., Competing Interests: The authors declare that they have no conflict of interest., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Fertility is a major component of fitness but its genetic architecture remains poorly understood. Using a full diallel cross of 50 Drosophila Genetic Reference Panel inbred lines with whole genome sequences, we found substantial genetic variation in fertility largely attributable to females. We mapped genes associated with variation in female fertility by genome-wide association analysis of common variants in the fly genome. Validation of candidate genes by RNAi knockdown confirmed the role of the dopamine 2-like receptor ( Dop2R ) in promoting egg laying. We replicated the Dop2R effect in an independently collected productivity dataset and showed that the effect of the Dop2R variant was mediated in part by regulatory gene expression variation. This study demonstrates the strong potential of genome-wide association analysis in this diverse panel of inbred strains and subsequent functional analyses for understanding the genetic architecture of fitness traits.

Selective breeding is a classic technique that enables an experimenter to modify a heritable target trait as desired. Direct selective breeding for extreme sleep and circadian phenotypes in flies successfully alters these behaviors, and sleep and circadian perturbations emerge as correlated responses to selection for other traits in mice, rats, and dogs. The application of sequencing technologies to the process of selective breeding identifies the genetic network impacting the selected trait in a holistic way. Breeding techniques preserve the extreme phenotypes generated during selective breeding, generating community resources for further functional testing. Selective breeding is thus a unique strategy that can explore the phenotypic limits of sleep and circadian behavior, discover correlated responses of traits having shared genetic architecture with the target trait, identify naturally-occurring genomic variants and gene expression changes that affect trait variability, and pinpoint genes with conserved roles., (Published by Oxford University Press on behalf of Sleep Research Society (SRS) 2022.)

The endogenous circadian period of animals and humans is typically very close to 24 h. Individuals with much longer circadian periods have been observed, however, and in the case of humans, these deviations have health implications. Previously, we observed a line of Drosophila with a very long average period of 31.3 h for locomotor activity behavior. Preliminary mapping indicated that the long period did not map to known canonical clock genes but instead mapped to multiple chromosomes. Using RNA-Seq, we surveyed the whole transcriptome of fly heads from this line across time and compared it with a wild-type control. A three-way generalized linear model revealed that approximately two-thirds of the genes were expressed differentially among the two genotypes, while only one quarter of the genes varied across time. Using these results, we applied algorithms to search for genes that oscillated over 24 h, identifying genes not previously known to cycle. We identified 166 differentially expressed genes that overlapped with a previous Genome-wide Association Study (GWAS) of circadian behavior, strongly implicating them in the long-period phenotype. We tested mutations in 45 of these genes for their effect on the circadian period. Mutations in Alk, alph, CG10089, CG42540, CG6034, Kairos ( CG6123 ), CG8768, klg, Lar, sick , and tinc had significant effects on the circadian period, with seven of these mutations increasing the circadian period of locomotor activity behavior. Genetic rescue of mutant Kairos restored the circadian period to wild-type levels, suggesting it has a critical role in determining period length in constant darkness.

Sleep is ubiquitous across animal species, but why it persists is not well understood. Here we observe natural selection act on Drosophila sleep by relaxing bi-directional artificial selection for extreme sleep duration for 62 generations. When artificial selection was suspended, sleep increased in populations previously selected for short sleep. Likewise, sleep decreased in populations previously selected for long sleep when artificial selection was relaxed. We measured the corresponding changes in the allele frequencies of genomic variants responding to artificial selection. The allele frequencies of these variants reversed course in response to relaxed selection, and for short sleepers, the changes exceeded allele frequency changes that would be expected under random genetic drift. These observations suggest that the variants are causal polymorphisms for sleep duration responding to natural selection pressure. These polymorphisms may therefore pinpoint the most important regions of the genome maintaining variation in sleep duration.

Behaviors associated with reproduction are major contributors to the evolutionary success of organisms and are subject to many evolutionary forces, including natural and sexual selection, and sexual conflict. Successful reproduction involves a range of behaviors, from finding an appropriate mate, courting, and copulation, to the successful production and (in oviparous animals) deposition of eggs following mating. As a consequence, behaviors and genes associated with reproduction are often under strong selection and evolve rapidly. Courtship rituals in flies follow a multimodal pattern, mediated through visual, chemical, tactile, and auditory signals. Premating behaviors allow males and females to assess the species identity, reproductive state, and condition of their partners. Conflicts between the "interests" of individual males, and/or between the reproductive strategies of males and females, often drive the evolution of reproductive behaviors. For example, seminal proteins transmitted by males often show evidence of rapid evolution, mediated by positive selection. Postmating behaviors, including the selection of oviposition sites, are highly variable and Drosophila species span the spectrum from generalists to obligate specialists. Chemical recognition features prominently in adaptation to host plants for feeding and oviposition. Selection acting on variation in pre-, peri-, and postmating behaviors can lead to reproductive isolation and incipient speciation. Response to selection at the genetic level can include the expansion of gene families, such as those for detecting pheromonal cues for mating, or changes in the expression of genes leading to visual cues such as wing spots that are assessed during mating. Here, we consider the evolution of reproductive behavior in Drosophila at two distinct, yet complementary, scales. Some studies take a microevolutionary approach, identifying genes and networks involved in reproduction, and then dissecting the genetics underlying complex behaviors in D. melanogaster Other studies take a macroevolutionary approach, comparing reproductive behaviors across the genus Drosophila and how these might correlate with environmental cues. A full synthesis of this field will require unification across these levels., (Copyright © 2020 Anholt et al.)

Although sleep is heritable and conserved across species, sleep duration varies from individual to individual. A shared genetic architecture between sleep duration and other evolutionarily important traits could explain this variability. Learning and memory are critical traits sharing a genetic architecture with sleep. We wanted to know whether learning and memory would be altered in extreme long or short sleepers. We therefore assessed the short-term learning and memory ability of flies from the Sleep Inbred Panel (SIP), a collection of 39 extreme long- and short-sleeping inbred lines of Drosophila . Neither long nor short sleepers had appreciable learning, in contrast to a moderate-sleeping control. We also examined the response of long and short sleepers to enriched social conditions, a paradigm previously shown to induce morphological changes in the brain. While moderate-sleeping control flies had increased daytime sleep and quantifiable increases in brain structures under enriched social conditions, flies of the Sleep Inbred Panel did not display these changes. The SIP thus emerges as an important model for the relationship between sleep and learning and memory., Competing Interests: Conflicts of Interest: The authors declare no conflicts of interest.

Circadian rhythms influence physiological processes from sleep-wake cycles to body temperature and are controlled by highly conserved cycling molecules. Although the mechanistic basis of the circadian clock has been known for decades, the extent to which circadian rhythms vary in nature and the underlying genetic basis for that variation is not well understood. We measured circadian period (Ʈ) and rhythmicity index in the Drosophila Genetic Reference Panel (DGRP) and observed extensive genetic variation in both. Seven DGRP lines had sexually dimorphic arrhythmicity and one line had an exceptionally long Ʈ. Genome-wide analyses identified 584 polymorphisms in 268 genes. We observed differences among transcripts for nine genes predicted to interact among themselves and canonical clock genes in the long period line and a control. Mutations/RNAi knockdown targeting these genes also affected circadian behavior. Our observations reveal that complex genetic interactions influence high levels of variation in circadian phenotypes.

Understanding how genomic variation causes differences in observable phenotypes remains a major challenge in biology. It is difficult to trace the sequence of events originating from genomic variants to changes in transcriptional responses or protein modifications. Ideally, one would conduct experiments with individuals that are at either extreme of the trait of interest, but such resources are often not available. Further, advances in genome editing will enable testing of candidate polymorphisms individually and in combination. Here we have created a resource for the study of sleep with 39 inbred lines of Drosophila -the Sleep Inbred Panel (SIP). SIP lines have stable long- and short-sleeping phenotypes developed from naturally occurring polymorphisms. These lines are fully sequenced, enabling more accurate targeting for genome editing and transgenic constructs. This panel facilitates the study of intermediate transcriptional and proteomic correlates of sleep, and supports genome editing studies to verify polymorphisms associated with sleep duration., (Copyright © 2018 Negron et al.)

DNA copy number variation is associated with many high phenotypic heterogeneity disorders. We systematically examined the impact of Drosophila melanogaster deletions on gene expression profiles to ask whether increased expression variability owing to reduced gene dose might underlie this phenotypic heterogeneity. Indeed, we found that one-dose genes have higher gene expression variability relative to two-dose genes. We then asked whether this increase in variability could be explained by intrinsic noise within cells due to stochastic biochemical events, or whether expression variability is due to extrinsic noise arising from more complex interactions. Our modeling showed that intrinsic gene expression noise averages at the organism level and thus cannot explain increased variation in one-dose gene expression. Interestingly, expression variability was related to the magnitude of expression compensation, suggesting that regulation, induced by gene dose reduction, is noisy. In a remarkable exception to this rule, the single X chromosome of males showed reduced expression variability, even compared with two-dose genes. Analysis of sex-transformed flies indicates that X expression variability is independent of the male differentiation program. Instead, we uncovered a correlation between occupancy of the chromatin-modifying protein encoded by males absent on the first ( mof ) and expression variability, linking noise suppression to the specialized X chromosome dosage compensation system. MOF occupancy on autosomes in both sexes also lowered transcriptional noise. Our results demonstrate that gene dose reduction can lead to heterogeneous responses, which are often noisy. This has implications for understanding gene network regulatory interactions and phenotypic heterogeneity. Additionally, chromatin modification appears to play a role in dampening transcriptional noise., (Copyright © 2018 Lee et al.)

Patterns of sleep often vary among individuals. But sleep and activity may also vary within an individual, fluctuating in pattern across time. One possibility is that these daily fluctuations in sleep are caused by the underlying genotype of the individual. However, differences attributable to genetic causes are difficult to distinguish from environmental factors in outbred populations such as humans. We therefore employed Drosophila as a model of intra-individual variability in sleep using previously collected sleep and activity data from the Drosophila Genetic Reference Panel, a collection of wild-derived inbred lines. Individual flies had significant daily fluctuations in their sleep patterns, and these fluctuations were heritable. Using the standard deviation of sleep parameters as a metric, we conducted a genome-wide association study. We found 663 polymorphisms in 104 genes associated with daily fluctuations in sleep. We confirmed the effects of 12 candidate genes on the standard deviation of sleep parameters. Our results suggest that daily fluctuations in sleep patterns are due in part to gene activity., (Published by Oxford University Press on behalf of Sleep Research Society (SRS) 2017.)

Why do some individuals need more sleep than others? Forward mutagenesis screens in flies using engineered mutations have established a clear genetic component to sleep duration, revealing mutants that convey very long or short sleep. Whether such extreme long or short sleep could exist in natural populations was unknown. We applied artificial selection for high and low night sleep duration to an outbred population of Drosophila melanogaster for 13 generations. At the end of the selection procedure, night sleep duration diverged by 9.97 hours in the long and short sleeper populations, and 24-hour sleep was reduced to 3.3 hours in the short sleepers. Neither long nor short sleeper lifespan differed appreciably from controls, suggesting little physiological consequences to being an extreme long or short sleeper. Whole genome sequence data from seven generations of selection revealed several hundred thousand changes in allele frequencies at polymorphic loci across the genome. Combining the data from long and short sleeper populations across generations in a logistic regression implicated 126 polymorphisms in 80 candidate genes, and we confirmed three of these genes and a larger genomic region with mutant and chromosomal deficiency tests, respectively. Many of these genes could be connected in a single network based on previously known physical and genetic interactions. Candidate genes have known roles in several classic, highly conserved developmental and signaling pathways-EGFR, Wnt, Hippo, and MAPK. The involvement of highly pleiotropic pathway genes suggests that sleep duration in natural populations can be influenced by a wide variety of biological processes, which may be why the purpose of sleep has been so elusive.

Ovariole number has a direct role in the number of eggs produced by an insect, suggesting that it is a key morphological fitness trait. Many studies have documented the variability of ovariole number and its relationship to other fitness and life-history traits in natural populations of Drosophila However, the genes contributing to this variability are largely unknown. Here, we conducted a genome-wide association study of ovariole number in a natural population of flies. Using mutations and RNAi-mediated knockdown, we confirmed the effects of 24 candidate genes on ovariole number, including a novel gene, anneboleyn (formerly CG32000 ), that impacts both ovariole morphology and numbers of offspring produced. We also identified pleiotropic genes between ovariole number traits and sleep and activity behavior. While few polymorphisms overlapped between sleep parameters and ovariole number, 39 candidate genes were nevertheless in common. We verified the effects of seven genes on both ovariole number and sleep: bin3 , blot , CG42389 , kirre , slim , VAChT , and zfh1 Linkage disequilibrium among the polymorphisms in these common genes was low, suggesting that these polymorphisms may evolve independently., (Copyright © 2017 Lobell et al.)

Differences in phenotype among genetically identical individuals exposed to the same environmental condition are often noted in genetic studies. Despite this commonplace observation, little is known about the causes of this variability, which has been termed microenvironmental plasticity. One possibility is that stochastic or technical sources of variance produce these differences. A second possibility is that this variation has a genetic component. We have explored gene expression robustness in the transcriptomes of 730 individual Drosophila melanogaster of 16 fixed genotypes, nine of which are infected with Wolbachia Three replicates of flies were grown, controlling for food, day/night cycles, humidity, temperature, sex, mating status, social exposure, and circadian timing of RNA extraction. Despite the use of inbred genotypes, and carefully controlled experimental conditions, thousands of genes were differentially expressed, revealing a unique and dynamic transcriptional signature for each individual fly. We found that 23% of the transcriptome was differentially expressed among individuals, and that the variability in gene expression among individuals is influenced by genotype. This transcriptional variation originated from specific gene pathways, suggesting a plastic response to the microenvironment; but there was also evidence of gene expression differences due to stochastic fluctuations. These observations reveal previously unappreciated genetic sources of variability in gene expression among individuals, which has implications for complex trait genetics and precision medicine., (Copyright © 2016 Lin et al.)

The heparan sulfate proteoglycan syndecans are transmembrane proteins involved in multiple physiological processes, including cell-matrix adhesion and inflammation. Recent evidence from model systems and humans suggest that syndecans have a role in energy balance and nutrient metabolism regulation. However, much remains to be learned about the mechanisms through which syndecans influence these phenotypes. Previously, we reported that Drosophila melanogaster Syndecan (Sdc) mutants had reduced metabolic activity compared to controls. Here, we knocked down endogenous Sdc expression in the fat body (the functional equivalent of mammalian adipose tissue and liver) to investigate whether the effects on metabolism originate from this tissue. We found that knocking down Sdc in the fat body leads to flies with higher levels of glycogen and fat and that survive longer during starvation, likely due to their extra energy reserves and an increase in gluconeogenesis. However, compared to control flies, they are also more sensitive to environmental stresses (e.g. bacterial infection and cold) and have reduced metabolic activity under normal feeding conditions. Under the same conditions, fat-body Sdc reduction enhances expression of genes involved in glyceroneogenesis and gluconeogenesis and induces a drastic decrease in phosphorylation levels of AKT and extracellular signal regulated kinase 1/2 (ERK1/2). Altogether, these findings strongly suggest that Drosophila fat body Sdc is involved in a mechanism that shifts resources to different physiological functions according to nutritional status., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Mutation and natural selection shape the genetic variation in natural populations. Here, we directly estimated the spontaneous mutation rate by sequencing new Drosophila mutation accumulation lines maintained with minimal natural selection. We inferred strong stabilizing natural selection on quantitative traits because genetic variation among wild-derived inbred lines was much lower than predicted from a neutral model and the mutational effects were much larger than allelic effects of standing polymorphisms. Stabilizing selection could act directly on the traits, or indirectly from pleiotropic effects on fitness. However, our data are not consistent with simple models of mutation-stabilizing selection balance; therefore, further empirical work is needed to assess the balance of evolutionary forces responsible for quantitative genetic variation., Competing Interests: The authors declare that no competing interests exist.

Background: A generally accepted approach to the analysis of RNA-Seq read count data does not yet exist. We sequenced the mRNA of 726 individuals from the Drosophila Genetic Reference Panel in order to quantify differences in gene expression among single flies. One of our experimental goals was to identify the optimal analysis approach for the detection of differential gene expression among the factors we varied in the experiment: genotype, environment, sex, and their interactions. Here we evaluate three different filtering strategies, eight normalization methods, and two statistical approaches using our data set. We assessed differential gene expression among factors and performed a statistical power analysis using the eight biological replicates per genotype, environment, and sex in our data set., Results: We found that the most critical considerations for the analysis of RNA-Seq read count data were the normalization method, underlying data distribution assumption, and numbers of biological replicates, an observation consistent with previous RNA-Seq and microarray analysis comparisons. Some common normalization methods, such as Total Count, Quantile, and RPKM normalization, did not align the data across samples. Furthermore, analyses using the Median, Quantile, and Trimmed Mean of M-values normalization methods were sensitive to the removal of low-expressed genes from the data set. Although it is robust in many types of analysis, the normal data distribution assumption produced results vastly different than the negative binomial distribution. In addition, at least three biological replicates per condition were required in order to have sufficient statistical power to detect expression differences among the three-way interaction of genotype, environment, and sex., Conclusions: The best analysis approach to our data was to normalize the read counts using the DESeq method and apply a generalized linear model assuming a negative binomial distribution using either edgeR or DESeq software. Genes having very low read counts were removed after normalizing the data and fitting it to the negative binomial distribution. We describe the results of this evaluation and include recommended analysis strategies for RNA-Seq read count data.

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.

Background: Mitochondria are organelles found in nearly all eukaryotic cells that play a crucial role in cellular survival and function. Mitochondrial function is under the control of nuclear and mitochondrial genomes. While the latter has been the focus of most genetic research, we remain largely ignorant about the nuclear-encoded genomic control of inter-individual variability in mitochondrial function. Here, we used Drosophila melanogaster as our model organism to address this question., Results: We quantified mitochondrial state 3 and state 4 respiration rates and P:O ratio in mitochondria isolated from the thoraces of 40 sequenced inbred lines of the Drosophila Genetic Reference Panel. We found significant within-population genetic variability for all mitochondrial traits. Hence, we performed genome-wide association mapping and identified 141 single nucleotide polymorphisms (SNPs) associated with differences in mitochondrial respiration and efficiency (P ≤1 × 10-5). Gene-centered regression models showed that 2-3 SNPs can explain 31, 13, and 18% of the phenotypic variation in state 3, state 4, and P:O ratio, respectively. Most of the genes tagged by the SNPs are involved in organ development, second messenger-mediated signaling pathways, and cytoskeleton remodeling. One of these genes, sallimus (sls), encodes a component of the muscle sarcomere. We confirmed the direct effect of sls on mitochondrial respiration using two viable mutants and their coisogenic wild-type strain. Furthermore, correlation network analysis revealed that sls functions as a transcriptional hub in a co-regulated module associated with mitochondrial respiration and is connected to CG7834, which is predicted to encode a protein with mitochondrial electron transfer flavoprotein activity. This latter finding was also verified in the sls mutants., Conclusions: Our results provide novel insights into the genetic factors regulating natural variation in mitochondrial function in D. melanogaster. The integrative genomic approach used in our study allowed us to identify sls as a novel hub gene responsible for the regulation of mitochondrial respiration in muscle sarcomere and to provide evidence that sls might act via the electron transfer flavoprotein/ubiquinone oxidoreductase complex.

Epistasis is an important feature of the genetic architecture of quantitative traits, but the dynamics of epistatic interactions in natural populations and the relationship between epistasis and pleiotropy remain poorly understood. Here, we studied the effects of epistatic modifiers that segregate in a wild-derived Drosophila melanogaster population on the mutational effects of P-element insertions in Semaphorin-5C (Sema-5c) and Calreticulin (Crc), pleiotropic genes that affect olfactory behaviour and startle behaviour and, in the case of Crc, sleep phenotypes. We introduced Canton-S B (CSB) third chromosomes with or without a P-element insertion at the Crc or Sema-5c locus in multiple wild-derived inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and assessed the effects of epistasis on the olfactory response to benzaldehyde and, for Crc, also on sleep. In each case, we found substantial epistasis and significant variation in the magnitude of epistasis. The predominant direction of epistatic effects was to suppress the mutant phenotype. These observations support a previous study on startle behaviour using the same D. melanogaster chromosome substitution lines, which concluded that suppressing epistasis may buffer the effects of new mutations. However, epistatic effects are not correlated among the different phenotypes. Thus, suppressing epistasis appears to be a pervasive general feature of natural populations to protect against the effects of new mutations, but different epistatic interactions modulate different phenotypes affected by mutations at the same pleiotropic gene.

Syndecans are a family of type-I transmembrane proteins that are involved in cell-matrix adhesion, migration, neuronal development, and inflammation. Previous quantitative genetic studies pinpointed Drosophila Syndecan (dSdc) as a positional candidate gene affecting variation in fat storage between two Drosophila melanogaster strains. Here, we first used quantitative complementation tests with dSdc mutants to confirm that natural variation in this gene affects variability in Drosophila fat storage. Next, we examined the effects of a viable dSdc mutant on Drosophila whole-body energy metabolism and associated traits. We observed that young flies homozygous for the dSdc mutation had reduced fat storage and slept longer than homozygous wild-type flies. They also displayed significantly reduced metabolic rate, lower expression of spargel (the Drosophila homologue of PGC-1), and reduced mitochondrial respiration. Compared to control flies, dSdc mutants had lower expression of brain insulin-like peptides, were less fecund, more sensitive to starvation, and had reduced life span. Finally, we tested for association between single nucleotide polymorphisms (SNPs) in the human SDC4 gene and variation in body composition, metabolism, glucose homeostasis, and sleep traits in a cohort of healthy early pubertal children. We found that SNP rs4599 was significantly associated with resting energy expenditure (P = 0.001 after Bonferroni correction) and nominally associated with fasting glucose levels (P = 0.01) and sleep duration (P = 0.044). On average, children homozygous for the minor allele had lower levels of glucose, higher resting energy expenditure, and slept shorter than children homozygous for the common allele. We also observed that SNP rs1981429 was nominally associated with lean tissue mass (P = 0.035) and intra-abdominal fat (P = 0.049), and SNP rs2267871 with insulin sensitivity (P = 0.037). Collectively, our results in Drosophila and humans argue that syndecan family members play a key role in the regulation of body metabolism.

Recent human studies reveal a widespread association between short sleep and obesity. Two hypotheses, which are not mutually exclusive, might explain this association. First, genetic factors that reduce endogenous sleep times might also impact energy stores, an assertion that we confirmed in a previous study. Second, metabolism may be altered by chronic partial sleep deprivation. Here we address the second assertion by measuring the impact of long-term partial sleep deprivation on energy stores using Drosophila as a model. We subjected flies to long-term partial sleep deprivation via two different methods: a mechanical stimulus and a light stimulus. We then measured whole-body triglycerides and glycogen, two important sources of energy for the fly, and compared them to un-stimulated controls. We also measured changes in energy stores in response to a random circadian clock shift. Sex and line-dependent alterations in glycogen and/or triglyceride levels occurred in response to the circadian clock shift and in flies subjected to a single night of sleep deprivation using light. Thus, consistent with previous studies, our findings suggest that acute sleep loss and changes to the circadian clock can alter metabolism. Significant changes in energy stores were also observed when flies were subjected to chronic sleep loss via the mechanical stimulus, although not the light stimulus. Interestingly, mechanical stimulation resulted in the same change in energy stores even when it was not associated with sleep deprivation, suggesting that the changes are caused by stress rather than sleep loss. These findings emphasize the importance of taking stress into account when evaluating the relationship between sleep loss and metabolism.

Most behaviors manifest themselves through interactions with environments. Sleep, however, is characterized by immobility and reduced responsiveness. Although nearly all animals sleep, the purpose of sleep remains an enduring puzzle. Drosophila melanogaster exhibits all the behavioral characteristics of mammalian sleep, enabling the use of powerful genetic approaches to dissect conserved fundamental neurogenetic aspects of sleep. Drosophila studies over the past four years have identified novel genes and pathways modulating sleep, such as Shaker and sleepless, and candidate brain regions known to function in circadian regulation and learning and memory. Advances in systems genetics coupled with the ability to target specific brain regions enable the characterization of transcriptional networks and neural circuits contributing to phenotypic variation in sleep.

Sleep disorders are common in humans, and sleep loss increases the risk of obesity and diabetes. Studies in Drosophila have revealed molecular pathways and neural tissues 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 expression to identify candidate genes. We independently confirmed that molecular polymorphisms in Catsup (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. Quantitative genetic analysis of natural phenotypic variation is an efficient method for revealing candidate genes and pathways.

Although intensively studied, the biological purpose of sleep is not known. To identify candidate genes affecting sleep, we assayed 136 isogenic P-element insertion lines of Drosophila melanogaster. Since sleep has been negatively correlated with energy reserves across taxa, we measured energy stores (whole-body protein, glycogen, and triglycerides) in these lines as well. Twenty-one insertions with known effects on physiology, development, and behavior affect 24-hr sleep time. Thirty-two candidate insertions significantly impact energy stores. Mutational genetic correlations among sleep parameters revealed that the genetic basis of the transition between sleep and waking states in males and females may be different. Furthermore, sleep bout number can be decoupled from waking activity in males, but not in females. Significant genetic correlations are present between sleep phenotypes and glycogen stores in males, while sleep phenotypes are correlated with triglycerides in females. Differences observed in male and female sleep behavior in flies may therefore be related to sex-specific differences in metabolic needs. Sleep thus emerges as a complex trait that exhibits extensive pleiotropy and sex specificity. The large mutational target that we observed implicates genes functioning in a variety of biological processes, suggesting that sleep may serve a number of different functions rather than a single purpose.

Quantitative traits are shaped by networks of pleiotropic genes . To understand the mechanisms that maintain genetic variation for quantitative traits in natural populations and to predict responses to artificial and natural selection, we must evaluate pleiotropic effects of underlying quantitative trait genes and define functional allelic variation at the level of quantitative trait nucleotides (QTNs). Catecholamines up (Catsup), which encodes a negative regulator of tyrosine hydroxylase , the rate-limiting step in the synthesis of the neurotransmitter dopamine, is a pleiotropic quantitative trait gene in Drosophila melanogaster. We used association mapping to determine whether the same or different QTNs at Catsup are associated with naturally occurring variation in multiple quantitative traits. We sequenced 169 Catsup alleles from a single population and detected 33 polymorphisms with little linkage disequilibrium (LD). Different molecular polymorphisms in Catsup are independently associated with variation in longevity, locomotor behavior, and sensory bristle number. Most of these polymorphisms are potentially functional variants in protein coding regions, have large effects, and are not common. Thus, Catsup is a pleiotropic quantitative trait gene, but individual QTNs do not have pleiotropic effects. Molecular population genetic analyses of Catsup sequences are consistent with balancing selection maintaining multiple functional polymorphisms.

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.

The ability to withstand periods of scarce food resources is an important fitness trait. Starvation resistance is a quantitative trait controlled by multiple interacting genes and exhibits considerable genetic variation in natural populations. This genetic variation could be maintained in the face of strong selection due to a trade-off in resource allocation between reproductive activity and individual survival. Knowledge of the genes affecting starvation tolerance and the subset of genes that affect variation in starvation resistance in natural populations would enable us to evaluate this hypothesis from a quantitative genetic perspective. We screened 933 co-isogenic P-element insertion lines to identify candidate genes affecting starvation tolerance. A total of 383 P-element insertions induced highly significant and often sex-specific mutational variance in starvation resistance. We also used deficiency complementation mapping followed by complementation to mutations to identify 12 genes contributing to variation in starvation resistance between two wild-type strains. The genes we identified are involved in oogenesis, metabolism, and feeding behaviors, indicating a possible link to reproduction and survival. However, we also found genes with cell fate specification and cell proliferation phenotypes, which implies that resource allocation during development and at the cellular level may also influence the phenotypic response to starvation.