Quantitative trait loci affecting starvation resistance in Drosophila melanogaster

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.

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.

Physiological and metabolomic consequences of reduced expression of the Drosophila brummer triglyceride Lipase

Disruption of lipolysis has widespread effects on intermediary metabolism and organismal phenotypes. Defects in lipolysis can be modeled in Drosophila melanogaster through genetic manipulations of brummer (bmm), which encodes a triglyceride lipase orthologous to mammalian Adipose Triglyceride Lipase. RNAi-mediated knock-down of bmm in all tissues or metabolic specific tissues results in reduced locomotor activity, altered sleep patterns and reduced lifespan. Metabolomic analysis on flies in which bmm is downregulated reveals a marked reduction in medium chain fatty acids, long chain saturated fatty acids and long chain monounsaturated and polyunsaturated fatty acids, and an increase in diacylglycerol levels. Elevated carbohydrate metabolites and tricarboxylic acid intermediates indicate that impairment of fatty acid mobilization as an energy source may result in upregulation of compensatory carbohydrate catabolism. bmm downregulation also results in elevated levels of serotonin and dopamine neurotransmitters, possibly accounting for the impairment of locomotor activity and sleep patterns. Physiological phenotypes and metabolomic changes upon reduction of bmm expression show extensive sexual dimorphism. Altered metabolic states in the Drosophila model are relevant for understanding human metabolic disorders, since pathways of intermediary metabolism are conserved across phyla.

A screen for sleep and starvation resistance identifies a wake-promoting role for the auxiliary channel unc79

The regulation of sleep and metabolism are highly interconnected, and dysregulation of sleep is linked to metabolic diseases that include obesity, diabetes, and heart disease. Furthermore, both acute and long-term changes in diet potently impact sleep duration and quality. To identify novel factors that modulate interactions between sleep and metabolic state, we performed a genetic screen for their roles in regulating sleep duration, starvation resistance, and starvation-dependent modulation of sleep. This screen identified a number of genes with potential roles in regulating sleep, metabolism, or both processes. One such gene encodes the auxiliary ion channel UNC79, which was implicated in both the regulation of sleep and starvation resistance. Genetic knockdown or mutation of unc79 results in flies with increased sleep duration, as well as increased starvation resistance. Previous findings have shown that unc79 is required in pacemaker for 24-hours circadian rhythms. Here, we find that unc79 functions in the mushroom body, but not pacemaker neurons, to regulate sleep duration and starvation resistance. Together, these findings reveal spatially localized separable functions of unc79 in the regulation of circadian behavior, sleep, and metabolic function.

The tweety Gene Family: From Embryo to Disease

The tweety genes encode gated chloride channels that are found in animals, plants, and even simple eukaryotes, signifying their deep evolutionary origin. In vertebrates, the tweety gene family is highly conserved and consists of three members—ttyh1, ttyh2, and ttyh3—that are important for the regulation of cell volume. While research has elucidated potential physiological functions of ttyh1 in neural stem cell maintenance, proliferation, and filopodia formation during neural development, the roles of ttyh2 and ttyh3 are less characterized, though their expression patterns during embryonic and fetal development suggest potential roles in the development of a wide range of tissues including a role in the immune system in response to pathogen-associated molecules. Additionally, members of the tweety gene family have been implicated in various pathologies including cancers, particularly pediatric brain tumors, and neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. Here, we review the current state of research using information from published articles and open-source databases on the tweety gene family with regard to its structure, evolution, expression during development and adulthood, biochemical and cellular functions, and role in human disease. We also identify promising areas for further research to advance our understanding of this important, yet still understudied, family of genes.

Functional Diversification, Redundancy, and Epistasis among Paralogs of the Drosophila melanogaster Obp50a-d Gene Cluster

Large multigene families, such as the insect odorant-binding proteins (OBPs), are thought to arise through functional diversification after repeated gene duplications. Whereas many OBPs function in chemoreception, members of this family are also expressed in tissues outside chemosensory organs. Paralogs of the Obp50 gene cluster are expressed in metabolic and male reproductive tissues, but their functions and interrelationships remain unknown. Here, we report the genetic dissection of four members of the Obp50 cluster, which are in close physical proximity without intervening genes. We used CRISPR technology to excise the entire cluster while introducing a PhiC31 reintegration site to reinsert constructs in which different combinations of the constituent Obp genes were either intact or rendered inactive. We performed whole transcriptome sequencing and assessed sexually dimorphic changes in transcript abundances (transcriptional niches) associated with each gene-edited genotype. Using this approach, we were able to estimate redundancy, additivity, diversification, and epistasis among Obp50 paralogs. We analyzed the effects of gene editing of this cluster on organismal phenotypes and found a significant skewing of sex ratios attributable to Obp50a, and sex-specific effects on starvation stress resistance attributable to Obp50d. Thus, there is functional diversification within the Obp50 cluster with Obp50a contributing to development and Obp50d to stress resistance. The deletion-reinsertion approach we applied to the Obp50 cluster provides a general paradigm for the genetic dissection of paralogs of multigene families.

Behavioral and Transcriptional Response to Selection for Olfactory Behavior in Drosophila

The detection, discrimination, and behavioral responses to chemical cues in the environment can have marked effects on organismal survival and reproduction, eliciting attractive or aversive behavior. To gain insight into mechanisms mediating this hedonic valence, we applied thirty generations of divergent artificial selection for Drosophila melanogaster olfactory behavior. We independently selected for positive and negative behavioral responses to two ecologically relevant chemical compounds: 2,3-butanedione and cyclohexanone. We also tested the correlated responses to selection by testing behavioral responses to other odorants and life history traits. Measurements of behavioral responses of the selected lines and unselected controls to additional odorants showed that the mechanisms underlying responses to these odorants are, in some cases, differentially affected by selection regime and generalization of the response to other odorants was only detected in the 2,3-butanedione selection lines. Food consumption and lifespan varied with selection regime and, at times, sex. An analysis of gene expression of both selection regimes identified multiple differentially expressed genes. New genes and genes previously identified in mediating olfactory behavior were identified. In particular, we found functional enrichment of several gene ontology terms, including cell-cell adhesion and sulfur compound metabolic process, the latter including genes belonging to the glutathione S-transferase family. These findings highlight a potential role for glutathione S-transferases in the evolution of hedonic valence to ecologically relevant volatile compounds and set the stage for a detailed investigation into mechanisms by which these genes mediate attraction and aversion.

Systems genetics of the Drosophila metabolome

How effects of DNA sequence variants are transmitted through intermediate endophenotypes to modulate organismal traits remains a central question in quantitative genetics. This problem can be addressed through a systems approach in a population in which genetic polymorphisms, gene expression traits, metabolites, and complex phenotypes can be evaluated on the same genotypes. Here, we focused on the metabolome, which represents the most proximal link between genetic variation and organismal phenotype, and quantified metabolite levels in 40 lines of the Drosophila melanogaster Genetic Reference Panel. We identified sex-specific modules of genetically correlated metabolites and constructed networks that integrate DNA sequence variation and variation in gene expression with variation in metabolites and organismal traits, including starvation stress resistance and male aggression. Finally, we asked to what extent SNPs and metabolites can predict trait phenotypes and generated trait- and sex-specific prediction models that provide novel insights about the metabolomic underpinnings of complex phenotypes.

The Genetics of Male Pheromone Preference Difference Between Drosophila melanogaster and Drosophila simulans

Species of flies in the genus Drosophila differ dramatically in their preferences for mates, but little is known about the genetic or neurological underpinnings of this evolution. Recent advances have been made to our understanding of one case: pheromone preference evolution between the species D. melanogaster and D. simulans. Males of both species are very sensitive to the pheromone 7,11-HD that is present only on the cuticle of female D. melanogaster. In one species this cue activates courtship, and in the other it represses it. This change in valence was recently shown to result from the modification of central processing neurons, rather than changes in peripherally expressed receptors, but nothing is known about the genetic changes that are responsible. In the current study, we show that a 1.35 Mb locus on the X chromosome has a major effect on male 7,11-HD preference. Unfortunately, when this locus is divided, the effect is largely lost. We instead attempt to filter the 159 genes within this region using our newfound understanding of the neuronal underpinnings of this phenotype to identify and test candidate genes. We present the results of these tests, and discuss the difficulty of identifying the genetic architecture of behavioral traits and the potential of connecting these genetic changes to the neuronal modifications that elicit different behaviors.

Does gene flow aggravate or alleviate maladaptation to environmental stress in small populations?

Environmental change can expose populations to unfamiliar stressors, and maladaptive responses to those stressors may result in population declines or extirpation. Although gene flow is classically viewed as a cause of maladaptation, small and isolated populations experiencing high levels of drift and little gene flow may be constrained in their evolutionary response to environmental change. We provide a case study using the model Trinidadian guppy system that illustrates the importance of considering gene flow and genetic drift when predicting (mal)adaptive response to acute stress. We compared population genomic patterns and acute stress responses of inbred guppy populations from headwater streams either with or without a recent history of gene flow from a more diverse mainstem population. Compared to "no-gene flow" analogues, we found that populations with recent gene flow showed higher genomic variation and increased stress tolerance-but only when exposed to a stress familiar to the mainstem population (heat shock). All headwater populations showed similar responses to a familiar stress in headwater environments (starvation) regardless of gene flow history, whereas exposure to an entirely unfamiliar stress (copper sulfate) showed population-level variation unrelated to environment or recent evolutionary history. Our results suggest that (mal)adaptive responses to acutely stressful environments are determined in part by recent evolutionary history and in part by previous exposure. In some cases, gene flow may provide the variation needed to persist, and eventually adapt, in the face of novel stress.

Dissection of Complex, Fitness-Related Traits in Multiple Drosophila Mapping Populations Offers Insight into the Genetic Control of Stress Resistance

We leverage two complementary Drosophila melanogaster mapping panels to genetically dissect starvation resistance-an important fitness trait. Using >1600 genotypes from the multiparental Drosophila Synthetic Population Resource (DSPR), we map numerous starvation stress QTL that collectively explain a substantial fraction of trait heritability. Mapped QTL effects allowed us to estimate DSPR founder phenotypes, predictions that were correlated with the actual phenotypes of these lines. We observe a modest phenotypic correlation between starvation resistance and triglyceride level, traits that have been linked in previous studies. However, overlap among QTL identified for each trait is low. Since we also show that DSPR strains with extreme starvation phenotypes differ in desiccation resistance and activity level, our data imply multiple physiological mechanisms contribute to starvation variability. We additionally exploited the Drosophila Genetic Reference Panel (DGRP) to identify sequence variants associated with starvation resistance. Consistent with prior work these sites rarely fall within QTL intervals mapped in the DSPR. We were offered a unique opportunity to directly compare association mapping results across laboratories since two other groups previously measured starvation resistance in the DGRP. We found strong phenotypic correlations among studies, but extremely low overlap in the sets of genomewide significant sites. Despite this, our analyses revealed that the most highly associated variants from each study typically showed the same additive effect sign in independent studies, in contrast to otherwise equivalent sets of random variants. This consistency provides evidence for reproducible trait-associated sites in a widely used mapping panel, and highlights the polygenic nature of starvation resistance.

Starvation resistance is associated with developmentally specified changes in sleep, feeding and metabolic rate

Food shortage represents a primary challenge to survival, and animals have adapted diverse developmental, physiological and behavioral strategies to survive when food becomes unavailable. Starvation resistance is strongly influenced by ecological and evolutionary history, yet the genetic basis for the evolution of starvation resistance remains poorly understood. The fruit fly Drosophila melanogaster provides a powerful model for leveraging experimental evolution to investigate traits associated with starvation resistance. While control populations only live a few days without food, selection for starvation resistance results in populations that can survive weeks. We have previously shown that selection for starvation resistance results in increased sleep and reduced feeding in adult flies. Here, we investigate the ontogeny of starvation resistance-associated behavioral and metabolic phenotypes in these experimentally selected flies. We found that selection for starvation resistance resulted in delayed development and a reduction in metabolic rate in larvae that persisted into adulthood, suggesting that these traits may allow for the accumulation of energy stores and an increase in body size within these selected populations. In addition, we found that larval sleep was largely unaffected by starvation selection and that feeding increased during the late larval stages, suggesting that experimental evolution for starvation resistance produces developmentally specified changes in behavioral regulation. Together, these findings reveal a critical role for development in the evolution of starvation resistance and indicate that selection can selectively influence behavior during defined developmental time points.

Ade2 Functions in the Drosophila Fat Body To Promote Sleep

Metabolic state is a potent modulator of sleep and circadian behavior, and animals acutely modulate their sleep in accordance with internal energy stores and food availability. Across phyla, hormones secreted from adipose tissue act in the brain to control neural physiology and behavior to modulate sleep and metabolic state. Growing evidence suggests the fat body is a critical regulator of complex behaviors, but little is known about the genes that function within the fat body to regulate sleep. To identify molecular factors functioning in non-neuronal tissues to regulate sleep, we performed an RNAi screen selectively knocking down genes in the fat body. We found that knockdown of Phosphoribosylformylglycinamidine synthase/Pfas (Ade2), a highly conserved gene involved the biosynthesis of purines, sleep regulation and energy stores. Flies heterozygous for multiple Ade2 mutations are also short sleepers and this effect is partially rescued by restoring Ade2 to the Drosophila fat body. Targeted knockdown of Ade2 in the fat body does not alter arousal threshold or the homeostatic response to sleep deprivation, suggesting a specific role in modulating baseline sleep duration. Together, these findings suggest Ade2 functions within the fat body to promote both sleep and energy storage, providing a functional link between these processes.

MimicrEE2: Genome-wide forward simulations of Evolve and Resequencing studies

Evolve and Resequencing (E&R) studies allow us to monitor adaptation at the genomic level. By sequencing evolving populations at regular time intervals, E&R studies promise to shed light on some of the major open questions in evolutionary biology such as the repeatability of evolution and the molecular basis of adaptation. However, data interpretation, statistical analysis and the experimental design of E&R studies increasingly require simulations of evolving populations, a task that is difficult to accomplish with existing tools, which may i) be too slow, ii) require substantial reformatting of data, iii) not support an adaptive scenario of interest or iv) not sufficiently capture the biology of the used model organism. Therefore we developed MimicrEE2, a multi-threaded Java program for genome-wide forward simulations of evolving populations. MimicrEE2 enables the convenient usage of available genomic resources, supports biological particulars of model organism frequently used in E&R studies and offers a wide range of different adaptive models (selective sweeps, polygenic adaptation, epistasis). Due to its user-friendly and efficient design MimicrEE2 will facilitate simulations of E&R studies even for small labs with limited bioinformatics expertise or computational resources. Additionally, the scripts provided for executing MimicrEE2 on a computer cluster permit the coverage even of a large parameter space. MimicrEE2 runs on any computer with Java installed. It is distributed under the GPLv3 license at https://sourceforge.net/projects/mimicree2/.

Variation in sleep and metabolic function is associated with latitude and average temperature in Drosophila melanogaster

Regulation of sleep and metabolic homeostasis is critical to an animal's survival and under stringent evolutionary pressure. Animals display remarkable diversity in sleep and metabolic phenotypes; however, an understanding of the ecological forces that select for, and maintain, these phenotypic differences remains poorly understood. The fruit fly, Drosophila melanogaster, is a powerful model for investigating the genetic regulation of sleep and metabolic function, and screening in inbred fly lines has led to the identification of novel genetic regulators of sleep. Nevertheless, little is known about the contributions of naturally occurring genetic differences to sleep, metabolic phenotypes, and their relationship with geographic or environmental gradients. Here, we quantified sleep and metabolic phenotypes in 24 D. melanogaster populations collected from diverse geographic localities. These studies reveal remarkable variation in sleep, starvation resistance, and energy stores. We found that increased sleep duration is associated with proximity to the equator and elevated average annual temperature, suggesting that environmental gradients strongly influence natural variation in sleep. Further, we found variation in metabolic regulation of sleep to be associated with free glucose levels, while starvation resistance associates with glycogen and triglyceride stores. Taken together, these findings reveal robust naturally occurring variation in sleep and metabolic traits in D. melanogaster, providing a model to investigate how evolutionary and ecological history modulate these complex traits.

Learning to starve: impacts of food limitation beyond the stress period

Starvation is common among wild animal populations, and many individuals experience repeated bouts of starvation over the course of their lives. Although much information has been gained through laboratory studies of acute starvation, little is known about how starvation affects an animal once food is again available (i.e. during the refeeding and recovery phases). Many animals exhibit a curious phenomenon – some seem to ‘get better’ at starving following exposure to one or more starvation events – by this we mean that they exhibit potentially adaptive responses, including reduced rates of mass loss, reduced metabolic rates, and lower costs of digestion. During subsequent refeedings they may also exhibit improved digestive efficiency and more rapid mass gain. Importantly, these responses can last until the next starvation bout or even be inherited and expressed in the subsequent generation. Currently, however, little is known about the molecular regulation and physiological mechanisms underlying these changes. Here, we identify areas of research that can fill in the most pressing knowledge gaps. In particular, we highlight how recently refined techniques (e.g. stable isotope tracers, quantitative magnetic resonance and thermal measurement) as well as next-generation sequencing approaches (e.g. RNA-seq, proteomics and holobiome sequencing) can address specific starvation-focused questions. We also describe outstanding unknowns ripe for future research regarding the timing and severity of starvation, and concerning the persistence of these responses and their interactions with other ecological stressors.

Molecular Markers for Biomass Traits: Association, Interaction and Genetic Divergence in Silkworm Bombyx mori

Improvement of high yielding, disease resistant silkworm strains became imminent to increase production of silk, which is a major revenue earner for sericulturists. Since environment interacts with phenotype, conventional breeding did not result in commendable yield improvement in synthetic strains of silkworm, Bombyx mori. Identification of DNA markers associated with different economically important biomass traits and its introgression could assist molecular breeding and expression of stabilized high yielding characters, but genetic basis of most quantitative traits in silkworm is poorly understood due to its polygenic control. Correlation analysis (R = 0.9) revealed significant interrelation among biomass traits viz., larval duration (TLD), larval weight (LWT), cocoon weight (CWT), shell weight (SWT), shell ratio (SR) and floss content. PCR using inter simple sequence repeat (ISSR) primers revealed 92% polymorphism among 14 tropical and temperate strains of B. mori, with average diversity index of 0.747. Stepwise multiple regression analysis (MRA) selected 35 ISSR markers positively or negatively correlated with different biomass traits, illustrated polygenic control. ISSR marker 830.81050bp was significantly associated with LWT, CWT, SWT, SR and floss content, indicated its pleiotropic role. Two ISSR markers, 835.51950bp and 825.9710bp showed significant association with floss content and TLD. These markers were segregated in F2 generation and Chi-square test confirmed (χ2 = ~45; P < 0.05) its genetic contribution to the associated biomass traits. Strains, with both positively and negatively correlated markers, had intermediate mean value for biomass traits (eg. SWT = 0.17 ± 0.014 g in GNM and Moria) indicated interaction of loci in natural populations. Low yielding Indian strains grouped together by Hierarchical clustering. Chinese and Japanese strains were distributed in the periphery of ALSCAL matrix indicated convergence of genetic characters in Indian strains. Average genetic distance between Chinese strains and Indian strains (0.193) significantly ( P < 0.01) varied from that between Chinese and Japanese strains. Interaction of loci and allelic substitutions induced phenotypic plasticity in temperate B. mori populations on tropic adaptation in India. These outcomes show possibility to combine favorable alleles at different QTL to increase larval, cocoon and shell weight.

Regulatory Mechanisms of Metamorphic Neuronal Remodeling Revealed Through a Genome-Wide Modifier Screen in Drosophila melanogaster

During development, neuronal remodeling shapes neuronal connections to establish fully mature and functional nervous systems. Our previous studies have shown that the RNA-binding factor alan shepard (shep) is an important regulator of neuronal remodeling during metamorphosis in Drosophila melanogaster, and loss of shep leads to smaller soma size and fewer neurites in a stage-dependent manner. To shed light on the mechanisms by which shep regulates neuronal remodeling, we conducted a genetic modifier screen for suppressors of shep-dependent wing expansion defects and cellular morphological defects in a set of peptidergic neurons, the bursicon neurons, that promote posteclosion wing expansion. Out of 702 screened deficiencies that covered 86% of euchromatic genes, we isolated 24 deficiencies as candidate suppressors, and 12 of them at least partially suppressed morphological defects in shep mutant bursicon neurons. With RNA interference and mutant alleles of individual genes, we identified Daughters against dpp (Dad) and Olig family (Oli) as shep suppressor genes, and both of them restored the adult cellular morphology of shep-depleted bursicon neurons. Dad encodes an inhibitory Smad protein that inhibits bone morphogenetic protein (BMP) signaling, raising the possibility that shep interacted with BMP signaling through antagonism of Dad. By manipulating expression of the BMP receptor tkv, we found that activated BMP signaling was sufficient to rescue loss-of-shep phenotypes. These findings reveal mechanisms of shep regulation during neuronal development, and they highlight a novel genetic shep interaction with the BMP signaling pathway that controls morphogenesis in mature, terminally differentiated neurons during metamorphosis.

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies

The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana, using flowering and growth-related traits.

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

Background

Obesity-related diseases are major contributors to morbidity and mortality in the developed world. Molecular diagnostics and targets of therapies to combat nutritional imbalance are urgently needed in the clinic. Invertebrate animals have been a cornerstone of basic research efforts to dissect the genetics of metabolism and nutrient response. We set out to use fruit flies reared on restricted and nutrient-rich diets to identify genes associated with starvation resistance, body mass and composition, in a survey of genetic variation across the Drosophila Genetic Reference Panel (DGRP).

Results

We measured starvation resistance, body weight and composition in DGRP lines on each of two diets and used several association mapping strategies to harness this panel of phenotypes for molecular insights. We tested DNA sequence variants for a relationship with single metabolic traits and with multiple traits at once, using a scheme for cross-phenotype association mapping; we focused our association tests on homologs of human disease genes and common polymorphisms; and we tested for gene-by-diet interactions. The results revealed gene and gene-by-diet associations between 17 variants and body mass, whole-body triglyceride and glucose content, or starvation resistance. Focused molecular experiments validated the role in body mass of an uncharacterized gene, CG43921 (which we rename heavyweight), and previously unknown functions for the diacylglycerol kinase rdgA, the huntingtin homolog htt, and the ceramide synthase schlank in nutrient-dependent body mass, starvation resistance, and lifespan.

Conclusions

Our findings implicate a wealth of gene candidates in fly metabolism and nutrient response, and ascribe novel functions to htt, rdgA, hwt and schlank.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3137-9) contains supplementary material, which is available to authorized users.

Natural Genetic Variation and Candidate Genes for Morphological Traits in Drosophila melanogaster

Body size is a complex character associated to several fitness related traits that vary within and between species as a consequence of environmental and genetic factors. Latitudinal and altitudinal clines for different morphological traits have been described in several species of Drosophila and previous work identified genomic regions associated with such variation in D. melanogaster. However, the genetic factors that orchestrate morphological variation have been barely studied. Here, our main objective was to investigate genetic variation for different morphological traits associated to the second chromosome in natural populations of D. melanogaster along latitudinal and altitudinal gradients in Argentina. Our results revealed weak clinal signals and a strong population effect on morphological variation. Moreover, most pairwise comparisons between populations were significant. Our study also showed important within-population genetic variation, which must be associated to the second chromosome, as the lines are otherwise genetically identical. Next, we examined the contribution of different candidate genes to natural variation for these traits. We performed quantitative complementation tests using a battery of lines bearing mutated alleles at candidate genes located in the second chromosome and six second chromosome substitution lines derived from natural populations which exhibited divergent phenotypes. Results of complementation tests revealed that natural variation at all candidate genes studied, invected, Fasciclin 3, toucan, Reticulon-like1, jing and CG14478, affects the studied characters, suggesting that they are Quantitative Trait Genes for morphological traits. Finally, the phenotypic patterns observed suggest that different alleles of each gene might contribute to natural variation for morphological traits. However, non-additive effects cannot be ruled out, as wild-derived strains differ at myriads of second chromosome loci that may interact epistatically with mutant alleles.

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits.

Natural variability in Drosophila larval and pupal NaCl tolerance

The regulation of NaCl is essential for the maintenance of cellular tonicity and functionality, and excessive salt exposure has many adverse effects. The fruit fly, Drosophila melanogaster, is a good osmoregulator and some strains can survive on media with very low or high NaCl content. Previous analyses of mutant alleles have implicated various stress signaling cascades in NaCl sensitivity or tolerance; however, the genes influencing natural variability of NaCl tolerance remain for the most part unknown. Here, we use two approaches to investigate natural variation in D. melanogaster NaCl tolerance. We describe four D. melanogaster lines that were selected for different degrees of NaCl tolerance, and present data on their survival, development, and pupation position when raised on varying NaCl concentrations. After finding evidence for natural variation in salt tolerance, we present the results of Quantitative Trait Loci (QTL) mapping of natural variation in larval and pupal NaCl tolerance, and identify different genomic regions associated with NaCl tolerance during larval and pupal development.

TEMPLE: analysing population genetic variation at transcription factor binding sites

Genetic variation occurring at the level of regulatory sequences can affect phenotypes and fitness in natural populations. This variation can be analysed in a population genetic framework to study how genetic drift and selection affect the evolution of these functional elements. However, doing this requires a good understanding of the location and nature of regulatory regions and has long been a major hurdle. The current proliferation of genomewide profiling experiments of transcription factor occupancies greatly improves our ability to identify genomic regions involved in specific DNA-protein interactions. Although software exists for predicting transcription factor binding sites (TFBS), and the effects of genetic variants on TFBS specificity, there are no tools currently available for inferring this information jointly with the genetic variation at TFBS in natural populations. We developed the software Transcription Elements Mapping at the Population LEvel (TEMPLE), which predicts TFBS, evaluates the effects of genetic variants on TFBS specificity and summarizes the genetic variation occurring at TFBS in intraspecific sequence alignments. We demonstrate that TEMPLE's TFBS prediction algorithms gives identical results to PATSER, a software distribution commonly used in the field. We also illustrate the unique features of TEMPLE by analysing TFBS diversity for the TF Senseless (SENS) in one ancestral and one cosmopolitan population of the fruit fly Drosophila melanogaster. TEMPLE can be used to localize TFBS that are characterized by strong genetic differentiation across natural populations. This will be particularly useful for studies aiming to identify adaptive mutations. TEMPLE is a java-based cross-platform software that easily maps the genetic diversity at predicted TFBSs using a graphical interface, or from the Unix command line.

Starvation resistance and tissue-specific gene expression of stress-related genes in a naturally inbred ant population

Starvation is one of the most common and severe stressors in nature. Not only does it lead to death if not alleviated, it also forces the starved individual to allocate resources only to the most essential processes. This creates energetic trade-offs which can lead to many secondary challenges for the individual. These energetic trade-offs could be exacerbated in inbred individuals, which have been suggested to have a less efficient metabolism. Here, we studied the effect of inbreeding on starvation resistance in a natural population of Formica exsecta ants, with a focus on survival and tissue-specific expression of stress, metabolism and immunity-related genes. Starvation led to large tissue-specific changes in gene expression, but inbreeding had little effect on most of the genes studied. Our results illustrate the importance of studying stress responses in different tissues instead of entire organisms.

The genetic basis for mating-induced sex differences in starvation resistance in Drosophila melanogaster

Multiple genetic and environmental factors interact to influence starvation resistance, which is an important determinant of fitness in many organisms, including Drosophila melanogaster. Recent studies have revealed that mating can alter starvation resistance in female D. melanogaster, but little is known about the behavioral and physiological mechanisms underlying such mating-mediated changes in starvation resistance. In the present study, we first investigated whether the effect of mating on starvation resistance is sex-specific in D. melanogaster. As indicated by a significant sex×mating status interaction, mating increased starvation resistance in females but not in males. In female D. melanogaster, post-mating increase in starvation resistance was mainly attributed to increases in food intake and in the level of lipid storage relative to lean body weight. We then performed quantitative genetic analysis to estimate the proportion of the total phenotypic variance attributable to genetic differences (i.e., heritability) for starvation resistance in mated male and female D. melanogaster. The narrow-sense heritability (h(2)) of starvation resistance was 0.235 and 0.155 for males and females, respectively. Mated females were more resistant to starvation than males in all genotypes, but the degree of such sexual dimorphism varied substantially among genotypes, as indicated by a significant sex×genotype interaction for starvation resistance. Cross-sex genetic correlation was greater than 0 but less than l for starvation resistance, implying that the genetic architecture of this trait was partially shared between the two sexes. For both sexes, starvation resistance was positively correlated with longevity and lipid storage at genetic level. The present study suggests that sex differences in starvation resistance depend on mating status and have a genetic basis in D. melanogaster.

Identification of Drosophila Mutants Affecting Defense to an Entomopathogenic Fungus

Fungi cause the majority of insect disease. However, to date attempts to model host–fungal interactions with Drosophila have focused on opportunistic human pathogens. Here, we performed a screen of 2,613 mutant Drosophila lines to identify host genes affecting susceptibility to the natural insect pathogen Metarhizium anisopliae (Ma549). Overall, 241 (9.22%) mutant lines had altered resistance to Ma549. Life spans ranged from 3.0 to 6.2 days, with females being more susceptible than males in all lines. Speed of kill correlated with within-host growth and onset of sporulation, but total spore production is decoupled from host genotypes. Results showed that mutations affected the ability of Drosophila to restrain rather than tolerate infections and suggested trade-offs between antifungal and antibacterial genes affecting cuticle and gut structural barriers. Approximately, 13% of mutations where in genes previously associated with host pathogen interactions. These encoded fast-acting immune responses including coagulation, phagocytosis, encapsulation and melanization but not the slow-response induction of anti-fungal peptides. The non-immune genes impact a wide variety of biological functions, including behavioral traits. Many have human orthologs already implicated in human disorders; while others were mutations in protein and non-protein coding genes for which disease resistance was the first biological annotation.

Enhanced Sleep Is an Evolutionarily Adaptive Response to Starvation Stress in Drosophila

Animals maximize fitness by modulating sleep and foraging strategies in response to changes in nutrient availability. Wild populations of the fruit fly, Drosophila melanogaster, display highly variable levels of starvation and desiccation resistance that differ in accordance with geographic location, nutrient availability, and evolutionary history. Further, flies potently modulate sleep in response to changes in food availability, and selection for starvation resistance enhances sleep, revealing strong genetic relationships between sleep and nutrient availability. To determine the genetic and evolutionary relationship between sleep and nutrient deprivation, we assessed sleep in flies selected for desiccation or starvation resistance. While starvation resistant flies have higher levels of triglycerides, desiccation resistant flies have enhanced glycogen stores, indicative of distinct physiological adaptations to food or water scarcity. Strikingly, selection for starvation resistance, but not desiccation resistance, leads to increased sleep, indicating that enhanced sleep is not a generalized consequence of higher energy stores. Thermotolerance is not altered in starvation or desiccation resistant flies, providing further evidence for context-specific adaptation to environmental stressors. F₂ hybrid flies were generated by crossing starvation selected flies with desiccation selected flies, and the relationship between nutrient deprivation and sleep was examined. Hybrids exhibit a positive correlation between starvation resistance and sleep, while no interaction was detected between desiccation resistance and sleep, revealing that prolonged sleep provides an adaptive response to starvation stress. Therefore, these findings demonstrate context-specific evolution of enhanced sleep in response to chronic food deprivation, and provide a model for understanding the evolutionary relationship between sleep and nutrient availability.

Multiple-Line Inference of Selection on Quantitative Traits

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population genetics test for selection acting on a quantitative trait that is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inferences. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test can distinguish between different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signature of lineage-specific selection not seen in two-line tests.

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.

Epistasis for quantitative traits in Drosophila

The role of gene-gene interactions in the genetic architecture of quantitative traits is controversial, despite the biological plausibility of nonlinear molecular interactions underpinning variation in quantitative traits. In strictly outbreeding populations, genetic architecture is inferred indirectly by estimating variance components; however, failure to detect epistatic variance does not mean lack of epistatic gene action and is even consistent with pervasive epistasis. In Drosophila, more focused approaches to detecting epistatic gene action are possible, based on the ability to create de novo mutations and perform crosses among them; to construct inbred lines, artificial selection lines, and chromosome substitution lines; to map quantitative trait loci affecting complex traits by linkage and association; and to evaluate effects of induced mutations on multiple wild-derived backgrounds. Here, I review evidence for epistasis in Drosophila from the application of these methods, and conclude that additivity is an emergent property of underlying epistatic gene action for Drosophila quantitative traits. Such studies can be used to infer novel, highly interconnected genetic networks that are enriched for gene ontology categories and metabolic and cellular pathways. The consequence of epistasis is that the main effects of each of the interacting loci depend on allele frequency, which negatively impacts the predictive ability of additive models. Finally, epistasis results in hidden quantitative genetic variation in natural populations (genetic canalization) and the potential for rapid evolution of Dobzhansky-Muller incompatibilities (speciation).

Fine-mapping and selective sweep analysis of QTL for cold tolerance in Drosophila melanogaster

There is a growing interest in investigating the relationship between genes with signatures of natural selection and genes identified in QTL mapping studies using combined population and quantitative genetics approaches. We dissected an X-linked interval of 6.2 Mb, which contains two QTL underlying variation in chill coma recovery time (CCRT) in Drosophila melanogaster from temperate (European) and tropical (African) regions. This resulted in two relatively small regions of 131 kb and 124 kb. The latter one co-localizes with a very strong selective sweep in the European population. We examined the genes within and near the sweep region individually using gene expression analysis and P-element insertion lines. Of the genes overlapping with the sweep, none appears to be related to CCRT. However, we have identified a new candidate gene of CCRT, brinker, which is located just outside the sweep region and is inducible by cold stress. We discuss these results in light of recent population genetics theories on quantitative traits.

Altered regulation of sleep and feeding contributes to starvation resistance in Drosophila melanogaster

Animals respond to changes in food availability by adjusting sleep and foraging strategies to optimize their fitness. Wild populations of the fruit fly, Drosophila melanogaster, display highly variable levels of starvation resistance that are dependent on geographic location, food availability and evolutionary history. How behaviors that include sleep and feeding vary in Drosophila with increased starvation resistance is unclear. We have generated starvation-resistant flies through experimental evolution to investigate the relationship between foraging behaviors and starvation resistance. Outbred populations of D. melanogaster were selected for starvation resistance over 60 generations. This selection process resulted in flies with a threefold increase in total lipids that survive up to 18 days without food. We tested starvation-selected (S) flies for sleep and feeding behaviors to determine the effect that selection for starvation resistance has had on foraging behavior. Flies from three replicated starvation-selected populations displayed a dramatic reduction in feeding and prolonged sleep duration compared to fed control (F) populations, suggesting that modified sleep and feeding may contribute to starvation resistance. A prolonged larval developmental period contributes to the elevated energy stores present in starvation-selected flies. By preventing S larvae from feeding longer than F larvae, we were able to reduce energy stores in adult S flies to the levels seen in adult F flies, thus allowing us to control for energy storage levels. However, the reduction of energy stores in S flies fails to generate normal sleep and feeding behavior seen in F flies with similar energy stores. These findings suggest that the behavioral changes observed in S flies are due to genetic regulation of behavior rather than elevated lipid levels. Testing S-F hybrid individuals for both feeding and sleep revealed a lack of correlation between food consumption and sleep duration, indicating further independence in genetic factors underlying the sleep and feeding changes observed in S flies. Taken together, these findings provide evidence that starvation selection results in prolonged sleep and reduced feeding through a mechanism that is independent of elevated energy stores. These findings suggest that changes in both metabolic function and behavior contribute to the increase in starvation resistance seen in flies selected for starvation resistance.

Neuronal remodeling during metamorphosis is regulated by the alan shepard (shep) gene in Drosophila melanogaster

Peptidergic neurons are a group of neuronal cells that synthesize and secrete peptides to regulate a variety of biological processes. To identify genes controlling the development and function of peptidergic neurons, we conducted a screen of 545 splice-trap lines and identified 28 loci that drove expression in peptidergic neurons when crossed to a GFP reporter transgene. Among these lines, an insertion in the alan shepard (shep) gene drove expression specifically in most peptidergic neurons. shep transcripts and SHEP proteins were detected primarily and broadly in the central nervous system (CNS) in embryos, and this expression continued into the adult stage. Loss of shep resulted in late pupal lethality, reduced adult life span, wing expansion defects, uncoordinated adult locomotor activities, rejection of males by virgin females, and reduced neuropil area and reduced levels of multiple presynaptic markers throughout the adult CNS. Examination of the bursicon neurons in shep mutant pharate adults revealed smaller somata and fewer axonal branches and boutons, and all of these cellular phenotypes were fully rescued by expression of the most abundant wild-type shep isoform. In contrast to shep mutant animals at the pharate adult stage, shep mutant larvae displayed normal bursicon neuron morphologies. Similarly, shep mutant adults were uncoordinated and weak, while shep mutant larvae displayed largely, although not entirely, normal locomotor behavior. Thus, shep played an important role in the metamorphic development of many neurons.

Gene-by-temperature interactions and candidate plasticity genes for morphological traits in Drosophila melanogaster

Understanding the genetic architecture of any quantitative trait requires identifying the genes involved in its expression in different environmental conditions. This goal can be achieved by mutagenesis screens in genetically tractable model organisms such as Drosophila melanogaster. Temperature during ontogenesis is an important environmental factor affecting development and phenotypic variation in holometabolous insects. In spite of the importance of phenotypic plasticity and genotype by environment interaction (GEI) for fitness related traits, its genetic basis has remained elusive. In this context, we analyzed five different adult morphological traits (face width, head width, thorax length, wing size and wing shape) in 42 co-isogenic single P-element insertional lines of Drosophila melanogaster raised at 17°C and 25°C. Our analyses showed that all lines differed from the control for at least one trait in males or females at either temperature. However, no line showed those differences for all traits in both sexes and temperatures simultaneously. In this sense, the most pleiotropic candidate genes were CG34460, Lsd-2 and Spn. Our analyses also revealed extensive genetic variation for all the characters mostly indicated by strong GEIs. Further, our results indicate that GEIs were predominantly explained by changes in ranking order in all cases suggesting that a moderate number of genes are involved in the expression of each character at both temperatures. Most lines displayed a plastic response for at least one trait in either sex. In this regard, P-element insertions affecting plasticity of a large number of traits were associated to the candidate genes Btk29A, CG43340, Drak and jim. Further studies will help to elucidate the relevance of these genes on the morphogenesis of different body structures in natural populations of D. melanogaster.

Genetic architecture of olfactory behavior in Drosophila melanogaster: differences and similarities across development

In the holometabolous insect Drosophila melanogaster, genetic, physiological and anatomical aspects of olfaction are well known in the adult stage, while larval stages olfactory behavior has received some attention it has been less studied than its adult counterpart. Most of these studies focus on olfactory receptor (Or) genes that produce peripheral odor recognition. In this paper, through a loss-of-function screen using P-element inserted lines and also by means of expression analyses of larval olfaction candidate genes, we extended the uncovering of the genetic underpinnings of D. melanogaster larval olfactory behavior by demonstrating that larval olfactory behavior is, in addition to Or genes, orchestrated by numerous genes with diverse functions. Also, our results point out that the genetic architecture of olfactory behavior in D. melanogaster presents a dynamic and changing organization across environments and ontogeny.

What model organisms and interactomics can reveal about the genetics of human obesity

Genome-wide association studies have identified a number of genes associated with human body weight. While some of these genes are large fields within obesity research, such as MC4R, POMC, FTO and BDNF, the majority do not have a clearly defined functional role explaining why they may affect body weight. Here, we searched biological databases and discovered 33 additional genes associated with human obesity (CADM2, GIPR, GPCR5B, LRP1B, NEGR1, NRXN3, SH2B1, FANCL, GNPDA2, HMGCR, MAP2K5, NUDT3, PRKD1, QPCTL, TNNI3K, MTCH2, DNAJC27, SLC39A8, MTIF3, RPL27A, SEC16B, ETV5, HMGA1, TFAP2B, TUB, ZNF608, FAIM2, KCTD15, LINGO2, POC5, PTBP2, TMEM18, TMEM160). We find that the majority have orthologues in distant species, such as D. melanogaster and C. elegans, suggesting that they are important for the biology of most bilateral species. Intriguingly, signalling cascade genes and transcription factors are enriched among these obesity genes, and several of the genes show properties that could be useful for potential drug discovery. In this review, we demonstrate how information from several distant model species, interactomics and signalling pathway analysis represents an important way to better understand the functional diversity of the surprisingly high number of molecules that seem to be important for human obesity.

Functional genomics in Drosophila models of human disease

It is occasionally observed that common sporadic diseases have rare familial counterparts in which mutations at a single locus result in a similar disorder exhibiting simple Mendelian inheritance. Such an observation is often sufficient justification for the creation of a disease model in the fly. Whether the system is based on the over-expression of a toxic variant of a human protein or requires the loss of function of an orthologous fly gene, the consequent phenotypes can be used to understand pathogenesis through the discovery of genetic modifiers. Such genetic screening can be completed rapidly in the fly and in this review we outline how libraries of mutants are generated and how consequent changes in disease-related phenotypes are assessed. The bioinformatic approaches to processing the copious amounts of data so generated are also presented. The next phase of fly modelling will tackle the challenges of complex diseases in which many genes are associated with risk in the human. There is growing interest in the use of interactomics and epigenetics to provide proteome- and genome-scale descriptions of the regulatory dysfunction that results in disease.

A critical assessment of storytelling: gene ontology categories and the importance of validating genomic scans

In the age of whole-genome population genetics, so-called genomic scan studies often conclude with a long list of putatively selected loci. These lists are then further scrutinized to annotate these regions by gene function, corresponding biological processes, expression levels, or gene networks. Such annotations are often used to assess and/or verify the validity of the genome scan and the statistical methods that have been used to perform the analyses. Furthermore, these results are frequently considered to validate "true-positives" if the identified regions make biological sense a posteriori. Here, we show that this approach can be potentially misleading. By simulating neutral evolutionary histories, we demonstrate that it is possible not only to obtain an extremely high false-positive rate but also to make biological sense out of the false-positives and construct a sensible biological narrative. Results are compared with a recent polymorphism data set from Drosophila melanogaster.

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster

Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP–based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.

The ability to accurately predict values of complex phenotypes from genotype data will revolutionize plant and animal breeding, personalized medicine, and evolutionary biology. To date, genomic prediction has utilized high-density single-nucleotide polymorphism (SNP) genotyping arrays, but the availability of sequence data opens new frontiers for genomic prediction methods. This article is the first application of genomic phenotype prediction using whole-genome sequence data in a substantial sample of a higher eukaryote. We use ∼2.5 million SNPs with minor allele frequency greater than 2.5% derived from genomic sequences of the “Drosophila Genetic Reference Panel” to predict phenotypes for two traits, starvation resistance and startle-induced locomotor behavior. We systematically address prediction within versus across sexes, genomic best linear unbiased prediction (GBLUP) versus a Bayesian approach, and the effect of SNP density. We find that (i) genomic prediction can be efficiently implemented using sequence data via GBLUP, (ii) there is little gain in predictive ability if the number of SNPs is increased above 150,000, and (iii) neither implicit nor explicit marker selection substantially improves the predictive ability. Although the findings must be seen against the background of small sample sizes, the results illustrate both the potential of the approach and the challenges ahead.

A screen for genes expressed in the olfactory organs of Drosophila melanogaster identifies genes involved in olfactory behaviour

Background

For insects the sense of smell and associated olfactory-driven behaviours are essential for survival. Insects detect odorants with families of olfactory receptor proteins that are very different to those of mammals, and there are likely to be other unique genes and genetic pathways involved in the function and development of the insect olfactory system.

Methodology/Principal Findings

We have performed a genetic screen of a set of 505 Drosophila melanogaster gene trap insertion lines to identify novel genes expressed in the adult olfactory organs. We identified 16 lines with expression in the olfactory organs, many of which exhibited expression of the trapped genes in olfactory receptor neurons. Phenotypic analysis showed that six of the lines have decreased olfactory responses in a behavioural assay, and for one of these we showed that precise excision of the P element reverts the phenotype to wild type, confirming a role for the trapped gene in olfaction. To confirm the identity of the genes trapped in the lines we performed molecular analysis of some of the insertion sites. While for many lines the reported insertion sites were correct, we also demonstrated that for a number of lines the reported location of the element was incorrect, and in three lines there were in fact two pGT element insertions.

Conclusions/Significance

We identified 16 new genes expressed in the Drosophila olfactory organs, the majority in neurons, and for several of the gene trap lines demonstrated a defect in olfactory-driven behaviour. Further characterisation of these genes and their roles in olfactory system function and development will increase our understanding of how the insect olfactory system has evolved to perform the same essential function to that of mammals, but using very different molecular genetic mechanisms.

The Drosophila melanogaster Genetic Reference Panel

A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.

Genetics and neurobiology of aggression in Drosophila

Aggressive behavior is widely present throughout the animal kingdom and is crucial to ensure survival and reproduction. Aggressive actions serve to acquire territory, food, or mates and in defense against predators or rivals; while in some species these behaviors are involved in establishing a social hierarchy. Aggression is a complex behavior, influenced by a broad range of genetic and environmental factors. Recent studies in Drosophila provide insight into the genetic basis and control of aggression. The state of the art on aggression in Drosophila and the many opportunities provided by this model organism to unravel the genetic and neurobiological basis of aggression are reviewed.

Genetic basis of wing morphogenesis in Drosophila: sexual dimorphism and non-allometric effects of shape variation

BACKGROUND

The Drosophila wing represents a particularly appropriate model to investigate the developmental control of phenotypic variation. Previous studies which aimed to identify candidate genes for wing morphology demonstrated that the genetic basis of wing shape variation in D. melanogaster is composed of numerous genetic factors causing small, additive effects. In this study, we analyzed wing shape in males and females from 191 lines of D. melanogaster, homozygous for a single P-element insertion, using geometric morphometrics techniques. The analysis allowed us to identify known and novel candidate genes that may contribute to the expression of wing shape in each sex separately and to compare them to candidate genes affecting wing size which have been identified previously using the same lines.

RESULTS

Our results indicate that more than 63% of induced mutations affected wing shape in one or both sexes, although only 33% showed significant differences in both males and females. The joint analysis of wing size and shape revealed that only 19% of the P-element insertions caused coincident effects on both components of wing form in one or both sexes. Further morphometrical analyses revealed that the intersection between veins showed the smallest displacements in the proximal region of the wing. Finally, we observed that mutations causing general deformations were more common than expected in both sexes whereas the opposite occurred with those generating local changes. For most of the 94 candidate genes identified, this seems to be the first record relating them with wing shape variation.

CONCLUSIONS

Our results support the idea that the genetic architecture of wing shape is complex with many different genes contributing to the trait in a sexually dimorphic manner. This polygenic basis, which is relatively independent from that of wing size, is composed of genes generally involved in development and/or metabolic functions, especially related to the regulation of different cellular processes such as motility, adhesion, communication and signal transduction. This study suggests that understanding the genetic basis of wing shape requires merging the regulation of vein patterning by signalling pathways with processes that occur during wing development at the cellular level.

Analysis of the effects of inbreeding on lifespan and starvation resistance in Drosophila melanogaster

Because of their decreased overall fitness and genetic variability inbred individuals are expected to show reduced survival and lifespan under most environmental conditions as compared with outbred individuals. Whereas evidence for the deleterious effects of inbreeding on lifespan has been previously provided, only a few studies have investigated effects of inbreeding on survival under starved conditions. In the present study we compared the abilities of inbred and outbred adult Drosophila melanogaster to survive under starved and fed conditions. We found that inbreeding reduced lifespan but had no effect on starvation resistance. The results indicate highly trait specific consequences of inbreeding. Possible mechanisms behind the observed results are discussed.

Changed gene expression for candidate ageing genes in long-lived Bicyclus anynana butterflies

Candidate genes for the regulation of lifespan have emerged from studies that use mutants and genetically manipulated model organisms. However, it is rarely addressed whether these genes contribute to lifespan variation in populations of these species that capture natural standing genetic variation. Here, we explore expression variation in three candidate ageing genes, Indy, sod2, and catalase, in Bicyclus anynana, a butterfly with well understood ecology. We used lines established from natural populations and artificially selected for increased adult starvation resistance. They show a considerable increase in adult lifespan under both starvation and optimal food conditions. We measured adult butterflies of various ages, under a range of optimal and starvation diets, from two selected populations and one unselected control population. In all lines, Indy and catalase are up-regulated in response to starvation while this is not evident for sod2. Under starvation, Indy and catalase are up-regulated in, while this is not evident for sod2. Under optimal food conditions, Indy is down-regulated at a later age, with Indy expression showing relatively high inter-individual variation. We find differences between the selected lines and the unselected line. Under starvation conditions, expression is higher for catalase in one, and for sod2 in both selected lines. Importantly, sod2 expression is also higher in the selected populations under optimal food conditions. We conclude that sod2, but not Indy, is involved in the response to artificial selection for increased starvation resistance. The role of catalase is less clear because of the differences between the two selected lines. Moreover, sod2 appears to be a candidate gene that underpins the genetic correlation between starvation resistance and longevity. Our study indicates that some, but not all, genes identified through mutant screens in other organisms may underpin standing genetic variation for ageing-related traits in stocks of Bicyclus butterflies established from natural populations. Clearly, this needs to be investigated in other organisms as well, especially in the organisms to which mutants screens were applied. This information will narrow down the list of genes that underpin variation in lifespan and ageing in extant populations of organisms, and which may serve as candidate genes in humans.