Drosophila melanogaster is a leading animal model for understanding basic genetic principles for biomedical research and for quantitative, population and evolutionary genetics and genomics. The D. melanogaster Genetic Reference Panel (DGRP) of ~200 inbred strains with full genome sequences is a publicly available resource for genome wide association (GWA) studies of quantitative traits, systems genetics, and population genomic analyses. However, the small size of the DGRP limits the power to map rare variants or variants with small effect sizes. Here, we describe the DGRP Version 3 (DGRP3), consisting of full genome sequences from 1,233 inbred lines, of which 1,037 are currently extant. The DGRP3 harbors extensive genetic diversity, with 8,760,339 molecular polymorphisms including single nucleotide polymorphisms, insertions, deletions, inversions, tandem duplications and complex rearrangements. We identified 80,894 damaging variants and 4,550 genes with at least one loss-of-function haplotype. We inferred 16 mitochondrial haplotype groups, determined the microbial composition, and quantified the numbers of sensory bristles for the DGRP3 lines. We performed GWA analyses for inbreeding depression, host control of microbiome composition, and numbers of sensory bristles, identifying novel candidate variants and genes for each. The accompanying online tool (flydgrp.org) implements state-of-the-art association mapping methods and provides results for users DGRP3 data.

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

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.

The genetics of phenotypic responses to changing environments remains elusive. Using whole genome quantitative gene expression as a model, we studied how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed at different environments (25 °C and 18 °C). We found a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increased at 18 °C relative to 25 °C for most genes that had a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments were shared and had similar effects, analysis of the environment-specific eQTLs revealed enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks were highly conserved across environments. Genes with higher network connectivity were under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

A major challenge in modern biology is to understand how naturally occurring variation in DNA sequences affects complex organismal traits through networks of intermediate molecular phenotypes. This question is best addressed in a genetic mapping population in which all molecular polymorphisms are known and for which molecular endophenotypes and complex traits are assessed on the same genotypes. Here, we performed deep RNA sequencing of 200 Drosophila Genetic Reference Panel inbred lines with complete genome sequences and for which phenotypes of many quantitative traits have been evaluated. We mapped expression quantitative trait loci for annotated genes, novel transcribed regions, transposable elements, and microbial species. We identified host variants that affect expression of transposable elements, independent of their copy number, as well as microbiome composition. We constructed sex-specific expression quantitative trait locus regulatory networks. These networks are enriched for novel transcribed regions and target genes in heterochromatin and euchromatic regions of reduced recombination, as well as genes regulating transposable element expression. This study provides new insights regarding the role of natural genetic variation in regulating gene expression and generates testable hypotheses for future functional analyses.

The genetics of phenotypic responses to changing environments remains elusive. Using whole-genome quantitative gene expression as a model, here we study how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed in different environments (25 °C and 18 °C). We find a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increases at 18 °C relative to 25 °C for most genes that have a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments are shared and have similar effects, analysis of the environment-specific eQTLs reveals enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks are highly conserved across environments. Genes with higher network connectivity are under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

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.

Pigmentation varies within and between species and is often adaptive. The amount of pigmentation on the abdomen of Drosophila melanogaster is a relatively simple morphological trait, which serves as a model for mapping the genetic basis of variation in complex phenotypes. Here, we assessed natural variation in female abdominal pigmentation in 175 sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel, derived from the Raleigh, NC population. We quantified the proportion of melanization on the two most posterior abdominal segments, tergites 5 and 6 (T5, T6). We found significant genetic variation in the proportion of melanization and high broad-sense heritabilities for each tergite. Genome-wide association studies identified over 150 DNA variants associated with the proportion of melanization on T5 (84), T6 (34), and the difference between T5 and T6 (35). Several of the top variants associated with variation in pigmentation are in tan, ebony, and bric-a-brac1, genes known to affect D. melanogaster abdominal pigmentation. Mutational analyses and targeted RNAi-knockdown showed that 17 out of 28 (61%) novel candidate genes implicated by the genome-wide association study affected abdominal pigmentation. Several of these genes are involved in developmental and regulatory pathways, chitin production, cuticle structure, and vesicle formation and transport. These findings show that genetic variation may affect multiple steps in pathways involved in tergite development and melanization. Variation in these novel candidates may serve as targets for adaptive evolution and sexual selection in D. melanogaster.

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

The Drosophila melanogaster Genetic Reference Panel (DGRP) is a community resource of 205 sequenced inbred lines, derived to improve our understanding of the effects of naturally occurring genetic variation on molecular and organismal phenotypes. We used an integrated genotyping strategy to identify 4,853,802 single nucleotide polymorphisms (SNPs) and 1,296,080 non-SNP variants. Our molecular population genomic analyses show higher deletion than insertion mutation rates and stronger purifying selection on deletions. Weaker selection on insertions than deletions is consistent with our observed distribution of genome size determined by flow cytometry, which is skewed toward larger genomes. Insertion/deletion and single nucleotide polymorphisms are positively correlated with each other and with local recombination, suggesting that their nonrandom distributions are due to hitchhiking and background selection. Our cytogenetic analysis identified 16 polymorphic inversions in the DGRP. Common inverted and standard karyotypes are genetically divergent and account for most of the variation in relatedness among the DGRP lines. Intriguingly, variation in genome size and many quantitative traits are significantly associated with inversions. Approximately 50% of the DGRP lines are infected with Wolbachia, and four lines have germline insertions of Wolbachia sequences, but effects of Wolbachia infection on quantitative traits are rarely significant. The DGRP complements ongoing efforts to functionally annotate the Drosophila genome. Indeed, 15% of all D. melanogaster genes segregate for potentially damaged proteins in the DGRP, and genome-wide analyses of quantitative traits identify novel candidate genes. The DGRP lines, sequence data, genotypes, quality scores, phenotypes, and analysis and visualization tools are publicly available.

Limited lifespan and senescence are quantitative traits, controlled by many interacting genes with individually small and environmentally plastic effects, complicating genetic analysis. We performed genome wide analysis of gene expression for two Drosophila melanogaster lines selected for postponed senescence and one control, unselected line to identify candidate genes affecting lifespan as well as variation in lifespan. We obtained gene expression profiles for young flies of all lines, all lines at the time only 10% of the control lines survived, and the time at which 10% of the selected lines survived. Transcriptional responses to aging involved 19% of the genome. The transcriptional signature of aging involved the down-regulation of genes affecting proteolysis, metabolism, oxidative phosphorylation, and mitochrondrial function; and the up-regulation of genes affecting protein synthesis, immunity, defense responses, and the detoxification of xenobiotic substances. The transcriptional signature of postponed senescence involved the up-regulation of proteases and phosphatases and genes affecting detoxification of xenobiotics; and the down-regulation of genes affecting immunity, defense responses, metabolism and muscle function. Functional tests of 17 mutations confirmed 12 novel genes affecting Drosophila lifespan. Identification of genes affecting longevity by analysis of gene expression changes in lines selected for postponed senescence thus complements alternative genetic approaches.

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.

A comprehensive understanding of the genetic basis of phenotypic adaptation in nature requires the identification of the functional allelic variation underlying adaptive phenotypes. The manner in which organisms respond to temperature extremes is an adaptation in many species. In the current study, we investigate the role of molecular variation in senescence marker protein-30 (Smp-30) on natural phenotypic variation in cold tolerance in Drosophila melanogaster. Smp-30 encodes a product that is thought to be involved in the regulation of Ca2+ ion homeostasis and has been shown previously to be differentially expressed in response to cold stress. Thus, we sought to assess whether molecular variation in Smp-30 was associated with natural phenotypic variation in cold tolerance in a panel of naturally derived inbred lines from a population in Raleigh, North Carolina. We identified four non-coding polymorphisms that were strongly associated with natural phenotypic variation in cold tolerance. Interestingly, two polymorphisms that were in close proximity to one another (2 bp apart) exhibited opposite phenotypic effects. Consistent with the maintenance of a pair of antagonistically acting polymorphisms, tests of molecular evolution identified a significant excess of maintained variation in this region, suggesting balancing selection is acting to maintain this variation. These results suggest that multiple mutations in non-coding regions can have significant effects on phenotypic variation in adaptive traits within natural populations, and that balancing selection can maintain polymorphisms with opposite effects on phenotypic variation.

Chemical recognition is essential for survival and reproduction. Adaptive evolution has resulted in diverse chemoreceptor families, in which polymorphisms contribute to individual variation in chemosensation. To gain insights into the genetic determinants of individual variation in odorant recognition, we measured olfactory responses to two structurally similar odorants in a population of wild-derived inbred lines of Drosophila melanogaster. Odorant-binding proteins (OBPs) are the first components of the insect olfactory system to encounter odorants. Previously four single-nucleotide polymorphisms (SNPs) in the Obp99 group were associated with variation in olfactory responses to benzaldehyde. Here, we identify six different SNPs that are associated with variation in responses to a structurally similar odorant, acetophenone, in the same Obp genes. Five SNPs are in coding regions of Obp99b and Obp99d and one SNP is in the 3'-untranslated region of Obp99a (A610G). We found that the 610G allele is associated with higher response scores to acetophenone than the 610A allele, but with lower expression of Obp99a, suggesting that binding of acetophenone to Opb99a might limit rather than facilitate access to odorant receptors. Our results show that overlapping sets of OBPs contribute to odorant recognition for structurally similar odorants, but that different SNPs are associated with odorant-specific individual variation. Thus, dual olfactory recognition where OBPs regulate odorant access to receptors may enhance olfactory discrimination.

Determining the genetic architecture of complex traits is challenging because phenotypic variation arises from interactions between multiple, environmentally sensitive alleles. We quantified genome-wide transcript abundance and phenotypes for six ecologically relevant traits in D. melanogaster wild-derived inbred lines. We observed 10,096 genetically variable transcripts and high heritabilities for all organismal phenotypes. The transcriptome is highly genetically intercorrelated, forming 241 transcriptional modules. Modules are enriched for transcripts in common pathways, gene ontology categories, tissue-specific expression and transcription factor binding sites. The high degree of transcriptional connectivity allows us to infer genetic networks and the function of predicted genes from annotations of other genes in the network. Regressions of organismal phenotypes on transcript abundance implicate several hundred candidate genes that form modules of biologically meaningful correlated transcripts affecting each phenotype. Overlapping transcripts in modules associated with different traits provide insight into the molecular basis of pleiotropy between complex traits.

Background: Aggressive behavior is an important component of fitness in most animals. Aggressive behavior is genetically complex, with natural variation attributable to multiple segregating loci with allelic effects that are sensitive to the physical and social environment. However, we know little about the genes and genetic networks affecting natural variation in aggressive behavior. Populations of Drosophila melanogaster harbor quantitative genetic variation in aggressive behavior, providing an excellent model system for dissecting the genetic basis of naturally occurring variation in aggression.Results: Correlating variation in transcript abundance with variation in complex trait phenotypes is a rapid method for identifying candidate genes. We quantified aggressive behavior in 40 wild-derived inbred lines of D. melanogaster and performed a genome-wide association screen for quantitative trait transcripts and single feature polymorphisms affecting aggression. We identified 266 novel candidate genes associated with aggressive behavior, many of which have pleiotropic effects on metabolism, development, and/or other behavioral traits. We performed behavioral tests of mutations in 12 of these candidate genes, and show that nine indeed affected aggressive behavior. We used the genetic correlations among the quantitative trait transcripts to derive a transcriptional genetic network associated with natural variation in aggressive behavior. The network consists of nine modules of correlated transcripts that are enriched for genes affecting common functions, tissue-specific expression patterns, and/or DNA sequence motifs.Conclusions: Correlations among genetically variable transcripts that are associated with genetic variation in organismal behavior establish a foundation for understanding natural variation for complex behaviors in terms of networks of interacting genes.

Identification of risk alleles for human behavioral disorders through genomewide association studies (GWAS) has been hampered by a daunting multiple testing problem. This problem can be circumvented for some phenotypes by combining genomewide studies in model organisms with subsequent candidate gene association analyses in human populations. Here, we characterized genetic networks that underlie the response to ethanol exposure in Drosophila melanogaster by measuring ethanol knockdown time in 40 wild-derived inbred Drosophila lines. We associated phenotypic variation in ethanol responses with genomewide variation in gene expression and identified modules of correlated transcripts associated with a first and second exposure to ethanol vapors as well as the induction of tolerance. We validated the computational networks and assessed their robustness by transposon-mediated disruption of focal genes within modules in a laboratory inbred strain, followed by measurements of transcript abundance of connected genes within the module. Many genes within the modules have human orthologs, which provides a stepping stone for the identification of candidate genes associated with alcohol drinking behavior in human populations. We demonstrated the potential of this translational approach by identifying seven intronic single nucleotide polymorphisms of the Malic Enzyme 1 (ME1) gene that are associated with cocktail drinking in 1687 individuals of the Framingham Offspring cohort, implicating that variation in levels of cytoplasmic malic enzyme may contribute to variation in alcohol consumption.

Trudy Mackay and colleagues measure sleep phenotypes in 40 wild-derived Drosophila lines, and report candidate genes and transcriptional networks associated with sleep regulation. Sleep disorders are common in humans, and sleep loss increases the risk of obesity and diabetes1. Studies in Drosophila2,3 have revealed molecular pathways4,5,6,7 and neural tissues8,9,10 regulating sleep; however, genes that maintain genetic variation for sleep in natural populations are unknown. Here, we characterized sleep in 40 wild-derived Drosophila lines and observed abundant genetic variation in sleep architecture. We associated sleep with genome-wide variation in gene expression11 to identify candidate genes. We independently confirmed that molecular polymorphisms in 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.