Robert R. H. Anholt

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.

Systems genetics of complex traits in Drosophila melanogaster.

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.

Epistasis dominates the genetic architecture of Drosophila quantitative traits

Epistasis—nonlinear genetic interactions between polymorphic loci—is the genetic basis of canalization and speciation, and epistatic interactions can be used to infer genetic networks affecting quantitative traits. However, the role that epistasis plays in the genetic architecture of quantitative traits is controversial. Here, we compared the genetic architecture of three Drosophila life history traits in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and a large outbred, advanced intercross population derived from 40 DGRP lines (Flyland). We assessed allele frequency changes between pools of individuals at the extremes of the distribution for each trait in the Flyland population by deep DNA sequencing. The genetic architecture of all traits was highly polygenic in both analyses. Surprisingly, none of the SNPs associated with the traits in Flyland replicated in the DGRP and vice versa. However, the majority of these SNPs participated in at least one epistatic interaction in the DGRP. Despite apparent additive effects at largely distinct loci in the two populations, the epistatic interactions perturbed common, biologically plausible, and highly connected genetic networks. Our analysis underscores the importance of epistasis as a principal factor that determines variation for quantitative traits and provides a means to uncover genetic networks affecting these traits. Knowledge of epistatic networks will contribute to our understanding of the genetic basis of evolutionarily and clinically important traits and enhance predictive ability at an individualized level in medicine and agriculture.

Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines

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.

QUANTITATIVE GENETIC ANALYSES OF COMPLEX BEHAVIOURS IN DROSOPHILA

Behaviours are exceptionally complex quantitative traits. Sensitivity to environmental variation and genetic background, the presence of sexual dimorphism, and the widespread functional pleiotropy that is inherent in behavioural phenotypes pose daunting challenges for unravelling their underlying genetics. Drosophila melanogaster provides an attractive system for elucidating the unifying principles of the genetic architectures that drive behaviours, as genetically identical individuals can be reared rapidly in controlled environments and extensive publicly accessible genetic resources are available. Recent advances in quantitative genetic and functional genomic approaches now enable the extensive characterization of complex genetic networks that mediate behaviours in this important model organism.

The genetic architecture of odor-guided behavior in Drosophila: epistasis and the transcriptome.

We combined transcriptional profiling and quantitative genetic analysis to elucidate the genetic architecture of olfactory behavior in Drosophila melanogaster. We applied whole-genome expression analysis to five coisogenic smell-impaired (smi) mutant lines and their control. We used analysis of variance to partition variation in transcript abundance between males and females and between smi genotypes and to determine the genotype-by-sex interaction. A total of 666 genes showed sexual dimorphism in transcript abundance, and 530 genes were coregulated in response to one or more smi mutations, showing considerable epistasis at the level of the transcriptome in response to single mutations. Quantitative complementation tests of mutations at these coregulated genes with the smi mutations showed that in most cases (67%) epistatic interactions for olfactory behavior mirrored epistasis at the level of transcription, thus identifying new candidate genes regulating olfactory behavior.

Functional dissection of Odorant binding protein genes in Drosophila melanogaster

Most organisms rely on olfaction for survival and reproduction. The olfactory system of Drosophila melanogaster is one of the best characterized chemosensory systems and serves as a prototype for understanding insect olfaction. Olfaction in Drosophila is mediated by multigene families of odorant receptors and odorant binding proteins (OBPs). Although molecular response profiles of odorant receptors have been well documented, the contributions of OBPs to olfactory behavior remain largely unknown. Here, we used RNAi‐mediated suppression of Obp gene expression and measurements of behavioral responses to 16 ecologically relevant odorants to systematically dissect the functions of 17 OBPs. We quantified the effectiveness of RNAi‐mediated suppression by quantitative real‐time polymerase chain reaction and used a proteomic liquid chromatography and tandem mass spectrometry procedure to show target‐specific suppression of OBPs expressed in the antennae. Flies in which expression of a specific OBP is suppressed often show altered behavioral responses to more than one, but not all, odorants, in a sex‐dependent manner. Similarly, responses to a specific odorant are frequently affected by suppression of expression of multiple, but not all, OBPs. These results show that OBPs are essential for mediating olfactory behavioral responses and suggest that OBP‐dependent odorant recognition is combinatorial.

Dynamic Genetic Interactions Determine Odor-Guided Behavior in Drosophila melanogaster

Understanding the genetic architecture of complex traits requires identification of the underlying genes and characterization of gene-by-gene and genotype-by-environment interactions. Behaviors that mediate interactions between organisms and their environment are complex traits expected to be especially sensitive to environmental conditions. Previous studies on the olfactory avoidance response of Drosophila melanogaster showed that the genetic architecture of this model behavior depends on epistatic networks of pleiotropic genes. We performed a screen of 1339 co-isogenic p[GT1]-element insertion lines to identify novel genes that contribute to odor-guided behavior and identified 55 candidate genes with known p[GT1]-element insertion sites. Characterization of the expression profiles of 10 p[GT1]-element insertion lines showed that the effects of the transposon insertions are often dependent on developmental stage and that hypomorphic mutations in developmental genes can elicit profound adult behavioral deficits. We assessed epistasis among these genes by constructing all possible double heterozygotes and measuring avoidance responses under two stimulus conditions. We observed enhancer and suppressor effects among subsets of these P-element-tagged genes, and surprisingly, epistatic interactions shifted with changes in the concentration of the olfactory stimulus. Our results show that the manifestation of epistatic networks dynamically changes with alterations in the environment.

Neurogenetic networks for startle-induced locomotion in Drosophila melanogaster

Understanding how the genome empowers the nervous system to express behaviors remains a critical challenge in behavioral genetics. The startle response is an attractive behavioral model for studies on the relationship between genes, brain, and behavior, as the ability to respond rapidly to harmful changes in the environment is a universal survival trait. Drosophila melanogaster provides a powerful system in which genetic studies on individuals with controlled genetic backgrounds and reared under controlled environmental conditions can be combined with neuroanatomical studies to analyze behaviors. In a screen of 720 lines of D. melanogaster, carrying single P[GT1] transposon insertions, we found 267 lines that showed significant changes in startle-induced locomotor behavior. Excision of the transposon reversed this effect in five lines out of six tested. We infer that most of the 267 lines show mutant effects on startle-induced locomotion that are caused by the transposon insertions. We selected a subset of 15 insertions in the same genetic background in autosomal genes with strong mutant effects and crossed them to generate all 105 possible nonreciprocal double heterozygotes. These hybrids revealed an extensive network of epistatic interactions on the behavioral trait. In addition, we observed changes in neuroanatomy that were caused by these 15 mutations, individually and in their double heterozygotes. We find that behavioral and neuroanatomical phenotypes are determined by a common set of genes that are organized as partially overlapping genetic networks.

Genome-wide association analysis of oxidative stress resistance in Drosophila melanogaster.

Background Aerobic organisms are susceptible to damage by reactive oxygen species. Oxidative stress resistance is a quantitative trait with population variation attributable to the interplay between genetic and environmental factors. Drosophila melanogaster provides an ideal system to study the genetics of variation for resistance to oxidative stress. Methods and Findings We used 167 wild-derived inbred lines of the Drosophila Genetic Reference Panel for a genome-wide association study of acute oxidative stress resistance to two oxidizing agents, paraquat and menadione sodium bisulfite. We found significant genetic variation for both stressors. Single nucleotide polymorphisms (SNPs) associated with variation in oxidative stress resistance were often sex-specific and agent-dependent, with a small subset common for both sexes or treatments. Associated SNPs had moderately large effects, with an inverse relationship between effect size and allele frequency. Linear models with up to 12 SNPs explained 67–79% and 56–66% of the phenotypic variance for resistance to paraquat and menadione sodium bisulfite, respectively. Many genes implicated were novel with no known role in oxidative stress resistance. Bioinformatics analyses revealed a cellular network comprising DNA metabolism and neuronal development, consistent with targets of oxidative stress-inducing agents. We confirmed associations of seven candidate genes associated with natural variation in oxidative stress resistance through mutational analysis. Conclusions We identified novel candidate genes associated with variation in resistance to oxidative stress that have context-dependent effects. These results form the basis for future translational studies to identify oxidative stress susceptibility/resistance genes that are evolutionary conserved and might play a role in human disease.