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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.

The statistical power of genome-wide association (GWA) studies to detect risk alleles for human diseases is limited by the unfavorable ratio of SNPs to study subjects. This multiple testing problem can be surmounted with very large population sizes when common alleles of large effects give rise to disease status. However, GWA approaches fall short when many rare alleles may give rise to a common disease, or when the number of subjects that can be recruited is limited. Here, we demonstrate that this multiple testing problem can be overcome by a comparative genomics approach in which an initial genome-wide screen in a genetically amenable model organism is used to identify human orthologues that may harbor risk alleles for adult-onset primary open angle glaucoma (POAG). Glaucoma is a major cause of blindness, which affects over 60 million people worldwide. Several genes have been associated with juvenile onset glaucoma, but genetic factors that predispose to adult onset primary open angle glaucoma (POAG) remain largely unknown. Previous genome-wide analysis in a Drosophila ocular hypertension model identified transcripts with altered regulation and showed induction of the unfolded protein response (UPR) upon overexpression of transgenic human glaucoma-associated myocilin (MYOC). We selected 16 orthologous genes with 62 polymorphic markers and identified in two independent human populations two genes of the UPR that harbor POAG risk alleles, BIRC6 and PDIA5. Thus, effectiveness of the UPR in response to accumulation of misfolded or aggregated proteins may contribute to the pathogenesis of POAG and provide targets for early therapeutic intervention.

Genotype by environment interactions (GEI) play a major part in shaping the genetic architecture of quantitative traits and are confounding factors in genetic studies, for example, in attempts to associate genetic variation with disease susceptibility. It is generally not known what proportion of phenotypic variation is due to GEI and how many and which genes contribute to GEI. Behaviors are complex traits that mediate interactions with the environment and, thus, are ideally suited for studies of GEI. Olfactory behavior in Drosophila melanogaster presents an opportunity to systematically dissect GEI, since large numbers of genetically identical individuals can be reared under defined environmental conditions and the olfactory system of Drosophila and its behavioral response to odorants have been well characterized. We assessed variation in olfactory behavior in a population of 41 wild-derived inbred lines and asked to what extent different larval-rearing environments would influence adult olfactory behavior and whether GEI is a minor or major contributing source of phenotypic variation. We found that ~50% of phenotypic variation in adult olfactory behavior is attributable to GEI. In contrast, transcriptional analysis revealed that only 20 genes show GEI at the level of gene expression [false discovery rate (FDR) < 0.05], some of which are associated with physiological responses to environmental chemicals. Quantitative complementation tests with piggyBac-tagged mutants for 2 of these genes (CG9664 and Transferrin 1) demonstrate that genes that show transcriptional GEI are candidate genes for olfactory behavior and that GEI at the level of gene expression is correlated with GEI at the level of phenotype.

Using quantitative trait locus (QTL) mapping, we studied the genetic basis of the difference in pigmentation between two sister species of Drosophila: Drosophila yakuba, which, like other members of the D. melanogaster subgroup, shows heavy black pigmentation on the abdomen of males and females, and D. santomea, an endemic to the African island of Sao Tome, which has virtually no pigmentation. Here we mapped four QTL with large effects on this interspecific difference in pigmentation: two on the X chromosome and one each on the second and third chromosomes. The same four QTL were detected in male hybrids in the backcrosses to both D. santomea and D. yakuba and in the female D. yakuba backcross hybrids. All four QTL exhibited strong epistatic interactions in male backcross hybrids, but only one pair of QTL interacted in females from the backcross to D. yabuka. All QTL from each species affected pigmentation in the same direction, consistent with adaptive evolution driven by directional natural selection. The regions delimited by the QTL included many positional candidate loci in the pigmentation pathway, including genes affecting catecholamine biosynthesis, melanization of the cuticle, and many additional pleiotropic effects.

The pyruvate carboxylase (PC) gene has been characterized in the first identification of the human PC gene structure. Screening cDNA and the gene of those with the simple A form of PC deficiency brought out an 1828G-->A missense mutation in 11 Ojibwa and 2 Cree patients and a 2229G--> T transversion mutation in two people of Micmac origin, two brothers. Identification of common pathogenic mutations has been made and a founder effect in the Cree and Ojibwa patients has been shown. In Native Americans, or Amerindians, PC deficiency has been shown to be associated with two missense mutations.

Senescence, i.e., functional decline with age, is a major determinant of health span in a rapidly aging population, but the genetic basis of interindividual variation in senescence remains largely unknown. Visual decline and age-related eye disorders are common manifestations of senescence, but disentangling age-dependent visual decline in human populations is challenging due to inability to control genetic background and variation in histories of environmental exposures. We assessed the genetic basis of natural variation in visual senescence by measuring age-dependent decline in phototaxis using Drosophila melanogaster as a genetic model system. We quantified phototaxis at 1, 2, and 4 wk of age in the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and found an average decline in phototaxis with age. We observed significant genetic variation for phototaxis at each age and significant genetic variation in senescence of phototaxis that is only partly correlated with phototaxis. Genome-wide association analyses in the DGRP and a DGRP-derived outbred, advanced intercross population identified candidate genes and genetic networks associated with eye and nervous system development and function, including seven genes with human orthologs previously associated with eye diseases. Ninety percent of candidate genes were functionally validated with targeted RNAi-mediated suppression of gene expression. Absence of candidate genes previously implicated with longevity indicates physiological systems may undergo senescence independent of organismal life span. Furthermore, we show that genes that shape early developmental processes also contribute to senescence, demonstrating that senescence is part of a genetic continuum that acts throughout the life span. [ABSTRACT FROM AUTHOR]

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 Drosophila 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Background: Locomotion is an integral component of most animal behaviors, and many human health problems are associated with locomotor deficits. Locomotor behavior is a complex trait, with population variation attributable to many interacting loci with small effects that are sensitive to environmental conditions. However, the genetic basis of this complex behavior is largely uncharacterized., Results: We quantified locomotor behavior of Drosophila melanogaster in a large population of inbred lines derived from a single natural population, and derived replicated selection lines with different levels of locomotion. Estimates of broad-sense and narrow-sense heritabilities were 0.52 and 0.16, respectively, indicating substantial non-additive genetic variance for locomotor behavior. We used whole genome expression analysis to identify 1,790 probe sets with different expression levels between the selection lines when pooled across replicates, at a false discovery rate of 0.001. The transcriptional responses to selection for locomotor, aggressive and mating behavior from the same base population were highly overlapping, but the magnitude of the expression differences between selection lines for increased and decreased levels of behavior was uncorrelated. We assessed the locomotor behavior of ten mutations in candidate genes with altered transcript abundance between selection lines, and identified seven novel genes affecting this trait., Conclusion: Expression profiling of genetically divergent lines is an effective strategy for identifying genes affecting complex behaviors, and reveals that a large number of pleiotropic genes exhibit correlated transcriptional responses to multiple behaviors.