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The abundant and widely distributed deermice Peromyscus leucopus and P. maniculatus are important reservoirs for several different zoonotic agents in North America. For the pathogens they persistently harbor, these species are also examples of the phenomenon of infection tolerance. In the present study a prior observation of absent expression of the high-affinity Fc immunoglobulin gamma receptor I (FcγRI), or CD64, in P. leucopus was confirmed in an experimental infection with Borreliella burgdorferi, a Lyme disease agent. We demonstrate that the null phenotype is attributable to a long-standing inactivation of the Fcgr1 gene in both species by a deletion of the promoter and coding sequence for the signal peptide for FcγRI. The Fcgr1 pseudogene was also documented in the related species P. polionotus. Six other Peromyscus species, including P. californicus, have coding sequences for a full-length FcγRI, including a consensus signal peptide. An inference from reported phenotypes for null Fcgr1 mutations engineered in Mus musculus is that one consequence of pseudogenization of Fcgr1 is comparatively less inflammation during infection than in animals, including humans, with undisrupted, fully active genes. [ABSTRACT FROM AUTHOR]

We use ATAC-seq to examine chromatin accessibility for four different tissues in Drosophila melanogaster: adult female brain, ovaries, and both wing and eye-antennal imaginal discs from males. Each tissue is assayed in eight different inbred strain genetic backgrounds, seven associated with a reference quality genome assembly. We develop a method for the quantile normalization of ATAC-seq fragments and test for differences in coverage among genotypes, tissues, and their interaction at 44099 peaks throughout the euchromatic genome. For the strains with reference quality genome assemblies, we correct ATAC-seq profiles for read mis-mapping due to nearby polymorphic structural variants (SVs). Comparing coverage among genotypes without accounting for SVs results in a highly elevated rate (55%) of identifying false positive differences in chromatin state between genotypes. After SV correction, we identify 1050, 30383, and 4508 regions whose peak heights are polymorphic among genotypes, among tissues, or exhibit genotype-by-tissue interactions, respectively. Finally, we identify 3988 candidate causative variants that explain at least 80% of the variance in chromatin state at nearby ATAC-seq peaks. Author summary: Chromatin states are well described in Drosophila melanogaster embryos, but adult and pre-adult tissues are poorly studied, as are differences among genotypes. We carried out ATAC-seq on four different tissues in eight different inbred genotypes with biological replicates within tissue and genotype. We discover that apparent differences in coverage, and by inference chromatin openness, are often due to segregating structural variants (SVs) that can only be corrected for if strains are associated with high-quality genome assemblies. After correction for false positives associated with SVs, we identify thousands of regions that appear to vary in chromatin state between genotypes or vary between genotypes in a tissue-dependent manner. It has been widely speculated that cis-regulatory variants contribute to standing variation in complex traits. If this is true, chromatin states that vary between individuals, perhaps in a tissue-dependent manner, are likely to be enriched for quantitative trait loci. [ABSTRACT FROM AUTHOR]

Drosophila melanogaster has proved an effective system with which to understand the evolutionary genetics and molecular mechanisms of insecticide resistance. Insecticide use has left signatures of selection in the fly genome, and both functional and quantitative genetic studies in the system have identified genes and variants associated with resistance. Here, we use D. melanogaster and leverage a bulk phenotyping and pooled sequencing "extreme quantitative trait loci" approach to genetically dissect variation in resistance to malathion, an organophosphate insecticide. We resolve 2 quantitative trait loci, one of which implicates allelic variation at the cytochrome P450 gene Cyp6g1, a strong candidate based on previous work. The second shows no overlap with hits from a previous genome-wide association study for malathion resistance, recapitulating other studies showing that different strategies for complex trait dissection in flies can yield apparently different architectures. Notably, we see no genetic signal at the Ace gene. Ace encodes the target of organophosphate insecticide inhibition, and genome-wide association studies have identified strong Ace-linked associations with resistance in flies. The absence of quantitative trait locus implicating Ace here is most likely because our mapping population does not segregate for several of the known functional polymorphisms impacting resistance at Ace, perhaps because our population is derived from flies collected prior to the widespread use of organophosphate insecticides. Our fundamental approach can be an efficient, powerful strategy to dissect genetic variation in resistance traits. Nonetheless, studies seeking to interrogate contemporary insecticide resistance variation may benefit from deriving mapping populations from more recently collected strains. [ABSTRACT FROM AUTHOR]

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations. [ABSTRACT FROM AUTHOR]

Experimental evolution systems allow the genomic study of adaptation, and so far this has been done primarily in asexual systems with small genomes, such as bacteria and yeast (1-3). Here we present whole-genome resequencing data from Drosophila melanogaster populations that have experienced over 600 generations of laboratory selection for accelerated development. Flies in these selected populations develop from egg to adult ~20% faster than flies of ancestral control populations, and have evolved a number of other correlated phenotypes. On the basis of 688,520 intermediate-frequency, high-quality single nucleotide polymorphisms, we identify several dozen genomic regions that show strong allele frequency differentiation between a pooled sample of five replicate populations selected for accelerated development and pooled controls. On the basis of resequencing data from a single replicate population with accelerated development, as well as single nucleotide polymorphism data from individual flies from each replicate population, we infer little allele frequency differentiation between replicate populations within a selection treatment. Signatures of selection are qualitatively different than what has been observed in asexual species; in our sexual populations, adaptation is not associated with 'classic' sweeps whereby newly arising, unconditionally advantageous mutations become fixed. More parsimonious explanations include 'incomplete' sweep models, in which mutations have not had enough time to fix, and 'soft' sweep models, in which selection acts on pre-existing, common genetic variants. We conclude that, at least for life history characters such as development time, unconditionally advantageous alleles rarely arise, are associated with small net fitness gains or cannot fix because selection coefficients change over time., Experimental evolution uses well-defined selection protocols to force phenotypic divergence (4,5). Studies of experimentally evolved populations have identified mutations responsible for particular adaptations (6) and provided some general insights into [...]

We develop and implement a strategy to map QTL in two synthetic populations of Drosophila melanogaster each initiated with eight inbred founder strains. These recombinant populations allow simultaneous estimates of QTL location, effect, and frequency. Five X-linked QTL influencing bristle number were resolved to intervals of ~l.3 cM. We confirm previous observations of bristle number QTL distal to 4A at the tip of the chromosome and identify two novel QTL in 7F-8C, an interval that does not include any classic bristle number candidate genes. If QTL at the tip of the X are biallelic they appear to be intermediate in frequency, although there is evidence that these QTL may reside in multiallelic haplotypes. Conversely, the two QTL mapping to the middle of the X chromosome are likely rare: in each case the minor allele is observed in only 1 of the 16 founders. Assuming additivity and biallelism we estimate that identified QTL contribute 1.0 and 8.7%, respectively, to total phenotypic variation in male abdominal and sternopleural bristle number in nature. Models that seek to explain the maintenance of genetic variation make different predictions about the population frequency of QTL alleles. Thus, mapping QTL in eight-way recombinant populations can distinguish between these models.

Currently, the relevance of common genetic variants--particularly those significantly associated with phenotypic variation in laboratory studies--to standing phenotypic variation in the wild is poorly understood. To address this, we quantified the relationship between achaete-scute complex (ASC) polymorphisms and Drosophila bristle number phenotypes in several new population samples. MC22 is a biallelic, nonrepetitive-length polymorphism 97 bp downstream of the scute transcript. It has been previously shown to be associated with sternopleural bristle number variation in both sexes in a set of isogenic lines. We replicated this association in a large cohort of wild-caught Drosophila melanogaster. We also detected a significant association at MC22 in an outbred population maintained under laboratory conditions for ~25 years, but the phenotypic effects in this sample were opposite from the direction estimated in the initial study. Finally, no significant associations were detected in a second large wild-caught cohort or in a set of 134 nearly isogenic lines. Our ability to repeat the initial association in wild samples suggests that it was not spurious. Nevertheless, inconsistent results from the other three panels suggest that the relationship between polymorphic genetic markers and loci contributing to continuous variation is not a simple one.

Drosophila melanogaster males perform a courtship ritual consisting of a series of dependent fixed-action patterns. The yellow (y) gene is required for normal male courtship behavior and subsequent mating success. To better characterize the requirement for y in the manifestation of innate male sexual behavior, we measured the male mating success (MMS) of 12 hypomorphic y mutants and matched-outbred-background controls using a [y.sup.+] rescue element on a freely segregating minichromosome. We found that 4 hypomorphs significantly reduced MMS to varying degrees. Reduced MMS was largely independent of adult pigmentation patterns. These mutations defined a 300-bp regulatory region upstream of the transcription start, the mating-success regulatory sequence (MRS), whose function is required for normal MMS. Visualization of gene action via GFP and a Yellow antibody suggests that the MRS directs y transcription in a small number of cells in the third instar CNS, the developmental stage previously implicated in the role of y with regard to male courtship behavior. The presence of Yellow protein in these cells positively correlates with MMS in a subset of mutants. The MRS contains a regulatory sequence controlling larval pigmentation and a 35-bp sequence that is highly conserved within the genus Drosophila and is predicted to bind known transcription factors.

The Enhancer of split complex [E(spl)-C] in Drosophila encompasses a variety of functional elements controlling bristle patterning and on the basis of prior work is a strong candidate for harboring alleles having subtle effects on bristle number variation. Here we extend earlier studies identifying associations between complex phenotypes and polymorphisms segregating among inbred laboratory lines of Drosophila and test the influence of E(spl)-C on bristle number variation in a natural cohort. We describe results from an association mapping study using 203 polymorphisms spread throughout the E (spl)-C genotyped in 2000 wild-caught Drosophila melanogaster: Despite power to detect associations accounting for as little as 2% of segregating variation for bristle number, and saturating the region with single-nucleotide polymorphisms (SNPs), we identified no single SNP marker showing a significant (additive over loci) effect after correcting for multiple tests. Using a newly developed test we conservatively identify six regions of the E (spl)-C in which the insertion of transposable elements as a class contributes to variation in bristle number, apparently in a sex- or trait-limited fashion. Finally, we carry out all possible 20,503 two-way tests for epistasis and identify a slight excess of marginally significant interactions, although none survive multiple-testing correction. It may not be straightforward to extend the results of laboratory-based association studies to natural populations.

To extend results from laboratory genetic mapping experiments to natural populations it is necessary to estimate the phenotypic effects attributable to laboratory-identified genetic factors in nature. We retested a polymorphism found to be strongly associated with an increase of 0.35 sternopleural bristles in laboratory strains in two large samples of wild-caught Drosophila melanogaster. Despite >90% power to detect effects as low as 0.27 bristles (

We test the hypothesis that naturally occurring nonsynonymous variants in the Delta ligand of the Notch signaling pathway contribute to standing variation in sternopleural and/or abdominal bristle number in Drosophila melanogaster, for both a large cohort of wild-caught flies and previously described laboratory lines. We sequenced the transcribed region of Delta for 16 naturally occurring chromosomes and 65 SNPs, including 7 nonsynonymous SNPs (nsSNPs), were observed. Identified nsSNPs and 6 additional common SNPs, all located in exon 6 and the 3' UTR, were genotyped in 2060 wild-caught flies using an OLA-based methodology and genotyped in 38 additional natural chromosomes via DNA sequencing. None of the genotyped nsSNPs were significantly associated with natural variation in bristle number as assessed by a permutation test. A 95% upper bound on the additive genetic variance attributable to each genotyped SNP in the large natural cohort is

Author(s): Patrícia Beldade (corresponding author) [1]; Paul M. Brakefield [1]; Anthony D. Long [2] The colour patterns decorating butterfly wings provide ideal material to study the reciprocal interactions between evolution [...]

Abstract Background Butterfly wing color patterns are a key model for integrating evolutionary developmental biology and the study of adaptive morphological evolution. Yet, despite the biological, economical and educational value of butterflies they are still relatively under-represented in terms of available genomic resources. Here, we describe an Expression Sequence Tag (EST) project for Bicyclus anynana that has identified the largest available collection to date of expressed genes for any butterfly. Results By targeting cDNAs from developing wings at the stages when pattern is specified, we biased gene discovery towards genes potentially involved in pattern formation. Assembly of 9,903 ESTs from a subtracted library allowed us to identify 4,251 genes of which 2,461 were annotated based on BLAST analyses against relevant gene collections. Gene prediction software identified 2,202 peptides, of which 215 longer than 100 amino acids had no homology to any known proteins and, thus, potentially represent novel or highly diverged butterfly genes. We combined gene and Single Nucleotide Polymorphism (SNP) identification by constructing cDNA libraries from pools of outbred individuals, and by sequencing clones from the 3' end to maximize alignment depth. Alignments of multi-member contigs allowed us to identify over 14,000 putative SNPs, with 316 genes having at least one high confidence double-hit SNP. We furthermore identified 320 microsatellites in transcribed genes that can potentially be used as genetic markers. Conclusion Our project was designed to combine gene and sequence polymorphism discovery and has generated the largest gene collection available for any butterfly and many potential markers in expressed genes. These resources will be invaluable for exploring the potential of B. anynana in particular, and butterflies in general, as models in ecological, evolutionary, and developmental genetics.

"Evolve and resequence" (E&R) studies combine experimental evolution and whole‐genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms such as bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling—the number of discrete time points sequence data are collected from evolving populations. Using data from an E&R experiment with outcrossing Saccharomyces cerevisiae in which populations were sequenced 17 times over ~540 generations, we address the following questions: (a) Do more time points improve the ability to identify candidate regions underlying selection? And (b) does high‐resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high‐resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e., models assuming constant selection coefficients), and two where trajectories suggest more context‐dependent responses (i.e., models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling eight or more time points has clear benefits for studying complex evolutionary dynamics. [ABSTRACT FROM AUTHOR]

Vernal pools are unique in their isolation and the strong selection acting on their resident species. Vernal pool clam shrimp (Eulimnadia texana) are a promising model due to ease of culturing, short generation time, small genomes, and obligate desiccated diapaused eggs. Clam shrimp are also androdioecious (sexes include males and hermaphrodites), and here we use population-scaled recombination rates to support the hypothesis that the heterogametic sex is recombination free in these shrimp. We collected short-read sequence data from pooled samples from different vernal pools to gain insights into local adaptation. We identify genomic regions in which some populations have allele frequencies that differ significantly from the metapopulation. BayPass (Gautier M. 2015. Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201(4):1555–1579.) detected 19 such genomic regions showing an excess of population subdivision. These regions on average are 550 bp in size and had 2.5 genes within 5 kb of them. Genes located near these regions are involved in Malpighian tubule function and osmoregulation, an essential function in vernal pools. It is likely that salinity profiles vary between pools and over time, and variants at these genes are adapted to local salinity conditions. [ABSTRACT FROM AUTHOR]

Vernal pool clamshrimp (Eulimnadia texana) are a promising model system due to their ease of lab culture, short generation time, modest sized genome, a somewhat rare stable androdioecious sex determination system, and a requirement to reproduce via desiccated diapaused eggs. We generated a highly contiguous genome assembly using 46x of PacBio long read data and 216x of Illumina short reads, and annotated using Illumina RNAseq obtained from adult males or hermaphrodites. Of the 120Mb genome 85%is contained in the largest eight contigs, the smallest of which is 4.6Mb. The assembly contains 98%of transcripts predicted via RNAseq. This assembly is qualitatively different from scaffolded Illumina assemblies: It is produced from long reads that contain sequence data along their entire length, and is thus gap free. The contiguity of the assembly allows us to order the HOX genes within the genome, identifying two loci that contain HOX gene orthologs, and which approximately maintain the order observed in other arthropods. We identified a partial duplication of the Antennapedia complex adjacent to the few genes homologous to the Bithorax locus. Because the sex chromosome of an androdioecious species is of special interest, we used existing allozyme and microsatellite markers to identify the E. texana sex chromosome, and find that it comprises nearly half of the genome of this species. Linkage patterns indicate that recombination is extremely rare and perhaps absent in hermaphrodites, and as a result the location of the sex determining locus will be difficult to refine using recombination mapping. [ABSTRACT FROM AUTHOR]

A major goal in the analysis of complex traits is to partition the observed genetic variation in a trait into components due to individual loci and perhaps variants within those loci. However, in both QTL mapping and genetic association studies, the estimated percent variation attributable to a QTL is upwardly biased conditional on it being discovered. This bias was first described in two-way QTL mapping experiments by William Beavis, and has been referred to extensively as "the Beavis effect." The Beavis effect is likely to occur in multiparent population (MPP) panels as well as collections of sequenced lines used for genome-wide association studies (GWAS). However, the strength of the Beavis effect is unknown--and often implicitly assumed to be negligible--when "hits" are obtained from an association panel consisting of hundreds of inbred lines tested across millions of SNPs, or in multiparent mapping populations where mapping involves fitting a complex statistical model with several d.f. at thousands of genetic intervals. To estimate the size of the effect in more complex panels, we performed simulations of both biallelic and multiallelic QTL in two major Drosophila melanogaster mapping panels, the GWAS-based Drosophila Genetic Reference Panel (DGRP), and the MPP the Drosophila Synthetic Population Resource (DSPR). Our results show that overestimation is determined most strongly by sample size and is only minimally impacted by the mapping design. When , 100, 200, 500, and 1000 lines are employed, the variance attributable to hits is inflated by factors of 6, 3, 1.5, and 1.1, respectively, for a QTL that truly contributes 5% to the variation in the trait. This overestimation indicates that QTL could be difficult to validate in follow-up replication experiments where additional individuals are examined. Further, QTL could be difficult to cross-validate between the two Drosophila resources. We provide guidelines for: (1) the sample sizes necessary to accurately estimate the percent variance to an identified QTL, (2) the conditions under which one is likely to replicate a mapped QTL in a second study using the same mapping population, and (3) the conditions under which a QTL mapped in one mapping panel is likely to replicate in the other (DGRP and DSPR). [ABSTRACT FROM AUTHOR]

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect-sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have associated many single variants with complex disease, yet the better part of heritable complex disease risk remains unexplained. Analytical tools designed to work under specific population genetic models are needed. Rare variants are increasingly shown to be important in human complex disease, but most existing GWAS data do not cover rare variants. Explicit population genetic models predict that genes contributing to complex traits and experiencing recurrent, unconditionally deleterious, mutation will harbor multiple rare, causative mutations of subtle effect. It is difficult to identify genes harboring rare variants of large effect that contribute to complex disease risk via the single marker association tests typically used in GWAS. Gene/region-based association tests may have the power detect associations by combining information from multiple markers, but have yielded limited success in practice. This is partially because many methods have not been widely applied. Here, we empirically demonstrate the utility of a procedure based on the rank truncated product (RTP) method, filtered to reduce the effects of linkage disequilibrium. We apply the procedure to the Wellcome Trust Case Control Consortium (WTCCC) data set, and uncover previously unidentified associations, some of which have been replicated in much larger studies. We show that, in the absence of significant rare variant coverage, RTP based methods still have the power to detect associated genes. We recommend that RTP-based methods be applied to all existing GWAS data to maximize the usefulness of those data. For this, we provide efficient software implementing our procedure. [ABSTRACT FROM AUTHOR]

Natural populations exhibit a great deal of interindividual genetic variation in the response to toxins, exemplified by the variable clinical efficacy of pharmaceutical drugs in humans, and the evolution of pesticide resistant insects. Such variation can result from several phenomena, including variable metabolic detoxification of the xenobiotic, and differential sensitivity of the molecular target of the toxin. Our goal is to genetically dissect variation in the response to xenobiotics, and characterize naturally-segregating polymorphisms that modulate toxicity. Here, we use the Drosophila Synthetic Population Resource (DSPR), a multiparent advanced intercross panel of recombinant inbred lines, to identify QTL (Quantitative Trait Loci) underlying xenobiotic resistance, and employ caffeine as a model toxic compound. Phenotyping over 1,700 genotypes led to the identification of ten QTL, each explaining 4.5–14.4% of the broad-sense heritability for caffeine resistance. Four QTL harbor members of the cytochrome P450 family of detoxification enzymes, which represent strong a priori candidate genes. The case is especially strong for Cyp12d1, with multiple lines of evidence indicating the gene causally impacts caffeine resistance. Cyp12d1 is implicated by QTL mapped in both panels of DSPR RILs, is significantly upregulated in the presence of caffeine, and RNAi knockdown robustly decreases caffeine tolerance. Furthermore, copy number variation at Cyp12d1 is strongly associated with phenotype in the DSPR, with a trend in the same direction observed in the DGRP (Drosophila Genetic Reference Panel). No additional plausible causative polymorphisms were observed in a full genomewide association study in the DGRP, or in analyses restricted to QTL regions mapped in the DSPR. Just as in human populations, replicating modest-effect, naturally-segregating causative variants in an association study framework in flies will likely require very large sample sizes. [ABSTRACT FROM AUTHOR]

For most complex traits we have a poor understanding of the positions, phenotypic effects, and population frequencies of the underlying genetic variants contributing to their variation. Recently, several groups have developed multi-parent advanced intercross mapping panels in different model organisms in an attempt to improve our ability to characterize causative genetic variants. These panels are powerful and are particularly well suited to the dissection of phenotypic variation generated by rare alleles and loci segregating multiple functional alleles. We describe studies using one such panel, the Drosophila Synthetic Population Resource (DSPR), and the implications for our understanding of the genetic basis of complex traits. In particular, we note that many loci of large effect appear to be multiallelic. If multiallelism is a general rule, analytical approaches designed to identify multiallelic variants should be a priority for both genome-wide association studies (GWASs) and multi-parental panels. [ABSTRACT FROM AUTHOR]

Modern genetic mapping is plagued by the “missing heritability” problem, which refers to the discordance between the estimated heritabilities of quantitative traits and the variance accounted for by mapped causative variants. One major potential explanation for the missing heritability is allelic heterogeneity, in which there are multiple causative variants at each causative gene with only a fraction having been identified. The majority of genome-wide association studies (GWAS) implicitly assume that a single SNP can explain all the variance for a causative locus. However, if allelic heterogeneity is prevalent, a substantial amount of genetic variance will remain unexplained. In this paper, we take a haplotype-based mapping approach and quantify the number of alleles segregating at each locus using a large set of 7922 eQTL contributing to regulatory variation in the Drosophila melanogaster female head. Not only does this study provide a comprehensive eQTL map for a major community genetic resource, the Drosophila Synthetic Population Resource, but it also provides a direct test of the allelic heterogeneity hypothesis. We find that 95% of cis-eQTLs and 78% of trans-eQTLs are due to multiple alleles, demonstrating that allelic heterogeneity is widespread in Drosophila eQTL. Allelic heterogeneity likely contributes significantly to the missing heritability problem common in GWAS studies. [ABSTRACT FROM AUTHOR]