Abundance and distribution of transposable elements in two Drosophila QTL mapping resources.

Here we present computational machinery to efficiently and accurately identify transposable element (TE) insertions in 146 next-generation sequenced inbred strains of Drosophila melanogaster. The panel of lines we use in our study is composed of strains from a pair of genetic mapping resources: the Drosophila Genetic Reference Panel (DGRP) and the Drosophila Synthetic Population Resource (DSPR). We identified 23,087 TE insertions in these lines, of which 83.3% are found in only one line. There are marked differences in the distribution of elements over the genome, with TEs found at higher densities on the X chromosome, and in regions of low recombination. We also identified many more TEs per base pair of intronic sequence and fewer TEs per base pair of exonic sequence than expected if TEs are located at random locations in the euchromatic genome. There was substantial variation in TE load across genes. For example, the paralogs derailed and derailed-2 show a significant difference in the number of TE insertions, potentially reflecting differences in the selection acting on these loci. When considering TE families, we find a very weak effect of gene family size on TE insertions per gene, indicating that as gene family size increases the number of TE insertions in a given gene within that family also increases. TEs are known to be associated with certain phenotypes, and our data will allow investigators using the DGRP and DSPR to assess the functional role of TE insertions in complex trait variation more generally. Notably, because most TEs are very rare and often private to a single line, causative TEs resulting in phenotypic differences among individuals may typically fail to replicate across mapping panels since individual elements are unlikely to segregate in both panels. Our data suggest that "burden tests" that test for the effect of TEs as a class may be more fruitful.

Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster.

Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper results in cell and tissue damage ranging in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes respond to nonessential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the heavy metal stress response. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource using a combination of differential expression analysis and expression quantitative trait locus mapping. Differential expression analysis revealed clear patterns of tissue-specific expression. Tissue and treatment specific responses to copper stress were also detected using expression quantitative trait locus mapping. Expression quantitative trait locus associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited both genotype-by-tissue and genotype-by-treatment effects on gene expression under copper stress, illuminating tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight candidate genes for future functional characterization.

Naturally segregating genetic variants contribute to thermal tolerance in a Drosophila melanogaster model system.

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants within the genes that control this trait is of high importance if we want to better comprehend thermal physiology. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource as a model system. First, we used quantitative genetics and Quantitative Trait Loci mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to (1) alter tissue-specific gene expression and (2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Real-time monitoring of intracellular signal transduction in PC12 cells by two-dimensional surface plasmon resonance imager.

Real-time observation of intracellular process of signal transduction is very useful for biomedical and pharmaceutical applications as well as for basic research work of cell biology. The conventional methods used to observe intracellular reactions have not been convenient with several steps such as labeling and washing steps prior to the readout. Consequently, there is a critical need for label-free observation techniques for monitoring intracellular reactions. For feasible and reagentless observation of intracellular alterations in real time, we examined the use of a high-resolution two-dimensional surface plasmon resonance (2D-SPR) imager for monitoring of intracellular signal transduction that was mainly translocation of protein kinase C via local refractive index change in PC12 cells adhered on a gold sensor slide without any indicator reagent. PC12 cells were stimulated with KCl and phorbol-12-myristate-13-acetate (PMA, a protein kinase C [PKC] activator) at different concentrations in order to induce intracellular PKC translocation. 2D-SPR signal (reflection intensity change) is very consistent with the cellular response normally detected for these stimulants. Our results suggest that complex intracellular reactions could be real-time monitored and characterized by the 2D-SPR imager. It is further expected that signal transmission that was followed by the translocation of signaling proteins could be observed at the single cell level with the high-resolution 2D-SPR imager.

Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster.

Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper quickly results in cell and tissue damage that can range in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes also respond to other non-essential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the response to heavy metal stress. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource (DSPR) using a combination of differential expression analysis and expression quantitative trait locus (eQTL) mapping. Differential expression analysis revealed clear patterns of tissue-specific expression, primarily driven by a more pronounced gene expression response in gut tissue. eQTL mapping of gene expression under control and copper conditions as well as for the change in gene expression following copper exposure (copper response eQTL) revealed hundreds of genes with tissue-specific local cis-eQTL and many distant trans-eQTL. eQTL associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited genotype by environment effects on gene expression under copper stress, illuminating several tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight many candidate genes for future functional characterization.

Naturally segregating genetic variants contribute to thermal tolerance in a D. melanogaster model system.

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation, are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants of the genes that control this trait is of high importance if we want to better comprehend how this trait evolves in natural populations. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource (DSPR) as a model system. First, we used quantitative genetics and Quantitative Trait Loci (QTL) mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to 1) alter tissue-specific gene expression and 2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Discovery of malathion resistance QTL in Drosophila melanogaster using a bulked phenotyping approach.

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.

Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing.

Despite the value of recombinant inbred lines for the dissection of complex traits, large panels can be difficult to maintain, distribute, and phenotype. An attractive alternative to recombinant inbred lines for many traits leverages selecting phenotypically extreme individuals from a segregating population, and subjecting pools of selected and control individuals to sequencing. Under a bulked or extreme segregant analysis paradigm, genomic regions contributing to trait variation are revealed as frequency differences between pools. Here, we describe such an extreme quantitative trait locus, or extreme quantitative trait loci, mapping strategy that builds on an existing multiparental population, the Drosophila Synthetic Population Resource, and involves phenotyping and genotyping a population derived by mixing hundreds of Drosophila Synthetic Population Resource recombinant inbred lines. Simulations demonstrate that challenging, yet experimentally tractable extreme quantitative trait loci designs (≥4 replicates, ≥5,000 individuals/replicate, and selecting the 5-10% most extreme animals) yield at least the same power as traditional recombinant inbred line-based quantitative trait loci mapping and can localize variants with sub-centimorgan resolution. We empirically demonstrate the effectiveness of the approach using a 4-fold replicated extreme quantitative trait loci experiment that identifies 7 quantitative trait loci for caffeine resistance. Two mapped extreme quantitative trait loci factors replicate loci previously identified in recombinant inbred lines, 6/7 are associated with excellent candidate genes, and RNAi knock-downs support the involvement of 4 genes in the genetic control of trait variation. For many traits of interest to drosophilists, a bulked phenotyping/genotyping extreme quantitative trait loci design has considerable advantages.

Genetic dissection of innate immune memory in Drosophila melanogaster.

Current studies have demonstrated that innate immunity possesses memory characteristics. Although the molecular mechanisms underlying innate immune memory have been addressed by numerous studies, genetic variations in innate immune memory and the associated genes remain unclear. Here, we explored innate immune memory in 163 lines of Drosophila melanogaster from the Drosophila Synthetic Population Resource. In our assay system, prior training with low pathogenic bacteria (Micrococcus luteus) increased the survival rate of flies after subsequent challenge with highly pathogenic bacteria (Staphylococcus aureus). This positive training effect was observed in most lines, but some lines exhibited negative training effects. Survival rates under training and control conditions were poorly correlated, suggesting that distinct genetic factors regulate training effects and normal immune responses. Subsequent quantitative trait loci analysis suggested that four loci containing 80 genes may be involved in regulating innate immune memory. Among them, Adgf-A, which encodes an extracellular adenosine deaminase-related growth factor, was shown to be associated with training effects. Our study findings help to elucidate the genetic architecture of innate immune memory in Drosophila and may provide insight for new therapeutic treatments aimed at boosting immunity.

Characterizing the genetic basis of copper toxicity in Drosophila reveals a complex pattern of allelic, regulatory, and behavioral variation.

A range of heavy metals are required for normal cell function and homeostasis. However, the anthropogenic release of metal compounds into soil and water sources presents a pervasive health threat. Copper is one of many heavy metals that negatively impacts diverse organisms at a global scale. Using a combination of quantitative trait locus (QTL) mapping and RNA sequencing in the Drosophila Synthetic Population Resource, we demonstrate that resistance to the toxic effects of ingested copper in D. melanogaster is genetically complex and influenced by allelic and expression variation at multiple loci. QTL mapping identified several QTL that account for a substantial fraction of heritability. Additionally, we find that copper resistance is impacted by variation in behavioral avoidance of copper and may be subject to life-stage specific regulation. Gene expression analysis further demonstrated that resistant and sensitive strains are characterized by unique expression patterns. Several of the candidate genes identified via QTL mapping and RNAseq have known copper-specific functions (e.g., Ccs, Sod3, CG11825), and others are involved in the regulation of other heavy metals (e.g., Catsup, whd). We validated several of these candidate genes with RNAi suggesting they contribute to variation in adult copper resistance. Our study illuminates the interconnected roles that allelic and expression variation, organism life stage, and behavior play in copper resistance, allowing a deeper understanding of the diverse mechanisms through which metal pollution can negatively impact organisms.

The molecular architecture of Drosophila melanogaster defense against Beauveria bassiana explored through evolve and resequence and quantitative trait locus mapping.

Little is known about the genetic architecture of antifungal immunity in natural populations. Using two population genetic approaches, quantitative trait locus (QTL) mapping and evolve and resequence (E&R), we explored D. melanogaster immune defense against infection with the fungus Beauveria bassiana. The immune defense was highly variable both in the recombinant inbred lines from the Drosophila Synthetic Population Resource used for our QTL mapping and in the synthetic outbred populations used in our E&R study. Survivorship of infection improved dramatically over just 10 generations in the E&R study, and continued to increase for an additional nine generations, revealing a trade-off with uninfected longevity. Populations selected for increased defense against B. bassiana evolved cross resistance to a second, distinct B. bassiana strain but not to bacterial pathogens. The QTL mapping study revealed that sexual dimorphism in defense depends on host genotype, and the E&R study indicated that sexual dimorphism also depends on the specific pathogen to which the host is exposed. Both the QTL mapping and E&R experiments generated lists of potentially causal candidate genes, although these lists were nonoverlapping.

Dissecting the Genetic Basis of Variation in Drosophila Sleep Using a Multiparental QTL Mapping Resource.

There is considerable variation in sleep duration, timing and quality in human populations, and sleep dysregulation has been implicated as a risk factor for a range of health problems. Human sleep traits are known to be regulated by genetic factors, but also by an array of environmental and social factors. These uncontrolled, non-genetic effects complicate powerful identification of the loci contributing to sleep directly in humans. The model system, Drosophila melanogaster, exhibits a behavior that shows the hallmarks of mammalian sleep, and here we use a multitiered approach, encompassing high-resolution QTL mapping, expression QTL data, and functional validation with RNAi to investigate the genetic basis of sleep under highly controlled environmental conditions. We measured a battery of sleep phenotypes in >750 genotypes derived from a multiparental mapping panel and identified several, modest-effect QTL contributing to natural variation for sleep. Merging sleep QTL data with a large head transcriptome eQTL mapping dataset from the same population allowed us to refine the list of plausible candidate causative sleep loci. This set includes genes with previously characterized effects on sleep and circadian rhythms, in addition to novel candidates. Finally, we employed adult, nervous system-specific RNAi on the Dopa decarboxylase, dyschronic, and timeless genes, finding significant effects on sleep phenotypes for all three. The genes we resolve are strong candidates to harbor causative, regulatory variation contributing to sleep.

A naturally-occurring 22-bp coding deletion in Ugt86Dd reduces nicotine resistance in Drosophila melanogaster.

OBJECTIVE: Segregating genetic variants contribute to the response to toxic, xenobiotic compounds, and identifying these causative sites can help describe the mechanisms underlying metabolism of toxic compounds. In previous work we implicated the detoxification gene Ugt86Dd in the genetic control of larval nicotine resistance in Drosophila melanogaster. Furthermore, we suggested that a naturally-occurring 22-bp deletion that leads to a stop codon in exon 2 of the gene markedly reduces resistance. Here we use homology directed CRISPR/Cas9 gene editing to specifically test this hypothesis. RESULTS: We edited chromosome three from an inbred strain named A4 which carries the insertion allele at Ugt86Dd, successfully generated four alleles carrying the 22-bp Ugt86Dd deletion, and substituted edited chromosomes back into the A4 background. The original A4 strain, and an un-edited control strain in the same A4 background, show no significant difference in egg-to-adult or larva-to-adult viability on either control media or nicotine-supplemented media, and only slightly delayed development in nicotine media. However, strains carrying the 22-bp deletion showed reduced viability in nicotine conditions, and significantly longer development. Our data strongly suggest that the naturally-occurring 22-bp insertion/deletion event in Ugt86Dd directly impacts variation in nicotine resistance in D. melanogaster.

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.

Lead Modulates trans- and cis-Expression Quantitative Trait Loci (eQTLs) in Drosophila melanogaster Heads.

Lead exposure has long been one of the most important topics in global public health because it is a potent developmental neurotoxin. Here, an eQTL analysis, which is the genome-wide association analysis of genetic variants with gene expression, was performed. In this analysis, the male heads of 79 Drosophila melanogaster inbred lines from Drosophila Synthetic Population Resource (DSPR) were treated with or without developmental exposure, from hatching to adults, to 250 µM lead acetate [Pb(C2H3O2)2]. The goal was to identify genomic intervals that influence the gene-expression response to lead. After detecting 1798 cis-eQTLs and performing an initial trans-eQTL analysis, we focused our analysis on lead-sensitive "trans-eQTL hotspots," defined as genomic regions that are associated with a cluster of genes in a lead-dependent manner. We noticed that the genes associated with one of the 14 detected trans-eQTL hotspots, Chr 2L: 6,250,000 could be roughly divided into two groups based on their differential expression profile patterns and different categories of function. This trans-eQTL hotspot validates one identified in a previous study using different recombinant inbred lines. The expression of all the associated genes in the trans-eQTL hotspot was visualized with hierarchical clustering analysis. Besides the overall expression profile patterns, the heatmap displayed the segregation of differential parental genetic contributions. This suggested that trans-regulatory regions with different genetic contributions from the parental lines have significantly different expression changes after lead exposure. We believe this study confirms our earlier study, and provides important insights to unravel the genetic variation in lead susceptibility in Drosophila model.

The Beavis Effect in Next-Generation Mapping Panels in Drosophila melanogaster.

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).

Identification of Splicing Quantitative Trait Loci (sQTL) in Drosophila melanogaster with Developmental Lead (Pb2+) Exposure.

Lead (Pb) poisoning has been a major public health issue globally and the recent Flint water crisis has drawn nation-wide attention to its effects. To better understand how lead plays a role as a neurotoxin, we utilized the Drosophila melanogaster model to study the genetic effects of lead exposure during development and identified lead-responsive genes. In our previous studies, we have successfully identified hundreds of lead-responsive expression QTLs (eQTLs) by using RNA-seq analysis on heads collected from the Drosophila Synthetic Population Resource. Cis-eQTLs, also known as allele-specific expression (ASE) polymorphisms, are generally single-nucleotide polymorphisms in the promoter regions of genes that affect expression of the gene, such as by inhibiting the binding of transcription factors. Trans-eQTLs are genes that regulate mRNA levels for many genes, and are generally thought to be SNPs in trans-acting transcription or translation factors. In this study, we focused our attention on alternative splicing events that are affected by lead exposure. Splicing QTLs (sQTLs), which can be caused by SNPs that alter splicing or alternative splicing (AS), such as by changing the sequence-specific binding affinity of splicing factors to the pre-mRNA. We applied two methods in search for sQTLs by using RNA-seq data from control and lead-exposed w1118Drosophila heads. First, we used the fraction of reads in a gene that falls in each exon as the phenotype. Second, we directly compared the transcript counts among the various splicing isoforms as the phenotype. Among the 1,236 potential Pb-responsive sQTLs (p < 0.0001, FDR < 0.39), mostly cis-sQTLs, one of the most distinct genes is Dscam1 (Down Syndrome Cell Adhesion Molecule), which has over 30,000 potential alternative splicing isoforms. We have also identified a candidate Pb-responsive trans-sQTL hotspot that appears to regulate 129 genes that are enriched in the "cation channel" gene ontology category, suggesting a model in which alternative splicing of these channels might lead to an increase in the elimination of Pb2+ from the neurons encoding these channels. To our knowledge, this is the first paper that uses sQTL analyses to understand the neurotoxicology of an environmental toxin in any organism, and the first reported discovery of a candidate trans-sQTL hotspot.

Modeling X-linked ancestral origins in multiparental populations.

The models for the mosaic structure of an individual's genome from multiparental populations have been developed primarily for autosomes, whereas X chromosomes receive very little attention. In this paper, we extend our previous approach to model ancestral origin processes along two X chromosomes in a mapping population, which is necessary for developing hidden Markov models in the reconstruction of ancestry blocks for X-linked quantitative trait locus mapping. The model accounts for the joint recombination pattern, the asymmetry between maternally and paternally derived X chromosomes, and the finiteness of population size. The model can be applied to various mapping populations such as the advanced intercross lines (AIL), the Collaborative Cross (CC), the heterogeneous stock (HS), the Diversity Outcross (DO), and the Drosophila synthetic population resource (DSPR). We further derive the map expansion, density (per Morgan) of recombination breakpoints, in advanced intercross populations with L inbred founders under the limit of an infinitely large population size. The analytic results show that for X chromosomes the genetic map expands linearly at a rate (per generation) of two-thirds times 1 - 10/(9L) for the AIL, and at a rate of two-thirds times 1 - 1/L for the DO and the HS, whereas for autosomes the map expands at a rate of 1 - 1/L for the AIL, the DO, and the HS.

Fine-mapping nicotine resistance loci in Drosophila using a multiparent advanced generation inter-cross population.

Animals in nature are frequently challenged by toxic compounds, from those that occur naturally in plants as a defense against herbivory, to pesticides used to protect crops. On exposure to such xenobiotic substances, animals mount a transcriptional response, generating detoxification enzymes and transporters that metabolize and remove the toxin. Genetic variation in this response can lead to variation in the susceptibility of different genotypes to the toxic effects of a given xenobiotic. Here we use Drosophila melanogaster to dissect the genetic basis of larval resistance to nicotine, a common plant defense chemical and widely used addictive drug in humans. We identified quantitative trait loci (QTL) for the trait using the DSPR (Drosophila Synthetic Population Resource), a panel of multiparental advanced intercross lines. Mapped QTL collectively explain 68.4% of the broad-sense heritability for nicotine resistance. The two largest-effect loci-contributing 50.3 and 8.5% to the genetic variation-map to short regions encompassing members of classic detoxification gene families. The largest QTL resides over a cluster of ten UDP-glucuronosyltransferase (UGT) genes, while the next largest QTL harbors a pair of cytochrome P450 genes. Using RNAseq we measured gene expression in a pair of DSPR founders predicted to harbor different alleles at both QTL and showed that Ugt86Dd, Cyp28d1, and Cyp28d2 had significantly higher expression in the founder carrying the allele conferring greater resistance. These genes are very strong candidates to harbor causative, regulatory polymorphisms that explain a large fraction of the genetic variation in larval nicotine resistance in the DSPR.