Identifying Loci Contributing to Natural Variation in Xenobiotic Resistance in Drosophila

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.

Using Drosophila to identify naturally occurring genetic modifiers of amyloid beta 42- and tau-induced toxicity

Alzheimer's disease is characterized by 2 pathological proteins, amyloid beta 42 and tau. The majority of Alzheimer's disease cases in the population are sporadic and late-onset Alzheimer's disease, which exhibits high levels of heritability. While several genetic risk factors for late-onset Alzheimer's disease have been identified and replicated in independent studies, including the ApoE ε4 allele, the great majority of the heritability of late-onset Alzheimer's disease remains unexplained, likely due to the aggregate effects of a very large number of genes with small effect size, as well as to biases in sample collection and statistical approaches. Here, we present an unbiased forward genetic screen in Drosophila looking for naturally occurring modifiers of amyloid beta 42- and tau-induced ommatidial degeneration. Our results identify 14 significant SNPs, which map to 12 potential genes in 8 unique genomic regions. Our hits that are significant after genome-wide correction identify genes involved in neuronal development, signal transduction, and organismal development. Looking more broadly at suggestive hits (P < 10-5), we see significant enrichment in genes associated with neurogenesis, development, and growth as well as significant enrichment in genes whose orthologs have been identified as significantly or suggestively associated with Alzheimer's disease in human GWAS studies. These latter genes include ones whose orthologs are in close proximity to regions in the human genome that are associated with Alzheimer's disease, but where a causal gene has not been identified. Together, our results illustrate the potential for complementary and convergent evidence provided through multitrait GWAS in Drosophila to supplement and inform human studies, helping to identify the remaining heritability and novel modifiers of complex diseases.

The genetic basis of variation in immune defense against Lysinibacillus fusiformis infection in Drosophila melanogaster

The genetic causes of phenotypic variation often differ depending on the population examined, particularly if the populations were founded by relatively small numbers of genotypes. Similarly, the genetic causes of phenotypic variation among similar traits (resistance to different xenobiotic compounds or pathogens) may also be completely different or only partially overlapping. Differences in genetic causes for variation in the same trait among populations suggests context dependence for how selection acts on those traits. Similarities in the genetic causes of variation for different traits, on the other hand, suggests pleiotropy which would also influence how natural selection shapes variation in a trait. We characterized immune defense against a natural Drosophila pathogen, the Gram-positive bacterium Lysinibacillus fusiformis, in three different populations and found almost no overlap in the genetic architecture of variation in survival post infection. However, when comparing our results to a similar experiment with the fungal pathogen, B. bassiana, we found a convincing shared QTL peak for both pathogens. This peak contains the Bomanin cluster of Drosophila immune effectors. Loss of function mutants and RNAi knockdown experiments confirms a role of some of these genes in immune defense against both pathogens. This suggests that natural selection may act on the entire cluster of Bomanin genes (and the linked region under the QTL) or specific peptides for specific pathogens.

The genome sequence of the Neotropical brown stink bug, Euschistus heros provides insights into population structure, demographic history and signatures of adaptation

The Neotropical brown stink bug, Euschistus heros, is a major pest of soybean in South America. The importance of E. heros as a pest has grown significantly in recent times due to increases in its abundance and range, and the evolution of insecticide resistance. Recent work has begun to examine the genetic diversity, population structure, and genetic mechanisms of insecticide resistance in E. heros. However, to date, investigation of these topics has been hampered by a lack of genomic resources for this species. Here we address this need by assembling a high-quality draft genome for E. heros. We used a combination of short and long read sequencing to assemble an E. heros genome of 1.4 Gb comprising 906 contigs with a contig N50 of 3.5 MB. We leveraged this new genomic resource, in combination with genotyping by sequencing, to explore genetic diversity in populations of this species in Brazil and identify genetic loci in the genome which are under selection. Our genome-wide analyses, confirm that there are two populations of E. heros co-occurring in different geographical regions in Brazil, and that, in certain regions of the country these populations are hybridizing. We identify several regions of the genome as under selection, including markers associated with putative insecticide resistance genes. Taken together, the new genomic resources generated in this study will accelerate research into fundamental aspects of stinkbug biology and applied aspects relating to the sustainable control of a highly damaging crop pest.

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.

Xenobiotic responses in insects

Insects have evolved a powerful detoxification system to protect themselves against environmental and anthropogenic xenobiotics including pesticides and nanoparticles. The resulting tolerance to insecticides is an immense problem in agriculture. In this study, we summarize advances in our understanding of insect xenobiotic responses: the detoxification strategies and the regulation mechanisms against xenobiotics including nanoparticles, the problem of response specificity and the potential usefulness of this study field for an elaborate pest management. In particular, we highlight that versatility of the detoxification system relies on the relatively unspecific recognition of a broad range of potential toxic substances that trigger either of various canonical xenobiotic responses signaling pathways, including CncC/Keap1, HR96, AHR/ARNT, GPCR, and MAPK/CREB. However, it has emerged that the actual response to an inducer may nevertheless be specific. There are two nonexclusive possibilities that may explain response specificity: (1) differential cross-talk between the known pathways and (2) additional, yet unidentified regulators and pathways of detoxification. Hence, a deeper and broader understanding of the regulation mechanisms of xenobiotic response in insects in the future might facilitate the development and application of highly efficient and environmentally friendly pest control methods, allowing us to face the challenge of the world population growth.

Trade-offs between cost of ingestion and rate of intake drive defensive toxin use

Animals that ingest toxins can become unpalatable and even toxic to predators and parasites through toxin sequestration. Because most animals rapidly eliminate toxins to survive their ingestion, it is unclear how populations transition from susceptibility and toxin elimination to tolerance and accumulation as chemical defence emerges. Studies of chemical defence have generally focused on species with active toxin sequestration and target-site insensitivity mutations or toxin-binding proteins that permit survival without necessitating toxin elimination. Here, we investigate whether animals that presumably rely on toxin elimination for survival can use ingested toxins for defence. We use the A4 and A3 Drosophila melanogaster fly strains from the Drosophila Synthetic Population Resource (DSPR), which respectively possess high and low metabolic nicotine resistance among DSPR fly lines. We find that ingesting nicotine increased A4 but not A3 fly survival against Leptopilina heterotoma wasp parasitism. Further, we find that despite possessing genetic variants that enhance toxin elimination, A4 flies accrued more nicotine than A3 individuals, likely by consuming more medium. Our results suggest that enhanced toxin metabolism can allow greater toxin intake by offsetting the cost of toxin ingestion. Passive toxin accumulation that accompanies increased toxin intake may underlie the early origins of chemical defence.

A Population Genomic Assessment of Three Decades of Evolution in a Natural Drosophila Population

Population genetics seeks to illuminate the forces shaping genetic variation, often based on a single snapshot of genomic variation. However, utilizing multiple sampling times to study changes in allele frequencies can help clarify the relative roles of neutral and non-neutral forces on short time scales. This study compares whole-genome sequence variation of recently collected natural population samples of Drosophila melanogaster against a collection made approximately 35 years prior from the same locality—encompassing roughly 500 generations of evolution. The allele frequency changes between these time points would suggest a relatively small local effective population size on the order of 10,000, significantly smaller than the global effective population size of the species. Some loci display stronger allele frequency changes than would be expected anywhere in the genome under neutrality—most notably the tandem paralogs Cyp6a17 and Cyp6a23, which are impacted by structural variation associated with resistance to pyrethroid insecticides. We find a genome-wide excess of outliers for high genetic differentiation between old and new samples, but a larger number of adaptation targets may have affected SNP-level differentiation versus window differentiation. We also find evidence for strengthening latitudinal allele frequency clines: northern-associated alleles have increased in frequency by an average of nearly 2.5% at SNPs previously identified as clinal outliers, but no such pattern is observed at random SNPs. This project underscores the scientific potential of using multiple sampling time points to investigate how evolution operates in natural populations, by quantifying how genetic variation has changed over ecologically relevant timescales.

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.

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Canalization and Robustness in Human Genetics and Disease

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

Genomic and transcriptomic analyses in Drosophila suggest that the ecdysteroid kinase-like (EcKL) gene family encodes the 'detoxification-by-phosphorylation' enzymes of insects

Phosphorylation is a phase II detoxification reaction that, among animals, occurs near exclusively in insects, but the enzymes responsible have never been cloned or otherwise identified. We propose the hypothesis that members of the arthropod-specific ecdysteroid kinase-like (EcKL) gene family encode detoxicative kinases. To test this hypothesis, we annotated the EcKL gene family in 12 species of Drosophila and explored their evolution within the genus. Many ancestral EcKL clades are evolutionarily unstable and have experienced repeated gene gain and loss events, while others are conserved as single-copy orthologs. Leveraging multiple published gene expression datasets from D. melanogaster, and using the cytochrome P450s-a classical detoxification family-as a test case, we demonstrate relationships between xenobiotic induction, detoxification tissue-enriched expression and evolutionary instability in the EcKLs and the P450s. We devised a systematic method for identifying candidate detoxification genes in large gene families that is concordant with experimentally determined functions of P450 genes in D. melanogaster. Applying this method to the EcKLs suggested a significant proportion of these genes play roles in detoxification, and that the EcKLs may constitute a detoxification gene family in insects. Additionally, we estimate that between 11 and 16 uncharacterised D. melanogaster P450s are strong detoxification candidates. Lastly, we also found previously unreported genomic and transcriptomic variation in a number of EcKLs and P450s associated with toxic stress phenotypes using a targeted phenome-wide association study (PheWAS) approach in D. melanogaster, presenting multiple future avenues of research for detoxification genetics in this species.

Phenotypic Responses to and Genetic Architecture of Sterility Following Exposure to Sub-Lethal Temperature During Development

Thermal tolerance range, based on temperatures that result in incapacitating effects, influences species’ distributions and has been used to predict species’ response to increasing temperature. Reproductive performance may also be negatively affected at less extreme temperatures, but such sublethal heat-induced sterility has been relatively ignored in studies addressing the potential effects of, and ability of species’ to respond to, predicted climate warming. The few studies examining the link between increased temperature and reproductive performance typically focus on adults, although effects can vary between life history stages. Here we assessed how sublethal heat stress during development impacted subsequent adult fertility and its plasticity, both of which can provide the raw material for evolutionary responses to increased temperature. We quantified phenotypic and genetic variation in fertility of Drosophila melanogaster reared at standardized densities in three temperatures (25, 27, and 29°C) from a set of lines of the Drosophila Genetic Reference Panel (DGRP). We found little phenotypic variation at the two lower temperatures with more variation at the highest temperature and for plasticity. Males were more affected than females. Despite reasonably large broad-sense heritabilities, a genome-wide association study found little evidence for additive genetic variance and no genetic variants were robustly linked with reproductive performance at specific temperatures or for phenotypic plasticity. We compared results on heat-induced male sterility with other DGRP results on relevant fitness traits measured after abiotic stress and found an association between male susceptibility to sterility and male lifespan reduction following oxidative stress. Our results suggest that sublethal stress during development has profound negative consequences on male adult reproduction, but despite phenotypic variation in a population for this response, there is limited evolutionary potential, either through adaptation to a specific developmental temperature or plasticity in response to developmental heat-induced sterility.

Macdonald S. 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.

Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity

There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.

Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster

Learning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used the Drosophila synthetic population resource (DSPR), a multiparent mapping resource in the model system Drosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a "heat box" to learn to remain on one side of a chamber (place learning) and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for ~49 000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA-Seq on pooled samples of seven high performing and seven low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance.

Determinants of QTL Mapping Power in the Realized Collaborative Cross

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

Cis- and trans-acting variants contribute to survivorship in a naïve Drosophila melanogaster population exposed to ryanoid insecticides

Around the world insecticides are being deregistered and banned, as their environmental costs are deemed too great or their efficacy against pest insects is reduced through the evolution of insecticide resistance. With the introduction of replacement insecticides comes the responsibility to assess the way new insecticides perturb various levels of biological systems, from insect physiology to ecosystems. We used a systems genetics approach to identify genetic variants affecting survivorship of Drosophila melanogaster exposed to chlorantraniliprole. The study population was completely naïve to this insecticide chemistry and yet we find associations with variants in neuromuscular genes and coregulated detoxification genes. We predict that these variants will increase in populations of this “sentinel species” as these insecticides are applied in the environment.

Insecticide resistance is a paradigm of microevolution, and insecticides are responsible for the strongest cases of recent selection in the genome of Drosophila melanogaster. Here we use a naïve population and a novel insecticide class to examine the ab initio genetic architecture of a potential selective response. Genome-wide association studies (GWAS) of chlorantraniliprole susceptibility reveal variation in a gene of major effect, Stretchin Myosin light chain kinase (Strn-Mlck), which we validate with linkage mapping and transgenic manipulation of gene expression. We propose that allelic variation in Strn-Mlck alters sensitivity to the calcium depletion attributable to chlorantraniliprole’s mode of action. GWAS also reveal a network of genes involved in neuromuscular biology. In contrast, phenotype to transcriptome associations identify differences in constitutive levels of multiple transcripts regulated by cnc, the homolog of mammalian Nrf2. This suggests that genetic variation acts in trans to regulate multiple metabolic enzymes in this pathway. The most outstanding association is with the transcription level of Cyp12d1 which is also affected in cis by copy number variation. Transgenic overexpression of Cyp12d1 reduces susceptibility to both chlorantraniliprole and the closely related insecticide cyantraniliprole. This systems genetics study reveals multiple allelic variants segregating at intermediate frequency in a population that is completely naïve to this new insecticide chemistry and it foreshadows a selective response among natural populations to these chemicals.

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.

What can genetic association panels tell us about evolutionary processes in insects?

If we are to fully comprehend the evolution of insect diversity at a genomic level we need to understand how natural selection can alter genetically encoded characters within populations. Genetic association panels have the potential to be standard bearers in this endeavour. They enable the mapping of phenotypes to genotypes at unprecedented resolution while simultaneously providing population genomic samples that can be interrogated for the tell-tale signs of selection. Analyses of these panels promise to elucidate the entanglement of gene ontologies, pathways, developmental processes and evolutionary constraints, and inform how these are shaped by adaptation.

Shared Genomic Regions Underlie Natural Variation in Diverse Toxin Responses

Phenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis often find that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins, and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome substitution strains, and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation.

Changes in Neuronal Signaling and Cell Stress Response Pathways are Associated with a Multigenic Response of Drosophila melanogaster to DDT Selection

The adaptation of insect populations to insecticidal control is a continual threat to human health and sustainable agricultural practices, but many complex genomic mechanisms involved in this adaption remain poorly understood. This study applied a systems approach to investigate the interconnections between structural and functional variance in response to dichlorodiphenyltrichloroethane (DDT) within the Drosophila melanogaster strain 91-R. Directional selection in 6 selective sweeps coincided with constitutive gene expression differences in DDT resistant flies, including the most highly upregulated transcript, Unc-115 b, which plays a central role in axon guidance, and the most highly downregulated transcript, the angiopoietin-like CG31832, which is involved in directing vascular branching and dendrite outgrowth but likely may be under trans-regulatory control. Direct functions and protein–protein interactions mediated by differentially expressed transcripts control changes in cell migration, signal transduction, and gene regulatory cascades that impact the nervous system. Although changes to cellular stress response pathways involve 8 different cytochrome P450s, stress response, and apoptosis is controlled by a multifacetted regulatory mechanism. These data demonstrate that DDT selection in 91-R may have resulted in genome-wide adaptations that impacts genetic and signal transduction pathways that converge to modify stress response, cell survival, and neurological functions. This study implicates the involvement of a multigenic mechanism in the adaptation to a chemical insecticide, which impact interconnected regulatory cascades. We propose that DDT selection within 91-R might act systemically, wherein pathway interactions function to reinforce the epistatic effects of individual adaptive changes on an additive or nonadditive basis.

The Sleep Inbred Panel, a Collection of Inbred Drosophila melanogaster with Extreme Long and Short Sleep Duration

Understanding how genomic variation causes differences in observable phenotypes remains a major challenge in biology. It is difficult to trace the sequence of events originating from genomic variants to changes in transcriptional responses or protein modifications. Ideally, one would conduct experiments with individuals that are at either extreme of the trait of interest, but such resources are often not available. Further, advances in genome editing will enable testing of candidate polymorphisms individually and in combination. Here we have created a resource for the study of sleep with 39 inbred lines of Drosophila-the Sleep Inbred Panel (SIP). SIP lines have stable long- and short-sleeping phenotypes developed from naturally occurring polymorphisms. These lines are fully sequenced, enabling more accurate targeting for genome editing and transgenic constructs. This panel facilitates the study of intermediate transcriptional and proteomic correlates of sleep, and supports genome editing studies to verify polymorphisms associated with sleep duration.

Gene Regulatory Variation in Drosophila melanogaster Renal Tissue

Genetic variation influencing levels of gene expression is abundant in natural populations, and may exert its effects through complex mechanisms that depend on an organism's genetic background and the tissue in which expression is measured. We investigated natural variation in gene expression in the Malpighian tubules of three inbred Drosophila melanogaster strains and their F₁ hybrids. One of the strains was from a population in the species' ancestral range (Zambia), while the other two were from a more recently derived population (Sweden). Although closely related, the two Swedish strains differed greatly in terms of their expression inheritance when hybridized with the Zambian strain, with one Swedish strain showing a large excess of genes with recessive expression inheritance, as well as a large number of genes with overdominant inheritance. Although most expression variation could be attributed to trans-regulation, there were ∼200 genes that showed allele-specific expression differences in each of the between-population hybrids, indicating that cis-regulation contributes as well. The cis-regulated genes were enriched with cytochrome P450 genes, and the upstream regions of six of these genes were incorporated into transgenic reporter gene constructs to test their effects on expression. Differential expression was observed for five of the six reporter genes in the Malpighian tubule, suggesting that a large proportion of cis-regulatory variation lies directly upstream of the affected gene. In most cases, the differential expression was specific to the Malpighian tubule or greater in this tissue than in the rest of the body, highlighting the importance of single-tissue studies of gene expression variation.

Dynamic miRNA-mRNA regulations are essential for maintaining Drosophila immune homeostasis during Micrococcus luteus infection

Pathogen bacteria infections can lead to dynamic changes of microRNA (miRNA) and mRNA expression profiles, which may control synergistically the outcome of immune responses. To reveal the role of dynamic miRNA-mRNA regulation in Drosophila innate immune responses, we have detailedly analyzed the paired miRNA and mRNA expression profiles at three time points during Drosophila adult males with Micrococcus luteus (M. luteus) infection using RNA- and small RNA-seq data. Our results demonstrate that differentially expressed miRNAs and mRNAs represent extensively dynamic changes over three time points during Drosophila with M. luteus infection. The pathway enrichment analysis indicates that differentially expressed genes are involved in diverse signaling pathways, including Toll and Imd as well as orther signaling pathways at three time points during Drosophila with M. luteus infection. Remarkably, the dynamic change of miRNA expression is delayed by compared to mRNA expression change over three time points, implying that the "time" parameter should be considered when the function of miRNA/mRNA is further studied. In particular, the dynamic miRNA-mRNA regulatory networks have shown that miRNAs may synergistically regulate gene expressions of different signaling pathways to promote or inhibit innate immune responses and maintain homeostasis in Drosophila, and some new regulators involved in Drosophila innate immune response have been identified. Our findings strongly suggest that miRNA regulation is a key mechanism involved in fine-tuning cooperatively gene expressions of diverse signaling pathways to maintain innate immune response and homeostasis in Drosophila. Taken together, the present study reveals a novel role of dynamic miRNA-mRNA regulation in immune response to bacteria infection, and provides a new insight into the underlying molecular regulatory mechanism of Drosophila innate immune responses.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor ([Formula: see text]), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms.

Natural diversity facilitates the discovery of conserved chemotherapeutic response mechanisms

Organismal fitness depends on adaptation to complex niches where chemical compounds and pathogens are omnipresent. These stresses can lead to the fixation of alleles in both xenobiotic responses and proliferative signaling pathways that promote survival in these niches. However, both xenobiotic responses and proliferative pathways vary within and among species. For example, genetic differences can accumulate within populations because xenobiotic exposures are not constant and selection is variable. Additionally, neutral genetic variation can accumulate in conserved proliferative pathway genes because these systems are robust to genetic perturbations given their essential roles in normal cell-fate specification. For these reasons, sensitizing mutations or chemical perturbations can disrupt pathways and reveal cryptic variation. With this fundamental view of how organisms respond to cytotoxic compounds and cryptic variation in conserved signaling pathways, it is not surprising that human patients have highly variable responses to chemotherapeutic compounds. These different responses result in the low FDA-approval rates for chemotherapeutics and underscore the need for new approaches to understand these diseases and therapeutic interventions. Model organisms, especially the classic invertebrate systems of Caenorhabditis elegans and Drosophila melanogaster, can be used to combine studies of natural variation across populations with responses to both xenobiotic compounds and chemotherapeutics targeted to conserved proliferative signaling pathways.

Strong epistatic and additive effects of linked candidate SNPs for Drosophila pigmentation have implications for analysis of genome-wide association studies results

Background

The mapping resolution of genome-wide association studies (GWAS) is limited by historic recombination events and effects are often assigned to haplotype blocks rather than individual SNPs. It is not clear how many of the SNPs in the block, and which ones, are causative. Drosophila pigmentation is a powerful model to dissect the genetic basis of intra-specific and inter-specific phenotypic variation. Three tightly linked SNPs in the t-MSE enhancer have been identified in three D. melanogaster populations as major contributors to female abdominal pigmentation. This enhancer controls the expression of the pigmentation gene tan (t) in the abdominal epidermis. Two of the three SNPs were confirmed in an independent study using the D. melanogaster Genetic Reference Panel established from a North American population.

Results

We determined the functional impact of SNP1, SNP2, and SNP3 using transgenic lines to test all possible haplotypes in vivo. We show that all three candidate SNPs contribute to female Drosophila abdominal pigmentation. Interestingly, only two SNPs agree with the effect predicted by GWAS; the third one goes in the opposite direction because of linkage disequilibrium between multiple functional SNPs. Our experimental design uncovered strong additive effects for the three SNPs, but we also found significant epistatic effects explaining up to 11% of the total variation.

Conclusions

Our results suggest that linked causal variants are important for the interpretation of GWAS and functional validation is needed to understand the genetic architecture of traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1262-7) contains supplementary material, which is available to authorized users.

Loci Contributing to Boric Acid Toxicity in Two Reference Populations of Drosophila melanogaster

Populations maintain considerable segregating variation in the response to toxic, xenobiotic compounds. To identify variants associated with resistance to boric acid, a commonly-used household insecticide with a poorly understood mechanism of action, we assayed thousands of individuals from hundreds of strains. Using the Drosophila Synthetic Population Resource (DSPR), a multi-parental population (MPP) of inbred genotypes, we mapped six QTL to short genomic regions containing few protein-coding genes (3–188), allowing us to identify plausible candidate genes underlying resistance to boric acid toxicity. One interval contains multiple genes from the cytochrome P450 family, and we show that ubiquitous RNAi of one of these genes, Cyp9b2, markedly reduces resistance to the toxin. Resistance to boric acid is positively correlated with caffeine resistance. The two phenotypes additionally share a pair of QTL, potentially suggesting a degree of pleiotropy in the genetic control of resistance to these two distinct xenobiotics. Finally, we screened the Drosophila Genetic Reference Panel (DGRP) in an attempt to identify sequence variants within mapped QTL that are associated with boric acid resistance. The approach was largely unsuccessful, with only one QTL showing any associations at QTL-specific 20% False Discovery Rate (FDR) thresholds. Nonetheless, these associations point to a potential candidate gene that can be targeted in future validation efforts. Although the mapping data resulting from the two reference populations do not clearly overlap, our work provides a starting point for further genetic dissection of the processes underlying boric acid toxicity in insects.

AS3MT-mediated tolerance to arsenic evolved by multiple independent horizontal gene transfers from bacteria to eukaryotes

Organisms have evolved the ability to tolerate toxic substances in their environments, often by producing metabolic enzymes that efficiently detoxify the toxicant. Inorganic arsenic is one of the most toxic and carcinogenic substances in the environment, but many organisms, including humans, metabolise inorganic arsenic to less toxic metabolites. This multistep process produces mono-, di-, and trimethylated arsenic metabolites, which the organism excretes. In humans, arsenite methyltransferase (AS3MT) appears to be the main metabolic enzyme that methylates arsenic. In this study, we examined the evolutionary origin of AS3MT and assessed the ability of different genotypes to produce methylated arsenic metabolites. Phylogenetic analysis suggests that multiple, independent horizontal gene transfers between different bacteria, and from bacteria to eukaryotes, increased tolerance to environmental arsenic during evolution. These findings are supported by the observation that genetic variation in AS3MT correlates with the capacity to methylate arsenic. Adaptation to arsenic thus serves as a model for how organisms evolve to survive under toxic conditions.