Systems genomics of metabolic phenotypes in wild-type Drosophila melanogaster

Mitonuclear interactions shape both direct and parental effects of diet on fitness and involve a SNP in mitoribosomal 16s rRNA

Nutrition is a primary determinant of health, but responses to nutrition vary with genotype. Epistasis between mitochondrial and nuclear genomes may cause some of this variation, but which mitochondrial loci and nutrients participate in complex gene-by-gene-by-diet interactions? Furthermore, it remains unknown whether mitonuclear epistasis is involved only in the immediate responses to changes in diet, or whether mitonuclear genotype might modulate sensitivity to variation in parental nutrition, to shape intergenerational fitness responses. Here, in Drosophila melanogaster, we show that mitonuclear epistasis shapes fitness responses to variation in dietary lipids and amino acids. We also show that mitonuclear genotype modulates the parental effect of dietary lipid and amino acid variation on offspring fitness. Effect sizes for the interactions between diet, mitogenotype, and nucleogenotype were equal to or greater than the main effect of diet for some traits, suggesting that dietary impacts cannot be understood without first accounting for these interactions. Associating phenotype to mtDNA variation in a subset of populations implicated a C/T polymorphism in mt:lrRNA, which encodes the 16S rRNA of the mitochondrial ribosome. This association suggests that directionally different responses to dietary changes can result from variants on mtDNA that do not change protein coding sequence, dependent on epistatic interactions with variation in the nuclear genome.

Natural alleles at the Doa locus underpin evolutionary changes in Drosophila lifespan and fecundity

'Evolve and resequence' (E&R) studies in Drosophila melanogaster have identified many candidate loci underlying the evolution of ageing and life history, but experiments that validate the effects of such candidates remain rare. In a recent E&R study we have identified several alleles of the LAMMER kinase Darkener of apricot (Doa) as candidates for evolutionary changes in lifespan and fecundity. Here, we use two complementary approaches to confirm a functional role of Doa in life-history evolution. First, we used transgenic RNAi to study the effects of Doa at the whole-gene level. Ubiquitous silencing of expression in adult flies reduced both lifespan and fecundity, indicating pleiotropic effects. Second, to characterize segregating variation at Doa, we examined four candidate single nucleotide polymorphisms (SNPs; Doa-1, -2, -3, -4) using a genetic association approach. Three candidate SNPs had effects that were qualitatively consistent with expectations based on our E&R study: Doa-2 pleiotropically affected both lifespan and late-life fecundity; Doa-1 affected lifespan (but not fecundity); and Doa-4 affected late-life fecundity (but not lifespan). Finally, the last candidate allele (Doa-3) also affected lifespan, but in the opposite direction from predicted.

Genetic variation of macronutrient tolerance in Drosophila melanogaster

Carbohydrates, proteins and lipids are essential nutrients to all animals; however, closely related species, populations, and individuals can display dramatic variation in diet. Here we explore the variation in macronutrient tolerance in Drosophila melanogaster using the Drosophila genetic reference panel, a collection of ~200 strains derived from a single natural population. Our study demonstrates that D. melanogaster, often considered a "dietary generalist", displays marked genetic variation in survival on different diets, notably on high-sugar diet. Our genetic analysis and functional validation identify several regulators of macronutrient tolerance, including CG10960/GLUT8, Pkn and Eip75B. We also demonstrate a role for the JNK pathway in sugar tolerance and de novo lipogenesis. Finally, we report a role for tailless, a conserved orphan nuclear hormone receptor, in regulating sugar metabolism via insulin-like peptide secretion and sugar-responsive CCHamide-2 expression. Our study provides support for the use of nutrigenomics in the development of personalized nutrition.

Phenotyping of Drosophila Melanogaster-A Nutritional Perspective

The model organism Drosophila melanogaster was increasingly applied in nutrition research in recent years. A range of methods are available for the phenotyping of D. melanogaster, which are outlined in the first part of this review. The methods include determinations of body weight, body composition, food intake, lifespan, locomotor activity, reproductive capacity and stress tolerance. In the second part, the practical application of the phenotyping of flies is demonstrated via a discussion of obese phenotypes in response to high-sugar diet (HSD) and high-fat diet (HFD) feeding. HSD feeding and HFD feeding are dietary interventions that lead to an increase in fat storage and affect carbohydrate-insulin homeostasis, lifespan, locomotor activity, reproductive capacity and stress tolerance. Furthermore, studies regarding the impacts of HSD and HFD on the transcriptome and metabolome of D. melanogaster are important for relating phenotypic changes to underlying molecular mechanisms. Overall, D. melanogaster was demonstrated to be a valuable model organism with which to examine the pathogeneses and underlying molecular mechanisms of common chronic metabolic diseases in a nutritional context.

Genome-wide Phenotypic RNAi Screen in the Drosophila Wing: Global Parameters

We have screened a collection of UAS-RNAi lines targeting 10,920 Drosophila protein-coding genes for phenotypes in the adult wing. We identified 3653 genes (33%) whose knockdown causes either larval/pupal lethality or a mutant phenotype affecting the formation of a normal wing. The most frequent phenotypes consist of changes in wing size, vein differentiation, and patterning, defects in the wing margin and in the apposition of the dorsal and ventral wing surfaces. We also defined 16 functional categories encompassing the most relevant aspect of each protein function and assigned each Drosophila gene to one of these functional groups. This allowed us to identify which mutant phenotypes are enriched within each functional group. Finally, we used previously published gene expression datasets to determine which genes are or are not expressed in the wing disc. Integrating expression, phenotypic and molecular information offers considerable precision to identify the relevant genes affecting wing formation and the biological processes regulated by them.

Physiological and metabolomic consequences of reduced expression of the Drosophila brummer triglyceride Lipase

Disruption of lipolysis has widespread effects on intermediary metabolism and organismal phenotypes. Defects in lipolysis can be modeled in Drosophila melanogaster through genetic manipulations of brummer (bmm), which encodes a triglyceride lipase orthologous to mammalian Adipose Triglyceride Lipase. RNAi-mediated knock-down of bmm in all tissues or metabolic specific tissues results in reduced locomotor activity, altered sleep patterns and reduced lifespan. Metabolomic analysis on flies in which bmm is downregulated reveals a marked reduction in medium chain fatty acids, long chain saturated fatty acids and long chain monounsaturated and polyunsaturated fatty acids, and an increase in diacylglycerol levels. Elevated carbohydrate metabolites and tricarboxylic acid intermediates indicate that impairment of fatty acid mobilization as an energy source may result in upregulation of compensatory carbohydrate catabolism. bmm downregulation also results in elevated levels of serotonin and dopamine neurotransmitters, possibly accounting for the impairment of locomotor activity and sleep patterns. Physiological phenotypes and metabolomic changes upon reduction of bmm expression show extensive sexual dimorphism. Altered metabolic states in the Drosophila model are relevant for understanding human metabolic disorders, since pathways of intermediary metabolism are conserved across phyla.

Prediction of complex phenotypes using the Drosophila melanogaster metabolome

Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.

Influence of Lab Adapted Natural Diet and Microbiota on Life History and Metabolic Phenotype of Drosophila melanogaster

Symbiotic microbiota can help its host to overcome nutritional challenges, which is consistent with a holobiont theory of evolution. Our project investigated the effects produced by the microbiota community, acquired from the environment and horizontal transfer, on metabolic traits related to obesity. The study applied a novel approach of raising Drosophila melanogaster, from ten wild-derived genetic lines on naturally fermented peaches, preserving genuine microbial conditions. Larvae raised on the natural and standard lab diets were significantly different in every tested phenotype. Frozen peach food provided nutritional conditions similar to the natural ones and preserved key microbial taxa necessary for survival and development. On the peach diet, the presence of parental microbiota increased the weight and development rate. Larvae raised on each tested diet formed microbial communities distinct from each other. The effect that individual microbial taxa produced on the host varied significantly with changing environmental and genetic conditions, occasionally to the degree of opposite correlations.

Construction and Analysis of Human Diseases and Metabolites Network

The relationship between aberrant metabolism and the initiation and progression of diseases has gained considerable attention in recent years. To gain insights into the global relationship between diseases and metabolites, here we constructed a human diseases-metabolites network (HDMN). Through analyses based on network biology, the metabolites associated with the same disorder tend to participate in the same metabolic pathway or cascade. In addition, the shortest distance between disease-related metabolites was shorter than that of all metabolites in the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic network. Both disease and metabolite nodes in the HDMN displayed slight clustering phenomenon, resulting in functional modules. Furthermore, a significant positive correlation was observed between the degree of metabolites and the proportion of disease-related metabolites in the KEGG metabolic network. We also found that the average degree of disease metabolites is larger than that of all metabolites. Depicting a comprehensive characteristic of HDMN could provide great insights into understanding the global relationship between disease and metabolites.

The metabolome as a link in the genotype-phenotype map for peroxide resistance in the fruit fly, Drosophila melanogaster

BACKGROUND

Genetic association studies that seek to explain the inheritance of complex traits typically fail to explain a majority of the heritability of the trait under study. Thus, we are left with a gap in the map from genotype to phenotype. Several approaches have been used to fill this gap, including those that attempt to map endophenotype such as the transcriptome, proteome or metabolome, that underlie complex traits. Here we used metabolomics to explore the nature of genetic variation for hydrogen peroxide (H2O2) resistance in the sequenced inbred Drosophila Genetic Reference Panel (DGRP).

RESULTS

We first studied genetic variation for H2O2 resistance in 179 DGRP lines and along with identifying the insulin signaling modulator u-shaped and several regulators of feeding behavior, we estimate that a substantial amount of phenotypic variation can be explained by a polygenic model of genetic variation. We then profiled a portion of the aqueous metabolome in subsets of eight 'high resistance' lines and eight 'low resistance' lines. We used these lines to represent collections of genotypes that were either resistant or sensitive to the stressor, effectively modeling a discrete trait. Across the range of genotypes in both populations, flies exhibited surprising consistency in their metabolomic signature of resistance. Importantly, the resistance phenotype of these flies was more easily distinguished by their metabolome profiles than by their genotypes. Furthermore, we found a metabolic response to H2O2 in sensitive, but not in resistant genotypes. Metabolomic data further implicated at least two pathways, glycogen and folate metabolism, as determinants of sensitivity to H2O2. We also discovered a confounding effect of feeding behavior on assays involving supplemented food.

CONCLUSIONS

This work suggests that the metabolome can be a point of convergence for genetic variation influencing complex traits, and can efficiently elucidate mechanisms underlying trait variation.

Tissue-specific analysis of lipid species in Drosophila during overnutrition by UHPLC-MS/MS and MALDI-MSI

Diets high in calories can be used to model metabolic diseases, including obesity and its associated comorbidities, in animals. Drosophila melanogaster fed high-sugar diets (HSDs) exhibit complications of human obesity including hyperglycemia, hyperlipidemia, insulin resistance, cardiomyopathy, increased susceptibility to infection, and reduced longevity. We hypothesize that lipid storage in the high-sugar-fed fly's fat body (FB) reaches a maximum capacity, resulting in the accumulation of toxic lipids in other tissues or lipotoxicity. We took two approaches to characterize tissue-specific lipotoxicity. Ultra-HPLC-MS/MS and MALDI-MS imaging enabled spatial and temporal localization of lipid species in the FB, heart, and hemolymph. Substituent chain length was diet dependent, with fewer odd chain esterified FAs on HSDs in all sample types. By contrast, dietary effects on double bond content differed among organs, consistent with a model where some substituent pools are shared and others are spatially restricted. Both di- and triglycerides increased on HSDs in all sample types, similar to observations in obese humans. Interestingly, there were dramatic effects of sugar feeding on lipid ethers, which have not been previously associated with lipotoxicity. Taken together, we have identified candidate endocrine mechanisms and molecular targets that may be involved in metabolic disease and lipotoxicity.

Systems genetics of the Drosophila metabolome

How effects of DNA sequence variants are transmitted through intermediate endophenotypes to modulate organismal traits remains a central question in quantitative genetics. This problem can be addressed through a systems approach in a population in which genetic polymorphisms, gene expression traits, metabolites, and complex phenotypes can be evaluated on the same genotypes. Here, we focused on the metabolome, which represents the most proximal link between genetic variation and organismal phenotype, and quantified metabolite levels in 40 lines of the Drosophila melanogaster Genetic Reference Panel. We identified sex-specific modules of genetically correlated metabolites and constructed networks that integrate DNA sequence variation and variation in gene expression with variation in metabolites and organismal traits, including starvation stress resistance and male aggression. Finally, we asked to what extent SNPs and metabolites can predict trait phenotypes and generated trait- and sex-specific prediction models that provide novel insights about the metabolomic underpinnings of complex phenotypes.

Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

Background

Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear.

Results

To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2471 genes) were significantly differentially expressed for the effect of diet, and 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, P_adj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (FDR P_adj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing many cellular and nuclear processes (Fisher exact test, P_adj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, many key genes such as InR, chico, most insulin peptide genes, and the nutrient-sensing pathways were not observed.

Conclusions

Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

Mitonuclear conflict and cooperation govern the integration of genotypes, phenotypes and environments

The mitonuclear genome is the most successful co-evolved mutualism in the history of life on Earth. The cross-talk between the mitochondrial and nuclear genomes has been shaped by conflict and cooperation for more than 1.5 billion years, yet this system has adapted to countless genomic reorganizations by each partner, and done so under changing environments that have placed dramatic biochemical and physiological pressures on evolving lineages. From putative anaerobic origins, mitochondria emerged as the defining aerobic organelle. During this transition, the two genomes resolved rules for sex determination and transmission that made uniparental inheritance the dominant, but not a universal pattern. Mitochondria are much more than energy-producing organelles and play crucial roles in nutrient and stress signalling that can alter how nuclear genes are expressed as phenotypes. All of these interactions are examples of genotype-by-environment (GxE) interactions, gene-by-gene (GxG) interactions (epistasis) or more generally context-dependent effects on the link between genotype and phenotype. We provide evidence from our own studies in Drosophila, and from those of other systems, that mitonuclear interactions—either conflicting or cooperative—are common features of GxE and GxG. We argue that mitonuclear interactions are an important model for how to better understand the pervasive context-dependent effects underlying the architecture of complex phenotypes. Future research in this area should focus on the quantitative genetic concept of effect size to place mitochondrial links to phenotype in a proper context.

This article is part of the theme issue ‘Linking the mitochondrial genotype to phenotype: a complex endeavour’.

The cuticle inward barrier in Drosophila melanogaster is shaped by mitochondrial and nuclear genotypes and a sex-specific effect of diet

An important role of the insect cuticle is to prevent wetting (i.e., permeation of water) and also to prevent penetration of potentially harmful substances. This barrier function mainly depends on the hydrophobic cuticle surface composed of lipids including cuticular hydrocarbons (CHCs). We investigated to what extent the cuticle inward barrier function depends on the genotype, comprising mitochondrial and nuclear genes in the fruit fly Drosophila melanogaster, and investigated the contribution of interactions between mitochondrial and nuclear genotypes (mito-nuclear interactions) on this function. In addition, we assessed the effects of nutrition and sex on the cuticle barrier function. Based on a dye penetration assay, we find that cuticle barrier function varies across three fly lines that were captured from geographically separated regions in three continents. Testing different combinations of mito-nuclear genotypes, we show that the inward barrier efficiency is modulated by the nuclear and mitochondrial genomes independently. We also find an interaction between diet and sex. Our findings provide new insights into the regulation of cuticle inward barrier function in nature.

The evolutionary potential of diet-dependent effects on lifespan and fecundity in a multi-parental population of Drosophila melanogaster

The nutritional conditions experienced by a population have a major role in shaping trait evolution in many taxa. Constraints exerted by nutrient limitation or nutrient imbalance can influence the maximal value that fitness components such as reproduction and lifespan attains, and organisms may shift how resources are allocated to different structures and functions in response to changes in nutrition. Whether the phenotypic changes associated with changes in nutrition represent an adaptive response is largely unknown. Further, it is unclear whether the response of fitness components to diet even has the potential to evolve in most systems. In this study, we use an admixed multi-parental population of Drosophila melanogaster reared in three different diet conditions to estimate quantitative genetic parameters for lifespan and fecundity. We find significant genetic variation for both traits in our population and show that lifespan has moderate to high heritabilities within diets. Genetic correlations for lifespan between diets were significantly less than one, demonstrating a strong genotype by diet interaction. These findings demonstrate substantial standing genetic variation in our population that is comparable to natural populations and highlights the potential for adaptation to changing nutritional environments.

KDM5D-mediated H3K4 demethylation is required for sexually dimorphic gene expression in mouse embryonic fibroblasts

Males and females share the same genetic code, but gene expression profile often displays differences between two sexes. Mouse embryonic fibroblasts (MEFs) have been used to experiment as a useful tool to test gene function. They have also been characterized by gender-based differences in expressed genes such as Y-linked Sry or X-linked Hprt. However, there is no report on sex differences in global gene expression. Here, using the next-generation RNA sequencing, we compared the comprehensive transcriptome of MEFs derived from two sexes. In comparison with the female group, the male group up-regulated 27 differentially expressed genes (DEGs), in which a male-specific histone demethylase KDM5D gene is included, and 7 DEGs were down-regulated. Based on the results by searching the ENCODE analysis, it was shown that the expression of 15 genes identified is potentially regulated by the methylation of H3K4me1 or H3K4me3. Interestingly, we demonstrated that both of H3K4 methylation are induced by knocking down KDM5D, which causes changes in patterns of eight DEGs found in male MEFs. Collectively, these data not only suggest an importance of KDM5D-mediated demethylation of H3K4 involved in the sexually dimorphic gene expression in male MEFs, but also may provide information regarding sex-dependent changes in gene expression when MEFs are used for experiments.

Genetic redundancy fuels polygenic adaptation in Drosophila

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic-i.e., result from selection on a large number of genetic loci-but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes-e.g., fitness, metabolic rate, and fat content-and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

Random Forest Analysis of Untargeted Metabolomics Data Suggests Increased Use of Omega Fatty Acid Oxidation Pathway in Drosophila Melanogaster Larvae Fed a Medium Chain Fatty Acid Rich High-Fat Diet

Obesity is a complex disease, shaped by both genetic and environmental factors such as diet. In this study, we use untargeted metabolomics and Drosophila melanogaster to model how diet and genotype shape the metabolome of obese phenotypes. We used 16 distinct outbred genotypes of Drosophila larvae raised on normal (ND) and high-fat (HFD) diets, to produce three distinct phenotypic classes; genotypes that stored more triglycerides on a ND relative to the HFD, genotypes that stored more triglycerides on a HFD relative to ND, and genotypes that showed no change in triglyceride storage on either of the two diets. Using untargeted metabolomics we characterized 350 metabolites: 270 with definitive chemical IDs and 80 that were chemically unidentified. Using random forests, we determined metabolites that were important in discriminating between the HFD and ND larvae as well as between the triglyceride phenotypic classes. We found that flies fed on a HFD showed evidence of an increased use of omega fatty acid oxidation pathway, an alternative to the more commonly used beta fatty acid oxidation pathway. Additionally, we observed no correlation between the triglyceride storage phenotype and free fatty acid levels (laurate, caprate, caprylate, caproate), indicating that the distinct metabolic profile of fatty acids in high-fat diet fed Drosophila larvae does not propagate into triglyceride storage differences. However, dipeptides did show moderate differences between the phenotypic classes. We fit Gaussian graphical models (GGMs) of the metabolic profiles for HFD and ND flies to characterize changes in metabolic network structure between the two diets, finding the HFD to have a greater number of edges indicating that metabolome varies more across samples on a HFD. Taken together, these results show that, in the context of obesity, metabolomic profiles under distinct dietary conditions may not be reliable predictors of phenotypic outcomes in a genetically diverse population.

Genotype to phenotype: Diet-by-mitochondrial DNA haplotype interactions drive metabolic flexibility and organismal fitness

Diet may be modified seasonally or by biogeographic, demographic or cultural shifts. It can differentially influence mitochondrial bioenergetics, retrograde signalling to the nuclear genome, and anterograde signalling to mitochondria. All these interactions have the potential to alter the frequencies of mtDNA haplotypes (mitotypes) in nature and may impact human health. In a model laboratory system, we fed four diets varying in Protein: Carbohydrate (P:C) ratio (1:2, 1:4, 1:8 and 1:16 P:C) to four homoplasmic Drosophila melanogaster mitotypes (nuclear genome standardised) and assayed their frequency in population cages. When fed a high protein 1:2 P:C diet, the frequency of flies harbouring Alstonville mtDNA increased. In contrast, when fed the high carbohydrate 1:16 P:C food the incidence of flies harbouring Dahomey mtDNA increased. This result, driven by differences in larval development, was generalisable to the replacement of the laboratory diet with fruits having high and low P:C ratios, perturbation of the nuclear genome and changes to the microbiome. Structural modelling and cellular assays suggested a V161L mutation in the ND4 subunit of complex I of Dahomey mtDNA was mildly deleterious, reduced mitochondrial functions, increased oxidative stress and resulted in an increase in larval development time on the 1:2 P:C diet. The 1:16 P:C diet triggered a cascade of changes in both mitotypes. In Dahomey larvae, increased feeding fuelled increased β-oxidation and the partial bypass of the complex I mutation. Conversely, Alstonville larvae upregulated genes involved with oxidative phosphorylation, increased glycogen metabolism and they were more physically active. We hypothesise that the increased physical activity diverted energy from growth and cell division and thereby slowed development. These data further question the use of mtDNA as an assumed neutral marker in evolutionary and population genetic studies. Moreover, if humans respond similarly, we posit that individuals with specific mtDNA variations may differentially metabolise carbohydrates, which has implications for a variety of diseases including cardiovascular disease, obesity, and perhaps Parkinson's Disease.

Sex and genotype effects on nutrient-dependent fitness landscapes in Drosophila melanogaster

The sexes perform different reproductive roles and have evolved sometimes strikingly different phenotypes. One focal point of adaptive divergence occurs in the context of diet and metabolism, and males and females of a range of species have been shown to require different nutrients to maximize their fitness. Biochemical analyses in Drosophila melanogaster have confirmed that dimorphism in dietary requirements is associated with molecular sex differences in metabolite titres. In addition, they also showed significant within-sex genetic variation in the metabolome. To date however, it is unknown whether this metabolic variation translates into differences in reproductive fitness. The answer to this question is crucial to establish whether genetic variation is selectively neutral or indicative of constraints on sex-specific physiological adaptation and optimization. Here we assay genetic variation in consumption and metabolic fitness effects by screening male and female fitness of thirty D. melanogaster genotypes across four protein-to-carbohydrate ratios. In addition to confirming sexual dimorphism in consumption and fitness, we find significant genetic variation in male and female dietary requirements. Importantly, these differences are not explained by feeding responses and probably reflect metabolic variation that, in turn, suggests the presence of genetic constraints on metabolic dimorphism.

Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases

The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases.

Evolutionary responses of Drosophila melanogaster under chronic malnutrition

Drosophila species have successfully spread and adapted to diverse climates across the globe. For D. melanogaster, rotting vegetative matter provides the primary substrate for mating and oviposition, and also acts as a nutritional resource for developing larvae and adult flies. The transitory nature of decaying vegetation exposes D. melanogaster to rapidly changing nutrient availability. As evidenced by their successful global spread, flies are capable of dealing with fluctuating nutritional reserves within their respective ecological niches. Therefore, D. melanogaster populations might contain standing genetic variation to support survival during periods of nutrient scarcity. The natural history and genetic tractability of D. melanogaster make the fly an ideal model for studies on the genetic basis of resistance to nutritional stress. We review artificial selection studies on nutritionally-deprived D. melanogaster and summarize the phenotypic outcomes of selected animals. Many of the reported evolved traits phenocopy mutants of the nutrient-sensing PI3K/Akt pathway. Given that the PI3K/Akt pathway is also responsive to acute nutritional stress, the PI3K/Akt pathway might underlie traits evolved under chronic nutritional deprivation. Future studies that directly test for the genetic mechanisms driving evolutionary responses to nutritional stress will take advantage of the ease in manipulating fly nutrient availability in the laboratory.

High fat diet alters Drosophila melanogaster sexual behavior and traits: decreased attractiveness and changes in pheromone profiles

Sexual traits convey information about individual quality to potential mates. Environmental and genetic factors affect sexual trait expression and perception via effects on animal condition and health. High fat diet (HFD) is one environmental factor that adversely affects Drosophila melanogaster health, and its effects on animal health are mediated through conserved metabolic signaling pathways. HFD decreases female attractiveness, resulting in reduced male mating behaviors toward HFD females. HFD also affects the ability of males to judge mate attractiveness and likely alters fly condition and sexual traits to impact mating behavior. Here we show that HFD affects both visual (body size) and non-visual (pheromone profiles) sexual traits, which likely contribute to decreased fly attractiveness. We also demonstrate that adult-specific HFD effects on male mate preference can be rescued by changing metabolic signaling. These results demonstrate that HFD alters Drosophila sexual cues to reflect concurrent effects on condition and that less severe behavioral defects can be reversed by genetic manipulations that rescue fly health. This work expands on current knowledge of the role that metabolic signaling pathways play in linking animal health, sexual traits, and mating behavior, and provides a robust assay in a genetically tractable system to continue examining these processes.

Drosophila as a model to study obesity and metabolic disease

Excess adipose fat accumulation, or obesity, is a growing problem worldwide in terms of both the rate of incidence and the severity of obesity-associated metabolic disease. Adipose tissue evolved in animals as a specialized dynamic lipid storage depot: adipose cells synthesize fat (a process called lipogenesis) when energy is plentiful and mobilize stored fat (a process called lipolysis) when energy is needed. When a disruption of lipid homeostasis favors increased fat synthesis and storage with little turnover owing to genetic predisposition, overnutrition or sedentary living, complications such as diabetes and cardiovascular disease are more likely to arise. The vinegar fly Drosophila melanogaster (Diptera: Drosophilidae) is used as a model to better understand the mechanisms governing fat metabolism and distribution. Flies offer a wealth of paradigms with which to study the regulation and physiological effects of fat accumulation. Obese flies accumulate triacylglycerols in the fat body, an organ similar to mammalian adipose tissue, which specializes in lipid storage and catabolism. Discoveries in Drosophila have ranged from endocrine hormones that control obesity to subcellular mechanisms that regulate lipogenesis and lipolysis, many of which are evolutionarily conserved. Furthermore, obese flies exhibit pathophysiological complications, including hyperglycemia, reduced longevity and cardiovascular function - similar to those observed in obese humans. Here, we review some of the salient features of the fly that enable researchers to study the contributions of feeding, absorption, distribution and the metabolism of lipids to systemic physiology.

RNA Interference (RNAi) Screening in Drosophila

In the last decade, RNA interference (RNAi), a cellular mechanism that uses RNA-guided degradation of messenger RNA transcripts, has had an important impact on identifying and characterizing gene function. First discovered in Caenorhabditis elegans, RNAi can be used to silence the expression of genes through introduction of exogenous double-stranded RNA into cells. In Drosophila, RNAi has been applied in cultured cells or in vivo to perturb the function of single genes or to systematically probe gene function on a genome-wide scale. In this review, we will describe the use of RNAi to study gene function in Drosophila with a particular focus on high-throughput screening methods applied in cultured cells. We will discuss available reagent libraries and cell lines, methodological approaches for cell-based assays, and computational methods for the analysis of high-throughput screens. Furthermore, we will review the generation and use of genome-scale RNAi libraries for tissue-specific knockdown analysis in vivo and discuss the differences and similarities with the use of genome-engineering methods such as CRISPR/Cas9 for functional analysis.

Metabolomics: State-of-the-Art Technologies and Applications on Drosophila melanogaster

Metabolomics is one of the latest "omics" technology concerned with the high-throughput identification and quantification of metabolites, the final products of cellular processes. The revealed data provide an instantaneous snapshot of an organism's metabolic pathways, which can be used to explain its phenotype or physiology. On the other hand, Drosophila has shown its power in studying metabolism and related diseases. At this stage, we have the state-of-the-art knowledge in place: a potential candidate to study cellular metabolism (Drosophila melanogaster) and a powerful methodology for metabolic network decipherer (metabolomics). Yet missing is advanced metabolomics technologies like isotope-assisted metabolomics optimized for Drosophila. In this chapter, we will discuss on the current status and future perspectives in technologies and applications of Drosophila metabolomics.

Genetic Dissection of Nutrition-Induced Plasticity in Insulin/Insulin-Like Growth Factor Signaling and Median Life Span in a Drosophila Multiparent Population

The nutritional environments that organisms experience are inherently variable, requiring tight coordination of how resources are allocated to different functions relative to the total amount of resources available. A growing body of evidence supports the hypothesis that key endocrine pathways play a fundamental role in this coordination. In particular, the insulin/insulin-like growth factor signaling (IIS) and target of rapamycin (TOR) pathways have been implicated in nutrition-dependent changes in metabolism and nutrient allocation. However, little is known about the genetic basis of standing variation in IIS/TOR or how diet-dependent changes in expression in this pathway influence phenotypes related to resource allocation. To characterize natural genetic variation in the IIS/TOR pathway, we used >250 recombinant inbred lines (RILs) derived from a multiparental mapping population, the Drosophila Synthetic Population Resource, to map transcript-level QTL of genes encoding 52 core IIS/TOR components in three different nutritional environments [dietary restriction (DR), control (C), and high sugar (HS)]. Nearly all genes, 87%, were significantly differentially expressed between diets, though not always in ways predicted by loss-of-function mutants. We identified cis (i.e., local) expression QTL (eQTL) for six genes, all of which are significant in multiple nutrient environments. Further, we identified trans (i.e., distant) eQTL for two genes, specific to a single nutrient environment. Our results are consistent with many small changes in the IIS/TOR pathways. A discriminant function analysis for the C and DR treatments identified a pattern of gene expression associated with the diet treatment. Mapping the composite discriminant function scores revealed a significant global eQTL within the DR diet. A correlation between the discriminant function scores and the median life span (r = 0.46) provides evidence that gene expression changes in response to diet are associated with longevity in these RILs.

Metabolomic Studies in Drosophila

Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila, often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research.

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the 'omic' opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

Dietary protein content alters both male and female contributions to Drosophila melanogaster female post-mating response traits

Males transfer sperm, proteins and other molecules to females during mating. In Drosophila melanogaster, these molecules contribute to the induction of egg maturation, ovulation, oviposition, sperm storage and changes in female receptivity. This suite of physiological and behavioral changes is referred to as the female post-mating response (PMR). Protein is a necessary macronutrient for both male and female reproduction, but imbalances in protein content can decrease reproductive potential. Dietary protein affects the production of proteins in the male ejaculate that are important for induction of the PMR, and female fecundity increases with dietary protein while lifetime mating rate decreases. The effects of dietary protein levels on other aspects of the female PMR and on male ability to induce the PMR are unknown. To investigate how protein content affects PMR, we raised flies on diets containing low, moderate or high levels of protein and mated females and males from each diet in a combinatorial manner. We first measured the mating duration for each pair, an indication of male reproductive investment, and then evaluated two aspects of the female PMR, fecundity and female remating latency. We found that mating duration was negatively correlated with male dietary protein, and females that mated with high protein males laid fewer eggs. Female diet had no effect on mating duration, but females fed diets with higher protein content laid more eggs and remated sooner. Therefore, dietary protein levels can affect postcopulatory processes important for reproductive output in a sexually dimorphic manner.

Experimental Evolution and Heart Function in Drosophila

Drosophila melanogaster is a good model species for the study of heart function. However, most previous work on D. melanogaster heart function has focused on the effects of large-effect genetic variants. We compare heart function among 18 D. melanogaster populations that have been selected for altered development time, aging, or stress resistance. We find that populations with faster development and faster aging have increased heart dysfunction, measured as percentage heart failure after electrical pacing. Experimental evolution of different triglyceride levels, by contrast, has little effect on heart function. Evolved differences in heart function correlate with allele frequency changes at many loci of small effect. Genomic analysis of these populations produces a list of candidate loci that might affect cardiac function at the intersection of development, aging, and metabolic control mechanisms.

Genetic and Genomic Response to Selection for Food Consumption in Drosophila melanogaster

Food consumption is an essential component of animal fitness; however, excessive food intake in humans increases risk for many diseases. The roles of neuroendocrine feedback loops, food sensing modalities, and physiological state in regulating food intake are well understood, but not the genetic basis underlying variation in food consumption. Here, we applied ten generations of artificial selection for high and low food consumption in replicate populations of Drosophila melanogaster. The phenotypic response to selection was highly asymmetric, with significant responses only for increased food consumption and minimal correlated responses in body mass and composition. We assessed the molecular correlates of selection responses by DNA and RNA sequencing of the selection lines. The high and low selection lines had variants with significantly divergent allele frequencies within or near 2081 genes and 3526 differentially expressed genes in one or both sexes. A total of 519 genes were both genetically divergent and differentially expressed between the divergent selection lines. We performed functional analyses of the effects of RNAi suppression of gene expression and induced mutations for 27 of these candidate genes that have human orthologs and the strongest statistical support, and confirmed that 25 (93 %) affected the mean and/or variance of food consumption.

Considerations when choosing a genetic model organism for metabolomics studies

Model organisms are important in many areas of chemical biology. In metabolomics, model organisms can provide excellent samples for methods development as well as the foundation of comparative phylometabolomics, which will become possible as metabolomics applications expand. Comparative studies of conserved and unique metabolic pathways will help in the annotation of metabolites as well as provide important new targets of investigation in biology and biomedicine. However, most chemical biologists are not familiar with genetics, which needs to be considered when choosing a model organism. In this review we summarize the strengths and weaknesses of several genetic systems, including natural isolates, recombinant inbred lines, and genetic mutations. We also discuss methods to detect targets of selection on the metabolome.

Genomic Trajectories to Desiccation Resistance: Convergence and Divergence Among Replicate Selected Drosophila Lines

Adaptation to environmental stress is critical for long-term species persistence. With climate change and other anthropogenic stressors compounding natural selective pressures, understanding the nature of adaptation is as important as ever in evolutionary biology. In particular, the number of alternative molecular trajectories available for an organism to reach the same adaptive phenotype remains poorly understood. Here, we investigate this issue in a set of replicated Drosophila melanogaster lines selected for increased desiccation resistance-a classical physiological trait that has been closely linked to Drosophila species distributions. We used pooled whole-genome sequencing (Pool-Seq) to compare the genetic basis of their selection responses, using a matching set of replicated control lines for characterizing laboratory (lab-)adaptation, as well as the original base population. The ratio of effective population size to census size was high over the 21 generations of the experiment at 0.52-0.88 for all selected and control lines. While selected SNPs in replicates of the same treatment (desiccation-selection or lab-adaptation) tended to change frequency in the same direction, suggesting some commonality in the selection response, candidate SNP and gene lists often differed among replicates. Three of the five desiccation-selection replicates showed significant overlap at the gene and network level. All five replicates showed enrichment for ovary-expressed genes, suggesting maternal effects on the selected trait. Divergence between pairs of replicate lines for desiccation-candidate SNPs was greater than between pairs of control lines. This difference also far exceeded the divergence between pairs of replicate lines for neutral SNPs. Overall, while there was overlap in the direction of allele frequency changes and the network and functional categories affected by desiccation selection, replicates showed unique responses at all levels, likely reflecting hitchhiking effects, and highlighting the challenges in identifying candidate genes from these types of experiments when traits are likely to be polygenic.

Cross-phenotype association tests uncover genes mediating nutrient response in Drosophila

Background

Obesity-related diseases are major contributors to morbidity and mortality in the developed world. Molecular diagnostics and targets of therapies to combat nutritional imbalance are urgently needed in the clinic. Invertebrate animals have been a cornerstone of basic research efforts to dissect the genetics of metabolism and nutrient response. We set out to use fruit flies reared on restricted and nutrient-rich diets to identify genes associated with starvation resistance, body mass and composition, in a survey of genetic variation across the Drosophila Genetic Reference Panel (DGRP).

Results

We measured starvation resistance, body weight and composition in DGRP lines on each of two diets and used several association mapping strategies to harness this panel of phenotypes for molecular insights. We tested DNA sequence variants for a relationship with single metabolic traits and with multiple traits at once, using a scheme for cross-phenotype association mapping; we focused our association tests on homologs of human disease genes and common polymorphisms; and we tested for gene-by-diet interactions. The results revealed gene and gene-by-diet associations between 17 variants and body mass, whole-body triglyceride and glucose content, or starvation resistance. Focused molecular experiments validated the role in body mass of an uncharacterized gene, CG43921 (which we rename heavyweight), and previously unknown functions for the diacylglycerol kinase rdgA, the huntingtin homolog htt, and the ceramide synthase schlank in nutrient-dependent body mass, starvation resistance, and lifespan.

Conclusions

Our findings implicate a wealth of gene candidates in fly metabolism and nutrient response, and ascribe novel functions to htt, rdgA, hwt and schlank.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3137-9) contains supplementary material, which is available to authorized users.

Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes

INTRODUCTION

'Multi-omics' datasets obtained from an organism of interest reared under different environmental treatments are increasingly common. Identifying the links among metabolites and transcripts can help to elucidate our understanding of the impact of environment at different levels within the organism. However, many methods for characterizing physiological connections cannot address unidentified metabolites.

OBJECTIVES

Here, we use Eigenvector Metabolite Analysis (EvMA) to examine links between metabolomic, transcriptomic, and phenotypic variation data and to assess the impact of environmental factors on these associations. Unlike other methods, EvMA can be used to analyze datasets that include unidentified metabolites and unannotated transcripts.

METHODS

To demonstrate the utility of EvMA, we analyzed metabolomic, transcriptomic, and phenotypic datasets produced from 20 Drosophila melanogaster genotypes reared on four dietary treatments. We used a hierarchical distance-based method to cluster the metabolites. The links between metabolite clusters, gene expression, and overt phenotypes were characterized using the eigenmetabolite (first principal component) of each cluster.

RESULTS

EvMA recovered chemically related groups of metabolites within the clusters. Using the eigenmetabolite, we identified genes and phenotypes that significantly correlated with each cluster. EvMA identifies new connections between the phenotypes, metabolites, and gene transcripts. Conclusion EvMA provides a simple method to identify correlations between metabolites, gene expression, and phenotypes, which can allow us to partition multivariate datasets into meaningful biological modules and identify under-studied metabolites and unannotated gene transcripts that may be central to important biological processes. This can be used to inform our understanding of the effect of environmental mechanisms underlying physiological states of interest.

Reconstruction of Haplotype-Blocks Selected during Experimental Evolution

The genetic analysis of experimentally evolving populations typically relies on short reads from pooled individuals (Pool-Seq). While this method provides reliable allele frequency estimates, the underlying haplotype structure remains poorly characterized. With small population sizes and adaptive variants that start from low frequencies, the interpretation of selection signatures in most Evolve and Resequencing studies remains challenging. To facilitate the characterization of selection targets, we propose a new approach that reconstructs selected haplotypes from replicated time series, using Pool-Seq data. We identify selected haplotypes through the correlated frequencies of alleles carried by them. Computer simulations indicate that selected haplotype-blocks of several Mb can be reconstructed with high confidence and low error rates, even when allele frequencies change only by 20% across three replicates. Applying this method to real data from D. melanogaster populations adapting to a hot environment, we identify a selected haplotype-block of 6.93 Mb. We confirm the presence of this haplotype-block in evolved populations by experimental haplotyping, demonstrating the power and accuracy of our haplotype reconstruction from Pool-Seq data. We propose that the combination of allele frequency estimates with haplotype information will provide the key to understanding the dynamics of adaptive alleles.

Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution

The effective population size (Ne) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term Ne. They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to Ne. Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of Ne, which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate Ne estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide Ne estimates, we extend our method using a recursive partitioning approach to estimate Ne locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their Ne estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest.

Genetic and Sex-Specific Transgenerational Effects of a High Fat Diet in Drosophila melanogaster

An organism's phenotype is the product of its environment and genotype, but an ancestor's environment can also be a contributing factor. The recent increase in caloric intake and decrease in physical activity of developed nations' populations is contributing to deteriorating health and making the study of the longer term impacts of a changing lifestyle a priority. The dietary habits of ancestors have been shown to affect phenotype in several organisms, including humans, mice, and the fruit fly. Whether the ancestral dietary effect is purely environmental or if there is a genetic interaction with the environment passed down for multiple generations, has not been determined previously. Here we used the fruit fly, Drosophila melanogaster, to investigate the genetic, sex-specific, and environmental effects of a high fat diet for three generations' on pupal body weights across ten genotypes. We also tested for genotype-specific transgenerational effects on metabolic pools and egg size across three genotypes. We showed that there were substantial differences in transgenerational responses to ancestral diet between genotypes and sexes through both first and second descendant generations. Additionally, there were differences in phenotypes between maternally and paternally inherited dietary effects. We also found a treated organism's reaction to a high fat diet was not a consistent predictor of its untreated descendants' phenotype. The implication of these results is that, given our interest in understanding and preventing metabolic diseases like obesity, we need to consider the contribution of ancestral environmental experiences. However, we need to be cautious when drawing population-level generalization from small studies because transgenerational effects are likely to exhibit substantial sex and genotype specificity.

Drosophila as a Model for Diabetes and Diseases of Insulin Resistance

Despite the importance of insulin signaling pathways in human disease, initial concerns that insect physiology and sugar metabolism differ enough from humans that flies would not model human disease hampered research in this area. However, during the past 10-15 years, evidence has accumulated that flies can indeed model various aspects of diabetes and related human disorders. This cluster of diseases impact insulin and insulin signaling pathways, fields which have been discussed in many excellent review articles in recent years. In this chapter, we restrict our focus to specific examples of diabetes-related disease models in Drosophila, discussing the advantages and limitations of these models in light of physiological similarities and differences between insects and mammals. We discuss features of metabolism and sugar regulation that are shared between flies and mammals, and specific Drosophila models for Type 1 and Type 2 diabetes, Metabolic syndrome, and related abnormalities including insulin resistance and heart disease. We conclude that fly models for diabetes and related disorders enhance our ability to identify genes and discern functional interactions that can be exploited for disease intervention.

Mitonuclear Epistasis for Development Time and Its Modification by Diet in Drosophila

Mitochondrial (mtDNA) and nuclear genes have to operate in a coordinated manner to maintain organismal function, and the regulation of this homeostasis presents a substantial source of potential epistatic (G × G) interactions. How these interactions shape the fitness landscape is poorly understood. Here we developed a novel mitonuclear epistasis model, using selected strains of the Drosophila Genetic Reference Panel (DGRP) and mitochondrial genomes from within Drosophila melanogaster and D. simulans to test the hypothesis that mtDNA × nDNA interactions influence fitness. In total we built 72 genotypes (12 nuclear backgrounds × 6 mtDNA haplotypes, with 3 from each species) to dissect the relationship between genotype and phenotype. Each genotype was assayed on four food environments. We found considerable variation in several phenotypes, including development time and egg-to-adult viability, and this variation was partitioned into genetic (G), environmental (E), and higher-order (G × G, G × E, and G × G × E) components. Food type had a significant impact on development time and also modified mitonuclear epistases, evidencing a broad spectrum of G × G × E across these genotypes. Nuclear background effects were substantial, followed by mtDNA effects and their G × G interaction. The species of mtDNA haplotype had negligible effects on phenotypic variation and there was no evidence that mtDNA variation has different effects on male and female fitness traits. Our results demonstrate that mitonuclear epistases are context dependent, suggesting the selective pressure acting on mitonuclear genotypes may vary with food environment in a genotype-specific manner.

Using Drosophila to study the evolution of herbivory and diet specialization

Herbivory evolved many times independently across the insect phylogeny, and its evolution is linked with increased rates of diversification. Plants present many barriers to potential herbivores, among them are the so-called secondary chemicals and other molecular defenses such as protease inhibitors that deter herbivores. To understand the mechanisms behind the emergence of herbivory and subsequent species radiations of insects driven largely by diet specialization, it is important to identify the molecular basis associated with these evolutionary transitions. However, most herbivore species lack the genomic information and genetic tools required to identify functionally important genes. The notable exception is the genus Drosophila in which herbivory evolved at least three times independently, and for which abundant genomic data are available. Furthermore, contained within the family Drosophilidae is Drosophila melanogaster, the first genetic model animal. Here, we provide a synthesis of the salient tools that the D. melanogaster system provides to identify functionally important genes required for herbivory and subsequent diet specialization across insects.

Sharpening Precision Medicine by a Thorough Interrogation of Metabolic Individuality

Precision medicine is an active component of medical practice today, but aspirations are to both broaden its reach to a greater diversity of individuals and improve its “precision” by enhancing the ability to define even more disease states in combination with associated treatments. Given complexity of human phenotypes, much work is required. In this review, we deconstruct this challenge at a high level to define what is needed to move closer toward these aspirations. In the context of the variables that influence the diverse array of phenotypes across human health and disease – genetics, epigenetics, environmental influences, and the microbiome – we detail the factors behind why an individual's biochemical (metabolite) composition is increasingly regarded as a key element to precisely defining phenotypes. Although an individual's biochemical (metabolite) composition is generally regarded, and frequently shown, to be a surrogate to the phenotypic state, we review how metabolites (and therefore an individual's metabolic profile) are also functionally related to the myriad of phenotypic influencers like genetics and the microbiota. We describe how using the technology to comprehensively measure an individual's biochemical profile – metabolomics – is integrative to defining individual phenotypes and how it is currently being deployed in efforts to continue to elaborate on human health and disease in large population studies. Finally, we summarize instances where metabolomics is being used to assess individual health in instances where signatures (i.e. biomarkers) have been defined.

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Untargeted biochemical profiling has the potential to phenotype individuals where genetic associations do not seem to show penetrance

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Metabolomics can be leveraged with other ‘omics data to discern phenotype information that is driven by environmental, microbiota, or epigenetic factors.

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Tracking the biochemical profile of individuals may help discern effectiveness or response to treatment or disease progression.

Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila

Genetic and environmental factors influence complex disease in humans, such as metabolic syndrome, and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al. (2014), where we raised 20 wild-type genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole-genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA and N-arachidonoyl dopamine make physiological links between the gross phenotypes across diets, whereas leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual’s genetic and environmental context.

Melanocortin 4 receptor mutations contribute to the adaptation of cavefish to nutrient-poor conditions

Despite recent advances in the understanding of morphological evolution, the genetic underpinnings of behavioral and physiological evolution remain largely unknown. Here, we study the metabolic changes that evolved in independently derived populations of the Mexican cavefish, Astyanax mexicanus. A hallmark of cave environments is scarcity of food. Cavefish populations rely almost entirely on sporadic food input from outside of the caves. To survive under these conditions, cavefish have evolved a range of adaptations, including starvation resistance and binge eating when food becomes available. The use of these adaptive strategies differs among independently derived cave populations. Although all cavefish populations tested lose weight more slowly than their surface conspecifics during restricted rations, only a subset of cavefish populations consume more food than their surface counterparts. A candidate gene-based screen led to the identification of coding mutations in conserved residues of the melanocortin 4 receptor (MC4R) gene, contributing to the insatiable appetite found in some populations of cavefish. Intriguingly, one of the mutated residues has been shown to be linked to obesity in humans. We demonstrate that the allele results in both reduced maximal response and reduced basal activity of the receptor in vitro. We further validate in vivo that the mutated allele contributes to elevated appetite, growth, and starvation resistance. The allele appears to be fixed in cave populations in which the overeating phenotype is present. The presence of the same allele in multiple caves appears to be due to selection from standing genetic variation present in surface populations.

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size.

Patterns of linkage disequilibrium and long range hitchhiking in evolving experimental Drosophila melanogaster populations

Whole-genome resequencing of experimental populations evolving under a specific selection regime has become a popular approach to determine genotype-phenotype maps and understand adaptation to new environments. Despite its conceptual appeal and success in identifying some causative genes, it has become apparent that many studies suffer from an excess of candidate loci. Several explanations have been proposed for this phenomenon, but it is clear that information about the linkage structure during such experiments is needed. Until now only Pool-Seq (whole-genome sequencing of pools of individuals) data were available, which do not provide sufficient information about the correlation between linked sites. We address this problem in two complementary analyses of three replicate Drosophila melanogaster populations evolving to a new hot temperature environment for almost 70 generations. In the first analysis, we sequenced 58 haploid genomes from the founder population and evolved flies at generation 67. We show that during the experiment linkage disequilibrium (LD) increased almost uniformly over much greater distances than typically seen in Drosophila. In the second analysis, Pool-Seq time series data of the three replicates were combined with haplotype information from the founder population to follow blocks of initial haplotypes over time. We identified 17 selected haplotype-blocks that started at low frequencies in the base population and increased in frequency during the experiment. The size of these haplotype-blocks ranged from 0.082 to 4.01 Mb. Moreover, between 42% and 46% of the top candidate single nucleotide polymorphisms from the comparison of founder and evolved populations fell into the genomic region covered by the haplotype-blocks. We conclude that LD in such rising haplotype-blocks results in long range hitchhiking over multiple kilobase-sized regions. LD in such haplotype-blocks is therefore a major factor contributing to an excess of candidate loci. Although modifications of the experimental design may help to reduce the hitchhiking effect and allow for more precise mapping of causative variants, we also note that such haplotype-blocks might be well suited to study the dynamics of selected genomic regions during experimental evolution studies.