Systems Genomics of Metabolic Phenotypes in Wild-TypeDrosophila melanogaster

Abstract

Systems biology is an approach to dissection of complex traits that explicitly recognizes the impact of genetic, physiological, and environmental interactions in the generation of phenotypic variation. We describe comprehensive transcriptional and metabolic profiling in Drosophila melanogaster across four diets, finding little overlap in modular architecture. Genotype and genotype-by-diet interactions are a major component of transcriptional variation (24 and 5.3% of the total variation, respectively) while there were no main effects of diet (<1%). Genotype was also a major contributor to metabolomic variation (16%), but in contrast to the transcriptome, diet had a large effect (9%) and the interaction effect was minor (2%) for the metabolome. Yet specific principal components of these molecular phenotypes measured in larvae are strongly correlated with particular metabolic syndrome-like phenotypes such as pupal weight, larval sugar content and triglyceride content, development time, and cardiac arrhythmia in adults. The second principal component of the metabolomic profile is especially informative across these traits with glycine identified as a key loading variable. To further relate this physiological variability to genotypic polymorphism, we performed evolve-and-resequence experiments, finding rapid and replicated changes in gene frequency across hundreds of loci that are specific to each diet. Adaptation to diet is thus highly polygenic. However, loci differentially transcribed across diet or previously identified by RNAi knockdown or expression QTL analysis were not the loci responding to dietary selection. Therefore, loci that respond to the selective pressures of diet cannot be readily predicted a priori from functional analyses.

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

“…Of these fish, we found six that were heterozygous and one that was homozygous for the derived allele (Table 1). These frequencies are in line with previous results of standing genetic variation in cavefish (4) and in marine stickleback populations for alleles responsible for reduced body armor in fresh water populations (14), supporting the possibility that there was selection from standing genetic variation.…”

“…Protas et al (6) mapped sensitivity to dissolved amino acids, weight loss on sustained fasts, and condition factor using quantitative trait loci (QTL) analysis, but the genetic underpinning has not been identified for any of these traits. The genetic basis of metabolic variation, in particular, has recently undergone a resurgence in interest (12)(13)(14), but it still remains poorly understood in vertebrates.…”

Drosophilaas a model to study obesity and metabolic disease

“…One can also assess the ability to survive on and process high-calorie obesogenic diets, or the degree of 'obesity tolerance'. Like humans, some obese flies can be quite healthy , whereas other genotypes develop severe effects with only modest levels of overfeeding Nakagami et al, 2003;Teesalu et al, 2017 wild-caught Drosophila strains exhibited various degrees of dietdependent obesity, consistent with a model where fat storage represents a balance between optimizing storage depots and overloading the animal (Reed et al, 2014(Reed et al, , 2010.…”

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

“…The large effect genetic mutants identified via classical genetic techniques are typically not segregating in natural populations, which is not surprising, given the central role of the pathways involved [79]. Additionally, despite the fact that several large effect mutations have been found to influence lifespan in D. melanogaster [2], mapping studies and evolution experiments using natural populations have not independently identified these same genes as important contributors to natural genetic variation [2,80 -82], with few exceptions [76,77]. These results are not owing to a lack of genetic variation at these loci, given the populations used are derived from wild populations and typically have high heritabilities for most phenotypes, including gene expression levels of some of these same genes [83].…”