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

Abstract

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.

Phenotyping of Drosophila Melanogaster—A Nutritional Perspective

“…As described by Ng’oma et al (2020), 10 days of feeding of an HSD containing 1 M sucrose alters multiple genetic networks (examined with RNA-seq) in outbred females ( Drosophila Synthetic Population Resource) in comparison to control-fed flies. Although genes encoding the proteins of insulin/insulin-like signaling/the TOR pathway, including Dilp5 , Rheb , and Sirt2 , showed a significant elevation in expression, the effect of an HSD was not limited to key genes but rather affected a wide range of biological pathways and cofactors [ 153 ].…”

“… Transcriptional alterations following intake of a high-sugar diet (HSD) in Drosophila melanogaster . Ingestion of an HSD causes upregulation (blue box) and downregulation (red box) of genes involved in metabolism and energy provision, infection and stress responses, nuclear regulation, and development (modified from [ 129 , 136 , 151 , 152 , 153 ]). …”

Combining metabolomics and experimental evolution reveals key mechanisms underlying longevity differences in laboratory evolved Drosophila melanogaster populations

“…Our work also adds to the growing body of evidence that canonical genetic mechanisms are not always the primary drivers of complex trait variation in "real" populations or laboratory population approximating real populations 28,29,120 . While these mechanisms are highly relevant in certain contexts (i.e.…”

Combining Metabolomics and Experimental Evolution Reveals Key Mechanisms Underlying Longevity Differences in Laboratory Evolved Drosophila melanogaster Populations

“…Our work also adds to the growing body of evidence that canonical genetic mechanisms are not always the primary drivers of complex trait variation in "real" populations or laboratory populations approximating real populations [28,29,121]. While these mechanisms are highly relevant in certain contexts (i.e., mutant screens, studies in specific genetic backgrounds, etc.…”