ArticleG3 (Bethesda, Md.)2015
Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila.
Article in G3 (Bethesda, Md.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 39 citations in OpenAlex.
- Mapping of genotype-by-environment interaction loci for Metabolic Syndrome-like traits using the multi-parentbioRxiv : the preprint server for biology · 2025Article
- Phenotyping ofBiomolecules · 2022Review
- Physiological and metabolomic consequences of reduced expression of the Drosophila brummer triglyceride Lipase.PloS one · 2021Article
- Influence of Lab Adapted Natural Diet and Microbiota on Life History and Metabolic Phenotype ofMicroorganisms · 2020Article
- Metabogenomics reveals four candidate regions involved in the pathophysiology of Equine Metabolic Syndrome.Molecular and cellular probes · 2020Article
- The metabolome as a link in the genotype-phenotype map for peroxide resistance in the fruit fly, Drosophila melanogaster.BMC genomics · 2020Article
- Tissue-specific analysis of lipid species inJournal of lipid research · 2020Article
- Systems genetics of theGenome research · 2020Article
- Rapid metabolic shifts occur during the transition between hunger and satiety in Drosophila melanogaster.Nature communications · 2019Article
- The cuticle inward barrier inPeerJ · 2019Article
- Article
- Genotype to phenotype: Diet-by-mitochondrial DNA haplotype interactions drive metabolic flexibility and organismal fitness.PLoS genetics · 2018Review
- Metabolomic Studies inGenetics · 2017Review
- Genetic Dissection of Nutrition-Induced Plasticity in Insulin/Insulin-Like Growth Factor Signaling and Median Life Span in aGenetics · 2017Article
- Considerations when choosing a genetic model organism for metabolomics studies.Current opinion in chemical biology · 2017Review
- Drosophila as a Model for Diabetes and Diseases of Insulin Resistance.Current topics in developmental biology · 2017Review
- Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes.Metabolomics : Official journal of the Metabolomic Society · 2016Article
- Genetic and Sex-Specific Transgenerational Effects of a High Fat Diet in Drosophila melanogaster.PloS one · 2016Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
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.
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