Natural variation in sugar tolerance associates with changes in signaling and mitochondrial ribosome biogenesis
- University of Minnesota, United States
- University of Helsinki, Finland
- The University of North Carolina at Chapel Hill, United States
- Cited 2
- Views 1,499
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Abstract
How dietary selection impacts genome evolution to define the optimal range of nutrient intake is a poorly understood question with medical relevance. We have addressed this question by analyzing Drosophila simulans and sechellia, recently diverged species with differential diet choice. D. sechellia larvae, specialized to a nutrient scarce diet, did not survive on sugar rich conditions, while the generalist species D. simulans was sugar tolerant. Sugar tolerance in D. simulans was a tradeoff for performance on low energy diet and was associated with global reprogramming of metabolic gene expression. Hybridization and phenotype-based introgression revealed the genomic regions of D. simulans that were sufficient for sugar tolerance. These regions included genes that are involved in mitochondrial ribosome biogenesis and intracellular signaling, such as PPP1R15/Gadd34 and SERCA, which contributed to sugar tolerance. In conclusion, genomic variation affecting genes involved in global metabolic control defines the optimal range for dietary macronutrient composition.
Article and author information
Author details
Funding
Suomen Akatemia (286767)
- Ville Hietakangas
Novo Nordisk Foundation (NNF16OC0021460)
- Ville Hietakangas
Sigrid Juséliuksen Säätiö
- Ville Hietakangas
Finnish Diabetes Foundation
- Ville Hietakangas
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Patricia J Wittkopp, University of Michigan, United States
Publication history
- Received: August 6, 2018
- Accepted: November 27, 2018
- Accepted Manuscript published: November 27, 2018 (version 1)
- Version of Record published: December 20, 2018 (version 2)
Copyright
© 2018, Melvin et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Computational and Systems Biology
- Genetics and Genomics
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- Chromosomes and Gene Expression
- Genetics and Genomics
