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Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster

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 acros...

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Autores principales: Reed, Laura K., Lee, Kevin, Zhang, Zhi, Rashid, Lubna, Poe, Amy, Hsieh, Benjamin, Deighton, Nigel, Glassbrook, Norm, Bodmer, Rolf, Gibson, Greg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063932/
https://www.ncbi.nlm.nih.gov/pubmed/24671769
http://dx.doi.org/10.1534/genetics.114.163857
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author Reed, Laura K.
Lee, Kevin
Zhang, Zhi
Rashid, Lubna
Poe, Amy
Hsieh, Benjamin
Deighton, Nigel
Glassbrook, Norm
Bodmer, Rolf
Gibson, Greg
author_facet Reed, Laura K.
Lee, Kevin
Zhang, Zhi
Rashid, Lubna
Poe, Amy
Hsieh, Benjamin
Deighton, Nigel
Glassbrook, Norm
Bodmer, Rolf
Gibson, Greg
author_sort Reed, Laura K.
collection PubMed
description 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.
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spelling pubmed-40639322014-06-23 Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster Reed, Laura K. Lee, Kevin Zhang, Zhi Rashid, Lubna Poe, Amy Hsieh, Benjamin Deighton, Nigel Glassbrook, Norm Bodmer, Rolf Gibson, Greg Genetics Investigations 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. Genetics Society of America 2014-06 2014-03-25 /pmc/articles/PMC4063932/ /pubmed/24671769 http://dx.doi.org/10.1534/genetics.114.163857 Text en Copyright © 2014 by the Genetics Society of America Available freely online through the author-supported open access option.
spellingShingle Investigations
Reed, Laura K.
Lee, Kevin
Zhang, Zhi
Rashid, Lubna
Poe, Amy
Hsieh, Benjamin
Deighton, Nigel
Glassbrook, Norm
Bodmer, Rolf
Gibson, Greg
Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster
title Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster
title_full Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster
title_fullStr Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster
title_full_unstemmed Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster
title_short Systems Genomics of Metabolic Phenotypes in Wild-Type Drosophila melanogaster
title_sort systems genomics of metabolic phenotypes in wild-type drosophila melanogaster
topic Investigations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063932/
https://www.ncbi.nlm.nih.gov/pubmed/24671769
http://dx.doi.org/10.1534/genetics.114.163857
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