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Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels

Metabolic homeostasis is sustained by complex biological networks that respond to nutrient availability. Genetic and environmental factors may disrupt this equilibrium, leading to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we p...

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Autores principales: Gao, Arwen W., Sterken, Mark G., uit de Bos, Jelmi, van Creij, Jelle, Kamble, Rashmi, Snoek, Basten L., Kammenga, Jan E., Houtkooper, Riekelt H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6120624/
https://www.ncbi.nlm.nih.gov/pubmed/30108180
http://dx.doi.org/10.1101/gr.232322.117
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author Gao, Arwen W.
Sterken, Mark G.
uit de Bos, Jelmi
van Creij, Jelle
Kamble, Rashmi
Snoek, Basten L.
Kammenga, Jan E.
Houtkooper, Riekelt H.
author_facet Gao, Arwen W.
Sterken, Mark G.
uit de Bos, Jelmi
van Creij, Jelle
Kamble, Rashmi
Snoek, Basten L.
Kammenga, Jan E.
Houtkooper, Riekelt H.
author_sort Gao, Arwen W.
collection PubMed
description Metabolic homeostasis is sustained by complex biological networks that respond to nutrient availability. Genetic and environmental factors may disrupt this equilibrium, leading to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we performed quantitative genetic analysis using a population of 199 recombinant inbred lines (RILs) in the nematode Caenorhabditis elegans. We focused on the genomic regions that control metabolite levels by measuring fatty acid (FA) and amino acid (AA) composition in the RILs using targeted metabolomics. The genetically diverse RILs showed a large variation in their FA and AA levels with a heritability ranging from 32% to 82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite quantitative trait loci (mQTL). We focused on mQTL displaying highly significant linkage and heritability, including an mQTL for the FA C14:1 on Chromosome I, and another mQTL for the FA C18:2 on Chromosome IV. Using introgression lines (ILs), we were able to narrow down both mQTL to a 1.4-Mbp and a 3.6-Mbp region, respectively. RNAi-based screening focusing on the Chromosome I mQTL identified several candidate genes for the C14:1 mQTL, including lagr-1, Y87G2A.2, nhr-265, nhr-276, and nhr-81. Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. Furthermore, it allows us to investigate interventions such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.
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spelling pubmed-61206242018-09-05 Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels Gao, Arwen W. Sterken, Mark G. uit de Bos, Jelmi van Creij, Jelle Kamble, Rashmi Snoek, Basten L. Kammenga, Jan E. Houtkooper, Riekelt H. Genome Res Research Metabolic homeostasis is sustained by complex biological networks that respond to nutrient availability. Genetic and environmental factors may disrupt this equilibrium, leading to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we performed quantitative genetic analysis using a population of 199 recombinant inbred lines (RILs) in the nematode Caenorhabditis elegans. We focused on the genomic regions that control metabolite levels by measuring fatty acid (FA) and amino acid (AA) composition in the RILs using targeted metabolomics. The genetically diverse RILs showed a large variation in their FA and AA levels with a heritability ranging from 32% to 82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite quantitative trait loci (mQTL). We focused on mQTL displaying highly significant linkage and heritability, including an mQTL for the FA C14:1 on Chromosome I, and another mQTL for the FA C18:2 on Chromosome IV. Using introgression lines (ILs), we were able to narrow down both mQTL to a 1.4-Mbp and a 3.6-Mbp region, respectively. RNAi-based screening focusing on the Chromosome I mQTL identified several candidate genes for the C14:1 mQTL, including lagr-1, Y87G2A.2, nhr-265, nhr-276, and nhr-81. Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. Furthermore, it allows us to investigate interventions such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions. Cold Spring Harbor Laboratory Press 2018-09 /pmc/articles/PMC6120624/ /pubmed/30108180 http://dx.doi.org/10.1101/gr.232322.117 Text en © 2018 Gao et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
spellingShingle Research
Gao, Arwen W.
Sterken, Mark G.
uit de Bos, Jelmi
van Creij, Jelle
Kamble, Rashmi
Snoek, Basten L.
Kammenga, Jan E.
Houtkooper, Riekelt H.
Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
title Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
title_full Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
title_fullStr Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
title_full_unstemmed Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
title_short Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
title_sort natural genetic variation in c. elegans identified genomic loci controlling metabolite levels
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6120624/
https://www.ncbi.nlm.nih.gov/pubmed/30108180
http://dx.doi.org/10.1101/gr.232322.117
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