Summary of Study ST000999

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000676. The data can be accessed directly via it's Project DOI: 10.21228/M8968S This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST000999
Study TitleNatural genetic variation in C. elegans identified genomic loci controlling metabolite levels
Study TypeMetabolomics in C. elegans
Study SummaryMetabolic 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 32-82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite QTL (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.
Institute
Academic Medical Center of Amsterdam
Last NameGao
First NameArwen
AddressMeibergdreef 9, Amsterdam, North-Holland, 1105 AZ, Netherlands
Emailw.gao@amc.nl
Phone0031205663827
Submit Date2018-07-05
Analysis Type DetailLC-MS
Release Date2018-07-13
Release Version1
Arwen Gao Arwen Gao
https://dx.doi.org/10.21228/M8968S
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR000676
Project DOI:doi: 10.21228/M8968S
Project Title:Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels
Project Type:Targeted metabolomics analysis
Project Summary: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 32-82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite QTL (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.
Institute:Academic Medical Center of Amsterdam
Last Name:Gao
First Name:Arwen
Address:Meibergdreef 9, Amsterdam, North-Holland, 1105 AZ, Netherlands
Email:w.gao@amc.nl
Phone:0031205663827
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