Summary of Study ST000999

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, 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.


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.
Academic Medical Center of Amsterdam
Last NameGao
First NameArwen
AddressMeibergdreef 9, Amsterdam, North-Holland, 1105 AZ, Netherlands
Submit Date2018-07-05
Analysis Type DetailLC-MS
Release Date2018-07-13
Release Version1
Arwen Gao Arwen Gao application/zip

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Combined analysis:

Analysis ID AN001628
Analysis type MS
Chromatography type Unspecified
Chromatography system Waters Acquity
Column none
MS instrument type Triple quadrupole
MS instrument name Waters Quattro Premier XE
Units nmol/mg of protein


Chromatography ID:CH001146
Chromatography Summary:For fatty acids:The MS system consisted of an Acquity UPLC Binary Solvent manager (Waters, Milford MA) and an Acquity UPLC sample manager connected to a Quattro Premier XE mass spectrometer (Waters, Milford MA), used in the negative ESI mode. For amino acids:Liquid chromatography was performed at 50°C using a Acquity UPLC BEH C18, 1.7 µm, 2.1 x 100 mm column (Waters, Milford MA) and the injected volume was 10 µL. Mass spectrometry experiments were performed using a Micromass Quattro Premier XE Tandem Mass Spectrometer (waters, Milford, MA). The mass spectrometer was used in the multiple reaction monitoring mode (MRM) in the ESI-positive mode.
Instrument Name:Waters Acquity
Column Name:none
Chromatography Type:Unspecified