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Title: A Comprehensive Plasma Metabolomics Dataset for a Cohort of Mouse Knockouts within the International Mouse Phenotyping Consortium.

Authors: Barupal, Dinesh K; Zhang, Ying; Shen, Tong; Fan, Sili; Roberts, Bryan S; Fitzgerald, Patrick; Wancewicz, Benjamin; Valdiviez, Luis; Wohlgemuth, Gert; Byram, Gregory; Choy, Ying Yng; Haffner, Bennett; Showalter, Megan R; Vaniya, Arpana; Bloszies, Clayton S; Folz, Jacob S; Kind, Tobias; Flenniken, Ann M; McKerlie, Colin; Nutter, Lauryl M J; Lloyd, Kent C; Fiehn, Oliver

Published In Metabolites, (2019 May 22)

Abstract: Mouse knockouts facilitate the study ofgene functions. Often, multiple abnormal phenotypes are induced when a gene is inactivated. The International Mouse Phenotyping Consortium (IMPC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples from 30 unique mouse gene knockouts and corresponding wildtype mice from the IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases, and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.

PubMed ID: 31121816 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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