A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium

Dinesh K. Barupal, Ying Zhang, Tong Shen, Sili Fan, Bryan S. Roberts, Patrick Fitzgerald, Benjamin Wancewicz, Luis Valdiviez, Gert Wohlgemuth, Gregory Byram, Ying Yng Choy, Bennett Haffner, Megan R. Showalter, Arpana Vaniya, Clayton S. Bloszies, Jacob S. Folz, Tobias Kind, Ann M. Flenniken, Colin McKerlie, Lauryl M.J. Nutter & 2 others Kevin C K Lloyd, Oliver Fiehn

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article number101
JournalMetabolites
Volume9
Issue number5
DOIs
StatePublished - May 1 2019

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Metabolomics
Knockout Mice
Metabolites
Plasmas
Oxylipins
Genes
Phenotype
Liquid chromatography
Bile Acids and Salts
Gas chromatography
Gene Knockout Techniques
Mass spectrometry
Information Storage and Retrieval
Steroids
Liquid Chromatography
Gas Chromatography
Gas Chromatography-Mass Spectrometry
Ions
Mass Spectrometry
Software

Keywords

  • Functional genomics
  • GC-MS
  • IMPC
  • LC-MS
  • Lipidomics
  • Metabolic phenotyping
  • Metabolomics
  • Mouse knockouts

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology

Cite this

A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium. / 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, Kevin C K; Fiehn, Oliver.

In: Metabolites, Vol. 9, No. 5, 101, 01.05.2019.

Research output: Contribution to journalArticle

Barupal, DK, Zhang, Y, Shen, T, Fan, S, Roberts, BS, Fitzgerald, P, Wancewicz, B, Valdiviez, L, Wohlgemuth, G, Byram, G, Choy, YY, Haffner, B, Showalter, MR, Vaniya, A, Bloszies, CS, Folz, JS, Kind, T, Flenniken, AM, McKerlie, C, Nutter, LMJ, Lloyd, KCK & Fiehn, O 2019, 'A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium', Metabolites, vol. 9, no. 5, 101. https://doi.org/10.3390/metabo9050101
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, Kevin C K ; Fiehn, Oliver. / A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium. In: Metabolites. 2019 ; Vol. 9, No. 5.
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