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

被引：41

作者：

Barupal, Dinesh K. ^{[1
]}

Zhang, Ying ^{[1
]}

Shen, Tong ^{[1
]}

Fan, Sili ^{[1
]}

Roberts, Bryan S. ^{[1
]}

Fitzgerald, Patrick ^{[1
]}

Wancewicz, Benjamin ^{[1
]}

Valdiviez, Luis ^{[1
]}

Wohlgemuth, Gert ^{[1
]}

Byram, Gregory ^{[1
]}

Choy, Ying Yng ^{[1
]}

Haffner, Bennett ^{[1
]}

Showalter, Megan R. ^{[1
]}

Vaniya, Arpana ^{[1
]}

Bloszies, Clayton S. ^{[1
]}

Folz, Jacob S. ^{[1
]}

Kind, Tobias ^{[1
]}

Flenniken, Ann M. ^{[2
,3
]}

McKerlie, Colin ^{[2
,4
]}

Nutter, Lauryl M. J. ^{[2
,4
]}

Lloyd, Kent C. ^{[5
]}

Fiehn, Oliver ^{[1
]}

机构：

[1] Univ Calif Davis, NIH West Coast Metabol Ctr, 451 Hlth Sci Dr, Davis, CA 95616 USA

[2] Ctr Phenogen, Toronto, ON M5T 3H7, Canada

[3] Mt Sinai Hosp, Lunenfeld Tanenbaum Res Inst, Toronto, ON M5G 1X5, Canada

[4] Hosp Sick Children, Toronto, ON M5G 1X8, Canada

[5] Univ Calif Davis, Mouse Biol Program, Davis, CA 95616 USA

来源：

METABOLITES | 2019年 / 9卷 / 05期

基金：

美国国家卫生研究院;

关键词：

Metabolic phenotyping; metabolomics; lipidomics; functional genomics; mouse knockouts; IMPC; LC-MS; GC-MS; GENOME-WIDE; GENE; ASSOCIATION;

D O I：

10.3390/metabo9050101

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页数：14

共 28 条

[1] MetaMapp: mapping and visualizing metabolomic data by integrating information from biochemical pathways and chemical and mass spectral similarity [J].

Barupal, Dinesh K. ;

Haldiya, Pradeep K. ;

Wohlgemuth, Gert ;

Kind, Tobias ;

Kothari, Shanker L. ;

Pinkerton, Kent E. ;

Fiehn, Oliver .

BMC BIOINFORMATICS, 2012, 13

[2] Generation and quality control of lipidomics data for the alzheimer's disease neuroimaging initiative cohort [J].

Barupal, Dinesh Kumar ;

Fan, Sili ;

Wancewicz, Benjamin ;

Cajka, Tomas ;

Sa, Michael ;

Showalter, Megan R. ;

Baillie, Rebecca ;

Tenenbaum, Jessica D. ;

Louie, Gregory ;

Kaddurah-Daouk, Rima ;

Fiehn, Oliver .

SCIENTIFIC DATA, 2018, 5

[3] Chemical Similarity Enrichment Analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets [J].

Barupal, Dinesh Kumar ;

Fiehn, Oliver .

SCIENTIFIC REPORTS, 2017, 7

[4] Inactivation of Metabolic Genes Causes Short- and Long-Range dys-Regulation in Escherichia coli Metabolic Network [J].

Barupal, Dinesh Kumar ;

Lee, Sang Jun ;

Karoly, Edward D. ;

Adhya, Sankar .

PLOS ONE, 2013, 8 (12)

[5] Structure Annotation of All Mass Spectra in Untargeted Metabolomics [J].

Blazenovic, Ivana ;

Kind, Tobias ;

Sa, Michael R. ;

Ji, Jian ;

Vaniya, Arpana ;

Wancewicz, Benjamin ;

Roberts, Bryan S. ;

Torbasinovic, Hrvoje ;

Lee, Tack ;

Mehta, Sajjan S. ;

Showalter, Megan R. ;

Song, Hosook ;

Kwok, Jessica ;

Jahn, Dieter ;

Kim, Jayoung ;

Fiehn, Oliver .

ANALYTICAL CHEMISTRY, 2019, 91 (03) :2155-2162

[6] Towards an encyclopaedia of mammalian gene function: the International Mouse Phenotyping Consortium [J].

Brown, Steve D. M. ;

Moore, Mark W. .

DISEASE MODELS & MECHANISMS, 2012, 5 (03) :289-292

[7] Recon3D enables a three-dimensional view of gene variation in human metabolism [J].

Brunk, Elizabeth ;

Sahoo, Swagatika ;

Zielinski, Daniel C. ;

Altunkaya, Ali ;

Drager, Andreas ;

Mih, Nathan ;

Gatto, Francesco ;

Nilsson, Avlant ;

Gonzalez, German Andres Preciat ;

Aurich, Maike Kathrin ;

Prlic, Andreas ;

Sastry, Anand ;

Danielsdottir, Anna D. ;

Heinken, Almut ;

Noronha, Alberto ;

Rose, Peter W. ;

Burley, Stephen K. ;

Fleming, Ronan M. T. ;

Nielsen, Jens ;

Thiele, Ines ;

Palsson, Bernhard O. .

NATURE BIOTECHNOLOGY, 2018, 36 (03) :272-+

[8] Integrated metabolomics and proteomics highlight altered nicotinamide and polyamine pathways in lung adenocarcinoma [J].

Fahrmann, Johannes F. ;

Grapov, Dmitry ;

Wanichthanarak, Kwanjeera ;

DeFelice, Brian C. ;

Salemi, Michelle R. ;

Rom, William N. ;

Gandara, David R. ;

Phinney, Brett S. ;

Fiehn, Oliver ;

Pass, Harvey ;

Miyamoto, Suzanne .

CARCINOGENESIS, 2017, 38 (03) :271-280

[9] Systematic Error Removal Using Random Forest for Normalizing Large-Scale Untargeted Lipidomics Data [J].

Fan, Sili ;

Kind, Tobias ;

Cajka, Tomas ;

Hazen, Stanley L. ;

Tang, W. H. Wilson ;

Kaddurah-Daouk, Rima ;

Irvin, Marguerite R. ;

Arnett, Donna K. ;

Barupal, Dinesh K. ;

Fiehn, Oliver .

ANALYTICAL CHEMISTRY, 2019, 91 (05) :3590-3596

[10]

Fiehn Oliver, 2016, Curr Protoc Mol Biol, V114, DOI 10.1002/0471142727.mb3004s114

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