Metabolomics as a hypothesis-generating functional genomics tool for the annotation of Arabidopsis thaliana genes of "unknown function"

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dc.contributor.authorQuanbeck, Stephanie M.en
dc.contributor.authorBrachova, Libuseen
dc.contributor.authorCampbell, Alexis A.en
dc.contributor.authorGuan, Xinen
dc.contributor.authorPerera, Annen
dc.contributor.authorHe, Kunen
dc.contributor.authorRhee, Seung Y.en
dc.contributor.authorBais, Preetien
dc.contributor.authorDickerson, Julie A.en
dc.contributor.authorDixon, Philipen
dc.contributor.authorWohlgemuth, Gerten
dc.contributor.authorFiehn, Oliveren
dc.contributor.authorBarkan, Lenoreen
dc.contributor.authorLange, Irisen
dc.contributor.authorLange, B. Markusen
dc.contributor.authorLee, Insuken
dc.contributor.authorCortes, Diegoen
dc.contributor.authorSalazar, Carolinaen
dc.contributor.authorShuman, Joelen
dc.contributor.authorShulaev, Vladimiren
dc.contributor.authorHuhman, David V.en
dc.contributor.authorSumner, Lloyd W.en
dc.contributor.authorRoth, Mary R.en
dc.contributor.authorWelti, Ruthen
dc.contributor.authorIlarslan, Hilalen
dc.contributor.authorWurtele, Eve S.en
dc.contributor.authorNikolau, Basil J.en
dc.date.accessioned2019-05-02T13:13:52Zen
dc.date.available2019-05-02T13:13:52Zen
dc.date.issued2012en
dc.description.abstractMetabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs.en
dc.description.notesThis work was supported by the National Science Foundation (grants no. MCB 0520140 and 0820823). Additional support included: funding from the National Science Foundation Major Research Instrumentation grant no. DBI 0521587 (Ruth Welti); National Science Foundation Arabidopsis 2010 DBI0520267 (Eve S. Wurtele); The Samuel Roberts Noble Foundation for personnel support (Lloyd W. Sumner and David V. Hultman) and instrumentation purchase; Carnegie Institution for Science (Kun He, Seung Y. Rhee) and National Science Foundation grant DBI-0640769 (Seung Y. Rhee); Yun Lu for performing GC TOEMS in the Fiehn laboratory; Agricultural Research Center at Washington State University (B. Markus Lange). The authors would also like to acknowledge the W. M. Keck Foundation for support at Iowa State University. We acknowledge the very kind support of all the collaborators listed at www.plantmetabolomics.org, who contributed Arabidopsis T-DNA tagged mutant seed stocks, in particular the late Dr. Christian R. H. Raetz (Duke University) for the seed stock carrying the lpxA-1 allele, and Dr. David J. Oliver (Iowa State University) for the seed stock carrying the oxp1 allele.en
dc.description.sponsorshipNational Science Foundation [MCB 0520140, 0820823, DBI-0640769]en
dc.description.sponsorshipNational Science Foundation Major Research Instrumentation grant [DBI 0521587]en
dc.description.sponsorshipNational Science Foundation Arabidopsis [2010 DBI0520267]en
dc.description.sponsorshipSamuel Roberts Noble Foundationen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.3389/fpls.2012.00015en
dc.identifier.eissn1664-462Xen
dc.identifier.other15en
dc.identifier.pmid22645570en
dc.identifier.urihttp://hdl.handle.net/10919/89337en
dc.identifier.volume3en
dc.language.isoenen
dc.publisherFrontiersen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectArabidopsisen
dc.subjectmetabolomicsen
dc.subjectgene annotationen
dc.subjectfunctional genomicsen
dc.subjectdatabaseen
dc.titleMetabolomics as a hypothesis-generating functional genomics tool for the annotation of Arabidopsis thaliana genes of "unknown function"en
dc.title.serialFrontiers In Plant Scienceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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