Metabolomic Characterization of Knock-Out Mutants in Arabidopsis - Development of a Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis (MeKO)

ABSTRACT: Despite recent intensive research efforts in functional genomics, the functions of only a limited number of Arabidopsis (Arabidopsis thaliana) genes have been determined experimentally. Thus, improving gene annotation remains a major challenge in plant science. Because metabolite profiling can characterize the metabolomic phenotype of a genetic perturbation of plant metabolism, it provides clues to the function of genes of interest. In this regard, we chose 50 Arabidopsis mutants including a set of characterized and uncharacterized mutants, which resemble wild-type plants. We performed metabolite profiling of the plants using gas chromatography-mass spectrometry (GC-MS). To make the dataset available as an efficient public functional genomics tool for hypothesis generation, we developed the MeKO database, which allows evaluation of whether a mutation affects metabolism during normal growth. This database contains images of mutants, statistical data analyses, and data on differential metabolite accumulation. Non-processed data, including chromatograms, mass spectra, and experimental meta-data, follow the guidelines of the Metabolomics Standards Initiative (MSI) and are freely downloadable. Proof-of-concept analysis suggests that the MeKO database is highly useful for gene annotation and for generation of hypotheses for genes of interest. MeKO is publicly available at http://prime.psc.riken.jp/meko/.

INSTRUMENT(S): Leco Pegasus III

SUBMITTER: Atsushi Fukushima 

PROVIDER: MTBLS47 | MetaboLights | 2014-03-01

REPOSITORIES: MetaboLights