数据库简述：Metabolomic Characterization of Knock-Out Mutants in Arabidopsis – Development of a Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis
数据库主要信息：Despite recent intensive research efforts in functional genomics, the functions of only a limited number of Arabidopsis (Arabidopsis thaliana) genes have been determined experimentally and improving gene annotation remains a major challenge in plant science. As metabolite profiling can characterize the metabolomic phenotype of a genetic perturbation in the plant metabolism, it provides clues to the function(s) of genes of interest. We chose 50 Arabidopsis mutants including a set of characterized and uncharacterized mutants, that 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 our MeKO database. It allows evaluation of whether a mutation affects metabolism during normal plant growth and contains images of mutants, data on differences in metabolite accumulation, and interactive analysis tools. Non-processed data, including chromatograms, mass spectra, and experimental metadata, follow the guidelines set by Metabolomics Standards Initiative (MSI) and are freely downloadable. Proof-of-concept analysis suggests that the MeKO database is highly useful for the generation of hypotheses for genes of interest and for improving gene annotation.
Graduate School of Pharmaceutical Sciences, Chiba University, Chiba-shi, Chiba 263-8522, Japan
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