LETTER

Comprehensive Analysis of the Mouse Metabolome Based on the Transcriptome

    • 1Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
    • 2Division of Genomic Information Resource Exploration, Science of Biological Supramolecular Systems, Yokohama City University, Graduate School of Integrated Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
    • 3Multimedia Development Center, Advanced Technology Development Department, NTT Software Corporation, Naka-ku, Yokohama, Kanagawa 231-8554, Japan
    • 4Genome Science Laboratory, RIKEN, Hirosawa, Wako, Saitama 351-0198, Japan
Published June 2, 2003. Vol 13 Issue 6b, pp. 1345-1349. https://doi.org/10.1101/gr.974603
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Abstract

The complete set of cDNAs encoding the enzymes of known metabolic pathways has not previously been available for any mammal. Here, transcripts encoding the metabolic pathways of the mouse (mouse metabolome) were reconstructed by making use of the KEGG metabolic pathway database and gene ontology (GO) assignment to the mouse representative transcript and protein set (RTPS), which contains all available mouse transcript sequences including the FANTOM set of RIKEN mouse cDNA clones. By assigning EC numbers extracted from the molecular function ontology in GO, the known mouse transcriptome was predicted to encode enzymes with 726 unique EC numbers. Of these, 648 EC numbers were newly assigned based on the FANTOM set. The mouse metabolome confirmed by cDNA analysis includes almost all of the enzymes of well known pathways such as the tricarboxylic acid cycle and urea cycle. On the other hand, analysis of enzymes required for the tryptophan metabolism pathway revealed a lack of connectivity, indicating that cDNAs/genes encoding several key enzymes remain to be identified. The information derived from coexpression from the cDNA microarray analysis of enzymes of known function may lead to identification of the missing components of the metabolome, and will add new insights into the connectivity of the mammalian metabolic pathways.

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