For proper control of biological activity, some key genes are highly expressed in a particular spatiotemporal domain. Mining of such spatiotemporally expressed genes using large-scale gene expression data derived from a broad range of experimental sources facilitates our understanding of genome-scale functional gene networks. However, comprehensive information on spatiotemporally expressed genes is lacking in plants. To collect such information, we devised a new index, Δdmax, which is the maximum difference in relative gene expression levels between sample runs which are neighboring when sorted by the levels. Employing this index, we comprehensively evaluated transcripts using large-scale RNA sequencing (RNA-Seq) data stored in the Sequence Read Archive for eight plant species: Arabidopsis thaliana (Arabidopsis), Solanum lycopersicum (tomato), Solanum tuberosum (potato), Oryza sativa (rice), Sorghum bicolor (sorghum), Vitis vinifera (grape), Medicago truncatula (Medicago), and Glycine max (soybean). Based on the frequency distribution of the Δdmax values, approximately 70,000 transcripts showing 0.3 or larger Δdmax values were extracted for the eight species. Information on these genes including the Δdmax values, functional annotations, conservation among species, and experimental conditions where the genes show high expression levels is provided in a new database, CATchUP (http://plantomics.mind.meiji.ac.jp/CATchUP). The CATchUP database assists in identifying genes specifically expressed under particular conditions with powerful search functions and an intuitive graphical user interface.
Keywords: Database; Gene expression profile; RNA-Seq; Spatiotemporal gene expression; Specific expression; Transcriptome.
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