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a catalog of worldwide biological databases

A wide range of resources on gene expression profiling enhance various strategies in plant molecular biology particularly in characterization of gene function. We have updated our gene expression profile database, RiceXPro (http://ricexpro.dna.affrc.go.jp/), to provide more comprehensive information on the transcriptome of rice encompassing the entire growth cycle and various experimental conditions. The gene expression profiles are currently grouped into three categories, namely, 'field/development' with 572 data corresponding to 12 data sets, 'plant hormone' with 143 data corresponding to 13 data sets and 'cell- and tissue-type' comprising of 38 microarray data. In addition to the interface for retrieving expression information of a gene/genes in each data set, we have incorporated an interface for a global approach in searching an overall view of the gene expression profiles from multiple data sets within each category. Furthermore, we have also added a BLAST search function that enables users to explore expression profile of a gene/genes with similarity to a query sequence. Therefore, the updated version of RiceXPro can be used more efficiently to survey the gene expression signature of rice in sufficient depth and may also provide clues on gene function of other cereal crops.

The root system is a crucial determinant of plant growth potential because of its important functions, e.g. uptake of water and nutrients, structural support and interaction with symbiotic organisms. Elucidating the molecular mechanism of root development and functions is therefore necessary for improving plant productivity, particularly for crop plants, including rice (Oryza sativa). As an initial step towards developing a comprehensive understanding of the root system, we performed a large-scale transcriptome analysis of the rice root via a combined laser microdissection and microarray approach. The crown root was divided into eight developmental stages along the longitudinal axis and three radial tissue types at two different developmental stages, namely: epidermis, exodermis and sclerenchyma; cortex; and endodermis, pericycle and stele. We analyzed a total of 38 microarray data and identified 22,297 genes corresponding to 17,010 loci that showed sufficient signal intensity as well as developmental- and tissue type-specific transcriptome signatures. Moreover, we clarified gene networks associated with root cap function and lateral root formation, and further revealed antagonistic and synergistic interactions of phytohormones such as auxin, cytokinin, brassinosteroids and ethylene, based on the expression pattern of genes related to phytohormone biosynthesis and signaling. Expression profiling of transporter genes defined not only major sites for uptake and transport of water and nutrients, but also distinct signatures of the radial transport system from the rhizosphere to the xylem vessel for each nutrient. All data can be accessed from our gene expression profile database, RiceXPro (http://ricexpro.dna.affrc.go.jp), thereby providing useful information for understanding the molecular mechanisms involved in root system development of crop plants.

Elucidating the function of all predicted genes in rice remains as the ultimate goal in cereal genomics in order to ensure the development of improved varieties that will sustain an expanding world population. We constructed a gene expression database (RiceXPro, URL: http://ricexpro.dna.affrc.go.jp/) to provide an overview of the transcriptional changes throughout the growth of the rice plant in the field. RiceXPro contains two data sets corresponding to spatiotemporal gene expression profiles of various organs and tissues, and continuous gene expression profiles of leaf from transplanting to harvesting. A user-friendly web interface enables the extraction of specific gene expression profiles by keyword and chromosome search, and basic data analysis, thereby providing useful information as to the organ/tissue and developmental stage specificity of expression of a particular gene. Analysis tools such as t-test, calculation of fold change and degree of correlation facilitate the comparison of expression profiles between two random samples and the prediction of function of uncharacterized genes. As a repository of expression data encompassing growth in the field, this database can provide baseline information of genes that underlie various agronomically important traits in rice.