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.

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.

BackgroundPlant growth depends on synergistic interactions between internal and external signals, and yield potential of crops is a manifestation of how these complex factors interact, particularly at critical stages of development. As an initial step towards developing a systems-level understanding of the biological processes underlying the expression of overall agronomic potential in cereal crops, a high-resolution transcriptome analysis of rice was conducted throughout life cycle of rice grown under natural field conditions.ResultsA wide range of gene expression profiles based on 48 organs and tissues at various developmental stages identified 731 organ/tissue specific genes as well as 215 growth stage-specific expressed genes universally in leaf blade, leaf sheath, and root. Continuous transcriptome profiling of leaf from transplanting until harvesting further elucidated the growth-stage specificity of gene expression and uncovered two major drastic changes in the leaf transcriptional program. The first major change occurred before the panicle differentiation, accompanied by the expression of RFT1, a putative florigen gene in long day conditions, and the downregulation of the precursors of two microRNAs. This transcriptome change was also associated with physiological alterations including phosphate-homeostasis state as evident from the behavior of several key regulators such as miR399. The second major transcriptome change occurred just after flowering, and based on analysis of sterile mutant lines, we further revealed that the formation of strong sink, i.e., a developing grain, is not the major cause but is rather a promoter of this change.ConclusionsOur study provides not only the genetic basis for functional genomics in rice but also new insight into understanding the critical physiological processes involved in flowering and seed development, that could lead to novel strategies for optimizing crop productivity.

Similarity of gene expression across a wide range of biological conditions can be efficiently used in characterization of gene function. We have constructed a rice gene coexpression database, RiceFREND (http://ricefrend.dna.affrc.go.jp/), to identify gene modules with similar expression profiles and provide a platform for more accurate prediction of gene functions. Coexpression analysis of 27 201 genes was performed against 815 microarray data derived from expression profiling of various organs and tissues at different developmental stages, mature organs throughout the growth from transplanting until harvesting in the field and plant hormone treatment conditions, using a single microarray platform. The database is provided with two search options, namely, ‘single guide gene search’ and ‘multiple guide gene search’ to efficiently retrieve information on coexpressed genes. A user-friendly web interface facilitates visualization and interpretation of gene coexpression networks in HyperTree, Cytoscape Web and Graphviz formats. In addition, analysis tools for identification of enriched Gene Ontology terms and cis-elements provide clue for better prediction of biological functions associated with the coexpressed genes. These features allow users to clarify gene functions and gene regulatory networks that could lead to a more thorough understanding of many complex agronomic traits.