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.

SUMMARYThe 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.

We elucidated the genome sequence of Glycine max cv. Enrei to provide a reference for characterization of Japanese domestic soybean cultivars. The whole genome sequence obtained using a next-generation sequencer was used for reference mapping into the current genome assembly of G. max cv. Williams 82 obtained by the Soybean Genome Sequencing Consortium in the USA. After sequencing and assembling the whole genome shotgun reads, we obtained a data set with about 928 Mbs total bases and 60,838 gene models. Phylogenetic analysis provided glimpses into the ancestral relationships of both cultivars and their divergence from the complex that include the wild relatives of soybean. The gene models were analyzed in relation to traits associated with anthocyanin and flavonoid biosynthesis and an overall profile of the proteome. The sequence data are made available in DAIZUbase in order to provide a comprehensive informatics resource for comparative genomics of a wide range of soybean cultivars in Japan and a reference tool for improvement of soybean cultivars worldwide.

The Rice TOGO Browser is an online public resource designed to facilitate integration and visualization of mapping data of bacterial artificial chromosome (BAC)/P1-derived artificial chromosome (PAC) clones, genes, restriction fragment length polymorphism (RFLP)/simple sequence repeat (SSR) markers and phenotype data represented as quantitative trait loci (QTLs) onto the genome sequence, and to provide a platform for more efficient utilization of genome information from the point of view of applied genomics as well as functional genomics. Three search options, namely keyword search, region search and trait search, generate various types of data in a user-friendly interface with three distinct viewers, a chromosome viewer, an integrated map viewer and a sequence viewer, thereby providing the opportunity to view the position of genes and/or QTLs at the chromosomal level and to retrieve any sequence information in a user-defined genome region. Furthermore, the gene list, marker list and genome sequence in a specified region delineated by RFLP/SSR markers and any sequences designed as primers can be viewed and downloaded to support forward genetics approaches. An additional feature of this database is the graphical viewer for BLAST search to reveal information not only for regions with significant sequence similarity but also for regions adjacent to those with similarity but with no hits between sequences. An easy to use and intuitive user interface can help a wide range of users in retrieving integrated mapping information including agronomically important traits on the rice genome sequence. The database can be accessed at http://agri-trait.dna.affrc.go.jp/.