RiceXPro: a platform for monitoring gene expression in japonica rice grown under natural field conditions

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

Gene Organization in Rice Revealed by Full-Length cDNA Mapping and Gene Expression Analysis through Microarray

Rice (Oryza sativa L.) is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA) sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE) genes, 33K annotated non-expressed (ANE) genes, and 5.5K non-annotated expressed (NAE) genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria

Sequencing and Analysis of Approximately 40 000 Soybean cDNA Clones from a Full-Length-Enriched cDNA Library

A large collection of full-length cDNAs is essential for the correct annotation of genomic sequences and for the functional analysis of genes and their products. We obtained a total of 39 936 soybean cDNA clones (GMFL01 and GMFL02 clone sets) in a full-length-enriched cDNA library which was constructed from soybean plants that were grown under various developmental and environmental conditions. Sequencing from 5′ and 3′ ends of the clones generated 68 661 expressed sequence tags (ESTs). The EST sequences were clustered into 22 674 scaffolds involving 2580 full-length sequences. In addition, we sequenced 4712 full-length cDNAs. After removing overlaps, we obtained 6570 new full-length sequences of soybean cDNAs so far. Our data indicated that 87.7% of the soybean cDNA clones contain complete coding sequences in addition to 5′- and 3′-untranslated regions. All of the obtained data confirmed that our collection of soybean full-length cDNAs covers a wide variety of genes. Comparative analysis between the derived sequences from soybean and Arabidopsis, rice or other legumes data revealed that some specific genes were involved in our collection and a large part of them could be annotated to unknown functions. A large set of soybean full-length cDNA clones reported in this study will serve as a useful resource for gene discovery from soybean and will also aid a precise annotation of the soybean genome

Rice Stress-Resistant SNP Database.

BACKGROUND:Rice (Oryza sativa L.) yield is limited inherently by environmental stresses, including biotic and abiotic stresses. Thus, it is of great importance to perform in-depth explorations on the genes that are closely associated with the stress-resistant traits in rice. The existing rice SNP databases have made considerable contributions to rice genomic variation information but none of them have a particular focus on integrating stress-resistant variation and related phenotype data into one web resource. RESULTS:Rice Stress-Resistant SNP database (http://bioinformatics.fafu.edu.cn/RSRS) mainly focuses on SNPs specific to biotic and abiotic stress-resistant ability in rice, and presents them in a unified web resource platform. The Rice Stress-Resistant SNP (RSRS) database contains over 9.5 million stress-resistant SNPs and 797 stress-resistant candidate genes in rice, which were detected from more than 400 stress-resistant rice varieties. We incorporated the SNPs function, genome annotation and phenotype information into this database. Besides, the database has a user-friendly web interface for users to query, browse and visualize a specific SNP efficiently. RSRS database allows users to query the SNP information and their relevant annotations for individual variety or more varieties. The search results can be visualized graphically in a genome browser or displayed in formatted tables. Users can also align SNPs between two or more rice accessions. CONCLUSION:RSRS database shows great utility for scientists to further characterize the function of variants related to environmental stress-resistant ability in rice