Database Commons

a catalog of worldwide biological databases

The Rice Online expression profiles Array Database version 2 (ROADv2; https://roadv2.khu.ac.kr ), an enhanced database for rice gene expression analysis, transitions from the previous microarray platforms to RNA-Seq data for improved accuracy. It encompasses 328 datasets from diverse experimental series, including anatomy, abiotic and biotic stress, hormone response, and nutrient starvation. Key updates include gene annotation (upgraded to RGAP version 7) and functional enrichment data (utilizing recent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) versions). ROADv2 debuts protein-protein interaction (PPI) network analysis and broadens interactive visualization across all features. Gene expression data are segmented into anatomy, biotic, abiotic, nutrient, and hormone categories, with user-interactive heatmaps displaying normalized log2 expression and log2 fold change data. Coexpression correlation analysis identifies genes with similar patterns, visualized through interactive network graphs. Functional enrichment tools display GO and KEGG analyses with significant terms emphasized in various formats. PPI network analysis integrates coexpression data to enhance prediction accuracy. Validation studies affirm the database's reliability, demonstrating reproducible tissue/organ-specific expression patterns. ROADv2 provides a comprehensive resource for rice functional genomics studies.

BACKGROUND: Microarray technologies facilitate high-throughput gene expression analysis. However, the diversity of platforms for rice gene expression analysis hinders efficient analysis. Tools to broadly integrate microarray data from different platforms are needed.
RESULTS: In this study, we developed the Rice Oligonucleotide Array Database (ROAD, http://www.ricearray.org) to explore gene expression across 1,867 publicly available rice microarray hybridizations. The ROAD's user-friendly web interface and variety of visualization tools facilitate the extraction of gene expression profiles using gene and microarray element identifications. The ROAD supports meta-analysis of genes expressed in different tissues and at developmental stages. Co-expression analysis tool provides information on co-regulation between genes under general, abiotic and biotic stress conditions. Additionally, functional analysis tools, such as Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthology, are embedded in the ROAD. These tools facilitate the identification of meaningful biological patterns in a list of query genes.
CONCLUSIONS: The Rice Oligonucleotide Array Database provides comprehensive gene expression profiles for all rice genes, and will be a useful resource for researchers of rice and other grass species.