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.

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.

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.