OryzaExpress：An integrated Database for Gene Expression Networks in Rice

Similarity of gene expression profiles provides important clues for understanding biological functions of genes, biological processes and metabolic pathways related with genes. Gene expression network (GEN) is a powerful tool to simultaneously grasp such similarities of expression profiles among genes. For GEN construction, Pearson correlation coefficient (PCC) has been widely used as an index to evaluate similarities of expression profiles for gene pairs. However, calculation of PCC for all gene pairs requires large amounts of both time and computer resources. Based on correspondence analysis (CA), we developed a precise and efficient new method for GEN construction, which takes minimal time even for large-scale expression data with general computational circumstances. Using the new method, we constructed rice GENs from large-scale microarray data stored in NCBI GEO. The 871 microarray expression data (Affymetrix) were normalized in logarithmic scale by the robust multi-array average (RMA) method. To evaluate similarities of gene expression profiles, we used a new index DCA, which is defined as the distance between genes in a low dimensional space (projection) obtained from CA. We then, collected and integrated rice omics annotations in public and distinct databases. The integrated information contains annotations of genome, transcriptome and metabolic pathways. We have updated the integrated database OryzaExpress for browsing GENs and providing principal omics annotations with a graphical and interactive viewer. OryzaExpress is a comprehensive rice database that exploits powerful omics approaches from all perspectives in plant science. http://riceball.lab.nig.ac.jp/oryzaexpress/ http://bioinf.mind.meiji.ac.jp/OryzaExpress/ (mirror site)