Abstract
Recent advances in genomics and transcriptomics have yielded a vast amount of microarray data and have begun to deepen our understanding of biological systems. Gene coexpression across publicly available microarrays has demonstrated its usefulness for investigating transcriptome and for predicting unknown gene functions in different organisms from yeast to humans. In Oryza sativa, however, no overall coexpression-network module has been examined in detail. Here we present the coexpression clusters of rice genes based on unbiased graph clustering of the network of 4,495 genes. The coexpression network was constructed by using over 230 microarrays. The resultant network displayed several properties of complex networks such as the scale-free degree distribution. We detected 1,220 clusters using the DPClus algorithm that can extract densely connected clusters, and these were evaluated using the enrichment analysis of gene ontology. We conclude that this approach is important for generating experimentally testable hypotheses for uncharacterized gene functions in rice. The data are downloadable from the PRIMe website (http://prime.psc.riken.jp/rico/index.html).
