C02
RiceFREND: Gene Expression Network Database of Oryza sativa ssp. japonica

Date: Saturday, January 12, 2013
Time: 1:45 PM
Room: California
Nobukazu Namiki , Mitsubishi Space Software Co.,Ltd., Tsukuba, Ibaraki, Japan
Yutaka Sato , National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan
Hinako Takehisa , National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan
Kaori Kamatsuki , Mitsubishi Space Software Co.,Ltd., Tsukuba, Ibaraki, Japan
Minami Hiroshi , Mitsubishi Space Software Co., Ltd., Tsukuba, Ibaraki, Japan
Hiroshi Ikawa , Mitsubishi Space Software Co.,Ltd., Tsukuba, Ibaraki, Japan
Hajime Ohyanagi , Mitsubishi Space Software Co., Ltd., Tsukuba, Ibaraki, Japan
Kazuhiko Sugimoto , National Institute of Agrobiological Science, Tsukuba, Ibaraki, Japan
Baltazar Antonio , National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan
Yoshiaki Nagamura , National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan
Gene coexpression network analysis is a powerful approach to identify gene functions. We have developed a gene coexpresion database of rice, RiceFREND (http://ricefrend.dna.affrc.go.jp/), to provide a platform for prediction of gene function based on similarity of expression across a wide range of biological conditions. The coexpression analysis of 27,201 genes was based on 815 microarray data of organs and tissues at specific stages of growth and development, organs obtained throughout the entire growth in the field from transplanting until harvesting, and plants subjected to treatment with various plant hormones. The database is provided with two search options, namely, ‘single guide gene’ and ‘multiple guide gene’ searches that generate a tabular list of genes with highly correlated expression patterns and a user-friendly web interface for analysis of gene coexpression networks. Three gene network viewers, namely HyperTree, Cytoscape Web and Graphviz allow the users to visualize and interpret the coexpression data more efficiently. In addition, we incorporated analysis tools for identification of enriched GO terms and cis-elements for better prediction of biological functions associated with the coexpressed genes. These features allow users to clarify gene functions and gene regulatory networks that could lead to a more thorough understanding of many complex agronomic traits in rice.