title: Transcriptome coexpression analysis using ATTED-II for integrated transcriptomic/metabolomic analysis.
abstract: Transcriptome coexpression analysis is an excellent tool for predicting the physiological functions of genes. It is based on the "guilt-by-association" principle. Generally, genes involved in certain metabolic processes are coordinately regulated. In other words, coexpressed genes tend to be involved in common or closely related biological processes. Genes of which the metabolic functions have been identified are preselected as "guide" genes and are used to check the transcriptome coexpression fidelity to the pathway and to determine the threshold value of correlation coefficients to be used for subsequent analysis. The coexpression analysis provides a network of the relationships between "guide" and candidate genes that serves to create the criteria by which gene functions can be predicted. Here we describe a procedure to narrow down the number of candidate genes by means of the publicly available database, designated Arabidopsis thaliana trans-factor and cis-element prediction database (ATTED-II).
authors.affiliation: RIKEN Plant Science Center, Yokohama, Japan.
authors.forename: Keiko
authors.initials: K
authors.lastname: Yonekura-Sakakibara
authors.forename: Kazuki
authors.initials: K
authors.lastname: Saito
mesh_terms: D017360:Arabidopsis / Q000235:genetics* / Q000378:metabolism; D029681:Arabidopsis Proteins / Q000235:genetics / Q000378:metabolism*; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D017343:Genes, Plant; D055442:Metabolome; D058977:Molecular Sequence Annotation; D012984:Software; D059467:Transcriptome
chemical_list: D029681:Arabidopsis Proteins