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 identi fied 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 coef ficients 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). © Springer Science+Business Media, LLC 2013.