Yonekura-Sakakibara Keiko, Saito Kazuki
RIKEN Plant Science Center, Yokohama, Japan.
Methods Mol Biol. 2013;1011:317-26. doi: 10.1007/978-1-62703-414-2_25.
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).
转录组共表达分析是预测基因生理功能的一种优秀工具。它基于“关联有罪”原则。一般来说，参与特定代谢过程的基因是协同调控的。换句话说，共表达的基因往往参与共同或密切相关的生物学过程。已确定代谢功能的基因被预选为“引导”基因，并用于检查转录组共表达对该途径的保真度，以及确定用于后续分析的相关系数阈值。共表达分析提供了一个“引导”基因与候选基因之间关系的网络，该网络用于创建预测基因功能的标准。在此，我们描述一种通过公开可用数据库（称为拟南芥转录因子和顺式元件预测数据库（ATTED-II））来缩小候选基因数量的程序。
