Graduate School of Information Science, Tohoku University, 6-3-09 Aramaki-Aza-Aoba, Aoba-ku, Sendai 980-8679, Japan.
J Plant Res. 2010 May;123(3):311-9. doi: 10.1007/s10265-010-0333-6. Epub 2010 Apr 10.
Gene coexpression analyses are a powerful method to predict the function of genes and/or to identify genes that are functionally related to query genes. The basic idea of gene coexpression analyses is that genes with similar functions should have similar expression patterns under many different conditions. This approach is now widely used by many experimental researchers, especially in the field of plant biology. In this review, we will summarize recent successful examples obtained by using our gene coexpression database, ATTED-II. Specifically, the examples will describe the identification of new genes, such as the subunits of a complex protein, the enzymes in a metabolic pathway and transporters. In addition, we will discuss the discovery of a new intercellular signaling factor and new regulatory relationships between transcription factors and their target genes. In ATTED-II, we provide two basic views of gene coexpression, a gene list view and a gene network view, which can be used as guide gene approach and narrow-down approach, respectively. In addition, we will discuss the coexpression effectiveness for various types of gene sets.
基因共表达分析是一种强大的方法，可以预测基因的功能和/或识别与查询基因在功能上相关的基因。基因共表达分析的基本思想是，具有相似功能的基因在许多不同条件下应该具有相似的表达模式。这种方法现在被许多实验研究人员广泛使用，特别是在植物生物学领域。在这篇综述中，我们将总结使用我们的基因共表达数据库 ATTED-II 获得的最近的成功案例。具体来说，这些例子描述了新基因的鉴定，如复杂蛋白质的亚基、代谢途径中的酶和转运蛋白。此外，我们还将讨论一种新的细胞间信号因子的发现以及转录因子与其靶基因之间新的调控关系。在 ATTED-II 中，我们提供了基因共表达的两种基本视图，即基因列表视图和基因网络视图，它们可以分别作为引导基因方法和缩小范围方法使用。此外，我们还将讨论各种类型的基因集的共表达有效性。
