Goda Hideki, Sasaki Eriko, Akiyama Kenji, Maruyama-Nakashita Akiko, Nakabayashi Kazumi, Li Weiqiang, Ogawa Mikihiro, Yamauchi Yukika, Preston Jeremy, Aoki Ko, Kiba Takatoshi, Takatsuto Suguru, Fujioka Shozo, Asami Tadao, Nakano Takeshi, Kato Hisashi, Mizuno Takeshi, Sakakibara Hitoshi, Yamaguchi Shinjiro, Nambara Eiji, Kamiya Yuji, Takahashi Hideki, Hirai Masami Yokota, Sakurai Tetsuya, Shinozaki Kazuo, Saito Kazuki, Yoshida Shigeo, Shimada Yukihisa
RIKEN Plant Science Center, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.
Plant J. 2008 Aug;55(3):526-42. doi: 10.1111/j.0960-7412.2008.03510.x.
We analyzed global gene expression in Arabidopsis in response to various hormones and in related experiments as part of the AtGenExpress project. The experimental agents included seven basic phytohormones (auxin, cytokinin, gibberellin, brassinosteroid, abscisic acid, jasmonate and ethylene) and their inhibitors. In addition, gene expression was investigated in hormone-related mutants and during seed germination and sulfate starvation. Hormone-inducible genes were identified from the hormone response data. The effects of each hormone and the relevance of the gene lists were verified by comparing expression profiles for the hormone treatments and related experiments using Pearson's correlation coefficient. This approach was also used to analyze the relationships among expression profiles for hormone responses and those included in the AtGenExpress stress-response data set. The expected correlations were observed, indicating that this approach is useful to monitor the hormonal status in the stress-related samples. Global interactions among hormones-inducible genes were analyzed in a pairwise fashion, and several known and novel hormone interactions were detected. Genome-wide transcriptional gene-to-gene correlations, analyzed by hierarchical cluster analysis (HCA), indicated that our data set is useful for identification of clusters of co-expressed genes, and to predict the functions of unknown genes, even if a gene's function is not directly related to the experiments included in AtGenExpress. Our data are available online from AtGenExpressJapan; the results of genome-wide HCA are available from PRIMe. The data set presented here will be a versatile resource for future hormone studies, and constitutes a reference for genome-wide gene expression in Arabidopsis.
作为拟南芥基因表达谱计划（AtGenExpress）项目的一部分，我们分析了拟南芥在各种激素作用下以及相关实验中的全基因组基因表达情况。实验试剂包括七种基本植物激素（生长素、细胞分裂素、赤霉素、油菜素内酯、脱落酸、茉莉酸和乙烯）及其抑制剂。此外，还研究了激素相关突变体、种子萌发过程和硫酸盐饥饿条件下的基因表达。从激素反应数据中鉴定出激素诱导基因。通过使用皮尔逊相关系数比较激素处理和相关实验的表达谱，验证了每种激素的作用以及基因列表的相关性。该方法还用于分析激素反应的表达谱与AtGenExpress应激反应数据集中的表达谱之间的关系。观察到了预期的相关性，表明该方法可用于监测应激相关样本中的激素状态。以成对方式分析了激素诱导基因之间的全局相互作用，检测到了一些已知和新的激素相互作用。通过层次聚类分析（HCA）分析的全基因组转录基因与基因之间的相关性表明，我们的数据集可用于识别共表达基因簇，并预测未知基因的功能，即使一个基因的功能与AtGenExpress中包含的实验没有直接关系。我们的数据可从AtGenExpressJapan在线获取；全基因组HCA的结果可从PRIMe获取。这里呈现的数据集将是未来激素研究的通用资源，并构成拟南芥全基因组基因表达的参考。
