Global landscape of a co-expressed gene network in barley and its application to gene discovery in Triticeae crops.
Global landscape of a co-expressed gene network in barley and its application to gene discovery in Triticeae crops.
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DOI：
10.1093/pcp/pcr035
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发表时间：
2011-05
影响因子：
4.9
通讯作者：
Shinozaki K
中科院分区：
文献类型：
--
作者：
Mochida K;Uehara-Yamaguchi Y;Yoshida T;Sakurai T;Shinozaki K
积累的转录组数据可用于研究涉及各种生物系统的基因调控网络。从全面收集的转录组数据集生成的共表达分析数据集现在代表了能够促进发现具有密切相关表达模式的基因的有效资源。为了构建大麦的共表达网络，我们分析了45个公开的实验系列，这些实验系列由1，347组大麦基因芯片数据组成。基于基因间的加权相关系数，构建了一个全局大麦共表达网络，并将其划分为子网络模块簇。由此产生的集群是大麦转录组中的功能调控模块的候选者。为了注释每个模块，我们使用拟南芥和二穗短柄草中的基因进行比较注释。大麦和两个模式物种之间的比较分析的基础上，我们调查的功能特性的基因本体论（GO）的条款的代表性分布。已鉴定出参与干旱胁迫响应和纤维素生物合成的模块puplant。这些模块进行了讨论，以证明共表达分析的有效性。此外，我们应用共表达基因的数据集结合比较分析，试图发现潜在的小麦属特异性网络模块。这些结果表明，大麦转录组的共表达网络的分析与比较分析一起，应该促进大麦基因发现的过程。此外，所获得的见解应转移到小麦族植物的调查。本分析中生成的相关数据集可在http://coexpression.psc.riken.jp/barley/上公开访问。
Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression network for barley, we analyzed 45 publicly available experimental series, which are composed of 1,347 sets of GeneChip data for barley. On the basis of a gene-to-gene weighted correlation coefficient, we constructed a global barley co-expression network and classified it into clusters of subnetwork modules. The resulting clusters are candidates for functional regulatory modules in the barley transcriptome. To annotate each of the modules, we performed comparative annotation using genes in Arabidopsis and Brachypodium distachyon. On the basis of a comparative analysis between barley and two model species, we investigated functional properties from the representative distributions of the gene ontology (GO) terms. Modules putatively involved in drought stress response and cellulose biogenesis have been identified. These modules are discussed to demonstrate the effectiveness of the co-expression analysis. Furthermore, we applied the data set of co-expressed genes coupled with comparative analysis in attempts to discover potentially Triticeae-specific network modules. These results demonstrate that analysis of the co-expression network of the barley transcriptome together with comparative analysis should promote the process of gene discovery in barley. Furthermore, the insights obtained should be transferable to investigations of Triticeae plants. The associated data set generated in this analysis is publicly accessible at http://coexpression.psc.riken.jp/barley/.
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影响因子：
9.5
作者：
Moreno-Risueno MA;Busch W;Benfey PN
通讯作者：
Benfey PN
影响因子：
4.9
作者：
Hamada, Kazuki;Hongo, Kohei;Yano, Kentaro
通讯作者：
Yano, Kentaro
影响因子：
5.3
作者：
Mochida, Keiichi;Saisho, Daisuke;Shinozaki, Kazuo
通讯作者：
Shinozaki, Kazuo
影响因子：
14.9
作者：
Barrett T;Troup DB;Wilhite SE;Ledoux P;Rudnev D;Evangelista C;Kim IF;Soboleva A;Tomashevsky M;Marshall KA;Phillippy KH;Sherman PM;Muertter RN;Edgar R
通讯作者：
Edgar R
影响因子：
14.9
作者：
Barrett T;Troup DB;Wilhite SE;Ledoux P;Evangelista C;Kim IF;Tomashevsky M;Marshall KA;Phillippy KH;Sherman PM;Muertter RN;Holko M;Ayanbule O;Yefanov A;Soboleva A
通讯作者：
Soboleva A