Comprehensive network analysis of anther-expressed genes in rice by the combination of 33 laser microdissection and 143 spatiotemporal microarrays.
Comprehensive network analysis of anther-expressed genes in rice by the combination of 33 laser microdissection and 143 spatiotemporal microarrays.
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DOI：
10.1371/journal.pone.0026162
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Watanabe M
中科院分区：
文献类型：
--
作者：
Aya K;Suzuki G;Suwabe K;Hobo T;Takahashi H;Shiono K;Yano K;Tsutsumi N;Nakazono M;Nagamura Y;Matsuoka M;Watanabe M
从大规模的转录组数据系统构建的共表达网络反映了具有相似表达模式的基因之间的相互作用和功能，是全面了解生物事件和挖掘新基因的有力工具。在拟南芥(一种双子叶模式植物)中，从非常大的微阵列数据集构建了高分辨率的共表达网络，这些网络作为在线信息资源公开可用。然而，到目前为止，水稻(模式单子叶植物)的转录组数据有限，这使得水稻研究人员很难实现可靠的共表达分析。在本研究中，我们利用44K安捷伦水稻基因芯片数据库进行了共表达网络分析，其中包括33个激光显微切割(LM)-花药基因芯片数据集，以及在RicexPro中存储的143个时空转录组数据集。通过皮尔逊相关系数(PCC)方法和基于相互等级(MR)的截断，从176个微阵列数据集生成的水稻共表达网络的整个数据包含24,258个基因和60,441个基因对。利用这些数据集，我们构建了花药中两个特定生物事件--减数分裂和花粉壁合成的高分辨率共表达网络。减数分裂网络包含许多已知或推测的减数分裂基因，包括与减数分裂起始和重组相关的基因。在花粉壁合成网络中，有效地鉴定了与孢粉素生物合成途径有关的几个候选基因。因此，这两个子网络是水稻共表达网络分析效率的重要例证。我们的共表达分析包括花药中花粉和绒毡层细胞的分离转录，这能够为水稻雄配子体发育过程中的转录调控提供准确的信息。本文提供的共表达网络数据为水稻研究人员阐明重要而复杂的生物学事件提供了有用的资源。
Co-expression networks systematically constructed from large-scale transcriptome data reflect the interactions and functions of genes with similar expression patterns and are a powerful tool for the comprehensive understanding of biological events and mining of novel genes. In Arabidopsis (a model dicot plant), high-resolution co-expression networks have been constructed from very large microarray datasets and these are publicly available as online information resources. However, the available transcriptome data of rice (a model monocot plant) have been limited so far, making it difficult for rice researchers to achieve reliable co-expression analysis. In this study, we performed co-expression network analysis by using combined 44 K agilent microarray datasets of rice, which consisted of 33 laser microdissection (LM)-microarray datasets of anthers, and 143 spatiotemporal transcriptome datasets deposited in RicexPro. The entire data of the rice co-expression network, which was generated from the 176 microarray datasets by the Pearson correlation coefficient (PCC) method with the mutual rank (MR)-based cut-off, contained 24,258 genes and 60,441 genes pairs. Using these datasets, we constructed high-resolution co-expression subnetworks of two specific biological events in the anther, “meiosis” and “pollen wall synthesis”. The meiosis network contained many known or putative meiotic genes, including genes related to meiosis initiation and recombination. In the pollen wall synthesis network, several candidate genes involved in the sporopollenin biosynthesis pathway were efficiently identified. Hence, these two subnetworks are important demonstrations of the efficiency of co-expression network analysis in rice. Our co-expression analysis included the separated transcriptomes of pollen and tapetum cells in the anther, which are able to provide precise information on transcriptional regulation during male gametophyte development in rice. The co-expression network data presented here is a useful resource for rice researchers to elucidate important and complex biological events.
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