Exploring Tomato Gene Functions Based on Coexpression Modules Using Graph Clustering and Differential Coexpression Approaches
Exploring Tomato Gene Functions Based on Coexpression Modules Using Graph Clustering and Differential Coexpression Approaches
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DOI：
10.1104/pp.111.188367
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发表时间：
2012-04-01
期刊：
影响因子：
7.4
通讯作者：
Kusano, Miyako
中科院分区：
文献类型：
--
作者：
Fukushima, Atsushi;Nishizawa, Tomoko;Kusano, Miyako
基因间共表达分析为预测植物未知基因功能提供了基础信息，是一种很有前景的方法。我们研究了番茄（Solanum lycopersicum）基因表达的各种关联，以无偏的方式预测未知基因的功能。我们从公开可用的数据库和我们自己的杂交中获得了300多个微阵列，在这里，我们展示了番茄共表达网络和共表达模块。网络的拓扑特征是高度异构的。我们通过图聚类从数据集中提取了465个共表达模块，使用户可以有效地将图划分为一组聚类。其中88%是通过基因本体术语系统分配的。我们的方法揭示了番茄转录组数据中的功能模块；共表达模块的主要功能与生物学相关。我们还研究了由叶片、果实和根样本组成的数据集之间的差异共表达，以进一步了解番茄转录组。我们现在证明(1)重复基因，以及代谢基因，表现出少量但显著的差异共表达；(2)基因共表达的逆转发生在涉及番茄红素和类黄酮生物合成的两种代谢途径中。使用定量实时聚合酶链反应对六个选定基因的发现进行了独立的实验验证。我们的研究结果表明，差异共表达可能有助于研究代谢途径中的关键调控步骤。本文报道的方法和结果将有助于筛选候选基因，进一步进行番茄代谢功能基因组学研究。
Gene-to-gene coexpression analysis provides fundamental information and is a promising approach for predicting unknown gene functions in plants. We investigated various associations in the gene expression of tomato (Solanum lycopersicum) to predict unknown gene functions in an unbiased manner. We obtained more than 300 microarrays from publicly available databases and our own hybridizations, and here, we present tomato coexpression networks and coexpression modules. The topological characteristics of the networks were highly heterogenous. We extracted 465 total coexpression modules from the data set by graph clustering, which allows users to divide a graph effectively into a set of clusters. Of these, 88% were assigned systematically by Gene Ontology terms. Our approaches revealed functional modules in the tomato transcriptome data; the predominant functions of coexpression modules were biologically relevant. We also investigated differential coexpression among data sets consisting of leaf, fruit, and root samples to gain further insights into the tomato transcriptome. We now demonstrate that (1) duplicated genes, as well as metabolic genes, exhibit a small but significant number of differential coexpressions, and (2) a reversal of gene coexpression occurred in two metabolic pathways involved in lycopene and flavonoid biosynthesis. Independent experimental verification of the findings for six selected genes was done using quantitative real-time polymerase chain reaction. Our findings suggest that differential coexpression may assist in the investigation of key regulatory steps in metabolic pathways. The approaches and results reported here will be useful to prioritize candidate genes for further functional genomics studies of tomato metabolism.