Construction of citrus gene coexpression networks from microarray data using random matrix theory.
Construction of citrus gene coexpression networks from microarray data using random matrix theory.
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DOI：
10.1038/hortres.2015.26
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发表时间：
2015
影响因子：
8.7
通讯作者：
Gmitter FG Jr
中科院分区：
文献类型：
--
作者：
Du D;Rawat N;Deng Z;Gmitter FG Jr
柑橘基因组测序完成后，基因功能注释成为新的挑战。基因共表达分析可用于使用公开可得的微阵列数据集的功能注释。本研究利用230个甜橙子（Citrus sinensis）基因芯片构建了7个共表达网络，包括1个条件无关网络和6个条件依赖网络（柑橘溃疡病、黄龙病、叶片、果皮、果肉和果肉）。总的来说，这些网络包含6256个节点（基因）中的37633条边，占柑橘微阵列可测基因的52.11%。然后，这些网络划分功能模块，使用马尔可夫聚类算法。分别检测到343个和60个模块的基因本体生物过程术语和KEGG途径术语。最后，使用371个基因的另一表达数据对这些网络进行独立验证。该研究为柑橘的功能分析提供了新的靶点。
After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.