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Construction and analysis of microRNA-transcription factor regulation network in arabidopsis

机译:拟南芥microRNA转录因子调控网络的构建与分析

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摘要

Transcription factors (TFs) and microRNAs (miRNAs) are two major types of regulators of gene expression, at transcriptional and post-transcriptional levels, respectively. By gathering their gene regulatory relationships, gene regulatory networks (GRNs) could be formed. A network motif is a type of connection pattern among a set of nodes which appears significantly more frequently than in random networks. Investigations of the network motifs often yield biological insights into the nature of the network. The previous study on miRNA??TF regulation networks concentrated on animals, and relied heavily on computational predictions. The authors collected data concerning miRNA regulation and transcriptional regulation relationships in Arabidopsis from publicly available databases, and further incorporated them with the protein??protein interaction data. All the data in the author??s collection are supported by experiments. They screened the network motifs, whose size ranges between 1 and 4. The biological implications of the motifs were further analysed, and a flower development related network was constructed as an example. In this example, they illustrated the relevance of the network with the given process, and proposed the association of several genes with flowers by a network cluster identification. In this study, they analysed the properties of the GRN in Arabidopsis, and discussed their biological implications, as well as their potential applications.
机译:转录因子(TFs)和microRNA(miRNA)是两种主要的基因表达调节剂,分别处于转录水平和转录后水平。通过收集它们的基因调控关系,可以形成基因调控网络(GRN)。网络主题是一组节点之间的连接模式,与随机网络相比,其出现频率更高。对网络图案的调查通常会产生对网络本质的生物学见解。先前关于miRNA ?? TF调控网络的研究主要集中在动物身上,并严重依赖于计算预测。作者从公开的数据库中收集了拟南芥中有关miRNA调控和转录调控关系的数据,并将其与蛋白质-蛋白质相互作用数据结合在一起。实验中支持了作者集合中的所有数据。他们筛选了大小在1到4之间的网络图案。进一步分析了这些图案的生物学含义,并构建了一个与花卉发育相关的网络作为示例。在此示例中,他们说明了网络与给定过程的相关性,并通过网络簇识别提出了几种基因与花的关联。在这项研究中,他们分析了拟南芥中GRN的特性,并讨论了它们的生物学意义以及潜在应用。

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  • 来源
    《Systems Biology, IET》 |2014年第3期|76-86|共11页
  • 作者

    Tang L.; Zhang Z.; Gu P.; Chen M.;

  • 作者单位

    Department of Bioinformatics, College of Life Sciences, People??s Republic China|c|;

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  • 正文语种 eng
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