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Combinatorial network of primary and secondary microRNA-driven regulatory mechanisms.

机译:一级和二级microRNA驱动的调控机制的组合网络。

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Recent miRNA transfection experiments show strong evidence that miRNAs influence not only their target but also non-target genes; the precise mechanism of the extended regulatory effects of miRNAs remains to be elucidated. A hypothetical two-layer regulatory network in which transcription factors (TFs) function as important mediators of miRNA-initiated regulatory effects was envisioned, and a comprehensive strategy was developed to map such miRNA-centered regulatory cascades. Given gene expression profiles after miRNA-perturbation, along with putative miRNA-gene and TF-gene regulatory relationships, highly likely degraded targets were fetched by a non-parametric statistical test; miRNA-regulated TFs and their downstream targets were mined out through linear regression modeling. When applied to 53 expression datasets, this strategy discovered combinatorial regulatory networks centered around 19 miRNAs. A tumor-related regulatory network was diagrammed as an example, with the important tumor-related regulators TP53 and MYC playing hub connector roles. A web server is provided for query and analysis of all reported data in this article. Our results reinforce the growing awareness that non-coding RNAs may play key roles in the transcription regulatory network. Our strategy could be applied to reveal conditional regulatory pathways in many more cellular contexts.
机译:最近的miRNA转染实验表明,有力的证据表明miRNA不仅影响其靶标,而且还影响非靶标基因。 miRNA扩展调控作用的确切机制仍有待阐明。设想了一个假设的两层调节网络,其中转录因子(TFs)作为miRNA引发的调节作用的重要介体,并且开发了一种全面的策略来绘制这种以miRNA为中心的调节级联。给定miRNA扰动后的基因表达谱,以及推定的miRNA基因和TF基因调控关系,通过非参数统计测试可以获取很可能降解的靶标。通过线性回归模型挖掘出miRNA调控的TF及其下游靶标。当应用于53个表达数据集时,该策略发现了以19个miRNA为中心的组合调控网络。以一个与肿瘤相关的调节网络为例,重要的与肿瘤相关的调节器TP53和MYC发挥了集线器连接器的作用。本文提供了一个Web服务器,用于查询和分析所有报告的数据。我们的结果增强了人们日益增长的认识,即非编码RNA可能在转录调控网络中发挥关键作用。我们的策略可用于揭示更多细胞环境中的条件调节途径。

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