Combinatorial network of primary and secondary microRNA-driven regulatory mechanisms.
Combinatorial network of primary and secondary microRNA-driven regulatory mechanisms.
复制标题
microRNA驱动的初级和次级调节机制的组合网络
DOI：
10.1093/nar/gkp638
复制
发表时间：
2009-10
影响因子：
14.9
通讯作者：
Li YX
中科院分区：
文献类型：
--
作者：
Tu K;Yu H;Hua YJ;Li YY;Liu L;Xie L;Li YX
最近的miRNA转染实验表明，有力的证据表明，miRNA不仅影响其靶基因，而且影响非靶基因; miRNA的扩展调节作用的精确机制仍有待阐明。设想了一个假设的双层调控网络，其中转录因子（TF）作为miRNA启动的调控效应的重要介质发挥作用，并开发了一种全面的策略来绘制这种以miRNA为中心的调控级联。通过非参数统计检验，得到miRNA干扰后的基因表达谱，沿着假定的miRNA-基因和TF-基因调控关系，提取高度可能降解的靶标;通过线性回归建模，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miRNAs为中心的组合调控网络。以肿瘤相关调控网络为例，其中重要的肿瘤相关调控因子TP 53和MYC扮演着枢纽连接器的角色。本文提供了一个Web服务器，用于查询和分析所有报告数据。我们的研究结果加强了人们对非编码RNA可能在转录调控网络中发挥关键作用的认识。我们的策略可以应用于揭示更多细胞环境中的条件调控途径。
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.
登录
查看更多内容
影响因子：
14.9
作者：
Wang X;Wang X
通讯作者：
Wang X
影响因子：
11.2
作者：
Sampson, Valerie B.;Rong, Nancy H.;Krueger, Leslie J.
通讯作者：
Krueger, Leslie J.
影响因子：
64.8
作者：
O'Donnell, KA;Wentzel, EA;Mendell, JT
通讯作者：
Mendell, JT
影响因子：
64.8
作者：
He, Lin;He, Xingyue;Hannon, Gregory J.
通讯作者：
Hannon, Gregory J.
影响因子：
64.5
作者：
Lewis, BP;Shih, IH;Burge, CB
通讯作者：
Burge, CB