Identification of microRNA-regulated gene networks by expression analysis of target genes.
Identification of microRNA-regulated gene networks by expression analysis of target genes.
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DOI：
10.1101/gr.130435.111
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发表时间：
2012-06
期刊：
影响因子：
7
通讯作者：
Banfi S
中科院分区：
文献类型：
--
作者：
Gennarino VA;D'Angelo G;Dharmalingam G;Fernandez S;Russolillo G;Sanges R;Mutarelli M;Belcastro V;Ballabio A;Verde P;Sardiello M;Banfi S
MicroRNA (miRNA) 和转录因子通过其特定的基因调控网络控制真核细胞的增殖、分化和代谢。然而，与转录因子不同，目前我们对 miRNA 调控过程的了解还很有限。在这里，我们引入基因网络分析作为深入了解 miRNA 生物学的新方法。基于 miRNA 靶标共表达荟萃分析 (CoMeTa) 对所有人类 miRNA 进行系统分析，为 miRNA 分配高分辨率的生物学功能，并提供人类 miRNA 调控网络的全面、基因组规模的分析。此外，基因共靶向分析表明 miRNA 协同调节参与相似过程的基因组。我们通过关注三个特征较差的 miRNA（miR-519d/190/340）来实验验证 CoMeTa 程序，CoMeTa 预测它们与 TGFβ 通路相关。使用肺腺癌 A549 细胞作为模型系统，我们发现 miR-519d 和 miR-190 抑制 TGFβ 信号传导，而 miR-340 增强 TGFβ 信号传导及其对细胞增殖、形态和散射的影响。基于这些发现，我们将共表达分析形式化并提出作为第二代程序的通用范例，以识别真正的靶标并推断 miRNA 的生物学作用和网络群落。
MicroRNAs (miRNAs) and transcription factors control eukaryotic cell proliferation, differentiation, and metabolism through their specific gene regulatory networks. However, differently from transcription factors, our understanding of the processes regulated by miRNAs is currently limited. Here, we introduce gene network analysis as a new means for gaining insight into miRNA biology. A systematic analysis of all human miRNAs based on Co-expression Meta-analysis of miRNA Targets (CoMeTa) assigns high-resolution biological functions to miRNAs and provides a comprehensive, genome-scale analysis of human miRNA regulatory networks. Moreover, gene cotargeting analyses show that miRNAs synergistically regulate cohorts of genes that participate in similar processes. We experimentally validate the CoMeTa procedure through focusing on three poorly characterized miRNAs, miR-519d/190/340, which CoMeTa predicts to be associated with the TGFβ pathway. Using lung adenocarcinoma A549 cells as a model system, we show that miR-519d and miR-190 inhibit, while miR-340 enhances TGFβ signaling and its effects on cell proliferation, morphology, and scattering. Based on these findings, we formalize and propose co-expression analysis as a general paradigm for second-generation procedures to recognize bona fide targets and infer biological roles and network communities of miRNAs.
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影响因子：
64.8
作者：
Baek, Daehyun;Villen, Judit;Shin, Chanseok;Camargo, Fernando D.;Gygi, Steven P.;Bartel, David P.
通讯作者：
Bartel, David P.
影响因子：
14.9
作者：
Grillo G;Turi A;Licciulli F;Mignone F;Liuni S;Banfi S;Gennarino VA;Horner DS;Pavesi G;Picardi E;Pesole G
通讯作者：
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影响因子：
7
作者：
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通讯作者：
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影响因子：
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作者：
Kapinas, Kristina;Kessler, Catherine B.;Delany, Anne M.
通讯作者：
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影响因子：
14.9
作者：
Betel D;Wilson M;Gabow A;Marks DS;Sander C
通讯作者：
Sander C