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通过整合多维高通量数据发现 microRNA 调控网络。

Discovery of microRNA regulatory networks by integrating multidimensional high-throughput data.

机构信息

Sun Yat-sen University, Guangzhou, People's Republic of China.

出版信息

Adv Exp Med Biol. 2013;774:251-66. doi: 10.1007/978-94-007-5590-1_13.

DOI:10.1007/978-94-007-5590-1_13
PMID:23377977
Abstract

MicroRNAs (miRNAs) are endogenous non-coding RNAs (ncRNAs) of approximately 22 nt that regulate the expression of a large fraction of genes by targeting messenger RNAs (mRNAs). However, determining the biologically significant targets of miRNAs is an ongoing challenge. In this chapter, we describe how to identify miRNA-target interactions and miRNA regulatory networks from high-throughput deep sequencing, CLIP-Seq (HITS-CLIP, PAR-CLIP) and degradome sequencing data using starBase platforms. In starBase, several web-based and stand-alone computational tools were developed to discover Argonaute (Ago) binding and cleavage sites, miRNA-target interactions, perform enrichment analysis of miRNA target genes in Gene Ontology (GO) categories and biological pathways, and identify combinatorial effects between Ago and other RNA-binding proteins (RBPs). Investigating target pathways of miRNAs in human CLIP-Seq data, we found that many cancer-associated miRNAs modulate cancer pathways. Performing an enrichment analysis of genes targeted by highly expressed miRNAs in the mouse brain showed that many miRNAs are involved in cancer-associated MAPK signaling and glioma pathways, as well as neuron-associated neurotrophin signaling and axon guidance pathways. Moreover, thousands of combinatorial binding sites between Ago and RBPs were identified from CLIP-Seq data suggesting RBPs and miRNAs coordinately regulate mRNA transcripts. As a means of comprehensively integrating CLIP-Seq and Degradome-Seq data, the starBase platform is expected to identify clinically relevant miRNA-target regulatory relationships, and reveal multi-dimensional post-transcriptional regulatory networks involving miRNAs and RBPs. starBase is available at http://starbase.sysu.edu.cn/ .

摘要

微小 RNA(miRNA)是大约 22 个核苷酸的内源性非编码 RNA(ncRNA),通过靶向信使 RNA(mRNA)来调节大量基因的表达。然而,确定 miRNA 的生物学意义靶标是一个持续的挑战。在本章中,我们描述了如何使用 starBase 平台从高通量深度测序、CLIP-Seq(HITS-CLIP、PAR-CLIP)和降解组测序数据中识别 miRNA-靶标相互作用和 miRNA 调控网络。在 starBase 中,开发了几个基于网络的和独立的计算工具,用于发现 Argonaute(Ago)结合和切割位点、miRNA-靶标相互作用、在基因本体论(GO)类别和生物途径中对 miRNA 靶基因进行富集分析,以及识别 Ago 和其他 RNA 结合蛋白(RBP)之间的组合效应。在人类 CLIP-Seq 数据中研究 miRNA 的靶标途径,我们发现许多与癌症相关的 miRNA 调节癌症途径。对在小鼠脑中高度表达的 miRNA 靶向的基因进行富集分析表明,许多 miRNA 参与癌症相关的 MAPK 信号和神经胶质瘤途径,以及神经元相关的神经营养因子信号和轴突导向途径。此外,从 CLIP-Seq 数据中鉴定出数千个 Ago 和 RBP 之间的组合结合位点,表明 RBP 和 miRNA 协同调节 mRNA 转录本。作为综合整合 CLIP-Seq 和 Degradome-Seq 数据的一种手段,starBase 平台有望识别具有临床意义的 miRNA-靶标调控关系,并揭示涉及 miRNA 和 RBP 的多维转录后调控网络。starBase 可在 http://starbase.sysu.edu.cn/ 获得。

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