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Discovery of microRNA Regulatory Networks by Integrating Multidimensional High-Throughput Data

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MicroRNA Cancer Regulation

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 774))

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/.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (No. 30830066, 30900820); Ministry of Science and Technology of China, National Basic Research Program (No. 2011CB811300); the funds from Guangdong Province (No. S2012010010510); The project of Science and Technology New Star in ZhuJiang Guangzhou city (No. 2012J2200025); Fundamental Research Funds for the Central Universities (No. 2011330003161070); China Postdoctoral Science Foundation (No. 200902348).

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Authors and Affiliations

  1. RNA Information Center, Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou, 510275, P. R. China

    Jian-Hua Yang & Liang-Hu Qu

  2. Biotechnology Research Center, Sun Yat-sen University, Guangzhou, 510275, P. R. China

    Liang-Hu Qu

Authors
  1. Jian-Hua Yang
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  2. Liang-Hu Qu
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Correspondence to Liang-Hu Qu .

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Editors and Affiliations

  1. Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany

    Ulf Schmitz

  2. Dept. of Systems Biology and Bioinformat, Universität Rostock Institut of Computer Science, Rostock, Germany

    Olaf Wolkenhauer

  3. Rostock, Germany

    Julio Vera

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Yang, JH., Qu, LH. (2013). Discovery of microRNA Regulatory Networks by Integrating Multidimensional High-Throughput Data. In: Schmitz, U., Wolkenhauer, O., Vera, J. (eds) MicroRNA Cancer Regulation. Advances in Experimental Medicine and Biology, vol 774. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5590-1_13

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