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

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


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


microRNAs Ago CLIP-Seq starBase RNA-binding proteins miRNA-target interactions Cancer-associated miRNAs Degradome-Seq Post-transcriptional regulation deepView 



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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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.RNA Information Center, Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory for BiocontrolSun Yat-sen UniversityGuangzhouP. R. China
  2. 2.Biotechnology Research CenterSun Yat-sen UniversityGuangzhouP. R. China

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