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Circular RNAs pp 193–207Cite as

Discovering circRNA-microRNA Interactions from CLIP-Seq Data

Part of the Methods in Molecular Biology book series (MIMB,volume 1724)

Abstract

Circular RNAs (circRNAs) represent an abundant group of noncoding RNAs in eukaryotes and are emerging as important regulatory molecules in physiological and pathological processes. However, the precise mechanisms and functions of most of circRNAs remain largely unknown. In this chapter, we describe how to identify circRNA-microRNA interactions from Argonaute (AGO) cross-linking and immunoprecipitation followed by sequencing (CLIP-Seq) and RNA-Seq data using starBase platform and software. We developed three stand-alone computational software, including circSeeker, circAnno, and clipSearch, to identify and annotate circRNAs and their interactions with microRNAs (miRNAs). In addition, we developed interactive Web applications to evaluate circRNA-miRNA interactions identified from CLIP-Seq data and discover the miRNA-sponge circRNAs. starBase platform provides a genome browser to comparatively analyze these interactions at multiple levels. As a means of comprehensively integrating CLIP-Seq and RNA-Seq data, starBase platform is expected to reveal the regulatory networks involving miRNAs and circRNAs. The software and platform are available at http://starbase.sysu.edu.cn/circTools.php.

Key words

  • circRNA
  • CLIP-Seq
  • microRNA
  • Interactome
  • RNA-Seq
  • miRNA sponge

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (No. 31370791, 91440110); Funds from Guangdong Province (No. S2012010010510, S2013010012457); the project of Science and Technology New Star in ZhuJiang Guangzhou city (No. 2012J2200025); Fundamental Research Funds for the Central Universities (No. 2011330003161070, 14lgjc18); China Postdoctoral Science Foundation (No. 200902348); and seeding project fund at School of Medicine, South China University of Technology (yxy2016005). This research is supported in part by the Guangdong Province Key Laboratory of Computational Science and the Guangdong Province Computational Science Innovative Research Team.

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Authors and Affiliations

  1. School of Medicine, South China University of Technology, Guangzhou, People’s Republic of China

    Xiao-Qin Zhang

  2. Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Pok Fu Lam, Hong Kong

    Xiao-Qin Zhang

  3. Key Laboratory of Gene Engineering of the Ministry of Education, Guangzhou, People’s Republic of China

    Jian-Hua Yang

  4. State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou, People’s Republic of China

    Jian-Hua Yang

Authors
  1. Xiao-Qin Zhang
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  2. Jian-Hua Yang
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Corresponding author

Correspondence to Jian-Hua Yang .

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Editors and Affiliations

  1. Department of Internal Medicine III Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, Heidelberg, Germany

    Christoph Dieterich

  2. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany

    Argyris Papantonis

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Zhang, XQ., Yang, JH. (2018). Discovering circRNA-microRNA Interactions from CLIP-Seq Data. In: Dieterich, C., Papantonis, A. (eds) Circular RNAs. Methods in Molecular Biology, vol 1724. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7562-4_16

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  • DOI: https://doi.org/10.1007/978-1-4939-7562-4_16

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  • Publisher Name: Humana Press, New York, NY

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  • Online ISBN: 978-1-4939-7562-4

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