Discovery of microRNA regulatory networks by integrating multidimensional high-throughput data
- PMID: 23377977
- DOI: 10.1007/978-94-007-5590-1_13
Discovery of microRNA regulatory networks by integrating multidimensional high-throughput data
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/ .
Similar articles
-
starBase: a database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data.Nucleic Acids Res. 2011 Jan;39(Database issue):D202-9. doi: 10.1093/nar/gkq1056. Epub 2010 Oct 30. Nucleic Acids Res. 2011. PMID: 21037263 Free PMC article.
-
Discovering circRNA-microRNA Interactions from CLIP-Seq Data.Methods Mol Biol. 2018;1724:193-207. doi: 10.1007/978-1-4939-7562-4_16. Methods Mol Biol. 2018. PMID: 29322451
-
starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data.Nucleic Acids Res. 2014 Jan;42(Database issue):D92-7. doi: 10.1093/nar/gkt1248. Epub 2013 Dec 1. Nucleic Acids Res. 2014. PMID: 24297251 Free PMC article.
-
The use of high-throughput sequencing methods for plant microRNA research.RNA Biol. 2015;12(7):709-19. doi: 10.1080/15476286.2015.1053686. RNA Biol. 2015. PMID: 26016494 Free PMC article. Review.
-
A tale of two sequences: microRNA-target chimeric reads.Genet Sel Evol. 2016 Apr 4;48:31. doi: 10.1186/s12711-016-0209-x. Genet Sel Evol. 2016. PMID: 27044644 Free PMC article. Review.
Cited by
-
miRsig: a consensus-based network inference methodology to identify pan-cancer miRNA-miRNA interaction signatures.Sci Rep. 2017 Jan 3;7:39684. doi: 10.1038/srep39684. Sci Rep. 2017. PMID: 28045122 Free PMC article.
-
Targeted deletion of miR-132/-212 impairs memory and alters the hippocampal transcriptome.Learn Mem. 2016 Jan 15;23(2):61-71. doi: 10.1101/lm.039578.115. Print 2016 Feb. Learn Mem. 2016. PMID: 26773099 Free PMC article.
-
Role of microRNAs in plant drought tolerance.Plant Biotechnol J. 2015 Apr;13(3):293-305. doi: 10.1111/pbi.12318. Epub 2015 Jan 13. Plant Biotechnol J. 2015. PMID: 25583362 Free PMC article. Review.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Research Materials