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High-throughput identification of C/D box snoRNA targets with CLIP and RiboMeth-seq

Gumienny, Rafal and Jedlinski, Dominik J. and Schmidt, Alexander and Gypas, Foivos and Martin, Georges and Vina-Vilaseca, Arnau and Zavolan, Mihaela. (2017) High-throughput identification of C/D box snoRNA targets with CLIP and RiboMeth-seq. Nucleic Acids Research, 45 (5). pp. 2341-2353.

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Abstract

High-throughput sequencing has greatly facilitated the discovery of long and short non-coding RNAs (ncRNAs), which frequently guide ribonucleoprotein complexes to RNA targets, to modulate their metabolism and expression. However, for many ncRNAs, the targets remain to be discovered. In this study, we developed computational methods to map C/D box snoRNA target sites using data from core small nucleolar ribonucleoprotein crosslinking and immunoprecipitation and from transcriptome-wide mapping of 2'-O-ribose methylation sites. We thereby assigned the snoRNA guide to a known methylation site in the 18S rRNA, we uncovered a novel partially methylated site in the 28S ribosomal RNA, and we captured a site in the 28S rRNA in interaction with multiple snoRNAs. Although we also captured mRNAs in interaction with snoRNAs, we did not detect 2'-O-methylation of these targets. Our study provides an integrated approach to the comprehensive characterization of 2'-O-methylation targets of snoRNAs in species beyond those in which these interactions have been traditionally studied and contributes to the rapidly developing field of 'epitranscriptomics'.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (Zavolan)
05 Faculty of Science > Departement Biozentrum > Services Biozentrum > Proteomics (Schmidt)
UniBasel Contributors:Zavolan, Mihaela and Gumienny, Rafal Wojciech and Jedlinski, Dominik and Schmidt, Alexander and Gypas, Foivos and Martin, Georges and Vina Vilaseca, Arnau
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Oxford University Press
ISSN:0301-5610
e-ISSN:1362-4962
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
Identification Number:
Last Modified:17 May 2018 08:45
Deposited On:26 Oct 2017 15:17

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