Cargando…

CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome

Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We pr...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Zijun, Xing, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766199/
https://www.ncbi.nlm.nih.gov/pubmed/28934506
http://dx.doi.org/10.1093/nar/gkx646
_version_ 1783292333263945728
author Zhang, Zijun
Xing, Yi
author_facet Zhang, Zijun
Xing, Yi
author_sort Zhang, Zijun
collection PubMed
description Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We present CLAM (CLIP-seq Analysis of Multi-mapped reads). CLAM uses an expectation–maximization algorithm to assign multi-mapped reads and calls peaks combining uniquely and multi-mapped reads. To demonstrate the utility of CLAM, we applied it to a wide range of public CLIP-seq/RIP-seq datasets involving numerous splicing factors, microRNAs and m(6)A RNA methylation. CLAM recovered a large number of novel RNA regulatory sites inaccessible by uniquely mapped reads. The functional significance of these sites was demonstrated by consensus motif patterns and association with alternative splicing (splicing factors), transcript abundance (AGO2) and mRNA half-life (m(6)A). CLAM provides a useful tool to discover novel protein–RNA interactions and RNA modification sites from CLIP-seq and RIP-seq data, and reveals the significant contribution of repetitive elements to the RNA regulatory landscape of the human transcriptome.
format Online
Article
Text
id pubmed-5766199
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-57661992018-01-19 CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome Zhang, Zijun Xing, Yi Nucleic Acids Res Computational Biology Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We present CLAM (CLIP-seq Analysis of Multi-mapped reads). CLAM uses an expectation–maximization algorithm to assign multi-mapped reads and calls peaks combining uniquely and multi-mapped reads. To demonstrate the utility of CLAM, we applied it to a wide range of public CLIP-seq/RIP-seq datasets involving numerous splicing factors, microRNAs and m(6)A RNA methylation. CLAM recovered a large number of novel RNA regulatory sites inaccessible by uniquely mapped reads. The functional significance of these sites was demonstrated by consensus motif patterns and association with alternative splicing (splicing factors), transcript abundance (AGO2) and mRNA half-life (m(6)A). CLAM provides a useful tool to discover novel protein–RNA interactions and RNA modification sites from CLIP-seq and RIP-seq data, and reveals the significant contribution of repetitive elements to the RNA regulatory landscape of the human transcriptome. Oxford University Press 2017-09-19 2017-08-09 /pmc/articles/PMC5766199/ /pubmed/28934506 http://dx.doi.org/10.1093/nar/gkx646 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computational Biology
Zhang, Zijun
Xing, Yi
CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome
title CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome
title_full CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome
title_fullStr CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome
title_full_unstemmed CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome
title_short CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome
title_sort clip-seq analysis of multi-mapped reads discovers novel functional rna regulatory sites in the human transcriptome
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766199/
https://www.ncbi.nlm.nih.gov/pubmed/28934506
http://dx.doi.org/10.1093/nar/gkx646
work_keys_str_mv AT zhangzijun clipseqanalysisofmultimappedreadsdiscoversnovelfunctionalrnaregulatorysitesinthehumantranscriptome
AT xingyi clipseqanalysisofmultimappedreadsdiscoversnovelfunctionalrnaregulatorysitesinthehumantranscriptome