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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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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 |
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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 |
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