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Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks
RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitat...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4861959/ https://www.ncbi.nlm.nih.gov/pubmed/27161996 http://dx.doi.org/10.1038/srep25711 |
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author | Nishtala, Sneha Neelamraju, Yaseswini Janga, Sarath Chandra |
author_facet | Nishtala, Sneha Neelamraju, Yaseswini Janga, Sarath Chandra |
author_sort | Nishtala, Sneha |
collection | PubMed |
description | RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional networks. |
format | Online Article Text |
id | pubmed-4861959 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48619592016-05-23 Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks Nishtala, Sneha Neelamraju, Yaseswini Janga, Sarath Chandra Sci Rep Article RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional networks. Nature Publishing Group 2016-05-10 /pmc/articles/PMC4861959/ /pubmed/27161996 http://dx.doi.org/10.1038/srep25711 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Nishtala, Sneha Neelamraju, Yaseswini Janga, Sarath Chandra Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
title | Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
title_full | Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
title_fullStr | Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
title_full_unstemmed | Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
title_short | Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
title_sort | dissecting the expression relationships between rna-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4861959/ https://www.ncbi.nlm.nih.gov/pubmed/27161996 http://dx.doi.org/10.1038/srep25711 |
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