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Predicting effective microRNA target sites in mammalian mRNAs
MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4532895/ https://www.ncbi.nlm.nih.gov/pubmed/26267216 http://dx.doi.org/10.7554/eLife.05005 |
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author | Agarwal, Vikram Bell, George W Nam, Jin-Wu Bartel, David P |
author_facet | Agarwal, Vikram Bell, George W Nam, Jin-Wu Bartel, David P |
author_sort | Agarwal, Vikram |
collection | PubMed |
description | MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-canonical interactions. Here, we show that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical. Accordingly, we developed an improved quantitative model of canonical targeting, using a compendium of experimental datasets that we pre-processed to minimize confounding biases. This model, which considers site type and another 14 features to predict the most effectively targeted mRNAs, performed significantly better than existing models and was as informative as the best high-throughput in vivo crosslinking approaches. It drives the latest version of TargetScan (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks. DOI: http://dx.doi.org/10.7554/eLife.05005.001 |
format | Online Article Text |
id | pubmed-4532895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-45328952015-08-13 Predicting effective microRNA target sites in mammalian mRNAs Agarwal, Vikram Bell, George W Nam, Jin-Wu Bartel, David P eLife Computational and Systems Biology MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-canonical interactions. Here, we show that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical. Accordingly, we developed an improved quantitative model of canonical targeting, using a compendium of experimental datasets that we pre-processed to minimize confounding biases. This model, which considers site type and another 14 features to predict the most effectively targeted mRNAs, performed significantly better than existing models and was as informative as the best high-throughput in vivo crosslinking approaches. It drives the latest version of TargetScan (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks. DOI: http://dx.doi.org/10.7554/eLife.05005.001 eLife Sciences Publications, Ltd 2015-08-12 /pmc/articles/PMC4532895/ /pubmed/26267216 http://dx.doi.org/10.7554/eLife.05005 Text en © 2015, Agarwal et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Agarwal, Vikram Bell, George W Nam, Jin-Wu Bartel, David P Predicting effective microRNA target sites in mammalian mRNAs |
title | Predicting effective microRNA target sites in mammalian mRNAs |
title_full | Predicting effective microRNA target sites in mammalian mRNAs |
title_fullStr | Predicting effective microRNA target sites in mammalian mRNAs |
title_full_unstemmed | Predicting effective microRNA target sites in mammalian mRNAs |
title_short | Predicting effective microRNA target sites in mammalian mRNAs |
title_sort | predicting effective microrna target sites in mammalian mrnas |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4532895/ https://www.ncbi.nlm.nih.gov/pubmed/26267216 http://dx.doi.org/10.7554/eLife.05005 |
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