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-...
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doaj-a795d72f226e46a8803f727538963f182021-05-04T23:57:48ZengeLife Sciences Publications LtdeLife2050-084X2015-08-01410.7554/eLife.05005Predicting effective microRNA target sites in mammalian mRNAsVikram Agarwal0George W Bell1Jin-Wu Nam2David P Bartel3Howard Hughes Medical Institute, Whitehead Institute for Biomedical Research, Cambridge, United States; Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, United StatesBioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, United StatesHoward Hughes Medical Institute, Whitehead Institute for Biomedical Research, Cambridge, United States; Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; Department of Life Science, College of Natural Sciences, Hanyang University, Seoul, KoreaHoward Hughes Medical Institute, Whitehead Institute for Biomedical Research, Cambridge, United States; Department of Biology, Massachusetts Institute of Technology, Cambridge, United StatesMicroRNA 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.https://elifesciences.org/articles/05005miRNA targetmiRNA-binding sitemiRNA target predictionpost-transcriptional gene regulation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Vikram Agarwal George W Bell Jin-Wu Nam David P Bartel |
spellingShingle |
Vikram Agarwal George W Bell Jin-Wu Nam David P Bartel Predicting effective microRNA target sites in mammalian mRNAs eLife miRNA target miRNA-binding site miRNA target prediction post-transcriptional gene regulation |
author_facet |
Vikram Agarwal George W Bell Jin-Wu Nam David P Bartel |
author_sort |
Vikram Agarwal |
title |
Predicting effective microRNA target sites in mammalian mRNAs |
title_short |
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_sort |
predicting effective microrna target sites in mammalian mrnas |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2015-08-01 |
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. |
topic |
miRNA target miRNA-binding site miRNA target prediction post-transcriptional gene regulation |
url |
https://elifesciences.org/articles/05005 |
work_keys_str_mv |
AT vikramagarwal predictingeffectivemicrornatargetsitesinmammalianmrnas AT georgewbell predictingeffectivemicrornatargetsitesinmammalianmrnas AT jinwunam predictingeffectivemicrornatargetsitesinmammalianmrnas AT davidpbartel predictingeffectivemicrornatargetsitesinmammalianmrnas |
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1721476760498864128 |