Unknown

Dataset Information

0

Predicting effective microRNA target sites in mammalian mRNAs.


ABSTRACT: 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.

SUBMITTER: Agarwal V 

PROVIDER: S-EPMC4532895 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

Predicting effective microRNA target sites in mammalian mRNAs.

Agarwal Vikram V   Bell George W GW   Nam Jin-Wu JW   Bartel David P DP  

eLife 20150812


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 can  ...[more]

Similar Datasets

| S-EPMC2587246 | biostudies-literature
| S-EPMC2909566 | biostudies-literature
| S-EPMC4578708 | biostudies-other
| S-EPMC1855297 | biostudies-literature
| S-EPMC1887587 | biostudies-literature
| S-EPMC5903666 | biostudies-literature
| S-EPMC3737542 | biostudies-literature
| S-EPMC2955701 | biostudies-literature
| S-EPMC3167593 | biostudies-literature
| S-EPMC2664332 | biostudies-literature