Format

Send to

Choose Destination
Elife. 2015 Aug 12;4. doi: 10.7554/eLife.05005.

Predicting effective microRNA target sites in mammalian mRNAs.

Author information

1
Howard Hughes Medical Institute, Whitehead Institute for Biomedical Research, Cambridge, United States.
2
Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, United States.

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.

KEYWORDS:

computational biology; evolutionary biology; genomics; human; miRNA target prediction; miRNA targets; miRNA-binding sites; mouse; post-transcriptional gene regulation; rat; systems biology; zebrafish

PMID:
26267216
PMCID:
PMC4532895
DOI:
10.7554/eLife.05005
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for eLife Sciences Publications, Ltd Icon for PubMed Central
Loading ...
Support Center