Predicting effective microRNA target sites in mammalian mRNAs (VSports在线直播)
- PMID: 26267216
- PMCID: PMC4532895
- DOI: "V体育官网" 10.7554/eLife.05005
Predicting effective microRNA target sites in mammalian mRNAs (VSports注册入口)
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. VSports手机版.
Keywords: computational biology; evolutionary biology; genomics; human; miRNA target prediction; miRNA targets; miRNA-binding sites; mouse; post-transcriptional gene regulation; rat; systems biology; zebrafish V体育安卓版. .
Conflict of interest statement
The authors declare that no competing interests exist.
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References
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