TY - JOUR TI - Predicting effective microRNA target sites in mammalian mRNAs AU - Agarwal, Vikram AU - Bell, George W AU - Nam, Jin-Wu AU - Bartel, David P A2 - Izaurralde, Elisa VL - 4 PY - 2015 DA - 2015/08/12 SP - e05005 C1 - eLife 2015;4:e05005 DO - 10.7554/eLife.05005 UR - https://doi.org/10.7554/eLife.05005 AB - 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. KW - miRNA target KW - miRNA-binding site KW - miRNA target prediction KW - post-transcriptional gene regulation JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -