Predicting effective microRNA target sites in mammalian mRNAs
Vikram Agarwal,
George W Bell,
Jin-Wu Nam,
David P Bartel
Affiliations
Vikram Agarwal
Howard 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 States
George W Bell
Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, United States
Jin-Wu Nam
Howard 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, Korea
David P Bartel
Howard Hughes Medical Institute, Whitehead Institute for Biomedical Research, Cambridge, United States; Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
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.