mirWIP: microRNA Target Prediction Based on miRNP Enriched Transcripts. Target prediction for animal microRNAs has been hindered by the small number of verified targets available for evaluating the accuracy of predicted microRNA:target interactions. Recently, a dataset of 3404 microRNA-associated mRNA transcripts was identified by immuno-precipitation (IP) of the RNA-induced silencing complex (RISC) components, AIN-1 and AIN-2. Analysis of this dataset reveals enrichment for defining characteristics of functional microRNA target interactions, including structural accessibility of target sequences, the total free energy of microRNA:target hybridization, and the topology of base-pairing to the 5’ seed region of the microRNA. These enriched characteristics form the basis for a quantitative microRNA target prediction method, mirWIP (microRNA targets by Weighting IP dataset parameters), that optimizes sensitivity to verified microRNA:target interactions and specificity to the AIN-IP dataset. The mirWIP method can capture all of the known conserved microRNA:mRNA target relationships in C. elegans at a lower false positive rate than the current standard methods.
References in zbMATH (referenced in 1 article )
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