Molecular Biology

, Volume 52, Issue 3, pp 467–477 | Cite as

Efficiency of the miRNA–mRNA Interaction Prediction Programs

  • O. M. PlotnikovaEmail author
  • M. Y. Skoblov


miRNAs play a key role in regulation of gene expression. Nowadays it is known more than 2500 human miRNAs, while a majority of miRNA–mRNA interactions remains unidentified. The recent development of a high-throughput CLASH (crosslinking, ligation and sequencing of hybrids) technique for discerning miRNA–mRNA interactions allowed an experimental analysis of the human miRNA–mRNA interactome. Therefore, it allowed us, for the first time, make an experimental analysis of the human miRNA–mRNA interactome as a whole and an evaluation of the quality of most commonly used miRNA prediction tools (TargetScan, PicTar, PITA, RNA22 and miRanda). To estimate efficiency of the miRNA–mRNA prediction tools, we used next parameters: sensitivity, positive predicted value, predictions in different mRNA regions (3' UTR, CDS, 5' UTR), predictions for different types of interactions (5 classes), predictions of “canonical” and “nocanonical” interactions, similarity with the random generated data. The analysis revealed low efficiency of all prediction programs in comparison with the CLASH data in terms of the all examined parameters.


miRNA–mRNA interaction miRNA binding sites CLASH prediction program TargetScan PicTar PITA RNA22 miRanda 





coding DNA sequence


crosslinking, ligation and sequencing of hybrids


UV crosslinking and immunoprecipitation


individual-nucleotide resolution cross-linking and immunoprecipitation


Human Embryonic Kidney 293 cells


human genome version 19


high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation






positive predictive value


RNA-induced silencing complex


untranslated region


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Copyright information

© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  1. 1.Moscow Institute of Physics and Technology (State University)DolgoprudnyRussia
  2. 2.Research Centre for Medical GeneticsMoscowRussia

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