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Molecular Biology

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

Efficiency of the miRNA–mRNA Interaction Prediction Programs

  • O. M. Plotnikova
  • M. Y. Skoblov
Bioinformatics

Abstract

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.

Keywords

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

Abbreviations

AGO

argonaute

CDS

coding DNA sequence

CLASH

crosslinking, ligation and sequencing of hybrids

CLIP

UV crosslinking and immunoprecipitation

iCLIP

individual-nucleotide resolution cross-linking and immunoprecipitation

HEK293

Human Embryonic Kidney 293 cells

hg19

human genome version 19

HITS-CLIP

high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation

miRNA

microRNA

PAR-CLIP

photoactivatableribonucleoside-enhanced-immunoprecipitation

PPV

positive predictive value

RISC

RNA-induced silencing complex

UTR

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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