Abstract
MicroRNAs (miRNAs) posttranscriptionally repress the expression of protein-coding genes. Based on the partial complementarity between miRNA and messenger RNA pairs with a mandatory so-called ‘seed’ sequence, many thousands of potential targets can be identified. Our open-source software library, miRmap, ranks these potential targets with a biologically meaningful criterion, the repression strength. MiRmap combines thermodynamic, evolutionary, probabilistic and sequence-based features, which cover features from TargetScan, PITA, PACMIT and miRanda. Our miRmap web application offers a user-friendly and feature-rich resource for browsing precomputed miRNA target predictions for model organisms, as well as for predicting and ranking targets for user-submitted sequences. MiRmap web integrates sorting, filtering and exporting of results from multiple queries, as well as providing programmatic access, and is available at http://mirmap.ezlab.org.
Highlights
MicroRNAs are short (22 nt) noncoding RNAs that guide the RNA-induced silencing complex (RISC) to posttranscriptionally repress the expression of protein-coding genes by binding to targeted messenger RNAs [1,2,3]
In the miRNA–messenger RNAs (mRNAs) binding map based on Ago HITSCLIP (HIgh-Throughput Sequencing of RNA isolated by CrossLinking ImmunoPrecipitation) [5], 73% of the studied target sites have a seed match
We recently proposed a ranking function of miRNAmediated repression strength parameterized from experimentally measured effects on mRNA or protein levels resulting in prediction of biologically meaningful potential targets [6]
Summary
MicroRNAs (miRNAs) are short (22 nt) noncoding RNAs that guide the RNA-induced silencing complex (RISC) to posttranscriptionally repress the expression of protein-coding genes by binding to targeted messenger RNAs (mRNAs) [1,2,3]. While searching for seed matches in 30-UTR is a widely used feature for miRNA target prediction, it yields a very high number of potential targets. Implemented as an open-source Python software library, the miRmap library implements a comprehensive range of features using thermodynamic, probabilistic, evolutionary and sequence-based approaches to rank potential miRNA targets using information beyond the seed match.
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