Journal Article

Identification of microRNA activity by Targets' Reverse EXpression

Stefano Volinia, Rosa Visone, Marco Galasso, Elda Rossi and Carlo M. Croce

in Bioinformatics

Volume 26, issue 1, pages 91-97
Published in print January 2010 | ISSN: 1367-4803
Published online November 2009 | e-ISSN: 1460-2059 | DOI:

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Motivation: Non-coding microRNAs (miRNAs) act as regulators of global protein output. While their major effect is on protein levels of target genes, it has been proven that they also specifically impact on the messenger RNA level of targets. Prominent interest in miRNAs strongly motivates the need for increasing the options available to detect their cellular activity.

Results: We used the effect of miRNAs over their targets for the detection of miRNA activity using mRNAs expression profiles. Here we describe the method, called T-REX (from Targets' Reverse EXpression), compare it to other similar applications, show its effectiveness and apply it to build activity maps. We used six different target predictions from each of four algorithms: TargetScan, PicTar, DIANA-microT and DIANA Union. First, we proved the sensitivity and specificity of our technique in miRNA over-expression and knock-out animal models. Then, we used whole transcriptome data from acute myeloid leukemia to show that we could identify critical miRNAs in a real life, complex, clinically relevant dataset. Finally, we studied 66 different cellular conditions to confirm and extend the current knowledge on the role of miRNAs in cellular physiology and in cancer.

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Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  4939 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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