MiRBooking simulates the stoichiometric mode of action of microRNAs.

Nathanaël Weill,Paul Dallaire,François Major,Julie Pelloux,Nicolas Scott,Véronique Lisi

doi:10.1093/nar/gkv619

Nathanaël Weill, Paul Dallaire + Show 4 more

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https://doi.org/10.1093/nar/gkv619

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Abstract

In eucaryotes, gene expression is regulated by microRNAs (miRNAs) which bind to messenger RNAs (mRNAs) and interfere with their translation into proteins, either by promoting their degradation or inducing their repression. We study the effect of miRNA interference on each gene using experimental methods, such as microarrays and RNA-seq at the mRNA level, or luciferase reporter assays and variations of SILAC at the protein level. Alternatively, computational predictions would provide clear benefits. However, no algorithm toward this task has ever been proposed. Here, we introduce a new algorithm to predict genome-wide expression data from initial transcriptome abundance. The algorithm simulates the miRNA and mRNA hybridization competition that occurs in given cellular conditions, and derives the whole set of miRNA::mRNA interactions at equilibrium (microtargetome). Interestingly, solving the competition improves the accuracy of miRNA target predictions. Furthermore, this model implements a previously reported and fundamental property of the microtargetome: the binding between a miRNA and a mRNA depends on their sequence complementarity, but also on the abundance of all RNAs expressed in the cell, i.e. the stoichiometry of all the miRNA sites and all the miRNAs given their respective abundance. This model generalizes the miRNA-induced synchronistic silencing previously observed, and described as sponges and competitive endogenous RNAs.

Highlights

MicroRNA genes are transcribed into primary transcripts, which are processed into mature single-stranded RNA molecules of ∼22 nucleotides [1]
Mature miRNAs are incorporated in the RNA-induced silencing complex (RISC), which initially exposes seed nucleotides 2–5 to the surface that serve as an hybridization template with a complementary site on a messenger RNA [2,3,4]
In the microtargetomes of three different cell lines (DU145, PC3 and HCT116) computed by miRBooking, we found the reverse ratio of perfect- and 1-mismatch duplexes (Supplementary Figure S2B), i.e. ∼70% of the matches are perfect

Summary

Introduction

MicroRNA (miRNA) genes are transcribed into primary transcripts, which are processed into mature single-stranded RNA molecules of ∼22 nucleotides [1]. Mature miRNAs are incorporated in the RNA-induced silencing complex (RISC), which initially exposes seed nucleotides 2–5 to the surface that serve as an hybridization template with a complementary site on a messenger RNA (mRNA) [2,3,4]. Determining the silencing effect exerted on each gene is key to studying cell behavior This is currently accomplished using various experimental techniques, such as luciferase reporter assays [2,7,8], microarrays [9,10] and RNA-seq [11], variants of SILAC (stable isotope labeling by amino acids in cell culture) [12,13], and variants of CLIP (crosslinking immunoprecipitation) [14,15,16]. Accumulating evidences indicate that (iv) miRNA-induced silencing is subject to cellular conditions [17,18,19,20]

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