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RIsearch2: Suffix Array-based Large-scale Prediction of RNA-RNA Interactions and SiRNA Off-targets

Overview
Specialty Biochemistry
Date 2017 Jan 22
PMID 28108657
Citations 50
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Abstract

Intermolecular interactions of ncRNAs are at the core of gene regulation events, and identifying the full map of these interactions bears crucial importance for ncRNA functional studies. It is known that RNA-RNA interactions are built up by complementary base pairings between interacting RNAs and high level of complementarity between two RNA sequences is a powerful predictor of such interactions. Here, we present RIsearch2, a large-scale RNA-RNA interaction prediction tool that enables quick localization of potential near-complementary RNA-RNA interactions between given query and target sequences. In contrast to previous heuristics which either search for exact matches while including G-U wobble pairs or employ simplified energy models, we present a novel approach using a single integrated seed-and-extend framework based on suffix arrays. RIsearch2 enables fast discovery of candidate RNA-RNA interactions on genome/transcriptome-wide scale. We furthermore present an siRNA off-target discovery pipeline that not only predicts the off-target transcripts but also computes the off-targeting potential of a given siRNA. This is achieved by combining genome-wide RIsearch2 predictions with target site accessibilities and transcript abundance estimates. We show that this pipeline accurately predicts siRNA off-target interactions and enables off-targeting potential comparisons between different siRNA designs. RIsearch2 and the siRNA off-target discovery pipeline are available as stand-alone software packages from http://rth.dk/resources/risearch.

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References
1.
Wang J, Liu T, Zhao B, Lu Q, Wang Z, Cao Y . sRNATarBase 3.0: an updated database for sRNA-target interactions in bacteria. Nucleic Acids Res. 2015; 44(D1):D248-53. PMC: 4702819. DOI: 10.1093/nar/gkv1127. View

2.
Khorshid M, Hausser J, Zavolan M, van Nimwegen E . A biophysical miRNA-mRNA interaction model infers canonical and noncanonical targets. Nat Methods. 2013; 10(3):253-5. DOI: 10.1038/nmeth.2341. View

3.
Lorenz R, Bernhart S, Honer Zu Siederdissen C, Tafer H, Flamm C, Stadler P . ViennaRNA Package 2.0. Algorithms Mol Biol. 2011; 6:26. PMC: 3319429. DOI: 10.1186/1748-7188-6-26. View

4.
Boudreau R, Spengler R, Hylock R, Kusenda B, Davis H, Eichmann D . siSPOTR: a tool for designing highly specific and potent siRNAs for human and mouse. Nucleic Acids Res. 2012; 41(1):e9. PMC: 3592398. DOI: 10.1093/nar/gks797. View

5.
Ballantyne M, McDonald R, Baker A . lncRNA/MicroRNA interactions in the vasculature. Clin Pharmacol Ther. 2016; 99(5):494-501. PMC: 4881297. DOI: 10.1002/cpt.355. View