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      RIsearch2: suffix array-based large-scale prediction of RNA–RNA interactions and siRNA off-targets

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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 GU 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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          Most cited references34

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            An improved algorithm for matching biological sequences.

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              TarBase: A comprehensive database of experimentally supported animal microRNA targets.

              MicroRNAs (miRNAs) are approximately 22-nt RNA segments that are involved in the regulation of protein expression primarily by binding to one or more target sites on an mRNA transcript and inhibiting translation. MicroRNAs are likely to factor into multiple developmental pathways, multiple mechanisms of gene regulation, and underlie an array of inherited disease processes and phenotypic determinants. Several computational programs exist to predict miRNA targets in mammals, fruit flies, worms, and plants. However, to date, there is no systematic collection and description of miRNA targets with experimental support. We describe a database, TarBase, which houses a manually curated collection of experimentally tested miRNA targets, in human/mouse, fruit fly, worm, and zebrafish, distinguishing between those that tested positive and those that tested negative. Each positive target site is described by the miRNA that binds it, the gene in which it occurs, the nature of the experiments that were conducted to test it, the sufficiency of the site to induce translational repression and/or cleavage, and the paper from which all these data were extracted. Additionally, the database is functionally linked to several other useful databases such as Gene Ontology (GO) and UCSC Genome Browser. TarBase reveals significantly more experimentally supported targets than even recent reviews claim, thereby providing a comprehensive data set from which to assess features of miRNA targeting that will be useful for the next generation of target prediction programs. TarBase can be accessed at http://www.diana.pcbi.upenn.edu/tarbase.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                05 May 2017
                20 January 2017
                20 January 2017
                : 45
                : 8
                : e60
                Affiliations
                [1 ]Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
                [2 ]Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
                [3 ]Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
                [4 ]Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, 1090 Wien, Austria
                [5 ]Bioinformatics Group, Department of Computer Science & IZBI-Interdisciplinary Center for Bioinformatics & LIFE-Leipzig Research Center for Civilization Diseases & Competence Center for Scalable Data Services and Solutions, University Leipzig, Härtelstraße 16–18, 04107 Leipzig, Germany
                [6 ]Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04103 Leipzig, Germany
                [7 ]Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
                [8 ]Research Group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Währingerstraße 17, 1090 Wien, Austria
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +45 353 33578; Fax: +45 353 34704; Email: gorodkin@ 123456rth.dk
                []These authors contributed equally to the paper as first authors.
                []Currently with the Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St., Boston, MA 02115, USA.
                Author information
                http://orcid.org/0000-0001-7132-0800
                Article
                gkw1325
                10.1093/nar/gkw1325
                5416843
                28108657
                7b17d138-b9ca-43b8-ba32-39515337b6eb
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 19 December 2016
                : 21 November 2016
                Page count
                Pages: 13
                Categories
                Methods Online

                Genetics
                Genetics

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