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      DIANA-LncBase v3: indexing experimentally supported miRNA targets on non-coding transcripts

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          Abstract

          DIANA-LncBase v3.0 ( www.microrna.gr/LncBase) is a reference repository with experimentally supported miRNA targets on non-coding transcripts. Its third version provides approximately half a million entries, corresponding to ∼240 000 unique tissue and cell type specific miRNA–lncRNA pairs. This compilation of interactions is derived from the manual curation of publications and the analysis of >300 high-throughput datasets. miRNA targets are supported by 14 experimental methodologies, applied to 243 distinct cell types and tissues in human and mouse. The largest part of the database is highly confident, AGO-CLIP-derived miRNA-binding events. LncBase v3.0 is the first relevant database to employ a robust CLIP-Seq-guided algorithm, microCLIP framework, to analyze 236 AGO-CLIP-Seq libraries and catalogue ∼370 000 miRNA binding events. The database was redesigned from the ground up, providing new functionalities. Known short variant information, on >67,000 experimentally supported target sites and lncRNA expression profiles in different cellular compartments are catered to users. Interactive visualization plots, portraying correlations of miRNA–lncRNA pairs, as well as lncRNA expression profiles in a wide range of cell types and tissues, are presented for the first time through a dedicated page. LncBase v3.0 constitutes a valuable asset for ncRNA research, providing new insights to the understanding of the still widely unexplored lncRNA functions.

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          Most cited references15

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          Gene silencing by microRNAs: contributions of translational repression and mRNA decay.

          Despite their widespread roles as regulators of gene expression, important questions remain about target regulation by microRNAs. Animal microRNAs were originally thought to repress target translation, with little or no influence on mRNA abundance, whereas the reverse was thought to be true in plants. Now, however, it is clear that microRNAs can induce mRNA degradation in animals and, conversely, translational repression in plants. Recent studies have made important advances in elucidating the relative contributions of these two different modes of target regulation by microRNAs. They have also shed light on the specific mechanisms of target silencing, which, although it differs fundamentally between plants and animals, shares some common features between the two kingdoms.
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            Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

            mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
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              Ago HITS-CLIP decodes miRNA-mRNA interaction maps

              Summary MicroRNAs (miRNAs) play critical roles in the regulation of gene expression. However, since miRNA activity requires base pairing with only 6-8 nucleotides of mRNA, predicting target mRNAs is a major challenge. Recently, high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) has identified functional protein-RNA interaction sites. Here we use HITS-CLIP to covalently crosslink native Argonaute (Ago) protein-RNA complexes in mouse brain. This produced two simultaneous datasets—Ago-miRNA and Ago-mRNA binding sites—that were combined with bioinformatic analysis to identify miRNA-target mRNA interaction sites. We validated genome-wide interaction maps for miR-124, and generated additional maps for the 20 most abundant miRNAs present in P13 mouse brain. Ago HITS-CLIP provides a general platform for exploring the specificity and range of miRNA action in vivo, and identifies precise sequences for targeting clinically relevant miRNA-mRNA interactions.
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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
                08 January 2020
                16 November 2019
                16 November 2019
                : 48
                : D1
                : D101-D110
                Affiliations
                [1 ] DIANA-Lab, Department of Electrical and Computer Engineering, Univ. of Thessaly , 38221 Volos, Greece
                [2 ] Hellenic Pasteur Institute , 11521 Athens, Greece
                [3 ] Department of Computer Science and Biomedical Informatics, Univ. of Thessaly , 351 31 Lamia, Greece
                [4 ] Department of Informatics and Telecommunications, Postgraduate Program: ‘Information Technologies in Medicine and Biology’, University of Athens , 15784 Athens, Greece
                Author notes
                To whom correspondence should be addressed. Tel: +30 24210 74758; Fax: +30 24210 74997; Email: arhatzig@ 123456uth.gr
                Correspondence may also be addressed to Dimitra Karagkouni. Tel: +30 24210 74758; Fax: +30 24210 74997; Email: dkaragkouni@ 123456uth.gr

                Equal Contribution.

                Article
                gkz1036
                10.1093/nar/gkz1036
                7145509
                31732741
                7a30c952-7f55-45b0-b1a0-c86cea84e0eb
                © The Author(s) 2019. 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/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 November 2019
                : 16 October 2019
                : 22 September 2019
                Page count
                Pages: 10
                Funding
                Funded by: ELIXIR-GR
                Award ID: MIS-5002780
                Funded by: Competitiveness, Entrepreneurship and Innovation
                Award ID: NSRF 2014–2020
                Funded by: European Regional Development Fund 10.13039/501100008530
                Funded by: European Social Fund 10.13039/501100004895
                Award ID: MIS-5000432
                Categories
                Database Issue

                Genetics
                Genetics

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