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      miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database

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          Abstract

          MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase ( http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.

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          Most cited references 47

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          miRDB: an online resource for microRNA target prediction and functional annotations

          MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
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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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              miRecords: an integrated resource for microRNA–target interactions

              MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2016
                20 November 2015
                20 November 2015
                : 44
                : Database issue , Database issue
                : D239-D247
                Affiliations
                [1 ]Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan
                [2 ]Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, 106, Taiwan
                [3 ]Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan
                [4 ]Center for Bioinformatics Research, National Chiao Tung University, Hsinchu, 300, Taiwan
                [5 ]Clinical Research Center, Chung Shan Medical University Hospital, Taichung, 402, Taiwan
                [6 ]Institute of Population Health Sciences, National Health Research Institutes, Miaoli, 350, Taiwan
                [7 ]Interdisciplinary Program of Life Science, National Tsing Hua University, Hsinchu, 300, Taiwan
                [8 ]Institute of Molecular Medicine and Bioengineering, National Chiao Tung University, Hsinchu, 300, Taiwan
                [9 ]Degree Program of Applied Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan
                [10 ]Gynecologic Cancer Center, Department of Obstetrics and Gynecology, Cathay General Hospital, Taipei, 106, Taiwan
                [11 ]Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung, 402, Taiwan
                [12 ]Department of Obstetrics and Gynecology, Hsinchu Mackay Memorial Hospital, Hsinchu, 300, Taiwan
                [13 ]Mackay Medicine, Nursing and Management College, Taipei, 112, Taiwan
                [14 ]Department of Medicine, Mackay Medical College, New Taipei City, 252, Taiwan
                [15 ]Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
                [16 ]Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +886 3 5712121 (Ext. 56952); Fax: +886 3 5729288; Email: bryan@ 123456mail.nctu.edu.tw
                Correspondence may also be addressed to Wen-Lian Hsu. Tel: +886 2 27883799 (Ext. 2202); Fax: +886 2 27824814; Email: hsu@ 123456iis.sinica.edu.tw
                []These authors contributed equally to this work as first authors.
                Article
                10.1093/nar/gkv1258
                4702890
                26590260
                © The Author(s) 2015. 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.

                Page count
                Pages: 9
                Product
                Categories
                Database Issue
                Custom metadata
                04 January 2016

                Genetics

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