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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 68

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          MicroRNAs: genomics, biogenesis, mechanism, and function.

           David Bartel (2004)
          MicroRNAs (miRNAs) are endogenous approximately 22 nt RNAs that can play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression. Although they escaped notice until relatively recently, miRNAs comprise one of the more abundant classes of gene regulatory molecules in multicellular organisms and likely influence the output of many protein-coding genes.
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            miRBase: annotating high confidence microRNAs using deep sequencing data

            We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.
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              Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs.

              MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression in plants and animals. To investigate the influence of miRNAs on transcript levels, we transfected miRNAs into human cells and used microarrays to examine changes in the messenger RNA profile. Here we show that delivering miR-124 causes the expression profile to shift towards that of brain, the organ in which miR-124 is preferentially expressed, whereas delivering miR-1 shifts the profile towards that of muscle, where miR-1 is preferentially expressed. In each case, about 100 messages were downregulated after 12 h. The 3' untranslated regions of these messages had a significant propensity to pair to the 5' region of the miRNA, as expected if many of these messages are the direct targets of the miRNAs. Our results suggest that metazoan miRNAs can reduce the levels of many of their target transcripts, not just the amount of protein deriving from these transcripts. Moreover, miR-1 and miR-124, and presumably other tissue-specific miRNAs, seem to downregulate a far greater number of targets than previously appreciated, thereby helping to define tissue-specific gene expression in humans.
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                Author and article information

                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.
                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
                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.

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                Pages: 9
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                Database Issue
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                04 January 2016

                Genetics

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