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      Circular RNA profiling reveals an abundant circHIPK3 that regulates cell growth by sponging multiple miRNAs

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          Abstract

          Circular RNAs (circRNAs) represent a class of widespread and diverse endogenous RNAs that may regulate gene expression in eukaryotes. However, the regulation and function of human circRNAs remain largely unknown. Here we generate ribosomal-depleted RNA sequencing data from six normal tissues and seven cancers, and detect at least 27,000 circRNA candidates. Many of these circRNAs are differently expressed between the normal and cancerous tissues. We further characterize one abundant circRNA derived from Exon2 of the HIPK3 gene, termed circHIPK3. The silencing of circHIPK3 but not HIPK3 mRNA significantly inhibits human cell growth. Via a luciferase screening assay, circHIPK3 is observed to sponge to 9 miRNAs with 18 potential binding sites. Specifically, we show that circHIPK3 directly binds to miR-124 and inhibits miR-124 activity. Our results provide evidence that circular RNA produced from precursor mRNA may have a regulatory role in human cells.

          Abstract

          Circular RNAs are formed from exon back-splicing, the significance of these endogenous RNAs is beginning to be unraveled. Here, the authors identify thousands of circular RNAs differentially expressed between normal and cancer tissues and show that an abundant circular RNA generated from HIPK3 regulates cell growth.

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          Most cited references14

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          NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy

          The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of genomic, transcript and protein sequence records. These records are selected and curated from public sequence archives and represent a significant reduction in redundancy compared to the volume of data archived by the International Nucleotide Sequence Database Collaboration. The database includes over 16 000 organisms, 2.4 × 106 genomic records, 13 × 106 proteins and 2 × 106 RNA records spanning prokaryotes, eukaryotes and viruses (RefSeq release 49, September 2011). The RefSeq database is maintained by a combined approach of automated analyses, collaboration and manual curation to generate an up-to-date representation of the sequence, its features, names and cross-links to related sources of information. We report here on recent growth, the status of curating the human RefSeq data set, more extensive feature annotation and current policy for eukaryotic genome annotation via the NCBI annotation pipeline. More information about the resource is available online (see http://www.ncbi.nlm.nih.gov/RefSeq/).
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            Genome-wide analysis of drosophila circular RNAs reveals their structural and sequence properties and age-dependent neural accumulation.

            Circularization was recently recognized to broadly expand transcriptome complexity. Here, we exploit massive Drosophila total RNA-sequencing data, >5 billion paired-end reads from >100 libraries covering diverse developmental stages, tissues, and cultured cells, to rigorously annotate >2,500 fruit fly circular RNAs. These mostly derive from back-splicing of protein-coding genes and lack poly(A) tails, and the circularization of hundreds of genes is conserved across multiple Drosophila species. We elucidate structural and sequence properties of Drosophila circular RNAs, which exhibit commonalities and distinctions from mammalian circles. Notably, Drosophila circular RNAs harbor >1,000 well-conserved canonical miRNA seed matches, especially within coding regions, and coding conserved miRNA sites reside preferentially within circularized exons. Finally, we analyze the developmental and tissue specificity of circular RNAs and note their preferred derivation from neural genes and enhanced accumulation in neural tissues. Interestingly, circular isoforms increase substantially relative to linear isoforms during CNS aging and constitute an aging biomarker. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
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              The UCSC Known Genes.

              The University of California Santa Cruz (UCSC) Known Genes dataset is constructed by a fully automated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data from Genbank. The detailed steps of this process are described. Extensive cross-references from this dataset to other genomic and proteomic data were constructed. For each known gene, a details page is provided containing rich information about the gene, together with extensive links to other relevant genomic, proteomic and pathway data. As of July 2005, the UCSC Known Genes are available for human, mouse and rat genomes. The Known Genes serves as a foundation to support several key programs: the Genome Browser, Proteome Browser, Gene Sorter and Table Browser offered at the UCSC website. All the associated data files and program source code are also available. They can be accessed at http://genome.ucsc.edu. The genomic coverage of UCSC Known Genes, RefSeq, Ensembl Genes, H-Invitational and CCDS is analyzed. Although UCSC Known Genes offers the highest genomic and CDS coverage among major human and mouse gene sets, more detailed analysis suggests all of them could be further improved.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                06 April 2016
                2016
                : 7
                : 11215
                Affiliations
                [1 ]Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University; Department of Oncology, Shanghai Medical College, Fudan University , Shanghai 200032, China
                [2 ]State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai 200032, China
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                ncomms11215
                10.1038/ncomms11215
                4823868
                27050392
                1f6dfbfc-feb8-4e86-840e-9fc6e6c8b622
                Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 09 August 2015
                : 03 March 2016
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