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    An atlas of human long non-coding RNAs with accurate 5′ ends

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    nihms-1058548.pdf
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    PDF
    Description:
    Accepted manuscript
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    Type
    Article
    Authors
    Hon, Chung-Chau
    Ramilowski, Jordan A.
    Harshbarger, Jayson
    Bertin, Nicolas
    Rackham, Owen J. L.
    Gough, Julian
    Denisenko, Elena
    Schmeier, Sebastian cc
    Poulsen, Thomas M.
    Severin, Jessica
    Lizio, Marina cc
    Kawaji, Hideya cc
    Kasukawa, Takeya cc
    Itoh, Masayoshi
    Burroughs, A. Maxwell
    Noma, Shohei
    Djebali, Sarah
    Alam, Tanvir cc
    Medvedeva, Yulia A.
    Testa, Alison C.
    Lipovich, Leonard
    Yip, Chi-Wai
    Abugessaisa, Imad cc
    Mendez, Mickaël
    Hasegawa, Akira
    Tang, Dave
    Lassmann, Timo
    Heutink, Peter cc
    Babina, Magda
    Wells, Christine A.
    Kojima, Soichi cc
    Nakamura, Yukio
    Suzuki, Harukazu
    Daub, Carsten O.
    Hoon, Michiel J. L. de
    Arner, Erik
    Hayashizaki, Yoshihide
    Carninci, Piero
    Forrest, Alistair R. R.
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2017-03-01
    Online Publication Date
    2017-03-01
    Print Publication Date
    2017-03
    Permanent link to this record
    http://hdl.handle.net/10754/623789
    
    Metadata
    Show full item record
    Abstract
    Long non-coding RNAs (lncRNAs) are largely heterogeneous and functionally uncharacterized. Here, using FANTOM5 cap analysis of gene expression (CAGE) data, we integrate multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5′ ends and expression profiles across 1,829 samples from the major human primary cell types and tissues. Genomic and epigenomic classification of these lncRNAs reveals that most intergenic lncRNAs originate from enhancers rather than from promoters. Incorporating genetic and expression data, we show that lncRNAs overlapping trait-associated single nucleotide polymorphisms are specifically expressed in cell types relevant to the traits, implicating these lncRNAs in multiple diseases. We further demonstrate that lncRNAs overlapping expression quantitative trait loci (eQTL)-associated single nucleotide polymorphisms of messenger RNAs are co-expressed with the corresponding messenger RNAs, suggesting their potential roles in transcriptional regulation. Combining these findings with conservation data, we identify 19,175 potentially functional lncRNAs in the human genome.
    Citation
    Hon C-C, Ramilowski JA, Harshbarger J, Bertin N, Rackham OJL, et al. (2017) An atlas of human long non-coding RNAs with accurate 5′ ends. Nature 543: 199–204. Available: http://dx.doi.org/10.1038/nature21374.
    Sponsors
    FANTOM5 was made possible by research grants for the RIKEN Omics Science Center and the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT to Y.H. It was also supported by research grants for the RIKEN Preventive Medicine and Diagnosis Innovation Program (RIKEN PMI) to Y.H. and the RIKEN Centre for Life Science Technologies, Division of Genomic Technologies (RIKEN CLST (DGT)) from the MEXT, Japan. A.R.R.F. is supported by a Senior Cancer Research Fellowship from the Cancer Research Trust, the MACA Ride to Conquer Cancer and the Australian Research Council’s Discovery Projects funding scheme (DP160101960). S.D. is supported by award number U54HG007004 from the National Human Genome Research Institute of the National Institutes of Health, funding from the Ministry of Economy and Competitiveness (MINECO) under grant number BIO2011-26205, and SEV-2012-0208 from the Spanish Ministry of Economy and Competitiveness. Y.A.M. is supported by the Russian Science Foundation, grant 15-14-30002. We thank RIKEN GeNAS for generation of the CAGE and RNA-seq libraries, the Netherlands Brain Bank for brain materials, the RIKEN BioResource Centre for providing cell lines and all members of the FANTOM5 consortium for discussions, in particular H. Ashoor, M. Frith, R. Guigo, A. Tanzer, E. Wood, H. Jia, K. Bailie, J. Harrow, E. Valen, R. Andersson, K. Vitting-Seerup, A. Sandelin, M. Taylor, J. Shin, R. Mori, C. Mungall and T. Meehan.
    Publisher
    Springer Nature
    Journal
    Nature
    DOI
    10.1038/nature21374
    Additional Links
    http://www.nature.com/nature/journal/v543/n7644/full/nature21374.html
    ae974a485f413a2113503eed53cd6c53
    10.1038/nature21374
    Scopus Count
    Collections
    Articles; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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