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Nat Commun. 2014 Nov 12;5:5336. doi: 10.1038/ncomms6336.

Nuclear stability and transcriptional directionality separate functionally distinct RNA species.

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The Bioinformatics Centre, Department of Biology and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, DK-2200 Copenhagen, Denmark.
Centre for mRNP Biogenesis and Metabolism, Department of Molecular Biology and Genetics, C.F. Møllers Alle 3, Building 1130, DK-8000 Aarhus, Denmark.
1] Department of Informatics, University of Bergen, Thormøhlensgate 55, N-5008 Bergen, Norway [2] Department of Molecular and Cellular Biology, Harvard University, 7 Divinity Avenue, Cambridge, Massachusetts 02138, USA.
1] Department for Molecular Biology and Genetics, Cornell University, 526 Campus Road, Ithaca, New York 14853, USA [2] Department of Molecular and Cell Biology, Institute for Systems Genomics, University of Connecticut, Storrs, Connecticut 06269, USA.


Mammalian genomes are pervasively transcribed, yielding a complex transcriptome with high variability in composition and cellular abundance. Although recent efforts have identified thousands of new long non-coding (lnc) RNAs and demonstrated a complex transcriptional repertoire produced by protein-coding (pc) genes, limited progress has been made in distinguishing functional RNA from spurious transcription events. This is partly due to present RNA classification, which is typically based on technical rather than biochemical criteria. Here we devise a strategy to systematically categorize human RNAs by their sensitivity to the ribonucleolytic RNA exosome complex and by the nature of their transcription initiation. These measures are surprisingly effective at correctly classifying annotated transcripts, including lncRNAs of known function. The approach also identifies uncharacterized stable lncRNAs, hidden among a vast majority of unstable transcripts. The predictive power of the approach promises to streamline the functional analysis of known and novel RNAs.

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