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Integrative classification of human coding and noncoding genes through RNA metabolism profiles

Item Type:Article
Title:Integrative classification of human coding and noncoding genes through RNA metabolism profiles
Creators Name:Mukherjee, N. and Calviello, L. and Hirsekorn, A. and de Pretis, S. and Pelizzola, M. and Ohler, U.
Abstract:Pervasive transcription of the human genome results in a heterogeneous mix of coding RNAs and long noncoding RNAs (lncRNAs). Only a small fraction of lncRNAs have demonstrated regulatory functions, thus making functional lncRNAs difficult to distinguish from nonfunctional transcriptional byproducts. This difficulty has resulted in numerous competing human lncRNA classifications that are complicated by a steady increase in the number of annotated lncRNAs. To address these challenges, we quantitatively examined transcription, splicing, degradation, localization and translation for coding and noncoding human genes. We observed that annotated lncRNAs had lower synthesis and higher degradation rates than mRNAs and discovered mechanistic differences explaining slower lncRNA splicing. We grouped genes into classes with similar RNA metabolism profiles, containing both mRNAs and lncRNAs to varying extents. These classes exhibited distinct RNA metabolism, different evolutionary patterns and differential sensitivity to cellular RNA-regulatory pathways. Our classification provides an alternative to genomic context-driven annotations of lncRNAs.
Keywords:Gene Expression, HEK293 Cells, Messenger RNA, Molecular Sequence Annotation, Open Reading Frames, RNA Splicing, Untranslated RNA
Source:Nature Structural & Molecular Biology
ISSN:1545-9993
Publisher:Nature Publishing Group
Volume:24
Number:1
Page Range:86-96
Date:January 2017
Official Publication:https://doi.org/10.1038/nsmb.3325
PubMed:View item in PubMed
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https://edoc.mdc-berlin.de/16857/Preprint version

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