Post-transcriptional regulatory patterns revealed by protein-RNA interactions
Autor: | Zanzoni, Andreas, Spinelli, Lionel, Ribeiro, Diogo M., Tartaglia, Gian Gaetano, Brun, Christine |
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Přispěvatelé: | Theories and Approaches of Genomic Complexity (TAGC), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre for Genomic Regulation [Barcelona] (CRG), Universitat Pompeu Fabra [Barcelona] (UPF)-Centro Nacional de Analisis Genomico [Barcelona] (CNAG), Centre National de la Recherche Scientifique (CNRS), ANR-11-IDEX-0001,Amidex,INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE(2011), European Project: 309545,EC:FP7:ERC,ERC-2012-StG_20111109,RIBOMYLOME(2013), Zanzoni, Andreas, INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE - - Amidex2011 - ANR-11-IDEX-0001 - IDEX - VALID, The Role of Non-coding RNA in Protein Networks and Neurodegenerative Diseases - RIBOMYLOME - - EC:FP7:ERC2013-01-01 - 2017-12-31 - 309545 - VALID |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Cellular signalling networks
[SDV]Life Sciences [q-bio] lcsh:R RNA-Binding Proteins lcsh:Medicine Regulon Article Gene regulatory networks [SDV] Life Sciences [q-bio] Gene Expression Regulation Humans lcsh:Q Protein Interaction Maps RNA Messenger RNA Processing Post-Transcriptional Gene expression regulation humans protein interaction maps RNA messenger RNA-binding proteins regulon transcriptome RNA processing post-transcriptional [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] Transcriptome lcsh:Science [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM] |
Zdroj: | Scientific Reports Scientific Reports, Nature Publishing Group, 2019, 9 (1), pp.4302. ⟨10.1038/s41598-019-40939-2⟩ Scientific Reports, 2019, 9 (1), pp.4302. ⟨10.1038/s41598-019-40939-2⟩ Scientific Reports, Vol 9, Iss 1, Pp 1-13 (2019) Recercat. Dipósit de la Recerca de Catalunya instname |
ISSN: | 2045-2322 |
Popis: | International audience; the coordination of the synthesis of functionally-related proteins can be achieved at the post-transcriptional level by the action of common regulatory molecules, such as RNA-binding proteins (RBPs). Despite advances in the genome-wide identification of RBPs and their binding transcripts, the protein-RNA interaction space is still largely unexplored, thus hindering a broader understanding of the extent of the post-transcriptional regulation of related coding RNAs. Here, we propose a computational approach that combines protein-mRNA interaction networks and statistical analyses to provide an inferred regulatory landscape for more than 800 human RBPs and identify the cellular processes that can be regulated at the post-transcriptional level. We show that 10% of the tested sets of functionally-related mRNAs can be post-transcriptionally regulated. Moreover, we propose a classification of (i) the RBps and (ii) the functionally-related mRNAs, based on their distinct behaviors in the functional landscape, hinting towards mechanistic regulatory hypotheses. In addition, we demonstrate the usefulness of the inferred functional landscape to investigate the cellular role of both well-characterized and novel RBps in the context of human diseases. While transcription contributes to coordinated gene expression in time and space, several studies highlighted the discordance between levels of mRNAs and protein production 1,2. This indicates that the regulation of mRNA transcripts is key to achieve coordinated protein synthesis. Indeed, it has been shown that sets of transcripts coding for functionally related proteins are bound by common regulatory molecules, such as RNA-binding proteins (RBPs) and/or non-coding RNAs, thus forming the so-called RNA regulons 3,4. Early protein-RNA interaction mapping studies in yeast demonstrated that many RBPs bind specific mRNAs coding for proteins involved in the same biological process (e.g., ribosome biogenesis, chromatin architecture, oxidative phosphorylation) or that are cytotopically related (e.g., cell wall, endoplasmic reticulum, mitochon-drion) 5,6. In mammalian cells, several sets of related mRNAs are part of RNA regulons as well, e.g., histone mRNAs bound by the stem-loop binding protein (SLBP) 7 , transcripts involved in inflammation regulated by the RBPs ELAVL1, HNRNPL and TTP 8 , those implicated in DNA damage response and regulated by the RBPs BCLAF1, ELAVL1 and THRAP3 9,10 and mRNAs coding for cell cycle and proliferation factors bound by Dead end protein homolog 1 (DND1) and Pumilio 1 (PUM1) proteins 9. As this regulatory phenomenon has been observed in different species, RNA regulons represent a conserved feature of the post-transcriptional regulation in eukaryotes 3,4,11. However, even though RNA regulon perturbations can lead to the onset of neurological diseases and cancers in human 12-14 , the control of these regulatory circuits exerted by RBPs is rather sketchy 15,16 , therefore calling for further scrutiny. A deeper understanding of post-transcriptional regulation is subordinate to the availability of experimentally verified protein-mRNA interaction data. Over the last years, studies based on high-throughput methods to detect RNA molecules bound by RBPs, such as RNA immunoprecipitation and CLIP-based techniques 17,18 allowed to identify thousands of protein-RNA interactions. However, these studies have focused on the binding ability of a reduced number of established RBPs in a few cell lines 18 , indicating that the protein-RNA interactions space is largely unexplored. Moreover, thanks to the recent development of RNA interactome capture technologies |
Databáze: | OpenAIRE |
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