Deciphering the complexity of human non-coding promoter-proximal transcriptome.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
01 08 2019
Historique:
received: 03 07 2018
revised: 08 11 2018
accepted: 07 12 2018
pubmed: 12 12 2018
medline: 17 6 2020
entrez: 12 12 2018
Statut: ppublish

Résumé

Long non-coding RNAs (lncRNAs) have gained increasing relevance in epigenetic regulation and nuclear functional organization. High-throughput sequencing approaches have revealed frequent non-coding transcription in promoter-proximal regions. However, a comprehensive catalogue of promoter-associated RNAs (paRNAs) and an analysis of the possible interactions with neighboring genes and genomic regulatory elements are missing. Integrating data from multiple cell types and experimental platforms we identified thousands of paRNAs in the human genome. paRNAs are transcribed in both sense and antisense orientation, are mostly non-polyadenylated and retained in the cell nucleus. Transcriptional regulators, epigenetic effectors and activating chromatin marks are enriched in paRNA-positive promoters. Furthermore, paRNA-positive promoters exhibit chromatin signatures of both active promoters and enhancers. Promoters with paRNAs reside preferentially at chromatin loop boundaries, suggesting an involvement in anchor site recognition and chromatin looping. Importantly, these features are independent of the transcriptional state of neighboring genes. Thus, paRNAs may act as cis-regulatory modules with an impact on local recruitment of transcription factors, epigenetic state and chromatin loop organization. This study provides a comprehensive analysis of the promoter-proximal transcriptome and offers novel insights into the roles of paRNAs in epigenetic processes and human diseases. Genomic coordinates of predicted paRNAs are available at https://figshare.com: https://doi.org/10.6084/m9.figshare.7392791.v1 and https://doi.org/10.6084/m9.figshare.4856630.v2. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 30535182
pii: 5237560
doi: 10.1093/bioinformatics/bty981
pmc: PMC6662291
doi:

Substances chimiques

Chromatin 0
RNA, Long Noncoding 0

Banques de données

figshare
['10.6084/m9.figshare.7392791.v1', '10.6084/m9.figshare.4856630.v2']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2529-2534

Subventions

Organisme : Medical Research Council
ID : MR/P000711/1
Pays : United Kingdom

Informations de copyright

© The Author(s) 2018. Published by Oxford University Press.

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Auteurs

Sarah N Mapelli (SN)

Tumor Biology and Experimental Therapeutics Program, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.
Institute of Computational Science, Università della Svizzera Italiana (USI), Lugano, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.

Sara Napoli (S)

Tumor Biology and Experimental Therapeutics Program, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.

Giuseppina Pisignano (G)

Tumor Biology and Experimental Therapeutics Program, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.

Ramon Garcia-Escudero (R)

Tumor Biology and Experimental Therapeutics Program, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.
Molecular Oncology Unit-CIEMAT and Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain.

Giuseppina M Carbone (GM)

Tumor Biology and Experimental Therapeutics Program, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.

Carlo V Catapano (CV)

Tumor Biology and Experimental Therapeutics Program, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
Department of Oncology, Faculty of Biology and Medicine, University of Lausanne, Lausanne1066, Switzerland.

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Classifications MeSH