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1 août 2019
- doi: 10.1093/bioinformatics/bty981
- issn: 1367-4803
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Units of inheritance Units of heredity Organisation Methods of analysis Analysis and chemistry Analytical methods Chemical analysis Analysis methods Analysis and examinationCiter ce document
S.N. Mapelli et al., « Deciphering the complexity of human non-coding promoter-proximal transcriptome. », Serveur académique Lausannois, ID : 10.1093/bioinformatics/bty981
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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.