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LncPepAtlas: a comprehensive resource for exploring the translational landscape of long non-coding RNAs.

Authors :
Zhou X
Qin Y
Li J
Fan L
Zhang S
Zhang B
Wu L
Gao A
Yang Y
Lv X
Guo B
Sun L
Source :
Nucleic acids research [Nucleic Acids Res] 2024 Oct 22. Date of Electronic Publication: 2024 Oct 22.
Publication Year :
2024
Publisher :
Ahead of Print

Abstract

Long non-coding RNAs were commonly viewed as non-coding elements. However, they are increasingly recognized for their ability to be translated into proteins, thereby playing a significant role in various cellular processes and diseases. With developments in biotechnology and computational algorithms, a range of novel approaches are being applied to investigate the translation of long non-coding RNA (lncRNAs). Herein, we developed the LncPepAtlas database (http://www.cnitbiotool.net/LncPepAtlas/), which aims to compile multiple evidences for the translation of lncRNAs and annotations for the upstream regulation of lncRNAs across various species. LncPepAtlas integrated compelling evidence from nine distinct sources for the translation of lncRNAs. These include a dataset comprising 2631 publicly available Ribo-seq samples from nine species, which has been collected and analysed. LncPepAtlas offers extensive annotation for lncRNA upstream regulation and expression profiles across various cancers, tissues or cell lines at transcriptional and translational levels. Importantly, it enables novel antigen predictions for lncRNA-encoded peptides. By identifying numerous peptide candidates that could potentially bind to major histocompatibility complex class I and II molecules, this work may provide new insights into cancer immunotherapy. The function of peptides were inferred by aligning them with experimentally detected proteins. LncPepAtlas aims to become a convenient resource for exploring translatable lncRNAs.<br /> (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Details

Language :
English
ISSN :
1362-4962
Database :
MEDLINE
Journal :
Nucleic acids research
Publication Type :
Academic Journal
Accession number :
39435995
Full Text :
https://doi.org/10.1093/nar/gkae905