Wang, Xuan, Zhang, Yuxin, Chen, Kunqi, Liang, Zhanmin, Ma, Jiongming, Xia, Rong, de Magalhaes, Joao Pedro 
ORCID: 0000-0002-6363-2465, Rigden, Daniel J ORCID: 0000-0002-7565-8937, Meng, Jia ORCID: 0000-0003-3455-205X and Song, Bowen
(2023)
m7GHub V2.0: an updated database for decoding the N7-methylguanosine (m<SUP>7</SUP>G) epitranscriptome.
NUCLEIC ACIDS RESEARCH, 52 (D1).
D203-D212.
Abstract
With recent progress in mapping N7-methylguanosine (m7G) RNA methylation sites, tens of thousands of experimentally validated m7G sites have been discovered in various species, shedding light on the significant role of m7G modification in regulating numerous biological processes including disease pathogenesis. An integrated resource that enables the sharing, annotation and customized analysis of m7G data will greatly facilitate m7G studies under various physiological contexts. We previously developed the m7GHub database to host mRNA m7G sites identified in the human transcriptome. Here, we present m7GHub v.2.0, an updated resource for a comprehensive collection of m7G modifications in various types of RNA across multiple species: an m7GDB database containing 430 898 putative m7G sites identified in 23 species, collected from both widely applied next-generation sequencing (NGS) and the emerging Oxford Nanopore direct RNA sequencing (ONT) techniques; an m7GDiseaseDB hosting 156 206 m7G-associated variants (involving addition or removal of an m7G site), including 3238 disease-relevant m7G-SNPs that may function through epitranscriptome disturbance; and two enhanced analysis modules to perform interactive analyses on the collections of m7G sites (m7GFinder) and functional variants (m7GSNPer). We expect that m7Ghub v.2.0 should serve as a valuable centralized resource for studying m7G modification. It is freely accessible at: www.rnamd.org/m7GHub2.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Humans, Guanosine, Data Interpretation, Statistical, RNA Processing, Post-Transcriptional, Databases, Nucleic Acid, High-Throughput Nucleotide Sequencing |
| Divisions: | Faculty of Health and Life Sciences Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 30 Jan 2024 10:10 |
| Last Modified: | 30 Jan 2024 10:59 |
| DOI: | 10.1093/nar/gkad789 |
| Open Access URL: | https://doi.org/10.1093/nar/gkad789 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3178083 |
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