TY - JOUR
T1 - RMDisease V2.0
T2 - an updated database of genetic variants that affect RNA modifications with disease and trait implication
AU - Song, Bowen
AU - Wang, Xuan
AU - Liang, Zhanmin
AU - Ma, Jiongming
AU - Huang, Daiyun
AU - Wang, Yue
AU - de Magalhães, João Pedro
AU - Rigden, Daniel J.
AU - Meng, Jia
AU - Liu, Gang
AU - Chen, Kunqi
AU - Wei, Zhen
N1 - Funding Information:
National Natural Science Foundation of China [32100519 and 31671373]; XJTLU Key Program Special Fund [KSF-E-51 and KSF-P-02]; Scientific Research Foundation for Advanced Talents of Fujian Medical University [XRCZX202109].
Publisher Copyright:
© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.
PY - 2023/1/6
Y1 - 2023/1/6
N2 - Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications (RMs) and multiple human diseases, but distinguishing the functional or disease-related single nucleotide variants (SNVs) from the majority of ‘silent’ variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetic variants and RMs concerning human disease pathogenesis. In this work, we present RMDisease v2.0, an updated database with expanded coverage. Using deep learning models and from 873 819 experimentally validated RM sites, we identified a total of 1 366 252 RM-associated variants that may affect (add or remove an RM site) 16 different types of RNA modifications (m6A, m5C, m1A, m5U, ψ, m6Am, m7G, A-to-I, ac4C, Am, Cm, Um, Gm, hm5C, D and f5C) in 20 organisms (human, mouse, rat, zebrafish, maize, fruit fly, yeast, fission yeast, Arabidopsis, rice, chicken, goat, sheep, pig, cow, rhesus monkey, tomato, chimpanzee, green monkey and SARS-CoV-2). Among them, 14 749 disease- and 2441 trait-associated genetic variants may function via the perturbation of epitranscriptomic markers. RMDisease v2.0 should serve as a useful resource for studying the genetic drivers of phenotypes that lie within the epitranscriptome layer circuitry, and is freely accessible at: www.rnamd.org/rmdisease2.
AB - Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications (RMs) and multiple human diseases, but distinguishing the functional or disease-related single nucleotide variants (SNVs) from the majority of ‘silent’ variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetic variants and RMs concerning human disease pathogenesis. In this work, we present RMDisease v2.0, an updated database with expanded coverage. Using deep learning models and from 873 819 experimentally validated RM sites, we identified a total of 1 366 252 RM-associated variants that may affect (add or remove an RM site) 16 different types of RNA modifications (m6A, m5C, m1A, m5U, ψ, m6Am, m7G, A-to-I, ac4C, Am, Cm, Um, Gm, hm5C, D and f5C) in 20 organisms (human, mouse, rat, zebrafish, maize, fruit fly, yeast, fission yeast, Arabidopsis, rice, chicken, goat, sheep, pig, cow, rhesus monkey, tomato, chimpanzee, green monkey and SARS-CoV-2). Among them, 14 749 disease- and 2441 trait-associated genetic variants may function via the perturbation of epitranscriptomic markers. RMDisease v2.0 should serve as a useful resource for studying the genetic drivers of phenotypes that lie within the epitranscriptome layer circuitry, and is freely accessible at: www.rnamd.org/rmdisease2.
UR - http://www.scopus.com/inward/record.url?scp=85142208634&partnerID=8YFLogxK
U2 - 10.1093/nar/gkac750
DO - 10.1093/nar/gkac750
M3 - Article
C2 - 36062570
AN - SCOPUS:85142208634
SN - 0305-1048
VL - 51
SP - D1388-D1396
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - D1
ER -
