RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication

Author:

Song Bowen123ORCID,Wang Xuan1,Liang Zhanmin1,Ma Jiongming13,Huang Daiyun14,Wang Yue24ORCID,de Magalhães João Pedro5ORCID,Rigden Daniel J3,Meng Jia136ORCID,Liu Gang2,Chen Kunqi7ORCID,Wei Zhen15

Affiliation:

1. Department of Biological Sciences, Xi’an Jiaotong-Liverpool University , Suzhou, 215123, China

2. Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University , Suzhou , 215123 , China

3. Institute of Systems, Molecular and Integrative Biology, University of Liverpool , Liverpool L7 8TX, UK

4. Department of Computer Science, University of Liverpool , Liverpool L7 8TX, UK

5. Institute of Life Course and Medical Sciences, University of Liverpool , Liverpool L7 8TX , UK

6. AI University Research Centre, Xi’an Jiaotong-Liverpool University , Suzhou , 215123 , China

7. Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University , Fuzhou , 350004 , China

Abstract

Abstract 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.

Funder

National Natural Science Foundation of China

XJTLU Key Program Special Fund

Scientific Research Foundation for Advanced Talents of Fujian Medical University

Publisher

Oxford University Press (OUP)

Subject

Genetics

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