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

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 previou...

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Autores principales: Song, Bowen, Wang, Xuan, Liang, Zhanmin, Ma, Jiongming, Huang, Daiyun, Wang, Yue, de Magalhães, João Pedro, Rigden, Daniel J, Meng, Jia, Liu, Gang, Chen, Kunqi, Wei, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825452/
https://www.ncbi.nlm.nih.gov/pubmed/36062570
http://dx.doi.org/10.1093/nar/gkac750
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author Song, Bowen
Wang, Xuan
Liang, Zhanmin
Ma, Jiongming
Huang, Daiyun
Wang, Yue
de Magalhães, João Pedro
Rigden, Daniel J
Meng, Jia
Liu, Gang
Chen, Kunqi
Wei, Zhen
author_facet Song, Bowen
Wang, Xuan
Liang, Zhanmin
Ma, Jiongming
Huang, Daiyun
Wang, Yue
de Magalhães, João Pedro
Rigden, Daniel J
Meng, Jia
Liu, Gang
Chen, Kunqi
Wei, Zhen
author_sort Song, Bowen
collection PubMed
description 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 (m(6)A, m(5)C, m(1)A, m(5)U, Ψ, m(6)Am, m(7)G, A-to-I, ac(4)C, Am, Cm, Um, Gm, hm(5)C, D and f(5)C) 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.
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spelling pubmed-98254522023-01-10 RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication Song, Bowen Wang, Xuan Liang, Zhanmin Ma, Jiongming Huang, Daiyun Wang, Yue de Magalhães, João Pedro Rigden, Daniel J Meng, Jia Liu, Gang Chen, Kunqi Wei, Zhen Nucleic Acids Res Database Issue 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 (m(6)A, m(5)C, m(1)A, m(5)U, Ψ, m(6)Am, m(7)G, A-to-I, ac(4)C, Am, Cm, Um, Gm, hm(5)C, D and f(5)C) 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. Oxford University Press 2022-09-05 /pmc/articles/PMC9825452/ /pubmed/36062570 http://dx.doi.org/10.1093/nar/gkac750 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Song, Bowen
Wang, Xuan
Liang, Zhanmin
Ma, Jiongming
Huang, Daiyun
Wang, Yue
de Magalhães, João Pedro
Rigden, Daniel J
Meng, Jia
Liu, Gang
Chen, Kunqi
Wei, Zhen
RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication
title RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication
title_full RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication
title_fullStr RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication
title_full_unstemmed RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication
title_short RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication
title_sort rmdisease v2.0: an updated database of genetic variants that affect rna modifications with disease and trait implication
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825452/
https://www.ncbi.nlm.nih.gov/pubmed/36062570
http://dx.doi.org/10.1093/nar/gkac750
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