Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications and multiple human diseases but distinguishing the functional or disease-related SNVs from the majority of ‘silent’ variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetics variants and RNA modifications 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 RNA modification sites, we identified a total of 1,366,252 RNA modification (RM)-associated variants that may affect (add or remove RM site) 16 different types of RNA modification (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 COVID-19). Among them, 14,749 disease- and 2,441 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.