Cruciani, SoniaDelgado-Tejedor, AnnaPryszcz, Leszek Piotr, 1985-Medina, RebecaLlovera Nadal, LaiaNovoa, Eva Maria2025-05-142025-05-142025Cruciani S, Delgado-Tejedor A, Pryszcz LP, Medina R, Llovera L, Novoa EM. De novo basecalling of RNA modifications at single molecule and nucleotide resolution. Genome Biol. 2025 Feb 25;26(1):38. DOI: 10.1186/s13059-025-03498-61474-7596http://hdl.handle.net/10230/70384RNA modifications influence RNA function and fate, but detecting them in individual molecules remains challenging for most modifications. Here we present a novel methodology to generate training sets and build modification-aware basecalling models. Using this approach, we develop the m6ABasecaller, a basecalling model that predicts m6A modifications from raw nanopore signals. We validate its accuracy in vitro and in vivo, revealing stable m6A modification stoichiometry across isoforms, m6A co-occurrence within RNA molecules, and m6A-dependent effects on poly(A) tails. Finally, we demonstrate that our method generalizes to other RNA and DNA modifications, paving the path towards future efforts detecting other modifications.application/pdfeng© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s13059-025-03498-6BasecallingMachine learningN6-methyladenosineNanopore sequencingNative RNARNA modificationsSingle molecule resolutionTraining datainfo:eu-repo/semantics/openAccess