De novo basecalling of RNA modifications at single molecule and nucleotide resolution.

ABSTRACT: RNA 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.

SUBMITTER: Cruciani S 

PROVIDER: S-EPMC11853310 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature