Ab initio detection of multiple epitranscriptomic modifications from Oxford nanopore technology direct RNA sequencing data

Read full text
Authors: Adriano Fonzino, Bruno Fosso, Grazia Visci, Carmela Gissi, Graziano Pesole, Ernesto Picardi
Cited by: 1
References: 28

Abstract

Charting the eukaryotic epitranscriptome by direct RNA sequencing is promising but still very challenging, as current bioinformatics tools are based on modification-unaware software and require multiple modification-specific learning steps. Here, we introduce NanoSpeech, a modification-aware basecaller for the ab initio simultaneous detection of multiple modified bases using a transformer model, and NanoListener, which implements a simulated randomers strategy for robust training datasets and a new generation of ONT basecallers. NanoListener and NanoSpeech are independent of the specific ONT chemistry. Once a training dataset has been created, a single model with an expanded vocabulary can accurately basecall both unmodified and modified bases.

Fields of Study & Subjects

RNA modifications and cancer RNA and protein synthesis mechanisms RNA regulation and disease

Publication details

Journal / source
Briefings in Bioinformatics
Publisher
Oxford University Press (OUP)
Volume
27
Issue
1
Publication date
1 January 2026
Language
EN