Work

Detecting m6A at single-molecular resolution via direct RNA sequencing and realistic training data

Year: 2024

Type: article

Abstract: Direct RNA sequencing offers the possibility to simultaneously identify canonical bases and epi-transcriptomic modifications in each single RNA molecule. Thus far, the development of computational methods has been hampered by the lack of biologically realistic training data that carries modification labels at molecular resolution. Here, we report on the synthesis of such samples and the development of a bespoke algorithm, mAFiA (m 6 A Finding Algorithm), that accurately detects single m 6 A nucleotides in both synthetic RNAs and natural mRNA on single read level. Our approach uncovers distinct modification patterns in single molecules that would appear identical at the ensemble level. Compared to existing methods, mAFiA also demonstrates improved accuracy in measuring site-level m 6 A stoichiometry in biological samples.

Source: Nature Communications

DOI: 10.1038/s41467-024-47661-2

Authors: Adrian Chan, Isabel S. Naarmann-de Vries, Carolin P. M. Scheitl, Claudia Höbartner, Christoph Dieterich

Institutions: Heidelberg University, German Centre for Cardiovascular Research, University of Würzburg

Language: English

Topic: RNA modifications and cancer

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $6,790

Funders: Deutsche Forschungsgemeinschaft, Klaus Tschira Stiftung