MoDorado: enhanced detection of tRNA modifications in nanopore sequencing by off-label use of modification callers

Rapid and accurate identification of transfer RNA (tRNA) modifications is crucial for understanding their role in protein translation and disease. However, their detection on tRNAs is challenging due to high modification density. With the release of the nanopore direct RNA sequencing kit SQK-RNA004, de novo modification calling models became available for pseudouridine (Ψ), m6A, inosine, and m5C, as part of the Dorado basecaller. By applying the Ψ model to tRNAs, we mapped both known and previously uncharacterized Ψ sites in Schizosaccharomyces pombe, and identified the corresponding pseudouridine synthases. This led to the discovery of two novel modification sites, Pus7-dependent Ψ8 and Pus1-dependent Ψ22. Furthermore, we have developed MoDorado, an algorithm to detect modifications beyond those used in model training ("off-label use"). It does so by assessing differences in modification predictions between modified and nonmodified samples using pre-trained, modification-specific models. By repurposing the Ψ/m6A/inosine/m5C models, MoDorado detected seven additional modifications (ncm5U, mcm5U, mcm5s2U, m7G, queuosine, m1A, and i6A), thus generating an expanded map of these tRNA modifications in S. pombe. This work provides a generalized framework for leveraging pre-trained models in determining the intricate landscape of tRNA modifications.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-08-11
DOI
https://doi.org/10.1093/nar/gkaf795
Citations
8
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
6.45

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article

MoDorado: enhanced detection of tRNA modifications in nanopore sequencing by off-label use of modification callers

Wiep van der Toorn, Michael Piechotta, Bhargesh Indravadan Patel, Wang Liu-wei et al.
8 citations
Nucleic Acids Research
RNA modifications and cancer
6.45
article

MoDorado: enhanced detection of tRNA modifications in nanopore sequencing by off-label use of modification callers

Wiep van der Toorn, Michael Piechotta, Bhargesh Indravadan Patel, Wang Liu-wei, Ann E. Ehrenhofer‐Murray, Christoph Dieterich, Max von Kleist, Yu Sun, Franziskus N. M. Rübsam
article en
8 citations

Abstract

Rapid and accurate identification of transfer RNA (tRNA) modifications is crucial for understanding their role in protein translation and disease. However, their detection on tRNAs is challenging due to high modification density. With the release of the nanopore direct RNA sequencing kit SQK-RNA004, de novo modification calling models became available for pseudouridine (Ψ), m6A, inosine, and m5C, as part of the Dorado basecaller. By applying the Ψ model to tRNAs, we mapped both known and previously uncharacterized Ψ sites in Schizosaccharomyces pombe, and identified the corresponding pseudouridine synthases. This led to the discovery of two novel modification sites, Pus7-dependent Ψ8 and Pus1-dependent Ψ22. Furthermore, we have developed MoDorado, an algorithm to detect modifications beyond those used in model training ("off-label use"). It does so by assessing differences in modification predictions between modified and nonmodified samples using pre-trained, modification-specific models. By repurposing the Ψ/m6A/inosine/m5C models, MoDorado detected seven additional modifications (ncm5U, mcm5U, mcm5s2U, m7G, queuosine, m1A, and i6A), thus generating an expanded map of these tRNA modifications in S. pombe. This work provides a generalized framework for leveraging pre-trained models in determining the intricate landscape of tRNA modifications.

Nucleic Acids ResearchVol. 53(15)
Heidelberg University (DE), Robert Koch Institute (DE), University Hospital Heidelberg (DE), Humboldt-Universität zu Berlin (DE), German Centre for Cardiovascular Research (DE), Max Planck Institute for Molecular Genetics (DE), Freie Universität Berlin (DE)
European Commission, Deutscher Akademischer Austauschdienst, Deutsche Forschungsgemeinschaft, China Scholarship Council, Humboldt-Universität zu Berlin, Berlin Mathematics Research Center MATH+
Openalex Percentile: Top 3%
RNA modifications and cancer
6.45
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