Nature reviews. Molecular cell biologyOct 14, 2025

Detecting single RNA molecule changes using nanopore sequencing and base-calling models

mRNA Technology Weekly Brief ↗PubMed ↗DOI ↗

Updated Jan 7, 2026

Abstract

Over 20-fold differences were observed in the number of predicted N-methyladenosine (mA)-modified sites across three base-calling models.

Nanopore direct RNA sequencing can detect RNA modifications in native RNA molecules.
Modification prediction has been integrated into base-calling with pretrained, modification-aware models.
Current models are available for mA, inosine (I), pseudouridine (Ψ), and N-methylcytosine (mC).
Key limitations include potential cross-reactivities with other modifications and variability in false positive rates.
Threshold choices for modification calling and model accuracy validation remain unclear.
Standardized analysis pipelines for RNA modification mapping are currently lacking.

Simplified

Nanopore direct RNA sequencing has enabled the detection of RNA modifications in native RNA molecules, initially through the analysis of signal alterations and base-calling errors. More recently, modification prediction has been integrated into the base-calling step using pretrained, modification-aware base-calling models. So far, such models have been made available for N-methyladenosine (mA), inosine (I), pseudouridine (Ψ) and N-methylcytosine (mC), enabling RNA modification mapping in single-molecule resolution. However, their performance remains largely unclear. In this Progress, we discuss key limitations and uncertainties associated with base-calling models, including their potential cross-reactivities with other modifications, variability in false positive rates across models, unclear threshold choices for modification calling, insufficient orthogonal validation of model accuracy and lack of standardized analysis pipelines. To illustrate some of these issues, we compared the performance of three base-calling models on identical RNA samples, observing over 20-fold differences in the number of predicted mA-modified sites. As these models are increasingly adopted, it is crucial to understand their limitations to ensure best practices and avoid misinterpretation of epitranscriptomics data. 6 6 5 5 6

Full Text

Full text is available at the source.

View Full Text ↗

Funding

Competing interests

Competing interests: E.M.N. is a member of the scientific advisory board of IMMAGINA Biotech. S.C. and E.M.N. have received travel bursaries from ONT to present their work at conferences.

PubMed

Detecting single RNA molecule changes using nanopore sequencing and base-calling models

Abstract

Full Text

Funding

Competing interests

You found one interesting study. We’ll send the next 7.

What Lands in Your Inbox Each Week:

Recent issues from the mrna technology brief

Abstract

Full Text

Funding

Competing interests

Related papers

You found one interesting study. We’ll send the next 7.

What Lands in Your Inbox Each Week:

Recent issues from the mrna technology brief