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Enhanced detection of RNA modifications and read mapping with high-accuracy nanopore RNA basecalling models
Gregor Diensthuber1,2, Leszek P Pryszcz1, Laia Llovera1
1Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain.
Genome Research
|September 13, 2024
Summary
New basecalling models improve nanopore direct RNA sequencing (DRS) for studying RNA modifications. This enhances detection of N6-methyladenosine (m6A) and other modifications, even at low levels, boosting accuracy and read mapping.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Nanopore direct RNA sequencing (DRS) is a powerful tool for epitranscriptome analysis, enabling detection of RNA modifications in native molecules.
- Detecting N6-methyladenosine (m6A) modifications via DRS is challenging due to low basecalling error signals, limiting sensitivity to high stoichiometry sites.
Purpose of the Study:
- To develop and validate alternative RNA basecalling models for enhanced detection of RNA modifications, particularly m6A, in nanopore DRS data.
- To improve the sensitivity and accuracy of nanopore DRS for epitranscriptome studies, especially for low stoichiometry modifications.
Main Methods:
- Utilized alternative RNA basecalling models trained on unmodified sequences to amplify the basecalling error signal associated with m6A modifications.
- Evaluated the performance of these alternative models in terms of m6A detection sensitivity, basecalling accuracy, and read mappability compared to standard models.
- Assessed the impact of alternative models on the detection of other RNA modifications like pseudouridine (Ψ) and N1-methylpseudouridine (m1Ψ).
Main Results:
- Alternative basecalling models significantly increased the error signal for m6A, enabling enhanced detection and improved sensitivity at low stoichiometries.
- High-accuracy alternative models achieved up to 97% median basecalling accuracy, surpassing current models (91% median accuracy).
- The use of alternative models led to increased read mapping, particularly for shorter RNA fractions, and enhanced detection of Ψ and m1Ψ modifications.
Conclusions:
- Alternative RNA basecalling models represent a significant advancement for nanopore DRS, improving the detection of various RNA modifications.
- These models enhance read mappability and overall basecalling accuracy, broadening the applicability of DRS for epitranscriptomic research.
- The developed approach offers a more sensitive and accurate method for studying the dynamic landscape of RNA modifications.
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