MethylomeMiner: A novel tool for high-resolution analysis of bacterial methylation patterns from nanopore sequencing

DNA methylation plays a key role in gene regulation, genome stability, bacterial adaptation, and many other essential cellular processes. Thanks to nanopore sequencing technology, it is now possible to detect these modifications during sequencing without any prior chemical treatment. However, methylation data processing and their interpretation in a biological context remain challenging as there are no convenient and easy-to-use tools available for this purpose. Therefore, here, we present a simple Python-based tool, MethylomeMiner, to process methylation calls from nanopore sequencing. The tool allows high-confidence methylation sites to be selected based on coverage and methylation rate and assigned to coding or non-coding regions using genome annotation. In addition, the tool supports population-level analysis using pangenome data to compare methylation patterns across multiple bacterial genomes. Altogether, MethylomeMiner provides a straightforward and reproducible workflow that can be easily integrated into existing analyses and helps uncover the functional roles of DNA methylation in bacterial genomes.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.10.047
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

MethylomeMiner: A novel tool for high-resolution analysis of bacterial methylation patterns from nanopore sequencing

Martina Lengerová, Matěj Bezdíček, Helena Škutková, Katerina Jureckova et al.
Computational and Structural Biotechnology Journal
Genomics and Phylogenetic Studies
article

MethylomeMiner: A novel tool for high-resolution analysis of bacterial methylation patterns from nanopore sequencing

Martina Lengerová, Matěj Bezdíček, Helena Škutková, Katerina Jureckova, Marketa Jakubickova, Michaela Zbudilova
article en

Abstract

DNA methylation plays a key role in gene regulation, genome stability, bacterial adaptation, and many other essential cellular processes. Thanks to nanopore sequencing technology, it is now possible to detect these modifications during sequencing without any prior chemical treatment. However, methylation data processing and their interpretation in a biological context remain challenging as there are no convenient and easy-to-use tools available for this purpose. Therefore, here, we present a simple Python-based tool, MethylomeMiner, to process methylation calls from nanopore sequencing. The tool allows high-confidence methylation sites to be selected based on coverage and methylation rate and assigned to coding or non-coding regions using genome annotation. In addition, the tool supports population-level analysis using pangenome data to compare methylation patterns across multiple bacterial genomes. Altogether, MethylomeMiner provides a straightforward and reproducible workflow that can be easily integrated into existing analyses and helps uncover the functional roles of DNA methylation in bacterial genomes.

Computational and Structural Biotechnology JournalVol. 27
Masaryk University (CZ), Brno University of Technology (CZ)
Grantová Agentura České Republiky
Openalex Percentile: Top 73%
Genomics and Phylogenetic Studies
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