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

## TL;DR

MethylomeMiner is a new tool that simplifies the analysis of DNA methylation patterns in bacteria using nanopore sequencing data.

## Contribution

The novel contribution is a Python-based tool for processing and interpreting bacterial methylation data with genome annotation and pangenome support.

## Key findings

- MethylomeMiner enables high-confidence identification of methylation sites based on coverage and methylation rate.
- The tool supports population-level analysis by comparing methylation patterns across multiple bacterial genomes.
- It integrates into existing workflows to help uncover the functional roles of DNA methylation in bacteria.

## 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.