SeqWord Motif Mapper: A Tool for Rapid Statistical Analysis and Visualization of Epigenetic Modifications in Bacterial Genomes

Abstract

Genomic methylation in bacteria plays a crucial role in gene regulation, chromosome replication, pathogenicity, and defense against phages. While single-molecule real-time (SMRT) sequencing technologies have advanced the detection of epigenetically modified bases, the statistical analysis of their distribution and the possible roles they play in bacterial cells remains challenging. To address this gap, we developed SeqWord Motif Mapper (SWMM), a computational tool designed for the statistical analysis and visualization of bacterial methylation patterns. SWMM utilizes PacBio sequencing data to identify sequence coverage, methylation motif distribution, and putative functional associations. Implemented in Python 3.9, the tool is platform-independent and requires minimal dependencies, making it accessible to a wide range of users. The SWMM command-line interface and a web-based version of the program facilitate the exploration of epigenetic modifications across bacterial genomes. Through case studies on different bacterial and archaeal taxa, we demonstrated that genome methylation in microorganisms extends beyond canonical sites and possibly influences gene expression, adaptation, and genome architecture. The tool enables detailed statistical evaluation of methylation motif distribution and provides insights into the potential regulatory roles of epigenetic modifications in bacterial genomes. SWMM is freely available at https://begp.bi.up.ac.za, with source code hosted on GitHub at https://github.com/chrilef/BactEpiGenPro.