Computational Workflow for Genome-Wide DNA Methylation Profiling and Differential Methylation Analysis

DNA methylation is a crucial epigenetic modification that influences gene expression and plays a role in various biological processes. High-throughput sequencing techniques, such as bisulfite sequencing (BS-seq) and enzymatic methyl sequencing (EM-seq), enable genome-wide profiling of DNA methylation patterns with single-base resolution. In this protocol, we present a bioinformatics pipeline for analyzing genome-wide DNA methylation. We outline the step-by-step process of the essential analyses, including quality control using FASTQ for BS- and EM-seqs raw reads, read alignment with commonly used aligners such as Bowtie2 and BS-Seeker2, DNA methylation calling to generate CGmap files, identification of differentially methylated regions (DMRs) using tools including MethylC-analyzer and HOME, data visualization, and post-alignment analyses. Compared to existing workflows, this pipeline integrates multiple steps into a single protocol, lowering the technical barrier, improving reproducibility, and offering flexibility for both plant and animal methylome studies. To illustrate the application of BS-seq and EM-seq, we demonstrate a case study on analyzing a mutant in Arabidopsis thaliana with a mutation in the met1 gene, which encodes a DNA methyltransferase, and results in global CG hypomethylation and altered gene regulation. This example highlights the biological insights that can be gained through systematic methylome analysis. Our workflow is adaptable to any organism with a reference genome and provides a robust framework for uncovering methylation-associated regulatory mechanisms. All scripts and detailed instructions are provided in GitHub repository: https://github.com/PaoyangLab/Methylation_Analysis. Key features • Provides a comprehensive pipeline for genome-wide DNA methylation analysis. • Step-by-step command line for DMR identification and post-analysis with visualization.