DNA methylation is a key regulatory layer of the epigenome, shaping cell identity by influencing chromatin organization and gene activity. Methylation patterns serve as robust biomarkers—detectable even from peripheral blood—and enable powerful inferences about cellular state and lineage. However, generating whole-genome methylation maps has traditionally relied on bisulfite sequencing, a labour-intensive and low-throughput method that is difficult to automate.
Enzymatic DNA shearing in combination with enzymatic methylome sequencing (EM-seq), removes several manual steps. Using robotics for automated liquid handling now enables scalable and gentle conversion chemistry suitable for high-throughput applications. We established a fully automated workflow for EM-seq library preparation in 96-well format and used it to generate over 1,400 whole-genome methylomes from blood-derived DNA with a failure rate below 1.2%. Sequencing (~140 trillion bp total) demonstrated highly consistent performance across samples with minimal batch variability.
Despite strong library quality metrics (high Q30), EM-seq libraries sequenced on patterned flow-cell Illumina instruments showed reduced output driven by low %PF (passing filter). We discuss a likely mechanistic explanation linked to NEB EM-seq v1 library architecture and provide recommendations for optimizing kit design and adapting the 96-reaction kit for robotic workflows. Together, this work establishes a robust pipeline for population-scale methylome generation and identifies key considerations for EM-seq usage on modern sequencing platforms.