This study investigates the dynamic DNA methylation landscape in the human genome across 30 diverse cell and tissue types using whole-genome bisulfite sequencing (WGBS). The authors identified 21.8% of autosomal CpGs that exhibit dynamic changes, primarily located distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, such as enhancers and transcription factor binding sites (TFBS), suggesting their role in lineage-specific regulation. The study also found that differentially methylated regions (DMRs) often contain SNPs associated with cell type-related diseases, as determined by GWAS. The authors highlight the inefficiency of WGBS, with 70-80% of sequencing reads providing little information about CpG methylation. They demonstrate the utility of their DMR set by classifying unknown samples and identifying representative signature regions that recapitulate major DNA methylation dynamics. The findings suggest that only a fraction of CpGs change their methylation state as part of coordinated regulatory programs, providing a starting point for more effective reduced representation approaches to capture informative CpGs and pinpoint regulatory elements.This study investigates the dynamic DNA methylation landscape in the human genome across 30 diverse cell and tissue types using whole-genome bisulfite sequencing (WGBS). The authors identified 21.8% of autosomal CpGs that exhibit dynamic changes, primarily located distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, such as enhancers and transcription factor binding sites (TFBS), suggesting their role in lineage-specific regulation. The study also found that differentially methylated regions (DMRs) often contain SNPs associated with cell type-related diseases, as determined by GWAS. The authors highlight the inefficiency of WGBS, with 70-80% of sequencing reads providing little information about CpG methylation. They demonstrate the utility of their DMR set by classifying unknown samples and identifying representative signature regions that recapitulate major DNA methylation dynamics. The findings suggest that only a fraction of CpGs change their methylation state as part of coordinated regulatory programs, providing a starting point for more effective reduced representation approaches to capture informative CpGs and pinpoint regulatory elements.