Table 2 Summary of DNA methylation editing and detection techniques
From: DNA methylation in melanoma immunotherapy: mechanisms and therapeutic opportunities
Technique | Principle | Advantages | Limitations | Applications in Research |
|---|---|---|---|---|
CRISPR-dCas9 methylation editing | Catalytically inactive Cas9 (dCas9) fused to DNMT or TET enzymes for targeted methylation or demethylation; SunTag enhances targeting efficiency via peptide arrays | Precise locus-specific targeting; easy sgRNA design; enhanced efficiency using SunTag; maintains epigenetic memory | Potential off-target methylation; complexity in SunTag optimization | Precise epigenetic editing; functional studies of gene regulation; modeling tumor suppressor and oncogene expression |
CRISPRoff/CRISPRon | Programmable, reversible epigenetic modulation (DNA methylation and histone modifications) using dCas9 fusion proteins | Stable and reversible epigenetic changes; minimal risk of DNA mutations | Potential off-target effects; requires further in vivo validation | Studying reversible epigenetic regulation; exploring therapeutic potential for diseases involving aberrant gene silencing or activation |
Genome-wide beadchip arrays (HumanMethylationEPICv2) | Bisulfite-converted DNA hybridized to genome-wide CpG probes (> 900 K sites) | Extensive coverage; validated, cost-effective method for genome-wide methylation profiling. Widely available open access bioinformatic packages for analysis | Limited genome-wide coverage (~ 28 M total CpGs); poor representation of repetitive regions; potential GC bias | Epigenome-wide association studies; biomarker discovery; correlating methylation profiles with clinical outcomes and therapeutic responses |
Enzymatic methylation sequencing (TET2/APOBEC-based) | TET2 and APOBEC enzymes discriminate methylated from unmethylated cytosines without bisulfite-induced degradation | Improved genome-wide coverage; reduced GC bias; more uniform representation of methylation sites | Requires careful enzymatic optimization; bioinformatic complexity | Comprehensive profiling of DNA methylation; improved assessment of methylation patterns in diverse cell types, including rare immune cells |
Single-cell bisulfite sequencing (scWGBS, RRBS, sci-MET) | Single-cell resolution DNA methylation analysis via bisulfite conversion | High-resolution methylation profiling; reveals cellular heterogeneity; detects rare or transient cell states | Technically demanding; expensive; requires fresh tissue and specialized bioinformatics tools | Characterizing tumor and tissue heterogeneity; exploring mechanisms of drug resistance; integration with other single-cell “omics” approaches |
Single-cell CGI-seq (scCGI-seq) | Conversion-free method using methylation-sensitive restriction enzymes for single-cell methylation profiling | Scalable; avoids DNA damage associated with bisulfite treatment; suited for CpG island methylation | Limited to CpG-rich regions; intermediate genome coverage | Profiling methylation in CpG islands at single-cell resolution; integration into multi-omics single-cell workflows |