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Table 1 Different methods in genome-wide methylation profiling

From: DNA methylation: potential biomarker in Hepatocellular Carcinoma

 

Platform

Features

Number of regions analysed per sample

Methylation information on site specific CpG loci

Methylation information on non-CpG loci

Advantages

Disadvantages

Microarray based

Methylated CpG Island Amplification and Microarray (MCAM-chip)

Enzyme-based techniques that rely on restriction enzymes (SmaI and XmaI) followed by profiling on promoter array

~25,000 human promoters (depends on array density)

No

No

Do not require bisulfite conversion, good coverage on region with low CpG density.

Require substantial quantities of input genomic DNA, low sample throughput, do not report methylation status at single nucleotide level, bias may occur due to genomic distribution of CpG loci, limited to mostly promoter regions.

 

Differential Methylation Hybridization and Microarray (DMH-chip)

Enzyme-based techniques that rely on restriction enzymes (MseI and BstUI) followed by profiling on promoter array

     
 

Methylated DNA Immunoprecipitation and Microarray (MeDIP-chip)

Immunoprecipitation of methylated DNA with a monoclonal antibody followed by profiling on promoter array

     

Beadarray based

GoldenGate

Bisulfite convertion of DNA followed by microbead based microarray

~1,500 CpG sites

Yes

No

Require minimum input genomic DNA, high sample throughput, provide methylation status at CpG loci, fairly accurate and reproducible.

Bisulfite treatment may not be complete, bisulfite treatment caused DNA degradation, limited to mostly promoter regions.

 

Infinium 27K

~27,000 CpG sites

     
 

Infinium 450K

~450,000 CpG sites

     

High throughput sequencing

Bisulfite sequencing

Bisulphite conversion of DNA followed by capture and high throughput sequencing

Whole genome

Yes

Yes

High resolution mapping of methylation status at single nucleotide level, no cross hybridization bias.

Bisulfite treatment may not be complete, bisulfite treatment caused DNA degradation, low sample throughput, expensive, complex bioinformatic analysis.