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    DNA methylation is a major type of epigenetic modifications that plays a crucial role in a variety of physiological and pathological processes such as gene regulation, biological development, disease initiation/progression, etc. Alteration of methylation pattern has been repeatedly observed in various cancer types. Compared to whole genome methylation profiling studies, methylation detection of only selected candidate regions is a more targeted approach and it makes methylation analysis with large sample size more feasible and accessible in different settings. However, due to the limitations of sanger sequencing in throughput and cost, the targeted approach has long been restricted in small scale studies and applications. In this context, MethylTarget combines Genesky proprietary target enrichment techniques and NGS to offer a novel solution for methylation state analysis of targeted genomic regions. MethylTarget dramatically increases data throughput and brings down the cost.

    Technique Highlights

    High Resolution Methylation state detection at single-nucleotide resolution
    High efficiency, Fast turnaround Effective screening of methylation state through selected genomic regions on NGS platform
    Cost Effective spend much less on same task compared to Sanger method
    Proved quality of probe design High-quality probe design based on Genesky’s years of experience in the area of targeted genomic region analysis ensures the enrichment quality.
    Low sample input Requires 1ug to run the assay compared to >5 ug in other Methylation analysis platforms

    Sample Requirement

    Sample Type: Genomic DNA
    Amount: DNA >= 1 ug; concentration >= 100 ng/ul
    Purity: OD260/280 = 1.7~2.0
    Sample without severe degradation 

    Service Workflow

    1. Customized experimental design 
    2. Sample receiving
    3. DNA extraction and QC
    4. Library preparation and sequencing 

    5. Project closure report 

    Data Analysis Workflow

    1. Raw data statistics
    2. QC results
    3. Alignment against reference genome
    4. Methylation site prediction & CG,CHG, CHH categorization 
    5. Estimation of DNA methylation level
    6. 5mC level in different gene structural elements
    7. Identification of differential methylated regions
    8. Function annotation of the proximate genes near differential methylated regions
    9. Customized data analysis


    1. Project closure report

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