Open Access Highly Accessed Research article

An improved method for genome wide DNA methylation profiling correlated to transcription and genomic instability in two breast cancer cell lines

Jian Li17*, Fei Gao1234, Ning Li23, Shengting Li1, Guangliang Yin3, Geng Tian23, Shangang Jia23, Kai Wang157, Xiuqing Zhang23, Huanming Yang6, Anders Lade Nielsen1 and Lars Bolund137

Author Affiliations

1 Institute of Human Genetics, University of Aarhus, The Bartholin building, DK-8000, Aarhus C, Denmark

2 Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 101300, PR China

3 Beijing Genomics Institute, Shenzhen, Guangdong, 518083, PR China

4 Graduate School of Chinese Academy of Sciences, Yuquan Road 19A, Beijing, 100039, PR China

5 Bioinformatics Research Center (BiRC), University of Aarhus, Hoegh-Guldergs Gade 10, Building 1090, DK-8000, Aarhus, Denmark

6 Beijing Genomics Institute, B6 Industrial Zone, Beijing, 101300, PR China

7 Danish Centre for Translational Breast cancer research (DCTB), Strandboulevarden 49, DK-2100, Copenhagen, Denmark

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BMC Genomics 2009, 10:223  doi:10.1186/1471-2164-10-223

Published: 13 May 2009



DNA methylation is a widely studied epigenetic mechanism known to correlate with gene repression and genomic stability. Development of sensitive methods for global detection of DNA methylation events is of particular importance.


We here describe a technique, called modified methylation-specific digital karyotyping (MMSDK) based on methylation-specific digital karyotyping (MSDK) with a novel sequencing approach. Briefly, after a tandem digestion of genomic DNA with a methylation-sensitive mapping enzyme and a fragmenting enzyme, short sequence tags are obtained. These tags are amplified, followed by direct, massively parallel sequencing (Solexa 1G Genome Analyzer). This method allows high-throughput and low-cost genome-wide DNA methylation mapping. We applied this method to investigate global DNA methylation profiles for widely used breast cancer cell lines, MCF-7 and MDA-MB-231, which are representatives for luminal-like and mesenchymal-like cancer types, respectively. By comparison, a highly similar overall DNA methylation pattern was revealed for the two cell lines. However a cohort of individual genomic loci with significantly different DNA methylation status between two cell lines was identified. Furthermore, we revealed a genome-wide significant correlation between gene expression and the methylation status of gene promoters with CpG islands (CGIs) in the two cancer cell lines, and a correlation of gene expression and the methylation status of promoters without CGIs in MCF-7 cells.


The MMSDK method will be a valuable tool to increase the current knowledge of genome wide DNA methylation profiles.