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

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Abstract

Background: 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. Results: 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. Conclusion: The MMSDK method will be a valuable tool to increase the current knowledge of genome wide DNA methylation profiles. © 2009 Li et al; licensee BioMed Central Ltd.

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Li, J., Gao, F., Li, N., Li, S., Yin, G., Tian, G., … Bolund, L. (2009). An improved method for genome wide DNA methylation profiling correlated to transcription and genomic instability in two breast cancer cell lines. BMC Genomics, 10. https://doi.org/10.1186/1471-2164-10-223

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