Project description:The goal of the experiment – genome-wide profiling of DNA methylation reveals a class of normally methylated CpG island promoters Keywords: DNA methylation, Methylated CpG island amplification coupled with promoter arrays, normal tissue
Project description:We propose that tetraploidy induces epigentic changes including DNA methylation due to the abnormal chromatin in the cells. To test our hypothesis, we employed methylated CpG island recovery assay (MIRA) assisted microarray to determine the DNA methylation profiles in both diploid and tetraploid cells. First, we conducted a methylated-CpG island recovery assay (MIRA). Briefly, we enriched for methylated CpG islands with methylated DNA binding proteins, MBD2/MBD3L1. The pulled down DNA fragments containing CpG islands and input DNA fragments were amplified with real-time PCR. After labeling, they were hybridized to CpG island promoter array. Data were collected and analyzed.
Project description:Epigenomics is developing a colon cancer screening assay based on differential methylation of specific CpG sites for the detection of early stage disease. A genome-wide methylation analysis and oligonucleotide array study using DNA from various stages of colon cancer and normal tissue have been completed to obtain candidate CpG markers. Based on results obtained in the above studies, Epigenomics has moved to the final stages of feasibility with a specific, highly sensitive real-time marker assay that is able to detect colon cancer DNA in blood plasma.
Project description:Genome-wide methylation analysis was performed by methylated DNA immunoprecipitation (MeDIP)-CpG island (CGI) microarray analysis to identify candidate CGIs specifically methylated in mouse colon tumors associated with colitis. We sucessfully identified 23 candidate CGIs methylated in tumors.
Project description:Genome-wide methylation analysis was performed by methylated DNA immunoprecipitation (MeDIP)-CpG island (CGI) microarray analysis to identify the CpG methylation levels of Parp-1 wildtype, Parp-1 deficient or Parp inhibitor treated mouse embryonic stem cells.
Project description:Methylation of CpG islands is associated with transcriptional repression and, in cancer, leads to the abnormal silencing of tumor-suppressor genes. We developed a novel and robust technique that allows the unbiased, genome wide detection of CpG-methylation in limited DNA samples, without applying methylation-sensitive restriction endonucleases or bisulfite-treatment. The approach is based on a recombinant, methyl-CpG binding protein that efficiently binds CpG-methylated DNA depending on its degree of CpG methylation. Its application in methyl-CpG immunoprecipitation (MCIp) facilitates the monitoring of CpG-island methylation on a genome wide level (in combination with CpG-island microarrays). The power of this novel approach was demonstrated by the profiling of three myeloid cell lines leading to the identification of more than a hundred aberrantly methylated CpG islands and many novel, putative tumor-suppressor genes. Keywords: MCIp on Chip
Project description:Methylated genomic fragments from tumor DNA and matching normal control were enriched with the methylated-CpG island recovery assay (MIRA); amplified, labeled and hybridized on Agilent CpG island tiling oligo arrays. MIRA enriched samples from tumor were labeled with Cy5 while MIRA enriched DNA samples from normal tissue were labeled with Cy3. Keywords: Cancer
Project description:Embryonic stem cells can be differentiated in vitro to produce a variety of somatic cell types. We have employed the mDIP method combined with hybridization to a tiling microarray to obtain a genome-wide methylation analysis of all UnMethylated Regions(UMRs). We show that this differentiation is accompanied by an intrinsic process of extensive aberrant CpG island de novo methylation that includes developmental and cancer target genes. CpG-methylated genomic DNA was enriched using a methyl-DNA immunoprecipitation (mDIP) assay. DNA from the input and bound (enriched) DNA for each sample were labeled and hybridized on the array to define the methylation state of each region.
Project description:Background: Researching the murine epigenome in disease models has been hampered by the lack of an appropriate and cost-effective DNA methylation array. Until recently, investigators have been limited to the relatively expensive and analysis intensive bisulphite sequencing methods. Here, we performed a comprehensive, comparative analysis between the new Mouse Methylation BeadChip (MMB) and reduced representation bisulphite sequencing (RRBS) in two murine models of colorectal carcinogenesis, providing insight into the utility to each platforms in a real world environment. Results: We captured 1.47x106 CpGs by RRBS and 2.64x105 CpGs by MMB, mapping to 13,778 and 13,365 CpG islands, respectively. RRBS captured significantly more CpGs per island (median 41 for RRBS versus 2 for MMB). We found that 64.4% of intra-island CpG methylation variability can be captured by measuring approximately one quarter of CpG island (CGI) CpGs. MMB was more precise in measuring DNA methylation, especially at sites that had low RRBS coverage. This impacted differential methylation analysis, with more statistically significantly differentially methylated CpG sites identified by MMB in all experimental conditions, however the difference was minute when appropriate thresholding for the magnitude of methylation change (0.2 beta value difference) was applied, providing confidence that both techniques can identify similar differential DNA methylation. Gene ontology enrichment analysis of differentially hypermethylated gene promoters identified similar biological processes and pathways by both RRBS and MMB across two murine model systems. Conclusion: MMB is an effective tool for profiling the murine methylome that performs comparably to RRBS, identifying similar differentially methylated pathways. Although MMB captures a similar proportion of CpG islands, it does so with fewer CpGs per island. We show that subsampling informative CpGs from CpG islands is an appropriate strategy to capture whole island variation. Choice of technology is experiment dependent and will be predicated on the underlying biology being probed.
Project description:Background: Researching the murine epigenome in disease models has been hampered by the lack of an appropriate and cost-effective DNA methylation array. Until recently, investigators have been limited to the relatively expensive and analysis intensive bisulphite sequencing methods. Here, we performed a comprehensive, comparative analysis between the new Mouse Methylation BeadChip (MMB) and reduced representation bisulphite sequencing (RRBS) in two murine models of colorectal carcinogenesis, providing insight into the utility to each platforms in a real world environment. Results: We captured 1.47x106 CpGs by RRBS and 2.64x105 CpGs by MMB, mapping to 13,778 and 13,365 CpG islands, respectively. RRBS captured significantly more CpGs per island (median 41 for RRBS versus 2 for MMB). We found that 64.4% of intra-island CpG methylation variability can be captured by measuring approximately one quarter of CpG island (CGI) CpGs. MMB was more precise in measuring DNA methylation, especially at sites that had low RRBS coverage. This impacted differential methylation analysis, with more statistically significantly differentially methylated CpG sites identified by MMB in all experimental conditions, however the difference was minute when appropriate thresholding for the magnitude of methylation change (0.2 beta value difference) was applied, providing confidence that both techniques can identify similar differential DNA methylation. Gene ontology enrichment analysis of differentially hypermethylated gene promoters identified similar biological processes and pathways by both RRBS and MMB across two murine model systems. Conclusion: MMB is an effective tool for profiling the murine methylome that performs comparably to RRBS, identifying similar differentially methylated pathways. Although MMB captures a similar proportion of CpG islands, it does so with fewer CpGs per island. We show that subsampling informative CpGs from CpG islands is an appropriate strategy to capture whole island variation. Choice of technology is experiment dependent and will be predicated on the underlying biology being probed.