Project description:This SuperSeries is composed of the following subset Series: GSE15746: Methylation detection Oligonucleotide Microarray Analysis: high resolution method for CpG island methylation detection 1 GSE15747: Methylation detection Oligonucleotide Microarray Analysis: high resolution method for CpG island methylation detection 2 Refer to individual Series
Project description:This SuperSeries is composed of the following subset Series: GSE27940: Methylation detection Oligonucleotide Microarray Analysis: high resolution method for CpG island methylation detection 3. GSE27943: Gene Expression Array of Human Ovarian Cancer. GSE28013: Representational Oligonucleotide Microarray Analysis (ROMA) array for Copy Number Variation Detection. Refer to individual Series
Project description:We describe an optimized microarray method for identifying genome-wide CpG island methylation called Microarray-based Methylation Assessment of Single Samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimised combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared to a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison to previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation. Keywords: Methylation genomic hybridizations.
Project description:10% of methylation sites in CpG islands. In this study, the genome-wide CpG islands of human sperm, oocyte and pre-implantation embryos were analyzed using the almost complete coverage of promoters and CpG islands (most methylation-producing regions) methylation microarray method (MeDIP-Chip). Dynamic changes in methylation of sub-regions to understand the dynamic pattern of CpG island and promoter methylation, possible regulatory mechanisms of this methylation dynamic change, and function during early embryonic development.
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: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 CpG islend microarray . 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.
