PAGE 3 OF 11 The digestion time is 3 h. As few as four 250 ml tubes were used for each sample pair for ampliﬁcation of the representation each with a 100 ml volume reaction. The cycle conditions were 958C for 1 min, 728C for 3 min, for 15 cycles, followed by a 10-min extension at 728C. The contents of the tubes for each pair were pooled when completed. Representations were cleaned by phe- nol:chloroform extraction, precipitated, resuspended and the concentration determined. Representations were run on a gel to check for content, the McrBC digested repre- sentation being 100–150 bp shorter on average than the Mock. DNA was labeled as described with minor changes (29). Brieﬂy, 2 mg of DNA template was placed (dissolved in TE at pH 8) in a 0.2 ml PCR tube. Five microliters of random nonomers (Sigma Genosys) were added brought up to 25 ml with dH2O, and mixed. The tubes were placed in Tetrad at 1008C for 5 min, then on ice for 5 min. To this 5 ml of NEB Buﬀer 2, 5 ml of dNTPs (0.6 nm dCTP, 1.2-nm dATP, dTTP, dGTP), 5 ml of label (Cy3-dCTP or Cy5-dCTP) from GE Healthcare, 2 ml of NEB Klenow fragment and 2 ml dH2O were added. Procedures for hybridization and washing were followed as reported pre- viously (29) with the exception that oven temperature for hybridization was increased to 508C. In general two hybri- dizations were performed for all samples (carried out as dye swaps to decrease variation of labeled nucleotide incorporation) with the exception for samples analyzed in Figure 2 where four hybridizations were performed. Data analysis and statistics Microarray images were scanned on GenePix 4000B scan- ner and data extracted using Nimblescan software (Nimblegen Systems Inc.). For each probe, the geometric mean of the ratios (GeoMeanRatio) of McrBc and control treated samples were then calculated for each experiment and its associated dye swap. The GeoMeanRatios of all the samples in a dataset were then normalized using quan- tile normalization method (31). The normalized ratios for each experiment were then collapsed to get one value for all probes in every MspI fragment using the median polish model. The collapsed data were then used for further ana- lysis (32). Collapsed fragment data were then subjected to Welch’s two-sample t-test for identifying signiﬁcant diﬀerences between tumors and normals. P-values were corrected for multiple testing by controlling false discov- ery rate (FDR) (Benjamini-Hochberg algorithm) (33) implemented in R [multitest package (34)]. Signiﬁcance threshold was set at 0.001 for breast and 0.05 for the smaller ovarian set. General computations and statistics were performed in Python (35), S-Plus and R (32). Bisulfite sequencing Probes were identiﬁed with diﬀering methylation between the two samples, SKBR3 and chp-skn-1. DNAs from the two samples were treated with bisulﬁte using the EZ DNA Methylation-Gold Kit (Zymo Research, CA, USA). PCR primers were designed to ﬂank the corresponding MspI fragments using MethPrimer (36). For two fragments, the PCR-ampliﬁed fragments were ligated Nucleic Acids Research, 2009, Vol. 37, No. 12 e89 and transformed using the TOPO-TA Cloning kit (Invitrogen, CA, USA); the transformant clones were picked for plasmid extraction, which were then sequenced. To increase throughput, the remaining 32 were sequenced as PCR products. Results for subcloning and direct sequencing were compared to determine the peak heights required to call heterozygotes. McrBC PCR The sequence of the MTSS1 CpG island was obtained, including sequence beyond the ends of the island to aid in the design of PCR primers. Genomic DNA was digested with McrBC or mock digested followed by heat killing. Ten nanograms of DNA was used for PCR with Qiagen Taq polymerase for 30 cycles. Ten microliters of this product was then used as template for an additional 15 cycles of PCR. Products were run on 2% agarose gel, and pictures were taken to illustrate the fragments that were methylated. RESULTS In order to further investigate the role that CpG island methylation plays in cancer, we have designed a new com- prehensive CpG island microarray and have developed robust methods for its use. While sharing some similarities to previously developed methylation arrays (22,27,37), our method has several features that allow for increased CpG- island coverage and sensitivity. First, we utilized high- density oligonucleotide arrays with close to 400K features that allowed us to maximize tiling coverage of 26 219 out of 27 801 (HG17) annotated CpG islands (which includes non-promoter islands), while other CpG island arrays only contain selected promoter sequences (22,37). Second, our hybridization target, because it is made from MspI representations, enriches for CpG island sequences by 10-fold relative to total genomic DNA (based on the size or the MspI ampliﬁable fragment) and thus provides superior hybridization speciﬁcity. In addition since this method is representational based, very little DNA is required (as little as 50 ng) which makes this method well suited to the analysis of primary tumors. Third, each island generally corresponds to mul- tiple MspI fragments, yielding positional information of which portion of an island is methylated. Finally, our method is based on enzymatic depletion of methylated sequences with fewer steps than other methods (37,38); having fewer steps may be less prone to variability. The enzyme chosen for depletion, McrBC, has the unusual recognition site A/GCm(N40–3000)A/GCm and has been used by others to analyze methylation including its appli- cation to arrays (39,40). This enzyme recognizes two methyl groups and because of the varied distance and that the methyl groups can be on the same or both strands (41), a type of combinatorial recognition and cleavage occurs, which greatly increases the number of potentially methylated CpG dinucleotides that can be queried. Using in-silico analysis we calculate using McrBC (speciﬁcally the preferred distance for recognition between methyl cytosines of 40–150 bp) our methodology queries over