Digital Restriction Enzyme Analysis of Methylation (DREAM) by Next Generation Sequencing Yields High Resolution Maps of DNA Methylation.

Abstract 567 Methylation of CpG dinucleotides in DNA is a key epigenetic feature important for × chromosome inactivation, silencing of retrotransposons and genomic imprinting. DNA methylation undergoes complex changes in leukemia, most notably methylation of CpG islands at promoters and associated gene silencing. The direct comparison of epigenomes in normal and neoplastic blood cells will likely increase our understanding of the complex pathology of leukemia. We have developed a digital restriction enzyme analysis of methylation (DREAM) for quantitative mapping of DNA methylation with high resolution on the genome-wide scale. To perform the analysis, genomic DNA is sequentially digested with a pair of enzymes recognizing the same restriction site (CCCGGG) containing a CpG dinucleotide. The first enzyme, SmaI, cuts only at unmethylated CpG and leaves blunt ends. The second enzyme, XmaI, is not blocked by methylation and leaves a short 5' overhang. The enzymes thus create methylation-specific signatures at ends of digested DNA fragments. These are deciphered by next generation sequencing. Methylation levels for each sequenced restriction site are calculated based on the numbers of DNA molecules with the methylated or unmethylated signatures. Using the DREAM method and sequencing on the Illumina Gene Analyzer II platform, we analyzed DNA methylation in a normal adult blood sample. We acquired 32.5 million sequence tags; of these, 16.6 million were mapped to SmaI/XmaI sites unique in the human genome. With a threshold of minimum 5-fold coverage, we obtained quantitative information on the DNA methylation level of 85,171 CpG sites (23% of all genomic SmaI/XmaI sites) in 21,240 genes. The accuracy of DREAM methylation data was validated by a strong correlation with the bisulfite pyrosequencing analysis of 49 genes (R=0.83) and of spiked in plasmid DNA. In normal blood, methylation was strikingly bimodal with 39% sites showing methylation levels below 5% and 28% sites being hypermethylated at levels >95%. Methylation was largely absent within CpG islands (CGI) and more prevalent outside (non-CGI). Close to transcription start sites (within 500 bp), methylation >75% was found only in 0.65% of CGIs compared to 14% in non-CGIs (P<0.001). The methylated CGI promoters were significantly enriched for genes expressed in spermatogenesis and likely correspond to a class of potential cancer-testis antigens previously identified. Away from transcription start sites (>2 kb), methylation >75% was found in 24% of CGIs compared to 72% of non-CGIs (P<0.001). Transcription end regions were methylated in 20% in CGIs compared to 68% in non-CGIs (P<0.001). Also, we observed that 1.4% of CGIs had evidence of half methylation (35-65%), representing potentially imprinted genes. Indeed, this class includes known imprinted regions at chromosomes 8q24.3 and 11p15. Finally, we compared non-CGI promoters showing significant methylation to those free of methylation. Unmethylated promoters were more likely to be expressed in normal blood, and to encode for genes involved in metabolic processes and their regulation. In conclusion, high resolution quantitative methylation analysis is feasible using the DREAM method, and reveals important classes of genes based on methylation in normal blood. Disclosures: No relevant conflicts of interest to declare.