Abstract
Genome wide analysis of DNA methylation provides important information in a variety of diseases, including cancer. Here, we describe a simple method, Digital Restriction Enzyme Analysis of Methylation (DREAM), based on next generation sequencing analysis of methylation-specific signatures created by sequential digestion of genomic DNA with SmaI and XmaI enzymes. DREAM provides information on 150,000 unique CpG sites, of which 39,000 are in CpG islands and 30,000 are at transcription start sites of 13,000 RefSeq genes. We analyzed DNA methylation in healthy white blood cells and found methylation patterns to be remarkably uniform. Inter individual differences > 30% were observed only at 227 of 28,331 (0.8%) of autosomal CpG sites. Similarly, > 30% differences were observed at only 59 sites when we comparing the cord and adult blood. These conserved methylation patterns contrasted with extensive changes affecting 18–40% of CpG sites in a patient with acute myeloid leukemia and in two leukemia cell lines. The method is cost effective, quantitative (r2 = 0.93 when compared with bisulfite pyrosequencing) and reproducible (r2 = 0.997). Using 100-fold coverage, DREAM can detect differences in methylation greater than 10% or 30% with a false positive rate below 0.05 or 0.001, respectively. DREAM can be useful in quantifying epigenetic effects of environment and nutrition, correlating developmental epigenetic variation with phenotypes, understanding epigenetics of cancer and chronic diseases, measuring the effects of drugs on DNA methylation or deriving new biological insights into mammalian genomes.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Acknowledgments
The data discussed in this publication have been deposited in NCBI's Gene Expression OmnibusCitation47 and are accessible through GEO Series accession number GSE39787 (www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39787). This work was supported by National Institutes of Health grants CA100632, CA121104, CA046939, CA123344, CA016672 and DE022015; a grant from the Stand Up to Cancer Foundations and a grant from the University of Texas MD Anderson Center for Cancer Epigenetics. J.P.I. is an American Cancer Society Clinical Research professor supported by a generous gift from the F. M. Kirby Foundation.
Supplemental Materials
Supplemental materials may be found here: www.landesbioscience.com/journals/epigenetics/article/22552