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Conserved DNA methylation patterns in healthy blood cells and extensive changes in leukemia measured by a new quantitative technique.

ABSTRACT: We describe a simple method, Digital Restriction Enzyme Analysis of Methylation (DREAM), based on sequential DNA digestion with a pair of methylation-blocked and methylation-tolerant neoschizomeric restriction enzymes SmaI/XmaI followed by end repair and ultra-deep sequencing. DREAM provides information on 160,000 unique CpG sites of which 39,000 are in CpG islands, and 33,000 are at transcription start sites (-1 kb to +1 kb) of 13,139 RefSeq genes. We compared DNA methylation values in white blood cells from 4 healthy individuals and found them to be remarkably uniform. Interindividual differences >30% were observed only at 227 of 28,331 (0.8%) of autosomal CCCGGG sites covered by 100+ sequencing reads. Similarly, differences at only 59 sites were observed between the cord and adult blood. Conserved methylation patterns in healthy blood cells contrasted with extensive changes affecting 18-40% of CpG sites in leukemia. The method is cost effective, quantitative (r2=0.93 when compared to bisulfite pyrosequencing), reproducible (r2=0.997), and can detect differences >25% with false positive rate <0.001. Accurate analysis of changes in DNA methylation will 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE39787 | GEO | 2012/11/08

SECONDARY ACCESSION(S): PRJNA171709

REPOSITORIES: GEO

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Project description:We describe a simple method, Digital Restriction Enzyme Analysis of Methylation (DREAM), based on sequential DNA digestion with a pair of methylation-blocked and methylation-tolerant neoschizomeric restriction enzymes SmaI/XmaI followed by end repair and ultra-deep sequencing. DREAM provides information on 160,000 unique CpG sites of which 39,000 are in CpG islands, and 33,000 are at transcription start sites (-1 kb to +1 kb) of 13,139 RefSeq genes. We compared DNA methylation values in white blood cells from 4 healthy individuals and found them to be remarkably uniform. Interindividual differences >30% were observed only at 227 of 28,331 (0.8%) of autosomal CCCGGG sites covered by 100+ sequencing reads. Similarly, differences at only 59 sites were observed between the cord and adult blood. Conserved methylation patterns in healthy blood cells contrasted with extensive changes affecting 18-40% of CpG sites in leukemia. The method is cost effective, quantitative (r2=0.93 when compared to bisulfite pyrosequencing), reproducible (r2=0.997), and can detect differences >25% with false positive rate <0.001. Accurate analysis of changes in DNA methylation will 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. Digital restriction enzyme analysis of methylation (DREAM) was performed to determine the DNA methylation profiles of healthy white blood cells from cord blood and adult blood, acute myeloid leukemia bone marrow, and two leukemia cell lines (HEL and K562). In this approach, genomic DNA is sequentially cut at CCCGGG sites with the methylation-sensitive enzyme SmaI (blunt ends) and its methylation-tolerant neoschizomer XmaI (5'CCGG overhangs), creating different end sequences that represent methylation status of the CCCGGG sites. These end sequences are analyzed by next-generation sequencing, and thereafter the methylation status at individual CCCGGG sites across the genome can be determined.

Project description:Methylation of cytosines at CpG sites is a common epigenetic DNA modification that can be measured by a large number of methods, now even in a genome-wide manner for hundreds of thousands of sites. The application of DNA methylation analysis is becoming widely popular in complex disorders, for example, to understand part of the “missing inheritance”. The DNA samples most readily available for methylation studies are derived from whole blood. However, blood consists of many functionally and developmentally distinct cell populations in varying proportions. We studied whether such variation might affect the interpretation of methylation studies based on whole blood DNA. We found in healthy male blood donors there is important variation in the methylation profiles of whole blood, mononuclear cells, granulocytes, and cells from seven selected purified lineages. CpG methylation between mononuclear cells and granulocytes differed for 22% of the 8252 probes covering the selected 343 genes implicated in immune-related disorders by genome-wide association studies, and at least one probe was differentially methylated for 85% of the genes, indicating that whole blood methylation results might be unintelligible. For individual genes, even if the overall methylation patterns might appear similar, a few CpG sites in the regulatory regions may have opposite methylation patterns (i.e., hypo/hyper) in the main blood cell types. We conclude that interpretation of whole blood methylation profiles should be performed with great caution and for any differences implicated in a disorder, the differences resulting from varying proportions of white blood cell types should be considered. Six healthy male blood donors, age 38 ± 13.6 years, were included in the study. From each individual, global DNA methylation levels were analyzed in whole blood, peripheral blood mononuclear cells (PBMC) and granulocytes as well as for seven isolated cell populations (CD4+ T cells, CD8+ T cells, CD56+ NK cells, CD19+ B cells, CD14+ monocytes, neutrophils, and eosinophils), n=60 samples analyzed in total.

Project description:Background DNA methylation has been recognized as a key mechanism in cell differentiation. Various studies have compared tissues to characterize epigenetically regulated genomic regions, but due to differences in study design and focus there still is no consensus as to the annotation of genomic regions predominantly involved in tissue-specific methylation. We used a new algorithm to identify and annotate tissue-specific Differentially Methylated Regions (tDMRs) in Illumina 450k chip data on four peripheral (blood, saliva, buccal swab and hair follicles) and six internal tissues (liver, muscle, pancreas, subcutaneous fat, omentum, spleen with matched blood samples). Results The majority of tDMRs, in both relative and absolute terms, occurred in CpG-poor regions. Further analysis revealed that these regions were associated with alternative transcription events (alternative first exons, mutually exclusive exons and cassette exons). Only a minority of tDMRs mapped to gene-body CpG islands (13%) or CpG islands shores (25%) suggesting a less prominent role for these regions than indicated previously. Implementation of ENCODE annotations showed enrichment of tDMRs in DNase hypersensitive sites and transcription factor binding sites. Despite the predominance of tissue differences, inter-individual differences in DNA methylation in internal tissues were correlated with that in blood for a subset of CpG sites in a locus and tissue-specific manner. Conclusions We conclude that tDMRs preferentially occur in CpG-poor regions and are associated with alternative transcription. Furthermore, our data suggest the utility of creating an atlas cataloguing variably methylated regions in internal tissues that are marked by DNA methylation measured in easy accessible peripheral tissues. Comparison of four peripheral (blood, saliva, buccal swab and hair follicles in n=5) and six internal tissues (liver, muscle, pancreas, subcutaneous fat, omentum, spleen with matched blood samples in n=6).

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Conserved DNA methylation patterns in healthy blood cells and extensive changes in leukemia measured by a new quantitative technique.

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