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Human embryonic stem cells HELP-tagging cytosine methylation data (Albert Einstein College of Medicine)

ABSTRACT: Background: To perform epigenome-wide association studies in human disease, assays need to be comprehensive and quantitative while remaining cost-effective. We explored how the strengths of prior tag-based cytosine methylation assays based on massively-parallel sequencing can be maximised analytically. Results: We find that the use of the EcoP15I restriction enzyme to generate long tags and the normalisation of methylation-sensitive by methylation-insensitive restriction enzyme representations greatly improve assay performance. When exploring sources of bias, we find that the length of the restriction fragment has moderate effects on EcoP15I digestion, while base composition exerts minimal effects. We detail the analytical workflow that maximises the quantitative capabilities of this modified assay. Also revealed are polymorphic sequences in the genome that could confound microarray, bisulphite sequencing or mass spectrometry-based assays, and a position effect causing hypomethylation of transposable elements near gene promoters. Conclusions: The new combined assay, referred to as HELP-tagging, interrogates over 1.8 million loci in the human genome quantitatively with a single lane of Illumina sequencing. When the goal is to study not only CG-dense sequence but also the CG-depleted majority of the genome, this assay system should be suitable.

ORGANISM(S): Homo sapiens

PROVIDER: GSE19937 | GEO | 2010/04/12

SECONDARY ACCESSION(S): PRJNA122627

REPOSITORIES: GEO

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Project description:Genome wide methylation profiling of gliomas is likely to provide important clues to improving treatment outcomes. Restriction enzyme based approaches have been widely utilized for methylation profiling of cancer genomes and will continue to have importance in combination with higher density microarrays. With the availability of the human genome sequence and microarray probe sequences, these approaches can be readily characterized and optimized via in silico modeling. We adapted the previously described HpaII/MspI based Methylation Sensitive Restriction Enzyme (MSRE) assay for use with two-color Agilent 244K CpG island microarrays. In this assay, fragmented genomic DNA is digested in separate reactions with isoschizomeric HpaII (methylation-sensitive) and MspI (methylation-insensitive) restriction enzymes. Using in silico hybridization, we found that genomic fragmentation with BfaI was superior to MseI, providing a maximum effective coverage of 22,362 CpG islands in the human genome. In addition, we confirmed the presence of an internal control group of fragments lacking HpaII/MspI sites which enable separation of methylated and unmethylated fragments. We used this method on genomic DNA isolated from normal brain, U87MG cells, and a glioblastoma patient tumor sample and confirmed selected differentially methylated CpG islands using bisulfite sequencing. Along with additional validation points, we performed a receiver operating characteristics (ROC) analysis to determine the optimal threshold (p â¤ 0.001). Based on this threshold, we identified ~2400 CpG islands common to all three samples and 145 CpG islands unique to glioblastoma. These data provide general guidance to individuals seeking to maximize effective coverage using restriction enzyme based methylation profiling approaches. Five samples: normal human brain DNA, U87MG cell line, glioblastoma tumor, human DNA treated with SssI enzyme used as positive control, and Genomiphied human DNA used as negative control. Two technical replicates were performed on all samples except the negative control.

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Human embryonic stem cells HELP-tagging cytosine methylation data (Albert Einstein College of Medicine)

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