Evaluation of affinity-based genome-wide DNA methylation data: Effects of CpG density, amplification bias, and copy number variation

Abstract

DNA methylation is an essential epigenetic modification that plays a key role associated with the regulation of gene expression during differentiation, but in disease states such as cancer, the DNA methylation landscape is often deregulated. There are now numerous technologies available to interrogate the DNA methylation status of CpG sites in a targeted or genome-wide fashion, but each method, due to intrinsic biases, potentially interrogates different fractions of the genome. In this study, we compare the affinity-purification of methylated DNA between two popular genome-wide techniques, methylated DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain-based capture (MBDCap), and show that each technique operates in a different domain of the CpG density landscape. We explored the effect of whole-genome amplification and illustrate that it can reduce sensitivity for detecting DNA methylation in GC-rich regions of the genome. By using MBDCap, we compare and contrast microarray-and sequencing-based readouts and highlight the impact that copy number variation (CNV) can make in differential comparisons of methylomes. These studies reveal that the analysis of DNA methylation data and genome coverage is highly dependent on the method employed, and consideration must be made in light of the GC content, the extent of DNA amplification, and the copy number.

Adverse Childhood Experiences and Frequent Insufficient Sleep in 5U.S. States, 2009: A Retrospective Cohort Study

“…Nonetheless, this preliminary study was able to discover hundreds of differentially methylated promoters so future studies with better balance are likely discover many more. Finally, there is currently no 'gold standard' for measuring the methylome, yet MeDIP is a well-established genome-wide method that has been evaluated [46,[61][62][63][64][65] and we confirmed all the micro-array calls in the top 11 methylation differences. Current genome-wide methods are more complementary than interchangeable and each has its strengths and weaknesses.…”

Methyl-CpG/MBD2 Interaction Requires Minimum Separation and Exhibits Minimal Sequence Specificity

“…This result builds on previous work that has reported on read coverage of the MethylMiner kit as a function of local CpG density (24,25) and CpG number (16), noting low sensitivity to sparsely methylated DNA. Our data uniquely analyzes the explicit property of the DNA fragment (CpG number) with high certainty of methylation level (M.SssI treatment) while accounting for the background frequency of reads with a given CpG count (dividing the fraction of pulldown by the fraction of input) and resolving the bias for less frequent, highly methylated reads.…”

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value

“…Alignment statistics for samples used in this study are given in Supplementary Table 5. MBDCap-Seq platform was previously shown to interrogate CpG dense regions of the genome 23 . To accurately delineate regions of the genome assayable by MBDCap-Seq, we used fully methylated sample (SssI blood sample) to guide us to the genomic regions attracting sequenced tags.…”

“…Here we carry out genome-wide DNA methylation profiling of formalin-fixed paraffin-embedded (FFPE) triple-negative clinical DNA samples, using affinity capture of methylated DNA with recombinant methyl-CpG binding domain of MBD2 protein, followed by next generation sequencing (MBDCap-Seq) 20,21 . This high-resolution technique allows for genome-wide methylation analysis of CpG rich DNA 22,23 . Using MBDCap-Seq, we identify regional methylation profiles specific to TNBC, which we validate using methylation data extracted from TCGA breast cancer cohort 13 .…”