Project description:DNA methylation plays a vital role in genome dynamics and, in the human genome, occurs predominantly at cytosine guanine dinucleotide (CpG) sites. The diploid haploid human genome analysed here contains around 2060 million CpG sites (methylome) where DNA methylation can vary, affecting many biological processes in health and disease. Using whole-genome bisulfite sequencing, we report the essentially complete (92.6282%) methylome of human peripheral blood mononuclear cells (PBMC) which constitute an important source for clinical blood tests world-wide. We find the majority of CpG sites (68.4% at false positive rate of 0.46%) and only <0.2% of non-CpG sites to be methylated, demonstrating that non-CpG cytosine methylation is negligible in human PBMC. Analysis of the PBMC methylome revealed a rich landscape of epigenomic data for 20 distinct features including regulatory, protein-coding, RNA gene coding, non-coding and repeat sequences. Alu element mobility, for instance, was found to negatively correlate with their methylation levels, emphasizing the critical role of DNA methylation in genome stability. Integration of our methylome data with the previously determined genome sequence of the same Asian individual analysed here, enabled a first assessment of allele-specific methylation (ASM) differences between the two haploid methylomes of any individual. Using a conservative cut-off (p <0.001), we identified 599 haploid differentially methylated regions (hDMRs) covering 287 genes. Of these, 76 genes had hDMRs within 2kb of their transcriptional start sites of which >80% displayed allele-specific expression (ASE) after random testing using TA clone sequencing of the same PBMC sample. These data show, that ASM is a recurrent phenomenon and highly correlated with ASE, suggesting that imprinting may be more common than previously thought. Our study not only provides a comprehensive resource for future epigenomic research but also demonstrates a paradigm of large-scale epigenomics studies through new sequencing technology. We report the essentially complete (92.6282%) methylome of human peripheral blood mononuclear cells (PBMC) which constitute an important source for clinical blood tests world-wide.

Project description:Background: Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium Methylation EPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price. Methods: Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000ng), medium (300-1000ng), and low (150ng-300ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array. Results: After quality control, an average of 3,708,550 CpG sites per sample was detected by MC-seq with DNA quantity >1000ng. Reproducibility of MC-seq detected CpG sites was high with strong correlation estimates for CpG methylation among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98~0.99). However, methylation for a small proportion of CpGs (N=235) differed significantly between the two platforms, with differences in beta values of greater than 0.5. Conclusions: Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.

Dataset Information

The DNA methylome of human peripheral blood mononuclear cells

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