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. 2010 Nov 9;8(11):e1000533.
doi: 10.1371/journal.pbio.1000533.

The DNA methylome of human peripheral blood mononuclear cells

Yingrui Li  1 , Jingde Zhu, Geng Tian, Ning Li, Qibin Li, Mingzhi Ye, Hancheng Zheng, Jian Yu, Honglong Wu, Jihua Sun, Hongyu Zhang, Quan Chen, Ruibang Luo, Minfeng Chen, Yinghua He, Xin Jin, Qinghui Zhang, Chang Yu, Guangyu Zhou, Jinfeng Sun, Yebo Huang, Huisong Zheng, Hongzhi Cao, Xiaoyu Zhou, Shicheng Guo, Xueda Hu, Xin Li, Karsten Kristiansen, Lars Bolund, Jiujin Xu, Wen Wang, Huanming Yang, Jian Wang, Ruiqiang Li, Stephan Beck, Jun Wang, Xiuqing Zhang
Affiliations

The DNA methylome of human peripheral blood mononuclear cells

Yingrui Li et al. PLoS Biol. .

Abstract

DNA methylation plays an important role in biological processes in human health and disease. Recent technological advances allow unbiased whole-genome DNA methylation (methylome) analysis to be carried out on human cells. Using whole-genome bisulfite sequencing at 24.7-fold coverage (12.3-fold per strand), we report a comprehensive (92.62%) methylome and analysis of the unique sequences in human peripheral blood mononuclear cells (PBMC) from the same Asian individual whose genome was deciphered in the YH project. PBMC constitute an important source for clinical blood tests world-wide. We found that 68.4% of CpG sites and <0.2% of non-CpG sites were methylated, demonstrating that non-CpG cytosine methylation is minor in human PBMC. Analysis of the PBMC methylome revealed a rich epigenomic landscape for 20 distinct genomic features, including regulatory, protein-coding, non-coding, RNA-coding, and repeat sequences. Integration of our methylome data with the YH genome sequence enabled a first comprehensive assessment of allele-specific methylation (ASM) between the two haploid methylomes of any individual and allowed the identification of 599 haploid differentially methylated regions (hDMRs) covering 287 genes. Of these, 76 genes had hDMRs within 2 kb of their transcriptional start sites of which >80% displayed allele-specific expression (ASE). These data demonstrate that ASM is a recurrent phenomenon and is highly correlated with ASE in human PBMCs. Together with recently reported similar studies, our study provides a comprehensive resource for future epigenomic research and confirms new sequencing technology as a paradigm for large-scale epigenomics studies.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Landscape of the PBMC methylome.
Heat maps show distinct methylation and CpG density patterns for different genomic features. Each panel represents a separate feature, and n refers to the number of analyzed CpGs (per-strand depth ≥10) within that feature. CpG density (x-axis) is defined as the number of CpG dinucleotides in 200 bp windows. Methylation level (y-axis) is defined as the mean methylation level of cytosines in CpGs. The thin black lines within each heat map denote the median methylation level of CpGs at the given local density. The red gradient indicates the abundance of CpGs that fall into bins of given methylation levels and CpG densities. The blue bar charts above each heat map show the distribution of CpG densities, projected onto the x-axis of the heat maps. The green bar charts to the right of the heat maps show the distribution of methylation levels, projected onto the y-axis of the heat maps.
Figure 2
Figure 2. Canonical DNA methylation profiles of expressed and silent genes in PBMC.
Expression status was determined by digital gene expression profiling (DGEP). Genes with ≥5 DGEP tags were defined as expressed (n = 5,251, color-coded red). Genes with no DGEP tag were defined as silent (n = 3,912, color-coded blue). The canonical gene structure is defined by 7 different features, denoted by the x-axis. The length of each feature was normalized and divided into equal numbers of bins. Each dot denotes the mean methylation level per bin and the respective lines denote the 5-bin moving average. Each feature was analyzed separately for the numbers listed in the table below the figure. The green vertical line indicates the mean location of the transcription start sites (TSS).
Figure 3
Figure 3. Example of a gene (FANK1) newly identified to display allele-specific methylation (ASM).
Tracks 1 and 2 show the position of exon 1 and the associated CpG island, respectively. Track 3 shows the position of the identified haploid differentially methylated region (hDMR), W and C denote the forward (Watson) and reverse (Crick) strands of allele 1, and W' and C' denote the corresponding strands of allele 2. The DNA methylation status is color-coded: hypomethylated (yellow) and hypermethylated (blue). The bottom track shows the underlying bisulfite sequencing data for each CpG in the hDMR. The color code is as above, except for unfilled boxes, which denote the absence of data. The actual methylation level (shown as yellow:blue ratio) was derived from an average of 14.7 reads per CpG site.
Figure 4
Figure 4. Venn diagram showing the relationship between haploid differentially methylated regions (hDMRs, red), known imprinted genes (blue), and their intersections (green).
In the intersection, 17 known imprinted genes overlapped with 12 hDMRs in their genomic space.
See this image and copyright information in PMC

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