Charting a dynamic DNA methylation landscape of the human genome

Abstract

DNA methylation is a defining feature of mammalian cellular identity and essential for normal development1,2. Most cell types, except germ cells and pre-implantation embryos3–5, display relatively stable DNA methylation patterns with 70–80% of all CpGs being methylated6. Despite recent advances we still have a too limited understanding of when, where and how many CpGs participate in genomic regulation. Here we report the in depth analysis of 42 whole genome bisulfite sequencing (WGBS) data sets across 30 diverse human cell and tissue types. We observe dynamic regulation for only 21.8% of autosomal CpGs within a normal developmental context, a majority of which are distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, particularly enhancers and transcription factor binding sites (TFBS), which allow identification of key lineage specific regulators. In addition, differentially methylated regions (DMRs) often harbor SNPs associated with cell type related diseases as determined by GWAS. The results also highlight the general inefficiency of WGBS as 70–80% of the sequencing reads across these data sets provided little or no relevant information regarding CpG methylation. To further demonstrate the utility of our DMR set, we use it to classify unknown samples and identify representative signature regions that recapitulate major DNA methylation dynamics. In summary, although in theory every CpG can change its methylation state, our results suggest that only a fraction does so as part of coordinated regulatory programs. Therefore our selected DMRs can serve as a starting point to help guide novel, more effective reduced representation approaches to capture the most informative fraction of CpGs as well as further pinpoint putative regulatory elements.

Global delay in nascent strand DNA methylation

“…Prior studies have also suggested that intermediate levels of methylation are frequently found around transcription factor (TF) binding sites 13,29,30 . To compare these local events with the global patterns described above, we re-examined our bulk and arrested ESC datasets and utilized previously determined TF binding sites based on chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments in ESCs as well as their differentiated derivatives.…”

“…DNMT1 activity is further directed to the replication fork through its interaction with the proliferating cell nuclear antigen (PCNA) DNA clamp 11 , and deletion of DNMT1s PCNA-binding domain has been reported to delay post replication remethylation 12 . More conceptually, accurate reestablishment of the human methylome requires catalytic activity at ~45 million heterogeneously distributed CpGs (roughly 80% of CpG sites within the diploid genome) that must be completed within a single cell cycle 13 . Given this scale, it may not be surprising that some earlier studies have observed a lag in nascent strand methylation in somatic and transformed cells 14–18 , which presumably reflects the kinetic discrepancy between rapid polymer extension from the 3′-OH of the previously incorporated base versus the multistep transfer of a methyl-group to hemi-methylated CpG dyads 19,20 .…”

DNA methylation and healthy human aging

“…Just as patterns of gene expression differ across tissues, so do patterns of DNA methylation (Byun et al ., 2009; Ziller et al ., 2013). In fact, tissue of origin is the primary difference in DNA methylation profiles from different samples, regardless of whether they originate from the same or different individuals (Davies et al ., 2012; Ziller et al ., 2013; Jiang et al ., 2015).…”

Reduced DNA methylation patterning and transcriptional connectivity define human skin aging

“…However, whole‐genome bisulfite sequencing is expensive and time‐consuming and requires substantial computational resources. Furthermore, methylation levels are often similar between neighboring CpGs, and only a minor fraction of the mammalian genome undergoes dynamic methylation changes (Ziller et al ., 2013). This suggests that a subset of CpG dinucleotides can be used to analyze genomic DNA methylation patterns (Ziller et al ., 2013).…”

“…Furthermore, methylation levels are often similar between neighboring CpGs, and only a minor fraction of the mammalian genome undergoes dynamic methylation changes (Ziller et al ., 2013). This suggests that a subset of CpG dinucleotides can be used to analyze genomic DNA methylation patterns (Ziller et al ., 2013). In this context, the Infinium 450k array represents the most widely used platform and allows the methylation analysis of more than 450 000 cytosine residues in the human genome.…”