Charting a dynamic DNA methylation landscape of the human genome

By Michael J. Ziller, H. Gu, F. Müller, Julie Donaghey, Linus T. Tsai, Oliver Kohlbacher, Phil L. de Jager, E. Rosen, David A. Bennett, Bradley E. Bernstein and 2 more. Nature, 2013

1,316 citations recorded by the source corpus.

DNA methylation is a defining feature of mammalian cellular identity and is essential for normal development. Most cell types, except germ cells and pre-implantation embryos, display relatively stable DNA methylation patterns, with 70–80% of all CpGs being methylated. Despite recent advances, we still have a limited understanding of when, where and how many CpGs participate in genomic regulation. Here we report the in-depth analysis of 42 whole-genome bisulphite sequencing 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, most of which are distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, particularly enhancers and transcription-factor-binding sites, which allow identification of key lineage-specific regulators. In addition, differentially methylated regions (DMRs) often contain single nucleotide polymorphisms associated with cell-type-related diseases as determined by genome-wide association studies. The results also highlight the general inefficiency of whole-genome bisulphite sequencing, as 70–80% of the sequencing reads across these data sets provided little or no relevant information about CpG methylation. To demonstrate further 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 guide new, more effective reduced representation approaches to capture the most informative fraction of CpGs, as well as further pinpoint putative regulatory elements.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/30fdefc9f8984b37c54b62ecd8318226c482379e

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Citations in the corpus

Transcriptional Addiction in Cancer (2017, neutral): “Methylation of enhancer and promoter sites can prevent TF binding and thus silences genes (Figure 2H) (Ziller et al., 2013).”
Role of TET enzymes in DNA methylation, development, and cancer (2016, background): “Thus, in contrast to a relatively static DNAmethylation environment, the gain and loss of DNA methylation at regulatory regions are prominent features of normal development (Hon et al. 2013; Ziller et al. 2013).”
Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016, background): “Recent technological advancement has permitted high-throughput measurement of human genome, epigenome, metabolome, transcriptome and proteome at the population level (G. T. Consortium, 2015; Kim et al., 2014; Roadmap Epigenomics et al., 2015; Shin et al., 2014; Wellcome Trust Case Control, 2007; Zil”
DNA methylation and healthy human aging (2015, background): “Just as patterns of gene expression differ across tissues, so do patterns of DNA methylation (Byun et al., 2009; Ziller et al., 2013).”
Effects of the social environment and stress on glucocorticoid receptor gene methylation: a systematic review (2014, neutral): “The stability of DNA methylation is also a point of interest (64).”
Regulatory T Cells and Human Disease. (2020, background): “Recent genome-wide association studies of common polygenic autoimmune diseases have revealed that ∼60% of autoimmune-causal single-nucleotide polymorphisms (SNPs) are mapped to noncoding enhancer regions of immune cells (130–132), including cell type–specific superenhancers (132), and cell type–spec”
Brain Plasticity and Human Evolution (2017, neutral): “Nevertheless, methylomes from various tissues and cell types show a high degree of similarity for the majority of CpG sites (Ziller et al. 2013).”
Interpreting thelanguage of histone and DNA modifications (2014, background): “[194] primarily by the maintenance methyltransferase DNMT1 [195] (Fig.”
High-resolution genome-wide DNA methylation maps of mouse primary female dermal fibroblasts and keratinocytes (2014, neutral): “A major event during developmental differentiation in mammals is the demethylation of regions of DNA to produce TS-HMRs that may function to activate expression of nearby tissue-specific genes [14,15,18,25-28].”
A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data (2014, methodology): “Although here we focus on a single chromosome from mouse embryogenesis data for illustrative purposes, we have also applied our method to perform this analysis for the mouse whole genome (Supplementary Material 2) and a whole-genome bisulfite sequencing study of Alzheimer’s disease (AD) in humans (3”
Reversing DNA Methylation: Mechanisms, Genomics, and Biological Functions (2014, neutral): “Maintaining proper gene expression and cellular identity requires precise control of the DNA methylation pattern (Ji et al., 2010; Ziller et al., 2013).”
DNA methylation: a historical perspective. (2022, neutral): “Once the DNA methylation landscape is set up in the early epiblast, methylation appears static at most features, with the exception of the subset of CpGs typically found outside of promoter regions that shows dynamic methylation changes during differentiation [206,208,222,266].”