Genome-scale DNA methylation maps of pluripotent and differentiated cells

By Alexander Meissner, Tarjei S. Mikkelsen, H. Gu, Marius Wernig, J. Hanna, A. Sivachenko, Xiaolan Zhang, Bradley E. Bernstein, Chad Nusbaum, David B. Jaffe and 3 more. Nature, 2008

2,609 citations recorded by the source corpus.

DNA methylation is essential for normal development and has been implicated in many pathologies including cancer. Our knowledge about the genome-wide distribution of DNA methylation, how it changes during cellular differentiation and how it relates to histone methylation and other chromatin modifications in mammals remains limited. Here we report the generation and analysis of genome-scale DNA methylation profiles at nucleotide resolution in mammalian cells. Using high-throughput reduced representation bisulphite sequencing and single-molecule-based sequencing, we generated DNA methylation maps covering most CpG islands, and a representative sampling of conserved non-coding elements, transposons and other genomic features, for mouse embryonic stem cells, embryonic-stem-cell-derived and primary neural cells, and eight other primary tissues. Several key findings emerge from the data. First, DNA methylation patterns are better correlated with histone methylation patterns than with the underlying genome sequence context. Second, methylation of CpGs are dynamic epigenetic marks that undergo extensive changes during cellular differentiation, particularly in regulatory regions outside of core promoters. Third, analysis of embryonic-stem-cell-derived and primary cells reveals that ‘weak’ CpG islands associated with a specific set of developmentally regulated genes undergo aberrant hypermethylation during extended proliferation in vitro, in a pattern reminiscent of that reported in some primary tumours. More generally, the results establish reduced representation bisulphite sequencing as a powerful technology for epigenetic profiling of cell populations relevant to developmental biology, cancer and regenerative medicine.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/549783a062f3561542aae9f3c3da0591036805d2

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In Molecular Biology

1. Hao Wu
2. Manolis Kellis
3. Peter A. Jones
4. Yi Zhang
5. Cole Trapnell
6. Manel Esteller
7. Richard A. Young
8. A. Bird

Citations in the corpus

• A double take on bivalent promoters. (2013, background): “Interestingly, promoters that lose both H3K4me3 and H3K27me3 have a high probability of becoming DNA-hypermethylated (Meissner et al. 2008), supporting a role for both marks in preventing DNA methylation.”
• Epigenetics in alternative pre-mRNA splicing (2011, neutral): “DNA methylation patterns correlate better with histone methylation patterns than with genome sequence context (Meissner et al., 2008).”
• CTCF-Mediated Functional Chromatin Interactome in Pluripotent Cells (2011, methodology): “To measure the intensities of different histone modifications in or proximal to CTCF loops, we adopted the publicly available seven histone modification data sets (H3K4me1, H3K4me2, H3K4me3, H3K36me3, H3K27me3, H3K9me3 and H3K20me3) derived from ES cell”
• Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal (2014, positive): “Bivalent domains showed the lowest DNA methylation (5%; Figure S4D), which was consistent with the inverse correlation of DNA methylation and H3K4me3 (Meissner et al., 2008).”
• DNA methylation: a historical perspective. (2022, neutral): “Reduced representation bisulfite sequencing (RRBS) showed limited dynamic methylation over the majority of promoters and uncovered specific focal methylation changes at more distal, highly conserved putative regulatory sites [206] (Figure 5E).”
• Differential methylation analysis for BS-seq data under general experimental design (2016, background): “It often shows abnormality in many diseases such as cancer (Bird, 2002; Reik, 2007; Meissner et al., 2008; Kriaucionis and Heintz, 2009; Teschendorff et al., 2010; Szulwach et al., 2011b; Seisenberger et al., 2012).”
• CpG islands and the regulation of transcription. (2011, background): “Differences in gene-associated CGI methylation between one somatic tissue and another have also been reported, although these are relatively rare compared with differences between germline and somatic CGIs (Meissner et al. 2008).”
• DNA methylome analysis using short bisulfite sequencing data (2012, background): “In the first, termed directional libraries, adapters are attached to the DNA fragments such that only the original top or bottom strands will be sequenced 7,30 .”
• Charting histone modifications and the functional organization of mammalian genomes (2011, methodology): “assays for chromatin accessibility; whole-genome and reduced-representation bisulphite sequencing (BS-seq”
• Genomewide Analysis of PRC1 and PRC2 Occupancy Identifies Two Classes of Bivalent Domains (2008, background): “PcGoccupied regions are largely un-methylated at the DNA level, at least in ES cells [57], and this could favor retention of CG-rich sequences.”