Cited by 1,357Epigenetics and DNA MethylationGenomics and Chromatin DynamicsGenetic Syndromes and Imprinting

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Charting a dynamic DNA methylation landscape of the human genome

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Ziller, Michael J., Gu, Hongcang, Müller, Fabian, Donaghey, Julie, Tsai, Linus T.-Y., Kohlbacher, Oliver, De Jager, Philip L., Rosen, Evan D., Bennett, David A., Bernstein, Bradley E., Gnirke, Andreas, Meissner, Alexander·2013·Nature

DOI 10.1038/nature12433PMC PMC3821869

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Abstract

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.

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Longtin, A., Watowich, M. M., Sadoughi, B., Petersen, R. M., Brosnan, S. F., Buetow, K. H., Cai, Q., Gurven, M., Higham, J. P., Highland, H. M., et al. (2025) · PLoS Genetics · doi:10.1371/journal.pgen.1011667 · Cited by 14
Exercise and DNA methylation in skeletal muscle
Sharples, A. P., & Seaborne, R. A. E. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-816193-7.00010-5 · Cited by 14
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Li, M., Qi, L., Xu, J., Zhong, L., Chan, S., Chen, S., Shao, X., Zheng, L., Dong, Z.-X., Fang, T., et al. (2020) · Molecular Therapy — Oncolytics · doi:10.1016/j.omto.2020.10.004 · Cited by 14
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Li, X. ‐., Liu, L. ‐., Dong, H., Yang, J. ‐., Wang, W. ‐., Zhang, Q.-K., Wang, C. ‐., Zhou, J., & Chen, H. (2020) · Animal Genetics · doi:10.1111/age.13029 · Cited by 14
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Wang, X., Campbell, M. R., Cho, H., Pittman, G. S., Martos, S. N., & Bell, D. A. (2023) · Clinical Epigenetics · doi:10.1186/s13148-023-01507-8 · Cited by 14
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Single-base resolution analysis of DNA epigenome via high-throughput sequencing
Peng, J., Xia, B., & Yi, C. (2016) · Science China Life Sciences · doi:10.1007/s11427-016-5013-x · Cited by 14
The dynamic changes of DNA methylation in primordial germ cell differentiation
Duan, L., Liu, Y., Wang, J., Liao, J., & Hu, J. (2016) · Gene · doi:10.1016/j.gene.2016.06.036 · Cited by 14
Methylation associated transcriptional repression of ELOVL5 in novel colorectal cancer cell lines
Boot, A., Oosting, J., van Eendenburg, J. D. H., Kuppen, P. J. K., Morreau, H., & van Wezel, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0184900 · Cited by 14
Global DNA Methylation Level Monitoring by methyl-CpG Binding Domain-Fused Luciferase
Baba, Y., Karube, I., & Yoshida, W. (2018) · Analytical Letters · doi:10.1080/00032719.2018.1494739 · Cited by 14
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Grunert, M., Appelt, S., Grossfeld, P., & Sperling, S. (2020) · Journal of Cardiovascular Development and Disease · doi:10.3390/jcdd7040055 · Cited by 13
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Lahtinen, A., Häkkinen, A., Puttonen, S., Vanttola, P., Viitasalo, K., Porkka‐Heiskanen, T., Härmä, M., & Paunio, T. (2021) · Scientific Reports · doi:10.1038/s41598-021-82627-0 · Cited by 13
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Velasco, G., Ulveling, D., Rondeau, S., Marzin, P., Unoki, M., Cormier‐Daire, V., & Francastel, C. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22073735 · Cited by 14
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Dottore, G. R., Lanzolla, G., Comi, S., Menconi, F., Cristofani‐Mencacci, L., Dallan, I., Marcocci, C., & Marinò, M. (2022) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgac645 · Cited by 13
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Ouni, M., Eichelmann, F., Jähnert, M., Krause, C., Saussenthaler, S., Ott, C., Gottmann, P., Speckmann, T., Huypens, P., Wolter, S., et al. (2023) · Molecular Metabolism · doi:10.1016/j.molmet.2023.101774 · Cited by 13
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An integrative approach for efficient analysis of whole genome bisulfite sequencing data
Lee, J. H., Park, S., & Kenta, N. (2015) · BMC Genomics · doi:10.1186/1471-2164-16-s12-s14 · Cited by 13
Decoding transcriptional enhancers: Evolving from annotation to functional interpretation
Engel, K. L., Mackiewicz, M., Hardigan, A. A., Myers, R., & Savic, D. (2016) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2016.05.014 · Cited by 13

Authors: Ziller, M. J., Gu, H., Müller, F., Donaghey, J., Tsai, L. T.-Y., Kohlbacher, O., De Jager, P. L., Rosen, E. D., Bennett, D. A., Bernstein, B. E., Gnirke, A., & Meissner, A.
Affiliations: Broad Institute (US)
Harvard University (US)
Beth Israel Deaconess Medical Center (US)
Quantitative Biology Center (DE)
Rush University Medical Center (US)
Corresponding author: Meissner, Alexander
ORCID: Ziller, Michael J.
Gu, Hongcang
Müller, Fabian
Tsai, Linus T.-Y.
Kohlbacher, Oliver
Rosen, Evan D.
Bennett, David A.
Bernstein, Bradley E.
Gnirke, Andreas
Meissner, Alexander
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2013-08
Volume: 500
Issue: 7463
Pages: 477-481
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature12433
PMC: PMC3821869
OpenAlex: W2163327652
Cited by: 1,357
References: 30
Citations by year: 2026: 48 · 2025: 42 · 2024: 99 · 2023: 74 · 2022: 112 · 2021: 97 · 2020: 91 · 2019: 103 · 2018: 100 · 2017: 128 · 2016: 151 · 2015: 159 · 2014: 133 · 2013: 17
FWCI: 68.63
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
Locations: Nature (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
Max Planck Digital Library (submittedVersion, other-oa)
Funders: National Institute on Aging (R01AG017917, R01AG36042, P30-AG 10161, R01‐AG17917, R01 AG15819, R01AG036042, R01AG015819, P30AG010161, RF1AG036042)
National Institute of General Medical Sciences (P01GM099117)
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK087092)
National Institute of Environmental Health Sciences (U01ES017155, ES017690)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Syndromes and Imprinting
Keywords: CpG methylation, cell type-specific methylation, differentially methylated regions, enhancers, transcription factor binding sites, gene regulatory elements, single nucleotide polymorphisms, epigenetic regulation, bisulfite sequencing, epigenome mapping
MeSH terms: Binding Sites, Enhancer Elements, Genetic, Humans, Organ Specificity, Sulfites, Transcription Factors, Genome, Human, Sequence Analysis, DNA, CpG Islands, DNA Methylation, Polymorphism, Single Nucleotide, Genome-Wide Association Study

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Charting a dynamic DNA methylation landscape of the human genome

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