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Human body epigenome maps reveal noncanonical DNA methylation variation
Open accessAbstract
As part of the Epigenome Roadmap Project, genome-wide maps of DNA methylation and transcriptomes together with genomic DNA sequencing of 18 different primary human tissue types from 4 individuals are presented; analysis reveals widespread differential methylation of CG sites between tissues, and the presence of non-CG methylation in adult tissues. As part of the Epigenome Roadmap project, Joseph Ecker and colleagues provide genome-wide maps of DNA methylation and transcriptomes, in conjunction with genomic DNA sequencing, of 18 different primary human tissue types from four individuals. Analysis of the datasets reveals widespread differential methylation of CG sites between tissues, and methylation at regulatory elements generally has a negative correlation with gene expression as expected. A surprising amount of non-CG methylation is found in a subpopulation of cells in many tissues. Understanding the diversity of human tissues is fundamental to disease and requires linking genetic information, which is identical in most of an individual’s cells, with epigenetic mechanisms that could have tissue-specific roles. Surveys of DNA methylation in human tissues have established a complex landscape including both tissue-specific and invariant methylation patterns1,2. Here we report high coverage methylomes that catalogue cytosine methylation in all contexts for the major human organ systems, integrated with matched transcriptomes and genomic sequence. By combining these diverse data types with each individuals’ phased genome3, we identified widespread tissue-specific differential CG methylation (mCG), partially methylated domains, allele-specific methylation and transcription, and the unexpected presence of non-CG methylation (mCH) in almost all human tissues. mCH correlated with tissue-specific functions, and using this mark, we made novel predictions of genes that escape X-chromosome inactivation in specific tissues. Overall, DNA methylation in several genomic contexts varies substantially among human tissues.
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“Intragenic DMRs that stretch for kilobases (large-DMRs) can overlap with tissue defining “signature genes” as well as with predicted super-enhancers, which are clusters of enhancers that function cooperatively (4, 10, 11).”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [4]
In the citing paper
“These dynamically methylated CpGs cluster into over 1 million tissue specific differentially methylated regions (DMRs).”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [4]
In the citing paper
“direct comparison of whole genome methylome profiles derived from numerous cell types has revealed that under normal physiological conditions 15%-21% of CpGs vary in methylation status between human tissues (4, 5).”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [4]
In the citing paper
“These tissue-type specific DMRs are defined by both lineage specific gain and loss of 5mC during embryogenesis.”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [4]
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Cites
Human DNA methylomes at base resolution show widespread epigenomic differences
Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti-Filippini, J., Nery, J. R., Lee, L., Ye, Z., Ngo, Q.-M., et al. (2009) · Nature · doi:10.1038/nature08514 · Cited by 4,673
Self-citationGREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
Super-enhancers in the control of cell identity and disease
Hnisz, D., Abraham, B. J., Lee, T. I., Lau, A., Saint-André, V., Sigova, A. A., Hoke, H. A., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.09.053 · Cited by 3,662
Irizarry, R. A., Ladd-Acosta, C., Wen, B., Wu, Z., Montano, C., Onyango, P., Cui, H., Gabo, K., Rongione, M., Webster, M., et al. (2009) · Nature Genetics · doi:10.1038/ng.298 · Cited by 2,177
X-inactivation profile reveals extensive variability in X-linked gene expression in females
Carrel, L., & Willard, H. F. (2005) · Nature · doi:10.1038/nature03479 · Cited by 2,097
Global epigenomic reconfiguration during mammalian brain development
Lister, R., Mukamel, E. A., Nery, J. R., Urich, M., Puddifoot, C. A., Johnson, N. D., Lucero, J., Huang, Y., Dwork, A. J., Schultz, M. D., et al. (2013) · Science · doi:10.1126/science.1237905 · Cited by 1,830
Self-citationConserved role of intragenic DNA methylation in regulating alternative promoters
Maunakea, A. K., Nagarajan, R. P., Bilenky, M., Ballinger, T. J., D’Souza, C., Fouse, S. D., Johnson, B. E., Hong, C., Nielsen, C., Zhao, Y., et al. (2010) · Nature · doi:10.1038/nature09165 · Cited by 1,743
Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells
Lister, R., Pelizzola, M., Kida, Y. S., Hawkins, R. D., Nery, J. R., Hon, G. C., Antosiewicz‐Bourget, J., O’Malley, R. C., Castanon, R., Klugman, S. A., et al. (2011) · Nature · doi:10.1038/nature09798 · Cited by 1,595
Self-citationCharting a dynamic DNA methylation landscape of the human genome
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., et al. (2013) · Nature · doi:10.1038/nature12433 · Cited by 1,357
Plasticity of Adult Stem Cells
Wagers, A. J., & Weissman, I. L. (2004) · Cell · doi:10.1016/s0092-8674(04)00208-9 · Cited by 1,268
Doi, A., Park, I., Wen, B., Murakami, P. N., Aryee, M. J., Irizarry, R. A., Herb, B. R., Ladd‐Acosta, C., Rho, J., Loewer, S., et al. (2009) · Nature Genetics · doi:10.1038/ng.471 · Cited by 1,201
Liu, Y., Aryee, M. J., Padyukov, L., Fallin, M. D., Hesselberg, E., Rúnarsson, Á. R., Reinius, L. E., Acevedo, N., Taub, M. A., Ronninger, M., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2487 · Cited by 997
Epigenomic Analysis of Multilineage Differentiation of Human Embryonic Stem Cells
Xie, W., Schultz, M. D., Lister, R., Hou, Z., Rajagopal, N., Ray, P. R., Whitaker, J. W., Tian, S., Hawkins, R. D., Leung, D., et al. (2013) · Cell · doi:10.1016/j.cell.2013.04.022 · Cited by 739
Self-citationDynamic DNA methylation across diverse human cell lines and tissuesPreprint
Varley, K. E., Gertz, J., Bowling, K. M., Parker, S. L., Reddy, T. E., Pauli, F., Cross, M. K., Williams, B. A., Stamatoyannopoulos, J. A., Crawford, G. E., et al. (2013) · Genome Research · doi:10.1101/gr.147942.112 · Cited by 725
Berman, B. P., Weisenberger, D. J., Aman, J. F., Hinoue, T., Ramjan, Z., Liu, Y., Noushmehr, H., Lange, C. P. E., van Dijk, C. M., Tollenaar, R. A. E. M., et al. (2012) · Nature Genetics · doi:10.1038/ng.969 · Cited by 660
Non-CpG methylation of the PGC-1α promoter through DNMT3B controls mitochondrial density.
Barrès, R., Osler, M. E., Yan, J., Rune, A., Fritz, T., Caidahl, K., Krook, A., & Zierath, J. R. (2009) · Cell Metabolism · doi:10.1016/j.cmet.2009.07.011 · Cited by 602
Parviz, F., Matullo, C., Garrison, W. D., Savatski, L., Adamson, J. W., Ning, G., Kaestner, K. H., Rossi, J. M., Zaret, K. S., & Duncan, S. A. (2003) · Nature Genetics · doi:10.1038/ng1175 · Cited by 588
Hon, G. C., Hawkins, R. D., Caballero, O. L., Lo, C., Lister, R., Pelizzola, M., Valsesia, A., Ye, Z., Kuan, S., Edsall, L. E., et al. (2012) · Genome Research · doi:10.1101/gr.125872.111 · Cited by 583
Self-citationEpigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues
Hon, G. C., Rajagopal, N., Shen, Y., McCleary, D. F., Yue, F., Dang, M. D., & Ren, B. (2013) · Nature Genetics · doi:10.1038/ng.2746 · Cited by 477
Self-citationDecoding the regulatory landscape of medulloblastoma using DNA methylation sequencing
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Gutierrez-Arcelus, M., Lappalainen, T., Montgomery, S. B., Buil, A., Ongen, H., Yurovsky, A., Bryois, J., Giger, T., Romano, L., Planchon, A., et al. (2013) · eLife · doi:10.7554/elife.00523 · Cited by 440
Schroeder, D. I., Blair, J. D., Lott, P. C., Yu, H. O. K., Hong, D., Crary-Dooley, F. K., Ashwood, P., Walker, C. K., Korf, I. F., Robinson, W. P., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1215145110 · Cited by 317
‘Leveling’ the playing field for analyses of single-base resolution DNA methylomes
Schultz, M. D., Schmitz, R. J., & Ecker, J. R. (2012) · Trends in Genetics · doi:10.1016/j.tig.2012.10.012 · Cited by 301
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Selvaraj, S., Dixon, J. R., Bansal, V., & Ren, B. (2013) · Nature Biotechnology · doi:10.1038/nbt.2728 · Cited by 294
Self-citationCell type–specific DNA methylation at intragenic CpG islands in the immune systemPreprint
Deaton, A. M., Webb, S., Kerr, A. R. W., Illingworth, R. S., Guy, J., Andrews, R., & Bird, A. P. (2011) · Genome Research · doi:10.1101/gr.118703.110 · Cited by 293
Integrative analysis of haplotype-resolved epigenomes across human tissues
Leung, D., Jung, I., Rajagopal, N., Schmitt, A. D., Selvaraj, S., Lee, A. Y., Yen, C., Lin, S., Lin, Y., Qiu, Y., et al. (2015) · Nature · doi:10.1038/nature14217 · Cited by 228
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Stankunas, K., Shang, C., Twu, K. Y., Kao, S.-C., Jenkins, N. A., Copeland, N. G., Sanyal, M., Selleri, L., Cleary, M. L., & Chang, C. (2008) · Circulation Research · doi:10.1161/circresaha.108.175489 · Cited by 156
Predicting the human epigenome from DNA motifs
Whitaker, J. W., Chen, Z., & Wang, W. T. (2014) · Nature Methods · doi:10.1038/nmeth.3065 · Cited by 119
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Yuen, S. L., Ogut, O., & Brozovich, F. V. (2009) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00132.2009 · Cited by 65
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Liu, X. S., Wu, H., Ji, X., Stelzer, Y., Wu, X., Czauderna, S., Shu, J., Dadon, D., Young, R. A., & Jaenisch, R. (2016) · Cell · doi:10.1016/j.cell.2016.08.056 · Cited by 1,224
“DMRs upstream of mouse MyoD gene were defined based on human/mouse genome homology (Schultz et al., 2015).”
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GTEx Consortium, Tukiainen, T., Villani, A.-C., Yen, A., Rivas, M. A., Marshall, J. L., Satija, R., Aguirre, M., Gauthier, L., Fleharty, M., et al. (2017) · Nature · doi:10.1038/nature24265 · Cited by 1,138
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Bell, C. G., Lowe, R., Adams, P. D., Baccarelli, A. A., Beck, S., Bell, J. T., Christensen, B. C., Gladyshev, V. N., Heijmans, B. T., Horvath, S., et al. (2019) · Genome Biology · doi:10.1186/s13059-019-1824-y · Cited by 1,025
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Metadata
- Authors
- Schultz, M. D., He, Y., Whitaker, J. W., Hariharan, M., Mukamel, E. A., Leung, D., Rajagopal, N., Nery, J. R., Urich, M. A., Chen, H., Lin, S., Lin, Y., Jung, I., Schmitt, A. D., Selvaraj, S., Ren, B., Sejnowski, T. J., Wang, W., & Ecker, J. R.
- Affiliations
- Salk Institute for Biological Studies (US)
- University of California San Diego (US)
- Ludwig Cancer Research (US)
- Stanford University (US)
- Washington University in St. Louis (US)
- Corresponding author
- Ecker, Joseph R.
- ORCID
- Venue
- Nature
- Published
- 2015-06-01
- Volume
- 523
- Issue
- 7559
- Pages
- 212-216
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4499021
- OpenAlex
- W1506411903
- Cited by
- 690
- References
- 30
- Citations by year
- 2026: 30 · 2025: 43 · 2024: 39 · 2023: 61 · 2022: 61 · 2021: 65 · 2020: 80 · 2019: 69 · 2018: 81 · 2017: 63 · 2016: 68 · 2015: 28
- FWCI
- 34.75
- Type
- journal article
- Language
- en
- Update notices
- erratum (2015-11-25)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Gordon and Betty Moore Foundation
- Mary K. Chapman Foundation
- University of Texas at Austin
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R00HL119617, K99HL119617, F32HL110473)
- National Institute of General Medical Sciences (T32GM008666)
- National Institute of Neurological Disorders and Stroke (R00NS080911, K99NS080911)
- National Institute of Environmental Health Sciences (U01ES017166, R01ES024984)
- 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
- DNA methylation, non-CG methylation, tissue-specific methylation, partially methylated domains, allele-specific methylation, X chromosome inactivation escape, gene expression, regulatory elements
- MeSH terms
- Age Factors, Alleles, Chromosome Mapping, Female, Gene Expression Regulation, Humans, Male, Organ Specificity, Genetic Variation, DNA Methylation, Gene Expression Profiling, Epigenesis, Genetic
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