The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Flagged first, then by citations
Cited by
Sorted by citations
Items 501–600 of 682
Ushijima, H., Maekawa, R., Igarashi, E., & Akashi, S. (2019) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-019-02304-5 · Cited by 3
Baubec, T., & Defossez, P. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2020.02.001 · Cited by 3
Puppala, N. V., Tammineni, R., Saradadevi, G. P., & Mohannath, G. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.03.526984 · Cited by 3
Wang, J., Yuan, W., Liu, F., Liu, G., Geng, X., Li, C., Zhang, C., Li, N., & Li, X. (2024) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2024.10.008 · Cited by 3
Stage-specific DNA methylation dynamics in mammalian heart development
Zhang, F., & Evans, T. (2025) · Epigenomics · doi:10.1080/17501911.2025.2467024 · Cited by 2
Chavan, A., Jones, C., Lawrence, W., & Choudhury, S. R. (2025) · Epigenetics & Chromatin · doi:10.1186/s13072-025-00610-9 · Cited by 2
Le, C., Lewis, M., Harris, C., Berger, L., Chavez-Iglesias, E., Morse, L. M., Sucher, A., Roy, R., Olshen, A. B., Hammer, M. J., et al. (2025) · Cancer Medicine · doi:10.1002/cam4.71067 · Cited by 2
Methylome Profiling of a Deuterostome Invertebrate Using Oxford Nanopore Technology ( ONT )
Kwong, S. L. T., Budd, A. M., Hung, J. Y., Villacorta‐Rath, C., & Uthicke, S. (2025) · Molecular Ecology Resources · doi:10.1111/1755-0998.70026 · Cited by 2
Nishihara, H., & Komiya, A. (2026) · Genome biology · doi:10.1186/s13059-026-04050-w · Cited by 2
Probabilistic modelling of single-cell bisulfite sequencing data with MethylVI
Weinberger, E., Qiu, W., Tian, W., Zeng, Q., Ergen, C., Kronfeld, O., Kim, M., Yosef, N., Ecker, J. R., & Lee, S. (2026) · Nature Machine Intelligence · doi:10.1038/s42256-026-01225-9 · Cited by 2
Self-citationBatista, R. A., Durand, É., Mörchen, M., Azevedo, J., Simon, S., Dubin, M., Kumar, V., Lacoste, E., Cruaud, C., Blassiau, C., et al. (2026) · PLoS Genetics · doi:10.1371/journal.pgen.1012127 · Cited by 2
Niu, H., Wang, D., Cai, X.-Q., Fang, H.-H., & Li, Y. (2025) · BMC Infectious Diseases · doi:10.1186/s12879-025-11288-5 · Cited by 2
Epigenomic Measurements in Brain Tissues
Satterlee, J. S. (2022) · Springer eBooks · doi:10.1007/978-3-030-88832-9_148 · Cited by 2
Driver or Passenger: Epigenomes in Alzheimer’s Disease
Hoffmann, A., Sportelli, V., Ziller, M. J., & Spengler, D. (2017) · Epigenomes · doi:10.3390/epigenomes1010005 · Cited by 2
DNA Methylation Assays Using Bisulphite Sequencing and Next-Generation Sequencing
Merkel, A., & Heath, S. C. (2018) · Comprehensive analytical chemistry · doi:10.1016/bs.coac.2018.07.003 · Cited by 2
Tan, M., Wang, S., Li, F., Xu, H., Gao, J., & Zhu, L. (2022) · Carcinogenesis · doi:10.1093/carcin/bgac048 · Cited by 2
BAllC and BAllCools: efficient formatting and operating for single-cell DNA methylation data
Tian, W., Ding, W., Shen, J., Li, D., Wang, T., & Ecker, J. R. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae404 · Cited by 2
Self-citationDNA methylation oscillation defines classes of enhancersPreprint
Libertini, E., Hamoudi, R., Heath, S. C., Lancashire, L., García, A. R., Grassi, L., Downes, K., Ouwehand, W. H., Javierre, B. M., Cairns, J., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/262212 · Cited by 2
Li, Y., Teng, W., Xu, C., Yu, H. S., Kong, L., Liu, S., & Li, Q. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.22.481396 · Cited by 2
A Multimodal Single-Cell Epigenomic and 3D Genome Atlas of the Human Basal GangliaPreprint
Ding, W., Klein, A., Báez-Becerra, C. T., Rink, J. A., Bartlett, A., Wang, R., Zeng, Q., Castanon, R., Nery, J. R., Osgood, E., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.12.705594 · Cited by 2
Self-citationExploring DNA methylation profiles in blood samples of canine gastrointestinal lymphoma
Nakamura, M., Matsumoto, Y., Nagata, M., Yasuda, K., Yonekawa, K., Muramatsu, S., Goshima, A., Nakaki, R., Yokoyama, N., Nakashima, K., et al. (2025) · PLoS ONE · doi:10.1371/journal.pone.0339388 · Cited by 1
Epigenetic Determinants of Weight Management: Methylation Signatures
Milagro, F. I., Riezu‐Boj, J. I., & Martínez, J. A. (2015) · Current Nutrition Reports · doi:10.1007/s13668-015-0140-8 · Cited by 1
Cerebral organoids: a promising model in cellular technologies
Шнайдер, Т. А. (2018) · Vavilov Journal of Genetics and Breeding · doi:10.18699/vj18.344 · Cited by 1
Mordeniz, C. (2023) · Annals of Reviews & Research · doi:10.19080/arr.2023.09.555765 · Cited by 1
Genome-wide DNA methylation profiling of the octoploid strawberry (Fragaria × ananassa)
Jang, H., Han, H., Oh, Y., Han, K., Kim, D.-S., & Lee, S. (2026) · Epigenetics Insights · doi:10.48130/epi-0026-0002 · Cited by 1
Apparent methylation of mitochondrial DNA in WGBS is dominated by technical artifacts
Yin, J.-J., Gong, Z., & Mao, S.-Q. (2026) · Epigenetics & Chromatin · doi:10.1186/s13072-026-00692-z · Cited by 1
Genetic Information and How It Flows
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.003 · Cited by 1
DNA Methylation in Eukaryotes: Regulation and Function
Niller, H. H., Demcsák, A., & Minárovits, J. (2018) · Springer eBooks · doi:10.1007/978-3-319-50542-8_24 · Cited by 2
Kumar, N., Singh, A., Sahu, U., Desai, D. N., Kumar, M., Bhatia, S., & Sanyal, A. (2024) · Livestock diseases and management · doi:10.1007/978-981-99-9195-2_6 · Cited by 1
Su, S.-H., Cai, X.-Q., Li, Y., Ai-hui, X., Huang, Q., Niu, H., You, Q., & Sun, G. (2025) · BMC Infectious Diseases · doi:10.1186/s12879-025-10452-1 · Cited by 1
Zeng, A., Liu, H., He, S., Luo, X., Zhang, Z., Fu, M., & Yu, B. (2025) · Epigenetics & Chromatin · doi:10.1186/s13072-025-00619-0 · Cited by 1
Diversity of Human CpG Islands
Mendizabal, I., & Yi, S. V. (2017) · Springer eBooks · doi:10.1007/978-3-319-31143-2_67-1 · Cited by 1
Basic Genetics and Epigenetics of Childhood Lung Disease
Wambach, J., Chaudhari, B. P., & Hamvas, A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-44887-1.00003-1 · Cited by 1
Demethylation of Non-CpG Sites in DNA Is Initiated by TET2 5-Methylcytosine Dioxygenase
Dey, A. S., Bhattacharya, C., Guan, Y., Jha, B. K., & Mukherji, M. (2021) · DNA · doi:10.3390/dna1010004 · Cited by 1
Clinical Application of Molecular Bioinformatics
Liu, Y., Yan, F., Liu, X., Weng, M., Wang, X., Zeng, Y., & Gao, H. (2022) · Translational bioinformatics · doi:10.1007/978-981-16-7893-6_13 · Cited by 1
Methods for Analyzing DNA Cytosine Modifications Genome-wide
Rauch, T. A., & Pfeifer, G. P. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91909-8.00030-x · Cited by 1
Cunningham, C., Ji, L., McKinney, E., Benowitz, K., Schmitz, R., & Moore, A. J. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/139634 · Cited by 1
Reply to ‘DNA methylation haplotypes as cancer markers’
Diep, D. H., & Zhang, K. (2018) · Nature Genetics · doi:10.1038/s41588-018-0186-9 · Cited by 1
Effects of early-life adversity on the adult phenotype in European starlings
Gott, A. (2018) · Cited by 1
Mapping the epigenomic landscape of post-traumatic stress disorder in human cortical neuronsPreprint
Núñez-Ríos, D. L., Nagamatsu, S. T., Martínez‐Magaña, J. J., Hurd, Y. L., Rompala, G. R., Krystal, J. H., & Montalvo‐Ortiz, J. L. (2024) · medRxiv · doi:10.1101/2024.10.11.24315258 · Cited by 1
DNA Methylation Dynamics of Dose-dependent Acute Exercise, Training Adaptation, and DetrainingPreprint
Hariharan, M., Patel, S., Song, H., Rehman, A., Barragan, C., Bartlett, A., Castanon, R., Nery, J. R., Rothenberg, V., Chen, H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.22.650067 · Cited by 1
Self-citationChanges in DNA Methylation During Anoxia and Reoxygenation in Crucian Carp BrainPreprint
Winklhofer, M., Andersen, Ø., & Lefevre, S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.30.667361 · Cited by 1
Xu, H., Chien, J.-F., Kozlenkov, A., Vadukapuram, R., Li, J., Wei, Y., Dwork, A. J., Liu, C., Dracheva, S. M., & Mukamel, E. A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.18.706675 · Cited by 1
Self-citation355 Fetal Growth is Associated with Altered Expression of Imprinted Genes in the Placenta
Piyasena, C., Khulan, B., Menon, G. N., & Drake, A. J. (2012) · Archives of Disease in Childhood · doi:10.1136/archdischild-2012-302724.0355
Epigenomic Measurements in Brain Tissues
Satterlee, J. S. (2015) · Springer eBooks · doi:10.1007/978-1-4614-6434-1_148-1
Abdallah, B. Y. (2016) · Human Biology
Valdés, M. C. (2016) · DukeSpace (Duke University)
High-Throughput Techniques for DNA Methylation Profiling
Sophie Petropoulos, A., Cheishvili, D., & Moshe Szyf, A. (2016) · Methods in pharmacology and toxicology · doi:10.1007/978-1-4939-6743-8_1
Mukamel, E. A., & Lister, R. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-801596-4.00005-8
Self-citationChen, X. '., Fan, Y., Cheng, J., Xu, B., Wang, Y., Yergeau, D. A., Easton, J. B., Downing, J. R., & Zhang, J. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/132985
Gay Genes? Genetics and Sexual Orientation
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.011
Methods for Assessing DNA Cytosine Modifications Genome-Wide
Rauch, T. A., & Pfeifer, G. P. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-805388-1.00009-2
Eliseyeva, M. (2017) · International Journal of Biomedicine · doi:10.21103/article7(4)_em
McDonald, J. I. (2017) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k73f4p2b
Diep, D. H., & Zhang, K. (2018) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2018.07.008
Regulation of Gene Expression by Global Methylation Pattern in Plants Development
Yadav, V. K., Mohan, K., Kumar, N., & Yadav, V. K. (2019) · Wiley eBooks · doi:10.1002/9781119509967.ch13
Impact of genome plasticity on health and disease
Forero, D. A., González‐Giraldo, Y., & Patrinos, G. P. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817819-5.00001-2
A dynamical system model for predicting gene expression from the epigenomePreprint
Brunner, J. D., Kim, J., Downing, T. L., Mjolsness, E., & Kober, K. M. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.03.234740
Definitions of Technical Terms
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.015
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.005
Genes and Environments in Human Development
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.004
Genes, Personality and Personality Disorders
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.008
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.006
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.013
Transcriptomic and epigenetic changes after the phenotypic rescue of a Rett Syndrome mouse model
Vargas-Landín, D. B. (2021) · UWA Profiles and Research Repository (UWA) · doi:10.26182/9kh2-8h70
An analytical pipeline for DNA Methylation Array Biomarker StudiesPreprint
Lu, J., Korbie, D. J., & Trau, M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.14.452293
Roles of sex phenotype and sex chromosome dosage in sex-biased DNA methylation
AlOgayil, N. (2021) · eScholarship@McGill (McGill) · doi:10.82308/38951
Genes, Religiosity and Political Commitment
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.010
Genes, Education and Intelligence
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.007
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.012
Epigenomic Measurements in Brain Tissues
Satterlee, J. S. (2016) · Springer eBooks · doi:10.1007/978-1-4939-3474-4_148
Genes, Food, Exercise and Weight
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.009
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.002
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.016
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.001
Faculty Opinions recommendation of Landscape of X chromosome inactivation across human tissues.
Shoubridge, C. (2018) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.731935913.793553266
Advances in Single Molecule, Real-Time (SMRT) Sequencing
Ameur, A., & Hestand, M. S. (2019) · MDPI eBooks · doi:10.3390/books978-3-03921-701-4
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.017
Muotri, A. R. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.727141110.793560515
Diversity of Human CpG Islands
Mendizabal, I., & Yi, S. V. (2019) · Springer eBooks · doi:10.1007/978-3-319-55530-0_67
Implications of Genotype and Environment on Variation in DNA Methylation
Lim, I. Y., Lin, X., & Karnani, N. (2019) · Springer eBooks · doi:10.1007/978-3-319-55530-0_56
Alexander, D. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108566520.014
Carlberg, C., & Molnár, F. (2016) · Springer eBooks · doi:10.1007/978-94-017-7741-4_10
(2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813635-5.16001-x
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review