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Impact of cytosine methylation on DNA binding specificities of human transcription factors
Open accessAbstract
Positives and negatives of methylated CpG: When the DNA bases cytosine and guanine are next to each other, a methyl group is generally added to the pyrimidine, generating a mCpG dinucleotide. This modification alters DNA structure but can also affect function by inhibiting transcription factor (TF) binding. Yin et al. systematically analyzed the effect of CpG methylation on the binding of 542 human TFs (see the Perspective by Hughes and Lambert). In addition to inhibiting binding of some TFs, they found that mCpGs can promote binding of others, particularly TFs involved in development, such as homeodomain proteins. Science , this issue p. eaaj2239 ; see also p. 489
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“Of interest, the HNF4A binding motif does not contain a CG which can be methylated, thus making it a methylation-insensitive TF (11, 17).”
From Hepatocyte Nuclear Factor 4‐Alpha Is Essential for the Active Epigenetic State at Enhancers in Mouse Liver (2019) · cites this paper as [17]
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“Although many TF, including several members of the ETS family, display reduced binding affinities to DNA motifs containing methylated cytosine residues (44)”
From PU.1-Dependent Enhancer Inhibition Separates Tet2 -Deficient Hematopoiesis from Malignant Transformation (2022) · cites this paper as [44]
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“Given that the affinity of many transcription factors, including CTCF31, is negatively impacted by methylation of their binding sites32, it is possible that hypermethylation of DMR_394 disrupts binding of regulatory proteins and adversely affects the organization and regulation of genes nearby.”
From Integrated analysis of behavioral, epigenetic, and gut microbiome analyses in AppNL-G-F, AppNL-F, and wild type mice (2021) · cites this paper as [32]
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“DNA methylation (5-methylcytosine or 5mC) is associated with gene repression (16) and can disrupt the binding of many TFs (17, 18).”
From Hepatocyte Nuclear Factor 4‐Alpha Is Essential for the Active Epigenetic State at Enhancers in Mouse Liver (2019) · cites this paper as [17]
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“These studies unexpectedly uncovered that certain interactions between TFs and low affinity binding sites can be enhanced by the presence of 5mC.”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [28]
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Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Coot : model-building tools for molecular graphics
Emsley, P., & Cowtan, K. (2004) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444904019158 · Cited by 30,571
Features and development of Coot
Emsley, P., Lohkamp, B., Scott, W. G., & Cowtan, K. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910007493 · Cited by 29,915
Takahashi, K., & Yamanaka, S. (2006) · Cell · doi:10.1016/j.cell.2006.07.024 · Cited by 26,673
PHENIX : a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L.-W., Kapral, G. J., Grosse-Kunstleve, R. W., et al. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909052925 · Cited by 23,716
Phaser crystallographic software
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., & Read, R. J. (2007) · Journal of Applied Crystallography · doi:10.1107/s0021889807021206 · Cited by 20,612
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Kabsch, W. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909047337 · Cited by 16,463
Overview of the CCP 4 suite and current developments
Winn, M. D., Ballard, C. C., Cowtan, K. D., Dodson, E. J., Emsley, P., Evans, P. R., Keegan, R. M., Krissinel, E. B., Leslie, A. G. W., McCoy, A., et al. (2011) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910045749 · Cited by 12,353
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Yang, X., Wang, C., Nie, H., Zhou, J., He, X., & Ou, C. (2022) · Aging · doi:10.18632/aging.204399 · Cited by 10
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Barnhart, K. T., Pretorius, E. S., Marunich, R., & Hummel, A. C. (2004) · PubMed · Cited by 10
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Lam, D. D., Nikolic, A. A., Zhao, C., Mirza‐Schreiber, N., Krężel, W., Oexle, K., & Winkelmann, J. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab355 · Cited by 10
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Hernández-Corchado, A., & Najafabadi, H. S. (2022) · Genome biology · doi:10.1186/s13059-022-02713-y · Cited by 8
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Jolma, A., Laverty, K. U., Fathi, A., Yang, A. W. H., Yellan, I., Vorontsov, I. E., Inukai, S., Kribelbauer-Swietek, J. F., Gralak, A. J., Razavi, R., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.11.622097 · Cited by 9
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Huhtala, L., Karabiyik, G., & Rautajoki, K. J. (2024) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdae162 · Cited by 8
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Qi, R., Yu, T., Wang, S., Zhou, Y., Sun, Y., Jiang, D., Huang, Z., Chen, G., Zhao, G., Zhang, Y., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116028 · Cited by 8
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Wang, Y., Pandak, W. M., Hylemon, P. B., Min, H., Min, J., Fuchs, M. A., Sanyal, A. J., & Ren, S. (2023) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00184.2023 · Cited by 8
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Anaemia, macrocytosis, vitamin B12 and folate levels in elderly Zimbabweans.
Allain, T. J., Gomo, Z. A. R., Wilson, A. O., Ndemera, B., Adamchak, D. J., & Matenga, J. A. (1997) · PubMed · Cited by 8
Gapsys, V., Khabiri, M., de Groot, B. L., & Freddolino, L. (2018) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.8b04187 · Cited by 8
Nguyen, V. T. C., Nguyen, T. H., Doan, N. N. T., Pham, T. M. Q., Nguyen, G. T. H., Nguyen, T. D., Tran, T. T. T., Long, V. D., Phan, T. H., Jasmine, T. X., et al. (2023) · medRxiv · doi:10.1101/2023.04.12.23288460 · Cited by 8
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Lo, E. K. W., Idrizi, A., Tryggvadóttir, R., Zhou, W., Hou, W., Ji, H., Cahan, P., & Feinberg, A. P. (2025) · Genome Medicine · doi:10.1186/s13073-025-01452-6 · Cited by 7
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Chen, T., Dong, Y., Sun, X., Xu, L., Ma, X., Tao, Y., Wang, F., Zhang, H., Li, J., Li, K., et al. (2025) · 中国科学通报:英文版 · doi:10.1016/j.scib.2025.07.009 · Cited by 8
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Hu, H., Wu, D., Liu, X., Yu, H., Xu, J., Cai, W., Huang, Y., Bai, R., Zhang, J., Gu, Y., et al. (2021) · Epigenomics · doi:10.2217/epi-2021-0231 · Cited by 7
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Hörberg, J., Hallbäck, B., Moreau, K., & Reymer, A. (2022) · QRB Discovery · doi:10.1017/qrd.2022.21 · Cited by 7
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Nenning, K., Gesperger, J., Furtner, J., Nemc, A., Roetzer-Pejrimovsky, T., Choi, S. W., Mitter, C., Leber, S. L., Hofmanninger, J., Klughammer, J., et al. (2023) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdad136 · Cited by 7
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Metadata
- Authors
- Yin, Y., Morgunova, E., Jolma, A., Kaasinen, E., Sahu, B., Khund-Sayeed, S., Das, P. K., Kivioja, T., Dave, K., Zhong, F., Nitta, K. R., Taipale, M., Popov, A., Ginno, P. A., Domcke, S., Yan, J., Schübeler, D., Vinson, C., & Taipale, J.
- Affiliations
- Karolinska Institutet (SE)
- University of Helsinki (FI)
- National Institutes of Health (US)
- European Synchrotron Radiation Facility (FR)
- Friedrich Miescher Institute (CH)
- University of Basel (CH)
- Corresponding author
- Taipale, Jussi
- ORCID
- Venue
- Science
- Published
- 2017-05-05
- Volume
- 356
- Issue
- 6337
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC8009048
- OpenAlex
- W2610903912
- Cited by
- 1,257
- References
- 97
- Citations by year
- 2026: 92 · 2025: 138 · 2024: 148 · 2023: 159 · 2022: 166 · 2021: 150 · 2020: 125 · 2019: 125 · 2018: 113 · 2017: 37
- FWCI
- 44.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Academy of Finland Center of Excellence in Cancer Genetics
- European Research Area SynBio
- Center for Innovative Medicine at Karolinska Institutet
- Knut and Alice Wallenberg Foundation
- Göran Gustafsson Foundation
- Vetenskapsrådet
- 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 › Molecular Biology › DNA and Nucleic Acid Chemistry
- Keywords
- cytosine methylation, CpG methylation, transcription factor binding specificity, DNA methylation, homeodomain transcription factor, 5-methylcytosine, hydrophobic interactions, epigenetic regulation, gene regulatory elements
- MeSH terms
- Protein Domains, Cytosine, DNA, Humans, Protein Binding, Transcription Factors, Dinucleoside Phosphates, Genome, Human, CpG Islands, DNA Methylation, Epigenesis, Genetic, SELEX Aptamer Technique
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