DNA methylation presents distinct binding sites for human transcription factors
Open accessAbstract
DNA methylation, especially CpG methylation at promoter regions, has been generally considered as a potent epigenetic modification that prohibits transcription factor (TF) recruitment, resulting in transcription suppression. Here, we used a protein microarray-based approach to systematically survey the entire human TF family and found numerous purified TFs with methylated CpG (mCpG)-dependent DNA-binding activities. Interestingly, some TFs exhibit specific binding activity to methylated and unmethylated DNA motifs of distinct sequences. To elucidate the underlying mechanism, we focused on Kruppel-like factor 4 (KLF4), and decoupled its mCpG- and CpG-binding activities via site-directed mutagenesis. Furthermore, KLF4 binds specific methylated or unmethylated motifs in human embryonic stem cells in vivo. Our study suggests that mCpG-dependent TF binding activity is a widespread phenomenon and provides a new framework to understand the role and mechanism of TFs in epigenetic regulation of gene transcription.
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A protein microarray study interrogating more than 1,500 transcription factors found over 40 that can bind methylated motifs.
“A protein microarray study that interrogated more than 1,500 TFs found over 40 TFs that are able to bind methylated motifs (27).”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [27]
The deduced Kd values of ZMYM3, AP2α and KLF4 for their methylated motifs are 460 nM, 399 nM and 479 nM, respectively.
“The deduced Kd values of ZMYM3, AP2α and KLF4 were determined as 460 nM, 399 nM and 479 nM, respectively.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
Of 154 methylated DNA motifs examined on a human protein microarray, 150 showed strong binding signals to at least one protein.
“Of the 154 methylated motifs examined, 150 showed strong binding signals to at least one protein on the microarray.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
Many other protein domains, including homeobox, HLH and E2F domains, might interact with mCpG sites.
“A global survey of methylated-DNA-binding proteins suggests that many other protein domains might also be able to interact with mCpG sites, including homeobox, HLH and E2F domains53.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
In total, 41 transcription factors and 6 cofactors bind to at least one methylated sequence.
“In total, 41 TFs and 6 cofactors were found to bind to at least one methylated sequence.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
No obvious affinity was detected when the tested motifs were unmethylated.
“no obvious affinity could be detected when these tested motifs were unmethylated.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
MeCP2 and KLF4 share a common structural feature involving one arginine and one asparagine.
“A structural comparison of MeCP2 and KLF4 indeed showed a common structural feature involving one arginine and one asparagine53.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
If the methylation status of the KLF4 binding sequences is exchanged, KLF4 loses the ability to bind either sequence.
“If the methylation status of these two sequences is exchanged, KLF4 loses the ability to bind to either sequence53.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
The competition assay ensures that identified interactions are methylation-dependent rather than due to CpG-flanking sequences.
“This competition assay ensures that the identified interactions are indeed methylation-dependent, rather than due to CpG-flanking sequences.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
Factors with binding activity to methylated sequences are widespread among transcription factor subfamilies.
“the factors that showed binding activity to methylated sequences were widespread among various TF subfamilies, such as zf-C2H2, homeobox, bHLH (basic helix–loop–helix), forkhead, bZIP and HMG (high-mobility group) box.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
KLF4 and HOXA5 bind mCpG sites in both humans and mice.
“a few proteins such as KLF4 and homeobox A5 (HOXA5) were shown to bind mCpG sites in both species”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
KLF4 binds methylated enhancer regions in embryonic stem cells.
“Based on the analysis of KLF4 binding in ES cells, we also found that KLF4 binds to methylated enhancer regions53”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
For many newly discovered methylated DNA-binding proteins, the methylated motifs differ from the non-methylated motifs.
“for many newly discovered methylated DNA-binding proteins, the methylated motifs differ from the non-methylated motifs53.”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
Several members of these families, including HOXA5, HOXA9, GATA3 and GATA4, can bind methylated DNA.
“Interestingly, several of their members showed the ability to bind to methylated DNA, including HOXA5, HOXA9, GATA3 and GATA4 (REF. 53).”
From Transcription factors as readers and effectors of DNA methylation (2016) · cites this paper as [53]
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Cites
The Pfam Protein Families Database
Bateman, A. G. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.276 · Cited by 14,062 · see citing works
Jaenisch, R., & Bird, A. (2003) · Nature Genetics · doi:10.1038/ng1089 · Cited by 6,325 · see citing works
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 · see citing works
Jones, P. A., & Baylin, S. B. (2007) · Cell · doi:10.1016/j.cell.2007.01.029 · Cited by 4,515 · see citing works
Epigenetics in human disease and prospects for epigenetic therapy
Egger, G., Liang, G., Aparicio, A., & Jones, P. A. (2004) · Nature · doi:10.1038/nature02625 · Cited by 3,232 · see citing works
The Pfam protein families database
Bateman, A. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh121 · Cited by 3,127 · see citing works
DNA methylation and human disease
Robertson, K. D. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1655 · Cited by 2,864 · see citing works
Chen, X., Han, X., Yuan, P., Fang, F., Huss, M., Vega, V. B., Wong, E., Orlov, Y. L., Zhang, W., Jiang, J., et al. (2008) · Cell · doi:10.1016/j.cell.2008.04.043 · Cited by 2,474 · see citing works
Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma
Noushmehr, H., Weisenberger, D. J., Diefes, K., Phillips, H. S., Pujara, K., Berman, B. P., Pan, F., Pelloski, C. E., Sulman, E. P., Bhat, K. P., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.03.017 · Cited by 2,337 · see citing works
Stability and flexibility of epigenetic gene regulation in mammalian development
Reik, W. (2007) · Nature · doi:10.1038/nature05918 · Cited by 1,963 · cited 4× · see citing works
“On the other hand, consistent with the important role of DNA methylation in the development of cancer (Egger et al., 2004; Reik, 2007), there was a significant enrichment for known oncogenes and tumor suppressors (10/47; p<0.”
BackgroundInfluentialXie, X., Lu, J., Kulbokas, E. J., Golub, T. R., Mootha, V., Lindblad-Toh, K., Lander, E. S., & Kellis, M. (2005) · Nature · doi:10.1038/nature03441 · Cited by 1,872 · see citing works
Phenotypic plasticity and the epigenetics of human disease
Feinberg, A. P. (2007) · Nature · doi:10.1038/nature05919 · Cited by 1,613 · see citing works
Lewis, J. D., Meehan, R. R., Henzel, W. J., Maurer-Fogy, I., Jeppesen, P., Klein, F., & Bird, A. (1992) · Cell · doi:10.1016/0092-8674(92)90610-o · Cited by 1,371 · see citing works
Hydroxylation of 5-Methylcytosine by TET1 Promotes Active DNA Demethylation in the Adult Brain
Guo, J. U., Su, Y., Zhong, C., Ming, G., & Song, H. (2011) · Cell · doi:10.1016/j.cell.2011.03.022 · Cited by 1,355 · see citing works
Self-citationDNA methylation and gene silencing in cancer
Baylin, S. B. (2005) · Nature Clinical Practice Oncology · doi:10.1038/ncponc0354 · Cited by 1,156 · see citing works
Ramsahoye, B., Biniszkiewicz, D., Lyko, F., Clark, V. H., Bird, A., & Jaenisch, R. (2000) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.97.10.5237 · Cited by 1,018 · see citing works
Dynamic Readers for 5-(Hydroxy)Methylcytosine and Its Oxidized Derivatives
Spruijt, C. G., Gnerlich, F., Smits, A. H., Pfaffeneder, T., Jansen, P. W. T. C., Bauer, C., Münzel, M., Wagner, M., Müller, M., Khan, F., et al. (2013) · Cell · doi:10.1016/j.cell.2013.02.004 · Cited by 973 · see citing works
Neuronal Activity–Induced Gadd45b Promotes Epigenetic DNA Demethylation and Adult Neurogenesis
Dengke, K., Jang, M., Guo, J. U., Kitabatake, Y., Chang, M.-L., Pow-anpongkul, N., Flavell, R. A., Lu, B., Ming, G., & Song, H. (2009) · Science · doi:10.1126/science.1166859 · Cited by 929 · see citing works
Self-citationDNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia
Figueroa, M. E., Lugthart, S., Li, Y., Erpelinck-Verschueren, C. A. J., Deng, X., Christos, P. J., Schifano, E. D., Booth, J. G., van Putten, W., Skrabanek, L. A., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2009.11.020 · Cited by 833 · see citing works
Protocol for the fast chromatin immunoprecipitation (ChIP) method
Nelson, J. D., Denisenko, O. N., & Bomsztyk, K. (2006) · Nature Protocols · doi:10.1038/nprot.2006.27 · Cited by 771 · see citing works
DNA methylation inhibits transcription indirectly via a methyl-CpG binding protein
Boyes, J., & Bird, A. P. (1991) · Cell · doi:10.1016/0092-8674(91)90267-3 · Cited by 733 · see citing works
Liu, X. S., Brutlag, D. L., & Liu, J. S. (2002) · Nature Biotechnology · doi:10.1038/nbt717 · Cited by 670 · see citing works
Identification of a mammalian protein that binds specifically to DNA containing methylated CpGs
Meehan, R. R., Lewis, J., McKay, S. J., Kleiner, E., & Bird, A. P. (1989) · Cell · doi:10.1016/0092-8674(89)90430-3 · Cited by 659 · see citing works
Glycosylation regulates Notch signalling
Haines, N., & Irvine, K. D. (2003) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1228 · Cited by 643 · see citing works
Nucleosome-Interacting Proteins Regulated by DNA and Histone Methylation
Bartke, T., Vermeulen, M., Xhemalce, B., Robson, S. C., Mann, M., & Kouzarides, T. (2010) · Cell · doi:10.1016/j.cell.2010.10.012 · Cited by 611 · see citing works
Quenneville, S., Verde, G., Corsinotti, A., Kapopoulou, A., Jakobsson, J., Offner, S., Baglivo, I., Pedone, P. V., Grimaldi, G., Riccio, A., et al. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.08.032 · Cited by 606 · see citing works
Genomic Distribution and Inter-Sample Variation of Non-CpG Methylation across Human Cell Types
Ziller, M. J., Müller, F., Liao, J., Zhang, Y., Gu, H., Bock, C., Boyle, P. J., Epstein, C. B., Bernstein, B., Lengauer, T., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002389 · Cited by 398 · see citing works
Hu, S., Xie, Z., Onishi, A., Yu, X., Jiang, L., Lin, J., Rho, H., Woodard, C. L., Wang, H., Jeong, J. S., et al. (2009) · Cell · doi:10.1016/j.cell.2009.08.037 · Cited by 377 · see citing works
Self-citationA Family of Human Zinc Finger Proteins That Bind Methylated DNA and Repress Transcription
Filion, G. J. P., Zhenilo, S. V., Salozhin, S. V., Yamada, D., Prokhortchouk, E., & Defossez, P. (2005) · Molecular and Cellular Biology · doi:10.1128/mcb.26.1.169-181.2006 · Cited by 357 · see citing works
A Universal Framework for Regulatory Element Discovery across All Genomes and Data Types
Elemento, O., Slonim, N., & Tavazoie, S. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.09.027 · Cited by 306 · see citing works
MeCP2 Binding to DNA Depends upon Hydration at Methyl-CpG
Ho, K. L., McNae, I. W., Schmiedeberg, L., Klose, R. J., Bird, A. P., & Walkinshaw, M. D. (2008) · Molecular Cell · doi:10.1016/j.molcel.2007.12.028 · Cited by 282 · see citing works
Functional Analysis of Promoter CPG-Methylation using a CpG-Free Luciferase Reporter Vector
Klug, M., & Rehli, M. (2006) · Epigenetics · doi:10.4161/epi.1.3.3327 · Cited by 249 · see citing works
Rishi, V., Bhattacharya, P., Chatterjee, R., Rozenberg, J. M., Zhao, J., Glass, K., FitzGerald, P. C., & Vinson, C. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1008688107 · Cited by 221 · see citing works
Chiang, C.-H. J., Su, Y.-J., Wen, Z.-X., Yoritomo, N., Ross, C. A., Margolis, R., Song, H.-J., & Guo, L.-M. (2011) · Molecular Psychiatry · doi:10.1038/mp.2011.13 · Cited by 199 · see citing works
Self-citationIdentification of the DNA sequence that interacts with the gut-enriched Kruppel-like factor
Shields, J. M. (1998) · Nucleic Acids Research · doi:10.1093/nar/26.3.796 · Cited by 179 · see citing works
Identification of regions correlating MGMT promoter methylation and gene expression in glioblastomas
Everhard, S., Tost, J., abdalaoui, H. E., Crinière, E., Busato, F., Marie, Y., Gut, I. G., Sanson, M., Mokhtari, K., Laigle–Donadey, F., et al. (2009) · Neuro-Oncology · doi:10.1215/15228517-2009-001 · Cited by 177 · see citing works
Yu, X., Lin, J., Zack, D. J., & Qian, J. X. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl595 · Cited by 163 · see citing works
Self-citationGene silencing by methyl-CpG-binding proteins.
Nan, X.-S., Cross, S. H., & Bird, A. (1998) · Novartis Foundation symposium · doi:10.1002/9780470515501.ch2 · Cited by 142 · see citing works
Analysis of Protein–DNA Interactions Using Surface Plasmon Resonance
Majka, J., & Speck, C. (2006) · Springer eBooks · doi:10.1007/10_026 · Cited by 130 · see citing works
An atomic model of Zfp57 recognition of CpG methylation within a specific DNA sequencePreprint
Liu, Y., Toh, H., Sasaki, H., Zhang, X., & Cheng, X. (2012) · Genes & Development · doi:10.1101/gad.202200.112 · Cited by 128 · see citing works
Mann, I. K., Chatterjee, R., Zhao, J., He, X., Weirauch, M. T., Hughes, T. R., & Vinson, C. (2013) · Genome Research · doi:10.1101/gr.146654.112 · Cited by 126 · cited 1× · see citing works
“Our approach also showed some false negatives because some known methylated DNA binding proteins were not identified in this study (Mann et al., 2013; Spruijt et al., 2013).”
BackgroundThe structure of the Klf4 DNA-binding domain links to self-renewal and macrophage differentiation
Schuetz, A., Nana, D., Rose, C., Zocher, G., Milanovic, M., Koenigsmann, J., Blasig, R., Heinemann, U., & Carstanjen, D. (2011) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-010-0618-x · Cited by 100 · see citing works
hPDI: a database of experimental human protein–DNA interactions
Xie, Z., Hu, S., Blackshaw, S., Zhu, H., & Qian, J. X. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp631 · Cited by 84 · see citing works
Self-citationLandry, J. P., Zhu, X. D., & Gregg, J. (2004) · Optics Letters · doi:10.1364/ol.29.000581 · Cited by 74 · see citing works
Zhu, X. D., Landry, J. P., Sun, Y.-S., Gregg, J. P., Lam, K. S., & Guo, X. (2007) · Applied Optics · doi:10.1364/ao.46.001890 · Cited by 70 · see citing works
Bartels, S. J. J., Spruijt, C. G., Brinkman, A. B., Jansen, P. W. T. C., Vermeulen, M., & Stunnenberg, H. G. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025884 · Cited by 55 · see citing works
Fei, Y. Y., Schmidt, A., Bylund, G., Johansson, D., Henriksson, S., Lebrilla, C. B., Solnick, J. V., Borén, T., & Zhu, X. (2011) · Analytical Chemistry · doi:10.1021/ac201260c · Cited by 48 · see citing works
Karlsson, Q. H., Schelcher, C., Verrall, E., Petosa, C., & Sinclair, A. J. (2008) · PLoS Pathogens · doi:10.1371/journal.ppat.1000005 · Cited by 39 · see citing works
Characterization of Protein–Protein Interactions Using Protein MicroarraysPreprint
Paul, C., Rho, H., Neiswinger, J., & Zhu, H. (2016) · Cold Spring Harbor Protocols · doi:10.1101/pdb.prot087965 · Cited by 13 · see citing works
Self-citationCharacterization of Protein–DNA Interactions Using Protein MicroarraysPreprint
Hu, S., Xie, Z., Blackshaw, S., Qian, J. X., & Zhu, H. (2011) · Cold Spring Harbor Protocols · doi:10.1101/pdb.prot5614 · Cited by 11 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
The Human Transcription Factors
Lambert, S. A., Jolma, A., Campitelli, L. F., Das, P. K., Yin, Y., Albu, M., Chen, X., Taipale, J., Hughes, T. R., & Weirauch, M. T. (2018) · Cell · doi:10.1016/j.cell.2018.01.029 · Cited by 3,399 · see citing works
Impact of cytosine methylation on DNA binding specificities of human transcription factors
Yin, Y., Morgunova, E., Jolma, A., Kaasinen, E., Sahu, B., Khund-Sayeed, S., Das, P. K., Kivioja, T., Dave, K., Zhong, F., et al. (2017) · Science · doi:10.1126/science.aaj2239 · Cited by 1,257 · see citing works
DNA methylation aging clocks: challenges and recommendations
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 · see citing works
Dynamic DNA methylation: In the right place at the right time
Luo, C., Hajkova, P., & Ecker, J. R. (2018) · Science · doi:10.1126/science.aat6806 · Cited by 668 · see citing works
Transcription factors as readers and effectors of DNA methylation
Zhu, H., Wang, G., & Qian, J. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.83 · Cited by 649 · see citing works
Self-citationDistribution, recognition and regulation of non-CpG methylation in the adult mammalian brain
Guo, J. U., Su, Y., Shin, J. H., Shin, J., Li, H., Xie, B., Zhong, C., Hu, S., Le, T., Fan, G., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3607 · Cited by 714 · see citing works
Self-citationCompetition between DNA methylation and transcription factors determines binding of NRF1
Domcke, S., Bardet, A. F., Adrian Ginno, P., Hartl, D., Burger, L., & Schübeler, D. (2015) · Nature · doi:10.1038/nature16462 · Cited by 508 · see citing works
The Genetics of Transcription Factor DNA Binding Variation
Deplancke, B., Alpern, D., & Gardeux, V. (2016) · Cell · doi:10.1016/j.cell.2016.07.012 · Cited by 390 · see citing works
Sensitivity of transcription factors to DNA methylation
Héberlé, É., & Bardet, A. F. (2019) · Essays in Biochemistry · doi:10.1042/ebc20190033 · Cited by 347 · see citing works
Role of DNA Methylation in Modulating Transcription Factor Occupancy
Maurano, M. T., Wang, H., John, S., Shafer, A., Canfield, T., Lee, K., & Stamatoyannopoulos, J. A. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.07.024 · Cited by 281 · see citing works
Transcriptional and epigenomic landscapes of CNS and non-CNS vascular endothelial cells
Sabbagh, M. F., Heng, J. S., Luo, C., Castanon, R. G., Nery, J. R., Rattner, A., Goff, L. A., Ecker, J. R., & Nathans, J. (2018) · eLife · doi:10.7554/elife.36187 · Cited by 245 · see citing works
Watson, C. T., Roussos, P., Garg, P., Ho, D. J., Azam, N., Katsel, P. L., Haroutunian, V., & Sharp, A. J. (2016) · Genome Medicine · doi:10.1186/s13073-015-0258-8 · Cited by 201 · see citing works
Pflueger, C., Tan, D., Swain, T., Nguyen, T., Pflueger, J., Nefzger, C., Polo, J. M., Ford, E., & Lister, R. (2018) · Genome Research · doi:10.1101/gr.233049.117 · Cited by 188 · see citing works
Wan, J., Oliver, V. F., Wang, G., Zhu, H., Zack, D. J., Merbs, S. L., & Qian, J. (2015) · BMC Genomics · doi:10.1186/s12864-015-1271-4 · Cited by 165 · see citing works
Self-citationWilson, S., Qi, J., & Filipp, F. V. (2016) · Scientific Reports · doi:10.1038/srep32611 · Cited by 126 · see citing works
Evolving insights on how cytosine methylation affects protein-DNA binding
Dantas Machado, A. C., Zhou, T., Rao, S., Goel, P., Rastogi, C., Lazarovici, A., Bussemaker, H. J., & Rohs, R. (2015) · Briefings in Functional Genomics · doi:10.1093/bfgp/elu040 · Cited by 124 · see citing works
Structural basis for Klf4 recognition of methylated DNA
Liu, Y., Olanrewaju, Y. O., Zheng, Y., Hashimoto, H., Blumenthal, R. M., Zhang, X., & Cheng, X. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku134 · Cited by 99 · see citing works
Decoding the role of TET family dioxygenases in lineage specification
Wu, X., Li, G., & Xie, R. (2018) · Epigenetics & Chromatin · doi:10.1186/s13072-018-0228-7 · Cited by 43 · see citing works
Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet
Viner, C., Ishak, C. A., Johnson, J., Walker, N. J., Shi, H., Sjöberg-Herrera, M. K., Shen, S. Y., Lardo, S. M., Adams, D. J., Ferguson-Smith, A. C., et al. (2016) · doi:10.1101/043794 · Cited by 18 · see citing works
Epigenetic preparation of future gene induction kinetics
Xiong, J., & Zhu, B. (2025) · Annual Review of Genetics · doi:10.1146/annurev-genet-012825-093148 · Cited by 12 · see citing works
- Authors
- Hu, S., Wan, J., Su, Y., Song, Q., Zeng, Y., Nguyen, H. N., Shin, J., Cox, E., Rho, H. S., Woodard, C., Xia, S., Liu, S., Lyu, H., Ming, G.-L., Wade, H., Song, H., Qian, J., & Zhu, H.
- Affiliations
- Johns Hopkins University (US)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Wade, Herschel
- Song, Hongjun
- Qian, Jiang
- Zhu, Heng
- ORCID
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2013-09-03
- Volume
- 2
- Pages
- e00726-e00726
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC3762332
- OpenAlex
- W2128059998
- Cited by
- 349
- References
- 50
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 13 · 2023: 19 · 2022: 31 · 2021: 25 · 2020: 25 · 2019: 33 · 2018: 37 · 2017: 39 · 2016: 34 · 2015: 29 · 2014: 26 · 2013: 4
- FWCI
- 13.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (R01 GM076102, U54 RR020839, U24 CA160036, U54 HG006434, R21 EY021897, NS047344, MH087874, ES021957, NS048271, HD069184)
- The Simons Foundation Autism Research Initiative
- Dr Miriam and Sheldon G Adelson Medical Research Foundation
- Maryland Stem Cell Research Fund (2009-MSCRFE-0063-00, 2012-MSCRFII-0063-00)
- Simons Foundation
- Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
- 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 › Kruppel-like factors research
- Keywords
- DNA methylation, CpG methylation, transcription factors, DNA-binding activity, KLF4, epigenetic regulation of transcription, human embryonic stem cells, protein microarrays, transcriptional repression
- MeSH terms
- Kruppel-Like Factor 4, Binding Sites, Humans, Promoter Regions, Genetic, Transcription Factors, CpG Islands, DNA Methylation
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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 ›
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