The DOI matches its Crossref record; 97 of the 97 references it cites were found in a registry or an index.
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
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
In the citing paper
“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]
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
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
Flagged first, then by citations
Cited by
Sorted by citations
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861
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
Self-citationDNA methylation-based biomarkers and the epigenetic clock theory of ageing
Horvath, S., & Raj, K. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0004-3 · Cited by 3,095
Macrophages in immunoregulation and therapeutics
Chen, S., Saeed, A. F. U. H., Liu, Q., Jiang, Q., Xu, H., Xiao, G. G., Rao, L., & Duo, Y. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01452-1 · Cited by 2,477
The diverse roles of DNA methylation in mammalian development and disease
Greenberg, M., & Bourc’his, D. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0159-6 · Cited by 2,272
JASPAR 2020: update of the open-access database of transcription factor binding profiles
Fornes, O., Castro-Mondragon, J. A., Khan, A., van der Lee, R., Zhang, X., Richmond, P. A., Modi, B. P., Correard, S., Gheorghe, M., Baranašić, D., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1001 · Cited by 1,763
The DNA methyltransferase family: a versatile toolkit for epigenetic regulation
Lyko, F. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.80 · Cited by 1,510
The chromatin accessibility landscape of primary human cancers
Corces, M. R., Granja, J. M., Shams, S., Louie, B. H., Seoane, J. A., Zhou, W., Silva, T. C., Groeneveld, C., Wong, C. K., Cho, S. W., et al. (2018) · Science · doi:10.1126/science.aav1898 · Cited by 1,230
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
YY1 Is a Structural Regulator of Enhancer-Promoter Loops
Weintraub, A. S., Li, C. H., Zamudio, A. V., Sigova, A. A., Hannett, N. M., Day, D. S., Abraham, B. J., Cohen, M. A., Nabet, B., Buckley, D. L., et al. (2017) · Cell · doi:10.1016/j.cell.2017.11.008 · Cited by 992
Navigating the DNA methylation landscape of cancer
Nishiyama, A., & Nakanishi, M. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.05.002 · Cited by 1,001
Sensitive tumour detection and classification using plasma cell-free DNA methylomes
Shen, S. Y., Singhania, R., Fehringer, G., Chakravarthy, A., Roehrl, M. H. A., Chadwick, D., Zuzarte, P. C., Borgida, A., Wang, T. T., Li, T., et al. (2018) · Nature · doi:10.1038/s41586-018-0703-0 · Cited by 983
DNA methylation: a historical perspective
Mattei, A. L., Bailly, N., & Meissner, A. (2022) · Trends in Genetics · doi:10.1016/j.tig.2022.03.010 · Cited by 920
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
Boltz-2: Towards Accurate and Efficient Binding Affinity PredictionPreprint
Passaro, S., Corso, G., Wohlwend, J., Reveiz, M., Thaler, S., Somnath, V. R., Getz, N., Portnoi, T., Roy, J., Stark, H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.14.659707 · Cited by 940
Bentsen, M. S., Goymann, P., Schultheis, H., Klee, K., Petrova, A., Wiegandt, R., Fust, A., Preussner, J., Kuenne, C. T., Braun, T. W., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18035-1 · Cited by 649
A DNA methylation atlas of normal human cell types
Loyfer, N., Magenheim, J., Peretz, A., Cann, G., Bredno, J., Klochendler, A., Fox-Fisher, I., Shabi-Porat, S., Hecht, M., Pelet, T., et al. (2023) · Nature · doi:10.1038/s41586-022-05580-6 · Cited by 656
DNA Methylation Clocks in Aging: Categories, Causes, and Consequences
Field, A. E., Robertson, N., Wang, T., Havas, A. P., Ideker, T., & Adams, P. D. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.08.008 · Cited by 644
Molecular mechanisms of transgenerational epigenetic inheritance
Fitz-James, M. H., & Cavalli, G. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-021-00438-5 · Cited by 589
Mechanisms regulating zygotic genome activation
Schulz, K. N., & Harrison, M. M. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0087-x · Cited by 564
The impact of cellular metabolism on chromatin dynamics and epigenetics
Reid, M. A., Dai, Z., & Locasale, J. W. (2017) · Nature Cell Biology · doi:10.1038/ncb3629 · Cited by 515
Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation
Min, J. L., Hemani, G., Hannon, E., Dekkers, K. F., Castillo-Fernandez, J., Luijk, R., Carnero-Montoro, E., Lawson, D. J., Burrows, K., Suderman, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00923-x · Cited by 506
The evolving metabolic landscape of chromatin biology and epigenetics
Dai, Z., Ramesh, V., & Locasale, J. W. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0270-8 · Cited by 508
Mechanisms of early placental development in mouse and humans
Hemberger, M., Hanna, C. W., & Dean, W. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0169-4 · Cited by 515
Induced pluripotent stem cells (iPSCs): molecular mechanisms of induction and applications
Cerneckis, J., Cai, H., & Shi, Y. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01809-0 · Cited by 452
Sex Differences in Gene Expression and Regulatory Networks across 29 Human Tissues
Lopes‐Ramos, C. M., Chen, C.-Y., Kuijjer, M. L., Paulson, J. N., Sonawane, A. R., Fagny, M., Platig, J., Glass, K., Quackenbush, J. F., & DeMeo, D. L. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107795 · Cited by 462
The genomics of oxidative DNA damage, repair, and resulting mutagenesis
Poetsch, A. R. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2019.12.013 · Cited by 420
A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex
Yao, Z., Liu, H., Xie, F., Fischer, S., Adkins, R. S., Aldridge, A. I., Ament, S. A., Bartlett, A., Behrens, M. M., Van den Berge, K., et al. (2021) · Nature · doi:10.1038/s41586-021-03500-8 · Cited by 398
Global reference mapping of human transcription factor footprints
Vierstra, J., Lazar, J., Sandstrom, R., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Haugen, E., et al. (2020) · Nature · doi:10.1038/s41586-020-2528-x · Cited by 386
The interaction landscape between transcription factors and the nucleosome
Zhu, F., Farnung, L., Kaasinen, E., Sahu, B., Yin, Y., Wei, B., Dodonova, S., Nitta, K. R., Morgunova, E. Y., Taipale, M., et al. (2018) · Nature · doi:10.1038/s41586-018-0549-5 · Cited by 369
Self-citationThe AP-1 transcriptional complex: Local switch or remote command?
Bejjani, F., Evanno, E., Zibara, K., Piechaczyk, M., & Jariel‐Encontre, I. (2019) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2019.04.003 · Cited by 370
The DNA methylation landscape of advanced prostate cancer
Zhao, S. G., Chen, W. S., Li, H., Foye, A., Zhang, M., Sjöström, M., Aggarwal, R. R., Playdle, D., Liao, A., Alumkal, J. J., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0648-8 · Cited by 357
Sensitivity of transcription factors to DNA methylation
Héberlé, É., & Bardet, A. F. (2019) · Essays in Biochemistry · doi:10.1042/ebc20190033 · Cited by 347
Exercise Metabolism and Adaptation in Skeletal Muscle
Smith, J. A. B., Murach, K. A., Dyar, K. A., & Zierath, J. R. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00606-x · Cited by 342
Statistical and integrative system-level analysis of DNA methylation data
Teschendorff, A. E., & Relton, C. L. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.86 · Cited by 297
Deciphering the multi-scale, quantitative cis-regulatory code
Kim, S., & Wysocka, J. (2023) · Molecular Cell · doi:10.1016/j.molcel.2022.12.032 · Cited by 302
DNA methylation atlas of the mouse brain at single-cell resolution
Liu, H., Zhou, J., Tian, W., Luo, C., Bartlett, A., Aldridge, A., Lucero, J., Osteen, J. K., Nery, J. R., Chen, H., et al. (2021) · Nature · doi:10.1038/s41586-020-03182-8 · Cited by 289
G-quadruplexes are transcription factor binding hubs in human chromatin
Spiegel, J., Cuesta, S. M., Adhikari, S., Hänsel‐Hertsch, R., Tannahill, D., & Balasubramanian, S. (2021) · Genome biology · doi:10.1186/s13059-021-02324-z · Cited by 279
Biological embedding of experience: a primer on epigenetics
Aristizabal, M. J., Anreiter, I., Halldorsdottir, T., Odgers, C. L., McDade, T. W., Goldenberg, A., Mostafavi, S., Kobor, M. S., Binder, E. B., Sokolowski, M. B., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1820838116 · Cited by 268
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
Johnson, K. C., Anderson, K. J., Courtois, E. T., Gujar, A. D., Barthel, F. P., Varn, F. S., Luo, D., Seignon, M., Yi, E. S., Kim, H., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00926-8 · Cited by 277
Lago, S., Nadai, M., Cernilogar, F. M., Kazerani, M., Domíniguez Moreno, H., Schotta, G., & Richter, S. N. (2021) · Nature Communications · doi:10.1038/s41467-021-24198-2 · Cited by 269
Characterizing cis-regulatory elements using single-cell epigenomics
Preissl, S., Gaulton, K. J., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-022-00509-1 · Cited by 251
Liu, Y., Rosikiewicz, W., Pan, Z., Jillette, N., Wang, P., Taghbalout, A., Foox, J., Mason, C. E., Carroll, M. P., Cheng, A. W., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02510-z · Cited by 260
Transposable elements as a potent source of diverse cis -regulatory sequences in mammalian genomes
Sundaram, V., & Wysocka, J. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0347 · Cited by 253
DNA methylation disruption reshapes the hematopoietic differentiation landscape
Izzo, F., Lee, S. C., Poran, A., Chaligne, R., Gaiti, F., Gross, B., Murali, R. R., Deochand, S. D., Ang, C., Jones, P. W., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0595-4 · Cited by 236
Transcription Factors Drive Tet2-Mediated Enhancer Demethylation to Reprogram Cell Fate
Sardina, J. L., Collombet, S., Tian, T. V., Gómez, A., Stefano, B. D., Berenguer, C., Brumbaugh, J., Stadhouders, R., Segura-Morales, C., Gut, M., et al. (2018) · Cell stem cell · doi:10.1016/j.stem.2018.08.016 · Cited by 242
Nondestructive, base-resolution sequencing of 5-hydroxymethylcytosine using a DNA deaminase
Schutsky, E. K., DeNizio, J. E., Hu, P., Liu, M. Y., Nabel, C. S., Fabyanic, E. B., Hwang, Y., Bushman, F. D., Wu, H., & Kohli, R. M. (2018) · Nature Biotechnology · doi:10.1038/nbt.4204 · Cited by 234
Low-Affinity Binding Sites and the Transcription Factor Specificity Paradox in Eukaryotes
Kribelbauer, J. F., Rastogi, C., Bussemaker, H. J., & Mann, R. S. (2019) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100617-062719 · Cited by 231
Sequence determinants of human gene regulatory elements
Sahu, B., Hartonen, T., Pihlajamaa, P., Wei, B., Dave, K., Zhu, F., Kaasinen, E., Lidschreiber, K., Lidschreiber, M., Daub, C. O., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-01009-4 · Cited by 198
Self-citationMatsuda, T., Irie, T., Katsurabayashi, S., Hayashi, Y., Nagai, T., Hamazaki, N., Adefuin, A. M. D., Miura, F., Ito, T., Kimurâ, H., et al. (2019) · Neuron · doi:10.1016/j.neuron.2018.12.010 · Cited by 231
Killaars, A. R., Grim, J. C., Walker, C. J., Hushka, E. A., Brown, T. E., & Anseth, K. S. (2018) · Advanced Science · doi:10.1002/advs.201801483 · Cited by 209
Catarino, R. R., & Stark, A. (2018) · Genes & Development · doi:10.1101/gad.310367.117 · Cited by 215
Mechanisms of Interplay between Transcription Factors and the 3D Genome
Kim, S., & Shendure, J. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.08.010 · Cited by 218
The microbiota programs DNA methylation to control intestinal homeostasis and inflammation
Ansari, I., Raddatz, G., Gutekunst, J., Ridnik, M., Cohen, D., Abu-Remaileh, M., Tuganbaev, T., Shapiro, H., Pikarsky, E., Elinav, E., et al. (2020) · Nature Microbiology · doi:10.1038/s41564-019-0659-3 · Cited by 208
Kaluscha, S., Domcke, S., Wirbelauer, C., Stadler, M. B., Durdu, S., Burger, L., & Schübeler, D. (2022) · Nature Genetics · doi:10.1038/s41588-022-01241-6 · Cited by 228
Self-citationThe Roles of Human DNA Methyltransferases and Their Isoforms in Shaping the Epigenome
Gujar, H., Weisenberger, D. J., & Liang, G. (2019) · Genes · doi:10.3390/genes10020172 · Cited by 210
Short tandem repeats bind transcription factors to tune eukaryotic gene expression
Horton, C. A., Alexandari, A. M., Hayes, M. G. B., Marklund, E., Schaepe, J. M., Aditham, A. K., Shah, N., Suzuki, P., Shrikumar, A., Afek, A., et al. (2023) · Science · doi:10.1126/science.add1250 · Cited by 207
Epigenetics of Male Infertility: The Role of DNA Methylation
Rotondo, J. C., Lanzillotti, C., Mazziotta, C., Tognon, M. G., & Martini, F. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.689624 · Cited by 197
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
Candidate silencer elements for the human and mouse genomes
Jayavelu, N. D., Jajodia, A., Mishra, A., & Hawkins, R. D. (2020) · Nature Communications · doi:10.1038/s41467-020-14853-5 · Cited by 193
Simpson, D. J., & Chandra, T. (2021) · Aging Cell · doi:10.1111/acel.13452 · Cited by 195
Enhancer DNA methylation: implications for gene regulation
Angeloni, A., & Bogdanović, O. (2019) · Essays in Biochemistry · doi:10.1042/ebc20190030 · Cited by 181
Liu, Y., Wu, F.-Y., Tian, R.-Y., Shi, Y., Xu, Z.-Q., Liu, J.-Y., Huang, J., Xue, F.-F., Liu, B.-Y., & Liu, G. (2023) · Communications Biology · doi:10.1038/s42003-022-04154-6 · Cited by 178
Ginno, P. A., Gaidatzis, D., Feldmann, A., Hoerner, L., Imanci, D., Burger, L., Zilbermann, F., Peters, A. H. F. M., Edenhofer, F., Smallwood, S. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16354-x · Cited by 179
Self-citationSingle nucleus multi-omics identifies human cortical cell regulatory genome diversity
Luo, C., Liu, H., Xie, F., Armand, E. J., Siletti, K., Bakken, T. E., Fang, R., Doyle, W. I., Stuart, T., Hodge, R. D., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100107 · Cited by 173
Spatiotemporal DNA methylome dynamics of the developing mouse fetus
He, Y., Hariharan, M., Gorkin, D. U., Dickel, D. E., Luo, C., Castanon, R., Nery, J. R., Lee, A. Y., Zhao, Y., Huang, H., et al. (2020) · Nature · doi:10.1038/s41586-020-2119-x · Cited by 165
DNA methylation predicts age and provides insight into exceptional longevity of bats
Wilkinson, G. S., Adams, D. M., Haghani, A., Lu, A. T.-H., Zoller, J. A., Breeze, C. E., Arnold, B. D., Ball, H. C., Carter, G. G., Cooper, L. N., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21900-2 · Cited by 175
Evolution of DNA Methylome Diversity in Eukaryotes
de Mendoza, A., Lister, R., & Bogdanović, O. (2019) · Journal of Molecular Biology · doi:10.1016/j.jmb.2019.11.003 · Cited by 170
Mechanisms that regulate the activities of TET proteins
Joshi, K., Liu, S., Breslin, P., & Zhang, J. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04396-x · Cited by 177
Epigenetics in Insects: Genome Regulation and the Generation of Phenotypic Diversity
Glastad, K. M., Hunt, B. G., & Goodisman, M. A. D. (2018) · Annual Review of Entomology · doi:10.1146/annurev-ento-011118-111914 · Cited by 176
Rizzardi, L. F., Hickey, P. F., Rodriguez DiBlasi, V., Tryggvadóttir, R., Callahan, C. M., Idrizi, A., Hansen, K. D., & Feinberg, A. P. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0297-8 · Cited by 146
An Adversarial DNA N6-Methyladenine-Sensor Network Preserves Polycomb Silencing
Kweon, S.-M., Chen, Y., Moon, E., Kvederavičiūtė, K., Klimašauskas, S., & Feldman, D. E. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.03.018 · Cited by 168
Vorontsov, I. E., Eliseeva, I. A., Zinkevich, A. O., Nikonov, M., Abramov, S., Boytsov, A., Kamenets, V., Kasianova, A. M., Kolmykov, S. K., Yevshin, I., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1077 · Cited by 163
Self-citationSystematic analysis of binding of transcription factors to noncoding variants
Yan, J., Qiu, Y., dos Santos, A. M. R., Yin, Y., Li, Y. E., Vinckier, N., Nariai, N., Benaglio, P., Raman, A., Li, X., et al. (2021) · Nature · doi:10.1038/s41586-021-03211-0 · Cited by 163
Self-citationBell, C. G., Gao, F., Yuan, W., Roos, L., Acton, R., Xia, Y., Bell, J. T., Ward, K. J., Mangino, M., Hysi, P. G., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-01586-1 · Cited by 157
Generating specificity in genome regulation through transcription factor sensitivity to chromatin
Isbel, L., Grand, R. S., & Schübeler, D. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00512-6 · Cited by 152
Self-citationGene activation precedes DNA demethylation in response to infection in human dendritic cells
Pacis, A., Mailhot-Léonard, F., Tailleux, L., Randolph, H. E., Yotova, V., Dumaine, A., Grenier, J., & Barreiro, L. B. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814700116 · Cited by 152
Taming transposable elements in vertebrates: from epigenetic silencing to domestication
Almeida, M. V., Vernaz, G., Putman, A. L. K., & Miska, E. A. (2022) · Trends in Genetics · doi:10.1016/j.tig.2022.02.009 · Cited by 150
ChromID identifies the protein interactome at chromatin marks
Villaseñor, R., Pfaendler, R., Ambrosi, C. M., Butz, S., Giuliani, S., Bryan, E., Sheahan, T. W., Gable, A. L., Schmolka, N., Manzo, M., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0434-2 · Cited by 145
Genetic and epigenetic regulation of human aging and longevity
Morris, B. J., Willcox, B. J., & Donlon, T. A. (2019) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2018.08.039 · Cited by 140
Editing the Epigenome: Reshaping the Genomic Landscape
Holtzman, L., & Gersbach, C. A. (2018) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-083117-021632 · Cited by 147
Genetic–epigenetic interactions in cis: a major focus in the post-GWAS era
Do, C., Shearer, A., Suzuki, M., Terry, M. B., Gelernter, J. E., Greally, J. M., & Tycko, B. (2017) · Genome biology · doi:10.1186/s13059-017-1250-y · Cited by 145
Epigenetic mechanisms regulating T-cell responses
Schmidl, C., Delacher, M., Huehn, J., & Feuerer, M. (2018) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2018.07.014 · Cited by 153
Similarity regression predicts evolution of transcription factor sequence specificity
Lambert, S. A., Yang, A. W. H., Sasse, A., Cowley, G., Albu, M., Caddick, M. X., Morris, Q., Weirauch, M. T., & Hughes, T. R. (2019) · Nature Genetics · doi:10.1038/s41588-019-0411-1 · Cited by 141
Methylation across the central dogma in health and diseases: new therapeutic strategies
Liu, R., Zhao, E., Yu, H., Yuan, C., Abbas, M. N., & Cui, H. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01528-y · Cited by 155
TET Enzymes and 5hmC in Adaptive and Innate Immune Systems
Lio, C. J., & Rao, A. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00210 · Cited by 144
Nam, A. S., Dusaj, N., Izzo, F., Murali, R., Myers, R. M., Mouhieddine, T. H., Sotelo, J., Benbarche, S., Waarts, M., Gaiti, F., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01179-9 · Cited by 140
Rauluševičiūtė, I., Drabløs, F., & Rye, M. B. (2020) · BMC Medical Genomics · doi:10.1186/s12920-020-0657-6 · Cited by 129
Genome-wide quantification of the effects of DNA methylation on human gene regulation
Lea, A. J., Vockley, C. M., Johnston, R. A., Carpio, C. A. D., Barreiro, L. B., Reddy, T. E., & Tung, J. (2018) · eLife · doi:10.7554/elife.37513 · Cited by 138
DNA Methylation and Susceptibility to Autism Spectrum Disorder
Tremblay, M. W., & Jiang, Y. (2019) · Annual Review of Medicine · doi:10.1146/annurev-med-120417-091431 · Cited by 139
Quantitative Analysis of the DNA Methylation Sensitivity of Transcription Factor Complexes
Kribelbauer, J. F., Laptenko, O., Chen, S., Martini, G. D., Freed-Pastor, W. A., Prives, C. L., Mann, R. S., & Bussemaker, H. J. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.05.069 · Cited by 130
Gene Regulatory Network Analysis Identifies Sex-Linked Differences in Colon Cancer Drug Metabolism
Lopes‐Ramos, C. M., Kuijjer, M. L., Ogino, S., Fuchs, C. S., DeMeo, D. L., Glass, K., & Quackenbush, J. F. (2018) · Cancer Research · doi:10.1158/0008-5472.can-18-0454 · Cited by 122
Knaupp, A. S., Buckberry, S., Pflueger, J., Lim, S. M., Ford, E., Larcombe, M. R., Rossello, F. J., de Mendoza, A., Alaei, S., Firas, J., et al. (2017) · Cell Stem Cell · doi:10.1016/j.stem.2017.11.007 · Cited by 127
Paradoxical association of TET loss of function with genome-wide DNA hypomethylation
López-Moyado, I. F., Tsagaratou, A., Yuita, H., Seo, H., Delatte, B., Heinz, S., Benner, C. W., & Rao, A. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1903059116 · Cited by 130
Dura, M., Teissandier, A., Armand, M., Barau, J., Lapoujade, C., Fouchet, P., Bonneville, L., Schulz, M., Weber, M., Baudrin, L. G., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01040-z · Cited by 135
Retention of paternal DNA methylome in the developing zebrafish germline
Skvortsova, K., Tarbashevich, K., Stehling, M., Lister, R., Irimia, M., Raz, E., & Bogdanović, O. (2019) · Nature Communications · doi:10.1038/s41467-019-10895-6 · Cited by 126
de Mendoza, A., Nguyen, T. V., Ford, E., Poppe, D., Buckberry, S., Pflueger, J., Grimmer, M., Stolzenburg, S., Bogdanović, O., Oshlack, A., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02728-5 · Cited by 130
Rube, H. T., Rastogi, C., Feng, S., Kribelbauer, J. F., Li, A., Becerra, B., Melo, L. A. N., Viet, B., Li, X., Adam, H., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01307-0 · Cited by 123
Halter, T., Wang, J., Amesefe, D., Lastrucci, E., Charvin, M., Singla‐Rastogi, M., & Navarro, L. (2021) · eLife · doi:10.7554/elife.62994 · Cited by 115
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
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
