Analog epigenetic memory revealed by targeted chromatin editing
Open accessPreprint — published as 10.1016/j.xgen.2025.100985
Abstract
Summary: Chemical modifications to histones and DNA play a crucial role in the regulation of transcription and in the maintenance of chromatin states that are not permissive to gene expression [1–3]. However, the landscape of gene expression states that these modifications stably maintain remains uncharted. Here, we show that gene expression can be memorized at a wide range of levels thus implementing analog epigenetic memory. Mechanistically, we find that DNA methylation serves a primary role in maintaining memory across cell divisions while histone modifications only follow DNA methylation to regulate gene expression. Employing targeted epigenetic editing and time-course analysis, we analyzed the temporal stability of gene expression and DNA methylation post removal of epigenetic effectors. We found that the grade of DNA methylation in the gene’s promoter, defined as the mean fraction of methylated CpGs, remains stable over time and inversely correlates with gene expression level. By contrast, Histone 3 lysine 9 trimethylation (H3K9me3) could not persist after removal of its writer in the absence of DNA methylation. These experimental findings, combined with our chromatin modification model, indicate that the absence of positive feedback mechanisms around DNA methylation - unlike those found in histone modifications - enable the temporal stability of the DNA methylation grade, which leads to analog memory. These results expand current knowledge on how epigenetic memory is achieved in natural systems. Moreover, we anticipate that analog memory through graded DNA methylation will enable to program mammalian cells with fine-grained information storage. This capability will significantly enhance the sophistication of engineered cell functionality in applications including tissue engineering, organoids, and cell therapies.
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
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Chromatin modifications and their function
Kouzarides, T. (2007) · Cell · doi:10.1016/j.cell.2007.02.005 · Cited by 10,883 · see citing works
ColabFold - Making protein folding accessible to all
Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2021) · doi:10.1101/2021.08.15.456425 · Cited by 9,391 · see citing works
Regulation of chromatin by histone modifications
Bannister, A. J., & Kouzarides, T. (2011) · Cell Research · doi:10.1038/cr.2011.22 · Cited by 6,012 · see citing works
Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine
Ito, S., Shen, L., Dai, Q., Wu, S. C., Collins, L. B., Swenberg, J. A., He, C., & Zhang, Y. (2011) · Science · doi:10.1126/science.1210597 · Cited by 3,451 · see citing works
Nan, X., Ng, H.-H., Johnson, C. A., Laherty, C. D., Turner, B. M., Eisenman, R. N., & Bird, A. (1998) · Nature · doi:10.1038/30764 · Cited by 3,440 · see citing works
Selective recognition of methylated lysine 9 on histone H3 by the HP1 chromo domain
Bannister, A. J., Zegerman, P., Partridge, J. F., Miska, E. A., Thomas, J. O., Allshire, R. C., & Kouzarides, T. (2001) · Nature · doi:10.1038/35065138 · Cited by 2,903 · see citing works
The molecular hallmarks of epigenetic control
Allis, C. D., & Jenuwein, T. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.59 · Cited by 2,809 · see citing works
Trained immunity: A program of innate immune memory in health and– disease
Netea, M. G., Joosten, L. A. B., Latz, E., Mills, K. H. G., Natoli, G., Stunnenberg, H. G., O’Neill, L. A. J., & Xavier, R. J. (2016) · Science · doi:10.1126/science.aaf1098 · Cited by 2,768 · see citing works
Methylated DNA and MeCP2 recruit histone deacetylase to repress transcription
Jones, P. L., Veenstra, G. J. C., Wade, P. A., Vermaak, D., Kass, S. U., Landsberger, N., Strouboulis, J., & Wolffe, A. P. (1998) · Nature Genetics · doi:10.1038/561 · Cited by 2,734 · see citing works
Stochastic Simulation of Chemical Kinetics
Gillespie, D. T. (2006) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.58.032806.104637 · Cited by 2,072 · see citing works
DNMT3L connects unmethylated lysine 4 of histone H3 to de novo methylation of DNA
Ooi, S. K. T., Qiu, C., Bernstein, E., Li, K., Jia, D., Yang, Z., Erdjument‐Bromage, H., Tempst, P., Lin, S., Allis, C. D., et al. (2007) · Nature · doi:10.1038/nature05987 · Cited by 1,558 · see citing works
Schultz, D. C., Ayyanathan, K., Negorev, D., Maul, G. G., & Rauscher, F. J. (2002) · Genes & Development · doi:10.1101/gad.973302 · Cited by 1,313 · see citing works
Editing DNA Methylation in the Mammalian Genome
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 · see citing works
Felsenfeld, G., & Groudine, M. T. (2003) · Nature · doi:10.1038/nature01411 · Cited by 1,153 · see citing works
Histone post-translational modifications - cause and consequence of genome function
Millán-Zambrano, G., Burton, A., Bannister, A. J., & Schneider, R. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00468-7 · Cited by 1,116 · see citing works
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation
Yao, Z., van Velthoven, C. T. J., Nguyen, T. N., Goldy, J., Sedeno-Cortes, A. E., Baftizadeh, F., Bertagnolli, D., Casper, T., Chiang, M., Crichton, K., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.021 · Cited by 1,065 · see citing works
Role of TET enzymes in DNA methylation, development, and cancer
Rasmussen, K. D., & Helin, K. (2016) · Genes & Development · doi:10.1101/gad.276568.115 · Cited by 1,040 · see citing works
DNA methylation pathways and their crosstalk with histone methylation
Du, J., Johnson, L. M., Jacobsen, S. E., & Patel, D. J. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm4043 · Cited by 1,000 · see citing works
The Methyl-CpG-binding Protein MeCP2 Links DNA Methylation to Histone Methylation
Fuks, F., Hurd, P. J., Wolf, D., Nan, X., Bird, A. P., & Kouzarides, T. (2003) · Journal of Biological Chemistry · doi:10.1074/jbc.m210256200 · Cited by 994 · see citing works
DNA Methylation in MammalsPreprint
Li, E., & Zhang, Y. (2014) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a019133 · Cited by 952 · see citing works
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 876 · see citing works
The interplay of histone modifications – writers that read
Zhang, T., Cooper, S., & Brockdorff, N. (2015) · EMBO Reports · doi:10.15252/embr.201540945 · Cited by 809 · see citing works
Histone H3 lysine 4 methylation patterns in higher eukaryotic genes
Schneider, R., Bannister, A. J., Myers, F. A., Thorne, A. W., Crane‐Robinson, C., & Kouzarides, T. (2003) · Nature Cell Biology · doi:10.1038/ncb1076 · Cited by 792 · see citing works
Ten principles of heterochromatin formation and function
Allshire, R. C., & Madhani, H. D. (2017) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.119 · Cited by 783 · see citing works
Cell Fates as High-Dimensional Attractor States of a Complex Gene Regulatory Network
Huang, S., Eichler, G., Bar-Yam, Y., & Ingber, D. E. (2005) · Physical Review Letters · doi:10.1103/physrevlett.94.128701 · Cited by 775 · see citing works
Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing
Nuñez, J. K., Chen, J., Pommier, G. C., Cogan, J. Z., Replogle, J. M., Adriaens, C., Ramadoss, G. N., Shi, Q., Hung, K. L., Samelson, A. J., et al. (2021) · Cell · doi:10.1016/j.cell.2021.03.025 · Cited by 760 · see citing works
Linking Stochastic Dynamics to Population Distribution: An Analytical Framework of Gene Expression
Friedman, N., Cai, L., & Xie, X. S. (2006) · Physical Review Letters · doi:10.1103/physrevlett.97.168302 · Cited by 700 · see citing works
Clark, S. J., Argelaguet, R., Kapourani, C.-A., Stubbs, T. M., Lee, H. J., Alda-Catalinas, C., Krueger, F., Sanguinetti, G., Kelsey, G., Marioni, J. C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03149-4 · Cited by 657 · see citing works
Chromatin modifiers and remodellers: regulators of cellular differentiation
Chen, T., & Dent, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3607 · Cited by 629 · see citing works
Krüppel-associated boxes are potent transcriptional repression domains.
Margolin, J., Friedman, J. R., Meyer, W. K.-H., Vissing, H., Thiesen, H., & Rauscher, F. J. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.10.4509 · Cited by 619 · see citing works
Epigenomic analysis detects widespread gene-body DNA hypomethylation in chronic lymphocytic leukemia
Kulis, M., Heath, S. C., Bibikova, M. V., Queirós, A. C., Navarro, A., Clot, G., Martínez‐Trillos, A., Castellano, G., Heath, I. B., Pinyol, M., et al. (2012) · Nature Genetics · doi:10.1038/ng.2443 · Cited by 568 · see citing works
DNA methylation and memory formation
Day, J. J., & Sweatt, J. D. (2010) · Nature Neuroscience · doi:10.1038/nn.2666 · Cited by 488 · see citing works
A Polycomb-based switch underlying quantitative epigenetic memory
Angel, A., Song, J., Dean, C., & Howard, M. (2011) · Nature · doi:10.1038/nature10241 · Cited by 478 · see citing works
Editing the epigenome: technologies for programmable transcription and epigenetic modulation
Thakore, P. I., Black, J. B., Hilton, I. B., & Gersbach, C. A. (2016) · Nature Methods · doi:10.1038/nmeth.3733 · Cited by 451 · see citing works
Multi-omics profiling of mouse gastrulation at single-cell resolution
Argelaguet, R., Clark, S. J., Mohammed, H., Stapel, L. C., Krueger, C., Kapourani, C.-A., Imaz-Rosshandler, I., Lohoff, T., Xiang, Y., Hanna, C. W., et al. (2019) · Nature · doi:10.1038/s41586-019-1825-8 · Cited by 450 · see citing works
Dynamics and Memory of Heterochromatin in Living Cells
Hathaway, N. A., Bell, O., Hodges, C., Miller, E. L., Neel, D. S., & Crabtree, G. R. (2012) · Cell · doi:10.1016/j.cell.2012.03.052 · Cited by 446 · see citing works
What is a cell type and how to define it?
Zeng, H. (2022) · Cell · doi:10.1016/j.cell.2022.06.031 · Cited by 439 · see citing works
Theoretical Analysis of Epigenetic Cell Memory by Nucleosome Modification
Dodd, I. B., Micheelsen, M. A., Sneppen, K., & Thon, G. (2007) · Cell · doi:10.1016/j.cell.2007.02.053 · Cited by 436 · see citing works
A Brief History of EpigeneticsPreprint
Felsenfeld, G. (2014) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a018200 · Cited by 420 · see citing works
Dynamics of epigenetic regulation at the single-cell level
Bintu, L., Yong, J., Antebi, Y., McCue, K., Kazuki, Y., Uno, N., Oshimura, M., & Elowitz, M. (2016) · Science · doi:10.1126/science.aab2956 · Cited by 408 · see citing works
Targa, F. R., Pikaart, M. J., Burgess-Beusse, B. L., Bell, A. C., Litt, M. D., West, A. G., Gaszner, M., & Felsenfeld, G. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.102179399 · Cited by 381 · see citing works
Ecco, G., Imbeault, M., & Trono, D. (2017) · Development · doi:10.1242/dev.132605 · Cited by 368 · see citing works
Epigenetic regulation of the innate immune response to infection
Zhang, Q., & Cao, X. (2019) · Nature Reviews Immunology · doi:10.1038/s41577-019-0151-6 · Cited by 366 · see citing works
Methylation-Dependent and -Independent Genomic Targeting Principles of the MBD Protein Family
Baubec, T., Ivánek, R., Lienert, F., & Schübeler, D. (2013) · Cell · doi:10.1016/j.cell.2013.03.011 · Cited by 365 · see citing works
Stem cell pluripotency and transcription factor Oct4
Pan, G., CHANG, Z. Y., Schöler, H. R., & Pei, D. (2002) · Cell Research · doi:10.1038/sj.cr.7290134 · Cited by 363 · see citing works
Epigenetic regulation of memory formation and maintenancePreprint
Zovkic, I. B., Karlsson, M. G., & Sweatt, J. D. (2013) · Learning & Memory · doi:10.1101/lm.026575.112 · Cited by 362 · see citing works
Jackson, M., Krassowska, A., Gilbert, N., Chevassut, T. J. T., Forrester, L. M., Ansell, J., & Ramsahoye, B. H. (2004) · Molecular and Cellular Biology · doi:10.1128/mcb.24.20.8862-8871.2004 · Cited by 345 · see citing works
Epigenetic inheritance and the missing heritability
Trerotola, M., Relli, V., Simeone, P., & Alberti, S. (2015) · Human Genomics · doi:10.1186/s40246-015-0041-3 · Cited by 318 · see citing works
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 · see citing works
Epigenetic control of innate and adaptive immune memory
Lau, C. M., Adams, N. M., Geary, C. D., Weizman, O.-E., Rapp, M., Pritykin, Y., Leslie, C. S., & Sun, J. C.-Y. (2018) · Nature Immunology · doi:10.1038/s41590-018-0176-1 · Cited by 279 · see citing works
SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2
Stein, R. A., & Mchaourab, H. S. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1010483 · Cited by 258 · see citing works
Specific or not specific recruitment of DNMTs for DNA methylation, an epigenetic dilemma
Hervouet, É., Peixoto, P., Delage-Mourroux, R., Boyer‐Guittaut, M., & Cartron, P. (2018) · Clinical Epigenetics · doi:10.1186/s13148-018-0450-y · Cited by 255 · see citing works
Vecchio, D. D., & Murray, R. M. (2014) · Princeton University Press eBooks · doi:10.1515/9781400850501 · Cited by 250 · see citing works
O’Geen, H., Ren, C., Nicolet, C. M., Perez, A. A., Halmai, J. A. N. M., Le, V. M., Mackay, J. P., Farnham, P., & Segal, D. J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx578 · Cited by 242 · see citing works
Laird, C. D., Pleasant, N. D., Clark, A. D., Sneeden, J. L., Hassan, K. M. A., Manley, N. C., Vary, J. C., Morgan, T. M., Hansen, R. S., & Stöger, R. J. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2536758100 · Cited by 211 · see citing works
The sound of silence: Transgene silencing in mammalian cell engineering
Cabrera, A., Edelstein, H. I., Glykofrydis, F., Love, K. S., Palacios, S., Tycko, J., Zhang, M., Lensch, S., Shields, C. E., Livingston, M., et al. (2022) · Cell Systems · doi:10.1016/j.cels.2022.11.005 · Cited by 201 · see citing works
Self-citationThe contradictory definitions of heterochromatin: transcription and silencing
Huisinga, K. L., Brower‐Toland, B. D., & Elgin, S. C. R. (2006) · Chromosoma · doi:10.1007/s00412-006-0052-x · Cited by 200 · see citing works
RNA m6A regulates transcription via DNA demethylation and chromatin accessibility
Deng, S., Zhang, J., Su, J., Zuo, Z., Zeng, L., Liu, K., Zheng, Y., Huang, X., Bai, R., Zhuang, L., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01173-1 · Cited by 187 · see citing works
Proteins that bind methylated DNA and human cancer: reading the wrong words
Lopez‐Serra, L., & Esteller, M. (2008) · British Journal of Cancer · doi:10.1038/sj.bjc.6604374 · Cited by 181 · see citing works
Maintaining differentiated cellular identity
Holmberg, J., & Perlmann, T. (2012) · Nature reviews genetics · doi:10.1038/nrg3209 · Cited by 161 · see citing works
A multi-landing pad DNA integration platform for mammalian cell engineering
Gaidukov, L., Wróblewska, L., Teague, B. P., Nelson, T., Zhang, X., Liu, Y., Jagtap, K., Mamo, S., Tseng, W. A., Lowe, A. L., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky216 · Cited by 161 · see citing works
Self-citationPolicarpi, C., Munafò, M., Tsagkris, S., Carlini, V., & Hackett, J. A. (2024) · Nature Genetics · doi:10.1038/s41588-024-01706-w · Cited by 152 · see citing works
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 149 · see citing works
Tracing dynamic changes of DNA methylation at single cell resolution
Stelzer, Y., Shivalila, C. S., Soldner, F., Markoulaki, S., & Jaenisch, R. (2015) · Cell · doi:10.1016/j.cell.2015.08.046 · Cited by 141 · see citing works
TET1 is a maintenance DNA demethylase that prevents methylation spreading in differentiated cells
Jin, C., Lu, Y., Jelı́nek, J., Liang, S., Estecio, M. R., Barton, M. C., & Issa, J. J. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku372 · Cited by 130 · see citing works
Methylation and epigenetic fidelity
Riggs, A. D., & Xiong, Z. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307781100 · Cited by 121 · see citing works
Structural and Functional Coordination of DNA and Histone MethylationPreprint
Cheng, X. (2014) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a018747 · Cited by 119 · see citing works
Direct readout of heterochromatic H3K9me3 regulates DNMT1-mediated maintenance DNA methylation
Ren, W., Fan, H., Grimm, S. A., Guo, Y., Kim, J. J., Yin, J., Li, L., Petell, C. J., Tan, X.-F., Zhang, Z., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2009316117 · Cited by 118 · see citing works
Vecchio, D. D., & Murray, R. M. (2014) · Princeton University Press eBooks · doi:10.23943/princeton/9780691161532.001.0001 · Cited by 104 · see citing works
Brown, D. A., Cerbo, V. D., Feldmann, A., Ahn, J., Ito, S., Blackledge, N. P., Nakayama, M., McClellan, M. J., Dimitrova, E., Turberfield, A. H., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.08.030 · Cited by 98 · see citing works
Flow cytometry of fluorescent proteins
Telford, W. G., Hawley, T. S., Subach, F. V., Verkhusha, V. V., & Hawley, R. G. (2012) · Methods · doi:10.1016/j.ymeth.2012.01.003 · Cited by 92 · see citing works
Systematic Transfer of Prokaryotic Sensors and Circuits to Mammalian Cells
Stanton, B. C., Siciliano, V., Ghodasara, A., Wroblewska, L., Clancy, K., Trefzer, A., Chesnut, J., Weiss, R., & Voigt, C. A. (2014) · ACS Synthetic Biology · doi:10.1021/sb5002856 · Cited by 88 · see citing works
Self-citationChromatin and transcriptional regulation by reversible RNA methylation
Wei, J., & He, C. (2021) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2020.11.005 · Cited by 63 · see citing works
Lim, Y. C., Li, J., Ni, Y., Liang, Q. H., Zhang, J., Yeo, G. S., Lyu, J., Jin, S., & Ding, C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0181155 · Cited by 60 · see citing works
A ‘poly-transfection’ method for rapid, one-pot characterization and optimization of genetic systems
Gam, J. J., DiAndreth, B., Jones, R. D., Huh, J. H., & Weiss, R. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz623 · Cited by 56 · see citing works
Self-citationJusiak, B., Jagtap, K., Gaidukov, L., Duportet, X., Bandara, K., Chu, J., Zhang, L., Weiss, R., & Lu, T. K. (2019) · ACS Synthetic Biology · doi:10.1021/acssynbio.8b00089 · Cited by 51 · see citing works
Self-citationUpadhyay, A. K., Horton, J. R., Zhang, X., & Cheng, X. (2011) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2011.08.003 · Cited by 46 · see citing works
Epigenetic cell memory: The gene’s inner chromatin modification circuit
Bruno, S., Williams, R. J., & Vecchio, D. D. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009961 · Cited by 45 · see citing works
Self-citationZhuang, A., Gu, X., Ge, T., Wang, S., Ge, S., Chai, P., Jia, R., & Fan, X. (2023) · 癌症：英文版 · doi:10.1002/cac2.12471 · Cited by 39 · see citing works
Epigenetic Gene Expression and Regulation
(2015) · Elsevier eBooks · doi:10.1016/c2013-0-14005-6 · Cited by 39 · see citing works
Protection against telomeric position effects by the chicken cHS4 β-globin insulator
Rincón‐Arano, H., Furlan-Magaril, M., & Targa, F. R. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704999104 · Cited by 36 · see citing works
Saunderson, E. A., Encabo, H. H., Devis, J., Rouault‐Pierre, K., Piganeau, M., Bell, C. G., Gribben, J. G., Bonnet, D. A., & Ficz, G. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2300224120 · Cited by 30 · see citing works
Dynamics of Epigenetic Regulation at the Single-Cell Level
Bintu, L. (2016) · Biophysical Journal · doi:10.1016/j.bpj.2015.11.1704 · Cited by 26 · see citing works
Uchida, N., Hanawa, H., Yamamoto, M., & Shimada, T. (2013) · Human Gene Therapy Methods · doi:10.1089/hgtb.2012.152 · Cited by 24 · see citing works
Distinct silencer states generate epigenetic states of heterochromatin
Saxton, D. S., & Rine, J. (2022) · Molecular Cell · doi:10.1016/j.molcel.2022.08.002 · Cited by 20 · see citing works
Köhler, A., Haußer, J., Harsch, A., Bernhardt, S., Häußermann, L., Brenner, L.-M., Lungu, C., Olayioye, M. A., Bashtrykov, P., & Jeltsch, A. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100739 · Cited by 8 · see citing works
Model reduction and stochastic analysis of the histone modification circuit
Bruno, S., Williams, R. J., & Vecchio, D. D. (2022) · European Control Conference (ECC) · doi:10.23919/ecc55457.2022.9838047 · Cited by 5 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Epigenetic memory: The role of the crosstalk between histone modifications and DNA methylation
Vecchio, D. D. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.08.034 · Cited by 11 · see citing works
Guerra-Resendez, R. S., Lydon, S. L., Ma, A. J., Bedford, G. C., Reed, D. R., Kim, S. H., Terán, E. R., Nishiguchi, T., Escobar, M., DiNardo, A. R., et al. (2025) · ACS Synthetic Biology · doi:10.1021/acssynbio.4c00569 · Cited by 8 · see citing works
Trainable computation in molecular networksPreprint
Trifonova, K., Falk, M. J., Rouches, M. N., Vaikuntanathan, S., Elowitz, M. B., & Murugan, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.28.696421 · Cited by 7 · see citing works
Conceptualization of memory within the framework of cognitive systems theory
Gribkov, A. A., & Zelenskii, A. A. (2025) · Философская мысль · doi:10.25136/2409-8728.2025.11.76544 · Cited by 1 · see citing works
A computational framework for epigenetic plasticity in memory
Delamare, G., Wagle, S., Gräff, J., & Claudia Clopath, A. (2026) · Brain · doi:10.1093/brain/awag094 · Cited by 1 · see citing works
Epigenetics of Genes Displaying High and Preferential Expression in Myoblasts
Ehrlich, K. C., Lacey, M. R., Pradhan, S., & Ehrlich, M. (2026) · Epigenomes · doi:10.3390/epigenomes10010020 · Cited by 1 · see citing works
Epigenetic Gene Networks Governing Immune State Transitions Across the Lifespan
Al-Ewaidat, O. A., & Naffaa, M. M. (2026) · Immunology · doi:10.1111/imm.70161 · Cited by 2 · see citing works
Reversing transgene silencing via targeted chromatin editingPreprint
Salibi, E., Palacios, S., lu, E. E. A., Weiss, R., Schlaeger, T. M., Collins, J. J., & Vecchio, D. D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.28.685244 · Cited by 1 · see citing works
Self-citationA Physics-based Model Reveals Mechanisms of Epigenetic MemoryPreprint
Navarro, E. J., Poole, W., Lismer, A., Qu, J., Kafetzopoulos, I., Parry, A., Ijaz, J., Santambrogio, A., Spangler, R., Martín-Zamora, F. M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.16.699330
Stochastic modeling of epigenetic memory
Bruno, S., & Vecchio, D. D. (2026) · npj Systems Biology and Applications · doi:10.1038/s41540-026-00664-9
Self-citationGraded versus ON/OFF control in quantitative gene expression and epigenetic memory
Dean, C., & Howard, M. (2026) · The EMBO Journal · doi:10.1038/s44318-026-00750-y
Targeting DNA Methylation: New Paradigms and the Advent of Gene-Selective Tools
Gilbert, J., & Calzaferri, F. (2026) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.6c00218
Written in development and lost in ageing: the grammar of cellular identity
Yücel, A. D., Molière, A., & Gladyshev, V. N. (2026) · Nature · doi:10.1038/s41586-026-10955-0
- Authors
- Palacios, S., Bruno, S., Weiss, R., Salibi, E., Kane, A., Ilia, K., & Del Vecchio, D.
- Affiliations
- Massachusetts Institute of Technology (US)
- Dana-Farber Cancer Institute (US)
- Venue
- Cell Genomics
- Publisher
- openRxiv
- Published
- 2024-02-16
- Volume
- 5
- Issue
- 11
- Pages
- 100985-100985
- ISSN
- 2666-979X (ISSN-L)
- OpenAlex
- W4414111079
- Cited by
- 13
- References
- 88
- Citations by year
- 2026: 8 · 2025: 5
- FWCI
- 3.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-nd
- www.biorxiv.org/about/FAQ#license (vor)
- Locations
- Cell Genomics (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation (2027949)
- U.S. Department of Defense
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
- 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 › Gene Regulatory Network Analysis
- Keywords
- chromatin modification, DNA methylation, histone modifications, positive feedback, synthetic biology
- MeSH terms
- Gene Editing, Epigenetic Memory, Chromatin, Histones, Humans, DNA Methylation, Histone Code, 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
