Emergence of activation or repression in transcriptional control under a fixed molecular context
Open accessPreprint — published as 10.1073/pnas.2413715122
Abstract
For decades, studies have noted that transcription factors (TFs) can behave as either activators or repressors of different target genes. More recently, evidence suggests TFs can act on transcription simultaneously in positive and negative ways. Here we use biophysical models of gene regulation to define, conceptualize and explore these two aspects of TF action: “duality”, where TFs can be overall both activators and repressors at the level of the transcriptional response, and “coherent and incoherent” modes of regulation, where TFs act mechanistically on a given target gene either as an activator or a repressor (coherent) or as both (incoherent). For incoherent TFs, the overall response depends on three kinds of features: the TF’s mechanistic effects, the dynamics and effects of additional regulatory molecules or the transcriptional machinery, and the occupancy of the TF on DNA. Therefore, activation or repression can be tuned by just the TF-DNA binding affinity, or the number of TF binding sites, given an otherwise fixed molecular context. Moreover, incoherent TFs can cause non-monotonic transcriptional responses, increasing over a certain concentration range and decreasing outside the range, and we clarify the relationship between non-monotonicity and common assumptions of gene regulation models. Using the mammalian SP1 as a case study and well controlled, synthetically designed target sequences, we find experimental evidence for incoherent action and activation, repression or non-monotonicity tuned by affinity. Our work highlights the importance of moving from a TF-centric view to a systems view when reasoning about transcriptional control.
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These observations can quantitatively be explained by a biophysical model where a TF activates a rate-limiting step in transcriptional activation and represses other steps, such that a second step becomes rate limiting once a certain TF occupancy is exceeded.
“These observations can quantitatively be explained by a biophysical model46 where a TF activates a rate-limiting step in transcriptional activation and represses other steps, such that a second step becomes rate limiting once a certain TF occupancy is exceeded (Figures 3H and 3I; see STAR Methods, section biophysical models).”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [46]
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Experimental — accuracy not yet measuredUnder common biophysical assumptions, increases in motif number and affinity lead to higher TF occupancy.
“Under common biophysical assumptions, increases in these two quantities lead to higher TF occupancy.46,47”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [46]
Non-monotonous effects of a transcription factor with respect to binding site affinity can arise when gene regulation is limited at multiple steps and the transcription factor acts incoherently on those steps, promoting transcription at some steps and hindering it at others.
“In that work, we show that non-monotonous effects of a TF with respect to binding site affinity can arise when gene regulation is limited at multiple steps, and a TF acts incoherently on those steps, such that it acts on one or more steps to promote transcription, and on other steps to hinder it.”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [46]
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Cites
How eukaryotic transcriptional activators work
Ptashne, M. (1988) · Nature · doi:10.1038/335683a0 · Cited by 1,828 · see citing works
The Phosphorylation Status of Nuclear NF-ΚB Determines Its Association with CBP/p300 or HDAC-1
Zhong, H., May, M. J., Jimi, E., & Ghosh, S. (2002) · Molecular Cell · doi:10.1016/s1097-2765(02)00477-x · Cited by 930 · see citing works
Kulakovskiy, I. V., Vorontsov, I. E., Yevshin, I., Sharipov, R., Fedorova, A. D., Rumynskiy, E. I., Medvedeva, Y. A., Magana-Mora, A., Bajić, V. B., Papatsenko, D., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1106 · Cited by 921 · see citing works
Getting up to speed with transcription elongation by RNA polymerase II
Jonkers, I., & Lis, J. T. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3953 · Cited by 876 · see citing works
Transcriptional regulation by the numbers: models
Bintu, L., Buchler, N. E. G., García, H. G., Gerland, U., Terence Hwa, B., Kondev, J., & Phillips, R. (2005) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2005.02.007 · Cited by 784 · see citing works
Quantitative model for gene regulation by lambda phage repressor.
Ackers, G. K., Johnson, A. D., & Shea, M. A. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.4.1129 · Cited by 590 · see citing works
Glucocorticoid receptor control of transcription: precision and plasticity via allostery
Weikum, E. R., Knuesel, M. T., Ortlund, E. A., & Yamamoto, K. R. (2017) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.152 · Cited by 533 · see citing works
Ross, S. E., Best, J. L., Zon, L. I., & Gill, G. (2002) · Molecular Cell · doi:10.1016/s1097-2765(02)00682-2 · Cited by 365 · see citing works
Low Affinity Binding Site Clusters Confer Hox Specificity and Regulatory Robustness
Crocker, J., Abe, N., Rinaldi, L., McGregor, A. P., Frankel, N., Wang, S., Alsawadi, A., Valenti, P., Plaza, S., Payre, F., et al. (2015) · Cell · doi:10.1016/j.cell.2014.11.041 · Cited by 363 · see citing works
Nucleosome-mediated cooperativity between transcription factors
Mirny, L. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0913805107 · Cited by 349 · see citing works
MYC protein interactors in gene transcription and cancer
Lourenco, C., Resetca, D., Redel, C., Lin, P., MacDonald, A. S., Ciaccio, R., Kenney, T. M. G., Wei, Y., Andrews, D. W., Sunnerhagen, M., et al. (2021) · Nature reviews. Cancer · doi:10.1038/s41568-021-00367-9 · Cited by 341 · see citing works
Suboptimization of developmental enhancers
Farley, E. K., Olson, K. M., Zhang, W., Brandt, A. J., Rokhsar, D. S., & Levine, M. S. (2015) · Science · doi:10.1126/science.aac6948 · Cited by 319 · see citing works
Nucleosome-bound SOX2 and SOX11 structures elucidate pioneer factor function
Dodonova, S. O., Zhu, F., Dienemann, C., Taipale, J., & Cramer, P. (2020) · Nature · doi:10.1038/s41586-020-2195-y · Cited by 265 · see citing works
Ben-Shushan, E., Thompson, J. R., Gudas, L. J., & Bergman, Y. (1998) · Molecular and Cellular Biology · doi:10.1128/mcb.18.4.1866 · Cited by 235 · see citing works
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 216 · see citing works
The Why of YY1: Mechanisms of Transcriptional Regulation by Yin Yang 1
Verheul, T. C. J., van Hijfte, L., Perenthaler, E., & Barakat, T. S. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.592164 · Cited by 197 · see citing works
Information integration and energy expenditure in gene regulation
Estrada, J., Wong, F., DePace, A. H., & Gunawardena, J. (2016) · Cell · doi:10.1016/j.cell.2016.06.012 · Cited by 168 · see citing works
Self-citationSauer, F., & Jäckle, H. (1991) · Nature · doi:10.1038/353563a0 · Cited by 163 · see citing works
Regulation of transcription: from lambda to eukaryotes
Ptashne, M. (2005) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2005.04.003 · Cited by 158 · see citing works
Context-dependent Transcriptional Regulation
Fry, C. J., & Farnham, P. (1999) · Journal of Biological Chemistry · doi:10.1074/jbc.274.42.29583 · Cited by 157 · see citing works
Conversion of Dorsal from an activator to a repressor by the global corepressor Groucho
Dubnicoff, T., Valentine, S. A., Chen, G., Shi, T., Lengyel, J. A., Paroush, Z., & Courey, A. J. (1997) · Genes & Development · doi:10.1101/gad.11.22.2952 · Cited by 155 · see citing works
High-Throughput Discovery and Characterization of Human Transcriptional Effectors
Tycko, J., DelRosso, N. V., Hess, G. T., Aradhana, Banerjee, A., Mukund, A. X., Van, M. V., Ego, B. K., Yao, D., Spees, K., et al. (2020) · Cell · doi:10.1016/j.cell.2020.11.024 · Cited by 152 · see citing works
A Linear Framework for Time-Scale Separation in Nonlinear Biochemical Systems
Gunawardena, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036321 · Cited by 147 · see citing works
Self-citationlentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements
Gordon, M. G., Inoue, F., Martin, B., Schubach, M., Agarwal, V., Whalen, S., Feng, S., Zhao, J., Ashuach, T., Ziffra, R. S., et al. (2020) · Nature Protocols · doi:10.1038/s41596-020-0333-5 · Cited by 144 · see citing works
Control of transcription by Krüppel through interactions with TFIIB and TFIIEβ
Sauer, F., Fondell, J. D., Ohkuma, Y., Roeder, R. G., & Jäckle, H. (1995) · Nature · doi:10.1038/375162a0 · Cited by 132 · see citing works
Large-scale mapping and mutagenesis of human transcriptional effector domains
DelRosso, N., Tycko, J., Suzuki, P., Andrews, C., Aradhana, Mukund, A., Liongson, I., Ludwig, C., Spees, K., Fordyce, P., et al. (2023) · Nature · doi:10.1038/s41586-023-05906-y · Cited by 130 · see citing works
Laplacian Dynamics on General Graphs
Mirzaev, I., & Gunawardena, J. (2013) · Bulletin of Mathematical Biology · doi:10.1007/s11538-013-9884-8 · Cited by 123 · see citing works
Self-citationLow-affinity transcription factor binding sites shape morphogen responses and enhancer evolution
Ramos, A. I., & Barolo, S. (2013) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2013.0018 · Cited by 116 · see citing works
Valentine, S. A., Chen, G., Shandala, T., Fernandez, J., Mische, S., Saint, R., & Courey, A. J. (1998) · Molecular and Cellular Biology · doi:10.1128/mcb.18.11.6584 · Cited by 114 · see citing works
Dimerization and the control of transcription by Krüppel
Sauer, F., & Jäckle, H. (1993) · Nature · doi:10.1038/364454a0 · Cited by 108 · see citing works
The Transcriptional Specificity of NF-κB Dimers Is Coded within the κB DNA Response Elements
Wang, V. Y., Huang, W. J. M., Asagiri, M., Spann, N. J., Hoffmann, A., Glass, C. K., & Ghosh, G. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.08.042 · Cited by 107 · see citing works
Kirov, N., Zhelnin, L., Shah, J., & Rushlow, C. A. (1993) · The EMBO Journal · doi:10.1002/j.1460-2075.1993.tb05988.x · Cited by 101 · see citing works
Swinstead, E. E., Paakinaho, V., Presman, D. M., & Hager, G. L. (2016) · BioEssays · doi:10.1002/bies.201600137 · Cited by 100 · see citing works
Incorporating Nucleosomes into Thermodynamic Models of Transcription Regulation
Raveh-Sadka, T., Levo, M., & Segal, E. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02008-7_15 · Cited by 97 · see citing works
A Simple Grammar Defines Activating and Repressing cis-Regulatory Elements in Photoreceptors
White, M. A., Kwasnieski, J. C., Myers, C. A., Shen, S. Q., Corbo, J. C., & Cohen, B. A. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.09.066 · Cited by 87 · see citing works
Iwafuchi, M., Cuesta, I., Donahue, G., Takenaka, N., Osipovich, A. B., Magnuson, M. A., Röder, H., Seeholzer, S. H., Santisteban, P., & Zaret, K. S. (2020) · Nature Genetics · doi:10.1038/s41588-020-0591-8 · Cited by 82 · see citing works
The same dorsal binding site mediates both activation and repression in a context‐dependent manner.
Pan, D., & Courey, A. J. (1992) · The EMBO Journal · doi:10.1002/j.1460-2075.1992.tb05235.x · Cited by 79 · see citing works
Transcription factors: bound to activate or repress
Latchman, D. S. (2001) · Trends in Biochemical Sciences · doi:10.1016/s0968-0004(01)01812-6 · Cited by 74 · see citing works
Pioneer-like factor GAF cooperates with PBAP (SWI/SNF) and NURF (ISWI) to regulate transcriptionPreprint
Judd, J., Duarte, F. M., & Lis, J. T. (2020) · Genes & Development · doi:10.1101/gad.341768.120 · Cited by 71 · see citing works
Park, J., Estrada, J., Johnson, G. L., Vincent, B. J., Ricci-Tam, C., Bragdon, M. D. J., Shulgina, Y., Cha, A., Wunderlich, Z., Gunawardena, J., et al. (2018) · bioRxiv · doi:10.7554/elife.41266 · Cited by 68 · see citing works
Self-citationGene Regulation in and out of Equilibrium
Wong, F. J., & Gunawardena, J. (2020) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-121219-081542 · Cited by 65 · see citing works
Self-citationLi, Z., Zhao, J., Tikhanovich, I., Kuravi, S., Helzberg, J. H., Dorko, K., Roberts, B., Kumer, S. C., & Weinman, S. A. (2015) · Cell Death and Differentiation · doi:10.1038/cdd.2015.125 · Cited by 61 · see citing works
Collapse of the hepatic gene regulatory network in the absence of FoxA factors
Reizel, Y., Morgan, A., Gao, L., Lan, Y., Manduchi, E., Waite, E. L., Wang, A. W., Wells, A., & Kaestner, K. H. (2020) · Genes & Development · doi:10.1101/gad.337691.120 · Cited by 60 · see citing works
Katan‐Khaykovich, Y., Agami, R., & Shaul, Y. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.18.3621 · Cited by 56 · see citing works
Transcriptional squelching re-examined
Natesan, S., Rivera, V. M., Molinari, E., & Gilman, M. Z. (1997) · Nature · doi:10.1038/37019 · Cited by 56 · see citing works
Crossing the line between activation and repression
Ma, J. (2004) · Trends in Genetics · doi:10.1016/j.tig.2004.11.004 · Cited by 55 · see citing works
Dual-function transcription factors and their entourage
Boyle, P. M., & Després, C. (2010) · Plant Signaling & Behavior · doi:10.4161/psb.5.6.11570 · Cited by 46 · see citing works
Zhao, C., York, A. J., Yang, F., Forsthoefel, D. J., Davé, V., Fu, D., Zhang, D., Corado, M., Small, S., Seeger, M. A., et al. (2002) · Development · doi:10.1242/dev.129.7.1669 · Cited by 43 · see citing works
Mukund, A. X., Tycko, J., Allen, S. J., Robinson, S. A., Andrews, C. J., Sinha, J., Ludwig, C., Spees, K. K., Bassik, M. C., & Bintu, L. (2023) · Cell Systems · doi:10.1016/j.cels.2023.07.001 · Cited by 40 · see citing works
Negative reciprocity, not ordered assembly, underlies the interaction of Sox2 and Oct4 on DNA
Biddle, J., Nguyen, M., & Gunawardena, J. (2019) · eLife · doi:10.7554/elife.41017 · Cited by 38 · see citing works
Self-citationTaheri, F., & Bazán, H. E. P. (2007) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.06-1008 · Cited by 34 · see citing works
Tamura, I., Maekawa, R., Jozaki, K., Ohkawa, Y., Takagi, H., Doi‐Tanaka, Y., Shirafuta, Y., Mihara, Y., Taketani, T., Sato, S., et al. (2020) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2020.111085 · Cited by 31 · see citing works
Rosée, A. L., Häder, T., Wainwright, D., Sauer, F., & Jäckle, H. (1999) · Mechanisms of Development · doi:10.1016/s0925-4773(99)00219-1 · Cited by 31 · see citing works
Martinez-Corral, R., Park, M., Biette, K. M., Friedrich, D., Scholes, C., Khalil, A. S., Gunawardena, J., & DePace, A. H. (2023) · Cell Systems · doi:10.1016/j.cels.2023.02.003 · Cited by 29 · see citing works
Self-citationNonequilibrium models of optimal enhancer function
Grah, R., Zoller, B., & Tkačik, G. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2006731117 · Cited by 26 · see citing works
Sp1 Mediates the Constitutive Expression and Repression of the PDSS2 Gene in Lung Cancer Cells
Hu, L., Chen, Q., Wang, S., Zhang, N., Meng, P., Liu, T., & Bu, Y. (2019) · Genes · doi:10.3390/genes10120977 · Cited by 25 · see citing works
Cellular Toxicity Induced by SRF-Mediated Transcriptional Squelching
Lin, H., McGrath, J. P., Wang, P., & Lee, T. (2006) · Toxicological Sciences · doi:10.1093/toxsci/kfl172 · Cited by 22 · see citing works
Accelerated evolution of a minimal 63–amino acid dual transcription factor
Brödel, A. K., Rodrigues, R., Jaramillo, A., & Isalan, M. (2020) · Science Advances · doi:10.1126/sciadv.aba2728 · Cited by 21 · see citing works
Quantifying the regulatory role of individual transcription factors in Escherichia coli
Guharajan, S., Chhabra, S., Parisutham, V., & Brewster, R. C. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109952 · Cited by 18 · see citing works
Barr, K. A., & Reinitz, J. (2017) · PLOS ONE · doi:10.1371/journal.pone.0180861 · Cited by 17 · see citing works
Fu, D. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki691 · Cited by 17 · see citing works
When Activators Repress and Repressors Activate: A Qualitative Analysis of the Shea–Ackers Model
Gedeon, T., Mischaikow, K., Patterson, K., & Traldi, E. (2008) · Bulletin of Mathematical Biology · doi:10.1007/s11538-008-9313-6 · Cited by 16 · see citing works
Enhancer Sequences Influence the Role of the Amino-Terminal Domain of Bicoid in Transcription
Fu, D., Zhao, C., & Ma, J. (2003) · Molecular and Cellular Biology · doi:10.1128/mcb.23.13.4439-4448.2003 · Cited by 16 · see citing works
Fauquenoy, S., Robette, G., Kula, A., Vanhulle, C., Bouchat, S., Delacourt, N., Rodari, A., Marban, C., Schwartz, C., Burny, A., et al. (2017) · Scientific Reports · doi:10.1038/srep43221 · Cited by 13 · see citing works
Transcriptional activators in the early Drosophila embryo perform different kinetic roles
Harden, T. T., Vincent, B. J., & DePace, A. H. (2023) · Cell Systems · doi:10.1016/j.cels.2023.03.006 · Cited by 10 · see citing works
Self-citationEstrada, J., Andrew, N., Gibson, D., Chang, F. S., Gnad, F., & Gunawardena, J. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004995 · Cited by 9 · see citing works
Self-citationRegulatory properties of transcription factors with diverse mechanistic function
Ali, M. Z., Guharajan, S., Parisutham, V., & Brewster, R. C. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012194 · Cited by 7 · see citing works
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Research works printed but not linked: 2
- [36]Mahdavi Sara “ Flexibility and sensitivity in gene regulation out of equilibrium”. en. In: bioRxiv (2023), p. 2023.04.11.536490. PMC11573582 39499638
- [58]Pya Natalya and Wood Simon N. “ Shape constrained additive models”. In: Stat. Comput. 25. 3 (2015), pp. 543– 559.
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Design principles of cell-state-specific enhancers in hematopoiesis
Frömel, R., Rühle, J., Bernal Martinez, A., Szu-Tu, C., Pacheco Pastor, F., Martinez-Corral, R., & Velten, L. (2025) · Cell · doi:10.1016/j.cell.2025.04.017 · Cited by 29 · see citing works
Self-citation
- Authors
- Martinez-Corral, R., Friedrich, D., Frömel, R., Velten, L., Gunawardena, J., & DePace, A. H.
- Affiliations
- Harvard University (US)
- Universitat Pompeu Fabra (ES)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Martinez-Corral, Rosa
- DePace, Angela H.
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- openRxiv
- Published
- 2024-06-02
- Volume
- 122
- Issue
- 39
- Pages
- e2413715122-e2413715122
- ISSN
- 0027-8424 (ISSN-L)
- PMC
- PMC11160767
- OpenAlex
- W4414384778
- Cited by
- 18
- References
- 67
- Citations by year
- 2026: 12 · 2025: 6
- FWCI
- 5.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by-nc-nd)
- PubMed Central (submittedVersion, cc-by-nc)
- Funders
- National Science Foundation (1715184, CAREER, 1452557)
- Howard Hughes Medical Institute
- European Molecular Biology Organization (ALTF683-2019)
- European Molecular Biology Laboratory
- Ministerio de Ciencia, Innovación y Universidades (PID2019‐108082GA‐I00, PID2022-142210NA-I00, PID2019, CEX2020-001049-S MCIN/AEI /10.13039/501100011033, RYC2021-033860-I, .13039/501100011033, 501100011033)
- Centres de Recerca de Catalunya (501100011033)
- European Commission (13039/501100011033, 501100011033)
- Generalitat de Catalunya (501100011033, PID2019)
- Ministerio de Ciencia e Innovación (MCIN/AEI/10, .13039/501100011033, RYC2021-033860-I, / AEI/10, PID2019, 501100011033, CEX2020-001049-S, RYC2021, PID2022)
- National Institutes of Health
- Agencia Estatal de Investigación (501100011033, 13039, .13039/501100011033, AEI/10, PID2019)
- National Institute of General Medical Sciences (R01GM122928)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- Sp1, transcriptional regulation
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