Multiplex enhancer-reporter assays uncover unsophisticated TP53 enhancer logic
Open accessAbstract
Transcription factors regulate their target genes by binding to regulatory regions in the genome. Although the binding preferences of TP53 are known, it remains unclear what distinguishes functional enhancers from nonfunctional binding. In addition, the genome is scattered with recognition sequences that remain unoccupied. Using two complementary techniques of multiplex enhancer-reporter assays, we discovered that functional enhancers could be discriminated from nonfunctional binding events by the occurrence of a single TP53 canonical motif. By combining machine learning with a meta-analysis of TP53 ChIP-seq data sets, we identified a core set of more than 1000 responsive enhancers in the human genome. This TP53 cistrome is invariably used between cell types and experimental conditions, whereas differences among experiments can be attributed to indirect nonfunctional binding events. Our data suggest that TP53 enhancers represent a class of unsophisticated cell-autonomous enhancers containing a single TP53 binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors.
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A comparison of binding studies shows that functional p53 binding is independent of cell type and treatment.
“Moreover, a comparison of binding studies shows that functional p53 binding is independent of cell type and treatment.19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
Genome-wide data do not support promoter-specific activities of p53, but instead suggest unsophisticated p53 binding.
“Genome-wide data, however, do not support promoter-specific activities of p53, but instead suggest unsophisticated p53 binding.19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
A recent comparison of multiple genome-wide p53 binding studies showed that spacers and half-sites have no role in functional p53 binding.
“A recent comparison of multiple genome-wide p53 binding studies, however, showed that spacers and half-sites have no role in functional p53 binding.19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
Gene downregulation through distal enhancer interference by p53 binding is not supported by data from humans.
“but is not supported by data from humans.18, 19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
The current model describes p53 solely as a transcriptional activator and not as a repressor.
“The current model describes p53 solely as a transcriptional activator and not as repressor,53 and is supported by multiple genome-wide analyses.18, 19, 23, 24, 89”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
Recent approaches to predict functional sites that lead to target gene activation rely on ranking p53 binding sites based on multiple genome-wide data sets.
“To predict functional sites that lead to target gene activation, recent approaches now rely on ranking p53 binding sites based on multiple genome-wide data sets.18, 19, 56”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
p53 binds target genes independent of cell type and treatment.
“recent findings indicate that p53 binds target genes independent of cell type and treatment.19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
Functional p53 binding sites consist of two decameric half-sites, and likely do not contain spacers in between.
“Functional p53 binding sites consist of two decameric half-sites, and likely do not contain spacers in between. 19, 56”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
Noncanonical binding sites, including half-sites, appear to be non-functional.
“Noncanonical binding sites, including half-sites, appear to be non-functional. 19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
Functional p53 binding sites are independent of cell type and treatment.
“Functional p53 binding sites are independent of cell type and treatment. 19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
P53 mostly acts alone to activate target genes, and does not depend on cofactors binding to the same promoter.
“P53 mostly acts alone to activate target genes, and does not depend on cofactors binding to the same promoter. 19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [19]
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Cook, J. L., Rn, R., Jf, G., Fe, F., Dy, C., & Alam, J. (1995) · PubMed · Cited by 16 · see citing works
Fixated on fixation - using ChIP to interrogate the dynamics of chromatin interactions
Keren, L., & Segal, E. (2013) · Genome biology · doi:10.1186/gb4139 · Cited by 3 · see citing works
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The multiple mechanisms that regulate p53 activity and cell fate
Hafner, A., Bulyk, M. L., Jambhekar, A., & Lahav, G. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0110-x · Cited by 1,129 · see citing works
Census and evaluation of p53 target genes
Fischer, M. (2017) · Oncogene · doi:10.1038/onc.2016.502 · Cited by 971 · see citing works
Jacobs, J., Atkins, M., Davie, K., Imrichova, H., Romanelli, L., Christiaens, V., Hulselmans, G., Potier, D., Wouters, J., Taskiran, I. I., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0140-x · Cited by 155 · see citing works
Self-citationBravo González-Blas, C., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2024) · Nature Cell Biology · doi:10.1038/s41556-023-01316-4 · Cited by 85 · see citing works
“To assess whether the predicted enhancers are active, we performed a massively parallel reporter assay (MPRA) using a previously published enhancer-barcoding strategy 36 (Fig.”
Self-citationEnhancer grammar of liver cell types and hepatocyte zonation states
González-Blas, C. B., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2022) · doi:10.1101/2022.12.08.519575 · Cited by 5 · see citing works
Self-citation
- Authors
- Verfaillie, A., Svetlichnyy, D., Imrichova, H., Davie, K., Fiers, M., Kalender Atak, Z., Hulselmans, G., Christiaens, V., & Aerts, S.
- Affiliations
- KU Leuven (BE)
- Corresponding author
- Aerts, Stein
- ORCID
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2016-05-18
- Volume
- 26
- Issue
- 7
- Pages
- 882-895
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- PMC
- PMC4937571
- OpenAlex
- W2408306345
- Cited by
- 82
- References
- 86
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 11 · 2023: 7 · 2022: 7 · 2021: 9 · 2020: 7 · 2019: 9 · 2018: 7 · 2017: 12 · 2016: 2
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lirias (submittedVersion, cc-by)
- HighWire Press Open Archive (submittedVersion)
- Funders
- The Research Foundation - Flanders
- FWO (G.0640.13, G.0791.14)
- Special Research Fund (BOF) KU Leuven (PF/10/016, OT/13/103)
- Foundation Against Cancer (2010-154, 2012-F2)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- TP53, enhancers, transcription factor binding, cistrome, transcriptional regulation, machine learning
- MeSH terms
- Binding Sites, Biological Assay, Enhancer Elements, Genetic, Humans, Protein Binding, Transcriptional Activation, Tumor Suppressor Protein p53, Genes, Reporter, MCF-7 Cells
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.
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