The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Functional evolution of the p53 regulatory network through its target response elements
Abstract
Transcriptional network evolution is central to the development of complex biological systems. Networks can evolve through variation of master regulators and/or by changes in regulation of genes within networks. To gain insight into meaningful evolutionary differences in large networks, it is essential to address the functional consequences of sequence differences in response elements (REs) targeted by transcription factors. Using a combination of custom bioinformatics and multispecies alignment of promoter regions, we investigated the functional evolution of REs in terms of responsiveness to the sequence-specific transcription factor p53, a tumor suppressor and master regulator of stress responses. We identified REs orthologous to known p53 targets in human and rodent cells or alternatively REs related to the established p53 consensus. The orthologous REs were assigned p53 transactivation capabilities based on rules determined from model systems, and a functional heat map was developed to visually summarize conservation of sequence and relative level of responsiveness to p53 for 47 REs in 14 species. Individual REs exhibited marked differences in transactivation potentials and widespread evolutionary turnover. Functional differences were often not predicted from consensus sequence evaluations. Of the established human p53 REs analyzed, 91% had sequence conservation in at least one nonprimate species compared with 67.5% for functional conservation. Surprisingly, there was almost no conservation of functional REs for genes involved in DNA metabolism or repair between humans and rodents, suggesting important differences in p53 stress responses and cancer development.
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?
In the citing paper
“P53‐REs consist of 2 10‐base pair (bp) palindromic DNA segments with the consensus sequence of 5′‐Pu1Pu2Pu3C4(A/T)5(A/T)5′G4′Py3′Py2′Py1′‐3′ for each of the two half‐sites, where Pu and Py denote purine and pyrimidine bases, respectively [36, 37].”
From The TP53 tumor suppressor gene: From molecular biology to clinical investigations (2025) · cites this paper as [37]
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
Transcriptional activation by recruitment
Ptashne, M., & Gann, A. (1997) · Nature · doi:10.1038/386569a0 · Cited by 1,158
A Global Map of p53 Transcription-Factor Binding Sites in the Human Genome
Wei, C.-L., Wu, Q., Vega, V. B., Chiu, K. P., Ng, P., Zhang, T., Shahab, A., Yong, H. C., Fu, Y., Weng, Z., et al. (2006) · Cell · doi:10.1016/j.cell.2005.10.043 · Cited by 1,141
An Apolipoprotein Influencing Triglycerides in Humans and Mice Revealed by Comparative Sequencing
Pennacchio, L. A., Olivier, M., Hubacek, J. A., Cohen, J. C., Cox, D. R., Fruchart, J.-C., Krauss, R. M., & Rubin, E. M. (2001) · Science · doi:10.1126/science.1064852 · Cited by 921
Dermitzakis, E. T., & Clark, A. G. (2002) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a004169 · Cited by 463
p53 and DNA damage-inducible expression of the xeroderma pigmentosum group C gene
Adimoolam, S., & Ford, J. M. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.202485699 · Cited by 321
p53 Binds and Activates the Xeroderma Pigmentosum DDB2 Gene in Humans but Not Mice
Tan, T., & Chu, G. (2002) · Molecular and Cellular Biology · doi:10.1128/mcb.22.10.3247-3254.2002 · Cited by 167
Menendez, D., Inga, A., & Resnick, M. A. (2006) · Molecular and Cellular Biology · doi:10.1128/mcb.26.6.2297-2308.2006 · Cited by 81
Self-citation
Research works printed but not linked: 36
- 10.1016/j.cell.2005.10.042 · DOI · Paper page
- 10.1101/gad.831000 · DOI · Paper page
- 10.1038/nature02415 · DOI · Paper page
- 10.1073/pnas.95.26.15446 · DOI
- 10.1242/dev.00711 · DOI
- 10.1038/35000615 · DOI · Paper page
- 10.1073/pnas.0508103103 · DOI
- 10.1073/pnas.0501721102 · DOI
- 10.1073/pnas.1633803100 · DOI · Paper page
- 10.1128/MCB.22.24.8612-8625.2002 · DOI
- 10.4161/cc.4.8.1904 · DOI
- 10.1128/MCB.01742-06 · DOI
- 10.1073/pnas.012283399 · DOI · Paper page
- 10.1038/75556 · DOI · Paper page
- 10.1016/S0168-9525(02)02595-7 · DOI · Paper page
- 10.1016/j.febslet.2006.07.004 · DOI
- 10.1128/MCB.25.14.6077-6089.2005 · DOI
- 10.1016/j.molcel.2006.10.018 · DOI · Paper page
- 10.1128/MCB.19.2.1438 · DOI · Paper page
- 10.1016/S0092-8674(03)00308-8 · DOI · Paper page
- GC Das, CV Shivakumar, SD Todd Oncogene 10, 449–455 (1995).
- 10.1002/bies.950170611 · DOI
- 10.1006/bbrc.1996.0663 · DOI
- 10.1038/sj.neo.7900211 · DOI
- 10.1101/gr.2195604 · DOI
- 10.1371/journal.pbio.0020398 · DOI · Paper page
- 10.1371/journal.pbio.0030093 · DOI · Paper page
- 10.1186/gb-2004-5-9-r61 · DOI · Paper page
- 10.1016/j.mrrev.2003.06.002 · DOI
- 10.1371/journal.pgen.0030127 · DOI
- 10.1186/1471-2164-8-141 · DOI
- 10.1073/pnas.0404998101 · DOI
- 10.1093/hmg/ddi202 · DOI
- 10.1101/gr.1933104 · DOI · Paper page
- 10.1093/nar/gkg129 · DOI · Paper page
- 10.1093/nar/24.1.238 · DOI · Paper page
Cited by
The expanding universe of p53 targets
Menendez, D., Inga, A., & Resnick, M. A. (2009) · Nature Reviews Cancer · doi:10.1038/nrc2730 · Cited by 568
Self-citationA highly specific SpCas9 variant is identified by in vivo screening in yeast
Casini, A., Olivieri, M., Petris, G., Montagna, C., Reginato, G., Maule, G., Lorenzin, F., Prandi, D., Romanel, A., Demichelis, F., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4066 · Cited by 493
Self-citationRegulating tumor suppressor genes: post-translational modifications
Chen, L., Liu, S., & Tao, Y. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-0196-9 · Cited by 449
The Toll-like receptor gene family is integrated into human DNA damage and p53 networks
Menendez, D., Shatz, M., Azzam, K., Garantziotis, S., Fessler, M. B., & Resnick, M. A. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001360 · Cited by 148
Self-citationShatz, M., Menendez, D., & Resnick, M. A. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-4134 · Cited by 143
Self-citation
Metadata
- Authors
- Jegga, A. G., Inga, A., Menendez, D., Aronow, B. J., & Resnick, M. A.
- Affiliations
- *Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229-3039;
- Molecular Mutagenesis Unit, National Institute for Cancer Research, 16132 Genoa, Italy; and
- Laboratory Molecular Genetics, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2008-01-22
- Volume
- 105
- Issue
- 3
- Pages
- 944-949
- ISSN
- 0027-8424
- 1091-6490
- Cited by
- 63
- References
- 7
- Language
- en
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Functional evolution of the p53 regulatory network through its target response elements. https://app.cochat.ai/papers/10.1073/pnas.0704694105
- The paper
- Jegga, A. G., Inga, A., Menendez, D., Aronow, B. J., & Resnick, M. A. (2008). Functional evolution of the p53 regulatory network through its target response elements. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0704694105
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.