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[Preprint]. 2024 Sep 25:2024.09.24.614594.
doi: 10.1101/2024.09.24.614594.

p53motifDB: integration of genomic information and tumor suppressor p53 binding motifs

Gabriele Baniulyte  1 , Sawyer M Hicks  1 , Morgan A Sammons  1
Affiliations

p53motifDB: integration of genomic information and tumor suppressor p53 binding motifs

Gabriele Baniulyte et al. bioRxiv. .

Abstract

The tumor suppressor gene TP53 encodes the DNA binding transcription factor p53 and is one of the most commonly mutated genes in human cancer. Tumor suppressor activity requires binding of p53 to its DNA response elements and subsequent transcriptional activation of a diverse set of target genes. Despite decades of close study, the logic underlying p53 interactions with its numerous potential genomic binding sites and target genes is not yet fully understood. Here, we present a database of DNA and chromatin-based information focused on putative p53 binding sites in the human genome to allow users to generate and test new hypotheses related to p53 activity in the genome. Users can query genomic locations based on experimentally observed p53 binding, regulatory element activity, genetic variation, evolutionary conservation, chromatin modification state, and chromatin structure. We present multiple use cases demonstrating the utility of this database for generating novel biological hypotheses, such as chromatin-based determinants of p53 binding and potential cell type-specific p53 activity. All database information is also available as a precompiled sqlite database for use in local analysis or as a Shiny web application.

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Conflict of interest statement

CONFLICT OF INTERESTS STATEMENTS The Authors declare no conflicts of interest.

Figures

Figure 1:
Figure 1:. Selection and characteristics of p53 response elements (p53RE) in the hg38 human genome assembly.
A) The number of p53RE identified using nucleotide binding preferences from HOMER (ChIP-seq-derived) compared to JASPAR (in vitro SELEX-derived). The distribution of method-specific scoring for p53RE either found with both methods or with only a single method for B) HOMER or C) JASPAR. D) A seqLogo representation of nucleotide preferences for p53RE identified from both HOMER and JASPAR binding preferences. seqLogo representation of nucleotide preferences for E) HOMER-specific or F) JASPAR-specific p53RE. Each heatmap represents the nucleotide frequency between the shared p53RE and either the HOMER or JASPAR-specific p53RE.
Figure 2:
Figure 2:. Overlap between identified p53RE and experimentally-validated p53 binding events across four comprehensive meta-analyses.
Upset-style plot of overlap between p53RE and experimentally-derived p53 binding events (via ChIP-seq) for four separate meta-analyses.
Figure 3:
Figure 3:. Characterization of p53RE and their localization within repetitive genomic elements.
A) The percentage of p53RE found within each class of repeat element. A total of 254,075/412,586 p53RE (63%) are found within repeat elements. B) The distribution of p53RE with synteny to MM39 and found in repeat elements. C) The percentage of p53RE with experimentally-validated p53 binding (Riege et al., 2020) and their distribution within repeat elements. D) The distribution of p53-bound versus p53-unbound p53RE and their localization within LINE, SINE, LTR, DNA, and simple repeats, which represent the five most common repeat types with p53RE. E) Number of p53-bound p53RE within each class and type of repeat element for the five most common repeat types and their enrichment versus p53-unbound p53RE.
Figure 4:
Figure 4:. Analysis of p53RE and their localization within chromHMM genome segments.
A) The percentage of p53RE found within each of the 16 chromHMM fullstack summary groups compared to the percentage of the human genome covered by that chromHMM feature (Vu and Ernst, 2022). B) The percentage (white boxes) and fold-change enrichment (color scale) of bound p53RE versus unbound p53RE found within each of the 16 chromHMM fullstack summary groups. p53 binding data are from the Riege et al meta-analysis (Riege et al., 2020). C) The rank order of p53-bound p53RE (x-axis) versus the percent of p53-bound p53RE that are found within each of the 100 detailed chromHMM fullstack genomic segments. Arrows represent an enrichment/fold-change of greater than 2 (red upward arrows) or less than −2 (blue downward arrows) for p53-bound versus p53-unbound p53RE. D) The actual enrichment/fold-change for p53-bound versus unbound p53RE for each chromHMM fullstack segment labeled in C.
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References

    1. Amemiya H. M., Kundaje A., and Boyle A. P. (2019). The ENCODE Blacklist: Identification of Problematic Regions of the Genome. Sci Rep 9, 9354. doi: 10.1038/s41598-019-45839-z - DOI - PMC - PubMed
    1. Bannister A. J., and Kouzarides T. (2011). Regulation of chromatin by histone modifications. Cell Res 21, 381–395. doi: 10.1038/cr.2011.22 - DOI - PMC - PubMed
    1. Bernstein B. E., Kamal M., Lindblad-Toh K., Bekiranov S., Bailey D. K., Huebert D. J., et al. (2005). Genomic Maps and Comparative Analysis of Histone Modifications in Human and Mouse. Cell 120, 169–181. doi: 10.1016/j.cell.2005.01.001 - DOI - PubMed
    1. Bourque G., Leong B., Vega V. B., Chen X., Lee Y. L., Srinivasan K. G., et al. (2008). Evolution of the mammalian transcription factor binding repertoire via transposable elements. Genome Res. 18, 1752–1762. doi: 10.1101/gr.080663.108 - DOI - PMC - PubMed
    1. Castro-Mondragon J. A., Riudavets-Puig R., Rauluseviciute I., Berhanu Lemma R., Turchi L., Blanc-Mathieu R., et al. (2022). JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles. Nucleic Acids Research 50, D165–D173. doi: 10.1093/nar/gkab1113 - DOI - PMC - PubMed

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