Distinct p53 genomic binding patterns in normal and cancer-derived human cells - PubMed (original) (raw)
Comparative Study
. 2011 Dec 15;10(24):4237-49.
doi: 10.4161/cc.10.24.18383. Epub 2011 Dec 15.
Affiliations
- PMID: 22127205
- PMCID: PMC3272258
- DOI: 10.4161/cc.10.24.18383
Comparative Study
Distinct p53 genomic binding patterns in normal and cancer-derived human cells
Krassimira Botcheva et al. Cell Cycle. 2011.
Abstract
We report here genome-wide analysis of the tumor suppressor p53 binding sites in normal human cells. 743 high-confidence ChIP-seq peaks representing putative genomic binding sites were identified in normal IMR90 fibroblasts using a reference chromatin sample. More than 40% were located within 2 kb of a transcription start site (TSS), a distribution similar to that documented for individually studied, functional p53 binding sites and, to date, not observed by previous p53 genome-wide studies. Nearly half of the high-confidence binding sites in the IMR90 cells reside in CpG islands, in marked contrast to sites reported in cancer-derived cells. The distinct genomic features of the IMR90 binding sites do not reflect a distinct preference for specific sequences, since the de novo developed p53 motif based on our study is similar to those reported by genome-wide studies of cancer cells. More likely, the different chromatin landscape in normal, compared with cancer-derived cells, influences p53 binding via modulating availability of the sites. We compared the IMR90 ChIPseq peaks to the recently published IMR90 methylome and demonstrated that they are enriched at hypomethylated DNA. Our study represents the first genome-wide, de novo mapping of p53 binding sites in normal human cells and reveals that p53 binding sites reside in distinct genomic landscapes in normal and cancer-derived human cells.
Figures
Figure 1
p53 ChIP-seq map at the CDKN1A locus. (A) Overview of chromosome 6. Plotted are ChIP-seq (red) and Input-seq (blue) coverage maps. (B) ChIP-seq map across a 35 kb genomic region of the CDKN1A locus. Previously reported p53 binding sites A–E (marked with vertical gray lines) and the newly identified site F are shown. Other features plotted include CGIs (olive green), RefSeq genes (dark blue), spliced ESTs (magenta) and p53 PET3+ clusters (orange), all downloaded from the UCSC Genome Browser (hg18) and p53 binding sites predicted by p53MH algorithm (green). For details, see Supplemental Methods. (C) qPCR validation of p53 binding at CDKN1A. For each site, the hg18 coordinates and the distance to the TSS (CDKN1A transcript NM_000389) are shown. The position of the peak maximum is shown for site F. The indicated region from chr22 was used as a negative control for p53 binding. Enrichment is calculated as percentage of Input; average results are shown from duplicate qPCR samples. FU, 6 h treatment with 5-FU; NS, no stimulation; DO1, ChIP with p53 specific DO1 antibody; IgG, ChIP with non-specific IgG.
Figure 2
p53 ChIP-seq validation. (A) Examples of ChIP-seq peaks that coincide with the reference p53 REs (see Table S4A) at the target genes BBC3, PLK3, LIF and GPX1. ChIP-seq (red) and Input-seq (blue) coverage maps in 5 kb regions are plotted and centered at the reference REs (marked with vertical gray lines). All annotated features shown (e.g., RefSeq genes, CGIs, p53 PET3+ and p53MH predicted binding sites) are as indicated on Figure 1. (B) Examples of newly identified binding sites validated by qPCR at the genes LMNA, DCP1B and NEAT1. Average enrichment is calculated as a percentage of Input; results shown are from duplicate qPCR samples. FU, 6 h treatment with 5-FU; NS, no stimulation; DO1, ChIP with p53 specific DO1 antibody; IgG, ChIP with non-specific IgG.
Figure 3
p53 ChIP-seq peaks from IMR90 are strongly enriched for predicted p53 binding sites and for TSSs. (A) Distribution of p53 binding sites, predicted by the p53MH algorithm as a function of distance (nt) to the peak maximum. p53 ChIP-seq peaks are highly enriched for p53MH sites within 50 nt of the peak maximum. (B) Distribution of TSSs as a function of distance (kb) to the peak maximum. p53 ChIP-seq peaks, unlike Input-seq peaks, are enriched for TSSs within 2 kb of the peak maximum.
Figure 4
Genomic distribution of p53 binding sites in IMR90 cells. (A) Gene-associated ChIP-seq (red) and Input-seq (blue) peaks are categorized as either “single,” located in only one of the genic regions defined below and typically associated with a single transcript, or “multiple,” located in more than one genic region due to proximity to more than one transcript. Intergenic peaks are located outside the boundaries of any gene extended 20 kb upstream and 5 kb downstream. (B) Breakdown of the relative positions for the peaks associated with single genic regions shows ChIP-seq peaks tightly clustered in the immediate vicinity of TSSs. The following non overlapping genic regions were considered for this analysis: 20-5 kb to TSS, 5-2 kb to TSS, 2 kb ± TSS, 2–5 kb downstream of TSS, intron or exon 0 (if > 5 kb downstream of TSS) and within 5 kb downstream of transcription end site (TES) (see Table S6 for details).
Figure 5
Distribution of p53 binding sites with respect to CGIs and TSSs. Compared were high-confidence sites we identified in IMR90 (743 ChIP-seq peaks) with those reported in HCT116 (310 PET3+ loci23) and U2OS (1516 ChIP-chip sites; 2137 ChIP-seq sites25). p53 binding sites are highly enriched at TSSs and CGIs only in the normal IMR90 cells. Cells treated with 5-FU for 6 h (FU, 6 h) or with actinomycin D for 24 h (ActD, 24 h). ChIPs in all four experiments were done with the p53-specific antibody DO1.
Figure 6
High-confidence p53 ChIP-seq peaks are enriched at hypomethylated DNA in IMR90 cells. (A) p53 ChIP-seq peaks (red), unlike Input-seq peaks (blue), are enriched at CGIs. The number of genomic CpG dinucleotides (hg18) is plotted in 10 nt bins as a function of the distance to the peak maximum. (B) p53 ChIP-seq peaks (red), but not Input-seq peaks (blue), are enriched at hypomethylated DNA. Relative methylation density (mean mC/C ratio) calculated from the data reported for IMR90 by Lister et al. is plotted as a function of distance to the peak maximum (ChIP-seq peaks) or to CGI centers (B, C, E and F). (C) p53 ChIP-seq peaks in CGIs (green) and out of CGIs (orange) are enriched at hypomethylated DNA. (D) Distribution of all human CGIs (UCSC definition) with respect to TSS. The distance (bp) from CGI center to the nearest TSS is plotted on a log scale. Proximal CGIs (within 2 kb of a TSS) are shown in green and distal CGIs (away from TSSs) in purple. CGIs, at which high-confidence p53 ChIP-seq peaks, are found are plotted in red (note the change in the scale). (E) The hypomethylation level of ChIP-seq peaks in proximal CGIs (red) is similar to that of all human proximal CGIs (green). (F) ChIP-seq peaks in distal CGIs (red) are far more hypomethylated than the human distal CGIs (purple).
Figure 7
Motif analysis of the 743 high-confidence p53 ChIP-seq peaks identified in IMR90 cells using MEME. (A) Sequence logo depicting the p53CSI motif (E-value 1.2e−1059). (B) p53CSI motif distribution in the 743 high-confidence peaks. Number of p53CSI motifs found (in 20 bp bins) is plotted vs. the distance (bp) between the motif center and the peak maximum. Strong enrichment of the p53CSI motif is observed within 100 nt centered at the peak maximum.
Figure 8
DAVID functional annotation analysis of the genes associated with high-confidence p53 ChIP-seq peaks in IMR90 cells. (A) Most highly enriched KEGG pathways (p-value < 0.01). Fold enrichment is shown as calculated by DAVID. (B) Most highly enriched clusters of genes with enrichment score above 1.3. See Table S10 for all enriched clusters.
Comment in
- Dissimilar DNA binding by p53 in normal and tumor-derived cells.
Freed-Pastor WA, Prives C. Freed-Pastor WA, et al. Cell Cycle. 2011 Dec 15;10(24):4207. doi: 10.4161/cc.10.24.18723. Epub 2011 Dec 15. Cell Cycle. 2011. PMID: 22127203 No abstract available.
Similar articles
- Cell context dependent p53 genome-wide binding patterns and enrichment at repeats.
Botcheva K, McCorkle SR. Botcheva K, et al. PLoS One. 2014 Nov 21;9(11):e113492. doi: 10.1371/journal.pone.0113492. eCollection 2014. PLoS One. 2014. PMID: 25415302 Free PMC article. - p53 binding sites in normal and cancer cells are characterized by distinct chromatin context.
Bao F, LoVerso PR, Fisk JN, Zhurkin VB, Cui F. Bao F, et al. Cell Cycle. 2017;16(21):2073-2085. doi: 10.1080/15384101.2017.1361064. Epub 2017 Sep 28. Cell Cycle. 2017. PMID: 28820292 Free PMC article. - Multiple testing methods for ChIP-Chip high density oligonucleotide array data.
Keleş S, van der Laan MJ, Dudoit S, Cawley SE. Keleş S, et al. J Comput Biol. 2006 Apr;13(3):579-613. doi: 10.1089/cmb.2006.13.579. J Comput Biol. 2006. PMID: 16706714 - Methylation and deamination of CpGs generate p53-binding sites on a genomic scale.
Zemojtel T, Kielbasa SM, Arndt PF, Chung HR, Vingron M. Zemojtel T, et al. Trends Genet. 2009 Feb;25(2):63-6. doi: 10.1016/j.tig.2008.11.005. Epub 2008 Dec 26. Trends Genet. 2009. PMID: 19101055 - Retrotransposon-derived p53 binding sites enhance telomere maintenance and genome protection.
Lieberman PM. Lieberman PM. Bioessays. 2016 Oct;38(10):943-9. doi: 10.1002/bies.201600078. Epub 2016 Aug 19. Bioessays. 2016. PMID: 27539745 Free PMC article. Review.
Cited by
- NEAT1 modulates the TIRR/53BP1 complex to maintain genome integrity.
Kilgas S, Syed A, Toolan-Kerr P, Swift ML, Roychoudhury S, Sarkar A, Wilkins S, Quigley M, Poetsch AR, Botuyan MV, Cui G, Mer G, Ule J, Drané P, Chowdhury D. Kilgas S, et al. Nat Commun. 2024 Sep 30;15(1):8438. doi: 10.1038/s41467-024-52862-w. Nat Commun. 2024. PMID: 39349456 Free PMC article. - Decoding the lncRNAome Across Diverse Cellular Stresses Reveals Core p53-effector Pan-cancer Suppressive lncRNAs.
Mitra R, Adams CM, Eischen CM. Mitra R, et al. Cancer Res Commun. 2023 May 11;3(5):842-859. doi: 10.1158/2767-9764.CRC-22-0473. eCollection 2023 May. Cancer Res Commun. 2023. PMID: 37377895 Free PMC article. - Research on Predicting the Occurrence of Hepatocellular Carcinoma Based on Notch Signal-Related Genes Using Machine Learning Algorithms.
Zhou D, Cao S, Xie H. Zhou D, et al. Turk J Gastroenterol. 2023 Jul;34(7):760-770. doi: 10.5152/tjg.2023.22357. Turk J Gastroenterol. 2023. PMID: 37051625 Free PMC article. - The Long and the Short of It: NEAT1 and Cancer Cell Metabolism.
Smith NE, Spencer-Merris P, Fox AH, Petersen J, Michael MZ. Smith NE, et al. Cancers (Basel). 2022 Sep 9;14(18):4388. doi: 10.3390/cancers14184388. Cancers (Basel). 2022. PMID: 36139550 Free PMC article. Review. - The Role of TP53 Mutations in _EGFR_-Mutated Non-Small-Cell Lung Cancer: Clinical Significance and Implications for Therapy.
Canale M, Andrikou K, Priano I, Cravero P, Pasini L, Urbini M, Delmonte A, Crinò L, Bronte G, Ulivi P. Canale M, et al. Cancers (Basel). 2022 Feb 23;14(5):1143. doi: 10.3390/cancers14051143. Cancers (Basel). 2022. PMID: 35267450 Free PMC article. Review.
References
- Anderson CW, Appella E. Signaling to the p53 tumor suppressor through pathways activated by genotoxic and non-genotoxic stresses. In: Bradshaw RA, Dennis EA, editors. Handbook of Cell Signaling. Elsevier; 2009.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Research Materials
Miscellaneous