Figures and data in Dissecting the DNA binding landscape and gene regulatory network of p63 and p53

Figures
Tables
Additional files

8 figures, 1 table and 4 additional files

Figures

Figure 1

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Meta-analysis of p63-dependent gene regulation.

(A) Distribution of the number of genes found in each of the *p63 Expression Score* groups. Because *p63 Expression Score* group ‘14’ and ‘−12’ contained only two genes they were included in group ‘13’ and ‘−11’, respectively, for further analyses. (B) 16 datasets on p63-dependent gene expression from 11 studies. EE – exogenous p63 expression; sh KD – shRNA-mediated knockdown; si KD – siRNA-mediated knockdown; KO - sgRNA-mediated knockout (C) A heatmap displaying the regulation of 15 genes with positive and 15 genes with negative *p63 Expression Scores. GAPDH* and *GAPDHS* represent negative controls.

Figure 2

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Gene sets enriched among genes commonly regulated by p63.

Enrichment of (**A, B, C, E**) MSigDB gene sets or (D) genes up- and down-regulated across squamous cell cancers (SCC) (Cancer Genome Atlas Research Network et al., 2018) among genes ranked by the *p63 Expression Score*.

Figure 3

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Transcription factors in the p63 GRN.

(A) Significant (adj.p-value≤0.05) enrichment of TF binding at genes with a *p63 Expression Score* ≥8 (green) or ≤ −8 (red) as identified by Enrichr (Kuleshov et al., 2016). (B) Enrichment of MSigDB gene sets among genes ranked by the *p63 Expression Score*. Scatter plots displays the log₂(fold-change) of previously collected high confidence DREAM target genes (Fischer et al., 2016a) (C) across the 16 p63-dependent gene expression profiling datasets and (D) MCF10A cells treated with DMSO or Nutlin in addition to shControl and shp63 (Karsli Uzunbas et al., 2019). *CDKN1A* levels serve as control. The black line indicates the median.

Figure 4

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p63 and p53 regulate largely distinct target gene sets.

(A) The *p63 Expression Score* compared to the previously published *p53 Expression Score* that was generated using the same meta-analysis approach (Fischer et al., 2016a) for all 16,198 genes for which both scores were available. (B) The scatter plot displays the log₂(fold-change) of previously collected high confidence direct p53 target genes (Fischer, 2017) across the 16 p63-dependent gene expression profiling datasets. The black line indicates the median. The data indicates a large degree of independence of p53 targets from p63-dependent expression.

Figure 5 with 4 supplements

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The p63 and p53 DNA-binding landscape.

(**A and B**) The number of p63 and p53 binding peaks sorted by the number of datasets that commonly identified/support the peak. (C) The number of p53 and p63 peaks identified in the 28 p53 and 20 p63 ChIP-seq datasets, respectively. (D) The relative number of ‘known’ p53 and p63 motifs found by HOMER v4.10 (Heinz et al., 2010) under p53 and p63 peaks, respectively, with increasing dataset support. (E) Schematic of ‘p53’, ‘p63’ and ‘p53+p63’ peak selection for further analyses. (F) De novo motif search results from HOMER v4.10 for the ‘p53+p63’, ‘p53’, and ‘p63’ peak sets. The first round of motif search identified the ‘primary’ motif in each peak set. Using an iterative approach, all peaks that contained the ‘primary’ motif were removed and the de novo motif search was repeated. This iterative approach was followed until no more p53/p63-like motif was identified.

Figure 5—figure supplement 1

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Correlation between p53 and p63 binding frequency and motif consensus.

(**A and B**) Correlation between dataset support for p53 and p63 binding. (**C to F**) Correlation between HOMER motif score for primary and secondary ‘p53+p63’ motifs and dataset support for (**C and D**) p53 binding or (**E and F**) p63 binding.

Figure 5—figure supplement 2

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Correlation between p53 and p63 binding frequency and motif consensus.

Correlation between HOMER motif score for primary, secondary, and tertiary (**A to C**) ‘p53’ motifs or (**D to F**) ‘p63’ motifs and dataset support for (**A to C**) p53 binding or (**D to F**) p63 binding.

Figure 5—figure supplement 3

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Top motifs co-enriched with primary ‘p53+p63’, ‘p53’, and ‘p63’ motifs at the respective DNA sites.

Figure 5—figure supplement 4

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TFs with significantly similar binding repertoirs.

Top 20 TFs with ChIP-seq peak sets similar to (A) the common p53+p63 sites, (B) the unique p53 sites, and (C) the unique p63 sites (Figure 5E) as identified using CistromeDB toolkit.

Of note, some TP53 ChIP-seq datasets are wrongly labeled ‘T’ in the database.

Figure 6

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The DNA-binding landscape of p53.

DNA sites occupied by p53 in at least five datasets were searched iterative with the motifs identified by our iterative de novo search (Figure 5F). We searched first for the primary ‘p53+p63’ motif and among all remaining sites for the primary ‘p53’ motif. All other ‘p53+p63’ and ‘p53’ motifs were searched subsequently.

Figure 7 with 1 supplement

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The DNA-binding landscape of p63.

DNA sites occupied by p63 in at least five datasets were searched iterative with the motifs identified by our iterative de novo search (Figure 5F). We searched first for the primary ‘p53+p63’ motif and among all remaining sites for the primary ‘p63’ motif. All other ‘p53+p63’ and ‘p63’ motifs were searched subsequently (Supplementary file 3).

Figure 7—figure supplement 1

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Complement to Table 1.

Genes identified as significantly up- or down-regulated in at least the half of all datasets (|*p63 Expression Score|*| ≥ 8) that are linked to p63-binding sites supported by at least half of all datasets (≥10) through binding within 5 kb from their TSS or through double-elite enhancer:gene associations (Fishilevich et al., 2017). Using these thresholds we identified 138 and 42 high-probability candidates as directly up- and down-regulated by p63, respectively. Gene names marked in red are also up- or down-regulated across SCCs (Cancer Genome Atlas Research Network et al., 2018).

Figure 8 with 1 supplement

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p63/SCC 28-gene set correlates with poorer survival in HNSC.

Kaplan-Meier plots of TCGA HNSC patient survival data. (A) Patients were subdivided in four equally sized subgroups based on expression levels of the 28-gene set. The results suggest a poorer survival of patients with an up-regulated expression of the set genes. (B) To corroborate this finding patients of the subgroups low-med, med-high, and high from (A) were joined to form a new high group. Boxplot in bins of 10 of *TP63* FPKM expression values in TCGA HNCS patient sample data compared to (C) FPKM values of a meta-gene comprising the 28-gene set and (D) ssGSEA scores of the 28-gene set. X-axis is right-censored at 100 to better visualize the effect. The full graph is displayed in Figure 8—figure supplement 1.

Figure 8—figure supplement 1

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Extension of Figure 8C and D.

Boxplot in bins of 10 of *TP63* FPKM expression values in TCGA HNCS patient sample data compared to (A) FPKM values of a meta-gene comprising the 28-gene set and (B) ssGSEA scores of the 28-gene set. Complementary to Figure 8C and D.

Tables

Table 1

High-probability direct p63 target genes.

Genes identified as significantly up- or down-regulated in at least the half of all datasets (|p63 Expression Score| ≥ 8) that are linked to p63-binding sites supported by at least half of all datasets (≥10) through binding within 5 kb from their TSS or through double-elite enhancer-gene associations (Fishilevich et al., 2017). Using these thresholds we identified 138 and 42 high-probability candidates as directly up- and down-regulated by p63, respectively. Gene names marked in bold are also up- or down-regulated across SCCs (Cancer Genome Atlas Research Network et al., 2018).

Gene symbol	p63 Expression Score	p63 binding within 5 kb from TSS	p63 binding linked through enhancer	Gene symbol	p63 Expression Score	p63 binding within 5 kb from TSS	p63 binding linked through enhancer
DUSP6	14	yes	yes	FSCN1	8	yes	yes
RAB38	14	yes	yes	GINS3	8	yes	no
GSDME	13	yes	yes	GM2A	8	yes	yes
*LAD1*	13	yes	yes	*HMGA2*	8	yes	yes
*S100A2*	13	yes	yes	HSPA4L	8	yes	yes
*TMEM40*	13	yes	yes	JAG1	8	yes	yes
*FGFBP1*	12	yes	yes	KCTD12	8	yes	no
HAS3	12	yes	no	KIAA0930	8	yes	yes
NECTIN1	12	yes	yes	KIF14	8	no	yes
TCOF1	12	yes	yes	KIRREL1	8	no	yes
DUSP7	11	yes	yes	LIG1	8	yes	yes
*IL1B*	11	no	yes	*LPAR3*	8	yes	yes
MREG	11	no	yes	LRRFIP2	8	no	yes
PA2G4	11	yes	no	MALT1	8	no	yes
RGS20	11	yes	no	MAST4	8	no	yes
SDC1	11	no	yes	MCM3	8	no	yes
*SFN*	11	yes	yes	*MMP14*	8	yes	yes
STK17A	11	yes	yes	MMRN2	8	yes	no
*VSNL1*	11	yes	yes	NOM1	8	yes	no
ARHGAP25	10	yes	yes	NRCAM	8	yes	yes
CDCA4	10	yes	yes	NRG1	8	no	yes
DUSP11	10	yes	no	OAS3	8	yes	yes
*FAT2*	10	yes	no	PPFIBP1	8	yes	yes
*FERMT1*	10	yes	yes	PROCR	8	yes	no
IL4R	10	yes	yes	QSOX2	8	yes	yes
INPP1	10	yes	yes	RAD51C	8	yes	yes
*IRF6*	10	no	yes	*RASSF6*	8	no	yes
ITGA6	10	no	yes	RFX7	8	yes	no
KIZ	10	yes	no	SH3PXD2A	8	no	yes
MAPKBP1	10	no	yes	SLC1A5	8	yes	yes
MYO10	10	yes	yes	SLC2A9	8	yes	yes
MYO19	10	yes	yes	SLC37A2	8	yes	no
ORC1	10	no	yes	SMAD5	8	yes	no
PAK1	10	yes	no	SPATS2	8	no	yes
*PTHLH*	10	yes	yes	SSRP1	8	no	yes
SMTN	10	yes	no	TGFB1	8	yes	yes
WDFY2	10	yes	no	TMEM237	8	yes	no
*XDH*	10	yes	yes	TOMM34	8	yes	no
ARHGDIB	9	yes	yes	*TRIM7*	8	yes	yes
AURKB	9	yes	no	TRIP13	8	yes	no
BTBD11	9	yes	no	TSPAN5	8	yes	no
C6orf106	9	yes	no	TSR1	8	no	yes
CARD10	9	yes	yes	TYMS	8	yes	yes
CHAF1A	9	no	yes	UCK2	8	yes	yes
*CSTA*	9	yes	no	UTP4	8	no	yes
*CYP27B1*	9	yes	no	YAP1	8	yes	no
*FEZ1*	9	yes	yes	YES1	8	yes	yes
GNA15	9	yes	no	ZFP36L2	8	no	yes
*GPX2*	9	yes	no	APH1B	-8	no	yes
GSTP1	9	yes	no	BIRC3	-8	yes	yes
HRAS	9	yes	yes	C9orf3	-8	yes	yes
IFI16	9	yes	yes	CHST3	-8	no	yes
KREMEN1	9	yes	yes	CPQ	-8	no	yes
LDLR	9	yes	no	DUSP8	-8	yes	no
MAPK6	9	yes	yes	EPCAM	-8	no	yes
MYO5A	9	no	yes	ERBB2	-8	no	yes
NCAPH2	9	yes	no	FBN1	-8	no	yes
NDE1	9	yes	yes	ITFG1	-8	yes	no
NDST1	9	yes	yes	LLGL2	-8	yes	yes
*NIPAL4*	9	yes	yes	NCSTN	-8	no	yes
PPIF	9	no	yes	OPN3	-8	no	yes
*PPP4R4*	9	yes	no	*PBX1*	-8	yes	yes
PTTG1	9	yes	yes	PDXK	-8	no	yes
RAPGEF5	9	yes	yes	PLAC8	-8	yes	yes
*RNASE7*	9	yes	yes	S100A4	-8	no	yes
RRP12	9	no	yes	*SPOCK1*	-8	no	yes
*SERPINB13*	9	yes	no	TNS3	-8	no	yes
SNCA	9	no	yes	ARL6IP5	-9	no	yes
STX6	9	yes	no	*COBL*	-9	no	yes
AK4	8	no	yes	CUEDC1	-9	yes	yes
ARHGAP23	8	yes	yes	GSN	-9	yes	no
ASCC3	8	yes	yes	PDGFC	-9	yes	yes
BRCA1	8	yes	no	PGPEP1	-9	no	yes
BTBD10	8	yes	yes	PLXNB2	-9	yes	yes
CCNK	8	yes	no	PXDN	-9	no	yes
CCT4	8	yes	no	RALGPS1	-9	yes	yes
CD44	8	yes	yes	ROR1	-9	yes	no
CDC42SE1	8	yes	no	SLC16A5	-9	yes	yes
CDCA7	8	yes	no	TM4SF1	-9	yes	yes
*COL17A1*	8	yes	no	ALDH3B1	−10	yes	yes
CRKL	8	yes	yes	*CYP1B1*	−10	no	yes
DRAP1	8	yes	yes	HHAT	−10	yes	yes
EHD4	8	no	yes	MEGF8	−10	no	yes
ERCC6L	8	no	yes	PTGES	−10	yes	no
ESRP1	8	no	yes	PTTG1IP	−10	no	yes
*FABP5*	8	yes	no	RPS27L	−10	yes	yes
FANCI	8	yes	yes	SECTM1	−10	yes	yes
FLOT2	8	yes	no	SLC22A5	−10	yes	no
*FOSL1*	8	yes	yes	TNFSF15	−10	yes	yes
FRMD4B	8	yes	no	SRD5A3	−11	yes	no

Additional files

Supplementary file 1 Detailed information on publicly available p63-dependent gene expression profiling and p63 ChIP-seq datasets that were integrated in this study.: https://cdn.elifesciences.org/articles/63266/elife-63266-supp1-v2.xlsx
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Supplementary file 2 Meta-analysis from 16 p63-dependent gene expression information datasets (listed in Suppelemtary File 1) to generate the p63 Expression Score for 19,156 human genes.: https://cdn.elifesciences.org/articles/63266/elife-63266-supp2-v2.xlsx
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Supplementary file 3 p63- and p53-binding sites identified in at least 5 out of 20 and 28 ChIP-seq datasets, respectively. Binding sites are listed with their ChIP-seq dataset support and highest scoring p63 response elements (p63REs) or p53REs. Genes associated with p63-binding sites through proximal TSS binding or enhancers are listed.: https://cdn.elifesciences.org/articles/63266/elife-63266-supp3-v2.xlsx
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Transparent reporting form: https://cdn.elifesciences.org/articles/63266/elife-63266-transrepform-v2.docx
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