Abstract

Human embryonic stem cell (hESC) differentiation promises advances in regenerative medicine1,2,3, yet conversion of hESCs into transplantable cells or tissues remains poorly understood. Using our keratinocyte differentiation system, we employ a multi-dimensional genomics approach to interrogate the contributions of inductive morphogens retinoic acid and bone morphogenetic protein 4 (BMP4) and the epidermal master regulator p63 (encoded by TP63)4,5 during surface ectoderm commitment. In contrast to other master regulators6,7,8,9, p63 effects major transcriptional changes only after morphogens alter chromatin accessibility, establishing an epigenetic landscape for p63 to modify. p63 distally closes chromatin accessibility and promotes accumulation of H3K27me3 (trimethylated histone H3 lysine 27). Cohesin HiChIP10 visualizations of chromosome conformation show that p63 and the morphogens contribute to dynamic long-range chromatin interactions, as illustrated by TFAP2C regulation11. Our study demonstrates the unexpected dependency of p63 on morphogenetic signaling and provides novel insights into how a master regulator can specify diverse transcriptional programs based on the chromatin landscape induced by exposure to specific morphogens.

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Data availability

All sequencing data are available through Gene Expression Omnibus (GEO) accession number: GSE119997.

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References

  1. 1.

    Walmsley, G. G. et al. Induced pluripotent stem cells in regenerative medicine and disease modeling. Curr. Stem. Cell. Res. Ther. 9, 73–81 (2014).

  2. 2.

    Inoue, H., Nagata, N., Kurokawa, H. & Yamanaka, S. iPS cells: a game changer for future medicine. EMBO J. 33, 409–417 (2014).

  3. 3.

    Hanna, J. et al. Treatment of sickle cell anemia mouse model with iPS cells generated from autologous skin. Science 318, 1920–1923 (2007).

  4. 4.

    Umegaki-Arao, N. et al. Induced pluripotent stem cells from human revertant keratinocytes for the treatment of epidermolysis bullosa. Sci. Transl. Med. 6, 264ra164 (2014).

  5. 5.

    Sebastiano, V. et al. Human COL7A1-corrected induced pluripotent stem cells for the treatment of recessive dystrophic epidermolysis bullosa. Sci. Transl. Med. 6, 264ra163 (2014).

  6. 6.

    Zaret, K. S. & Carroll, J. S. Pioneer transcription factors: establishing competence for gene expression. Genes Dev. 25, 2227–2241 (2011).

  7. 7.

    Yang, A. et al. p63 is essential for regenerative proliferation in limb, craniofacial and epithelial development. Nature 398, 714–718 (1999).

  8. 8.

    Mills, A. A. et al. p63 is a p53 homologue required for limb and epidermal morphogenesis. Nature 398, 708–713 (1999).

  9. 9.

    Lupien, M. et al. FoxA1 translates epigenetic signatures into enhancer-driven lineage-specific transcription. Cell 132, 958–970 (2008).

  10. 10.

    Mumbach, M. R. et al. HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat. Methods 13, 919–922 (2016).

  11. 11.

    Qiao, Y. et al. AP2γ regulates neural and epidermal development downstream of the BMP pathway at early stages of ectodermal patterning. Cell Res. 22, 1546–1561 (2012).

  12. 12.

    Metallo, C. M., Ji, L., de Pablo, J. J. & Palecek, S. P. Retinoic acid and bone morphogenetic protein signaling synergize to efficiently direct epithelial differentiation of human embryonic stem cells. Stem Cells 26, 372–380 (2008).

  13. 13.

    Itoh, M. et al. Generation of 3D skin equivalents fully reconstituted from human induced pluripotent stem cells (iPSCs). PLoS ONE 8, e77673 (2013).

  14. 14.

    Guenou, H. et al. Human embryonic stem-cell derivatives for full reconstruction of the pluristratified epidermis: a preclinical study. Lancet 374, 1745–1753 (2009).

  15. 15.

    Coraux, C. et al. Reconstituted skin from murine embryonic stem cells. Curr. Biol. 13, 849–853 (2003).

  16. 16.

    Chen, G. et al. Chemically defined conditions for human iPSC derivation and culture. Nat. Methods 8, 424–429 (2011).

  17. 17.

    Owens, D. W. & Lane, E. B. The quest for the function of simple epithelial keratins. BioEssays 25, 748–758 (2003).

  18. 18.

    Senoo, M., Pinto, F., Crum, C. P. & McKeon, F. p63 is essential for the proliferative potential of stem cells in stratified epithelia. Cell 129, 523–536 (2007).

  19. 19.

    Koster, M. I. & Roop, D. R. Mechanisms regulating epithelial stratification. Annu. Rev. Cell. Dev. Biol. 23, 93–113 (2007).

  20. 20.

    Green, H., Easley, K. & Iuchi, S. Marker succession during the development of keratinocytes from cultured human embryonic stem cells. Proc. Natl Acad. Sci. USA 100, 15625–15630 (2003).

  21. 21.

    Yang, A. et al. p63, a p53 homolog at 3q27-29, encodes multiple products with transactivating, death-inducing, and dominant-negative activities. Mol. Cell 2, 305–316 (1998).

  22. 22.

    Truong, A. B., Kretz, M., Ridky, T. W., Kimmel, R. & Khavari, P. A. p63 regulates proliferation and differentiation of developmentally mature keratinocytes. Genes Dev. 20, 3185–3197 (2006).

  23. 23.

    Romano, R. A., Ortt, K., Birkaya, B., Smalley, K. & Sinha, S. An active role of the ΔN isoform of p63 in regulating basal keratin genes K5 and K14 and directing epidermal cell fate. PLoS One 4, e5623 (2009).

  24. 24.

    LeBoeuf, M. et al. Hdac1 and Hdac2 act redundantly to control p63 and p53 functions in epidermal progenitor cells. Dev. Cell. 19, 807–818 (2010).

  25. 25.

    Nylander, K. et al. Differential expression of p63 isoforms in normal tissues and neoplastic cells. J. Pathol. 198, 417–427 (2002).

  26. 26.

    Aberdam, E. et al. A pure population of ectodermal cells derived from human embryonic stem cells. Stem Cells 26, 440–444 (2008).

  27. 27.

    Li, G. et al. c-Jun is essential for organization of the epidermal leading edge. Dev. Cell 4, 865–877 (2003).

  28. 28.

    Mehic, D., Bakiri, L., Ghannadan, M., Wagner, E. F. & Tschachler, E. Fos and jun proteins are specifically expressed during differentiation of human keratinocytes. J. Invest. Dermatol. 124, 212–220 (2005).

  29. 29.

    McLarren, K. W., Litsiou, A. & Streit, A. DLX5 positions the neural crest and preplacode region at the border of the neural plate. Dev. Biol. 259, 34–47 (2003).

  30. 30.

    Ezhkova, E. et al. Ezh2 orchestrates gene expression for the stepwise differentiation of tissue-specific stem cells. Cell 136, 1122–1135 (2009).

  31. 31.

    Rapisarda, V. et al. p63 transcription factor regulates nuclear shape and expression of nuclear envelope-associated genes in epidermal keratinocytes. J. Invest. Dermatol. 137, 2157–2167 (2017).

  32. 32.

    Wamstad, J. A. et al. Dynamic and coordinated epigenetic regulation of developmental transitions in the cardiac lineage. Cell 151, 206–220 (2012).

  33. 33.

    Ay, F., Bailey, T. L. & Noble, W. S. Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts. Genome Res. 24, 999–1011 (2014).

  34. 34.

    Barton, C. E. et al. Novel p63 target genes involved in paracrine signaling and keratinocyte differentiation. Cell Death Dis. 1, e74 (2010).

  35. 35.

    Koh, L. F., Ng, B. K., Bertrand, J. & Thierry, F. Transcriptional control of late differentiation in human keratinocytes by TAp63 and Notch. Exp. Dermatol. 24, 754–760 (2015).

  36. 36.

    Schwartzman, O. et al. UMI-4C for quantitative and targeted chromosomal contact profiling. Nat. Methods 13, 685–691 (2016).

  37. 37.

    Rinaldi, L. et al. Dnmt3a and Dnmt3b associate with enhancers to regulate human epidermal stem cell homeostasis. Cell Stem Cell 19, 491–501 (2016).

  38. 38.

    Wu, H. et al. Dnmt3a-dependent nonpromoter DNA methylation facilitates transcription of neurogenic genes. Science 329, 444–448 (2010).

  39. 39.

    Lin-Shiao, E. et al. KMT2D regulates p63 target enhancers to coordinate epithelial homeostasis. Genes Dev. 32, 181–193 (2018).

  40. 40.

    Hsu, P. D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013).

  41. 41.

    Mali, P., Esvelt, K. M. & Church, G. M. Cas9 as a versatile tool for engineering biology. Nat. Methods 10, 957–963 (2013).

  42. 42.

    Natsume, T., Kiyomitsu, T., Saga, Y. & Kanemaki, M. T. Rapid protein depletion in human cells by auxin-inducible degron tagging with short homology donors. Cell Rep. 15, 210–218 (2016).

  43. 43.

    Jacobi, A. M. et al. Simplified CRISPR tools for efficient genome editing and streamlined protocols for their delivery into mammalian cells and mouse zygotes. Methods 121-122, 16–28 (2017).

  44. 44.

    Liang, X., Potter, J., Kumar, S., Ravinder, N. & Chesnut, J. D. Enhanced CRISPR/Cas9-mediated precise genome editing by improved design and delivery of gRNA, Cas9 nuclease, and donor DNA. J. Biotechnol. 241, 136–146 (2017).

  45. 45.

    Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

  46. 46.

    Andrews, S. FastQC (version 0.11.3); http://www.bioinformatics.babraham.ac.uk/projects/fastqc.

  47. 47.

    Hwang, S., Kim, E., Lee, I. & Marcotte, E. M. Systematic comparison of variant calling pipelines using gold standard personal exome variants. Sci. Rep. 5, 17875 (2015).

  48. 48.

    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

  49. 49.

    Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

  50. 50.

    Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

  51. 51.

    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

  52. 52.

    Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

  53. 53.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

  54. 54.

    Saldanha, A. J. Java Treeview–extensible visualization of microarray data. Bioinformatics 20, 3246–3248 (2004).

  55. 55.

    Huang da, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

  56. 56.

    McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).

  57. 57.

    Ernst, J. & Kellis, M. ChromHMM: automating chromatin-state discovery and characterization. Nat. Methods 9, 215–216 (2012).

  58. 58.

    Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome. Biol. 16, 259 (2015).

  59. 59.

    Anders, S. et al. Count-based differential expression analysis of RNA sequencing data using R and Bioconductor. Nat. Protoc. 8, 1765–1786 (2013).

  60. 60.

    Scholz, F. & Stephens, M. K-sample Anderson-Darling tests. J. Am. Stats Assoc. 82, 918–924 (1987).

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Acknowledgements

We thank members of the Oro Laboratory, P. Greenside, J. Wysocka, A. Kundaje, O. Wapinski, and D. Webster for helpful discussions and comments. This work was supported by a CIRM Tools grant RT3-07796 (A.E.O.), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)/National Institutes of Health (NIH) grant F32AR070565 (J.M.P.), NIAMS/NIH grant AR45192 (P.A.K.), NIH P50 HG007735 (H.Y.C.), and NIH K99/R00 5R00AR065490 (X.B.). H.Y.C. is an Investigator of the Howard Hughes Medical Institute.

Author information

Author notes

    • Sandra P. Melo

    Present address: Agilent Technologies, Santa Clara, CA, USA

    • Elizaveta Bashkirova

    Present address: Columbia Stem Cell Initiative, Columbia University Medical Center, New York, NY, USA

    • Eric Liaw

    Present address: David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    • Xiaomin Bao

    Present address: Departments of Molecular Sciences and Dermatology, Northwestern University, Evanston, IL, USA

  1. These authors contributed equally: Jillian M. Pattison, Sandra P. Melo, Samantha N. Piekos.

Affiliations

  1. Program in Epithelial Biology, Stanford University School of Medicine, Stanford, CA, USA

    • Jillian M. Pattison
    • , Sandra P. Melo
    • , Samantha N. Piekos
    • , Jessica L. Torkelson
    • , Elizaveta Bashkirova
    • , Maxwell R. Mumbach
    • , Charlotte Rajasingh
    • , Hanson Hui Zhen
    • , Lingjie Li
    • , Eric Liaw
    • , Daniel Alber
    • , Adam J. Rubin
    • , Gautam Shankar
    • , Xiaomin Bao
    • , Howard Y. Chang
    • , Paul A. Khavari
    •  & Anthony E. Oro
  2. Center for Personal Dynamic Regulomes, Stanford, CA, USA

    • Maxwell R. Mumbach
    •  & Howard Y. Chang
  3. Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA

    • Howard Y. Chang

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Contributions

S.P.M. and J.M.P. designed and executed experiments, analyzed data, and wrote the manuscript. S.N.P. analyzed data and wrote the manuscript. J.L.T., E.B., M.R.M., C.R., H.H.Z., L.L., and X.B. executed experiments and contributed to experimental design. E.L., D.A., A.J.R., and G.S. contributed to data analysis. H.Y.C. and P.A.K. contributed to experimental design. A.E.O. designed experiments, analyzed data, wrote the manuscript, and conceived the project with S.P.M.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Anthony E. Oro.

Integrated supplementary information

  1. Supplementary Figure 1 Establishment of a feeder-free defined keratinocyte differentiation protocol.

    a, Previous protocols use BMP4 and RA, in addition to FGF inhibitors (SU), to differentiate stem cells into keratinocytes. The combination of BMP4 and RA produced the highest levels of p63 by day 7, regardless of the presence of SU. The percentage of p63-positive cells was calculated through counting of three independent images; error bars represent s.d. b, Stem cells differentiated in E6 medium with BMP4 and RA generated a greater number of p63-positive cells by day 7, as compared to stem cells differentiated using the FAD protocol (n = 3). c, Stem cells maintained without feeders in defined medium produced the most homogeneous population of cells expressing p63 at day 7 (n = 3). Error bars represent s.d. d, In the defined protocol, only the combination of BMP4 and RA treatment yielded enough p63 expression to produce cells that survive in keratinocyte selection medium (n = 3). Error bars represent s.d. Scale bars, 50 μm.

  2. Supplementary Figure 2 Functional evaluation of the p63 gain and loss of function H9 hESC lines.

    a, Dox-inducible p63 protein levels after 2 d of 2 μg/ml Dox treatment. p63 overexpression (+ Dox) resulted in slowed cell proliferation as measured through growth curves (n = 3). Errors bars represent s.d. b, Validation of the p63KO line using western blotting. While p63KO cells responded to RA/BMP treatment, differentiation in DKSFM resulted in rapid death, rendering these cells incapable of becoming keratinocytes (n = 3). Error bars indicate s.d. c, qRT–PCR in day 7 p63WT, day 0 p63GOF, and mature keratinocyte (NHK) cells revealing that the ΔNp63-alpha isoform was the predominant variant expressed in our system. Error bars represent s.d., n = 2. d, RNA-seq tracks depicting the expression of the ΔNp63 isoform in the p63WT and p63KO day 7 cells. Exons indicated in black show the region deleted in the p63KO cells (exons 6–8). Tracks represent n = 2. e, Expression of pluripotency markers and epithelial differentiation markers in day 0 p63GOF cells with and without Dox treatment, compared to day 7 p63WT cells (n = 2). Overexpression of p63 upon Dox treatment did not cause the cells to exit pluripotency. f, Expression of key transcription factors associated with epithelial development and differentiation (n = 2). Some factors were induced by morphogens and repressed by p63 at day 7, while others were only affected by the morphogens, thus p63 independent. p63 only altered expression of p63-dependent factors after RA/BMP4 treatment. g, qRT–PCR for p63-dependent transcription factors in day 7 p63GOF, with and without Dox (n = 4). Overexpression of p63 at day 7 did not further alter gene expression. Error bars represent s.e.m. (NS, not significant).

  3. Supplementary Figure 3 Chromatin accessibility and histone modifications are both morphogen and p63 dependent.

    a, Overlap in p63 binding sites (ChIP-seq) between day 0 p63GOF, day 7 p63WT, and keratinocytes (kc), n = 2. b, Only H3K27me3 histone marks are dependent on p63 presence, as is illustrated by the percent of differential peaks between day 7 p63WT and day 7 p63KO. c, Histograms depicting enrichment of histone modifications in day 7 p63WT and day 7 p63KO, in a 10-kb window, n = 2. H3K4me1, H3K4me3, and H3K27ac are similar between p63WT and p63KO, while H3K27me3 is noticeably reduced in p63KO. d, Western blots showing that global levels of H3K27me3 protein decrease in day 7 p63KO, while levels of Ezh2 do not (n = 4). Levels of Ezh2 protein are quantified relative to day 7 and are indicated above the blot. e, GO biological processes associated with H3K27me3 regions that are morphogen dependent. f, ChromHMM analysis indicates that the majority of p63 binding sites and sites that increase in accessibility upon morphogen treatment are located in strong enhancer regions. Conversely, the sites with differential H3K27me3 marks are not located in strong enhancer regions. g, By GREAT analysis, the majority of p63 binding sites at day 7 can be associated with differentially expressed genes. The reverse analysis interrogating how many differentially expressed genes are associated with a p63 binding site shows drastically different results. h, Genes that are associated with p63 binding sites and changing ATAC regions are more highly expressed in p63KO than p63WT, as analyzed by GREAT.

  4. Supplementary Figure 4 Cohesin HiChIP pipeline and read-depth statistics.

    a, Analysis pipeline for the cohesin HiChIP assay. HiChIP libraries were sequenced over two HiSeq lanes and raw reads were processed using Hi-C Pro. Binned 5-kb-resolution matrix files were used to build Virtual 4C maps while 10-kb-resolution matrices were further processed through FitHiC to call high-confidence contacts. The cutoff for processing was as follows: at least 10 counts per interaction with FDR < 0.001. b, Read-depth statistics for the cohesin HiChIP in all four cell types. Read depth is listed in millions and valid read pairs (PETs) and cis pairs are represented in the bar graph.

  5. Supplementary Figure 5 GREAT is a poor predictor of connectivity between distal elements and TSSs.

    a, Histograms by distance from the TSS of the number of p63 binding sites (BS) connected to TSSs as assigned by GREAT (single nearest gene; blue, left panel) and by high-confidence cohesin HiChIP contacts (red, right panel). b, Overlap of genes associated with at least one p63 BS by GREAT (blue) versus cohesin HiChIP contacts (red). c, Overlap of specific p63 BS–TSS associations as determined by GREAT (blue) versus cohesin HiChIP contacts (red).

  6. Supplementary Figure 6 Genes connected to p63 by direct binding, direct cohesin contact, or via one element are negatively regulated.

    a, Histograms of Monte Carlo simulation of the number of genes (blue) in a randomly generated gene list that are connected to p63 in day 7 p63WT cells through 0°, 1°, 2°, or 3° contacts. This is compared to the number of p63-dependent genes connected to p63 in these same configurations at day 7 (red). FDR is <0.05 for all configurations except 3° connections. b, ecdf of the change in expression level (day 7 p63WT versus day 7 p63KO) of genes connected to p63 by 0º (orange), 1º (blue), 2º (green), 3º (purple), and all (red) connections compared to all genes (black). n is the number of genes, two-sided t test.

  7. Supplementary Figure 7 TSSs associated with p63-dependent H3K27me3 regions are not differentially regulated.

    a, Changes in high-confidence cohesin connectivity strength between various cell types of the following contacts: p63–TSS, p63–p63-dependent (p63-dep) H3K27me3, and p63–p63-dep H3K27me3 where both elements are connected to the TSS. P values were calculated using a two-sample Anderson-Darling test. n is the number of contacts. b, ecdfs of the change in expression level (day 7 p63WT versus day 7 p63KO) of genes connected to a p63-dependent H3K27me3 region (left panel, red), both p63 and a p63-dependent H3K27me3 region (left panel, purple), or a morphogen-dependent (morph-dep) ATAC site (right panel, green) compared to all protein-coding genes (left and right panels, black). Genes connected to a p63-dependent H3K27me3 region or both p63 and a p63-dependent H3K27me3 region are not significantly differentially regulated relative to all genes. Genes connected to a morph-dependent ATAC region are significantly more likely to be negatively regulated by p63 compared to all genes. n is the number of genes, two-sided test. c, FDR of the change in strength of connectivity in high-confidence cohesin contacts between various cell types. d, Scatterplots of changes in connectivity strength of high-confidence cohesin contacts between various cell types; red depicts >2-fold change with P < 0.05, while blue depicts <–2-fold change with P < 0.05, in wild-type cells. CPM, counts per million. glmQLFit was performed, which builds a generalized linear model and then estimates the quasi-likelihood dispersion from the deviance.

  8. Supplementary Figure 8 The epigenetic landscape at the TFAP2C locus.

    a, TFAP2C regulation is both morphogen and p63 dependent, n = 2. b, At the TFAP2C locus, within 400 kb, there is one p63 binding site, one morphogen- and p63-dependent ATAC-seq peak, and one p63-dependent H3K27me3 region (raw signal visualized by IGV tracks, n = 2). Cohesin HiChIP shows that these elements are highly connected upon morphogen treatment and p63 presence (n = 3). The four virtual 4C plots represent interactions from four viewpoints within this locus, and these viewpoints are labeled in the top left corner of each graph and highlighted in gray. c, Schematics to represent the different chromatin connections present at the TFAP2C locus in all four cellular contexts. d, The ATAC day 7 peak was deleted using CRISPR–Cas9 to generate a heterozygous knockout (ATAC-KO) for the region downstream of TFAP2C and to determine the effects of its loss on TFAP2C expression. Immunofluorescence analysis reveals that loss of the ATAC day 7 peak results in a significant decrease in TFAP2C expression at day 7 (*P = 0.04 from three independent images). Error bars represent s.e.m. Scale bar, 20 μm.

  9. Supplementary Figure 9 UMI-4C validation of the cohesin HiChIP.

    a, Virtual 4C comparison of the UMI-4C data and the cohesin HiChIP data in the day 7 p63WT and day 7 p63KO cell lines. The left half of the panel depicts the UMI-4C with the following three primer viewpoints (indicated by the dotted line): the TSS, the p63 binding site, and the ATAC day 7 peak at the TFAP2C locus. The data were normalized to the number of valid reads per locus and the gray shading represents s.e.m. from NextSeq replicates (n = 2). Sequencing depth was comparable between the two cell types displayed. The right panel depicts the Virtual 4C plots of HiChIP and shows similar long-range interactions to those detected using UMI-4C. b, UMI-4C viewpoint primers used to detect long-range interactions. All DS primers were synthesized with the Illumina prefix listed and the universal primer was used in both rounds of PCR as the reverse primer. TruSeq-indexed adaptors 3–6 were used in this study.

  10. Supplementary Figure 10 A 5-bp point mutation within the p63 binding site disrupts p63-mediated regulation of TFAP2C expression.

    a, The p63 binding site was mutated using CRISPR–Cas9 and homology-directed repair techniques to disrupt p63 binding (p63BSPM). The two overlapping p63 motifs within the 520-bp BSKO region were targeted with two gRNAs to mutate the four highlighted nucleotides (*)—the most highly conserved nucleotides within the canonical predicted p63 binding motif. The chromatogram depicts the sequence of the BSPM cell line and the mutated base pairs are indicated by asterisks. An EcoRI site was engineered in at the fifth highlighted base pair and this new sequence does not contain a predicted p63 binding motif. b, Disruption of the p63 binding site leads to a significant increase in TFAP2C expression similar to the levels seen in day 7 p63BSKO cells. Relative pixel intensity was calculated from three independent images and error bars represent s.e.m. (***P < 0.005; NS, not significant). Scale bar, 20 μm. c, qRT–PCR reveals that TFAP2C mRNA levels are significantly increased in the p63BSPM line (***P < 0.005) relative to day 7 p63WT cells. Error bars represent s.e.m., n = 3. d, ChIP–qPCR for p63 at the TFAP2C locus shows that disruption of the p63 binding site (p63BS) results in a significant decrease in p63 binding (***P = 0.00014) at this region (n = 2). This decrease in binding results in a loss of TFAP2C regulation. The graph depicts signal relative to input and error bars represent s.e.m.

  11. Supplementary Figure 11 Full scans of western blots referenced in the figures. a, Expression of p63 upon different morphogen treatments.

    b, Western blot validation of the engineered cell lines. Blots show p63 and GAPDH expression. The fourth column of the right blots depicts p63 expression in the p63BSKO line, corresponding to Fig. 4c. Blots for K18 expression corresponding to Supplementary Fig. 2e are also shown. c, Levels of H3K27me3 and pan-H3 nuclear loading control corresponding to Supplementary Fig. 3d. Protein levels of Ezh2 are also depicted. All of the above blots represent n = 3.

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https://doi.org/10.1038/s41588-018-0263-0