UTX is a chromatin modifier required for development and neural lineage specification, but how it controls these biological processes is unclear. To determine the molecular mechanisms of UTX, we identified novel UTX protein interaction partners. Here we show that UTX and 53BP1 directly interact and co-occupy promoters in human embryonic stem cells and differentiating neural progenitor cells. Human 53BP1 contains a UTX-binding site that diverges from its mouse homolog by 41%, and disruption of the 53BP1–UTX interaction abrogated human, but not mouse, neurogenesis in vitro. The 53BP1–UTX interaction is required to upregulate key neurodevelopmental genes during the differentiation of human embryonic stem cells into neurons or into cortical organoids. 53BP1 promotes UTX chromatin binding, and in turn H3K27 modifications and gene activation, at a subset of genomic regions, including neurogenic genes. Overall, our data suggest that the 53BP1–UTX interaction supports the activation of key genes required for human neurodevelopment.

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Code availability

Bash script for ChIP-seq is available from figshare https://doi.org/10.6084/m9.figshare.7411835.

Data availability

All sequencing data have been deposited in the Gene Expression Omnibus with the accession code GSE108116. Data that support the findings of this study are available from the corresponding author upon reasonable request.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


  1. 1.

    Wang, C. et al. UTX regulates mesoderm differentiation of embryonic stem cells independent of H3K27 demethylase activity. Proc. Natl Acad. Sci. USA 109, 15324–15329 (2012).

  2. 2.

    Welstead, G. G. et al. X-linked H3K27me3 demethylase Utx is required for embryonic development in a sex-specific manner. Proc. Natl Acad. Sci. USA 109, 13004–13009 (2012).

  3. 3.

    Guo, C. et al. Global identification of MLL2-targeted loci reveals MLL2’s role in diverse signaling pathways. Proc. Natl Acad. Sci. USA 109, 17603–17608 (2012).

  4. 4.

    Hong, S. et al. Identification of JmjC domain-containing UTX and JMJD3 as histone H3 lysine 27 demethylases. Proc. Natl Acad. Sci. USA 104, 18439–18444 (2007).

  5. 5.

    Tie, F., Banerjee, R., Conrad, P. A., Scacheri, P. C. & Harte, P. J. Histone demethylase UTX and chromatin remodeler BRM bind directly to CBP and modulate acetylation of histone H3 lysine 27. Mol. Cell. Biol. 32, 2323–2334 (2012).

  6. 6.

    Miller, S. A., Mohn, S. E. & Weinmann, A. S. Jmjd3 and UTX play a demethylase-independent role in chromatin remodeling to regulate T-box family member-dependent gene expression. Mol. Cell 40, 594–605 (2010).

  7. 7.

    Vandamme, J. et al. The C. elegans H3K27 demethylase UTX-1 is essential for normal development, independent of its enzymatic activity. PLoS Genet. 8, e1002647 (2012).

  8. 8.

    Shpargel, K. B., Starmer, J., Wang, C., Ge, K. & Magnuson, T. UTX-guided neural crest function underlies craniofacial features of Kabuki syndrome. Proc. Natl Acad. Sci. USA 114, E9046–E9055 (2017).

  9. 9.

    Petruk, S. et al. Delayed accumulation of H3K27me3 on nascent DNA is essential for recruitment of transcription factors at early stages of stem cell differentiation. Mol. Cell 66, 247–257.e5 (2017).

  10. 10.

    Wang, S. P. et al. A UTX-MLL4-p300 transcriptional regulatory network coordinately shapes active enhancer landscapes for eliciting transcription. Mol. Cell 67, 308–321.e6 (2017).

  11. 11.

    Gage, F. H. & Temple, S. Neural stem cells: generating and regenerating the brain. Neuron 80, 588–601 (2013).

  12. 12.

    Panier, S. & Boulton, S. J. Double-strand break repair: 53BP1 comes into focus. Nat. Rev. Mol. Cell Biol. 15, 7–18 (2014).

  13. 13.

    Ward, I. M., Minn, K., van Deursen, J. & Chen, J. p53 Binding protein 53BP1 is required for DNA damage responses and tumor suppression in mice. Mol. Cell. Biol. 23, 2556–2563 (2003).

  14. 14.

    Cuella-Martin, R. et al. 53BP1 integrates DNA repair and p53-dependent cell fate decisions via distinct mechanisms. Mol. Cell 64, 51–64 (2016).

  15. 15.

    Puc, J., Aggarwal, A. K. & Rosenfeld, M. G. Physiological functions of programmed DNA breaks in signal-induced transcription. Nat. Rev. Mol. Cell Biol. 18, 471–476 (2017).

  16. 16.

    Bunch, H. et al. Transcriptional elongation requires DNA break-induced signalling. Nat. Commun. 6, 10191 (2015).

  17. 17.

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

  18. 18.

    Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).

  19. 19.

    Kuo, L. J. & Yang, L. X. Gamma-H2AX—a novel biomarker for DNA double-strand breaks. In Vivo 22, 305–309 (2008).

  20. 20.

    Kadoshima, T. et al. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell-derived neocortex. Proc. Natl Acad. Sci. USA 110, 20284–20289 (2013).

  21. 21.

    Lancaster, M. A. & Knoblich, J. A. Generation of cerebral organoids from human pluripotent stem cells. Nat. Protoc. 9, 2329–2340 (2014).

  22. 22.

    Brose, K. et al. Slit proteins bind Robo receptors and have an evolutionarily conserved role in repulsive axon guidance. Cell 96, 795–806 (1999).

  23. 23.

    Carl, M., Loosli, F. & Wittbrodt, J. Six3 inactivation reveals its essential role for the formation and patterning of the vertebrate eye. Development 129, 4057–4063 (2002).

  24. 24.

    Lagutin, O. V. et al. Six3 repression of Wnt signaling in the anterior neuroectoderm is essential for vertebrate forebrain development. Genes Dev. 17, 368–379 (2003).

  25. 25.

    Burgold, T. et al. The histone H3 lysine 27-specific demethylase Jmjd3 is required for neural commitment. PLoS One 3, e3034 (2008).

  26. 26.

    Jepsen, K. et al. SMRT-mediated repression of an H3K27 demethylase in progression from neural stem cell to neuron. Nature 450, 415–419 (2007).

  27. 27.

    Park, D. H. et al. Activation of neuronal gene expression by the JMJD3 demethylase is required for postnatal and adult brain neurogenesis. Cell Rep. 8, 1290–1299 (2014).

  28. 28.

    Iwabuchi, K., Bartel, P.L., Li, B., Marraccino, R. & Fields, S. Two cellular proteins that bind to wild-type butnot mutant p53.Proc. Natl Acad. Sci. USA 91, 6098–6102 (1994).

  29. 29.

    Madabhushi, R. et al. Activity-induced DNA breaks govern the expression of neuronal early-response genes. Cell 161, 1592–1605 (2015).

  30. 30.

    Schwer, B. et al. Transcription-associated processes cause DNA double-strand breaks and translocations in neural stem/progenitor cells. Proc. Natl Acad. Sci. USA 113, 2258–2263 (2016).

  31. 31.

    Wei, P. C. et al. Long neural genes harbor recurrent DNA break clusters in neural stem/progenitor cells. Cell 164, 644–655 (2016).

  32. 32.

    Wang, X. et al. JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy. Mol. Cell. Proteomics 13, 3663–3673 (2014).

  33. 33.

    Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

  34. 34.

    Landt, S. G. et al. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 22, 1813–1831 (2012).

  35. 35.

    Kharchenko, P. V., Tolstorukov, M. Y. & Park, P. J. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat. Biotechnol. 26, 1351–1359 (2008).

  36. 36.

    Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

  37. 37.

    Zhang, Y., Shin, H., Song, J. S., Lei, Y. & Liu, X. S. Identifying positioned nucleosomes with epigenetic marks in human from ChIP-Seq. BMC Genomics 9, 537 (2008).

  38. 38.

    Zang, C. et al. A clustering approach for identification of enriched domains from histone modification ChIP-Seq data. Bioinformatics 25, 1952–1958 (2009).

  39. 39.

    Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).

  40. 40.

    Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

  41. 41.

    Aldiri, I. et al. The dynamic epigenetic landscape of the retina during development, reprogramming, and tumorigenesis. Neuron 94, 550–568.e10 (2017).

  42. 42.

    Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).

  43. 43.

    Robinson, M. D. & Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 11, R25 (2010).

  44. 44.

    Downing, J. R. et al. The Pediatric Cancer Genome Project. Nat. Genet. 44, 619–622 (2012).

  45. 45.

    Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

  46. 46.

    Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).

  47. 47.

    Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

  48. 48.

    Liberzon, A. et al. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).

  49. 49.

    Miller, J. A. et al. Transcriptional landscape of the prenatal human brain. Nature 508, 199–206 (2014).

  50. 50.

    Leek, J. T., Johnson, W. E., Parker, H. S., Jaffe, A. E. & Storey, J. D. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28, 882–883 (2012).

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The authors thank M. A. Dyer for helpful discussions; X. Cao, and Y.-G. Han for helpful comments; A. Andersen and C. Guess for editing the manuscript; J. Houston for cell sorting; S. Olsen and D. Roeber for sequencing samples; A. Nityanandam for optimizing the cortical organoid protocol and technical advice; V. Stewart for mouse embryo injection; S. Porter and S. Miller for mi-seq analysis of in-frame clones and mouse embryos; L. Ding and M. Rusch for sequencing mapping; V. Frohlich, J. Klein, L. Griffiths, J. Peters, L. Milburn, and Y. Li for experimental assistance. M.E. is funded by the NIH (1F32HD093276). J.P. is funded by American Lebanese Syrian Associated Charities and NIH (R01GM114260, R01AG047928, and R01AG053987). J.C.P is funded by American Lebanese Syrian Associated Charities and American Cancer Society (132096-RSG-18-032-01-DDC).

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Author notes

  1. These authors contributed equally: Xiaoyang Yang, Beisi Xu.


  1. Department of Developmental Neurobiology and Division of Developmental Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    • Xiaoyang Yang
    • , Brett Mulvey
    • , Myron Evans
    • , Samuel Jordan
    • , Arishna Patel
    •  & Jamy C. Peng
  2. Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    • Beisi Xu
    • , Yong-Dong Wang
    •  & Yiping Fan
  3. Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    • Vishwajeeth Pagala
    •  & Junmin Peng


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X.Y.: IP-WB, ChIP, 53BP1-KO, 53BP1 in-frame deletions, cortical organoids. B.X.: all seq analysis except whole-genome sequencing. B.M.: initial IP for mass spectrometry, IP-WB, and UTX mutant. M.E.: 53bp1 mutant analyses. S.J.: recombinant protein co-IP-WB. Y.-D.W.: whole-genome sequence analysis. V.P. and J.P.: proteomic analyses. A.P.: transcript profilings and image quantification. Y.F.: B.X. supervision. J.C.P: project design, ChIP, IP, data analysis, and manuscript writing.

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The authors declare no competing interests.

Corresponding author

Correspondence to Jamy C. Peng.

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