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ABSTRACT Coincident transcription and DNA replication causes replication stress and genome instability. Rapidly dividing mouse pluripotent stem cells are highly transcriptionally active and

experience elevated replication stress, yet paradoxically maintain genome integrity. Here, we study FOXD3, a transcriptional repressor enriched in pluripotent stem cells, and show that its

repression of transcription upon S phase entry is critical to minimizing replication stress and preserving genome integrity. Acutely deleting _Foxd3_ leads to immediate replication stress,

G2/M phase arrest, genome instability and p53-dependent apoptosis. FOXD3 binds near highly transcribed genes during S phase entry, and its loss increases the expression of these genes.

Transient inhibition of RNA polymerase II in S phase reduces observed replication stress and cell cycle defects. Loss of FOXD3-interacting histone deacetylases induces replication stress,

while transient inhibition of histone acetylation opposes it. These results show how a transcriptional repressor can play a central role in maintaining genome integrity through the transient

inhibition of transcription during S phase, enabling faithful DNA replication. Access through your institution Buy or subscribe This is a preview of subscription content, access via your

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subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS HISTONE H1 FACILITATES RESTORATION OF H3K27ME3 DURING DNA REPLICATION BY CHROMATIN COMPACTION

Article Open access 10 July 2023 CHD1 PROTECTS GENOME INTEGRITY AT PROMOTERS TO SUSTAIN HYPERTRANSCRIPTION IN EMBRYONIC STEM CELLS Article Open access 11 August 2021 H3K4ME3 REGULATES RNA

POLYMERASE II PROMOTER-PROXIMAL PAUSE-RELEASE Article Open access 01 March 2023 DATA AVAILABILITY The 4SU-seq, streptavidin pulldown sequencing, CUT&Tag and MULTI-seq data have been

deposited in the Gene Expression Omnibus (GEO) database under accession number GSE183420. Mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE

repository under accession number PXD035284. The following GEO datasets were analyzed in this study: ATAC-seq (GSE93147) and ChIP–seq for OCT4, SOX2 and NANOG (GSE56312), H3K27ac (GSE93147),

Pol II (GSE23943) and γH2AX (GSE69143). The University of Alabama at Birmingham Cancer data analysis portal is accessible through https://ualcan.path.uab.edu. The STRING database is

accessible through https://string-db.org. Source data are provided with this paper. CODE AVAILABILITY No custom code was developed in this study. REFERENCES * Liu, L., Michowski, W.,

Kolodziejczyk, A. & Sicinski, P. The cell cycle in stem cell proliferation, pluripotency and differentiation. _Nat. Cell Biol._ 21, 1060–1067 (2019). Article  CAS  PubMed  PubMed Central

  Google Scholar  * Ciemerych, M. A. & Sicinski, P. Cell cycle in mouse development. _Oncogene_ 24, 2877–2898 (2005). Article  CAS  PubMed  Google Scholar  * Lawson, K. A., Meneses, J.

J. & Pedersen, R. A. Clonal analysis of epiblast fate during germ layer formation in the mouse embryo. _Development_ 113, 891–911 (1991). Article  CAS  PubMed  Google Scholar  * Snow, M.

H. L. Gastrulation in the mouse: growth and regionalization of the epiblast. _Development_ 42, 293–303 (1977). Article  Google Scholar  * Efroni, S. et al. Global transcription in

pluripotent embryonic stem cells. _Cell Stem Cell_ 2, 437–447 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * Percharde, M., Bulut-Karslioglu, A. & Ramalho-Santos, M.

Hypertranscription in development, stem cells, and regeneration. _Dev. Cell_ 40, 9–21 (2017). Article  CAS  PubMed  Google Scholar  * Solter, D., Škreb, N. & Damjanov, I. Cell cycle

analysis in the mouse egg-cylinder. _Exp. Cell. Res._ 64, 331–334 (1971). Article  CAS  PubMed  Google Scholar  * Ahuja, A. K. et al. A short G1 phase imposes constitutive replication stress

and fork remodelling in mouse embryonic stem cells. _Nat. Commun._ 7, 10660 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Liu, L. et al. G1 cyclins link proliferation,

pluripotency and differentiation of embryonic stem cells. _Nat. Cell Biol._ 19, 177–188 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hamperl, S., Bocek, M. J., Saldivar,

J. C., Swigut, T. & Cimprich, K. A. Transcription–replication conflict orientation modulates R-loop levels and activates distinct DNA damage responses. _Cell_ 170, 774–786 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar  * García-Muse, T. & Aguilera, A. Transcription–replication conflicts: how they occur and how they are resolved. _Nat. Rev. Mol. Cell

Biol._ 17, 553–563 (2016). Article  PubMed  Google Scholar  * Saldivar, J. C. et al. An intrinsic S/G2 checkpoint enforced by ATR. _Science_ 361, 806–810 (2018). Article  CAS  PubMed 

PubMed Central  Google Scholar  * Saldivar, J. C., Cortez, D. & Cimprich, K. A. The essential kinase ATR: ensuring faithful duplication of a challenging genome. _Nat. Rev. Mol. Cell

Biol._ 18, 622–636 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Zeman, M. K. & Cimprich, K. A. Causes and consequences of replication stress. _Nat. Cell Biol._ 16, 2–9

(2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Banáth, J. P. et al. Explanation for excessive DNA single-strand breaks and endogenous repair foci in pluripotent mouse

embryonic stem cells. _Exp. Cell. Res._ 315, 1505–1520 (2009). Article  PubMed  Google Scholar  * Chuykin, I. A., Lianguzova, M. S., Pospelova, T. V. & Pospelov, V. A. Activation of DNA

damage response signaling in mouse embryonic stem cells. _Cell Cycle_ 7, 2922–2928 (2008). Article  CAS  PubMed  Google Scholar  * Turinetto, V. et al. High basal γH2AX levels sustain

self-renewal of mouse embryonic and induced pluripotent stem cells. _Stem Cells_ 30, 1414–1423 (2012). Article  CAS  PubMed  Google Scholar  * Ziegler-Birling, C., Helmrich, A., Tora, L.

& Torres-Padilla, M.-E. Distribution of p53 binding protein 1 (53BP1) and phosphorylated H2A.X during mouse preimplantation development in the absence of DNA damage. _Int. J. Dev. Biol._

53, 1003–1011 (2009). Article  CAS  PubMed  Google Scholar  * Choi, E.-H., Yoon, S. & Kim, K. P. Combined ectopic expression of homologous recombination factors promotes embryonic stem

cell differentiation. _Mol. Ther._ 26, 1154–1165 (2018). Article  CAS  PubMed  PubMed Central  Google Scholar  * Cervantes, R. B., Stringer, J. R., Shao, C., Tischfield, J. A. &

Stambrook, P. J. Embryonic stem cells and somatic cells differ in mutation frequency and type. _Proc. Natl Acad. Sci. USA_ 99, 3586–3590 (2002). Article  CAS  PubMed  PubMed Central  Google

Scholar  * Sutton, J. et al. Genesis, a winged helix transcriptional repressor with expression restricted to embryonic stem cells. _J. Biol. Chem._ 271, 23126–23133 (1996). Article  CAS 

PubMed  Google Scholar  * Labosky, P. A. & Kaestner, K. H. The winged helix transcription factor _Hfh2_ is expressed in neural crest and spinal cord during mouse development. _Mech.

Dev._ 76, 185–190 (1998). Article  CAS  PubMed  Google Scholar  * Hromas, R. et al. Genesis, a winged helix transcriptional repressor, has embryonic expression limited to the neural crest,

and stimulates proliferation in vitro in a neural development model. _Cell Tissue Res._ 297, 371–382 (1999). Article  CAS  PubMed  Google Scholar  * Dottori, M., Gross, M. K., Labosky, P.

& Goulding, M. The winged-helix transcription factor Foxd3 suppresses interneuron differentiation and promotes neural crest cell fate. _Development_ 128, 4127–4138 (2001). Article  CAS 

PubMed  Google Scholar  * Pohl, B. S. & Knöchel, W. Overexpression of the transcriptional repressor FoxD3 prevents neural crest formation in _Xenopus_ embryos. _Mech. Dev._ 103, 93–106

(2001). Article  CAS  PubMed  Google Scholar  * Steiner, A. B. et al. FoxD3 regulation of Nodal in the Spemann organizer is essential for _Xenopus_ dorsal mesoderm development. _Development_

133, 4827–4838 (2006). Article  CAS  PubMed  Google Scholar  * Krishnakumar, R. et al. FOXD3 regulates pluripotent stem cell potential by simultaneously initiating and repressing enhancer

activity. _Cell Stem Cell_ 18, 104–117 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Respuela, P. et al. Foxd3 promotes exit from naive pluripotency through enhancer

decommissioning and inhibits germline specification. _Cell Stem Cell_ 18, 118–133 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hanna, L. A., Foreman, R. K., Tarasenko, I.

A., Kessler, D. S. & Labosky, P. A. Requirement for Foxd3 in maintaining pluripotent cells of the early mouse embryo. _Genes Dev._ 16, 2650–2661 (2002). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Liu, Y. & Labosky, P. A. Regulation of embryonic stem cell self-renewal and pluripotency by Foxd3. _Stem Cells_ 26, 2475–2484 (2008). Article  CAS  PubMed 

Google Scholar  * Pijuan-Sala, B. et al. A single-cell molecular map of mouse gastrulation and early organogenesis. _Nature_ 566, 490–495 (2019). Article  CAS  PubMed  PubMed Central  Google

Scholar  * Tabula Sapiens Consortium et al. The Tabula Sapiens: a multiple-organ, single-cell transcriptomic atlas of humans. _Science_ 376, eabl4896 (2022). Article  Google Scholar  *

Paglini, M. G. & Rovasio, R. A. Cell cycle of neural crest cells in the early migratory stage in vivo. _Cell Prolif._ 27, 571–578 (1994). Article  Google Scholar  * Katsuta, E. et al.

_H2AX_ mRNA expression reflects DNA repair, cell proliferation, metastasis, and worse survival in breast cancer. _Am. J. Cancer Res._ 12, 793–804 (2022). CAS  PubMed  PubMed Central  Google

Scholar  * Bonner, W. M. et al. γH2AX and cancer. _Nat. Rev. Cancer_ 8, 957–967 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * Niwa, H., Miyazaki, J. & Smith, A. G.

Quantitative expression of Oct-3/4 defines differentiation, dedifferentiation or self-renewal of ES cells. _Nat. Genet._ 24, 372–376 (2000). Article  CAS  PubMed  Google Scholar  *

Masamsetti, V. P. et al. Replication stress induces mitotic death through parallel pathways regulated by WAPL and telomere deprotection. _Nat. Commun._ 10, 4224 (2019). Article  PubMed 

PubMed Central  Google Scholar  * Mankouri, H. W., Huttner, D. & Hickson, I. D. How unfinished business from S-phase affects mitosis and beyond. _EMBO J._ 32, 2661–2671 (2013). Article 

CAS  PubMed  PubMed Central  Google Scholar  * Lukas, C. et al. 53BP1 nuclear bodies form around DNA lesions generated by mitotic transmission of chromosomes under replication stress. _Nat.

Cell Biol._ 13, 243–253 (2011). Article  CAS  PubMed  Google Scholar  * van der Heijden, T. et al. Real-time assembly and disassembly of human RAD51 filaments on individual DNA molecules.

_Nucleic Acids Res._ 35, 5646–5657 (2007). Article  PubMed  PubMed Central  Google Scholar  * Ma, C. J., Gibb, B., Kwon, Y., Sung, P. & Greene, E. C. Protein dynamics of human RPA and

RAD51 on ssDNA during assembly and disassembly of the RAD51 filament. _Nucleic Acids Res._ 45, 749–761 (2017). Article  CAS  PubMed  Google Scholar  * Despras, E., Daboussi, F., Hyrien, O.,

Marheineke, K. & Kannouche, P. L. ATR/Chk1 pathway is essential for resumption of DNA synthesis and cell survival in UV-irradiated XP variant cells. _Hum. Mol. Genet._ 19, 1690–1701

(2010). Article  CAS  PubMed  Google Scholar  * Atashpaz, S. et al. ATR expands embryonic stem cell fate potential in response to replication stress. _eLife_ 9, e54756 (2020). Article  CAS 

PubMed  PubMed Central  Google Scholar  * Nakatani, T. et al. DNA replication fork speed underlies cell fate changes and promotes reprogramming. _Nat. Genet._ 54, 318–327 (2022). Article 

CAS  PubMed  PubMed Central  Google Scholar  * Macfarlan, T. S. et al. Embryonic stem cell potency fluctuates with endogenous retrovirus activity. _Nature_ 487, 57–63 (2012). Article  CAS 

PubMed  PubMed Central  Google Scholar  * Choi, Y. J. et al. Deficiency of microRNA miR-34a expands cell fate potential in pluripotent stem cells. _Science_ 355, eaag1927 (2017). Article 

PubMed  PubMed Central  Google Scholar  * Buecker, C. et al. Reorganization of enhancer patterns in transition from naive to primed pluripotency. _Cell Stem Cell_ 14, 838–853 (2014). Article

  CAS  PubMed  PubMed Central  Google Scholar  * Galonska, C., Ziller, M. J., Karnik, R. & Meissner, A. Ground state conditions induce rapid reorganization of core pluripotency factor

binding before global epigenetic reprogramming. _Cell Stem Cell_ 17, 462–470 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * Flynn, R. A. et al. 7SK–BAF axis controls

pervasive transcription at enhancers. _Nat. Struct. Mol. Biol._ 23, 231–238 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * McGinnis, C. S. et al. MULTI-seq: sample

multiplexing for single-cell RNA sequencing using lipid-tagged indices. _Nat. Methods_ 16, 619–626 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  * Clouaire, T. et al.

Comprehensive mapping of histone modifications at DNA double-strand breaks deciphers repair pathway chromatin signatures. _Mol. Cell_ 72, 250–262 (2018). Article  CAS  PubMed  PubMed Central

  Google Scholar  * Kim, D. I. et al. An improved smaller biotin ligase for BioID proximity labeling. _Mol. Biol. Cell_ 27, 1188–1196 (2016). Article  CAS  PubMed  PubMed Central  Google

Scholar  * Cole, M. F., Johnstone, S. E., Newman, J. J., Kagey, M. H. & Young, R. A. Tcf3 is an integral component of the core regulatory circuitry of embryonic stem cells. _Genes Dev._

22, 746–755 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * van den Berg, D. L. C. et al. An Oct4-centered protein interaction network in embryonic stem cells. _Cell Stem

Cell_ 6, 369–381 (2010). Article  PubMed  PubMed Central  Google Scholar  * Guo, Y. et al. The embryonic stem cell transcription factors Oct-4 and FoxD3 interact to regulate

endodermal-specific promoter expression. _Proc. Natl Acad. Sci. USA_ 99, 3663–3667 (2002). Article  CAS  PubMed  PubMed Central  Google Scholar  * Chen, Y.-H. et al. Transcription shapes DNA

replication initiation and termination in human cells. _Nat. Struct. Mol. Biol._ 26, 67–77 (2019). Article  CAS  PubMed  Google Scholar  * Ma, Y., Kanakousaki, K. & Buttitta, L. How the

cell cycle impacts chromatin architecture and influences cell fate. _Front. Genet._ 6, 19 (2015). Article  PubMed  PubMed Central  Google Scholar  * Ginno, P. A., Burger, L., Seebacher, J.,

Iesmantavicius, V. & Schübeler, D. Cell cycle-resolved chromatin proteomics reveals the extent of mitotic preservation of the genomic regulatory landscape. _Nat. Commun._ 9, 4048

(2018). Article  PubMed  PubMed Central  Google Scholar  * Tichy, E. D. et al. Mouse embryonic stem cells, but not somatic cells, predominantly use homologous recombination to repair

double-strand DNA breaks. _Stem Cells Dev._ 19, 1699–1711 (2010). Article  CAS  PubMed  PubMed Central  Google Scholar  * Teng, L., Mundell, N. A., Frist, A. Y., Wang, Q. & Labosky, P.

A. Requirement for Foxd3 in the maintenance of neural crest progenitors. _Development_ 135, 1615–1624 (2008). Article  CAS  PubMed  Google Scholar  * Montero-Balaguer, M. et al. The mother

superior mutation ablates _foxd3_ activity in neural crest progenitor cells and depletes neural crest derivatives in zebrafish. _Dev. Dyn._ 235, 3199–3212 (2006). Article  CAS  PubMed 

Google Scholar  * Stewart, R. A. et al. Zebrafish _foxd3_ is selectively required for neural crest specification, migration and survival. _Dev. Biol._ 292, 174–188 (2006). Article  CAS 

PubMed  Google Scholar  * Lister, J. A. et al. Zebrafish Foxd3 is required for development of a subset of neural crest derivatives. _Dev. Biol._ 290, 92–104 (2006). Article  CAS  PubMed 

Google Scholar  * Xu, M. et al. FOXD3, frequently methylated in colorectal cancer, acts as a tumor suppressor and induces tumor cell apoptosis under ER stress via p53. _Carcinogenesis_ 41,

1253–1262 (2020). Article  CAS  PubMed  Google Scholar  * Li, D. et al. FOXD3 is a novel tumor suppressor that affects growth, invasion, metastasis and angiogenesis of neuroblastoma.

_Oncotarget_ 4, 2021–2044 (2013). Article  PubMed  PubMed Central  Google Scholar  * Yan, J.-H., Zhao, C.-L., Ding, L.-B. & Zhou, X. FOXD3 suppresses tumor growth and angiogenesis in

non-small cell lung cancer. _Biochem. Biophys. Res. Commun._ 466, 111–116 (2015). Article  CAS  PubMed  Google Scholar  * Chen, A. F. et al. GRHL2-dependent enhancer switching maintains a

pluripotent stem cell transcriptional subnetwork after exit from naive pluripotency. _Cell Stem Cell_ 23, 226–238 (2018). Article  CAS  PubMed  PubMed Central  Google Scholar  * Marks, H. et

al. The transcriptional and epigenomic foundations of ground state pluripotency. _Cell_ 149, 590–604 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Dovey, O. M., Foster, C.

T. & Cowley, S. M. Histone deacetylase 1 (HDAC1), but not HDAC2, controls embryonic stem cell differentiation. _Proc. Natl Acad. Sci. USA_ 107, 8242–8247 (2010). Article  CAS  PubMed 

PubMed Central  Google Scholar  * Beard, C., Hochedlinger, K., Plath, K., Wutz, A. & Jaenisch, R. Efficient method to generate single-copy transgenic mice by site-specific integration in

embryonic stem cells. _Genesis_ 44, 23–28 (2006). Article  CAS  PubMed  Google Scholar  * Freimer, J. W., Hu, T. J. & Blelloch, R. Decoupling the impact of microRNAs on translational

repression versus RNA degradation in embryonic stem cells. _eLife_ 7, e38014 (2018). Article  PubMed  PubMed Central  Google Scholar  * Kaya-Okur, H. S., Janssens, D. H., Henikoff, J. G.,

Ahmad, K. & Henikoff, S. Efficient low-cost chromatin profiling with CUT&Tag. _Nat. Protoc._ 15, 3264–3283 (2020). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kaya-Okur,

H. S. et al. CUT&Tag for efficient epigenomic profiling of small samples and single cells. _Nat. Commun._ 10, 1930 (2019). Article  PubMed  PubMed Central  Google Scholar  * Dobin, A. et

al. STAR: ultrafast universal RNA-seq aligner. _Bioinformatics_ 29, 15–21 (2013). Article  CAS  PubMed  Google Scholar  * Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient

general purpose program for assigning sequence reads to genomic features. _Bioinformatics_ 30, 923–930 (2014). Article  CAS  PubMed  Google Scholar  * Robinson, M. D., McCarthy, D. J. &

Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. _Bioinformatics_ 26, 139–140 (2010). Article  CAS  PubMed  Google Scholar  *

Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. _Nucleic Acids Res._ 44, W160–W165 (2016). Article  PubMed  PubMed Central  Google Scholar  *

Jin, Y., Tam, O. H., Paniagua, E. & Hammell, M. TEtranscripts: a package for including transposable elements in differential expression analysis of RNA-seq datasets. _Bioinformatics_ 31,

3593–3599 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * 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). Article  PubMed  PubMed Central  Google Scholar  * Ewels, P. A. et al. The nf-core framework for community-curated bioinformatics pipelines. _Nat.

Biotechnol._ 38, 276–278 (2020). Article  CAS  PubMed  Google Scholar  * Liu, X. et al. In situ capture of chromatin interactions by biotinylated dCas9. _Cell_ 170, 1028–1043 (2017). Article

  CAS  PubMed  PubMed Central  Google Scholar  * Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. _Nat. Methods_ 9, 357–359 (2012). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Danecek, P. et al. Twelve years of SAMtools and BCFtools. _Gigascience_ 10, giab008 (2021). Article  PubMed  PubMed Central  Google Scholar  * Zhang, Y. et al.

Model-based analysis of ChIP–seq (MACS). _Genome Biol._ 9, R137 (2008). Article  PubMed  PubMed Central  Google Scholar  * Li, Q., Brown, J. B., Huang, H. & Bickel, P. J. Measuring

reproducibility of high-throughput experiments. _Ann. Appl. Stat._ 5, 1752–1779 (2011). Article  Google Scholar  * Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities

for comparing genomic features. _Bioinformatics_ 26, 841–842 (2010). Article  CAS  PubMed  PubMed Central  Google Scholar  * 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). Article  CAS  PubMed  PubMed Central  Google Scholar  *

Pohl, A. & Beato, M. bwtool: a tool for bigWig files. _Bioinformatics_ 30, 1618–1619 (2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hao, Y. et al. Integrated analysis of

multimodal single-cell data. _Cell_ 184, 3573–3587 (2021). Article  CAS  PubMed  PubMed Central  Google Scholar  * Lun, A. T. L., McCarthy, D. J. & Marioni, J. C. A step-by-step

workflow for low-level analysis of single-cell RNA-seq data with Bioconductor. _F1000Res._ 5, 2122 (2016). PubMed  PubMed Central  Google Scholar  * Ge, S. X., Jung, D. & Yao, R.

ShinyGO: a graphical gene-set enrichment tool for animals and plants. _Bioinformatics_ 36, 2628–2629 (2020). Article  CAS  PubMed  Google Scholar  * Chandrashekar, D. S. et al. UALCAN: a

portal for facilitating tumor subgroup gene expression and survival analyses. _Neoplasia_ 19, 649–658 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Gu, Z., Eils, R. &

Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. _Bioinformatics_ 32, 2847–2849 (2016). Article  CAS  PubMed  Google Scholar  * Mootha, V. K.

et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. _Nat. Genet._ 34, 267–273 (2003). Article  CAS  PubMed  Google Scholar

  * 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).

Article  CAS  PubMed  PubMed Central  Google Scholar  * Szklarczyk, D. et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in

genome-wide experimental datasets. _Nucleic Acids Res._ 47, D607–D613 (2019). Article  CAS  PubMed  Google Scholar  * Huang, H. H. et al. Proteasome inhibitor-induced modulation reveals the

spliceosome as a specific therapeutic vulnerability in multiple myeloma. _Nat. Commun._ 11, 1931 (2020). Article  CAS  PubMed  PubMed Central  Google Scholar  * Cox, J. & Mann, M.

MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. _Nat. Biotechnol._ 26, 1367–1372 (2008). Article 

CAS  PubMed  Google Scholar  * Gierlinski, M., Gastaldello, F., Cole, C. & Barton, G. J. Proteus: an R package for downstream analysis of MaxQuant output. Preprint at _bioRxiv_

https://doi.org/10.1101/416511 (2018). * Bai, G. et al. HLTF promotes fork reversal, limiting replication stress resistance and preventing multiple mechanisms of unrestrained DNA synthesis.

_Mol. Cell_ 78, 1237–1251 (2020). Article  CAS  PubMed  PubMed Central  Google Scholar  * Fischer, M. Census and evaluation of p53 target genes. _Oncogene_ 36, 3943–3956 (2017). Article  CAS

  PubMed  PubMed Central  Google Scholar  Download references ACKNOWLEDGEMENTS We thank K. Cimprich for helpful discussions and consultation. We thank M. T. McManus for providing access to

equipment. We thank D. Lim, B. Schwer and B. Marsh for critical reading of the manuscript. Technical support by the University of California, San Francisco (UCSF), Parnassus Flow Cytometry

Core, The PCAT at UCSF and the UCSF Center for Advanced Technology is greatly appreciated. This publication includes data generated at the University of California, San Diego, IGM Genomics

Center using an Illumina NovaSeq 6000 that was purchased with funding from a National Institutes of Health SIG grant (S10 OD026929). This work was supported by the National Institute of

General Medical Sciences of the National Institutes of Health grant R01GM125089 (to R.B.) and the German Research Foundation Research Fellowship 363120021 (to D.G.). AUTHOR INFORMATION

Author notes * These authors contributed equally: Kayla Lenshoek, Ryan M. Boileau. AUTHORS AND AFFILIATIONS * The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research,

Center for Reproductive Sciences, University of California, San Francisco, San Francisco, CA, USA Deniz Gökbuget, Kayla Lenshoek, Ryan M. Boileau, Jonathan Bayerl, Diana J. Laird & 

Robert Blelloch * Department of Urology, University of California, San Francisco, San Francisco, CA, USA Deniz Gökbuget, Kayla Lenshoek, Ryan M. Boileau & Robert Blelloch * Helen Diller

Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA Deniz Gökbuget, Kayla Lenshoek, Ryan M. Boileau, Hector Huang, Arun P. Wiita & Robert

Blelloch * Department of Obstetrics, Gynecology and Reproductive Science, University of California, San Francisco, San Francisco, CA, USA Jonathan Bayerl & Diana J. Laird * Department of

Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA Hector Huang & Arun P. Wiita Authors * Deniz Gökbuget View author publications You can also search

for this author inPubMed Google Scholar * Kayla Lenshoek View author publications You can also search for this author inPubMed Google Scholar * Ryan M. Boileau View author publications You

can also search for this author inPubMed Google Scholar * Jonathan Bayerl View author publications You can also search for this author inPubMed Google Scholar * Hector Huang View author

publications You can also search for this author inPubMed Google Scholar * Arun P. Wiita View author publications You can also search for this author inPubMed Google Scholar * Diana J. Laird

View author publications You can also search for this author inPubMed Google Scholar * Robert Blelloch View author publications You can also search for this author inPubMed Google Scholar

CONTRIBUTIONS Conceptualization: D.G. and R.B. Methodology: D.G. Investigation: D.G., K.L., R.M.B., J.B. and H.H. Visualization: D.G. Software: D.G. Formal analysis: D.G. Resources: A.P.W.,

D.J.L. and R.B. Data curation: D.G. Funding acquisition: D.G. and R.B. Project administration: R.B. Supervision: D.G. and R.B. Writing, original draft: D.G. Writing, review and editing: D.G.

and R.B. CORRESPONDING AUTHOR Correspondence to Robert Blelloch. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION

_Nature Structural & Molecular Biology_ thanks David Gilbert, Duanqing Pei and Jianlong Wang for their contribution to the peer review of this work. Primary Handling Editors: Sara Osman,

Tiago Faial and Carolina Perdigoto, in collaboration with the _Nature Structural & Molecular Biology_ team. Peer reviewer reports are available. ADDITIONAL INFORMATION PUBLISHER’S NOTE

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 SINGLE CELL SEQUENCING DATA ANALYSIS

OF FOXD3 EXPRESSING CELLS IN EARLY MOUSE EMBRYOGENESIS AND ADULT HUMAN TISSUES. A,B, UMAP plots of single cell transcriptomes at different days during prenatal mouse development31 showing

identified cell populations (A) and _Foxd3_ mRNA level (B). Populations with high _Foxd3_ mRNA levels are highlighted in legend (cross). C,D, UMAP plots of single cell transcriptomes32 in

adult human stromal (C) and immune tissues (D) showing identified cell populations. E,F, Overlay of _FOXD3_ mRNA expression on UMAP plots from adult human stromal (E) and immune tissues (F)

shown in C and D, respectively. Source data EXTENDED DATA FIG. 2 COEXPRESSION ANALYSIS OF FOXD3 EXPRESSING CELLS IN EARLY MOUSE EMBRYOGENESIS. A, GO biological term analysis of transcripts

co-expressed with Foxd3 (see Methods). B, Protein interaction network analysis using STRING database with transcripts co-expressed with Foxd3. C, Violin plots of _H2afx_ mRNA levels in cells

with >1 normalized count of _Foxd3_ mRNA (Foxd3+) or <1 normalized count of _Foxd3_ mRNA (Foxd3−). Statistical test used: Wilcoxon rank sum test. ****_P_ < 0.0001. Source data

EXTENDED DATA FIG. 3 LOSS OF FOXD3 RESULTS IN INCREASED APOPTOSIS PRECEDED BY CELL CYCLE ARREST IN G2/M. A, Model and kinetics of FOXD3 loss following treatment of _Foxd3_iKO ESCs with 4HT

(T) versus EtOH (E) as measured by immunoblots. See quantifications of immunoblots in Fig. 1b. EtOH serves as solvent control. Triangles in model represent _loxP_ sites. Approximate location

of molecular weight marker shown. B, Flow cytometry measurement of fraction of cells positive for the apoptotic marker Annexin V after 14-, 24- and 48-hour treatment of _Foxd3_iKO cells

with 4HT versus EtOH (n = 3 independent cultures per treatment and timepoint). C,D, Time course of DNA content histogram comparisons (C) and quantification of cell cycle distributions (D) in

_Foxd3_iKO cells treated with 4HT or EtOH for 8, 14, 24 and 32 hours (n = 3 independent cultures per treatment and timepoint). E, Model (left) and kinetics of OCT4 loss following 16- and

24-hour treatment of _Oct4_tetOff ESCs with doxycycline (D) as measured by immunoblots (middle). Quantification of independent repeats relative to H2O (H) solvent control (right) (n = 2

independent cultures per treatment and timepoint). Approximate location of molecular weight marker shown. Mean and s.e.m. are shown (B,D,E). Statistical test used: Two-way ANOVA with Šidák

correction (B,D,E). *_P_ < 0.05,**_P_ < 0.01,***_P_ < 0.001,****_P_ < 0.0001 (B,D,E). Source data EXTENDED DATA FIG. 4 DIFFERENTIAL TRANSCRIPTION MEASUREMENTS USING 4SU-SEQ DATA

AT DIFFERENT TIMEPOINTS FOLLOWING TREATMENTS OF _FOXD3_IKO AND _OCT4_TETOFF CELLS. A, B, MA plots of _Foxd3_iKO (A) and _Oct4_tetOff (B) at shown hours of treatment. Genes with FDR < 0.05

shown in blue. p53 target genes101 with FDR < 0.05 are shown in red. Names of consistently differentially expressed genes in a are shown. C, Number of differentially expressed (FDR < 

0.05) genes shown for each treatment time and genotype. D, Top10 significant KEGG pathways for upregulated genes in _Foxd3_iKO at 24 hours of 4HT treatment. Statistical test used: Fisher’s

exact test (D). Source data EXTENDED DATA FIG. 5 ANALYSIS OF ROLE OF P53 AND ID2 IN APOPTOSIS AND CELL CYCLE PHENOTYPES ASSOCIATED WITH FOXD3 LOSS. A, Western analysis of p53 activation in

24-hour EtOH (E) and 4HT (T) treated _Foxd3_iKO cells. Blot was probed for p53, p53 (S15P) and GAPDH loading control. Two replicates from two independent cultures are shown. Approximate

location of molecular weight marker shown. B, Western analysis of p53 loss in multiple candidate _Trp53_ CRISPR-Cas9 deletion clones in _Foxd3_iKO background (_Foxd3_iKO-_Trp53_KO). Blots

were probed for p53 and GAPDH loading control. Clones 17 and 48 were chosen for further experiments (highlighted with triangle). Approximate location of molecular weight marker shown.

Results were independently confirmed once. C, Annexin V and SYTOX staining flow cytometry quantification of two independent 48-hour 4HT versus EtOH treated _Foxd3_iKO-_Trp53_KO clones (n = 3

independent cultures per treatment of clone 48 and 4HT-treated clone 17, and n = 2 for EtOH-treated clone 17). D, Percentage of _Foxd3_iKO-_Trp53_KO cells in different cell cycle phases

following 24 (n = 2 independent cultures per treatment) and 48 hours (n = 3 independent cultures per treatment) of 4HT versus EtOH treatment. Data for two independent clones shown. E,

qRT-PCR analysis of two independent _Id2_ CRISPR-Cas9 induced deletion clones in a _Foxd3_iKO background (_Foxd3_iKO-_Id2_KO). Id2 mRNA was normalized on Gapdh (n = 2 independent cultures

per condition). F, Annexin V and SYTOX staining flow cytometry quantifications of two independent _Foxd3_iKO-_Id2_KO clones following 24 and 48 hours of 4HT versus EtOH treatment (n = 3

independent cultures per treatment of clone 18 and n = 1 for clone 46 treatments). G, Quantification fraction of cells of two independent _Foxd3_iKO-_Id2_KO clones in each cell cycle phase

as measured by DNA content following 48 hours of 4HT versus EtOH treatment (n = 3 independent cultures per treatment of clone 18 and n = 1 for clone 46 treatments). H, Quantifications of

53BP1 foci in high-content confocal microscopy images of _Foxd3_iKO-_Trp53_KO cells following 24 hours 4HT versus EtOH treatment (n = 4 independent cultures per treatment). _Foxd3_iKO data

from Fig. 2a are shown in comparison. I, Quantifications of 53BP1 foci in high-content confocal microscopy images of _Foxd3_iKO cells following 24 hours 4HT versus EtOH treatment using

different indicated culture conditions (n = 8 independent cultures per treatment and culture condition). Note Y axis is represented on log scale which visually results in increased

resolution at low values and decreased resolution at high values (C,F). Data points represent independent cultures (C-I). Mean and s.e.m. are shown (C-I). Statistical tests used: Two-way

ANOVA with Šidák correction (C,D,F), two-tailed Student’s t-test (D,G,I), one-way ANOVA with Tukey correction (E,H). *_P_ < 0.05,**_P_ < 0.01,***_P_ < 0.001,****_P_ < 0.0001

(C-I). Source data EXTENDED DATA FIG. 6 LOSS OF FOXD3 DURING EMBRYOGENESIS RESULTS IN INCREASED DNA DAMAGE MARKERS. A, Experimental design of embryo aggregations. B, Whole mount stainings of

non-aggregated embryos for trophectoderm marker CDX2 and inner cell mass marker OCT4. Results were independently confirmed once. C, Representative confocal microscopy images of whole mount

embryo stainings for DAPI, 53BP1 and GFP. D, Quantifications of fraction of GFP+ cells with more than two large 53BP1 foci using high-content microscopy of whole mount embryo stainings

previously with prior treatment with 4HT (n = 90 GFP+ cells from 20 embryos) versus EtOH (n = 62 GFP+ cells from 20 embryos). E, Representative confocal microscopy images of whole mount

embryo stainings for DAPI, γH2AX and GFP. F, Quantifications of fraction of GFP+ cells with more than two large γH2AX foci using high-content microscopy of whole mount embryo stainings with

prior treatment with 4HT (n = 271 GFP+ cells from 20 embryos) versus EtOH (n = 51 GFP+ cells from 20 embryos). Scalebar equals 25 µm (B), 10 µm (C,E). Means are shown (D,F). Statistical test

used: Two-tailed Mann-Whitney test (D,F). ****_P_ < 0.0001 (D,F). Source data EXTENDED DATA FIG. 7 GENE SET ENRICHMENT ANALYSIS OF 2C GENE SETS IN DIFFERENTIAL NASCENT EXPRESSION DATA

UPON FOXD3 LOSS. A,B, Gene set enrichment plots for 2C gene sets45,46 (A) and (B) using differential nascent expression data from 24- and 32-hour 4HT versus EtOH treated _Foxd3_iKO cells. C,

Significantly differential expressed repeat RNAs in 32-hour 4HT versus EtOH treated _Foxd3_iKO cells. Mean is shown (C). *FDR < 0.05 (C). Source data EXTENDED DATA FIG. 8 PHASIC FOXD3

SA−SEQ QUALITY CONTROL AND PEAK ANALYSIS. A, Scheme of endogenous and exogenous Avi-HA tag modified FOXD3 (see Methods). B, Immunoblot validation of exogenous (exo) and endogenous (endo)

FOXD3-Avi ESC lines probed with anti-FOXD3, anti-HA and anti-GAPDH antibodies. Doxycycline (Dox) concentrations (ng/ml) shown. Approximate location of molecular weight marker shown. Results

were independently confirmed at least twice. C,D, Experimental design (C) and flow cytometry cell percentages per cell cycle phase (D) of SA-seq experiment in endogenously FOXD3 Avi-Tag

expressing ESCs synchronized and released from G2/M using CDK1i. Triangles and squares indicate samples used for sequencing and are shown relative to WT ESCs (circles). E, HOMER motif

enrichment analysis ±50 bp from the center of FOXD3 peaks. Resulting _P_ values for top 10 motifs shown. F,G, Genome tracks at _Fhit_ (F) and _Ddit4_ (G) loci of endogenous (FOXD3endo) and

exogenous (FOXD3exo) FOXD3-AviTag SA-seq data from synchronized and asynchronous FOXD3 Avi-Tag expressing ESCs, and ChIP-seq data for OCT4, SOX2, NANOG and H3K27ac plotted as CPM. H, HOMER

motif enrichment analysis ±200 bp from the center of FOXD3 peaks. Resulting _P_ values for top 10 motifs shown. I, Box plots of 4SU-seq read counts (CPM) at genes bodies nearby all FOXD3

sites called with IDR stringency thresholds of 0.1 (N = 1092 sites), 0.05 (N = 869 sites), 0.01 (N = 559 sites), 0.001 (N = 328 sites) and 0.0001 (N = 328 sites) (see Methods). Box plots

show median center, 25th and 75th percentile box bounds, and 1.5× interquartile range whisker limits. Source data EXTENDED DATA FIG. 9 EXPANDED FOXD3 BINDING AND TRANSCRIPTIONAL REGULATION

ANALYSIS. A, Box plots of 4SU-seq read counts (CPM) at all OSN (N = 10397 sites), FOXD3 (N = 1110 sites) or all other ATAC-accessible sites (N = 116976 sites). Box plots show median center,

25th and 75th percentile box bounds, and 1.5× interquartile range whisker limits. B, qRT-PCR for major satellite repeats and _Foxd3_ mRNA in _Foxd3_iKO at 24 hours of 4HT versus EtOH

treatment (n = 3 independent cultures per treatment and target). Data normalized on _Gapdh_ mRNA. C, Metagene plots (top) and heatmap plots (bottom) of SA-seq data at all ATAC-accessible

sites (N = 127719) for endogenous (FOXD3endo) and exogenous (FOXD3exo) FOXD3-AviTag SA-seq data from synchronized and asynchronous FOXD3 Avi-Tag expressing ESCs, no biotin FOXD3 control and

ChIP-seq data for OCT4, SOX2 and NANOG plotted as CPM. Mean and s.e.m. shown (B). Statistical tests used: Wilcoxon rank sum test with Benjamini-Hochberg correction (A), two-tailed Student’s

t-test (B). *_P_ < 0.05, ****_P_ < 0.0001 (A,B). Source data EXTENDED DATA FIG. 10 PHASIC SEQUENCING DATA ANALYSIS AND FOXD3 CANCER META-ANALYSIS. A,B, Schematic (A) and results (B) of

DNA content FACS analysis of _Foxd3_iKO cells used for 4SU-seq at different release times after double thymidine block and 24-hour 4HT vs EtOH treatment. C, Immunoblot for experiment shown

in A and B probed for FOXD3 at 0 and 1-hour release from double thymidine block. See below quantification of FOXD3 protein level normalized on loading control (LC) – a non-specific lower kDa

band consistently shown by FOXD3 antibody. Approximate location of molecular weight marker shown. Comparable results were independently confirmed once. D,E, Experimental design (D) and box

plots (E) of log2 fold changes of CUT&Tag sequencing data for H3K4me3 at TSS nearby FOXD3 sites obtained from 24-hour 4HT versus EtOH treated _Foxd3_iKO cells sorted into G1/early S, mid

S and late S/G2/M. Wedges represent quartiles with increasing nascent transcription rate based on 4SU-seq data (for FOXD3 nearby TSS: Nq1 = 359, Nq2 = 360, Nq3 = 352, Nq4 = 337 and for

other TSS: Nq1 = 26822, Nq2 = 26820, Nq3 = 26828, Nq4 = 26844). F,G, Schematic (F) and results (G) of DNA content FACS analysis of double thymidine blocked cells treated for 14 hours with

4HT versus EtOH before being released for shown hours. H, Quantification of γH2AX foci from high content confocal microscopy data of 24-hour 4HT versus EtOH treatment with or without

triptolide addition (n = 8 independent cultures for each treatment). I, Heatmap analysis of stage specific Foxd3 mRNA levels in cancer types available via UALCAN. Clustered by K-means. J,

Box plot representation of stage dependent FOXD3 expression in uveal melanoma available via UALCAN. See full statistical test results in Supplementary Table 3 (E). Box plots show median

center, 25th and 75th percentile box bounds, and 1.5× interquartile range whisker limits (E). Mean with s.e.m. are shown (H). Statistical tests used: Wilcoxon rank sum test with

Benjamini-Hochberg correction (E), two-tailed Student’s t-test (H). *_P_ < 0.05 (E). Source data SUPPLEMENTARY INFORMATION REPORTING SUMMARY PEER REVIEW FILE SUPPLEMENTARY TABLES 1–4

Supplementary Table 1. Oligonucleotides and synthesized sequences. Supplementary Table 2. Antibody list. Supplementary Table 3. Statistical test results for Fig. 4 and Extended Data Fig. 10c

comparisons. Supplementary Table 4. Statistical test results for Fig. 5j comparisons. SOURCE DATA SOURCE DATA FIG. 1 Source data of graphs. SOURCE DATA FIG. 2 Source data of graphs. SOURCE

DATA FIG. 3 Source data of graphs. SOURCE DATA FIG. 4 Source data of graphs. SOURCE DATA FIG. 5 Source data of graphs. SOURCE DATA FIG. 6 Source data of graphs. SOURCE DATA EXTENDED DATA

FIG. 1 Source data of graphs. SOURCE DATA EXTENDED DATA FIG. 2 Source data of graphs. SOURCE DATA EXTENDED DATA FIG. 3 Source data of graphs and uncropped immunoblots. SOURCE DATA EXTENDED

DATA FIG. 4 Source data of graphs. SOURCE DATA EXTENDED DATA FIG. 5 Source data of graphs and uncropped immunoblots. SOURCE DATA EXTENDED DATA FIG. 6 Source data of graphs. SOURCE DATA

EXTENDED DATA FIG. 7 Source data of graphs. SOURCE DATA EXTENDED DATA FIG. 8 Source data of graphs and uncropped immunoblots. SOURCE DATA EXTENDED DATA FIG. 9 Source data of graphs. SOURCE

DATA EXTENDED DATA FIG. 10 Source data of graphs and uncropped immunoblots. RIGHTS AND PERMISSIONS Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to

this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the

terms of such publishing agreement and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Gökbuget, D., Lenshoek, K., Boileau, R.M. _et al._ Transcriptional

repression upon S phase entry protects genome integrity in pluripotent cells. _Nat Struct Mol Biol_ 30, 1561–1570 (2023). https://doi.org/10.1038/s41594-023-01092-7 Download citation *

Received: 25 July 2022 * Accepted: 07 August 2023 * Published: 11 September 2023 * Issue Date: October 2023 * DOI: https://doi.org/10.1038/s41594-023-01092-7 SHARE THIS ARTICLE Anyone you

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