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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.,
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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
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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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