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Mistimed origin licensing and activation stabilize common fragile sites under tight DNA-replication checkpoint activation

Nature Structural & Molecular Biology volume 30, pages 539–550 (2023)Cite this article

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Abstract

Genome integrity requires replication to be completed before chromosome segregation. The DNA-replication checkpoint (DRC) contributes to this coordination by inhibiting CDK1, which delays mitotic onset. Under-replication of common fragile sites (CFSs), however, escapes surveillance, resulting in mitotic chromosome breaks. Here we asked whether loose DRC activation induced by modest stresses commonly used to destabilize CFSs could explain this leakage. We found that tightening DRC activation or CDK1 inhibition stabilizes CFSs in human cells. Repli-Seq and molecular combing analyses showed a burst of replication initiations implemented in mid S-phase across a subset of late-replicating sequences, including CFSs, while the bulk genome was unaffected. CFS rescue and extra-initiations required CDC6 and CDT1 availability in S-phase, implying that CDK1 inhibition permits mistimed origin licensing and firing. In addition to delaying mitotic onset, tight DRC activation therefore supports replication completion of late origin-poor domains at risk of under-replication, two complementary roles preserving genome stability.

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Fig. 1: Stringent DRC activation rescues CFSs.
Fig. 2: Repli-Seq analysis of SDR-containing domains in cells treated as indicated.
Fig. 3: Genome-wide analysis of genes more than 300 kb long.
Fig. 4: RO induces extra-initiations in FHIT without impacting bulk genome replication.
Fig. 5: CFS rescue and extra-initiations require CDC6 and CDT1 availability during S phase.

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Data availability

In addition to the Repli-seq data (GEO: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE134709) generated in our previous study, all raw sequencing files and processed count matrices generated in this study were deposited in Gene Expression Omnibus (GEO) under accession number GSE185282. Previously published data (accessions numbers) have been included in the Methods section where appropriate. The genome-wide data used in the current study have been either generated for the purpose of the study or downloaded directly from GEO (as indicated in the paper); no additional software or code was used to collect the data. The computer codes and further processing data are available on the GitHub repositories of the team (https://github.com/CL-CHEN-Lab/). Additional codes are available upon request. Source data are provided with this paper.

Code availability

The computer codes and further processing data are available on the corresponding GitHub repositories of the team (https://github.com/CL-CHEN-Lab/).

References

  1. Lin, Y. C. & Prasanth, S. G. Replication initiation: implications in genome integrity. DNA Repair 103, 103131 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hu, Y. & Stillman, B. Origins of DNA replication in eukaryotes. Mol. Cell 83, 352–372 (2023).

    Article  CAS  PubMed  Google Scholar 

  3. Costa, A. & Diffley, J. F. X. The initiation of eukaryotic DNA replication. Annu. Rev. Biochem. 91, 107–131 (2022).

    Article  PubMed  Google Scholar 

  4. Boos, D. & Ferreira, P. Origin firing regulations to control genome replication timing. Genes 10, 199 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Courtot, L., Hoffmann, J. S. & Bergoglio, V. The protective role of dormant origins in response to replicative stress. Int. J. Mol. Sci. 19, 3569 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  6. 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 

  7. Lemmens, B. et al. DNA replication determines timing of mitosis by restricting CDK1 and PLK1 activation. Mol. Cell 71, 117–128 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. 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 

  9. Lafarga, V. et al. TIAR marks nuclear G2/M transition granules and restricts CDK1 activity under replication stress. EMBO Rep. 20, e46224 (2019).

    Article  PubMed  Google Scholar 

  10. Garcia-Muse, T. & Aguilera, A. R Loops: from physiological to pathological roles. Cell 179, 604–618 (2019).

    Article  CAS  PubMed  Google Scholar 

  11. Chedin, F. & Benham, C. J. Emerging roles for R-loop structures in the management of topological stress. J. Biol. Chem. 295, 4684–4695 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Promonet, A. et al. Topoisomerase 1 prevents replication stress at R-loop-enriched transcription termination sites. Nat. Commun. 11, 3940 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Barlow, J. H. et al. Identification of early replicating fragile sites that contribute to genome instability. Cell 152, 620–632 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Tubbs, A. et al. Dual roles of poly(dA:dT) tracts in replication initiation and fork collapse. Cell 174, 1127–1142 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Waisertreiger, I., Popovich, K., Block, M., Anderson, K. R. & Barlow, J. H. Visualizing locus-specific sister chromatid exchange reveals differential patterns of replication stress-induced fragile site breakage. Oncogene 39, 1260–1272 (2020).

    Article  CAS  PubMed  Google Scholar 

  16. St Germain, C. P. et al. Genomic patterns of transcription-replication interactions in mouse primary B cells. Nucleic Acids Res. 50, 2051–2073 (2022).

    Article  CAS  Google Scholar 

  17. Gros, J. et al. Post-licensing specification of eukaryotic replication origins by facilitated MCM2-7 sliding along DNA. Mol. Cell 60, 797–807 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Foss, E. J. et al. Sir2 suppresses transcription-mediated displacement of MCM2-7 replicative helicases at the ribosomal DNA repeats. PLoS Genet. 15, e1008138 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Powell, S. K. et al. Dynamic loading and redistribution of the MCM2-7 helicase complex through the cell cycle. EMBO J. 34, 531–543 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Sugimoto, N., Maehara, K., Yoshida, K., Ohkawa, Y. & Fujita, M. Genome-wide analysis of the spatiotemporal regulation of firing and dormant replication origins in human cells. Nucleic Acids Res. 46, 6683–6696 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Liu, Y. et al. Transcription shapes DNA replication initiation to preserve genome integrity. Genome Biol. 22, 176 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Li, J. et al. The human pre-replication complex is an open complex. Cell 186, 98–111 (2023).

    Article  CAS  PubMed  Google Scholar 

  23. Kumar, C. & Remus, D. Eukaryotic replication origins: strength in flexibility. Nucleus 7, 292–300 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Petryk, N. et al. Replication landscape of the human genome. Nat. Commun. 7, 10208 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Macheret, M. & Halazonetis, T. D. Intragenic origins due to short G1 phases underlie oncogene-induced DNA replication stress. Nature 555, 112–116 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. 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 

  27. Blin, M. et al. Transcription-dependent regulation of replication dynamics modulates genome stability. Nat. Struct. Mol. Biol. 26, 58–66 (2019).

    Article  CAS  PubMed  Google Scholar 

  28. Zhao, P. A., Sasaki, T. & Gilbert, D. M. High-resolution Repli-Seq defines the temporal choreography of initiation, elongation and termination of replication in mammalian cells. Genome Biol. 21, 76 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Debatisse, M. & Rosselli, F. A journey with common fragile sites: from S phase to telophase. Genes Chromosomes Cancer 58, 305–316 (2019).

    Article  CAS  PubMed  Google Scholar 

  30. Pentzold, C. et al. FANCD2 binding identifies conserved fragile sites at large transcribed genes in avian cells. Nucleic Acids Res. 46, 1280–1294 (2018).

    Article  CAS  PubMed  Google Scholar 

  31. Brison, O. et al. Transcription-mediated organization of the replication initiation program across large genes sets common fragile sites genome-wide. Nat. Commun. 10, 5693 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sarni, D. et al. 3D genome organization contributes to genome instability at fragile sites. Nat. Commun. 11, 3613 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Casper, A. M., Nghiem, P., Arlt, M. F. & Glover, T. W. ATR regulates fragile site stability. Cell 111, 779–789 (2002).

    Article  CAS  PubMed  Google Scholar 

  34. Mocanu, C. & Chan, K. L. Mind the replication gap. R. Soc. Open Sci. 8, 201932 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Glover, T. W., Berger, C., Coyle, J. & Echo, B. DNA polymerase alpha inhibition by aphidicolin induces gaps and breaks at common fragile sites in human chromosomes. Hum. Genet. 67, 136–142 (1984).

    Article  CAS  PubMed  Google Scholar 

  36. Koundrioukoff, S. et al. Stepwise activation of the ATR signaling pathway upon increasing replication stress impacts fragile site integrity. PLoS Genet. 9, e1003643 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kapor, S., Cokic, V. & Santibanez, J. F. Mechanisms of hydroxyurea-induced cellular senescence: an oxidative stress connection? Oxid. Med. Cell Longev. 2021, 7753857 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Técher, H., Koundrioukoff, S., Nicolas, A. & Debatisse, M. The impact of replication stress on replication dynamics and DNA damage in vertebrate cells. Nat. Rev. Genet. 18, 535–550 (2017).

    Article  PubMed  Google Scholar 

  39. Pai, C. C. & Kearsey, S. E. A critical balance: dNTPs and the maintenance of genome stability. Genes 8, 57 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Shaikh, N. et al. Replication stress generates distinctive landscapes of DNA copy number alterations and chromosome scale losses. Genome Biol. 23, 223 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Sarni, D. & Kerem, B. The complex nature of fragile site plasticity and its importance in cancer. Curr. Opin. Cell Biol. 40, 131–136 (2016).

    Article  CAS  PubMed  Google Scholar 

  42. Petropoulos, M., Champeris Tsaniras, S., Taraviras, S. & Lygerou, Z. Replication licensing aberrations, replication stress, and genomic instability. Trends Biochem. Sci. 44, 752–764 (2019).

    Article  CAS  PubMed  Google Scholar 

  43. Vassilev, L. T. Cell cycle synchronization at the G2/M phase border by reversible inhibition of CDK1. Cell Cycle 5, 2555–2556 (2006).

    Article  CAS  PubMed  Google Scholar 

  44. Hochegger, H. et al. An essential role for Cdk1 in S phase control is revealed via chemical genetics in vertebrate cells. J. Cell Biol. 178, 257–268 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Katsuno, Y. et al. Cyclin A-Cdk1 regulates the origin firing program in mammalian cells. Proc. Natl Acad. Sci. USA 106, 3184–3189 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Mocanu, C. et al. DNA replication is highly resilient and persistent under the challenge of mild replication stress. Cell Rep. 39, 110701 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Le Tallec, B. et al. Molecular profiling of common fragile sites in human fibroblasts. Nat. Struct. Mol. Biol. 18, 1421–1423 (2011).

    Article  PubMed  Google Scholar 

  48. El Achkar, E., Gerbault-Seureau, M., Muleris, M., Dutrillaux, B. & Debatisse, M. Premature condensation induces breaks at the interface of early and late replicating chromosome bands bearing common fragile sites. Proc. Natl Acad. Sci. USA 102, 18069–18074 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Simoneau, A. & Zou, L. An extending ATR–CHK1 circuitry: the replication stress response and beyond. Curr. Opin. Genet. Dev. 71, 92–98 (2021).

    Article  CAS  PubMed  Google Scholar 

  50. Core, L. J. et al. Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat. Genet. 46, 1311–1320 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hochegger, H., Takeda, S. & Hunt, T. Cyclin-dependent kinases and cell-cycle transitions: does one fit all? Nat. Rev. Mol. Cell Biol. 9, 910–916 (2008).

    Article  CAS  PubMed  Google Scholar 

  52. Letessier, A. et al. Cell-type-specific replication initiation programs set fragility of the FRA3B fragile site. Nature 470, 120–123 (2011).

    Article  CAS  PubMed  Google Scholar 

  53. Sedlackova, H. et al. Equilibrium between nascent and parental MCM proteins protects replicating genomes. Nature 587, 297–302 (2020).

    Article  CAS  PubMed  Google Scholar 

  54. Zhou, Y., Pozo, P. N., Oh, S., Stone, H. M. & Cook, J. G. Distinct and sequential re-replication barriers ensure precise genome duplication. PLoS Genet. 16, e1008988 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Arlt, M. F., Ozdemir, A. C., Birkeland, S. R., Wilson, T. E. & Glover, T. W. Hydroxyurea induces de novo copy number variants in human cells. Proc. Natl Acad. Sci. USA 108, 17360–17365 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Lyu, X., Chastain, M. & Chai, W. Genome-wide mapping and profiling of γH2AX binding hotspots in response to different replication stress inducers. BMC Genomics 20, 579 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Daigh, L. H., Liu, C., Chung, M., Cimprich, K. A. & Meyer, T. Stochastic endogenous replication stress causes ATR-triggered fluctuations in CDK2 activity that dynamically adjust global DNA synthesis rates. Cell Syst. 7, 17–27 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Park, S. H. et al. Locus-specific transcription silencing at the FHIT gene suppresses replication stress-induced copy number variant formation and associated replication delay. Nucleic Acids Res. 49, 7507–7524 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Parker, M. W., Botchan, M. R. & Berger, J. M. Mechanisms and regulation of DNA replication initiation in eukaryotes. Crit. Rev. Biochem. Mol. Biol. 52, 107–144 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Clijsters, L. & Wolthuis, R. PIP-box-mediated degradation prohibits re-accumulation of Cdc6 during S phase. J. Cell Sci. 127, 1336–1345 (2014).

    CAS  PubMed  Google Scholar 

  61. Pozo, P. N. & Cook, J. G. Regulation and function of Cdt1; a key factor in cell proliferation and genome stability. Genes 8, 2 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Fu, H. et al. Dynamics of replication origin over-activation. Nat. Commun. 12, 3448 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Arias, E. E. & Walter, J. C. PCNA functions as a molecular platform to trigger Cdt1 destruction and prevent re-replication. Nat. Cell Biol. 8, 84–90 (2006).

    Article  CAS  PubMed  Google Scholar 

  64. Senga, T. et al. PCNA is a cofactor for Cdt1 degradation by CUL4/DDB1-mediated N-terminal ubiquitination. J. Biol. Chem. 281, 6246–6252 (2006).

    Article  CAS  PubMed  Google Scholar 

  65. Takeda, D. Y., Parvin, J. D. & Dutta, A. Degradation of Cdt1 during S phase is Skp2-independent and is required for efficient progression of mammalian cells through S phase. J. Biol. Chem. 280, 23416–23423 (2005).

    Article  CAS  PubMed  Google Scholar 

  66. Nishitani, H. et al. Two E3 ubiquitin ligases, SCF-Skp2 and DDB1-Cul4, target human Cdt1 for proteolysis. EMBO J. 25, 1126–1136 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Tena, A. et al. Induction of recurrent break cluster genes in neural progenitor cells differentiated from embryonic stem cells in culture. Proc. Natl Acad. Sci. USA 117, 10541–10546 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Debatisse, M., Berry, M. & Buttin, G. Stepwise isolation and properties of unstable Chinese hamster cell variants that overproduce adenylate deaminase. Mol. Cell. Biol. 2, 1346–1353 (1982).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Técher, H. et al. Signaling from Mus81–Eme2-dependent DNA damage elicited by Chk1 deficiency modulates replication fork speed and origin usage. Cell Rep. 14, 1114–1127 (2016).

    Article  PubMed  Google Scholar 

  71. Le Tallec, B. et al. Common fragile site profiling in epithelial and erythroid cells reveals that most recurrent cancer deletions lie in fragile sites hosting large genes. Cell Rep. 4, 420–428 (2013).

    Article  PubMed  Google Scholar 

  72. Arbona, J. M., Goldar, A., Hyrien, O., Arneodo, A. & Audit, B. The eukaryotic bell-shaped temporal rate of DNA replication origin firing emanates from a balance between origin activation and passivation. eLife 7, e35192 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The three teams contributing to the work (those of M.D., C.-L.C., C.T.) have been supported by the Fondation pour la Recherche Médicale (FRM) (programme DBI20131228560). The teams of M.D. and C-L.C. are supported by the Agence Nationale pour la Recherche (ANR) AAPG 2019 ‘TELOCHROM’. M.D.’s team is also supported by ANR AAPG 2020 ‘CARE-ME’. C.-L.C.’s team is supported by the ANR ‘ReDeFINe’, the INCa PLBIO19 076 and by grants from the Curie Institute YPI program, the ATIP-Avenir program from CNRS and Plan Cancer from INSERM, CNRS 80|Prime inter-disciplinary program. S.G. was supported by ATIP-Avenir and Plan Cancer for his post-doc fellowship, S.E.-H. by the FRM program, D.A. by a fellowship from the Ligue Nationale Contre le Cancer, R.M.-G. by the ANR TELOCHROM, S.-J.K. by the ANR CARE-me. We acknowledge the Imaging and Cytometry Platform (UMS 3655 CNRS/US 23 INSERM) of Gustave Roussy Cancer Campus for assistance with cell sorting and the High-Throughput Sequencing facility of I2BC for its sequencing and bioinformatics expertise. We thank N. Alary for his help with the statistical analysis and for help in preparing the figures. We thank N. Alary for help with bioinformatics analyses and preparing the figures, A. Renoult for some γH2AX foci experiments and M. Schertzer for critical reading of the manuscript.

Author information

Author notes

  1. Dana Azar

    Present address: Laboratoire Biodiversité et Génomique Fonctionnelle, Faculté des Sciences, Université Saint-Joseph, Beirut, Lebanon

  2. Sami El-Hilali

    Present address: Villefranche sur mer Developmental Biology Laboratory, CNRS UMR7009, Villefranche-sur-Mer, France

  3. Anne-Marie Lachages

    Present address: UTCBS, CNRS UMR 8258/ INSERM U 1267, Sorbonne-Paris-Cité University, Paris, France

  4. These authors contributed equally: Olivier Brison, Stefano Gnan, Dana Azar.

Authors and Affiliations

  1. CNRS UMR 9019, Gustave Roussy Institute, Villejuif, France

    Olivier Brison, Stéphane Koundrioukoff, Rodrigo Melendez-Garcia, Su-Jung Kim, Mélanie Schmidt & Michelle Debatisse

  2. Paris-Saclay University, Gif-sur-Yvette, France

    Olivier Brison, Rodrigo Melendez-Garcia, Su-Jung Kim, Mélanie Schmidt, Yan Jaszczyszyn & Claude Thermes

  3. Curie Institute, PSL Research University, CNRS UMR 3244, Paris, France

    Stefano Gnan, Dana Azar, Sami El-Hilali, Anne-Marie Lachages & Chun-Long Chen

  4. Sorbonne University, Paris, France

    Stefano Gnan, Dana Azar, Stéphane Koundrioukoff, Sami El-Hilali, Chun-Long Chen & Michelle Debatisse

  5. Institute for Integrative Biology of the Cell (I2BC), UMR 9198CNRS, CEA, Paris-Sud University, Gif-sur-Yvette, France

    Yan Jaszczyszyn & Claude Thermes

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Contributions

M.D. and O.B. conceived the project and wrote the paper. C.-L.C., S.K., S.G. and C.T. provided critical revision of the manuscript and contributed to figure preparation. O.B. contributed to and directed D.A.’s, M.S.’s and A.-M.L.’s bench work, and analyzed the results. D.A., S.K., R.M.G., S.-J.K., M.S. and A.-M.L. contributed to biological experiments, including cell culture, cell sorting, FACS analyses, immunoprecipitation of BrdU-labeled DNA and molecular cytogenetics. Y.J. did the Repli-Seq libraries and the sequencing. S.G., S.E.-H. and C.-L.C. performed sequencing data analyses and statistical analyses. O.B., S.G. and D.A. contributed equally to this work.

Corresponding author

Correspondence to Michelle Debatisse.

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Nature Structural & Molecular Biology thanks Kay Huebner, David Gilbert, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Editor recognition statement (if applicable to your journal) Beth Moorefield, Carolina Perdigoto, and Dimitris Typas were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team

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Extended data

Extended Data Fig. 1 RO 10 μM reversibly blocks cells in G2-phase, without triggering DNA damage.

A: Gating strategy for FACS analyses. Cells gated for subsequent analysis are enclosed in polygons; A: live cells, B: single cells; G1/S/G2-M: cell cycle phases, SSC: side scatter; FSC: forward scatter; PE-Texas Red: Intensity of propidium iodide; APC: BrdU intensity (when BrdU labelling was performed). For some experiments, cell cycle analysis (rightmost panel) is presented as histograms (cell counts as ordinates). B-E: FACS analysis of human lymphoblasts (JEFF), of primary fibroblasts (MRC5), and of immortalized Chinese hamster fibroblasts (GMA32) treated with RO. The concentrations used and times of treatment are indicated, NT: Non-treated cells. Each experiment was done once. F: Experimental scheme for G-I. Exponentially growing (exp. gr.) cells were treated as indicated then released in normal medium (t0) and analysed by immunofluorescence (IF) with anti-γH2AX antibodies at indicated times. G: IF analysis of JEFF lymphoblasts. HU 1mM is used as positive control. Note the presence of mitotic cells (white arrows) in the 30 min panel. Scale bars: 20 µm. The percentage of nuclei with foci in each sample was determined by eye counting (histogram). H-I: GMA32 cells were analysed by FACS (H) or IF (I) as in F; white arrows and scale bars as in G. For quantification, pictures of 20 microscopic fields for each sample were assembled and the intensity of global red fluorescence was determined with Image Gauge (histogram). Experiments shown in G-I were carried out once.

Source data

Extended Data Fig. 2 Cytogenetic analysis of cells treated with Aph, ARO or HU −/+ ATRi.

A, B: Metaphase plates from JEFF and MRC5 cells treated with Aph 600 nM for 16 h. Chromosomes were stained with Giemsa, arrowheads point to breaks. Two biologically independent experiments were done. C, D: Examples of chromosome breaks (white arrowheads) at FRA3B/FHIT or FRA16D/WWOX in JEFF cells (C) and at FRA1L/NEGR1 or FRA3L/LSAMP in MRC5 (D). Biologically independent experiments were done twice (C) or once (D). Left panels: FISH with probes specific to fragile genes (green) in association with probes specific to the centromere of corresponding chromosomes when available (red). Right panels: Chromosomes counter-stained with DAPI. Contrast was enhanced to better visualise the breaks. E: Total breaks and breaks at FRA3L and FRA1L were determined in normal MRC5 fibroblasts. Results are presented as in Fig. 1c. Biologically independent experiments were done twice (total breaks) or once (FRA3L and FRA1L), each experiment corresponding to analysis of 100 metaphases. Data are presented as mean values for total breaks. F-H: Impact of DRC signalling on chromosome stability in HU-treated JEFF lymphoblasts. F: A biologically independent duplicate of western blots shown in Fig. 1d was carried out and signals on digital images were quantified. The histogram shows the results of the two biologically independent experiments, HU values are presented relative to that in non-treated cells (NT). Data are presented as mean values. G: Example of a metaphase plate displaying mitotic catastrophe (24% of all metaphases) induced in cells treated with HU + ATRi (as in Fig. 1g). Metaphase plates were prepared and analysed as in A. The arrows point to multi-broken chromosomes. Biologically independent experiments were done twice. H: Examples of an atypical break at FRA3B, FISH and Giemsa staining as in C. Atypical breaks at FRA3B were commonly observed in HU+ATRi (50% of FRA3B breaks) but were not seen in Aph- or HU-treated cells (two biologically independent experiments). Scale bars: 20 µm on metaphase plates (A, B, G) and 0,5 µm on chromosomes (C, D, H).

Source data

Extended Data Fig. 3 Analysis of Repli-Seq data.

A: Representative FACS profile showing the gate position for cell sorting. Fluorescent units are reported on the x axis and the cell counts on the y axis. The percentage of replicated DNA (based on the G1 and G2 peaks) is shown at the top. B: Simulation of S-phase progression (based on72). Blue curve: percentage of replicated DNA shown as a function of simulation cycle. Red curve: typical bell-shaped curve given by the ratio between origin firing and un-replicated DNA as a function of simulation cycle. C: Density of active forks in function of the percentage of replicated DNA obtained in the simulation. The relative quantity of newly replicated DNA inside each fraction has then been used to normalize the Repli-Seq data. D: Heat-map showing Pearson correlation coefficient between individual biological replicate of NT, Aph and ARO samples. E: Repli-Seq profiles of FRA3B and FRA16D showing the profiles of individual replicates in each condition in grey, and the average profiles in blue for NT, green for Aph and orange for ARO (as in Fig. 1b, c). Biologically independent experiments were performed three times for NT, twice for Aph and ARO with similar results. Data are presented as mean values.

Extended Data Fig. 4 Analyses of bulk large genes.

A: GRO-seq, RT and URIs along all genes over 300 kb and flanking regions (as in Fig. 3a). Bulk genes are divided into 4 groups according to their transcription levels: high (1st group, n = 119), medium (2nd group, n = 203 and 3rd group, n = 377) very low (4th group, n = 83). Genes within each group (and those hosting a SDR) are presented according to decreasing transcription levels. B-D: Boxplot comparison of URIs along large genes and flanking regions. Bounds of box: 25th and 75th percentiles; centre line: median; lower (upper) whisker: lower (upper) bound - (+) 1.5 x Interquartile range (IQR). Statistical significance was set to P≤0.05, the corresponding p values are indicated in the plots. B: Average Aph-induced URIs for genes (coloured boxes) and their flanking regions (±100 kb) (grey boxes). P values relative to the differences in URI between gene bodies and flanking regions have been calculated using one-sided Wilcoxon matched-pairs signed rank test (adjusted with FDR) with an alternative hypothesis of the gene bodies to have a lower Aph-URI compared to the flanking regions. P values for comparison of URIs between gene bodies and flanking regions are shown in black and have been calculated using two-sided Wilcoxon rank sum test and adjusted with FDR. C: Average URIs in Aph- and ARO-treated cells. Left panel: over whole gene, right panel: over later-replicated region (S50 ≥ RTmedian) of each gene. RTmedian: median replication timing for each gene. P values have been calculated as in B with alternative hypothesis of gene to have a lower URI in Aph- compared to the ARO-treated cells. D: URIs in Aph- and ARO-treated cells across genomic regions of different RT categories, defined accordingly to their S50 in NT cells; Early (0.1 ≤ S50 < 0.33, n = 18128), Mid (0.33 ≤ S50 < 0.66, n = 21319) and Late (0.66 ≤ S50 ≤ 0.9, n = 13177). Bins with extreme S50 values (S50 < 0.1 or S50 > 0.9) were excluded from this analysis. P-values have been calculated using two-sided Wilcoxon matched-pairs signed rank test. Only the late-replicating regions displayed a significant rescue.

Extended Data Fig. 5 Molecular combing analysis of the FHIT locus, principle and examples.

A: Map of the FHIT gene, with the position its 10 exons (ex) and of the 29 short probes (l5.5 to 6.6 Kb)-long - dark green rectangles), organized in five motifs (a-e) that constitute the FISH code bar initially used for identification of a region 1.6 Mb-long encompassing the gene52. Six longer probes (from left to right, size in kb L1: 40, L2: 50, L3: 40, L4: 40, L5: 60 and L6: 30) were recently added to facilitate screening (light green rectangles). B: Examples of DNA fibres bearing FISH tracks (revealed in green) and replication signals (pulse 1: IdU in blue, pulse 2: CldU in red) from cells treated as Fig. 1e. Three colour-painting and FISH alone are shown. A schematic representation of the fiber (in grey) is also presented, arrowheads indicate the direction of fork progression and blue squares the estimated positions of initiation events.

Extended Data Fig. 6 Supplementary results relative to western blots.

A-D: MCM7 protein accumulates on chromatin of S6/G2 cells grown in ARO. A: Experimental scheme. B: Quality-control of the fractionation procedure. Ponceau staining is shown as a loading control and size of molecular weight markers is indicated. The levels of GAPDH (cytoplasmic marker) and histone H4 (nuclear marker) were analysed with corresponding antibodies. Experiment was done once. C: Cells were treated as in A, fractionated and protein extracts were analysed with MCM7 antibodies. Two biologically independent experiments were done with similar results. D: Biologically independent duplicate of the experiment shown in Fig. 4g (middle panel, chromatin). E: Kinetics of CDC6 and CDT1 depletion. JEFF cells were transfected with siCDC6, siCDT1 or sictrl. At indicated times after transfection, total protein extracts were prepared to assess the level of each factor. Beta-actin was used as a loading control. Experiments were done once.

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Extended Data Fig. 7 RO does not reduce large gene transcription.

A, B: Exponentially growing cells were grown for 16h in different media (colour code shown on the right). The map of the genes is shown above the histograms with the position exons (ex) (like in Extended Data Fig. 5a) and of intronic primers used for the qPCR (i-F/R) and A: Fixed chromatin from JEFF lymphoblasts was immunoprecipitated with anti-RNA polymerase II antibodies (Methods). The density of RNA polymerase II along FHIT and WWOX was determined by qPCR with the indicated intronic primers. Results are presented as fold enrichment relative to the levels obtained with control immunoglobulins. Note the accumulation of RNA polymerase on the FHIT promoter detected by the intron 1 (i1) primers. Two biologically independent experiments were done with similar results. B: Comparison of nascent RNA levels along the FHIT and WWOX in JEFF lymphoblasts, and of primary RNA levels along the NEGR1 in MRC5 fibroblasts. JEFF cells were treated as in A and pulse-labelled with 5-ethynyl-uridine. Nascent RNAs were purified by affinity chromatography and quantified by RT-qPCR with the indicated primers. Results are presented relative to the level in NT cells. Experiments were done once. C: FHIT transcription across the cell cycle. Non-treated JEFF lymphoblasts were FACS-sorted (left inset) in 4 fractions and RNA extracted from each of them. Primary RNA levels were quantified by RT-qPCR as in A. Results for each primer pair were normalized using cyclophilin B (PPIB) RNA as endogenous control and are presented relative to the total amount of transcripts (sum of G1+S1+S2+G2/M). In the rightmost histogram, the sum of the transcript levels detected by all primer pairs in each fraction is expressed relative to the sum of the levels of all transcripts in all fractions. Two biologically independent experiments were done. Data are presented as mean values.

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Extended Data Fig. 8 Resilience of cells transfected at different stages of the cell cycle.

A: Cell cycle progression was followed by FACS analysis at the indicated times after the BrdU pulse (t0) in JEFF lymphoblasts non-transfected (Nt) or transfected with the indicated siRNAs. Fractions of the cells in each phase of the cell cycle were quantified (percentages indicated in red polygons of each panel); unlabelled (G1, S, G2) and BrdU labelled (G1b, Sb, G2b). The nomenclature is the same for all panels. B: Nt cells that were in G1 at the time of BrdU pulse (G1) exit this phase, enter unlabelled in S-phase (S) and are back in G1 by 16 h with kinetics fully compatible with the known parameters of JEFF cell cycle (G1: 6 h; S: 8 h; G2M: 2 h). In striking contrast, cells transfected in G1 exit this phase and enter S-phase extremely slowly. By 24 h post-transfection, only a small fraction of them have progressed to S. C, D: Non-transfected cells that were G2M (G2/M) (C) or in S (Sb) (D) at the time of BrdU pulse progress as expected in the cycle. Cells transfected G2/M or in S-phase exited these phases with a 6-h delay. This delay is still visible when cells transfected in S-phase progress in G2M (labelled G2/M) and then in G1 (labelled G1). Experiments were done once.

Extended Data Fig. 9 Examples of metaphase plates observed in experiments of Fig. 5b.

A: Upper panel: Experimental scheme. Lower panels: Protein extracts from cells used in Fig. 5b (two biologically independent experiments) were prepared to assess the level of each factor. Ponceau staining was used as a loading control. B: Examples of BrdU-labelled and unlabelled metaphases plates observed in the two biologically independent experiments shown in Fig. 5b. Note that the labelling reveals classical replication bands, showing that cells were engaged in the S-phase during the pulse. Scale bars: 20 μm.

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Extended Data Fig. 10

Tables of antibodies and PCR primers used in this study.

Supplementary information

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Brison, O., Gnan, S., Azar, D. et al. Mistimed origin licensing and activation stabilize common fragile sites under tight DNA-replication checkpoint activation. Nat Struct Mol Biol 30, 539–550 (2023). https://doi.org/10.1038/s41594-023-00949-1

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