Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Transcription-dependent regulation of replication dynamics modulates genome stability

Abstract

Common fragile sites (CFSs) are loci that are hypersensitive to replication stress and hotspots for chromosomal rearrangements in cancers. CFSs replicate late in S phase, are cell-type specific and nest in large genes. The relative impact of transcription–replication conflicts versus a low density in initiation events on fragility is currently debated. Here we addressed the relationships between transcription, replication, and instability by manipulating the transcription of endogenous large genes in chicken and human cells. We found that inducing low transcription with a weak promoter destabilized large genes, whereas stimulating their transcription with strong promoters alleviated instability. Notably, strong promoters triggered a switch to an earlier replication timing, supporting a model in which high transcription levels give cells more time to complete replication before mitosis. Transcription could therefore contribute to maintaining genome integrity, challenging the dominant view that it is exclusively a threat.

This is a preview of subscription content

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Impact of DMD transcription activation on its replication and fragility in DT40 cells.
Fig. 2: Impact of CCSER1 overexpression on its replication and fragility in DT40 cells.
Fig. 3: Impact of FHIT overexpression on its replication timing and fragility in human HCT116 cells.
Fig. 4: Impact of DMD transcription modulation on its replication timing and fragility in DT40 cells.
Fig. 5: Impact of gene length on transcription-dependent shift in replication timing.

Data availability

The data that support the findings of this study as well as custom R scripts are available from the corresponding authors upon reasonable request.

References

  1. Gaillard, H., Garcia-Muse, T. & Aguilera, A. Replication stress and cancer. Nat. Rev. Cancer 15, 276–289 (2015).

    CAS  Article  Google Scholar 

  2. Macheret, M. & Halazonetis, T. D. DNA replication stress as a hallmark of cancer. Annu. Rev. Pathol. 10, 425–448 (2015).

    CAS  Article  Google Scholar 

  3. Techer, 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).

    CAS  Article  Google Scholar 

  4. Debatisse, M., Le Tallec, B., Letessier, A., Dutrillaux, B. & Brison, O. Common fragile sites: mechanisms of instability revisited. Trends Genet. 28, 22–32 (2012).

    CAS  Article  Google Scholar 

  5. 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  Google Scholar 

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

    CAS  Article  Google Scholar 

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

    Article  Google Scholar 

  8. Smith, D. I., McAvoy, S., Zhu, Y. & Perez, D. S. Large common fragile site genes and cancer. Semin. Cancer Biol. 17, 31–41 (2007).

    CAS  Article  Google Scholar 

  9. Helmrich, A., Ballarino, M. & Tora, L. Collisions between replication and transcription complexes cause common fragile site instability at the longest human genes. Mol. Cell 44, 966–977 (2011).

    CAS  Article  Google Scholar 

  10. Wilson, T. E. et al. Large transcription units unify copy number variants and common fragile sites arising under replication stress. Genome Res. 25, 189–200 (2015).

    CAS  Article  Google Scholar 

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

    CAS  Article  Google Scholar 

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

    CAS  Article  Google Scholar 

  13. Le Beau, M. M. et al. Replication of a common fragile site, FRA3B, occurs late in S phase and is delayed further upon induction: implications for the mechanism of fragile site induction. Hum. Mol. Genet. 7, 755–761 (1998).

    Article  Google Scholar 

  14. Naim, V., Wilhelm, T., Debatisse, M. & Rosselli, F. ERCC1 and MUS81-EME1 promote sister chromatid separation by processing late replication intermediates at common fragile sites during mitosis. Nat. Cell Biol. 15, 1008–1015 (2013).

    CAS  Article  Google Scholar 

  15. Ying, S. et al. MUS81 promotes common fragile site expression. Nat. Cell Biol. 15, 1001–1007 (2013).

    CAS  Article  Google Scholar 

  16. Minocherhomji, S. et al. Replication stress activates DNA repair synthesis in mitosis. Nature 528, 286–290 (2015).

    CAS  Article  Google Scholar 

  17. Bhowmick, R., Minocherhomji, S. & Hickson, I. D. RAD52 facilitates mitotic DNA synthesis following replication stress. Mol. Cell 64, 1117–1126 (2016).

    CAS  Article  Google Scholar 

  18. Sotiriou, S. K. et al. Mammalian RAD52 functions in break-induced replication repair of collapsed DNA replication forks. Mol. Cell 64, 1127–1134 (2016).

    CAS  Article  Google Scholar 

  19. Di Marco, S. et al. RECQ5 helicase cooperates with MUS81 endonuclease in processing stalled replication forks at common fragile sites during mitosis. Mol. Cell 66, 658–671.e8 (2017).

    Article  Google Scholar 

  20. Madireddy, A. et al. FANCD2 facilitates replication through common fragile sites. Mol. Cell 64, 388–404 (2016).

    CAS  Article  Google Scholar 

  21. 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  Google Scholar 

  22. Rivera-Mulia, J. C. & Gilbert, D. M. Replication timing and transcriptional control: beyond cause and effect-part III. Curr. Opin. Cell Biol. 40, 168–178 (2016).

    CAS  Article  Google Scholar 

  23. Zlotorynski, E. et al. Molecular basis for expression of common and rare fragile sites. Mol. Cell. Biol. 23, 7143–7151 (2003).

    CAS  Article  Google Scholar 

  24. Zhang, H. & Freudenreich, C. H. An AT-rich sequence in human common fragile site FRA16D causes fork stalling and chromosome breakage in S. cerevisiae. Mol. Cell 27, 367–379 (2007).

    Article  Google Scholar 

  25. Durkin, S. G. & Glover, T. W. Chromosome fragile sites. Annu. Rev. Genet. 41, 169–192 (2007).

    CAS  Article  Google Scholar 

  26. Tubbs, A. et al. Dual roles of poly(dA:dT) tracts in replication initiation and fork collapse. Cell 174, 1127–1142.e19 (2018).

    CAS  Article  Google Scholar 

  27. Wahba, L., Costantino, L., Tan, F. J., Zimmer, A. & Koshland, D. S1-DRIP-seq identifies high expression and polyA tracts as major contributors to R-loop formation. Genes Dev. 30, 1327–1338 (2016).

    CAS  Article  Google Scholar 

  28. Buerstedde, J. M. & Takeda, S. Increased ratio of targeted to random integration after transfection of chicken B cell lines. Cell 67, 179–188 (1991).

    CAS  Article  Google Scholar 

  29. Muntoni, F., Torelli, S. & Ferlini, A. Dystrophin and mutations: one gene, several proteins, multiple phenotypes. Lancet Neurol. 2, 731–740 (2003).

    CAS  Article  Google Scholar 

  30. Hassan-Zadeh, V. et al. USF binding sequences from the HS4 insulator element impose early replication timing on a vertebrate replicator. PLoS Biol. 10, e1001277 (2012).

    CAS  Article  Google Scholar 

  31. Rivera-Mulia, J. C. et al. Dynamic changes in replication timing and gene expression during lineage specification of human pluripotent stem cells. Genome Res. 25, 1091–1103 (2015).

    CAS  Article  Google Scholar 

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

    CAS  Article  Google Scholar 

  33. 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).

    CAS  Article  Google Scholar 

  34. Rodriguez-Martinez, M. et al. The gastrula transition reorganizes replication-origin selection in Caenorhabditis elegans. Nat. Struct. Mol. Biol. 24, 290–299 (2017).

    CAS  Article  Google Scholar 

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

    CAS  Article  Google Scholar 

  36. Prioleau, M. N. & MacAlpine, D. M. DNA replication origins-where do we begin? Genes Dev. 30, 1683–1697 (2016).

    CAS  Article  Google Scholar 

  37. Aladjem, M. I. & Redon, C. E. Order from clutter: selective interactions at mammalian replication origins. Nat. Rev. Genet. 18, 101–116 (2017).

    CAS  Article  Google Scholar 

  38. Kurat, C. F., Yeeles, J. T., Patel, H., Early, A. & Diffley, J. F. Chromatin controls DNA replication origin selection, lagging-strand synthesis, and replication fork rates. Mol. Cell 65, 117–130 (2017).

    CAS  Article  Google Scholar 

  39. Patel, K. et al. FAM190A deficiency creates a cell division defect. Am. J. Pathol. 183, 296–303 (2013).

    CAS  Article  Google Scholar 

  40. Waters, C. E., Saldivar, J. C., Hosseini, S. A. & Huebner, K. The FHIT gene product: tumor suppressor and genome “caretaker”. Cell. Mol. Life Sci. 71, 4577–4587 (2014).

    CAS  Article  Google Scholar 

  41. Miron, K., Golan-Lev, T., Dvir, R., Ben-David, E. & Kerem, B. Oncogenes create a unique landscape of fragile sites. Nat. Commun. 6, 7094 (2015).

    CAS  Article  Google Scholar 

  42. Donato, J. J., Chung, S. C. & Tye, B. K. Genome-wide hierarchy of replication origin usage in Saccharomyces cerevisiae. PLoS Genet. 2, e141 (2006).

    Article  Google Scholar 

  43. Lunyak, V. V., Ezrokhi, M., Smith, H. S. & Gerbi, S. A. Developmental changes in the Sciara II/9A initiation zone for DNA replication. Mol. Cell. Biol. 22, 8426–8437 (2002).

    CAS  Article  Google Scholar 

  44. Gros, J. et al. Post-licensing specification of eukaryotic replication origins by facilitated Mcm2-7 sliding along DNA. Mol. Cell 60, 797–807 (2015).

    CAS  Article  Google Scholar 

  45. Snyder, M., Sapolsky, R. J. & Davis, R. W. Transcription interferes with elements important for chromosome maintenance in Saccharomyces cerevisiae. Mol. Cell. Biol. 8, 2184–2194 (1988).

    CAS  Article  Google Scholar 

  46. Looke, M. et al. Relicensing of transcriptionally inactivated replication origins in budding yeast. J. Biol. Chem. 285, 40004–40011 (2010).

    CAS  Article  Google Scholar 

  47. Mori, S. & Shirahige, K. Perturbation of the activity of replication origin by meiosis-specific transcription. J. Biol. Chem. 282, 4447–4452 (2007).

    CAS  Article  Google Scholar 

  48. Krummel, K. A., Denison, S. R., Calhoun, E., Phillips, L. A. & Smith, D. I. The common fragile site FRA16D and its associated gene WWOX are highly conserved in the mouse at Fra8E1. Genes Chromosomes Cancer 34, 154–167 (2002).

    CAS  Article  Google Scholar 

  49. Debatisse, M., El Achkar, E. & Dutrillaux, B. Common fragile sites nested at the interfaces of early and late-replicating chromosome bands: cis acting components of the G2/M checkpoint? Cell Cycle 5, 578–581 (2006).

    CAS  Article  Google Scholar 

  50. Smith, D. I., Zhu, Y., McAvoy, S. & Kuhn, R. Common fragile sites, extremely large genes, neural development and cancer. Cancer Lett. 232, 48–57 (2006).

    CAS  Article  Google Scholar 

  51. Gabel, H. W. et al. Disruption of DNA-methylation-dependent long gene repression in Rett syndrome. Nature 522, 89–93 (2015).

    CAS  Article  Google Scholar 

  52. Kotsantis, P. et al. Increased global transcription activity as a mechanism of replication stress in cancer. Nat. Commun. 7, 13087 (2016).

    CAS  Article  Google Scholar 

  53. Arakawa, H., Lodygin, D. & Buerstedde, J. M. Mutant loxP vectors for selectable marker recycle and conditional knock-outs. BMC Biotechnol. 1, 7 (2001).

    CAS  Article  Google Scholar 

  54. Yin, D. X., Zhu, L. & Schimke, R. T. Tetracycline-controlled gene expression system achieves high-level and quantitative control of gene expression. Anal. Biochem. 235, 195–201 (1996).

    CAS  Article  Google Scholar 

  55. Smith, K. A., Gorman, P. A., Stark, M. B., Groves, R. P. & Stark, G. R. Distinctive chromosomal structures are formed very early in the amplification of CAD genes in Syrian hamster cells. Cell 63, 1219–1227 (1990).

    CAS  Article  Google Scholar 

  56. Anglana, M., Apiou, F., Bensimon, A. & Debatisse, M. Dynamics of DNA replication in mammalian somatic cells: nucleotide pool modulates origin choice and interorigin spacing. Cell 114, 385–394 (2003).

    CAS  Article  Google Scholar 

  57. Michalet, X. et al. Dynamic molecular combing: stretching the whole human genome for high-resolution studies. Science 277, 1518–1523 (1997).

    CAS  Article  Google Scholar 

  58. Labit, H. et al. A simple and optimized method of producing silanized surfaces for FISH and replication mapping on combed DNA fibers. Biotechniques 45, 649–652 (2008). 654, 656-648.

    CAS  Article  Google Scholar 

  59. Lebofsky, R., Heilig, R., Sonnleitner, M., Weissenbach, J. & Bensimon, A. DNA replication origin interference increases the spacing between initiation events in human cells. Mol. Biol. Cell. 17, 5337–5345 (2006).

    CAS  Article  Google Scholar 

  60. R Core Team. R: a Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017); http://www.r-project.org/.

  61. De Carli, F., Gaggioli, V., Millot, G. A. & Hyrien, O. Single-molecule, antibody-free fluorescent visualisation of replication tracts along barcoded DNA molecules. Int. J. Dev. Biol. 60, 297–304 (2016).

    Article  Google Scholar 

Download references

Acknowledgements

We thank S. Lambert and O. Hyrien for critical reading of the manuscript. The authors would like to acknowledge the Cell and Tissue Imaging Platform – PICT-IBiSA (member of France-Bioimaging) of the Genetics and Developmental Biology Department (UMR3215/U934) of Institut Curie for help with light microscopy, the Flow Cytometry Platform Imagoseine of Institut Jacques Monod, Université Paris Diderot, and the Imaging and Cytometry Platform (PFIC) of Institut Gustave Roussy for assistance with cell sorting. The M.D. team is supported by the Agence Nationale de la Recherche (grant ANR-13-BSV6-0008-01/FRA-Dom), the Association pour la Recherche sur le Cancer (grant Subvention Libre Sl220130607073), and the Institut National du Cancer (grants INCa subventions 2013-103 and PLBIO17-194). The M.N.P. team is supported by the Association pour la Recherche sur le Cancer (grant Labellisation PGA120150202272) and the Agence Nationale de la Recherche (grant ANR-15-CE12-0004-01). M.B. was supported by fellowships from the Ministère de l’Enseignement Supérieur et de la Recherche and the Ligue contre le cancer.

Author information

Authors and Affiliations

Authors

Contributions

M.B., B.L.T., and C.B. performed the experiments in avian DT40 cells and M.B., B.L.T., C.B., M.N.P., and M.D. analyzed the data. V.N. and M.S. performed the experiments in human HCT116 cells and V.N., M.S., and M.D. analyzed the data. G.A.M. computed DNA combing coverage. B.L.T. and M.D. wrote the manuscript. B.L.T. and M.D. planned the project.

Corresponding authors

Correspondence to Benoît Le Tallec or Michelle Debatisse.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Integrated supplementary information

Supplementary Figure 1 Tetracycline-induced transcriptional activation of DMD in DT40 cells.

a, Transcriptional activation using a Tet-ON inducible system. Tet-pro, Tet promoter. b, Construction of a stable DT40 cell line expressing the TR gene encoding the Tet repressor. Clone TR1 exhibited the best tetracycline-induced transcriptional activation of the luciferase reporter gene and was subsequently used for the Tet promoter integration. BsrR, blasticidin resistance gene. c, Targeting strategy. The 5’ part of the two DMD alleles, starting at exon 1 (e1, black box), is shown. Alleles were sequentially targeted in the TR1 cell line with constructs 1 then 2. Despite numerous attempts, we were unable to integrate the Tet promoter precisely upstream of the first exon of DMD; we therefore shifted the insertion site and managed to integrate the construct 4.1 kb downstream of the DMD transcription start site (TSS). As a result, the DMDTet allele is ~ 4 kb shorter than the WT DMD gene (992 and 996 kb, respectively). A synthetic DMD exon 1 was inserted together with the Tet promoter to fully reconstitute the DMD transcript, which was confirmed by RT–qPCR (Fig. 1a). Targeting construct 1 contained (1) a 2.1-kb-long 5ʹ homology region, (2) a puromycin selection cassette (PURO) made of the chicken β-actin promoter, the puromycin resistance gene (PuroR) and SV40 polyadenylation signals (pA) flanked by loxP sites (white arrowheads), (3) a 71-bp linker (violet line), (4) the Tet promoter (Tet-pro) upstream of a synthetic DMD exon 1, and (5) a 2.1-kb-long 3ʹ homology region. Targeting construct 2 was similar to targeting construct 1 except that the ZEO selection cassette contained a zeocin resistance gene (ZeoR) and that a 60-bp linker (pink line) was used. Recombinants were identified by PCR using the indicated primers (gray arrows) and by Southern blot with AflII and EcoRV restriction sites and the indicated probes. Excision of the selection cassettes was achieved by transient induction of Cre recombinase activity on 4-hydroxytamoxifen (TX) treatment and verified by PCR with primers d/e. d,e, Screening of recombinant clones by PCR (d) and Southern blot (e). + and – indicate positive and negative clones, respectively. Arrows point to the bands of the expected size described in c. Asterisks indicate non-specific bands. L, ladder. f, Verification of excision of the floxed selection cassettes by PCR using primers d/e. Before excision, the presence of the GC-rich (>71.76%) β-actin promoter prevents amplification in standard PCR conditions. L, ladder. g,h, Activation of DMD transcription has no visible impact on cell growth or cell cycle. g, Representative growth curves of WT, TR1 and DMDTet/Tet cells without tetracycline (left; this experiment was performed independently four times for WT cells and twice for TR1 cells and DMDTet/Tet cells without tetracycline with similar results) and of WT and DMDTet/Tet cells with or without tetracycline (right; this experiment was performed twice independently with similar results). The population doubling time of both WT cells and DMDTet/Tet cells with tetracycline is ~ 9.2 h, indicating that the induction of DMD transcription has no impact on cell growth. h, Representative bivariate BrdU/DNA FACS analysis of WT, TR1 and DMDTet/Tet cells with or without tetracycline (this experiment was performed twice independently with similar results). Gates indicate the fraction of cells in the G1, S and G2+M phases of the cell cycle. i, DMD is not fragile in the absence of aphidicolin in WT and DMDTet/Tet cells with tetracycline. Metaphase spreads were prepared from exponentially growing cells. Breaks were localized by FISH using probes flanking DMD. n = 1 cell culture. Numbers of broken and total chromosomes are presented on top. This experiment was performed once

Supplementary Figure 2 Examples of two-color FISH on metaphase spreads from aphidicolin-treated DT40 and human cells.

ac,e, DT40 cells were grown for 16 h with 0.6 μM aphidicolin. Metaphase spreads were hybridized with biotin or digoxigenin-labeled probes (red and green signals, respectively) flanking DMD (a,e), PARK2 (b) or CCSER1 (c); chromosomes were counterstained with DAPI (blue signal). Reverse DAPI staining is also shown. Intact and broken alleles of DMD, PARK2 or CCSER1 are boxed with a dotted and a solid line, respectively. Enlarged panels highlight chromosomes with breaks. The arrow indicates the position of the break. The cell line is indicated on the left. Scale bar, 2 μm. d, HCT116 cells were grown for 16 h with 0.15 μM aphidicolin. Metaphase spreads were hybridized with three biotinylated probes overlapping FRA3B as well as a chromosome 3 centromeric probe (red and green signals, respectively); chromosomes were counterstained with DAPI (blue signal). Reverse DAPI staining is also shown. Breaks on the long arm of chromosome 3 (Chr 3q) were determined on reverse DAPI staining. Intact and broken FRA3B or Chr 3q are boxed with a dotted and a solid line, respectively. Enlarged panels highlight chromosomes with breaks at FRA3B or Chr 3q. The arrow indicates the position of the break. The cell line is indicated on the left. Scale bar, 2 μm

Supplementary Figure 3 Molecular combing analysis of the DMD and CCSER1 loci.

a, Top, DMD gene (yellow box) and Morse-code probes (green boxes) used in DNA combing experiments to identify the locus. C, centromeric; T, telomeric. An example of a DNA fiber bearing the whole Morsecode is shown (the DNA fiber presented here spans several microscope fields of view; please note that background was removed to improve clarity). Bottom, same as above for the CCSER1 gene. b, Scheme of the protocol for double pulse-labeling of replication in asynchronous cell cultures. c, Example of raw images showing combed DNA fibers from WT DT40 cells. Top, DNA fibers counterstained in red and Morse-code probes in green. Bottom, same microscope field with IdU and CldU replication signals revealed in blue and red, respectively, and Morse-code probes in green (please note that the red and blue channels were adjusted). A fiber bearing part of the DMD Morsecode and a replication signal consisting of an IdU tract followed by a CldU tract is detected (white box). The single stranded DNA signal is stronger at the level of the replication tracts because of antibody cross-reactivity. Scale bar, 5 μm. d, Principles of replication signal analysis. A schematic representation of typical replication patterns visualized after immunofluorescence is shown. Blue and red tracts represent neo-synthesized DNA labeled with IdU and CldU, respectively. DNA fibers are in gray. Successive pulses of IdU and CldU allow the recognition of initiation (i) and termination (t) events as well as the recognition and orientation of ongoing replication forks. Black vertical arrows indicate the estimated positions of initiation and termination events

Supplementary Figure 4 Schematic representation of all DNA fibers with replication signals analyzed in this study.

a,b, From top to bottom: DMD (a) or CCSER1 (b) loci (yellow box), Morse-code probes (green boxes) used in DNA combing experiments and DNA fibers aligned along the locus using the Morsecode. Morsecodes comprise 32 probes organized in seven motifs (A–E, I, K) and 27 probes organized in five motifs (A–E) for DMD and CCSER1, respectively. Pink boxes represent the inserted constructs. DNA fibers are represented by a gray line, IdU and CldU tracts are in blue and red, respectively. Only DNA fibers with replication signals are shown (1,064 and 1,018 fibers have been collected for the DMD locus in WT and DMDTet/Tet cells with tetracycline, respectively; 636 and 1,436 fibers have been collected for the CCSER1 locus in WT and CCSER1βa/βa cells, respectively). The cell line, number (n) and mean length of fibers with replication signals are indicated on the left. DNA fibers are randomly organized. Please note that DNA fibers are fairly often interrupted at the level of a Morse-code probe; this is especially visible for fibers aligned along the CCSER1 locus. The explanation stems from the frequently dotted DNA fiber counterstaining that prevents a precise determination of the DNA molecule boundaries, which were therefore set to the visible Morse-code probes. This also explains why the total DNA coverage is not entirely homogeneous bus is higher at the level of the Morse-code probes used to identify DMD or CCSER1 (see Figs. 1c,d and 2c,d). Cen, centromeric; Tel, telomeric

Supplementary Figure 5 Overexpression of CCSER1 in DT40 cells.

a, Targeting strategy. The 5ʹ part of the two CCSER1 alleles, starting at exon 1 (e1, black box), is shown. Alleles were sequentially targeted with constructs 1 then 2. As for DMD, despite numerous attempts, we were unable to replace the endogenous CCSER1 promoter by the chicken β-actin promoter; we therefore shifted the insertion site and managed to integrate the construct 9,864 bp downstream of the CCSER1 TSS. As a result, the CCSER1βa allele is ~ 10 kb shorter than the WT CCSER1 gene (606 and 616 kb, respectively). A synthetic CSSER1 exon 1 was inserted together with the β-actin promoter to fully reconstitute the CCSER1 transcript, which was confirmed by RT–qPCR (Fig. 2a). Targeting construct 1 contained (1) a 2-kb-long 5’ homology region, (2) a blasticidin selection cassette (BSR) made of the chicken β-actin promoter, the blasticidin resistance gene (BsrR) and SV40 polyadenylation signals (pA) flanked by loxP sites (white arrowheads), (3) an 89-bp linker (violet line), (4) the chicken β-actin promoter upstream of a synthetic CCSER1 exon 1, and (5) a 2-kb-long 3’ homology region. Targeting construct 2 was similar to targeting construct 1 except that the PURO selection cassette contained a puromycin resistance gene (PuroR), an 86-bp linker (pink line) was used, and a 20-bp sequence (orange line) was inserted between the 5’ homology region and the left loxP site to allow the hybridization of primer k in order to distinguish the CCSER1PURO-βa and CCSER1BSR-βa alleles. Recombinants were identified by PCR using the indicated primers (gray arrows) and by Southern blot with AflII and EcoRV restriction sites and the indicated probes. Please note that the floxed selection cassette located upstream of the β-actin promoter–exon 1 was not excised in the CCSER1βa/βa cells used in Fig. 2 to block transcription coming from the endogenous CCSER1 promoter. b,c, Screening of recombinant clones by PCR (b) and Southern blot (c). + and – indicate positive and negative clones, respectively. Arrows point to the bands of the expected size described in a. Asterisks indicate non-specific bands. L, ladder. d,e, Impact of CCSER1 overexpression on cell physiology. d, Representative growth curves of WT and CCSER1βa/βa cells (this experiment was performed independently four times for WT cells and twice for CCSER1βa/βa cells with similar results). CCSER1 overexpression slows down cell growth, with a population doubling time of ~ 12.4 h compared to ~ 9.2 h for WT cells. e, Representative bivariate BrdU/DNA FACS analysis of WT and CCSER1βa/βa cells (this experiment was performed twice independently with similar results). Gates indicate the fraction of cells in the G1, S and G2+M phases of the cell cycle. The S-phase fraction of CCSER1βa/βa cells is slightly lower than for WT cells. f, Quantification of 5-ethynyl uridine incorporation into nascent CCSER1 RNAs in WT and CCSER1βa/βa cells (median and extreme values; nWT = 2 independent cell cultures, nCCSER1βa/βa = 3). On top, a map of CCSER1 with its exons, the position of the β-actin promoter–CCSER1 exon 1 insertion site and that of the intronic primer pairs used to monitor transcript formation is presented. i1a and i1b measure the level of nascent CCSER1 RNAs upstream and downstream of the promoter insertion site, respectively. This experiment was performed independently twice for WT cells and three times for CCSER1βa/βa cells with similar results. g, CCSER1 is not fragile in the absence of aphidicolin in WT and CCSER1βa/βa cells. Metaphase spreads were prepared from exponentially growing cells. Breaks were localized by FISH using probes flanking CCSER1. n = 1 cell culture. Numbers of broken and total chromosomes are presented on top. This experiment was performed once. h, Heterozygous CCSER1+/βa cells used in Fig. 5a. The BSR selection cassette was excised to prevent any interference in the comparison between the CCSER1βa and CCSER1βa-puro-polyA alleles. Excision was achieved by transient induction of Cre recombinase activity on 4-hydroxytamoxifen (TX) treatment and verified by the loss of antibiotic resistance

Supplementary Figure 6 Overexpression of FHIT in human HCT116 cells.

a, Targeting strategy. The FHIT promoter was replaced in HCT116 cells by an EF1α-hygromycin selection cassette using CRISPR–Cas9-mediated genome editing. EF1α (elongation factor-1 alpha) is a constitutive, robust promoter of human origin that can efficiently drive ectopic gene expression. The 5’ part of the two FHIT alleles, starting at exon 1 (e1, black box), is shown. Cas9-mediated cleavage (represented as black scissors) was achieved thanks to a pair of guide RNAs (gRNA1 and gRNA2, light and dark orange lines), resulting in the deletion of a ~ 1.9-kb region centered on FHIT promoter/exon 1. The inserted EF1α-hygromycin selection cassette was present in a homologous recombination (HR) targeting vector (HR710PA-1-FHIT plasmid), where it was flanked by sequences homologous to the FHIT promoter region 10 bp adjacent to the Cas9 cutting sites (the 5’ and 3’ homology regions extend over 985 and 974 bp, respectively). The HR710PA-1-FHIT plasmid also contained an hsvTK selection cassette located next to the 3’ homology region, which allowed the elimination of cells that have integrated the plasmid not via HR by sensitizing them to ganciclovir. Recombinants were identified by PCR using the indicated primers (gray arrows). The insertion of the EF1α-hygromycin selection cassette massively upregulated FHIT transcription despite the absence of exon 1, as observed by nascent RNA quantification (Fig. 3a). b, Identification of recombinant clones by PCR. + indicates a positive clone. A 4,242-bp-long PCR product is amplified from the WT FHIT allele using the m/p primer pair, while no PCR product is obtained after insertion of the EF1α-hygromycin cassette, allowing discrimination between homozygous and heterozygous clones. Arrows point to the bands of the expected size described in a. Asterisks indicate non-specific bands. L, ladder

Supplementary Figure 7 Modulation of DMD transcription in DT40 cells.

a,b, Targeting strategy for Tet promoter (a) or chicken β-actin promoter (b) insertion on one DMD allele. The 5’ part of the two DMD alleles, starting at exon 1 (e1, black box), is shown. As previously described (see Supplementary Fig. 1c), constructs were integrated 4.1 kb downstream of the DMD TSS; a synthetic DMD exon 1 was inserted together with the promoter to fully reconstitute the DMD transcript. a, One allele was targeted in the TR1 cell line with the targeting construct 1 described in Supplementary Fig. 1c. b, One allele was targeted in WT cells with a targeting construct that contained (1) a 2.1-kb-long 5’ homology region, (2) a puromycin selection cassette (PURO) made of the chicken β-actin promoter, the puromycin resistance gene (PuroR) and SV40 polyadenylation signals (pA) flanked by loxP sites (white arrowheads), (3) an 89-bp linker (orange line), (4) the chicken β-actin promoter upstream of a synthetic DMD exon 1, and (5) a 2.1-kb-long 3’ homology region. Recombinants were identified by PCR using the indicated primers (gray arrows). Excision of the selection cassettes was achieved by transient induction of Cre recombinase activity on 4-hydroxytamoxifen (TX) treatment and verified by PCR with primers d/e (a) or d/l (b). c,d, Screening of recombinant clones by PCR in DMD+/Tet (c) or DMD+/βa (d) cells. + and – indicate positive and negative clones, respectively. Arrows point to the bands of the expected size described in a and b. L, ladder. e,f, Verification of excision of the floxed selection cassette in DMD+/Tet (e) or DMD+/βa (f) cells by PCR using primers described in a and b. Before excision, the presence of the GC-rich (>71.76%) β-actin promoter prevents amplification in standard PCR conditions. Asterisks indicate non-specific bands. L, ladder. g, Representative growth curves of WT and DMD+/βa cells (this experiment was performed independently four times for WT cells and twice for DMD+/βa cells with similar results). Induction of DMD transcription by the β-actin promoter has no visible impact on cell growth in heterozygous cells

Supplementary Figure 8 Insertion of SV40 polyadenylation signals downstream of the β-actin promoter in DT40 cells.

a, Targeting strategy. The 5’ part of the two CCSER1 alleles, starting at exon 1 (e1, black box), is shown. Alleles were first targeted with construct 1 containing 2-kb-long 5’ and 3’ homology regions flanking the chicken β-actin promoter followed by the puromycin resistance gene (PuroR) and SV40 polyadenylation signals (pA) to generate the CCSER1βa-puro-polyA allele of heterozygous CCSER1+/βa-puro-polyA cells used in Fig. 5b. The insertion site is the same as that of the β-actin promoter alone, 9,864 bp downstream of the CCSER1 TSS (see Supplementary Fig. 5h). The "β-actin promoter-PuroR gene-SV40 polyadenylation signals" transgene was flanked by loxP sites (white arrowheads). WT CCSER1 allele 2 was then targeted with construct 2 to generate CCSER1βa-puro-polyA/βa-bsr-polyA cells used in Fig. 5c,d. Construct 2 was similar to construct 1 except that the puromycin resistance gene was replaced by the blasticidin resistance gene (BsrR). Insertion of both constructs induced early termination of CCSER1 transcription ~ 12 kb after the TSS. b,c, Screening of recombinant clones by PCR (b) and Southern blot (c). + and – indicate positive and negative clones, respectively. Arrows point to the bands of the expected size described in a. Asterisks indicate non-specific bands. L, ladder. d,e, Impact of early termination of CCSER1 transcription on cell physiology. d, Representative growth curves of WT and CCSER1βa-puro-polyA/βa-bsr-polyA cells (this experiment was performed independently four times for WT cells and twice for CCSER1βa-puro-polyA/βa-bsr-polyA cells with similar results). Early termination of CCSER1 transcription slightly slows down cell growth, with a population doubling time of ~ 10.9 h compared to ~ 9.3 h for WT cells. e, Representative bivariate BrdU/DNA FACS analysis of WT and CCSER1βa-puro-polyA/βa-bsr-polyA cells (this experiment was performed twice independently with similar results). Gates indicate the fraction of cells in the G1, S and G2+M phases of the cell cycle. The S-phase fraction of CCSER1βa-puro-polyA/βa-bsr-polyA cells is slightly lower than for WT cells. f, CCSER1 is not fragile in the absence of aphidicolin in WT and CCSER1βa-puro-polyA/βa-bsr-polyA cells. Metaphase spreads were prepared from exponentially growing cells. Breaks were localized by FISH using probes flanking CCSER1. n = 1 cell culture. Numbers of broken and total chromosomes are presented on top. This experiment was performed once. g, Gating strategy for bivariate FACS analysis. Exponentially growing DT40 cells were pulse-labeled with BrdU and fixed in ethanol. Immunodetection of BrdU was performed after partial denaturation of DNA. DNA was counterstained with propidium iodide (PI) prior to flow cytometry analysis. Cells were gated through the FSC-A versus PE-A (SSC) plot to distinguish between dead and living cells. Living cells were then interrogated by the ratios of area (Pe-Cy5-A) to height (Pe-Cy5-H) of the PI signal to gate out cell aggregates. Finally, living, single cells were analyzed for their BrdU uptake (FITC-A) versus their PI signal (Pe-Cy5-A), which provides a typical horseshoe-shaped profile allowing to discriminate between cells in G1, S and G2+M phases of the cell cycle. Pink numbers correspond to the percentage of gated cells

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8

Reporting Summary

Supplementary Table 1

FISH analysis of chromosome breaks at the DMD, CCSER1, PARK2 and FHIT loci in the different cell lines used in this study. Breaks on the long arm of chromosome 3 (Chr 3q) were determined on reverse-DAPI staining.

Supplementary Table 2

Primers used in this study. Please note that for quantification of CCSER1 mRNA level, manual alignment identified a different exon 10 from the one predicted by the Ensembl gene annotation system. RT-qPCR analysis confirmed that this exon is present in CCSER1 mRNA in our cell lines (see Fig. 2a).

Supplementary Table 3

Replication timing control loci. Quality control experiments confirmed enrichment of known early-, mid- and late-replicated loci in the expected fractions for replication timing profiles presented in Figs. 1e, 1f, 2e, 2f, 4c, 4d, 5a and 5b.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Blin, M., Le Tallec, B., Nähse, V. et al. Transcription-dependent regulation of replication dynamics modulates genome stability. Nat Struct Mol Biol 26, 58–66 (2019). https://doi.org/10.1038/s41594-018-0170-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41594-018-0170-1

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing