Skip to main content

Thank you for visiting 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.

Genome-wide mapping of long-range contacts unveils clustering of DNA double-strand breaks at damaged active genes


The ability of DNA double-strand breaks (DSBs) to cluster in mammalian cells has been a subject of intense debate in recent years. Here we used a high-throughput chromosome conformation capture assay (capture Hi-C) to investigate clustering of DSBs induced at defined loci in the human genome. The results unambiguously demonstrated that DSBs cluster, but only when they are induced within transcriptionally active genes. Clustering of damaged genes occurs primarily during the G1 cell-cycle phase and coincides with delayed repair. Moreover, DSB clustering depends on the MRN complex as well as the Formin 2 (FMN2) nuclear actin organizer and the linker of nuclear and cytoplasmic skeleton (LINC) complex, thus suggesting that active mechanisms promote clustering. This work reveals that, when damaged, active genes, compared with the rest of the genome, exhibit a distinctive behavior, remaining largely unrepaired and clustered in G1, and being repaired via homologous recombination in postreplicative cells.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Capture Hi-C reveals DSB-induced local changes in chromosome folding.
Figure 2: Clustering occurs for DSBs induced on different chromosomes and correlates with γ-H2AX level.
Figure 3: DSBs within transcriptionally active genes that are repaired by homologous recombination in postreplicative cells undergo clustering.
Figure 4: DSB clustering is favored during the G1 cell-cycle phase.
Figure 5: Clustered HR-prone DSBs exhibit delayed repair in G1.
Figure 6: DSB clustering depends on the MRN complex as well as on the LINC complex and the FMN2 actin organizer.
Figure 7: Model for DSB clustering.

Accession codes

Primary accessions



  1. 1

    Dion, V., Kalck, V., Horigome, C., Towbin, B.D. & Gasser, S.M. Increased mobility of double-strand breaks requires Mec1, Rad9 and the homologous recombination machinery. Nat. Cell Biol. 14, 502–509 (2012).

    CAS  Article  Google Scholar 

  2. 2

    Miné-Hattab, J. & Rothstein, R. Increased chromosome mobility facilitates homology search during recombination. Nat. Cell Biol. 14, 510–517 (2012).

    Article  Google Scholar 

  3. 3

    Neumann, F.R. et al. Targeted INO80 enhances subnuclear chromatin movement and ectopic homologous recombination. Genes Dev. 26, 369–383 (2012).

    CAS  Article  Google Scholar 

  4. 4

    Lisby, M., Mortensen, U.H. & Rothstein, R. Colocalization of multiple DNA double-strand breaks at a single Rad52 repair centre. Nat. Cell Biol. 5, 572–577 (2003).

    CAS  Article  Google Scholar 

  5. 5

    Aten, J.A. et al. Dynamics of DNA double-strand breaks revealed by clustering of damaged chromosome domains. Science 303, 92–95 (2004).

    CAS  Article  Google Scholar 

  6. 6

    Krawczyk, P.M. et al. Chromatin mobility is increased at sites of DNA double-strand breaks. J. Cell Sci. 125, 2127–2133 (2012).

    CAS  Article  Google Scholar 

  7. 7

    Krawczyk, P.M., Stap, J., van Oven, C., Hoebe, R. & Aten, J.A. Clustering of double strand break-containing chromosome domains is not inhibited by inactivation of major repair proteins. Radiat. Prot. Dosimetry 122, 150–153 (2006).

    CAS  Article  Google Scholar 

  8. 8

    Neumaier, T. et al. Evidence for formation of DNA repair centers and dose-response nonlinearity in human cells. Proc. Natl. Acad. Sci. USA 109, 443–448 (2012).

    Article  Google Scholar 

  9. 9

    Becker, A., Durante, M., Taucher-Scholz, G. & Jakob, B. ATM alters the otherwise robust chromatin mobility at sites of DNA double-strand breaks (DSBs) in human cells. PLoS One 9, e92640 (2014).

    Article  Google Scholar 

  10. 10

    Jakob, B., Splinter, J. & Taucher-Scholz, G. Positional stability of damaged chromatin domains along radiation tracks in mammalian cells. Radiat. Res. 171, 405–418 (2009).

    CAS  Article  Google Scholar 

  11. 11

    Kruhlak, M.J. et al. Changes in chromatin structure and mobility in living cells at sites of DNA double-strand breaks. J. Cell Biol. 172, 823–834 (2006).

    CAS  Article  Google Scholar 

  12. 12

    Kruhlak, M.J., Celeste, A. & Nussenzweig, A. Spatio-temporal dynamics of chromatin containing DNA breaks. Cell Cycle 5, 1910–1912 (2006).

    CAS  Article  Google Scholar 

  13. 13

    Soutoglou, E. et al. Positional stability of single double-strand breaks in mammalian cells. Nat. Cell Biol. 9, 675–682 (2007).

    CAS  Article  Google Scholar 

  14. 14

    Marnef, A. & Legube, G. Organizing DNA repair in the nucleus: DSBs hit the road. Curr. Opin. Cell Biol. 46, 1–8 (2017).

    CAS  Article  Google Scholar 

  15. 15

    Cho, N.W., Dilley, R.L., Lampson, M.A. & Greenberg, R.A. Interchromosomal homology searches drive directional ALT telomere movement and synapsis. Cell 159, 108–121 (2014).

    CAS  Article  Google Scholar 

  16. 16

    Caron, P. et al. Non-redundant functions of ATM and DNA-PKcs in response to DNA double-strand breaks. Cell Rep. 13, 1598–1609 (2015).

    CAS  Article  Google Scholar 

  17. 17

    Roukos, V. et al. Spatial dynamics of chromosome translocations in living cells. Science 341, 660–664 (2013).

    CAS  Article  Google Scholar 

  18. 18

    Mladenov, E., Magin, S., Soni, A. & Iliakis, G. DNA double-strand-break repair in higher eukaryotes and its role in genomic instability and cancer: cell cycle and proliferation-dependent regulation. Semin. Cancer Biol. 37-38, 51–64 (2016).

    CAS  Article  Google Scholar 

  19. 19

    Orthwein, A. et al. A mechanism for the suppression of homologous recombination in G1 cells. Nature 528, 422–426 (2015).

    CAS  Article  Google Scholar 

  20. 20

    Clouaire, T. & Legube, G. DNA double strand break repair pathway choice: a chromatin based decision? Nucleus 6, 107–113 (2015).

    CAS  Article  Google Scholar 

  21. 21

    Aymard, F. et al. Transcriptionally active chromatin recruits homologous recombination at DNA double-strand breaks. Nat. Struct. Mol. Biol. 21, 366–374 (2014).

    CAS  Article  Google Scholar 

  22. 22

    Pfister, S.X. et al. SETD2-dependent histone H3K36 trimethylation is required for homologous recombination repair and genome stability. Cell Rep. 7, 2006–2018 (2014).

    CAS  Article  Google Scholar 

  23. 23

    Carvalho, S. et al. SETD2 is required for DNA double-strand break repair and activation of the p53-mediated checkpoint. eLife 3, e02482 (2014).

    Article  Google Scholar 

  24. 24

    Daugaard, M. et al. LEDGF (p75) promotes DNA-end resection and homologous recombination. Nat. Struct. Mol. Biol. 19, 803–810 (2012).

    CAS  Article  Google Scholar 

  25. 25

    Hajjoul, H. et al. High-throughput chromatin motion tracking in living yeast reveals the flexibility of the fiber throughout the genome. Genome Res. 23, 1829–1838 (2013).

    CAS  Article  Google Scholar 

  26. 26

    Schoenfelder, S. et al. The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements. Genome Res. 25, 582–597 (2015).

    CAS  Article  Google Scholar 

  27. 27

    Iacovoni, J.S. et al. High-resolution profiling of gammaH2AX around DNA double strand breaks in the mammalian genome. EMBO J. 29, 1446–1457 (2010).

    CAS  Article  Google Scholar 

  28. 28

    Aymard, F. & Legube, G. A TAD closer to ATM. Mol. Cell. Oncol. 3, e1134411 (2016).

    Article  Google Scholar 

  29. 29

    Bolzer, A. et al. Three-dimensional maps of all chromosomes in human male fibroblast nuclei and prometaphase rosettes. PLoS Biol. 3, e157 (2005).

    Article  Google Scholar 

  30. 30

    Nagai, S. et al. Functional targeting of DNA damage to a nuclear pore-associated SUMO-dependent ubiquitin ligase. Science 322, 597–602 (2008).

    CAS  Article  Google Scholar 

  31. 31

    Oza, P., Jaspersen, S.L., Miele, A., Dekker, J. & Peterson, C.L. Mechanisms that regulate localization of a DNA double-strand break to the nuclear periphery. Genes Dev. 23, 912–927 (2009).

    CAS  Article  Google Scholar 

  32. 32

    Chiolo, I. et al. Double-strand breaks in heterochromatin move outside of a dynamic HP1a domain to complete recombinational repair. Cell 144, 732–744 (2011).

    CAS  Article  Google Scholar 

  33. 33

    Jakob, B. et al. DNA double-strand breaks in heterochromatin elicit fast repair protein recruitment, histone H2AX phosphorylation and relocation to euchromatin. Nucleic Acids Res. 39, 6489–6499 (2011).

    CAS  Article  Google Scholar 

  34. 34

    Harding, S.M., Boiarsky, J.A. & Greenberg, R.A. ATM dependent silencing links nucleolar chromatin reorganization to DNA damage recognition. Cell Rep. 13, 251–259 (2015).

    CAS  Article  Google Scholar 

  35. 35

    van Sluis, M. & McStay, B. A localized nucleolar DNA damage response facilitates recruitment of the homology-directed repair machinery independent of cell cycle stage. Genes Dev. 29, 1151–1163 (2015).

    CAS  Article  Google Scholar 

  36. 36

    Chailleux, C. et al. Quantifying DNA double-strand breaks induced by site-specific endonucleases in living cells by ligation-mediated purification. Nat. Protoc. 9, 517–528 (2014).

    CAS  Article  Google Scholar 

  37. 37

    Crosetto, N. et al. Nucleotide-resolution DNA double-strand break mapping by next-generation sequencing. Nat. Methods 10, 361–365 (2013).

    CAS  Article  Google Scholar 

  38. 38

    Mitra, A., Skrzypczak, M., Ginalski, K. & Rowicka, M. Strategies for achieving high sequencing accuracy for low diversity samples and avoiding sample bleeding using illumina platform. PLoS One 10, e0120520 (2015).

    Article  Google Scholar 

  39. 39

    Lottersberger, F., Karssemeijer, R.A., Dimitrova, N. & de Lange, T. 53BP1 and the LINC complex promote microtubule-dependent DSB mobility and DNA repair. Cell 163, 880–893 (2015).

    CAS  Article  Google Scholar 

  40. 40

    Belin, B.J., Lee, T. & Mullins, R.D. DNA damage induces nuclear actin filament assembly by Formin-2 and Spire-1/2 that promotes efficient DNA repair. eLife 4, e07735 (2015).

    Article  Google Scholar 

  41. 41

    Lee, C.S., Lee, K., Legube, G. & Haber, J.E. Dynamics of yeast histone H2A and H2B phosphorylation in response to a double-strand break. Nat. Struct. Mol. Biol. 21, 103–109 (2014).

    CAS  Article  Google Scholar 

  42. 42

    Chiarle, R. et al. Genome-wide translocation sequencing reveals mechanisms of chromosome breaks and rearrangements in B cells. Cell 147, 107–119 (2011).

    CAS  Article  Google Scholar 

  43. 43

    Klein, I.A. et al. Translocation-capture sequencing reveals the extent and nature of chromosomal rearrangements in B lymphocytes. Cell 147, 95–106 (2011).

    CAS  Article  Google Scholar 

  44. 44

    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 

  45. 45

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

    CAS  Article  Google Scholar 

  46. 46

    Tsouroula, K. et al. Temporal and spatial uncoupling of DNA double strand break repair pathways within mammalian heterochromatin. Mol. Cell 63, 293–305 (2016).

    CAS  Article  Google Scholar 

  47. 47

    Ginno, P.A., Lim, Y.W., Lott, P.L., Korf, I. & Chédin, F. GC skew at the 5′ and 3′ ends of human genes links R-loop formation to epigenetic regulation and transcription termination. Genome Res. 23, 1590–1600 (2013).

    CAS  Article  Google Scholar 

  48. 48

    Harrigan, J.A. et al. Replication stress induces 53BP1-containing OPT domains in G1 cells. J. Cell Biol. 193, 97–108 (2011).

    CAS  Article  Google Scholar 

  49. 49

    Lukas, C. et al. 53BP1 nuclear bodies form around DNA lesions generated by mitotic transmission of chromosomes under replication stress. Nat. Cell Biol. 13, 243–253 (2011).

    CAS  Article  Google Scholar 

  50. 50

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

    CAS  Article  Google Scholar 

  51. 51

    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).

    CAS  Article  Google Scholar 

  52. 52

    Kalocsay, M., Hiller, N.J. & Jentsch, S. Chromosome-wide Rad51 spreading and SUMO-H2A.Z-dependent chromosome fixation in response to a persistent DNA double-strand break. Mol. Cell 33, 335–343 (2009).

    CAS  Article  Google Scholar 

  53. 53

    Ryu, T. et al. Heterochromatic breaks move to the nuclear periphery to continue recombinational repair. Nat. Cell Biol. 17, 1401–1411 (2015).

    CAS  Article  Google Scholar 

  54. 54

    Matsuoka, S. et al. ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage. Science 316, 1160–1166 (2007).

    CAS  Article  Google Scholar 

  55. 55

    Yamada, K., Ono, M., Perkins, N.D., Rocha, S. & Lamond, A.I. Identification and functional characterization of FMN2, a regulator of the cyclin-dependent kinase inhibitor p21. Mol. Cell 49, 922–933 (2013).

    CAS  Article  Google Scholar 

  56. 56

    Nagano, T. et al. Comparison of Hi-C results using in-solution versus in-nucleus ligation. Genome Biol. 16, 175 (2015).

    Article  Google Scholar 

  57. 57

    Wingett, S. et al. HiCUP: pipeline for mapping and processing Hi-C data. F1000Res. 4, 1310 (2015).

    Article  Google Scholar 

  58. 58

    Lawrence, M. et al. Software for computing and annotating genomic ranges. PLOS Comput. Biol. 9, e1003118 (2013).

    CAS  Article  Google Scholar 

  59. 59

    Robinson, M.D., McCarthy, D.J. & Smyth, G.K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    CAS  Article  Google Scholar 

  60. 60

    Hu, Y. et al. OmicCircos: a simple-to-use R Package for the circular visualization of multidimensional omics data. Cancer Inform. 13, 13–20 (2014).

    CAS  Article  Google Scholar 

  61. 61

    Dey, N. et al. Richardson-Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution. Microsc. Res. Tech. 69, 260–266 (2006).

    Article  Google Scholar 

Download references


We thank S. Andrews, K. Tabbada and S. Wingett (Babraham Institute) for probe design and quality control of Hi-C data. Funding was provided by the Polish National Science Centre (2011/02/A/NZ2/00014 to K.G. and 2015/17/D/NZ2/03711 to M.S.) and the Foundation for Polish Science (TEAM to K.G.). Funding to M.R. was provided by NIH (NIH 5 R01 GM 112131). M.A. and E.G. were supported by the Fondation pour la Recherche Médicale (FRM). Funding in G.L.'s laboratory was provided by grants from the European Research Council (ERC-2014-CoG 647344), Agence Nationale pour la Recherche (ANR-14-CE10-0002-01and ANR-13-BSV8-0013), the Institut National contre le Cancer (INCA PLBIO15-199) and the Ligue Nationale contre le Cancer (LNCC).

Author information




F.A., E.G., B.M.J., B.B. and C.A. performed experiments. M.A., V.R. and J.S.I. performed bioinformatic analyses of Hi-C and BLESS data sets. A.B., K.G., M.S., and M.R. performed BLESS experiments. P.F. contributed to capture Hi-C experimental design, experiments and analyses. G.L. conceived and analyzed experiments. F.A. and G.L. wrote the manuscript. All authors commented and edited the manuscript.

Corresponding author

Correspondence to Gaëlle Legube.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Capture Hi-C biological-replicate reports.

a. Table summarizing the number of reads pairs (total or uniquely mapped) obtained for each sample in the two biological replicates (BR#1 and BR#2). Total number of pairs (first lane), or pairs joining two close loci (cis <10kb), two loci on the same chromosome (cis>10kb) or two loci on different chromosomes (trans) are indicated. b. Hi-CUP summary reports showing the proportion of trans, cis close (<10kb) and cis far (>10kb) reads pairs for each samples. c. SeqMonk generated snap shot of read pairs density across chromosome 1, for each samples. Position of 2Mb domains where were designed the probes, as well as AsiSI-induced DSBs positions are shown on the top. Read pairs are strongly enriched in captured domains. d. Box-plot showing the natural log number of interactions (normalized, see Online Methods) between all possible pairs of 2Mb captured (C) or uncaptured (NC) domains on the genome for each samples. (Wilcoxon Mann-Whitney) Center line: median; Box limits the first and third quartiles; Whiskers: maximum and minimum without outliers e. Scatterplot showing the number of interactions (normalized) between all possible pairs of 100kb bins captured for BR#1 (x axis) versus BR#2 (y axis) for undamaged (-4OHT, left) and damaged samples (+4OHT, right).

Supplementary Figure 2 Additional differential (damaged versus undamaged) interaction heat maps.

a-b. Differential heatmaps at a 100kb resolution are shown for BR#2, on the same regions presented Fig. 1b (a) or for both replicates (BR#1 and BR#2) on additional regions located on chromosome 9 and 20 as indicated (b). Data are expressed as natural log of differential interaction count (normalized, see Online Methods). Arrows indicate DSBs positions. Black and grey bars indicate captured domains positions. The γH2AX profiles (normalized ChIP seq counts, smoothed using 100kb windows) obtained across the same regions by ChIP-seq are shown (middle panels, Aymard, F. et al, Nat Struct Mol Biol. 4, 366-74, 2014). Positions are indicated in bp.

Supplementary Figure 3 Interactions between 2-Mb domains surrounding DSBs.

a. Clustering does not correlate with position in the nucleus. In the DIvA system, given that AsiSI induces a constant number of DSBs, clustering can be inferred by γH2AX foci size (Fig. 4a). Following γH2AX staining, images were acquired (objective X100) and foci were identified using the foci 3D picker plugin (ImageJ). Their Euclidian distance from the center was further computed. Analysis was performed on 19 cells acquired from 3 independent experiments. The scatterplot presented below show that foci size does not correlate with distance to center. b. Circos plots showing statistically significant (p<0.05) interactions induced after 4OHT treatment at selected captured domains (3 controls regions (top panels), 3 domains exhibiting high clustering (middle panels) and 3 domains showing low clustering (low panels)). c. Initial proximity potentiates but is not sufficient for DSB clustering. Number of reads (normalized) were scored for each pairs of 2Mb domains either within the same chromosome (intrachromosomal, left panels) or between different chromosomes (interchromosomal, right panels) before (x axis) and after (y axis) DSB induction, for both BR#1 and BR#2 as indicated. As expected intrachromosomal contacts are enriched in all conditions compared to interchromosomal contacts (see scales). DSB induction triggered increased contact frequencies both within and between chromosomes. Of note, domains that exhibit very low contact frequencies before 4OHT (right panels, low read counts) do not show higher contact after 4OHT suggesting that initial proximity favours clustering. However, loci exhibiting high contact frequency before 4OHT do not necessarily show more frequent contact after 4OHT (left panels see arrows), indicating that although necessary, initial proximity is not enough to sustain clustering.

Supplementary Figure 4 DSB clustering is favored at HR-prone DSBs.

a. Clustering ability correlates with RAD51 binding. Number of interactions between each domain were measured and p values between damaged and undamaged samples were computed based on both replicates. –log10(p) are indicated, with negative fold changes (FC<0, damaged<undamaged) in blue, and positive fold change (FC>0, damaged>undamaged) in yellow. DSBs are sorted based on the ChIP-Seq level of RAD51 recruited on the break (Aymard, F. et al, Nat Struct Mol Biol. 4, 366-74, 2014). b. Cleavage efficiency is not significantly different between HR-prone and NHEJ-prone DSBs. Cleavage was measured by BLESS (Crosetto, N. et al, Nat Methods. 4, 362-5, 2013), in DIvA cells at HR-prone or NHEJ-prone DSBs (as indicated) (Clouaire, T. et al, manuscript in preparation). p=0.831 (Wilcoxon-Mann-Whitney test). Center line: median; Box limits: 2nd and 3rd quartiles; Whiskers: Maximum and minimum without outliers; Points: outliers.

Supplementary Figure 5 Cycle dependency of DSB clustering and repair in DIvA cells.

a. For cell cycle analysis in high throughput microscopy analyses, G1 and G2 cells are sorted based on Hoechst intensity. An example of Hoechst distribution for an experiment is shown. b. Averaged foci number (left panel) and foci size (middle panel) in G1 and G2 nuclei using 4 independent experiments (>1000 nuclei in each replicate). Foci number and foci size were set to 1 in G1. Mean and s.e.m are shown for n=4, independent experiments. * p<0.05; **** p<0.001 (one sample t-test). Right panel shows the average ratio between foci size and foci number per cells, hereafter named as the « clustering index » (n=4, independent experiments). c. Experimental pipeline used to analyze repair kinetics of clustered and unclustered DSBs in G1 and cycling cells (Fig. 5a): DIvA cells were first either arrested in G1 using lovastatin treatment for 48h or left untreated (cycling). Cells were next treated 4hours with 4OHT to induce DSBs, and further treated with auxin (IAA) to induce enzyme degradation and repair. Cells were collected at 0h, 2h, 8h, and 14h after IAA addition, and subjected to FACS analysis (Fig. S5d) and cleavage assay (Fig. 5a). Briefly, DNA was extracted and ligated to a biotinylated double strand oligonucleotide cohesive with AsiSI sites. After strepatividin purification, pulled down DNA is measured by qPCR at selected DSBs. Percent of purified DNA compared to input reflects the extent of cleavage of a given DSB in the cell population at a given time point. d. FACS profiles indicating the cell cycle distribution at each time point collected for repair kinetics analysis. e. Western blot was performed in cycling and G1-arrested cells (following lovastatin treatment) before and after damage induction and 2h after IAA addition in order to verify that enzyme degradation following IAA addition is as efficient in both conditions.

Supplementary Figure 6 Repair kinetics in cells synchronized in G1, analyzed by BLESS.

a. Experimental pipeline used for Fig.5b: DIvA cells were synchronized using double thymidine block. 12h after release (entering in G1) cells were treated 4hours with 4OHT to induce DSBs, and further treated with auxin (IAA) for 2 additional hours to induce enzyme degradation and repair. Cells were collected before 4OHT treatment, 4h after 4OHT and 2h after IAA addition and subjected to BLESS. b. FACS analysis of the cell cycle at the different time points used for BLESS. c. Example of BLESS data obtained at a specific AsiSI induced DSB. DSB is indicated by an arrow d. Box plot showing the average BLESS count on +/- 500bp centered on the 100 DSBs analyzed in this study (top panel) or around the other AsiSI sites on the genome (bottom panel). Center line: median; Box limits: 2nd and 3rd quartiles; Whiskers: Maximum and minimum without outliers; Points: outliers.

Supplementary Figure 7 siRNA efficiency, measured by RT–qPCR.

cDNA levels were quantified by RT-qPCR in control siRNAs or NBS1, MRE11, RNF8, 53BP1, XRCC4, SUN1, SUN2 and FMN2 siRNAs transfected DIvA cells. Mean and s.e.m from qPCR technical replicates are shown. A representative experiment is presented (n=3)

Supplementary Figure 8 Changes in DSB clustering, analyzed by high-throughput microscopy.

a. DIvA cells were transfected with the indicated siRNA, treated with 4OHT (4h) and subjected to γH2AX staining. Image acquisition was performed using a high throughput microscope. Average foci size (x axis) and number of foci (y axis) were determined in each cells and plotted against each other. The percent of cluster positive cells relative to the entire population were calculated as described in Fig.6. Left panels show a representative experiment and right panels show the mean and s.e.m of cluster positive cells in independent experiments (RNF8, XRCC4, n=3; Sun1 n=5; 53BP1 n=4). ns, non-significant (paired t-test). b. Clustering index upon depletion of MRE11, NBS1, 53BP1, XRCC4, or RNF8 (top panel) or SUN1, SUN2 and FMN2 (bottom panel) by siRNA was measured as described Fig. S5b. Clustering index in cells transfected with control siRNA is set to 1. The mean and s.e.m of 4 independent experiment is shown. * p<0.05, ** p<0.01, *** p<0.005 (one sample t-test). c. Clustering was analyzed by high throughput microscopy in 4OHT treated DIvA untreated (NT) or pre-treated with DRB (100μM). A representative experiment is shown. d. Quantification of cluster positive cells is shown for two independent experiments upon DRB treatment at 100μM (top panels) or as the mean and s.e.m for 3 independent experiments upon DRB treatment at 20μM (bottom panel), p=0.0003 (paired t-test).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8 and Supplementary Note (PDF 1269 kb)

Supplementary Table 1

Genomic coordinates (hg19) of probes used for Capture Hi-C (XLSX 169 kb)

Supplementary Table 2

Domain names, associated AsiSI sites and size of the gaps between Captured domains (XLSX 15 kb)

Supplementary Table 3

Oligonucleotides for quantitative PCR used in this study (XLSX 10 kb)

Supplementary Table 4

siRNA sequences used in this study (XLSX 9 kb)

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Aymard, F., Aguirrebengoa, M., Guillou, E. et al. Genome-wide mapping of long-range contacts unveils clustering of DNA double-strand breaks at damaged active genes. Nat Struct Mol Biol 24, 353–361 (2017).

Download citation

Further reading


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