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

Nature Structural & Molecular Biology volume 24, pages 353–361 (2017)Cite this article

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Abstract

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.

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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.

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Acknowledgements

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).

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Author notes

  1. François Aymard, Marion Aguirrebengoa and Emmanuelle Guillou: These authors contributed equally to this work.

Authors and Affiliations

  1. LBCMCP, Centre de Biologie Integrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France

    François Aymard, Marion Aguirrebengoa, Emmanuelle Guillou, Beatrix Bugler, Coline Arnould, Vincent Rocher & Gaëlle Legube

  2. Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK

    Biola M Javierre & Peter Fraser

  3. Bioinformatic Plateau I2MC, INSERM and University of Toulouse, Toulouse, France

    Jason S Iacovoni

  4. Laboratory of Bioinformatics and Systems Biology, Centre of New Technologies, University of Warsaw, Warsaw, Poland

    Anna Biernacka, Magdalena Skrzypczak & Krzysztof Ginalski

  5. Department of Biochemistry and Molecular Biology, University of Texas Medical Branch at Galveston, Galveston, Texas, USA

    Maga Rowicka

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Contributions

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.

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Correspondence to Gaëlle Legube.

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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)

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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). https://doi.org/10.1038/nsmb.3387

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