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Liquid chromatin Hi-C characterizes compartment-dependent chromatin interaction dynamics

Nature Genetics volume 53, pages 367–378 (2021)Cite this article

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Abstract

Nuclear compartmentalization of active and inactive chromatin is thought to occur through microphase separation mediated by interactions between loci of similar type. The nature and dynamics of these interactions are not known. We developed liquid chromatin Hi-C to map the stability of associations between loci. Before fixation and Hi-C, chromosomes are fragmented, which removes strong polymeric constraint, enabling detection of intrinsic locus–locus interaction stabilities. Compartmentalization is stable when fragments are larger than 10–25 kb. Fragmentation of chromatin into pieces smaller than 6 kb leads to gradual loss of genome organization. Lamin-associated domains are most stable, whereas interactions for speckle- and polycomb-associated loci are more dynamic. Cohesin-mediated loops dissolve after fragmentation. Liquid chromatin Hi-C provides a genome-wide view of chromosome interaction dynamics.

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Fig. 1: Approach for measuring chromatin interaction stability.
Fig. 2: Extensive fragmentation of chromatin leads to liquefied chromatin.
Fig. 3: Hi-C analysis reveals chromosome disassembly upon chromatin liquefication.
Fig. 4: Kinetics of chromatin fragmentation and chromatin dissolution.
Fig. 5: Dissociation kinetics of chromatin interactions at different sub-nuclear structures.
Fig. 6: Chromatin loop dissociation upon fragmentation.
Fig. 7: Illustration of chromatin interaction dynamics in the nucleus and model for cohesin loss after chromatin digestion.

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Data availability

All sequencing data have been submitted to a public data repository (GEO, accession number GSE134590). Data are available through the 4D Nucleome data portal. Source data are provided with this paper.

Code availability

All code for data processing and analysis, described in detail in the Methods, is available through the following GitHub accounts:

https://github.com/tborrman/liquid-chromatin-Hi-C

https://github.com/tborrman/DpnII-seq

https://github.com/dekkerlab/5C-CBFb-SMMHC-Inhib

https://github.com/dekkerlab/cMapping

https://github.com/dekkerlab/cworld-dekker

https://github.com/hms-dbmi/hic-data-analysis-bootcamp

https://github.com/mirnylab/cooltools/tree/master/cooltools

References

  1. Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Rao, S. S. P. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Chen, Y. et al. Mapping 3D genome organization relative to nuclear compartments using TSA-Seq as a cytological ruler. J. Cell Biol. 217, 4025–4048 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Nir, G. et al. Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling. PLoS Genet. 14, e1007872 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Wang, S. et al. Spatial organization of chromatin domains and compartments in single chromosomes. Science 353, 598–602 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Dekker, J. & Mirny, L. A. The 3D genome as moderator of chromosomal communication. Cell 164, 1110–1121 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Nagano, T. et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature 502, 59–64 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Nagano, T. et al. Cell-cycle dynamics of chromosomal organization at single-cell resolution. Nature 547, 61–67 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ramani, V. et al. Massively multiplex single-cell Hi-C. Nat. Methods 14, 263–266 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Naumova, N. et al. Organization of the mitotic chromosome. Science 342, 948–953 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Gibcus, J. H. et al. A pathway for mitotic chromosome formation. Science 359, eaao6135 (2018).

  12. Kaaij, L. J. T., van der Weide, R. H., Ketting, R. F. & de Wit, E. Systemic loss and gain of chromatin architecture throughout zebrafish development. Cell Rep. 24, 1–10.e4 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hug, C. B., Grimaldi, A. G., Kruse, K. & Vaquerizas, J. M. Chromatin architecture emerges during zygotic genome activation independent of transcription. Cell 169, 216–228.e19 (2017).

    Article  CAS  PubMed  Google Scholar 

  14. Bickmore, W. A. & van Steensel, B. Genome architecture: domain organization of interphase chromosomes. Cell 152, 1270–1284 (2013).

    Article  CAS  PubMed  Google Scholar 

  15. Bonev, B. & Cavalli, G. Organization and function of the 3D genome. Nat. Rev. Genet. 17, 772 (2016).

    Article  CAS  PubMed  Google Scholar 

  16. Dekker, J. et al. The 4D nucleome project. Nature 549, 219–226 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Simonis, M. et al. Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture-on-chip (4C). Nat. Genet. 38, 1348–1354 (2006).

    Article  CAS  PubMed  Google Scholar 

  18. Tang, Z. et al. CTCF-mediated human 3D genome architecture reveals chromatin topology for transcription. Cell 163, 1611–1627 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. de Wit, E. et al. CTCF binding polarity determines chromatin looping. Mol Cell 60, 676–684 (2015).

    Article  PubMed  Google Scholar 

  20. Guo, Y. et al. CRISPR inversion of CTCF sites alters genome topology and enhancer/promoter function. Cell 162, 900–910 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Vietri Rudan, M. et al. Comparative Hi-C reveals that CTCF underlies evolution of chromosomal domain architecture. Cell Rep. 10, 1297–1309 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Riggs, A. D. DNA methylation and late replication probably aid cell memory, and type I DNA reeling could aid chromosome folding and enhancer function. Phil. Trans. R. Soc. B 326, 285–297 (1990).

    CAS  PubMed  Google Scholar 

  23. Nasmyth, K. Disseminating the genome: joining, resolving, and separating sister chromatids during mitosis and meiosis. Annu. Rev. Genet. 35, 673–745 (2001).

    Article  CAS  PubMed  Google Scholar 

  24. Alipour, E. & Marko, J. F. Self-organization of domain structures by DNA-loop-extruding enzymes. Nucleic Acids Res. 40, 11202–11212 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Sanborn, A. L. et al. Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes. Proc. Natl Acad. Sci. USA 112, E6456–E6465 (2015).

    Article  CAS  PubMed  Google Scholar 

  26. Fudenberg, G. et al. Formation of chromosomal domains by loop extrusion. Cell Rep. 15, 2038–2049 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Fudenberg, G., Abdennur, N., Imakaev, M., Goloborodko, A. & Mirny, L. A. Emerging evidence of chromosome folding by loop extrusion. Cold Spring Harb. Symp. Quant. Biol. 82, 45–55 (2017).

    Article  PubMed  Google Scholar 

  28. Rao, S. S. P. et al. Cohesin loss eliminates all loop domains. Cell 171, 305–320 e24 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Falk, M. et al. Heterochromatin drives organization of conventional and inverted nuclei. Nature 570, 395–399 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Nuebler, J., Fudenberg, G., Imakaev, M., Abdennur, N. & Mirny, L. A. Chromatin organization by an interplay of loop extrusion and compartmental segregation. Proc. Natl Acad. Sci. USA 115, E6697–E6706 (2018).

    Article  CAS  PubMed  Google Scholar 

  31. Di Pierro, M., Zhang, B., Aiden, E. L., Wolynes, P. G. & Onuchic, J. N. Transferable model for chromosome architecture. Proc. Natl Acad. Sci. USA 113, 12168–12173 (2016).

    Article  PubMed  Google Scholar 

  32. Jost, D., Carrivain, P., Cavalli, G. & Vaillant, C. Modeling epigenome folding: formation and dynamics of topologically associated chromatin domains. Nucleic Acids Res. 42, 9553–9561 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Erdel, F. & Rippe, K. Formation of chromatin subcompartments by phase separation. Biophys. J. 114, 2262–2270 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Michieletto, D., Orlandini, E. & Marenduzzo, D. Polymer model with epigenetic recoloring reveals a pathway for the de novo establishment and 3D organization of chromatin domains. Phys. Rev. X 6, 041047 (2016).

    Google Scholar 

  35. Shi, G., Liu, L., Hyeon, C. & Thirumalai, D. Interphase human chromosome exhibits out of equilibrium glassy dynamics. Nat. Commun. 9, 3161 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  36. MacPherson, Q., Beltran, B. & Spakowitz, A. J. Bottom-up modeling of chromatin segregation due to epigenetic modifications. Proc. Natl Acad. Sci. USA 115, 12739–12744 (2018).

    Article  CAS  PubMed  Google Scholar 

  37. Marshall, W. F. et al. Interphase chromosomes undergo constrained diffusional motion in living cells. Curr. Biol. 7, 930–939 (1997).

    Article  CAS  PubMed  Google Scholar 

  38. Shinkai, S., Nozaki, T., Maeshima, K. & Togashi, Y. Dynamic nucleosome movement provides structural information of topological chromatin domains in living human cells. PLoS Comput. Biol. 12, e1005136 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Nagashima, R. et al. Single nucleosome imaging reveals loose genome chromatin networks via active RNA polymerase II. J. Cell Biol. 218, 1511–1530 (2019).

  40. Bronshtein, I. et al. Transient anomalous diffusion of telomeres in the nucleus of mammalian cells. Phys. Rev. Lett. 103, 018102 (2009).

    Article  Google Scholar 

  41. Hediger, F., Neumann, F. R., Van Houwe, G., Dubrana, K. & Gasser, S. M. Live imaging of telomeres: yKu and Sir proteins define redundant telomere-anchoring pathways in yeast. Curr. Biol. 12, 2076–2089 (2002).

    Article  CAS  PubMed  Google Scholar 

  42. Bronshtein, I. et al. Loss of lamin A function increases chromatin dynamics in the nuclear interior. Nat. Commun. 6, 8044 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Thakar, R., Gordon, G. & Csink, A. K. Dynamics and anchoring of heterochromatic loci during development. J. Cell Sci. 119, 4165–4175 (2006).

    Article  CAS  PubMed  Google Scholar 

  44. Therizols, P., Duong, T., Dujon, B., Zimmer, C. & Fabre, E. Chromosome arm length and nuclear constraints determine the dynamic relationship of yeast subtelomeres. Proc. Natl Acad. Sci. USA 107, 2025–2030 (2010).

    Article  CAS  PubMed  Google Scholar 

  45. Zidovska, A., Weitz, D. A. & Mitchison, T. J. Micron-scale coherence in interphase chromatin dynamics. Proc. Natl Acad. Sci. USA 110, 15555–15560 (2013).

    Article  CAS  PubMed  Google Scholar 

  46. Leibler, L. Theory of microphase separation in block copolymers. Macromolecules 13, 1602–1617 (1980).

    Article  CAS  Google Scholar 

  47. de Gennes, P.-G. Scaling Theory of Polymer Physics (Cornell Univ. Press, 1979).

  48. Matsen, M. W. & Schick, M. Stable and unstable phases of a linear multiblcok copolymer melt. Macromolecules 27, 7157–7163 (1994).

    Article  CAS  Google Scholar 

  49. Dekker, J., Rippe, K., Dekker, M. & Kleckner, N. Capturing chromosome conformation. Science 295, 1306–1311 (2002).

    Article  CAS  PubMed  Google Scholar 

  50. Dostie, J. et al. Chromosome conformation capture carbon copy (5C): a massively parallel solution for mapping interactions between genomic elements. Genome Res. 16, 1299–1309 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Chien, R. et al. Cohesin mediates chromatin interactions that regulate mammalian beta-globin expression. J. Biol. Chem. 286, 17870–17878 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kang, Y., Kim, Y. W., Kang, J., Yun, W. J. & Kim, A. Erythroid specific activator GATA-1-dependent interactions between CTCF sites around the beta-globin locus. Biochim. Biophys. Acta, Gene Regul. Mech. 1860, 416–426 (2017).

    Article  CAS  Google Scholar 

  53. Tolhuis, B., Palstra, R. J., Splinter, E., Grosveld, F. & de Laat, W. Looping and interaction between hypersensitive sites in the active beta-globin locus. Mol. Cell 10, 1453–1465 (2002).

    Article  CAS  PubMed  Google Scholar 

  54. Splinter, E. et al. CTCF mediates long-range chromatin looping and local histone modification in the beta-globin locus. Genes Dev. 20, 2349–2354 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Belaghzal, H., Dekker, J. & Gibcus, J. H. Hi-C 2.0: an optimized Hi-C procedure for high-resolution genome-wide mapping of chromosome conformation. Methods 123, 56–65 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Stephens, A. D., Banigan, E. J., Adam, S. A., Goldman, R. D. & Marko, J. F. Chromatin and lamin A determine two different mechanical response regimes of the cell nucleus. Mol. Biol. Cell 28, 1984–1996 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Stephens, A. D. et al. Chromatin histone modifications and rigidity affect nuclear morphology independent of lamins. Mol. Biol. Cell 29, 220–233 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Banigan, E. J., Stephens, A. D. & Marko, J. F. Mechanics and buckling of biopolymeric shells and cell nuclei. Biophys. J. 113, 1654–1663 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Quinodoz, S. A. et al. Higher-order inter-chromosomal hubs shape 3D genome organization in the nucleus. Cell 174, 744–757 e24 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Xiong, K. & Ma, J. Revealing Hi-C subcompartments by imputing high-resolution inter-chromosomal interactions. Nat. Commun. 10, 5069 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Dialynas, G. K. et al. Plasticity of HP1 proteins in mammalian cells. J. Cell Sci. 120, 3415–3424 (2007).

    Article  CAS  PubMed  Google Scholar 

  62. Liang, C. & Stillman, B. Persistent initiation of DNA replication and chromatin-bound MCM proteins during the cell cycle in cdc6 mutants. Genes Dev. 11, 3375–3386 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ciosk, R. et al. Cohesin’s binding to chromosomes depends on a separate complex consisting of Scc2 and Scc4 proteins. Mol. Cell 5, 243–254 (2000).

    Article  CAS  PubMed  Google Scholar 

  64. Srinivasan, M. et al. The cohesin ring uses its hinge to organize DNA using non-topological as well as topological mechanisms. Cell 173, 1508–1519 e18 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Gartenberg, M. R., Neumann, F. R., Laroche, T., Blaszczyk, M. & Gasser, S. M. Sir-mediated repression can occur independently of chromosomal and subnuclear contexts. Cell 119, 955–967 (2004).

    Article  CAS  PubMed  Google Scholar 

  66. Gibson, B. A. et al. Organization of chromatin by intrinsic and regulated phase separation. Cell 179, 470–484.e21 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Larson, A. G. et al. Liquid droplet formation by HP1α suggests a role for phase separation in heterochromatin. Nature 547, 236–240 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Tatavosian, R. et al. Nuclear condensates of the Polycomb protein chromobox 2 (CBX2) assemble through phase separation. J. Biol. Chem. 294, 1451–1463 (2019).

    Article  CAS  PubMed  Google Scholar 

  69. Plys, A. J. et al. Phase separation of Polycomb-repressive complex 1 is governed by a charged disordered region of CBX2. Genes Dev. 33, 799–813 (2019).

  70. Kaustov, L. et al. Recognition and specificity determinants of the human cbx chromodomains. J. Biol. Chem. 286, 521–529 (2011).

    Article  CAS  PubMed  Google Scholar 

  71. Ferraiuolo, M. A., Sanyal, A., Naumova, N., Dekker, J. & Dostie, J. From cells to chromatin: capturing snapshots of genome organization with 5C technology. Methods 58, 255–267 (2012).

    Article  CAS  PubMed  Google Scholar 

  72. Lajoie, B. R., van Berkum, N. L., Sanyal, A. & Dekker, J. My5C: web tools for chromosome conformation capture studies. Nat. Methods 6, 690–691 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

J.D. and J.F.M. acknowledge support from the National Institutes of Health Common Fund 4D Nucleome Program (U54-DK107980). This work was also supported by a grant from the National Human Genome Research Institute (NHGRI) to J.D. (HG003143) and to Z.W. (HG009446), and by grants from the National Cancer Institute (U54-CA193419) and from the National Institutes of Health (R01-GM105847 to J.F.M. and K99-GM123195 to A.D.S.). J.D. is an investigator of the Howard Hughes Medical Institute. We thank L. A. Mirny and E. J. Banigan for discussions, and J. Ma for sharing K562 sub-compartment assignments.

Author information

Author notes

  1. These authors contributed equally: Houda Belaghzal, Tyler Borrman.

Authors and Affiliations

  1. Program in Systems Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA

    Houda Belaghzal, Denis L. Lafontaine, Sergey V. Venev & Job Dekker

  2. Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA

    Tyler Borrman & Zhiping Weng

  3. Biology Department, University of Massachusetts Amherst, Amherst, MA, USA

    Andrew D. Stephens

  4. Department of Molecular Biosciences, Northwestern University, Evanston, IL, USA

    John F. Marko

  5. Department of Physics and Astronomy, Northwestern University, Evanston, IL, USA

    John F. Marko

  6. Howard Hughes Medical Institute, Chevy Chase, MD, USA

    Job Dekker

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Contributions

J.D. conceived the study. H.B. performed all 3C, 5C, Hi-C and liquid chromatin Hi-C and chromatin fractionation experiments. D.L.L. performed restriction digestion efficiency (DpnII-seq) experiments. A.D.S. performed micromechanical studies and analyzed the data. T.B. and H.B. analyzed data. S.V. contributed analysis tools for liquid chromatin Hi-C analysis. J.F.M. provided polymer scaling ideas relevant to data interpretation. All authors contributed to the writing of the manuscript.

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Correspondence to Job Dekker.

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The authors declare no competing interests.

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Peer review information Nature Genetics thanks Bing Ren and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Chromosome conformation in isolated nuclei.

a, Hi-C 2.0 intra-chromosomal interaction maps for K562 cells (top) and purified nuclei (bottom). b, 5 C interaction map of 1 Mb region surrounding the beta-globin locus in K562 cells. Top: cells. Bottom: purified nuclei. CTCF-mediated interactions are preserved in purified nuclei. Red circles: positions of CTCF sites, purple square Beta-globin locus control region (LCR). c, Representative 3C-PCR (out of two experiments) for a 44,120 kb region surrounding the beta-globin LCR on chromosome 11, detects at high resolution the known looping interactions between the LCR and the expressed gamma-globin genes (HBE1, HBG2) in K562 cells. Looping interactions are not detected in GM12878 cells that do not express these genes. Top: cells. Bottom: purified nuclei. Each data point is the average of 3 PCR reactions; error bars indicate standard error of the mean. d, Compartmentalization saddle plots: average intra-chromosomal interaction frequencies between 100 kb bins, normalized by genomic distance. Bins are sorted by their PC1 value derived from Hi-C data obtained with K562 cells. In these plots preferential B-B interactions are in the upper left corner, and preferential A-A interactions are in the lower right corner. Numbers in the corners represent the strength of AA interactions as compared to AB interactions and BB interactions over BA interactions. Left: cells. Right: purified nuclei. e, Spearman correlation of PC1 in cells vs PC1 in nuclei for chromosome 2 at 100 kb resolution (ρ = 0.99).

Extended Data Fig. 2 Chromosome conformation dissolution upon chromatin fragmentation.

a, Workflow for Liquid chromatin Hi-C. b, Illustration of loss of structure metric using a pre-digested sample and a control. c, Hi-C interaction maps and compartmentalization saddle plots for a second replicate of control nuclei (incubated for 4 hours in restriction buffer) and nuclei pre-digested with HindIII for 4 hours. d, Left: Spearman correlation of DpnII restriction digestion efficiency (DpnII-seq) and PC1 for chromosome 2 at 40 kb resolution. Right: Partial correlation of LOS (LOS residuals) with PC1 after controlling for restriction efficiency (DpnII-seq), for chromosome 2 at 40 kb resolution. Spearman correlation is indicated. e, compartmentalization saddle plots for the corresponding conditions. Numbers indicate strength of A-A and B-B interactions for inter-chromosomal interactions.

Extended Data Fig. 3 Experimental protocol and computational workflow for DpnII-seq.

a, Schematic of DpnII-seq experimental protocol for recovering DNA fragments digested by the restriction enzyme DpnII. b, Directed graph of DpnII-seq computational pipeline. c, Histogram of distance to nearest DpnII recognition site for each recovered DpnII digested fragment. d, Raw DpnII-seq signal displaying multiple copy number states (2 N, 3 N, 4 N) within chromosome 3 (data binned at 40 kb). e, Copy number corrected DpnII-seq signal displaying single copy number state (2 N) across chromosome 3.

Extended Data Fig. 4 Average fragment size per bin and correlation with chromatin stability.

a, DNA purified from nuclei pre-digested with DpnII for 4 hours were separated into slices of three sizes and run on a Fragment Analyzer. One experiment was performed. b, Fragment Analyzer distributions of DNA fragment sizes for the three separated slices (RFU: relative fluorescence unit, LM: lower marker, fragment sizes at distribution peaks are given in blue). c, Top plot: Eigenvector 1 values (PC1, 40 kb resolution) across a section of chromosome 2, representing A (red) and B (blue) compartments. Bottom three plots: Normalized coverage of fragments from given slice size across a section of chromosome 2. d, Percentages of fragments mapped to each subcompartment for given slice size. e, Top plot: LOS along chromosome 2 at 40 kb resolution for nuclei pre-digested with DpnII. Middle plot: Average fragment size estimated for every 40 kb bin after pre-digestion with DpnII (Methods). Bottom plot: LOS-residuals for nuclei pre-digested with DpnII after correction for average fragment size. f, Boxplot of average fragment size for A compartment bins (n = 35836) and B compartment bins (n = 33252). Significance determined by two-sample two tailed t-test (p < 2.2e-16, t = -80.535, d.f. = 67270, 95% CI = -0.1228385,-0.1170014). Boxplot middle line is the median, the lower and upper edges of the box are the first and third quartiles, the whiskers extend to interquartile range (IQR) × 1.5 from the box. Outliers are represented as points. g, Left plot: correlation between LOS for nuclei pre-digested with DpnII and average fragment size. Grey line indicates moving average used for residual calculation. Right plot: partial correlation between residuals of LOS for nuclei pre-digested with DpnII and residuals of PC1 after correcting for correlations between LOS and average fragment size and PC1 and average fragment size (for chromosome 2, Spearman correlation values are indicated). h, Left plot: Correlation between DpnII-seq signal and average fragment size. Right plot: correlation between residuals of LOS after correcting for average fragment size and residuals of LOS after correcting for DpnII-seq signal (for chromosome 2, Spearman correlation values are indicated). i, Partial correlation between residuals of t1/2 and residuals of PC1 after correcting for correlations between t1/2 and average fragment size and PC1 and average fragment size.

Extended Data Fig. 5 Liquid chromatin Hi-C results are reproducible using the restriction enzyme FatI.

a, Restriction sites for the selected restriction enzymes. Black triangles denote cut sites. b, Top plot: Eigenvector 1 values (PC1, 40 kb resolution) across a section of chromosome 2, representing A (red) and B (blue) compartments. Bottom three plots: Coverage of restriction sites (40 kb resolution). Spearman correlation between restriction site coverage and PC1 is given for each restriction site track. c, Third replicate of DpnII predigest liquid chromatin Hi-C. Hi-C interaction maps of chromosome 2 binned at 500 kb. Bottom left: control nuclei in restriction buffer for 4 hours. Top right: nuclei digested for 4 hours with DpnII prior to Hi-C. Left track: Eigenvector 1 values (PC1, 40 kb resolution) across a section of chromosome 2, representing A (red) and B (blue) compartments. d, Top plot: LOS along chromosome 2 at 40 kb resolution for nuclei pre-digested with DpnII. Middle plot: DpnII-seq signal. Bottom plot: LOS-residuals for nuclei pre-digested with DpnII after correction for DpnII-seq signal. e, FatI predigest liquid chromatin Hi-C. Hi-C interaction maps of chromosome 2 binned at 500 kb. Bottom left: control nuclei in restriction buffer for 4 hours. Top right: nuclei digested for 4 hours with FatI prior to Hi-C. Left track: Eigenvector 1 values (PC1, 40 kb resolution) across a section of chromosome 2, representing A (red) and B (blue) compartments. f, Top plot: LOS along chromosome 2 at 40 kb resolution for nuclei pre-digested with FatI. Middle plot: FatI-seq signal. Bottom plot: LOS-residuals for nuclei pre-digested with FatI after correction for FatI-seq signal. g, Left plot: Correlation between LOS for nuclei pre-digested with DpnII and PC1. Right plot: partial correlation between residuals of LOS for nuclei pre-digested with DpnII and residuals of PC1 after correcting for correlations between LOS and DpnII-seq and PC1 and DpnII-seq signal (for chromosome 2, Spearman correlation values are indicated). h, Left plot: Correlation between LOS for nuclei pre-digested with FatI and PC1. Right plot: partial correlation between residuals of LOS for nuclei pre-digested with FatI and residuals of PC1 after correcting for correlations between LOS and FatI-seq and PC1 and FatI-seq signal (for chromosome 2, Spearman correlation values are indicated). i, Correlation between LOS for nuclei pre-digested with FatI and LOS for nuclei pre-digested with DpnII (genome wide, Spearman correlation values are indicated). j, Correlation between residuals of LOS for nuclei pre-digested with FatI and residuals of LOS for nuclei pre-digested with DpnII after correcting for correlations between FatI LOS and FatI-seq and DpnII LOS and DpnII-seq (genome wide, Spearman correlation values are indicated).

Extended Data Fig. 6 Variations in Half-life and LOS are not explained by DpnII digestion kinetics.

a, DpnII-seq signals along chromosome 2 after indicated times of digestion. Spearman correlations between DpnII-seq and t1/2 at each timepoint is indicated. b, t1/2 residuals along chromosome 2 after correcting t1/2 values by the correlation between t1/2 and DpnII-seq signals shown on the left obtained after the indicated times of digestion. Spearman correlation between t1/2 residuals and PC1 residuals are indicated. c, Top: Genome wide scatterplot of t1/2 versus 1 hour DpnII-seq signal. Gray line: moving average. Bar plot above shows the number of loci displaying various levels of DpnII-mediated cuts. Bottom: residuals of t1/2 calculated by subtracting t1/2 from the corresponding average t1/2 (gray line in top plot) plotted vs. number of DpnII cuts. Red dots: loci in the A compartment; Blue dots: loci in the B compartment. The majority of loci have 500-1100 cuts. When comparing loci with similar number of DpnII cut we observe that loci in the A compartment have shorter t1/2 values as compared to loci in the B compartment. d, Top: LOS along chromosome 2 at the indicated timepoints of digestion and calculated by comparison to Hi-C data obtained after 1 hour of digestion. Middle: calculation of t1/2 from LOS at different timepoints. Bottom: t1/2 along chromosome 2. This t1/2 is calculated using the Hi-C data obtained after 1 hour of pre-digestion as starting point. e, Partial correlation between LOS and PC1 after correcting for their correlations with DpnII-seq. LOS (at 2 hours) is calculated as in panel C using the Hi-C data obtained after 1 hour of pre-digestion as starting point. f, Partial correlation between t1/2 and PC1 after correcting for their correlations with DpnII seq. t1/2 is calculated as in panel D using the Hi-C data obtained after 1 hour of pre-digestion as starting point. Spearman correlations are indicated.

Extended Data Fig. 7 Liquid chromatin-Hi-C protocol and quantification of loss of structure after chromatin pre-digestion.

a, Workflow for Liquid chromatin Hi-C timecourse. CL = cross-linking step. b, Compartment strength derived from compartment saddle plots (See Methods). Left: Diagram depicting compartment strength calculation for B-B interactions. Plot to the right of diagram: B-B interaction strength as a function of bin number for all timepoints of the time course. Right: Diagram depicting compartment strength calculation for A-A interactions. Plot to the right of diagram: A-A interaction strength as a function of bin number for all time points of the time course. c, Top: LOS signal across a 40 Mb region on chromosome 2 calculated for indicated timepoints in the digestion timecourse. Line colors as in Fig. 4e. Bottom: Exponential curve fit to LOS timepoints for a single 40 kb bin. t1/2 (dashed vertical blue line) representing time elapsed to reach half saturation of LOS signal. d, Left: Density distributions of t1/2 for A and B compartments. Right: t1/2 saddle plots: average intra-chromosomal interaction frequencies between 40 kb bins, normalized by genomic distance. Bins are sorted by their t1/2 value derived from digestion timecourse. Bins with high t1/2 preferentially interact (bottom right of heatmap) and bins with low t1/2 preferentially interact (top left of heatmap). e, Scatterplot of t1/2 vs t1/2 for two timecourse replicates (R1 and R2) on chromosome 2. Regression line (red). Spearman correlation is indicated. f, Scatterplot of PC1 vs t1/2 for chromosome 2. A compartment (red); B compartment (blue). g, Left: Scatterplot of percent interactions occurring in cis within a 6 Mb distance out of total genome wide interactions for each 40 kb bin in control Hi-C map (Cis %) vs PC1. Middle: Cis% vs t1/2. Right: Scatterplot of partial correlation between PC1 and t1/2 controlled by Cis %. A compartment (red); B compartment (blue). Solid red lines are regression lines. Spearman correlations are indicated.

Extended Data Fig. 8 Associations between sub-nuclear structures and chromatin interaction stability.

a, Spearman correlation matrix between signals for various chromatin state markers of various sub-nuclear structures, chromatin remodellers and histone modifications with row order determined by hierarchical clustering. b, The genome was split into 16 bins, where each bin corresponds to sets of loci that share the same t1/2 interval. For each t1/2 interval the mean z-score signal enrichment for various markers of sub-nuclear structures, chromatin remodellers and histone modifications was calculated and shown as a heatmap. Row order determined by hierarchical clustering. c, 3 Mb region surrounding HoxD locus. Top: Hi-C contact map for K562 control nuclei showing the position of the HoxD locus. Tracks: ChIP-seq tracks for polycomb subunits (cyan) and the polycomb associated histone modification H3K27me3 (green). t1/2 (blue). Minus strand and plus-strand signal of total RNA-seq (red). Refseq Genes (blue/black). The polycomb-bound domain displays shorter half-life compared to expressed genes in flanking regions.

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Supplementary Tables 1–4

Supplementary Video 1

Example of measurement of the elasticity of a single isolated nucleus. This nucleus is not digested with a restriction enzyme. Example of measurement of the elasticity of a single isolated nucleus. This nucleus is digested with DpnII prior to measurement for 1 hour.

Supplementary Video 2

Example of measurement of the elasticity of a single isolated nucleus. This nucleus is digested with DpnII prior to measurement for 1 hour.

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Data shown in Fig. 4b

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Data shown in Fig. 5b

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Unprocessed Western Blots

Source Data Extended Data Fig. 8

Statistical source data for Extended Data Figure 8a

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Belaghzal, H., Borrman, T., Stephens, A.D. et al. Liquid chromatin Hi-C characterizes compartment-dependent chromatin interaction dynamics. Nat Genet 53, 367–378 (2021). https://doi.org/10.1038/s41588-021-00784-4

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