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3D ATAC-PALM: super-resolution imaging of the accessible genome

Abstract

To image the accessible genome at nanometer scale in situ, we developed three-dimensional assay for transposase-accessible chromatin-photoactivated localization microscopy (3D ATAC-PALM) that integrates an assay for transposase-accessible chromatin with visualization, PALM super-resolution imaging and lattice light-sheet microscopy. Multiplexed with oligopaint DNA–fluorescence in situ hybridization (FISH), RNA–FISH and protein fluorescence, 3D ATAC-PALM connected microscopy and genomic data, revealing spatially segregated accessible chromatin domains (ACDs) that enclose active chromatin and transcribed genes. Using these methods to analyze genetically perturbed cells, we demonstrated that genome architectural protein CTCF prevents excessive clustering of accessible chromatin and decompacts ACDs. These results highlight 3D ATAC-PALM as a useful tool to probe the structure and organizing mechanism of the genome.

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Fig. 1: Visualizing the accessible genome topology by 3D ATAC-PALM.
Fig. 2: ACDs are associated with active chromosomal segments.
Fig. 3: Structural variation of accessible chromatin upon acute loss of CTCF.

Data availability

The raw and processed next-generation sequencing data was deposited to NCBI GEO with public accession number GSE126112. The source data for figures and extended figures are available online as Source Data. Other data supporting the findings of this study are available from the corresponding authors upon reasonable request.

Code availability

The software for identifying, localizing and plotting single-molecule data is freely available after execution of a research license with HHMI. The codes for the g(r) and DBSCAN analysis is freely available from https://github.com/ammondongp/3D_ATAC_PALM.

References

  1. 1.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Dekker, J. et al. Capturing chromosome conformation. Science 295, 1306–1311 (2002).

    CAS  PubMed  Google Scholar 

  3. 3.

    Wit, E. De & Laat, W. De A decade of 3C technologies: insights into nuclear organization. Genes Dev. 26, 11–24 (2012).

    PubMed  PubMed Central  Google Scholar 

  4. 4.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Dekker, J., Marti-Renom, M. A. & Mirny, L. A. Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data. Nat. Rev. Genet. 14, 390–403 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Finn, E. H. et al. Extensive heterogeneity and intrinsic variation in spatial genome organization. Cell 176, 1502–1515 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Levine, M., Cattoglio, C. & Tjian, R. Looping back to leap forward: transcription enters a new era. Cell 157, 13–25 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Wu, C. The 5’ ends of Drosophila heat shock genes in chromatin are hypersensitive to DNase I. Nature 286, 854–860 (1980).

    CAS  PubMed  Google Scholar 

  9. 9.

    Boyle, A. P. et al. High-resolution mapping and characterization of open chromatin across the genome. Cell 132, 311–322 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Chen, X. et al. ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing. Nat. Methods 13, 1013–1020 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Grimm, J. B. et al. Bright photoactivatable fluorophores for single-molecule imaging. Nat. Methods 13, 985–988 (2016).

    CAS  PubMed  Google Scholar 

  14. 14.

    Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).

    CAS  PubMed  Google Scholar 

  15. 15.

    Chen, B. C. et al. Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346, 1257998 (2014).

    PubMed  PubMed Central  Google Scholar 

  16. 16.

    Legant, W. R. et al. High-density three-dimensional localization microscopy across large volumes. Nat. Methods 13, 359–365 (2016).

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Huang, B., Wang, W., Bates, M. & Zhuang, X. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810–813 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Peebles, P. J. E. Statistical analysis of catalogs of extragalactic objects. I. theory. Astrophys. J. 185, 413 (1973).

    Google Scholar 

  19. 19.

    Sengupta, P. et al. Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis. Nat. Methods 8, 969–975 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Ester, M., Kriegel, H. P., Sander, J. & Xu, X. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proc. 2nd International Conference on Knowledge Discovery and Data Mining (KDD ‘96) 226–231 (AAAI Press, 1996).

  21. 21.

    Sakaue-Sawano, A. et al. Genetically encoded tools for optical dissection of the mammalian cell cycle. Mol. Cell 68, 626–640 (2017).

    CAS  PubMed  Google Scholar 

  22. 22.

    Kieffer-Kwon, K. R. et al. Myc regulates chromatin decompaction and nuclear architecture during B cell activation. Mol. Cell 67, 566–578.e10 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Beliveau, B. J. et al. Versatile design and synthesis platform for visualizing genomes with oligopaint FISH probes. Proc. Natl Acad. Sci. USA 109, 21301–21306 (2012).

    CAS  PubMed  Google Scholar 

  24. 24.

    Beliveau, B. J. et al. Single-molecule super-resolution imaging of chromosomes and in situ haplotype visualization using Oligopaint FISH probes. Nat. Commun. 6, e7147 (2015).

    Google Scholar 

  25. 25.

    Boettiger, A. N. et al. Super-resolution imaging reveals distinct chromatin folding for different epigenetic states. Nature 529, 418–422 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Bintu, B. et al. Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells. Science 362, eaau1783 (2018).

    PubMed  PubMed Central  Google Scholar 

  28. 28.

    Sabari, B. R. et al. Coactivator condensation at super-enhancers links phase separation and gene control. Science 361, 387–392 (2018).

    Google Scholar 

  29. 29.

    Jin, C. H3.3/H2A.Z double variant-containing nucleosomes mark ‘nucleosome-free regions’ of active promoters and other regulatory regions. Nat. Genet. 41, 941–945 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Nora, E. P. et al. Targeted degradation of CTCF decouples local insulation of chromosome domains from genomic compartmentalization. Cell 169, 930–944 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Nishimura, K., Fukagawa, T., Takisawa, H., Kakimoto, T. & Kanemaki, M. An auxin-based degron system for the rapid depletion of proteins in nonplant cells. Nat. Methods 6, 917–922 (2009).

    CAS  PubMed  Google Scholar 

  32. 32.

    Wutz, G. et al. Topologically associating domains and chromatin loops depend on cohesin and are regulated by CTCF, WAPL, and PDS5 proteins. EMBO J. 36, 3573–3599 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Hsieh, T. H. S. Mapping nucleosome resolution chromosome folding in yeast by Micro-C. Cell 162, 108–119 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Hsieh, T.-H. S. et al. Resolving the 3D landscape of transcription-linked mammalian chromatin folding. Preprint at bioRxiv https://doi.org/10.1101/638775 (2019).

  35. 35.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    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).

    CAS  PubMed  Google Scholar 

  37. 37.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    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.

  39. 39.

    Li, G. et al. Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell 148, 84–98 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Xie, L. et al. A dynamic interplay of enhancer elements regulates Klf4 expression in naïve pluripotency. Genes Dev. 31, 1795–1808 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. & Zhuang, X. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, 356–372 (2015).

    Google Scholar 

  42. 42.

    Shah, S. et al. Dynamics and spatial genomics of the nascent transcriptome by intron seqFISH. Cell 174, 363–376.e16 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Corces, M. R. et al. The chromatin accessibility landscape of primary human cancers. Science 362, e1898 (2018).

    Google Scholar 

  44. 44.

    Picelli, S. et al. Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. Genome Res. 24, 2033–2040 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Liu, Z. et al. 3D imaging of Sox2 enhancer clusters in embryonic stem cells. eLife 3, 1–29 (2014).

    Google Scholar 

  46. 46.

    Kiskowski, M. A., Hancock, J. F. & Kenworthy, A. K. On the use of Ripley’s K-function and its derivatives to analyze domain size. Biophys. J. 97, 1095–1103 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Veatch, S. L. et al. Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting. PLoS ONE 7, e31457 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank X. Darzacq, S. Chong, T. Graham, D. McSwiggen and C. Cattoglio for critical reading of the manuscript, the Tjian-Darzacq laboratory members for helpful discussions and P. Sengupta and H. Rouault for advice on data analysis. We thank D. Walpita and K. Schaefer with assistance for fluorescence-activated cell sorting experiments, D. Alcor for Airyscan Imaging and M. Radcliff for assistance. This work is supported by the Howard Hughes Medical Institute (HHMI) and the Janelia Visitor Program. Y.F.Q. and B.Z. acknowledge support by the National Science Foundation Grant MCB-1715859. H.Y.C. acknowledges support by NIH grant P50-HG007735. X.C. is supported by Swedish Research Council International Postdoctoral Fellowship (VR-2016- 06794) and starting grant (VR-2017-02074), Jeanssons foundation grant (JS2018-0004) and a Vleugl grant. W.R.L. acknowledges support from the Searle Scholars Program, the Beckman Young Investigator Program, an NIH New Innovator Award (DP2GM136653) and the Packard Fellows Program.

Author information

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Authors

Contributions

L.X. and Z.L. conceived and designed the study. L.X., P.D., T.-H.S.H. and X.C. performed the experiments and analyzed the data. L.X., P.D., Z.L. and R.T. wrote the manuscript. Z.L and R.T. supervised the study.

Corresponding authors

Correspondence to Robert Tjian or Zhe Liu.

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The authors declare no competing interests.

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Peer review information Rita Strack was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 3D ATAC-PALM labeling strategy.

a, N-hydroxysuccinimide (NHS) ester chemical conjugation chemistry. PA-JF549 dye coupled with the NHS ester reacts with the primary amine group on the Tn5 ME oligos to yield the stable dye-oligo conjugate via the covalent amide bond. b, The chromatogram of PA-JF549 NHS ester and oligo amine reaction by reverse phase High Pressure Liquid Chromatography (HPLC). The oligo-dye stable conjugates (smaller peaks as indicated by arrows) were selectively purified. Representative image from n = 3 independent experiments. c, Tagmentation analysis of in vitro constituted Tn5-PA-JF549 and Nextera Tn5 transposome by combining the Tn5 transposome with mouse genomic DNA followed by PCR and an electropherogram analysis by Bioanalyzer. A reaction without transposase was used as a negative control. d-f, Genome-wide comparison of ATAC-seq libraries prepared from mouse ESCs by using either in-house prepared Tn5 PA-JF549 or commercially available Nextera Tn5. The ATAC-seq experiment for Tn5 PA-JF549 was performed after 3D ATAC-PALM imaging from the same sample. The comparison was made by analyzing the insert size distribution (d), the enrichment around transcription start sites (TSS) (e) and at all ATAC-seq peaks (f). In (f), a Pearson correlation coefficient was calculated by genome-wide correlation analysis. g, Representative tracks for Tn5 PA-JF549 ATAC-seq, Nextera Tn5 ATAC-seq and DNaseI-seq (ENCODE) data illustrated by using UCSC genome browser. Cis-regulatory elements representing promoters (for Klf4 and Rad23b genes) and enhancers (for Klf4 gene) are highlighted in the shaded area. Experiments in Fig. c-g were repeated twice with similar results.

Extended Data Fig. 2 Characterization of 3D ATAC-PALM localizations.

a, The box plot compares the number of 3D ATAC-PALM localizations in the full-dose (73 cells, ~100 nM Tn5 PA-JF549) and half-dose (36 cells, ~50 nM) labeling conditions. The middle line represents median. The two-sided Student’s t-test was performed. b, ATAC-PALM localizations (lower left) were separated as in-nucleus and out-nucleus fractions based on the H2B-GFP mask (upper left). The merged image was shown in the upper right panel. The color bar indicates the localization density calculated by using a canopy radius of 250 nm. Lower right panel shows the percentage of localizations falling into the H2B-GFP mask from 30 cells. The middle line represents median. c, Pair auto-correlation function g(r) of ATAC-PALM localizations calculated for MEFs. The center curve represents the mean value and the error bars represent S.E.M. d, Schematics for the FUCCI(CA) system in which the first 100 amino acids of hCdt1 lacking the Cy motif (1/100) Cy(-) is fused to mClover and the first 100 amino acids of hGeminin is fused to HaloTag stained by the JF646 HaloTag ligand. G1 phase cells exhibit only green and S phase cells display only far red fluorescence, whereas dual color positive cells correspond to G2/M phase. e, Pair auto-correlation function g(r) for ATAC-PALM localizations calculated across different cell cycle phases. The error bars represent S.E.M. The two-sided Mann-Whitney U test was performed. f, ATAC-seq peak density distribution in the WT (grey line) and TSA treated (green line) cells for each of 500 bins across chromosome 1. Green arrowheads indicate new accessible chromatin induced by TSA treatment. g, Heatmaps of ATAC-seq signal were plotted over CTCF binding sites (putative insulator sites), enhancers (defined by H3K27ac ChIP-seq) and promoter regions in the mouse genome with DMSO or TSA treatment (50µM, 6h). Statistics source data are provided in Source Data Extended Fig. 2.

Source Data Extended Fig. 2

Extended Data Fig. 3 Two-color 3D PALM imaging of accessible chromatin and landmark proteins in the active chromatin.

a and b, PCR genotyping validates the correct knock-in of HaloTag in frame with histone variant H2A.Z (a) or Mediator subunit MED1 (b) coding sequence in mESCs. We obtained heterozygous and homozygous HaloTag labeling to endogenous H2A.Z and MED1, respectively. All knock-in cells were validated by Sanger sequencing. Experiments were repeated two times. c, 2D pair cross-correlation function C(r) calculated for accessible chromatin localizations and H2A.Z or MED1, in contrast to that of HP1 in Fig. 2g. Circles represent mean values for cross-correlation function at a given radius (r). The error bars represent S.E.M. d, Comparison of pair auto-correlation function g(r) calculated with ATAC labeling alone and ATAC labeling - DNA FISH condition. The error bars represent S.E.M. The two-sided Mann-Whitney U test was performed. Experiments were repeated three times. e, 3D illustration of colocalized accessible chromatin and HaloTag labeled H2A.Z protein localizations within a single nucleus. The color-coded localization density was calculated with a canopy radius of 250 nm. Scale bar: 2µm. The accessible chromatin was labelled with PA-JF549, while H2A.Z-HaloTag molecules were labelled with PA-JF646. f and g, 3D illustration of colocalized accessible chromatin and HaloTag labeled H2A.Z protein localizations in representative sub-regions with volume of 2µm×2µm×2µm. Scale bar: 1µm. h and i, 3D illustration of colocalized accessible chromatin and HaloTag-MED1 protein localizations in representative sub-regions with volume of 2µm×2µm×2µm. Scale bar: 1µm. Experiments were repeated 3 times and data were pooled together for analysis for (d)-(h). Statistics source data are provided in Source Data Extended Fig. 3.

Source Data Extended Fig. 3

Extended Data Fig. 4 Efficient depletion of CTCF by the AID degron system.

a, Western blotting (WB) analysis of endogenous HaloTag-mAID-CTCF at indicated time points after the auxin treatment and wash off recovery with OCT4 as the internal control. b, Quantifying WB intensity as grey scale values for the corresponding WB bands in (a). c, Single cell analysis of HaloTag-mAID-CTCF and OCT4 protein levels after auxin treatment. HaloTag-mAID-CTCF was stained with 100nM HaloTag ligand JF549 and OCT4 was detected by immunofluorescence. FU stands for arbitrary fluorescent unit, with extra-cellular background subtracted. The middle line represents mean fluorescence value. Experiment was repeated two times for (a)-(c) with similar results. Two-sided Mann-Whitney U test was used for analysis with p value for Halo JF549 group < 0.0001 and for OCT4 group 0.3232. d, Flow cytometry analysis of CTCF levels before (-auxin), after (+auxin) auxin treatment and after auxin wash off. The parent Tir1 ES cells (Tir1 – Auxin; Tir1 + Auxin) were used as the negative control. ~50,000 gated live cells were recorded and analyzed for each condition. Experiments were repeated three times. e, DNA synthesis analysis of HaloTag-mAID-CTCF ESCs by the Click-iT EdU labeling kit at the indicated time points (D, Days) after auxin treatment. Experiments were performed two times and representative images are shown. f, Cell proliferation analysis of Wild type (WT), parental Tir1, and two clones of Halo-mAID-CTCF ESCs. Upper panel, without auxin treatment, different cell lines showed similar growth rates. Lower panel, acute CTCF depletion significantly slowed down cell proliferation after 36 hours (two-tailed Student’s t-test with p value < 0.05). Data from two technical replicates from two N-CTCF-mAID clones were shown. g, Single cell colony formation assay by alkaline phosphatase staining for WT, parental Tir1, and Halo-mAID-CTCF ESCs at indicated time points after auxin treatment. Biological replicates n = 2. Statistics source data are provided in Source Data Extended Fig. 4.

Source Data Extended Fig. 4

Extended Data Fig. 5 Enhanced clustering of ACDs upon CTCF depletion.

a, Pair auto-correlation function g(r) of ATAC-PALM localizations from GFP-mAID-CTCF ESCs under normal, auxin-treated and auxin wash-off (~24 hours) conditions. The error bars represent S.E.M. Two-sided Mann-Whitney U test was performed. b, HaloTag-mAID-CTCF cells were processed for genome-wide ATAC-seq analysis under conditions including without auxin, auxin treatment and washout after auxin treatment. Three biological replicates were performed. c, ATAC-seq enrichment at a representative genomic region under normal (-auxin), auxin-treated (+auxin) and recovery conditions for HaloTag-mAID-CTCF cells. CTCF ChIP-seq track is displayed below as a reference. Experiments were performed 3 times. d, Bi-allelic CTCF-HaloTag knock-in cells were infected with either lentiviral particles containing the empty vector (shCon) or lentiviral vectors expressing two independent shRNAs against CTCF (#1 and #2). Cells were selected with Puromycin for two days and stained with 200nM JF549 HaloTag ligand and DAPI before confocal imaging. Biological replicates n = 2. e, Enhanced accessible chromatin clustering after shRNA mediated CTCF knockdown, which was monitored by staining cells with 200nM JF646. The g(r) analysis of 3D ATAC-PALM localizations showed significant increased g(0) in CTCF knockdown cells, compared with control cells. The curve center represents the mean and the error bar represents S.E.M. The two-sided Mann-Whitney U test was performed. f, CTCF knockdown cells were processed for genome-wide ATAC-seq analysis. CTCF knockdown by both shRNAs (C #1 and C #2) markedly reduced the chromatin accessibility at CTCF binding sites compared to shCon cells without significantly affecting that at enhancers and promoters. g, Violin plot of localization density of top 100 rank ordered ACDs among 4 individual cells for each condition. The black bar indicates the median value. For statistical test, data from 4 individual cells for each condition were pooled together and two-sided Mann-Whitney U test was applied. Statistics source data are provided in Source Data Extended Fig. 5.

Source Data Extended Fig. 5

Extended Data Fig. 6 Measuring structural changes of ATAC-rich and ATAC-poor segments upon CTCF depletion by Oligopaint DNA-FISH.

a-b, Alignment of Hi-C heatmap, ATAC-seq, CTCF ChIP-seq tracks for two chromosomal regions harboring pluripotency genes Klf4 (Chr4) and Nanog (Chr6). ATAC-rich (R1-6; red) and ATAC-poor (P1-5; black) segments are underlined. The sizes of each domain are R1(633kb),P1(1133kb), R2(643kb), P2(1100kb), R3(1120kb), R4(1250kb), P3(740kb), R5(640kb), P4(690kb), P5(690kb), R6(990kb). See details on the domain coordinates in the Methods. c, Two-dimensional sphericity score and 3D volume (by voxels) plot of all the ATAC-rich and ATAC-poor segments (iso-surfaces) in Supplementary Video 6 marked by 3D Oligopaint DNA-FISH probes. d, Violin plot of 3D volumes (the number of voxels) of five ATAC-poor segments (P1-P5) before and after CTCF depletion. Throughout the volume measurements in this study, each voxel size is x=48.9 nm, y=48.9 nm, z=199 nm. The number (n) of alleles analyzed is indicated at the bottom. The black bar indicates the median value for each data set and two-sided Mann-Whitney U test was applied for statistical test. P-values for P1-P5 are: p1=0.585, p2=0.932, p3=0.226, p4=0.849, p5=0.853. e, Representative iso-surfaces of an ATAC-poor segment (P5, green) before (-) and after (+) CTCF depletion (12 hours). Scale bar, 1 µm. Biological replicates n=3. Statistics source data are provided in Source Data Extended Fig. 6.

Source Data Extended Fig. 6

Extended Data Fig. 7 CTCF depletion significantly reduced the number of loops and the degree of TAD domain insulation by high-resolution Micro-C analysis.

a, Number of loops in WT-mESC, CTCF-AID mESC -auxin, and +auxin conditions. We identified a similar number of loops in WT-mESC (n=4887) and CTCF-AID mESC -auxin (n=5764), while only 1442 loops were identified after CTCF depletion under identical loop calling criteria. We performed two biological replicates and the data was pooled for analysis. b-c, Aggregate peak analysis on paired-CTCF sites or called loops from Micro-C and Hi-C 1data. Loops were greatly disrupted in Micro-C data after CTCF depletion, which showed a 1.67-fold decrease at CTCF sites or 1.59-fold decrease at called loop loci, respectively. We obtain much fewer loops from previous Hi-C data likely due to the lower resolution1. d, Snapshots of Micro-C contact maps on chr8:80M-95M at 32-kb resolution. Contact maps showed more inter-TAD contacts (loss of insulation) and modestly higher inter-compartment domain contacts after CTCF depletion. Hi-C data also showed a similar result but with a slightly different plaid-like pattern. e, Heatmap of insulation strength at CTCF-binding sites. Insulation strength was over 2-fold decrease at the top 25% of CTCF binding sites after CTCF depletion. f, Scatter plots of insulation strength at the called boundaries. Micro-C and Hi-C both showed consistent insulation loss (higher insulation score) after CTCF depletion.

Extended Data Fig. 8 CTCF depletion significantly increased the contact probability in A compartment by high-resolution Micro-C analysis.

a, Snapshots of Micro-C contact maps on the entire Chr2, showing the plaid-like compartments before and after auxin-mediated CTCF depletion (6 hours). b, Compartment analysis by principle component analysis (PCA). The plots showed the eigenvector of the first PCA. Positive value is compartment A, and negative value is compartment B. There is no noticeable change in the large-scale compartment organization after CTCF depletion. c, Genome-wide analysis of the compartment strength. The saddle plot showed the contact probability between compartments and showed B-B on the top-left corner and A-A on the bottom-right corner. There is no significant compartment change after CTCF depletion. d, Comparison of compartment change in Micro-C and Hi-C. No dramatic change was found, albeit Micro-C appears to capture more changes in compartment strength than Hi-C after CTCF depletion. e-f, Genome-wide contact probability decaying curve by Micro-C (e) and Hi-C (f). See also Fig. 3h. Data from two biological replicates was pooled for analysis.

Supplementary information

Supplementary Information

Supplementary Note.

Reporting Summary

Supplementary Video 1

3D representation of 3D ATAC-PALM localizations of WT mouse ESCs (left) and mouse embryonic fibroblast (MEF) (right) by ViSP, a 3D single molecule localization display software. Biological replicates n = 3. See also Fig. 1c.

Supplementary Video 2

Colocalization of 3D ATAC-PALM localizations (density color coded by blue-red scheme) and Oligopaint DNA–FISH signal (green channel) at a ~0.7 Mb ATAC-rich segment on Chr6 (Nanog locus). The overall two-color 3D ATAC-PALM and Oligopaint DNA–FISH are shown in the left panel and the colocalization of two DNA–FISH loci and their corresponding ACDs are shown in the right panels. Biological replicates n = 3. See also Fig. 2b.

Supplementary Video 3

Colocalization of 3D ATAC-PALM localizations (density color coded by blue-red scheme) and Oligopaint DNA–FISH signal (green channel) at a ~0.7 Mb ATAC-rich segment on Chr4 (Klf4 locus). (Upper left) Alignment of Hi-C contact matrix, ATAC-seq and H3K4me3 tracks spanning a region containing pluripotency Klf4 gene on Chromosome 4. 3D Oligopaint DNA–FISH probes targeting to the ATAC-rich segment are indicated by the green bars. (Lower panel) The overall two-color 3D ATAC-PALM and Oligopaint DNA–FISH are shown in the left panel and the colocalization of two DNA–FISH loci and their corresponding ACDs are shown in the right panels. The quantification of 3D ATAC-PALM density around two ATAC-rich DNA–FISH loci was shown in the top right panel. Experiments were repeated twice.

Supplementary Video 4

3D representation of spatial exclusion of 3D ATAC-PALM signals (red channel) and HP1-GFP labeled heterochromatin structure (turquoise channel) in ESC. Biological replicates n = 3. See also Fig. 2g.

Supplementary Video 5

3D representation of 3D ATAC-PALM localizations in normal (left) or CTCF-depleted (right) ESCs. We performed at least four biological replicates and the results were reproducible. See also Fig. 3b.

Supplementary Video 6

A video showing the representative 3D Oligopaint DNA–FISH Airyscan image of one ATAC-rich segment on Chr4 (R3, red) and one ATAC-poor segment on Chr6 (P5, green) in WT mESCs. Five DAPI-stained nuclei are shown (blue color). We tested multiple ATAC-rich (n = 6) and ATAC-poor (n = 5) pairs in different chromosomes and the results were reproducible. Scale bar, 4 μm. See also Extended Data Fig. 6c.

Source data

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Source Data Extended Data Fig. 4

Unprocessed western blots

Source Data Extended Data Fig. 4

Unprocessed western blots

Source Data Extended Data Fig. 5

Statistical source data

Source Data Extended Data Fig. 6

Statistical source data

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Xie, L., Dong, P., Chen, X. et al. 3D ATAC-PALM: super-resolution imaging of the accessible genome. Nat Methods 17, 430–436 (2020). https://doi.org/10.1038/s41592-020-0775-2

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