Skip to main content

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

  • Article
  • Published:

Phase separation of ligand-activated enhancers licenses cooperative chromosomal enhancer assembly

Nature Structural & Molecular Biology volume 26, pages 193–203 (2019)Cite this article

Subjects

Abstract

A crucial feature of differentiated cells is the rapid activation of enhancer-driven transcriptional programs in response to signals. The potential contributions of physicochemical properties of enhancer assembly in signaling events remain poorly understood. Here we report that in human breast cancer cells, the acute 17β-estradiol-dependent activation of functional enhancers requires assembly of an enhancer RNA–dependent ribonucleoprotein (eRNP) complex exhibiting properties of phase-separated condensates. Unexpectedly, while acute ligand-dependent assembly of eRNPs resulted in enhancer activation sensitive to chemical disruption of phase separation, chronically activated enhancers proved resistant to such disruption, with progressive maturation of eRNPs to a more gel-like state. Acute, but not chronic, stimulation resulted in ligand-induced, condensin-dependent changes in spatial chromatin conformation based on homotypic enhancer association, resulting in cooperative enhancer-activation events. Thus, distinct physicochemical properties of eRNP condensates on enhancers serve as determinants of rapid ligand-dependent alterations in chromosomal architecture and cooperative enhancer activation.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Acutely active E2-responsive MegaTrans enhancers concentrate a protein complex that can undergo phase transition.
Fig. 2: Effect of phase-separation inhibition on acute enhancer transcriptional activation.
Fig. 3: Rapid ligand-induced interactions between distant MegaTrans enhancers.
Fig. 4: Role of enhancer RNAs and condensins in E2 induced chromosomal dynamics and eRNP assembly.
Fig. 5: Chronic stimulation with E2 causes a fluid to hydrogel-like transition at enhancers and prevents ligand-induced enhancer proximity.
Fig. 6: Model summary.

Similar content being viewed by others

Data availability

Next-gen sequencing data sets generated from this study can be accessed at GEO using accession ID GSE99544. Distance measurements from microscopy experiments are included in this published article (and its supplementary information files). All data sets and code used in this study are available from the corresponding author upon reasonable request.

References

  1. Bulger, M. & Groudine, M. Functional and mechanistic diversity of distal transcription enhancers. Cell 144, 327–339 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Long, H. K., Prescott, S. L. & Wysocka, J. Ever-changing landscapes: transcriptional enhancers in development and evolution. Cell 167, 1170–1187 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Loven, J. et al. Selective inhibition of tumor oncogenes by disruption of super-enhancers. Cell 153, 320–334 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Parker, S. C. et al. Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants. Proc. Natl Acad. Sci. USA 110, 17921–17926 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ji, X. et al. 3D chromosome regulatory landscape of human pluripotent cells. Cell. Stem. Cell. 18, 262–275 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Kieffer-Kwon, K. R. et al. Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation. Cell 155, 1507–1520 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Shin, H. Y. et al. Hierarchy within the mammary STAT5-driven Wap super-enhancer. Nat. Genet. 48, 904–911 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hnisz, D., Shrinivas, K., Young, R. A., Chakraborty, A. K. & Sharp, P. A. A phase separation model for transcriptional control. Cell 169, 13–23 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Harlen, K. M. & Churchman,L. S. The code and beyond: transcription regulation by the RNA polymerase II carboxy-terminal domain. Nat. Rev. Mol. Cell Biol. 18, 263–273 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Alberti, S. Phase separation in biology. Curr. Biol. 27, R1097–R1102 (2017).

    Article  CAS  PubMed  Google Scholar 

  12. Banani, S. F., Lee, H. O., Hyman, A. A. & Rosen, M. K. Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18, 285–298 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Sin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017).

    Article  CAS  Google Scholar 

  14. Cho, W. K. et al. Mediator and RNA polymerase II clusters associate in transcription-dependent condensates. Science 361, 412–415 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Sabari, B. R. et al. Coactivator condensation at super-enhancers links phase separation and gene control. Science 361, https://doi.org/10.1126/science.aar3958 (2018).

  16. Boija, A. et al. Transcriptionfactors activate genes through the phase-separation capacity of their activation domains. Cell 175, 1842–1855 (2018).

    Article  CAS  PubMed  Google Scholar 

  17. Boehning,M. et al. RNA polymerase II clustering through carboxy-terminal domain phase separation. Nat. Struct. Mol. Biol. 25, 833–840 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Chong, S. et al. Imaging dynamic and selective low-complexity domain interactions that control gene transcription. Science 361, eaar2555 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Kwon, I. et al. Phosphorylation-regulated binding of RNA polymerase II to fibrous polymers of low-complexity domains. Cell 155, 1049–1060 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lu, H. et al. Phase-separation mechanism for C-terminal hyperphosphorylation of RNA polymerase II. Nature 558, 318–323 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Boulay, G. et al. Cancer-specific retargeting of BAF complexes by a prion-like domain. Cell 171, 163–178 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Carroll, J. S. et al. Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein FoxA1. Cell 122, 33–43 (2005).

    Article  CAS  PubMed  Google Scholar 

  23. Li, W. et al. Functional roles of enhancer RNAs for oestrogen-dependent transcriptional activation. Nature 498, 516–520 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hah, N. et al. A rapid, extensive, and transient transcriptional response to estrogen signaling in breast cancer cells. Cell 145, 622–634 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Liu, Z. et al. Enhancer activation requires trans-recruitment of a mega transcription factor complex. Cell 159, 358–373 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Pnueli, L., Rudnizky, S., Yosefzon, Y. & Melamed, P. RNA transcribed from a distal enhancer is required for activating the chromatin at the promoter of the gonadotropin α-subunit gene. Proc. Natl Acad. Sci. USA 112, 4369–4374 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Kim, T. K. et al. Widespread transcription at neuronal activity-regulated enhancers. Nature 465, 182–187 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Li, W., Notani, D. & Rosenfeld, M. G. Enhancers as non-coding RNA transcription units: recent insights and future perspectives. Nat. Rev. Genet. 17, 207–223 (2016).

    Article  CAS  PubMed  Google Scholar 

  29. Dyson, H. J. & Wright, P. E. Intrinsically unstructured proteins and their functions. Nat. Rev. Mol. Cell Biol. 6, 197 (2005).

    Article  CAS  PubMed  Google Scholar 

  30. Tantos, A., Han, K. H. & Tompa, P. Intrinsic disorder in cell signaling and gene transcription. Mol. Cell. Endocrinol. 348, 457–465 (2012).

    Article  CAS  PubMed  Google Scholar 

  31. Li, W. et al. Condensin I and II complexes license full estrogen receptor alpha-dependent enhancer activation. Mol. Cell 59, 188–202 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Bojcsuk, D., Nagy, G. & Balint, B. L. Inducible super-enhancers are organized based on canonical signal-specific transcription factor binding elements. Nucleic Acids Res 45, 3693–3706 (2016).

    PubMed Central  Google Scholar 

  33. Kato, M. et al. Cell-free formation of RNA granules: low complexity sequence domains form dynamic fibers within hydrogels. Cell 149, 753–767 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Mitrea, D. M. et al. Methods for physical characterization of phase-separated bodies and membrane-less organelles. J. Mol. Biol. 430, 4773–4805 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Banerjee, P. R., Milin, A. N., Moosa, M. M., Onuchic, P. L. & Deniz, A. A. Reentrant phase transition drives dynamic substructure formation in ribonucleoprotein droplets. Angew. Chem. Int. Ed. Engl. 56, 11354–11359 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Elbaum-Garfinkle, S. et al. The disordered P granule protein LAF-1 drives phase separation into droplets with tunable viscosity and dynamics. Proc. Natl Acad. Sci. USA 112, 7189–7194 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Wang, J. et al. A molecular grammar governing the driving forces for phase separation of prion-like RNA binding proteins. Cell 174, 688–699 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Shin, Y. et al. Spatiotemporal control of intracellular phase transitions using light-activated optodroplets. Cell 168, 159–171 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Nott, T. J. et al. Phase transition of a disordered nuage protein generates environmentally responsive membraneless organelles. Mol. Cell 57, 936–947 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Lin, Y. et al. Toxic PR poly-dipeptides encoded by the C9orf72 repeat expansion target LC domain polymers. Cell 167, 789–802 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Kato, M. & McKnight, S. L. A solid-state conceptualization of information transfer from gene to message to protein. Annu. Rev. Biochem. 87, 351–390 (2017).

    Article  PubMed  CAS  Google Scholar 

  42. Franco, H. L., Nagari, A. & Kraus, W. L. TNFalpha signaling exposes latent estrogen receptor binding sites to alter the breast cancer cell transcriptome. Mol. Cell 58, 21–34 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kaikkonen, M. U. et al. Remodeling of the enhancer landscape during macrophage activation is coupled to enhancer transcription. Mol. Cell 51, 310–325 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Brangwynne, C. P., Mitchison, T. J. & Hyman, A. A. Active liquid-like behavior of nucleoli determines their size and shape in Xenopus laevis oocytes. Proc. Natl Acad. Sci. USA 108, 4334–4339 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Shin, Y. et al. Liquid nuclear condensates mechanically sense and restructure the genome. Cell 175, 1481–1491 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Brown, J. M. et al. Association between active genes occurs at nuclear speckles and is modulated by chromatin environment. J. Cell. Biol. 182, 1083–1097 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Shopland, L. S., Johnson, C. V., Byron, M., McNeil, J. & Lawrence, J. B. Clustering of multiple specific genes and gene-rich R-bands around SC-35 domains: evidence for local euchromatic neighborhoods. J. Cell. Biol. 162, 981–990 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Skowronska-Krawczyk, D. et al. Required enhancer-matrin-3 network interactions for a homeodomain transcription program. Nature 514, 257–261 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Marzahn, M. R. et al. Higher-order oligomerization promotes localization of SPOP to liquid nuclear speckles. EMBO J. 35, 1254–1275 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Mitrea, D. M. & Kriwacki, R. W. Phase separation in biology; functional organization of a higher order. Cell. Commun. Signal. 14, 1 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Ji, X. et al. SR proteins collaborate with 7SK and promoter-associated nascent RNA to release paused polymerase. Cell 153, 855–868 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Pandit, S. et al. Genome-wide analysis reveals SR protein cooperation and competition in regulated splicing. Mol. Cell 50, 223–235 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Lai, F. & Shiekhattar, R. Enhancer RNAs: the new molecules of transcription. Curr. Opin. Genet. Dev. 25, 38–42 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Hah, N., Murakami, S., Nagari, A., Danko, C. G. & Kraus, W. L. Enhancer transcripts mark active estrogen receptor binding sites. Genome Res. 23, 1210–1223 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Mittag,T. & Parker,R. Multiple modes of protein-protein interactions promote RNP granule assembly. J. Mol. Biol. 430, 4636–4649 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Keenholtz, R. A. et al. Oligomerization and ATP stimulate condensin-mediated DNA compaction. Sci. Rep. 7, 14279 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Hirano, T. Capturing condensin in chromosomes. Nat. Genet. 49, 119–1420 (2017).

    Article  CAS  Google Scholar 

  59. D’Ambrosio, C. et al. Identification of cis-acting sites for condensin loading onto budding yeast chromosomes. Genes Dev. 22, 2215–2227 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Haeusler, R. A., Pratt-Hyatt, M., Good, P. D., Gipson, T. A. & Engelke, D. R. Clustering of yeast tRNA genes is mediated by specific association of condensin with tRNA gene transcription complexes. Genes Dev. 22, 2204–2214 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wood, A. J., Severson, A. F. & Meyer, B. J. Condensin and cohesin complexity: the expanding repertoire of functions. Nat. Rev. Genet. 11, 391–404 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Crane, E. et al. Condensin-driven remodelling of X chromosome topology during dosage compensation. Nature 523, 240–244 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Lin, Y., Protter, D. S., Rosen, M. K. & Parker, R. Formation and maturation of phase-separated liquid droplets by RNA-binding proteins. Mol. Cell 60, 208–219 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Patel, A. et al. A liquid-to-solid phase transition of the ALS protein FUS accelerated by disease mutation. Cell 162, 1066–1077 (2015).

    Article  CAS  PubMed  Google Scholar 

  65. Molliex, A. et al. Phase separation by low complexity domains promotes stress granule assembly and drives pathological fibrillization. Cell 163, 123–133 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Phair, R. D., Gorski, S. A. & Misteli, T. Measurement of dynamic protein binding to chromatin in vivo, using photobleaching microscopy. Methods Enzymol. 375, 393–414 (2004).

    Article  CAS  PubMed  Google Scholar 

  67. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors are grateful to J. Hightower for assistance with figure preparation. S.J.N. was a recipient of postdoctoral fellowship from American Heart Association (14POST19860025) and a T32 Fellowship (5T32DK007044). D.M. was supported by NIH-NIDDK Grant no. 5F32DK112682. Q.M. was a recipient of an American Cancer Society postdoctoral fellowship (PF-16-211-01-TBE). The authors gratefully acknowledge UB North Campus Confocal Imaging Facility (supported by NSF major research instrumentation Grant DBI no. 0923133) and A. Siegel for assistance with microscopy. Grant no. NS047101 supports the UCSD microscopy core facility. This work was supported by grants from the University at Buffalo, SUNY, Collage of Arts and Sciences to P.R.B. and to M.G.R. (nos. DK018477, DK039949, NS034934 and CA173903). M.G.R. is an investigator with the Howard Hughes Medical Institute. The authors declare no conflict of interests.

Author information

Author notes

  1. These authors contributed equally: Lu Yang, Dario Meluzzi, Soohwan Oh, Feng Yang.

Authors and Affiliations

  1. Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA, USA

    Sreejith J. Nair, Lu Yang, Dario Meluzzi, Soohwan Oh, Feng Yang, Meyer J. Friedman, Susan Wang, Tom Suter, Amir Gamliel, Qi Ma, Jie Zhang, Yiren Hu, Yuliang Tan, Kenneth A. Ohgi, Ranveer Singh Jayani & Michael G. Rosenfeld

  2. Biological Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA

    Soohwan Oh & Yiren Hu

  3. Cellular and Molecular Medicine Graduate Program, University of California, San Diego, La Jolla, CA, USA

    Susan Wang

  4. Department of Physics, University at Buffalo—SUNY, Buffalo, NY, USA

    Ibraheem Alshareedah & Priya R. Banerjee

  5. Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Aneel K. Aggarwal

Authors
  1. Sreejith J. Nair
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dario Meluzzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Soohwan Oh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Feng Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Meyer J. Friedman
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Susan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Tom Suter
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ibraheem Alshareedah
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Amir Gamliel
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Qi Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Jie Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Yiren Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yuliang Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Kenneth A. Ohgi
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Ranveer Singh Jayani
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Priya R. Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Aneel K. Aggarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Michael G. Rosenfeld
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.J.N., LY. and M.G.R. designed the experimental strategies. D.M. generated codes and carried out informatics analyses on FISH images. S.J.N. and J.Z. performed FISH experiments, vector design and cloning. F.Y. performed ChIP-seq analyses and GATA3 mutation studies with S.J.N. D.M., Y.T. and Q.M. performed the bioinformatics analyses. S.O. performed 4 C and GRO-seq assays. S.W. and T.S performed live-cell imaging. A.G. performed the in situ Hi-C. S.J.N., F.Y. and Y.H. carried out the knockdown experiments. M.F. purified proteins for in vitro assays. P.R.B and I.A. performed in vitro phase-separation assays, FRAP and data analysis. R.S.J. performed ATAC-Seq. K.O. prepared samples for deep sequencing. S.J.N. carried out the b-isox precipitation assay, 1,6-HD experiments and optodroplet assays. S.J.N. and M.G.R. conceived and supervised the project. S.J.N. and M.G.R. wrote the manuscript with input from P.R.B, A.K.A., L.Y. and D.M.

Corresponding authors

Correspondence to Sreejith J. Nair or Michael G. Rosenfeld.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Integrated supplementary information

Supplementary Figure 1 Meta-analysis of chromatin-binding factors on MegaTrans enhancers.

a Quantitative meta-analysis of the ChIP-seq data of the binding of indicated factors on 1248 MegaTrans enhancers, compared to 5833 weak ERα-bound enhancers and 11167 non-ERα active enhancers, performed in the presence or absence of E2 (1 h). b. ATAC-seq profile of three categories of enhancers. Genomic co-ordinates of enhancer regions are provided in Supplementary Table 1.

Supplementary Figure 2 Evidence for phase-separation potential of MegaTrans components.

a. Computational analysis of amino acid sequences of indicated proteins using Predictor of Natural Disordered Region (PONDR). Score of >0.5 is predicted to be disordered domain b. Droplet formation by purified recombinant GATA3-MBP and ERα-MBP. The protein concentration in each case was 7 µM in 25 mM Tris buffer, pH 7.5 containing 5% PEG 8000 and 200 mM NaCl. MBP-alone do not form droplet under similar conditions c. Distribution of aspect ratios of GAvTA3-MBP and ERα-MBP protein droplets. Boxes represent interquartile ranges (IQRs). Whisker represents points in lower and upper quartiles within 1.5 IQR from lower and upper edges of IQR. d. GATA3-MBP and ERα-MBP concentrate in single droplets indicating miscibility. Plots represent the fluorescent intensity profiles of the two proteins across within a GATA3-ERα droplet formed in 25 mM Tris buffer (pH 7.5) containing 500 mM NaCl. e, f, g. Representative example of optodroplet assay in MCF7 cells expressing (e) mCherry-Cry2 (f) GATA3-IDR-mCherry-Cry2 (g) ERα-IDR-mCherry-Cry2. Cry2 was activated with 488 nm laser light for the indicated period of time.

Supplementary Figure 3 In vivo evidence supporting transcription-factor condensate on MegaTrans enhancers and role of IDR.

a. RNA FISH showing localization of transcribing TFF1 locus to mCherry-ERα foci. The non-E2 target loci are not recruited to the foci b. Quantitation of RNA FISH measuring median distance between ERα-mCherry signal and an E2 target (TFF1 intron, n = 32) and non-E2 target (DYRK1, n = 42). Boxes represent interquartile ranges (IQRs). Whisker represents points in lower and upper quartiles within 1.5 IQR from lower and upper edges of IQR. P-values were calculated using Wilcoxon Rank Sum test with continuity correction. c. Representative FRAP experiment images of ERα-Turquoise transfected MCF7 cell, treated with 1hr of E2 at indicated time periods. Regions outlined in circles indicate bleached foci. Data representative of >10 cells in each time point d. Efficient shRNA-dependent depletion of GATA3 mRNA, measured using Q-PCR using GATA3 mRNA primers, in a clonal MCF7 cell line. Data shown are individual values as mean ± s.d. P-value calculated with unpaired Student’s t-test. Data are representative of 3 independent experiments. shCTL represent non-targeting control shRNA. e. Western blot showing equivalent expression of HA-tagged GATA3-WT and GATA3-IDR mut in MCF7 cells. f. GATA3-WT but not GATA3-IDR mutant can rescue expression of FOXC1 mRNA. Results are shown as individual data points (circles), mean ± s.d. Data is representative of 3 independent experiments.

Supplementary Figure 4 Effect of aliphatic alcohols on the E2 transcription program.

a. Q-PCR analysis of E2-induced eRNA expression from the TFF1, SMAD7 and PGR enhancer in MCF7 cells treated with indicated aliphatic alcohols (1,6-HD: 1,6-hexanediol, 2,5-HD: 2,5-hexanediol, 1,4-BD: 1,4-butanediol) compared to untreated cells (UT). Data indicate mean ± s.d. p-value calculated using unpaired Student’s t-test. Pooled data from at least 3 independent experiments b. Meta-analysis of GRO-seq data on MCF7 cells stimulated with E2 for 1 h followed by 5 min treatment with 2,5-HD or 1,6-HD on MegaTrans, Weak ERα and Non-ERα bound enhancer program genome-wide. c. Meta-analysis of GRO-seq data on MCF7 cells stimulated with E2 for 1 h followed by 5 min treatment with 2,5-HD or 1,6-HD on E2 regulated coding genes genome-wide. Boxes represent interquartile ranges (IQRs). Whisker represents points in lower and upper quartiles within 1.5 IQR from lower and upper edges of IQR d. Effect of 1,6-HD treatment on the recruitment of ERα, RARα and AP2γ on indicated enhancers. Results are shown as individual data points (circles), mean ± SD (lines). Data is representative of three independent experiments. e. Western blot on whole cell lystate from MCF7 cells treated with 7.5% of 2,5-HD or 1,6-HD for 5 min followed by 100 nM E2 for 30 min.

Supplementary Figure 5 E2-mediated architectural changes on chromosome 21 detected by proximity-based-ligation approaches.

a. A/B compartments (top panel) and TAD boundaries (bottom panel) calculated from the Hi-C data indicating that these genomic compartments are unaffected by E2 treatment b. Contact map from Hi-C data, analyzed at a resolution of 1 Mb, indicating the presence of very long-distance interactions (enriched contacts) as well as the expected short-range interactions c. 4C-seq revealing TFF1e interactions with the DSCAM-AS1 enhancer region, using TFF1e as a view point, based on analysis of data after excluding all interactions at less than 2 Mb to permit quantitative analysis of interactions between these loci separated by >2 Mb. GRO-seq data of locus is given as a reference.

Supplementary Figure 6 E2 stimulation results in dynamic proximity of MegaTrans enhancers in chromosome 21.

a. Effects of E2 on the proximity of indicated MegaTrans enhancer loci. Arrowhead points to the pair of loci in proximity. Image representative of at least 200 nuclei examined in independent experiments b. Comparison of cumulative distribution of distances between indicated MegaTrans enhancers demonstrate that 3D distances between these loci are reduced in response to E2 stimulation. c. Data from DNA FISH targeting genomic regions that showed or did not show induced proximity with E2 treatment. CP = Control Probes targeting non-ERα bound genomic regions. Numbers on the box plots represent median distance. Data are median ± interquartile range. P-value was calculated using Wilcoxon rank sum test with continuity correction. (b,c) Data pooled from total of at least 150 nuclei examined in replicates d. Relationship between median spatial distance and genomic distance for all pairs of TADs on Chr.21 in IMR90 cells, calculated using published data70. The solid line is the best-fit of a power-law function with scaling exponent S. This function was used to predict the expected median spatial distance between any two probed genomic loci in the basal condition. A cut-off distance equal to 40% of the predicted median distance for any two given loci was arbitrarily used to define the spatial proximity of those loci. For example, since the predicted median distance between the TFF1 and NRIP1 loci in IMR90 cells was 1.5 µm, the cut-off distance was taken to be 1.5 x 0.4 = 0.6 µm (600 nm). See Methods for more details.

Supplementary Figure 7 RNA FISH data showing fraction of cells actively transcribing E2 targets.

a. RNA FISH image using intronic and exonic probe against TFF1 mRNA in MCF7 cells treated 15 min with E2. Pooled data from total of > 200 nuclei in replicate. The fraction of cells expressing or not expressing exonic probe is indicated b. RNA FISH image using intronic and exonic probe against NRIP1 mRNA in MCF7 cells treated 15 min with E2. Pooled data from total of > 200 nuclei in replicate. The fraction of cells expressing or not expressing exonic probe is indicated c. Percent of cells (E2-treated, 15 min) expressing NRIP1 or TFF1 by intronic RNA FISH probes, expressing 0, 1, or 2 alleles d. Intensity vs. distance plot of all examined RNA FISH signal using NRIP1 intronic probe in relation to the TFF1 probe (A.U. = Arbitrary Unit) e. Intensity vs. distance plot of all examined RNA FISH signal using DOPEY2 intronic probe in relation to TFF1 probe.

Supplementary Figure 8 Interchromatin granules in E2-regulated enhancer activity.

a. Effect of NRIP1 colocalization with ICG on its transcription b. Effect of TFF1 colocalization with ICG on its transcription. Data for a and b are median ± interquartile range. P-value was calculated using Wilcoxon rank sum test. >80 nuclei were examined in replicate c. Colocalization of transcribing TFF1 and NRIP1 loci with ICG. Highlighted area in square is magnified in image to the right. Arrowheads point to proximity of mTFF1 and mNRIP1 signals to the same ICG domain and arrows point to the weak NRIP1 signal that is not proximal to ICG. d. Transcriptional effect on NRIP1 locus colocalizing with a transcribing TFF1 locus in the same ICG. Data are mean ± s.d. P-value calculated by Mann-Whitney test. >100 nuclei were examined in replicate e. Knockdown efficiency of ICG component SRSF1and U2AF1 in MCF7 cells. siCTL represent scrambled oligo used for control transfection. Data pooled from 3 experiments. f. Q-PCR analysis demonstrated the inhibition of E2-induced eRNA expression from TFF1, NRIP1e, FOXC1e, and SMAD7e as a result of knockdown of SRSF1. g. Q-PCR analysis demonstrated the inhibition of E2-induced eRNA expression from TFF1, NRIP1e, FOXC1e, and SMAD7e as a result of knockdown of U2AF1. Data in e,f and g indicate mean ± s.d. P-value calculated using unpaired Student’s t-test. Pooled data from at least 3 independent experiments.

Supplementary Figure 9 Role of eRNAs and condensins in E2-induced MegaTrans enhancer association.

a. Efficient knockdown of TFF1 eRNA by ASO in cells used for DNA FISH experiments. Data representative of 3 independent experiments. b. Effect of TFF1 eRNA knockdown on E2 induced spatial association of NRIP1/TFF1 loci as represented by cumulative distribution of distances. P-value calculated with Kolmogorov–Smirnov test. >200 nuclei analyzed for each data set c. Homopolymeric poly(U) RNA did not have any significant effect on the FRAP recovery rate of GATA3-MBP (7 µM) droplets in 25 mM Tris, pH 7.5, 5% PEG 8000, 200 mM NaCl buffer. d. Representative microscopic images of GATA3-MBP/TFF1 eRNA droplets from FRAP experiment quantified in Fig. 4c. e. Representative microscopic images of ERα-MBP/TFF1 eRNA droplets from FRAP experiment quantified in Fig. 4d. f. Meta-analysis of ChIP-seq data31 with or without E2 stimulation using NCAPG (Condensin I)(Top panel) or NCAPH2 (Condensin II)(Bottom panel) antibodies for the MegaTrans enhancers, weak ERα-bound enhancers and non-ERα enhancers g. Efficient knockdown of TFF1 eRNA and NRIP1 eRNA with ASO in cells used for Condensin ChIP experiments (Fig. 4e). Data representative of 3 independent experiments. h. Efficient knockdown of NCAPG, NCAPH2 and RAD21 using shRNA. Data representative of 3 independent replicates. siNC represent non-targeting siRNA used as a control i. Cumulative distribution of distance of TFF1/NRIP1 in MCF7 cells on knockdown of RAD21, NCAPG or NCAPH2. P-value calculated with Kolmogorov–Smirnov test. Data pooled from >200 nuclei from two independent experiments.

Supplementary Figure 10 Distinct effects of acute and chronic E2 treatment on transcription and biophysical properties of enhancer condensates.

a. ChIP experiment demonstrating the effect of acute and chronic E2 treatment on the recruitment of MegaTrans component RARα on TFF1 and NRIP1 enhancers. b. PRO-seq analysis on genes induced by 30 min of E2 treatment and transcriptional status of same set of genes after 14 h of E2 exposure c. PRO-seq analysis on genes transcribed by 14 h of E2 treatment and the transcriptional status of same set of genes after a second dose of 100 nM E2 for 1 h (after 14 h E2 treatment). For b and c, boxes represent interquartile ranges. Whiskers extend 1.5× the interquartile range from the 25th and 75th percentiles. P-values calculated with two sample t-test. d. Representative images of FRAP experiments quantified in Fig. 5b, showing ERα-mTurquoise foci formed after 30min (top panel) or 16 h (bottom panel) of E2 treatment, at indicated time points after bleaching. Photobleached regions are outlined in circles e. Representative image showing the effect of 1,6-HD on ERα/GATA3/TFF1 eRNA droplets formed in the presence of 5% PEG 8000 and 200 mM NaCl at indicated period after initial formation of the droplets.

Supplementary information

Supplementary Figures and Supplementary Notes

Supplementary Figures 1–10 and Supplementary Note 1

Reporting Summary

Supplementary Video 1

In vitro droplet formation by GATA3-MBP. Time-lapse video showing fusion of in vitro GATA3-MBP droplets

Supplementary Video 2

In vitro droplet formation by ERα-MBP. Time-lapse video showing fusion of in vitro ERα-MBP droplets

Supplementary Video 3

Optodroplet assay with GATA3-IDR. Blue light–induced formation of droplets by GATA3 (aa.105–260)-mCherry-Cry2 proteins in 293T cells.

Supplementary Video 4

Optodroplet assay with ERα–IDR. Blue light–induced formation of droplets by ERα (aa.79–174)-mCherry-Cry2 proteins in 293T cells.

Supplementary Video 5

Optodroplet assay with Cry2 alone. Time-lapse video of blue light activation of 293T cells expression mCherry-Cry2 alone.

Supplementary Video 6

E2-induced foci formation by ERα-Turquoise. MCF7 cells expressing ERα-Turquoise was treated with 100nM E2, resulting in the formation of clustering.

Supplementary Table 1

Co-ordinates of MegaTrans, weak ERα and non-ER enhancers aligned on hg18.

Supplementary Table 2

DNA FISH analysis data. Distances between genomic loci examined in this study.

Supplementary Table 3

RNA FISH analysis data. Intensity–spatial distance relationship calculated from RNA FISH.

Supplementary Table 4

List of oligos. Oligos, siRNAs and antisense oligos (ASOs) used in the study.

Supplementary Table 5

List of BAC and Fosmid clones. Clone ID and genomic coverage of BAC Clones used for DNA FISH experiments.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nair, S.J., Yang, L., Meluzzi, D. et al. Phase separation of ligand-activated enhancers licenses cooperative chromosomal enhancer assembly. Nat Struct Mol Biol 26, 193–203 (2019). https://doi.org/10.1038/s41594-019-0190-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41594-019-0190-5

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

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

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