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Disordered C-terminal domain drives spatiotemporal confinement of RNAPII to enhance search for chromatin targets

Abstract

Efficient gene expression requires RNA polymerase II (RNAPII) to find chromatin targets precisely in space and time. How RNAPII manages this complex diffusive search in three-dimensional nuclear space remains largely unknown. The disordered carboxy-terminal domain (CTD) of RNAPII, which is essential for recruiting transcription-associated proteins, forms phase-separated droplets in vitro, hinting at a potential role in modulating RNAPII dynamics. In the present study, we use single-molecule tracking and spatiotemporal mapping in living yeast to show that the CTD is required for confining RNAPII diffusion within a subnuclear region enriched for active genes, but without apparent phase separation into condensates. Both Mediator and global chromatin organization are required for sustaining RNAPII confinement. Remarkably, truncating the CTD disrupts RNAPII spatial confinement, prolongs target search, diminishes chromatin binding, impairs pre-initiation complex formation and reduces transcription bursting. The present study illuminates the pivotal role of the CTD in driving spatiotemporal confinement of RNAPII for efficient gene expression.

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Fig. 1: Spatiotemporal mapping of transcription machinery in living yeast nucleus.
Fig. 2: CTD governs spatiotemporal dynamics of RNAPII.
Fig. 3: The interplay of CTD, chromatin organization and Mediator shapes RNAPII anisotropic diffusion.
Fig. 4: No substantial RNAPII clustering in yeast nucleoplasm.
Fig. 5: CTD facilitates RNAPII target search kinetics.
Fig. 6: CTD truncation impairs PIC formation.
Fig. 7: CTD length controls burst size and frequency of HSP82 gene transcription.

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Data availability

Raw single-molecule trajectory coordinates are accessible at Zenodo (https://doi.org/10.5281/zenodo.10570246 (ref. 93)). All other data supporting the findings of the present study are available from the corresponding author on reasonable request. Source data are provided with this paper.

Code availability

Customized code can be found at GitHub (https://github.com/yhinling/Ling-et-al-2024 (ref. 94)).

References

  1. Cramer, P., Bushnell, D. A. & Kornberg, R. D. Structural basis of transcription: RNA polymerase II at 2.8 angstrom resolution. Science 292, 1863–1876 (2001).

    Article  CAS  PubMed  Google Scholar 

  2. Corden, J. L. RNA polymerase II C-terminal domain: tethering transcription to transcript and template. Chem. Rev. 113, 8423–8455 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Eick, D. & Geyer, M. The RNA polymerase II carboxy-terminal domain (CTD) code. Chem. Rev. 113, 8456–8490 (2013).

    Article  CAS  PubMed  Google Scholar 

  4. 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 

  5. Buratowski, S. Progression through the RNA polymerase II CTD cycle. Mol. Cell 36, 541–546 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Thompson, C. M., Koleske, A. J., Chao, D. M. & Young, R. A. A multisubunit complex associated with the RNA polymerase II CTD and TATA-binding protein in yeast. Cell 73, 1361–1375 (1993).

    Article  CAS  PubMed  Google Scholar 

  7. West, M. L. & Corden, J. L. Construction and analysis of yeast RNA polymerase II CTD deletion and substitution mutations. Genetics 140, 1223–1233 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hsin, J. P., Sheth, A. & Manley, J. L. RNAP II CTD phosphorylated on threonine-4 is required for histone mRNA 3′-end processing. Science 334, 683–686 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Bartolomei, M. S., Halden, N. F., Cullen, C. R. & Corden, J. L. Genetic analysis of the repetitive carboxyl-terminal domain of the largest subunit of mouse RNA polymerase II. Mol. Cell. Biol. 8, 330–339 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Litingtung, Y. et al. Growth retardation and neonatal lethality in mice with a homozygous deletion in the C-terminal domain of RNA polymerase II. Mol. Gen. Genet. 261, 100–105 (1999).

    Article  CAS  PubMed  Google Scholar 

  11. Babokhov, M., Mosaheb, M. M., Baker, R. W. & Fuchs, S. M. Repeat-specific functions for the C-terminal domain of RNA polymerase II in budding yeast. G3 (Bethesda) 8, 1593–1601 (2018).

    Article  CAS  PubMed  Google Scholar 

  12. Meisels, E., Gileadi, O. & Corden, J. L. Partial truncation of the yeast RNA polymerase II carboxyl-terminal domain preferentially reduces expression of glycolytic genes. J. Biol. Chem. 270, 31255–31261 (1995).

    Article  CAS  PubMed  Google Scholar 

  13. Quintero-Cadena, P., Lenstra, T. L. & Sternberg, P. W. RNA Pol II length and disorder enable cooperative scaling of transcriptional bursting. Mol. Cell 79, 207–220 e208 (2020).

    Article  CAS  PubMed  Google Scholar 

  14. Sawicka, A. et al. Transcription activation depends on the length of the RNA polymerase II C-terminal domain. EMBO J. 40, e107015 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Allison, L. A. & Ingles, C. J. Mutations in RNA polymerase II enhance or suppress mutations in GAL4. Proc. Natl Acad. Sci. USA 86, 2794–2798 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Scafe, C. et al. RNA polymerase II C-terminal repeat influences response to transcriptional enhancer signals. Nature 347, 491–494 (1990).

    Article  CAS  PubMed  Google Scholar 

  17. Gerber, H. P. et al. RNA polymerase II C-terminal domain required for enhancer-driven transcription. Nature 374, 660–662 (1995).

    Article  CAS  PubMed  Google Scholar 

  18. Chapman, R. D., Heidemann, M., Hintermair, C. & Eick, D. Molecular evolution of the RNA polymerase II CTD. Trends Genet. 24, 289–296 (2008).

    Article  CAS  PubMed  Google Scholar 

  19. Yang, C. & Stiller, J. W. Evolutionary diversity and taxon-specific modifications of the RNA polymerase II C-terminal domain. Proc. Natl Acad. Sci. USA 111, 5920–5925 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. 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 

  21. 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 

  22. Guo, Y. E. et al. Pol II phosphorylation regulates a switch between transcriptional and splicing condensates. Nature 572, 543–548 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Cho, W. K. et al. RNA polymerase II cluster dynamics predict mRNA output in living cells. eLife https://doi.org/10.7554/eLife.13617 (2016).

  24. Cisse, I. I. et al. Real-time dynamics of RNA polymerase II clustering in live human cells. Science 341, 664–667 (2013).

    Article  CAS  PubMed  Google Scholar 

  25. 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 

  26. Boija, A. et al. Transcription factors activate genes through the phase-separation capacity of their activation domains. Cell 175, 1842–1855.e1816 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Wei, M. T. et al. Nucleated transcriptional condensates amplify gene expression. Nat. Cell Biol. 22, 1187–1196 (2020).

    Article  CAS  PubMed  Google Scholar 

  28. McSwiggen, D. T., Mir, M., Darzacq, X. & Tjian, R. Evaluating phase separation in live cells: diagnosis, caveats, and functional consequences. Genes Dev. 33, 1619–1634 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Musacchio, A. On the role of phase separation in the biogenesis of membraneless compartments. EMBO J. 41, e109952 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Chong, S. et al. Imaging dynamic and selective low-complexity domain interactions that control gene transcription. Science https://doi.org/10.1126/science.aar2555 (2018).

  31. Palacio, M. & Taatjes, D. J. Merging established mechanisms with new insights: condensates, hubs, and the regulation of RNA polymerase II transcription. J. Mol. Biol. 434, 167216 (2022).

    Article  CAS  PubMed  Google Scholar 

  32. Tjong, H., Gong, K., Chen, L. & Alber, F. Physical tethering and volume exclusion determine higher-order genome organization in budding yeast. Genome Res. 22, 1295–1305 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gasser, S. M., Hediger, F., Taddei, A., Neumann, F. R. & Gartenberg, M. R. The function of telomere clustering in yeast: the circe effect. Cold Spring Harb. Symp. Quant. Biol. 69, 327–337 (2004).

    Article  CAS  PubMed  Google Scholar 

  34. Rosa, A. & Everaers, R. Structure and dynamics of interphase chromosomes. PLoS Comput. Biol. 4, e1000153 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Zimmer, C. & Fabre, E. Principles of chromosomal organization: lessons from yeast. J. Cell Biol. 192, 723–733 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Berger, A. B. et al. High-resolution statistical mapping reveals gene territories in live yeast. Nat. Methods 5, 1031–1037 (2008).

    Article  CAS  PubMed  Google Scholar 

  37. Duan, Z. et al. A three-dimensional model of the yeast genome. Nature 465, 363–367 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Miura, F. et al. Absolute quantification of the budding yeast transcriptome by means of competitive PCR between genomic and complementary DNAs. BMC Genom. 9, 574 (2008).

    Article  Google Scholar 

  39. Gong, K., Tjong, H., Zhou, X. J. & Alber, F. Comparative 3D genome structure analysis of the fission and the budding yeast. PLoS ONE 10, e0119672 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Tokuda, N. & Sasai, M. Heterogeneous spatial distribution of transcriptional activity in budding yeast nuclei. Biophys. J. 112, 491–504 (2017).

    Article  CAS  PubMed  Google Scholar 

  41. Huisinga, K. L. & Pugh, B. F. A genome-wide housekeeping role for TFIID and a highly regulated stress-related role for SAGA in Saccharomyces cerevisiae. Mol. Cell 13, 573–585 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Erickson, H. P. Size and shape of protein molecules at the nanometer level determined by sedimentation, gel filtration, and electron microscopy. Biol. Proced. Online 11, 32–51 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Portz, B. et al. Structural heterogeneity in the intrinsically disordered RNA polymerase II C-terminal domain. Nat. Commun. 8, 15231 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hansen, A. S., Amitai, A., Cattoglio, C., Tjian, R. & Darzacq, X. Guided nuclear exploration increases CTCF target search efficiency. Nat. Chem. Biol. 16, 257–266 (2020).

    Article  CAS  PubMed  Google Scholar 

  45. 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 

  46. Mazzocca, M. et al. Chromatin organization drives the search mechanism of nuclear factors. Nat. Commun. 14, 6433 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hansen, A. S., Pustova, I., Cattoglio, C., Tjian, R. & Darzacq, X. CTCF and cohesin regulate chromatin loop stability with distinct dynamics. eLife https://doi.org/10.7554/eLife.25776 (2017).

  48. Baek, I., Friedman, L. J., Gelles, J. & Buratowski, S. Single-molecule studies reveal branched pathways for activator-dependent assembly of RNA polymerase II pre-initiation complexes. Mol. Cell 81, 3576–3588.e3576 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Schilbach, S., Wang, H., Dienemann, C. & Cramer, P. Yeast PIC-Mediator structure with RNA polymerase II C-terminal domain. Proc. Natl Acad. Sci. USA 120, e2220542120 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Yahia, Y. et al. RNA polymerase II CTD is dispensable for transcription and required for termination in human cells. EMBO Rep. 24, e56150 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Warfield, L. et al. Transcription of nearly all yeast RNA polymerase II-transcribed genes is dependent on transcription factor TFIID. Mol. Cell 68, 118–129.e115 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Robinson, P. J., Bushnell, D. A., Trnka, M. J., Burlingame, A. L. & Kornberg, R. D. Structure of the mediator head module bound to the carboxy-terminal domain of RNA polymerase II. Proc. Natl Acad. Sci. USA 109, 17931–17935 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Wu, C. Heat shock transcription factors: structure and regulation. Annu. Rev. Cell Dev. Biol. 11, 441–469 (1995).

    Article  CAS  PubMed  Google Scholar 

  54. Jakobsen, B. K. & Pelham, H. R. Constitutive binding of yeast heat shock factor to DNA in vivo. Mol. Cell. Biol. 8, 5040–5042 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Park, H. O. & Craig, E. A. Positive and negative regulation of basal expression of a yeast HSP70 gene. Mol. Cell. Biol. 9, 2025–2033 (1989).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Sorger, P. K. & Pelham, H. R. Purification and characterization of a heat-shock element binding protein from yeast. EMBO J. 6, 3035–3041 (1987).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Sorger, P. K. & Pelham, H. R. Yeast heat shock factor is an essential DNA-binding protein that exhibits temperature-dependent phosphorylation. Cell 54, 855–864 (1988).

    Article  CAS  PubMed  Google Scholar 

  58. Sewitz, S. A. et al. Heterogeneous chromatin mobility derived from chromatin states is a determinant of genome organisation in S. cerevisiae. Preprint at bioRxiv https://doi.org/10.1101/106344 (2017).

  59. 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 

  60. Lyons, H. et al. Functional partitioning of transcriptional regulators by patterned charge blocks. Cell 186, 327–345.e328 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zhao, Z. W. et al. Spatial organization of RNA polymerase II inside a mammalian cell nucleus revealed by reflected light-sheet superresolution microscopy. Proc. Natl Acad. Sci. USA 111, 681–686 (2014).

    Article  CAS  PubMed  Google Scholar 

  62. Lu, F., Portz, B. & Gilmour, D. S. The C-terminal domain of RNA polymerase II is a multivalent targeting sequence that supports Drosophila development with only consensus heptads. Mol. Cell 73, 1232–1242.e1234 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Kovacs, D. et al. HSF1Base: a comprehensive database of HSF1 (heat shock factor 1) target genes. Int. J. Mol. Sci. https://doi.org/10.3390/ijms20225815 (2019).

  64. Pincus, D. et al. Genetic and epigenetic determinants establish a continuum of Hsf1 occupancy and activity across the yeast genome. Mol. Biol. Cell. 29, 3168–3182 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Zhao, T. et al. Ssl2/TFIIH function in transcription start site scanning by RNA polymerase II in Saccharomyces cerevisiae. eLife https://doi.org/10.7554/eLife.71013 (2021).

  66. Lenstra, T. L. & Larson, D. R. Single-molecule mRNA detection in live yeast. Curr. Protoc. Mol. Biol. 113, 142411–142415 (2016).

    Article  Google Scholar 

  67. Nguyen, V. Q. et al. Spatiotemporal coordination of transcription preinitiation complex assembly in live cells. Mol. Cell 81, 3560–3575.e3566 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zheng, Q. et al. Rational design of fluorogenic and spontaneously blinking labels for super-resolution imaging. ACS Cent. Sci. 5, 1602–1613 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Grimm, J. B. et al. A general method to improve fluorophores for live-cell and single-molecule microscopy. Nat. Methods 12, 244–250 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Vallotton, P. et al. Diatrack particle tracking software: review of applications and performance evaluation. Traffic 18, 840–852 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Persson, F., Linden, M., Unoson, C. & Elf, J. Extracting intracellular diffusive states and transition rates from single-molecule tracking data. Nat. Methods 10, 265–269 (2013).

    Article  PubMed  Google Scholar 

  72. Kim, J. M. et al. Single-molecule imaging of chromatin remodelers reveals role of ATPase in promoting fast kinetics of target search and dissociation from chromatin. eLife https://doi.org/10.7554/eLife.69387 (2021).

  73. Teves, S. S. et al. A stable mode of bookmarking by TBP recruits RNA polymerase II to mitotic chromosomes. eLife https://doi.org/10.7554/eLife.35621 (2018).

  74. Medler, S. et al. Evidence for a complex of transcription factor IIB with poly(A) polymerase and cleavage factor 1 subunits required for gene looping. J. Biol. Chem. 286, 33709–33718 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Vink, J. N. A., Brouns, S. J. J. & Hohlbein, J. Extracting transition rates in particle tracking using analytical diffusion distribution analysis. Biophys. J. 119, 1970–1983 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Park, S. et al. Dynamic interactions between the RNA chaperone Hfq, small regulatory RNAs, and mRNAs in live bacterial cells. eLife https://doi.org/10.7554/eLife.64207 (2021).

  77. Hansen, A. S. et al. Robust model-based analysis of single-particle tracking experiments with Spot-On. eLife https://doi.org/10.7554/eLife.33125 (2018).

  78. Heckert, A., Dahal, L., Tjian, R. & Darzacq, X. Recovering mixtures of fast-diffusing states from short single-particle trajectories. eLife https://doi.org/10.7554/eLife.70169 (2022).

  79. Wagner, T., Kroll, A., Haramagatti, C. R., Lipinski, H. G. & Wiemann, M. Classification and segmentation of nanoparticle diffusion trajectories in cellular micro environments. PLoS ONE 12, e0170165 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Pinholt, H. D., Bohr, S. S., Iversen, J. F., Boomsma, W. & Hatzakis, N. S. Single-particle diffusional fingerprinting: a machine-learning framework for quantitative analysis of heterogeneous diffusion. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2104624118 (2021).

  81. Saxton, M. J. Lateral diffusion in an archipelago. Single-particle diffusion. Biophys. J. 64, 1766–1780 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Koo, P. K. & Mochrie, S. G. Systems-level approach to uncovering diffusive states and their transitions from single-particle trajectories. Phys. Rev. E 94, 052412 (2016).

    Article  PubMed  Google Scholar 

  83. Kapadia, N., El-Hajj, Z. W. & Reyes-Lamothe, R. Bound2Learn: a machine learning approach for classification of DNA-bound proteins from single-molecule tracking experiments. Nucleic Acids Res. 49, e79 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Luan, J. et al. Distinct properties and functions of CTCF revealed by a rapidly inducible degron system. Cell Rep. 34, 108783 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Chazeau, A., Katrukha, E. A., Hoogenraad, C. C. & Kapitein, L. C. Studying neuronal microtubule organization and microtubule-associated proteins using single molecule localization microscopy. Methods Cell Biol. 131, 127–149 (2016).

    Article  PubMed  Google Scholar 

  86. Bohrer, C. H. et al. A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM. Nat. Methods 18, 669–677 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Morawska, M. & Ulrich, H. D. An expanded tool kit for the auxin-inducible degron system in budding yeast. Yeast 30, 341–351 (2013).

    Article  CAS  PubMed  Google Scholar 

  88. Papagiannakis, A., de Jonge, J. J., Zhang, Z. & Heinemann, M. Quantitative characterization of the auxin-inducible degron: a guide for dynamic protein depletion in single yeast cells. Sci. Rep. 7, 4704 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Gesnel, M. C., Del Gatto-Konczak, F. & Breathnach, R. Combined use of MS2 and PP7 coat fusions shows that TIA-1 dominates hnRNP A1 for K-SAM exon splicing control. J. Biomed. Biotechnol. 2009, 104853 (2009).

    Article  PubMed  Google Scholar 

  90. Brouwer, I., Kerklingh, E., van Leeuwen, F. & Lenstra, T. L. Dynamic epistasis analysis reveals how chromatin remodeling regulates transcriptional bursting. Nat. Struct. Mol. Biol. https://doi.org/10.1038/s41594-023-00981-1 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Li, L., Waymack, R., Gad, M. & Wunderlich, Z. Two promoters integrate multiple enhancer inputs to drive wild-type knirps expression in the Drosophila melanogaster embryo. Genetics https://doi.org/10.1093/genetics/iyab154 (2021).

  92. Zhang, T. et al. An improved method for whole protein extraction from yeast Saccharomyces cerevisiae. Yeast 28, 795–798 (2011).

    Article  CAS  PubMed  Google Scholar 

  93. Ling, Y. H. Ling et al 2024 [Data set]. Zenodo https://doi.org/10.5281/zenodo.10570246 (2024).

  94. Ling, Y. H. Ling-et-al-2024. GitHub https://github.com/yhinling/Ling-et-al-2024 (2024).

  95. 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  PubMed Central  Google Scholar 

  96. Taddei, A. & Gasser, S. M. Structure and function in the budding yeast nucleus. Genetics 192, 107–129 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Tsai, K. L. et al. A conserved Mediator-CDK8 kinase module association regulates Mediator-RNA polymerase II interaction. Nat. Struct. Mol. Biol. 20, 611–619 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Knuesel, M. T., Meyer, K. D., Bernecky, C. & Taatjes, D. J. The human CDK8 subcomplex is a molecular switch that controls Mediator coactivator function. Genes Dev. 23, 439–451 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Elmlund, H. et al. The cyclin-dependent kinase 8 module sterically blocks Mediator interactions with RNA polymerase II. Proc. Natl Acad. Sci. USA 103, 15788–15793 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Mazza, D., Abernathy, A., Golob, N., Morisaki, T. & McNally, J. G. A benchmark for chromatin binding measurements in live cells. Nucleic Acids Res. 40, e119 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank S. Cho and G. Ling for assistance in image processing; L. Lavis for providing Janelia Fluor dyes; K. Xie for IUPRED3 data mining; X. Tang and S. Liu for computational assistance; N. Jones, V.Schoonderwoert and C. Almonte for microscopy technical support; K. Yuen and G. Mizuguchi for plasmids and yeast strains; C. Kaplan and J. Yao for valuable information on strain-sensitivity to MPA; A. Hansen, A. Musacchio, C. Wong, I. Cissé and J. M. Kim for helpful discussions; and members of the Wu laboratory for comments. The present study was supported by the National Institutes of Health (grant nos. GM132290 and R35GM149291 to C.W.) and the Croucher Foundation (Y.H.L.).

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Authors and Affiliations

Authors

Contributions

Y.H.L., J.L.C. and C.W. designed the experiments. Y.H.L. performed the experiments and analysed the data. Z.Y. performed SMT on Hsf1-Halo in the WT background. G.P. contributed to the initial trial of spatiotemporal mapping. Z.Y., C.L. and C.Y. assisted in experiments. Y.H.L., J.L.C. and C.W. wrote the manuscript.

Corresponding author

Correspondence to Carl Wu.

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The authors declare no competing interests.

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Nature Cell Biology thanks Hiroshi Kimura, Yan Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Single-molecule tracking in living yeast.

a, ER and nucleolus shown by Elo3-GFP and Gar1-GFP. Scale bar, 1.0 μm. b, Coarse-grained representation of yeast interphase chromosomes, physically constrained by telomere (TEL)-nuclear envelope and centromere-spindle pole body (CEN-SPB) tethering. c, Overlay of RPB1Rpo21-HaloJF552 trajectories on the nucleus relative to ER and nucleolar GFP markers. Rainbow colours indicate the first appearance of each trajectory. Scale bar, 1 μm. d, Single-molecule trajectories of RPB1Rpo21-HaloJF552 (free or bound) with diffusion coefficients. Scale bar, 0.2 μm. e, Protein of interested (POI) fused with HaloTag, labeled with JF552-HaloTag ligand (JF552-HTL) (top). Initial laser exposure of JF552 resulted in strong ‘nuclear glow’, followed by shelving in dark state and stochastic reactivation, leading to single-molecule detection. Nucleus circled in red. Scale bar, 1.0 μm. (bottom). f, Strong 555 nm laser exposure for 5 min does not result in noticeable cell death or growth arrest. Scale bar, 4.0 μm. g, ER and nucleolar GFP markers for cell cycle stage identification. Scale bar, 1.0 μm. h, Diffusion coefficient histograms of various nuclear proteins (n: number of trajectories; mean value ± s.d.). i, Assessing the mean diffusion coefficients of the bound population reveals no substantial difference between histones (H2B, H3 and H2A.Z) and proteins that can move along DNA (for example RNAPII, RNAPIII, Paf1), while nucleolar RNAPI, and proteins that are physically tethered (Cse4 and Sir4) have notably lower values (n = 100 resamplings; mean value ± s.d.). Source numerical data are available in source data.

Source data

Extended Data Fig. 2 Multiparameter classification of trajectories.

a, Unsupervised vbSPT overfits SMT data of RNAPII (n = 100 resamplings; mean value ± s.d.). b, Diffusion coefficient histogram for fast and slow states from 2-state HMM using vbSPT. A minor fraction of very slowly diffusing trajectories was misclassified as fast-state (dashed circle) (n: number of trajectories; mean value ± s.d.). c, Unsupervised multiparameter classification of RNAPII trajectories with UMAP dimensionality reduction and GMM clustering. d, Diffusion coefficient (D) distribution for the classified clusters (n: number of trajectories; mean value ± s.d.). e,f, similar to c and d, but with multiparameter classification semi-supervised by 2-state HMM. d,f, Compared to b, Fast-class diffusion coefficient distribution showed less tailing (dashed circle). g, 10 parameters used for classification and their distributions in identified classes (n = 3733 trajectories for class 1 and n = 2607 trajectories for class 2; median (line), IQR (box), 10–90 percentile (whiskers) and outliers (crosses); two-tailed unpaired t-test, *** P < 0. 000000001). Source numerical data are available in source data.

Source data

Extended Data Fig. 3 Spatiotemporal mapping reveals dynamics of nucleosome and nuclear landmark proteins.

a, Nuclei in G1 cells with minimal drift selected for spatiotemporal mapping. Scale bar: 1.0 μm. b, Localization density calculated using 150 nm detection radius from bins separated by 10 nm. c, 150 nm detection radius and bin distance of 10 nm provide optimal coverage and resolution for the density on the bound map of RNAPII. Scale bar: 0.5 μm (n = 15 cells; Error bar: centroid of nucleolus ± s.d.). d, 3D simulation of the yeast interphase genome based on 3 C data37. e, Top mRNA genes simulation maps based on gene expression data in minimal medium38. Left panel is reuse of Fig. 1d top panel (n: number of genes). f, Freely diffusing NLSx2-Halo map. Scale bar: 0.5 μm (Error bar: centroid of nucleolus ± s.d.; n: number of nuclei). g, Bound Cse4 (left) and Sir4 (right) maps (Error bar: centroid of nucleolus ± s.d.; n: number of nuclei). Sir4 bound map showed dense regions proximal and distal to the centromere, mirroring the telomere clusters of short and long chromosomes35,37,95. h, Bound H2B diffusion coefficient map. A 300 nm detection radius was used. Scale bar: 0.5 μm (Error bar: centroid of nucleolus ± s.d.; n: number of nuclei). Telomere and centromere movements are confined due to attachment to the nuclear envelope and spindle pole body, respectively96. Likewise, the local diffusion coefficients of chromatin-bound H2B reveal lower histone dynamics near centromeres and telomeres (Extended Data Fig. 1h, i).

Extended Data Fig. 4 Spatiotemporal dynamics of RNAPII, RNAPI and RNAPIII.

a, Fraction of free and bound in nucleoplasm (NPL) and nucleolus (NOL) (n = 100 resamplings; mean value ± s.d.). b, Distribution (area normalized) of free RNAPII, RNAPI and RNAPIII in nucleoplasm and nucleolus (n = 100 resamplings; mean value ± s.d.). c, Simulation of Nucleoplasm/Nucleolus distribution. d, Diffusion coefficients and molecular weights of free RNAPII, RNAPI and RNAPIII in nucleoplasm (n = 100 resamplings; mean value ± s.d.). e,f IUPRED3 disorder scores for the largest subunit of e, RNAPI (Rpa190) and f, RNAPIII (Rpo31). Residues with predicted scores above 0.5 considered disordered. g, Dfree of RNAPII and CTD mutants in nucleoplasm (n = 100 resamplings; mean value ± s.d.). Source numerical data are available in source data.

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Extended Data Fig. 5 CTD length affects RNAPII subcellular distribution and expression.

a, Diffusion coefficient histogram for RNAPII with varying CTD lengths (n: number of trajectories; mean value ± s.d.). b-c, b, nuclear/cytoplasmic ratio and c, relative nuclear intensity of WT RNAPII and CTD mutants (median (line), IQR (box), 10–90 percentile (whiskers) and outliers (crosses), n = 95 nuclei for CTD0, 52 nuclei for CTD8, 69 nuclei for CTD9, 64 nuclei for CTD10, 112 nuclei for CTD15, 108 nuclei for CTD20, 69 nuclei for CTD26, 73 nuclei for CTD52, 91 nuclei for CTD78, 102 nuclei for CTD104). CTD truncation led to increased cytoplasmic and nucleolar distribution, and overexpression of RNAPII. d, Amount of bound RNAPII normalized to nuclear fluorescence intensity (n = 100 resamplings; mean value ± s.d.). The normalized value is an approximation, as the relationship between nuclear fluorescence intensity and RNAPII levels may not be strictly linear. e, Fluorescence signal of RPB1Rpo21-AID*-miRFP670nano3 (red) before and after RNAPII degradation by auxin. Nucleolar and ER markers in green. Scale bar: 1.0 μm. f, Western blot showing time course degradation of RPB1Rpo21-AID* by auxin, detected using CTD antibody (top), and Ponceau S staining on total protein (bottom). g,h, Cells expressing ectopic RPB1Rpo21-Halo in an RPB1Rpo21 AID background show minimal changes in the g, bound fraction (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, * P = 0.015275) and h, f180/0 of RNAPII after auxin treatment, compared to those in WT expressing RPB1Rpo21-Halo (n = 100 resamplings; mean value ± s.d.). i, Spot assay for strains with prd5Δ, GFP markers (GGEGp), RPB1Rpo21-nCDT26, or RPB1Rpo21-nCDT26-Halo showing identical growth. j, Spot assay demonstrating impaired cell growth for RPB1Rpo21 or MED14Rgr1 AID degron. All AID* constructs contain miRFP670nano3 as a fluorescence marker. k, Spot assay for strains with HaloTag fusions to various PIC component subunits to assess MPA sensitivity. Ssl2-Halo (TFIIH), Halo-Ssl2 (TFIIH), Tfa2-Halo (TFIIE), Tfg2-Halo (TFIIF) exhibited MPA sensitivity. Source numerical data and unprocessed blots are available in source data.

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Extended Data Fig. 6 CTD length impacts free RNAPII anisotropy.

a, Brownian simulations indicate substantial apparent anisotropy for mean displacement longer than 350 nm (n = 100 resamplings; mean value ± s.d.). b, Apparent anisotropy due to nuclear confinement in small yeast nucleus. c, CTD length increase leads to an elevation in f180/0 trend (n = 100 resamplings; mean value ± s.d.). Source numerical data are available in source data.

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Extended Data Fig. 7 Investigating the role of Mediator in spatiotemporal confinement of RNAPII.

a, Bound Mediator map (left). Free RNAPII-CTD26 map showing confined trajectories (right). Scale bar: 0.5 μm. (Error bar: centroid of nucleolus ± s.d.; n: number of nuclei). b, Free RNAPII-CTD26 map in MED14Rgr1 AID. Scale bar: 0.5 μm (Error bar: centroid of nucleolus ± s.d.; n: number of nuclei). c-d, c, Dfree in nucleoplasm (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, ns P = 0.510991) and d, Nucleoplasm/Nucleolus of RNPAII-CTD26 in MED14Rgr1 AID (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, *** P = 0.000008). e-g, e, Mediator bound fraction (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, ** P = 0.006771), f, RNAPII bound fraction (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, ns P = 0.157495) and g, f180/0 for RNAPII-CTD9 in CTD26 background (n = 100 resamplings; mean value ± s.d.). h,i, h, Relative bound fraction (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, * P = 0.012696, ** P = 0.001329) and i, f180/0 for RNAPII-CTD26 and RNAPII-CTD9 in WT and ssn3Δ (n = 100 resamplings; mean value ± s.d.). Deleting Cdk8SSN3 from the Mediator kinase module enhances interaction between the Mediator and RNAPII97,98,99 without changing free RNAPII confinement. j,k, j, Relative bound fraction (n = 100 resamplings; mean value ± s.d.; two-tailed unpaired t-test, * P ≤ 0.05 and *** P ≤ 0.001. Comparison between before and after auxin treatment: P = 0.000014 for CTD26 and P = 0.0222222 for CTD9. Comparison between CTD26 and CTD26 after auxin treatment: P = 0.034745) and k, f180/0 (n = 100 resamplings; mean value ± s.d.) for RNAPII-CTD26 and RNAPII-CTD9 in MED14Rgr1 AID. ln, l, Survival probability of H2B-corrected residence times (n = 10,000 resamplings; mean value ± s.d.), m, stably bound fractions (n = 10,000 resamplings; mean value ± s.d.; two-tailed unpaired t-test, ** P = 0.002245) and n, mean residence times (n = 10,000 resamplings; mean value ± s.d.; two-tailed unpaired t-test, * P = 0.019928) for RNAPII-CTD9 in MED14Rgr1 AID. Source numerical data are available in source data.

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Extended Data Fig. 8 Fast and slow tracking mode of single-molecule tracking.

a, Fast tracking with high laser power and short frame rate (10 ms/frame) reveals diffusive dynamics of free (red) and bound (blue) molecules. b, Single-step disappearance of chromatin-bound RNAPII in fast tracking. c, Slow tracking with low laser power and long frame rate (250 ms/frame) reveals residence time of bound molecules (blue). d, Single-step disappearance of chromatin-bound RNAPII in slow tracking. b-d, Here we term ‘disappearance’ as we cannot definitively differentiate between the molecule diffusing out of the focal plane or photobleaching within the living cell. e, CDF of bound displacement of RNAPII, H2B, H3 and H2A.Z to determine the rmax for trajectory linking in slow tracking100. f, In G1 cells, nucleosomal H2B (representing the stable binding population) was hypothesized to bind for a sufficiently long period, such that during image acquisition, their dissociation was barely observed. Nonetheless, the observed residence times for H2B typically fall within 30 seconds, due to factors such as photobleaching, dye blinking, chromatin/nuclear movements, and focus drift. g, Survival probability of Halo-H2B observed residence times in CTD26 (WT) and CTD9 strains (n: number of trajectories; mean value ± s.d.). h, Decay constant of stably bound Halo-H2B (ksb) in CTD26 (WT) and CTD9 strains (n = 10,000 resamplings; mean value ± s.d.; two-tailed unpaired t-test, ns P = 0.339598). Source numerical data are available in source data.

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Extended Data Fig. 9 CTD length controls HSP82 transcription bursting, with minimal effect on Hsf1 dynamics.

a, b, a, Diffusion coefficient histograms for Hsf1-Halo and b, survival probability of bound Hsf1-Halo under heat shock in CTD26 (WT) (left) and CTD9 (right) strains (n: number of trajectories; mean value ± s.d.). c, d, c, HSP82 ON time and d, OFF time cumulative distribution function (CDF) under heat shock in CTD26 (WT) (left) and CTD9 (right) strains (n: number of ON or OFF events; mean value ± s.d.). Source numerical data are available in source data.

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Extended Data Fig. 10 CTD is necessary but not sufficient for confining protein diffusion.

a, HaloTag (NLSx2-Halo) and Halo-CTD fusions diffusion coefficient histogram by CTD length (n: number of trajectories; mean value ± s.d.). The first plot is reuse of the top panel’s second plot from Extended Data Fig. 1h. b, HaloTag and Halo-CTD fusions bulk wide-field staining using JFX650 in live cell. Scale bar: 1.0 μm. c, Nucleoplasm/Nucleolus ratios for freely diffusing HaloTag and Halo-CTD fusions (n = 100 resamplings; mean value ± s.d.). d, Protein disorder affects hydrodynamic radius (Rh). e, Theoretical relationship between molecule weight and Rh for folded and unfolded peptides (data from Fluidic Analytics). f, g, f, Dfree and estimated Rh of the HaloTag and Halo-CTD fusions in nucleoplasm and nucleolus. Data fitted with Stokes-Einstein equation to calculate g, apparent viscosity (η) of yeast nucleoplasm (NPL) and nucleolus (NOL), respectively. KB: Boltzmann’s constant. T: Temperature in Kelvin; 295.15 K (22 °C) (n = 100 resamplings; mean value ± s.d.). h, f180/0 plot for HaloTag and Halo-CTD fusions (n = 100 resamplings; mean value ± s.d.). Source numerical data are available in source data.

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Supplementary information

Supplementary Information

Supplementary Tables 1 and 2 and Figs. 1–5.

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Supplementary Video 1

Single-molecule tracking of RNAPII. JF552 signal is in red and ER and nucleolar GFP markers are in green. For demonstration only, because simultaneous GFP marker imaging affects single-molecule signal-to-noise ratio. Scale bar, 2.0 μm, Recorded frame rate: 30 ms per frame. Playback speed: 30 ms per frame.

Supplementary Video 2

Fast tracking of RNAPII-CTD26 (WT) and RNAPII-CTD9. Nucleolus is in grey, nuclear envelope and plasma membrane outlined in solid and dashed white, respectively. Scale bar, 1.0 μm. Colour scale represents mean instantaneous velocity of trajectory (µm s−1). Recorded frame rate: 10 ms per frame. Playback speed: 40 ms per frame.

Supplementary Video 3

Anisotropic trajectory of free RNAPII. Scale bar, 0.2 μm. Recorded frame rate: 10 ms per frame. Playback speed: 50 ms per frame.

Supplementary Video 4

Sir4-HaloJFX650 in WT and esc1Δ yku70Δ strain. Scale bar, 1.0 μm. Recorded frame rate: 50 ms per frame. Playback speed: 50 ms per frame.

Supplementary Video 5

Slow tracking kymograph of chromatin-bound RNAPII. Recorded frame rate: 250 ms per frame. Playback speed: 100 ms per frame.

Supplementary Video 6

HSP82 transcription bursting in WT under non-HS condition. In addition to a strong signal at nuclear TS, cytoplasmic mRNAs are visible from 10:40 to 19:20. Scale bar, 1.0 μm. Recorded frame rate: 20 s per frame. Playback speed: 100 ms per frame.

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Ling, Y.H., Ye, Z., Liang, C. et al. Disordered C-terminal domain drives spatiotemporal confinement of RNAPII to enhance search for chromatin targets. Nat Cell Biol 26, 581–592 (2024). https://doi.org/10.1038/s41556-024-01382-2

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