Chromatin jets define the properties of cohesin-driven in vivo loop extrusion

Ya Guo, Ediem Al-Jibury, Rosalba Garcia-Millan, Konstantinos Ntagiantas, James W.D. King, Alex J. Nash, Niels Galjart, Boris Lenhard, Daniel Rueckert, Amanda G. Fisher, Gunnar Pruessner*, Matthias Merkenschlager

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Complex genomes show intricate organization in three-dimensional (3D) nuclear space. Current models posit that cohesin extrudes loops to form self-interacting domains delimited by the DNA binding protein CTCF. Here, we describe and quantitatively characterize cohesin-propelled, jet-like chromatin contacts as landmarks of loop extrusion in quiescent mammalian lymphocytes. Experimental observations and polymer simulations indicate that narrow origins of loop extrusion favor jet formation. Unless constrained by CTCF, jets propagate symmetrically for 1–2 Mb, providing an estimate for the range of in vivo loop extrusion. Asymmetric CTCF binding deflects the angle of jet propagation as experimental evidence that cohesin-mediated loop extrusion can switch from bi- to unidirectional and is controlled independently in both directions. These data offer new insights into the physiological behavior of in vivo cohesin-mediated loop extrusion and further our understanding of the principles that underlie genome organization.

Original languageEnglish
Pages (from-to)3769-3780.e5
JournalMolecular Cell
Volume82
Issue number20
Early online date30 Sep 2022
DOIs
Publication statusPublished - 20 Oct 2022

Bibliographical note

Funding Information:
We thank J. Elliott and B. Patel for cell sorting, L. Game for sequencing, and A. Thomas for computational support. This work was supported by the Medical Research Council UK, The Wellcome Trust (222845/Z/21/Z to K.N. and Investigator Award 099276/Z/12/Z to M.M.), EMBO (ALTF 620-2016 to Y.G.), a UK Government Industrial Strategy Rutherford Fund Fellowship (Y.G.), a UK National Productivity Investment Fund Ph.D. studentship in Data Science or Artificial Intelligence (E.A.-J.), and the Shanghai Science and Technology Commission (20PJ1405500/21DZ2210200 to Y.G.). R.G.-M. was supported in part by the European Research Council under the EU's Horizon 2020 Programme (grant number 740269) and acknowledges support from a St John's College Research Fellowship, University of Cambridge. Y.G. E.A.-J. R.G.-M. K.N. B.L. D.R. A.G.F. G.P. and M.M. conceptualized the study. Y.G. generated the data. Y.G. E.A.-J. R.G.-M. K.N. J.W.D.K. A.J.N. G.P. and M.M. analyzed and visualized the data. K.N. did the computer simulation. N.G. contributed unique reagents and expertise. Y.G. E.A.-J. R.G.-M. K.N. B.L. D.R. A.G.F. G.P. and M.M. wrote the manuscript. The authors declare no competing interests. We support inclusive, diverse, and equitable conduct of research.

Funding Information:
We thank J. Elliott and B. Patel for cell sorting, L. Game for sequencing, and A. Thomas for computational support. This work was supported by the Medical Research Council UK , The Wellcome Trust ( 222845/Z/21/Z to K.N. and Investigator Award 099276/Z/12/Z to M.M.), EMBO ( ALTF 620-2016 to Y.G.), a UK Government Industrial Strategy Rutherford Fund Fellowship (Y.G.), a UK National Productivity Investment Fund Ph.D. studentship in Data Science or Artificial Intelligence (E.A.-J.), and the Shanghai Science and Technology Commission ( 20PJ1405500 / 21DZ2210200 to Y.G.). R.G.-M. was supported in part by the European Research Council under the EU’s Horizon 2020 Programme (grant number 740269 ) and acknowledges support from a St John’s College Research Fellowship, University of Cambridge.

Publisher Copyright:
© 2022 The Authors

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