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Mechanistic modeling of chromatin folding to understand function

Abstract

Experimental approaches have been applied to address questions in understanding three-dimensional chromatin organization and function. As datasets increase in size and complexity, it becomes a challenge to reach a mechanistic interpretation of experimental results. Polymer simulations and mechanistic modeling have been applied to explain experimental observations and their links to different aspects of genome function. Here we provide a guide for biologists, explaining different simulation approaches and the contexts in which they have been used.

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Fig. 1: Coarse-grained molecular dynamics simulations of chromatin.
Fig. 2: Commonly used models for understanding chromosome organization.
Fig. 3: A gene locus model: the Highly Predictive Heteromorphic Polymer model (HiP-HoP).

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References

  1. Han, J., Zhang, Z. & Wang, K. 3C and 3C-based techniques: the powerful tools for spatial genome organization deciphering. Mol. Cytogenet. 11, 21 (2018).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376–380 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Schmitt, A. D. et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042–2059 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Vian, L. et al. The energetics and physiological impact of cohesin extrusion. Cell 173, 1165–1178.e20 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. van der Maarel, J. R. C. Introduction to Biopolymer Physics (World Scientific Publishing, 2007).

  8. Ingólfsson, H. I. et al. The power of coarse graining in biomolecular simulations. Wiley Interdiscip. Rev. Comput. Mol. Sci. 4, 225–248 (2014).

    PubMed  Google Scholar 

  9. Serra, F. et al. Restraint-based three-dimensional modeling of genomes and genomic domains. FEBS Lett. 589, 2987–2995 (2015). 20 Pt A.

    CAS  PubMed  Google Scholar 

  10. Giorgetti, L. et al. Predictive polymer modeling reveals coupled fluctuations in chromosome conformation and transcription. Cell 157, 950–963 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  12. Baù, D. et al. The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nat. Struct. Mol. Biol. 18, 107–114 (2011).

    PubMed  Google Scholar 

  13. Frenkel, D. & Smit, B. Understanding Molecular Simulation (Elsevier, 2001).

  14. Hollingsworth, S. A. & Dror, R. O. Molecular dynamics simulation for all. Neuron 99, 1129–1143 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Fosado, Y. A. G. et al. A single nucleotide resolution model for large-scale simulations of double stranded DNA. Soft Matter 12, 9458–9470 (2016).

    CAS  PubMed  Google Scholar 

  16. Ouldridge, T. E., Louis, A. A. & Doye, J. P. K. Structural, mechanical, and thermodynamic properties of a coarse-grained DNA model. J. Chem. Phys. 134, 085101 (2011).

    PubMed  Google Scholar 

  17. Arya, G. & Schlick, T. Role of histone tails in chromatin folding revealed by a mesoscopic oligonucleosome model. Proc. Natl Acad. Sci. USA 103, 16236–16241 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Mirny, L. A. The fractal globule as a model of chromatin architecture in the cell. Chromosome Res. 19, 37–51 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Cook, P. R. & Marenduzzo, D. Entropic organization of interphase chromosomes. J. Cell Biol. 186, 825–834 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  21. Barbieri, M. et al. Complexity of chromatin folding is captured by the strings and binders switch model. Proc. Natl Acad. Sci. USA 109, 16173–16178 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Brackley, C. A., Taylor, S., Papantonis, A., Cook, P. R. & Marenduzzo, D. Nonspecific bridging-induced attraction drives clustering of DNA-binding proteins and genome organization. Proc. Natl Acad. Sci. USA 110, E3605–E3611 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Brackley, C. A., Johnson, J., Kelly, S., Cook, P. R. & Marenduzzo, D. Simulated binding of transcription factors to active and inactive regions folds human chromosomes into loops, rosettes and topological domains. Nucleic Acids Res. 44, 3503–3512 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Brackley, C. A. et al. Ephemeral protein binding to DNA shapes stable nuclear bodies and chromatin domains. Biophys. J. 112, 1085–1093 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 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  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Brackley, C. A. et al. Extrusion without a motor: a new take on the loop extrusion model of genome organization. Nucleus 9, 95–103 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Nora, E. P. et al. Targeted degradation of CTCF decouples local insulation of chromosome domains from genomic compartmentalization. Cell 169, 930–944.e22 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Schwarzer, W. et al. Two independent modes of chromatin organization revealed by cohesin removal. Nature 551, 51–56 (2017).

    PubMed  PubMed Central  Google Scholar 

  34. Haarhuis, J. H. I. et al. The cohesin release factor WAPL restricts chromatin loop extension. Cell 169, 693–707.e14 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 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 

  36. Goloborodko, A., Marko, J. F. & Mirny, L. A. Chromosome compaction by active loop extrusion. Biophys. J. 110, 2162–2168 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Hughes, J. R. et al. Analysis of hundreds of cis-regulatory landscapes at high resolution in a single, high-throughput experiment. Nat. Genet. 46, 205–212 (2014).

    CAS  PubMed  Google Scholar 

  40. Brackley, C. A. et al. Predicting the three-dimensional folding of cis-regulatory regions in mammalian genomes using bioinformatic data and polymer models. Genome Biol. 17, 59 (2016).

    PubMed  PubMed Central  Google Scholar 

  41. Buckle, A., Brackley, C. A., Boyle, S., Marenduzzo, D. & Gilbert, N. Polymer simulations of heteromorphic chromatin predict the 3D folding of complex genomic loci. Mol. Cell 72, 786–797.e11 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Risca, V. I., Denny, S. K., Straight, A. F. & Greenleaf, W. J. Variable chromatin structure revealed by in situ spatially correlated DNA cleavage mapping. Nature 541, 237–241 (2017).

    CAS  PubMed  Google Scholar 

  43. Schlick, T., Hayes, J. & Grigoryev, S. Toward convergence of experimental studies and theoretical modeling of the chromatin fiber. J. Biol. Chem. 287, 5183–5191 (2012).

    CAS  PubMed  Google Scholar 

  44. Bascom, G. D., Sanbonmatsu, K. Y. & Schlick, T. Mesoscale modeling reveals hierarchical looping of chromatin fibers near gene regulatory elements. J. Phys. Chem. B 120, 8642–8653 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Ou, H. D. et al. ChromEMT: visualizing 3D chromatin structure and compaction in interphase and mitotic cells. Science 357, eaag0025 (2017).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Chiang, M. et al. Polymer modeling predicts chromosome reorganization in senescence. Cell Rep. 28, 3212–3223.e6 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Schalch, T., Duda, S., Sargent, D. F. & Richmond, T. J. X-ray structure of a tetranucleosome and its implications for the chromatin fibre. Nature 436, 138–141 (2005).

    CAS  PubMed  Google Scholar 

  49. Hinckley, D. M., Freeman, G. S., Whitmer, J. K. & de Pablo, J. J. An experimentally-informed coarse-grained 3-site-per-nucleotide model of DNA: structure, thermodynamics, and dynamics of hybridization. J. Chem. Phys. 139, 144903 (2013).

    PubMed  PubMed Central  Google Scholar 

  50. Brackley, C. A., Morozov, A. N. & Marenduzzo, D. Models for twistable elastic polymers in Brownian dynamics, and their implementation for LAMMPS. J. Chem. Phys. 140, 135103 (2014).

    CAS  PubMed  Google Scholar 

  51. Bascom, G. D., Myers, C. G. & Schlick, T. Mesoscale modeling reveals formation of an epigenetically driven HOXC gene hub. Proc. Natl Acad. Sci. USA 116, 4955–4962 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Wocjan, T., Klenin, K. & Langowski, J. Brownian dynamics simulation of DNA unrolling from the nucleosome. J. Phys. Chem. B 113, 2639–2646 (2009).

    CAS  PubMed  Google Scholar 

  53. Brackley, C. A., Allan, J., Keszenman-Pereyra, D. & Marenduzzo, D. Topological constraints strongly affect chromatin reconstitution in silico. Nucleic Acids Res. 43, 63–73 (2015).

    CAS  PubMed  Google Scholar 

  54. Wiese, O., Marenduzzo, D. & Brackley, C. A. Nucleosome positions alone can be used to predict domains in yeast chromosomes. Proc. Natl Acad. Sci. USA 116, 17307–17315 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Chiariello, A. M., Annunziatella, C., Bianco, S., Esposito, A. & Nicodemi, M. Polymer physics of chromosome large-scale 3D organisation. Sci. Rep. 6, 29775 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Racko, D., Benedetti, F., Dorier, J. & Stasiak, A. Are TADs supercoiled? Nucleic Acids Res. 47, 521–532 (2019).

    CAS  PubMed  Google Scholar 

  57. Barbieri, M. et al. Active and poised promoter states drive folding of the extended HoxB locus in mouse embryonic stem cells. Nat. Struct. Mol. Biol. 24, 515–524 (2017).

    CAS  PubMed  Google Scholar 

  58. Serra, F. et al. Automatic analysis and 3D-modeling of Hi-C data using TADbit reveals structural features of the fly chromatin colors. PLOS Comput. Biol. 13, e1005665 (2017).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Bianco, S. et al. Polymer physics predicts the effects of structural variants on chromatin architecture. Nat. Genet. 50, 662–667 (2018).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Plimpton, S. Fast parallel algorithms for short-range molecular-dynamics. J. Comput. Phys. 117, 1–19 (1995).

    CAS  Google Scholar 

  63. Anderson, J. A., Lorenz, C. D. & Travesset, A. General purpose molecular dynamics simulations fully implemented on graphics processing units. J. Comput. Phys. 227, 5342–5359 (2008).

    Google Scholar 

  64. Limbach, H.-J., Arnold, A., Mann, B. & Holm, C. ESPResSo – an extensible simulation package for research on soft matter systems. Comput. Phys. Commun. 174, 704–727 (2006).

    CAS  Google Scholar 

  65. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 27–28 (1996). 33–38.

    Google Scholar 

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Acknowledgements

The authors would like to thank members of their groups for stimulating discussions. Research in the Marenduzzo group is supported by the European Research Council (CoG 648050, THREEDCELLPHYSICS); research in the Gilbert lab is funded by the UK Medical Research Council (MR/J00913X/1 and MC_UU_00007/13).

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C.A.B. designed and co-wrote the manuscript. D.M. co-wrote the manuscript. G.N. conceived and co-wrote the manuscript.

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Correspondence to Davide Marenduzzo or Nick Gilbert.

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Peer review information Lei Tang and Nicole Rusk were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Brackey, C.A., Marenduzzo, D. & Gilbert, N. Mechanistic modeling of chromatin folding to understand function. Nat Methods 17, 767–775 (2020). https://doi.org/10.1038/s41592-020-0852-6

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