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. 2017:82:45-55.
doi: 10.1101/sqb.2017.82.034710. Epub 2018 May 4.

Emerging Evidence of Chromosome Folding by Loop Extrusion

Geoffrey Fudenberg  1 , Nezar Abdennur  2   3 , Maxim Imakaev  3 , Anton Goloborodko  3   4 , Leonid A Mirny  3   4
Affiliations

Emerging Evidence of Chromosome Folding by Loop Extrusion

Geoffrey Fudenberg et al. Cold Spring Harb Symp Quant Biol. 2017.

Abstract

Chromosome organization poses a remarkable physical problem with many biological consequences: How can molecular interactions between proteins at the nanometer scale organize micron-long chromatinized DNA molecules, insulating or facilitating interactions between specific genomic elements? The mechanism of active loop extrusion holds great promise for explaining interphase and mitotic chromosome folding, yet remains difficult to assay directly. We discuss predictions from our polymer models of loop extrusion with barrier elements and review recent experimental studies that provide strong support for loop extrusion, focusing on perturbations to CTCF and cohesin assayed via Hi-C in interphase. Finally, we discuss a likely molecular mechanism of loop extrusion by structural maintenance of chromosomes complexes.

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Figures

Figure 1.
Figure 1.
Polymer model of loop extrusion with barrier elements recapitulates features of interphase chromosome folding (see also Supplemental Movie 1). (A) Illustrations of the four key parameters governing the dynamics of interphase loop extrusion: LEF velocity, LEF lifetime, LEF separation, and barrier strength. Characterizing how changes to these parameters affect Hi-C maps in silico allows us to make experimental predictions for perturbations. (B) To compare our models with Hi-C experiments, we generate ensembles of conformations for each set of parameters, and then compute average contact maps. To compare with imaging experiments, we can calculate other observables (e.g., pairwise distance between loci). (C) Interphase Hi-C data from mouse neural progenitor cells (Bonev et al. 2017), plotted with HiGlass (Kerpedjiev et al. 2017), annotated with features that can emerge via loop extrusion in blue (i–iv). Arc diagrams depict how stochastic configurations of LEF-mediated loops in distinct nuclei can lead to the population-averaged features. Chromatin loops directly held by LEFs are depicted with yellow arcs, whereas dashed gray arcs depict “transitive loops” from sets of adjacent LEFs. (i) Insulation, observed as squares along the diagonal of Hi-C maps (i.e., TADs), arises when extrusion barriers halt LEF translocation. LEFs then facilitate additional contacts within TADs, but not between TADs. (ii) Flames (or tracks), observed as straight lines often emerging from the borders of TADs, arise when LEFs become halted on one side at a barrier while continuing to extrude from the other side (referred to as “lines” in Fudenberg et al. 2016). (iii) Peaks of enriched contact frequency often appear at the corners of TADs and also often coincide with intersection points of flames. These peaks emerge as a result of LEFs being halted on both sides by extrusion barriers. (iv) Peak grids can emerge either when internal boundaries are skipped or via transitive sets of LEF-mediated loops.
Figure 2.
Figure 2.
Loop extrusion polymer simulations predict the consequences of cohesin and CTCF perturbations. (Top row) Simulated Hi-C maps for indicated perturbations. (Bottom row) P(s) for indicated perturbation compared to WT P(s). All simulations considered a 36-Mb chain (3600 monomers) with the same positions and orientations of CTCF barriers (separated by 300 kb) and the same LEF velocity (250 3D-per-1D steps). (A) WT simulations used processivity 200 kb, separation 200 kb, and barrier strength 0.995. The shoulder in P(s), indicative of compaction via loop extrusion, is indicated in gray. (B) For ΔCohesin, our simulations predict the loss of TADs, peaks, flames, and the shoulder of P(s). ΔCohesin was simulated using processivity 200 kb, separation 2 Mb, and boundary strength 0.995. This can represent the loss of actively extruding cohesins via ΔNipbl, ΔRad21, or other cohesin subunits. (C) For ΔCTCF, our simulations predict the loss of TADs, peaks, flames, yet no discernible change to P(s). This arises because CTCF plays an instructive role for the activity of extrusion. ΔCTCF was simulated using processivity 200 kb, separation 200 kb, and boundary strength 0.9. (D) For ΔWapl, our simulations predict the emergence of additional peaks, including at further genomic separations, as well as an extension of the shoulder in P(s). ΔWapl was simulated using processivity 1 Mb, separation 150 kb, and boundary strength 0.995.
Figure 3.
Figure 3.
Experimental phenotypes are consistent with predictions from loop extrusion simulations. (Top row) Unperturbed experimental Hi-C maps, replotted from indicated studies (see Supplemental Methods; also see interactive HiGlass displays, http://mirnylab.mit.edu/projects/emerging-evidence-for-loop-extrusion). (Middle row) Hi-C maps for indicated perturbations. (Bottom row) P(s) for indicated perturbation compared to unperturbed P(s) normalized to contact frequency at 10 kb. (A) Schwarzer et al. (2017) used tissue-specific CRE-inducible gene deletion in mouse liver cells to deplete Nipbl. (B) Nora et al. (2017) used an auxin-inducible degron system to deplete CTCF in mESCs. (C) Haarhuis et al. (2017) deleted Wapl in the Hap1 haploid human cell line, via CRISPR.
Figure 4.
Figure 4.
(A) Walking as a possible mechanism of SMC translocation, with SMC arms in yellow and orange and kleisin in blue, creating a shackled walker. (B) Walking along a chromatin fiber, by hopping from linker to linker without disrupting nucleosomal DNA. (C) Benefit of topological entrapment: An SMC walker without a kleisin can step from one chromatin strand (gray) to another in its vicinity (black), whereas a shackled SMC walker with a kleisin is able to track in cis over long distances. (D) Two possible mechanisms for converting translocation to extrusion: The first involves a single translocating motor attached to an anchor, leading to single-sided extrusion; the second involves two motors translocating in opposite directions, leading to two-sided extrusion. (E) Possible realizations of motor activity by SMCs (i–iii). (i) A single SMC acting as single motor that switches between entrapped chromatin strands, effectively performing two-sided extrusion; (ii) dimerized SMCs performing two-sided extrusion; (iii) alternatively dimerized SMCs performing two-sided extrusion.
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