A Predictive Computational Model of the Dynamic 3D Interphase Yeast Nucleus

Wong, Hua; Marie-Nelly, Hervé; Herbert, Sébastien; Carrivain, Pascal; Blanc, Hervé; Koszul, Romain; Fabre, Emmanuelle; Zimmer, Christophe

doi:10.1016/j.cub.2012.07.069

Cited by 152 publications

(225 citation statements)

References 49 publications

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“…This description was recently complemented by the first Hi-C comprehensive maps (Rodley et al 2009;Duan et al 2010), which confirmed an organization guided by nuclear landmarks, including TEL that congregate in foci (Gotta et al 1996;Schober et al 2008). Recent Brownian dynamics (BD) simulations confirmed this structural model by recapitulating Hi-C and imaging data, assuming that physical tethering at TEL and CEN and volume exclusion were driving chromosome conformations (Tjong et al 2012;Wong et al 2012).…”

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confidence: 65%

High-throughput chromatin motion tracking in living yeast reveals the flexibility of the fiber throughout the genome

et al. 2013

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Chromosome dynamics are recognized to be intimately linked to genomic transactions, yet the physical principles governing spatial fluctuations of chromatin are still a matter of debate. Using high-throughput single-particle tracking, we recorded the movements of nine fluorescently labeled chromosome loci located on chromosomes III, IV, XII, and XIV of Saccharomyces cerevisiae over an extended temporal range spanning more than four orders of magnitude (10 -2 -10 3 sec). Spatial fluctuations appear to be characterized by an anomalous diffusive behavior, which is homogeneous in the time domain, for all sites analyzed. We show that this response is consistent with the Rouse polymer model, and we confirm the relevance of the model with Brownian dynamics simulations and the analysis of the statistical properties of the trajectories. Moreover, the analysis of the amplitude of fluctuations by the Rouse model shows that yeast chromatin is highly flexible, its persistence length being qualitatively estimated to <30 nm. Finally, we show that the Rouse model is also relevant to analyze chromosome motion in mutant cells depleted of proteins that bind to or assemble chromatin, and suggest that it provides a consistent framework to study chromatin dynamics. We discuss the implications of our findings for yeast genome architecture and for target search mechanisms in the nucleus.

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confidence: 65%

High-throughput chromatin motion tracking in living yeast reveals the flexibility of the fiber throughout the genome

et al. 2013

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“…These observations indicate that centromere clustering can shape the interphase genome architecture by imposing strong geometrical constraints on chromosome positioning. Notably, in other organisms, such as yeasts (6,44,(49)(50)(51)(52) and Drosophila melanogaster (8,9), centromere clustering plays a prominent role in shaping the interphase genome structures. A model based on interchromosomal interactions formed by only subcentromeric regions suffices to reproduce the correct radial positions of all chromosomes.…”

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confidence: 99%

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Tjong

Kalhor

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization. (14), and single-cell (15) and in situ Hi-C (16)], close chromatin contacts can now be identified at increasing resolution, providing new insight into genome organization. These methods measure the relative frequencies of chromosome interactions averaged over a large population of cells. However, individual 3D genome structures can vary dramatically from cell to cell even within an isogenic sample, especially with respect to long-range interactions (15,17,18). This structural variability poses a great challenge to the interpretation of ensemble-averaged Hi-C data (14,(19)(20)(21)(22)(23) and prevents the direct detection of cooperative interactions co-occurring in the same cell. This problem is particularly evident for long-range (cis) and interchromosomal (trans) interactions, which are generally observed at relatively low frequencies and are therefore present only in a small subset of individual cells at any given time (3,11,15). Despite their low frequencies, long-range and interchromosome interaction patterns are not random noise. In fact, these interactions are more informative than short-range interactions in determining the global genome architectures in cells and are often functionally relevant-interactions between transcriptionally active regions are often interchromosomal in nature (14). Owing to their variable nature, long-range and trans interactions can be part of alternative, structurally different conformations, which makes their interpretation in form of consensus structures impossible. However, inferring which of the long-range interactions co-occur in the same cell from ensemble Hi-C data remains a major challenge.These challenges cannot be easily overcome even by the new single-cell Hi-C techno...

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“…c . This explains the intrachromosomal contact frequency P (s) ∼ s −1.5 for yeast genome, pointing to an equilibrium globule [8,[37][38][39].…”

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“…Dynamical implication of our finding φ bac φ yeast < φ ∞ c φ human < φ virus , and the correlations of φ yeast < φ ∞ c with P (s) ∼ s −1.5 for budding yeast [37] and φ ∞ c φ human with P (s) ∼ s −1 for mature human cells [9] provide a new framework for understanding the origin of qualitatively distinct chromosome organization in various organisms and cell types. Given that cellular environment is replete with crowding particles, the volume fractions estimated here for different organisms may well be only lower bounds, and thus we expect that glassy dynamics is prevalent especially in higher-order organisms.…”

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Confinement-Induced Glassy Dynamics in a Model for Chromosome Organization

et al. 2015

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Recent experiments showing scaling of the intrachromosomal contact probability, P (s) ∼ s −1 with the genomic distance s, are interpreted to mean a self-similar fractal-like chromosome organization. However, scaling of P (s) varies across organisms, requiring an explanation. We illustrate dynamical arrest in a highly confined space as a discriminating marker for genome organization, by modeling chromosome inside a nucleus as a homopolymer confined to a sphere of varying sizes. Brownian dynamics simulations show that the chain dynamics slows down as the polymer volume fraction (φ) inside the confinement approaches a critical value φc. The universal value of φ ∞ c ≈ 0.44 for a sufficiently long polymer (N 1) allows us to discuss genome dynamics using φ as a single parameter. Our study shows that the onset of glassy dynamics is the reason for the segregated chromosome organization in human (N ≈ 3 × 10 9 , φ φ ∞ c ), whereas chromosomes of budding yeast (N ≈ 10 8 , φ < φ ∞ c ) are equilibrated with no clear signature of such organization.

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A Predictive Computational Model of the Dynamic 3D Interphase Yeast Nucleus

Cited by 152 publications

References 49 publications

High-throughput chromatin motion tracking in living yeast reveals the flexibility of the fiber throughout the genome

High-throughput chromatin motion tracking in living yeast reveals the flexibility of the fiber throughout the genome

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Confinement-Induced Glassy Dynamics in a Model for Chromosome Organization

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