Nucleosome dynamics and maintenance of epigenetic states of CpG islands

Sneppen, Kim; Dodd, Ian B.

doi:10.1103/physreve.93.062417

Cited by 14 publications

(7 citation statements)

References 54 publications

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“…The copyright holder for this preprint this version posted January 1, 2021. ; https://doi.org/10.1101/2020.12.30.424823 doi: bioRxiv preprint mathematical form does not change on time intervals of different lengths (self-similarity). The emergence of temporal scale-invariance and scaling behaviour are hallmarks of collective, selforganisation processes (26), suggesting that DNA methylation marks are established via a collective mechanism involving interacting DNMT3 enzyme molecules (27,28). Importantly, if such interactions involve different genomic loci they might lead to the spatial coordination of de novo methylation (26).…”

Section: De Novo Dna Methylation Is a Collective Phenomenon Involving Spatial Coordination Across Extended Genomic Domainsmentioning

confidence: 99%

Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback betweende novoDNA methylation and chromatin condensates

Olmeda

Lohoff

Clark

et al. 2021

Preprint

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SummaryRecent breakthroughs in single-cell genomics allow probing molecular states of cells with unprecedented detail along the sequence of the DNA. Biological function relies, however, on emergent processes in the three-dimensional space of the nucleus, such as droplet formation through phase separation. Here, we use single-cell multi-omics sequencing to develop a theoretical framework to rigorously map epigenome profiling along the DNA sequence onto a description of the emergent spatial dynamics in the nucleus. Drawing on scNMT-seq multi-omics sequencing in vitro and in vivo we exemplify our approach in the context of exit from pluripotency and global de novo methylation of the genome. We show how DNA methylation patterns of the embryonic genome are established through the interplay between spatially correlated DNA methylation and topological changes to the DNA. This feedback leads to the predicted formation of 30-40nm sized condensates of methylated DNA and determines genome-scale DNA methylation rates. We verify these findings with orthogonal single cell multi-omics data that combine the methylome with HiC measurements. Notably, this scale of chromatin organization has recently been described by super-resolution microscopy. Using this framework, we identify local methylation correlations in gene bodies that precede transcriptional changes at the exit from pluripotency. Our work provides a general framework of how mechanistic insights into emergent processes underlying cell fate decisions can be gained by the combination of single-cell multi-omics and methods from theoretical physics that have not been applied in the context of genomics before.HighlightsWe develop methodology to infer collective spatio-temporal processes in the physical space of the nucleus from single-cell methylome sequencing experiments.We show that DNA methylation relies on a feedback between de novo methylation and nanoscale changes in DNA topology, leading to the formation of methylation condensates.Chromatin condensates at this scale have recently been described by high-resolution microscopy but have remained without mechanistic explanation.Using this framework, we identify changes in the distribution of DNA methylation marks in gene bodies that precede gene silencing at the exit from pluripotency.

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Section: De Novo Dna Methylation Is a Collective Phenomenon Involving Spatial Coordination Across Extended Genomic Domainsmentioning

confidence: 99%

Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback betweende novoDNA methylation and chromatin condensates

Olmeda

Lohoff

Clark

et al. 2021

Preprint

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“…The determination of epigenetic regulatory mechanisms has triggered an interest in developing mathematical models regarding both epigenetic regulation (ER) of gene expression [27, 33, 34, 41-43, 45, 50-53] and epigenetic memory [50][51][52][54][55][56][57][58].…”

Section: Introductionmentioning

confidence: 99%

Bivalent chromatin as a therapeutic target in cancer: Anin silicopredictive approach for combining epigenetic drugs

Alarcón

Sardanyés

Guillamón

et al. 2020

Preprint

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Tumour cell heterogeneity is a major barrier for efficient design of targeted anti-cancer therapies. A diverse distribution of phenotypically distinct tumour-cell subpopulations prior to drug treatment predisposes to non-uniform responses, leading to the elimination of sensitive cancer cells whilst leaving resistant subpopulations unharmed. Few strategies have been proposed for quantifying the variability associated to individual cancer-cell heterogeneity and minimizing its undesirable impact on clinical outcomes. Here, we report a computational approach that allows the rational design of combinatorial therapies involving epigenetic drugs against chromatin modifiers. We have formulated a stochastic model of a bivalent transcription factor that allows us to characterise three different qualitative behaviours, namely: bistable, high- and low-gene expression. Comparison between analytical results and experimental data determined that the so-called bistable and high-gene expression behaviours can be identified with undifferentiated and differentiated cell types, respectively. Since undifferentiated cells with an aberrant self-renewing potential might exhibit a cancer/metastasis-initiating phenotype, we analysed the efficiency of combining epigenetic drugs against the background of heterogeneity within the bistable sub-ensemble. Whereas single-targeted approaches mostly failed to circumvent the therapeutic problems represented by tumour heterogeneity, combinatorial strategies fared much better. Specifically, the more successful combinations were predicted to involve modulators of the histone H3K4 and H3K27 demethylases KDM5 and KDM6A/UTX. Those strategies involving the H3K4 and H3K27 methyltransferases MLL2 and EZH2, however, were predicted to be less effective. Our theoretical framework provides a coherent basis for the development of an in-silico platform capable of identifying the epigenetic drugs combinations best-suited to therapeutically manage non-uniform responses of heterogenous cancer cell populations.

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“…By switching on or off different parts of the genome, ER is in fact responsible for the variety of phenotypes in complex multicellular organisms (where all somatic cells are genetically identical). Recent advances in experimental determination of ER mechanisms have triggered an ever-growing interest in developing mathematical models regarding both ER of gene expression [11–16] and epigenetic memory [12–14, 17–20]. Identification of the molecular culprits underlying the ER capacity to drive the transition between normal and highly restrictive/permissive chromatin states is expected to have major impact in the understanding and therapeutic management of ageing-related diseases including cancer [7, 21, 22].…”

Section: Introductionmentioning

confidence: 99%

A multiscale model of epigenetic heterogeneity-driven cell fate decision-making

et al. 2019

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The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer.

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Nucleosome dynamics and maintenance of epigenetic states of CpG islands

Cited by 14 publications

References 54 publications

Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback betweende novoDNA methylation and chromatin condensates

Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback betweende novoDNA methylation and chromatin condensates

Bivalent chromatin as a therapeutic target in cancer: Anin silicopredictive approach for combining epigenetic drugs

A multiscale model of epigenetic heterogeneity-driven cell fate decision-making

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