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Stochastic models of nucleosome dynamics reveal regulatory rules of stimulus-induced epigenome remodeling

ABSTRACT: Stochastic models of nucleosome dynamics reveal regulatory rules of stimulus-induced epigenome remodeling

PROVIDER: PRJNA657750 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR12465892_1.fastq.gz	Fastqsanger.gz
	SRR12465892_2.fastq.gz	Fastqsanger.gz
	SRR12465893_1.fastq.gz	Fastqsanger.gz
	SRR12465893_2.fastq.gz	Fastqsanger.gz
	SRR16844023_1.fastq.gz	Fastqsanger.gz

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Stochastic models of nucleosome dynamics reveal regulatory rules of stimulus-induced epigenome remodeling

Project description:The genomic positions of nucleosomes are a defining feature of the epigenomic state and hence of cell identity. Signal-dependent transcription factors (SDTFs), upon activation, modify the positioning of nucleosomes and cause epigenome remodeling. Here, we developed Markov models of nucleosome wrapping and unwrapping, and fit them to high resolution deep sequencing data of DNA accessibility to reveal biophysical principles of nucleosome dynamics. We found that 1) the dynamics of DNA unwrapping are significantly slower in vivo than reported from in vitro experimental data, 2) there is clear evidence for cooperativity in wrapping and unwrapping, 3) SDTF activity produced highest eviction probability when its binding site is close to but not on top of the nucleosome dyad, and 4) oscillatory SDTFs produce more variability than constant SDTF activities. Our work uncovers the regulatory rules governing nucleosome dynamics in vivo, which can predict epigenomic alterations during inflammation at single nucleosome resolution.

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Stochastic models of nucleosome dynamics reveal regulatory rules of stimulus-induced epigenome remodeling.

Project description:The genomic positions of nucleosomes are a defining feature of the cell's epigenomic state, but signal-dependent transcription factors (SDTFs), upon activation, bind to specific genomic locations and modify nucleosome positioning. Here we leverage SDTFs as perturbation probes to learn about nucleosome dynamics in living cells. We develop Markov models of nucleosome dynamics and fit them to time course sequencing data of DNA accessibility. We find that (1) the dynamics of DNA unwrapping are significantly slower in cells than reported from cell-free experiments, (2) only models with cooperativity in wrapping and unwrapping fit the available data, (3) SDTF activity produces the highest eviction probability when its binding site is adjacent to but not on the nucleosome dyad, and (4) oscillatory SDTF activity results in high location variability. Our work uncovers the regulatory rules governing SDTF-induced nucleosome dynamics in live cells, which can predict chromatin accessibility alterations during inflammation at single-nucleosome resolution.

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Epigenome wide Association and Stochastic Epigenetic Mutation analysis on cord blood of preterm birth.

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Project description:Sequence-to-function neural networks learn cis-regulatory sequence rules driving many types of genomic data. Interpreting these models to relate the sequence rules to underlying biological processes remains challenging, especially for complex genomic readouts such as MNase-seq, which maps nucleosome occupancy but is confounded by experimental bias. We introduce pairwise influence by sequence attribution (PISA), an interpretation tool that combinatorially decodes which bases contributed to the readout at a specific genomic coordinate. PISA visualizes the effects of transcription factor motifs, detects undiscovered motifs with complex contribution patterns, and reveals experimental biases. By learning the bias for MNase-seq, PISA enables unprecedented nucleosome prediction models, allowing the \emph{de novo} discovery of nucleosome-positioning motifs and their long-range chromatin effects, as well as the design of sequences with altered nucleosome configurations. These results show that PISA is a versatile tool that expands our ability to train and interpret sequence-to-function neural networks on genomics data and understand the underlying cis-regulatory code.

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Comprehensive nucleosome interactome screen establishes fundamental principles of nucleosome binding

Project description:Nuclear proteins bind chromatin to execute and regulate genome-templated processes. While structural and biochemical studies of individual nucleosome interactions have suggested that an acidic patch on the nucleosome disk surface may be a common site for recruitment to chromatin, the pervasiveness of acidic patch binding and whether other nucleosome surface binding hot-spots exist remains unclear. Here, we use nucleosome affinity proteomics with a library of nucleosomes that collectively disrupts all exposed histone surfaces to establish the universal principles of nucleosome binding. We find that the acidic patch and two adjacent surfaces are the primary hot-spots for nucleosome disk binding and are critical for the majority of nucleosome-protein interactions. In contrast, nearly half of the nucleosome disk surface participates only minimally in protein binding. In addition to establishing the fundamental principles of chromatin binding, our screen defines nucleosome surface requirements of nearly 300 nucleosome interacting proteins implicated in diverse nuclear processes including transcription, DNA damage repair, cell cycle regulation, and nuclear architecture. Building from our screen, we demonstrate that the Anaphase-Promoting Complex/Cyclosome directly binds the acidic patch and elucidate a redundant charge-based mechanism of acidic patch binding by nuclear pore protein ELYS. Overall, our interactome screen illuminates a highly competitive nucleosome binding hub for chromatin-targeted activities and curates a list of nucleosome interacting proteins that will enable mechanistic exploration of many unexpected chromatin-templated nuclear processes.

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