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Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration [Cut&Tag]

ABSTRACT: Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration [Cut&Tag]

PROVIDER: PRJNA891666 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR21944914_1.fastq.gz	Fastqsanger.gz
	SRR21944914_2.fastq.gz	Fastqsanger.gz
	SRR21944915_1.fastq.gz	Fastqsanger.gz
	SRR21944915_2.fastq.gz	Fastqsanger.gz
	SRR21944916_1.fastq.gz	Fastqsanger.gz

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Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration

Project description:Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration

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Single Cell Epigenome Profiling of Cardiac Non-myocyte

Project description:The mammalian heart is composed of a variety types of cells that can be roughly categorized into cardiomyocytes and non-myocytes. Instead of being bystanders of cardiac function, cardiac non-myocytes provide critical structural, mechanical and electrophysiological support to the working myocardium. However, the precise cellular identity and molecular features of the non-myocytes at single cell level remain elusive. Depiction of epigenetic landscape with transcriptomic signatures using the latest single cell multi-omics has the potential to unravel the molecular programs of cardiac non-myocytes underlying their cellular diversity. To characterize the molecular and cellular features of cardiac non-myocytes populations in the adult murine heart at single cell level. We applied single cell Assay for Transposase Aaccessible Chromatin using sequencing (scATAC-seq) in combination with high-throughput single cell RNA-seq (scRNA-seq) to map the epigenetic landscape and gene expression program of cardiac non-myocytes from adult murine heart. Through integrated dual-omics data analysis, we categorize the cardiac non-myocytes into 4 defined populations including endothelial cells, fibroblast, pericytes and immune cells with distinct chromatin accessibility patterns. Cis- and trans-regulatory factors for each cell type were identified. In particular, unbiased sub-clustering and functional annotation of the cardiac fibroblast (FB), indicated the heterogeneity and functionality of FB subtypes associated with cellular response, cytoskeleton organization and immune regulation. We further validated the expression and function of novel markers in major FB sub-populations and experimentally determined the distribution of the FB sub-populations in healthy and injured murine heart. In summary, we comprehensively characterized the non-myocyte cellular identity at the single-cell level and defined FB subpopulations by their functional states.

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Single Cell Transcriptome Profiling of Cardiac Non-myocyte

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Fibronectin Induced Cardiac Myocyte Hypertrophy

Project description:Gene expression changes in neonatal rat ventricular myocytes plated in fibronectin (2 samples) or uncoated plates (2 samples). Keywords = Hypertrophy Cardiac Myocyte Fibronectin Keywords: repeat sample

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Mapping the cellular and molecular landscape of cardiac non-myocytes in murine type-2 diabetes

Project description:Here we define key single-cell transcriptional alterations within cardiac non-myocytes, from ventricles of spontaneously type-2 diabetic (db/db) and control (db/h) mouse hearts ([B6.BKS(D)-Lepr<db>/J], stock #000697). The cell preparation sequenced consisted of metabolically active, live and nucleated non-myocyte cells, which were depleted of endothelial cells. The objective of this experiment was to develop a framework for understanding the dynamics of cardiac cell networks in murine type-2 diabetes, as a resource for future mechanistic studies.

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