Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes (scATAC-Seq)

ABSTRACT: Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes (scATAC-Seq)

PROVIDER: PRJNA1163381 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR30751678_1.fastq.gz	Fastqsanger.gz
	SRR30751678_2.fastq.gz	Fastqsanger.gz
	SRR30751679_1.fastq.gz	Fastqsanger.gz
	SRR30751679_2.fastq.gz	Fastqsanger.gz
	SRR30751680_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes (scATAC-Seq)

Project description:(scRNA and scATAC) in profiling non-myocytes (non-CMs) from young, middle-aged, and elderly mice. Non-CMs, vital in heart development, physiology, and pathology, are understudied compared to cardiomyocytes. Our analysis revealed aging response heterogeneity and its dynamics over time among non-CM cell types. Immune cells, notably macrophages and neutrophils, showed significant aging alterations, while endothelial cells displayed moderate changes. We identified distinct aging signatures within the cell type, including differential gene expression and transcription factor activity, along with motif variation. Sub-cluster analysis revealed intra-cell type heterogeneity, characterized by diverse aging patterns. The senescence-associated secretory phenotype (SASP) emerged as a key aging-related phenotype. Moreover, aging significantly influenced cell-cell communication, especially impacting a fibroblast sub-cluster with high expression of Erbb4. This study elucidates the complex cellular and molecular landscape of cardiac aging in non-CMs, highlighting their importance in cardiac aging and offering guidance for future potential therapeutic avenues to treat aging-related heart diseases.

2024-11-01 | GSE277701 | GEO

Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes

Project description:Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes

| PRJNA1163378 | ENA

Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes (scRNA-Seq)

Project description:Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes (scRNA-Seq)

| PRJNA1163382 | ENA

Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes (scRNA-Seq)

2024-11-01 | GSE277700 | GEO

Decoding aging in the heart via single cell dual omics of non-cardiomyocytes.

Project description:To understand heart aging at the single-cell level, we employed single-cell dual omics (scRNA-seq and scATAC-seq) in profiling non-myocytes (non-CMs) from young, middle-aged, and elderly mice. Non-CMs, vital in heart development, physiology, and pathology, are understudied compared to cardiomyocytes. Our analysis revealed aging response heterogeneity and its dynamics over time. Immune cells, notably macrophages and neutrophils, showed significant aging alterations, while endothelial cells displayed moderate changes. We identified distinct aging signatures within the cell type, including differential gene expression, transcription factor activity, and motif variation. Sub-cluster analysis revealed intra-cell type heterogeneity, characterized by diverse aging patterns. The senescence-associated secretory phenotype emerged as a key aging-related phenotype. Moreover, aging significantly influenced cell-cell communication, especially impacting a fibroblast sub-cluster with high expression of ERBB4. This study elucidates the complex cellular and molecular landscape of cardiac aging and offers guidance for potential therapeutic avenues to treat aging-related heart diseases.

| S-EPMC11681900 | biostudies-literature

Decoding Aging in the Heart via Single Cell Dual Omics of Non-Cardiomyocytes

Project description:This SuperSeries is composed of the SubSeries listed below.

2024-11-01 | GSE277702 | GEO

Decoding Trp53 regulatory program with knockout cell epigenomic landscape analyses [scATAC-seq]

Project description:Decoding Trp53 regulatory program with knockout cell epigenomic landscape analyses [scATAC-seq]

| PRJNA899904 | ENA

Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses (scATAC-seq)

Project description:Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses (scATAC-seq)

| PRJNA892987 | ENA

scATAC-seq of mouse Plasmodium-specific CD4+ T cells

Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 4, 7, and 32 to undergo processing and to generate scATAC-seq dataset. At Day 7, CXCR5+ and CXCR6+ cells were recovered separately. At Day 32, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scATAC-seq dataset was analysed to investigate epigenomic landscapes of CD4+ T cells from effector to memory states.

2020-10-14 | E-MTAB-9402 | biostudies-arrayexpress

scATAC-seq of early brain organoid development from pluripotency

Project description:To study developmental trajectories in brain organoids, we conducted scRNA-seq and scATAC-seq in parallel on a dense timecourse of early development.

2022-08-18 | E-MTAB-11998 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data