Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell transcriptomic profiling of the aging mouse brain

ABSTRACT: Single-cell transcriptomic profiling of the aging mouse brain

PROVIDER: PRJNA532831 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR8895030.fastq.gz	Fastqsanger.gz
	SRR8895031.fastq.gz	Fastqsanger.gz
	SRR8895032.fastq.gz	Fastqsanger.gz
	SRR8895023.fastq.gz	Fastqsanger.gz
	SRR8895033.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 16

Similar Datasets

Single-cell transcriptomic profiling of the aging mouse brain

Project description:The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand–receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.

2019-07-01 | GSE129788 | GEO

Spatial transcriptomic profiling of the aging mouse brain [spatial scRNA-seq]

Project description:The mammalian brain can be divided into distinct structural and functional regions to perform a variety of diverse functions, but during normal aging, exactly how each region is affected, and the information interaction changes between different regions, remains largely unknown. To gain a better insight into these processes, here we generate a single-cell spatial transcriptomic (ST) atlas of young and old mice brains involving cerebrum, brain stem and fiber tracts regions. Based on the unbiased classification of spatial molecular atlas, 27 distinguished brain spatial domains were obtained, which are similar to known anatomical regions, but slightly different. Through differential expression analysis and gene set enrichment analysis (GSEA), we identified aging-related genes and pathways that vary in a coordinated or opposite manner across regions. Combined with single-cell transcriptomic data, we characterized the spatial distribution of cell types, identified an up-regulated gene Ifi27 across regions and cell types in VIS region. Through ligand-receptor interaction analysis, we identified all possible information interaction changes between regions with aging. In summary, we establish a brain spatial molecular atlas (accessible online at https:) to provide a rich resource of spatially differentially expressed genes and information interaction, which may help to understand aging and provide novel insights into the molecular mechanism of brain aging.

2024-02-20 | GSE193107 | GEO

Transcriptomic signatures of the aging brain at single-cell resolution

Project description:Transcriptomic signatures of the aging brain at single-cell resolution

| PRJNA742781 | ENA

Single-cell Genomic and Transcriptomic Analysis of the Aging Human Brain

Project description:Single-cell Genomic and Transcriptomic Analysis of the Aging Human Brain

| PRJNA1028776 | ENA

Spatial transcriptomic profiling of the aging mouse brain [spatial scRNA-seq]

Project description:Spatial transcriptomic profiling of the aging mouse brain [spatial scRNA-seq]

| PRJNA794837 | ENA

Single-cell transcriptome analysis of aging brain

Project description:Single-cell transcriptome analysis of aging brain

| PRJNA717176 | ENA

A single-cell transcriptomic atlas of mouse pituitary aging

Project description:Aging is a multifactorial process with significant functional alterations of the human body including endocrinal systems which control the whole-body physiology and metabolism. In this vein, aging-induced decline of endocrine function are associated with multiple physiological and metabolic diseases. However, aging-associated molecular shifts in the pituitary gland, the central organ of the endocrine system, have not been dissected systemically. In this study, we conducted single-cell transcriptomic analysis of the anterior pituitary gland by comparing old and young male mice. Single-cell transcriptomics not only increased the resolution for clustering of various cell types in the pituitary gland, but also enabled detailed analysis of differential expression and intercellular communication caused by aging. In summary, our study constructed the first single-cell transcriptomic atlas of pituitary aging and identified associated features of in a single-cell level, providing resources to develop novel potential therapeutic targets for aging-associated endocrine dysfunction.

2023-09-08 | GSE242296 | GEO

Transcriptomic signatures of the aging brain at single-cell resolution

Project description:Aging is a major risk factor for neurodegenerative diseases that impose tremendous burdens on people and societies today. To understand trajectories of neurological aging in a primate, we generated one of the most comprehensive brain transcriptional datasets to date in a unique population of naturalistic, behaviorally phenotyped rhesus macaques. In this experiment, we generated 71,863 single-nucleus RNA-seq transcriptomes from the dorsolateral prefrontal cortex of 24 adult females spanning all ages. We find that, of all tested cell classes, oligodendrocytes were the only cell type to significantly increase in proportion with age. We also identify hundreds of genes that change significantly with age in one or more cell types, providing a valuable window into cell-type-specific aging in the prefrontal cortex. Our findings lend insight into biological mechanisms underlying brain aging and indicate promising directions for improving neurological health.

2022-09-26 | GSE179236 | GEO

A single-cell transcriptomic atlas of mouse pituitary aging

Project description:A single-cell transcriptomic atlas of mouse pituitary aging

| PRJNA1013052 | ENA

Heterochronic parabiosis reprograms the mouse brain transcriptome by shifting aging signatures in multiple cell types

Project description:Aging is a complex process involving transcriptomic changes associated with deterioration across multiple tissues and organs, including the brain. Recent studies using heterochronic parabiosis have shown that various aspects of aging-associated decline are modifiable or even reversible. To better understand how this occurs, we performed single-cell transcriptomic profiling of young and old mouse brains following parabiosis. For each cell type, we catalogued alterations in gene expression, molecular pathways, transcriptional networks, ligand-receptor interactions, and senescence status. Our analyses identified gene signatures demonstrating that heterochronic parabiosis regulates several hallmarks of aging in a cell-type-specific manner. Brain endothelial cells were found to be especially malleable to this intervention, exhibiting dynamic transcriptional changes that affect vascular structure and function. These findings suggest novel strategies for slowing deterioration and driving regeneration in the aging brain through approaches that do not rely on disease-specific mechanisms or actions of individual circulating factors.

2023-01-14 | GSE222510 | GEO

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