Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets(scRNASeq)

ABSTRACT: Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets(scRNASeq)

PROVIDER: PRJNA802837 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets

Project description:Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets

| PRJNA801114 | ENA

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets

Project description:Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets

| PRJNA982855 | ENA

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets(scATACSeq)

Project description:Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets(scATACSeq)

| PRJNA800439 | ENA

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets(scRNASeq)

Project description:The functional heterogeneity of β-cells is important for metabolism and diseases, but the nature and mechanism of such variation at molecular level remain elusive. Here we explore this question by comparing both single cell RNA-seq and single cell ATAC-seq maps of healthy and type II diabetic (T2D) human islets. We dissect the T2D-associated single cell trajectory and identified signature genes and enhancers in β-cells. We also map the 3D genome of both α- and β-cells with low-input eHi-C approach to unravel the cell type-specific gene regulatory circuits. Strikingly, more than one third of the T2D signature genes show significant intra-donor heterogeneity at single cell level; these genes are functionally distinct from other signature genes that are largely invariant among cells from the same individual but differentially expressed between donors, suggesting different roles in T2D pathogenesis. Importantly, we identified consistent intra-donor variations at both transcriptomic and epigenomic levels, which strongly support the heterogenous β-cell states and transcription programs. Finally, we construct the disease-signature regulatory networks and pinpointed HNF1A as one of the top transcription factors governing T2D-associated β-cell heterogeneity. Taken together, we provide the first multi-omic characterization of β-cell heterogeneity and reveals its connection to T2D.

2023-08-09 | GSE195986 | GEO

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets (Hi-C)

Project description:Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets (Hi-C)

| PRJNA801119 | ENA

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets

2023-08-10 | GSE234754 | GEO

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets(scATACSeq)

2023-08-09 | GSE194401 | GEO

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets (Hi-C)

2023-08-09 | GSE195522 | GEO

Single cell multi-omics analysis deconstructs diabetes-associated β-cell heterogeneity in human islets

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

2023-08-09 | GSE195523 | GEO

Human Pluripotent Stem Cell-derived Islets Ameliorate Diabetes in Nonhuman Primates [human_singlecell]

Project description:Pluripotent stem cell-derived islets (hPSC-islets) are a promising cell resource for diabetes treatment. Here, we demonstrate that transplantation of pluripotent stem cell-derived islets into diabetic nonprimates effectively restored endogenous insulin secretion and improved glycemic control. Single-cell RNA sequencing analysis of S6D2 clusters confirmed the existence of the three major pancreatic endocrine cell populations (β cells, α-like cells and δ-like cells) and their proportions, which altogether accounted for 80%. Importantly, hierarchical clustering of S6D2 hCiPSC-islets, 10 wpt kidney grafts and primary islets showed that the hCiPSC differentiated pancreatic endocrine cells shared similar global gene expression profiles to their native counterparts in primary islets. Single-cell RNA sequencing analysis on PBMCs revealed the potential immune response of recipient macaque to hCiPSC-islets.

2022-02-04 | GSE185036 | 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