Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations.

ABSTRACT: Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations.

PROVIDER: PRJNA934285 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR23438400_1.fastq.gz	Fastqsanger.gz
	SRR23438400_2.fastq.gz	Fastqsanger.gz
	SRR23438401_1.fastq.gz	Fastqsanger.gz
	SRR23438401_2.fastq.gz	Fastqsanger.gz
	SRR23438402_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 68

Similar Datasets

Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations [scATAC-seq]

Project description:Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations [scATAC-seq]

| PRJNA934479 | ENA

Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations [scRNA-seq]

Project description:Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations [scRNA-seq]

| PRJNA934478 | ENA

Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations [scATAC-seq]

Project description:Innate lymphoid cells (ILCs) are highly plastic immune cells that have been separated into 3 main subsets, characterized by distinct phenotypic and functional profiles. Using single cell approaches, heightened heterogeneity of mouse ILCs has been recently appreciated, imprinted by tissue signals that shape their transcriptome and epigenome. Intra-subset diversity has also been observed in human ILCs. However, combined transcriptomic and epigenetic analyses of single ILCs in humans are lacking. Here we show high transcriptional and epigenetic heterogeneity among human circulating ILCs in healthy individuals. We describe phenotypically distinct subclusters within main circulating ILC populations. We show diverse chromatin accessibility within main ILC subsets, compatible with differentially poised states. We validate the use of this healthy donor-based analysis as resource dataset to infer ILC changes occurring in disease conditions. Overall, our work provides new insights in the complex human ILC biology. We anticipate our work to be a starting point to facilitate hypothesis-driven studies in patients, without the need to perform single cell OMICs using precious patients’ material

2023-09-01 | GSE225167 | GEO

Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations [scRNA-seq]

2023-09-01 | GSE225168 | GEO

Dynamic single-cell regulomes characterize human peripheral blood ILC subpopulations.

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

2023-09-01 | GSE225169 | GEO

Dynamic single-cell regulomes characterize human peripheral blood innate lymphoid cell subpopulations.

Project description:Innate lymphoid cells (ILCs) are plastic immune cells divided into 3 main subsets, characterized by distinct phenotypic and functional profiles. Using single cell approaches, heightened heterogeneity of mouse ILCs has been appreciated, imprinted by tissue signals that shape their transcriptome and epigenome. Intra-subset diversity has also been observed in human ILCs. However, combined transcriptomic and epigenetic analyses of single ILCs in humans are lacking. Here, we show high transcriptional and epigenetic heterogeneity among human circulating ILCs in healthy individuals. We describe phenotypically distinct subclusters and diverse chromatin accessibility within main ILC populations, compatible with differentially poised states. We validate the use of this healthy donor-based analysis as resource dataset to help inferring ILC changes occurring in disease conditions. Overall, our work provides insights in the complex human ILC biology. We anticipate it to facilitate hypothesis-driven studies in patients, without the need to perform single cell OMICs using precious patients' material.

| S-EPMC10483052 | biostudies-literature

Dynamic chromatin structure during early ILC progenitor differentiation

Project description:To characterize the epigenomes during early ILC progenitor differentiation, we did DNase-seq, CUT&RUN and scMNase-seq assays in all-lymphoid progenitor (ALP), early innate lymphoid progenitor (EILP), and innate lymphoid cell progenitor (ILCP) cells.

2019-05-30 | GSE128483 | GEO

Systemic human ILC precursors provide a substrate for tissue ILC differentiation

Project description:Innate lymphoid cells (ILC) represent innate versions of T helper and cytotoxic T cells that differentiate from committed ILC precursors (ILCP). Still, how ILCP relate to mature tissue-resident ILCs remains unclear. We observed that a population of CD117+ ILC from peripheral blood (PB) of healthy donors does not represent any conical ILC subset, but expressed marker (CD117) commonly expressed by hemato-lymphoid progenitors. We therefore hypothesized PB CD117+ ILC might include uncommitted lymphoid precursors. In order to further understand the identity of PB CD117+ ILC, we profiled the transcriptome of highly purified circulating CD117+ ILC compared to CD34+ HSC, the latter representing immature hematopoietic progenitors with multi-lineage potential. Clear differences in gene expression profiles emerged, with a large cluster of 1540 genes expressed at substantially higher levels in CD117+ ILC. In contrast, CD34+ HSC cells highly expressed genes involved in the broad development of diverse hematopoietic lineages. Compared to HSC, CD117+ ILC express high levels of TF that have been shown to be essential for murine ILC development and we did not detect transcripts characteristic of T and B cells development. Transcriptomic analysis suggested that CD117+ ILC represent lymphoid-biased progenitors carrying a TF expression profile resembling a multi-potent ILC precursor (ILCP).

2017-03-19 | GSE90834 | GEO

A lineage commitment checkpoint in early ILC development [bulk RNA-seq]

Project description:Understanding how cellular function is imprinted during development requires the identification of factors controlling lineage specification and commitment, and the intermediate progenitors in which they act. Using population level and single cell approaches, we examine transcriptional and functional heterogeneity within early innate lymphoid cells (ILC) progenitors. We identify a developmental bifurcation toward dendritic cell fate that reveals the uncommitted state of early specified ILC progenitors. We subsequently characterize an ILC-commitment checkpoint controlled by the transcription factor TCF-1. The present study reveals unexpected heterogeneity within early innate progenitor populations, and characterizes lineage infidelity that accompanies early ILC specification prior to commitment.

2019-04-22 | GSE113765 | GEO

Developmental Acquisition of Regulomes Underlies Innate Lymphoid Cell Functionality

Project description:Innate lymphoid cells (ILCs) play key roles in host defense, barrier integrity, and homeostasis, and they mirror adaptive CD4+ T helper (Th) cell subtypes in both usages of effector molecules and transcription factors. To better understand ILC subsets and their relationship with Th cells, we measured genome-wide chromatin accessibility. We found that chromatin in proximity to effector genes was selectively accessible in ILCs prior to high-level transcription upon activation. Accessibility of these regions was acquired in a stepwise manner during development and changed little after in vitro or in vivo activation. Conversely, dramatic chromatin remodeling occurred in naïve CD4+ T cells during Th cell differentiation using a type 2-infection model. This alteration results in a substantial convergence of Th2 cells toward ILC2 regulomes. Our data indicate extensive sharing of regulatory circuitry across the innate and adaptive compartments of the immune system, in spite of their divergent developing pathways.

2016-05-05 | GSE77695 | 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