Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell Transcriptomics Reveals the Divergent Developmental Lineage Trajectories during Human Pituitary Development

ABSTRACT: The anterior pituitary gland plays central roles in body growth, reproduction, metabolism and the stress response. In this study, we performed single-cell RNA-sequencing (scRNA-seq) of 4,113 individual cells from human fetal pituitaries. We characterized divergent developmental trajectories with distinct transitional intermediate states in five hormone-producing cell lineages. Furthermore, we characterized the cellular heterogeneity of pituitary stem cells, identifying a hybrid epithelial/mesenchymal state and an early-to-late state transition. These analyses define a single-cell resolution roadmap for human pituitary development.

ORGANISM(S): Homo sapiens

PROVIDER: GSE142653 | GEO | 2020/09/19

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Pituitary Tumors cDNA SAGE Libraries

Project description:Despite a considerable literature concerning the molecular pathogenesis of pituitary tumors, the mechanisms of pituitary tumors development and progression remain unknown. Four SAGE cDNA libraries were constructed using a pool of mRNA obtained from five GH-, two ACTH-secreting, and four non secreting pituitary tumors (NS), and three normal pituitaries from patients who had accidental death, using I-SAGE kit (Invitrogen). The aim of this study was to evaluate the differential gene expression profile by SAGE genes in different subtypes of pituitary tumors to contribute for understanding of pituitary tumorigenesis. Comparative analysis of gene expression profiles in subtypes of pituitary tumores.

2014-04-10 | E-GEOD-37153 | biostudies-arrayexpress

Pituitary Tumors cDNA SAGE Libraries

2014-04-10 | GSE37153 | GEO

Single-cell Transcriptomics Reveals the Divergent Developmental Lineage Trajectories during Human Pituitary Development

Project description:Single-cell Transcriptomics Reveals the Divergent Developmental Lineage Trajectories during Human Pituitary Development

| PRJNA597874 | ENA

Primary cilia are required for cell-type determination and angiogenesis in the pituitary development

Project description:To understand the molecular mechanisms underlying developmental abnormalities of the pituitary in Dyrk2-/- mice, we performed comprehensive whole-genome RNA sequencing of the pituitaries of wild-type and Dyrk2-/- mice at E12.5

2024-08-01 | GSE267748 | GEO

Analysis of chromatin accessibility in adult mouse pituitary using single-cell ATAC-seq

Project description:To gain insight into patterns of chromatin accessibility in distinct cell subtypes of mouse pituitary, pituitaries from two adult mice were collected and subjected to single-cell ATAC-seq analysis using 10X Genomics platform

2021-02-03 | GSE158070 | GEO

Divergent clonal differentiation trajectories of T cell exhaustion (scATAC-seq)

Project description:T cells activated by chronic antigen exposure in the setting of viral infections or cancer can adopt an exhausted T cell (TEx) state, characterized by reduced effector function and proliferative capacity, and the upregulation of inhibitory receptors. Here, we generate a single-cell multi-omic atlas of T cell exhaustion in chronic viral infection that redefines the phenotypic diversity and molecular regulation of TEx states. Longitudinal analysis of the T cell response identifies an early effector phenotype that is epigenetically primed for TEx differentiation. However, clonal T cell trajectories defined using paired single-cell RNA and T cell receptor (scRNA/TCR-seq) sequencing reveal divergent differentiation trajectories among clones that recognize shared antigens, resulting in TEx- or effector memory-biased clone behaviors. Multi-organ clonal analysis reveals that T cell clone behaviors are sensitive to the tissue environment, and the liver niche preclude the development of effector memory phenotypes and induce exaggerated exhaustion. Finally, we show that divergent clonal trajectories are driven by differences in TCR affinity, and that high-affinity T cell clones preferentially adopt the divergent fate, while low-affinity clones adopt effector memory fates that are deleted in high antigen niches. These findings reveal heterogeneity in clonal T cell responses to chronic antigen and link TCR signal strength and epigenetic programming to TEx cell fates and persistence, which may be manipulated for cancer immunotherapy.

2022-07-25 | GSE188669 | GEO

Divergent clonal differentiation trajectories of T cell exhaustion (scRNA-seq)

Project description:T cells activated by chronic antigen exposure in the setting of viral infections or cancer can adopt an exhausted T cell (Tex) state, characterized by reduced effector function and proliferative capacity, and the upregulation of inhibitory receptors. However, whether all antigen-specific T cell clones follow the same molecular and cellular Tex differentiation trajectory remains unclear. Here, we generate a single-cell multi-omic atlas of T cell exhaustion that redefines the phenotypic diversity and molecular regulation of Tex phenotypes. Longitudinal analysis during chronic viral infection identifies an early effector phenotype that is epigenetically primed for Tex differentiation and two late-stage Tex cell states with either a terminal exhaustion or a killer cell lectin-like receptor (KLR)-expressing cytotoxic gene signature. We define clonal trajectories of antigen-specific T cells using paired single-cell RNA and T cell receptor sequencing and reveal distinct differentiation trajectories resulting in terminal Tex-biased, KLR Tex-biased, or divergent clones that differentiate into both phenotypes. Comparison of Tex phenotypes among shared T cell clones that traffic to multiple organs reveals that clonal differentiation trajectories are maintained across tissues. Finally, we show that differences in clonal differentiation trajectory are driven by TCR signaling avidity, whereby high-avidity T cell clones preferentially adopt a terminal Tex fate, while low-avidity clones adopt an effector-like KLR Tex fate. These findings reveal clonal heterogeneity in the T cell response to chronic antigen and genomic programs that underlie Tex fates and persistence.

2022-07-25 | GSE188666 | GEO

Neural plate progenitors give rise to both anterior and posterior pituitary cells

Project description:The pituitary is the master neuroendocrine tissue, which regulates body homeostasis. It consists of the adenohypophysis (AH), which harbors hormones producing cells and the neurohypophysis (NH), which relays the direct passage of hormones from the brain to the periphery. We previously characterized the mouse NH cell identities (Chen Q et al., 2020). However, the zebrafish NH cell types remained unknown owning to surgical inaccessible and limited amount of the tissue. Using Mars-Seq single-cell sequencing (Jaitin et al., 2014), we characterized the cell types of the neurohypophyseal enriched population from the juvenile and adult zebrafish pituitaries, which laid the foundation for further lineage and functional research in this study.

2023-08-06 | GSE203075 | GEO

Single Nucleus Methylation Sequencing of Mouse Pituitary

Project description:The pituitary regulates growth, reproduction and other endocrine systems. To investigate transcriptional network epigenetic mechanisms, we generated paired single nucleus (sn) transcriptome and chromatin accessibility profiles in single mouse pituitaries, and genome-wide sn methylation datasets. Our analysis provided insight into cell type epigenetics, regulatory circuit and gene control mechanisms. Latent variable pathway analysis detected corresponding transcriptome and chromatin accessibility programs showing both inter-sexual and inter-individual variation. Multi-omics analysis of gene regulatory networks identified regulons whose composition and function within specific cell types were shaped by the promoter accessibility state of target genes. Co-accessibility analysis comprehensively identified putative cis-regulatory regions, including a domain upstream of Fshb that overlapped the fertility-linked rs11031006 human polymorphism; In vitro CRISPR-deletion at this locus increased Fshb levels, supporting this domain’s inferred regulatory role. The sn pituitary multi-omics atlas [link] is a public resource for elucidating cell-type specific gene regulatory mechanisms and principles of transcription circuit control. This GEO series contain raw (FASTQ) and processed data (ALLC) files for the sn methylation dataset generated by the snmC-seq2 method.

2021-02-23 | GSE152011 | GEO

Genome-wide evaluation of change in lncRNA expression in non-functioning pituitary adenoma using formalin-fixed and paraffin-embedded tissue specimens

Project description:Long noncoding RNAs (lncRNAs) have been implicated in the formation of many different types of tumors. However, expression profiles and potential functions of lncRNAs in non-functioning pituitary adenomas (NFPAs) have not been systematically evaluated. We evaluated the expression profiles and potential functions of lncRNAs in non-functioning pituitary adenomas (NFPAs). 10 formalin-fixed and paraffin-embedded (FFPE) tissue specimens (5 non-functioning pituitary adenomas (NFPAs) and 5 normal pituitaries(NPs)) were selected for RNA extraction and hybridization on Affymetrix microarrays. The NFPAs team was designed as the Tumor group (T), while the NPs team was designed as Normal group (N).

2016-02-06 | E-GEOD-77517 | 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