Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The fate switch between ON and OFF SACs is determined by Fezf1

ABSTRACT: The goal of this experiment was to define genes differentially expressed between E17.5 Fezf1Hete and Fezf1KO SAC cells, which were isolated by FACS from mice retinae.

ORGANISM(S): Mus musculus

PROVIDER: GSE132505 | GEO | 2019/12/04

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

The fate switch between ON and OFF SACs is determined by Fezf1

Project description:The fate switch between ON and OFF SACs is determined by Fezf1

| PRJNA548195 | ENA

Binary Fate Choice between Closely Related Interneuronal Types Is Determined by a Fezf1-Dependent Postmitotic Transcriptional Switch.

Project description:Many neuronal types occur as pairs that are similar in most respects but differ in a key feature. In some pairs of retinal neurons, called paramorphic, one member responds to increases and the other to decreases in luminance (ON and OFF responses). Here, we focused on one such pair, starburst amacrine cells (SACs), to explore how closely related neuronal types diversify. We find that ON and OFF SACs are transcriptionally distinct prior to their segregation, dendritic outgrowth, and synapse formation. The transcriptional repressor Fezf1 is selectively expressed by postmitotic ON SACs and promotes the ON fate and gene expression program while repressing the OFF fate and program. The atypical Rho GTPase Rnd3 is selectively expressed by OFF SACs and regulates their migration but is repressed by Fezf1 in ON SACs, enabling differential positioning of the two types. These results define a transcriptional program that controls diversification of a paramorphic pair.

| S-EPMC7007373 | biostudies-literature

Binary Fate Choice Between Closely Related Interneuronal Types is Determined by a Fezf1-Dependent Postmitotic Transcriptional Switch

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

2019-12-04 | GSE132555 | GEO

Comparison of gene expression pattern between Wild-type and Hypb knockout embryo yolk sacs

Project description:This study aimed at exploring the physiological function of mammalian HYPB by means of knockout mouse model. Homogenous disruption of mouse Hypb gene leads to embryonic lethality at E10.5-E11.5. Severe vascular defects were observed in the Hypb-/- embryos, yolk sac and placenta.In the mutant embryo and yolk sac, disorganized and abnormally dilated capillaries cannot be remodeled into large blood vessels or intricate networks. Thus, our results suggest that the mammalian HYPB HMT plays an important role in embryonic vascularization. Keywords: knockout, mouse embryo development, angiogenesis, yolk sac, E9.0, E10.5

2009-12-28 | GSE10113 | GEO

The transcriptome comparison between wildtype Hb9-GFP and Satb1-/-Hb9-GFP retinal ganglion cells (RGCs).

Project description:The goal of this experiment was to define genes differentially expressed between P6 Hb9-GFP and Satb1-/-Hb9-GFP cells, which were dissociated and FACS sorted from mice retinae.

2017-09-30 | GSE90652 | GEO

Binary Fate Choice Between Closely Related Interneuronal Types is Determined by a Fezf1-Dependent Postmitotic Transcriptional Switch

Project description:Binary Fate Choice Between Closely Related Interneuronal Types is Determined by a Fezf1-Dependent Postmitotic Transcriptional Switch

| PRJNA548349 | ENA

Von Hippel-Lindau Acts as a Metabolic Switch Controlling Nephron Progenitor Differentiation

Project description:RNA sequencing was performed on VHLNP+/- and VHLNP-/- E17.5 isolated nephron progenitors. E17.5 kidneys were dissected and screened using the GFP expression. Dissected kidneys that expressed GFP were dissociated into single cell suspensions and FACS sorted; each sample consisted of approximately 150,000 pooled nephron progenitor cells. RNA was extracted using the RNeasy Micro Kit (Qiagen). The Health Sciences Sequencing Core at Children’s Hospital of Pittsburgh performed library construction and RNA sequencing (single-end reads, 75bp). Bioinformatics quality control was performed using FastQC (version 0.11.5), and adapters were trimmed using BBDuk from the BBMap software package (version 37.41). Reads were aligned to transcripts assembled from the mm10 genome (GRCm38, GENCODE M17 ) using the Spliced Transcripts Alignments to a Reference software package (STAR, version 2.5.3a). Reads aligned to known transcripts were counted using the Bioconductor GenomicAlignments R package (version 1.10.1), and differential expression between VHLNP+/- and VHLNP-/- kidney samples was calculated using DESeq2 (version 1.18.1). Expression levels of 245 genes were identified as significantly altered between VHLNP+/- and VHLNP-/- samples (padj <= 0.05, fc > 2).

2019-05-31 | GSE122900 | GEO

Cell fate determined by the activation balance between PKR and SPHK1.

Project description:Double-stranded RNA (dsRNA)-dependent protein kinase R (PKR) activation via autophosphorylation is the central cellular response to stress that promotes cell death or apoptosis. However, the key factors and mechanisms behind the simultaneous activation of pro-survival signaling pathways remain unknown. We have discovered a novel regulatory mechanism for the maintenance of cellular homeostasis that relies on the phosphorylation interplay between sphingosine kinase 1 (SPHK1) and PKR during exogenous stress. We identified SPHK1 as a previously unrecognized PKR substrate. Phosphorylated SPHK1, a central kinase, mediates the activation of PKR-induced pro-survival pathways by the S1P/S1PR1/MAPKs/IKKα signal axis, and antagonizes PKR-mediated endoplasmic reticulum (ER) stress signal transduction under stress conditions. Otherwise, phosphorylated SPHK1 also acts as the negative feedback factor, preferentially binding to the latent form of PKR at the C-terminal kinase motif, inhibiting the homodimerization of PKR, suppressing PKR autophosphorylation, and reducing the signaling strength for cell death and apoptosis. Our results suggest that the balance of the activation levels between PKR and SPHK1, a probable hallmark of homeostasis maintenance, determines cell fate during cellular stress response.

| S-EPMC7852545 | biostudies-literature

Stochastic antagonism between two proteins governs a bacterial cell fate switch.

Project description:Cell fate decision circuits must be variable enough for genetically identical cells to adopt a multitude of fates, yet ensure that these states are distinct, stably maintained, and coordinated with neighboring cells. A long-standing view is that this is achieved by regulatory networks involving self-stabilizing feedback loops that convert small differences into long-lived cell types. We combined regulatory mutants and in vivo reconstitution with theory for stochastic processes to show that the marquee features of a cell fate switch in Bacillus subtilis-discrete states, multigenerational inheritance, and timing of commitments-can instead be explained by simple stochastic competition between two constitutively produced proteins that form an inactive complex. Such antagonistic interactions are commonplace in cells and could provide powerful mechanisms for cell fate determination more broadly.

| S-EPMC7526939 | biostudies-literature

Single cell transcriptome sequencing of CS11 and CS15 human yolk sacs

Project description:Yolk sac is an important site for early embryonic hematopoiesis. However, our understanding of early hematopoietic development is still very limited. Single cell transcriptome sequencing provides us with a good research method. Here, we performed single cell RNA-seq analysis for Carnegie stage 11 (CS11) and Carnegie stage 15 (CS15) human yolk sacs.

2020-02-16 | GSE137010 | 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