Geminin-regulated genes during neural fate acquisition of mouse embryonic stem cells
Transcriptomics Dataset
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General Information
AccessionGSE25737
TitleGeminin-regulated genes during neural fate acquisition of mouse embryonic stem cells
DescriptionFormation of the complex vertebrate nervous system begins when pluripotent cells of the early embryo are directed to acquire a neural fate. Although cell intrinsic controls play an important role in this process, the molecular nature of this regulation is not well defined. Here we assessed the role for Geminin, a nuclear protein expressed in embryonic cells, in neural fate acquisition from mouse embryonic stem (ES) cells. While Geminin knockdown does not affect the ability of ES cells to maintain or exit pluripotency, we found that it significantly impairs their ability to acquire a neural fate. Conversely, Geminin overexpression promotes neural gene expression, even in the presence of growth factor signaling that antagonizes neural transcriptional responses. These data demonstrate that Geminins activity contributes to mammalian neural cell fate acquisition. We investigated the mechanistic basis of this phenomenon and found that Geminin maintains a hyperacetylated and open chromatin conformation at neural genes. Interestingly, recombinant Geminin protein also rapidly alters chromatin acetylation and accessibility even when Geminin is combined with nuclear extract and chromatin in vitro. These findings define a novel activity for Geminin in regulation of chromatin structure. Together, these data support a role for Geminin as a cell intrinsic regulator of neural fate acquisition that promotes expression of neural genes by regulating chromatin accessibility and histone acetylation.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25737
RepositoryGene Expression Omnibus
Tools used to analyze the dataset
Keyword
Dataset Accession
Enrichr
Published May 2016
A comprehensive gene set enrichment analysis web server 2016 update
7759
65
Characteristic Direction
Published March 2014
A geometrical multivariate approach to identify differentially expressed genes
26829
GeneMANIA
Published June 2010
Biological network integration for gene prioritization and predicting gene function
7435
L1000CDS2
Published August 2016
An ultra-fast LINCS L1000 Characteristic Direction signature search engine
7756
PAEA
Published November 2015
Enrichment analysis tool implementing the principal angle method
3879
Canned Analyses generated with the dataset
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Dataset Accession
Tool Name
Direction
Geneset
Small molecules which mimic GMNN KD
L1000CDS2, Characteristic Direction
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse GMNN KD
L1000CDS2, Characteristic Direction
The L1000 database was queried in order to identify small molecule perturbations which rev...
Enrichment analysis of genes dysregulated in GMNN KD
PAEA, Characteristic Direction
An enrichment analysis was performed on the top most dyresgulated genes determined by appl...
Interaction network and enrichment analysis of genes downregulated in GMNN KD
GeneMANIA, Characteristic Direction
The analysis explores the gene interaction network and pathway enrichment of the top 50 mo...
Interaction network and enrichment analysis of genes upregulated in GMNN KD
GeneMANIA, Characteristic Direction
The analysis explores the gene interaction network and pathway enrichment of the top 50 mo...
Enrichment analysis of genes downregulated in GMNN KD
Enrichr, Characteristic Direction
An enrichment analysis was performed on the top 500 most downregulated genes identified by...
Enrichment analysis of genes upregulated in GMNN KD
Enrichr, Characteristic Direction
An enrichment analysis was performed on the top 500 most upregulated genes identified by a...
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