Gene expression profile of chemical-induced neural stem cells from defined fibroblasts
Transcriptomics Dataset
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General Information
AccessionGSE78938
TitleGene expression profile of chemical-induced neural stem cells from defined fibroblasts
DescriptionCellular reprogramming using chemically defined conditions, without genetic manipulation, is a promising approach for generating clinically relevant cell types for regenerative medicine and drug discovery. However, small molecule-driven approaches for inducing lineage-specific stem cells from somatic cells across lineage boundaries have been challenging to develop. Here, we report highly efficient reprogramming of mouse fibroblasts into induced neural stem cell-like cells (ciNSLCs) using a cocktail of nine small molecules (M9). The resulting ciNSLCs closely resemble primary neural stem cells molecularly and functionally. Transcriptome analysis revealed that M9 induces a gradual and specific conversion of fibroblasts towards a neural fate. During reprogramming specific transcription factors such as Elk1 and Gli2 that are downstream of M9-induced signaling pathways bind and activate endogenous master neural genes to specify neural identity. Our study therefore provides an effective chemical approach for generating neural stem cells from mouse fibroblasts, and reveals mechanistic insights into underlying reprogramming process.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE78938
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE78938
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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