Dissecting the direct reprogramming path of fibroblasts into neurons by single cell RNA-sequencing
Transcriptomics Dataset
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General Information
AccessionGSE67310
TitleDissecting the direct reprogramming path of fibroblasts into neurons by single cell RNA-sequencing
DescriptionDirect lineage reprogramming represents a remarkable conversion of cellular and transcriptome states. However, the intermediates through which individual cells progress are largely undefined. Here we used single cell RNA-seq at multiple time points to dissect direct reprogramming from mouse embryonic fibroblasts (MEFs) to induced neuronal (iN) cells. By deconstructing heterogeneity at each time point and ordering cells by transcriptome similarity rather than time we reconstructed a continuous reprogramming path. We find that overexpression of a single factor (Ascl1) results in a well-defined initialization causing cells to exit the cell cycle and re-focus gene expression through distinct neural transcription factors. However, overexpression of Ascl1 alone leads to abundant alternative fates that are suppressed by the combination of additional factors (Myt1l, Pou3f2). We find transgene silencing and emergence of alternative fates are the major efficiency limits of direct reprogramming. These data provide a high-resolution approach for understanding transcriptome states during lineage differentiation.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE67310
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 GSE67310
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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