Coding mutations and loss-of-imprinting in human pluripotent cells derived by nuclear transfer and defined factors [RNA-Seq]
Transcriptomics Dataset
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General Information
AccessionGSE61656
TitleCoding mutations and loss-of-imprinting in human pluripotent cells derived by nuclear transfer and defined factors [RNA-Seq]
DescriptionHuman pluripotent stem cells can be derived from somatic cells by forced expression of defined factors, and more recently by nuclear-transfer into human oocytes, revitalizing a debate on whether one reprogramming approach might be advantageous over the other. Here we compared the genetic and epigenetic stability of human nuclear-transfer embryonic stem cell (NT-ESC) lines and isogenic induced pluripotent stem cell (iPSC) lines, derived from the same somatic cell cultures of fetal, neonatal and adult origin. Both cell types shared similar genome-wide gene expression and DNA methylation profiles. Importantly, NT-ESCs and iPSCs have comparable numbers of de novo coding mutations but significantly higher than parthenogenetic ESCs. Similar to iPSCs NT-ESCs displayed clone- and gene-specific aberrations in DNA methylation and allele-specific expression of imprinted genes, similarly to iPSCs. The occurrence of these genetic and epigenetic defects in both NT-ESCs and iPSCs suggests that they are inherent to reprogramming, regardless of the underlying technique.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61656
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 GSE61656
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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