The PIAS-like coactivator Zmiz1 directly and selectively coregulates Notch1 in T-cell development and leukemia [RNA-Seq]
Transcriptomics Dataset
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General Information
AccessionGSE66145
TitleThe PIAS-like coactivator Zmiz1 directly and selectively coregulates Notch1 in T-cell development and leukemia [RNA-Seq]
DescriptionThe most recurrently mutated oncogene in T-cell acute lymphoblastic leukemia (T-ALL) is NOTCH1. The core Notch complex consists of an ICN protein, a Maml cofactor, and the DNA binding factor Rbpj. The known direct cofactors of Notch appear to act nonselectively, homogeneously driving Notch gene expression functions. It is unclear whether there are direct cofactors of Notch that act selectively and heterogeneously regulate ICN. We discovered that Zmiz1, a Protein Inhibitor of Activated STAT (PIAS)-like coactivator, directly bound ICN1. ChIP-Seq showed that Zmiz1 selectively co-bound only a subset of Notch-regulated enhancers. This led to hypothesize that Zmiz1 regulates only a subset of Notch1 target genes. To investigate this, we performed RNA-Seq on four 8946 cell linesin which L1601P (activated Notch1) or Zmiz1 were expressed alone or in combination. Zmiz1 induced ~10%% of Notch target genes. The Notch target gene that was most strongly induced by Zmiz1 was Myc. Our data suggest that Zmiz1 selectively amplifies a subset of Notch target genes with strong amplification of Myc.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66145
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 GSE66145
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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