Transcriptome sequencing of neonatal thymic epithelial cells.
Transcriptomics Dataset
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General Information
AccessionGSE44945
TitleTranscriptome sequencing of neonatal thymic epithelial cells.
DescriptionPurpose: In all vertebrates, the thymus is necessary and sufficient for production of classic adaptive T cells. The key components of the thymus are cortical and medullary thymic epithelial cells (cTECs and mTECs). Despite the capital role of TECs, our understanding of TEC biology is quite rudimentary. For instance, we ignore what might be the extent of divergence in the functional program of these two TECs populations. It also remains unclear why the number of TECs decreases rapidly with age, thereby leading to progressive thymic insufficiency. Methods: Systems level understanding of cell function begins with gene expression profiling, and the transcriptome is currently the only '-ome' that can be reliably tackled in its entirety in freshly harvested primary cells. In order to gain novel insights into TEC biology, we therefore decided to analyse the whole transcriptome of cTECs, mTECs and skin epithelial cells. We elected to analyse gene expression using RNA-seq rather microarrays because RNA-seq has higher sensitivity and dynamic range coupled to lower technical variations. Results: Our deep sequencing approach provides a unique perspective into the transcriptome of TECs. Consistent with their ability to express ectopic genes, we found that mTECs expressed more genes than other cell populations. Out of a total of 15,069 genes expressed in TECs, 25%% were differentially expressed by at least 5-fold in cTECs vs. mTECs. Genes expressed at higher levels in cTECs than mTECs regulate numerous cell functions including cell differentiation, cell movement and microtubule dynamics. Almost all positive regulators of the cell cycle were overexpressed in skin ECs relative to TECs. Conclusions: Our RNA-seq data provide novel insights into the transcriptional landscape of TECs, highlight substantial divergences in the transcriptome of TEC subsets and suggest that cell cycle progression is differentially regulated in TECS and skinECs. We believe that our work will therefore represent a valuable resource and will be of great interest to readers working in biological sciences, particularly in the areas of immunology and systems biology.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44945
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 GSE44945
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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