Single-Cell mRNA Sequencing Reveals Rare Intestinal Cell Types
Transcriptomics Dataset
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General Information
AccessionGSE62270
TitleSingle-Cell mRNA Sequencing Reveals Rare Intestinal Cell Types
DescriptionUnderstanding the development and function of an organ requires the characterization of all of its cell types. Traditional methods for visualizing and isolating sub-populations of cells are based on mRNA or protein expression of only few known marker genes. The unequivocal identification of a specific marker gene, however, poses a major challenge, particularly if this cell type is rare. Identifying rare cell types, such as stem cells, short-lived progenitors, cancer stem cells, or circulating tumor cells is crucial to acquire a better understanding of normal or diseased tissue biology. To address this challenge we sequenced the transcriptome of hundreds of randomly selected cells from mouse intestinal organoids, cultured self-organizing epithelial structures that contain all cell lineages of the mammalian intestine. Organoid buds, like intestinal crypts, harbor stem cells that continuously differentiate into a variety of cell types, occurring at widely different abundances. Since available computational methods can only resolve more abundant cell types, we developed RaceID, an algorithm for rare cell type identification in complex populations of single cells. We demonstrate that this algorithm can resolve cell types represented by only a single cell in a population of randomly sampled organoid cells. We use this algorithm to identify Reg4 as a novel marker for enteroendocrine cells, a rare population of hormone producing intestinal cells. Next, we use Reg4 expression to enrich for these rare cells and investigate the heterogeneity within this population. Reassuringly, RaceID confirmed the existence of known enteroendocrine lineages, and moreover, discovered novel subtypes, which we subsequently validated in vivo. Having validated RaceID by this proof-of-principle experiment we then apply the algorithm to ex vivo isolated LGR5 positive cells and their direct progeny and demonstrate homogeneity of the stem cell pool. We envision broad applicability of our method for discovering rare cell types and the corresponding marker genes in healthy and diseased organs.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62270
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 GSE62270
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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