Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of mouse limbal and corneal epithelial basal cells to characterize different gene expression patterns in the two cell types

ABSTRACT: Limbal vs. corneal epithelial basal cell gene expression patterns were identified and compared. Experiment Overall Design: 8 limbal and 8 corneal epithelial basal cells samples from 8 mice were dissected and mRNAs were isolated and amplified for microarray analysis

ORGANISM(S): Mus musculus

SUBMITTER: Mingyuan Zhou

PROVIDER: E-GEOD-4098 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptional profiling of enriched populations of stem cells versus transient amplifying cells. A comparison of limbal and corneal epithelial basal cells.

Zhou Mingyuan M Li Xin-min XM Lavker Robert M RM

The Journal of biological chemistry 20060504 28

The basal layer of limbal and central corneal epithelium is enriched in stem cells and transient amplifying cells, respectively. This physical separation of stem and transient amplifying cells makes the limbal/corneal epithelium an exceptionally suitable system for isolating basal cells enriched in these two proliferative populations. Prior attempts to isolate epithelial stem cells used methods such as proteolytic tissue dissociation and cell sorting that could potentially alter their gene expre ...[more]

PMID: 16675456

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Project description:Limbal stem cells (LSCs), known as corneal epithelial stem cells, are located at the basal epithelial layer of the corneal limbus and serve an important function in maintaining the homeostasis of the corneal epithelium. Several putative molecular markers of LSCs have been previously identified. However, the specificity of these markers remains largely controversial. To address this gap in the current understanding of LSCs, we performed a transcriptome profiling of heterogeneous corneal limbal basal cells using single-cell transcriptomics technology to identify LSCs and their exclusive markers. We isolated limbal basal cells from two young donors, constructed scRNA-seq libraries, generated RNA-sequencing data using the 10x Genomics platform, and then finally obtained the transcriptome of about 18,000 individual single-cells using Cell ranger (https://10xgenomics.com). Next, we performed quality control, filtering and data integration using Seurat package (https://satijalab.org/seurat), about 16,400 cells were retained for further downstream analysis such as dimensional reduction, unsupervised clustering, and Differentially expressed gene selection, trajectory analysis and visualization. We identified 11 unique clusters of cells assigned to a putative cell type based on published known biomarkers for differentiation, proliferation and putative epithelial stem cells. As a results, we found 2 Terminally Differentiated Cell (TDC), 3 Post-Mitotic Cell (PMC), 1 Transient Amplifying Cell (TAC), 2 Limbal Progenitor Cell (LPC), Putative Limbal Stem Cell (LSC) and 2 Melanocyte (MC) sub-cell type clusters. Furthermore, we confirmed the trajectory order of LSC differentiation for 9 clusters using Pseudotemporal and Functional PCA analysis. Lastly, we validated each assigned cell subtypes and determined their location in human corneal limbus tissue with 9 markers using RNAscope We were able to reveal the heterogeneity of corneal limbal basal epithelium by defining novel dynamic trajectories for cell types in a pseudotemporal manner. This approach allowed us to identify the distinct clusters of LSCs and progenitors with exclusively expressed markers, and might apply for translational research on regenerating a normal corneal epithelium and restoring vision.

Dataset Information

Transcription profiling of mouse limbal and corneal epithelial basal cells to characterize different gene expression patterns in the two cell types

Publications

Transcriptional profiling of enriched populations of stem cells versus transient amplifying cells. A comparison of limbal and corneal epithelial basal cells.

Similar Datasets

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