Single-cell transcriptome profiling reveals dermal and epithelium cell fate decisions during embryonic hair follicle development

Abstract

Characterization of the morphological structure during hair follicle development has been well documented, while the current understanding of the molecular mechanisms involved in follicle development remain limited. Here, using unbiased single-cell RNA sequencing, we analyzed 15,086 single cell transcriptome profiles from E13.5 and E16.5 fetal mice, and newborn mouse (postnatal day 0, P0) dorsal skin cells. Based on t-distributed Stochastic Neighbor Embedding (tSNE) clustering, we identified 14 cell clusters from skin cells and delineated their cell identity gene expression profiles. Pseudotime ordering analysis successfully constructed epithelium/dermal cell lineage differentiation trajectory and revealed sequential activation of key regulons involved during cell fate decisions. Along with this, intercellular communication between different cell populations were inferred based on a priori knowledge of ligand-receptor pairs. Together, our findings here provide a molecular landscape during hair follicle epithelium/dermal cell lineage fate decisions, and more importantly, recapitulate sequential activation of core regulatory transcriptional factors for different cell populations during hair follicle morphogenesis.

A single-cell transcriptome atlas during Cashmere goat hair follicle morphogenesis

“…Similar to the murine model, we also observed differential gene expression profiles in different DP cell populations from different hair follicles (primary hair follicles vs secondary hair follicles), which was also consistent with our recent findings on mice (Ge et al, 2019). Besides, an in-depth comparison of differentially expressed genes revealed that different DP cell populations require different transcriptional profiles, and it’s, therefore, plausible that the different induction signals may be involved during the asynchronous development of hair follicles.…”

“…Besides, we also compared our identified hair shaft and IRS signature genes with our recently identified murine hair shaft and IRS signature genes (Ge et al, 2019). Interestingly, we only observed about ∼8.8% overlapped IRS signature genes between mouse and goat (Fig.…”

“…The paucity of information regarding the cell heterogeneity within the hair follicles has obviously become the main obstacle in dissecting the hair follicle morphogenesis. scRNA seq has recently became robust tool in dissecting cell heterogeneity and several groups have also successfully used scRNA seq technology to reveal the molecular machinery underlying murine hair follicle development (Ge et al, 2019, Gupta et al, 2019, Mok et al, 2019), further emphasized its application prospect in hair follicle development-related researches.…”

Inference and analysis of cell-cell communication using CellChat

“…First, we performed clustering analysis of cells from E13.5 and E14.5 using the Louvain community detection method, respectively. The values of the resolution parameter in the Louvain community detection method were explored to produce the major cell populations in embryonic skin 20,75 . Thus, 11 and 13 cell populations were identified at E13.5 and E14.5, respectively (Supplementary Fig.…”

“…2ad). The cell populations were annotated based on the known markers 20,75 . Compared to E13.5, there were two specific populations at E14.5, including dermal condensate (DC) cells and pericytes.…”