Transcriptomics

Dataset Information

0

Single-Cell Transcriptomics Reveals the Differentiation and Spatial Signatures underlying Sheep Hair Follicle Heterogeneity and Wool Curvature


ABSTRACT: Here, Single-cell suspensions from the wavy wool and straight wool lambskins were prepared for unbiased single-cell RNA sequencing (scRNA-seq). Based on UAMP analysis, we identified 19 distinct populations from 15,830 single-cell transcriptomes and delineated their cellular identity from specific gene expression profiles. Furtherly, novel marker gene was applied in identifying dermal papilla cells isolated in vitro. By using pseudotime ordering analysis, we successfully constructed the epithelium cell lineage differentiation trajectory and revealed the dynamic gene expression profiles of matrix progenitors’ commitment to the hair shaft and inner root sheath (IRS) cells. Meanwhile, intercellular communication between different cell populations was inferred based on CellChat and the priori knowledge of ligand-receptor pairs, as a result strong intercellular communication and associated signaling pathways were revealed. Besides, to clarify the molecular mechanism of wool curvature, differentially expressed genes in specific cells between straight wool and curly wool were identified and analyzed. Our findings here provide unbiased and systematic view of transcriptional organization of sheep hair follicle, reveal the differentiation and spatial signatures underlying sheep hair follicle heterogeneity and wool curvature, which will provide a valuable resource for understanding the molecular pathways involved in sheep hair follicle development.

ORGANISM(S): Ovis aries

PROVIDER: GSE186204 | GEO | 2022/01/12

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2017-11-16 | GSE95785 | GEO
| PRJNA772954 | ENA
2019-08-01 | GSE85844 | GEO
2019-12-04 | GSE141384 | GEO
2009-03-31 | GSE14667 | GEO
2016-07-20 | GSE76259 | GEO
2014-12-31 | GSE62552 | GEO
2016-07-20 | E-GEOD-76259 | biostudies-arrayexpress
2024-02-19 | GSE193983 | GEO
2019-07-19 | GSE84947 | GEO