Dataset Information

Single cell sequencing of de-differentiated dermal adipocytes

ABSTRACT: Purpose: The goals of this study are to compare the de-differentiated dermal adipocytes with normal skin fibroblasts. Methods: Library prepared followed by 10X Genomics standard protocol. Transcriptome was generated by high throughput sequencing.

ORGANISM(S): Mus musculus

PROVIDER: GSE129371 | GEO | 2019/09/16

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Purpose: To test if there is a heterogeneity within brown adipocytes, we performed single cell RNA-sequencing of primary brown adipocytes isolated from mouse brown adipose tissue. Methods: Brown adipocytes from 10-week-old C57BL/6J male mice were freshly collected and resuspended in PBS containing 0.04% BSA at a concentration of 700~1200 cells/µl. Cell number and viability were measured using a TC20 Automated Cell Counter (BioRad). Single-cell RNA libraries were prepared according to the Chromium™ Single Cell 3' Reagent Kits v2 User Guide (10x Genomics). Approximately 10,000 cells were loaded on a Chromium single cell Controller instrument (10x Genomics) to generate single cell gel beads in emulsion (GEMs). The barcoded sequencing libraries were constructed using the Chromium Single-Cell 3′ Library Kit (10x Genomics) for enzymatic fragmentation, end-repair, A-tailing, adaptor ligation, ligation cleanup, sample index PCR, and PCR cleanup. Libraries were sequenced with a Hiseq 2500 instrument (Illumina) with a depth of 50k-100k reads per cell. Raw sequencing data were processed using the 10x Genomics Cell Ranger pipeline (version 2.0) to generate FASTQ files and aligned to mm10 genome to gene expression count. The subsequent data analysis was performed using “Seurat” package and R scripts. Cells with mitochondrial read rate > 50% and < 200 detectable genes were considered as low-quality and filtered out. Normalized and scaled data were clustered using the top significant principal components of highly variable genes. The t-distributed stochastic neighbor embedding (t-SNE) algorithm was used to visualize the resulting clusters. Cluster-specific markers were identified to generate heatmap and feature plots in the identified cell clusters. Genes were compared between different clusters using Bioconductor package “Limma” on normalized data. Gene Set Enrichment Analysis (GSEA) v3 was performed using genes ranked by the fold changes between different clusters to evaluate the significant activation of the C2 KEGG gene sets in MSigDb (http://software.broadinstitute.org/gsea/msigdb/collections.jsp). Results: Two major brown adipocyte subpopulations were clustered as brown adipocytes with high thermogenic activity (BA-H, 2,352 cells) and brown adipocytes with low thermogenic activity (BA-L, 1,250 cells). Conclusions: In summary, the brown adipocyte single cell transcriptomic reveals a unique subpopulation of brown adipocytes with low thermogenic activity. These cells hold a unique metabolic status, and the function of these cells is fundamentally different from the cells within the BA-H subpopulation.

Dataset Information

Single cell sequencing of de-differentiated dermal adipocytes

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets