Evaluation of Human Adipose Tissue Stromal Heterogeneity in Metabolic Disease Using Single-Cell RNA-Seq
Abstract
We have developed a robust protocol to generate single cell transcriptional profiles from adipose tissue samples of both human and mouse subjects using Drop-seq, a recently developed, cost-efficient method of highly parallel genome-wide expression profiling using nanoliter droplets. We have collected subcutaneous adipose tissue samples from >15 human subjects as well as one omental sample, resulting in the generation of transcriptional profiles for over ~50,000 individual cells. Additionally, we have generated profiles from ~22,000 cells from a combination of mouse subcutaneous, epididymal, and brown fat depots. Our analyses demonstrate expression profiles can be used to cluster individual cells into distinct cell types in an unbiased fashioned. We identify 1) most cell types known to be contained within adipose tissue SVF 2) many cell types and subtypes that have not previously been described, 3) depot-specific or enriched cell types. We can determine transcriptional markers for most cell types with higher specificity than currently accepted markers. These data begin to provide a comprehensive transcriptional atlas of subcutaneous adipose tissue cell types that will provide molecular handles to understanding and manipulating each cell types function. These results are hypothesis-generating, and provide the foundation for future studies that will 1) define functional roles for individual genes and cell types in development of obesity and insulin resistance and 2) examine novel targets against which we can design therapies to target specific pathogenic or or health-promoting cell types.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2018
- Accession Number
- AD1055791
Entities
People
- Linus T. Tsai
Organizations
- Beth Israel Deaconess Medical Center