2049-LB: Robust Single Nucleus RNA Sequencing Reveals Depot-Specific Cell Population Dynamics in Adipose Tissue Remodeling during Obesity

Single nucleus RNA sequencing (snRNA-seq) has emerged as an alternative approach to address the inherent limitations of single cell RNA sequencing (scRNA-seq). However, snRNA-seq encounters technical challenges in obtaining high-quality nuclei and RNA, which persistently hinder its applications. Here, we present a robust technique for isolating nuclei that effectively overcomes these challenges across various tissue types. Our method demonstrates a marked enhancement in the quality of snRNA-seq data, surpassing that of previously reported datasets. Employing this approach, we comprehensively characterize the cellular dynamics underlying adipose tissue remodeling during obesity. Various cell types within adipose tissue display substantial responses to obesity, with significant variations observed depending on fat depots. Through the integration of nuclear RNA-seq data acquired from adipocyte nuclei of different sizes, we identify multiple adipocyte subpopulations that can be categorized by size and functionality. Specifically, we characterize dysfunctional hypertrophic adipocytes prevalent in visceral adipose tissues during obesity, exhibiting hallmark features such as cellular stress, inflammation, and impaired gene expression. The adipocyte subpopulations contribute differentially to a range of biological pathways involved in the pathophysiology of adipose tissue during obesity. Collectively, our study establishes a robust snRNA-seq method that offers novel insights into the mechanisms orchestrating adipose tissue remodeling during obesity, with broader applicability extending to diverse biological systems.