Robust single nucleus RNA sequencing reveals depot-specific cell population dynamics in adipose tissue remodeling during obesity
Single nucleus RNA sequencing (snRNA-seq), an alternative to single cell RNA sequencing (scRNA-seq), encounters technical challenges in obtaining high-quality nuclei and RNA, persistently hindering its applications. Here, we present a robust technique for isolating nuclei across various tissue types, remarkably enhancing snRNA-seq data quality. Employing this approach, we comprehensively characterize the depot-dependent cellular dynamics of various cell types underlying adipose tissue remodeling during obesity. By integrating nuclear RNA-seq data from adipocyte nuclei of varying sizes, we identify distinct adipocyte subpopulations categorized by size and functionality. Specifically, we characterize dysfunctional hypertrophic adipocytes prevalent in visceral adipose tissues during obesity, exhibiting cellular stress, inflammation and impaired metabolic gene expression. Obesity-induced changes in gene expression profiles of adipocyte subpopulations reveal their distinct contributions to adipose tissue pathophysiology. Our study establishes a robust snRNA-seq method, providing novel insights into the mechanisms orchestrating adipose tissue remodeling during obesity, with broader applicability across diverse biological systems. Overall design: We conducted a comparative gene expression profiling analysis of snRNA-seq data from epididymal and inguinal white adipose tissues of lean and obese mice. Additionally, to define nuclear gene expression signatures associated with nucleus size and potentially corresponding to distinct adipocyte subpopulations, we performed RNA-seq on adipocyte nuclei isolated from inguinal white adipose tissues (iWAT) of Adipoq-NuTRAP mice fed a high-fat diet (HFD), sorted by size using flow cytometry. Adipocyte nuclei from iWAT of mice fed a normal chow diet were also included as controls.