Whytock Katie L, Sun Yifei, Divoux Adeline, Yu GongXin, Smith Steven R, Walsh Martin J, Sparks Lauren M
Translational Research Institute, AdventHealth, 301 E Princeton St, Orlando, FL 32804, USA.
Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
iScience. 2022 Jul 16;25(8):104772. doi: 10.1016/j.isci.2022.104772. eCollection 2022 Aug 19.
White adipose tissue (WAT) is a complex mixture of adipocytes and non-adipogenic cells. Characterizing the cellular composition of WAT is critical for identifying where potential alterations occur that impact metabolism. Most single-cell (sc) RNA-Seq studies focused on the stromal vascular fraction (SVF) which does not contain adipocytes and have used technology that has a 3' or 5' bias. Using full-length sc/single-nuclei (sn) RNA-Seq technology, we interrogated the transcriptional composition of WAT using: snRNA-Seq of whole tissue, snRNA-Seq of isolated adipocytes, and scRNA-Seq of SVF. Whole WAT snRNA-Seq provided coverage of major cell types, identified three distinct adipocyte clusters, and was capable of tracking adipocyte differentiation with pseudotime. Compared to WAT, adipocyte snRNA-Seq was unable to match adipocyte heterogeneity. SVF scRNA-Seq provided greater resolution of non-adipogenic cells. These findings provide critical evidence for the utility of sc full-length transcriptomics in WAT and SVF in humans.
白色脂肪组织(WAT)是脂肪细胞和非脂肪生成细胞的复杂混合物。表征WAT的细胞组成对于确定影响新陈代谢的潜在改变发生的位置至关重要。大多数单细胞(sc)RNA测序研究集中于不包含脂肪细胞的基质血管部分(SVF),并且使用了具有3'或5'偏向性的技术。我们使用全长sc/单细胞核(sn)RNA测序技术,通过以下方式探究WAT的转录组成:全组织snRNA测序、分离的脂肪细胞snRNA测序以及SVF的scRNA测序。全WAT snRNA测序覆盖了主要细胞类型,鉴定出三个不同的脂肪细胞簇,并且能够用伪时间追踪脂肪细胞分化。与WAT相比,脂肪细胞snRNA测序无法匹配脂肪细胞的异质性。SVF scRNA测序提供了更高分辨率的非脂肪生成细胞。这些发现为sc全长转录组学在人类WAT和SVF中的应用提供了关键证据。