Single-cell transcriptional networks in differentiating preadipocytes suggest drivers associated with tissue heterogeneity
Date
2020-04-30
Authors
Ramirez, Alfred K.
Dankel, Simon N.
Rastegarpanah, Bashir
Cai, Weikang
Xue, Ruidan
Crovella, Mark
Tseng, Yu-Hua
Kahn, C. Ronald
Kasif, Simon
Version
Published version
OA Version
Citation
Alfred K Ramirez, Simon N Dankel, Bashir Rastegarpanah, Weikang Cai, Ruidan Xue, Mark Crovella, Yu-Hua Tseng, C Ronald Kahn, Simon Kasif. 2020. "Single-cell transcriptional networks in differentiating preadipocytes suggest drivers associated with tissue heterogeneity.." Nat Commun, Volume 11, Issue 1, pp. 2117 - ?. https://doi.org/10.1038/s41467-020-16019-9
Abstract
White adipose tissue plays an important role in physiological homeostasis and metabolic disease. Different fat depots have distinct metabolic and inflammatory profiles and are differentially associated with disease risk. It is unclear whether these differences are intrinsic to the pre-differentiated stage. Using single-cell RNA sequencing, a unique network methodology and a data integration technique, we predict metabolic phenotypes in differentiating cells. Single-cell RNA-seq profiles of human preadipocytes during adipogenesis in vitro identifies at least two distinct classes of subcutaneous white adipocytes. These differences in gene expression are separate from the process of browning and beiging. Using a systems biology approach, we identify a new network of zinc-finger proteins that are expressed in one class of preadipocytes and is potentially involved in regulating adipogenesis. Our findings gain a deeper understanding of both the heterogeneity of white adipocytes and their link to normal metabolism and disease.
Description
License
© The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/