Literature DB >> 35318510

Insights from Studies of White Adipose Tissue Using Single-Cell Approaches.

Niklas Mejhert1, Mikael Rydén2.   

Abstract

Technologies allowing studies at single-cell resolution have provided important insights into how different cell populations contribute to tissue function. Application of these methods to white adipose tissue (WAT) has revealed how various metabolic aspects of this organ, such as insulin response, inflammation and tissue expansion, are regulated by specific WAT resident cells, including different subtypes of adipocytes, adipocyte progenitors as well as immune and endothelial cells. In this chapter, we provide an overview of the different technical approaches, their strengths and weaknesses, and summarize how these studies have improved our understanding of WAT function in health and disease.
© 2022. The Author(s), under exclusive license to Springer Nature Switzerland AG.

Entities:  

Keywords:  Obesity; Single-cell sequencing; Single-nucleus sequencing; Spatial transcriptomics; Type 2 diabetes

Mesh:

Year:  2022        PMID: 35318510     DOI: 10.1007/164_2021_578

Source DB:  PubMed          Journal:  Handb Exp Pharmacol        ISSN: 0171-2004


  63 in total

Review 1.  Single-Cell Applications of Next-Generation Sequencing.

Authors:  Naishitha Anaparthy; Yu-Jui Ho; Luciano Martelotto; Molly Hammell; James Hicks
Journal:  Cold Spring Harb Perspect Med       Date:  2019-10-01       Impact factor: 6.915

Review 2.  Weighing in on adipocyte precursors.

Authors:  Ryan Berry; Elise Jeffery; Matthew S Rodeheffer
Journal:  Cell Metab       Date:  2013-11-14       Impact factor: 27.287

3.  Deconstructing Adipogenesis Induced by β3-Adrenergic Receptor Activation with Single-Cell Expression Profiling.

Authors:  Rayanne B Burl; Vanesa D Ramseyer; Elizabeth A Rondini; Roger Pique-Regi; Yun-Hee Lee; James G Granneman
Journal:  Cell Metab       Date:  2018-06-21       Impact factor: 27.287

4.  Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin.

Authors:  Jesper Bäckdahl; Lovisa Franzén; Lucas Massier; Qian Li; Jutta Jalkanen; Hui Gao; Alma Andersson; Nayanika Bhalla; Anders Thorell; Mikael Rydén; Patrik L Ståhl; Niklas Mejhert
Journal:  Cell Metab       Date:  2021-08-10       Impact factor: 27.287

Review 5.  Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data.

Authors:  Tallulah S Andrews; Vladimir Yu Kiselev; Davis McCarthy; Martin Hemberg
Journal:  Nat Protoc       Date:  2020-12-07       Impact factor: 13.491

6.  Defining the lineage of thermogenic perivascular adipose tissue.

Authors:  Anthony R Angueira; Alexander P Sakers; Corey D Holman; Lan Cheng; Michelangella N Arbocco; Farnaz Shamsi; Matthew D Lynes; Rojesh Shrestha; Chihiro Okada; Kirill Batmanov; Katalin Susztak; Yu-Hua Tseng; Lucy Liaw; Patrick Seale
Journal:  Nat Metab       Date:  2021-04-12

7.  Characterization of the adipocyte cellular lineage in vivo.

Authors:  Ryan Berry; Matthew S Rodeheffer
Journal:  Nat Cell Biol       Date:  2013-02-24       Impact factor: 28.824

8.  Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography.

Authors:  Alma Andersson; Joseph Bergenstråhle; Michaela Asp; Ludvig Bergenstråhle; Aleksandra Jurek; José Fernández Navarro; Joakim Lundeberg
Journal:  Commun Biol       Date:  2020-10-09

9.  Single cell transcriptomics suggest that human adipocyte progenitor cells constitute a homogeneous cell population.

Authors:  Juan R Acosta; Simon Joost; Kasper Karlsson; Anna Ehrlund; Xidan Li; Myriam Aouadi; Maria Kasper; Peter Arner; Mikael Rydén; Jurga Laurencikiene
Journal:  Stem Cell Res Ther       Date:  2017-11-07       Impact factor: 6.832

10.  Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM.

Authors:  Marcus Alvarez; Elior Rahmani; Brandon Jew; Kristina M Garske; Zong Miao; Jihane N Benhammou; Chun Jimmie Ye; Joseph R Pisegna; Kirsi H Pietiläinen; Eran Halperin; Päivi Pajukanta
Journal:  Sci Rep       Date:  2020-07-03       Impact factor: 4.996

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