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. Author manuscript; available in PMC: 2024 Mar 7.
Published in final edited form as: Cell Metab. 2023 Mar 7;35(3):386–413. doi: 10.1016/j.cmet.2023.02.002
Single cell/nuclei analyses of adipose tissue
Whole tissue technologies Pros Cons
Single cell/nuclei sequencing

(e.g., 10x Genomics and other droplet-based methods)
  • Unbiased profiling of all cells in tissue
  • Genome-wide quantification of transcriptome/epigenome
  • High throughput for detection of cellular heterogeneity and rare cell types
  • Detection of cell fate trajectories
  • Stressful and biased isolation of cells/nuclei
  • Ambient RNA contamination (esp. snRNA-seq)
  • Limited sequencing depth
  • Lack of spatial information
Sequencing-based spatial transcriptomics

(e.g., GeoMx® Digital Spatial Profiler, Illumina Visium)
  • Spatial resolution of transcriptome
  • Detection of tissue microregions
  • Captures all cell types in tissue section
  • Limited cross-contamination between cell types
  • Lack of full cellular resolution
  • Adipocyte size and lipid content complicates transcriptome-to-cell assignment
  • Limited sequencing depth
  • Limited cell sampling per tissue sections
Hybridization/antibody-based spatial analyses

(e.g., MERFISH, CosMx, 10x Genomics Xenium)
  • Subcellular resolution of transcriptome/proteome in tissue
  • Detection of tissue microregions
  • Capture of all cell types in tissue section
  • Limited cross-contamination between cell types
  • Lack of unbiased detection
  • Limited detection depth
  • Limited cell sampling per tissue sections