Nature Cell BiologyDevelopmental BiologyPeer-reviewed journal article
Combined single-cell and spatial transcriptomics reveals the molecular, cellular and spatial bone marrow niche organization
Chiara BacciniD, Jude Al-SabahiD, Lars VelteniD, Patrick M. HelblingiD, Florian GrünschlägeriD, Pablo Hernández-MalmiercaiD, César Nombela‐ArrietaiD, Lars Michael SteinmetziD, Andreas TrumppiD, Simon F. HaasiD
Abstract
The bone marrow (BM) constitutes the primary site for life-long blood production and skeletal regeneration. However, its cellular composition and the spatial organization into distinct niches remains controversial. Here, we combine single-cell and spatially resolved transcriptomics to systematically map the molecular and cellular composition of the endosteal, sinusoidal, and arteriolar BM niches. This allowed us to transcriptionally profile all major BM resident cell types, determine their localization, and clarify the cellular and spatial sources of key growth factors and cytokines. Our data demonstrate that previously unrecognized Cxcl12-abundant reticular (CAR) cell subsets (i.e. Adipo- and Osteo-CAR cells) differentially localize to sinusoidal or arteriolar surfaces, locally act as professional cytokine secreting cells, and thereby establish distinct peri-vascular micro-niches. Importantly, we also demonstrate that the 3-dimensional organization of the BM can be accurately inferred from single-cell gene expression data using the newly developed RNA-Magnet algorithm. Together, our study reveals the cellular and spatial organization of BM niches, and offers a novel strategy to dissect the complex organization of whole organs in a systematic manner.\n\nOne Sentence SummaryIntegration of single-cell and spatial transcriptomics reveals the molecular, cellular and spatial organization of bone marrow niches
- organism: mouse
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: clustering
- research focus: dimensionality reduction
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 881
- FWCI
- 28.53
- Field percentile
- top 1%
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