Self-renewal and differentiation of skeletal stem and progenitor cells (SSPCs) are tightly regulated processes, with SSPC dysregulation leading to progressive bone disease. While the application of single-cell RNA sequencing (scRNAseq) to the bone field has led to major advancements in our understanding of SSPC heterogeneity, stem cells are tightly regulated by their neighboring cells which comprise the bone marrow niche. However, unbiased interrogation of these cells at the transcriptional level within their native niche environment has been challenging. Here, we combined spatial transcriptomics and scRNAseq using a predictive modeling pipeline derived from multiple deconvolution packages in adult mouse femurs to provide an endogenous, in vivo context of SSPCs within the niche. This combined approach localized SSPC subtypes to specific regions of the bone and identified cellular components and signaling networks utilized within the niche. Furthermore, the use of spatial transcriptomics allowed us to identify spatially restricted activation of metabolic and major morphogenetic signaling gradients derived from the vasculature and bone surfaces that establish microdomains within the marrow cavity. Overall, we demonstrate, for the first time, the feasibility of applying spatial transcriptomics to fully mineralized tissue and present a combined spatial and single-cell transcriptomic approach to define the cellular components of the stem cell niche, identify cell‒cell communication, and ultimately gain a comprehensive understanding of local and global SSPC regulatory networks within calcified tissue.

骨骼干细胞和祖细胞 （SSPCs） 的自我更新和分化是受到严格调节的过程，SSPC 失调会导致进行性骨病。虽然单细胞 RNA 测序 （scRNAseq） 在骨领域的应用使我们对 SSPC 异质性的理解取得了重大进展，但干细胞受到构成骨髓生态位的邻近细胞的严格调控。然而，在它们的天然生态位环境中对这些细胞进行转录水平的无偏倚询问一直具有挑战性。在这里，我们使用源自成年小鼠股骨中多个反卷积包的预测建模管道将空间转录组学和 scRNAseq 相结合，以提供生态位内 SSPC 的内源性体内背景。这种组合方法将 SSPC 亚型定位到骨骼的特定区域，并确定了生态位内利用的细胞成分和信号网络。此外，空间转录组学的使用使我们能够识别源自脉管系统和骨表面的代谢和主要形态发生信号梯度的空间限制激活，这些梯度在骨髓腔内建立微结构域。总体而言，我们首次证明了将空间转录组学应用于完全矿化组织的可行性，并提出了一种结合的空间和单细胞转录组学方法来定义干细胞生态位的细胞成分，识别细胞\u2012细胞通讯，并最终全面了解钙化组织内的局部和全球 SSPC 调控网络。