Advances in the application of spatial transcriptomics in understanding development and disease

Spatial transcriptomics (In this review, 'spatial transcriptomics' (ST) is employed as a overarching term, encompassing two distinct concepts. Firstly, 'tissue-level ST' refers to the capture of tissue samples at a resolution of 10-100 μm, encompassing 1-20 cells. Secondly, 'spatially resolved single-cell transcriptomics' (sc-ST) involves the analysis of individual cells or nuclei, with each sequencing unit measuring ≤ 2 μm) fuses high-throughput sequencing with positional information to map gene expression within intact tissues. By preserving spatial context, the technology uncovers cell types, signaling circuits and regulatory networks that drive organogenesis, differentiation and disease. Here we synthesize recent methodological advances and their application to developmental and clinical questions. The term "Spatial Transcriptomics" as used in this paper comprehensively encompasses all sequencing technologies that preserve spatial coordinates, including multimodal data such as transcriptomics (RNA), genomics (DNA), epigenomics (ATAC, CUT&Tag), and translationalomics (Ribo-seq).