Constructing the spatiotemporal atlas of single-cell lineage trajectories in stereotypic biological structures

Spatial transcriptomics technologies have emerged as instrumental tools for elucidating cellular heterogeneity and molecular regulation within the complex tissue microenvironment, but are constrained by insufficient gene recovery or an inability to achieve intact single-cell resolution. By integrating spatial transcriptomics and single-cell RNA sequencing technologies, we develop a mathematical method of single-cell resolved spatiotemporal (SCST) mapping that comprises tiered algorithms for constructing the spatial molecular atlas of the biospecimen at single-cell resolution across a timeline of development. The embedded spatial-smoothing algorithm in SCST significantly enhances the spatial mapping accuracy of single cells, thereby improving the fidelity of the annotation of cell identity to the equivalent <i>in vivo</i> cell type. Through 3D mathematical modeling, SCST facilitates the spatial reconstruction of a single-cell molecular atlas and the delineation of cellular heterogeneity. When integrated with temporal data, SCST can also delineate the spatiotemporal lineage trajectory at single-cell resolution in a developing biological entity.