Metabolic RNA labeling-based time-resolved single-cell RNA sequencing (scRNA-seq) has provided unprecedented tools to dissect the temporal dynamics and the complex gene regulatory networks of gene expression. However, this technology fails to reveal the spatial organization of cells in tissues, which also regulates the gene expression by intercellular communication. Herein, it is demonstrated that integrating time-resolved scRNA-seq with spatial transcriptomics is a new paradigm for spatiotemporal analysis. Metabolic RNA labeling-based time-resolved Well-TEMP-seq is first applied to profile the transcriptional dynamics of glioblastoma (GBM) cells and discover two potential pathways of EZH2-mediated mesenchymal transition in GBM. With spatial transcriptomics, it is further revealed that the crosstalk between CCL2