The dawn of spatiotemporal transcriptomics

Abstract

Gene expression of cells in the tissues is a heterogeneous and dynamic program across space and time. Spatiotemporal transcriptomics technologies have emerged as transforming tools to dissect the spatiotemporal patterns of gene regulation in diverse biological processes and enable new biological discoveries. In this Perspective, we first summarize two main strategies of spatiotemporal transcriptomics (i.e., time-series analysis-based spatiotemporal transcriptomics and metabolic RNA labeling-based spatiotemporal transcriptomics) and discuss their principles and typical applications. We also highlight the recent development of bioinformatics tools to analyze the spatiotemporal transcriptomics data, which contributes to the dynamical and predictive spatiotemporal modeling and deeper biological understanding. We further provide future outlooks for the rapid development of spatiotemporal transcriptomics technologies. We anticipate that the future will continue to see the advancement of spatiotemporal transcriptomics technologies with higher performance in the aspects of sensitivity, accuracy, and resolution, and the broader applications of spatiotemporal transcriptomics technologies in biomedical analysis.