Understanding the Cellular Spatiotemporal Dogma by Spatial and Single-cell Omics.

The biological complexity of plants arises from highly coordinated cellular activities. We propose that a "cellular spatiotemporal dogma" governs the zygote's programmed development into a complete plant and its adaptation to various environmental stresses, representing the set of principles describing how gene expression, cell identity, and function are coordinated across physical spatial contexts and temporal developmental progressions. Historically, our understanding of this dogma remains limited because traditional bulk tissue sequencing provides only a homogenized average of gene expression, making it challenging to isolate and resolve functionally significant but rare cell populations, such as the root quiescent center. However, the "resolution revolution" driven by single-cell and spatially resolved omics has dismantled these barriers to reveal cellular niches: local microenvironments where neighboring cells interact and coordinate function. Here, we firstly synthesize the current landscape of single-cell and spatial multi-omics technologies, highlighting how they bypass botanical barriers like the cell wall. Next, we detail how these technologies decode plant cellular characteristics, from defining novel cell subtypes to reconstructing dynamic trajectories and identifying pan-cell populations that remain ultra-conserved across hundreds of millions of years of evolution. Finally, we discuss the paradigm shift toward Large Foundation Models (FMs), which are computational paradigms that conceptualize biological data as a structured language to enable predictive modeling. Despite challenges such as data scarcity and phylogenetic bias, the integration of high-resolution omics with AI-driven intelligence is paving the way for a "Virtual Plant Cell, " a comprehensive digital model capable of simulating and predicting cellular responses to genetic and environmental perturbations, offering a transformative foundation for smart breeding and climate-resilient agriculture.