Yiqing Wang, Zhengzhi Tan, Nicole A Freeman, Ujjal J Phukan, Sydney A Greer, M Shahid Mukhtar
Spatial transcriptomics has transformed plant biology by restoring the spatial context of gene expression lost in bulk and dissociation-based transcriptomic approaches, revealing gene expression is cell-type specific and tightly organized by position within organs and developmental niches. Studies show spatially segregated developmental programs underlying growth and differentiation, compartmentalized programs controlling nutrient transport and embryogenesis, and sharply localized host responses in plant-microbe and plant-parasite interactions. The plant spatial transcriptomics community faces limitations including restricted spatial resolution, reliance on computational deconvolution, uneven taxonomic coverage, limited temporal resolution, and a gap between correlation and causal validation.
Spatial transcriptomics has transformed plant biology by restoring the spatial context lost in bulk and dissociation-based transcriptomic approaches. This review synthesizes recent progress across diverse plant species and tissues, showing that gene expression is not only cell-type specific but also tightly organized by position within organs and developmental niches. Studies of meristems, vascular tissues, and floral organs reveal spatially segregated developmental programs underlying growth and differentiation; seed and grain analyses uncover compartmentalized programs controlling nutrient transport, dormancy, and embryogenesis; plant-microbe and emerging plant-parasite studies show that symbiosis, immunity, and feeding-site development depend on sharply localized host responses; and work on photosynthesis, drought adaptation, and regeneration demonstrates that metabolic and stress-related processes are likewise spatially patterned. Together, these findings establish spatial gene expression as a fundamental organizing principle of plant development and physiology. At the same time, the plant spatial transcriptomics community faces important limitations, including restricted spatial resolution in standard array-based platforms, reliance on computational deconvolution, uneven taxonomic coverage, limited temporal resolution, and a persistent gap between correlation and causal validation. The next stage of plant spatial transcriptomics will require true single-cell spatial resolution, standardized computational pipelines, spatial multi-omics integration, improved benchmarking across platforms, and functional perturbation of spatially defined regulators. By connecting transcriptomic position to biological function, spatial transcriptomics is poised to move plant science from descriptive atlas-building toward mechanistic and predictive understanding with major implications for crop improvement and resilience.