Characterizing Plant Gene Expression in Cellular Context: How Spatial Transcriptomics Advances Plant Research

Understanding plant development at cellular resolution has long been limited by a key challenge: bulk RNA sequencing captures overall gene expression but loses spatial and cellular context. Single-cell approaches help distinguish gene expression patterns across different cell types, but they do not preserve the precise tissue location of those cells. This limitation is especially relevant in plant research, where many species are non-model organisms and well-defined marker genes for different cell types are often unavailable, making single-cell results difficult to interpret.

Spatial transcriptomics is changing this landscape by enabling researchers to map gene expression directly onto tissue architecture. This makes it possible to interpret cellular functions, identify tissue-specific gene activity, and characterize cell-cell communication in situ.

Here, we highlight four studies across diverse plant tissues, from roots to reproductive organs, to show how spatial information is becoming essential for decoding complex biological processes in plants.

Revealing Key Cell Groups in Root Regeneration from Stems

In woody plants such as poplar, vegetative propagation relies on the ability to regenerate roots from stem cuttings. However, this process can be inefficient and remains incompletely understood. Lv et al. demonstrated that spatial transcriptomics can identify key cell populations involved in root regeneration and reveal localized molecular interactions that drive this process.

Subsequent pseudo-temporal trajectory analysis based on spatial data provided a clear cell differentiation map, tracing the progression from stem cambium cells to xylem, phloem, cortex, and epidermal cells, and ultimately to root primordia. This study highlights how spatial transcriptomics can uncover the molecular programs underlying root regeneration and offers valuable insights for improving plant propagation techniques.

Understanding the Vegetative-to-Reproductive Transition in the Shoot Apex

For non-model plants such as loquat, the lack of well-defined marker genes makes single-cell data difficult to interpret. Zhao et al. addressed this challenge by integrating single-nucleus RNA sequencing with spatial transcriptomics to study the vegetative-to-reproductive transition in the shoot apex.

Although single-cell or single-nucleus analysis can identify distinct cell clusters, the biological roles of these clusters may remain unclear without spatial context. By incorporating spatial information, the researchers were able to assign functional identities to these cell populations and further explore cell-cell communication patterns, revealing regulatory networks underlying the phase transition. This work represents the first single-nucleus and spatial transcriptomic atlas of loquat shoot apices and provides a valuable reference for future studies in perennial woody species.

Decoding Specialized Cell Functions in Leaves

Specialized metabolites, such as artemisinin in Artemisia annua, are often produced by a small number of highly specialized cell types that are typically absent in model plants. This makes them particularly challenging to study using single-cell data alone.

Zhang et al. combined single-cell and spatial transcriptomics to construct a high-resolution atlas of glandular secretory trichomes (GSTs). By incorporating spatial information, the study showed that only six secretory cells within a 10-cell GST are mainly responsible for artemisinin biosynthesis and secretion. This precise localization of metabolic activity highlights how spatial transcriptomics can reveal functional differences within seemingly uniform structures, enabling a deeper understanding of specialized metabolism.

Deciphering Molecular Networks During Inflorescence Development

In crops such as wheat, developmental complexity directly influences yield. Zhang et al. constructed a single-cell-resolution spatial transcriptomic atlas of wheat spike development, covering five developmental stages across 16 tissue sections. The dataset includes over 53,000 cells, with a median of 724 genes detected per cell, providing a highly detailed view of tissue organization throughout spike development.

Using this spatially resolved dataset, the researchers uncovered cell-type-specific regulatory and metabolic patterns that contribute to spike architecture and grain number. Notably, rachis cells were identified as a key hub for nutrient and energy distribution during development, highlighting their important role in supporting yield formation. This study illustrates how spatial transcriptomics can connect tissue organization with agriculturally relevant traits.

Why Spatial Context Matters for Plant Research

Across these studies, a consistent message emerges: spatial information is not merely complementary; it is essential, especially for non-model plant species. Spatial transcriptomics enables researchers to:

• Resolve gene expression within intact tissue architecture
• Identify functionally distinct cell populations without relying solely on prior marker information
• Map developmental trajectories and regulatory interactions in situ
• Link cellular organization to physiological traits and metabolite production

By integrating spatial data with single-cell approaches, researchers can move beyond descriptive cell clustering toward a more mechanistic understanding of plant development and function.

Empowering Plant Research with Spatial Transcriptomics

At BMKGENE, our spatial transcriptomics services are designed to support a wide range of plant tissues, including structurally complex and non-model species. By combining optimized sample preparation, high-resolution sequencing, and integrative bioinformatics analysis, we help researchers uncover spatially resolved insights that are otherwise difficult to access.

As plant science continues to expand beyond traditional model systems, the ability to observe gene expression in its native tissue context will be key to unlocking new discoveries in development, metabolism, and crop improvement.

References

1. Lv, K., Liu, N., Niu, Y., et al. Spatial transcriptome analysis reveals de novo regeneration of poplar roots. Horticulture Research, 11(11), uhae237 (2024). https://doi.org/10.1093/hr/uhae237
2. Zhao, C., Huang, J., Jiang, Y., et al. A single-nucleus and spatial transcriptomic atlas of the shoot apex reveals insights into the vegetative-to-reproductive transition in loquat. Journal of Integrative Agriculture (2025). https://doi.org/10.1016/j.jia.2025.12.031
3. Zhang, M., Li, M., An, Y., et al. Single-nucleus transcriptomics reveal the morphogenesis and artemisinin biosynthesis in Artemisia annua glandular trichomes. Nature Communications, 16, 8646 (2025). https://doi.org/10.1038/s41467-025-63770-y
4. Zhang, X., Wang, Y., Song, X., et al. A single-cell-resolution spatial transcriptomic atlas decodes wheat spike development and yield potential. Molecular Plant, 19(2), 402–424 (2026). https://doi.org/10.1016/j.molp.2025.12.020