A Comprehensive Epidermal Map from a Poplar Single-Cell Shoot Atlas Reveals New Trichome-Specific Genes

Authors

Giabardo, A., Wood, J. C., Pandey, S. P., Brose, J., Cloud, S. S., Hamilton, J. P., Heise, A. D., Loya, R., Luo, Z., Mailloux, K., Vaillancourt, B., Wyneken, D. L. W., Schmitz, R. J., Urbanowicz, B. R., Tsai, C.-J., Buell, C. R.

Abstract

Poplar (Populus spp.) is a model system for tree biology. Specifically, P. tremula x P. alba INRA 717-1B4 (hereafter "poplar 717") has become an important platform for functional genomics and synthetic biology due to its rapid growth and ease of transgenesis. Here, we present a single-cell RNA-seq atlas of the poplar 717 shoot, including apical meristem, primary and secondary stems, and three stages of leaf development. Analysis of ca. 159,000 cells resolved 40 transcriptionally distinct clusters representing 7 major cell types, providing a high-resolution view of shoot development and tissue organization. We focused on the epidermis which constituted >15% of cells in the shoot atlas for in-depth characterization of epidermal heterogeneity. By integrating known marker genes with transcriptomic signatures consistent with established poplar leaf phytochemistry, we annotated epidermal cell subclusters corresponding to developmental stages, spatial location, and specialized cell types, including a distinct population of non-glandular trichomes. Coupling the single-cell RNA-seq atlas with bulk transcriptome data from glabrous mutants enabled the identification of novel trichome markers. Experimental validation of a representative trichome-specific promoter established a tool with potential to support cell type-targeted-metabolic engineering. We provide the poplar 717 atlas to the community through the BioPoplar Atlas Viewer (http://bio-poplar-atlas.com), providing a platform to explore the poplar transcriptome at single-cell resolution and a foundation for data-driven cell type-aware genetic engineering strategies in poplar.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 10 Jul 2026.

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