Objective Using cultivar 85-5 as the experimental material, Stereo-seq spatial transcriptomics technology was employed to analyze the in situ gene expression patterns of tuberous roots, thereby revealing the spatial heterogeneity of gene expression in root cells. Methods The optimal permeabilization duration was determined by fluorescence intensity and grayscale quantification, and the best bin resolution was identified by comparing gene detection efficiency and cell clustering performance across multiple parameter groups. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) were used for cell clustering. Cluster-specific differentially expressed genes (DEGs) were identified using the Seurat package, and qRT-PCR was performed to validate the reliability of spatial transcriptomic data. Results The optimal permeabilization time for frozen sections of R. glutinosa tuberous roots is 18 min, and a bin size of 200 is more suitable for the analysis of macroscopic cell populations in R. glutinosa tuberous roots. Root cells of R. glutinosa were classified into five distinct populations with unique spatial localization via PCA and UMAP. Specifically, clusters 1 and 2 were predominantly distributed in the phloem, cluster 3 in the periderm, and cluster 4 in the cambium. The qRT-PCR verified that gene DH2020-016897 was specifically expressed in the periderm, whereas DH2020-009767 and DH2020-009768 exhibited predominant expression in the cambium. Conclusion In this study, we established a high-resolution spatial transcriptomic atlas of R. glutinosa tuberous roots, delineating spatial distribution patterns of individual cell clusters and the expression profiles of key genes. These findings provide a fundamental resource for exploring tuberous roots development, secondary metabolite biosynthesis, and spatially resolved molecular regulatory networks underlying stress responses in R. glutinosa.

Rehmannia glutinosa Libosch.  /  tuberous root  /  spatial transcriptomics  /  cell cluster  /  real-time quantitative PCR