Project name: 水稻种胚萌发过程时空图谱

Description: Characterizing cell features of germinating seeds is essential for understanding the complex biological functions of different embryonic cells in regulating seed vigor and seedling establishment. In this study, we performed spatially enhanced resolution omics (Stereo-seq) and single-cell RNA sequencing (scRNA-seq) to capture spatially resolved single-cell transcriptomes of germinating rice embryos. An automated cell-segmentation model was developed based on deep-learning to accommodate the analysis requirements. The spatial transcriptome revealed known and novel cell types of rice embryo, including two new scutellum cell types. The temporal transcriptome revealed the expression dynamics of genes in different types of embryonic cells during the time course of seed germination and the key genes, particularly related to nutrient metabolism and biosynthesis and signaling of phytohormonesand were reprogrammed in a cell-type-specific manner. Our study provides a panoramic spatiotemporal transcriptome of rice embryo and a novel methodology for exploring the roles of different embryonic cells in seed germination.

Data type: Raw sequence reads

Sample scope: Other

Relevance: Agricultural

Release date: 2024-01-01

Last updated: 2024-01-01

Data size: 263.07GB