ASRSSTA: Arabidopsis Shoot Regeneration Single-cell Spatiotemporal Transcriptomic Atlas(Dataset ID: STDS0000237)
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Summary:
The gradual transition of pluripotent callus from root to shoot identity drives shoot regeneration. However, cell heterogeneity and their spatial organization during this cell-fate transition remain unclear, hindering our mechanistic understanding and utilization of plant regeneration. Here, we presented the first comprehensive time-series transcriptomic landscape of the shoot regeneration process at tissue, single-cell, and spatial resolution. During the early stage, we identified a crucial transition cell type, developing SAM (dSAM), which showed distinct dual root-shoot meristem characteristics. Further spatial transcriptomics analysis revealed that dSAM was derived from the QC-like cell (QCL) and eventually differentiated into a shoot system. Moreover, we found that PDL and QCL cells acted as dSAM surrounding barriers and created an isolated cytokinin-rich environment, facilitating shoot cell-fate establishment and development. Finally, the activation of epidermal development regulators ATML1 and MYB31 facilitated dSAM transition. These findings provide new perspectives to understand cell diversity and spatial organization during shoot regeneration.Overall design:
ASRSSTA database contains 3 part of transcriptomic atlas: 1) bulk RNA-seq data, containing 11 time points from SIM 0 to SIM 18, covered the whole process of shoot regeneration; 2) snRNA-seq data, covering 6 time points from SIM 4 to SIM 16, contained 79,139 single-nucleus transcriptomes from root-drived callus and 90,569 single-nucleus transcriptomes from cotyledon-drived callus; 3) Stereo-seq data, covering a total of 14 callus tissue sections with 8 sections in SIM 6, 4 sections in SIM 8 and 2 sections in SIM 10.Technology:
Stereo-Seq, scRNA, RNA-seq
Platform:
DNBSEQ-T10
Species:
Arabidopsis thaliana
Tissues:
Callus
Submission date: 2024-02-05Update date: 2024-03-08
Sample number: 48Section number: 14
Contributors
qinchao
Contact: qinchao@genomics.cn
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