| Accession |
PRJCA011425 |
| Title |
Spatiotemporal transcriptomic atlas of planarian characterizes spatial dynamics of regeneration |
| Relevance |
Model organism |
| Data types |
Raw sequence reads
|
| Organisms |
Schmidtea mediterranea
|
| Description |
The whole-body regeneration of planarian is a natural wonder that remains elusive. Spatially resolved transcriptomic (ST) technologies are promising tools to solve this mystery. Here, we presented the comprehensive three-dimensional (3D) spatiotemporal transcriptome landscape of planarian regeneration with distinct spatial sub-structures. The spatial distribution of cells during regeneration helps to understand the heterogeneity of planarian cells and identify a variety of gene expression modules. We identified 64 cell subpopulations and a novel pluripotent neoblast subtype with osr2 and 2dbd expression. Depletion of this novel neoblast made planarian more susceptible to sub-lethal radiation than that of the control group. Furthermore, we unveiled the gene modules that affect specific tissue development, including anterior, posterior polarity and neoblast-enriched modules. Moreover, functional analysis of hub genes identified by ST modules, such as plk1 and hes2, confirmed their important role in regeneration and demonstrated a powerful tool for screening novel regeneration-related and homeostasis genes. Last but not least, we compiled a publicly available online spatiotemporal analysis resource of planarian regeneration to facilitate further work. |
| Sample scope |
Spatial transcriptome |
| Release date |
2023-04-27 |
| Publication |
| PubMed ID |
Article title |
Journal name |
DOI |
Year |
| 37268637
|
Spatiotemporal transcriptomic atlas reveals the dynamic characteristics and key regulators of planarian regeneration
|
Nature Communications
|
10.1038/s41467-023-39016-0
|
2023
|
| 39439006
|
STASCAN deciphers fine-resolution cell distribution maps in spatial transcriptomics by deep learning
|
Genome Biology
|
10.1186/s13059-024-03421-5
|
2024
|
|
|
| Grants |
| Agency |
program |
Grant ID |
Grant title |
| No funding support
|
|
|
|
|
|
| Submitter |
yang
ying (yingyang@big.ac.cn)
|
| Organization |
Beijing Institute of Genomics |
| Submission date |
2022-08-24 |
