Acta Botanica YunnanicaBioinformaticsPeer-reviewed journal article
Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification
Shanni CaoiD, Xue Fei ZhaoiD, Zhuojin Li, Ranran YuiD, Yuqi LiiD, Xinkai ZhouiD, Wenhao YaniD, Dijun CheniD, Chao HeiD
Abstract
Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors (TFs) in intricate regulatory networks at a cell-type specific manner. Here we presented a reference single-cell transcriptomic atlas of Arabidopsis seedlings by integration of 40 published scRNA-seq datasets from representative tissues as well as the entire under- and above-ground parts. We identified 34 distinct cell types or states, largely expanding our current view of plant cell compositions. We then mapped the developmental trajectory of root-shoot lineage separation and identified differential gene expression programs that may regulate the cell fate determination of under- and above-ground organs. Lastly, we systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordination manner to control cell-type specific gene expression. Taken together, our study not only offers a valuable resource plant cell atlas exploration but also provides molecular insights into gene-regulatory programs that determines organ specify, particularly the differentiation between root and shoot.
- organism: Arabidopsis
- assay: scRNA-seq
- research focus: clustering
- research focus: trajectory inference
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 7
- FWCI
- 0.82
- Field percentile
- top 33%
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