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PlantST: Unraveling Plant Tissue Heterogeneity and Developmental Trajectories via Multimodal Graph Contrastive
Xuemei Guan1, Dezhi Zhi1, Liuyan Wang1
1College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China.
Summary
PlantST is a new computational framework for plant spatial transcriptomics (ST). It analyzes complex plant tissues, revealing developmental patterns and spatial organization for better biological insights.
Area of Science:
- Plant biology
- Genomics
- Bioinformatics
Background:
- Spatial transcriptomics (ST) is crucial for understanding tissue heterogeneity and development.
- Existing ST computational methods struggle with complex plant tissue architectures like vascular bundles and floral organs.
- This limits the application of ST in plant science.
Purpose of the Study:
- To develop a computational framework, PlantST, specifically designed for plant spatial omics data.
- To enable accurate analysis of complex plant tissue structures and developmental processes using ST.
- To overcome limitations of existing methods in plant ST analysis.
Main Methods:
- PlantST integrates spatial and transcriptional data.
- It identifies complex spatial domains within plant tissues.
- It reconstructs continuous developmental trajectories reflecting physical growth.
Main Results:
- PlantST was evaluated on Populus stem nodes and orchid floral organs.
- It demonstrated higher biological resolution compared to existing methods.
- It accurately resolved narrow functional boundaries (e.g., cambium-xylem-phloem) and developmental gradients.
Conclusions:
- PlantST effectively captures biologically meaningful spatial organization and developmental dynamics in complex plant tissues.
- It provides a robust analytical framework for plant ST datasets.
- It lays the methodological foundation for future high-resolution plant spatial atlases.
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