Cross-Species Plant Single-Cell Analysis: Community Challenges and Shared Solutions

Area of Science:

• Plant Biology
• Genomics
• Bioinformatics

Background:

• Single-cell genomics is revolutionizing plant biology but faces adoption barriers due to technical challenges, fragmented tools, and inconsistent analysis.
• Plant-specific constraints hinder the broader application of single-cell genomics techniques.

Purpose of the Study:

• To address community needs and design shared solutions for plant single-cell analysis.
• To establish frameworks for improving data quality, cell-type annotation, developmental trajectory reconstruction, visualization, and AI-driven workflows.

Main Methods:

• Convened researchers in the 2025 Summer Workshop for Plant Single-Cell Analysis.
• Identified five priority challenge areas in plant single-cell data analysis.
• Established PlantSCHub, a community-curated web portal for protocols, datasets, and tutorials.

Main Results:

• Defined priority areas: data quality improvement, automated annotation, trajectory/GRN inference, anatomical visualization, and AI-orchestrated workflows.
• Launched PlantSCHub to support reproducible plant single-cell analysis.
• Outlined roadmaps for cross-species integration, multimodal inference, spatial visualization, and AI scientist agents.

Conclusions:

• The developed solutions and PlantSCHub aim to create an interoperable ecosystem for plant single-cell studies.
• These efforts will accelerate scientific discovery and enhance crop improvement through advanced genomics and AI.
• Integration of scRNA-seq and scATAC-seq data is crucial for regulatory inference and cross-species analysis.