Single-cell genomics is rapidly reshaping plant biology, yet broader adoption is limited by plant-specific technical constraints, fragmented tools, and inconsistent analytical practices. Here we report outcomes from the 2025 Summer Workshop for Plant Single-Cell Analysis, which convened researchers to define community needs and design shared solutions. Participants identified five priority challenge areas: (1) improving data quality through imputation, simulation, and deep generative modeling; (2) developing automated, phylogenetically aware cell-type annotation frameworks; (3) reconstructing developmental trajectories and gene regulatory networks from single-cell and single-nucleus profiles; (4) creating visualization approaches that embed transcriptional states into anatomically grounded plant organ contexts; and (5) using Artificial Intelligence (AI) agents and foundation models to orchestrate end-to-end single-cell workflows. In response, we established PlantSCHub, a community-curated web portal that aggregates protocols, datasets, and tutorials to support reproducible plant single-cell analysis. We outline conceptual roadmaps for cross-species integration, multimodal trajectory and Gene Regulatory Networks (GRNs) inference, spatially anchored visualization, and AI scientist agents that dynamically coordinate analytical tools and literature. We discuss both scRNA-seq and scATAC-seq that are important for regulatory inference and cross-species analysis. Together, these efforts aim to transform isolated plant single-cell studies into an interoperable, evolving ecosystem that accelerates discovery and crop improvement.
Haghan et al. (2026) studied this question.