Single-cell atlases as meta-analytic compasses for developmental biology: a case study using the Arabidopsis root

Abstract

Plant development requires coordinated execution of gene regulatory programs across diverse cell types. While classical genetic and genomic approaches have revealed many of the genes required for plant growth and patterning, these methods often average signals across heterogeneous tissues, thereby obscuring how regulatory programs operate within individual cells. Therefore, resolving gene expression at the cellular level is essential for understanding how developmental decisions are made, integrated, and propagated during organ growth. The Arabidopsis thaliana root, with its simple anatomy and invariant cell lineages, provides an ideal system for addressing these questions. Recent advances in single-cell and single-nucleus transcriptomics have enabled construction of comprehensive cellular atlases that capture gene expression dynamics across cell identities and developmental trajectories. In this Expert View article, we highlight recent conceptual and technical developments that illustrate how single-cell atlases have transformed studies of root development. We emphasize how these atlases serve as community resources to inform the interpretation of new datasets, including those generated from mutants and in response to perturbation, as well as provide a platform for meta-analysis to initiate new studies. Using auxin signaling as a meta-analysis case study, we demonstrate how legacy transcriptomic data can be reinterpreted within a cell lineage-resolved framework. Finally, we highlight how spatial transcriptomics and rigorous data-sharing practices will extend cellular atlases across tissues and species, thereby enabling increasingly precise strategies for understanding and engineering plant growth and resilience.