Jul 2026· Journal of Experimental Botany· 0 citations
Medicine
TL;DR
This Expert Views article highlights recent conceptual and technical developments that illustrate how single-cell atlases have transformed studies of root development and highlights 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.
Abstract
Plant development arises from the 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. Resolving gene expression at cellular resolution is therefore essential for understanding how developmental decisions are made, integrated, and propagated during organ growth. The Arabidopsis 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 the construction of comprehensive cellular atlases that capture gene expression dynamics across cell identities and developmental trajectories. In this Expert Views 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 both 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.
It is argued that careful experimental design, robust data integration, and a clear understanding of cell identity are essential to obtain the full potential of plant single-cell and spatial omics in basic research and crop improvement.
L. De Veylder, Maite Saura-Sánchez, B. De Rybel et al.· The Plant Cell· 0 citations
It is argued that the next evolution of scRNA-seq must integrate three essential pillars: temporal dynamics, spatial information, and evolutionary conservation.
Shahab Ur Rehman, Rahmat Ali, Hosameldeen Mohamed Husien et al.· DNA and Cell Biology· 0 citations
This manuscript explores the current landscape of single-cell RNA sequencing (scRNA-seq), highlighting key studies that have leveraged this technology to advance biological understanding for clinical purposes through the construction of gene regulatory networks (GRNs) from single-cell transcriptomic data.
J. López-Castiblanco, L. López-Kleine, Yesid Cuesta-Astroz· Journal of Investigative Med...· 0 citations
This review synthesizes recent progress across diverse plant species and tissues, showing that gene expression is not only cell-type specific but also tightly organized by position within organs and developmental niches, establishing spatial gene expression as a fundamental organizing principle of plant development and...
Yiqing Wang, Zhengzhi Tan, Nicole A Freeman et al.· Plant Communications· 0 citations
A "cellular spatiotemporal dogma" governs the zygote's programmed development into a complete plant and its adaptation to various environmental stresses, representing the set of principles describing how gene expression, cell identity, and function are coordinated across physical spatial contexts and temporal developme...
The integrated Plant single-cell Database (iPscDB), an integrated and multifunctional platform that facilitates the integration and analysis of plant single-cell data, is presented, offering a practical and accessible resource for researchers with diverse technical backgrounds.
Peng Lu, Jing-Jing Jin, Jie-Meng Tao et al.· Nucleic Acids Research· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.