Understanding the Cellular Spatiotemporal Dogma by Spatial and Single-cell Omics

Clicks: 21
ID: 327046
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #160 of 406 articles by views in Journal of experimental botany

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 406 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The biological complexity of plants arises from highly coordinated cellular activities. We propose that 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 developmental progressions. Historically, our understanding of this dogma remains limited because traditional bulk tissue sequencing provides only a homogenized average of gene expression, making it challenging to isolate and resolve functionally significant but rare cell populations, such as the root quiescent center. However, the "resolution revolution" driven by single-cell and spatially resolved omics has dismantled these barriers to reveal cellular niches: local microenvironments where neighboring cells interact and coordinate function. Here, we firstly synthesize the current landscape of single-cell and spatial multi-omics technologies, highlighting how they bypass botanical barriers like the cell wall. Next, we detail how these technologies decode plant cellular characteristics, from defining novel cell subtypes to reconstructing dynamic trajectories and identifying pan-cell populations that remain ultra-conserved across hundreds of millions of years of evolution. Finally, we discuss the paradigm shift toward Large Foundation Models (FMs), which are computational paradigms that conceptualize biological data as a structured language to enable predictive modeling. Despite challenges such as data scarcity and phylogenetic bias, the integration of high-resolution omics with AI-driven intelligence is paving the way for a "Virtual Plant Cell, " a comprehensive digital model capable of simulating and predicting cellular responses to genetic and environmental perturbations, offering a transformative foundation for smart breeding and climate-resilient agriculture.
Reference Key
openalex_W7204936564 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chao Qin, Ziyi Zhang, Keke Xia
Are you one of these authors? Claim your profile
Journal Journal of experimental botany
Year 2026
DOI
10.1093/jxb/erag430
URL
https://doi.org/10.1093/jxb/erag430
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.