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Updated: Jan 24, 2026

Isolation and Transcriptome Analysis of Plant Cell Types

Isolation and Transcriptome Analysis of Plant Cell Types

Published on: April 7, 2023

Decoding plant cell heterogeneity and dynamics across responses, development, to evolution with single-cell

Dongbo Shi¹, Keiko Sugimoto², Kenji Fukushima³

¹RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa, Japan.

Current Opinion in Plant Biology

|January 22, 2026

Summary

Single-cell technologies reveal plant cell identity is dynamic and context-dependent, moving beyond static classifications. Integrating multiomic and spatial data captures cellular plasticity from stress responses to evolution.

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Published on: October 25, 2018

Area of Science:

Plant Biology
Genomics
Cellular Biology

Background:

Traditional plant cell classification relied on static, morphology-based methods.
These methods masked cellular heterogeneity and dynamic responses within tissues.

Purpose of the Study:

To redefine plant cell identity using advanced single-cell technologies.
To explore cellular heterogeneity, developmental trajectories, and responses to environmental cues.

Main Methods:

Single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq).
Integration of scRNA-seq with spatial transcriptomics and live imaging.
Comparative single-cell analyses across species, employing computational strategies for cross-species alignment.

Main Results:

Revealed hidden cellular heterogeneity and developmental trajectories in plant tissues.
Identified transient, spatially restricted cell states induced by environmental stimuli.
Demonstrated conserved cell-type groups and lineage-specific innovations across plant evolution.

Conclusions:

Plant cell identity is dynamic, context-dependent, and exists on continuous spectra.
Future frameworks should integrate discrete labels with state-based descriptions and multiomic spatial data.
This approach captures the full plasticity of plant cells across various timescales.