Deciphering plant–pathogen interaction with single‐cell omics

Abstract Plants are persistently exposed to a broad spectrum of pathogens, such as bacteria, fungi, oomycetes, and viruses, throughout their life cycle. Upon infection, plants activate defense‐related genes to limit damage and preserve reproductive fitness. In recent decades, most studies focused on elucidating plant immune responses at tissue or systemic level, whereas the cell‐type‐specific regulatory dynamics and cell heterogeneity during infection remain poorly understood due to methodological constraints. Recent advances in single‐cell omics have facilitated the precise decoding of cell heterogeneity during pathogen challenges. This review summarizes the technological developments in plant single‐cell omics and highlights their unique advantages for investigating nearly all stages of plant–pathogen interactions. From initial pathogen infection to the onset of local and systemic host resistance, single‐cell omics enables the identification of susceptible cell types, the discovery of cell‐type‐specific immune responses, the dissection of intercellular communication during pathogen invasion, the analysis of pathogen‐induced cell differentiation trajectories, and the spatial mapping of immune responses, with these details that are often masked in bulk analyses. By precisely capturing cellular dynamics and developmental trajectories in infected hosts, single‐cell omics is profoundly reshaping our understanding of plant–pathogen interactions. Furthermore, we propose a potential strategy for breeding crop varieties with cell‐type‐specific resistance.

Authors

Institutions

Publication Details

Journal
New plant protection.
Published
2026-09-15
DOI
https://doi.org/10.1002/npp2.70056
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Deciphering plant–pathogen interaction with single‐cell omics

Lu Gan, Huaibing Jin, Wénwén Liú, Syed S. Zaidi
New plant protection.
Single-cell and spatial transcriptomics
article

Deciphering plant–pathogen interaction with single‐cell omics

Lu Gan, Huaibing Jin, Wénwén Liú, Syed S. Zaidi
article en

Abstract

Abstract Plants are persistently exposed to a broad spectrum of pathogens, such as bacteria, fungi, oomycetes, and viruses, throughout their life cycle. Upon infection, plants activate defense‐related genes to limit damage and preserve reproductive fitness. In recent decades, most studies focused on elucidating plant immune responses at tissue or systemic level, whereas the cell‐type‐specific regulatory dynamics and cell heterogeneity during infection remain poorly understood due to methodological constraints. Recent advances in single‐cell omics have facilitated the precise decoding of cell heterogeneity during pathogen challenges. This review summarizes the technological developments in plant single‐cell omics and highlights their unique advantages for investigating nearly all stages of plant–pathogen interactions. From initial pathogen infection to the onset of local and systemic host resistance, single‐cell omics enables the identification of susceptible cell types, the discovery of cell‐type‐specific immune responses, the dissection of intercellular communication during pathogen invasion, the analysis of pathogen‐induced cell differentiation trajectories, and the spatial mapping of immune responses, with these details that are often masked in bulk analyses. By precisely capturing cellular dynamics and developmental trajectories in infected hosts, single‐cell omics is profoundly reshaping our understanding of plant–pathogen interactions. Furthermore, we propose a potential strategy for breeding crop varieties with cell‐type‐specific resistance.

New plant protection.
Université de Bordeaux (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Biologie du Fruit et Pathologie (FR), Institute of Plant Protection (CN), Chinese Academy of Agricultural Sciences (CN)
National Natural Science Foundation of China, Agricultural Science and Technology Innovation Program
Responsible consumption and production, Zero hunger
Openalex Percentile: Top 18%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.