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Plant Cell & Environment
Article . 2022 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Engineering effector‐triggered immunity in rice: Obstacles and perspectives

Authors: Kieu Thi Xuan Vo; Qi Yi; Jong‐Seong Jeon;

Engineering effector‐triggered immunity in rice: Obstacles and perspectives

Abstract

AbstractImproving rice immunity is one of the most effective approaches to reduce yield loss by biotic factors, with the aim of increasing rice production by 2050 amidst limited natural resources. Triggering a fast and strong immune response to pathogens, effector‐triggered immunity (ETI) has intrigued scientists to intensively study and utilize the mechanisms for engineering highly resistant plants. The conservation of ETI components and mechanisms across species enables the use of ETI components to generate broad‐spectrum resistance in plants. Numerous efforts have been made to introduce new resistance (R) genes, widen the effector recognition spectrum and generate on‐demand R genes. Although engineering ETI across plant species is still associated with multiple challenges, previous attempts have provided an enhanced understanding of ETI mechanisms. Here, we provide a survey of recent reports in the engineering of rice R genes. In addition, we suggest a framework for future studies of R gene−effector interactions, including genome‐scale investigations in both rice and pathogens, followed by structural studies of R proteins and effectors, and potential strategies to use important ETI components to improve rice immunity.

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Keywords

Crops, Agricultural, Oryza, Plant Immunity, Genetic Engineering, Plant Diseases, Signal Transduction

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
hybrid