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Tian J, Tang Z, Niu R, Zhou Y, Yang D, Chen D, Luo M, Mou R, Yuan M, Xu G. Engineering disease-resistant plants with alternative translation efficiency by switching uORF types through CRISPR. Sci China Life Sci 2024:10.1007/s11427-024-2588-9. [PMID: 38679667 DOI: 10.1007/s11427-024-2588-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 04/10/2024] [Indexed: 05/01/2024]
Abstract
Engineering disease-resistant plants can be a powerful solution to the issue of food security. However, it requires addressing two fundamental questions: what genes to express and how to control their expressions. To find a solution, we screen CRISPR-edited upstream open reading frame (uORF) variants in rice, aiming to optimize translational control of disease-related genes. By switching uORF types of the 5'-leader from Arabidopsis TBF1, we modulate the ribosome accessibility to the downstream firefly luciferase. We assume that by switching uORF types using CRISPR, we could generate uORF variants with alternative translation efficiency (CRISPR-aTrE-uORF). These variants, capable of boosting translation for resistance-associated genes and dampening it for susceptible ones, can help pinpoint previously unidentified genes with optimal expression levels. To test the assumption, we screened edited uORF variants and found that enhanced translational suppression of the plastic glutamine synthetase 2 can provide broad-spectrum disease resistance in rice with minimal fitness costs. This strategy, which involves modifying uORFs from none to some, or from some to none or different ones, demonstrates how translational agriculture can speed up the development of disease-resistant crops. This is vital for tackling the food security challenges we face due to growing populations and changing climates.
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Affiliation(s)
- Jingjing Tian
- National Key Laboratory of Crop Genetic Improvement, National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhijuan Tang
- State Key Laboratory of Hybrid Rice, Institute for Advanced Studies (IAS), Wuhan University, Wuhan, 430072, China
| | - Ruixia Niu
- State Key Laboratory of Hybrid Rice, Institute for Advanced Studies (IAS), Wuhan University, Wuhan, 430072, China
| | - Yulu Zhou
- State Key Laboratory of Hybrid Rice, Institute for Advanced Studies (IAS), Wuhan University, Wuhan, 430072, China
| | - Dan Yang
- National Key Laboratory of Crop Genetic Improvement, National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Dan Chen
- National Key Laboratory of Crop Genetic Improvement, National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Ming Luo
- State Key Laboratory of Hybrid Rice, Institute for Advanced Studies (IAS), Wuhan University, Wuhan, 430072, China
| | - Rui Mou
- State Key Laboratory of Hybrid Rice, Institute for Advanced Studies (IAS), Wuhan University, Wuhan, 430072, China
| | - Meng Yuan
- National Key Laboratory of Crop Genetic Improvement, National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China.
- Hubei Hongshan Laboratory, Wuhan, 430070, China.
| | - Guoyong Xu
- State Key Laboratory of Hybrid Rice, Institute for Advanced Studies (IAS), Wuhan University, Wuhan, 430072, China.
- Hubei Hongshan Laboratory, Wuhan, 430070, China.
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Wang J, Liu J, Guo Z. Natural uORF variation in plants. Trends Plant Sci 2024; 29:290-302. [PMID: 37640640 DOI: 10.1016/j.tplants.2023.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 07/04/2023] [Accepted: 07/19/2023] [Indexed: 08/31/2023]
Abstract
Taking advantage of natural variation promotes our understanding of phenotypic diversity and trait evolution, ultimately accelerating plant breeding, in which the identification of causal variations is critical. To date, sequence variations in the coding region and transcription level polymorphisms caused by variations in the promoter have been prioritized. An upstream open reading frame (uORF) in the 5' untranslated region (5' UTR) regulates gene expression at the post-transcription or translation level. In recent years, studies have demonstrated that natural uORF variations shape phenotypic diversity. This opinion article highlights recent researches and speculates on future directions for natural uORF variation in plants.
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Affiliation(s)
- Jiangen Wang
- Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Juhong Liu
- Fuzhou Institute for Data Technology Co., Ltd., Fuzhou 350207, China
| | - Zilong Guo
- Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
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Bai Y, Wang H, Zhu K, Cheng ZM. The dynamic arms race during the early invasion of woodland strawberry by Botrytis cinerea revealed by dual dense high-resolution RNA-seq analyses. Hortic Res 2023; 10:uhad225. [PMID: 38143486 PMCID: PMC10745266 DOI: 10.1093/hr/uhad225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/29/2023] [Indexed: 12/26/2023]
Abstract
Necrotrophic pathogens replicate massively upon colonizing plants, causing large-scale wilting and death of plant tissues. Understanding both mechanisms of pathogen invasion and host response processes prior to symptom appearance and their key regulatory networks is therefore important for defense against pathogen attack. Here, we investigated the mechanisms of interaction between woodland strawberry (Fragaria vesca) leaves and gray mold pathogen (Botrytis cinerea) at 14 infection time points during the first 12 hours of the infection period using a dense, high-resolution time series dual transcriptomic analysis, characterizing the arms race between strawberry F. vesca and B. cinerea before the appearance of localized lesions. Strawberry leaves rapidly initiated strong systemic defenses at the first sign of external stimulation and showed lower levels of transcriptomic change later in the infection process. Unlike the host plants, B. cinerea showed larger-scale transcriptomic changes that persisted throughout the infection process. Weighted gene co-expression network analysis identified highly correlated genes in 32 gene expression modules between B. cinerea and strawberry. Yeast two-hybrid and bimolecular fluorescence complementation assays revealed that the disease response protein FvRLP2 from woodland strawberry interacted with the cell death inducing proteins BcXYG1 and BcPG3 from B. cinerea. Overexpression of FvRLP2 in both strawberry and Arabidopsis inhibited B. cinerea infection, confirming these genes' respective functions. These findings shed light on the arms race process by which B. cinerea invades host plants and strawberry to defend against pathogen infection.
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Affiliation(s)
- Yibo Bai
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Ministry of Agriculture; Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Haibin Wang
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Kaikai Zhu
- Co-innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu 210037, China
| | - Zong-Ming Cheng
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
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Zhao Y, Zhu X, Chen X, Zhou JM. From plant immunity to crop disease resistance. J Genet Genomics 2022; 49:693-703. [PMID: 35728759 DOI: 10.1016/j.jgg.2022.06.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/07/2022] [Accepted: 06/08/2022] [Indexed: 11/28/2022]
Abstract
Plant diseases caused by diverse pathogens lead to serious reduction in crop yield and threaten food security worldwide. Genetic improvement of plant immunity is considered as the most effective and sustainable approach to control crop diseases. In the last decade, our understanding of plant immunity at both molecular and genomic levels has improved greatly. Combined with advances in biotechnologies, particularly CRISPR/Cas9-based genome editing, we can now rapidly identify new resistance genes and engineer disease resistance crop plants like never before. In this review, we summarize the current knowledge of plant immunity and outline existing and new strategies for disease resistance improvement in crop plants. We also discuss existing challenges in this field and suggest directions for future studies.
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Affiliation(s)
- Yan Zhao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaobo Zhu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University at Wenjiang, Chengdu Sichuan 611130, China
| | - Xuewei Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University at Wenjiang, Chengdu Sichuan 611130, China.
| | - Jian-Min Zhou
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing 100049, China; Hainan Yazhou Bay Seed Laboratory, Sanya, Hainai 572025, China.
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