An Optimized Editing Approach for Wheat Genes by Improving sgRNA Design and Transformation Strategies

Hexaploid wheat has a large genome, making it difficult for transgenes to produce phenotypes due to gene redundancy and tight linkage among genes. Multiple gene copies typically necessitate multiple targeting events during gene editing, followed by several generations of self-crossing to achieve homozygous genotypes. The high cost of transgenesis in wheat is another issue, which hinders the easy availability of gene-edited materials in wheat. In this study, we developed a comprehensive approach to improve wheat gene editing efficiency. First, we established a protoplast-based system to evaluate the relative efficiency of gene editing targets, which enabled the rapid and effective selection of optimal sgRNAs. We then compared two transformation strategies: biolistic bombardment and Agrobacterium-mediated transformation for generating edited wheat lines. Although biolistic bombardment showed higher initial editing efficiency, Agrobacterium-mediated transformation proved more effective for obtaining homozygous mutants. Notably, we discovered that deploying the same sgRNA through different vectors enhanced editing efficiency, whereas overlapping but distinct sgRNAs exhibited interference effects. Finally, we optimized the VITF-edit (virus-induced transgene free editing) technique using BSMV delivery to establish a relatively simple and easily applied wheat gene editing method for general laboratories.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-04-17
DOI
https://doi.org/10.3390/ijms26083796
Citations
1
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.81

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article

An Optimized Editing Approach for Wheat Genes by Improving sgRNA Design and Transformation Strategies

Zheng-Guang Yang, Rui‐xiang Zhang, Yunfei Zhang, Wei-Hang Sun et al.
1 citations
International Journal of Molecular Sciences
CRISPR and Genetic Engineering
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article

An Optimized Editing Approach for Wheat Genes by Improving sgRNA Design and Transformation Strategies

Zheng-Guang Yang, Rui‐xiang Zhang, Yunfei Zhang, Wei-Hang Sun, Kun‐Ming Chen, Wen-Ting Liu, Xiaodong Zhang, Binbin Li, Hao Yang, Zi Yang
article en
1 citations

Abstract

Hexaploid wheat has a large genome, making it difficult for transgenes to produce phenotypes due to gene redundancy and tight linkage among genes. Multiple gene copies typically necessitate multiple targeting events during gene editing, followed by several generations of self-crossing to achieve homozygous genotypes. The high cost of transgenesis in wheat is another issue, which hinders the easy availability of gene-edited materials in wheat. In this study, we developed a comprehensive approach to improve wheat gene editing efficiency. First, we established a protoplast-based system to evaluate the relative efficiency of gene editing targets, which enabled the rapid and effective selection of optimal sgRNAs. We then compared two transformation strategies: biolistic bombardment and Agrobacterium-mediated transformation for generating edited wheat lines. Although biolistic bombardment showed higher initial editing efficiency, Agrobacterium-mediated transformation proved more effective for obtaining homozygous mutants. Notably, we discovered that deploying the same sgRNA through different vectors enhanced editing efficiency, whereas overlapping but distinct sgRNAs exhibited interference effects. Finally, we optimized the VITF-edit (virus-induced transgene free editing) technique using BSMV delivery to establish a relatively simple and easily applied wheat gene editing method for general laboratories.

International Journal of Molecular SciencesVol. 26(8)
University of California, Riverside (US), Xinjiang Academy of Agricultural Sciences (CN), Ministry of Agriculture and Rural Affairs (CN), Northwest A&F University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shaanxi Province, Chinese Universities Scientific Fund
Openalex Percentile: Top 29%
CRISPR and Genetic Engineering
0.81
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