Development of an RNA virus vector for non-transgenic genome editing in tobacco and generation of berberine bridge enzyme-like mutants with reduced nicotine content

IF 4.6 4区 农林科学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Haiying Xiang, Binhuan Chen, Shuo Wang, Wanli Zeng, Jiarui Jiang, Weisong Kong, Haitao Huang, Qili Mi, Shuang Ni, Qian Gao, Zhenghe Li
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Abstract

Tobacco (Nicotiana tabacum) plants synthesize the psychoactive pyridine alkaloid nicotine, which has sparked growing interest in reducing nicotine levels through genome editing aiming at inactivating key biosynthetic genes. Although stable transformation-mediated genome editing is effective in tobacco, its polyploid nature complicates the complete knockout of genes and the segregation of transgenes from edited plants. In this study, we developed a non-transgenic genome editing method in tobacco by delivering the CRISPR/Cas machinery via an engineered negative-strand RNA rhabdovirus vector, followed by the regeneration of mutant plants through tissue culture. Using this method, we targeted six berberine bridge enzyme-like protein (BBL) family genes for mutagenesis, which are implicated in the last steps of pyridine alkaloid biosynthesis, in the commercial tobacco cultivar Hongda. We generated a panel of 16 mutant lines that were homozygous for mutations in various combinations of BBL genes. Alkaloid profiling revealed that lines homozygous for BBLa and BBLb mutations exhibited drastically reduced nicotine levels, while other BBL members played a minor role in nicotine synthesis. The decline of nicotine content in these lines was accompanied by reductions in anatabine and cotinine levels but increases in nornicotine and its derivative myosmine. Preliminary agronomic evaluation identified two low-nicotine lines with growth phenotypes comparable to those of wild-type plants under greenhouse and field conditions. Our work provides potentially valuable genetic materials for breeding low-nicotine tobacco and enhances our understanding of alkaloid biosynthesis.

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CiteScore
7.70
自引率
2.80%
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