RNAi and genome editing of sugarcane: Progress and prospects

生物 基因组编辑 RNA干扰 功能基因组学 生物技术 基因组 计算生物学 基因沉默 基因 分子育种 清脆的 遗传学 基因组学 核糖核酸
作者
Eleanor J. Brant,Evelyn Zuniga‐Soto,Fredy Altpeter
出处
期刊:Plant Journal [Wiley]
卷期号:121 (5): e70048-e70048 被引量:14
标识
DOI:10.1111/tpj.70048
摘要

SUMMARY Sugarcane, which provides 80% of global table sugar and 40% of biofuel, presents unique breeding challenges due to its highly polyploid, heterozygous, and frequently aneuploid genome. Significant progress has been made in developing genetic resources, including the recently completed reference genome of the sugarcane cultivar R570 and pan‐genomic resources from sorghum, a closely related diploid species. Biotechnological approaches including RNA interference (RNAi), overexpression of transgenes, and gene editing technologies offer promising avenues for accelerating sugarcane improvement. These methods have successfully targeted genes involved in important traits such as sucrose accumulation, lignin biosynthesis, biomass oil accumulation, and stress response. One of the main transformation methods—biolistic gene transfer or Agrobacterium ‐mediated transformation—coupled with efficient tissue culture protocols, is typically used for implementing these biotechnology approaches. Emerging technologies show promise for overcoming current limitations. The use of morphogenic genes can help address genotype constraints and improve transformation efficiency. Tissue culture‐free technologies, such as spray‐induced gene silencing, virus‐induced gene silencing, or virus‐induced gene editing, offer potential for accelerating functional genomics studies. Additionally, novel approaches including base and prime editing, orthogonal synthetic transcription factors, and synthetic directed evolution present opportunities for enhancing sugarcane traits. These advances collectively aim to improve sugarcane's efficiency as a crop for both sugar and biofuel production. This review aims to discuss the progress made in sugarcane methodologies, with a focus on RNAi and gene editing approaches, how RNAi can be used to inform functional gene targets, and future improvements and applications.
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