Improving the Traits of <em>Perilla frutescens</em> (L.) Britt Using Gene Editing Technology
2024
Sivabalan Karthik | Jia Chae | Seong Ju Han | Jee Hye Kim | Hye Jeong Kim | Young-Soo Chung | Hyun Uk Kim | Jae Bok Heo
Plant breeding has evolved significantly over time with the development of transformation and genome editing techniques. These new strategies help to improve desirable traits in plants. Perilla is a native oil crop grown in Korea. The leaves contain many secondary metabolites related to whitening, aging, antioxidants, and immunity, including rosmarinic acid, vitamin E, luteolin, anthocyanins, and beta-carotene. They are used as healthy and functional food ingredients. It is an industrially valuable cosmetics crop. In addition, perilla seeds are rich in polyunsaturated fatty acids, such as α-linolenic acid and linoleic acid. They are known to be effective in improving neutral lipids in the blood, improving blood circulation, and preventing dementia and cardiovascular diseases, making them excellent crops whose value can be increased through improved traits. This research will also benefit perilla seeds, which can increase their stock through various methods, such as the increased production of functional substances and improved productivity. Recently, significant attention has been paid to trait improvement research involving gene-editing technology. Among these strategies, CRISPR/Cas9 is highly adaptable, enabling accurate and efficient genome editing, targeted mutagenesis, gene knockouts, and the regulation of gene transcription. CRISPR/Cas9-based genome editing has enormous potential for improving perilla; however, the regulation of genome editing is still at an early stage. Therefore, this review summarizes the enhancement of perilla traits using genome editing technology and outlines future directions.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Directory of Open Access Journals
Découvrez la collection de ce fournisseur de données dans AGRIS