JOURNAL ARTICLE

NAC transcription factor SlNOR-like1 plays a dual regulatory role in tomato fruit cuticle formation.

  • Published In: Journal of Experimental Botany, 2024, v. 75, n. 7. P. 1903 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Liu, Gang-Shuai; Huang, Hua; Grierson, Donald; Gao, Ying; Ji, Xiang; Peng, Zhen-Zhen; Li, Hong-Li; Niu, Xiao-Lin; Jia, Wen; He, Jian-Lin; Xiang, Lan-Ting; Gao, Hai-Yan; Qu, Gui-Qin; Zhu, Hong-Liang; Zhu, Ben-Zhong; Luo, Yun-Bo; Fu, Da-Qi 3 of 3

Abstract

This article focuses on the role of the NAC transcription factor SlNOR-like1 in regulating tomato fruit cuticle development. Using CRISPR/Cas9-generated SlNOR-like1 knockout mutants (nor-like1), the study found that loss of SlNOR-like1 function leads to reduced cutin deposition and cuticle thickness, resulting in microcracking and increased fruit cracking, while simultaneously promoting wax accumulation on the fruit surface. Molecular analyses demonstrated that SlNOR-like1 directly activates key cutin biosynthesis genes SlGPAT6 and SlCD2 by binding their promoters, and represses wax biosynthesis and transport genes SlKCS1, SlCER1-2, SlWAX2, and SlLTPG1-like, thus exerting opposite regulatory effects on cutin and wax accumulation. These findings provide a new model for the transcriptional regulation of fruit cuticle formation, highlighting SlNOR-like1's dual role in maintaining cuticle integrity and post-harvest fruit quality.

Additional Information

  • Source:Journal of Experimental Botany. 2024/03, Vol. 75, Issue 7, p1903
  • Document Type:Article
  • Subject Area:Agriculture and Agribusiness
  • Publication Date:2024
  • ISSN:0022-0957
  • DOI:10.1093/jxb/erad410
  • Accession Number:176275805
  • Copyright Statement:Copyright of Journal of Experimental Botany is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.