外文摘要：Cannabis glandular trichomes (GTs) are economically and biotechnologically important structures that have a remarkable morphology and capacity to produce, store, and secrete diverse classes of secondary metabolites. However, our understanding of the developmental changes and the underlying molecular processes involved in cannabis GT development is limited. In this study, we developed Cannabis Glandular Trichome Detection Model (CGTDM), a deep learning-based model capable of differentiating and quantifying three types of cannabis GTs with a high degree of efficiency and accuracy. By profiling at eight different time points, we captured dynamic changes in gene expression, phenotypes, and metabolic processes associated with GT development. By integrating weighted gene co-expression network analysis with CGTDM measurements, we established correlations between phenotypic variations in GT traits and the global transcriptome profiles across the developmental gradient. Notably, we identified a module containing methyl jasmonate (MeJA)-responsive genes that significantly correlated with stalked GT density and cannabinoid content during development, suggesting the existence of a MeJA-mediated GT formation pathway. Our findings were further supported by the successful promotion of GT development in cannabis through exogenous MeJA treatment. Importantly, we have identified CsMYC4 as a key transcription factor that positively regulates GT formation via MeJA signaling in cannabis. These findings provide novel tools for GT detection and counting, as well as valuable information for understanding the molecular regulatory mechanism of GT formation, which has the potential to facilitate the molecular breeding, targeted engineering, informed harvest timing, and manipulation of cannabinoid production.
外文关键词：deep learning;Transcription factor;Cannabis;transcriptomics;glandular trichomes;MeJA signaling
作者：Chen, Wei;Gu, Yu;Liu, Yuanyuan;Huang, Xiaoqin;Zhao, Yuqing;Chen, Jingjing;Ouyang, Yuzeng;Li, Minxuan;Wu, Qinqin;Cai, Sen;Guo, Foqin;Zhu, Panpan;Ao, Deyong;You, Shijun;Vasseur, Liette
作者单位：Fujian Agr & Forestry Univ;Brock Univ
期刊名称：PLANT JOURNAL
期刊影响因子：0.0
出版年份：2024
出版刊次：118(4)
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台