Deep learning-based quantification and transcriptomic profiling reveal a methyl jasmonate-mediated glandular trichome formation pathway in Cannabis sativa.

Journal: The Plant journal : for cell and molecular biology
PMID:

Abstract

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 GTĀ 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.

Authors

  • Xiaoqin Huang
    The Pennsylvania State University Great Valley, Malvern, PA, USA.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.
  • Yuqing Zhao
    Faculty of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming, Yunnan 650201, PR China. Electronic address: kmyuqing@163.com.
  • Jingjing Chen
    Department of Cardiovascular Medicine, Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Yuzeng Ouyang
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Minxuan Li
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Yu Gu
    Microsoft Research, Redmond, WA, USA.
  • Qinqin Wu
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Sen Cai
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Foqin Guo
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Panpan Zhu
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Deyong Ao
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Shijun You
    Haixia Institute of Science and Technology, State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
  • Liette Vasseur
    Department of Biological Sciences, Brock University, St. Catharines, Ontario, L2S 3A1, Canada.
  • Yuanyuan Liu
    College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.