Evolution of terpene synthases in the sesquiterpene biosynthesis pathway and analysis of their transcriptional regulatory network in Asteraceae

生物 菊科 萜烯 倍半萜 生物合成 通路分析 植物 遗传学 基因 生物化学 基因表达
作者
Xiuping Yang,Fanbo Meng,Qian Cheng,Pengmian Feng,Xiaoming Song,Wei Chen
出处
期刊:Horticulture research [Nature Portfolio]
卷期号:12 (12): uhaf229-uhaf229 被引量:2
标识
DOI:10.1093/hr/uhaf229
摘要

The Asteraceae family, one of the largest angiosperm families, is rich in terpenoid secondary metabolites with significant medicinal value. Asteraceae plants have evolved a diverse array of terpenoid biosynthesis pathways, reflecting their adaptive significance and complex regulatory mechanisms. However, the evolutionary patterns and transcriptional regulatory mechanisms governing these biosynthetic processes remain unclear. This study investigates the evolution and transcriptional regulation of terpenoid biosynthesis genes in Asteraceae. Comparative genomic analysis of 19 Asteraceae and six out-group species revealed that Asteraceae species diverged ~74.03 million years ago and were distinctly divided into three subfamilies. A total of 1714 terpene synthase (TPS) genes were identified, predominantly in the TPS-a and TPS-b subfamilies. Caryophyllene-type sesquiterpene biosynthetic gene clusters (BGCs) were detected in 10 species, with their formation due to whole-genome duplication (WGD) and tandem duplication. By integrating weighted gene coexpression network analysis (WGCNA) and machine learning methods, key transcription factors regulating caryophyllene synthase (CPS) in Carthamus tinctorius were identified. A multilayered gene regulatory network was constructed to identify potential regulatory factors involved in TPS gene regulation under light stress. By exploring the evolutionary patterns and potential regulatory relationships involved in terpenoid biosynthesis in Asteraceae, this study provides important insights into TPS gene evolution. In addition, the findings also offer guidance for optimizing genetic engineering strategies in terpenoid-based drug development.
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