WRKY蛋白质结构域
转录因子
生物
MYB公司
计算生物学
药用植物
基因
生物技术
Cis监管模块
基因表达
抄写(语言学)
转录组
遗传学
增强子
植物
语言学
哲学
作者
Meizhen Wang,Xiaoxiao Qiu,Xian Pan,Caili Li
出处
期刊:Current Pharmaceutical Biotechnology
[Bentham Science]
日期:2020-06-22
卷期号:22 (6): 848-866
被引量:25
标识
DOI:10.2174/1389201021666200622121809
摘要
Plants produce thousands of chemically diverse secondary metabolites, many of which have valuable pharmaceutical properties. There is much interest in the synthesis of these pharmaceuticallyvaluable compounds, including the key enzymes and the transcription factors involved. The function and regulatory mechanism of transcription factors in biotic and abiotic stresses have been studied in depth. However, their regulatory roles in the biosynthesis of bioactive compounds, especially in medicinal plants, have only begun. Here, we review what is currently known about how transcription factors contribute to the synthesis of bioactive compounds (alkaloids, terpenoids, flavonoids, and phenolic acids) in medicinal plants. Recent progress has been made in the cloning and characterization of transcription factors in medicinal plants on the genome scale. So far, several large transcription factors have been identified in MYB, WRKY, bHLH, ZIP, AP2/ERF transcription factors. These transcription factors have been predicted to regulate bioactive compound production. These transcription factors positively or negatively regulate the expression of multiple genes encoding key enzymes, and thereby control the metabolic flow through the biosynthetic pathway. Although the research addressing this niche topic is in its infancy, significant progress has been made, and advances in high-throughput sequencing technology are expected to accelerate the discovery of key regulatory transcription factors in medicinal plants. This review is likely to be useful for those interested in the synthesis of pharmaceutically- valuable plant compounds, especially those aiming to breed or engineer plants that produce greater yields of these compounds.
科研通智能强力驱动
Strongly Powered by AbleSci AI