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Transcriptome sequencing of Cocos nucifera leaves in response to Rhynchophorus ferrugineus infestation

文献类型： 外文期刊

作者： Liu, Li 1 ; Yan, Wei 1 ; Liu, Bo 1 ;

作者机构： 1.Chinese Acad Trop Agr Sci, Hainan Key Lab Trop Oil Crops Biol, Coconut Res Inst, Wenchang, Peoples R China

关键词： red palm weevil; ROS scavenging; herbivore; coconut; host-plant resistance; flavonoid biosynthesis

期刊名称：FRONTIERS IN GENETICS （ 影响因子：3.7； 五年影响因子：4.3 ）

ISSN：

年卷期： 2023 年 14 卷

页码：

收录情况： SCI

摘要： Red palm weevil (RPW, Rhynchophorus ferrugineus) is an invasive pest of palms. In China, coconut (Cocos nucifera) production is being significantly affected by the RPW attack. To develop a long-term RPW control strategy, host-plant resistance is the most sustainable option. In this regard, the availability of transcriptome sequencing data from RPW-infected coconut plants can be highly useful. Therefore, the present study assessed coconut leaf physiological responses and transcriptional changes after different days of RPW attack i.e., 5, 10, 15, 20, and 25 days after infestation (DAI). A comparison of physiological data indicated that populations with the higher number of RPW insects i.e., population C (15 males +21 females) and D (20 males +28 females) triggered higher antioxidant enzyme activities. We used this data to study the transcriptomic responses on 5 and 20 DAI. Of the 38,432 detected transcripts, 3,984, 1,981, 3,925, and 2,257 were differentially expressed in CK (control/no RPW)_vs._C (5 DAI), CK_vs._D (5 DAI), CK_vs._C (20 DAI), and CK_vs._D (20 DAI), respectively. These transcripts were enriched in plant-pathogen interaction, phenylpropanoid/flavonoid biosynthesis, amino sugar and nucleotide sugar metabolism, plant hormone signal transduction, mitogen-activated protein kinase, and reactive oxygen scavenging pathway. We discuss these results and present several candidate genes to be manipulated for developing a sustainable strategy to control RPW attack regarding host-plant resistance. Furthermore, these findings provide a basis for developing effective early and late RPW attack detection strategies.

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