Suppr超能文献

青枯雷尔氏菌自然侵染木麻黄无性系的转录组和代谢组分析

Transcriptome and metabolome profiling in naturally infested Casuarina equisetifolia clones by Ralstonia solanacearum.

作者信息

Wei Yongcheng, Zhang Yong, Meng Jingxiang, Wang Yujiao, Zhong Chonglu, Ma Haibin

机构信息

Research Institute of Tropical Forestry, Chinese Academy of Forestry, Longdong, Guangzhou 510520, China.

出版信息

Genomics. 2021 Jul;113(4):1906-1918. doi: 10.1016/j.ygeno.2021.03.022. Epub 2021 Mar 23.

Abstract

Casuarina equisetifolia is an important pioneer tree and suffers from bacterial wilt caused by Ralstonia solanacearum. We collected resistant (R) and susceptible (S) C. equisetifolia clones naturally infected by R. solanacearum and compared their transcriptome and metabolome with a clone (CK) from a non-infested forest, in order to study their response and resistance to bacterial wilt. We identified 18 flavonoids differentially accumulated among the three clonal groups as potential selection biomarkers against R. solanacearum. Flavonoid synthesis-related genes were up-regulated in the resistant clones, probably enhancing accumulation of flavonoids and boosting resistance against bacterial wilt. The down-regulation of auxin/indoleacetic acid-related genes and up-regulation of brassinosteroid, salicylic acid and jasmonic acid-related differentially expressed genes in the R vs CK and R vs S clonal groups may have triggered defense signals and increased expression of defense-related genes against R. solanacearum. Overall, this study provides an important insight into pathogen-response and resistance to bacterial wilt in C. equisetifolia.

摘要

木麻黄是一种重要的先锋树种,易患青枯雷尔氏菌引起的青枯病。我们收集了自然感染青枯雷尔氏菌的抗性(R)和易感(S)木麻黄无性系,并将它们的转录组和代谢组与来自未受侵染森林的一个无性系(CK)进行比较,以研究它们对青枯病的反应和抗性。我们鉴定出在三个无性系组中差异积累的18种黄酮类化合物,作为抗青枯雷尔氏菌的潜在选择生物标志物。黄酮类化合物合成相关基因在抗性无性系中上调,可能增强了黄酮类化合物的积累并提高了对青枯病的抗性。在R与CK以及R与S无性系组中,生长素/吲哚乙酸相关基因的下调以及油菜素内酯、水杨酸和茉莉酸相关差异表达基因的上调,可能触发了防御信号并增加了抗青枯雷尔氏菌防御相关基因的表达。总体而言,本研究为木麻黄对病原体的反应和对青枯病的抗性提供了重要见解。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验