WRKY蛋白质结构域
生物
转录组
基因
参考基因
坎德拉烛台
红树林
基因表达
遗传学
适应(眼睛)
计算生物学
生态学
神经科学
作者
Wenyue Su,Congting Ye,Yihui Zhang,Saiqi Hao,Qingshun Quinn Li
标识
DOI:10.1016/j.scitotenv.2019.05.127
摘要
Mangrove forests are an important contributor to the coastal marine environment. They have developed unique adaptations to the harsh coastal wetland, yet their geographic distribution is limited by environmental temperature. The adaptive strategies of mangrove at the molecular level, however, have not been addressed. In the present work, transcriptome analyses were performed on different cold damaged plants of a mangrove species, Kandelia obovata. From the samples collected in the field after a cold stress, we found that distinct expression profiles of many key genes are related to extreme temperature responses. These include transcription factors such as WRKY and bHLH, and other genes encoding proteins like SnRK2, PR-1, KCS, involving in the pathways of plant hormones, plant-pathogen interactions, and long chain fatty acid synthesis. We also examined the transcriptomes of eight tissues of K. obovata to identify candidate genes involved in adaptation and development. While stress-responsive genes were globally expressed, tissue-specific genes with diverse functions might be involved in tissue development and adaptability. For examples, genes encoding CYP724B1 and ABCB1 were specifically expressed in the fruit and root, respectively. Additionally, 26 genes were identified as positively selected genes in K. obovata, six of them were found to be involved in chilling stress response, seed germination and oxidation-reduction processes, suggesting their roles in stressful environment adaptation. Together, these results shed light into the K. obovata's natural responses to cold snaps at the molecular level, and reveal a global gene expression portrait across different tissues. It also provides a transcriptome resource for further molecular ecology studies and conservation planning of this and other mangrove plants in their native and adopted environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI