National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China.
Function Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China.
Environ Sci Technol. 2023 Feb 21;57(7):2813-2825. doi: 10.1021/acs.est.2c07958. Epub 2023 Feb 10.
This paper presents a method for exploring the genetic mechanism underlying the plasma physiological indexes under heat stress in aquatic environments and for screening reliable stress biomarkers based on split-split-plot analysis (SSP), additive main effects and multiplicative interaction (AMMI) analysis, and genotype main effects and genotype × environment interaction (GGE) biplot analysis. The methodology developed was illustrated by applying it to a specific turbot heat stress case study. Five plasma physiological indexes (epinephrine, cortisol, alkaline phosphatase, superoxide dismutase, and blood glucose levels) were measured in turbot () under acute heat stress at four temperatures (18, 21, 24, and 27 °C) for various exposure times (3, 6, 9, 12, 24, 48, and 72 h). The SSP analysis showed that exposure time and temperature × gene interactions had significant ( < 0.01) effects on the activity/content of turbot plasma physiological indexes. The AMMI analysis showed the following: (1) that at each exposure time, the genotype effect > the genotype × temperature interaction > the temperature effect; (2) that during the whole experiment, the change trend of the contribution of the genotype × temperature interactions was similar to that of the temperature effect, and the changing trends of the contributions of the genotype × temperature interaction and the genotype effect were clearly completely reversed; and (3) that the 3-24-h period was the key period for the changes in the physiological indexes due to acute heat stress. The GGE biplot analysis showed that blood glucose and cortisol levels were reliable biomarkers and could be used as early warning markers for numerical simulations of physiological behavior.
本文提出了一种基于裂区-裂区分析（SSP）、加性主效应和互作（AMMI）分析以及基因型主效应和基因型×环境互作（GGE）双标图分析的方法，用于探索水生环境下热应激下血浆生理指标的遗传机制，并筛选可靠的应激生物标志物。该方法通过应用于特定的大菱鲆热应激案例研究进行了说明。在急性热应激下，测量了五个血浆生理指标（肾上腺素、皮质醇、碱性磷酸酶、超氧化物歧化酶和血糖水平）在五个温度（18、21、24 和 27°C）下暴露不同时间（3、6、9、12、24、48 和 72 小时）的大菱鲆（）中的活性/含量。SSP 分析表明，暴露时间和温度×基因互作对大菱鲆血浆生理指标的活性/含量有显著（<0.01）影响。AMMI 分析表明：（1）在每个暴露时间，基因型效应>基因型×温度互作>温度效应；（2）在整个实验过程中，基因型×温度互作的贡献变化趋势与温度效应相似，基因型×温度互作和基因型效应的贡献变化趋势明显完全相反；（3）3-24 小时是急性热应激引起生理指标变化的关键时期。GGE 双标图分析表明，血糖和皮质醇水平是可靠的生物标志物，可作为生理行为数值模拟的早期预警标志物。
