Genotype × ammonia interaction effects on plasma physiological indexes in turbot (Scophthalmus maximus) cultured under acute ammonia stress for different periods of times

Genotype by Temperature Interaction for Plasma Physiological Indexes in Turbot (Scophthalmus maximus) under Acute Heat Stress─Exploring a Method for Screening Physiological Biomarkers of Nontoxic Stress in Aquatic Environments

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 (Scophthalmus maximus) 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 (P < 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.