Abstract:Turbot (Scophthalmus maximus) belongs to the Scophthalmidae family and is one of the most economically valuable flatfish aquaculture species worldwide. It is widely distributed in the Mediterranean, Black, and Baltic Seas. China has made significant progress in introducing turbot as an aquaculture species over the past 30 years, but key challenges remain in advancing its industrial aquaculture. Because turbot are cold-water fish with strict environmental temperature requirements, they are particularly susceptible to temperature stress. In the turbot aquaculture area in North China, the natural seawater temperature exceeds 26 ℃ throughout the summer (May to September), rendering it unsuitable for turbot aquaculture during this period. Genetically improving the heat tolerance of turbot to overcome this limitation is critical to promoting the sustainable and stable development of the turbot industry. In this study, we estimated the genetic parameters of heat resistance and turbot growth traits. Thirty full-sib families were constructed by male-female pairing with equal weights of approximately 25 g, and heat resistance experiments were carried out. Thirty turbot were selected from each of the 30 families, total 900 individuals, for the large-scale high-temperature stress experiment evaluating the genetic parameters of high-temperature tolerance traits in turbot. Four models [linear animal model (LAM), cross-sectional linear animal model (CLAM), cross-sectional threshold animal model–variant 1 (CTAM1), and cross-sectional threshold animal model with probit link function (CTAMp)] were used to fit two high-temperature tolerance traits (upper limit trait of heat tolerance, UTT, and binary death survival trait, BTS). The variance components were estimated by the restricted maximum likelihood method. The heritability of the high-temperature tolerance traits in turbot was 0.110–0.208, which was a medium–low heritability trait. Among them, the heritability estimated by linear models (LAM and CLAM) was 0.110±0.074 and 0.155±0.082, respectively, and the heritability estimated by threshold models (CTAMl and CTAMp) was 0.214±0.072 and 0.208±0.074, respectively. This indicates that turbot high-temperature tolerance can be improved through genetic selection. The genetic correlations of the two heat-resistant phenotypic traits with body weight were –0.07±0.40 and –0.13±0.33, respectively, and the phenotypic correlations were –0.04±0.05 and –0.08±0.11, respectively, both of which were extremely low correlations. The correlation analysis of the estimated breeding values (EBVs) by different models showed that when different models fitted the same heat-resistant phenotype, the correlation coefficient between EBVs was ＞0.97. That is a high-intensity positive correlation, indicating that when the same phenotypic definition was used, the linear or threshold model had little effect on the ranking of EBVs. The correlation analysis of EBVs estimated by different models and phenotypes revealed key differences. The correlation coefficient between EBVs estimated using threshold models (CTAMl and CTAMp) and phenotypic BTS was higher than that of the linear models (LAM and CLAM). This suggests that phenotypic BTS is a more suitable heat-resistant trait than phenotypic UTT. In addition, the correlation coefficient between EBVs estimated by UTT and BTS in the linear model was ＜0.50. This indicates that the EBV rankings based on these two phenotypic definitions for heat tolerance in turbot were inconsistent. Therefore, using phenotypic BTS and cross-sectional threshold animal models (CLAMl or CTAMp) is more advantageous for estimating the genetic parameters of heat tolerance in turbot. The results of this study supplement the research on genetic parameters of heat tolerance in turbot and provide a theoretical basis for the formulation of breeding plans for heat tolerance traits in cold-water fish.
