The swimming performance of fish is crucial for their survival, playing a significant role in enhancing disease resistance and facilitating stress recovery, particularly in aquaculture fish. Understanding the genetic basis of fish swimming performance is essential for its integration as a key trait in selection breeding programs, especially for deeper offshore aquaculture. Spotted sea bass, an economically important aquaculture fish species in China, exhibits euryhaline and eurythermic characteristics and has demonstrated substantial potential for deep-sea aquaculture. Therefore, in our study, the absolute critical swimming speed (a.Ucrit) of juvenile spotted sea bass were assessed, ranging form 24.50 cm s−1 to 65.00 cm s−1, and this range enabled the identification of individuals with superior and inferior swimming abilities within the test population. Based on whole-genome resequencing, genome-wide association studies (GWAS) were conducted for three phenotypes of swimming performance, identifying 25 associated SNPs and 85 candidate genes, indicating that it is a polygenetic trait influenced by multiple biological processes. The heritability estimates for a.Ucrit and relative critical swimming speed (r.Ucrit) were 0.21 ± 0.08 and 0.22 ± 0.08, respectively. Furthermore, the impact of various genomic selection (GS) models and SNP densities on prediction accuracy of swimming performance was evaluated using genomic prediction (GP). The SVM model is recommended for continuous trait prediction of swimming performance, especially when SNP densities ranges between 500 and 50 K, as it provides more accurate, efficient and stable predictions. Our research further enhances the understanding of the genetic basis of fish swimming performance and holds promise for improving productivity in deep-sea aquaculture through genomic selection.
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