First genome-wide association study and genomic prediction for growth traits in spotted sea bass (Lateolabrax maculatus) using whole-genome resequencing

Spotted sea bass (Lateolabrax maculatus), widely distributed along the Chinese coasts, is an economically important aquaculture fish species. Recently, degeneration of genetic characteristics such as the decline in the growth rate severely hampers the development of its industry, and genetic improvement for this species is ur-gently required. In this study, the first genome-wide association study (GWAS) for growth traits (body weight, body height, total length and body length) were conducted and the potential performance of genomic selection (GS) were evaluated by genomic prediction of breeding values. Based on >4 million single-nucleotide poly-morphisms (SNPs) genotyped by whole-genome resequencing for 514 individuals from Dongying (DY, 301 in-dividuals) and Tangshan populations (TS, 213 individuals), GWAS detected a total of 66 growth-related SNPs located in multiple chromosomes but no major QTL, suggesting that growth traits were controlled by a polygenic genetic architecture. Candidate growth associated genes were identified to be involved in cytoskeleton reorga-nization, neuromodulation, angiogenesis and cell adhesion, and vascular endothelial growth factor (VEGF) and estrogen signaling pathways were considered to play important roles for growth. Predictive accuracies of the genomic estimated breeding value (GEBV) were compared among rrBLUP, BayesB, BayesC and BL models, and rrBLUP was determined as the optimal model for growth traits. Furthermore, the predictive performance based on different selection strategies of SNPs were compared, indicating using GWAS-informative SNPs was more efficient than random selected markers. These results highlighted the potential of GWAS to improve predictive accuracies of GS and reduce genotyping cost substantially. Our study laid the basis for further elucidate genetic mechanisms and demonstrated the application potential of GS approach for growth traits in spotted sea bass, which will facilitate future breeding of fast growth strains.