Genetic Architecture of Body Weight Variation and GWAS-Informed Genomic Selection in Formulated Diet-Adapted Mandarin Fish (Siniperca chuatsi)

Large variation in body weight poses a major challenge to the development and industrialization of formulated-feed aquaculture in Siniperca chuatsi. Breeding varieties that combine formulated-diet adaptation, rapid growth, and uniform body weight is therefore important for improving production efficiency. However, the genetic architecture of body weight and optimal genomic selection (GS) strategies remain poorly understood. Here, whole-genome resequencing was performed on 522 formulated-diet-adapted individuals. Genome-wide association study (GWAS) identified 21 significant loci, with candidate genes associated with lipid metabolism, endocrine regulation, and neuroendocrine signaling. Genomic prediction was evaluated using genome-wide single-nucleotide polymorphisms (SNPs) and GWAS-prioritized SNP panels with Bayesian and machine-learning models. Prediction accuracy increased with marker number and generally plateaued at approximately 30,000 SNPs. Random forest using GWAS-prioritized markers achieved the highest accuracy, improving prediction accuracy by 4.8% over genome-wide genomic best linear unbiased prediction (GBLUP) while using fewer markers. These findings demonstrate the potential of GWAS-informed marker prioritization to reduce marker requirements and improve GS efficiency for body weight in formulated-diet-adapted S. chuatsi.