Incorporating GWAS-derived prior information enhances genomic prediction for body size traits in the mud crab (Scylla...

Scylla paramamosain is an economically important marine crab species in Asia, yet the genetic architecture of its growth traits remains poorly characterized. This study employed an integrated approach combining genome-wide association studies (GWAS) and genomic prediction to dissect the genetic basis of four body size traits (carapace width, carapace length, posterior width of carapace, and body height) in 346 individuals genotyped at 3.9 million high-confidence SNPs. GWAS identified five pleiotropic loci and six candidate genes (including Exportin-5 and FANCI) shared among traits, with KEGG enrichment analysis underscoring the importance of metabolic pathways, particularly the citrate cycle. We further evaluated the genomic prediction performance of the GFBLUP model using two types of prior biological knowledge: functionally annotated SNPs derived from the top-enriched KEGG pathways, and trait-associated SNPs selected under varying GWAS significance thresholds. GFBLUP using trait-associated SNPs significantly outperformed standard GBLUP, with prediction accuracy gains of 0.528-0.888. Prediction accuracy increased with SNP panel size, exceeding 0.819 for all traits with the top 1000 SNPs and stabilizing beyond 5000 SNPs (0.837-0.865). An FDR threshold of 0.05 offered an optimal balance, achieving high accuracy (0.840-0.862) with a practical number of SNPs (7980-9302). In contrast, functionally informed GFBLUP provided only modest improvements (0.020-0.197), likely due to the inclusion of non-causal variants. These results demonstrate that low-density SNP panels informed by GWAS prior knowledge substantially enhance genomic prediction for body size traits in S. paramamosain, providing a practical breeding strategy and valuable insights into the genetic mechanisms of growth in non-model crustaceans.