Genomic predictions for resistance to Aeromonas hydrophila in pacu (Piaractus mesopotamicus) - Manso, Shisley C.S. [UNESP]; Garcia, Baltasar F. [UNESP]; Mastrochirico-Filho, Vito A. [UNESP]; Porto-Foresti, Fábio [UNESP]; Yáñez, José M.; Hashimoto, Diogo T. [UNESP] (Elsevier, 2024)
Infections caused by the bacterium Aeromonas hydrophila result in high mortality outbreaks in pacu (Piaractus mesopotamicus) production. An alternative to increase the resistance to A. hydrophila infection is the implementation of genomic selection programs, which can contribute to the sustainable development of the Brazilian aquaculture. In addition, low-density SNP panels, optimized by genotype imputation, represent a low-cost tool for implementing genomic selection on a commercial scale. This study aimed to evaluate the accuracy of genomic prediction using low (0.5 and 1 K) and medium (15 K imputed) density SNP panels; and compare breeding values accuracy with restriction-site associated DNA sequencing (18 K) and pedigree-based methods for individuals challenged for A. hydrophila. The genomic prediction analyses were conducted using genotypes from the medium-density SNP panel of pacu as reference and genotypes from a low-density SNP panel (0.5 and 1 K) using target genotype-by-sequencing technology (tGBS) for imputation. Approximately 15 K SNPs were successfully imputed with accuracy (r2) above 0.8. Time to death (TD) and binary survival (BS) against A. hydrophila infection were used as phenotypes for genomic prediction. Genomic values were estimated using the GBLUP model adopting different genotyping methods (SNP array and RAD-seq) and densities of SNPs (0.5 K, 1 K, and 15K_imputed for the array and 18 K for RAD-seq). Accuracies of genomic approaches using different methods and densities were compared to the pedigree method PBLUP to assess the benefits of incorporating genomic information. The accuracy of predicting breeding values using genomic methods outperformed the estimates obtained through PBLUP by 33%, 39%, and 67% for TD, and 36%, 39%, and 82% for BS, considering the densities of 0.5, 1, and 15K_imputed, respectively. The imputation strategy yielded better results in terms of genomic prediction accuracy for both traits. The RAD-seq genotyping method produced low-accuracy estimates (∼30% lower for both traits) compared to PBLUP, indicating that such method may not be suitable for genomic prediction of these traits. Genomic selection using genotype imputation is a viable and cost-effective approach to increase resistance to A. hydrophila infection in pacu and reduce genotyping costs without compromising genomic prediction accuracy.
Keywords: Genetic improvement; Genomic selection; Genotype imputation; Pacu