Genetic parameters and genomic prediction for nutritional quality-related traits of Pacific abalone (Haliotis discus hannai)

Abstract

The Pacific abalone (Haliotis discus hannai) is one of the most widely cultivated shellfish species in China. Nutritional quality-related traits are a major objective in aquatics as they determine the value of products and consumer preference. Estimating genetic parameters and the potential of genomic selection is significant in designing breeding programs, which has not been performed in abalone. In the study, we developed near infrared reflectance spectroscopy (NIRS) models for collagen content (CC) and taurine content (TC) in Pacific abalone, estimated the genetic parameters for glycogen content (GLY), total protein content (TPC), CC, and TC, and assessed the prediction ability of GBLUP and three Bayesian methods for the four nutritional traits. The genetic analysis included all 274 individuals and 69,530 high quality SNPs. The prediction correlation of the NIRS models were 0.9702 and 0.9289 for CC and TC, respectively. The heritability of GLY, TPC, CC, and TC was 0.33 ± 0.13, 0.42 ± 0.14, 0.02 ± 0.10 and 0.32 ± 0.13, respectively, while the heritability of growth traits in our study ranged from 0.34 ± 0.14 to 0.47 ± 0.14. Negative correlations were observed between GLY and both TPC (−0.96 ± 0.03) and TC (−0.90 ± 0.07), whereas moderate correlations were found between GLY and growth traits. The prediction ability for GLY, TPC, and TC was 0.21 ± 0.04 to 0.22 ± 0.03, 0.27 ± 0.02 to 0.29 ± 0.03, 0.20 ± 0.03 to 0.24 ± 0.02, respectively, using four genomic selection (GS) models (GBLUP, BayesA, BayesB, and BayesCpi). The results were encouraging and showed comparable performance for the predictability of genomic estimated breeding values, demonstrating the potential for GS in selection breeding of the nutritional quality-related traits in Pacific abalone.