Abstract:White shrimp (Penaeus vannamei), are native to the Pacific coastal waters of South America. With rapid growth rates and environmental adaptability, P. vannamei was introduced to China in 1988 and has since been promoted extensively for aquaculture. In 2022, its domestic production reached 2.09 million tons, accounting for one-third of the global annual aquaculture production of shrimp. P. vannamei has become a mainstay aquaculture industry of China, playing a crucial role in the economic development of coastal areas, increasing the income of fishermen, and maintaining the stable development of the rural fisheries economy. Growth traits present the most important economic trait of P. vannamei; however, with the continuous expansion of the scale culture and the deterioration of the culture environment, viral diseases are among the main causes of economic loss. Among them, white spot syndrome virus (WSSV) outbreaks have impacted many global regions since its first appearance in 1992. Infected shrimp have reduced intake, enlarged hepatopancreas, and white spots on the body. Currently, there is no effective method to prevent and control the spread of the virus, and the breeding of new varieties with both growth and WSSV resistance is urgently required. Obtaining precise genetic parameters for economic traits is the basis for developing breeding programs, and in particular, the precise assessment of heritability and genetic correlations, is an important guide in the development of selection indices, retention, and mating programs. Genetic parameter estimation mainly uses Pedigree-based Best Linear Unbiased Prediction (pBLUP). This method estimates breeding values by constructing an A matrix and correcting for different effectors and is widely used in genetic evaluation of economic traits in aquatic animals. However, pBLUP uses the A-matrix for resistance traits that are difficult to measure directly using siblings can only use 50% of the genetic variation, thus the assessment is not accurate. The use of individual typing information to construct a genomic matrix can accurately measure the true relationship between individuals, and the calculation of breeding values is performed considering the Mendelian sampling effect, which is conducive to improving the accuracy of the assessment. This assessment plays an important role in livestock and poultry breeding such as dairy cattle; however, shrimp single-tail value is low and is costly to perform at the population level. The single step genomic best linear unbiased prediction (ssGBLUP) types only some of the individuals, and composite genealogical and genotypic information is used for the breeding value assessment, which reduces the cost of individual typing. Accordingly, this method has been widely used in aquatic animals. Genomic breeding microarrays have also become an important genotyping tool in crop and livestock breeding due to their advantages of reproducibility, high accuracy, maneuverability, and low price. To assess the prospects for the application of breeding microarrays in the selection of new composite varieties for growth and WSSV resistance in the P. vannamei, this study used 59 lines of P. vannamei, totaling 1,770 individuals, and tested for WSSV infection using an independently bred high resistance line of P. vannamei. Based on the survival time of individual resistance to WSSV within the family line, 590 individuals were uniformly selected and typed using 55K SNP liquid-phase microarrays to obtain genotypic data for certain individuals. An ssGBLUP model was established by combining phenotypic values, genealogical and genotypic data, and the heritability and genetic correlation were estimated for the length of the body, the survival time of individual and half-lethal survival rate (SS50) after infection with WSSV. The heritabilities of body length and survival time in individual P. vannamei were 0.21±0.06 and 0.22±0.16, respectively, indicating medium heritability levels. The heritability of SS50 after infection with WSSV was 0.16±0.06, indicating a low heritability level. The prediction accuracy of heritability of body length based on the H-matrix was increased by 18.12% compared with the A-matrix after five-fold cross validation, and the prediction bias was not significantly different. The heritability prediction accuracy of survival time against WSSV was not significantly different from the A matrix, and the prediction bias was large in H-matrix. Furthermore, the heritability prediction accuracy of SS50 was reduced by 29.07% from the A matrix, and the prediction bias was large in the H-matrix. Based on the two-trait animal model, the estimated genetic correlation between the body length of P. vannamei and survival time of individuals against WSSV and SS50 were 0.13±0.20 and 0.30±0.22, respectively, which were not significantly different from 0 (P>0.05). The genetic correlation between the survival time of individuals against WSSV and SS50 was 0.95±0.03, which was not significantly different from 1 (P>0.05). The study showed that the genetic assessment of the growth of P. vannamei by microarray can effectively improve the accuracy of the assessment, the evaluation of WSSV survival time traits may be affected by the selection of individuals and other factors, and the prediction accuracy was not significantly improved. Finally, the survival time traits of individual anti-WSSV was better than the SS50 trait of family anti-WSSV in terms of accuracy and prediction bias. In the case that anti-WSSV survival time is highly correlated with the SS50 trait, anti-WSSV survival time can be considered as a target trait for genomic selection. In this study, we estimated the genetic parameters of growth and WSSV resistance in P. vannamei based on the typing information of 55K SNP liquid microarray “Yellow Sea Chip No.1,” which provides a reference for the application of breeding microarrays in selecting new multi-trait composite varieties of P. vannamei.
