Abstract:

【Background】 Since genomic selection (GS) was proposed by MEUWISSEN et al. in 2001, it has been widely used in the breeding of dairy cows, pigs, and other livestock, and has significantly improved the speed of genetic gain of various economic traits. In 2017, with the organization and coordination of the National Grazing Headquarter Station and within the framework of the National Swine Improvement Program, the genomic selection platform for pig breeding was officially launched. Although genomic selection has made positive achievements in pig breeding, and the developing of advanced genotyping technology reduced the costs dramatically, some issues were still existed, including the insufficient number of genotyped individuals in majority of core breeding farms and the inappropriate implementation processes has restricted its wide application in practice.【Objective】In combination with the actual situation of domestic pig breeding, the “two-step” strategy for genomic selection was proposed in this study, that is, the off-test evaluation and the early-stage prediction. Off-test evaluation referred to the genetic evaluation of replacement pigs by SSGBLUP after off-test, and early-stage prediction was carried out when the number of chips reached a certain scale. 【Method】 In this study, the 50 K chip datasets of three breeds consisting of Duroc, Landrace, and Yorkshire were used as the base group to simulate the large-scale population of different breeds, respectively. The four generations were simulated: the first three generations were treated as the base population, and the fourth generation as the test population, two traits with medium and low heritability was simulated for each individual. The estimated breeding values of SSGBLUP and traditional BLUP model for different traits were calculated by the pig genomic selection platform based on the HIBLUP software. The predictive performance of early-stage was evaluated according to whether the individual’s testing records have influence their genomic estimated breeding values (GEBV) in test population. 【Result】The results showed that the predictive performance of off-test evaluation and early-stage for traits with medium heritability were better than those with low heritability. The selection accuracy of SSGBLUP was better than traditional BLUP. Moreover, with the increase of the number of chips and the expansion of the population size, the prediction accuracy was higher. The early-stage predictive performance of SSGBLUP was better than that of traditional BLUP, the early-stage prediction could be carried out when the number of genotyped pigs reached about 2 000, and castrating the last 30% individuals according to GEBV could ensure that the top 1% excellent individuals would not be mistakenly eliminated. And the prediction accuracy performance was increasing with the increased number of genotyped pigs. 【Conclusion】 The “two-step” strategy pretty was conformed to the state of domestic breeding program, and was easy to implement and promote the pig breeding in China. When the number of genotyped pigs was small, off-test evaluation could be carried out to improve the accuracy of selection, as well as efficiency, to a certain extent; when the number of genotyped pigs was large, early-stage prediction could be performed by castrating the pigs on the lower rank of GEBV, which could increase the amount of testing for more excellent pigs, and could also strength the selection intensity and accelerate the genetic gain. The “two-step” strategy was in line with the actual requirements of genomic selection in pig industry. The implementation of this strategy could further promote the application of genomic selection and speed up the genetic gain in pig breeding.

Key words: genomic selection, pig, two-step, off-test evaluation, early-stage prediction