Abstract:

【Background】The contribution of genetic breeding is the highest in improving the efficiency of animal production. Through breeding, the animal husbandry enterprises can improve production efficiency and obtain maximum economic benefits. Genome selection has been widely used in plant and animal breeding. Genomic selection can estimate breeding values (EBV) by using high density markers covering the whole genome. Compared with pedigree information, the average relationship between individuals obtained by using these markers is more accurate, so that breeding values can be more accurately estimated, and the individuals can be selected. In practical breeding program, all individuals are not genotyped, especially for pigs, whose economic values are not high enough, hence the application of genomic selection is limited in pig breeding. The single-step genomic best linear unbiased prediction (ssGBLUP) can utilize both pedigree and genotypes information, allowing part of individuals are genotyped, thus greatly reducing genotyping costs while maintaining high prediction accuracy. At present, many studies have shown that the use of genomic selection in pig breeding can improve the accuracy of prediction, but in actual breeding, the breeding cost is also an important issue in livestock enterprises to consider. Therefore, how to implement breeding program economically and effectively is of great research value.【Objective】The effect of one-step genome selection on the population evaluation of Duroc was investigated, so as to provide the basis for genome selection breeding program.【Method】 In this study, three important economic traits of duroc pig born from 2009 to 2018 in a pig farm in Fujian province were studied. The accuracy of BLUP, GBLUP, and ssGBLUP was compared in calculating the estimated breeding value on reproductive and growth traits of Duroc pigs. The impacts of genotyped individuals with different proportions in the reference population on the ssGBLUP prediction abilities were explored, and the influence of different chip density on GBLUP prediction abilities was also studied. 【Result】 (1) The heritability of the age at 100 kg, the backfat, and eye muscle area was 0.257±0.038, 0.250±0.039 and 0.399±0.040, respectively; (2) Compared with BLUP, the accuracy of ssGBLUP was improved by 14.7%-51.1%; compared with GBLUP, the accuracy increased by 13.4%-45.7%; (3) When 10%-30% of individuals was genotyped, the prediction accuracy of ssGBLUP could exceed that of BLUP; the prediction accuracy reached a plateau when 40%-60% of individuals genotyped. 【Conclusion】Based on the above results, it was concluded that: (1) Compared with BLUP, ssGBLUP could improve the accuracy and reliability of EBV for each trait; compared with the GBLUP, ssGBLUP was slightly lower than the GBLUP with only pedigree information of those ungenotyped, but ssGBLUP performed better than the GBLUP method after the addition of phenotypes of the ungenotyped individuals. (2) As the proportion of genotyped individuals in the reference population increased, no matter which selection method was used to determine genotyped individuals (random selection and selection the key individuals), the prediction ability of ssGBLUP was gradually improved. The results showed that the ssGBLUP could improve the prediction ability of individual breeding value even if only a proportion of individuals was genotyped when the breeding budget was limited.

Key words: duroc, genomic selection, ssGBLUP, the proportion of individuals genotyped