Abstract
Breeding programs aiming to improve the performance of crossbreds may benefit from genomic prediction of crossbred (CB) performance for purebred (PB) selection candidates. In this review, we compared genomic prediction strategies that differed in 1) the genomic prediction model used or 2) the data used in the reference population. We found 27 unique studies, two of which used deterministic simulation, 11 used stochastic simulation, and 14 real data. Differences in accuracy and response to selection between strategies depended on i) the value of the purebred crossbred genetic correlation (), ii) the genetic distance between the parental lines, iii) the size of PB and CB reference populations, and iv) the relatedness of these reference populations to the selection candidates. In studies where a PB reference population was used, the use of a dominance model yielded accuracies that were equal to or higher than those of additive models. When was lower than ~0.8, and was caused mainly by G × E, it was beneficial to create a reference population of PB animals that are tested in a CB environment. In general, the benefit of collecting CB information increased with decreasing . For a given , the benefit of collecting CB information increased with increasing size of the reference populations. Collecting CB information was not beneficial when was higher than ~0.9, especially when the reference populations were small. Collecting only phenotypes of CB animals may slightly improve accuracy and response to selection, but requires that the pedigree is known. It is, therefore, advisable to genotype these CB animals as well. Finally, considering the breed-origin of alleles allows for modeling breed-specific effects in the CB, but this did not always lead to higher accuracies. Our review shows that the differences in accuracy and response to selection between strategies depend on several factors. One of the most important factors is , and we, therefore, recommend to obtain accurate estimates of of all breeding goal traits. Furthermore, knowledge about the importance of components of (i.e., dominance, epistasis, and G × E) can help breeders to decide which model to use, and whether to collect data on animals in a CB environment. Future research should focus on the development of a tool that predicts accuracy and response to selection from scenario specific parameters.
Highlights
Crossbreeding is the practice of mating animals from different purebred (PB) lines to produce crossbred (CB) animals, and is widely applied in pig and poultry production.This practice allows breeders to benefit from breed complementary by selecting parental lines for different traits and combine these traits in the crossbreds (Smith, 1964)
We found three studies that investigated the benefit of using the dominance model instead of the additive model for accuracy and response to selection
CB performance was primarily improved by increasing heterozygosity at overdominant loci, while with the additive model, CB performance was primarily improved by increasing the performance in the parental lines
Summary
Crossbreeding is the practice of mating animals from different purebred (PB) lines to produce crossbred (CB) animals, and is widely applied in pig and poultry production.This practice allows breeders to benefit from breed complementary by selecting parental lines for different traits and combine these traits in the crossbreds (Smith, 1964). Their results showed that, with 2,000 PB and 2,000 CB phenotypes for training, genotyping the 2,000 CB “in addition to” the PB improved accuracy by 0.02 for a trait with a heritability of 0.25 and an rpc of 0.7 (Table 6) This benefit was larger (0.04) when the number of genotyped CB animals was doubled to 4,000, or when own performance records of PB selection candidates were unavailable (model A-NOOP, 0.08). This difference in response depended on the accuracy of genomic prediction that was used in the equations In line with this result, a simulation study showed that, in the presence of dominance, response to selection per generation was increased by 0.07 gSD with a reference population of 400 CB animals, compared with a PB reference population of the same size (rpc not reported) (Kinghorn et al, 2010).
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