The breeding scheme of a Swiss sire line was modeled to compare different target traits and information sources for selection against boar taint. The impact of selection against boar taint on production traits was assessed for different economic weights of boar taint compounds. Genetic gain and breeding costs were evaluated using ZPlan+, a software based on selection index theory, gene flow method and economic modeling. Scenario I reflected the currently practiced breeding strategy as a reference scenario without selection against boar taint. Scenario II incorporated selection against the chemical compounds of boar taint, androstenone (AND), skatole (SKA) and indole (IND) with economic weights of -2.74, -1.69 and -0.99 Euro per unit of the log transformed trait, respectively. As information sources, biopsy-based performance testing of live boars (BPT) was compared with genomic selection (GS) and a combination of both. Scenario III included selection against the subjectively assessed human nose score (HNS) of boar taint. Information sources were either station testing of full and half sibs of the selection candidate or GS against HNS of boar taint compounds. In scenario I, annual genetic gain of log-transformed AND (SKA; IND) was 0.06 (0.09; 0.02) Euro, which was because of favorable genetic correlations with lean meat percentage and meat surface. In scenario II, genetic gain increased to 0.28 (0.20; 0.09) Euro per year when conducting BPT. Compared with BPT, genetic gain was smaller with GS. A combination of BPT and GS only marginally increased annual genetic gain, whereas variable costs per selection candidate augmented from 230 Euro (BPT) to 330 Euro (GS) or 380 Euro (both). The potential of GS was found to be higher when selecting against HNS, which has a low heritability. Annual genetic gain from GS was higher than from station testing of 4 full sibs and 76 half sibs with one or two measurements. The most effective strategy to reduce HNS was selecting against chemical compounds by conducting BPT. Because of heritabilities higher than 0.45 for AND, SKA and IND and high genetic correlations to HNS, the (correlated) response in units of the trait could be increased by 62% compared with scenario III with GS and even by 79% compared with scenario III, with station testing of siblings with two measurements. Increasing the economic weights of boar taint compounds amplified negative effects on average daily gain, drip loss and intramuscular fat percentage.

Reliable selection criteria are required for young riding horses to increase genetic gain by increasing accuracy of selection and decreasing generation intervals. In this study, selection strategies incorporating genomic breeding values (GEBVs) were evaluated. Relevant stages of selection in sport horse breeding programs were analyzed by applying selection index theory. Results in terms of accuracies of indices (r TI ) and relative selection response indicated that information on single nucleotide polymorphism (SNP) genotypes considerably increases the accuracy of breeding values estimated for young horses without own or progeny performance. In a first scenario, the correlation between the breeding value estimated from the SNP genotype and the true breeding value (5 accuracy of GEBV) was fixed to a relatively low value of r mg 5 0.5. For a low heritability trait (h 2 5 0.15), and an index for a young horse based only on information from both parents, additional genomic information doubles r TI from 0.27 to 0.54. Including the conventional information source 'own performance' into the before mentioned index, additional SNP information increases r TI by 40%. Thus, particularly with regard to traits of low heritability, genomic information can provide a tool for well-founded selection decisions early in life. In a further approach, different sources of breeding values (e.g. GEBV and estimated breeding values (EBVs) from different countries) were combined into an overall index when altering accuracies of EBVs and correlations between traits. In summary, we showed that genomic selection strategies have the potential to contribute to a substantial reduction in generation intervals in horse breeding programs.Keywords: accuracy of selection, breeding strategies, generation interval, genomic selection, sport horse ImplicationsThe availability of genomic information demands proper assessment of its impact on practical horse breeding programs. Accuracies of conventional breeding values do not increase significantly until a stallion is aged 8 to 12 years and his progeny enters competition. We showed that additional genomic information considerably increases the accuracy of breeding values estimated for foals, young horses without own performance, and horses without progeny performance. Therefore, genomic selection (GS) enables selection at an earlier stage, shortening generation intervals and opening room for increased genetic progress. Our results indicate that horse breeding organizations could likely benefit from the application of GS.

The availability of genomic information demands proper evaluation on how the kind (phenotypic versus genomic) and the amount of information influences the interplay of heritability (h(2)), genetic correlation (r(GiGj)) and economic weighting of traits with regard to the standard deviation of the index (σI). As σI is directly proportional to response to selection, it was the chosen parameter for comparing the indices. Three selection indices incorporating conventional and genomic information for a two trait (i and j) breeding goal were compared. Information sources were chosen corresponding to pig breeding applications. Index I incorporating an own performance in trait j served as reference scenario. In index II, additional information in both traits was contributed by a varying number of full-sibs (2, 7, 50). In index III, the conventional own performance in trait j was combined with genomic information for both traits. The number of animals in the reference population (NP = 1000, 5000, 10,000) and thus the accuracy of GBVs were varied. With more information included in the index, σI became more independent of r(GiGj), h(j)(2) and relative economic weighting. This applied for index II (more full-sibs) and for index III (more accurate GBVs). Standard deviations of index II with seven full-sibs and index III with NP = 1000 were similar when both traits had the same heritability. If the heritability of trait j was reduced (h(j)(2) = 0.1), σI of index III with NP = 1000 was clearly higher than for index II with seven full-sibs. When enhancing the relative economic weight of trait j, the decrease in σI of the conventional full-sib index was much stronger than for index III. Our results imply that NP = 1000 can be considered a minimum size for a reference population in pig breeding. These conclusions also hold for comparing the accuracies of the indices.

No abstract