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The low heritability and moderate repeatability of semen production traits in beef and dairy bulls suggest that nonadditive genetic effects, such as dominance and epistatic effects, play an important role in semen production and should therefore be considered in genetic improvement programs. In this study, the repeatability of semen production traits in Japanese Black bulls (JB) as beef bulls and Holstein bulls (HOL) as dairy bulls was evaluated by considering additive and nonadditive genetic effects using the Illumina BovineSNP50 BeadChip. We also evaluated the advantage of using more complete models that include nonadditive genetic effects by comparing the rank of genotyped animals and the phenotype prediction ability of each model. In total, 65,463 records for 615 genotyped JB and 48,653 records for 845 genotyped HOL were used to estimate additive and nonadditive (dominance and epistatic) variance components for semen volume (VOL), sperm concentration (CON), sperm motility (MOT), MOT after freeze-thawing (aMOT), and sperm number (NUM). In the model including both additive and nonadditive genetic effects, the broad-sense heritability (0.17 to 0.43) was more than twice as high as the narrow-sense heritability (0.04 to 0.11) for all traits and breeds, and the differences between the broad-sense heritability and repeatability were very small for VOL, NUM, and CON in both breeds. A large proportion of permanent environmental variance was explained by epistatic variance. The epistatic variance as a proportion of total phenotypic variance was 0.07 to 0.33 for all traits and breeds. In addition, heterozygosity showed significant positive relationships with NUM, MOT, and aMOT in JB and NUM in HOL, when the heterozygosity rate was included as a covariate. In a comparison of models, the inclusion of nonadditive genetic effects resulted in a re-ranking of the top genotyped bulls for the additive effects. Adjusting for nonadditive genetic effects could be expected to produce a more accurate breeding value, even if the models have similar fitting. However, including nonadditive genetic effects did not improve the ability of any model to predict phenotypic values for any trait or breed compared with the predictive ability of a model that includes only additive effects. Consequently, although nonadditive genetic effects, especially epistatic effects, play an important role in semen production traits, they do not improve prediction accuracy in beef and dairy bulls.Improving reproductive efficiency is a key objective in the beef and dairy cattle industries, and bull fertility is an important determinant of the reproductive performance of cows. The heritability of semen production traits is generally low; however, their repeatability is moderate. This difference between repeatability and heritability suggests that nonadditive genetic effects, such as dominance and epistatic genetic effects, could have an important role in semen production traits in bulls. Here, we estimated repeatability for semen production traits in beef and dairy bulls by considering additive and nonadditive genetic effects. Our results suggest that the contribution of nonadditive genetic effects to differences between repeatability and heritability was very high. Nonadditive genetic effects, especially epistatic effects, played important roles in semen production traits in beef and dairy bulls. However, we found that the inclusion of nonadditive genetic effects in a predictive model does not improve phenotypic prediction accuracy; further studies are needed to improve the predictive ability when using nonadditive genetic effects.

Objective: A formula is needed that is practical for current livestock breeding methods and that predicts the approximate rate of inbreeding (∆F) in populations where selection is performed according to four-path programs (sires to breed sons, sires to breed daughters, dams to breed sons, and dams to breed daughters). The formula widely used to predict inbreeding neglects selection, we need to develop a new formula that can be applied with or without selection.Methods: The core of the prediction is to incorporate the long-tern genetic influence of the selected parents in four-selection paths executed as sires to breed sons, sires to breed daughters, dams to breed sons, and dams to breed daughters. The rate of inbreeding was computed as the magnitude that is proportional to the sum of squared long-term genetic contributions of the parents of four-selection paths to the selected offspring.Results: We developed a formula to predict the rate of inbreeding in populations undergoing four-path selection on genomically enhanced breeding values and with discrete generations. The new formula can be applied with or without selection. Neglecting the effects of selection led to underestimation of the rate of inbreeding by 40% to 45%.Conclusion: The formula we developed here would be highly useful as a practical method for predicting the approximate rate of inbreeding (ΔF) in populations where selection is performed according to four-path programs.

OBJECTIVE Models for genomic selection assume that the reference population is an unselected population. However, in practice, genotyped individuals, such as progeny-tested bulls, are highly selected, and the reference population is created after preselection. In dairy cattle, the intensity of selection is higher in males than in females, suggesting that cows can be added to the reference population with less bias and loss of accuracy. The objective is to develop formulas applied to any genomic prediction studies or practice with preselected animals as reference population. METHODS We developed formulas for calculating the reliability and bias of genomically enhanced breeding values (GEBV) in the reference population where individuals are preselected on estimated breeding values. Based on the formulas presented, deterministic simulation was conducted by varying heritability, preselection percentage, and the reference population size. RESULTS The number of bulls equal to a cow regarding the reliability of GEBV was expressed through a simple formula for the reference population consisting of preselected animals. The bull population was vastly superior to the cow population regarding the reliability of GEBV for low-heritability traits. However, the superiority of reliability from the bull reference population over the cow population decreased as heritability increased. Bias was greater for bulls than cows. Bias and reduction in reliability of GEBV due to preselection was alleviated by expanding reference population. CONCLUSION Cows are easier in expanding reference population size compared with bulls and alleviate bias and reduction in reliability of GEBV of bulls which are highly preselected than cows by expanding the cow reference population.

We evaluated the genetic relationships (1) among feed efficiency traits with different fattening periods, (2) between feed efficiency traits and growth traits, and (3) between feed efficiency traits and carcass traits, to determine the influence of genetic factors on feed efficiency traits. In total, 4,578 Japanese Black cattle from a progeny testing program were used. Residual feed intake (RFI), residual BW gain (RG), and residual intake and BW gain (RIG) were defined as feed efficiency traits, and were measured for the first half (approximately 9 to 15 months of age), latter half (approximately 15 to 21 months of age), and total period of fattening (approximately 9 to 21 months of age). A single-trait animal model for estimating heritability and a two-trait animal model for estimating genetic and phenotypic correlations were used. The heritability estimates for RFI, RG, and RIG were different in each fattening period, ranging from 0.36 to 0.46, 0.19 to 0.28, and 0.28 to 0.34, respectively, and the heritability estimates for the total fattening period were greater than those for the first and latter halves separately. RIG showed the greatest preferred genetic correlation, with a greater feed conversion ratio than the other feed efficiency traits (ranging from -0.84 to -0.96). RG in the first and latter halves of the fattening period had different genetic correlations with the growth starting point (0.82 and -0.06, respectively) and maturity rate (0.49 and -0.51, respectively) of the Gompertz growth curve parameters, and is strongly dependent on the different fattening periods. Feed efficiency traits in different fattening periods had low genetic correlations with the carcass traits (from -0.05 to 0.19 for RFI; from 0.02 to 0.31 for RG; and from -0.11 to 0.20 for RIG). This study indicated the possibility for genetic improvement through the selection of high-RIG animals to decrease feed intake and increase BW gain without any unfavorable correlated responses affecting mature (asymptotic) weight and carcass grade.

OBJECTIVE In practical breeding, selection is often performed by ignoring the accuracy of evaluations and applying economic weights directly to the selection index coefficients of genetically standardized traits. The denominator of the standardized component trait of estimated genetic evaluations in practical selection varies with its reliability. Whereas theoretical methods for calculating the selection index coefficients of genetically standardized traits account for this variation, practical selection ignores reliability and assumes that it is equal to unity for each trait. The purpose of this study was to clarify the effects of ignoring the accuracy of the standardized component trait in selection criteria on selection responses and economic weights in retrospect. METHODS Theoretical methods were presented accounting for reliability of estimated genetic evaluations for the selection index composed of genetically standardized traits. RESULTS Selection responses and economic weights in retrospect resulting from practical selection were greater than those resulting from theoretical selection accounting for reliability when the accuracy of the estimated breeding value (EBV) or genomically enhanced breeding value (GEBV) was lower than those of the other traits in the index, but the opposite occurred when the accuracy of the EBV or GEBV was greater than those of the other traits. This trend was more conspicuous for traits with low economic weights than for those with high weights. CONCLUSION Failure of the practical index to account for reliability yielded economic weights in retrospect that differed from those obtained with the theoretical index. Our results indicated that practical indices that ignore reliability delay genetic improvement. Therefore, selection practices need to account for reliability, especially when the reliabilities of the traits included in the index vary widely.

Meat composition in beef is related to eating quality and food functionality. Genetic parameters for several meat compositions including free amino acid, peptide and sugar, however, remain poorly described. In this study, we estimated genetic parameters for 51 meat components, including free amino acids, peptides, sugars and fatty acid compositions, and two carcase traits in 1,354 heifers and 1,797 steers of Japanese Black cattle. Heritability estimates were generally equivalent to or moderately greater than those in previous studies of this breed. Genetic correlations between free amino acids, peptides and sugars and carcase traits were often negative, suggesting a trade-off between traits. Using two-trait animal models that treat records from the two sexes as different traits, we estimated sex-specific heritabilities and cross-sex genetic correlations which indicate the sex differences in genetic architecture. In these analyses, 12 traits showed significant heritability differences between sexes and cross-sex genetic correlations occasionally deviated from unity. These results could be used to inform future breeding schemes and investigations of the genetic architecture of meat compositions in beef.

The semen production traits of bulls from 2 major cattle breeds in Japan, Holstein and Japanese Black, were analyzed comprehensively using genome-wide markers. Weaker genetic correlations were observed between the 2 age groups (1 to 3 yr old and 4 to 6 yr old) regarding semen volume and sperm motility compared with those observed for sperm number and motility after freeze-thawing. The preselection of collected semen for freezing had a limited effect. Given the increasing importance of bull proofs at a young age because of genomic selection and the results from preliminary studies, we used a multiple-trait model that included motility after freeze-thawing with records collected at young ages. Based on variations in contemporary group effects, accounting for both seasonal and management factors, Holstein bulls may be more sensitive than Japanese Black bulls to seasonal environmental variations; however, the seasonal variations of contemporary group effects were smaller than those of overall contemporary group effects. The improvement of motilities, recorded immediately after collection and freeze-thawing, was observed in recent years; thus, good management and better freeze-thawing protocol may alleviate seasonal phenotypic differences. The detrimental effects of inbreeding were observed in all traits of both breeds; accordingly, the selection of candidate bulls with high inbreeding coefficients should be avoided per general recommendations. Semen production traits have never been considered for bull selection. However, negative genetic trends were observed. The magnitudes of the estimated h were comparable to those of other economically important traits. A single-step genomic BLUP will provide more accurate predictions of breeding values compared with BLUP; thus, marker genotype information is useful for estimating the genetic merits of bulls for semen production traits. The selection of these traits would improve sperm viability, a component related to breeding success, and alleviate negative genetic trends.

The objectives of this study were to estimate genetic parameters and to perform a genome‐wide association study (GWAS) for predicted methane‐related traits in Japanese Black steers. The methane production and yield traits were predicted using on‐farm measurable traits, such as dry matter intake and average daily gain. A total of 4,578 Japanese Black steers, which were progenies of 362 sires genotyped with imputed 551,995 single nucleotide polymorphisms (SNPs), had phenotypes of predicted methane‐related traits during the total fattening period (52 weeks). For the estimation of genetic parameters, the estimated heritabilities were moderate (ranged from 0.57 to 0.60). In addition, the estimated genetic correlations of methane production traits with most of carcass traits and feed‐efficiency traits were unfavorable, but those of methane yield traits were favorable or low. For the GWAS, no genome‐wide significant SNP was detected, but a total of four quantitative trait locus (QTL) regions that explained more than 5.0% of genetic variance were localized on the genome, and some candidate genes associated with growth and feed‐efficiency traits were located on the regions. Our results suggest that the predicted methane‐related traits are heritable and some QTL regions for the traits are localized on the genome in Japanese Black steers.

The objectives of this study were to better understand the genetic architecture and the possibility of genomic evaluation for feed efficiency traits by (i) performing genome-wide association studies (GWAS), and (ii) assessing the accuracy of genomic evaluation for feed efficiency traits, using single-step genomic best linear unbiased prediction (ssGBLUP)-based methods. The analyses were performed in residual feed intake (RFI), residual body weight gain (RG), and residual intake and body weight gain (RIG) during three different fattening periods. The phenotypes from 4,578 Japanese Black steers, which were progenies of 362 progeny-tested bulls and the genotypes from the bulls were used in this study. The results of GWAS showed that a total of 16, 8, and 12 gene ontology terms were related to RFI, RG, and RIG, respectively, and the candidate genes identified in RFI and RG were involved in olfactory transduction and the phosphatidylinositol signaling system, respectively. The realized reliabilities of genomic estimated breeding values were low to moderate in the feed efficiency traits. In conclusion, ssGBLUP-based method can lead to understand some biological functions related to feed efficiency traits, even with small population with genotypes, however, an alternative strategy will be needed to enhance the reliability of genomic evaluation.

Equations were developed to predict the equilibrium response to the aggregate genotype in units of genetic standard deviation by using selection index composed of GEBVs. A situation was considered in which four-path selection was executed as sires to breed sons, sires to breed daughters, dams to breed sons, and dams to breed daughters. In practice, index selection comprising standardized GEBVs is often used for the aggregate genotype in units of genetic standard deviation in accordance with the standardization of the true genetic value in the aggregate genotype. Economic weights of the breeding goal in units of genetic standard deviation are used as the coefficients of the standardized GEBVs of the practical index. However, the variance of GEBV necessary to standardize GEBV changes from generation to generation. It meant that economic weights in the breeding goal corresponding to the practical index changed during generations, although relative economic weights in the breeding goal among the component traits should be the same during generations. The practical index assumes GEBVs as estimates with no prediction errors, although GEBVs are estimates with prediction errors, which resulted in overestimation of the selection accuracy of the practical index. The asymptotic genetic gain from the practical index reacted sharply to the uncertainty in GEBVs compared with the theory-based index. Consequently, especially in practical breeding, the correct aggregate genotype in selection index theory associated with the practically used index must be examined and breeding goal should not include a component related to the uncertainty in GEBVs, because economic weights fluctuate during generations in line with the uncertainty in GEBVs.

Formulas were developed for calculating the asymptotic response from index and single trait selection for differential selection among male and female parents and of parents to produce male versus female replacements (four-path programs). The formulas were then used to study the effects on selection response in several scenarios. Index selection based on genomically enhanced breeding value (GEBV) achieved substantial genetic improvement even for low-heritability traits when their relative economic weights are greater than those of the other moderate-heritability index traits in spite of positive or negative genetic correlation between the two index traits. Index selection overwhelmed single trait selection with regard to selection response, particularly when genetic correlation was negative between the two index traits. When the reduction in genetic (co)variance after selection was ignored, the initial genetic response overestimated the asymptotic response and the overestimation was more remarkable for a moderately heritable trait than for a lowly heritable trait. The overestimation for the moderately heritable trait was more conspicuous in single trait selection than in index selection. The underestimation of the initial response during generation 0 due to the index selection was found for the lowly heritable traits when the lowly heritable traits had negative genetic correlation with the other moderately heritable traits and when economic weights of the lowly heritable traits were substantially small as compared to the other moderately heritable traits. The accounting percentage from a selection path from dams to breed sons for the total response per generation increased approximately from 30% to 39% when the selection percentage decreased from 10% to 1%. Applying selection based on GEBV in a selection path from dams to breed sons would make a great contribution to genetic improvement. Equilibrium correlated response to an unselected trait due to index selection became negative when initial genetic correlation during generation 0 between aggregate genotype and an unselected trait was negative. Consequently, we need to construct reference population for all the traits connected with the breeding goal in order to enable the genomic evaluations of all the traits connected with the breeding goal.

Because fatty acid composition influences the flavor and texture of meat, controlling it is particularly important for cattle breeds such as the Japanese Black, characterized by high meat quality. We evaluated the predictive ability of single-step genomic best linear unbiased prediction (ssGBLUP) in fatty acid composition of Japanese Black cattle by assessing the composition of seven fatty acids in 3088 cattle, of which 952 had genome-wide marker genotypes. All sires of the genotyped animals were genotyped, but their dams were not. Cross-validation was conducted for the 952 animals. The prediction accuracy was higher with ssGBLUP than with best linear unbiased prediction (BLUP) for all traits, and in an empirical investigation, the gain in accuracy of using ssGBLUP over BLUP increased as the deviations in phenotypic values of the animals increased. In addition, the superior accuracy of ssGBLUP tended to be more evident in animals whose maternal grandsire was genotyped than in other animals, although the effect was small.