Search

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.

Background Growth curves have been widely used in genetic analyses to gain insights into the growth characteristics of both animals and plants. However, several questions remain unanswered, including how the initial phenotypes affect growth and what is the duration of any such impact. For beef cattle production in Japan, calves are procured from farms that specialize in reproduction and then moved to other farms where they are fattened to achieve their market/purchase value. However, the causal effect of growth, while calves are on the reproductive farms, on their growth during fattening remains unclear. To investigate this, we developed a model that combines a structural equation with a growth curve model. The causal effect was modeled with B-splines, which allows inference of the effect as a curve. We fitted the proposed structural growth curve model to repeated measures of body weight from a Japanese beef cattle population (n = 3831) to estimate the curve of the causal effect of the calves’ initial weight on their trajectory of growth when they are on fattening farms. Results Maternal and reproduction farm effects explained 26% of the phenotypic variance of initial weight at fattening farms. The structural growth curve model was fitted to remove the effects of these factors in growth curve analysis at fattening farms. The estimated curve of causal effects remained at approximately 0.8 for 200 d after the calves entered the fattening farms, which means that 64% of the phenotypic variance was explained by the initial weight. Then, the effect decreased linearly and disappeared approximately 620 d after entering the fattening farms, which corresponded to an average age of 871.5 d. Conclusions The proposed model is expected to provide more accurate estimates of genetic values for growth patterns because the confounding causal factors such as maternal and reproduction farm effects are removed. Moreover, examination of the inferred curve of the causal effect enabled us to estimate the effect of a calf’s initial weight at arbitrary times during growth, which could provide suitable information for decision-making when shifting the time of slaughter, building models for genetic evaluation, and selecting calves for market. Electronic supplementary material The online version of this article (10.1186/s12711-019-0461-y) contains supplementary material, which is available to authorized users.

Background Genomic prediction is now an essential technology for genetic improvement in animal and plant breeding. Whereas emphasis has been placed on predicting the breeding values, the prediction of non-additive genetic effects has also been of interest. In this study, we assessed the potential of genomic prediction using non-additive effects for phenotypic prediction in Japanese Black, a beef cattle breed. In addition, we examined the stability of variance component and genetic effect estimates against population size by subsampling with different sample sizes. Results Records of six carcass traits, namely, carcass weight, rib eye area, rib thickness, subcutaneous fat thickness, yield rate and beef marbling score, for 9850 animals were used for analyses. As the non-additive genetic effects, dominance, additive-by-additive, additive-by-dominance and dominance-by-dominance effects were considered. The covariance structures of these genetic effects were defined using genome-wide SNPs. Using single-trait animal models with different combinations of genetic effects, it was found that 12.6–19.5 % of phenotypic variance were occupied by the additive-by-additive variance, whereas little dominance variance was observed. In cross-validation, adding the additive-by-additive effects had little influence on predictive accuracy and bias. Subsampling analyses showed that estimation of the additive-by-additive effects was highly variable when phenotypes were not available. On the other hand, the estimates of the additive-by-additive variance components were less affected by reduction of the population size. Conclusions The six carcass traits of Japanese Black cattle showed moderate or relatively high levels of additive-by-additive variance components, although incorporating the additive-by-additive effects did not improve the predictive accuracy. Subsampling analysis suggested that estimation of the additive-by-additive effects was highly reliant on the phenotypic values of the animals to be estimated, as supported by low off-diagonal values of the relationship matrix. On the other hand, estimates of the additive-by-additive variance components were relatively stable against reduction of the population size compared with the estimates of the corresponding genetic effects.

Intensive use of a few elite sires has increased the risk of the manifestation of deleterious recessive traits in cattle. Substantial genotyping data gathered using single-nucleotide polymorphism (SNP) arrays have identified the haplotypes with homozygous deficiency, which may compromise survival. We developed Japanese Black cattle haplotypes (JBHs) using SNP array data (4843 individuals) and identified deleterious recessive haplotypes using exome sequencing of 517 sires. We identified seven JBHs with homozygous deficiency. JBH_10 and JBH_17 were associated with the resuming of estrus after artificial insemination, indicating that these haplotypes carried deleterious mutations affecting embryonic survival. The exome data of 517 Japanese Black sires revealed that AC_000165.1:g.85341291C>G of IARS in JBH_8_2, AC_000174.1:g.74743512G>T of CDC45 in JBH_17, and a copy variation region (CNVR_27) of CLDN16 in JBH_1_1 and JBH_1_2 were the candidate mutations. A novel variant AC_000174.1:g.74743512G>T of CDC45 in JBH_17 was located in a splicing donor site at a distance of 5 bp, affecting pre-mRNA splicing. Mating between heterozygotes of JBH_17 indicated that homozygotes carrying the risk allele died around the blastocyst stage. Analysis of frequency of the CDC45 risk allele revealed that its carriers were widespread throughout the tested Japanese Black cattle population. Our approach can effectively manage the inheritance of recessive risk alleles in a breeding 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.

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 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.

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.

Various mutations in the AE1 (anion exchanger 1, band 3) gene cause dominant hereditary spherocytosis, a common congenital hemolytic anemia associated with deficiencies of AE1 of different degrees and loss of mutant protein from red blood cell membranes. To determine the mechanisms underlying decreases in AE1 protein levels, we employed K562 and HEK293 cell lines and Xenopus oocytes together with bovine wild-type AE1 and an R664X nonsense mutant responsible for dominant hereditary spherocytosis to analyze protein expression, turnover, and intracellular localization. R664X-mutant protein underwent rapid degradation and caused specifically increased turnover and impaired trafficking to the plasma membrane of the wild-type protein through hetero-oligomer formation in K562 cells. Consistent with those observations, co-expression of mutant and wild-type AE1 reduced anion transport by the wild-type protein in oocytes. Transfection studies in K562 and HEK293 cells revealed that the major pathway mediating degradation of both R664X and wild-type AE1 employed endoplasmic reticulum (ER)-associated degradation through the proteasomal pathway. Proteasomal degradation of R664X protein appeared to be independent of both ubiquitylation and N-glycosylation, and aggresome formation was not observed following proteasome inhibition. These findings indicate that AE1 R664X protein, which is associated with dominant hereditary spherocytosis, has a dominant-negative effect on the expression of wild-type AE1.

The implementation of genomic selection for Japanese Black cattle, known for rich marbling of their meat, is now being explored. Although multiple-step methods are often adopted for dairy cattle, they present shortcomings such as bias and loss of information in addition to operational complexity. These can be avoided using single-step genomic BLUP (ssGBLUP) based on the relationship matrix H, which is constructed from the numerator relationship matrix (A) augmented by the genomic relationship matrix (G). This study assessed the use of ssGBLUP for 3 economically important traits in Japanese Black cattle. Three aspects of ssGBLUP that are important for practical use were examined specifically: the mixing proportions of blending G with A, selection of subsets of genotyped animals used for constructing H, and prediction ability for ungenotyped animals. Different mixing proportions were tested to assess the influence of these proportions on variance component estimation and prediction accuracy. For all traits, the highest or nearly highest accuracy was obtained when the adopted mixing proportion provided heritability closest to that inferred based on A. However, the accuracy did not increase greatly under adjustment of the mixing proportion, thereby suggesting that the influence of the mixing proportion on the accuracy was limited. Genotype data of influential bulls showed a greater contribution to accuracy than that of bulls that were less influential. Genotyping animals with phenotypic records increased the accuracy. It can be prioritized over genotyping bulls that are not influential on the population. These results are expected to present good guides to the future expansion of genotyped populations. Even for animals without genotype data but with genotyped sires, ssGBLUP provided more accurate prediction than BLUP did. For both phenotype and breeding value prediction, ssGBLUP provides more accurate prediction than BLUP, suggesting its usefulness in genomic selection in Japanese Black cattle.