Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.     

Development of genetic evaluation for milk production traits of Holsteins in Japan

The procedure used for the genetic evaluation of dairy cattle in Japan has developed from a lactation sire–MGS model to a multiple‐lactation random regression test‐day animal model. Genetic evaluation of Holstein bulls in Japan began in 1989 with the use of field‐style progeny testing; dairy herd improvement program data from all over Japan were used, along with a sire and maternal grandsire model. In 1993, an animal model was introduced to estimate breeding values for yield and type traits. A random regression test‐day model was first applied in 2010. In the business of breeding dairy cattle, it is very important to users that estimated breeding values are reliable and stable among subsequent routine evaluations. With experience in the genetic evaluation of dairy cattle in Japan, Japanese researchers have found ways to improve the stability of estimated breeding values. These modifications involve changes in data editing, development of evaluation models, changes to the structures of unknown‐parent groups, awareness of the problems of predicting lactation yield from partial test‐day records, and adjustment for heterogeneity within herd variances. Here, I introduce developments in, and our experiences with, the genetic evaluation of yield traits of Holstein cattle in Japan.     

Linear and Poisson models for genetic evaluation of tick resistance in cross‐bred Hereford x Nellore cattle

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross‐bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick‐resistant animals.     

Optimal definition of contemporary groups for crossbred pigs in a joint purebred and crossbred genetic evaluation

In the pig industry, purebred animals are raised in nucleus herds and selected to produce crossbred progeny to perform in commercial environments. Crossbred and purebred performances are different, correlated traits. All purebreds in a pen have their performance assessed together at the end of a performance test. However, only selected crossbreds are removed (based on visual inspection) and measured at different times creating many small contemporary groups (CGs). This may reduce estimated breeding value (EBV) prediction accuracies. Considering this sequential recording of crossbreds, the objective was to investigate the impact of different CG definitions on genetic parameters and EBV prediction accuracy for crossbred traits. Growth rate (G_P) and ultrasound backfat (BF_P) records were available for purebreds. Lifetime growth (G_X) and backfat (BF_X) were recorded on crossbreds. Different CGs were tested: CG_all included farm, sex, birth year, and birth week; CG_week added slaughter week; and CG_day used slaughter day instead of week. Data of 124,709 crossbreds were used. The purebred phenotypes (62,274 animals) included three generations of purebred ancestors of these crossbreds and their CG mates. Variance components for four-trait models with different CG definitions were estimated with average information restricted maximum likelihood. Purebred traits’ variance components remained stable across CG definitions and varied slightly for BF_X. Additive genetic variances (and heritabilities) for G_X fluctuated more: 812 ± 36 (0.28 ± 0.01), 257 ± 15 (0.17 ± 0.01), and 204 ± 13 (0.15 ± 0.01) for CG_all, CG_week, and CG_day, respectively. Age at slaughter (AAS) and hot carcass weight (HCW) adjusted for age were investigated as alternatives for G_X. Both have potential for selection but lower heritabilities compared with G_X: 0.21 ± 0.01 (0.18 ± 0.01), 0.16 ± 0.02 (0.16 + 0.01), and 0.10 ± 0.01 (0.14 ± 0.01) for AAS (HCW) using CG_all, CG_week, and CG_day, respectively. The predictive ability, linear regression (LR) accuracy, bias, and dispersion of crossbred traits in crossbreds favored CG_day, but correlations with unadjusted phenotypes favored CG_all. In purebreds, CG_all showed the best LR accuracy, while showing small relative differences in bias and dispersion. Different CG scenarios showed no relevant impact on BF_X EBV. This study shows that different CG definitions may affect evaluation stability and animal ranking. Results suggest that ignoring slaughter dates in CG is more appropriate for estimating crossbred trait EBV for purebred animals.     

Comparison of models for genetic evaluation of number of inseminations to conception in Danish Holstein cows

Number of inseminations to conception (NINS), an important fertility trait, requires appropriate approaches for genetic evaluation due to its non‐normal distribution and censoring records. In this study, we analyzed NINS in 474 837 Danish Holstein cows at their first lactation by using seven models which deal with the categorical phenotypes and censored records in different manners, further assessed these models with regard to stability, lack of bias and accuracy of prediction. The estimated heritability from four models based on original NINS specified as a linear Gaussian model, categorical threshold model, threshold linear model and survival model were similar (0.031‐0.037). While for the other three models based on the binary response derived from NINS, referred as threshold model (TM), logistic and probit models (LOGM and PROM), the heritability were estimated as 0.027, 0.063 and 0.027, respectively. The model comparison concluded that different models could lead to slightly different sire rankings in terms of breeding values; a more complicated model led to less stability of prediction; the models based on the binary response derived from NINS (TM, LOGM and PROM) had slightly better performances in terms of unbiased and accurate prediction of breeding values.     

Impact of the event effect in genetic evaluation for ranking traits in horses

In genetic evaluation of horses, the genetic trend does not correspond into a phenotypic trend when using ranking as a phenotype due to its uniform distribution, and some other effects might be absorbing that trend. From a founder population, a further four discrete generations of 100 individuals were simulated under random mating. Then, ten additional discrete generations were simulated by selecting the best 10% of the animals. Likewise, an underlying variable with heritability 0.1 or 0.2, affected by an event environmental influence, generation and permanent environment, was simulated to establish the ranking assignment of 10 random participants or according to the competitive level for each event, in 10 or 100 structured or unstructured events. The ranking trait genetic evaluation model was tested to include or exclude the event effect and the permanent environment effect, depending on the scenario. The results showed that the event effect fitted the different competitive level of each event, leading to a 5% to 23% of selection response improvement for structured competitions. Therefore, the event effect should be included in the genetic evaluation models of horses. The permanent environment fitted or simulated did not significantly improve the selection response. The event effect explained the competition genetic level, by compensating the genetic trend obtained by selection.     

A method for the prediction of multitrait breeding values for use in stochastic simulation to compare progeny-testing schemes, with large progeny groups for proven sires

A method of approximating estimated breeding values (EBV) from a multivariate distribution of true breeding values (TBV) and EBV is proposed for use in large-scale stochastic simulation of alternative breeding schemes with a complex breeding goal. The covariance matrix of the multivariate distributions includes the additive genetic (co)variances and approximated prediction error (co)variances at different selection stages in the life of the animal. The prediction error (co)variance matrix is set up for one animal at a time, utilizing information on the selection candidate and its offspring, the parents, as well as paternal and maternal half- sibs. The EBV are a regression on TBV taking individual uncertainty into account, but with additional 'free' variation drawn at random. With the current information included in the calculation of the prediction error variance of a selection candidate, it is concluded that the method can be used to optimize progeny-testing schemes, where the progeny-tested sires are utilized with large progeny groups, e.g. through artificial insemination.     

Adjusting for heterogeneity of variance for carcass traits affects single and multiple trait selections in genetic evaluation of Japanese Black cattle

Heterogeneity of variance among subclasses of an effect is a potential source of bias in genetic evaluation. Degrees of the heterogeneity of variance among farm‐market‐year‐sex (FMYS) subclasses for carcass weight, beef marbling standard number, rib‐eye area, rib thickness and subcutaneous fat thickness were investigated in Japanese Black cattle. Consequences of adjusting for the heterogeneity on the predicted breeding values (PBVs) or on the genetic indexes derived from the PBVs of the five carcass traits were assessed. A total of 57 461 records were collected between 1997 and 2002 from steers and heifers fattened at farms across Japan. These records were grouped into 1591 FMYS subclasses. Bartlett's test showed that the degree of the heterogeneity of variance among the FMYS subclasses was sizeable in all traits (P < 0.0001). By applying a two‐step adjustment procedure it was possible to reduce the standard deviation, the coefficient of variation and the Gini coefficient of the phenotypic variances by 67.5% to 75.0% in the different traits. The applied adjustment caused a substantial re‐ranking of elite dams in the PBV for each trait as well as in the genetic index. This study provided evidence that the applied adjustment reduces the bias in the PBVs due to heterogeneous variances and increases the accuracy of bull‐dam selection.     

Multivariate genetic analysis to account for preselection and disqualified races in the genetic evaluation of racing performances in German trotters

Abstract

The genetic associations between racing performance and preselection of horses considered as the binary trait racing status (trotters without or with at least one racing performance in life were classified as 0 and 1, respectively) as well as disqualified races (disqualified and non-disqualified trotters were classified as 1 and 0, respectively) were analysed in German trotters. Variance components for racing performance traits square root of rank at finish, racing time per km, and log of earnings with racing status were estimated based on an animal model using REML. Heritabilities of racing status, racing time and rank at finish were 0.30, 0.21, and 0.06, respectively. The genetic correlations between racing status and racing time or rank at finish were ?0.74 and ?0.32, indicating that horses started at least once showed a higher genetic potential in racing time or finishing ability than never started horses. This showed the high preselection of German trotters especially based on racing time. To account for this preselection, it was recommended for additional use of racing status in the German evaluation system. Breeding values of the three racing performance traits were estimated by two distinct models, in- or excluding racing status and compared by using three criteria. Racing time per km showed the highest correlation (r=0.98) between breeding values evaluated by these two distinct models. Therefore, incorrect selection rate of horses using breeding values from the model without racing status, was lowest for racing time per km (9.7%). Selection response increased about 1% for this trait after including racing status in the model. For the estimation of rank at finish, inclusion of racing status in the multiple trait model was much more important as indicated by a low correlation between breeding values (r=0.29) and high percentage of incorrectly selected stallions (97.5%). The trait disqualified races was first analysed using an univariate threshold model. Heritability of this trait was low (h ²=0.12) and repeatability (r=0.43) showed a moderate magnitude. Using a linear multiple trait animal model, disqualified races showed a low heritability (h ²=0.05) and a moderate favourable genetic correlation (r _g=0.43) with racing time per km. Consequently, selection on racing time per km is expected to improve indirectly the reliability of racing performance. Combined selection of reduction in disqualified races and racing time may even further improve the reliability of racing trotters.     

Estimation of genetic parameters for longevity traits in dairy cattle: A review with focus on the characteristics of analytical models

Longevity is an economically important trait of dairy cattle for increasing the profitability of dairy management. The reasons for culling can be either voluntary (primarily productivity) or involuntary (primarily health and fertility). Longevity characteristics include: (i) true longevity (all culling reasons, including productivity); and (ii) functional longevity (all culling reasons, except productivity). Improvements to longevity are made to decrease the rate of involuntary culling rather than extend the herd life (HL). The proportional hazard model is useful for evaluating genetic ability for HL. However, the differences between estimates made using the proportional hazard model and those made using linear single or multiple‐trait animal models are not clear. The model commonly used for evaluation differs among countries. Productive traits, udder traits, and feet and legs traits are genetically correlated with longevity, and consequently these traits are used to indirectly evaluate longevity. The reliability of estimates of genetic ability for longevity is increased by combining direct and indirect estimates. In Japan, HL is evaluated using the multiple‐traits model. The genetic correlations between HL and other traits vary with the birth year. Therefore, these genetic correlations need to be reviewed regularly.     

Simulation study on the effects of excluding offspring information for genetic evaluation versus using genomic markers for selection in dog breeding

Different modes of selection in dogs were studied with a special focus on the availability of disease information. Canine hip dysplasia (CHD) in the German shepherd dog was used as an example. The study was performed using a simulation model, comparing cases when selection was based on phenotype, true or predicted breeding value, or genomic breeding value. The parameters in the simulation model were drawn from the real population data. The data on all parents and 40% of their progeny were assumed to be available for the genetic evaluation carried out by Gibbs sampling. With respect to the use of disease records on progeny, three scenarios were considered: random exclusion of disease data (no restrictions, N), general exclusion of disease data (G) and exclusion of disease data for popular sires (P). One round of selection was considered, and the response was expressed as change of mean CHD score, proportion of dogs scored as normal, proportion of dogs scored as clearly affected and true mean breeding value in progeny of popular sires in comparison with all sires. When no restrictions on data were applied, selection on breeding value was three times more efficient than when some systematic exclusion was practised. Higher selection response than in the exclusion cases was achieved by selecting on the basis of genomic breeding value and CHD score. Genomic selection would therefore be the method of choice in the future.     

不同蔗糖浓度、供体细胞保存温度和融合温度对小鼠体细胞克隆胚胎发育的影响

以昆明小鼠为实验动物,经过超数排卵后得到卵丘卵母细胞复合体(COCs),以卵丘细胞为核供体细胞,卵母细胞为核受体细胞进行核移植,分析比较了不同蔗糖浓度对小鼠卵母细胞去核时间、去核率及重构胚体外发育的影响,并探讨了供体细胞的保存温度和融合温度对重构胚体外发育的影响.结果表明,各蔗糖浓度组的去核率均达到100%,但3%、4...     

Establishment of a mouse- and egg-adapted strain for the evaluation of vaccine potency against H3N2 variant influenza virus in mice

Sporadic spreads of swine-origin influenza H3N2 variant (H3N2v) viruses were reported in humans, resulting in 437 human infections between 2011 and 2021 in the USA. Thus, an effective vaccine is needed to better control a potential pandemic for these antigenically distinct viruses from seasonal influenza. In this study, a candidate vaccine strain with efficient growth capacity in chicken embryos was established through serial blind passaging of A/Indiana/08/2011 (H3N2)v in mice and chicken embryos. Seven amino acid substitutions (M21I in PA; A138T, N165K, and V226A in HA; S312L in NP; T167I in M1; G62A in NS1 proteins) were found in the passaged viruses without a major change in the antigenicity. This mouse- and egg-adapted virus was used as a vaccine and challenge strain in mice to evaluate the efficacy of the H3N2v vaccine in different doses. Antibodies with high neutralizing titers were induced in mice immunized with 100 µg of inactivated whole-virus particles, and those mice were significantly protected from the challenge of homologous strain. The findings indicated that the established strain in the study was useful for vaccine study in mouse models.