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For beef semen usage on dairy cows, much of the research has focused on the performance of the crossbred calves, yet little focus has been given to the subsequent performance of the cow herself. This study aimed to evaluate the performance of dairy cows for milk yield, fertility, and survival traits after giving birth to beef × dairy crossbred calves and compare this with the performance after giving birth to purebred dairy calves. Further, we aimed to study if the effect of a difficult calving was the same regardless of whether the calf was purebred dairy or beef × dairy crossbred. Phenotypic records from 587,288 calving events from 1997 to 2020 were collected from the Swedish milk recording system from cows of the dairy breeds Swedish Red (SR) and Swedish Holstein. The sire beef breeds studied were Aberdeen Angus, Hereford (combined in category LHT), Charolais, Limousin, and Simmental (category HVY). Sixteen traits were defined and grouped in 3 categories: cumulative and 305-d milk, fat, and protein yield, daily milk yield, and 75-d milk yield as yield traits; calving to first insemination interval, calving to last insemination interval, first to last insemination interval, calving interval, and number of inseminations as fertility traits; and survival to 75 d or to next calving and lactation length as measures of survival. The data were analyzed for all traits for first and second parities separately using mixed linear models, with a focus on the estimates of cow breed by service sire breed combinations. All traits in parity 2 were adjusted for previous 305-d milk yield based on the expectation that low-yielding cows would more likely to be inseminated with beef semen. Overall, milk yield was lower after beef × dairy calvings compared with the purebred dairy calvings. The largest effects were found on cumulative yields and in second parity, with lower effects for yields early in lactation and yields in first parity. The largest decrease was 13 to 14 kg (0.12 phenotypic SD) for cumulative fat yield when breeding beef breed sires with purebred SR dams. For fertility traits, for most breed combinations, the effects were not large enough to be significant. Conversely, all beef × dairy crossbred combinations showed significantly lower results for survival to the next lactation, and mostly also for lactation length. There was some indication that dairy cows with beef × dairy calvings in parity 2 that were the result of maximum 2 inseminations in parity 1, had lower survival than corresponding calvings resulting from more than 2 inseminations. This could indicate that the former cows were marked for culling already when inseminated. There was generally an unfavorable effect of a difficult calving on all traits, however, there were almost no significant interactions between calving performance and dam by sire breed combination, and these interactions were never significant in first parity. [ABSTRACT FROM AUTHOR]

This study simulated the consequences of crossbreeding between Swedish Holstein and Swedish Red on herd dynamics and herd profitability under Swedish conditions. Two base herds were simulated using a stochastic herd simulation model, SimHerd Crossbred. The herds reflected average Swedish conventional and organic herds having purebred Swedish Holstein. For each base herd, 3 breeding strategies were simulated: pure-breeding, 2-breed terminal crossbreeding, and 2-breed rotational crossbreeding. The terminal crossbreeding strategy implied having a nucleus of Swedish Holstein and a proportion of F 1 Swedish Red × Swedish Holstein crossbred cows within the same herd. The crossbreds in this herd did not produce replacement heifers but exclusively beef × dairy cross calves. Beef semen was also used in the pure-breeding (10–20% in cows) and the rotational crossbreeding (40% in cows) strategies to retain a limited surplus of replacement heifers. To ensure an adequate number of crossbreds in the terminal crossbreeding strategy, X-sorted sexed semen was used for insemination in all the purebred heifers. The outcome was 67% purebred and 31% F 1 crossbreds in the herd. In addition, 31% heterosis was expressed compared with 67% heterosis expressed using a 2-breed rotational crossbreeding strategy. Compared with the pure-breeding strategy, crossbreeding increased the annual contribution margin per cow by €20 to €59, with the rotational crossbreeding strategy creating the largest profitability. The increased profitability was mainly due to improved functional traits, especially fertility. For the conventional production system, the replacement rate was 39.3% in the pure-breeding strategy and decreased to 35.8 and 30.1% in the terminal and rotational crossbreeding strategy, respectively. Similar changes happened in the organic production system. Additionally, the crossbreeding strategies earned €22 to €42 more annually per cow from selling live calves for slaughter due to the extended use of beef semen. Milk production was similar between pure-breeding and terminal crossbreeding, and only decreased 1 to 2% in rotational crossbreeding. These results show that crossbreeding between Swedish Holstein and Swedish Red can be profitable in both conventional and organic Swedish herds using the strategies we have simulated. However, some aspects remain to be investigated, such as the economically optimal breeding strategy, genetic improvement, and transition strategies. [ABSTRACT FROM AUTHOR]

In this study, we aimed to estimate and compare the genetic parameters of dry matter intake (DMI), energycorrected milk (ECM), and body weight (BW) as 3 feed efficiency-related traits across lactation in 3 dairy cattle breeds (Holstein, Nordic Red, and Jersey). The analyses were based on weekly records of DMI, ECM, and BW per cow across lactation for 842 primiparous Holstein cows, 746 primiparous Nordic Red cows, and 378 primiparous Jersey cows. A random regression model was applied to estimate variance components and genetic parameters for DMI, ECM, and BW in each lactation week within each breed. Phenotypic means of DMI, ECM, and BW observations across lactation showed to be in very similar patterns between breeds, whereas breed differences lay in the average level of DMI, ECM, and BW. Generally, for all studied breeds, the heritability for DMI ranged from 0.2 to 0.4 across lactation and was in a range similar to the heritability for ECM. The heritability for BW ranged from 0.4 to 0.6 across lactation, higher than the heritability for DMI or ECM. Among the studied breeds, the heritability estimates for DMI shared a very similar range between breeds, whereas the heritability estimates for ECM tended to be different between breeds. For BW, the heritability estimates also tended to follow a similar range between breeds. Among the studied traits, the genetic variance and heritability for DMI varied across lactation, and the genetic correlations between DMI at different lactation stages were less than unity, indicating a genetic heterogeneity of feed intake across lactation in dairy cattle. In contrast, BW was the most genetically consistent trait across lactation, where BW among all lactation weeks was highly correlated. Genetic correlations between DMI, ECM, and BW changed across lactation, especially in early lactation. Energy-corrected milk had a low genetic correlation with both DMI and BW at the beginning of lactation, whereas ECM was highly correlated with DMI in mid and late lactation. Based on our results, genetic heterogeneity of DMI, ECM, and BW across lactation generally was observed in all studied dairy breeds, especially for DMI, which should be carefully considered for the recording strategy of these traits. The genetic correlations between DMI, ECM, and BW changed across lactation and followed similar patterns between breeds. [ABSTRACT FROM AUTHOR]

Experiences from international sire evaluation indicate that the multiple-trait across-country evaluation method is sensitive to changes in genetic variance over time. Top bulls from birth year classes with inflated genetic variance will benefit, hampering reliable ranking of bulls. However, none of the methods available today enable countries to validate their national evaluation models for heterogeneity of genetic variance. We describe a new validation method to fill this gap comprising the following steps: estimating withinyear genetic variances using Mendelian sampling and its prediction error variance, fitting a weighted linear regression between the estimates and the years under study, identifying possible outliers, and defining a 95% empirical confidence interval for a possible trend in the estimates. We tested the specificity and sensitivity of the proposed validation method with simulated data using a real data structure. Moderate (M) and small (S) size populations were simulated under 3 scenarios: a control with homogeneous variance and 2 scenarios with yearly increases in phenotypic variance of 2 and 10%, respectively. Results showed that the new method was able to estimate genetic variance accurately enough to detect bias in genetic variance. Under the control scenario, the trend in genetic variance was practically zero in setting M. Testing cows with an average birth year class size of more than 43,000 in setting M showed that tolerance values are needed for both the trend and the outlier tests to detect only cases with a practical effect in larger data sets. Regardless of the magnitude (yearly increases in phenotypic variance of 2 or 10%) of the generated trend, it deviated statistically significantly from zero in all data replicates for both cows and bulls in setting M. In setting S with a mean of 27 bulls in a year class, the sampling error and thus the probability of a false-positive result clearly increased. Still, overall estimated genetic variance was close to the parametric value. Only rather strong trends in genetic variance deviated statistically significantly from zero in setting S. Results also showed that the new method was sensitive to the quality of the approximated reliabilities of breeding values used in calculating the prediction error variance. Thus, we recommend that only animals with a reliability of Mendelian sampling higher than 0.1 be included in the test and that low heritability traits be analyzed using bull data sets only. [ABSTRACT FROM AUTHOR]

Summary The aims of this study were to investigate the presence of genetic variation for susceptibility to pathogen-specific mastitis and to examine whether haplotypes of an identified quantitative trait locus with effect on unspecific mastitis resistance had different effects on specific mastitis pathogens. Bacteriological data on mastitis pathogens were obtained from the diagnostic laboratory at the Swedish National Veterinary Institute. The data were mainly from subclinical cases of mastitis but also clinical cases were included. Variance components were estimated for incidence of the six most frequent pathogens using Markov Chain Monte Carlo methodology via Gibbs sampling. Genetic variation for susceptibility to pathogen-specific mastitis was higher compared to estimates of general resistance to clinical mastitis in most other studies. However, because of the non-random nature of data collection, comparisons to other studies should be made by caution. The effect of haplotype on the risk of being infected by a given mastitis pathogen, relative to other pathogens, was studied using an allele substitution model. Although there were no significant haplotype substitution effects on the resistance to any of the six mastitis pathogens, there was a significant difference between the effects of two of the haplotypes regarding the risk of acquiring a Streptococcus dysgalactiae infection. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study was to assess the potential of video image analysis (VIA) in predicting various wholesale carcass cuts in cattle. Video image analysis and meat cut weights were available from two different sources: an experimental (n=346) and a commercial dataset (n=281). The cattle used were crossbred steers (predominant breeds were Belgian Blue, Angus, Friesian, Charolais, Holstein, Limousin, and Simmental) in the experimental dataset, and crossbred heifers (predominant breeds were Limousin, Belgian Blue, Charolais, and Simmental) in the commercial dataset. In both datasets, the meat cuts were grouped into four groups based on retail value: Low Value Cuts (LVC), Medium Value Cuts (MVC), High Value Cuts (HVC), and Very High Value Cuts (VHVC); total meat weight was calculated as the sum of the individual meat cut weights. In addition, total bone weight and total fat weight were available in the experimental dataset. In both datasets, a calibration and a validation sub-dataset were created for each of the carcass cut groups. Multiple regression analyses were applied to each calibration dataset to predict the cuts from using three different sets of models based on the predictors: 1) carcass weight only, 2) carcass weight plus EUROP carcass classification, and 3) carcass weight plus VIA parameters. The accuracy of predicting yields of cuts was superior to prediction of cut yields as a proportion of the carcass weight. Across both the experimental and the commercial datasets, the proportion of variation of wholesale cut yields in the validation dataset explained (R2) ranged from 0.33 (total fat weight in the experimental dataset) to 0.91 (total meat weight in the experimental dataset) using carcass weight as the sole predictor. The R2 increased to between 0.65 (LVC in the commercial dataset) and 0.97 (total meat weight in the experimental dataset) when carcass weight plus VIA variables were used as predictors. In the analyses of both the experimental and the commercial data, models that included the VIA variables had the lowest root mean square error of prediction across traits. Mean bias and correlations between the residuals and predicted values were generally not different from zero. Results from this study show that wholesale cuts in steers and heifers can be accurately predicted using multiple regression models incorporating carcass weight and VIA variables. The carcass images routinely stored provide a powerful tool for use in a beef breeding program to select for more valuable carcasses. [Copyright &y& Elsevier]

The aim of this study was to estimate genetic parameters and genetic trends for hip (HD) and elbow dysplasia (ED) in Swedish Rottweiler (RW) and Bernese Mountain Dog (BMD). Analyses were based on screening results of hip status for 14 693 RW and 8221 BMD and elbow status for 11 891 RW and 7963 BMD, as well as pedigree data for 16 614 RW and 9835 BMD, recorded by the Swedish Kennel Club. Components of (co)variance and breeding values were obtained with a mixed linear animal model. The model included the fixed effects of sex, birth month, age at screening and a combined random effect of clinic and year of examination. The need to include genetic groups for phantom parents in the model was evaluated by comparison of two different models: with and without genetic groups. Estimated heritabilities for HD and ED were between 0.34 and 0.42. The genetic correlation between the traits was weak and positive for RW ( r g = 0.23 ± 0.05) and not different from zero for BMD ( r g = 0.06 ± 0.06). F-statistics of the genetic group effects were not significant, implying that genetic groups do not need to be included in the model. Genetic trends indicated a genetic improvement in both traits. However, a faster genetic progress is expected if selection is based on predicted breeding values rather than phenotype. Based on the results, a statistical model for routine prediction of breeding values for HD and ED in Swedish dogs was suggested. [ABSTRACT FROM AUTHOR]

Access to individual performance records opens up possibilities for treatment of genotype by environment interaction in international genetic evaluations. The ability to distinguish similar from dissimilar environments is thus important. Reaction norms were used in this study to evaluate several variables for their suitability to classify production environments for studies on genotype by environment interaction. Reaction norms describe the phenotypic expression of a genotype as a function of the environment, and can be modelled by random regression on environmental descriptors. Fifteen variables that measure aspects of management, genetic composition and climate were computed on herd level. Suitability of each variable to detect genotype by environment interaction was assessed through likelihood ratio tests for significant linear or quadratic random regression terms. First lactation records from approximately 40 000 Guernsey cows in four countries (Australia, Canada, USA and Republic of South Africa) were used. Variables with significant effect were: herd size, within-herd standard deviation of lactation yield, peak milk yield, persistency, days to peak production, calving pattern, age at first calving, rate of maturity, and annual rainfall. Genetic correlation between extreme environments for milk peak yield, within-herd standard deviation and annual rainfall were lower than 0.91, indicating that re-ranking of animals may occur. [Copyright &y& Elsevier]

Presents a study which aimed to estimate genetic parameters for the multiple-trait herd cluster model, the reaction norm model and three models that treat country as production environment, using data on Guernsey cows from four countries. Methodology; Results and discussion.

Cattle develop preferential relationships with other individuals in the herd. These social interactions between individuals have a significant impact on both animal welfare and production. Given the relevance of social behaviour in dairy cattle, scientific studies have focused on understanding social interactions among cattle. These may also be influenced by individual area preferences, particularly when animals are housed in confined spaces. Therefore, investigating the relationship between individual area preferences and social interactions is essential for understanding social behaviour in dairy cattle. Real-time location systems provide the opportunity to monitor individual area preferences and social contacts at the same time. This study aims to assess the impact of dairy cows' area preferences on their daily social contacts and to determine the potential implications of overlooking individual area preferences in social behaviour studies. The individual position of the lactating cows was automatically collected once per second for two months on a Swedish commercial farm housing dairy cows inside a free-stall barn. The location data of 243 lactating cows was used to construct the social networks and to estimate the similarity of the area utilisation distributions between these individuals. The effect of utilisation distribution similarity in social networks was investigated by applying separable temporal exponential random graph mixed models. The role of different cow characteristics in the similarity of the utilisation distributions was assessed through a linear mixed model. Our analyses stressed the importance of similarity of area preference, parity, kindergarten effect, and filial relatedness in shaping daily social contacts in dairy cattle. The kindergarten effect refers to the effect on cow behaviour of being grouped together in the early stages of their lives. Similarity of area preference was influenced by the kindergarten effect and relatedness by pedigree, which favoured interactions between these individuals. The described approach allowed to disassociate the area preference from the social contacts between cows, providing more accurate results of the importance of the cow's characteristics on their social behaviour. [Display omitted] • Area preference affects daily social contacts in dairy cattle. • Kindergarten effect and filial relatedness influence area preference similarities between cows. • Individual area preferences should be considered when exploring social contacts in dairy cattle. [ABSTRACT FROM AUTHOR]

Farmers play a key role in conserving native livestock breeds, but without economic support, farms with native breeds may not be viable. We hypothesized that terminal crossbreeding can improve herd economy and decrease the economic support needed from society. Three scenarios were simulated using SimHerd Crossbred: a herd of purebred Swedish Polled Cattle, a herd of purebred Swedish Red, and a herd of 75% Swedish Polled Cattle and 25% F1 crossbreds. The results showed annual contribution margin per cow in the herd can be increased by €181 by crossbreeding compared with pure-breeding with the native breed, giving a 13.6% growth in contribution margin. However, the needed cost in subsidies paid by the government will remain unchanged if the population size of the native breed is to be maintained. Combining a crossbreeding strategy with the marketing of niche products may facilitate the conservation of native cattle. [ABSTRACT FROM AUTHOR]

The rennet-induced coagulation ability of milk is important in cheese production. For Swedish Red Dairy Cattle (RDC), this ability is reduced because of a high prevalence of noncoagulating (NC) milk. In this study, we simultaneously combined genetic parameters for NC milk, milk coagulation properties, milk composition, physical traits, and milk protein composition. Our aim was to estimate heritability and genetic and phenotypic correlations for NC milk and 24 traits (milk coagulation properties, milk composition, physical traits, and milk protein composition). Phenotypes and ∼7,000 SNP genotypes were available for all 600 Swedish RDC. The genotypes were imputed from ∼7,000 SNP to 50,000 SNP. Variance components and genetic parameters were estimated with an animal model. In Swedish RDC, a moderate heritability estimate of 0.28 was found for NC milk. For the other 24 traits, heritability estimates ranged from 0.12 to 0.77 (standard errors from 0.08 to 0.18). A total of 300 phenotypic and genetic correlations were estimated. For phenotypic and genetic correlations, 172 and 95 were significant, respectively. In general, most traits showing significant genetic correlations also showed significant phenotypic correlations. In this study, phenotypic and genetic correlations with NC milk suggest that many correlations between traits exist, making it difficult to predict the real consequences on the composition of milk, if selective breeding is applied on NC milk. We speculate that some of these consequences may lead to changes in the composition of milk, most likely affecting its physical and organoleptic properties. However, our results suggest that κ-casein could be used as an indicator trait to predict the occurrence of NC milk at the herd level. [ABSTRACT FROM AUTHOR]

In this study, we explored mating allocation in Holstein using genomic information for 24,333 Holstein females born in Denmark, Finland, and Sweden. We used 2 data sets of bulls: the top 50 genotyped bulls and the top 25 polled genotyped bulls on the Nordic total merit scale. We used linear programming to optimize economic scores within each herd, considering genetic level, genetic relationship, semen cost, the economic impact of genetic defects, polledness, and β-casein. We found that it was possible to reduce genetic relationships and eliminate expression of genetic defects with minimal effect on the genetic level in total merit index. Compared with maximizing only Nordic total merit index, the relative frequency of polled offspring increased from 13.5 to 22.5%, and that of offspring homozygous for β-casein (A2A2) from 66.7 to 75.0% in one generation, without any substantial negative impact on other comparison criteria. Using only semen from polled bulls, which might become necessary if dehorning is banned, considerably reduced the genetic level. We also found that animals carrying the polled allele were less likely to be homozygous for β-casein (A2A2) and more likely to be carriers of the genetic defect HH1. Hence, adding economic value to a monogenic trait in the economic score used for mating allocation sometimes negatively affected another monogenetic trait. We recommend that the comparison criteria used in this study be monitored in a modern genomic mating program. [ABSTRACT FROM AUTHOR]

In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows. [ABSTRACT FROM AUTHOR]

The amount of variance captured in genetic estimations may depend on whether a pedigree-based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits ( PGM) using pedigree-based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population-trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree-based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree-based relationship matrix. The ratio of the genomic to pedigree-based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress. [ABSTRACT FROM AUTHOR]

Breeding to reduce the prevalence of categorically scored hip dysplasia ( HD), based on phenotypic assessment of radiographic hip status, has had limited success. The aim of this study was to evaluate two selection strategies for improved hip status: truncation selection based on phenotypic record versus best linear unbiased prediction ( BLUP), using stochastic simulation and selection scenarios resembling those in real dog populations. In addition, optimum contribution selection ( OCS) was evaluated. Two traits were considered: HD (as a categorical trait with five classes and a heritability of 0.45 on the liability scale) and a continuous trait (with a heritability of 0.25) intended to represent other characteristics in the breeding goal. A population structure mimicking that in real dog populations was modelled. The categorical nature of HD caused a considerably lower genetic gain compared to simulating HD as a continuous trait. Genetic gain was larger for BLUP selection than for phenotypic selection in all scenarios. However, BLUP selection resulted in higher rates of inbreeding. By applying OCS, the rate of inbreeding was lowered to about the same level as phenotypic selection but with increased genetic improvement. For efficient selection against HD, use of BLUP breeding values should be prioritized. In small populations, BLUP should be used together with OCS or similar strategy to maintain genetic variation. [ABSTRACT FROM AUTHOR]

Summary The consequences of assuming a zero environmental covariance between a binary trait 'test-status' and a continuous trait on the estimates of genetic parameters by restricted maximum likelihood and Gibbs sampling and on response from genetic selection when the true environmental covariance deviates from zero were studied. Data were simulated for two traits (one that culling was based on and a continuous trait) using the following true parameters, on the underlying scale: h2 = 0.4; rA = 0.5; rE = 0.5, 0.0 or −0.5. The selection on the continuous trait was applied to five subsequent generations where 25 sires and 500 dams produced 1500 offspring per generation. Mass selection was applied in the analysis of the effect on estimation of genetic parameters. Estimated breeding values were used in the study of the effect of genetic selection on response and accuracy. The culling frequency was either 0.5 or 0.8 within each generation. Each of 10 replicates included 7500 records on 'test-status' and 9600 animals in the pedigree file. Results from bivariate analysis showed unbiased estimates of variance components and genetic parameters when true rE = 0.0. For rE = 0.5, variance components (13-19% bias) and especially (50-80%) were underestimated for the continuous trait, while heritability estimates were unbiased. For rE = −0.5, heritability estimates of test-status were unbiased, while genetic variance and heritability of the continuous trait together with were overestimated (25-50%). The bias was larger for the higher culling frequency. Culling always reduced genetic progress from selection, but the genetic progress was found to be robust to the use of wrong parameter values of the true environmental correlation between test-status and the continuous trait. Use of a bivariate linear-linear model reduced bias in genetic evaluations, when data were subject to culling. [ABSTRACT FROM AUTHOR]

Presents a study which developed functions of descriptive herd variables to define distinct production environments that account for the relative importance of each variable and the correlation between variables, and apply this model to milk production data from dairy countries. Materials and methods; Results and discussion; Conclusion.

In this study, we compared mating allocations in Nordic Red Dairy Cattle using genomic information. We used linear programming to optimize different economic scores within each herd, considering genetic level, semen cost, the economic impact of recessive genetic defects, and genetic relationships. We selected 9,841 genotyped females born in Denmark, Finland, or Sweden in 2019 for mating allocations. We used 2 different pedigree relationship coefficients, the first tracing the pedigree 3 generations back from the parents of the potential mating and the second based on all available pedigree information. We used 3 different genomic relationship coefficients, 1 SNP-by-SNP genomic relationship and 2 based on shared genomic segments. We found high correlations (≥0.83) between the pedigree and genomic relationship measures. The mating results showed that it was possible to reduce the different genetic relationships between parents with minimal effect on genetic level. Including the cost of known recessive genetic defects eliminated expression of genetic defects. It was possible to reduce genomic relationships between parents with pedigree measures, but it was best done with genomic measures. Linear programming maximized the economic score for all herds studied within seconds, which means that it is suitable for implementation in mating software to be used by advisors and farmers. [ABSTRACT FROM AUTHOR]

The development of breeding tools, such as genomic selection and sexed semen, has progressed rapidly in dairy cattle breeding during the past decades. In combination with beef semen, these tools are adopted increasingly at herd level. Dairy crossbreeding is emerging, but the economic and genetic consequences of combining it with the other breeding tools are relatively unknown. We investigated 5 different sexed semen schemes where 0, 50, and 90% of the heifers; 50% of the heifers + 25% of the first-parity cows; and 90% of the heifers + 45% of the first-parity cows were bred to sexed semen. The 5 schemes were combined in scenarios managing pure-breeding or terminal crossbreeding, including genomic testing of all newborn heifers or no testing, and keeping Swedish Red or Swedish Holstein as an initial breed. Thus, 40 scenarios were simulated, combining 2 stochastic simulation models: SimHerd Crossbred (operational returns) and ADAM (genetic returns). The sum of operational and genetic returns equaled the total economic return. Beef semen was used in all scenarios to limit the surplus of replacement heifers. Terminal crossbreeding implied having a nucleus of purebred females, where some were inseminated with semen of the opposite breed. The F 1 crossbred females were inseminated with beef semen. The reproductive performance played a role in improving the benefit of any of the tools. The most considerable total economic returns were achieved when all 4 breeding tools were combined. For Swedish Holstein, the highest total economic return compared with a pure-breeding scenario, without sexed semen and genomic test, was achieved when 90% sexed semen was used in heifers and 45% sexed semen was used for first-parity cows combined with genomic test and crossbreeding (+€58, 33% crossbreds in the herd). The highest total economic return for Swedish Red compared with a pure-breeding scenario, without sexed semen and genomic test, was achieved when 90% sexed semen was used in heifers combined with genomic test and crossbreeding (+€94, 46% crossbreds in the herd). Terminal crossbreeding resulted in lower genetic returns across the herd compared with the corresponding pure-breeding scenarios but was compensated by a higher operational return. [ABSTRACT FROM AUTHOR]

Milk that does not coagulate after rennet addition, also called noncoagulating (NC) milk, is unwanted in cheese production due to prolonged processing time. Amounts of whey and casein proteins, genetic variants, as well as posttranslational modifications (PTM) of proteins are all contributing factors in rennet-induced coagulation of milk. In this study, we conducted a wide-ranging investigation of milk proteins in milk samples from 616 Swedish Red dairy cattle using liquid chromatography-high resolution mass spectrometry. Relative concentration of proteins, genetic variants, and PTM were compared between NC milk and coagulating milk. The PTM investigated were phosphorylation of caseins and glycosylation of κ-casein. Several genetic variants and PTM were found, including rare phosphorylation variants of the α S -caseins. Genetic variants were found to effect the expressed amount of different proteins. Further, the effect of protein amounts and PTM on a binary NC milk trait was modeled using a generalized linear model. The model showed that NC milk significantly correlated with higher relative concentrations of α-lactalbumin and β-casein and lower relative concentrations of β-lactoglobulin and κ-casein. Regarding PTM of caseins, an effect on NC milk from a lower relative concentration of α S1 -casein with 8 phosphate groups were found, even though an effect from total relative concentration of α S1 -casein was not found. This study has provided insights into protein variants and PTM important for NC milk to improve this undesirable property. [ABSTRACT FROM AUTHOR]

This study compared the abilities of virgin heifer genomically enhanced breeding values (GEBV) and parent average breeding values (PA) to predict future cow performance. To increase confidence in genomic technology among farmers, a clear demonstration of the relationship between genomic predictions and future phenotypes is needed. We analyzed 12 different traits in first parity, including production, conformation, fertility, and other functional traits. Phenotype data were obtained from national milk recording schemes and breeding values from the Nordic Cattle Genetic Evaluation. Direct genomic breeding values were calculated using genomic BLUP and combined with traditional breeding values, using bivariate blending. The data covered 14,862 Red Dairy Cattle, 17,145 Holstein, and 7,330 Jersey genotyped virgin heifers born between 2013 and 2015 in Denmark, Finland, and Sweden. Phenotypes adjusted for systematic environmental effects were used as measures of cow performance. Two methods were used to compared virgin heifer GEBV and PA regarding their ability to predict future cow performance: (1) correlations between breeding values and adjusted phenotypes, (2) ranking cows into 4 quartiles for their virgin heifer GEBV or PA, and calculating actual cow performance for each quartile. We showed that virgin heifer GEBV predicted cow performance significantly better than PA for the vast majority of analyzed traits. The correlations with adjusted phenotypes were 38 to 136% higher for GEBV than for PA in Red Dairy Cattle, 42 to 194% higher for GEBV in Holstein, and 11 to 78% higher for GEBV in Jersey. The relative change between GEBV bottom and top quartiles compared with that between PA bottom and top quartiles ranged from 9 to 261% for RDC, 42 to 138% for Holstein, and 4 to 90% for Jersey. Hence, farmers in Denmark, Finland, and Sweden can have confidence in using genomic technology on their herds. [ABSTRACT FROM AUTHOR]

The aim of this simulation study was to investigate whether it is possible to detect the effect of genomic preselection on Mendelian sampling (MS) means or variances obtained by the MS validation test. Genomic preselection of bull calves is 1 additional potential source of bias in international evaluations unless adequately accounted for in national evaluations. Selection creates no bias in traditional breeding value evaluation if the data of all animals are included. However, this is not the case with genomic preselection, as it excludes culled bulls. Genomic breeding values become biased if calculated using a multistep procedure instead of, for example, a single-step method. Currently, about 60% of the countries participating in international bull evaluations have already adopted genomic selection in their breeding schemes. The data sent for multiple across-country evaluation can, therefore, be very heterogeneous, and a proper validation method is needed to ensure a fair comparison of the bulls included in international genetic evaluations. To study the effect of genomic preselection, we generated a total of 50 replicates under control and genomic preselection schemes using the structures of the real data and pedigree from a medium-size cow population. A genetic trend of 15% of the genetic standard deviation was created for both schemes. In carrying out the analyses, we used 2 different heritabilities: 0.25 and 0.10. From the start of genomic preselection, all bulls were genomically preselected. Their MS deviations were inflated with a value corresponding to selection of the best 10% of genomically tested bull calves. For cows, the MS deviations were unaltered. The results revealed a clear underestimation of bulls' breeding values (BV) after genomic preselection started, as well as a notable deviation from zero both in true and estimated MS means. The software developed recently for the MS validation test already produces yearly MS means, and they can be used to devise an appropriate test. Mean squared true MS of genomically preselected bulls was clearly inflated. After correcting for the simulated preselection bias, the true genetic variance was smaller than the parametric value used to simulate BV, and also below the variance based on the estimated BV. Based on this study, the lower the trait's heritability, the stronger the bias in estimated BV and MS means and variances. Daughters of genomically preselected bulls had higher true and estimated BV compared with the control scheme and only slightly elevated MS means, but no effect on genetic variances was observed. [ABSTRACT FROM AUTHOR]

In order to reduce the prevalence of inherited diseases in pedigree dogs, the feasibility of implementation of an international breeding program was investigated. One prerequisite is a strong genetic correlation between countries and our objective was to estimate this correlation for canine hip dysplasia (HD) across three countries to evaluate the feasibility of an international genetic evaluation. Data were provided by the Société Centrale Canine (SCC, France), Svenska Kennelklubben (SKK, Sweden) and The Kennel Club (KC, UK) on Golden retriever and Labrador retriever dogs. Trivariate analysis on the three different modes of scoring HD in France, Sweden and the UK was performed using a mixed linear animal model. Heritability, genetic correlation, number of common sires, genetic similarity, selection differentials and accuracy of selection were calculated. The estimated heritabilities of Golden retrievers (Labrador retrievers) for HD scores were 0.28 (0.15), 0.28 (0.29) and 0.41 (0.34) in France, Sweden and the UK, respectively. The feasibility of performing a genetic evaluation of HD across countries was indicated by the favourable genetic correlations estimated between score modes (ranged from 0.48 to 0.99). The accuracy of selection for the most recent birth year cohorts of male dogs was not improved by international evaluation compared to national evaluation. Improvement in genetic progress can however be achieved by selection across populations in different countries, particularly for small populations, which were indicated by the large difference between selection differentials based on the national and international evaluations. [ABSTRACT FROM AUTHOR]

The aim of this study was to estimate and compare genetic trends in Swedish Red cattle using a full multiple-trait ( MT) model and trait-group-wise models for female fertility, udder health and protein yield. Field data for maiden heifers from 1989 and cows with a first and second lactation between 1990 and 2007 were included. (Co)variance components were estimated prior to prediction of breeding values. The estimated genetic trends were clearly favourable for protein yield and udder conformation, and in most cases neutral to favourable for clinical mastitis and calving to first insemination. In maiden heifers, the trends were neutral for number of inseminations per service period. Unfavourable genetic trends were estimated for number of inseminations in the first two lactations, but the trends seemed less unfavourable from evaluations within trait groups compared with when using the full MT model. Excluding maiden heifer data affected genetic trends less than using trait-group-wise analyses instead of a full MT model. Unfavourable genetic trends in functional traits may be missed unless the traits are evaluated in a MT model including traits under strong selection. [ABSTRACT FROM AUTHOR]

Merging pedigree databases across countries may improve the ability of kennel organizations to monitor genetic variability and health-related issues of pedigree dogs. We used data provided by the Société Centrale Canine (France), Svenska Kennelklubben (Sweden) and the Kennel Club ( UK) to study the feasibility of merging pedigree databases across countries and describe breeding practices and international gene flow within the following four breeds: Bullmastiff ( BMA), English setter ( ESE), Bernese mountain dog ( BMD) and Labrador retriever ( LBR). After merging the databases, genealogical parameters and founder contributions were calculated according to the birth period, breed and registration country of the dogs. Throughout the investigated period, mating between close relatives, measured as the proportion of inbred individuals (considering only two generations of pedigree), decreased or remained stable, with the exception of LBR in France. Gene flow between countries became more frequent, and the origins of populations within countries became more diverse over time. In conclusion, the potential to reduce inbreeding within purebred dog populations through exchanging breeding animals across countries was confirmed by an improved effective population size when merging populations from different countries. [ABSTRACT FROM AUTHOR]

A breeding scheme using genomic selection and an indicator trait for environmental impact ( EI) was studied to find the most effective recording strategy in terms of annual monetary genetic gain and breakeven price for the recording of indicator traits. The breakeven price shows the investment space for developing a recording system for an indicator trait. The breeding goal consisted of three traits - milk production, functional trait and environmental impact - with economic values of €83, €82 and €−83, respectively. The first scenario included only breeding goal traits and no indicator traits (No IT). The other scenarios included all three breeding goal traits and one indicator trait ( IT) for EI. The indicator traits were recorded on a large scale (stayability after first lactation and stature), medium scale (live weight and greenhouse gases ( GHG) measured in the breath of the cow during milking) or small scale (residual feed intake and total enteric methane measured in a respiration chamber). In the scenario with stayability, the genetic gain in EI was over 11% higher than it was in No IT. The breakeven price of recording stayability was €8 per record. Stayability is easy to record in the national milk recording system, and its use as an indicator trait for EI would not generate any additional recording costs. Therefore, stayability would be a good indicator trait to use to mitigate EI. The highest genetic gain in EI (23% higher compared to No IT) was achieved when the GHG measured in the breath of the cow was used as indicator trait. The breakeven price for this indicator trait was €29 per record in the reference population. Ideally the recording of a specific indicator trait for EI would take place when: (i) the genetic correlation between the IT and EI is high; and (ii) the number of phenotypic records for the indicator trait is high enough to achieve a moderately high reliability of direct genomic values. [ABSTRACT FROM AUTHOR]

Using a combined multi-breed reference population, this study explored the influence of model specification and the effect of including a polygenic effect on the reliability of genomic breeding values (DGV and GEBV). The combined reference population consisted of 2986 Swedish Red Breed (SRB) and Finnish Ayrshire (FAY) dairy cattle. Bayesian methodology (common prior and mixture models with different prior distribution settings for the marker effects) as well as a best linear unbiased prediction with a genomic relationship matrix [genomic best linear unbiased predictor (GBLUP)] was used in the prediction of DGV. Mixture models including a polygenic effect were used to predict GEBV. In total, five traits with low, high and medium heritability were analysed. For the models using a mixture prior distribution, reliabilities of DGV tended to decrease with an increasing proportion of markers with small effects. The influence of the inclusion of a polygenic effect on the reliability of DGV varied across traits and model specifications. Average correlation between DGV with the Mendelian sampling term, across traits, was highest ( R2 = 0.25) for the GBLUP model and decreased with increasing proportion of markers with large effects. Reliabilities increased when DGV and parent average information were combined in an index. The GBLUP model with the largest gain across traits in the reliability of the index achieved the highest DGV mean reliability. However, the polygenic models showed to be less biased and more consistent in the estimation of DGV regardless of the model specifications compared with the mixture models without the polygenic effect. [ABSTRACT FROM AUTHOR]

Summary The genetic evaluation of Icelandic horses is currently based on results from breeding field tests of riding ability and conformation. The effect of integrating competition traits and/or test status into the genetic evaluation was studied concerning estimation bias, predictive ability, accuracy, correlations between breeding values and ranking of sires. Breeding field test data included 19 954 records from horses assessed in 11 countries during 1994-2008. Competition data included 44 160 records from 7687 horses competing in Iceland and Sweden in 1998-2008. Test status was defined as attendance of horses born in Iceland at breeding field tests and/or in competition. Overall, there were trivial differences between different genetic evaluation models regarding estimation bias and predictive ability. Very strong correlations were estimated between breeding values for combined indexes of conformation, riding ability and total score from different models. Higher accuracy was achieved for most of the traits when competition traits and/or test status were added to the model. Sires ranked differently when the new traits were added to the genetic evaluation model. It was concluded that competition traits should be integrated into the genetic evaluation. Further analyses on genetic parameters for test status and its relationship with the other traits are needed for future inclusion of test status in the genetic evaluation. [ABSTRACT FROM AUTHOR]

Three models for genetic evaluation of milk yield of Uruguayan Holstein cattle were compared using 159 169 lactation records from 81 928 cows calving between 1989 and 1998. Model I included the effects of herd-year-season, parity by age group, additive genetic merit, permanent environment, and residual. Model II included all effects in Model I, as well as number of days open and length of the dry period. Model III included all factors in Model II, and it accommodated heterogeneity of variance within contemporary groups (CG) through a pre-adjustment of the data based on empirical Bayes estimates of the CG variance. Estimates of heritability for milk yield were 0.23, 0.24 and 0.25, and estimates of repeatability were 0.55, 0.56 and 0.57 for Models I, II and III, respectively. Models were contrasted by examining changes in sire ranking and by a cross-validation procedure, based on the ability of the models to predict first, second and later lactations. Data were divided into two subsets, and records from one subset were predicted using location parameters estimated from the other subset. A resampling procedure was used to minimise the dependency on the sample structure. Correspondence between observed and predicted values was assessed in terms of square root of empirical mean square errors of prediction, percentage squared bias and the coefficient of determination ‘R2’. Adjustment for heterogeneous CG variance had a marked effect on rankings of animals, especially elite cows, where correlations between solutions from Models I and II versus Model III ranged from 0.53 to 0.80. The percentage of animals selected in common by each pair of models decreased when selection intensity increased. Cross-validation analyses suggested that an assumption of heterogeneity of CG variance is tenable, especially in later lactations, whereas some doubts arise in first lactations, most probably due to the data structure used in the analyses. [Copyright &y& Elsevier]