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The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Although dairy goat production, characterized by traditional production on small farms, is an important source of income in the Czech Republic and Slovakia, locally adapted breeds have not been fully consolidated over the last 100 yr due to large fluctuations in population size and inconsistent breeding programs that allowed for different crossbreeding strategies. Our main objective in this study was therefore to assess the conservation status of 4 Czech (Alpine Goat, White Shorthair, Brown Shorthair, and Czech Landrace) and 1 Slovak (Slovak White Shorthair) local goat breeds, to analyze their population structure and admixture, and to estimate their relatedness to several neighboring breeds. Our analyses included 142 goats belonging to 5 local breeds genotyped with the Illumina 50K BeadChip, and 618 previously genotyped animals representing 15 goat breeds from Austria and Switzerland (all analyses based on 46,862 autosomal SNPs and 760 animals). In general, the conservation status of the Czech and Slovak local goat breeds was satisfactory, with the exception of the Brown Shorthair goat, as the analyzed parameters (heterozygosity, haplotype richness, runs of homozygosity–based inbreeding, and effective population size) were mostly above the median of 20 breeds. However, for all 5 Czech and Slovakian breeds, an examination of historical effective population size indicated a substantial decline about 8 to 22 generations ago. In addition, our study revealed that the Czech and Slovakian breeds are not fully consolidated; for instance, White Shorthair and Brown Shorthair were not clearly distinguishable. Considerable admixture, especially in Czech Landrace (effective number of parental clusters = 4.2), and low but numerous migration rates from other Austrian and Swiss breeds were found. These results provide valuable insights for future breeding programs and genetic diversity management of local Czech and Slovak goat breeds. [Display omitted] [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. In recent years, genomic selection (GS) has accelerated genetic gain in dairy cattle breeds worldwide. Despite the evident genetic progress, several dairy populations have also encountered challenges such as heightened inbreeding rates and reduced effective population sizes. The challenge has been to find a balance between achieving substantial genetic gain while managing genetic diversity within the population, thereby mitigating the negative effects of inbreeding depression. This study aims to elucidate the impact of GS on pedigree and genomic rates of inbreeding (ΔF) and coancestry (ΔC) in Nordic Jersey (NJ) and Holstein (NH) cattle populations. Furthermore, key genetic metrics, including the generation interval (L), effective population size (Ne), and future effective population size (FNe) were assessed between 2 time periods, before and after GS, and across distinct animal cohorts in both breeds: females, bulls, and approved semen-producing bulls (AI-sires). Analysis of ΔF and ΔC revealed distinct trends across the studied periods and animal groups. Notably, there was a consistent increase in yearly ΔF for most animal groups in both breeds. An exception was observed in NH AI-sires, which demonstrated a slight decrease in yearly ΔF. Moreover, NJ displayed minimal changes in yearly ΔC between the periods, whereas NH exhibited elevated ΔC values across all animal groups. Particularly striking was the substantial increase in yearly ΔC within the NH female population, surging from 0.02% to 0.39% between the periods. Implementation of GS resulted in a reduction of the generation interval across all animal cohorts in both NJ and NH breeds. However, the extent of reduction was more pronounced in males compared with females. This reduction in generation interval influenced generational changes in ΔF and ΔC. Bulls and AI-sires of both breeds exhibited reduced generational ΔF between periods, in contrast to females that demonstrated an opposing pattern. Between the periods, NJ maintained a relatively stable Ne (29.4 before and 30.3 after GS), whereas NH experienced a notable decline from 54.3 to 42.8. Female groups in both breeds displayed a negative Ne trend, whereas males demonstrated either neutral or positive Ne developments. Regarding FNe, NJ exhibited positive FNe development with an increase from 40.7 to 57.2. The opposite was observed in NH, where FNe decreased from 198.8 to 42.7. In summary, it was evident that the genomic methods could detect differences between the populations and changes in ΔF and ΔC more efficiently than pedigree methods. Implementation of GS yielded positive outcomes within the NJ population regarding the rate of coancestry but the opposite was observed with NH. Moreover, analysis of ΔC data hints at the potential to decrease future ΔF through informed mating strategies. Conversely, NH faces more pressing concerns, even though ΔF remains comparatively modest in contrast to what has been observed in other Holstein populations. These findings underscore the necessity of genomic control of inbreeding and coancestry with strategic changes in the Nordic breeding schemes for dairy to ensure long-term sustainability in the forthcoming years. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Methane emissions will be added to many national ruminant breeding programs in the coming years. Little is known about the covariance structure of CH 4 traits over a lactation, which is important for optimizing recording strategies and establishing optimal genetic evaluation models. Our aim was to study CH 4 over a lactation using random regression (RR) models, and to compare the accuracy to a fixed regression repeatability model under different phenotyping strategies. Data were available from repeated measurements of CH 4 concentrations (ppm) recorded in the feed bins of milking robots on 52 commercial dairy farms in the Netherlands. In total, 36,370 averaged weekly records were available from 4,664 cows. Genetic parameters were estimated using a fixed regression model, and a RR model with first- to fifth-order Legendre polynomials for the additive genetic and within-lactation permanent environmental effect. The mean heritability (± SE) was 0.17 ± 0.04, and the mean within-lactation repeatability was 0.56 ± 0.03. The genetic correlations between DIM were high and ranged from 0.34 ± 0.36 to 1.00 ± <0.01. Permanent environmental correlations showed large deviations and ranged from −0.73 ± 0.08 to 1.00 ± <0.01. With a large number of full lactation daughter CH 4 records per bull, the reliability was not sensitive to using the fixed versus the RR model. However, when shorter periods were recorded at the start and end of the lactation, the fixed regression model resulted in a loss of reliability up to 28% for bulls. Assuming the fixed model when the true (co)variance structure is reflected by the RR model, more than twice as long of a recording from the start of lactation was required to achieve maximum reliability for a bull. Thus, a too simplistic model could result in implementing too little recording, and in lower genetic gains than predicted from the reliability. [ABSTRACT FROM AUTHOR]

Gains through breeding can be achieved through a combination of both between-breed and within-breed selection. Two suites of traits of particular interest to dairy producers when selecting beef bulls for mating to dairy females are calving-related attributes and the expected value of the subsequent calf, the latter usually being a function of expected carcass value. Estimated breed effects can be informative, particularly in the absence of across-breed genetic evaluations. The objective of the present study was to use a large national database of the progeny from beef-on-dairy matings to estimate the mean breed effects of the used beef sires. Calving performance (i.e., gestation length, calving difficulty score, and perinatal morality) as well as calf value were investigated; a series of slaughter-related traits (i.e., carcass metrics and age at slaughter) of the prime progeny were also investigated. Phenotypic data on up to 977,037 progeny for calving performance, 79,903 for calf price and 103,175 for carcass traits (including dairy × dairy progeny for comparative purposes) were used; sire breeds represented were Holstein-Friesian, Angus, Aubrac, Belgian Blue, Charolais, Hereford, Limousin, Salers, and Simmental. Large interbreed differences existed. The mean gestation length of male calves from beef sires varied from 282.3 d (Angus) to 287.4 d (Limousin) which were all longer than the mean of 280.9 d for Holstein-Friesian sired male calves. Relative to a Holstein-Friesian sire, the odds of dystocia varied from 1.43 (Angus) to 4.77 (Belgian Blue) but, once adjusted for both the estimated maternal genetic merit of the dam and direct genetic merit of the calf for calving difficulty, the range in odds ratios shrunk. A difference of €125.4 existed in calf sale price between the progeny of the different beef breeds investigated which represented over twice the residual standard deviation in calf price within the day of sale—Angus was the cheapest while Charolais calves were, on average, the most expensive calves. Mean carcass weight of steers, not adjusted for age at slaughter or carcass fat, varied from 327.1 kg (Angus) to 363.2 kg (Belgian Blue) for the beef breeds with the mean carcass weight of Holstein-Friesian steer progeny being 322.4 kg. Belgian Blues had, on average, the best carcass conformation with the Herefords and Angus having the worst of all beef breeds. Angus and Hereford steers were slaughtered the youngest of all beef breeds but just 9 d younger than the average of all other beef breeds yet 24 d younger than Holstein-Friesian sired progeny. Clear breed differences in calving and carcass performance exist among beef breeds mated to dairy females. Those breeds excelling in calving performance were not necessarily the best for carcass merit. [ABSTRACT FROM AUTHOR]

Reducing nitrogen pollution while maintaining milk production is a major challenge of dairy production. One of the keys to delivering on this challenge is to improve the efficiency of how dairy cows use nitrogen. Thus, estimating the nitrogen utilization of lactating grazing dairy cows and exploring the association between animal factors and productivity with nitrogen utilization are the first steps to understanding the nitrogen utilization complex in dairy cows. Nitrogen utilization metrics were derived from milk and body weight records from 1,291 grazing dairy cows of multiple breeds and crossbreeds; all cows had sporadic information on nitrogen intake concurrent with information on nitrogen sinks (and other nitrogen sources, such as body tissue mobilization). Several nitrogen utilization metrics were investigated, including nitrogen use efficiency (nitrogen output as products such as milk and meat divided by nitrogen intake) and nitrogen excreted (nitrogen intake less the nitrogen output as products such as milk and meat). In the present study, a primiparous Holstein-Friesian used, on average, 20.6% of the nitrogen it ate, excreting the surplus as feces and urine, representing 402 g of nitrogen per day. Intercow variability existed, with a between-cow standard deviation of 0.0094 for nitrogen use efficiency and 24 g of nitrogen per day for nitrogen excretion. As lactation progressed, nitrogen use efficiency declined and nitrogen excretion increased. Nevertheless, nitrogen use efficiency improved (i.e., decreased) from first to second parity, even though it did not improve from second to third parity or greater. Furthermore, nitrogen excretion continued to increase from first to third parity or greater. Nitrogen use efficiency and nitrogen excretion were negatively correlated (−0.56 to −0.40), signifying that dairy cows who partition more of the ingested nitrogen into products such as milk and meat, on average, also excrete less nitrogen. Milk urea nitrogen was, at best, weakly correlated with nitrogen use efficiency and nitrogen excretion; the correlations were between −0.01 and 0.06. In conclusion, several cow-level factors such as parity, stage of lactation, and breed were associated with the range of different nitrogen efficiency metrics investigated; moreover, even after accounting for such effects, 4.8% to 6.3% of the remaining variation in the nitrogen use efficiency and nitrogen balance metrics were attributable to intercow differences. [ABSTRACT FROM AUTHOR]

ABSTRACT: Livestock production systems with ruminants play a relevant role in the emission of the greenhouse gas CH4, which is known to significantly contribute to global warming. Consequently, it is a major societal concern to develop strategies in mitigating such emissions. In addition to breeding toward low-emitting cows, management strategies could also help in reducing greenhouse gas emissions from dairy farms. However, information is required for appropriate decision making. To the best of our knowledge, this is the first study that considers different, already available equations to estimate CH4 emissions of small-scale dairy farms in the mountain region, which largely differ from large dairy farms in the lowlands concerning management and production. For this study, 2 different production systems, both typical for small-scale dairy farming in mountain regions, were simultaneously run over 3 yr at an experimental farm as follows: (1) a high-input production system, characterized by intensive feeding with high amounts of external concentrates and maize silage, year-round housing, and high yielding Simmental cattle breed, and (2) a low-input production system, characterized by prevailing hay and pasture feeding and silage ban, thus covering most of the energy requirements by forage harvested on-farm and the use of the local Tyrolean Grey cattle breed. Results reveal that feeding management has a significant effect on the amount of CH4 emissions. The low-input production system produced less CH4 per cow and per day compared with the high-input production system. However, if calculated per kilogram of milk, the high-input scenario produced proportionally less CH4 than the low-input one. Findings of this study highlight the potential to assess in a fast and cost-effective way the CH4 emission in different dairy production systems. This information contributes to the debate about the future of sustainable milk production in mountain regions, where the production of feed resources is climatically constrained, and could be useful for breeding purposes toward lower CH4-emissions.

The genetic trend of milk yield for 4 French dairy sheep breeds (Lacaune, Basco-Béarnaise, Manech Tête Noire, and Manech Tête Rousse) was partitioned in Mendelian sampling trends by categories of animals defined by sex and by selection pathways. Five categories were defined, as follows: (1) artificial insemination (AI) males (after progeny testing), (2) males discarded after progeny testing, (3) natural mating males, (4) dams of males, and (5) dams of females. Dams of males and AI males were the most important sources of genetic progress, as observed in the decomposition in Mendelian sampling trends. The yearly contributions were more erratic for AI males than for dams of males, as AI males are averaged across a smaller number of individuals. Natural mating males and discarded males did not contribute to the trend in terms of Mendelian sampling, as their estimated Mendelian sampling term is either null (natural mating males) or negative (discarded males). Overall, in terms of Mendelian sampling, females contributed more than males to the total genetic gain, and we interpret that this is because females constitute a larger pool of genetic diversity. In addition, we computed long-term contributions from each individual to the following pseudo-generations (one pseudo-generation spanning 4 years). With this information, we studied the selection decisions (selected or not selected) for females, and the contributions to the following generations. Mendelian sampling was more important than parent average to determine the selection of individuals and their long-term contributions. Long-term contributions were greater for AI males (with larger progeny sizes than females) and in Basco-Béarnaise than in Lacaune (with the latter being a larger population). [ABSTRACT FROM AUTHOR]

ABSTRACT: In cattle, maternal immunoglobulins are transferred through colostrum to provide passive immunity to the neonatal calf once they are absorbed into circulation. Cows can be assessed for antibody- and cell-mediated immune responses (AMIR and CMIR, respectively), and through estimated breeding values (EBV) and genomic parent averages (GPA), cows can be classified as having high, average, or low immune response (IR). The objective of this study was to identify associations of colostral IgG concentrations with IR in dairy cows. High IR dairy cows identified by GPA or EBV were hypothesized to produce higher colostral IgG concentrations than cows with average or low IR. Colostrum was collected from Holstein dairy cows from 3 large commercial herds (n = 590) in the United States and 1 research herd at the Ontario Dairy Research Centre (n = 275) in Canada. For the US herds, IR GPA were available through genotyping. For the Canadian herd, IR EBV were available through phenotyping and pedigree information. Colostral IgG concentrations were measured by radial immunodiffusion and analyzed using general linear models in SAS. Based on a prediction equation, cows in US herds with a CMIR GPA of 1 would have colostral IgG concentrations 6.3 g/L higher on average than cows with a CMIR GPA of 0. High CMIR cows produced statistically greater colostral IgG concentrations (least squares mean ± standard error of the mean, 107.5 ± 7.7 g/L) than low CMIR cows (91.4 ± 7.1 g/L), with intermediate values for average CMIR cows (105.1 ± 5.6 g/L). No differences were found among AMIR categories in US cows. The Canadian herd showed a trend for cows with high CMIR EBV (continuous variable) to produce greater colostral IgG. No differences were observed among high, average, and low AMIR EBV classifications in Canadian cows. The findings suggest that selective breeding of Holstein cows to enhance CMIR could contribute to higher-quality colostrum in succeeding generations.

Small breeding programs are limited in achieving competitive genetic gain and prone to high rates of inbreeding. Thus, they often import genetic material to increase genetic gain and to limit the loss of genetic variability. However, the benefit of import depends on the strength of genotype-by-environment interaction. Import also diminishes the relevance of domestic selection and the use of domestic breeding animals. Introduction of genomic selection has potentially exacerbated this issue, but is also opening the potential for smaller breeding programs. The aim of this paper was to determine when and to what extent small breeding programs benefit from importing genetic material by quantifying the genetic gain as well as the sources of genetic gain. We simulated 2 cattle breeding programs of the same breed that represented a large foreign and a small domestic breeding program. The programs differed in selection parameters of sire selection, and in the initial genetic mean and annual genetic gain. We evaluated a control scenario without the use of foreign sires in the domestic breeding program and 24 scenarios that varied the percentage of domestic dams mated with foreign sires, the genetic correlation between the breeding programs (0.8 or 0.9), and the time of implementing genomic selection in the domestic compared with the foreign breeding program (concurrently or with a 10-yr delay). We compared the scenarios based on the genetic gain and genic standard deviation. Finally, we partitioned breeding values and genetic trends of the scenarios to quantify the contribution of domestic selection and import to the domestic genetic gain. The simulation revealed that when both breeding programs implemented genomic selection simultaneously, the use of foreign sires increased domestic genetic gain only when genetic correlation was 0.9 (10%–18% increase). In contrast, when the domestic breeding program implemented genomic selection with a 10-yr delay, import increased genetic gain at both tested correlations, 0.8 (5%–23% increase) and 0.9 (15%–53% increase). The increase was significant when we mated at least 10% or 25% domestic females with foreign sires and increased with the increasing use of foreign sires, but with a diminishing return. The partitioning analysis revealed that the contribution of import expectedly increased with the increased use of foreign sires. However, the increase did not depend on the genetic correlation and was not proportional to the increase in domestic genetic gain. This represents a peril for small breeding programs because they could be overly relying on import with diminishing returns for the genetic gain, marginal benefit for the genetic variability, and large loss of the domestic germplasm. The benefit and peril of import depends on an interplay of genetic correlation, extent of using foreign sires, and a breeding scheme. It is therefore crucial that small breeding programs assess the possible benefits of import beyond domestic selection. The benefit of import should be weighed against the perils of decreased use of domestic sires and decreased contribution and value of domestic selection. [Display omitted] [ABSTRACT FROM AUTHOR]

Livestock production systems with ruminants play a relevant role in the emission of the greenhouse gas CH 4 , which is known to significantly contribute to global warming. Consequently, it is a major societal concern to develop strategies in mitigating such emissions. In addition to breeding toward low-emitting cows, management strategies could also help in reducing greenhouse gas emissions from dairy farms. However, information is required for appropriate decision making. To the best of our knowledge, this is the first study that considers different, already available equations to estimate CH 4 emissions of small-scale dairy farms in the mountain region, which largely differ from large dairy farms in the lowlands concerning management and production. For this study, 2 different production systems, both typical for small-scale dairy farming in mountain regions, were simultaneously run over 3 yr at an experimental farm as follows: (1) a high-input production system, characterized by intensive feeding with high amounts of external concentrates and maize silage, year-round housing, and high yielding Simmental cattle breed, and (2) a low-input production system, characterized by prevailing hay and pasture feeding and silage ban, thus covering most of the energy requirements by forage harvested on-farm and the use of the local Tyrolean Grey cattle breed. Results reveal that feeding management has a significant effect on the amount of CH 4 emissions. The low-input production system produced less CH 4 per cow and per day compared with the high-input production system. However, if calculated per kilogram of milk, the high-input scenario produced proportionally less CH 4 than the low-input one. Findings of this study highlight the potential to assess in a fast and cost-effective way the CH 4 emission in different dairy production systems. This information contributes to the debate about the future of sustainable milk production in mountain regions, where the production of feed resources is climatically constrained, and could be useful for breeding purposes toward lower CH 4 -emissions. [ABSTRACT FROM AUTHOR]

Lactose, the principal carbohydrate found in milk, plays an important role in the physiological processes of milk production because it is related to milk volume, and it is responsible for the osmotic equilibrium between blood and milk in the mammary gland. In this study, factors affecting lactose content (LC) in sheep milk are investigated. For this purpose, 2,358 test-day records were sampled from 509 ewes (3–7 records per animal). The LC and other main milk traits were analyzed using a mixed linear model that included days in milk (DIM) class, parity, lambing month, and type of lambing as fixed effects and animal, permanent environment, and flock test day as random effects. The pedigree-based approach was used to estimate the heritability and repeatability of LC. Moreover, the genomic background of LC was investigated through a GWAS. The LC was affected by all tested factors (i.e., DIM class, parity, lambing month, and type of lambing). Low heritability (0.10 ± 0.05) and moderate repeatability (0.42 ± 0.02) were estimated for LC. High negative genetic correlations were estimated between LC and NaCl (−0.99 ± 0.01) and between LC and somatic cell count (−0.94 ± 0.05). Only 2 markers passed the chromosome-wide Bonferroni threshold. Results of the present study, although obtained on a relatively small sample, suggest the possibility to include LC in the breeding programs, particularly because of its strong relationship with NaCl and somatic cell count. [ABSTRACT FROM AUTHOR]

In cattle, maternal immunoglobulins are transferred through colostrum to provide passive immunity to the neonatal calf once they are absorbed into circulation. Cows can be assessed for antibody- and cell-mediated immune responses (AMIR and CMIR, respectively), and through estimated breeding values (EBV) and genomic parent averages (GPA), cows can be classified as having high, average, or low immune response (IR). The objective of this study was to identify associations of colostral IgG concentrations with IR in dairy cows. High IR dairy cows identified by GPA or EBV were hypothesized to produce higher colostral IgG concentrations than cows with average or low IR. Colostrum was collected from Holstein dairy cows from 3 large commercial herds (n = 590) in the United States and 1 research herd at the Ontario Dairy Research Centre (n = 275) in Canada. For the US herds, IR GPA were available through genotyping. For the Canadian herd, IR EBV were available through phenotyping and pedigree information. Colostral IgG concentrations were measured by radial immunodiffusion and analyzed using general linear models in SAS. Based on a prediction equation, cows in US herds with a CMIR GPA of 1 would have colostral IgG concentrations 6.3 g/L higher on average than cows with a CMIR GPA of 0. High CMIR cows produced statistically greater colostral IgG concentrations (least squares mean ± standard error of the mean, 107.5 ± 7.7 g/L) than low CMIR cows (91.4 ± 7.1 g/L), with intermediate values for average CMIR cows (105.1 ± 5.6 g/L). No differences were found among AMIR categories in US cows. The Canadian herd showed a trend for cows with high CMIR EBV (continuous variable) to produce greater colostral IgG. No differences were observed among high, average, and low AMIR EBV classifications in Canadian cows. The findings suggest that selective breeding of Holstein cows to enhance CMIR could contribute to higher-quality colostrum in succeeding generations. [ABSTRACT FROM AUTHOR]

Maintaining genetic variation in a population is important for long-term genetic gain. The existence of subpopulations within a breed helps maintain genetic variation and diversity. The 20,990 genotyped animals, representing the breeding animals in the year 2014, were identified as the sires of animals born after 2010 with at least 25 progenies, and females measured for type traits within the last 2 yr of data. K-means clustering with 5 clusters (C1, C2, C3, C4, and C5) was applied to the genomic relationship matrix based on 58,990 SNP markers to stratify the selected candidates into subpopulations. The general higher inbreeding resulting from within-cluster mating than across-cluster mating suggests the successful stratification into genetically different groups. The largest cluster (C4) contained animals that were less related to each animal within and across clusters. The average fixation index was 0.03, indicating that the populations were differentiated, and allele differences across the subpopulations were not due to drift alone. Starting with the selected candidates within each cluster, a family unit was identified by tracing back through the pedigree, identifying the genotyped ancestors, and assigning them to a pseudogeneration. Each of the 5 families (F1, F2, F3, F4, and F5) was traced back for 10 generations, allowing for changes in frequency of individual SNPs over time to be observed, which we call allele frequencies change. Alternative procedures were used to identify SNPs changing in a parallel or nonparallel way across families. For example, markers that have changed the most in the whole population, markers that have changed differently across families, and genes previously identified as those that have changed in allele frequency. The genomic trajectory taken by each family involves selective sweeps, polygenic changes, hitchhiking, and epistasis. The replicate frequency spectrum was used to measure the similarity of change across families and showed that populations have changed differently. The proportion of markers that reversed direction in allele frequency change varied from 0.00 to 0.02 if the rate of change was greater than 0.02 per generation, or from 0.14 to 0.24 if the rate of change was greater than 0.005 per generation within each family. Cluster-specific SNP effects for stature were estimated using only females and applied to obtain indirect genomic predictions for males. Reranking occurs depending on SNP effects used. Additive genetic correlations between clusters show possible differences in populations. Further research is required to determine how this knowledge can be applied to maintain diversity and optimize selection decisions in the future. [ABSTRACT FROM AUTHOR]

Genomic selection increases accuracy and decreases generation interval, accelerating genetic changes in populations. Assumptions of genetic improvement must be addressed to quantify the magnitude and direction of change. Genetic trends of US dairy cattle breeds were examined to determine the genetic gain since the implementation of genomic evaluations in 2009. Inbreeding levels and generation intervals were also investigated. Breeds included Ayrshire, Brown Swiss, Guernsey, Holstein (HO), and Jersey (JE), which were characterized by the evaluation breed the animal received. Mean genomic predicted breeding values ( P B V ¯) were analyzed per year to calculate genetic trends for bulls and cows. The data set contained 154,008 bulls and 33,022,242 cows born since 1975. Breakpoints were estimated using linear regression, and nonlinear regression was used to fit the piecewise model for the small sample number in some years. Generation intervals and inbreeding levels were also investigated since 1975. Milk, fat, and protein yields, somatic cell score, productive life, daughter pregnancy rate, and livability P B V ¯ were documented. In 2017, 100% of bulls in this data set were genotyped. The percentage of genotyped cows has increased 23 percentage points since 2010. Overall, production traits have increased steadily over time, as expected. The HO and JE breeds have benefited most from genomics, with up to 192% increase in genetic gain since 2009. Due to the low number of observations, trends for Ayrshire, Brown Swiss, and Guernsey are difficult to infer from. Trends in fertility are most substantial; particularly, most breeds are trending downwards and daughter pregnancy rate for JE has been decreasing steadily since 1975 for bulls and cows. Levels of genomic inbreeding are increasing in HO bulls and cows. In 2017, genomic inbreeding levels were 12.7% for bulls and 7.9% for cows. A suggestion to control this is to include the genomic inbreeding coefficient with a negative weight to the selection index of bulls with high future genomic inbreeding levels. For sires of bulls, the current generation intervals are 2.2 yr in HO, 3.2 in JE, 4.4 in Brown Swiss, 5.1 in Ayrshire, and 4.3 in Guernsey. The number of colored breed bulls in the United States is currently at an extremely low level, and this number will only increase with a market incentive or additional breed association involvement. Increased education and extension could be beneficial to increase knowledge about inbreeding levels, use of genomics and genetic improvement, and genetic diversity in the genomic selection era. [ABSTRACT FROM AUTHOR]

Interbull's multiple across-country evaluaftion provides national breeding organizations with breeding values for internationally used bulls, which integrate performance data obtained in different breeding populations, environments, and production systems. However, breeding value-based selection decisions on domestic individuals born to foreign sires can only benefit from Interbull breeding values if they are integrated such that their information can contribute to the breeding values of all related domestic animals. For that purpose, several methods have been proposed which either model Interbull breeding values as prior information in a Bayesian approach, as additional pseudo data points, or as correlated traits, where these methods also differ in their software and parameterization requirements. Further, the complexity of integration also depends on the traits and genetic evaluation models. Especially random regression models require attention because of the dimensionality discrepancy between the number of Interbull breeding values and the number of modeled genetic effects. This paper presents the results from integrating 16,063 Interbull breeding values into the domestic single-step random regression test-day model for milk, fat, and protein yield for Australian Red dairy cattle breeds. Interbull breeding values were modeled as pseudo data points with data point-specific residual variances derived within animal across traits, ignoring relationships between integrated animals. Results suggest that the integration was successful with regard to alignment of Interbull breeding values with their domestic equivalent as well as with regard to the individual and population-wide increase in reliabilities. Depending on the relationship structure between integration candidates, further work is required to account for those relationships in a computationally feasible manner. Other traits with separate parity effects nationally could use a similar approach, even if not modeled with a test-day model. [ABSTRACT FROM AUTHOR]

Reducing juvenile mortality in cattle is important for both economic and animal welfare reasons. Previous studies have revealed a large variability in mortality rates between breeds and sire progeny groups, with some extreme cases due to dominant mutations causing various syndromes among the descendants of mosaic bulls. The purpose of this study was to monitor sire-family calf mortality within the French and Walloon Holstein populations, and to use this information to detect genetic defects that might have been overlooked by lack of specific symptoms. In a population of heifers born from 1,001 bulls between 2017 and 2020, the average sire-family mortality rates were of 11.8% from birth to 1 year of age and of 4.2, 2.9, 3.1, and 3.2% for the perinatal, postnatal, preweaning, and postweaning subperiods, respectively. After outlining the 5 worst bulls per category, we paid particular attention to the bulls Mo and Pa, because they were half-brothers. Using a battery of approaches, including necropsies, karyotyping, genetic mapping, and whole-genome sequencing, we described 2 new independent genetic defects in their progeny and their molecular etiology. Mo was found to carry a de novo reciprocal translocation between chromosomes BTA26 and BTA29, leading to increased embryonic and juvenile mortality because of aneuploidy. Clinical examination of 2 calves that were monosomic for a large proportion of BTA29, including an orthologous segment deleted in human Jacobsen syndrome, revealed symptoms shared between species. In contrast, Pa was found to be mosaic for a dominant de novo nonsense mutation of GATA 6 binding protein (GATA6), causing severe cardiac malformations. In conclusion, our results highlight the power of monitoring juvenile mortality to identify dominant genetic defects due to de novo mutation events. [ABSTRACT FROM AUTHOR]

Holstein (HO) calves, 3-breed crossbred calves of Montbéliarde, Viking Red, and HO (MVH), and 3-breed crossbred calves of Normande, Jersey, and Viking Red (NJV) were compared for gestation length (GL), calf weight at birth (CW), calving difficulty (CD), and stillbirth (SB) in 2 research herds at the University of Minnesota. Calves were born from January 2009 to December 2019. For the St. Paul and Morris herds, HO calves (n = 1,121) were compared with MVH calves (n = 1,393) from primiparous and multiparous cows. For the single herd analysis at Morris, HO calves (n = 476), MVH calves (n = 922), and NJV calves (n = 405) were compared from primiparous and multiparous cows. Primiparous and multiparous births were analyzed separately because multiparous cows had multiple births, and CD and SB are likely different traits for primiparous and multiparous cows. Statistical analysis of GL, CW, CD, and SB included fixed effects of sex of calf, herd, breed group of calf, and year-season of calving. For the St. Paul and Morris herds, HO calves from primiparous (278 d) and multiparous (279 d) HO cows had shorter GL compared with MVH calves from primiparous (280 d) and multiparous (282 d) crossbred cows. The HO calves (39.4 and 43.2 kg, respectively) from primiparous and multiparous HO cows had lower CW compared with MVH calves (40.3 and 44.3 kg, respectively) from primiparous and multiparous crossbred cows. Calving difficulty and SB were not different for HO and MVH calves from primiparous and multiparous cows. For the single herd analysis at Morris, HO calves (278 and 279 d, respectively) from primiparous and multiparous HO cows had shorter GL compared with MVH calves (281 and 282 d, respectively) and NJV calves (282 and 282 d, respectively) from primiparous and multiparous crossbred cows. The CW of HO calves (38.6 and 42.0 kg, respectively) from primiparous and multiparous HO cows was lower compared with MVH calves (39.7 and 42.9 kg, respectively), but higher compared with NJV calves (35.1 and 38.0 kg, respectively) from primiparous and multiparous crossbred cows. Calving difficulty and SB did not differ for HO, MVH, and NJV calves from primiparous and multiparous cows. The longer GL for crossbred calves and higher CW for MVH calves did not increase CD and SB for primiparous and multiparous cows. Dairy producers may implement 3-breed rotational crossbreeding systems that include the HO, Jersey, Normande, Montbéliarde, and Viking Red breeds, and some breeds may increase GL and CW without an increase in CD and SB. [ABSTRACT FROM AUTHOR]

Widespread genotyping has enabled the identification of putative recessive mutations that affect fertility through early embryonic fetal loss, or that compromise neonate or calf viability. The use of artificial insemination in the global dairy population can rapidly spread these harmful mutations, and testing for multiple mutations can become relatively expensive if not all tests are available on the same SNP panel. However, it is possible to provide heifer and cow predicted carrier status to farmers at no additional cost if the animals are genotyped with a standard SNP panel. Additionally, for defects where the causal mutation is unknown but a haplotype of markers has been associated with the defect, the carrier status can be predicted based on that haplotype. The aims of this study were 3-fold: (1) to determine the accuracy of imputation of putative causal mutations for recessive deleterious conditions in Australian dairy cattle, (2) to impute carrier status for known recessive deleterious conditions in all genotyped Australian Holstein, Jersey, and Red breed cows, and (3) to determine the changes in carrier frequencies across time for these recessive deleterious mutations. We used the F1 statistic, combining precision and recall, to assess the accuracy of carrier status prediction. We showed that known deleterious mutations can be accurately imputed in Australian Holstein and Jersey cattle that are not directly genotyped for the causal mutation, with F1 ranging between 0.88 and 0.99. For recessive deleterious conditions not included on the standard Australian SNP panel, carrier status could be predicted using a marker haplotype, with F1 ranging from 0.91 to 0.92. Most putative causals and haplotypes were either stable with a low carrier percentage or had a declining carrier percentage. However, several recessive mutations showed a relatively high or increasing percentage, highlighting the importance of detecting carriers to reduce the number of at-risk matings. Furthermore, the high carrier percentage of the recently identified bovine lymphocyte intestinal retention defect mutation emphasizes the importance of detection of novel mutations., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The lifetime production of dairy cows is a complex trait influenced not only by genetics but also by the environment in which a cow lives and the management practices of the farmer. Moreover, these influential factors show complex interactions with each other, making it difficult to reliably predict the lifetime production of individual animals at birth. However, because well-managed dairy farms often have a surplus of youngstock, reliable lifetime production predictions would offer the opportunity to make more substantiated decisions when selecting calves or heifers to sell. Therefore, using data from Dutch herds, we constructed a dataset capturing information on genetics, environment, and management practices to develop multiple machine learning models capable of predicting the lifetime production of dairy cattle soon after birth. We found that a coupling of trends observed at the country level with farm-specific models largely outperforms off-the-shelf approaches. At birth, our best model could explain up to 47% of the variance in lifetime production, a considerable improvement compared with linear regression on the breeding values supplemented with the average lifetime production at farm level, which could explain only 21.7% of the variance in lifetime production. Moreover, we demonstrated that surplus youngstock selection according to our model could more than double the surplus animal selection effect compared with the benchmark methodology, offering opportunities to significantly increase the average (future) potential lifetime production of the retained heifers. Assuming a static 20% surplus liveborn heifer scenario and random surplus animal selection as the default, our best model for surplus animal selection resulted in a 9.4% greater lifetime production in the retained animals compared with the current Dutch average lifetime production., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Milking speed is an important trait influencing the udder health of dairy cows, as well as labor efficiency. However, it has received little attention in genomic association studies. The main objective of this study was to determine regions and genes on the genome with a potential effect on milking speed in Fleckvieh (dual-purpose Simmental) cattle. Genome-wide association studies were conducted using deregressed breeding values of bulls as phenotypes. We found 6 SNPs on 4 autosomes that were significantly associated with milking speed for additive effects. Significant regions on BTA4 and BTA19 correspond with findings for other dairy cattle breeds. Based on the observations of Fleckvieh breed managers, variation of milking speed in batches of daughters of some bulls is much higher than in daughter groups of other bulls. This difference in within-family variation may be caused by the transmission of alternative alleles from bulls being heterozygous for a gene affecting milking speed. To check on this, we considered the SD of yield deviations in milking speed of half-sib daughters as a new trait and performed GWAS for dominance effects. One signal on BTA5 passed the genome-wide Bonferroni threshold that corresponded to the significant signal from standard GWAS on deregressed breeding values. The key conclusion of this study is that several strong genomic signals were found for milking speed in Fleckvieh cattle, and that the strongest of them are supported by similar findings in Brown Swiss and Holstein Friesian cattle. Milking speed is a complex trait whose subprocesses have not yet been elucidated in detail. Hence, it remains a challenge to link the associated regions on the genome with causal genes and their functions., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

In vitro embryo production is one of the main reproductive techniques used in dairy Gyr cattle. In addition, linear type measures are well characterized and have been used in dairy Gyr breed selection for the last 4 decades. The estimation of genetic parameters for the number of aspirated oocytes and in vitro-produced embryos associated with the linear type measures would support genetic progress for animal breeding programs toward embryo production. This study aimed to estimate genetic parameters for aspirated oocytes, embryo in vitro production, and linear type traits, exploring the association between them. The repeatability model was applied to 14,251 ovum pick-up events from 1,916 Gyr donors. A subset of 604 donors from the same group had their body measurements taken. Single- and 2-trait analyses were carried out using the BLUPF90 family programs. Heritability estimates of 0.38, 0.34, and 0.20 were obtained for total oocytes, viable oocytes, and embryos, respectively, and the heritability of the linear type traits ranged from 0.22 to 0.40. High genetic correlations between total oocytes and viable oocytes (0.99), and between oocytes (total and viable) and embryos (0.83) were obtained. Low to high genetic (-0.07 to 0.92) and phenotypic (0.32-0.86) correlations were obtained between the linear type traits. Moreover, low phenotypic correlations (0.01-0.13) were observed for oocytes (total and viable) and embryos with the linear type traits, whereas low to moderate genetic correlations (0.07-0.42) were observed between the same traits, especially for ilium width (0.42), rump area (0.38), and hip height (0.33). Thus, selection for in vitro production is achievable in Gyr dairy cattle, and superior genetic progress is associated with the selection of oocytes (total and viable). Furthermore, the moderate genetic association between oocytes and embryos with linear type traits, especially ilium width suggests that progress on in vitro embryo production may be achieved by accessing these measurements., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Cull cows from dairy farms in the United States account for 10% of the beef market; however, few studies have evaluated the effects of crossbreeding on reasons for disposal and cull value of dairy cows. The objective of the study was to compare reasons for disposal and cull cow value of Holstein and crossbred cows (n = 1,292) in an experimental dairy herd at the University of Minnesota West Central Research and Outreach Center (Morris, MN). Cows were Holstein (n = 272), 1964 genetic control Holstein (n = 161), 3-breed crossbred cows (n = 538) composed of the Montbéliarde, Viking Red, and Holstein (MVH) breeds, and 3-breed crossbred cows (n = 321) composed of the Normande, Jersey, and Viking Red (NJV) breeds. The 1964 genetic control Holstein cows originated from a design initiated at the University of Minnesota for comparison of the 1964 Holstein and contemporary Holstein cows selected for production across time. Records spanned from January 2010 to December 2023. Reasons for disposal were recorded in PCDart Herd Management Software, and cull value and body weight were obtained from receipts from livestock cull markets. For all cows, the primary reasons for disposal were as follows: reproduction (44.4%), mastitis (18%), other reasons (14.6%), death (10.3%), dairy purposes (8.4%), and low production (4.3%). Independent variables for statistical analysis of cull value were the fixed effects of body weight at time of culling, DIM at culling (0-49 DIM, 50-99 DIM, 100-149 DIM, 150-199 DIM, 200-249 DIM, 250-299 DIM, 300-350 DIM, and >350 DIM), year (2010-2023), season (spring, summer, autumn, winter), parity (1, 2, 3, 4, 5+), primary reason for culling, breed group, and sire breed group nested within breed group. Least squares means for body weight at culling was 558 kg for Holsteins, 543 kg for 1964 Holsteins, 551 kg for MVH crossbred cows, and 499 kg for NJV crossbred cows. For the analysis across time, 2014 had the highest cull value ($1,126.98), and 2020 had the lowest gross cull value ($515.21). Cows culled at greater than 300 DIM had the highest cull value and cows culled at less than 50 DIM had the lowest cull value. Cows culled during the spring and summer had higher cull value compared with cows culled during the autumn and winter. The Holstein cows ($730.04) had lower gross value compared with 1964 Holsteins ($804.38) cows and MVH ($767.39) cows. The NJV ($771.39) cows were not different from crossbreds sired by Montbéliarde, Viking Red, and Holstein bulls. Results for comparisons of breed group are from one experimental herd, so inferences to the wider dairy cow population should be undertaken with caution. In summary, dairy producers may receive greater cull value from crossbred cows compared with Holstein cows., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

With the rapid development of animal phenomics and deep phenotyping, we can obtain thousands of traditional (but also molecular) phenotypes per individual. However, there is still a lack of exploration regarding how to handle this huge amount of data in the context of animal breeding, presenting a challenge that we are likely to encounter more and more in the future. This study aimed to (1) explore the use of the mega-scale linear mixed model (MegaLMM), a factor model-based approach that is able to simultaneously estimate (co)variance components and genetic parameters in the context of thousands of milk traits, hereafter called thousand-trait (TT) models; (2) compare the phenotype values and genomic breeding value (u) predictions for focal traits (i.e., traits that are targeted for prediction, compared with secondary traits that are helping to evaluate), from single-trait (ST) and TT models, respectively; (3) propose a new approximate method of GEBV (U) prediction with TT models and MegaLMM. We used a total of 3,421 milk mid-infrared (MIR) spectra wavepoints (called secondary traits) and 3 focal traits (average fat percentage [AFP], average methane production [ACH4], and average SCS [ASCS]) collected on 3,302 first-parity Holstein cows. The 3,421 milk MIR wavepoint traits were composed of 311 wavepoints in 11 classes (months in lactation). Genotyping information of 564,439 SNPs was available for all animals and was used to calculate the genomic relationship matrix. The MegaLMM was implemented in the framework of the Bayesian sparse factor model and solved through Gibbs sampling (Markov chain Monte Carlo). The heritabilities of the studied 3,421 milk MIR wavepoints gradually increased and then decreased in units of 311 wavepoints throughout the lactation. The genetic and phenotypic correlations between the first 311 wavepoints and the other 3,110 wavepoints were low. The accuracies of phenotype predictions from the ST model were lower than those from the TT model for AFP (0.51 vs. 0.93), ACH4 (0.30 vs. 0.86), and ASCS (0.14 vs. 0.33). The same trend was observed for the accuracies of u predictions for AFP (0.59 vs. 0.86), ACH4 (0.47 vs. 0.78), and ASCS (0.39 vs. 0.59). The average correlation between U predicted from the TT model and the new approximate method was 0.90. The new approximate method used for estimating U in MegaLMM will enhance the suitability of MegaLMM for applications in animal breeding. This study conducted an initial investigation into the application of thousands of traits in animal breeding and showed that the TT model is beneficial for the prediction of focal traits (phenotype and breeding values), especially for difficult-to-measure traits (e.g., ACH4)., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

This observational study determined the effect of genetic merit for fertility traits on estrous activity and duration and interestrous interval in nulliparous dairy heifers. We also compared estrous activity between estrous events with or without conception and determined the effect of genetic merit for fertility traits on age and BW at time of first detected estrous activity event. Activity monitoring devices (Heatime, SCR-Engineers) were fitted to Holstein-Friesian heifers aged 7 to 9 mo with positive or negative genetic merit for fertility traits (POS FertBV: average +5%, n = 275; NEG FertBV: average -5%, n = 249) and activity data were collected to the end of the first breeding period (15-17 mo). An estrous event was defined as when the activity change index exceeded 19.2 activity units (AU) for ≥6 consecutive hours. In total, 2,434 estrous events were identified (POS FertBV: n = 1,454; NEG FertBV: n = 980). Estrous event duration was defined as the period when the threshold was first exceeded and when activity dropped below threshold, without another event starting within 24 h of the end of the previous event. This definition included occurrences where activity crossed the threshold multiple times in a day; these were classified as a single estrous event. A second measure, high activity duration, was defined as the total time activity exceeded the threshold. To characterize estrous activity, baseline activity was determined from the previous 7 d of activity. Peak activity and total activity (area under the curve of activity above baseline) were calculated. A fifth variable, interestrous interval, was calculated as a proxy for estrous cycle length. Total activity and peak activity were greater in POS than NEG FertBV heifers (total activity: 548 vs. 464 AU, SED = 19.6 AU; peak activity: 72 vs. 65 AU, SE of the difference [SED] = 1.5 AU). The POS FertBV group had a mean estrous event duration and high activity duration of 15.1 and 15.0 h, compared with 14.1 and 14.1 h for the NEG FertBV group (SED = 0.30 and 0.29 h, respectively). Inter-estrous interval did not differ between POS FertBV and NEG FertBV heifers (19.5 vs. 20.0 d, SED = 0.49). Estrous events associated with conception were shorter than those not associated with conception (mean ± SEM, high activity duration: 13.0 ± 0.25 h vs. 13.9 ± 0.31 h, estrous event duration: 13.1 ± 0.25 h vs. 14 ± 0.32 h) and had less total activity (408 ± 15.2 vs. 487 ± 18.2 AU). The POS FertBV heifers were more likely to have their first estrous activity event than NEG FertBV heifers by a given age (hazard ratio [HR] = 1.26, 95% CI = 1.0-1.6) or BW (HR = 1.35, 95% CI = 1.1-1.6). The outcomes of this study provide evidence that positive genetic merit for fertility traits is associated with more overt estrous expression. Therefore, estrous expression traits may have potential to be used as earlier-in-life predictors of genetic merit for fertility., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Artificial insemination and embryo transfer (ET) are important in the reproduction of dairy cows. The conception rate after AI or ET is an essential indicator when selecting appropriate breeding methods. However, information on the environmental factors affecting ET conception rate when compared with AI is limited. We aimed to investigate environmental factors affecting ET conception rate and characterize the differences in environmental factors between AI and ET. Records of the first AI (n = 1,870,143) and ET (n = 29,922) from Holstein nulliparous, primiparous, and multiparous cows in Hokkaido, Japan, were analyzed using separate multivariable logistic regression models. For each breeding method, we grouped primiparous and multiparous cows according to milk yield at peak lactation (PY; <25, 25-30, 30-35, or ≥35 kg in primiparous; <40, 40-45, 45-50, or ≥50 kg in multiparous) and the interval from calving to first AI or to first ET (CFI and CFT, respectively; <60, 60-79, 80-99, or ≥100 d) to evaluate the effects of PY and CFI or CFT on conception rate. The AI conception rate decreased with increasing PY in primiparous and multiparous cows, whereas ET conception rate did not decrease significantly. Additionally, the ET conception rate did not decrease even in primiparous and multiparous cows slightly earlier than 60 d in CFI/CFT compared with those in CFI/CFT after 60 d, which differed from the AI conception rate. Collectively, breeding by ET leads to the avoidance of negative effects of high milk yield and calving on the conception rate, indicating that cows are fertile by ET within 60 d after calving., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Dairy cattle health traits are paramount from a welfare and economic viewpoint, and modern breeding programs therefore prioritize the genetic improvement of these traits. Estimated breeding values for health traits are published as the probability of animals staying healthy. They are obtained using threshold models, which assume that the observed binary phenotype (i.e., healthy or sick) is dictated by an underlying normally distributed liability exceeding or not exceeding a threshold. This methodology requires significant computing time and faces convergence challenges, as it implies a nonlinear system of equations. Linear models have more straightforward computations and provide a robust approximation to threshold models; thus, they could be used to overcome these challenges. However, linear models yield estimated breeding values on the observed scale, requiring an approximation to the liability scale analogous to that from threshold models to later obtain the estimated breeding values on the probability scale. In addition, the robustness of the approximation of linear to threshold models depends on the amount of information and the incidence of the trait, with extreme incidence (i.e., ≤5%) deviating from optimal approximation. Our objective was to test a transformation from the observed to the liability, and then to the probability scale, in the genetic evaluation of health traits with moderate and very low (extreme) incidence. Data comprised displaced abomasum (5.1 million), ketosis (3.6 million), lameness (5 million), and mastitis (6.3 million) records from a Holstein population with a pedigree of 6 million animals, of which 1.7 million were genotyped. Univariate threshold and linear models were performed to predict breeding values. The agreement between estimated breeding values on the probability scale derived from threshold and linear models was assessed using Spearman rank correlations and comparison of estimated breeding values distributions. Correlations were at least 0.95, and estimated breeding value distributions almost entirely overlapped for all the traits but displaced abomasum, the trait with the lowest incidence (2%). Computing time was ∼3 times longer for threshold than for linear models. In this Holstein population, the approximation was suboptimal for a trait with extreme incidence (2%). However, when the incidence was ≥6%, the approximation was robust, and its use is recommended along with linear models for analyzing categorical traits in large populations to ease the computational burden., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

This study explores how the metafounder (MF) concept enhances genetic evaluations in dairy cattle populations using single-step genomic best linear unbiased prediction (ssGBLUP). By improving the consideration of relationships among founder populations, MF ensures accurate alignment of pedigree and genomic relationships. The research aims to propose a method for grouping MF based on genotypic information, assess different approaches for estimating the gamma matrix, and compare unknown parent groups (UPG) and MF methodologies across various scenarios, including those with low and high pedigree completeness based on a simulated dairy cattle population. In the scenario where unknown ancestors are rare, the effect of UPG or MF on breeding values is minimal but MF still performs slightly better compared with UPG. The scenario with lower genotyping rates and more unknown parents shows significant differences in evaluations with and without UPG and also compared with MF. The study shows that ssGBLUP evaluations where UPG are considered via Quaas-Pollak-transformation in the pedigree-based and genomic relationship matrix (UPG&#95;fullQP) results in double counting and subsequently in a pronounced bias and overdispersion. Another focus is on the estimation of the gamma matrix, emphasizing the importance of crossbred genotypes for accuracy. Challenges emerge in classifying animals into subpopulations and further into MF or UPG, but the method used in this study, which is based on genotypes, results in predictions which are comparable to those obtained using the true subpopulations for the assignment. Estimated validation results using the linear regression method confirm the superior performance of MF evaluations, although differences compared with true validations are smaller. Notably, UPG&#95;fullQP's extreme bias is less evident in routine validation statistics., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Missing pedigrees may produce bias in genomic evaluations. Thus, strategies to deal with this problem have been proposed as using unknown parent groups (UPG) or truncated pedigrees. The aim of this study was to investigate the impact of modeling missing pedigrees under single-step genomic best linear unbiased prediction (ssGBLUP) evaluations for productive and reproductive traits in dairy buffalo using different approaches: (1) traditional BLUP without UPG (BLUP), (2) traditional BLUP including UPG (BLUP/UPG), (3) ssGBLUP without UPG (ssGBLUP), (4) ssGBLUP including UPG in the A and A 22 matrices (ssGBLUP/A&#95;UPG), (5) ssGBLUP including UPG in all elements of the H matrix (ssGBLUP/H&#95;UPG), (6) BLUP with pedigree truncation for the last 3 generations (BLUP/truncated), and (7) ssGBLUP with pedigree truncation for the last 3 generations (ssGBLUP/truncated). Unknown parent groups were not used in the scenarios with truncated pedigree. A total of 3,717, 4,126, and 3,823 records of the first lactation for accumulated 305-d milk yield (MY), age at first calving (AFC), and lactation length (LL), respectively, were used. Accuracies ranged from 0.27 for LL (BLUP) to 0.46 for MY (BLUP), bias ranged from -0.62 for MY (ssGBLUP) to 0.0002 for AFC (BLUP/truncated), and dispersion ranged from 0.88 for MY (BLUP/A&#95;UPG) to 1.13 for LL (BLUP). Genetic trend showed genetic gains for all traits across 20 years of selection, and the impact of including genomic information, UPG, or pedigree truncation under GEBV accuracies ranged among the evaluated traits. Overall, methods using UPG, truncation pedigree, and genomic information exhibited potential to improve GEBV accuracies, bias, and dispersion for all traits compared with other methods. Truncated scenarios promoted high genetic gains. In small populations with few genotyped animals, combining truncated pedigree or UPG with genomic information is a feasible approach to deal with missing pedigrees., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

In this paper, we present a comprehensive study of gestation length (GL) in 16 cattle breeds by using large genotype and animal record databases. Data included over 20 million gestations since 2000 and genotypes from one million calves. The study addressed the GL variability within and between breeds, estimation of its direct and maternal heritability coefficients, association with fitness and several economic traits, and QTL detection. The breed average GL varied from 279.7 to 294.4 d in Holstein and Blonde d'Aquitaine breeds, respectively. Standard deviations per breed were similar and ranged from 5.2 to 5.8 d. Direct heritability (i.e., for GL defined as a trait of the calf) was moderate to high (h 2 = 0.40-0.67), whereas the maternal heritability was low (0.04-0.06). Extreme breeding values for GL were strongly associated with a higher mortality during the first 2 d of life and were associated with milk production of dams for dairy breeds and precocity of females. Finally, several QTL were detected affecting GL with cumulated effects up to a few days, and at least 2 QTL were found to be shared between different breeds. Our study highlights the risks that would be associated with selection toward a reduced GL. Further genomic studies are needed to identify the causal variants and their association with juvenile mortality and other economic traits., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The welfare of calves is important to both farmers and consumers. Practices that increase the proportion of calves born alive and enable them to thrive through to weaning contribute to improved sustainability. Stillbirths (SB) are calvings where the calf dies at birth or within 24 h after birth. Preweaning mortality (PWM) refers to calves that die after the first day of life but before weaning based on termination data. Both SB and PWM are binary traits characterized by low heritability. Data collection for these traits is incomplete, compared with traits such as milk yield in cows. Despite these challenges, genetic variation can be measured and used to produce breeding tools, such as EBVs, to reduce calf mortality over time. The aim of this study was to compare the performance of various linear models to predict SB and PWM traits in Holstein and Jersey cattle and evaluate their applicability for industry-wide use in the Australian dairy industry. Calving records from around 2.25 million Holstein and Jersey dams were obtained from DataGene's Central Data Repository from the year 2000 onward, to calculate genetic parameters. About 7% of calves were recorded as SB in the period from 2000 to 2021 (n = 1.48 million calvings). The prevalence of PWM was much lower than SB during the same period at 2% (n = 0.89 million calves). Genetic parameters were estimated for SB direct, SB maternal, and PWM using bivariate linear models with calving ease (CE) as the second trait in the model. The heritability of these calf traits was low and varied between 1% and 5% depending on the breed, trait, and model. In Holstein cattle, heritabilities were 2% for PWM and SB direct and 1% for SB maternal, whereas in Jersey cattle heritabilities were 5% for PWM, 2% for SB direct, and 1% for SB maternal. The genetic trends for both SB direct and SB maternal in Holstein cattle indicate improvement in both traits, whereas there was no apparent increase or decrease in PWM in the past 2 decades. The coefficient of genetic variation for SB direct and PWM was between 11.7% and 23.0% in Holstein and Jersey cattle, demonstrating considerable genetic variation in calf survival traits as a first step to using genetic selection to increase the proportion of calves born alive and calves weaned. A focus on improved calf and calving recording practices is expected to increase the reliability of genetic predictions., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Large datasets allow estimation of feed required for individual milk components or body maintenance. Phenotypic regressions are useful for nutrition management, but genetic regressions are more useful in breeding programs. Dry matter intake records from 8,513 lactations of 6,621 Holstein cows were predicted from phenotypes or genomic evaluations for milk components and body size traits. The mixed models also included DIM, age-parity subclass, trial date, management group, and BW change during 28- and 42-d feeding trials in mid lactation. Phenotypic regressions of DMI on milk (0.014 ± 0.006), fat (3.06 ± 0.01), and protein (4.79 ± 0.25) were much less than corresponding genomic regressions (0.08 ± 0.03, 11.30 ± 0.47, and 9.35 ± 0.87, respectively) or sire genomic regressions multiplied by 2 (0.048 ± 0.04, 6.73 ± 0.94, and 4.98 ± 1.75). Thus, marginal feed costs as fractions of marginal milk revenue were higher from genetic than phenotypic regressions. According to the ECM formula, fat production requires 69% more DMI than protein production. In the phenotypic regression, it was estimated that protein production requires 56% more DMI than fat. However, the genomic regression for the animal showed a difference of only 21% more DMI for protein compared with fat, whereas the sire genomic regressions indicated approximately 35% more DMI for fat than protein. Estimates of annual maintenance in kilograms DMI/kilograms BW per lactation were similar from phenotypic regression (5.9 ± 0.14), genomic regression (5.8 ± 0.31), and sire genomic regression multiplied by 2 (5.3 ± 0.55) and are larger than those estimated by the National Academies for Science, Engineering, and Medicine based on NE L equations. Multiple regressions on genomic evaluations for the 5 type traits in body weight composite (BWC) showed that strength was the type trait most associated with BW and DMI, agreeing with the current BWC formula, whereas other traits were less useful predictors, especially for DMI. The Net Merit formula used to weight different genetic traits to achieve an economically optimal overall selection response was revised in 2021 to better account for these estimated regressions. To improve profitability, breeding programs should select smaller cows with negative residual feed intake that produce more milk, fat, and protein., (Copyright © 2024 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Buffaloes are vital contributors to the global dairy industry. Understanding the genetic basis of milk production traits in buffalo populations is essential for breeding programs and improving productivity. In this study, we conducted whole-genome resequencing on 387 buffalo genomes from 29 diverse Asian breeds, including 132 river buffaloes, 129 swamp buffaloes, and 126 crossbred buffaloes. We identified 36,548 copy number variants (CNV) spanning 133.29 Mb of the buffalo genome, resulting in 2,100 CNV regions (CNVR), with 1,993 shared CNVR being found within the studied buffalo types. Analyzing CNVR highlighted distinct genetic differentiation between river and swamp buffalo subspecies, verified by evolutionary tree and principal component analyses. Admixture analysis grouped buffaloes into river and swamp categories, with crossbred buffaloes displaying mixed ancestry. To identify candidate genes associated with milk production traits, we employed 3 approaches. First, we used Vst-based population differentiation, revealing 11 genes within CNVR that exhibited significant divergence between different buffalo breeds, including genes linked to milk production traits. Second, expression quantitative loci analysis revealed differentially expressed CNVR-derived genes (DECG) associated with milk production traits. Notably, known milk production-related genes were among these DECG, validating their relevance. Last, a GWAS identified 3 CNVR significantly linked to peak milk yield. Our study provides comprehensive genomic insights into buffalo populations and identifies candidate genes associated with milk production traits. These findings facilitate genetic breeding programs aimed at increasing milk yield and improving quality in this economically important livestock species., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Despite the rapid growth in popularity of the Jersey breed, most research on dairy cows in the United States has been done with the Holstein breed. Postpartum uterine diseases negatively influence reproductive performance of dairy cows and limited data are available regarding predisposing factors for uterine diseases in Jersey cows. Our objectives were to determine the prevalence and risk factors for purulent vaginal discharge (PVD) and its effect on fertility of lactating Jersey cows. This was a retrospective observational study with data collected from 3,822 Jersey cows. The Metricheck device was used for PVD diagnosis, and positive cases (≥50% of pus in exudate) were further classified for severity using the following 4 categories based on the amount of pus observed: 50 to 60% pus in exudate, 60 to 90% pus in exudate, 90 to 100% pus in exudate, and 90 to 100% pus in exudate + uterine fluid detected by palpation per rectum. Univariable and multivariable regression analyzes were conducted to dissect the risk factors for PVD and severity of PVD in Jerseys cows. The major risk factors for PVD were calving-related problems, retained fetal membrane, metritis, and days in the close-up diet. A subgroup of cows (n = 740) was scored for body condition and locomotion scores and had blood sampled in the peripartum for determination of plasma concentrations of nonesterified fatty acids and β-hydroxybutyrate. In the multivariable analysis that considered data collected for the subgroup of cows, peripartum nonesterified fatty acids, postpartum β-hydroxybutyrate, and peripartum locomotion and body condition scores were not retained in the reduced model of predictors of PVD. Not surprisingly, pregnancy per artificial insemination following the first and second services was reduced in cows diagnosed with PVD compared with cows without PVD. In addition, PVD was associated with increased odds of pregnancy loss after the first service and reduced hazard of pregnancy by 305 d in milk. The stratification of PVD severity according to the amount of pus observed and the consistency of the uterus was meaningful, as observed by the differences in reproductive outcomes between cows with diverging amounts of pus in the retrieved exudate. Risk factors for PVD in Jersey cows was similar to previously reported for Holstein cows, and a strong detrimental effect of PVD on fertility was also observed in Jersey cows. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the effect of using or not using the genotypes of the parents of a cow for imputing SNPs on the estimation of genomic inbreeding coefficients of cows. Imputation (i.e., genotyped plus imputed) genotypes from 68,127 Italian Holstein dairy cows registered in the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed. Cows were genotyped with the high-density (HD) Illumina Infinium BovineHD BeadChip and GeneSeek Genomic Profiler HD-150K, and the medium-density (MD) GeneSeek Genomic Profiler 3, GeneSeek Genomic Profiler 4, GeneSeek MD, and the Labogena MD. To assess differences among estimators, genomic inbreeding coefficients were estimated with 4 PLINK v1.9 estimators (F, F hat1 ,F hat2 , andF hat3 ), 2 genomic relationship matrix- (grm) based estimators (F grm and F grm2 , with the latter including also pedigree information), and one estimator of runs of homozygosity (ROH; F ROH ). Assuming that the correct genomic inbreeding coefficients should be those estimated from genotyped SNPs, a comparison of the genomic inbreeding coefficients estimated either with the genotyped SNPs or the SNPs after imputation was made. Information on the presence or absence of genotypic information from sire, dam, and maternal grandsire during the imputation was investigated. Genomic inbreeding coefficients estimated with genotyped SNPs or SNPs after imputation were consistent for F, F hat3 , F grm2 , and F ROH , when at least one of the parents was genotyped. Biased (mainly higher) genomic inbreeding coefficients of imputation SNPs were observed in cows that were genotyped with MD SNP panels whose SNPs were poorly represented in the selected imputation SNP dataset and also did not have their parents genotyped, when compared with what would be expected based on actual genotype data. For cows genotyped with MD the estimators F hat1 , F hat2 , and F grm provided higher genomic inbreeding coefficients of imputation SNPs even with both parents and the maternal grandsire genotyped. Overall, F ROH was the most robust estimator, followed by F and F hat3 . Our findings suggest that SNPs selection, parental genotyping and estimator should be considered for designing imputation strategies in dairy cattle for estimating genomic inbreeding with imputation SNPs. For computing genomic inbreeding coefficients, it is recommendable to have at least one parent genotyped and use an ROH-based estimator., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The performance of an adult dairy cow may be influenced by events that occur before her birth. The present study investigated the potential effects of 2 prenatal groups of factors, assisted reproductive technologies and maternal characteristics (e.g., dam parity), on offspring performance during their first lactation in populations of 2 dairy cow breeds: French Holstein and Montbéliarde. The different assisted reproductive technologies studied included the type of semen (conventional or X-sorted) used for AI and the technology of conception used (AI, embryo transfer, or in vitro fertilization). Three maternal characteristics were considered: (1) the dam age at first calving, (2) dam parity number, and (3) indicators of dam udder health during gestation (SCS and events of clinical mastitis). First, we investigated whether heifer survival from 3 d to 18 mo old was associated with any of the prenatal factors considered. We then estimated the associations of these prenatal factors with 8 traits of commercial interest: (1) stature, (2-4) milk, fat, and protein yields, (5) SCS, (6) clinical mastitis, and (7-8) heifer and cow conception rate, all measured on genotyped cows. Linear models were used for this study with the prenatal factors as covariates in the model, and for the 8 traits, phenotypes were adjusted for their corresponding genomic EBV. The results indicated that the survival rate of heifers born from embryo transfer was significantly higher than that of heifers born from AI (probably due to preferential management practices), and the other prenatal factors did not explain large differences in heifer survival. Among the Montbéliarde cows born from AI, those born from X-sorted semen showed a lightly but significantly lower milk yield than those born without X-sorting of the semen (-52 kg of milk in the first lactation). Among the Holstein cows, those born from embryo transfer presented significantly lower milk performance than cows born from AI. Regarding the maternal characteristics, none or very weak associations were found between the dam age at first calving and the offspring performance in both breeds. Dam parity, on the other hand, was associated with offspring performance for milk, fat, and protein yield in both breeds, but not in the same direction. In the Holstein breed, an increase in dam parity was favorable for offspring performance for milk, fat, and protein yield, whereas in the Montbéliarde breed, an increase in dam parity was associated with lower milk and protein yield and no association was found for fat yield. The udder health of the dam during gestation was not or only weakly associated with the traits studied in the offspring. Although some significant associations were identified due to the large sample size, the effects were modest, typically less than 1% of the phenotypic mean, and were not consistently observed across the 2 breeds., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Johne's disease (JD) is an infectious enteric disease in ruminants, causing substantial economic loss annually worldwide. This work aimed to estimate JD's genetic parameters and the phenotypic and genetic trends by incorporating recent data. It also explores the feasibility of a national genetic evaluation for JD susceptibility in Holstein cattle in the United States. The data were extracted from a JD data repository, maintained at the Council on Dairy Cattle Breeding, and initially supplied by 2 dairy record processing centers. The data comprised 365,980 Holstein cows from 1,048 herds participating in a voluntary control program for JD. Two protocol kits, IDEXX Paratuberculosis Screening Ab Test (IDX) and Parachek 2 (PCK), were used to analyze milk samples with the ELISA technique. Test results from the first 5 parities were considered. An animal was considered infected if it had at least one positive outcome. The overall average of JD incidence was 4.72% in these US Holstein cattle. Genotypes of 78,964 SNP markers were used for 25,000 animals randomly selected from the phenotyped population. Variance components and genetic parameters were estimated based on 3 models, namely, a pedigree-only threshold model (THR), a single-step threshold model (ssTHR), and a single-step linear model (ssLR). The posterior heritability estimates of JD susceptibility were low to moderate: 0.11 to 0.16 based on the 2 threshold models and 0.05 to 0.09 based on the linear model. The average reliability of EBVs of JD susceptibility using single-step analysis for animals with or without phenotypes varied from 0.18 (THR) to 0.22 (ssLR) for IDX and from 0.14 (THR) to 0.18 (ssTHR and ssLR) for PCK. Despite no prior direct genetic selection against JD, the estimated genetic trends of JD susceptibility were negative and highly significant. The correlations of bulls' PTA with economically important traits such as milk yield, milk protein, milk fat, somatic cell score, and mastitis were low, indicating a nonoverlapping genetic selection process with traits in current genetic evaluations. Our results suggest the feasibility of reducing the JD incidence rate by incorporating it into the national genetic evaluation programs., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the average information restricted maximum likelihood method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low-to-moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One hundred ninety-nine significant SNP located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The Finnish Ayrshire (FAY) belongs to the Nordic Red breeds and is characterized by high milk yield, high milk components, good fertility, and functional conformation. The FAY breeding program is based on genomic selection. Despite the benefits of selection on breeding values, autozygosity in the genome may increase due to selection, and increased autozygosity may cause inbreeding depression in selected traits. However, there is lack of studies concerning selection signatures in the FAY after genomic selection introduction. The aim of this study was to identify signatures of selection in FAY after the introduction of genomic selection. Genomic data included 45,834 SNPs. The genotyped animals were divided into 2 groups: animals born before genomic selection introduction (6,108 cows) and animals born after genomic selection introduction (47,361 cows). We identified the selection signatures using 3 complementary methods: 2 based on identification of selection signatures from runs of homozygosity (ROH) islands and one based on the decay of site-specific extended haplotype between populations at SNP sites (Rsb). In total, we identified 34 ROH islands on chromosomes 1, 3, 6, 8, 12-15, 17, 19, 22, and 26 in FAY animals born before genomic selection (between 1980 and 2011) and 30 ROH islands on chromosomes 1-3, 13-17, 22, and 25-26 in FAY animals born after genomic selection introduction (between 2015 and 2020). We additionally detected 22 ΔROH islands on chromosomes 2-3, 11, 13, 14, 16, 18, 20, and 25-26. Finally, a total of 31 Rsb regions on chromosomes 2, 3, 14, 18, 20, and 25 were identified. Based on the results, genomic selection has favored certain alleles and haplotypes on genomic regions related to traits relevant in the FAY breeding program: milk production, fertility, growth, beef production traits, and feed efficiency. Several genes related to these traits (e.g., PLA2G4A, MECR, CHUK, COX15, RICTOR, SHISA9, and SEMA4G) overlapped or partially overlapped the observed selection signature regions. The association of genotypes within these regions and their effects on traits relevant in the FAY breeding program should be studied and genetic regions undergoing selection monitored in the FAY population., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

This study aimed to set up a life cycle assessment (LCA) approach at the level of individual animals to assess the effects of a 3-breed crossbreeding program on the environmental impact of cows. The study involved 564 cows, 279 purebred Holstein Friesian (HO) and 285 crossbred cows (CR), that originated from a 3-breed crossbreeding program based on the rotational use of Viking Red, Montebèliarde, and HO sires and kept in 2 dairy herds of northern Italy (224 and 340 cows/herd, respectively). The reference unit of the LCA model was the lifetime of cows, from the birth to culling or death. Data were collected at different levels: individual animal-based data referred to the whole life (birth, calving, dry, cull or death dates, and milk production); individual test-date collection of body measures and BCS, used to predict BW and to estimate energy requirements; common farm-based data concerning herd management (diets composition, and materials used). Data were used to compute DMI, milk and milk components production, gross income (GI), and income over feed costs (IOFC) pertaining to the lifespan of cows. An individual LCA-derived approach was set up to compute global warming potential (GWP), acidification and eutrophication potential (AP and EP, respectively), and land occupation (LO), which have been associated with different functional units (cow in her whole life or per day of life; kilograms of milk fat plus protein, and GI and IOFC [in euros] produced in the herd life). Data were analyzed using a generalized linear model including the fixed effects of genetic group (CR vs. HO), farm, and their interaction (genetic group × farm). Compared with HO, CR cows completed more lactations (+12%), had earlier first calving (-2 wk), yielded more fat plus protein in milk both in the lifespan (+8%) and per day of life (+4%). Concerning the environmental impact, when compared with HO herd mates, CR cows had nominal greater emissions per cow in the whole life, similar emissions per day of life and ∼3% lower GWP, AP, and EP per kilogram of fat plus protein yielded in lifespan. Income over feed costs per unit of emission tended to be ∼4% greater in CR compared with HO cows. Also, the use of land tended to be lower in CR compared with HO in most indicators considered. In conclusion, LCA could be adapted to represent individual animals. Moreover, managing dairy cows according to a 3-breed rotational crossbreeding scheme may be regarded as a strategy that can contribute to mitigate the emissions and to improve the environmental impact of dairy operations., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Genetic improvement in small countries rely heavily on foreign genetics. In an importing country such as Uruguay, consideration of unknown parent groups (UPG) for foreign sires is essential. However, the use of UPG in genomic model evaluations may lead to bias in genomic estimated breeding values (GEBV). The objective of this study was to study different models including UPG or metafounders (MF) in the Uruguayan Holstein evaluation and to analyze bias, dispersion, and accuracy of GEBV predictions in BLUP and single-step genomic BLUP (ssGBLUP). A gamma matrix (Γ) was estimated either by using base allele population frequencies obtained by bounded linear regression (MFbounded), or by using 2 values to design Γ (i.e., a single value for the diagonal and a different value for the off-diagonal [MFrobust]). Both Γ estimators performed well in terms of GEBV predictions, but MFbounded was the best option. There is, however, some bias whose origin was not completely understood. UPG or MF seem to model correctly genetic progress for unknown parents except for the very first groups (earlier time period). As for validation bulls, bias was observed across all models, whereas for validation cows it was only observed with UPG in BLUP. Overdispersion was found in all models, but it was mostly detected in validation bulls. Ratio of accuracies indicated that ssGBLUP gave better predictions than BLUP., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Reduction of methane emission may become necessary for sustainable milk production. Several studies indicate a relationship between rumination time and the level of methane emission. The objectives of the current study were to estimate environmental factors affecting daily rumination time in high-yielding dairy cattle, genetic parameters for rumination time across parities, and environmental and genetic correlations between rumination time and economic traits, and to predict the consequence of inclusion of this trait in the Israeli breeding index. The data included more than 30 million daily records from 77,697 Israeli Holstein cows for rumination time and milk production. A lactation measure of daily rumination time per cow was computed as the mean of the residuals from a linear model analysis with rumination time as the dependent variable. The independent variables were parity and the square root, linear, quadradic and inverse of DIM by parity. Because of the shape of the lactation curve for rumination time, separate linear model analyses were performed for records up to 40 DIM and records with >40 DIM. The phenotypic correlation between first- and second-parity lactations for rumination time was almost 0.8, and close to 0.7 for milk. The heritability of lactation rumination time was close to 0.44 for parities 1 to 3. Heritability for milk production decreased from 0.5 in first parity to 0.3 in third parity. For both traits, genetic correlations among parities were all >0.9. Thus, for routine genetic analysis of rumination time, records in the different parities can be considered the same trait. The genetic correlation between rumination time and milk on first parity was 0.25 and increased slightly with increase in parity. Genetic correlations between rumination time, based on the first 40 DIM, were economically unfavorable with retained placenta but economically favorable with metritis, ketosis, and displaced abomasum. Genetic correlations between rumination time and the 9 traits included in the Israeli breeding index (milk, fat, and protein production; SCS; female fertility; herd-life; milk production persistency; calving ease; and calf mortality) were all economically favorable, except for the correlation of 0.17 with SCS. With the current index, daily rumination time with a current mean of 536 min and SD of 90 min is expected to increase by 11 min/d after 10 yr of selection. Inclusion of this trait with a positive index weight equivalent to 10% of the index should increase rumination time by 19 min. All changes in expected gains due to inclusion of rumination time in the index were economically positive, except for fat and SCS. Inclusion of rumination time in the index should result in 1 kg less gain in fat, a miniscule gain of 0.03 for SCS; and gains of 1.5 kg protein, 0.3% female fertility, and 5 d herd-life. Even though the case for a genetic correlation between rumination time and methane emission is still weak, inclusion of this trait in the commercial index may be justified, considering that equipment is now commercially available for routine recording at reasonable cost., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

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., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Pedigrees used in genetic evaluations contain errors. Because of such errors, assumptions regarding the relatedness among individuals in genetic evaluation models are wrong. Consequences of that have been investigated in earlier studies focusing on models that did not account for genomic information yet. The objective of this work was to investigate the effects of pedigree errors on the results from genetic evaluations using the single-step model, and the effect of such effects on results from validation studies with forward prediction. We used a real pedigree (n = 361,980) and real genotypes (n = 25,950) of Fleckvieh cattle, sampled in a way to provide a good consistency between pedigree and genomic relationships. Given the real pedigree and genotypes, true breeding values (TBV) were simulated to have a covariance structure equal to the matrix H assumed in a single-step model. Based on TBV, phenotypes were simulated with a heritability of 0.25. Genetic evaluations were conducted with a conventional animal model (i.e., without genomic information) and a single-step animal model under scenarios using either the correct pedigree or a pedigree containing 5%, 10%, or 20% of wrong records. Wrong records were simulated by randomly assigning wrong sires to nongenotyped females. The increasing rates of pedigree errors led to decreasing correlations between TBV and EBV and lower standard deviations of predictions. Less variation was observed because pedigree errors operate actually as a random exchange of daughters among bulls, making them look more similar to each other than they actually are. This occurs of course only when animals have progeny. Therefore, this decreased variation was more pronounced for progeny tested bulls than for young selection candidates. In a forward prediction validation scenario, the stronger decrease in variation when animals get progeny caused an apparent inflation of early predictions. This phenomenon may contribute to the usually observed problem of inflation of early predictions observed in validation studies., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

In recent years, research in animal breeding has increasingly focused on the topic of resilience, which is expected to continue in the future due to the need for high-yielding, healthy, and robust animals. In this context, an established approach is the calculation of resilience indicator traits with time series analyses. Examples are the variance and autocorrelation of daily milk yield in dairy cows. We applied this methodology to the German dairy cow population. Data from the 3 breeds (German Holstein, German Fleckvieh, and German Brown Swiss) were obtained, which included 13,949 lactations from 36 farms from the state Baden-Württemberg in Germany working with automatic milking systems. Using the milk yield data, the daily absolute milk yields, deviations between observed and expected daily milk yields, and relative proportions of daily milk yields in relation to lactation performance were calculated. We used the variance and autocorrelation of these data as phenotypes in our statistical analyses. We estimated a heritability of 0.047 for autocorrelation and heritabilities between 0.026 and 0.183 for variance-based indicator traits. Furthermore, significant breed differences could be observed, with a tendency of better resilience in Brown Swiss. The breed differences can be due to both genetic and environmental factors. A high value of a variance-based indicator trait indicates a low resilience. Performance traits were positively correlated with variance-based indicator traits calculated from absolute daily milk yields, but they were negatively correlated with variance-based indicators calculated from relative daily milk yields. Thus, they can be considered as different traits. Although variance-based indicators based on absolute daily milk yields were affected by the performance level, variance-based indicators based on relative daily milk yields were corrected for the performance level and also showed higher heritabilities. Thus, they seem to be more suitable for practical use. Further studies need to be conducted to calculate the correlations between resilience indicators, functional traits, and health traits., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Lactation curves were estimated for Montbéliarde (MO) × Holstein (HO) and Viking Red (VR) × HO 2-breed crossbred cows and for MO × VR/HO and VR × MO/HO 3-breed crossbred cows and their HO herdmates from test-day observations in 7 high-performance herds that participated in a designed study. Cows calved from 2010 to 2017. Test-day observations from milk recording were used to fit the lactation curves of cows in their first 3 lactations. Lactations of cows were required to have at least 250 DIM and to have at least 6 test days ≤265 DIM. Lactation curves from random regression (RR) were compared for 305-d production (kg), peak production (kg), peak day of production, and production from 4 to 103 DIM (kg), from 104 to 205 DIM (kg), and from 206 to 305 DIM (kg) for milk, fat, and protein. Also, the persistency of production was compared. First-lactation versus second- and third-lactation cows were analyzed separately for both the 2-breed and 3-breed crossbred cows and their respective HO herdmates. Legendre polynomial RR had the best goodness of fit for the lactation curves compared with Ali-Schaeffer and Wilmink RR from the test-day observations of milk, fat, and protein production. For fluid milk production of first-lactation cows, the MO × HO 2-breed crossbreds were not different from their HO herdmates for any of the lactation-curve characteristics, except persistency. However, the VR × HO 2-breed crossbreds had less fluid milk production compared with their HO herdmates. For first lactation, the MO × HO 2-breed crossbreds had more persistency of milk, fat, and protein production compared with their HO herdmates. The first-lactation MO × VR/HO 3-breed crossbreds had more persistency of fluid milk production compared with their HO herdmates. For second and third lactations, both the MO × HO and the VR × HO 2-breed crossbreds had higher fat production compared with their HO herdmates. Furthermore, the MO × HO 2-breed crossbreds had more protein production (kg) in all 3 periods of lactation compared with their HO herdmates. Crossbred cows may have advantages over HO cows for persistency of production in high-performance herds., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Over the past decades, daughter designs, including genotyped sires and their genotyped daughters, have been used as an approach to identify QTL related to economic traits. The aim of this study was to identify genomic regions inherited by Gir sire families and genes associated with number of viable oocytes (VO), total number of oocytes (TO), and number of embryos (EMBR) based on a daughter design approach. In total, 15 Gir sire families were selected. The number of daughters per family ranged from 26 to 395, which were genotyped with different SNP panels and imputed to the Illumina BovineHD BeadChip (777K) and had phenotypes for oocyte and embryo production. Daughters had phenotypic data for VO, TO, and EMBR. The search for QTL was performed through GWAS based on GBLUP. The QTL were found for each trait among and within families based on the top 10 genomic windows with the greatest genetic variance. For EMBR, genomic windows identified among families were located on BTA4, BTA5, BTA6, BTA7, BTA8, BTA13, BTA16, and BTA17, and they were most frequent on BTA7 within families. For VO, genomic windows were located on BTA2, BTA4, BTA5, BTA7, BTA17, BTA21, BTA22, BTA23, and BTA27 among families, being most frequent on BTA8 within families. For TO, the top 10 genomic windows were identified on BTA2, BTA4, BTA5, BTA7, BTA17, BTA21, BTA22, BTA26, and BTA27, being most frequent on BTA7 and BTA8 within families. Considering all results, the greatest number of genomic windows was found on BTA7, where the VCAN, XRCC4, TRNAC-ACA, HAPLN1, and EDIL3 genes were identified in the common regions. In conclusion, 15 Gir sire families with 26 to 395 daughters per family with phenotypes for oocyte and embryo production helped to identify the inheritance of several genomic regions, especially on BTA7, where the EDIL3, HAPLN1, and VCAN candidate genes were associated with number of oocytes and embryos in Gir cattle families., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The objective of this study was to perform a quantitative and qualitative evaluation of microbial contamination of harvested colostrum on 39 Czech dairy farms. The study identified the proportion of colostrum samples that met the recommended goals for total plate count (TPC), total coliform count (TCC), and gram-negative noncoliform count (NCC), and evaluated the effect of the farm, breed, parity, season of the year, time of calving, and colostrum volume on these 3 microbiological parameters. Colostrum samples from cows (n = 1,241; 57.6% from Czech Fleckvieh, and 42.4% from Holstein breed) were collected on dairy farms between autumn of 2015 and spring of 2017. The samples were collected after the first milking directly from milking buckets. In 155 out of 1,241 colostrum samples (26 farms, 6 samples each, except 1 farm), the species of microorganisms obtained by culture were determined, and the findings were classified into 4 groups according to the probable source of contamination as follows: (1) normal inhabitants of bovine skin and mucosa, (2) fecal contaminants, (3) environmental contaminants, and (4) potential gram-positive mammary pathogens. Our results showed heavy microbial contamination of collected colostrum samples (TPC median = 408,000 cfu/mL; TCC median = 200 cfu/mL; NCC median = 80 cfu/mL). Only 28.4% of samples met the requirement for TPC (<100,000 cfu/mL), 88.2% for TCC (<10,000 cfu/mL), and 86.0% for NCC (<5,000 cfu/mL). Among the tested factors, we found that farm had a significant effect on all 3 microbiological parameters, volume of colostrum had an effect on TPC (the highest TPC in <3.0 L of colostrum), and season had an effect on TCC and NCC (higher TCC in summer than in autumn and winter; the highest NCC in summer and higher in autumn than in spring and winter). Our results showed that most microbes isolated from colostrum belonged to normal inhabitants of bovine skin and mucosa, fecal, or environmental contaminants (i.e., 82.6%, 81.9%, and 75.5% of colostrum samples, respectively). Potential gram-positive mammary pathogens were found in 13.5% of samples. Escherichia coli was isolated from 9.0% of colostrum samples, and Streptococcus uberis and Streptococcus parauberis were each isolated from 5.2% of samples. Our study showed high microbial contamination of colostrum collected on dairy farms. Therefore, better hygiene and sanitation around colostrum harvest should be addressed by farmers. [ABSTRACT FROM AUTHOR]

Lactation yield estimates standardized to common lactation lengths of 270-d or 305-d equivalents are commonly used in management decision support tools and dairy cow genetic evaluations. The use of such measurements to quantify the (genetic) merit of individual cows fails to penalize cows that do not reach the standardized lactation length, or indeed reward cows that lactate for more than the standardized lactation length. The objective of the present study was to quantify the genetic and nongenetic factors associated with lactation length in seasonal-calving, pasture-based dairy cows. A total of 616,350 lactation length records from 285,598 Irish cows were used. Linear mixed models were used to quantify the associations between lactation length and calving month, parity, age at calving, previous dry period length, calving difficulty score, heterosis, recombination loss, breed, and herd size, as well as to estimate the genetic and residual variance components of lactation length. The median lactation length in the edited data set was 288 d, with 27% of cows achieving lactations of at least 305 d. Relative to cows calving in January, the lactations of cow calving in February, March, or April was, on average, 4.2, 12.7, and 21.9 d shorter, respectively. The lactation length of a first parity cow was, on average, 7.8, 8.6, and 8.4 d shorter than that of second, third, and fourth parity cows, respectively. Norwegian Red and Montbéliarde cows had, on average, a 4.7- and 1.6-d shorter lactation than Holstein-Friesian cows, respectively. The heritability estimate, coefficient of genetic variation, and repeatability estimate of lactation length were 0.02, 1.2%, and 0.04, respectively. Based on the genetic standard deviation for lactation length estimated in the present study (3.3 d), cows ranked in the top 20% for genetic merit for lactation length would be expected to have lactations 9.2 d longer than cows in the bottom 20%, demonstrating exploitable genetic variability. Given the vast array of genetic and nongenetic factors associated with lactation length, an approach which combines improved management practices and selective breeding may be an efficient and effective strategy to lengthen lactations. [ABSTRACT FROM AUTHOR]

During the last decade, the use of systematic crossbreeding in dairy cattle herds has increased in several countries of the world. The aim of this study was to estimate the effect of breed proportion and heterosis on milk production traits and udder health traits in dairy cattle. The study was based on records on milk yield (MY), protein yield (PY), fat yield (FY), somatic cell score (SCS), and mastitis (MAST) from 73,695 first-lactation dairy cows in 130 Danish herds applying systematic crossbreeding programs. Around 45% of the cows were crosses between Danish Holstein (DH), Danish Red (DR), or Danish Jersey (DJ), and the remaining were purebred DH, DR, or DJ. The statistical model included the fixed effects of herd-year, calving month, and calving age and an effect representing the lactation status of the cow. In addition, the model included a regression on calving interval from first to second lactation, a regression on the proportion of DH, DR, and DJ genes, and a regression on the degree of heterozygosity between DH and DR, DH and DJ, and DR and DJ. Random effects were the genetic effect of the cow and a residual. The effect of breed proportions was estimated relatively to DH. For MY, a pure DR yielded 461 kg milk less than DH, whereas a pure DJ yielded 2,259 kg milk less than a pure DH. Compared with DH, PY was 41.7 kg less for DJ, whereas PY for DR was 4.0 kg less than for DH. For FY, a DR yielded 10.6 kg less than DH, whereas there was no significant effect of breed proportion between DJ and DH. A DR cow had lower SCS (0.13) than DH, whereas DJ had higher SCS (0.14) than DH. There was no significant effect of breed proportion on MAST between the 3 breeds. Heterosis was significant in all combinations of breeds for MY, FY, and PY. Heterosis for crosses between DH and DR was 257 kg (3.2%), 11.9 kg (3.2%), and 8.9 kg (3.2%) for MY, PY, and FY, respectively. Corresponding figures for crosses between DH and DJ were 314 kg (4.4%), 14.3 kg (4.4%), and 10.4 kg (4.0%), whereas heterosis between DR and DJ was 462 kg (6.7%), 19.6 kg (6.7%), and 13.9 kg (5.4%) for MY, PY, and FY, respectively. Heterosis was only significant for SCS in the crosses between DH and DR. Heterosis effects for MAST were nonsignificant for all the crosses. The results obtained in this study demonstrate that in first lactation cows, there is a positive effect of heterosis on milk production traits, but limited effect on udder health traits. [ABSTRACT FROM AUTHOR]