Cow activity measurements can be used to define new fertility traits for use in genetic evaluation.

Cow activity measurements are widely used in herd management tools for estrus detection. The aim of this study was to examine whether a new trait based on activity measures can be useful for genetic evaluation of cow fertility in Norwegian Red dairy cattle. Data from 284 herds with Lely milking robot were collected. Daily measurements of cow activity level were available from Lely activity tags and included data from 13,224 lactations of 8,139 Norwegian Red cows. We analyzed daily activity and included records from 10 to 150 d in milk for cows with at least 50 records. The trait analyzed was interval from calving to first high activity (CFHA). In total 87% of the cows had at least one episode of high activity recorded. The mean (standard deviation) of CFHA was 42 (28) days. A linear animal repeatability model with fixed effects of month-year of calving, age-parity, and herd, and random animal and permanent environment effects was used for estimation of variance components. The trait CFHA showed significant genetic variation with a heritability of 0.05 (0.01). This trait reflects the cow's ability to return to estrus cycle and show estrus after calving, which are important aspects of cow fertility.

Heritability of subclinical endometritis in Norwegian Red cows.

Subclinical endometritis (SCE) is highly prevalent in dairy cows, causing negative effects on reproductive outcomes and the producer economy. Genetic selection for animals with better resilience against uterine disease should be prioritized due to both sustainability and animal welfare. Therefore, the aim of the present study was to estimate the heritability of SCE in the Norwegian Red (NR) population. Moreover, future perspectives of the condition as a fertility phenotype for breeding are discussed. A total of 1,642 NR cows were sampled for SCE at the time of artificial insemination, using cytotape. The percentage of polymorphonuclear cells (PMN) in each sample was established by cytology, through the counting of 300 PMN and epithelial cells. The mean percentage of PMN was 5%. Different trait definitions were examined, and SCE was defined as binary traits, based on the following cut-off levels of PMN: Cyto0 = PMN  >0, Cyto3 = PMN  >3%, Cyto5 = PMN  >5%, Cyto10 = PMN  >10%, and Cyto20 = PMN  >20%.  The mean ranged from 0.07 (Cyto20) to 0.59 (Cyto0). We also analyzed PMN as a continuous variable using percent PMN. Information on the animals and herds was obtained from the Norwegian Dairy Herd Recording System. The pedigree of cows with data included a total of 24,066 animals. A linear animal model was used to estimate the heritability. The only trait definition that had an estimated genetic variance larger than the standard error was Cyto5, with an estimated heritability of 0.04. For all other definitions, the genetic variance was not significantly different from zero. A cut-off level of 5% PMN has been established as a general threshold for the definition of SCE in earlier literature. The standard errors of the estimated variance components were relatively large, and results should be interpreted with caution. However, the current study indicates that SCE is heritable at a similar level to that of clinical endometritis and metritis, and has potential as a future fertility phenotype to be used for breeding purposes. A more feasible method to diagnose SCE is needed to establish larger data sets.

Genetic analysis of semen characteristic traits in Norwegian Red bulls at the artificial insemination center.

Compared with cow fertility, genetic analyses of bull fertility are limited and based on relatively few animals. The aim of the present study was to estimate genetic parameters for semen characteristics of Norwegian Red bulls at the artificial insemination (AI) center (Geno AI station, Stange, Norway) and to estimate genetic correlations between some of these traits and andrology traits measured at the performance test station. The data from the AI center consisted of records from 137,919 semen collections from 3,145 bulls with information on semen weight, sperm concentration, motility before and after cryopreservation, motility change during cryopreservation, and number of accepted straws made. Data from the performance test station included 12,522 observations from 3,219 bulls on semen volume, concentration, and motility (%) when fresh and after storing for 24 and 48 h. Genetic parameters were estimated using linear animal repeatability models that included fixed effects of year-month of observation, age of bull, interaction between semen collection number, and interval between collections for all traits and type of diluter for postcryopreservation traits. The random effects included test-day, permanent environmental, and additive genetic effects of the bull. Based on records from the AI center, we found that semen weight, sperm concentration, and number of straws were moderately heritable (0.18-0.20), whereas motility had a lower heritability (0.02-0.08). Heritability of motility (%) was higher after cryopreservation than before. Genetic correlations among the semen characteristics ranged from unfavorable (-0.35) to favorable (0.93), with standard errors ranging from 0.02 to 0.22. Among the most precise genetic correlation estimates, number of straws made from a batch correlated favorably with semen weight (0.62 ± 0.06) and sperm concentration (0.44 ± 0.08), whereas sperm concentration was negatively correlated with weight (-0.33 ± 0.09). The genetic correlation between motility (%) before and after cryopreservation was 0.64 ± 0.14, and motility change during cryopreservation had a strong favorable genetic correlation with motility after cryopreservation (-0.93 ± 0.02). The estimated genetic correlation (standard error) between the traits volume, concentration, and motility when fresh measured at the performance test station and their respective corresponding traits at the AI center were 0.83 (0.05), 0.78 (0.09), and 0.49 (0.31). The final product at the AI center (number of accepted straws) correlated genetically favorably with all semen characteristic traits recorded at the performance test station (ranging from 0.51 to 0.67). Our results show that the andrology testing done at the performance test station is a resource to identify the genetically best bulls for AI production.

Expression analysis of candidate genes for chronic subclinical mastitis in Norwegian Red cattle.

Chronic subclinical mastitis (SCM) is characterized by a long-term inflammation in the udder with high somatic cell count (SCC) in milk. Previously, several novel alternative SCM traits for Norwegian Red (NR) cattle have been defined to improve breeding strategies against chronic SCM. Quantitative trait loci and candidate genes affecting chronic SCM in NR have been identified. The aim of this study was to analyze the expression profiles of 14 selected candidate genes (RAD17, ACOT2, ACOT4, FOS, CXCL1, CXCL8, CCNB1, CDK7, TGFB3, SEL1L, STAT4, C6, GLI2, and SLC18A2). Twenty healthy NR cows with official genomic estimated breeding values (GEBV) for lactation average somatic cell scores (LSCS) were selected. Ten cows had high GEBV for LSCS (cows with low probability to have high SCC in milk during lactation) and 10 cows had low GEBV for LSCS (cows with high probability of having high SCC in milk). We isolated RNA from unstimulated peripheral blood mononuclear cells from these. Two out of the 14 analyzed genes showed significantly different results between groups. The group with high GEBV for LSCS displayed significantly higher expression of the CXCL1 gene than the low GEBV group. Grouping by lactation stage revealed significant differential expression of the FOS gene, with higher expression in early lactation (2-3 mo after calving) compared with late lactation (7-8 mo after calving). In addition, flow cytometry was performed on the peripheral blood mononuclear cells samples to analyze if number and type of isolated cells influenced the gene expression in the groups. The results in the current study provide identified genes that can be considered as possible candidate genes for chronic SCM in NR cows.

A genetic study of new udder health indicator traits with data from automatic milking systems.

The current study aimed to investigate new udder health traits based on data from automatic milking systems (AMS) for use in routine genetic evaluations. Data were from 77 commercial herds; out of these, 24 had equipment for measuring online cell count (OCC), whereas all had data on electrical conductivity (EC). A total of 4,714 Norwegian Red dairy cows and 2,363,928 milkings were included in the genetic analyses. Electrical conductivity was available on quarter level for each milking, whereas OCC was measured per milking. The AMS traits analyzed were log-transformed online cell count (lnOCC), maximum conductivity (ECmax), mean conductivity (ECmean), elevated mastitis risk (EMR), and log-transformed EMR (lnEMR). In addition, lactation mean somatic cell score (LSCS) was collected from the Norwegian dairy herd recording system. Elevated mastitis risk expresses the probability of a cow having mastitis and was calculated from smoothed lnOCC values according to individual trend and level of the OCC curve. The udder health traits from AMS were analyzed as repeated milkings from 30 to 320 DIM, and LSCS as repeated parities. In addition, both ECmax and lnOCC were analyzed as multiple traits by splitting the lactation into 5 periods. (Co)variance components were estimated from bivariate mixed linear animal models, and investigated traits showed genetic variation. Estimated heritabilities of ECmean, ECmax, and lnEMR were 0.35, 0.23, and 0.12, respectively, whereas EMR and lnOCC both showed heritabilities of 0.09. Heritability varied between periods of lactation, from 0.04 to 0.13 for lnOCC and from 0.12 to 0.27 for ECmax, although standard errors of certain periods were large. Genetic correlations among the AMS traits ranged from 0 to 0.99. The genetic correlations between EC-based traits and OCC-based traits in AMS were 0. Genetic correlations with LSCS were favorable, ranging from 0.37 to 0.80 (±0.11-0.22). The strongest correlation (0.80 ± 0.13) was found between LSCS and lnEMR. Results question the value of ECmax and ECmean as indicators of udder health in genetic evaluations and suggest OCC to be more valuable in this manner. This study demonstrates a potential of using AMS data as additional information on udder health for genetic evaluations, although further investigation is recommended before these traits can be implemented.

Genetic correlations between body weight, daily weight gain, and semen characteristic traits in young Norwegian Red bulls.

The aim of this study was to estimate genetic parameters for body weight (BW) at 150 d (Bw_150d), and 330 d (Bw_330d) of age and average daily weight gain (Dwg), and to estimate genetic correlations between these traits and semen characteristic traits: volume; concentration (Conc); motility in fresh, 24-h, and 48-h samples (Mot0h, Mot24h, Mot48h); and sperm defects. Data were collected at the performance test station of young Norwegian Red bulls from 2002 to 2012, before selection of bulls for artificial insemination. The weight and growth data consisted of observations for 3,209 bulls, and andrology information was available for up to 2,034 of these bulls. Genetic parameters were estimated using linear animal models. Models for BW and growth traits included the group and year the bull left the station and the pen they occupied during weighing (group-year-pen) and parity of their dam as fixed effects. Models for andrology traits had group-year, age in months (11 to 15), and the interaction between ejaculate number and days since previous collection included as fixed effects. Estimated heritability was 0.14 for Bw_150d, 0.26 for Bw_330d, and 0.34 for Dwg; the estimated genetic correlations among these traits were all favorable. Both BW traits correlated favorably with all the semen characteristic traits (0.20 to 0.76), whereas Dwg was favorably correlated with volume, Mot24h, Mot48h, and sperm defects, and unfavorably correlated with Conc (-0.25) and Mot0h (-0.53). Our results indicate that the genetic correlations between weight and growth traits and semen characteristics depend on the age of the bulls. Although most genetic correlations were favorable, selection for higher daily weight gain between 150 and 330 d might explain the slight negative genetic trends observed for semen characteristics in young Norwegian Red bulls.

Are farmer assessed temperament, milking speed, and leakage genetically the same traits in automatic milking systems and traditional milking systems?

The aim was to investigate whether subjectively scored milking speed, temperament, and leakage are genetically the same trait when measured in different milking systems. Data were provided by the Norwegian Dairy Herd Recording System and included a total of 260,731 first-parity Norwegian Red cows calving between January 2009 and February 2019 and milked either in a traditional milking system (milking parlor or pipeline) or by an automatic milking system (AMS). Genetic parameters were estimated and lower heritabilities and less genetic variation were found for the 3 traits when measured in AMS herds. The heritability of temperament, leakage, and milking speed were 0.05, 0.04, and 0.22, respectively, with data from AMS herds; and 0.09, 0.14, and 0.27, respectively, with data from cows milked in traditional milking systems. The genetic correlations between temperament and leakage (-0.19), between milking speed and leakage (-0.88), and between milking speed and temperament (0.30) in AMS were slightly stronger than between the corresponding traits assessed in other milking systems (-0.15, -0.82, and 0.16, respectively). The genetic correlations between traits across milking systems were strong: 0.98, 0.96, and 0.86 for milking speed, leakage, and temperament, respectively. Strong correlations indicate that the traits were almost genetically similar despite being scored in different milking systems. The rank correlations among estimated sire breeding values were strong: 0.98 and 0.99 for milking speed and leakage, with little or no reranking of bull performance across milking systems. Temperament had the lowest genetic correlation (0.86) and rank correlation (0.91) across milking systems. These data suggest that AMS farmers evaluate temperament slightly differently from farmers using other milking systems or that different aspects of temperament are important for farmers with AMS.

Identification of candidate genes affecting chronic subclinical mastitis in Norwegian Red cattle: combining genome-wide association study, topologically associated domains and pathway enrichment analysis.

The aim of this study was to identify genes associated with chronic subclinical mastitis (SCM) in Norwegian Red (NR) cattle. Twelve SCM traits defined based on fixed threshold for test-day somatic cell count (SCC) were, together with lactation-average somatic cell score (LSCS) used for association and pathway enrichment analyses. A GWAS was performed on 3795 genotyped NR bulls with 777K SNP data and phenotypic information from 7 300 847 test-day SCC observations from 3 543 764 cows. At 5% chromosome-wide significance level 36 unique SNP were detected to be associated with one or more of the traits. These SNPs were analysed for linked genes using genomic positions of topologically associated domains (TAD). For the SCM traits with SCC >50 000 and >100 000 cells/ml on two test-days in a row and LSCS, the same top significant genes were identified - checkpoint clamp loader component (RAD17) and cyclin B1 (CCNB1). The SCM traits with SCC >250 000, 300 000, 350 000 or 400 000 cells/ml on two test-days in a row and D400 (number of days before the first case with SCC >400 000 cells/ml) displayed similar top significant genes: acyl-CoA thioesterase 2 and 4 (ACOT2; ACOT4). For the traits SCM200_3 (SCC >200 000 cells/ml on three test-days in a row) and SCM150, SCM200 (SCC >150 000; 200 000 cells/ml on two test-days in a row) a group of chemokine (C-X-C motif) ligand genes and the Fos proto-oncogene, AP-1 transcription factor subunit (FOS) gene, were identified. Further functional studies of these identified candidate genes are necessary to clarify their actual role in development of chronic SCM in NR cattle.

Genetic analysis of semen characteristic traits in young Norwegian Red bulls.

The aim of this study was to estimate genetic parameters and genetic trends for male fertility in Norwegian Red bulls. We analyzed data on semen characteristics traits collected at the performance test station of young bulls from 1994 to 2016, in an andrology test used to ensure acceptable semen quality before being selected as an artificial insemination bull. Traits included were volume, concentration, and motility (percentage of moving sperm cells) in fresh samples and after storing for 24 and 48 h, and sperm defects. The data consisted of 14,972 ejaculates from 3,927 young (11-15 mo) Norwegian Red bulls. Genetic parameters were estimated using bivariate linear animal models that included age in months, group-year, and collection-group (main effect of the interaction between ejaculate number and interval between collections) as fixed effects, and test-day and additive genetic and permanent environment effect of the bull as random effects. Considerable genetic coefficients of variation were found for concentration and volume, with lower values for motility. Estimated heritabilities ranged from 0.02 and 0.03 (for sperm defects and motility in fresh samples) to 0.14 (volume and concentration measured on a continuous scale). All estimated genetic correlations were favorable, but the genetic correlations between volume and concentration and volume and sperm defects were not significantly different from zero. The genetic correlations between concentration and motility traits ranged from 0.53 to 0.83, and those between volume and the motility traits were between 0.24 and 0.57. All traits showed a slightly unfavorable genetic trend. Our results indicate that selection of bulls with better sperm quality is possible.

Genetic analyses of novel temperament and milkability traits in Norwegian Red cattle based on data from automatic milking systems.

The number of dairy cows milked in automatic milking systems (AMS) is steadily increasing in Norway. Capacity and efficiency of AMS are highly dependent on the individual cow's milking efficiency, such as milking speed and occupation time in the milking robot. Cows meet new challenges in herds utilizing AMS. Consequently, new or revised traits may be needed for genetic evaluation of dairy cattle. The AMS records relevant information on an individual cow basis. The aims of this study were to estimate genetic parameters of new automatically recorded milkability and temperament traits. Data from 77 commercial herds with Norwegian Red dairy cattle were analyzed by mixed linear animal models. The final data set contained 1,012,912 daily records from 4,883 cows in first to ninth lactation. For variance component estimation, univariate and bivariate models were used. Daily records of box time (BT), average flow rate (FR), kilograms of milk per minute of box time (MEF), handling time (HT), log-transformed HT, milking frequency, and milking interval were analyzed with repeatability models. Among these traits, FR, BT, and MEF showed the highest heritabilities of 0.48, 0.27, and 0.22, respectively, whereas heritability of log-transformed HT, HT, milking frequency, and milking interval was low (0.02-0.07). Unsuccessful milkings expressed as rejected milkings, incomplete milkings (IM), milkings with kick-offs (KO), and teat not found also showed low heritabilities (0.002-0.06). Due to low frequency, KO, rejected milkings, IM, and teat not found were also analyzed as proportions per lactation, which resulted in slightly higher heritability estimates. Genetic correlations were favorable and intermediate to strong between BT, HT, MEF, and FR with absolute values above 0.50. Intermediate and favorable correlations were found for IM and KO with BT, HT, MEF, and FR. Cow milkability in AMS can be improved by selection for reduced number of unsuccessful milkings, faster FR, increased MEF, and shorter BT and HT. Our results confirm that automatically recorded data on milkability and temperament can be valuable sources of information for routine genetic evaluations and that milking efficiency in AMS can be genetically improved.

Alternative subclinical mastitis traits for genetic evaluation in dairy cattle.

Chronic subclinical mastitis (SCM), characterized by changes in milk composition and high somatic cell count (SCC) in milk for a prolonged period of time, is often caused by a bacterial infection. Different levels of SCC have been suggested and used as threshold to identify subclinical infection. The aim of this study was to examine different definitions of SCM based on test-day SCC and estimate genetic parameters for these traits and their genetic correlation to milk production. Test-day SCC records from 1,209,128 Norwegian Red cows in lactation 1 to 3 were analyzed. Twelve SCM traits were defined as binary with 2 test-day SCC in a row above SCC thresholds from 50,000 to 400,000 cells/mL (SCM50, SCM100, SCM150, SCM200, SCM250, SCM300, SCM350, and SCM400), with 3 test-day SCC in a row above 200,000 and 400,000 cells/mL (SCM200_3 and SCM400_3), and the number of days before the first case with SCM50 (D50) or SCM400 (D400). The heritability and genetic correlations were estimated for SCM traits and the mean lactation-average somatic cell score (LSCS) using linear animal repeatability models. The total mean frequency of SCM ranged from 1.2% to 51.8%, for different trait definitions, high for low SCC threshold (SCM50) and low for the highest SCC threshold (SCM400_3). For the 2 traits based on number of days, the mean values were 104 (D50) and 117 (D400) days. The mean LSCS was 4.4 (equivalent to around 82,000 SCC). Heritabilities for the 12 alternative SCM traits were low and varied from 0.01 (SCM400_3) to 0.1 (SCM100), whereas for LSCS the estimated heritability was 0.3 and standard error varied from 0.001 to 0.003. Genetic correlations among the SCM traits ranged from 0.7 (D50 and SCM400) to 1 (SCM350 and SCM400), whereas between SCM traits and milk production the correlation ranged from 0.07 (LSCS) to 0.3 (D400). The standard error for genetic correlations varied from 0.001 to 0.06. The heritability was low and the genetic correlations were strong among SCM traits. Genetic correlations lower than 1 suggest that the alternative SCM traits are genetically different from LSCS, the trait currently used in genetic evaluations for Norwegian Red. Hence, the alternative traits will add information and improve breeding for better udder health.

The effects of crossbreeding with Norwegian Red dairy cattle on common postpartum diseases, fertility and body condition score.

Norwegian Red bulls, selected in Norway, have been used for crossbreeding with Israeli Holstein on commercial farms. The aim of this project was to investigate Norwegian Red×Israeli Holstein (NRX) performance to see how the daughters perform in a different environment than the one their sires were selected in. This was done by comparing health and fertility of NRX with their Israeli Holstein (HO) counterparts. The data consisted of 71 911 HO records and 10 595 NRX records from 33 855 cows in 23 Israeli dairy herds. Calving events took place between 2006 and 2016. Five postpartum disorders (mean frequency in HO v. NRX, %) recorded by veterinarians were analyzed: anestrus (37.4 v. 41.2), metritis (40.1 v. 28.6), ketosis (11.9 v. 7.1), lameness (7.1 v. 3.1) and retained placenta (6.2 v. 4.0). The incidence of abortions was also analyzed; HO had a mean frequency of 9.9% and NRX 8.2%. These traits were defined as binary traits, with '1' indicating that the disorder was present and a treatment took place at least once, or '0' if the cow did not show signs of that disorder. Days open (i.e. the number of days from calving to conception), body condition score (BCS) recorded on a 1 to 5 scale and changes in BCS from calving to peak lactation were also analyzed. A logistic model was used for the health traits, while days open and BCS were analyzed with linear models. The model included breed group, herd-year of calving, birth year and parity as fixed effects. There was a significantly higher risk (odds ratio for HO v. NRX in parentheses) of ketosis (1.46), metritis (1.78), lameness (2.07), retained placenta (1.41) and abortion (1.13) in HO compared with NRX. Israeli Holstein heifers and cows in parity 3 to 6 had fewer cases of anestrus than NRX but no differences were found between the groups in parities 1 and 2. Body condition score was higher for NRX than HO and there was less change in BCS from calving to peak lactation in NRX compared with HO. Likewise, NRX had fewer days open than HO. Results indicate that crossbreeding can produce cows with better fertility that are less susceptible to postpartum disorders.

Invited review: Genetics and claw health: Opportunities to enhance claw health by genetic selection.

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues related to genetic evaluation of claw health; discuss data sources, trait definitions, and data validation procedures; and present a review of genetic parameters, possible indicator traits, and status of genetic and genomic evaluations for claw disorders. Different sources of data and traits can be used to describe claw health. Severe cases of claw disorders can be identified by veterinary diagnoses. Data from lameness and locomotion scoring, activity information from sensors, and feet and leg conformation traits are used as auxiliary traits. The most reliable and comprehensive information is data from regular hoof trimming. In genetic evaluation, claw disorders are usually defined as binary traits, based on whether or not the claw disorder was present (recorded) at least once during a defined time period. The traits can be specific disorders, composite traits, or overall claw health. Data validation and editing criteria are needed to ensure reliable data at the trimmer, herd, animal, and record levels. Different strategies have been chosen, reflecting differences in herd sizes, data structures, management practices, and recording systems among countries. Heritabilities of the most commonly analyzed claw disorders based on data from routine claw trimming were generally low, with ranges of linear model estimates from 0.01 to 0.14, and threshold model estimates from 0.06 to 0.39. Estimated genetic correlations among claw disorders varied from -0.40 to 0.98. The strongest genetic correlations were found among sole hemorrhage (SH), sole ulcer (SU), and white line disease (WL), and between digital/interdigital dermatitis (DD/ID) and heel horn erosion (HHE). Genetic correlations between DD/ID and HHE on the one hand and SH, SU, or WL on the other hand were, in most cases, low. Although some of the studies were based on relatively few records and the estimated genetic parameters had large standard errors, there was, with some exceptions, consistency among studies. Various studies evaluate the potential of various data soureces for use in breeding. The use of hoof trimming data is recommended for maximization of genetic gain, although auxiliary traits, such as locomotion score and some conformation traits, may be valuable for increasing the reliability of genetic evaluations. Routine genetic evaluation of direct claw health has been implemented in the Netherlands (2010); Denmark, Finland, and Sweden (joint Nordic evaluation; 2011); and Norway (2014), and other countries plan to implement evaluations in the near future.

Invited review: Opportunities for genetic improvement of metabolic diseases.

Metabolic disorders are disturbances to one or more of the metabolic processes in dairy cattle. Dysfunction of any of these processes is associated with the manifestation of metabolic diseases or disorders. In this review, data recording, incidences, genetic parameters, predictors, and status of genetic evaluations were examined for (1) ketosis, (2) displaced abomasum, (3) milk fever, and (4) tetany, as these are the most prevalent metabolic diseases where published genetic parameters are available. The reported incidences of clinical cases of metabolic disorders are generally low (less than 10% of cows are recorded as having a metabolic disease per herd per year or parity/lactation). Heritability estimates are also low and are typically less than 5%. Genetic correlations between metabolic traits are mainly positive, indicating that selection to improve one of these diseases is likely to have a positive effect on the others. Furthermore, there may also be opportunities to select for general disease resistance in terms of metabolic stability. Although there is inconsistency in published genetic correlation estimates between milk yield and metabolic traits, selection for milk yield may be expected to lead to a deterioration in metabolic disorders. Under-recording and difficulty in diagnosing subclinical cases are among the reasons why interest is growing in using easily measurable predictors of metabolic diseases, either recorded on-farm by using sensors and milk tests or off-farm using data collected from routine milk recording. Some countries have already initiated genetic evaluations of metabolic disease traits and currently most of these use clinical observations of disease. However, there are opportunities to use clinical diseases in addition to predictor traits and genomic information to strengthen genetic evaluations for metabolic health in the future.

Foot and leg conformation traits have a small effect on genomic predictions of claw disorders in Norwegian Red cows.

The aim of this study was to evaluate whether the predictive correlation of genomic breeding values (GEBV) for claw disorders increased by including genetically correlated traits as additional information in the analyses. Predictive correlations of GEBV for claw disorders were calculated based on claw disorders only and by analyzing claw disorders together with genetically correlated foot and leg conformation traits. The claw disorders analyzed were corkscrew claw (CSC); infectious claw disorder, including dermatitis, heel horn erosion, and interdigital phlegmon; and laminitis-related claw disorder, including sole ulcer, white line disorder, and hemorrhage of sole and white line. The foot and leg conformation traits included were hoof quality, foot angle, rear leg rear view new, and rear leg rear view old. The data consisted of 183,728 daughters with claw health records and 421,319 daughters with foot and leg conformation scores. A 25K/54K single nucleotide polymorphism (SNP) data set containing 48,249 SNP was available for the analyses. The number of genotyped sires with daughter information in the analyses was 1,093 including claw disorders and 3,111 including claw disorders and foot and leg conformation traits. Predictive correlations of GEBV for CSC, infectious claw disorder, and laminitis-related claw disorder were calculated from a 10-fold cross-validation and from an additional validation set including the youngest sires. Only sires having daughters with claw health records were in the validation sets, thus increasing the reference population when adding foot and leg conformation traits. The results showed marginal improvement in the predictive correlation of GEBV for CSC when including hoof quality and foot angle, both in 10-fold cross-validation (from 0.35 to 0.37) and in the validation including the youngest sires (from 0.38 to 0.49). For infectious claw disorder and laminitis-related claw disorder, including foot and leg conformation traits had no effect on the predictive correlation of GEBV. Claw disorders are novel traits with a limited amount of historical data and, therefore, a small reference population. Increasing the reference population by including sires with daughter information on foot and leg conformation traits had small effect on the predictive correlation of GEBV. However, the small increase in predictive correlation of GEBV for CSC shows a possible gain when including moderate to high genetically correlated traits.

Invited review: overview of new traits and phenotyping strategies in dairy cattle with a focus on functional traits.

For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in genetic merit for health and fitness have been observed. Herd management has been challenged to compensate for these effects and to balance fertility, udder health and metabolic diseases against increased production to maximize profit without compromising welfare. Functional traits, such as direct information on cow health, have also become more important because of growing concern about animal well-being and consumer demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasingly important because of the growing competition for high-quality, plant-based sources of energy and protein. Disruptions to global environments because of climate change may encourage yet more emphasis on these traits. To be successful, it is vital that there be a balance between the effort required for data recording and subsequent benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure good data quality. To keep labour costs reasonable, existing data sources should be used as much as possible. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the use of mid-infrared spectroscopy to measure milk have shown considerable promise, and may provide cost-effective alternative phenotypes for difficult or expensive-to-measure traits, such as feed efficiency. There are other valuable data sources in countries that have compulsory documentation of veterinary treatments and drug use. Additional sources of data outside of the farm include, for example, slaughter houses (meat composition and quality) and veterinary labs (specific pathogens, viral loads). At the farm level, many data are available from automated and semi-automated milking and management systems. Electronic devices measuring physiological status or activity parameters can be used to predict events such as oestrus, and also behavioural traits. Challenges concerning the predictive biology of indicator traits or standardization need to be solved. To develop effective selection programmes for new traits, the development of large databases is necessary so that high-reliability breeding values can be estimated. For expensive-to-record traits, extensive phenotyping in combination with genotyping of females is a possibility.

Effect of dams' parity and age on daughters' milk yield in Norwegian Red cows.

The effect of age and parity of dams on their daughters' milk yield is not well known. Lactation data from 276,000 cows were extracted from the Norwegian Dairy Herd Recording System and analyzed using a linear animal model to estimate effects of parity and age within parity of dam. The 305-d milk yield of daughters decreased as parity of dam increased. Daughters of first-parity dams produced 149 kg more milk than did daughters of seventh-parity dams. We also observed an effect of age of dam within parity on 305-d milk yield of daughters in first lactation. Dams that were young at first calving gave birth to daughters with a higher milk yield compared with older dams within the same parity. The effect of age within parity of dam was highest for second-parity dams. Extensive use of heifers would have a systematic effect, and age and parity of dam should be included in the model when planning a future strategy.

Genomic predictions based on a joint reference population for the Nordic Red cattle breeds.

The main aim of this study was to compare accuracies of imputation and genomic predictions based on single and joint reference populations for Norwegian Red (NRF) and a composite breed (DFS) consisting of Danish Red, Finnish Ayrshire, and Swedish Red. The single nucleotide polymorphism (SNP) data for NRF consisted of 2 data sets: one including 25,000 markers (NRF25K) and the other including 50,000 markers (NRF50K). The NRF25K data set had 2,572 bulls, and the NRF50K data set had 1,128 bulls. Four hundred forty-two bulls were genotyped in both data sets (double-genotyped bulls). The DFS data set (DSF50K) included 50,000 markers of 13,472 individuals, of which around 4,700 were progeny-tested bulls. The NRF25K data set was imputed to 50,000 density using the software Beagle. The average error rate for the imputation of NRF25K decreased slightly from 0.023 to 0.021, and the correlation between observed and imputed genotypes changed from 0.935 to 0.936 when comparing the NRF50K reference and the NRF50K-DFS50K joint reference imputations. A genomic BLUP (GBLUP) model and a Bayesian 4-component mixture model were used to predict genomic breeding values for the NRF and DFS bulls based on the single and joint NRF and DFS reference populations. In the multiple population predictions, accuracies of genomic breeding values increased for the 3 production traits (milk, fat, and protein yields) for both NRF and DFS. Accuracies increased by 6 and 1.3 percentage points, on average, for the NRF and DFS bulls, respectively, using the GBLUP model, and by 9.3 and 1.3 percentage points, on average, using the Bayesian 4-component mixture model. However, accuracies for health or reproduction traits did not increase from the multiple population predictions. Among the 3 DFS populations, Swedish Red gained most in accuracies from the multiple population predictions, presumably because Swedish Red has a closer genetic relationship with NRF than Danish Red and Finnish Ayrshire. The Bayesian 4-component mixture model performed better than the GBLUP model for most production traits for both NRF and DFS, whereas no advantage was found for health or reproduction traits. In general, combining NRF and DFS reference populations was useful in genomic predictions for both the NRF and DFS bulls.

Genetic correlations between claw health and feet and leg conformation in Norwegian Red cows.

The aim of this study was to estimate genetic correlations between claw disorders and feet and leg conformation traits in Norwegian Red cows. A total of 188,928 cows with claw health status recorded at claw trimming from 2004 to September 2013 and 210,789 first-lactation cows with feet and leg conformation scores from 2001 to September 2013 were included in the analyses. Traits describing claw health were corkscrew claw, infectious claw disorders (dermatitis, heel horn erosion, and interdigital phlegmon), and laminitis-related claw disorders (sole ulcer, white line disorder, and hemorrhage of sole and white line). The feet and leg conformation traits were rear leg rear view (new and old definition), rear leg side view, foot angle, and hoof quality. Feet and leg conformation traits were scored linearly from 1 to 9, with optimum scores depending on the trait. Claw disorders were defined as binary (0/1) traits for each lactation. Threshold sire models were used to model claw disorders, whereas the feet and leg conformation traits were described by linear sire models. Three multivariate analyses were performed, each including the 5 feet and leg conformation traits and 1 of the 3 claw disorders at a time. Posterior means of heritability of liability of claw disorders ranged from 0.10 to 0.20 and heritabilities of feet and leg conformation traits ranged from 0.04 to 0.11. Posterior standard deviation of heritability was ≤0.01 for all traits. Genetic correlations between claw disorders and feet and leg conformation traits were all low or moderate, except between corkscrew claw and hoof quality (-0.86), which are supposed to measure the same trait. The genetic correlations between rear leg rear view (new) and infectious claw disorders (-0.20) and laminitis-related claw disorders (0.26), and between hoof quality and laminitis-related claw disorders (-0.33) were moderate. Eight of the 15 genetic correlations between claw disorders and feet and leg conformation traits had 0 included in the 95% highest posterior density interval. These results imply that selection for feet and leg conformation is not an efficient approach to genetically improve claw health in Norwegian Red cattle.

Genetic analyses of claw health in Norwegian Red cows.

The aim of this study was genetic analyses of claw health in Norwegian Red. Claw health status at claw trimming has, since 2004, been recorded in the Norwegian Dairy Herd Recording System. The claw trimmer records whether the cow has normal (healthy) claws or if one or more claw disorders are present. Nine defined claw disorders were recorded: corkscrew claw (CSC), heel horn erosion (HH), dermatitis (DE), sole ulcer (SU), white line disorder (WLD), hemorrhage of sole and white line (HSW), interdigital phlegmon (IDP), lameness (LAME), and acute trauma (AT). Data from 2004 to 2011, with a total of 204,892 claw health records, were analyzed. The disorders were defined as binary traits with 1 record per cow per lactation. Further, 3 groups of claw disorders were analyzed: infectious claw disorders (INFEC, containing HH, DE, and IDP); laminitis-related claw disorders (LAMIN, containing SU, WLD, and HSW); and overall claw disorder. The 9 single traits and the 3 groups were analyzed using univariate threshold sire models. Multivariate threshold models were performed for the 5 most frequent single traits (CSC, HH, DE, SU, and WLD) and for CSC together with the grouped traits INFEC and LAMIN. Posterior mean of heritability of liability ranged from 0.04 to 0.23, where CSC had the highest heritability. The posterior standard deviations of heritability were low, between 0.01 and 0.03, except for IDP (0.06). Heritability of liability to INFEC and LAMIN were both 0.11 and for overall claw disorders, the heritability was 0.13. Posterior means of the genetic correlation among the 5 claw disorders varied between 0.02 and 0.79, and the genetic correlations between DE and HH (0.65) and between WLD and SU (0.79) were highest. Genetic correlation between INFEC and CSC was close to zero (0.06), between LAMIN and CSC it was 0.31, and between LAMIN and INFEC it was 0.24. The results show that claw disorders are sufficiently heritable for genetic evaluation and inclusion in the breeding scheme. At present, data are scarce with few recorded daughters per sire. Claw trimming records from more herds would therefore be beneficial for routine genetic evaluation of claw health.