Economic weights of somatic cell score in dairy sheep

The economic weights for somatic cell score (SCS) have been calculated using profit functions. Economic data were collected in the Latxa breed. Three aspects have been considered: bulk tank milk payment, veterinary treatments due to high SCS, and culling. All of them are non-linear profit functions. Milk payment is based on the sum of the log-normal distributions of somatic cell count, and veterinary treatments on the probability of subclinical mastitis, which is inferred when individual SCS surpass some threshold. Both functions lead to non-standard distributions. The derivatives of the profit function were computed numerically. Culling was computed by assuming that a conceptual trait culled by mastitis (CBM) is genetically correlated to SCS. The economic weight considers the increase in the breeding value of CBM correlated to an increase in the breeding value of SCS, assuming genetic correlations ranging from 0 to 0.9. The relevance of the economic weights for selection purposes was checked by the estimation of genetic gains for milk yield and SCS under several scenarios of genetic parameters and economic weights. The overall economic weights for SCS range from − 2.6 to − 9.5 € per point of SCS, with an average of − 4 € per point of SCS, depending on the expected average SCS of the flock. The economic weight is higher around the thresholds for payment policies. Economic weights did not change greatly with other assumptions. The estimated genetic gains with economic weights of 0.83 € per l of milk yield and − 4 € per point of SCS, assuming a genetic correlation of − 0.30, were 3.85 l and − 0.031 SCS per year, with an associated increase in profit of 3.32 €. This represents a very small increase in profit (about 1%) relative to selecting only for milk yield. Other situations (increased economic weights, different genetic correlations) produced similar genetic gains and changes in profit. A desired-gains index reduced the increase in profit by 3%, although it could be greater depending on the genetic parameters. It is concluded that the inclusion of SCS in dairy sheep breeding programs is of low economic relevance and recommended only if recording is inexpensive or for animal welfare concerns.     

Estimation of economic values and financial losses associated with clinical mastitis and somatic cell score in Holstein dairy cattle

The objective of this study was to develop a method for calculating economic values of clinical mastitis (CM) and somatic cell score (SCS) for inclusion in a dairy cattle breeding goal in the context of a country where farm production and economic data are scarce. In order to calculate the costs and derive economic values for SCS, a new model, 'milk collection method', has been developed and was compared with the Meijering model with individual and average SCS distributions. For the population, estimated economic values using the milk collection method were 1.3 and 2.4 times higher than those of Meijering method with average and individual SCS, respectively. The milk collection method needs no assumptions about normality of the distribution of SCS and because of a lack of normality in Iranian data for SCS, the Meijering method resulted in economic values that were biased downwards. Failing to account for the fact that milk price penalties for SCS are applied at milk collection rather than individual cow level resulted in a further large downward bias in the economic value of SCS. When the distribution of data is unknown or difficult to approximate or when a transformation to normality is not straightforward, the milk collection method would be preferable. Inclusion of SCS and CM in the breeding goal for Iranian dairy cattle is justified based on these results. The model to calculate mastitis costs proposed here could be used to estimate economic values for CM in other developing countries where farm production and economic data are generally poor.     

Genetic parameters for resistance to trichostrongylid infection in dairy sheep

In sheep, the traditional chemical control of gastrointestinal nematode (GIN) parasites with anthelmintics has led to the widespread development of anthelmintic resistance. The selection of sheep with enhanced resistance to GIN parasites has been suggested as an alternative strategy to develop sustainable control of parasite infections. Most of the estimations of the genetic parameters for sheep resistance to GIN parasites have been obtained from young animals belonging to meat- and/or wool-specialised breeds. We present here the estimated genetic parameters for four parasite resistance traits studied in a commercial population of adult Spanish Churra dairy ewes. These involved two faecal egg counts (FECs) (LFEC0 and LFEC1) and two serum indicator traits, the anti-Teladorsagia circumcincta fourth stage larvae IgA (IgA) and the pepsinogen (Peps) levels. In addition, this study has allowed us to identify the environmental factors influencing parasite resistance in naturally infected Spanish Churra sheep and to quantify the genetic component of this complex phenotype. The heritabilities estimated for the two FECs analysed (0.12 for LFEC0 and 0.09 for LFEC1) were lower than those obtained for the examined serum indicators (0.19 for IgA and 0.21 for Peps). The genetic correlations between the traits ranged from 0.43 (Peps-IgA) to 0.82 (LFEC0-LFEC1) and were higher than their phenotypic counterparts, which ranged between 0.07 and 0.10. The heritabilities estimated for the studied traits were lower than previously reported in lambs. This may be due to the differences in the immune mechanisms controlling the infection in young (antibody reactions) and adult (hypersensitivity reactions) animals/sheep. In summary, this study demonstrates the presence of heritable variation in parasite resistance indicator traits in the Churra population studied, which suggests that genetic improvement is feasible for this complex trait in this population. However, further studies in which the experimental variables are controlled as much as possible are needed to identify the best trait that could be measured routinely in adult sheep as an indicator of parasite resistance.     

The effect of out-wintering pad design on dirtiness score, somatic cell score and mastitis incidence in dairy cows

This study aimed to compare three woodchip out-wintering pad (OWP) designs, and indoor cubicle housing with regard to cow dirtiness scores during the winter housing period, and udder health during both the winter period and the following lactation, for spring-calving dairy cows. The treatments were: an uncovered (UP) and covered (CP) OWP with a concrete feed apron; an uncovered OWP with self-feed silage pit provided directly on the woodchips (SP); and indoor cubicle housing (IC). Data were compared during 2 years: year 1 was a case study while year 2 was an experimental study. In year 1, treatments were UP (space allowance = 12 m2/cow), CP (6 m2/cow) and IC. In year 2, all three OWP designs (12 m2/cow) were compared with IC. Animals were assigned to treatments at the end of lactation in the autumn, and remained there while dry until calving the following spring. Subsequently, all cows were at pasture during lactation. Outcome measures for analysis were cow dirtiness score, somatic cell score (SCS) and incidence of clinical mastitis during the dry period and during lactation. Quarter milk samples were also taken at drying off, calving and 3 weeks post partum both years, and at approximately 113 days in milk in year 2. Samples were analysed for presence of mastitis-causing agents and SCS was determined. Sub-clinical mastitis was diagnosed when cows had an SCS greater than 200 000, or California mastitis test greater than 1 in at least one quarter. In year 1, cows in CP were dirtier than cows in the other two treatments. These animals also had the highest SCS during lactation and tended to have more mastitis-causing agents isolated from quarter milk samples. In year 2, when all cows were stocked at the same density, cows in the sheltered OWP (i.e. CP) had similar dirtiness scores to cows in cubicles and significantly lower dirtiness scores than cows in the unsheltered OWP designs, i.e. UP and SP. However, there were no effects on SCS or quarter sample results. Cleaning of OWP's stocked at 12 m2/cow reduced cow dirtiness scores. However, cleaning of CP in year 1 when cows were stocked at 6 m2/cow had no effect on dirtiness scores. We conclude that dry cows stocked at 12 m2/cow on OWP's are unlikely to have udder health problems in the subsequent lactation. Furthermore, provision of shelter and cleaning of the woodchips are management factors that help to keep cows clean on OWP's.     

Carryover of aflatoxin from feed to milk in dairy cows with low or high somatic cell counts

Aflatoxin M1 (AFM1) residues in milk are regulated in many parts of the world and can cost dairy farmers significantly due to lost milk sales. Additionally, due to the carcinogenicity of this compound contaminated milk can be a major public health concern. Thirty-four lactating dairy cows were utilised to investigate the relationship between somatic cell counts (SCC), milk yield and conversion of dietary aflatoxin B1 (AFB1) into milk AFM1 (carryover (CO)). The AFM1 in milk increased as soon as the first milking after animal ingestion with a pattern of increment up to the observed plateau (between 7th and 12th days of AFB1 ingestion). There was a significant (P < 0.01) effect of the milk yield whereas no effect could be attributed to the SCC levels or to the milk yield × SCC interaction. Similarly, the main effect of milk yield was also observed (P < 0.01) on the total amount of AFM1 excreted during the ingestion period. Although the plasma concentration of gamma-glutamyl transferase was significantly affected by aflatoxin administration, levels of this liver enzyme were within the normal range for lactating dairy cows. The current data suggest that milk yield is the major factor affecting the total excretion of AFM1 and that SCC as an indicator of mammary gland permeability was not related to an increase in AFM1 CO.     

Genetic analysis of milking ability in Lacaune dairy ewes

The milking ability of Lacaune ewes was characterised by derived traits of milk flow patterns, in an INRA experimental farm, from a divergent selection experiment in order to estimate the correlated effects of selection for protein and fat yields. The analysis of selected divergent line effects (involving 34 616 data and 1204 ewes) indicated an indirect improvement of milking traits (+17% for maximum milk flow and -10% for latency time) with a 25% increase in milk yield. Genetic parameters were estimated by multi-trait analysis with an animal model, on 751 primiparous ewes. The heritabilities of the traits expressed on an annual basis were high, especially for maximum flow (0.54) and for latency time (0.55). The heritabilities were intermediate for average flow (0.30), time at maximum flow (0.42) and phase of increasing flow (0.43), and low for the phase of decreasing flow (0.16) and the plateau of high flow (0.07). When considering test-day data, the heritabilities of maximum flow and latency time remained intermediate and stable throughout the lactation. Genetic correlations between milk yield and milking traits were all favourable, but latency time was less milk yield dependent (-0.22) than maximum flow (+0.46). It is concluded that the current dairy ewe selection based on milk solid yield is not antagonistic to milking ability.     

Environmental and genetic variation factors of artificial insemination success in French dairy sheep

Artificial inseminations (n = 678 168) recorded during 5 years in five French artificial insemination (AI) centres (2 'Lacaune', 1 'Manech tête rousse', 1 'Manech tête noire' and 1 'Basco béarnaise') were analysed to determine environmental and genetic factors affecting the insemination results. Analyses within centre-breed were performed using a linear model, which jointly estimates male and female fertility. This model combined four categories of data: the environmental effects related to the female, those related to the male, the non-sex-specific effects and finally the pedigree data of these males and females. After selection, the environmental female effects considered were age, synchronisation (0/1) on the previous year, total number of synchronisations during the female reproductive life, time interval between previous lambing and insemination, already dry or still lactating (0/1) when inseminated, and milk quantity produced during the previous year expressed as quartiles intra herd * year. The environmental male effects were motility and concentration of the semen. The non-sex-specific effects were the inseminator, the interaction herd * year nested within the inseminator, considered as random effects and the interaction year * season considered as a fixed effect. The main variation factors of AI success were relative to non-sex-specific effects and to female effects. Heritability estimates varied from 0.001 to 0.005 for male fertility and from 0.040 to 0.078 for female fertility. Repeatability estimates varied from 0.007 to 0.015 for male fertility and from 0.104 to 0.136 for female fertility. These parameters indicate that genetic improvement of AI results through a classical polygenic selection would be difficult. Moreover, in spite of the large quantity of variation factors fitted by the joint model, a very large residual variance remained unexplained.     

New mastitis phenotypes suitable for genomic selection in meat sheep and their genetic relationships with udder conformation and lamb live weights

Mastitis can prove expensive in sheep reared for meat production due to costs associated with treatment methods, poor lamb growth and premature culling of ewes. The most commonly used method to detect mastitis, in dairy systems, is somatic cell counts. However, in many meat-producing sheep flocks ewes are not routinely handled, thus regular milk sampling is not always possible. It is, therefore, worthwhile to investigate alternative phenotypes, such as those associated with udder conformation and methods of evaluating somatic cell counts in the milk, such as the California Mastitis Test. The main objectives of this study were therefore: (a) to estimate genetic parameters of traits relating to mastitis and udder conformation in a meat sheep breed; (b) estimate the level of association between somatic cell counts and the California Mastitis Test and (c) assess the relationships between mastitis and both udder conformation and lamb live weights. Data were collected from Texel ewes based on 29 flocks, throughout the UK, during 2015 and 2016. The ewes were scored twice each year, at mid- and late-lactation. Eight different conformation traits, relating to udder and teat characteristics, and milk samples were recorded. The data set comprised of data available for 2957 ewes. The pedigree file used contained sire and dam information for 31 775 individuals. The animal models used fitted relevant fixed and random effects. Heritability estimates for traits relating to mastitis (somatic cell score and the California Mastitis Test), ranged from 0.08 to 0.11 and 0.07 to 0.11, respectively. High genetic correlations were observed between somatic cell score and the California Mastitis Test (0.76 to 0.98), indicating the California Mastitis Test to be worthwhile for assessing infection levels, particularly at mid-lactation. The strongest correlations observed between the mastitis traits and the udder conformation traits were associated with udder depth (0.61 to 0.75) also at mid-lactation. Negative phenotypic correlations were estimated between mastitis and the weight of lamb reared by the ewe (−0.15 to −0.23), suggesting that lamb weights fell as infection levels rose. Genetic correlations were not significantly different from zero. Reducing mastitis will lead to improvements in flock productivity and the health and welfare of the animals. It will also improve the efficiency of production and the resilience to disease challenge. The economic benefits, therefore, of these results combined could be substantial not only in this breed but also in the overall meat sheep industry.     

Gelsolin expression in sheep milk somatic cells during lactation

The identification of genes involved in phenotypes related to milk quality is important for both economic and health aspects in livestock production. The aim of this study was to assess the level of gelsolin gene expression in two breeds of dairy sheep – Sarda and Gentile – with pronounced differences in quantitative and qualitative milk traits. Gelsolin, a type of actin-modulating proteins is involved in the processes of actin remodeling during cell growth and apoptosis; therefore a role of this protein in mammary changes during lactation was here hypothesized. Individual milk samples were collected three times during lactation from 26 ewes of the two breeds. The differential gene expression of gelsolin in the two breeds and the three lactation times was estimated by quantitative PCR on RNA extracted from milk somatic cells. Correlations of gelsolin gene expression with milk yield and quality and days of lactation were also estimated. The results showed that gelsolin gene expression was significantly higher in the Sarda compared to the Gentile at each lactation stage, in agreement with the longer lactation duration and the higher daily milk yield of the first breed. Significant correlations of gelsolin gene expression were found with milk fat content in Sarda breed (−0.46, P<0.05). Gelsolin expression analysis confirmed the link between gelsolin gene function and milk fat content of sheep.     

Economic consequences of mastitis and withdrawal of milk with high somatic cell count in Swedish dairy herds

The main aim was to assess the impact of mastitis on technical and economic results of a dairy herd under current Swedish farming conditions. The second aim was to investigate the effects obtained by withdrawing milk with high somatic cell count (SCC). A dynamic and stochastic simulation model, SimHerd, was used to study the effects of mastitis in a herd with 150 cows. Results given the initial incidence of mastitis (32 and 33 clinical and subclinical cases per 100 cow-years, respectively) were studied, together with the consequences of reducing or increasing the incidence of mastitis by 50%, modelling no clinical mastitis (CM) while keeping the incidence of subclinical mastitis (SCM) constant and vice versa. Six different strategies to withdraw milk with high SCC were compared. The decision to withdraw milk was based on herd-level information in three scenarios: withdrawal was initiated when the predicted bulk tank SCC exceeded 220 000, 200 000 or 180 000 cells/ml, and on cow-level information in three scenarios: withdrawal was initiated when the predicted SCC in an individual cow's milk exceeded 1 000 000, 750 000 or 500 000 cells/ml. The accuracy with which SCC was measured and predicted was assumed to affect the profitability of withdrawing milk with high SCC and this was investigated by applying high, low or no uncertainty to true SCC. The yearly avoidable cost of mastitis was estimated at €8235, assuming that the initial incidence of mastitis could be reduced by 50%. This cost corresponded to 5% of the herd net return given the initial incidence of mastitis. Expressed per cow-year, the avoidable cost of mastitis was €55. The costs per case of CM and SCM were estimated at €278 and €60, respectively. Withdrawing milk with high SCC was never profitable because this generated a substantial amount of milk withdrawal that was not offset by a sufficient increase in the average price per delivered kg milk. It had the most negative impact on net return when high incidence of mastitis was simulated. Withdrawing milk with high SCC based on low-uncertainty information reduced the amount of withdrawn milk and thus resulted in less negative effect on net return. It was concluded that the current milk-pricing system makes it more profitable for farmers to sell a larger amount of milk with higher SCC than to withdraw milk with high SCC to obtain payment premiums, at least in herds with mastitis incidences within the simulated ranges.     

Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11

Quantitative trait loci (QTL) affecting clinical mastitis (CM) and somatic cell score (SCS) were mapped on bovine chromosome 11. The mapping population consisted of 14 grandsire families belonging to three Nordic red cattle breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB) and Danish Red. The families had previously been shown to segregate for udder health QTL. A total of 524 progeny tested bulls were included in the analysis. A linkage map including 33 microsatellite and five SNP markers was constructed. We performed combined linkage disequilibrium and linkage analysis (LDLA) using the whole data set. Further analyses were performed for FA and SRB separately to study the origin of the identified QTL/haplotype and to examine if it was common in both populations. Finally, different two-trait models were fitted. These postulated either a pleiotropic QTL affecting both traits; two linked QTL, each affecting one trait; or one QTL affecting a single trait. A QTL affecting CM was fine-mapped. In FA, a haplotype having a strong association with a high negative effect on mastitis resistance was identified. The mapping precision of an earlier detected SCS-QTL was not improved by the LDLA analysis because of lack of linkage disequilibrium between the markers used and the QTL in the region.     

Variation in blood serum proteins and association with somatic cell count in dairy cattle from multi-breed herds

Blood serum proteins are significant indicators of animal health. Nevertheless, several factors should be considered to appropriately interpret their concentrations in blood. Therefore, the objectives of this study were (1) to assess the effect of herd productivity, breed, age and stage of lactation on serum proteins and (2) to investigate association between serum proteins and somatic cell count (SCC) in dairy cattle. Milk and blood samples were collected from 1508 cows of six different breeds (Holstein Friesian, Brown Swiss, Jersey, Simmental, Rendena and Alpine Grey) that were housed in 41 multi-breed herds. Milk samples were analyzed for composition and SCC, while blood samples were analyzed for serum proteins (i.e. total protein, albumin, globulin and albumin-to-globulin ratio (A : G)). Herds were classified as low or high production, according to the cow’s average daily milk energy yield adjusted for breed, days in milk (DIM) and parity. Data were analyzed using a linear mixed model that included the fixed effects of DIM, parity, SCS, breed, herd productivity and the random effect of the Herd-test date within productivity level. Cows in high producing herds (characterized also by greater use of concentrates in the diet) had greater serum albumin concentrations. Breed differences were reported for all traits, highlighting a possible genetic mechanism. The specialized breed Jersey and the two dual-purpose local breeds (Alpine Grey and Rendena) had the lowest globulin concentration and greatest A : G. Changes in serum proteins were observed through lactation. Total protein reached the highest concentration during the 4th month of lactation. Blood albumin increased with DIM following a quadratic pattern, while globulin decreased linearly. As a consequence, A : G increased linearly during lactation. Older cows had greater total protein and globulin concentrations, while albumin concentration seemed to be not particularly affected by age. A linear relationship between serum proteins and SCS was observed. High milk SCS was associated with greater total protein and globulin concentrations in blood. The rise in globulin concentration, together with a decrease in albumin concentrations, resulted in a decline in A : G as SCS of milk increased. In conclusion, such non-genetic factors must be considered to appropriately interpret serum proteins as potential animal welfare indicator and their evaluation represents an important first-step for future analysis based on the integration of metabolomics, genetic and genomic information for improving the robustness of dairy cows.     

Fine-mapping QTL for mastitis resistance on BTA9 in three Nordic red cattle breeds

A QTL affecting clinical mastitis and/or somatic cell score (SCS) has been reported previously on chromosome 9 from studies in 16 families from the Swedish Red and White (SRB), Finnish Ayrshire (FA) and Danish Red (DR) breeds. In order to refine the QTL location, 67 markers were genotyped over the whole chromosome in the 16 original families and 18 additional half-sib families. This enabled linkage disequilibrium information to be used in the analysis. Data were analysed by an approach that combines information from linkage and linkage disequilibrium, which allowed the QTL affecting clinical mastitis to be mapped to a small interval (<1 cM) between the markers BM4208 and INRA084 . This QTL showed a pleiotropic effect on SCS in the DR and SRB breeds. Haplotypes associated with variations in mastitis resistance were identified. The haplotypes were predictive in the general population and can be used in marker-assisted selection. Pleiotropic effects of the mastitis QTL were studied for three milk production traits and eight udder conformation traits. This QTL was also associated with yield traits in DR but not in FA or SRB. No QTL were found for udder conformation traits on chromosome 9.     

Relationships among somatic cell count, California mastitis test, impedance and bacteriological status of milk in goats and sheep in early lactation

The objectives of this trial were to evaluate and compare the test characteristics of a number of indirect tests of bacteriological status of the milk from goats and sheep and to assess the affect of varying levels of prevalence of infection on the performance of those tests.The somatic cell count, California mastitis test (CMT) score, electrical impedance and the bacteriological status of 220 and 262 milk samples from the glands of lactating dairy goats and sheep, respectively, were determined. The sensitivity and specificity of indirect tests in predicting the bacteriological status were compared by analyzing the areas under the receiver operating characteristic curve and calculating the likelihood ratio at various cut-off values.Bacteria were isolated from 17.7 and 4.6% of glands from goats and sheep, respectively. Somatic cell count was a better predictor of bacteriological status than either the CMT score or impedance in both goats and sheep. However, knowledge of the CMT score in both sheep and goats and the impedance in goats increases the likelihood of predicting the presence of a bacterial pathogen compared to no testing at all (P<0.05). Knowledge of the age and days postpartum of the animals at the time of testing did not increase the probability that infection status could be predicted. Variation in cut-off levels to predict infection status reported in the literature may be due to variation in the prevalence of infection in the populations studied. Use of likelihood ratio allows comparison of tests over a range of prevalence’s as likelihood ratios are independent of prevalence. The prevalence of infection within a herd should be considered when selecting a cut-off value for indirect testing for the presence of bacteria in milk of small ruminants.     

A hidden Markov model to predict early mastitis from test-day somatic cell scores

In many countries, high somatic cell scores (SCS) in milk are used as an indicator for mastitis because they are collected on a routine basis. However, individual test-day SCS are not very accurate in identifying infected cows. Mathematical models may improve the accuracy of the biological marker by making better use of the information contained in the available data. Here, a simple hidden Markov model (HMM) is described mathematically and applied to SCS recorded monthly on cows with or without clinical mastitis to evaluate its accuracy in estimating parameters (mean, variance and transition probabilities) under healthy or diseased states. The SCS means were estimated at 1.96 (s.d. = 0.16) and 4.73 (s.d. = 0.71) for the hidden healthy and infected states, and the common variance at 0.83 (s.d. = 0.11). The probability of remaining uninfected, recovering from infection, getting newly infected and remaining infected between consecutive test days was estimated at 78.84%, 60.49%, 11.70% and 15%, respectively. Three different health-related states were compared: clinical stages observed by farmers, subclinical cases defined for somatic cell counts below or above 250 000 cells/ml and infected stages obtained from the HMM. The results showed that HMM identifies infected cows before the appearance of clinical and subclinical signs, which may critically improve the power of the studies on the genetic determinants of SCS and reduce biases in predicting breeding values for SCS.     

Evaluating somatic cell scores with a Bayesian Gaussian linear state-space model

Because accurate characterization of health state is important for managing dairy herds, we propose to validate the use of a linear state-space model (LSSM) for evaluating monthly somatic cell scores (SCSs). To do so, we retrieved SCS from a dairy database and collected reports on clinical mastitis collected in 20 farms, during the period from January 2008 to December 2011 in the Walloon region of Belgium. The dependent variable was the SCS, and the independent variables were the number of days from calving, year of calving and parity. The LSSM also incorporated an error-free underlying variable that described the trend across time as a function of previous clinical and subclinical status. We computed the mean sum of squared differences between observed SCS and median values of the posterior SCS distribution and constructed the receiver operating characteristic (ROC) curve for SCS thresholds going from 0 to 6. Our results show SCS estimates are close to observed SCS and area under the ROC curve is higher than 90%. We discuss the meaning of the parameters in light of our current knowledge of the disease and propose methods to incorporate, in LSSM, this knowledge often expressed in the form of ordinary differential equations.     

Genetic parameters for pathogen-specific mastitis resistance in Danish Holstein Cattle

The objective of this study was to estimate heritabilities for and genetic correlations among different pathogen-specific mastitis traits. The traits were unspecific mastitis, which is all mastitis treatments regardless of the causative pathogen as well as mastitis caused by Streptococcus dysgalactiae, Escherichia coli, coagulase-negative staphylococci (CNS), Staphylococcus aureus and Streptococcus uberis. Also groups of pathogens were investigated, Gram-negative v. Gram-positive and contagious v. environmental pathogens. Data from 168 158 Danish Holstein cows calving first time between 1998 and 2006 were used in the analyses. Variances and covariances were estimated using uni- and bivariate threshold models via Gibbs sampling. Posterior means of heritabilities of pathogen-specific mastitis were lower than the heritability of unspecific mastitis, ranging from 0.035 to 0.076 for S. aureus and S. uberis, respectively. The heritabilities of groups of pathogen ranged from 0.053 to 0.087. Genetic correlations among the pathogen-specific mastitis traits ranged from 0.45 to 0.77. These estimates tended to be lowest for bacteria eliciting very different immune responses, which can be considered as the overall pleiotropic effect of genes affecting resistance to a specific pathogen, and highest for bacteria sharing characteristics regarding immune response. The genetic correlations between the groups of pathogens were high, 0.73 and 0.83. Results showed that the pathogen-specific traits used in this study should be considered as different traits. Genetic evaluation for pathogen-specific mastitis resistance may be beneficial despite lower heritabilities than unspecific mastitis because a pathogen-specific mastitis trait is a direct measure of an udder infection, and because the cost of a mastitis case caused by different pathogens has been shown to differ greatly. Sampling bias may be present because there were not pathogen information on all mastitis treatments and because some farms do not record pathogen information. Therefore, improved recording of pathogen information and mastitis treatments in general is critical for a successful genetic evaluation of udder health. Also, economic values have to be specified for each pathogen-specific trait separately.     

Nitric oxide concentrations in mammary quarters during heifer mastitis

The aim of this study was to evaluate nitric oxide (NOx) concentration in infected and non-infected mammary quarters of dairy heifers before and after calving. The relationship between bacterial species and NOx concentrations, as well as correlation between NOx concentrations and postpartum somatic cell count (SCC), was assessed. Coagulase-negative staphylococci, Staphylococcus aureus and Escherichia coli were the bacteria commonly isolated during the pre- and postpartum period. Infected quarters had greater NOx concentrations than non-infected quarters before (30.81 v. 22.83 μM/ml, P < 0.05) and after (9.56 v. 5.77 μM/ml, P < 0.0001) calving. It was determined that the interaction between sampling period and infectious status had no effect on NOx concentration (P < 0.16). Infected quarters had greater SCC (log₁₀) than healthy quarters (4.95 v. 4.39; P < 0.0001). NOx concentrations, however, did not correlate with SCC (r = 0.02). In summary, changes in NOx concentration were mainly dependent on the infectious status of the quarters with variations among the bacterial species (P < 0.05).     

Random regression models for genetic evaluation of clinical mastitis in dairy cattle

A genetic analysis of longitudinal binary clinical mastitis (CM) data recorded on about 90 000 first-lactation Swedish Holstein cows was carried out using linear random regression models (RRM). This method for genetic evaluation of CM has theoretical advantages compared to the method of linear cross-sectional models (CSM), which is currently being used. The aim of this study was to investigate the feasibility and suitability of estimating genetic parameters and predicting breeding values for CM with a linear sire RRM. For validation purposes, the estimates and predictions from the RRM were compared to those from linear sire longitudinal multivariate models (LMVM) and CSM. For each cow, the period from 10 days before to 241 days after calving was divided into four 1-week intervals followed by eight 4-week intervals. Within each interval, presence or absence of CM was scored as '1' or '0'. The linear RRM used to explain the trajectory of CM over time included a set of explanatory variables plus a third-order Legendre polynomial function of time for the sire effect. The time-dependent heritabilities and genetic correlations from the chosen RRM corresponded fairly well with estimates obtained from the linear LMVM for the separate intervals. Some discrepancy between the two methods was observed, with the more unstable results being obtained from the linear LMVM. Both methods indicated clearly that CM was not genetically the same trait throughout lactation. The correlations between predicted sire breeding values from the RRM, summarized over different time periods, and from linear CSM were rather high. They were, however, less than unity (0.74 to 0.96), which indicated some re-ranking of sires. Sire curves based on the time-specific breeding values from the RRM illustrated differences in intercept and slope among the best and the worst sires. To conclude, a linear sire RRM seemed to work well for genetic evaluation purposes, but was sensitive for estimation of genetic parameters.     

Mapping economic trait loci for somatic cell score in Holstein cattle using microsatellite markers and selective genotyping

Marker-assisted selection (MAS) uses genetic marker genotypes to predict an animal's production potential and will provide additional selection information for progeny testing. With the discovery of highly polymorphic microsatellite markers, the tools now exist to begin the search for economic trait loci (ETL), which is the first step toward MAS. The objective of this study was to identify ETL for somatic cell score in an existing Holstein population. Using the granddaughter design, sons from seven grandsire families were genotyped with 20 autosomal microsatellites from five chromosomes (4, 8, 13, 17, 23), with an emphasis on chromosome 23, which is the location of the bovine major histocompatibility complex (BoLA). Selective genotyping was used to reduce the number of genotypes required, in which the 10 highest and 10 lowest sons from the phenotypic distribution curve were tested (140 sons in seven families). One marker (513), located near BoLA, showed evidence of an ETL in three of five polymorphic families. Additional sons were genotyped from the five families to estimate the effect and to compare selective and ‘complete’ genotyping. Both methods detected an ETL at marker 513, but in different families. This study provides evidence of the usefulness of microsatellite markers and the granddaughter design in the detection of ETL; however, additional markers need to be evaluated to determine the usefulness of selective genotyping. Based on the results from the 20 studied markers, the most likely position of a somatic cell score ETL lies near marker 513, located on chromosome 23.