Genetic analysis of somatic cell score in danish holsteins using a liability-normal mixture model

Mixture models are appealing for identifying hidden structures affecting somatic cell score (SCS) data, such as unrecorded cases of subclinical mastitis. Thus, liability-normal mixture (LNM) models were used for genetic analysis of SCS data, with the aim of predicting breeding values for such cases of mastitis. Here, putative mastitis statuses and breeding values for liability to putative mastitis were inferred solely from SCS observations. In total, there were 395,906 test-day records for SCS from 50,607 Danish Holstein cows. Four different statistical models were fitted: A) a classical (nonmixture) random regression model for test-day SCS; B1) an LNM test-day model assuming homogeneous (co)variance components for SCS from healthy (IMI-) and infected (IMI+) udders; B2) an LNM model identical to B1, but assuming heterogeneous residual variances for SCS from IMI- and IMI+ udders; and C) an LNM model assuming fully heterogeneous (co)variance components of SCS from IMI- and IMI+ udders. For the LNM models, parameters were estimated with Gibbs sampling. For model C, variance components for SCS were lower, and the corresponding heritabilities and repeatabilities were substantially greater for SCS from IMI- udders relative to SCS from IMI+ udders. Further, the genetic correlation between SCS of IMI- and SCS of IMI+ was 0.61, and heritability for liability to putative mastitis was 0.07. Models B2 and C allocated approximately 30% of SCS records to IMI+, but for model B1 this fraction was only 10%. The correlation between estimated breeding values for liability to putative mastitis based on the model (SCS for model A) and estimated breeding values for liability to clinical mastitis from the national evaluation was greatest for model B1, followed by models A, C, and B2. This may be explained by model B1 categorizing only the most extreme SCS observations as mastitic, and such cases of subclinical infections may be the most closely related to clinical (treated) mastitis.

Family association between immune parameters and resistance to Aeromonas hydrophila infection in the Indian major carp, Labeo rohita

Seven innate immune parameters were investigated in 64 full-sib families (the offspring of 64 sires and 45 dams) from two year-classes of farmed rohu carp (Labeo rohita). Survival rates were also available from Aeromonas hydrophila infection (aeromoniasis) recorded in controlled challenge tests on a different sample of individuals from the same families. Due to strong confounding between the animal additive genetic effect and the family effects (common environmental+non-additive genetic), reliable additive (co)variance components and hence heritabilities and genetic correlations could not be obtained for the investigated parameters. Therefore, estimates of the association of challenge test survival with the studied immune parameters were obtained as product moment correlations between family least square means. These correlations revealed statistically significant (p<0.05) negative correlations of survival with bacterial agglutination titre (-0.48), serum haemolysin titre (-0.29) and haemagglutination titre (-0.34); and significant positive correlation with ceruloplasmin level (0.51). The correlations of survival to aeromoniasis with myeloperoxidase activity, superoxide production and lysozyme activity were found to be not significantly different from zero (p>0.05). Assuming that the negatively correlated candidate traits are not favourable as indirect selection criteria, the results suggest that ceruloplasmin level could potentially be a marker for resistance to aeromoniasis in rohu. The use of this immune parameter as an indirect selection criterion for increased resistance to aeromoniasis in rohu will, however, require that the parameter shows significant additive genetic variation and a significant genetic correlation with survival. Further studies are therefore needed to obtain a reliable heritability estimate for ceruloplasmin and its genetic correlation with survival from aeromoniasis.

Genotype by environment interaction for lamb weaning weight in two Norwegian sheep breeds1

Genotype x environment interaction (G x E) effects on live weaning weights of lambs were studied by using the 2 breeds Norwegian White sheep (NWS; heavy, long-tailed) and Spel sheep (Spel; lighter, short-tailed) as genetic groups (G). A total of 37,338 NWS lambs and 30,075 Spel lambs born from 1989 to 1999 on 40 farms that kept both breeds together were included in the analyses. Environment was characterized by farm x year (E). In a mixed linear model framework, significance of the random G x E effect and breed-specific environmental variances were tested by using a log-likelihood approach. Directions and magnitudes of the effect were described through variance component estimates. An across-genotype environmental correlation was also used. There was a significant G x E effect on lamb BW; significant breed differences were found for variance of flock x year effects, indicating different phenotypic plasticities with changing flock x year environments, with the NWS being more sensitive to environmental change. Further, the breed-specific residual variance was greater for NWS, indicating that the effects of environmental variation were larger for the weaning weights of the NWS breed within flock and year. Further, the correlation between flock x year effects for the 2 breeds was significantly different from unity (0.82 +/- 0.02), indicating that the common environment is "perceived" differently in the 2 breeds. The best environment for one breed is not necessarily best for the other breed, and vice versa. Solutions of flock x year effects may be used to describe how environmental characteristics such as climate and topography affect the production of different genotypes, and for clustering of environments, thus facilitating improvement of breeding programs and management schemes for domestic and wild ungulate populations.

A Method to Define Breeding Goals for Sustainable Dairy Cattle Production

The objective of this study was to present a method to define breeding goals for sustainable dairy cattle production by adding nonmarket values to market economic values for functional traits in the breeding goal. A nonmarket value can represent the value of improved animal welfare or societal influences for animal production. The nonmarket value for mastitis resistance, conception rate, and stillbirth were derived based on how much farmers or breeding companies were willing to lose in selection response for milk yield to improve functional traits. The desired response for milk yield corresponding to a given percent loss was obtained using desired gain indices. By allowing a 5% loss in the selection response for milk yield, the nonmarket value was found to be 40.4 euro for mastitis resistance, 16.1 euro for conception rate, and 9.7 euro for stillbirth. The nonmarket value increased proportionally with increasing loss in the selection response for milk yield, but the selection response was lower for conception rate than for mastitis resistance because of differences in market economic value and heritability. To increase the response for conception rate, the nonmarket value was also derived for 2 situations, in which the desired responses for milk yield, mastitis resistance, and conception rate were specified. The method can be used to define breeding goals for sustainable production and to increase the response for traits that are at critically low levels. When defining breeding goals for sustainable production, breeding organizations should predict the selection response based on market economic value and add non-market value for traits with unacceptable selection responses.

Genetic Associations Between Clinical Mastitis and Somatic Cell Score in Early First-Lactation Cows

The objectives of this study were to examine genetic associations between clinical mastitis and somatic cell score (SCS) in early first-lactation cows, to estimate genetic correlations between SCS of cows with and without clinical mastitis, and to compare genetic evaluations of sires based on SCS or clinical mastitis. Clinical mastitis records from 15 d before to 30 d after calving and first test-day SCS records (from 6 to 30 d after calving) from 499,878 first-lactation daughters of 2,043 sires were analyzed. Results from a bivariate linear sire model analysis of SCS in cows with and without clinical mastitis suggest that SCS is a heterogeneous trait. Heritability of SCS was 0.03 for mastitic cows and 0.08 for healthy cows, and the genetic correlation between the 2 traits was 0.78. The difference in rank between sire evaluations based on SCS of cows with and without clinical mastitis varied from -994 to 1,125, with mean 0. A bivariate analysis with a threshold-liability model for clinical mastitis and a linear Gaussian model for SCS indicated that heritability of liability to clinical mastitis is at least as large as that of SCS in early lactation. The mean (standard deviation) of the posterior distribution of heritability was 0.085 (0.006) for liability to clinical mastitis and 0.070 (0.003) for SCS. The posterior mean (standard deviation) of the genetic correlation between liability to clinical mastitis and SCS was 0.62 (0.03). A comparison of sire evaluations showed that genetic evaluation based on SCS was not able to identify the best sires for liability to clinical mastitis. The association between sire posterior means for liability to clinical mastitis and sire predicted transmitting ability for SCS was far from perfect.

Genetic Improvement in Mastitis Resistance: Comparison of Selection Criteria from Cross-Sectional and Random Regression Sire Models for Somatic Cell Score

Several selection criteria for reducing incidence of mastitis were developed from a random regression sire model for test-day somatic cell score (SCS). For comparison, sire transmitting abilities were also predicted based on a cross-sectional model for lactation mean SCS. Only first-crop daughters were used in genetic evaluation of SCS, and the different selection criteria were compared based on their correlation with incidence of clinical mastitis in second-crop daughters (measured as mean daughter deviations). Selection criteria were predicted based on both complete and reduced first-crop daughter groups (261 or 65 daughters per sire, respectively). For complete daughter groups, predicted transmitting abilities at around 30 d in milk showed the best predictive ability for incidence of clinical mastitis, closely followed by average predicted transmitting abilities over the entire lactation. Both of these criteria were derived from the random regression model. These selection criteria improved accuracy of selection by approximately 2% relative to a cross-sectional model. However, for reduced daughter groups, the cross-sectional model yielded increased predictive ability compared with the selection criteria based on the random regression model. This result may be explained by the cross-sectional model being more robust, i.e., less sensitive to precision of (co)variance components estimates and effects of data structure.

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

Genetic Analysis of Somatic Cell Score in Norwegian Cattle Using Random Regression Test-Day Models

The dataset used in this analysis contained a total of 341,736 test-day observations of somatic cell scores from 77,110 primiparous daughters of 1965 Norwegian Cattle sires. Initial analyses, using simple random regression models without genetic effects, indicated that use of homogeneous residual variance was appropriate. Further analyses were carried out by use of a repeatability model and 12 random regression sire models. Legendre polynomials of varying order were used to model both permanent environmental and sire effects, as did the Wilmink function, the Lidauer-Mäntysaari function, and the Ali-Schaeffer function. For all these models, heritability estimates were lowest at the beginning (0.05 to 0.07) and higher at the end (0.09 to 0.12) of lactation. Genetic correlations between somatic cell scores early and late in lactation were moderate to high (0.38 to 0.71), whereas genetic correlations for adjacent DIM were near unity. Models were compared based on likelihood ratio tests, Bayesian information criterion, Akaike information criterion, residual variance, and predictive ability. Based on prediction of randomly excluded observations, models with 4 coefficients for permanent environmental effect were preferred over simpler models. More highly parameterized models did not substantially increase predictive ability. Evaluation of the different model selection criteria indicated that a reduced order of fit for sire effects was desireable. Models with zeroth- or first-order of fit for sire effects and higher order of fit for permanent environmental effects probably underestimated sire variance. The chosen model had Legendre polynomials with 3 coefficients for sire, and 4 coefficients for permanent environmental effects. For this model, trajectories of sire variance and heritability were similar assuming either homogeneous or heterogeneous residual variance structure.

Genetic Improvement of Mastitis Resistance: Validation of Somatic Cell Score and Clinical Mastitis as Selection Criteria

Mean daughter deviations for clinical mastitis among second-crop daughters were regressed on predicted transmitting abilities for clinical mastitis and lactation mean somatic cell score in first-crop daughters to validate the predictive ability of these traits as selection criteria for reduced incidence of clinical mastitis. A total of 321 sires had 684,897 second-crop daughters, while predicted transmitting abilities were calculated for 2159 sires, based on 495,681 records of first-crop daughters. Predictive ability, as a measure of efficiency of selection, was 23 to 43% higher for clinical mastitis than for lactation mean somatic cell score. Compared to single-trait selection, predictive ability improved 8 to 13% from utilizing information on both traits. The relative weight that should be assigned to standardized predicted transmitting abilities from univariate genetic analyses were 60 to 67% for clinical mastitis and 33 to 40% for lactation mean somatic cell score. No significant nonlinear genetic relationship between the two traits was found.

Morbidity among self-employed farmers in Norway

A health survey among 923 self-employed Norwegian farmers was carried out in 1982 to investigate the state of non-hospital morbidity in the agricultural community. 85% of the nation-wide representative sample of active farmers answered the questionnaire. A disease was recorded, according to the International Classification of Diseases (ICD, 8th revision), when the farmer had been confined to bed/had reduced activity, or had consulted a medical practitioner, or used medication, all during the last 14 days. Congenital diseases were also recorded. The following findings were elicited: 56% of all morbidity came under the three headings cardiovascular diseases, musculoskeletal diseases, injuries; the incidence of cardiovascular diseases is rising in spite of the reduced average age of the agricultural population; within agriculture the following groups have the highest work-related morbidity: full-time farmers, grain-growing farmers, those farmers who have the greatest daily work load, and farmers who are physically exhausted at the end of the day.

Implant-tissue interface of endosseous dental implants in dogs. validity of clinical evaluation methods

Plaque and gingival bleeding were scored and probing, radiography, and histologic methods were used to evaluate clinical methods for estimating alterations of supporting structures at functioning endosseous dental implants. Twelve implant abutment posts in three Labrador retriever dogs were assessed. The observation period was 3 months of submerged healing followed by 6 months in function. In the presence of daily gingival cleaning, both plaque and gingival bleeding scores were reduced on implant abutments. No correlation was found between gingival scores and the degree of bone resorption. The correlation between probing and radiographic measurements was studied by comparing 136 parallel measurements. The average difference was 0.4 mm. Discrepancies were observed when evaluating bone loss that reached the shoulder area. Better accordance was obtained when moderate (2 to 4 mm) or extensive (6 to 8 mm) resorption was assessed. Histologic evaluation indicated alternating regions of implant-bone contact and fibrous encapsulation. Progressive infiltrates were observed in the permucosal area, sometimes extending into the deeper parts of the supporting bone. A combination of probing and radiographic measurements seems to give the most reliable information about the level of bone support and is recommended to be included in routine control of implant abutments.