Genetic parameters for clinical mastitis in Holstein-Friesians in the United Kingdom: a Bayesian analysis

A Bayesian threshold-liability model with Markov chain Monte Carlo techniqu es was used to infer genetic parameters for clinical mastitis records colle cted on Holstein-Friesian cows by one of the United Kingdom's national reco rding schemes. Four data sets were created to investigate the effect of dat a sampling methods on genetic parameter estimates for first and multi-lacta tion cows, separately. The data sets were: (1) cows with complete first lac tations only (8671 cows); (2) all cows, with first lactations whether compl ete or incomplete (10 967 cows); (3) cows with complete multi-lactations (3 2 948 records); and (4) all cow's with multiple lactations whether complete or incomplete (44 268 records). A Gaussian mixed linear model with sire ef fects was adopted for liability. Explanatory variables included in the mode l varied for each data set. Analyses were conducted using Gibbs sampling an d estimates were on the liability scale. Posterior means of heritability fo r clinical mastitis were higher for first lactations (0.11 and 0.10 for dat a sets 1 and 2, respectively) than for multiple lactations (0.09 and 0.07, for data sets 3 and 4, respectively). For multiple lactations, estimates of permanent environmental variance were higher for complete than incomplete lactations. Repeatability was 0.21 and 0.17 for data sets 3 and 4, respecti vely. This suggests the existence of effects, other than additive genetic e ffects, on susceptibility to mastitis that are common to all lactations. In first or multi-lactation data sets, heritability was proportionately 0.10 to 0.19 lower for data sets with all records (in which case the models had days in milk as a covariate) than for data with only complete lactation rec ords (models without days in milk as a covariate). This suggests an effect of data sampling on genetic parameter estimates. The regression of liabilit y on days in milk differed from zero, indicating that the probability of ma stitis is higher for longer lactations, as expected. Results also indicated that a regression on days in milk should be included in a model for geneti c evaluation of sires for mastitis resistance based on records in progress.