Genetic analysis of somatic cell score in Danish dairy cattle using random regression test-day model

Abstract

The objective of this study was to estimate the genetic and permanent environmental (PE) covariance functions for test-day records of logarithm of somatic cell count (SCS) of the first lactation for Danish Holstein cattle, and to test the hypotheses that: genetic and environmental variances change over first lactation, genetic correlations are near unity between any time points in first lactation, and including a Wilmink term will improve the likelihood of more than an extra order Legendre polynomial.Ten data sets, consisting of 1,190,584 test day somatic cell count (SCC) records from 149,233 Danish Holstein cows, were extracted from the national milk recording database. Each data set was analyzed with random regression models using AI-REML. Fixed effects in all models were age at first calving, herd test day, days carrying calf, effects of germ plasm importation (e.g. additive breed effects and heterosis) and stage of lactation as a fifth order normalized Legendre polynomial (LP) combined with a Wilmink term (exp(−0.09*DIM)). Random effects were co-variance functions for PE and additive genetic effects. The first and second data sets were analyzed using two classes of models. In the first class, PE and genetic effects were modeled by 1st to 4th order LPs combined with a Wilmink term. In the second class, 1st and 5th order LPs for PE effect and for genetic effect were modeled without Wilmink term. Of the models tested, the model with fifth order LP for both PE and genetic effects had the lowest −2ln(L). Furthermore, based on a likelihood ratio test, this model was not significantly better than a model with fifth order LP for PE effect and a fourth order LP for genetic effects. The last two models were applied to the other data sets (set 3 to set 10). In all ten data sets, the model with fifth order LP for PE effect and genetic effect were adequate to fit the data. The average heritability differed over the lactation and was lowest at the beginning (0.098) and higher at the end of lactation (0.138 to 0.151). Genetic correlations between daily SCS were high for adjacent tests (nearly 1) and low between the beginning and the end of lactation. The estimated environmental correlations were lower than the genetic correlations, but the trends were similar. Based on test-day records, the accuracy of genetic evaluations for SCC should be improved when the variation in heritabilities and correlations are taking into account.