Abstract
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.
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