Determination of single nucleotide polymorphisms associated with subclinical ketosis in Jersey cattle
Subclinical ketosis is a fresh cow disorder that is costly in terms of lost milk production and treatment cost. Although treatment and prevention strategies are available, prevention requires targeting animals that are likely to develop the disease. Whole-herd genotyping is becoming more common with commercial dairies, and identification of markers for ketosis predisposition would provide a valuable tool to producers. The objective of this study was to identify single nucleotide polymorphisms (SNP) that are associated with subclinical ketosis in Jersey cattle. Ketotic cows were identified by cowside test using the Precision Xtra meter. Blood and hair samples were collected from 54 Jerseys (ketotic and healthy herdmates on the same day) with <30 d in milk on New England dairy farms. Mean parity of cows was 2.8, with no difference (P > 0.05) between healthy and ketotic cows; no difference (P > 0.05) also was found for milk yield, 305-d mature-equivalent milk yield (ME305), or ME305 from the previous parity. Blood serum was analyzed for concentration of nonesterified fatty acid (NEFA) and β-hydroxybutyrate (BHBA). Hair samples were submitted to the American Jersey Cattle Association for genotyping with the BovineSNP50 BeadChip. Concentrations of NEFA and BHBA were analyzed using the SAS 9.2 MIXED procedure; differences in SNP frequency by ketosis status (healthy or ketotic) was analyzed using the χ2 test from the SAS 9.2 FREQ procedure. As expected, BHBA concentrations were greater (P ≤ 0.05) for ketotic cows compared with healthy herdmates (1.63 vs. 0.91 ± 0.17 mmol/L). For NEFA, concentrations tended to be greater (P ≤ 0.01) in ketotic cows compared with healthy cows (0.45 vs. 0.33 ± 0.05 mmol/L). Of the 54,609 SNP analyzed for each genotype, 1,685 were different (P ≤ 0.05) and 1,862 tended to differ (0.05 < P ≤ 0.1) between ketotic and healthy cows. These data suggest that genotypes from the BovineSNP50 BeadChip could be useful in predicting predisposition for ketosis in Jerseys, but examination of a larger data set is necessary to validate the predictive ability of the identified SNP.
ketosis, Jersey, SNP