Mycobacterium bovis is the primary agent of tuberculosis (TB) in cattle. The failure of Ireland and some other countries to reach TB-free status indicates a need to investigate complementary control strategies. One such approach would be genetic selection for increased resistance to TB. Previous research has shown that considerable genetic variation exists for susceptibility to the measures of M. bovis infection, confirmed M. bovis infection, and M. bovis-purified protein derivative (PPD) responsiveness. The objective of this study was to estimate the genetic and phenotypic correlations between economically important traits and these measures of M. bovis infection. A total of 20,148 and 17,178 cows with confirmed M. bovis infection and M. bovis-PPD responsiveness records, respectively, were available for inclusion in the analysis. First- to third-parity milk, fat, and protein yields, somatic cell count, calving interval, and survival, as well as first-parity body condition score records, were available on cows that calved between 1985 and 2007. Bivariate linear-linear and threshold-linear sire mixed models were used to estimate (co)variance components. The genetic correlations between economically important traits and the measures of M. bovis infection estimated from the linear-linear and threshold-linear sire models were similar. The genetic correlations between susceptibility to confirmed M. bovis infection and economically important traits investigated in this study were all close to zero. Mycobacterium bovis-PPD responsiveness was positively genetically correlated with fat production (0.39) and body condition score (0.36), and negatively correlated with somatic cell score (-0.34) and survival (-0.62). Hence, selection for increased survival may indirectly reduce susceptibility to M. bovis infection, whereas selection for reduced somatic cell count and increased fat production and body condition score may increase susceptibility to M. bovis infection.
Copyright © 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.