Genetic correlations between pathogen-specific mastitis and somatic cell count in Danish Holsteins

Area of Science:

• Animal Genetics
• Dairy Science
• Veterinary Epidemiology

Background:

• Somatic cell count (SCC) is a key indicator of udder health in dairy cattle.
• Mastitis, an inflammation of the mammary gland, poses significant economic and welfare challenges.
• Understanding genetic relationships between SCC and specific mastitis pathogens is crucial for breeding programs.

Purpose of the Study:

• To estimate genetic correlations (r(a)) between lactation average somatic cell count (LASCC) and six mastitis traits.
• To assess the potential impact of selecting for lower LASCC on reducing mastitis caused by specific pathogens.
• To evaluate the genetic basis of mastitis resistance in Danish Holstein cows.

Main Methods:

• Utilized a large dataset of 226,482 first-parity Danish Holstein cows (calving 1998-2008).
• Defined LASCC traits from 5 to 170 days (LASCC_170) and 300 days (LASCC_300) post-calving.
• Employed bivariate threshold-Gaussian models with Gibbs sampling to estimate variance components and genetic correlations.

Main Results:

• High positive genetic correlations were found between LASCC_170 and unspecific mastitis (r(a) = 0.71), coagulase-negative staphylococci (CNS) (r(a) = 0.69), Streptococcus dysgalactiae (r(a) = 0.65), and Streptococcus uberis (r(a) = 0.63).
• The genetic correlation between LASCC_170 and Staphylococcus aureus mastitis was lower (r(a) = 0.44), potentially underestimated due to low incidence and recording issues.
• LASCC_300 showed generally smaller genetic correlations with mastitis traits compared to LASCC_170.

Conclusions:

• Selection for reduced LASCC is expected to decrease the incidence of mastitis caused by major pathogens like Strep. uberis, Strep. dysgalactiae, and CNS.
• The study highlights the potential of genetic selection to improve udder health, though data recording improvements are recommended.
• Economic weights for pathogen-specific mastitis traits should be estimated for effective implementation in breeding indices.