Detection of genetic variability in dairy cattle infectivity for bovine tuberculosis.

This study investigated the genetics of bovine tuberculosis (bTB) infectivity in Holstein-Friesian dairy cows using British national data. The analyses included cows with recorded sires from herds affected by bTB outbreaks between 2000 and 2022. Animals were considered bTB-positive if they reacted positively to the skin test and/or had positive post-mortem findings. We introduced the "index case approach," based on the assumption that once the initial positively tested animals (index cases) are detected in a herd, subsequent infections (secondary cases) in the early stages of the breakdown are likely to be attributed to these animals. Genetic analysis of the number of secondary cases (NSC) associated with a given index case was used to establish evidence of genetic variability in bTB infectivity of cattle, and derive Estimated Breeding Values (EBVs) for infectivity for the sires of the index cases. Data were analyzed by employing Markov Chain Monte Carlo techniques to fit Generalized Linear Mixed Models with either Poisson, Zero-Inflated Poisson (ZIP), Hurdle Poisson, or Geometric distributions. All 4 models demonstrated presence of genetic variance in cattle infectivity, with the strongest evidence provided by the ZIP and Hurdle Poisson models. The Hurdle Poisson model offered the most accurate and least biased predictions. Sire infectivity EBVs from the Poisson, ZIP, and Geometric models showed strong concordance, with pairwise correlations of 0.90 or higher. In contrast, correlations between EBVs from the Hurdle Poisson model and the other models ranged from 0.36 to 0.39. The association of the sire infectivity EBVs with the average observed NSC per sire and the proportion of infectious index case daughters per sire was generally moderate with correlations between 44 and 47% and 65-69%, respectively. Agreement among models for identifying the genetically most infectious sires was also reasonable, with 151 out of 285 sires appearing in the top 10% across models, and 122 (42.8%) also aligning with the top 10% based on observed average NSC. Results provide novel evidence for exploitable genetic variance in bTB infectivity allowing the derivation of meaningful EBVs. Based on the estimated posterior mean genetic variances obtained, reduction in infectivity by one genetic standard deviation would result in a 32% - 44% decrease in the expected NSC per index case. Further research is warranted to refine the phenotypic definition of infectivity and assess correlation with other dairy traits.