Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows

Abstract

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.

Genome-Wide Association Study for Susceptibility to and Recoverability From Mastitis in Danish Holstein Cows

“…The raw phenotype data, analyzed in the current study, were edited and used by Welderufael et al (2017) to estimate genetic parameters for susceptibility to – and recoverability from mastitis in Danish Holstein cows using bi-variate threshold models. The data contained a total of 89,232 weekly transition records for a total of 1,791 Danish Holstein cows in parities 1–3 distributed over one research herd (Danish Cattle Research Center, Tjele, Denmark) and six commercial dairy herds.…”

“…The data contained a total of 89,232 weekly transition records for a total of 1,791 Danish Holstein cows in parities 1–3 distributed over one research herd (Danish Cattle Research Center, Tjele, Denmark) and six commercial dairy herds. Welderufael et al (2017) derived the transition records from SCC data recorded at every milking using voluntary milking system (VMS, DeLaval International AB, Tumba, Sweden) and stored in an online database. Mastitis could be caused by different pathogens to which the cows may respond differently.…”

Estimating individuals’ genetic and non-genetic effects underlying infectious disease transmission from temporal epidemic data

“…The approach developed in this study and integrated into SIRE complement and succeed previous studies that aimed to develop statistical methods for estimating genetic effects for the different host epidemiological traits [25,[30][31][32]34]. The key novelty of our approach lies in its ability to estimate genetic and non-genetic effects associated with all three epidemiological host traits from a range of temporal epidemic data, even when that data is incomplete.…”

“…However, analysing such data to draw joint inferences on both the disease epidemiology and host genetic variation has proven challenging [25,28]. Recent studies have expanded conventional quantitative genetics threshold models to enable joint genetic evaluation of cattle susceptibility to, and recoverability from, mastitis [29,30], which led to identification of novel SNPs and candidate genes associated with these traits [19]. However, because infectivity acts on group members rather than the focal individual itself, applying these technique to estimate genetic effects for infectivity is problematic.…”

GWAS using 2b-RAD sequencing identified three mastitis important SNPs via two-stage association analysis in Chinese Holstein cows

“…Bovine mastitis is the most complex and costly disease with high incidence, which seriously affects developing dairy industry worldwide (MAUNSELL et al 1998;SCHUKKEN et al 2009;WELDERUFAEL et al 2017). Infection with mastitis causes direct economic losses in several ways, including dramatically discount in milk yield, treatment costs, condemnation of milk because of antibiotic or bacterial contamination.…”