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- Welderufael, Berihu, et al.
(author)
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Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows
- 2017
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In: Journal of Dairy Science. - : American Dairy Science Association. - 0022-0302 .- 1525-3198. ; 100, s. 4706-4720
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Journal article (peer-reviewed)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.
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- Welderufael, Berihu, et al.
(author)
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Genetic Evaluation of Mastistis Liability and Recovery through Longitudinal Models of SCC
- 2013
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Conference paper (peer-reviewed)abstract
- Genetic evaluation of mastitis is performed either with cross-sectional or longitudinal models. In this study we aim to develop better longitudinal models using simulated SCC (Somatic Cell Count) which usually is used as a proxy to label clinical mastitis. Data was simulated for mastitis liability and recovery for two scenarios (28% and 95% mastitis cases/lactation) and two daughter groups of 60 and 150 per sire in 1200 herds. Weekly observations for SCC were simulated assuming a baseline curve for non-mastitic cows and deviations in case of a mastitis event. Binary data was created to define presence or absence of mastitis as 1 if the simulated SCC was above pre-specified boundary and 0 otherwise. The boundary was allowed to vary along the lactation curve modeled by a spline function with a multiple of 10 or 15. The dynamic nature of the SCC was taken in to consideration with the longitudinal approach and the patterns were captured by modelling transition probability of moving across the boundary. Thus, a transition from below to above the boundary is an indicator of the probability to contract mastitis, and a transition from above to below the boundary is an indicator of the recovery process. Estimated breeding values for mastitis liabilities and recovery were calculated in DMU. Our preliminary results showed the correlation between true and estimated breeding value for the simulated mastitis liability was 0.72 which is as good as the estimations based on clinical mastitis. Though the estimation accuracy for recovery (0.42) was not as high as for mastitis liability the transition probability model enables us to generate breeding values for mastitis recovery process.
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- Welderufael, Berihu, et al.
(author)
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Genetic evaulation of getting and recovering from an intramammary infection through longitudinal models of simulated somatic cell count
- 2013
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Other publication (other academic/artistic)abstract
- Mastitis, a bacterial intramammary infection, is one of the recently prioritized research thematic areas in the dairy cattle breeding programs. Genetic evaluation of mastitis is performed either with crosssectional or longitudinal models. The objective of this study was to develop better longitudinal models through the analysis of simulated somatic cell count (SC C) which is often used as a proxy to label clinical mastitis. Data were simulated for 2 traits: intramammary infection and recovery, for two scenarios (28% and 95% cases/lactation) and for two daughter groups of 60 and 150 per sire distributed over 1200 herds. Weekly observations for SCC were simulated assuming a baseline curve for non-mastitis cows and deviations in the case of a mastitis event. Binary data were created to define presence or absence of mastitis as 1 if the SCC was above pre-specified boundary (200000 cells/mL), and 0 otherwise. The boundary was allowed to vary along the lactation curve modeled by a spline function with a multiple of 10 or 15. The dynamic nature of the SCC was taken into consideration with the longitudinal approach; and the patterns were captured by modelling transition probabilities of moving across the boundary. Thus, a transition from below to above the boundary is an indicator of the probability to contract mastitis, and a transition from above to below the boundary is an indicator of the recovery process. Sire model with mean, fixed herd and random sire effects was fitted to calculate the estimated breeding values for intramammary infection and recovery using Bayesian inference and MCMC simulations in DMU, a statistical package for analyzing multivariate mixed models. Our preliminary results showed that the estimation accuracy or the correlation between true and estimated breeding value for the simulated intramammary infection mastitis was 0.72, which is as high as the estimations based on clinical mastitis. The estimation accuracy for recovery (0.42) was not as high as for getting infection. However, the transition probability model enables us to generate breeding values for the recovery process. The MCMC nonlinear and longitudinal approach leads to more precise genetic evaluation. This is because the MCMC fits well to the binary nature of getting infection; and the longitudinal approach uses more available information for the analysis.
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- Welderufael, Berihu, et al.
(author)
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Genome-Wide Association Study for Susceptibility to and Recoverability From Mastitis in Danish Holstein Cows
- 2018
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In: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 9
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Journal article (peer-reviewed)abstract
- Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to - but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t-test and a genome-wide significance level of P-value < 10(-4) was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to - or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2) and genes involved in macrophage recruitment and regulation of inflammations (PDGFD and PTX3) were suggested as possible causal genes for susceptibility to - and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to - and recoverability from mastitis.
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- Welderufael, Berihu, et al.
(author)
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Longitudinal Analysis of Somatic Cell Count for Joint Genetic Evaluation of Mastitis and Recovery Liability
- 2014
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In: Proceedings, 10th World Congress of Genetics Applied to Livestock Production.
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Conference paper (peer-reviewed)abstract
- Better models of genetic evaluation for mastitis can be developed through longitudinal analysis of somatic cell count (SCC) which usually is used as a proxy for mastitis. Mastitis and recovery data with weekly observations of SCC were simulated for daughter groups of 60 and 240 per sire. Data were created to define cases: 1 if SCC was above a pre-specified boundary, else 0. A transition from below to above the boundary indicates probability to contract mastitis, and the other way indicates recovery. The MCMCglmm package was used to estimate breeding values. In the 60 daughters group, accuracies ranged from 0.53 to 0.54 for mastitis and 0.22 to 0.23 for recovery. Whereas, in the 240 daughters group accuracies ranged from 0.83 to 0.85 for mastitis and 0.57 to 0.65 for recovery. Reasonable accuracies can be achieved from SCC based estimates.
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- Welderufael, Berihu, et al.
(author)
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Simultaneous genetic evaluation of simulated mastitis susceptibility and recovery ability using a bivariate threshold sire model
- 2016
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In: Acta agriculturae Scandinavica. Section A, Animal science. - : Informa UK Limited. - 0906-4702 .- 1651-1972. ; 66:3, s. 125-134
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Journal article (peer-reviewed)abstract
- The aim of this study was to develop a new approach for joint genetic evaluation of mastitis and recovery. Two mastitis incidences (0.28 and 0.95) measured via somatic cell count and three between traits genetic correlations (0.0, 0.2, and -0.2) were simulated for daughter group sizes of 60 and 240. A transition model was applied to model transitions between healthy and disease state. The RJMC package in DMU was used to estimate (co)variances. Heritabilities were consistent with the simulated value (0.039) for susceptibility and a bit upward biased for recovery. Estimates of genetic correlations were -0.055, 0.205, and -0.192 for the simulated values of 0.0, 0.2, and -0.2, respectively. For daughter group size of 60, accuracies of sire EBV ranged from 0.56 to 0.69 for mastitis and from 0.26 to 0.48 for recovery. The study demonstrated that both traits can be modeled jointly and simulated correlations could be correctly reproduced.
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