Predictive abilities of different statistical models for analysis of survival data in dairy cattle

The objective of this study was to compare alternative trait definitions and statistical models for genetic evaluation of survival in dairy cattle. Data from the first 5 lactations of 808,750 first-crop daughters of 3,064 Norwegian Red sires were analyzed. Seven sire models were used for genetic analyses: linear and threshold cross-sectional models for binary survival scores from first lactation; a linear multi-trait model for survival scores from the first 3 lactations; linear and threshold repeatability models for survival scores from the first 5 lactations; a Weibull frailty model for herd life in first lactation; and a Weibull frailty model for herd life in the first 5 lactations. The models were compared to assess predictive ability of sire estimated breeding values with respect to average survival 365 d after first calving for second-crop daughters (not included in calculation of predicted transmitting abilities) of 375 elite sires. Generally, the linear multi-trait model analyzing survival in the first 3 lactations as correlated traits gave more-accurate predicted sire breeding values compared with both linear and Weibull frailty models using data from first lactation only, even when the latter models were extended to include data up to the sixth lactation. The Weibull frailty models did not improve predictive ability of sire estimated breeding values over what was obtained using a simple cross-sectional linear model for binary survival in first lactation.     

Comparison between a Weibull proportional hazards model and a linear model for predicting the genetic merit of US Jersey sires for daughter longevity

Predicted transmitting abilities (PTA) of US Jersey sires for daughter longevity were calculated using a Weibull proportional hazards sire model and compared with predictions from a conventional linear animal model. Culling data from 268,008 Jersey cows with first calving from 1981 to 2000 were used. The proportional hazards model included time-dependent effects of herd-year-season contemporary group and parity by stage of lactation interaction, as well as time-independent effects of sire and age at first calving. Sire variances and parameters of the Weibull distribution were estimated, providing heritability estimates of 4.7% on the log scale and 18.0% on the original scale. The PTA of each sire was expressed as the expected risk of culling relative to daughters of an average sire. Risk ratios (RR) ranged from 0.7 to 1.3, indicating that the risk of culling for daughters of the best sires was 30% lower than for daughters of average sires and nearly 50% lower than than for daughters of the poorest sires. Sire PTA from the proportional hazards model were compared with PTA from a linear model similar to that used for routine national genetic evaluation of length of productive life (PL) using cross-validation in independent samples of herds. Models were compared using logistic regression of daughters' stayability to second, third, fourth, or fifth lactation on their sires' PTA values, with alternative approaches for weighting the contribution of each sire. Models were also compared using logistic regression of daughters' stayability to 36, 48, 60, 72, and 84 mo of life. The proportional hazards model generally yielded more accurate predictions according to these criteria, but differences in predictive ability between methods were smaller when using a Kullback-Leibler distance than with other approaches. Results of this study suggest that survival analysis methodology may provide more accurate predictions of genetic merit for longevity than conventional linear models.     

Prediction of longevity breeding values for US Holstein sires using survival analysis methodology

Breeding values of Holstein sires for daughter longevity in each of 9 geographical regions of the United States were predicted using a Weibull proportional hazards model. Longevity (also commonly referred to as herd life or length of productive life) was defined as the number of days from first calving until culling or censoring. Records from 2,322,389 Holstein cows with first calving from 1990 to 2000 were used. In addition to the sire's additive genetic merit, our failure time model included time-dependent effects of herd-year-season of calving, parity-stage of lactation, and within-herd-year quintiles for mature equivalent fat plus protein yield, as well as the time-independent effect of age at first calving. Sire variances and parameters of the Weibull distribution were estimated separately for each region. The relative risk of culling for daughters of each individual sire was expressed relative to that of daughters of an average sire (within a specific region). Predicted breeding values for functional longevity, expressed as relative risk ratios, ranged from 0.7 to 1.3. Sizable differences were observed between geographical regions in sire rankings, as well as estimated sire variances and gamma parameters (of the distribution of herd-year-season effects), suggesting that a single national ranking may not be appropriate for every region. Two random samples of herds were selected from the full national data set; these contained 375,086 records and 256,751 records, respectively. Predicted transmitting abilities (PTA) of sires for daughter longevity were calculated using the Weibull proportional hazards (sire) model described previously but without the correction for milk production. These were compared with predictions from a linear (animal) model, as currently used for routine genetic evaluation of length of productive life in the United States. Logistic regression of daughters' stayability to 36, 48, 60, 72, or 84 mo of life (among animals that had opportunity to stay that long) on sires' PTA indicated that the proportional hazards model yielded more accurate predictions of daughter longevity than the linear animal model, even though the latter relied on denser pedigree information.     

Random regression models for male and female fertility evaluation using longitudinal binary data

A longitudinal Bayesian threshold analysis of insemination outcomes was carried out using 2 random regression models with 3 (Model 1) and 5 (Model 2) parameters to model the additive genetic values at the liability scale. All insemination events of first-parity Holstein cows were used. The outcome of an insemination event was treated as a binary response of either a success (1) or a failure (0). Thus, all breeding information for a cow, including all service sires, was included, thereby allowing for a joint evaluation of male and female fertility. An edited data set of 369,353 insemination records from 210,373 first-lactation cows was used. On the liability scale, both models included the systematic effects of herd-year, month of insemination, technician, and regressions on age of service sire and milk yield during the first 100 d of lactation. The random effects in the model were the 3 or 5 random regression coefficients specific to each cow, the permanent effect of the cow, and the service sire effect. Using Model 1, the estimated heritability of an insemination outcome decreased from 0.035 at d 50 to 0.032 at d 140 and then increased continuously with DIM. The genetic correlations for insemination success at different time points ranged from 0.83 to 0.99, and their magnitude decreased with an increase in the interval between inseminations. A similar trend was observed for heritability and genetic correlations using Model 2. However, the average estimate of heritability was much higher (0.058) than those obtained using Model 1 or a repeatability model. In addition, the estimated genetic correlations followed the same trend as Model 1, but were lower and with a higher rate of decrease when the interval between inseminations increased. The posterior mean of service sire variance was 0.01 for both models, and permanent environmental variance was 0.05 and 0.02 for Models 1 and 2, respectively. Model comparison based on the Bayes factor indicated that Model 1 was more plausible, given the data.     

Bayesian analysis of liability of clinical mastitis in Norwegian cattle with a threshold model: effects of data sampling method and model specification.

First-lactation records of Norwegian Cattle were used to infer heritability of liability to clinical mastitis with a threshold sire model. Mastitis was defined as a binary response (presence or absence) in a defined period of first lactation (opportunity period). Length of opportunity period (from 30 d before calving up to 120 or 300 d of lactation) had less effect on heritability estimates than data sampling methods (include or exclude records of cows culled before the end of the opportunity period) whereas sire ranking was more affected by the former. Including all cows, whether culled before the end of the opportunity period or not, gave a sharper and more symmetric posterior distribution of heritability of liability to clinical mastitis. When we analyzed data for all cows, model specification had a small effect on heritability estimates, while sire ranking was affected markedly. Posterior means of heritability range from 0.058 to 0.074. A model regressing on the length of the opportunity period for culled cows without mastitis, was shown favorable for the two opportunity periods using Bayes factors and the deviance information criterion for model comparison. This model, in which liability of mastitis depends on time to culling, may allow utilizing information from all first lactations in genetic evaluation, irrespectively of duration and culling outcome.     

Relationship between reproduction traits and functional longevity in canadian dairy cattle

The aim of this study was to use survival analysis to assess the relationship between reproduction traits and functional longevity of Canadian dairy cattle. Data consisted of 1,702,857; 67,470; and 33,190 Holstein, Ayrshire, and Jersey cows, respectively. Functional longevity was defined as the number of days from first calving to culling, death, or censoring; adjusted for the effect of milk yield. The reproduction traits included calving traits (calving ease, calf size, and calf survival) and female fertility traits (number of services, days from calving to first service, days from first service to conception, and days open). The statistical model was a Weibull proportional hazards model and included the fixed effects of stage of lactation, season of production, the annual change in herd size, and type of milk recording supervision, age at first calving, effects of milk, fat, and protein yields calculated as within herd-year-parity deviations for each reproduction trait. Herd-year-season of calving and sire were included as random effects. Analysis was performed separately for each reproductive trait. Significant associations between reproduction traits and longevity were observed in all breeds. Increased risk of culling was observed for cows that required hard pull, calved small calves, or dead calves. Moreover, cows that require more services per conception, a longer interval between first service to conception, an interval between calving to first service greater than 90 d, and increased days open were at greater risk of being culled.     

Improving an Aggregate Phenotype in Replacements by Selecting Their Sires Conditioned on Dam Phenotypes

An indexing of total merit in expected progeny is outlined when the constituent merit from each trait is defined as a discrete quadratic equation. Information consisting of an estimated breeding value for each trait on each potential parent is used to define a trait index or a trait merit index for progeny. The selection of a specific sire for each mating, vis-a-vis the selection of a high ranking sire independent of any particular mating, is indicated more frequently when an interval along a trait scale exhibits strongly curvilinear merit and also spans the variation in trait index values among alternative matings. Variability in a trait index increases as heritability increases. Nonlinearity in a merit function dynamically describes the direction and relative selection pressure from one trait relative to another when indexes depend on dam or herd mean phenotypes. A method is proposed to quantify the role of merit from each trait relative to total merit. An example using three traits, milk yield, udder depth score, and rear leg score, is illustrated and evaluated.     

Genetic analysis of days from calving to first insemination and days open in Danish Holsteins using different models and censoring scenarios

The objectives of this study were to estimate genetic parameters and evaluate models for genetic evaluation of days from calving to first insemination (ICF) and days open (DO). Data including 509,512 first-parity records of Danish Holstein cows were analyzed using 5 alternative sire models that dealt with censored records in different ways: 1) a conventional linear model (LM) in which a penalty of 21 d was added to censored records; 2) a bivariate threshold-linear model (TLM), which included a threshold model for censoring status (0, 1) of the observations, and a linear model for ICF or DO without any penalty on censored records; 3) a right-censored linear model (CLM); 4) a Weibull proportional hazard model (SMW); and 5) a Cox proportional hazard model (SMC) constructed with piecewise constant baseline hazard function. The variance components for ICF and DO estimated from LM and TLM were similar, whereas CLM gave higher estimates of both additive genetic and residual components. Estimates of heritability from models LM, TLM, and CLM were very similar (0.102 to 0.108 for ICF, and 0.066 to 0.069 for DO). Heritabilities estimated using model SMW were 0.213 for ICF and 0.121 for DO in logarithmic scale. Using SMC, the estimates of heritability, defined as the log-hazard proportional factor for ICF and DO, were 0.013 and 0.009, respectively. Correlations between predicted transmitting ability from different models for sires with records from at least 20 daughters were far from unity, indicating that different models could lead to different rankings. The largest reranking was found between SMW and SMC, whereas negligible reranking was found among LM, TLM, and CLM. The 5 models were evaluated by comparing correlations between predicted transmitting ability from different data sets (the whole data set and 2 subsets, each containing half of the whole data set), for sires with records from at least 20 daughters, and χ² statistics based on predicted and observed daughter frequencies using a cross validation. The model comparisons showed that SMC had the best performance in predicting breeding values of the 2 traits. No significant difference was found among models LM, TLM, and CLM. The SMW model had a relatively poor performance, probably because the data are far from a Weibull distribution. The results from the present study suggest that SMC could be a good alternative for predicting breeding values of ICF and DO in the Danish Holstein population.     

Genetic analysis of somatic cell score in Norwegian cattle using random regression test-day models

The dataset used in this analysis contained a total of 341,736 test-day observations of somatic cell scores from 77,110 primiparous daughters of 1965 Norwegian Cattle sires. Initial analyses, using simple random regression models without genetic effects, indicated that use of homogeneous residual variance was appropriate. Further analyses were carried out by use of a repeatability model and 12 random regression sire models. Legendre polynomials of varying order were used to model both permanent environmental and sire effects, as did the Wilmink function, the Lidauer-M?ntysaari function, and the Ali-Schaeffer function. For all these models, heritability estimates were lowest at the beginning (0.05 to 0.07) and higher at the end (0.09 to 0.12) of lactation. Genetic correlations between somatic cell scores early and late in lactation were moderate to high (0.38 to 0.71), whereas genetic correlations for adjacent DIM were near unity. Models were compared based on likelihood ratio tests, Bayesian information criterion, Akaike information criterion, residual variance, and predictive ability. Based on prediction of randomly excluded observations, models with 4 coefficients for permanent environmental effect were preferred over simpler models. More highly parameterized models did not substantially increase predictive ability. Evaluation of the different model selection criteria indicated that a reduced order of fit for sire effects was desireable. Models with zeroth- or first-order of fit for sire effects and higher order of fit for permanent environmental effects probably underestimated sire variance. The chosen model had Legendre polynomials with 3 coefficients for sire, and 4 coefficients for permanent environmental effects. For this model, trajectories of sire variance and heritability were similar assuming either homogeneous or heterogeneous residual variance structure.     

Genetic evaluation for longevity of Dutch dairy bulls

Parameters needed for survival analysis of longevity records of cows to predict breeding values of their sires were estimated with data on Dutch Black and White and Red and White cows. The heritabilities of functional productive life were 0.041 and 0.036 on the log scale for Black and White and Red and White cows, respectively. Although the heritabilities and other parameters differed between both breeds, the resulting breeding values were hardly affected: the correlation between breeding values of Red and White bulls using either Red and White parameters or Black and White parameters was 0.992. Genetic correlations between the direct breeding value for functional longevity (based solely on longevity of sires' daughters) and breeding values for conformation, health, and fertility traits were calculated. Several alternative selection indices were investigated using these correlations. Based on the resulting reliabilities, it was concluded that the Dutch breeding value for functional longevity should be based on longevity, rump angle, teat placement, udder depth, feet and legs, and somatic cell count. The index was expressed on a scale with average of 100 and a standard deviation of 4 points (at 80% reliability). The economic value was Dfl. 65 per genetic standard deviation, which was 0.46 times the economic value of INET (Net Milk Revenue Index). For the breeding value for functional longevity that was first published in August 1999, slight modifications in the model were made.     

Genetic evaluation of mastitis in dairy cattle using linear models, threshold models, and survival analysis: a simulation study

The objective was to study, by simulation, whether survival analysis results in a more precise genetic evaluation for mastitis in dairy cattle than cross-sectional linear models and threshold models by using observation periods for mastitis of 2 lengths (the first 150 d of lactation, and the full lactation, respectively). True breeding values for mastitis liability on the underlying scale were simulated for daughters of 400 sires (average daughter group size, 60 or 150), and the possible event of a mastitis case within lactation for each cow was created. For the linear models and the threshold models, mastitis was defined as a binary trait within either the first 150 d of lactation or the full lactation. For the survival analysis, mastitis was defined as the number of days from calving to either the first case of mastitis (uncensored record) or to the day of censoring (i.e., day of culling, lactation d 150 or day of next calving; censored record). Cows could be culled early in lactation (within 10 d after calving) for calving-related reasons or later on because of infertility. The correlation between sire true breeding values for mastitis liability and sire predicted breeding values was greater when using the full lactation data (0.76) than when using data from the first 150 d (0.70) with an average of 150 daughters per sire. The corresponding results were 0.60 and 0.53, respectively, with an average of 60 daughters per sire. Under these simulated conditions, the method used had no effect on accuracy. The higher accuracy of sire breeding values can be translated into a greater genetic gain, unless counteracted by a longer generation interval.     

Impact of calving ease on functional longevity and herd amortization costs in Basque Holsteins using survival analysis

The aim of this study was to analyze the impact of calving ease (CE) on functional longevity of Basque Holsteins, using a Weibull proportional hazards model. The data considered for the analysis were 53,353 calving records from 25,810 Holstein cows distributed across 781 herds and sired by 746 bulls. The effects included in the statistical model were age at first calving, stage of lactation, interaction between year and season of calving, 305-d adjusted milk yield, CE, herd, and sire. Calving ease was considered as a time-dependent covariate and, as was the case for the rest of covariates included in the model, had a significant effect on functional longevity. Calvings needing assistance or surgery increased culling risk by 18%, when compared with unassisted calvings. The effect of CE on length of productive life in primiparous and multiparous cows was also investigated. A second analysis was performed replacing the CE effect with the interaction between parity and CE to evaluate the effect of CE in primiparous and multiparous cows. An increase in calving difficulty had a greater impact on culling during first lactations than in subsequent ones. Therefore, difficult calvings, mainly at first parities, had a high impact on herd amortization costs, increasing them by 10% in relation to easy calvings. Therefore, calving difficulty should be avoided as much as possible, especially in primiparous cows, to avoid reduction of profitability.     

Estimation of genetic parameters using sampled data from populations undergoing selection.

In populations undergoing selection, genetic (co)variances may be altered in amounts dependent on selection intensity among parents and the mating structure. In order to estimate the genetic parameters of the unselected population, all information that led to the current population must be included in the analysis. This is often not possible due to missing information or computer limitations, and, therefore, only samples of data and pedigree information of recent generations are included in analysis, and simplified operational models are used. Biases in genetic parameters, which were estimated by multitrait derivative-free REML method, were investigated in different strategies of sampling data and pedigree. In dual purpose cattle, in which young bulls are selected for growth before being progeny tested for milk yield, heritabilities and additive genetic correlations were all unbiased when all data and all relationships were used in an animal model. Using only recent data but all relationships in an animal model also gave unbiased estimates of heritabilities. Using an animal model for growth but a sire model for milk with all data gave an unbiased estimate of heritability for milk. When only recent data were used, the heritability estimate for milk was biased downward. In single purpose dairy populations, sire models gave biased estimates of genetic parameters even when all data were included in the analysis. Treating sire effects on second crop of daughters as fixed did not overcome selection bias.     

Genetic analysis of reproductive disorders and their relationship to fertility and milk yield in Austrian Fleckvieh dual-purpose cows

The objective of this study was to estimate genetic parameters for various reproductive disorders based on veterinary diagnoses for Austrian Fleckvieh (Simmental) dual-purpose cattle. The health traits analyzed included retained placenta, puerperal diseases, metritis, silent heat and anestrus, and cystic ovaries. Three composite traits were also evaluated: early reproductive disorders, late reproductive disorders, and all reproductive disorders. Heritabilities were estimated with logit threshold sire, linear sire, and linear animal models. The threshold model estimates for heritability ranged from 0.01 to 0.14, whereas the linear model estimates were lower, ranging from 0.005 to 0.04. Rank correlations among random effects of sires from linear and threshold sire models were high (>0.99), whereas correlations between any sire model (linear, threshold) and the linear animal model were lower (0.88-0.92). Genetic correlations among reproductive disorders, fertility traits, and milk yield were estimated with bivariate linear animal models. Fertility traits included interval from calving to first insemination, nonreturn rate at 56 d, and interval between first and last insemination. Milk yield was calculated as the mean from test-day 1 and test-day 2 after calving. Estimated genetic correlations were 1 among metritis, retained placenta, and puerperal diseases and 0.85 between silent heat-anestrus and cystic ovaries. Low to moderate correlations (−0.01 to 0.68) were obtained among the other disorders. Genetic correlations between reproductive disorders and fertility traits were favorable, whereas antagonistic relationships were observed between milk yield in early lactation and reproductive disorders. Pearson correlations between estimated breeding values for reproductive disorders and other routinely evaluated traits were computed, which revealed noticeable favorable relationships to longevity, calving ease maternal, and stillbirth maternal. The results showed that data from the Austrian health monitoring project can be used for genetic selection against reproductive disorders in Fleckvieh cattle.     

Short communication: genetic evaluation of the interval from first to last insemination with survival analysis and linear models

Sire breeding values for the interval between the first and last insemination were predicted using 4 proportional hazards models (survival analyses) and 2 linear mixed models to determine which would result in a more accurate genetic evaluation. A stochastic simulation describing the reproductive cycle of first-parity cows was conducted, in which true breeding values for conception rate were created. The model included the effects of sire and herd. The highest correlations between true breeding values for conception rate and breeding values for the interval between first and last insemination predicted by the survival analysis model and the linear model were 0.803 and 0.744, respectively. The results showed that when pregnancy status was known, survival models were more accurate than linear models to predict breeding values for conception rate when using observations on the interval between first and last insemination.     

Analysis of the relationship between type traits and functional survival in US Holstein cattle using a Weibull proportional hazards model

Survival analysis with a Weibull proportional hazards model was used to evaluate the effects of 15 linear type traits, 5 composite traits, and final score on the functional longevity of US Holstein cows. Culling data and type classification scores (measured in first lactation) from 891,524 cows with first calving from 1993 to 2000 were used. The data were divided into 9 geographical regions to determine whether the relationship between type traits and longevity differed according to climate or management system. Functional survival was defined as the number of days from first calving until culling or censoring, after correction for 305-d mature equivalent combined fat and protein yield. The Weibull model included time-dependent effects of herd-year-season, parity-stage of lactation, and within herd-year quintile ranking for combined fat and protein yield (nested within biennium), as well as time-independent effects of age at first calving and type classification score (type traits were analyzed one at a time). Type classification scores were rounded to the nearest 5 points, and the impact of each type trait on functional survival in each region was evaluated. Mean failure time ranged from 694 d in the South to 758 d in the North East. Risk of culling differed by region for several linear type traits, and differences were greatest for regions that were most dissimilar in climate and herd management (e.g., South East, East North Central, and West). Udder depth, fore udder attachment, udder cleft, and rear legs side view were consistently associated with functional longevity, regardless of region, but, the importance of some secondary traits, such as stature or dairy form, differed by region. The survival model applied in this study easily described both linear and nonlinear relationships between type traits and longevity while accounting for important time-dependent and time-independent explanatory variables.     

Comparison between a sire model and an animal model for genetic evaluation of fertility traits in Danish Holstein population

Comparisons between a sire model, a sire-dam model, and an animal model were carried out to evaluate the ability of the models to predict breeding values of fertility traits, based on data including 471,742 records from the first lactation of Danish Holstein cows, covering insemination years from 1995 to 2004. The traits in the analysis were days from calving to first insemination, calving interval, days open, days from first to last insemination, number of inseminations per conception, and nonreturn rate within 56 d after first service. The correlations between sire estimated breeding value (EBV) from the animal model and the sire-dam model were close to 1 for all the traits, and those between the animal model and the sire model ranged from 0.95 to 0.97. Model ability to predict sire breeding value was assessed using 4 criteria: 1) the correlation between sire EBV from 2 data subsets (DATA_A and DATA_B); 2) the correlation between sire EBV from training data (DATA_A or DATA_B) and yield deviation from test data (DATA_B or DATA_A) in a cross-validation procedure; 3) the correlation between the EBV of proven bulls, obtained from the whole data set (DATA_T) and from a reduced set of data (DATA_C1) that contained only the first-crop daughters of sires; and 4) the reliability of sire EBV, calculated from the prediction error variance of EBV. All criteria used showed that the animal model was superior to the sire model for all the traits. The sire-dam model performed as well as the animal model and had a slightly smaller computational demand. Averaged over the 6 traits, the correlations between sire EBV from DATA_A and DATA_B were 0.61 (sire model) versus 0.64 (animal model), the correlations between EBV from DATA_T and DATA_C1 for proven bulls were 0.59 versus 0.67, the correlations between EBV and yield deviation in the cross-validation were 0.21 versus 0.24, and the reliabilities of sire EBV were 0.42 versus 0.46. Model ability to predict cow breeding value was measured by the reliability of cow EBV, which increased from 0.21 using the sire model to 0.27 using the animal model. All the results suggest that the animal model, rather than the sire model, should be used for genetic evaluation of fertility traits.     

Comparison of methods for genetic evaluation of sires for survival of their daughters in the first three lactations.

Several approaches for analysis of survival in the first three lactations were compared using data from approximately 700,000 Canadian Holsteins. Two approaches (linear model and threshold model) were used to analyze a binary measure of survival. Other approaches were survival analyses to evaluate two measures of the number of days that cows were in milk during their first three lactations. One measure restricted days per lactation to < or = 305; the other was based on the actual number of days in milk without an upper limit on days per lactation. Variance components and breeding values (EBV) were estimated. Sire models were used almost exclusively, but one set of EBV was obtained using a linear animal model. Effects in the models were herd-year of calving, age at first calving, interaction of several factors related to herd, and production. Thus, all EBV were for functional herd life. Heritabilities were approximately 0.04, 0.07, and 0.10 from linear, threshold, and survival analyses, respectively. Correlations among sire EBV from all analyses using sire models were high, particularly for linear and threshold models (0.98). In contrast, correlations of EBV from sire models with EBV from the linear animal model were less than 0.90, regardless of the approach taken. In Canada, the current linear animal model remains in use for sire evaluation of herd life, but research with survival analyses will continue.     

Short communication: Heritability of susceptibility to infection by Mycobacterium avium ssp. paratuberculosis in Holstein cattle

Johne's disease in cattle is the result of infection of the small intestine by Mycobacterium avium ssp. paratuberculosis (MAP), leading to an incurable inflammatory bowel disease (Johne's disease or paratuberculosis). The disease is a concern both for its direct cost to dairy producers and for its zoonotic potential. The objective of this study was to estimate the heritability for susceptibility to infection of cattle by MAP using Johne's testing records (ELISA test for presence of antibodies to MAP in milk or blood) from US Holstein cattle from 2009 to 2016. Data sets were edited to include records from herds with 100 or more total records and sires with 50 or more daughters. Data sets were further edited to include (1) only herds with at least 1 positive test, (2) herds with at least 2.5% positive test results, and (3) herds with at least 5% positive test results to examine the effect of data from herds with higher proportions of positive tests, and presumably higher pathogen exposure, on heritability estimates. Two models were used in this study, a linear sire model and a binary threshold-probit sire model. Both were mixed models considering fixed effects of herd and age at test, the latter as a covariate accounting for linear and quadratic effects; random effects included sire and residual. Analyses were conducted using a restricted maximum likelihood method. Heritability estimates (±standard error) from the linear model were 0.041 ± 0.004, 0.050 ± 0.004, and 0.062 ± 0.007 for data from herds with at least 1 positive test, ≥2.5% positive tests, and ≥5% positive tests, respectively. Heritability estimates from the threshold model were 0.157 ± 0.014, 0.174 ± 0.016, and 0.186 ± 0.021 for data from herds with at least 1 positive test, ≥2.5% positive tests, and ≥5% positive tests, respectively. Heritability estimates from the linear model were affected by population incidence for positive tests, in contrast to estimates from the threshold model, likely accounting for the difference in magnitude of heritability estimates between models and suggesting that the threshold model analysis is the better choice. Heritability estimates increased as data were restricted to herds with presumed higher MAP exposure for both linear model and threshold model analyses. These estimates are similar to previous estimates in other dairy cattle populations and suggest the potential for selection to lessen susceptibility to MAP infection.     

Genomic selection for producer-recorded health event data in US dairy cattle

Emphasizing increased profit through increased dairy cow production has revealed a negative relationship of production with fitness and health traits. Decreased cow health can affect herd profitability through increased rates of involuntary culling and decreased or lost milk sales. The development of genomic selection methodologies, with accompanying substantial gains in reliability for low-heritability traits, may dramatically improve the feasibility of genetic improvement of dairy cow health. Producer-recorded health information may provide a wealth of information for improvement of dairy cow health, thus improving profitability. The principal objective of this study was to use health data collected from on-farm computer systems in the United States to estimate variance components and heritability for health traits commonly experienced by dairy cows. A single-step analysis was conducted to estimate genomic variance components and heritabilities for health events, including cystic ovaries, displaced abomasum, ketosis, lameness, mastitis, metritis, and retained placenta. A blended H matrix was constructed for a threshold model with fixed effects of parity and year-season and random effects of herd-year and sire. The single-step genomic analysis produced heritability estimates that ranged from 0.02 (standard deviation = 0.005) for lameness to 0.36 (standard deviation = 0.08) for retained placenta. Significant genetic correlations were found between lameness and cystic ovaries, displaced abomasum and ketosis, displaced abomasum and metritis, and retained placenta and metritis. Sire reliabilities increased, on average, approximately 30% with the incorporation of genomic data. From the results of these analyses, it was concluded that genetic selection for health traits using producer-recorded data are feasible in the United States, and that the inclusion of genomic data substantially improves reliabilities for these traits.