Genetic analysis of fertility-related diseases and disorders in Norwegian Red cows

Heritability of and genetic correlations among silent heat (SH), cystic ovaries (CO), metritis (MET), and retained placenta (RP) were inferred. These traits were chosen because they are the 4 most frequent fertility-related diseases and disorders among first-lactation cows in Norway. Records of 503,683 first-lactation daughters of 1,058 Norwegian Red sires with first calving from 2000 through 2006 were analyzed with a 4-variate threshold sire model. Presence or absence of each of the 4 diseases was scored as 1 or 0 based on whether or not the cow had at least 1 veterinary treatment for the disease. The mean frequency was 3.1% for SH, 0.9% for MET, 0.5% for CO, and 1.5% for RP. The model for liability had effects of age at calving and of month-year of calving, herd, sire of the cow, and a residual. Posterior mean (SD) of heritability of liability was 0.06 (0.01) for SH, 0.03 (0.01) for MET, 0.07 (0.01) for CO, and 0.06 (0.01) for RP. The genetic correlation between MET and RP was strong, with posterior mean (SD) 0.64 (0.10). A negative genetic correlation (−0.26) was found between RP and CO. The posterior distributions of the other genetic correlations included zero with high density, and could not be considered different from zero. The frequency of fertility-related diseases and disorders is very low in the Norwegian Red population at present, so there is limited scope for genetic improvement. However, this study indicates that reasonably precise genetic evaluation of sires is feasible for these traits given information from large daughter groups.     

Comparison of different models for genetic analysis of clinical mastitis in Austrian Fleckvieh dual-purpose cows

The performance of different models for genetic analyses of clinical mastitis in Austrian Fleckvieh dual-purpose cows was evaluated. The main objective was to compare threshold sire models (probit and logit) with linear sire and linear animal models using REML algorithm. For comparison, data were also analyzed using a Bayesian threshold sire model. The models were evaluated with respect to ranking of sires and their predictive ability in cross-validation. Only minor differences were observed in estimated variance components and heritability from Bayesian and REML probit models. Heritabilities for probit and logit models were 0.06 and 0.08, respectively, whereas heritabilities for linear sire and linear animal models were lower (0.02). Correlations among ranking of sires from threshold and linear sire models were high (>0.99), whereas correlations between any sire model (threshold or linear) and the linear animal model were slightly lower (0.96). The worst sires were ranked very similar across all models, whereas for the best sires some reranking occurred. Further, models were evaluated based on their ability to predict future data, which is one of the main concerns of animal breeders. The predictive ability of each model was determined by using 2 criteria: mean squared error and Pearson correlation between predicted and observed value. Overall, the 5 models did not differ in predictive ability. In contrast to expectations, sire models had the same predictive ability as animal models. Linear models were found to be robust toward departures from normality and performed equally well as threshold models.     

Genetic analysis of clinical mastitis and somatic cell count traits in Austrian Fleckvieh cows

The objectives of this study were to investigate genetic associations between clinical mastitis (CM) and different somatic cell count traits, and to examine their relationships, in terms of estimated breeding values, with other traits that are routinely evaluated in Austrian Fleckvieh dual-purpose cows. Records on veterinary treatments of CM were available from the Austrian health-monitoring project. For CM, 3 intervals in early lactation were considered: -10 to 50 d, 51 to 150 d, and -10 to 150 d after calving. Within each interval, absence or presence of CM was scored as 1 or 0 based on whether or not the cow had recorded at least one veterinary treatment of CM. The average somatic cell score of the first 2 test-days after calving was defined as early lactation average somatic cell score, and lactation mean somatic cell score was the average of all test-day somatic cell scores from 8 to 305 d after calving. Subclinical mastitis was expressed as a binary trait based on prolonged elevated somatic cell counts. If somatic cell counts on 3 consecutive test-days in the interval from 8 to 305 d after calving were above 200,000 cells/mL, the binary variable subclinical mastitis was defined as 1 and otherwise 0. Records of Austrian Fleckvieh cows, with calving from January 1, 2007, to February 28, 2009, were analyzed using univariate and bivariate sire models. Threshold liability models were applied for binary traits, and Gaussian models were used for early lactation average somatic cell score and lactation mean somatic cell score. A Bayesian approach using Gibbs sampling was applied for genetic analyses. Posterior means of heritability of liability to CM were 0.06 and 0.02 in the first and second interval, respectively, and 0.05 in the full period (-10 to 150 d). Heritability estimates of somatic cell count traits were higher (0.09 to 0.13). The posterior mean of the genetic correlation between CM in lactation period 1 (-10 to 50 d after calving) and 2 (51 to 150 d after calving) was close to unity. Posterior means of genetic correlations between CM and somatic cell count traits ranged from 0.64 to 0.77. Because CM and somatic cell count describe different aspects of udder health, information on both traits should be considered for selection of bulls. Correlations of sire breeding values revealed that especially the udder conformation trait udder depth may be useful as additional information to reduce both CM and somatic cell count.     

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.     

Estimates of genetic parameters for Canadian Holstein female reproduction traits

Age at first insemination, days from calving to first insemination, number of services, first-service nonreturn rate to 56 d, days from first service to conception, calving ease, stillbirth, gestation length, and calf size of Canadian Holstein cows were jointly analyzed in a linear multiple-trait model. Traits covered a wide spectrum of aspects related to reproductive performance of dairy cows. Other frequently used fertility characteristics, like days open or calving intervals, could easily be derived from the analyzed traits. Data included 94,250 records in parities 1 to 6 on 53,158 cows from Ontario and Quebec, born in the years 1997 to 2002. Reproductive characteristics of heifers and cows were treated as different but genetically correlated traits that gave 16 total traits in the analysis. Repeated records for later parities were modeled with permanent environmental effects. Direct and maternal genetic effects were included in linear models for traits related to calving performance. Bayesian methods with Gibbs sampling were used to estimate covariance components of the model and respective genetic parameters. Estimates of heritabilities for fertility traits were low, from 3% for nonreturn rate in heifers to 13% for age at first service. Interval traits had higher heritabilities than binary or categorical traits. Service sire, sire of calf, and artificial insemination technician were important (relative to additive genetic) sources of variation for nonreturn rate and traits related to calving performance. Fertility traits in heifers and older cows were not the same genetically (genetic correlations in general were smaller than 0.9). Genetic correlations (both direct and maternal) among traits indicated that different traits measured different aspects of reproductive performance of a dairy cow. These traits could be used jointly in a fertility index to allow for selection for better fertility of dairy cattle.     

Genetic parameters for female fertility traits and a fertility index in Spanish dairy cattle

Genetic correlations among female fertility traits (linear and binary) were estimated using 225,085 artificial insemination records from 120,713 lactations on 63,160 Holstein cows. Fertility traits were: calving interval, days open, a linear transformation of days open, days to first insemination, interval between first and last insemination, number of inseminations per service period, pregnancy within 56 and 90 d after first insemination, and success in first insemination. A bivariate animal model was implemented using Bayesian methods in the case of binary traits. Low heritabilities (0.02 to 0.06) were estimated for these fertility traits. Strong genetic correlations (0.89 to 0.99) were found among traits, except for days to first service, where the genetic correlation with other fertility traits ranged from −0.52 to −0.18 for binary traits, and from 0.50 to 0.82 for days to first service, calving interval, and days open. Four fertility indices were proposed utilizing information from insemination records; these indices combined one indicator of the beginning of the service period and one indicator of conception rate. Two additional indices used information from the milk-recording scheme, including calving interval and a linear transformation of days open. The fertility index composed of days to first service and pregnancy within 56 d achieved the highest genetic gain for reducing fertility cost, reducing days to first service, and reducing the number of inseminations per lactation ($8.60, −1.31 d, and −0.03 AI, respectively). This index achieved at least 15% higher genetic gain than obtained from indices with information from the milk recording scheme only (calving interval and days open).     

Estimation of variance components and genetic trends for twinning rate in Holstein dairy cattle of Iran

Calving records from the Animal Breeding Center of Iran, collected from January 1991 to December 2007 and comprising 1,163,594 Holstein calving events from 2,552 herds, were analyzed using a linear animal model, linear sire model, threshold animal model, and threshold sire model to estimate variance components, heritabilities, genetic correlations, and genetic trends for twinning rate in the first, second, and third parities. The overall twinning rate was 3.01%. Mean incidence of twins increased from first to fourth and later parities: 1.10, 3.20, 4.22, and 4.50%, respectively. For first-parity cows, a maximum frequency of twinning was observed from January through April (1.36%), and second- and third-parity cows showed peaks from July to September (at 3.35 and 4.55%, respectively). The phenotypic rate of twinning decreased from 1991 to 2007 for the first, second, and third parities. Sire predicted transmitting abilities were estimated using linear sire model and threshold sire model analyses. Sire transmitting abilities for twinning rate in the first, second, and third parities ranged from −0.30 to 0.42, −0.32 to 0.31, and −0.27 to 0.30, respectively. Heritability estimates of twinning rate for parities 1, 2, and 3 ranged from 1.66 to 10.6%, 1.35 to 9.0%, and 1.10 to 7.3%, respectively, using different models for analysis. Heritability estimates for twinning rate, obtained from the analysis of threshold models, were greater than the estimates of linear models. Solutions for age at calving for the first, second, and third parities demonstrated that cows older at calving were more likely to have twins. Genetic correlations for twinning rate between parities 2 and 3 were greater than correlations between parities 1 and 2 and between parities 1 and 3. There was a slightly increasing trend for twinning rate in parities 1, 2, and 3 over time with the analysis of linear animal and linear sire models, but the trend for twinning rate in parities 1, 2, and 3 with threshold animal model analysis was decreased over the years. There was a significant decreasing trend for twinning rate in parities 1 and 2 over time with the threshold sire model analysis, but the genetic trend for twinning rate in parity 3 with this model of analysis was significant and positive. In general, there were increasing genetic trends for twinning rate from parities 1 through 3 using different models of analysis.     

Relationships between reproductive traits of heifers and cows and yield traits for Holsteins in Japan

The objective of this study was to investigate relationships between reproductive traits in heifers and cows and yield traits for Holsteins in Japan. Insemination and lactation records for cows calved between 1990 and 2003 in Hokkaido region were obtained. Age at first service, age at conception, and conception rate for first service were calculated for heifers. Days from calving to first service, days open, and conception rate for first service were calculated for first- and second-parity cows. The yield traits used were 305-d milk, fat, and protein yields. A threshold animal model was applied for the conception rate for first service, and a linear animal model was applied for the other traits. Single-trait and 2-trait genetic analyses were performed by the Bayesian method using Gibbs sampling. Heritability estimates ranged from 0.027 to 0.051 for conception rate for first service, and from 0.074 to 0.128 for the other reproductive traits. If the relationships of other traits were not considered, days from calving to first service was favorable to genetic selection for reproductive traits because of relatively high heritability and because it can be available earlier than the days open. Genetic correlations among reproductive traits were high, especially in cows. The genetic correlations between reproductive traits for heifers and those for cows were lower than the genetic correlations between reproductive traits for first parity and those of second parity, suggesting that reproductive traits for heifers should be evaluated separately from reproductive traits for cows. Genetic correlations between yield and reproductive traits in cows were antagonistic. In contrast, genetic correlations between reproductive traits for heifers and yield traits were slightly desirable. Depending on the reporting rate of insemination records for heifers and the results of investigations for relationships with productive maturity, selection by reproductive traits for heifers will enable the improvement of reproductive performance without a loss in genetic progress for yield traits.     

Genetic relationships of clinical mastitis,cystic ovaries,and lameness with milk yield and somatic cell score in first-lactation Canadian Holsteins

The objective of this study was to investigate the genetic relationships of the 3 most frequently reported dairy cattle diseases (clinical mastitis, cystic ovaries, and lameness) with test-day milk yield and somatic cell score (SCS) in first-lactation Canadian Holstein cows using random regression models. Health data recorded by producers were available from the National Dairy Cattle Health System in Canada. Disease traits were defined as binary traits (0 = healthy, 1 = affected) based on whether or not the cow had at least one disease case recorded within 305 d after calving. Mean frequencies of clinical mastitis, cystic ovaries, and lameness were 12.7, 8.2, and 9.1%, respectively. For genetic analyses, a Bayesian approach using Gibbs sampling was applied. Bivariate linear sire random regression model analyses were carried out between each of the 3 disease traits and test-day milk yield or SCS. Random regressions on second-degree Legendre polynomials were used to model the daily sire additive genetic and cow effects on test-day milk yield and SCS, whereas only the intercept term was fitted for disease traits. Estimated heritabilities were 0.03, 0.03, and 0.02 for clinical mastitis, cystic ovaries, and lameness, respectively. Average heritabilities for milk yield were between 0.41 and 0.49. Average heritabilities for SCS ranged from 0.10 to 0.12. The average genetic correlations between daily milk yield and clinical mastitis, cystic ovaries, and lameness were 0.40, 0.26, and 0.23, respectively; however, the last estimate was not statistically different from zero. Cows with a high genetic merit for milk yield during the lactation were more susceptible to clinical mastitis and cystic ovaries. Estimates of genetic correlations between daily milk yield and clinical mastitis were moderate throughout the lactation. The genetic correlations between daily milk yield and cystic ovaries were near zero at the beginning of lactation and were highest at mid and end lactation. The average genetic correlation between daily SCS and clinical mastitis was 0.59 and was consistent throughout the lactation. The average genetic correlation between daily SCS and cystic ovaries was near zero (−0.01), whereas a moderate, but nonsignificant, correlation of 0.27 was observed between SCS and lameness. Unfavorable genetic associations between milk yield and diseases imply that production and health traits should be considered simultaneously in genetic selection.     

Genetic analyses of mastitis data using animal threshold models and genetic correlation with production traits

In the present study, 6 different mastitis data sets of 3 dairy herds with an overall herd size of 3200 German Holstein cows were analyzed. Data collection periods included the first 50, 100, or 300 d of lactation. The 3 data collection periods were analyzed with a lactation model and a test-day model. All models were animal threshold models. Mastitis frequencies in the lactation model data sets varied between 29 and 45%, and varied between 3 and 6% in the test-day model data sets. Depending on the period of data collection, heritabilities of liability to mastitis in the lactation models were 0.05 (50 d), 0.06 (100 d), and 0.07 (300 d). In the test-day models, heritabilities were slightly higher with values of 0.09 (50 and 100 d), and 0.06 (300 d). Between lactation models, the rank correlations between the relative breeding values were high and varied between 0.86 and 0.94. Rank correlations between the relative breeding values of the test-day models ranged from 0.68 to 0.87. The rank correlations between the relative breeding values of lactation models and test-day models varied from 0.51 and 0.80. Genetic correlations between mastitis and milk production traits were estimated with a linear animal test-day model. The correlations with mastitis were 0.29 (milk yield), 0.30 (fat yield), 0.20 (fat content), 0.34 (protein yield), and 0.20 (protein content). The estimated genetic correlation between mastitis and somatic cell score was 0.84.     

Exploration of relationships between claw disorders and milk yield in Holstein cows via recursive linear and threshold models

Relationships between claw disorders and test-day milk yield recorded in 2005 on 5,360 Holstein cows, kept on 11 large-scale dairy farms in eastern Germany, were analyzed in a Bayesian framework with standard linear and threshold models and recursive linear and threshold models. Four different claw disorders, digital dermatitis (DD), sole ulcer (SU), wall disorder (WD), and interdigital hyperplasia (IH), were scored as binary traits within 200 d after calving and analyzed separately. Incidences of disorders were 13.7% for DD, 16.5% for SU, 9.8% for WD, and 6.7% for IH. Heritabilities of disorders were greater when applying threshold or recursive threshold models than with linear or linear recursive models. Posterior means of genetic correlations between test-day milk production and claw disorders ranged from 0.17 to 0.44, suggesting that breeding strategies focusing on increased milk yield will increase incidences of disorders as a correlated response. A progressive path of lagged relationships was postulated for recursive models describing first the influence of test-day milk yield (MY1) on claw disorders and second, the effect of the disorder on milk production level at the following test day (MY2). In recursive models, structural coefficients describe recursive relationships at the phenotypic level. The structural coefficient λ₂₁ was the gradient of disease (trait 2) with respect to MY1 (trait 1) for a model with a recursive effect of trait 1 on trait 2. The increase of disease incidence of the 4 different disorders per 1-kg increase of MY1 ranged from λ₂₁=0.006 to λ₂₁= 0.024 on the visible scale when applying recursive linear models, and from λ₂₁= 0.003 to λ₂₁= 0.016 on the underlying liability scale for recursive threshold models. The rate of change in MY2 (trait 3) with respect to the previous claw disorder is given by λ₃₂ for a model with a recursive effect from trait 2 to trait 3. Structural coefficients λ₃₂ ranged from −0.12 to −0.68 predicting that a 1-unit increase in the incidence of any disorder reduces milk yield at the following test day by up to 0.67 kg. Rank correlations between sire posterior means for the same claw disorders among different models were >0.84, but some changes in rank of sires in distinct top-10 lists were observed. Structural equation models are of increasing importance in genetic evaluations, and this study showed the possible application of recursive systems, even for categorical data.     

Genetic parameters for female fertility in Nordic Holstein and Red Cattle dairy breeds

Genetic evaluation of female fertility in Danish, Finnish, and Swedish dairy cows was updated in 2015 to multiple-trait animal model evaluation, where heifer and cow fertility up to third parity are considered as separate traits. A model for conception rate was also developed, which required variance component estimation for Nordic Holstein and Nordic Red Dairy Cattle. We used a multiple-trait multiple-lactation sire model to determine variance components for interval from calving to first insemination, length of service period, and conception rate. Monte Carlo Expectation Maximization REML allowed estimation of all 11 traits simultaneously. Study data were sampled from Swedish Holstein (n = 140,040) and Red Dairy Cattle (n = 101,315) heifers and cows. Conception rate observations are binomial observations with various numbers of failures preceding an observation of success. Using a simulation study, we confirmed that including a service number effect into the conception rate model allowed us to model the change in expectation of successful AI with increasing number of services. Heifers outperformed cows in all fertility traits according to the phenotypic means in the records. Heritabilities for the traits varied from 3 to 7% for interval from calving to first insemination, from 1 to 5% for length of service period, and from 1 to 3% for conception rate. Genetic correlations within traits (i.e., between parities) were favorable, ranging from moderate to high; genetic correlations between heifer and cow traits were lower than between cow traits in different parities. Lowest genetic correlations between traits were for interval from calving to first insemination and conception rate, intermediate for interval from calving to first insemination and length of service period, and highest for length of service period and conception rate. The variance components estimated in this study have been used in Nordic fertility breeding value evaluations since 2016.     

Genetic association of clinical mastitis with test-day somatic cell score and milk yield during first lactation of Finnish Ayrshire cows

In this study the genetic association during lactation of 2 clinical mastitis (CM) traits: CM1 (7 d before to 30 d after calving) and CM2 (31 to 300 d after calving) with test-day somatic cell score (SCS) and milk yield (MY) was assessed using multitrait random regression sire models. The data analyzed were from 27,557 first-lactation Finnish Ayrshire cows. Random regressions on second- and third-order Legendre polynomials were used to model the daily genetic and permanent environmental variances of test-day SCS and MY, respectively, while only the intercept term was fitted for CM. Results showed that genetic correlations between CM and the test-day traits varied during lactation. Genetic correlations between CM1 and CM2 and test-day SCS during lactation varied from 0.41 to 0.77 and from 0.34 to 0.71, respectively. Genetic correlations of test-day MY with CM1 and CM2 ranged from 0.13 to 0.51 and from 0.49 to 0.66, respectively. Correlations between CM1 and SCS were strongest during early lactation, whereas correlations between CM2 and SCS were strongest in late lactation. Genetic correlations lower than unity indicate that CM and SCS measure different aspects of the trait mastitis. Milk yield in early lactation was more strongly correlated with both CM1 and CM2 than milk yield in later lactation. This suggests that selection for higher lactation MY through selection on increased milk yield in early lactation will have a more deleterious effect on genetic resistance to mastitis than selection for higher yield in late lactation. The approach used in this study for the estimation of the genetic associations between test-day and CM traits could be used to combine information from traits with different data structures, such as test-day SCS and CM traits in a multitrait random regression model for the genetic evaluation of udder health.     

Genetic selection for health traits using producer-recorded data. II. Genetic correlations, disease probabilities, and relationships with existing traits

The objectives of this study were to calculate genetic correlations between health traits that were recorded in on-farm herd management software programs and to assess relationships between these traits and other traits that are routinely evaluated in US dairy sires. Data consisted of 272,576 lactation incidence records for displaced abomasum (DA), ketosis (KET), mastitis (MAST), lameness (LAME), cystic ovaries (CYST), and metritis (MET) from 161,622 cows in 646 herds. These data were collected between January 1, 2001 and December 31, 2003 in herds using the Dairy Comp 305, DHI-Plus, or PCDART herd management software programs. Binary incidence data for all disorders were analyzed simultaneously using a multiple-trait threshold sire model that included random sire and herd-year-season of calving effects. Although data from multiple lactations were available for some animals, our genetic analysis included only first parity records due to concerns about selection bias and improper modeling of the covariance structure. Heritability estimates for the presence or absence of each disorder during first lactation were 0.14 for DA, 0.06 for KET, 0.09 for MAST, 0.03 for LAME, 0.04 for CYST, and 0.06 for MET. Estimated genetic correlations were 0.45 between DA and KET, 0.42 between KET and CYST, 0.20 between MAST and LAME, 0.19 between KET and LAME, 0.17 between DA and CYST, 0.17 between KET and LAME, 0.17 between KET and MET, and 0.16 between LAME and CYST. All other correlations were negligible. Correlations between predicted transmitting abilities for the aforementioned health traits and existing production, type, and fitness traits were low, though it must be noted that these estimates may have been biased by low reliability of the health trait evaluations. Based on results of this study, it appears that genetic selection for health disorders recorded in on-farm software programs can be effective. These traits can be incorporated into selection indices directly, or they can be combined into composite traits, such as "reproductive disorders", "metabolic disorders", or "early lactation disorders".     

Heritabilities of and genetic correlations among six health problems in Holstein cows

Information from 7712 lactations of Holstein dairy cows was collected from 33 commercial herds around Ithaca, NY in the 3 yr from 1981 to 1983. The data were divided into subsets corresponding to lactation 1, lactation 2, and lactation 3 or greater. To estimate heritabilities of dystocia, retained placenta, metritis, ovarian cysts, milk fever, and mastitis, a mixed linear model (herd-year fixed and sire random effects) with 0 or 1 as the observed response was used. Variance components were estimated using Henderson's Method 3. The results show moderate heritabilities (.15 to .40) for dystocia, metritis, milk fever, and mastitis and low heritability (less than .12) for retained placenta and cystic ovaries. Genetic correlations between dystocia, retained placenta, metritis, and mastitis were moderate in size and positive, whereas cystic ovaries were correlated negatively with dystocia and retained placenta. A general reproductive health trait (dystocia, retained placenta, metritis, cystic ovaries, and milk fever combined in one trait) also was analyzed. The estimated heritability of this trait was .21, .11, and .00 for first calf heifers, second lactation cows, and older cows, respectively.     

Survival analysis applied to genetic evaluation for female fertility in dairy cattle

The objective of this research was to study whether survival analysis results in a more accurate genetic evaluation for female fertility traits compared with the usual methodology based on linear models. The fertility trait studied was interval between calving and last insemination. A stochastic simulation describing the reproductive cycle of first-parity cows was done, in which true breeding values for conception rate were created. A model containing effects of sire and herd was used both with survival analysis and with mixed linear model analysis to predict sire breeding values. Correlations between true breeding values for conception rate and breeding values for calving to last insemination predicted by the best survival analysis model or the best linear model were 0.77 and 0.68, respectively. The results showed that when pregnancy status is known, survival analysis is a better method than linear models for genetic evaluation of conception rate when using observations on the interval between calving and last insemination.     

Phenotypic,genetic, and single nucleotide polymorphism marker associations between calf diseases and subsequent performance and disease occurrences of first-lactation German Holstein cows

A total of 31,396 females born from 2010 to 2013 in 43 large-scale Holstein-Friesian herds were phenotyped for calf and cow disease traits using a veterinarian diagnosis key. Calf diseases were general disease status (cGDS), calf diarrhea (cDIA), and calf respiratory disease (cRD) recorded from birth to 2 mo of age. Incidences were 0.48 for cGDS, 0.28 for cRD, and 0.21 for cDIA. Cow disease trait recording focused on the early period directly after calving in first parity, including the interval from 10 d before calving to 200 d in lactation. For cows, at least one entry for the respective disease implied a score = 1 (sick); otherwise, score = 0 (healthy). Corresponding cow diseases were first-lactation general disease status (flGDS), first-lactation diarrhea (flDIA), and first-lactation respiratory disease (flRD). Additional cow disease categories included mastitis (flMAST), claw disorders (flCLAW), female fertility disorders (flFF), and metabolic disorders (flMET). A further cow trait category considered first-lactation test-day production traits from official test-days 1 and 2 after calving. The genotype data set included 41,256 single nucleotide polymorphisms (SNP) from 9,388 females with phenotypes. Linear and generalized linear mixed models with a logit link-function were applied to Gaussian and categorical cow traits, respectively, considering the calf disease as a fixed effect. Most of the calf diseases were not significantly associated with the occurrence of any cow disease. By trend, increasing risks for the occurrence of cow diseases were observed for healthy calves, indicating mechanisms of disease resistance with aging. Also by trend, occurrence of calf diseases was associated with decreasing milk, protein, and fat yields. Univariate linear and threshold animal models were used to estimate heritabilities and breeding values (EBV) for all calf and cow traits. Heritabilities for cGDS and cRD were 0.06 and 0.07 for cDIA. Genetic correlations among all traits were estimated using linear-linear animal models in a series of bivariate runs. The genetic correlation between cDIA and cRD was 0.29. Apart from the genetic correlation between flRD with cGDS (?0.38), EBV correlations and genetic correlations between calf diseases with all cow traits were close to zero. Genome-wide association studies were applied to estimate SNP effects for cRD and cDIA, and for the corresponding traits observed in cows (flRD and flDIA). Different significant SNP markers contributed to cDIA and flDIA, or to cRD and flRD. The average correlation coefficient between cRD and flRD considering SNP effects from all chromosomes was 0.01, and between cDIA and flDIA was ?0.04. In conclusion, calf diseases are not appropriate early predictors for cow traits during the early lactation stage in parity 1.     

Genetic relationships between persistency and reproductive performance in first-lactation Canadian holsteins

The main objective of this study was to estimate genetic relationships between lactation persistency and reproductive performance in first lactation. Relationships with day in milk at peak milk yield and estimated 305-d milk yield were also investigated. The data set contained 33,312 first-lactation Canadian Holsteins with first-parity reproductive, persistency, and productive information. Reproductive performance traits included age at first insemination, nonreturn rate at 56 d after first insemination as a virgin heifer and as a first-lactation cow, calving difficulty at first calving and calving interval between first and second calving. Lactation persistency was defined as the Wilmink b parameter for milk yield and was calculated by fitting lactation curves to test day records using a multiple-trait prediction procedure. An 8-trait genetic analysis was performed using the Variance Component Estimation package (VCE 5) via Gibbs sampling to estimate genetic parameters for all traits. Heritabilities of persistency, day in milk at peak milk yield and estimated 305-d milk yield were 0.18, 0.09 and 0.45, respectively. Heritabilities of reproduction were low and ranged from 0.03 to 0.19. The highest heritability was for age at first insemination. Heifer reproductive traits were lowly genetically correlated, whereas cow reproductive traits were moderately correlated. Heifers younger than average when first inseminated and/or conceived successfully at first insemination tended to have a more persistent first lactation. First lactation was more persistent if heifers had difficulty calving (r(g) = 0.43), or conceived successfully at first insemination in first lactation (r(g) = 0.32) or had a longer interval between first and second calving (r(g) = 0.17). Estimates of genetic correlations of reproductive performance with estimated 305-d milk yield were different in magnitude, but similar in sign to those with persistency (0.02 to 0.51).     

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.     

Heritabilities and genetic correlations of body condition score and calving interval with yield, somatic cell score, and linear type traits in Brown Swiss cattle

This study aimed to estimate genetic parameters for body condition score (BCS), calving interval (CI), somatic cell score (SCS), yield, and linear type traits for the Italian Brown Swiss cattle population. A total of 32,359 records of first-parity lactating cows were collected from 2002 to 2004 in 4,885 dairy herds. The pedigree file included 96,661 animals. Multiple-trait animal models were analyzed using REML to estimate (co)variance components without repeated observations on traits. The estimated heritability was 0.15 for BCS, 0.05 for CI, and 0.06 for SCS, and ranged from 0.09 to 0.14 for test-day yield traits and from 0.07 to 0.32 for linear type traits. The genetic correlations of CI with yield and most linear type traits were positive, whereas the correlation between CI and BCS was negative (−0.35). For type traits, BCS showed, in general, a moderately negative genetic correlation except for strength, pastern, and heel height. The genetic correlation of CI or BCS with SCS was moderately low but favorable (0.19 and −0.26, respectively). The estimated correlations indicated that selection for greater yield and type traits can exert unfavorable effects on the reproductive ability of cows. To counterbalance these effects and to carry out early prediction of breeding values of bulls for fertility, inclusion of BCS in the breeding program is advisable.