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* Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, PO Box 5003, N-1432 Ås, Norway
Geno Breeding and A. I. Association, PO Box 5003, N-1432 Ås, Norway
Division of Genetic Epidemiology, Cancer Research UK Clinical Centre, St Jamess University Hospital, Leeds, LS9 7TF, United Kingdom
Department of Dairy Science, University of Wisconsin, Madison 53706
1 Corresponding author: bjorg.heringstad{at}umb.no
| ABSTRACT |
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Key Words: calving difficulty genetic parameter stillbirth threshold model
| INTRODUCTION |
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Many studies of genetic parameters of stillbirth and calving difficulty have applied linear models (e.g., Luo et al., 1999; Meyer et al., 2001b; Jamrozik et al., 2005), or single-trait threshold models (e.g., Steinbock et al., 2003; Wiggans et al., 2003; Hansen et al., 2004a,b). Gevrekçi et al. (2006) analyzed stillbirth and calving difficulty in multiparous American Holstein cows with a bivariate sire-maternal grandsire threshold model. These authors found direct and maternal heritabilities between 0.04 and 0.07; genetic correlations were 0.77 between direct effects, 0.84 between maternal effects, and close to zero between direct and maternal effects within and across traits.
Calving difficulty and stillbirth have been a part of the total merit index used for selection of Norwegian Red sires since 1978 (Geno, 2006). For these traits, bulls are genetically evaluated as sire of the calf (direct effect) and sire of the dam (maternal effect). In 2006, the relative weight placed on each of these traits in the total merit index was 1% (Geno, 2006). The low relative weight for these traits reflects the low frequencies of stillbirth and calving difficulties in the Norwegian Red population.
The objectives of this study were to infer genetic parameters of calving difficulty and stillbirth using a bivariate sire-maternal grandsire threshold model, and to evaluate phenotypic and genetic change for these traits in the Norwegian Red breed.
| MATERIALS AND METHODS |
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For the genetic analyses, a data set with first-calving records from 1989 to 2004 was extracted. We included only records for which both sire of calf and sire of the cow [i.e., maternal grandsire (mgs) of the calf] were known Norwegian Red AI sires. Records from multiple births, abortions, or with unknown sex of calf (0.7, 0.5, and 0.3% of the records, respectively) were excluded. The data set was further restricted to records with age at first calving between 21 and 34 mo, and from herd-year classes with at least 5 first-lactation cows. The final data set had 528,475 records and a total of 1,548 bulls that were sires, mgs, or both; 85,255 herd-year classes were represented.
Stillbirth was recorded as a binary trait (0 = born alive or 1 = dead at birth or within 24 h), whereas CD had 3 categories (1 = easy calving, 2 = slight problems, and 3 = difficult calving). All calving records had information on SB, and 97.6% had a CD score. For first calving the overall mean frequency of SB was 2.7%, and a total of 92.3% of the cows had easy calving, 5.3% had slight problems, and 2.4% had a difficult calving.
A sire pedigree file with 2,155 individuals was built by tracing the relationships via sires and mgs of the 1,548 bulls with records in the data set, back to 8 generations. A total of 215 males, of which 99% were born before 1980, had unknown sire or mgs, and these represent the base population in this study.
Model
A bivariate sire-mgs threshold liability model (Gianola and Foulley, 1983) was used for analysis of binary SB and of the ordered categorical CD. For each trait, the threshold model postulates an underlying continuous variable, liability (
), such that the observed categorical variable takes value j if Tj1
< Tj, where Tj1 and Tj are thresholds, and j = 1, 2, ..., J indexes the category to which the observation belongs. The thresholds must satisfy
= T0
T1
TJ =
. The threshold T1 was set to zero for each of the traits, because the parameter cannot be identified in a probit analysis. In matrix notation the model fitted can be written as
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where
is a vector of unobserved liabilities to CD and SB; ß is a vector of trait-specific systematic effects, including sex of calf (2 levels), age at first calving in months (14 levels), and month-year of first calving (168 levels) effects; h is a vector of herd-year of calving effects (85,255 levels); u' = [uCD' uSB'] is a vector of effects of the sire (s) and mgs of the calf for CD and SB, with uCD' = [sCD' mgsCD'] and uSB' = [sSB' mgsSB']; e is a vector of residuals, and X, Zh, and Zu are the corresponding incidence matrices. Sire and mgs effects were assumed to be correlated, and to follow the multivariate normal distribution, u
N(0, G0
A), where
![]() |
is the sire-mgs covariance matrix for the 2 traits and A is the matrix of additive genetic relationships among bulls. Effects of different herd-years were assumed to be normally and independently distributed:
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where
is the (co)variance matrix and I is an identity matrix. Residuals were assumed to follow the normal distribution
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where
is the residual (co)variance matrix. The residual variances for the liabilities of each of the categorical traits were set equal to 1 to attain parameter identification. A Bayesian approach using Markov chain Monte Carlo methods (e.g., Sorensen and Gianola, 2002) was implemented.
Prior Distributions.
Independent uniform priors were assigned to each of the elements of ß. As stated above, independent multivariate normal prior distributions were used for herd-year (h) and sire-mgs (u) effects, whereas independent inverse Wishart prior distributions were assigned to H0 and G0, the (co)variance matrices of h and u, respectively. The residual covariance (or correlation),
e1e2, was assigned a uniform bounded (1, 1) prior. The second threshold (T2) for CD was assumed to be distributed, a priori, as an ordered statistic from a uniform distribution, where 0 < T2.
Sampling and Convergence Diagnostics.
Draws from the posterior distributions of the parameters, except for the second threshold for CD and the residual correlation, were obtained using a Gibbs sampler (Sorensen and Gianola, 2002). For cows that did not have data for CD, "missing liabilities" were included in the augmented posterior distribution. The method of Albert and Chib (1997) was used for sampling the threshold, using a Metropolis algorithm, as described by Chang et al. (2006). Based on trace plots and the convergence diagnostics method of Raftery and Lewis (1992), a chain with a total length of 200,000 iterations was run. The first 10,000 samples were discarded as burn-in and all remaining 190,000 samples were kept for posterior inferences. The effective sample size for the parameters was smallest for herd variance for SB (1,310), and varied between 5,429 and 12,667 for heritabilities and genetic correlations. Acceptance rates for the Metropolis algorithms were 41% for the threshold for CD and 25% for the residual correlation.
Direct and Maternal (Co)variances.
Sire (
s2) and mgs (
mgs2) variances and covariance (
s,mgs2) for each trait were converted to direct (D) and maternal (M) genetic (co)variances using the relationship
![]() |
where
D2 and
M2 are direct and maternal additive genetic variances, respectively, and
DM is the additive genetic covariance between direct and maternal effects (Wiggans et al., 2003).
The phenotypic variance was
p2 =
s2 +
s,mgs2 +
mgs2 +
e2 and direct and maternal heritability were calculated as hD2 =
D2/
p2 and hM2 =
M2/
p2, respectively.
Additive genetic covariances between direct and maternal effects between SB and CD were obtained using (Luo et al., 1999):
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For each sample, a check was made that the 4 x 4 covariance matrix of direct and maternal additive genetic effects for the 2 traits was positive definite. All samples had positive determinants.
Norwegian Red
More than 95% of the dairy cows in Norway are Norwegian Red, and the population consists of approximately 280,000 cows, of which 98% participate in the Norwegian Dairy Herd Recording System. All herds participating in the recording system are active in the breeding program, and the best cows in these herds are elite-cows and potential bull-dams. Each year approximately 330 bull-calves from elite sires and elite dams are selected for performance testing. Around 130 of them are selected as test sires, and are progeny tested based on 250 to 300 daughters each. Of these, 10 to 12 are selected as elite sires based on their total merit index and average relationship with the population. About 90% of calves born are sired by Norwegian Red AI sires, 40% by test sires, and 60% by elite sires.
Genetic Evaluation of Sires and Genetic Change
Bulls were evaluated both as sire of calf (direct effect) and as sire of the cow [i.e., mgs of the calf (maternal effect)]. Sire posterior mean (liability scale) was used as genetic evaluation for direct effect, whereas genetic evaluation for maternal effect for sire i (mati) was calculated as mati = m
si 0.5
i where m
si is the posterior mean of mgs effect, and
i is the sire posterior mean for sire i.
Genetic change for direct and maternal effects on the 2 traits was assessed by plotting average sire posterior means against birth year of progeny (direct effect), and average genetic evaluation of maternal effect (mat) by year of calving of daughters. All calving records of the 1,548 sires and mgs were included (about 900,000 first-calving records) for calculation of genetic change. Thus, sires were weighted according to their number of progeny to reflect possible genetic change in the Norwegian Red population.
| RESULTS AND DISCUSSION |
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Although CD is more difficult to compare between populations because the scoring systems vary between countries, the frequency of difficult calving in Norwegian Red (overall mean frequency of 1.5%) is clearly lower than for other breeds. Hansen et al. (2004c) found that the frequency of difficult calving for first-calving Danish Holsteins decreased from 15% in 1985 to 9% in 2002. In Sweden, the mean frequency of difficult calvings in first parity was 4% for SRB and 8% for Holstein (Philipsson et al., 2006). In a study including 404,460 American Holstein cows (all parities), Gevrekçi et al. (2006) reported 73.1% easy calving, 13.2% slight problems, and 13.7% difficult calving (categories included here were "needed assistance" and "considerable force"). In a study of first-lactation Canadian Holstein cows, 19% of the male calves and 13% of the female calves were born with difficulty, where the categories were "hard pull" or "surgery needed" (Luo et al., 1999).
The lower frequency of CD and SB in Norwegian Red than in other breeds agrees with Heins et al. (2006), who compared calving difficulty and stillbirth of pure Holsteins vs. crossbreds. In their study, "Scandinavian Red" included both Norwegian Red and Swedish Red. Calves from Holstein first-calf heifers sired by Scandinavian Red bulls had significantly less calving difficulty (5.5%) and lower stillbirth rate (7.7%) than calves sired by Holstein bulls (16.4% difficult calving and 15.1% stillbirth). Heins et al. (2006) also showed that Scandinavian Red/Holstein crossbred dams had a lower frequency of calving difficulty (3.7%) and stillbirth (5.1%) at first calving than pure Holstein heifers (17.7% difficult calving and 14% stillbirths).
Heritability
Posterior distributions of direct and maternal heritability of liability to SB and CD are given in Figure 3
. For CD, direct heritability had a higher posterior mean (0.13 vs. 0.09) than maternal heritability, whereas for SB, the posterior distributions of direct and maternal heritability were more overlapping, with means of 0.07 and 0.08, respectively. These point estimates are in agreement with other recent threshold model estimates ranging from 0.04 to 0.12 for direct heritability and from 0.07 to 0.13 for maternal heritability for SB (Steinbock et al., 2003; Hansen et al., 2004b; Gevrekçi et al., 2006). Recent threshold model estimates of heritability for CD or calving ease range from 0.06 to 0.17 for direct heritability and from 0.04 to 0.12 for maternal heritability (Luo et al., 2002; Steinbock et al., 2003; Wiggans et al., 2003; Hansen et al., 2004a; Gevrekçi et al., 2006). Linear model estimates of heritability of SB and CD (e.g., Luo et al., 1999; Meyer et al., 2001b; Jamrozik et al., 2005) in general are lower than those obtained from threshold models.
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The lack of a sizable genetic correlation between direct and maternal effects for SB and CD indicates that bulls should be evaluated both as sires and maternal grandsires for these traits. Although large genetic correlations were found between direct effects, as well as between maternal effects, it is evident that SB and CD are not the same trait, and both should be included in the breeding objective for a population.
The correlation between herd-year effects was positive (0.66), whereas the residual correlation between the 2 traits was close to zero (Table 1
). This suggests that herds with low SB frequency tend to have a low rate of dystocia.
Genetic Change
Figure 6
indicates that there has been little or no genetic change in stillbirth at first calving in Norwegian Red, for either direct or maternal effects. For calving difficulty, Figure 7
indicates a slight genetic improvement for direct effect (sire of calf) and little or no genetic change for the maternal effect (sire of cow). These results are in contrast to the unfavorable genetic trends for SB and CD found for first-calving Holsteins. Hansen et al. (2004c) reported unfavorable genetic trends for both direct and maternal effects of stillbirth and for direct effect of CD in the Danish Holstein population, whereas no trend was observed for maternal calving difficulty. In the United States there has been an increasing trend for mean service sire PTA for percentage of difficult calvings for first-calf daughters over the last 10 yr (Van Tassel et al., 2003). Meyer et al. (2001b) reported an annual genetic change of 0.04 and 0.02 for direct and maternal effects for perinatal survival, which is the opposite of stillbirth, for US Holstein bulls born from 1984 to 1994.
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| CONCLUSIONS |
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| ACKNOWLEDGEMENTS |
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Received for publication November 28, 2006. Accepted for publication March 26, 2007.
| REFERENCES |
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. 2006. Bayesian inference for calving ease and stillbirth in Holsteins using a bivariate threshold sire-maternal grandsire model. Proc. 8th WCGALP, Belo Horizonte, Brazil. CD-ROM Commun. no. 0126.This article has been cited by other articles:
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D. P. Berry, J. M. Lee, K. A. Macdonald, and J. R. Roche Body Condition Score and Body Weight Effects on Dystocia and Stillbirths and Consequent Effects on Postcalving Performance J Dairy Sci, September 1, 2007; 90(9): 4201 - 4211. [Abstract] [Full Text] [PDF] |
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