# Presentation: 764372

## Genetic correlations between first and later parity calving ease in a sire-maternal grandsire model

*G. R. Wiggans*, C. P. Van Tassell, J. B. Cole, and L. L. M. Thornton*
- Animal Improvement Programs Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350

- INTRODUCTION
- First parity cows have higher incidence of calving difficulty than later parity cows
- In US calving ease evaluations, all parity calvings assumed to be single trait
- Genetic differences may exist between calving difficulty in first and later parities

- OBJECTIVES
- Determine genetic correlation between calving ease in first and later lactations for sire and MGS effects
- Examine if differences warrant multi-trait analysis

- DATA & METHODS
- Five samples of 250,000 from 13,000,000 Holstein calvings since 1980
- Limited to 2,600 most commonly occurring bulls as sire or MGS.
- Scores recorded on 1 to 5 scale (easy to hard)
- Herd-years required to have at least 20 calvings
- Number of herds ranged 721 – 860
- Compared threshold and linear model
- For linear model, scores transformed to linear scale
- Value was the standard normal deviate at midpoint of probability for category
- Probabilities calculated separately by sex of calf and for first and later parity
- Model
- Fixed
- Year-season of calving (two per year starting in April and October)
- Sex of calf within parity (1, 2, 3+)
- Birth year for sire and MGS effects
- Random
- Herd-year
- Sire
- MGS
- Error
- Variance component estimation
- AIREML on transformed scores and Gibbs sampling on original scores

- RESULTS
- Computing:
- AIREML converged quickly
- Gibbs Sampling took >20,000 samples for threshold stabilization
- Estimates:
- Bayesian and AIREML produced comparable genetic correlations between parity effects
- Considerable between sample variation for sire correlations (Table 1)
- Table 1. Genetic correlations between first and later parity calving ease effects
- MGS estimates were lower and more stable
- Avg correlation for MGS of 0.8 suggests substantial genetic differences by parity
- Correlation between traits is moderate and stable between traits (Table 2)
- Table 2. Correlations between sire and MGS effects by parity
- (Co)variance component estimates were slightly different from those currently used in evaluations (Table 3)

| Effect | Sample | Estimation Procedure |  |
| --- | --- | --- | --- |
|  |  | Bayesian | AIREML |
| Sire | 1 | 0.958 | 0.969 |
|  | 2 | 0.881 | 0.840 |
|  | 3 | 0.845 | 0.842 |
|  | 4 | 0.992 | 0.993 |
|  | 5 | 0.992 | 0.941 |
|  | Mean | 0.934 | 0.917 |
|  |  |  |  |
| MGS | 1 | 0.807 | 0.822 |
|  | 2 | 0.793 | 0.815 |
|  | 3 | 0.767 | 0.788 |
|  | 4 | 0.835 | 0.828 |
|  | 5 | 0.773 | 0.778 |
|  | Mean | 0.795 | 0.806 |

|  | Parity | MGS |  |
| --- | --- | --- | --- |
|  |  | 1 | 2+ |
| Sire | 1 | 0.551 | 0.518 |
|  | 2+ | 0.513 | 0.547 |

- RESULTS *(cont.)*
- Table 3. Variances relative to parity 1 residual
- Thresholds lower for later parity which is consistent with lower variance (Table 4)
- Differences in variance by parity combined with correlation of approximately 0.8 indicate value in modeling MGS CE effect separately by parity
- Table 4. Mean thresholds across 5 samples

| Parity | Threshold |  |
| --- | --- | --- |
|  | 3 | 4 |
| 1 | 2.42 ± 0.10 | 3.71 ± 0.18 |
| 2+ | 2.27 ± 0.09 | 3.24 ± 0.12 |

- CONCLUSIONS
- Correlations between first and later parity were high for sire effects, but around 0.8 for MGS
- Variances for later parity groups were less than first parity, especially for MGS
- Evaluations can be improved by treating first and later parities as correlated traits, particularly MGS
- Additional research is needed before implementation of separate genetic effects for first and later parities
- A bivariate threshold model should be considered for national evaluation
- A non-Markov Chain Monte Carlo implementation would be complicated
- A linear model on the transformed scale is possible, but approximations required for linear model may be unacceptable