Understanding cow evaluations in univariate and multivariate animal and random regression models.
The relationship between cow evaluations from a 305-d lactation yield animal model [i.e., lactation model (LM)] and a random regression model (RRM) were studied using the first-lactation milk yield of 2,477,807 Holstein heifers. In the LM analysis, 2 values of heritability were used, 0.35 (LM1-H) or 0.57 (LM2-H), the latter being equal to that used in the random regression model for the analysis of the Holstein test-day records (RRM-H). The relative weights on parent average (PA) and yield deviations (YD) were computed and studied to understand factors contributing to reranking of cows' predicted transmitting abilities (PTA) from the various models. The degree of relatedness and inbreeding were calculated for the top 2,000 cows from the various models. Analyses of Jersey milk yield in the first 3 parities was implemented using 305-d lactation yield multivariate animal (MLM-J) and random regression models (MRRM-J). The ability of both models using only first-parity yield records to predict evaluations in second and third parities when records for these later parities were excluded was studied in a sample of cows. The correlations of cow PTA between LM1-H or LM2-H and RRM-H were 0.91 and 0.92, respectively, in the Holstein data. The data sets used were identical in this case for all models in terms of number of cows and yield records. The correlations were slightly lower at 0.89, 0.87, and 0.88 for parities 1, 2, and 3 in the Jersey analyses, where the data sets were not identical. The relative weights on PA and YD were 0.28 (0.11) and 0.72 (0.89), respectively, from the LM2-H (RRM-H). The RRM-H placed more emphasis on YD and therefore on Mendelian sampling deviations. Thus, the top 2,000 cows from the RRM-H were less related and inbred. The average additive genetic relationship was 22% greater in the LM2-H and average inbreeding coefficients were 0.68 and 0.43% for the LM2-H and RRM-H, respectively. When records were initially available in the first parity, the MRRM-J predicted PTA in parities 2 and 3 with about 2 to 7% greater accuracy compared with the MLM-J.
Mrode
R
R
Scottish Agricultural College, Sir Stephen Watson Building, Penicuik, EH26 0PH, United Kingdom. Raphael.Mrode@sac.ac.uk
Coffey
M
M
D000818:Animals; D001947:Breeding; D002417:Cattle / Q000235:genetics* / Q000502:physiology; D005260:Female; D007774:Lactation; D008892:Milk / Q000378:metabolism; D008957:Models, Genetic; D015999:Multivariate Analysis; D010375:Pedigree; D012044:Regression Analysis