Estimation of accuracy and bias in genetic evaluations with genetic groups using sampling

¹ Animal Breeding and Genomics Centre, Animal Sciences Group, PO Box 65, 8200 AB, Lelystad, the Netherlands; Grange Beef Research Centre, Teagasc, Dunsany, Co. Meath, Ireland; School of Agriculture, Food and Veterinary Medicine, College of Life Sciences, University College Dublin, Belfield, Dublin 4, Ireland
² Grange Beef Research Centre, Teagasc, Dunsany, Co. Meath, Ireland
³ School of Agriculture, Food and Veterinary Medicine, College of Life Sciences, University College Dublin, Belfield, Dublin 4, Ireland
⁴ Irish Cattle Breeding Federation, Shinagh House, Bandon, Co. Cork, Ireland
⁵ Animal Breeding and Genomics Centre, Animal Sciences Group, PO Box 65, 8200 AB, Lelystad, the Netherlands

^* To whom correspondence should be addressed. E-mail: John.Hickey{at}wur.nl.

	Abstract

Accuracy and bias of estimated breeding values are important measures of the quality of genetic evaluations. A sampling method that accounts for the uncertainty in the estimation of genetic group effects was used to calculate accuracy and bias of estimated effects. The method works by repeatedly simulating phenotypes for multiple traits for a defined data and pedigree structure. These simulated values are analysed using BLUP with genetic groups in the relationship matrix. Accuracies and biases are then calculated as correlations among and differences between true and estimated values across all replicates, respectively. The method was applied to the Irish beef production data set for 15 traits and with 15 genetic groups to account for differences in breed means. Accuracy and bias of estimated genetic groups effects, estimated comparisons between genetic groups effects, estimated breeding values within genetic group, and estimated breeding values across genetic group were calculated. Small biases were detected for most estimated genetic group effects and most estimated comparisons between genetic group effects. Most of these were not of importance relative to the phenotypic standard deviation of the traits involved. For example, a bias of 0.78% of the phenotypic standard deviation was detected for carcass conformation in Aberdeen Angus. However, one trait, calf quality, which has very few performance records in the data set, displayed larger bias ranging from -10.31% to 5.85% of the phenotypic standard deviation across the different estimated genetic group effects. Large differences were observed in the accuracies of genetic group effects, ranging from 0.02 for feed intake in Holstein, which had no data recorded, to >0.97 for carcass conformation, a trait with large amounts of data recorded in the different genetic groups. Large differences were also observed in the accuracies of the comparisons among genetic group effects. The accuracies of the estimated breeding values within genetic group and estimated breeding values across genetic group were sometimes different; for example, carcass conformation in Belgian Blue had an average accuracy within genetic group of 0.69 compared to an average accuracy across genetic group of 0.89. This suggests that the accuracy of genetic groups should be taken into account when publishing estimated breeding values across genetic groups.

Key Words: accuracy, bias, data quality, genetic groups, multiple breed genetic evaluations