Nonadditive genetic effects are currently ignored in national genetic evaluations of farm animals because of ignorance of thelevel of dominance variance for traits of interest and the difficult computational problems involved. Potential gains fromincluding the effects of dominance in genetic evaluations include “purification” of additive values and availability ofpredictions of specific combining abilities for each pair of prospective parents. This study focused on making evaluation withdominance effects feasible computationally and on ascertaining benefits of such an evaluation for dairy cattle, beef cattle,and swine. Using iteration on data, computing costs for evaluation with dominance effects included costs could be less thantwice expensive as with only an additive model. With Method Â, variance components could be estimated for problemsinvolving up to 10 millions equations. Dominance effects accounted for up to 10% of phenotypic variance; estimates werelarger for growth traits. As a percentage of additive variance, the estimate of dominance variance reached 78% for 21-d litterweight of swine and 47% for post weaning weight of beef cattle. When dominance effects are ignored, additive evaluationsare “contaminated”; effects are greatest for evaluations of dams in a single large family. These changes in ranking wereimportant for dairy cattle, especially for dams of full-sibs, but were less important for swine. Specific combining abilitiescannot be included in sire evaluations and need to be computed separately for each set of parents. The predictions of specificcombining abilities could be used in computerized mating programs via the Internet. Gains from including the dominanceeffect in genetic evaluations would be moderate but would outweigh expenditures to produce those evaluations
