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Genetic evaluation in the presence of uncertain additive relationships. I. Use of phenotypic information to ascertain paternity

R. L. Sapp^*,1, W. Zhang^*, J. K. Bertrand^* and R. Rekaya^*,,2

^* Department of Animal and Dairy Science, and Department of Statistics, University of Georgia, Athens 30602

² Corresponding author: rrekaya{at}uga.edu

A simulation was carried out to investigate the implementation of a genetic evaluation when the additive relationship matrix is not completely known due to the presence of uncertain paternity in the pedigree. Data were simulated and analyzed using a linear mixed model that included a fixed contemporary group effect plus random additive and residual effects. For the univariate scenario, either 1 or 2 records of a single trait with heritabilities of 33, 50, and 67% were used to compute the probability of being the true sire (PTS) of each candidate sire for a given offspring. One record of 3 correlated traits was used to compute PTS in a 3-trait scenario. A Bayesian procedure via Markov Chain Monte Carlo was used to carry out the implementation, in which the PTS was computed without the need to invert the relationship matrix. The average probability of the true sire being identified as such (PSA), as well as the percentage difference (PD) between PSA and an equal prior probability assigned to each candidate sire, were computed for the single and 3-trait scenarios. Using 1 trait, PSA increased with an increase in heritability. When repeated records were considered, the PD was increased by 50 to 386% compared with using just 1 record per animal for the varying heritabilities and number of candidate sires, suggesting that phenotypic information was better able to discriminate among candidate sires when more than 1 record was used to determine PSA. Using 3 correlated traits increased PD by 77 to 98% when compared with using 1 record of a trait with 67% heritability. Similarly, the PD was increased by 105 to 1,021%, when compared with using 1 record of a trait with 33% heritability. These results indicate that the probability of identifying the true sire increased when 3 correlated traits were used to compute PSA. The correlations between true and predicted breeding values of 3 traits were increased by 6 to 7% for all animals and 64 to 89% for animals with unknown paternity in the pedigree when estimated probability of paternity was used as compared with equal prior probability assigned to each candidate sire. For traits such as birth weight and weaning weight, in which only 1 measurement is taken, the 3-trait scenario could result in more animals being assigned the true sire than if birth or weaning weight was used separately. Further research is needed to determine the performance of this methodology in field data as well as the potential implementation of this methodology in conjunction with molecular information.

Key Words: genetic evaluation • paternity testing • relationship matrix • uncertain paternity