Alternative methods of genetic evaluation which consider uncertain paternity were compared theoretically and through Monte Carlo simulation. Records were simulated for 300 base generation animals and 10 subsequent generations of 100 animals each. Probabilities of paternal uncertainty were either 20 or 50%, heritability was 0.05, 0.25 or 0.50, mating was random with a female-to-male ratio of 5, and selection of breeding animals was either random or by truncation on phenotype. Simulations were replicated 10 times. Differences in expected selection response, for the genetic evaluation methods studied, were largest when heritability was low and degree of paternal uncertainty high. Expected response to selection was maximized in all cases by using uncertain paternity methods instead of genetic grouping or other methods. Advantages over genetic grouping ranged from 0 to 16%. The exclusion of performance records of animals with paternal uncertainty reduced expected selection response by as much as 37%, in addition to the reduction in expected response caused by excluding from selection animals with uncertain parents. All methods that accounted for true or probable paternity, either directly or through genetic groups, yielded unbiased estimates of genetic trends. Key words: Uncertain parentage, numerator relationship matrix, genetic grouping, genetic evaluation, genetic progress, Monte Carlo Simulation
A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models
