Cyclic genotyping strategies. I: A comparison of ranking criteria

This research compares three different indices for ranking animals for genotyping for a single biallelic locus. The indices were designed to predict which animal to genotype in each genotyping cycle in order to maximize the utility of the resulting information across the entire population. In each genotyping cycle, a single animal is genotyped, segregation analysis used to provide genotype probabilities for the loci of ungenotyped animals, and the index applied to determine which animal to genotype in the next cycle. The first index is based on a linear regression model combining seven herd and individual animal attributes, with the remaining two indices based on genotype probability index (GPI) and numerator relationship (CON). The linear model gives superior predictive performance, in terms of utility (herd average GPI) for the initial 5% of the population genotyped. After this point, the best index is (CON)GPI), which combines a high degree of relationship of the animal to all other live animals in the pedigree, with a low GPI.