Evaluation of factors affecting individual assignment precision using microsatellite data from horse breeds and simulated breed crosses

Assignment tests have been utilized to investigate population classification, measure genetic diversity and to solve forensic questions. Using microsatellite data from 26 loci genotyped in eight horse breeds we examined how population differentiation, number of scored loci, number of scored animals per breed and loci variability affected individual assignment precision applying log likelihood methods. We found that both genetic differentiation and number of scored loci were highly important for recognizing the breed of origin. When comparing two and two breeds, a proportion of 95% of the most differentiated breeds (0.200 < or = FST < or = 0.259) could be identified scoring only three loci, while the corresponding number was six for the least differentiated breeds (0.080 < or = FST < or = 0.139). An identical proportion of simulated breed crosses, differentiated from their parental breeds by FST estimates in the range 0.050-0.069, was identified when scoring 12 loci. This level of source identification was not obtained for the less differentiated breed crosses. The current data further suggested that population sample size and locus variability were not critical for the assignment precision as long as moderately large sample sizes (> or = 20 animals per population) and fairly variable loci were used.