Incorporation of discrete genotype effects for multiple genes into animal model evaluations when only a small fraction of the population has been genotyped.

An efficient algorithm is described for marker-assisted selection appropriate for large populations, even though only a small fraction of the population is genotyped. Genotype probabilities for specific loci are computed for all animals without genotypes. Effects of the quantitative trait loci (QTL) are then estimated by a "cow model" and the appropriate effects are subtracted from the cows' records. Selection is based on genetic evaluations computed from the adjusted records after addition of each animal's QTL genotype effect. The proposed scheme was applied to 10 simulated populations of 37,000 cows generated over 30 yr and compared with a selection scheme based on a standard animal model. Two diallelic QTL with substitution effects of 0.5 and 0.32 phenotypic standard deviations were simulated with initial frequencies of 0.5 for both alleles. Means and standard errors of estimates of the QTL effects at yr 30 were 0.498 +/- 0.011 and 0.347 +/- 0.008. Thus, estimation of the larger QTL was nearly exact, whereas the smaller QTL was slightly overestimated. At yr 9 through 12 after the beginning of the breeding program, genetic gain in the marker-assisted selection scheme was 0.17 standard deviations greater than the standard scheme. This corresponds to nearly 2 yr of genetic progress relative to the standard scheme, or more than 40% of the total genetic gain obtained by the standard scheme at yr 9. Although genetic gain of the 2 schemes was nearly equal by yr 30, the Gibson effect of eventual greater progress by trait-based selection was not observed. Extension of the methods proposed in the current study could be applied to rank sires accurately including both marker and pedigree information for the large number of segregating QTL that will be detected by whole-genome single nucleotide polymorphism scans.