Quantitative traits (which include most production traits in livestock) are generally assumed to be influenced by a few genes with moderate or large effect and a greater number of genes of smaller effect. DNA tests are currently only available for a few of the genes with moderate or large effect. The aggregate effect of the remaining genes is referred to as the residual polygenic breeding value, which will often account for a very substantial proportion of the genetic variance for a trait. Furthermore, with multiple genes affecting each trait and multiple traits affected by most genes, optimizing the relative selection pressure to apply to each DNA test and the residual polygenic component is not a trivial task. The most efficient way to integrate the various sources of information is a combined analysis. The marker-adjusted estimated breeding value (MAEBV) for a trait is the sum of an estimated effect of each DNA test in the analysis plus the estimated residual polygenic breeding value. Although the application of MAEBV is in its infancy, the concept is not new.[2'5]
It may be tempting to try to adjust traditional estimated breeding values (EBVs) for DNA test results. However, if a sire has a large number of progeny with phenotypes, the accuracy of his traditional EBV will be high and it will not differ substantially from his MAEBV because his total genetic merit is already well established and the DNA tests only provide information about which genes contributed to his total merit. On the other hand, a set of young sires (without progeny or phenotypes) that are candidates for progeny testing would have low-accuracy EBVs that are simply the averages of their parents' EBVs; their MAEBVs could differ substantially from their traditional EBVs. The extent to which an EBV differs from a MAEBV depends on a number of factors, so the computation of MAEBVs is best done in a genetic evaluation system that considers all relevant sources of information simultaneously.
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