Best linear unbiased prediction of additive genetic merit using a combined-merit sire and dam model for marker-assisted selection

摘要

References(19) Cited-By(4) Herein we develop the sire and dam model counterpart of the combined-merit animal model (CM-AM) method for marker-assisted best linear unbiased prediction (BLUP) of breeding values, and thus for marker-assisted selection. With the current procedure, a specific data-structure, such as that of carcass traits in meat animals, is assumed in order that the solutions may be equivalent to those in the CM-AM method. The resulting system of mixed model equations becomes compact with the total additive genetic merit considered, and with non-parent animal equations absorbed, relative to the CM-AM method. Hence, the current procedure is expected to be useful for marker-assisted BLUP of breeding values for particular quantitative traits, especially in large outbreeding populations with complex pedigrees where the fraction of non-parents is high. A numerical illustration is given using data on carcass weight in beef cattle.