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

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  • Saito Seiko
    Cource of Environmental Management Science
  • Matsuda Hirokazu
    Course of Plant and Animal Sciences, Graduate School of Science and Technology
  • Iwaisaki Hiroaki
    Cource of Environmental Management Science Course of Plant and Animal Sciences, Graduate School of Science and Technology Department of Animal Science, Faculty of Agriculture, Niigata University

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  • Best linear unbiased prediction of addi

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Abstract

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.<br>

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