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Partitioning accuracies of breeding values due to additive and dominance effects for a high correlation of LD phase.
Additional file 1: Partitioning accuracies of breeding values due to additive and dominance effects for a high correlation of LD phase.
10.1186/s12711-015-0155-z Partitioning accuracies of breeding values due to additive and dominance effects for Scenario 1 and Scenario 5. 10.1186/s12711-015-0155-z Comparison of Scenario 1 with an additive scenario.
However, when selection in a breed was for purebred performance, accuracies of estimated breeding values due to additive and dominance effects were not very different (e.g. breed B in the reference scenario and scenarios 1 and 3).
Generally, in all scenarios, accuracies of estimated breeding values due to additive effects were greater than accuracies of estimated breeding values due to dominance effects.
The GS_POP-strategy could be performed without separate rearing of families, thereby reducing the bias of estimated breeding values due to common environmental effects and reducing costs related to separate rearing.
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In addition, the DYD describes the genetic value of a bull more accurately than its estimated breeding value due to the adjustment for the daughters' dams [ 18].
A 5k SNP panel appeared to give significantly lower accuracy of breeding value, likely due to insufficient LD, with such large distances between SNPs.
Genomic estimated breeding values were more accurate and showed more within-family variation than parent average breeding values; for genomic estimated breeding values, 30 to 40% of the variation was due to within-family differences.
However, the relatively low financial efforts to obtain estimated genomic breeding values compared to progeny performance testing make it possible to optimise breeding schemes in a holistic across-path approach, which also includes the risk of losing money due to opportunity costs.
Several investigators have advocated the application of hip breeding values to breeding decisions including Ginja et al. [19] most recently.
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