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In genomic selection, dense genome-wide markers are used to estimate genomic breeding values based on marker effects across the entire genome.
Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.
In cattle, Harris et al. (2008) used PB populations (Holstein-Friesian and Jersey) to predict the genomic breeding values of a cross between these two breeds.
Genomic selection (GS) is a method for predicting genomic breeding values using molecular markers covering the whole genome [ 1- 3].
Therefore, both of them were recommended for predicting genomic breeding values.
To measures accuracy of prediction, Pearson's correlation between the true and predicted genomic breeding values (rp,t) was estimated.
For most schemes it was assumed that the reliability of genomic breeding values (GEBV) was 0.6 across 4 pathways of selection.
Such a small proportion of phenotyped cows was sufficient to predict reliable genomic breeding values for cows without phenotypes for extreme THI.
Most studies that predict the gain by implementing genomic selection apply a deterministic approach that requires assumptions about the accuracy of the genomic breeding values.
Genomic breeding values are calculated using the same approach as window breeding values but utilized every SNP in the genome.
Several models to estimate genomic breeding values have been studied.
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