Genomic selection (GS) is a kind of SNP (single nucleotide polymorphisms) marker-assisted selection that when in linkage disequilibrium, explores all potentials quantitative trait loci (QTL) of the genome. The heritability, genome size, effective size of the population and level of inbreeding can change the accuracy of direct genomic breeding values. The breeding value obtained from the estimated markers effects is called direct genomic breeding value, while the combination of the direct genomic breeding value with the estimated breeding value is called genomic breeding value. The objective of this study will be to estimate the breeding value, the direct genomic breeding value and the correlation between them (accuracy) of simulated phenotypic and genotypic data of White Leghorn hens in linkage disequilibrium. The simulated scenarios will include different traits with distinct heritabilities (production and weight of eggs) and distinct levels of endogamy. Two scenarios will be created from a simulated historical population in order to generate linkage disequilibrium and genetic drift. In each scenario, the total egg rate from the 17th week to the 70th week of age and egg weight at 32 weeks of age traits will be simulated. The mating system will have distinct inbreeding approaches, one of them will be at random (no inbreeding control) and the other minimizing the inbreeding. The true genetic breeding value of each individual will be considered as the sum of the additive QTL effects the simulation will generate. The estimated breeding values will be obtained by restricted maximum likelihood method. A ridge regression model will be used to estimate the SNP markers effect in the computation of the direct genomic breeding value. The Spearman correlation coefficient between the direct genomic breeding values and the true genomic breeding values and the accuracies will be used to comparing the simulated scenarios.
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