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Precision of genetic parameters and breeding values estimated in marker assisted BLUP genetic evaluation.

Neuner S, Edel C, Emmerling R, Thaller G, Götz KU - Genet. Sel. Evol. (2009)

Bottom Line: This may result in bias and larger standard errors of the estimated parameters and, as a consequence, reduce the benefits of applying marker-assisted selection.These estimated phenotypes were then used in marker assisted BLUP (MA-BLUP) evaluations where only the genotyped animals and their close relatives were included.Models using YD of cows (bull dams) in addition to DYD of bulls resulted in much smaller standard errors for the estimated variance components.Accuracies of MA-BLUP breeding values for young bull candidates were strongly affected by the inclusion of cow information, but only marginally influenced by pedigree depth and proportions of genotyped animals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bavarian State Research Center for Agriculture, Institute of Animal Breeding, Grub, Germany. Stefan.Neuner@lfl.bayern.de

ABSTRACT
In practical implementations of marker-assisted selection economic and logistic restrictions frequently lead to incomplete genotypic data for the animals of interest. This may result in bias and larger standard errors of the estimated parameters and, as a consequence, reduce the benefits of applying marker-assisted selection. Our study examines the impact of the following factors: phenotypic information, depth of pedigree, and missing genotypes in the application of marker-assisted selection. Stochastic simulations were conducted to generate a typical dairy cattle population. Genetic parameters and breeding values were estimated using a two-step approach. First, pre-corrected phenotypes (daughter yield deviations (DYD) for bulls, yield deviations (YD) for cows) were calculated in polygenic animal models for the entire population. These estimated phenotypes were then used in marker assisted BLUP (MA-BLUP) evaluations where only the genotyped animals and their close relatives were included.Models using YD of cows (bull dams) in addition to DYD of bulls resulted in much smaller standard errors for the estimated variance components. The bias in DYD models was larger than in models including YD. Depth of pedigree had the strongest impact on the standard errors of all the estimated variance components. As expected, estimation of variance components was less precise with larger proportions of animals without genotypes in the pedigree. Accuracies of MA-BLUP breeding values for young bull candidates were strongly affected by the inclusion of cow information, but only marginally influenced by pedigree depth and proportions of genotyped animals.

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Estimated (----) additive genetic variance and variance explained by one QTL in comparison to their simulated (----) parameters when phenotypic information is used for bulls and cows. Phenotypic information corresponds to daughter yield deviations (DYD) of bulls and yield deviations (YD) of cows; Figure 2a presents results for MA-BLUP models with a short depth of pedigrees (see text for details), whereas in Figure 2b deep pedigrees were used for MA-BLUP evaluations.
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Figure 2: Estimated (----) additive genetic variance and variance explained by one QTL in comparison to their simulated (----) parameters when phenotypic information is used for bulls and cows. Phenotypic information corresponds to daughter yield deviations (DYD) of bulls and yield deviations (YD) of cows; Figure 2a presents results for MA-BLUP models with a short depth of pedigrees (see text for details), whereas in Figure 2b deep pedigrees were used for MA-BLUP evaluations.

Mentions: The effect of increasing the depth of the pedigree is summarized in the second and third lines of Table 4. The values of the estimated components are nearly the same whether the short or deep pedigree is applied, but standard errors indicate an increased accuracy for the estimates in the deep pedigree. The graphs in Figure 2 visualize the estimated standard errors. Increasing the pedigree depth reduces notably the variation between the replicates, which can also be seen from the higher LRT.


Precision of genetic parameters and breeding values estimated in marker assisted BLUP genetic evaluation.

Neuner S, Edel C, Emmerling R, Thaller G, Götz KU - Genet. Sel. Evol. (2009)

Estimated (----) additive genetic variance and variance explained by one QTL in comparison to their simulated (----) parameters when phenotypic information is used for bulls and cows. Phenotypic information corresponds to daughter yield deviations (DYD) of bulls and yield deviations (YD) of cows; Figure 2a presents results for MA-BLUP models with a short depth of pedigrees (see text for details), whereas in Figure 2b deep pedigrees were used for MA-BLUP evaluations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2657907&req=5

Figure 2: Estimated (----) additive genetic variance and variance explained by one QTL in comparison to their simulated (----) parameters when phenotypic information is used for bulls and cows. Phenotypic information corresponds to daughter yield deviations (DYD) of bulls and yield deviations (YD) of cows; Figure 2a presents results for MA-BLUP models with a short depth of pedigrees (see text for details), whereas in Figure 2b deep pedigrees were used for MA-BLUP evaluations.
Mentions: The effect of increasing the depth of the pedigree is summarized in the second and third lines of Table 4. The values of the estimated components are nearly the same whether the short or deep pedigree is applied, but standard errors indicate an increased accuracy for the estimates in the deep pedigree. The graphs in Figure 2 visualize the estimated standard errors. Increasing the pedigree depth reduces notably the variation between the replicates, which can also be seen from the higher LRT.

Bottom Line: This may result in bias and larger standard errors of the estimated parameters and, as a consequence, reduce the benefits of applying marker-assisted selection.These estimated phenotypes were then used in marker assisted BLUP (MA-BLUP) evaluations where only the genotyped animals and their close relatives were included.Models using YD of cows (bull dams) in addition to DYD of bulls resulted in much smaller standard errors for the estimated variance components.Accuracies of MA-BLUP breeding values for young bull candidates were strongly affected by the inclusion of cow information, but only marginally influenced by pedigree depth and proportions of genotyped animals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bavarian State Research Center for Agriculture, Institute of Animal Breeding, Grub, Germany. Stefan.Neuner@lfl.bayern.de

ABSTRACT
In practical implementations of marker-assisted selection economic and logistic restrictions frequently lead to incomplete genotypic data for the animals of interest. This may result in bias and larger standard errors of the estimated parameters and, as a consequence, reduce the benefits of applying marker-assisted selection. Our study examines the impact of the following factors: phenotypic information, depth of pedigree, and missing genotypes in the application of marker-assisted selection. Stochastic simulations were conducted to generate a typical dairy cattle population. Genetic parameters and breeding values were estimated using a two-step approach. First, pre-corrected phenotypes (daughter yield deviations (DYD) for bulls, yield deviations (YD) for cows) were calculated in polygenic animal models for the entire population. These estimated phenotypes were then used in marker assisted BLUP (MA-BLUP) evaluations where only the genotyped animals and their close relatives were included.Models using YD of cows (bull dams) in addition to DYD of bulls resulted in much smaller standard errors for the estimated variance components. The bias in DYD models was larger than in models including YD. Depth of pedigree had the strongest impact on the standard errors of all the estimated variance components. As expected, estimation of variance components was less precise with larger proportions of animals without genotypes in the pedigree. Accuracies of MA-BLUP breeding values for young bull candidates were strongly affected by the inclusion of cow information, but only marginally influenced by pedigree depth and proportions of genotyped animals.

Show MeSH
Related in: MedlinePlus