Estimating genomic breeding values and detecting QTL using univariate and bivariate models
2011
Estimating Genomic Breeding Values and Detecting QTL
publication
Evidence: moderate
Author Information
Author(s): Calus Mario PL, Mulder Han A, Veerkamp Roel F
Primary Institution: Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Lelystad, Netherlands
Hypothesis
What is the added value of multi-trait genomic selection?
Conclusion
Accuracy of estimated breeding values improved for both traits using bivariate compared to univariate models.
Supporting Evidence
- Correlations between estimated breeding values of different SNP based models were greater than 0.93 for the quantitative trait.
- Accuracies of breeding values of bivariate models were up to 0.08 higher than for univariate models.
- The bivariate BayesC model detected 14 out of 32 QTL for the quantitative trait.
- BayesC achieved highest accuracies of EBV and was one of the methods that found most QTL.
Takeaway
This study shows that using multiple traits together helps make better predictions about animal breeding values.
Methodology
Simulated dataset analyzed with four univariate and bivariate linear models to predict breeding values for juvenile animals.
Limitations
The study primarily used simulated data, which may not fully represent real-world scenarios.
Digital Object Identifier (DOI)
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