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Joint genomic evaluation of cows and bulls with BayesD for prediction of genotypic values and dominance deviations

Monday, August 18, 2014: 4:00 PM
Bayshore Grand Ballroom D (The Westin Bayshore)
Robin Wellmann , Institute of Animal Husbandry and Breeding, University Hohenheim, Stuttgart, Germany
Johann Ertl , Bavarian State Research Center for Agriculture, Institute of Animal Breeding, Grub, Germany
Reiner Emmerling , Bavarian State Research Center for Agriculture, Institute of Animal Breeding, Grub, Germany
Christian Edel , Bavarian State Research Center for Agriculture, Institute of Animal Breeding, Grub, Germany
Kay-Uwe Götz , Bavarian State Research Center for Agriculture, Institute of Animal Breeding, Grub, Germany
Jörn Bennewitz , Institute of Animal Husbandry and Breeding, University Hohenheim, Stuttgart, Germany
Recorded Presentation (flv)
Abstract Text:

The inclusion of dominance effects into models for genomic selection enables the utilization of non-additive genetic variance in mate selection programs. Usually, only genotyped individuals with own phenotypes are used for prediction. This study investigated whether the accuracies of genotypic values, dominance deviations, and breeding values can be increased by a joint evaluation of genotyped individuals with phenotyped offspring and with own phenotypic records. Daughter yield deviations for fat yield from 6,858 Fleckvieh bulls and yield deviations from 1,986 cows were used to estimate marker effects of 629,028 loci with BayesD.  The correlation between estimated genotypic values (EGV) and yield deviations (YD) increased by a joint evaluation of cows and bulls. BayesD2 with a moderately heavy tailed distribution of marker effects provided the highest correlation between EGV and YD (0.398), which was 0.027 larger than for G-BLUP with dominance. 

Keywords:

BayesD

Genomic selection

Prediction of genotypic values

See more of: Improving accuracy of genomic prediction
See more of: Genetic Improvement Programs: Selection using molecular information
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