\(r_{{u_{DS} }}\) | \({\mathbf{A}}\) | \({\mathbf{G}}\) |
---|
SGM_DGE | SGM_TBV | CGM_DGE | SGM_DGE | SGM_TBV | CGM_DGE |
---|
Accuracy of GESC |
 − 0.5 | 0.201 | 0.318 | 0.204 | 0.244 | 0.437 | 0.269 |
 0 | 0.347 | 0.430 | 0.341 | 0.449 | 0.556 | 0.436 |
 0.5 | 0.481 | 0.504 | 0.457 | 0.614 | 0.656 | 0.596 |
Accuracy of DGE |
 − 0.5 | 0.582 | 0.623 | 0.588 | 0.770 | 0.811 | 0.774 |
 0 | 0.583 | 0.604 | 0.580 | 0.768 | 0.792 | 0.765 |
 0.5 | 0.580 | 0.586 | 0.577 | 0.765 | 0.777 | 0.764 |
Bias of GESC |
 − 0.5 | 0.39 | 1.00 | 0.39 | 0.38 | 0.98 | 0.41 |
 0 | 0.92 | 1.01 | 0.94 | 0.94 | 0.99 | 0.93 |
 0.5 | 1.54 | 1.05 | 1.50 | 1.52 | 1.00 | 1.51 |
Bias of DGE |
 − 0.5 | 0.99 | 0.99 | 0.97 | 1.00 | 1.01 | 0.97 |
 0 | 0.98 | 0.99 | 1.01 | 0.99 | 1.00 | 1.00 |
 0.5 | 0.99 | 1.00 | 1.02 | 0.99 | 1.00 | 1.02 |
- Accuracy of predicted genetic effects of selection criteria (GESC) was calculated as the correlation between GESC and true TBV. Bias of GESC was the regression coefficient of true values of TBV on predicted values of GESC
- SGM_DGE used a social genetic model (SGM) with selection criteria based on direct genetic values (DGE); SGM_TBV used a SGM with selection criteria based on total breeding values (TBV); and CGM_DGE used the classical genetic model (CGM) with selection criteria based on DGE. Breeding schemes used either pedigree- (\({\mathbf{A}}\)) or genomic-based (\({\mathbf{G}}\)) relationships to predict genetic effects. The three breeding schemes were compared by making different assumptions for the trait simulated with SGE variance (\(\sigma_{{u_{S} }}^{2}\)) of 0.01 and correlation (\(r_{{u_{DS} }}\)) between SGE and DGE at − 0.5, 0, and 0.5. Group members were allocated at random. Accuracy and bias of predicted genetic effects were computed based on animals at generation \(t\) = 4