Table 2.

Accuracies of genomic prediction for the phenotypic values and true genetic values of teat number using 41,108 autosomal SNPs on 2936 Duroc boars in a tenfold validation study

Model and accuracy change	${\widehat{\text{R}}}_{0\text{tp}}=\text{corr}\left({\widehat{\text{g}}}_{0\text{j}},{\text{y}}_0\right)$	${\text{R}}_{0\text{jp}}={\text{R}}_{0\text{j}}\sqrt{{\text{h}}_{\text{j}}^2}$	${\text{R}}_{0\text{j}}=\text{corr}\left({\widehat{\text{g}}}_{0\text{j}},{\text{g}}_{0\text{j}}\right)$
Model 1A	${\widehat{\text{R}}}_{0\text{tp}}$ = 0.437 ± 0.064	${\text{R}}_{0\text{tp}}$ = 0.460	${\text{R}}_{0\text{t}}$ = 0.728 ± 0.004
Model 1B	${\widehat{\text{R}}}_{0\text{tp}}$ = 0.279 ± 0.076	${\text{R}}_{0\text{tp}}$ = 0.360	${\text{R}}_{0\text{t}}$ = 0.661 ± 0.007
$-{\text{c}}_{\text{ri}}$ of 1B relative to 1A	−36.16%	−21.74%	−9.20%
Model 2A	${\widehat{\text{R}}}_{0\mathrm{\alpha }\text{p}}$ = 0.435 ± 0.064	${\text{R}}_{0\mathrm{\alpha }\text{p}}$ = 0.425	${\text{R}}_{0\mathrm{\alpha }}$ = 0.700 ± 0.007
Model 2B	${\widehat{\text{R}}}_{0\mathrm{\alpha }\text{p}}$ = 0.275 ± 0.074	${\text{R}}_{0\mathrm{\alpha }\text{p}}$ = 0.320	${\text{R}}_{0\mathrm{\alpha }}$ = 0.624 ± 0.009
$-{\text{c}}_{\text{ri}}$ of 2B relative to 2A	−36.78%	−24.70%	−10.86%
Model 3A	${\widehat{\text{R}}}_{0\text{tp}}$ = 0.426 ± 0.066	${\text{R}}_{0\text{tp}}=0.446$	${\text{R}}_{0\text{t}}$ = 0.721 ± 0.004
$-{\text{c}}_{\text{ri}}$ of 3A relative to 1A	−2.52%	−3.04%	−0.96%
Model 4A	${\widehat{\text{R}}}_{0\mathrm{\alpha }\text{p}}=0.424\pm 0.066$	${\text{R}}_{0\mathrm{\alpha }\text{p}}=0.409$	${\text{R}}_{0\mathrm{\alpha }}=0.691\pm 0.007$
$-{\text{c}}_{\text{ri}}$ of 4A relative to 2A	−2.53%	−3.76%	−1.28%

Model 1A has additive and dominance effects and uses all 41,108 autosome SNPs. Model 1B is a modification of Model 1A by using the 85 significant SNPs as fixed non-genetic effects. Model 2A has additive effects only and uses all 41,108 autosome SNPs. Model 2B is a modification of Model 2A by using the 85 significant SNPs as fixed non-genetic effects. Model 3A has additive and dominance effects and uses 41,023 autosomal SNPs after removing the 85 significant SNPs. Model 4A has additive effects only and uses 41,023 autosomal SNPs after removing the 85 significant SNPs. ${\widehat{\text{R}}}_{0\text{jp}}$ is the observed accuracy of predicting phenotypic values from tenfold validations. ${\text{R}}_{0\text{jp}}$ is the expected accuracy of predicting phenotypic values. ${\text{R}}_{0\text{j}}$ is the expected accuracy of predicting genetic values calculated by GVCBLUP from tenfold validations, $\text{j}=\text{t}\text{or}\mathrm{\alpha }$. ${\text{h}}_{\text{t}}^2$ = 0.400 for Model 1A, = 0.297 for Model 1B, = 0.382 for Model 3. ${\widehat{\text{h}}}_{\mathrm{\alpha }}^2$ = 0.368 for Model 2A, 0.263 for Model 2B, = 0.350 for Model 4. $-{\text{c}}_{\text{ri}}$ is the decrease in accuracy