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Table 1 Ratios of additive, dominance, and residual of genetic variance component to the total phenotypic variance for different PBLUP and GBLUP models

From: Preselection of QTL markers enhances accuracy of genomic selection in Norway spruce

Model

\({\sigma }_{a}^{2}\)

\({\sigma }_{as}^{2}\)

\({\sigma }_{r}^{2}\)

\({\sigma }_{rs}^{2}\)

\({\overline{\sigma }}_{e}^{2}\)  

\({h}_{i}^{2}\)(SE)

\({H}_{i}^{2}\)(SE)

AIC

HT6

 PBLUP-A

6.48 (0.58)

1.13 (0.30)

  

28.99 (0.48)

0.18 (0.01)

 

43,680.9

 PBLUP-AR

4.44 (1.33)

0.60 (0.23)

0.92 (0.78)

1.36 (0.39)

28.24 (0.50)

0.13 (0.04)

0.15 (0.02)

43,670.3

 GBLUP-A

6.37 (0.56)

1.08 (0.28)

  

29.05 (0.47)

0.17 (0.01)

 

43,672.7

 GBLUP-AR*

4.02 (0.84)

0.62 (0.23)

1.13 (0.49)

1.31 (0.39)

28.24 (0.50)

0.11 (0.02)

0.15 (0.02)

43,656.4

HT12

 PBLUP-A

30.7 (5.0)

   

125.2 (4.0)

0.20 (0.03)

 

16,649.4

 PBLUP-AR

13.0 (5.2)

 

12.5 (4.3)

 

123.6 (4.0)

0.09 (0.03)

0.17 (0.02)

16,646.2

 GBLUP-A

26.6 (4.5)

   

127.0 (4.0)

0.17 (0.03)

 

16,651.1

 GBLUP-AR*

12.9 (4.5)

 

12.28(4.0)

 

123.6 (3.7)

0.09 (0.03)

0.17 (0.02)

16,644.6

DBH

 PBLUP-A

60.0 (5.5)

8.8 (2.8)

  

313.4 (1.9)

0.16 (0.01)

 

64,017.5

 PBLUP-AR

57.4 (5.7)

5.9 (2.6)

0 (0)

8.1 (4.3)

313.8 (5.8)

0.15 (0.01)

0.15 (0.01)

64,017.9

 GBLUP-A

56.8 (5.6)

8.7 (2.7)

  

319.6 (5.3)

0.15 (0.01)

 

64,023.2

 GBLUP-AR*

31.2 (7.3)

6.4 (2.6)

14.8 (4.7)

7.5 (4.3)

313.7 (5.8)

0.09 (0.02)

0.13 (0.01)

64,011.3

PILO

 PBLUP-A

1.78 (0.14)

   

1.51 (0.05)

0.54 (0.02)

 

4583.2

 PBLUP-AR

1.78 (0.14)

 

0 (0)

 

1.51 (0.05)

0.54 (0.02)

 

4585.2

 GBLUP-A

1.73 (0.14)

   

1.53 (0.05)

0.53 (0.02)

 

4580.9

 GBLUP-AR*

1.33 (0.20)

 

0.25 (0.11)

 

1.51 (0.05)

0.43 (0.05)

0.51 (0.02)

4576.9

BB

 PBLUP-A

1.30 (0.07)

0.14 (0.01)

  

0.33 (0.007)

0.73 (0.01)

 

2671.3

 PBLUP-AR

0.98 (0.23)

0.09 (0.02)

0.15 (0.12)

0.04 (0.01)

0.33 (0.007)

0.62 (0.11)

0.71 (0.02)

2667.5

 GBLUP-A

1.25 (0.07)

0.13 (0.01)

  

0.33 (0.007)

0.73 (0.01)

 

2591.5

 GBLUP-AR*

1.05 (0.12)

0.08 (0.02)

0.09 (0.05)

0.04 (0.01)

0.32 (0.007)

0.66 (0.04)

0.72 (0.01)

2579.1

FD

 PBLUP-A

0.014 (0.004)

   

0.201 (0.006)

0.06 (0.02)

 

-1354.3

 PBLUP-AR

0.014 (0.004)

 

0 (0)

 

0.208 (0.006)

0.06 (0.02)

0.06 (0.02)

-1352.3

 GBLUP-A*

0.015 (0.004)

   

0.208 (0.006)

0.07 (0.02)

 

-1357.0

 GBLUP-AR

0.015 (0.005)

 

0 (0)

 

0.208 (0.007)

0.07 (0.02)

0.07 (0.02)

-1355.0

  1. \({\sigma }_{a}^{2}, {\sigma }_{as}^{2}, {\sigma }_{r}^{2}, {\sigma }_{rs}^{2}, {\overline{\sigma }}_{e}^{2}\) represents variances of additive, additive-by-site, residual of genetic, residual of genetic-by-site, and the average of residual effects, respectively. \({h}_{i}^{2}\) and \({H}_{i}^{2}\) represent the narrow-sense and broad-sense heritabilities, respectively. AIC represents the Akaike information criterion. * represents that the model showed the smallest AIC value compared to all other GBLUP and PBLUP models