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Table 1 Estimates of variance components from four models of analysis and their proportions relative to the phenotypic variance

From: Genomic prediction using models with dominance and imprinting effects for backfat thickness and average daily gain in Danish Duroc pigs

Trait

Parametera

ADI

AD

AI

A

DG

\(\sigma_{l}^{2}\)

390 ± 81

397 ± 78

400 ± 84

424 ± 84

 

\(\sigma_{a}^{2}\)

803 ± 78

828 ± 74

891 ± 74

896 ± 74

 

\(\sigma_{d}^{2}\)

208 ± 46

225 ± 52

  
 

\(\sigma_{i}^{2}\)

66 ± 23

 

88 ± 24

 
 

\(\sigma_{e}^{2}\)

3093 ± 97

3138 ± 94

3208 ± 95

3248 ± 97

 

\(l^{2}\)

0.086 ± 0.017

0.087 ± 0.019

0.087 ± 0.017

0.093 ± 0.018

 

\(h_{a}^{2}\)

0.176 ± 0.016

0.181 ± 0.015

0.194 ± 0.014

0.196 ± 0.014

 

\(h_{d}^{2}\)

0.046 ± 0.009

0.049 ± 0.009

  
 

\(h_{i}^{2}\)

0.014 ± 0.005

 

0.019 ± 0.004

 
 

\(e^{2}\)

0.678 ± 0.022

0.684 ± 0.022

0.700 ± 0.021

0.711 ± 0.021

BF

\(\sigma_{l}^{2}\)

0.059 ± 0.019

0.066 ± 0.016

0.069 ± 0.018

0.070 ± 0.019

 

\(\sigma_{a}^{2}\)

0.341 ± 0.018

0.342 ± 0.018

0.350 ± 0.018

0.352 ± 0.017

 

\(\sigma_{d}^{2}\)

0.045 ± 0.012

0.046 ± 0.010

  
 

\(\sigma_{i}^{2}\)

0.015 ± 0.005

 

0.015 ± 0.005

 
 

\(\sigma_{e}^{2}\)

0.657 ± 0.023

0.664 ± 0.021

0.677 ± 0.021

0.689 ± 0.021

 

\(l^{2}\)

0.053 ± 0.017

0.059 ± 0.017

0.062 ± 0.019

0.063 ± 0.018

 

\(h_{a}^{2}\)

0.305 ± 0.014

0.306 ± 0.013

0.315 ± 0.013

0.317 ± 0.013

 

\(h_{d}^{2}\)

0.040 ± 0.009

0.041 ± 0.009

  
 

\(h_{i}^{2}\)

0.013 ± 0.005

 

0.015 ± 0.005

 
 

\(e^{2}\)

0.588 ± 0.020

0.594 ± 0.021

0.608 ± 0.020

0.621 ± 0.020

  1. DG, average daily gain; BF, backfat thickness; ADI, full model includes additive, dominance and imprinting effects; AD, model includes additive and dominance effects; AI, model includes additive and imprinting effects; A, model includes the additive effect
  2. aVariance components ± posterior standard deviations (\(\sigma_{l}^{2}\): litter effect, \(\sigma_{a}^{2}\): additive effect, \(\sigma_{d}^{2}\): dominance effect, \(\sigma_{i}^{2}\): imprinting effect, \(\sigma_{e}^{2}\): residual effect) and their proportions to the sum of variance components in the model ± posterior standard deviations (\(l^{2}\): litter effect, \(h_{a}^{2}\): additive genetic, \(h_{d}^{2}\): dominance effect, \(h_{i}^{2}\): imprinting effect, \(e^{2}\): residual effect)