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Table 5 Estimates of substitution effects and regression coefficients for predicting generation 8 phenotypes from training in ancestral generations (G1 to G7) for SNP rs14491030 using BayesB or a single SNP model in ASReml

From: Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions

Training generation

BayesBa

Single SNP animal modelb

Effect

Regressionc

Effect

Regressionc

G1-G7

2.55

1.55

3.05

1.53

G1

0.51

2.51

2.62

1.78

G2

1.13

4.05

2.64

1.77

G3

1.54

2.98

2.83

1.65

G4

2.64

1.77

2.96

1.58

G5

1.69

2.72

3.29

1.42

G6

1.51

2.33

4.05

1.15

G7

0.46

1.74

3.81

1.23

Averaged

1.50

2.46

3.16

1.51

  1. aThe effect of the most significant marker in the 1 Mb window with the largest variance
  2. bMost significant marker fitted as a fixed effect in an animal model using ASReml
  3. cRegression of hatch-adjusted phenotype on predicted merit using the estimate of the SNP effect
  4. dAverage of the 7 individual generation results
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Journal of Animal Science and Biotechnology

ISSN: 2049-1891