Page 206 - Linear Models for the Prediction of Animal Breeding Values 3rd Edition

Table 11.3. Mean and SNP effects from
SNP-BLUP model with polygenic effects.

Mean effects
9.940
SNP effects
1 0.078
2 −0.280
3 0.234
4 −0.075
5 0.098
6 0.128
7 0.000
8 0.000
9 −0.054
10 −0.018

Table 11.4. Direct genomic breeding values from models with polygenic effects.

SNP-BLUP model GBLUP
Polygenic DGV Polygenic DGV
Reference animals
13 0.011 0.066 0.011 0.064
14 −0.007 0.102 −0.007 0.106
15 0.043 0.071 0.043 0.074
16 0.076 0.299 0.076 0.305
17 −0.015 −0.473 −0.015 −0.477
18 −0.025 −0.343 −0.025 −0.345
19 −0.021 0.115 −0.021 0.115
Selection candidates
20 −0.056 −0.254 −0.056 −0.260
21 0.005 0.028 0.005 0.029
22 −0.006 0.102 −0.006 0.102
23 −0.004 −0.220 −0.004 −0.220
24 −0.008 0.125 −0.008 0.125
25 −0.003 0.051 −0.003 0.051
26 −0.006 0.316 −0.006 0.315

The mean solution from solving Eqn 11.16 was 9.940. The DGVs for the reference
and validation populations from both sets of MME are given in Table 11.4. As
expected, Eqns 11.14 and 11.16 gave similar results, but for this example, the inclusion
of 10% polygenic effects decreased the range of SNP solutions slightly but increased
the range for DGVs.

11.7 Single-step Approach

Since the genomic predictions are usually based on a subset of data used for national
evaluation, the DGV are usually combined with some measure of conventional breeding
values to incorporate additional information in the conventional evaluations.

190 Chapter 11