Table 4 Results^a of genomic prediction of the three traits using Bayesian BLUP or mixture models, according to number of main SNP effects

1000

0.347 (-0.124)

0.396 (-0.181)

0.356 (0.060)

0.334 (0.040)

0.319 (0.028)

0.318 (0.085)

2000

0.376 (-0.115)

0.409 (-0.174)

0.364 (0.055)

0.333 (0.056)

0.333 (0.026)

0.346 (0.054)

3000

0.400 (-0.107)

0.413 (-0.171)

0.348 (0.016)

0.359 (0.008)

0.345 (0.009)

0.359 (0.033)

4000

0.410 (-0.107)

0.422 (-0.164)

0.359 (0.026)

0.370 (0.012)

0.348 (0.008)

0.368 (0.019)

5000

0.417 (-0.102)

0.426 (-0.160)

0.368 (0.035)

0.375 (0.022)

0.358 (0.002)

0.371 (0.012)

6000

0.422 (-0.102)

0.430 (-0.161)

0.367 (0.026)

0.376 (0.028)

0.358 (0.009)

0.373 (0.016)

7000

0.423 (-0.108)

0.435 (-0.155)

0.369 (0.031)

0.378 (0.034)

0.363 (0.006)

0.374 (0.006)

8000

0.426 (-0.106)

0.437 (-0.143)

0.373 (0.041)

0.384 (0.044)

0.366 (0.003)

0.378 (0.002)

9000

0.425 (-0.103)

0.440 (-0.136)

0.373 (0.035)

0.384 (0.037)

0.368 (0.008)

0.376 (0.009)

10 000

0.428 (-0.100)

0.441 (-0.137)

0.376 (0.040)

0.389 (0.054)

0.369 (0.006)

0.375 (0.011)

20 000

0.427 (-0.101)

0.446 (-0.122)

0.384 (0.048)

0.384 (0.033)

0.372 (0.012)

0.382 (0.003)

30 000

0.427 (-0.111)

0.448 (-0.116)

0.384 (0.048)

0.388 (0.048)

0.372 (0.018)

0.386 (0.006)

40 000

0.427 (-0.108)

0.446 (-0.114)

0.383 (0.043)

0.390 (0.043)

0.373 (0.008)

0.384 (0.003)

50 000

0.424 (-0.121)

0.447 (-0.115)

0.385 (0.051)

0.387 (0.044)

0.375 (0.008)

0.383 (0.006)

492 057

0.429 (-0.120)

0.447 (-0.127)

0.389 (0.057)

0.390 (0.057)

0.372 (0.005)

0.378 (0.005)

Indiv. SNP

0.423 (-0.122)

0.439 (-0.122)

0.384 (0.059)

0.383 (0.048)

0.368 (0.069)

0.373 (0.026)

approach