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Table 3 Performance of ssGBLUPa in the subsequent evaluations in the sire line (SE in brackets)

From: Impact of genomic preselection on subsequent genetic evaluations with ssGBLUP using real data from pigs

Measure/preselection scenario

With records on animals in the validation generation

Without records on animals in the validation generation

Referenceb

VGPc

MGPd

Reference

VGP

MGP

Average daily gain during performance testing, size of validation population = 1382

 Estimated heritabilitye

0.24 (0.01)

0.25 (0.01)

0.33 (0.02)

0.24 (0.01)

0.24 (0.01)

0.35 (0.03)

 Validation accuracyf

0.51 (0.02)

0.51 (0.02)

0.50 (0.02)

0.47 (0.02)

0.47 (0.02)

0.44 (0.02)

 Level biasg

− 0.09 (0.02)

− 0.15 (0.02)

− 0.01 (0.02)

− 0.11(0.02)

− 0.11(0.02)

− 0.02 (0.02)

 Dispersion biash

0.48 (0.02)

0.49 (0.02)

0.48 (0.02)

0.48 (0.02)

0.48 (0.02)

0.46 (0.03)

Average daily gain throughout life, size of validation population = 1383

 Estimated heritability

0.26 (0.01)

0.28 (0.01)

0.33 (0.03)

0.27 (0.01)

0.27 (0.01)

0.35 (0.03)

 Validation accuracy

0.57 (0.02)

0.56 (0.02)

0.55 (0.02)

0.52 (0.02)

0.52 (0.02)

0.48 (0.02)

 Level bias

− 0.10 (0.02)

− 0.17 (0.02)

− 0.06 (0.02)

− 0.14 (0.02)

− 0.14 (0.02)

− 0.08 (0.02)

 Dispersion bias

0.48 (0.02)

0.49 (0.02)

0.50 (0.02)

0.47 (0.02)

0.47 (0.02)

0.49 (0.02)

Backfat thickness, size of validation population = 1383

 Estimated heritability

0.58 (0.01)

0.58 (0.01)

0.58 (0.02)

0.58 (0.01)

0.58 (0.01)

0.60 (0.03)

 Validation accuracy

0.69 (0.01)

0.68 (0.01)

0.67 (0.01)

0.63 (0.02)

0.63 (0.02)

0.56 (0.02)

 Level bias

− 0.02 (0.01)

− 0.03 (0.01)

− 0.03 (0.01)

− 0.05 (0.01)

− 0.05 (0.01)

− 0.09 (0.01)

 Dispersion bias

0.48 (0.01)

0.47 (0.01)

0.47 (0.01)

0.44 (0.01)

0.44 (0.01)

0.42 (0.02)

Loin depth, size of validation population = 1383

 Estimated heritability

0.55 (0.01)

0.55 (0.01)

0.55 (0.03)

0.55 (0.01)

0.55 (0.01)

0.57 (0.03)

 Validation accuracy

0.68 (0.01)

0.67 (0.01)

0.65 (0.02)

0.62 (0.02)

0.62 (0.02)

0.54 (0.02)

 Level bias

0.01 (0.01)

0.00 (0.01)

0.00 (0.01)

0.00 (0.01)

0.00 (0.01)

− 0.01 (0.01)

 Dispersion bias

0.50 (0.01)

0.50 (0.01)

0.48 (0.02)

0.48 (0.02)

0.48 (0.02)

0.45 (0.02)

  1. aSingle-step genomic best linear unbiased prediction
  2. bIn the reference scenario, the subsequent ssGBLUP evaluation used the entire available data until the validation generation
  3. cValidation generation preselection (VGP) scenario, in which all animals in the validation generation without progeny in the data were discarded
  4. dMulti-generation preselection (MGP) scenario, in which all animals in the validation and training generations without progeny in the data were discarded
  5. eThe heritability was estimated from an equivalent pedigree-based animal model in ASReml
  6. fValidation accuracy was computed as weighted Pearson’s correlation coefficient between progeny yield deviation and genomic estimated breeding value of all validation animals
  7. gLevel bias was computed as the weighted mean difference between progeny yield deviation and half of the genomic estimated breeding value across all validation animals, expressed in additive genetic standard deviation units of the trait
  8. hDispersion bias was measured by the weighted regression coefficient of progeny yield deviation on genomic estimated breeding value of all validation animals