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Table 3 Mean reliability and bias of estimated breeding value (EBV) and genomic EBV (GEBV) for SRS survival DAYS and STATUS with their standard errors (±SE) using pedigree based and genomic models

From: Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar)

Modelsa

Trait

Days

Status

Reliability ± SE b

Bias ± SE c

Reliability ± SE

Bias ± SE

PBLUP

0.342 ± 0.080

0.960 ± 0.146

0.201 ± 0.038

0.304 ± 0.042

GBLUP

0.414 ± 0.065

0.949 ± 0.097

0.256 ± 0.026

0.276 ± 0.026

SNPBLUP

0.429 ± 0.069

1.026 ± 0.110

0.256 ± 0.032

1.365 ± 0.096

PSNPBLUP

0.368 ± 0.069

0.814 ± 0.097

0.256 ± 0.039

0.798 ± 0.073

BAYESC

0.424 ± 0.066

0.961 ± 0.098

0.261 ± 0.026

0.287 ± 0.028

PBAYESC

0.389 ± 0.071

0.916 ± 0.106

0.256 ± 0.031

0.294 ± 0.029

BLASSO

0.424 ± 0.066

0.955 ± 0.097

0.262 ± 0.026

0.287 ± 0.026

PBLASSO

0.390 ± 0.072

0.937 ± 0.112

0.256 ± 0.029

0.285 ± 0.033

  1. aModels with pedigree: pedigree based BLUP (PBLUP), genomic BLUP (GBLUP), marker-effects BLUP with polygenic pedigree (PSNPBLUP) and Bayesian estimation methods with marker-effects and polygenic pedigree (PBAYESC and PBLASSO); Models with only marker-effects: market-effects BLUP (SNPBLUP) and Bayesian estimation methods (BAYESC and BLASSO)
  2. bThe effective number of SNPs used was 49 684 from the 50 K SNP array
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BMC Genomics

ISSN: 1471-2164

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