Table 1.

Accuracy of genomic prediction for BCWD survival DAYS in rainbow trout

Modela	Training sample				Testing sample
	Phenotyped fish	Genotyped fish	Effective SNPs	$h^2$ b	Genotyped fish	Predictive abilityc	Biasd
P-BLUP	7893	0	0	0.37	0	0.34	0.86
ssGBLUP	7893	1473	35,636	0.33	930	0.63	0.99
wssGBLUP2	7893	1473	35,623	0.33	930	0.67	0.71
wssGBLUP3	7893	1473	35,623	0.33	930	0.65	0.65
BayesB	1473	1473	35,636	0.23	930	0.71	1.16

^aThe estimated breeding values (EBV) were estimated with a pedigree-based animal model (P-BLUP); and the genomic EBV (GEBV) were estimated with three genomic selection (GS) models: single-step GBLUP (ssGBLUP), weighted ssGBLUP (wssGBLUP) and Bayesian method BayesB. The wssGBLUP2 and wssGBLUP3 corresponds to iteration 2 and 3, respectively

^bFor the GS models, $h^2$ is the proportion of phenotypic variance explained by the markers. For the P-BLUP model, $h^2$ is the trait narrow-sense heritability estimated from pedigree and phenotypic records

^cThe predictive ability of EBV $\left(P{A}_{EBV}\right)$ or GEBV $\left(P{A}_{GEBV}\right)$ was defined as the correlation of mid-parent EBV or GEBV with MPP from each PTF: $P{A}_{EBV}=CORR\left(MPP,MidparentEBV\right)$; $P{A}_{GEBV}=CORR\left(MPP,MidparentGEBV\right)$

^dThe bias of EBV $\left(Bia{s}_{EBV}\right)$ or GEBV $\left(Bia{s}_{GEBV}\right)$ was defined as the regression coefficient of performance MPP on predicted mid-parent EBV or GEBV: $Bia{s}_{EBV}=REGRES\left(MPP,MidparentEBV\right);Bia{s}_{GEBV}=REGRES\left(MPP,MidparentGEBV\right)$