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Fig. 7 | Genetics Selection Evolution

Fig. 7

From: A deterministic equation to predict the accuracy of multi-population genomic prediction with multiple genomic relationship matrices

Fig. 7

Potential accuracy of predicting the genomic value of individuals from population A under different models: within-population, single \({\mathbf{GRM}}\) (WPSG), within-population, multiple \({\mathbf{GRM}}\) (WPMG), multi-population, single \({\mathbf{GRM}}\) (MPSG), multi-population, multiple \({\mathbf{GRM}}\) (MPMG), in relation to different proportion of genetic variance explained by the causal SNP set. The following assumptions were made: \(M_{e}\) within population \(A\) based on 500 pre-selected causal SNPs (calculated from real genotype data) = 159; \(M_{e}\) across populations \(A\) and \(B\) based on 500 pre-selected causal SNPs (calculated from real genotype data) = 463; \(M_{e}\) within population \(A\) based on 48,412 non- causal SNPs (calculated from real genotype data) = 280; \(M_{e}\) across populations \(A\) and \(B\) based on 48,412 non-causal SNPs (calculated from real genotype data) = 32,970; \(M_{e}\) within population \(A\) based on all 48,912 SNPs (calculated from real genotype data) = 280; \(M_{e}\) across populations \(A\) and \(B\) based on all 48,912 SNPs (calculated from real genotype data) = 33,242; heritability of the trait = 0.3 in both populations; genetic correlation between populations \(A\) and \(B\) = 0.6; proportion of genetic variance explained by all SNPs = 0.8; number of individuals from population \(A\) in the training population = 476; number of individuals from population \(B\) in the training population = 5553

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