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Table 3 Relative difference in response to selection with family group composition and random group composition using pedigree-based (\(\overline{{{\varvec{D}}_{{\varvec{A}}} }}\)) and genomic-based (\(\overline{{{\varvec{D}}_{{\varvec{G}}} }}\)) relationships

From: Statistical model and testing designs to increase response to selection with constrained inbreeding in genomic breeding programs for pigs affected by social genetic effects

Scheme Variance components \(\overline{{D_{A} }}\) \(\overline{{D_{G} }}\) Percentage of \(\Delta D_{A\_G} > 0\)
SGM_DGE Estimated 1.016 1.027 24.7
SGM_DGE True 1.047 1.020 96.7
SGM_TBV Estimated 1.103 1.074 96.6
SGM_TBV True 1.075 1.057 94.3
CGM_DGE Estimated 1.080 1.049 97.1
  1. \(\Delta D_{A\_G} = {\raise0.7ex\hbox{${RS_{Fam}^{A} }$} \!\mathord{\left/ {\vphantom {{RS_{Fam}^{A} } {RS_{Ran}^{A} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${RS_{Ran}^{A} }$}} - {\raise0.7ex\hbox{${RS_{Fam}^{G} }$} \!\mathord{\left/ {\vphantom {{RS_{Fam}^{G} } {RS_{Ran}^{G} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${RS_{Ran}^{G} }$}}\), where \(RS_{Fam}^{A}\), \(RS_{Ran}^{A}\), \(RS_{Fam}^{G}\), \(RS_{Ran}^{G}\) are responses to selection (RS) obtained from the bootstrapping procedures for scenarios using group composition of families (Fam) and random (Ran) group composition for the use of pedigree- (\({\mathbf{A}}\)) and genomic-based (\({\mathbf{G}}\)) relationships. The bootstrapping procedures were repeated 5000 times, and \(\overline{{D_{A} }} = \overline{{{\raise0.7ex\hbox{${RS_{Fam}^{A} }$} \!\mathord{\left/ {\vphantom {{RS_{Fam}^{A} } {RS_{Ran}^{A} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${RS_{Ran}^{A} }$}}}}\) and \(\overline{{D_{G} }} = \overline{{{\raise0.7ex\hbox{${RS_{Fam}^{G} }$} \!\mathord{\left/ {\vphantom {{RS_{Fam}^{G} } {RS_{Ran}^{G} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${RS_{Ran}^{G} }$}}}}\) are the averages of the values from the repeated bootstrapping procedures
  2. The comparison between the two relationships was investigated under three breeding schemes: SGM_DGE used a social genetic model (SGM) with selection criteria based on direct genetic values (DGE); SGM_TBV used a SGM with selection criteria based on total breeding values (TBV); and CGM_DGE used the classical genetic model (CGM) with selection criteria based on DGE. Variance components used were true and estimated values. The trait was simulated with an SGE variance of 0.01 and a correlation between SGE and DGE of 0