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Table 4 Accuracy of genomic prediction for production traits using different reference populations to predict 270 younger individuals of the LM population

From: Using imputation-based whole-genome sequencing data to improve the accuracy of genomic prediction for combined populations in pigs

Reference seta (size of reference population) Method Trait
AGE BFT
LM (1499) GBLUP_80K 0.625 0.432
GBLUP_WGS 0.633 0.436
GBLUP_LD 0.642 0.445
GFBLUP_QTL 0.642 0.444
GFBLUP_GWAS 0.640 0.444
ssGBLUP_80K 0.739 0.677
ssGBLUP_WGS 0.738 0.663
ssGBLUP_LD 0.745 0.671
LM+ZX (1819) GBLUP_80K 0.615 0.431
GBLUP_WGS 0.636 0.443
GBLUP_LD 0.648 0.454
GFBLUP_QTL 0.638 0.443
GFBLUP_GWAS 0.635 0.452
ssGBLUP_80K 0.737 0.677
ssGBLUP_WGS 0.739 0.664
ssGBLUP_LD 0.746 0.673
ZX (320) GBLUP_80K 0.028 0.067
GBLUP_WGS 0.098 0.111
GBLUP_LD 0.164 0.142
GFBLUP_QTL 0.164 0.144
GFBLUP_GWAS 0.124 0.119
  1. GBLUP_80K genomic BLUP based on the 80K SNP panel; GBLUP_WGS GBLUP based on imputed whole-genome sequencing (WGS) data; GBLUP_LD GBLUP based on WGS after LD pruning; GFBLUP_QTL genomic feature BLUP with a genomic feature matrix constructed based on QTL prior information; GFBLUP_GWAS genomic feature BLUP with a genomic feature matrix constructed based on GWAS prior information; ssGBLUP_80K, ssGBLUP_WGS, ssGBLUP_LD For ssGBLUP, the H matrix was constructed based on the different genomic relationship matrices of the 80K chip panel, WGS data and WGS data after LD pruning and termed ssGBLUP_80K, ssGBLUP_WGS and ssGBLUP_LD, respectively; AGE days to 100 kg; BFT backfat thickness
  2. aYorkshire population of LM, ZX or LM plus the ZX reference population