Comparison of accuracy of genomic evaluation of body weight and average daily gain using different SNP densities in the F2 population of broiler chickens

This study evaluated the accuracy and bias of estimated breeding values (EBV) using pedigree-based BLUP (PBLUP) and single-step genomic BLUP (ssGBLUP). Genomic evaluations for body weight (BW) and average daily gain (ADG) were compared using either all SNPs or a subset with minor allele frequency (MAF) 0.4-0.5. Data included 312 F2 broilers genotyped with a 60K Illumina BeadChip and 176 non-genotyped birds (total 488). The effect of reduced SNP density on prediction accuracy and bias for BW and ADG at 2-4 weeks of age was assessed using ssGBLUP. To examine the effect of reducing SNP density by changing minor allele frequency, SNPs with allele frequencies of 0.4-0.5 were isolated. The accuracy and bias of genomic predictions from the 0.4-0.5 MAF SNP subset were compared with those obtained using the standard 60K SNP array and traditional BLUP. Our study showed that using low-coverage genotype data would be a cost-effective approach for genomic prediction in crossbred chickens even with a small population size (less than 500).