Abstract
Genetic improvement of body weight (BW) traits has received major consideration in the poultry industry due to their economic and environmental implications. With the rapid implementation of genomic selection (GS) in the poultry industry and a decrease in the cost of genotyping, genomic prediction (GP) is a feasible way to increase productivity. Moreover, a pre-selection of SNPs could represent a reasonable option to speed up GP. We used 312 F2 broiler chicken genotyped with 60K Illumina Beadchip to investigate the effect of reduced SNP densities on accuracy and bias of prediction using single-step genomic BLUP (ssGBLUP) for BW at 2-4 weeks of age (488 chickens). To investigate the effect of reduced SNP densities by varying minor allele frequency (MAF), SNPs were grouped into five subgroups with MAF of 0.05-0.1, 0.1-0.2, 0.2-0.3, 0.3-0.4 and 0.4-0.5. The accuracy and bias of genomic predictions from different MAF bins were compared to that using a standard array of 60k SNP genotypes and the traditional BLUP method. Our study showed that using a subset of common SNPs genotypes may increase accuracy of genomic predictions compared to using all SNPs, specifically in the studied F2 population with a limited number of genotyped/phenotyped individuals.