Genomic Evaluation of Average Daily Gain Traits in a Mixture of Arian Line and Urmia Iranian Native Chickens

The aims of this investigation were to compare the accuracy and bias of prediction of Estimated Breeding Values (EBV) for Average Daily Gain (ADG) at ۲-۴ weeks old by employing pedigree-based BLUP and single-step Genomic BLUP (ssGBLUP) techniques. Additionally, the study aimed to identify the optimal minor allele frequencies (MAF) threshold for pre-selecting SNPs for genetic prediction. The present investigation utilized a total of ۴۸۸ F۲ broiler chickens, which were derived from the crossbreeding of fast-growing Arian chickens and slow-growing native chickens from Urmia, Iran. These chickens were between ۲-۴ weeks old at the time of the study. Samples were genotyped using the Illumina ۶۰K chicken Beadchip. In order to examine the impact of MAF on prediction accuracy, a total of ۴۸,۳۷۹ quality-controlled SNPs were categorized into five subgroups based on their MAF values: ۰.۰۵-۰.۱, ۰.۱-۰.۲, ۰.۲-۰.۳, ۰.۳-۰.۴, and ۰.۴-۰.۵. The findings substantiated the dominance of ssGBLUP over conventional BLUP techniques. The average accuracy of GP improved by ۱.۹۶, ۳.۸۷, and ۲.۱۲% using ssGBLUP compared to BLUP method for ADG at ۲-۴ weeks of age, respectively. Using a specific MAF bin and a subset of SNPs based on age group significantly enhanced the accuracy of genomic prediction for ADG traits. Current results highlighted that the pre-selection of SNPs based on allele frequency may provide a reasonable compromise between accuracy of results, number of independent variables to be considered and computing requirements.

Keywords:

BLUP , Estimated breeding value , Minor allele frequencies , SNP , ssGBLUP.