A single-step genomic evaluation for milk production in Egyptian buffalo

Abstract

The objectives of this study were to estimate genetic parameters and identify candidate genes for milk production in Egyptian buffalo using single-step method. Daily milk yield of 174,619 records from 698 buffalo cows were used. Animals with high and low deviated performance were selected for genotyping with Axiom® Buffalo Genotyping array 90 K. Variance components were estimated using AIREMLF90 for single-step GBLUP. Accuracy of prediction was calculated using predicted ability approach. The percentage of genetic variance explained by a window segment of each 30 adjacent SNPs was calculated. The top 20 window segments for additive genetic variance were chosen for QTL and candidate genes retrieving. Heritability estimate for daily milk yield was moderate (0.20 ± 0.03). The accuracy of prediction (0.61) seems to be suitable under current challenges. The top ten window segments with largest effects are located on chromosomes 1, 2, 3, 4, 6, 9, 11, 12 and 16 and explained around 6% of additive genetic variance. These genomic regions are coincided with previously reported QTL in different cattle breeds and harbored many propitious candidate genes for milk production, for example: the Oct1 protein encoded by POU2F1 gene on chromosome 6 is known to have a role for the regulation of major milk protein genes expression and development of mammary gland. These results indicated that a more reliable estimation of genetic parameters from population with small size can be obtained with a single-step genomic evaluation. The identified genomic regions with highest proportion of additive genetic variance harbor promising candidate genes with biological roles associated with milk production. Our findings provided a solid basis for improving milk production in Egyptian buffalo with reasonable accuracy, since traditional methods is hindered by the lack of sufficient pedigree information. A further research including more animals, records, and genotypes is required to validate our findings.