Genomic Evaluation of Colombian Holstein Cattle Using Imputed Genotypes at Medium Density

• Main Authors: Juan C. Zambrano, Julián Echeverri, Albeiro López Herrera
• Format: Article
• Language: English
• Published: Universidad de Cordoba 2019-05-01
• Series: Revista MVZ Cordoba
• Subjects: Genotyping; genomic selection; single nucleotide polymorphism
• Online Access: https://revistas.unicordoba.edu.co/index.php/revistamvz/article/view/1704

Objective. The goal of this study was to determine the accuracy and bias of direct genomic values (DGV) using imputed genotypes at medium density in yield- and reproduction-related traits for Holstein cattle from Antioquia, Colombia.Materials and Methods. A total of 31 animals were genotyped with the Illumina BovineLD chip, 64 with Illumina BovineSNP50v2 and 48 with Illumina BovineHD. Two SNP panels (6K and 40K) were imputed to a density of 44K using the FINDHAP.f90 v4 program. The effects of the SNPs were estimated using the Bayes C method, using low-density (6K) genotypes as well as medium-density imputed genotypes (44_imputed). The accuracy and bias of the DGVs were determined by cross-validation. The evaluated traits were: milk yield (MY), percentage of protein (PP), percentage of fat (PF), somatic cell score (SCS), calving interval (CI) and open days (OD). Results. When using the 6K panel, the accuracy values for DGV (rpDGV;EBV) in all the studied traits ranged from 0.19 to 0.24, and the bias (bDGV;EBV) from 0.03 to 0.16. In contrast, using the 44K_imputed panel generated higher accuracy values ranging from 0.24 to 0.33 and a bias ranging from 0.03 to 0.26. Conclusions. The accuracy of prediction the DGV was higher with genotypes imputed to medium densities when compared to the accuracy of prediction obtained using low-density genotypes. Therefore, in this study it is concluded that the imputation of genotypes is very useful, because it improves the reliability of the genomic evaluation