Comparison of random regression models, traditional animal model and with the inclusion of molecular markers in the estimation of genetic parameters in Colombian Holstein cattle

Abstract

The use of molecular markers to identify desirable genes in animal production is known as marker-assisted selection. The traditional genetic evaluation model uses the BLUP methodology; when genetic markers are included in the evaluation model, the methodology is known as M-BLUP. In contrast, random regression models (RRM), unlike the models based on production at 305 days, consider factors that change for each animal from one test to another. The objective of this study was to compare variance components, genetic parameters and breeding values for milk production, protein percentage and somatic cell score in Colombian Holstein cattle using BLUP, M-BLUP and RRM. For the estimation of genetic parameters and values, 2003 lactations corresponding to 1417 cows in 55 herds were used, and effects of the order of delivery, herd, and contemporary group were included. The three traits presented greater heritability under the MBLUP model: 0.44 for protein percentage, 0.27 for milk production and 0.28 for somatic cell score. This was because the genetic variance was greater when M-BLUP was used, which allowed a greater accuracy of the breeding value estimation in the three traits. Therefore, the model that includes information on molecular markers is more suitable for genetic evaluation in Colombian Holstein cattle.

Keywords

• Dairy cattle
• Animal genetics
• Genetic markers
• Animal breeding
• Dairy production.