Genomic Prediction in Holstein Cows: Comparison Between Additive and Non-Additive Models for Productive Traits

• Grant number: 25/16266-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2025
• End date: September 30, 2026
• Field of knowledge: Agronomical Sciences - Animal Husbandry
• Principal Investigator: Gerson Barreto Mourão
• Grantee: Felipe Veronezzi Azzini
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil

Abstract

Brazilian dairy production faces increasing demands for higher output, requiring advancements in genetic breeding programs. In this context, genomic selection has emerged as a strategic tool, enabling greater accuracy in predicting the breeding value of animals. Traditionally, genetic models consider only additive effects, which may limit the estimation of parameters such as heritability and genetic variances. This project aims to assess the impact of including non-additive dominance effects in the genomic prediction of Holstein cows, comparing additive and non-additive models in the analysis of fat, protein, casein, somatic cell count, and milk yield. Phenotypic data from 7,664 cows and genotypes based on 79,295 SNPs will be used. Statistical analysis will be performed through mixed models, estimating variance components, heritability, and Spearman correlation between models. It is expected that considering dominance effects will lead to more accurate estimates and predictions, thereby increasing accuracy and contributing to greater efficiency in genomic selection programs, highlighting the importance of these effects in the genetic evaluation of dairy cattle.