Non-additive genomic models for the evaluation of dairy cows

Abstract

Genomic tools have enabled great advances in genetic studies in production animals, in this way, it became possible to identify regions of the genome and molecular markers associated with traits of significant economic impact on livestock. Traditionally, genomic approaches investigate additive genetic effects, however, the contribution of non-additive effects to genetic and phenotypic variance remains uncertain. Furthermore, such effects may aid in the identification of genomic regions which exhibit advantageous heterozygosity for traits of commercial interest. The aim of this study is to estimate individual genomic heterozygosity in a Genome-Wide Association Study (GWAS) for milk production and quality traits in Holstein cows using non - additive genomic models. Firstly, we proposed to work with simulated data to identify the model that best adjusts to study the effect of heterozygosity on genomic predictions. The simulation process will be carrying out by QMSim software and the package GenAbel from R software will be used to realize the Run of Heterozygosity (ROHet) analyses, with windows of 50, 100 and 200 bp. Subsequently, phenotypic information of 5,981 cows measured between the years 2012 to 2019, will be used in real data analysis. Genotypes of 1,067 cows will be used for the genetic analysis, with 747 cows were genotyped in a low density panel and 389 in a medium density. A GWAS adapted analyses will be used to identify the non-additive variation of the phenotype and possible QTLs and molecular markers associated with the heterotic regions. This is a complementary study to others carried out with the support of FAPESP in Genetic Improvement in Dairy Cattle and it is hoped that this will contribute to the expansion of scientific boundaries regarding the genetic structure of important traits in dairy farming, as well as, the investigation of alternatives genomic approaches to promote genetic progress in bovine populations. (AU)