Genomic association using principal components of morphometric traits in horses: identification of genes related to bone growth.

The measurement of morphometric traits in horses is important for determining breed qualification and is one of the main selection criteria for the species. The development of an index (HPC) that consists of principal components weighted by additive genetic values allows to explore the most relevant relationships using a reduced number of variables that explain the greatest amount of variation in the data. Genome-wide association studies (GWAS) using HPC are a relatively new approach that permits to identify regions related to a set of traits.

Principal components for morphometric traits in Campolina horses.

Principal component analysis (PCA) was applied to evaluate the genetic variability and relationship between 15 morphometric traits in 91,483 Campolina horses, as well as to propose an index based on an aggregate genotype that promotes a particular selection objective. PCA was applied to the genetic (co)variance matrix among variables. After calculation of the principal components, the breeding values were estimated to obtain an index related to the component that explained most of the variation.