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

Abstract

The measurement of morphometric traits in horses is important for determining breed quali cation and is one of the main selection criteria in 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. The aim of this study was to perform GWAS using HPC for 15 linear measurements as the explanatory variable in order to identify associated genomic regions and to elucidate the biological mechanisms linked to this index in Campolina horses. For GWAS, weighted single-step GBLUP was applied to HPC. The eight genomic windows that explained the highest proportion of additive genetic variance were identi ed. The sum of the additive variance explained by the eight windows was 95.89%. Genes involved in bone and cartilage development were identi ed (SPRY2, COL9A2, MIR30C, HEYL, BMP8B, LTBP1, FAM98A, and CRIM1). They represent potential positional candidates for the HPC of the linear measurements evaluated. The HPC is an e cient alternative to reduce the 15 usually measured traits in Campolina horses. Moreover, candidate genes inserted in region that explained high additive variance of the HPC were identi ed and might be ne-mapped for searching putative mutation/markers.

A complexidade da antracnose no feijão aspectos relevantes da resistência genética e genômica

“…Genome-wide association studies (GWASs) play an important role in identifying polymorphisms related to specific phenotypic traits (Bastos et al, 2023). To effectively utilize GWASs across a diverse panel of samples, it is crucial that markers are widely distributed across the genome (Tsunoda et al, 2019).…”