Genomic regions associated with performance in racing line of Quarter Horses

Abstract

Quarter Horses breed for rancing are able to run short distances faster than any other breed. Although in Brazil the effective number of animals in the racing line is relatively smaller compared to the other lines, its economic importance is substantial. Despite economic and scientific interest in this athletic trait, few efforts have been made to better understand the genetic and physiological mechanisms underlying this trait. The objective of this study was to perform genome-wide association studies (GWAS) in Quarter Horses of the racing line using equine single nucleotide polymorphism (SNP) genotyping chips for prospecting chromosome regions, genes and polymorphisms related to maximum speed index. Genotypic and phenotypic data from 305 horses genotyped with the 54 k or 65 k chip were used. Additional 187 not genotyped animal with SI record were added in the study, for a total of 492 animals and 620 horses in the pedigree used for the GWAS analysis GWAS was performed by the single-step genomic best linear unbiased prediction (ssGBLUP) method using two approaches: ssGWAS1 in which only SNP effects are recalculated at each iteration, and ssGWAS2 in which SNP effects are recalculated from updated genomic estimated breeding values (GEBVs) at each iteration. Twenty-one regions that explained more than 1% of the total genetic variance (gVar) in the maximum speed index were identified by ssGWAS1 and 12 by ssGWAS2. More than 40% of gVar was explained by these regions in ssGWAS1 and about 30% in ssGWAS2. Among chromosomes that explained more than 1% of genetic variance, five were common to both methods (equine autosomal chromosomes 3, 10, 15, 22, 25). The capacity to capture the largest number of small-effect quantitative trait loci was greater for ssGWAS1 than ssGWAS2. A total of 108 genes were identified with the first approach and 59 with the second approach. The present results show that the racing performance of Quarter Horses, given by the maximum speed index, is a quantitative trait and that no major genes exist. In general, the genes identified by enrichment analysis are related to the neuromotor system, bone and tendon development, hormonal responses, muscle contraction, and energy and sterol metabolism. These functions are considered important for the trait studied, corroborating these genes as candidates for racing performance in the Quarter Horse breed.

Exome analysis and functional classification of identified variants in racing Quarter Horses

“…In the studies of Pereira et al (2018Pereira et al ( , 2019, who used the single-step GBLUP method to estimate the effect of thousands of SNPs and genomic regions on SImax in the same racing Quarter Horses as used in the present study, one of the regions/windows on ECA15 found to be associated with the trait of interest harbors the SLC3A1 gene whose variant was also related to racing performance of Quarter Horses in the present study. In addition to this coincidence, these authors also found other regions that were relatively close (distance of 1.6 Mb) to the CCN6 (ECA10).…”

“…Association studies between DNA polymorphisms and racing performance in horses have been performed mainly on Thoroughbred horses, including punctual association analysis (candidate gene strategy) (Gu et al, 2010;Hill et al, 2010) and GWASs (Shin et al, 2015;Farries et al, 2019). However, some results obtained for Quarter Horses in both punctual genome analysis (Pereira et al, 2016a(Pereira et al, , 2016b and GWASs (Pereira et al, 2018) showed that the markers appropriate for the English breed are generally not suitable for the identification of superior racing animals of the North American breed.…”

Identification and Functional Annotation of Genes Related to Horses’ Performance: From GWAS to Post-GWAS

“…Furthermore, other genes are related to these two breeds, such as PPP4R2, PDZRN3 and SHQ1. It may be explained due to Thoroughbred being one of The horse breeds used in The formation of The racing line of Quarter Horses, and thus it is observed that The results of genetic studies involving these two breeds may be similar [19].…”

Genome-wide association study for milk production traits in a Brazilian Holstein population

“…The 10-SNP windows that explained more than 1% of the genetic variance were considered promising regions and used to identify potential candidate genes by using the National Center for Biotechnology Information (NCBI) database and Ensembl Genome Browser (http: / / www .ensembl .org/ index .html) through the biomaRt R package (http: / / www .bioconductor .org; Ensembl release 90). The threshold of 1% was chosen to identify the most important windows and to use the level used in other studies (e.g., Gonzalez-Pena et al, 2016;Zhu et al, 2017;Marques et al, 2018;Pereira et al, 2018). The Manhattan plots were created using qqman package (Turner, 2014).…”