Transmission ratio distortion detection by neutral genetic markers in the Pura Raza Española horse breed.

Transmission Ratio Distortion (TRD) is a genetic phenomenon widely demonstrated in several livestock species, but barely in equine species. The TRD occurs when certain genotypes are over- or under-represented in the offspring of a particular mating and can be caused by a variety of factors during gamete formation or during embryonic development. For this study, 126 394 trios consisting of a stallion, mare, and offspring were genotyped using a panel of 17 neutral microsatellite markers recommended by the International Society for Animal Genetics for paternity tests and individual identification. The number of alleles available for each marker ranges from 13 to 18, been 268 the total number of alleles investigated. The TRDscan v.2.0 software was used with the biallelic procedure to identify regions with distorted segregation ratios. After completing the analysis, a total of 12 alleles (out of 11 microsatellites) were identified with decisive evidence for genotypic TRD; 3 and 9 with additive and heterosis patterns, respectively. In addition, 19 alleles (out of 10 microsatellites) were identified displaying allelic TRD. Among them, 14 and 5 were parent-unspecific and stallion-mare-specific TRD. Out of the TRD regions, 24 genes were identified and annotated, predominantly associated with cholesterol metabolism and homeostasis. These genes are often linked to non-specific symptoms like impaired fertility, stunted growth, and compromised overall health. The results suggest a significant impact on the inheritance of certain genetic traits in horses. Further analysis and validation are needed to better understand the TRD impact before the potential implementation in the horse breeding programme strategies.

A genome-wide association study of mare fertility in the Pura Raza Español horse.

Despite the economic importance of fertility for the horse industry, few efforts have been made to achieve a better understanding of the genetic mechanisms underlying its control. This is probably due to the difficulty of obtaining reliable phenotypes and the complexity of modelling the environmental and management factors. This work is novel in that we propose to use reproductive efficiency (RE) as an indicator of mare fertility. To achieve this, we performed a genome-wide association study in the Pura Raza Español horse aimed at identifying genomic variants, regions, and candidate genes associated with fertility in mares. The dataset included 819 animals genotyped with the Affymetrix Axiom™ Equine 670 K single-nucleotide polymorphisms (SNPs) Genotyping Array and the deregressed breeding values for RE trait, obtained using a ssBLUP model, employed as pseudo-phenotypic data. Our results showed 28 SNPs potentially associated with RE, which explained 87.19% of the genetic variance and 6.61% of the phenotypic variance. Those results were further validated in BayesB, showing a correlation between observed and predicted RE of 0.57. In addition, 15 candidate genes (HTRA3, SPIRE1, APOE, ERCC1, FOXA3, NECTIN-2, KLC3, RSPH6A, PDPK1, MEIOB, PAQR4, NM3, PKD1, PRSS21, IFT140) previously related to fertility in mammals were associated with the markers and genomic regions significantly associated with RE. To our knowledge, this is the first genome-wide association study performed on mare fertility.

Screening and detection of chromosomal copy number alterations in the domestic horse using SNP-array genotyping data.

Chromosomal abnormalities are a common cause of infertility in horses. However, they are difficult to detect using automated methods. Here, we propose a simple methodology based on single nucleotide polymorphism (SNP)-array data that allows us to detect the main chromosomal abnormalities in horses in a single procedure. As proof of concept, we were able to detect chromosomal abnormalities in 33 out of 268 individuals, including monosomies, chimerisms, and male and female sex-reversions, by analyzing the raw signal intensity produced by an SNP array-based genotyping platform. We also demonstrated that the procedure is not affected by the SNP density of the array employed or by the inbreeding level of the individuals. Finally, the methodology proposed in this study could be performed in an open bioinformatic environment, thus permitting its integration as a flexible screening tool in diagnostic laboratories and genomic breeding programs.