Genomic diversity and structure in arabian horses revealed by whole-genome sequencing: establishment of an allele frequency database of common genetic variation.

backgroundThe Arabian horse is a culturally and historically influential breed that has contributed to the development of many modern horse populations. However, genomic resources for this breed remain limited, particularly population-level allele frequency datasets that support studies of genetic diversity, selection, and disease. The aim of this study was to generate a comprehensive allele frequency database for Arabian horses using representative sampling and high-coverage whole-genome sequencing.

resultsWe generated the first publicly available allele frequency database for the Arabian horse by sequencing pooled genomic DNA from 120 individuals originating from four distinct populations: Poland, the United States, Egypt, and Syria. Across the dataset, 11.7 million single nucleotide polymorphisms were identified, and both population-specific and global allele frequencies were estimated. Genome-wide analyses revealed substantial variation in polymorphism density, as well as multiple regions exhibiting fixation for alternate alleles. Principal component analysis, hierarchical clustering, and admixture analysis demonstrated clear genetic differentiation among the four populations. We detected 6,210 fixed genomic blocks, many of which overlapped with genes involved in metabolic and signaling pathways, suggesting potential historical selection. One such block corresponded to a region previously associated with insect bite hypersensitivity. To assess clinical relevance, we screened the dataset for known pathogenic variants linked to four inherited disorders described in Arabian horses. None of these variants were detected, and their absence was supported by high sequencing depth and confirmed through Sanger sequencing.

conclusionsThis study provides the first comprehensive allele frequency resource for the Arabian horse. The database enables robust variant filtering, facilitates the identification of candidate functional polymorphisms, and supports studies of genetic structure and selection. It represents an important foundation for future work in equine genomics and has practical applications in breeding, conservation genetics, and health management. Continued expansion of the dataset with additional populations will further enhance its value for research and applied genomics.