Exploratory analysis of genomic prediction profiles in Arequipa fighting cattle using commercial SNP panels

Genomic technologies based on single nucleotide polymorphisms (SNPs) have become valuable tools for the characterization of cattle populations lacking comprehensive phenotypic and pedigree records. This study explored genomic variability in Arequipa fighting cattle, a Creole-derived population associated with traditional cattle fighting events, using commercial SNP-based trait-derived genomic indices. A total of 95 adult animals were sampled, of which 60 and 22 individuals passed quality control for the Igenity Beef and Igenity Basic panels, respectively. Trait-derived genomic indices were analyzed using descriptive statistics and multivariate approaches to assess variability and patterns of similarity among individuals. The results revealed substantial variation among individuals, allowing the identification of animals with higher indices for growth performance, carcass yield, meat quality, and maternal traits. Ranking categories showed overlapping distributions across maternal and terminal groups, indicating a continuous pattern of genomic variation within the population. Milk protein markers showed a high frequency of β-casein A2A2 genotypes, while alleles associated with improved cheese-making properties were less frequent. Hierarchical clustering supported heterogeneous genomic profiles among individuals. Overall, these results provide an exploratory genomic characterization based on commercial SNP prediction systems, highlighting their potential for preliminary assessment in underrepresented cattle populations while acknowledging limitations due to lack of phenotypic validation and population-specific calibration.