Customized SNP Panel for Local Brazilian Sheep Breed Assignment

Abstract

Background/Objectives: Brazilian locally adapted sheep breeds represent valuable genetic resources. However, the commercial valorization of these breeds depends in part on genetic certification to support traceability and verify product origin. This study aimed to identify and evaluate a minimum set of highly informative SNPs for accurate and efficient breed assignment across five Brazilian locally adapted sheep breeds. Methods: A total of 677 samples were genotyped using the Embrapa Multispecies 65 K Illumina Infinium 1 chip, which contains 2926 markers for Ovis aries. The dataset was partitioned into training (n = 566) and independent testing (n = 111) sets. Markers were ranked according to genetic differentiation based on pairwise Wright’s fixation index (FST) using the Toolbox for Ranking and Evaluation of SNPs (TRES), generating three nested reduced panels of 288, 192, and 96 SNPs. Panel performance and preservation of population structure were evaluated using Random Forest classification, Principal Component Analysis (PCA), and ADMIXTURE. Results: The 96-SNP panel achieved classification accuracy comparable to that of the 2145-SNP post-QC baseline and the 192- and 288-SNP panels (Cochran’s Q test: Q = 6.00, df = 3, p = 0.112), with no statistically significant difference in classification performance despite the substantial reduction in marker number. PCA and ADMIXTURE analyses indicated that the 96-SNP panel preserved the major population structure observed with the full post-QC marker set. Conclusions: Although formal analytical validation of a dedicated low-density genotyping assay remains necessary before routine implementation, the in-silico marker selection and empirical validation performed here provide an evidence-based framework for translating high-density genomic information into accessible and cost-effective applications for breed assignment, traceability, and conservation of Brazilian locally adapted sheep genetic resources.