Genome-wide analysis provides insights into the conservation status and the genomic architecture of Gentile di Puglia sheep, a Merino-type breed

The Gentile di Puglia is a local Italian Merino-type sheep breed of high historical and economic value, known for its fine wool, and whose conservation depends on an accurate assessment of its genomic diversity. Using a medium-density Single−Nucleotide Polymorphism (SNP) array, we analysed the population structure, homozygosity and heterozygosity patterns of 1 337 individuals genotyped for 45 869 autosomal SNPs, representing one of the largest datasets available for a local sheep breed. Genetic diversity indices highlighted moderate−to−high heterozygosity and low genomic inbreeding. Population structure analysis revealed clear differentiation among farms shaped by historical breeding origins and recent management practices. Runs of homozygosity (ROH) analysis showed that most segments were short (< 4 Mb), indicating predominantly ancient inbreeding, likely reflecting historical demographic processes rather than recent consanguineous matings. Several recurrent ROH islands were identified on ovine chromosomes (OAR) 2, OAR6, OAR10, and OAR19, harbouring genes associated with growth, fat metabolism, reproduction, immunity, and environmental adaptation. Heterozygosity-rich regions (HRRs) consisted of short segments (< 1 Mb), with two HRR islands harbouring genes of potential functional relevance (VPS13B, CLCN3, NEK1, SH3RF1), which may contribute to reproductive traits, disease resistance, or overall fitness. Partial overlap between ROH and HRR islands was observed, suggesting a nuanced genetic structure in which patterns of homozygosity and heterozygosity may contribute differently to shaping genetic diversity. Overall, this integrated genomic approach provides a comprehensive assessment of the current genetic status of the Gentile di Puglia breed and a solid scientific foundation for the design and implementation of effective conservation strategies. In this context, genomic data serve as a critical resource for informed decision-making.