Analysis of ddRAD-seq data provides new insights into the genomic structure and patterns of diversity in Italian donkey populations

With more than 150 recognized breeds, donkeys assume relevant economic importance, especially in developing countries. Even if the estimated number of heads worldwide is 53M, this species received less attention than other livestock species. Italy has traditionally been considered one of the cradles of European donkey breeding, and despite a considerable loss of biodiversity, today still counts nine autochthonous populations. A total of 220 animals belonging to nine different populations were genotyped using the double-digest restriction site associated DNA (ddRAD) sequencing to investigate the pattern of diversity using a multi-Technique approach. A total of 418,602,730 reads were generated and successfully demultiplexed to obtain a medium-density SNP genotypes panel with about 27K markers. The diversity indices showed moderate levels of variability. The genetic distances and relationships, largely agree with the breeding history of the donkey populations under investigation. The results highlighted the separation of populations based on their genetic origin or geographical proximity between breeding areas, showed low to moderate levels of admixture, and indicated a clear genetic difference in some cases. For some breeds, the results also validate the success of proper management conservation plans. Identified runs of homozygosity islands, mapped within genomic regions related to immune response and local adaptation, are consistent with the characteristics of the species known for its rusticity and adaptability. This study is the first exhaustive genome-wide analysis of the diversity of Italian donkey populations. The results emphasized the high informativeness of genome-wide markers retrieved through the ddRAD approach. The findings take on great significance in designing and implementing conservation strategies. Standardized genotype arrays for donkey species would make it possible to combine worldwide datasets to provide further insights into the evolution of the genomic structure and origin of this important genetic resource.