| Summary: | The Lupo Italiano (Italian Wolfdog) is a domestic dog (Canis lupus familiaris) breed created in 1966 by crossing of Apennine grey wolves (Canis lupus italicus) to German Shepherd dogs (GSD). The breed has an official studbook with management protocols, under the control of the Ministry of Agriculture. The breed is characterized by strength, resistance, and strong capabilities in learning, as well as participation in search and rescue activities. Considering the depth and completeness of genealogical information, the high levels of inbreeding, and the presence of the wolf as a recent ancestor, the Lupo Italiano can be used as a model to investigate the effects of population structure and selection on wolf-dog hybridization. The aim of this work is to compare the genetic background of the Italian Wolfdog with that of the GSD, village dogs, grey wolves from the Apennines, and other dog populations, with a specific goal of detailing introgression between the Lupo Italiano, wolf and GSD. Three hundred and seventy-seven individuals were genotyped using a high density chip containing more than 170K SNPs. Genotypes for Lupo Italiano were provided by University of Milano and National Institutes of Health in Bethesda, MD. Those for the Apennine wolves were produced by ISPRA, and those for GSD, village dogs and grey wolves were publicly available (Dryad, Shannon et al. 2015). Samples and loci were quality checked, and then analyzed using Multi-Dimensional Scaling (MDS). The relationship matrix based on pedigrees was compared with the genomic relationship matrix (GRM), calculated using GCTA64 software. In addition, the genomic heterozygosity-based inbreeding coefficient has been estimated using PLINK v1.9 software. Reynolds distances were computed to define the relationships among the five populations. In addition, the Lupo Italiano, wolves and GSD were studied at the chromosomal level. As expected, the closest population to the Lupo Italiano is the German Shepherd dog (Reynold genetic distance 0.25), whereas the farthest ...
|
|---|