Genome-wide analysis reveals the patterns of genetic diversity and population structure of 8 Italian local chicken breeds.

The aim of this study was to conduct a genome-wide comparative analysis of 8 local Italian chicken breeds (Ermellinata di Rovigo, Millefiori di Lonigo [PML], Polverara Bianca, Polverara Nera, Padovana, Pepoi [PPP], Robusta Lionata, and Robusta Maculata), all under a conservation plan, to understand their genetic diversity and population structure. A total of 152 animals were analyzed using the Affymetrix Axiom 600 K Chicken Genotyping Array. The levels of genetic diversity were highest and lowest in PML and PPP, respectively. The results of genomic inbreeding based on runs of homozygosity (ROH; F) showed marked differences among breeds and ranged from 0.161 (PML) to 0.478 (PPP). Furthermore, in all breeds, short ROH (<4 Mb in length) were more frequent than long segments. Patterns of genetic differentiation, model-based clustering, and neighbor networks showed that most breeds formed nonoverlapping clusters and were clearly separate populations. The 2 Polverara breeds shared a similar genetic background and showed the lowest genetic differentiation in comparison with purebred lines; the local populations showed separated groups. PPP and PML were closer to the group of the purebred broiler lines (BRSA, BRSB, BRDA, and BRDB). Six genomic regions are presented as hotspots of autozygosity among the Italian chicken breeds, with candidate genes involved in multiple morphological phenotypes as breast muscle, muscle dry matter content, and body weight. This study is the first exhaustive genome-wide analysis of the diversity of these Italian local chickens from Veneto region. We conclude that breeds have conserved authentic genetic patterns. The results are of significant importance because they will help design and implement conservation strategies. In fact, the conservation of these breeds may also have positive impacts on the local economy, niche traditional markets, and offering a source of high-quality products to consumers. In this context, genomic information may play a crucial role in the management of local breeds.