Genetic diversity of Mediterranean cattle breeds related to geography and climate

In recent decades, changes in climate have caused impacts on natural and human systems. Mediterranean countries will be particularly affected by this phenomenon, with growing temperatures and reduced rainfall. Understanding how species and ecosystems respond to climate change has become a crucial focus in biodiversity conservation and management. The genome-wide SNP panels allows providing background information on genome structure in domestic animals, opening new perspectives to livestock genetics. The International Project GALIMED “Genetic Adaptation of Bovine Livestock and production systems in MEDiterranean region”, develops an integrated approach that combines the analysis of SNP markers, bioclimatic variables and farming system information to identify genotypes and breeding practices able to respond to climate change. Italian and Corsican local breeds are part of this project. The aim of the study is to identify genomic regions related to adaptation to climate change in these local breeds. Individuals of Cinisara (71), Modicana (72), Maremmana (25), Piemontese (21), Romagnola (21), Sarda (30), Sardo-Modicana (28) and Corse (31) breeds were genotyped using Bovine SNP 50k. Farming systems data were collected by interviewing breeders. Geographic coordinates and 19 bioclimatic variables were also available. Principal Components Analysis (PCA) was performed on SNPs data and climatic variables. Co-inertia (CIA) analysis was realized to detect a possible common structure between such different information. After edits, 43,625 SNPs were retained. The PC1 on individual genotypes differentiates Modicana from other breeds, and shows that Sardo-Modicana is close to Modicana, but is clearly admixed to another breed. The PC2 differentiates Cinisara from a cluster “Romagnola/Maremmana” and shows a large variability of the Modicana breed. The CIA coefficient between molecular data and both geographic and climatic information is equal to 0.38, (P-value=0.001), suggesting evidence of genetic adaptation to different climatic pressures. Further analyses are on going to identify the genetic regions with a potential adaptive role. The results will provide a solid scientific foundation to reconsiderobjectives and selection criteria and to improve farming practices to prepare livestock to new environmental conditions.