ANALYSIS OF GENOMIC DATA IN RUMINANT SPECIES FOR PARENTAGE, PRODUCT TRACING AND POPULATION STRUCTURE STUDIES

The availability of genomic and high performance computing technologies gave access to new approaches and methods to exploit the high number of genetic information provided, even in livestock species. These new tools can be used to unveil the relationships between different populations or individuals, to understand the genetic background of breeds, to define the genetic architecture of phenotypes or pathologies and to detect selection signatures that shaped the cattle, sheep and goat reared today. In this context, these technologies may provide breeders and breeders’ associations with new tools that may be used in livestock management. In fact, the estimation of genomic parentage among individuals can help in defining the least related animals in case of identical values of additive parentage and detect errors in pedigree declarations as well. Moreover, since DNA is immutable within animal life but very polymorphic between individuals, these tools may be of help in the definition of the breed or the individual of origin, improving food safety. In this thesis, I faced the complexity of genomic data in ruminant species, focusing in particular on goats. I reported three studies with distinct aims: i) study the signatures of selection in 369 animals of 16 Italian populations, and then focusing on the Valdostana goat breed which presents a breed-specific broad signature of selection in chromosome 7; ii) define a new method to develop panels of SNPs for parentage assessment that could be applied on species with unreliable genomic assembly; and iii) study the selection signatures in 929 animals of 41 Pakistani and Italian goat populations associated with a specific pigmentation pattern, the roan, detecting a candidate gene important in understanding the coat color genetics in goats and which could be also used as a marker for traceability of breeds that carry this peculiar phenotypic pattern.