New biological insights from genomics and metabolomics in a livestock species: fostering applications to improve the sustainability of pig production systems

Biomedical science is becoming a data-driven discipline, thanks to the advent of high-throughput -omic technologies. The different layers of biological complexity are being explored, from the genomic layer, closest to the genetic background, to the phenomic layer, i.e. the full set of phenotypes for an organism. The link between genotype and phenotype is hard to establish directly, due to the influence of the environment and the various -omic layers. Metabolomics can act as a good proxy for this link, by representing a set of intermediate phenotypes that are closely related to both genotype and phenotype. In this thesis, we explore how genomics and metabolomics can be applied in animal science, in particular in pigs. After providing a summary of the state of the art of the field, we present our work in pig genomics and metabolomics. First, we explored in-depth the ABO gene using to a large collection of public and in-house produced whole genome sequencing datasets. The same datasets, along with a set of assembled genomes, were then used for a comprehensive analysis of nuclear insertions of mitocondrial sequences in the pig genome, to elucidate the complex and reticulate evolutionary history of pigs. We then moved to metabolomics to explain the differences in genetic background between two Italian pig breeds, using a large dataset of untargeted metabolomics data. The same dataset was finally used to explore the metabolomic differences between castrated males and females in Italian Large White pigs. In conclusion, we were able to leverage the hundreds of genomic datasets available to obtain a large scale picture of the porcine genome and its evolutionary history; the results of the metabolomic analyses could pave the way for a more precise description of the relationship between the genetic background of pigs with phenotypes and production traits of interest.