Metabolomics is the emerging field of metabolome analysis that identify, quantify, and characterize a large number of metabolites in biological samples (e.g., milk, plasma, and serum), providing interesting insights into the so called intermediate phenotypes that lie in the middle between the genomic space (or level) and the final or external phenotypes, that in livestock might be production traits such as growth rate, milk production, fat deposition, and other economic relevant traits.
Metabolomics applied to animal breeding might become a cornerstone of the “next generation phenotyping” approaches that are needed to refine and improve trait description and, in turn, to improve prediction of the breeding values of the animals to cope with traditional and new objectives of the selection programs.
Integration of metabolomics with livestock genomics has been presented in just few studies with promising perspectives.
Genome-wide association studies with metabotypes (mGWAS) described thus far in cattle and pigs have linked genomic variability with metabotype levels in relevant biofluids.
Network reconstruction methodologies based on systems genetics concepts have been applied to disentangle the complexity of metabolomics information and linking metabolomics with other omics data.
New and conventional traits and related genetic architecture could be better defined using metabotypes opening opportunities for novel applications in animal breeding.