The future of systems genetics in farm animal sciences, a route out of the data jungle

Farm animal species are under intense selection on relatively small population sizes. Genetic and genomic selection has provided remarkable genetic gains in the last century. Nevertheless, current methods aiming to link genome to phenome in such populations remain limited, notably due to the difficulty to identify causal variants for complex traits. The diversity of species as well as breeds in livestock has diluted the number of genomic datasets available for each genome as compared to model organisms or human diseases. In this article, we propose a systems genetics approach as an opportunity to go beyond current limits and find a way out of the data jungle, taking advantage of novel computational development allowing integration of omics datasets from different analyses across species. A major challenge is that systems genetics requires careful but efficient data and metadata management, as well as rigorous statistical strategies on which approach to use. Here, we highlight examples of the broad contribution systems genetics can bring to farm animal sciences, particularly across species, notably in the genome-to-phenome field within the larger scope of agricultural challenges, including adaptation to environmental changes and animal welfare.