Multi-omics approaches to predict feed efficient sheep

Sheep farming has long been an important part of the rural economy and culture of the United Kingdom. It has always aimed to increase production efficiency to guarantee a plentiful supply of food and to keep producers profitable. However, feed costs have risen dramatically in recent years and continue to increase, posing a significant threat to producer profitability. In sheep production systems, feed accounts for more than 63% of total production costs. As a result, increasing productivity while using less feed and lower feed costs is becoming an increasingly tough dilemma for sheep producers. This piques farmers' interest in identifying and breeding animals with improved FE, which can aid in lowering overall production costs by employing genetic advancements for FE. Because metabolites are most closely related to biological phenotypes, identifying the metabolite biomarkers for FE can assist in distinguishing between feed-efficient and feed-inefficient animals. In doing so, it is also crucial to consider features such as carcass and meat quality, which may be affected positively or negatively by selecting feed efficient animals. The goal of this project will be to use metabolomics to identify metabolite markers associated with FE, carcass, and meat quality and to examine their biological backgrounds using big data deposited in the AFBI's NIFAB database. Secondly, utilising GWAS and post-GWAS analyses, relevant SNP markers in genomic datasets will be discovered. Finally, integrated genomics and metabolomics studies will be conducted to better understand the molecular basis of the genes and metabolites linked to FE, carcass, and meat quality parameters. The study will advise sheep farmers on the possibilities offered by genomics and metabolomics in selecting animals for breeding, as well as increasing farm profit potential by making FE selection more attainable at the farm level, making it easier to include as a breeding objective in ruminant systems.

FE: Feed efficiency, AFBI: Agri-food & Biosciences Institute, NIFAB: Northern Ireland Farm Animal Biobank, SNP: Single Nucleotide polymorphisms, GWAS: Genome-Wide Association Studies