Multi-omics Approach to Predict Economically Important Health and Production Traits in Livestock

The main objectives of the project are to:
1.Improve our understanding of the biological background of health attributes (including resistance to diseases), and carcass characteristics by utilizing genome-wide association studies (GWAS) and post-GWAS analysis.
2.Utilise metabolomics to identify intermediate molecular markers (i.e. metabolites) associated with health and carcass characteristics.
3.Investigate the genomic background of metabolites using metabolite GWAS (mGWAS).
4.Develop a standard genomic best linear unbiased prediction (gBLUP) model (Base Model) to predict traits of interest.
5.Develop novel multi-omics linear prediction models, compare their accuracy with the Base Model, and apply innovative predictive models to enhance precision genomic sheep breeding.
The project will use existing Agri-Food and Bioscience Institute (AFBI) big data collected over the last five years, including phenotypes (health recordings, high precision carcass characteristics and other key performance indicators such as live weight gain), and genomics and metabolomics data acquired from innovative sheep research projects.