Metabolomics identifies novel biomarkers for fat deposition, feed efficiency and growth in Italian Large White pigs

The Italian heavy pig sector relies on key traits that need optimization: feed efficiency, as pigs are slaughtered at a heavier weight; growth, as they have a minimum slaughter age; and the right fat proportion, since their meat is used for high-quality dry-cured hams. Advances in omics suggest that plasma untargeted metabolomics may provide biomarkers to improve evaluation accuracy. This study analyzed over 700 Italian Large White pigs, with random residuals extracted from genetic indexes routinely collected for selection. Pigs were grouped into five pools based on the trait of interest: feed conversion ratio (FCR), average daily gain (ADG), backfat thickness (BFT), lean cut (LC), and ham weight (HW). Machine learning, including the Boruta algorithm, identified discriminant metabolites associated with these traits. The SNP-based heritability of key metabolites was estimated using GEMMA. Boruta analyses detected 8 to 26 discriminant metabolites per trait, with only partial overlap. The most common were sphingomyelins, leucine-, isoleucine-, valine-, and tyrosine-derived metabolites. The highest metabolite overlap was found between HW and LC, sharing ~50%, especially amino acids. The average heritability was 0.25(±0.11), with three metabolites exceeding 0.5. These findings highlight the trait interplay and demonstrate metabolomics’ potential in identifying biochemical markers for growth, feed efficiency, and fat deposition. Such metabolites could enhance selection precision for high-quality dry-cured ham production. The research was supported by the Italian PRIN2022 project FEEDTHEPIG, funded by the European Union – NextGenerationEU under the National Recovery and Resilience Plan (PNRR) – Mission 4 Education and research – Component 2 From research to business – Investment 1.1 Notice PRIN 2022 PNRR (DD N. 1409 del 14/09/2022), proposal code P2022FZMJ9 – CUP J53D23018310001.