10 Utilizing1H NMR Spectroscopy to Quantify and Identify Biomarkers in Finishing Sheep

Abstract

Abstract Backfat and carcass fatness is an important quality attribute in meat animals. A substantial economic gain in the livestock industry may result from the discovery of metabolites, which can improve methods for predicting desirable livestock traits before harvest. Complex phenotypes can be identified for genetic selection or precision management using metabolic and genetic biomarkers. An analysis of ovine samples collected before harvest from wethers with different degrees of back fat was conducted using serum samples obtained from 15 sheep (5 from each back fat class), 60 d, 30 d, and just before harvest. This study quantified 55 serum metabolites that play important roles in ovine metabolism by 1H nuclear magnetic resonance (NMR) spectroscopy. An RNAseq dataset was generated from each sheep's muscle and adipose tissue at harvest. A statistical analysis of the data was performed using MetaboAnalyst Version 5.0 software in R. The results of multiple analyses showed that three metabolites, betaine, choline, and dimethylamine, are associated with sheep's fat class at a significance of (P < 0.01). Integration with gene expression datasets is still underway due to the limitations of annotating sheep genes. In addition, these metabolites are novel and have never been shown to modulate fat class in sheep. To elucidate methods of predicting which livestock produce ideal carcasses, further research is needed to investigate how betaine and choline impact fatness in sheep.