PSIX-16 - Urine Metabolome and Whole Blood Transcriptome of Beef Steers with Low or High Residual Feed Intake

Abstract: We analyzed the metabolome of urine samples to identify urinary metabolic biomarkers and whole blood transcriptome-based gene set enrichment to identify key pathways associated with divergent selection for low or high RFI in beef cattle. Low-RFI beef steers (n = 8; RFI = - 1.93 kg/d) and high-RFI beef steers (n = 8; RFI = + 2.01kg/d) were selected from a group of 56 growing crossbred beef steers after a 49-d performance testing period. At the end of the 49-d period, weekly urine and blood samples were collected three times from the low- and high-RFI steers. Metabolome analysis of the urine samples was conducted using a liquid chromatography–mass spectrometer and biomarker analysis of the metabolome data was performed to identify candidate biomarkers (FDR ≤ 0.05; AUC ≥ 0.85) associated with RFI. Whole-blood RNA sequencing was performed on an Illumina sequencer and gene set enrichment analysis (GSEA) was used to analyze differentially expressed (FDR ≤ 0.05) pathways. A total number of 557 metabolites were detected and identified. Biomarker analysis of the metabolome data identified N-acetyl-L-tyrosine, O-methyl-L-threonine, uridine, and threoninyl-hydroxyproline as candidate biomarkers (FDR ≤ 0.05; AUC > 0.85) of RFI. Results of GSEA revealed pathways associated with protein metabolism, cellular responses to external stimuli, and stress were differentially inhibited in high-RFI compared with low-RFI beef cattle, while pathways associated with binding and uptake of ligands by scavenger receptors and erythrocytes release/take up oxygen were differentially enriched (FDR < 0.05) in high-RFI beef steers. Taken together, our results revealed that urine is a potential source of metabolite biomarkers associated with RFI and beef steers divergently selected for low or high RFI have differential expressions of genes related to protein metabolism and stress responsiveness. high RFI revealed differential expressions of genes related to protein metabolism and stress responsiveness.