Abstract
Beef production is an important component of the world's food supply, with production being near 59 million tons in 2023 (USDA, 2023). Enhancing our understanding of the factors influencing metabolism will lead to improvements in production efficiency. Using RNA-seq and WGCNA of longissimus muscle samples, gene expression and metabolic pathway analyses were performed to examine relationships with ultrasound and body mass variables. In this study, body weight (BW), ultrasound back fat (BF), ultrasound muscle depth (MD), and body condition score (BCS) were traits recorded for 18 cull beef cows. As expected, all production-related traits monitored (WT, BF, MD, and BCS) in this study exhibited a positive correlation with each other. Large-scale transcriptome analyses were performed using RNA extracted from longissimus dorsi muscles. Weighted correlation network analysis (WGCNA) was employed to associate changes in traits with gene expression. In WGCNA, the dark-green module demonstrated a positive correlation (cor) with all traits, with the highest observed for BF (cor = 0.45, p = 0.07) and MD (cor = 0.45, p = 0.07). Functional analysis of the dark-green module highlighted olfactory transduction (p = 0.03) and RNA processing as significantly correlated (p = 0.08) with production traits. Additionally, the hematopoietic cell lineage pathway was reported as the most significant negative correlation with muscle depth (cor = -0.71, p = 0.001). We identified four hub genes (i.e., SEPTIN9, NONO, CCDC88C, and CACNA2D3) showing relationships with the traits measured. These findings provide further understanding of the molecular mechanisms influencing muscle and fat accretion in cull beef cows.