Abstract
Residual feed intake (RFI) is an important measure of feed efficiency for agricultural animals. Factors associated with cattle RFI include physiology, dietary factors, and the environment. However, a precise genetic mechanism underlying cattle RFI variations in duodenal tissue is currently unavailable. The present study aimed to identify the key genes and functional pathways contributing to variance in cattle RFI phenotypes using RNA sequencing (RNA-seq). Six bulls with extremely high or low RFIs were selected for detecting differentially expressed genes (DEGs) by RNA-seq, followed by conducting GO, KEGG enrichment, protein-protein interaction (PPI), and co-expression network (WGCNA, n = 10) analysis. A total of 380 differentially expressed genes was obtained from high and low RFI groups, including genes related to energy metabolism (ALDOA, HADHB, INPPL1), mitochondrial function (NDUFS1, RFN4, CUL1), and feed intake behavior (CCK). Two key sub-networks and 26 key genes were detected using GO analysis of DEGs and PPI analysis, such as TPM1 and TPM2, which are involved in mitochondrial pathways and protein synthesis. Through WGCNA, a gene network was built, and genes were sorted into 27 modules, among which the blue (r = 0.72, p = 0.03) and salmon modules (r = −0.87, p = 0.002) were most closely related with RFI. DEGs and genes from the main sub-networks and closely related modules were largely involved in metabolism; oxidative phosphorylation; glucagon, ribosome, and N-glycan biosynthesis, and the MAPK and PI3K-Akt signaling pathways. Through WGCNA, five key genes, including FN1 and TPM2, associated with the biological regulation of oxidative processes and skeletal muscle development were identified. Taken together, our data suggest that the duodenum has specific biological functions in regulating feed intake. Our findings provide broad-scale perspectives for identifying potential pathways and key genes involved in the regulation of feed efficiency in beef cattle.
Highlights
In the beef industry, feed provision accounts for more than 70% of total input costs (Patience et al, 2015)
All animal’s performance was presented in (Supplementary Table S3), and differential analysis for HRFI and LRFI group showed that the average daily feed intake (ADFI) and Residual feed intake (RFI) values were significantly higher in the HRFI group than in the LRFI group (p 0.004 and p 0.006, respectively) (Table 1)
Based on ADFI, we found that the HRFI group consumed 11.97% more feed than the LRFI group, average daily gain (ADG) values did not show significant differences between the Symbola log2FCb q-valuec
Summary
In the beef industry, feed provision accounts for more than 70% of total input costs (Patience et al, 2015). RFI is independent of growth traits such as average daily gain (ADG) and body weight (BW) (Baker et al, 2006) and is mainly related to economic traits such as dry matter intake (DMI) and feed conversion efficiency (FCR) (Gomes et al, 2012). Pathways such as adenosine 5′monophosphate (AMP)-activated protein kinase (AMPK) signaling (Karisa et al, 2014), metabolic pathways and oxidative stress (Tizioto et al, 2017), lipid metabolism (Tizioto et al, 2015), and the immune response (Gondret et al, 2017) were reported to be involved in RFI variance. Genes such as COL14A1 (de Lima et al, 2020), OGN (Vigors et al, 2019), ACE (Yi et al, 2015), and SMCT (de Lima et al, 2020) and quantitative trait loci such as EFEMP1 (de Lima et al, 2020) and SHC3 (Weber et al, 2016) were identified to be potentially related with RFI
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
