As global and national pressures to enhance the sustainability and efficiency of beef cattle production continue to grow, the Canadian beef industry requires a multifaceted approach to address these challenges. One promising and enduring solution lies in leveraging genetic and genomic technologies to enhance breeding strategies. By selecting for beef cattle with improved feed efficiency, producers can reduce feed resource use, lower emissions, and maintain the same level of production.
The focus of this research was to investigate the functional genetics underlying feed efficiency in Canadian beef cattle and identify functional SNP markers associated with this trait. Selecting for feed efficient (FE) cattle, measured by Residual Feed Intake (RFI; kg/d), has the potential to increase lean meat yield without requiring additional feed. Using RNA-Sequencing technology, we uncovered genetic mechanisms driving feed efficiency by identifying key regulatory genes, functional SNP markers, and associated QTLs. This approach enables the detection of genetic mutations (SNPs) derived from DNA sequence data that may influence feed efficiency, providing valuable insights for improving sustainability in beef production.
A population of 48 Canadian beef cattle from the Roy Berg Kinsella Research Ranch (Alberta, Canada), including 16 Angus, 16 Charolais, and 16 Kinsella hybrid composite animals were selected from a larger cohort of 738 cattle based on their extreme FE phenotypes. At slaughter, rumen papillae tissue was collected from each animal for RNA extraction.
The study identified 11 key regulatory genes (EIF4B, USP43, RHOD, SERPINB2, MYH1, MYL2, TCEANC, CKM, MYLPF, TNNC2, and ENSBTAG00000040518) that were significantly differentially expressed between high and low FE groups. These genes were linked to muscle contraction and muscle cell biological processes.
Analysis of functional SNPs revealed 1,137 uniquely fixed SNPs in the high FE group and 1,190 in the low FE group across breeds. When examining the co-localized QTL classes overlapping with these functional SNPs, we found distinct patterns:
- High FE SNPs evenly overlapped with four major QTL classes: Meat and Carcass (18.19%), Milk (27.34%), Reproduction (23.95%), and Production (27.08%), with a smaller proportion overlapping with Health (1.87%) and Exterior (1.57%).
- Low FE SNPs predominantly overlapped with Milk QTLs (59.65%), followed by Meat and Carcass (7.91%), Reproduction (14.95%), and Production (11.61%), with a smaller proportion overlapping with Health (2.83%) and Exterior (3.05%).
These findings suggest that less feed-efficient cattle may allocate more energy toward milk-related traits, while more feed-efficient cattle direct energy toward performance traits, such as meat production and yield. Selecting for higher feed efficiency in beef cattle could thus optimize energy partitioning for production-related traits, benefiting the beef industry.
The results of this research were presented at two major conferences and at the Ontario Beef Field Day:
- The American Society of Animal Science – Canadian Society of Animal Science – Western Section ASAS (ASAS-CSAS-WSASAS) conference in Calgary, Alberta, in July 2024.
- The European Federation of Animal Science (EAAP) conference in Florence, Italy, in September 2024.
- The Ontario Beef Research Centre (OBRC) Beef Field Day in Elora, Ontario, Canada in October 2024.
Authors: Stephanie Lam1, Leluo Guan2, Graham Plastow3, Ángela Cánovas1
1 Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada; 2 The University of British Columbia, Faculty of Land and Food Systems, Vancouver, Canada; 3 Livestock Gentec, University of Alberta, Department of Agriculture, Food and Nutritional Science, Edmonton, Canada
This research highlights the importance of collaboration between the University of Guelph’s Centre for Genetic Improvement of Livestock and the University of Alberta’s Livestock Gentec, and now UBC with Leluo Guan’s move there, to leverage Canadian herd databases and deliver actionable insights to benefit beef producers and the entire value chain.