Enhancing Sustainability of Cattle Production Systems through Discovery of Biomarkers for Feed Efficiency

Abstract

Feed inputs represent the largest variable cost of producing meat and milk from ruminant animals. Thus, strategies that improve the efficiency of feed utilization are needed to improve the global competitiveness of Israeli and U.S. cattle industries, and mitigate their environmental impact through reductions in nutrient excretions and greenhouse gas emissions. Implementation of innovative technologies that will enhance genetic merit for feed efficiency is arguably one of the most cost-effective strategies to meet future demands for animal-protein foods in an environmentally sustainable manner. While considerable genetic variation in feed efficiency exist within cattle populations, the expense of measuring individual-animal feed intake has precluded implementation of selection programs that target this trait. Residual feed intake (RFI) is a trait that quantifies between-animal variation in feed intake beyond that expected to meet energy requirements for maintenance and production, with efficient animals being those that eat less than expected for a given size and level of production. There remains a critical need to understand the biological drivers for genetic variation in RFI to facilitate development of effective selection programs in the future. Therefore, the aim of this project was to determine the biological basis for phenotypic variation in RFI of growing and lactating cattle, and discover metabolic biomarkers of RFI for early and more cost-effective selection of cattle for feed efficiency. Objectives were to: (1) Characterize the phenotypic relationships between RFI and production traits (growth or lactation), (2) Quantify inter-animal variation in residual HP, (3) Determine if divergent RFIphenotypes differ in HP, residual HP, recovered energy and digestibility, and (4) Determine if divergent RFI phenotypes differ in physical activity, feeding behavior traits, serum hormones and metabolites and hepatic mitochondrial traits. The major research findings from this project to date include: In lactating dairy cattle, substantial phenotypic variation in RFI was demonstrated as cows classified as having low RMEI consumed 17% less MEI than high-RMEI cows despite having similar body size and lactation productivity. Further, between-animal variation in RMEI was found to moderately associated with differences in RHP demonstrating that maintenance energy requirements contribute to observed differences in RFI. Quantifying energetic efficiency of dairy cows using RHP revealed that substantial changes occur as week of lactation advances—thus it will be critical to measure RMEI at a standardized stage of lactation. Finally, to determine RMEI in lactating dairy cows, individual DMI and production data should be collected for a minimum of 6 wk. We demonstrated that a favorably association exists between RFI in growing heifers and efficiency of forage utilization in pregnant cows. Therefore, results indicate that female progeny from parents selected for low RFI during postweaning development will also be efficient as mature females, which has positive implications for both dairy and beef cattle industries. Results from the beef cattle studies further extend our knowledge regarding the biological drivers of phenotypic variation in RFI of growing animals, and demonstrate that significant differences in feeding behavioral patterns, digestibility and heart rate exist between animals with divergent RFI. Feeding behavior traits may be an effective biomarker trait for RFI in beef and dairy cattle. There are differences in mitochondrial acceptor control and respiratory control ratios between calves with divergent RFI suggesting that variation in mitochondrial metabolism may be visible at the genome level. Multiple genes associated with mitochondrial energy processes are altered by RFI phenotype and some of these genes are associated with mitochondrial energy expenditure and major cellular pathways involved in regulation of immune responses and energy metabolism.