INTEGRATING METABOLOMICS AND GENOMICS BIOMARKERS TO IMPROVE PRODUCTION EFFICIENCY IN SHEEP
Date
2025-08-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
The growing global demand for food coupled with increasing pressure on natural resources, underscores the urgent need for more sustainable and efficient livestock production systems. In the context of sheep production, improving FE is a critical strategy for enhancing productivity, reducing input costs, and minimizing the environmental footprint of animal agriculture. This thesis set out to address these challenges by integrating phenotypic performance testing, metabolomics, and genomics to better understand and improve FE in sheep. Through a combination of DMI test optimization, metabolomics biomarker discovery, and selection signatures analyses, the study contributes new insights and tools for precision breeding. Chapter three addressed the inconsistency in FE testing by demonstrating that DMI testing can be significantly reduced in duration without sacrificing accuracy and precision of the FE test. The results showed that ewes, rams, and mixed-sex groups can be reliably evaluated for DMI using only 22, 24, and 25 days of data.
Description
The growing global demand for food coupled with increasing pressure on natural resources, underscores the urgent need for more sustainable and efficient livestock production systems. In the context of sheep production, improving FE is a critical strategy for enhancing productivity, reducing input costs, and minimizing the environmental footprint of animal agriculture. This thesis set out to address these challenges by integrating phenotypic performance testing, metabolomics, and genomics to better understand and improve FE in sheep. Through a combination of DMI test optimization, metabolomics biomarker discovery, and selection signatures analyses, the study contributes new insights and tools for precision breeding. Chapter three addressed the inconsistency in FE testing by demonstrating that DMI testing can be significantly reduced in duration without sacrificing accuracy and precision of the FE test. The results showed that ewes, rams, and mixed-sex groups can be reliably evaluated for DMI using only 22, 24, and 25 days of data, respectively, instead of the conventional 38-day test period. This finding supports cost-effective and scalable FE assessment, especially critical for smaller operations or national breeding programs with limited resources. Furthermore, chapter four explored the metabolic profile of FE using a targeted DI/LC-MS/MS metabolomics approach. It revealed significant time-dependent shifts in serum metabolite profiles between high and low FE animals. Key metabolites, including citric acid, PC aa C32:2, and SM(OH) C22:1 were identified across multiple timepoints with high predictive value (AUC: 0.86, 0.84, and 0.72 at 0, 28, and 64 days, respectively). Pathways such as glycerophospholipid metabolism and arachidonic acid metabolism were consistently enriched, suggesting a strong physiological link between lipid metabolism, energy utilization, and FE. These insights advance our understanding of the biochemical processes driving FE and highlight the potential of metabolite biomarkers as early, non-invasive tools for selection. In chapter five, whole-genome resequencing and selection signatures techniques were applied to identify genomic regions under selection for FE. Candidate genes such as PER2, EGFR, GLP1R, ITGB1, and SNRPN were located in regions with high Fst and θπ values, suggesting recent selection and relevance to traits like metabolism, circadian rhythm regulation, immune modulation, and neural signaling. The discovery of these genes, some of which have had known associations with FE and growth in other species adds to the species-specific genomic architecture of FE in sheep and lays the groundwork for marker-assisted or genomic selection strategies. By integrating shortened performance testing protocols, metabolic biomarker profiling, and genome-wide selection signatures mapping, this study demonstrates the power of multi-omics approaches to enhance the precision, efficiency, and biological relevance of selection for FE in sheep. The outcomes offer a comprehensive framework for precision breeding that aligns with global goals for sustainable agriculture and provides practical solutions for Canadian and international sheep producers facing rising input costs and tightening profit margins. Overall, this body of work not only contributes scientific knowledge but also provides tangible pathways for industry implementation, positioning integrated omics selection as a viable and transformative approach to improve livestock efficiency, sustainability, and competitiveness in the face of global challenges.
Keywords
Feed efficiency, Serum metabolites, Ewe lambs, Residual intake gain, Candidate biomarkers, Genomics selection, Selection signatures