Investigating Blood Biomarkers of Economic Traits in Sheep Using Metabolomics
Creators: Goldansaz, Seyed Ali 
Publisher: name: University of Alberta Library
Year: 2022

<p>Livestock metabolomics is an emerging field of metabolomics that is growing at a fast rate. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping livestock scientists paint a far more complete picture of animal metabolism and physiology. It is also helping livestock researchers identify robust biomarkers of health and disease. In this thesis, I applied livestock metabolomics techniques to study domestic sheep with the overarching objective of identifying blood biomarkers for important economic traits in sheep farming. In particular, I focused on several key traits including feed efficiency (the major pillar of cost of production), carcass merit and pregnancy (traits with substantial contribution to farm income). To lay the groundwork for these studies, I first conducted a systematic review of livestock metabolomics (chapter two of this thesis). The intent was to assess the status of livestock metabolomics in general, and to identify important gaps and trends relative to other fields of metabolomics research. As part of this review, I compiled all the known livestock metabolome data published until 2017 and made it publicly available in the Livestock Metabolome Database (LMDB; available at <a href="http://www.lmdb.ca" rel="noopener noreferrer" target="_blank">www.lmdb.ca</a>). Using the knowledge gained from this review, I then conducted a study that looked at how metabolomics could assess residual feed intake (RFI; a measure of feed efficiency) and carcass merit in sheep (chapter three of this thesis). Direct measurement of these traits is labor-intensive and expensive. Therefore, finding or developing easily measured metabolite markers for these traits would be expected to reduce operator costs and encourage their widespread measurement. Using a combination of quantitative metabolomic methods, I assessed the serum metabolome and identified 161 unique metabolites. I also identified a panel of candidate serum biomarkers consisting of three metabolites for predicting sheep RFI (with an area-under-the-receiver-operating-characteristic-curve [AU-ROC]=0.80), and two panels of candidate serum biomarkers for predicting sheep carcass merit, including seven metabolites for carcass yield grade (AU-ROC=0.77) and one metabolite for carcass muscle-to-bone ratio (AU-ROC=0.74). In chapter four, I used quantitative metabolomic techniques to identify and validate blood biomarkers of sheep pregnancy and litter size (PLS). Early detection of pregnant ewes and the number of lambs expected allows producers to adjust their management practices and feed rations based on ewe pregnancy requirements. I employed a longitudinal experimental design with separate discovery and validation phases aimed at identifying candidate blood biomarkers of sheep PLS. In doing so, I identified and quantified 107 metabolites associated with ewe pregnancy, and validated three panels of biomarkers (AU-ROC of 0.81-0.93) that can identify ewe PLS as early as 50 days post-breeding. These biomarkers are currently being translated into a handheld device that could be used as a low-cost, pen-side test for ewe PLS. It is hoped that the methods presented in this thesis would encourage more widespread application of metabolomics in livestock research, and the results presented here would provide added value for the sheep industry.</p>