Application of Multi-Omics Approaches to Maximize Beef Production by Aidin Foroutan Naddafi A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Animal Science Departments of Agricultural, Food & Nutritional Science and Biological Sciences University of Alberta © Aidin Foroutan Naddafi, 2021 1 ABSTRACT Approximately 70% of the cost of beef production is impacted by dietary intake. Maximizing production efficiency of beef cattle requires not only genetic selection to maximize feed efficiency (i.e. residual feed intake - RFI), but also adequate nutrition throughout all stages of growth and development to maximize efficiency of growth and reproductive capacity - even during gestation. Nutrient restriction during gestation has been shown to negatively affect postnatal growth and development as well as fertility of the offspring. This, when combined with RFI, may significantly affect energy partitioning in the offspring and subsequently important performance traits. Therefore, we decided to conduct a comprehensive multi-omics study (metabolomics, transcriptomics, epigenomics) to understand the biological mechanisms impacted by prenatal nutrition (normal-diet or Ndiet versus low-diet or Ldiet) and/or parental RFI (high-RFI or HRFI versus low-RFI or LRFI) in young Angus bulls. Four different tissues (Longissimus thoracis (LT) muscle, semimembranosus (SM) muscle, liver, and testis) and three biofluids (serum, semen, and ruminal fluid) were analyzed. Through the metabolomics study, we created the Bovine Metabolome Database (BMDB; www.bovinedb.ca) which contains 51,801 metabolites with unique compound structures in various tissues and biofluids. We also identified two serum candidate biomarker panels ((1) formate and leucine; (2) C4 (butyrylcarnitine) and LysoPC(28:0)), which can distinguish HRFI from LRFI animals with high sensitivity and specificity (area under the curve from receiver-operator characteristic (ROC) or AUROC > 0.85). Through the transcriptomics study, we found that differences in selection for parental RFI altered gene expression level of myocyte enhancer factor 2A [MEF2A] in tissues (LT muscle, SM muscle, liver, and testis) of young Angus bulls. Furthermore, the mRNA abundance of protocadherin 19 [PCDH19] in liver, and MEF2A in LT muscle were affected by prenatal undernutrition. We also ii detected correlations between gene expression in tissues with phenotypic measures of feed efficiency and body weight. Through the epigenomics study, we found 652 and 1400 differentially methylated regions (DMRs) that were affected by maternal diet and parental RFI, respectively. Through pathway analysis of the identified DMRs using the Ingenuity Pathway Analysis (IPA) tool, three networks associated with “cell survival and growth”, “disease or abnormalities”, and “connective tissue development” were identified as being overrepresented in the DMRs when comparing the Ndiet group to the Ldiet group. Similar pathway analysis for the HRFI and LRFI bulls showed overrepresentation of the number of DMRs in four networks involved in “embryonic development”, “DNA replication, DNA repair, and RNA processing”, “growth control and homeostasis”, as well as “lipid metabolism”. These findings provided new knowledge regarding underlying biological mechanisms regulating postnatal responses to prenatal nutrition and feed efficiency in beef bulls. iii PREFACE This thesis is an original work by Aidin Foroutan Naddafi. As detailed in the following, some chapters of this thesis have been submitted for publication as scholarly articles in which Dr. Carolyn Fitzsimmons and Dr. David Scott Wishart were the supervisory authors and have contributed to concepts formation and the manuscript composition. A version of Chapter 2 was published as • Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri-Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan, David S. Wishart. The bovine metabolome. Metabolites 2020, 10(6), 233; https://doi.org/10.3390/metabo10060233 A version of Chapter 3 was published as • Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Mark V. Berjanskii, David S. Wishart. Serum metabolite biomarkers for predicting residual feed intake (RFI) of young angus bulls. Metabolites 2020, 10(12), 491; https://doi.org/10.3390/metabo10120491 A version of Chapter 4 was published as • Aidin Foroutan, Julia Devos, David S. Wishart, Changxi Li, Marcos Colazo, John Kastelic, Jacob Thundathil, Carolyn Fitzsimmons. Impact of prenatal nutrition and selection for parental residual feed intake (RFI) on selected gene expression in young Angus bulls. Livestock Science. 2021, 243, 104365; https://doi.org/10.1016/j.livsci.2020.104365 iv CONTRIBUTIONS Chapter 1: I researched and wrote the entire chapter and generated all the figures used in this chapter. Drs. David Wishart and Carolyn Fitzsimmons provided editing and advice on content and layout. Chapter 2: I researched and wrote the chapter and generated all of the tables used in this chapter. I performed the literature review, compiled the data and assisted with entering the data into the BMDB. I also assisted in the design, formatting and editing of the BMDB. Dr. Hamed Piri- Moghadam assisted in ICP-MS data acquisition and Jiamin Zheng assisted in LC-MS/MS data acquisition. The other co-authors, Dr. AnChi Guo and Carin Li, performed the programming and database management required for the database while Dr. Carolyn Fitzsimmons, Dr. Rupasri Mandal, Dr. Hamed Piri-Moghadam, Dr. AnChi Guo, Dr. Le Luo Guan, Dr. David Wishart, Jiamin Zheng, and Carin Li provided editing and content advice. Chapter 3: I researched and wrote the chapter and generated all of the tables used in this chapter. Dr. Mark V. Berjanskii assisted in data analysis. The other co-authors, Dr. Carolyn Fitzsimmons, Dr. Rupasri Mandal, Dr. Mark V. Berjanskii, and Dr. David Wishart provided editing and content advice. Chapter 4: I researched and wrote the chapter and generated all of the tables used in this chapter. Julia Devos assisted in lab experiments. Dr. Marcos Colazo performed estrous synchronization, artificial insemination and sample collection. Dr. John Kastelic, Dr. Jacob Thundathil, and Dr. Carolyn Fitzsimmons designed the animal experiment and collected tissues from the bull progeny. Dr. Changxi Li calculated all RFI values. Dr. David Wishart, Dr. Changxi Li, Dr. Marcos Colazo, Dr. John Kastelic, Dr. Jacob Thundathil, and Dr. Carolyn Fitzsimmons provided editing and content advice. v Chapter 5: I researched and wrote the chapter and generated all of the tables used in this chapter. Dr. Arun Kommadath converted the subset of filtered Differentially Methylated Region (DMR) coordinates from the bovine UMD3.1.1 assembly to the bovine ARS-UCD1.2 assembly. Dr. Marcos Colazo performed estrous synchronization, artificial insemination and sample collection. Dr. John Kastelic, Dr. Jacob Thundathil, Dr. Carolyn Fitzsimmons, and Chinju Johnson assisted in design and collection of semen for the bull progeny. Dr. Changxi Li calculated all RFI values. Dr. David Wishart and Dr. Carolyn Fitzsimmons provided editing and content advice. Chapter 6: I researched and wrote the entire chapter. Drs. David Wishart and Carolyn Fitzsimmons provided editing and advice on content and layout. vi DEDICATION This work is dedicated to my wife, Azadeh Yasari, who has been a constant source of support and encouragement in every single moment of my life. I am truly thankful for having you in my life. This work is also dedicated to my parents, Dr. Abdolreza Foroutan Naddafi and Mrs. Vida Jahanara, for their love, sacrifice, and tolerance. vii ACKNOWLEDGMENTS First and foremost, I would like to express my deepest gratitude and sincere thanks to my supervisors, Dr. Carolyn Fitzsimmons and Dr. David Wishart, for their patience, professional guidance, and support, during the course of my thesis. Thanks to them, I learned the skills necessary to conduct research in a professional manner. This work would not have been possible without their continuous supervision and help. I would especially like to thank Dr. Le Luo Guan as a supervisory committee member for her invaluable and constructive comments, suggestions, and criticisms and for the time she spent to guide. I also would like to thank Dr. Rupasri Mandal, Dr. AnChi Guo, Dr. Hamed Piri- Moghadam, Dr. Mark Berjanskii, Dr. Ghader Manafiazar, Dr. Arun Kommadath, Dr. Allen Zhang, Dr. Changxi Li, Dr. Marcos Colazo, Dr. John Kastelic, Dr. Jacob Thundathil, Julia Devos, Jiamin Zheng, Rahmatollah Rajabzadeh, Amir Behrouzi, Seyed Ali Goldansaz, Shirin Zahraei, Michael Vinsky, Carin Li, Ying (Edison) Dong, Chinju Johnson, Mathew Johnson, and all fellows in The Metabolomics Innovation Centre (TMIC) as well as Alberta Livestock Gentec who have provided me with invaluable assistance, support, and inspiration throughout the course of my study. I also would like to thank Dr. Burim N. Ametaj, Dr. Fozia Saleem, Dr. Souhaila Bouatra, Dr. Nick Psychogios, Dr. Jianguo Xia, Vanessa Neveu, Roman Eisner, Craig Knox, Umar Farooq, Suzanna M. Dunn, Daya G. V. Emmanuel, Shanthipoosan Sivaraman, Ramprakash P. Periasamy, Michael J. Lewis for building the first platform of the Bovine Metabolome Database. I highly appreciate the Alberta Livestock Meat Agency (ALMA) for the financial support of this project. viii TABLE OF CONTENTS CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW ............................................... 1 1.1. INTRODUCTION ..............................................................................................................