Impact of Genetics on Meat Quality of Pigs and Beef Cattle by Huaigang Lei A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Animal Science Department of Agricultural, Food and Nutritional Science University of Alberta © Huaigang Lei, 2019 Abstract Meat has changed its role from just providing necessary nutrition for the human body to improving the quality of life by giving us eating satisfaction, resulting in the impetus for scientific research on meat quality. Although many strategies have been taken to improve meat quality, unacceptably inferior meat still exists, causing economic loss for the meat industry. Potentially, improving meat quality through animal breeding offers opportunities to obtain superior meat. Hence, to explore the possibility of future genetic selection of animals for meat quality, several studies investigating different meat quality traits, different species, and different sample handling strategies were conducted. Dark cutting beef is a significant defect caused by depletion of muscle glycogen before slaughter that may be affected by animal genetics. A case-control genome-wide association study (GWAS) on two groups of beef cattle was conducted and dark-cutting was analyzed as a binary trait (cases versus controls) using logistic regression in an additive model. There were no significant loci identified when correcting for multiple testing (false discovery rate, FDR) using a FDR < 0.05 threshold. The regions with the strongest support for association with the occurrence of dark cutting were identified using a 1 MB window and functional analysis using the Ingenuity Pathway Analysis (IPA), which identified genes involved in pyruvic acid modification, 2- deoxyglucose clearance and disposal, pyruvic acid release, sucrose recognition, energy production and metabolism of carbohydrate. Although the detected SNP associations require validation, results suggested the possibility for marker-assisted genomic selection of beef cattle for reduced likelihood of dark cutting; however, based on these results a much larger number of case samples will be required to validate these observations ii Consumer willingness to pay a premium when purchasing pork chops is driven by eating satisfaction. Genetic parameters were estimated for loin muscle sensory traits within a swine population and their associations with loin pH and intramuscular fat were analyzed. Animal pedigree and genotype information were analyzed separately, and positive genetic correlations between sensory measurements and pH and intramuscular fat were found, indicating that selection for intermediate pH and high intramuscular fat can help to increase sensory scores. However, as the genetic correlations were moderate to low, increase in pork sensory scores through selection for loin pH and intramuscular fat content would be slow. Important meat quality characteristics have been measured on fresh and previously frozen meat as part of previous genetic studies, but freezing may alter meat quality characteristics and therefore the relationships between genetic components and meat quality measurements. Results showed that pork quality traits measured before and after freezing and thawing were significantly (P<0.0001) different from each other and that intramuscular crude fat content exerted a large effect on the magnitude of change in L* (lightness) and b* (yellowness). Meat quality measurements of fresh pork were moderately to highly heritable except for b* and pH, with heritability estimates for L*, pH and drip loss higher when measured on fresh rather than frozen- thawed samples. Considering heritability and genetic correlation results, it could be concluded that whilst either fresh or frozen-thawed pork samples can be used for L*, a* (redness) and b* measurements can be used in genetic selection, pH and possibly drip loss should be measured in fresh pork samples rather than in those that have been frozen-thawed. Tenderness is one of the most important factors considered by consumers when purchasing meat and intramuscular connective tissue (IMCT) is a major factor responsible for the cooked meat background toughness. A GWAS was designed to identify variations (e.g.: iii single nucleotide polymorphisms (SNPs)) in genes along the genome associated with total collagen and collagen solubility. In total, 130 SNPs were detected for 3-day postmortem (3 dpm) total collagen content using SNP windows that explained more than 1% of the additive genetic variance, while 160 SNPs were detected for 3 dpm collagen solubility, and 150 and 190 SNPs were detected for 13 dpm total collagen content and collagen solubility, respectively. These results should be validated in a large beef cattle group before considering marker-assisted or genomic selection in beef cattle to increase beef tenderness. Collectively these results indicated that selection against dark cutting and for increased collagen solubility in beef, and for increased pork acceptability may be possible. iv Preface Along with the development of society, the role of meat has changed from just providing necessary nutrition for the human body to improving the quality of life by giving us eating satisfaction, leading to comprehensive scientific research in the meat quality area. Regardless of the many strategies being taken to improve meat quality, unacceptable meat with inferior quality persists, causing economic loss for the meat industry. Potentially, improving meat quality through animal breeding may lead to superior meat. This thesis incorporated several studies to explore the possibility of future genetic selection of animals to produce better meat. In Chapter 2 (A genome-wide case-control association study of dark cutting in beef cattle), two groups of beef cattle were used for genome-wide association study (GWAS) to identify variations (e.g.: SNPs) in genes associated with dark cutting beef and explore the biological relevance of those genes in the formation of dark cutting beef. This chapter has been submitted to Canadian Journal of Animal Science where Dr. Tianfu Yang, Dr. Shahid Mahmood, Dr. Bimol C. Roy, Dr. Changxi Li, Dr. Graham S. Plastow, and Dr. Heather L. Bruce are co- authors. For Chapter 3 (Genetic parameter estimation for sensory traits in longissimus muscle and their association with pH and intramuscular fat in pork chops), genetic parameters, including heritability, genetic and phenotypic correlations, were estimated for sensory traits of the longissimus muscle from 784 crossbred commercial pigs. The influence of intramuscular fat content and pH on pork chop sensory acceptability was also discussed. The sensory panel was run by Dr. Chamali Das. The data were analyzed using animal pedigree information and genotype information separately, and their difference was discussed. v For Chapter 4 (Efficacy of genetic parameter estimation of pork loin quality of crossbred commercial pigs using technological quality measurements of frozen and unfrozen product), fresh and frozen-thawed meat samples from more than 2000 crossbred commercial pigs were used to estimate genetic parameters, such as heritability, and genetic and phenotypic correlations between fresh and frozen-thawed products. This study reached a conclusion that either fresh or frozen-thawed samples could be used for L*, a* and b* measurements, but pH and drip loss should be measured in fresh samples rather than in frozen-thawed ones for genetic selection. Chapter 4 has been published in the Canadian Journal of Animal Science where Dr. Chunyan Zhang, Dr. Changxi Li, Dr. Graham S. Plastow, and Dr. Heather L. Bruce are co-authors (Canadian Journal of Animal Science, 2018, 98(3): 453-462, https://doi.org/10.1139/cjas-2017- 0154). Chapter 5 (Genome-wide association study of collagen in beef cattle) aims to identify variation (e.g. SNPs) in genes along the genome associated with total collagen and collagen solubility, and to explore the biological relevance of the genes to beef toughness caused by intramuscular connective tissue. In total, 137 beef cattle raised and managed at the Roy Berg Kinsella Ranch, University of Alberta, Canada, were used in this study. Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) was used for GWAS and significant results (SNP windows that explained more than 1% additive genetic variance) were obtained. Huaigang Lei vi To my wife, Tao Wang vii Acknowledgement I am extremely, deeply grateful to my supervisor Dr. Heather Bruce, for her excellent supervision and constant support during the whole time of my Ph.D. program. Dear Dr. Bruce, I really appreciate that you gave me the chance to join your group at the very beginning, and for subsequent plenty of opportunities and guidance you gave me to improve myself both in science and life. I am also very thankful that you inspired me to be serious-minded on what we are focusing on. I give my sincere gratitude to Dr. Changxi Li and Dr. Graham S. Plastow for their generous support and guidance as my Ph.D. supervisory committees. Without your knowledge, criticism, and support, there was no way I could finish my Ph.D. program. You both impressed upon me deeply during the supervisory process and I am very grateful for that. I owe my gratitude to Dr. Leluo Guan and Dr. Richard Uhrig for their time and criticism on my research during my candidacy exam. Thank you Dr. Ben Willing, Dr. David Wishart, Dr. Neil Harris, and Dr. Rongcai Yang for all the support you gave me during the courses I was taking. Special thanks are given to Dr. Bimol C. Roy, for his countless cares in the lab; to Dr. Shahid Mahmood for his generous suggestions about graduate studies here at the University of Alberta; to Dr. Linda Ho for her support during my program; to Dr. Chunyan Zhang, Dr. Tianfu Yang, and Dr. Tiago Valente for their guidance of my studies. Many thanks are given to all the colleagues in Dr. Bruce’s lab and Livestock Gentec, they all helped me at some extent during my study. They are: Dr. Chamali Das, Dr. Elda Dervishi, Dr. Everestus Akanno, Dr. Feng Zhang, Dr. Kirill Krivushin, Dr. Marzieh Heidaritabar, Dr. viii Mohammed Abo-Ismail, Dr.