UNDERSTANDING THE GENETICS UNDERLYING MASTITIS USING A MULTI-PRONGED APPROACH A Dissertation Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Asha Marie Miles December 2019 © 2019 Asha Marie Miles UNDERSTANDING THE GENETICS UNDERLYING MASTITIS USING A MULTI-PRONGED APPROACH Asha Marie Miles, Ph. D. Cornell University 2019 This dissertation addresses deficiencies in the existing genetic characterization of mastitis due to granddaughter study designs and selection strategies based primarily on lactation average somatic cell score (SCS). Composite milk samples were collected across 6 sampling periods representing key lactation stages: 0-1 day in milk (DIM), 3- 5 DIM, 10-14 DIM, 50-60 DIM, 90-110 DIM, and 210-230 DIM. Cows were scored for front and rear teat length, width, end shape, and placement, fore udder attachment, udder cleft, udder depth, rear udder height, and rear udder width. Independent multivariable logistic regression models were used to generate odds ratios for elevated SCC (≥ 200,000 cells/ml) and farm-diagnosed clinical mastitis. Within our study cohort, loose fore udder attachment, flat teat ends, low rear udder height, and wide rear teats were associated with increased odds of mastitis. Principal component analysis was performed on these traits to create a single new phenotype describing mastitis susceptibility based on these high-risk phenotypes. Cows (N = 471) were genotyped on the Illumina BovineHD 777K SNP chip and considering all 14 traits of interest, a total of 56 genome-wide associations (GWA) were performed and 28 significantly associated quantitative trait loci (QTL) were identified. Special focus was given to the aforementioned mastitis risk traits, and candidate gene investigation revealed both immune function and cell proliferation related genes in the areas surrounding associated QTL, suggesting that selecting for mastitis resistant cows based on these traits would be an effective method for increasing mastitis resiliency in a herd. Tracking the progression of SCS during the study period identified extreme populations of cows that remained “chronic” (SCS ≥ 4) or “healthy” (SCS < 4). Fixation indices were calculated and 2 SNPs identified that demonstrated moderate allelic differentiation of “healthy” from both “chronic” and “average” cows (FST ≥ 0.4). GWAs were performed for SCS at each sampled stage in lactation, area under the SCS curve, and median SCS, and each approach significantly associated unique QTL spanning the genome. This suggests that alternative methods to lactation average SCS must be employed to more efficiently select for mastitis-resistant cows. BIOGRAPHICAL SKETCH Asha Miles was born in Ithaca, NY, just before her family moved to California’s Central Valley. Growing up in a little town in rural San Joaquin County, her passion for agriculture sprouted when she joined the 4-H program in high school. She graduated high school in 2008 during which she spent three years in a Biotechnology Regional Occupation Program. She attended University of California at Davis and earned her Bachelor of Science in Biotechnology in 2012, where she completed an undergraduate honors research thesis in which she created a bioassay for endocrine disrupters in the glucocorticoid signaling pathway. Shortly thereafter, she completed a Master of Science in Animal Biology in 2015, examining the differential expression of antimicrobial peptides in the porcine small intestine after E. coli challenge and treatment with human lysozyme transgenic goat milk. Returning to her Ithaca roots, she enrolled in Cornell’s Animal Science doctoral program in 2015, investigating the genetics underlying mastitis in dairy cattle. Upon completion of her Ph.D., she will begin a postdoctoral scholar position at Pennsylvania State University exploring the role of the microbiome in food animal health and disease. As a biotechnologist, she believes the technological augmentation of agriculture is a critical tool. As an academic, she believes progressive change always begins with education. As a humanitarian, she believes that technology and education can only have meaning if brought to people who need them in an accessible manner. For these reasons, she is dedicated to agricultural research and the global dissemination of information to multiple facets of society, including scientists, regulators, students, and farmers. v To all the teachers, learners, and inspirers I’ve met along the way. vi ACKNOWLEDGEMENTS This work would not have been possible without the support of my Special Committee, the work of many graduate and undergraduate students associated with Cornell Animal Science, the patience of the Cornell Statistical Consulting Unit, research funding by the NIFA Animal Health Project #NYC-127898, personal funding by Investigative Biology in the College of Arts and Sciences, the participation of dairy farmers, and of course, their cows. vii TABLE OF CONTENTS BIOGRAPHICAL SKETCH …………………………………………………………………v DEDICATION ……………………………………………………………………………... vi ACKNOWLEDGEMENTS ……………………………………………………………….. vii CHAPTER 1: INTRODUCTION 1.A: Origins …………………………………………………………………………. 1 1.B: A critical issue for the dairy industry ………………………………………….. 2 1.C: Genetic evaluation of complex traits …………………………………………... 5 1.D: Mastitis and genomic selection ………………………………………………... 9 1.E: Current understanding and gaps in knowledge ……………………………….. 11 References …………………………………………………………………………. 14 CHAPTER 2: UDDER AND TEAT CONFORMATIONAL RISK FACTORS FOR ELEVATED SOMATIC CELL COUNT AND CLINICAL MASTITIS IN NEW YORK HOLSTEINS Title Page …………………………………………………………………………. 23 Abstract …………………………………………………………………………… 24 Introduction ……………………………………………………………………….. 26 Materials and Methods ……………………………………………………………. 27 Results …………………………………………………………………………….. 33 Discussion ………………………………………………………………………… 40 Acknowledgements ……………………………………………………………….. 45 References ………………………………………………………………………… 46 CHAPTER 3: GENOME WIDE ASSOCIATIONS FOR UDDER AND TEAT CONFORMATIONAL RISK FACTORS FOR MASTITIS IN HOLSTEIN COWS Title Page ………………………………………………………………………….. 50 Abstract ……………………………………………………………………………. 51 Introduction ………………………………………………………………………... 53 Materials and Methods …………………………………………………………….. 55 Results ……………………………………………………………………………... 57 Discussion …………………………………………………………………………. 64 Conclusions ………………………………………………………………………... 72 Declarations ………………………………………………………………………... 73 viii References …………………………………………………………………………. 75 CHAPTER 4: TIME- AND POPULATION-DEPENDENT GENETIC PATTERNS UNDERLIE BOVINE MILK SOMATIC CELL COUNT Title Page ………………………………………………………………………….. 90 Abstract ……………………………………………………………………………. 91 Introduction ………………………………………………………………………... 93 Materials and Methods …………………………………………………………….. 94 Results ……………………………………………………………………………... 99 Discussion ………………………………………………………………..………. 105 Conclusions ………………………………………………………………………. 114 Acknowledgements ..……………………………………………………………... 115 References ..………………………………………………………………………. 116 CHAPTER 5: IMPLICATIONS FOR FUTURE RESEARCH AND CONCLUDING REMARKS Concluding Remarks.……………………………………………………………... 139 References ..………………………………………………………………………. 144 ix LIST OF FIGURES Figure 1.1. The “Iceberg Principle”………………………………………………………….. 4 Figure 2.1. The characterization of teat ends………………………………………………..32 Figure 3.1. Creation of a new “mastitis risk” trait…………………………………………..59 Figure 3.2. Manhattan plot for fore udder attachment………………………………………61 Figure 3.3. Manhattan plot for udder depth…………………………………………………62 Figure 3.4. Manhattan plot for udder height………………………………………………...63 Figure 3.5. Manhattan plot for rear teat end shape………………………………………….65 Figure 3.6. Manhattan plot for rear teat width………………………………………………66 Supplementary Figure 3.1. Quantile-Quantile plots………………………………………...86 Figure 4.1. Overview of SCS-based population stratification………………………………97 Figure 4.2. FST by marker comparison of populations……………………………………..101 Figure 4.3. FST by marker and linkage disequilibrium on BTA 4………………………….102 Figure 4.4. Manhattan plots for SCS by lactation stage……………………………………106 Supplementary Figure 4.1. Quantile-Quantile plots………………………………………..129 Figure 5.1. Gene ontology across all approaches…………………………………………..141 x LIST OF TABLES Table 2.1. Explanation of six selected sampling periods………………………………....…29 Table 2.2. A description of the cow demographics………………………………………….34 Table 2.3. Udder and teat trait frequencies……………………………………………… ….36 Table 2.4. Contrast odds ratios for elevated SCC model……………………………………38 Table 2.5. Contrast odds ratios for clinical mastitis model………………………………….39 Table 2.6. The Goodman-Kruskal Gamma statistic of association………………………….41 Table 2.7. Univariate analyses of variables of interest……………………………………... 42 Table 3.1. Udder and teat genome-wide association models………………………………. 58 Supplementary Table 3.1. Significantly associated QTL and candidate genes…………….. 87 Table 4.1. Descriptive statistics of each SCS phenotype………………………………….. 100 Table 4.2. Differentiating markers and their allele frequencies……………………………103 Table 4.3. SCS genome-wide association models………………………………………… 104 Supplementary Table 4.1. Differentiated QTL and candidate genes……………………… 130 Supplementary Table 4.2. Significantly associated QTL and candidate genes…………… 132 xi CHAPTER 1: INTRODUCTION 1.A: Origins The term “mastitis” originates from the Greek mastos, meaning “breast”, and -itis, a suffix meaning “inflammation”. Inflammation etymology can be traced to the Latin inflammationem,