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Using Systems Genetics to Unravel the Genetics of Bone-Related Traits

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Using Systems Genetics to Unravel the Genetics of Bone-Related Traits Using Systems Genetics to Unravel the Genetics of Bone-related Traits Basel Maher Al-Barghouthi Ramallah, State of Palestine Bachelor of Science, Biology, The University of Texas at Austin, 2013 Master of Science, Bioinformatics, University of Michigan, 2015 Master of Science, Biological and Physical Sciences, University of Virginia, 2017 A Dissertation presented to the Graduate Faculty of the University of Virginia in Candidacy for the Degree of Doctor of Philosophy Department of Biochemistry and Molecular Genetics University of Virginia August 2021 Dr. Charles Farber Dr. Stefan Bekiranov Dr. Mete Civelek Dr. Jason Papin Dr. Stephen Rich Dr. Jeffrey Saucerman II Abstract Osteoporosis is a highly prevalent disease, characterized by reduced bone strength and an increased susceptibility to bone fractures, with over 10 million affected individuals in the U.S. alone. As populations age more successfully, the prevalence of osteoporosis is expected to rise; therefore, understanding the genetic basis of bone strength and related traits is of the utmost importance to the development of therapeutic interventions aimed at reducing the societal burden of osteoporosis. To this end, over the last decade, geneticists have performed genome-wide association studies (GWASs) of bone mineral density (BMD) in order to gain insight into the genetics of osteoporosis. These studies have been very successful, identifying over 1,100 independent associations to date. However, efforts to understand the genetics of bone and to discover actionable therapeutic targets have been limited due to two main shortcomings of BMD GWASs. First, GWASs in the bone field have almost exclusively focused on BMD as a trait. While BMD is a clinically relevant predictor of osteoporosis, it only explains part of the variance in bone strength. Second, progress has been limited due to the inherent difficulties in identifying the causal genes that underlie GWAS associations. Here, we address these limitations by utilizing systems genetics approaches. Using a novel mouse population, the Diversity Outbred, we perform a GWAS of 55 bone traits and identify putatively causal genes underlying some of the GWAS associations. Furthermore, we utilize systems genetics approaches in order to inform existing BMD GWASs. The work presented in this dissertation provides a resource that will increase our understanding of the genetics of bone, and presents methodological techniques that are applicable across myriad complex traits. III Dedication This dissertation is dedicated to my mother Reem, my father Maher, my brother Faris, and my sister Liane. Without your love and support, I wouldn’t have been able to achieve this. ~Promise fulfilled~ IV Table of Contents Abstract II Dedication III List of Figures VII Chapter 1: Introduction ............................................................................................................ 1 1.1 The skeleton as a dynamic system ...................................................................... 2 1.2 Current state of osteoporosis genetics ............................................................... 4 1.3 Using systems genetics to inform bone GWAS ............................................... 6 1.3.1 Epigenetics-based approaches .......................................................................... 7 1.3.2 Transcriptomics-based approaches ................................................................. 9 1.3.2.1 eQTL colocalization .......................................................................... 9 1.3.2.2 Transcriptome-wide association studies ...................................... 12 1.3.3 Network-based approaches ............................................................................ 15 1.3.3.1 Biological networks ......................................................................... 16 1.3.3.2 Co-expression networks ................................................................. 17 1.3.3.3 Bayesian networks ........................................................................... 19 1.4 The mouse as a model for bone-related traits ................................................. 22 1.5 Summary ............................................................................................................... 25 Chapter 2: Systems Genetics Analyses in Diversity Outbred Mice Inform BMD GWAS and Identify Determinants of Bone Strength 28 2.1 Abstract ................................................................................................................. 29 2.2 Introduction ......................................................................................................... 30 2.3 Results ................................................................................................................... 32 2.3.1 Development of a resource for the systems genetics of bone strength ................................................................................................ 32 2.3.2 Identification of bone-associated nodes ......................................... 35 V 2.3.3 Using BANs to inform human BMD GWAS ................................ 38 2.3.4 Identification of QTLs for strength-related traits in the DO ...... 43 2.3.5 Overlap with human BMD GWAS ................................................. 43 2.3.6 Identification of potentially causal genes ........................................ 45 2.3.7 Characterization of a QTL on Chromosome 1 influencing bone morphology ................................................................................................... 47 2.3.8 Qsox1 is responsible for the effect of locus 1 on cortical bone morphology ................................................................................................... 49 2.4 Discussion ............................................................................................................ 54 2.5 Methods ................................................................................................................ 58 2.6 Data availability.................................................................................................... 78 2.7 Code availability ................................................................................................... 79 2.8 Acknowledgements ............................................................................................. 79 Chapter 3: Transcriptome-wide Association Study and eQTL Colocalization Identify Potentially Causal Genes Responsible for Bone Mineral Density GWAS Associations 81 3.1 Abstract ................................................................................................................. 82 3.2 Introduction ......................................................................................................... 83 3.3 Results ................................................................................................................... 85 3.3.1 TWAS and eQTL colocalization identify potentially causal BMD GWAS genes ..................................................................................... 85 3.3.2 Characterization of genes identified by TWAS/eQTL colocalization ................................................................................................ 86 3.3.3 PPP6R3 is a candidate causal gene for a GWAS association on Chr. 11 ..................................................................................................... 90 3.3.4 PPP6R3 is a regulator of femoral geometry, BMD, and vertebral microarchitecture ................................................................. 92 3.4 Discussion ............................................................................................................ 97 3.5 Methods .............................................................................................................. 101 3.6 Data availability.................................................................................................. 109 VI 3.7 Code availability ................................................................................................. 109 3.8 Acknowledgements ........................................................................................... 109 Chapter 4: Concluding Remarks and Future Directions 111 4.1 Summary and conclusions................................................................................ 112 4.1.1 Association mapping of bone-related traits .................................. 112 4.1.2 Systems genetics analyses in mouse inform human BMD GWAS ................................................................................. 113 4.1.3 A combined TWAS/eQTL colocalization approach informs BMD GWAS .............................................................................................. 115 4.2 Limitations .......................................................................................................... 116 4.2.1 Bone-specific –omics data ............................................................... 116 4.2.2 Single-cell –omics data ..................................................................... 116 4.2.3 Beyond steady-state transcriptomics data ..................................... 118 4.2.4 Non-European ancestries ................................................................ 118 4.2.5 Investigating the genetics of other aspects of bone .................... 119 4.3 Future directions ............................................................................................... 119 Appendix A: Supplementary Data 122 Appendix B: Supplemental
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