THE UNIVERSITY OF CHICAGO INTEGRATIVE GENETIC ANALYSIS OF BEHAVIORAL AND METABOLIC TRAITS IN AN ADVANCED INTERCROSS LINE OF MICE A DISSERTATION SUBMITTED TO THE FACULTY OF THE DIVISION OF THE BIOLOGICAL SCIENCES AND THE PRITZKER SCHOOL OF MEDICINE IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF HUMAN GENETICS BY NATALIA M. GONZALES CHICAGO, ILLINOIS DECEMBER 2017 Copyright c 2017 by Natalia M. Gonzales All Rights Reserved Freely available under a CC-BY 4.0 International license "Man had always assumed that he was more intelligent than dolphins because he had achieved so much - the wheel, New York, wars and so on... In fact there was only one species on the planet more intelligent than dolphins, and they spent a lot of their time in behavioural research laboratories running round inside wheels and conducting frighteningly elegant and subtle experiments on man. The fact that once again man completely misinterpreted this relationship was entirely according to these creatures' plans." Douglas Adams, The Hitchhiker's Guide to the Galaxy, 1979. Table of Contents LIST OF FIGURES . vi LIST OF TABLES . vii ACKNOWLEDGMENTS . viii ABSTRACT . xi 1 INTRODUCTION . 1 1.1 Genetic approaches for studying phenotypic variation . 1 1.2 Major insights from human GWAS and implications for psychiatric traits . 4 1.3 Model organisms can be used to circumvent some limitations of human GWAS 6 1.4 Genetic analysis in advanced intercross lines . 7 1.5 GWAS in structured populations . 9 1.6 Overview . 10 2 MOUSE GWAS OF INTERMEDIATE PHENOTYPES FOR HUMAN PSYCHI- ATRIC AND METABOLIC DISEASE . 12 2.1 Introduction . 12 2.1.1 What is an intermediate phenotype? . 12 2.1.2 Intermediate phenotypes for human substance use disorders . 14 2.1.3 Modeling metabolic syndrome in the LG × SM AIL . 20 2.2 Methods . 21 2.2.1 Animals . 21 2.2.2 CPP and locomotor activity . 22 2.2.3 PPI and startle . 23 2.2.4 Fasting blood glucose levels . 23 2.2.5 Body weight . 24 2.2.6 Muscle weight and bone length . 24 2.2.7 Genotyping by sequencing . 24 2.2.8 DNA alignment . 25 2.2.9 Variant calling and imputation . 25 2.2.10 QTL mapping model . 26 2.2.11 Heritability estimates . 26 2.2.12 Genome-wide significance . 26 2.2.13 QTL intervals . 27 2.3 Results . 27 2.3.1 Genetic architecture in the LG × SM AIL . 27 2.3.2 Validation of the LOCO-LMM . 30 2.3.3 Identifying potentially spurious QTLs . 33 2.3.4 QTLs for behavior . 35 2.3.5 QTLs for metabolism and physiology . 40 iv 2.3.6 Discussion . 45 2.4 Contributions . 47 2.5 Supplementary Materials . 48 2.5.1 Supplementary Methods . 48 2.5.2 Supplementary Figures . 60 2.5.3 Supplementary Tables . 60 3 INTEGRATIVE ANALYSIS OF GENOTYPES, PHENOTYPES AND GENE EX- PRESSION DATA . 68 3.1 Introduction . 68 3.1.1 Rationale for an integrative analysis of QTLs and eQTLs . 69 3.1.2 Relevance of HIP, PFC and STR to behavior and disease . 70 3.1.3 Global patterns of gene expression appear highly conserved in humans and mice . 71 3.2 Methods . 73 3.2.1 RNA sequencing . 73 3.2.2 cis-eQTLs . 75 3.2.3 trans-eQTLs . 76 3.2.4 Integration of QTLs and eQTLs . 76 3.2.5 URLs . 77 3.3 Results . 77 3.3.1 cis and trans-eQTLs . 77 3.3.2 Integration of eQTLs and behavioral QTLs . 82 3.3.3 Integration of eQTLs and metabolic QTLs . 93 3.3.4 Discussion . 102 3.4 Contributions . 104 3.5 Supplementary Materials . 104 3.5.1 Supplementary Methods . 104 3.5.2 Supplementary Figures . 105 3.5.3 Supplementary Tables . 105 4 CONCLUSIONS . 110 4.1 GBS as a genotyping strategy in large samples of outbred mice . 111 4.2 An integrative analysis of QTLs and eQTLs identified several candidate genes 111 4.3 Replication of an association between Csmd1 and locomotor activity identified in G34 . 113 4.4 Genetic architecture of complex traits in model organisms and humans . 114 4.5 Model organisms and human disease . 116 REFERENCES . 117 v List of Figures 2.1 AIL phenotypes. 22 2.2 Genetic architecture in the LG × SM AIL. 29 2.3 MAF by QTL effect size in the LG × SM AIL. 30 2.4 Heritability of metabolic and physiological traits in the LG × SM AIL. 31 2.5 Heritability of behavioral traits in the LG × SM AIL. 32 2.6 Coat color GWAS validates the use of a LOCO-LMM. 34 2.7 Identification of outliers for startle and PPI. 60 2.8 SNP density. 61 2.9 Heat map of correlations among body weight, muscle, bone and glucose traits. 62 2.10 Heat map of correlations among CPP traits. 63 2.11 Heat map of correlations among methamphetamine activity traits. 64 2.12 Heat map of correlations among PPI and startle traits. 65 2.13 Heat map of correlations among saline activity traits. 66 2.14 Manhattan plots. 67 3.1 cis-eQTLs and trans-eQTL hotspots in HIP, PFC and STR. 79 3.2 QTL for locomotor activity (D5 saline, 0-30 min) on chromosome 4. 83 3.3 Csmd1 and activity in G34 and G50-56 of the LG × SM AIL. 84 3.4 Csmd1 expression in HIP. 85 3.5 Locomotor activity in Csmd1 knockout mice. 86 3.6 QTL for locomotor activity (D1 side changes, 0-30 min) on chromosome 17. 88 3.7 Expression of Crim1, Qpct, and Vit in HIP. 89 3.8 QTL for startle response (block 2) on chromosome 7. 90 3.9 QTL for mean startle response on chromosome 17. 92 3.10 QTL for mean startle response on chromosome 17. 94 3.11 QTL for D4 body weight on chromosome 2. 96 3.12 A second QTL for D8 body weight on chromosome 4. 98 3.13 QTL for body weight on D8 of the CPP test on chromosome 7. 99 3.14 QTL for EDL muscle weight on chromosome 4. 101 3.15 Summary of eQTLs by brain region. 106 3.16 cis-eQTLs and trans-eQTLs in HIP. 107 3.17 cis-eQTLs and trans-eQTLs in PFC. 108 3.18 cis-eQTLs and trans-eQTLs in STR. 109 vi List of Tables 1 2.1 GBS genotype concordance. 60 2.2 Trait summary statistics, heritabilities, and covariates. 60 2.3 Summary of QTLs. 65 3.1 Master trans regulators and their target genes. 106 1. Note: Due to the large size of some tables, the tables have been provided in a supplementary file accompanying the dissertation. In such cases, the page number provided above directs the reader to a table's caption. vii ACKNOWLEDGMENTS I've incurred a lot of debt in graduate school. It's not the financial kind, it's the good kind - the kind of debt that's impossible to repay. I doubt I'd have been able to complete this journey without the lessons I learned from Elaine and Roger Gonzales, my parents. Both of them grew up in rural New Mexico and come from large families. They managed to make their way through college (fueled primarily by potted meat and saltines, as my mom tells it), and my dad also served in the army and earned a master's degree. They've always put a high value on education; I remember them emphasizing the importance of having a college degree when I was quite young. To some extent, I think this is because they probably struggled a lot along the way and didn't want me to take knowledge for granted. I can't thank them enough for the incredible foresight, selflessness, and hard work that provided me with the.