Escherichia coli is an incredibly diverse group of bacteria that consist of both commensal and pathogenic strains that cause disease in a wide variety of tissues in many different animals. The current dogma, based on years of extensive molecular and genetic studies, is that individual strains have adapted to specific environments through acquisition of specific genes or come from lineages that are particularly suited to a unique tissue or host. However, mastitis-associated E. coli (MAEC) have thus far resisted such descriptions. The fitness and virulence factors of MAEC are poorly understood and molecular tools are rarely applied. This dissertation reports new approaches to assess virulence of MAEC strains, enabling comparative genomic studies across multiple strains as well as genome-wide analysis of specific successful MAEC isolates. I outline the identification of the first virulence factor of MAEC, a ferric dicitrate receptor that is essential for colonization of a lactating mammary gland in a murine model. Genes previously studied in the contexts of other extraintestinal E. coli infections were also implicated in mastitis. These include a type III capsule found in the MAEC strain M12, which is crucial for dissemination from the mammary gland to the spleen. A mutant unable to produce capsule had diminished lethality in Galleria mellonella and decreased kidney colonization in a mouse urinary tract infection. I also report a link between zinc uptake, bile salts, and capsule production. I have utilized a transposon mutant library paired with deep sequencing of transposon junctions to elucidate the fitness factors needed to grow in milk and colonization of both murine and insect models. This analysis implicates a broad set of genes and metabolic pathways pertinent to these conditions. In addition to Tn-seq, I sequenced 94 MAEC genomes and identified genes associated with disease severity, growth in milk, and colonization of mammary glands in cow and mouse models. Employing bioinformatic tools to interrogate the pan-genome, I identified genes that are involved in biofilm formation and adhesion that were specifically associated with either mild or severe disease. In summary, I have employed several powerful genetic, genomic, computational, and molecular approaches to the characterization of mastitis associated E. coli. This work provides the groundwork for future experiments to better understand the host-pathogen interface and a model for mastitis-associated E. coli.

In der Epidemiologie spielen Körpermaße eine wichtige Rolle als Indikatoren für häufig vorkommende Zivilisationskrankheiten wie zum Beispiel Herz-Kreislauf-Erkrankungen oder Diabetes. Die Vermessung von Hand ist dabei als Goldstandard etabliert. Betrachtet werden häufig Körpergröße, Körpergewicht, Oberarmlänge, Oberarmumfang, Taillenumfang, Hüftumfang, Oberschenkellänge, Oberschenkelumfang und Wadenumfang. Für viele dieser Maße beziehungsweise davon abgeleiteter Größen existieren bereits genomweite Assoziationsstudien, wie zum Beispiel innerhalb des GIANT-Konsortiums zu Körpergröße, Body Mass Index und Taille, Hüfte und Taille-Hüfte-Verhältnis. Ziel dieser Arbeit war es, die 3D-Anthropometrie über den Körper-Scanner als neue Messmethode zu etablieren. Dazu stand das ANTHROSCAN VITUS XXL SYSTEM, bestehend aus dem Körper-Scanner VITUS XXL und der Software ANTHROSCAN BASIS von dem Unternehmen Human Solutions zur Verfügung. Die Körper-Scanner-Software bestimmt gemäß DIN EN ISO 20685 standardmäßig über 150 Maße mit der Möglichkeit der Hinzunahme weiterer Körpermaße. Das Hauptaugenmerk lag auf der Untersuchung der Messgenauigkeit der neuen Körper-Scanner-Methode. Dies beinhaltete zunächst die Analyse der Übereinstimmung von Mehrfachmessungen durch den Körper-Scanner. Dazu wurden sowohl Intra-Beobachter-Reliabilitäten als auch Inter-Beobachter-Reliabilitäten bestimmt. Zur Quantifizierung der Konkordanz wurde der Overall Concordance Correlation Coefficient verwendet. Diese Ergebnisse wurden mit denen aus der klassischen Anthropometrie verglichen. Für beide Messmethoden konnten dabei – bis auf wenige Ausnahmen für die 3D-Anthropometrie – sehr gute Ergebnisse ermittelt werden. Im Anschluss daran erfolgt die Untersuchung der Validität, das heißt der Vergleich der manuellen mit der automatisierten Messung. Die Konkordanz wurde ebenfalls über den Overall Concordance Correlation Coefficient bestimmt. Die resultierenden Übereinstimmungen liegen alle im guten bis sehr guten Bereich. Darauf aufbauend wurde untersucht, wie gut sich aus den bestehenden Körper-Scanner-Maßen Derivate bilden lassen. Dies wurde am Beispiel der Körperoberfläche als zweidimensionales Objekt analysiert. Dabei erfolgten zunächst auch wieder Reliabilitätsuntersuchungen bezüglich Intra-Beobachter-Reliabilität und Inter-Beobachter-Reliabilität. Die berechneten Werte gemäß Overall Concordance Correlation Coefficient lagen beide im sehr guten Bereich. Zur Bestimmung der Körperoberfläche werden im Alltag empirische Formeln zur Schätzung der Körperoberfläche über Körpergröße und Körpergewicht herangezogen. Dementsprechend wurde, unter der Annahme der validen Bestimmung der Körperoberfläche über den Körper-Scanner, diese tatsächliche Oberfläche mit der geschätzten Oberfläche aus den empirischen Formeln verglichen. Die Ergebnisse waren überraschend gut. Insgesamt hervorzuheben sind die Formeln nach Fujimoto & Watanabe, Shuter & Aslani und Sendroy & Cecchini. Dennoch war es über Reparametrisierung mit den vorliegenden Daten möglich, eine Verbesserung der Oberflächenschätzung durch empirische Formeln mit Körpergröße und Körpergewicht zu erreichen. Entsprechende Formeln wurden entsprechend zur weiteren Anwendung vorgeschlagen. Da die Bestimmung von Körpermaßen durch die händische Vermessung bisher nur auf einige wenige Maße beschränkt war, existieren folglich auch nur für diese Phänotypen Resultate aus genetischen Assoziationsanalysen. Dies betrifft vor allem die Körpergröße, den Body Mass Index und das Taille-Hüfte-Verhältnis. Durch Ermittlung von mehr als dem Zehnfachen der bisher üblichen Maße, können nun auch genomweite Assoziationsstudien bezüglich dieser Körpermaße durchgeführt werden. Dies erfolgte hier für die über 150 Körpermaße der knapp 7.500 vermessenen und genotypisierten LIFE-Adult-Probanden. Zunächst wurden die Daten hinsichtlich ihrer Korrelationsstruktur analysiert. Jeder Proband lässt sich über die etwa 150 Maße charakterisieren, welche jedoch Korrelationen untereinander aufweisen. Dementsprechend war es erforderlich, diese Korrelationsstruktur zu untersuchen und gegebenenfalls eine Dimensionsreduktion beziehungsweise eine Einteilung in Gruppen von Körpermaßen vorzunehmen. Es zeigte sich, dass sich die knapp 150 Körpermaße in weniger als zehn Gruppen zusammenfassen lassen. Auf der Suche nach einem Referenzmaß für jede Gruppe fiel auf, dass bisher im Rahmen der klassischen Anthropometrie nicht betrachtete Maße eine beachtenswerte Rolle spielen. Dazu zählen Abstand Taillenband zur Taille, Höhe Taille, Schulterbreite aber auch Armumfang, Armdurchmesser, Beinumfang und beispielsweise Schrittlänge. Im Rahmen der genomweiten Assoziationsanalyse wurden in dieser Arbeit einige ausgewählte Resultate derjenigen Körpermaße der 3D-Anthropometrie präsentiert, für welche es ein passendes Äquivalent in der klassischen Anthropometrie gibt. Dabei konnten genomweit signifikante Assoziationen für Körpergröße, Oberarmlänge und Oberarmumfang festgestellt werden.:1. Einführung 1.1 Bedeutung der Anthropometrie 1.2 Klassische Messung und 3D-Körper-Scanner 1.3 Fragestellung der Arbeit 2. Validität, Reliabilität und Akzeptanz der automatisierten und klassischen Messung bei Erwachsenen und Kindern 3. Möglichkeit der Ableitung weiterer Größen aus dem 3D-Körper-Scan am Beispiel der Körperoberfläche 4. Genomweite Assoziationsanalyse bezüglich 3D-Körper-Scanner-Maßen 4.1 Warum noch eine GWAS zu Körpermaßen? 4.2 Welche Daten stehen zur Verfügung? 4.3 Vorbereitungen der GWAS 4.3.1 Fallzahl, Datenvollständigkeit und Ausreißer 4.3.2 Korrelation zwischen den Merkmalen 4.3.3 Hauptkomponentenanalyse 4.3.4 Partielle Kleinste-Quadrate-Methode (Diskriminanzanalyse) 4.3.5 Cluster-Verfahren 1: k-Means-Clustering 4.3.6 Clusterverfahren 2: Hierarchische Cluster-Analyse 4.3.7 Vergleich 4.4 Was genau passiert bei einer GWAS? 4.4.1 Qualitätskontrolle 4.4.2 Imputation 4.4.3 Statistische Tests 4.5 Ergebnisse der GWAS 5. Zusammenfassung Literaturverzeichnis Abbildungsverzeichnis Darstellung des eigenen Beitrags Selbstständigkeitserklärung Lebenslauf Publikationen Danksagung

Understanding the regenerative capacity and the role of human AT2s in the distal lung is imperative for defining alveolar response to injury and disease. Additionally, due to human AT2 expression of COPD genome wide association study (GWAS) genes, they are an especially relevant cell type to study the disease. Here we apply CRISPR-interference (CRISPRi) to reduce the expression of COPD GWAS gene, ADGRG6, to interrogate its function in induced pluripotent stem cell-derived type 2 alveolar epithelial cells (iAT2s). We find that decreased expression of ADGRG6 in iAT2s caused disruption to iAT2 cell polarity, organization of the actin cytoskeleton, and establishment of tight junctions. In addition, ADGRG6 knockdown (kd) causes a hyperproliferative phenotype. Finally, we find that ADGRG6-kd may contribute to dysregulation of tight junction formation in the presence of cigarette smoke.

Genome-wide association studies(GWAS) are used to find associations betweengenetic markers and diseases. One part of GWAS is to study interactions be-tween markers which can play an important role in the risk for the disease. Thesearch for interactions can be computationally intensive. The aim of this thesiswas to improve the performance of software used for gene-environment interac-tion by using parallel programming techniques on graphical processors. A studyof the new programs performance, speedup and efficiency was made using mul-tiple simulated datasets. The program shows significantly better performancecompared with the older program.

Fusarium head blight (FHB) is a devastating wheat (Triticum aestivum L.) disease worldwide. Presently, there is insufficient FHB resistance in the Canadian wheat germplasm. Genome-wide association study (GWAS) and genomic selection (GS) can be utilized to identify sources of resistance that could benefit wheat breeding. To define the genetic architecture of FHB resistance, association panels from a spring and a winter collection were evaluated using the Wheat Illumina Infinium 90K array. A total of 206 accessions from the spring panel and 73 from the winter panel were evaluated in field trials for 3-4 years at two locations, namely Morden (Manitoba) and Ottawa (Ontario). These accessions were phenotyped for FHB incidence (INC), severity (SEV), visual rating index (VRI), and deoxynivalenol (DON) content. Significant (p < 0.05) differences among genotypes for all traits were found. Genetic characterization using the wheat 90K array identified a set of 20,501 single nucleotide polymorphisms (SNPs). The probe sequences (~100 bp) of these SNPs were mapped to the Chinese Spring reference genome v2.0 to identify 13,760 SNPs in the spring panel, and 10,421 SNPs in the winter panel covering all 21 wheat chromosomes. GWAS was performed to identify novel FHB resistance loci for INC, SEV, VRI and DON content for the spring and the combined panels separately using these 13,760 SNPs and for the winter panel using 10,421 SNPs. A total of 107, 157, 174 unique quantitative trait loci (QTNs) were identified for the four traits using two single-locus and seven multi-locus GWAS models for the spring, winter, and combined panels, respectively. These QTNs represent a valuable genetic resource for the improvement of FHB resistance in commercially grown wheat cultivars. In addition, these GWAS-defined QTNs were further used for GS to determine the breeding value (BV) of individuals as outlined below. In order to understand the role of the model and that of the marker type and density in trait prediction modelling, a GS study was conducted. GS is considered as an important tool for increasing genetic gain for economically important traits such as FHB resistance. GS uses genome-wide molecular markers to develop statistical models that predict genomic estimated breeding values (GEBVs) of an individual. Our results support genomic prediction (GP) as an alternative to phenotypic selection to predict the BVs of individuals for this trait. GS accounts for minor effect QTNs, which is beneficial when breeding for quantitative traits. Moderate to high GP accuracies can be achieved for FHB resistance-related traits when implemented in a breeding program. The correlation between the estimate of the missing phenotypic value and the observed phenotype is known as predictive ability (r). Overall, the predictive ability increased significantly using a QTN-based GP approach for FHB traits in wheat and its wild relatives. DON content had the highest predictive ability among all FHB traits, and that was in the winter panel, highlighting the importance of objectively measured traits in breeding for disease resistant genotypes. Interestingly, the winter panel contained several wild relative species that may harbor genes of interest to prevent the accumulation of mycotoxins in the grain. This study showed the usability of genomic prediction by improving the predictive ability of the FHB traits, which can be applied in early generation selection to accelerate the improvement of FHB resistance in wheat. The results show that GS can be successfully implemented in wheat breeding programs over multiple breeding cycles and can be effective for economically important traits. It is anticipated that GS will play a substantial role in the future of wheat breeding.

Genome-wide studies are prone to false positives due to inherently low priors and statistical power. One approach to ameliorate this problem is to seek validation of reported candidate genes across independent studies: genes with repeatedly discovered effects are less likely to be false positives. Inversely, genes reported only as many times as expected by chance alone, while possibly representing novel discoveries, are also more likely to be false positives. We show that, across over 30 genome-wide studies that reported Drosophila and Daphnia genes with possible roles in thermal adaptation, the combined lists of candidate genes and orthologous groups are rapidly approaching the total number of genes and orthologous groups in the respective genomes. This is consistent with the expectation of high frequency of false positives. The majority of these spurious candidates have been identified by one or a few studies, as expected by chance alone. In contrast, a noticeable minority of genes have been identified by numerous studies with the probabilities of such discoveries occurring by chance alone being exceedingly small. For this subset of genes, different studies are in agreement with each other despite differences in the ecological settings, genomic tools and methodology, and reporting thresholds. We provide a reference set of presumed true positives among Drosophila candidate genes and orthologous groups involved in response to changes in temperature, suitable for cross-validation purposes. Despite this approach being prone to false negatives, this list of presumed true positives includes several hundred genes, consistent with the “omnigenic” concept of genetic architecture of complex traits.

Genome-wide association studies (GWASs) have reported numerous associations between risk variants and Alzheimer’s disease (AD). However, these associations do not necessarily indicate a causal relationship. If the risk variants can be demonstrated to be biologically functional, the possibility of a causal relationship would be increased. In this article, we reviewed all of the published GWASs to extract the genome-wide significant (p < 5×10−8) and replicated associations between risk variants and AD or AD-biomarkers. The regulatory effects of these risk variants on the expression of a novel class of non-coding RNAs (piRNAs) and protein-coding RNAs (mRNAs), the alteration of proteins caused by these variants, the associations between AD and these variants in our own sample, the expression of piRNAs, mRNAs and proteins in human brains targeted by these variants, the expression correlations between the risk genes and APOE, the pathways and networks that the risk genes belonged to, and the possible long non-coding RNAs (LncRNAs) that might regulate the risk genes were analyzed, to investigate the potential biological functions of the risk variants and explore the potential mechanisms underlying the SNP-AD associations. We found replicated and significant associations for AD or AD-biomarkers, surprisingly, only at 17 SNPs located in 11 genes/snRNAs/LncRNAs in eight genomic regions. Most of these 17 SNPs enriched some AD-related pathways or networks, and were potentially functional in regulating piRNAs and mRNAs; some SNPs were associated with AD in our sample, and some SNPs altered protein structures. Most of the protein-coding genes regulated by the risk SNPs were expressed in human brain and correlated with APOE expression. We conclude that these variants were most robust risk markers for AD, and their contributions to AD risk was likely to be causal. As expected, APOE and the lipoprotein metabolism pathway possess the highest weight among these contributions.

Posttraumatic stress disorder (PTSD) is a psychiatric condition that presents with 3 main symptoms're-experiencing, avoidance/numbing, and hyper arousal'after an individual experiences a traumatic event. Recent evidence suggests a potential genetic basis for PTSD and a sub symptom of hyper arousal, sleep, as a potential pathway for PTSD development, but no study has identified candidate genes associated with specific symptoms such as sleep difficulty. Based on a conceptual framework in which specific genes are associated with the onset of PTSD, this study used a genome-wide association study (GWAS) method with a case control study design to compare the genomes of individuals with and without PTSD. A secondary GWAS dataset from a study on alcohol dependence in European and African Americans was obtained from the National Center for Biotechnology Information. PTSD cases and controls were analyzed using PLINK software. Signals from 2 single nucleotide polymorphisms (SNPs), which have not been previously associated with PTSD, exceeded the established genome-wide threshold: SNP rs13160949 on chromosome 5 (p = 7.33x10-9, OR: 1.565) and SNP rs2283877 on chromosome 22 (p = 2.55x10-8, OR: 1.748). Neither SNP, though, maintained genomewide significance following corrected tests for multiple testing, population stratification, and false discovery, so the planned analysis for possible associations with PTSD by symptom category then by the sub symptom of sleep could not be completed. The results of this study suggest that PTSD may be the result of polygenic SNPs with weak effects, which supports a recent study indicating the disease may be highly polygenic. Positive social change implications include bringing attention to the clinical and research community that PTSD may involve complex polygenic factors in need of further study.

Bovine mastitis, or inflammation of the mammary gland, has substantial economic and animal welfare implications. A genetic basis for mastitis resistance traits is recognized and can be used to guide selective breeding programs. The discovery of regions of the genome associated with mastitis resistance, and knowledge of the underlying molecular mechanisms responsible, can facilitate development of efficient mastitis control and therapeutic strategies. The objectives of this dissertation research were to identify sites of genetic variation associated with mastitis resistance, and to define the contributions of the milk-secreting epithelial cells to mammary gland immune responses and mastitis resistance. Twenty seven regions of the bovine genome potentially involved in mastitis resistance were identified in Holstein dairy cattle. Additionally, this research demonstrates a role of bovine mammary epithelial cells in mastitis resistance, and provides guidance for the use of an in vitro model for mastitis studies. Primary bovine mammary epithelial cells from mastitis-resistant cows have differential expression of 42 inflammatory genes compared with cells from mastitis-susceptible cows, highlighting the importance of epithelial cells in mastitis resistance. Bovine mammary epithelial cells display both similarities and differences in pro-inflammatory gene expression compared to fibroblasts, and their expression of inflammatory genes is influenced by administration of the enzyme phospholipase A2. The growth potential of milk-derived bovine mammary epithelial cells in vitro can be extended, facilitating their use in mastitis studies, by transfection with a viral protein. Collectively, this research contributes to current knowledge on bovine mastitis resistance and in vitro models.

Our understanding of genetic predisposition to inflammatory and autoimmune diseases has been enhanced by large scale quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, the resolution and interpretation of QTL linkage mapping or GWAS findings are limited. In this work, we complement genetic predictions for several human diseases including multiple sclerosis (MS) and systemic capillary leakage syndrome (SCLS) with genetic and functional data in model organisms to associate genes with phenotypes and diseases. Focusing on MS, an autoimmune inflammatory disease of the central nervous system (CNS), we experimentally tested the effect of three of the GWAS candidate genes (SLAMF1, SLAMF2 and SLAMF7) in the experimental autoimmune encephalomyelitis (EAE) mouse model and found a male-specific locus distal to these loci regulating CNS autoimmune disease. Functional data in mouse suggests this male-specific locus modulates the frequency of immune cells including CD11b+, TCRαβ+CD4+Foxp3+, and TCRαβ+CD8+IL-17+ cells during EAE disease. Orchiectomy experiments demonstrate that this male specific phenotype is dependent on testis but not testosterone (T) or 5α-dihydrotestosterone (DHT). Using a bioinformatic approach, we identified SLAMF8 and SLAMF9 along with other differentially expressed genes in linkage with MS-GWAS predictions whose expression is testis-dependent, but not directly regulated by T or DHT, as potential positional candidates regulating CNS autoimmune disease. Further refinement of this locus is required to identify the causal gene(s) that may be targeted for prevention and/or treatment of MS in men. Using SCLS, an extremely rare disorder of unknown etiology characterized by recurrent episodes of vascular leakage, we identified and modeled this disease in an inbred mouse strain, SJL, using susceptibility to histamine- and infection-triggered vascular leak as the major phenotypic readout. This trait “Histamine hypersensitivity” (Histh/Histh) was mapped to a region on Chr 6. Remarkably, Histh is syntenic to the genomic locus most strongly associated with SCLS in humans (3p25.3). Subsequent studies found that the Histh locus is not unique to SJL but additional mouse strains also exhibit Histh phenotype. Considering GWAS studies in SCLS are limited by the small number of patients, we utilized interval-specific SNP-based association testing among Histh phenotyped mouse strains to predict Histh candidates. Furthermore, to dissect the complexity of Histh QTL, we developed network-based functional prediction methods to rank genes in this locus by predicting functional association with multiple Histh-related processes. The top-ranked genes include Cxcl12, Ret, Cacna1c, and Cntn3, all of which have strong functional associations and are proximal to SNPs segregating with Histh. Lastly, we utilized the power of integrating genetic and functional approaches to understand susceptibility to Bordetella pertussis and pertussis toxin (PTX) induced histamine sensitization (Bphs/Bphs), a sub-phenotype with an established role in autoimmunity. Congenic mapping in mice had earlier linked Bphs to histamine H1 receptor gene (Hrh1/H1R) and demonstrated that H1R differs at three amino acid residues in Bphs-susceptible and -resistant mice. Our subsequent studies identified eight inbred mouse strains that were susceptible to Bphs despite carrying a resistant H1R allele. Genetic analyses mapped the locus complementing Bphs to mouse Chr 6, in linkage disequilibrium with Hrh1; we have designated this Bphs-enhancer (Bphse). Similar to the approaches used for Histh, we utilized interval-specific SNP based association testing and network-based functional enrichment to predict nine candidate loci for Bphse including Atp2b2, Atg7, Pparg, Syn2, Ift122, Raf1, Mkrn2, Timp4 and Gt(ROSA)26Sor. Overall, these studies demonstrate the power of integrating genetic and functional methods in humans and animal models to predict highly plausible loci underlying QTL/GWAS data.