The immune response to a given cancer can profoundly influence a tumour's trajectory and response to treatment, but the ability to analyse this component of the microenvironment is still limited. To this end, a number of immune marker gene signatures have been reported which were designed to enable the profiling of the immune system from transcriptomics data from tissue and blood samples. Our initial analyses of these resources suggested that these existing signatures had a number of serious deficiencies. In this study, a co-expression based approach led to the development of a new set of immune cell marker gene signatures (ImSig). ImSig supports the quantitative and qualitative assessment of eight immune cell types in expression data generated from either blood or tissue. The utility of ImSig was validated across a wide variety of clinical datasets and compared to published signatures. Evidence is provided for the superiority of ImSig and the utility of network analysis for data deconvolution, demonstrating the ability to monitor changes in immune cell abundance and activation state. ImSig was also used to examine immune infiltration in the context of cancer classification and treatment. Patient-matched ER+ breast cancer samples before and after treatment with letrozole were analysed. Significant elevation of infiltration of macrophages and T cells on treatment was observed in responders but not in non-responders, potentially revealing a biomarker for response. ImSig was also used to study the immune infiltrate in 12 cancer types. By computing the relative abundance of immune cells in these samples, their relationship to survival was investigated. It was interesting to observe that half of the cancers showed trends towards poor prognosis with increased infiltration of immune cells. ImSig alongside the network-based framework can also be used for a more explorative analysis such as to identify biomarkers and activation or differentiation states of immune cells. Melanoma is a highly immunogenic cancer and has shown tremendous success with immune checkpoint inhibitors in a subset of patients. In chapter-6, the molecular subgrouping of melanoma was explored using a network-based approach. Despite the plethora of evidence suggesting various aspects of the immune system to contribute towards the response to immunotherapy in melanoma, there has been little to no effort to consider this heterogeneity while developing molecular subgroups. The use of ImSig was therefore explored for the stratification of melanoma patients into immuno-subgroups. The subgrouping methodology divided the tumours into four groups with different immune profiles. Interestingly, these groupings showed prognostic significance, reiterating the need to consider the heterogeneity of immune cells in future studies. On identifying the most dominant phenotypes that contribute towards prognosis of these patients and in comparison to the published subgroupings of melanoma, we argue that the subgroup of samples enriched in keratin genes are not clinically meaningful. ImSig and the associated analysis framework described in this work, support the retrospective analysis of tissue derived transcriptomics data enabling better characterisation of immune infiltrate associated with disease, and in so doing, provide a resource useful for prognosis and potentially in guiding treatment.

Duplication of the genome and successful mitotic cell division requires the coordinated activity of hundreds of proteins. Many are known, but a complete list of the components of the cell cycle machinery is still lacking. This thesis describes a series of data driven analyses to assemble a comprehensive list of genes induced during the human cell cycle. To start with, a meta-analysis of previous transcriptomics studies revealed a larger number of cell cycle genes consistently expressed across multiple human cell types than previously reported. Following this observation, the cell cycle transcriptome was further investigated with the generation of a new time-course microarray dataset on normal human dermal fibroblasts (NHDF) undergoing synchronised cell division. Network cluster analysis of these data identified transcripts whose expression was associated with different stages of cell cycle progression. Co-expression of these transcripts was then analysed using a complementary dataset that included genome-wide promoter expression of a wide range of human primary cells. This resulted in the identification of a core set of 545 cell cycle genes, mainly associated with G1/S to M phases, which showed a high degree of co-expression across all cell types. Expression of 75% of these genes was also found conserved in mouse, as revealed by the analysis of a new microarray experiment generated from mouse fibroblasts. Gene Ontology and motif enrichment analysis validated the list with significant enrichments for terms and transcription factor biding sites linked with cell cycle biology. Toward a better interpretation of these 545 genes, a meticulous manual annotation exercise was carried out. Unsurprisingly, the majority of these genes were known to be involved in S and M phases-associated processes, however 50 genes were functionally uncharacterised. A subset of 36 of these were then taken forward for subcellular localisation assays. These studies were performed by transfection of human embryonic kidney cells (HEK293T) with GFP-tagged cDNA clones leading to the finding of four uncharacterised proteins co-localising with the centrosome, a crucial organelle for normal cell cycle progression. This thesis represents an attempt in documenting the genes actively transcribed and therefore likely involved in the processes associated with cell cycle, hence providing a comprehensive catalogue of its key components. In so doing, I have also identified a significant number of new genes likely to contribute to this central process vital in health and disease.

Schistosoma mansoni is a member of a genus of platyhelminths whose members cause the disease schistosomiasis. Particularly prevalent in sub-Saharan Africa, it is thought to be directly responsible for approximately 5500 deaths per year, as well as contributing significantly to morbidity, being responsible for 3.3 million lost disability-adjusted life years. Schistosomes are dioecious and male and female worms find one another and pair in the blood vessels of the host's liver. This sets in motion a unique feature of schistosome biology, the pairing-dependent sexual maturation of the female worms. Over the course of the next three weeks, the females fully develop their reproductive organs, especially ovaries and vitellarian tissue, to allow for the production of large quantities of eggs, which not only play a crucial role in the transmission of the parasites but are also responsible for much of the pathology associated with schistosomiasis. This thesis aims to explore the changes in gene expression which take place following pairing and result in the sexual maturation of females. To do so, RNA-Seq data was produced from male and female worms from mixed sex as well as single sex infections at 18, 21, 28, 35, 38 and 49 days post infection and analysed to understand when and how gene expression changes in paired worms. Then gene expression was examined in worms that had been removed from their partner to examine the process of regression, where female worms lose much of their reproductive tissue. The last experiments describe examine gene expression in the testes and ovaries of schistosomes, to reveal differences between the gonads of worms from mixed and single sex infections and understand in more detail how these worms may regulate the growth of their reproductive organs, contributing to our knowledge of schistosome biology.

Preterm birth (PTB) is a global public health problem that has significant adverse effects on neonatal mortality and morbidity. Progress in understanding the pathological mechanisms underlying PTB has been greatly hampered by the complex and polygenic nature of the disease. As a result, a multifaceted approach may hold promise for identifying true causal factors. The main objective of this thesis is to identify genes that play a role in the etiology of PTB using experimental data derived from different molecular levels (genome, transcriptome, and epigenome). To achieve this goal, we performed association studies using a candidate gene approach to identify genetic factors contributing to PTB. Our analysis of genetic variants in three OXT pathway genes (oxytocin (OXT), oxytocin receptor (OXTR), and leucyl/cystinyl aminopeptidase (LNPEP)) revealed several common polymorphisms in LNPEP that show significant association with prematurity. Large-scale sequence analysis of the OXTR gene identified several novel rare coding variants that might be of etiologic importance. Our results suggest that these variants, in aggregate, appear to make some contribution to susceptibility to PTB. We also examined the gene expression profiles in the human placenta to identify, at the transcriptomic level, candidate genes for PTB. Using splicing-sensitive microarray and deep sequencing technologies, we identified transcriptome signatures that differ between term (with and without labor) and preterm placental tissues and between placental and other human tissues. The transcriptome data were analyzed not only at the gene-level, but also at the exon-level, enabling the detection of alternative splicing events. The exon-level analysis revealed more frequent disruption of alternative splicing in preterm than term placental tissues, indicating that alternative splicing may represent one possible mechanism contributing to PTB. Our study at the epigenomic level was pursued through investigation of placental DNA methylation profiles. We, using a genome-wide approach, detected a panel of genes showing labor- and gestational age-associated methylation differences. Selected genes were validated using bisulfite sequencing and methylation-specific PCR. SLC30A3, a validated differentially methylated gene between term labor and preterm labor amnion tissues, for instance, may potentially play a role in the pathogenesis of PTB. Taken together, this thesis work provides a valuable source of novel candidate genes for PTB, and future research using integrative systems biology approaches may shed light on the molecular mechanisms underlying this complex, heterogeneous disease.

<p>Type 2 diabetes is characterized by insufficient insulin secretion to maintain euglycemia in the setting of peripheral insulin resistance. The majority of insulin-resistant diabetics are obese, yet not all insulin-resistant obese individuals develop diabetes. This obesity/diabetes dichotomy suggests that genetic factors play a pivotal role in disease pathogenesis.</p><p>Gene mapping has identified genetic quantitative trait loci (QTL) influencing disease-related phenotypes. To uncover molecular pathways leading from genotype to clinical trait, we classify phenotypes in greater depth and identify QTL that influence combinations of physiological traits, mRNA levels, and metabolite abundance. A major challenge then becomes deciphering the causal interrelationships among correlated phenotypes. </p><p>In this dissertation, we develop methods for building causal direction into an undirected network by including QTLs for each phenotype. We then apply and validate these methods in an F2 intercross between the diabetes-resistant C57BL/6 leptinob/ob (B6ob/ob) and the diabetes-susceptible BTBR leptinob/ob (BTBRob/ob) mouse strains. We show that genomic analysis can be integrated with liver transcriptional and metabolite profiling data to construct causal networks for specific metabolic processes in liver. This causal network construction led to the discovery of a pathway by which glutamine induces Phosphoenolpyruvate carboxykinase (Pck1) expression.</p><p>To investigate glutamine induction of Pck1 in the context of diabetes, we perform mRNA expression analysis and metabolic profiling in liver of the parental strains. We find glutamine is decreased with obesity in both strains; in the diabetes-resistant B6 strain, liver Pck1 expression parallels glutamine abundance, but in the diabetes-susceptible BTBR strain, Pck1 is elevated with obesity. Follow-up in vitro studies indicate that α-ketoglutarate, which is elevated nearly two fold in the livers of BTBR relative to B6 mice in vivo, may mediate the glutamine effect. We hypothesize that hepatic Pck1 is regulated by glutamine abundance in the liver of B6 animals, but in the presence of high α-ketoglutarate, Pck1 becomes uncoupled from glutamine regulation in the livers of diabetes-susceptible BTBR mice.</p><p>Our method of causal network construction led to the discovery of glutamine induction of a key hepatic gluconeogenic enzyme, a pathway potentially disrupted in the diabetes-susceptible BTBR mouse. Future studies will include identifying hepatic mediators of the glutamine effect, and applying QTL-directed networks to multiple organs to ultimately define causal relationships between tissues involved in diabetes progression.</p> / Dissertation

The endometrium is receptive to the embryo during a restricted window in the mid-secretory phase. My objectives were to develop a minimally-invasive endometrial sampling method for gene expression profiling, and to identify genes differentially expressed in the receptive phase. Twenty-three normo-ovulatory women underwent uterine fluid aspiration during the pre-receptive (LH+2) and receptive (LH+7) phase of the same natural cycle. RNA was extracted, reverse transcribed, amplified and hybridized to whole-genome microarrays. Unsupervised hierarchical clustering revealed self-segregation of pre-receptive and receptive samples. Importantly, profiling by uterine fluid aspiration was representative of biopsy. An unpaired t-test with a false discovery rate of 0.05 and a Δ threshold of 4-fold identified 245 unique transcripts as differentially expressed in the receptive phase. NanoString analysis validated 96% of these genes. This approach will now allow us to correlate expression of these candidate biomarkers to implantation outcomes, towards the development of clinical assays predictive for endometrial receptivity.

The endometrium is receptive to the embryo during a restricted window in the mid-secretory phase. My objectives were to develop a minimally-invasive endometrial sampling method for gene expression profiling, and to identify genes differentially expressed in the receptive phase. Twenty-three normo-ovulatory women underwent uterine fluid aspiration during the pre-receptive (LH+2) and receptive (LH+7) phase of the same natural cycle. RNA was extracted, reverse transcribed, amplified and hybridized to whole-genome microarrays. Unsupervised hierarchical clustering revealed self-segregation of pre-receptive and receptive samples. Importantly, profiling by uterine fluid aspiration was representative of biopsy. An unpaired t-test with a false discovery rate of 0.05 and a Δ threshold of 4-fold identified 245 unique transcripts as differentially expressed in the receptive phase. NanoString analysis validated 96% of these genes. This approach will now allow us to correlate expression of these candidate biomarkers to implantation outcomes, towards the development of clinical assays predictive for endometrial receptivity.

Despite virtually identical genomes, inbred animals often vary in phenotype, including behaviour, but the molecular basis of this phenomenon is unknown. Our hypothesis is that differences in behaviour between inbred rats are correlated with differential cortical mRNA transcript levels. 40 Lewis rats were subjected to 5 behavioural tests: two were used to categorize 10 animals into either “high” or “low” phenotype groups. Microarray gene expression profiling was performed for 5 rats from each group. Three main analyses were performed to: (1) identify differential expression between the high and low groups, (2) identify correlations between transcript levels and individual behaviour scores, and (3) determine if the results of this replicate experiment overlapped with a previous pilot experiment. Some array results were confirmed by RT-PCR. We found that this experiment did not replicate the findings from the pilot, however several genes of interest were determined and were validated by RT-PCR.

Two immunologically distinct strains of poultry coccidium Eimeria maxima, Guelph (GS) and M6 strains, were investigated. Paired in vivo experiments demonstrated that GS and M6 have prepatent periods of approximately 120 h followed by peak oocyst shedding at 144 150 h post inoculation. Fecundity of E. maxima M6 (12.8×103±1.95 oocysts shed/oocyst inoculated) was approximately twice that of GS (6.9×103±3.33) when inoculated with 1×103 infective oocysts per bird. Numerous sequential observations of synchronized populations of oocysts sporulating at 26°C showed no difference in the sporulation kinetics of the two strains; in both strains, sporogony was divided into five morphologically distinguishable stages whose abundance peaked at the following times during sporulation: unsporulated oocysts at 0 h; sporoblast anlagen at 18 h; sporoblasts without sporocyst walls at 22 h; and sporocysts without mature sporozoites at 38 h. Total RNA was isolated from four stages of sporogonic development (18 h, 22 h and 38 h of sporulation, and excysting sporozoites). These RNA samples were quantitatively pooled from each strain separately prior to selection of poly A mRNA that was then fragmented, end-labeled and pyrosequenced using an Illumina HiSeq 2000 sequencer. The resulting transcriptome sequences (~48.8×109bp total reads) were paired and de novo assembled. Ten thousands transcripts (5,000 from each strain) were searched against GenBank using blastx. A total of 2,067 transcripts of GS and 1,610 transcripts of M6 were assigned to putative biological function; ~60% of functionally annotated transcripts mapped to metabolic or cellular processes. GPI anchored surface antigens (SAgs) identified in GS (18 SAgs) and M6 (18 SAgs) belonged to four major multi copy gene families and 2 single copy loci. Relative expression of SAgs expressed by both strains was generally similar; however, 3 GPI-anchored SAgs were uniquely expressed by each of GS and M6. One multigene locus demonstrated strain-specific SAg expression that may explain the lack of cross immunity between these strains. This represents the first transcriptome data of sporulation of E. maxima and first comparison of immunologically distinct strains of any Eimeria sp. These data should aid in the search for antigenic targets that could be included in future subunit vaccines against these important agricultural parasites. / Research Funding: Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ontario Ministry of Agriculture and Food (OMAF); Funding of Studies: Iraqi Ministry of Higher Education and Scientific Research (MOHESR) for PhD scholarship support; American Society of Parasitologists for a Marc Dresden Travel Award to attend the 2012 ASP Annual Meeting.

Despite virtually identical genomes, inbred animals often vary in phenotype, including behaviour, but the molecular basis of this phenomenon is unknown. Our hypothesis is that differences in behaviour between inbred rats are correlated with differential cortical mRNA transcript levels. 40 Lewis rats were subjected to 5 behavioural tests: two were used to categorize 10 animals into either “high” or “low” phenotype groups. Microarray gene expression profiling was performed for 5 rats from each group. Three main analyses were performed to: (1) identify differential expression between the high and low groups, (2) identify correlations between transcript levels and individual behaviour scores, and (3) determine if the results of this replicate experiment overlapped with a previous pilot experiment. Some array results were confirmed by RT-PCR. We found that this experiment did not replicate the findings from the pilot, however several genes of interest were determined and were validated by RT-PCR.