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Genes are typically expressed in equal amounts from both parentally inherited chromosomes. However, recent studies have demonstrated that genes can be preferentially transcribed from a locus. Non-random preferential expression of alleles can occur in a parent-of-origin pattern, known as imprinting, where epigenetic factors regulate their transcription. Alternatively, it can occur in a haplotype-specific pattern, where cis-acting polymorphisms in regulatory regions are thought to underlie the phenomenon. Both forms of unequal allelic expression have been associated with human disease. Consequently, it is important to identify genes subject to unequal allelic expression and characterize mechanisms that regulate differential transcription. This thesis presents the results of a screen for unequal allelic expression where approximately 50 murine transcripts homologous to genes on human chromosome 7 were analyzed. Human chromosome 7 was selected due to its association with several human disorders that show parent-of-origin effects. The screen identified non-imprinted preferential allelic expression in numerous transcripts and demonstrated that such patterns can occur in tissue specific patterns. Paraoxonase-1 (Pon1), a gene implicated in arthrosclerosis, was identified as having a dynamic pattern of allelic expression which varies throughout embryonic development. This finding represents the first report of a developmentally regulated pattern of allelic variance. Carboxypeptidase-A4 (Cpa4) was identified as having a tissue-specific imprinted pattern of expression, where the maternal allele was preferentially expressed in all embryonic tissues, with the exception of the brain. The Krüppel-like factor 14 gene (Klf14), a novel imprinted transcript, was found to have ubiquitous maternal expression in all human and murine tissues analyzed. A differentially methylated region, generally associated with imprinted transcripts, was not found in the gene’s CpG island, nor was a differential pattern of histone modifications identified. However, it was determined that maternal methylation regulates the transcript. The data in this thesis contribute to our understanding of the numerous patterns of allelic expression that exist in nature and the diverse mechanisms that regulate them. Ultimately, quantitative analyses of allelic expression patterns and the identification of their underlying genomic DNA sequences will become standard protocol in all biomedical studies.

A RIDGE (Region of IncreaseD Gene Expression), as defined by previous studies, is a consecutive set of active genes on a chromosome that span a region around 110 kbp long. This study investigated RIDGE formation by focusing on the well-defined, immunological important MHC locus. Macrophages were assayed for gene expression levels using the Affymetrix MG-U74Av2 chip are were either 1) uninfected, 2) primed with IFN-g, 3) viral activated with mCMV, or 4) both primed and viral activated. Gene expression data from these conditions was studied using data structures and new software developed for the visualisation and handling of structured functional genomic data. Specifically, the data was used to study RIDGE structures and investigate whether physically linked genes were also functionally related, and exhibited co-expression and potentially co-regulation. A greater number of RIDGEs with a greater number of members than expected by chance were found. Observed RIDGEs featured functional associations between RIDGE members (mainly explored via GO, UniProt, and Ingenuity), shared upstream control elements (via PROMO, TRANSFAC, and ClustalW), and similar gene expression profiles. Furthermore RIDGE formation cannot be explained by sequence duplication events alone. When the analysis was extended to the entire mouse genome, it became apparent that known genomic loci (for example the protocadherin loci) were more likely to contain more and longer RIDGEs. RIDGEs outside such loci tended towards single-gene RIDGEs unaffected by the conditions of study. New RIDGEs were also uncovered in the cascading response to IFNg priming and mCMV infection, as found by investigating an extensive time series during the first 12 hours after treatment. Existing RIDGEs were found to be elongated having more members the further the cascade progress.

The aquaculture sector is currently thriving, and has expanded to meet the demand for fish and shellfish as an alternative protein source to meat. This is especially true for high value products such as Atlantic salmon, where in Scotland salmon farming is reported to be worth> £1 billion to the national economy. Currently around 40% of farmed fish and shellfish destined for human consumption are derived from aquaculture. Therefore, a great deal of attention is paid to problems that the industry faces, with fish diseases of paramount importance. A variety of species of bacteria, viruses and parasites are common in the aquatic environment, which can result in serious diseases amongst fish stocks. As a result, ways to improve disease resistance have been the focus of much attention, with the use of vaccines considered a desirable way forward. However, other approaches are also followed, such as the use of immunostimulants to improve fish health in a more limited, non-specific way, or the use of genetic markers to allow selective breeding of important disease resistance traits. For all of these approaches more information is needed on the pathways that give rise to disease resistance in fish in different situations, to allow their manipulation or monitoring, and the studies in this thesis are directed towards this goal. Fish has been used as a model to study the evolution of vertebrate immunolity for some deacades, especially work on humoral immune responses where knowledge on antibody production has dominated much of the literature on fish immunology. In contrast, little known about specific cell-mediated immunity in fish, even though it also likely plays an important role in the immune system and disease resistance. Therefore, this thesis has been focused on analysing such responses, taking advantage of the recently discovered cytokines of adaptive immune responses in fish, which allow transcriptomic studies in particular to look at the molecules turned on during infection and after vaccination. Thus the goal of this thesis was to take advantage of some successful vaccines that exist for rainbow trout, and examine the gene expression changes that occur in vaccinated trout post-challenge with the homologus pathogen, and to try to dissect pathways that may correlate with disease resistance in this species.

Pulmonary arterial hypertension (PAH) is a disease of the lung vessels that causes severe effects on the right ventricle of the heart; ultimately, most patients with severe PAH die as a result of right heart failure. However, little is known about the causes of right heart failure. Here, we describe a pattern of gene expression that differs between the normal rat left ventricle (LV) and right ventricle (RV). These genes are known to be involved in the development of the heart as well as adaptations to the heart during stress. This gene expression pattern is used as a baseline to describe changes in gene expression the occur in the RV as a result of adaptive hypertrophy, stimulated by chronic hypoxia, or right ventricular failure (RVF), caused by administration of Su5416 and hypoxia. The genes differing between RVF and hypertrophy encode glycolytic enzymes, mitochondrial electron transport chain complexes, cell-growth promoting proteins, and angiogenic capillary maintenance proteins. Additionally, we show that RVF is associated with an increase in the serum cytokine production of IL-1 beta, IL-10, TNF-alpha, and VEGF. Finally, we show that treatment with the beta-adrenergic receptor blocker carvedilol partially changed the gene expression pattern seen with RVF. The most profound effects were on the genes encoding glycolytic enzymes and mitochondrial electron transport chain complexes. Together, these results show that the normal LV and RV have a distinct pattern of expression and that the failing RV is characterized by changes in cell growth, angiogenesis, and energy utilization. Treatment with carvedilol can partially reverse these gene expression changes in the failing RV.

Epigenetic misregulation of gene expression is known to be an important feature in cancer. This has mainly been studied at the level of changes in DNA methylation and histone modifications at individual genes. In this thesis I have set out to investigate whether there are long-range changes in chromatin structure linked to altered gene expression in breast cancer. From large published datasets, I used a computational approach to identify large genomic regions which are coordinately misregulated in breast cancer independent of copy number aberrations (genomic effects). I found 26 regions of co-ordinate regulation of neighbouring genes that are consistent between breast tumours and breast cancer cell lines. These regions had different expression phenotypes (activation, repression, no change) compared to normal breast and also with tumour subtype (luminal vs basal and ER status). The regions of epigenetic regulation (RER) identified in breast cancer were mostly cancer type specific. I investigated the mechanism of long-range misregulation at one such region on chromosome 16p11.2 which is aberrantly activated in breast cancer. Interestingly, in estrogen-receptor positive (ER+ve) cells, genes in this region are upregulated relative to estrogen receptor negative (ER-ve) cells. Using fluorescence in situ hybridisation (FISH) I found that in ER+ve breast cancer cell lines and tumour tissue this region is in a more decondensed chromatin architecture than in ER-ve cell lines and tumour tissue. Furthermore this region was very compact in a normal breast epithelial cell line and breast tissue corresponding to what would be expected from the expression data. Estrogen was found to play a key role in maintaining the aberrant decondensation of chromatin at this locus on chr16p11.2, as shown by compaction of the region by starving ER+ve cells of estrogen and decompaction upon subsequent estrogen treatment. Interestingly there was also an estrogen mediated repositioning of the 16p11.2 RER domain away from the nuclear centre in hormone starved conditions and towards the centre upon estrogen stimulation. Together these results show that estrogen is key to regulating the changes in nuclear organisation and chromatin decompaction at this locus, which are associated with aberrant patterns of gene expression in ER+ve breast cancer.

Introduction Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive (ER+) post-menopausal breast cancer. However, response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. There is a need to identify pre- or early on-treatment biomarkers to predict sensitivity which outperform those currently used, in a move towards stratified treatments and improved patient care. Given the heterogeneity known to exist in the breast cancer population, and the limited availability of matched pre- and on-treatment clinical material, this study also sought to develop novel data integration approaches allowing for the inclusion of similar previously published datasets, thus maximising the power of this study. Experimental Design Pre- and on-treatment (at 14 days and 3-months) biopsies were obtained from 34 postmenopausal women with ER+ breast cancer receiving 3 months of neoadjuvant letrozole. Illumina Beadarray gene expression data from these samples were combined with Affymetrix GeneChip data from a similar published study (n=55) and crossplatform integration approaches were evaluated. Dynamic clinical response was assessed for each patient from periodic 3D ultrasound measurements during treatment. Results Despite intrinsic differences between different microarray technologies, suitably similar studies can be directly integrated for robust and meaningful meta-analysis with improved statistical power. After mapping probe sequences to Ensembl genes it was demonstrated that, ComBat and cross platform normalisation (XPN), significantly outperform mean-centering and distance-weighted discrimination (DWD) in terms of minimising inter-platform variance. In particular it was observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets. A pipeline for the successful integration of microarray datasets from different platforms was developed. Using this approach a classifier of clinical response to endocrine therapy in the neoadjuvant setting based on the expression of 4 genes was developed which predicted response with 96% and 91% accuracy in training (n=73) and independent validation (n=44) datasets respectively. An early on-treatment biopsy was found to improve predictive power in addition to pre-treatment alone. Conclusions Using a novel data integration approach developed as part of this study, a model comprising 4 novel biomarkers for accurate and robust prediction of clinical response to AIs by two weeks of treatment has been generated and validated. On-going work will investigate the applicability to other anti-estrogens, and the adjuvant setting and will assess the potential for a new therapy response test.