Differently expressed genes e.g. in a disease may play a role in the etiology or progression of the disease. The traditional approach of finding differentially expressed genes is to compare the expression levels in the groups, and produce a list of differentially expressed candidate genes. With many pairwise comparisons, the risk of introducing type I and type II errors is high. One solution is to group together genes that are co-expressed into modules. Weighted gene coexpression network analysis (WGCNA) uses a topological overlap module approach and has been proved to find patterns that have been undetected by gene-to-gene comparison methods. qPCR has high sensitivity and specificity, and advances in technology has increased its throughput. The goal of the project was to construct WGCNA modules from qPCR data and evaluate the WGCNA method in five previously published qPCR data sets. There was little overlap between the differentially expressed genes found in the published articles and the candidates found by WGCNA. In three data sets WGCNA failed to produce any significant genes. In one of the data set significant genes were found where the original article failed. In one data set, 19 out of 60 genes that are top-ranked by the original authors were found in significant WGCNA modules. The biggest challenge with this type of comparison is to determine whether results that differ from the published studies are more or less biologically relevant. It is difficult to draw conclusions on whether the method is suitable for use for analysis of qPCR data based on this study.

Recent developments in automation and novel experimental techniques have led to the accumulation of vast amounts of biological data and the emergence of numerous databases to store the wealth of information. Consequentially, bioinformatics have drawn considerable attention, accompanied by the development of a plethora of tools for the analysis of biological data. DNA microarrays constitute a prominent example of a high-throughput experimental technique that has required substantial contribution of bioinformatics tools. Following its popularity there is an on-going effort to integrate gene expression with other types of data in a common analytical approach. Pathway based microarray analysis seeks to facilitate microarray data in conjunction with biochemical pathway data and look for a coordinated change in the expression of genes constituting a pathway. However, it has been observed that genes in a pathway may show variable expression, with some appearing activated while others repressed. This thesis aims to add some contribution to pathway based microarray analysis and assist the interpretation of such observations, based on the fact that in all organisms a substantial number of genes take part in more than one biochemical pathway. It explores the hypothesis that the expression of such genes represents a net effect of their contribution to all their constituent pathways, applying statistical and data mining approaches. A heuristic search methodology is proposed to manipulate the pathway contribution of genes to follow underlying trends and interpret microarray results centred on pathway behaviour. The methodology is further refined to account for distinct genes encoding enzymes that catalyse the same reaction, and applied to modules, shorter chains of reactions forming sub-networks within pathways. Results based on various datasets are discussed, showing that the methodology is promising and may assist a biologist to decipher the biochemical state of an organism, in experiments where pathways exhibit variable expression.

Emotional processing and characterization of internal and external stimuli is believed to play an integral role in consumer acceptance or rejection of food products. In this research three experiments were completed with the ultimate goal of adding to the growing body of research pertaining to food, emotions and acceptance using traditional affective sensory methods in combination with implicit (uncontrollable) and explicit (cognitive) emotional measures. Sweetness equivalence of several artificial (acesulfame potassium, saccharin and sucralose) and natural (42% high fructose corn syrup and honey) sweeteners were established to a 5% sucrose solution. Differences in consumer acceptability and emotional response to sucrose (control) and four equi-sweet alternatives (acesulfame potassium, high fructose corn syrup, honey, and sucralose) in tea were evaluated using a 9-point hedonic scale, check-all-that-apply (CATA) emotion term questionnaire (explicit), and automated facial expression analysis (AFEA) (implicit). Facial expression responses and emotion term categorization based on selection frequencies were able to adequately discern differences in emotional response as it related to hedonic liking between sweetener categories (artificial; natural). The potential influence of varying product information on consumer acceptance and emotional responses was then evaluated in relation to three sweeteners (sucrose, ace-k, HFCS) in tea solutions. Observed differences in liking and emotional term characterizations based on the validity of product information for sweeteners were attributed to cognitive dissonance. False informational cues had an observed dampening effect on the implicit emotional response to alternative sweeteners. Significant moderate correlations between liking and several basic emotions supported the belief that implicit emotions are contextually specific. Limitations pertaining to AFEA data collection and emotional interpretations to sweeteners include high panelist variability (within and across), calibration techniques, video quality, software sensitivity, and a general lack of consistency concerning methods of analysis. When used in conjunction with traditional affective methodology and cognitive emotional characterization, AFEA provides an additional layer of valued information about the consumer food experience. / Master of Science in Life Sciences

Skin cancer is one of the most common forms of adult solid tumour. The incidence is increasing rapidly making skin cancer a major health problem in several countries. Cutaneous Malignant Melanoma (CMM) is the least common but the most life threatening type of skin cancers and is responsible for 90% of all skin malignancy associated deaths. The precise cellular and molecular etiology of malignant melanoma is quite complex and the molecular events directly related to melanoma progression are yet to be elucidated. However, recent advances in molecular biology have resulted in a clearer understanding of the cellular and molecular events of skin cancer development. The best-characterized locus associated with CMM development is the CDKN2A that maps to chromosome 9p21 and encodes for the cell cycle regulator p16 tumour suppressor gene (TSG), and is frequently inactivated in melanoma tumours. In addition to p16, other loci located in 9p21 appear to be important in CMM development and functional evidence for the presence of TSG(s) has been provided (Parris et al., 1999). The aim of our study is to contribute to the understanding of CMM development by isolating and characterising novel TSG(s) at this location. In order to pursue identifying potential TSG(s), we have developed several monochromosome hybrids using microcell mediated chromosome transfer, and evaluated the tumourigenicity of the constructed hybrids by anchorage independent growth in soft agar. For the molecular biology aspects, expression analysis of the genes in the 9p21 region was carried out by reverse transcription PCR. Potential candidate tumour suppressor genes were then carefully evaluated by generating expression profiles via conducting real time PCR. Experimental evidence is provided which supports the candidacy of interferon alpha 1 (IFNA1) as a tumour suppressor gene for melanoma development.

The recent increase in availability of next generation sequencing methodologies has led to extensive analysis of the genome of Clostridium difficile. In contrast, protein expression analysis, crucial to the elucidation of mechanisms of disease, has severely lagged behind. In this study, in-depth proteomic analysis of three strains of varying virulence, demonstrated previously in an animal model, has been undertaken against a background of the sequenced genomes. Strain B-1 is a historic, virulent, ribotype 005 clone, strain A represents the emerging hypervirulent 027 ribotype, while strain Tra5/5, ribotype 001, is of low virulence. To undertake a comprehensive overview of the expressed proteome, both 1D and 2D gel electrophoresis were used to separate and display the protein content of each isolate. This was coupled to MALDI-TOF and LC-MS/MS mass spectrometry for protein identification. A total of 888 different proteins were characterised by comparative analysis of isolates grown in parallel for 64 hours on blood agar. Of these, only 38% were shared between all isolates. An additional 350, 243 and 398 proteins were detected from broth cultures, and the use of a hexapeptide bead library, designed to capture low abundance proteins, led to the detection of a further 148, 127, and 171 proteins in strains A, B-1 and Tra5/5 respectively. Relative differential expression was investigated using Differential In Gel Electrophoresis (DIGE), and five proteins were shown to have a statistically higher concentration in strain A, twelve in strain B-1 and eight in strain Tra5/5. A number of these were surface proteins, with selected S-layer proteins found to be up-regulated in each strain, and the flagellar protein, FliC, up-regulated in both A and B-1. Furthermore, differential post-translation modification events were seen in flagellar and S-layer proteins. In-vivo expression of these proteins was mapped using Western blotting. Immunodetection of the majority of these, including FliC and the high molecular weight S-layer protein, were conserved between the three strains, but a notable series of immunoreactive protein spots were present in strains A and Tra5/5 but not B-1, most likely corresponding to an additional S-layer protein present in the genomes these strains, but not that of B-1. Protein expression differences for a number of previously proposed virulence proteins were evident between strains, including toxin B, sporulation, flagella and the S-layer proteins, metabolic enzymes, stress response proteins and ABC transporters. This study strongly supports the view that the virulence of Clostridium difficile is multifactorial, and that a number of related factors, although not directly required for pathogenicity, may serve to modulate the virulence of individual strains.

Various types of recurrent neural networks have been used as models for the regulatory relationships between genes. The neural network is trained on the data from micro-array techniques, each gene corresponds to a neuron in the network. The data from the micro-array technologies has numerous genes, but usually involves few samples, this makes the network heavily under-determined. In this work we will propose a method that can cope with the poorness of the data. We will use a Hopfield-type neural network to model the ontogenetic differentiation of female honeybees. A method that identifies the genes that determine the castes is proposed.

<p>Various types of recurrent neural networks have been used as models for the regulatory relationships between genes. The neural network is trained on the data from micro-array techniques, each gene corresponds to a neuron in the network. The data from the micro-array technologies has numerous genes, but usually involves few samples, this makes the network heavily under-determined. In this work we will propose a method that can cope with the poorness of the data. We will use a Hopfield-type neural network to model the ontogenetic differentiation of female honeybees. A method that identifies the genes that determine the castes is proposed.</p>

<p>In order to derive reliable protein networks it has recently been suggested that the combination of information from both gene and protein level is required. In this thesis a combination of gene expression and protein chip analysis was performed when constructing protein networks. Proteins with high affinity to the same substrates and encoded by genes with high correlation is here thought to constitute reliable protein networks. The protein networks derived are unfortunately not as reliable as were hoped for. According to the tests performed, the method derived in this thesis does not perform more than slightly better than chance. However, the poor results can depend on the data used, since mismatching and shortage of data has been evident.</p>

Serine/Arginine-rich proteins (SR-proteins) have been well characterized in metazoans and in the flowering plant Arabidopsis thaliana. But so far no attempts on characterizing SR-proteins in the moss Physcomitrella patens have been done. SR-proteins are a conserved family of splicing regulators essential for constitutive- and alternative splicing. SR-proteins are mediators of alternative splicing (AS) and may be alternatively spliced themselves as a form of gene regulation. Three novel SR-proteins of the SR-subfamily were identified in P. patens. The three genes show conserved intron-exon structure and protein domain distribution, not surprising since the gene family has evidently evolved through gene duplications. The SR-proteins PpSR40 and PpSR36 show differential tissue-specific expression, whereas PpSR39 does not. Tissue-specific expression of SR-proteins has also been seen in A. thaliana. SR-proteins determine splice-site usage in a concentration dependent manner. SR-protein overexpression experiments in A. thaliana and Oryza sativa have shown alteration of splicing patterns of endogenous SR-proteins. Overexpression of PpSR40 did not alter the splicing patterns of PpSR40, PpSR36 and PpSR39. This suggests that they might not be a substrate for PpSR40. These first results of SR-protein characterization in P. patens may provide insights on the SR-protein regulation mechanisms of the common land plant ancestor.

Aging, characterized by a time-dependent functional decline, eventually results in the death of an organism. Unfortunately, this complex biological phenomenon is poorly understood. In order to dissect the molecular changes associated with aging, the identification and molecular characterization of the genes that regulate this universal process is absolutely necessary. The expectation is that the isolated genes potentially have human homologues and can be experimentally analyzed in Drosophila melanogaster in order to determine basic function. In an attempt to find candidate genes that may influence aging, the enhancer trap technique was utilized to identify age-related regulatory elements. The genomic regions surrounding the insertion site of the enhancer trap lines have the potential to be regulated by the characterized enhancer. A previous screen determined the temporal pattern of 180 enhancers trap lines, known as DJ lines. Many of these lines demonstrated an expression pattern that was associated with age. Several of the genes within the nearby genomic regions of six sequenced DJ lines, DJ695, DJ710, DJ849, DJ767, DJ761 and DJ694, were chosen for transcript quantification. Prior to gene quantification, reverse transcription, an essential step in the experimental procedure, was assessed for the error it incorporated into quantification. Specifically, an exogenous molecule was used to ensure that unsuccessful reverse transcription reactions had the potential to be identified and, soon after, discarded. This was achieved through the use of a spike RNA molecule, Luciferase. Luciferase was shown to be a diagnostic tool that can be used in determining reverse transcription efficiency. Eight genes were chosen from the aforementioned DJ lines and quantitative PCR revealed that the natural regulation of some genes were comparable to the, previously obtained, expression pattern of the enhancer trap line. Although the expression of other genes did not correlate to that of the enhancer trap lines, all genes exhibited expression patterns that were age-associated. The known functions of these candidate genes and the relevant homologues are discussed. These findings validate the use of the enhancer trap technique in the identification of candidate genes involved in the aging process. / Thesis (Master, Biology) -- Queen's University, 2009-02-09 10:59:16.871