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In this thesis, we classified user comments posted on online forums related to “Newborn Genome Sequencing” (NGS). User comments were annotated as irrelevant, positive, negative, or mixed by two annotators. The objective was to create a classification model that could predict the sentiment of each user comment with a high accuracy. To compare classifiers, a baseline classifier (Accuracy 52%) was created. We created a single classifier (called flat comment-level classifier with accuracy of 65.14%) to classify comments into irrelevant, positive, negative, or mixed. A more sophisticated classifier, named two-level comment classifier, consisting of two classifiers, was created (Accuracy 69.81%): - The first classifier that classified each comment into relevant or irrelevant ones. - The second classifier that classified each relevant comment (predicted by the first classifier) as positive, negative, or mixed. 18 extra features were generated to improve the accuracy of the flat classification compared to baseline classifier (from 52% to 65.14% for flat comment classification, and 69.48% to 69.81% for two-level comment classification). Attempts were made to enhance the result of the two-level comment classifier by using the discourse structure of each sentence in a comment. The accuracy achieved by this enhanced two-level classifier was 64.24%. Therefore, removing irrelevant EDUs did not improve the accuracy. To achieve the above-mentioned enhancement, all comments were segmented into their consisting elementary discourse units (EDUs). We removed irrelevant EDUs from the relevant comments before running the second classifier. Furthermore, we performed EDU-level classification by creating two classifiers: - A flat classifier: classified all EDUs into irrelevant, positive, negative, or neutral - A two-level EDU: classified EDUs, first, into relevant or irrelevant and then classified the relevant EDUs (predicted by the first classifier) into positive, negative, or neutral ones. The accuracy achieved for the flat EDU-level classifier was 81.84%. However, due to the highly imbalanced nature of the EDU dataset, the F-measure for positive, negative, and neutral class was very low. Under-sampling was performed to improve the F-measure for positive, negative, and neutral class. Another topic investigated was to know why forum users supported or rejected NGS. To extract the arguments, the comments were segmented into EDUs. Following segmenting, each EDU was annotated as relevant or irrelevant to NGS. Each relevant EDU was annotated as for or against NGS. Topic related EDUs were selected as well as two EDUs before and after the topic-related EDUs. Bigrams, trigrams, four-grams and five-grams were created from extracted EDUs. Five-grams were more meaningful for human annotators, and were therefore favoured and ranked based on frequency in the dataset. Following ranking of the five grams, the top five were selected as the possible arguments.

Genome sequencing is emerging as a powerful tool to identify the molecular mechanism of cancer progression. However, the software tools to define genomic and post-genomic mutations are just in its infancy. We have used a novel software algorithm to analyse the cancer genome by DNAseq and expressed cancer genome arising from transcription by RNAseq to define dominant sources of potentially expressed tumour-specific mutations and oncogenic targets. We focus primarily on the rare human pleomorphic sarcoma as a disease of high unmet clinical need but use a range of cancer models to accelerate the development of the pipeline. First, we applied next generation sequencing of whole exomes of tumour tissues and two matched normal tissues (blood and “normal” tumour adjacent tissue) from a small set of patients to define parameters for use of the new software. The approaches identified significant mutations in tumour relative to germline DNA, but also in normal adjacent tissue, relative to normal germline, consistent with known field cancerization. Thus, in setting up the larger sequencing screen in the subsequent set of twenty cancer pleomorphic sarcoma cancer patients, whole exome sequencing was performed on tumour tissue and their matched normal adjacent tissues, rather than germline blood derived DNA, to define truly tumour-specific mutations. This approach provided sets of recurrent non-synonymous mutations in tumour tissue such as a transmembrane protease and suggests potential therapeutic targets for future focus that are highly tumour specific in pleomorphic sarcoma. A major problem with using DNA genomics only to define drugable landscapes in cancer is that the tumour genome is static and the mutations do not reflect the expressed cancer landscape at the time of surgery. Thus, in a smaller subset of patients we also applied shotgun RNAseq to determine the number of expressed mutated genes. We defined within the parameters chosen, from 8-17% of the mutated genome is expressed as defined at the RNA level. However, to our surprise, there were an order of magnitude more RNA mutations that were not DNA encoded suggestive of RNA editing events. Each patient showed elevated RNA edits that were independent of each other suggesting a highly-patient, cancer-specific perturbation in the specificity of the RNA editing machinery. We thus developed a cancer cell model to validate the RNA-editing software and we found we could recapitulate some of the RNA edits observed in clinical tumour tissue, in particular the signalling kinase in the MAP kinase-kinase-kinase-kinase super-family. It was interesting that RNA edits can often cluster in exon-intron boundaries suggesting a link to splicing and allows us to begin to produce “rules” for RNA editing. These data provide future direction to understand the role of RNA editing, as well as DNA encoded mutations, as mutagenic events and possible drugable targets in cancer signalling. Lastly, novel or orphan mutant proteins observed in human cancers, whether from DNA encoded mutant proteins or from RNA-edited driven mutant protein synthesis require new tools and technologies to discover new oncogenic signalling mechanisms. We developed an SBP-tagged affinity purification method in combination with label-free SWATH mass spectrometry to identify a novel binding protein for the gain-of-function mutant protein in a key metastatic gene, ELMO1. This identified an elevated interaction with another oncogenic protein encoded by AGR2 gene and validates this proteomics discovery platform to further advance function of new mutated proteins. In conclusion, we have applied and validated newly emerging software to begin to interrogate cancer tissue from patients of unmet clinical need in order to define new mechanisms of cancer progression and to define possibly new or better drug targets for new therapies. The data identified highly recurrent genome encoded mutations in human pleomorphic sarcoma and a potentially novel, targetable landscape represented by RNA editing driven mutant protein production. This will provide a foundation for future work on making better choices to advance our ability to improve patient management in human pleomorphic sarcoma.

In 2005 an equine rhinitis A virus (ERAV) isolate was recovered from a febrile horse during a respiratory outbreak in Ontario. This isolate (ERAV/ON/05) was propagated in cell culture and used to study its genomic characteristics and to investigate the clinical features in experimentally infected ponies. The fulllength genome of this isolate was sequenced and compared with other ERAV available in GenBank. The isolate genome is 7839 nucleotides (nts) in length with a variable 5’UTR and a more conserved 3’UTR. When the isolate was compared to other reported ERAV, an insertion of 13 nts in the 5’UTR was identified. Phylogenetic analysis demonstrated that ERAV/ON/05 was closely related to the ERAV/PERV isolate, which was recovered in 1962 in the United Kingdom. An experimental model was developed to study the clinical infection in naïve healthy ponies (ERAV/ON/05 n=4 and placebo n=4). ERAV/ON/05 induced clinical respiratory disease compared to placebo. The clinical signs consisted of pyrexia, nasal discharge, increased and abnormal lung sounds, increased size of submandibular lymph nodes and persistent mucopus in the trachea (up to 21 days post-infection). The virus was isolated from the lower and upper airways up to day 7 post-infection, corresponding with the detection of neutralizing ERAV antibodies. Assessment of the cytokine profile from bronchoalveolar lavage (BAL) cells demonstrated that this infection induced down-regulation of the mRNA expression of IL-4. One year later, four previously infected ponies with neutralizing antibodies to ERAV were assigned to a reinfection trial. None of the re-infected ponies developed clinical disease, and only one animal had a four-fold increase in antibody titres to ERAV. Attempts to recover the virus from the re-infected ponies using cell culture were negative; however, a down-regulation of the mRNA expression of IL-4 and IFN-β was identified in BAL cells. In conclusion, this study shows that the genome of ERAV has not significantly changed in the last 50 years and more importantly the virus induces clinical respiratory disease similar to other common equine respiratory viruses.

Necrotic enteritis (NE) is an economically important, but poorly understood, disease of poultry, typically caused by Clostridium perfringens Type A strains that carry the NetB toxin gene. The objective of the current research was to identify additional genes associated with NE-causing C. perfringens strains, and thus putatively involved in virulence. To identify novel NE-associated genes, the draft genome sequences of seven C. perfringens NE isolates and one isolate from a healthy chicken were compared against nine non-poultry genomes, and three highly-conserved NE-associated loci (NELoc-1 – 3) were identified. The largest locus (NELoc-1) encoded 37 putative proteins, including NetB, an internalin-like protein, a ricin-domain protein, two leukocidins, several cell-surface proteins and a cyclic-di-guanidine monophosphate (c-di-GMP) signaling system. NELoc-1 and -3 were both localized to separate plasmids that are both predicted to undergo conjugative transfer. These findings suggest that NE pathogenesis involves multiple virulence factors that are encoded on discrete pathogenicity loci, some of which are plasmid-borne. To further elucidate the genetic basis of NE pathogenicity, a microarray was developed based on two of the sequenced NE bird isolates, and used to assess the gene content of 54 isolates from chickens with and without NE. Variable genomic regions associated with netB-positive isolates were identified, including several chromosomal fitness-related loci, such as a carbohydrate ABC transporter, ferric-iron siderophore uptake system, and adhesion locus. Additional loci were related to plasmid maintenance. This study suggests that chromosomal background confers a selective advantage to NE-causing strains, possibly through mechanisms involving iron acquisition, carbohydrate metabolism and plasmid maintenance Finally, the relationship between netB presence, NetB production and host NE status was examined to assess the hypothesis that netB-positive isolates from healthy birds frequently do not express NetB toxin. The expression of NetB toxin was determined in 57 poultry isolates, demonstrating that NetB expression is closely correlated with the presence of netB, and independent of host disease status. In conclusion, these studies have identified a number of C. perfringens genes predicted to play a role in NE pathogenesis, and suggest that NE is a complex, multifactorial disease involving both host and plasmid-encoded virulence factors.

Vibrio parahaemolyticus is considered to be an emerging, yet understudied, human pathogen. The V. parahaemolyticus BB22OP genome was sequenced to allow for a comparative analysis between the genome of BB22OP and another previously sequenced, pathogenic strain of V. parahaemolyticus, RIMD2210633. V. parahaemolyticus BB22OP is interesting because it exhibits a spontaneous phenotypic switch in colony morphology due to the loss of a functional OpaR; this also influences virulence. OpaR is the major quorum-sensing regulator in V. parahaemolyticus homologous to LuxR from V. harveyi. When opaR is removed from the RIMD2210633 genome, the same phenotypic switch is not seen indicating a difference between the quorum-sensing systems in these two strains. Understanding the regulatory variation in these two strains has the potential to provide key insights into the control of pathogenesis in this organism. Initially, the BB22OP genome sequencing results aligned into 125 contigs. The genome has now been assembled into two distinct chromosomes with only two gaps remaining to be filled. These gaps are located in the integron region, which is difficult to assemble due to its structure. The integron is a series of gene cassettes separated by inverted repeats that facilitate recombination events that build the integron. The integron region is further evidence of genetic differences between the two strains. The integron in the RIMD2210633 strain is comprised of 69 gene cassettes, while the BB22OP integron contains at least 86 gene cassettes. There are 313 genes novel to the BB22OP genome, which could result in the phenotypic differences seen in these two strains. Additionally five of the 313 genes are predicted to be transcriptional regulators indicating the potential for differential gene regulation. Further comparative analysis will likely reveal more phenotypic divergence between the physiology of RIMD2210633 and BB22OP. Additionally, the CsrA regulatory network was explored in RIMD2210633. CsrA was first characterized in E. coli as a global regulator of carbon storage and metabolism. RIMD2210633 contains a CsrA homolog and was predicted to contain four CsrA-regulating sRNAs (CsrB1-3 and CsrC), and this work confirmed that these sRNAs regulate CsrA in the same manner as in E. coli. CsrA and the same CsrA-regulating sRNAs were found in the BB22OP genome as well. Since CsrA is known to regulate glycogen production, a qualitative iodine-staining plate assay and a quantitative glycogen assay were used to indirectly measure CsrA activity in the presence and absence of individual regulatory sRNAs. The RIMD2210633 CsrA, CsrB1, CsrB2, CsrB3 and CsrC were shown to have the predicted physiological role in recombinant E. coli, with higher glycogen levels observed when CsrA was active and lower levels when each of the sRNAs was overexpressed. CsrA is also known to regulate biofilm production and virulence factors. In an attempt to develop a screening method for potential CsrA targets, a transcriptional/translational fusion system was developed. Transcriptional and translational fusions to β-galactosidase were created to PdksA, PglgC1 and PtoxR from RIMD2210633. CsrA or CsrB2 was overexpressed in recombinant E. coli containing each of the fusion constructs in order to see what happens to the gene expression from these promoters at low and high CsrA activity levels. Surprisingly, changing the activity levels of CsrA impacted both transcriptional and translational levels making the results of the assay difficult to interpret. Collectively these efforts have enhanced our understanding of V. parahaemolyticus. In particular, the sequencing of BB22OP has allowed for a comparative analysis between the BB22OP and RIMD2210633 strains. These strains have remarkably conserved genomes despite the phenotypic differences they exhibit. It appears there is variation in the quorum-sensing systems of these two strains. Further analysis will reveal how the quorum-sensing regulons differ and how this impacts the virulence of these two pathogenic V. parahaemolyticus strains. / Master of Science

Yes / Pantoea stewartii is known to be the causative agent of Stewart's wilt, which usually affects sweet corn (Zea mays) with the corn flea beetle as the transmission vector. In this work, we present the whole-genome sequence of Pantoea stewartii strain M009, isolated from a Malaysian tropical rainforest waterfall. / University of Malaya via High Impact Research Grants (UM C/625/1/HIR/MOHE/CHAN/01 no. A-000001- 50001 and UM C/625/1/HIR/MOHE/CHAN/14/1 no. H-50001-A000027)

Compared to microarray-based genotyping, next-generation whole genome-sequencing (WGS) studies have the strength to provide greater information for the identification of rare variants, which likely account for a significant portion of missing heritability of common human diseases. In WGS, family-based studies are important because they are likely enriched for rare disease variants that segregate with the disease in relatives. We propose a multilevel model to detect disease variants using family-based WGS data with longitudinal measures. This model incorporates the correlation structure from family pedigrees and that from repeated measures. The iterative generalized least squares (IGLS) algorithm was applied to estimation of parameters and test of associations. The model was applied to the data of Genetic Analysis Workshop 18 and compared with existing linear mixed effect (LME) models. The multilevel model shows higher power at practical p-value levels and a better type I error control than LME model. Both multilevel and LME models, which utilize the longitudinal repeated information, have higher power than the method that only utilize data collected at one time point.