VariScan Software

VariScan is a software package for the analysis of DNA sequence polymorphisms at the whole genome scale. Among other features, the software:(1) can conduct many population genetic analyses; (2) incorporates a multiresolution wavelet transform-based method that allows capturing relevant information from DNA polymorphism data; and (3) it facilitates the visualization of the results in the most commonly used genome browsers.

Annonaceae substitution rates: a codon model perspective

The Annonaceae includes cultivated species of economic interest and represents an important source of information for better understanding the evolution of tropical rainforests. In phylogenetic analyses of DNA sequence data that are used to address evolutionary questions, it is imperative to use appropriate statistical models. Annonaceae are cases in point: Two sister clades, the subfamilies Annonoideae and Malmeoideae, contain the majority of Annonaceae species diversity. The Annonoideae generally show a greater degree of sequence divergence compared to the Malmeoideae, resulting in stark differences in branch lengths in phylogenetic trees. Uncertainty in how to interpret and analyse these differences has led to inconsistent results when estimating the ages of clades in Annonaceae using molecular dating techniques. We ask whether these differences may be attributed to inappropriate modelling assumptions in the phylogenetic analyses. Specifically, we test for (clade-specific) differences in rates of non-synonymous and synonymous substitutions. A high ratio of nonsynonymous to synonymous substitutions may lead to similarity of DNA sequences due to convergence instead of common ancestry, and as a result confound phylogenetic analyses. We use a dataset of three chloroplast genes (rbcL, matK, ndhF) for 129 species representative of the family. We find that differences in branch lengths between major clades are not attributable to different rates of non-synonymous and synonymous substitutions. The differences in evolutionary rate between the major clades of Annonaceae pose a challenge for current molecular dating techniques that should be seen as a warning for the interpretation of such results in other organisms.

Gene filtering with optimal threshold selection

Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.

Divergence with gene flow and fine-scale phylogeographical structure in the wedge-billed woodcreeper, Glyphorynchus spirurus, a Neotropical rainforest bird.

Determining the relative roles of vicariance and selection in restricting gene flow between populations is of central importance to the evolutionary process of population divergence and speciation. Here we use molecular and morphological data to contrast the effect of isolation (by mountains and geographical distance) with that of ecological factors (altitudinal gradients) in promoting differentiation in the wedge-billed woodcreeper, Glyphorynchus spirurus, a tropical forest bird, in Ecuador. Tarsus length and beak size increased relative to body size with altitude on both sides of the Andes, and were correlated with the amount of moss on tree trunks, suggesting the role of selection in driving adaptive divergence. In contrast, molecular data revealed a considerable degree of admixture along these altitudinal gradients, suggesting that adaptive divergence in morphological traits has occurred in the presence of gene flow. As suggested by mitochondrial DNA sequence data, the Andes act as a barrier to gene flow between ancient subspecific lineages. Genome-wide amplified fragment length polymorphism markers reflected more recent patterns of gene flow and revealed fine-scale patterns of population differentiation that were not detectable with mitochondrial DNA, including the differentiation of isolated coastal populations west of the Andes. Our results support the predominant role of geographical isolation in driving genetic differentiation in G. spirurus, yet suggest the role of selection in driving parallel morphological divergence along ecological gradients.

High-Throughput Screening for Novel Prostate Cancer Drug Targets –Getting Personal

Prostate cancers form a heterogeneous group of diseases and there is a need for novel biomarkers, and for more efficient and targeted methods of treatment. In this thesis, the potential of microarray data, RNA interference (RNAi) and compound screens were utilized in order to identify novel biomarkers, drug targets and drugs for future personalized prostate cancer therapeutics. First, a bioinformatic mRNA expression analysis covering 9873 human tissue and cell samples, including 349 prostate cancer and 147 normal prostate samples, was used to distinguish in silico prevalidated putative prostate cancer biomarkers and drug targets. Second, RNAi based high-throughput (HT) functional profiling of 295 prostate and prostate cancer tissue specific genes was performed in cultured prostate cancer cells. Third, a HT compound screen approach using a library of 4910 drugs and drug-like molecules was exploited to identify potential drugs inhibiting prostate cancer cell growth. Nine candidate drug targets, with biomarker potential, and one cancer selective compound were validated in vitro and in vivo. In addition to androgen receptor (AR) signaling, endoplasmic reticulum (ER) function, arachidonic acid (AA) pathway, redox homeostasis and mitosis were identified as vital processes in prostate cancer cells. ERG oncogene positive cancer cells exhibited sensitivity to induction of oxidative and ER stress, whereas advanced and castrate-resistant prostate cancer (CRPC) could be potentially targeted through AR signaling and mitosis. In conclusion, this thesis illustrates the power of systems biological data analysis in the discovery of potential vulnerabilities present in prostate cancer cells, as well as novel options for personalized cancer management.

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Enhanced mucosal re-epithelialization induced by short chain fatty acids in experimental colitis

The short chain fatty acids (SCFA) are the best nutrients for the colonocytes. Glucose is poorly used as a fuel but may be transformed into SCFA by colonic bacteria. The aim of this study was to investigate the effect of SCFA or glucose on experimental colitis. Colitis was induced in 30 Wistar rats by colonic instillation of 4% acetic acid. Five days later they were randomized to receive twice a day colonic lavage containing saline (controls, N = 10), 10% hypertonic glucose (N = 10) or SCFA (N = 10) until day 8 when they were killed. At autopsy, the colon was removed and weighed and the mucosa was evaluated macro- and microscopically and stripped out for DNA assay. Data are reported as mean ± SD or median [range] as appropriate. All animals lost weight but there was no difference between groups. Colon weight was significantly lower in the SCFA group (3.8 ± 0.5 g) than in the control (5.3 ± 2.1 g) and glucose (5.2 ± 1.3 g) groups (P<0.05). Macroscopically, the severity of inflammation was less in SCFA (grade 2 [1-5]) than in control (grade 9 [4-10]) and glucose-treated (grade 9 [2-10]) animals (P<0.01). Microscopically, ulceration of the mucosa was more severe in the glucose and control groups than in the SCFA group. The DNA content of the mucosa of SCFA-treated animals (8.2 [5.0-20.2] mg/g of tissue) was higher than in glucose-treated (5.1 [4.2-8.5] mg/g of tissue; P<0.01) and control (6.2 [4.5-8.9] mg/g of tissue; P<0.05) animals. We conclude that SCFA may enhance mucosal re-epithelialization in experimental colitis, whereas hypertonic glucose is of no benefit.

The biological effects of high-pressure gas on the yeast transcriptome

The aim of the present study was to examine the feasibility of DNA microarray technology in an attempt to construct an evaluation system for determining gas toxicity using high-pressure conditions, as it is well known that pressure increases the concentration of a gas. As a first step, we used yeast (Saccharomyces cerevisiae) as the indicator organism and analyzed the mRNA expression profiles after exposure of yeast cells to nitrogen gas. Nitrogen gas was selected as a negative control since this gas has low toxicity. Yeast DNA microarray analysis revealed induction of genes whose products were localized to the membranes, and of genes that are involved in or contribute to energy production. Furthermore, we found that nitrogen gas significantly affected the transport system in the cells. Interestingly, nitrogen gas also resulted in induction of cold-shock responsive genes. These results suggest the possibility of applying yeast DNA microarray to gas bioassays up to 40 MPa. We therefore think that "bioassays" are ideal for use in environmental control and protection studies.

Cryptic species status of Anopheles (Diptera: Culicidae) mosquitoes in Canada using a multidisciplinary approach

Many species of Anopheles mosquitoes (Diptera: Culicidae) are now recognized as species complexes whose members are often indistinguishable morphologically but identifiable based on ecological, genetic, or behavioural data. Because the members of species complexes often differ in their vector potential, accurate identification of vector species is essential for successful mosquito control. To investigate the cryptic species status of Anopheles mosquitoes in Canada, specimens were collected from across the country and examined using morphological, molecular, and ecological data. Six of the seven traditionally recognised species from Canada were collected from locations in British Columbia, Quebec, Newfoundland and Labrador, and throughout Ontario, including Anopheles barberi, An. earlei, An. freeborni, An. punctipennis, An. quadrimaculatus s.l., and An. walkeri. Variation in polymorphic traits within An. earlei, An. punctipennis, and An. quadrimaculatus s.l. were quantified and egg morphology examined using scanning electron microscopy. Morphological identification of adult and larval specimens suggested that two described cryptic species, An. perplexens and An. smaragdinus, were present in Canada. DNA sequence data were analysed for evidence of cryptic species using three molecular markers: COl, ITS2, and ITS!. Intraspecific COl variation was very low in most species «1 %), except for An. punctipennis with 2% sequence divergence between those from British Columbia (BC) and Ontario (ON), and An. walkeri with 7% sequence divergence between populations from Manitoulin Island (NO) and Long Point Provincial Park (LP). Similar patterns were also seen using ITS2 and ITS 1. Therefore, molecular data revealed the presence of two putative cryptic species within two species examined (i.e., An. walkeri and An. punctipennis), corresponding to collection location (i.e., NO vs. LP and BC vs. ON, respectively). Surprisingly, there was no molecular support for the presence of either An. perplexens or An. smaragdinus in Canada despite the morphological assessments. Ecological data from all collection sites were recorded and are available in an online database designed to manage all collection and identification data. Current bionomic information, including regional abundance, larval habitat, and species associations, was determined for each species. This multidisciplinary study of Anopheles mosquitoes is the first detailed investigation of these potential disease vectors in Canada and demonstrates the importance of an integrated approach to anopheline systematics that includes molecular data.

Étude de la virulence et de la résistance aux antibiotiques des Staphylococcus aureus résistants à la méthicilline chez le porc à l'abattoir au Québec

Depuis quelques années et dans plusieurs pays, un nouveau type de Staphylococcus aureus résistant à la méthicilline (SARM), le séquence type (ST) 398, a été fréquemment retrouvé chez les porcs et chez les fermiers en contact avec ces porcs. Au Canada, très peu d’informations sont disponibles concernant le SARM d’origine porcine. Une première étude dans notre laboratoire a permis de récolter 107 isolats de SARM provenant de deux abattoirs porcins du Québec. Le présent travail vise à caractériser les gènes de virulence et de résistance aux antibiotiques de ces SARM, d’étudier leur formation de biofilm en relation avec la spécificité du groupe agr et de vérifier la localisation plasmidique et la transférabilité de ces gènes à des souches de SARM d’origine humaine. Plusieurs souches ont démontré différents patrons phénotypiques de résistance aux antibiotiques. Vingt-quatre souches représentatives de ces isolats ont été soumises à une caractérisation plus approfondie par une étude génotypique en utilisant une biopuce à ADN et un grand nombre de gènes de virulence a été détecté codant pour des entérotoxines staphylococcales, des leucocidines, des hémolysines, des auréolysines, des facteurs d’immunoévasion, des superantigènes, des facteurs d’adhésion et des facteurs impliqués dans la formation de biofilm. Des gènes de résistance envers les aminoglycosides, les macrolides, les lincosamides, les tétracyclines et les biocides ont été également détectés par biopuce et leur localisation plasmidique a par la suite été déterminée. La transférabilité de ces gènes de souches porcines à des souches de SARM d’origine humaine a été démontrée par conjugaison bactérienne; ainsi le transfert horizontal de certains gènes de résistance aux antibiotiques et de virulence a été observé. Ces travaux de recherche apportent une meilleure connaissance de la résistance aux antibiotiques et de la virulence des SARM d’origine porcine et de leur potentiel de contribution à l’émergence de certaines résistances et facteurs de virulence chez le SARM d’origine humaine.

Modélisation des bi-grappes et sélection des variables pour des données de grande dimension : application aux données d’expression génétique

Les simulations ont été implémentées avec le programme Java.

Mécanismes moléculaires de la réplication préférentielle du VIH-1 dans les cellules à polarisation Th1Th17 versus Th1 : rôle de PPARG dans la régulation négative de la réplication virale

Les cellules T CD4+ humaines sont hétérogènes du point de vue de la permissivité à l’infection par le virus de l’immunodéficience humaine de type 1 (VIH-1). Notre laboratoire a préalablement démontré que les cellules Th1 à phénotype CXCR3+CCR6- sont relativement résistantes à l’infection par le VIH-1 alors que les cellules Th1Th17 à phénotype CXCR3+CCR6+ y sont hautement permissives. La réplication du VIH dépend de plusieurs facteurs cellulaires de restriction ou de permissivité agissant à différentes étapes du cycle viral. Toutefois, malgré plusieurs avancées, la compréhension des voies de signalisation cellulaire impliquées dans la régulation de la réplication du VIH est encore limitée. L’objectif majeur de ce projet de maîtrise est de caractériser les mécanismes moléculaires de la permissivité et de la résistance au VIH respectivement dans les cellules Th1Th17 et Th1. Ce mémoire est divisé en quatre parties qui visent: (i) l’identification des voies canoniques et des fonctions biologiques différemment régulées dans les cellules Th1Th17 versus Th1 par l’analyse de leur transcriptome au niveau du génome entier; (ii) la validation de l’expression différentielle des gènes d’intérêt identifiés par biopuces au niveau des transcrits et des protéines; (iii) la caractérisation du rôle fonctionnel de certains de ces facteurs (i.e., PPARG, AhR) sur la réplication du VIH dans les cellules Th1Th17 versus Th1; et (iv) l’identification du niveau auquel ces facteurs interfèrent avec le cycle de réplication du VIH. Nos résultats d’analyse du transcriptome du génome entier par Gene Set Enrichment Analysis et Ingenuity Pathway Analysis indiquent que les cellules à profil Th1Th17 sont plus susceptibles à l’activation cellulaire et à l’apoptose, favorisent plus l’inflammation et expriment moins fortement les gènes liés à la dégradation protéosomale comparé aux cellules à profil Th1. Ces différences dans la régulation de diverses voies et fonctions biologiques permettent en partie d’expliquer la susceptibilité à l’infection par le VIH dans ces cellules. Nous avons ensuite confirmé l’expression différentielle de certains gènes d’intérêt dans les cellules Th1Th17 (CXCR6, PPARG, ARNTL, CTSH, PTPN13, MAP3K4) versus Th1 (SERPINB6, PTK2) au niveau de l’ARNm et des protéines. Finalement, nous avons démontré le rôle des facteurs de transcription PPARG et AhR dans la régulation de la réplication du VIH. L’activation de la voie PPARG par la rosiglitazone induit la diminution importante de la réplication du VIH dans les cellules T CD4+, alors que l’activation de la voie AhR par les ligands exogènes TCDD et FICZ augmente de façon significative la réplication virale. Nous proposons que la voie PPARG agit comme un régulateur négatif de la réplication du VIH dans ces cellules, en interférant avec la polarisation Th17 et probablement en inhibant l’activité transcriptionnelle du facteur NF-kB. Les rôles des formes nucléaires versus cytoplasmiques du récepteur Ahr semblent être diamétralement opposés, dans la mesure où l’interférence ARN contre AhR s’associe également à l’augmentation de la réplication virale. Il est ainsi possible que la forme cytoplasmique d’AhR, connue par son activité E3 ligase, participe à la dégradation protéosomale des particules virales. Le mécanisme par lequel le AhR nucléaire versus cytoplasmique interfère avec la réplication virale est en cours d’étude au laboratoire. Cette étude représente la première caractérisation de l’expression différentielle de gènes au niveau du génome entier de sous-populations T CD4+ permissives versus résistantes à l’infection par le VIH. Nos résultats identifient de nouvelles cibles moléculaires pour de nouvelles stratégies thérapeutiques visant à limiter la réplication du VIH dans les lymphocytes T CD4+ primaires.

Actinobacillus pleuropneumoniae induces SJPL cell cycle arrest in G2/M-phase and inhibits porcine reproductive and respiratory syndrome virus replication

Background: Porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important pathogens in the swine industry and causes important economic losses. No effective antiviral drugs against it are commercially available. We recently reported that the culture supernatant of Actinobacillus pleuropneumoniae, the porcine pleuropneumonia causative agent, has an antiviral activity in vitro against PRRSV in SJPL cells. Objectives of this study were (i) to identify the mechanism behind the antiviral activity displayed by A. pleuropneumoniae and (ii) to characterize the active molecules present in the bacterial culture supernatant. Methods: Antibody microarray analysis was used in order to point out cellular pathways modulated by the A. pleuropneumoniae supernatant. Subsequent, flow cytometry analysis and cell cycle inhibitors were used to confirm antibody microarray data and to link them to the antiviral activity of the A. pleuropneumoniae supernatant. Finally, A. pleuropneumoniae supernatant characterization was partially achieved using mass spectrometry. Results: Using antibody microarray, we observed modulations in G2/M-phase cell cycle regulation pathway when SJPL cells were treated with A. pleuropneumoniae culture supernatant. These modulations were confirmed by a cell cycle arrest at the G2/M-phase when cells were treated with the A. pleuropneumoniae culture supernatant. Furthermore, two G2/M-phase cell cycle inhibitors demonstrated the ability to inhibit PRRSV infection, indicating a potential key role for PRRSV infection. Finally, mass spectrometry lead to identify two molecules (m/z 515.2 and m/z 663.6) present only in the culture supernatant. Conclusions: We demonstrated for the first time that A. pleuropneumoniae is able to disrupt SJPL cell cycle resulting in inhibitory activity against PRRSV. Furthermore, two putative molecules were identified from the culture supernatant. This study highlighted the cell cycle importance for PRRSV and will allow the development of new prophylactic or therapeutic approaches against PRRSV.

MicroRNA–mRNA interaction network using TSK-type recurrent neural fuzzy network

MicroRNAs are short non-coding RNAs that can regulate gene expression during various crucial cell processes such as differentiation, proliferation and apoptosis. Changes in expression profiles of miRNA play an important role in the development of many cancers, including CRC. Therefore, the identification of cancer related miRNAs and their target genes are important for cancer biology research. In this paper, we applied TSK-type recurrent neural fuzzy network (TRNFN) to infer miRNA–mRNA association network from paired miRNA, mRNA expression profiles of CRC patients. We demonstrated that the method we proposed achieved good performance in recovering known experimentally verified miRNA–mRNA associations. Moreover, our approach proved successful in identifying 17 validated cancer miRNAs which are directly involved in the CRC related pathways. Targeting such miRNAs may help not only to prevent the recurrence of disease but also to control the growth of advanced metastatic tumors. Our regulatory modules provide valuable insights into the pathogenesis of cancer

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, and many others, offer tremendous promise for the personalized treatment of cancer. These technologies measure the amount of specific proteins, RNA, DNA or other molecular targets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumor specimens are heterogeneous; an individual specimen typically contains unknown amounts of multiple tissues types. Thus, the measured molecular concentrations result from an unknown mixture of tissue types, and must be normalized to account for the composition of the mixture. For example, a breast tumor biopsy may contain normal, dysplastic and cancerous epithelial cells, as well as stromal components (fatty and connective tissue) and blood and lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic and cancerous epithelial cells. The remaining tissue components serve to “contaminate” the signal of interest. The proportion of each of the tissue components changes as a function of patient characteristics (e.g., age), and varies spatially across the tumor region. Because each of the tissue components produces a different molecular signature, and the amount of each tissue type is specimen dependent, we must estimate the tissue composition of the specimen, and adjust the molecular signal for this composition. Using the idea of a chemical mass balance, we consider the total measured concentrations to be a weighted sum of the individual tissue signatures, where weights are determined by the relative amounts of the different tissue types. We develop a compositional source apportionment model to estimate the relative amounts of tissue components in a tumor specimen. We then use these estimates to infer the tissuespecific concentrations of key molecular targets for sub-typing individual tumors. We anticipate these specific measurements will greatly improve our ability to discriminate between different classes of tumors, and allow more precise matching of each patient to the appropriate treatment