L'acide désoxyribonucléique (ADN) et l'acide ribonucléique (ARN) sont des polymères de nucléotides essentiels à la cellule. À l'inverse de l'ADN qui sert principalement à stocker l'information génétique, les ARN sont impliqués dans plusieurs processus métaboliques. Par exemple, ils transmettent l’information génétique codée dans l’ADN. Ils sont essentiels pour la maturation des autres ARN, la régulation de l’expression génétique, la prévention de la dégradation des chromosomes et le ciblage des protéines dans la cellule. La polyvalence fonctionnelle de l'ARN résulte de sa plus grande diversité structurale. Notre laboratoire a développé MC-Fold, un algorithme pour prédire la structure des ARN qu'on représente avec des graphes d'interactions inter-nucléotidiques. Les sommets de ces graphes représentent les nucléotides et les arêtes leurs interactions. Notre laboratoire a aussi observé qu'un petit ensemble de cycles d'interactions à lui seul définit la structure de n'importe quel motif d'ARN. La formation de ces cycles dépend de la séquence de nucléotides et MC-Fold détermine les cycles les plus probables étant donnée cette séquence. Mon projet de maîtrise a été, dans un premier temps, de définir une base de données des motifs structuraux et fonctionnels d'ARN, bdMotifs, en terme de ces cycles. Par la suite, j’ai implanté un algorithme, MC-Motifs, qui recherche ces motifs dans des graphes d'interactions et, entre autres, ceux générés par MC-Fold. Finalement, j’ai validé mon algorithme sur des ARN dont la structure est connue, tels que les ARN ribosomaux (ARNr) 5S, 16S et 23S, et l'ARN utilisé pour prédire la structure des riborégulateurs. Le mémoire est divisé en cinq chapitres. Le premier chapitre présente la structure chimique, les fonctions cellulaires de l'ARN et le repliement structural du polymère. Dans le deuxième chapitre, je décris la base de données bdMotifs. Dans le troisième chapitre, l’algorithme de recherche MC-Motifs est introduit. Le quatrième chapitre présente les résultats de la validation et des prédictions. Finalement, le dernier chapitre porte sur la discussion des résultats suivis d’une conclusion sur le travail. / Deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) are polymers of nucleotides essential for the survival of the cell. Contrary to DNA, whose main role is to store genetic information, RNA is involved in multiple metabolic processes. For example, RNA is involved in the transfer of information from DNA to protein, the processing and modification of other RNAs, the regulation of gene expression, the end-maintenance of chromosomes, and the sorting of proteins within the cell. This functional versatility of RNA comes from its structural diversity. Our laboratory developed MC-Fold, an algorithm that predicts RNA structures by representing them with nucleotide interaction graphs. The nodes in these graphs represent the nucleotides, and the edges the interactions between them. Our laboratory also observed that a limited number of interaction cycles can define the structure of any RNA motif. The formation of these cycles is determined by the nucleotide sequence and MC-Fold determines the most likely cycles based on that sequence. In this Master Degree project, I first built a database of structural and functional RNA motifs, bdMotifs, based on their constituent cycles. Then, I implemented an algorithm, MC-Motifs, which detects motifs within interaction graphs generated either by MC-Fold or by any other method. Finally, I validated my algorithm on known RNA structures such as the 5S, 16S and 23S ribosomal RNA (rRNA) and predicted structure of riboswitches. The Master thesis is divided into five chapters. The first chapter presents the chemical structure of RNA, its cellular functions and the structural folding of the polymer. In the second chapter, the database bdMotifs is described. In the third chapter, the MC-Motifs algorithm is introduced. In the fourth chapter, I present the results of MC-Motifs. Finally, in the last chapter, I discuss theses results and I give a conclusion on the project.

Both microRNAs (miRNAs) and RNA-binding proteins (RBPs) regulate post- transcriptional events, but the post-transcriptional contribution to the global mammalian transcriptomes is still not well understood. In this study we study the synergistic interaction between microRNAs that inhibit gene production, and a special RBP, HuR, that positively regulates mRNA stability. We examined their relationship in terms of spatial, conservational and expressional perspective. We show comprehensive mapping of HuR binding sites by combination of its structural and sequential preferences; and cross-platform normalization method within a process of refining miRNA and HuR binding site mapping. Finally, we observed co-evolution of miRNA and HuR binding sites by looking at their proximity and conservation levels. Collectively, our data suggest that mammalian microRNAs and HuR, with seemingly opposing regulatory effects, cooperatively regulate their mutual targets.

The effects of a mutation in one gene can occasionally be suppressed by mutation in another gene. Genetic suppression indicates functional relationships and provides clues about the mechanism and order of action in genetic pathways. Here I explored the existing yeast deletion collection to identify suppressor relationships. The collection was released in 2000 and it is known that some strains in the collection have acquired mutations. Whole genome sequencing of 48 yeast deletion strains corresponding to 26 genome integrity genes was performed. High-throughput sequencing revealed a broad mutational spectrum including point mutations, indels, and copy number variations. I identified and experimentally validated two new suppressor mutations (sgs1 mutations in both top3Δ and rmi1Δ strains) corresponding to gene pairs with previously known suppressor relationships. Thus, high-throughput sequencing and analysis of yeast deletion strains can identify suppressor mutations. The resulting genome sequences also provide a baseline for future laboratory evolution experiments.

Both microRNAs (miRNAs) and RNA-binding proteins (RBPs) regulate post- transcriptional events, but the post-transcriptional contribution to the global mammalian transcriptomes is still not well understood. In this study we study the synergistic interaction between microRNAs that inhibit gene production, and a special RBP, HuR, that positively regulates mRNA stability. We examined their relationship in terms of spatial, conservational and expressional perspective. We show comprehensive mapping of HuR binding sites by combination of its structural and sequential preferences; and cross-platform normalization method within a process of refining miRNA and HuR binding site mapping. Finally, we observed co-evolution of miRNA and HuR binding sites by looking at their proximity and conservation levels. Collectively, our data suggest that mammalian microRNAs and HuR, with seemingly opposing regulatory effects, cooperatively regulate their mutual targets.

As drought can impinge significantly on forest health and productivity, the mechanisms by which forest trees respond to drought is of interest. The research presented herein examined the intra-specific variation in the Populus balsamifera drought response, examining the potential role of the transcriptome to configure growth, metabolism and development in response to water deficit. Amassing evidence indicates that different species of Populus have divergent mechanisms and Three lines of inquiry were pursued to investigate the intraspecific variation the drought response in P. balsamifera. First, the transcriptome responses of six genotypes of P. balsamifera were examined using Affymetrix Poplar GeneChips under well-watered and water-deficit conditions. A core species-level transcriptome response was identified. Significantly, intraspecific variation in the drought transcriptome was also identified. The data support a role for genotype-derived variation in the magnitude of P. balsamifera transcriptome remodelling playing a role in conditioning drought responsiveness. Second, the impact of drought-stress induced declines in stomatal conductance, as well as an alteration in stomatal development in two genotypes was examined. Patterns of transcript abundance of genes hypothesised to underpin stomatal development had patterns congruent with their role in modulation of stomatal development. These results suggest that stomatal development may play a role as a long-term mechanism to limit water loss from P. balsamifera leaves under conditions of drought-stress. Finally, the drought-induced metabolome of six P. balsmaifera genotypes was interrogated. Metabolite profiling reveled amino acids such as isoleucine and proline and sugars such as galactinol and raffinose were found with increased abundance, whereas TCA intermediates succinic and malic acid were found with decreased abundance in response to drought. Comparative analysis of the metabolome and the transcriptome revealed genotypic-specific variation in energy and carbohydrate metabolism. Taken together, the findings reported in this thesis form a foundation to understand the basis of intraspecific variation in the drought response in P. balsamifera. Transcripts and metabolites that contribute to within-species differences in drought tolerance were defined. These molecular components are useful targets for both future study, as well as efforts aimed at protecting and growing trees of this important species under challenging environmental conditions.

To improve fungal identification using a single DNA sequence, I introduce the Barcode Similarity Group (BSG) defined as a cluster of sequences that share greater than or equal to a threshold amount of genetic similarity with each other. As a test case, I created 393 BSGs from 2463 Cortinarius ITS sequences using a 94% similarity cut-off value in DOTUR. Some BSGs may contain multiple species. The BSG database was used to label environmental sequences, find misidentified or mislabeled sequences, and find potential cryptic species and novel species. Expert taxonomists will be needed to perform detailed morphological and phylogenetic studies to identify the individual species within each BSG. The main advantage of using BSGs is that it clusters together sequences using total genetic relatedness and does not rely on any taxonomy for identification. A website was created where the RDP Classifier is used to classify a query sequence into a BSG.

Antibiotic resistance is a worsening threat to human health. Increasing our understanding of the mechanisms causing this resistance will be of great benefit in designing methods to evade resistance and in developing new classes of antibiotics. In this thesis, I have used the TetR Family Transcriptional Regulators (TFRs), which constitute one of the largest antibiotic resistance regulator families, as a model system to study the structure, function and evolution of antibiotic resistance determinants. I performed a thorough examination of the variation and conservation seen in TFR sequences and structures using computational approaches. Through structure comparison, I have identified the most conserved features shared by the TFR family that are crucial for their stability and function. Based on my findings on conserved TFR structural features, a quantitative assay of binding affinity determination was developed. Through sequence comparison and a residue contact map method, I discovered the existence of a conserved residue network that correlates well with the known allostery pathway of TetR. This predicted allosteric communication network was experimentally tested in TtgR. I have also developed methods to identify TFR operator sequences through genomic comparisons and validated my prediction through experiments. In addition, I have developed an in vivo system that can be used to identify and characterize proteins that mediate resistance to almost any antibiotic. This system is simple, fast, and scalable for high-throughput applications, and could be used to discover a wide range of novel antibiotic resistance mechanisms. The principles that I applied to the TFR family could also be applied to other protein families.

The cellular prion protein (PrPC) is unique amongst mammalian proteins in that it not only has the capacity to aggregate (in the form of scrapie PrP; PrPSc) and cause neuronal degeneration, but can also act as an independent vector for the transmission of disease from one individual to another of the same or, in some instances, other species. Since the discovery of PrPC nearly thirty years ago, two salient questions have remained largely unanswered, namely, (i) what is the normal function of the cellular protein in the central nervous system, and (ii) what is/are the factor(s) involved in the misfolding of PrPC into PrPSc? To shed light on aspects of these questions, we undertook a discovery-based interactome investigation of PrPC in mouse neuroblastoma cells (Chapter 2), and among the candidate interactors, identified two members of the ZIP family of zinc transporters (ZIP6 and ZIP10) as possessing a PrP-like domain. Detailed analyses revealed that the LIV-1 subfamily of ZIP transporters (to which ZIPs 6 and 10 belong) are in fact the evolutionary ancestors of prions (Chapter 3). We were further able to demonstrate that PrPC likely emerged from a ZIP ancestor molecule nearly half-a-billion years ago via a retrotransposition event (Chapter 4). Moreover, biochemical investigations on ZIP10, as a model LIV-1 ZIP transporter, demonstrated that the ectodomain shedding of ZIP10 observed in prion-infected mice resembles a cellular response to transition metal starvation and suggested that prion disease in mice might phenocopy a transition metal starvation status (Chapter 5). These studies have opened a new angle to study prion biology in health and disease. Biochemical investigations on other LIV-1 ZIPs and attempts at the structural elucidation of the PrP-like domain of LIV-1 ZIP proteins are ongoing and have not been included in this thesis.

As drought can impinge significantly on forest health and productivity, the mechanisms by which forest trees respond to drought is of interest. The research presented herein examined the intra-specific variation in the Populus balsamifera drought response, examining the potential role of the transcriptome to configure growth, metabolism and development in response to water deficit. Amassing evidence indicates that different species of Populus have divergent mechanisms and Three lines of inquiry were pursued to investigate the intraspecific variation the drought response in P. balsamifera. First, the transcriptome responses of six genotypes of P. balsamifera were examined using Affymetrix Poplar GeneChips under well-watered and water-deficit conditions. A core species-level transcriptome response was identified. Significantly, intraspecific variation in the drought transcriptome was also identified. The data support a role for genotype-derived variation in the magnitude of P. balsamifera transcriptome remodelling playing a role in conditioning drought responsiveness. Second, the impact of drought-stress induced declines in stomatal conductance, as well as an alteration in stomatal development in two genotypes was examined. Patterns of transcript abundance of genes hypothesised to underpin stomatal development had patterns congruent with their role in modulation of stomatal development. These results suggest that stomatal development may play a role as a long-term mechanism to limit water loss from P. balsamifera leaves under conditions of drought-stress. Finally, the drought-induced metabolome of six P. balsmaifera genotypes was interrogated. Metabolite profiling reveled amino acids such as isoleucine and proline and sugars such as galactinol and raffinose were found with increased abundance, whereas TCA intermediates succinic and malic acid were found with decreased abundance in response to drought. Comparative analysis of the metabolome and the transcriptome revealed genotypic-specific variation in energy and carbohydrate metabolism. Taken together, the findings reported in this thesis form a foundation to understand the basis of intraspecific variation in the drought response in P. balsamifera. Transcripts and metabolites that contribute to within-species differences in drought tolerance were defined. These molecular components are useful targets for both future study, as well as efforts aimed at protecting and growing trees of this important species under challenging environmental conditions.

To improve fungal identification using a single DNA sequence, I introduce the Barcode Similarity Group (BSG) defined as a cluster of sequences that share greater than or equal to a threshold amount of genetic similarity with each other. As a test case, I created 393 BSGs from 2463 Cortinarius ITS sequences using a 94% similarity cut-off value in DOTUR. Some BSGs may contain multiple species. The BSG database was used to label environmental sequences, find misidentified or mislabeled sequences, and find potential cryptic species and novel species. Expert taxonomists will be needed to perform detailed morphological and phylogenetic studies to identify the individual species within each BSG. The main advantage of using BSGs is that it clusters together sequences using total genetic relatedness and does not rely on any taxonomy for identification. A website was created where the RDP Classifier is used to classify a query sequence into a BSG.