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Thesis Reference Thesis Bioinformatics tools to assist drug candidate discovery in venom gland transcriptomes KOUA, Dominique Kadio Abstract Current pharmaceutical research is actively exploring the field of natural peptides. Venomics addresses this issue with the study of toxins. The concomitant development of sequencing techniques is opening new perspectives of understanding biological mechanisms. Transcriptome sequencing of specific tissues is undertaken to better understand and characterize the context of gene expression. In this framework, transcriptomic data made available require automated processing workflows and user-friendly interfaces for data exploitation and comprehension. We present TATools, a bioinformatic platform that provides a unique management environment for understanding transcriptome data by merging results of diverse classical sequence analysis. Additional features and dedicated viewer pages makes TATools a valuable solution for highlighting novelty in a single transcriptome as well as cross-analysis of several transcriptomes in the same environment. TATools is validated in the context of venomics. This thesis reports the genesis of the design of TATools as exposed in two published articles and a manuscript (at this stage under [...] Reference KOUA, Dominique Kadio. Bioinformatics tools to assist drug candidate discovery in venom gland transcriptomes. Thèse de doctorat : Univ. Genève, 2012, no. Sc. 4471 URN : urn:nbn:ch:unige-239511 DOI : 10.13097/archive-ouverte/unige:23951 Available at: http://archive-ouverte.unige.ch/unige:23951 Disclaimer: layout of this document may differ from the published version. 1 / 1 UNIVERSITE DE GENEVE FACULTE DES SCIENCES Département d'informatique Professeur Ron D. Appel Institut Suisse de Bioinformatique Dr. Frédérique Lisacek LABORATOIRES ATHERIS Dr. Reto Stöcklin Bioinformatics tools to assist drug candidate discovery in venom gland transcriptomes. THESE présentée à la faculté des sciences de l'Université de Genève pour obtenir le grade de Docteur ès sciences, mention Bioinformatique par Dominique Kadio Koua de Bouaké (Côte d'Ivoire) Thèse N° 4471 Genève Centre d'impression UNIGE 1er octobre 2012 Thesis Bioinformatics tools to assist potential drug candidate discovery in venom gland transcriptomes. KOUA, Dominique Kadio Abstract Current pharmaceutical research is actively exploring the field of natural peptides. Venomics addresses this issue with the study of toxins. The concomitant development of sequencing techniques is opening new perspectives of understanding biological mechanisms. Transcriptome sequencing of specific tissues is undertaken to better understand and characterize the context of gene expression. In this framework, transcriptomic data made available require automated processing workflows and user-friendly interfaces for data exploitation and comprehension. We present TATools, a bioinformatic platform that provides a unique management environment for understanding transcriptome data by merging results of diverse classical sequence analysis. Additional features and dedicated viewer pages makes TATools a valuable solution for highlighting novelty in a single transcriptome as well as cross-analysis of several transcriptomes in the same environment. TATools is validated in the context of venomics. This thesis reports the genesis of the design of TATools as exposed in two published articles and a manuscript (at this stage under revision) and it describes the final outcome of this work with the support of a submitted manuscript detailing the analysis workflow. The use of TATools is illustrated with the study of the Conus consors venom gland transcriptome and subsequent conopeptide identification and classification. Other applications of parts of the TATools platform are shown in another two published articles. Reference KOUA, Dominique Kadio. Bioinformatics tools to assist drug candidate discovery in venom gland transcriptomes. Thèse de doctorat : Univ. Genève, 2012, no. Sc. Xxxx iii Remerciements Merci infiniment à, Professeur Ron D. Appel de l'Université de Genève, Président du jury Professeur Amos Bairoch de l'Université de Genève, expert interne, Professeur Oliver Hartley de l'Université de Genève, expert interne, Professeur Jordi Molgo du CNRS en France, expert externe, Docteure Frédérique Lisacek de l'Institut Suisse de Bioinformatique, Co-directrice, Docteur Reto Stöcklin des Laboratoires Atheris de Genève, Co-Directeur, les honorables membres du jury qui ont accepté de consacrer de leur temps à l’évaluation et à l'amélioration des travaux que j'ai présenté. Je voudrais remercier toutes les personnes qui par leur confiance, leur soutien et leur assistance ont permis la réalisation de ces travaux de thèse. Grand merci à Sylvie et Reto Stöcklin d'avoir bien voulu m'offrir l'opportunité de réaliser mes travaux de thèse au sein des Laboratoires Atheris. Merci à Frédérique Lisacek qui m'a accueilli dans le groupe PIG de l'Institut Suisse de Bioinformatique et qui a toujours eu confiance en moi. Merci à Reto et à tous les partenaires du projet CONCO pour les belles expériences de collaboration internationales auxquelles j'ai eu l'occasion de participer. Merci à mes co-directeurs de thèse d'avoir toujours été présents et disponibles pour l'encadrement de ces travaux. Grand merci pour l'amitié que vous ne cessez de me témoigner. Je voudrais également remercier Philippe Favreau (Philou) pour ses conseils et ses orientations ainsi que pour sa disponibilité sans faille. Je voudrais remercier tout mes collègues des Laboratoires Atheris. Cela a été un plaisir quotidien de travailler au sein d'une équipe tout aussi compétente que sympathique. Que Estelle B., Roman M., Coralie D., Aude V., Cecile C., Nicolas H., Frederic P., Francine A., Florence B., Xavier S., Daniel B., Vera O., Hadrien G., Alain C., Sebastien D., Florence A., et tous trouvent ici ma reconnaissance pour les excellents moments que nous avons partagés. Je remercie également mes parents, mes frères et sœurs pour leur affection et leur soutien indéfectible malgré la distance. Très chers André K., Joséphine B., Suzanne K. Jean-Baptiste A., iv Jacques A., Florence K., Eugène G., Innocent K., Vincent K., Denis K., j'ai essayé de puiser dans votre courage et votre optimisme la force de mener de l'avant les taches qui m'incombaient. Merci d'être toujours là. Ma reconnaissance va aussi à l'endroit des responsables de la Résidence Universitaire de Champel pour l'ambiance très conviviale et familiale et pour votre soutien toujours attentif. Merci en particulier à Joachim H., Manuel L., Alfred F., Lukas W., Philippe M., Hans F., Albert O., Albert M., Carlos S., Peter R., ainsi qu'à tous les résidents que j'ai eu énormément de plaisir à rencontrer. Grand merci à Véronique M., Jocelyne B., Dolnide D., Laure V. Sylvie S. et Gabrielle de B. pour leur inestimable aide dans les questions administratives. Merci à tous mes collègues du SIB pour leur amitié et l'exemple stimulant de leur qualité scientifique. Merci en particulier à Patricia P., Christian S. Béatrice C., Lorenzo C., Markus M., Fréderic N., Erik A. Je voudrais également adresser mes sincères remerciements à toutes les personnes de l'Institut Suisse de Bioinformatique et de l'Université de Genève pour leur disponibilité et leur assistance toujours cordiale. Merci a tous mes amis d'ici et d'ailleurs pour leur soutien. GRAND MERCI A VOUS TOUS. Deo Omnis Gloria ! v Présentation générale La recherche pharmaceutique moderne est essentiellement basée sur le criblage à haut débit de molécules candidates en vue de leur sélection comme comme principes actifs ciblant spécifiquement des récepteurs biologiques impliqués dans les pathologies à guérir. Il apparaît toutefois que depuis une quinzaine d'années, le nombre de molécules nouvelles proposées par l'industrie pharmaceutique est en constante regression. Il est dès lors fondamental d'envisager l'exploration de nouvelles sources de composés bioactifs. Dans ce contexte, les peptides naturels occupent une place de plus en plus importante dans les programmes de recherche. D'une manière particulière, les venins animaux, connus pour être des cocktails de composés hautement actifs et spécifiques ont été largement étudiés et ont déjà révélé une grande partie de leur richesse. Toutefois, avec l'émergence de nouvelles techniques de séquençage à haut débit, l'exploration de l'éventail complet des protéines en cours d'expression par la 'lecture' des ARN messagers (transcriptome) des glandes à venin est devenue possible et économiquement accessible. Cette nouvelle approche présente l'avantage de permettre une exploration plus détaillée des potentialités de l'appareil venimeux. Toutefois, l'amélioration des techniques de séquençage entraîne la production de transcriptomes de plus en plus volumineux composés de millions de 'reads'. L'analyse bioinformatique des transcriptomes afin d'identifier les peptides pouvant avoir un intérêt apparaît donc comme une étape cruciale de la recherche pharmaceutique basée sur l'exploration des transcriptomes. L'analyse des approches classiques d'analyse bioinformatique des transcriptomes a permis de mettre en lumière quelques problèmes pour lesquels la présente étude propose une solution. En effet, du fait du volume croissant de données transcriptomiques produites et de la variété d'outils d'analyse existant, l'exploitation pratique des transcriptomes s'avère encore très limitée. Quatre problèmes principaux ont été dégagés dans le présent travail: 1- La méthodologie d'analyse actuelle n'est pas optimale
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