<p>cDNA microarrays is one of the first high-throughput gene expression technologies that has emerged within molecular biology for the purpose of functional genomics. cDNA microarrays compare the gene expression levels between cell samples, for thousands of genes simultaneously. </p><p>The microarray technology offers new challenges when it comes to data analysis, since the thousands of genes are examined in parallel, but with very few replicates, yielding noisy estimation of gene effects and variances. Although careful image analyses and normalisation of the data is applied, traditional methods for inference like the Student <i>t</i> or Fisher’s <i>F</i>-statistic fail to work.</p><p>In this thesis, four papers on the topics of empirical Bayes and full Bayesian methods for two-channel microarray data (as e.g. cDNA) are presented. These contribute to proving that empirical Bayes methods are useful to overcome the specific data problems. The sample distributions of all the genes involved in a microarray experiment are summarized into prior distributions and improves the inference of each single gene.</p><p>The first part of the thesis includes biological and statistical background of cDNA microarrays, with an overview of the different steps of two-channel microarray analysis, including experimental design, image analysis, normalisation, cluster analysis, discrimination and hypothesis testing. The second part of the thesis consists of the four papers. Paper I presents the empirical Bayes statistic <i>B</i>, which corresponds to a <i>t</i>-statistic. Paper II is based on a version of <i>B</i> that is extended for linear model effects. Paper III assesses the performance of empirical Bayes models by comparisons with full Bayes methods. Paper IV provides extensions of <i>B</i> to what corresponds to <i>F</i>-statistics.</p>

Microarray-based comparative genomic hybridization (array-CGH) has emerged as a versatile platform with a wide range of applications in molecular genetics. This thesis focuses on the development of array-CGH with a specific aim to approach disease-related questions through improved strategies in array construction and enhanced resolution of analysis. In <b>paper I</b>, we applied an array covering 11 Mb of 22q, encompassing the NF2 locus, for deletion detection in sporadic schwannoma. Hemizygous deletions and tumor heterogeneity were identified. Array-CGH was established as a reliable platform for detection of DNA dosage alterations. <b>Paper II</b> described the construction of the NF2 gene-specific microarray for high-resolution scanning of deletions in the NF2 locus. We report a novel PCR-based non-redundant strategy for microarray fabrication, which considerably improved the sensitivity and reliability of deletion detection. <b>Paper III</b> reported the first tiling-path array comprehensively covering a human chromosome. The usefulness of the 22q-array was demonstrated by applying it to detect DNA dosage-alterations in 22q-associated disorders. In <b>paper IV</b>, we optimized array-CGH protocols for deletion detection in 22q11 deletion-syndrome. We showed that genomic and cDNA clones are not optimal for analysis of 22q11 locus and that PCR-based non-redundant strategy is reliable for deletion detection in such regions. In <b>paper V</b>, we utilized the 22q-array for understanding the genetic basis of schwannomatosis. Two commonly deleted regions were identified within the IGL and the GSTT1/CABIN1 loci. Further investigations using high-resolution arrays, bioinformatic analysis and mutational screening were performed. Missense mutations, specific to the schwannomatosis- and NF2 samples, were identified in the CABIN1 gene. <b>Paper VI</b> described the first array-CGH study for comprehensive and high-resolution profiling of deletions spanning the 17q11 locus. Both typical and atypical deletions were identified in NF1 samples. Bioinformatic analysis revealed novel segmental duplications, which can potentially mediate 17q11 deletions.

cDNA microarrays is one of the first high-throughput gene expression technologies that has emerged within molecular biology for the purpose of functional genomics. cDNA microarrays compare the gene expression levels between cell samples, for thousands of genes simultaneously. The microarray technology offers new challenges when it comes to data analysis, since the thousands of genes are examined in parallel, but with very few replicates, yielding noisy estimation of gene effects and variances. Although careful image analyses and normalisation of the data is applied, traditional methods for inference like the Student t or Fisher’s F-statistic fail to work. In this thesis, four papers on the topics of empirical Bayes and full Bayesian methods for two-channel microarray data (as e.g. cDNA) are presented. These contribute to proving that empirical Bayes methods are useful to overcome the specific data problems. The sample distributions of all the genes involved in a microarray experiment are summarized into prior distributions and improves the inference of each single gene. The first part of the thesis includes biological and statistical background of cDNA microarrays, with an overview of the different steps of two-channel microarray analysis, including experimental design, image analysis, normalisation, cluster analysis, discrimination and hypothesis testing. The second part of the thesis consists of the four papers. Paper I presents the empirical Bayes statistic B, which corresponds to a t-statistic. Paper II is based on a version of B that is extended for linear model effects. Paper III assesses the performance of empirical Bayes models by comparisons with full Bayes methods. Paper IV provides extensions of B to what corresponds to F-statistics.

Concerns about climate changes and scarcity of fossil fuels are rising. Hence wood is becoming an attractive source of renewable energy and raw material and these new dimensions have prompted increasing interest in wood formation in trees, in both the scientific community and wider public. In this thesis, the focus is on a key process in wood development: programmed cell death (PCD) in the development of xylem elements. Since secondary cell wall formation is dependent, inter alia, upon the life time of xylem elements, the qualitative features of wood will be affected by PCD in xylem, about which there is little information. This thesis focuses on the anatomical, morphological and transcriptional features of PCD during xylem development in both the stem of hybrid aspen, Populus tremula (L.) x tremuloides (Michx.) and the hypocotyl of the herbaceous model system Arabidopsis thaliana (L. Heynh.). In Populus, the progressive removal of organelles from the cytoplasm before the time of death (vacuolar bursts) and the slowness of the cell death process, illustrated by DNA fragmentation assays (such as TUNEL and Comet assays), have been ascertained in the xylem fibres by microscopic analyses. Furthermore, candidate genes for the regulation of fibre cell death were identified either from a Populus EST library obtained from woody tissues undergoing fibre cell death or from microarray experiments in Populus stem, and further assessed in an in silico comparative transcriptomic analysis of Arabidopsis thaliana. These candidate genes were either putative novel regulators of fibre cell death or members of previously described families of cell death-related genes, such as autophagy-related genes. The induction of the latter and the previous microscopic observations suggest the importance of autophagy in the degradation of the cytoplasmic contents specifically in the xylem fibres. Vacuolar bursts in the vessels were the only previously described triggers of PCD in the xylem, which induce the very rapid degradation of the nuclei and surrounding cytoplasmic contents, therefore unravelling a unique previously unrecorded type of PCD in the xylem fibres, principally involving autophagy. Arabidopsis is an attractive alternative model plant for exploring some aspects of wood formation, such as the characterisation of negative regulators of PCD. Therefore, the anatomy of Arabidopsis hypocotyls was also investigated and the ACAULIS5 (ACL5) gene, encoding an enzyme involved in polyamine biosynthesis, was identified as a key regulator of xylem specification, specifically in the vessel elements, though its negative effect on the cell death process. Taken together, PCD in xylem development seems to be a highly specific process, involving unique cell death morphology and molecular machinery. In addition, the technical challenges posed by the complexity of the woody tissues examined highlighted the need for specific methods for assessing PCD and related phenomena in wood. / Oron för klimatförändringar och brist på fossila bränslen har ökat påtagligt under de senaste åren. De enorma möjligheter som skogsråvaran erbjuder som alternativ källa för förnyelsebar energi och råmaterial har väckt ett stort intresse också för den biologiska processen bakom vedbildning i träd. Denna avhandling fokuserar på en viktig process i vedbildning: programmerad celldöd (PCD) i xylemet. Xylemcellernas livstid påverkar bildningen av sekundära cellväggar, vilket i sin tur påverkar vedens kvalitativa egenskaperna, så som veddensitet. Trots dess betydelse för viktiga egenskaper hos vedråvaran existerar fortfarande väldigt lite information om xylem PCD på cellulär eller molekylär nivå. I den här avhandlingen belyses de anatomiska, morfologiska och genetiska aspekterna av PCD i xylemutveckling i både stam av hybridasp, Populus tremula (L.) x tremuloides (Michx.) och hypokotyl av det örtartade modellsystemet Arabidopsis thaliana (L. Heynh.). Xylemet i både Populus och Arabidopsis består av två olika celltyper; de vattentransporterade kärlen och de stödjande fibrerna. Det är känt att celldöd i kärlen pågår mycket snabbt efter att den centrala vakuolen brister och de hydrolytiska enzymer släpps in i cytoplasman. I den här avhandlingen ligger fokus på fibrerna i Populus xylemet. Med hjälp av mikroskopianalyser av cellmorfologin (elektronmikroskopi) och DNA-fragmentering i cellkärnan (TUNEL- och Comet-analyser) kunde vi konstatera att till skillnad från kärlen så uppvisar fibrerna en långsam och progressiv nedbrytning av organellerna och cellkärnans DNA före vakuolbristning. Dessutom har kandidatgener för reglering av fibercelldöd identifierats antingen från ett Populus EST bibliotek från vedartade vävnader som genomgår fibercelldöd eller från mikroarray experiment i Populus stam. Dessa kandidatgener är antingen potentiella nya regulatorer av fibercelldöd eller medlemmar av tidigare beskrivna familjer av celldödsrelaterade gener. Bland de sistnämnda finns autofagi-relaterade gener, vilket stöder funktionen av autofagi i samband med autolys av cellinnehållet i xylemfibrerna. Dessa studier pekar därför på en typ av PCD som har inte tidigare beskrivits för xylemet. Arabidopsis är ett alternativt växtmodellsystem för studier av vissa aspekter av vedbildningen, såsom karakteriseringen av negativa regulatorer av PCD. Därför har också hypokotylanatomin analyserats, och ACAULIS5 (ACL5) genen, som kodar för ett enzym i biosyntesen av polyaminer, har visats vara en viktig regulator av xylemspecifikation genom dess negativa effekt på kärlens celldöd. Sammantaget visar denna avhandling att PCD i xylemutvecklingen verkar involvera unika morfologiska och molekylära mekanismer. Vi visar dessutom att komplexiteten hos de vedartade vävnaderna leder till ett behov av bättre anpassade verktyg för att djupare kunna bedöma PCD och liknande fenomen i veden. / Även med namnet Moreau-Courtois, Charleen L. samt Moreau, Charleen.

Recentment ha estat demostrada l’existència de cèl.lules progenitores en el greix que envolta el cor. Aquesta nova font cel!lular ha esdevingut una bona alternativa per a regenerar el miocardi infartat. Per aquest motiu, és possible que posant en contacte el teixit adipós cardíac en forma de biomembrana amb la zona infartada es pugui limitar l’extensió de l’infart de miocardi. Els objectius de la present tesi són: 1) Generar els perfils genètics de l’evolució de l’IM en el model porcí. 2) Determinar l’existència de cèl.lules mesenquimals al teixit adipós d’origen pericardíac i caracteritzar-les. 3) Avaluar l’efecte de la transposició d’un pedicle adipós pericardíac vascularitzat sobre: a. l’IAM en el model porcí per a valorar els possibles efectes beneficiosos sobre la mida de l’infart i la funció ventricular. b. l’ICM en el model porcí per a valorar els possibles efectes beneficiosos sobre la mida de l’infart i la funció ventricular.

This thesis consists of two parts. The first part focuses on high-dimensional classification problems in microarray experiments. The second part deals with forecasting problems with a large number of categories in predictors. Classification problems in microarray experiments refer to discriminating subjects with different biologic phenotypes or known tumor subtypes as well as to predicting the clinical outcomes or the prognostic stages of subjects. One important characteristic of microarray data is that the number of genes is much larger than the sample size. The penalized logistic regression method is known for simultaneous variable selection and classification. However, the performance of this method declines as the number of variables increases. With this concern, in the first study, we propose a new classification approach that employs the penalized logistic regression method iteratively with a controlled size of gene subsets to maintain variable selection consistency and classification accuracy. The second study is motivated by a modern microarray experiment that includes two layers of replicates. This new experimental setting causes most existing classification methods, including penalized logistic regression, not appropriate to be directly applied because the assumption of independent observations is violated. To solve this problem, we propose a new classification method by incorporating random effects into penalized logistic regression such that the heterogeneity among different experimental subjects and the correlations from repeated measurements can be taken into account. An efficient hybrid algorithm is introduced to tackle computational challenges in estimation and integration. Applications to a breast cancer study show that the proposed classification method obtains smaller models with higher prediction accuracy than the method based on the assumption of independent observations. The second part of this thesis develops a new forecasting approach for large-scale datasets associated with a large number of predictor categories and with predictor structures. The new approach, beyond conventional tree-based methods, incorporates a general linear model and hierarchical splits to make trees more comprehensive, efficient, and interpretable. Through an empirical study in the air cargo industry and a simulation study containing several different settings, the new approach produces higher forecasting accuracy and higher computational efficiency than existing tree-based methods.

L'alimentation en eau constitue le principal facteur limitant la croissance, voire la survie des<br />plantes. Les modèles climatiques prévoient pour les 50 à 100 années à venir une baisse des<br />précipitations et des températures estivales accrues dans la moitié sud de la France. La durée<br />de vie d'une forêt de pin maritime, de sa plantation jusqu'à la coupe d'exploitation est<br />justement de 50 ans. Il est donc important de savoir si ces organismes pourront faire face à ces<br />brusques changements climatiques ; en d'autres termes si les variétés améliorées plantées<br />aujourd'hui pourront maintenir le niveau actuel de productivité dans un milieu plus pauvre en<br />eau, et tolérer des épisodes de sécheresse intense. La capacité de ces organismes à faire face à<br />ces perturbations brutales dépendra à la fois de leur plasticité phénotypique et de leur diversité<br />génétique. Dans le cadre de cette thèse, nous avons étudié la plasticité moléculaire du système<br />racinaire de jeunes plants de pin maritime élevés en milieu hydroponique et soumis à un stress<br />osmotique par ajout de polyéthylène glycol. Un plan factoriel croisant deux écotypes (France<br />et Maroc) par cinq niveaux de stress a permis d'analyser les réponses du transcriptome et du<br />protéome à court et long terme. Nos investigations ont porté sur l'accumulation des transcrits<br />de 7000 gènes et de 1200 protéines. L'analyse statistique des données a permis d'identifier<br />des gènes dont la plasticité moléculaire est génétiquement contrôlée, révélant des stratégies de<br />réponse différentes de chaque écotype. La valeur adaptative de ces gènes pourra alors être<br />confirmée par l'interprétation des patrons de diversité nucléotidique de ces gènes candidats.

The past few decades have witnessed a revolution in recombinant DNA and nucleic acid sequencing technologies. Recently however, technologies capable of massively high-throughout, genome-wide data collection, combined with computational and statistical tools for data mining, integration and modeling have enabled the construction of predictive networks that capture cellular regulatory states, paving the way for ‘Systems biology’. Consequently, protein interactions can be captured in the context of a cellular interaction network and emergent ‘system’ properties arrived at, that may not have been possible by conventional biology. The ability to generate data from multiple, non-redundant experimental sources is one of the important facets to systems biology. Towards this end, we have established a novel platform called ‘spotted cell microarrays’ for conducting image-based genetic screens. We have subsequently used spotted cell microarrays for studying multidimensional phenotypes in yeast under different regulatory states. In particular, we studied the response to mating pheromone using a cell microarray comprised of the yeast non-essential deletion library and analyzed morphology changes to identify novel genes that were involved in mating. An important aspect of the mating response pathway is large-scale spatiotemporal changes to the proteome, an aspect of proteomics, still largely obscure. In our next study, we used an imaging screen and a computational approach to predict and validate the complement of proteins that polarize and change localization towards the mating projection tip. By adopting such hybrid approaches, we have been able to, not only study proteins involved in specific pathways, but also their behavior in a systemic context, leading to a broader comprehension of cell function. Lastly, we have performed a novel metabolic starvation-based screen using the GFP-tagged collection to study proteome dynamics in response to nutrient limitation and are currently in the process of rationalizing our observations through follow-up experiments. We believe this study to have implications in evolutionarily conserved cellular mechanisms such as protein turnover, quiescence and aging. Our technique has therefore been applied towards addressing several interesting aspects of yeast cellular physiology and behavior and is now being extended to mammalian cells. / text

Hyaluronic acid (HA) is one of the primary chemical building blocks of the extracellular matrix and thus is an attractive material for biomedical applications. FDA approved HA-based materials are available as dermal fillers, joint viscosupplements, vitreous substitutes, and abdominal adhesion barriers. The engineering of new HA-based materials and applications is an active area of research. Here we develop several new types of HA-based hydrogels with unique and useful properties. To address the challenge of delivering hydrophobic drugs from hydrophilic hydrogel matrices we have grafted HA hydrogels with [Beta]-cyclodextrin to create hydrogels capable of binding poorly water soluble drugs. To create HA hydrogels with unique anisotropic swelling behavior we have developed a dual-crosslinking technique in which a super-swelling chemically crosslinked hydrogel is patterned with low-swelling photocrosslinked domains. When this dual-crosslinked hydrogel is swelled it contorts into a new shape because of differential swelling among photopatterned regions. To address the challenge of creating hydrogel scaffolds with biomimetic branched porosity we have invented a "crystal templating" technique. This technique grows dendritic crystals throughout a biopolymer solution, crosslinks the biopolymer around the crystals, and washes the crystals away to yield a hydrogel with a dendritic macroporous network. Lastly, we invented a method for patterning a substrate with a microarray of hydrogel compartments. A microarray of living cells is obtained when cells are seeded on the hydrogel patterned substrate. This method addresses the need for an inexpensive, simple method for obtaining living cell microarrays that does not require clean room labs and lithographic expertise. Each of these new materials were based on hyaluronic acid hydrogels but the methods are generalizable to hydrogels of other polymers too. In conclusion, the novel methods in this dissertation are a significant contribution to the engineering of HA-based materials. / text

Η νόσος Αλτσχάιμερ καταλαμβάνει την πρωτοκαθεδρία στις μη αναστρέψιμες άνοιες με τους επιδημιολογικούς της δείκτες να αυξάνονται όσο μεγαλώνει το προσδόκιμο ζωής του ανθρώπου. Η χρήση φαρμάκων, με αρχική στόχευση άλλη πάθηση, στη νόσο Αλτσχάιμερ αποκαλείται φαρμακευτικός επαναπροσδιορισμός και προσφέρει σαφή πλεονεκτήματα στην ασφάλεια, την ταχύτητα και το κόστος ανάπτυξης μίας εν δυνάμει θεραπείας, ιδιαίτερα όταν η μέχρι σήμερα αντιμετώπιση της πάθησης περιορίζεται στην καθυστέρηση εξέλιξης της βλάβης και τις δευτερογενείς εκδηλώσεις. Στην παρούσα εργασία, εκμεταλλευτήκαμε εργαλεία φαρμακευτικής επαναστόχευσης που βασίζονται στις γονιδιακές υπογραφές πέντε μελετών μικροσυστοιχιών της νόσου Αλτσχάιμερ. Καίριο στάδιο στη συγκρότηση γονιδιακών υπογραφών είναι ο προσδιορισμός της διαφορικής έκφρασης των γονιδίων. Εφαρμόζοντας τρεις διαφορετικές τεχνικές (Limma, ChDir, mAP-KL) για το σκοπό αυτό και τοποθετώντας τα αποτέλεσματα σε τέσσερα ξεχωριστά εργαλεία φαρμακευτικής επαναστόχευσης (cMap, SPIEDw, sscMap, LINCS-L1000), αναδείξαμε φάρμακα που συστηματικά αντιστρατεύονται τη νόσο. Η περαιτέρω ανάλυση σε επίπεδο χημικής δομής, λειτουργικών μονοπατιών και δικτυακής θεώρησης προσδιόρισε το μηχανισμό δράσης των φαρμάκων και πρότεινε νέα βιοδραστικά μόρια ως δυνατικές θεραπευτικές επιλογές. / Alzheimer’s disease dominates dementias of irreversible cause with alarming epidemiologic characteristics due to rise of human life expectancy. The use of initially otherwise purposed drugs in Alzheimer is described as drug repositioning and offers clear advantages in terms of safety, speed and cost issues in the development of a potential therapy, particularly when current treatments are limitited to symptoms’ delay and secondary comorbidities. In this study, we exploited drug repurposing tools based on gene signatures from five microarray experiments of Alzheimer’s disease. A fundamental step in constructing gene signatures is to define differential gene expression. For this purpose, we used three different methods (Limma, ChDir, mAP-KL) which we analyzed with four distinct drug repurposing tools (cMap, SPIEDw, sscMap, LINCS-L1000) and found drugs that systematically reverse the disease signature. Further processing of the results with regard to chemical structure, pathway and network analysis revealed the mode of the drugs’ actions and highlighted them as potential therapeutic choices for Alzheimer’s disease.