Le paysage nucléotidique – la manière dont la composition nucléotidique varie le long du génome – est une caractéristique marquante de l'organisation des génomes et varie fortement entre espèces. Plusieurs hypothèses émergent des nombreux débats autour des mécanismes évolutifs à l'origine de ces hétérogénéités du taux de GC, parmi lesquelles la conversion génique biaisée vers G et C (BGC) et la sélection sur l'usage du code (SUC). La BGC est un processus neutre associé à la recombinaison qui favorise les allèles en G ou C au détriment des allèles en A ou T. La SUC est une force de sélection qui favorise les codons dits « préférés », ceux dont la traduction serait la plus efficace. Contrairement à ceux des vertébrés, les paysages nucléotidiques des plantes sont peu connus. La plupart des études ont été consacrées au génome d'Arabidopsis thaliana, pauvre en GC et homogène, et à celui du riz, riche en GC et hétérogène. Le contraste entre ces deux génomes a souvent été généralisé comme une dichotomie entre dicotylédones et monocotylédones, mais cette vision est clairement phylogénétiquement biaisée.Les objectifs de ce travail de thèse sont de caractériser les paysages nucléotidiques des angiospermes à une large échelle phylogénétique et de mieux comprendre quels sont les mécanismes évolutifs jouant sur l'évolution de ces paysages nucléotidiques. Comment varient les paysages nucléotidiques le long de la phylogénie des angiospermes ? SUC et BGC façonnent-elles ces paysages nucléotidiques ? Les différents taxons sont-ils affectés avec la même intensité ?Pour répondre à ces questions, j'ai utilisé une approche de génomique comparative basée sur l'analyse de données EST chez plus de 230 espèces d'angiospermes et de gymnospermes. L'exploration des paysages nucléotidiques de ce large éventail de plantes a montré que les patrons d'hétérogénéité des paysages nucléotidiques suivent un continuum le long de la phylogénie, avec des groupes particulièrement riches et hétérogènes en GC, les graminées par exemple. Mes résultats suggèrent que les paysages nucléotidiques des plantes pourraient avoir été façonnés par la BGC et, dans une moindre mesure, par la SUC. Des épisodes indépendants d'enrichissement et d'appauvrissement en GC ont vraisemblablement eu lieu au cours de l'évolution des plantes, et pourraient être expliqués par des variations d'intensité de ces mécanismes. En utilisant une prédiction du degré d'expression des EST, j'ai également mis en évidence une diversité dans les codons préférés entre espèces. Les préférences d'usage des codons se sont révélées plus labiles au cours de l'évolution pour les codons des acides aminés au code quatre et six fois dégénéré. J'ai pu lier l'évolution des préférences d'usage des codons à l'évolution de la composition nucléotidique des génomes. Mes résultats suggèrent que la composition en base des génomes, affectée en partie par la BGC, orienterait la coévolution entre préférence d'usage du code et ARNt. / The nucleotide landscape – the way base composition varies along a genome – is a striking feature of genome organization and is highly variable between species. The evolutionary causes of such heterogeneity in GC content have been much debated. Biased gene conversion towards G and C (BGC) and selection on codon usage (SCU) are thought to be main forces. BGC is a neutral process associated with recombination favouring G and C alleles over A and T ones. SCU is a selection process favouring the so-called “preferred” codons, i.e., those whose translation is the most efficient. Contrary to vertebrates, plant nucleotide landscapes are still poorly known. Most studies focused on the GC-poor and homogeneous Arabidopsis thaliana genome and on the GC-rich and heterogeneous rice genome. The contrast between these two genomes was often generalized as a dicot/monocot dichotomy but this vision is clearly phylogenetically biased.The objectives of this study are to characterize angiosperm nucleotide landscapes on a wide phylogenetic scale and to better understand the evolutionary mechanisms acting upon the evolution of nucleotide landscapes. To what extent do nucleotide landscapes vary across angiosperm phylogeny? Are nucleotide landscapes shaped by BGC and SCU? Are taxa affected with the same intensity?To tackle these issues, I used a comparative genomic approach relying on EST data analysis on over 230 angiosperm and gymnosperm species. Through the nucleotide landscape survey for such a wide range of species I found a continuum of GC-heterogeneity patterns across phylogeny, some taxa such as Poaceae being strikingly GC-rich and heterogeneous. My results suggest that nucleotide landscapes could have been shaped by BGC and, to a lesser extent, by SCU. GC-content enrichment and impoverishment are likely to have occurred several times independently during plant evolution and could be explained by intensity variations of BGC and SCU. Using a proxy for EST expression level, I also characterized the diversity of preferred codons between species. Codon usage preferences were shown to be evolutionarily more unstable for four- and six-fold degenerate codon families. Finally, I could link the evolution of codon usage preferences to the evolution of genome base composition. My results suggest that genome base composition, partially shaped by BGC, seems to drive the coevolution between codon usage preferences and tRNAs.

by Shuk-kei Lau. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 141-148). / Abstracts in English and Chinese. / Acknowledgement --- p.i / Table of Contents --- p.ii / Abstract --- p.vi / 論文摘要 --- p.viii / Abbreviations --- p.ix / List of Figures --- p.x / List of Tables --- p.xii / Chapter Chapter 1 --- Introduction / Chapter 1.1 --- General introduction --- p.1 / Chapter 1.2 --- HBV and its role in hepatocarcinogenesis --- p.3 / Chapter 1.2.1 --- Current situation of HBV infection and the HCC incidencein the world --- p.3 / Chapter 1.2.2 --- Current situation of HBV infection and the HCC incidencein Hong Kong --- p.4 / Chapter 1.2.3 --- Genetic organization of HBV --- p.4 / Chapter 1.2.4 --- Principle of hepatocarcinogenesis induced by HBV --- p.5 / Chapter 1.2.4.1 --- Role of chronic hepatitis in hepatocarcinogenesis --- p.5 / Chapter 1.2.4.2 --- Role of HBV in hepatocarcinogenesis --- p.6 / Chapter 1.2.5 --- Current screening tests for HCC --- p.7 / Chapter 1.2.6 --- Current therapies for HCC --- p.9 / Chapter 1.3 --- Aim of the present study --- p.13 / Chapter 1.4 --- "Combining Expressed Sequence Tag (EST), Suppression Subtractive Hybridization and cDNA microarray for rapid differentially by expressed genes screening" --- p.14 / Chapter 1.4.1 --- Expressed Sequence Tag (EST) --- p.14 / Chapter 1.4.2 --- cDNA subtraction --- p.15 / Chapter 1.4.3 --- cDNA microarray --- p.16 / Chapter Chapter 2 --- Materials and Methods / Chapter 2.1 --- PCR-select cDNA subtraction --- p.17 / Chapter 2.1.1 --- Amplification of subtracted cDNA clones by PCR --- p.17 / Chapter 2.1.2 --- Cycle sequencing of subtracted cDNA clones --- p.18 / Chapter 2.1.3 --- Sequence analysis using BLAST server and Stanford Online Universal Resource for Clones and ESTs (SOURCE) --- p.19 / Chapter 2.2 --- cDNA microarray analysis --- p.20 / Chapter 2.2.1 --- Array fabrication --- p.20 / Chapter 2.2.1.1 --- Amplification of cDNA clones by PCR --- p.20 / Chapter 2.2.1.2 --- Purification of PCR products --- p.21 / Chapter 2.2.1.3 --- Cycle sequencing for clones checking --- p.22 / Chapter 2.2.2 --- Microarray printing --- p.22 / Chapter 2.2.2.1 --- Preparation of cDNA target --- p.22 / Chapter 2.2.2.2 --- Arraying --- p.22 / Chapter 2.2.3 --- Screening of differentially expressed genes in hepatocellular carcinoma and its surrounding normal counterpart by cDNA microarray --- p.23 / Chapter 2.2.3.1 --- Extraction of RNA --- p.23 / Chapter 2.2.3.2 --- RNA labeling --- p.24 / Chapter 2.2.3.3 --- Microarray hybridization --- p.26 / Chapter 2.2.3.4 --- Collection of data --- p.27 / Chapter 2.2.3.5 --- Data normalization and analysis --- p.28 / Chapter 2.3 --- Molecular cloning and characterization of a novel cDNA clone differentially expressed in HCC --- p.30 / Chapter 2.3.1 --- Tissue distribution of T2L522 gene --- p.30 / Chapter 2.3.1.1 --- Northern hybridization --- p.30 / Chapter 2.3.1.2 --- Reverse-transcriptase polymerase chain reaction (RT-PCR) --- p.33 / Chapter 2.3.2 --- Expression level of T2L522 in HCC and its surrounding normal counterpart --- p.33 / Chapter 2.3.3 --- Identification of interacting partner of T2L522 using yeast two-hybrid assay --- p.35 / Chapter 2.3.3.1 --- "Cloning of T2L522 gene into the yeast two-hybrid DNA-BD vector, pGBKT7" --- p.35 / Chapter 2.3.3.2 --- Transformation of yeast competent cells --- p.39 / Chapter 2.3.3.3 --- Mating of T2L522-BD with pretransformed human liver cDNA library --- p.40 / Chapter 2.3.3.4 --- Colony lift p-galactosidase filter assay --- p.42 / Chapter 2.3.4 --- Subcellular localization of T2L522 gene by tagging with green fluorescence protein (GFP) --- p.43 / Chapter 2.3.4.1 --- "Cloning of T2L522 gene into the eukaryotic GFP expression vector, pEGFP-Cl" --- p.43 / Chapter 2.3.4.2 --- Transfection of pEGFP-T2L522 into HepG2 cell --- p.43 / Chapter Chapter 3 --- Results / Chapter 3.1 --- PCR-select cDNA subtraction --- p.45 / Chapter 3.1.1 --- The sequencing results of subtracted-HCC cDNA clones --- p.45 / Chapter 3.1.2 --- Categorization of ESTs sequenced from subtracted-HCC library --- p.45 / Chapter 3.2 --- Microarray analysis --- p.49 / Chapter 3.2.1 --- Array fabrication --- p.49 / Chapter 3.2.1.1 --- Amplification of cDNA microarray targets --- p.49 / Chapter 3.2.2 --- Microarray printing --- p.52 / Chapter 3.2.3 --- Microarray analysis of differentially expressed genesin hepatocellular carcinoma and its surrounding normal counterpart --- p.55 / Chapter 3.2.4 --- Data collection --- p.57 / Chapter 3.2.5 --- Image processing: spots finding and quantitation --- p.61 / Chapter 3.2.6 --- Data normalization and analysis --- p.61 / Chapter 3.3 --- Molecular cloning and characterization of a novel cDNA clone differentially expressed in HCC --- p.73 / Chapter 3.3.1 --- Tissue distribution of T2L522 --- p.77 / Chapter 3.3.1.1 --- Northern hybridization --- p.77 / Chapter 3.3.1.2 --- Reverse-transcriptase polymerase chain reaction (RT-PCR) --- p.79 / Chapter 3.3.2 --- Expression level of T2L522 in hepatocellular carcinoma and its surrounding normal counterpart --- p.81 / Chapter 3.3.3 --- Identification of interacting partner of T2L522 using yeast two-hybrid assay --- p.85 / Chapter 3.3.4 --- Subcellular localization of GFP tagged T2L522 --- p.87 / Chapter Chapter 4 --- Discussion / Chapter 4.1 --- EST analysis on subtracted-HCC cDNA library --- p.89 / Chapter 4.2 --- cDNA microarray analysis --- p.92 / Chapter 4.2.1 --- Generation of reliable data using cDNA microarray --- p.92 / Chapter 4.2.1.1 --- Reproducibility of signal and normalized ratio --- p.92 / Chapter 4.2.2 --- Comparison of data between multiple slides --- p.96 / Chapter 4.2.2.1 --- Assession of data quality and statistical significance --- p.96 / Chapter 4.2.2.2 --- Interpretation of gene expression data from single and multiple hybridizarion --- p.97 / Chapter 4.3 --- Candidate genes differentially expressed in HCC and its surrounding normal counterpart --- p.99 / Chapter 4.3.1 --- Protein up-regulated in HCC --- p.99 / Chapter 4.3.1.1 --- Extracellular matrix protein --- p.99 / Chapter 4.3.1.2 --- Protein involved in other metabolism --- p.100 / Chapter 4.3.1.3 --- Protein involved in transcription and translation --- p.100 / Chapter 4.3.2 --- Protein down-regulated in HCC --- p.101 / Chapter 4.3.2.1 --- Membrane associated protein --- p.101 / Chapter 4.3.2.2 --- Protein involved in other metabolism --- p.102 / Chapter 4.3.2.2 --- Secretory protein --- p.104 / Chapter 4.3.3 --- Novel protein differentially expressed in HCC --- p.107 / Chapter 4.4 --- "TBC1 domain containing protein, T2L522" --- p.108 / Chapter 4.4.1 --- Possible involvement of T2L522 gene in HCC --- p.109 / Chapter 4.4.2 --- Tissue distribution and expression pattern of T2L522 --- p.110 / Chapter 4.4.3 --- Potential interacting partner of T2L522 --- p.110 / Chapter 4.4.4 --- Subcellular localization of T2L522 --- p.112 / Chapter 4.5 --- Summary --- p.113 / Appendix --- p.114 / References --- p.141

A Febre de Chikungunya é uma doença sistêmica causada por arbovírus e estima-se que afete cerca de 1 milhão de pessoas anualmente. Os principais sintomas associados com esta doença são febre e poliartralgia, podendo esta última assumir um caráter crônico em cerca de metade dos casos. Devido aos inúmeros surtos que ocorreram nos últimos 50 anos, diversos estudos tiveram como objetivo determinar os mecanismos de replicação do vírus e da resposta imune. Mesmo assim, pouco se sabe sobre quais moléculas possibilitam o processo de infecção. Já foi demonstrada a importância de interferons, principalmente de tipo I, citocinas e quimiocinas na diminuição da replicação viral. Além disso, há uma preferência do vírus por tipos celulares específicos como células endoteliais e epiteliais. Porém, estudos mostram informações contraditórias referentes ao papel de células mononucleares do sangue periférico (PBMC), principalmente com relação a monócitos e células B e T. Diante deste contexto, o tratamento utilizado atualmente é direcionado apenas ao alívio de sintomas uma vez que não existem drogas ou vacinas licenciadas específicas para esta doença. Logo, o objetivo deste trabalho é estudar as modificações transcricionais que ocorrem em amostras humanas durante o processo de infecção pelo vírus de Chikungunya de modo a esclarecer os mecanismos utilizados pelo sistema imune em resposta a infecção. Além disso, este estudo tem como finalidade apontar possíveis diferenças transcricionais entre amostras crônicas e não-crônicas. / The Chikungunya Fever is a systemic disease transmitted by arboviruses and is estimated to affect 1 million people annually. The main symptoms associated with this disease are fever and polyarthralgia, which can develop to chronic features in about half of the cases. Due to outbreaks that occurred in the last 50 years, many studies had the goal of determining the mechanisms of virus replication and immune response. Nevertheless, it is still poorly understood which molecules enable the ocurrence of the infection process. It has already been shown the importance of interferons, mainly type I, cytokines and chemokines in restricting the viral replication. In addition, the Chikungunya virus shows a preference for specific cell types such as endothelial and epithelial cells. However, studies display contradictory information regarding the role of peripheral blood mononuclear cells (PBMC), mainly in relation to monocytes and B and T cells. Given this context, the treatment currently used is directed only to alleviate the symptoms since there are no specific licensed drugs or vaccines for this disease. Therefore, the objective of this work was to study the transcriptional modifications that occur in humans during the process of Chikungunya virus infection in order to clarify the mechanisms used by the immune system. In addition, it aims to point out possible transcriptional differences between sample from the Chronic and Non-Chronic acute phase of the infection.

This study has successfully identified transcripts differentially expressed in the salivary gland and midgut and provides candidate genes that are critical to response to parasite invasion. Furthermore, an open-source Glossina resource (G-ESTMAP) was developed that provides interactive features and browsing of functional genomics data for researchers working in the field of Trypanosomiasis on the African continent.

Questions have been raised about the genomic complexity of the human genome, since it was reported that it only consisted of 32,000 genes. Alternative splicing is considered the explanation of the enormous difference between the number of genes and the number of proteins. Aligning expressed sequence tags (ESTs) to the genomic sequence has become a popular approach for gene prediction, revealing alternative splice variants. The aim in this thesis is to identify and analyse splice variants of the adhesion family of G protein-coupled receptors using EST data. 75% of the genes in the data set of 33 sequences were found to have a total of 51 splice variants. About half of the variants were considered functional.

This thesis provides an in-depth analyze of expressed sequence tags (EST) that represent pieces of eukaryotic mRNA by using unsupervised hidden Markov model (HMM). ESTs are short nucleotide sequences that are used primarily for rapid identificationof new genes with potential coding regions (CDS). ESTs are made by sequencing on double-stranded cDNA and the synthesizedESTs are stored in digital form, usually in FASTA format. Since sequencing is often randomized and that parts of mRNA contain non-coding regions, some ESTs will not represent CDS.It is desired to remove these unwanted ESTs if the purpose is to identifygenes associated with CDS. Application of stochastic HMM allow identification of region contents in a EST. Softwares like ESTScanuse HMM in which a training of the HMM is done by supervised learning with annotated data. However, because there are not always annotated data at hand this thesis focus on the ability to train an HMM with unsupervised learning on data containing ESTs, both with and without CDS. But the data used for training is not annotated, i.e. the regions that an EST consists of are unknown. In this thesis a new HMM is introduced where the parameters of the HMM are in focus so that they are reasonablyconsistent with biologically important regionsof an mRNA such as the Kozak sequence, poly(A)-signals and poly(A)-tails to guide the training and decoding correctly with ESTs to proper statesin the HMM. Transition probabilities in the HMMhas been adapted so that it represents the mean length and distribution of the different regions in mRNA. Testing of the HMM's specificity and sensitivityhave been performed via BLAST by blasting each EST and compare the BLAST results with the HMM prediction results.A regression analysis test shows that the length of ESTs used when training the HMM is significantly important, the longer the better. The final resultsshows that it is possible to train an HMM with unsupervised machine learning but to be comparable to supervised machine learning as ESTScan, further expansion of the HMM is necessary such as frame-shift correction of ESTs byimproving the HMM's ability to choose correctly positioned start codons or nucleotides. Usually the false positive results are because of incorrectly positioned start codons leadingto too short CDS lengths. Since no frame-shift correction is implemented, short predicted CDS lengths are not acceptable and is hence not counted as coding regionsduring prediction. However, when there is a lack of supervised models then unsupervised HMM is a potential replacement with stable performance and able to be adapted forany eukaryotic organism.

This study aimed to examine relative effect of perceived expressed emotion of schizophrenic patients and their caregivers&rsquo / expressed emotion on the symptom severity and quality of life at the framework of Vulnerability-Stress Model. Before the main study, for evaluating the psychometric properties of the Perceived Expressed Emotion Scale (PEES) a pilot study was conducted with the seventy five patients. Results of the pilot study provided support for the reliability and validity of PEES that had two factors, namely, criticism/hostility and emotional over-involvement. The main study was conducted at two stages. At time one assessment, one hundred and sixteen patients were administered PEES, Positive and Negative Symptom Scale for schizophrenia (PANSS), WHO&rsquo / s Quality of Life Scale (WHOQOL-BREF), and open ended questions to explore the views about their illness. Their caregivers were administered Expressed Emotion Scale (EES). After six month follow up, time two assessment was conducted 103 patients remained on the study using PANSS and WHOQOL-BREF. In order to test the main hypothesis of the study a series of repeated ANOVA analyses were conducted. The results revealed that patients&rsquo / perceived expressed emotion was a more robust component on quality of life and symptom severity than caregivers&rsquo / expressed emotion. It was found that patients&rsquo / perceived criticism/hostility was a toxic element on positive and negative symptoms, and total scores of PANSS, whereas patients&rsquo / perceived emotional over-involvement had a protector effect on social and environmental domain of standardized culture of WHOQOL-BREF. It was seen that symptom severity evaluated using PANSS improved from time one assessment to time two assessment. After discussing the findings in the framework of the literature, the limitations and the clinical implications of the results and directions for future studies were suggested.

<p>Questions have been raised about the genomic complexity of the human genome, since it was reported that it only consisted of 32,000 genes. Alternative splicing is considered the explanation of the enormous difference between the number of genes and the number of proteins. Aligning expressed sequence tags (ESTs) to the genomic sequence has become a popular approach for gene prediction, revealing alternative splice variants. The aim in this thesis is to identify and analyse splice variants of the adhesion family of G protein-coupled receptors using EST data. 75% of the genes in the data set of 33 sequences were found to have a total of 51 splice variants. About half of the variants were considered functional.</p>

Microarray technology permit us to study the expression levels of thousands of genes simultaneously. The technique has a wide range of applications including identification of genes that change their expression in cells due to disease or drug stimuli. The dissertation is addressing statistical methods for the selection of differentially expressed genes in two experimental conditions. We propose two different methods for the selection of differentially expressed genes. The first method is a classical approach, where we consider a common distribution for the summary measure of equally expressed genes. To estimate this common distribution, the Johnson system of distribution is used. The advantage of using Johnson system is that, there is no need of a parametric assumption for gene expression data. In contrast to other classical methods, in the proposed method, there is a sharing of information across the genes by the assumption of a common distribution for the summary measure of equally expressed genes. The second method is the gene selection using a mixture model approach and Baye's theorem. This approach also uses the Johnson System of distribution for the estimation of distribution of summary measure. Johnson system of distribution has the flexibility of covering a wide variety of distributional shapes. This system provides a unique distribution corresponding to each pair of mathematically possible values of skewness and kurtosis. The significant flexibility of Johnson system is very useful in characterizing the complicated data set like microarray data. In this dissertation we propose a novel algorithm for the estimation of the four parameters of the Johnson system.

This study has successfully identified transcripts differentially expressed in the salivary gland and midgut and provides candidate genes that are critical to response to parasite invasion. Furthermore, an open-source Glossina resource (G-ESTMAP) was developed that provides interactive features and browsing of functional genomics data for researchers working in the field of Trypanosomiasis on the African continent.