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

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.

<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>

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.

Philosophiae Doctor - PhD / 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. / South Africa

by Ng Tak Pan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 151-168). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgements --- p.iv / Abbreviations --- p.v / Table of Contents --- p.vi / List of Figures --- p.x / List of Tables --- p.xiii / Chapter Chapter One --- Literature Review / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Nutraceutical and Medicinal Properties of L. edodes --- p.4 / Chapter 1.2.1 --- Nutritional value --- p.4 / Chapter 1.2.2 --- Hypocholesterolaemic Effect --- p.5 / Chapter 1.2.3 --- Anti-tumor Effect --- p.5 / Chapter 1.2.4 --- Anti-viral Effect --- p.6 / Chapter 1.2.5 --- Immunopotentiating Effect --- p.6 / Chapter 1.3 --- Life cycle of L. edodes --- p.7 / Chapter 1.4 --- Environmental factors affecting mycelial growth and fruit body --- p.11 / Chapter 1.4.1 --- Nutrient requirement --- p.11 / Chapter 1.4.2 --- Physical and chemical factors --- p.12 / Chapter 1.5 --- Molecular studies on mushroom development --- p.15 / Chapter 1.5.1 --- Mating-type genes --- p.15 / Chapter 1.5.2 --- Hydrophobins --- p.19 / Chapter 1.5.3 --- Fruiting regulatory genes --- p.23 / Chapter 1.5.4 --- Molecular studies on fruit body development of I. edodes --- p.24 / Chapter 1.5.4.1 --- Identification of L. edodes genes --- p.24 / Chapter 1.5.4.2 --- Functional characterization of L. edodes genes --- p.27 / Chapter 1.5.4.3 --- Transformation in L. edodes --- p.28 / Chapter Chapter Two --- Expressed Sequence Tags (ESTs) of L. edodes / Chapter 2.1 --- Introduction --- p.30 / Chapter 2.2 --- Materials and Methods --- p.33 / Chapter 2.2.1 --- Generation of expressed sequence tag --- p.33 / Chapter 2.2.1.1 --- Mushroom cultivation and RNA extraction --- p.33 / Chapter 2.2.1.2 --- Construction of primordium cDNA library --- p.34 / Chapter 2.2.1.3 --- Mass excision of pBK-CMV plasmid --- p.34 / Chapter 2.2.1.4 --- Random screening of mass excised cDNA clone --- p.38 / Chapter 2.2.1.5 --- Isolation of recombinant plasmid --- p.38 / Chapter 2.2.1.6 --- Generation of 3´ة end partially sequence --- p.39 / Chapter 2.2.1.7 --- Sequence analysis --- p.40 / Chapter 2.2.2 --- Reverse dot-blot Hybridization --- p.40 / Chapter 2.2.2.1 --- PCR amplification of cDNA clone --- p.40 / Chapter 2.2.2.2 --- Membrane preparation --- p.40 / Chapter 2.2.2.3 --- cDNA probe preparation --- p.41 / Chapter 2.2.2.4 --- Hybridization --- p.42 / Chapter 2.2.2.5 --- Stringent washing and autoradiography --- p.43 / Chapter 2.3 --- Results --- p.44 / Chapter 2.3.1 --- Construction of primordium cDNA library --- p.44 / Chapter 2.3.2 --- Screening of recombinant clone --- p.44 / Chapter 2.3.3 --- Isolation and reconfirmation of recombinant plasmid --- p.46 / Chapter 2.3.4 --- Generation of EST --- p.47 / Chapter 2.3.5 --- EST identity --- p.47 / Chapter 2.3.6 --- Reverse dot-blot hybridization --- p.56 / Chapter 2.3.7 --- Analysis of hybridization signal --- p.60 / Chapter 2.4 --- Discussion --- p.71 / Chapter Chapter Three --- Sequence Analysis and Transcriptional Profiling of Genes Encoding GTP-binding Proteins / Chapter 3.1 --- Introduction --- p.78 / Chapter 3.2 --- Materials and Methods --- p.82 / Chapter 3.2.1 --- Sequence manipulation --- p.82 / Chapter 3.2.2 --- Northern blot hybridization --- p.82 / Chapter 3.2.2.1 --- RNA fragmentation by formaldehyde gel electrophoresis --- p.82 / Chapter 3.2.2.2 --- RNA fixation by capillary method --- p.83 / Chapter 3.2.2.3 --- Probe preparation --- p.84 / Chapter 3.2.2.4 --- Hybridization --- p.85 / Chapter 3.2.2.5 --- Stringent washing and autoradiography --- p.85 / Chapter 3.2.3 --- Real-Time SYBR Green RT-PCR --- p.85 / Chapter 3.2.3.1 --- Primer design --- p.85 / Chapter 3.2.3.2 --- RT-PCR reaction --- p.86 / Chapter 3.3 --- Results --- p.88 / Chapter 3.3.1 --- Sequence manipulation --- p.88 / Chapter 3.3.2 --- Transcriptional analysis --- p.103 / Chapter 3.4 --- Discussion --- p.108 / Chapter 3.4.1 --- Heterotrimeric G proteins --- p.108 / Chapter 3.4.2 --- Ras-related protein Rab7 --- p.112 / Chapter 3.4.3 --- Developmentally regulated GTP-binding protein --- p.113 / Chapter Chapter Four --- Yeast Complementation and Over-expression tests of Le.Gβ1 and Le.Gγ1 / Chapter 4.1 --- Introduction --- p.115 / Chapter 4.2 --- Materials and Methods --- p.120 / Chapter 4.2.1 --- "Yeast strains, media and yeast vectors" --- p.120 / Chapter 4.2.2 --- Primer design --- p.121 / Chapter 4.2.3 --- RT-PCR Amplification of Le.Gβ1 and Le.Gγ1 --- p.121 / Chapter 4.2.4 --- Purification of PCR products --- p.122 / Chapter 4.2.5 --- Enzymatic digestion and purification --- p.122 / Chapter 4.2.6 --- Ligation and E. coli transformation --- p.122 / Chapter 4.2.7 --- PCR screening of E. coli transformants --- p.124 / Chapter 4.2.8 --- Plasmids extraction --- p.124 / Chapter 4.2.9 --- Yeast transformation --- p.124 / Chapter 4.2.10 --- Mating test --- p.125 / Chapter 4.3 --- Results --- p.129 / Chapter 4.3.1 --- Cloning of Le.Gβ1 and Le.Gγ1 --- p.129 / Chapter 4.3.2 --- Yeast transformation --- p.129 / Chapter 4.3.3 --- Mating test --- p.130 / Chapter 4.4 --- Discussion --- p.141 / Chapter Chapter Five --- General Discussion --- p.144 / References --- p.151

The interactions between Medicago truncatula and Phytophthora medicaginis were examined using skl, a mutant blocked in ethylene perception, and a range of wild accessions of this plant species. P. medicaginis infection of M. truncatula plants resulted in compatible responses, whereas the mutant genotype was found to be hyper-susceptible to the pathogen. Phytophthora reproduction and colonization rates of Medicago tissues supported this conclusion. Infection of skl with different pathogens reinforced this observation. Ethylene production in infected A17 and skl roots showed reduced ethylene evolution in the mutant and suggested that a positive feedback loop, known as autocatalytic ethylene production, amplified the ethylene signal. To complement the study, expression analyses of defense response genes in this interaction were studied by real time RTPCR of Phytophthora-infected and mock-infected roots. The genes analyzed were PAL, CHS, IFR, ACC oxidase, GST, and PR10. The sequences needed for the analysis were found through the scrutiny of the M. truncatula EST database employing phylogenetics and bio-informatics tools. In A17 all the genes studied were up-regulated, although the specific gene expression patterns differed. The comparison of gene expression between A17 and skl genotypes allowed the differentiation between ethylene-dependent and ethylene-independent responses. Discrete results showed that ACC oxidase homologues were downregulated in the ethylene perception mutant, corroborating the ethylene observations. However, the expression of genes involved in the phenylpropanoid metabolism was increased in skl relative to A17, suggestive of an antagonism between the ethylene perception pathway and the regulation of the phenylpropanoid pathway. This result implied that Medicago phytoalexins accumulate in the disease interaction, but raised questions about their role in resistance to Phytophthora infection. This study establishes a link between mechanisms that regulate symbiotic infection and the regulation of disease resistance to Oomycete pathogens, especially P. medicaginis. The results served to identify a series of Phytophthora-induced genes, which remain pathogen-responsive even in the absence of a functional ethylene perception pathway. While it is possible that the products of these genes are involved in resistance to P. medicaginis, the present results demonstrate that ethylene perception is required for resistance.

This project focuses on the use of sponge genetic transcripts in the form of expressed sequence tags (ESTs) readily available in Genbank to search for novel genes using bioinformatics analysis tools. Marine sponge species are known to house a diversity of marine microbes and are known as the ‘living fossils’ of the animal kingdom because of the large number of ancient genes they house. Genomic mining can be a useful tool in discovering these orthologous genes. This study utilized the techniques of genomic mining of 11 previously described sponge species transcripts. The results of this study provide a better understanding of the genomic structure of the organisms studied by creating a more detailed genetic map and examining a specific environmental snapshot of the genes in each sponge. Novel methods for dissecting beneficial information from large scale data sets available in genomic libraries utilizing bioinformatics search tool MGRAST were examined. The results of this study indicate that sponges house numerous genes that are likely to be evolutionary predecessors of genes in higher eukaryotes. Support was also given to the notion that microbial communities play a role in metabolic pathways of sponges.