Étude transcriptionnelle d'une souche pathogène aviaire de Escherichia coli (APEC) et son mutant Pst (phosphate specific transport)

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

IQRray, a new method for Affymetrix microarray quality control, and the homologous organ conservation score, a new benchmark method for quality control metrics.

MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Affymetrix Whole-Transcript Human Gene 1.0 ST array is highly concordant with standard 3' expression arrays.

The recently released Affymetrix Human Gene 1.0 ST array has two major differences compared with standard 3' based arrays: (i) it interrogates the entire mRNA transcript, and (ii) it uses DNA targets. To assess the impact of these differences on array performance, we performed a series of comparative hybridizations between the Human Gene 1.0 ST and the Affymetrix HG-U133 Plus 2.0 and the Illumina HumanRef-8 BeadChip arrays. Additionally, both RNA and DNA targets were hybridized on HG-U133 Plus 2.0 arrays. The results show that the overall reproducibility of the Gene 1.0 ST array is best. When looking only at the high intensity probes, the reproducibility of the Gene 1.0 ST array and the Illumina BeadChip array is equally good. Concordance of array results was assessed using different inter-platform mappings. Agreements are best between the two labeling protocols using HG-U133 Plus 2.0 array. The Gene 1.0 ST array is most concordant with the HG-U133 array hybridized with cDNA targets. This may reflect the impact of the target type. Overall, the high degree of correspondence provides strong evidence for the reliability of the Gene 1.0 ST array.

Profilage Moléculaire de la Scoliose Idiopathique de l’Adolescent

La scoliose idiopathique de l’adolescent (SIA) est la déformation la plus fréquente en orthopédie pédiatrique. C'est une maladie qui génère des déformations complexes du rachis, du thorax et du bassin affectant plus sévèrement et majoritairement les filles à la puberté. Malgré de nombreuses années de recherches approfondies dans le domaine de la SIA, la cause n'a toujours pas été résolue. OBJECTIFS : Il a été démontré qu’il existe une dysfonction de la signalisation de la mélatonine par les protéines G inhibitrices (Gi) dans les ostéoblastes isolés de patients atteints de SIA. Ceci a conduit à une stratification des patients en trois groupes fonctionnels. Le but de ce projet de maîtrise est d’établir les profils d’expression moléculaire correspondant à chacun des groupes fonctionnels. Les objectifs spécifiques sont d’identifier les gènes responsables de l’initiation de la SIA et du défaut différentiel observé dans la signalisation des récepteurs couplés aux protéines Gi. MÉTHODES : Des ARNs ont été préparés à partir d’ostéoblastes isolés de patients atteints de SIA sélectionnés pour chaque groupe fonctionnel et comparés aux ARNs obtenus d’ostéoblastes de sujets sains. En plus, des cellules sanguines (PBMCs) isolées d’une paire de jumelles monozygotes discordantes pour la scoliose ont été étudiées pour comparer leur profil d’expression génétique. Nous avons utilisé des biopuces à ADN contenant un ensemble de 54,000 sondes permettant l’analyse du niveau d’expression de plus de 47,000 transcrits représentant 30,000 gènes humains bien caractérisés (Affymetrix, GeneChip® Human gene 1.0 ST array). Les gènes retenus ont par la suite été validés par qPCR sur un plus grand nombre de patients afin de tester la spécificité des profils d’expression pour chaque groupe de patients à partir des cellules osseuses dérivées lors de la chirurgie. RÉSULTATS: Le profilage moléculaire proposé permettra d’établir les fondements moléculaires de la SIA selon le test fonctionnel développé par le Dr Moreau et son équipe et d’identifier de nouveaux gènes associés à la SIA. Ce projet a permis de mettre en évidence des gènes possiblement impliqués dans le défaut de signalisation associé aux protéines Gi communs aux trois groupes, ainsi que des gènes spécifiques à certains groupes, pouvant contribuer au développement de certaines co-morbidités et/ou au risque d’aggravation des déformations rachidiennes. L’étude préliminaire des jumelles monozygotes discordantes pour la scoliose a mis en évidence un nombre limité de gènes possiblement associés au défaut de signalisation observé chez la jumelle scoliotique, gènes dont l’expression pourrait être influencée par des modifications d’ordre épigénétique liées à l’environnement. CONCLUSION: Les données obtenues par des approches de transcriptomiques dans le cadre de ce projet soutiennent notre méthode de stratification fonctionnelle des patients SIA et ont conduit à l’identification de nouveaux gènes associés à la SIA. Ces résultats jettent un éclairage nouveau sur la SIA et contribuent à une meilleure compréhension des mécanismes et facteurs impliqués dans l’étiologie de la SIA. À cet égard, nos résultats permettront éventuellement d’identifier des cibles thérapeutiques potentielles et des traitements personnalisés compte tenu des profils moléculaires distincts observés pour chaque groupe de patients.

Identification et caractérisation de gènes impliqués dans la virulence de Salmonella typhi suite à une analyse globale par biopuces de l'infection de macrophages humains en culture

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Identification et caractérisation de gènes impliqués dans la virulence de Salmonella typhi suite à une analyse globale par biopuces de l'infection de macrophages humains en culture

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Lineage relationship of prostate cancer cell types based on gene expression

Background: Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells. Methods: Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology) and pattern 4 (aglandular) sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype) and LuCaP 49 (neuroendocrine/small cell carcinoma) grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts. Results: Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like) grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness. Conclusions: Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.

Gene expression relationship between prostate cancer cells of Gleason 3, 4 and normal epithelial cells as revealed by cell type-specific transcriptomes

Background: Prostate cancer cells in primary tumors have been typed CD10(-)/CD13(-)/CD24(hi)/CD26(+)/CD38(lo)/CD44(-)/CD104(-). This CD phenotype suggests a lineage relationship between cancer cells and luminal cells. The Gleason grade of tumors is a descriptive of tumor glandular differentiation. Higher Gleason scores are associated with treatment failure. Methods: CD26(+) cancer cells were isolated from Gleason 3+3 (G3) and Gleason 4+4 (G4) tumors by cell sorting, and their gene expression or transcriptome was determined by Affymetrix DNA array analysis. Dataset analysis was used to determine gene expression similarities and differences between G3 and G4 as well as to prostate cancer cell lines and histologically normal prostate luminal cells. Results: The G3 and G4 transcriptomes were compared to those of prostatic cell types of non-cancer, which included luminal, basal, stromal fibromuscular, and endothelial. A principal components analysis of the various transcriptome datasets indicated a closer relationship between luminal and G3 than luminal and G4. Dataset comparison also showed that the cancer transcriptomes differed substantially from those of prostate cancer cell lines. Conclusions: Genes differentially expressed in cancer are potential biomarkers for cancer detection, and those differentially expressed between G3 and G4 are potential biomarkers for disease stratification given that G4 cancer is associated with poor outcomes. Differentially expressed genes likely contribute to the prostate cancer phenotype and constitute the signatures of these particular cancer cell types.

Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine

Background: The rapid progress currently being made in genomic science has created interest in potential clinical applications; however, formal translational research has been limited thus far. Studies of population genetics have demonstrated substantial variation in allele frequencies and haplotype structure at loci of medical relevance and the genetic background of patient cohorts may often be complex. Methods and Findings: To describe the heterogeneity in an unselected clinical sample we used the Affymetrix 6.0 gene array chip to genotype self-identified European Americans (N = 326), African Americans (N = 324) and Hispanics (N = 327) from the medical practice of Mount Sinai Medical Center in Manhattan, NY. Additional data from US minority groups and Brazil were used for external comparison. Substantial variation in ancestral origin was observed for both African Americans and Hispanics; data from the latter group overlapped with both Mexican Americans and Brazilians in the external data sets. A pooled analysis of the African Americans and Hispanics from NY demonstrated a broad continuum of ancestral origin making classification by race/ethnicity uninformative. Selected loci harboring variants associated with medical traits and drug response confirmed substantial within-and between-group heterogeneity. Conclusion: As a consequence of these complementary levels of heterogeneity group labels offered no guidance at the individual level. These findings demonstrate the complexity involved in clinical translation of the results from genome-wide association studies and suggest that in the genomic era conventional racial/ethnic labels are of little value.

Sequential analysis of global gene expression profiles in immature and in vitro matured bovine oocytes: potential molecular markers of oocyte maturation

Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Genic expression of the uterine leiomyoma in reproductive-aged women after treatment with goserelin

Objective: To identify the genes presenting different expression in uterine leiomyomas after goserelin treatment. Design: Retrospective analyses of tissue obtained in a prospective clinical study. Setting: School of Medicine of the University of Sao Paulo. Patient(s): 30 nulliparous black women aged 20 to 45 years with symptoms of uterine leiomyoma, uterine volume over 300 mL, and surgical indications for myomectomy. Intervention(s): Fifteen patients were given a monthly dose of 3.6 mg of goserelin over 3 months before surgery (group A), and 15 patients underwent surgery without any previous treatment (group B). Five random samples from each group were analyzed using the microarray technique with the Affymetrix platform (GeneChip Rat Genome 230 2.0 Array). Main Outcome Measure(s): Quantification of transcript expression levels of uterine fibroids in patients treated or not treated with goserelin. Result(s): Of the total of 47,000 sequences that were analyzed, representing approximately 38,500 human genes already characterized, we found a differential expression of 174 genes. Of these, 70 were up-regulated (33 genes with known function) and 104 were down-regulated (65 genes with known function) in samples from group A (treated) when compared with group B (nontreated). Conclusion(s): The genic expression of uterine leiomyomas changes in women who have had goserelin treatment when compared with nontreated patients. (Fertil Steril (R) 2010; 94: 1072-7. (C) 2010 by American Society for Reproductive Medicine.)

Gene Expression Profiling and Association Studies Implicate the Neuregulin Signaling Pathway in Behçet's Disease Susceptibility

Behçet's disease (BD) is a complex disease with genetic and environmental risk factors implicated in its etiology; however, its pathophysiology is poorly understood. To decipher BD's genetic underpinnings, we combined gene expression profiling with pathway analysis and association studies. We compared the gene expression profiles in peripheral blood mononuclear cells (PBMCs) of 15 patients and 14 matched controls using Affymetrix microarrays and found that the neuregulin signaling pathway was over-represented among the differentially expressed genes. The Epiregulin (EREG), Amphiregulin (AREG), and Neuregulin-1 (NRG1) genes of this pathway stand out as they are also among the top differentially expressed genes. Twelve haplotype tagging SNPs at the EREG-AREG locus and 15 SNPs in NRG1 found associated in at least one published BD genome-wide association study were tested for association with BD in a dataset of 976 Iranian patients and 839 controls. We found a novel association with BD for the rs6845297 SNP located downstream of EREG, and replicated three associations at NRG1 (rs4489285, rs383632, and rs1462891). Multifactor dimensionality reduction analysis indicated the existence of epistatic interactions between EREG and NRG1 variants. EREG-AREG and NRG1, which are members of the epidermal growth factor (EGF) family, seem to modulate BD susceptibility through main effects and gene–gene interactions. These association findings support a role for the EGF/ErbB signaling pathway inBD pathogenesis that warrants further investigation and highlight the importance of combining genetic and genomic approaches to dissect the genetic architecture of complex diseases.

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.