Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

eVOC: a controlled vocabulary for unifying gene expression data.

Expression data contribute significantly to the biological value of the sequenced human genome, providing extensive information about gene structure and the pattern of gene expression. ESTs, together with SAGE libraries and microarray experiment information, provide a broad and rich view of the transcriptome. However, it is difficult to perform large-scale expression mining of the data generated by these diverse experimental approaches. Not only is the data stored in disparate locations, but there is frequent ambiguity in the meaning of terms used to describe the source of the material used in the experiment. Untangling semantic differences between the data provided by different resources is therefore largely reliant on the domain knowledge of a human expert. We present here eVOC, a system which associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. We have curated and annotated 7016 cDNA libraries represented in dbEST, as well as 104 SAGE libraries,with expression information,and provide this as an integrated, public resource that allows the linking of transcripts and libraries with expression terms. Both the vocabularies and the vocabulary-annotated libraries can be retrieved from http://www.sanbi.ac.za/evoc/. Several groups are involved in developing this resource with the aim of unifying transcript expression information.

The direct effects of tacrolimus and cyclosporin A on isolated human islets: A functional, survival and gene expression study.

The use of immunosuppressive drugs in transplanted patients is associated with the development of diabetes, possibly due to β-cell toxicity. To better understand the mechanisms leading to post-transplant diabetes, we investigated the actions of prolonged exposure of isolated human islets to therapeutical levels of tacrolimus (Tac) or cyclosporin A (CsA). Islets were isolated from the pancreas of multiorgan donors by enzymatic digestion and density gradient centrifugation. Functional, survival and molecular studies were then performed after 4 days of incubation with therapeutical concentrations of Tac or  CsA. Glucose-induced insulin secretion was significantly decreased in Tac, but not in CsA exposed islets, which was associated with a reduction of the amount of insulin granules as shown by electron microscopy. The percentage of apoptotic β-cells was higher in Tac than CsA exposed islets. Microarray experiments followed by Gene Set Enrichment Analysis revealed that gene expression was more markedly affected upon Tac treatment. In conclusion, Tac and CsA affect features of beta-cell differently, with several changes occurring at the molecular level.

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Modulation des réactions alloimmunitaires par les cytokines maîtresses IFN-γ et TGF-β

L’injection de cellules immunologiquement compétentes à un hôte histo-incompatible amène une réaction qui peut se traduire par la maladie du greffon-contre-l’hôte (GVHD). La GVHD demeure une barrière importante à une utilisation plus répandue de la greffe allogénique de cellules hématopoïétiques (AHCT), pourtant un traitement efficace pour traiter de nombreuses maladies. Une meilleure compréhension des mécanismes qui sous-tendent cette pathologie pourrait en faciliter le traitement et la prévention. L’Interféron-gamma (IFN-γ) et le Transforming Growth Factor-béta (TGF-β) sont deux cytokines maîtresses de l’immunité impliquées dans la fonction et l’homéostasie des cellules greffées. Nous démontrons chez la souris que l’IFN-γ limite la reconstitution lympho-hématopoïétique de façon dose-dépendante en mobilisant des mécanismes d’apoptose et en inhibant la prolifération cellulaire. Le TGF-β est quant à lui généralement connu comme un immunosuppresseur qui contrôle l’immunité en utilisant plusieurs voies de signalisation. Le rôle relatif de ces voies en AHCT est inconnu. Nous avons étudié une de ces voies en greffant des cellules provenant de donneurs déficients pour le gène SMAD3 (SMAD3-KO), un médiateur central de la voie canonique du TGF-β, à des souris histo-incompatibles. Bien que l’absence de SMAD3 ne cause aucune maladie chez nos souris donneuses, l’injection de cellules SMAD3-KO amène une GVHD du colon sévère chez le receveur. Cette atteinte est caractérisée par une différenciation Th1 et une infiltration massive de granulocytes témoignant d’un rôle central de SMAD3 dans la physiologie des lymphocytes T CD4 et des cellules myéloïdes. Nous avons focalisé ensuite nos efforts sur le rôle de SMAD3 chez les lymphocytes T CD4 en sachant que SMAD3 était actif chez les lymphocytes T CD4 tolérants. Nous avons découvert que SMAD3 était rapidement inactivé après une activation des cellules T, suggérant que l’inactivation de SMAD3 était fonctionnellement importante pour briser l’état de tolérance. Des études de micro-puces d’ADNc nous ont montré que SMAD3 contrôlait en effet l’expression de nombreux transcrits de gènes connus comme étant reliés à la tolérance et/ou à des processus biologiques dont les rôles dans le maintien de la tolérance sont plausibles.

Comparaison des méthodes d'analyse de l'expression différentielle basée sur la dépendance des niveaux d'expression

La technologie des microarrays demeure à ce jour un outil important pour la mesure de l'expression génique. Au-delà de la technologie elle-même, l'analyse des données provenant des microarrays constitue un problème statistique complexe, ce qui explique la myriade de méthodes proposées pour le pré-traitement et en particulier, l'analyse de l'expression différentielle. Toutefois, l'absence de données de calibration ou de méthodologie de comparaison appropriée a empêché l'émergence d'un consensus quant aux méthodes d'analyse optimales. En conséquence, la décision de l'analyste de choisir telle méthode plutôt qu'une autre se fera la plupart du temps de façon subjective, en se basant par exemple sur la facilité d'utilisation, l'accès au logiciel ou la popularité. Ce mémoire présente une approche nouvelle au problème de la comparaison des méthodes d'analyse de l'expression différentielle. Plus de 800 pipelines d'analyse sont appliqués à plus d'une centaine d'expériences sur deux plateformes Affymetrix différentes. La performance de chacun des pipelines est évaluée en calculant le niveau moyen de co-régulation par l'entremise de scores d'enrichissements pour différentes collections de signatures moléculaires. L'approche comparative proposée repose donc sur un ensemble varié de données biologiques pertinentes, ne confond pas la reproductibilité avec l'exactitude et peut facilement être appliquée à de nouvelles méthodes. Parmi les méthodes testées, la supériorité de la sommarisation FARMS et de la statistique de l'expression différentielle TREAT est sans équivoque. De plus, les résultats obtenus quant à la statistique d'expression différentielle corroborent les conclusions d'autres études récentes à propos de l'importance de prendre en compte la grandeur du changement en plus de sa significativité statistique.

Histone H2B-R95A mutant identifies the pheromone pathway that signals cell cycle arrest during rapamycin response

La rapamycine est un immunosuppresseur utilisé pour traiter plusieurs types de maladies dont le cancer du rein. Son fonctionnement par l’inhibition de la voie de Tor mène à des changements dans des processus physiologiques, incluant le cycle cellulaire. Chez Saccharomyces cerevisiae, la rapamycine conduit à une altération rapide et globale de l’expression génique, déclenchant un remodelage de la chromatine. Nous proposons que les modifications des histones peuvent jouer un rôle crucial dans le remodelage de la chromatine en réponse à la rapamycine. Notre objectif principal est d’identifier d’une banque de mutants d’histone les variantes qui vont échouer à répondre à la rapamycine dans une tentative de réaliser une caractérisation des modifications d’histone critiques pour la réponse à cette drogue. Ainsi, nous avons réalisé un criblage d’une banque de mutants d’histone et identifié plusieurs mutants d‘histone dont la résistance à la rapamycine a été altérée. Nous avons caractérisé une de ces variantes d’histone, à savoir H2B, qui porte une substitution de l’alanine en arginine en position 95 (H2B-R95A) et démontré que ce mutant est extrêmement résistant à la rapamycine, et non à d’autres drogues. Des immunoprécipitations ont démontré que H2B-R95A est défectueux pour former un complexe avec Spt16, un facteur essentiel pour la dissociation de H2A et H2B de la chromatine, permetant la réplication et la transcription par les ADN et ARN polymérases, respectivement. Des expériences de ChIP-Chip et de micropuce ont démontré que l’arginine 95 de H2B est requise pour recruter Spt16 afin de permettre l’expression d’une multitude de gènes, dont certains font partie de la voie des phéromones. Des évidences seront présentées pour la première fois démontrant que la rapamycine peut activer la voie des phéromones et qu’une défectuosité dans cette voie cause la résistante à cette drogue.

Transcriptomic analysis of rhizobium leguminosarum biovar viciae in symbiosis with host plants pisum sativum and Vicia cracca

Rhizobium leguminosarum bv. viciae forms nitrogen-fixing nodules on several legumes, including pea (Pisum sativum) and vetch (Vicia cracca), and has been widely used as a model to study nodule biochemistry. To understand the complex biochemical and developmental changes undergone by R. leguminosarum bv. viciae during bacteroid development, microarray experiments were first performed with cultured bacteria grown on a variety of carbon substrates (glucose, pyruvate, succinate, inositol, acetate, and acetoacetate) and then compared to bacteroids. Bacteroid metabolism is essentially that of dicarboxylate-grown cells (i.e., induction of dicarboxylate transport, gluconeogenesis and alanine synthesis, and repression of sugar utilization). The decarboxylating arm of the tricarboxylic acid cycle is highly induced, as is gamma-aminobutyrate metabolism, particularly in bacteroids from early (7-day) nodules. To investigate bacteroid development, gene expression in bacteroids was analyzed at 7, 15, and 21 days postinoculation of peas. This revealed that bacterial rRNA isolated from pea, but not vetch, is extensively processed in mature bacteroids. In early development (7 days), there were large changes in the expression of regulators, exported and cell surface molecules, multidrug exporters, and heat and cold shock proteins. fix genes were induced early but continued to increase in mature bacteroids, while nif genes were induced strongly in older bacteroids. Mutation of 37 genes that were strongly upregulated in mature bacteroids revealed that none were essential for nitrogen fixation. However, screening of 3,072 mini-Tn5 mutants on peas revealed previously uncharacterized genes essential for nitrogen fixation. These encoded a potential magnesium transporter, an AAA domain protein, and proteins involved in cytochrome synthesis.

Exposure of Escherichia coli and Salmonella enterica serovar Typhimurium to triclosan induces a species-specific response, including drug detoxification

Objectives: The use of triclosan within various environments has been linked to the development of multiple drug resistance (MDR) through the increased expression of efflux pumps such as AcrAB-ToIC. In this work, we investigate the effect of triclosan exposure in order to ascertain the response of two species to the presence of this widely used biocide. Methods: The transcriptomes of Salmonella enterica serovar Typhimurium SL1344 and Escherichia coli K-12 MG1655 after exposure to the MIC of triclosan (0.12 mg/L) were determined in microarray experiments. Phenotypic validation of the transcriptomic data included RT-PCR, ability to form a biofilm and motility assays. Results: Despite important differences in the triclosan-dependent transcriptomes of the two species, increased expression of efflux pump component genes was seen in both. Increased expression of soxS was observed in Salmonella Typhimurium, however, within E. coli, decreased expression was seen. Expression of fabBAGI in Salmonella Typhimurium was decreased, whereas in E. coli expression of fabABFH was increased. Increased expression of ompR and genes within this regulon (e.g. ompC, csgD and ssrA) was seen in the transcriptome of Salmonella Typhimurium. An unexpected response of E. coli was the differential expression of genes within operons involved in iron homeostasis; these included fhu, fep and ent. Conclusions: These data indicate that whilst a core response to triclosan exposure exists, the differential transcriptome of each species was different. This suggests that E. coli K-12 should not be considered the paradigm for the Enterobacteriaceae when exploring the effects of antimicrobial agents.

Nutrient sensing and signalling in plants: Potassium and phosphorus

Potassium and phosphorus are important macronutrients for crops but are often deficient in the field. Very little is known about how plants sense fluctuations in K and P and how information about K and P availability is integrated at the whole plant level into physiological and metabolic adaptations. This chapter reviews recent advances in discovering molecular responses of plants to K and P deficiency by microarray experiments. These studies provide us not only with a comprehensive picture of adaptive mechanisms, but also with a large number of transcriptional markers that can be used to identify upstream components of K and P signalling pathways. On the basis of the available information we discuss putative receptors and signals involved in the sensing and integration of K and P status both at the cellular and at the whole plant level. These involve membrane potential, voltage-dependent ion channels, intracellular Ca and pH, and transcription factors, as well as hormones and metabolites for systemic signalling. Genetic screens of reporter lines for transcriptional markers and metabolome analysis of K- and P-deficient plants are likely to further advance our knowledge in this area in the near future.

The global effect of follicle-stimulating hormone and tumour necrosis factor α on gene expression in cultured bovine ovarian granulosa cells

Background Oocytes mature in ovarian follicles surrounded by granulosa cells. During follicle growth, granulosa cells replicate and secrete hormones, particularly steroids close to ovulation. However, most follicles cease growing and undergo atresia or regression instead of ovulating. To investigate the effects of stimulatory (follicle-stimulating hormone; FSH) and inhibitory (tumour necrosis factor alpha; TNFα) factors on the granulosa cell transcriptome, bovine ovaries were obtained from a local abattoir and pools of granulosa cells were cultured in vitro for six days under defined serum-free conditions with treatments present on days 3–6. Initially dose–response experiments (n = 4) were performed to determine the optimal concentrations of FSH (0.33 ng/ml) and TNFα (10 ng/ml) to be used for the microarray experiments. For array experiments cells were cultured under control conditions, with FSH, with TNFα, or with FSH plus TNFα (n = 4 per group) and RNA was harvested for microarray analyses. Results Statistical analysis showed primary clustering of the arrays into two groups, control/FSH and TNFα/TNFα plus FSH. The effect of TNFα on gene expression dominated that of FSH, with substantially more genes differentially regulated, and the pathways and genes regulated by TNFα being similar to those of FSH plus TNFα treatment. TNFα treatment reduced the endocrine activity of granulosa cells with reductions in expression of FST, INHA, INBA and AMH. The top-ranked canonical pathways and GO biological terms for the TNFα treatments included antigen presentation, inflammatory response and other pathways indicative of innate immune function and fibrosis. The two most significant networks also reflect this, containing molecules which are present in the canonical pathways of hepatic fibrosis/hepatic stellate cell activation and transforming growth factor β signalling, and these were up regulated. Upstream regulator analyses also predicted TNF, interferons γ and β1 and interleukin 1β. Conclusions In vitro, the transcriptome of granulosa cells responded minimally to FSH compared with the response to TNFα. The response to TNFα indicated an active process akin to tissue remodelling as would occur upon atresia. Additionally there was reduction in endocrine function and induction of an inflammatory response to TNFα that displays features similar to immune cells.

Protein variation in blood-dwelling schistosome worms generated by differential splicing of micro-exon gene transcripts

Schistosoma mansoni is a well-adapted blood-dwelling parasitic helminth, persisting for decades in its human host despite being continually exposed to potential immune attack. Here, we describe in detail micro-exon genes (MEG) in S. mansoni, some present in multiple copies, which represent a novel molecular system for creating protein variation through the alternate splicing of short (<= 36 bp) symmetric exons organized in tandem. Analysis of three closely related copies of one MEG family allowed us to trace several evolutionary events and propose a mechanism for micro-exon generation and diversification. Microarray experiments show that the majority of MEGs are up-regulated in life cycle stages associated with establishment in the mammalian host after skin penetration. Sequencing of RT-PCR products allowed the description of several alternate splice forms of micro-exon genes, highlighting the potential use of these transcripts to generate a complex pool of protein variants. We obtained direct evidence for the existence of such pools by proteomic analysis of secretions from migrating schistosomula and mature eggs. Whole-mount in situ hybridization and immunolocalization showed that MEG transcripts and proteins were restricted to glands or epithelia exposed to the external environment. The ability of schistosomes to produce a complex pool of variant proteins aligns them with the other major groups of blood parasites, but using a completely different mechanism. We believe that our data open a new chapter in the study of immune evasion by schistosomes, and their ability to generate variant proteins could represent a significant obstacle to vaccine development.

Global Gene Expression Analysis during Sporulation of the Aquatic Fungus Blastocladiella emersonii

The Blastocladiella emersonii life cycle presents a number of drastic biochemical and morphological changes, mainly during two cell differentiation stages: germination and sporulation. To investigate the transcriptional changes taking place during the sporulation phase, which culminates with the production of the zoospores, motile cells responsible for the dispersal of the fungus, microarray experiments were performed. Among the 3,773 distinct genes investigated, a total of 1,207 were classified as differentially expressed, relative to time zero of sporulation, at at least one of the time points analyzed. These results indicate that accurate transcriptional control takes place during sporulation, as well as indicating the necessity for distinct molecular functions throughout this differentiation process. The main functional categories overrepresented among upregulated genes were those involving the microtubule, the cytoskeleton, signal transduction involving Ca(2+), and chromosome organization. On the other hand, protein biosynthesis, central carbon metabolism, and protein degradation were the most represented functional categories among downregulated genes. Gene expression changes were also analyzed in cells sporulating in the presence of subinhibitory concentrations of glucose or tryptophan. Data obtained revealed overexpression of microtubule and cytoskeleton transcripts in the presence of glucose, probably causing the shape and motility problems observed in the zoospores produced under this condition. In contrast, the presence of tryptophan during sporulation led to upregulation of genes involved in oxidative stress, proteolysis, and protein folding. These results indicate that distinct physiological pathways are involved in the inhibition of sporulation due to these two classes of nutrient sources.

Estudos de expressão gênica utilizando-se microarrays: delineamento, análise, e aplicações na pesquisa zootécnica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)