Cloning and expression analysis of a HSP70 gene from Pacific abalone (Haliotis discus hannai)

Heat shock protein 70 (HSP70), the primary member of HSPs that are responsive of thermal stress, is found in all multicellular organisms and functions mostly as molecular chaperon. The inducible HSP70 cDNA cloned from Pacific abalone (Haliotis discus hannai) using rapid amplification of cDNA ends (RACE), was highly homologous to other HSP70 genes. The full-length cDNA of the Pacific abalone HSP70 was 2631 bp, consisting of a 5'-terminal untranslated region (UTR) of 90 bp, a 3'-terminal UTR of 573 by with a canonical polyadenylation signal sequence AATAAA and a poly (A) tail, and an open reading frame of 1968 bp. The HSP70 cDNA encoded a polypeptide of 655 amino acids with an ATPase domain of 382 amino acids, the substrate peptide binding domain of 161 amino acids and a C-terminus domain of 112 amino acids. The temporal expression of HSP70 was measured by semi-quantitative RT-PCR after heat shock and bacterial challenge. Challenge of Pacific abalone with heat shock or the pathogenic bacteria Vibrio anguillarum resulted in a dramatic increase in the expression of HSP70 mRNA level in muscle, followed by a recovery to normal level after 96 h. Unlike the muscle, the levels of HSP70 expression in gills reached the top at 12 h and maintained a relatively high level compared with the control after thermal and bacterial challenge. The upregulated mRNA expression of HSP70 in the abalone following heat shock and infection response indicates that the HSP70 gene is inducible and involved in immune response. (c) 2006 Elsevier Ltd. All rights reserved.

Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer

Background: The bioenergetic status of non-small cell lung cancer correlates with tumour aggressiveness. The voltage dependent anion channel type 1 (VDAC1) is a component of the mitochondrial permeability transition pore, regulates mitochondrial ATP/ADP exchange suggesting that its over-expression could be associated with energy dependent processes including increased proliferation and invasiveness. To test this hypothesis, we conducted an in vivo gene-expression meta-analysis of surgically resected non-small cell lung cancer (NSCLC) using 602 individual expression profiles, to examine the impact of VDAC1 on survival.

Analysis of HSC activity and compensatory Hox gene expression profile in Hoxb cluster mutant fetal liver cells

Overexpression of Hoxb4 in bone marrow cells promotes expansion of hematopoietic stem cell (HSC) populations in vivo and in vitro, indicating that this homeoprotein can activate the genetic program that determines self-renewal. However, this function cannot be solely attributed to Hoxb4 because Hoxb4(-/-) mice are viable and have an apparently normal HSC number. Quantitative polymerase chain reaction analysis showed that Hoxb4(-/-) c-Kit(+) fetal liver cells expressed moderately higher levels of several Hoxb cluster genes than control cells, raising the possibility that normal HSC activity in Hoxb4(-/-) mice is due to a compensatory up-regulation of other Hoxb genes. In this study, we investigated the competitive repopulation potential of HSCs lacking Hoxb4 alone, or in conjunction with 8 other Hoxb genes. Our results show that Hoxb4(-/-) and Hoxb1-b9(-/-) fetal liver cells retain full competitive repopulation potential and the ability to regenerate all myeloid and lymphoid lineages. Quantitative Hox gene expression profiling in purified c-KIt(+) Hoxb1-bg(-/-) fetal liver cells revealed an interaction between the Hoxa, b, and c clusters with variation in expression levels of Hoxa4, -a11, and -c4. Together, these studies show a complex network of genetic interactions between several Hox genes in primitive hematopoietic cells and demonstrate that HSCs lacking up to 30% of the active Hox genes remain fully competent.

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes

BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

Expression analysis of the AtPHO1 gene family in Arabidopsis thaliana and the involvement of AtPHO1 in the regulation of stomatal movements

Résumé Le transfert du phosphate des racines vers les feuilles s'effectue par la voie du xylème. Il a été précédemment démontré que la protéine AtPHO1 était indispensable au transfert du phosphate dans les vaisseaux du xylème des racines chez la plante modèle Arabidopsis thaliana. Le séquençage et l'annotation du génome d'Arabidopsis ont permis d'identifier dix séquences présentant un niveau de similarité significatif avec le gène AtPHO1 et constituant une nouvelle famille de gène appelé la famille de AtPHO1. Basée sur une étude moléculaire et génétique, cette thèse apporte des éléments de réponse pour déterminer le rôle des membres de ia famille de AtPHO1 chez Arabidopsis, inconnue à ce jour. Dans un premier temps, une analyse bioinformatique des séquences protéiques des membres de la famille de AtPHO1 a révélé la présence dans leur région N-terminale d'un domaine nommé SPX. Ce dernier est conservé parmi de nombreuses protéines impliquées dans l'homéostasie du phosphate chez la levure, renforçant ainsi l'hypothèse que les membres de la famille de AtPHO1 auraient comme AtPHO1 un rôle dans l'équilibre du phosphate dans la plante. En parallèle, la localisation tissulaire de l'expression des gènes AtPHO dans Arabidopsis a été identifiée par l'analyse de plantes transgéniques exprimant le gène rapporteur uidA sous le contrôle des promoteurs respectifs des gènes AtPHO. Un profil d'expression de chaque gène AtPHO au cours du développement de la plante a été obtenu. Une expression prédominante au niveau des tissus vasculaires des racines, des feuilles, des tiges et des fleurs a été observée, suggérant que les gènes AtPHO pourraient avoir des fonctions redondantes au niveau du transfert de phosphate dans le cylindre vasculaire de ces différents organes. Toutefois, plusieurs régions promotrices des gènes AtPHO contrôlent également un profil d'expression GUS non-vasculaire, indiquant un rôle putatif des gènes AtPHO dans l'acquisition ou le recyclage de phosphate dans la plante. Dans un deuxième temps, l'analyse de l'expression des gènes AtPHO durant une carence en phosphate a établi que seule l'expression des gènes AtPHO1, AtPHO1; H1 et AtPHO1; H10 est régulée par cette carence. Une étude approfondie de leur expression en réponse à des traitements affectant l'homéostasie du phosphate dans la plante a ensuite démontré leur régulation par différentes voies de signalisation. Ensuite, une analyse détaillée de la régulation de l'expression du gène AtPHO1; H1O dans des feuilles d'Arabidopsis blessées ou déshydratées a révélé que ce gène constitue le premìer gène marqueur d'une nouvelle voie de signalisation induite par l'OPDA, pas par le JA et dépendante de la protéine COI1. Ces résultats démontrent pour la première fois que l'OPDA et le JA peuvent activer différents gènes via des voies de signalisation dépendantes de COI1. Enfin, cette thèse révèle l'identification d'un nouveau rôle de la protéine AtPHO1 dans la régulation de l'action de l'ABA au cours des processus de fermeture stomatique et de germination des graines chez Arabidopsis. Bien que les fonctions exactes des protéines AtPHO restent à être déterminées, ce travail de thèse suggère leur implication dans la propagation de différents signaux dans la plante via la modulation du potentiel membranaire et/ou l'affectation de la composition en ions des cellules comme le font de nombreux transporteurs ou régulateur du transport d'ions. Summary Phosphate is transferred from the roots to the shoot via the xylem. The requirement for AtPHO1 protein to transfer phosphate to the xylem vessels of the root has been previously demonstrated in Arabidopsis thaliana. The sequencing and the annotation of the Arabidopsis genome had allowed the identification of ten sequences that show a significant level of similarity with the AtPHO1 gene. These 10 genes, of unknown functions, constitute a new gene family called the AtPHO1 gene family. Based on a molecular and genetics study, this thesis reveals some information needed to understand the role of the AtPHO1 family members in the plant Arabidopsis. First, a bioinformatics study revealed that the AtPHO sequences contained, in the N-terminal hydrophilic region, a motif called SPX and conserved among multiple proteins involved in phosphate homeostasis in yeast. This finding reinforces the hypothesis that all AtPHO1 family members have, as AtPHO1, a role in phosphate homeostasis. In parallel, we identified the pattern of expression of AtPHO genes in Arabidopsis via analysis of transgenic plants expressing the uidA reporter gene under the control of respective AtPHO promoter regions. The results exhibit a predominant expression of AtPHO genes in vascular tissues of all organs of the plant, implying that these AtPHO genes could have redundant functions in the transfer of phosphate to the vascular cylinder of various organs. The GUS expression pattern for several AtPHO promoter regions was also detected in non-vascular tissue indicating a broad role of AtPHO genes in the acquisition or in the recycling of phosphate in the plant. In a second step, the analysis of the expression of AtPHO genes during phosphate starvation established that only the expression of the AtPHO1, AtPHO1; H1 and AtPHO1; H10 genes were regulated by Pi starvation. Interestingly, different signalling pathways appeared to regulate these three genes during various treatments affecting Pi homeostasis in the plant. The third chapter presents a detailed analysis of the signalling pathways regulating the expression of the AtPHO1; H10 gene in Arabidopsis leaves during wound and dehydrated stresses. Surprisingly, the expression of AtPHO1; H10 was found to be regulated by OPDA (the precursor of JA) but not by JA itself and via the COI1 protein (the central regulator of the JA signalling pathway). These results demonstrated for the first time that OPDA and JA could activate distinct genes via COI1-dependent pathways. Finally, this thesis presents the identification of a novel role of the AtPHO1 protein in the regulation of ABA action in Arabidopsis guard cells and during seed germination. Although the exact role and function of AtPHO1 still need to be determined, these last findings suggest that AtPHO1 and by extension other AtPHO proteins could mediate the propagation of various signals in the plant by modulating the membrane potential and/or by affecting cellular ion composition, as it is the case for many ion transporters or regulators of ion transport.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Identification of hepatic molecular mechanisms of action of alpha-tocopherol using global gene expression profile analysis in rats

The recent discovery that vitamin E (VE) regulates gene activity at the transcriptional level indicates that VE may exert part of its biological effects by mechanisms which may be independent of its well-recognised antioxidant function. The objective of this study was the identification of hepatic vitamin E-sensitive genes and examination of the effects of VE on their corresponding biological endpoints. Two groups of male rats were randomly assigned to either a VE-sufficient diet or to a control diet deficient in VE for 290 days. High-density oligonucleotide microarrays comprising over 7000 genes were used to assess the transcriptional response of the liver. Differential gene expression was monitored over a period of 9 months, at four different time-points, and rats were individually profiled. This experimental strategy identified several VE-sensitive genes, which were chronically altered by dietary VE. VE supplementation down-regulated scavenger receptor CD36, coagulation factor IX and 5-alpha-steroid reductase type 1 mRNA levels while hepatic gamma glutamyl-cysteinyl synthetase was significantly up-regulated. Measurement of the corresponding biological endpoints such as activated partial thromboplastin time, plasma dihydrotestosterone and hepatic glutathione substantiated the gene chip data which indicated that dietary VE plays an important role in a range of metabolic processes within the liver. (C) 2004 Elsevier B.V. All rights reserved.