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Sample records for approaches gene expression

  1. A constructive approach to gene expression dynamics

    International Nuclear Information System (INIS)

    Recently, experiments on mRNA abundance (gene expression) have revealed that gene expression shows a stationary organization described by a scale-free distribution. Here we propose a constructive approach to gene expression dynamics which restores the scale-free exponent and describes the intermediate state dynamics. This approach requires only one assumption: Markov property

  2. A stochastic approach to multi-gene expression dynamics

    International Nuclear Information System (INIS)

    In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

  3. A sequence-based approach to identify reference genes for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Chari Raj

    2010-08-01

    Full Text Available Abstract Background An important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer may not be suitable in another (e.g. breast cancer. Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate. Methods Serial analysis of gene expression (SAGE profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR, and their impact on differential expression analysis of microarray data was evaluated. Results We show that (i conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii reference genes identified for lung cancer do not perform well for other cancer types (breast and brain, (iii reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung

  4. Regulation of gene expression by hypoxia: a molecular approach.

    Science.gov (United States)

    Beitner-Johnson, D; Shull, G E; Dedman, J R; Millhorn, D E

    1997-11-01

    Oxygen is a strict requirement for cell function. The cellular mechanisms by which organisms detect and respond to changes in oxygen tension remain a major unanswered question in pulmonary physiology. Part of the difficulty in addressing this question is due to the limited scope of experiments that can be performed in vivo. In the past few years, several laboratories have begun to make progress in this area, using a variety of cell culture model systems and sophisticated genetic manipulations. Here, we review the current state of knowledge of regulation of gene expression by hypoxia, and describe novel experimental approaches that promise to broaden our understanding of how cells and whole organisms respond to alterations in O2 tension. PMID:9407603

  5. Randomized Algorithmic Approach for Biclustering of Gene Expression Data

    OpenAIRE

    Sradhanjali Nayak; Debahuti Mishra; Satyabrata Das; Amiya Kumar Rath

    2011-01-01

    Microarray data processing revolves around the pivotal issue of locating genes altering their expression in response to pathogens, other organisms or other multiple environmental conditions resulted out of a comparison between infected and uninfected cells or tissues. To have a comprehensive analysis of the corollaries of certain treatments, deseases and developmental stages embodied as a data matrix on gene expression data is possible through simultaneous observation and monitoring of the ex...

  6. Biclustering using Parallel Fuzzy Approach for Analysis of Microarray Gene Expression Data

    OpenAIRE

    Dwitiya Tyagi-Tiwari; Sujoy Das; Manoj Jha; Namita Srivastava

    2015-01-01

    Biclusters are required to analyzing gene expression patterns of genes comparing rows in expression profiles and analyzing expression profiles of samples by comparing columns in gene expression matrix. In the process of biclustering we need to cluster genes and samples. The algorithm presented in this paper is based upon the two-way clustering approach in which the genes and samples are clustered using parallel fuzzy C-means clustering using message passing interface, we call it MFCM. MFCM ap...

  7. A general co-expression network-based approach to gene expression analysis: comparison and applications

    Directory of Open Access Journals (Sweden)

    Zhang Weixiong

    2010-02-01

    Full Text Available Abstract Background Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric. Results Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression networks that are very different from that of value-based networks in the literature. Using a large set of synthetic and real microarray data, we demonstrate the superior performance of our approach over several popular existing algorithms. Applications of our approach to yeast, Arabidopsis and human cancer microarray data reveal many interesting modules, including a fatal subtype of lymphoma and a gene module regulating yeast telomere integrity, which were missed by the existing methods. Conclusions We demonstrated that our novel approach is very effective in discovering the modular structures in microarray data, both for genes and for samples. As the method is essentially parameter-free, it may be applied to large data sets where the number of clusters is difficult to estimate. The method is also very general and can be applied to other types of data. A MATLAB implementation of our algorithm can be downloaded from http://cs.utsa.edu/~jruan/Software.html.

  8. Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

    KAUST Repository

    Abusamra, Heba

    2016-07-20

    The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

  9. Biclustering using Parallel Fuzzy Approach for Analysis of Microarray Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Dwitiya Tyagi-Tiwari

    2015-09-01

    Full Text Available Biclusters are required to analyzing gene expression patterns of genes comparing rows in expression profiles and analyzing expression profiles of samples by comparing columns in gene expression matrix. In the process of biclustering we need to cluster genes and samples. The algorithm presented in this paper is based upon the two-way clustering approach in which the genes and samples are clustered using parallel fuzzy C-means clustering using message passing interface, we call it MFCM. MFCM applied for clustering on genes and samples which maximize membership function values of the data set. It is a parallelized rework of a parallel fuzzy two-way clustering algorithm for microarray gene expression data [9], to study the efficiency and parallelization improvement of the algorithm. The algorithm uses gene entropy measure to filter the clustered data to find biclusters. The method is able to get highly correlated biclusters of the gene expression dataset.

  10. Candidate gene prioritization by network analysis of differential expression using machine learning approaches

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    Nitsch Daniela

    2010-09-01

    Full Text Available Abstract Background Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals. To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network. Results We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (Simple Expression Ranking. Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the Heat Kernel Diffusion Ranking leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%. Conclusion In this study we

  11. Gene expression

    International Nuclear Information System (INIS)

    We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn2+ or Cd2+. We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

  12. A graphical model approach for inferring large-scale networks integrating gene expression and genetic polymorphism

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    Carey Vincent J

    2009-05-01

    Full Text Available Abstract Background Graphical models (e.g., Bayesian networks have been used frequently to describe complex interaction patterns and dependent structures among genes and other phenotypes. Estimation of such networks has been a challenging problem when the genes considered greatly outnumber the samples, and the situation is exacerbated when one wishes to consider the impact of polymorphisms (SNPs in genes. Results Here we describe a multistep approach to infer a gene-SNP network from gene expression and genotyped SNP data. Our approach is based on 1 construction of a graphical Gaussian model (GGM based on small sample estimation of partial correlation and false-discovery rate multiple testing; 2 extraction of a subnetwork of genes directly linked to a target candidate gene of interest; 3 identification of cis-acting regulatory variants for the genes composing the subnetwork; and 4 evaluating the identified cis-acting variants for trans-acting regulatory effects of the target candidate gene. This approach identifies significant gene-gene and gene-SNP associations not solely on the basis of gene co-expression but rather through whole-network modeling. We demonstrate the method by building two complex gene-SNP networks around Interferon Receptor 12B2 (IL12RB2 and Interleukin 1B (IL1B, two biologic candidates in asthma pathogenesis, using 534,290 genotyped variants and gene expression data on 22,177 genes from total RNA derived from peripheral blood CD4+ lymphocytes from 154 asthmatics. Conclusion Our results suggest that graphical models based on integrative genomic data are computationally efficient, work well with small samples, and can describe complex interactions among genes and polymorphisms that could not be identified by pair-wise association testing.

  13. Determination of the Ultimate Limit States of Shallow Foundations using Gene Expression Programming (GEP) Approach

    DEFF Research Database (Denmark)

    Tahmasebi poor, A; Barari, Amin; Behnia, M;

    2015-01-01

    In this study, a gene expression programming (GEP) approach was employed to develop modified expressions for predicting the bearing capacity of shallow foundations founded on granular material. The model was validate against the results of load tests on full-scale and model footings obtained from...

  14. A combinatorial bidirectional and bicistronic approach for coordinated multi-gene expression in corn.

    Science.gov (United States)

    Kumar, Sandeep; AlAbed, Diaa; Whitteck, John T; Chen, Wei; Bennett, Sara; Asberry, Andrew; Wang, Xiujuan; DeSloover, Daniel; Rangasamy, Murugesan; Wright, Terry R; Gupta, Manju

    2015-03-01

    Transgene stacking in trait development process through genetic engineering is becoming complex with increased number of desired traits and multiple modes of action for each trait. We demonstrate here a novel gene stacking strategy by combining bidirectional promoter (BDP) and bicistronic approaches to drive coordinated expression of multi-genes in corn. A unidirectional promoter, Ubiquitin-1 (ZMUbi1), from Zea mays was first converted into a synthetic BDP, such that a single promoter can direct the expression of two genes from each end of the promoter. The BDP system was then combined with a bicistronic organization of genes at both ends of the promoter by using a Thosea asigna virus 2A auto-cleaving domain. With this gene stacking configuration, we have successfully obtained expression in transgenic corn of four transgenes; three transgenes conferring insect (cry34Ab1 and cry35Ab1) and herbicide (aad1) resistance, and a phiyfp reporter gene using a single ZMUbi1 bidirectional promoter. Gene expression analyses of transgenic corn plants confirmed better coordinated expression of the four genes compared to constructs driving each gene by independent unidirectional ZmUbi1 promoter. To our knowledge, this is the first report that demonstrates application of a single promoter for co-regulation of multiple genes in a crop plant. This stacking technology would be useful for engineering metabolic pathways both for basic and applied research. PMID:25657118

  15. Vaccine-induced modulation of gene expression in turbot peritoneal cells. A microarray approach.

    Science.gov (United States)

    Fontenla, Francisco; Blanco-Abad, Verónica; Pardo, Belén G; Folgueira, Iria; Noia, Manuel; Gómez-Tato, Antonio; Martínez, Paulino; Leiro, José M; Lamas, Jesús

    2016-07-01

    We used a microarray approach to examine changes in gene expression in turbot peritoneal cells after injection of the fish with vaccines containing the ciliate parasite Philasterides dicentrarchi as antigen and one of the following adjuvants: chitosan-PVMMA microspheres, Freund́s complete adjuvant, aluminium hydroxide gel or Matrix-Q (Isconova, Sweden). We identified 374 genes that were differentially expressed in all groups of fish. Forty-two genes related to tight junctions and focal adhesions and/or actin cytoskeleton were differentially expressed in free peritoneal cells. The profound changes in gene expression related to cell adherence and cytoskeleton may be associated with cell migration and also with the formation of cell-vaccine masses and their attachment to the peritoneal wall. Thirty-five genes related to apoptosis were differentially expressed. Although most of the proteins coded by these genes have a proapoptotic effect, others are antiapoptotic, indicating that both types of signals occur in peritoneal leukocytes of vaccinated fish. Interestingly, many of the genes related to lymphocytes and lymphocyte activity were downregulated in the groups injected with vaccine. We also observed decreased expression of genes related to antigen presentation, suggesting that macrophages (which were abundant in the peritoneal cavity after vaccination) did not express these during the early inflammatory response in the peritoneal cavity. Finally, several genes that participate in the inflammatory response were differentially expressed, and most participated in resolution of inflammation, indicating that an M2 macrophage response is generated in the peritoneal cavity of fish one day post vaccination. PMID:27318565

  16. Functional Associations by Response Overlap (FARO), a functional genomics approach matching gene expression phenotypes

    DEFF Research Database (Denmark)

    Nielsen, Henrik Bjørn; Mundy, J.; Willenbrock, Hanni

    2007-01-01

    The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors...... for deriving 'Functional Association(s) by Response Overlap' (FARO) between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability...... to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates...

  17. Biclustering of gene expression data: hybridization of GRASP with other heuristic/metaheuristic approaches

    OpenAIRE

    Musacchia, Francesco

    2013-01-01

    Researchers who work on large amount of data have to face vari- ous problems such as data mining and information retrieval: this is the case of gene expression. The general scope of these experiments is to find co-regulated genes, in order to understand the biologic pathways underlying a particular phenomenon. A clustering con- cept can be used to find out if co-regulated genes can be active only over some conditions. Recently, some biclustering approaches have been used to find groups of co-...

  18. Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach

    Science.gov (United States)

    Anjum, Arfa; Jaggi, Seema; Lall, Shwetank; Bhowmik, Arpan; Rai, Anil

    2016-01-01

    Abstract Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, which may be proteins. A gene is declared differentially expressed if an observed difference or change in read counts or expression levels between two experimental conditions is statistically significant. To identify differentially expressed genes between two conditions, it is important to find statistical distributional property of the data to approximate the nature of differential genes. In the present study, the focus is mainly to investigate the differential gene expression analysis for sequence data based on compound distribution model. This approach was applied in RNA-seq count data of Arabidopsis thaliana and it has been found that compound Poisson distribution is more appropriate to capture the variability as compared with Poisson distribution. Thus, fitting of appropriate distribution to gene expression data provides statistically sound cutoff values for identifying differentially expressed genes. PMID:26949988

  19. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach.

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    Gaurang Mahajan

    Full Text Available High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

  20. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach.

    Science.gov (United States)

    Mahajan, Gaurang; Mande, Shekhar C

    2015-01-01

    High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

  1. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach.

    Science.gov (United States)

    Mahajan, Gaurang; Mande, Shekhar C

    2015-01-01

    High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner. PMID:26562430

  2. Using intron splicing trick for preferential gene expression in transduced cells: an approach for suicide gene therapy.

    Science.gov (United States)

    Pourzadegan, F; Shariati, L; Taghizadeh, R; Khanahmad, H; Mohammadi, Z; Tabatabaiefar, M A

    2016-01-01

    Suicide gene therapy is one of the most innovative approaches in which a potential toxic gene is delivered to the targeted cancer cell by different target delivery methods. We constructed a transfer vector to express green fluorescent protein (GFP) in transduced cells but not in packaging cells. We placed gfp under the control of the cytomegalovirus (CMV) promoter, which is positioned between the two long-terminal repeats in reverse direction. The intron-2 sequence of the human beta globin gene with two poly-A signals and several stop codons on the antisense strand was placed on the leading strand between the CMV promoter and gfp. For lentiviral production, the HEK293T and line were co-transfected with the PMD2G, psPAX2 and pLentiGFP-Ins2 plasmids. The HEK293T and line were transduced with this virus. PCR was performed for evaluation of intron splicing in transduced cells. The GFP expression was seen in 65% of the cells transduced. The PCR amplification of the genomic DNA of transduced cells confirmed the splicing of intron 2. The strategy is significant to accomplish our goal for preserving the packaging cells from the toxic gene expression during viral assembly and the resultant reduction in viral titration. Also it serves to address several other issues in the gene therapy.

  3. Experimental approaches for the study of oxytocin and vasopressin gene expression in the central nervous system

    Science.gov (United States)

    Scordalakes, Elka M.; Yue, Chunmei; Gainer, Harold

    2016-01-01

    Intron-specific probes measure heteronuclear RNA (hnRNA) levels and thus approximate the transcription rates of genes, in part because of the rapid turnover of this intermediate form of RNA in the cell nucleus. Previously, we used oxytocin (Oxt)- and vasopressin (Avp)- intron-specific riboprobes to measure changes in Oxt and Avp hnRNA levels in the supraoptic nucleus (SON) by quantitative in situ hybridization (ISH) after various classical physiological perturbations, including acute and chronic salt loading, and lactation. In the present experiments, we used a novel experimental model to study the neurotransmitter regulation of Oxt and Avp gene expression in the rat SON in vivo. Bilateral cannulae connected via tubing to Alzet osmotic mini-pumps were positioned over the SON. In every experiment, one SON was infused with PBS and served as the control SON in each animal, and the contralateral SON received infusions of various neurotransmitter agonists and antagonists. Using this approach, we found that Avp but not Oxt gene expression increased after acute (2–5 h) combined excitatory amino acid agonist and GABA antagonist treatment, similar to what we found after an acute hyperosmotic stimulus. Since both OXT and AVP are known to be comparably and robustly secreted in response to acute osmotic stimuli in vivo and glutamate agonists in vitro, our results indicate a dissociation between OXT secretion and Oxt gene transcription in vivo. PMID:18655870

  4. Identifying the genetic variation of gene expression using gene sets: application of novel gene Set eQTL approach to PharmGKB and KEGG.

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    Ryan Abo

    Full Text Available Genetic variation underlying the regulation of mRNA gene expression in humans may provide key insights into the molecular mechanisms of human traits and complex diseases. Current statistical methods to map genetic variation associated with mRNA gene expression have typically applied standard linkage and/or association methods; however, when genome-wide SNP and mRNA expression data are available performing all pair wise comparisons is computationally burdensome and may not provide optimal power to detect associations. Consideration of different approaches to account for the high dimensionality and multiple testing issues may provide increased efficiency and statistical power. Here we present a novel approach to model and test the association between genetic variation and mRNA gene expression levels in the context of gene sets (GSs and pathways, referred to as gene set - expression quantitative trait loci analysis (GS-eQTL. The method uses GSs to initially group SNPs and mRNA expression, followed by the application of principal components analysis (PCA to collapse the variation and reduce the dimensionality within the GSs. We applied GS-eQTL to assess the association between SNP and mRNA expression level data collected from a cell-based model system using PharmGKB and KEGG defined GSs. We observed a large number of significant GS-eQTL associations, in which the most significant associations arose between genetic variation and mRNA expression from the same GS. However, a number of associations involving genetic variation and mRNA expression from different GSs were also identified. Our proposed GS-eQTL method effectively addresses the multiple testing limitations in eQTL studies and provides biological context for SNP-expression associations.

  5. Snapshot of the eukaryotic gene expression in muskoxen rumen--a metatranscriptomic approach.

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    Meng Qi

    Full Text Available BACKGROUND: Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. METHODOLOGY/PRINCIPAL FINDINGS: In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus, with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6, GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. CONCLUSIONS/SIGNIFICANCE: The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes.

  6. A Novel Approach for Discovering Condition-Specific Correlations of Gene Expressions within Biological Pathways by Using Cloud Computing Technology

    Directory of Open Access Journals (Sweden)

    Tzu-Hao Chang

    2014-01-01

    Full Text Available Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells, for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions.

  7. A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

    Science.gov (United States)

    Chang, Tzu-Hao; Wu, Shih-Lin; Wang, Wei-Jen; Horng, Jorng-Tzong; Chang, Cheng-Wei

    2014-01-01

    Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions. PMID:24579087

  8. A novel approach for a foreign gene expression by Newcastle disease virus

    Science.gov (United States)

    Newcastle disease virus (NDV) has been developed as vectors using reverse genetics technology to express foreign genes for vaccine, anticancer and gene therapy purposes. The foreign genes are usually inserted into the intergenic region of the NDV genome as an additional transcription unit. Based on ...

  9. A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer

    OpenAIRE

    Leckie Christopher; Shi Fan; MacIntyre Geoff; Haviv Izhak; Boussioutas Alex; Kowalczyk Adam

    2010-01-01

    Abstract Background In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the ...

  10. A Hybrid SOM-SVM Approach for the Zebrafish Gene Expression Analysis

    Institute of Scientific and Technical Information of China (English)

    Wei Wu; Xin Liu; Min Xu; Jin-Rong Peng; Rudy Setiono

    2005-01-01

    Microarray technology can be employed to quantitatively measure the expression of thousands of genes in a single experiment. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large amount of expression data generated by this technology makes the study of certain complex biological problems possible, and machine learning methods are expected to play a crucial role in the analysis process. In this paper,we present our results from integrating the self-organizing map (SOM) and the support vector machine (SVM) for the analysis of the various functions of zebrafish genes based on their expression. The most distinctive characteristic of our zebrafish gene expression is that the number of samples of different classes is imbalanced. We discuss how SOM can be used as a data-filtering tool to improve the classification performance of the SVM on this data set.

  11. Transgenic approach to express the channelrhodopsin 2 gene in arginine vasopressin neurons of rats.

    Science.gov (United States)

    Ishii, Masahiro; Hashimoto, Hirofumi; Ohkubo, Jun-Ichi; Ohbuchi, Toyoaki; Saito, Takeshi; Maruyama, Takashi; Yoshimura, Mitsuhiro; Yamamoto, Yukiyo; Kusuhara, Koichi; Ueta, Yoichi

    2016-09-01

    Optogenetics provides a powerful tool to regulate neuronal activity by light-sensitive ion channels such as channelrhodopsin 2 (ChR2). Arginine vasopressin (AVP; also known as the anti-diuretic hormone) is a multifunctional hormone which is synthesized in the magnocellular neurosecretory cells (MNCs) of the hypothalamus. Here, we have generated a transgenic rat that expresses an AVP-ChR2-enhanced green fluorescent protein (eGFP) fusion gene in the MNCs of the hypothalamus. The eGFP fluorescence that indicates the expression of ChR2-eGFP was observed in the supraoptic nucleus (SON) and in the magnocellular division of the paraventricular nucleus (PVN) that is known to contain AVP-secreting neurons. The eGFP fluorescence intensities in those nuclei and posterior pituitary were markedly increased after chronic salt loading (2% NaCl in drinking water for 5days). ChR2-eGFP was localized mainly in the membrane of AVP-positive MNCs. Whole-cell patch-clamp recordings were performed from single MNCs isolated from the SON of the transgenic rats, and blue light evoked repetitive action potentials. Our work provides for the first time an optogenetic approach to selectively activate AVP neurons in the rat. PMID:27493075

  12. Gene expression analysis approach to establish possible links between Parkinson's disease, cancer and cardiovascular diseases.

    Science.gov (United States)

    Karim, Sajjad; Mirza, Zeenat; Kamal, Mohammad A; Abuzenadah, Adel M; Al-Qahtani, Mohammed H

    2014-01-01

    Non-communicable chronic diseases have been apparently established as threat to human health, and are currently the world's main killer. Cardiovascular diseases (CVD), cancer, diabetes and neurodegenerative diseases are collectively amounting to more than 60% of non-communicable disease burden across world. Tremendous advancements in healthcare enabled us to fight several health problems primarily infectious diseases. However, this increased longevity where in many cases an individual suffers from several such chronic diseases simultaneously, making treatment complex. Finding whether diseases can coexist in an individual by chance or there exists a possible association between them is vital. Our goal is to establish possible existing link among CVD, cancer and Parkinson's disease (PD) for better understanding of the associated molecular network. In this study, we integrated multiple dataset retrieved from the National Centre for Biotechnology Information's Gene Expression Omnibus database, and took a systems-biology approach to compare and distinguish the molecular network associated with PD, cancer and CVD. We identified 230, 308 and 1619 differentially expressed genes for CVD, cancer and PD dataset respectively using cut off p value2. We integrated these data with known pathways using Ingenuity Pathway Analysis tool and found following common pathways associated with all three diseases to be most affected; epithelial adherens junction signaling, remodelling of epithelial adherens junctions, role of BRCA1 in DNA damage response, sphingomyelin metabolism, 3- phosphoinositide biosynthesis, acute myeloid leukemia signaling, type I diabetes mellitus signaling, agrin interactions at neuromuscular junction, role of IL-17A in arthritis, and antigen presentation pathways. In conclusion, CVD, cancer and PD appear tightly associated at molecular level.

  13. Correlating overrepresented upstream motifs to gene expression a computational approach to regulatory element discovery in eukaryotes

    CERN Document Server

    Caselle, M; Provero, P

    2002-01-01

    Gene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory elements in the upstream region of eukaryotic genes. The genes are grouped in sets sharing an overrepresented short motif in their upstream sequence. For each set, the average expression level from a microarray experiment is determined: If this level is significantly higher or lower than the average taken over the whole genome, then the overerpresented motif shared by the genes in the set is likely to play a role in their regulation. The method was tested by applying it to the genome of Saccharomyces cerevisiae, using the publicly available results of a DNA microarray experiment, in which expression levels for virtually all the genes were measured during the diauxic shift from fermentation to respiration. Several known motifs were correctly identified, and a new candidate regulat...

  14. PR gene families of citrus: their organ specific-biotic and abiotic inducible expression profiles based on ESTs approach

    Directory of Open Access Journals (Sweden)

    Magnólia A. Campos

    2007-01-01

    Full Text Available In silico expression profiles, of the discovered 3,103 citrus ESTs putatively encoding for PR protein families (PR-1 to PR-17, were evaluated using the Brazil citrus genome EST CitEST/database. Hierarchical clustering was displayed to identify similarities in expression patterns among citrus PR-like gene families (PRlgf in 33 selected cDNA libraries. In this way, PRlgf preferentially expressed by organ and citrus species, and library conditions were highlighted. Changes in expression profiles of clusters for each of the 17 PRlgf expressed in organs infected by pathogens or drought-stressed citrus species were displayed for relative suppression or induction gene expression in relation to the counterpart control. Overall, few PRlgf showed expression 2-fold higher in pathogen-infected than in uninfected organs, even though the differential expression profiles displayed have been quite diverse among studied species and organs. Furthermore, an insight into some contigs from four PRlgf pointed out putative members of multigene families. They appear to be evolutionarily conserved within citrus species and/or organ- or stress-specifically expressed. Our results represent a starting point regarding the extent of expression pattern differences underlying PRlgf expression and reveal genes that may prove to be useful in studies regarding biotechnological approaches or citrus resistance markers.

  15. A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer

    Directory of Open Access Journals (Sweden)

    Leckie Christopher

    2010-09-01

    Full Text Available Abstract Background In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the statistical and biological significance of those discoveries. Results In this paper, we develop a robust and efficient method for exploratory analysis of microarray data, which produces a number of different orderings (rankings of both genes and samples (reflecting correlation among those genes and samples. The core algorithm is closely related to biclustering, and so we first compare its performance with several existing biclustering algorithms on two real datasets - gastric cancer and lymphoma datasets. We then show on the gastric cancer data that the sample orderings generated by our method are highly statistically significant with respect to the histological classification of samples by using the Jonckheere trend test, while the gene modules are biologically significant with respect to biological processes (from the Gene Ontology. In particular, some of the gene modules associated with biclusters are closely linked to gastric cancer tumorigenesis reported in previous literature, while others are potentially novel discoveries. Conclusion In conclusion, we have developed an effective and efficient method, Bi-Ordering Analysis, to detect informative patterns in gene expression microarrays by ranking genes and samples. In addition, a number of evaluation metrics were applied to assess both the statistical and biological significance of the resulting bi-orderings. The methodology was validated on gastric cancer and lymphoma datasets.

  16. Classification of Micro Array Gene Expression Data using Factor Analysis Approach with Naïve Bayesian Classifier

    OpenAIRE

    Tamilselvi Madeswaran; G.M.Kadhar Nawaz

    2013-01-01

    Microarray data studies produce large number of data and in order to analyze such large micro array data lies on Data mining or Statistical Analysis. Our objective is to classify the micro arraygene expression data. Usually before going for the classification the dimensionality reduction will be performed on the micro array gene expression dataset. A statistical approach for the extraction of thegene has been proposed. The drawback in the statistical analysis is that, it doesn’t identify the ...

  17. A novel biclustering approach with iterative optimization to analyze gene expression data

    Directory of Open Access Journals (Sweden)

    Ohta H

    2012-09-01

    Full Text Available Sawannee Sutheeworapong,1,2 Motonori Ota,4 Hiroyuki Ohta,1 Kengo Kinoshita2,31Department of Biological Sciences, Graduate School of Biosciences and Biotechnology, Tokyo Institute of Technology, Tokyo, Japan; 2Graduate School of Information Sciences, 3Institute of Development, Aging and Cancer, Tohoku University, Miyagi, Japan; 4Graduate School of Information Sciences, Nagoya University, Nagoya, JapanObjective: With the dramatic increase in microarray data, biclustering has become a promising tool for gene expression analysis. Biclustering has been proven to be superior over clustering in identifying multifunctional genes and searching for co-expressed genes under a few specific conditions; that is, a subgroup of all conditions. Biclustering based on a genetic algorithm (GA has shown better performance than greedy algorithms, but the overlap state for biclusters must be treated more systematically.Results: We developed a new biclustering algorithm (binary-iterative genetic algorithm [BIGA], based on an iterative GA, by introducing a novel, ternary-digit chromosome encoding function. BIGA searches for a set of biclusters by iterative binary divisions that allow the overlap state to be explicitly considered. In addition, the average of the Pearson’s correlation coefficient was employed to measure the relationship of genes within a bicluster, instead of the mean square residual, the popular classical index. As compared to the six existing algorithms, BIGA found highly correlated biclusters, with large gene coverage and reasonable gene overlap. The gene ontology (GO enrichment showed that most of the biclusters are significant, with at least one GO term over represented.Conclusion: BIGA is a powerful tool to analyze large amounts of gene expression data, and will facilitate the elucidation of the underlying functional mechanisms in living organisms.Keywords: biclustering, microarray data, genetic algorithm, Pearson’s correlation coefficient

  18. Effect of Thyrotropin Releasing Hormone (TRH on Gene Expressions in Rat Pancreas: Approach by Microarray Hybridization

    Directory of Open Access Journals (Sweden)

    Luo LG

    2004-07-01

    Full Text Available CONTEXT: Thyrotropin releasing hormone (TRH, originally identified as a hypothalamic hormone, expresses in the pancreas. The effects of TRH such as, inhibiting amylase secretion in rats through a direct effect on acinar cells, enhancing basal glucagon secretion from isolated perfused rat pancreas, and potentiating glucose-stimulated insulin secretion in perfused rat islets and insulin-secreting clonal beta-cell lines, suggest that TRH may play a role in pancreas. TRH also enlarged pancreas and increased pancreatic DNA content but deletion of TRH gene expression caused hyperglycemia in mice, suggesting that TRH may play a critical role in pancreatic development; however, the biological mechanisms of TRH in the adult pancreas remains unclear. OBJECTIVES: This study explored the effect of TRH on rat pancreas. SUBJECTS: Four male-Sprague-Dawley-rats (200-250 g were given 10 microg/kg BW of TRH intraperitoneally on 1st and 3rd day and sacrificed on 7th day. Four same-strain rats without TRH injection served as controls. MAIN OUTCOME MEASURES: Wet pancreatic weights were measured. Pancreatic tissues were homogenized and extracted. The insulin levels of the extracts were measured by ELISA. Total RNA from the pancreases were fluorescently labeled and hybridized to microarray with 1,081 spot genes. RESULTS: TRH increased pancreatic wet weight and insulin contents. About 75% of the 1,081 genes were detected in the pancreas. TRH regulated up 99 genes and down 76 genes. The administration of TRH induced various types of gene expressions, such as G-protein coupled receptors (GPCR and signal transduction related genes (GPCR kinase 4, transducin beta subunit 5, arrestin beta1MAPK3, MAPK5, c-Src kinase, PKCs, PI3 kinase, growth factors (PDGF-B, IGF-2, IL-18, IGF-1, IL-2, IL-6, endothelin-1 and apoptotic factors (Bcl2, BAD, Bax. CONCLUSION: Reprogramming of transcriptome may be a way for TRH-regulation of pancreatic cellular functions.

  19. A new experimental approach for studying bacterial genomic island evolution identifies island genes with bacterial host-specific expression patterns

    Directory of Open Access Journals (Sweden)

    Nickerson Cheryl A

    2006-01-01

    Full Text Available Abstract Background Genomic islands are regions of bacterial genomes that have been acquired by horizontal transfer and often contain blocks of genes that function together for specific processes. Recently, it has become clear that the impact of genomic islands on the evolution of different bacterial species is significant and represents a major force in establishing bacterial genomic variation. However, the study of genomic island evolution has been mostly performed at the sequence level using computer software or hybridization analysis to compare different bacterial genomic sequences. We describe here a novel experimental approach to study the evolution of species-specific bacterial genomic islands that identifies island genes that have evolved in such a way that they are differentially-expressed depending on the bacterial host background into which they are transferred. Results We demonstrate this approach by using a "test" genomic island that we have cloned from the Salmonella typhimurium genome (island 4305 and transferred to a range of Gram negative bacterial hosts of differing evolutionary relationships to S. typhimurium. Systematic analysis of the expression of the island genes in the different hosts compared to proper controls allowed identification of genes with genera-specific expression patterns. The data from the analysis can be arranged in a matrix to give an expression "array" of the island genes in the different bacterial backgrounds. A conserved 19-bp DNA site was found upstream of at least two of the differentially-expressed island genes. To our knowledge, this is the first systematic analysis of horizontally-transferred genomic island gene expression in a broad range of Gram negative hosts. We also present evidence in this study that the IS200 element found in island 4305 in S. typhimurium strain LT2 was inserted after the island had already been acquired by the S. typhimurium lineage and that this element is likely not

  20. Ascidian gene-expression profiles

    OpenAIRE

    William R Jeffery

    2002-01-01

    With the advent of gene-expression profiling, a large number of genes can now be investigated simultaneously during critical stages of development. This approach will be particularly informative in studies of ascidians, basal chordates whose genomes and embryology are uniquely suited for mapping developmental gene networks.

  1. Angiogenesis related gene expression profiles of EA.hy926 cells induced by irbesartan: a possible novel therapeutic approach

    Institute of Scientific and Technical Information of China (English)

    MA Cong; LU Xue-chun; LUO Yun; CAO Jian; YANG Bo; GAO Yan; LIU Xian-feng; FAN Li

    2012-01-01

    Background Angiogenesis occurs commonly in various physiological and pathological processes.Improving blood supply through promoting angiogenesis is a novel approach for treating ischemic diseases.Angiotensin Ⅱ type 1 receptor blockers (ARBs) dominate the management of hypertension,but evidence of their role in angiogenesis is contradictory.Here we explored the angiogenic effects of ARBs through characterizing gene expression of the human umbilical vein endothelial cell line EA.hy926 exposed to irbesartan.Methods The human umbilical vein endothelial cell line EA.hy926 was grown for 72 hours after treatment with different concentrations of irbesartan.The cell proliferative capacity was assessed by CCK8 assay at 24,48 and 72 hours.Gene expression levels in EA.hy926 cells responding to irbesartan were measured under optimal proliferation conditions by microarray analysis using Affymetrix U133 plus 2.0.The differential expression of genes involved in angiogenesis was identified through cluster analysis of the resulting microarray data.Quantitative RT-PCR and Western blotting analyses were used to validate differential gene expression related to the angiogenesis process.Results In the 10-4,10-5,10-6 mol/L treatment groups,cell proliferation studies revealed significantly increased proliferation in EA.hy926 cells after 24 hours of irbesartan treatment.However,after 48 and 72 hours of treatment with different concentrations of irbesartan,there was no significant difference in cell proliferation observed in any treatment group.We selected the group stimulated with irbersartan at a concentration of 10-6 mol/L for microarray experiments.Statistical analysis of the microarray data resulted in the identification of 56 gene transcripts whose expression patterns were significantly correlated,negatively or positively,with irbesartan treatment.Cluster analysis showed that these genes were involved in angiogenesis,extracellular stimulus,binding reactions and skeletal system

  2. A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Maud H W Starmans

    Full Text Available BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited.

  3. Swarm Intelligence Approach Based on Adaptive ELM Classifier with ICGA Selection for Microarray Gene Expression and Cancer Classification

    Directory of Open Access Journals (Sweden)

    T. Karthikeyan

    2014-05-01

    Full Text Available The aim of this research study is based on efficient gene selection and classification of microarray data analysis using hybrid machine learning algorithms. The beginning of microarray technology has enabled the researchers to quickly measure the position of thousands of genes expressed in an organic/biological tissue samples in a solitary experiment. One of the important applications of this microarray technology is to classify the tissue samples using their gene expression representation, identify numerous type of cancer. Cancer is a group of diseases in which a set of cells shows uncontrolled growth, instance that interrupts upon and destroys nearby tissues and spreading to other locations in the body via lymph or blood. Cancer has becomes a one of the major important disease in current scenario. DNA microarrays turn out to be an effectual tool utilized in molecular biology and cancer diagnosis. Microarrays can be measured to establish the relative quantity of mRNAs in two or additional organic/biological tissue samples for thousands/several thousands of genes at the same time. As the superiority of this technique become exactly analysis/identifying the suitable assessment of microarray data in various open issues. In the field of medical sciences multi-category cancer classification play a major important role to classify the cancer types according to the gene expression. The need of the cancer classification has been become indispensible, because the numbers of cancer victims are increasing steadily identified by recent years. To perform this proposed a combination of Integer-Coded Genetic Algorithm (ICGA and Artificial Bee Colony algorithm (ABC, coupled with an Adaptive Extreme Learning Machine (AELM, is used for gene selection and cancer classification. ICGA is used with ABC based AELM classifier to chose an optimal set of genes which results in an efficient hybrid algorithm that can handle sparse data and sample imbalance. The

  4. Classification of Micro Array Gene Expression Data using Factor Analysis Approach with Naïve Bayesian Classifier

    Directory of Open Access Journals (Sweden)

    Tamilselvi Madeswaran

    2013-10-01

    Full Text Available Microarray data studies produce large number of data and in order to analyze such large micro array data lies on Data mining or Statistical Analysis. Our objective is to classify the micro arraygene expression data. Usually before going for the classification the dimensionality reduction will be performed on the micro array gene expression dataset. A statistical approach for the extraction of thegene has been proposed. The drawback in the statistical analysis is that, it doesn’t identify the important genes. Here for the classification process we use k-nearest neighbor and SVM and Naïve Bayesian classifiers. From the experimental result our proposed classifiers show increase in the efficiency and accuracy.

  5. Dietary approaches to stop hypertension influence on insulin receptor substrate-1gene expression: A randomized controlled clinical trial

    Directory of Open Access Journals (Sweden)

    Marzieh Kafeshani

    2015-01-01

    Full Text Available Background: Insulin receptor substrate (IRS Type 1 is a main substrate for the insulin receptor, controls insulin signaling in skeletal muscle, adipose tissue, and the vascular, so it is an important candidate gene for insulin resistance (IR. We aimed to compare the effects of the Dietary Approaches to Stop Hypertension (DASH and Usual Dietary Advices (UDA on IRS1 gene expression in women at risk for cardiovascular disease. Materials and Methods: A randomized controlled clinical trial was performed in 44 women at risk for cardiovascular disease. Participants were randomly assigned to a UDA diet or the DASH diet. The DASH diet was rich in fruits, vegetables, whole grains, and low-fat dairy products and low in saturated fat, total fat, cholesterol, refined grains, and sweets, with a total of 2400 mg/day sodium. The UDA diet was a regular diet with healthy dietary advice. Gene expression was assessed by the real-time polymerase chain reaction at the first of study and after 12 weeks. Independent sample t-test and paired-samples t-test were used to compare means of all variables within and between two groups respectively. Results: IRS1 gene expression was increased in DASH group compared with UDA diet (P = 0.00. Weight and waist circumference decreased in DASH group significantly compared to the UDA group (P < 0.05 but the results between the two groups showed no significant difference. Conclusion: DASH diet increased IRS1 gene expression and probably has beneficial effects on IR risks.

  6. Unintended Changes in Genetically Modified Rice Expressing the Lysine-Rich Fusion Protein Gene Revealed by a Proteomics Approach

    Institute of Scientific and Technical Information of China (English)

    ZHAO Xiang-xiang; TANG Tang; LIU Fu-xia; LU Chang-li; HU Xiao-lan; JI Li-lian; LIU Qiao-quan

    2013-01-01

    Development of new technologies for evaluating genetically modiifed (GM) crops has revealed that there are unintended insertions and expression changes in GM crops. Proifling techniques are non-targeted approaches and are capable of detecting more unintended changes in GM crops. Here, we report the application of a comparative proteomic approach to investigate the protein proifle differences between a GM rice line, which has a lysine-rich protein gene, and its non-transgenic parental line. Proteome analysis by two-dimensional gel electrophoresis (2-DE) and mass spectrum analysis of the seeds identiifed 22 differentially expressed protein spots. Apart from a number of glutelins that were detected as targeted proteins in the GM line, the majority of the other changed proteins were involved in carbohydrate metabolism, protein synthesis and stress responses. These results indicated that the altered proteins were not associated with plant allergens or toxicity.

  7. An efficient approach to finding Siraitia grosvenorii triterpene biosynthetic genes by RNA-seq and digital gene expression analysis

    Directory of Open Access Journals (Sweden)

    Song Cai

    2011-07-01

    Full Text Available Abstract Background Siraitia grosvenorii (Luohanguo is an herbaceous perennial plant native to southern China and most prevalent in Guilin city. Its fruit contains a sweet, fleshy, edible pulp that is widely used in traditional Chinese medicine. The major bioactive constituents in the fruit extract are the cucurbitane-type triterpene saponins known as mogrosides. Among them, mogroside V is nearly 300 times sweeter than sucrose. However, little is known about mogrosides biosynthesis in S. grosvenorii, especially the late steps of the pathway. Results In this study, a cDNA library generated from of equal amount of RNA taken from S. grosvenorii fruit at 50 days after flowering (DAF and 70 DAF were sequenced using Illumina/Solexa platform. More than 48,755,516 high-quality reads from a cDNA library were generated that was assembled into 43,891 unigenes. De novo assembly and gap-filling generated 43,891 unigenes with an average sequence length of 668 base pairs. A total of 26,308 (59.9% unique sequences were annotated and 11,476 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. cDNA sequences for all of the known enzymes involved in mogrosides backbone synthesis were identified from our library. Additionally, a total of eighty-five cytochrome P450 (CYP450 and ninety UDP-glucosyltransferase (UDPG unigenes were identified, some of which appear to encode enzymes responsible for the conversion of the mogroside backbone into the various mogrosides. Digital gene expression profile (DGE analysis using Solexa sequencing was performed on three important stages of fruit development, and based on their expression pattern, seven CYP450s and five UDPGs were selected as the candidates most likely to be involved in mogrosides biosynthesis. Conclusion A combination of RNA-seq and DGE analysis based on the next generation sequencing technology was shown to be a powerful method for identifying

  8. Ecotoxicological diagnosis of striped dolphin (Stenella coeruleoalba) from the Mediterranean basin by skin biopsy and gene expression approach.

    Science.gov (United States)

    Panti, Cristina; Spinsanti, Giacomo; Marsili, Letizia; Casini, Silvia; Frati, Francesco; Fossi, Maria Cristina

    2011-11-01

    Mediterranean cetacean odontocetes are exposed to environmental stress, in particular to persistent organic pollutants, polycyclic aromatic hydrocarbons and trace elements. In the present study, the response of "gene-expression biomarkers" was evaluated in Mediterranean striped dolphin (Stenella coeruleoalba) skin biopsies collected in three sampling areas: Pelagos sanctuary (Ligurian sea), Ionian sea, and Strait of Gibraltar. The mRNA levels of five putative biomarker genes (aryl hydrocarbon receptor, E2F-1 transcription factor, cytochrome P450 1A, estrogen receptor 1, and heat shock protein 70) were measured for the first time by quantitative real-time PCR in cetacean skin biopsies. The different responses of most of the genes reflected contamination levels in the three sampling areas. Pelagos sanctuary dolphins appeared to be the most exposed to toxicological stress, having the highest up-regulation of CYP1A and AHR. Moreover, a cluster analysis distinguished the populations on the basis of the gene expression biomarker used in our study, showing different pattern between Mediterranean sea and Strait of Gibraltar. Our results suggest that this molecular approach applied to non-destructive biopsy material is a powerful diagnostic tool for evaluating ecotoxicological impact on cetacean populations. PMID:21695511

  9. Ecotoxicological diagnosis of striped dolphin (Stenella coeruleoalba) from the Mediterranean basin by skin biopsy and gene expression approach.

    Science.gov (United States)

    Panti, Cristina; Spinsanti, Giacomo; Marsili, Letizia; Casini, Silvia; Frati, Francesco; Fossi, Maria Cristina

    2011-11-01

    Mediterranean cetacean odontocetes are exposed to environmental stress, in particular to persistent organic pollutants, polycyclic aromatic hydrocarbons and trace elements. In the present study, the response of "gene-expression biomarkers" was evaluated in Mediterranean striped dolphin (Stenella coeruleoalba) skin biopsies collected in three sampling areas: Pelagos sanctuary (Ligurian sea), Ionian sea, and Strait of Gibraltar. The mRNA levels of five putative biomarker genes (aryl hydrocarbon receptor, E2F-1 transcription factor, cytochrome P450 1A, estrogen receptor 1, and heat shock protein 70) were measured for the first time by quantitative real-time PCR in cetacean skin biopsies. The different responses of most of the genes reflected contamination levels in the three sampling areas. Pelagos sanctuary dolphins appeared to be the most exposed to toxicological stress, having the highest up-regulation of CYP1A and AHR. Moreover, a cluster analysis distinguished the populations on the basis of the gene expression biomarker used in our study, showing different pattern between Mediterranean sea and Strait of Gibraltar. Our results suggest that this molecular approach applied to non-destructive biopsy material is a powerful diagnostic tool for evaluating ecotoxicological impact on cetacean populations.

  10. Gene Expression Omnibus (GEO)

    Data.gov (United States)

    U.S. Department of Health & Human Services — Gene Expression Omnibus is a public functional genomics data repository supporting MIAME-compliant submissions of array- and sequence-based data. Tools are provided...

  11. A Bayesian approach for decision making on the identification of genes with different expression levels: an application to Escherichia coli bacterium data.

    Science.gov (United States)

    Saraiva, Erlandson F; Louzada, Francisco; Milan, Luís A; Meira, Silvana; Cobre, Juliana

    2012-01-01

    A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially expressed. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating sequentially credibility intervals from predictive densities which are constructed using the sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained report evidence that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a well-known publicly available data set on Escherichia coli bacterium.

  12. A transgenic approach to control hemipteran insects by expressing insecticidal genes under phloem-specific promoters

    Science.gov (United States)

    Javaid, Shaista; Amin, Imran; Jander, Georg; Mukhtar, Zahid; Saeed, Nasir A.; Mansoor, Shahid

    2016-01-01

    The first generation transgenic crops used strong constitutive promoters for transgene expression. However, tissue-specific expression is desirable for more precise targeting of transgenes. Moreover, piercing/sucking insects, which are generally resistant to insecticidal Bacillus thuringiensis (Bt) proteins, have emerged as a major pests since the introduction of transgenic crops expressing these toxins. Phloem-specific promoters isolated from Banana bunchy top virus (BBTV) were used for the expression of two insecticidal proteins, Hadronyche versuta (Blue Mountains funnel-web spider) neurotoxin (Hvt) and onion leaf lectin, in tobacco (Nicotiana tabacum). Here we demonstrate that transgenic plants expressing Hvt alone or in combination with onion leaf lectin are resistant to Phenacoccus solenopsis (cotton mealybug), Myzus persicae (green peach aphids) and Bemisia tabaci (silver leaf whitefly). The expression of both proteins under different phloem-specific promoters resulted in close to 100% mortality and provided more rapid protection than Hvt alone. Our results suggest the employment of the Hvt and onion leaf lectin transgenic constructs at the commercial level will reduce the use of chemical pesticides for control of hemipteran insect pests. PMID:27708374

  13. Quality Measures for Gene Expression Biclusters

    OpenAIRE

    Beatriz Pontes; Ral Girldez; Aguilar-Ruiz, Jess S.

    2015-01-01

    An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Further...

  14. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

    A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...

  15. PR gene families of citrus: their organ specific-biotic and abiotic inducible expression profiles based on ESTs approach

    OpenAIRE

    Magnólia A. Campos; Daniel D. Rosa; Juliana Érika C. Teixeira; Maria Luisa P.N. Targon; De Souza, Alessandra A.; Paiva, Luciano V.; Dagmar R. Stach-Machado; Machado, Marcos A

    2007-01-01

    In silico expression profiles, of the discovered 3,103 citrus ESTs putatively encoding for PR protein families (PR-1 to PR-17), were evaluated using the Brazil citrus genome EST CitEST/database. Hierarchical clustering was displayed to identify similarities in expression patterns among citrus PR-like gene families (PRlgf) in 33 selected cDNA libraries. In this way, PRlgf preferentially expressed by organ and citrus species, and library conditions were highlighted. Changes in expression profil...

  16. Systems Biology as a Comparative Approach to Understand Complex Gene Expression in Neurological Diseases

    Directory of Open Access Journals (Sweden)

    Francisco J. Esteban

    2013-05-01

    Full Text Available Systems biology interdisciplinary approaches have become an essential analytical tool that may yield novel and powerful insights about the nature of human health and disease. Complex disorders are known to be caused by the combination of genetic, environmental, immunological or neurological factors. Thus, to understand such disorders, it becomes necessary to address the study of this complexity from a novel perspective. Here, we present a review of integrative approaches that help to understand the underlying biological processes involved in the etiopathogenesis of neurological diseases, for example, those related to autism and autism spectrum disorders (ASD endophenotypes. Furthermore, we highlight the role of systems biology in the discovery of new biomarkers or therapeutic targets in complex disorders, a key step in the development of personalized medicine, and we demonstrate the role of systems approaches in the design of classifiers that can shorten the time for behavioral diagnosis of autism.

  17. The approaches to mathematical modeling of recA, umuD genes expression in bacteria Escherichia coli after UV-irradiation

    International Nuclear Information System (INIS)

    The modern data of recA, umuD genes expression of the system of SOS-repair at classical object of radiation genetic researches - bacteria Escherichia coli, after ultraviolet irradiation are presented. Essentially a new method of analysis of SOS-genes expression is considered. It was shown that using this method it is possible to determine the character of induction of some SOS-genes more precisely. The possible approach to the mathematical description of SOS-response of cells by construction of the system of the differential equations is presented

  18. Decreased approach behavior and nucleus accumbens immediate early gene expression in response to Parkinsonian ultrasonic vocalizations in rats.

    Science.gov (United States)

    Pultorak, Joshua D; Kelm-Nelson, Cynthia A; Holt, Lauren R; Blue, Katherine V; Ciucci, Michelle R; Johnson, Aaron M

    2016-08-01

    Many individuals with Parkinson disease (PD) have difficulty producing normal speech and voice, resulting in problems with interpersonal communication and reduced quality of life. Translational animal models of communicative dysfunction have been developed to assess disease pathology. However, it is unknown whether acoustic feature changes associated with vocal production deficits in these animal models lead to compromised communication. In rodents, male ultrasonic vocalizations (USVs) have a well-established role in functional inter-sexual communication. To test whether acoustic deficits in USVs observed in a PTEN-induced putative kinase 1 (PINK1) knockout (KO) PD rat model compromise communication, we presented recordings of male PINK1 KO USVs and normal wild-type (WT) USVs to female rat listeners. We measured approached behavior and immediate early gene expression (c-Fos) in brain regions implicated in auditory processing and sexual motivation. Our results suggest that females show reduced approach in response to PINK1 KO USVs compared with WT. Moreover, females exposed to PINK1 KO USVs had lower c-Fos immunolabeling in the nucleus accumbens, a region implicated in sexual motivation. These results are the first to demonstrate that vocalization deficits in a rat PD model result in compromised communication. Thus, the PINK1 KO PD model may be valuable for assessing treatments aimed at restoring vocal communicative function. PMID:26313334

  19. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

    Directory of Open Access Journals (Sweden)

    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  20. Gene expression in the Parkinson's disease brain

    OpenAIRE

    Lewis, Patrick A.; Cookson, Mark R.

    2012-01-01

    The study of gene expression has undergone a transformation in the past decade as the benefits of the sequencing of the human genome have made themselves felt. Increasingly, genome wide approaches are being applied to the analysis of gene expression in human disease as a route to understanding the underlying pathogenic mechanisms. In this review, we will summarise current state of gene expression studies of the brain in Parkinson's disease, and examine how these techniques can be used to gain...

  1. Quality measures for gene expression biclusters.

    Science.gov (United States)

    Pontes, Beatriz; Girldez, Ral; Aguilar-Ruiz, Jess S

    2015-01-01

    An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Furthermore, most of biclustering approaches use a measure or cost function that determines the quality of biclusters. Having a suitable quality metric for bicluster is a critical aspect, not only for guiding the search, but also for establishing a comparison criteria among the results obtained by different biclustering techniques. In this paper, we analyse a large number of existing approaches to quality measures for gene expression biclusters, as well as we present a comparative study of them based on their capability to recognize different expression patterns in biclusters. PMID:25763839

  2. Synthetic promoter libraries- tuning of gene expression

    DEFF Research Database (Denmark)

    Hammer, Karin; Mijakovic, Ivan; Jensen, Peter Ruhdal

    2006-01-01

    be met by using promoter libraries. This approach generally consists of inserting a library of promoters in front of the gene to be studied, whereby the individual promoters might deviate either in their spacer sequences or bear slight deviations from the consensus sequence of a vegetative promoter. Here......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...... knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can...

  3. Positron emission tomography imaging of gene expression

    International Nuclear Information System (INIS)

    The merging of molecular biology and nuclear medicine is developed into molecular nuclear medicine. Positron emission tomography (PET) of gene expression in molecular nuclear medicine has become an attractive area. Positron emission tomography imaging gene expression includes the antisense PET imaging and the reporter gene PET imaging. It is likely that the antisense PET imaging will lag behind the reporter gene PET imaging because of the numerous issues that have not yet to be resolved with this approach. The reporter gene PET imaging has wide application into animal experimental research and human applications of this approach will likely be reported soon

  4. cis sequence effects on gene expression

    Directory of Open Access Journals (Sweden)

    Jacobs Kevin

    2007-08-01

    Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

  5. Global Identification of Significantly Expressed Genes in Developing Endosperm of Rice by Expression Sequence Tags and cDNA Array Approaches

    Institute of Scientific and Technical Information of China (English)

    Qichao Tu; Haitao Dong; Haigen Yao; Yongqi Fang; Cheng'en Dai; Hongmei Luo; Jian Yao; Dong Zhao; Debao Li

    2008-01-01

    Rice endosperm plays a very important role in seedling germination and determines the qualities of fice grain.Although studies on specific gene categories in endosperm have been carried out,global view of gene expression at a transcription level in rice endosperm is still limited.To gain a better understanding of the global and tissue-specific gene expression profiles in rice endosperm,a cDNA library from rice endosperm of immature seeds was sequenced.A cDNA array was constructed based on the tentative unique transcripts derived from expression sequence tag (EST) assembling results and then hybridized with cONAs from five different tissues or organs including endosperm,embryo,leaf,stem and root of rice.Significant redundancy was found for genes encoding prolamin,glutelin,allergen,and starch synthesis proteins,accounting for~34% of the total ESTs obtained.The cDNA array revealed 87 significantly expressed genes in endosperm compared with the other four organs or tissues.These genes included 13 prolamin family proteins,17 glutelin family proteins,12 binding proteins,nine catalytic proteins and four ribosomal proteins,indicating a complicated biological processing in rice endosperm.In addition,Northern verification of 1,4-alpha-glucan branching enzyme detected two isoforms in rice endosperm,the larger one of which only existed in endosperm.

  6. The transcriptional response in human umbilical vein endothelial cells exposed to insulin: a dynamic gene expression approach.

    Directory of Open Access Journals (Sweden)

    Barbara Di Camillo

    Full Text Available BACKGROUND: In diabetes chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation through the activation of the MAP kinases, which in turn regulate cellular proliferation. However, it is not known whether insulin itself could increase the transcription of specific genes for cellular proliferation in the endothelium. Hence, the characterization of transcriptional modifications in endothelium is an important step for a better understanding of the mechanism of insulin action and the relationship between endothelial cell dysfunction and insulin resistance. METHODOLOGY AND PRINCIPAL FINDINGS: The transcriptional response of endothelial cells in the 440 minutes following insulin stimulation was monitored using microarrays and compared to a control condition. About 1700 genes were selected as differentially expressed based on their treated minus control profile, thus allowing the detection of even small but systematic changes in gene expression. Genes were clustered in 7 groups according to their time expression profile and classified into 15 functional categories that can support the biological effects of insulin, based on Gene Ontology enrichment analysis. In terms of endothelial function, the most prominent processes affected were NADH dehydrogenase activity, N-terminal myristoylation domain binding, nitric-oxide synthase regulator activity and growth factor binding. Pathway-based enrichment analysis revealed "Electron Transport Chain" significantly enriched. Results were validated on genes belonging to "Electron Transport Chain" pathway, using quantitative RT-PCR. CONCLUSIONS: As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment. Since chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation

  7. Tumor-specific gene expression patterns with gene expression profiles

    Institute of Scientific and Technical Information of China (English)

    RUAN Xiaogang; LI Yingxin; LI Jiangeng; GONG Daoxiong; WANG Jinlian

    2006-01-01

    Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.

  8. A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression.

    Science.gov (United States)

    Smith, Ashley A; Huang, Yen-Tsung; Eliot, Melissa; Houseman, E Andres; Marsit, Carmen J; Wiencke, John K; Kelsey, Karl T

    2014-06-01

    Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.

  9. Detecting cognizable trends of gene expression in a time series RNA-sequencing experiment: a bootstrap approach

    Indian Academy of Sciences (India)

    SHATAKSHEE CHATTERJEE; PARTHA P. MAJUMDER; PRIYANKA PANDEY

    2016-09-01

    Study of temporal trajectory of gene expression is important. RNA sequencing is popular in genome-scale studies of transcription. Because of high expenses involved, many time-course RNA sequencing studies are challenged by inadequacy of sample sizes. This poses difficulties in conducting formal statistical tests of significance of null hypotheses. We propose a bootstrap algorithm to identify ‘cognizable’ ‘time-trends’ of gene expression. Properties of the proposed algorithm are derived using a simulation study. The proposed algorithm captured known ‘time-trends’ in the simulated data with a high probability of success, even when sample sizes were small (n<10). The proposed statistical method is efficient and robust to capture ‘cognizable’ ‘time-trends’ in RNA sequencing data.

  10. Imaging gene expression in gene therapy

    International Nuclear Information System (INIS)

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k+) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k+ gene expression where the H S V-1 t k+ gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([18 F]F H P G; [18 F]-A C V), and pyrimidine- ([123/131 I]I V R F U; [124/131I]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [123/131I]I V R F U imaging with the H S V-1 t k+ reporter gene will be presented

  11. Imaging gene expression in gene therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wiebe, Leonard I. [Alberta Univ., Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

    1997-12-31

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} gene expression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

  12. A gene sets approach for identifying prognostic gene signatures for outcome prediction

    OpenAIRE

    Kim Yong Sung; Kim Seon-Young

    2008-01-01

    Abstract Background Gene expression profiling is a promising approach to better estimate patient prognosis; however, there are still unresolved problems, including little overlap among similarly developed gene sets and poor performance of a developed gene set in other datasets. Results We applied a gene sets approach to develop a prognostic gene set from multiple gene expression datasets. By analyzing 12 independent breast cancer gene expression datasets comprising 1,756 tissues with 2,411 pr...

  13. A functional genomics approach using radiation-induced changes in gene expression to study low dose radiation effects in vitro and in vivo

    Energy Technology Data Exchange (ETDEWEB)

    Fornace, Jr, A J

    2007-03-03

    Abstract for final report for project entitled A functional genomics approach using radiation-induced changes in gene expression to study low dose radiation effects in vitro and in vivo which has been supported by the DOE Low Dose Radiation Research Program for approximately 7 years. This project has encompassed two sequential awards, ER62683 and then ER63308, in the Gene Response Section in the Center for Cancer Research at the National Cancer Institute. The project was temporarily suspended during the relocation of the Principal Investigators laboratory to the Dept. of Genetics and Complex Diseases at Harvard School of Public Health at the end of 2004. Remaining support for the final year was transferred to this new site later in 2005 and was assigned the DOE Award Number ER64065. The major aims of this project have been 1) to characterize changes in gene expression in response to low-dose radiation responses; this includes responses in human cells lines, peripheral blood lymphocytes (PBL), and in vivo after human or murine exposures, as well as the effect of dose-rate on gene responses; 2) to characterize changes in gene expression that may be involved in bystander effects, such as may be mediated by cytokines and other intercellular signaling proteins; and 3) to characterize responses in transgenic mouse models with relevance to genomic stability. A variety of approaches have been used to study transcriptional events including microarray hybridization, quantitative single-probe hybridization which was developed in this laboratory, quantitative RT-PCR, and promoter microarray analysis using genomic regulatory motifs. Considering the frequent responsiveness of genes encoding cytokines and related signaling proteins that can affect cellular metabolism, initial efforts were initiated to study radiation responses at the metabolomic level and to correlate with radiation-responsive gene expression. Productivity includes twenty-four published and in press manuscripts

  14. Homeobox gene expression in Brachiopoda

    DEFF Research Database (Denmark)

    Altenburger, Andreas; Martinez, Pedro; Wanninger, Andreas

    2011-01-01

    The molecular control that underlies brachiopod ontogeny is largely unknown. In order to contribute to this issue we analyzed the expression pattern of two homeobox containing genes, Not and Cdx, during development of the rhynchonelliform (i.e., articulate) brachiopod Terebratalia transversa....... Not is a homeobox containing gene that regulates the formation of the notochord in chordates, while Cdx (caudal) is a ParaHox gene involved in the formation of posterior tissues of various animal phyla. The T. transversa homolog, TtrNot, is expressed in the ectoderm from the beginning of gastrulation until...... formation. TtrNot expression is absent in unfertilized eggs, in embryos prior to gastrulation, and in settled individuals during and after metamorphosis. Comparison with the expression patterns of Not genes in other metazoan phyla suggests an ancestral role for this gene in gastrulation and germ layer...

  15. Approaches to systems biology. Four methods to study single-cell gene expression, cell motility, antibody reactivity, and respiratory metabolism

    DEFF Research Database (Denmark)

    Hagedorn, Peter

    To understand how complex systems, such as cells, function, comprehensive Measurements of their constituent parts must be made. This can be achieved by combining methods that are each optimized to measure specific parts of the system. Four such methods,each covering a different area, are presented......: Transcript profiling of one cell type extracted from a complex tissue containing several cell types; observation and recording of cell motility; measurement of antibody reactivities using microarrays; and invivo measurement of free and bound NADH in mitochondria. Detailed statistical analysis of the data...... from such measurements allows models of the system to be developed and tested. For each of the methods, such analysis and modelling approaches have beenapplied and are presented: Differentially regulated genes are identified and classified according to function; cell-specfic motility models...

  16. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

    Science.gov (United States)

    Perualila-Tan, Nolen; Kasim, Adetayo; Talloen, Willem; Verbist, Bie; Göhlmann, Hinrich W H; Shkedy, Ziv

    2016-08-01

    The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery. PMID:27269248

  17. Quality measures for gene expression biclusters.

    Directory of Open Access Journals (Sweden)

    Beatriz Pontes

    Full Text Available An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Furthermore, most of biclustering approaches use a measure or cost function that determines the quality of biclusters. Having a suitable quality metric for bicluster is a critical aspect, not only for guiding the search, but also for establishing a comparison criteria among the results obtained by different biclustering techniques. In this paper, we analyse a large number of existing approaches to quality measures for gene expression biclusters, as well as we present a comparative study of them based on their capability to recognize different expression patterns in biclusters.

  18. Shuffling Yeast Gene Expression Data

    OpenAIRE

    Bilke, Sven

    2000-01-01

    A new method to sort gene expression patterns into functional groups is presented. The method is based on a sorting algorithm using a non-local similarity score, which takes all other patterns in the dataset into account. The method is therefore very robust with respect to noise. Using the expression data for yeast, we extract information about functional groups. Without prior knowledge of parameters the cell cycle regulated genes in yeast can be identified. Furthermore a second, independent ...

  19. Vascular gene expression: a hypothesis

    OpenAIRE

    Martínez-Navarro, Angélica C.; Galván-Gordillo, Santiago V.; Xoconostle-Cázares, Beatriz; Ruiz-Medrano, Roberto

    2013-01-01

    The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular ti...

  20. Mining Association Rules among Gene Functions in Clusters of Similar Gene Expression Maps

    OpenAIRE

    An, Li; Obradovic, Zoran; Smith, Desmond; Bodenreider, Olivier; Megalooikonomou, Vasileios

    2009-01-01

    Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules ...

  1. The acute impact of polyphenols from Hibiscus sabdariffa in metabolic homeostasis: an approach combining metabolomics and gene-expression analyses.

    Science.gov (United States)

    Beltrán-Debón, Raúl; Rodríguez-Gallego, Esther; Fernández-Arroyo, Salvador; Senan-Campos, Oriol; Massucci, Francesco A; Hernández-Aguilera, Anna; Sales-Pardo, Marta; Guimerà, Roger; Camps, Jordi; Menendez, Javier A; Joven, Jorge

    2015-09-01

    We explored the acute multifunctional effects of polyphenols from Hibiscus sabdariffa in humans to assess possible consequences on the host's health. The expected dynamic response was studied using a combination of transcriptomics and metabolomics to integrate specific functional pathways through network-based methods and to generate hypotheses established by acute metabolic effects and/or modifications in the expression of relevant genes. Data were obtained from healthy male volunteers after 3 hours of ingestion of an aqueous Hibiscus sabdariffa extract. The data were compared with data obtained prior to the ingestion, and the overall findings suggest that these particular polyphenols had a simultaneous role in mitochondrial function, energy homeostasis and protection of the cardiovascular system. These findings suggest beneficial actions in inflammation, endothelial dysfunction, and oxidation, which are interrelated mechanisms. Among other effects, the activation of the heme oxygenase-biliverdin reductase axis, the systemic inhibition of the renin-angiotensin system, the inhibition of the angiotensin-converting enzyme, and several actions mirroring those of the peroxisome proliferator-activated receptor agonists further support this notion. We also found concordant findings in the serum of the participants, which include a decrease in cortisol levels and a significant increase in the active vasodilator metabolite of bradykinin (des-Arg(9)-bradykinin). Therefore, our data support the view that polyphenols from Hibiscus sabdariffa play a regulatory role in metabolic health and in the maintenance of blood pressure, thus implying a multi-faceted impact in metabolic and cardiovascular diseases. PMID:26234931

  2. Application of multidisciplinary analysis to gene expression.

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xuefel (University of New Mexico, Albuquerque, NM); Kang, Huining (University of New Mexico, Albuquerque, NM); Fields, Chris (New Mexico State University, Las Cruces, NM); Cowie, Jim R. (New Mexico State University, Las Cruces, NM); Davidson, George S.; Haaland, David Michael; Sibirtsev, Valeriy (New Mexico State University, Las Cruces, NM); Mosquera-Caro, Monica P. (University of New Mexico, Albuquerque, NM); Xu, Yuexian (University of New Mexico, Albuquerque, NM); Martin, Shawn Bryan; Helman, Paul (University of New Mexico, Albuquerque, NM); Andries, Erik (University of New Mexico, Albuquerque, NM); Ar, Kerem (University of New Mexico, Albuquerque, NM); Potter, Jeffrey (University of New Mexico, Albuquerque, NM); Willman, Cheryl L. (University of New Mexico, Albuquerque, NM); Murphy, Maurice H. (University of New Mexico, Albuquerque, NM)

    2004-01-01

    Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from

  3. Correction of gene expression data

    DEFF Research Database (Denmark)

    Darbani Shirvanehdeh, Behrooz; Stewart, C. Neal, Jr.; Noeparvar, Shahin;

    2014-01-01

    This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies....... For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce...

  4. CHROMATIN LOOPS, GENE POSITIONING AND GENE EXPRESSION

    Directory of Open Access Journals (Sweden)

    Sjoerd eHolwerda

    2012-10-01

    Full Text Available Technological developments and intense research over the last years have led to a better understanding of the three-dimensional structure of the genome and its influence on genome function inside the cell nucleus. We will summarize topological studies performed on four model gene loci: the α- and β-globin gene loci, the antigen receptor loci, the imprinted H19-Igf2 locus and the Hox gene clusters. Collectively, these studies show that regulatory DNA sequences physically contact genes to control their transcription. Proteins set up the three-dimensional configuration of the genome and we will discuss the roles of the key structural organizers CTCF and cohesin, the nuclear lamina and the transcription machinery. Finally, genes adopt non-random positions in the nuclear interior. We will review studies on gene positioning and propose that cell-specific genome conformations can juxtapose a regulatory sequence on one chromosome to a responsive gene on another chromosome to cause altered gene expression in subpopulations of cells.

  5. Shuffling Yeast Gene Expression Data

    CERN Document Server

    Bilke, S

    2000-01-01

    A new method to sort gene expression patterns into functional groups is presented. The method is based on a sorting algorithm using a non-local similarity score, which takes all other patterns in the dataset into account. The method is therefore very robust with respect to noise. Using the expression data for yeast, we extract information about functional groups. Without prior knowledge of parameters the cell cycle regulated genes in yeast can be identified. Furthermore a second, independent cell clock is identified. The capability of the algorithm to extract information about signal flow in the regulatory network underlying the expression patterns is demonstrated.

  6. Gene expression in colorectal cancer

    DEFF Research Database (Denmark)

    Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder;

    2002-01-01

    Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...... known genes and 157 ESTs were found to be highly relevant for CRC. The alteration of known genes was confirmed in >70% of the cases by array analysis of 25 single samples. Two-way hierarchical average linkage cluster analysis clustered normal tissue together with Dukes' A, clustered Dukes' B with Dukes...

  7. Transgenic Arabidopsis Gene Expression System

    Science.gov (United States)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

    The Transgenic Arabidopsis Gene Expression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

  8. Zipf's Law in Gene Expression

    CERN Document Server

    Furusawa, C; Furusawa, Chikara; Kaneko, Kunihiko

    2002-01-01

    Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1, i.e., they obey Zipf's law. Furthermore, by simulations of a simple model with an intra-cellular reaction network, we found that Zipf's law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

  9. Gene expression profiles in irradiated cancer cells

    Science.gov (United States)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C.

    2013-07-01

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.

  10. Gene expression profiles in irradiated cancer cells

    International Nuclear Information System (INIS)

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses

  11. Human papillomavirus gene expression

    International Nuclear Information System (INIS)

    To determine the role of tissue differentiation on expression of each of the papillomavirus mRNA species identified by electron microscopy, the authors prepared exon-specific RNA probes that could distinguish the alternatively spliced mRNA species. Radioactively labeled single-stranded RNA probes were generated from a dual promoter vector system and individually hybridized to adjacent serial sections of formalin-fixed, paraffin-embedded biopsies of condylomata. Autoradiography showed that each of the message species had a characteristic tissue distribution and relative abundance. The authors have characterized a portion of the regulatory network of the HPVs by showing that the E2 ORF encodes a trans-acting enhancer-stimulating protein, as it does in BPV-1 (Spalholz et al. 1985). The HPV-11 enhancer was mapped to a 150-bp tract near the 3' end of the URR. Portions of this region are duplicated in some aggressive strains of HPV-6 (Boshart and zur Hausen 1986; Rando et al. 1986). To test the possible biological relevance of these duplications, they cloned tandem arrays of the enhancer and demonstrated, using a chloramphenicol acetyltransferase (CAT) assay, that they led to dramatically increased transcription proportional to copy number. Using the CAT assays, the authors found that the E2 proteins of several papillomavirus types can cross-stimulate the enhancers of most other types. This suggests that prior infection of a tissue with one papillomavirus type may provide a helper effect for superinfection and might account fo the HPV-6/HPV-16 coinfections in condylomata that they have observed

  12. Identifying Gene Interaction Enrichment for Gene Expression Data

    OpenAIRE

    Jigang Zhang; Jian Li; Hong-Wen Deng

    2009-01-01

    Gene set analysis allows the inclusion of knowledge from established gene sets, such as gene pathways, and potentially improves the power of detecting differentially expressed genes. However, conventional methods of gene set analysis focus on gene marginal effects in a gene set, and ignore gene interactions which may contribute to complex human diseases. In this study, we propose a method of gene interaction enrichment analysis, which incorporates knowledge of predefined gene sets (e.g. gene ...

  13. Identifying Driver Genes in Cancer by Triangulating Gene Expression, Gene Location, and Survival Data

    Science.gov (United States)

    Rouam, Sigrid; Miller, Lance D; Karuturi, R Krishna Murthy

    2014-01-01

    Driver genes are directly responsible for oncogenesis and identifying them is essential in order to fully understand the mechanisms of cancer. However, it is difficult to delineate them from the larger pool of genes that are deregulated in cancer (ie, passenger genes). In order to address this problem, we developed an approach called TRIAngulating Gene Expression (TRIAGE through clinico-genomic intersects). Here, we present a refinement of this approach incorporating a new scoring methodology to identify putative driver genes that are deregulated in cancer. TRIAGE triangulates – or integrates – three levels of information: gene expression, gene location, and patient survival. First, TRIAGE identifies regions of deregulated expression (ie, expression footprints) by deriving a newly established measure called the Local Singular Value Decomposition (LSVD) score for each locus. Driver genes are then distinguished from passenger genes using dual survival analyses. Incorporating measurements of gene expression and weighting them according to the LSVD weight of each tumor, these analyses are performed using the genes located in significant expression footprints. Here, we first use simulated data to characterize the newly established LSVD score. We then present the results of our application of this refined version of TRIAGE to gene expression data from five cancer types. This refined version of TRIAGE not only allowed us to identify known prominent driver genes, such as MMP1, IL8, and COL1A2, but it also led us to identify several novel ones. These results illustrate that TRIAGE complements existing tools, allows for the identification of genes that drive cancer and could perhaps elucidate potential future targets of novel anticancer therapeutics. PMID:25949096

  14. Vascular Gene Expression: A Hypothesis

    Directory of Open Access Journals (Sweden)

    Angélica Concepción eMartínez-Navarro

    2013-07-01

    Full Text Available The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular tissues. This tissue-specific expression in Arabidopsis is predicted by the overrepresentation of GA/CT-rich motifs in gene promoters. In this work we have searched for common motifs in upstream regions of the homologous genes from plants considered to possess a primitive vascular tissue (a lycophyte, as well as from others that lack a true vascular tissue (a bryophyte, and finally from chlorophytes. Both lycophyte and bryophyte display motifs similar to those found in Arabidopsis with a significantly low E-value, while the chlorophytes showed either a different conserved motif or no conserved motif at all. These results suggest that these same genes are expressed coordinately in non- vascular plants; this coordinate expression may have been one of the prerequisites for the development of conducting tissues in plants. We have also analyzed the phylogeny of conserved proteins that may be involved in phloem function and development. The presence of CmPP16, APL, FT and YDA in chlorophytes suggests the recruitment of ancient regulatory networks for the development of the vascular tissue during evolution while OPS is a novel protein specific to vascular plants.

  15. Analysis of multiplex gene expression maps obtained by voxelation

    Directory of Open Access Journals (Sweden)

    Smith Desmond J

    2009-04-01

    Full Text Available Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

  16. Gene expression profile of pulpitis.

    Science.gov (United States)

    Galicia, J C; Henson, B R; Parker, J S; Khan, A A

    2016-06-01

    The cost, prevalence and pain associated with endodontic disease necessitate an understanding of the fundamental molecular aspects of its pathogenesis. This study was aimed to identify the genetic contributors to pulpal pain and inflammation. Inflamed pulps were collected from patients diagnosed with irreversible pulpitis (n=20). Normal pulps from teeth extracted for various reasons served as controls (n=20). Pain level was assessed using a visual analog scale (VAS). Genome-wide microarray analysis was performed using Affymetrix GeneTitan Multichannel Instrument. The difference in gene expression levels were determined by the significance analysis of microarray program using a false discovery rate (q-value) of 5%. Genes involved in immune response, cytokine-cytokine receptor interaction and signaling, integrin cell surface interactions, and others were expressed at relatively higher levels in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (⩾30 mm on VAS) compared with those with moderate to severe pain. This exploratory study provides a molecular basis for the clinical diagnosis of pulpitis. With an enhanced understanding of pulpal inflammation, future studies on treatment and management of pulpitis and on pain associated with it can have a biological reference to bridge treatment strategies with pulpal biology. PMID:27052691

  17. Gene Expression in Trypanosomatid Parasites

    Directory of Open Access Journals (Sweden)

    Santiago Martínez-Calvillo

    2010-01-01

    Full Text Available The parasites Leishmania spp., Trypanosoma brucei, and Trypanosoma cruzi are the trypanosomatid protozoa that cause the deadly human diseases leishmaniasis, African sleeping sickness, and Chagas disease, respectively. These organisms possess unique mechanisms for gene expression such as constitutive polycistronic transcription of protein-coding genes and trans-splicing. Little is known about either the DNA sequences or the proteins that are involved in the initiation and termination of transcription in trypanosomatids. In silico analyses of the genome databases of these parasites led to the identification of a small number of proteins involved in gene expression. However, functional studies have revealed that trypanosomatids have more general transcription factors than originally estimated. Many posttranslational histone modifications, histone variants, and chromatin modifying enzymes have been identified in trypanosomatids, and recent genome-wide studies showed that epigenetic regulation might play a very important role in gene expression in this group of parasites. Here, we review and comment on the most recent findings related to transcription initiation and termination in trypanosomatid protozoa.

  18. Gene Expression Data Knowledge Discovery using Global and Local Clustering

    OpenAIRE

    H, Swathi.

    2010-01-01

    To understand complex biological systems, the research community has produced huge corpus of gene expression data. A large number of clustering approaches have been proposed for the analysis of gene expression data. However, extracting important biological knowledge is still harder. To address this task, clustering techniques are used. In this paper, hybrid Hierarchical k-Means algorithm is used for clustering and biclustering gene expression data is used. To discover both local and global cl...

  19. A NGS approach to the encrusting Mediterranean sponge Crella elegans (Porifera, Demospongiae, Poecilosclerida): transcriptome sequencing, characterization and overview of the gene expression along three life cycle stages.

    Science.gov (United States)

    Pérez-Porro, A R; Navarro-Gómez, D; Uriz, M J; Giribet, G

    2013-05-01

    Sponges can be dominant organisms in many marine and freshwater habitats where they play essential ecological roles. They also represent a key group to address important questions in early metazoan evolution. Recent approaches for improving knowledge on sponge biological and ecological functions as well as on animal evolution have focused on the genetic toolkits involved in ecological responses to environmental changes (biotic and abiotic), development and reproduction. These approaches are possible thanks to newly available, massive sequencing technologies-such as the Illumina platform, which facilitate genome and transcriptome sequencing in a cost-effective manner. Here we present the first NGS (next-generation sequencing) approach to understanding the life cycle of an encrusting marine sponge. For this we sequenced libraries of three different life cycle stages of the Mediterranean sponge Crella elegans and generated de novo transcriptome assemblies. Three assemblies were based on sponge tissue of a particular life cycle stage, including non-reproductive tissue, tissue with sperm cysts and tissue with larvae. The fourth assembly pooled the data from all three stages. By aggregating data from all the different life cycle stages we obtained a higher total number of contigs, contigs with blast hit and annotated contigs than from one stage-based assemblies. In that multi-stage assembly we obtained a larger number of the developmental regulatory genes known for metazoans than in any other assembly. We also advance the differential expression of selected genes in the three life cycle stages to explore the potential of RNA-seq for improving knowledge on functional processes along the sponge life cycle.

  20. Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data

    Science.gov (United States)

    Moignard, Victoria; Göttgens, Berthold; Adryan, Boris

    2016-01-01

    Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete pipeline for the analysis of single cell qPCR data that uses the mathematics behind bursty expression to develop more accurate and robust algorithms for analyzing the origin of heterogeneity in experimental samples, specifically an algorithm for clustering cells by their bursting behavior (Simulated Annealing for Bursty Expression Clustering, SABEC) and a statistical tool for comparing the kinetic parameters of bursty expression across populations of cells (Estimation of Parameter changes in Kinetics, EPiK). We applied these methods to hematopoiesis, including a new single cell dataset in which transcription factors (TFs) involved in the earliest branchpoint of blood differentiation were individually up- and down-regulated. We could identify two unique sub-populations within a seemingly homogenous group of hematopoietic stem cells. In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. Detailed information about gene regulatory mechanisms can therefore be obtained simply from high throughput single cell gene expression data, which should be widely applicable given the rapid expansion of single cell genomics. PMID:27551778

  1. The Gene Expression Omnibus Database.

    Science.gov (United States)

    Clough, Emily; Barrett, Tanya

    2016-01-01

    The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

  2. The Gene Expression Omnibus database

    Science.gov (United States)

    Clough, Emily; Barrett, Tanya

    2016-01-01

    The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

  3. A systematic screen for genes expressed in definitive endoderm by Serial Analysis of Gene Expression (SAGE

    Directory of Open Access Journals (Sweden)

    Jones Steven JM

    2007-08-01

    Full Text Available Abstract Background The embryonic definitive endoderm (DE gives rise to organs of the gastrointestinal and respiratory tract including the liver, pancreas and epithelia of the lung and colon. Understanding how DE progenitor cells generate these tissues is critical to understanding the cause of visceral organ disorders and cancers, and will ultimately lead to novel therapies including tissue and organ regeneration. However, investigation into the molecular mechanisms of DE differentiation has been hindered by the lack of early DE-specific markers. Results We describe the identification of novel as well as known genes that are expressed in DE using Serial Analysis of Gene Expression (SAGE. We generated and analyzed three longSAGE libraries from early DE of murine embryos: early whole definitive endoderm (0–6 somite stage, foregut (8–12 somite stage, and hindgut (8–12 somite stage. A list of candidate genes enriched for expression in endoderm was compiled through comparisons within these three endoderm libraries and against 133 mouse longSAGE libraries generated by the Mouse Atlas of Gene Expression Project encompassing multiple embryonic tissues and stages. Using whole mount in situ hybridization, we confirmed that 22/32 (69% genes showed previously uncharacterized expression in the DE. Importantly, two genes identified, Pyy and 5730521E12Rik, showed exclusive DE expression at early stages of endoderm patterning. Conclusion The high efficiency of this endoderm screen indicates that our approach can be successfully used to analyze and validate the vast amount of data obtained by the Mouse Atlas of Gene Expression Project. Importantly, these novel early endoderm-expressing genes will be valuable for further investigation into the molecular mechanisms that regulate endoderm development.

  4. Comparative genomics of the relationship between gene structure and expression

    NARCIS (Netherlands)

    Ren, X.

    2006-01-01

    The relationship between the structure of genes and their expression is a relatively new aspect of genome organization and regulation. With more genome sequences and expression data becoming available, bioinformatics approaches can help the further elucidation of the relationships between gene struc

  5. Mitochondrial RNA granules: Compartmentalizing mitochondrial gene expression.

    Science.gov (United States)

    Jourdain, Alexis A; Boehm, Erik; Maundrell, Kinsey; Martinou, Jean-Claude

    2016-03-14

    In mitochondria, DNA replication, gene expression, and RNA degradation machineries coexist within a common nondelimited space, raising the question of how functional compartmentalization of gene expression is achieved. Here, we discuss the recently characterized "mitochondrial RNA granules," mitochondrial subdomains with an emerging role in the regulation of gene expression. PMID:26953349

  6. Genomic Imbalances in Rhabdomyosarcoma Cell Lines Affect Expression of Genes Frequently Altered in Primary Tumors: An Approach to Identify Candidate Genes Involved in Tumor Development

    NARCIS (Netherlands)

    E. Missiaglia; J. Selfe; M. Hamdi; D. Williamson; G. Schaaf; C. Fang; J. Koster; B. Summersgill; B. Messahel; R Versteeg; K. Pritchard-Jones; M. Kool; J. Shipley

    2009-01-01

    Rhabdomyosarcomas (RMS) are the most common pediatric soft tissue sarcomas. They resemble developing skeletal muscle and are histologically divided into two main subtypes; alveolar and embryonal RMS. Characteristic genomic aberrations, including the PAX3- and PAX7-FOXO1 fusion genes in alveolar case

  7. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions. Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  8. Effective Clustering Algorithms for Gene Expression Data

    CERN Document Server

    Chandrasekhar, T; Elayaraja, E

    2012-01-01

    Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. Identification of co-expressed genes and coherent patterns is the central goal in microarray or gene expression data analysis and is an important task in Bioinformatics research. In this paper, K-Means algorithm hybridised with Cluster Centre Initialization Algorithm (CCIA) is proposed Gene Expression Data. The proposed algorithm overcomes the drawbacks of specifying the number of clusters in the K-Means methods. Experimental analysis shows that the proposed method performs well on gene Expression Data when compare with the traditional K- Means clustering and Silhouette Coefficients cluster measure.

  9. Correlating Expression Data with Gene Function Using Gene Ontology

    Institute of Scientific and Technical Information of China (English)

    LIU,Qi; DENG,Yong; WANG,Chuan; SHI,Tie-Liu; LI,Yi-Xue

    2006-01-01

    Clustering is perhaps one of the most widely used tools for microarray data analysis. Proposed roles for genes of unknown function are inferred from clusters of genes similarity expressed across many biological conditions.However, whether function annotation by similarity metrics is reliable or not and to what extent the similarity in gene expression patterns is useful for annotation of gene functions, has not been evaluated. This paper made a comprehensive research on the correlation between the similarity of expression data and of gene functions using Gene Ontology. It has been found that although the similarity in expression patterns and the similarity in gene functions are significantly dependent on each other, this association is rather weak. In addition, among the three categories of Gene Ontology, the similarity of expression data is more useful for cellular component annotation than for biological process and molecular function. The results presented are interesting for the gene functions prediction research area.

  10. Gene expression analysis identifies global gene dosage sensitivity in cancer

    DEFF Research Database (Denmark)

    Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata;

    2015-01-01

    Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gene...... expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles...... for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying...

  11. Gene expression signatures for colorectal cancer microsatellite status and HNPCC

    DEFF Research Database (Denmark)

    Kruhøffer, M; Jensen, J L; Laiho, P;

    2005-01-01

    is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene expression......-deficient tumours into sporadic MSI and HNPCC cases, and validated this by a mathematical cross-validation approach. The demonstration that this two-step classification approach can identify MSI as well as HNPCC cases merits further gene expression studies to identify prognostic signatures....

  12. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  13. Quantitative Real Time PCR approach to study gene expression profile during prenatal growth of skeletal muscle in pig of Duroc and Pietrain breeds

    Directory of Open Access Journals (Sweden)

    M. Cagnazzo

    2010-01-01

    Full Text Available The quantitative real time-PCR (QRT-PCR is a very sensitive method used to quantify mRNA level in gene expression analysis. Combining amplification, detection and quantification in a single step, allows a more accurate measurement compared to the traditional PCR end point analysis (Pfaffl, 2001; Bustin, 2002.

  14. Daunomycin-TFO Conjugates for Downregulation of Gene Expression

    Science.gov (United States)

    Capobianco, Massimo L.; Catapano, Carlo V.

    Daunomycin has shown interesting properties as a stabilizing agent for the antigene methodology. This approach consists of targeting a polypurine region of a given gene, with a triplex forming oligonucleotide (TFO), realizing a triple helix complex (triplex), with the aim of down-regulating gene expression. This chapter describes the basic principles of the triplex approach, the chemistry underlining the binding of daunomycin to oligonucleotides, and some results of gene-inhibition obtained with daunomycin-TFO conjugates with different targets.

  15. A comparative expression analysis of gene transcripts in brain tissue of non-transgenic and GH-transgenic zebrafish (Danio rerio using a DDRT-PCR approach

    Directory of Open Access Journals (Sweden)

    Fernanda A. Alves-Costa

    2012-06-01

    Full Text Available The presence of higher level of exogenous growth hormone (GH in transgenic animals could lead to several physiological alterations. A GH transgenic zebrafish (Danio rerio line was compared to nontransgenic (NT samples of the species through a DDRT-PCR approach, with the goal of identifying candidate differentially expressed transcripts in brain tissues that could be involved in GH overexpression. Densitometric analyses of two selected amplification products, p300 and ADCY2, pointed to a significant lower gene expression in the transgenic zebrafish (104.02 ± 57.71; 224.10 ± 91.73 when compared to NT samples (249.75 ± 30.08; 342.95 ± 65.19. The present data indicate that p300 and ADCY2 are involved in a regulation system for GH when high circulating levels of this hormone are found in zebrafishes.A presença de níveis mais elevados do hormônio de crescimento (GH em animais transgênicos poderia levar a várias alterações fisiológicas. Uma linhagem transgênica de paulistinha (Danio rerio para o GH foi comparada com amostras não transgênicas (NT desta espécie, através de uma abordagem de DDRT-PCR, com o objetivo de identificar transcritos candidatos diferencialmente expressos em tecido cerebral que poderiam estar envolvidos na superexpressão de GH. Análises densitométricas de dois produtos de amplificação selecionados, p300 e ADCY2, apontaram uma expressão gênica significativamente menor nas amostras transgênicas de paulistinha (104.02 ± 57.71; 224.10 ± 91.73, quando comparadas com as amostras NT (249.75 ± 30.08; 342.95±65.19. Os presentes dados indicam que p300 e ADCY2 estão envolvidos em um sistema de regulação do GH, quando altos níveis circulantes desse hormônio são encontrados em paulistinha.

  16. Cross-platform prediction of gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Shu-Hong Lin

    Full Text Available Gene expression signatures can predict the activation of oncogenic pathways and other phenotypes of interest via quantitative models that combine the expression levels of multiple genes. However, as the number of platforms to measure genome-wide gene expression proliferates, there is an increasing need to develop models that can be ported across diverse platforms. Because of the range of technologies that measure gene expression, the resulting signal values can vary greatly. To understand how this variation can affect the prediction of gene expression signatures, we have investigated the ability of gene expression signatures to predict pathway activation across Affymetrix and Illumina microarrays. We hybridized the same RNA samples to both platforms and compared the resultant gene expression readings, as well as the signature predictions. Using a new approach to map probes across platforms, we found that the genes in the signatures from the two platforms were highly similar, and that the predictions they generated were also strongly correlated. This demonstrates that our method can map probes from Affymetrix and Illumina microarrays, and that this mapping can be used to predict gene expression signatures across platforms.

  17. RNAi and Homologous Over-Expression Based Functional Approaches Reveal Triterpenoid Synthase Gene-Cycloartenol Synthase Is Involved in Downstream Withanolide Biosynthesis in Withania somnifera.

    Directory of Open Access Journals (Sweden)

    Smrati Mishra

    Full Text Available Withania somnifera Dunal, is one of the most commonly used medicinal plant in Ayurvedic and indigenous medicine traditionally owing to its therapeutic potential, because of major chemical constituents, withanolides. Withanolide biosynthesis requires the activities of several enzymes in vivo. Cycloartenol synthase (CAS is an important enzyme in the withanolide biosynthetic pathway, catalyzing cyclization of 2, 3 oxidosqualene into cycloartenol. In the present study, we have cloned full-length WsCAS from Withania somnifera by homology-based PCR method. For gene function investigation, we constructed three RNAi gene-silencing constructs in backbone of RNAi vector pGSA and a full-length over-expression construct. These constructs were transformed in Agrobacterium strain GV3101 for plant transformation in W. somnifera. Molecular and metabolite analysis was performed in putative Withania transformants. The PCR and Southern blot results showed the genomic integration of these RNAi and overexpression construct(s in Withania genome. The qRT-PCR analysis showed that the expression of WsCAS gene was considerably downregulated in stable transgenic silenced Withania lines compared with the non-transformed control and HPLC analysis showed that withanolide content was greatly reduced in silenced lines. Transgenic plants over expressing CAS gene displayed enhanced level of CAS transcript and withanolide content compared to non-transformed controls. This work is the first full proof report of functional validation of any metabolic pathway gene in W. somnifera at whole plant level as per our knowledge and it will be further useful to understand the regulatory role of different genes involved in the biosynthesis of withanolides.

  18. RNAi and Homologous Over-Expression Based Functional Approaches Reveal Triterpenoid Synthase Gene-Cycloartenol Synthase Is Involved in Downstream Withanolide Biosynthesis in Withania somnifera.

    Science.gov (United States)

    Mishra, Smrati; Bansal, Shilpi; Mishra, Bhawana; Sangwan, Rajender Singh; Asha; Jadaun, Jyoti Singh; Sangwan, Neelam S

    2016-01-01

    Withania somnifera Dunal, is one of the most commonly used medicinal plant in Ayurvedic and indigenous medicine traditionally owing to its therapeutic potential, because of major chemical constituents, withanolides. Withanolide biosynthesis requires the activities of several enzymes in vivo. Cycloartenol synthase (CAS) is an important enzyme in the withanolide biosynthetic pathway, catalyzing cyclization of 2, 3 oxidosqualene into cycloartenol. In the present study, we have cloned full-length WsCAS from Withania somnifera by homology-based PCR method. For gene function investigation, we constructed three RNAi gene-silencing constructs in backbone of RNAi vector pGSA and a full-length over-expression construct. These constructs were transformed in Agrobacterium strain GV3101 for plant transformation in W. somnifera. Molecular and metabolite analysis was performed in putative Withania transformants. The PCR and Southern blot results showed the genomic integration of these RNAi and overexpression construct(s) in Withania genome. The qRT-PCR analysis showed that the expression of WsCAS gene was considerably downregulated in stable transgenic silenced Withania lines compared with the non-transformed control and HPLC analysis showed that withanolide content was greatly reduced in silenced lines. Transgenic plants over expressing CAS gene displayed enhanced level of CAS transcript and withanolide content compared to non-transformed controls. This work is the first full proof report of functional validation of any metabolic pathway gene in W. somnifera at whole plant level as per our knowledge and it will be further useful to understand the regulatory role of different genes involved in the biosynthesis of withanolides.

  19. Gene expression regulators--MicroRNAs

    Institute of Scientific and Technical Information of China (English)

    CHEN Fang; YIN Q. James

    2005-01-01

    A large class of non-coding RNAs found in small molecule RNAs are closely associated with the regulation of gene expression, which are called microRNA (miRNA). MiRNAs are coded in intergenic or intronic regions and can be formed into foldback hairpin RNAs. These transcripts are cleaved by Dicer, generating mature miRNAs that can silence their target genes in different modes of action. Now, research on small molecule RNAs has gotten breakthrough advance in biology. To discover miRNA genes and their target genes has become hot topics in RNA research. This review attempts to look back the history of miRNA discovery, to introduce the methods of screening miRNAs, to localize miRNA loci in genome, to seek miRNA target genes and the biological function, and to discuss the working mechanisms of miRNAs. Finally, we will discuss the potential important roles of miRNAs in modulating the genesis, development, growth, and differentiation of organisms. Thus, it can be predicted that a complete understanding of miRNA functions will bring us some new concepts, approaches and strategies for the study of living beings.

  20. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy (Davis, CA); Bachkirova, Elena (Davis, CA); Rey, Michael (Davis, CA)

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  1. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  2. Bayesian biclustering of gene expression data

    OpenAIRE

    Liu Jun S; Gu Jiajun

    2008-01-01

    Abstract Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions/samples. Although several biclustering algorithms have been studied, few are based on rigorous statistical models. Results We developed a Bayesian biclustering model (BBC), and implemented a Gibbs sampling procedure for its statistical in...

  3. Analysis of Gene Expression Patterns Using Biclustering.

    Science.gov (United States)

    Roy, Swarup; Bhattacharyya, Dhruba K; Kalita, Jugal K

    2016-01-01

    Mining microarray data to unearth interesting expression profile patterns for discovery of in silico biological knowledge is an emerging area of research in computational biology. A group of functionally related genes may have similar expression patterns under a set of conditions or at some time points. Biclustering is an important data mining tool that has been successfully used to analyze gene expression data for biologically significant cluster discovery. The purpose of this chapter is to introduce interesting patterns that may be observed in expression data and discuss the role of biclustering techniques in detecting interesting functional gene groups with similar expression patterns. PMID:26350227

  4. Gene Expression Profiling in the Hibernating Primate, Cheirogaleus Medius.

    Science.gov (United States)

    Faherty, Sheena L; Villanueva-Cañas, José Luis; Klopfer, Peter H; Albà, M Mar; Yoder, Anne D

    2016-01-01

    Hibernation is a complex physiological response that some mammalian species employ to evade energetic demands. Previous work in mammalian hibernators suggests that hibernation is activated not by a set of genes unique to hibernators, but by differential expression of genes that are present in all mammals. This question of universal genetic mechanisms requires further investigation and can only be tested through additional investigations of phylogenetically dispersed species. To explore this question, we use RNA-Seq to investigate gene expression dynamics as they relate to the varying physiological states experienced throughout the year in a group of primate hibernators-Madagascar's dwarf lemurs (genus Cheirogaleus). In a novel experimental approach, we use longitudinal sampling of biological tissues as a method for capturing gene expression profiles from the same individuals throughout their annual hibernation cycle. We identify 90 candidate genes that have variable expression patterns when comparing two active states (Active 1 and Active 2) with a torpor state. These include genes that are involved in metabolic pathways, feeding behavior, and circadian rhythms, as might be expected to correlate with seasonal physiological state changes. The identified genes appear to be critical for maintaining the health of an animal that undergoes prolonged periods of metabolic depression concurrent with the hibernation phenotype. By focusing on these differentially expressed genes in dwarf lemurs, we compare gene expression patterns in previously studied mammalian hibernators. Additionally, by employing evolutionary rate analysis, we find that hibernation-related genes do not evolve under positive selection in hibernating species relative to nonhibernators. PMID:27412611

  5. Gene expression profiling of chicken intestinal host responses

    NARCIS (Netherlands)

    Hemert, van S.

    2007-01-01

    Chicken lines differ in genetic disease susceptibility. The scope of the research described in this thesis was to identify genes involved in genetic disease resistance in the chicken intestine. Therefore gene expression in the jejunum was investigated using a microarray approach. An intestine specif

  6. In vivo pancreatic β-cell-specific expression of antiaging gene Klotho: a novel approach for preserving β-cells in type 2 diabetes.

    Science.gov (United States)

    Lin, Yi; Sun, Zhongjie

    2015-04-01

    Protein expression of an antiaging gene, Klotho, was depleted in pancreatic islets in patients with type 2 diabetes mellitus (T2DM) and in db/db mice, an animal model of T2DM. The objective of this study was to investigate whether in vivo expression of Klotho would preserve pancreatic β-cell function in db/db mice. We report for the first time that β-cell-specific expression of Klotho attenuated the development of diabetes in db/db mice. β-Cell-specific expression of Klotho decreased hyperglycemia and enhanced glucose tolerance. The beneficial effects of Klotho were associated with significant improvements in T2DM-induced decreases in number of β-cells, insulin storage levels in pancreatic islets, and glucose-stimulated insulin secretion from pancreatic islets, which led to increased blood insulin levels in diabetic mice. In addition, β-cell-specific expression of Klotho decreased intracellular superoxide levels, oxidative damage, apoptosis, and DNAJC3 (a marker for endoplasmic reticulum stress) in pancreatic islets. Furthermore, β-cell-specific expression of Klotho increased expression levels of Pdx-1 (insulin transcription factor), PCNA (a marker of cell proliferation), and LC3 (a marker of autophagy) in pancreatic islets in db/db mice. These results reveal that β-cell-specific expression of Klotho improves β-cell function and attenuates the development of T2DM. Therefore, in vivo expression of Klotho may offer a novel strategy for protecting β-cells in T2DM. PMID:25377875

  7. Deriving Trading Rules Using Gene Expression Programming

    Directory of Open Access Journals (Sweden)

    Adrian VISOIU

    2011-01-01

    Full Text Available This paper presents how buy and sell trading rules are generated using gene expression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of genetic algorithms in deriving trading rules is presented. Gene expression programming is applied in a form where multiple types of operators and operands are used. This gives birth to multiple gene contexts and references between genes in order to keep the linear structure of the gene expression programming chromosome. The setup of multiple gene contexts is presented. The case study shows how to use the proposed gene setup to derive trading rules encoded by Boolean expressions, using a dataset with the reference exchange rates between the Euro and the Romanian leu. The conclusions highlight the positive results obtained in deriving useful trading rules.

  8. Biologically supervised hierarchical clustering algorithms for gene expression data.

    Science.gov (United States)

    Boratyn, Grzegorz M; Datta, Susmita; Datta, Somnath

    2006-01-01

    Cluster analysis has become a standard part of gene expression analysis. In this paper, we propose a novel semi-supervised approach that offers the same flexibility as that of a hierarchical clustering. Yet it utilizes, along with the experimental gene expression data, common biological information about different genes that is being complied at various public, Web accessible databases. We argue that such an approach is inherently superior than the standard unsupervised approach of grouping genes based on expression data alone. It is shown that our biologically supervised methods produce better clustering results than the corresponding unsupervised methods as judged by the distance from the model temporal profiles. R-codes of the clustering algorithm are available from the authors upon request. PMID:17947147

  9. The Role of Multiple Transcription Factors In Archaeal Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Charles J. Daniels

    2008-09-23

    Since the inception of this research program, the project has focused on two central questions: What is the relationship between the 'eukaryal-like' transcription machinery of archaeal cells and its counterparts in eukaryal cells? And, how does the archaeal cell control gene expression using its mosaic of eukaryal core transcription machinery and its bacterial-like transcription regulatory proteins? During the grant period we have addressed these questions using a variety of in vivo approaches and have sought to specifically define the roles of the multiple TATA binding protein (TBP) and TFIIB-like (TFB) proteins in controlling gene expression in Haloferax volcanii. H. volcanii was initially chosen as a model for the Archaea based on the availability of suitable genetic tools; however, later studies showed that all haloarchaea possessed multiple tbp and tfb genes, which led to the proposal that multiple TBP and TFB proteins may function in a manner similar to alternative sigma factors in bacterial cells. In vivo transcription and promoter analysis established a clear relationship between the promoter requirements of haloarchaeal genes and those of the eukaryal RNA polymerase II promoter. Studies on heat shock gene promoters, and the demonstration that specific tfb genes were induced by heat shock, provided the first indication that TFB proteins may direct expression of specific gene families. The construction of strains lacking tbp or tfb genes, coupled with the finding that many of these genes are differentially expressed under varying growth conditions, provided further support for this model. Genetic tools were also developed that led to the construction of insertion and deletion mutants, and a novel gene expression scheme was designed that allowed the controlled expression of these genes in vivo. More recent studies have used a whole genome array to examine the expression of these genes and we have established a linkage between the expression of

  10. Differential network analysis from cross-platform gene expression data

    Science.gov (United States)

    Zhang, Xiao-Fei; Ou-Yang, Le; Zhao, Xing-Ming; Yan, Hong

    2016-01-01

    Understanding how the structure of gene dependency network changes between two patient-specific groups is an important task for genomic research. Although many computational approaches have been proposed to undertake this task, most of them estimate correlation networks from group-specific gene expression data independently without considering the common structure shared between different groups. In addition, with the development of high-throughput technologies, we can collect gene expression profiles of same patients from multiple platforms. Therefore, inferring differential networks by considering cross-platform gene expression profiles will improve the reliability of network inference. We introduce a two dimensional joint graphical lasso (TDJGL) model to simultaneously estimate group-specific gene dependency networks from gene expression profiles collected from different platforms and infer differential networks. TDJGL can borrow strength across different patient groups and data platforms to improve the accuracy of estimated networks. Simulation studies demonstrate that TDJGL provides more accurate estimates of gene networks and differential networks than previous competing approaches. We apply TDJGL to the PI3K/AKT/mTOR pathway in ovarian tumors to build differential networks associated with platinum resistance. The hub genes of our inferred differential networks are significantly enriched with known platinum resistance-related genes and include potential platinum resistance-related genes. PMID:27677586

  11. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette;

    2006-01-01

    shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes....... Unfortunately, current human genome-wide DNA sequence variation do not allow signatures of selective sweeps to be inferred using frequency-based approaches [4] and [5] . However, estimates of linkage disequilibrium (LD) - i.e. the extent of non-random association of alleles along chromosomes - are expected...

  12. An EST-based approach for identifying genes expressed in the intestine and gills of pre-smolt Atlantic salmon (Salmo salar

    Directory of Open Access Journals (Sweden)

    Adzhubei Alexei

    2005-12-01

    Full Text Available Abstract Background The Atlantic salmon is an important aquaculture species and a very interesting species biologically, since it spawns in fresh water and develops through several stages before becoming a smolt, the stage at which it migrates to the sea to feed. The dramatic change of habitat requires physiological, morphological and behavioural changes to prepare the salmon for its new environment. These changes are called the parr-smolt transformation or smoltification, and pre-adapt the salmon for survival and growth in the marine environment. The development of hypo-osmotic regulatory ability plays an important part in facilitating the transition from rivers to the sea. The physiological mechanisms behind the developmental changes are largely unknown. An understanding of the transformation process will be vital to the future of the aquaculture industry. A knowledge of which genes are expressed prior to the smoltification process is an important basis for further studies. Results In all, 2974 unique sequences, consisting of 779 contigs and 2195 singlets, were generated for Atlantic salmon from two cDNA libraries constructed from the gills and the intestine, accession numbers [Genbank: CK877169-CK879929, CK884015-CK886537 and CN181112-CN181464]. Nearly 50% of the sequences were assigned putative functions because they showed similarity to known genes, mostly from other species, in one or more of the databases used. The Swiss-Prot database returned significant hits for 1005 sequences. These could be assigned predicted gene products, and 967 were annotated using Gene Ontology (GO terms for molecular function, biological process and/or cellular component, employing an annotation transfer procedure. Conclusion This paper describes the construction of two cDNA libraries from pre-smolt Atlantic salmon (Salmo salar and the subsequent EST sequencing, clustering and assigning of putative function to 1005 genes expressed in the gills and/or intestine.

  13. Gene expression of the endolymphatic sac

    DEFF Research Database (Denmark)

    Friis, Morten; Martin-Bertelsen, Tomas; Friis-Hansen, Lennart;

    2011-01-01

    that the endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology...... was used to investigate the gene expression of the endolymphatic sac with the surrounding dura. Characteristic and novel endolymphatic sac genes were determined by comparing with expressions in pure dura. Results: In all, 463 genes were identified specific for the endolymphatic sac. Functional annotation...

  14. The functional landscape of mouse gene expression

    Directory of Open Access Journals (Sweden)

    Zhang Wen

    2004-12-01

    Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

  15. Bimodal gene expression patterns in breast cancer

    OpenAIRE

    Nikolsky Yuri; Bugrim Andrej; Shi Weiwei; Kirillov Eugene; Bessarabova Marina; Nikolskaya Tatiana

    2010-01-01

    Abstract We identified a set of genes with an unexpected bimodal distribution among breast cancer patients in multiple studies. The property of bimodality seems to be common, as these genes were found on multiple microarray platforms and in studies with different end-points and patient cohorts. Bimodal genes tend to cluster into small groups of four to six genes with synchronised expression within the group (but not between the groups), which makes them good candidates for robust conditional ...

  16. Topological Features In Cancer Gene Expression Data

    OpenAIRE

    Lockwood, Svetlana; Krishnamoorthy, Bala

    2014-01-01

    We present a new method for exploring cancer gene expression data based on tools from algebraic topology. Our method selects a small relevant subset from tens of thousands of genes while simultaneously identifying nontrivial higher order topological features, i.e., holes, in the data. We first circumvent the problem of high dimensionality by dualizing the data, i.e., by studying genes as points in the sample space. Then we select a small subset of the genes as landmarks to construct topologic...

  17. Network Security via Biometric Recognition of Patterns of Gene Expression

    Science.gov (United States)

    Shaw, Harry C.

    2016-01-01

    Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of gene expression for security. Molecular biology provides a rich source of gene expression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time expression and assay of gene expression products.

  18. A comparative gene expression database for invertebrates

    Directory of Open Access Journals (Sweden)

    Ormestad Mattias

    2011-08-01

    Full Text Available Abstract Background As whole genome and transcriptome sequencing gets cheaper and faster, a great number of 'exotic' animal models are emerging, rapidly adding valuable data to the ever-expanding Evo-Devo field. All these new organisms serve as a fantastic resource for the research community, but the sheer amount of data, some published, some not, makes detailed comparison of gene expression patterns very difficult to summarize - a problem sometimes even noticeable within a single lab. The need to merge existing data with new information in an organized manner that is publicly available to the research community is now more necessary than ever. Description In order to offer a homogenous way of storing and handling gene expression patterns from a variety of organisms, we have developed the first web-based comparative gene expression database for invertebrates that allows species-specific as well as cross-species gene expression comparisons. The database can be queried by gene name, developmental stage and/or expression domains. Conclusions This database provides a unique tool for the Evo-Devo research community that allows the retrieval, analysis and comparison of gene expression patterns within or among species. In addition, this database enables a quick identification of putative syn-expression groups that can be used to initiate, among other things, gene regulatory network (GRN projects.

  19. Differential gene expression during Trypanosoma cruzi metacyclogenesis

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Krieger

    1999-09-01

    Full Text Available The transformation of epimastigotes into metacyclic trypomastigotes involves changes in the pattern of expressed genes, resulting in important morphological and functional differences between these developmental forms of Trypanosoma cruzi. In order to identify and characterize genes involved in triggering the metacyclogenesis process and in conferring to metacyclic trypomastigotes their stage specific biological properties, we have developed a method allowing the isolation of genes specifically expressed when comparing two close related cell populations (representation of differential expression or RDE. The method is based on the PCR amplification of gene sequences selected by hybridizing and subtracting the populations in such a way that after some cycles of hybridization-amplification genes specific to a given population are highly enriched. The use of this method in the analysis of differential gene expression during T. cruzi metacyclogenesis (6 hr and 24 hr of differentiation and metacyclic trypomastigotes resulted in the isolation of several clones from each time point. Northern blot analysis showed that some genes are transiently expressed (6 hr and 24 hr differentiating cells, while others are present in differentiating cells and in metacyclic trypomastigotes. Nucleotide sequencing of six clones characterized so far showed that they do not display any homology to gene sequences available in the GeneBank.

  20. Multivariate search for differentially expressed gene combinations

    Directory of Open Access Journals (Sweden)

    Klebanov Lev

    2004-10-01

    Full Text Available Abstract Background To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure of microarray data. A more general two-sample hypothesis is formulated in terms of the joint distribution of any sub-vector of expression signals. Results By building on an earlier proposed multivariate test statistic, we propose a new algorithm for identifying differentially expressed gene combinations. The algorithm includes an improved random search procedure designed to generate candidate gene combinations of a given size. Cross-validation is used to provide replication stability of the search procedure. A permutation two-sample test is used for significance testing. We design a multiple testing procedure to control the family-wise error rate (FWER when selecting significant combinations of genes that result from a successive selection procedure. A target set of genes is composed of all significant combinations selected via random search. Conclusions A new algorithm has been developed to identify differentially expressed gene combinations. The performance of the proposed search-and-testing procedure has been evaluated by computer simulations and analysis of replicated Affymetrix gene array data on age-related changes in gene expression in the inner ear of CBA mice.

  1. Gene Expression Profiling in Porcine Fetal Thymus

    Institute of Scientific and Technical Information of China (English)

    Yanjiong Chen; Shengbin Li; Lin Ye; Jianing Geng; Yajun Deng; Songnian Hu

    2003-01-01

    obtain an initial overview of gene diversity and expression pattern in porcinethymus, 11,712 ESTs (Expressed Sequence Tags) from 100-day-old porcine thymus(FTY) were sequenced and 7,071 cleaned ESTs were used for gene expressionanalysis. Clustered by the PHRAP program, 959 contigs and 3,074 singlets wereobtained. Blast search showed that 806 contigs and 1,669 singlets (totally 5,442ESTs) had homologues in GenBank and 1,629 ESTs were novel. According to theGene Ontology classification, 36.99% ESTs were cataloged into the gene expressiongroup, indicating that although the functional gene (18.78% in defense group) ofthymus is expressed in a certain degree, the 100-day-old porcine thymus still existsin a developmental stage. Comparative analysis showed that the gene expressionpattern of the 100-day-old porcine thymus is similar to that of the human infantthymus.

  2. Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

    Directory of Open Access Journals (Sweden)

    Paules Richard S

    2007-11-01

    Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

  3. Visually Relating Gene Expression and in vivo DNA Binding Data

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Min-Yu; Mackey, Lester; Ker?,; nen, Soile V. E.; Weber, Gunther H.; Jordan, Michael I.; Knowles, David W.; Biggin, Mark D.; Hamann, Bernd

    2011-09-20

    Gene expression and in vivo DNA binding data provide important information for understanding gene regulatory networks: in vivo DNA binding data indicate genomic regions where transcription factors are bound, and expression data show the output resulting from this binding. Thus, there must be functional relationships between these two types of data. While visualization and data analysis tools exist for each data type alone, there is a lack of tools that can easily explore the relationship between them. We propose an approach that uses the average expression driven by multiple of ciscontrol regions to visually relate gene expression and in vivo DNA binding data. We demonstrate the utility of this tool with examples from the network controlling early Drosophila development. The results obtained support the idea that the level of occupancy of a transcription factor on DNA strongly determines the degree to which the factor regulates a target gene, and in some cases also controls whether the regulation is positive or negative.

  4. Nucleosome repositioning underlies dynamic gene expression.

    Science.gov (United States)

    Nocetti, Nicolas; Whitehouse, Iestyn

    2016-03-15

    Nucleosome repositioning at gene promoters is a fundamental aspect of the regulation of gene expression. However, the extent to which nucleosome repositioning is used within eukaryotic genomes is poorly understood. Here we report a comprehensive analysis of nucleosome positions as budding yeast transit through an ultradian cycle in which expression of >50% of all genes is highly synchronized. We present evidence of extensive nucleosome repositioning at thousands of gene promoters as genes are activated and repressed. During activation, nucleosomes are relocated to allow sites of general transcription factor binding and transcription initiation to become accessible. The extent of nucleosome shifting is closely related to the dynamic range of gene transcription and generally related to DNA sequence properties and use of the coactivators TFIID or SAGA. However, dynamic gene expression is not limited to SAGA-regulated promoters and is an inherent feature of most genes. While nucleosome repositioning occurs pervasively, we found that a class of genes required for growth experience acute nucleosome shifting as cells enter the cell cycle. Significantly, our data identify that the ATP-dependent chromatin-remodeling enzyme Snf2 plays a fundamental role in nucleosome repositioning and the expression of growth genes. We also reveal that nucleosome organization changes extensively in concert with phases of the cell cycle, with large, regularly spaced nucleosome arrays being established in mitosis. Collectively, our data and analysis provide a framework for understanding nucleosome dynamics in relation to fundamental DNA-dependent transactions.

  5. Expression of streptavidin gene in bacteria and plants

    International Nuclear Information System (INIS)

    Six biotin-containing proteins are present in plants, representing at least four different biotin enzymes. The physiological function of these biotin enzymes is not understood. Streptavidin, a protein from Streptomyces avidinii, binds tightly and specifically to biotin causing inactivation of biotin enzymes. One approach to elucidating the physiological function of biotin enzymes in plant metabolism is to create transgenic plants expressing the streptavidin gene. A plasmid containing a fused streptavidin-beta-galactosidase gene has been expressed in E. coli. We also have constructed various fusion genes that include an altered CaMV 35S promoter, signal peptides to target the streptavidin protein to specific organelles, and the streptavidin coding gene. We are examining the expression of these genes in cells of carrot

  6. Phytochrome-regulated Gene Expression

    Institute of Scientific and Technical Information of China (English)

    Peter H. Quail

    2007-01-01

    Identification of all genes involved in the phytochrome (phy)-mediated responses of plants to their light environment is an important goal in providing an overall understanding of light-regulated growth and development. This article highlights and integrates the central findings of two recent comprehensive studies in Arabidopsis that have identified the genome-wide set of phy-regulated genes that respond rapidly to red-light signals upon first exposure of dark-grown seedlings, and have tested the functional relevance to normal seedling photomorphogenesis of an initial subset of these genes. The data: (a) reveal considerable complexity in the channeling of the light signals through the different phy-family members (phyA to phyE) to responsive genes; (b) identify a diversity of transcription-factor-encoding genes as major early, if not primary, targets of phy signaling, and, therefore, as potentially important regulators in the transcriptional-network hierarchy; and (c) identify auxin-related genes as the dominant class among rapidly-regulated, hormone-related genes. However, reverse-genetic functional profiling of a selected subset of these genes reveals that only a limited fraction are necessary for optimal phy-induced seedling deetiolation.

  7. Probabilistic estimation of microarray data reliability and underlying gene expression

    Directory of Open Access Journals (Sweden)

    Sigvardsson Mikael

    2003-09-01

    Full Text Available Abstract Background The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data. Results Our approach yields a quantitative measure of two important parameter classes: First, the probability P(σ|S that a gene is in the biological state σ in a certain variety, given its observed expression S in the samples of that variety. Second, sample specific error probabilities which serve as consistency indicators of the measured samples of each variety. The method and its limitations are tested on gene expression data for developing murine B-cells and a t-test is used as reference. On a set of known genes it performs better than the t-test despite the crude discretization into only two expression levels. The consistency indicators, i.e. the error probabilities, correlate well with variations in the biological material and thus prove efficient. Conclusions The proposed method is effective in determining differential gene expression and sample reliability in replicated microarray data. Already at two discrete expression levels in each sample, it gives a good explanation of the data and is comparable to standard techniques.

  8. Selection of low-variance expressed Malus x domestica (apple) genes for use as quantitative PCR reference genes (housekeepers)

    Science.gov (United States)

    To accurately measure gene expression using PCR-based approaches, there is the need for reference genes that have low variance in expression (housekeeping genes) to normalise the data for RNA quantity and quality. For non-model species such as Malus x domestica (apples), previously, the selection of...

  9. Complexity, Post-genomic Biology and Gene Expression Programs

    Science.gov (United States)

    Williams, Rohan B. H.; Luo, Oscar Junhong

    Gene expression represents the fundamental phenomenon by which information encoded in a genome is utilised for the overall biological objectives of the organism. Understanding this level of information transfer is therefore essential for dissecting the mechanistic basis of form and function of organisms. We survey recent developments in the methodology of the life sciences that is relevant for understanding the organisation and function of the genome and review our current understanding of the regulation of gene expression, and finally, outline some new approaches that may be useful in understanding the organisation of gene regulatory systems.

  10. Gene expression profile of sprinter's muscle.

    Science.gov (United States)

    Yoshioka, M; Tanaka, H; Shono, N; Shindo, M; St-Amand, J

    2007-12-01

    We have characterized the global gene expression profile in left vastus lateralis muscles of sprinters and sedentary men. The gene expression profile was analyzed by using serial analysis of gene expression (SAGE) method. The abundantly expressed transcripts in the sprinter's muscle were mainly involved in contraction and energy metabolism, whereas six transcripts were corresponding to potentially novel transcripts. Thirty-eight transcripts were differentially expressed between the sprinter and sedentary individuals. Moreover, sprinters showed higher expressions of both uncharacterized and potentially novel transcripts. Sprinters also highly expressed seven transcripts, such as glycine-rich protein, myosin heavy polypeptide (MYH) 2, expressed sequence tag similar to (EST) fructose-bisphosphate aldolase 1 isoform A (ALDOA), glyceraldehyde-3-phosphate dehydrogenase and ATP synthase F0 subunit 6. On the other hand, 20 transcripts such as MYH1, tropomyosin 2 and 3, troponin C slow, C2 fast, I slow, T1 slow and T3 fast, myoglobin, creatine kinase, ALDOA, glycogen phosphorylase, cytochrome c oxidase II and III, and NADH dehydrogenase 1 and 2 showed lower expression levels in the sprinters than the sedentary controls. The current study has characterized the global gene expressions in sprinters and identified a number of transcripts that can be subjected to further mechanistic analysis.

  11. Extracting expression modules from perturbational gene expression compendia

    OpenAIRE

    Van Dijck Patrick; Maere Steven; Kuiper Martin

    2008-01-01

    Abstract Background Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclus...

  12. SIGNATURE: A workbench for gene expression signature analysis

    Directory of Open Access Journals (Sweden)

    Chang Jeffrey T

    2011-11-01

    Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

  13. Gene expression in periodontal tissues following treatment

    Directory of Open Access Journals (Sweden)

    Eisenacher Martin

    2008-07-01

    Full Text Available Abstract Background In periodontitis, treatment aimed at controlling the periodontal biofilm infection results in a resolution of the clinical and histological signs of inflammation. Although the cell types found in periodontal tissues following treatment have been well described, information on gene expression is limited to few candidate genes. Therefore, the aim of the study was to determine the expression profiles of immune and inflammatory genes in periodontal tissues from sites with severe chronic periodontitis following periodontal therapy in order to identify genes involved in tissue homeostasis. Gingival biopsies from 12 patients with severe chronic periodontitis were taken six to eight weeks following non-surgical periodontal therapy, and from 11 healthy controls. As internal standard, RNA of an immortalized human keratinocyte line (HaCaT was used. Total RNA was subjected to gene expression profiling using a commercially available microarray system focusing on inflammation-related genes. Post-hoc confirmation of selected genes was done by Realtime-PCR. Results Out of the 136 genes analyzed, the 5% most strongly expressed genes compared to healthy controls were Interleukin-12A (IL-12A, Versican (CSPG-2, Matrixmetalloproteinase-1 (MMP-1, Down syndrome critical region protein-1 (DSCR-1, Macrophage inflammatory protein-2β (Cxcl-3, Inhibitor of apoptosis protein-1 (BIRC-1, Cluster of differentiation antigen 38 (CD38, Regulator of G-protein signalling-1 (RGS-1, and Finkel-Biskis-Jinkins murine osteosarcoma virus oncogene (C-FOS; the 5% least strongly expressed genes were Receptor-interacting Serine/Threonine Kinase-2 (RIP-2, Complement component 3 (C3, Prostaglandin-endoperoxide synthase-2 (COX-2, Interleukin-8 (IL-8, Endothelin-1 (EDN-1, Plasminogen activator inhibitor type-2 (PAI-2, Matrix-metalloproteinase-14 (MMP-14, and Interferon regulating factor-7 (IRF-7. Conclusion Gene expression profiles found in periodontal tissues following

  14. The rules of gene expression in plants: Organ identity and gene body methylation are key factors for regulation of gene expression in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Gutiérrez Rodrigo A

    2008-09-01

    Full Text Available Abstract Background Microarray technology is a widely used approach for monitoring genome-wide gene expression. For Arabidopsis, there are over 1,800 microarray hybridizations representing many different experimental conditions on Affymetrix™ ATH1 gene chips alone. This huge amount of data offers a unique opportunity to infer the principles that govern the regulation of gene expression in plants. Results We used bioinformatics methods to analyze publicly available data obtained using the ATH1 chip from Affymetrix. A total of 1887 ATH1 hybridizations were normalized and filtered to eliminate low-quality hybridizations. We classified and compared control and treatment hybridizations and determined differential gene expression. The largest differences in gene expression were observed when comparing samples obtained from different organs. On average, ten-fold more genes were differentially expressed between organs as compared to any other experimental variable. We defined "gene responsiveness" as the number of comparisons in which a gene changed its expression significantly. We defined genes with the highest and lowest responsiveness levels as hypervariable and housekeeping genes, respectively. Remarkably, housekeeping genes were best distinguished from hypervariable genes by differences in methylation status in their transcribed regions. Moreover, methylation in the transcribed region was inversely correlated (R2 = 0.8 with gene responsiveness on a genome-wide scale. We provide an example of this negative relationship using genes encoding TCA cycle enzymes, by contrasting their regulatory responsiveness to nitrate and methylation status in their transcribed regions. Conclusion Our results indicate that the Arabidopsis transcriptome is largely established during development and is comparatively stable when faced with external perturbations. We suggest a novel functional role for DNA methylation in the transcribed region as a key determinant

  15. Optogenetic Control of Gene Expression in Drosophila.

    Directory of Open Access Journals (Sweden)

    Yick-Bun Chan

    Full Text Available To study the molecular mechanism of complex biological systems, it is important to be able to artificially manipulate gene expression in desired target sites with high precision. Based on the light dependent binding of cryptochrome 2 and a cryptochrome interacting bHLH protein, we developed a split lexA transcriptional activation system for use in Drosophila that allows regulation of gene expression in vivo using blue light or two-photon excitation. We show that this system offers high spatiotemporal resolution by inducing gene expression in tissues at various developmental stages. In combination with two-photon excitation, gene expression can be manipulated at precise sites in embryos, potentially offering an important tool with which to examine developmental processes.

  16. Regulation of meiotic gene expression in plants

    Directory of Open Access Journals (Sweden)

    Adele eZhou

    2014-08-01

    Full Text Available With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been built. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa, wheat (Triticum aestivum, petunia (Petunia hybrida, sunflower (Helianthus annuus, and maize (Zea mays. Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on gene expression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how gene expression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs, that might be involved in the regulation of meiotic transcription patterns.

  17. Regulation of Gene Expression in Protozoa Parasites

    Directory of Open Access Journals (Sweden)

    Consuelo Gomez

    2010-01-01

    Full Text Available Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  18. Gene expression profiling in autoimmune diseases

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo;

    2007-01-01

    A central issue in autoimmune disease is whether the underlying inflammation is a repeated stereotypical process or whether disease specific gene expression is involved. To shed light on this, we analysed whether genes previously found to be differentially regulated in rheumatoid arthritis (RA...... differences in peripheral blood mononuclear cell (MNC) gene expression patterns between 15 newly diagnosed HT patients and 15 matched healthy controls. However, the MNC expression levels of five genes were significantly upregulated in 25 IBD patients, compared to 18 matched healthy controls (CD14, FACL2, FCN1...... immunoinflammatory diseases, but only if accompanied by pronounced systemic manifestations. This suggests that at least some of the genes activated in RA are predominantly or solely related to general and disease-nonspecific autoimmune processes...

  19. Energy intake and adiponectin gene expression

    OpenAIRE

    Qiao, Liping; Lee, Bonggi; Kinney, Brice; Yoo, Hyung sun; Shao, Jianhua

    2011-01-01

    Hypoadiponectinemia and decreased adiponectin gene expression in white adipose tissue (WAT) have been well observed in obese subjects and animal models. However, the mechanism for obesity-associated hypoadiponectinemia is still largely unknown. To investigate the regulatory role of energy intake, dietary fat, and adiposity in adiponectin gene expression and blood adiponectin level, a series of feeding regimens was employed to manipulate energy intake and dietary fat in obese-prone C57BL/6, ge...

  20. Facilitated diffusion buffers noise in gene expression

    OpenAIRE

    Schoech, Armin; Zabet, Nicolae Radu

    2014-01-01

    Transcription factors perform facilitated diffusion (3D diffusion in the cytosol and 1D diffusion on the DNA) when binding to their target sites to regulate gene expression. Here, we investigated the influence of this binding mechanism on the noise in gene expression. Our results showed that, for biologically relevant parameters, the binding process can be represented by a two-state Markov model and that the accelerated target finding due to facilitated diffusion leads to a reduction in both ...

  1. PRAME gene expression profile in medulloblastoma

    Directory of Open Access Journals (Sweden)

    Tânia Maria Vulcani-Freitas

    2011-02-01

    Full Text Available Medulloblastoma is the most common malignant tumors of central nervous system in the childhood. The treatment is severe, harmful and, thus, has a dismal prognosis. As PRAME is present in various cancers, including meduloblastoma, and has limited expression in normal tissues, this antigen can be an ideal vaccine target for tumor immunotherapy. In order to find a potential molecular target, we investigated PRAME expression in medulloblastoma fragments and we compare the results with the clinical features of each patient. Analysis of gene expression was performed by real-time quantitative PCR from 37 tumor samples. The Mann-Whitney test was used to analysis the relationship between gene expression and clinical characteristics. Kaplan-Meier curves were used to evaluate survival. PRAME was overexpressed in 84% samples. But no statistical association was found between clinical features and PRAME overexpression. Despite that PRAME gene could be a strong candidate for immunotherapy since it is highly expressed in medulloblastomas.

  2. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

    Science.gov (United States)

    dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis.

  3. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

    Science.gov (United States)

    dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

  4. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

    Directory of Open Access Journals (Sweden)

    Odelta dos Santos

    Full Text Available Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR, one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis.

  5. Inferring gene networks from discrete expression data

    KAUST Repository

    Zhang, L.

    2013-07-18

    The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.

  6. Translational control of gene expression and disease

    NARCIS (Netherlands)

    Calkhoven, Cornelis F; Müller, Christine; Leutz, Achim

    2002-01-01

    In the past decade, translational control has been shown to be crucial in the regulation of gene expression. Research in this field has progressed rapidly, revealing new control mechanisms and adding constantly to the list of translationally regulated genes. There is accumulating evidence that trans

  7. Perspectives: Gene Expression in Fisheries Management

    Science.gov (United States)

    Nielsen, Jennifer L.; Pavey, Scott A.

    2010-01-01

    Functional genes and gene expression have been connected to physiological traits linked to effective production and broodstock selection in aquaculture, selective implications of commercial fish harvest, and adaptive changes reflected in non-commercial fish populations subject to human disturbance and climate change. Gene mapping using single nucleotide polymorphisms (SNPs) to identify functional genes, gene expression (analogue microarrays and real-time PCR), and digital sequencing technologies looking at RNA transcripts present new concepts and opportunities in support of effective and sustainable fisheries. Genomic tools have been rapidly growing in aquaculture research addressing aspects of fish health, toxicology, and early development. Genomic technologies linking effects in functional genes involved in growth, maturation and life history development have been tied to selection resulting from harvest practices. Incorporating new and ever-increasing knowledge of fish genomes is opening a different perspective on local adaptation that will prove invaluable in wild fish conservation and management. Conservation of fish stocks is rapidly incorporating research on critical adaptive responses directed at the effects of human disturbance and climate change through gene expression studies. Genomic studies of fish populations can be generally grouped into three broad categories: 1) evolutionary genomics and biodiversity; 2) adaptive physiological responses to a changing environment; and 3) adaptive behavioral genomics and life history diversity. We review current genomic research in fisheries focusing on those that use microarrays to explore differences in gene expression among phenotypes and within or across populations, information that is critically important to the conservation of fish and their relationship to humans.

  8. A Rough Set based Gene Expression Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    J. J. Emilyn

    2011-01-01

    Full Text Available Problem statement: Microarray technology helps in monitoring the expression levels of thousands of genes across collections of related samples. Approach: The main goal in the analysis of large and heterogeneous gene expression datasets was to identify groups of genes that get expressed in a set of experimental conditions. Results: Several clustering techniques have been proposed for identifying gene signatures and to understand their role and many of them have been applied to gene expression data, but with partial success. The main aim of this work was to develop a clustering algorithm that would successfully indentify gene patterns. The proposed novel clustering technique (RCGED provides an efficient way of finding the hidden and unique gene expression patterns. It overcomes the restriction of one object being placed in only one cluster. Conclusion/Recommendations: The proposed algorithm is termed intelligent because it automatically determines the optimum number of clusters. The proposed algorithm was experimented with colon cancer dataset and the results were compared with Rough Fuzzy K Means algorithm.

  9. Aberrant Gene Expression in Acute Myeloid Leukaemia

    DEFF Research Database (Denmark)

    Bagger, Frederik Otzen

    Summary Acute Myeloid Leukaemia (AML) is an aggressive cancer of the bone marrow, affecting formation of blood cells during haematopoiesis. This thesis presents investigation of AML using mRNA gene expression profiles (GEP) of samples extracted from the bone marrow of healthy and diseased subjects...... genes and genetic signatures and for reducing dimensionally of gene expression data. Next, we have used machine-learning methods to predict survival and to assess important predictors based on these results. General application of a number of these methods has been implemented into two public query...

  10. Gene expression profiling: can we identify the right target genes?

    Directory of Open Access Journals (Sweden)

    J. E. Loyd

    2008-12-01

    Full Text Available Gene expression profiling allows the simultaneous monitoring of the transcriptional behaviour of thousands of genes, which may potentially be involved in disease development. Several studies have been performed in idiopathic pulmonary fibrosis (IPF, which aim to define genetic links to the disease in an attempt to improve the current understanding of the underlying pathogenesis of the disease and target pathways for intervention. Expression profiling has shown a clear difference in gene expression between IPF and normal lung tissue, and has identified a wide range of candidate genes, including those known to encode for proteins involved in extracellular matrix formation and degradation, growth factors and chemokines. Recently, familial pulmonary fibrosis cohorts have been examined in an attempt to detect specific genetic mutations associated with IPF. To date, these studies have identified families in which IPF is associated with mutations in the gene encoding surfactant protein C, or with mutations in genes encoding components of telomerase. Although rare and clearly not responsible for the disease in all individuals, the nature of these mutations highlight the importance of the alveolar epithelium in disease pathogenesis and demonstrate the potential for gene expression profiling in helping to advance the current understanding of idiopathic pulmonary fibrosis.

  11. Leaving out control groups: an internal contrast analysis of gene expression profiles in atrial fibrillation patients--a systems biology approach to clinical categorization.

    Science.gov (United States)

    Vanhoutte, Kurt; de Asmundis, Carlo; Francesconi, Anna; Figysl, Jurgen; Steurs, Griet; Boussy, Tim; Roos, Markus; Mueller, Andreas; Massimo, Lucio; Paparella, Gaetano; Van Caelenberg, Kristien; Chierchia, Gian Battista; Sarkozy, Andrea; Terradellas, Pedro Brugada Y; Zizi, Martin

    2009-01-01

    Atrial fibrillation (AF) is a frequent chronic dysrythmia with an incidence that increases with age (>40). Because of its medical and socio-economic impacts it is expected to become an increasing burden on most health care systems. AF is a multi-factorial disease for which the identification of subtypes is warranted. Novel approaches based on the broad concepts of systems biology may overcome the blurred notion of normal and pathological phenotype, which is inherent to high throughput molecular arrays analysis. Here we apply an internal contrast algorithm on AF patient data with an analytical focus on potential entry pathways into the disease. We used a RMA (Robust Multichip Average) normalized Affymetrix micro-array data set from 10 AF patients (geo_accession #GSE2240). Four series of probes were selected based on physiopathogenic links with AF entryways: apoptosis (remodeling), MAP kinase (cell remodeling), OXPHOS (ability to sustain hemodynamic workload) and glycolysis (ischemia). Annotated probe lists were polled with Bioconductor packages in R (version 2.7.1). Genetic profile contrasts were analysed with hierarchical clustering and principal component analysis. The analysis revealed distinct patient groups for all probe sets. A substantial part (54% till 67%) of the variance is explained in the first 2 principal components. Genes in PC1/2 with high discriminatory value were selected and analyzed in detail. We aim for reliable molecular stratification of AF. We show that stratification is possible based on physiologically relevant gene sets. Genes with high contrast value are likely to give pathophysiological insight into permanent AF subtypes.

  12. Gene Expression Profiling in the Hibernating Primate, Cheirogaleus Medius

    Science.gov (United States)

    Faherty, Sheena L.; Villanueva-Cañas, José Luis; Klopfer, Peter H.; Albà, M. Mar; Yoder, Anne D.

    2016-01-01

    Hibernation is a complex physiological response that some mammalian species employ to evade energetic demands. Previous work in mammalian hibernators suggests that hibernation is activated not by a set of genes unique to hibernators, but by differential expression of genes that are present in all mammals. This question of universal genetic mechanisms requires further investigation and can only be tested through additional investigations of phylogenetically dispersed species. To explore this question, we use RNA-Seq to investigate gene expression dynamics as they relate to the varying physiological states experienced throughout the year in a group of primate hibernators—Madagascar’s dwarf lemurs (genus Cheirogaleus). In a novel experimental approach, we use longitudinal sampling of biological tissues as a method for capturing gene expression profiles from the same individuals throughout their annual hibernation cycle. We identify 90 candidate genes that have variable expression patterns when comparing two active states (Active 1 and Active 2) with a torpor state. These include genes that are involved in metabolic pathways, feeding behavior, and circadian rhythms, as might be expected to correlate with seasonal physiological state changes. The identified genes appear to be critical for maintaining the health of an animal that undergoes prolonged periods of metabolic depression concurrent with the hibernation phenotype. By focusing on these differentially expressed genes in dwarf lemurs, we compare gene expression patterns in previously studied mammalian hibernators. Additionally, by employing evolutionary rate analysis, we find that hibernation-related genes do not evolve under positive selection in hibernating species relative to nonhibernators. PMID:27412611

  13. Biclustering Methods: Biological Relevance and Application in Gene Expression Analysis

    OpenAIRE

    Ali Oghabian; Sami Kilpinen; Sampsa Hautaniemi; Elena Czeizler

    2014-01-01

    DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering) methods where genes (or respectively samples) are grouped together based on the similarity of their expressi...

  14. Introduction to the Gene Expression Analysis.

    Science.gov (United States)

    Segundo-Val, Ignacio San; Sanz-Lozano, Catalina S

    2016-01-01

    In 1941, Beadle and Tatum published experiments that would explain the basis of the central dogma of molecular biology, whereby the DNA through an intermediate molecule, called RNA, results proteins that perform the functions in cells. Currently, biomedical research attempts to explain the mechanisms by which develops a particular disease, for this reason, gene expression studies have proven to be a great resource. Strictly, the term "gene expression" comprises from the gene activation until the mature protein is located in its corresponding compartment to perform its function and contribute to the expression of the phenotype of cell.The expression studies are directed to detect and quantify messenger RNA (mRNA) levels of a specific gene. The development of the RNA-based gene expression studies began with the Northern Blot by Alwine et al. in 1977. In 1969, Gall and Pardue and John et al. independently developed the in situ hybridization, but this technique was not employed to detect mRNA until 1986 by Coghlan. Today, many of the techniques for quantification of RNA are deprecated because other new techniques provide more information. Currently the most widely used techniques are qPCR, expression microarrays, and RNAseq for the transcriptome analysis. In this chapter, these techniques will be reviewed. PMID:27300529

  15. Biclustering methods: biological relevance and application in gene expression analysis.

    Science.gov (United States)

    Oghabian, Ali; Kilpinen, Sami; Hautaniemi, Sampsa; Czeizler, Elena

    2014-01-01

    DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering) methods where genes (or respectively samples) are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes). An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical) methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1) we examine how well the considered (bi)clustering methods differentiate various sample types; (2) we evaluate how well the groups of genes discovered by the (bi)clustering methods are annotated with similar Gene Ontology categories; (3) we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4) we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples. PMID:24651574

  16. Biclustering methods: biological relevance and application in gene expression analysis.

    Directory of Open Access Journals (Sweden)

    Ali Oghabian

    Full Text Available DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering methods where genes (or respectively samples are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes. An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1 we examine how well the considered (biclustering methods differentiate various sample types; (2 we evaluate how well the groups of genes discovered by the (biclustering methods are annotated with similar Gene Ontology categories; (3 we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4 we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

  17. Regulation of gene expression in human tendinopathy

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    Archambault Joanne M

    2011-05-01

    Full Text Available Abstract Background Chronic tendon injuries, also known as tendinopathies, are common among professional and recreational athletes. These injuries result in a significant amount of morbidity and health care expenditure, yet little is known about the molecular mechanisms leading to tendinopathy. Methods We have used histological evaluation and molecular profiling to determine gene expression changes in 23 human patients undergoing surgical procedures for the treatment of chronic tendinopathy. Results Diseased tendons exhibit altered extracellular matrix, fiber disorientation, increased cellular content and vasculature, and the absence of inflammatory cells. Global gene expression profiling identified 983 transcripts with significantly different expression patterns in the diseased tendons. Global pathway analysis further suggested altered expression of extracellular matrix proteins and the lack of an appreciable inflammatory response. Conclusions Identification of the pathways and genes that are differentially regulated in tendinopathy samples will contribute to our understanding of the disease and the development of novel therapeutics.

  18. Referring Expressions: A Unified Approach

    Institute of Scientific and Technical Information of China (English)

    K.M. Jaszczolt

    2001-01-01

    @@ 0. Introduction Expressions used by speakers to refer are commonly divided into two categories: that of directly referring expressions and that of expressions whose referring function is secured by the context of utterance. Directly referring expressions are normally said to include proper names, some pronouns including demonstrative, and demonstrative phrases. The other category comprises mainly definite and indefinite descriptions, the first being their most acclaimed representative. Definite descriptions are widely acknowledged to have referential uses. They are not referring expressions, so to speak, by default,but rather as a result of a contextually determined interpretation. As a category, they are frequently said to belong with quantifiers (Neale 1990; Recanati 1993). However, the arguments for classifying them with referring expressions are ample (Bach 1987a; Larson & Segal 1995; Brown 1995; Jaszczolt 1997a,1997b, 1999b). It is argued in Part I of this paper that although definite descriptions exhibit an ambiguity of use between the referential and the attributive reading, they also exhibit the property of having an unmarked, salient interpretation which makes them akin to directly referential terms. This salient reading is the referential interpretation, arrived at with the help of the hearer′s presumption of the presence of strong referential intention that supports the speaker′s utterance.

  19. Noise minimization in eukaryotic gene expression.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2004-06-01

    Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  20. VESPUCCI: Exploring Patterns of Gene Expression in Grapevine.

    Science.gov (United States)

    Moretto, Marco; Sonego, Paolo; Pilati, Stefania; Malacarne, Giulia; Costantini, Laura; Grzeskowiak, Lukasz; Bagagli, Giorgia; Grando, Maria Stella; Moser, Claudio; Engelen, Kristof

    2016-01-01

    Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult. In this paper, we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI), a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

  1. VESPUCCI: exploring patterns of gene expression in grapevine

    Directory of Open Access Journals (Sweden)

    Marco eMoretto

    2016-05-01

    Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

  2. Soybean physiology and gene expression during drought.

    Science.gov (United States)

    Stolf-Moreira, R; Medri, M E; Neumaier, N; Lemos, N G; Pimenta, J A; Tobita, S; Brogin, R L; Marcelino-Guimarães, F C; Oliveira, M C N; Farias, J R B; Abdelnoor, R V; Nepomuceno, A L

    2010-10-05

    Soybean genotypes MG/BR46 (Conquista) and BR16, drought-tolerant and -sensitive, respectively, were compared in terms of morphophysiological and gene-expression responses to water stress during two stages of development. Gene-expression analysis showed differential responses in Gmdreb1a and Gmpip1b mRNA expression within 30 days of water-deficit initiation in MG/BR46 (Conquista) plants. Within 45 days of initiating stress, Gmp5cs and Gmpip1b had relatively higher expression. Initially, BR16 showed increased expression only for Gmdreb1a, and later (45 days) for Gmp5cs, Gmdefensin and Gmpip1b. Only BR16 presented down-regulated expression of genes, such as Gmp5cs and Gmpip1b, 30 days after the onset of moisture stress, and Gmgols after 45 days of stress. The faster perception of water stress in MG/BR46 (Conquista) and the better maintenance of up-regulated gene expression than in the sensitive BR16 genotype imply mechanisms by which the former is better adapted to tolerate moisture deficiency.

  3. Convergence of linkage, gene expression and association data demonstrates the influence of the RAR-related orphan receptor alpha (RORA) gene on neovascular AMD: A systems biology based approach

    Science.gov (United States)

    Silveira, Alexandra C.; Morrison, Margaux A.; Ji, Fei; Xu, Haiyan; Reinecke, James B.; Adams, Scott M.; Arneberg, Trevor M.; Janssian, Maria; Lee, Joo-Eun; Yuan, Yang; Schaumberg, Debra A.; Kotoula, Maria G.; Tsironi, Evangeline E.; Tsiloulis, Aristoteles N.; Chatzoulis, Dimitrios Z.; Miller, Joan W.; Kim, Ivana K.; Hageman, Gregory H.; Farrer, Lindsay A.; Haider, Neena B.; DeAngelis, Margaret M.

    2009-01-01

    To identify novel genes and pathways associated with AMD, we performed microarray gene expression and linkage analysis which implicated the candidate gene, retinoic acid receptor-related orphan receptor alpha (RORA, 15q). Subsequent genotyping of 159 RORA single nucleotide polymorphisms (SNPs) in a family-based cohort, followed by replication in an unrelated case-control cohort, demonstrated that SNPs and haplotypes located in intron 1 were significantly associated with neovascular AMD risk in both cohorts. This is the first report demonstrating a possible role for RORA, a receptor for cholesterol, in the pathophysiology of AMD. Moreover, we found a significant interaction between RORA and the ARMS2/HTRA1 locus suggesting a novel pathway underlying AMD pathophysiology. PMID:19786043

  4. Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders

    Science.gov (United States)

    Oswald, Michaela; Curran, Mark; Lamberth, Sarah; Townsend, Robert; Hamilton, Jennifer D.; Chernoff, David N.; Carulli, John; Townsend, Michael; Weinblatt, Michael; Kern, Marlena; Pond, Cassandra; Lee, Annette; Gregersen, Peter K.

    2015-01-01

    Objective To establish whether the analysis of whole blood gene expression can be useful in predicting or monitoring response to anti-TNF therapy in RA. Methods Whole blood RNA (PAXgene) was obtained at baseline and 14 weeks on three independent cohorts with a combined total of 250 patients with rheumatoid arthritis beginning anti-TNF therapy. We employed an approach to gene expression analysis that is based on gene expression “modules”. Results Good and Moderate Responders by EULAR criteria exhibited highly significant and consistent changes in multiple gene expression modules using a hyper geometric analysis after 14 weeks of therapy. Strikingly, non responders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all three cohorts, indicating that immunological changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and non-responders at baseline in the three cohorts. Conclusions These data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors. PMID:25371395

  5. Gene expression analysis in RA: towards personalized medicine

    NARCIS (Netherlands)

    Burska, A.N.; Roget, K.; Blits, M.; Gomez, L.; Loo, F.A.J. van de; Hazelwood, L.D.; Verweij, C.L.; Rowe, A.; Goulielmos, G.N.; Baarsen, L.G. van; Ponchel, F.

    2014-01-01

    Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathog

  6. Time-Course Gene Set Analysis for Longitudinal Gene Expression Data.

    Directory of Open Access Journals (Sweden)

    Boris P Hejblum

    2015-06-01

    Full Text Available Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial, and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package.

  7. Translational machinery of the chaetognath Spadella cephaloptera: a transcriptomic approach to the analysis of cytosolic ribosomal protein genes and their expression

    Directory of Open Access Journals (Sweden)

    Casanova Jean-Paul

    2007-08-01

    Full Text Available Abstract Background Chaetognaths, or arrow worms, are small marine, bilaterally symmetrical metazoans. The objective of this study was to analyse ribosomal protein (RP coding sequences from a published collection of expressed sequence tags (ESTs from a chaetognath (Spadella cephaloptera and to use them in phylogenetic studies. Results This analysis has allowed us to determine the complete primary structures of 23 out of 32 RPs from the small ribosomal subunit (SSU and 32 out of 47 RPs from the large ribosomal subunit (LSU. Ten proteins are partially determined and 14 proteins are missing. Phylogenetic analyses of concatenated RPs from six animals (chaetognath, echinoderm, mammalian, insect, mollusc and sponge and one fungal taxa do not resolve the chaetognath phylogenetic position, although each mega-sequence comprises approximately 5,000 amino acid residues. This is probably due to the extremely biased base composition and to the high evolutionary rates in chaetognaths. However, the analysis of chaetognath RP genes revealed three unique features in the animal Kingdom. First, whereas generally in animals one RP appeared to have a single type of mRNA, two or more genes are generally transcribed for one RP type in chaetognath. Second, cDNAs with complete 5'-ends encoding a given protein sequence can be divided in two sub-groups according to a short region in their 5'-ends: two novel and highly conserved elements have been identified (5'-TAATTGAGTAGTTT-3' and 5'-TATTAAGTACTAC-3' which could correspond to different transcription factor binding sites on paralog RP genes. And, third, the overall number of deduced paralogous RPs is very high compared to those published for other animals. Conclusion These results suggest that in chaetognaths the deleterious effects of the presence of paralogous RPs, such as apoptosis or cancer are avoided, and also that in each protein family, some of the members could have tissue-specific and extra-ribosomal functions

  8. Comparison of gene expression methods to identify genes responsive to perfluorooctane sulfonic acid.

    Science.gov (United States)

    Hu, Wenyue; Jones, Paul D; Decoen, Wim; Newsted, John L; Giesy, John P

    2005-01-01

    Genome-wide expression techniques are being increasingly used to assess the effects of environmental contaminants. Oligonucleotide or cDNA microarray methods make possible the screening of large numbers of known sequences for a given model species, while differential display analysis makes possible analysis of the expression of all the genes from any species. We report a comparison of two currently popular methods for genome-wide expression analysis in rat hepatoma cells treated with perfluorooctane sulfonic acid. The two analyses provided 'complimentary' information. Approximately 5% of the 8000 genes analyzed by the GeneChip array, were altered by a factor of three or greater. Differential display results were more difficult to interpret, since multiple gene products were present in most gel bands so a probabilistic approach was used to determine which pathways were affected. The mechanistic interpretation derived from these two methods was in agreement, both showing similar alterations in a specific set of genes. PMID:21783471

  9. Gene expression characterizes different nutritional strategies among three mixotrophic protists.

    Science.gov (United States)

    Liu, Zhenfeng; Campbell, Victoria; Heidelberg, Karla B; Caron, David A

    2016-07-01

    Mixotrophic protists, i.e. protists that can carry out both phototrophy and heterotrophy, are a group of organisms with a wide range of nutritional strategies. The ecological and biogeochemical importance of these species has recently been recognized. In this study, we investigated and compared the gene expression of three mixotrophic protists, Prymnesium parvum, Dinobyron sp. and Ochromonas sp. under light and dark conditions in the presence of prey using RNA-Seq. Gene expression of the obligately phototrophic P. parvum and Dinobryon sp. changed significantly between light and dark treatments, while that of primarily heterotrophic Ochromonas sp. was largely unchanged. Gene expression of P. parvum and Dinobryon sp. shared many similarities, especially in the expression patterns of genes related to reproduction. However, key genes involved in central carbon metabolism and phagotrophy had different expression patterns between these two species, suggesting differences in prey consumption and heterotrophic nutrition in the dark. Transcriptomic data also offered clues to other physiological traits of these organisms such as preference of nitrogen sources and photo-oxidative stress. These results provide potential target genes for further exploration of the mechanisms of mixotrophic physiology and demonstrate the potential usefulness of molecular approaches in characterizing the nutritional modes of mixotrophic protists. PMID:27194617

  10. Geometry of the Gene Expression Space of Individual Cells.

    Directory of Open Access Journals (Sweden)

    Yael Korem

    2015-07-01

    Full Text Available There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a

  11. Alternative-splicing-mediated gene expression

    Science.gov (United States)

    Wang, Qianliang; Zhou, Tianshou

    2014-01-01

    Alternative splicing (AS) is a fundamental process during gene expression and has been found to be ubiquitous in eukaryotes. However, how AS impacts gene expression levels both quantitatively and qualitatively remains to be fully explored. Here, we analyze two common models of gene expression, each incorporating a simple splice mechanism that a pre-mRNA is spliced into two mature mRNA isoforms in a probabilistic manner. In the constitutive expression case, we show that the steady-state molecular numbers of two mature mRNA isoforms follow mutually independent Poisson distributions. In the bursting expression case, we demonstrate that the tail decay of the steady-state distribution for both mature mRNA isoforms that in general are not mutually independent can be characterized by the product of mean burst size and splicing probability. In both cases, we find that AS can efficiently modulate both the variability (measured by variance) and the noise level of the total mature mRNA, and in particular, the latter is always lower than the noise level of the pre-mRNA, implying that AS always reduces the noise. These results altogether reveal that AS is a mechanism of efficiently controlling the gene expression noise.

  12. Gene expression analysis of precision-cut human liver slices indicate stable expression of hepatotoxicity related genes

    NARCIS (Netherlands)

    Elferink, Maria; Olinga, Peter; van Leeuwen, E. M.; Bauerschmidt, S.; Polman, J.; Schoonen, W. G.; Heisterkamp, S. H.; Groothuis, Genoveva

    2011-01-01

    In the process of drug development it is of high importance to test the safety of new drugs with predictive value for human toxicity. A promising approach of toxicity testing is based on changes in the gene expression profile of the liver. Toxicity screening based on animal liver cells cannot be dir

  13. Gene expression analysis of precision-cut human liver slices indicates stable expression of ADME-Tox related genes

    NARCIS (Netherlands)

    Elferink, M. G. L.; Olinga, P.; van Leeuwen, E. M.; Bauerschmidt, S.; Polman, J.; Schoonen, W. G.; Heisterkamp, S. H.; Groothuis, G. M. M.

    2011-01-01

    In the process of drug development it is of high importance to test the safety of new drugs with predictive value for human toxicity. A promising approach of toxicity testing is based on shifts in gene expression profiling of the liver. Toxicity screening based on animal liver cells cannot be direct

  14. Gene expression analysis of flax seed development

    Directory of Open Access Journals (Sweden)

    Sharpe Andrew

    2011-04-01

    Full Text Available Abstract Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages seed coats (globular and torpedo stages and endosperm (pooled globular to torpedo stages and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST (GenBank accessions LIBEST_026995 to LIBEST_027011 were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152 had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid

  15. Ocular Surface Development and Gene Expression

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    Shivalingappa K. Swamynathan

    2013-01-01

    Full Text Available The ocular surface—a continuous epithelial surface with regional specializations including the surface and glandular epithelia of the cornea, conjunctiva, and lacrimal and meibomian glands connected by the overlying tear film—plays a central role in vision. Molecular and cellular events involved in embryonic development, postnatal maturation, and maintenance of the ocular surface are precisely regulated at the level of gene expression by a well-coordinated network of transcription factors. A thorough appreciation of the biological characteristics of the ocular surface in terms of its gene expression profiles and their regulation provides us with a valuable insight into the pathophysiology of various blinding disorders that disrupt the normal development, maturation, and/or maintenance of the ocular surface. This paper summarizes the current status of our knowledge related to the ocular surface development and gene expression and the contribution of different transcription factors to this process.

  16. Gene Expression in the Human Endolymphatic Sac

    DEFF Research Database (Denmark)

    Møller, Martin Nue; Kirkeby, Svend; Vikeså, Jonas;

    2015-01-01

    OBJECTIVES/HYPOTHESIS: The purpose of the present study is to explore, demonstrate, and describe the expression of genes related to the solute carrier (SLC) molecules of ion transporters in the human endolymphatic sac. STUDY DESIGN: cDNA microarrays and immunohistochemistry were used for analyses...... of fresh human endolymphatic sac tissue samples. METHODS: Twelve tissue samples of the human endolymphatic sac were obtained during translabyrinthine surgery for vestibular schwannoma. Microarray technology was used to investigate tissue sample expression of solute carrier family genes, using adjacent dura...... mater as control. Immunohistochemistry was used for verification of translation of selected genes, as well as localization of the specific protein within the sac. RESULTS: An extensive representation of the SLC family genes were upregulated in the human endolymphatic sac, including SLC26a4 Pendrin, SLC4...

  17. Parsimonious selection of useful genes in microarray gene expression data

    OpenAIRE

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio

    2011-01-01

    Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number of features and a few observations, making the modeling a non-trivial undertaking. In this work we apply entropic filter methods for gene selection, in combination with several off-the-shelf classifiers. The introduction of bootstrap resampling techniques permits the achiev...

  18. Sequencing and Gene Expression Analysis of Leishmania tropica LACK Gene.

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    Nour Hammoudeh

    2014-12-01

    Full Text Available Leishmania Homologue of receptors for Activated C Kinase (LACK antigen is a 36-kDa protein, which provokes a very early immune response against Leishmania infection. There are several reports on the expression of LACK through different life-cycle stages of genus Leishmania, but only a few of them have focused on L.tropica.The present study provides details of the cloning, DNA sequencing and gene expression of LACK in this parasite species. First, several local isolates of Leishmania parasites were typed in our laboratory using PCR technique to verify of Leishmania parasite species. After that, LACK gene was amplified and cloned into a vector for sequencing. Finally, the expression of this molecule in logarithmic and stationary growth phase promastigotes, as well as in amastigotes, was evaluated by Reverse Transcription-PCR (RT-PCR technique.The typing result confirmed that all our local isolates belong to L.tropica. LACK gene sequence was determined and high similarity was observed with the sequences of other Leishmania species. Furthermore, the expression of LACK gene in both promastigotes and amastigotes forms was confirmed.Overall, the data set the stage for future studies of the properties and immune role of LACK gene products.

  19. Extracting expression modules from perturbational gene expression compendia

    Directory of Open Access Journals (Sweden)

    Van Dijck Patrick

    2008-04-01

    Full Text Available Abstract Background Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclustering methods on the other hand are specifically designed to capture such partial coexpression patterns, but they show a variety of other drawbacks. For instance, some biclustering methods are less suited to identify overlapping biclusters, while others generate highly redundant biclusters. Also, none of the existing biclustering tools takes advantage of the staple of perturbational expression data analysis: the identification of differentially expressed genes. Results We introduce a novel method, called ENIGMA, that addresses some of these issues. ENIGMA leverages differential expression analysis results to extract expression modules from perturbational gene expression data. The core parameters of the ENIGMA clustering procedure are automatically optimized to reduce the redundancy between modules. In contrast to the biclusters produced by most other methods, ENIGMA modules may show internal substructure, i.e. subsets of genes with distinct but significantly related expression patterns. The grouping of these (often functionally related patterns in one module greatly aids in the biological interpretation of the data. We show that ENIGMA outperforms other methods on artificial datasets, using a quality criterion that, unlike other criteria, can be used for algorithms that generate overlapping clusters and that can be modified to take redundancy between clusters into account. Finally, we apply ENIGMA to the Rosetta compendium of expression profiles for

  20. Applications of queueing theory to stochastic models of gene expression

    Science.gov (United States)

    Kulkarni, Rahul

    2012-02-01

    The intrinsic stochasticity of cellular processes implies that analysis of fluctuations (`noise') is often essential for quantitative modeling of gene expression. Recent single-cell experiments have carried out such analysis to characterize moments and entire probability distributions for quantities of interest, e.g. mRNA and protein levels across a population of cells. Correspondingly, there is a need to develop general analytical tools for modeling and interpretation of data obtained from such single-cell experiments. One such approach involves the mapping between models of stochastic gene expression and systems analyzed in queueing theory. The talk will provide an overview of this approach and discuss how theorems from queueing theory (e.g. Little's Law) can be used to derive exact results for general stochastic models of gene expression. In the limit that gene expression occurs in bursts, analytical results can be obtained which provide insight into the effects of different regulatory mechanisms on the noise in protein steady-state distributions. In particular, the approach can be used to analyze the effect of post-transcriptional regulation by non-coding RNAs leading to new insights and experimentally testable predictions.

  1. Gene expression profiling in sinonasal adenocarcinoma.

    OpenAIRE

    Sébille-Rivain Véronique; Malard Olivier; Guisle-Marsollier Isabelle; Ferron Christophe; Renaudin Karine; Quéméner Sylvia; Tripodi Dominique; Verger Christian; Géraut Christian; Gratas-Rabbia-Ré Catherine

    2009-01-01

    Abstract Background Sinonasal adenocarcinomas are uncommon tumors which develop in the ethmoid sinus after exposure to wood dust. Although the etiology of these tumors is well defined, very little is known about their molecular basis and no diagnostic tool exists for their early detection in high-risk workers. Methods To identify genes involved in this disease, we performed gene expression profiling using cancer-dedicated microarrays, on nine matched samples of sinonasal adenocarcinomas and n...

  2. Visualizing Gene Expression In Situ

    Energy Technology Data Exchange (ETDEWEB)

    Burlage, R.S.

    1998-11-02

    Visualizing bacterial cells and describing their responses to the environment are difficult tasks. Their small size is the chief reason for the difficulty, which means that we must often use many millions of cells in a sample in order to determine what the average response of the bacteria is. However, an average response can sometimes mask important events in bacterial physiology, which means that our understanding of these organisms will suffer. We have used a variety of instruments to visualize bacterial cells, all of which tell us something different about the sample. We use a fluorescence activated cell sorter to sort cells based on the fluorescence provided by bioreporter genes, and these can be used to select for particular genetic mutations. Cells can be visualized by epifluorescent microscopy, and sensitive photodetectors can be added that allow us to find a single bacterial cell that is fluorescent or bioluminescent. We have also used standard photomultipliers to examine cell aggregates as field bioreporter microorganisms. Examples of each of these instruments show how our understanding of bacterial physiology has changed with the technology.

  3. Epigenetic control of antioxidant gene expression

    OpenAIRE

    Wild, Brigitte

    2015-01-01

    Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología Molecular. Fecha de lectura: 29-10-2015 To respond to exogenous and endogenous stimuli, organisms have developed a variety of mechanisms to modulate the quantity, duration and the type of response to these stimuli. Of these mechanisms, one of the most important is the regulation of gene expression. This regulation of gene expression occurs at various levels but especially by th...

  4. Optogenetics for gene expression in mammalian cells.

    Science.gov (United States)

    Müller, Konrad; Naumann, Sebastian; Weber, Wilfried; Zurbriggen, Matias D

    2015-02-01

    Molecular switches that are controlled by chemicals have evolved as central research instruments in mammalian cell biology. However, these tools are limited in terms of their spatiotemporal resolution due to freely diffusing inducers. These limitations have recently been addressed by the development of optogenetic, genetically encoded, and light-responsive tools that can be controlled with the unprecedented spatiotemporal precision of light. In this article, we first provide a brief overview of currently available optogenetic tools that have been designed to control diverse cellular processes. Then, we focus on recent developments in light-controlled gene expression technologies and provide the reader with a guideline for choosing the most suitable gene expression system.

  5. Validation of commonly used reference genes for sleep-related gene expression studies

    Directory of Open Access Journals (Sweden)

    Castro Rosa MRPS

    2009-05-01

    Full Text Available Abstract Background Sleep is a restorative process and is essential for maintenance of mental and physical health. In an attempt to understand the complexity of sleep, multidisciplinary strategies, including genetic approaches, have been applied to sleep research. Although quantitative real time PCR has been used in previous sleep-related gene expression studies, proper validation of reference genes is currently lacking. Thus, we examined the effect of total or paradoxical sleep deprivation (TSD or PSD on the expression stability of the following frequently used reference genes in brain and blood: beta-actin (b-actin, beta-2-microglobulin (B2M, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, and hypoxanthine guanine phosphoribosyl transferase (HPRT. Results Neither TSD nor PSD affected the expression stability of all tested genes in both tissues indicating that b-actin, B2M, GAPDH and HPRT are appropriate reference genes for the sleep-related gene expression studies. In order to further verify these results, the relative expression of brain derived neurotrophic factor (BDNF and glycerol-3-phosphate dehydrogenase1 (GPD1 was evaluated in brain and blood, respectively. The normalization with each of four reference genes produced similar pattern of expression in control and sleep deprived rats, but subtle differences in the magnitude of expression fold change were observed which might affect the statistical significance. Conclusion This study demonstrated that sleep deprivation does not alter the expression stability of commonly used reference genes in brain and blood. Nonetheless, the use of multiple reference genes in quantitative RT-PCR is required for the accurate results.

  6. Genes Expressed in Human Tumor Endothelium

    Science.gov (United States)

    St. Croix, Brad; Rago, Carlo; Velculescu, Victor; Traverso, Giovanni; Romans, Katharine E.; Montgomery, Elizabeth; Lal, Anita; Riggins, Gregory J.; Lengauer, Christoph; Vogelstein, Bert; Kinzler, Kenneth W.

    2000-08-01

    To gain a molecular understanding of tumor angiogenesis, we compared gene expression patterns of endothelial cells derived from blood vessels of normal and malignant colorectal tissues. Of over 170 transcripts predominantly expressed in the endothelium, 79 were differentially expressed, including 46 that were specifically elevated in tumor-associated endothelium. Several of these genes encode extracellular matrix proteins, but most are of unknown function. Most of these tumor endothelial markers were expressed in a wide range of tumor types, as well as in normal vessels associated with wound healing and corpus luteum formation. These studies demonstrate that tumor and normal endothelium are distinct at the molecular level, a finding that may have significant implications for the development of anti-angiogenic therapies.

  7. Gene Expression Data Knowledge Discovery using Global and Local Clustering

    CERN Document Server

    H, Swathi

    2010-01-01

    To understand complex biological systems, the research community has produced huge corpus of gene expression data. A large number of clustering approaches have been proposed for the analysis of gene expression data. However, extracting important biological knowledge is still harder. To address this task, clustering techniques are used. In this paper, hybrid Hierarchical k-Means algorithm is used for clustering and biclustering gene expression data is used. To discover both local and global clustering structure biclustering and clustering algorithms are utilized. A validation technique, Figure of Merit is used to determine the quality of clustering results. Appropriate knowledge is mined from the clusters by embedding a BLAST similarity search program into the clustering and biclustering process. To discover both local and global clustering structure biclustering and clustering algorithms are utilized. To determine the quality of clustering results, a validation technique, Figure of Merit is used. Appropriate ...

  8. Development of Gene Expression Signatures for Practical Radiation Biodosimetry

    International Nuclear Information System (INIS)

    Purpose: In a large-scale radiologic emergency, estimates of exposure doses and radiation injury would be required for individuals without physical dosimeters. Current methods are inadequate for the task, so we are developing gene expression profiles for radiation biodosimetry. This approach could provide both an estimate of physical radiation dose and an indication of the extent of individual injury or future risk. Methods and Materials: We used whole genome microarray expression profiling as a discovery platform to identify genes with the potential to predict radiation dose across an exposure range relevant for medical decision making in a radiologic emergency. Human peripheral blood from 10 healthy donors was irradiated ex vivo, and global gene expression was measured both 6 and 24 h after exposure. Results: A 74-gene signature was identified that distinguishes between four radiation doses (0.5, 2, 5, and 8 Gy) and controls. More than one third of these genes are regulated by TP53. A nearest centroid classifier using these same 74 genes correctly predicted 98% of samples taken either 6 h or 24 h after treatment as unexposed, exposed to 0.5, 2, or ≥5 Gy. Expression patterns of five genes (CDKN1A, FDXR, SESN1, BBC3, and PHPT1) from this signature were also confirmed by real-time polymerase chain reaction. Conclusion: The ability of a single gene set to predict radiation dose throughout a window of time without need for individual pre-exposure controls represents an important advance in the development of gene expression for biodosimetry

  9. Effect of surgical procedures on prostate tumor gene expression profiles

    Institute of Scientific and Technical Information of China (English)

    Jie Li; Zhi-Hong Zhang; Chang-Jun Yin; Christian Pavlovich; Jun Luo; Robert Getzenberg; Wei Zhang

    2012-01-01

    Current surgical treatment of prostate cancer is typically accomplished by either open radical prostatectomy (ORP) or robotic-assisted laparoscopic radical prostatectomy (RALRP).Intra-operative procedural differences between the two surgical approaches may alter the molecular composition of resected surgical specimens,which are indispensable for molecular analysis and biomarker evaluation.The objective of this study is to investigate the effect of different surgical procedures on RNA quality and genome-wide expression signature.RNA integrity number (RIN) values were compared between total RNA samples extracted from consecutive LRP (n=11 ) and ORP (n=24) prostate specimens.Expression profiling was performed using the Agilent human whole-genome expression microarrays.Expression differences by surgical type were analyzed by Volcano plot analysis and gene ontology analysis.Quantitative reverse transcription (RT)-PCR was used for expression validation in an independent set of LRP (n=8) and ORP (n=8) samples.The LRP procedure did not compromise RNA integrity.Differential gene expression by surgery types was limited to a small subset of genes,the number of which was smaller than that expected by chance.Unexpectedly,this small subset of differentially expressed genes was enriched for those encoding transcription factors,oxygen transporters and other previously reported surgery-induced stress-response genes,and demonstrated unidirectional reduction in LRP specimens in comparison to ORP specimens.The effect of the LRP procedure on RNA quality and genome-wide transcript levels is negligible,supporting the suitability of LRP surgical specimens for routine molecular analysis.Blunted in vivo stress response in LRP specimens,likely mediated by CO2 insufflation but not by longer ischemia time,is manifested in the reduced expression of stress-response genes in these specimens.

  10. Sequence and gene expression evolution of paralogous genes in willows.

    Science.gov (United States)

    Harikrishnan, Srilakshmy L; Pucholt, Pascal; Berlin, Sofia

    2015-12-22

    Whole genome duplications (WGD) have had strong impacts on species diversification by triggering evolutionary novelties, however, relatively little is known about the balance between gene loss and forces involved in the retention of duplicated genes originating from a WGD. We analyzed putative Salicoid duplicates in willows, originating from the Salicoid WGD, which took place more than 45 Mya. Contigs were constructed by de novo assembly of RNA-seq data derived from leaves and roots from two genotypes. Among the 48,508 contigs, 3,778 pairs were, based on fourfold synonymous third-codon transversion rates and syntenic positions, predicted to be Salicoid duplicates. Both copies were in most cases expressed in both tissues and 74% were significantly differentially expressed. Mean Ka/Ks was 0.23, suggesting that the Salicoid duplicates are evolving by purifying selection. Gene Ontology enrichment analyses showed that functions related to DNA- and nucleic acid binding were over-represented among the non-differentially expressed Salicoid duplicates, while functions related to biosynthesis and metabolism were over-represented among the differentially expressed Salicoid duplicates. We propose that the differentially expressed Salicoid duplicates are regulatory neo- and/or subfunctionalized, while the non-differentially expressed are dose sensitive, hence, functionally conserved. Multiple evolutionary processes, thus drive the retention of Salicoid duplicates in willows.

  11. Garlic Influences Gene Expression In Vivo and In Vitro.

    Science.gov (United States)

    Charron, Craig S; Dawson, Harry D; Novotny, Janet A

    2016-02-01

    There is a large body of preclinical research aimed at understanding the roles of garlic and garlic-derived preparations in the promotion of human health. Most of this research has targeted the possible functions of garlic in maintaining cardiovascular health and in preventing and treating cancer. A wide range of outcome variables has been used to investigate the bioactivity of garlic, ranging from direct measures of health status such as cholesterol concentrations, blood pressure, and changes in tumor size and number, to molecular and biochemical measures such as mRNA gene expression, protein concentration, enzyme activity, and histone acetylation status. Determination of how garlic influences mRNA gene expression has proven to be a valuable approach to elucidating the mechanisms of garlic bioactivity. Preclinical studies investigating the health benefits of garlic far outnumber human studies and have made frequent use of mRNA gene expression measurement. There is an immediate need to understand mRNA gene expression in humans as well. Although safety and ethical constraints limit the types of available human tissue, peripheral whole blood is readily accessible, and measuring mRNA gene expression in whole blood may provide a unique window to understanding how garlic intake affects human health. PMID:26764328

  12. Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

    Energy Technology Data Exchange (ETDEWEB)

    Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands); Pronk, Tessa E. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Brandhof, Evert-Jan van den [Centre for Environmental Quality, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Ven, Leo T.M. van der [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Piersma, Aldert H. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands)

    2013-10-01

    The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol and saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.

  13. Gene expression profiling of human erythroid progenitors by micro-serial analysis of gene expression.

    Science.gov (United States)

    Fujishima, Naohito; Hirokawa, Makoto; Aiba, Namiko; Ichikawa, Yoshikazu; Fujishima, Masumi; Komatsuda, Atsushi; Suzuki, Yoshiko; Kawabata, Yoshinari; Miura, Ikuo; Sawada, Ken-ichi

    2004-10-01

    We compared the expression profiles of highly purified human CD34+ cells and erythroid progenitor cells by micro-serial analysis of gene expression (microSAGE). Human CD34+ cells were purified from granulocyte colony-stimulating factor-mobilized blood stem cells, and erythroid progenitors were obtained by cultivating these cells in the presence of stem cell factor, interleukin 3, and erythropoietin. Our 10,202 SAGE tags allowed us to identify 1354 different transcripts appearing more than once. Erythroid progenitor cells showed increased expression of LRBA, EEF1A1, HSPCA, PILRB, RANBP1, NACA, and SMURF. Overexpression of HSPCA was confirmed by real-time polymerase chain reaction analysis. MicroSAGE revealed an unexpected preferential expression of several genes in erythroid progenitor cells in addition to the known functional genes, including hemoglobins. Our results provide reference data for future studies of gene expression in various hematopoietic disorders, including myelodysplastic syndrome and leukemia.

  14. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

    Schembri, Mark; Kjærgaard, K.; Klemm, Per

    2003-01-01

    to antimicrobial treatments and host immune defence responses. Escherichia coli has been used as a model organism to study the mechanisms of growth within adhered communities. In this study, we use DNA microarray technology to examine the global gene expression profile of E. coli during sessile growth compared...

  15. Population-level control of gene expression

    Science.gov (United States)

    Nevozhay, Dmitry; Adams, Rhys; van Itallie, Elizabeth; Bennett, Matthew; Balazsi, Gabor

    2011-03-01

    Gene expression is the process that translates genetic information into proteins, that determine the way cells live, function and even die. It was demonstrated that cells with identical genomes exposed to the same environment can differ in their protein composition and therefore phenotypes. Protein levels can vary between cells due to the stochastic nature of intracellular biochemical events, indicating that the genotype-phenotype connection is not deterministic at the cellular level. We asked whether genomes could encode isogenic cell populations more reliably than single cells. To address this question, we built two gene circuits to control three cell population-level characteristics: gene expression mean, coefficient of variation and non-genetic memory of previous expression states. Indeed, we found that these population-level characteristics were more predictable than the gene expression of single cells in a well-controlled environment. This research was supported by the NIH Director's New Innovator Award 1DP2 OD006481-01 and Welch Foundation Grant C-1729.

  16. The Low Noise Limit in Gene Expression.

    Directory of Open Access Journals (Sweden)

    Roy D Dar

    Full Text Available Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1 a global noise floor uniformly imposed on all genes by expression bursting; and (2 high noise distributed to only a select group of genes.

  17. Gene expression analysis of zebrafish heart regeneration.

    Directory of Open Access Journals (Sweden)

    Ching-Ling Lien

    2006-08-01

    Full Text Available Mammalian hearts cannot regenerate. In contrast, zebrafish hearts regenerate even when up to 20% of the ventricle is amputated. The mechanism of zebrafish heart regeneration is not understood. To systematically characterize this process at the molecular level, we generated transcriptional profiles of zebrafish cardiac regeneration by microarray analyses. Distinct gene clusters were identified based on temporal expression patterns. Genes coding for wound response/inflammatory factors, secreted molecules, and matrix metalloproteinases are expressed in regenerating heart in sequential patterns. Comparisons of gene expression profiles between heart and fin regeneration revealed a set of regeneration core molecules as well as tissue-specific factors. The expression patterns of several secreted molecules around the wound suggest that they play important roles in heart regeneration. We found that both platelet-derived growth factor-a and -b (pdgf-a and pdgf-b are upregulated in regenerating zebrafish hearts. PDGF-B homodimers induce DNA synthesis in adult zebrafish cardiomyocytes. In addition, we demonstrate that a chemical inhibitor of PDGF receptor decreases DNA synthesis of cardiomyocytes both in vitro and in vivo during regeneration. Our data indicate that zebrafish heart regeneration is associated with sequentially upregulated wound healing genes and growth factors and suggest that PDGF signaling is required.

  18. Cluster Analysis of Gene Expression Data

    CERN Document Server

    Domany, E

    2002-01-01

    The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical experiment uses a few tens of such chips, each dedicated to a single sample - such as tissue extracted from a particular tumor. The results of such an experiment contain several hundred thousand numbers, that come in the form of a table, of several thousand rows (one for each gene) and 50 - 100 columns (one for each sample). We developed a clustering methodology to mine such data. In this review I provide a very basic introduction to the subject, aimed at a physics audience with no prior knowledge of either gene expression or clustering methods. I explain what genes are, what is gene expression and how it is measured by DNA chips. Next I explain what is meant by "clustering" and how we analyze the massive amounts of data from such experiments, and present results obtained from a...

  19. Gene Expression Commons: an open platform for absolute gene expression profiling.

    Directory of Open Access Journals (Sweden)

    Jun Seita

    Full Text Available Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

  20. Statistical Approach to Gene Evolution

    CERN Document Server

    Chattopadhyay, S; Chakrabarti, J; Chattopadhyay, Sujay; Kanner, William A.; Chakrabarti, Jayprokas

    2001-01-01

    The evolution in coding DNA sequences brings new flexibility and freedom to the codon words, even as the underlying nucleotides get significantly ordered. These curious contra-rules of gene organisation are observed from the distribution of words and the second moments of the nucleotide letters. These statistical data give us the physics behind the classification of bacteria.

  1. Regulation of methane genes and genome expression

    Energy Technology Data Exchange (ETDEWEB)

    John N. Reeve

    2009-09-09

    At the start of this project, it was known that methanogens were Archaeabacteria (now Archaea) and were therefore predicted to have gene expression and regulatory systems different from Bacteria, but few of the molecular biology details were established. The goals were then to establish the structures and organizations of genes in methanogens, and to develop the genetic technologies needed to investigate and dissect methanogen gene expression and regulation in vivo. By cloning and sequencing, we established the gene and operon structures of all of the “methane” genes that encode the enzymes that catalyze methane biosynthesis from carbon dioxide and hydrogen. This work identified unique sequences in the methane gene that we designated mcrA, that encodes the largest subunit of methyl-coenzyme M reductase, that could be used to identify methanogen DNA and establish methanogen phylogenetic relationships. McrA sequences are now the accepted standard and used extensively as hybridization probes to identify and quantify methanogens in environmental research. With the methane genes in hand, we used northern blot and then later whole-genome microarray hybridization analyses to establish how growth phase and substrate availability regulated methane gene expression in Methanobacterium thermautotrophicus ΔH (now Methanothermobacter thermautotrophicus). Isoenzymes or pairs of functionally equivalent enzymes catalyze several steps in the hydrogen-dependent reduction of carbon dioxide to methane. We established that hydrogen availability determine which of these pairs of methane genes is expressed and therefore which of the alternative enzymes is employed to catalyze methane biosynthesis under different environmental conditions. As were unable to establish a reliable genetic system for M. thermautotrophicus, we developed in vitro transcription as an alternative system to investigate methanogen gene expression and regulation. This led to the discovery that an archaeal protein

  2. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    OpenAIRE

    Jesús Lascorz; Kari Hemminki; Asta Försti

    2011-01-01

    Background: A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-r...

  3. Outlier Analysis for Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Chao Yan; Guo-Liang Chen; Yi-Fei Shen

    2004-01-01

    The rapid developments of technologies that generate arrays of gene data enable a global view of the transcription levels of hundreds of thousands of genes simultaneously. The outlier detection problem for gene data has its importance but together with the difficulty of high dimensionality. The sparsity of data in high dimensional space makes each point a relatively good outlier in the view of traditional distance-based definitions. Thus, finding outliers in high dimensional data is more complex. In this paper, sme basic outlier analysis algorithms are discussed and a new genetic algorithm is presented. This algorithm is to find best dimension projections based on a revised cell-based algorithm and to give explanations to solutions. It can solve the outlier detection problem for gene expression data and for other high dimensional data as well.

  4. Coevolution of gene expression among interacting proteins

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Wall, Dennis P.; Eisen,Michael B.

    2004-03-01

    Physically interacting proteins or parts of proteins are expected to evolve in a coordinated manner that preserves proper interactions. Such coevolution at the amino acid-sequence level is well documented and has been used to predict interacting proteins, domains, and amino acids. Interacting proteins are also often precisely coexpressed with one another, presumably to maintain proper stoichiometry among interacting components. Here, we show that the expression levels of physically interacting proteins coevolve. We estimate average expression levels of genes from four closely related fungi of the genus Saccharomyces using the codon adaptation index and show that expression levels of interacting proteins exhibit coordinated changes in these different species. We find that this coevolution of expression is a more powerful predictor of physical interaction than is coevolution of amino acid sequence. These results demonstrate previously uncharacterized coevolution of gene expression, adding a different dimension to the study of the coevolution of interacting proteins and underscoring the importance of maintaining coexpression of interacting proteins over evolutionary time. Our results also suggest that expression coevolution can be used for computational prediction of protein protein interactions.

  5. Identification of differently expressed genes in human colorectal adenocarcinoma

    Institute of Scientific and Technical Information of China (English)

    Yao Chen; Yi-Zeng Zhang; Zong-Guang Zhou; Gang Wang; Zeng-Ni Yi

    2006-01-01

    AIM: To investigate the differently expressed genes in human colorectal adenocarcinoma.METHODS: The integrated approach for gene expression profiling that couples suppression subtractive hybridization, high-throughput cDNA array, sequencing,bioinformatics analysis, and reverse transcriptase realtime quantitative polymerase chain reaction (PCR)was carried out. A set of cDNA clones including 1260SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with florescent-labeled probes prepared from RNA of human colorectal adenocarcinoma (HCRAC) and normal colorectal tissues.RESULTS: A total of 86 genes were identified, 16 unknown genes and 70 known genes. The transcription factor Sox9 influencing cell differentiation was downregulated. At the same time, Heat shock protein 10 KDis downregulated and Calmoulin is up-regulated.CONCLUSION: Downregulation of heat shock protein 10 KD lost its inhibition of Ras, and then attenuated the Ras GTPase signaling pathway, increased cell proliferation and inhibited cell apoptosis. Down-regulated transcription factor Sox9 influences cell differentiation and cell-specific gene expression. Down-regulated Sox9 also decreases its binding to calmodulin, accumulates calmodulin as receptor-activated kinase and phosphorylase kinase due to the activation of PhK.

  6. Motif-guided sparse decomposition of gene expression data for regulatory module identification

    Directory of Open Access Journals (Sweden)

    Hoffman Eric P

    2011-03-01

    Full Text Available Abstract Background Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated. Results We propose a novel approach, motif-guided sparse decomposition (mSD, to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1 transcription factor activity and (2 the strength of the predicted gene regulation event(s. Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer. Conclusion We have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The

  7. Gene gun delivery systems for cancer vaccine approaches.

    Science.gov (United States)

    Aravindaram, Kandan; Yang, Ning Sun

    2009-01-01

    Gene-based immunization with transgenic DNA vectors expressing tumor-associated antigens (TAA), cytokines, or chemokines, alone or in combination, provides an attractive approach to increase the cytotoxic T cell immunity against various cancer diseases. With this consideration, particle-mediated or gene gun technology has been developed as a nonviral method for gene transfer into various mammalian tissues. It has been shown to induce both humoral and cell-mediated immune responses in both small and large experimental animals. A broad range of somatic cell types, including primary cultures and established cell lines, has been successfully transfected ex vivo or in vitro by gene gun technology, either as suspension or adherent cultures. Here, we show that protocols and techniques for use in gene gun-mediated transgene delivery system for skin vaccination against melanoma using tumor-associated antigen (TAA) human gpl00 and reporter gene assays as experimental systems.

  8. Gene expression profiling in sinonasal adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Sébille-Rivain Véronique

    2009-11-01

    Full Text Available Abstract Background Sinonasal adenocarcinomas are uncommon tumors which develop in the ethmoid sinus after exposure to wood dust. Although the etiology of these tumors is well defined, very little is known about their molecular basis and no diagnostic tool exists for their early detection in high-risk workers. Methods To identify genes involved in this disease, we performed gene expression profiling using cancer-dedicated microarrays, on nine matched samples of sinonasal adenocarcinomas and non-tumor sinusal tissue. Microarray results were validated by quantitative RT-PCR and immunohistochemistry on two additional sets of tumors. Results Among the genes with significant differential expression we selected LGALS4, ACS5, CLU, SRI and CCT5 for further exploration. The overexpression of LGALS4, ACS5, SRI, CCT5 and the downregulation of CLU were confirmed by quantitative RT-PCR. Immunohistochemistry was performed for LGALS4 (Galectin 4, ACS5 (Acyl-CoA synthetase and CLU (Clusterin proteins: LGALS4 was highly up-regulated, particularly in the most differentiated tumors, while CLU was lost in all tumors. The expression of ACS5, was more heterogeneous and no correlation was observed with the tumor type. Conclusion Within our microarray study in sinonasal adenocarcinoma we identified two proteins, LGALS4 and CLU, that were significantly differentially expressed in tumors compared to normal tissue. A further evaluation on a new set of tissues, including precancerous stages and low grade tumors, is necessary to evaluate the possibility of using them as diagnostic markers.

  9. Gene expression profiles in skeletal muscle after gene electrotransfer

    Directory of Open Access Journals (Sweden)

    Eriksen Jens

    2007-06-01

    Full Text Available Abstract Background Gene transfer by electroporation (DNA electrotransfer to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have therefore investigated transcriptional changes through gene expression profile analyses, morphological changes by histological analysis, and physiological changes by force generation measurements. DNA electrotransfer was obtained using a combination of a short high voltage pulse (HV, 1000 V/cm, 100 μs followed by a long low voltage pulse (LV, 100 V/cm, 400 ms; a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP and excised at 4 hours, 48 hours or 3 weeks after treatment. Results Differentially expressed genes were investigated by microarray analysis, and descriptive statistics were performed to evaluate the effects of 1 electroporation, 2 DNA injection, and 3 time after treatment. The biological significance of the results was assessed by gene annotation and supervised cluster analysis. Generally, electroporation caused down-regulation of structural proteins e.g. sarcospan and catalytic enzymes. Injection of DNA induced down-regulation of intracellular transport proteins e.g. sentrin. The effects on muscle fibres were transient as the expression profiles 3 weeks after treatment were closely related with the control muscles. Most interestingly, no changes in the expression of proteins involved in inflammatory responses or muscle regeneration was detected, indicating limited muscle damage and regeneration. Histological analysis revealed structural changes with loss of cell integrity and striation pattern in some fibres after DNA+HV+LV treatment, while HV+LV pulses alone showed preservation of cell integrity. No difference in the force generation capacity was observed in

  10. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

    Hojman, Pernille; Zibert, John R; Gissel, Hanne;

    2007-01-01

    BACKGROUND: Gene transfer by electroporation (DNA electrotransfer) to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have...... investigated by microarray analysis, and descriptive statistics were performed to evaluate the effects of 1) electroporation, 2) DNA injection, and 3) time after treatment. The biological significance of the results was assessed by gene annotation and supervised cluster analysis.Generally, electroporation...

  11. Multi-species microarrays reveal the effect of sequence divergence on gene expression profiles

    OpenAIRE

    Gilad, Yoav; Rifkin, Scott A.; Bertone, Paul; Gerstein, Mark; White, Kevin P

    2005-01-01

    Interspecies comparisons of gene expression levels will increase our understanding of the evolution of transcriptional mechanisms and help to identify targets of natural selection. This approach holds particular promise for apes, as many human-specific adaptations are thought to result from differences in gene expression rather than in coding sequence. To date, however, all studies directly comparing interspecies gene expression have been performed on single-species arrays, so that it has bee...

  12. Radiopharmaceuticals to monitor the expression of transferred genes in gene transfer therapy

    International Nuclear Information System (INIS)

    The development and application of radiopharmaceuticals has, in many instances, been based on the pharmacological properties of therapeutic agents. The molecular biology-biotechnology revolution has had an important impact on treatment of diseases, in part through the reduced toxicity of 'biologicals', in part because of their specificity for interaction at unique molecular sites and in part because of their selective delivery to the target site. Immunotherapeutic approaches include the use of monoclonal antibodies (MABs), MAB-fragments and chemotactic peptides. Such agents currently form the basis of both diagnostic and immunotherapeutic radiopharmaceuticals. More recently, gene transfer techniques have been advanced to the point that a new molecular approach, gene therapy, has become a reality. Gene therapy offers an opportunity to attack disease at its most fundamental level. The therapeutic mechanism is based on the expression of a specific gene or genes, the product of which will invoke immunological, receptor-based or enzyme-based therapeutic modalities. Several approaches to gene therapy of cancer have been envisioned, the most clinically-advanced concepts involving the introduction of genes that will encode for molecular targets nor normally found in healthy mammalian cells. A number of gene therapy clinical trials are based on the introduction of the Herpes simplex virus type-1 (HSV-1) gene that encodes for viral thymidine kinase (tk+). Once HSV-1 tk+ is expressed in the target (cancer) cell, therapy can be effected by the administration of a highly molecularly-targeted and systemically non-toxic antiviral drug such as ganciclovir. The development of radiodiagnostic imaging in gene therapy will be reviewed, using HSV-1 tk+ and radioiodinated IVFRU as a basis for development of the theme. Molecular targets that could be exploited in gene therapy, other than tk+, will be identified

  13. Radiopharmaceuticals to monitor the expression of transferred genes in gene transfer therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wiebe, L. I. [University of Alberta, Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

    1997-10-01

    The development and application of radiopharmaceuticals has, in many instances, been based on the pharmacological properties of therapeutic agents. The molecular biology-biotechnology revolution has had an important impact on treatment of diseases, in part through the reduced toxicity of `biologicals`, in part because of their specificity for interaction at unique molecular sites and in part because of their selective delivery to the target site. Immunotherapeutic approaches include the use of monoclonal antibodies (MABs), MAB-fragments and chemotactic peptides. Such agents currently form the basis of both diagnostic and immunotherapeutic radiopharmaceuticals. More recently, gene transfer techniques have been advanced to the point that a new molecular approach, gene therapy, has become a reality. Gene therapy offers an opportunity to attack disease at its most fundamental level. The therapeutic mechanism is based on the expression of a specific gene or genes, the product of which will invoke immunological, receptor-based or enzyme-based therapeutic modalities. Several approaches to gene therapy of cancer have been envisioned, the most clinically-advanced concepts involving the introduction of genes that will encode for molecular targets nor normally found in healthy mammalian cells. A number of gene therapy clinical trials are based on the introduction of the Herpes simplex virus type-1 (HSV-1) gene that encodes for viral thymidine kinase (tk+). Once HSV-1 tk+ is expressed in the target (cancer) cell, therapy can be effected by the administration of a highly molecularly-targeted and systemically non-toxic antiviral drug such as ganciclovir. The development of radiodiagnostic imaging in gene therapy will be reviewed, using HSV-1 tk+ and radioiodinated IVFRU as a basis for development of the theme. Molecular targets that could be exploited in gene therapy, other than tk+, will be identified

  14. Development of a synthetic gene network to modulate gene expression by mechanical forces.

    Science.gov (United States)

    Kis, Zoltán; Rodin, Tania; Zafar, Asma; Lai, Zhangxing; Freke, Grace; Fleck, Oliver; Del Rio Hernandez, Armando; Towhidi, Leila; Pedrigi, Ryan M; Homma, Takayuki; Krams, Rob

    2016-01-01

    The majority of (mammalian) cells in our body are sensitive to mechanical forces, but little work has been done to develop assays to monitor mechanosensor activity. Furthermore, it is currently impossible to use mechanosensor activity to drive gene expression. To address these needs, we developed the first mammalian mechanosensitive synthetic gene network to monitor endothelial cell shear stress levels and directly modulate expression of an atheroprotective transcription factor by shear stress. The technique is highly modular, easily scalable and allows graded control of gene expression by mechanical stimuli in hard-to-transfect mammalian cells. We call this new approach mechanosyngenetics. To insert the gene network into a high proportion of cells, a hybrid transfection procedure was developed that involves electroporation, plasmids replication in mammalian cells, mammalian antibiotic selection, a second electroporation and gene network activation. This procedure takes 1 week and yielded over 60% of cells with a functional gene network. To test gene network functionality, we developed a flow setup that exposes cells to linearly increasing shear stress along the length of the flow channel floor. Activation of the gene network varied logarithmically as a function of shear stress magnitude. PMID:27404994

  15. Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering.

    Science.gov (United States)

    Deveci, Mehmet; Küçüktunç, Onur; Eren, Kemal; Bozdağ, Doruk; Kaya, Kamer; Çatalyürek, Ümit V

    2016-01-01

    Rapid development and increasing popularity of gene expression microarrays have resulted in a number of studies on the discovery of co-regulated genes. One important way of discovering such co-regulations is the query-based search since gene co-expressions may indicate a shared role in a biological process. Although there exist promising query-driven search methods adapting clustering, they fail to capture many genes that function in the same biological pathway because microarray datasets are fraught with spurious samples or samples of diverse origin, or the pathways might be regulated under only a subset of samples. On the other hand, a class of clustering algorithms known as biclustering algorithms which simultaneously cluster both the items and their features are useful while analyzing gene expression data, or any data in which items are related in only a subset of their samples. This means that genes need not be related in all samples to be clustered together. Because many genes only interact under specific circumstances, biclustering may recover the relationships that traditional clustering algorithms can easily miss. In this chapter, we briefly summarize the literature using biclustering for querying co-regulated genes. Then we present a novel biclustering approach and evaluate its performance by a thorough experimental analysis. PMID:26626937

  16. FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

    DEFF Research Database (Denmark)

    Manijak, Mieszko P.; Nielsen, Henrik Bjørn

    2011-01-01

    circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700......BACKGROUND: Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

  17. Gene expression in Pseudomonas aeruginosa swarming motility

    Directory of Open Access Journals (Sweden)

    Déziel Eric

    2010-10-01

    Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressed genes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in gene expression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

  18. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

    Directory of Open Access Journals (Sweden)

    Teng Shaolei

    2013-01-01

    Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

  19. Annotation of gene function in citrus using gene expression information and co-expression networks

    OpenAIRE

    Wong, Darren CJ; Sweetman, Crystal; Ford, Christopher M

    2014-01-01

    Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related bi...

  20. Differential expression of cell adhesion genes

    DEFF Research Database (Denmark)

    Stein, Wilfred D; Litman, Thomas; Fojo, Tito;

    2005-01-01

    It is well known that tumors arising from tissues such as kidney, pancreas, liver and stomach are particularly refractory to treatment. Searching for new anticancer drugs using cells in culture has yielded some effective therapies, but these refractory tumors remain intractable. Studies that comp......It is well known that tumors arising from tissues such as kidney, pancreas, liver and stomach are particularly refractory to treatment. Searching for new anticancer drugs using cells in culture has yielded some effective therapies, but these refractory tumors remain intractable. Studies...... survival might, therefore, act through such a matrix-to-cell suppression of apoptosis. Indeed, correlative mining of gene expression and patient survival databases suggests that poor survival in patients with metastatic cancer correlates highly with tumor expression of a common theme: the genes involved...

  1. Regulation of Gene Expression in Protozoa Parasites

    OpenAIRE

    Consuelo Gomez; Esther Ramirez, M.; Mercedes Calixto-Galvez; Olivia Medel; Rodríguez, Mario A

    2010-01-01

    Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or dru...

  2. Gene expression profiling: methods and protocols

    OpenAIRE

    Manuela Monti

    2012-01-01

    There must be some good reasons to last for a second edition on the very same topic: likely, the topic is crucial to basic and applied science, it is a very rapid evolving topic and there must occurred some breakthroughs meanwhile the two editions. Well, I think that all of these reasons are here to justify this very wellcome second edition of “Gene expression profiling”, a topic that is crucial....

  3. Proteomic and gene expression patterns of keratoconus

    Directory of Open Access Journals (Sweden)

    Arkasubhra Ghosh

    2013-01-01

    Full Text Available Keratoconus is a progressive corneal thinning disease associated with significant tissue remodeling activities and activation of a variety of signaling networks. However, it is not understood how differential gene and protein expression direct function in keratoconus corneas to drive the underlying pathology, ectasia. Research in the field has focused on discovering differentially expressed genes and proteins and quantifying their levels and activities in keratoconus patient samples. In this study, both microarray analysis of total ribonucleic acid (RNA and whole proteome analyses are carried out using corneal epithelium and tears from keratoconus patients and compared to healthy controls. A number of structural proteins, signaling molecules, cytokines, proteases, and enzymes have been found to be deregulated in keratoconus corneas. Together, the data provide clues to the complex process of corneal degradation which suggest novel ways to clinically diagnose and manage the disease. This review will focus on discussing these recent advances in the knowledge of keratoconus biology from a gene expression and function point-of-view.

  4. Carbon Nanomaterials Alter Global Gene Expression Profiles.

    Science.gov (United States)

    Woodman, Sara; Short, John C W; McDermott, Hyoeun; Linan, Alexander; Bartlett, Katelyn; Gadila, Shiva Kumar Goud; Schmelzle, Katie; Wanekaya, Adam; Kim, Kyoungtae

    2016-05-01

    Carbon nanomaterials (CNMs), which include carbon nanotubes (CNTs) and their derivatives, have diverse technological and biomedical applications. The potential toxicity of CNMs to cells and tissues has become an important emerging question in nanotechnology. To assess the toxicity of CNTs and fullerenol C60(OH)24, we in the present work used the budding yeast Saccharomyces cerevisiae, one of the simplest eukaryotic organisms that share fundamental aspects of eukaryotic cell biology. We found that treatment with CNMs, regardless of their physical shape, negatively affected the growth rates, end-point cell densities and doubling times of CNM-exposed yeast cells when compared to unexposed cells. To investigate potential mechanisms behind the CNMs-induced growth defects, we performed RNA-Seq dependent transcriptional analysis and constructed global gene expression profiles of fullerenol C60(OH)24- and CNT-treated cells. When compared to non-treated control cells, CNM-treated cells displayed differential expression of genes whose functions are implicated in membrane transporters and stress response, although differentially expressed genes were not consistent between CNT- and fullerenol C60(OH)24-treated groups, leading to our conclusion that CNMs could serve as environmental toxic factors to eukaryotic cells. PMID:27483901

  5. Analysis of gene expression in rabbit muscle

    Directory of Open Access Journals (Sweden)

    Alena Gálová

    2014-02-01

    Full Text Available Increasing consumer knowledge of the link between diet and health has raised the demand for high quality food. Meat and meat products may be considered as irreplaceable in human nutrition. Breeding livestock to higher content of lean meat and the use of modern hybrids entails problems with the quality of meat. Analysing of livestock genomes could get us a great deal of important information, which may significantly affect the improvement process. Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS, which utilizes high-density single-nucleotide polymorphism (SNP, provides a new way to tackle this issue. New technologies now allow producing microarrays containing thousands of hybridization probes on a single membrane or other solid support. We used microarray analysis to study gene expression in rabbit muscle during different developmental age stages. The outputs from GeneSpring GX sotware are presented in this work. After the evaluation of gene expression in rabbits, will be selected genes of interest in relation to meat quality parameters and will be further analyzed by the available methods of molecular biology and genetics.

  6. A genetic ensemble approach for gene-gene interaction identification

    Directory of Open Access Journals (Sweden)

    Ho Joshua WK

    2010-10-01

    Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

  7. Internet Resources for Gene Expression Analysis in Arabidopsis thaliana.

    Science.gov (United States)

    Hehl, Reinhard; Bülow, Lorenz

    2008-09-01

    The number of online databases and web-tools for gene expression analysis in Arabidopsis thaliana has increased tremendously during the last years. These resources permit the database-assisted identification of putative cis-regulatory DNA sequences, their binding proteins, and the determination of common cis-regulatory motifs in coregulated genes. DNA binding proteins may be predicted by the type of cis-regulatory motif. Further questions of combinatorial control based on the interaction of DNA binding proteins and the colocalization of cis-regulatory motifs can be addressed. The database-assisted spatial and temporal expression analysis of DNA binding proteins and their target genes may help to further refine experimental approaches. Signal transduction pathways upstream of regulated genes are not yet fully accessible in databases mainly because they need to be manually annotated. This review focuses on the use of the AthaMap and PathoPlant((R)) databases for gene expression regulation analysis and discusses similar and complementary online databases and web-tools. Online databases are helpful for the development of working hypothesis and for designing subsequent experiments. PMID:19506727

  8. Wavelet based approach for facial expression recognition

    Directory of Open Access Journals (Sweden)

    Zaenal Abidin

    2015-03-01

    Full Text Available Facial expression recognition is one of the most active fields of research. Many facial expression recognition methods have been developed and implemented. Neural networks (NNs have capability to undertake such pattern recognition tasks. The key factor of the use of NN is based on its characteristics. It is capable in conducting learning and generalizing, non-linear mapping, and parallel computation. Backpropagation neural networks (BPNNs are the approach methods that mostly used. In this study, BPNNs were used as classifier to categorize facial expression images into seven-class of expressions which are anger, disgust, fear, happiness, sadness, neutral and surprise. For the purpose of feature extraction tasks, three discrete wavelet transforms were used to decompose images, namely Haar wavelet, Daubechies (4 wavelet and Coiflet (1 wavelet. To analyze the proposed method, a facial expression recognition system was built. The proposed method was tested on static images from JAFFE database.

  9. Reduced expression of Autographa californica nucleopolyhedrovirus ORF34, an essential gene, enhances heterologous gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Salem, Tamer Z. [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbial Molecular Biology, AGERI, Agricultural Research Center, Giza 12619 (Egypt); Division of Biomedical Sciences, Zewail University, Zewail City of Science and Technology, Giza 12588 (Egypt); Zhang, Fengrui [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Thiem, Suzanne M., E-mail: smthiem@msu.edu [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824 (United States)

    2013-01-20

    Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter gene expression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

  10. Human cellular protein patterns and their link to genome DNA mapping and sequencing data: towards an integrated approach to the study of gene expression

    DEFF Research Database (Denmark)

    Celis, J E; Rasmussen, H H; Leffers, H;

    1993-01-01

    Analysis of cellular protein patterns by computer-aided two-dimensional gel electrophoresis together with recent advances in protein sequence analysis and expression systems have made possible the establishment of comprehensive two-dimensional gel protein databases that may link protein and DNA m...

  11. Refining gene signatures: a Bayesian approach

    Directory of Open Access Journals (Sweden)

    Labbe Aurélie

    2009-12-01

    Full Text Available Abstract Background In high density arrays, the identification of relevant genes for disease classification is complicated by not only the curse of dimensionality but also the highly correlated nature of the array data. In this paper, we are interested in the question of how many and which genes should be selected for a disease class prediction. Our work consists of a Bayesian supervised statistical learning approach to refine gene signatures with a regularization which penalizes for the correlation between the variables selected. Results Our simulation results show that we can most often recover the correct subset of genes that predict the class as compared to other methods, even when accuracy and subset size remain the same. On real microarray datasets, we show that our approach can refine gene signatures to obtain either the same or better predictive performance than other existing methods with a smaller number of genes. Conclusions Our novel Bayesian approach includes a prior which penalizes highly correlated features in model selection and is able to extract key genes in the highly correlated context of microarray data. The methodology in the paper is described in the context of microarray data, but can be applied to any array data (such as micro RNA, for example as a first step towards predictive modeling of cancer pathways. A user-friendly software implementation of the method is available.

  12. The transcriptional regulation of regucalcin gene expression.

    Science.gov (United States)

    Yamaguchi, Masayoshi

    2011-01-01

    Regucalcin, which is discovered as a calcium-binding protein in 1978, has been shown to play a multifunctional role in many tissues and cell types; regucalcin has been proposed to play a pivotal role in keeping cell homeostasis and function for cell response. Regucalcin and its gene are identified in over 15 species consisting of regucalcin family. Comparison of the nucleotide sequences of regucalcin from vertebrate species is highly conserved in their coding region with throughout evolution. The regucalcin gene is localized on the chromosome X in rat and human. The organization of rat regucalcin gene consists of seven exons and six introns and several consensus regulatory elements exist upstream of the 5'-flanking region. AP-1, NF1-A1, RGPR-p117, β-catenin, and other factors have been found to be a transcription factor in the enhancement of regucalcin gene promoter activity. The transcription activity of regucalcin gene is enhanced through intracellular signaling factors that are mediated through the phosphorylation and dephosphorylation of nuclear protein in vitro. Regucalcin mRNA and its protein are markedly expressed in the liver and kidney cortex of rats. The expression of regucalcin mRNA in the liver and kidney cortex has been shown to stimulate by hormonal factors (including calcium, calcitonin, parathyroid hormone, insulin, estrogen, and dexamethasone) in vivo. Regucalcin mRNA expression is enhanced in the regenerating liver after partial hepatectomy of rats in vivo. The expression of regucalcin mRNA in the liver and kidney with pathophysiological state has been shown to suppress, suggesting an involvement of regucalcin in disease. Liver regucalcin expression is down-regulated in tumor cells, suggesting a suppressive role in the development of carcinogenesis. Liver regucalcin is markedly released into the serum of rats with chemically induced liver injury in vivo. Serum regucalcin has a potential sensitivity as a specific biochemical marker of chronic

  13. Cholinergic regulation of VIP gene expression in human neuroblastoma cells

    DEFF Research Database (Denmark)

    Kristensen, Bo; Georg, Birgitte; Fahrenkrug, Jan

    1997-01-01

    Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing......Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing...

  14. The similarity of gene expression between human and mouse tissues

    OpenAIRE

    Dowell, Robin D.

    2011-01-01

    Meta-analysis of human and mouse microarray data reveals conservation of patterns of gene expression that will help to better characterize the evolution of gene expression. See research article: http://genomebiology.com/2010/11/12/R124

  15. Up-regulation of SNCA gene expression: implications to synucleinopathies.

    Science.gov (United States)

    Tagliafierro, L; Chiba-Falek, O

    2016-07-01

    Synucleinopathies are a group of neurodegenerative diseases that share a common pathological lesion of intracellular protein inclusions largely composed by aggregates of alpha-synuclein protein. Accumulating evidence, including genome wide association studies, has implicated alpha-synuclein (SNCA) gene in the etiology of synucleinopathies. However, the precise variants within SNCA gene that contribute to the sporadic forms of Parkinson's disease (PD), dementia with Lewy bodies (DLB), multiple system atrophy (MSA), and other synucleinopathies and their molecular mechanisms of action remain elusive. It has been suggested that SNCA expression levels are critical for the development of these diseases. Here, we review several model systems that have been developed to advance the understanding of the role of SNCA expression levels in the etiology of synucleinopathies. We also describe different molecular mechanisms that regulate SNCA gene expression and discuss possible strategies for SNCA down-regulation as means for therapeutic approaches. Finally, we highlight some examples that underscore the relationships between the genetic association findings and the regulatory mechanisms of SNCA expression, which suggest that genetic variability in SNCA locus is directly responsible, at least in part, to the changes in gene expression and explain the reported associations of SNCA with synucleinopathies. Future studies utilizing induced pluripotent stem cells (iPSCs)-derived neuronal lines and genome editing by CRISPR/Cas9, will allow us to validate, characterize, and manipulate the effects of particular cis-genetic variants on SNCA expression. Moreover, this model system will enable us to compare different neuronal and glial lineages involved in synucleinopathies representing an attractive strategy to elucidate-common and specific-SNCA-genetic variants, regulatory mechanisms, and vulnerable expression levels underlying synucleinopathy spectrum disorders. This forthcoming

  16. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    Directory of Open Access Journals (Sweden)

    Jun Yao

    Full Text Available Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT, recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  17. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    Science.gov (United States)

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W K Alfred; Weinstein, John N

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  18. The gene expression profiling of hepatocellular carcinoma by a network analysis approach shows a dominance of intrinsically disordered proteins (IDPs) between hub nodes.

    Science.gov (United States)

    Singh, Sakshi; Colonna, Giovanni; Di Bernardo, Giovanni; Bergantino, Francesca; Cammarota, Marcella; Castello, Giuseppe; Costantini, Susan

    2015-11-01

    We have analyzed the transcriptomic data from patients with hepatocellular carcinoma (HCC) after viral HCV infection at the various stages of the disease by means of a networking analysis using the publicly available E-MTAB-950 dataset. The data was compared with those obtained in our group from HepG2 cells, a cancer cell line that lacks the viral infection. By sequential pruning of data, and also taking into account the data from cells of healthy patients as blanks, we were able to obtain a distribution of hub genes for the various stages that characterize the disease and finally, we isolated a metabolic sub-net specific to HCC alone. The general picture is that the basic organization to energetically and metabolically sustain the cells in both the normal and diseased conditions is the same, but a complex cluster of sub-networks controlled by hub genes drives the HCC progression with high metabolic flexibility and plasticity. In particular, we have extracted a sub-net of genes strictly correlated to other hub genes of the network from HepG2 cells, but specific for the HCC and mainly devoted to: (i) control at chromatin levels of cell division; (ii) control of ergastoplasmatic stress through protein degradation and misfolding; (iii) control of the immune response also through an increase of mature T-cells in the thymus. This sub-net is characterized by 26 hub genes coding for intrinsically disordered proteins with a high ability to interact with numerous molecular partners. Moreover, we have also noted that periphery molecules, that is, with one or very few interactions (e.g., cytokines or post-translational enzymes), which do not have a central role in the clusters that make up the global metabolic network, essentially have roles as information transporters. The results evidence a strong presence of intrinsically disordered proteins with key roles as hubs in the sub-networks that characterize the various stages of the disease, conferring a structural plasticity to

  19. Genes involved in Drosophila glutamate receptor expression and localization

    Directory of Open Access Journals (Sweden)

    Featherstone David E

    2005-06-01

    types of genes identified, rather than the identities of individual genes. This genomic approach, which circumvents many technical caveats in favor of a wider perspective, suggests that glutamate receptor cluster formation involves many cellular processes, including: 1 cell adhesion and signaling, 2 extensive and relatively specific regulation of gene expression and RNA, 3 the actin and microtubule cytoskeletons, and 4 many novel/unexplored processes, such as those involving mucin/polycystin-like proteins and proteins of unknown function.

  20. A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes.

    Science.gov (United States)

    Cho, Samuel Sunghwan; Kim, Yongkang; Yoon, Joon; Seo, Minseok; Shin, Su-Kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

    2016-01-01

    Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of

  1. A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes.

    Directory of Open Access Journals (Sweden)

    Samuel Sunghwan Cho

    Full Text Available Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs. However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods

  2. Gene Expression Profiling of Xeroderma Pigmentosum

    Directory of Open Access Journals (Sweden)

    Bowden Nikola A

    2006-05-01

    Full Text Available Abstract Xeroderma pigmentosum (XP is a rare recessive disorder that is characterized by extreme sensitivity to UV light. UV light exposure results in the formation of DNA damage such as cyclobutane dimers and (6-4 photoproducts. Nucleotide excision repair (NER orchestrates the removal of cyclobutane dimers and (6-4 photoproducts as well as some forms of bulky chemical DNA adducts. The disease XP is comprised of 7 complementation groups (XP-A to XP-G, which represent functional deficiencies in seven different genes, all of which are believed to be involved in NER. The main clinical feature of XP is various forms of skin cancers; however, neurological degeneration is present in XPA, XPB, XPD and XPG complementation groups. The relationship between NER and other types of DNA repair processes is now becoming evident but the exact relationships between the different complementation groups remains to be precisely determined. Using gene expression analysis we have identified similarities and differences after UV light exposure between the complementation groups XP-A, XP-C, XP-D, XP-E, XP-F, XP-G and an unaffected control. The results reveal that there is a graded change in gene expression patterns between the mildest, most similar to the control response (XP-E and the severest form (XP-A of the disease, with the exception of XP-D. Distinct differences between the complementation groups with neurological symptoms (XP-A, XP-D and XP-G and without (XP-C, XP-E and XP-F were also identified. Therefore, this analysis has revealed distinct gene expression profiles for the XP complementation groups and the first step towards understanding the neurological symptoms of XP.

  3. An anatomic gene expression atlas of the adult mouse brain

    OpenAIRE

    Ng, Lydia; Bernard, Amy; Lau, Chris; Overly, Caroline C.; Dong, Hong-Wei; Kuan, Chihchau; Pathak, Sayan; Sunkin, Susan M.; Dang, Chinh; Bohland, Jason W.; Bokil, Hemant; Mitra, Partha P.; Puelles, Luis; Hohmann, John; Anderson, David J.

    2009-01-01

    Studying gene expression provides a powerful means of understanding structure-function relationships in the nervous system. The availability of genome-scale in situ hybridization datasets enables new possibilities for understanding brain organization based on gene expression patterns. The Anatomic Gene Expression Atlas (AGEA) is a new relational atlas revealing the genetic architecture of the adult C57Bl/6J mouse brain based on spatial correlations across expression data for thousands of gene...

  4. Transcriptome-Wide Differential Gene Expression in Bicyclus anynana Butterflies: Female Vision-Related Genes Are More Plastic.

    Science.gov (United States)

    Macias-Muñoz, Aide; Smith, Gilbert; Monteiro, Antónia; Briscoe, Adriana D

    2016-01-01

    Vision is energetically costly to maintain. Consequently, over time many cave-adapted species downregulate the expression of vision genes or even lose their eyes and associated eye genes entirely. Alternatively, organisms that live in fluctuating environments, with different requirements for vision at different times, may evolve phenotypic plasticity for expression of vision genes. Here, we use a global transcriptomic and candidate gene approach to compare gene expression in the heads of a polyphenic butterfly. Bicyclus anynana have two seasonal forms that display sexual dimorphism and plasticity in eye morphology, and female-specific plasticity in opsin gene expression. Nonchoosy dry season females downregulate opsin expression, consistent with the high physiological cost of vision. To identify other genes associated with sexually dimorphic and seasonally plastic differences in vision, we analyzed RNA-sequencing data from whole head tissues. We identified two eye development genes (klarsicht and warts homologs) and an eye pigment biosynthesis gene (henna) differentially expressed between seasonal forms. By comparing sex-specific expression across seasonal forms, we found that klarsicht, warts, henna, and another eye development gene (domeless) were plastic in a female-specific manner. In a male-only analysis, white (w) was differentially expressed between seasonal forms. Reverse transcription polymerase chain reaction confirmed that warts and white are expressed in eyes only, whereas klarsicht, henna and domeless are expressed in both eyes and brain. We find that differential expression of eye development and eye pigment genes is associated with divergent eye phenotypes in B. anynana seasonal forms, and that there is a larger effect of season on female vision-related genes.

  5. Bi-clustering gene expression data under constraints

    OpenAIRE

    Le, Thanh; Fierro Gutiérrez, Ana Carolina Elisa; Guns, Tias; van Leeuwen, Matthijs; Nijssen, Siegfried; De Raedt, Luc; Marchal, Kathleen

    2013-01-01

    This paper presents a constraint-based approach to mining bi-clusters in gene expression data. Instead of designing an algorithm for each specific task, we propose to use constraint programming to turn the mining problem into a constraint satisfaction and/or optimisation problem. We demonstrate this promising approach on two cases. The first is to mine a single constant-row bi-cluster under noise constraints. The second is to mine a set of generic noisy constant-row bi-clusters under structu...

  6. Studying the Complex Expression Dependences between Sets of Coexpressed Genes

    Directory of Open Access Journals (Sweden)

    Mario Huerta

    2014-01-01

    Full Text Available Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.

  7. Mining gene expression data by interpreting principal components

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    Mortazavi Ali

    2006-04-01

    Full Text Available Abstract Background There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis. Results We present a method for automatically identifying such candidate sets of biologically relevant genes using a combination of principal components analysis and information theoretic metrics. To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene microarray expression datasets (or in any other similarly structured high-dimensional dataset. We applied these tools to two public datasets, and highlight sets of genes most affected by specific subsets of conditions (e.g. tissues, treatments, samples, etc.. Statistically significant associations for highlighted gene sets were shown via global analysis for Gene Ontology term enrichment. Together with covariate associations, the tool provides a basis for building testable hypotheses about the biological or experimental causes of observed variation. Conclusion We provide an unsupervised data mining technique for diverse microarray expression datasets that is distinct from major methods now in routine use. In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes. It

  8. Gene expression in developing watermelon fruit

    Directory of Open Access Journals (Sweden)

    Hernandez Alvaro

    2008-06-01

    Full Text Available Abstract Background Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb. Matsum. & Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR. Results High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon

  9. Gene Expression Profile Changes in Germinating Rice

    Institute of Scientific and Technical Information of China (English)

    Dongli He; Chao Han; Pingfang Yang

    2011-01-01

    Water absorption is a prerequisite for seed germination.During imbibition,water influx causes the resumption of many physiological and metabolic processes in growing seed.In order to obtain more complete knowledge about the mechanism of seed germination,two-dimensional gel electrophoresis was applied to investigate the protein profile changes of rice seed during the first 48 h of imbibition.Thirtynine differentially expressed proteins were identified,including 19 down-regulated and 20 up-regulated proteins.Storage proteins and some seed development- and desiccation-associated proteins were down regulated.The changed patterns of these proteins indicated extensive mobilization of seed reserves.By contrast,catabolism-associated proteins were up regulated upon imbibition.Semi-quantitative real time polymerase chain reaction analysis showed that most of the genes encoding the down- or upregulated proteins were also down or up regulated at mRNA level.The expression of these genes was largely consistent at mRNA and protein levels.In providing additional information concerning gene regulation in early plant life,this study will facilitate understanding of the molecular mechanisms of seed germination.

  10. Nuclear AXIN2 represses MYC gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Rennoll, Sherri A.; Konsavage, Wesley M.; Yochum, Gregory S., E-mail: gsy3@psu.edu

    2014-01-03

    Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC gene expression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC gene expression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling.

  11. Performance Analysis of Enhanced Clustering Algorithm for Gene Expression Data

    CERN Document Server

    Chandrasekhar, T; Elayaraja, E

    2011-01-01

    Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this paper we applied K-Means with Automatic Generations of Merge Factor for ISODATA- AGMFI. Though AGMFI has been applied for clustering of Gene Expression Data, this proposed Enhanced Automatic Generations of Merge Factor for ISODATA- EAGMFI Algorithms overcome the drawbacks of AGMFI in terms of specifying the optimal number of clusters and initialization of good cluster centroids. Experimental results on Gene Expression Data show that the proposed EAGMFI algorithms could identify compact clus...

  12. Novel redox nanomedicine improves gene expression of polyion complex vector

    OpenAIRE

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an RO...

  13. Simultaneous clustering of multiple gene expression and physical interaction datasets.

    Directory of Open Access Journals (Sweden)

    Manikandan Narayanan

    2010-04-01

    Full Text Available Many genome-wide datasets are routinely generated to study different aspects of biological systems, but integrating them to obtain a coherent view of the underlying biology remains a challenge. We propose simultaneous clustering of multiple networks as a framework to integrate large-scale datasets on the interactions among and activities of cellular components. Specifically, we develop an algorithm JointCluster that finds sets of genes that cluster well in multiple networks of interest, such as coexpression networks summarizing correlations among the expression profiles of genes and physical networks describing protein-protein and protein-DNA interactions among genes or gene-products. Our algorithm provides an efficient solution to a well-defined problem of jointly clustering networks, using techniques that permit certain theoretical guarantees on the quality of the detected clustering relative to the optimal clustering. These guarantees coupled with an effective scaling heuristic and the flexibility to handle multiple heterogeneous networks make our method JointCluster an advance over earlier approaches. Simulation results showed JointCluster to be more robust than alternate methods in recovering clusters implanted in networks with high false positive rates. In systematic evaluation of JointCluster and some earlier approaches for combined analysis of the yeast physical network and two gene expression datasets under glucose and ethanol growth conditions, JointCluster discovers clusters that are more consistently enriched for various reference classes capturing different aspects of yeast biology or yield better coverage of the analysed genes. These robust clusters, which are supported across multiple genomic datasets and diverse reference classes, agree with known biology of yeast under these growth conditions, elucidate the genetic control of coordinated transcription, and enable functional predictions for a number of uncharacterized genes.

  14. Improving detection of differentially expressed gene sets by applying cluster enrichment analysis to Gene Ontology

    Directory of Open Access Journals (Sweden)

    Gu JianLei

    2009-08-01

    Full Text Available Abstract Background Gene set analysis based on Gene Ontology (GO can be a promising method for the analysis of differential expression patterns. However, current studies that focus on individual GO terms have limited analytical power, because the complex structure of GO introduces strong dependencies among the terms, and some genes that are annotated to a GO term cannot be found by statistically significant enrichment. Results We proposed a method for enriching clustered GO terms based on semantic similarity, namely cluster enrichment analysis based on GO (CeaGO, to extend the individual term analysis method. Using an Affymetrix HGU95aV2 chip dataset with simulated gene sets, we illustrated that CeaGO was sensitive enough to detect moderate expression changes. When compared to parent-based individual term analysis methods, the results showed that CeaGO may provide more accurate differentiation of gene expression results. When used with two acute leukemia (ALL and ALL/AML microarray expression datasets, CeaGO correctly identified specifically enriched GO groups that were overlooked by other individual test methods. Conclusion By applying CeaGO to both simulated and real microarray data, we showed that this approach could enhance the interpretation of microarray experiments. CeaGO is currently available at http://chgc.sh.cn/en/software/CeaGO/.

  15. Stochastic gene expression with bursting and positive feedback

    Science.gov (United States)

    Platini, Thierry; Pendar, Hodjat; Kulkarni, Rahul

    2012-02-01

    Stochasticity (or noise) in the process of gene expression can play a critical role in cellular circuits that control switching between probabilistic cell-fate decisions in diverse organisms. Such circuits often include positive feedback loops as critical elements. In some cases (e.g. HIV-1 viral infections), switching between different cell fates occurs even in the absence of bistability in the underlying deterministic model. To characterize the role of noise in such systems, we analyze a simple gene expression circuit that includes contributions from both transcriptional and translational bursting and positive feedback effects. Using a combination of analytical approaches and stochastic simulations, we explore how the underlying parameters control the corresponding mean and variance in protein distributions.

  16. Mapping the genetic architecture of gene expression in human liver.

    Directory of Open Access Journals (Sweden)

    Eric E Schadt

    2008-05-01

    Full Text Available Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large

  17. Use of bacterially expressed dsRNA to downregulate Entamoeba histolytica gene expression.

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    Carlos F Solis

    Full Text Available BACKGROUND: Modern RNA interference (RNAi methodologies using small interfering RNA (siRNA oligonucleotide duplexes or episomally synthesized hairpin RNA are valuable tools for the analysis of gene function in the protozoan parasite Entamoeba histolytica. However, these approaches still require time-consuming procedures including transfection and drug selection, or costly synthetic molecules. PRINCIPAL FINDINGS: Here we report an efficient and handy alternative for E. histolytica gene down-regulation mediated by bacterial double-stranded RNA (dsRNA targeting parasite genes. The Escherichia coli strain HT115 which is unable to degrade dsRNA, was genetically engineered to produce high quantities of long dsRNA segments targeting the genes that encode E. histolytica beta-tubulin and virulence factor KERP1. Trophozoites cultured in vitro were directly fed with dsRNA-expressing bacteria or soaked with purified dsRNA. Both dsRNA delivery methods resulted in significant reduction of protein expression. In vitro host cell-parasite assays showed that efficient downregulation of kerp1 gene expression mediated by bacterial dsRNA resulted in significant reduction of parasite adhesion and lytic capabilities, thus supporting a major role for KERP1 in the pathogenic process. Furthermore, treatment of trophozoites cultured in microtiter plates, with a repertoire of eighty-five distinct bacterial dsRNA segments targeting E. histolytica genes with unknown function, led to the identification of three genes potentially involved in the growth of the parasite. CONCLUSIONS: Our results showed that the use of bacterial dsRNA is a powerful method for the study of gene function in E. histolytica. This dsRNA delivery method is also technically suitable for the study of a large number of genes, thus opening interesting perspectives for the identification of novel drug and vaccine targets.

  18. Gene Expression Control by Glucocorticoid Receptors during Innate Immune Responses

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    André M. Xavier

    2016-04-01

    Full Text Available Glucocorticoids (GCs are potent anti-inflammatory compounds that have been extensively used in clinical practice for several decades. GCs effects on inflammation are generally mediated through GC receptors (GRs. Signal transduction through these nuclear receptors leads to dramatic changes in gene expression programs in different cell types, typically due to GR binding to DNA or to transcription modulators. During the last decade the view of GCs as exclusive anti-inflammatory molecules has been challenged. GR negative interference in pro-inflammatory gene expression was a landmark in terms of molecular mechanisms that suppress immune activity. In fact, GR can induce varied inhibitory molecules, including a negative regulator of Toll-like receptors (TLRs pathway, or subject key transcription factors, such as NF-B and AP-1, to a repressor mechanism. In contrast, the expression of some acute-phase proteins (APPs and other players of innate immunity generally requires GR signaling. Consequently, GRs must operate context-dependent inhibitory, permissive or stimulatory effects on host defense signaling triggered by pathogens or tissue damage. This review aims to disclose how contradictory or comparable effects on inflammatory gene expression can depend on pharmacological approach (including selective glucocorticoid receptor modulators; SEGRMs, cell culture, animal treatment or transgenic strategies used as models. Although the current view of GR-signaling integrated many advances in the field, some answers to important questions remain elusive.

  19. Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

    KAUST Repository

    Horiuchi, Youko

    2015-12-23

    Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression

  20. Gene expression profiling of cutaneous wound healing

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    Wang Ena

    2007-02-01

    Full Text Available Abstract Background Although the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events. Study Design This study was part of a placebo-controlled double-blind clinical trial in which basal cell carcinomas were treated topically with an immunomodifier – toll-like receptor 7 agonist: imiquimod. The fourteen patients with basal cell carcinoma in the placebo arm of the trial received placebo treatment consisting solely of vehicle cream. A skin punch biopsy was obtained immediately before treatment and at the end of the placebo treatment (after 2, 4 or 8 days. 17.5K cDNA microarrays were utilized to profile the biopsy material. Results Four gene signatures whose expression changed relative to baseline (before wound induction by the pre-treatment biopsy were identified. The largest group was comprised predominantly of inflammatory genes whose expression was increased throughout the study. Two additional signatures were observed which included preferentially pro-inflammatory genes in the early post-treatment biopsies (2 days after pre-treatment biopsies and repair and angiogenesis genes in the later (4 to 8 days biopsies. The fourth and smallest set of genes was down-regulated throughout the study. Early in wound healing the expression of markers of both M1 and M2 macrophages were increased, but later M2 markers predominated. Conclusion The initial response to a cutaneous wound induces powerful transcriptional activation of pro-inflammatory stimuli which may alert the host defense. Subsequently and in the absence of infection, inflammation subsides and it is replaced by angiogenesis and remodeling. Understanding this transition which may be driven by a change from a mixed macrophage population to predominately M2

  1. Network Completion for Static Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Natsu Nakajima

    2014-01-01

    Full Text Available We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.

  2. Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression

    DEFF Research Database (Denmark)

    Hustinx, Steven R; Cao, Dengfeng; Maitra, Anirban;

    2004-01-01

    Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available online SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human...... of this program. Novel differentially expressed genes in a cancer type can be identified by revisiting updated and expanded SAGE databases. TAGmapper should prove to be a powerful tool for the discovery of novel tumor markers through assignment of uncharacterized SAGE tags....

  3. Array2BIO: from microarray expression data to functional annotation of co-regulated genes

    Directory of Open Access Journals (Sweden)

    Rasley Amy

    2006-06-01

    Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

  4. Quantitative analysis of cell-type specific gene expression in the green alga Volvox carteri

    Directory of Open Access Journals (Sweden)

    Hallmann Armin

    2006-12-01

    Full Text Available Abstract Background The multicellular alga Volvox carteri possesses only two cell types: mortal, motile somatic cells and potentially immortal, immotile reproductive cells. It is therefore an attractive model system for studying how cell-autonomous cytodifferentiation is programmed within a genome. Moreover, there are ongoing genome projects both in Volvox carteri and in the closely related unicellular alga Chlamydomonas reinhardtii. However, gene sequencing is only the beginning. To identify cell-type specific expression and to determine relative expression rates, we evaluate the potential of real-time RT-PCR for quantifying gene transcript levels. Results Here we analyze a diversified pool of 39 target genes by real-time RT-PCR for each cell type. This gene pool contains previously known genes with unknown localization of cellular expression, 28 novel genes which are described in this study for the first time, and a few known, cell-type specific genes as a control. The respective gene products are, for instance, part of photosynthesis, cellular regulation, stress response, or transport processes. We provide expression data for all these genes. Conclusion The results show that quantitative real-time RT-PCR is a favorable approach to analyze cell-type specific gene expression in Volvox, which can be extended to a much larger number of genes or to developmental or metabolic mutants. Our expression data also provide a basis for a detailed analysis of individual, previously unknown, cell-type specifically expressed genes.

  5. Ascorbic Acid and Gene Expression: Another Example of Regulation of Gene Expression by Small Molecules?

    OpenAIRE

    Belin, Sophie; Kaya, Ferdinand; Burtey, Stéphane; Fontes, Michel

    2010-01-01

    Ascorbic acid (vitamin C, AA) has long been considered a food supplement necessary for life and for preventing scurvy. However, it has been reported that other small molecules such as retinoic acid (vitamin A) and different forms of calciferol (vitamin D) are directly involved in regulating the expression of numerous genes. These molecules bind to receptors that are differentially expressed in the embryo and are therefore crucial signalling molecules in vertebrate development. The question is...

  6. Autism and increased paternal age related changes in global levels of gene expression regulation.

    Directory of Open Access Journals (Sweden)

    Mark D Alter

    Full Text Available A causal role of mutations in multiple general transcription factors in neurodevelopmental disorders including autism suggested that alterations in global levels of gene expression regulation might also relate to disease risk in sporadic cases of autism. This premise can be tested by evaluating for changes in the overall distribution of gene expression levels. For instance, in mice, variability in hippocampal-dependent behaviors was associated with variability in the pattern of the overall distribution of gene expression levels, as assessed by variance in the distribution of gene expression levels in the hippocampus. We hypothesized that a similar change in variance might be found in children with autism. Gene expression microarrays covering greater than 47,000 unique RNA transcripts were done on RNA from peripheral blood lymphocytes (PBL of children with autism (n = 82 and controls (n = 64. Variance in the distribution of gene expression levels from each microarray was compared between groups of children. Also tested was whether a risk factor for autism, increased paternal age, was associated with variance. A decrease in the variance in the distribution of gene expression levels in PBL was associated with the diagnosis of autism and a risk factor for autism, increased paternal age. Traditional approaches to microarray analysis of gene expression suggested a possible mechanism for decreased variance in gene expression. Gene expression pathways involved in transcriptional regulation were down-regulated in the blood of children with autism and children of older fathers. Thus, results from global and gene specific approaches to studying microarray data were complimentary and supported the hypothesis that alterations at the global level of gene expression regulation are related to autism and increased paternal age. Global regulation of transcription, thus, represents a possible point of convergence for multiple etiologies of autism and other

  7. Detection of gene expression pattern in the early stage after spinal cord injury by gene chip

    Institute of Scientific and Technical Information of China (English)

    刘成龙; 靳安民; 童斌辉

    2003-01-01

    Objective: To study the changes of the gene expression pattern of spinal cord tissues in the early stage after injury by DNA microarray (gene chip). Methods: The contusion model of rat spinal cord was established according to Allen's falling strike method and the gene expression patterns of normal and injured spinal cord tissues were studied by gene chip. Results: The expression of 45 genes was significantly changed in the early stage after spinal cord injury, in which 22 genes up-regulated and 23 genes down-regulated. Conclusions: The expression of some genes changes significantly in the early stage after spinal cord injury, which indicates the complexity of secondary spinal cord injury.

  8. Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis.

    Science.gov (United States)

    Ippolito, Danielle L; AbdulHameed, Mohamed Diwan M; Tawa, Gregory J; Baer, Christine E; Permenter, Matthew G; McDyre, Bonna C; Dennis, William E; Boyle, Molly H; Hobbs, Cheryl A; Streicker, Michael A; Snowden, Bobbi S; Lewis, John A; Wallqvist, Anders; Stallings, Jonathan D

    2016-01-01

    Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be associated with the fibrosis pathology by computationally mining DrugMatrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague Dawley rats dosed with varying concentrations of 3 fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,4'-methylenedianiline) and 2 nonfibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. The 67-plex gene panel accurately diagnosed fibrosis in both microarray and multiplexed-gene expression assays. Necrosis and inflammatory infiltration were comorbid with fibrosis. ANOVA with contrasts identified that 51 of the 67 predicted genes were significantly associated with the fibrosis phenotype, with 24 of these specific to fibrosis alone. The protein product of the gene most strongly correlated with the fibrosis phenotype PCOLCE (Procollagen C-Endopeptidase Enhancer) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (P < .05). Semiquantitative global mass spectrometry analysis of the plasma identified an additional 5 protein products of the gene panel which increased after fibrogenic toxicant administration: fibronectin, ceruloplasmin, vitronectin, insulin-like growth factor binding protein, and α2-macroglobulin. These results support the data mining approach for identifying gene and/or protein panels for assessing liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology.

  9. Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

    Directory of Open Access Journals (Sweden)

    Guo Zheng

    2006-01-01

    Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex

  10. MDR1 gene expression in primary colorectal carcinomas.

    OpenAIRE

    Pirker, R; Wallner, J.; Gsur, A; Götzl, M.; Zöchbauer, S; Scheithauer, W.; Depisch, D

    1993-01-01

    The expression of the MDR1 gene, a multidrug resistance gene, was prospectively determined in 113 primary colorectal carcinoma specimens and correlated with clinical data including survival durations of the patients. MDR1 RNA was detected in 65% of the carcinomas. No expression of the MDR2 gene was seen, MDR1 gene expression was independent of age and sex of the patients, size and histologic grading of the tumour, lymph node involvement and distant metastasis. Kaplan-Meier analysis revealed t...

  11. Prognostic Gene Expression Profiles in Breast Cancer

    DEFF Research Database (Denmark)

    Sørensen, Kristina Pilekær

    Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group and offe......Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... developed metastasis and 82 primary breast tumors from patients who remained metastasis-free, by microarray gene expression profiling. We employed a nested case-control design, where samples were matched, in this study one-to-one, to exclude differences in gene expression based on tumor type, tumor size...

  12. Regulation of gene expression by hypoxia.

    Science.gov (United States)

    Millhorn, D E; Czyzyk-Krzeska, M; Bayliss, D A; Lawson, E E

    1993-12-01

    The present study was undertaken to determine if gene expression for tyrosine hydroxylase (TH), the rate limiting enzyme in the biosynthesis of catecholamines, is regulated in the carotid body, sympathetic ganglia and adrenal medulla by hypoxia. We found that a reduction in oxygen tension from 21% to 10% caused a substantial increase (200% at 1 hour and 500% at 6 hours exposure) in the concentration of TH mRNA in carotid body type I cells but not in either the sympathetic ganglia or adrenal gland. In addition, we found that hypercapnia, another natural stimulus of carotid body activity, failed to enhance TH mRNA in type I cells. Removal of the sensory and sympathetic innervation of the carotid body failed to prevent the induction of TH mRNA by hypoxia in type I cells. Our results show that TH gene expression is regulated by hypoxia in the carotid body but not in other peripheral catecholamine synthesizing tissue and that the regulatory mechanism is intrinsic to type I cells. PMID:7909954

  13. A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

    DEFF Research Database (Denmark)

    de Jong, Simone; Boks, Marco P M; Fuller, Tova F;

    2012-01-01

    of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co......-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One...... of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in...

  14. Biclustering for the comprehensive search of correlated gene expression patterns using clustered seed expansion

    OpenAIRE

    Yun, Taegyun; Yi, Gwan-Su

    2013-01-01

    Background In a functional analysis of gene expression data, biclustering method can give crucial information by showing correlated gene expression patterns under a subset of conditions. However, conventional biclustering algorithms still have some limitations to show comprehensive and stable outputs. Results We propose a novel biclustering approach called “BIclustering by Correlated and Large number of Individual Clustered seeds (BICLIC)” to find comprehensive sets of correlated expression p...

  15. Peripheral blood gene expression profiles in COPD subjects

    OpenAIRE

    2011-01-01

    To identify non-invasive gene expression markers for chronic obstructive pulmonary disease (COPD), we performed genome-wide expression profiling of peripheral blood samples from 12 subjects with significant airflow obstruction and an equal number of non-obstructed controls. RNA was isolated from Peripheral Blood Mononuclear Cells (PBMCs) and gene expression was assessed using Affymetrix U133 Plus 2.0 arrays. Tests for gene expression changes that discriminate between COPD cases (FEV1< 70% pre...

  16. Real-time feedback control of gene expression

    OpenAIRE

    Uhlendorf, Jannis

    2013-01-01

    Gene expression is fundamental for the functioning of cellular processes and is tightly regulated. Inducible promoters allow one to perturb gene expression by changing the expression level of a protein from its physiological level. This is a common tool to decipher the functioning of biological processes: the expression level of a gene is changed and one observes how the perturbed cell behaves differently from an unperturbed cell. A shortcoming of inducible promoters is the difficulty to appl...

  17. A chain reaction approach to modelling gene pathways.

    Science.gov (United States)

    Cheng, Gary C; Chen, Dung-Tsa; Chen, James J; Soong, Seng-Jaw; Lamartiniere, Coral; Barnes, Stephen

    2012-08-01

    BACKGROUND: Of great interest in cancer prevention is how nutrient components affect gene pathways associated with the physiological events of puberty. Nutrient-gene interactions may cause changes in breast or prostate cells and, therefore, may result in cancer risk later in life. Analysis of gene pathways can lead to insights about nutrient-gene interactions and the development of more effective prevention approaches to reduce cancer risk. To date, researchers have relied heavily upon experimental assays (such as microarray analysis, etc.) to identify genes and their associated pathways that are affected by nutrient and diets. However, the vast number of genes and combinations of gene pathways, coupled with the expense of the experimental analyses, has delayed the progress of gene-pathway research. The development of an analytical approach based on available test data could greatly benefit the evaluation of gene pathways, and thus advance the study of nutrient-gene interactions in cancer prevention. In the present study, we have proposed a chain reaction model to simulate gene pathways, in which the gene expression changes through the pathway are represented by the species undergoing a set of chemical reactions. We have also developed a numerical tool to solve for the species changes due to the chain reactions over time. Through this approach we can examine the impact of nutrient-containing diets on the gene pathway; moreover, transformation of genes over time with a nutrient treatment can be observed numerically, which is very difficult to achieve experimentally. We apply this approach to microarray analysis data from an experiment which involved the effects of three polyphenols (nutrient treatments), epigallo-catechin-3-O-gallate (EGCG), genistein, and resveratrol, in a study of nutrient-gene interaction in the estrogen synthesis pathway during puberty. RESULTS: In this preliminary study, the estrogen synthesis pathway was simulated by a chain reaction model. By

  18. Coactivators in PPAR-Regulated Gene Expression

    Directory of Open Access Journals (Sweden)

    Navin Viswakarma

    2010-01-01

    Full Text Available Peroxisome proliferator-activated receptor (PPARα, β (also known as δ, and γ function as sensors for fatty acids and fatty acid derivatives and control important metabolic pathways involved in the maintenance of energy balance. PPARs also regulate other diverse biological processes such as development, differentiation, inflammation, and neoplasia. In the nucleus, PPARs exist as heterodimers with retinoid X receptor-α bound to DNA with corepressor molecules. Upon ligand activation, PPARs undergo conformational changes that facilitate the dissociation of corepressor molecules and invoke a spatiotemporally orchestrated recruitment of transcription cofactors including coactivators and coactivator-associated proteins. While a given nuclear receptor regulates the expression of a prescribed set of target genes, coactivators are likely to influence the functioning of many regulators and thus affect the transcription of many genes. Evidence suggests that some of the coactivators such as PPAR-binding protein (PBP/PPARBP/thyroid hormone receptor-associated protein 220 (TRAP220/mediator complex subunit 1 (MED1 may exert a broader influence on the functions of several nuclear receptors and their target genes. Investigations into the role of coactivators in the function of PPARs should strengthen our understanding of the complexities of metabolic diseases associated with energy metabolism.

  19. Seed-Based Biclustering of Gene Expression Data

    OpenAIRE

    Jiyuan An; Alan Wee-Chung Liew; Colleen C Nelson

    2012-01-01

    BACKGROUND: Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar e...

  20. Gene therapy approaches for spinal cord injury

    Science.gov (United States)

    Bright, Corinne

    As the biomedical engineering field expands, combination technologies are demonstrating enormous potential for treating human disease. In particular, intersections between the rapidly developing fields of gene therapy and tissue engineering hold promise to achieve tissue regeneration. Nonviral gene therapy uses plasmid DNA to deliver therapeutic proteins in vivo for extended periods of time. Tissue engineering employs biomedical materials, such as polymers, to support the regrowth of injured tissue. In this thesis, a combination strategy to deliver genes and drugs in a polymeric scaffold was applied to a spinal cord injury model. In order to develop a platform technology to treat spinal cord injury, several nonviral gene delivery systems and polymeric scaffolds were evaluated in vitro and in vivo. Nonviral vector trafficking was evaluated in primary neuronal culture to develop an understanding of the barriers to gene transfer in neurons and their supporting glia. Although the most efficient gene carrier in vitro differed from the optimal gene carrier in vivo, confocal and electron microscopy of these nonviral vectors provided insights into the interaction of these vectors with the nucleus. A novel pathway for delivering nanoparticles into the nuclei of neurons and Schwann cells via vesicle trafficking was observed in this study. Reporter gene expression levels were evaluated after direct and remote delivery to the spinal cord, and the optimal nonviral vector, dose, and delivery strategy were applied to deliver the gene encoding the basic fibroblast growth factor (bFGF) to the spinal cord. An injectable and biocompatible gel, composed of the amphiphillic polymer poly(ethylene glycol)-poly(epsilon-caprolactone)-poly(ethylene glycol) (PEG-PCL-PEG) was evaluated as a drug and gene delivery system in vitro, and combined with the optimized nonviral gene delivery system to treat spinal cord injury. Plasmid DNA encoding the bFGF gene and the therapeutic NEP1--40 peptide

  1. Expression Divergence of Duplicate Genes in the Protein Kinase Superfamily in Pacific Oyster.

    Science.gov (United States)

    Gao, Dahai; Ko, Dennis C; Tian, Xinmin; Yang, Guang; Wang, Liuyang

    2015-01-01

    Gene duplication has been proposed to serve as the engine of evolutionary innovation. It is well recognized that eukaryotic genomes contain a large number of duplicated genes that evolve new functions or expression patterns. However, in mollusks, the evolutionary mechanisms underlying the divergence and the functional maintenance of duplicate genes remain little understood. In the present study, we performed a comprehensive analysis of duplicate genes in the protein kinase superfamily using whole genome and transcriptome data for the Pacific oyster. A total of 64 duplicated gene pairs were identified based on a phylogenetic approach and the reciprocal best BLAST method. By analyzing gene expression from RNA-seq data from 69 different developmental and stimuli-induced conditions (nine tissues, 38 developmental stages, eight dry treatments, seven heat treatments, and seven salty treatments), we found that expression patterns were significantly correlated for a number of duplicate gene pairs, suggesting the conservation of regulatory mechanisms following divergence. Our analysis also identified a subset of duplicate gene pairs with very high expression divergence, indicating that these gene pairs may have been subjected to transcriptional subfunctionalization or neofunctionalization after the initial duplication events. Further analysis revealed a significant correlation between expression and sequence divergence (as revealed by synonymous or nonsynonymous substitution rates) under certain conditions. Taken together, these results provide evidence for duplicate gene sequence and expression divergence in the Pacific oyster, accompanying its adaptation to harsh environments. Our results provide new insights into the evolution of duplicate genes and their expression levels in the Pacific oyster.

  2. Expression of RNA-interference/antisense transgenes by the cognate promoters of target genes is a better gene-silencing strategy to study gene functions in rice.

    Science.gov (United States)

    Li, Jing; Jiang, Dagang; Zhou, Hai; Li, Feng; Yang, Jiawei; Hong, Laifa; Fu, Xiao; Li, Zhibin; Liu, Zhenlan; Li, Jianming; Zhuang, Chuxiong

    2011-03-03

    Antisense and RNA interference (RNAi)-mediated gene silencing systems are powerful reverse genetic methods for studying gene function. Most RNAi and antisense experiments used constitutive promoters to drive the expression of RNAi/antisense transgenes; however, several reports showed that constitutive promoters were not expressed in all cell types in cereal plants, suggesting that the constitutive promoter systems are not effective for silencing gene expression in certain tissues/organs. To develop an alternative method that complements the constitutive promoter systems, we constructed RNAi and/or antisense transgenes for four rice genes using a constitutive promoter or a cognate promoter of a selected rice target gene and generated many independent transgenic lines. Genetic, molecular, and phenotypic analyses of these RNAi/antisense transgenic rice plants, in comparison to previously-reported transgenic lines that silenced similar genes, revealed that expression of the cognate promoter-driven RNAi/antisense transgenes resulted in novel growth/developmental defects that were not observed in transgenic lines expressing constitutive promoter-driven gene-silencing transgenes of the same target genes. Our results strongly suggested that expression of RNAi/antisense transgenes by cognate promoters of target genes is a better gene-silencing approach to discovery gene function in rice.

  3. Expression of RNA-interference/antisense transgenes by the cognate promoters of target genes is a better gene-silencing strategy to study gene functions in rice.

    Directory of Open Access Journals (Sweden)

    Jing Li

    Full Text Available Antisense and RNA interference (RNAi-mediated gene silencing systems are powerful reverse genetic methods for studying gene function. Most RNAi and antisense experiments used constitutive promoters to drive the expression of RNAi/antisense transgenes; however, several reports showed that constitutive promoters were not expressed in all cell types in cereal plants, suggesting that the constitutive promoter systems are not effective for silencing gene expression in certain tissues/organs. To develop an alternative method that complements the constitutive promoter systems, we constructed RNAi and/or antisense transgenes for four rice genes using a constitutive promoter or a cognate promoter of a selected rice target gene and generated many independent transgenic lines. Genetic, molecular, and phenotypic analyses of these RNAi/antisense transgenic rice plants, in comparison to previously-reported transgenic lines that silenced similar genes, revealed that expression of the cognate promoter-driven RNAi/antisense transgenes resulted in novel growth/developmental defects that were not observed in transgenic lines expressing constitutive promoter-driven gene-silencing transgenes of the same target genes. Our results strongly suggested that expression of RNAi/antisense transgenes by cognate promoters of target genes is a better gene-silencing approach to discovery gene function in rice.

  4. Global gene expression analysis of the zoonotic parasite Trichinella spiralis revealed novel genes in host parasite interaction.

    Directory of Open Access Journals (Sweden)

    Xiaolei Liu

    Full Text Available BACKGROUND: Trichinellosis is a typical food-borne zoonotic disease which is epidemic worldwide and the nematode Trichinella spiralis is the main pathogen. The life cycle of T. spiralis contains three developmental stages, i.e. adult worms, new borne larva (new borne L1 larva and muscular larva (infective L1 larva. Stage-specific gene expression in the parasites has been investigated with various immunological and cDNA cloning approaches, whereas the genome-wide transcriptome and expression features of the parasite have been largely unknown. The availability of the genome sequence information of T. spiralis has made it possible to deeply dissect parasite biology in association with global gene expression and pathogenesis. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we analyzed the global gene expression patterns in the three developmental stages of T. spiralis using digital gene expression (DGE analysis. Almost 15 million sequence tags were generated with the Illumina RNA-seq technology, producing expression data for more than 9,000 genes, covering 65% of the genome. The transcriptome analysis revealed thousands of differentially expressed genes within the genome, and importantly, a panel of genes encoding functional proteins associated with parasite invasion and immuno-modulation were identified. More than 45% of the genes were found to be transcribed from both strands, indicating the importance of RNA-mediated gene regulation in the development of the parasite. Further, based on gene ontological analysis, over 3000 genes were functionally categorized and biological pathways in the three life cycle stage were elucidated. CONCLUSIONS AND SIGNIFICANCE: The global transcriptome of T. spiralis in three developmental stages has been profiled, and most gene activity in the genome was found to be developmentally regulated. Many metabolic and biological pathways have been revealed. The findings of the differential expression of several protein

  5. A Resampling Based Clustering Algorithm for Replicated Gene Expression Data.

    Science.gov (United States)

    Li, Han; Li, Chun; Hu, Jie; Fan, Xiaodan

    2015-01-01

    In gene expression data analysis, clustering is a fruitful exploratory technique to reveal the underlying molecular mechanism by identifying groups of co-expressed genes. To reduce the noise, usually multiple experimental replicates are performed. An integrative analysis of the full replicate data, instead of reducing the data to the mean profile, carries the promise of yielding more precise and robust clusters. In this paper, we propose a novel resampling based clustering algorithm for genes with replicated expression measurements. Assuming those replicates are exchangeable, we formulate the problem in the bootstrap framework, and aim to infer the consensus clustering based on the bootstrap samples of replicates. In our approach, we adopt the mixed effect model to accommodate the heterogeneous variances and implement a quasi-MCMC algorithm to conduct statistical inference. Experiments demonstrate that by taking advantage of the full replicate data, our algorithm produces more reliable clusters and has robust performance in diverse scenarios, especially when the data is subject to multiple sources of variance. PMID:26671802

  6. Expression profiles for six zebrafish genes during gonadal sex differentiation

    DEFF Research Database (Denmark)

    Jørgensen, Anne; Morthorst, Jane E.; Andersen, Ole;

    2008-01-01

    the precise timing of expression of six genes previously suggested to be associated with sex differentiation in zebrafish. The current study investigates the expression of all six genes in the same individual fish with extensive sampling dates during sex determination and -differentiation. RESULTS: In...... investigated on cDNA from the same fish allowing comparison of the high and low expressers of genes that are expected to be highest expressed in either males or females. There were 78% high or low expressers of all three "male" genes (ar, sox9a and dmrt1) in the investigated period and 81% were high or low...

  7. Signal Transduction Pathways that Regulate CAB Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Chory, Joanne

    2004-12-31

    The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

  8. Signal Transduction Pathways that Regulate CAB Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Chory, Joanne

    2006-01-16

    The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

  9. Using interpolation to estimate system uncertainty in gene expression experiments.

    Directory of Open Access Journals (Sweden)

    Lee J Falin

    Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.

  10. Functional analysis of prognostic gene expression network genes in metastatic breast cancer models.

    Directory of Open Access Journals (Sweden)

    Thomas R Geiger

    Full Text Available Identification of conserved co-expression networks is a useful tool for clustering groups of genes enriched for common molecular or cellular functions [1]. The relative importance of genes within networks can frequently be inferred by the degree of connectivity, with those displaying high connectivity being significantly more likely to be associated with specific molecular functions [2]. Previously we utilized cross-species network analysis to identify two network modules that were significantly associated with distant metastasis free survival in breast cancer. Here, we validate one of the highly connected genes as a metastasis associated gene. Tpx2, the most highly connected gene within a proliferation network specifically prognostic for estrogen receptor positive (ER+ breast cancers, enhances metastatic disease, but in a tumor autonomous, proliferation-independent manner. Histologic analysis suggests instead that variation of TPX2 levels within disseminated tumor cells may influence the transition between dormant to actively proliferating cells in the secondary site. These results support the co-expression network approach for identification of new metastasis-associated genes to provide new information regarding the etiology of breast cancer progression and metastatic disease.

  11. GECKO: a complete large-scale gene expression analysis platform

    Directory of Open Access Journals (Sweden)

    Heuer Michael

    2004-12-01

    Full Text Available Abstract Background Gecko (Gene Expression: Computation and Knowledge Organization is a complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community. Results Based on a client-server architecture, with a centralized repository of typically many tens of thousands of Affymetrix scans, Gecko includes automatic processing pipelines for uploading data from remote sites, a data base, a computational engine implementing ~ 50 different analysis tools, and a client application. Among available analysis tools are clustering methods, principal component analysis, supervised classification including feature selection and cross-validation, multi-factorial ANOVA, statistical contrast calculations, and various post-processing tools for extracting data at given error rates or significance levels. On account of its open architecture, Gecko also allows for the integration of new algorithms. The Gecko framework is very general: non-Affymetrix and non-gene expression data can be analyzed as well. A unique feature of the Gecko architecture is the concept of the Analysis Tree (actually, a directed acyclic graph, in which all successive results in ongoing analyses are saved. This approach has proven invaluable in allowing a large (~ 100 users and distributed community to share results, and to repeatedly return over a span of years to older and potentially very complex analyses of gene expression data. Conclusions The Gecko system is being made publicly available as free software http://sourceforge.net/projects/geckoe. In totality or in parts, the Gecko framework should prove useful to users and system developers with a broad range of analysis needs.

  12. An Expression Refinement Process Ensures Singular Odorant Receptor Gene Choice.

    Science.gov (United States)

    Abdus-Saboor, Ishmail; Al Nufal, Mohammed J; Agha, Maha V; Ruinart de Brimont, Marion; Fleischmann, Alexander; Shykind, Benjamin M

    2016-04-25

    Odorant receptor (OR) gene choice in mammals is a paradigmatic example of monogenic and monoallelic transcriptional selection, in which each olfactory sensory neuron (OSN) chooses to express one OR allele from over 1,000 encoded in the genome [1-3]. This process, critical for generation of the circuit from nose to brain [4-6], is thought to occur in two steps: a slow initial phase that randomly activates a single OR allele, followed by a rapid feedback that halts subsequent expression [7-14]. Inherent in this model is a finite failure rate wherein multiple OR alleles may be activated prior to feedback suppression [15, 16]. Confronted with more than one receptor, the neuron would need to activate a refinement mechanism to eliminate multigenic OR expression and resolve unique neuronal identity [16], critical to the generation of the circuit from nose to olfactory bulb. Here we used a genetic approach in mice to reveal a new facet of OR regulation that corrects adventitious activation of multiple OR alleles, restoring monogenic OR expression and unique neuronal identity. Using the tetM71tg model system, in which the M71 OR is expressed in >95% of mature OSNs and potently suppresses the expression of the endogenous OR repertoire [10], we provide clear evidence of a post-selection refinement (PSR) process that winnows down the number of ORs. We further demonstrate that PSR efficiency is linked to OR expression level, suggesting an underlying competitive process and shedding light on OR gene switching and the fundamental mechanism of singular OR choice. PMID:27040780

  13. Changes in gene expression and signal transduction in microgravity

    Science.gov (United States)

    Hughes-Fulford, M.

    2001-01-01

    Studies from space flights over the past three decades have demonstrated that basic physiological changes occur in humans during space flight. These changes include cephalic fluid shifts, loss of fluid and electrolytes, loss of muscle mass, space motion sickness, anemia, reduced immune response, and loss of calcium and mineralized bone. The cause of most of these manifestations is not known and until recently, the general approach was to investigate general systemic changes, not basic cellular responses to microgravity. This laboratory has recently studied gene growth and activation of normal osteoblasts (MC3T3-El) during spaceflight. Osteoblast cells were grown on glass coverslips and loaded in the Biorack plunger boxes. The osteoblasts were launched in a serum deprived state, activated in microgravity and collected in microgravity. The osteoblasts were examined for changes in gene expression and signal transduction. Approximately one day after growth activation significant changes were observed in gene expression in 0-G flight samples. Immediate early growth genes/growth factors cox-2, c-myc, bcl2, TGF beta1, bFGF and PCNA showed a significant diminished mRNA induction in microgravity FCS activated cells when compared to ground and 1-G flight controls. Cox-1 was not detected in any of the samples. There were no significant differences in the expression of reference gene mRNA between the ground, 0-G and 1-G samples. The data suggest that quiescent osteoblasts are slower to enter the cell cycle in microgravity and that the lack of gravity itself may be a significant factor in bone loss in spaceflight. Preliminary data from our STS 76 flight experiment support our hypothesis that a basic biological response occurs at the tissue, cellular, and molecular level in 0-G. Here we examine ground-based and space flown data to help us understand the mechanism of bone loss in microgravity.

  14. Inferring developmental stage composition from gene expression in human malaria.

    Directory of Open Access Journals (Sweden)

    Regina Joice

    Full Text Available In the current era of malaria eradication, reducing transmission is critical. Assessment of transmissibility requires tools that can accurately identify the various developmental stages of the malaria parasite, particularly those required for transmission (sexual stages. Here, we present a method for estimating relative amounts of Plasmodium falciparum asexual and sexual stages from gene expression measurements. These are modeled using constrained linear regression to characterize stage-specific expression profiles within mixed-stage populations. The resulting profiles were analyzed functionally by gene set enrichment analysis (GSEA, confirming differentially active pathways such as increased mitochondrial activity and lipid metabolism during sexual development. We validated model predictions both from microarrays and from quantitative RT-PCR (qRT-PCR measurements, based on the expression of a small set of key transcriptional markers. This sufficient marker set was identified by backward selection from the whole genome as available from expression arrays, targeting one sentinel marker per stage. The model as learned can be applied to any new microarray or qRT-PCR transcriptional measurement. We illustrate its use in vitro in inferring changes in stage distribution following stress and drug treatment and in vivo in identifying immature and mature sexual stage carriers within patient cohorts. We believe this approach will be a valuable resource for staging lab and field samples alike and will have wide applicability in epidemiological studies of malaria transmission.

  15. Gene expression during fruit ripening in avocado.

    Science.gov (United States)

    Christoffersen, R E; Warm, E; Laties, G G

    1982-06-01

    The poly(A) (+)RNA populations from avocado fruit (Persea americana Mill cv. Hass) at four stages of ripening were isolated by two cycles of oligo-dT-cellulose chromatography and examined by invitro translation, using the rabbit reticulocyte lysate system, followed by two-dimensional gel electrophoresis (isoelectric focusing followed by sodium dodecyl sulfate polyacrylamide gel electrophoresis) of the resulting translation products. Three mRNAs increased dramatically with the climacteric rise in respiration and ethylene production. The molecular weights of the corresponding translation products from the ripening-related mRNAs are 80,000, 36,000, and 16,500. These results indicate that ripening may be linked to the expression of specific genes.

  16. Individual variation of adipose gene expression and identification of covariated genes by cDNA microarrays

    NARCIS (Netherlands)

    Boeuf, S.; Keijer, J.; Franssen-Hal, van N.L.W.; Klaus, S.

    2002-01-01

    Gene expression profiling through the application of microarrays provides comprehensive assessment of gene expression levels in a given tissue or cell population, as well as information on changes of gene expression in altered physiological or pathological situations. Microarrays are particularly su

  17. An integrative genomic approach reveals coordinated expression of intronic miR-335, miR-342, and miR-561 with deregulated host genes in multiple myeloma

    Directory of Open Access Journals (Sweden)

    Agnelli Luca

    2008-08-01

    Full Text Available Abstract Background The role of microRNAs (miRNAs in multiple myeloma (MM has yet to be fully elucidated. To identify miRNAs that are potentially deregulated in MM, we investigated those mapping within transcription units, based on evidence that intronic miRNAs are frequently coexpressed with their host genes. To this end, we monitored host transcript expression values in a panel of 20 human MM cell lines (HMCLs and focused on transcripts whose expression varied significantly across the dataset. Methods miRNA expression was quantified by Quantitative Real-Time PCR. Gene expression and genome profiling data were generated on Affymetrix oligonucleotide microarrays. Significant Analysis of Microarrays algorithm was used to investigate differentially expressed transcripts. Conventional statistics were used to test correlations for significance. Public libraries were queried to predict putative miRNA targets. Results We identified transcripts specific to six miRNA host genes (CCPG1, GULP1, EVL, TACSTD1, MEST, and TNIK whose average changes in expression varied at least 2-fold from the mean of the examined dataset. We evaluated the expression levels of the corresponding intronic miRNAs and identified a significant correlation between the expression levels of MEST, EVL, and GULP1 and those of the corresponding miRNAs miR-335, miR-342-3p, and miR-561, respectively. Genome-wide profiling of the 20 HMCLs indicated that the increased expression of the three host genes and their corresponding intronic miRNAs was not correlated with local copy number variations. Notably, miRNAs and their host genes were overexpressed in a fraction of primary tumors with respect to normal plasma cells; however, this finding was not correlated with known molecular myeloma groups. The predicted putative miRNA targets and the transcriptional profiles associated with the primary tumors suggest that MEST/miR-335 and EVL/miR-342-3p may play a role in plasma cell homing and

  18. Reciprocal regulation of transcription factors and PLC isozyme gene expression in adult cardiomyocytes.

    Science.gov (United States)

    Singal, Tushi; Dhalla, Naranjan S; Tappia, Paramjit S

    2010-06-01

    By employing a pharmacological approach, we have shown that phospholipase C (PLC) activity is involved in the regulation of gene expression of transcription factors such as c-Fos and c-Jun in cardiomyocytes in response to norepinephrine (NE). However, there is no information available regarding the identity of specific PLC isozymes involved in the regulation of c-Fos and c-Jun or on the involvement of these transcription factors in PLC isozyme gene expression in adult cardiomyocytes. In this study, transfection of cardiomyocytes with PLC isozyme specific siRNA was found to prevent the NE-mediated increases in the corresponding PLC isozyme gene expression, protein content and activity. Unlike PLC gamma(1) gene, silencing of PLC beta(1), beta(3) and delta(1) genes with si RNA prevented the increases in c-Fos and c-Jun gene expression in response to NE. On the other hand, transfection with c-Jun si RNA suppressed the NE-induced increase in c-Jun as well as PLC beta(1), beta(3) and delta(1) gene expression, but had no effect on PLC gamma(1) gene expression. Although transfection of cardiomyocytes with c-Fos si RNA prevented NE-induced expression of c-Fos, PLC beta(1) and PLC beta(3) genes, it did not affect the increases in PLC delta(1) and PLC gamma(1) gene expression. Silencing of either c-Fos or c-Jun also depressed the NE-mediated increases in PLC beta(1), beta(3) and gamma(1) protein content and activity in an isozyme specific manner. Furthermore, silencing of all PLC isozymes as well as of c-Fos and c-Jun resulted in prevention of the NE-mediated increase in atrial natriuretic factor gene expression. These findings, by employing gene silencing techniques, demonstrate that there occurs a reciprocal regulation of transcription factors and specific PLC isozyme gene expression in cardiomyocytes.

  19. Modulation of R-gene expression across environments.

    Science.gov (United States)

    MacQueen, Alice; Bergelson, Joy

    2016-03-01

    Some environments are more conducive to pathogen growth than others, and, as a consequence, plants might be expected to invest more in resistance when pathogen growth is favored. Resistance (R-) genes in Arabidopsis thaliana have unusually extensive variation in basal expression when comparing the same R-gene among accessions collected from different environments. R-gene expression variation was characterized to explore whether R-gene expression is up-regulated in environments favoring pathogen proliferation and down-regulated when risks of infection are low; down-regulation would follow if costs of R-gene expression negatively impact plant fitness in the absence of disease. Quantitative reverse transcription-PCR was used to quantify the expression of 13 R-gene loci in plants grown in eight environmental conditions for each of 12 A. thaliana accessions, and large effects of the environment on R-gene expression were found. Surprisingly, almost every change in the environment--be it a change in biotic or abiotic conditions--led to an increase in R-gene expression, a response that was distinct from the average transcriptome response and from that of other stress response genes. These changes in expression are functional in that environmental change prior to infection affected levels of specific disease resistance to isolates of Pseudomonas syringae. In addition, there are strong latitudinal clines in basal R-gene expression and clines in R-gene expression plasticity correlated with drought and high temperatures. These results suggest that variation in R-gene expression across environments may be shaped by natural selection to reduce fitness costs of R-gene expression in permissive or predictable environments. PMID:26983577

  20. Gene therapy in glaucoma-3: Therapeutic approaches

    Directory of Open Access Journals (Sweden)

    Mohamed Abdel-Monem Soliman Mahdy

    2010-01-01

    Recently, several promising genetic therapeutic approaches had been investigated. Some are either used to stop apoptosis and halt further glaucomatous damage, wound healing modulating effect or long lasting intraocular pressure lowering effects than the conventional commercially available antiglaucoma medications. Method of Literature Search The literature was searched on the Medline database using the PubMed interface. The key words for search were glaucoma, gene therapy, and genetic diagnosis of glaucoma.

  1. Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors

    Directory of Open Access Journals (Sweden)

    Skubitz Amy PN

    2008-05-01

    Full Text Available Abstract The heterogeneity that soft tissue sarcomas (STS exhibit in their clinical behavior, even within histological subtypes, complicates patient care. Histological appearance is determined by gene expression. Morphologic features are generally good predictors of biologic behavior, however, metastatic propensity, tumor growth, and response to chemotherapy may be determined by gene expression patterns that do not correlate well with morphology. One approach to identify heterogeneity is to search for genetic markers that correlate with differences in tumor behavior. Alternatively, subsets may be identified based on gene expression patterns alone, independent of knowledge of clinical outcome. We have reported gene expression patterns that distinguish two subgroups of clear cell renal carcinoma (ccRCC, and other gene expression patterns that distinguish heterogeneity of serous ovarian carcinoma (OVCA and aggressive fibromatosis (AF. In this study, gene expression in 53 samples of STS and AF [including 16 malignant fibrous histiocytoma (MFH, 9 leiomyosarcoma, 12 liposarcoma, 4 synovial sarcoma, and 12 samples of AF] was determined at Gene Logic Inc. (Gaithersburg, MD using Affymetrix GeneChip® U_133 arrays containing approximately 40,000 genes/ESTs. Gene expression analysis was performed with the Gene Logic Genesis Enterprise System® Software and Expressionist software. Hierarchical clustering of the STS using our three previously reported gene sets, each generated subgroups within the STS that for some subtypes correlated with histology, and also suggested the existence of subsets of MFH. All three gene sets also recognized the same two subsets of the fibromatosis samples that we had found in our earlier study of AF. These results suggest that these subgroups may have biological significance, and that these gene sets may be useful for sub-classification of STS. In addition, several genes that are targets of some anti-tumor drugs were found to

  2. A Novel Approach to Functional Analysis of the Ribulose Bisphosphate Carboxylase Small Subunit Gene by Agrobacterium-Mediated Gene Silencing

    Institute of Scientific and Technical Information of China (English)

    Xiao-Fu Zhou; Peng-Da Ma; Ren-Hou Wang; Bo Liu; Xing-Zhi Wang

    2006-01-01

    A novel approach to virus-induced post-transcriptional gene silencing for studying the function of the ribulose bisphosphate carboxylase small subunlt (rbcS) gene was established and optimized using potato virus X vector and Nicotiana benthamiana as experimental material. The analysis of silencing phenomena,transcriptional level, protein expression, and pigment measurement showed that the expression of the rbcS endogenous gene was inactivated by the expression of a 500-bp homologous cDNA fragment carried in the virus vector.

  3. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR

    OpenAIRE

    Thein Swee; Jiang Jie; Best Steve; Silver Nicholas

    2006-01-01

    Abstract Background Control genes, which are often referred to as housekeeping genes, are frequently used to normalise mRNA levels between different samples. However, the expression level of these genes may vary among tissues or cells and may change under certain circumstances. Thus, the selection of housekeeping genes is critical for gene expression studies. To address this issue, 7 candidate housekeeping genes including several commonly used ones were investigated in isolated human reticulo...

  4. Cloning and expression in Saccharomyces cerevisiae of chit2 gene from Beauveria bassiana

    Institute of Scientific and Technical Information of China (English)

    SONG Jin-zhu; YANG Xiao-xue; WANG Yun; YANG Qian

    2009-01-01

    To study recycled trashes from shrimps and crabs in the sea through chitinase secreted by microor-ganisms, the chitinase gene chit2 was cloned and sequenced from Beauveria bassiana by the polymerase chain reaction (PCR), and was ligated into the yeast expression vector pYES2. The expression vector plasmid was transformed into Saccharomyces cerevisiae H158. Gene expression took place upon induction with 2% galac-tose. The measurement of enzyme activity shows that the expression production can be expressed in active forms and secreted to the medium. The enzyme activity approaches the peak of 0. 63 U/mL when the culture time is 36 h.

  5. Biclustering of gene expression data by non-smooth non-negative matrix factorization

    Directory of Open Access Journals (Sweden)

    Carazo Jose M

    2006-02-01

    Full Text Available Abstract Background The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions. One of the major challenges in the analysis of such datasets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated to different physiological states. Results In this work we present a methodology able to cluster genes and conditions highly related in sub-portions of the data. Our approach is based on a new data mining technique, Non-smooth Non-Negative Matrix Factorization (nsNMF, able to identify localized patterns in large datasets. We assessed the potential of this methodology analyzing several synthetic datasets as well as two large and heterogeneous sets of gene expression profiles. In all cases the method was able to identify localized features related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The uncovered structures showed a clear biological meaning in terms of relationships among functional annotations of genes and the phenotypes or physiological states of the associated conditions. Conclusion The proposed approach can be a useful tool to analyze large and heterogeneous gene expression datasets. The method is able to identify complex relationships among genes and conditions that are difficult to identify by standard clustering algorithms.

  6. Expression profiles for six zebrafish genes during gonadal sex differentiation

    DEFF Research Database (Denmark)

    Jørgensen, Anne; Morthorst, Jane E.; Andersen, Ole;

    2008-01-01

    BACKGROUND: The mechanism of sex determination in zebrafish is largely unknown and neither sex chromosomes nor a sex-determining gene have been identified. This indicates that sex determination in zebrafish is mediated by genetic signals from autosomal genes. The aim of this study was to determine...... the precise timing of expression of six genes previously suggested to be associated with sex differentiation in zebrafish. The current study investigates the expression of all six genes in the same individual fish with extensive sampling dates during sex determination and -differentiation. RESULTS...... "female" genes (fig alpha and cyp19a1a). When comparing all five genes with expected sex related expression 56% show expression expected for either male or female. Furthermore, the expression of all genes was investigated in different tissue of adult male and female zebrafish. CONCLUSION: In zebrafish...

  7. CDX2 gene expression in acute lymphoblastic leukemia

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    Hanaa H. Arnaoaut

    2014-06-01

    Full Text Available CDX genes are classically known as regulators of axial elongation during early embryogenesis. An unsuspected role for CDX genes has been revealed during hematopoietic development. The CDX gene family member CDX2 belongs to the most frequent aberrantly expressed proto-oncogenes in human acute leukemias and is highly leukemogenic in experimental models. We used reversed transcriptase polymerase chain reaction (RT-PCR to determine the expression level of CDX2 gene in 30 pediatric patients with acute lymphoblastic leukemia (ALL at diagnosis and 30 healthy volunteers. ALL patients were followed up to detect minimal residual disease (MRD on days 15 and 42 of induction. We found that CDX2 gene was expressed in 50% of patients and not expressed in controls. Associations between gene expression and different clinical and laboratory data of patients revealed no impact on different findings. With follow up, we could not confirm that CDX2 expression had a prognostic significance.

  8. Precise regulation of gene expression dynamics favors complex promoter architectures.

    Directory of Open Access Journals (Sweden)

    Dirk Müller

    2009-01-01

    Full Text Available Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure.

  9. Expression profiling identifies genes involved in emphysema severity

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    Bowman Rayleen V

    2009-09-01

    Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

  10. Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

    Directory of Open Access Journals (Sweden)

    Mika Gustafsson

    Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

  11. Thermal evolution of gene expression profiles in Drosophila subobscura

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    Beltran Sergi

    2007-03-01

    Full Text Available Abstract Background Despite its pervasiveness, the genetic basis of adaptation resulting in variation directly or indirectly related to temperature (climatic gradients is poorly understood. By using 3-fold replicated laboratory thermal stocks covering much of the physiologically tolerable temperature range for the temperate (i.e., cold tolerant species Drosophila subobscura we have assessed whole-genome transcriptional responses after three years of thermal adaptation, when the populations had already diverged for inversion frequencies, pre-adult life history components, and morphological traits. Total mRNA from each population was compared to a reference pool mRNA in a standard, highly replicated two-colour competitive hybridization experiment using cDNA microarrays. Results A total of 306 (6.6% cDNA clones were identified as 'differentially expressed' (following a false discovery rate correction after contrasting the two furthest apart thermal selection regimes (i.e., 13°C vs . 22°C, also including four previously reported candidate genes for thermotolerance in Drosophila (Hsp26, Hsp68, Fst, and Treh. On the other hand, correlated patterns of gene expression were similar in cold- and warm-adapted populations. Analysis of functional categories defined by the Gene Ontology project point to an overrepresentation of genes involved in carbohydrate metabolism, nucleic acids metabolism and regulation of transcription among other categories. Although the location of differently expressed genes was approximately at random with respect to chromosomes, a physical mapping of 88 probes to the polytene chromosomes of D. subobscura has shown that a larger than expected number mapped inside inverted chromosomal segments. Conclusion Our data suggest that a sizeable number of genes appear to be involved in thermal adaptation in Drosophila, with a substantial fraction implicated in metabolism. This apparently illustrates the formidable challenge to

  12. Serial Analysis of Gene Expression: Applications in Human Studies

    OpenAIRE

    Renu Tuteja; Narendra Tuteja

    2004-01-01

    Serial analysis of gene expression (SAGE) is a powerful tool, which provides quantitative and comprehensive expression profile of genes in a given cell population. It works by isolating short fragments of genetic information from the expressed genes that are present in the cell being studied. These short sequences, called SAGE tags, are linked together for efficient sequencing. The frequency of each SAGE tag in the cloned multimers directly reflects the transcript abundance. Therefore, SAGE r...

  13. Regulated system for heterologous gene expression in Penicillium chrysogenum.

    OpenAIRE

    Graessle, S.; de Haas, H.; Friedlin, E; Kürnsteiner, H; Stöffler, G; Redl, B

    1997-01-01

    A system for regulated heterologous gene expression in the filamentous fungus Penicillium chrysogenum was established. This is the first heterologous expression system to be developed for this organism. Expression of a recombinant fungal xylanase gene (xylp) and the cDNA for the human tear lipocalin (LCNI) was achieved by placing the encoding sequences under the control of the repressible acid phosphatase gene (phoA) promoter of P. chrysogenum. Secreted recombinant proteins were detected in t...

  14. Links between core promoter and basic gene features influence gene expression

    Directory of Open Access Journals (Sweden)

    Sinvani Hadar

    2008-02-01

    Full Text Available Abstract Background Diversity in rates of gene expression is essential for basic cell functions and is controlled by a variety of intricate mechanisms. Revealing general mechanisms that control gene expression is important for understanding normal and pathological cell functions and for improving the design of expression systems. Here we analyzed the relationship between general features of genes and their contribution to expression levels. Results Genes were divided into four groups according to their core promoter type and their characteristics analyzed statistically. Surprisingly we found that small variations in the TATA box are linked to large differences in gene length. Genes containing canonical TATA are generally short whereas long genes are associated with either non-canonical TATA or TATA-less promoters. These differences in gene length are primarily determined by the size and number of introns. Generally, gene expression was found to be tightly correlated with the strength of the TATA-box. However significant reduction in gene expression levels were linked with long TATA-containing genes (canonical and non-canonical whereas intron length hardly affected the expression of TATA-less genes. Interestingly, features associated with high translation are prevalent in TATA-containing genes suggesting that their protein production is also more efficient. Conclusion Our results suggest that interplay between core promoter type and gene size can generate significant diversity in gene expression.

  15. Differential gene co-expression networks via Bayesian biclustering models

    OpenAIRE

    Gao, Chuan; Zhao, Shiwen; McDowell, Ian C.; Brown, Christopher D.; Barbara E Engelhardt

    2014-01-01

    Identifying latent structure in large data matrices is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression data, where each network encodes relationships between genes that are locally co-regulated by shared biological mechanisms. To do this, we develop a Bayesian statistical model for biclustering to infer subsets of co-regulated genes whose covariation may be observed in only a subset of the samples. Our biclustering me...

  16. Biclustering of Linear Patterns In Gene Expression Data

    OpenAIRE

    Gao, Qinghui; Ho, Christine; Jia, Yingmin; Li, Jingyi Jessica; Huang, Haiyan

    2012-01-01

    Identifying a bicluster, or submatrix of a gene expression dataset wherein the genes express similar behavior over the columns, is useful for discovering novel functional gene interactions. In this article, we introduce a new algorithm for finding biClusters with Linear Patterns (CLiP). Instead of solely maximizing Pearson correlation, we introduce a fitness function that also considers the correlation of complementary genes and conditions. This eliminates the need for a priori determination ...

  17. Gene expression in epithelial cells in response to pneumovirus infection

    Directory of Open Access Journals (Sweden)

    Rosenberg Helene F

    2001-05-01

    Full Text Available Abstract Respiratory syncytial virus (RSV and pneumonia virus of mice (PVM are viruses of the family Paramyxoviridae, subfamily pneumovirus, which cause clinically important respiratory infections in humans and rodents, respectively. The respiratory epithelial target cells respond to viral infection with specific alterations in gene expression, including production of chemoattractant cytokines, adhesion molecules, elements that are related to the apoptosis response, and others that remain incompletely understood. Here we review our current understanding of these mucosal responses and discuss several genomic approaches, including differential display reverse transcription-polymerase chain reaction (PCR and gene array strategies, that will permit us to unravel the nature of these responses in a more complete and systematic manner.

  18. Differential Expression of Salinity Resistance Gene on Cotton

    Institute of Scientific and Technical Information of China (English)

    YE Wu-wei; YU Shu-xun

    2008-01-01

    @@ Salinity resistance and differential gene expression associated with salinity in cotton germplasm were studied,because of the large scale area of salinity in China,and its significant negative effects on the cotton production.The salinityresisted genes and their differential expression were studied under the stress of NaCI on cotton.There were found,under the NaCI stress,1644 genes differentially expressed from the salinity-sensitive cotton and only 817 genes differentially expressed from the salinityresisted cotton.

  19. Genome-wide age-related changes in DNA methylation and gene expression in human PBMCs.

    Science.gov (United States)

    Steegenga, Wilma T; Boekschoten, Mark V; Lute, Carolien; Hooiveld, Guido J; de Groot, Philip J; Morris, Tiffany J; Teschendorff, Andrew E; Butcher, Lee M; Beck, Stephan; Müller, Michael

    2014-06-01

    Aging is a progressive process that results in the accumulation of intra- and extracellular alterations that in turn contribute to a reduction in health. Age-related changes in DNA methylation have been reported before and may be responsible for aging-induced changes in gene expression, although a causal relationship has yet to be shown. Using genome-wide assays, we analyzed age-induced changes in DNA methylation and their effect on gene expression with and without transient induction with the synthetic transcription modulating agent WY14,643. To demonstrate feasibility of the approach, we isolated peripheral blood mononucleated cells (PBMCs) from five young and five old healthy male volunteers and cultured them with or without WY14,643. Infinium 450K BeadChip and Affymetrix Human Gene 1.1 ST expression array analysis revealed significant differential methylation of at least 5 % (ΔYO > 5 %) at 10,625 CpG sites between young and old subjects, but only a subset of the associated genes were also differentially expressed. Age-related differential methylation of previously reported epigenetic biomarkers of aging including ELOVL2, FHL2, PENK, and KLF14 was confirmed in our study, but these genes did not display an age-related change in gene expression in PBMCs. Bioinformatic analysis revealed that differentially methylated genes that lack an age-related expression change predominantly represent genes involved in carcinogenesis and developmental processes, and expression of most of these genes were silenced in PBMCs. No changes in DNA methylation were found in genes displaying transiently induced changes in gene expression. In conclusion, aging-induced differential methylation often targets developmental genes and occurs mostly without change in gene expression.

  20. Genome-wide age-related changes in DNA methylation and gene expression in human PBMCs.

    Science.gov (United States)

    Steegenga, Wilma T; Boekschoten, Mark V; Lute, Carolien; Hooiveld, Guido J; de Groot, Philip J; Morris, Tiffany J; Teschendorff, Andrew E; Butcher, Lee M; Beck, Stephan; Müller, Michael

    2014-06-01

    Aging is a progressive process that results in the accumulation of intra- and extracellular alterations that in turn contribute to a reduction in health. Age-related changes in DNA methylation have been reported before and may be responsible for aging-induced changes in gene expression, although a causal relationship has yet to be shown. Using genome-wide assays, we analyzed age-induced changes in DNA methylation and their effect on gene expression with and without transient induction with the synthetic transcription modulating agent WY14,643. To demonstrate feasibility of the approach, we isolated peripheral blood mononucleated cells (PBMCs) from five young and five old healthy male volunteers and cultured them with or without WY14,643. Infinium 450K BeadChip and Affymetrix Human Gene 1.1 ST expression array analysis revealed significant differential methylation of at least 5 % (ΔYO > 5 %) at 10,625 CpG sites between young and old subjects, but only a subset of the associated genes were also differentially expressed. Age-related differential methylation of previously reported epigenetic biomarkers of aging including ELOVL2, FHL2, PENK, and KLF14 was confirmed in our study, but these genes did not display an age-related change in gene expression in PBMCs. Bioinformatic analysis revealed that differentially methylated genes that lack an age-related expression change predominantly represent genes involved in carcinogenesis and developmental processes, and expression of most of these genes were silenced in PBMCs. No changes in DNA methylation were found in genes displaying transiently induced changes in gene expression. In conclusion, aging-induced differential methylation often targets developmental genes and occurs mostly without change in gene expression. PMID:24789080

  1. Inferring single-cell gene expression mechanisms using stochastic simulation

    Science.gov (United States)

    Daigle, Bernie J.; Soltani, Mohammad; Petzold, Linda R.; Singh, Abhyudai

    2015-01-01

    Motivation: Stochastic promoter switching between transcriptionally active (ON) and inactive (OFF) states is a major source of noise in gene expression. It is often implicitly assumed that transitions between promoter states are memoryless, i.e. promoters spend an exponentially distributed time interval in each of the two states. However, increasing evidence suggests that promoter ON/OFF times can be non-exponential, hinting at more complex transcriptional regulatory architectures. Given the essential role of gene expression in all cellular functions, efficient computational techniques for characterizing promoter architectures are critically needed. Results: We have developed a novel model reduction for promoters with arbitrary numbers of ON and OFF states, allowing us to approximate complex promoter switching behavior with Weibull-distributed ON/OFF times. Using this model reduction, we created bursty Monte Carlo expectation-maximization with modified cross-entropy method (‘bursty MCEM2’), an efficient parameter estimation and model selection technique for inferring the number and configuration of promoter states from single-cell gene expression data. Application of bursty MCEM2 to data from the endogenous mouse glutaminase promoter reveals nearly deterministic promoter OFF times, consistent with a multi-step activation mechanism consisting of 10 or more inactive states. Our novel approach to modeling promoter fluctuations together with bursty MCEM2 provides powerful tools for characterizing transcriptional bursting across genes under different environmental conditions. Availability and implementation: R source code implementing bursty MCEM2 is available upon request. Contact: absingh@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573914

  2. Identification of transcription-factor genes expressed in the Arabidopsis female gametophyte

    Directory of Open Access Journals (Sweden)

    Kang Il-Ho

    2010-06-01

    study have not been reported previously as being expressed in the female gametophyte. Therefore, they might represent novel regulators and provide entry points for reverse genetic and molecular approaches to uncover the gene regulatory networks underlying female gametophyte development.

  3. Binary gene expression patterning of the molt cycle: the case of chitin metabolism.

    Directory of Open Access Journals (Sweden)

    Shai Abehsera

    Full Text Available In crustaceans, like all arthropods, growth is accompanied by a molting cycle. This cycle comprises major physiological events in which mineralized chitinous structures are built and degraded. These events are in turn governed by genes whose patterns of expression are presumably linked to the molting cycle. To study these genes we performed next generation sequencing and constructed a molt-related transcriptomic library from two exoskeletal-forming tissues of the crayfish Cherax quadricarinatus, namely the gastrolith and the mandible cuticle-forming epithelium. To simplify the study of such a complex process as molting, a novel approach, binary patterning of gene expression, was employed. This approach revealed that key genes involved in the synthesis and breakdown of chitin exhibit a molt-related pattern in the gastrolith-forming epithelium. On the other hand, the same genes in the mandible cuticle-forming epithelium showed a molt-independent pattern of expression. Genes related to the metabolism of glucosamine-6-phosphate, a chitin precursor synthesized from simple sugars, showed a molt-related pattern of expression in both tissues. The binary patterning approach unfolds typical patterns of gene expression during the molt cycle of a crustacean. The use of such a simplifying integrative tool for assessing gene patterning seems appropriate for the study of complex biological processes.

  4. Noise in gene expression is coupled to growth rate

    OpenAIRE

    Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

    2015-01-01

    Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four...

  5. Expression of UGA-Containing Mycoplasma Genes in Bacillus subtilis

    OpenAIRE

    Kannan, T. R.; Baseman, Joel B.

    2000-01-01

    We used Bacillus subtilis to express UGA-containing Mycoplasma genes encoding the P30 adhesin (one UGA) of Mycoplasma pneumoniae and methionine sulfoxide reductase (two UGAs) of Mycoplasma genitalium. Due to natural UGA suppression, these Mycoplasma genes were expressed as full-length protein products, but at relatively low efficiency, in recombinant wild-type Bacillus. The B. subtilis-expressed Mycoplasma proteins appeared as single bands and not as multiple bands compared to expression in r...

  6. Multiscale Embedded Gene Co-expression Network Analysis

    OpenAIRE

    Song, Won-Min; Zhang, Bin

    2015-01-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a...

  7. Retinoic acid-mediated gene expression in transgenic reporter zebrafish.

    Science.gov (United States)

    Perz-Edwards, A; Hardison, N L; Linney, E

    2001-01-01

    Retinoic acid-mediated gene activation is important for normal vertebrate development. The size and nature of retinoic acid make it difficult to identify the precise cellular location of this signaling molecule throughout an embryo. Additionally, retinoic acid (RA) signaling is regulated by a complex combination of receptors, coactivators, and antagonizing proteins. Thus, in order to integrate these signals and identify regions within a whole developing embryo where cells can respond transcriptionally to retinoic acid, we have used a reporter transgenic approach. We have generated several stable lines of transgenic zebrafish which use retinoic acid response elements to drive fluorescent protein expression. In these zebrafish lines, transgene expression is localized to regions of the neural tube, retina, notochord, somites, heart, pronephric ducts, branchial arches, and jaw muscles in embryos and larvae. Transgene expression can be induced in additional regions of the neural tube and retina as well as the immature notochord, hatching gland, enveloping cell layer, and fin by exposing embryos to retinoic acid. Treatment with retinoic acid synthase inhibitors, citral and diethylaminobenzaldehyde (DEAB), during neurulation, greatly reduces transgene expression. DEAB treatment of embryos at gastrulation phenocopies the embryonic effects of vitamin A deprivation or targeted disruption of the RA synthase retinaldehyde dehydrogenase-2 in other vertebrates. Together these data suggest that the reporter expression we see in zebrafish is dependent upon conserved vertebrate pathways of RA synthesis.

  8. An efficient RNA isolation procedure and identification of reference genes for normalization of gene expression in blueberry.

    Science.gov (United States)

    Vashisth, Tripti; Johnson, Lisa Klima; Malladi, Anish

    2011-12-01

    Application of transcriptomics approaches can greatly enhance our understanding of blueberry physiology. The success of transcriptomics approaches is dependent on the extraction of high-quality RNA which is complicated by the abundance of polyphenolics and polysaccharides in blueberry. Additionally, transcriptomics requires the accurate quantification of transcript abundance. Quantitative real-time polymerase chain reaction (qRT-PCR) is a robust method to determine transcript abundance. Normalization of gene expression using stably expressed reference genes is essential in qRT-PCR. An evaluation of the stability of expression of reference genes has not yet been reported in blueberry. The objectives of this study were to develop an effective procedure for extracting RNA from different organs and to evaluate potential reference genes for qRT-PCR analyses in blueberry. RNA of high quality and yield was extracted from eight and six organs of rabbiteye and southern highbush blueberry, respectively, using a modified cetyltrimethyl ammonium bromide-based method. The expression stability of 12 reference genes was evaluated. UBIQUITIN-CONJUGATING ENZYME (UBC28), RNA HELICASE-LIKE (RH8), CLATHRIN ADAPTER COMPLEXES MEDIUM SUBUNIT FAMILY PROTEIN (CACSa), and POLYUBIQUITIN (UBQ3b) were the most stably expressed genes across multiple organs in both blueberry species. Further, the expression stability of the reference genes in the branch abscission zone following treatment with fruit abscission-inducing compounds was analyzed. CACSa, RH8, and UBC28 were the most stably expressed genes in the abscission zone under abscission-inducing conditions. We suggest a preliminary evaluation of UBC28, CACSa, RH8, and UBQ3b to identify the most suitable reference genes for the experimental conditions under consideration in blueberry.

  9. Expressed genes in regenerating rat liver after partial hepatectomy

    Institute of Scientific and Technical Information of China (English)

    Cun-Shuan Xu; Salman Rahrnan; Jing-Bo Zhang; Cui-Fang Chang; Jin-Yun Yuan; Wen-Qiang Li; Hong-Peng Han; Ke-Jin Yang; Li-Feng Zhao; Yu-Chang Li; Hui-Yong Zhang

    2005-01-01

    AIM: To reveal the liver regeneration (LR) and its controlas well as the occurrence of liver disease and to study the gene expression profiles of 551 genes after partial hepatectomy (PH) in regenerating rat livers.METHODS: Five hundred and fifty-one expressed sequence tags screened by suppression subtractive hybridization were made into an in-house cDNA microarray, and the expressive genes and their expressive profiles in regenerating rat livers were analyzed by microarray and bioinformatics. RESULTS: Three hundred of the analyzed 551 genes were up- or downregulated more than twofolds at one or more time points during LR. Most of the genes were up- or downregulated 2-5 folds, but the highest reached 90 folds of the control. One hundred and thirty-nine of themshowed upregulation, 135 displayed downregulation, and up or down expression of 26 genes revealed a dependence on regenerating livers. The genes expressedin 24-h regenerating livers were much more than those in the others. Cluster analysis and generalization analysis showed that there were at least six distinct temporal patterns of gene expression in the regenerating livers, that is, genes were expressed in the immediate early phase, early phase, intermediate phase, early-late phase, late phase, terminal phase. CONCLUSION: In LR, the number of down-regulated genes was almost similar to that of the upregulated genes; the successively altered genes were more than the rapidly transient genes. The temporal patterns of gene expression were similar 2 and 4 h, 12 and 16 h, 48 and 96 h, 72 and 144 h after PH. Microarray combined with suppressive subtractive hybridization can effectively identify the genes related to LR.

  10. Mutants of Agrobacterium tumefaciens with elevated vir gene expression

    International Nuclear Information System (INIS)

    Expression of Agrobacterium tumefaciens virulence (vir) genes requires virA, virG, and a plant-derived inducing compound such as acetosyringone. To identify the critical functional domains of virA and virG, a mutational approach was used. Agrobacterium A136 harboring plasmid pGP159, which contains virA, virG, and a reporter virB:lacZ gene fusion, was mutagenized with UV light or nitrosoguanidine. Survivors that formed blue colonies on a plate containing 5-bromo-4-chloro-3-indolyl beta-D-galactoside were isolated and analyzed. Quantification of beta-galactosidase activity in liquid assays identified nine mutant strains. By plasmid reconstruction and other procedures, all mutations mapped to the virA locus. These mutations caused an 11- to 560-fold increase in the vegetative level of virB:lacZ reporter gene expression. DNA sequence analysis showed that the mutations are located in four regions of VirA: transmembrane domain one, the active site, a glycine-rich region with homology to ATP-binding sites, and a region at the C terminus that has homology to the N terminus of VirG

  11. Conserved co-expression for candidate disease gene prioritization

    Directory of Open Access Journals (Sweden)

    Huynen Martijn A

    2008-04-01

    Full Text Available Abstract Background Genes that are co-expressed tend to be involved in the same biological process. However, co-expression is not a very reliable predictor of functional links between genes. The evolutionary conservation of co-expression between species can be used to predict protein function more reliably than co-expression in a single species. Here we examine whether co-expression across multiple species is also a better prioritizer of disease genes than is co-expression between human genes alone. Results We use co-expression data from yeast (S. cerevisiae, nematode worm (C. elegans, fruit fly (D. melanogaster, mouse and human and find that the use of evolutionary conservation can indeed improve the predictive value of co-expression. The effect that genes causing the same disease have higher co-expression than do other genes from their associated disease loci, is significantly enhanced when co-expression data are combined across evolutionarily distant species. We also find that performance can vary significantly depending on the co-expression datasets used, and just using more data does not necessarily lead to better prioritization. Instead, we find that dataset quality is more important than quantity, and using a consistent microarray platform per species leads to better performance than using more inclusive datasets pooled from various platforms. Conclusion We find that evolutionarily conserved gene co-expression prioritizes disease candidate genes better than human gene co-expression alone, and provide the integrated data as a new resource for disease gene prioritization tools.

  12. Statistical Inference and Reverse Engineering of Gene Regulatory Networks from Observational Expression Data

    OpenAIRE

    Emmert-Streib, Frank; Glazko, Galina V.; Altay, Gökmen; Matos Simoes, Ricardo de

    2012-01-01

    In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms.

  13. Simpler Evaluation of Predictions and Signature Stability for Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Yvonne E. Pittelkow

    2009-01-01

    Full Text Available Scientific advances are raising expectations that patient-tailored treatment will soon be available. The development of resulting clinical approaches needs to be based on well-designed experimental and observational procedures that provide data to which proper biostatistical analyses are applied. Gene expression microarray and related technology are rapidly evolving. It is providing extremely large gene expression profiles containing many thousands of measurements. Choosing a subset from these gene expression measurements to include in a gene expression signature is one of the many challenges needing to be met. Choice of this signature depends on many factors, including the selection of patients in the training set. So the reliability and reproducibility of the resultant prognostic gene signature needs to be evaluated, in such a way as to be relevant to the clinical setting. A relatively straightforward approach is based on cross validation, with separate selection of genes at each iteration to avoid selection bias. Within this approach we developed two different methods, one based on forward selection, the other on genes that were statistically significant in all training blocks of data. We demonstrate our approach to gene signature evaluation with a well-known breast cancer data set.

  14. Global gene expression analysis for evaluation and design of biomaterials

    Directory of Open Access Journals (Sweden)

    Nobutaka Hanagata, Taro Takemura and Takashi Minowa

    2010-01-01

    Full Text Available Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data.

  15. Identification of imprinted genes subject to parent-of-origin specific expression in Arabidopsis thaliana seeds

    LENUS (Irish Health Repository)

    McKeown, Peter C

    2011-08-12

    confirmed via allele-specific transcript analysis across a range of different accessions. Differentially methylated regions were identified adjacent to ATCDC48 and PDE120, which may represent candidate imprinting control regions. Finally, we demonstrate that expression levels of these three genes in vegetative tissues are MET1-dependent, while their uniparental maternal expression in the seed is not dependent on MET1. Conclusions Using a cDNA-AFLP transcriptome profiling approach, we have identified three genes, ATCDC48, PDE120 and MS5-like which represent novel maternally expressed imprinted genes in the Arabidopsis thaliana seed. The extent of overlap between our cDNA-AFLP screen for maternally expressed imprinted genes, and other screens for imprinted and endosperm-expressed genes is discussed.

  16. Gene Expression Pattern of Signal Transduction in Chronic Myeloid Leukemia

    Institute of Scientific and Technical Information of China (English)

    LI Huiyu; JIE Shenghua; GUO Tiannan; HUANG Shi'ang

    2006-01-01

    To explore the transcriptional gene expression profiles of signaling pathway in Chronic myeloid leukemia (CML), a series of cDNA microarray chips were tested. The results showed that differentially expressed genes related to singal transduction in CML were screened out and the genes involved in Phosphoinositide 3-kinases (PI3K), Ras-MAPK (mitogen-activated protein kinase) and other signaling pathway genes simultaneously. The results also showed that most of these genes were up-expression genes , which suggested that signal transduction be overactivated in CML. Further analysis of these differentially expressed signal transduction genes will be helpful to understand the molecular mechanism of CML and find new targets of treatment.

  17. The expression of HER-2/neu gene in colon cancer tissues and its clinical significance

    Institute of Scientific and Technical Information of China (English)

    Jing Jin; Yuxuan Che; Qimin Wang; Fang Liu; Man Li; Lifen Wang; Xiuhua Sun; Yang Zhang

    2013-01-01

    Objective:The article aims to detect the expression of HER-2/neu gene in colon cancer tissues and adjacent tissues, to analyze the relationship between dif erent pathologic types and clinical features, also to invest the distribution of patients with positive expression of HER-2 gene. Methods:The expression of HER-2 gene in the 223 samples with colon can-cer was detected by immunochemical approach. The expression of HER-2 gene in colon cancer tissues and adjacent tissues and dif erent pathologic types was analyzed byχ2 test. The correlation between the expression of HER-2 gene and clinical features was analyzed by Spearman. Results:The number of positive expression of HER-2 gene in colon cancer tissues and adjacent tissues were 74 and 0 respectively, the dif erence has statistical significance. The number of papil ary or tubular adenocarcinoma was 182, among them, 60 cases were positive expression. The number of mucinous adenocarcinoma was 41, among them, 14 cases were positive expression. The expression of HER-2/neu gene has no correlation with sex, age, the maximum diameter, general classification, degree of dif erentiation and depth of invasion, which has no statistical significance. However, the expression of HER-2/neu gene has correlation with metastasis of lymph node and Dukes stage, which has statistical significance. The expression of HER-2/neu gene was positive correlation with metastasis of lymph node and Dukes stage. The correlated coef icient index was 0.320 and 0.320 respectively. In the 74 patients with positive expression of HER-2 gene, 59.4%of them were 60-74 years old. And there was 97.3%of the patients without family history of adenocarcinoma. Conclusion:The expression of HER-2/neu gene in colon cancer tissues was higher than in adjacent tissues. The expression of HER-2/neu gene has no correlation with sex, age, the maximum diameter, general classification, degree of dif erentiation and depth of invasion, but has correlation with metastasis of

  18. Dynamic covariation between gene expression and proteome characteristics

    Directory of Open Access Journals (Sweden)

    Lehtinen Tommi O

    2005-08-01

    Full Text Available Abstract Background Cells react to changing intra- and extracellular signals by dynamically modulating complex biochemical networks. Cellular responses to extracellular signals lead to changes in gene and protein expression. Since the majority of genes encode proteins, we investigated possible correlations between protein parameters and gene expression patterns to identify proteome-wide characteristics indicative of trends common to expressed proteins. Results Numerous bioinformatics methods were used to filter and merge information regarding gene and protein annotations. A new statistical time point-oriented analysis was developed for the study of dynamic correlations in large time series data. The method was applied to investigate microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle. Conclusion We show that the properties of proteins synthesized correlate dynamically with the gene expression profile, indicating that not only is the actual identity and function of expressed proteins important for cellular responses but that several physicochemical and other protein properties correlate with gene expression as well. Gene expression correlates strongly with amino acid composition, composition- and sequence-derived variables, functional, structural, localization and gene ontology parameters. Thus, our results suggest that a dynamic relationship exists between proteome properties and gene expression in many biological systems, and therefore this relationship is fundamental to understanding cellular mechanisms in health and disease.

  19. Benzoic Acid-Inducible Gene Expression in Mycobacteria.

    Directory of Open Access Journals (Sweden)

    Marte S Dragset

    Full Text Available Conditional expression is a powerful tool to investigate the role of bacterial genes. Here, we adapt the Pseudomonas putida-derived positively regulated XylS/Pm expression system to control inducible gene expression in Mycobacterium smegmatis and Mycobacterium tuberculosis, the causative agent of human tuberculosis. By making simple changes to a Gram-negative broad-host-range XylS/Pm-regulated gene expression vector, we prove that it is possible to adapt this well-studied expression system to non-Gram-negative species. With the benzoic acid-derived inducer m-toluate, we achieve a robust, time- and dose-dependent reversible induction of Pm-mediated expression in mycobacteria, with low background expression levels. XylS/Pm is thus an important addition to existing mycobacterial expression tools, especially when low basal expression is of particular importance.

  20. Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

    International Nuclear Information System (INIS)

    Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html

  1. Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

    Directory of Open Access Journals (Sweden)

    Ryden Tobias

    2010-10-01

    Full Text Available Abstract Background Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. Results The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. Conclusions We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html.

  2. Large Scale Gene Expression Meta-Analysis Reveals Tissue-Specific, Sex-Biased Gene Expression in Humans

    Science.gov (United States)

    Mayne, Benjamin T.; Bianco-Miotto, Tina; Buckberry, Sam; Breen, James; Clifton, Vicki; Shoubridge, Cheryl; Roberts, Claire T.

    2016-01-01

    The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analyzed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes), followed by the heart (375 genes), kidney (224 genes), colon (218 genes), and thyroid (163 genes). More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs, and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

  3. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  4. Expression Divergence of Tandemly Arrayed Genes in Human and Mouse

    Directory of Open Access Journals (Sweden)

    Valia Shoja

    2007-01-01

    Full Text Available Tandemly arrayed genes (TAGs account for about one third of the duplicated genes in eukaryotic genomes, yet there has not been any systematic study of their gene expression patterns. Taking advantage of recently published large-scale microarray data sets, we studied the expression divergence of 361 two-member TAGs in human and 212 two-member TAGs in mouse and examined the effect of sequence divergence, gene orientation, and chromosomal proximity on the divergence of TAG expression patterns. Our results show that there is a weak negative correlation between sequence divergence of TAG members and their expression similarity. There is also a weak negative correlation between chromosomal proximity of TAG members and their expression similarity. We did not detect any significant relationship between gene orientation and expression similarity. We also found that downstream TAG members do not show significantly narrower expression breadth than upstream members, contrary to what we predict based on TAG expression divergence hypothesis that we propose. Finally, we show that both chromosomal proximity and expression correlation in TAGs do not differ significantly from their neighboring non-TAG gene pairs, suggesting that tandem duplication is unlikely to be the cause for the higher-than-random expression association between neighboring genes on a chromosome in human and mouse.

  5. Gene length and expression level shape genomic novelties

    OpenAIRE

    Grishkevich, Vladislav; YANAI, Itai

    2014-01-01

    Gene duplication and alternative splicing are important mechanisms in the production of genomic novelties. Previous work has shown that a gene’s family size and the number of splice variants it produces are inversely related, although the underlying reason is not well understood. Here, we report that gene length and expression level together explain this relationship. We found that gene lengths correlate with both gene duplication and alternative splicing: Longer genes are less likely to prod...

  6. Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decomposition

    Institute of Scientific and Technical Information of China (English)

    Ferran Reverter; Esteban Vegas; Pedro Sánchez

    2010-01-01

    The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes.Visualization tools are used to identify genes with similar profiles in microarray studies.Given the large number of genes recorded in microarray experiments,gene expression data are generally displayed on a low dimensional plot,based on linear methods.However,microarray data show nonlinearity,due to high-order terms of interaction between genes,so alternative approaches,such as kernel methods,may be more appropriate.We introduce a technique that combines kernel principal component analysis(KPCA)and Biplot to visualize gene expression profiles.Our approach relies on the singular value decomposition of the input matrix and incorporates an additional step that involves KPCA.The main properties of our method are the extraction of nonlinear features and the preservation of the input variables(genes)in the output display.We apply this algorithm to colon tumor,leukemia and lymphoma datasets.Our approach reveals the underlying structure of the gene expression profiles and provides a more intuitive understanding of the gene and sample association.

  7. Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

    KAUST Repository

    Fujii, Chisato

    2015-04-16

    Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

  8. Isolation of Specific Neurons from C. elegans Larvae for Gene Expression Profiling

    OpenAIRE

    W Clay Spencer; Rebecca McWhirter; Tyne Miller; Pnina Strasbourger; Owen Thompson; Hillier, LaDeana W.; Waterston, Robert H.; Miller, David M.

    2014-01-01

    Background The simple and well-described structure of the C. elegans nervous system offers an unprecedented opportunity to identify the genetic programs that define the connectivity and function of individual neurons and their circuits. A correspondingly precise gene expression map of C. elegans neurons would facilitate the application of genetic methods toward this goal. Here we describe a powerful new approach, SeqCeL (RNA-Seq of C. elegans cells) for producing gene expression profiles of s...

  9. Application of simulated annealing to the biclustering of gene expression data

    OpenAIRE

    Bolshakova, Nadia; Cunningham, Padraig

    2006-01-01

    In a gene expression data matrix, a bicluster is a submatrix of genes and conditions that exhibits a high correlation of expression activity across both rows and columns. The problem of locating the most significant bicluster has been shown to be NP-complete. Heuristic approaches such as Cheng and Church?s greedy node deletion algorithm have been previously employed. It is to be expected that stochastic search techniques such as evolutionary algorithms or simulated anneal...

  10. Integrated Weighted Gene Co-expression Network Analysis with an Application to Chronic Fatigue Syndrome

    OpenAIRE

    Rajeevan Mangalathu S; Suarez Charlyn J; Whistler Toni; Papp Jeanette C; Sobel Eric M; Presson Angela P; Vernon Suzanne D; Horvath Steve

    2008-01-01

    Abstract Background Systems biologic approaches such as Weighted Gene Co-expression Network Analysis (WGCNA) can effectively integrate gene expression and trait data to identify pathways and candidate biomarkers. Here we show that the additional inclusion of genetic marker data allows one to characterize network relationships as causal or reactive in a chronic fatigue syndrome (CFS) data set. Results We combine WGCNA with genetic marker data to identify a disease-related pathway and its causa...

  11. Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood

    Directory of Open Access Journals (Sweden)

    Turner Renee J

    2009-08-01

    Full Text Available Abstract Background Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization. Methods Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT, 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. Results Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder. Conclusion The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.

  12. Cell cycle gene expression under clinorotation

    Science.gov (United States)

    Artemenko, Olga

    2016-07-01

    Cyclins and cyclin-dependent kinase (CDK) are main regulators of the cell cycle of eukaryotes. It's assumes a significant change of their level in cells under microgravity conditions and by other physical factors actions. The clinorotation use enables to determine the influence of gravity on simulated events in the cell during the cell cycle - exit from the state of quiet stage and promotion presynthetic phase (G1) and DNA synthesis phase (S) of the cell cycle. For the clinorotation effect study on cell proliferation activity is the necessary studies of molecular mechanisms of cell cycle regulation and development of plants under altered gravity condition. The activity of cyclin D, which is responsible for the events of the cell cycle in presynthetic phase can be controlled by the action of endogenous as well as exogenous factors, but clinorotation is one of the factors that influence on genes expression that regulate the cell cycle.These data can be used as a model for further research of cyclin - CDK complex for study of molecular mechanisms regulation of growth and proliferation. In this investigation we tried to summarize and analyze known literature and own data we obtained relatively the main regulators of the cell cycle in altered gravity condition.

  13. Assembly and Expression of Shark Ig Genes.

    Science.gov (United States)

    Hsu, Ellen

    2016-05-01

    Sharks are modern descendants of the earliest vertebrates possessing Ig superfamily receptor-based adaptive immunity. They respond to immunogen with Abs that, upon boosting, appear more rapidly and show affinity maturation. Specific Abs and immunological memory imply that Ab diversification and clonal selection exist in cartilaginous fish. Shark Ag receptors are generated through V(D)J recombination, and because it is a mechanism known to generate autoreactive receptors, this implies that shark lymphocytes undergo selection. In the mouse, the ∼2.8-Mb IgH and IgL loci require long-range, differential activation of component parts for V(D)J recombination, allelic exclusion, and receptor editing. These processes, including class switching, evolved with and appear inseparable from the complex locus organization. In contrast, shark Igs are encoded by 100-200 autonomously rearranging miniloci. This review describes how the shark primary Ab repertoire is generated in the absence of structural features considered essential in mammalian Ig gene assembly and expression. PMID:27183649

  14. Transgenic zebrafish recapitulating tbx16 gene early developmental expression.

    Directory of Open Access Journals (Sweden)

    Simon Wells

    Full Text Available We describe the creation of a transgenic zebrafish expressing GFP driven by a 7.5 kb promoter region of the tbx16 gene. This promoter segment is sufficient to recapitulate early embryonic expression of endogenous tbx16 in the presomitic mesoderm, the polster and, subsequently, in the hatching gland. Expression of GFP in the transgenic lines later in development diverges to some extent from endogenous tbx16 expression with the serendipitous result that one line expresses GFP specifically in commissural primary ascending (CoPA interneurons of the developing spinal cord. Using this line we demonstrate that the gene mafba (valentino is expressed in CoPA interneurons.

  15. Gene expression profiles of the developing human retina

    Institute of Scientific and Technical Information of China (English)

    WANG Feng; LI Huiming; LIU Wenwen; XU Ping; HU Gengxi; CHENG Yidong; JIA Libin; HUANG Qian

    2004-01-01

    Retina is a multilayer and highly specialized tissue important in converting light into neural signals. In humans, the critical period for the formation of complex multiplayer structure takes place during embryogenesis between 12 and 28 weeks. The morphologic changes during retinal development in humans have been studied but little is known about the molecular events essential for the formation of the retina. To gain further insights into this process, cDNA microarrays containing 16361 human gene probes were used to measure the gene expression levels in retinas. Of the 16361 genes, 68.7%, 71.4% and 69.7% showed positive hybridization with cDNAs made from 12-16 week fetal, 22-26 week fetal and adult retinas. A total of 814 genes showed a minimum of 3-fold changes between the lowest and highest expression levels among three time points and among them, 106 genes had expression levels with the hybridization intensity above 100 at one or more time points. The clustering analysis suggested that the majority of differentially expressed genes were down-regulated during the retinal development. The differentially expressed genes were further classified according to functions of known genes, and were ranked in decreasing order according to frequency: development, differentiation, signal transduction, protein synthesis and translation, metabolism, DNA binding and transcription, DNA synthesis-repair-recombination, immuno-response, ion channel- transport, cell receptor, cytoskeleton, cell cycle, pro-oncogene, stress and apoptosis related genes. Among these 106 differentially expressed genes, 60 are already present in NEI retina cDNA or EST Databank but the remaining 46 genes are absent and thus identified as "function unknown". To validate gene expression data from the microarray, real-time RT-PCR was performed for 46 "function unknown" genes and 6 known retina specific expression genes, and β-actin was used as internal control. Twenty-seven of these genes showed very similar

  16. Ranking differentially expressed genes from Affymetrix gene expression data: methods with reproducibility, sensitivity, and specificity

    Directory of Open Access Journals (Sweden)

    Shimizu Kentaro

    2009-04-01

    Full Text Available Abstract Background To identify differentially expressed genes (DEGs from microarray data, users of the Affymetrix GeneChip system need to select both a preprocessing algorithm to obtain expression-level measurements and a way of ranking genes to obtain the most plausible candidates. We recently recommended suitable combinations of a preprocessing algorithm and gene ranking method that can be used to identify DEGs with a higher level of sensitivity and specificity. However, in addition to these recommendations, researchers also want to know which combinations enhance reproducibility. Results We compared eight conventional methods for ranking genes: weighted average difference (WAD, average difference (AD, fold change (FC, rank products (RP, moderated t statistic (modT, significance analysis of microarrays (samT, shrinkage t statistic (shrinkT, and intensity-based moderated t statistic (ibmT with six preprocessing algorithms (PLIER, VSN, FARMS, multi-mgMOS (mmgMOS, MBEI, and GCRMA. A total of 36 real experimental datasets was evaluated on the basis of the area under the receiver operating characteristic curve (AUC as a measure for both sensitivity and specificity. We found that the RP method performed well for VSN-, FARMS-, MBEI-, and GCRMA-preprocessed data, and the WAD method performed well for mmgMOS-preprocessed data. Our analysis of the MicroArray Quality Control (MAQC project's datasets showed that the FC-based gene ranking methods (WAD, AD, FC, and RP had a higher level of reproducibility: The percentages of overlapping genes (POGs across different sites for the FC-based methods were higher overall than those for the t-statistic-based methods (modT, samT, shrinkT, and ibmT. In particular, POG values for WAD were the highest overall among the FC-based methods irrespective of the choice of preprocessing algorithm. Conclusion Our results demonstrate that to increase sensitivity, specificity, and reproducibility in microarray analyses, we need

  17. Microdissection of the gene expression codes driving nephrogenesis.

    Science.gov (United States)

    Potter, S Steven; Brunskill, Eric W; Patterson, Larry T

    2010-01-01

    The kidney represents an excellent model system for learning the principles of organogenesis. It is intermediate in complexity, and employs many commonly used developmental processes. As such, kidney development has been the subject of intensive study, using a variety of techniques, including in situ hybridization, organ culture and gene targeting, revealing many critical genes and pathways. Nevertheless, proper organogenesis requires precise patterns of cell type specific differential gene expression, involving very large numbers of genes. This review is focused on the use of global profiling technologies to create an atlas of gene expression codes driving development of different mammalian kidney compartments. Such an atlas allows one to select a gene of interest, and to determine its expression level in each element of the developing kidney, or to select a structure of interest, such as the renal vesicle, and to examine its complete gene expression state. Novel component specific molecular markers are identified, and the changing waves of gene expression that drive nephrogenesis are defined. As the tools continue to improve for the purification of specific cell types and expression profiling of even individual cells it is possible to predict an atlas of gene expression during kidney development that extends to single cell resolution. PMID:21220959

  18. More attention should be paid on the interpretation of gene expression data

    Institute of Scientific and Technical Information of China (English)

    Eric Verna

    2012-01-01

    Molecular profiling of gene expression is important for determining signatures in cancer progression and diagnosis.For this purpose,polymerase chain reactionbased techniques are preferentially used as a feasible and sensitive approach.Nevertheless,when relative quantitative analyses are performed on gene expression,the interpretation of mathematical equations must be carefully done.This letter to the editor is focused on recently published gene expression data in World Journal of Gastroenterology by Ozmen et al demonstrating increased levels of LYVE-1,VEGFR-3 and CD44 genes in gastric cancer samples compared to nonneoplastic gastric tissues.However,there are major concerns about misinterpretation of the gene expression data obtained with the 2-△△ct relative quantitative method.In the study,2-△△Ct values calculated for many samples were smaller than 1 (2-△△ct < 1) which indicate decreased levels of LYVE-1,VEGFR-3 and CD44 gene expression in the gastric cancer tissues.This unfortunate mistake is an important example showing how a simple error in the interpretation of relative-quantitative gene expression data may result in misleading scientific conclusions.In this letter,a brief explanation of the 2-△△ct method is given.In addition,the importance of technical quality and interpretation in gene expression studies is discussed.

  19. Biasogram: visualization of confounding technical bias in gene expression data

    DEFF Research Database (Denmark)

    Krzystanek, Marcin; Szallasi, Zoltan Imre; Eklund, Aron Charles

    2013-01-01

    Gene expression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factor...

  20. MEPD: medaka expression pattern database, genes and more.

    Science.gov (United States)

    Alonso-Barba, Juan I; Rahman, Raza-Ur; Wittbrodt, Joachim; Mateo, Juan L

    2016-01-01

    The Medaka Expression Pattern Database (MEPD; http://mepd.cos.uni-heidelberg.de/) is designed as a repository of medaka expression data for the scientific community. In this update we present two main improvements. First, we have changed the previous clone-centric view for in situ data to a gene-centric view. This is possible because now we have linked all the data present in MEPD to the medaka gene annotation in ENSEMBL. In addition, we have also connected the medaka genes in MEPD to their corresponding orthologous gene in zebrafish, again using the ENSEMBL database. Based on this, we provide a link to the Zebrafish Model Organism Database (ZFIN) to allow researches to compare expression data between these two fish model organisms. As a second major improvement, we have modified the design of the database to enable it to host regulatory elements, promoters or enhancers, expression patterns in addition to gene expression. The combination of gene expression, by traditional in situ, and regulatory element expression, typically by fluorescence reporter gene, within the same platform assures consistency in terms of annotation. In our opinion, this will allow researchers to uncover new insights between the expression domain of genes and their regulatory landscape. PMID:26450962

  1. FGX : a frequentist gene expression index for Affymetrix arrays

    NARCIS (Netherlands)

    Purutçuoğlu, Vilda; Wit, Ernst

    2007-01-01

    We consider a new frequentist gene expression index for Affymetrix oligonucleotide DNA arrays, using a similar probe intensity model as suggested previously, called the Bayesian gene expression index (BGX). According to this model, the perfect match and mismatch values are assumed to be correlated a

  2. RNA preparation and characterization for gene expression studies

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Much information can be obtained from knowledge of the relative expression level of each gene in the transcriptome. With the current advances in technology as little as a single cell is required as starting material for gene expression experiments. The mRNA from a single cell may be linearly ampl...

  3. Peripheral blood gene expression profiles in COPD subjects.

    Science.gov (United States)

    Bhattacharya, Soumyaroop; Tyagi, Shivraj; Srisuma, Sorachai; Demeo, Dawn L; Shapiro, Steven D; Bueno, Raphael; Silverman, Edwin K; Reilly, John J; Mariani, Thomas J

    2011-01-01

    To identify non-invasive gene expression markers for chronic obstructive pulmonary disease (COPD), we performed genome-wide expression profiling of peripheral blood samples from 12 subjects with significant airflow obstruction and an equal number of non-obstructed controls. RNA was isolated from Peripheral Blood Mononuclear Cells (PBMCs) and gene expression was assessed using Affymetrix U133 Plus 2.0 arrays.Tests for gene expression changes that discriminate between COPD cases (FEV1 80% predicted, FEV1/FVC > 0.7) were performed using Significance Analysis of Microarrays (SAM) and Bayesian Analysis of Differential Gene Expression (BADGE). Using either test at high stringency (SAM median FDR = 0 or BADGE p Pearson and Spearman correlation coefficients (p < 0.05), identified a set of 86 genes. A total of 16 markers showed evidence of significant correlation (p < 0.05) with quantitative traits and differential expression between cases and controls. We further compared our peripheral gene expression markers with those we previously identified from lung tissue of the same cohort. Two genes, RP9and NAPE-PLD, were identified as decreased in COPD cases compared to controls in both lung tissue and blood. These results contribute to our understanding of gene expression changes in the peripheral blood of patients with COPD and may provide insight into potential mechanisms involved in the disease. PMID:21884629

  4. Expression and mapping of anthocyanin biosynthesis genes in carrot

    Science.gov (United States)

    Anthocyanin gene expression has been extensively studied in leaves, fruits and flowers of numerous plants. Little, however, is known about anthocyanin accumulation in roots, or in carrots or other Apiaceae. We quantified expression of six anthocyanin biosynthetic genes (phenylalanine ammonia-lyase (...

  5. Digital gene expression tag profiling analysis of the gene expression patterns regulating the early stage of mouse spermatogenesis.

    Directory of Open Access Journals (Sweden)

    Xiujun Zhang

    Full Text Available Detailed characterization of the gene expression patterns in spermatogonia and primary spermatocytes is critical to understand the processes which occur prior to meiosis during normal spermatogenesis. The genome-wide expression profiles of mouse type B spermatogonia and primary spermatocytes were investigated using the Solexa/Illumina digital gene expression (DGE system, a tag based high-throughput transcriptome sequencing method, and the developmental processes which occur during early spermatogenesis were systematically analyzed. Gene expression patterns vary significantly between mouse type B spermatogonia and primary spermatocytes. The functional analysis revealed that genes related to junction assembly, regulation of the actin cytoskeleton and pluripotency were most significantly differently expressed. Pathway analysis indicated that the Wnt non-canonical signaling pathway played a central role and interacted with the actin filament organization pathway during the development of spermatogonia. This study provides a foundation for further analysis of the gene expression patterns and signaling pathways which regulate the molecular mechanisms of early spermatogenesis.

  6. ANALYSES ON DIFFERENTIALLY EXPRESSED GENES ASSOCIATED WITH HUMAN BREAST CANCER

    Institute of Scientific and Technical Information of China (English)

    MENG Xu-li; DING Xiao-wen; XU Xiao-hong

    2006-01-01

    Objective: To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods: Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe. mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip. The different gene expressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5>3.5 meant significant up-regulation. Cy3/Cy5<0.25 meant significant down-regulation. Results: The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressed genes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressed genes did partially exist in the breast cancer tissues. Conclusion: Changes in multi-gene expression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

  7. Use of eukaryotic expression technology in the functional analysis of cloned genes

    International Nuclear Information System (INIS)

    The purpose of this chapter is to describe ways in which eukaryotic expression technology can be used to identify and to analyze the function of cloned eukaryotic genes. The assumption is made that the clone of interest has been sequenced and an open reading frame has been identified. Although expression of genomic sequences will be briefly discussed, in general it is assumed that the sequence of interest is a cDNA. This chapter is divided into three sections. The first section describes several possible strategies for maximizing heterologous gene expression in the cells of higher eukaryotes. The second section deals with potential assays for gene expression based on function, and the third section describes some immunological approaches. Overall, the focus is on the use of techniques which yield information not obtainable from heterologous gene expression in bacteria or yeast

  8. Imaging gene expression in real-time using aptamers

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Ilchung [Iowa State Univ., Ames, IA (United States)

    2012-01-01

    Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

  9. Imaging gene expression in real-time using aptamers

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Il Chung [Iowa State Univ., Ames, IA (United States)

    2011-01-01

    Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

  10. Imaging gene expression in real-time using aptamers

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Il Chung

    2011-12-13

    Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

  11. Imaging gene expression in real-time using aptamers

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Ilchung [Iowa State Univ., Ames, IA (United States)

    2012-11-02

    Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

  12. Differential endometrial gene expression in pregnant and nonpregnant sows

    DEFF Research Database (Denmark)

    Østrup, Esben; Bauersachs, Stefan; Blum, Helmut;

    2010-01-01

    obtained from the endometrium of pregnant sows and sows inseminated with inactivated semen. Analysis of the microarray data revealed 263 genes to be significantly differentially expressed between the pregnant and nonpregnant sows. Most gene ontology terms significantly enriched at pregnancy had allocated......In an attempt to unveil molecular processes controlling the porcine placentation, we have investigated the pregnancy-induced gene expression in the endometrium using the Affymetrix GeneChip Porcine Genome Array. At Day 14 after insemination, at the time of initial placentation, samples were...... the three terms oxidoreductase activity, lipid metabolic process, and organic acid metabolic process had an overrepresentation of down-regulated genes. A gene interaction network based on the genes identified in the gene ontology term developmental processes identified genes likely to be involved...

  13. The effect of negative autoregulation on eukaryotic gene expression

    Science.gov (United States)

    Nevozhay, Dmitry; Adams, Rhys; Murphy, Kevin; Josic, Kresimir; Balázsi, G. Ábor

    2009-03-01

    Negative autoregulation is a frequent motif in gene regulatory networks, which has been studied extensively in prokaryotes. Nevertheless, some effects of negative feedback on gene expression in eukaryotic transcriptional networks remain unknown. We studied how the strength of negative feedback regulation affects the characteristics of gene expression in yeast cells carrying synthetic transcriptional cascades. We observed a drastic reduction of gene expression noise and a change in the shape of the dose-response curve. We explained these experimentally observed effects by stochastic simulations and a simple set of algebraic equations.

  14. Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects

    Directory of Open Access Journals (Sweden)

    van Eijk Kristel R

    2012-11-01

    Full Text Available Abstract Background The predominant model for regulation of gene expression through DNA methylation is an inverse association in which increased methylation results in decreased gene expression levels. However, recent studies suggest that the relationship between genetic variation, DNA methylation and expression is more complex. Results Systems genetic approaches for examining relationships between gene expression and methylation array data were used to find both negative and positive associations between these levels. A weighted correlation network analysis revealed that i both transcriptome and methylome are organized in modules, ii co-expression modules are generally not preserved in the methylation data and vice-versa, and iii highly significant correlations exist between co-expression and co-methylation modules, suggesting the existence of factors that affect expression and methylation of different modules (i.e., trans effects at the level of modules. We observed that methylation probes associated with expression in cis were more likely to be located outside CpG islands, whereas specificity for CpG island shores was present when methylation, associated with expression, was under local genetic control. A structural equation model based analysis found strong support in particular for a traditional causal model in which gene expression is regulated by genetic variation via DNA methylation instead of gene expression affecting DNA methylation levels. Conclusions Our results provide new insights into the complex mechanisms between genetic markers, epigenetic mechanisms and gene expression. We find strong support for the classical model of genetic variants regulating methylation, which in turn regulates gene expression. Moreover we show that, although the methylation and expression modules differ, they are highly correlated.

  15. Expression regulation of design process gene in product design

    DEFF Research Database (Denmark)

    Fang, Lusheng; Li, Bo; Tong, Shurong;

    2011-01-01

    To improve the design process efficiency, this paper proposes the principle and methodology that design process gene controls the characteristics of design process under the framework of design process reuse and optimization based on design process gene. First, the concept of design process gene ...... with the example of design management gene. Last, the regulation mode that the regulator gene regulates the expression of the structural gene is established and it is illustrated by taking the design process management gene as an example. © (2011) Trans Tech Publications....

  16. Gene expression profiling of placentas affected by pre-eclampsia

    DEFF Research Database (Denmark)

    Hoegh, Anne Mette; Borup, Rehannah; Nielsen, Finn Cilius;

    2010-01-01

    Several studies point to the placenta as the primary cause of pre-eclampsia. Our objective was to identify placental genes that may contribute to the development of pre-eclampsia. RNA was purified from tissue biopsies from eleven pre-eclamptic placentas and eighteen normal controls. Messenger RNA...... expression from pooled samples was analysed by microarrays. Verification of the expression of selected genes was performed using real-time PCR. A surprisingly low number of genes (21 out of 15,000) were identified as differentially expressed. Among these were genes not previously associated with pre-eclampsia...... as bradykinin B1 receptor and a 14-3-3 protein, but also genes that have already been connected with pre-eclampsia, for example, inhibin beta A subunit and leptin. A low number of genes were repeatedly identified as differentially expressed, because they may represent the endpoint of a cascade of events...

  17. Decoupling Linear and Nonlinear Associations of Gene Expression

    KAUST Repository

    Itakura, Alan

    2013-05-01

    The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

  18. Fundamental principles of energy consumption for gene expression

    Science.gov (United States)

    Huang, Lifang; Yuan, Zhanjiang; Yu, Jianshe; Zhou, Tianshou

    2015-12-01

    How energy is consumed in gene expression is largely unknown mainly due to complexity of non-equilibrium mechanisms affecting expression levels. Here, by analyzing a representative gene model that considers complexity of gene expression, we show that negative feedback increases energy consumption but positive feedback has an opposite effect; promoter leakage always reduces energy consumption; generating more bursts needs to consume more energy; and the speed of promoter switching is at the cost of energy consumption. We also find that the relationship between energy consumption and expression noise is multi-mode, depending on both the type of feedback and the speed of promoter switching. Altogether, these results constitute fundamental principles of energy consumption for gene expression, which lay a foundation for designing biologically reasonable gene modules. In addition, we discuss possible biological implications of these principles by combining experimental facts.

  19. Discovering Coherent Biclusters from Gene Expression Data Using Zero-Suppressed Binary Decision Diagrams

    OpenAIRE

    Yoon, Sungroh; Nardini, Christine; Benini, Luca; De Micheli, Giovanni

    2005-01-01

    The biclustering method can be a very useful analysis tool when some genes have multiple functions and experimental conditions are diverse in gene expression measurement. This is because the biclustering approach, in contrast to the conventional clustering techniques, focuses on finding a subset of the genes and a subset of the experimental conditions that together exhibit coherent behavior. However, the biclustering problem is inherently intractable, and it is often computationally costly to...

  20. Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data

    Directory of Open Access Journals (Sweden)

    Tintle Nathan L

    2012-08-01

    Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

  1. Regulating gene expression : surprises still in store

    NARCIS (Netherlands)

    Jansen, Ritsert C.; Nap, Jan-Peter

    2004-01-01

    Understanding how genes constitute and contribute to the regulatory networks that result in phenotypic diversity is the major challenge of the post-genome era. Recently, it has been shown that major players in gene regulation can be identified by genome-wide linkage analysis of whole-genome gene exp

  2. Gene expression profiling in adipose tissue from growing broiler chickens

    Science.gov (United States)

    Hausman, Gary J; Barb, C Rick; Fairchild, Brian D; Gamble, John; Lee-Rutherford, Laura

    2014-01-01

    In this study, total RNA was collected from abdominal adipose tissue samples obtained from ten broiler chickens at 3, 4, 5, and 6 weeks of age and prepared for gene microarray analysis with Affymetrix GeneChip Chicken Genome Arrays (Affymetrix) and quantitative real-time PCR analysis. Studies of global gene expression in chicken adipose tissue were initiated since such studies in many animal species show that adipose tissue expresses and secretes many factors that can influence growth and physiology. Microarray results indicated 333 differentially expressed adipose tissue genes between 3 and 6 wk, 265 differentially expressed genes between 4 and 6 wk and 42 differentially expressed genes between 3 and 4 wk. Enrichment scores of Gene Ontology Biological Process categories indicated strong age upregulation of genes involved in the immune system response. In addition to microarray analysis, quantitative real-time PCR analysis was used to confirm the influence of age on the expression of adipose tissue CC chemokine ligands (CCL), toll-like receptor (TLR)-2, lipopolysaccharide-induced TNF factor (LITAF), chemokine (C-C motif) receptor 8 (CCR8), and several other genes. Between 3 and 6 wk of age CCL5, CCL1, and CCR8 expression increased (P = 0.0001) with age. Furthermore, TLR2, CCL19, and LITAF expression increased between 4 and 6 wk of age (P = 0.001). This is the first demonstration of age related changes in CCL, LITAF, and TLR2 gene expression in chicken adipose tissue. Future studies are needed to elucidate the role of these adipose tissue genes in growth and the immune system. PMID:26317054

  3. Gene expression profiles in stages II and III colon cancers

    DEFF Research Database (Denmark)

    Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino;

    2012-01-01

    PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material ...

  4. Dimensionality of Data Matrices with Applications to Gene Expression Profiles

    Science.gov (United States)

    Feng, Xingdong

    2009-01-01

    Probe-level microarray data are usually stored in matrices. Take a given probe set (gene), for example, each row of the matrix corresponds to an array, and each column corresponds to a probe. Often, people summarize each array by the gene expression level. Is one number sufficient to summarize a whole probe set for a specific gene in an array?…

  5. An Effective Tri-Clustering Algorithm Combining Expression Data with Gene Regulation Information

    Directory of Open Access Journals (Sweden)

    Ao Li

    2009-04-01

    Full Text Available Motivation: Bi-clustering algorithms aim to identify sets of genes sharing similar expression patterns across a subset of conditions. However direct interpretation or prediction of gene regulatory mechanisms may be difficult as only gene expression data is used. Information about gene regulators may also be available, most commonly about which transcription factors may bind to the promoter region and thus control the expression level of a gene. Thus a method to integrate gene expression and gene regulation information is desirable for clustering and analyzing. Methods: By incorporating gene regulatory information with gene expression data, we define regulated expression values (REV as indicators of how a gene is regulated by a specific factor. Existing bi-clustering methods are extended to a three dimensional data space by developing a heuristic TRI-Clustering algorithm. An additional approach named Automatic Boundary Searching algorithm (ABS is introduced to automatically determine the boundary threshold. Results: Results based on incorporating ChIP-chip data representing transcription factor-gene interactions show that the algorithms are efficient and robust for detecting tri-clusters. Detailed analysis of the tri-cluster extracted from yeast sporulation REV data shows genes in this cluster exhibited significant differences during the middle and late stages. The implicated regulatory network was then reconstructed for further study of defined regulatory mechanisms. Topological and statistical analysis of this network demonstrated evidence of significant changes of TF activities during the different stages of yeast sporulation, and suggests this approach might be a general way to study regulatory networks undergoing transformations.

  6. An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer

    Directory of Open Access Journals (Sweden)

    Huang Tim

    2010-11-01

    Full Text Available Abstract Background The nuclear transcription factor estrogen receptor alpha (ER-alpha is the target of several antiestrogen therapeutic agents for breast cancer. However, many ER-alpha positive patients do not respond to these treatments from the beginning, or stop responding after being treated for a period of time. Because of the association of gene transcription alteration and drug resistance and the emerging evidence on the role of DNA methylation on transcription regulation, understanding of these relationships can facilitate development of approaches to re-sensitize breast cancer cells to treatment by restoring DNA methylation patterns. Methods We constructed a hierarchical empirical Bayes model to investigate the simultaneous change of gene expression and promoter DNA methylation profiles among wild type (WT and OHT/ICI resistant MCF7 breast cancer cell lines. Results We found that compared with the WT cell lines, almost all of the genes in OHT or ICI resistant cell lines either do not show methylation change or hypomethylated. Moreover, the correlations between gene expression and methylation are quite heterogeneous across genes, suggesting the involvement of other factors in regulating transcription. Analysis of our results in combination with H3K4me2 data on OHT resistant cell lines suggests a clear interplay between DNA methylation and H3K4me2 in the regulation of gene expression. For hypomethylated genes with alteration of gene expression, most (~80% are up-regulated, consistent with current view on the relationship between promoter methylation and gene expression. Conclusions We developed an empirical Bayes model to study the association between DNA methylation in the promoter region and gene expression. Our approach generates both global (across all genes and local (individual gene views of the interplay. It provides important insight on future effort to develop therapeutic agent to re-sensitize breast cancer cells to treatment.

  7. Regulated expression of foreign genes in vivo after germline transfer.

    OpenAIRE

    Passman, R S; Fishman, G I

    1994-01-01

    Tight transcriptional control of foreign genes introduced into the germline of transgenic mice would be of great experimental value in studies of gene function. To develop a system in which the spatial and temporal expression of candidate genes implicated in cardiac development or function could be tightly controlled in vivo, we have generated transgenic mice expressing a tetracycline-controlled transactivator (tTA) under the control of a rat alpha myosin heavy chain promoter (MHC alpha-tTA m...

  8. Inducible gene expression system by 3-hydroxypropionic acid

    OpenAIRE

    Zhou, Shengfang; Ainala, Satish Kumar; Seol, Eunhee; Nguyen, Trinh Thi; Park, Sunghoon

    2015-01-01

    Background 3-Hydroxypropionic acid (3-HP) is an important platform chemical that boasts a variety of industrial applications. Gene expression systems inducible by 3-HP, if available, are of great utility for optimization of the pathways of 3-HP production and excretion. Results Here we report the presence of unique inducible gene expression systems in Pseudomonas denitrificans and other microorganisms. In P. denitrificans, transcription of three genes (hpdH, mmsA and hbdH-4) involved in 3-HP ...

  9. Pancreatic expression of human insulin gene in transgenic mice.

    OpenAIRE

    Bucchini, D; Ripoche, M A; Stinnakre, M G; Desbois, P; Lorès, P; Monthioux, E; Absil, J; Lepesant, J A; Pictet, R; Jami, J

    1986-01-01

    We have investigated the possibility of obtaining integration and expression of a native human gene in transgenic mice. An 11-kilobase (kb) human chromosomal DNA fragment including the insulin gene (1430 base pairs) was microinjected into fertilized mouse eggs. This fragment was present in the genomic DNA of several developing animals. One transgenic mouse and its progeny were analyzed for expression of the foreign gene. Synthesis and release of human insulin was revealed by detection of the ...

  10. Gene expression profiles of mouse spermatogenesis during recovery from irradiation

    DEFF Research Database (Denmark)

    Shah, Fozia J; Tanaka, Masami; Nielsen, John E;

    2009-01-01

    the cellular changes that happen during recovery from irradiation by means of histology. We have earlier generated gene expression profiles during induction of spermatogenesis in mouse postnatal developing testes and found a correlation between profiles and the expressing cell types. The aim of the present...... work was to utilize the link between expression profile and cell types to follow the cellular changes that occur during post-irradiation recovery of spermatogenesis in order to describe recovery by means of gene expression. METHODS: Adult mouse testes were subjected to irradiation with 1 Gy...... or a fractionated radiation of two times 1 Gy. Testes were sampled every third or fourth day to follow the recovery of spermatogenesis and gene expression profiles generated by means of differential display RT-PCR. In situ hybridization was in addition performed to verify cell-type specific gene expression patterns...

  11. Sequential construction of a model for modular gene expression control, applied to spatial patterning of the Drosophila gene hunchback.

    Science.gov (United States)

    Spirov, Alexander V; Myasnikova, Ekaterina M; Holloway, David M

    2016-04-01

    Gene network simulations are increasingly used to quantify mutual gene regulation in biological tissues. These are generally based on linear interactions between single-entity regulatory and target genes. Biological genes, by contrast, commonly have multiple, partially independent, cis-regulatory modules (CRMs) for regulator binding, and can produce variant transcription and translation products. We present a modeling framework to address some of the gene regulatory dynamics implied by this biological complexity. Spatial patterning of the hunchback (hb) gene in Drosophila development involves control by three CRMs producing two distinct mRNA transcripts. We use this example to develop a differential equations model for transcription which takes into account the cis-regulatory architecture of the gene. Potential regulatory interactions are screened by a genetic algorithms (GAs) approach and compared to biological expression data.

  12. Performance Analysis of Enhanced Clustering Algorithm for Gene Expression Data

    Directory of Open Access Journals (Sweden)

    T. Chandrasekhar

    2011-11-01

    Full Text Available Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this paper we applied K-Means with Automatic Generations of Merge Factor for ISODATA- AGMFI. Though AGMFI has been applied for clustering of Gene Expression Data, this proposed Enhanced Automatic Generations of Merge Factor for ISODATA- EAGMFI Algorithms overcome the drawbacks of AGMFI in terms of specifying the optimal number of clusters and initialization of good cluster centroids. Experimental results on Gene Expression Data show that the proposed EAGMFI algorithms could identify compact clusters with perform well in terms of the Silhouette Coefficients cluster measure.

  13. Toxicogenomic Analysis Suggests Chemical-Induced Sexual Dimorphism in the Expression of Metabolic Genes in Zebrafish Liver

    OpenAIRE

    Xun Zhang; Choong Yong Ung; Siew Hong Lam; Jing Ma; Yu Zong Chen; Louxin Zhang; Zhiyuan Gong; Baowen Li

    2012-01-01

    Differential gene expression in two sexes is widespread throughout the animal kingdom, giving rise to sex-dimorphic gene activities and sex-dependent adaptability to environmental cues, diets, growth and development as well as susceptibility to diseases. Here, we present a study using a toxicogenomic approach to investigate metabolic genes that show sex-dimorphic expression in the zebrafish liver triggered by several chemicals. Our analysis revealed that, besides the known genes for xenobioti...

  14. Biclustering of the Gene Expression Data by Coevolution Cuckoo Search

    OpenAIRE

    Lu Yin; Yongguo Liu

    2015-01-01

    Biclustering has a potential to discover the local expression patterns analyzing the gene expression data which provide clues about biological processes. However, since it is proven that the biclustering problem is NP-hard, it is necessary to seek more effective algorithm. Cuckoo Search (CS) models the brood parasitism behavior of cuckoo to solve the optimization problem and outperforms the other existing algorithms. In this paper, we introduce a new algorithm for biclustering gene expression...

  15. GEE: An Informatics Tool for Gene Expression Data Explore

    OpenAIRE

    Lee, Soo Youn; Park, Chan Hee; Yoon, Jun Hee; Yun, Sunmin; Kim, Ju Han

    2016-01-01

    Objectives Major public high-throughput functional genomic data repositories, including the Gene Expression Omnibus (GEO) and ArrayExpress have rapidly expanded. As a result, a large number of diverse high-throughput functional genomic data retrieval systems have been developed. However, high-throughput functional genomic data retrieval remains challenging. Methods We developed Gene Expression data Explore (GEE), the first powerful, flexible web and mobile search application for searching who...

  16. Differential expression of olfactory genes in the southern house mosquito and insights into unique odorant receptor gene isoforms

    OpenAIRE

    Walter S Leal; Choo, Young-Moo; Xu, Pingxi; da Silva, Cherre S. B.; Ueira-Vieira, Carlos

    2013-01-01

    Mosquitoes use their acute sense of smell to locate hosts, oviposition sites, and repellents. Here, we investigated by next generation sequencing the key molecular components of the olfactory system of the southern house mosquito—a vector of West Nile virus. We studied differential expression of genes in antennae—the main olfactory organ—and nonolfactory tissues. Additionally, we prospected for unknown genes with transcripts enriched in antennae. Our approach, which was validated by quantitat...

  17. An atlas of gene expression and gene co-regulation in the human retina.

    Science.gov (United States)

    Pinelli, Michele; Carissimo, Annamaria; Cutillo, Luisa; Lai, Ching-Hung; Mutarelli, Margherita; Moretti, Maria Nicoletta; Singh, Marwah Veer; Karali, Marianthi; Carrella, Diego; Pizzo, Mariateresa; Russo, Francesco; Ferrari, Stefano; Ponzin, Diego; Angelini, Claudia; Banfi, Sandro; di Bernardo, Diego

    2016-07-01

    The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it). PMID:27235414

  18. DNA microarray analysis of genes differentially expressed in adipocyte differentiation

    Indian Academy of Sciences (India)

    Chunyan Yin; Yanfeng Xiao; Wei Zhang; Erdi Xu; Weihua Liu; Xiaoqing Yi; Ming Chang

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  19. Expression of HOX C homeobox genes in lymphoid cells.

    Science.gov (United States)

    Lawrence, H J; Stage, K M; Mathews, C H; Detmer, K; Scibienski, R; MacKenzie, M; Migliaccio, E; Boncinelli, E; Largman, C

    1993-08-01

    The class I homeobox genes located in four clusters in mammalian genomes (HOX A, HOX B, HOX C, and HOX D) appear to play a major role in fetal development. Previous surveys of homeobox gene expression in human leukemic cell lines have shown that certain HOX A genes are expressed only in myeloid cell lines, whereas HOX B gene expression is largely restricted to cells with erythroid potential. We now report a survey of the expression patterns of 9 homeobox genes from the HOX C locus in a panel of 24 human and 7 murine leukemic cell lines. The most striking observation is the lymphoid-specific pattern of expression of HOX C4, located at the 3' end of the locus. A major transcript of 1.9 kilobases is observed in both T-cell and B-cell lines. HOX C4 expression is also detected in normal human marrow and peripheral blood lymphocytes, but not in mature granulocytes or monocytes. HOX C8 is also expressed in human lymphoid cells but is expressed in other blood cell types as well. However, the HOX C8 transcript pattern is lineage specific. These data, in conjunction with earlier findings, suggest that homeobox gene expression influences lineage determination during hematopoiesis.

  20. Seed-based biclustering of gene expression data.

    Directory of Open Access Journals (Sweden)

    Jiyuan An

    Full Text Available BACKGROUND: Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. METHODS: In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns (a a gene set, and (b the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. CONCLUSIONS: This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.

  1. Profiling gene expression in human placentae of different gestational ages: an OPRU Network and UW SCOR Study.

    Science.gov (United States)

    Mikheev, Andrei M; Nabekura, Tomohiro; Kaddoumi, Amal; Bammler, Theo K; Govindarajan, Rajgopal; Hebert, Mary F; Unadkat, Jashvant D

    2008-11-01

    We used the whole-genome approach to identify major functional categories of genes whose expression depends on gestational age. Using microarray analysis, we compared gene expression profiles in the villous tissues of first (45-59 days) and second trimester (109-115 days) placentae with C-section term placentae. We found that in first trimester placentae, genes related to cell cycle, DNA, amino acids, and carbohydrate metabolism were significantly overrepresented, while genes related to signal transduction were underrepresented. Among genes involved in organism defense, we identified genes involved in chemical response, metabolism, and transport. Analysis of signal transduction pathways suggested, and subsequently confirmed independently, that the Wnt pathway was changed with gestational age leading to inhibition of beta-catenin protein expression. Our study will serve as a reference database to gain insight into the regulation of gene expression in the developing placentae and to compare with gene expression in placentae from complicated pregnancies.

  2. Paralogous Genes as a Tool to Study the Regulation of Gene Expression

    DEFF Research Database (Denmark)

    Hoffmann, Robert D

    their duplicate were found to be under less purifying selection. A gene ontology (GO) term enrichment analysis showed that paralogs with similar expression levels were enriched in GO terms related to macromolecular complexes, whereas paralogs with different expression levels were enriched in terms associated...... new functions, or their gene products are in a dosage balance. Regulatory DNA elements - some of which are conserved across species and hence called conserved non-coding sequences (CNSs) - that control expression of duplicated genes are thus under similar purifying selection. In the present study, I...... have performed in-depth analyses of paralogous genes in Arabidopsis thaliana, their expression profile, their sequence conservation, and their functions, in order to investigate the relationship between gene expression and retention of paralogous genes. Paralogs with lower expression than...

  3. Agrobacterium-mediated transient gene expression and silencing: a rapid tool for functional gene assay in potato.

    Directory of Open Access Journals (Sweden)

    Pudota B Bhaskar

    Full Text Available Potato is the third most important food crop worldwide. However, genetic and genomic research of potato has lagged behind other major crops due to the autopolyploidy and highly heterozygous nature associated with the potato genome. Reliable and technically undemanding techniques are not available for functional gene assays in potato. Here we report the development of a transient gene expression and silencing system in potato. Gene expression or RNAi-based gene silencing constructs were delivered into potato leaf cells using Agrobacterium-mediated infiltration. Agroinfiltration of various gene constructs consistently resulted in potato cell transformation and spread of the transgenic cells around infiltration zones. The efficiency of agroinfiltration was affected by potato genotypes, concentration of Agrobacterium, and plant growth conditions. We demonstrated that the agroinfiltration-based transient gene expression can be used to detect potato proteins in sub-cellular compartments in living cells. We established a double agroinfiltration procedure that allows to test whether a specific gene is associated with potato late blight resistance pathway mediated by the resistance gene RB. This procedure provides a powerful approach for high throughput functional assay for a large number of candidate genes in potato late blight resistance.

  4. Deoxyribozymes inhibit the expression of periodl gene in vitro

    Institute of Scientific and Technical Information of China (English)

    ZHOU Wei; WANG Yueqi; LIU Yanyou; PENG Wenzhen; XIAO Jing; ZHU Bin; WANG Zhengrong

    2005-01-01

    To investigate the effect of two deoxyribozymes targeting periodl (perl) mRNA in vitro for exploring a novel gene therapy approach about circadian rhythm diseases, the specific deoxyribozymes targeting perl were designed and synthesized chemically following MFold analysis according to its mRNA secondary structure, perl RNA fragments were prepared by in vitro transcription of pcDNA3.1 (+)-perl164:256. The cleavage reactions containing deoxyribozymes and perl RNA fragments were performed under certain conditions. With the transfection technique mediated by LipofectAMINETM, pcDNA3-perl and DRz164 or DRz256 were introduced into NIH3T3 cells. The effects of deoxyribozymes on perl were studied by reverse transcript-polymerase chain reaction (RT-PCR) and flow cytometry (FCM). When deoxyribozymes and RNA transcripts were incubated under the adopted conditions at 37℃ for 2 h, about 63% of perl164:256 RNA transcripts were cleaved by DRz164 and about 50.5% by DRz256. After cotransfecting pcDNA3-perl with DRz164 or DRz256, the expression of perl mRNA was decreased, as indicated by RT-PCR semi-quantity analysis. FCM analysis showed that Perl protein was inhibited. Both DRz164 and DRz256 targeting perl have the specific cleavage activity toward perl mRNA in vitro and can highly block the expression of perl gene in cellular milieu.

  5. BICLUSTERING GENE EXPRESSION DATASET USING ENHANCED BARYCENTER CROSSING MINIMIZATION

    Directory of Open Access Journals (Sweden)

    Tamer Mohamed

    2013-01-01

    Full Text Available There are two main categories of bi-clustering approaches graph-based bi-clustering, and non-graph based bi-clustering. In graph-based bi-clustering algorithm the input dataset is converted into bigraph such as bipartite graph, and apply some heuristic local searching techniques to minimize the number of crossings between edges in the Bigraph such as BaryCenter (BC used in SPHier algorithm. The main problem of graph-based bi-clustering algorithm is to extract the best bi-clusters, and this leads to the ordering of gene expression dataset before we apply biclustering algorithm. In bipartite graph this is achieved through minimizing the number of crossings in bipartite graph. As we minimize the number of crossings in the bipartite graph, the gene expression dataset becomes more ordered, and this enhances the results of biclustering algorithm. The main goal of our proposed algorithm is the enhancement of graph-based biclustering algorithm by enhancing BaryCenter crossing minimization heuristics of bipartite graph. In the proposed algorithm we add the rank of each node to the rank of its neighbors, and using the position of each node in the calculations to give a new rank to each node, and using this rank for reordering the nodes of each layer.

  6. A gene expression atlas of early craniofacial development.

    Science.gov (United States)

    Brunskill, Eric W; Potter, Andrew S; Distasio, Andrew; Dexheimer, Phillip; Plassard, Andrew; Aronow, Bruce J; Potter, S Steven

    2014-07-15

    We present a gene expression atlas of early mouse craniofacial development. Laser capture microdissection (LCM) was used to isolate cells from the principal critical microregions, whose development, differentiation and signaling interactions are responsible for the construction of the mammalian face. At E8.5, as migrating neural crest cells begin to exit the neural fold/epidermal ectoderm boundary, we examined the cranial mesenchyme, composed of mixed neural crest and paraxial mesoderm cells, as well as cells from adjacent neuroepithelium. At E9.5 cells from the cranial mesenchyme, overlying olfactory placode/epidermal ectoderm, and underlying neuroepithelium, as well as the emerging mandibular and maxillary arches were sampled. At E10.5, as the facial prominences form, cells from the medial and lateral prominences, the olfactory pit, multiple discrete regions of underlying neuroepithelium, the mandibular and maxillary arches, including both their mesenchymal and ectodermal components, as well as Rathke's pouch, were similarly sampled and profiled using both microarray and RNA-seq technologies. Further, we performed single cell studies to better define the gene expression states of the early E8.5 pioneer neural crest cells and paraxial mesoderm. Taken together, and analyzable by a variety of biological network approaches, these data provide a complementing and cross validating resource capable of fueling discovery of novel compartment specific markers and signatures whose combinatorial interactions of transcription factors and growth factors/receptors are responsible for providing the master genetic blueprint for craniofacial development. PMID:24780627

  7. Gene expression module-based chemical function similarity search

    OpenAIRE

    Li, Yun; Hao, Pei; Zheng, Siyuan; Tu, Kang; Fan, Haiwei; Zhu, Ruixin; Ding, Guohui; Dong, Changzheng; Wang, Chuan; Li, Xuan; Thiesen, H.-J.; Chen, Y. Eugene; Jiang, HuaLiang; Liu, Lei; Li, Yixue

    2008-01-01

    Investigation of biological processes using selective chemical interventions is generally applied in biomedical research and drug discovery. Many studies of this kind make use of gene expression experiments to explore cellular responses to chemical interventions. Recently, some research groups constructed libraries of chemical related expression profiles, and introduced similarity comparison into chemical induced transcriptome analysis. Resembling sequence similarity alignment, expression pat...

  8. Temporal dynamics of gene expression in the lung in a baboon model of E. coli sepsis

    Directory of Open Access Journals (Sweden)

    Zhu Hua

    2007-02-01

    Full Text Available Abstract Background Bacterial invasion during sepsis induces disregulated systemic responses that could lead to fatal lung failure. The purpose of this study was to relate the temporal dynamics of gene expression to the pathophysiological changes in the lung during the first and second stages of E. coli sepsis in baboons. Results Using human oligonucleotide microarrays, we have explored the temporal changes of gene expression in the lung of baboons challenged with sublethal doses of E. coli. Temporal expression pattern and biological significance of the differentially expressed genes were explored using clustering and pathway analysis software. Expression of selected genes was validated by real-time PCR. Cytokine levels in tissue and plasma were assayed by multiplex ELISA. Changes in lung ultrastructure were visualized by electron microscopy. We found that genes involved in primary inflammation, innate immune response, and apoptosis peaked at 2 hrs. Inflammatory and immune response genes that function in the stimulation of monocytes, natural killer and T-cells, and in the modulation of cell adhesion peaked at 8 hrs, while genes involved in wound healing and functional recovery were upregulated at 24 hrs. Conclusion The analysis of gene expression modulation in response to sepsis provides the baseline information that is crucial for the understanding of the pathophysiology of systemic inflammation and may facilitate the development of future approaches for sepsis therapy.

  9. Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.

    Science.gov (United States)

    Creanza, Teresa Maria; Liguori, Maria; Liuni, Sabino; Nuzziello, Nicoletta; Ancona, Nicola

    2016-01-01

    Differential gene expression analyses to investigate multiple sclerosis (MS) molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN)-β treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1) that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS) development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment. PMID:27314336

  10. Gene Body Methylation can alter Gene Expression and is a Therapeutic Target in Cancer

    Science.gov (United States)

    Yang, Xiaojing; Han, Han; De Carvalho, Daniel D.; Lay, Fides D.; Jones, Peter A.; Liang, Gangning

    2014-01-01

    SUMMARY DNA methylation in promoters is well known to silence genes and is the presumed therapeutic target of methylation inhibitors. Gene body methylation is positively correlated with expression yet its function is unknown. We show that 5-aza-2'-deoxycytidine treatment not only reactivates genes but decreases the over-expression of genes, many of which are involved in metabolic processes regulated by c-MYC. Down-regulation is caused by DNA demethylation of the gene bodies and restoration of high levels of expression requires remethylation by DNMT3B. Gene body methylation may therefore be an unexpected therapeutic target for DNA methylation inhibitors, resulting in the normalization of gene over-expression induced during carcinogenesis. Our results provide direct evidence for a causal relationship between gene body methylation and transcription. PMID:25263941

  11. Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

    Science.gov (United States)

    Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

  12. Building an atlas of gene expression driving kidney development: pushing the limits of resolution.

    Science.gov (United States)

    Potter, S Steven; Brunskill, Eric W

    2014-04-01

    Changing gene expression patterns is the essential driver of developmental processes. Growth factors, micro-RNAs, long intergenic noncoding RNAs, and epigenetic marks, such as DNA methylation and histone modifications, all work by impacting gene expression. The key features of developing cells, including their ability to communicate with others, are defined primarily by their gene-expression profiles. It is therefore clear that a gene-expression atlas of the developing kidney can provide a useful tool for the developmental nephrology research community. Toward this end, the GenitoUrinary Development Molecular Anatomy Project (GUDMAP) consortium has worked to create an atlas of the changing gene-expression patterns that drive kidney development. In this article, the global gene-expression profiling strategies of GUDMAP are reviewed. The initial work used laser-capture microdissection to purify multiple compartments of the developing kidney, including cap mesenchyme, renal vesicle, S-shaped bodies, proximal tubules, and more, which were then gene-expression profiled using microarrays. Resolution of the atlas was then improved by using transgenic mice with specific cell types labeled with green fluorescent protein (GFP), allowing their purification and profiling. In addition, RNA-Seq replaced microarrays. Currently, the atlas is being pushed to the single-cell resolution using microfluidic approaches that allow high-throughput RNA-Seq analysis of hundreds of individual cells. Results can identify novel types of cells and define interesting heterogeneities present within cell populations. PMID:23996451

  13. Noise in gene expression is coupled to growth rate.

    Science.gov (United States)

    Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

    2015-12-01

    Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. PMID:26355006

  14. Gene Expression Prediction by Soft Integration and the Elastic Net—Best Performance of the DREAM3 Gene Expression Challenge

    OpenAIRE

    Mika Gustafsson; Michael Hörnquist

    2010-01-01

    Background: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression va...

  15. Parabolic flight induces changes in gene expression patterns in Arabidopsis thaliana.

    Science.gov (United States)

    Paul, Anna-Lisa; Manak, Michael S; Mayfield, John D; Reyes, Matthew F; Gurley, William B; Ferl, Robert J

    2011-10-01

    Our primary objective was to evaluate gene expression changes in Arabidopsis thaliana in response to parabolic flight as part of a comprehensive approach to the molecular biology of spaceflight-related adaptations. In addition, we wished to establish parabolic flight as a tractable operations platform for molecular biology studies. In a succession of experiments on NASA's KC-135 and C-9 parabolic aircraft, Arabidopsis plants were presented with replicated exposure to parabolic flight. Transcriptome profiling revealed that parabolic flight caused changes in gene expression patterns that stood the statistical tests of replication on three different flight days. The earliest response, after 20 parabolas, was characterized by a prominence of genes associated with signal transduction. After 40 parabolas, this prominence was largely replaced by genes associated with biotic and abiotic stimuli and stress. Among these responses, three metabolic processes stand out in particular: the induction of auxin metabolism and signaling, the differential expression of genes associated with calcium-mediated signaling, and the repression of genes associated with disease resistance and cell wall biochemistry. Many, but not all, of these responses are known to be involved in gravity sensing in plants. Changes in auxin-related gene expression were also recorded by reporter genes tuned to auxin signal pathways. These data demonstrate that the parabolic flight environment is appropriate for molecular biology research involving the transition to microgravity, in that with replication, proper controls, and analyses, gene expression changes can be observed in the time frames of typical parabolic flight experiments.

  16. Empirical validation of the S-Score algorithm in the analysis of gene expression data

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2006-03-01

    Full Text Available Abstract Background Current methods of analyzing Affymetrix GeneChip® microarray data require the estimation of probe set expression summaries, followed by application of statistical tests to determine which genes are differentially expressed. The S-Score algorithm described by Zhang and colleagues is an alternative method that allows tests of hypotheses directly from probe level data. It is based on an error model in which the detected signal is proportional to the probe pair signal for highly expressed genes, but approaches a background level (rather than 0 for genes with low levels of expression. This model is used to calculate relative change in probe pair intensities that converts probe signals into multiple measurements with equalized errors, which are summed over a probe set to form the S-Score. Assuming no expression differences between chips, the S-Score follows a standard normal distribution, allowing direct tests of hypotheses to be made. Using spike-in and dilution datasets, we validated the S-Score method against comparisons of gene expression utilizing the more recently developed methods RMA, dChip, and MAS5. Results The S-score showed excellent sensitivity and specificity in detecting low-level gene expression changes. Rank ordering of S-Score values more accurately reflected known fold-change values compared to other algorithms. Conclusion The S-score method, utilizing probe level data directly, offers significant advantages over comparisons using only probe set expression summaries.

  17. Quantitative assessment of gene expression network module-validation methods.

    Science.gov (United States)

    Li, Bing; Zhang, Yingying; Yu, Yanan; Wang, Pengqian; Wang, Yongcheng; Wang, Zhong; Wang, Yongyan

    2015-01-01

    Validation of pluripotent modules in diverse networks holds enormous potential for systems biology and network pharmacology. An arising challenge is how to assess the accuracy of discovering all potential modules from multi-omic networks and validating their architectural characteristics based on innovative computational methods beyond function enrichment and biological validation. To display the framework progress in this domain, we systematically divided the existing Computational Validation Approaches based on Modular Architecture (CVAMA) into topology-based approaches (TBA) and statistics-based approaches (SBA). We compared the available module validation methods based on 11 gene expression datasets, and partially consistent results in the form of homogeneous models were obtained with each individual approach, whereas discrepant contradictory results were found between TBA and SBA. The TBA of the Zsummary value had a higher Validation Success Ratio (VSR) (51%) and a higher Fluctuation Ratio (FR) (80.92%), whereas the SBA of the approximately unbiased (AU) p-value had a lower VSR (12.3%) and a lower FR (45.84%). The Gray area simulated study revealed a consistent result for these two models and indicated a lower Variation Ratio (VR) (8.10%) of TBA at 6 simulated levels. Despite facing many novel challenges and evidence limitations, CVAMA may offer novel insights into modular networks. PMID:26470848

  18. Flies selected for longevity retain a young gene expression profile

    DEFF Research Database (Denmark)

    Sarup, Pernille Merete; Sørensen, Peter; Loeschcke, Volker

    2011-01-01

      We investigated correlated responses in the transcriptomes of longevity-selected lines of Drosophila melanogaster to identify pathways that affect life span in metazoan systems. We evaluated the gene expression profile in young, middle-aged, and old male flies, finding that 530 genes were...... differentially expressed between selected and control flies when measured at the same chronological age. The longevity-selected flies consistently showed expression profiles more similar to control flies one age class younger than control flies of the same age. This finding is in accordance with a younger gene...... expression profile in longevity-selected lines. Among the genes down-regulated in longevity-selected lines, we found a clear over-representation of genes involved in immune functions, supporting the hypothesis of a life-shortening effect of an overactive immune system, known as inflammaging. We judged...

  19. Computational gene expression profiling under salt stress reveals patterns of co-expression.

    Science.gov (United States)

    Sanchita; Sharma, Ashok

    2016-03-01

    Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

  20. Gene expression profiles of Nitrosomonas europaea, an obligate chemolitotroph

    Energy Technology Data Exchange (ETDEWEB)

    Daniel J. Arp

    2005-05-25

    Nitrosomonas europaea is an aerobic lithoautotrophic bacterium that uses ammonia (NH3) as its energy source. As a nitrifier, it is an important participant in the nitrogen cycle, which can also influence the carbon cycle. The focus of this work was to explore the genetic structure and mechanisms underlying the lithoautotrophic growth style of N. europaea. Whole genome gene expression: The gene expression profile of cells in exponential growth and during starvation was analyzed using microarrays. During growth, 98% of the genes increased in expression at least two fold compared to starvation conditions. In growing cells, approximately 30% of the genes were expressed eight fold higher, Approximately 10% were expressed more than 15 fold higher. Approximately 3% (91 genes) were expressed to more than 20 fold of their levels in starved cells. Carbon fixation gene expression: N. europaea fixes carbon via the Calvin-Benson-Bassham (CBB) cycle via a type I ribulose bisphosphate carboxylase/oxygenase (RubisCO). This study showed that transcription of cbb genes was up-regulated when the carbon source was limited, while amo, hao and other energy harvesting related genes were down-regulated. Iron related gene expression: Because N. europaea has a relatively high content of hemes, sufficient Fe must be available in the medium for it to grow. The genome revealed that approximately 5% of the coding genes in N. europaea are dedicated to Fe transport and assimilation. Nonetheless, with the exception of citrate biosynthesis genes, N. europaea lacks genes for siderophore production. The Fe requirements for growth and the expression of the putative membrane siderophore receptors were determined. The N. europaea genome has over 100 putative genes ({approx}5% of the coding genes) related to Fe uptake and its siderophore receptors could be grouped phylogenetically in four clusters. Fe related genes, such as a number of TonB-dependent Fe-siderophore receptors for ferrichrome and

  1. Gene expression profiles of Nitrosomonas europaea, an obligate chemolitotroph

    Energy Technology Data Exchange (ETDEWEB)

    Daniel J Arp

    2005-06-15

    Nitrosomonas europaea is an aerobic lithoautotrophic bacterium that uses ammonia (NH3) as its energy source. As a nitrifier, it is an important participant in the nitrogen cycle, which can also influence the carbon cycle. The focus of this work was to explore the genetic structure and mechanisms underlying the lithoautotrophic growth style of N. europaea. Whole genome gene expression. The gene expression profile of cells in exponential growth and during starvation was analyzed using microarrays. During growth, 98% of the genes increased in expression at least two fold compared to starvation conditions. In growing cells, approximately 30% of the genes were expressed eight fold higher, Approximately 10% were expressed more than 15 fold higher. Approximately 3% (91 genes) were expressed to more than 20 fold of their levels in starved cells. Carbon fixation gene expression. N. europaea fixes carbon via the Calvin-Benson-Bassham (CBB) cycle via a type I ribulose bisphosphate carboxylase/oxygenase (RubisCO). This study showed that transcription of cbb genes was up-regulated when the carbon source was limited, while amo, hao and other energy harvesting related genes were down-regulated. Iron related gene expression. Because N. europaea has a relatively high content of hemes, sufficient Fe must be available in the medium for it to grow. The genome revealed that approximately 5% of the coding genes in N. europaea are dedicated to Fe transport and assimilation. Nonetheless, with the exception of citrate biosynthesis genes, N. europaea lacks genes for siderophore production. The Fe requirements for growth and the expression of the putative membrane siderophore receptors were determined. The N. europaea genome has over 100 putative genes ({approx}5% of the coding genes) related to Fe uptake and its siderophore receptors could be grouped phylogenetically in four clusters. Fe related genes, such as a number of TonB-dependent Fe-siderophore receptors for ferrichrome and

  2. Detecting microRNA activity from gene expression data.

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-01-01

    BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  3. Detecting microRNA activity from gene expression data

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-05-18

    Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  4. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    Willard M. Freeman

    2002-01-01

    Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

  5. Expression of homeobox genes in the mouse olfactory epithelium.

    Science.gov (United States)

    Parrilla, Marta; Chang, Isabelle; Degl'Innocenti, Andrea; Omura, Masayo

    2016-10-01

    Homeobox genes constitute a large family of genes widely studied because of their role in the establishment of the body pattern. However, they are also involved in many other events during development and adulthood. The main olfactory epithelium (MOE) is an excellent model to study neurogenesis in the adult nervous system. Analyses of homeobox genes during development show that some of these genes are involved in the formation and establishment of cell diversity in the MOE. Moreover, the mechanisms of expression of odorant receptors (ORs) constitute one of the biggest enigmas in the field. Analyses of OR promoters revealed the presence of homeodomain binding sites in their sequences. Here we characterize the expression patterns of a set of 49 homeobox genes in the MOE with in situ hybridization. We found that seven of them (Dlx3, Dlx5, Dlx6, Msx1, Meis1, Isl1, and Pitx1) are zonally expressed. The homeobox gene Emx1 is expressed in three guanylate cyclase(+) populations, two located in the MOE and the third one in an olfactory subsystem known as Grüneberg ganglion located at the entrance of the nasal cavity. The homeobox gene Tshz1 is expressed in a unique patchy pattern across the MOE. Our findings provide new insights to guide functional studies that aim to understand the complexity of transcription factor expression and gene regulation in the MOE. J. Comp. Neurol. 524:2713-2739, 2016. © 2016 Wiley Periodicals, Inc. PMID:27243442

  6. The Iterative Signature Algorithm for the analysis of large scale gene expression data

    CERN Document Server

    Bergmann, S R; Barkai, N; Bergmann, Sven; Ihmels, Jan; Barkai, Naama

    2003-01-01

    We present a new approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster, we assign both genes and conditions to context-dependent and potentially overlapping transcription modules. We provide a rigorous definition of a transcription module as the object to be retrieved from the expression data. An efficient algorithm, that searches for the modules encoded in the data by iteratively refining sets of genes and conditions until they match this definition, is established. Each iteration involves a linear map, induced by the normalized expression matrix, followed by the application of a threshold function. We argue that our method is in fact a generalization of Singular Value Decomposition, which corresponds to the special case where no threshold is applied. We show analytically that for noisy expression data our approach leads to better classificatio...

  7. A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

    Directory of Open Access Journals (Sweden)

    Emond Mary

    2007-09-01

    Full Text Available Abstract Background Marfan syndrome (MFS is a heritable connective tissue disorder caused by mutations in the fibrillin-1 gene. This syndrome constitutes a significant identifiable subtype of aortic aneurysmal disease, accounting for over 5% of ascending and thoracic aortic aneurysms. Results We used spotted membrane DNA macroarrays to identify genes whose altered expression levels may contribute to the phenotype of the disease. Our analysis of 4132 genes identified a subset with significant expression differences between skin fibroblast cultures from unaffected controls versus cultures from affected individuals with known fibrillin-1 mutations. Subsequently, 10 genes were chosen for validation by quantitative RT-PCR. Conclusion Differential expression of many of the validated genes was associated with MFS samples when an additional group of unaffected and MFS affected subjects were analyzed (p-value -6 under the null hypothesis that expression levels in cultured fibroblasts are unaffected by MFS status. An unexpected observation was the range of individual gene expression. In unaffected control subjects, expression ranges exceeding 10 fold were seen in many of the genes selected for qRT-PCR validation. The variation in expression in the MFS affected subjects was even greater.

  8. Expression of venom gene homologs in diverse python tissues suggests a new model for the evolution of snake venom.

    Science.gov (United States)

    Reyes-Velasco, Jacobo; Card, Daren C; Andrew, Audra L; Shaney, Kyle J; Adams, Richard H; Schield, Drew R; Casewell, Nicholas R; Mackessy, Stephen P; Castoe, Todd A

    2015-01-01

    Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression.

  9. Applications of Little's Law to stochastic models of gene expression

    CERN Document Server

    Elgart, Vlad; Kulkarni, Rahul V

    2010-01-01

    The intrinsic stochasticity of gene expression can lead to large variations in protein levels across a population of cells. To explain this variability, different sources of mRNA fluctuations ('Poisson' and 'Telegraph' processes) have been proposed in stochastic models of gene expression. Both Poisson and Telegraph scenario models explain experimental observations of noise in protein levels in terms of 'bursts' of protein expression. Correspondingly, there is considerable interest in establishing relations between burst and steady-state protein distributions for general stochastic models of gene expression. In this work, we address this issue by considering a mapping between stochastic models of gene expression and problems of interest in queueing theory. By applying a general theorem from queueing theory, Little's Law, we derive exact relations which connect burst and steady-state distribution means for models with arbitrary waiting-time distributions for arrival and degradation of mRNAs and proteins. The de...

  10. The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

    Science.gov (United States)

    Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

    2011-02-01

    The gonadal soma-derived factor (GSDF) belongs to the transforming growth factor-β superfamily and is conserved in teleostean fish species. Gsdf is specifically expressed in the gonads, and gene expression is restricted to the granulosa and Sertoli cells in trout and medaka. The gsdf gene expression is correlated to early testis differentiation in medaka and was shown to stimulate primordial germ cell and spermatogonia proliferation in trout. In the present study, we show that the gsdf gene localizes to a syntenic chromosomal fragment conserved among vertebrates although no gsdf-related gene is detected on the corresponding genomic region in tetrapods. We demonstrate using quantitative RT-PCR that most of the genes localized in the synteny are specifically expressed in medaka gonads. Gsdf is the only gene of the synteny with a much higher expression in the testis compared to the ovary. In contrast, gene expression pattern analysis of the gsdf surrounding genes (nup54, aff1, klhl8, sdad1, and ptpn13) indicates that these genes are preferentially expressed in the female gonads. The tissue distribution of these genes is highly similar in medaka and zebrafish, two teleostean species that have diverged more than 110 million years ago. The cellular localization of these genes was determined in medaka gonads using the whole-mount in situ hybridization technique. We confirm that gsdf gene expression is restricted to Sertoli and granulosa cells in contact with the premeiotic and meiotic cells. The nup54 gene is expressed in spermatocytes and previtellogenic oocytes. Transcripts corresponding to the ovary-specific genes (aff1, klhl8, and sdad1) are detected only in previtellogenic oocytes. No expression was detected in the gonocytes in 10 dpf embryos. In conclusion, we show that the gsdf gene localizes to a syntenic chromosomal fragment harboring evolutionary conserved genes in vertebrates. These genes are preferentially expressed in previtelloogenic oocytes, and thus, they

  11. Novel redox nanomedicine improves gene expression of polyion complex vector

    International Nuclear Information System (INIS)

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an ROS scavenger. When polyethyleneimine (PEI)/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI)/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF)-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  12. Novel redox nanomedicine improves gene expression of polyion complex vector

    Science.gov (United States)

    Toh, Kazuko; Yoshitomi, Toru; Ikeda, Yutaka; Nagasaki, Yukio

    2011-12-01

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an ROS scavenger. When polyethyleneimine (PEI)/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI)/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF)-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  13. Novel redox nanomedicine improves gene expression of polyion complex vector

    Directory of Open Access Journals (Sweden)

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Full Text Available Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP as an ROS scavenger. When polyethyleneimine (PEI/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  14. Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Hu Xiaohua

    2011-07-01

    Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

  15. Design and Implementation of Visual Dynamic Display Software of Gene Expression Based on GTK

    Institute of Scientific and Technical Information of China (English)

    JIANG Wei; MENG Fanjiang; LI Yong; YU Xiao

    2009-01-01

    The paper presented an implement method for a dynamic gene expression display software based on the GTK. This method established the dynamic presentation system of gene expression which according to gene expression data from gene chip hybridize at different time, adopted a linearity combination model and Pearson correlation coefficient algorithm. The system described the gene expression changes in graphic form, the gene expression changes with time and the changes in characteristics of the gene expression, also the changes in relations of the gene expression and regulation relationships among genes. The system also provided an integrated platform for analysis on gene chips data, especially for the research on the network of gene regulation.

  16. Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas

    OpenAIRE

    Zhou, Ruigang; MAN, YIGANG

    2016-01-01

    The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed gene...

  17. Characterization of MTAP Gene Expression in Breast Cancer Patients and Cell Lines.

    Directory of Open Access Journals (Sweden)

    Sarah Franco Vieira de Oliveira

    Full Text Available MTAP is a ubiquitously expressed gene important for adenine and methionine salvage. The gene is located at 9p21, a chromosome region often deleted in breast carcinomas, similar to CDKN2A, a recognized tumor suppressor gene. Several research groups have shown that MTAP acts as a tumor suppressor, and some therapeutic approaches were proposed based on a tumors´ MTAP status. We analyzed MTAP and CDKN2A gene (RT-qPCR and protein (western-blotting expression in seven breast cancer cell lines and evaluated their promoter methylation patterns to better characterize the contribution of these genes to breast cancer. Cytotoxicity assays with inhibitors of de novo adenine synthesis (5-FU, AZA and MTX after MTAP gene knockdown showed an increased sensitivity, mainly to 5-FU. MTAP expression was also evaluated in two groups of samples from breast cancer patients, fresh tumors and paired normal breast tissue, and from formalin-fixed paraffin embedded (FFPE core breast cancer samples diagnosed as Luminal-A tumors and triple negative breast tumors (TNBC. The difference of MTAP expression between fresh tumors and normal tissues was not statistically significant. However, MTAP expression was significantly higher in Luminal-A breast tumors than in TNBC, suggesting the lack of expression in more aggressive breast tumors and the possibility of using the new approaches based on MTAP status in TNBC.

  18. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

    Energy Technology Data Exchange (ETDEWEB)

    Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

    2004-05-18

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  19. Molecular subsets in the gene expression signatures of scleroderma skin.

    Directory of Open Access Journals (Sweden)

    Ausra Milano

    Full Text Available BACKGROUND: Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production. METHODOLOGY AND FINDINGS: We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc with diffuse scleroderma (dSSc, 7 patients with SSc with limited scleroderma (lSSc, 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001 and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud's phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc. CONCLUSIONS AND SIGNIFICANCE: Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrates multiple distinct gene expression programs

  20. Dopamine receptor-mediated regulation of neuronal "clock" gene expression.

    Science.gov (United States)

    Imbesi, M; Yildiz, S; Dirim Arslan, A; Sharma, R; Manev, H; Uz, T

    2009-01-23

    Using a transgenic mice model (i.e. "clock" knockouts), clock transcription factors have been suggested as critical regulators of dopaminergic behaviors induced by drugs of abuse. Moreover, it has been shown that systemic administration of psychostimulants, such as cocaine and methamphetamine regulates the striatal expression of clock genes. However, it is not known whether dopamine receptors mediate these regulatory effects of psychostimulants at the cellular level. Primary striatal neurons in culture express dopamine receptors as well as clock genes and have been successfully used in studying dopamine receptor functioning. Therefore, we investigated the role of dopamine receptors on neuronal clock gene expression in this model using specific receptor agonists. We found an inhibitory effect on the expression of mClock and mPer1 genes with the D2-class (i.e. D2/D3) receptor agonist quinpirole. We also found a generalized stimulatory effect on the expression of clock genes mPer1, mClock, mNPAS2 (neuronal PAS domain protein 2), and mBmal1 with the D1-class (i.e. D1) receptor agonist SKF38393. Further, we tested whether systemic administration of dopamine receptor agonists causes similar changes in striatal clock gene expression in vivo. We found quinpirole-induced alterations in mPER1 protein levels in the mouse striatum (i.e. rhythm shift). Collectively, our results indicate that the dopamine receptor system may mediate psychostimulant-induced changes in clock gene expression. Using striatal neurons in culture as a model, further research is needed to better understand how dopamine signaling modulates the expression dynamics of clock genes (i.e. intracellular signaling pathways) and thereby influences neuronal gene expression, neuronal transmission, and brain functioning. PMID:19017537

  1. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  2. Translational Approaches towards Cancer Gene Therapy: Hurdles and Hopes

    OpenAIRE

    Yadollah Omidi; Jaleh Barar

    2012-01-01

    Introduction: Of the cancer gene therapy approaches, gene silencing, suicide/apoptosis inducing gene therapy, immunogene therapy and targeted gene therapy are deemed to sub­stantially control the biological consequences of genomic changes in cancerous cells. Thus, a large number of clinical trials have been conducted against various malignancies. In this review, we will discuss recent translational progresses of gene and cell therapy of cancer. Methods: Essential information on gene therapy o...

  3. A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network.

    Science.gov (United States)

    Ruan, Xiyun; Li, Hongyun; Liu, Bo; Chen, Jie; Zhang, Shibao; Sun, Zeqiang; Liu, Shuangqing; Sun, Fahai; Liu, Qingyong

    2015-08-01

    The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson's correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson's correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

  4. Gene gymnastics: Synthetic biology for baculovirus expression vector system engineering.

    Science.gov (United States)

    Vijayachandran, Lakshmi S; Thimiri Govinda Raj, Deepak B; Edelweiss, Evelina; Gupta, Kapil; Maier, Josef; Gordeliy, Valentin; Fitzgerald, Daniel J; Berger, Imre

    2013-01-01

    Most essential activities in eukaryotic cells are catalyzed by large multiprotein assemblies containing up to ten or more interlocking subunits. The vast majority of these protein complexes are not easily accessible for high resolution studies aimed at unlocking their mechanisms, due to their low cellular abundance and high heterogeneity. Recombinant overproduction can resolve this bottleneck and baculovirus expression vector systems (BEVS) have emerged as particularly powerful tools for the provision of eukaryotic multiprotein complexes in high quality and quantity. Recently, synthetic biology approaches have begun to make their mark in improving existing BEVS reagents by de novo design of streamlined transfer plasmids and by engineering the baculovirus genome. Here we present OmniBac, comprising new custom designed reagents that further facilitate the integration of heterologous genes into the baculovirus genome for multiprotein expression. Based on comparative genome analysis and data mining, we herein present a blueprint to custom design and engineer the entire baculovirus genome for optimized production properties using a bottom-up synthetic biology approach. PMID:23328086

  5. In situ gene expression in mixed-culture biofilms: Evidence of metabolic interactions between community members

    DEFF Research Database (Denmark)

    Møller, Søren; Sternberg, Claus; Andersen, Jens Bo;

    1998-01-01

    , Furthermore, in fixed biofilm samples organism identity was determined and gene expression was visualized at the same time by combining GFP expression with in situ hybridization with fluorescence-labeled 16S rRNA targeting probes. This combination of techniques is a powerful approach for investigating......Microbial communities growing in laboratory-based pow chambers were investigated in order to study compartmentalization of specific gene expression. Among the community members studied, the focus,vas in particular on Pseudomonas putida and a strain of an Acinetobacter sp., and the genes studied...... are involved in the biodegradation of toluene and related aromatic compounds. The upper-pathway promoter (Pu) and the meta-pathway promoter (Pm) from the TOL plasmid were fused independently to the gene coding for the green fluorescent protein (GFP), and expression from these promoters was studied in P. putida...

  6. An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics

    CERN Document Server

    Charlebois, Daniel A; Fraser, Dawn; Kaern, Mads

    2011-01-01

    We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo method to simulate time-dependent statistical characteristics of growing cell populations. To benchmark performance, we compare simulation results with steadystate and time-dependent analytical solutions for several scenarios, including steadystate and time-dependent gene expression, and the effects on population heterogeneity of cell growth, division, and DNA replication. This comparison demonstrates that the algorithm provides an efficient and accurate approach to simulate how complex biological features influence gene expression. We also use the algorithm to model gene expression dynamics within "bet-hedging" cell populations during their adaption to environmental stress. These simulations indicate that the algorithm provides a framework suitable for simulating and ana...

  7. Extracting gene expression profiles common to colon and pancreatic adenocarcinoma using simultaneous nonnegative matrix factorization.

    Science.gov (United States)

    Badea, Liviu

    2008-01-01

    In this paper we introduce a clustering algorithm capable of simultaneously factorizing two distinct gene expression datasets with the aim of uncovering gene regulatory programs that are common to the two phenotypes. The siNMF algorithm simultaneously searches for two factorizations that share the same gene expression profiles. The two key ingredients of this algorithm are the nonnegativity constraint and the offset variables, which together ensure the sparseness of the factorizations. While cancer is a very heterogeneous disease, there is overwhelming recent evidence that the differences between cancer subtypes implicate entire pathways and biological processes involving large numbers of genes, rather than changes in single genes. We have applied our simultaneous factorization algorithm looking for gene expression profiles that are common between the more homogeneous pancreatic ductal adenocarcinoma (PDAC) and the more heterogeneous colon adenocarcinoma. The fact that the PDAC signature is active in a large fraction of colon adeocarcinoma suggests that the oncogenic mechanisms involved may be similar to those in PDAC, at least in this subset of colon samples. There are many approaches to uncovering common mechanisms involved in different phenotypes, but most are based on comparing gene lists. The approach presented in this paper additionally takes gene expression data into account and can thus be more sensitive. PMID:18229692

  8. Gene expression profiling of canine osteosarcoma reveals genes associated with short and long survival times

    Directory of Open Access Journals (Sweden)

    Rao Nagesha AS

    2009-09-01

    Full Text Available Abstract Background Gene expression profiling of spontaneous tumors in the dog offers a unique translational opportunity to identify prognostic biomarkers and signaling pathways that are common to both canine and human. Osteosarcoma (OS accounts for approximately 80% of all malignant bone tumors in the dog. Canine OS are highly comparable with their human counterpart with respect to histology, high metastatic rate and poor long-term survival. This study investigates the prognostic gene profile among thirty-two primary canine OS using canine specific cDNA microarrays representing 20,313 genes to identify genes and cellular signaling pathways associated with survival. This, the first report of its kind in dogs with OS, also demonstrates the advantages of cross-species comparison with human OS. Results The 32 tumors were classified into two prognostic groups based on survival time (ST. They were defined as short survivors (dogs with poor prognosis: surviving fewer than 6 months and long survivors (dogs with better prognosis: surviving 6 months or longer. Fifty-one transcripts were found to be differentially expressed, with common upregulation of these genes in the short survivors. The overexpressed genes in short survivors are associated with possible roles in proliferation, drug resistance or metastasis. Several deregulated pathways identified in the present study, including Wnt signaling, Integrin signaling and Chemokine/cytokine signaling are comparable to the pathway analysis conducted on human OS gene profiles, emphasizing the value of the dog as an excellent model for humans. Conclusion A molecular-based method for discrimination of outcome for short and long survivors is useful for future prognostic stratification at initial diagnosis, where genes and pathways associated with cell cycle/proliferation, drug resistance and metastasis could be potential targets for diagnosis and therapy. The similarities between human and canine OS makes the

  9. Spatial gene expression quantification in changing morphologies

    NARCIS (Netherlands)

    D. Botman

    2016-01-01

    In systems biology, an organisms’ behavior is explained from the interactions among individual components such as genes and proteins. With few exceptions, interactions among genes and proteins are not measured directly and are therefore inferred from the observed output of a biological system. A net

  10. In plants, expression breadth and expression level distinctly and non-linearly correlate with gene structure

    Directory of Open Access Journals (Sweden)

    Yang Hangxing

    2009-11-01

    Full Text Available Abstract Background Compactness of highly/broadly expressed genes in human has been explained as selection for efficiency, regional mutation biases or genomic design. However, highly expressed genes in flowering plants were shown to be less compact than lowly expressed ones. On the other hand, opposite facts have also been documented that pollen-expressed Arabidopsis genes tend to contain shorter introns and highly expressed moss genes are compact. This issue is important because it provides a chance to compare the selectionism and the neutralism views about genome evolution. Furthermore, this issue also helps to understand the fates of introns, from the angle of gene expression. Results In this study, I used expression data covering more tissues and employ new analytical methods to reexamine the correlations between gene expression and gene structure for two flowering plants, Arabidopsis thaliana and Oryza sativa. It is shown that, different aspects of expression pattern correlate with different parts of gene sequences in distinct ways. In detail, expression level is significantly negatively correlated with gene size, especially the size of non-coding regions, whereas expression breadth correlates with non-coding structural parameters positively and with coding region parameters negatively. Furthermore, the relationships between expression level and structural parameters seem to be non-linear, with the extremes of structural parameters possibly scale as power-laws or logrithmic functions of expression levels. Conclusion In plants, highly expressed genes are compact, especially in the non-coding regions. Broadly expressed genes tend to contain longer non-coding sequences, which may be necessary for complex regulations. In combination with previous studies about other plants and about animals, some common scenarios about the correlation between gene expression and gene structure begin to emerge. Based on the functional relationships between

  11. State-related alterations of gene expression in bipolar disorder

    DEFF Research Database (Denmark)

    Munkholm, Klaus; Vinberg, Maj; Berk, Michael;

    2012-01-01

    Munkholm K, Vinberg M, Berk M, Kessing LV. State-related alterations of gene expression in bipolar disorder: a systematic review. Bipolar Disord 2012: 14: 684-696. © 2012 The Authors. Journal compilation © 2012 John Wiley & Sons A/S. Objective:  Alterations in gene expression in bipolar disorder...... on comprehensive database searches for studies on gene expression in patients with bipolar disorder in specific mood states, was conducted. We searched Medline, Embase, PsycINFO, and The Cochrane Library, supplemented by manually searching reference lists from retrieved publications. Results:  A total of 17...

  12. Gene expression during testis development in Duroc boars

    DEFF Research Database (Denmark)

    Lervik, Siri; Kristoffersen, Anja Bråthen; Conley, Lene;

    2015-01-01

    . Nine clusters of genes with significant differential expression over time and 49 functional charts were found in the analysed testis samples. Pro