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Sample records for based gene expression

  1. Classification of genes based on gene expression analysis

    SciTech Connect

    Angelova, M. Myers, C. Faith, J.

    2008-05-15

    Systems biology and bioinformatics are now major fields for productive research. DNA microarrays and other array technologies and genome sequencing have advanced to the point that it is now possible to monitor gene expression on a genomic scale. Gene expression analysis is discussed and some important clustering techniques are considered. The patterns identified in the data suggest similarities in the gene behavior, which provides useful information for the gene functionalities. We discuss measures for investigating the homogeneity of gene expression data in order to optimize the clustering process. We contribute to the knowledge of functional roles and regulation of E. coli genes by proposing a classification of these genes based on consistently correlated genes in expression data and similarities of gene expression patterns. A new visualization tool for targeted projection pursuit and dimensionality reduction of gene expression data is demonstrated.

  2. Robust PCA based method for discovering differentially expressed genes.

    PubMed

    Liu, Jin-Xing; Wang, Yu-Tian; Zheng, Chun-Hou; Sha, Wen; Mi, Jian-Xun; Xu, Yong

    2013-01-01

    How to identify a set of genes that are relevant to a key biological process is an important issue in current molecular biology. In this paper, we propose a novel method to discover differentially expressed genes based on robust principal component analysis (RPCA). In our method, we treat the differentially and non-differentially expressed genes as perturbation signals S and low-rank matrix A, respectively. Perturbation signals S can be recovered from the gene expression data by using RPCA. To discover the differentially expressed genes associated with special biological progresses or functions, the scheme is given as follows. Firstly, the matrix D of expression data is decomposed into two adding matrices A and S by using RPCA. Secondly, the differentially expressed genes are identified based on matrix S. Finally, the differentially expressed genes are evaluated by the tools based on Gene Ontology. A larger number of experiments on hypothetical and real gene expression data are also provided and the experimental results show that our method is efficient and effective.

  3. Control of alphavirus-based gene expression using engineered riboswitches.

    PubMed

    Bell, Christie L; Yu, Dong; Smolke, Christina D; Geall, Andrew J; Beard, Clayton W; Mason, Peter W

    2015-09-01

    Alphavirus-based replicons are a promising nucleic acid vaccine platform characterized by robust gene expression and immune responses. To further explore their use in vaccination, replicons were engineered to allow conditional control over their gene expression. Riboswitches, comprising a ribozyme actuator and RNA aptamer sensor, were engineered into the replicon 3' UTR. Binding of ligand to aptamer modulates ribozyme activity and, therefore, gene expression. Expression from DNA-launched and VRP-packaged replicons containing riboswitches was successfully regulated, achieving a 47-fold change in expression and modulation of the resulting type I interferon response. Moreover, we developed a novel control architecture where riboswitches were integrated into the 3' and 5' UTR of the subgenomic RNA region of the TC-83 virus, leading to an 1160-fold regulation of viral replication. Our studies demonstrate that the use of riboswitches for control of RNA replicon expression and viral replication holds promise for development of novel and safer vaccination strategies.

  4. Nonlinear model-based method for clustering periodically expressed genes.

    PubMed

    Tian, Li-Ping; Liu, Li-Zhi; Zhang, Qian-Wei; Wu, Fang-Xiang

    2011-01-01

    Clustering periodically expressed genes from their time-course expression data could help understand the molecular mechanism of those biological processes. In this paper, we propose a nonlinear model-based clustering method for periodically expressed gene profiles. As periodically expressed genes are associated with periodic biological processes, the proposed method naturally assumes that a periodically expressed gene dataset is generated by a number of periodical processes. Each periodical process is modelled by a linear combination of trigonometric sine and cosine functions in time plus a Gaussian noise term. A two stage method is proposed to estimate the model parameter, and a relocation-iteration algorithm is employed to assign each gene to an appropriate cluster. A bootstrapping method and an average adjusted Rand index (AARI) are employed to measure the quality of clustering. One synthetic dataset and two biological datasets were employed to evaluate the performance of the proposed method. The results show that our method allows the better quality clustering than other clustering methods (e.g., k-means) for periodically expressed gene data, and thus it is an effective cluster analysis method for periodically expressed gene data.

  5. An Agent-Based Clustering Approach for Gene Selection in Gene Expression Microarray.

    PubMed

    Ramos, Juan; Castellanos-Garzón, José A; González-Briones, Alfonso; de Paz, Juan F; Corchado, Juan M

    2017-03-09

    Gene selection is a major research area in microarray analysis, which seeks to discover differentially expressed genes for a particular target annotation. Such genes also often called informative genes are able to differentiate tissue samples belonging to different classes of the studied disease. Despite the fact that there is a wide number of proposals, the complexity imposed by this problem remains a challenge today. This research proposes a gene selection approach by means of a clustering-based multi-agent system. This proposal manages different filter methods and gene clustering through coordinated agents to discover informative gene subsets. To assess the reliability of our approach, we have used four important and public gene expression datasets, two Lung cancer datasets, Colon and Leukemia cancer dataset. The achieved results have been validated through cluster validity measures, visual analytics, a classifier and compared with other gene selection methods, proving the reliability of our proposal.

  6. Computing gene expression data with a knowledge-based gene clustering approach.

    PubMed

    Rosa, Bruce A; Oh, Sookyung; Montgomery, Beronda L; Chen, Jin; Qin, Wensheng

    2010-01-01

    Computational analysis methods for gene expression data gathered in microarray experiments can be used to identify the functions of previously unstudied genes. While obtaining the expression data is not a difficult task, interpreting and extracting the information from the datasets is challenging. In this study, a knowledge-based approach which identifies and saves important functional genes before filtering based on variability and fold change differences was utilized to study light regulation. Two clustering methods were used to cluster the filtered datasets, and clusters containing a key light regulatory gene were located. The common genes to both of these clusters were identified, and the genes in the common cluster were ranked based on their coexpression to the key gene. This process was repeated for 11 key genes in 3 treatment combinations. The initial filtering method reduced the dataset size from 22,814 probes to an average of 1134 genes, and the resulting common cluster lists contained an average of only 14 genes. These common cluster lists scored higher gene enrichment scores than two individual clustering methods. In addition, the filtering method increased the proportion of light responsive genes in the dataset from 1.8% to 15.2%, and the cluster lists increased this proportion to 18.4%. The relatively short length of these common cluster lists compared to gene groups generated through typical clustering methods or coexpression networks narrows the search for novel functional genes while increasing the likelihood that they are biologically relevant.

  7. Random forests-based differential analysis of gene sets for gene expression data.

    PubMed

    Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

    2013-04-10

    In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for

  8. Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm.

    PubMed

    Dong, Li-Yang; Zhou, Wei-Zhong; Ni, Jun-Wei; Xiang, Wei; Hu, Wen-Hao; Yu, Chang; Li, Hai-Yan

    2017-02-01

    The objective of this study was to identify the optimal gene and gene set for hepatocellular carcinoma (HCC) utilizing differential expression and differential co-expression (DEDC) algorithm. The DEDC algorithm consisted of four parts: calculating differential expression (DE) by absolute t-value in t-statistics; computing differential co-expression (DC) based on Z-test; determining optimal thresholds on the basis of Chi-squared (χ2) maximization and the corresponding gene was the optimal gene; and evaluating functional relevance of genes categorized into different partitions to determine the optimal gene set with highest mean minimum functional information (FI) gain (Δ*G). The optimal thresholds divided genes into four partitions, high DE and high DC (HDE-HDC), high DE and low DC (HDE-LDC), low DE and high DC (LDE‑HDC), and low DE and low DC (LDE-LDC). In addition, the optimal gene was validated by conducting reverse transcription-polymerase chain reaction (RT-PCR) assay. The optimal threshold for DC and DE were 1.032 and 1.911, respectively. Using the optimal gene, the genes were divided into four partitions including: HDE-HDC (2,053 genes), HED-LDC (2,822 genes), LDE-HDC (2,622 genes), and LDE-LDC (6,169 genes). The optimal gene was microtubule‑associated protein RP/EB family member 1 (MAPRE1), and RT-PCR assay validated the significant difference between the HCC and normal state. The optimal gene set was nucleoside metabolic process (GO\\GO:0009116) with Δ*G = 18.681 and 24 HDE-HDC partitions in total. In conclusion, we successfully investigated the optimal gene, MAPRE1, and gene set, nucleoside metabolic process, which may be potential biomarkers for targeted therapy and provide significant insight for revealing the pathological mechanism underlying HCC.

  9. Configurable pattern-based evolutionary biclustering of gene expression data

    PubMed Central

    2013-01-01

    Background Biclustering algorithms for microarray data aim at discovering functionally related gene sets under different subsets of experimental conditions. Due to the problem complexity and the characteristics of microarray datasets, heuristic searches are usually used instead of exhaustive algorithms. Also, the comparison among different techniques is still a challenge. The obtained results vary in relevant features such as the number of genes or conditions, which makes it difficult to carry out a fair comparison. Moreover, existing approaches do not allow the user to specify any preferences on these properties. Results Here, we present the first biclustering algorithm in which it is possible to particularize several biclusters features in terms of different objectives. This can be done by tuning the specified features in the algorithm or also by incorporating new objectives into the search. Furthermore, our approach bases the bicluster evaluation in the use of expression patterns, being able to recognize both shifting and scaling patterns either simultaneously or not. Evolutionary computation has been chosen as the search strategy, naming thus our proposal Evo-Bexpa (Evolutionary Biclustering based in Expression Patterns). Conclusions We have conducted experiments on both synthetic and real datasets demonstrating Evo-Bexpa abilities to obtain meaningful biclusters. Synthetic experiments have been designed in order to compare Evo-Bexpa performance with other approaches when looking for perfect patterns. Experiments with four different real datasets also confirm the proper performing of our algorithm, whose results have been biologically validated through Gene Ontology. PMID:23433178

  10. Identification of feature genes for smoking-related lung adenocarcinoma based on gene expression profile data

    PubMed Central

    Liu, Ying; Ni, Ran; Zhang, Hui; Miao, Lijun; Wang, Jing; Jia, Wenqing; Wang, Yuanyuan

    2016-01-01

    This study aimed to identify the genes and pathways associated with smoking-related lung adenocarcinoma. Three lung adenocarcinoma associated datasets (GSE43458, GSE10072, and GSE50081), the subjects of which included smokers and nonsmokers, were downloaded to screen the differentially expressed feature genes between smokers and nonsmokers. Based on the identified feature genes, we constructed the protein–protein interaction (PPI) network and optimized feature genes using closeness centrality (CC) algorithm. Then, the support vector machine (SVM) classification model was constructed based on the feature genes with higher CC values. Finally, pathway enrichment analysis of the feature genes was performed. A total of 213 down-regulated and 83 up-regulated differentially expressed genes were identified. In the constructed PPI network, the top ten nodes with higher degrees and CC values included ANK3, EPHA4, FGFR2, etc. The SVM classifier was constructed with 27 feature genes, which could accurately identify smokers and nonsmokers. Pathways enrichment analysis for the 27 feature genes revealed that they were significantly enriched in five pathways, including proteoglycans in cancer (EGFR, SDC4, SDC2, etc.), and Ras signaling pathway (FGFR2, PLA2G1B, EGFR, etc.). The 27 feature genes, such as EPHA4, FGFR2, and EGFR for SVM classifier construction and cancer-related pathways of Ras signaling pathway and proteoglycans in cancer may play key roles in the progression and development of smoking-related lung adenocarcinoma. PMID:27994470

  11. Gene expression of a gene family in maize based on noncollinear haplotypes

    PubMed Central

    Song, Rentao; Messing, Joachim

    2003-01-01

    Genomic regions of nearly every species diverged into different haplotypes, mostly based on point mutations, small deletions, and insertions that do not affect the collinearity of genes within a species. However, the same genomic interval containing the z1C gene cluster of two inbred lines of Zea mays significantly lost their gene collinearity and also differed in the regulation of each remaining gene set. Furthermore, when inbreds were reciprocally crossed, hybrids exhibited an unexpected shift of expression patterns so that “overdominance” instead of “dominance complementation” of allelic and nonallelic gene expression occurred. The same interval also differed in length (360 vs. 263 kb). Segmental rearrangements led to sequence changes, which were further enhanced by the insertion of different transposable elements. Changes in gene order affected not only z1C genes but also three unrelated genes. However, the orthologous interval between two subspecies of rice (not rice cultivars) was conserved in length and gene order, whereas changes between two maize inbreds were as drastic as changes between maize and sorghum. Given that chromosomes could conceivably consist of intervals of haplotypes that are highly diverged, one could envision endless breeding opportunities because of their linear arrangement along a chromosome and their expression potential in hybrid combinations (“binary” systems). The implication of such a hypothesis for heterosis is discussed. PMID:12853580

  12. Gene regulatory network clustering for graph layout based on microarray gene expression data.

    PubMed

    Kojima, Kaname; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

    2010-01-01

    We propose a statistical model realizing simultaneous estimation of gene regulatory network and gene module identification from time series gene expression data from microarray experiments. Under the assumption that genes in the same module are densely connected, the proposed method detects gene modules based on the variational Bayesian technique. The model can also incorporate existing biological prior knowledge such as protein subcellular localization. We apply the proposed model to the time series data from a synthetically generated network and verified the effectiveness of the proposed model. The proposed model is also applied the time series microarray data from HeLa cell. Detected gene module information gives the great help on drawing the estimated gene network.

  13. Minimal gene selection for classification and diagnosis prediction based on gene expression profile

    PubMed Central

    Mehridehnavi, Alireza; Ziaei, Lia

    2013-01-01

    Background: Up to date different methods have been used in order to dimensions reduction, classification, clustering and prediction of cancers based on gene expression profiling. The aim of this study is extracting most significant genes and classifying of Diffuse Large B-cell Lymphoma (DLBCL) patients on the basis of their gene expression profiles. Materials and Methods: We studied 40 DLBCL patients and 4026 genes. We utilized Artificial Neural Network (ANN) for classification of patients in two groups: Germinal center and Activated like. As we were faced with low number of patients (40) and numerous genes (4026), we tried to deploy one optimum network and achieve to minimum error. Moreover we used signal to noise (S/N) ratio as a main tool for dimension reduction. We tried to select suitable training data and so to train just one network instead of 26 networks. Finally, we extracted two most significant genes. Result: In this study two most significant genes based on their S/N ratios were selected. After selection of suitable training samples, the training and testing error were 0 and 7% respectively. Conclusion: We have shown that the use of two most significant genes based on their S/N ratios and selection of suitable training samples can lead to classify DLBCL patients with a rather good result. Actually with the aid of mentioned methods we could compensate lack of enough number of patients, improve accuracy of classifying and reduce complication of computations and so running time. PMID:23977654

  14. Density based pruning for identification of differentially expressed genes from microarray data

    PubMed Central

    2010-01-01

    Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning) is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO) with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune PMID:21047384

  15. A biomarker-based screen of a gene expression compendium ...

    EPA Pesticide Factsheets

    Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse liver. A gene expression biomarker of 48 genes which accurately predicted Nrf2 activation was used to identify factors which resulted in a gene expression profile with significant correlation to the biomarker. A number of novel insights were made. Chemicals that activated the xenosensor constitutive activated receptor (CAR) consistently activated Nrf2 across hundreds of profiles, possibly downstream of Cyp-induced increases in oxidative stress. Nrf2 activation was also found to be negatively regulated by the growth hormone (GH)- and androgen-regulated transcription factor STAT5b, a transcription factor suppressed by CAR. Nrf2 was activated when STAT5b was suppressed in female mice vs. male mice, after exposure to estrogens, or in genetic mutants in which GH signaling was disrupted. A subset of the mutants that show STAT5b suppression and Nrf2 activation result in increased resistance to environmental stressors and increased longevity. This study describes a novel approach for understanding the network of factors that regulate the Nrf2 pathway and highlights novel interactions between Nrf2, CAR and STAT5b transcription factors. (This abstract does not represent EPA policy.) Computational appr

  16. Modeling Gene Networks in Saccharomyces cerevisiae Based on Gene Expression Profiles.

    PubMed

    Zhang, Yulin; Lv, Kebo; Wang, Shudong; Su, Jionglong; Meng, Dazhi

    2015-01-01

    Detailed and innovative analysis of gene regulatory network structures may reveal novel insights to biological mechanisms. Here we study how gene regulatory network in Saccharomyces cerevisiae can differ under aerobic and anaerobic conditions. To achieve this, we discretized the gene expression profiles and calculated the self-entropy of down- and upregulation of gene expression as well as joint entropy. Based on these quantities the uncertainty coefficient was calculated for each gene triplet, following which, separate gene logic networks were constructed for the aerobic and anaerobic conditions. Four structural parameters such as average degree, average clustering coefficient, average shortest path, and average betweenness were used to compare the structure of the corresponding aerobic and anaerobic logic networks. Five genes were identified to be putative key components of the two energy metabolisms. Furthermore, community analysis using the Newman fast algorithm revealed two significant communities for the aerobic but only one for the anaerobic network. David Gene Functional Classification suggests that, under aerobic conditions, one such community reflects the cell cycle and cell replication, while the other one is linked to the mitochondrial respiratory chain function.

  17. Study of human dopamine sulfotransferases based on gene expression programming.

    PubMed

    Si, Hongzong; Zhao, Jiangang; Cui, Lianhua; Lian, Ning; Feng, Hanlin; Duan, Yun-Bo; Hu, Zhide

    2011-09-01

    A quantitative model is developed to predict the Km of 47 human dopamine sulfotransferases by gene expression programming. Each kind of compound is represented by several calculated structural descriptors of moment of inertia A, average electrophilic reactivity index for a C atom, relative number of triple bonds, RNCG relative negative charge, HA-dependent HDSA-1, and HBCA H-bonding charged surface area. Eight fitness functions of the gene expression programming method are used to find the best nonlinear model. The best quantitative model with squared standard error and square of correlation coefficient are 0.096 and 0.91 for training data set, and 0.102 and 0.88 for test set, respectively. It is shown that the gene expression programming-predicted results with fitness function are in good agreement with experimental ones.

  18. Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

    PubMed

    Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

    2016-06-01

    Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer.

  19. Synthetic RNA-based switches for mammalian gene expression control.

    PubMed

    Ausländer, Simon; Fussenegger, Martin

    2017-04-04

    Synthetic ribonucleic acid (RNA)-based gene switches control RNA functions in a ligand-responsive manner. Key building blocks are aptamers that specifically bind to small molecules or protein ligands. Engineering approaches often combine rational design and high-throughput screening to identify optimal connection sites or sequences. In this report, we discuss basic principles and emerging design strategies for the engineering of RNA-based gene switches in mammalian cells. Their small size compared with those of transcriptional gene switches, together with advancements in design strategies and performance, may bring RNA-based switches to the forefront of biomedical and biotechnological applications.

  20. Noise-based switches and amplifiers for gene expression

    PubMed Central

    Hasty, Jeff; Pradines, Joel; Dolnik, Milos; Collins, J. J.

    2000-01-01

    The regulation of cellular function is often controlled at the level of gene transcription. Such genetic regulation usually consists of interacting networks, whereby gene products from a single network can act to control their own expression or the production of protein in another network. Engineered control of cellular function through the design and manipulation of such networks lies within the constraints of current technology. Here we develop a model describing the regulation of gene expression and elucidate the effects of noise on the formulation. We consider a single network derived from bacteriophage λ and construct a two-parameter deterministic model describing the temporal evolution of the concentration of λ repressor protein. Bistability in the steady-state protein concentration arises naturally, and we show how the bistable regime is enhanced with the addition of the first operator site in the promotor region. We then show how additive and multiplicative external noise can be used to regulate expression. In the additive case, we demonstrate the utility of such control through the construction of a protein switch, whereby protein production is turned “on” and “off” by using short noise pulses. In the multiplicative case, we show that small deviations in the transcription rate can lead to large fluctuations in the production of protein, and we describe how these fluctuations can be used to amplify protein production significantly. These results suggest that an external noise source could be used as a switch and/or amplifier for gene expression. Such a development could have important implications for gene therapy. PMID:10681449

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

    PubMed Central

    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

  2. Automated target preparation for microarray-based gene expression analysis.

    PubMed

    Raymond, Frédéric; Metairon, Sylviane; Borner, Roland; Hofmann, Markus; Kussmann, Martin

    2006-09-15

    DNA microarrays have rapidly evolved toward a platform for massively paralleled gene expression analysis. Despite its widespread use, the technology has been criticized to be vulnerable to technical variability. Addressing this issue, recent comparative, interplatform, and interlaboratory studies have revealed that, given defined procedures for "wet lab" experiments and data processing, a satisfactory reproducibility and little experimental variability can be achieved. In view of these advances in standardization, the requirement for uniform sample preparation becomes evident, especially if a microarray platform is used as a facility, i.e., by different users working in the laboratory. While one option to reduce technical variability is to dedicate one laboratory technician to all microarray studies, we have decided to automate the entire RNA sample preparation implementing a liquid handling system coupled to a thermocycler and a microtiter plate reader. Indeed, automated RNA sample preparation prior to chip analysis enables (1) the reduction of experimentally caused result variability, (2) the separation of (important) biological variability from (undesired) experimental variation, and (3) interstudy comparison of gene expression results. Our robotic platform can process up to 24 samples in parallel, using an automated sample preparation method that produces high-quality biotin-labeled cRNA ready to be hybridized on Affymetrix GeneChips. The results show that the technical interexperiment variation is less pronounced than with manually prepared samples. Moreover, experiments using the same starting material showed that the automated process yields a good reproducibility between samples.

  3. Persistent gene expression in mouse nasal epithelia following feline immunodeficiency virus-based vector gene transfer.

    PubMed

    Sinn, Patrick L; Burnight, Erin R; Hickey, Melissa A; Blissard, Gary W; McCray, Paul B

    2005-10-01

    Gene transfer development for treatment or prevention of cystic fibrosis lung disease has been limited by the inability of vectors to efficiently and persistently transduce airway epithelia. Influenza A is an enveloped virus with natural lung tropism; however, pseudotyping feline immunodeficiency virus (FIV)-based lentiviral vector with the hemagglutinin envelope protein proved unsuccessful. Conversely, pseudotyping FIV with the envelope protein from influenza D (Thogoto virus GP75) resulted in titers of 10(6) transducing units (TU)/ml and conferred apical entry into well-differentiated human airway epithelial cells. Baculovirus GP64 envelope glycoproteins share sequence identity with influenza D GP75 envelope glycoproteins. Pseudotyping FIV with GP64 from three species of baculovirus resulted in titers of 10(7) to 10(9) TU/ml. Of note, GP64 from Autographa californica multicapsid nucleopolyhedrovirus resulted in high-titer FIV preparations (approximately 10(9) TU/ml) and conferred apical entry into polarized primary cultures of human airway epithelia. Using a luciferase reporter gene and bioluminescence imaging, we observed persistent gene expression from in vivo gene transfer in the mouse nose with A. californica GP64-pseudotyped FIV (AcGP64-FIV). Longitudinal bioluminescence analysis documented persistent expression in nasal epithelia for approximately 1 year without significant decline. According to histological analysis using a LacZ reporter gene, olfactory and respiratory epithelial cells were transduced. In addition, methylcellulose-formulated AcGP64-FIV transduced mouse nasal epithelia with much greater efficiency than similarly formulated vesicular stomatitis virus glycoprotein-pseudotyped FIV. These data suggest that AcGP64-FIV efficiently transduces and persistently expresses a transgene in nasal epithelia in the absence of agents that disrupt the cellular tight junction integrity.

  4. Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading

    PubMed Central

    Wang, Mei-Hui; Marinotti, Osvaldo; Zhong, Daibin; James, Anthony A.; Walker, Edward; Guda, Tom; Kweka, Eliningaya J.; Githure, John; Yan, Guiyun

    2013-01-01

    Information on population age structure of mosquitoes under natural conditions is fundamental to the understanding of vectorial capacity and crucial for assessing the impact of vector control measures on malaria transmission. Transcriptional profiling has been proposed as a method for predicting mosquito age for Aedes and Anopheles mosquitoes, however, whether this new method is adequate for natural conditions is unknown. This study tests the applicability of transcriptional profiling for age-grading of Anopheles gambiae, the most important malaria vector in Africa. The transcript abundance of two An. gambiae genes, AGAP009551 and AGAP011615, was measured during aging under laboratory and field conditions in three mosquito strains. Age-dependent monotonic changes in transcript levels were observed in all strains evaluated. These genes were validated as age-grading biomarkers using the mark, release and recapture (MRR) method. The MRR method determined a good correspondence between actual and predicted age, and thus demonstrated the value of age classifications derived from the transcriptional profiling of these two genes. The technique was used to establish the age structure of mosquito populations from two malaria-endemic areas in western Kenya. The population age structure determined by the transcriptional profiling method was consistent with that based on mosquito parity. This study demonstrates that the transcription profiling method based on two genes is valuable for age determination of natural mosquitoes, providing a new approach for determining a key life history trait of malaria vectors. PMID:23936017

  5. Detecting Essential Proteins Based on Network Topology, Gene Expression Data and Gene Ontology Information.

    PubMed

    Zhang, Wei; Xu, Jia; Li, Yuanyuan; Zou, Xiufen

    2016-10-07

    The identification of essential proteins in protein-protein interaction (PPI) networks is of great significance for understanding cellular processes. With the increasing availability of large-scale PPI data, numerous centrality measures based on network topology have been proposed to detect essential proteins from PPI networks. However, most of the current approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology annotation information. In this paper, we propose a novel centrality measure, called TEO, for identifying essential proteins by combining network topology, gene expression profiles and GO information. To evaluate the performance of the TEO method, we compare it with five other methods (degree, betweenness, NC, Pec, CowEWC) in detecting essential proteins from two different yeast PPI datasets. The simulation results show that adding GO information can effectively improve the predicted precision and that our method outperforms the others in predicting essential proteins.

  6. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes: implications for hepatic gene expression

    PubMed Central

    Ivanov, Maxim; Kals, Mart; Lauschke, Volker; Barragan, Isabel; Ewels, Philip; Käller, Max; Axelsson, Tomas; Lehtiö, Janne; Milani, Lili; Ingelman-Sundberg, Magnus

    2016-01-01

    To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene- and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications. PMID:27131363

  7. Design-Based Learning for Biology: Genetic Engineering Experience Improves Understanding of Gene Expression

    ERIC Educational Resources Information Center

    Ellefson, Michelle R.; Brinker, Rebecca A.; Vernacchio, Vincent J.; Schunn, Christian D.

    2008-01-01

    Gene expression is a difficult topic for students to learn and comprehend, at least partially because it involves various biochemical structures and processes occurring at the microscopic level. Designer Bacteria, a design-based learning (DBL) unit for high-school students, applies principles of DBL to the teaching of gene expression. Throughout…

  8. Evaluation and Validation of Reference Genes for Normalization of Quantitative Real-Time PCR Based Gene Expression Studies in Peanut

    PubMed Central

    Cindhuri, Katamreddy Sri; Sharma, Kiran K.

    2013-01-01

    The quantitative real-time PCR (qPCR) based techniques have become essential for gene expression studies and high-throughput molecular characterization of transgenic events. Normalizing to reference gene in relative quantification make results from qPCR more reliable when compared to absolute quantification, but requires robust reference genes. Since, ideal reference gene should be species specific, no single internal control gene is universal for use as a reference gene across various plant developmental stages and diverse growth conditions. Here, we present validation studies of multiple stably expressed reference genes in cultivated peanut with minimal variations in temporal and spatial expression when subjected to various biotic and abiotic stresses. Stability in the expression of eight candidate reference genes including ADH3, ACT11, ATPsyn, CYP2, ELF1B, G6PD, LEC and UBC1 was compared in diverse peanut plant samples. The samples were categorized into distinct experimental sets to check the suitability of candidate genes for accurate and reliable normalization of gene expression using qPCR. Stability in expression of the references genes in eight sets of samples was determined by geNorm and NormFinder methods. While three candidate reference genes including ADH3, G6PD and ELF1B were identified to be stably expressed across experiments, LEC was observed to be the least stable, and hence must be avoided for gene expression studies in peanut. Inclusion of the former two genes gave sufficiently reliable results; nonetheless, the addition of the third reference gene ELF1B may be potentially better in a diverse set of tissue samples of peanut. PMID:24167633

  9. Evaluation and validation of reference genes for normalization of quantitative real-time PCR based gene expression studies in peanut.

    PubMed

    Reddy, Dumbala Srinivas; Bhatnagar-Mathur, Pooja; Cindhuri, Katamreddy Sri; Sharma, Kiran K

    2013-01-01

    The quantitative real-time PCR (qPCR) based techniques have become essential for gene expression studies and high-throughput molecular characterization of transgenic events. Normalizing to reference gene in relative quantification make results from qPCR more reliable when compared to absolute quantification, but requires robust reference genes. Since, ideal reference gene should be species specific, no single internal control gene is universal for use as a reference gene across various plant developmental stages and diverse growth conditions. Here, we present validation studies of multiple stably expressed reference genes in cultivated peanut with minimal variations in temporal and spatial expression when subjected to various biotic and abiotic stresses. Stability in the expression of eight candidate reference genes including ADH3, ACT11, ATPsyn, CYP2, ELF1B, G6PD, LEC and UBC1 was compared in diverse peanut plant samples. The samples were categorized into distinct experimental sets to check the suitability of candidate genes for accurate and reliable normalization of gene expression using qPCR. Stability in expression of the references genes in eight sets of samples was determined by geNorm and NormFinder methods. While three candidate reference genes including ADH3, G6PD and ELF1B were identified to be stably expressed across experiments, LEC was observed to be the least stable, and hence must be avoided for gene expression studies in peanut. Inclusion of the former two genes gave sufficiently reliable results; nonetheless, the addition of the third reference gene ELF1B may be potentially better in a diverse set of tissue samples of peanut.

  10. dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

    PubMed Central

    Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

    2009-01-01

    Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

  11. Gene expression-based biomarkers for discriminating early and late stage of clear cell renal cancer

    PubMed Central

    Bhalla, Sherry; Chaudhary, Kumardeep; Kumar, Ritesh; Sehgal, Manika; Kaur, Harpreet; Sharma, Suresh; Raghava, Gajendra P. S.

    2017-01-01

    In this study, an attempt has been made to identify expression-based gene biomarkers that can discriminate early and late stage of clear cell renal cell carcinoma (ccRCC) patients. We have analyzed the gene expression of 523 samples to identify genes that are differentially expressed in the early and late stage of ccRCC. First, a threshold-based method has been developed, which attained a maximum accuracy of 71.12% with ROC 0.67 using single gene NR3C2. To improve the performance of threshold-based method, we combined two or more genes and achieved maximum accuracy of 70.19% with ROC of 0.74 using eight genes on the validation dataset. These eight genes include four underexpressed (NR3C2, ENAM, DNASE1L3, FRMPD2) and four overexpressed (PLEKHA9, MAP6D1, SMPD4, C11orf73) genes in the late stage of ccRCC. Second, models were developed using state-of-art techniques and achieved maximum accuracy of 72.64% and 0.81 ROC using 64 genes on validation dataset. Similar accuracy was obtained on 38 genes selected from subset of genes, involved in cancer hallmark biological processes. Our analysis further implied a need to develop gender-specific models for stage classification. A web server, CancerCSP, has been developed to predict stage of ccRCC using gene expression data derived from RNAseq experiments. PMID:28349958

  12. Identification of hub genes and pathways associated with retinoblastoma based on co-expression network analysis.

    PubMed

    Wang, Q L; Chen, X; Zhang, M H; Shen, Q H; Qin, Z M

    2015-12-08

    The objective of this paper was to identify hub genes and pathways associated with retinoblastoma using centrality analysis of the co-expression network and pathway-enrichment analysis. The co-expression network of retinoblastoma was constructed by weighted gene co-expression network analysis (WGCNA) based on differentially expressed (DE) genes, and clusters were obtained through the molecular complex detection (MCODE) algorithm. Degree centrality analysis of the co-expression network was performed to explore hub genes present in retinoblastoma. Pathway-enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Validation of hub gene expression in retinoblastoma was performed by reverse transcription-polymerase chain reaction (RT-PCR) analysis. The co-expression network based on 221 DE genes between retinoblastoma and normal controls consisted of 210 nodes and 3965 edges, and 5 clusters of the network were evaluated. By assessing the centrality analysis of the co-expression network, 21 hub genes were identified, such as SNORD115-41, RASSF2, and SNORD115-44. According to RT-PCR analysis, 16 of the 21 hub genes were differently expressed, including RASSF2 and CDCA7, and 5 were not differently expressed in retinoblastoma compared to normal controls. Pathway analysis showed that genes in 2 clusters were enriched in 3 pathways: purine metabolism, p53 signaling pathway, and melanogenesis. In this study, we successfully identified 16 hub genes and 3 pathways associated with retinoblastoma, which may be potential biomarkers for early detection and therapy for retinoblastoma.

  13. Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile.

    PubMed

    Long, Jin; Liu, Zhe; Wu, Xingda; Xu, Yuanhong; Ge, Chunlin

    2016-05-01

    The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

  14. Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity

    PubMed Central

    Kamath, Vidya P.; Torres-Roca, Javier F.

    2017-01-01

    The use of gene expression-based classifiers has resulted in a number of promising potential signatures of patient diagnosis, prognosis, and response to therapy. However, these approaches have also created difficulties in trying to use gene expression alone to predict a complex trait. A practical approach to this problem is to integrate existing biological knowledge with gene expression to build a composite predictor. We studied the problem of predicting radiation sensitivity within human cancer cell lines from gene expression. First, we present evidence for the need to integrate known biological conditions (tissue of origin, RAS, and p53 mutational status) into a gene expression prediction problem involving radiation sensitivity. Next, we demonstrate using linear regression, a technique for incorporating this knowledge. The resulting correlations between gene expression and radiation sensitivity improved through the use of this technique (best-fit adjusted R2 increased from 0.3 to 0.84). Overfitting of data was examined through the use of simulation. The results reinforce the concept that radiation sensitivity is not driven solely by gene expression, but rather by a combination of distinct parameters. We show that accounting for biological heterogeneity significantly improves the ability of the model to identify genes that are associated with radiosensitivity.

  15. Localization of the modified base J in telomeric VSG gene expression sites of Trypanosoma brucei.

    PubMed

    van Leeuwen, F; Wijsman, E R; Kieft, R; van der Marel, G A; van Boom, J H; Borst, P

    1997-12-01

    African trypanosomes such as Trypanosoma brucei undergo antigenic variation in the bloodstream of their mammalian hosts by regularly changing the variant surface glycoprotein (VSG) gene expressed. The transcribed VSG gene is invariably located in a telomeric expression site. There are multiple expression sites and one way to change the VSG gene expressed is by activating a new site and inactivating the previously active one. The mechanisms that control expression site switching are unknown, but have been suggested to involve epigenetic regulation. We have found previously that VSG genes in silent (but not active) expression sites contain modified restriction endonuclease cleavage sites, and we have presented circumstantial evidence indicating that this is attributable to the presence of a novel modified base beta-D-glucosyl-hydroxymethyluracil, or J. To directly test this, we have generated antisera that specifically recognize J-containing DNA and have used these to determine the precise location of this modified thymine in the telomeric VSG expression sites. By anti J-DNA immunoprecipitations, we found that J is present in telomeric VSG genes in silenced expression sites and not in actively transcribed telomeric VSG genes. J was absent from inactive chromosome-internal VSG genes. DNA modification was also found at the boundaries of expression sites. In the long 50-bp repeat arrays upstream of the promoter and in the telomeric repeat arrays downstream of the VSG gene, J was found both in silent and active expression sites. This suggests that silencing results in a gradient of modification spreading from repetitive DNA flanks into the neighboring expression site sequences. In this paper, we discuss the possible role of J in silencing of expression sites.

  16. Prediction of highly expressed genes in microbes based on chromatin accessibility

    PubMed Central

    Willenbrock, Hanni; Ussery, David W

    2007-01-01

    Background It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI) values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes. Results We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes. Conclusion This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches. PMID:17295928

  17. GeneShelf: a web-based visual interface for large gene expression time-series data repositories.

    PubMed

    Kim, Bohyoung; Lee, Bongshin; Knoblach, Susan; Hoffman, Eric; Seo, Jinwook

    2009-01-01

    A widespread use of high-throughput gene expression analysis techniques enabled the biomedical research community to share a huge body of gene expression datasets in many public databases on the web. However, current gene expression data repositories provide static representations of the data and support limited interactions. This hinders biologists from effectively exploring shared gene expression datasets. Responding to the growing need for better interfaces to improve the utility of the public datasets, we have designed and developed a new web-based visual interface entitled GeneShelf (http://bioinformatics.cnmcresearch.org/GeneShelf). It builds upon a zoomable grid display to represent two categorical dimensions. It also incorporates an augmented timeline with expandable time points that better shows multiple data values for the focused time point by embedding bar charts. We applied GeneShelf to one of the largest microarray datasets generated to study the progression and recovery process of injuries at the spinal cord of mice and rats. We present a case study and a preliminary qualitative user study with biologists to show the utility and usability of GeneShelf.

  18. Gene Expression Signature-Based Screening Identifies New Broadly Effective Influenza A Antivirals

    PubMed Central

    Josset, Laurence; Textoris, Julien; Loriod, Béatrice; Ferraris, Olivier; Moules, Vincent; Lina, Bruno; N'Guyen, Catherine; Diaz, Jean-Jacques; Rosa-Calatrava, Manuel

    2010-01-01

    Classical antiviral therapies target viral proteins and are consequently subject to resistance. To counteract this limitation, alternative strategies have been developed that target cellular factors. We hypothesized that such an approach could also be useful to identify broad-spectrum antivirals. The influenza A virus was used as a model for its viral diversity and because of the need to develop therapies against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection by different influenza A virus subtypes which would allow the identification of potential antiviral drugs with a broad anti-influenza spectrum of activity. We analyzed the cellular gene expression response to infection with five different human and avian influenza A virus strains and identified 300 genes as differentially expressed between infected and non-infected samples. The most 20 dysregulated genes were used to screen the connectivity map, a database of drug-associated gene expression profiles. Candidate antivirals were then identified by their inverse correlation to the query signature. We hypothesized that such molecules would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified and their effects were tested in vitro on five influenza A strains. Six of the molecules inhibited influenza viral growth. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five out of the eight identified molecules, demonstrating that this strategy could contribute to identifying new broad anti-influenza agents acting on cellular gene expression. The identified infection signature genes, the expression of which are modified upon infection, could encode cellular proteins involved in the viral life cycle. This is the first study showing that gene expression-based screening can be

  19. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures

    PubMed Central

    Zhang, Hang; Xie, Ziyang; Yang, Yuwen; Zhao, Yizhen

    2017-01-01

    Microarray analysis of gene expression is often used to diagnose different types of disease. Many studies report remarkable achievements in nervous system disease. Clinical diagnosis of schizophrenia (SCZ) still depends on doctors' experience, which is unreliable and needs to be more objective and quantified. To solve this problem, we collected whole blood gene expression data from four studies, including 152 individuals with schizophrenia (SCZ) and 138 normal controls in different regions. The correlation-based feature selection (CFS, one of the machine learning methods) algorithm was applied in this study, and 103 significantly differentially expressed genes between patients and controls, called “feature genes,” were selected; then, a model for SCZ diagnosis was built. The samples were subdivided into 10 groups, and cross-validation showed that the model we constructed achieved nearly 100% classification accuracy. Mathematical evaluation of the datasets before and after data processing proved the effectiveness of our algorithm. Feature genes were enriched in Parkinson's disease, oxidative phosphorylation, and TGF-beta signaling pathways, which were previously reported to be associated with SCZ. These results suggest that the analysis of gene expression in whole blood by our model could be a useful tool for diagnosing SCZ. PMID:28280741

  20. Hessian regularization based non-negative matrix factorization for gene expression data clustering.

    PubMed

    Liu, Xiao; Shi, Jun; Wang, Congzhi

    2015-01-01

    Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method with great success in machine learning. Although the traditional manifold regularization method, Laplacian regularization (LR), can improve the performance of NMF, LR still suffers from the problem of its weak extrapolating power. Hessian regularization (HR) is a newly developed manifold regularization method, whose natural properties make it more extrapolating, especially for small sample data. In this work, we propose the HR-based NMF (HR-NMF) algorithm, and then apply it to represent gene expression data for further clustering task. The clustering experiments are conducted on five commonly used gene datasets, and the results indicate that the proposed HR-NMF outperforms LR-based NMM and original NMF, which suggests the potential application of HR-NMF for gene expression data.

  1. Knowledge-based analysis of microarray gene expression data by using support vector machines

    SciTech Connect

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

    The authors introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. They test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, they use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

  2. Expression of Human Skin-Specific Genes Defined by Transcriptomics and Antibody-Based Profiling

    PubMed Central

    Edqvist, Per-Henrik D.; Fagerberg, Linn; Hallström, Björn M.; Danielsson, Angelika; Edlund, Karolina; Uhlén, Mathias

    2014-01-01

    To increase our understanding of skin, it is important to define the molecular constituents of the cell types and epidermal layers that signify normal skin. We have combined a genome-wide transcriptomics analysis, using deep sequencing of mRNA from skin biopsies, with immunohistochemistry-based protein profiling to characterize the landscape of gene and protein expression in normal human skin. The transcriptomics and protein expression data of skin were compared to 26 (RNA) and 44 (protein) other normal tissue types. All 20,050 putative protein-coding genes were classified into categories based on patterns of expression. We found that 417 genes showed elevated expression in skin, with 106 genes expressed at least five-fold higher than that in other tissues. The 106 genes categorized as skin enriched encoded for well-known proteins involved in epidermal differentiation and proteins with unknown functions and expression patterns in skin, including the C1orf68 protein, which showed the highest relative enrichment in skin. In conclusion, we have applied a genome-wide analysis to identify the human skin-specific proteome and map the precise localization of the corresponding proteins in different compartments of the skin, to facilitate further functional studies to explore the molecular repertoire of normal skin and to identify biomarkers related to various skin diseases. PMID:25411189

  3. Accurate Gene Expression-Based Biodosimetry Using a Minimal Set of Human Gene Transcripts

    SciTech Connect

    Tucker, James D.; Joiner, Michael C.; Thomas, Robert A.; Grever, William E.; Bakhmutsky, Marina V.; Chinkhota, Chantelle N.; Smolinski, Joseph M.; Divine, George W.; Auner, Gregory W.

    2014-03-15

    Purpose: Rapid and reliable methods for conducting biological dosimetry are a necessity in the event of a large-scale nuclear event. Conventional biodosimetry methods lack the speed, portability, ease of use, and low cost required for triaging numerous victims. Here we address this need by showing that polymerase chain reaction (PCR) on a small number of gene transcripts can provide accurate and rapid dosimetry. The low cost and relative ease of PCR compared with existing dosimetry methods suggest that this approach may be useful in mass-casualty triage situations. Methods and Materials: Human peripheral blood from 60 adult donors was acutely exposed to cobalt-60 gamma rays at doses of 0 (control) to 10 Gy. mRNA expression levels of 121 selected genes were obtained 0.5, 1, and 2 days after exposure by reverse-transcriptase real-time PCR. Optimal dosimetry at each time point was obtained by stepwise regression of dose received against individual gene transcript expression levels. Results: Only 3 to 4 different gene transcripts, ASTN2, CDKN1A, GDF15, and ATM, are needed to explain ≥0.87 of the variance (R{sup 2}). Receiver-operator characteristics, a measure of sensitivity and specificity, of 0.98 for these statistical models were achieved at each time point. Conclusions: The actual and predicted radiation doses agree very closely up to 6 Gy. Dosimetry at 8 and 10 Gy shows some effect of saturation, thereby slightly diminishing the ability to quantify higher exposures. Analyses of these gene transcripts may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations or in clinical radiation emergencies.

  4. Allen Brain Atlas-Driven Visualizations: a web-based gene expression energy visualization tool.

    PubMed

    Zaldivar, Andrew; Krichmar, Jeffrey L

    2014-01-01

    The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

  5. Weighted gene co-expression based biomarker discovery for psoriasis detection.

    PubMed

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-11-15

    Psoriasis is a chronic inflammatory disease of the skin with an unknown aetiology. The disease manifests itself as red and silvery scaly plaques distributed over the scalp, lower back and extensor aspects of the limbs. After receiving scant consideration for quite a few years, psoriasis has now become a prominent focus for new drug development. A group of closely connected and differentially co-expressed genes may act in a network and may serve as molecular signatures for an underlying phenotype. A weighted gene coexpression network analysis (WGCNA), a system biology approach has been utilized for identification of new molecular targets for psoriasis. Gene coexpression relationships were investigated in 58 psoriatic lesional samples resulting in five gene modules, clustered based on the gene coexpression patterns. The coexpression pattern was validated using three psoriatic datasets. 10 highly connected and informative genes from each module was selected and termed as psoriasis specific hub signatures. A random forest based binary classifier built using the expression profiles of signature genes robustly distinguished psoriatic samples from the normal samples in the validation set with an accuracy of 0.95 to 1. These signature genes may serve as potential candidates for biomarker discovery leading to new therapeutic targets. WGCNA, the network based approach has provided an alternative path to mine out key controllers and drivers of psoriasis. The study principle from the current work can be extended to other pathological conditions.

  6. A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

    PubMed Central

    Hang, Bo; Zou, Xiaoping; Mao, Jian-Hua

    2016-01-01

    Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A network was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system. PMID:27419373

  7. Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data

    PubMed Central

    Wang, Haiying; Zheng, Huiru; Simpson, David; Azuaje, Francisco

    2006-01-01

    Background Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data. Results Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE), this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model) performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re-sampling techniques were

  8. WF-MSB: a weighted fuzzy-based biclustering method for gene expression data.

    PubMed

    Chen, Lien-Chin; Yu, Philip S; Tseng, Vincent S

    2011-01-01

    Biclustering is an important analysis method on gene expression data for finding a subset of genes sharing compatible expression patterns. Although some biclustering algorithms have been proposed, few provided a query-driven approach for biologists to search the biclusters, which contain a certain gene of interest. In this paper, we proposed a generalised fuzzy-based approach, namely Weighted Fuzzy-based Maximum Similarity Biclustering (WF-MSB), for extracting a query-driven bicluster based on the user-defined reference gene. A fuzzy-based similarity measurement and condition weighting approach are used to extract significant biclusters in expression levels. Both of the most similar bicluster and the most dissimilar bicluster to the reference gene are discovered by WF-MSB. The proposed WF-MSB method was evaluated in comparison with MSBE on a real yeast microarray data and synthetic data sets. The experimental results show that WF-MSB can effectively find the biclusters with significant GO-based functional meanings.

  9. Integrating biological knowledge based on functional annotations for biclustering of gene expression data.

    PubMed

    Nepomuceno, Juan A; Troncoso, Alicia; Nepomuceno-Chamorro, Isabel A; Aguilar-Ruiz, Jesús S

    2015-05-01

    Gene expression data analysis is based on the assumption that co-expressed genes imply co-regulated genes. This assumption is being reformulated because the co-expression of a group of genes may be the result of an independent activation with respect to the same experimental condition and not due to the same regulatory regime. For this reason, traditional techniques are recently being improved with the use of prior biological knowledge from open-access repositories together with gene expression data. Biclustering is an unsupervised machine learning technique that searches patterns in gene expression data matrices. A scatter search-based biclustering algorithm that integrates biological information is proposed in this paper. In addition to the gene expression data matrix, the input of the algorithm is only a direct annotation file that relates each gene to a set of terms from a biological repository where genes are annotated. Two different biological measures, FracGO and SimNTO, are proposed to integrate this information by means of its addition to-be-optimized fitness function in the scatter search scheme. The measure FracGO is based on the biological enrichment and SimNTO is based on the overlapping among GO annotations of pairs of genes. Experimental results evaluate the proposed algorithm for two datasets and show the algorithm performs better when biological knowledge is integrated. Moreover, the analysis and comparison between the two different biological measures is presented and it is concluded that the differences depend on both the data source and how the annotation file has been built in the case GO is used. It is also shown that the proposed algorithm obtains a greater number of enriched biclusters than other classical biclustering algorithms typically used as benchmark and an analysis of the overlapping among biclusters reveals that the biclusters obtained present a low overlapping. The proposed methodology is a general-purpose algorithm which allows

  10. A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer’s Disease Diagnosis

    PubMed Central

    Voyle, Nicola; Keohane, Aoife; Newhouse, Stephen; Lunnon, Katie; Johnston, Caroline; Soininen, Hilkka; Kloszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon; Hodges, Angela; Kiddle, Steven; Dobson, Richard JB.

    2015-01-01

    Background: Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer’s disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust. Objectives: This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts. Methods: Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis. Results: Gene and pathway level models performed similarly to each other and to a model based on demographic information only. Conclusions: Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach. PMID:26484910

  11. A stationary wavelet entropy-based clustering approach accurately predicts gene expression.

    PubMed

    Nguyen, Nha; Vo, An; Choi, Inchan; Won, Kyoung-Jae

    2015-03-01

    Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation.

  12. Genomic DNA-based absolute quantification of gene expression in Vitis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Many studies in which gene expression is quantified by polymerase chain reaction represent the expression of a gene of interest (GOI) relative to that of a reference gene (RG). Relative expression is founded on the assumptions that RG expression is stable across samples, treatments, organs, etc., an...

  13. QSAR study of 1,4-dihydropyridine calcium channel antagonists based on gene expression programming.

    PubMed

    Si, Hong Zong; Wang, Tao; Zhang, Ke Jun; Hu, Zhi De; Fan, Bo Tao

    2006-07-15

    The gene expression programming, a novel machine learning algorithm, is used to develop quantitative model as a potential screening mechanism for a series of 1,4-dihydropyridine calcium channel antagonists for the first time. The heuristic method was used to search the descriptor space and select the descriptors responsible for activity. A nonlinear, six-descriptor model based on gene expression programming with mean-square errors 0.19 was set up with a predicted correlation coefficient (R2) 0.92. This paper provides a new and effective method for drug design and screening.

  14. A method for multiplex gene synthesis employing error correction based on expression.

    PubMed

    Hsiau, Timothy H-C; Sukovich, David; Elms, Phillip; Prince, Robin N; Strittmatter, Tobias; Stritmatter, Tobias; Ruan, Paul; Curry, Bo; Anderson, Paige; Sampson, Jeff; Anderson, J Christopher

    2015-01-01

    Our ability to engineer organisms with new biosynthetic pathways and genetic circuits is limited by the availability of protein characterization data and the cost of synthetic DNA. With new tools for reading and writing DNA, there are opportunities for scalable assays that more efficiently and cost effectively mine for biochemical protein characteristics. To that end, we have developed the Multiplex Library Synthesis and Expression Correction (MuLSEC) method for rapid assembly, error correction, and expression characterization of many genes as a pooled library. This methodology enables gene synthesis from microarray-synthesized oligonucleotide pools with a one-pot technique, eliminating the need for robotic liquid handling. Post assembly, the gene library is subjected to an ampicillin based quality control selection, which serves as both an error correction step and a selection for proteins that are properly expressed and folded in E. coli. Next generation sequencing of post selection DNA enables quantitative analysis of gene expression characteristics. We demonstrate the feasibility of this approach by building and testing over 90 genes for empirical evidence of soluble expression. This technique reduces the problem of part characterization to multiplex oligonucleotide synthesis and deep sequencing, two technologies under extensive development with projected cost reduction.

  15. Identification and expression of cuticular protein genes based on Locusta migratoria transcriptome

    PubMed Central

    Zhao, Xiaoming; Gou, Xin; Qin, Zhongyu; Li, Daqi; Wang, Yan; Ma, Enbo; Li, Sheng; Zhang, Jianzhen

    2017-01-01

    Many types of cuticular proteins are found in a single insect species, and their number and features are very diversified among insects. The cuticle matrix consists of many different proteins that confer the physical properties of the exoskeleton. However, the number and properties of cuticle proteins in Locusta migratoria remain unclear. In the present study, Illumina sequencing and de novo assembly were combined to characterize the transcriptome of L. migratoria. Eighty-one cuticular protein genes were identified and divided into five groups: the CPR family (51), Tweedle (2), CPF/CPFLs (9), CPAP family (9), and other genes (10). Based on the expression patterns in different tissues and stages, most of the genes as a test were distributed in the integument, pronotum and wings, and expressed in selected stages with different patterns. The results showed no obvious correlation between the expression patterns and the conservative motifs. Additionally, each cluster displayed a different expression pattern that may possess a different function in the cuticle. Furthermore, the complexity of the large variety of genes displayed differential expression during the molting cycle may be associated with cuticle formation and may provide insights into the gene networks related to cuticle formation. PMID:28368027

  16. Transcriptome based identification and tissue expression profiles of chemosensory genes in Blattella germanica (Blattaria: Blattidae).

    PubMed

    Niu, Dong-Juan; Liu, Yan; Dong, Xiao-Tong; Dong, Shuang-Lin

    2016-06-01

    Blattalla germanica is one of the most notorious household insect pests, and evolutionally more primitive than those well studied moths and flies, regarding the molecular mechanisms of chemosensation. In this study, we sequenced, for the first time, the antennal transcriptome of B. germanica using the Illumina HiSeq™ 2000 platform and then conducted the bioinformatic analysis of the data. In total, we identified 73 putative chemosensory genes, with 62 genes being novel in this species. These chemosensory genes included 48 odorant binding proteins (OBPs), 9 chemosensory proteins (CSPs), 6 sensory neuron membrane proteins (SNMPs), 5 odorant receptors (ORs) and 5 ionotropic receptors (IRs). Notably, Plus-C OBPs account for an exceptionally high proportion (39.58%) of the total 48 OBPs in this primitive insect. To predict the chemosensory functions of the genes, a detailed global tissue expression profiling was investigated by reverse transcription polymerase chain reaction (RT-PCR). Most OBP genes showed a chemosensory tissue biased profile, while CSP transcripts were widely and evenly expressed in different tissues. Furthermore, we found that more than half the chemosensory genes were expressed in the cerci, implying the important chemosensory functions of the organ in B. germanica. Taken together, our study provides important bases for elucidation of the molecular mechanisms and evolution of insect chemosensation, and for development of the chemosensation based techniques to control B. germanica.

  17. Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

    NASA Astrophysics Data System (ADS)

    Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

    2009-02-01

    Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

  18. Biclustering of Gene Expression Data by Correlation-Based Scatter Search

    PubMed Central

    2011-01-01

    Background The analysis of data generated by microarray technology is very useful to understand how the genetic information becomes functional gene products. Biclustering algorithms can determine a group of genes which are co-expressed under a set of experimental conditions. Recently, new biclustering methods based on metaheuristics have been proposed. Most of them use the Mean Squared Residue as merit function but interesting and relevant patterns from a biological point of view such as shifting and scaling patterns may not be detected using this measure. However, it is important to discover this type of patterns since commonly the genes can present a similar behavior although their expression levels vary in different ranges or magnitudes. Methods Scatter Search is an evolutionary technique that is based on the evolution of a small set of solutions which are chosen according to quality and diversity criteria. This paper presents a Scatter Search with the aim of finding biclusters from gene expression data. In this algorithm the proposed fitness function is based on the linear correlation among genes to detect shifting and scaling patterns from genes and an improvement method is included in order to select just positively correlated genes. Results The proposed algorithm has been tested with three real data sets such as Yeast Cell Cycle dataset, human B-cells lymphoma dataset and Yeast Stress dataset, finding a remarkable number of biclusters with shifting and scaling patterns. In addition, the performance of the proposed method and fitness function are compared to that of CC, OPSM, ISA, BiMax, xMotifs and Samba using Gene the Ontology Database. PMID:21261986

  19. Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

    PubMed Central

    2012-01-01

    Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process. PMID:23256600

  20. Monoterpenoid-based preparations in beehives affect learning, memory, and gene expression in the bee brain.

    PubMed

    Bonnafé, Elsa; Alayrangues, Julie; Hotier, Lucie; Massou, Isabelle; Renom, Allan; Souesme, Guillaume; Marty, Pierre; Allaoua, Marion; Treilhou, Michel; Armengaud, Catherine

    2017-02-01

    Bees are exposed in their environment to contaminants that can weaken the colony and contribute to bee declines. Monoterpenoid-based preparations can be introduced into hives to control the parasitic mite Varroa destructor. The long-term effects of monoterpenoids are poorly investigated. Olfactory conditioning of the proboscis extension reflex (PER) has been used to evaluate the impact of stressors on cognitive functions of the honeybee such as learning and memory. The authors tested the PER to odorants on bees after exposure to monoterpenoids in hives. Octopamine receptors, transient receptor potential-like (TRPL), and γ-aminobutyric acid channels are thought to play a critical role in the memory of food experience. Gene expression levels of Amoa1, Rdl, and trpl were evaluated in parallel in the bee brain because these genes code for the cellular targets of monoterpenoids and some pesticides and neural circuits of memory require their expression. The miticide impaired the PER to odors in the 3 wk following treatment. Short-term and long-term olfactory memories were improved months after introduction of the monoterpenoids into the beehives. Chronic exposure to the miticide had significant effects on Amoa1, Rdl, and trpl gene expressions and modified seasonal changes in the expression of these genes in the brain. The decrease of expression of these genes in winter could partly explain the improvement of memory. The present study has led to new insights into alternative treatments, especially on their effects on memory and expression of selected genes involved in this cognitive function. Environ Toxicol Chem 2017;36:337-345. © 2016 SETAC.

  1. Predicting Autism Spectrum Disorder Using Blood-based Gene Expression Signatures and Machine Learning

    PubMed Central

    Oh, Dong Hoon; Kim, Il Bin; Kim, Seok Hyeon; Ahn, Dong Hyun

    2017-01-01

    Objective The aim of this study was to identify a transcriptomic signature that could be used to classify subjects with autism spectrum disorder (ASD) compared to controls on the basis of blood gene expression profiles. The gene expression profiles could ultimately be used as diagnostic biomarkers for ASD. Methods We used the published microarray data (GSE26415) from the Gene Expression Omnibus database, which included 21 young adults with ASD and 21 age- and sex-matched unaffected controls. Nineteen differentially expressed probes were identified from a training dataset (n=26, 13 ASD cases and 13 controls) using the limma package in R language (adjusted p value <0.05) and were further analyzed in a test dataset (n=16, 8 ASD cases and 8 controls) using machine learning algorithms. Results Hierarchical cluster analysis showed that subjects with ASD were relatively well-discriminated from controls. Based on the support vector machine and K-nearest neighbors analysis, validation of 19-DE probes with a test dataset resulted in an overall class prediction accuracy of 93.8% as well as a sensitivity and specificity of 100% and 87.5%, respectively. Conclusion The results of our exploratory study suggest that the gene expression profiles identified from the peripheral blood samples of young adults with ASD can be used to identify a biological signature for ASD. Further study using a larger cohort and more homogeneous datasets is required to improve the diagnostic accuracy. PMID:28138110

  2. Two novel gene expression systems based on the yeasts Schwanniomyces occidentalis and Pichia stipitis.

    PubMed

    Piontek, M; Hagedorn, J; Hollenberg, C P; Gellissen, G; Strasser, A W

    1998-09-01

    Two non-Saccharomyces yeasts have been developed as hosts for heterologous gene expression. The celD gene from Clostridium thermocellum, encoding a heat-stable cellulase, served as the test sequence. The first system is based on the amylolytic species Schwanniomyces occidentalis, the second on the xylolytic species Pichia stipitis. The systems comprise auxotrophic host strains (trp5 in the case of S. occidentalis; trp5-10, his3 in the case of P. stipitis) and suitable transformation vectors. Vector components consist of an S. occidentalis-derived autonomously replicating sequence (SwARS) and the Saccharomyces cerevisiae-derived TRP5 sequence for plasmid propagation and selection in the yeast hosts, an ori and an ampicillin-resistance sequence for propagation and selection in a bacterial host. A range of vectors has been engineered employing different promoter elements for heterologous gene expression control in both species. Homologous elements derived from highly expressed genes of the respective hosts appeared to be of superior quality: in the case of S. occidentalis that of the GAM1 gene, in the case of P. stipitis that of the XYL1 gene. Further elements tested are the S. cerevisiae-derived ADH1 and PDC1 promoter sequences.

  3. Microarray Based Gene Expression Analysis of Murine Brown and Subcutaneous Adipose Tissue: Significance with Human

    PubMed Central

    Boparai, Ravneet K.; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Background Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. Methodology/Principle Findings The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Conclusion Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose

  4. Gene expression-based classifications of fibroadenomas and phyllodes tumours of the breast.

    PubMed

    Vidal, Maria; Peg, Vicente; Galván, Patricia; Tres, Alejandro; Cortés, Javier; Ramón y Cajal, Santiago; Rubio, Isabel T; Prat, Aleix

    2015-06-01

    using gene expression-based data is feasible and might provide clinically useful biological and prognostic information.

  5. Gene expression-based prognostic signatures in lung cancer: ready for clinical use?

    PubMed

    Subramanian, Jyothi; Simon, Richard

    2010-04-07

    A substantial number of studies have reported the development of gene expression-based prognostic signatures for lung cancer. The ultimate aim of such studies should be the development of well-validated clinically useful prognostic signatures that improve therapeutic decision making beyond current practice standards. We critically reviewed published studies reporting the development of gene expression-based prognostic signatures for non-small cell lung cancer to assess the progress made toward this objective. Studies published between January 1, 2002, and February 28, 2009, were identified through a PubMed search. Following hand-screening of abstracts of the identified articles, 16 were selected as relevant. Those publications were evaluated in detail for appropriateness of the study design, statistical validation of the prognostic signature on independent datasets, presentation of results in an unbiased manner, and demonstration of medical utility for the new signature beyond that obtained using existing treatment guidelines. Based on this review, we found little evidence that any of the reported gene expression signatures are ready for clinical application. We also found serious problems in the design and analysis of many of the studies. We suggest a set of guidelines to aid the design, analysis, and evaluation of prognostic signature studies. These guidelines emphasize the importance of focused study planning to address specific medically important questions and the use of unbiased analysis methods to evaluate whether the resulting signatures provide evidence of medical utility beyond standard of care-based prognostic factors.

  6. The distribution-based p-value for the outlier sum in differential gene expression analysis.

    PubMed

    Chen, Lin-An; Chen, Dung-Tsa; Chan, Wenyaw

    2010-03-01

    Outlier sums were proposed by Tibshirani & Hastie (2007) and Wu (2007) for detecting outlier genes where only a small subset of disease samples shows unusually high gene expression, but they did not develop their distributional properties and formal statistical inference. In this study, a new outlier sum for detection of outlier genes is proposed, its asymptotic distribution theory is developed, and the p-value based on this outlier sum is formulated. Its analytic form is derived on the basis of the large-sample theory. We compare the proposed method with existing outlier sum methods by power comparisons. Our method is applied to DNA microarray data from samples of primary breast tumors examined by Huang et al. (2003). The results show that the proposed method is more efficient in detecting outlier genes.

  7. Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures

    PubMed Central

    Welsh, Eric A.

    2017-01-01

    Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA) can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified. PMID:28265563

  8. An EST-based analysis identifies new genes and reveals distinctive gene expression features of Coffea arabica and Coffea canephora

    PubMed Central

    2011-01-01

    Background Coffee is one of the world's most important crops; it is consumed worldwide and plays a significant role in the economy of producing countries. Coffea arabica and C. canephora are responsible for 70 and 30% of commercial production, respectively. C. arabica is an allotetraploid from a recent hybridization of the diploid species, C. canephora and C. eugenioides. C. arabica has lower genetic diversity and results in a higher quality beverage than C. canephora. Research initiatives have been launched to produce genomic and transcriptomic data about Coffea spp. as a strategy to improve breeding efficiency. Results Assembling the expressed sequence tags (ESTs) of C. arabica and C. canephora produced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters of C. arabica and 16,665 clusters of C. canephora. We detected different GC3 profiles between these species that are related to their genome structure and mating system. BLAST analysis revealed similarities between coffee and grape (Vitis vinifera) genes. Using KA/KS analysis, we identified coffee genes under purifying and positive selection. Protein domain and gene ontology analyses suggested differences between Coffea spp. data, mainly in relation to complex sugar synthases and nucleotide binding proteins. OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species. Among the interesting families annotated are new cystatins, glycine-rich proteins and RALF-like peptides. Hierarchical clustering was used to independently group C. arabica and C. canephora expression clusters according to expression data extracted from EST libraries, resulting in the identification of differentially expressed genes. Based on these results, we emphasize gene annotation and discuss plant defenses, abiotic stress and cup quality-related functional categories. Conclusion We present the first comprehensive genome-wide transcript

  9. Outcome-based profiling of astrocytic tumours identifies prognostic gene expression signatures which link molecular and morphology-based pathology.

    PubMed

    Beetz, Christian; Bergner, Sven; Brodoehl, Stefan; Brodhun, Michael; Ewald, Christian; Kalff, Rolf; Krüger, Jutta; Patt, Stephan; Kiehntopf, Michael; Deufel, Thomas

    2006-11-01

    Astrocytomas are intracranial malignancies for which invasive growth and high motility of tumour cells preclude total resection; the tumours usually recur in a more aggressive and, eventually, lethal form. Clinical outcome is highly variable and the accuracy of morphology-based prognostic statements is limited. In order to identify novel molecular markers for prognosis we obtained expression profiles of: i) tumours associated with particularly long recurrence-free intervals, ii) tumours which led to rapid patient death, and iii) tumour-free control brain. Unsupervised data analysis completely separated the three sample entities indicating a strong impact of the selection criteria on general gene expression. Consequently, significant numbers of specifically expressed genes could be identified for each entity. An extended set of tumours was then investigated by RT-PCR targeting 12 selected genes. Data from these experiments were summarised into a sample-specific index which assigns tumours to high- and low-risk groups as successfully as does morphology-based grading. Moreover, this index directly correlates with definite survival suggesting that integrated gene expression data allow individualised prognostic statements. We also analysed localisation of selected marker transcripts by in situ hybridization. Our finding of cell-specificity for some of these outcome-determining genes relates global expression data to the presence of morphological correlates of tumour behaviour and, thus, provides a link between morphology-based and molecular pathology. Our identification of expression signatures that are associated individually with clinical outcome confirms the prognostic relevance of gene expression data and, thus, represents a step towards eventually implementing molecular diagnosis into clinical practice in neuro-oncology.

  10. Anticancer drug clustering in lung cancer based on gene expression profiles and sensitivity database

    PubMed Central

    Gemma, Akihiko; Li, Cai; Sugiyama, Yuka; Matsuda, Kuniko; Seike, Yoko; Kosaihira, Seiji; Minegishi, Yuji; Noro, Rintaro; Nara, Michiya; Seike, Masahiro; Yoshimura, Akinobu; Shionoya, Aki; Kawakami, Akiko; Ogawa, Naoki; Uesaka, Haruka; Kudoh, Shoji

    2006-01-01

    background The effect of current therapies in improving the survival of lung cancer patients remains far from satisfactory. It is consequently desirable to find more appropriate therapeutic opportunities based on informed insights. A molecular pharmacological analysis was undertaken to design an improved chemotherapeutic strategy for advanced lung cancer. Methods We related the cytotoxic activity of each of commonly used anti-cancer agents (docetaxel, paclitaxel, gemcitabine, vinorelbine, 5-FU, SN38, cisplatin (CDDP), and carboplatin (CBDCA)) to corresponding expression pattern in each of the cell lines using a modified NCI program. Results We performed gene expression analysis in lung cancer cell lines using cDNA filter and high-density oligonucleotide arrays. We also examined the sensitivity of these cell lines to these drugs via MTT assay. To obtain our reproducible gene-drug sensitivity correlation data, we separately analyzed two sets of lung cancer cell lines, namely 10 and 19. In our gene-drug correlation analyses, gemcitabine consistently belonged to an isolated cluster in a reproducible fashion. On the other hand, docetaxel, paclitaxel, 5-FU, SN-38, CBDCA and CDDP were gathered together into one large cluster. Conclusion These results suggest that chemotherapy regimens including gemcitabine should be evaluated in second-line chemotherapy in cases where the first-line chemotherapy did not include this drug. Gene expression-drug sensitivity correlations, as provided by the NCI program, may yield improved therapeutic options for treatment of specific tumor types. PMID:16813650

  11. An siRNA-based method for efficient silencing of gene expression in mature brown adipocytes

    PubMed Central

    Isidor, Marie S.; Winther, Sally; Basse, Astrid L.; Petersen, M. Christine H.; Cannon, Barbara; Nedergaard, Jan; Hansen, Jacob B.

    2016-01-01

    ABSTRACT Brown adipose tissue is a promising therapeutic target for opposing obesity, glucose intolerance and insulin resistance. The ability to modulate gene expression in mature brown adipocytes is important to understand brown adipocyte function and delineate novel regulatory mechanisms of non-shivering thermogenesis. The aim of this study was to optimize a lipofection-based small interfering RNA (siRNA) transfection protocol for efficient silencing of gene expression in mature brown adipocytes. We determined that a critical parameter was to deliver the siRNA to mature adipocytes by reverse transfection, i.e. transfection of non-adherent cells. Using this protocol, we effectively knocked down both high- and low-abundance transcripts in a model of mature brown adipocytes (WT-1) as well as in primary mature mouse brown adipocytes. A functional consequence of the knockdown was confirmed by an attenuated increase in uncoupled respiration (thermogenesis) in response to β-adrenergic stimulation of mature WT-1 brown adipocytes transfected with uncoupling protein 1 siRNA. Efficient gene silencing was also obtained in various mouse and human white adipocyte models (3T3-L1, primary mouse white adipocytes, hMADS) with the ability to undergo “browning.” In summary, we report an easy and versatile reverse siRNA transfection protocol to achieve specific silencing of gene expression in various models of mature brown and browning-competent white adipocytes, including primary cells. PMID:27386153

  12. A mRNA-based thermosensor controls expression of rhizobial heat shock genes

    PubMed Central

    Nocker, Andreas; Hausherr, Thomas; Balsiger, Sylvia; Krstulovic, Nila-Pia; Hennecke, Hauke; Narberhaus, Franz

    2001-01-01

    Expression of several heat shock operons, mainly coding for small heat shock proteins, is under the control of ROSE (repression of heat shock gene expression) in various rhizobial species. This negatively cis-acting element confers temperature control by preventing expression at physiological temperatures. We provide evidence that ROSE-mediated regulation occurs at the post-transcriptional level. A detailed mutational analysis of ROSE1–hspA translationally fused to lacZ revealed that its highly conserved 3′-half is required for repression at normal temperatures (30°C). The mRNA in this region is predicted to form an extended secondary structure that looks very similar in all 15 known ROSE elements. Nucleotides involved in base pairing are strongly conserved, whereas nucleotides in loop regions are more divergent. Base substitutions leading to derepression of the lacZ fusion at 30°C exclusively resided in potential stem structures. Optimised base pairing by elimination of a bulged residue and by introduction of complementary nucleotides in internal loops resulted in ROSE elements that were tightly repressed not only at normal but also at heat shock temperatures. We propose a model in which the temperature-regulated secondary structure of ROSE mRNA influences heat shock gene expression by controlling ribosome access to the ribosome-binding site. PMID:11726689

  13. A mRNA-based thermosensor controls expression of rhizobial heat shock genes.

    PubMed

    Nocker, A; Hausherr, T; Balsiger, S; Krstulovic, N P; Hennecke, H; Narberhaus, F

    2001-12-01

    Expression of several heat shock operons, mainly coding for small heat shock proteins, is under the control of ROSE (repression of heat shock gene expression) in various rhizobial species. This negatively cis-acting element confers temperature control by preventing expression at physiological temperatures. We provide evidence that ROSE-mediated regulation occurs at the post-transcriptional level. A detailed mutational analysis of ROSE(1)-hspA translationally fused to lacZ revealed that its highly conserved 3'-half is required for repression at normal temperatures (30 degrees C). The mRNA in this region is predicted to form an extended secondary structure that looks very similar in all 15 known ROSE elements. Nucleotides involved in base pairing are strongly conserved, whereas nucleotides in loop regions are more divergent. Base substitutions leading to derepression of the lacZ fusion at 30 degrees C exclusively resided in potential stem structures. Optimised base pairing by elimination of a bulged residue and by introduction of complementary nucleotides in internal loops resulted in ROSE elements that were tightly repressed not only at normal but also at heat shock temperatures. We propose a model in which the temperature-regulated secondary structure of ROSE mRNA influences heat shock gene expression by controlling ribosome access to the ribosome-binding site.

  14. Microarray-Based Analysis of Differential Gene Expression between Infective and Noninfective Larvae of Strongyloides stercoralis

    PubMed Central

    Ramanathan, Roshan; Varma, Sudhir; Ribeiro, José M. C.; Myers, Timothy G.; Nolan, Thomas J.; Abraham, David; Lok, James B.; Nutman, Thomas B.

    2011-01-01

    Background Differences between noninfective first-stage (L1) and infective third-stage (L3i) larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. Methods and Findings Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs) obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased) having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004), and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90). Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE) had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest. Conclusions A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding

  15. Microarray-based gene expression profiling to elucidate effectiveness of fermented Codonopsis lanceolata in mice.

    PubMed

    Choi, Woon Yong; Kim, Ji Seon; Park, Sung Jin; Ma, Choong Je; Lee, Hyeon Yong

    2014-04-08

    In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL). Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out.

  16. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    PubMed Central

    Choi, Woon Yong; Kim, Ji Seon; Park, Sung Jin; Ma, Choong Je; Lee, Hyeon Yong

    2014-01-01

    In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL). Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out. PMID:24717412

  17. Distributed Function Mining for Gene Expression Programming Based on Fast Reduction

    PubMed Central

    Deng, Song; Yue, Dong; Yang, Le-chan; Fu, Xiong; Feng, Ya-zhou

    2016-01-01

    For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model. Thorough comparative experiments for DFMGEP-FR, centralized GEP and the parallel gene expression programming algorithm based on simulated annealing (parallel GEPSA) are included in this paper. For the waveform, mushroom, connect-4 and musk datasets, the comparative results show that the average time-consumption of DFMGEP-FR drops by 89.09%%, 88.85%, 85.79% and 93.06%, respectively, in contrast to centralized GEP and by 12.5%, 8.42%, 9.62% and 13.75%, respectively, compared with parallel GEPSA. Six well-studied UCI test data sets demonstrate the efficiency and capability of our proposed DFMGEP-FR algorithm for distributed function mining. PMID:26751200

  18. Distributed Function Mining for Gene Expression Programming Based on Fast Reduction.

    PubMed

    Deng, Song; Yue, Dong; Yang, Le-chan; Fu, Xiong; Feng, Ya-zhou

    2016-01-01

    For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model. Thorough comparative experiments for DFMGEP-FR, centralized GEP and the parallel gene expression programming algorithm based on simulated annealing (parallel GEPSA) are included in this paper. For the waveform, mushroom, connect-4 and musk datasets, the comparative results show that the average time-consumption of DFMGEP-FR drops by 89.09%%, 88.85%, 85.79% and 93.06%, respectively, in contrast to centralized GEP and by 12.5%, 8.42%, 9.62% and 13.75%, respectively, compared with parallel GEPSA. Six well-studied UCI test data sets demonstrate the efficiency and capability of our proposed DFMGEP-FR algorithm for distributed function mining.

  19. Identification of key genes associated with the human abdominal aortic aneurysm based on the gene expression profile

    PubMed Central

    CHEN, XUDONG; ZHENG, CHENGFEI; HE, YUNJUN; TIAN, LU; LI, JIANHUI; LI, DONGLIN; JIN, WEI; LI, MING; ZHENG, SHUSEN

    2015-01-01

    The present study was aimed at screening the key genes associated with abdominal aortic aneurysm (AAA) in the neck, and to investigate the molecular mechanism underlying the development of AAA. The gene expression profile, GSE47472, including 14 AAA neck samples and eight donor controls, was downloaded from the Gene Expression Omnibus database. The total AAA samples were grouped into two types to avoid bias. Differentially expressed genes (DEGs) were screened in patients with AAA and subsequently compared with donor controls using linear models for microarray data, or the Limma package in R, followed by gene ontology enrichment analysis. Furthermore, a protein-protein interaction (PPI) network based on the DEGs was constructed to detect highly connected regions using a Cytoscape plugin. In total, 388 DEGs in the AAA samples were identified. These DEGs were predominantly associated with limb development, including embryonic limb development and appendage development. Nuclear receptor co-repressor 1 (NCOR1), histone 4 (H4), E2F transcription factor 4 (E2F4) and hepatocyte nuclear factor 4α (HNF4A) were the four transcription factors associated with AAA. Furthermore, HNF4A indirectly interacted with the other three transcription factors. Additionally, six clusters were selected from the PPI network. The DEG screening process and the construction of an interaction network enabled an understanding of the mechanism of AAA to be gleaned. HNF4A may exert an important role in AAA development through its interactions with the three other transcription factors (E2F4, NCOR1 and H4), and the mechanism of this coordinated regulation of the transcription factors in AAA may provide a suitable target for the development of therapeutic intervention strategies. PMID:26498477

  20. Function-Based Metagenomic Library Screening and Heterologous Expression Strategy for Genes Encoding Phosphatase Activity.

    PubMed

    Villamizar, Genis A Castillo; Nacke, Heiko; Daniel, Rolf

    2017-01-01

    The release of phosphate from inorganic and organic phosphorus compounds can be mediated enzymatically. Phosphate-releasing enzymes, comprising acid and alkaline phosphatases, are recognized as useful biocatalysts in applications such as plant and animal nutrition, bioremediation and diagnostic analysis. Metagenomic approaches provide access to novel phosphatase-encoding genes. Here, we describe a function-based screening approach for rapid identification of genes conferring phosphatase activity from small-insert and large-insert metagenomic libraries derived from various environments. This approach bears the potential for discovery of entirely novel phosphatase families or subfamilies and members of known enzyme classes hydrolyzing phosphomonoester bonds such as phytases. In addition, we provide a strategy for efficient heterologous phosphatase gene expression.

  1. Circular RNA and gene expression profiles in gastric cancer based on microarray chip technology.

    PubMed

    Sui, Weiguo; Shi, Zhoufang; Xue, Wen; Ou, Minglin; Zhu, Ying; Chen, Jiejing; Lin, Hua; Liu, Fuhua; Dai, Yong

    2017-03-01

    The aim of the present study was to screen gastric cancer (GC) tissue and adjacent tissue for differences in mRNA and circular (circRNA) expression, to analyze the differences in circRNA and mRNA expression, and to investigate the circRNA expression in gastric carcinoma and its mechanism. circRNA and mRNA differential expression profiles generated using Agilent microarray technology were analyzed in the GC tissues and adjacent tissues. qRT-PCR was used to verify the differential expression of circRNAs and mRNAs according to the interactions between circRNAs and miRNAs as well as the possible existence of miRNA and mRNA interactions. We found that: i) the circRNA expression profile revealed 1,285 significant differences in circRNA expression, with circRNA expression downregulated in 594 samples and upregulated in 691 samples via interactions with miRNAs. The qRT-PCR validation experiments showed that hsa_circRNA_400071, hsa_circRNA_000543 and hsa_circRNA_001959 expression was consistent with the microarray analysis results. ii) 29,112 genes were found in the GC tissues and adjacent tissues, including 5,460 differentially expressed genes. Among them, 2,390 differentially expressed genes were upregulated and 3,070 genes were downregulated. Gene Ontology (GO) analysis of the differentially expressed genes revealed these genes involved in biological process classification, cellular component classification and molecular function classification. Pathway analysis of the differentially expressed genes identified 83 significantly enriched genes, including 28 upregulated genes and 55 downregulated genes. iii) 69 differentially expressed circRNAs were found that might adsorb specific miRNAs to regulate the expression of their target gene mRNAs. The conclusions are: i) differentially expressed circRNAs had corresponding miRNA binding sites. These circRNAs regulated the expression of target genes through interactions with miRNAs and might become new molecular biomarkers for GC

  2. A cell-based in vitro alternative to identify skin sensitizers by gene expression

    SciTech Connect

    Hooyberghs, Jef Schoeters, Elke; Lambrechts, Nathalie; Nelissen, Inge; Witters, Hilda; Schoeters, Greet; Heuvel, Rosette van den

    2008-08-15

    The ethical and economic burden associated with animal testing for assessment of skin sensitization has triggered intensive research effort towards development and validation of alternative methods. In addition, new legislation on the registration and use of cosmetics and chemicals promote the use of suitable alternatives for hazard assessment. Our previous studies demonstrated that human CD34{sup +} progenitor-derived dendritic cells from cord blood express specific gene profiles upon exposure to low molecular weight sensitizing chemicals. This paper presents a classification model based on this cell type which is successful in discriminating sensitizing chemicals from non-sensitizing chemicals based on transcriptome analysis of 13 genes. Expression profiles of a set of 10 sensitizers and 11 non-sensitizers were analyzed by RT-PCR using 9 different exposure conditions and a total of 73 donor samples. Based on these data a predictive dichotomous classifier for skin sensitizers has been constructed, which is referred to as . In a first step the dimensionality of the input data was reduced by selectively rejecting a number of exposure conditions and genes. Next, the generalization of a linear classifier was evaluated by a cross-validation which resulted in a prediction performance with a concordance of 89%, a specificity of 97% and a sensitivity of 82%. These results show that the present model may be a useful human in vitro alternative for further use in a test strategy towards the reduction of animal use for skin sensitization.

  3. Use of lactobacilli and their pheromone-based regulatory mechanism in gene expression and drug delivery.

    PubMed

    Diep, D B; Mathiesen, G; Eijsink, V G H; Nes, I F

    2009-01-01

    Lactobacilli are common microorganisms in diverse vegetables and meat products and several of these are also indigenous inhabitants in the gastro-intestinal (GI) tract of humans and animals where they are believed to have health promoting effects on the host. One of the highly appreciated probiotic effects is their ability to inhibit the growth of pathogens by producing antimicrobial peptides, so-called bacteriocins. Production of some bacteriocins has been shown to be strictly regulated through a quorum-sensing based mechanism mediated by a secreted peptide-pheromone (also called induction peptide; IP), a membrane-located sensor (histidine protein kinase; HPK) and a cytoplasmic response regulator (RR). The interaction between an IP and its sensor, which is highly specific, leads to activation of the cognate RR which in turn binds to regulated promoters and activates gene expression. The HPKs and RRs are built up by conserved modules, and the signalling between them within a network is efficient and directional, and can easily be activated by exogenously added synthetic IPs. Consequently, components from such regulatory networks have successfully been exploited in construction of a number of inducible gene expression systems. In this review, we discuss some well-characterised quorum sensing networks involved in bacteriocin production in lactobacilli, with special focus on the use of the regulatory components in gene expression and on lactobacilli as potential delivery vehicle for therapeutic and vaccine purposes.

  4. A Digital Gene Expression-Based Bovine Gene Atlas Evaluating 92 Adult, Juvenile and Fetal Cattle Tissues

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A comprehensive transcriptome survey, or “Gene Atlas,” provides information essential for a complete understanding of the genomic biology of an organism. Using a digital gene expression approach, we developed a Gene Atlas of RNA abundance in 92 adult, juvenile and fetal cattle tissues. The samples...

  5. An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

    PubMed Central

    2010-01-01

    Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

  6. In vivo imaging of inducible tyrosinase gene expression with an ultrasound array-based photoacoustic system

    NASA Astrophysics Data System (ADS)

    Harrison, Tyler; Paproski, Robert J.; Zemp, Roger J.

    2012-02-01

    Tyrosinase, a key enzyme in the production of melanin, has shown promise as a reporter of genetic activity. While green fluorescent protein has been used extensively in this capacity, it is limited in its ability to provide information deep in tissue at a reasonable resolution. As melanin is a strong absorber of light, it is possible to image gene expression using tyrosinase with photoacoustic imaging technologies, resulting in excellent resolutions at multiple-centimeter depths. While our previous work has focused on creating and imaging MCF-7 cells with doxycycline-controlled tyrosinase expression, we have now established the viability of these cells in a murine model. Using an array-based photoacoustic imaging system with 5 MHz center frequency, we capture interleaved ultrasound and photoacoustic images of tyrosinase-expressing MCF-7 tumors both in a tissue mimicking phantom, and in vivo. Images of both the tyrosinase-expressing tumor and a control tumor are presented as both coregistered ultrasound-photoacoustic B-scan images and 3-dimensional photoacoustic volumes created by mechanically scanning the transducer. We find that the tyrosinase-expressing tumor is visible with a signal level 12dB greater than that of the control tumor in vivo. Phantom studies with excised tumors show that the tyrosinase-expressing tumor is visible at depths in excess of 2cm, and have suggested that our imaging system is sensitive to a transfection rate of less than 1%.

  7. Sex-based differences in gene expression in hippocampus following postnatal lead exposure

    SciTech Connect

    Schneider, J.S. Anderson, D.W.; Sonnenahalli, H.; Vadigepalli, R.

    2011-10-15

    The influence of sex as an effect modifier of childhood lead poisoning has received little systematic attention. Considering the paucity of information available concerning the interactive effects of lead and sex on the brain, the current study examined the interactive effects of lead and sex on gene expression patterns in the hippocampus, a structure involved in learning and memory. Male or female rats were fed either 1500 ppm lead-containing chow or control chow for 30 days beginning at weaning.Blood lead levels were 26.7 {+-} 2.1 {mu}g/dl and 27.1 {+-} 1.7 {mu}g/dl for females and males, respectively. The expression of 175 unique genes was differentially regulated between control male and female rats. A total of 167 unique genes were differentially expressed in response to lead in either males or females. Lead exposure had a significant effect without a significant difference between male and female responses in 77 of these genes. In another set of 71 genes, there were significant differences in male vs. female response. A third set of 30 genes was differentially expressed in opposite directions in males vs. females, with the majority of genes expressed at a lower level in females than in males. Highly differentially expressed genes in males and females following lead exposure were associated with diverse biological pathways and functions. These results show that a brief exposure to lead produced significant changes in expression of a variety of genes in the hippocampus and that the response of the brain to a given lead exposure may vary depending on sex. - Highlights: > Postnatal lead exposure has a significant effect on hippocampal gene expression patterns. > At least one set of genes was affected in opposite directions in males and females. > Differentially expressed genes were associated with diverse biological pathways.

  8. Ribozyme-based aminoglycoside switches of gene expression engineered by genetic selection in S. cerevisiae.

    PubMed

    Klauser, Benedikt; Atanasov, Janina; Siewert, Lena K; Hartig, Jörg S

    2015-05-15

    Systems for conditional gene expression are powerful tools in basic research as well as in biotechnology. For future applications, it is of great importance to engineer orthogonal genetic switches that function reliably in diverse contexts. RNA-based switches have the advantage that effector molecules interact immediately with regulatory modules inserted into the target RNAs, getting rid of the need of transcription factors usually mediating genetic control. Artificial riboswitches are characterized by their simplicity and small size accompanied by a high degree of modularity. We have recently reported a series of hammerhead ribozyme-based artificial riboswitches that allow for post-transcriptional regulation of gene expression via switching mRNA, tRNA, or rRNA functions. A more widespread application was so far hampered by moderate switching performances and a limited set of effector molecules available. Here, we report the re-engineering of hammerhead ribozymes in order to respond efficiently to aminoglycoside antibiotics. We first established an in vivo selection protocol in Saccharomyces cerevisiae that enabled us to search large sequence spaces for optimized switches. We then envisioned and characterized a novel strategy of attaching the aptamer to the ribozyme catalytic core, increasing the design options for rendering the ribozyme ligand-dependent. These innovations enabled the development of neomycin-dependent RNA modules that switch gene expression up to 25-fold. The presented aminoglycoside-responsive riboswitches belong to the best-performing RNA-based genetic regulators reported so far. The developed in vivo selection protocol should allow for sampling of large sequence spaces for engineering of further optimized riboswitches.

  9. Subtyping of Gliomaby Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach

    PubMed Central

    Tang, Wenlong; Cao, Hongbao; Zhang, Ji-Gang; Duan, Junbo; Lin, Dongdong; Wang, Yu-Ping

    2013-01-01

    It is realized that a combined analysis of different types of genomic measurements tends to give more reliable classification results. However, how to efficiently combine data with different resolutions is challenging. We propose a novel compressed sensing based approach for the combined analysis of gene expression and copy number variants data for the purpose of subtyping six types of Gliomas. Experimental results show that the proposed combined approach can substantially improve the classification accuracy compared to that of using either of individual data type. The proposed approach can be applicable to many other types of genomic data. PMID:25267935

  10. Problem-Based Test: The Effect of Fibroblast Growth Factor on Gene Expression

    ERIC Educational Resources Information Center

    Szeberenyi, Jozsef

    2011-01-01

    This paper shows the results of an experiment in which the effects of fibroblast growth factor (FGF), actinomycin D (Act D; an inhibitor of transcription), and cycloheximide (CHX; an inhibitor of translation) were studied on the expression of two genes: a gene called "Fnk" and the gene coding for glyceraldehyde-3-phosphate dehydrogenase (GAPDH).…

  11. Ecdysone Receptor-based Singular Gene Switches for Regulated Transgene Expression in Cells and Adult Rodent Tissues

    PubMed Central

    Lee, Seoghyun; Sohn, Kyung-Cheol; Choi, Dae-Kyoung; Won, Minho; Park, Kyeong Ah; Ju, Sung-Kyu; Kang, Kidong; Bae, Young-Ki; Hur, Gang Min; Ro, Hyunju

    2016-01-01

    Controlled gene expression is an indispensable technique in biomedical research. Here, we report a convenient, straightforward, and reliable way to induce expression of a gene of interest with negligible background expression compared to the most widely used tetracycline (Tet)-regulated system. Exploiting a Drosophila ecdysone receptor (EcR)-based gene regulatory system, we generated nonviral and adenoviral singular vectors designated as pEUI(+) and pENTR-EUI, respectively, which contain all the required elements to guarantee regulated transgene expression (GAL4-miniVP16-EcR, termed GvEcR hereafter, and 10 tandem repeats of an upstream activation sequence promoter followed by a multiple cloning site). Through the transient and stable transfection of mammalian cell lines with reporter genes, we validated that tebufenozide, an ecdysone agonist, reversibly induced gene expression, in a dose- and time-dependent manner, with negligible background expression. In addition, we created an adenovirus derived from the pENTR-EUI vector that readily infected not only cultured cells but also rodent tissues and was sensitive to tebufenozide treatment for regulated transgene expression. These results suggest that EcR-based singular gene regulatory switches would be convenient tools for the induction of gene expression in cells and tissues in a tightly controlled fashion. PMID:27673563

  12. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    PubMed Central

    Warnat, Patrick; Eils, Roland; Brors, Benedikt

    2005-01-01

    Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85%) were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and microarray technologies

  13. Blood-based gene expression signatures of medication-free outpatients with major depressive disorder: integrative genome-wide and candidate gene analyses.

    PubMed

    Hori, Hiroaki; Sasayama, Daimei; Teraishi, Toshiya; Yamamoto, Noriko; Nakamura, Seiji; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

    2016-01-05

    Several microarray-based studies have investigated gene expression profiles in major depressive disorder (MDD), yet with highly variable findings. We examined blood-based genome-wide expression signatures of MDD, focusing on molecular pathways and networks underlying differentially expressed genes (DEGs) and behaviours of hypothesis-driven, evidence-based candidate genes for depression. Agilent human whole-genome arrays were used to measure gene expression in 14 medication-free outpatients with MDD who were at least moderately ill and 14 healthy controls matched pairwise for age and sex. After filtering, we compared expression of entire probes between patients and controls and identified DEGs. The DEGs were evaluated by pathway and network analyses. For the candidate gene analysis, we utilized 169 previously prioritized genes and examined their case-control separation efficiency and correlational co-expression network in patients relative to controls. The 317 screened DEGs mapped to a significantly over-represented pathway, the "synaptic transmission" pathway. The protein-protein interaction network was also significantly enriched, in which a number of key molecules for depression were included. The co-expression network of candidate genes was markedly disrupted in patients. This study provided evidence for an altered molecular network along with several key molecules in MDD and confirmed that the candidate genes are worthwhile targets for depression research.

  14. Blood-based gene expression signatures of medication-free outpatients with major depressive disorder: integrative genome-wide and candidate gene analyses

    PubMed Central

    Hori, Hiroaki; Sasayama, Daimei; Teraishi, Toshiya; Yamamoto, Noriko; Nakamura, Seiji; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

    2016-01-01

    Several microarray-based studies have investigated gene expression profiles in major depressive disorder (MDD), yet with highly variable findings. We examined blood-based genome-wide expression signatures of MDD, focusing on molecular pathways and networks underlying differentially expressed genes (DEGs) and behaviours of hypothesis-driven, evidence-based candidate genes for depression. Agilent human whole-genome arrays were used to measure gene expression in 14 medication-free outpatients with MDD who were at least moderately ill and 14 healthy controls matched pairwise for age and sex. After filtering, we compared expression of entire probes between patients and controls and identified DEGs. The DEGs were evaluated by pathway and network analyses. For the candidate gene analysis, we utilized 169 previously prioritized genes and examined their case-control separation efficiency and correlational co-expression network in patients relative to controls. The 317 screened DEGs mapped to a significantly over-represented pathway, the “synaptic transmission” pathway. The protein-protein interaction network was also significantly enriched, in which a number of key molecules for depression were included. The co-expression network of candidate genes was markedly disrupted in patients. This study provided evidence for an altered molecular network along with several key molecules in MDD and confirmed that the candidate genes are worthwhile targets for depression research. PMID:26728011

  15. Expression Atlas update—a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

    PubMed Central

    Petryszak, Robert; Burdett, Tony; Fiorelli, Benedetto; Fonseca, Nuno A.; Gonzalez-Porta, Mar; Hastings, Emma; Huber, Wolfgang; Jupp, Simon; Keays, Maria; Kryvych, Nataliya; McMurry, Julie; Marioni, John C.; Malone, James; Megy, Karine; Rustici, Gabriella; Tang, Amy Y.; Taubert, Jan; Williams, Eleanor; Mannion, Oliver; Parkinson, Helen E.; Brazma, Alvis

    2014-01-01

    Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of ‘baseline’ expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful ‘contrasts’, i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user. PMID:24304889

  16. Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

    NASA Astrophysics Data System (ADS)

    Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

    Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed

  17. Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

    PubMed

    Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

    2012-07-15

    Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary

  18. Dissecting Gene Expression Changes Accompanying a Ploidy-Based Phenotypic Switch

    PubMed Central

    Cromie, Gareth A.; Tan, Zhihao; Hays, Michelle; Jeffery, Eric W.; Dudley, Aimée M.

    2016-01-01

    Aneuploidy, a state in which the chromosome number deviates from a multiple of the haploid count, significantly impacts human health. The phenotypic consequences of aneuploidy are believed to arise from gene expression changes associated with the altered copy number of genes on the aneuploid chromosomes. To dissect the mechanisms underlying altered gene expression in aneuploids, we used RNA-seq to measure transcript abundance in colonies of the haploid Saccharomyces cerevisiae strain F45 and two aneuploid derivatives harboring disomies of chromosomes XV and XVI. F45 colonies display complex “fluffy” morphologies, while the disomic colonies are smooth, resembling laboratory strains. Our two disomes displayed similar transcriptional profiles, a phenomenon not driven by their shared smooth colony morphology nor simply by their karyotype. Surprisingly, the environmental stress response (ESR) was induced in F45, relative to the two disomes. We also identified genes whose expression reflected a nonlinear interaction between the copy number of a transcriptional regulatory gene on chromosome XVI, DIG1, and the copy number of other chromosome XVI genes. DIG1 and the remaining chromosome XVI genes also demonstrated distinct contributions to the effect of the chromosome XVI disome on ESR gene expression. Expression changes in aneuploids appear to reflect a mixture of effects shared between different aneuploidies and effects unique to perturbing the copy number of particular chromosomes, including nonlinear copy number interactions between genes. The balance between these two phenomena is likely to be genotype- and environment-specific. PMID:27836908

  19. Human Lacrimal Gland Gene Expression

    PubMed Central

    Aakalu, Vinay Kumar; Parameswaran, Sowmya; Maienschein-Cline, Mark; Bahroos, Neil; Shah, Dhara; Ali, Marwan; Krishnakumar, Subramanian

    2017-01-01

    Background The study of human lacrimal gland biology and development is limited. Lacrimal gland tissue is damaged or poorly functional in a number of disease states including dry eye disease. Development of cell based therapies for lacrimal gland diseases requires a better understanding of the gene expression and signaling pathways in lacrimal gland. Differential gene expression analysis between lacrimal gland and other embryologically similar tissues may be helpful in furthering our understanding of lacrimal gland development. Methods We performed global gene expression analysis of human lacrimal gland tissue using Affymetrix ® gene expression arrays. Primary data from our laboratory was compared with datasets available in the NLM GEO database for other surface ectodermal tissues including salivary gland, skin, conjunctiva and corneal epithelium. Results The analysis revealed statistically significant difference in the gene expression of lacrimal gland tissue compared to other ectodermal tissues. The lacrimal gland specific, cell surface secretory protein encoding genes and critical signaling pathways which distinguish lacrimal gland from other ectodermal tissues are described. Conclusions Differential gene expression in human lacrimal gland compared with other ectodermal tissue types revealed interesting patterns which may serve as the basis for future studies in directed differentiation among other areas. PMID:28081151

  20. Parkinson's disease candidate gene prioritization based on expression profile of midbrain dopaminergic neurons

    PubMed Central

    2010-01-01

    Background Parkinson's disease is the second most common neurodegenerative disorder. The pathological hallmark of the disease is degeneration of midbrain dopaminergic neurons. Genetic association studies have linked 13 human chromosomal loci to Parkinson's disease. Identification of gene(s), as part of the etiology of Parkinson's disease, within the large number of genes residing in these loci can be achieved through several approaches, including screening methods, and considering appropriate criteria. Since several of the indentified Parkinson's disease genes are expressed in substantia nigra pars compact of the midbrain, expression within the neurons of this area could be a suitable criterion to limit the number of candidates and identify PD genes. Methods In this work we have used the combination of findings from six rodent transcriptome analysis studies on the gene expression profile of midbrain dopaminergic neurons and the PARK loci in OMIM (Online Mendelian Inheritance in Man) database, to identify new candidate genes for Parkinson's disease. Results Merging the two datasets, we identified 20 genes within PARK loci, 7 of which are located in an orphan Parkinson's disease locus and one, which had been identified as a disease gene. In addition to identifying a set of candidates for further genetic association studies, these results show that the criteria of expression in midbrain dopaminergic neurons may be used to narrow down the number of genes in PARK loci for such studies. PMID:20716345

  1. A host-based RT-PCR gene expression signature to identify acute respiratory viral infection.

    PubMed

    Zaas, Aimee K; Burke, Thomas; Chen, Minhua; McClain, Micah; Nicholson, Bradly; Veldman, Timothy; Tsalik, Ephraim L; Fowler, Vance; Rivers, Emanuel P; Otero, Ronny; Kingsmore, Stephen F; Voora, Deepak; Lucas, Joseph; Hero, Alfred O; Carin, Lawrence; Woods, Christopher W; Ginsburg, Geoffrey S

    2013-09-18

    Improved ways to diagnose acute respiratory viral infections could decrease inappropriate antibacterial use and serve as a vital triage mechanism in the event of a potential viral pandemic. Measurement of the host response to infection is an alternative to pathogen-based diagnostic testing and may improve diagnostic accuracy. We have developed a host-based assay with a reverse transcription polymerase chain reaction (RT-PCR) TaqMan low-density array (TLDA) platform for classifying respiratory viral infection. We developed the assay using two cohorts experimentally infected with influenza A H3N2/Wisconsin or influenza A H1N1/Brisbane, and validated the assay in a sample of adults presenting to the emergency department with fever (n = 102) and in healthy volunteers (n = 41). Peripheral blood RNA samples were obtained from individuals who underwent experimental viral challenge or who presented to the emergency department and had microbiologically proven viral respiratory infection or systemic bacterial infection. The selected gene set on the RT-PCR TLDA assay classified participants with experimentally induced influenza H3N2 and H1N1 infection with 100 and 87% accuracy, respectively. We validated this host gene expression signature in a cohort of 102 individuals arriving at the emergency department. The sensitivity of the RT-PCR test was 89% [95% confidence interval (CI), 72 to 98%], and the specificity was 94% (95% CI, 86 to 99%). These results show that RT-PCR-based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting.

  2. A modified ABCDE model of flowering in orchids based on gene expression profiling studies of the moth orchid Phalaenopsis aphrodite.

    PubMed

    Su, Chun-Lin; Chen, Wan-Chieh; Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

    2013-01-01

    Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns.

  3. Differential Evolution of MAGE Genes Based on Expression Pattern and Selection Pressure

    PubMed Central

    Zhao, Qi; Caballero, Otavia L.; Simpson, Andrew J. G.; Strausberg, Robert L.

    2012-01-01

    Starting from publicly-accessible datasets, we have utilized comparative and phylogenetic genome analyses to characterize the evolution of the human MAGE gene family. Our characterization of genomic structures in representative genomes of primates, rodents, carnivora, and macroscelidea indicates that both Type I and Type II MAGE genes have undergone lineage-specific evolution. The restricted expression pattern in germ cells of Type I MAGE orthologs is observed throughout evolutionary history. Unlike Type II MAGEs that have conserved promoter sequences, Type I MAGEs lack promoter conservation, suggesting that epigenetic regulation is a central mechanism for controlling their expression. Codon analysis shows that Type I but not Type II MAGE genes have been under positive selection. The combination of genomic and expression analysis suggests that Type 1 MAGE promoters and genes continue to evolve in the hominin lineage, perhaps towards functional diversification or acquiring additional specific functions, and that selection pressure at codon level is associated with expression spectrum. PMID:23133577

  4. Differential evolution of MAGE genes based on expression pattern and selection pressure.

    PubMed

    Zhao, Qi; Caballero, Otavia L; Simpson, Andrew J G; Strausberg, Robert L

    2012-01-01

    Starting from publicly-accessible datasets, we have utilized comparative and phylogenetic genome analyses to characterize the evolution of the human MAGE gene family. Our characterization of genomic structures in representative genomes of primates, rodents, carnivora, and macroscelidea indicates that both Type I and Type II MAGE genes have undergone lineage-specific evolution. The restricted expression pattern in germ cells of Type I MAGE orthologs is observed throughout evolutionary history. Unlike Type II MAGEs that have conserved promoter sequences, Type I MAGEs lack promoter conservation, suggesting that epigenetic regulation is a central mechanism for controlling their expression. Codon analysis shows that Type I but not Type II MAGE genes have been under positive selection. The combination of genomic and expression analysis suggests that Type 1 MAGE promoters and genes continue to evolve in the hominin lineage, perhaps towards functional diversification or acquiring additional specific functions, and that selection pressure at codon level is associated with expression spectrum.

  5. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    PubMed Central

    Matsumoto, Tomotaka; Mineta, Katsuhiko; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  6. A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

    PubMed

    Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs.

  7. A bayesian mixed regression based prediction of quantitative traits from molecular marker and gene expression data.

    PubMed

    Bhattacharjee, Madhuchhanda; Sillanpää, Mikko J

    2011-01-01

    Both molecular marker and gene expression data were considered alone as well as jointly to serve as additive predictors for two pathogen-activity-phenotypes in real recombinant inbred lines of soybean. For unobserved phenotype prediction, we used a bayesian hierarchical regression modeling, where the number of possible predictors in the model was controlled by different selection strategies tested. Our initial findings were submitted for DREAM5 (the 5th Dialogue on Reverse Engineering Assessment and Methods challenge) and were judged to be the best in sub-challenge B3 wherein both functional genomic and genetic data were used to predict the phenotypes. In this work we further improve upon this previous work by considering various predictor selection strategies and cross-validation was used to measure accuracy of in-data and out-data predictions. The results from various model choices indicate that for this data use of both data types (namely functional genomic and genetic) simultaneously improves out-data prediction accuracy. Adequate goodness-of-fit can be easily achieved with more complex models for both phenotypes, since the number of potential predictors is large and the sample size is not small. We also further studied gene-set enrichment (for continuous phenotype) in the biological process in question and chromosomal enrichment of the gene set. The methodological contribution of this paper is in exploration of variable selection techniques to alleviate the problem of over-fitting. Different strategies based on the nature of covariates were explored and all methods were implemented under the bayesian hierarchical modeling framework with indicator-based covariate selection. All the models based in careful variable selection procedure were found to produce significant results based on permutation test.

  8. Census of genes expressed in porcine embryos and reproductive tissues by mining an expressed sequence tag database based on human genes.

    PubMed

    Jiang, Zhihua; Zhang, Ming; Wasem, Vaughn D; Michal, Jennifer J; Zhang, Hao; Wright, Raymond W

    2003-10-01

    A total of 98,898 expressed sequence tags (ESTs) derived from embryos and reproductive tissues in pigs were identified in the GenBank "est_others" database. Pig embryos were collected at 11, 12, 13, 14, 15, 20, 30, and 45 days after gestation. The reproductive tissues were sampled from testis, ovary, endometrium, hypothalamus, anterior pituitary, uterus, and placenta. A gene-oriented approach was developed to annotate these porcine EST sequences to census the genes expressed from these sources. Of the 33 308 mRNA sequences from the human genes used as references (data accessed on 1 November 2002), 9410 had the porcine EST homologs expressed in embryos and 11 795 had the EST homologs expressed in reproductive tissues. The entire genome contributes at least 28.3% of its genes to embryo development and 35.4% of its genes to reproduction. Using the EST entry numbers as indicators of gene expression, we determined that the gene expression patterns differ significantly between embryos and reproductive tissues in pigs. The basic active genes were identified for each source, but most of them are not coexpressed abundantly. Few genes were expressed on the Y chromosome (P < 0.01), but they may represent counterparts of the double-dose genes that remain active in an inactivated X chromosome in females but are needed for proper development and growth. The census provides a panel of transcripts in a broad sense that can be used as targets to study the mechanisms involved in embryo development and reproduction in pigs and other mammals, including humans.

  9. Model-Based Characterization of Inflammatory Gene Expression Patterns of Activated Macrophages

    PubMed Central

    Ehlting, Christian; Thomas, Maria; Zanger, Ulrich M.; Sawodny, Oliver; Häussinger, Dieter; Bode, Johannes G.

    2016-01-01

    Macrophages are cells with remarkable plasticity. They integrate signals from their microenvironment leading to context-dependent polarization into classically (M1) or alternatively (M2) activated macrophages, representing two extremes of a broad spectrum of divergent phenotypes. Thereby, macrophages deliver protective and pro-regenerative signals towards injured tissue but, depending on the eliciting damage, may also be responsible for the generation and aggravation of tissue injury. Although incompletely understood, there is emerging evidence that macrophage polarization is critical for these antagonistic roles. To identify activation-specific expression patterns of chemokines and cytokines that may confer these distinct effects a systems biology approach was applied. A comprehensive literature-based Boolean model was developed to describe the M1 (LPS-activated) and M2 (IL-4/13-activated) polarization types. The model was validated using high-throughput transcript expression data from murine bone marrow derived macrophages. By dynamic modeling of gene expression, the chronology of pathway activation and autocrine signaling was estimated. Our results provide a deepened understanding of the physiological balance leading to M1/M2 activation, indicating the relevance of co-regulatory signals at the level of Akt1 or Akt2 that may be important for directing macrophage polarization. PMID:27464342

  10. Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

    PubMed

    Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

    2013-01-01

    Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

  11. SVD-based anatomy of gene expressions for correlation analysis in Arabidopsis thaliana.

    PubMed

    Fukushima, Atsushi; Wada, Masayoshi; Kanaya, Shigehiko; Arita, Masanori

    2008-12-01

    Gene co-expression analysis has been widely used in recent years for predicting unknown gene function and its regulatory mechanisms. The predictive accuracy depends on the quality and the diversity of data set used. In this report, we applied singular value decomposition (SVD) to array experiments in public databases to find that co-expression linkage could be estimated by a much smaller number of array data. Correlations of co-expressed gene were assessed using two regulatory mechanisms (feedback loop of the fundamental circadian clock and a global transcription factor Myb28), as well as metabolic pathways in the AraCyc database. Our conclusion is that a smaller number of informative arrays across tissues can suffice to reproduce comparable results with a state-of-the-art co-expression software tool. In our SVD analysis on Arabidopsis data set, array experiments that contributed most as the principal components included stamen development, germinating seed and stress responses on leaf.

  12. Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming.

    PubMed

    Li, Yuqin; You, Guirong; Jia, Baoxiu; Si, Hongzong; Yao, Xiaojun

    2014-01-01

    Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R (2)) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.

  13. A PSO-Based Approach for Pathway Marker Identification From Gene Expression Data.

    PubMed

    Mandal, Monalisa; Mondal, Jyotirmay; Mukhopadhyay, Anirban

    2015-09-01

    In this article, a new and robust pathway activity inference scheme is proposed from gene expression data using Particle Swarm Optimization (PSO). From microarray gene expression data, the corresponding pathway information of the genes are collected from a public database. For identifying the pathway markers, the expression values of each pathway consisting of genes, termed as pathway activity, are summarized. To measure the goodness of a pathway activity vector, t-score is widely used in the existing literature. The weakness of existing techniques for inferring pathway activity is that they intend to consider all the member genes of a pathway. But in reality, all the member genes may not be significant to the corresponding pathway. Therefore, those genes, which are responsible in the corresponding pathway, should be included only. Motivated by this, in the proposed method, using PSO, important genes with respect to each pathway are identified. The objective is to maximize the average t-score. For the pathway activities inferred from different percentage of significant pathways, the average absolute t -scores are plotted. In addition, the top 50% pathway markers are evaluated using 10-fold cross validation and its performance is compared with that of other existing techniques. Biological relevance of the results is also studied.

  14. Classification of Dengue Fever Patients Based on Gene Expression Data Using Support Vector Machines

    PubMed Central

    Khan, Asif M.; Gil, Laura H. V. G.; Marques, Ernesto T. A.; Calzavara-Silva, Carlos E.; Tan, Tin Wee

    2010-01-01

    Background Symptomatic infection by dengue virus (DENV) can range from dengue fever (DF) to dengue haemorrhagic fever (DHF), however, the determinants of DF or DHF progression are not completely understood. It is hypothesised that host innate immune response factors are involved in modulating the disease outcome and the expression levels of genes involved in this response could be used as early prognostic markers for disease severity. Methodology/Principal Findings mRNA expression levels of genes involved in DENV innate immune responses were measured using quantitative real time PCR (qPCR). Here, we present a novel application of the support vector machines (SVM) algorithm to analyze the expression pattern of 12 genes in peripheral blood mononuclear cells (PBMCs) of 28 dengue patients (13 DHF and 15 DF) during acute viral infection. The SVM model was trained using gene expression data of these genes and achieved the highest accuracy of ∼85% with leave-one-out cross-validation. Through selective removal of gene expression data from the SVM model, we have identified seven genes (MYD88, TLR7, TLR3, MDA5, IRF3, IFN-α and CLEC5A) that may be central in differentiating DF patients from DHF, with MYD88 and TLR7 observed to be the most important. Though the individual removal of expression data of five other genes had no impact on the overall accuracy, a significant combined role was observed when the SVM model of the two main genes (MYD88 and TLR7) was re-trained to include the five genes, increasing the overall accuracy to ∼96%. Conclusions/Significance Here, we present a novel use of the SVM algorithm to classify DF and DHF patients, as well as to elucidate the significance of the various genes involved. It was observed that seven genes are critical in classifying DF and DHF patients: TLR3, MDA5, IRF3, IFN-α, CLEC5A, and the two most important MYD88 and TLR7. While these preliminary results are promising, further experimental investigation is necessary to validate

  15. A gene-expression-based neural code for food abundance that modulates lifespan

    PubMed Central

    Entchev, Eugeni V; Patel, Dhaval S; Zhan, Mei; Steele, Andrew J; Lu, Hang; Ch'ng, QueeLim

    2015-01-01

    How the nervous system internally represents environmental food availability is poorly understood. Here, we show that quantitative information about food abundance is encoded by combinatorial neuron-specific gene-expression of conserved TGFβ and serotonin pathway components in Caenorhabditis elegans. Crosstalk and auto-regulation between these pathways alters the shape, dynamic range, and population variance of the gene-expression responses of daf-7 (TGFβ) and tph-1 (tryptophan hydroxylase) to food availability. These intricate regulatory features provide distinct mechanisms for TGFβ and serotonin signaling to tune the accuracy of this multi-neuron code: daf-7 primarily regulates gene-expression variability, while tph-1 primarily regulates the dynamic range of gene-expression responses. This code is functional because daf-7 and tph-1 mutations bidirectionally attenuate food level-dependent changes in lifespan. Our results reveal a neural code for food abundance and demonstrate that gene expression serves as an additional layer of information processing in the nervous system to control long-term physiology. DOI: http://dx.doi.org/10.7554/eLife.06259.001 PMID:25962853

  16. A gene-expression-based neural code for food abundance that modulates lifespan.

    PubMed

    Entchev, Eugeni V; Patel, Dhaval S; Zhan, Mei; Steele, Andrew J; Lu, Hang; Ch'ng, QueeLim

    2015-05-12

    How the nervous system internally represents environmental food availability is poorly understood. Here, we show that quantitative information about food abundance is encoded by combinatorial neuron-specific gene-expression of conserved TGFβ and serotonin pathway components in Caenorhabditis elegans. Crosstalk and auto-regulation between these pathways alters the shape, dynamic range, and population variance of the gene-expression responses of daf-7 (TGFβ) and tph-1 (tryptophan hydroxylase) to food availability. These intricate regulatory features provide distinct mechanisms for TGFβ and serotonin signaling to tune the accuracy of this multi-neuron code: daf-7 primarily regulates gene-expression variability, while tph-1 primarily regulates the dynamic range of gene-expression responses. This code is functional because daf-7 and tph-1 mutations bidirectionally attenuate food level-dependent changes in lifespan. Our results reveal a neural code for food abundance and demonstrate that gene expression serves as an additional layer of information processing in the nervous system to control long-term physiology.

  17. Forensic diagnosis of ante- and postmortem burn based on aquaporin-3 gene expression in the skin.

    PubMed

    Kubo, Hidemichi; Hayashi, Takahito; Ago, Kazutoshi; Ago, Mihoko; Kanekura, Takuro; Ogata, Mamoru

    2014-05-01

    In order to diagnose death associated with fire, it is essential to show that the person was exposed to heat while still alive. We investigated both AQP1 and AQP3 expression in the skin of an experimental burn model, as well as in forensic autopsy cases, and discuss its role in the differential diagnosis of ante- and postmortem burns. In animal experiments, there was no difference in AQP1 gene expression among four groups (n=4): antemortem burn, postmortem burn, mechanical wound, and control. However, AQP3 expression in the antemortem burn was increased significantly compared with that of the other groups even at 5min after burn. Water content of the skin was decreased significantly by the burn procedure. Consistent with animal experiments, AQP3 gene expression in the skin of antemortem burn cases was increased significantly compared with postmortem burns, mechanical wounds, and controls (n=12 in each group). These observations suggest that dermal AQP3 gene expression was increased to maintain water homeostasis in response to dehydration from burn. Finally, our results suggest that AQP3 gene expression may be useful for forensic molecular diagnosis of antemortem burn.

  18. Development of a plant viral-vector-based gene expression assay for the screening of yeast cytochrome p450 monooxygenases.

    PubMed

    Hanley, Kathleen; Nguyen, Long V; Khan, Faizah; Pogue, Gregory P; Vojdani, Fakhrieh; Panda, Sanjay; Pinot, Franck; Oriedo, Vincent B; Rasochova, Lada; Subramanian, Mani; Miller, Barbara; White, Earl L

    2003-02-01

    Development of a gene discovery tool for heterologously expressed cytochrome P450 monooxygenases has been inherently difficult. The activity assays are labor-intensive and not amenable to parallel screening. Additionally, biochemical confirmation requires coexpression of a homologous P450 reductase or complementary heterologous activity. Plant virus gene expression systems have been utilized for a diverse group of organisms. In this study we describe a method using an RNA vector expression system to phenotypically screen for cytochrome P450-dependent fatty acid omega-hydroxylase activity. Yarrowia lipolytica CYP52 gene family members involved in n-alkane assimilation were amplified from genomic DNA, cloned into a plant virus gene expression vector, and used as a model system for determining heterologous expression. Plants infected with virus vectors expressing the yeast CYP52 genes (YlALK1-YlALK7) showed a distinct necrotic lesion phenotype on inoculated plant leaves. No phenotype was detected on negative control constructs. YlALK3-, YlALK5-, and YlALK7-inoculated plants all catalyzed the terminal hydroxylation of lauric acid as confirmed using thin-layer and gas chromatography/mass spectrometry methods. The plant-based cytochrome P450 phenotypic screen was tested on an n-alkane-induced Yarrowia lipolytica plant virus expression library. A subset of 1,025 random library clones, including YlALK1-YlALK7 constructs, were tested on plants. All YlALK gene constructs scored positive in the randomized screen. Following nucleotide sequencing of the clones that scored positive using a phenotypic screen, approximately 5% were deemed appropriate for further biochemical analysis. This report illustrates the utility of a plant-based system for expression of heterologous cytochrome P450 monooxygenases and for the assignment of gene function.

  19. ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions

    PubMed Central

    Tan, Jie; Hammond, John H.; Hogan, Deborah A.

    2016-01-01

    ABSTRACT The increasing number of genome-wide assays of gene expression available from public databases presents opportunities for computational methods that facilitate hypothesis generation and biological interpretation of these data. We present an unsupervised machine learning approach, ADAGE (analysis using denoising autoencoders of gene expression), and apply it to the publicly available gene expression data compendium for Pseudomonas aeruginosa. In this approach, the machine-learned ADAGE model contained 50 nodes which we predicted would correspond to gene expression patterns across the gene expression compendium. While no biological knowledge was used during model construction, cooperonic genes had similar weights across nodes, and genes with similar weights across nodes were significantly more likely to share KEGG pathways. By analyzing newly generated and previously published microarray and transcriptome sequencing data, the ADAGE model identified differences between strains, modeled the cellular response to low oxygen, and predicted the involvement of biological processes based on low-level gene expression differences. ADAGE compared favorably with traditional principal component analysis and independent component analysis approaches in its ability to extract validated patterns, and based on our analyses, we propose that these approaches differ in the types of patterns they preferentially identify. We provide the ADAGE model with analysis of all publicly available P. aeruginosa GeneChip experiments and open source code for use with other species and settings. Extraction of consistent patterns across large-scale collections of genomic data using methods like ADAGE provides the opportunity to identify general principles and biologically important patterns in microbial biology. This approach will be particularly useful in less-well-studied microbial species. IMPORTANCE The quantity and breadth of genome-scale data sets that examine RNA expression in diverse

  20. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

    PubMed Central

    Efferth, Thomas; Greten, Henry Johannes

    2012-01-01

    Withania somnifera (L.) Dunal (Indian ginseng, winter cherry, Solanaceae) is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts). The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin) and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin) was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others. PMID:27605335

  1. Microfluidic droplet-based PCR instrumentation for high-throughput gene expression profiling and biomarker discovery

    PubMed Central

    Hayes, Christopher J.; Dalton, Tara M.

    2015-01-01

    PCR is a common and often indispensable technique used in medical and biological research labs for a variety of applications. Real-time quantitative PCR (RT-qPCR) has become a definitive technique for quantitating differences in gene expression levels between samples. Yet, in spite of this importance, reliable methods to quantitate nucleic acid amounts in a higher throughput remain elusive. In the following paper, a unique design to quantify gene expression levels at the nanoscale in a continuous flow system is presented. Fully automated, high-throughput, low volume amplification of deoxynucleotides (DNA) in a droplet based microfluidic system is described. Unlike some conventional qPCR instrumentation that use integrated fluidic circuits or plate arrays, the instrument performs qPCR in a continuous, micro-droplet flowing process with droplet generation, distinctive reagent mixing, thermal cycling and optical detection platforms all combined on one complete instrument. Detailed experimental profiling of reactions of less than 300 nl total volume is achieved using the platform demonstrating the dynamic range to be 4 order logs and consistent instrument sensitivity. Furthermore, reduced pipetting steps by as much as 90% and a unique degree of hands-free automation makes the analytical possibilities for this instrumentation far reaching. In conclusion, a discussion of the first demonstrations of this approach to perform novel, continuous high-throughput biological screens is presented. The results generated from the instrument, when compared with commercial instrumentation, demonstrate the instrument reliability and robustness to carry out further studies of clinical significance with added throughput and economic benefits. PMID:27077035

  2. Effect of Long-Term Storage in TRIzol on Microarray-Based Gene Expression Profiling

    PubMed Central

    Ma, Wencai; Wang, Michael; Wang, Zhi-Qiang; Sun, Luhong; Graber, David; Matthews, Jairo; Champlin, Richard; Yi, Qing; Orlowski, Robert Z.; Kwak, Larry W.; Weber, Donna M.; Thomas, Sheeba K.; Shah, Jatin; Kornblau, Steven; Davis, R. Eric

    2010-01-01

    Background Although TRIzol is widely used for preservation and isolation of RNA, there is suspicion that prolonged sample storage in TRIzol may affect array-based gene expression profiling (GEP), via premature termination during reverse transcription (RT). Methods GEP on Illumina arrays compared paired aliquots (cryopreserved or stored in TRIzol) of primary samples of multiple myeloma (MM) and acute myeloid leukemia (AML). Data were analyzed at the “probe level” (a single consensus value) or “bead level” (multiple measurements provided by individual beads). Results TRIzol storage does not affect standard probe-level comparisons between sample groups: different preservation methods did not generate differentially-expressed probes (DEPs) within MM or AML sample groups, or substantially affect the many DEPs distinguishing between these groups. Differences were found by gene set enrichment analysis, but were dismissible because of instability with permutation of sample labels, unbalanced restriction to TRIzol aliquots, inconsistency between MM and AML groups, and lack of biological plausibility. Bead-level comparisons found many DEPs within sample pairs, but most (73%) were <2-fold changed. There was no consistent evidence that TRIzol causes premature RT termination. Instead, a subset of DEPs were systematically due to increased signals in TRIzol-preserved samples from probes near the 5’ end of transcripts, suggesting better mRNA preservation with TRIzol. Conclusions TRIzol preserves RNA quality well, without a deleterious effect on GEP. Samples stored frozen with and without TRIzol may be compared by GEP with only minor concern for systematic artifacts. Impact The standard practice of prolonged sample storage in TRIzol is suitable for GEP. PMID:20805315

  3. A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae

    PubMed Central

    Reider Apel, Amanda; d'Espaux, Leo; Wehrs, Maren; Sachs, Daniel; Li, Rachel A.; Tong, Gary J.; Garber, Megan; Nnadi, Oge; Zhuang, William; Hillson, Nathan J.; Keasling, Jay D.; Mukhopadhyay, Aindrila

    2017-01-01

    Despite the extensive use of Saccharomyces cerevisiae as a platform for synthetic biology, strain engineering remains slow and laborious. Here, we employ CRISPR/Cas9 technology to build a cloning-free toolkit that addresses commonly encountered obstacles in metabolic engineering, including chromosomal integration locus and promoter selection, as well as protein localization and solubility. The toolkit includes 23 Cas9-sgRNA plasmids, 37 promoters of various strengths and temporal expression profiles, and 10 protein-localization, degradation and solubility tags. We facilitated the use of these parts via a web-based tool, that automates the generation of DNA fragments for integration. Our system builds upon existing gene editing methods in the thoroughness with which the parts are standardized and characterized, the types and number of parts available and the ease with which our methodology can be used to perform genetic edits in yeast. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important enzyme, taxadiene synthase (TXS). This approach enabled us to diagnose an issue with TXS solubility, the resolution of which yielded a 25-fold improvement in taxadiene production. PMID:27899650

  4. A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae.

    PubMed

    Reider Apel, Amanda; d'Espaux, Leo; Wehrs, Maren; Sachs, Daniel; Li, Rachel A; Tong, Gary J; Garber, Megan; Nnadi, Oge; Zhuang, William; Hillson, Nathan J; Keasling, Jay D; Mukhopadhyay, Aindrila

    2017-01-09

    Despite the extensive use of Saccharomyces cerevisiae as a platform for synthetic biology, strain engineering remains slow and laborious. Here, we employ CRISPR/Cas9 technology to build a cloning-free toolkit that addresses commonly encountered obstacles in metabolic engineering, including chromosomal integration locus and promoter selection, as well as protein localization and solubility. The toolkit includes 23 Cas9-sgRNA plasmids, 37 promoters of various strengths and temporal expression profiles, and 10 protein-localization, degradation and solubility tags. We facilitated the use of these parts via a web-based tool, that automates the generation of DNA fragments for integration. Our system builds upon existing gene editing methods in the thoroughness with which the parts are standardized and characterized, the types and number of parts available and the ease with which our methodology can be used to perform genetic edits in yeast. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important enzyme, taxadiene synthase (TXS). This approach enabled us to diagnose an issue with TXS solubility, the resolution of which yielded a 25-fold improvement in taxadiene production.

  5. A blood-based gene expression and signaling pathway analysis to differentiate between high and low grade gliomas

    PubMed Central

    Ponnampalam, Stephen N.; Kamaluddin, Nor Rizan; Zakaria, Zubaidah; Matheneswaran, Vickneswaran; Ganesan, Dharmendra; Haspani, Mohammed Saffari; Ryten, Mina; Hardy, John A.

    2016-01-01

    The aims of the present study were to undertake gene expression profiling of the blood of glioma patients to determine key genetic components of signaling pathways and to develop a panel of genes that could be used as a potential blood-based biomarker to differentiate between high and low grade gliomas, non-gliomas and control samples. In this study, blood samples were obtained from glioma patients, non-glioma and control subjects. Ten samples each were obtained from patients with high and low grade tumours, respectively, ten samples from non-glioma patients and twenty samples from control subjects. Total RNA was isolated from each sample after which first and second strand synthesis was performed. The resulting cRNA was then hybridized with the Agilent Whole Human Genome (4×44K) microarray chip according to the manufacturer's instructions. Universal Human Reference RNA and samples were labeled with Cy3 CTP and Cy5 CTP, respectively. Microarray data were analyzed by the Agilent Gene Spring 12.1V software using stringent criteria which included at least a 2-fold difference in gene expression between samples. Statistical analysis was performed using the unpaired Student's t-test with a P<0.01. Pathway enrichment was also performed, with key genes selected for validation using droplet digital polymerase chain reaction (ddPCR). The gene expression profiling indicated that were a substantial number of genes that were differentially expressed with more than a 2-fold change (P<0.01) between each of the four different conditions. We selected key genes within significant pathways that were analyzed through pathway enrichment. These key genes included regulators of cell proliferation, transcription factors, cytokines and tumour suppressor genes. In the present study, we showed that key genes involved in significant and well established pathways, could possibly be used as a potential blood-based biomarker to differentiate between high and low grade gliomas, non-gliomas and

  6. A blood-based gene expression and signaling pathway analysis to differentiate between high and low grade gliomas.

    PubMed

    Ponnampalam, Stephen N; Kamaluddin, Nor Rizan; Zakaria, Zubaidah; Matheneswaran, Vickneswaran; Ganesan, Dharmendra; Haspani, Mohammed Saffari; Ryten, Mina; Hardy, John A

    2017-01-01

    The aims of the present study were to undertake gene expression profiling of the blood of glioma patients to determine key genetic components of signaling pathways and to develop a panel of genes that could be used as a potential blood-based biomarker to differentiate between high and low grade gliomas, non-gliomas and control samples. In this study, blood samples were obtained from glioma patients, non-glioma and control subjects. Ten samples each were obtained from patients with high and low grade tumours, respectively, ten samples from non-glioma patients and twenty samples from control subjects. Total RNA was isolated from each sample after which first and second strand synthesis was performed. The resulting cRNA was then hybridized with the Agilent Whole Human Genome (4x44K) microarray chip according to the manufacturer's instructions. Universal Human Reference RNA and samples were labeled with Cy3 CTP and Cy5 CTP, respectively. Microarray data were analyzed by the Agilent Gene Spring 12.1V software using stringent criteria which included at least a 2-fold difference in gene expression between samples. Statistical analysis was performed using the unpaired Student's t-test with a p<0.01. Pathway enrichment was also performed, with key genes selected for validation using droplet digital polymerase chain reaction (ddPCR). The gene expression profiling indicated that were a substantial number of genes that were differentially expressed with more than a 2-fold change (p<0.01) between each of the four different conditions. We selected key genes within significant pathways that were analyzed through pathway enrichment. These key genes included regulators of cell proliferation, transcription factors, cytokines and tumour suppressor genes. In the present study, we showed that key genes involved in significant and well established pathways, could possibly be used as a potential blood-based biomarker to differentiate between high and low grade gliomas, non-gliomas and

  7. Host-Based Peripheral Blood Gene Expression Analysis for Diagnosis of Infectious Diseases.

    PubMed

    Holcomb, Zachary E; Tsalik, Ephraim L; Woods, Christopher W; McClain, Micah T

    2017-02-01

    Emerging pandemic infectious threats, inappropriate antibacterial use contributing to multidrug resistance, and increased morbidity and mortality from diagnostic delays all contribute to a need for improved diagnostics in the field of infectious diseases. Historically, diagnosis of infectious diseases has relied on pathogen detection; however, a novel concept to improve diagnostics in infectious diseases relies instead on the detection of changes in patterns of gene expression in circulating white blood cells in response to infection. Alterations in peripheral blood gene expression in the infected state are robust and reproducible, yielding diagnostic and prognostic information to help facilitate patient treatment decisions.

  8. A novel mutual information-based Boolean network inference method from time-series gene expression data

    PubMed Central

    Barman, Shohag; Kwon, Yung-Keun

    2017-01-01

    Background Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately. Results In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI) method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods. Conclusions Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network. PMID:28178334

  9. Interaction-Based Feature Selection for Uncovering Cancer Driver Genes Through Copy Number-Driven Expression Level.

    PubMed

    Park, Heewon; Niida, Atsushi; Imoto, Seiya; Miyano, Satoru

    2017-02-01

    Driver gene selection is crucial to understand the heterogeneous system of cancer. To identity cancer driver genes, various statistical strategies have been proposed, especially the L1-type regularization methods have drawn a large amount of attention. However, the statistical approaches have been developed purely from algorithmic and statistical point, and the existing studies have applied the statistical approaches to genomic data analysis without consideration of biological knowledge. We consider a statistical strategy incorporating biological knowledge to identify cancer driver gene. The alterations of copy number have been considered to driver cancer pathogenesis processes, and the region of strong interaction of copy number alterations and expression levels was known as a tumor-related symptom. We incorporate the influence of copy number alterations on expression levels to cancer driver gene-selection processes. To quantify the dependence of copy number alterations on expression levels, we consider [Formula: see text] and [Formula: see text] effects of copy number alterations on expression levels of genes, and incorporate the symptom of tumor pathogenesis to gene-selection procedures. We then proposed an interaction-based feature-selection strategy based on the adaptive L1-type regularization and random lasso procedures. The proposed method imposes a large amount of penalty on genes corresponding to a low dependency of the two features, thus the coefficients of the genes are estimated to be small or exactly 0. It implies that the proposed method can provide biologically relevant results in cancer driver gene selection. Monte Carlo simulations and analysis of the Cancer Genome Atlas (TCGA) data show that the proposed strategy is effective for high-dimensional genomic data analysis. Furthermore, the proposed method provides reliable and biologically relevant results for cancer driver gene selection in TCGA data analysis.

  10. Digital Gene Expression Analysis Based on De Novo Transcriptome Assembly Reveals New Genes Associated with Floral Organ Differentiation of the Orchid Plant Cymbidium ensifolium

    PubMed Central

    Yang, Fengxi; Zhu, Genfa

    2015-01-01

    Cymbidium ensifolium belongs to the genus Cymbidium of the orchid family. Owing to its spectacular flower morphology, C. ensifolium has considerable ecological and cultural value. However, limited genetic data is available for this non-model plant, and the molecular mechanism underlying floral organ identity is still poorly understood. In this study, we characterize the floral transcriptome of C. ensifolium and present, for the first time, extensive sequence and transcript abundance data of individual floral organs. After sequencing, over 10 Gb clean sequence data were generated and assembled into 111,892 unigenes with an average length of 932.03 base pairs, including 1,227 clusters and 110,665 singletons. Assembled sequences were annotated with gene descriptions, gene ontology, clusters of orthologous group terms, the Kyoto Encyclopedia of Genes and Genomes, and the plant transcription factor database. From these annotations, 131 flowering-associated unigenes, 61 CONSTANS-LIKE (COL) unigenes and 90 floral homeotic genes were identified. In addition, four digital gene expression libraries were constructed for the sepal, petal, labellum and gynostemium, and 1,058 genes corresponding to individual floral organ development were identified. Among them, eight MADS-box genes were further investigated by full-length cDNA sequence analysis and expression validation, which revealed two APETALA1/AGL9-like MADS-box genes preferentially expressed in the sepal and petal, two AGAMOUS-like genes particularly restricted to the gynostemium, and four DEF-like genes distinctively expressed in different floral organs. The spatial expression of these genes varied distinctly in different floral mutant corresponding to different floral morphogenesis, which validated the specialized roles of them in floral patterning and further supported the effectiveness of our in silico analysis. This dataset generated in our study provides new insights into the molecular mechanisms underlying floral

  11. Gene Expression Music Algorithm-Based Characterization of the Ewing Sarcoma Stem Cell Signature

    PubMed Central

    2016-01-01

    Gene Expression Music Algorithm (GEMusicA) is a method for the transformation of DNA microarray data into melodies that can be used for the characterization of differentially expressed genes. Using this method we compared gene expression profiles from endothelial cells (EC), hematopoietic stem cells, neuronal stem cells, embryonic stem cells (ESC), and mesenchymal stem cells (MSC) and defined a set of genes that can discriminate between the different stem cell types. We analyzed the behavior of public microarray data sets from Ewing sarcoma (“Ewing family tumors,” EFT) cell lines and biopsies in GEMusicA after prefiltering DNA microarray data for the probe sets from the stem cell signature. Our results demonstrate that individual Ewing sarcoma cell lines have a high similarity to ESC or EC. Ewing sarcoma cell lines with inhibited Ewing sarcoma breakpoint region 1-Friend leukemia virus integration 1 (EWSR1-FLI1) oncogene retained the similarity to ESC and EC. However, correlation coefficients between GEMusicA-processed expression data between EFT and ESC decreased whereas correlation coefficients between EFT and EC as well as between EFT and MSC increased after knockdown of EWSR1-FLI1. Our data support the concept of EFT being derived from cells with features of embryonic and endothelial cells. PMID:27446218

  12. Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers.

    PubMed

    Ashworth, Justin; Bernard, Brady; Reynolds, Sheila; Plaisier, Christopher L; Shmulevich, Ilya; Baliga, Nitin S

    2014-12-01

    Thousands of unique mutations in transcription factors (TFs) arise in cancers, and the functional and biological roles of relatively few of these have been characterized. Here, we used structure-based methods developed specifically for DNA-binding proteins to systematically predict the consequences of mutations in several TFs that are frequently mutated in cancers. The explicit consideration of protein-DNA interactions was crucial to explain the roles and prevalence of mutations in TP53 and RUNX1 in cancers, and resulted in a higher specificity of detection for known p53-regulated genes among genetic associations between TP53 genotypes and genome-wide expression in The Cancer Genome Atlas, compared to existing methods of mutation assessment. Biophysical predictions also indicated that the relative prevalence of TP53 missense mutations in cancer is proportional to their thermodynamic impacts on protein stability and DNA binding, which is consistent with the selection for the loss of p53 transcriptional function in cancers. Structure and thermodynamics-based predictions of the impacts of missense mutations that focus on specific molecular functions may be increasingly useful for the precise and large-scale inference of aberrant molecular phenotypes in cancer and other complex diseases.

  13. Entropy-based cluster validation and estimation of the number of clusters in gene expression data.

    PubMed

    Novoselova, Natalia; Tom, Igor

    2012-10-01

    Many external and internal validity measures have been proposed in order to estimate the number of clusters in gene expression data but as a rule they do not consider the analysis of the stability of the groupings produced by a clustering algorithm. Based on the approach assessing the predictive power or stability of a partitioning, we propose the new measure of cluster validation and the selection procedure to determine the suitable number of clusters. The validity measure is based on the estimation of the "clearness" of the consensus matrix, which is the result of a resampling clustering scheme or consensus clustering. According to the proposed selection procedure the stable clustering result is determined with the reference to the validity measure for the null hypothesis encoding for the absence of clusters. The final number of clusters is selected by analyzing the distance between the validity plots for initial and permutated data sets. We applied the selection procedure to estimate the clustering results on several datasets. As a result the proposed procedure produced an accurate and robust estimate of the number of clusters, which are in agreement with the biological knowledge and gold standards of cluster quality.

  14. Gene expression analysis of biopsy samples reveals critical limitations of transcriptome‐based molecular classifications of hepatocellular carcinoma

    PubMed Central

    Makowska, Zuzanna; Boldanova, Tujana; Adametz, David; Quagliata, Luca; Vogt, Julia E.; Dill, Michael T.; Matter, Mathias S.; Roth, Volker; Terracciano, Luigi

    2016-01-01

    Abstract Molecular classification of hepatocellular carcinomas (HCC) could guide patient stratification for personalized therapies targeting subclass‐specific cancer ‘driver pathways’. Currently, there are several transcriptome‐based molecular classifications of HCC with different subclass numbers, ranging from two to six. They were established using resected tumours that introduce a selection bias towards patients without liver cirrhosis and with early stage HCCs. We generated and analyzed gene expression data from paired HCC and non‐cancerous liver tissue biopsies from 60 patients as well as five normal liver samples. Unbiased consensus clustering of HCC biopsy profiles identified 3 robust classes. Class membership correlated with survival, tumour size and with Edmondson and Barcelona Clinical Liver Cancer (BCLC) stage. When focusing only on the gene expression of the HCC biopsies, we could validate previously reported classifications of HCC based on expression patterns of signature genes. However, the subclass‐specific gene expression patterns were no longer preserved when the fold‐change relative to the normal tissue was used. The majority of genes believed to be subclass‐specific turned out to be cancer‐related genes differentially regulated in all HCC patients, with quantitative rather than qualitative differences between the molecular subclasses. With the exception of a subset of samples with a definitive β‐catenin gene signature, biological pathway analysis could not identify class‐specific pathways reflecting the activation of distinct oncogenic programs. In conclusion, we have found that gene expression profiling of HCC biopsies has limited potential to direct therapies that target specific driver pathways, but can identify subgroups of patients with different prognosis. PMID:27499918

  15. Histogenetic compartments of the mouse centromedial and extended amygdala based on gene expression patterns during development.

    PubMed

    García-López, Margarita; Abellán, Antonio; Legaz, Isabel; Rubenstein, John L R; Puelles, Luis; Medina, Loreta

    2008-01-01

    The amygdala controls emotional and social behavior and regulates instinctive reflexes such as defense and reproduction by way of descending projections to the hypothalamus and brainstem. The descending amygdalar projections are suggested to show a cortico-striato-pallidal organization similar to that of the basal ganglia (Swanson [2000] Brain Res 886:113-164). To test this model we investigated the embryological origin and molecular properties of the mouse centromedial and extended amygdalar subdivisions, which constitute major sources of descending projections. We analyzed the distribution of key regulatory genes that show restricted expression patterns within the subpallium (Dlx5, Nkx2.1, Lhx6, Lhx7/8, Lhx9, Shh, and Gbx1), as well as genes considered markers for specific subpallial neuronal subpopulations. Our results indicate that most of the centromedial and extended amygdala is formed by cells derived from multiple subpallial subdivisions. Contrary to a previous suggestion, only the central--but not the medial--amygdala derives from the lateral ganglionic eminence and has striatal-like features. The medial amygdala and a large part of the extended amygdala (including the bed nucleus of the stria terminalis) consist of subdivisions or cell groups that derive from subpallial, pallial (ventral pallium), or extratelencephalic progenitor domains. The subpallial part includes derivatives from the medial ganglionic eminence, the anterior peduncular area, and possibly a novel subdivision, called here commissural preoptic area, located at the base of the septum and related to the anterior commissure. Our study provides a molecular and morphological foundation for understanding the complex embryonic origins and adult organization of the centromedial and extended amygdala.

  16. Histogenetic Compartments of the Mouse Centromedial and Extended Amygdala Based on Gene Expression Patterns during Development

    PubMed Central

    García-López, Margarita; Abellán, Antonio; Legaz, Isabel; Rubenstein, John L.R.; Puelles, Luis; Medina, Loreta

    2016-01-01

    The amygdala controls emotional and social behavior and regulates instinctive reflexes such as defense and reproduction by way of descending projections to the hypothalamus and brainstem. The descending amygdalar projections are suggested to show a cortico-striato-pallidal organization similar to that of the basal ganglia (Swanson [2000] Brain Res 886:113–164). To test this model we investigated the embryological origin and molecular properties of the mouse centromedial and extended amygdalar subdivisions, which constitute major sources of descending projections. We analyzed the distribution of key regulatory genes that show restricted expression patterns within the subpallium (Dlx5, Nkx2.1, Lhx6, Lhx7/8, Lhx9, Shh, and Gbx1), as well as genes considered markers for specific subpallial neuronal subpopulations. Our results indicate that most of the centromedial and extended amygdala is formed by cells derived from multiple subpallial subdivisions. Contrary to a previous suggestion, only the central—but not the medial—amygdala derives from the lateral ganglionic eminence and has striatal-like features. The medial amygdala and a large part of the extended amygdala (including the bed nucleus of the stria terminalis) consist of subdivisions or cell groups that derive from subpallial, pallial (ventral pallium), or extratelencephalic progenitor domains. The subpallial part includes derivatives from the medial ganglionic eminence, the anterior peduncular area, and possibly a novel subdivision, called here commissural preoptic area, located at the base of the septum and related to the anterior commissure. Our study provides a molecular and morphological foundation for understanding the complex embryonic origins and adult organization of the centromedial and extended amygdala. PMID:17990271

  17. Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women

    PubMed Central

    Niu, Tianhua; Zhou, Yu; Zhang, Lan; Zeng, Yong; Zhu, Wei; Wang, Yu-ping; Deng, Hong-wen

    2016-01-01

    Background Existing microarray studies of bone mineral density (BMD) have been critical for understanding the pathophysiology of osteoporosis, and have identified a number of candidate genes. However, these studies were limited by their relatively small sample sizes and were usually analyzed individually. Here, we propose a novel network-based meta-analysis approach that combines data across six microarray studies to identify functional modules from human protein-protein interaction (PPI) data, and highlight several differentially expressed genes (DEGs) and a functional module that may play an important role in BMD regulation in women. Methods Expression profiling studies were identified by searching PubMed, Gene Expression Omnibus (GEO) and ArrayExpress. Two meta-analysis methods were applied across different gene expression profiling studies. The first, a nonparametric Fisher’s method, combined p-values from individual experiments to identify genes with large effect sizes. The second method combined effect sizes from individual datasets into a meta-effect size to gain a higher precision of effect size estimation across all datasets. Genes with Q test’s p-values < 0.05 or I2 values > 50% were assessed by a random effects model and the remainder by a fixed effects model. Using Fisher’s combined p-values, functional modules were identified through an integrated analysis of microarray data in the context of large protein–protein interaction (PPI) networks. Two previously published meta-analysis studies of genome-wide association (GWA) datasets were used to determine whether these module genes were genetically associated with BMD. Pathway enrichment analysis was performed with a hypergeometric test. Results Six gene expression datasets were identified, which included a total of 249 (129 high BMD and 120 low BMD) female subjects. Using a network-based meta-analysis, a consensus module containing 58 genes (nodes) and 83 edges was detected. Pathway enrichment

  18. Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle.

    PubMed

    Song, Hyun-Seob; Reifman, Jaques; Wallqvist, Anders

    2014-01-01

    Prediction of possible flux distributions in a metabolic network provides detailed phenotypic information that links metabolism to cellular physiology. To estimate metabolic steady-state fluxes, the most common approach is to solve a set of macroscopic mass balance equations subjected to stoichiometric constraints while attempting to optimize an assumed optimal objective function. This assumption is justifiable in specific cases but may be invalid when tested across different conditions, cell populations, or other organisms. With an aim to providing a more consistent and reliable prediction of flux distributions over a wide range of conditions, in this article we propose a framework that uses the flux minimization principle to predict active metabolic pathways from mRNA expression data. The proposed algorithm minimizes a weighted sum of flux magnitudes, while biomass production can be bounded to fit an ample range from very low to very high values according to the analyzed context. We have formulated the flux weights as a function of the corresponding enzyme reaction's gene expression value, enabling the creation of context-specific fluxes based on a generic metabolic network. In case studies of wild-type Saccharomyces cerevisiae, and wild-type and mutant Escherichia coli strains, our method achieved high prediction accuracy, as gauged by correlation coefficients and sums of squared error, with respect to the experimentally measured values. In contrast to other approaches, our method was able to provide quantitative predictions for both model organisms under a variety of conditions. Our approach requires no prior knowledge or assumption of a context-specific metabolic functionality and does not require trial-and-error parameter adjustments. Thus, our framework is of general applicability for modeling the transcription-dependent metabolism of bacteria and yeasts.

  19. RNase One Gene Isolation, Expression, and Affinity Purification Models Research Experimental Progression and Culminates with Guided Inquiry-Based Experiments

    ERIC Educational Resources Information Center

    Bailey, Cheryl P.

    2009-01-01

    This new biochemistry laboratory course moves through a progression of experiments that generates a platform for guided inquiry-based experiments. RNase One gene is isolated from prokaryotic genomic DNA, expressed as a tagged protein, affinity purified, and tested for activity and substrate specificity. Student pairs present detailed explanations…

  20. Gene ontology based characterization of expressed sequence tags (ESTs) of Brassica rapa cv. Osome.

    PubMed

    Arasan, Senthil Kumar Thamil; Park, Jong-In; Ahmed, Nasar Uddin; Jung, Hee-Jeong; Lee, In-Ho; Cho, Yong-Gu; Lim, Yong-Pyo; Kang, Kwon-Kyoo; Nou, Ill-Sup

    2013-07-01

    Chinese cabbage (Brassica rapa) is widely recognized for its economic importance and contribution to human nutrition but abiotic and biotic stresses are main obstacle for its quality, nutritional status and production. In this study, 3,429 Express Sequence Tag (EST) sequences were generated from B. rapa cv. Osome cDNA library and the unique transcripts were classified functionally using a gene ontology (GO) hierarchy, Kyoto encyclopedia of genes and genomes (KEGG). KEGG orthology and the structural domain data were obtained from the biological database for stress related genes (SRG). EST datasets provided a wide outlook of functional characterization of B. rapa cv. Osome. In silico analysis revealed % 83 of ESTs to be well annotated towards reeds one dimensional concept. Clustering of ESTs returned 333 contigs and 2,446 singlets, giving a total of 3,284 putative unigene sequences. This dataset contained 1,017 EST sequences functionally annotated to stress responses and from which expression of randomly selected SRGs were analyzed against cold, salt, drought, ABA, water and PEG stresses. Most of the SRGs showed differentially expression against these stresses. Thus, the EST dataset is very important for discovering the potential genes related to stress resistance in Chinese cabbage, and can be of useful resources for genetic engineering of Brassica sp.

  1. Impaired brain StAR and HSP70 gene expression in zebrafish exposed to Methyl-Parathion based insecticide.

    PubMed

    da Rosa, João Gabriel Santos; Koakoski, Gessi; Piato, Angelo L; Bogo, Maurício Reis; Bonan, Carla Denise; Barcellos, Leonardo José Gil

    2016-01-01

    Fish production ponds and natural water body areas located in close proximity to agricultural fields receive water with variable amounts of agrochemicals, and consequently, compounds that produce adverse effects may reach nontarget organisms. The aim of this study was to investigate whether waterborne methyl-parathion-based insecticide (MPBI) affected gene expression patterns of brain glucocorticoid receptor (GR), steroidogenic acute regulatory protein (StAR), and heat shock protein 70 (hsp70) in adult zebrafish (Danio rerio) exposed to this chemical for 96 h. Treated fish exposed to MPBI-contaminated water showed an inhibition of brain StAR and hsp70 gene expression. Data demonstrated that MPBI produced a decrease brain StAR and hsp70 gene expression.

  2. Hessian regularization based symmetric nonnegative matrix factorization for clustering gene expression and microbiome data.

    PubMed

    Ma, Yuanyuan; Hu, Xiaohua; He, Tingting; Jiang, Xingpeng

    2016-12-01

    Nonnegative matrix factorization (NMF) has received considerable attention due to its interpretation of observed samples as combinations of different components, and has been successfully used as a clustering method. As an extension of NMF, Symmetric NMF (SNMF) inherits the advantages of NMF. Unlike NMF, however, SNMF takes a nonnegative similarity matrix as an input, and two lower rank nonnegative matrices (H, H(T)) are computed as an output to approximate the original similarity matrix. Laplacian regularization has improved the clustering performance of NMF and SNMF. However, Laplacian regularization (LR), as a classic manifold regularization method, suffers some problems because of its weak extrapolating ability. In this paper, we propose a novel variant of SNMF, called Hessian regularization based symmetric nonnegative matrix factorization (HSNMF), for this purpose. In contrast to Laplacian regularization, Hessian regularization fits the data perfectly and extrapolates nicely to unseen data. We conduct extensive experiments on several datasets including text data, gene expression data and HMP (Human Microbiome Project) data. The results show that the proposed method outperforms other methods, which suggests the potential application of HSNMF in biological data clustering.

  3. Proposed method for dimensionality reduction based on framework in gene expression domain.

    PubMed

    Macedo, D C; Ishikawa, E C M; Santos, C B; Matos, S N; Borges, H B; Francisco, A C

    2014-12-12

    The excessive use of attributes may affect the search for patterns and extraction of useful knowledge, because they harm the learning performance of algorithms in both speed and success rate. The use of dimensionality reduction methods is therefore an important alternative; however, these methods do not deal with the reduction of attributes in a specific area. This article presents a method based on framework concepts of domain for reducing attributes in a domain. The input method is a set of databases related to a domain, and the main process is the identification of common and variable attributes, plus the reduction of attributes in the original database. The proposed method was applied in the gene expression domain, using databases. The method can be used to analyze the most relevant attributes in a specific domain, granting greater confidence for models created for the application of a data mining task, thus, a previously known method in data mining. Attribute selection was also applied in the three databases for the comparison of the results. Analyses of the results using the criterion of cross-validation revealed that the employment of the methods resulted in the improvement of success rates compared to the databases containing the full range of attributes.

  4. SNP-based large-scale identification of allele-specific gene expression in human B cells.

    PubMed

    Song, Min-Young; Kim, Hye-Eun; Kim, Sun; Choi, Ick-Hwa; Lee, Jong-Keuk

    2012-02-10

    Polymorphism and variations in gene expression provide the genetic basis for human variation. Allelic variation of gene expression, in particular, may play a crucial role in phenotypic variation and disease susceptibility. To identify genes with allelic expression in human cells, we genotyped genomic DNA and cDNA isolated from 31 immortalized B cell lines from three Centre d'Etude du Polymorphisme Humain (CEPH) families using high-density single-nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs. We identified seven SNPs in five genes with monoallelic expression, 146 SNPs in 125 genes with allelic imbalance in expression with preferentially higher expression of one allele in a heterozygous individual. The monoallelically expressed genes (ERAP2, MDGA1, LOC644422, SDCCAG3P1 and CLTCL1) were regulated by cis-acting, non-imprinted differential allelic control. In addition, all monoallelic gene expression patterns and allelic imbalances in gene expression in B cells were transmitted from parents to offspring in the pedigree, indicating genetic transmission of allelic gene expression. Furthermore, frequent allele substitution, probably due to RNA editing, was also observed in 21 genes in 23 SNPs as well as in 48 SNPs located in regions containing no known genes. In this study, we demonstrated that allelic gene expression is frequently observed in human B cells, and SNP chips are very useful tools for detecting allelic gene expression. Overall, our data provide a valuable framework for better understanding allelic gene expression in human B cells.

  5. Gene expression-based biological test for major depressive disorder: an advanced study

    PubMed Central

    Watanabe, Shin-ya; Numata, Shusuke; Iga, Jun-ichi; Kinoshita, Makoto; Umehara, Hidehiro; Ishii, Kazuo; Ohmori, Tetsuro

    2017-01-01

    Purpose Recently, we could distinguished patients with major depressive disorder (MDD) from nonpsychiatric controls with high accuracy using a panel of five gene expression markers (ARHGAP24, HDAC5, PDGFC, PRNP, and SLC6A4) in leukocyte. In the present study, we examined whether this biological test is able to discriminate patients with MDD from those without MDD, including those with schizophrenia and bipolar disorder. Patients and methods We measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR), and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD. Results This expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively. Conclusion Further research to identify MDD-specific markers is needed to improve the performance of this biological test. PMID:28260899

  6. Principal Components Analysis Based Unsupervised Feature Extraction Applied to Gene Expression Analysis of Blood from Dengue Haemorrhagic Fever Patients

    PubMed Central

    Taguchi, Y-h.

    2017-01-01

    Dengue haemorrhagic fever (DHF) sometimes occurs after recovery from the disease caused by Dengue virus (DENV), and is often fatal. However, the mechanism of DHF has not been determined, possibly because no suitable methodologies are available to analyse this disease. Therefore, more innovative methods are required to analyse the gene expression profiles of DENV-infected patients. Principal components analysis (PCA)-based unsupervised feature extraction (FE) was applied to the gene expression profiles of DENV-infected patients, and an integrated analysis of two independent data sets identified 46 genes as critical for DHF progression. PCA using only these 46 genes rendered the two data sets highly consistent. The application of PCA to the 46 genes of an independent third data set successfully predicted the progression of DHF. A fourth in vitro data set confirmed the identification of the 46 genes. These 46 genes included interferon- and heme-biosynthesis-related genes. The former are enriched in binding sites for STAT1, STAT2, and IRF1, which are associated with DHF-promoting antibody-dependent enhancement, whereas the latter are considered to be related to the dysfunction of spliceosomes, which may mediate haemorrhage. These results are outcomes that other type of bioinformatic analysis could hardly achieve. PMID:28276456

  7. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    PubMed

    Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2015-01-01

    Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

  8. Correlation of gene expression and contaminat concentrations in wild largescale suckers: a field-based study

    USGS Publications Warehouse

    Christiansen, Helena E.; Mehinto, Alvina C.; Yu, Fahong; Perry, Russell W.; Denslow, Nancy D.; Maule, Alec G.; Mesa, Matthew G.

    2014-01-01

    Toxic compounds such as organochlorine pesticides (OCs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ether flame retardants (PBDEs) have been detected in fish, birds, and aquatic mammals that live in the Columbia River or use food resources from within the river. We developed a custom microarray for largescale suckers (Catostomus macrocheilus) and used it to investigate the molecular effects of contaminant exposure on wild fish in the Columbia River. Using Significance Analysis of Microarrays (SAM) we identified 72 probes representing 69 unique genes with expression patterns that correlated with hepatic tissue levels of OCs, PCBs, or PBDEs. These genes were involved in many biological processes previously shown to respond to contaminant exposure, including drug and lipid metabolism, apoptosis, cellular transport, oxidative stress, and cellular chaperone function. The relation between gene expression and contaminant concentration suggests that these genes may respond to environmental contaminant exposure and are promising candidates for further field and laboratory studies to develop biomarkers for monitoring exposure of wild fish to contaminant mixtures found in the Columbia River Basin. The array developed in this study could also be a useful tool for studies involving endangered sucker species and other sucker species used in contaminant research.

  9. Expression profile based gene clusters for ischemic stroke detection Whole blood gene clusters for ischemic stroke detection

    PubMed Central

    Adamski, Mateusz G; Li, Yan; Wagner, Erin; Yu, Hua; Seales-Bailey, Chloe; Soper, Steven A; Murphy, Michael; Baird, Alison E

    2014-01-01

    In microarray studies alterations in gene expression in circulating leukocytes have shown utility for ischemic stroke diagnosis. We studied forty candidate markers identified in three gene expression profiles to (1) quantitate individual transcript expression, (2) identify transcript clusters and (3) assess the clinical diagnostic utility of the clusters identified for ischemic stroke detection. Using high throughput next generation qPCR 16 of the 40 transcripts were significantly up-regulated in stroke patients relative to control subjects (p<0.05). Six clusters of between 5 and 7 transcripts discriminated between stroke and control (p values between 1.01e-9 and 0.03). A 7 transcript cluster containing PLBD1, PYGL, BST1, DUSP1, FOS, VCAN and FCGR1A showed high accuracy for stroke classification (AUC=0.854). These results validate and improve upon the diagnostic value of transcripts identified in microarray studies for ischemic stroke. The clusters identified show promise for acute ischemic stroke detection. PMID:25135788

  10. Predicting gene targets of perturbations via network-based filtering of mRNA expression compendia

    PubMed Central

    Cosgrove, Elissa J.; Zhou, Yingchun; Gardner, Timothy S.; Kolaczyk, Eric D.

    2008-01-01

    Motivation: DNA microarrays are routinely applied to study diseased or drug-treated cell populations. A critical challenge is distinguishing the genes directly affected by these perturbations from the hundreds of genes that are indirectly affected. Here, we developed a sparse simultaneous equation model (SSEM) of mRNA expression data and applied Lasso regression to estimate the model parameters, thus constructing a network model of gene interaction effects. This inferred network model was then used to filter data from a given experimental condition of interest and predict the genes directly targeted by that perturbation. Results: Our proposed SSEM–Lasso method demonstrated substantial improvement in sensitivity compared with other tested methods for predicting the targets of perturbations in both simulated datasets and microarray compendia. In simulated data, for two different network types, and over a wide range of signal-to-noise ratios, our algorithm demonstrated a 167% increase in sensitivity on average for the top 100 ranked genes, compared with the next best method. Our method also performed well in identifying targets of genetic perturbations in microarray compendia, with up to a 24% improvement in sensitivity on average for the top 100 ranked genes. The overall performance of our network-filtering method shows promise for identifying the direct targets of genetic dysregulation in cancer and disease from expression profiles. Availability: Microarray data are available at the Many Microbe Microarrays Database (M3D, http://m3d.bu.edu). Algorithm scripts are available at the Gardner Lab website (http://gardnerlab.bu.edu/SSEMLasso). Contact: kolaczyk@math.bu.edu Supplementary information: Supplementary Data are available at Bioinformatics on line. PMID:18779235

  11. Gene Expression Profiling of Development and Anthocyanin Accumulation in Kiwifruit (Actinidia chinensis) Based on Transcriptome Sequencing

    PubMed Central

    Zeng, Shaohua; Xiao, Gong; Wang, Gan; Wang, Ying; Peng, Ming; Huang, Hongwen

    2015-01-01

    Red-fleshed kiwifruit (Actinidia chinensis Planch. ‘Hongyang’) is a promising commercial cultivar due to its nutritious value and unique flesh color, derived from vitamin C and anthocyanins. In this study, we obtained transcriptome data of ‘Hongyang’ from seven developmental stages using Illumina sequencing. We mapped 39–54 million reads to the recently sequenced kiwifruit genome and other databases to define gene structure, to analyze alternative splicing, and to quantify gene transcript abundance at different developmental stages. The transcript profiles throughout red kiwifruit development were constructed and analyzed, with a focus on the biosynthesis and metabolism of compounds such as phytohormones, sugars, starch and L-ascorbic acid, which are indispensable for the development and formation of quality fruit. Candidate genes for these pathways were identified through MapMan and phylogenetic analysis. The transcript levels of genes involved in sucrose and starch metabolism were consistent with the change in soluble sugar and starch content throughout kiwifruit development. The metabolism of L-ascorbic acid was very active, primarily through the L-galactose pathway. The genes responsible for the accumulation of anthocyanin in red kiwifruit were identified, and their expression levels were investigated during kiwifruit development. This survey of gene expression during kiwifruit development paves the way for further investigation of the development of this uniquely colored and nutritious fruit and reveals which factors are needed for high quality fruit formation. This transcriptome data and its analysis will be useful for improving kiwifruit genome annotation, for basic fruit molecular biology research, and for kiwifruit breeding and improvement. PMID:26301713

  12. Gene Expression Profiling of Development and Anthocyanin Accumulation in Kiwifruit (Actinidia chinensis) Based on Transcriptome Sequencing.

    PubMed

    Li, Wenbin; Liu, Yifei; Zeng, Shaohua; Xiao, Gong; Wang, Gan; Wang, Ying; Peng, Ming; Huang, Hongwen

    2015-01-01

    Red-fleshed kiwifruit (Actinidia chinensis Planch. 'Hongyang') is a promising commercial cultivar due to its nutritious value and unique flesh color, derived from vitamin C and anthocyanins. In this study, we obtained transcriptome data of 'Hongyang' from seven developmental stages using Illumina sequencing. We mapped 39-54 million reads to the recently sequenced kiwifruit genome and other databases to define gene structure, to analyze alternative splicing, and to quantify gene transcript abundance at different developmental stages. The transcript profiles throughout red kiwifruit development were constructed and analyzed, with a focus on the biosynthesis and metabolism of compounds such as phytohormones, sugars, starch and L-ascorbic acid, which are indispensable for the development and formation of quality fruit. Candidate genes for these pathways were identified through MapMan and phylogenetic analysis. The transcript levels of genes involved in sucrose and starch metabolism were consistent with the change in soluble sugar and starch content throughout kiwifruit development. The metabolism of L-ascorbic acid was very active, primarily through the L-galactose pathway. The genes responsible for the accumulation of anthocyanin in red kiwifruit were identified, and their expression levels were investigated during kiwifruit development. This survey of gene expression during kiwifruit development paves the way for further investigation of the development of this uniquely colored and nutritious fruit and reveals which factors are needed for high quality fruit formation. This transcriptome data and its analysis will be useful for improving kiwifruit genome annotation, for basic fruit molecular biology research, and for kiwifruit breeding and improvement.

  13. [Study on action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis based on techniques of gene expression profile and molecular fingerprint].

    PubMed

    Zhou, Wei; Song, Xiang-gang; Chen, Chao; Wang, Shu-mei; Liang, Sheng-wang

    2015-08-01

    Action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis were discussed based on gene expression profile and molecular fingerprint in this paper. First, gene expression profiles of atherosclerotic carotid artery tissues and histologically normal tissues in human body were collected, and were screened using significance analysis of microarray (SAM) to screen out differential gene expressions; then differential genes were analyzed by Gene Ontology (GO) analysis and KEGG pathway analysis; to avoid some genes with non-outstanding differential expression but biologically importance, Gene Set Enrichment Analysis (GSEA) were performed, and 7 chemical ingredients with higher negative enrichment score were obtained by Cmap method, implying that they could reversely regulate the gene expression profiles of pathological tissues; and last, based on the hypotheses that similar structures have similar activities, 336 ingredients of compound Danshen dripping pills were compared with 7 drug molecules in 2D molecular fingerprints method. The results showed that 147 differential genes including 60 up-regulated genes and 87 down regulated genes were screened out by SAM. And in GO analysis, Biological Process ( BP) is mainly concerned with biological adhesion, response to wounding and inflammatory response; Cellular Component (CC) is mainly concerned with extracellular region, extracellular space and plasma membrane; while Molecular Function (MF) is mainly concerned with antigen binding, metalloendopeptidase activity and peptide binding. KEGG pathway analysis is mainly concerned with JAK-STAT, RIG-I like receptor and PPAR signaling pathway. There were 10 compounds, such as hexadecane, with Tanimoto coefficients greater than 0.85, which implied that they may be the active ingredients (AIs) of compound Danshen dripping pills in treatment of carotid atherosclerosis (CAs). The present method can be applied to the research on material

  14. Nucleic-acid based gene therapeutics: delivery challenges and modular design of nonviral gene carriers and expression cassettes to overcome intracellular barriers for sustained targeted expression.

    PubMed

    Hsu, Charlie Yu Ming; Uludağ, Hasan

    2012-05-01

    The delivery of nucleic acid molecules into cells to alter physiological functions at the genetic level is a powerful approach to treat a wide range of inherited and acquired disorders. Biocompatible materials such as cationic polymers, lipids, and peptides are being explored as safer alternatives to viral gene carriers. However, the comparatively low efficiency of nonviral carriers currently hampers their translation into clinical settings. Controlling the size and stability of carrier/nucleic acid complexes is one of the primary hurdles as the physicochemical properties of the complexes can define the uptake pathways, which dictate intracellular routing, endosomal processing, and nucleocytoplasmic transport. In addition to nuclear import, subnuclear trafficking, posttranscriptional events, and immune responses can further limit transfection efficiency. Chemical moieties, reactive linkers or signal peptide have been conjugated to carriers to prevent aggregation, induce membrane destabilization and localize to subcellular compartments. Genetic elements can be inserted into the expression cassette to facilitate nuclear targeting, delimit expression to targeted tissue, and modulate transgene expression. The modular option afforded by both gene carriers and expression cassettes provides a two-tier multicomponent delivery system that can be optimized for targeted gene delivery in a variety of settings.

  15. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining.

    PubMed

    Hulsegge, Ina; Woelders, Henri; Smits, Mari; Schokker, Dirkjan; Jiang, Li; Sørensen, Peter

    2013-05-15

    Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank genes and processes in brain areas and pituitary involved in reproductive traits in cattle using information derived from three different data sources: gene expression, protein-protein interactions, and literature. We identified 59, 89, 53, 23, and 71 genes in bovine amygdala, dorsal hypothalamus, hippocampus, pituitary, and ventral hypothalamus, respectively, potentially involved in processes underlying estrus and estrous behavior. Functional annotation of the candidate genes points to a number of tissue-specific processes of which the "neurotransmitter/ion channel/synapse" process in the amygdala, "steroid hormone receptor activity/ion binding" in the pituitary, "extracellular region" in the ventral hypothalamus, and "positive regulation of transcription/metabolic process" in the dorsal hypothalamus are most prominent. The regulation of the functional processes in the various tissues operate at different biological levels, including transcriptional, posttranscriptional, extracellular, and intercellular signaling levels.

  16. Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming

    PubMed Central

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

    Sketching is one of the most important processes in the conceptual stage of design. Previous studies have relied largely on the analyses of sketching process and outcomes; whereas surface electromyographic (sEMG) signals associated with sketching have received little attention. In this study, we propose a method in which 11 basic one-stroke sketching shapes are identified from the sEMG signals generated by the forearm and upper arm muscles from 4 subjects. Time domain features such as integrated electromyography, root mean square and mean absolute value were extracted with analysis windows of two length conditions for pattern recognition. After reducing data dimensionality using principal component analysis, the shapes were classified using Gene Expression Programming (GEP). The performance of the GEP classifier was compared to the Back Propagation neural network (BPNN) and the Elman neural network (ENN). Feature extraction with the short analysis window (250 ms with a 250 ms increment) improved the recognition rate by around 6.4% averagely compared with the long analysis window (2500 ms with a 2500 ms increment). The average recognition rate for the eleven basic one-stroke sketching patterns achieved by the GEP classifier was 96.26% in the training set and 95.62% in the test set, which was superior to the performance of the BPNN and ENN classifiers. The results show that the GEP classifier is able to perform well with either length of the analysis window. Thus, the proposed GEP model show promise for recognizing sketching based on sEMG signals. PMID:27790083

  17. Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming.

    PubMed

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

    Sketching is one of the most important processes in the conceptual stage of design. Previous studies have relied largely on the analyses of sketching process and outcomes; whereas surface electromyographic (sEMG) signals associated with sketching have received little attention. In this study, we propose a method in which 11 basic one-stroke sketching shapes are identified from the sEMG signals generated by the forearm and upper arm muscles from 4 subjects. Time domain features such as integrated electromyography, root mean square and mean absolute value were extracted with analysis windows of two length conditions for pattern recognition. After reducing data dimensionality using principal component analysis, the shapes were classified using Gene Expression Programming (GEP). The performance of the GEP classifier was compared to the Back Propagation neural network (BPNN) and the Elman neural network (ENN). Feature extraction with the short analysis window (250 ms with a 250 ms increment) improved the recognition rate by around 6.4% averagely compared with the long analysis window (2500 ms with a 2500 ms increment). The average recognition rate for the eleven basic one-stroke sketching patterns achieved by the GEP classifier was 96.26% in the training set and 95.62% in the test set, which was superior to the performance of the BPNN and ENN classifiers. The results show that the GEP classifier is able to perform well with either length of the analysis window. Thus, the proposed GEP model show promise for recognizing sketching based on sEMG signals.

  18. Gene expression-based dosimetry by dose and time in mice following acute radiation exposure.

    PubMed

    Tucker, James D; Divine, George W; Grever, William E; Thomas, Robert A; Joiner, Michael C; Smolinski, Joseph M; Auner, Gregory W

    2013-01-01

    Rapid and reliable methods for performing biological dosimetry are of paramount importance in the event of a large-scale nuclear event. Traditional dosimetry approaches lack the requisite rapid assessment capability, ease of use, portability and low cost, which are factors needed for triaging a large number of victims. Here we describe the results of experiments in which mice were acutely exposed to (60)Co gamma rays at doses of 0 (control) to 10 Gy. Blood was obtained from irradiated mice 0.5, 1, 2, 3, 5, and 7 days after exposure. mRNA expression levels of 106 selected genes were obtained by reverse-transcription real time PCR. Stepwise regression of dose received against individual gene transcript expression levels provided optimal dosimetry at each time point. The results indicate that only 4-7 different gene transcripts are needed to explain ≥ 0.69 of the variance (R(2)), and that receiver-operator characteristics, a measure of sensitivity and specificity, of ≥ 0.93 for these statistical models were achieved at each time point. These models provide an excellent description of the relationship between the actual and predicted doses up to 6 Gy. At doses of 8 and 10 Gy there appears to be saturation of the radiation-response signals with a corresponding diminution of accuracy. These results suggest that similar analyses in humans may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations.

  19. Gene Expression-Based Dosimetry by Dose and Time in Mice Following Acute Radiation Exposure

    PubMed Central

    Tucker, James D.; Divine, George W.; Grever, William E.; Thomas, Robert A.; Joiner, Michael C.; Smolinski, Joseph M.; Auner, Gregory W.

    2013-01-01

    Rapid and reliable methods for performing biological dosimetry are of paramount importance in the event of a large-scale nuclear event. Traditional dosimetry approaches lack the requisite rapid assessment capability, ease of use, portability and low cost, which are factors needed for triaging a large number of victims. Here we describe the results of experiments in which mice were acutely exposed to 60Co gamma rays at doses of 0 (control) to 10 Gy. Blood was obtained from irradiated mice 0.5, 1, 2, 3, 5, and 7 days after exposure. mRNA expression levels of 106 selected genes were obtained by reverse-transcription real time PCR. Stepwise regression of dose received against individual gene transcript expression levels provided optimal dosimetry at each time point. The results indicate that only 4–7 different gene transcripts are needed to explain ≥ 0.69 of the variance (R2), and that receiver-operator characteristics, a measure of sensitivity and specificity, of ≥ 0.93 for these statistical models were achieved at each time point. These models provide an excellent description of the relationship between the actual and predicted doses up to 6 Gy. At doses of 8 and 10 Gy there appears to be saturation of the radiation-response signals with a corresponding diminution of accuracy. These results suggest that similar analyses in humans may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations. PMID:24358280

  20. Genome-Based Genetic Tool Development for Bacillus methanolicus: Theta- and Rolling Circle-Replicating Plasmids for Inducible Gene Expression and Application to Methanol-Based Cadaverine Production

    PubMed Central

    Irla, Marta; Heggeset, Tonje M. B.; Nærdal, Ingemar; Paul, Lidia; Haugen, Tone; Le, Simone B.; Brautaset, Trygve; Wendisch, Volker F.

    2016-01-01

    Bacillus methanolicus is a thermophilic methylotroph able to overproduce amino acids from methanol, a substrate not used for human or animal nutrition. Based on our previous RNA-seq analysis a mannitol inducible promoter and a putative mannitol activator gene mtlR were identified. The mannitol inducible promoter was applied for controlled gene expression using fluorescent reporter proteins and a flow cytometry analysis, and improved by changing the -35 promoter region and by co-expression of the mtlR regulator gene. For independent complementary gene expression control, the heterologous xylose-inducible system from B. megaterium was employed and a two-plasmid gene expression system was developed. Four different replicons for expression vectors were compared with respect to their copy number and stability. As an application example, methanol-based production of cadaverine was shown to be improved from 11.3 to 17.5 g/L when a heterologous lysine decarboxylase gene cadA was expressed from a theta-replicating rather than a rolling-circle replicating vector. The current work on inducible promoter systems and compatible theta- or rolling circle-replicating vectors is an important extension of the poorly developed B. methanolicus genetic toolbox, valuable for genetic engineering and further exploration of this bacterium. PMID:27713731

  1. Genome-Based Genetic Tool Development for Bacillus methanolicus: Theta- and Rolling Circle-Replicating Plasmids for Inducible Gene Expression and Application to Methanol-Based Cadaverine Production.

    PubMed

    Irla, Marta; Heggeset, Tonje M B; Nærdal, Ingemar; Paul, Lidia; Haugen, Tone; Le, Simone B; Brautaset, Trygve; Wendisch, Volker F

    2016-01-01

    Bacillus methanolicus is a thermophilic methylotroph able to overproduce amino acids from methanol, a substrate not used for human or animal nutrition. Based on our previous RNA-seq analysis a mannitol inducible promoter and a putative mannitol activator gene mtlR were identified. The mannitol inducible promoter was applied for controlled gene expression using fluorescent reporter proteins and a flow cytometry analysis, and improved by changing the -35 promoter region and by co-expression of the mtlR regulator gene. For independent complementary gene expression control, the heterologous xylose-inducible system from B. megaterium was employed and a two-plasmid gene expression system was developed. Four different replicons for expression vectors were compared with respect to their copy number and stability. As an application example, methanol-based production of cadaverine was shown to be improved from 11.3 to 17.5 g/L when a heterologous lysine decarboxylase gene cadA was expressed from a theta-replicating rather than a rolling-circle replicating vector. The current work on inducible promoter systems and compatible theta- or rolling circle-replicating vectors is an important extension of the poorly developed B. methanolicus genetic toolbox, valuable for genetic engineering and further exploration of this bacterium.

  2. Simulating the time series of a selected gene expression profile in an agent-based tumor model

    NASA Astrophysics Data System (ADS)

    Mansury, Yuri; Deisboeck, Thomas S.

    2004-09-01

    To elucidate the role of environmental conditions in molecular-level dynamics and to study their impact on macroscopic brain tumor growth patterns, the expression of the genes Tenascin C and PCNA in a 2D agent-based model for the migratory trait is calibrated using experimental data from the literature, while the expression of these genes for the proliferative trait is obtained as the model output. Numerical results confirm that the gene expression of Tenascin C is indeed consistently higher in the migratory glioma cell phenotype and show that the expression of PCNA is consistently higher among proliferating tumor cells. Intriguingly, the time series of the tumor cells’ gene expression exhibit a sudden change in behavior during the invasion of the tumor into a nutrient-abundant region, showing a robust positive correlation between the expression of Tenascin C and the tumor’s diameter, yet a strong negative correlation between the expression of PCNA and the diameter. These molecular-level dynamics correspond to the emergence of a structural asymmetry in the form of a bulging tumor rim in the nutrient-abundant region. The simulated time series thus supports the critical role of the migratory cell phenotype during both the tumor system’s overall macroscopic expansion and the evolvement of regional growth patterns, particularly in the later stages. Furthermore, detrended fluctuation analysis (DFA) suggests that for prediction purposes, the simulated gene expression profiles of Tenascin C and PCNA that were determined separately for the migrating and proliferating phenotypes exhibit lesser predictability than those of the phenotypic mixture combining all viable tumor cells typically found in clinical biopsies. Finally, partitioning the tumor into distinct geographic regions of interest (ROI) reveals that the gene expression profile of tumor cells in the quadrant close to the nutrient-abundant region is representative for the entire tumor whereas the expression

  3. Microarray-based characterization of differential gene expression during vocal fold wound healing in rats.

    PubMed

    Welham, Nathan V; Ling, Changying; Dawson, John A; Kendziorski, Christina; Thibeault, Susan L; Yamashita, Masaru

    2015-03-01

    The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets.

  4. Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

    PubMed

    Ganesh Kumar, Pugalendhi; Kavitha, Muthu Subash; Ahn, Byeong-Cheol

    2016-01-01

    This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR)-based method for redefining the criterion function of f-information (FI) to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA), which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS). Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony algorithm (ABC) on all the datasets. In the global cancer map with repeated measurements (GCM_RM) dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%). In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively classified

  5. Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data

    PubMed Central

    Ahn, Byeong-Cheol

    2016-01-01

    This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR)-based method for redefining the criterion function of f-information (FI) to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA), which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS). Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony algorithm (ABC) on all the datasets. In the global cancer map with repeated measurements (GCM_RM) dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%). In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively classified

  6. A gene expression signature-based approach reveals the mechanisms of action of the Chinese herbal medicine berberine

    PubMed Central

    Lee, Kuen-Haur; Lo, Hsiang-Ling; Tang, Wan-Chun; Hsiao, Heidi Hao-yun; Yang, Pei-Ming

    2014-01-01

    Berberine (BBR), a traditional Chinese herbal medicine, was shown to display anticancer activity. In this study, we attempted to provide a global view of the molecular pathways associated with its anticancer effect through a gene expression-based chemical approach. BBR-induced differentially expressed genes obtained from the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) were analyzed using the Connectivity Map (CMAP) database to compare similarities of gene expression profiles between BBR and CMAP compounds. Candidate compounds were further analyzed using the Search Tool for Interactions of Chemicals (STITCH) database to explore chemical-protein interactions. Results showed that BBR may inhibit protein synthesis, histone deacetylase (HDAC), or AKT/mammalian target of rapamycin (mTOR) pathways. Further analyses demonstrated that BBR inhibited global protein synthesis and basal AKT activity, and induced endoplasmic reticulum (ER) stress and autophagy, which was associated with activation of AMP-activated protein kinase (AMPK). However, BBR did not alter mTOR or HDAC activities. Interestingly, BBR induced the acetylation of α-tubulin, a substrate of HDAC6. In addition, the combination of BBR and SAHA, a pan-HDAC inhibitor, synergistically inhibited cell proliferation and induced cell cycle arrest. Our results provide novel insights into the mechanisms of action of BBR in cancer therapy. PMID:25227736

  7. A gene expression signature-based approach reveals the mechanisms of action of the Chinese herbal medicine berberine.

    PubMed

    Lee, Kuen-Haur; Lo, Hsiang-Ling; Tang, Wan-Chun; Hsiao, Heidi Hao-yun; Yang, Pei-Ming

    2014-09-17

    Berberine (BBR), a traditional Chinese herbal medicine, was shown to display anticancer activity. In this study, we attempted to provide a global view of the molecular pathways associated with its anticancer effect through a gene expression-based chemical approach. BBR-induced differentially expressed genes obtained from the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) were analyzed using the Connectivity Map (CMAP) database to compare similarities of gene expression profiles between BBR and CMAP compounds. Candidate compounds were further analyzed using the Search Tool for Interactions of Chemicals (STITCH) database to explore chemical-protein interactions. Results showed that BBR may inhibit protein synthesis, histone deacetylase (HDAC), or AKT/mammalian target of rapamycin (mTOR) pathways. Further analyses demonstrated that BBR inhibited global protein synthesis and basal AKT activity, and induced endoplasmic reticulum (ER) stress and autophagy, which was associated with activation of AMP-activated protein kinase (AMPK). However, BBR did not alter mTOR or HDAC activities. Interestingly, BBR induced the acetylation of α-tubulin, a substrate of HDAC6. In addition, the combination of BBR and SAHA, a pan-HDAC inhibitor, synergistically inhibited cell proliferation and induced cell cycle arrest. Our results provide novel insights into the mechanisms of action of BBR in cancer therapy.

  8. Quantitative Reverse Transcription-qPCR-Based Gene Expression Analysis in Plants.

    PubMed

    Abdallah, Heithem Ben; Bauer, Petra

    2016-01-01

    The investigation of gene expression is an initial and essential step to understand the function of a gene in a physiological context. Reverse transcription-quantitative real-time PCR (RT-qPCR) assays are reproducible, quantitative, and fast. They can be adapted to study model and non-model plant species without the need to have whole genome or transcriptome sequence data available. Here, we provide a protocol for a reliable RT-qPCR assay, which can be easily adapted to any plant species of interest. We describe the design of the qPCR strategy and primer design, considerations for plant material generation, RNA preparation and cDNA synthesis, qPCR setup and run, and qPCR data analysis, interpretation, and final presentation.

  9. Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

    PubMed Central

    Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

    2016-01-01

    Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

  10. Revealing constitutively expressed resistance genes in Agrostis species using PCR-based motif-directed RNA fingerprinting.

    PubMed

    Budak, Hikmet; Su, Senem; Ergen, Neslihan

    2006-12-01

    Agrostis species are mainly used in athletic fields and golf courses. Their integrity is maintained by fungicides, which makes the development of disease-resistance varieties a high priority. However, there is a lack of knowledge about resistance (R) genes and their use for genetic improvement in Agrostis species. The objective of this study was to identify and clone constitutively expressed cDNAs encoding R gene-like (RGL) sequences from three Agrostis species (colonial bentgrass (A. capillaris L.), creeping bentgrass (A. stolonifera L.) and velvet bentgrass (A. canina L.)) by PCR-based motif-directed RNA fingerprinting towards relatively conserved nucleotide binding site (NBS) domains. Sixty-one constitutively expressed cDNA sequences were identified and characterized. Sequence analysis of ESTs and probable translation products revealed that RGLs are highly conserved among these three Agrostis species. Fifteen of them were shown to share conserved motifs found in other plant disease resistance genes such as MLA13, Xa1, YR6, YR23 and RPP5. The molecular evolutionary forces, analysed using the Ka/Ks ratio, reflected purifying selection both on NBS and leucine-rich repeat (LRR) intervening regions of discovered RGL sequences in these species. This study presents, for the first time, isolation and characterization of constitutively expressed RGL sequences from Agrostis species revealing the presence of TNL (TIR-NBS-LRR) type R genes in monocot plants. The characterized RGLs will further enhance knowledge on the molecular evolution of the R gene family in grasses.

  11. Microarray-based analysis of gene expression in lycopersicon esculentum seedling roots in response to cadmium, chromium, mercury, and lead.

    PubMed

    Hou, Jing; Liu, Xinhui; Wang, Juan; Zhao, Shengnan; Cui, Baoshan

    2015-02-03

    The effects of heavy metals in agricultural soils have received special attention due to their potential for accumulation in crops, which can affect species at all trophic levels. Therefore, there is a critical need for reliable bioassays for assessing risk levels due to heavy metals in agricultural soil. In the present study, we used microarrays to investigate changes in gene expression of Lycopersicon esculentum in response to Cd-, Cr-, Hg-, or Pb-spiked soil. Exposure to (1)/10 median lethal concentrations (LC50) of Cd, Cr, Hg, or Pb for 7 days resulted in expression changes in 29 Cd-specific, 58 Cr-specific, 192 Hg-specific and 864 Pb-specific genes as determined by microarray analysis, whereas conventional morphological and physiological bioassays did not reveal any toxicant stresses. Hierarchical clustering analysis showed that the characteristic gene expression profiles induced by Cd, Cr, Hg, and Pb were distinct from not only the control but also one another. Furthermore, a total of three genes related to "ion transport" for Cd, 14 genes related to "external encapsulating structure organization", "reproductive developmental process", "lipid metabolic process" and "response to stimulus" for Cr, 11 genes related to "cellular metabolic process" and "cellular response to stimulus" for Hg, 78 genes related to 20 biological processes (e.g., DNA metabolic process, monosaccharide catabolic process, cell division) for Pb were identified and selected as their potential biomarkers. These findings demonstrated that microarray-based analysis of Lycopersicon esculentum was a sensitive tool for the early detection of potential toxicity of heavy metals in agricultural soil, as well as an effective tool for identifying the heavy metal-specific genes, which should be useful for assessing risk levels due to heavy metals in agricultural soil.

  12. Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.

    PubMed

    Chen, Ming-Huang; Yang, Wu-Lung R; Lin, Kuan-Ting; Liu, Chia-Hung; Liu, Yu-Wen; Huang, Kai-Wen; Chang, Peter Mu-Hsin; Lai, Jin-Mei; Hsu, Chun-Nan; Chao, Kun-Mao; Kao, Cheng-Yan; Huang, Chi-Ying F

    2011-01-01

    Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.

  13. Live fluorescent RNA-based detection of pluripotency gene expression in embryonic and induced pluripotent stem cells of different species.

    PubMed

    Lahm, Harald; Doppler, Stefanie; Dreßen, Martina; Werner, Astrid; Adamczyk, Klaudia; Schrambke, Dominic; Brade, Thomas; Laugwitz, Karl-Ludwig; Deutsch, Marcus-André; Schiemann, Matthias; Lange, Rüdiger; Moretti, Alessandra; Krane, Markus

    2015-02-01

    The generation of induced pluripotent stem (iPS) cells has successfully been achieved in many species. However, the identification of truly reprogrammed iPS cells still remains laborious and the detection of pluripotency markers requires fixation of cells in most cases. Here, we report an approach with nanoparticles carrying Cy3-labeled sense oligonucleotide reporter strands coupled to gold-particles. These molecules are directly added to cultured cells without any manipulation and gene expression is evaluated microscopically after overnight incubation. To simultaneously detect gene expression in different species, probe sequences were chosen according to interspecies homology. With a common target-specific probe we could successfully demonstrate expression of the GAPDH house-keeping gene in somatic cells and expression of the pluripotency markers NANOG and GDF3 in embryonic stem cells and iPS cells of murine, human, and porcine origin. The population of target gene positive cells could be purified by fluorescence-activated cell sorting. After lentiviral transduction of murine tail-tip fibroblasts Nanog-specific probes identified truly reprogrammed murine iPS cells in situ during development based on their Cy3-fluorescence. The intensity of Nanog-specific fluorescence correlated positively with an increased capacity of individual clones to differentiate into cells of all three germ layers. Our approach offers a universal tool to detect intracellular gene expression directly in live cells of any desired origin without the need for manipulation, thus allowing conservation of the genetic background of the target cell. Furthermore, it represents an easy, scalable method for efficient screening of pluripotency which is highly desirable during high-throughput cell reprogramming and after genomic editing of pluripotent stem cells.

  14. Noninferiority tests based on concordance correlation coefficient for assessment of the agreement for gene expression data from microarray experiments.

    PubMed

    Liao, Chen-Tuo; Lin, Chia-Ying; Liu, Jen-Pei

    2007-01-01

    Microarray is one of the breakthrough technologies in the twenty-first century. Despite of its great potential, transition and realization of microarray technology into the clinically useful commercial products have not been as rapid as the technology could promise. One of the primary reasons is lack of agreement and poor reproducibility of the intensity measurements on gene expression obtained from microarray experiments. Current practices often use the testing the hypothesis of zero Pearson correlation coefficient to assess the agreement of gene expression levels between the technical replicates from microarray experiments. However, Pearson correlation coefficient is to evaluate linear association between two variables and fail to take into account changes in accuracy and precision. Hence, it is not appropriate for evaluation of agreement of gene expression levels between technical replicates. Therefore, we propose to use the concordance correlation coefficient to assess agreement of gene expression levels between technical replicates. We also apply the Generalized Pivotal Quantities to obtain the exact confidence interval for concordance coefficient. In addition, based on the concept of noninferiority test, a one-sided (1 - alpha) lower confidence limit for concordance correlation coefficient is employed to test the hypothesis that the agreement of expression levels of the same genes between two technical replicates exceeds some minimal requirement of agreement. We conducted a simulation study, under various combinations of mean differences, variability, and sample size, to empirically compare the performance of different methods for assessment of agreement in terms of coverage probability, expected length, size, and power. Numerical data from published papers illustrate the application of the proposed methods.

  15. Autonomous Bacterial Localization and Gene Expression Based on Nearby Cell Receptor Density

    DTIC Science & Technology

    2013-01-22

    density, these cells expressed marker proteins to indicate phenotypic response. Specifically, site-specific synthesis of bacterial quorum sensing ...Escherichia coli; quorum sensing ; synthetic biology Introduction Synthetic biology engenders design-based rewiring of a cell’s genetic circuitry for the...the signal transduction processes of quorum sensing (QS) as a means of inter- and intra-species communication and the coordination of population-based

  16. The Gene Expression Omnibus Database.

    PubMed

    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/.

  17. Prediction of lung cancer based on serum biomarkers by gene expression programming methods.

    PubMed

    Yu, Zhuang; Chen, Xiao-Zheng; Cui, Lian-Hua; Si, Hong-Zong; Lu, Hai-Jiao; Liu, Shi-Hai

    2014-01-01

    In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are frequently- used lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.

  18. Method of controlling gene expression

    DOEpatents

    Peters, Norman K.; Frost, John W.; Long, Sharon R.

    1991-12-03

    A method of controlling expression of a DNA segment under the control of a nod gene promoter which comprises administering to a host containing a nod gene promoter an amount sufficient to control expression of the DNA segment of a compound of the formula: ##STR1## in which each R is independently H or OH, is described.

  19. The flow of gene expression.

    PubMed

    Misteli, Tom

    2004-03-01

    Gene expression is a highly interconnected multistep process. A recent meeting in Iguazu Falls, Argentina, highlighted the need to uncover both the molecular details of each single step as well as the mechanisms of coordination among processes in order to fully understand the expression of genes.

  20. Effect of medium/ω-6 long chain triglyceride-based emulsion on leucocyte death and inflammatory gene expression

    PubMed Central

    Cury-Boaventura, M F; Gorjão, R; Martins de Lima, T; Fiamoncini, J; Godoy, A B P; Deschamphs, F C; Soriano, F G; Curi, R

    2011-01-01

    Lipid emulsion (LE) containing medium/ω-6 long chain triglyceride-based emulsion (MCT/ω-6 LCT LE) has been recommended in the place of ω-6 LCT-based emulsion to prevent impairment of immune function. The impact of MCT/ω-6 LCT LE on lymphocyte and neutrophil death and expression of genes related to inflammation was investigated. Seven volunteers were recruited and infusion of MCT/ω-6 LCT LE was performed for 6 h. Four volunteers received saline and no change was found. Blood samples were collected before, immediately afterwards and 18 h after LE infusion. Lymphocytes and neutrophils were studied immediately after isolation and after 24 and 48 h in culture. The following determinations were carried out: plasma-free fatty acids, triacylglycerol and cholesterol concentrations, plasma fatty acid composition, neutral lipid accumulation in lymphocytes and neutrophils, signs of lymphocyte and neutrophil death and lymphocyte expression of genes related to inflammation. MCT/ω-6 LCT LE induced lymphocyte and neutrophil death. The mechanism for MCT/ω-6 LCT LE-dependent induction of leucocyte death may involve changes in neutral lipid content and modulation of expression of genes related to cell death, proteolysis, cell signalling, inflammatory response, oxidative stress and transcription. PMID:21682721

  1. Investigation of TbfA in Riemerella anatipestifer using plasmid-based methods for gene over-expression and knockdown

    PubMed Central

    Liu, MaFeng; Wang, MengYi; Zhu, DeKang; Wang, MingShu; Jia, RenYong; Chen, Shun; Sun, KunFeng; Yang, Qiao; Wu, Ying; Chen, XiaoYue; Biville, Francis; Cheng, AnChun

    2016-01-01

    Riemerella anatipestifer is a duck pathogen that has caused serious economic losses to the duck industry worldwide. Despite this, there are few reported studies of the physiological and pathogenic mechanisms of Riemerella anatipestifer infection. In previous study, we have shown that TonB1 and TonB2 were involved in hemin uptake. TonB family protein (TbfA) was not investigated, since knockout of this gene was not successful at that time. Here, we used a plasmid based gene over-expression and knockdown to investigate its function. First, we constructed three Escherichia-Riemerella anatipestifer shuttle vectors containing three different native Riemerella anatipestifer promoters. The shuttle plasmids were introduced into Riemerella anatipestifer ATCC11845 by conjugation at an efficiency of 5 × 10−5 antibiotic-resistant transconjugants per recipient cell. Based on the high-expression shuttle vector pLMF03, a method for gene knockdown was established. Knockdown of TbfA in Riemerella anatipestifer ATCC11845 decreased the organism’s growth ability in TSB medium but did not affect its hemin utilization. In contrast, over-expression of TbfA in Riemerella anatipestifer ATCC11845ΔtonB1ΔtonB2. Significantly promoted the organism’s growth in TSB medium but significantly inhibited its hemin utilization. Collectively, these findings suggest that TbfA is not involved in hemin utilization by Riemerella anatipestifer. PMID:27845444

  2. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

    PubMed Central

    2014-01-01

    Background Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. Methods We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and

  3. De Novo Sequencing-Based Transcriptome and Digital Gene Expression Analysis Reveals Insecticide Resistance-Relevant Genes in Propylaea japonica (Thunberg) (Coleoptea: Coccinellidae)

    PubMed Central

    Jin, Feng-Liang; Qiu, Bao-Li; Wu, Jian-Hui; Ren, Shun-Xiang

    2014-01-01

    The ladybird Propylaea japonica (Thunberg) is one of most important natural enemies of aphids in China. This species is threatened by the extensive use of insecticides but genomics-based information on the molecular mechanisms underlying insecticide resistance is limited. Hence, we analyzed the transcriptome and expression profile data of P. japonica in order to gain a deeper understanding of insecticide resistance in ladybirds. We performed de novo assembly of a transcriptome using Illumina's Solexa sequencing technology and short reads. A total of 27,243,552 reads were generated. These were assembled into 81,458 contigs and 33,647 unigenes (6,862 clusters and 26,785 singletons). Of the unigenes, 23,965 (71.22%) have putative homologues in the non-redundant (nr) protein database from NCBI, using BLASTX, with a cut-off E-value of 10−5. We examined COG, GO and KEGG annotations to better understand the functions of these unigenes. Digital gene expression (DGE) libraries showed differences in gene expression profiles between two insecticide resistant strains. When compared with an insecticide susceptible profile, a total of 4,692 genes were significantly up- or down- regulated in a moderately resistant strain. Among these genes, 125 putative insecticide resistance genes were identified. To confirm the DGE results, 16 selected genes were validated using quantitative real time PCR (qRT-PCR). This study is the first to report genetic information on P. japonica and has greatly enriched the sequence data for ladybirds. The large number of gene sequences produced from the transcriptome and DGE sequencing will greatly improve our understanding of this important insect, at the molecular level, and could contribute to the in-depth research into insecticide resistance mechanisms. PMID:24959827

  4. Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

    SciTech Connect

    Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith; Yin, John Liu; Byers, Richard

    2012-08-24

    Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

  5. Sphingoid Base Metabolism in Yeast: Mapping Gene Expression Patterns Into Qualitative Metabolite Time Course Predictions

    PubMed Central

    2001-01-01

    Can qualitative metabolite time course predictions be inferred from measured mRNA expression patterns? Speaking against this possibility is the large number of ‘decoupling’ control points that lie between these variables, i.e. translation, protein degradation, enzyme inhibition and enzyme activation. Speaking for it is the notion that these control points might be coordinately regulated such that action exerted on the mRNA level is informative of action exerted on the protein and metabolite levels. A simple kinetic model of sphingoid base metabolism in yeast is postulated. When the enzyme activities in this model are modulated proportional to mRNA expression levels measured in heat shocked yeast, the model yields a transient rise and fall in sphingoid bases followed by a permanent rise in ceramide. This finding is in qualitative agreement with experiments and is thus consistent with the aforementioned coordinated control system hypothesis. PMID:18629242

  6. Discovering modulators of gene expression

    PubMed Central

    Babur, Özgün; Demir, Emek; Gönen, Mithat; Sander, Chris; Dogrusoz, Ugur

    2010-01-01

    Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein–protein interactions and transcription factor–target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes. PMID:20466809

  7. Comparative Analysis of RNAi-Based Methods to Down-Regulate Expression of Two Genes Expressed at Different Levels in Myzus persicae

    PubMed Central

    Mulot, Michaël; Boissinot, Sylvaine; Monsion, Baptiste; Rastegar, Maryam; Clavijo, Gabriel; Halter, David; Bochet, Nicole; Erdinger, Monique; Brault, Véronique

    2016-01-01

    With the increasing availability of aphid genomic data, it is necessary to develop robust functional validation methods to evaluate the role of specific aphid genes. This work represents the first study in which five different techniques, all based on RNA interference and on oral acquisition of double-stranded RNA (dsRNA), were developed to silence two genes, ALY and Eph, potentially involved in polerovirus transmission by aphids. Efficient silencing of only Eph transcripts, which are less abundant than those of ALY, could be achieved by feeding aphids on transgenic Arabidopsis thaliana expressing an RNA hairpin targeting Eph, on Nicotiana benthamiana infected with a Tobacco rattle virus (TRV)-Eph recombinant virus, or on in vitro-synthesized Eph-targeting dsRNA. These experiments showed that the silencing efficiency may differ greatly between genes and that aphid gut cells seem to be preferentially affected by the silencing mechanism after oral acquisition of dsRNA. In addition, the use of plants infected with recombinant TRV proved to be a promising technique to silence aphid genes as it does not require plant transformation. This work highlights the need to pursue development of innovative strategies to reproducibly achieve reduction of expression of aphid genes. PMID:27869783

  8. Gene expression signature based screening identifies ribonucleotide reductase as a candidate therapeutic target in Ewing sarcoma

    PubMed Central

    Goss, Kelli L.; Gordon, David J.

    2016-01-01

    There is a critical need in cancer therapeutics to identify targeted therapies that will improve outcomes and decrease toxicities compared to conventional, cytotoxic chemotherapy. Ewing sarcoma is a highly aggressive bone and soft tissue cancer that is caused by the EWS-FLI1 fusion protein. Although EWS-FLI1 is specific for cancer cells, and required for tumorigenesis, directly targeting this transcription factor has proven challenging. Consequently, targeting unique dependencies or key downstream mediators of EWS-FLI1 represent important alternative strategies. We used gene expression data derived from a genetically defined model of Ewing sarcoma to interrogate the Connectivity Map and identify a class of drugs, iron chelators, that downregulate a significant number of EWS-FLI1 target genes. We then identified ribonucleotide reductase M2 (RRM2), the iron-dependent subunit of ribonucleotide reductase (RNR), as one mediator of iron chelator toxicity in Ewing sarcoma cells. Inhibition of RNR in Ewing sarcoma cells caused apoptosis in vitro and attenuated tumor growth in an in vivo, xenograft model. Additionally, we discovered that the sensitivity of Ewing sarcoma cells to inhibition or suppression of RNR is mediated, in part, by high levels of SLFN11, a protein that sensitizes cells to DNA damage. This work demonstrates a unique dependency of Ewing sarcoma cells on RNR and supports further investigation of RNR inhibitors, which are currently used in clinical practice, as a novel approach for treating Ewing sarcoma. PMID:27557498

  9. Discovery of molecular associations among aging, stem cells, and cancer based on gene expression profiling.

    PubMed

    Wang, Xiaosheng

    2013-04-01

    The emergence of a huge volume of "omics" data enables a computational approach to the investigation of the biology of cancer. The cancer informatics approach is a useful supplement to the traditional experimental approach. I reviewed several reports that used a bioinformatics approach to analyze the associations among aging, stem cells, and cancer by microarray gene expression profiling. The high expression of aging- or human embryonic stem cell-related molecules in cancer suggests that certain important mechanisms are commonly underlying aging, stem cells, and cancer. These mechanisms are involved in cell cycle regulation, metabolic process, DNA damage response, apoptosis, p53 signaling pathway, immune/inflammatory response, and other processes, suggesting that cancer is a developmental and evolutional disease that is strongly related to aging. Moreover, these mechanisms demonstrate that the initiation, proliferation, and metastasis of cancer are associated with the deregulation of stem cells. These findings provide insights into the biology of cancer. Certainly, the findings that are obtained by the informatics approach should be justified by experimental validation. This review also noted that next-generation sequencing data provide enriched sources for cancer informatics study.

  10. Gene Expression Patterns in Ovarian Carcinomas

    PubMed Central

    Schaner, Marci E.; Ross, Douglas T.; Ciaravino, Giuseppe; Sørlie, Therese; Troyanskaya, Olga; Diehn, Maximilian; Wang, Yan C.; Duran, George E.; Sikic, Thomas L.; Caldeira, Sandra; Skomedal, Hanne; Tu, I-Ping; Hernandez-Boussard, Tina; Johnson, Steven W.; O'Dwyer, Peter J.; Fero, Michael J.; Kristensen, Gunnar B.; Børresen-Dale, Anne-Lise; Hastie, Trevor; Tibshirani, Robert; van de Rijn, Matt; Teng, Nelson N.; Longacre, Teri A.; Botstein, David; Brown, Patrick O.; Sikic, Branimir I.

    2003-01-01

    We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers. PMID:12960427

  11. Blood-Based Gene Expression Signatures of Autistic Infants and Toddlers

    PubMed Central

    Glatt, Stephen J.; Tsuang, Ming T.; Winn, Mary; Chandler, Sharon D.; Collins, Melanie; Lopez, Linda; Weinfeld, Melanie; Carter, Cindy; Schork, Nicholas

    2013-01-01

    Objective Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD-risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with autism have yet emerged. Method Using a community-based, prospective, longitudinal method, we identified 60 infants and toddlers at-risk for ASDs (autistic disorder and pervasive developmental disorder), 34 at-risk for language delay (LD), 17 at-risk for global developmental delay (DD), and 68 typically developing (TD) comparison children. Diagnoses were confirmed via longitudinal follow-up. Each child's mRNA expression profile in peripheral blood mononuclear cells (PBMCs) was determined by microarray. Results Potential ASD biomarkers were discovered in one half of the sample and used to build a classifier with high diagnostic accuracy in the remaining half of the sample. Conclusions The mRNA expression abnormalities reliably observed in PBMCs, which are safely and easily assayed in babies, offer the first potential peripheral blood-based early biomarker panel of risk for autism in infants and toddlers. Future work should verify these biomarkers and evaluate if they may also serve as indirect indices of deviant molecular neural mechanisms in autism. PMID:22917206

  12. A Cross-Species Gene Expression Marker-Based Genetic Map and QTL Analysis in Bambara Groundnut.

    PubMed

    Chai, Hui Hui; Ho, Wai Kuan; Graham, Neil; May, Sean; Massawe, Festo; Mayes, Sean

    2017-02-22

    Bambara groundnut (Vigna subterranea (L.) Verdc.) is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL) involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs) were generated at the (unmasked) probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds) of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan) of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops.

  13. A Cross-Species Gene Expression Marker-Based Genetic Map and QTL Analysis in Bambara Groundnut

    PubMed Central

    Chai, Hui Hui; Ho, Wai Kuan; Graham, Neil; May, Sean; Massawe, Festo; Mayes, Sean

    2017-01-01

    Bambara groundnut (Vigna subterranea (L.) Verdc.) is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL) involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs) were generated at the (unmasked) probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds) of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan) of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops. PMID:28241413

  14. Differential expression analysis for individual cancer samples based on robust within-sample relative gene expression orderings across multiple profiling platforms

    PubMed Central

    Guan, Qingzhou; Chen, Rou; Yan, Haidan; Cai, Hao; Guo, You; Li, Mengyao; Li, Xiangyu; Tong, Mengsha; Ao, Lu; Li, Hongdong; Hong, Guini; Guo, Zheng

    2016-01-01

    The highly stable within-sample relative expression orderings (REOs) of gene pairs in a particular type of human normal tissue are widely reversed in the cancer condition. Based on this finding, we have recently proposed an algorithm named RankComp to detect differentially expressed genes (DEGs) for individual disease samples measured by a particular platform. In this paper, with 461 normal lung tissue samples separately measured by four commonly used platforms, we demonstrated that tens of millions of gene pairs with significantly stable REOs in normal lung tissue can be consistently detected in samples measured by different platforms. However, about 20% of stable REOs commonly detected by two different platforms (e.g., Affymetrix and Illumina platforms) showed inconsistent REO patterns due to the differences in probe design principles. Based on the significantly stable REOs (FDR<0.01) for normal lung tissue consistently detected by the four platforms, which tended to have large rank differences, RankComp detected averagely 1184, 1335 and 1116 DEGs per sample with averagely 96.51%, 95.95% and 94.78% precisions in three evaluation datasets with 25, 57 and 58 paired lung cancer and normal samples, respectively. Individualized pathway analysis revealed some common and subtype-specific functional mechanisms of lung cancer. Similar results were observed for colorectal cancer. In conclusion, based on the cross-platform significantly stable REOs for a particular normal tissue, differentially expressed genes and pathways in any disease sample measured by any of the platforms can be readily and accurately detected, which could be further exploited for dissecting the heterogeneity of cancer. PMID:27634898

  15. An approach to transgene expression in liver endothelial cells using a liposome-based gene vector coated with hyaluronic acid.

    PubMed

    Yamada, Yuma; Hashida, Masahiro; Hayashi, Yasuhiro; Tabata, Mai; Hyodo, Mamoru; Ara, Mst Naznin; Ohga, Noritaka; Hida, Kyoko; Harashima, Hideyoshi

    2013-09-01

    Dysfunctional sinusoidal liver endothelial cells (LECs) are associated with liver diseases, such as liver fibrosis, cirrhosis, and portal hypertension. Because of this, gene therapy targeted to LECs would be a useful and productive strategy for directly treating these diseases at the level of genes. Here, we report on the development of a transgene vector that specifically targets LECs. The vector is a liposome-based gene vector coated with hyaluronic acid (HA). HA is a natural ligand for LECs and confers desirable properties on particles, rendering them biodegradable, biocompatible, and nonimmunogenic. In this study, we constructed HA-modified carriers, and evaluated cellular uptake and transfection activity using cultured LECs from KSN nude mice (KSN-LECs). Cellular uptake analyses showed that KSN-LECs recognized the HA-modified carriers more effectively than skin endothelial cells. The transfection assay indicated that the efficient gene expression in KSN-LECs, using the HA-modified carriers, required an adequate lipid composition and a functional device to control intracellular trafficking. This finding contributes to our overall knowledge of transgene expression targeted to LECs.

  16. RNase one gene isolation, expression, and affinity purification models research experimental progression and culminates with guided inquiry-based experiments.

    PubMed

    Bailey, Cheryl P

    2009-01-01

    This new biochemistry laboratory course moves through a progression of experiments that generates a platform for guided inquiry-based experiments. RNase One gene is isolated from prokaryotic genomic DNA, expressed as a tagged protein, affinity purified, and tested for activity and substrate specificity. Student pairs present detailed explanations of materials and methods and the semester culminates in a poster session. Experimental plans take into account the expense and time required to move from gene isolation to enzyme assays. This combination of instructor-guided and student-designed experiments is a manageable foray into guided inquiry-based learning in a biochemistry laboratory course, while providing a cohesive story and context for individual experiments.

  17. Identification of biomarkers that distinguish chemical contaminants based on gene expression profiles

    PubMed Central

    2014-01-01

    Background High throughput transcriptomics profiles such as those generated using microarrays have been useful in identifying biomarkers for different classification and toxicity prediction purposes. Here, we investigated the use of microarrays to predict chemical toxicants and their possible mechanisms of action. Results In this study, in vitro cultures of primary rat hepatocytes were exposed to 105 chemicals and vehicle controls, representing 14 compound classes. We comprehensively compared various normalization of gene expression profiles, feature selection and classification algorithms for the classification of these 105 chemicals into14 compound classes. We found that normalization had little effect on the averaged classification accuracy. Two support vector machine (SVM) methods, LibSVM and sequential minimal optimization, had better classification performance than other methods. SVM recursive feature selection (SVM-RFE) had the highest overfitting rate when an independent dataset was used for a prediction. Therefore, we developed a new feature selection algorithm called gradient method that had a relatively high training classification as well as prediction accuracy with the lowest overfitting rate of the methods tested. Analysis of biomarkers that distinguished the 14 classes of compounds identified a group of genes principally involved in cell cycle function that were significantly downregulated by metal and inflammatory compounds, but were induced by anti-microbial, cancer related drugs, pesticides, and PXR mediators. Conclusions Our results indicate that using microarrays and a supervised machine learning approach to predict chemical toxicants, their potential toxicity and mechanisms of action is practical and efficient. Choosing the right feature and classification algorithms for this multiple category classification and prediction is critical. PMID:24678894

  18. Mining and gene ontology based annotation of SSR markers from expressed sequence tags of Humulus lupulus.

    PubMed

    Singh, Swati; Gupta, Sanchita; Mani, Ashutosh; Chaturvedi, Anoop

    2012-01-01

    Humulus lupulus is commonly known as hops, a member of the family moraceae. Currently many projects are underway leading to the accumulation of voluminous genomic and expressed sequence tag sequences in public databases. The genetically characterized domains in these databases are limited due to non-availability of reliable molecular markers. The large data of EST sequences are available in hops. The simple sequence repeat markers extracted from EST data are used as molecular markers for genetic characterization, in the present study. 25,495 EST sequences were examined and assembled to get full-length sequences. Maximum frequency distribution was shown by mononucleotide SSR motifs i.e. 60.44% in contig and 62.16% in singleton where as minimum frequency are observed for hexanucleotide SSR in contig (0.09%) and pentanucleotide SSR in singletons (0.12%). Maximum trinucleotide motifs code for Glutamic acid (GAA) while AT/TA were the most frequent repeat of dinucleotide SSRs. Flanking primer pairs were designed in-silico for the SSR containing sequences. Functional categorization of SSRs containing sequences was done through gene ontology terms like biological process, cellular component and molecular function.

  19. Delivery of RNA-based molecules to human hematopoietic stem and progenitor cells for modulation of gene expression.

    PubMed

    Diener, Yvonne; Bosio, Andreas; Bissels, Ute

    2016-11-01

    Gene modulation of human hematopoietic stem and progenitor cells (HSPCs) harbors great potential for therapeutic application of these cells and presents a versatile tool in basic research to enhance our understanding of HSPC biology. However, stable genetic modification might be adverse, particularly in clinical settings. Here, we review a broad range of approaches to transient, nonviral modulation of protein expression with a focus on RNA-based methods. We compare different delivery methods and describe the usefulness of RNA molecules for overexpression as well as downregulation of proteins in HSPCs.

  20. Mining Gene Expression Data of Multiple Sclerosis

    PubMed Central

    Zhu, Zhenli; Huang, Zhengliang; Li, Ke

    2014-01-01

    Objectives Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example. Materials and methods Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control) were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models’ performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined. Results An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score. Conclusions The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases. PMID:24932510

  1. Machine learning-based classification of diffuse large B-cell lymphoma patients by eight gene expression profiles.

    PubMed

    Zhao, Shuangtao; Dong, Xiaoli; Shen, Wenzhi; Ye, Zhen; Xiang, Rong

    2016-05-01

    Gene expression profiling (GEP) had divided the diffuse large B-cell lymphoma (DLBCL) into molecular subgroups: germinal center B-cell like (GCB), activated B-cell like (ABC), and unclassified (UC) subtype. However, this classification with prognostic significance was not applied into clinical practice since there were more than 1000 genes to detect and interpreting was difficult. To classify cancer samples validly, eight significant genes (MYBL1, LMO2, BCL6, MME, IRF4, NFKBIZ, PDE4B, and SLA) were selected in 414 patients treated with CHOP/R-CHOP chemotherapy from Gene Expression Omnibus (GEO) data sets. Cutoffs for each gene were obtained using receiver-operating characteristic curves (ROC) new model based on the support vector machine (SVM) estimated the probability of membership into one of two subgroups: GCB and Non-GCB (ABC and UC). Furtherly, multivariate analysis validated the model in another two cohorts including 855 cases in all. As a result, patients in the training and validated cohorts were stratified into two subgroups with 94.0%, 91.0%, and 94.4% concordance with GEP, respectively. Patients with Non-GCB subtype had significantly poorer outcomes than that with GCB subtype, which agreed with the prognostic power of GEP classification. Moreover, the similar prognosis received in the low (0-2) and high (3-5) IPI scores group demonstrated that the new model was independent of IPI as well as GEP method. In conclusion, our new model could stratify DLBCL patients with CHOP/R-CHOP regimen matching GEP subtypes effectively.

  2. DNA microarray-based experimental strategy for trustworthy expression profiling of the hippocampal genes by astaxanthin supplementation in adult mouse

    PubMed Central

    Yook, Jang Soo; Shibato, Junko; Rakwal, Randeep; Soya, Hideaki

    2015-01-01

    Naturally occurring astaxantin (ASX) is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood–brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses) using DNA microarray (Agilent 4 × 44 K whole mouse genome chip) analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin) on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197) as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus. PMID:26981356

  3. Relationships among CFTR expression, HCO3- secretion, and host defense may inform gene- and cell-based cystic fibrosis therapies.

    PubMed

    Shah, Viral S; Ernst, Sarah; Tang, Xiao Xiao; Karp, Philip H; Parker, Connor P; Ostedgaard, Lynda S; Welsh, Michael J

    2016-05-10

    Cystic fibrosis (CF) is caused by mutations in the gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR) anion channel. Airway disease is the major source of morbidity and mortality. Successful implementation of gene- and cell-based therapies for CF airway disease requires knowledge of relationships among percentages of targeted cells, levels of CFTR expression, correction of electrolyte transport, and rescue of host defense defects. Previous studies suggested that, when ∼10-50% of airway epithelial cells expressed CFTR, they generated nearly wild-type levels of Cl(-) secretion; overexpressing CFTR offered no advantage compared with endogenous expression levels. However, recent discoveries focused attention on CFTR-mediated HCO3 (-) secretion and airway surface liquid (ASL) pH as critical for host defense and CF pathogenesis. Therefore, we generated porcine airway epithelia with varying ratios of CF and wild-type cells. Epithelia with a 50:50 mix secreted HCO3 (-) at half the rate of wild-type epithelia. Likewise, heterozygous epithelia (CFTR(+/-) or CFTR(+/∆F508)) expressed CFTR and secreted HCO3 (-) at ∼50% of wild-type values. ASL pH, antimicrobial activity, and viscosity showed similar relationships to the amount of CFTR. Overexpressing CFTR increased HCO3 (-) secretion to rates greater than wild type, but ASL pH did not exceed wild-type values. Thus, in contrast to Cl(-) secretion, the amount of CFTR is rate-limiting for HCO3 (-) secretion and for correcting host defense abnormalities. In addition, overexpressing CFTR might produce a greater benefit than expressing CFTR at wild-type levels when targeting small fractions of cells. These findings may also explain the risk of airway disease in CF carriers.

  4. Monoallelic Gene Expression in Mammals.

    PubMed

    Chess, Andrew

    2016-11-23

    Monoallelic expression not due to cis-regulatory sequence polymorphism poses an intriguing problem in epigenetics because it requires the unequal treatment of two segments of DNA that are present in the same nucleus and that can indeed have absolutely identical sequences. Here, I focus on a few recent developments in the field of monoallelic expression that are of particular interest and raise interesting questions for future work. One development is regarding analyses of imprinted genes, in which recent work suggests the possibility that intriguing networks of imprinted genes exist and are important for genetic and physiological studies. Another issue that has been raised in recent years by a number of publications is the question of how skewed allelic expression should be for it to be designated as monoallelic expression and, further, what methods are appropriate or inappropriate for analyzing genomic data to examine allele-specific expression. Perhaps the most exciting recent development in mammalian monoallelic expression is a clever and carefully executed analysis of genetic diversity of autosomal genes subject to random monoallelic expression (RMAE), which provides compelling evidence for distinct evolutionary forces acting on random monoallelically expressed genes.

  5. Tuning noise in gene expression.

    PubMed

    Tyagi, Sanjay

    2015-05-05

    The relative contribution of promoter architecture and the associated chromatin environment in regulating gene expression noise has remained elusive. In their recent work, Arkin, Schaffer and colleagues (Dey et al, 2015) show that mean expression and noise for a given promoter at different genomic loci are uncorrelated and influenced by the local chromatin environment.

  6. Gene Expression Atlas update—a value-added database of microarray and sequencing-based functional genomics experiments

    PubMed Central

    Kapushesky, Misha; Adamusiak, Tomasz; Burdett, Tony; Culhane, Aedin; Farne, Anna; Filippov, Alexey; Holloway, Ele; Klebanov, Andrey; Kryvych, Nataliya; Kurbatova, Natalja; Kurnosov, Pavel; Malone, James; Melnichuk, Olga; Petryszak, Robert; Pultsin, Nikolay; Rustici, Gabriella; Tikhonov, Andrew; Travillian, Ravensara S.; Williams, Eleanor; Zorin, Andrey; Parkinson, Helen; Brazma, Alvis

    2012-01-01

    Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive and the European Nucleotide Archive. A simple interface allows the user to query for differential gene expression either by gene names or attributes or by biological conditions, e.g. diseases, organism parts or cell types. Since our previous report we made 20 monthly releases and, as of Release 11.08 (August 2011), the database supports 19 species, which contains expression data measured for 19 014 biological conditions in 136 551 assays from 5598 independent studies. PMID:22064864

  7. LuxCDE-luxAB-based promoter reporter system to monitor the Yersinia enterocolitica O:3 gene expression in vivo

    PubMed Central

    Bozcal, Elif; Dagdeviren, Melih; Uzel, Atac

    2017-01-01

    It is crucial to understand the in vitro and in vivo regulation of the virulence factor genes of bacterial pathogens. In this study, we describe the construction of a versatile reporter system for Yersinia enterocolitica serotype O:3 (YeO3) based on the luxCDABE operon. In strain YeO3-luxCDE we integrated the luciferase substrate biosynthetic genes, luxCDE, into the genome of the bacterium so that the substrate is constitutively produced. The luxAB genes that encode the luciferase enzyme were cloned into a suicide vector to allow cloning of any promoter-containing fragment upstream the genes. When the obtained suicide-construct is mobilized into YeO3-luxCDE bacteria, it integrates into the recipient genome via homologous recombination between the cloned promoter fragment and the genomic promoter sequence and thereby generates a single-copy and stable promoter reporter. Lipopolysaccharide (LPS) O-antigen (O-ag) and outer core hexasaccharide (OC) of YeO3 are virulence factors necessary to colonization of the intestine and establishment of infection. To monitor the activities of the OC and O-ag gene cluster promoters we constructed the reporter strains YeO3-Poc::luxAB and YeO3-Pop1::luxAB, respectively. In vitro, at 37°C both promoter activities were highest during logarithmic growth and decreased when the bacteria entered stationary growth phase. At 22°C the OC gene cluster promoter activity increased during the late logarithmic phase. Both promoters were more active in late stationary phase. To monitor the promoter activities in vivo, mice were infected intragastrically and the reporter activities monitored by the IVIS technology. The mouse experiments revealed that both LPS promoters were well expressed in vivo and could be detected by IVIS, mainly from the intestinal region of orally infected mice. PMID:28235077

  8. Selection of reference genes for qPCR- and ddPCR-based analyses of gene expression in Senescing Barley leaves.

    PubMed

    Zmienko, Agnieszka; Samelak-Czajka, Anna; Goralski, Michal; Sobieszczuk-Nowicka, Ewa; Kozlowski, Piotr; Figlerowicz, Marek

    2015-01-01

    Leaf senescence is a tightly regulated developmental or stress-induced process. It is accompanied by dramatic changes in cell metabolism and structure, eventually leading to the disintegration of chloroplasts, the breakdown of leaf proteins, internucleosomal fragmentation of nuclear DNA and ultimately cell death. In light of the global and intense reorganization of the senescing leaf transcriptome, measuring time-course gene expression patterns in this model is challenging due to the evident problems associated with selecting stable reference genes. We have used oligonucleotide microarray data to identify 181 genes with stable expression in the course of dark-induced senescence of barley leaf. From those genes, we selected 5 candidates and confirmed their invariant expression by both reverse transcription quantitative PCR and droplet digital PCR (ddPCR). We used the selected reference genes to normalize the level of the expression of the following senescence-responsive genes in ddPCR assays: SAG12, ICL, AGXT, CS and RbcS. We were thereby able to achieve a substantial reduction in the data variability. Although the use of reference genes is not considered mandatory in ddPCR assays, our results show that it is advisable in special cases, specifically those that involve the following conditions: i) a low number of repeats, ii) the detection of low-fold changes in gene expression or iii) series data comparisons (such as time-course experiments) in which large sample variation greatly affects the overall gene expression profile and biological interpretation of the data.

  9. Dynamic modeling of gene expression data

    NASA Technical Reports Server (NTRS)

    Holter, N. S.; Maritan, A.; Cieplak, M.; Fedoroff, N. V.; Banavar, J. R.

    2001-01-01

    We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

  10. Norovirus gene expression and replication.

    PubMed

    Thorne, Lucy G; Goodfellow, Ian G

    2014-02-01

    Noroviruses are small, positive-sense RNA viruses within the family Caliciviridae, and are now accepted widely as a major cause of acute gastroenteritis in both developed and developing countries. Despite their impact, our understanding of the life cycle of noroviruses has lagged behind that of other RNA viruses due to the inability to culture human noroviruses (HuNVs). Our knowledge of norovirus biology has improved significantly over the past decade as a result of numerous technological advances. The use of a HuNV replicon, improved biochemical and cell-based assays, combined with the discovery of a murine norovirus capable of replication in cell culture, has improved greatly our understanding of the molecular mechanisms of norovirus genome translation and replication, as well as the interaction with host cell processes. In this review, the current state of knowledge of the intracellular life of noroviruses is discussed with particular emphasis on the mechanisms of viral gene expression and viral genome replication.

  11. A Modified ABCDE Model of Flowering in Orchids Based on Gene Expression Profiling Studies of the Moth Orchid Phalaenopsis aphrodite

    PubMed Central

    Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

    2013-01-01

    Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns. PMID:24265826

  12. Mass spectrometry-based proteomics identifies UPF1 as a critical gene expression regulator in MonoMac 6 cells.

    PubMed

    Ochs, Meike J; Ossipova, Elena; Oliynyk, Ganna; Steinhilber, Dieter; Suess, Beatrix; Jakobsson, Per-Johan

    2013-06-07

    5-Lipoxygenase (5-LO) catalyzes the two initial steps in the biosynthesis of leukotrienes, a group of inflammatory lipid mediators derived from arachidonic acid. Recently, we have demonstrated that 5-LO mRNA expression is regulated by alternative splicing and nonsense-mediated mRNA decay (NMD). In addition to this, 5-LO protein expression was reduced on translational level in UPF1 knockdown cells, suggesting that UPF1 has a positive influence on 5-LO translation. Therefore, a mass spectrometry-based proteomics study was performed to identify compartment-specific protein expression changes upon UPF1 knockdown in differentiated and undifferentiated MM6 cells. The proteomics analysis revealed that the knockdown of UPF1 results in numerous protein changes in the microsomal fraction (~21%) but not in the cytosolic fraction (<1%). The results suggest that UPF1 is a critical gene expression regulator in a compartment-specific way. During differentiation by TGFβ and calcitriol, the majority of UPF1 regulated proteins were adjusted to normal level. This indicates that the translational regulation by UPF1 can potentially be cell differentiation-dependent.

  13. Digital gene expression signatures for maize development.

    PubMed

    Eveland, Andrea L; Satoh-Nagasawa, Namiko; Goldshmidt, Alexander; Meyer, Sandra; Beatty, Mary; Sakai, Hajime; Ware, Doreen; Jackson, David

    2010-11-01

    Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect the determinacy of axillary meristems and thus alter branching patterns, an important agronomic trait. In this work, we developed and tested a framework for analysis of tag-based, digital gene expression profiles using Illumina's high-throughput sequencing technology and the newly assembled B73 maize reference genome. We also used a mutation in the RA3 gene to identify putative expression signatures specific to stem cell fate in axillary meristem determinacy. The RA3 gene encodes a trehalose-6-phosphate phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of digital gene expression libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20- to 21-nucleotide reads with frequencies spanning 4 orders of magnitude. Unique sequence tags were anchored to 3'-ends of individual transcripts by DpnII and NlaIII digests, which were multiplexed during sequencing. We mapped 86% of nonredundant signature tags to the maize genome, which associated with 37,117 gene models and unannotated regions of expression. In total, 66% of genes were detected by at least nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) in functional analyses of differentially expressed maize genes. Results from this study provide a basis for the analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

  14. Mining Temporal Protein Complex Based on the Dynamic PIN Weighted with Connected Affinity and Gene Co-Expression.

    PubMed

    Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Hu, Xiaohua; Yang, Jincai

    2016-01-01

    The identification of temporal protein complexes would make great contribution to our knowledge of the dynamic organization characteristics in protein interaction networks (PINs). Recent studies have focused on integrating gene expression data into static PIN to construct dynamic PIN which reveals the dynamic evolutionary procedure of protein interactions, but they fail in practice for recognizing the active time points of proteins with low or high expression levels. We construct a Time-Evolving PIN (TEPIN) with a novel method called Deviation Degree, which is designed to identify the active time points of proteins based on the deviation degree of their own expression values. Owing to the differences between protein interactions, moreover, we weight TEPIN with connected affinity and gene co-expression to quantify the degree of these interactions. To validate the efficiencies of our methods, ClusterONE, CAMSE and MCL algorithms are applied on the TEPIN, DPIN (a dynamic PIN constructed with state-of-the-art three-sigma method) and SPIN (the original static PIN) to detect temporal protein complexes. Each algorithm on our TEPIN outperforms that on other networks in terms of match degree, sensitivity, specificity, F-measure and function enrichment etc. In conclusion, our Deviation Degree method successfully eliminates the disadvantages which exist in the previous state-of-the-art dynamic PIN construction methods. Moreover, the biological nature of protein interactions can be well described in our weighted network. Weighted TEPIN is a useful approach for detecting temporal protein complexes and revealing the dynamic protein assembly process for cellular organization.

  15. Microarray-based gene expression analysis of strong seed dormancy in rice cv. N22 and less dormant mutant derivatives.

    PubMed

    Wu, Tao; Yang, Chunyan; Ding, Baoxu; Feng, Zhiming; Wang, Qian; He, Jun; Tong, Jianhua; Xiao, Langtao; Jiang, Ling; Wan, Jianmin

    2016-02-01

    Seed dormancy in rice is an important trait related to the pre-harvest sprouting resistance. In order to understand the molecular mechanisms of seed dormancy, gene expression was investigated by transcriptome analysis using seeds of the strongly dormant cultivar N22 and its less dormant mutants Q4359 and Q4646 at 24 days after heading (DAH). Microarray data revealed more differentially expressed genes in Q4359 than in Q4646 compared to N22. Most genes differing between Q4646 and N22 also differed between Q4359 and N22. GO analysis of genes differentially expressed in both Q4359 and Q4646 revealed that some genes such as those for starch biosynthesis were repressed, whereas metabolic genes such as those for carbohydrate metabolism were enhanced in Q4359 and Q4646 seeds relative to N22. Expression of some genes involved in cell redox homeostasis and chromatin remodeling differed significantly only between Q4359 and N22. The results suggested a close correlation between cell redox homeostasis, chromatin remodeling and seed dormancy. In addition, some genes involved in ABA signaling were down-regulated, and several genes involved in GA biosynthesis and signaling were up-regulated. These observations suggest that reduced seed dormancy in Q4359 was regulated by ABA-GA antagonism. A few differentially expressed genes were located in the regions containing qSdn-1 and qSdn-5 suggesting that they could be candidate genes underlying seed dormancy. Our work provides useful leads to further determine the underling mechanisms of seed dormancy and for cloning seed dormancy genes from N22.

  16. Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

    PubMed Central

    2013-01-01

    Background Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets. Results A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student’s t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups. Conclusions The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease. PMID:24188919

  17. Differential Hippocampal Gene Expression and Pathway Analysis in an Etiology-Based Mouse Model of Major Depressive Disorder

    PubMed Central

    Zubenko, George S.; Hughes, Hugh B.; Jordan, Rick M.; Lyons-Weiler, James; Cohen, Bruce M.

    2015-01-01

    We have recently reported the creation and initial characterization of an etiology-based recombinant mouse model of a severe and inherited form of Major Depressive Disorder (MDD). This was achieved by replacing the corresponding mouse DNA sequence witha6-base DNA sequence from the human CREB1promoterthat is associated with MDD in individuals from families with recurrent, early-onset MDD (RE-MDD). In the current study, we explored the effect of the pathogenic Creb1 allele on gene expression in the mouse hippocampus, a brain region that is altered in structure and function in MDD. Mouse whole-genome profiling was performed using the Illumina MouseWG-6 v2.0 Expression BeadChip microarray. Univariate analysis identified 269 differentially-expressed genes in the hippocampus of the mutant mouse. Pathway analyses highlighted 11 KEGG pathways: the phosphatidylinositol signaling system, which has been widely implicated in MDD, Bipolar Disorder, and the action of mood stabilizers; gap junction and long-term potentiation, which mediate cognition and memory functions often impaired in MDD; cardiac muscle contraction, insulin signaling pathway, and three neurodegenerative brain disorders (Alzheimer’s, Parkinson’s, and Huntington’s Diseases) that are associated with MDD; ribosome and proteasome pathways affecting protein synthesis/degradation; and the oxidative phosphorylation pathway that is key to energy production. These findings illustrate the merit of this congenic C57BL/6 recombinant mouse as a model of RE-MDD, and demonstrate its potential for highlighting molecular and cellular pathways that contribute to the biology of MDD. The results also inform our understanding of the mechanisms that underlie the comorbidity of MDD with other disorders. PMID:25059218

  18. Gold nanoprobe-based method for sensing activated leukocyte cell adhesion molecule (ALCAM) gene expression, as a breast cancer biomarker.

    PubMed

    Eskandari, Leila; Akbarzadeh, Abolfazl; Zarghami, Nosratollah; Rahmati-Yamchi, Mohammad

    2017-03-01

    In breast cancer, a proper biomarker for the assessment of metastasis and poor prognosis is the RNA of activated leukocyte cell adhesion molecule (ALCAM) gene, which is expressed at high levels in breast tumor. We applied DNA-functionalized gold nanoparticles as the target-specific probes, for detecting specific sequences of DNA or RNA. At high MgCL2 concentrations, nanoprobes aggregate in the absence of the complementary DNA sequence and alteration in the solution color is detectable by evaluating the localized surface plasmon resonance (LSPR). But in the presence of complementary DNA, nanoprobes hybridize to the complementary sequence; therefore, no aggregation takes place, and no color change is observed. We designed a gold nanoprobe-based method that promptly detects the ALCAM gene expression in a low reaction volume with high sensitivity and specificity. This method is simple, fast, selective, and quantitative and can be done with small concentrations of the target (fmol/μL). Limit of detection of the method corresponded to 300 fmol/μL of synthetic ALCAM target.

  19. Covariance Structure Models for Gene Expression Microarray Data

    ERIC Educational Resources Information Center

    Xie, Jun; Bentler, Peter M.

    2003-01-01

    Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…

  20. Differential Gene Expression in Glaucoma

    PubMed Central

    Jakobs, Tatjana C.

    2014-01-01

    In glaucoma, regardless of its etiology, retinal ganglion cells degenerate and eventually die. Although age and elevated intraocular pressure (IOP) are the main risk factors, there are still many mysteries in the pathogenesis of glaucoma. The advent of genome-wide microarray expression screening together with the availability of animal models of the disease has allowed analysis of differential gene expression in all parts of the eye in glaucoma. This review will outline the findings of recent genome-wide expression studies and discuss their commonalities and differences. A common finding was the differential regulation of genes involved in inflammation and immunity, including the complement system and the cytokines transforming growth factor β (TGFβ) and tumor necrosis factor α (TNFα). Other genes of interest have roles in the extracellular matrix, cell–matrix interactions and adhesion, the cell cycle, and the endothelin system. PMID:24985133

  1. Differential gene expression in glaucoma.

    PubMed

    Jakobs, Tatjana C

    2014-07-01

    In glaucoma, regardless of its etiology, retinal ganglion cells degenerate and eventually die. Although age and elevated intraocular pressure (IOP) are the main risk factors, there are still many mysteries in the pathogenesis of glaucoma. The advent of genome-wide microarray expression screening together with the availability of animal models of the disease has allowed analysis of differential gene expression in all parts of the eye in glaucoma. This review will outline the findings of recent genome-wide expression studies and discuss their commonalities and differences. A common finding was the differential regulation of genes involved in inflammation and immunity, including the complement system and the cytokines transforming growth factor β (TGFβ) and tumor necrosis factor α (TNFα). Other genes of interest have roles in the extracellular matrix, cell-matrix interactions and adhesion, the cell cycle, and the endothelin system.

  2. Imputing gene expression to maximize platform compatibility.

    PubMed

    Zhou, Weizhuang; Han, Lichy; Altman, Russ B

    2017-02-15

    Microarray measurements of gene expression constitute a large fraction of publicly shared biological data, and are available in the Gene Expression Omnibus (GEO). Many studies use GEO data to shape hypotheses and improve statistical power. Within GEO, the Affymetrix HG-U133A and HG-U133 Plus 2.0 are the two most commonly used microarray platforms for human samples; the HG-U133 Plus 2.0 platform contains 54 220 probes and the HG-U133A array contains a proper subset (21 722 probes). When different platforms are involved, the subset of common genes is most easily compared. This approach results in the exclusion of substantial measured data and can limit downstream analysis. To predict the expression values for the genes unique to the HG-U133 Plus 2.0 platform, we constructed a series of gene expression inference models based on genes common to both platforms. Our model predicts gene expression values that are within the variability observed in controlled replicate studies and are highly correlated with measured data. Using six previously published studies, we also demonstrate the improved performance of the enlarged feature space generated by our model in downstream analysis.

  3. Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

    PubMed

    Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

    2015-03-09

    Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors.

  4. Pathway-Based Factor Analysis of Gene Expression Data Produces Highly Heritable Phenotypes That Associate with Age

    PubMed Central

    Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

    2015-01-01

    Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 “pathway phenotypes” that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38×10−5). These phenotypes are more heritable (h2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. PMID:25758824

  5. Transgenic Arabidopsis Gene Expression System

    NASA Technical Reports Server (NTRS)

    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.

  6. Zipf's Law in Gene Expression

    NASA Astrophysics Data System (ADS)

    Furusawa, Chikara; Kaneko, Kunihiko

    2003-02-01

    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 intracellular 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.

  7. Neighboring Genes Show Correlated Evolution in Gene Expression.

    PubMed

    Ghanbarian, Avazeh T; Hurst, Laurence D

    2015-07-01

    When considering the evolution of a gene's expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking.

  8. ESTROGENIC STATUS MODULATES DMBA-MEDIATED HEPATIC GENE EXPRESSION: MICROARRAY-BASED ANALYSIS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Estrogenic status in women influences the metabolism and toxicity of polycyclic aromatic hydrocarbons (PAH). The objective of this study was to examine the influence of estradiol (E2) on 7,12 dimethylbenz(a)anthracene (DMBA), a ligand for aryl hydrocarbon receptor, mediated changes on gene expressio...

  9. Growth response and expression of muscle growth-related candidate genes in adult zebrafish fed plant and fishmeal protein-based diets.

    PubMed

    Ulloa, Pilar E; Peña, Andrea A; Lizama, Carla D; Araneda, Cristian; Iturra, Patricia; Neira, Roberto; Medrano, Juan F

    2013-03-01

    The main objective of this study was to examine the effects of a plant protein- vs. fishmeal-based diet on growth response in a population of 24 families, as well as expression of growth-related genes in the muscle of adult zebrafish (Danio rerio). Each family was split to create two fish populations with similar genetic backgrounds, and the fish were fed either fishmeal (FM diet) or plant protein (PP diet) as the unique protein source in their diets from 35 to 98 days postfertilization (dpf). To understand the effect of the PP diet on gene expression, individuals from three families, representative of the mean weight in both populations, were selected. To understand the effect of familiar variation on gene expression, the same families were evaluated separately. At 98 dpf, growth-related genes Igf1a, Igf2a, mTOR, Pld1a, Mrf4, Myod, Myogenin, and Myostatin1b were evaluated. In males, Myogenin, Mrf4, and Igf2a showed changes attributable to the PP diet. In females, the effect of the PP diet did not modulate the expression in any of the eight genes studied. The effect of familiar variation on gene expression was observed among families. This study shows that PP diet and family variation have effects on gene expression in fish muscle.

  10. Weighted gene co-expression network analysis in identification of metastasis-related genes of lung squamous cell carcinoma based on the Cancer Genome Atlas database

    PubMed Central

    Tian, Feng; Zhao, Jinlong; Kang, Zhenxing

    2017-01-01

    Background Lung squamous cell carcinoma (lung SCC) is a common type of malignancy. Its pathogenesis mechanism of tumor development is unclear. The aim of this study was to identify key genes for diagnosis biomarkers in lung SCC metastasis. Methods We searched and downloaded mRNA expression data and clinical data from The Cancer Genome Atlas (TCGA) database to identify differences in mRNA expression of primary tumor tissues from lung SCC with and without metastasis. Gene co-expression network analysis, protein-protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and quantitative real-time polymerase chain reactions (qRT-PCR) were used to explore the biological functions of the identified dysregulated genes. Results Four hundred and eighty-two differentially expressed genes (DEGs) were identified between lung SCC with and without metastasis. Nineteen modules were identified in lung SCC through weighted gene co-expression network analysis (WGCNA). Twenty-three DEGs and 26 DEGs were significantly enriched in the respective pink and black module. KEGG pathway analysis displayed that 26 DEGs in the black module were significantly enriched in bile secretion pathway. Forty-nine DEGs in the two gene co-expression module were used to construct PPI network. CFTR in the black module was the hub protein, had the connectivity with 182 genes. The results of qRT-PCR displayed that FIGF, SFTPD, DYNLRB2 were significantly down-regulated in the tumor samples of lung SCC with metastasis and CFTR, SCGB3A2, SSTR1, SCTR, ROPN1L had the down-regulation tendency in lung SCC with metastasis compared to lung SCC without metastasis. Conclusions The dysregulated genes including CFTR, SCTR and FIGF might be involved in the pathology of lung SCC metastasis and could be used as potential diagnosis biomarkers or therapeutic targets for lung SCC. PMID:28203405

  11. Serum-based culture conditions provoke gene expression variability in mouse embryonic stem cells as revealed by single cell analysis

    PubMed Central

    Guo, Guoji; Pinello, Luca; Han, Xiaoping; Lai, Shujing; Shen, Li; Lin, Ta-Wei; Zou, Keyong; Yuan, Guo-Cheng; Orkin, Stuart H.

    2015-01-01

    Summary Variation in gene expression is an important feature of mouse embryonic stem cells (ESCs). However, the mechanisms responsible for global gene expression variation in ESCs are not fully understood. We performed single cell mRNA-seq analysis of mouse ESCs and uncovered significant heterogeneity in ESCs cultured in serum. We define highly variable gene clusters with distinct chromatin states; and show that bivalent genes are prone to expression variation. At the same time, we identify an ESC priming pathway that initiates the exit from the naïve ESC state. Finally, we provide evidence that a large proportion of intracellular network variability is due to the extracellular culture environment. Serum free culture reduces cellular heterogeneity and transcriptome variation in ESCs. PMID:26804902

  12. Plant Omics Data Center: An Integrated Web Repository for Interspecies Gene Expression Networks with NLP-Based Curation

    PubMed Central

    Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

    2015-01-01

    Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. PMID:25505034

  13. Resource Sharing Controls Gene Expression Bursting.

    PubMed

    Caveney, Patrick M; Norred, S Elizabeth; Chin, Charles W; Boreyko, Jonathan B; Razooky, Brandon S; Retterer, Scott T; Collier, C Patrick; Simpson, Michael L

    2017-02-17

    Episodic gene expression, with periods of high expression separated by periods of no expression, is a pervasive biological phenomenon. This bursty pattern of expression draws from a finite reservoir of expression machinery in a highly time variant way, i.e., requiring no resources most of the time but drawing heavily on them during short intense bursts, that intimately links expression bursting and resource sharing. Yet, most recent investigations have focused on specific molecular mechanisms intrinsic to the bursty behavior of individual genes, while little is known about the interplay between resource sharing and global expression bursting behavior. Here, we confine Escherichia coli cell extract in both cell-sized microfluidic chambers and lipid-based vesicles to explore how resource sharing influences expression bursting. Interestingly, expression burst size, but not burst frequency, is highly sensitive to the size of the shared transcription and translation resource pools. The intriguing implication of these results is that expression bursts are more readily amplified than initiated, suggesting that burst formation occurs through positive feedback or cooperativity. When extrapolated to prokaryotic cells, these results suggest that large translational bursts may be correlated with large transcriptional bursts. This correlation is supported by recently reported transcription and translation bursting studies in E. coli. The results reported here demonstrate a strong intimate link between global expression burst patterns and resource sharing, and they suggest that bursting plays an important role in optimizing the use of limited, shared expression resources.

  14. Blood-Based Gene Expression Signatures of Infants and Toddlers with Autism

    ERIC Educational Resources Information Center

    Glatt, Stephen J.; Tsuang, Ming T.; Winn, Mary; Chandler, Sharon D.; Collins, Melanie; Lopez, Linda; Weinfeld, Melanie; Carter, Cindy; Schork, Nicholas; Pierce, Karen; Courchesne, Eric

    2012-01-01

    Objective: Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with…

  15. Using PCR to Target Misconceptions about Gene Expression

    PubMed Central

    Wright, Leslie K.; Newman, Dina L.

    2013-01-01

    We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about gene expression. Biology students typically do not have a clear understanding of the difference between genes (DNA) and gene expression (mRNA/protein) and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and gene expression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect) predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and gene expression. PMID:23858358

  16. MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation.

    PubMed

    Wang, Luman; Mo, Qiaochu; Wang, Jianxin

    2015-01-01

    Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches.

  17. Prediction of Metabolic Flux Distribution from Gene Expression Data Based on the Flux Minimization Principle

    DTIC Science & Technology

    2014-11-14

    expression data. The proposed algorithm minimizes a weighted sum of flux magnitudes, while biomass production can be bounded to fit an ample range from...approach to investigate metabolism and metabolic processes is to analyze the flow of material and energy through a metabolic network. In particular, the...maximizing a certain fitness function (typically, biomass production) and estimates the flux distribution by solving a linear programming (LP

  18. A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose-Response Curve.

    PubMed

    Goswami, C Pankaj; Cheng, L; Alexander, P S; Singal, A; Li, L

    2015-02-01

    Gene expression data before and after treatment with an individual drug and the IC20 of dose-response data were utilized to predict two drugs' interaction effects on a diffuse large B-cell lymphoma (DLBCL) cancer cell. A novel drug interaction scoring algorithm was developed to account for either synergistic or antagonistic effects between drug combinations. Different core gene selection schemes were investigated, which included the whole gene set, the drug-sensitive gene set, the drug-sensitive minus drug-resistant gene set, and the known drug target gene set. The prediction scores were compared with the observed drug interaction data at 6, 12, and 24 hours with a probability concordance (PC) index. The test result shows the concordance between observed and predicted drug interaction ranking reaches a PC index of 0.605. The scoring reliability and efficiency was further confirmed in five drug interaction studies published in the GEO database.

  19. Hexosamine template. A platform for modulating gene expression and for sugar-based drug discovery.

    PubMed

    Elmouelhi, Noha; Aich, Udayanath; Paruchuri, Venkata D P; Meledeo, M Adam; Campbell, Christopher T; Wang, Jean J; Srinivas, Raja; Khanna, Hargun S; Yarema, Kevin J

    2009-04-23

    This study investigates the breadth of cellular responses engendered by short chain fatty acid (SCFA)-hexosamine hybrid molecules, a class of compounds long used in "metabolic glycoengineering" that are now emerging as drug candidates. First, a "mix and match" strategy showed that different SCFA (n-butyrate and acetate) appended to the same core sugar altered biological activity, complementing previous results [Campbell et al. J. Med. Chem. 2008, 51, 8135-8147] where a single type of SCFA elicited distinct responses. Microarray profiling then compared transcriptional responses engendered by regioisomerically modified ManNAc, GlcNAc, and GalNAc analogues in MDA-MB-231 cells. These data, which were validated by qRT-PCR or Western analysis for ID1, TP53, HPSE, NQO1, EGR1, and VEGFA, showed a two-pronged response where a core set of genes was coordinately regulated by all analogues while each analogue simultaneously uniquely regulated a larger number of genes. Finally, AutoDock modeling supported a mechanism where the analogues directly interact with elements of the NF-kappaB pathway. Together, these results establish the SCFA-hexosamine template as a versatile platform for modulating biological activity and developing new therapeutics.

  20. Regulation of ABO gene expression.

    PubMed

    Kominato, Yoshihiko; Hata, Yukiko; Matsui, Kazuhiro; Takizawa, Hisao

    2005-07-01

    The ABO blood group system is important in blood transfusions and in identifying individuals during criminal investigations. Two carbohydrate antigens, the A and B antigens, and their antibodies constitute this system. Although biochemical and molecular genetic studies have demonstrated the molecular basis of the histo-blood group ABO system, some aspects remain to be elucidated. To explain the molecular basis of how the ABO genes are controlled in cell type-specific expression, during normal cell differentiation, and in cancer cells with invasive and metastatic potential that lack A/B antigens, it is essential to understand the regulatory mechanism of ABO gene transcription. We review the transcriptional regulation of the ABO gene, including positive and negative elements in the upstream region of the gene, and draw some inferences that help to explain the phenomena described above.

  1. Time-course investigation of the gene expression profile during Fasciola hepatica infection: A microarray-based study

    PubMed Central

    Rojas-Caraballo, Jose; López-Abán, Julio; Fernández-Soto, Pedro; Vicente, Belén; Collía, Francisco; Muro, Antonio

    2015-01-01

    Fasciolosis is listed as one of the most important neglected tropical diseases according with the World Health Organization and is also considered as a reemerging disease in the human beings. Despite there are several studies describing the immune response induced by Fasciola hepatica in the mammalian host, investigations aimed at identifying the expression profile of genes involved in inducing hepatic injury are currently scarce. Data presented here belong to a time-course investigation of the gene expression profile in the liver of BALB/c mice infected with F. hepatica metacercariae at 7 and 21 days after experimental infection. The data published here have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE69588, previously published by Rojas-Caraballo et al. (2015) in PLoS One [1]. PMID:26697343

  2. A new high-performance heterologous fungal expression system based on regulatory elements from the Aspergillus terreus terrein gene cluster.

    PubMed

    Gressler, Markus; Hortschansky, Peter; Geib, Elena; Brock, Matthias

    2015-01-01

    Recently, the Aspergillus terreus terrein gene cluster was identified and selected for development of a new heterologous expression system. The cluster encodes the specific transcription factor TerR that is indispensable for terrein cluster induction. To identify TerR binding sites, different recombinant versions of the TerR DNA-binding domain were analyzed for specific motif recognition. The high affinity consensus motif TCGGHHWYHCGGH was identified from genes required for terrein production and binding site mutations confirmed their essential contribution to gene expression in A. terreus. A combination of TerR with its terA target promoter was tested as recombinant expression system in the heterologous host Aspergillus niger. TerR mediated target promoter activation was directly dependent on its transcription level. Therefore, terR was expressed under control of the regulatable amylase promoter PamyB and the resulting activation of the terA target promoter was compared with activation levels obtained from direct expression of reporters from the strong gpdA control promoter. Here, the coupled system outcompeted the direct expression system. When the coupled system was used for heterologous polyketide synthase expression high metabolite levels were produced. Additionally, expression of the Aspergillus nidulans polyketide synthase gene orsA revealed lecanoric acid rather than orsellinic acid as major polyketide synthase product. Domain swapping experiments assigned this depside formation from orsellinic acid to the OrsA thioesterase domain. These experiments confirm the suitability of the expression system especially for high-level metabolite production in heterologous hosts.

  3. A new high-performance heterologous fungal expression system based on regulatory elements from the Aspergillus terreus terrein gene cluster

    PubMed Central

    Gressler, Markus; Hortschansky, Peter; Geib, Elena; Brock, Matthias

    2015-01-01

    Recently, the Aspergillus terreus terrein gene cluster was identified and selected for development of a new heterologous expression system. The cluster encodes the specific transcription factor TerR that is indispensable for terrein cluster induction. To identify TerR binding sites, different recombinant versions of the TerR DNA-binding domain were analyzed for specific motif recognition. The high affinity consensus motif TCGGHHWYHCGGH was identified from genes required for terrein production and binding site mutations confirmed their essential contribution to gene expression in A. terreus. A combination of TerR with its terA target promoter was tested as recombinant expression system in the heterologous host Aspergillus niger. TerR mediated target promoter activation was directly dependent on its transcription level. Therefore, terR was expressed under control of the regulatable amylase promoter PamyB and the resulting activation of the terA target promoter was compared with activation levels obtained from direct expression of reporters from the strong gpdA control promoter. Here, the coupled system outcompeted the direct expression system. When the coupled system was used for heterologous polyketide synthase expression high metabolite levels were produced. Additionally, expression of the Aspergillus nidulans polyketide synthase gene orsA revealed lecanoric acid rather than orsellinic acid as major polyketide synthase product. Domain swapping experiments assigned this depside formation from orsellinic acid to the OrsA thioesterase domain. These experiments confirm the suitability of the expression system especially for high-level metabolite production in heterologous hosts. PMID:25852654

  4. Estrogen-Responsive Transient Expression Assay Using a Brain Aromatase-Based Reporter Gene in Zebrafish (Danio rerio)

    PubMed Central

    Kim, Dong-Jae; Seok, Seung-Hyeok; Baek, Min-Won; Lee, Hui-Young; Na, Yi-Rang; Park, Sung-Hoon; Lee, Hyun-Kyoung; Dutta, Noton Kumar; Kawakami, Koichi; Park, Jae-Hak

    2009-01-01

    Whereas endogenous estrogens play an important role in the development, maintenance, and function of female and male reproductive organs, xenoestrogens present in the environment disrupt normal endocrine function in humans and wildlife. Various in vivo and in vitro assays have been developed to screen these xenoestrogens. However, traditional in vivo assays are laborious and unsuitable for large-scale screening, and in vitro assays do not necessarily replicate in vivo functioning. To overcome these limitations, we developed a transient expression assay in zebrafish, into which a brain aromatase (cyp19a1b)-based estrogen-responsive reporter gene was introduced. In response to 17β-estradiol (10−6 M) and heptachlor (10−6 M), zebrafish embryos carrying the reporter construct expressed enhanced green fluorescent protein in the olfactory bulb, telencephalon, preoptic area, and mediobasal hypothalamus. This system will serve to model the in vivo conversion and breakdown of estrogenic compounds and thus provide a rapid preliminary screening method to estimate their estrogenicity. PMID:19887024

  5. Gene expression profile of pulpitis

    PubMed Central

    Galicia, Johnah C.; Henson, Brett R.; Parker, Joel S.; Khan, Asma A.

    2016-01-01

    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 in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (≥30mm on VAS) compared to 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

  6. Gene expression profile of pulpitis.

    PubMed

    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.

  7. Comprehensive transcriptome-based characterization of differentially expressed genes involved in microsporogenesis of radish CMS line and its maintainer.

    PubMed

    Xie, Yang; Zhang, Wei; Wang, Yan; Xu, Liang; Zhu, Xianwen; Muleke, Everlyne M; Liu, Liwang

    2016-09-01

    Microsporogenesis is an indispensable period for investigating microspore development and cytoplasmic male sterility (CMS) occurrence. Radish CMS line plays a critical role in elite F1 hybrid seed production and heterosis utilization. However, the molecular mechanisms of microspore development and CMS occurrence have not been thoroughly uncovered in radish. In this study, a comparative analysis of radish floral buds from a CMS line (NAU-WA) and its maintainer (NAU-WB) was conducted using next generation sequencing (NGS) technology. Digital gene expression (DGE) profiling revealed that 3504 genes were significantly differentially expressed between NAU-WA and NAU-WB library, among which 1910 were upregulated and 1594 were downregulated. Gene ontology (GO) analysis showed that these differentially expressed genes (DEGs) were mainly enriched in extracellular region, catalytic activity, and response to stimulus. KEGG enrichment analysis revealed that the DEGs were predominantly associated with flavonoid biosynthesis, glycolysis, and biosynthesis of secondary metabolites. Real-time quantitative PCR analysis showed that the expression profiles of 13 randomly selected DEGs were in high agreement with results from Illumina sequencing. Several candidate genes encoding ATP synthase, auxin response factor (ARF), transcription factors (TFs), chalcone synthase (CHS), and male sterility (MS) were responsible for microsporogenesis. Furthermore, a schematic diagram for functional interaction of DEGs from NAU-WA vs. NAU-WB library in radish plants was proposed. These results could provide new information on the dissection of the molecular mechanisms underlying microspore development and CMS occurrence in radish.

  8. Stress-induced Hsp70 gene expression and inactivation of Cryptosporidium parvum oocysts by chlorine-based oxidants.

    PubMed

    Bajszár, George; Dekonenko, Alexander

    2010-03-01

    Our research on the mechanisms of action of chlorine-based oxidants on Cryptosporidium parvum oocysts in water revealed a dual-phase effect: (i) response to oxidative stress, which was demonstrated by induced expression of the Hsp70 heat shock gene, and (ii) oocyst inactivation as a result of long-term exposure to oxidants. The relative biocidal effects of sodium hypochlorite (bleach) and electrolytically generated mixed oxidant solution (MOS) on C. parvum oocysts were compared at identical free chlorine concentrations. Oocyst inactivation was determined by quantitative reverse transcription-PCR (qRT-PCR) amplification of the heat-induced Hsp70 mRNA and compared with tissue culture infectivity. According to both assays, within the range between 25 and 250 mg/liter free chlorine and with 4 h contact time, MOS exhibits a higher efficacy in oocyst inactivation than hypochlorite. Other RNA-based viability assays, aimed at monitoring the levels of beta-tubulin mRNA and 18S rRNA, showed relatively slow decay rates of these molecules following disinfection by chlorine-based oxidants, rendering these molecular diagnostic viability markers inappropriate for disinfection efficacy assessment.

  9. Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo

    PubMed Central

    Sayal, Rupinder; Dresch, Jacqueline M; Pushel, Irina; Taylor, Benjamin R; Arnosti, David N

    2016-01-01

    Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale. DOI: http://dx.doi.org/10.7554/eLife.08445.001 PMID:27152947

  10. De novo transcriptome characterization of the ghost moth, Thitarodes pui, and elevation-based differences in the gene expression of its larvae.

    PubMed

    Wu, Wenjing; Sun, Hongxia; Guo, Jixing; Jiang, Fengze; Liu, Xin; Zhang, Guren

    2015-12-10

    Thitarodes pui larvae are the hosts of a medicinal fungus, Ophiocordyceps sinensis, and are naturally distributed at an altitude of 4100-4650 m on Segrila Mountain of the Tibetan Plateau. Here, we conducted transcriptome profiling of T. pui larvae based on the Illumina high-throughput sequencing platform. Subsequently, we explored elevation-based differences of T. pui by comparing gene expression profiles between larvae at high-altitude (natural conditions) and larvae exposed to short-term (2months) low-altitude conditions. A total of 105,935,208 clean reads were assembled into 70,048 unigenes with a mean length of 639 bp. All unigenes were searched against public databases, with 51.26% unigenes being successfully annotated in the NR, SWISS-PROT, EuKaryotic Orthologous Groups (KOG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genome (KEGG) databases. A total of 11,846 unigenes were functionally classified into 239 KEGG pathways. Metabolism was the most represented pathway, with 4271 unigenes (36.05%). Using the transcriptome data as a reference, 629 (311 up-regulated/318 down-regulated) genes were differentially expressed by low-altitude larvae when compared with those of high-altitude larvae. The most significantly differentially expressed genes were annotated in the processes of carbohydrate metabolism, lipid metabolism, and respiration. This report provides valuable information about the T. pui transcriptome for future genomic studies, including how gene expression is altered in larvae reared at different elevations.

  11. Blood-Based Gene Expression Profiles Models for Classification of Subsyndromal Symptomatic Depression and Major Depressive Disorder

    PubMed Central

    Yu, Shunying; Yuan, Chengmei; Hong, Wu; Wang, Zuowei; Cui, Jian; Shi, Tieliu; Fang, Yiru

    2012-01-01

    Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD, and matched controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell–derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls. PMID:22348066

  12. Blood-based gene expression profiles models for classification of subsyndromal symptomatic depression and major depressive disorder.

    PubMed

    Yi, Zhenghui; Li, Zezhi; Yu, Shunying; Yuan, Chengmei; Hong, Wu; Wang, Zuowei; Cui, Jian; Shi, Tieliu; Fang, Yiru

    2012-01-01

    Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD, and matched controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell-derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls.

  13. Gene expression throughout a vertebrate's embryogenesis

    PubMed Central

    2011-01-01

    Background Describing the patterns of gene expression during embryonic development has broadened our understanding of the processes and patterns that define morphogenesis. Yet gene expression patterns have not been described throughout vertebrate embryogenesis. This study presents statistical analyses of gene expression during all 40 developmental stages in the teleost Fundulus heteroclitus using four biological replicates per stage. Results Patterns of gene expression for 7,000 genes appear to be important as they recapitulate developmental timing. Among the 45% of genes with significant expression differences between pairs of temporally adjacent stages, significant differences in gene expression vary from as few as five to more than 660. Five adjacent stages have disproportionately more significant changes in gene expression (> 200 genes) relative to other stages: four to eight and eight to sixteen cell stages, onset of circulation, pre and post-hatch, and during complete yolk absorption. The fewest differences among adjacent stages occur during gastrulation. Yet, at stage 16, (pre-mid-gastrulation) the largest number of genes has peak expression. This stage has an over representation of genes in oxidative respiration and protein expression (ribosomes, translational genes and proteases). Unexpectedly, among all ribosomal genes, both strong positive and negative correlations occur. Similar correlated patterns of expression occur among all significant genes. Conclusions These data provide statistical support for the temporal dynamics of developmental gene expression during all stages of vertebrate development. PMID:21356103

  14. Does FACS perturb gene expression?

    PubMed

    Richardson, Graham M; Lannigan, Joanne; Macara, Ian G

    2015-02-01

    Fluorescence activated cell sorting is the technique most commonly used to separate primary mammary epithelial sub-populations. Many studies incorporate this technique before analyzing gene expression within specific cellular lineages. However, to our knowledge, no one has examined the effects of fluorescence activated cell sorting (FACS) separation on short-term transcriptional profiles. In this study, we isolated a heterogeneous mixture of cells from the mouse mammary gland. To determine the effects of the isolation and separation process on gene expression, we harvested RNA from the cells before enzymatic digestion, following enzymatic digestion, and following a mock FACS sort where the entire cohort of cells was retained. A strict protocol was followed to minimize disruption to the cells, and to ensure that no subpopulations were enriched or lost. Microarray analysis demonstrated that FACS causes minimal disruptions to gene expression patterns, but prior steps in the mammary cell isolation process are followed by upregulation of 18 miRNA's and rapid decreases in their predicted target transcripts. © 2015 International Society for Advancement of Cytometry.

  15. GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles

    PubMed Central

    Antanaviciute, Agne; Daly, Catherine; Crinnion, Laura A.; Markham, Alexander F.; Watson, Christopher M.; Bonthron, David T.; Carr, Ian M.

    2015-01-01

    Motivation: In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually. Results: Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias toward the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples. Availability and Implementation: Freely available on the web at http://dna.leeds.ac.uk/GeneTIER/. Contact: umaan@leeds.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25861967

  16. Genome-Wide Identification and Transcriptome-Based Expression Profiling of the Sox Gene Family in the Nile Tilapia (Oreochromis niloticus)

    PubMed Central

    Wei, Ling; Yang, Chao; Tao, Wenjing; Wang, Deshou

    2016-01-01

    The Sox transcription factor family is characterized with the presence of a Sry-related high-mobility group (HMG) box and plays important roles in various biological processes in animals, including sex determination and differentiation, and the development of multiple organs. In this study, 27 Sox genes were identified in the genome of the Nile tilapia (Oreochromis niloticus), and were classified into seven groups. The members of each group of the tilapia Sox genes exhibited a relatively conserved exon-intron structure. Comparative analysis showed that the Sox gene family has undergone an expansion in tilapia and other teleost fishes following their whole genome duplication, and group K only exists in teleosts. Transcriptome-based analysis demonstrated that most of the tilapia Sox genes presented stage-specific and/or sex-dimorphic expressions during gonadal development, and six of the group B Sox genes were specifically expressed in the adult brain. Our results provide a better understanding of gene structure and spatio-temporal expression of the Sox gene family in tilapia, and will be useful for further deciphering the roles of the Sox genes during sex determination and gonadal development in teleosts. PMID:26907269

  17. Identification of human HK genes and gene expression regulation study in cancer from transcriptomics data analysis.

    PubMed

    Chen, Meili; Xiao, Jingfa; Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer.

  18. Distinct gene expression responses of two anticonvulsant drugs in a novel human embryonic stem cell based neural differentiation assay protocol.

    PubMed

    Schulpen, Sjors H W; de Jong, Esther; de la Fonteyne, Liset J J; de Klerk, Arja; Piersma, Aldert H

    2015-04-01

    Hazard assessment of chemicals and pharmaceuticals is increasingly gaining from knowledge about molecular mechanisms of toxic action acquired in dedicated in vitro assays. We have developed an efficient human embryonic stem cell neural differentiation test (hESTn) that allows the study of the molecular interaction of compounds with the neural differentiation process. Within the 11-day differentiation protocol of the assay, embryonic stem cells lost their pluripotency, evidenced by the reduced expression of stem cell markers Pou5F1 and Nanog. Moreover, stem cells differentiated into neural cells, with morphologically visible neural structures together with increased expression of neural differentiation-related genes such as βIII-tubulin, Map2, Neurogin1, Mapt and Reelin. Valproic acid (VPA) and carbamazepine (CBZ) exposure during hESTn differentiation led to concentration-dependent reduced expression of βIII-tubulin, Neurogin1 and Reelin. In parallel VPA caused an increased gene expression of Map2 and Mapt which is possibly related to the neural protective effect of VPA. These findings illustrate the added value of gene expression analysis for detecting compound specific effects in hESTn. Our findings were in line with and could explain effects observed in animal studies. This study demonstrates the potential of this assay protocol for mechanistic analysis of specific compound-induced inhibition of human neural cell differentiation.

  19. Genomics-based screening of differentially expressed genes in the brains of mice exposed to silver nanoparticles via inhalation

    NASA Astrophysics Data System (ADS)

    Lee, Hye-Young; Choi, You-Jin; Jung, Eun-Jung; Yin, Hu-Quan; Kwon, Jung-Taek; Kim, Ji-Eun; Im, Hwang-Tae; Cho, Myung-Haing; Kim, Ju-Han; Kim, Hyun-Young; Lee, Byung-Hoon

    2010-06-01

    Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 ± 1.72 nm; 1.91 × 107 particles/cm3) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

  20. The Underlying Bases of Gene Expression Differences in Stable Transformants of the ROSY Locus in DROSOPHILA MELANOGASTER

    PubMed Central

    Daniels, Stephen B.; McCarron, Margaret; Love, Carol; Clark, Stephen H.; Chovnick, Arthur

    1986-01-01

    This report represents a continuation of our laboratory's effort to understand the major phenomena associated with P-M dysgenesis-mediated transformation in Drosophila. A group of stable transformants are characterized with respect to rosy gene expression. Stable, true-breeding, line-specific variants in gene expression are described. These are shown to be associated with single transposons present in each line, and the lines are free of functional P elements. The effects on expression are cis-acting, and there are no identifiable rosy DNA sequence lesions associated with these transposons. Evidence is presented that demonstrates that two features of the transformation experimental system are responsible for such variation. The first relates to the fact that the transposons insert at numerous genomic sites. Both heterochromatic and euchromatic position effects are characterized. The second relates to the fact that transformation involves dysgenic mobilization of a P-element transposon. This process is mutagenic, and such a mutation is characterized. PMID:3013723

  1. Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network.

    PubMed

    Jiang, Xue; Zhang, Han; Quan, Xiongwen

    2016-01-01

    Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets.

  2. Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network

    PubMed Central

    Quan, Xiongwen

    2016-01-01

    Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets. PMID:28042568

  3. Spliced leader-based analyses reveal the effects of polycyclic aromatic hydrocarbons on gene expression in the copepod Pseudodiaptomus poplesia.

    PubMed

    Zhuang, Yunyun; Yang, Feifei; Xu, Donghui; Chen, Hongju; Zhang, Huan; Liu, Guangxing

    2017-02-01

    Polycyclic aromatic hydrocarbons (PAHs) are a group of toxic and carcinogenic pollutants that can adversely affect the development, growth and reproduction of marine organisms including copepods. However, knowledge on the molecular mechanisms regulating the response to PAH exposure in marine planktonic copepods is limited. In this study, we investigated the survival and gene expression of the calanoid copepod Pseudodiaptomus poplesia upon exposure to two PAHs, 1, 2-dimethylnaphthalene (1, 2-NAPH) and pyrene. Acute toxicity responses resulted in 96-h LC50 of 788.98μgL(-1) and 54.68μgL(-1) for 1, 2-NAPH and pyrene, respectively. Using the recently discovered copepod spliced leader as a primer, we constructed full-length cDNA libraries from copepods exposed to sublethal concentrations and revealed 289 unique genes of diverse functions, including stress response genes and novel genes previously undocumented for this species. Eighty-three gene families were specifically expressed in PAH exposure libraries. We further analyzed the expression of seven target genes by reverse transcription-quantitative PCR in a time-course test with three sublethal concentrations. These target genes have primary roles in detoxification, oxidative defense, and signal transduction, and include different forms of glutathione S-transferase (GST), glutathione peroxidases (GPX), peroxiredoxin (PRDX), methylmalonate-semialdehyde dehydrogenase (MSDH) and ras-related C3 botulinum toxin substrate (RAC1). Expression stability of seven candidate reference genes were evaluated and the two most stable ones (RPL15 and RPS20 for 1, 2-NAPH exposure, RPL15 and EF1D for pyrene exposure) were used to normalize the expression levels of the target genes. Significant upregulation was detected in GST-T, GST-DE, GPX4, PRDX6 and RAC1 upon 1, 2-NAPH exposure, and GST-DE and MSDH upon pyrene exposure. These results indicated that the oxidative stress was induced and that signal transduction might be affected by PAH

  4. Safe and Sensitive Antiviral Screening Platform Based on Recombinant Human Coronavirus OC43 Expressing the Luciferase Reporter Gene

    PubMed Central

    Shen, Liang; Yang, Yang; Ye, Fei; Liu, Gaoshan; Desforges, Marc

    2016-01-01

    Human coronaviruses (HCoVs) cause 15 to 30% of mild upper respiratory tract infections. However, no specific antiviral drugs are available to prevent or treat HCoV infections to date. Here, we developed four infectious recombinant HCoVs-OC43 (rHCoVs-OC43) which express the Renilla luciferase (Rluc) reporter gene. Among these four rHCoVs-OC43, rOC43-ns2DelRluc (generated by replacing ns2 with the Rluc gene) showed robust luciferase activity with only a slight impact on its growth characteristics. Additionally, this recombinant virus remained stable for at least 10 passages in BHK-21 cells. rOC43-ns2DelRluc was comparable to its parental wild-type virus (HCoV-OC43-WT) with respect to the quantity of the antiviral activity of chloroquine and ribavirin. We showed that chloroquine strongly inhibited HCoV-OC43 replication in vitro, with a 50% inhibitory concentration (IC50) of 0.33 μM. However, ribavirin showed inhibition of HCoV-OC43 replication only at high concentrations which may not be applicable to humans in clinical treatment, with an IC50 of 10 μM. Furthermore, using a luciferase-based small interfering RNA (siRNA) screening assay, we identified double-stranded-RNA-activated protein kinase (PKR) and DEAD box RNA helicases (DDX3X) that exhibited antiviral activities, which were further verified by the use of HCoV-OC43-WT. Therefore, rOC43-ns2DelRluc represents a promising safe and sensitive platform for high-throughput antiviral screening and quantitative analysis of viral replication. PMID:27381385

  5. Differentiation between Acute Skin Rejection in Allotransplantation and T-Cell Mediated Skin Inflammation Based on Gene Expression Analysis

    PubMed Central

    Wolfram, Dolores; Morandi, Evi M.; Eberhart, Nadine; Hautz, Theresa; Hackl, Hubert; Zelger, Bettina; Riede, Gregor; Wachter, Tanja; Dubrac, Sandrine; Ploner, Christian; Pierer, Gerhard; Schneeberger, Stefan

    2015-01-01

    Advances in microsurgical techniques and immunosuppressive medication have rendered transplantation of vascularized composite allografts possible, when autologous tissue is neither available nor sufficient for reconstruction. However, skin rejection and side effects of long-term immunosuppression still remain a major hurdle for wide adoption of this excellent reconstructive technique. Histopathologic changes during acute skin rejection in vascular composite allotransplantation often mimic inflammatory skin disorders and are hard to distinguish. Hence, the identification of diagnostic and therapeutic markers specific for skin rejection is of particular clinical need. Here we present novel markers allowing for early differentiation between rejection in hind limb allotransplantation and contact hypersensitivity. Assessment of Ccl7, Il18, and Il1b expression is most indicative of distinguishing skin rejection from skin inflammatory disorders. Gene expression levels varied significantly across skin types and regions, indicating localization specific mechanism of leukocyte migration and infiltration. Expression of Il12b, Il17a, and Il1b gene expression levels differed significantly between rejection and inflammation, independent of the skin type. In synopsis of the RNA expression profile and previously assessed protein expression, the Il1 family appears as a promising option for accurate skin rejection diagnosis and, as a following step, for development of novel rejection treatments. PMID:25756043

  6. Body weight and abdominal fat gene expression profile in response to a novel hydroxycitric acid-based dietary supplement.

    PubMed

    Roy, Sashwati; Rink, Cameron; Khanna, Savita; Phillips, Christina; Bagchi, Debasis; Bagchi, Manashi; Sen, Chandan K

    2004-01-01

    Obesity is a global public health problem, with about 315 million people worldwide estimated to fall into the WHO-defined obesity categories. Traditional herbal medicines may have some potential in managing obesity. Botanical dietary supplements often contain complex mixtures of phytochemicals that have additive or synergistic interactions. The dried fruit rind of Garcinia cambogia, also known as Malabar tamarind, is a unique source of (-)-hydroxycitric acid (HCA), which exhibits a distinct sour taste and has been safely used for centuries in Southeastern Asia to make meals more filling. Recently it has been demonstrated that HCA-SX or Super Citrimax, a novel derivative of HCA, is safe when taken orally and that HCA-SX is bioavailable in the human plasma as studied by GC-MS. Although HCA-SX has been observed to be conditionally effective in weight management in experimental animals as well as in humans, its mechanism of action remains to be understood. We sought to determine the effects of low-dose oral HCA-SX on the body weight and abdominal fat gene expression profile of Sprague-Dawley rats. We observed that at doses relevant for human consumption dietary HCA-SX significantly contained body weight growth. This response was associated with lowered abdominal fat leptin expression while plasma leptin levels remained unaffected. Repeated high-density microarray analysis of 9960 genes and ESTs present in the fat tissue identified a small set (approximately 1% of all genes screened) of specific genes sensitive to dietary HCA-SX. Other genes, including vital genes transcribing for mitochondrial/nuclear proteins and which are necessary for fundamental support of the tissue, were not affected by HCA-SX. Under the current experimental conditions, HCA-SX proved to be effective in restricting body weight gain in adult rats. Functional characterization of HCA-SX-sensitive genes revealed that upregulation of genes encoding serotonin receptors represent a distinct effect of

  7. Development and evaluation of a novel RT-qPCR based test for the quantification of HER2 gene expression in breast cancer.

    PubMed

    El Hadi, Hicham; Abdellaoui-Maane, Imane; Kottwitz, Denise; El Amrani, Manal; Bouchoutrouch, Nadia; Qmichou, Zineb; Karkouri, Mehdi; ElAttar, Hicham; Errihani, Hassan; Fernandez, Pedro L; Bakri, Youssef; Sefrioui, Hassan; Moumen, Abdeladim

    2017-03-20

    Accurate measurement of Human epidermal growth factor receptor (HER2) gene expression is central for breast or stomach cancer therapy orientation and prognosis. The current standards testing methods for HER2 expression are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). In the current study, we explored the use of quantitative real time reverse transcription-PCR (RT-qPCR) as a potential method for the accurate relative quantification of the HER2 gene using formalin fixed paraffin embedded (FFPE) breast cancer biopsy samples. The main aim of the current study is to measure the level of concordance of RT-qPCR based quantification of HER2 overexpression with both IHC and FISH. Accordingly, an endogenous control gene (ECG) is required for this relative quantification and should ideally be expressed equivalently across tested samples. Stably expressed ECGs have been selected from a panel of seven genes using GenEx V6 software which is based on geNorm and NormFinder and statistical methods. Quantification of HER2 gene expression was performed by our RT-qPCR-based test and compared to the results obtained by both IHC and FISH methods. HER2 gene quantification using RT-qPCR test was normalized using the two ECGs (RPL30 and RPL37A) that were successfully identified and selected from a panel of seven genes as the most stable and reliable ECGs. We evaluated a total of 216 FFPE tissue samples from breast cancer patients. The results obtained with RT-qPCR in the current study were compared to both IHC and FISH data collected for the same patients. In addition to an internal evaluation, an external evaluation of this assay was also performed in a recognized pathology center in Europe (Clinic Barcelona Hospital Universitari, Spain) using 116 FFPE breast cancer tissue samples. The results demonstrated a high concordance between RT-qPCR and either IHC (98%) or FISH (72%) methods. Accordantly, the overall concordance was 85%. To our knowledge, this is the

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

    PubMed Central

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

    2015-01-01

    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. PMID:26689951

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

    PubMed

    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.

  10. Mindfulness-Based Stress Reduction training reduces loneliness and pro-inflammatory gene expression in older adults: a small randomized controlled trial.

    PubMed

    Creswell, J David; Irwin, Michael R; Burklund, Lisa J; Lieberman, Matthew D; Arevalo, Jesusa M G; Ma, Jeffrey; Breen, Elizabeth Crabb; Cole, Steven W

    2012-10-01

    Lonely older adults have increased expression of pro-inflammatory genes as well as increased risk for morbidity and mortality. Previous behavioral treatments have attempted to reduce loneliness and its concomitant health risks, but have had limited success. The present study tested whether the 8-week Mindfulness-Based Stress Reduction (MBSR) program (compared to a Wait-List control group) reduces loneliness and downregulates loneliness-related pro-inflammatory gene expression in older adults (N = 40). Consistent with study predictions, mixed effect linear models indicated that the MBSR program reduced loneliness, compared to small increases in loneliness in the control group (treatment condition × time interaction: F(1,35) = 7.86, p = .008). Moreover, at baseline, there was an association between reported loneliness and upregulated pro-inflammatory NF-κB-related gene expression in circulating leukocytes, and MBSR downregulated this NF-κB-associated gene expression profile at post-treatment. Finally, there was a trend for MBSR to reduce C Reactive Protein (treatment condition × time interaction: (F(1,33) = 3.39, p = .075). This work provides an initial indication that MBSR may be a novel treatment approach for reducing loneliness and related pro-inflammatory gene expression in older adults.

  11. Mindfulness-Based Stress Reduction Training Reduces Loneliness and Pro-Inflammatory Gene Expression in Older Adults: A Small Randomized Controlled Trial

    PubMed Central

    Creswell, J. David; Irwin, Michael R.; Burklund, Lisa J.; Lieberman, Matthew D.; Arevalo, Jesusa M. G.; Ma, Jeffrey; Breen, Elizabeth Crabb; Cole, Steven W.

    2013-01-01

    Lonely older adults have increased expression of pro-inflammatory genes as well as increased risk for morbidity and mortality. Previous behavioral treatments have attempted to reduce loneliness and its concomitant health risks, but have had limited success. The present study tested whether the 8-week Mindfulness-Based Stress Reduction (MBSR) program (compared to a Wait-List control group) reduces loneliness and downregulates loneliness-related pro-inflammatory gene expression in older adults (N=40). Consistent with study predictions, mixed effect linear models indicated that the MBSR program reduced loneliness, compared to small increases in loneliness in the control group (treatment condition × time interaction: F(1,35)=7.86, p=.008). Moreover, at baseline, there was an association between reported loneliness and upregulated pro-inflammatory NF-κB-related gene expression in circulating leukocytes, and MBSR downregulated this NF-κB-associated gene expression profile at post-treatment. Finally, there was a trend for MBSR to reduce C Reactive Protein (treatment condition × time interaction: (F(1,33)=3.39, p=.075). This work provides an initial indication that MBSR may be a novel treatment approach for reducing loneliness and related pro-inflammatory gene expression in older adults. PMID:22820409

  12. Harnessing gene expression networks to prioritize candidate epileptic encephalopathy genes.

    PubMed

    Oliver, Karen L; Lukic, Vesna; Thorne, Natalie P; Berkovic, Samuel F; Scheffer, Ingrid E; Bahlo, Melanie

    2014-01-01

    We apply a novel gene expression network analysis to a cohort of 182 recently reported candidate Epileptic Encephalopathy genes to identify those most likely to be true Epileptic Encephalopathy genes. These candidate genes were identified as having single variants of likely pathogenic significance discovered in a large-scale massively parallel sequencing study. Candidate Epileptic Encephalopathy genes were prioritized according to their co-expression with 29 known Epileptic Encephalopathy genes. We utilized developing brain and adult brain gene expression data from the Allen Human Brain Atlas (AHBA) and compared this to data from Celsius: a large, heterogeneous gene expression data warehouse. We show replicable prioritization results using these three independent gene expression resources, two of which are brain-specific, with small sample size, and the third derived from a heterogeneous collection of tissues with large sample size. Of the nineteen genes that we predicted with the highest likelihood to be true Epileptic Encephalopathy genes, two (GNAO1 and GRIN2B) have recently been independently reported and confirmed. We compare our results to those produced by an established in silico prioritization approach called Endeavour, and finally present gene expression networks for the known and candidate Epileptic Encephalopathy genes. This highlights sub-networks of gene expression, particularly in the network derived from the adult AHBA gene expression dataset. These networks give clues to the likely biological interactions between Epileptic Encephalopathy genes, potentially highlighting underlying mechanisms and avenues for therapeutic targets.

  13. Differential gene expression in anatomical compartments of the human eye

    PubMed Central

    Diehn, Jennifer J; Diehn, Maximilian; Marmor, Michael F; Brown, Patrick O

    2005-01-01

    Background The human eye is composed of multiple compartments, diverse in form, function, and embryologic origin, that work in concert to provide us with our sense of sight. We set out to systematically characterize the global gene expression patterns that specify the distinctive characteristics of the various eye compartments. Results We used DNA microarrays representing approximately 30,000 human genes to analyze gene expression in the cornea, lens, iris, ciliary body, retina, and optic nerve. The distinctive patterns of expression in each compartment could be interpreted in relation to the physiology and cellular composition of each tissue. Notably, the sets of genes selectively expressed in the retina and in the lens were particularly large and diverse. Genes with roles in immune defense, particularly complement components, were expressed at especially high levels in the anterior segment tissues. We also found consistent differences between the gene expression patterns of the macula and peripheral retina, paralleling the differences in cell layer densities between these regions. Based on the hypothesis that genes responsible for diseases that affect a particular eye compartment are likely to be selectively expressed in that compartment, we compared our gene expression signatures with genetic mapping studies to identify candidate genes for diseases affecting the cornea, lens, and retina. Conclusion Through genome-scale gene expression profiling, we were able to discover distinct gene expression 'signatures' for each eye compartment and identified candidate disease genes that can serve as a reference database for investigating the physiology and pathophysiology of the eye. PMID:16168081

  14. Single-cell multiple gene expression analysis based on single-molecule-detection microarray assay for multi-DNA determination.

    PubMed

    Li, Lu; Wang, Xianwei; Zhang, Xiaoli; Wang, Jinxing; Jin, Wenrui

    2015-01-07

    We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3×10(-16) mol L(-1). The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three types of cDNAs corresponding to beta-2-microglobulin, glyceraldehyde-3-phosphate dehydrogenase and ribosomal protein, large, P2 mRNAs in single human breast cancer cells and 5 random synthetic DNAts are simultaneously quantified to examine the SMA and SMA-based single-cell multiple gene expression analysis.

  15. Detection of overlapping protein complexes in gene expression, phenotype and pathways of Saccharomyces cerevisiae using Prorank based Fuzzy algorithm.

    PubMed

    Manikandan, P; Ramyachitra, D; Banupriya, D

    2016-04-15

    Proteins show their functional activity by interacting with other proteins and forms protein complexes since it is playing an important role in cellular organization and function. To understand the higher order protein organization, overlapping is an important step towards unveiling functional and evolutionary mechanisms behind biological networks. Most of the clustering algorithms do not consider the weighted as well as overlapping complexes. In this research, Prorank based Fuzzy algorithm has been proposed to find the overlapping protein complexes. The Fuzzy detection algorithm is incorporated in the Prorank algorithm after ranking step to find the overlapping community. The proposed algorithm executes in an iterative manner to compute the probability of robust clusters. The proposed and the existing algorithms were tested on different datasets such as PPI-D1, PPI-D2, Collins, DIP, Krogan Core and Krogan-Extended, gene expression such as GSE7645, GSE22269, GSE26923, pathways such as Meiosis, MAPK, Cell Cycle, phenotypes such as Yeast Heterogeneous and Yeast Homogeneous datasets. The experimental results show that the proposed algorithm predicts protein complexes with better accuracy compared to other state of art algorithms.

  16. Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

    PubMed Central

    Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

    2015-01-01

    Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

  17. Evaluation of a nanotechnology-based approach to induce gene-expression in human THP-1 macrophages under inflammatory conditions.

    PubMed

    Bernal, Laura; Alvarado-Vázquez, Abigail; Ferreira, David Wilson; Paige, Candler A; Ulecia-Morón, Cristina; Hill, Bailey; Caesar, Marina; Romero-Sandoval, E Alfonso

    2017-02-01

    Macrophages orchestrate the initiation and resolution of inflammation by producing pro- and anti-inflammatory products. An imbalance in these mediators may originate from a deficient or excessive immune response. Therefore, macrophages are valid therapeutic targets to restore homeostasis under inflammatory conditions. We hypothesize that a specific mannosylated nanoparticle effectively induces gene expression in human macrophages under inflammatory conditions without undesirable immunogenic responses. THP-1 macrophages were challenged with lipopolysaccharide (LPS, 5μg/mL). Polyethylenimine (PEI) nanoparticles grafted with a mannose receptor ligand (Man-PEI) were used as a gene delivery method. Nanoparticle toxicity, Man-PEI cellular uptake rate and gene induction efficiency (GFP, CD14 or CD68) were studied. Potential immunogenic responses were evaluated by measuring the production of tumor necrosis factor-alpha (TNF-α), Interleukin (IL)-6 and IL-10. Man-PEI did not produce cytotoxicity, and it was effectively up-taken by THP-1 macrophages (69%). This approach produced a significant expression of GFP (mRNA and protein), CD14 and CD68 (mRNA), and transiently and mildly reduced IL-6 and IL-10 levels in LPS-challenged macrophages. Our results indicate that Man-PEI is suitable for inducing an efficient gene overexpression in human macrophages under inflammatory conditions with limited immunogenic responses. Our promising results set the foundation to test this technology to induce functional anti-inflammatory genes.

  18. The Salinity Responsive Mechanism of a Hydroxyproline-Tolerant Mutant of Peanut Based on Digital Gene Expression Profiling Analysis

    PubMed Central

    Song, Xiaojun; Wang, Jingshan; Zhao, Mingxia; Qiao, Lixian

    2016-01-01

    Soil salinity seriously limits plant growth and yield. Strategies have been developed for plants to cope with various environmental stresses during evolution. To screen for the broad-spectrum genes and the molecular mechanism about a hydroxyproline-tolerant mutant of peanut with enhanced salinity resistance under salinity stress, digital gene expression (DGE) sequencing was performed in the leaves of salinity-resistant mutant (S2) and Huayu20 as control (S4) under salt stress. The results indicate that major transcription factor families linked to salinity stress responses (NAC, bHLH, WRKY, AP2/ERF) are differentially expressed in the leaves of peanut under salinity stress. In addition, genes related to cell wall loosening and stiffening (xyloglucan endotransglucosylase/hydrolases, peroxidases, lipid transfer protein, expansin, extension), late embryogenesis abundant protein family, fatty acid biosynthesis and metabolism (13-lipoxygenase omega-6 fatty acid desaturase, omega-3 fatty acid desaturase) and some previously reported stress-related genes encoding proteins such as defensin, universal stress protein, metallothionein, peroxidase etc, and some other known or unknown function stress related genes, have been identified. The information from this study will be useful for further research on the mechanism of salinity resistance and will provide a useful genomic resource for the breeding of salinity resistance variety in peanut. PMID:27661086

  19. Pulmonary Gene Expression Profiling of Inhaled Ricin

    DTIC Science & Technology

    2007-11-02

    in which 34 genes had statistically significant changes in gene expression. Transcripts identified by the assay included those that facilitate...gene expression. Transcripts identified by the assay included those that facilitate tissue healing (early growth response gene (egr)-1), regulate...impingement to determine aerosol concentration. Ricin concentrations from impinger samples were measured by protein assay (Pierce, MicroBCA, Rockford

  20. RNA sequencing to study gene expression and SNP variations associated with growth in zebrafish fed a plant protein-based diet.

    PubMed

    Ulloa, Pilar E; Rincón, Gonzalo; Islas-Trejo, Alma; Araneda, Cristian; Iturra, Patricia; Neira, Roberto; Medrano, Juan F

    2015-06-01

    The objectives of this study were to measure gene expression in zebrafish and then identify SNP to be used as potential markers in a growth association study. We developed an approach where muscle samples collected from low- and high-growth fish were analyzed using RNA-Sequencing (RNA-seq), and SNP were chosen from the genes that were differentially expressed between the low and high groups. A population of 24 families was fed a plant protein-based diet from the larval to adult stages. From a total of 440 males, 5 % of the fish from both tails of the weight gain distribution were selected. Total RNA was extracted from individual muscle of 8 low-growth and 8 high-growth fish. Two pooled RNA-Seq libraries were prepared for each phenotype using 4 fish per library. Libraries were sequenced using the Illumina GAII Sequencer and analyzed using the CLCBio genomic workbench software. One hundred and twenty-four genes were differentially expressed between phenotypes (p value < 0.05 and FDR < 0.2). From these genes, 164 SNP were selected and genotyped in 240 fish samples. Marker-trait analysis revealed 5 SNP associated with growth in key genes (Nars, Lmod2b, Cuzd1, Acta1b, and Plac8l1). These genes are good candidates for further growth studies in fish and to consider for identification of potential SNPs associated with different growth rates in response to a plant protein-based diet.

  1. Benzaldehyde Schiff bases regulation to the metabolism, hemolysis, and virulence genes expression in vitro and their structure-microbicidal activity relationship.

    PubMed

    Xia, Lei; Xia, Yu-Fen; Huang, Li-Rong; Xiao, Xiao; Lou, Hua-Yong; Liu, Tang-Jingjun; Pan, Wei-Dong; Luo, Heng

    2015-06-05

    There is an urgent need to develop new antibacterial agents because of multidrug resistance by bacteria and fungi. Schiff bases (aldehyde or ketone-like compounds) exhibit intense antibacterial characteristics, and are therefore, promising candidates as antibacterial agents. To investigate the mechanism of action of newly designed benzaldehyde Schiff bases, a series of high-yielding benzaldehyde Schiff bases were synthesized, and their structures were determined by NMR and MS spectra data. The structure-microbicidal activity relationship of derivatives was investigated, and the antibacterial mechanisms were investigated by gene assays for the expression of functional genes in vitro using Escherichia coli, Staphylococcus aureus, and Bacillus subtilis. The active compounds were selective for certain active groups. The polar substitution of the R2 group of the amino acids in the Schiff bases, affected the antibacterial activity against E. coli and S. aureus; specific active group at the R3 or R4 groups of the acylhydrazone Schiff bases could improve their inhibitory activity against these three tested organisms. The antibacterial mechanism of the active benzaldehyde Schiff bases appeared to regulate the expression of metabolism-associated genes in E. coli, hemolysis-associated genes in B. subtilis, and key virulence genes in S. aureus. Some benzaldehyde Schiff bases were bactericidal to all the three strains and appeared to regulate gene expression associated with metabolism, hemolysis, and virulence, in vitro. The newly designed benzaldehyde Schiff bases possessed unique antibacterial activity and might be potentially useful for prophylactic or therapeutic intervention of bacterial infections.

  2. 454 pyrosequencing-based analysis of gene expression profiles in the amphipod Melita plumulosa: transcriptome assembly and toxicant induced changes.

    PubMed

    Hook, Sharon E; Twine, Natalie A; Simpson, Stuart L; Spadaro, David A; Moncuquet, Philippe; Wilkins, Marc R

    2014-08-01

    Next generation sequencing using Roche's 454 pyrosequencing platform can be used to generate genomic information for non-model organisms, although there are bioinformatic challenges associated with these studies. These challenges are compounded by a lack of a standardized protocol to either assemble data or to evaluate the quality of a de novo transcriptome. This study presents an assembly of the control and toxicant responsive transcriptome of Melita plumulosa, an Australian amphipod commonly used in ecotoxicological studies. RNA was harvested from control amphipods, juvenile amphipods, and from amphipods exposed to either metal or diesel contaminated sediments. This RNA was used as the basis for a 454 based transcriptome sequencing effort. Sequencing generated 1.3 million reads from control, juvenile, metal-exposed and diesel-exposed amphipods. Different read filtering and assembly protocols were evaluated to generate an assembly that (i) had an optimal number of contigs; (ii) had long contigs; (iii) contained a suitable representation of conserved genes; and (iv) had long ortholog alignment lengths relative to the length of each contig. A final assembly, generated using fixed-length trimming based on the sequence quality scores, followed by assembly using the MIRA algorithm, produced the best results. The 26,625 contigs generated via this approach were annotated using Blast2GO, and the differential expression between treatments and control was determined by mapping with BWA followed by DESeq. Although the mapping generated low coverage, many differentially expressed contigs, including some with known developmental or toxicological function, were identified. This study demonstrated that 454 pyrosequencing is an effective means of generating reference transcriptome information for organisms, such as the amphipod M. plumulosa, that have no genomic information available in databases or in closely related sequenced species. It also demonstrated how optimization of

  3. Differential Gene Expression during Larval Metamorphic Development in the Pearl Oyster, Pinctada fucata, Based on Transcriptome Analysis

    PubMed Central

    Zhang, Bo; Huang, Guiju; Liu, Baosuo; Fan, Sigang; Zhang, Dongling

    2016-01-01

    P. fucata experiences a series of transformations in appearance, from swimming larvae to sessile juveniles, during which significant changes in gene expression likely occur. Thus, P. fucata could be an ideal model in which to study the molecular mechanisms of larval metamorphosis during development in invertebrates. To study the molecular driving force behind metamorphic development in larvae of P. fucata, transcriptomes of five larval stages (trochophore, D-shape, umbonal, eyespots, and spats) were sequenced using an Illumina HiSeq™ 2000 system and assembled and characterized with the transcripts of six tissues. As a result, a total of 174,126 unique transcripts were assembled and 60,999 were annotated. The number of unigenes varied among the five larval stages. Expression profiles were distinctly different between trochophore, D-shape, umbonal, eyespots, and spats larvae. As a result, 29 expression trends were sorted, of which eight were significant. Among others, 80 development-related, differentially expressed unigenes (DEGs) were identified, of which the majority were homeobox-containing genes. Most DEGs occurred among trochophore, D-shaped, and UES (umbonal, eyespots, and spats) larvae as verified by qPCR. Principal component analysis (PCA) also revealed significant differences in expression among trochophore, D-shaped, and UES larvae with ten transcripts identified but no matching annotations. PMID:27843935

  4. Does inbreeding affect gene expression in birds?

    PubMed

    Hansson, Bengt; Naurin, Sara; Hasselquist, Dennis

    2014-09-01

    Inbreeding increases homozygosity, exposes genome-wide recessive deleterious alleles and often reduces fitness. The physiological and reproductive consequences of inbreeding may be manifested already during gene regulation, but the degree to which inbreeding influences gene expression is unknown in most organisms, including in birds. To evaluate the pattern of inbreeding-affected gene expression over the genome and in relation to sex, we performed a transcriptome-wide gene expression (10 695 genes) study of brain tissue of 10-day-old inbred and outbred, male and female zebra finches. We found significantly lower gene expression in females compared with males at Z-linked genes, confirming that dosage compensation is incomplete in female birds. However, inbreeding did not affect gene expression at autosomal or sex-linked genes, neither in males nor in females. Analyses of single genes again found a clear sex-biased expression at Z-linked genes, whereas only a single gene was significantly affected by inbreeding. The weak effect of inbreeding on gene expression in zebra finches contrasts to the situation, for example, in Drosophila where inbreeding has been found to influence gene expression more generally and at stress-related genes in particular.

  5. Development and Validation of a Gene-Based Model for Outcome Prediction in Germ Cell Tumors Using a Combined Genomic and Expression Profiling Approach.

    PubMed

    Korkola, James E; Heck, Sandy; Olshen, Adam B; Feldman, Darren R; Reuter, Victor E; Houldsworth, Jane; Bosl, George J; Chaganti, R S K

    2015-01-01

    Germ Cell Tumors (GCT) have a high cure rate, but we currently lack the ability to accurately identify the small subset of patients who will die from their disease. We used a combined genomic and expression profiling approach to identify genomic regions and underlying genes that are predictive of outcome in GCT patients. We performed array-based comparative genomic hybridization (CGH) on 53 non-seminomatous GCTs (NSGCTs) treated with cisplatin based chemotherapy and defined altered genomic regions using Circular Binary Segmentation. We identified 14 regions associated with two year disease-free survival (2yDFS) and 16 regions associated with five year disease-specific survival (5yDSS). From corresponding expression data, we identified 101 probe sets that showed significant changes in expression. We built several models based on these differentially expressed genes, then tested them in an independent validation set of 54 NSGCTs. These predictive models correctly classified outcome in 64-79.6% of patients in the validation set, depending on the endpoint utilized. Survival analysis demonstrated a significant separation of patients with good versus poor predicted outcome when using a combined gene set model. Multivariate analysis using clinical risk classification with the combined gene model indicated that they were independent prognostic markers. This novel set of predictive genes from altered genomic regions is almost entirely independent of our previously identified set of predictive genes for patients with NSGCTs. These genes may aid in the identification of the small subset of patients who are at high risk of poor outcome.

  6. [Neuronal plasticity and gene expression].

    PubMed

    Sokolova, O O; Shtark, M B; Lisachev, P D

    2010-01-01

    Neuronal plasticity--a fundamental feature of brain--provides adequate interactions with dynamic environment. One of the most deeply investigated forms of the neuronal plasticity is a long-term potentiation (LTP)--a phenomenon underlying learning and memory. Signal paths activated during LTP converge into the nuclear of the neuron, giving rise to launch of the molecular-genetic programs, which mediate structural and functional remodeling of synapses. In the review data concerning involvement of multilevel gene expression into plastic change under neuronal activation are summarized.

  7. Analysis of baseline gene expression levels from ...

    EPA Pesticide Factsheets

    The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

  8. Transcriptome-Based Identification of Differently Expressed Genes from Xanthomonas oryzae pv. oryzae Strains Exhibiting Different Virulence in Rice Varieties

    PubMed Central

    Noh, Tae-Hwan; Song, Eun-Sung; Kim, Hong-Il; Kang, Mi-Hyung; Park, Young-Jin

    2016-01-01

    Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial blight (BB) in rice (Oryza sativa L.). In this study, we investigated the genome-wide transcription patterns of two Xoo strains (KACC10331 and HB1009), which showed different virulence patterns against eight rice cultivars, including IRBB21 (carrying Xa21). In total, 743 genes showed a significant change (p-value < 0.001 in t-tests) in their mRNA expression levels in the HB1009 (K3a race) strain compared with the Xoo KACC10331 strain (K1 race). Among them, four remarkably enriched GO terms, DNA binding, transposition, cellular nitrogen compound metabolic process, and cellular macromolecule metabolic process, were identified in the upregulated genes. In addition, the expression of 44 genes was considerably higher (log2 fold changes > 2) in the HB1009 (K3a race) strain than in the Xoo KACC10331 (K1 race) strain. Furthermore, 13 and 12 genes involved in hypersensitive response and pathogenicity (hrp) and two-component regulatory systems (TCSs), respectively, were upregulated in the HB1009 (K3a race) strain compared with the Xoo KACC10331 (K1 race) strain, which we determined using either quantitative real-time PCR analysis or next-generation RNA sequencing. These results will be helpful to improve our understanding of Xoo and to gain a better insight into the Xoo–rice interactions. PMID:26907259

  9. Design and multiseries validation of a web-based gene expression assay for predicting breast cancer recurrence and patient survival.

    PubMed

    Van Laar, Ryan K

    2011-05-01

    Gene expression analysis is a valuable tool for determining the risk of disease recurrence and overall survival of an individual patient with breast cancer. The purpose of this study was to create and validate a robust prognostic algorithm and implement it within an online analysis environment. Genomic and clinical data from 477 clinically diverse patients with breast cancer were analyzed with Cox regression models to identify genes associated with outcome, independent of standard prognostic factors. Percentile-ranked expression data were used to train a "metagene" algorithm to stratify patients as having a high or low risk of recurrence. The classifier was applied to 1016 patients from five independent series. The 200-gene algorithm stratifies patients into risk groups with statistically and clinically significant differences in recurrence-free and overall survival. Multivariate analysis revealed the classifier to be the strongest predictor of outcome in each validation series. In untreated node-negative patients, 88% sensitivity and 44% specificity for 10-year recurrence-free survival was observed, with positive and negative predictive values of 32% and 92%, respectively. High-risk patients appear to significantly benefit from systemic adjuvant therapy. A 200-gene prognosis signature has been developed and validated using genomic and clinical data representing a range of breast cancer clinicopathological subtypes. It is a strong independent predictor of patient outcome and is available for research use.

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

    SciTech Connect

    Salem, Tamer Z.; Zhang, Fengrui; Thiem, Suzanne M.

    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.

  11. Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas.

    PubMed

    Eising, Else; Huisman, Sjoerd M H; Mahfouz, Ahmed; Vijfhuizen, Lisanne S; Anttila, Verneri; Winsvold, Bendik S; Kurth, Tobias; Ikram, M Arfan; Freilinger, Tobias; Kaprio, Jaakko; Boomsma, Dorret I; van Duijn, Cornelia M; Järvelin, Marjo-Riitta R; Zwart, John-Anker; Quaye, Lydia; Strachan, David P; Kubisch, Christian; Dichgans, Martin; Davey Smith, George; Stefansson, Kari; Palotie, Aarno; Chasman, Daniel I; Ferrari, Michel D; Terwindt, Gisela M; de Vries, Boukje; Nyholt, Dale R; Lelieveldt, Boudewijn P F; van den Maagdenberg, Arn M J M; Reinders, Marcel J T

    2016-04-01

    Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

  12. [Structure and expression of thyroglobulin gene].

    PubMed

    Vassart, G; Brocas, H; Christophe, D; de Martynoff, G; Leriche, A; Mercken, L; Pohl, V; Van Heuverswyn, B

    1982-01-01

    Thyroglobulin is composed of two 300000 dalton polypeptide chains, translated from an 8000 base mRNA. Preparation of a full length cDNA and its cloning in E. coli have lead to the demonstration that the polypeptides of thyroglobulin protomers were identical. Used as molecular probes, the cloned cDNA allowed the isolation of a fragment of thyroglobulin gene. Electron microscopic studies have demonstrated that this gene contains more than 90% intronic material separating small size exons (less than 200 bp). Sequencing of bovine thyroglobulin structural gene is in progress. Preliminary results show evidence for the existence of repetitive segments. Availability of cloned DNA complementary to bovine and human thyroglobulin mRNA allows the study of genetic defects of thyroglobulin gene expression in the human and in various animal models.

  13. Involvement of Differential Relationship between HCV Replication and Hepatic PRR Signaling Gene Expression in Responsiveness to IFN-Based Therapy.

    PubMed

    Yuki, Nobukazu; Matsumoto, Shinji; Kato, Michio; Yamaguchi, Toshikazu

    2013-01-01

    Aim. To gain an insight into the effect of HCV replication-associated interference with the IFN system on hepatic mRNA expression involved in IFN production. Methods. Relative mRNA expression of TLR3/RIG-I signaling genes involved in IFN- β production was correlated with positive- and negative-strand HCV RNAs in pretreatment liver tissues responsive and nonresponsive to peginterferon and ribavirin for chronic hepatitis C genotype 1. Treatment response was analyzed for per protocol population at weeks 12 (n = 45) and 24 (n = 40) and at 24 weeks aftertreatment (n = 38). Results. HCV replication had no relation to the expression of TLR3, RIG-I, TRIF, IPS-1, IRF3, and IFN- β mRNAs in responders. In striking contrast, positive- and/or negative-strand HCV showed positive correlations with TLR3, RIG-I, TRIF, IPS-1, and IRF3 mRNAs in week-12 nonresponders; with RIG-I, TRIF, IPS-1, and IRF3 mRNAs in week-24 nonresponders; and with TLR3, RIG-I, and IRF3 mRNAs in posttreatment nonresponders. Thus mRNA expression of TLR3/RIG-I signaling genes was increased in relation to viral replication in nonresponders. Conclusions. The findings in IFN nonresponders may imply a host feedback response to severe impairment of the IFN system associated with HCV replication.

  14. RNA-seq based detection of differentially expressed genes in the skeletal muscle of Duroc pigs with distinct lipid profiles

    PubMed Central

    Cardoso, T. F.; Cánovas, A.; Canela-Xandri, O.; González-Prendes, R.; Amills, M.; Quintanilla, R.

    2017-01-01

    We have used a RNA-seq approach to investigate differential expression in the skeletal muscle of swine (N = 52) with divergent lipid profiles i.e. HIGH (increased intramuscular fat and muscle saturated and monounsaturated fatty acid contents, higher serum lipid concentrations and fatness) and LOW pigs (leaner and with an increased muscle polyunsaturated fatty acid content). The number of mRNAs and non-coding RNAs (ncRNAs) expressed in the porcine gluteus medius muscle were 18,104 and 1,558, respectively. At the nominal level of significance (P-value ≤ 0.05), we detected 1,430 mRNA and 12 non-coding RNA (ncRNA) transcripts as differentially expressed (DE) in the gluteus medius muscle of HIGH vs LOW pigs. This smaller contribution of ncRNAs to differential expression may have biological and technical reasons. We performed a second analysis, that was more stringent (P-value ≤ 0.01 and fold-change ≥ 1.5), and only 96 and 0 mRNA-and ncRNA-encoding genes happened to be DE, respectively. The subset of DE mRNA genes was enriched in pathways related with lipid (lipogenesis and triacylglycerol degradation) and glucose metabolism. Moreover, HIGH pigs showed a more lipogenic profile than their LOW counterparts. PMID:28195222

  15. Vibrio cholerae anaerobic induction of virulence gene expression is controlled by thiol-based switches of virulence regulator AphB

    PubMed Central

    Liu, Zhi; Yang, Menghua; Peterfreund, Gregory L.; Tsou, Amy M.; Selamoglu, Nur; Daldal, Fevzi; Zhong, Zengtao; Kan, Biao; Zhu, Jun

    2011-01-01

    Bacterial pathogens have evolved sophisticated signal transduction systems to coordinately control the expression of virulence determinants. For example, the human pathogen Vibrio cholerae is able to respond to host environmental signals by activating transcriptional regulatory cascades. The host signals that stimulate V. cholerae virulence gene expression, however, are still poorly understood. Previous proteomic studies indicated that the ambient oxygen concentration plays a role in V. cholerae virulence gene expression. In this study, we found that under oxygen-limiting conditions, an environment similar to the intestines, V. cholerae virulence genes are highly expressed. We show that anaerobiosis enhances dimerization and activity of AphB, a transcriptional activator that is required for the expression of the key virulence regulator TcpP, which leads to the activation of virulence factor production. We further show that one of the three cysteine residues in AphB, C235, is critical for oxygen responsiveness, as the AphBC235S mutant can activate virulence genes under aerobic conditions in vivo and can bind to tcpP promoters in the absence of reducing agents in vitro. Mass spectrometry analysis suggests that under aerobic conditions, AphB is modified at the C235 residue. This modification is reversible between oxygen-rich aquatic environments and oxygen-limited human hosts, suggesting that V. cholerae may use a thiol-based switch mechanism to sense intestinal signals and activate virulence. PMID:21187377

  16. Gene-expression signature of tumor recurrence in patients with stage II and III colon cancer treated with 5'fluoruracil-based adjuvant chemotherapy.

    PubMed

    Giráldez, María Dolores; Lozano, Juan José; Cuatrecasas, Míriam; Alonso-Espinaco, Virginia; Maurel, Joan; Mármol, Maribel; Hörndler, Carlos; Ortego, Javier; Alonso, Vicente; Escudero, Pilar; Ramírez, Gina; Petry, Christoph; Lasalvia, Luis; Bohmann, Kerstin; Wirtz, Ralph; Mira, Aurea; Castells, Antoni

    2013-03-01

    Although receiving adjuvant chemotherapy after radical surgery, a disappointing proportion of patients with colorectal cancer will develop tumor recurrence. Probability of relapse is currently predicted from pathological staging, there being a need for additional markers to further select high-risk patients. This study was aimed to identify a gene-expression signature to predict tumor recurrence in patients with Stages II and III colon cancer treated with 5'fluoruracil (5FU)-based adjuvant chemotherapy. Two-hundred and twenty-eight patients diagnosed with Stages II-III colon cancer and treated with surgical resection and 5FU-based adjuvant chemotherapy were included. RNA was extracted from formalin-fixed, paraffin-embedded tissue samples and expression of 27 selected candidate genes was analyzed by RT-qPCR. A tumor recurrence predicting model, including clinico-pathological variables and gene-expression profiling, was developed by Cox regression analysis and validated by bootstrapping. The regression analysis identified tumor stage and S100A2 and S100A10 gene expression as independently associated with tumor recurrence. The risk score derived from this model was able to discriminate two groups with a highly significant different probability of tumor recurrence (HR, 2.75; 95%CI, 1.71-4.39; p = 0.0001), which it was maintained when patients were stratified according to tumor stage. The algorithm was also able to distinguish two groups with different overall survival (HR, 2.68; 95%CI, 1.12-6.42; p = 0.03). Identification of a new gene-expression signature associated with a high probability of tumor recurrence in patients with Stages II and III colon cancer receiving adjuvant 5FU-based chemotherapy, and its combination in a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies.

  17. Effects of high-sulphur water on hepatic gene expression of steers fed fibre-based diets.

    PubMed

    Kessler, K L; Olson, K C; Wright, C L; Austin, K J; McInnerney, K; Johnson, P S; Cockrum, R R; Jons, A M; Cammack, K M

    2013-10-01

    Sulphur-induced polioencephalomalacia (sPEM), a neurological disorder affecting ruminants, is frequently associated with the consumption of high-sulphur (S) water and subsequent poor performance. Currently, there is no economical method for S removal from surface water sources, and alternative water sources are typically neither readily available nor cost-effective. Determination of genes differentially expressed in response to high-S water consumption may provide a better understanding of the physiology corresponding to high dietary S and ultimately lead to the development of treatment and prevention strategies. The objective of this study was to determine changes in gene expression in the liver, an organ important for S metabolism, of fibre-fed steers consuming high-S water. For this study, liver tissues were collected on the final day of a trial from yearling steers randomly assigned to low-S water control (566 mg/kg SO4 ; n = 24), high-S water (3651 mg/kg SO4 ; n = 24) or high-S water plus clinoptilolite supplemented at either 2.5% (n = 24) or 5.0% (n = 24) of diet dry matter (DM). Microarray analyses on randomly selected healthy low-S control (n = 4) and high-S (n = 4; no clinoptilolite) steers using the Affymetrix GeneChip Bovine Genome Array revealed 488 genes upregulated (p < 0.05) and 154 genes downregulated (p < 0.05) in response to the high- vs. low-S water consumption. Real-time RT-PCR confirmed the upregulation (p < 0.10) of seven genes involved in inflammatory response and immune functions. Changes in such genes suggest that ruminant animals administered high-S water may be undergoing an inflammation or immune response, even if signs of sPEM or compromised health are not readily observed. Further study of these, and other affected genes, may deliver new insights into the physiology underlying the response to high dietary S, ultimately leading to the development of treatments for high S-affected ruminant

  18. A gene expression biomarker accurately predicts estrogen ...

    EPA Pesticide Factsheets

    The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

  19. Mechanoregulation of gene expression in fibroblasts

    PubMed Central

    Wang, James H.-C.; Thampatty, Bhavani P.; Lin, Jeen-Shang; Im, Hee-Jeong

    2010-01-01

    Mechanical loads placed on connective tissues alter gene expression in fibroblasts through mechanotransduction mechanisms by which cells convert mechanical signals into cellular biological events, such as gene expression of extracellular matrix components (e.g., collagen). This mechanical regulation of ECM gene expression affords maintenance of connective tissue homeostasis. However, mechanical loads can also interfere with homeostatic cellular gene expression and consequently cause the pathogenesis of connective tissue diseases such as tendinopathy and osteoarthritis. Therefore, the regulation of gene expression by mechanical loads is closely related to connective tissue physiology and pathology. This article reviews the effects of various mechanical loading conditions on gene regulation in fibroblasts and discusses several mechanotransduction mechanisms. Future research directions in mechanoregulation of gene expression are also suggested. PMID:17331678

  20. Biological role of microRNA-103 based on expression profile and target genes analysis in pigs.

    PubMed

    Li, Guoxi; Wu, Zongsong; Li, Xinjian; Ning, Xiaomin; Li, Yanjie; Yang, Gongshe

    2011-10-01

    MicroRNAs (miRNAs) are endogenously expressed RNAs consisting of 20-24 nucleotides. These molecules are thought to repress protein translation by binding to target mRNAs. However, biological functions have not been assigned to most of the 175 porcine miRNAs registered in miRBase (release 15.0). In an effort to uncover miR-103 important in pigs, we examined the integrative tissue expression profile and gene ontology (GO) term enrichment of predicted target genes to determine the global biological functions of miR-103. Our results demonstrated that miR-103 is involved in various biological processes including brain development, lipid metabolism, adipocyte differentiation, hematopoiesis, and immunity. Moreover, we also experimentally verified effects of miR-103 in porcine preadipocytes. miR-103 levels increased in differentiating adipocytes, and inhibition of miR-103 effectively inhibited preadipocyte differentiation. In addition, mRNA levels of the putative miR-103 target RAI14 were higher in miR-103 inhibitor-treated adipocytes. These results demonstrate that miR-103 is involved in porcine preadipocyte differentiation and may act through the putative target gene RAI14. In a word, our data provide new insights into the global biological role of miR-103.

  1. Multiplex image-based autophagy RNAi screening identifies SMCR8 as ULK1 kinase activity and gene expression regulator

    PubMed Central

    Jung, Jennifer; Nayak, Arnab; Schaeffer, Véronique; Starzetz, Tatjana; Kirsch, Achim K; Müller, Stefan; Dikic, Ivan; Mittelbronn, Michel; Behrends, Christian

    2017-01-01

    Autophagy is an intracellular recycling and degradation pathway that depends on membrane trafficking. Rab GTPases are central for autophagy but their regulation especially through the activity of Rab GEFs remains largely elusive. We employed a RNAi screen simultaneously monitoring different populations of autophagosomes and identified 34 out of 186 Rab GTPase, GAP and GEF family members as potential autophagy regulators, amongst them SMCR8. SMCR8 uses overlapping binding regions to associate with C9ORF72 or with a C9ORF72-ULK1 kinase complex holo-assembly, which function in maturation and formation of autophagosomes, respectively. While focusing on the role of SMCR8 during autophagy initiation, we found that kinase activity and gene expression of ULK1 are increased upon SMCR8 depletion. The latter phenotype involved association of SMCR8 with the ULK1 gene locus. Global mRNA expression analysis revealed that SMCR8 regulates transcription of several other autophagy genes including WIPI2. Collectively, we established SMCR8 as multifaceted negative autophagy regulator. DOI: http://dx.doi.org/10.7554/eLife.23063.001 PMID:28195531

  2. Differential Gene Expression in Human Cerebrovascular Malformations

    PubMed Central

    Shenkar, Robert; Elliott, J. Paul; Diener, Katrina; Gault, Judith; Hu, Ling-Jia; Cohrs, Randall J.; Phang, Tzulip; Hunter, Lawrence; Breeze, Robert E.; Awad, Issam A.

    2009-01-01

    OBJECTIVE We sought to identify genes with differential expression in cerebral cavernous malformations (CCMs), arteriovenous malformations (AVMs), and control superficial temporal arteries (STAs) and to confirm differential expression of genes previously implicated in the pathobiology of these lesions. METHODS Total ribonucleic acid was isolated from four CCM, four AVM, and three STA surgical specimens and used to quantify lesion-specific messenger ribonucleic acid expression levels on human gene arrays. Data were analyzed with the use of two separate methodologies: gene discovery and confirmation analysis. RESULTS The gene discovery method identified 42 genes that were significantly up-regulated and 36 genes that were significantly down-regulated in CCMs as compared with AVMs and STAs (P = 0.006). Similarly, 48 genes were significantly up-regulated and 59 genes were significantly down-regulated in AVMs as compared with CCMs and STAs (P = 0.006). The confirmation analysis showed significant differential expression (P < 0.05) in 11 of 15 genes (angiogenesis factors, receptors, and structural proteins) that previously had been reported to be expressed differentially in CCMs and AVMs in immunohistochemical analysis. CONCLUSION We identify numerous genes that are differentially expressed in CCMs and AVMs and correlate expression with the immunohistochemistry of genes implicated in cerebrovascular malformations. In future efforts, we will aim to confirm candidate genes specifically related to the pathobiology of cerebrovascular malformations and determine their biological systems and mechanistic relevance. PMID:12535382

  3. Screening of Pleural Mesotheliomas for DNA-damage Repair Players by Digital Gene Expression Analysis Can Enhance Clinical Management of Patients Receiving Platin-Based Chemotherapy

    PubMed Central

    Walter, Robert Fred Henry; Vollbrecht, Claudia; Werner, Robert; Mairinger, Thomas; Schmeller, Jan; Flom, Elena; Wohlschlaeger, Jeremias; Barbetakis, Nikolaos; Paliouras, Dimitrios; Chatzinikolaou, Fotios; Adamidis, Vasilis; Tsakiridis, Kosmas; Zarogoulidis, Paul; Trakada, Georgia; Christoph, Daniel Christian; Schmid, Kurt Werner; Mairinger, Fabian Dominik

    2016-01-01

    Background: Malignant pleural mesothelioma (MPM) is a rare, predominantly asbestos-related and biologically highly aggressive tumour leading to a dismal prognosis. Multimodality therapy consisting of platinum-based chemotherapy is the treatment of choice. The reasons for the rather poor efficacy of platinum compounds remain largely unknown. Material and Methods: For this exploratory mRNA study, 24 FFPE tumour specimens were screened by digital gene expression analysis. Based on data from preliminary experiments and recent literature, a total of 366 mRNAs were investigated using a Custom CodeSet from NanoString. All statistical analyses were calculated with the R i386 statistical programming environment. Results: CDC25A and PARP1 gene expression were correlated with lymph node spread, BRCA1 and TP73 expression levels with higher IMIG stage. NTHL1 and XRCC3 expression was associated with TNM stage. CHECK1 as well as XRCC2 expression levels were correlated with tumour progression in the overall cohort of patients. CDKN2A and MLH1 gene expression influenced overall survival in this collective. In the adjuvant treated cohort only, CDKN2A, CHEK1 as well as ERCC1 were significantly associated with overall survival. Furthermore, TP73 expression was associated with progression in this subgroup. Conclusion: DNA-damage response plays a crucial role in response to platin-based chemotherapeutic regimes. In particular, CHEK1, XRCC2 and TP73 are strongly associated with tumour progression. ERCC1, MLH1, CDKN2A and most promising CHEK1 are prognostic markers for OS in MPM. TP73, CDKN2A, CHEK1 and ERCC1 seem to be also predictive markers in adjuvant treated MPMs. After a prospective validation, these markers may improve clinical and pathological practice, finally leading to a patients' benefit by an enhanced clinical management. PMID:27698933

  4. Microarray-based identification of differentially expressed genes in intracellular Brucella abortus within RAW264.7 cells.

    PubMed

    Tian, Mingxing; Qu, Jing; Han, Xiangan; Zhang, Min; Ding, Chan; Ding, Jiabo; Chen, Guanghua; Yu, Shengqing

    2013-01-01

    Brucella spp. is a species of facultative intracellular Gram-negative bacteria that induces abortion and causes sterility in domesticated mammals and chronic undulant fever in humans. Important determinants of Brucella's virulence and potential for chronic infection include the ability to circumvent the host cell's internal surveillance system and the capability to proliferate within dedicated and non-dedicated phagocytes. Hence, identifying genes necessary for intracellular survival may hold the key to understanding Brucella infection. In the present study, microarray analysis reveals that 7.82% (244/3334) of all Brucella abortus genes were up-regulated and 5.4% (180/3334) were down-regulated in RAW264.7 cells, compared to free-living cells in TSB. qRT-PCR verification further confirmed a >5-fold up-regulation for fourteen genes. Functional analysis classified araC, ddp, and eryD as to partake in information storage and processing, alp, flgF and virB9 to be involved in cellular processes, hpcd and aldh to play a role in metabolism, mfs and nikC to be involved in both cellular processes and metabolism, and four hypothetical genes (bruAb1_1814, bruAb1_0475, bruAb1_1926, and bruAb1_0292) had unknown functions. Furthermore, we constructed a B. abortus 2308 mutant Δddp where the ddp gene is deleted in order to evaluate the role of ddp in intracellular survival. Infection assay indicated significantly higher adherence and invasion abilities of the Δddp mutant, however it does not survive well in RAW264.7 cells. Brucella may survive in hostile intracellular environment by modulating gene expression.

  5. Evaluation of the hormonal state of columnar apple trees (Malus x domestica) based on high throughput gene expression studies.

    PubMed

    Krost, Clemens; Petersen, Romina; Lokan, Stefanie; Brauksiepe, Bastienne; Braun, Peter; Schmidt, Erwin R

    2013-02-01

    The columnar phenotype of apple trees (Malus x domestica) is characterized by a compact growth habit with fruit spurs instead of lateral branches. These properties provide significant economic advantages by enabling high density plantings. The columnar growth results from the presence of a dominant allele of the gene Columnar (Co) located on chromosome 10 which can appear in a heterozygous (Co/co) or homozygous (Co/Co) state. Although two deep sequencing approaches could shed some light on the transcriptome of columnar shoot apical meristems (SAMs), the molecular mechanisms of columnar growth are not yet elaborated. Since the influence of phytohormones is believed to have a pivotal role in the establishment of the phenotype, we performed RNA-Seq experiments to study genes associated with hormone homeostasis and clearly affected by the presence of Co. Our results provide a molecular explanation for earlier findings on the hormonal state of columnar apple trees. Additionally, they allow hypotheses on how the columnar phenotype might develop. Furthermore, we show a statistically approved enrichment of differentially regulated genes on chromosome 10 in the course of validating RNA-Seq results using additional gene expression studies.

  6. Microarray-based genomic profiling reveals novel genomic aberrations in follicular lymphoma which associate with patient survival and gene expression status.

    PubMed

    Schwaenen, Carsten; Viardot, Andreas; Berger, Hilmar; Barth, Thomas F E; Bentink, Stefan; Döhner, Hartmut; Enz, Martina; Feller, Alfred C; Hansmann, Martin-Leo; Hummel, Michael; Kestler, Hans A; Klapper, Wolfram; Kreuz, Markus; Lenze, Dido; Loeffler, Markus; Möller, Peter; Müller-Hermelink, Hans-Konrad; Ott, German; Rosolowski, Maciej; Rosenwald, Andreas; Ruf, Sandra; Siebert, Reiner; Spang, Rainer; Stein, Harald; Truemper, Lorenz; Lichter, Peter; Bentz, Martin; Wessendorf, Swen

    2009-01-01

    Follicular lymphoma (FL) is characterized by a large number of chromosomal aberrations. However, their exact genomic extension and involved target genes remain to be determined. For this purpose, we used array-based intermediate-high resolution genomic profiling in combination with Affymetrix gene expression analysis. Tumor specimens from 128 FL patients were analyzed for the presence of genomic aberrations and the results were correlated to clinical data sets and mRNA expression levels. In 114 (89%) of the 128 analyzed cases, a total of 688 genomic aberrations (384 gains/amplifications and 304 losses) were detected. Frequent genomic aberrations were: -1p36 (18%), +2p15 (24%), -3q (14%), -6q (25%), +7p (19%), +7q (23%), +8q (14%), -9p (16%), -11q (15%), +12q (20%), -13q (11%), -17p (16%), +18p (18%), and +18q (28%). Critical segments of these imbalances were delineated to genomic fragments with a minimum size down to 0.2 Mb. By comparison of these with mRNA gene expression data, putative candidate genes were identified. Moreover, we found that deletions affecting the tumor suppressor gene CDKN2A/B on 9p21 were detected in nontransformed FL grade I-II. For this aberration as well as for -6q25 and -6q26, an association with inferior survival was observed.

  7. Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data

    PubMed Central

    2011-01-01

    Background Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. Description The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps

  8. Looking in the Mouth for Noninvasive Gene Expression-Based Methods to Detect Oral, Oropharyngeal, and Systemic Cancer

    PubMed Central

    Adami, Guy R.; Adami, Alexander J.

    2012-01-01

    Noninvasive diagnosis, whether by sampling body fluids, body scans, or other technique, has the potential to simplify early cancer detection. A classic example is Pap smear screening, which has helped to reduce cervical cancer 75% over the last 50 years. No test is error-free; the real concern is sufficient accuracy combined with ease of use. This paper will discuss methods that measure gene expression or epigenetic markers in oral cells or saliva to diagnose oral and pharyngeal cancers, without requiring surgical biopsy. Evidence for lung and other distal cancer detection is also reviewed. PMID:23050165

  9. Identification of adaptation-specific differences in mRNA expression of sessile and pedunculate oak based on osmotic-stress-induced genes.

    PubMed

    Porth, Ilga; Koch, Margit; Berenyi, Maria; Burg, Agnes; Burg, Kornel

    2005-10-01

    Quercus petraea (Matt.) Liebl. and Q. robur L. hybridize frequently and occupy similar, though distinct, ecological niches. So far, genetic discrimination between these species at the molecular level has been based mainly on neutral markers. Because such markers often exhibit low species differentiation because of high genetic compatibility and exchange between Q. robur and Q. petraea at these loci, we used adaptation-related expressed genes as markers. Accordingly, we identified osmotic-stress-induced genes in a Q. petraea cell line grown under moderate osmotic stress conditions. Two subtraction libraries were established from callus cells cultured under hyperosmotic stress for 1 or 48 h. Thirty-three differentially expressed sequence tags (ESTs) (from 70 originally isolated) were classified according to their putative functions. At least five of these gene products may contribute to osmotic-stress tolerance in oak: betaine aldehyde dehydrogenase, two trans-acting transcription factors (one abscsic acid (ABA)-responsive, the other ABA-independent), a glutathione-S- transferase and a heat-shock cognate protein. Seven genes were selected based on their putative function and their expression monitored in vivo. Leaf tissue from Q. petraea and Q. robur plantlets grown hydroponically under hyperosmotic conditions was harvested after 0, 1, 6, 24 or 72 h and analyzed by real-time polymerase chain reaction (PCR). We found indications of osmotic stress adaptation in Q. petraea based on up-regulation of genes related to protective functions, whereas down-regulation of these genes was evident in Q. robur. Thus, genetic markers related to adaptive traits may be useful for differentiating Q. petraea and Q. robur genotypes.

  10. Long-term replacement of a mutated nonfunctional CNS gene: reversal of hypothalamic diabetes insipidus using an EIAV-based lentiviral vector expressing arginine vasopressin.

    PubMed

    Bienemann, Alison S; Martin-Rendon, Enca; Cosgrave, Anna S; Glover, Colin P J; Wong, Liang-Fong; Kingsman, Susan M; Mitrophanous, Kyriacos A; Mazarakis, Nicholas D; Uney, James B

    2003-05-01

    Due to the complexity of brain function and the difficulty in monitoring alterations in neuronal gene expression, the potential of lentiviral gene therapy vectors to treat disorders of the CNS has been difficult to fully assess. In this study, we have assessed the utility of a third-generation equine infectious anemia virus (EIAV) in the Brattleboro rat model of diabetes insipidus, in which a mutation in the arginine vasopressin (AVP) gene results in the production of nonfunctional mutant AVP precursor protein. Importantly, by using this model it is possible to monitor the success of the gene therapy treatment by noninvasive assays. Injection of an EIAV-CMV-AVP vector into the supraoptic nuclei of the hypothalamus resulted in expression of functional AVP peptide in magnocellular neurons. This was accompanied by a 100% recovery in water homeostasis as assessed by daily water intake, urine production, and urine osmolality lasting for a 1-year measurement period. These data show that a single gene defect leading to a neurological disorder can be corrected with a lentiviral-based strategy. This study highlights the potential of using viral gene therapy for the long-term treatment of disorders of the CNS.

  11. Familial aggregation analysis of gene expressions

    PubMed Central

    Rao, Shao-Qi; Xu, Liang-De; Zhang, Guang-Mei; Li, Xia; Li, Lin; Shen, Gong-Qing; Jiang, Yang; Yang, Yue-Ying; Gong, Bin-Sheng; Jiang, Wei; Zhang, Fan; Xiao, Yun; Wang, Qing K

    2007-01-01

    Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-wide gene expressions, the direct phenotypic measures of genes, as the traits to investigate several extended issues regarding the distributions of familially aggregated genes on chromosomes or in functions. In this study we conducted a genome-wide familial aggregation analysis by using the in vitro cell gene expressions of 3300 human autosome genes (Problem 1 data provided to Genetic Analysis Workshop 15) in order to answer three basic genetics questions. First, we investigated how gene expressions aggregate among different types (degrees) of relative pairs. Second, we conducted a bioinformatics analysis of highly familially aggregated genes to see how they are distributed on chromosomes. Third, we performed a gene ontology enrichment test of familially aggregated genes to find evidence to support their functional consensus. The results indicated that 1) gene expressions did aggregate in families, especially between sibs. Of 3300 human genes analyzed, there were a total of 1105 genes with one or more significant (empirical p < 0.05) familial correlation; 2) there were several genomic hot spots where highly familially aggregated genes (e.g., the chromosome 6 HLA genes cluster) were clustered; 3) as we expected, gene ontology enrichment tests revealed that the 1105 genes were aggregating not only in families but also in functional categories. PMID:18466548

  12. Methods for monitoring multiple gene expression

    SciTech Connect

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    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.

  13. Methods for monitoring multiple gene expression

    SciTech Connect

    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.

  14. Methods for monitoring multiple gene expression

    DOEpatents

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2008-06-01

    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.

  15. Selection and validation of potato candidate genes for maturity corrected resistance to Phytophthora infestans based on differential expression combined with SNP association and linkage mapping

    PubMed Central

    Muktar, Meki S.; Lübeck, Jens; Strahwald, Josef; Gebhardt, Christiane

    2015-01-01

    Late blight of potato (Solanum tuberosum L.) caused by the oomycete Phytophthora infestans (Mont.) de Bary, is one of the most important bottlenecks of potato production worldwide. Cultivars with high levels of durable, race unspecific, quantitative resistance are part of a solution to this problem. However, breeding for quantitative resistance is hampered by the correlation between resistance and late plant maturity, which is an undesirable agricultural attribute. The objectives of our research are (i) the identification of genes that condition quantitative resistance to P. infestans not compromised by late plant maturity and (ii) the discovery of diagnostic single nucleotide polymorphism (SNP) markers to be used as molecular tools to increase efficiency and precision of resistance breeding. Twenty two novel candidate genes were selected based on comparative transcript profiling by SuperSAGE (serial analysis of gene expression) in groups of plants with contrasting levels of maturity corrected resistance (MCR). Reproducibility of differential expression was tested by quantitative real time PCR and allele specific pyrosequencing in four new sets of genotype pools with contrasting late blight resistance levels, at three infection time points and in three independent infection experiments. Reproducibility of expression patterns ranged from 28 to 97%. Association mapping in a panel of 184 tetraploid cultivars identified SNPs in five candidate genes that were associated with MCR. These SNPs can be used in marker-assisted resistance breeding. Linkage mapping in two half-sib families (n = 111) identified SNPs in three candidate genes that were linked with MCR. The differentially expressed genes that showed association and/or linkage with MCR putatively function in phytosterol synthesis, fatty acid synthesis, asparagine synthesis, chlorophyll synthesis, cell wall modification, and in the response to pathogen elicitors. PMID:26442110

  16. The Malus domestica sugar transporter gene family: identifications based on genome and expression profiling related to the accumulation of fruit sugars

    PubMed Central

    Wei, Xiaoyu; Liu, Fengli; Chen, Cheng; Ma, Fengwang; Li, Mingjun

    2014-01-01

    In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of “Gala” apple. Genes for sugar alcohol [including 17 sorbitol transporters (SOTs)], sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs). Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties. PMID:25414708

  17. Gene Expression in Single Cells Isolated from the CWR-R1 Prostate Cancer Cell Line and Human Prostate Tissue Based on the Side Population Phenotype

    PubMed Central

    Gangavarapu, Kalyan J; Miller, Austin; Huss, Wendy J

    2016-01-01

    Defining biological signals at the single cell level can identify cancer initiating driver mutations. Techniques to isolate single cells such as microfluidics sorting and magnetic capturing systems have limitations such as: high cost, labor intense, and the requirement of a large number of cells. Therefore, the goal of our current study is to identify a cost and labor effective, reliable, and reproducible technique that allows single cell isolation for analysis to promote regular laboratory use, including standard reverse transcription PCR (RT-PCR). In the current study, we utilized single prostate cells isolated from the CWR-R1 prostate cancer cell line and human prostate clinical specimens, based on the ATP binding cassette (ABC) transporter efflux of dye cycle violet (DCV), side population assay. Expression of four genes: ABCG2; Aldehyde dehydrogenase1A1 (ALDH1A1); androgen receptor (AR); and embryonic stem cell marker, Oct-4, were determined. Results from the current study in the CWR-R1 cell line showed ABCG2 and ALDH1A1 gene expression in 67% of single side population cells and in 17% or 100% of non-side population cells respectively. Studies using single cells isolated from clinical specimens showed that the Oct-4 gene is detected in only 22% of single side population cells and in 78% of single non-side population cells. Whereas, AR gene expression is in 100% single side population and non-side population cells isolated from the same human prostate clinical specimen. These studies show that performing RT-PCR on single cells isolated by FACS can be successfully conducted to determine gene expression in single cells from cell lines and enzymatically digested tissue. While these studies provide a simple yes/no expression readout, the more sensitive quantitative RT-PCR would be able to provide even more information if necessary. PMID:27785389

  18. Graphene based gene transfection

    NASA Astrophysics Data System (ADS)

    Feng, Liangzhu; Zhang, Shuai; Liu, Zhuang

    2011-03-01

    Graphene as a star in materials research has been attracting tremendous attentions in the past few years in various fields including biomedicine. In this work, for the first time we successfully use graphene as a non-toxic nano-vehicle for efficient gene transfection. Graphene oxide (GO) is bound with cationic polymers, polyethyleneimine (PEI) with two different molecular weights at 1.2 kDa and 10 kDa, forming GO-PEI-1.2k and GO-PEG-10k complexes, respectively, both of which are stable in physiological solutions. Cellular toxicity tests reveal that our GO-PEI-10k complex exhibits significantly reduced toxicity to the treated cells compared to the bare PEI-10k polymer. The positively charged GO-PEI complexes are able to further bind with plasmid DNA (pDNA) for intracellular transfection of the enhanced green fluorescence protein (EGFP) gene in HeLa cells. While EGFP transfection with PEI-1.2k appears to be ineffective, high EGFP expression is observed using the corresponding GO-PEI-1.2k as the transfection agent. On the other hand, GO-PEI-10k shows similar EGFP transfection efficiency but lower toxicity compared with PEI-10k. Our results suggest graphene to be a novel gene delivery nano-vector with low cytotoxicity and high transfection efficiency, promising for future applications in non-viral based gene therapy.Graphene as a star in materials research has been attracting tremendous attentions in the past few years in various fields including biomedicine. In this work, for the first time we successfully use graphene as a non-toxic nano-vehicle for efficient gene transfection. Graphene oxide (GO) is bound with cationic polymers, polyethyleneimine (PEI) with two different molecular weights at 1.2 kDa and 10 kDa, forming GO-PEI-1.2k and GO-PEG-10k complexes, respectively, both of which are stable in physiological solutions. Cellular toxicity tests reveal that our GO-PEI-10k complex exhibits significantly reduced toxicity to the treated cells compared to the bare PEI

  19. Association of tissue lineage and gene expression: conservatively and differentially expressed genes define common and special functions of tissues

    PubMed Central

    2010-01-01

    Background Embryogenesis is the process by which the embryo is formed, develops, and establishes developmental hierarchies of tissues. The recent advance in microarray technology made it possible to investigate the tissue specific patterns of gene expression and their relationship with tissue lineages. This study is focused on how tissue specific functions, tissue lineage, and cell differentiation are correlated, which is essential to understand embryonic development and organism complexity. Results We performed individual gene and gene set based analysis on multiple tissue expression data, in association with the classic topology of mammalian fate maps of embryogenesis. For each sub-group of tissues on the fate map, conservatively, differentially and correlatively expressed genes or gene sets were identified. Tissue distance was found to correlate with gene expression divergence. Tissues of the ectoderm or mesoderm origins from the same segments on the fate map shared more similar expression pattern than those from different origins. Conservatively expressed genes or gene sets define common functions in a tissue group and are related to tissue specific diseases, which is supported by results from Gene Ontology and KEGG pathway analysis. Gene expression divergence is larger in certain human tissues than in the mouse homologous tissues. Conclusion The results from tissue lineage and gene expression analysis indicate that common function features of neighbor tissue groups were defined by the conservatively expressed genes and were related to tissue specific diseases, and differentially expressed genes contribute to the functional divergence of tissues. The difference of gene expression divergence in human and mouse homologous tissues reflected the organism complexity, i.e. distinct neural development levels and different body sizes. PMID:21172044

  20. Clustering cancer gene expression data by projective clustering ensemble

    PubMed Central

    Yu, Xianxue; Yu, Guoxian

    2017-01-01

    Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

  1. Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain.

    PubMed

    Gavai, Anand K; Supandi, Farahaniza; Hettling, Hannes; Murrell, Paul; Leunissen, Jack A M; van Beek, Johannes H G M

    2015-01-01

    Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer

  2. Analysis of bHLH coding genes using gene co-expression network approach.

    PubMed

    Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

    2016-07-01

    Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

  3. Microarray-based gene expression profiling reveals genes and pathways involved in the oncogenic function of REG3A on pancreatic cancer cells.

    PubMed

    Xu, Qianqian; Fu, Rong; Yin, Guoxiao; Liu, Xiulan; Liu, Yang; Xiang, Ming

    2016-03-10

    We previously reported that regenerating islet-derived protein 3 alpha (REG3A) exacerbates pancreatic malignancies. The mechanism of this effect has not been clearly elucidated. Here we first identified key differentially expressed genes (DEGs) and signal pathways in the pancreatic cancer cell line SW1990, compared to two control cell lines, by microarray analysis. We then identified key genes and pathways regulated by REG3A or the cytokine IL6 in SW1990 cells. Afterwards, these DEGs induced by REG3A or IL6 were subjected to KEGG pathway enrichment analysis and GO function analysis by the DAVID online tool. Ultimately, we constructed protein-protein interaction networks among the DEGs by Cytoscape. Among the three pancreatic cell lines, SW1990 exhibited highly deterioration with the activation of genes and pathways related to proliferation, survival, angiogenesis, and invasion. As a result, 50 DEGs enriched in 11 pathways were identified in REG3A-treated SW1990 cells, and 28 DEGs enriched in 9 pathways were detected in IL6-treated cells. Overall, results of microarray analysis followed by qRT-PCR and Western blotting suggest that REG3A regulates pancreatic cell growth by increasing the expression of at least 8 genes: JAK1, STAT3, IL10, FOXM1, KRAS, MYC, CyclinD1, and c-fos; and activation of at least 4 signal pathways: TGFβ, PDGF, angiogenesis and RAS. Similar results were obtained with IL6 treatment. Regulation network analysis confirmed the cell growth related DEGs, and further uncovered three transcription factor families with immune functions regulated by REG3A.

  4. Meta-analysis of gene expression data identifies causal genes for prostate cancer.

    PubMed

    Wang, Xiang-Yang; Hao, Jian-Wei; Zhou, Rui-Jin; Zhang, Xiang-Sheng; Yan, Tian-Zhong; Ding, De-Gang; Shan, Lei

    2013-01-01

    Prostate cancer is a leading cause of death in male populations across the globe. With the advent of gene expression arrays, many microarray studies have been conducted in prostate cancer, but the results have varied across different studies. To better understand the genetic and biologic mechanisms of prostate cancer, we conducted a meta-analysis of two studies on prostate cancer. Eight key genes were identified to be differentially expressed with progression. After gene co-expression analysis based on data from the GEO database, we obtained a co- expressed gene list which included 725 genes. Gene Ontology analysis revealed that these genes are involved in actin filament-based processes, locomotion and cell morphogenesis. Further analysis of the gene list should provide important clues for developing new prognostic markers and therapeutic targets.

  5. Nonreplicating vaccinia vector efficiently expresses recombinant genes.

    PubMed

    Sutter, G; Moss, B

    1992-11-15

    Modified vaccinia Ankara (MVA), a highly attenuated vaccinia virus strain that has been safety tested in humans, was evaluated for use as an expression vector. MVA has multiple genomic deletions and is severely host cell restricted: it grows well in avian cells but is unable to multiply in human and most other mammalian cells tested. Nevertheless, we found that replication of viral DNA appeared normal and that both early and late viral proteins were synthesized in human cells. Proteolytic processing of viral structural proteins was inhibited, however, and only immature virus particles were detected by electron microscopy. We constructed an insertion plasmid with the Escherichia coli lacZ gene under the control of the vaccinia virus late promoter P11, flanked by sequences of MVA DNA, to allow homologous recombination at the site of a naturally occurring 3500-base-pair deletion within the MVA genome. MVA recombinants were isolated and propagated in permissive avian cells and shown to express the enzyme beta-galactosidase upon infection of nonpermissive human cells. The amount of enzyme made was similar to that produced by a recombinant of vaccinia virus strain Western Reserve, which also had the lacZ gene under control of the P11 promoter, but multiplied to high titers. Since recombinant gene expression is unimpaired in nonpermissive human cells, MVA may serve as a highly efficient and exceptionally safe vector.

  6. DNA sequence of 15 base pairs is sufficient to mediate both glucocorticoid and progesterone induction of gene expression

    SciTech Connect

    Straehle, U.; Klock, G.; Schuetz, G.

    1987-11-01

    To define the recognition sequence of the glucocorticoid receptor and its relationship with that of the progesterone receptor, oligonucleotides derived from the glucocorticoid response element of the tyrosine aminotransferase gene were tested upstream of a heterologous promoter for their capacity to mediate effects of these two steroids. The authors show that a 15-base-pair sequence with partial symmetry is sufficient to confer glucocorticoid inducibility on the promoter of the herpes simplex virus thymidine kinase gene. The same 15-base-pair sequence mediates induction by progesterone. Point mutations in the recognition sequence affect inducibility by glucocorticoids and progesterone similarly. Together with the strong conservation of the sequence of the DNA-binding domain of the two receptors, these data suggest that both proteins recognize a sequence that is similar, if not the same.

  7. Estimation and Testing of Gene Expression Heterosis

    PubMed Central

    Liu, Peng; Nettleton, Dan

    2014-01-01

    Heterosis, also known as the hybrid vigor, occurs when the mean phenotype of hybrid off-spring is superior to that of its two inbred parents. The heterosis phenomenon is extensively utilized in agriculture though the molecular basis is still unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers have begun to compare expression levels of thousands of genes between parental inbred lines and their hybrid offspring to search for evidence of gene expression heterosis. Standard statistical approaches for separately analyzing expression data for each gene can produce biased and highly variable estimates and unreliable tests of heterosis. To address these shortcomings, we develop a hierarchical model to borrow information across genes. Using our modeling framework, we derive empirical Bayes estimators and an inference strategy to identify gene expression heterosis. Simulation results show that our proposed method outperforms the more traditional strategy used to detect gene expression heterosis. This article has supplementary material online. PMID:25435758

  8. Estimation and Testing of Gene Expression Heterosis.

    PubMed

    Ji, Tieming; Liu, Peng; Nettleton, Dan

    2014-09-01

    Heterosis, also known as the hybrid vigor, occurs when the mean phenotype of hybrid off-spring is superior to that of its two inbred parents. The heterosis phenomenon is extensively utilized in agriculture though the molecular basis is still unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers have begun to compare expression levels of thousands of genes between parental inbred lines and their hybrid offspring to search for evidence of gene expression heterosis. Standard statistical approaches for separately analyzing expression data for each gene can produce biased and highly variable estimates and unreliable tests of heterosis. To address these shortcomings, we develop a hierarchical model to borrow information across genes. Using our modeling framework, we derive empirical Bayes estimators and an inference strategy to identify gene expression heterosis. Simulation results show that our proposed method outperforms the more traditional strategy used to detect gene expression heterosis. This article has supplementary material online.

  9. Predicting early brain metastases based on clinicopathological factors and gene expression analysis in advanced HER2-positive breast cancer patients.

    PubMed

    Duchnowska, Renata; Jassem, Jacek; Goswami, Chirayu Pankaj; Dundar, Murat; Gökmen-Polar, Yesim; Li, Lang; Woditschka, Stephan; Biernat, Wojciech; Sosińska-Mielcarek, Katarzyna; Czartoryska-Arłukowicz, Bogumiła; Radecka, Barbara; Tomasevic, Zorica; Stępniak, Piotr; Wojdan, Konrad; Sledge, George W; Steeg, Patricia S; Badve, Sunil

    2015-03-01

    The overexpression or amplification of the human epidermal growth factor receptor 2 gene (HER2/neu) is associated with high risk of brain metastasis (BM). The identification of patients at highest immediate risk of BM could optimize screening and facilitate interventional trials. We performed gene expression analysis using complementary deoxyribonucleic acid-mediated annealing, selection, extension and ligation and real-time quantitative reverse transcription PCR (qRT-PCR) in primary tumor samples from two independent cohorts of advanced HER2 positive breast cancer patients. Additionally, we analyzed predictive relevance of clinicopathological factors in this series. Study group included discovery Cohort A (84 patients) and validation Cohort B (75 patients). The only independent variables associated with the development of early BM in both cohorts were the visceral location of first distant relapse [Cohort A: hazard ratio (HR) 7.4, 95 % CI 2.4-22.3; p < 0.001; Cohort B: HR 6.1, 95 % CI 1.5-25.6; p = 0.01] and the lack of trastuzumab administration in the metastatic setting (Cohort A: HR 5.0, 95 % CI 1.4-10.0; p = 0.009; Cohort B: HR 10.0, 95 % CI 2.0-100.0; p = 0.008). A profile including 13 genes was associated with early (≤36 months) symptomatic BM in the discovery cohort. This was refined by qRT-PCR to a 3-gene classifier (RAD51, HDGF, TPR) highly predictive of early BM (HR 5.3, 95 % CI 1.6-16.7; p = 0.005; multivariate analysis). However, predictive value of the classifier was not confirmed in the independent validation Cohort B. The presence of visceral metastases and the lack of trastuzumab administration in the metastatic setting apparently increase the likelihood of early BM in advanced HER2-positive breast cancer.

  10. A biomarker-based screen of a gene expression compendium reveals regulation of Nrf2 by CAR and STAT5b

    EPA Science Inventory

    Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse l...

  11. Module Anchored Network Inference: A Sequential Module-Based Approach to Novel Gene Network Construction from Genomic Expression Data on Human Disease Mechanism

    PubMed Central

    Keller, Susanna R.; Lee, Jae K.

    2017-01-01

    Different computational approaches have been examined and compared for inferring network relationships from time-series genomic data on human disease mechanisms under the recent Dialogue on Reverse Engineering Assessment and Methods (DREAM) challenge. Many of these approaches infer all possible relationships among all candidate genes, often resulting in extremely crowded candidate network relationships with many more False Positives than True Positives. To overcome this limitation, we introduce a novel approach, Module Anchored Network Inference (MANI), that constructs networks by analyzing sequentially small adjacent building blocks (modules). Using MANI, we inferred a 7-gene adipogenesis network based on time-series gene expression data during adipocyte differentiation. MANI was also applied to infer two 10-gene networks based on time-course perturbation datasets from DREAM3 and DREAM4 challenges. MANI well inferred and distinguished serial, parallel, and time-dependent gene interactions and network cascades in these applications showing a superior performance to other in silico network inference techniques for discovering and reconstructing gene network relationships. PMID:28197408

  12. Optimization of transient gene expression system in Gerbera jemosonii petals.

    PubMed

    Hussein, Gihan M; Abu El-Heba, Ghada A; Abdou, Sara M; Abdallah, Naglaa A

    2013-01-01

    Low transformation efficiency and long generation time for production of transgenic Gerbera jemosonii plants leads to vulnerable gene function studies. Thus, transient expression of genes would be an efficient alternative. In this investigation, a transient expression system for gerbera petals based on the Agrobacterium infiltration protocol was developed using the reporter genes β-glucuronidase (gus) and green florescence protein (gfp). Results revealed the incapability of using the gfp gene as a reporter gene for transient expression study in gerbera flowers due to the detection of green fluorescent color in the non-infiltrated gerbera flower petals. However, the gus reporter gene was successfully utilized for optimizing and obtaining the suitable agroinfiltration system in gerbera flowers. The expression of GUS was detectable after three days of agroinfiltration in gerbera cultivars "Express" and "White Grizzly" with dark pink and white flower colors, respectively. The vacuum agroinfiltration protocol has been applied on the cultivar "Express" for evaluating the transient expression of the two genes involved in the anthocyanin pathway (iris-dfr and petunia-f3' 5'h), which is responsible for the color in flowers. In comparison to the control, transient expression results showed change in the anthocyanin pigment in all infiltrated flowers with color genes. Additionally, blue color was detected in the stigma and pollen grains in the infiltrated flowers. Moreover, blue colors with variant intensities were observed in produced calli during the routine work of stable transformation with f3' 5'h gene.

  13. Gene expression profile analyses of mice livers injured by Leigongteng

    PubMed Central

    Chen, Yong; Zhang, Xiao-Ming; Han, Feng-Mei; Du, Peng; Xia, Qi-Song

    2007-01-01

    AIM: To analyze the gene expression profiles of mice livers injured by Leigongteng and explore the relationship between the differentially expressed genes and liver damage. METHODS: The experimental mice were randomly divided into a control group and a liver-injured group in which the mice were administrated 33 μγ of triptolide/kg per day for 30 d. Liver mRNAs were extracted from animals in both groups and were reverse-transcribed to cDNA with dUTP labeled by different fluorescence (Cy3, Cy5) as hybridization probes. The mixed probes were hybridized with oligonucleotide microarray chips. The fluorescent signal results were acquired by scanner and analyzed with software. RESULTS: Among the 35852 target genes, 29 genes were found to be significantly differentially expressed, with 20 genes up-regulated and 9 genes down-regulated. The reliability of the differentially expressed genes was validated by RT-PCR experiments of 5 randomly selected differentially expressed genes. CONCLUSION: Based on the biological functions of the differentially expressed genes, it is obvious that the occurrence and development of liver damage induced by Leigongteng in mice are highly associated with immune response, metabolism, apoptosis and the cell skeleton of liver cells. This might be important for elucidating the regulatory network of gene expression associated with liver damage and it may also be important for discovering the pathogenic mechanisms of liver damage induced by Leigongteng. PMID:17659714

  14. Digital Gene Expression Tag Profiling Analysis of the Gene Expression Patterns Regulating the Early Stage of Mouse Spermatogenesis

    PubMed Central

    Meng, Lijun; Liu, Meiling; Zhao, Lina; Hu, Fen; Ding, Cunbao; Wang, Yang; He, Baoling; Pan, Yuxin; Fang, Wei; Chen, Jing; Hu, Songnian; Jia, Mengchun

    2013-01-01

    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. PMID:23554914

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

    PubMed Central

    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. PMID:26919744

  16. Gene expression and cAMP.

    PubMed Central

    Nagamine, Y; Reich, E

    1985-01-01

    By comparing the 5'-flanking region of the porcine gene for the urokinase form of plasminogen activator with those of other cAMP-regulated genes, we identify a 29-nucleotide sequence that is tentatively proposed as the cAMP-regulatory unit. Homologous sequences are present (i) in the cAMP-regulated rat tyrosine aminotransferase, prolactin, and phosphoenolpyruvate carboxykinase genes and (ii) 5' to the transcription initiation sites of cAMP-regulated Escherichia coli genes. From this we conclude that the expression of cAMP-responsive genes in higher eukaryotes may be controlled, as in E. coli, by proteins that form complexes with cAMP and then show sequence-specific DNA-binding properties. The complex formed by cAMP and the regulatory subunit of the type II mammalian protein kinase might be one candidate for this function. Based on several homologies we suggest that this subunit may have retained both the DNA-binding specificity and transcription-regulating properties in addition to the nucleotide-binding domains of the bacterial cAMP-binding protein. If this were so, dissociation of protein kinase by cAMP would activate two processes: (i) protein phosphorylation by the catalytic subunit and (ii) transcription regulation by the regulatory subunit. PMID:2991882

  17. Arabidopsis gene expression patterns during spaceflight

    NASA Astrophysics Data System (ADS)

    Paul, A.-L.; Ferl, R. J.

    The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments resulted in the differential expression of hundreds of genes. A 5 day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β -Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on two fronts. First, expression patterns visualized with the Adh/GUS transgene were used to address specifically the possibility that spaceflight induces a hypoxic stress response, and to assess whether any spaceflight response was similar to control terrestrial hypoxia-induced gene expression patterns. (Paul et al., Plant Physiol. 2001, 126:613). Second, genome-wide patterns of native gene expression were evaluated utilizing the Affymetrix ATH1 GeneChip? array of 8,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes identified with the arrays was further characterized with quantitative Real-Time RT PCR (ABI - TaqmanTM). Comparison of the patterns of expression for arrays of hybridized with RNA isolated from plants exposed to spaceflight compared to the control arrays revealed hundreds of genes that were differentially expressed in response to spaceflight, yet most genes that are hallmarks of hypoxic stress were unaffected. These results will be discussed in light of current models for plant responses to the spaceflight environment, and with regard to potential future flight opportunities.

  18. Hepatic IFNL4 expression is associated with non-response to interferon-based therapy through the regulation of basal interferon-stimulated gene expression in chronic hepatitis C patients.

    PubMed

    Murakawa, Miyako; Asahina, Yasuhiro; Kawai-Kitahata, Fukiko; Nakagawa, Mina; Nitta, Sayuri; Otani, Satoshi; Nagata, Hiroko; Kaneko, Shun; Asano, Yu; Tsunoda, Tomoyuki; Miyoshi, Masato; Itsui, Yasuhiro; Azuma, Seishin; Kakinuma, Sei; Tanaka, Yasuhito; Iijima, Sayuki; Tsuchiya, Kaoru; Izumi, Namiki; Tohda, Shuji; Watanabe, Mamoru

    2016-12-30

    Single nucleotide polymorphisms (SNPs) within or near interferon lambda 4 (IFNL4) gene located upstream of IFNL3 are associated with response to anti-HCV therapy both in interferon (IFN)-based and IFN-free regimens. IFNL4 encodes IFNλ4, a newly discovered type III IFN, and its expression is controlled by rs368234815-TT/ΔG, which is in strong linkage disequilibrium (LD) with other tag SNPs within or near IFNL4 such as rs12979860 and rs8099917. Intrahepatic expression levels of IFN-stimulated genes (ISGs) affect the responsiveness to IFNα and are also associated with IFNL4 genotype. However, IFNL4 expressions and its role in intrinsic antiviral innate immunity remain unclear. This study evaluated the effect of IFNL4 on intrahepatic ISG expression and investigated its relationship with treatment outcomes in liver samples obtained from 49 chronic hepatitis C patients treated with pegylated (PEG)-IFN/ribavirin therapy. IFNL4 mRNA was detected in 11 of 22 patients with IFNL4-unfavorable SNPs but not in patients with favorable genotypes. IFNL4 expression was associated with non-response to PEG-IFN/ribavirin therapy. Intrahepatic expression of antiviral ISGs (ISG15 and MX1) was significantly higher in IFNL4-unfavorable patients with detectable IFNL4 mRNA than in patients with undetectable IFNL4 mRNA, whereas the expression of suppressive ISGs (RNF125, SOCS1, SOCS3, and RNF11) was lower in patients with detectable IFNL4 mRNA. In summary, intrahepatic expression of IFNL4 was associated with increased antiviral ISG expression and decreased suppressive ISG expression at baseline, resulting in poor responsiveness to IFNα-based therapy in HCV infection.

  19. Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies.

    PubMed

    Kosinová, Lucie; Cahová, Monika; Fábryová, Eva; Týcová, Irena; Koblas, Tomáš; Leontovyč, Ivan; Saudek, František; Kříž, Jan

    2016-01-01

    The use of RT-qPCR provides a powerful tool for gene expression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of gene expression. Despite of this, freshly isolated islets frequently serve as a control in various gene expression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3) in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for gene expression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for gene expression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information from 48 hrs onwards.

  20. Partial least squares regression, support vector machine regression, and transcriptome-based distances for prediction of maize hybrid performance with gene expression data.

    PubMed

    Fu, Junjie; Falke, K Christin; Thiemann, Alexander; Schrag, Tobias A; Melchinger, Albrecht E; Scholten, Stefan; Frisch, Matthias

    2012-03-01

    The performance of hybrids can be predicted with gene expression data from their parental inbred lines. Implementing such prediction approaches in breeding programs promises to increase the efficiency of hybrid breeding. The objectives of our study were to compare the accuracy of prediction models employing multiple linear regression (MLR), partial least squares regression (PLS), support vector machine regression (SVM), and transcriptome-based distances (D(B)). For a factorial of 7 flint and 14 dent maize lines, the grain yield of the hybrids was assessed and the gene expression of the parental lines was profiled with a 56k microarray. The accuracy of the prediction models was measured by the correlation between predicted and observed yield employing two cross-validation schemes. The first modeled the prediction of hybrids when testcross data are available for both parental lines (type 2 hybrids), and the second modeled the prediction of hybrids when no testcross data for the parental lines were available (type 0 hybrids). MLR, SVM, and PLS resulted in a high correlation between predicted and observed yield for type 2 hybrids, whereas for type 0 hybrids D(B) had greater prediction accuracy. The regression methods were robust to the choice of the set of profiled genes and required only a few hundred genes. In contrast, for an accurate hybrid prediction with D(B), 1,000-1,500 genes were required, and the prediction accuracy depended strongly on the set of profiled genes. We conclude that for prediction within one set of genetic material MLR is a promising approach, and for transferring prediction models from one set of genetic material to a related one, the transcriptome-based distance D(B) is most promising.

  1. A predictive approach to identify genes differentially expressed

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using 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 indicate 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 publicly available data set on Escherichia coli bacteria.

  2. Second-Generation Recombination-Based In Vivo Expression Technology for Large-Scale Screening for Vibrio cholerae Genes Induced during Infection of the Mouse Small Intestine

    PubMed Central

    Osorio, C. G.; Crawford, J. A.; Michalski, J.; Martinez-Wilson, H.; Kaper, J. B.; Camilli, A.

    2005-01-01

    We have constructed an improved recombination-based in vivo expression technology (RIVET) and used it as a screening method to identify Vibrio cholerae genes that are transcriptionally induced during infection of infant mice. The improvements include the introduction of modified substrate cassettes for resolvase that can be positively and negatively selected for, allowing selection of resolved strains from intestinal homogenates, and three different tnpR alleles that cover a range of translation initiation efficiencies, allowing identification of infection-induced genes that have low-to-moderate basal levels of transcription during growth in vitro. A transcriptional fusion library of 8,734 isolates of a V. cholerae El Tor strain that remain unresolved when the vibrios are grown in vitro was passed through infant mice, and 40 infection-induced genes were identified. Nine of these genes were inactivated by in-frame deletions, and their roles in growth in vitro and fitness during infection were measured by competition assays. Four mutant strains were attenuated >10-fold in vivo compared with the parental strain, demonstrating that infection-induced genes are enriched in genes essential for virulence. PMID:15664940

  3. Stratified gene expression analysis identifies major amyotrophic lateral sclerosis genes.

    PubMed

    Jones, Ashley R; Troakes, Claire; King, Andrew; Sahni, Vibhu; De Jong, Simone; Bossers, Koen; Papouli, Efterpi; Mirza, Muddassar; Al-Sarraj, Safa; Shaw, Christopher E; Shaw, Pamela J; Kirby, Janine; Veldink, Jan H; Macklis, Jeffrey D; Powell, John F; Al-Chalabi, Ammar

    2015-05-01

    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of motor neurons resulting in progressive paralysis. Gene expression studies of ALS only rarely identify the same gene pathways as gene association studies. We hypothesized that analyzing tissues by matching on degree of disease severity would identify different patterns of gene expression from a traditional case-control comparison. We analyzed gene expression changes in 4 postmortem central nervous system regions, stratified by severity of motor neuron loss. An overall comparison of cases (n = 6) and controls (n = 3) identified known ALS gene, SOX5, as showing differential expression (log2 fold change = 0.09, p = 5.5 × 10(-5)). Analyses stratified by disease severity identified expression changes in C9orf72 (p = 2.77 × 10(-3)), MATR3 (p = 3.46 × 10(-3)), and VEGFA (p = 8.21 × 10(-4)), all implicated in ALS through genetic studies, and changes in other genes in pathways involving RNA processing and immune response. These findings suggest that analysis of gene expression stratified by disease severity can identify major ALS genes and may be more efficient than traditional case-control comparison.

  4. Gravity-Induced Gene Expression in Plants.

    NASA Astrophysics Data System (ADS)

    Sederoff, Heike; Heber, Steffen; Howard, Brian; Myburg-Nichols, Henrietta; Hammond, Rebecca; Salinas-Mondragon, Raul; Brown, Christopher S.

    Plants sense changes in their orientation towards the vector of gravity and respond with directional growth. Several metabolites in the signal transduction cascade have been identified. However, very little is known about the interaction between these sensing and signal transduction events and even less is known about their role in the differential growth response. Gravity induced changes in transcript abundance have been identified in Arabidopsis whole seedlings and root apices (Moseyko et al. 2002; Kimbrough et al. 2004). Gravity induced transcript abundance changes can be observed within less than 1 min after stimulation (Salinas-Mondragon et al. 2005). Gene expression however requires not only transcription but also translation of the mRNA. Translation can only occur when mRNA is associated with ribosomes, even though not all mRNA associated with ribosomes is actively translated. To approximate translational capacity we quantified whole genome transcript abundances in corn stem pulvini during the first hour after gravity stimulation in total and poly-ribosomal fractions. As in Arabidopsis root apices, transcript abundances of several clusters of genes responded to gravity stimulation. The vast majority of these transcripts were also found to associate with polyribosomes in the same temporal and quantitative pattern. These genes are transcriptionally regulated by gravity stimulation, but do not exhibit translational regulation. However, a small group of genes showed increased transcriptional regulation after gravity stimulation, but no association with polysomes. These transcripts likely are translationally repressed. The mechanism of translational repression for these transcripts is unknown. Based on the hypothesis that the genes essential for gravitropic responses should be expressed in most or all species, we compared the temporal gravity induced expression pattern of all orthologs identified between maize and Arabidopsis. A small group of genes showed high

  5. Transcription activator-like effector-mediated regulation of gene expression based on the inducible packaging and delivery via designed extracellular vesicles.

    PubMed

    Lainšček, Duško; Lebar, Tina; Jerala, Roman

    2017-02-26

    Transcription activator-like effector (TALE) proteins present a powerful tool for genome editing and engineering, enabling introduction of site-specific mutations, gene knockouts or regulation of the transcription levels of selected genes. TALE nucleases or TALE-based transcription regulators are introduced into mammalian cells mainly via delivery of the coding genes. Here we report an extracellular vesicle-mediated delivery of TALE transcription regulators and their ability to upregulate the reporter gene in target cells. Designed transcriptional activator TALE-VP16 fused to the appropriate dimerization domain was enriched as a cargo protein within extracellular vesicles produced by mammalian HEK293 cells stimulated by Ca-ionophore and using blue light- or rapamycin-inducible dimerization systems. Blue light illumination or rapamycin increased the amount of the TALE-VP16 activator in extracellular vesicles and their addition to the target cells resulted in an increased expression of the reporter gene upon addition of extracellular vesicles to the target cells. This technology therefore represents an efficient delivery for the TALE-based transcriptional regulators.

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

    PubMed Central

    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

  7. The simian virus 40 minimal origin and the 72-base-pair repeat are required simultaneously for efficient induction of late gene expression with large tumor antigen.

    PubMed

    Hartzell, S W; Byrne, B J; Subramanian, K N

    1984-10-01

    We have studied the temporal regulation of simian virus 40 (SV40) late gene expression by construction and transient expression analysis of plasmids containing the transposon Tn9 chloramphenicol acetyltransferase gene placed downstream from the late control region. The SV40 origin region in the early (but not the late) orientation promotes chloramphenicol acetyltransferase gene expression efficiently in monkey cells lacking large tumor (T) antigen. In monkey cells producing T antigen, the promoter activity of the late control region is induced by approximately 1,000-fold above the basal level. By deletion and point mutagenesis, we define two domains of the late control region required for efficient induction with T antigen. Domain I is the minimal replication origin containing T-antigen binding site II. Domain II consists of the 72-base-pair (bp) repeat and a 19-bp downstream sequence up to nucleotide 270. Domains I and II should act synergistically because the absence of either one or the other decreases induction efficiency by 2 orders of magnitude. Though a complete copy of domain II is optimal, the origin-proximal 22-bp portion of this domain is sufficient. The 21-bp repeat, located between domains I and II, is dispensable for this induction, as are sequences located downstream from nucleotide 270 in the late orientation.

  8. Environment Control to Improve Recombinant Protein Yields in Plants Based on Agrobacterium-Mediated Transient Gene Expression.

    PubMed

    Fujiuchi, Naomichi; Matoba, Nobuyuki; Matsuda, Ryo

    2016-01-01

    Agrobacterium-mediated transient expression systems enable plants to produce a wide range of recombinant proteins on a rapid timescale. To achieve economically feasible upstream production and downstream processing, two yield parameters should be considered: (1) recombinant protein content per unit biomass and (2) recombinant protein productivity per unit area-time at the end of the upstream production. Because environmental factors in the upstream production have impacts on these parameters, environment control is important to maximize the recombinant protein yield. In this review, we summarize the effects of pre- and postinoculation environmental factors in the upstream production on the yield parameters and discuss the basic concept of environment control for plant-based transient expression systems. Preinoculation environmental factors associated with planting density, light quality, and nutrient supply affect plant characteristics, such as biomass and morphology, which in turn affect recombinant protein content and productivity. Accordingly, environment control for such plant characteristics has significant implications to achieve a high yield. On the other hand, postinoculation environmental factors, such as temperature, light intensity, and humidity, have been shown to affect recombinant protein content. Considering that recombinant protein production in Agrobacterium-mediated transient expression systems is a result of a series of complex biological events starting from T-DNA transfer from Agrobacterium tumefaciens to protein biosynthesis and accumulation in leaf tissue, we propose that dynamic environment control during the postinoculation process, i.e., changing environmental conditions at an appropriate timing for each event, may be a promising approach to obtain a high yield. Detailed descriptions of plant growth conditions and careful examination of environmental effects will significantly contribute to our knowledge to stably obtain high recombinant

  9. Environment Control to Improve Recombinant Protein Yields in Plants Based on Agrobacterium-Mediated Transient Gene Expression

    PubMed Central

    Fujiuchi, Naomichi; Matoba, Nobuyuki; Matsuda, Ryo

    2016-01-01

    Agrobacterium-mediated transient expression systems enable plants to produce a wide range of recombinant proteins on a rapid timescale. To achieve economically feasible upstream production and downstream processing, two yield parameters should be considered: (1) recombinant protein content per unit biomass and (2) recombinant protein productivity per unit area–time at the end of the upstream production. Because environmental factors in the upstream production have impacts on these parameters, environment control is important to maximize the recombinant protein yield. In this review, we summarize the effects of pre- and postinoculation environmental factors in the upstream production on the yield parameters and discuss the basic concept of environment control for plant-based transient expression systems. Preinoculation environmental factors associated with planting density, light quality, and nutrient supply affect plant characteristics, such as biomass and morphology, which in turn affect recombinant protein content and productivity. Accordingly, environment control for such plant characteristics has significant implications to achieve a high yield. On the other hand, postinoculation environmental factors, such as temperature, light intensity, and humidity, have been shown to affect recombinant protein content. Considering that recombinant protein production in Agrobacterium-mediated transient expression systems is a result of a series of complex biological events starting from T-DNA transfer from Agrobacterium tumefaciens to protein biosynthesis and accumulation in leaf tissue, we propose that dynamic environment control during the postinoculation process, i.e., changing environmental conditions at an appropriate timing for each event, may be a promising approach to obtain a high yield. Detailed descriptions of plant growth conditions and careful examination of environmental effects will significantly contribute to our knowledge to stably obtain high recombinant

  10. Gene Expression Noise, Fitness Landscapes, and Evolution

    NASA Astrophysics Data System (ADS)

    Charlebois, Daniel

    The stochastic (or noisy) process of gene expression can have fitness consequences for living organisms. For example, gene expression noise facilitates the development of drug resistance by increasing the time scale at which beneficial phenotypic states can be maintained. The present work investigates the relationship between gene expression noise and the fitness landscape. By incorporating the costs and benefits of gene expression, we track how the fluctuation magnitude and timescale of expression noise evolve in simulations of cell populations under stress. We find that properties of expression noise evolve to maximize fitness on the fitness landscape, and that low levels of expression noise emerge when the fitness benefits of gene expression exceed the fitness costs (and that high levels of noise emerge when the costs of expression exceed the benefits). The findings from our theoretical/computational work offer new hypotheses on the development of drug resistance, some of which are now being investigated in evolution experiments in our laboratory using well-characterized synthetic gene regulatory networks in budding yeast. Nserc Postdoctoral Fellowship (Grant No. PDF-453977-2014).

  11. Distinct carbohydrate and lipid-based molecular patterns within lipopolysaccharides from Burkholderia cepacia contribute to defense-associated differential gene expression in Arabidopsis thaliana.

    PubMed

    Madala, Ntakadzeni E; Molinaro, Antonio; Dubery, Ian A

    2012-02-01

    Lipopolysaccharides are structural components within the cell walls of Gram-negative bacteria. The LPSs as microbe-associated molecular pattern (MAMP) molecules can trigger defense-related responses involved in MAMP-triggered immunity and basal resistance in plants, presumably from an initial perception event. LPS from Burkholderia cepacia as well as two fragments, the glycolipid, lipid A and the polysaccharide (OPS-core) chain, were used to treat Arabidopsis thaliana seedlings to evaluate the eliciting activities of the individual LPS sub-domains by means of Annealing Control Primer-based Differential Display transcript profiling. Genes found to be up-regulated encode for proteins involved in signal perception and transduction, transcriptional regulation and defense - and stress responses. Furthermore, genes encoding proteins involved in chaperoning, secretion, protein-protein interactions and protein degradation were differentially expressed. It is concluded that intact LPS, as well as the two sub-components, induced the expression of a broad range of genes associated with perception and defense as well as metabolic reprogramming of cellular activities in support of immunity and basal resistance. Whilst the lipid A and OPS moieties were able to up-regulate sub-sets of defense-associated genes over the same spectrum of categories as intact LPS, the up-regulation observed with intact LPS was the more comprehensive, suggesting that the lipid A and glycan molecular patterns of the molecule act as partial agonists, but that the intact LPS structure is required for full agonist activity.

  12. Inducible gene expression systems and plant biotechnology.

    PubMed

    Corrado, Giandomenico; Karali, Marianthi

    2009-01-01

    Plant biotechnology relies heavily on the genetic manipulation of crops. Almost invariantly, the gene of interest is expressed in a constitutive fashion, although this may not be strictly necessary for several applications. Currently, there are several regulatable expression systems for the temporal, spatial and quantitative control of transgene activity. These molecular switches are based on components derived from different organisms, which range from viruses to higher eukaryotes. Many inducible systems have been designed for fundamental and applied research and since their initial development, they have become increasingly popular in plant molecular biology. This review covers a broad number of inducible expression systems examining their properties and relevance for plant biotechnology in its various guises, from molecular breeding to pharmaceutical and industrial applications. For each system, we examine some advantages and limitations, also in relation to the strategy on which they rely. Besides being necessary to control useful genes that may negatively affect crop yield and quality, we discuss that inducible systems can be also used to increase public acceptance of GMOs, reducing some of the most common concerns. Finally, we suggest some directions and future developments for their further diffusion in agriculture and biotechnology.

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

    SciTech Connect

    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 specific tfb

  14. Stability and multiattractor dynamics of a toggle switch based on a two-stage model of stochastic gene expression.

    PubMed

    Strasser, Michael; Theis, Fabian J; Marr, Carsten

    2012-01-04

    A toggle switch consists of two genes that mutually repress each other. This regulatory motif is active during cell differentiation and is thought to act as a memory device, being able to choose and maintain cell fate decisions. Commonly, this switch has been modeled in a deterministic framework where transcription and translation are lumped together. In this description, bistability occurs for transcription factor cooperativity, whereas autoactivation leads to a tristable system with an additional undecided state. In this contribution, we study the stability and dynamics of a two-stage gene expression switch within a probabilistic framework inspired by the properties of the Pu/Gata toggle switch in myeloid progenitor cells. We focus on low mRNA numbers, high protein abundance, and monomeric transcription-factor binding. Contrary to the expectation from a deterministic description, this switch shows complex multiattractor dynamics without autoactivation and cooperativity. Most importantly, the four attractors of the system, which only emerge in a probabilistic two-stage description, can be identified with committed and primed states in cell differentiation. To begin, we study the dynamics of the system and infer the mechanisms that move the system between attractors using both the quasipotential and the probability flux of the system. Next, we show that the residence times of the system in one of the committed attractors are geometrically distributed. We derive an analytical expression for the parameter of the geometric distribution, therefore completely describing the statistics of the switching process and elucidate the influence of the system parameters on the residence time. Moreover, we find that the mean residence time increases linearly with the mean protein level. This scaling also holds for a one-stage scenario and for autoactivation. Finally, we study the implications of this distribution for the stability of a switch and discuss the influence of the

  15. Gene expression in the etiology of schizophrenia.

    PubMed

    Bray, Nicholas J

    2008-05-01

    Gene expression represents a fundamental interface between genes and environment in the development and ongoing plasticity of the human brain. Individual differences in gene expression are likely to underpin much of human diversity, including psychiatric illness. In the past decade, the development of microarray and proteomic technology has enabled global description of gene expression in schizophrenia. However, it is difficult on the basis of gene expression assays alone to distinguish between those changes that constitute primary etiology and those that reflect secondary pathology, compensatory mechanisms, or confounding influences. In this respect, tests of genetic association with schizophrenia will be instructive because changes in gene expression that result from gene variants that are associated with the disorder are likely to be of primary etiological significance. However, regulatory polymorphism is extremely difficult to recognize on the basis of sequence interrogation alone. Functional assays at the messenger RNA and/or protein level will be essential in elucidating the molecular mechanisms underlying genetic association with schizophrenia and are likely to become increasingly important in the identification of regulatory variants with which to test for association with the disorder and related traits. Once established, etiologically relevant changes in gene expression can be recapitulated in model systems in order to elucidate the molecular and physiological pathways that may ultimately give rise to the condition.

  16. Visualizing Gene Expression In Situ

    SciTech Connect

    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.

  17. Noise minimisation in gene expression switches.

    PubMed

    Monteoliva, Diana; McCarthy, Christina B; Diambra, Luis

    2013-01-01

    Gene expression is subject to stochastic variation which leads to fluctuations in the rate of protein production. Recently, a study in yeast at a genomic scale showed that, in some cases, gene expression variability alters phenotypes while, in other cases, these remain unchanged despite fluctuations in the expression of other genes. These studies suggested that noise in gene expression is a physiologically relevant trait and, to prevent harmful stochastic variation in the expression levels of some genes, it can be subject to minimisation. However, the mechanisms for noise minimisation are still unclear. In the present work, we analysed how noise expression depends on the architecture of the cis-regulatory system, in particular on the number of regulatory binding sites. Using analytical calculations and stochastic simulations, we found that the fluctuation level in noise expression decreased with the number of regulatory sites when regulatory transcription factors interacted with only one other bound transcription factor. In contrast, we observed that there was an optimal number of binding sites when transcription factors interacted with many bound transcription factors. This finding suggested a new mechanism for preventing large fluctuations in the expression of genes which are sensitive to the concentration of regulators.

  18. Noise Minimisation in Gene Expression Switches

    PubMed Central

    Monteoliva, Diana; McCarthy, Christina B.; Diambra, Luis

    2013-01-01

    Gene expression is subject to stochastic variation which leads to fluctuations in the rate of protein production. Recently, a study in yeast at a genomic scale showed that, in some cases, gene expression variability alters phenotypes while, in other cases, these remain unchanged despite fluctuations in the expression of other genes. These studies suggested that noise in gene expression is a physiologically relevant trait and, to prevent harmful stochastic variation in the expression levels of some genes, it can be subject to minimisation. However, the mechanisms for noise minimisation are still unclear. In the present work, we analysed how noise expression depends on the architecture of the cis-regulatory system, in particular on the number of regulatory binding sites. Using analytical calculations and stochastic simulations, we found that the fluctuation level in noise expression decreased with the number of regulatory sites when regulatory transcription factors interacted with only one other bound transcription factor. In contrast, we observed that there was an optimal number of binding sites when transcription factors interacted with many bound transcription factors. This finding suggested a new mechanism for preventing large fluctuations in the expression of genes which are sensitive to the concentration of regulators. PMID:24376783

  19. Nucleosome repositioning underlies dynamic gene expression.

    PubMed

    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.

  20. Gene Expression Patterns in Human Liver Cancers

    PubMed Central

    Chen, Xin; Cheung, Siu Tim; So, Samuel; Fan, Sheung Tat; Barry, Christopher; Higgins, John; Lai, Kin-Man; Ji, Jiafu; Dudoit, Sandrine; Ng, Irene O.L.; van de Rijn, Matt; Botstein, David; Brown, Patrick O.

    2002-01-01

    Hepatocellular carcinoma (HCC) is a leading cause of death worldwide. Using cDNA microarrays to characterize patterns of gene expression in HCC, we found consistent differences between the expression patterns in HCC compared with those seen in nontumor liver tissues. The expression patterns in HCC were also readily distinguished from those associated with tumors metastatic to liver. The global gene expression patterns intrinsic to each tumor were sufficiently distinctive that multiple tumor nodules from the same patient could usually be recognized and distinguished from all the others in the large sample set on the basis of their gene expression patterns alone. The distinctive gene expression patterns are characteristic of the tumors and not the patient; the expression programs seen in clonally independent tumor nodules in the same patient were no more similar than those in tumors from different patients. Moreover, clonally related tumor masses that showed distinct expression profiles were also distinguished by genotypic differences. Some features of the gene expression patterns were associated with specific phenotypic and genotypic characteristics of the tumors, including growth rate, vascular invasion, and p53 overexpression. PMID:12058060

  1. [DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer].

    PubMed

    Kwiatkowski, Przemysław; Wierzbicki, Piotr; Kmieć, Andrzej; Godlewski, Janusz

    2012-06-11

     Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations. Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment. The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

  2. An internal regulatory element controls troponin I gene expression

    SciTech Connect

    Yutzey, K.E.; Kline, R.L.; Konieczmy, S.F. . Dept. of Biological Sciences)

    1989-04-01

    During skeletal myogenesis, approximately 20 contractile proteins and related gene products temporally accumulate as the cells fuse to form multinucleated muscle fibers. In most instances, the contractile protein genes are regulated transcriptionally, which suggests that a common molecular mechanism may coordinate the expression of this diverse and evolutionarily unrelated gene set. Recent studies have examined the muscle-specific cis-acting elements associated with numerous contractile protein genes. All of the identified regulatory elements are positioned in the 5'-flanking regions, usually within 1,500 base pairs of the transcription start site. Surprisingly, a DNA consensus sequence that is common to each contractile protein gene has not been identified. In contrast to the results of these earlier studies, the authors have found that the 5'-flanking region of the quail troponin I (TnI) gene is not sufficient to permit the normal myofiber transcriptional activation of the gene. Instead, the TnI gene utilizes a unique internal regulatory element that is responsible for the correct myofiber-specific expression pattern associated with the TnI gene. This is the first example in which a contractile protein gene has been shown to rely primarily on an internal regulatory element to elicit transcriptional activation during myogenesis. The diversity of regulatory elements associated with the contractile protein genes suggests that the temporal expression of the genes may involve individual cis-trans regulatory components specific for each gene.

  3. Identifying nonspecific SAGE tags by context of gene expression.

    PubMed

    Ge, Xijin; Wang, San Ming

    2008-01-01

    Many serial analysis of gene expression (SAGE) tags can be matched to multiple genes, leading to difficulty in SAGE data interpretation and analysis. As only a subset of genes in the human genome are transcribed in a certain type of tissue/cell, we used microarray expression data from different tissue types to define contexts of gene expression and to annotate SAGE tags collected from the same or similar tissue sources. To predict the original transcript contributing a nonspecific SAGE tag collected from a particular tissue, we ranked the corresponding genes by their expression levels determined by microarray. We developed a tissue-specific SAGE tag annotation database based on microarray data collected from 73 normal human tissues and 18 cancer tissues and cell lines. The database can be queried online at: http://www.basic.northwestern.edu/SAGE/. The accuracy of this database was confirmed by experimental data.

  4. A hammerhead ribozyme inhibits ADE1 gene expression in yeast.

    PubMed

    Ferbeyre, G; Bratty, J; Chen, H; Cedergren, R

    1995-03-21

    To study factors that affect in vivo ribozyme (Rz) activity, a model system has been devised in Saccharomyces cerevisiae based on the inhibition of ADE1 gene expression. This gene was chosen because Rz action can be evaluated visually by the Red phenotype produced when the activity of the gene product is inhibited. Different plasmid constructs allowed the expression of the Rz either in cis or in trans with respect to ADE1. Rz-related inhibition of ADE1 expression was correlated with a Red phenotype and a diminution of ADE1 mRNA levels only when the Rz gene was linked 5' to ADE1. The presence of the expected 3' cleavage fragment was demonstrated using a technique combining RNA ligation and PCR. This yeast system and detection technique are suited to the investigation of general factors affecting Rz-catalyzed inhibition of gene expression under in vivo conditions.

  5. Cell Cycle Programs of Gene Expression Control Morphogenetic Protein Localization

    PubMed Central

    Lord, Matthew; Yang, Melody C.; Mischke, Michelle; Chant, John

    2000-01-01

    Genomic studies in yeast have revealed that one eighth of genes are cell cycle regulated in their expression. Almost without exception, the significance of cell cycle periodic gene expression has not been tested. Given that many such genes are critical to cellular morphogenesis, we wanted to examine the importance of periodic gene expression to this process. The expression profiles of two genes required for the axial pattern of cell division, BUD3 and BUD10/AXL2/SRO4, are strongly cell cycle regulated. BUD3 is expressed close to the onset of mitosis. BUD10 is expressed in late G1. Through promotor-swap experiments, the expression profile of each gene was altered and the consequences examined. We found that an S/G2 pulse of BUD3 expression controls the timing of Bud3p localization, but that this timing is not critical to Bud3p function. In contrast, a G1 pulse of BUD10 expression plays a direct role in Bud10p localization and function. Bud10p, a membrane protein, relies on the polarized secretory machinery specific to G1 to be delivered to its proper location. Such a secretion-based targeting mechanism for membrane proteins provides cells with flexibility in remodeling their architecture or evolving new forms. PMID:11134078

  6. Identification, Expression Profiling and Fluorescence-Based Binding Assays of a Chemosensory Protein Gene from the Western Flower Thrips, Frankliniella occidentalis

    PubMed Central

    Zhang, Zhi-Ke; Lei, Zhong-Ren

    2015-01-01

    Using RT-PCR and RACE-PCR strategies, we cloned and identified a new chemosensory protein (FoccCSP) from the Western flower thrips, Frankliniella occidentalis, a species for which no chemosensory protein (CSP) has yet been identified. The FoccCSP gene contains a 387 bp open-reading frame encoding a putative protein of 128 amino acids with a molecular weight of 14.51 kDa and an isoelectric point of 5.41. The deduced amino acid sequence contains a putative signal peptide of 19 amino acid residues at the N-terminus, as well as the typical four—cysteine signature found in other insect CSPs. As FoccCSP is from a different order of insect than other known CSPs, the GenBank FoccCSP homolog showed only 31-50% sequence identity with them. A neighbor-joining tree was constructed and revealed that FoccCSP is in a group with CSPs from Homopteran insects (e.g., AgosCSP4, AgosCSP10, ApisCSP, and NlugCSP9), suggesting that these genes likely developed from a common ancestral gene. The FoccCSP gene expression profile of different tissues and development stages was measured by quantitative real-time PCR. The results of this analysis revealed this gene is predominantly expressed in the antennae and also highly expressed in the first instar nymph, suggesting a function for FoccCSP in olfactory reception and in particular life activities during the first instar nymph stage. We expressed recombinant FoccCSP protein in a prokaryotic expression system and purified FoccCSP protein by affinity chromatography using a Ni-NTA-Sepharose column. Using N-phenyl-1-naphthylamine (1-NPN) as a fluorescent probe in fluorescence-based competitive binding assay, we determined the binding affinities of 19 volatile substances for FoccCSP protein. This analysis revealed that anisic aldehyde, geraniol and methyl salicylate have high binding affinities for FoccCSP, with KD values of 10.50, 15.35 and 35.24 μM, respectively. Thus, our study indicates that FoccCSP may play an important role in regulating

  7. Deep sequencing-based transcriptional analysis of bovine mammary epithelial cells gene expression in response to in vitro infection with Staphylococcus aureus stains.

    PubMed

    Wang, Xiao; Xiu, Lei; Hu, Qingliang; Cui, Xinjie; Liu, Bingchun; Tao, Lin; Wang, Ting; Wu, Jingging; Chen, Yuan; Chen, Yan

    2013-01-01

    Staphylococcus aureus (S. aureus) is an important etiological organism in chronic and subclinical mastitis in lactating cows. Given the fundamental role the primary bovine mammary epithelial cells (pBMECs) play as a major first line of defense against invading pathogens, their interactions with S. aureus was hypothesized to be crucial to the establishment of the latter's infection process. This hypothesis was tested by investigating the global transcriptional responses of pBMECs to three S. aureus strains (S56,S178 and S36) with different virulent factors, using a tag-based high-throughput transcriptome sequencing technique. Approximately 4.9 million total sequence tags were obtained from each of the three S. aureus-infected libraries and the control library. Referenced to the control, 1720, 219, and 427 differentially expressed unique genes were identified in the pBMECs infected with S56, S178 and S36 S. aureus strains respectively. Gene ontology (GO) and pathway analysis of the S56-infected pBMECs referenced to those of the control revealed that the differentially expressed genes in S56-infected pBMECs were significantly involved in inflammatory response, cell signalling pathways and apoptosis. In the same vein, the clustered GO terms of the differentially expressed genes of the S178-infected pBMECs were found to comprise immune responses, metabolism transformation, and apoptosis, while those of the S36-infected pBMECs were primarily involved in cell cycle progression and immune responses. Furthermore, fundamental differences were observed in the levels of expression of immune-related genes in response to treatments with the three S. aureus strains. These differences were especially noted for the expression of important pro-inflammatory molecules, including IL-1α, TNF, EFNB1, IL-8, and EGR1. The transcriptional changes associated with cellular signaling and the inflammatory response in this study may reflect different immunomodulatory mechanisms that underlie

  8. Gene expression homeostasis and chromosome architecture

    PubMed Central

    Seshasayee, Aswin Sai Narain

    2014-01-01

    In rapidly growing populations of bacterial cells, including those of the model organism Escherichia coli, genes essential for growth - such as those involved in protein synthesis - are expressed at high levels; this is in contrast to many horizontally-acquired genes, which are maintained at low transcriptional levels.1 This balance in gene expression states between 2 distinct classes of genes is established by a galaxy of transcriptional regulators, including the so-called nucleoid associated proteins (NAP) that contribute to shaping the chromosome.2 Besides these active players in gene regulation, it is not too far-fetched to anticipate that genome organization in terms of how genes are arranged on the chromosome,3 which is the result of long-drawn transactions among genome rearrangement processes and selection, and the manner in which it is structured inside the cell, plays a role in establishing this balance. A recent study from our group has contributed to the literature investigating the interplay between global transcriptional regulators and genome organization in establishing gene expression homeostasis.4 In particular, we address a triangle of functional interactions among genome organization, gene expression homeostasis and horizontal gene transfer. PMID:25997086

  9. Unmasking ultradian rhythms in gene expression

    PubMed Central

    van der Veen, Daan R.; Gerkema, Menno P.

    2017-01-01

    Biological oscillations with an ultradian time scale of 1 to several hours include cycles in behavioral arousal, episodic glucocorticoid release, and gene expression. Ultradian rhythms are thought to have an extrinsic origin because of a perceived absence of ultradian rhythmicity in vitro and a lack of known molecular ultradian oscillators. We designed a novel, non–spectral-analysis method of separating ultradian from circadian components and applied it to a published gene expression dataset with an ultradian sampling resolution. Ultradian rhythms in mouse hepatocytes in vivo have been published, and we validated our approach using this control by confirming 175 of 323 ultradian genes identified in a prior study and found 862 additional ultradian genes. For the first time, we now report ultradian expression of >900 genes in vitro. Sixty genes exhibited ultradian transcriptional rhythmicity, both in vivo and in vitro, including 5 genes involved in the cell cycle. Within these 60 genes, we identified significant enrichment of specific DNA motifs in the 1000 bp proximal promotor, some of which associate with known transcriptional factors. These findings are in strong support of instrinsically driven ultradian rhythms and expose potential molecular mechanisms and functions underlying ultradian rhythms that remain unknown.—Van der Veen, D. R., Gerkema, M. P. Unmasking ultradian rhythms in gene expression. PMID:27871062

  10. Gene expression profile analysis of ventilator-associated pneumonia

    PubMed Central

    XU, XIAOLI; YUAN, BO; LIANG, QUAN; HUANG, HUIMIN; YIN, XIANGYI; SHENG, XIAOYUE; NIE, NIUYAN; FANG, HONGMEI

    2015-01-01

    Based on the gene expression profile of patients with ventilator-associated pneumonia (VAP) and patients not affected by the disease, the present study aimed to enhance the current understanding of VAP development using bioinformatics methods. The expression profile GSE30385 was downloaded from the Gene Expression Omnibus database. The Linear Models for Microarray Data package in R language was used to screen and identify differentially expressed genes (DEGs), which were grouped as up- and down-regulated genes. The up- and downregulated genes were functionally enriched using the Database for Annotation, Visualization and Integrated Discovery system and then annotated according to TRANSFAC, Tumor Suppressor Gene and Tumor Associated Gene databases. Subsequently, the protein-protein interaction (PPI) network was constructed, followed by module analysis using CFinder software. A total of 69 DEGs, including 33 up- and 36 downregulated genes were screened out in patients with VAP. Upregulated genes were mainly enriched in functions and pathways associated with the immune response (including the genes ELANE and LTF) and the mitogen-activated protein kinase (MAPK) signaling pathway (including MAPK14). The PPI network comprised 64 PPI pairs and 44 nodes. The top two modules were enriched in different pathways, including the MAPK signaling pathway. Genes including ELANE, LTF and MAPK14 may have important roles in the development of VAP via altering the immune response and the MAPK signaling pathway. PMID:26459786

  11. Gene Expression Profiling in the Type 1 Diabetes Rat Diaphragm

    PubMed Central

    van Lunteren, Erik; Moyer, Michelle

    2009-01-01

    Background Respiratory muscle contractile performance is impaired by diabetes, mechanisms of which included altered carbohydrate and lipid metabolism, oxidative stress and changes in membrane electrophysiology. The present study examined to what extent these cellular perturbations involve changes in gene expression. Methodology/Principal Findings Diaphragm muscle from streptozotocin-diabetic rats was analyzed with Affymetrix gene expression arrays. Diaphragm from diabetic rats had 105 genes with at least ±2-fold significantly changed expression (55 increased, 50 decreased), and these were assigned to gene ontology groups based on over-representation analysis using DAVID software. There was increased expression of genes involved in palmitoyl-CoA hydrolase activity (a component of lipid metabolism) (P = 0.037, n = 2 genes, fold change 4.2 to 27.5) and reduced expression of genes related to carbohydrate metabolism (P = 0.000061, n = 8 genes, fold change −2.0 to −8.5). Other gene ontology groups among upregulated genes were protein ubiquitination (P = 0.0053, n = 4, fold change 2.2 to 3.4), oxidoreductase activity (P = 0.024, n = 8, fold change 2.1 to 6.0), and morphogenesis (P = 0.012, n = 10, fold change 2.1 to 4.3). Other downregulated gene groups were extracellular region (including extracellular matrix and collagen) (P = 0.00032, n = 13, fold change −2.2 to −3.7) and organogenesis (P = 0.032, n = 7, fold change −2.1 to −3.7). Real-time PCR confirmed the directionality of changes in gene expression for 30 of 31 genes tested. Conclusions/Significance These data indicate that in diaphragm muscle type 1 diabetes increases expression of genes involved in lipid energetics, oxidative stress and protein ubiquitination, decreases expression of genes involved in carbohydrate metabolism, and has little effect on expression of ion channel genes. Reciprocal changes in expression of genes involved in

  12. Improved detection of differentially expressed genes through incorporation of gene locations.

    PubMed

    Xiao, Guanghua; Reilly, Cavan; Khodursky, Arkady B

    2009-09-01

    In determining differential expression in cDNA microarray experiments, the expression level of an individual gene is usually assumed to be independent of the expression levels of other genes, but many recent studies have shown that a gene's expression level tends to be similar to that of its neighbors on a chromosome, and differentially expressed (DE) genes are likely to form clusters of similar transcriptional activity along the chromosome. When modeled as a one-dimensional spatial series, the expression level of genes on the same chromosome frequently exhibit significant spatial correlation, reflecting spatial patterns in transcription. By modeling these spatial correlations, we can obtain improved estimates of transcript levels. Here, we demonstrate the existence of spatial correlations in transcriptional activity in the Escherichia coli (E. coli) chromosome across more than 50 experimental conditions. Based on this finding, we propose a hierarchical Bayesian model that borrows information from neighboring genes to improve the estimation of the expression level of a given gene and hence the detection of DE genes. Furthermore, we extend the model to account for the circular structure of E. coli chromosome and the intergenetic distance between gene neighbors. The simulation studies and analysis of real data examples in E. coli and yeast Saccharomyces cerevisiae show that the proposed method outperforms the commonly used significant analysis of microarray (SAM) t-statistic in detecting DE genes.

  13. Expression of polarity genes in human cancer.

    PubMed

    Lin, Wan-Hsin; Asmann, Yan W; Anastasiadis, Panos Z

    2015-01-01

    Polarity protein complexes are crucial for epithelial apical-basal polarity and directed cell migration. Since alterations of these processes are common in cancer, polarity proteins have been proposed to function as tumor suppressors or oncogenic promoters. Here, we review the current understanding of polarity protein functions in epithelial homeostasis, as well as tumor formation and progression. As most previous studies focused on the function of single polarity proteins in simplified model systems, we used a genomics approach to systematically examine and identify the expression profiles of polarity genes in human cancer. The expression profiles of polarity genes were distinct in different human tissues and classified cancer types. Additionally, polarity expression profiles correlated with disease progression and aggressiveness, as well as with identified cancer types, where specific polarity genes were commonly altered. In the case of Scribble, gene expression analysis indicated its common amplification and upregulation in human cancer, suggesting a tumor promoting function.

  14. Regulation of Gene Expression in Protozoa Parasites

    PubMed Central

    Gomez, Consuelo; Esther Ramirez, M.; Calixto-Galvez, Mercedes; Medel, Olivia; 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 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. PMID:20204171

  15. Expression signature based on TP53 target genes doesn't predict response to TP53-MDM2 inhibitor in wild type TP53 tumors.

    PubMed

    Sonkin, Dmitriy

    2015-10-22

    A number of TP53-MDM2 inhibitors are currently under investigation as therapeutic agents in a variety of clinical trials in patients with TP53 wild type tumors. Not all wild type TP53 tumors are sensitive to such inhibitors. In an attempt to improve selection of patients with TP53 wild type tumors, an mRNA expression signature based on 13 TP53 transcriptional target genes was recently developed (Jeay et al. 2015). Careful reanalysis of TP53 status in the study validation data set of cancer cell lines considered to be TP53 wild type detected TP53 inactivating alterations in 23% of cell lines. The subsequent reanalysis of the remaining TP53 wild type cell lines clearly demonstrated that unfortunately the 13-gene signature cannot predict response to TP53-MDM2 inhibitor in TP53 wild type tumors.

  16. Patterns of Immune Infiltration in Breast Cancer and Their Clinical Implications: A Gene-Expression-Based Retrospective Study

    PubMed Central

    Ali, H. Raza; Chlon, Leon; Pharoah, Paul D. P.; Caldas, Carlos

    2016-01-01

    Background Immune infiltration of breast tumours is associated with clinical outcome. However, past work has not accounted for the diversity of functionally distinct cell types that make up the immune response. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast tumours influence survival and treatment response, and whether these effects differ by molecular subtype. Methods and Findings We applied an established computational approach (CIBERSORT) to bulk gene expression profiles of almost 11,000 tumours to infer the proportions of 22 subsets of immune cells. We investigated associations between each cell type and survival and response to chemotherapy, modelling cellular proportions as quartiles. We found that tumours with little or no immune infiltration were associated with different survival patterns according to oestrogen receptor (ER) status. In ER-negative disease, tumours lacking immune infiltration were associated with the poorest prognosis, whereas in ER-positive disease, they were associated with intermediate prognosis. Of the cell subsets investigated, T regulatory cells and M0 and M2 macrophages emerged as the most strongly associated with poor outcome, regardless of ER status. Among ER-negative tumours, CD8+ T cells (hazard ratio [HR] = 0.89, 95% CI 0.80–0.98; p = 0.02) and activated memory T cells (HR 0.88, 95% CI 0.80–0.97; p = 0.01) were associated with favourable outcome. T follicular helper cells (odds ratio [OR] = 1.34, 95% CI 1.14–1.57; p < 0.001) and memory B cells (OR = 1.18, 95% CI 1.0–1.39; p = 0.04) were associated with pathological complete response to neoadjuvant chemotherapy in ER-negative disease, suggesting a role for humoral immunity in mediating response to cytotoxic therapy. Unsupervised clustering analysis using immune cell proportions revealed eight subgroups of tumours, largely defined by the balance between M0, M1, and M2 macrophages, with distinct

  17. Amino acid regulation of gene expression.

    PubMed Central

    Fafournoux, P; Bruhat, A; Jousse, C

    2000-01-01

    The impact of nutrients on gene expression in mammals has become an important area of research. Nevertheless, the current understanding of the amino acid-dependent control of gene expression is limited. Because amino acids have multiple and important functions, their homoeostasis has to be finely maintained. However, amino-acidaemia can be affected by certain nutritional conditions or various forms of stress. It follows that mammals have to adjust several of their physiological functions involved in the adaptation to amino acid availability by regulating the expression of numerous genes. The aim of the present review is to examine the role of amino acids in regulating mammalian gene expression and protein turnover. It has been reported that some genes involved in the control of growth or amino acid metabolism are regulated by amino acid availability. For instance, limitation of several amino acids greatly increases the expression of the genes encoding insulin-like growth factor binding protein-1, CHOP (C/EBP homologous protein, where C/EBP is CCAAT/enhancer binding protein) and asparagine synthetase. Elevated mRNA levels result from both an increase in the rate of transcription and an increase in mRNA stability. Several observations suggest that the amino acid regulation of gene expression observed in mammalian cells and the general control process described in yeast share common features. Moreover, amino acid response elements have been characterized in the promoters of the CHOP and asparagine synthetase genes. Taken together, the results discussed in the present review demonstrate that amino acids, by themselves, can, in concert with hormones, play an important role in the control of gene expression. PMID:10998343

  18. Prediction of gene expression in embryonic structures of Drosophila melanogaster.

    PubMed

    Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

    2007-07-01

    Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

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

    PubMed

    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.

  20. Relationships among CFTR expression, HCO3− secretion, and host defense may inform gene- and cell-based cystic fibrosis therapies

    PubMed Central

    Shah, Viral S.; Ernst, Sarah; Tang, Xiao Xiao; Karp, Philip H.; Parker, Connor P.; Ostedgaard, Lynda S.; Welsh, Michael J.

    2016-01-01

    Cystic fibrosis (CF) is caused by mutations in the gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR) anion channel. Airway disease is the major source of morbidity and mortality. Successful implementation of gene- and cell-based therapies for CF airway disease requires knowledge of relationships among percentages of targeted cells, levels of CFTR expression, correction of electrolyte transport, and rescue of host defense defects. Previous studies suggested that, when ∼10–50% of airway epithelial cells expressed CFTR, they generated nearly wild-type levels of Cl− secretion; overexpressing CFTR offered no advantage compared with endogenous expression levels. However, recent discoveries focused attention on CFTR-mediated HCO3− secretion and airway surface liquid (ASL) pH as critical for host defense and CF pathogenesis. Therefore, we generated porcine airway epithelia with varying ratios of CF and wild-type cells. Epithelia with a 50:50 mix secreted HCO3− at half the rate of wild-type epithelia. Likewise, heterozygous epithelia (CFTR+/− or CFTR+/∆F508) expressed CFTR and secreted HCO3− at ∼50% of wild-type values. ASL pH, antimicrobial activity, and viscosity showed similar relationships to the amount of CFTR. Overexpressing CFTR increased HCO3− secretion to rates greater than wild type, but ASL pH did not exceed wild-type values. Thus, in contrast to Cl− secretion, the amount of CFTR is rate-limiting for HCO3− secretion and for correcting host defense abnormalities. In addition, overexpressing CFTR might produce a greater benefit than expressing CFTR at wild-type levels when targeting small fractions of cells. These findings may also explain the risk of airway disease in CF carriers. PMID:27114540

  1. Noncytopathic Sindbis virus RNA vectors for heterologous gene expression

    PubMed Central

    Agapov, Eugene V.; Frolov, Ilya; Lindenbach, Brett D.; Prágai, Béla M.; Schlesinger, Sondra; Rice, Charles M.

    1998-01-01

    Infection of vertebrate cells with alphaviruses normally leads to prodigious expression of virus-encoded genes and a dramatic inhibition of host protein synthesis. Recombinant Sindbis viruses and replicons have been useful as vectors for high level foreign gene expression, but the cytopathic effects of viral replication have limited their use to transient studies. We recently selected Sindbis replicons capable of persistent, noncytopathic growth in BHK cells and describe here a new generation of Sindbis vectors useful for long-term foreign gene expression based on such replicons. Foreign genes of interest as well as the dominant selectable marker puromycin N-acteyltransferase, which confers resistance to the drug puromycin, were expressed as subgenomic transcripts of noncytopathic replicons or defective-interfering genomes complemented in trans by a replicon. Based on these strategies, we developed vectors that can be initiated via either RNA or DNA transfection and analyzed them for their level and stability of foreign gene expression. Noncytopathic Sindbis vectors express reasonably high levels of protein in nearly every cell. These vectors should prove to be flexible tools for the rapid expression of heterologous genes under conditions in which cellular metabolism is not perturbed, and we illustrate their utility with a number of foreign proteins. PMID:9789028

  2. Perspectives: Gene Expression in Fisheries Management

    USGS Publications Warehouse

    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.

  3. Full Design Automation of Multi-State RNA Devices to Program Gene Expression Using Energy-Based Optimization

    PubMed Central

    Majer, Eszter; Daròs, José-Antonio; Jaramillo, Alfonso

    2013-01-01

    Small RNAs (sRNAs) can operate as regulatory agents to control protein expression by interaction with the 5′ untranslated region of the mRNA. We have developed a physicochemical framework, relying on base pair interaction energies, to design multi-state sRNA devices by solving an optimization problem with an objective function accounting for the stability of the transition and final intermolecular states. Contrary to the analysis of the reaction kinetics of an ensemble of sRNAs, we solve the inverse problem of finding sequences satisfying targeted reactions. We show here that our objective function correlates well with measured riboregulatory activity of a set of mutants. This has enabled the application of the methodology for an extended design of RNA devices with specified behavior, assuming different molecular interaction models based on Watson-Crick interaction. We designed several YES, NOT, AND, and OR logic gates, including the design of combinatorial riboregulators. In sum, our de novo approach provides a new paradigm in synthetic biology to design molecular interaction mechanisms facilitating future high-throughput functional sRNA design. PMID:23935479

  4. Gene Expression Profiling of Breast Cancer Brain Metastasis

    PubMed Central

    Lee, Ji Yun; Park, Kyunghee; Lee, Eunjin; Ahn, TaeJin; Jung, Hae Hyun; Lim, Sung Hee; Hong, Mineui; Do, In-Gu; Cho, Eun Yoon; Kim, Duk-Hwan; Kim, Ji-Yeon; Ahn, Jin Seok; Im, Young-Hyuck; Park, Yeon Hee

    2016-01-01

    The biology of breast cancer brain metastasis (BCBM) is poorly understood. We aimed to explore genes that are implicated in the process of brain metastasis of primary breast cancer (BC). NanoString nCounter Analysis covering 252 target genes was used for comparison of gene expression levels between 20 primary BCs that relapsed to brain and 41 BCBM samples. PAM50-based intrinsic subtypes such as HER2-enriched and basal-like were clearly over-represented in BCBM. A panel of 22 genes was found to be significantly differentially expressed between primary BC and BCBM. Five of these genes, CXCL12, MMP2, MMP11, VCAM1, and MME, which have previously been associated with tumor progression, angiogenesis, and metastasis, clearly discriminated between primary BC and BCBM. Notably, the five genes were significantly upregulated in primary BC compared to BCBM. Conversely, SOX2 and OLIG2 genes were upregulated in BCBM. These genes may participate in metastatic colonization but not in primary tumor development. Among patient-matched paired samples (n = 17), a PAM50 molecular subtype conversion was observed in eight cases (47.1%), with a trend toward unfavorable subtypes in patients with the distinct gene expression. Our findings, although not conclusive, reveal differentially expressed genes that might mediate the brain metastasis process. PMID:27340107

  5. Improved integrative framework combining association data with gene expression features to prioritize Crohn's disease genes.

    PubMed

    Ning, Kaida; Gettler, Kyle; Zhang, Wei; Ng, Sok Meng; Bowen, B Monica; Hyams, Jeffrey; Stephens, Michael C; Kugathasan, Subra; Denson, Lee A; Schadt, Eric E; Hoffman, Gabriel E; Cho, Judy H

    2015-07-15

    Genome-wide association studies in Crohn's disease (CD) have identified 140 genome-wide significant loci. However, identification of genes driving association signals remains challenging. Furthermore, genome-wide significant thresholds limit false positives at the expense of decreased sensitivity. In this study, we explored gene features contributing to CD pathogenicity, including gene-based association data from CD and autoimmune (AI) diseases, as well as gene expression features (eQTLs, epigenetic markers of expression and intestinal gene expression data). We developed an integrative model based on a CD reference gene set. This integrative approach outperformed gene-based association signals alone in identifying CD-related genes based on statistical validation, gene ontology enrichment, differential expression between M1 and M2 macrophages and a validation using genes causing monogenic forms of inflammatory bowel disease as a reference. Besides gene-level CD association P-values, association with AI diseases was the strongest predictor, highlighting generalized mechanisms of inflammation, and the interferon-γ pathway particularly. Within the 140 high-confidence CD regions, 598 of 1328 genes had low prioritization scores, highlighting genes unlikely to contribute to CD pathogenesis. For select regions, comparably high integrative model scores were observed for multiple genes. This is particularly evident for regions having extensive linkage disequilibrium such as the IBD5 locus. Our analyses provide a standardized reference for prioritizing potential CD-related genes, in regions with both highly significant and nominally significant gene-level association P-values. Our integrative model may be particularly valuable in prioritizing rare, potentially private, missense variants for which genome-wide evidence for association may be unattainable.

  6. Improved integrative framework combining association data with gene expression features to prioritize Crohn's disease genes

    PubMed Central

    Ning, Kaida; Gettler, Kyle; Zhang, Wei; Ng, Sok Meng; Bowen, B. Monica; Hyams, Jeffrey; Stephens, Michael C.; Kugathasan, Subra; Denson, Lee A.; Schadt, Eric E.; Hoffman, Gabriel E.; Cho, Judy H.

    2015-01-01

    Genome-wide association studies in Crohn's disease (CD) have identified 140 genome-wide significant loci. However, identification of genes driving association signals remains challenging. Furthermore, genome-wide significant thresholds limit false positives at the expense of decreased sensitivity. In this study, we explored gene features contributing to CD pathogenicity, including gene-based association data from CD and autoimmune (AI) diseases, as well as gene expression features (eQTLs, epigenetic markers of expression and intestinal gene expression data). We developed an integrative model based on a CD reference gene set. This integrative approach outperformed gene-based association signals alone in identifying CD-related genes based on statistical validation, gene ontology enrichment, differential expression between M1 and M2 macrophages and a validation using genes causing monogenic forms of inflammatory bowel disease as a reference. Besides gene-level CD association P-values, association with AI diseases was the strongest predictor, highlighting generalized mechanisms of inflammation, and the interferon-γ pathway particularly. Within the 140 high-confidence CD regions, 598 of 1328 genes had low prioritization scores, highlighting genes unlikely to contribute to CD pathogenesis. For select regions, comparably high integrative model scores were observed for multiple genes. This is particularly evident for regions having extensive linkage disequilibrium such as the IBD5 locus. Our analyses provide a standardized reference for prioritizing potential CD-related genes, in regions with both highly significant and nominally significant gene-level association P-values. Our integrative model may be particularly valuable in prioritizing rare, potentially private, missense variants for which genome-wide evidence for association may be unattainable. PMID:25935003

  7. 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

    PubMed Central

    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

  8. Control of gene expression in trypanosomes.

    PubMed Central

    Vanhamme, L; Pays, E

    1995-01-01

    Trypanosomes are protozoan agents of major parasitic diseases such as Chagas' disease in South America and sleeping sickness of humans and nagana disease of cattle in Africa. They are transmitted to mammalian hosts by specific insect vectors. Their life cycle consists of a succession of differentiation and growth phases requiring regulated gene expression to adapt to the changing extracellular environment. Typical of such stage-specific expression is that of the major surface antigens of Trypanosoma brucei, procyclin in the procyclic (insect) form and the variant surface glycoprotein (VSG) in the bloodstream (mammalian) form. In trypanosomes, the regulation of gene expression is effected mainly at posttranscriptional levels, since primary transcription of most of the genes occurs in long polycistronic units and is constitutive. The transcripts are processed by transsplicing and polyadenylation under the influence of intergenic polypyrimidine tracts. These events show some developmental regulation. Untranslated sequences of the mRNAs seem to play a prominent role in the stage-specific control of individual gene expression, through a modulation of mRNA abundance. The VSG and procyclin transcription units exhibit particular features that are probably related to the need for a high level of expression. The promoters and RNA polymerase driving the expression of these units resemble those of the ribosomal genes. Their mutually exclusive expression is ensured by controls operating at several levels, including RNA elongation. Antigenic variation in the bloodstream is achieved through DNA rearrangements or alternative activation of the telomeric VSG gene expression sites. Recent discoveries, such as the existence of a novel nucleotide in telomeric DNA and the generation of point mutations in VSG genes, have shed new light on the mechanisms and consequences of antigenic variation. PMID:7603410

  9. Digital gene expression for non-model organisms

    PubMed Central

    Hong, Lewis Z.; Li, Jun; Schmidt-Küntzel, Anne; Warren, Wesley C.; Barsh, Gregory S.

    2011-01-01

    Next-generation sequencing technologies offer new approaches for global measurements of gene expression but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra-high-throughput sequencing of 27-bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6–8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high-quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus) and identify genes likely to control differences in the color of spotted versus non-spotted regions. PMID:21844123

  10. Application of multidisciplinary analysis to gene expression.

    SciTech Connect

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

    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

  11. Evidence-based gene predictions in plant genomes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Automated evidence-based gene building is a rapid and cost-effective way to provide reliable gene annotations on newly sequenced genomes. One of the limitations of evidence-based gene builders, however, is their requirement for gene expression evidence—known proteins, full-length cDNAs, or expressed...

  12. Reference genes for gene expression analysis in proliferating and differentiating human keratinocytes.

    PubMed

    Lanzafame, Manuela; Botta, Elena; Teson, Massimo; Fortugno, Paola; Zambruno, Giovanna; Stefanini, Miria; Orioli, Donata

    2015-04-01

    Abnormalities in keratinocyte growth and differentiation have a pathogenic significance in many skin disorders and result in gene expression alterations detectable by quantitative real-time RT-PCR (qRT-PCR). Relative quantification based on endogenous control (EC) genes is the commonly adopted approach, and the use of multiple reference genes from independent pathways is considered a best practice guideline, unless fully validated EC genes are available. The literature on optimal reference genes during in vitro calcium-induced differentiation of normal human epidermal keratinocytes (NHEK) is inconsistent. In many studies, the expression of target genes is compared to that of housekeeping genes whose expression, however, significantly varies during keratinocyte differentiation. Here, we report the results of our investigations on the expression stability of 15 candidate EC genes, including those commonly used as reference in expression analysis by qRT-PCR, during NHEK calcium-induced differentiation. We demonstrate that YWHAZ and UBC are extremely stable genes, and therefore, they represent optimal EC genes for expression studies in proliferating and calcium-induced differentiating NHEK. Furthermore, we demonstrate that YWHAZ/14-3-3-zeta is a suitable reference for quantitative comparison of both transcript and protein levels.

  13. Modeling gene expression in time and space.

    PubMed

    Rué, Pau; Garcia-Ojalvo, Jordi

    2013-01-01

    Cell populations rarely exhibit gene-expression profiles that are homogeneous in time and space. In the temporal domain, dynamical behaviors such as oscillations and pulses of protein production pervade cell biology, underlying phenomena as diverse as circadian rhythmicity, cell cycle control, stress and damage responses, and stem-cell pluripotency. In multicellular populations, spatial heterogeneities are crucial for decision making and development, among many other functions. Cells need to exquisitely coordinate this temporal and spatial variation to survive. Although the spatiotemporal character of gene expression is challenging to quantify experimentally at the level of individual cells, it is beneficial from the modeling viewpoint, because it provides strong constraints that can be probed by theoretically analyzing mathematical models of candidate gene and protein circuits. Here, we review recent examples of temporal dynamics and spatial patterning in gene expression to show how modeling such phenomenology can help us unravel the molecular mechanisms of cellular function.

  14. Chemically regulated gene expression in plants.

    PubMed

    Padidam, Malla

    2003-04-01

    Chemically inducible systems that activate or inactivate gene expression have many potential applications in the determination of gene function and in plant biotechnology. The precise timing and control of gene expression are important aspects of chemically inducible systems. Several systems have been developed and used to analyze gene function, marker-free plant transformation, site-specific DNA excision, activation tagging, conditional genetic complementation, and restoration of male fertility. Chemicals that are used to regulate transgene expression include the antibiotic tetracycline, the steroids dexamethasone and estradiol, copper, ethanol, the inducer of pathogen-related proteins benzothiadiazol, herbicide safeners, and the insecticide methoxyfenozide. Systems that are suitable for field application are particularly useful for experimental systems and have potential applications in biotechnology.

  15. CIRCADIAN CLOCK AND CELL CYCLE GENE EXPRESSION

    PubMed Central

    Metz, Richard P.; Qu, Xiaoyu; Laffin, Brian; Earnest, David; Porter, Weston W.

    2009-01-01

    Mouse mammary epithelial cells (HC-11) and mammary tissues were analyzed for developmental changes in circadian clock, cellular proliferation and differentiation marker genes. Expression of the clock genes, Per1 and Bmal1, were elevated in differentiated HC-11 cells whereas Per2 mRNA levels were higher in undifferentiated cells. This differentiation-dependent profile of clock gene expression was consistent with that observed in mouse mammary glands as Per1 and Bmal1 mRNA levels were elevated in late pregnant and lactating mammary tissues, while Per2 expression was higher in proliferating virgin and early pregnant glands. In both HC-11 cells and mammary glands, elevated Per2 expression was positively correlated with c-Myc and Cyclin D1 mRNA levels while Per1 and Bmal1 expression changed in conjunction with ß-casein mRNA levels. Interestingly, developmental stage had differential effects on rhythms of clock gene expression in the mammary gland. These data suggest that circadian clock genes may play a role in mouse mammary gland development and differentiation. PMID:16261617

  16. Gene expression defines natural changes in mammalian lifespan

    PubMed Central

    Fushan, Alexey A; Turanov, Anton A; Lee, Sang-Goo; Kim, Eun Bae; Lobanov, Alexei V; Yim, Sun Hee; Buffenstein, Rochelle; Lee, Sang-Rae; Chang, Kyu-Tae; Rhee, Hwanseok; Kim, Jong-So; Yang, Kap-Seok; Gladyshev, Vadim N

    2015-01-01

    Mammals differ more than 100-fold in maximum lifespan, which can be altered in either direction during evolution, but the molecular basis for natural changes in longevity is not understood. Divergent evolution of mammals also led to extensive changes in gene expression within and between lineages. To understand the relationship between lifespan and variation in gene expression, we carried out RNA-seq-based gene expression analyses of liver, kidney, and brain of 33 diverse species of mammals. Our analysis uncovered parallel evolution of gene expression and lifespan, as well as the associated life-history traits, and identified the processes and pathways involved. These findings provide direct insights into how nature reversibly adjusts lifespan and other traits during adaptive radiation of lineages. PMID:25677554

  17. Evaluating Fumonisin Gene Expression in Fusarium verticillioides.

    PubMed

    Scala, Valeria; Visentin, Ivan; Cardinale, Francesca

    2017-01-01

    Transcript levels of key genes in a biosynthetic pathway are often taken as a proxy for metabolite production. This is the case of FUM1, encoding the first dedicated enzyme in the metabolic pathway leading to the production of the mycotoxins Fumonisins by fungal species belonging to the genus Fusarium. FUM1 expression can be quantified by different methods; here, we detail a protocol based on quantitative reverse transcriptase polymerase chain reaction (RT-qPCR), by which relative or absolute transcript abundance can be estimated in Fusaria grown in vitro or in planta. As very seldom commercial kits for RNA extraction and cDNA synthesis are optimized for fungal samples, we developed a protocol tailored for these organisms, which stands alone but can be also easily integrated with specific reagents and kits commercially available.

  18. All-optical regulation of gene expression in targeted cells

    NASA Astrophysics Data System (ADS)

    Wang, Yisen; He, Hao; Li, Shiyang; Liu, Dayong; Lan, Bei; Hu, Minglie; Cao, Youjia; Wang, Chingyue

    2014-06-01

    Controllable gene expression is always a challenge and of great significance to biomedical research and clinical applications. Recently, various approaches based on extra-engineered light-sensitive proteins have been developed to provide optogenetic actuators for gene expression. Complicated biomedical techniques including exogenous genes engineering, transfection, and material delivery are needed. Here we present an all-optical method to regulate gene expression in targeted cells. Intrinsic or exogenous genes can be activated by a Ca2+-sensitive transcription factor nuclear factor of activated T cells (NFAT) driven by a short flash of femtosecond-laser irradiation. When applied to mesenchymal stem cells, expression of a differentiation regulator Osterix can be activated by this method to potentially induce differentiation of them. A laser-induced ``Ca2+-comb'' (LiCCo) by multi-time laser exposure is further developed to enhance gene expression efficiency. This noninvasive method hence provides an encouraging advance of gene expression regulation, with promising potential of applying in cell biology and stem-cell science.

  19. Paternally expressed genes predominate in the placenta.

    PubMed

    Wang, Xu; Miller, Donald C; Harman, Rebecca; Antczak, Douglas F; Clark, Andrew G

    2013-06-25

    The discovery of genomic imprinting through studies of manipulated mouse embryos indicated that the paternal genome has a major influence on placental development. However, previous research has not demonstrated paternal bias in imprinted genes. We applied RNA sequencing to trophoblast tissue from reciprocal hybrids of horse and donkey, where genotypic differences allowed parent-of-origin identification of most expressed genes. Using this approach, we identified a core group of 15 ancient imprinted genes, of which 10 were paternally expressed. An additional 78 candidate imprinted genes identified by RNA sequencing also showed paternal bias. Pyrosequencing was used to confirm the imprinting status of six of the genes, including the insulin receptor (INSR), which may play a role in growth regulation with its reciprocally imprinted ligand, histone acetyltransferase-1 (HAT1), a gene involved in chromatin modification, and lymphocyte antigen 6 complex, locus G6C, a newly identified imprinted gene in the major histocompatibility complex. The 78 candidate imprinted genes displayed parent-of-origin expression bias in placenta but not fetus, and most showed less than 100% silencing of the imprinted allele. Some displayed variability in imprinting status among individuals. This variability results in a unique epigenetic signature for each placenta that contributes to variation in the intrauterine environment and thus presents the opportunity for natural selection to operate on parent-of-origin differential regulation. Taken together, these features highlight the plasticity of imprinting in mammals and the central importance of the placenta as a target tissue for genomic imprinting.

  20. EXCAVATOR: a computer program for efficiently mining gene expression data.

    PubMed

    Xu, Dong; Olman, Victor; Wang, Li; Xu, Ying

    2003-10-01

    Massive amounts of gene expression data are generated using microarrays for functional studies of genes and gene expression data clustering is a useful tool for studying the functional relationship among genes in a biological process. We have developed a computer package EXCAVATOR for clustering gene expression profiles based on our new framework for representing gene expression data as a minimum spanning tree. EXCAVATOR uses a number of rigorous and efficient clustering algorithms. This program has a number of unique features, including capabilities for: (i) data- constrained clustering; (ii) identification of genes with similar expression profiles to pre-specified seed genes; (iii) cluster identification from a noisy background; (iv) computational comparison between different clustering results of the same data set. EXCAVATOR can be run from a Unix/Linux/DOS shell, from a Java interface or from a Web server. The clustering results can be visualized as colored figures and 2-dimensional plots. Moreover, EXCAVATOR provides a wide range of options for data formats, distance measures, objective functions, clustering algorithms, methods to choose number of clusters, etc. The effectiveness of EXCAVATOR has been demonstrated on several experimental data sets. Its performance compares favorably against the popular K-means clustering method in terms of clustering quality and computing time.

  1. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

    PubMed

    Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

    2015-01-01

    The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  2. Hepatic Xenobiotic Metabolizing Enzyme Gene Expression ...

    EPA Pesticide Factsheets

    BACKGROUND: Differences in responses to environmental chemicals and drugs between life stages are likely due in part to differences in the expression of xenobiotic metabolizing enzymes and transporters (XMETs). No comprehensive analysis of the mRNA expression of XMETs has been carried out through life stages in any species. RESULTS: Using full-genome arrays, the mRNA expression of all XMETs and their regulatory proteins was examined during fetal (gestation day (GD) 19), neonatal (postnatal day (PND) 7), prepubescent (PND32), middle age (12 months), and old age (18 and 24 months) in the C57BL/6J (C57) mouse liver and compared to adults. Fetal and neonatal life stages exhibited dramatic differences in XMET mRNA expression compared to the relatively minor effects of old age. The total number of XMET probe sets that differed from adults was 636, 500, 84, 5, 43, and 102 for GD19, PND7, PND32, 12 months, 18 months and 24 months, respectively. At all life stages except PND32, under-expressed genes outnumbered over-expressed genes. The altered XMETs included those in all of the major metabolic and transport phases including introduction of reactive or polar groups (Phase I), conjugation (Phase II) and excretion (Phase III). In the fetus and neonate, parallel increases in expression were noted in the dioxin receptor, Nrf2 components and their regulated genes while nuclear receptors and regulated genes were generally down-regulated. Suppression of male-specific XMETs w

  3. An Efficient and Robust Statistical Modeling Approach to Discover Differentially Expressed Genes Using Genomic Expression Profiles

    PubMed Central

    Thomas, Jeffrey G.; Olson, James M.; Tapscott, Stephen J.; Zhao, Lue Ping

    2001-01-01

    We have developed a statistical regression modeling approach to discover genes that are differentially expressed between two predefined sample groups in DNA microarray experiments. Our model is based on well-defined assumptions, uses rigorous and well-characterized statistical measures, and accounts for the heterogeneity and genomic complexity of the data. In contrast to cluster analysis, which attempts to define groups of genes and/or samples that share common overall expression profiles, our modeling approach uses known sample group membership to focus on expression profiles of individual genes in a sensitive and robust manner. Further, this approach can be used to test statistical hypotheses about gene expression. To demonstrate this methodology, we compared the expression profiles of 11 acute myeloid leukemia (AML) and 27 acute lymphoblastic leukemia (ALL) samples from a previous study (Golub et al. 1999) and found 141 genes differentially expressed between AML and ALL with a 1% significance at the genomic level. Using this modeling approach to compare different sample groups within the AML samples, we identified a group of genes whose expression profiles correlated with that of thrombopoietin and found that genes whose expression associated with AML treatment outcome lie in recurrent chromosomal locations. Our results are compared with those obtained using t-tests or Wilcoxon rank sum statistics. PMID:11435405

  4. Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

    PubMed

    Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

    2014-05-01

    Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering.

  5. Gene Expression Profiling during Pregnancy in Rat Brain Tissue

    PubMed Central

    Mann, Phyllis E.

    2014-01-01

    The neurophysiological changes that occur during pregnancy in the female mammal have led to the coining of the phrases “expectant brain” and “maternal brain”. Although much is known of the hormonal changes during pregnancy, alterations in neurotransmitter gene expression have not been well-studied. We examined gene expression in the ventromedial nucleus of the hypothalamus (VMH) during pregnancy based on the fact that this nucleus not only modulates the physiological changes that occur during pregnancy but is also involved in the development of maternal behavior. This study was designed to identify genes that are differentially expressed between mid- and late-pregnancy in order to determine which genes may be associated with the onset and display of maternal behavior and the development of the maternal brain. A commercially available PCR array containing 84 neurotransmitter receptor and regulator genes (RT2 Profiler PCR array) was used. Brains were harvested from rats on days 12 and 21 of gestation, frozen, and micropunched to obtain the VMH. Total RNA was extracted, cDNA prepared, and SYBR Green qPCR was performed. In the VMH, expression of five genes were reduced on day 21 of gestation compared to day 12 (Chrna6, Drd5, Gabrr2, Prokr2, and Ppyr1) whereas Chat, Chrm5, Drd4, Gabra5, Gabrg2, LOC289606, Nmu5r2, and Npy5r expression was elevated. Five genes were chosen to be validated in an additional experiment based on their known involvement in maternal behavior onset. This experiment confirmed that gene expression for both the CCK-A receptor and the GABAAR γ2 receptor increases at the end of pregnancy. In general, these results identify genes possibly involved in the establishment of the maternal brain in rats and indicate possible new genes to be investigated. PMID:24961703

  6. Structure and expression of ubiquitin genes of Drosophila melanogaster.

    PubMed Central

    Lee, H S; Simon, J A; Lis, J T

    1988-01-01

    We isolated and characterized two related ubiquitin genes from Drosophila melanogaster, polyubiquitin and UB3-D. The polyubiquitin gene contained 18 repeats of the 228-base-pair monomeric ubiquitin-encoding unit arranged in tandem. This gene was localized to a minor heat shock puff site, 63F, and it encoded a constitutively expressed 4.4-kilobase polyubiquitin-encoding mRNA, whose level was induced threefold by heat shock. To investigate the pattern of expression of the polyubiquitin gene in developing animals, a polyubiquitin-lacZ fusion gene was introduced into the Drosophila genome by germ line transformation. The fusion gene was expressed at high levels in a tissue-general manner at all