Evaluation of Appropriate Reference Genes for Gene Expression Normalization during Watermelon Fruit Development.

Science.gov (United States)

Kong, Qiusheng; Yuan, Jingxian; Gao, Lingyun; Zhao, Liqiang; Cheng, Fei; Huang, Yuan; Bie, Zhilong

2015-01-01

Gene expression analysis in watermelon (Citrullus lanatus) fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR) is a routine technique for gene expression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC), β-actin (ClACT), and alpha tubulin 5 (ClTUA5) as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND) was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1), a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of gene expression in the studies on watermelon fruit biology.

Evaluation of suitable reference genes for gene expression studies ...

Indian Academy of Sciences (India)

2011-12-14

Dec 14, 2011 ... MADS family of TFs control floral organ identity within each whorl of the flower by activating downstream genes. Measuring gene expression in different tissue types and developmental stages is of fundamental importance in TFs functional research. In last few years, quantitative real-time. PCR (qRT-PCR) ...

Imaging gene expression in gene therapy

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-31

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

Garlic Influences Gene Expression In Vivo and In Vitro.

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

2016-02-01

There is a large body of preclinical research aimed at understanding the roles of garlic and garlic-derived preparations in the promotion of human health. Most of this research has targeted the possible functions of garlic in maintaining cardiovascular health and in preventing and treating cancer. A wide range of outcome variables has been used to investigate the bioactivity of garlic, ranging from direct measures of health status such as cholesterol concentrations, blood pressure, and changes in tumor size and number, to molecular and biochemical measures such as mRNA gene expression, protein concentration, enzyme activity, and histone acetylation status. Determination of how garlic influences mRNA gene expression has proven to be a valuable approach to elucidating the mechanisms of garlic bioactivity. Preclinical studies investigating the health benefits of garlic far outnumber human studies and have made frequent use of mRNA gene expression measurement. There is an immediate need to understand mRNA gene expression in humans as well. Although safety and ethical constraints limit the types of available human tissue, peripheral whole blood is readily accessible, and measuring mRNA gene expression in whole blood may provide a unique window to understanding how garlic intake affects human health. © 2016 American Society for Nutrition.

A composite peripheral blood gene expression measure as a potential diagnostic biomarker in bipolar disorder

DEFF Research Database (Denmark)

Munkholm, Klaus; Peijs, L; Vinberg, M

2015-01-01

as a diagnostic and state biomarker in bipolar disorder. First, messenger RNA levels of 19 candidate genes were assessed in peripheral blood mononuclear cells of 37 rapid cycling bipolar disorder patients in different affective states (depression, mania and euthymia) during a 6-12-month period and in 40 age...... subjects. In patients with bipolar disorder, upregulation of NDUFV2 was observed in a depressed state compared with a euthymic state. The composite gene expression measure for discrimination between patients and healthy control subjects on the basis of 19 genes generated an area under the receiver...

Reproducibility of gene expression across generations of Affymetrix microarrays

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Haslett Judith N

2003-06-01

Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

Expression profiling identifies genes involved in emphysema severity

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Bowman Rayleen V

2009-09-01

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

A new measure for gene expression biclustering based on non-parametric correlation.

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Flores, Jose L; Inza, Iñaki; Larrañaga, Pedro; Calvo, Borja

2013-12-01

One of the emerging techniques for performing the analysis of the DNA microarray data known as biclustering is the search of subsets of genes and conditions which are coherently expressed. These subgroups provide clues about the main biological processes. Until now, different approaches to this problem have been proposed. Most of them use the mean squared residue as quality measure but relevant and interesting patterns can not be detected such as shifting, or scaling patterns. Furthermore, recent papers show that there exist new coherence patterns involved in different kinds of cancer and tumors such as inverse relationships between genes which can not be captured. The proposed measure is called Spearman's biclustering measure (SBM) which performs an estimation of the quality of a bicluster based on the non-linear correlation among genes and conditions simultaneously. The search of biclusters is performed by using a evolutionary technique called estimation of distribution algorithms which uses the SBM measure as fitness function. This approach has been examined from different points of view by using artificial and real microarrays. The assessment process has involved the use of quality indexes, a set of bicluster patterns of reference including new patterns and a set of statistical tests. It has been also examined the performance using real microarrays and comparing to different algorithmic approaches such as Bimax, CC, OPSM, Plaid and xMotifs. SBM shows several advantages such as the ability to recognize more complex coherence patterns such as shifting, scaling and inversion and the capability to selectively marginalize genes and conditions depending on the statistical significance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

SIGNATURE: A workbench for gene expression signature analysis

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Chang Jeffrey T

2011-11-01

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

Variation-preserving normalization unveils blind spots in gene expression profiling

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Roca, Carlos P.; Gomes, Susana I. L.; Amorim, Mónica J. B.; Scott-Fordsmand, Janeck J.

2017-01-01

RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression. PMID:28276435

Analysis of multiplex gene expression maps obtained by voxelation

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Smith Desmond J

2009-04-01

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

Analysis of multiplex gene expression maps obtained by voxelation.

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An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

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

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

DEFF Research Database (Denmark)

Manijak, Mieszko P.; Nielsen, Henrik Bjørn

2011-01-01

circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

Bayesian assignment of gene ontology terms to gene expression experiments

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Sykacek, P.

2012-01-01

Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

Bayesian assignment of gene ontology terms to gene expression experiments.

Science.gov (United States)

Sykacek, P

2012-09-15

Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

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Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

2015-01-27

Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

Estradiol-induced gene expression in largemouth bass (Micropterus salmoides)

Science.gov (United States)

Bowman, C.J.; Kroll, K.J.; Gross, T.G.; Denslow, N.D.

2002-01-01

Vitellogenin (Vtg) and estrogen receptor (ER) gene expression levels were measured in largemouth bass to evaluate the activation of the ER-mediated pathway by estradiol (E2). Single injections of E2 ranging from 0.0005 to 5 mg/kg up-regulated plasma Vtg in a dose-dependent manner. Vtg and ER mRNAs were measured using partial cDNA sequences corresponding to the C-terminal domain for Vtg and the ligand-binding domain of ER?? sequences. After acute E2-exposures (2 mg/kg), Vtg and ER mRNAs and plasma Vtg levels peaked after 2 days. The rate of ER mRNA accumulation peaked 36-42 h earlier than Vtg mRNA. The expression window for ER defines the primary response to E2 in largemouth bass and that for Vtg a delayed primary response. The specific effect of E2 on other estrogen-regulated genes was tested during these same time windows using differential display RT-PCR. Specific up-regulated genes that are expressed in the same time window as Vtg were ERp72 (a membrane-bound disulfide isomerase) and a gene with homology to an expressed gene identified in zebrafish. Genes that were expressed in a pattern that mimics the ER include the gene for zona radiata protein ZP2, and a gene with homology to an expressed gene found in winter flounder. One gene for fibrinogen ?? was down-regulated and an unidentified gene was transiently up-regulated after 12 h of exposure and returned to basal levels by 48 h. Taken together these studies indicate that the acute molecular response to E2 involves a complex network of responses over time. ?? 2002 Elsevier Science Ireland Ltd. All rights reserved.

The accuracy of survival time prediction for patients with glioma is improved by measuring mitotic spindle checkpoint gene expression.

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Li Bie

Full Text Available Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001, and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67 labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time.

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

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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. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

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Benjamin Mayne

2016-10-01

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

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations.

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Sahra Uygun

2016-12-01

Full Text Available Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets.

Quantifying engineered nanomaterial toxicity: comparison of common cytotoxicity and gene expression measurements

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Donald H. Atha

2017-11-01

Full Text Available Abstract Background When evaluating the toxicity of engineered nanomaterials (ENMS it is important to use multiple bioassays based on different mechanisms of action. In this regard we evaluated the use of gene expression and common cytotoxicity measurements using as test materials, two selected nanoparticles with known differences in toxicity, 5 nm mercaptoundecanoic acid (MUA-capped InP and CdSe quantum dots (QDs. We tested the effects of these QDs at concentrations ranging from 0.5 to 160 µg/mL on cultured normal human bronchial epithelial (NHBE cells using four common cytotoxicity assays: the dichlorofluorescein assay for reactive oxygen species (ROS, the lactate dehydrogenase assay for membrane viability (LDH, the mitochondrial dehydrogenase assay for mitochondrial function, and the Comet assay for DNA strand breaks. Results The cytotoxicity assays showed similar trends when exposed to nanoparticles for 24 h at 80 µg/mL with a threefold increase in ROS with exposure to CdSe QDs compared to an insignificant change in ROS levels after exposure to InP QDs, a twofold increase in the LDH necrosis assay in NHBE cells with exposure to CdSe QDs compared to a 50% decrease for InP QDs, a 60% decrease in the mitochondrial function assay upon exposure to CdSe QDs compared to a minimal increase in the case of InP and significant DNA strand breaks after exposure to CdSe QDs compared to no significant DNA strand breaks with InP. High-throughput quantitative real-time polymerase chain reaction (qRT-PCR data for cells exposed for 6 h at a concentration of 80 µg/mL were consistent with the cytotoxicity assays showing major differences in DNA damage, DNA repair and mitochondrial function gene regulatory responses to the CdSe and InP QDs. The BRCA2, CYP1A1, CYP1B1, CDK1, SFN and VEGFA genes were observed to be upregulated specifically from increased CdSe exposure and suggests their possible utility as biomarkers for toxicity. Conclusions This study can

Differential Gene Expression and Aging

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Laurent Seroude

2002-01-01

Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

A deep auto-encoder model for gene expression prediction.

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Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

2017-11-17

Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

Polycistronic gene expression in Aspergillus niger.

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Schuetze, Tabea; Meyer, Vera

2017-09-25

Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

Gene expression and adaptive noncoding changes during human evolution.

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Babbitt, Courtney C; Haygood, Ralph; Nielsen, William J; Wray, Gregory A

2017-06-05

Despite evidence for adaptive changes in both gene expression and non-protein-coding, putatively regulatory regions of the genome during human evolution, the relationship between gene expression and adaptive changes in cis-regulatory regions remains unclear. Here we present new measurements of gene expression in five tissues of humans and chimpanzees, and use them to assess this relationship. We then compare our results with previous studies of adaptive noncoding changes, analyzing correlations at the level of gene ontology groups, in order to gain statistical power to detect correlations. Consistent with previous studies, we find little correlation between gene expression and adaptive noncoding changes at the level of individual genes; however, we do find significant correlations at the level of biological function ontology groups. The types of function include processes regulated by specific transcription factors, responses to genetic or chemical perturbations, and differentiation of cell types within the immune system. Among functional categories co-enriched with both differential expression and noncoding adaptation, prominent themes include cancer, particularly epithelial cancers, and neural development and function.

Over-expression of Eph and ephrin genes in advanced ovarian cancer: ephrin gene expression correlates with shortened survival

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Lincoln Douglas

2006-06-01

Full Text Available Abstract Background Increased expression of Eph receptor tyrosine kinases and their ephrin ligands has been implicated in tumor progression in a number of malignancies. This report describes aberrant expression of these genes in ovarian cancer, the commonest cause of death amongst gynaecological malignancies. Methods Eph and ephrin expression was determined using quantitative real time RT-PCR. Correlation of gene expression was measured using Spearman's rho statistic. Survival was analysed using log-rank analysis and (was visualised by Kaplan-Meier survival curves. Results Greater than 10 fold over-expression of EphA1 and a more modest over-expression of EphA2 were observed in partially overlapping subsets of tumors. Over-expression of EphA1 strongly correlated (r = 0.801; p Conclusion These data imply that increased levels of ephrins A1 and A5 in the presence of high expression of Ephs A1 and A2 lead to a more aggressive tumor phenotype. The known functions of Eph/ephrin signalling in cell de-adhesion and movement may explain the observed correlation of ephrin expression with poor prognosis.

Prediction of highly expressed genes in microbes based on chromatin accessibility

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Willenbrock, Hanni; Ussery, David

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...

A pipeline to determine RT-QPCR control genes for evolutionary studies: application to primate gene expression across multiple tissues.

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Olivier Fedrigo

Full Text Available Because many species-specific phenotypic differences are assumed to be caused by differential regulation of gene expression, many recent investigations have focused on measuring transcript abundance. Despite the availability of high-throughput platforms, quantitative real-time polymerase chain reaction (RT-QPCR is often the method of choice because of its low cost and wider dynamic range. However, the accuracy of this technique heavily relies on the use of multiple valid control genes for normalization. We created a pipeline for choosing genes potentially useful as RT-QPCR control genes for measuring expression between human and chimpanzee samples across multiple tissues, using published microarrays and a measure of tissue-specificity. We identified 13 genes from the pipeline and from commonly used control genes: ACTB, USP49, ARGHGEF2, GSK3A, TBP, SDHA, EIF2B2, GPDH, YWHAZ, HPTR1, RPL13A, HMBS, and EEF2. We then tested these candidate genes and validated their expression stability across species. We established the rank order of the most preferable set of genes for single and combined tissues. Our results suggest that for at least three tissues (cerebral cortex, liver, and skeletal muscle, EIF2B2, EEF2, HMBS, and SDHA are useful genes for normalizing human and chimpanzee expression using RT-QPCR. Interestingly, other commonly used control genes, including TBP, GAPDH, and, especially ACTB do not perform as well. This pipeline could be easily adapted to other species for which expression data exist, providing taxonomically appropriate control genes for comparisons of gene expression among species.

Gene and protein expression of epidermal growth factor measured on the kidney 24 hours after irradiation correlates to late radiation damage

International Nuclear Information System (INIS)

Otsuka, Makoto; Hatakenaka, Masamitsu

2001-01-01

This study was designed to evaluate the proliferative response of epidermal growth factor (EGF) gene expression as an early indicator of late renal radiation damage. EGF gene expression was measured in the irradiated left kidney of C3H/HeSlc mice using RT-PCR 24 hours after radiation doses of 9, 12, or 15 Gy. In a second experiment, the same radiation doses were administered to the right kidney plus the lower half of the left kidney. The partly irradiated left kidneys were harvested and EGF gene expression was measured. The irradiated whole right kidneys were subjected to immunohistochemical staining for EGF protein. In a third experiment, 12 Gy was administered to the right kidney plus the lower half of the left kidney. The mice underwent left nephrectomy 24 hours after radiation, and the EGF gene expression in the kidney was correlated with the blood urea nitrogen (BUN) level representing late renal functional damage. EGF expression increased in 1 of 10 control mice and in 9 of 10 mice that received 15 Gy. The extent of increase of EGF was dependent on radiation dose. In mice having an increased BUN level after irradiation, 7 of 10 had EGF positive irradiated kidneys. All six mice whose BUN levels were unchanged had EGF-negative irradiated kidneys. EGF protein staining was observed in tubule cells only, not in glomerular cells. The amount of EGF protein staining correlated with radiation dose to some extent. EGF gene expression seems to be a very early indicator of late radiation damage to the kidney. (author)

Gene Expression Profiling in Fish Toxicology: A Review.

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Kumar, Girish; Denslow, Nancy D

In this review, we present an overview of transcriptomic responses to chemical exposures in a variety of fish species. We have discussed the use of several molecular approaches such as northern blotting, differential display reverse transcription-polymerase chain reaction (DDRT-PCR), suppression subtractive hybridization (SSH), real time quantitative PCR (RT-qPCR), microarrays, and next-generation sequencing (NGS) for measuring gene expression. These techniques have been mainly used to measure the toxic effects of single compounds or simple mixtures in laboratory conditions. In addition, only few studies have been conducted to examine the biological significance of differentially expressed gene sets following chemical exposure. Therefore, future studies should focus more under field conditions using a multidisciplinary approach (genomics, proteomics and metabolomics) to understand the synergetic effects of multiple environmental stressors and to determine the functional significance of differentially expressed genes. Nevertheless, recent developments in NGS technologies and decreasing costs of sequencing holds the promise to uncover the complexity of anthropogenic impacts and biological effects in wild fish populations.

A multiplex branched DNA assay for parallel quantitative gene expression profiling.

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Flagella, Michael; Bui, Son; Zheng, Zhi; Nguyen, Cung Tuong; Zhang, Aiguo; Pastor, Larry; Ma, Yunqing; Yang, Wen; Crawford, Kimberly L; McMaster, Gary K; Witney, Frank; Luo, Yuling

2006-05-01

We describe a novel method to quantitatively measure messenger RNA (mRNA) expression of multiple genes directly from crude cell lysates and tissue homogenates without the need for RNA purification or target amplification. The multiplex branched DNA (bDNA) assay adapts the bDNA technology to the Luminex fluorescent bead-based platform through the use of cooperative hybridization, which ensures an exceptionally high degree of assay specificity. Using in vitro transcribed RNA as reference standards, we demonstrated that the assay is highly specific, with cross-reactivity less than 0.2%. We also determined that the assay detection sensitivity is 25,000 RNA transcripts with intra- and interplate coefficients of variance of less than 10% and less than 15%, respectively. Using three 10-gene panels designed to measure proinflammatory and apoptosis responses, we demonstrated sensitive and specific multiplex gene expression profiling directly from cell lysates. The gene expression change data demonstrate a high correlation coefficient (R(2)=0.94) compared with measurements obtained using the single-plex bDNA assay. Thus, the multiplex bDNA assay provides a powerful means to quantify the gene expression profile of a defined set of target genes in large sample populations.

Construction and use of gene expression covariation matrix

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Bellis Michel

2009-07-01

Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements

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Elaswarapu Ramnath

2010-11-01

Full Text Available Abstract Background Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC, are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC processes as transcriptomic profiling becomes more commonplace in the clinical setting. Results Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms. Conclusions ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance

Confidence in Phase Definition for Periodicity in Genes Expression Time Series.

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El Anbari, Mohammed; Fadda, Abeer; Ptitsyn, Andrey

2015-01-01

Circadian oscillation in baseline gene expression plays an important role in the regulation of multiple cellular processes. Most of the knowledge of circadian gene expression is based on studies measuring gene expression over time. Our ability to dissect molecular events in time is determined by the sampling frequency of such experiments. However, the real peaks of gene activity can be at any time on or between the time points at which samples are collected. Thus, some genes with a peak activity near the observation point have their phase of oscillation detected with better precision then those which peak between observation time points. Separating genes for which we can confidently identify peak activity from ambiguous genes can improve the analysis of time series gene expression. In this study we propose a new statistical method to quantify the phase confidence of circadian genes. The numerical performance of the proposed method has been tested using three real gene expression data sets.

PRAME Gene Expression in Acute Leukemia and Its Clinical Significance

International Nuclear Information System (INIS)

Ding, Kai; Wang, Xiao-ming; Fu, Rong; Ruan, Er-bao; Liu, Hui; Shao, Zong-hong

2012-01-01

To investigate the expression of the preferentially expressed antigen of melanoma (PRAME) gene in acute leukemia and its clinical significance. The level of expressed PRAME mRNA in bone marrow mononuclear cells from 34 patients with acute leukemia (AL) and in 12 bone marrow samples from healthy volunteers was measured via RT-PCR. Correlation analyses between PRAME gene expression and the clinical characteristics (gender, age, white blood count, immunophenotype of leukemia, percentage of blast cells, and karyotype) of the patients were performed. The PRAME gene was expressed in 38.2% of all 34 patients, in 40.7% of the patients with acute myelogenous leukemia (AML, n=27), and in 28.6% of the patients with acute lymphoblastic leukemia (ALL, n=7), but was not expressed in the healthy volunteers. The difference in the expression levels between AML and ALL patients was statistically significant. The rate of gene expression was 80% in M 3 , 33.3% in M 2 , and 28.6% in M 5 . Gene expression was also found to be correlated with CD15 and CD33 expression and abnormal karyotype, but not with age, gender, white blood count or percentage of blast cells. The PRAME gene is highly expressed in acute leukemia and could be a useful marker to monitor minimal residual disease. This gene is also a candidate target for the immunotherapy of acute leukemia

Gene expression inference with deep learning.

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Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-06-15

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

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Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Scaling of gene expression data allowing the comparison of different gene expression platforms

NARCIS (Netherlands)

van Ruissen, Fred; Schaaf, Gerben J.; Kool, Marcel; Baas, Frank; Ruijter, Jan M.

2008-01-01

Serial analysis of gene expression (SAGE) and microarrays have found a widespread application, but much ambiguity exists regarding the amalgamation of the data resulting from these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce

cis sequence effects on gene expression

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Jacobs Kevin

2007-08-01

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

Variation in gene expression within clones of the earthworm Dendrobaena octaedra.

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Marina Mustonen

Full Text Available Gene expression is highly plastic, which can help organisms to both acclimate and adapt to changing environments. Possible variation in gene expression among individuals with the same genotype (among clones is not widely considered, even though it could impact the results of studies that focus on gene expression phenotypes, for example studies using clonal lines. We examined the extent of within and between clone variation in gene expression in the earthworm Dendrobaena octaedra, which reproduces through apomictic parthenogenesis. Five microsatellite markers were developed and used to confirm that offspring are genetic clones of their parent. After that, expression of 12 genes was measured from five individuals each from six clonal lines after exposure to copper contaminated soil. Variation in gene expression was higher over all genotypes than within genotypes, as initially assumed. A subset of the genes was also examined in the offspring of exposed individuals in two of the clonal lines. In this case, variation in gene expression within genotypes was as high as that observed over all genotypes. One gene in particular (chymotrypsin inhibitor also showed significant differences in the expression levels among genetically identical individuals. Gene expression can vary considerably, and the extent of variation may depend on the genotypes and genes studied. Ensuring a large sample, with many different genotypes, is critical in studies comparing gene expression phenotypes. Researchers should be especially cautious inferring gene expression phenotypes when using only a single clonal or inbred line, since the results might be specific to only certain genotypes.

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

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Paules Richard S

2007-11-01

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

Epigenetic regulation on the gene expression signature in esophagus adenocarcinoma.

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Xi, Ting; Zhang, Guizhi

2017-02-01

Understanding the molecular mechanisms represents an important step in the development of diagnostic and therapeutic measures of esophagus adenocarcinoma (NOS). The objective of this study is to identify the epigenetic regulation on gene expression in NOS, shedding light on the molecular mechanisms of NOS. In this study, 78 patients with NOS were included and the data of mRNA, miRNA and DNA methylation of were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis between NOS and controls was performed in terms of gene expression, miRNA expression, and DNA methylation. Bioinformatic analysis was followed to explore the regulation mechanisms of miRNA and DNA methylationon gene expression. Totally, up to 1320 differentially expressed genes (DEGs) and 32 differentially expressed miRNAs were identified. 240 DEGs that were not only the target genes but also negatively correlated with the screened differentially expressed miRNAs. 101 DEGs were found to be highlymethylated in CpG islands. Then, 8 differentially methylated genes (DMGs) were selected, which showed down-regulated expression in NOS. Among of these genes, 6 genes including ADHFE1, DPP6, GRIA4, CNKSR2, RPS6KA6 and ZNF135 were target genes of differentially expressed miRNAs (hsa-mir-335, hsa-mir-18a, hsa-mir-93, hsa-mir-106b and hsa-mir-21). The identified altered miRNA, genes and DNA methylation site may be applied as biomarkers for diagnosis and prognosis of NOS. Copyright © 2016 Elsevier GmbH. All rights reserved.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

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Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

Science.gov (United States)

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

Modulation of gene expression made easy

DEFF Research Database (Denmark)

Solem, Christian; Jensen, Peter Ruhdal

2002-01-01

A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

VESPUCCI: exploring patterns of gene expression in grapevine

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Marco eMoretto

2016-05-01

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

Towards precise classification of cancers based on robust gene functional expression profiles

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Zhu Jing

2005-03-01

Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge

A longitudinal study of gene expression in healthy individuals

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Tessier Michel

2009-06-01

Full Text Available Abstract Background The use of gene expression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of gene expression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22–55 years and > 55 years and gender. Methods Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR, as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays. Results Gene expression levels as assessed by qRT-PCR and microarray were relatively stable over time with ~2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressed genes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF, 95% of all samples profiled fell within 1.5–2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray gene expression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers. Conclusion This study defines the range and variability of gene expression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal gene expression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated

ACE-it: a tool for genome-wide integration of gene dosage and RNA expression data

NARCIS (Netherlands)

van Wieringen, W.N.; Belien, J.A.M.; Vosse, S.; Achame, E.M.; Ylstra, B.

2006-01-01

Summary: We describe a tool, called ACE-it (Array CGH Expression integration tool). ACE-it links the chromosomal position of the gene dosage measured by array CGH to the genes measured by the expression array. ACE-it uses this link to statistically test whether gene dosage affects RNA expression. ©

Measurement of Gene Expression in Archival Paraffin-Embedded Tissues

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Cronin, Maureen; Pho, Mylan; Dutta, Debjani; Stephans, James C.; Shak, Steven; Kiefer, Michael C.; Esteban, Jose M.; Baker, Joffre B.

2004-01-01

Throughout the last decade many laboratories have shown that mRNA levels in formalin-fixed and paraffin-embedded (FPE) tissue specimens can be quantified by reverse transcriptase-polymerase chain reaction (RT-PCR) techniques despite the extensive RNA fragmentation that occurs in tissues so preserved. We have developed RT-PCR methods that are sensitive, precise, and that have multianalyte capability for potential wide use in clinical research and diagnostic assays. Here it is shown that the extent of fragmentation of extracted FPE tissue RNA significantly increases with archive storage time. Probe and primer sets for RT-PCR assays based on amplicons that are both short and homogeneous in length enable effective reference gene-based data normalization for cross comparison of specimens that differ substantially in age. A 48-gene assay used to compare gene expression profiles from the same breast cancer tissue that had been either frozen or FPE showed very similar profiles after reference gene-based normalization. A 92-gene assay, using RNA extracted from three 10-μm FPE sections of archival breast cancer specimens (dating from 1985 to 2001) yielded analyzable data for these genes in all 62 tested specimens. The results were substantially concordant when estrogen receptor, progesterone receptor, and HER2 receptor status determined by RT-PCR was compared with immunohistochemistry assays for these receptors. Furthermore, the results highlight the advantages of RT-PCR over immunohistochemistry with respect to quantitation and dynamic range. These findings support the development of RT-PCR analysis of FPE tissue RNA as a platform for multianalyte clinical diagnostic tests. PMID:14695316

Circadian expression of clock genes and clock-controlled genes in the rat retina

NARCIS (Netherlands)

Kamphuis, Willem; Cailotto, Cathy; Dijk, Frederike; Bergen, Arthur; Buijs, Ruud M.

2005-01-01

The circadian expression patterns of genes encoding for proteins that make up the core of the circadian clock were measured in rat retina using real-time quantitative PCR (qPCR). Transcript levels of several genes previously used for normalization of qPCR assays were determined and the effect of

Profile of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium determined through serial analysis of gene expression (SAGE)

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Sharon, Dror; Blackshaw, Seth; Cepko, Constance L.; Dryja, Thaddeus P.

2002-01-01

We used the serial analysis of gene expression (SAGE) technique to catalogue and measure the relative levels of expression of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium (RPE) from one or both of two humans, aged 88 and 44 years. The cone photoreceptor contribution to all transcription in the retina was found to be similar in the macula versus the retinal periphery, whereas the rod contribution was greater in the periphery versus the macula. Genes encoding structural proteins for axons were found to be expressed at higher levels in the macula versus the retinal periphery, probably reflecting the large proportion of ganglion cells in the central retina. In comparison with the younger eye, the peripheral retina of the older eye had a substantially higher proportion of mRNAs from genes encoding proteins involved in iron metabolism or protection against oxidative damage and a substantially lower proportion of mRNAs from genes encoding proteins involved in rod phototransduction. These differences may reflect the difference in age between the two donors or merely interindividual variation. The RPE library had numerous previously unencountered tags, suggesting that this cell type has a large, idiosyncratic repertoire of expressed genes. Comparison of these libraries with 100 reported nonocular SAGE libraries revealed 89 retina-specific or enriched genes expressed at substantial levels, of which 14 are known to cause a retinal disease and 53 are RPE-specific genes. We expect that these libraries will serve as a resource for understanding the relative expression levels of genes in the retina and the RPE and for identifying additional disease genes. PMID:11756676

Using gene expression noise to understand gene regulation

NARCIS (Netherlands)

Munsky, B.; Neuert, G.; van Oudenaarden, A.

2012-01-01

Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a

Equivalent Gene Expression Profiles between Glatopa™ and Copaxone®.

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Josephine S D'Alessandro

Full Text Available Glatopa™ is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Gene expression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone®. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate--responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student's t-test and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering statistical analyses were utilized to look for differences in gene expression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; gene expression profiles induced by Copaxone and Glatopa were not significantly different; and gene expression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent gene expression profiles between Copaxone and Glatopa.

Time-Delay Effects on Constitutive Gene Expression*

International Nuclear Information System (INIS)

Feng Yan-Ling; Wang Dan; Tang Xu-Lei; Dong Jian-Min

2017-01-01

The dynamics of constitutive gene expression with delayed mRNA degradation is investigated, where the intrinsic noise caused by the small number of reactant molecules is introduced. It is found that the oscillatory behavior claimed in previous investigations does not appear in the approximation of small time delay, and the steady state distribution still follows the Poisson law. Furthermore, we introduce the extrinsic noise induced by surrounding environment to explore the effects of this noise and time delay on the Fano factor. Based on a delay Langevin equation and the corresponding Fokker–Planck equation, the distribution of mRNA copy-number is achieved analytically. The time delay and extrinsic noise play similar roles in the gene expression system, that is, they are able to result in the deviation of the Fano factor from 1 evidently. The measured Fano factor for constitutive gene expression is slightly larger than 1, which is perhaps attributed to the time-delay effect. (paper)

Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.

Science.gov (United States)

Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J

2013-01-01

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.

Characterization of differentially expressed genes using high-dimensional co-expression networks

DEFF Research Database (Denmark)

Coelho Goncalves de Abreu, Gabriel; Labouriau, Rodrigo S.

2010-01-01

We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput gene expression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressed genes. It is argued that differentially expressed genes located in highly interconnected regions of the co-expression network are less informative than...

Regulation of eucaryotic gene expression

Energy Technology Data Exchange (ETDEWEB)

Brent, R.; Ptashne, M.S

1989-05-23

This patent describes a method of regulating the expression of a gene in a eucaryotic cell. The method consists of: providing in the eucaryotic cell, a peptide, derived from or substantially similar to a peptide of a procaryotic cell able to bind to DNA upstream from or within the gene, the amount of the peptide being sufficient to bind to the gene and thereby control expression of the gene.

Viral promoters can initiate expression of toxin genes introduced into Escherichia coli

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Jacob Daniela

2005-06-01

Full Text Available Abstract Background The expression of recombinant proteins in eukaryotic cells requires the fusion of the coding region to a promoter functional in the eukaryotic cell line. Viral promoters are very often used for this purpose. The preceding cloning procedures are usually performed in Escherichia coli and it is therefore of interest if the foreign promoter results in an expression of the gene in bacteria. In the case molecules toxic for humans are to be expressed, this knowledge is indispensable for the specification of safety measures. Results We selected five frequently used viral promoters and quantified their activity in E. coli with a reporter system. Only the promoter from the thymidine kinase gene from HSV1 showed no activity, while the polyhedrin promoter from baculovirus, the early immediate CMV promoter, the early SV40 promoter and the 5' LTR promoter from HIV-1 directed gene expression in E. coli. The determination of transcription start sites in the immediate early CMV promoter and the polyhedrin promoter confirmed the existence of bacterial -10 and -35 consensus sequences. The importance of this heterologous gene expression for safety considerations was further supported by analysing fusions between the aforementioned promoters and a promoter-less cytotoxin gene. Conclusion According to our results a high percentage of viral promoters have the ability of initiating gene expression in E. coli. The degree of such heterologous gene expression can be sufficient for the expression of toxin genes and must therefore be considered when defining safety measures for the handling of corresponding genetically modified organisms.

Gene expression of the endolymphatic sac

DEFF Research Database (Denmark)

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

2011-01-01

that the endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology...

Radiation-modulated gene expression in C. elegans

International Nuclear Information System (INIS)

Nelson, G.A.; Bayeta, E.; Perez, C.; Lloyd, E.; Jones, T.; Smith, A.; Tian, J.

2003-01-01

Full text: We use the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation with emphasis effects of charged particle radiation and have described the fluence vs. response relationships for mutation, chromosome aberration and certain developmental errors. These endpoints quantify the biological after repair and compensation pathways have completed their work. In order to address the control of these reactions we have turned to gene expression profiling to identify genes that uniquely respond to high LET species or respond differentially as a function of radiation properties. We have employed whole genome microarray methods to map gene expression following exposure to gamma rays, protons and accelerated iron ions. We found that 599 of 17871 genes analyzed showed differential expression 3 hrs after exposure to 3 Gy of at least one radiation types. 193 were up-regulated, 406 were down-regulated, and 90% were affected by only one species of radiation. Genes whose transcription levels responded significantly mapped to definite statistical clusters that were unique for each radiation type. We are now trying to establish the functional relationships of the genes their relevance to mitigation of radiation-induced damage. Three approaches are being used. First, bioinformatics tools are being used to determine the roles of genes in co-regulated gene sets. Second, we are applying the technique of RNA interference to determine whether our radiation-induced genes affect cell survival (measured in terms of embryo survival) and chromosome aberration (intestinal anaphase bridges). Finally we are focussing on the response of the most strongly-regulated gene in our data set. This is the autosomal gene, F36D3.9, whose predicted structure is that of a cysteine protease resembling cathepsin B. An enzymological approach is being used to characterize this gene at the protein level. This work was supported by NASA Cooperative Agreement NCC9-149

Multi-targeted priming for genome-wide gene expression assays

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Adomas Aleksandra B

2010-08-01

Full Text Available Abstract Background Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of Saccharomyces cerevisiae and of Neurospora crassa, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays. Results We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of Saccharomyces cerevisiae and Neurospora crassa while avoiding priming ribosomal RNA or transfer RNA. Examining the response of Saccharomyces cerevisiae to nitrogen deficiency and profiling Neurospora crassa early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression. Conclusions Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and N. crassa early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and

Development of Gene Expression Signatures for Practical Radiation Biodosimetry

International Nuclear Information System (INIS)

Paul, Sunirmal; Amundson, Sally A.

2008-01-01

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

Comparative gene expression of intestinal metabolizing enzymes.

Science.gov (United States)

Shin, Ho-Chul; Kim, Hye-Ryoung; Cho, Hee-Jung; Yi, Hee; Cho, Soo-Min; Lee, Dong-Goo; Abd El-Aty, A M; Kim, Jin-Suk; Sun, Duxin; Amidon, Gordon L

2009-11-01

The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant gene expressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal gene expression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs.

In situ gene expression and ecophysiology of thermophilic Cyanobacteria

DEFF Research Database (Denmark)

Jensen, Sheila Ingemann

-378), the expression patterns of various functional genes (with an emphasis on nif genes involved in N2-fixation), the protein levels of nitrogenase (NifH), the N2-fixation activity, as well as microsensor based measurements on O2 availability, production and consumption were investigated in situ over the entire diel...... cycle. Interestingly, it was found that while the nif genes are expressed, and nitrogenase is synthesized once the mat gets anoxic in the early evening, the largest N2-fixation activity occurs as a burst during dim light in the early morning, albeit protein levels remained high over the entire course...

Inferring gene expression dynamics via functional regression analysis

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Leng Xiaoyan

2008-01-01

Full Text Available Abstract Background Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary gene expression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, gene expression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal gene expression profiles. Conclusion Our findings point to specific reactivation patterns of gene expression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating gene expression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

Synthetic promoter libraries- tuning of gene expression

DEFF Research Database (Denmark)

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

2006-01-01

knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...

Evolutionary constraints shape caste-specific gene expression across 15 ant species.

Science.gov (United States)

Morandin, Claire; Mikheyev, Alexander S; Pedersen, Jes Søe; Helanterä, Heikki

2017-05-01

Development of polymorphic phenotypes from similar genomes requires gene expression differences. However, little is known about how morph-specific gene expression patterns vary on a broad phylogenetic scale. We hypothesize that evolution of morph-specific gene expression, and consequently morph-specific phenotypic evolution, may be constrained by gene essentiality and the amount of pleiotropic constraints. Here, we use comparative transcriptomics of queen and worker morphs, that is, castes, from 15 ant species to understand the constraints of morph-biased gene expression. In particular, we investigate how measures of evolutionary constraints at the sequence level (expression level, connectivity, and number of gene ontology [GO] terms) correlate with morph-biased expression. Our results show that genes indeed vary in their potential to become morph-biased. The existence of genes that are constrained in becoming caste-biased potentially limits the evolutionary decoupling of the caste phenotypes, that is, it might result in "caste load" occasioning from antagonistic fitness variation, similarly to sexually antagonistic fitness variation between males and females. On the other hand, we suggest that genes under low constraints are released from antagonistic variation and thus more likely to be co-opted for morph specific use. Overall, our results suggest that the factors that affect sequence evolutionary rates and evolution of plastic expression may largely overlap. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Prediction of highly expressed genes in microbes based on chromatin accessibility

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Ussery David W

2007-02-01

Full Text Available Abstract 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.

Cis-regulatory somatic mutations and gene-expression alteration in B-cell lymphomas.

Science.gov (United States)

Mathelier, Anthony; Lefebvre, Calvin; Zhang, Allen W; Arenillas, David J; Ding, Jiarui; Wasserman, Wyeth W; Shah, Sohrab P

2015-04-23

With the rapid increase of whole-genome sequencing of human cancers, an important opportunity to analyze and characterize somatic mutations lying within cis-regulatory regions has emerged. A focus on protein-coding regions to identify nonsense or missense mutations disruptive to protein structure and/or function has led to important insights; however, the impact on gene expression of mutations lying within cis-regulatory regions remains under-explored. We analyzed somatic mutations from 84 matched tumor-normal whole genomes from B-cell lymphomas with accompanying gene expression measurements to elucidate the extent to which these cancers are disrupted by cis-regulatory mutations. We characterize mutations overlapping a high quality set of well-annotated transcription factor binding sites (TFBSs), covering a similar portion of the genome as protein-coding exons. Our results indicate that cis-regulatory mutations overlapping predicted TFBSs are enriched in promoter regions of genes involved in apoptosis or growth/proliferation. By integrating gene expression data with mutation data, our computational approach culminates with identification of cis-regulatory mutations most likely to participate in dysregulation of the gene expression program. The impact can be measured along with protein-coding mutations to highlight key mutations disrupting gene expression and pathways in cancer. Our study yields specific genes with disrupted expression triggered by genomic mutations in either the coding or the regulatory space. It implies that mutated regulatory components of the genome contribute substantially to cancer pathways. Our analyses demonstrate that identifying genomically altered cis-regulatory elements coupled with analysis of gene expression data will augment biological interpretation of mutational landscapes of cancers.

Biasogram: visualization of confounding technical bias in gene expression data

DEFF Research Database (Denmark)

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

2013-01-01

Gene expression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factors...... such as RNA quality and array hybridization conditions. If such technical bias is correlated with the clinical variable of interest, the likelihood of identifying false positive genes is increased. Here we describe a method to visualize an expression matrix as a projection of all genes onto a plane defined...... by a clinical variable and a technical nuisance variable. The resulting plot indicates the extent to which each gene is correlated with the clinical variable or the technical variable. We demonstrate this method by applying it to three clinical trial microarray data sets, one of which identified genes that may...

Molecular subsets in the gene expression signatures of scleroderma skin.

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Ausra Milano

2008-07-01

Full Text Available Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc with diffuse scleroderma (dSSc, 7 patients with SSc with limited scleroderma (lSSc, 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001 and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud's phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc.Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrates multiple distinct gene expression programs in the skin of patients with scleroderma.

Adaptive Evolution of Gene Expression in Drosophila.

Science.gov (United States)

Nourmohammad, Armita; Rambeau, Joachim; Held, Torsten; Kovacova, Viera; Berg, Johannes; Lässig, Michael

2017-08-08

Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Adaptive Evolution of Gene Expression in Drosophila

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Armita Nourmohammad

2017-08-01

Full Text Available Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

Gene expression and 18FDG uptake in atherosclerotic carotid plaques

DEFF Research Database (Denmark)

Pedersen, Sune Folke; Graebe, Martin; Fisker Hag, Anne Mette

2010-01-01

) and an additional ipsilateral internal carotid artery stenosis of greater than 60% were recruited. FDG uptake in the carotids was determined by PET/computed tomography and expressed as mean and maximal standardized uptake values (SUVmean and SUVmax). The atherosclerotic plaques were subsequently recovered...... by carotid endarterectomy. The gene expression of markers of vulnerability - CD68, IL-18, matrix metalloproteinase 9, cathepsin K, GLUT-1, and hexokinase type II (HK2) - were measured in plaques by quantitative PCR. RESULTS: In a multivariate linear regression model, GLUT-1, CD68, cathepsin K, and HK2 gene...... expression remained in the final model as predictive variables of FDG accumulation calculated as SUVmean (R=0.26, PK, and HK2 gene expression as independent predictive variables of FDG accumulation calculated...

Multitarget Effects of Danqi Pill on Global Gene Expression Changes in Myocardial Ischemia

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Qiyan Wang

2018-01-01

Full Text Available Danqi pill (DQP is a widely prescribed traditional Chinese medicine (TCM in the treatment of cardiovascular diseases. The objective of this study is to systematically characterize altered gene expression pattern induced by myocardial ischemia (MI in a rat model and to investigate the effects of DQP on global gene expression. Global mRNA expression was measured. Differentially expressed genes among the sham group, model group, and DQP group were analyzed. The gene ontology enrichment analysis and pathway analysis of differentially expressed genes were carried out. We quantified 10,813 genes. Compared with the sham group, expressions of 339 genes were upregulated and 177 genes were downregulated in the model group. The upregulated genes were enriched in extracellular matrix organization, response to wounding, and defense response pathways. Downregulated genes were enriched in fatty acid metabolism, pyruvate metabolism, PPAR signaling pathways, and so forth. This indicated that energy metabolic disorders occurred in rats with MI. In the DQP group, expressions of genes in the altered pathways were regulated back towards normal levels. DQP reversed expression of 313 of the 516 differentially expressed genes in the model group. This study provides insight into the multitarget mechanism of TCM in the treatment of complex diseases.

Long-term Dietary Macronutrients and Hepatic Gene Expression in Aging Mice.

Science.gov (United States)

Gokarn, Rahul; Solon-Biet, Samantha M; Cogger, Victoria C; Cooney, Gregory J; Wahl, Devin; McMahon, Aisling C; Mitchell, James R; Mitchell, Sarah J; Hine, Christopher; de Cabo, Rafael; Raubenheimer, David; Simpson, Stephen J; Le Couteur, David G

2018-04-23

Nutrition influences both hepatic function and aging, but mechanisms are poorly understood. Here, the effects of lifelong, ad libitum-fed diets varying in macronutrients and energy on hepatic gene expression were studied. Gene expression was measured using Affymetrix mouse arrays in livers of 46 mice aged 15 months fed one of 25 diets varying in protein, carbohydrates, fat, and energy density from 3 weeks of age. Gene expression was almost entirely influenced by protein intake. Carbohydrate and fat intake had few effects on gene expression compared with protein. Pathways and processes associated with protein intake included those involved with mitochondrial function, metabolic signaling (PI3K-Akt, AMPK, mTOR) and metabolism of protein and amino acids. Protein intake had variable effects on genes associated with regulation of longevity and influenced by caloric restriction. Among the genes of interest with expression that were significantly associated with protein intake are Cth, Gls2, Igf1, and Nnmt, which were increased with higher protein intake, and Igf2bp2, Fgf21, Prkab2, and Mtor, which were increased with lower protein intake. Dietary protein has a powerful impact on hepatic gene expression in older mice, with some overlap with genes previously reported to be involved with regulation of longevity or caloric restriction.

Repetitive Imaging of Reporter Gene Expression in the Lung

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Jean-Christophe Richard

2003-10-01

Full Text Available Positron emission tomographic imaging is emerging as a powerful technology to monitor reporter transgene expression in the lungs and other organs. However, little information is available about its usefulness for studying gene expression over time. Therefore, we infected 20 rats with a replication-deficient adenovirus containing a fusion gene encoding for a mutant Herpes simplex virus type-1 thymidine kinase and an enhanced green fluorescent protein. Five additional rats were infected with a control virus. Pulmonary gene transfer was performed via intratracheal administration of vector using a surfactant-based method. Imaging was performed 4–6 hr, and 4, 7, and 10 days after gene transfer, using 9-(4-[18F]-fluoro-3-hydroxymethylbutylguanine, an imaging substrate for the mutant kinase. Lung tracer uptake assessed with imaging was moderately but significantly increased 4–6 hr after gene transfer, was maximal after 4 days, and was no longer detectable by 10 days. The temporal pattern of transgene expression measured ex vivo with in vitro assays of thymidine kinase activity and green fluorescent protein was similar to imaging. In conclusion, positron emission tomography is a reliable new tool to evaluate the onset and duration of reporter gene expression noninvasively in the lungs of intact animals.

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

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María Ballester

Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

Transient expression of β-glucuronidase gene in indica and ...

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co-transfer of DNAs to cells was monitored by analyzing transient gus expression 24 h after .... induction frequency was determined by measuring the ... Effect of age on transient expression of gus gene and production of hygromycin .... japonica varieties via electric discharge particle acceleration of .... yellow stem borer.

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

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Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue

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Usadel Björn

2007-05-01

Full Text Available Abstract Background Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, faithful visualization methods are beneficial for revealing interesting gene expression patterns and functional relationships of coexpressed genes. Such screening helps to gain deeper insights into regulatory behavior and cellular responses, as will be discussed for expression data of developing barley endosperm tissue. For that purpose, high-throughput multidimensional scaling (HiT-MDS, a recent method for similarity-preserving data embedding, is substantially refined and used for (a assessing the quality and reliability of centroid gene expression patterns, and for (b derivation of functional relationships of coexpressed genes of endosperm tissue during barley grain development (0–26 days after flowering. Results Temporal expression profiles of 4824 genes at 14 time points are faithfully embedded into two-dimensional displays. Thereby, similar shapes of coexpressed genes get closely grouped by a correlation-based similarity measure. As a main result, by using power transformation of correlation terms, a characteristic cloud of points with bipolar sandglass shape is obtained that is inherently connected to expression patterns of pre-storage, intermediate and storage phase of endosperm development. Conclusion The new HiT-MDS-2 method helps to create global views of expression patterns and to validate centroids obtained from clustering programs. Furthermore, functional gene annotation for developing endosperm barley tissue is successfully mapped to the visualization, making easy localization of major centroids of enriched functional categories possible.

Muscle gene expression patterns in human rotator cuff pathology.

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Choo, Alexander; McCarthy, Meagan; Pichika, Rajeswari; Sato, Eugene J; Lieber, Richard L; Schenk, Simon; Lane, John G; Ward, Samuel R

2014-09-17

Rotator cuff pathology is a common source of shoulder pain with variable etiology and pathoanatomical characteristics. Pathological processes of fatty infiltration, muscle atrophy, and fibrosis have all been invoked as causes for poor outcomes after rotator cuff tear repair. The aims of this study were to measure the expression of key genes associated with adipogenesis, myogenesis, and fibrosis in human rotator cuff muscle after injury and to compare the expression among groups of patients with varied severities of rotator cuff pathology. Biopsies of the supraspinatus muscle were obtained arthroscopically from twenty-seven patients in the following operative groups: bursitis (n = 10), tendinopathy (n = 7), full-thickness rotator cuff tear (n = 8), and massive rotator cuff tear (n = 2). Quantitative polymerase chain reaction (qPCR) was performed to characterize gene expression pathways involved in myogenesis, adipogenesis, and fibrosis. Patients with a massive tear demonstrated downregulation of the fibrogenic, adipogenic, and myogenic genes, indicating that the muscle was not in a state of active change and may have difficulty responding to stimuli. Patients with a full-thickness tear showed upregulation of fibrotic and adipogenic genes; at the tissue level, these correspond to the pathologies most detrimental to outcomes of surgical repair. Patients with bursitis or tendinopathy still expressed myogenic genes, indicating that the muscle may be attempting to accommodate the mechanical deficiencies induced by the tendon tear. Gene expression in human rotator cuff muscles varied according to tendon injury severity. Patients with bursitis and tendinopathy appeared to be expressing pro-myogenic genes, whereas patients with a full-thickness tear were expressing genes associated with fatty atrophy and fibrosis. In contrast, patients with a massive tear appeared to have downregulation of all gene programs except inhibition of myogenesis. These data highlight the

Creating and validating cis-regulatory maps of tissue-specific gene expression regulation

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O'Connor, Timothy R.; Bailey, Timothy L.

2014-01-01

Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

Impact of blood collection and processing on peripheral blood gene expression profiling in type 1 diabetes.

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Yip, Linda; Fuhlbrigge, Rebecca; Atkinson, Mark A; Fathman, C Garrison

2017-08-18

The natural history of type 1 diabetes (T1D) is challenging to investigate, especially as pre-diabetic individuals are difficult to identify. Numerous T1D consortia have been established to collect whole blood for gene expression analysis from individuals with or at risk to develop T1D. However, with no universally accepted protocol for their collection, differences in sample processing may lead to variances in the results. Here, we examined whether the choice of blood collection tube and RNA extraction kit leads to differences in the expression of genes that are changed during the progression of T1D, and if these differences could be minimized by measuring gene expression directly from the lysate of whole blood. Microarray analysis showed that the expression of 901 genes is highly influenced by sample processing using the PAXgene versus the Tempus system. These included a significant number of lymphocyte-specific genes and genes whose expression has been reported to differ in the peripheral blood of at-risk and T1D patients compared to controls. We showed that artificial changes in gene expression occur when control and T1D samples were processed differently. The sample processing-dependent differences in gene expression were largely due to loss of transcripts during the RNA extraction step using the PAXgene system. The majority of differences were not observed when gene expression was measured in whole blood lysates prepared from blood collected in PAXgene and Tempus tubes. We showed that the gene expression profile of samples processed using the Tempus system is more accurate than that of samples processed using the PAXgene system. Variation in sample processing can result in misleading changes in gene expression. However, these differences can be minimized by measuring gene expression directly in whole blood lysates.

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

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Gutiérrez Rodrigo A

2008-09-01

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

The functional landscape of mouse gene expression

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Zhang Wen

2004-12-01

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

Capturing heterogeneity in gene expression studies by surrogate variable analysis.

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Jeffrey T Leek

2007-09-01

Full Text Available It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on gene expression levels. In addition to the measured variable(s of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of gene expression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.

Expression of Sox genes in tooth development.

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Kawasaki, Katsushige; Kawasaki, Maiko; Watanabe, Momoko; Idrus, Erik; Nagai, Takahiro; Oommen, Shelly; Maeda, Takeyasu; Hagiwara, Nobuko; Que, Jianwen; Sharpe, Paul T; Ohazama, Atsushi

2015-01-01

Members of the Sox gene family play roles in many biological processes including organogenesis. We carried out comparative in situ hybridization analysis of seventeen sox genes (Sox1-14, 17, 18, 21) during murine odontogenesis from the epithelial thickening to the cytodifferentiation stages. Localized expression of five Sox genes (Sox6, 9, 13, 14 and 21) was observed in tooth bud epithelium. Sox13 showed restricted expression in the primary enamel knots. At the early bell stage, three Sox genes (Sox8, 11, 17 and 21) were expressed in pre-ameloblasts, whereas two others (Sox5 and 18) showed expression in odontoblasts. Sox genes thus showed a dynamic spatio-temporal expression during tooth development.

Cross-platform comparison of SYBR® Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC study

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Dial Stacey L

2008-07-01

Full Text Available Abstract Background The MicroArray Quality Control (MAQC project evaluated the inter- and intra-platform reproducibility of seven microarray platforms and three quantitative gene expression assays in profiling the expression of two commercially available Reference RNA samples (Nat Biotechnol 24:1115-22, 2006. The tested microarrays were the platforms from Affymetrix, Agilent Technologies, Applied Biosystems, GE Healthcare, Illumina, Eppendorf and the National Cancer Institute, and quantitative gene expression assays included TaqMan® Gene Expression PCR Assay, Standardized (Sta RT-PCR™ and QuantiGene®. The data showed great consistency in gene expression measurements across different microarray platforms, different technologies and test sites. However, SYBR® Green real-time PCR, another common technique utilized by half of all real-time PCR users for gene expression measurement, was not addressed in the MAQC study. In the present study, we compared the performance of SYBR Green PCR with TaqMan PCR, microarrays and other quantitative technologies using the same two Reference RNA samples as the MAQC project. We assessed SYBR Green real-time PCR using commercially available RT2 Profiler™ PCR Arrays from SuperArray, containing primer pairs that have been experimentally validated to ensure gene-specificity and high amplification efficiency. Results The SYBR Green PCR Arrays exhibit good reproducibility among different users, PCR instruments and test sites. In addition, the SYBR Green PCR Arrays have the highest concordance with TaqMan PCR, and a high level of concordance with other quantitative methods and microarrays that were evaluated in this study in terms of fold-change correlation and overlap of lists of differentially expressed genes. Conclusion These data demonstrate that SYBR Green real-time PCR delivers highly comparable results in gene expression measurement with TaqMan PCR and other high-density microarrays.

Over-expression of Gene FaASR Promotes Strawberry Fruit Coloring

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Liu Zhongjie

2015-11-01

Full Text Available Fruit development and ripening is a complicate process. Although much progress has been made on the ripenig process, the molecular mechamism of fruit development is not yet clear. In this study, we used ‘Sweet Charlie’ strawberry as test materials, based on cloning the strawberries ASR homologous gene, we carried out the bioinformatics and temporal expression analysis of FaASR, by manipulating ASR gene expression level in strawberry fruit, we tested the changes of physiological indicators, including sugar, ABA, pigments content, and fruit firmness, as well as phenotypic changes. In addition, we measured the expression changes of some anthocyanin-related gene, such as CHS and UFGT, by which we revealed the regulation mechanisms of ASR gene over strawberry fruit ripening. Strawberry ASR contained a typical domain of ABA/WDS that was related to fruit ripening and stress-resistance, and ASR gene over-expression could promote strawberry fruit coloring, endogenous ABA and sucrose accumulation, fruit softening, and induced the transcription levels of anthocyanin-related genes CHS and UFGT. The present study will further reveal the molecular mechanisms of information transmission in fruit development, and will also play an important foundation for future molecular improvement of strawberries breeding.

Profiling Gene Expression in Germinating Brassica Roots.

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Park, Myoung Ryoul; Wang, Yi-Hong; Hasenstein, Karl H

2014-01-01

Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressed genes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root-shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for gene expression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that gene expression studies that are based on the entire root miss important differences in gene expression that SPGE is able to resolve for example growth adjustments during gravitropism.

Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies.

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Lucie Kosinová

Full Text Available 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

Comprehensive analysis of gene expression patterns of hedgehog-related genes

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Baillie David

2006-10-01

Full Text Available Abstract Background The Caenorhabditis elegans genome encodes ten proteins that share sequence similarity with the Hedgehog signaling molecule through their C-terminal autoprocessing Hint/Hog domain. These proteins contain novel N-terminal domains, and C. elegans encodes dozens of additional proteins containing only these N-terminal domains. These gene families are called warthog, groundhog, ground-like and quahog, collectively called hedgehog (hh-related genes. Previously, the expression pattern of seventeen genes was examined, which showed that they are primarily expressed in the ectoderm. Results With the completion of the C. elegans genome sequence in November 2002, we reexamined and identified 61 hh-related ORFs. Further, we identified 49 hh-related ORFs in C. briggsae. ORF analysis revealed that 30% of the genes still had errors in their predictions and we improved these predictions here. We performed a comprehensive expression analysis using GFP fusions of the putative intergenic regulatory sequence with one or two transgenic lines for most genes. The hh-related genes are expressed in one or a few of the following tissues: hypodermis, seam cells, excretory duct and pore cells, vulval epithelial cells, rectal epithelial cells, pharyngeal muscle or marginal cells, arcade cells, support cells of sensory organs, and neuronal cells. Using time-lapse recordings, we discovered that some hh-related genes are expressed in a cyclical fashion in phase with molting during larval development. We also generated several translational GFP fusions, but they did not show any subcellular localization. In addition, we also studied the expression patterns of two genes with similarity to Drosophila frizzled, T23D8.1 and F27E11.3A, and the ortholog of the Drosophila gene dally-like, gpn-1, which is a heparan sulfate proteoglycan. The two frizzled homologs are expressed in a few neurons in the head, and gpn-1 is expressed in the pharynx. Finally, we compare the

EVALUATION OF THE PROGNOSTIC VALUE OF nm23 GENE EXPRESSION IN BREAST CANCER

Institute of Scientific and Technical Information of China (English)

刘红; 毛慧生; 傅西林; 方志沂; 冯玉梅; 范宇; 李树玲

2002-01-01

Objective: To investigate the expression of nm23 gene and evaluate its prognostic value in breast cancer. Methods: nm23 expressions were detected in 101 breast cancer patients (group 1) by immunohistochemistry. RT-PCR and immunohistochemistry were used to measure expressions of nm23 gene in another 68 patients with breast cancer (group 2). Results: nm23 gene expression in group 1 was inversely associated with distant metastasis and lymph node metastasis (P<0.05). In 44 patients with negative lymph node, 9 cases progressed to distant metastasis, 7 of them (77.8%) showed low expression of nm23 gene (P<0.05). In 57 patients with positive lymph node, 24 our of 29 patients who had no distant metastasis (82.8%) expressed nm23 gene at high level (P<0.05). Meanwhile, there were 6 patients with distant metastasis in the group 2, all of thenm expressed nm23 gene mRNA at low level. Conclusion: The results showed that nm23 gene might play an independent role in predicting prognosis of breast cancer.

Simple Comparative Analyses of Differentially Expressed Gene Lists May Overestimate Gene Overlap.

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Lawhorn, Chelsea M; Schomaker, Rachel; Rowell, Jonathan T; Rueppell, Olav

2018-04-16

Comparing the overlap between sets of differentially expressed genes (DEGs) within or between transcriptome studies is regularly used to infer similarities between biological processes. Significant overlap between two sets of DEGs is usually determined by a simple test. The number of potentially overlapping genes is compared to the number of genes that actually occur in both lists, treating every gene as equal. However, gene expression is controlled by transcription factors that bind to a variable number of transcription factor binding sites, leading to variation among genes in general variability of their expression. Neglecting this variability could therefore lead to inflated estimates of significant overlap between DEG lists. With computer simulations, we demonstrate that such biases arise from variation in the control of gene expression. Significant overlap commonly arises between two lists of DEGs that are randomly generated, assuming that the control of gene expression is variable among genes but consistent between corresponding experiments. More overlap is observed when transcription factors are specific to their binding sites and when the number of genes is considerably higher than the number of different transcription factors. In contrast, overlap between two DEG lists is always lower than expected when the genetic architecture of expression is independent between the two experiments. Thus, the current methods for determining significant overlap between DEGs are potentially confounding biologically meaningful overlap with overlap that arises due to variability in control of expression among genes, and more sophisticated approaches are needed.

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

2012-05-01

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

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy; Bachkirova, Elena; Rey, Michael

2013-10-01

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

Biofilm-Associated Gene Expression in Staphylococcus pseudintermedius on a Variety of Implant Materials.

Science.gov (United States)

Crawford, Evan C; Singh, Ameet; Gibson, Thomas W G; Scott Weese, J

2016-05-01

To evaluate the expression of biofilm-associated genes in Staphylococcus pseudintermedius on multiple clinically relevant surfaces. In vitro experimental study. Two strains of methicillin-resistant S. pseudintermedius isolated from clinical infections representing the most common international isolates. A quantitative polymerase chain reaction (qPCR) assay for expression of genes related to biofilm initial adhesion, formation/maturation, antimicrobial resistance, and intracellular communication was developed and validated. S. pseudintermedius biofilms were grown on 8 clinically relevant surfaces (polymethylmethacrylate, stainless steel, titanium, latex, silicone, polydioxanone, polystyrene, and glass) and samples of logarithmic and stationary growth phases were collected. Gene expression in samples was measured by qPCR. Significant differences in gene expression were identified between surfaces and between bacterial strains for most gene/strain/surface combinations studied. Expression of genes responsible for production of extracellular matrix were increased in biofilms. Expression of genes responsible for initial adhesion and intracellular communication was markedly variable. Antimicrobial resistance gene expression was increased on multiple surfaces, including stainless steel and titanium. A method for evaluation of expression of multiple biofilm-associated genes in S. pseudintermedius was successfully developed and applied to the study of biofilms on multiple surfaces. Variations in expression of these genes have a bearing on understanding the development and treatment of implant-associated biofilm infections and will inform future clinical research. © Copyright 2016 by The American College of Veterinary Surgeons.

Determinants of human adipose tissue gene expression

DEFF Research Database (Denmark)

Viguerie, Nathalie; Montastier, Emilie; Maoret, Jean-José

2012-01-01

weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

Adrenal-kidney-gonad complex measurements may not predict gonad-specific changes in gene expression patterns during temperature-dependent sex determination in the red-eared slider turtle (Trachemys scripta elegans).

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Ramsey, Mary; Crews, David

2007-08-01

Many turtles, including the red-eared slider turtle (Trachemys scripta elegans) have temperature-dependent sex determination in which gonadal sex is determined by temperature during the middle third of incubation. The gonad develops as part of a heterogenous tissue complex that comprises the developing adrenal, kidney, and gonad (AKG complex). Owing to the difficulty in excising the gonad from the adjacent tissues, the AKG complex is often used as tissue source in assays examining gene expression in the developing gonad. However, the gonad is a relatively small component of the AKG, and gene expression in the adrenal-kidney (AK) compartment may interfere with the detection of gonad-specific changes in gene expression, particularly during early key phases of gonadal development and sex determination. In this study, we examine transcript levels as measured by quantitative real-time polymerase chain reaction for five genes important in slider turtle sex determination and differentiation (AR, ERalpha, ERbeta, aromatase, and Sf1) in AKG, AK, and isolated gonad tissues. In all cases, gonad-specific gene expression patterns were attenuated in AKG versus gonad tissue. All five genes were expressed in the AK in addition to the gonad at all stages/temperatures. Inclusion of the AK compartment masked important changes in gonadal gene expression. In addition, AK and gonad expression patterns are not additive, and gonadal gene expression cannot be predicted from intact AKG measurements. (c) 2007 Wiley-Liss, Inc.

LINE FUSION GENES: a database of LINE expression in human genes

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Park Hong-Seog

2006-06-01

Full Text Available Abstract Background Long Interspersed Nuclear Elements (LINEs are the most abundant retrotransposons in humans. About 79% of human genes are estimated to contain at least one segment of LINE per transcription unit. Recent studies have shown that LINE elements can affect protein sequences, splicing patterns and expression of human genes. Description We have developed a database, LINE FUSION GENES, for elucidating LINE expression throughout the human gene database. We searched the 28,171 genes listed in the NCBI database for LINE elements and analyzed their structures and expression patterns. The results show that the mRNA sequences of 1,329 genes were affected by LINE expression. The LINE expression types were classified on the basis of LINEs in the 5' UTR, exon or 3' UTR sequences of the mRNAs. Our database provides further information, such as the tissue distribution and chromosomal location of the genes, and the domain structure that is changed by LINE integration. We have linked all the accession numbers to the NCBI data bank to provide mRNA sequences for subsequent users. Conclusion We believe that our work will interest genome scientists and might help them to gain insight into the implications of LINE expression for human evolution and disease. Availability http://www.primate.or.kr/line

Gene expression of manganese superoxide dismutase in human glioma cells

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Novi S. Hardiany

2010-02-01

Full Text Available Aim This study analyze the MnSOD gene expression as endogenous antioxidant in human glioma cells compared with leucocyte cells as control.Methods MnSOD gene expression of 20 glioma patients was analyzed by measuring the relative expression of mRNA and enzyme activity of MnSOD in brain and leucocyte cells. The relative expression of mRNA MnSOD was determined by using quantitative Real Time RT-PCR and the enzyme activity of MnSOD using biochemical kit assay (xantine oxidase inhibition. Statistic analysis for mRNA and enzyme activity of MnSOD was performed using Kruskal Wallis test.Results mRNA of MnSOD in glioma cells of 70% sample was 0.015–0.627 lower, 10% was 1.002-1.059 and 20% was 1.409-6.915 higher than in leucocyte cells. Also the specific activity of MnSOD enzyme in glioma cells of 80% sample showed 0,064-0,506 lower and 20% sample was 1.249-2.718 higher than in leucocyte cells.Conclusion MnSOD gene expression in human glioma cells are significantly lower than its expression in leucocytes cells. (Med J Indones 2010; 19:21-5Keywords : MnSOD, glioma, gene expression

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

KAUST Repository

Horiuchi, Youko

2015-12-23

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

Evaluating Transcription Factor Activity Changes by Scoring Unexplained Target Genes in Expression Data.

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Evi Berchtold

Full Text Available Several methods predict activity changes of transcription factors (TFs from a given regulatory network and measured expression data. But available gene regulatory networks are incomplete and contain many condition-dependent regulations that are not relevant for the specific expression measurement. It is not known which combination of active TFs is needed to cause a change in the expression of a target gene. A method to systematically evaluate the inferred activity changes is missing. We present such an evaluation strategy that indicates for how many target genes the observed expression changes can be explained by a given set of active TFs. To overcome the problem that the exact combination of active TFs needed to activate a gene is typically not known, we assume a gene to be explained if there exists any combination for which the predicted active TFs can possibly explain the observed change of the gene. We introduce the i-score (inconsistency score, which quantifies how many genes could not be explained by the set of activity changes of TFs. We observe that, even for these minimal requirements, published methods yield many unexplained target genes, i.e. large i-scores. This holds for all methods and all expression datasets we evaluated. We provide new optimization methods to calculate the best possible (minimal i-score given the network and measured expression data. The evaluation of this optimized i-score on a large data compendium yields many unexplained target genes for almost every case. This indicates that currently available regulatory networks are still far from being complete. Both the presented Act-SAT and Act-A* methods produce optimal sets of TF activity changes, which can be used to investigate the difficult interplay of expression and network data. A web server and a command line tool to calculate our i-score and to find the active TFs associated with the minimal i-score is available from https://services.bio.ifi.lmu.de/i-score.

Building gene co-expression networks using transcriptomics data for systems biology investigations

DEFF Research Database (Denmark)

Kadarmideen, Haja; Watson-Haigh, Nathan S.

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four......) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT...... (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended....

Hepatic gene expression profiling using GeneChips in zebrafish exposed to 17{alpha}-methyldihydrotestosterone

Energy Technology Data Exchange (ETDEWEB)

Hoffmann, J.L.; Thomason, R.G.; Lee, D.M.; Brill, J.L.; Price, B.B.; Carr, G.J. [Miami Valley Innovation Center, Procter and Gamble Company, P.O. Box 538707, Cincinnati, OH 45253-8707 (United States); Versteeg, D.J. [Miami Valley Innovation Center, Procter and Gamble Company, P.O. Box 538707, Cincinnati, OH 45253-8707 (United States)], E-mail: versteeg.dj@pg.com

2008-04-28

Concentration and time-dependent changes in hepatic gene expression were examined in adult, female zebrafish (Danio rerio) exposed to 0, 0.1, 0.7, 4.9 {mu}g/L of a model androgen, 17{alpha}-methyldihydrotestosterone (MDHT). At 24 and 168 h, fish were sacrificed and liver was extracted for gene expression analysis using custom Affymetrix GeneChip Zebrafish Genome Microarrays. In an effort to link gene expression changes to higher levels of biological organization, blood was collected for measurement of plasma steroid hormones (17{beta}-estradiol (E2), testosterone (T)) and vitellogenin (VTG) using ELISA. Body and ovary weight were also measured. A significant reduction in E2 occurred at 24 h (0.7 and 4.9 {mu}g/L) and 168 h (4.9 {mu}g/L) following MDHT exposure. In contrast, T was significantly increased at 24 h (4.9 {mu}g/L) and 168 h (0.1, 0.7, 4.9 {mu}g/L). 171 and 575 genes were significantly affected in a concentration-dependent manner at either 24 or 168 h by MDHT exposure at p {<=} 0.001 and p {<=} 0.01, respectively. Genes involved in retinoic acid metabolism (e.g. aldehyde dehydrogenase 8, member A1; retinol dehydrogenase 12), steroid biosynthesis and metabolism (e.g. hydroxysteroid (11{beta}) dehydrogenase 2; hydroxy-delta-5-steroid dehydrogenase, 3 beta-), hormone transport (e.g. sex hormone binding globulin), and regulation of cell growth and proliferation (e.g. N-myc downstream regulated gene 1; spermidinespermine N(1)-acetyltransferase) were affected by MDHT exposure. In this study, we identified genes involved in a variety of biological processes that have the potential to be used as markers of exposure to androgenic substances. Genes identified in this study provide information on the potential mode of action of strong androgens in female fish. In addition, when used for screening of EDC's, these genes may also serve as sensitive markers of exposure to androgenic compounds.

A constructive approach to gene expression dynamics

International Nuclear Information System (INIS)

Ochiai, T.; Nacher, J.C.; Akutsu, T.

2004-01-01

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

Alteration in follistatin gene expression detected in prenatally androgenized rats.

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Salehi Jahromi, Marziyeh; Ramezani Tehrani, Fahimeh; Hill, Jennifer W; Noroozzadeh, Mahsa; Zarkesh, Maryam; Ghasemi, Asghar; Zadeh-Vakili, Azita

2017-06-01

Impaired ovarian follicle development, the hallmark of polycystic ovarian syndrome (PCOS), is believed to be due to the changes in expression of related genes such as follistatin (FST). Expression of FST gene and methylation level of its promoter in theca cells from adult female rats, prenatally exposed to androgen excess, during different phases of the estrus cycle was determined and compared with controls. Eight pregnant Wistar rats (experimental group) were treated by subcutaneous injection of 5 mg free testosterone on day 20 of pregnancy, while controls (n = 8) received 500 ml solvent. Based on observed vaginal smear, adult female offspring of mothers were divided into three groups. Levels of serum steroidogenic sexual hormones and gonadotropins, expression and promoter methylation of the FST gene were measured using ELISA, cyber-green real-time PCR and bisulfite sequence PCR (BSP), respectively. Compared to controls, the relative expression of FST gene in the treated group decreased overall by 0.85 fold; despite significant changes in different phases, but no significant differences in methylation of FST promoter. Our results reveal that manifestation of PCOS-like phenotype following prenatal exposure to excess androgen is associated with irregularity in expression of the FST gene during the estrus cycle.

Stably Expressed Genes Involved in Basic Cellular Functions.

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Kejian Wang

Full Text Available Stably Expressed Genes (SEGs whose expression varies within a narrow range may be involved in core cellular processes necessary for basic functions. To identify such genes, we re-analyzed existing RNA-Seq gene expression profiles across 11 organs at 4 developmental stages (from immature to old age in both sexes of F344 rats (n = 4/group; 320 samples. Expression changes (calculated as the maximum expression / minimum expression for each gene of >19000 genes across organs, ages, and sexes ranged from 2.35 to >109-fold, with a median of 165-fold. The expression of 278 SEGs was found to vary ≤4-fold and these genes were significantly involved in protein catabolism (proteasome and ubiquitination, RNA transport, protein processing, and the spliceosome. Such stability of expression was further validated in human samples where the expression variability of the homologous human SEGs was significantly lower than that of other genes in the human genome. It was also found that the homologous human SEGs were generally less subject to non-synonymous mutation than other genes, as would be expected of stably expressed genes. We also found that knockout of SEG homologs in mouse models was more likely to cause complete preweaning lethality than non-SEG homologs, corroborating the fundamental roles played by SEGs in biological development. Such stably expressed genes and pathways across life-stages suggest that tight control of these processes is important in basic cellular functions and that perturbation by endogenous (e.g., genetics or exogenous agents (e.g., drugs, environmental factors may cause serious adverse effects.

Lithium ions induce prestalk-associated gene expression and inhibit prespore gene expression in Dictyostelium discoideum

NARCIS (Netherlands)

Peters, Dorien J.M.; Lookeren Campagne, Michiel M. van; Haastert, Peter J.M. van; Spek, Wouter; Schaap, Pauline

1989-01-01

We investigated the effect of Li+ on two types of cyclic AMP-regulated gene expression and on basal and cyclic AMP-stimulated inositol 1,4,5-trisphosphate (Ins(1,4,5)P3) levels. Li+ effectively inhibits cyclic AMP-induced prespore gene expression, half-maximal inhibition occurring at about 2mM-LiCl.

Gene coexpression measures in large heterogeneous samples using count statistics.

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Wang, Y X Rachel; Waterman, Michael S; Huang, Haiyan

2014-11-18

With the advent of high-throughput technologies making large-scale gene expression data readily available, developing appropriate computational tools to process these data and distill insights into systems biology has been an important part of the "big data" challenge. Gene coexpression is one of the earliest techniques developed that is still widely in use for functional annotation, pathway analysis, and, most importantly, the reconstruction of gene regulatory networks, based on gene expression data. However, most coexpression measures do not specifically account for local features in expression profiles. For example, it is very likely that the patterns of gene association may change or only exist in a subset of the samples, especially when the samples are pooled from a range of experiments. We propose two new gene coexpression statistics based on counting local patterns of gene expression ranks to take into account the potentially diverse nature of gene interactions. In particular, one of our statistics is designed for time-course data with local dependence structures, such as time series coupled over a subregion of the time domain. We provide asymptotic analysis of their distributions and power, and evaluate their performance against a wide range of existing coexpression measures on simulated and real data. Our new statistics are fast to compute, robust against outliers, and show comparable and often better general performance.

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

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Castro Rosa MRPS

2009-05-01

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

Gene expression of osteogenic factors following gene therapy in mandibular lengthening.

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Wu, Guoping; Zhou, Bin; Hu, Chunbing; Li, Shaolan

2015-03-01

This study investigated the effect of gene therapy on the expression of osteogenic mediators in mandibular distraction osteogenesis rabbits. Bilateral mandibular osteotomies were performed in 45 New-Zealand rabbits. After a latency of 3 days, the mandibles were elongated using distractors with a rate of 0.8 mm/d for 7 days. After the completion of distraction, the rabbits were randomly divided into 5 groups: 2 μg (0.1 μg/μL) of recombinant plasmid pIRES-hVEGF165-hBMP-2, recombinant plasmid pIRES-hBMP2, recombinant plasmid pIRES-hVEGF165, pIRES, and the same volume of normal saline were injected into the distraction gap of groups A, B, C, D, and E, respectively, followed by electroporation. Three animals were killed at the 7th, 14th, and 28th day after gene transfected in different groups, respectively. The lengthened mandibles were harvested and processed for immunohistochemical examinations; the mean optic densities (MODs) and integral optical density of bone morphogenetic protein (BMP-2) and transforming growth factor β1 (TGF-β1)-positive cells were measured by CMIAS-2001A computerized image analyzer. The data were analyzed with SPSS (SPSS Inc, Chicago, IL). Bone morphogenetic protein 2 and TGF-β1 staining was mainly located in inflammatory cells, monocytes, fibroblasts, osteoblasts, osteocytes, and chondrocytes in the distraction zones. Their strongest expression reached to the peak at the seventh day and decreased at the 14th day of consolidation stage; at the 28th day, they expressed weakly. Image analysis results show that, at the seventh day, the expression of BMP-2 in group B (0.26 ± 0.03, 0.36 ± 0.02) was the strongest; there was significant difference among them (P < 0.01), whereas the expression of TGF-β1 in group C (0.38 ± 0.06, 1.05 ± 0.19) is strongest followed by group A (0.34 ± 0.05, 0.95 ± 0.16) and B (0.33 ± 0.07, 0.90 ± 0.19). At every time point, the level of expression of BMP-2 and TGF-β1 in gene therapy groups (groups A, B, and

Expression of the gene cluster associated with the Escherichia coli pilus adhesin K99.

OpenAIRE

Lee, J H; Isaacson, R E

1995-01-01

The biogenesis of the pilus adhesin K99 is dependent on the expression of eight contiguous genes, fanA to fanH. Transposon mutants were prepared by using TnlacZ and TnphoA, and selected transposon mutants were used to measure expression of each K99 gene. Expression of the K99 genes is likely controlled at the transcription level, since in general, there were no differences between the results obtained with the two transposons. fanC was the most highly expressed, and fanD was expressed at very...

In search of suitable reference genes for gene expression studies of human renal cell carcinoma by real-time PCR

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Kristiansen Glen

2007-06-01

Full Text Available Abstract Background Housekeeping genes are commonly used as endogenous reference genes for the relative quantification of target genes in gene expression studies. No conclusive systematic study comparing the suitability of different candidate reference genes in clear cell renal cell carcinoma has been published to date. To remedy this situation, 10 housekeeping genes for normalizing purposes of RT-PCR measurements already recommended in various studies were examined with regard to their usefulness as reference genes. Results The expression of the potential reference genes was examined in matched malignant and non-malignant tissue specimens from 25 patients with clear cell renal cell carcinoma. Quality assessment of isolated RNA performed with a 2100 Agilent Bioanalyzer showed a mean RNA integrity number of 8.7 for all samples. The between-run variations related to the crossing points of PCR reactions of a control material ranged from 0.17% to 0.38%. The expression of all genes did not depend on age, sex, and tumour stage. Except the genes TATA box binding protein (TBP and peptidylprolyl isomerase A (PPIA, all genes showed significant differences in expression between malignant and non-malignant pairs. The expression stability of the candidate reference genes was additionally controlled using the software programs geNorm and NormFinder. TBP and PPIA were validated as suitable reference genes by normalizing the target gene ADAM9 using these two most stably expressed genes in comparison with up- and down-regulated housekeeping genes of the panel. Conclusion Our study demonstrated the suitability of the two housekeeping genes PPIA and TBP as endogenous reference genes when comparing malignant tissue samples with adjacent normal tissue samples from clear cell renal cell carcinoma. Both genes are recommended as reference genes for relative gene quantification in gene profiling studies either as single gene or preferably in combination.

Stochastic gene expression in Arabidopsis thaliana.

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Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

2017-12-14

Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

Deriving Trading Rules Using Gene Expression Programming

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Adrian VISOIU

2011-01-01

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

Using PCR to Target Misconceptions about Gene Expression

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Leslie K. Wright

2013-02-01

Full Text Available 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.

Differential gene expression during Trypanosoma cruzi metacyclogenesis

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Marco Aurelio Krieger

1999-09-01

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

Conditional gene expression in the mouse using a Sleeping Beauty gene-trap transposon

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Hackett Perry B

2006-06-01

Full Text Available Abstract Background Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern. Results Here we report the systematic development and testing of a transposon-based gene-trap system incorporating the doxycycline-repressible Tet-Off (tTA system that is capable of activating the expression of genes under control of a Tet response element (TRE promoter. We demonstrate that the gene trap system is fully functional in vitro by introducing the "gene-trap tTA" vector into human cells by transposition and identifying clones that activate expression of a TRE-luciferase transgene in a doxycycline-dependent manner. In transgenic mice, we mobilize gene-trap tTA vectors, discover parameters that can affect germline mobilization rates, and identify candidate gene insertions to demonstrate the in vivo functionality of the vector system. We further demonstrate that the gene-trap can act as a reporter of endogenous gene expression and it can be coupled with bioluminescent imaging to identify genes with tissue-specific expression patterns. Conclusion Akin to the GAL4/UAS system used in the fly, we have made progress developing a tool for mutating and revealing the expression of mouse genes by generating the tTA transactivator in the presence of a secondary TRE-regulated reporter molecule. A vector like the gene

A comparative gene expression database for invertebrates

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Ormestad Mattias

2011-08-01

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

Genetic Variants Contribute to Gene Expression Variability in Humans

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Hulse, Amanda M.; Cai, James J.

2013-01-01

Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed. PMID:23150607

Correction of gene expression data

DEFF Research Database (Denmark)

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

2014-01-01

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

Gene expression in colorectal cancer

DEFF Research Database (Denmark)

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

2002-01-01

Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

Multiscale Embedded Gene Co-expression Network Analysis.

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Won-Min Song

2015-11-01

Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Multiscale Embedded Gene Co-expression Network Analysis.

Science.gov (United States)

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Night-time restricted feeding normalises clock genes and Pai-1 gene expression in the db/db mouse liver.

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Kudo, T; Akiyama, M; Kuriyama, K; Sudo, M; Moriya, T; Shibata, S

2004-08-01

An increase in PAI-1 activity is thought to be a key factor underlying myocardial infarction. Mouse Pai-1 (mPai-1) activity shows a daily rhythm in vivo, and its transcription seems to be controlled not only by clock genes but also by humoral factors such as insulin and triglycerides. Thus, we investigated daily clock genes and mPai-1 mRNA expression in the liver of db/db mice exhibiting high levels of glucose, insulin and triglycerides. Locomotor activity was measured using an infrared detection system. RT-PCR or in situ hybridisation methods were applied to measure gene expression. Humoral factors were measured using measurement kits. The db/ db mice showed attenuated locomotor activity rhythms. The rhythmic expression of mPer2 mRNA was severely diminished and the phase of mBmal1 oscillation was advanced in the db/db mouse liver, whereas mPai-1 mRNA was highly and constitutively expressed. Night-time restricted feeding led to a recovery not only from the diminished locomotor activity, but also from the diminished Per2 and advanced mBmal1 mRNA rhythms. Expression of mPai-1 mRNA in db/db mice was reduced to levels far below normal. Pioglitazone treatment slightly normalised glucose and insulin levels, with a slight reduction in mPai-1 gene expression. We demonstrated that Type 2 diabetes impairs the oscillation of the peripheral oscillator. Night-time restricted feeding rather than pioglitazone injection led to a recovery from the diminished locomotor activity, and altered oscillation of the peripheral clock and mPai-1 mRNA rhythm. Thus, we conclude that scheduled restricted food intake may be a useful form of treatment for diabetes.

Differential gene expression of wheat progeny with contrasting levels of transpiration efficiency.

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Xue, Gang-Ping; McIntyre, C Lynne; Chapman, Scott; Bower, Neil I; Way, Heather; Reverter, Antonio; Clarke, Bryan; Shorter, Ray

2006-08-01

High water use efficiency or transpiration efficiency (TE) in wheat is a desirable physiological trait for increasing grain yield under water-limited environments. The identification of genes associated with this trait would facilitate the selection for genotypes with higher TE using molecular markers. We performed an expression profiling (microarray) analysis of approximately 16,000 unique wheat ESTs to identify genes that were differentially expressed between wheat progeny lines with contrasting TE levels from a cross between Quarrion (high TE) and Genaro 81 (low TE). We also conducted a second microarray analysis to identify genes responsive to drought stress in wheat leaves. Ninety-three genes that were differentially expressed between high and low TE progeny lines were identified. One fifth of these genes were markedly responsive to drought stress. Several potential growth-related regulatory genes, which were down-regulated by drought, were expressed at a higher level in the high TE lines than the low TE lines and are potentially associated with a biomass production component of the Quarrion-derived high TE trait. Eighteen of the TE differentially expressed genes were further analysed using quantitative RT-PCR on a separate set of plant samples from those used for microarray analysis. The expression levels of 11 of the 18 genes were positively correlated with the high TE trait, measured as carbon isotope discrimination (Delta(13)C). These data indicate that some of these TE differentially expressed genes are candidates for investigating processes that underlie the high TE trait or for use as expression quantitative trait loci (eQTLs) for TE.

Pattern Recognition of Gene Expression with Singular Spectrum Analysis

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Hossein Hassani

2014-07-01

Full Text Available Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its association with considerable error, each can only partially explain bicoid characteristics. In this paper, a modified version of singular spectrum analysis is examined for filtering and extracting the bicoid gene expression signal. The results with strong evidence indicate that the proposed technique is able to remove noise more effectively and can be considered as a promising method for filtering gene expression measurements for other applications.

Comparison of co-expression measures: mutual information, correlation, and model based indices.

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Song, Lin; Langfelder, Peter; Horvath, Steve

2012-12-09

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI

Expression profiles of sugarcane under drought conditions: Variation in gene regulation

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Júlio César Farias de Andrade

2015-01-01

Full Text Available AbstractDrought is a major factor in decreased sugarcane productivity because of the resulting morphophysiological effects that it causes. Gene expression studies that have examined the influence of water stress in sugarcane have yielded divergent results, indicating the absence of a fixed pattern of changes in gene expression. In this work, we investigated the expression profiles of 12 genes in the leaves of a drought-tolerant genotype (RB72910 of sugarcane and compared the results with those of other studies. The genotype was subjected to 80–100% water availability (control condition and 0–20% water availability (simulated drought. To analyze the physiological status, the SPAD index, Fv/Fm ratio, net photosynthesis (A, stomatal conductance (gs and stomatal transpiration (E were measured. Total RNA was extracted from leaves and the expression of SAMDC, ZmPIP2-1 protein, ZmTIP4-2 protein, WIP protein, LTP protein, histone H3, DNAj, ferredoxin I, β-tubulin, photosystem I, gene 1 and gene 2 was analyzed by quantitative real-time PCR (RT-PCR. Important differences in the expression profiles of these genes were observed when compared with other genotypes, suggesting that complex defense mechanisms are activated in response to water stress. However, there was no recognizable pattern for the changes in expression of the different proteins associated with tolerance to drought stress.

Vascular Gene Expression: A Hypothesis

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Angélica Concepción eMartínez-Navarro

2013-07-01

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

GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

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Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

2018-01-01

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancer-related gene

International Nuclear Information System (INIS)

Wu, Mingsong; Tu, Tao; Huang, Yunchao; Cao, Yi

2013-01-01

To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration and proliferation in vitro. The

Clustering approaches to identifying gene expression patterns from DNA microarray data.

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Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

The evolution of gene expression in primates

OpenAIRE

Tashakkori Ghanbarian, Avazeh

2015-01-01

The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes 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 e...

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

International Nuclear Information System (INIS)

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

2013-01-01

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.

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

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

2013-01-20

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

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

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Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

2016-01-01

The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis

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Chun Chen

2016-03-01

Full Text Available Abstract The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host–pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S, 28S rRNA(28S and elongation factor 1 alpha-like protein (EF1, were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae, and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189, 28S (1.414 and EF1 (3. The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis.

Early pregnancy peripheral blood gene expression and risk of preterm delivery: a nested case control study

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Muhie Seid Y

2009-12-01

Full Text Available Abstract Background Preterm delivery (PTD is a significant public health problem associated with greater risk of mortality and morbidity in infants and mothers. Pathophysiologic processes that may lead to PTD start early in pregnancy. We investigated early pregnancy peripheral blood global gene expression and PTD risk. Methods As part of a prospective study, ribonucleic acid was extracted from blood samples (collected at 16 weeks gestational age from 14 women who had PTD (cases and 16 women who delivered at term (controls. Gene expressions were measured using the GeneChip® Human Genome U133 Plus 2.0 Array. Student's T-test and fold change analysis were used to identify differentially expressed genes. We used hierarchical clustering and principle components analysis to characterize signature gene expression patterns among cases and controls. Pathway and promoter sequence analyses were used to investigate functions and functional relationships as well as regulatory regions of differentially expressed genes. Results A total of 209 genes, including potential candidate genes (e.g. PTGDS, prostaglandin D2 synthase 21 kDa, were differentially expressed. A set of these genes achieved accurate pre-diagnostic separation of cases and controls. These genes participate in functions related to immune system and inflammation, organ development, metabolism (lipid, carbohydrate and amino acid and cell signaling. Binding sites of putative transcription factors such as EGR1 (early growth response 1, TFAP2A (transcription factor AP2A, Sp1 (specificity protein 1 and Sp3 (specificity protein 3 were over represented in promoter regions of differentially expressed genes. Real-time PCR confirmed microarray expression measurements of selected genes. Conclusions PTD is associated with maternal early pregnancy peripheral blood gene expression changes. Maternal early pregnancy peripheral blood gene expression patterns may be useful for better understanding of PTD

Widespread ectopic expression of olfactory receptor genes

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Yanai Itai

2006-05-01

Full Text Available Abstract Background Olfactory receptors (ORs are the largest gene family in the human genome. Although they are expected to be expressed specifically in olfactory tissues, some ectopic expression has been reported, with special emphasis on sperm and testis. The present study systematically explores the expression patterns of OR genes in a large number of tissues and assesses the potential functional implication of such ectopic expression. Results We analyzed the expression of hundreds of human and mouse OR transcripts, via EST and microarray data, in several dozens of human and mouse tissues. Different tissues had specific, relatively small OR gene subsets which had particularly high expression levels. In testis, average expression was not particularly high, and very few highly expressed genes were found, none corresponding to ORs previously implicated in sperm chemotaxis. Higher expression levels were more common for genes with a non-OR genomic neighbor. Importantly, no correlation in expression levels was detected for human-mouse orthologous pairs. Also, no significant difference in expression levels was seen between intact and pseudogenized ORs, except for the pseudogenes of subfamily 7E which has undergone a human-specific expansion. Conclusion The OR superfamily as a whole, show widespread, locus-dependent and heterogeneous expression, in agreement with a neutral or near neutral evolutionary model for transcription control. These results cannot reject the possibility that small OR subsets might play functional roles in different tissues, however considerable care should be exerted when offering a functional interpretation for ectopic OR expression based only on transcription information.

Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

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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. PMID:23382867

Development of a cDNA microarray for the measurement of gene expression in the sheep scab mite Psoroptes ovis

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Burgess Stewart TG

2012-02-01

Full Text Available Abstract Background Sheep scab is caused by the ectoparasitic mite Psoroptes ovis which initiates a profound cutaneous inflammatory response, leading to the development of the skin lesions which are characteristic of the disease. Existing control strategies rely upon injectable endectocides and acaricidal dips but concerns over residues, eco-toxicity and the development of acaricide resistance limit the sustainability of this approach. In order to identify alternative means of disease control, a deeper understanding of both the parasite and its interaction with the host are required. Methods Herein we describe the development and utilisation of an annotated P. ovis cDNA microarray containing 3,456 elements for the measurement of gene expression in this economically important ectoparasite. The array consists of 981 P. ovis EST sequences printed in triplicate along with 513 control elements. Array performance was validated through the analysis of gene expression differences between fed and starved P. ovis mites. Results Sequences represented on the array include homologues of major house dust mite allergens and tick salivary proteins, along with factors potentially involved in mite reproduction and xenobiotic metabolism. In order to validate the performance of this unique resource under biological conditions we used the array to analyse gene expression differences between fed and starved P. ovis mites. These analyses identified a number of house dust mite allergen homologues up-regulated in fed mites and P. ovis transcripts involved in stress responses, autophagy and chemosensory perception up-regulated in starved mites. Conclusion The P. ovis cDNA microarray described here has been shown to be both robust and reproducible and will enable future studies to analyse gene expression in this important ectoparasite.

Dynamic association rules for gene expression data analysis.

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Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

Gene expression in periodontal tissues following treatment

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Eisenacher Martin

2008-07-01

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

An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

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Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

2009-01-01

In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli.

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Ståhlberg, Anders; Elbing, Karin; Andrade-Garda, José Manuel; Sjögreen, Björn; Forootan, Amin; Kubista, Mikael

2008-04-16

The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions. We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition. Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli

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Andrade-Garda José

2008-04-01

Full Text Available Abstract Background The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions. Results We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition. Conclusion Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.

Spatial reconstruction of single-cell gene expression data.

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Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

Cell Wall Composition and Candidate Biosynthesis Gene Expression During Rice Development

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Lin, Fan; Manisseri, Chithra; Fagerström, Alexandra; Peck, Matthew L.; Vega-Sánchez, Miguel E.; Williams, Brian; Chiniquy, Dawn M.; Saha, Prasenjit; Pattathil, Sivakumar; Conlin, Brian; Zhu, Lan; Hahn, Michael G.; Willats, William G. T.; Scheller, Henrik V.; Ronald, Pamela C.; Bartley, Laura E.

2016-08-01

Cell walls of grasses, including cereal crops and biofuel grasses, comprise the majority of plant biomass and intimately influence plant growth, development and physiology. However, the functions of many cell wall synthesis genes, and the relationships among and the functions of cell wall components remain obscure. To better understand the patterns of cell wall accumulation and identify genes that act in grass cell wall biosynthesis, we characterized 30 samples from aerial organs of rice (Oryza sativa cv. Kitaake) at 10 developmental time points, 3-100 d post-germination. Within these samples, we measured 15 cell wall chemical components, enzymatic digestibility and 18 cell wall polysaccharide epitopes/ligands. We also used quantitative reverse transcription-PCR to measure expression of 50 glycosyltransferases, 15 acyltransferases and eight phenylpropanoid genes, many of which had previously been identified as being highly expressed in rice. Most cell wall components vary significantly during development, and correlations among them support current understanding of cell walls. We identified 92 significant correlations between cell wall components and gene expression and establish nine strong hypotheses for genes that synthesize xylans, mixed linkage glucan and pectin components. This work provides an extensive analysis of cell wall composition throughout rice development, identifies genes likely to synthesize grass cell walls, and provides a framework for development of genetically improved grasses for use in lignocellulosic biofuel production and agriculture.

Gene expression profiles in skeletal muscle after gene electrotransfer

DEFF Research Database (Denmark)

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

2007-01-01

BACKGROUND: Gene transfer by electroporation (DNA electrotransfer) to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have...... caused down-regulation of structural proteins e.g. sarcospan and catalytic enzymes. Injection of DNA induced down-regulation of intracellular transport proteins e.g. sentrin. The effects on muscle fibres were transient as the expression profiles 3 weeks after treatment were closely related......) followed by a long low voltage pulse (LV, 100 V/cm, 400 ms); a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP) and excised at 4 hours, 48 hours or 3 weeks after treatment. RESULTS: Differentially expressed genes were...

A robust approach based on Weibull distribution for clustering gene expression data

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Gong Binsheng

2011-05-01

Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

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Licamele Louis

2010-03-01

Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.

Comparative gene expression between two yeast species

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Guan Yuanfang

2013-01-01

Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

Interactive visualization of gene regulatory networks with associated gene expression time series data

NARCIS (Netherlands)

Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

2008-01-01

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Serial analysis of gene expression (SAGE)

NARCIS (Netherlands)

van Ruissen, Fred; Baas, Frank

2007-01-01

In 1995, serial analysis of gene expression (SAGE) was developed as a versatile tool for gene expression studies. SAGE technology does not require pre-existing knowledge of the genome that is being examined and therefore SAGE can be applied to many different model systems. In this chapter, the SAGE

Using interpolation to estimate system uncertainty in gene expression experiments.

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Lee J Falin

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

An Interactive Database of Cocaine-Responsive Gene Expression

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Willard M. Freeman

2002-01-01

Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

CDX2 gene expression in acute lymphoblastic leukemia

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Arnaoaut, H.H.; Mokhtar, D.A.; Samy, R.M.; Omar, Sh.A.; Khames, S.A.

2014-01-01

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

Identification of reference genes in human myelomonocytic cells for gene expression studies in altered gravity.

Science.gov (United States)

Thiel, Cora S; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Unverdorben, Felix; Buttron, Isabell; Lauber, Beatrice; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E; Ullrich, Oliver

2015-01-01

Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series

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Madeira Sara C

2009-06-01

Full Text Available Abstract Background The ability to monitor the change in expression patterns over time, and to observe the emergence of coherent temporal responses using gene expression time series, obtained from microarray experiments, is critical to advance our understanding of complex biological processes. In this context, biclustering algorithms have been recognized as an important tool for the discovery of local expression patterns, which are crucial to unravel potential regulatory mechanisms. Although most formulations of the biclustering problem are NP-hard, when working with time series expression data the interesting biclusters can be restricted to those with contiguous columns. This restriction leads to a tractable problem and enables the design of efficient biclustering algorithms able to identify all maximal contiguous column coherent biclusters. Methods In this work, we propose e-CCC-Biclustering, a biclustering algorithm that finds and reports all maximal contiguous column coherent biclusters with approximate expression patterns in time polynomial in the size of the time series gene expression matrix. This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques. We also propose extensions to deal with missing values, discover anticorrelated and scaled expression patterns, and different ways to compute the errors allowed in the expression patterns. We propose a scoring criterion combining the statistical significance of expression patterns with a similarity measure between overlapping biclusters. Results We present results in real data showing the effectiveness of e-CCC-Biclustering and its relevance in the discovery of regulatory modules describing the transcriptomic expression patterns occurring in Saccharomyces cerevisiae in response to heat stress. In particular, the results show the advantage of considering approximate patterns when compared to state of

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.

2013-07-18

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

Reference Gene Screening for Analyzing Gene Expression Across Goat Tissue

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Yu Zhang

2013-12-01

Full Text Available Real-time quantitative PCR (qRT-PCR is one of the important methods for investigating the changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of real-time quantitative PCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We used real-time quantitative PCR to detect the expression levels of eight reference gene candidates (18S, TBP, HMBS, YWHAZ, ACTB, HPRT1, GAPDH and EEF1A2 in ten tissues types sourced from Boer goats. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in genes expression stability. When all tissues were considered, 18S, TBP and HMBS is the optimal reference combination for calibrating quantitative PCR analysis of gene expression from goat tissues. Dividing data set by tissues, ACTB was the most stable in stomach, small intestine and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney and GAPDH in muscle. Overall, this study provided valuable information about the goat reference genes that can be used in order to perform a proper normalisation when relative quantification by qRT-PCR studies is undertaken.

Studying the Complex Expression Dependences between Sets of Coexpressed Genes

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Mario Huerta

2014-01-01

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

Real-Time Gene Expression Profiling of Live Shewanella Oneidensis Cells

Energy Technology Data Exchange (ETDEWEB)

Xiaoliang Sunney Xie

2009-03-30

The overall objective of this proposal is to make real-time observations of gene expression in live Shewanella oneidensis cells with high sensitivity and high throughput. Gene expression, a central process to all life, is stochastic because most genes often exist in one or two copies per cell. Although the central dogma of molecular biology has been proven beyond doubt, due to insufficient sensitivity, stochastic protein production has not been visualized in real time in an individual cell at the single-molecule level. We report the first direct observation of single protein molecules as they are generated, one at a time in a single live E. coli cell, yielding quantitative information about gene expression [Science 2006; 311: 1600-1603]. We demonstrated a general strategy for live-cell single-molecule measurements: detection by localization. It is difficult to detect single fluorescence protein molecules inside cytoplasm - their fluorescence is spread by fast diffusion to the entire cell and overwhelmed by the strong autofluorescence. We achieved single-molecule sensitivity by immobilizing the fluorescence protein on the cell membrane, where the diffusion is much slowed. We learned that under the repressed condition protein molecules are produced in bursts, with each burst originating from a stochastically-transcribed single messenger RNA molecule, and that protein copy numbers in the bursts follow a geometric distribution. We also simultaneously published a paper reporting a different method using β-glactosidase as a reporter [Nature 440, 358 (2006)]. Many important proteins are expressed at low levels, inaccessible by previous proteomic techniques. Both papers allowed quantification of protein expression with unprecedented sensitivity and received overwhelming acclaim from the scientific community. The Nature paper has been identified as one of the most-cited papers in the past year [http://esi-topics.com/]. We have also an analytical framework describing the

Gene expression of the mismatch repair gene MSH2 in primary colorectal cancer

DEFF Research Database (Denmark)

Jensen, Lars Henrik; Kuramochi, Hidekazu; Crüger, Dorthe Gylling

2011-01-01

promoter was only detected in 14 samples and only at a low level with no correlation to gene expression. MSH2 gene expression was not a prognostic factor for overall survival in univariate or multivariate analysis. The gene expression of MSH2 is a potential quantitative marker ready for further clinical...

Gene expression analysis in lymphoblasts derived from patients with autism spectrum disorder

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Yasuda Yuka

2011-05-01

Full Text Available Abstract Background The autism spectrum disorders (ASDs are complex neurodevelopmental disorders that result in severe and pervasive impairment in the development of reciprocal social interaction and verbal and nonverbal communication skills. In addition, individuals with ASD have stereotypical behavior, interests and activities. Rare mutations of some genes, such as neuroligin (NLGN 3/4, neurexin (NRXN 1, SHANK3, MeCP2 and NHE9, have been reported to be associated with ASD. In the present study, we investigated whether alterations in mRNA expression levels of these genes could be found in lymphoblastoid cell lines derived from patients with ASD. Methods We measured mRNA expression levels of NLGN3/4, NRXN1, SHANK3, MeCP2, NHE9 and AKT1 in lymphoblastoid cells from 35 patients with ASD and 35 healthy controls, as well as from 45 patients with schizophrenia and 45 healthy controls, using real-time quantitative reverse transcriptase polymerase chain reaction assays. Results The mRNA expression levels of NLGN3 and SHANK3 normalized by β-actin or TBP were significantly decreased in the individuals with ASD compared to controls, whereas no difference was found in the mRNA expression level of MeCP2, NHE9 or AKT1. However, normalized NLGN3 and SHANK3 gene expression levels were not altered in patients with schizophrenia, and expression levels of NLGN4 and NRXN1 mRNA were not quantitatively measurable in lymphoblastoid cells. Conclusions Our results provide evidence that the NLGN3 and SHANK3 genes may be differentially expressed in lymphoblastoid cell lines from individuals with ASD compared to those from controls. These findings suggest the possibility that decreased mRNA expression levels of these genes might be involved in the pathophysiology of ASD in a substantial population of ASD patients.

The Sporothrix schenckii Gene Encoding for the Ribosomal Protein L6 Has Constitutive and Stable Expression and Works as an Endogenous Control in Gene Expression Analysis

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Elías Trujillo-Esquivel

2017-09-01

Full Text Available Sporothrix schenckii is one of the causative agents of sporotrichosis, a worldwide-distributed mycosis that affects humans and other mammals. The interest in basic and clinical features of this organism has significantly increased in the last years, yet little progress in molecular aspects has been reported. Gene expression analysis is a set of powerful tools that helps to assess the cell response to changes in the extracellular environment, the genetic networks controlling metabolic pathways, and the adaptation to different growth conditions. Most of the quantitative methodologies used nowadays require data normalization, and this is achieved measuring the expression of endogenous control genes. Reference genes, whose expression is assumed to suffer minimal changes regardless the cell morphology, the stage of the cell cycle or the presence of harsh extracellular conditions are commonly used as controls in Northern blotting assays, microarrays, and semi-quantitative or quantitative RT-PCR. Since the biology of the organisms is usually species specific, it is difficult to find a reliable group of universal genes that can be used as controls for data normalization in experiments addressing the gene expression, regardless the taxonomic classification of the organism under study. Here, we compared the transcriptional stability of the genes encoding for elongation factor 1A, Tfc1, a protein involved in transcription initiation on Pol III promoters, ribosomal protein L6, histone H2A, β-actin, β-tubulin, glyceraldehyde 3-phosphate dehydrogenase, UAF30, the upstream activating factor 30, and the transcription initiation factor TFIID subunit 10, during the fungal growth in different culture media and cell morphologies. Our results indicated that only the gene encoding for the ribosomal protein L6 showed a stable and constant expression. Furthermore, it displayed not transcriptional changes when S. schenckii infected larvae of Galleria mellonella or

Ionizing Radiation Affects Gene Expression in Mouse Skin and Bone

Science.gov (United States)

Terada, Masahiro; Tahimic, Candice; Sowa, Marianne B.; Schreurs, Ann-Sofie; Shirazi-Fard, Yasaman; Alwood, Joshua; Globus, Ruth K.

2017-01-01

Future long-duration space exploration beyond low earth orbit will increase human exposure to space radiation and microgravity conditions as well as associated risks to skeletal health. In animal studies, radiation exposure (greater than 1 Gy) is associated with pathological changes in bone structure, enhanced bone resorption, reduced bone formation and decreased bone mineral density, which can lead to skeletal fragility. Definitive measurements and detection of bone loss typically require large and specialized equipment which can make their application to long duration space missions logistically challenging. Towards the goal of developing non-invasive and less complicated monitoring methods to predict astronauts' health during spaceflight, we examined whether radiation induced gene expression changes in skin may be predictive of the responses of skeletal tissue to radiation exposure. We examined oxidative stress and growth arrest pathways in mouse skin and long bones by measuring gene expression levels via quantitative polymerase chain reaction (qPCR) after exposure to total body irradiation (IR). To investigate the effects of irradiation on gene expression, we used skin and femora (cortical shaft) from the following treatment groups: control (normally loaded, sham-irradiated), and IR (0.5 Gy 56Fe 600 MeV/n and 0.5 Gy 1H 150 MeV/n), euthanized at one and 11 days post-irradiation (IR). To determine the extent of bone loss, tibiae were harvested and cancellous microarchitecture in the proximal tibia quantified ex vivo using microcomputed tomography (microCT). Statistical analysis was performed using Student's t-test. At one day post-IR, expression of FGF18 in skin was significantly greater (3.8X) than sham-irradiated controls, but did not differ at 11 days post IR. Expression levels of other genes associated with antioxidant response (Nfe2l2, FoxO3 and Sod1) and the cell cycle (Trp53, Cdkn1a, Gadd45g) did not significantly differ between the control and IR groups

Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

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Robert T Gaeta

. Furthermore, our microarray analysis did not provide strong evidence that homoeologous rearrangements were a determinant of genome-wide nonadditive gene expression. In light of the inherent limitations of the Arabidopsis microarray to measure gene expression in polyploid Brassicas, further studies are warranted.

Fatty acid composition and desaturase gene expression in flax (Linum usitatissimum L.).

Science.gov (United States)

Thambugala, Dinushika; Cloutier, Sylvie

2014-11-01

Little is known about the relationship between expression levels of fatty acid desaturase genes during seed development and fatty acid (FA) composition in flax. In the present study, we looked at promoter structural variations of six FA desaturase genes and their relative expression throughout seed development. Computational analysis of the nucleotide sequences of the sad1, sad2, fad2a, fad2b, fad3a and fad3b promoters showed several basic transcriptional elements including CAAT and TATA boxes, and several putative target-binding sites for transcription factors, which have been reported to be involved in the regulation of lipid metabolism. Using semi-quantitative reverse transcriptase PCR, the expression patterns throughout seed development of the six FA desaturase genes were measured in six flax genotypes that differed for FA composition but that carried the same desaturase isoforms. FA composition data were determined by phenotyping the field grown genotypes over four years in two environments. All six genes displayed a bell-shaped pattern of expression peaking at 20 or 24 days after anthesis. Sad2 was the most highly expressed. The expression of all six desaturase genes did not differ significantly between genotypes (P = 0.1400), hence there were no correlations between FA desaturase gene expression and variations in FA composition in relatively low, intermediate and high linolenic acid genotypes expressing identical isoforms for all six desaturases. These results provide further clues towards understanding the genetic factors responsible for FA composition in flax.

Personality and gene expression: Do individual differences exist in the leukocyte transcriptome?

Science.gov (United States)

Vedhara, Kavita; Gill, Sana; Eldesouky, Lameese; Campbell, Bruce K; Arevalo, Jesusa M G; Ma, Jeffrey; Cole, Steven W

2015-02-01

The temporal and situational stability of personality has led generations of researchers to hypothesize that personality may have enduring effects on health, but the biological mechanisms of such relationships remain poorly understood. In the present study, we utilized a functional genomics approach to examine the relationship between the 5 major dimensions of personality and patterns of gene expression as predicted by 'behavioural immune response' theory. We specifically focussed on two sets of genes previously linked to stress, threat, and adverse socio-environmental conditions: pro-inflammatory genes and genes involved in Type I interferon and antibody responses. An opportunity sample of 121 healthy individuals was recruited (86 females; mean age 24 years). Individuals completed a validated measure of personality; questions relating to current health behaviours; and provided a 5ml sample of peripheral blood for gene expression analysis. Extraversion was associated with increased expression of pro-inflammatory genes and Conscientiousness was associated with reduced expression of pro-inflammatory genes. Both associations were independent of health behaviours, negative affect, and leukocyte subset distributions. Antiviral and antibody-related gene expression was not associated with any personality dimension. The present data shed new light on the long-observed epidemiological associations between personality, physical health, and human longevity. Further research is required to elucidate the biological mechanisms underlying these associations. Copyright © 2014 Elsevier Ltd. All rights reserved.

The relationship among gene expression, the evolution of gene dosage, and the rate of protein evolution.

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Jean-François Gout

2010-05-01

Full Text Available The understanding of selective constraints affecting genes is a major issue in biology. It is well established that gene expression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that gene expression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of gene expression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressed genes. This rule also holds for other taxa: in yeast, we find a clear relationship between gene expression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing gene expression level or affecting the encoded protein should on average be stronger in highly expressed genes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with gene expression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of gene expression and the different facets of gene evolution.

Noise minimization in eukaryotic gene expression.

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Hunter B Fraser

2004-06-01

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

Noise minimization in eukaryotic gene expression

Energy Technology Data Exchange (ETDEWEB)

Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

2004-01-15

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

Noise minimization in eukaryotic gene expression

International Nuclear Information System (INIS)

Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

2004-01-01

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

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks

NARCIS (Netherlands)

Waaijenborg, S.; Zwinderman, A.H.

2009-01-01

ABSTRACT: BACKGROUND: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the

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

Directory of Open Access Journals (Sweden)

Ali Oghabian

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

Using a periclinal chimera to unravel layer-specific gene expression in plants.

Science.gov (United States)

Filippis, Ioannis; Lopez-Cobollo, Rosa; Abbott, James; Butcher, Sarah; Bishop, Gerard J

2013-09-01

Plant organs are made from multiple cell types, and defining the expression level of a gene in any one cell or group of cells from a complex mixture is difficult. Dicotyledonous plants normally have three distinct layers of cells, L1, L2 and L3. Layer L1 is the single layer of cells making up the epidermis, layer L2 the single cell sub-epidermal layer and layer L3 constitutes the rest of the internal cells. Here we show how it is possible to harvest an organ and characterise the level of layer-specific expression by using a periclinal chimera that has its L1 layer from Solanum pennellii and its L2 and L3 layers from Solanum lycopersicum. This is possible by measuring the level of the frequency of species-specific transcripts. RNA-seq analysis enabled the genome-wide assessment of whether a gene is expressed in the L1 or L2/L3 layers. From 13 277 genes that are expressed in both the chimera and the parental lines and with at least one polymorphism between the parental alleles, we identified 382 genes that are preferentially expressed in L1 in contrast to 1159 genes in L2/L3. Gene ontology analysis shows that many genes preferentially expressed in L1 are involved in cutin and wax biosynthesis, whereas numerous genes that are preferentially expressed in L2/L3 tissue are associated with chloroplastic processes. These data indicate the use of such chimeras and provide detailed information on the level of layer-specific expression of genes. © 2013 East Malling Research The Plant Journal © 2013 John Wiley & Sons Ltd.

Positive selection on gene expression in the human brain

DEFF Research Database (Denmark)

Khaitovich, Philipp; Tang, Kun; Franz, Henriette

2006-01-01

Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

A stochastic approach to multi-gene expression dynamics

International Nuclear Information System (INIS)

Ochiai, T.; Nacher, J.C.; Akutsu, T.

2005-01-01

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

Assays for noninvasive imaging of reporter gene expression

International Nuclear Information System (INIS)

Gambhir, S.S.; Barrio, J.R.; Herschman, H.R.; Phelps, M.E.

1999-01-01

Repeated, noninvasive imaging of reporter gene expression is emerging as a valuable tool for monitoring the expression of genes in animals and humans. Monitoring of organ/cell transplantation in living animals and humans, and the assessment of environmental, behavioral, and pharmacologic modulation of gene expression in transgenic animals should soon be possible. The earliest clinical application is likely to be monitoring human gene therapy in tumors transduced with the herpes simplex virus type 1 thymidine kinase (HSV1-tk) suicide gene. Several candidate assays for imaging reporter gene expression have been studied, utilizing cytosine deaminase (CD), HSV1-tk, and dopamine 2 receptor (D2R) as reporter genes. For the HSV1-tk reporter gene, both uracil nucleoside derivatives (e.g., 5-iodo-2'-fluoro-2'-deoxy-1-β-D-arabinofuranosyl-5-iodouracil [FIAU] labeled with 124 I, 131 I ) and acycloguanosine derivatives {e.g., 8-[ 18 F]fluoro-9-[[2-hydroxy-1-(hydroxymethyl)ethoxy]methyl]guanine (8-[ 18 F]-fluoroganciclovir) ([ 18 F]FGCV), 9-[(3-[ 18 F]fluoro-1-hydroxy-2-propoxy)methyl]guanine ([ 18 F]FHPG)} have been investigated as reporter probes. For the D2R reporter gene, a derivative of spiperone {3-(2'-[ 18 F]-Fluoroethyl)spiperone ([ 18 F]FESP)} has been used with positron emission tomography (PET) imaging. In this review, the principles and specific assays for imaging reporter gene expression are presented and discussed. Specific examples utilizing adenoviral-mediated delivery of a reporter gene as well as tumors expressing reporter genes are discussed

PRAME gene expression profile in medulloblastoma

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Tânia Maria Vulcani-Freitas

2011-02-01

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

Systematic identification of human housekeeping genes possibly useful as references in gene expression studies.

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Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

2017-09-01

The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative

Mining gene expression data of multiple sclerosis.

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Pi Guo

Full Text Available 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.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.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.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

FocusHeuristics - expression-data-driven network optimization and disease gene prediction.

Science.gov (United States)

Ernst, Mathias; Du, Yang; Warsow, Gregor; Hamed, Mohamed; Endlich, Nicole; Endlich, Karlhans; Murua Escobar, Hugo; Sklarz, Lisa-Madeleine; Sender, Sina; Junghanß, Christian; Möller, Steffen; Fuellen, Georg; Struckmann, Stephan

2017-02-16

To identify genes contributing to disease phenotypes remains a challenge for bioinformatics. Static knowledge on biological networks is often combined with the dynamics observed in gene expression levels over disease development, to find markers for diagnostics and therapy, and also putative disease-modulatory drug targets and drugs. The basis of current methods ranges from a focus on expression-levels (Limma) to concentrating on network characteristics (PageRank, HITS/Authority Score), and both (DeMAND, Local Radiality). We present an integrative approach (the FocusHeuristics) that is thoroughly evaluated based on public expression data and molecular disease characteristics provided by DisGeNet. The FocusHeuristics combines three scores, i.e. the log fold change and another two, based on the sum and difference of log fold changes of genes/proteins linked in a network. A gene is kept when one of the scores to which it contributes is above a threshold. Our FocusHeuristics is both, a predictor for gene-disease-association and a bioinformatics method to reduce biological networks to their disease-relevant parts, by highlighting the dynamics observed in expression data. The FocusHeuristics is slightly, but significantly better than other methods by its more successful identification of disease-associated genes measured by AUC, and it delivers mechanistic explanations for its choice of genes.

Plasticity-Related Gene Expression During Eszopiclone-Induced Sleep.

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Gerashchenko, Dmitry; Pasumarthi, Ravi K; Kilduff, Thomas S

2017-07-01

Experimental evidence suggests that restorative processes depend on synaptic plasticity changes in the brain during sleep. We used the expression of plasticity-related genes to assess synaptic plasticity changes during drug-induced sleep. We first characterized sleep induced by eszopiclone in mice during baseline conditions and during the recovery from sleep deprivation. We then compared the expression of 18 genes and two miRNAs critically involved in synaptic plasticity in these mice. Gene expression was assessed in the cerebral cortex and hippocampus by the TaqMan reverse transcription polymerase chain reaction and correlated with sleep parameters. Eszopiclone reduced the latency to nonrapid eye movement (NREM) sleep and increased NREM sleep amounts. Eszopiclone had no effect on slow wave activity (SWA) during baseline conditions but reduced the SWA increase during recovery sleep (RS) after sleep deprivation. Gene expression analyses revealed three distinct patterns: (1) four genes had higher expression either in the cortex or hippocampus in the group of mice with increased amounts of wakefulness; (2) a large proportion of plasticity-related genes (7 out of 18 genes) had higher expression during RS in the cortex but not in the hippocampus; and (3) six genes and the two miRNAs showed no significant changes across conditions. Even at a relatively high dose (20 mg/kg), eszopiclone did not reduce the expression of plasticity-related genes during RS period in the cortex. These results indicate that gene expression associated with synaptic plasticity occurs in the cortex in the presence of a hypnotic medication. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

MacoNPV baculovirus midgut-specific gene expression during infection of the bertha armyworm, Mamestra configurata

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Donly, B. Cameron, E-mail: Cam.Donly@agr.gc.ca [London Research and Development Centre, AAFC, London, ON (Canada); Kaplanoglu, Emine [London Research and Development Centre, AAFC, London, ON (Canada); Theilmann, David A. [Summerland Research and Development Centre, AAFC, Summerland, BC (Canada); Baldwin, Doug; Sieminska, Edyta; Hegedus, Dwayne D.; Erlandson, Martin A. [Saskatoon Research and Development Centre, AAFC, Saskatoon, SK (Canada)

2016-12-15

Baculoviruses have two forms, occlusion derived virus (ODV) which is responsible for primary infection in host midgut tissue and budded virus (BV), which infects all other host tissues during secondary infection. This study examined the primary infection by ODV of midgut cells of bertha armyworm Mamestra configurata fourth instar larvae and measured the expression of viral genes over a time course of infection. Both digital PCR and RNA sequencing methods showed the profile of transcription to be different from those produced by AcMNPV BV infection of in vitro cell cultures. This included having unique collections of genes expressed early, as well as much greater late gene expression of p6.9 and much reduced expression of polh and p10. These differences likely reflect characteristics unique to the critical step of in vivo midgut cell infection, and provide insights into the processes that regulate viral gene expression in different host tissues. -- Highlights: •The transcriptome of MacoNPV ODV in larval midgut was measured by RNA-seq and digital PCR. •The earliest genes expressed included fusion protein, hoar, and me53. •p6.9 was highly expressed late but polH and p10 were less so. •These patterns are unique from BV of other baculoviruses in tissue culture cells.

MacoNPV baculovirus midgut-specific gene expression during infection of the bertha armyworm, Mamestra configurata

International Nuclear Information System (INIS)

Donly, B. Cameron; Kaplanoglu, Emine; Theilmann, David A.; Baldwin, Doug; Sieminska, Edyta; Hegedus, Dwayne D.; Erlandson, Martin A.

2016-01-01

Baculoviruses have two forms, occlusion derived virus (ODV) which is responsible for primary infection in host midgut tissue and budded virus (BV), which infects all other host tissues during secondary infection. This study examined the primary infection by ODV of midgut cells of bertha armyworm Mamestra configurata fourth instar larvae and measured the expression of viral genes over a time course of infection. Both digital PCR and RNA sequencing methods showed the profile of transcription to be different from those produced by AcMNPV BV infection of in vitro cell cultures. This included having unique collections of genes expressed early, as well as much greater late gene expression of p6.9 and much reduced expression of polh and p10. These differences likely reflect characteristics unique to the critical step of in vivo midgut cell infection, and provide insights into the processes that regulate viral gene expression in different host tissues. -- Highlights: •The transcriptome of MacoNPV ODV in larval midgut was measured by RNA-seq and digital PCR. •The earliest genes expressed included fusion protein, hoar, and me53. •p6.9 was highly expressed late but polH and p10 were less so. •These patterns are unique from BV of other baculoviruses in tissue culture cells.

Decoupling Linear and Nonlinear Associations of Gene Expression

KAUST Repository

Itakura, Alan

2013-05-01

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

Decoupling Linear and Nonlinear Associations of Gene Expression

KAUST Repository

Itakura, Alan

2013-01-01

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

Genetic architecture of gene expression in the chicken

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Stanley Dragana

2013-01-01

Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

Gene expression profile data for mouse facial development

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Sonia M. Leach

2017-08-01

Full Text Available This article contains data related to the research articles "Spatial and Temporal Analysis of Gene Expression during Growth and Fusion of the Mouse Facial Prominences" (Feng et al., 2009 [1] and “Systems Biology of facial development: contributions of ectoderm and mesenchyme” (Hooper et al., 2017 In press [2]. Embryonic mammalian craniofacial development is a complex process involving the growth, morphogenesis, and fusion of distinct facial prominences into a functional whole. Aberrant gene regulation during this process can lead to severe craniofacial birth defects, including orofacial clefting. As a means to understand the genes involved in facial development, we had previously dissected the embryonic mouse face into distinct prominences: the mandibular, maxillary or nasal between E10.5 and E12.5. The prominences were then processed intact, or separated into ectoderm and mesenchyme layers, prior analysis of RNA expression using microarrays (Feng et al., 2009, Hooper et al., 2017 in press [1,2]. Here, individual gene expression profiles have been built from these datasets that illustrate the timing of gene expression in whole prominences or in the separated tissue layers. The data profiles are presented as an indexed and clickable list of the genes each linked to a graphical image of that gene׳s expression profile in the ectoderm, mesenchyme, or intact prominence. These data files will enable investigators to obtain a rapid assessment of the relative expression level of any gene on the array with respect to time, tissue, prominence, and expression trajectory.

Integrated olfactory receptor and microarray gene expression databases

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Crasto Chiquito J

2007-06-01

Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

Gene expression analysis of flax seed development

Science.gov (United States)

2011-01-01

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

Gene expression analysis of flax seed development

Directory of Open Access Journals (Sweden)

Sharpe Andrew

2011-04-01

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

Evidence against the energetic cost hypothesis for the short introns in highly expressed genes

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Niu Deng-Ke

2008-05-01

Full Text Available Abstract Background In animals, the moss Physcomitrella patens and the pollen of Arabidopsis thaliana, highly expressed genes have shorter introns than weakly expressed genes. A popular explanation for this is selection for transcription efficiency, which includes two sub-hypotheses: to minimize the energetic cost or to minimize the time cost. Results In an individual human, different organs may differ up to hundreds of times in cell number (for example, a liver versus a hypothalamus. Considered at the individual level, a gene specifically expressed in a large organ is actually transcribed tens or hundreds of times more than a gene with a similar expression level (a measure of mRNA abundance per cell specifically expressed in a small organ. According to the energetic cost hypothesis, the former should have shorter introns than the latter. However, in humans and mice we have not found significant differences in intron length between large-tissue/organ-specific genes and small-tissue/organ-specific genes with similar expression levels. Qualitative estimation shows that the deleterious effect (that is, the energetic burden of long introns in highly expressed genes is too negligible to be efficiently selected against in mammals. Conclusion The short introns in highly expressed genes should not be attributed to energy constraint. We evaluated evidence for the time cost hypothesis and other alternatives.

Global gene expression in cotton (Gossypium hirsutum L. leaves to waterlogging stress.

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Yanjun Zhang

Full Text Available Cotton is sensitive to waterlogging stress, which usually results in stunted growth and yield loss. To date, the molecular mechanisms underlying the responses to waterlogging in cotton remain elusive. Cotton was grown in a rain-shelter and subjected to 0 (control-, 10-, 15- and 20-d waterlogging at flowering stage. The fourth-leaves on the main-stem from the top were sampled and immediately frozen in liquid nitrogen for physiological measurement. Global gene transcription in the leaves of 15-d waterlogged plants was analyzed by RNA-Seq. Seven hundred and ninety four genes were up-regulated and 1018 genes were down-regulated in waterlogged cotton leaves compared with non-waterlogged control. The differentially expressed genes were mainly related to photosynthesis, nitrogen metabolism, starch and sucrose metabolism, glycolysis and plant hormone signal transduction. KEGG (Kyoto Encyclopedia of Genes and Genomes analysis indicated that most genes related to flavonoid biosynthesis, oxidative phosphorylation, amino acid metabolism and biosynthesis as well as circadian rhythm pathways were differently expressed. Waterlogging increased the expression of anaerobic fermentation related genes, such as alcohol dehydrogenase (ADH, but decreased the leaf chlorophyll concentration and photosynthesis by down-regulating the expression of photosynthesis related genes. Many genes related to plant hormones and transcription factors were differently expressed under waterlogging stress. Most of the ethylene related genes and ethylene-responsive factor-type transcription factors were up-regulated under water-logging stress, suggesting that ethylene may play key roles in the survival of cotton under waterlogging stress.

Supplementary Material for: Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

KAUST Repository

Horiuchi, Youko; Harushima, Yoshiaki; Fujisawa, Hironori; Mochizuki, Takako; Fujita, Masahiro; Ohyanagi, Hajime; Kurata, Nori

2015-01-01

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

Sarcoptes scabiei mites modulate gene expression in human skin equivalents.

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Marjorie S Morgan

Full Text Available The ectoparasitic mite, Sarcoptes scabiei that burrows in the epidermis of mammalian skin has a long co-evolution with its hosts. Phenotypic studies show that the mites have the ability to modulate cytokine secretion and expression of cell adhesion molecules in cells of the skin and other cells of the innate and adaptive immune systems that may assist the mites to survive in the skin. The purpose of this study was to identify genes in keratinocytes and fibroblasts in human skin equivalents (HSEs that changed expression in response to the burrowing of live scabies mites. Overall, of the more than 25,800 genes measured, 189 genes were up-regulated >2-fold in response to scabies mite burrowing while 152 genes were down-regulated to the same degree. HSEs differentially expressed large numbers of genes that were related to host protective responses including those involved in immune response, defense response, cytokine activity, taxis, response to other organisms, and cell adhesion. Genes for the expression of interleukin-1α (IL-1α precursor, IL-1β, granulocyte/macrophage-colony stimulating factor (GM-CSF precursor, and G-CSF precursor were up-regulated 2.8- to 7.4-fold, paralleling cytokine secretion profiles. A large number of genes involved in epithelium development and keratinization were also differentially expressed in response to live scabies mites. Thus, these skin cells are directly responding as expected in an inflammatory response to products of the mites and the disruption of the skin's protective barrier caused by burrowing. This suggests that in vivo the interplay among these skin cells and other cell types, including Langerhans cells, dendritic cells, lymphocytes and endothelial cells, is responsible for depressing the host's protective response allowing these mites to survive in the skin.

Sarcoptes scabiei Mites Modulate Gene Expression in Human Skin Equivalents

Science.gov (United States)

Morgan, Marjorie S.; Arlian, Larry G.; Markey, Michael P.

2013-01-01

The ectoparasitic mite, Sarcoptes scabiei that burrows in the epidermis of mammalian skin has a long co-evolution with its hosts. Phenotypic studies show that the mites have the ability to modulate cytokine secretion and expression of cell adhesion molecules in cells of the skin and other cells of the innate and adaptive immune systems that may assist the mites to survive in the skin. The purpose of this study was to identify genes in keratinocytes and fibroblasts in human skin equivalents (HSEs) that changed expression in response to the burrowing of live scabies mites. Overall, of the more than 25,800 genes measured, 189 genes were up-regulated >2-fold in response to scabies mite burrowing while 152 genes were down-regulated to the same degree. HSEs differentially expressed large numbers of genes that were related to host protective responses including those involved in immune response, defense response, cytokine activity, taxis, response to other organisms, and cell adhesion. Genes for the expression of interleukin-1α (IL-1α) precursor, IL-1β, granulocyte/macrophage-colony stimulating factor (GM-CSF) precursor, and G-CSF precursor were up-regulated 2.8- to 7.4-fold, paralleling cytokine secretion profiles. A large number of genes involved in epithelium development and keratinization were also differentially expressed in response to live scabies mites. Thus, these skin cells are directly responding as expected in an inflammatory response to products of the mites and the disruption of the skin’s protective barrier caused by burrowing. This suggests that in vivo the interplay among these skin cells and other cell types, including Langerhans cells, dendritic cells, lymphocytes and endothelial cells, is responsible for depressing the host’s protective response allowing these mites to survive in the skin. PMID:23940705

Identification of suitable reference genes for gene expression studies of shoulder instability.

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Mariana Ferreira Leal

Full Text Available Shoulder instability is a common shoulder injury, and patients present with plastic deformation of the glenohumeral capsule. Gene expression analysis may be a useful tool for increasing the general understanding of capsule deformation, and reverse-transcription quantitative polymerase chain reaction (RT-qPCR has become an effective method for such studies. Although RT-qPCR is highly sensitive and specific, it requires the use of suitable reference genes for data normalization to guarantee meaningful and reproducible results. In the present study, we evaluated the suitability of a set of reference genes using samples from the glenohumeral capsules of individuals with and without shoulder instability. We analyzed the expression of six commonly used reference genes (ACTB, B2M, GAPDH, HPRT1, TBP and TFRC in the antero-inferior, antero-superior and posterior portions of the glenohumeral capsules of cases and controls. The stability of the candidate reference gene expression was determined using four software packages: NormFinder, geNorm, BestKeeper and DataAssist. Overall, HPRT1 was the best single reference gene, and HPRT1 and B2M composed the best pair of reference genes from different analysis groups, including simultaneous analysis of all tissue samples. GenEx software was used to identify the optimal number of reference genes to be used for normalization and demonstrated that the accumulated standard deviation resulting from the use of 2 reference genes was similar to that resulting from the use of 3 or more reference genes. To identify the optimal combination of reference genes, we evaluated the expression of COL1A1. Although the use of different reference gene combinations yielded variable normalized quantities, the relative quantities within sample groups were similar and confirmed that no obvious differences were observed when using 2, 3 or 4 reference genes. Consequently, the use of 2 stable reference genes for normalization, especially

Meta-analysis of differentiating mouse embryonic stem cell gene expression kinetics reveals early change of a small gene set.

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Clive H Glover

2006-11-01

Full Text Available Stem cell differentiation involves critical changes in gene expression. Identification of these should provide endpoints useful for optimizing stem cell propagation as well as potential clues about mechanisms governing stem cell maintenance. Here we describe the results of a new meta-analysis methodology applied to multiple gene expression datasets from three mouse embryonic stem cell (ESC lines obtained at specific time points during the course of their differentiation into various lineages. We developed methods to identify genes with expression changes that correlated with the altered frequency of functionally defined, undifferentiated ESC in culture. In each dataset, we computed a novel statistical confidence measure for every gene which captured the certainty that a particular gene exhibited an expression pattern of interest within that dataset. This permitted a joint analysis of the datasets, despite the different experimental designs. Using a ranking scheme that favored genes exhibiting patterns of interest, we focused on the top 88 genes whose expression was consistently changed when ESC were induced to differentiate. Seven of these (103728_at, 8430410A17Rik, Klf2, Nr0b1, Sox2, Tcl1, and Zfp42 showed a rapid decrease in expression concurrent with a decrease in frequency of undifferentiated cells and remained predictive when evaluated in additional maintenance and differentiating protocols. Through a novel meta-analysis, this study identifies a small set of genes whose expression is useful for identifying changes in stem cell frequencies in cultures of mouse ESC. The methods and findings have broader applicability to understanding the regulation of self-renewal of other stem cell types.

Detecting microRNA activity from gene expression data

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Madden, Stephen F

2010-05-18

Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Detecting microRNA activity from gene expression data.

LENUS (Irish Health Repository)

Madden, Stephen F

2010-01-01

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes

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Øvstebø Reidun

2010-05-01

Full Text Available Abstract Background Gene expression in lipopolysaccharide (LPS-stimulated monocytes is mainly studied by quantitative real-time reverse transcription PCR (RT-qPCR using GAPDH (glyceraldehyde 3-phosphate dehydrogenase or ACTB (beta-actin as reference gene for normalization. Expression of traditional reference genes has been shown to vary substantially under certain conditions leading to invalid results. To investigate whether traditional reference genes are stably expressed in LPS-stimulated monocytes or if RT-qPCR results are dependent on the choice of reference genes, we have assessed and evaluated gene expression stability of twelve candidate reference genes in this model system. Results Twelve candidate reference genes were quantified by RT-qPCR in LPS-stimulated, human monocytes and evaluated using the programs geNorm, Normfinder and BestKeeper. geNorm ranked PPIB (cyclophilin B, B2M (beta-2-microglobulin and PPIA (cyclophilin A as the best combination for gene expression normalization in LPS-stimulated monocytes. Normfinder suggested TBP (TATA-box binding protein and B2M as the best combination. Compared to these combinations, normalization using GAPDH alone resulted in significantly higher changes of TNF-α (tumor necrosis factor-alpha and IL10 (interleukin 10 expression. Moreover, a significant difference in TNF-α expression between monocytes stimulated with equimolar concentrations of LPS from N. meningitides and E. coli, respectively, was identified when using the suggested combinations of reference genes for normalization, but stayed unrecognized when employing a single reference gene, ACTB or GAPDH. Conclusions Gene expression levels in LPS-stimulated monocytes based on RT-qPCR results differ significantly when normalized to a single gene or a combination of stably expressed reference genes. Proper evaluation of reference gene stabiliy is therefore mandatory before reporting RT-qPCR results in LPS-stimulated monocytes.

Differentially expressed genes in iron-induced prion protein conversion

International Nuclear Information System (INIS)

Kim, Minsun; Kim, Eun-hee; Choi, Bo-Ran; Woo, Hee-Jong

2016-01-01

The conversion of the cellular prion protein (PrP C ) to the protease-resistant isoform is the key event in chronic neurodegenerative diseases, including transmissible spongiform encephalopathies (TSEs). Increased iron in prion-related disease has been observed due to the prion protein-ferritin complex. Additionally, the accumulation and conversion of recombinant PrP (rPrP) is specifically derived from Fe(III) but not Fe(II). Fe(III)-mediated PK-resistant PrP (PrP res ) conversion occurs within a complex cellular environment rather than via direct contact between rPrP and Fe(III). In this study, differentially expressed genes correlated with prion degeneration by Fe(III) were identified using Affymetrix microarrays. Following Fe(III) treatment, 97 genes were differentially expressed, including 85 upregulated genes and 12 downregulated genes (≥1.5-fold change in expression). However, Fe(II) treatment produced moderate alterations in gene expression without inducing dramatic alterations in gene expression profiles. Moreover, functional grouping of identified genes indicated that the differentially regulated genes were highly associated with cell growth, cell maintenance, and intra- and extracellular transport. These findings showed that Fe(III) may influence the expression of genes involved in PrP folding by redox mechanisms. The identification of genes with altered expression patterns in neural cells may provide insights into PrP conversion mechanisms during the development and progression of prion-related diseases. - Highlights: • Differential genes correlated with prion degeneration by Fe(III) were identified. • Genes were identified in cell proliferation and intra- and extracellular transport. • In PrP degeneration, redox related genes were suggested. • Cbr2, Rsad2, Slc40a1, Amph and Mvd were expressed significantly.

Regulation of meiotic gene expression in plants

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Adele eZhou

2014-08-01

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

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

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Tintle Nathan L

2012-08-01

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

Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease.

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Peter R Sinnaeve

Full Text Available Systemic and local inflammation plays a prominent role in the pathogenesis of atherosclerotic coronary artery disease, but the relationship of whole blood gene expression changes with coronary disease remains unclear. We have investigated whether gene expression patterns in peripheral blood correlate with the severity of coronary disease and whether these patterns correlate with the extent of atherosclerosis in the vascular wall. Patients were selected according to their coronary artery disease index (CADi, a validated angiographical measure of the extent of coronary atherosclerosis that correlates with outcome. RNA was extracted from blood of 120 patients with at least a stenosis greater than 50% (CADi > or = 23 and from 121 controls without evidence of coronary stenosis (CADi = 0. 160 individual genes were found to correlate with CADi (rho > 0.2, P<0.003. Prominent differential expression was observed especially in genes involved in cell growth, apoptosis and inflammation. Using these 160 genes, a partial least squares multivariate regression model resulted in a highly predictive model (r(2 = 0.776, P<0.0001. The expression pattern of these 160 genes in aortic tissue also predicted the severity of atherosclerosis in human aortas, showing that peripheral blood gene expression associated with coronary atherosclerosis mirrors gene expression changes in atherosclerotic arteries. In conclusion, the simultaneous expression pattern of 160 genes in whole blood correlates with the severity of coronary artery disease and mirrors expression changes in the atherosclerotic vascular wall.

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

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Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

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Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Novel gene sets improve set-level classification of prokaryotic gene expression data.

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Holec, Matěj; Kuželka, Ondřej; Železný, Filip

2015-10-28

Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

Gene expression analysis of FABP4 in gastric cancer

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Abdulkarim Yasin Karim

2016-06-01

Full Text Available Purpose: Gastric cancer has high incidence and mortality rate in several countries and is still one of the most frequent and lethal disease. In this study, we aimed to determine diagnostic markers in gastric cancer by molecular techniques; include mRNA expression analysis of FABP4 gene. Fatty acid binding protein 4 (FABP4 gene encodes the fatty acid binding protein found in adipocytes. The protein encoded by FABP4 are a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. Material and Methods: Total RNA were extracted from paired tumor and normal tissues of 47 gastric cancer. The mRNA expression level of FABP4 was measured employing semi- quantitative reverse transcription- polymerase chain reaction (RT- PCR. Results: The mRNA expression level of FABP4 was significantly decreased (down- regulated. Conclusion: Down-regulation of FABP4 gene seems to occur at the initial steps of gastric cancer development. In order to confirm the relationship between the gastric tumor and FABP4 gene, further analysis like immunohistochemistry and epigenetc techniques are necessary. [Cukurova Med J 2016; 41(2.000: 248-252

Differential neutrophil gene expression in early bovine pregnancy

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Kizaki Keiichiro

2013-02-01

Full Text Available Abstract Background In food production animals, especially cattle, the diagnosis of gestation is important because the timing of gestation directly affects the running of farms. Various methods have been used to detect gestation, but none of them are ideal because of problems with the timing of detection or the accuracy, simplicity, or cost of the method. A new method for detecting gestation, which involves assessing interferon-tau (IFNT-stimulated gene expression in peripheral blood leukocytes (PBL, was recently proposed. PBL fractionation methods were used to examine whether the expression profiles of various PBL populations could be used as reliable diagnostic markers of bovine gestation. Methods PBL were collected on days 0 (just before artificial insemination, 7, 14, 17, 21, and 28 of gestation. The gene expression levels of the PBL were assessed with microarray analysis and/or quantitative real-time reverse transcription (q PCR. PBL fractions were collected by flow cytometry or density gradient cell separation using Histopaque 1083 or Ficoll-Conray solutions. The expression levels of four IFNT-stimulated genes, interferon-stimulated protein 15 kDa (ISG15, myxovirus-resistance (MX 1 and 2, and 2′-5′-oligoadenylate synthetase (OAS1, were then analyzed in each fraction through day 28 of gestation using qPCR. Results Microarray analysis detected 72 and 28 genes in whole PBL that were significantly higher on days 14 and 21 of gestation, respectively, than on day 0. The upregulated genes included IFNT-stimulated genes. The expression levels of these genes increased with the progression of gestation until day 21. In flow cytometry experiments, on day 14 the expression levels of all of the genes were significantly higher in the granulocyte fraction than in the other fractions. Their expression gradually decreased through day 28 of gestation. Strong correlations were observed between the expression levels of the four genes in the granulocyte

Selective modes determine evolutionary rates, gene compactness and expression patterns in Brassica.

Science.gov (United States)

Guo, Yue; Liu, Jing; Zhang, Jiefu; Liu, Shengyi; Du, Jianchang

2017-07-01

It has been well documented that most nuclear protein-coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K a ) and the rates of synonymous substitution (K s ) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue-specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K a /K s ), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Expression and functional assessment of candidate type 2 diabetes susceptibility genes identify four new genes contributing to human insulin secretion

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Fatou K. Ndiaye

2017-06-01

Full Text Available Objectives: Genome-wide association studies (GWAS have identified >100 loci independently contributing to type 2 diabetes (T2D risk. However, translational implications for precision medicine and for the development of novel treatments have been disappointing, due to poor knowledge of how these loci impact T2D pathophysiology. Here, we aimed to measure the expression of genes located nearby T2D associated signals and to assess their effect on insulin secretion from pancreatic beta cells. Methods: The expression of 104 candidate T2D susceptibility genes was measured in a human multi-tissue panel, through PCR-free expression assay. The effects of the knockdown of beta-cell enriched genes were next investigated on insulin secretion from the human EndoC-βH1 beta-cell line. Finally, we performed RNA-sequencing (RNA-seq so as to assess the pathways affected by the knockdown of the new genes impacting insulin secretion from EndoC-βH1, and we analyzed the expression of the new genes in mouse models with altered pancreatic beta-cell function. Results: We found that the candidate T2D susceptibility genes' expression is significantly enriched in pancreatic beta cells obtained by laser capture microdissection or sorted by flow cytometry and in EndoC-βH1 cells, but not in insulin sensitive tissues. Furthermore, the knockdown of seven T2D-susceptibility genes (CDKN2A, GCK, HNF4A, KCNK16, SLC30A8, TBC1D4, and TCF19 with already known expression and/or function in beta cells changed insulin secretion, supporting our functional approach. We showed first evidence for a role in insulin secretion of four candidate T2D-susceptibility genes (PRC1, SRR, ZFAND3, and ZFAND6 with no previous knowledge of presence and function in beta cells. RNA-seq in EndoC-βH1 cells with decreased expression of PRC1, SRR, ZFAND6, or ZFAND3 identified specific gene networks related to T2D pathophysiology. Finally, a positive correlation between the expression of Ins2 and the

Validation of suitable reference genes for quantitative gene expression analysis in Panax ginseng

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Meizhen eWang

2016-01-01

Full Text Available Reverse transcription-qPCR (RT-qPCR has become a popular method for gene expression studies. Its results require data normalization by housekeeping genes. No single gene is proved to be stably expressed under all experimental conditions. Therefore, systematic evaluation of reference genes is necessary. With the aim to identify optimum reference genes for RT-qPCR analysis of gene expression in different tissues of Panax ginseng and the seedlings grown under heat stress, we investigated the expression stability of eight candidate reference genes, including elongation factor 1-beta (EF1-β, elongation factor 1-gamma (EF1-γ, eukaryotic translation initiation factor 3G (IF3G, eukaryotic translation initiation factor 3B (IF3B, actin (ACT, actin11 (ACT11, glyceraldehyde-3-phosphate dehydrogenase (GAPDH and cyclophilin ABH-like protein (CYC, using four widely used computational programs: geNorm, Normfinder, BestKeeper, and the comparative ΔCt method. The results were then integrated using the web-based tool RefFinder. As a result, EF1-γ, IF3G and EF1-β were the three most stable genes in different tissues of P. ginseng, while IF3G, ACT11 and GAPDH were the top three-ranked genes in seedlings treated with heat. Using three better reference genes alone or in combination as internal control, we examined the expression profiles of MAR, a multiple function-associated mRNA-like non-coding RNA (mlncRNA in P. ginseng. Taken together, we recommended EF1-γ/IF3G and IF3G/ACT11 as the suitable pair of reference genes for RT-qPCR analysis of gene expression in different tissues of P. ginseng and the seedlings grown under heat stress, respectively. The results serve as a foundation for future studies on P. ginseng functional genomics.

Identification of differentially expressed genes in flax (Linum usitatissimum L.) under saline-alkaline stress by digital gene expression.

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Yu, Ying; Huang, Wengong; Chen, Hongyu; Wu, Guangwen; Yuan, Hongmei; Song, Xixia; Kang, Qinghua; Zhao, Dongsheng; Jiang, Weidong; Liu, Yan; Wu, Jianzhong; Cheng, Lili; Yao, Yubo; Guan, Fengzhi

2014-10-01

The salinization and alkalization of soil are widespread environmental problems, and alkaline salt stress is more destructive than neutral salt stress. Therefore, understanding the mechanism of plant tolerance to saline-alkaline stress has become a major challenge. However, little attention has been paid to the mechanism of plant alkaline salt tolerance. In this study, gene expression profiling of flax was analyzed under alkaline-salt stress (AS2), neutral salt stress (NSS) and alkaline stress (AS) by digital gene expression. Three-week-old flax seedlings were placed in 25 mM Na2CO3 (pH11.6) (AS2), 50mM NaCl (NSS) and NaOH (pH11.6) (AS) for 18 h. There were 7736, 1566 and 454 differentially expressed genes in AS2, NSS and AS compared to CK, respectively. The GO category gene enrichment analysis revealed that photosynthesis was particularly affected in AS2, carbohydrate metabolism was particularly affected in NSS, and the response to biotic stimulus was particularly affected in AS. We also analyzed the expression pattern of five categories of genes including transcription factors, signaling transduction proteins, phytohormones, reactive oxygen species proteins and transporters under these three stresses. Some key regulatory gene families involved in abiotic stress, such as WRKY, MAPKKK, ABA, PrxR and ion channels, were differentially expressed. Compared with NSS and AS, AS2 triggered more differentially expressed genes and special pathways, indicating that the mechanism of AS2 was more complex than NSS and AS. To the best of our knowledge, this was the first transcriptome analysis of flax in response to saline-alkaline stress. These data indicate that common and diverse features of saline-alkaline stress provide novel insights into the molecular mechanisms of plant saline-alkaline tolerance and offer a number of candidate genes as potential markers of tolerance to saline-alkaline stress. Copyright © 2014 Elsevier B.V. All rights reserved.

Housekeeping genes for quantitative expression studies in the three-spined stickleback Gasterosteus aculeatus

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Becker Sven

2008-01-01

Full Text Available Abstract Background During the last years the quantification of immune response under immunological challenges, e.g. parasitation, has been a major focus of research. In this context, the expression of immune response genes in teleost fish has been surveyed for scientific and commercial purposes. Despite the fact that it was shown in teleostei and other taxa that the gene for beta-actin is not the most stably expressed housekeeping gene (HKG, depending on the tissue and experimental treatment, the gene has been used as a reference gene in such studies. In the three-spined stickleback, Gasterosteus aculeatus, other HKG than the one for beta-actin have not been established so far. Results To establish a reliable method for the measurement of immune gene expression in Gasterosteus aculeatus, sequences from the now available genome database and an EST library of the same species were used to select oligonucleotide primers for HKG, in order to perform quantitative reverse-transcription (RT PCR. The expression stability of ten candidate reference genes was evaluated in three different tissues, and in five parasite treatment groups, using the three algorithms BestKeeper, geNorm and NormFinder. Our results showed that in most of the tissues and treatments HKG that could not be used so far due to unknown sequences, proved to be more stably expressed than the one for beta-actin. Conclusion As they were the most stably expressed genes in all tissues examined, we suggest using the genes for the L13a ribosomal binding protein and ubiquitin as alternative or additional reference genes in expression analysis in Gasterosteus aculeatus.

Induction of UMUC+ gene expression in Escherichia coli irradiated by near ultraviolet light

International Nuclear Information System (INIS)

Sato, N.; Ohnishi, T.; Tano, K.; Nozu, K.; Yamamoto, K.

1985-01-01

The induction of umu + gene expression caused by irradiation with near ultraviolet light (BLB; black light blue) was studied in Escherichia coli K-12 strains with special reference to the effects of SOS repair deficiencies. The umuC + gene expression was measured as the enzymic activity of β-galactosidase which is regulated by the promoter of the umuC + operon carried in a plasmid DNA carrying a promoter of umuC + operon, a umuD + gene and a umuC + -lacZ + gene fusion. A high induction of the umuC + gene expression was observed in the uvrA cells in the case of BLB or UV irradiation as compared with the parental wild-type cells. Caffeine inhibited the induction of the umuC + gene expression due to BLB or UV irradiation in both strains. There was very little induction in lexA and recA mutants. In contrast with UV irradiation, there was no killing of cells by BLB irradiation in any strain (wild, uvrA, lexA and recA). Possible implications of the experimental results were discussed. (author)

Improved gene expression signature of testicular carcinoma in situ

DEFF Research Database (Denmark)

Almstrup, Kristian; Leffers, Henrik; Lothe, Ragnhild A

2007-01-01

on global gene expression in testicular CIS have been previously published. We have merged the two data sets on CIS samples (n = 6) and identified the shared gene expression signature in relation to expression in normal testis. Among the top-20 highest expressed genes, one-third was transcription factors...... development' were significantly altered and could collectively affect cellular pathways like the WNT signalling cascade, which thus may be disrupted in testicular CIS. The merged CIS data from two different microarray platforms, to our knowledge, provide the most precise CIS gene expression signature to date....

Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis.

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Ang Cui

Full Text Available Gene expression-based signatures help identify pathways relevant to diseases and treatments, but are challenging to construct when there is a diversity of disease mechanisms and treatments in patients with complex diseases. To overcome this challenge, we present a new application of an in silico gene expression deconvolution method, ISOpure-S1, and apply it to identify a common gene expression signature corresponding to response to treatment in 33 juvenile idiopathic arthritis (JIA patients. Using pre- and post-treatment gene expression profiles only, we found a gene expression signature that significantly correlated with a reduction in the number of joints with active arthritis, a measure of clinical outcome (Spearman rho = 0.44, p = 0.040, Bonferroni correction. This signature may be associated with a decrease in T-cells, monocytes, neutrophils and platelets. The products of most differentially expressed genes include known biomarkers for JIA such as major histocompatibility complexes and interleukins, as well as novel biomarkers including α-defensins. This method is readily applicable to expression datasets of other complex diseases to uncover shared mechanistic patterns in heterogeneous samples.

The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

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Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

2011-02-01

The gonadal soma-derived factor (GSDF) belongs to the transforming growth factor-β superfamily and is conserved in teleostean fish species. Gsdf is specifically expressed in the gonads, and gene expression is restricted to the granulosa and Sertoli cells in trout and medaka. The gsdf gene expression is correlated to early testis differentiation in medaka and was shown to stimulate primordial germ cell and spermatogonia proliferation in trout. In the present study, we show that the gsdf gene localizes to a syntenic chromosomal fragment conserved among vertebrates although no gsdf-related gene is detected on the corresponding genomic region in tetrapods. We demonstrate using quantitative RT-PCR that most of the genes localized in the synteny are specifically expressed in medaka gonads. Gsdf is the only gene of the synteny with a much higher expression in the testis compared to the ovary. In contrast, gene expression pattern analysis of the gsdf surrounding genes (nup54, aff1, klhl8, sdad1, and ptpn13) indicates that these genes are preferentially expressed in the female gonads. The tissue distribution of these genes is highly similar in medaka and zebrafish, two teleostean species that have diverged more than 110 million years ago. The cellular localization of these genes was determined in medaka gonads using the whole-mount in situ hybridization technique. We confirm that gsdf gene expression is restricted to Sertoli and granulosa cells in contact with the premeiotic and meiotic cells. The nup54 gene is expressed in spermatocytes and previtellogenic oocytes. Transcripts corresponding to the ovary-specific genes (aff1, klhl8, and sdad1) are detected only in previtellogenic oocytes. No expression was detected in the gonocytes in 10 dpf embryos. In conclusion, we show that the gsdf gene localizes to a syntenic chromosomal fragment harboring evolutionary conserved genes in vertebrates. These genes are preferentially expressed in previtelloogenic oocytes, and thus, they

Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.

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Neutelings Godfrey

2010-04-01

Full Text Available Abstract Background Quantitative real-time PCR (qRT-PCR is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs. Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L. Results Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups. qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59. LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both ge

Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.).

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Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

2010-04-19

Quantitative real-time PCR (qRT-PCR) is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs). Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L). Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs) and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH) as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups.qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59). LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both geNorm-designated- and Norm

Growth hormone regulation of metabolic gene expression in muscle: a microarray study in hypopituitary men.

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Sjögren, Klara; Leung, Kin-Chuen; Kaplan, Warren; Gardiner-Garden, Margaret; Gibney, James; Ho, Ken K Y

2007-07-01

Muscle is a target of growth hormone (GH) action and a major contributor to whole body metabolism. Little is known about how GH regulates metabolic processes in muscle or the extent to which muscle contributes to changes in whole body substrate metabolism during GH treatment. To identify GH-responsive genes that regulate substrate metabolism in muscle, we studied six hypopituitary men who underwent whole body metabolic measurement and skeletal muscle biopsies before and after 2 wk of GH treatment (0.5 mg/day). Transcript profiles of four subjects were analyzed using Affymetrix GeneChips. Serum insulin-like growth factor I (IGF-I) and procollagens I and III were measured by RIA. GH increased serum IGF-I and procollagens I and III, enhanced whole body lipid oxidation, reduced carbohydrate oxidation, and stimulated protein synthesis. It induced gene expression of IGF-I and collagens in muscle. GH reduced expression of several enzymes regulating lipid oxidation and energy production. It reduced calpain 3, increased ribosomal protein L38 expression, and displayed mixed effects on genes encoding myofibrillar proteins. It increased expression of circadian gene CLOCK, and reduced that of PERIOD. In summary, GH exerted concordant effects on muscle expression and blood levels of IGF-I and collagens. It induced changes in genes regulating protein metabolism in parallel with a whole body anabolic effect. The discordance between muscle gene expression profiles and metabolic responses suggests that muscle is unlikely to contribute to GH-induced stimulation of whole body energy and lipid metabolism. GH may regulate circadian function in skeletal muscle by modulating circadian gene expression with possible metabolic consequences.

The Medicago truncatula gene expression atlas web server

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Tang Yuhong

2009-12-01

Full Text Available Abstract Background Legumes (Leguminosae or Fabaceae play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA web server for this purpose. Description The Medicago truncatula Gene Expression Atlas (MtGEA web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible

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

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Simone de Jong

Full Text Available Despite large-scale genome-wide association studies (GWAS, the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1, is located in, and regulated by the major histocompatibility (MHC complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.

Multiplex preamplification of specific cDNA targets prior to gene expression analysis by TaqMan Arrays

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Ribal María

2008-06-01

Full Text Available Abstract Background An accurate gene expression quantification using TaqMan Arrays (TA could be limited by the low RNA quantity obtained from some clinical samples. The novel cDNA preamplification system, the TaqMan PreAmp Master Mix kit (TPAMMK, enables a multiplex preamplification of cDNA targets and therefore, could provide a sufficient amount of specific amplicons for their posterior analysis on TA. Findings A multiplex preamplification of 47 genes was performed in 22 samples prior to their analysis by TA, and relative gene expression levels of non-preamplified (NPA and preamplified (PA samples were compared. Overall, the mean cycle threshold (CT decrement in the PA genes was 3.85 (ranging from 2.07 to 5.01. A high correlation (r between the gene expression measurements of NPA and PA samples was found (mean r = 0.970, ranging from 0.937 to 0.994; p Conclusion We demonstrate that cDNA preamplification using the TPAMMK before TA analysis is a reliable approach to simultaneously measure gene expression of multiple targets in a single sample. Moreover, this procedure was validated in genes from degraded RNA samples and low abundance expressed genes. This combined methodology could have wide applications in clinical research, where scarce amounts of degraded RNA are usually obtained and several genes need to be quantified in each sample.

Gene expression in peripheral immune cells following cardioembolic stroke is sexually dimorphic.

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Boryana Stamova

Full Text Available Epidemiological studies suggest that sex has a role in the pathogenesis of cardioembolic stroke. Since stroke is a vascular disease, identifying sexually dimorphic gene expression changes in blood leukocytes can inform on sex-specific risk factors, response and outcome biology. We aimed to examine the sexually dimorphic immune response following cardioembolic stroke by studying the differential gene expression in peripheral white blood cells.Blood samples from patients with cardioembolic stroke were obtained at ≤3 hours (prior to treatment, 5 hours and 24 hours (after treatment after stroke onset (n = 23; 69 samples and compared with vascular risk factor controls without symptomatic vascular diseases (n = 23, 23 samples (ANCOVA, false discovery rate p≤0.05, |fold change| ≥1.2. mRNA levels were measured on whole-genome Affymetrix microarrays. There were more up-regulated than down-regulated genes in both sexes, and females had more differentially expressed genes than males following cardioembolic stroke. Female gene expression was associated with cell death and survival, cell-cell signaling and inflammation. Male gene expression was associated with cellular assembly, organization and compromise. Immune response pathways were over represented at ≤3, 5 and 24 h after stroke in female subjects but only at 24 h in males. Neutrophil-specific genes were differentially expressed at 3, 5 and 24 h in females but only at 5 h and 24 h in males.There are sexually dimorphic immune cell expression profiles following cardioembolic stroke. Future studies are needed to confirm the findings using qRT-PCR in an independent cohort, to determine how they relate to risk and outcome, and to compare to other causes of ischemic stroke.

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

KAUST Repository

Abusamra, Heba

2016-07-20

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

Positron emission tomography imaging of gene expression

International Nuclear Information System (INIS)

Tang Ganghua

2001-01-01

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

Understanding gene expression in coronary artery disease through ...

Indian Academy of Sciences (India)

Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes. Prathima ... Table 2. Differentially expressed genes in CAD compared to age and gender matched controls. .... Regulation of nuclear pre-mRNA domain containing 1A.

A GMM-IG framework for selecting genes as expression panel biomarkers.

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Wang, Mingyi; Chen, Jake Y

2010-01-01

The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies. We developed a new framework, Gaussian Mixture Modeling-Coupled Information Gain (GMM-IG). In this framework, we first apply a two-component Gaussian mixture model (GMM) to estimate the conditional probability distributions of gene expression data between two different types of samples, for example, normal versus cancer. An expectation-maximization algorithm is then used to estimate the maximum likelihood parameters of a mixture of two Gaussian models in the feature space and determine the underlying expression levels of genes. Gene expression results from different studies are discretized, based on GMM estimations and then unified. Significantly differentially-expressed genes are filtered and assessed with information gain (IG) measures. DNA microarray experimental data for lung cancers from three different prior studies was processed using the new GMM-IG method. Target gene markers from a gene expression panel were selected and compared with several conventional computational biomarker data analysis methods. GMM-IG showed consistently high accuracy for several classification assessments. A high reproducibility of gene selection results was also determined from statistical validations. Our study shows that the GMM-IG framework can overcome poor reliability issues from single-study DNA microarray experiment while maintaining high accuracies by combining true signals from multiple studies. We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple

Gene expression profile of pulpitis.

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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.

Mel-18, a mammalian Polycomb gene, regulates angiogenic gene expression of endothelial cells.

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Jung, Ji-Hye; Choi, Hyun-Jung; Maeng, Yong-Sun; Choi, Jung-Yeon; Kim, Minhyung; Kwon, Ja-Young; Park, Yong-Won; Kim, Young-Myeong; Hwang, Daehee; Kwon, Young-Guen

2010-10-01

Mel-18 is a mammalian homolog of Polycomb group (PcG) genes. Microarray analysis revealed that Mel-18 expression was induced during endothelial progenitor cell (EPC) differentiation and correlates with the expression of EC-specific protein markers. Overexpression of Mel-18 promoted EPC differentiation and angiogenic activity of ECs. Accordingly, silencing Mel-18 inhibited EC migration and tube formation in vitro. Gene expression profiling showed that Mel-18 regulates angiogenic genes including kinase insert domain receptor (KDR), claudin 5, and angiopoietin-like 2. Our findings demonstrate, for the first time, that Mel-18 plays a significant role in the angiogenic function of ECs by regulating endothelial gene expression. Copyright © 2010 Elsevier Inc. All rights reserved.

Temporal course of gene expression during motor memory formation in primary motor cortex of rats.

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Hertler, B; Buitrago, M M; Luft, A R; Hosp, J A

2016-12-01

Motor learning is associated with plastic reorganization of neural networks in primary motor cortex (M1) that depends on changes in gene expression. Here, we investigate the temporal profile of these changes during motor memory formation in response to a skilled reaching task in rats. mRNA-levels were measured 1h, 7h and 24h after the end of a training session using microarray technique. To assure learning specificity, trained animals were compared to a control group. In response to motor learning, genes are sequentially regulated with high time-point specificity and a shift from initial suppression to later activation. The majority of regulated genes can be linked to learning-related plasticity. In the gene-expression cascade following motor learning, three different steps can be defined: (1) an initial suppression of genes influencing gene transcription. (2) Expression of genes that support translation of mRNA in defined compartments. (3) Expression of genes that immediately mediates plastic changes. Gene expression peaks after 24h - this is a much slower time-course when compared to hippocampus-dependent learning, where peaks of gene-expression can be observed 6-12h after training ended. Copyright © 2016 Elsevier Inc. All rights reserved.

Gene Expression Omnibus (GEO)

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

GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

Science.gov (United States)

Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

2016-12-05

subnetwork identification algorithms. The two searching algorithms resulted in better classification and gene/gene-set agreement compared to the original greedy search of the GNFS method. The identified lung cancer subnetwork using the proposed searching algorithm resulted in an improvement of the cross-dataset validation and an increase in the consistency of findings between two independent datasets. The homogeneity measurement of the datasets was conducted to assess dataset compatibility in cross-dataset validation. The lung cancer dataset with higher homogeneity showed a better result when using the GS search while the dataset with low homogeneity showed a better result when using the PN search. The 10-fold cross-dataset validation on the independent lung cancer datasets showed higher classification performance of the proposed algorithms when compared with the greedy search in the original GNFS method. The proposed searching algorithms provide a higher number of genes in the subnetwork expansion step than the greedy algorithm. As a result, the performance of the subnetworks identified from the GSNFS method was improved in terms of classification performance and gene/gene-set level agreement depending on the homogeneity of the datasets used in the analysis. Some common genes obtained from the four datasets using different searching algorithms are genes known to play a role in lung cancer. The improvement of classification performance and the gene/gene-set level agreement, and the biological relevance indicated the effectiveness of the GSNFS method for gene subnetwork identification using expression data.

Validation of endogenous normalizing genes for expression analyses in adult human testis and germ cell neoplasms.

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Svingen, T; Jørgensen, A; Rajpert-De Meyts, E

2014-08-01

The measurement of gene expression levels in cells and tissues typically depends on a suitable point of reference for inferring biological relevance. For quantitative (or real-time) RT-PCR assays, the method of choice is often to normalize gene expression data to an endogenous gene that is stably expressed across the samples analysed: a so-called normalizing or housekeeping gene. Although this is a valid strategy, the identification of stable normalizing genes has proved challenging and a gene showing stable expression across all cells or tissues is unlikely to exist. Therefore, it is necessary to define suitable normalizing genes for specific cells and tissues. Here, we report on the performance of a panel of nine commonly employed normalizing genes in adult human testis and testicular pathologies. Our analyses revealed significant variability in transcript abundance for commonly used normalizers, highlighting the importance of selecting appropriate normalizing genes as comparative measurements can yield variable results when different normalizing genes are employed. Based on our results, we recommend using RPS20, RPS29 or SRSF4 when analysing relative gene expression levels in human testis and associated testicular pathologies. OCT4 and SALL4 can be used with caution as second-tier normalizers when determining changes in gene expression in germ cells and germ cell tumour components, but the relative transcript abundance appears variable between different germ cell tumour types. We further recommend that such studies should be accompanied by additional assessment of histology and cellularity of each sample. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

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Marsico, Annalisa

2013-01-01

Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

Science.gov (United States)

Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

2013-09-01

The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

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

Directory of Open Access Journals (Sweden)

Turner Renee J

2009-08-01

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

Validation of reference genes for quantifying changes in gene expression in virus-infected tobacco.

Science.gov (United States)

Baek, Eseul; Yoon, Ju-Yeon; Palukaitis, Peter

2017-10-01

To facilitate quantification of gene expression changes in virus-infected tobacco plants, eight housekeeping genes were evaluated for their stability of expression during infection by one of three systemically-infecting viruses (cucumber mosaic virus, potato virus X, potato virus Y) or a hypersensitive-response-inducing virus (tobacco mosaic virus; TMV) limited to the inoculated leaf. Five reference-gene validation programs were used to establish the order of the most stable genes for the systemically-infecting viruses as ribosomal protein L25 > β-Tubulin > Actin, and the least stable genes Ubiquitin-conjugating enzyme (UCE) genes were EF1α > Cysteine protease > Actin, and the least stable genes were GAPDH genes, three defense responsive genes were examined to compare their relative changes in gene expression caused by each virus. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative effects of DHEA and DHT on gene expression in human LNCaP prostate cancer cells.

Science.gov (United States)

Steele, Vernon E; Arnold, Julia T; Lei, Hanh; Izmirlian, Grant; Blackman, Marc R

2006-01-01

DHEA is widely used as a dietary supplement in older men. Because DHEA can be converted to androgens or estrogens, such use may promote prostate cancer. In this study, the effects of DHEA were compared with those of DHT using gene expression array profiles in human LNCaP prostate cancer cells. LNCaP cells were exposed to DHEA (300 nM), DHT (300 nM), or vehicle for 48 h, and mRNA expression was measured using Affymetrix HU-95 gene chips. Gene expression values were sorted in ascending order on the p-values corresponding to the extent of differential RNA expression between control and either hormone treatment. S100 calcium binding protein, neurotensin, 24-dehydrocholesterol reductase, and anterior-gradient 2 homologue were the four most differentially expressed genes (p-values all DHT treatment (p DHT were used for pathway analysis. DHT decreased expression of more genes involved in intercellular communication, signal transduction, nucleic acid binding and transport, and in structural components, such as myosin and golgin, than DHEA. These data revealed consistent, measurable changes in gene expression patterns following treatment of LNCaP prostate cancer cells with DHEA and DHT. Understanding the mechanisms of DHEA versus DHT actions in the prostate may help clarify the separate and interactive effects of androgenic and estrogenic actions in prostate cancer progression.

Over-expression of brain-derived neurotrophic factor in mesenchymal stem cells transfected with recombinant lentivirus BDNF gene.

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Zhang, X; Zhu, J; Zhang, K; Liu, T; Zhang, Z

2016-12-30

This study was aimed at investigating the expression of brain-derived neurotrophic factor (BDNF) in mesenchymal stem cells (MSCs) modified with recombinant lentivirus bearing BDNF gene. Lentivirus vectors bearing BDNF gene were constructed. MSCs were isolated from rats and cultured. The lentiviral vectors containing BDNF gene were transfected into the MSCs, and BDNF gene and protein expressions were monitored with enhanced green fluorescent protein (EGFP). RT-PCR and Western blot were used to measure gene and protein expressions, respectibvely in MSCs, MSCs-EGFP and MSCs-EGFP-BDNF groups. Green fluorescence assay confirmed successful transfection of BDNF gene recombinant lentivirus into MSCs. RT-PCR and Western blot revealed that BDNF gene and protein expressions in the MSCs-EGFP-BDNF group were significantly higher than that in MSCs group and MSCs-EGFP group. There were no statistically significant differences in gene expression between MSCs and MSCs-EGFP groups. MSCs can over-express BDNF when transfected with recombinant lentivirus bearing BDNF gene.

Gene expression patterns in pancreatic tumors, cells and tissues.

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Anson W Lowe

2007-03-01

Full Text Available Cancers of the pancreas originate from both the endocrine and exocrine elements of the organ, and represent a major cause of cancer-related death. This study provides a comprehensive assessment of gene expression for pancreatic tumors, the normal pancreas, and nonneoplastic pancreatic disease.DNA microarrays were used to assess the gene expression for surgically derived pancreatic adenocarcinomas, islet cell tumors, and mesenchymal tumors. The addition of normal pancreata, isolated islets, isolated pancreatic ducts, and pancreatic adenocarcinoma cell lines enhanced subsequent analysis by increasing the diversity in gene expression profiles obtained. Exocrine, endocrine, and mesenchymal tumors displayed unique gene expression profiles. Similarities in gene expression support the pancreatic duct as the origin of adenocarcinomas. In addition, genes highly expressed in other cancers and associated with specific signal transduction pathways were also found in pancreatic tumors.The scope of the present work was enhanced by the inclusion of publicly available datasets that encompass a wide spectrum of human tissues and enabled the identification of candidate genes that may serve diagnostic and therapeutic goals.

"Hook"-calibration of GeneChip-microarrays: Chip characteristics and expression measures

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Krohn Knut

2008-08-01

Full Text Available Abstract Background Microarray experiments rely on several critical steps that may introduce biases and uncertainty in downstream analyses. These steps include mRNA sample extraction, amplification and labelling, hybridization, and scanning causing chip-specific systematic variations on the raw intensity level. Also the chosen array-type and the up-to-dateness of the genomic information probed on the chip affect the quality of the expression measures. In the accompanying publication we presented theory and algorithm of the so-called hook method which aims at correcting expression data for systematic biases using a series of new chip characteristics. Results In this publication we summarize the essential chip characteristics provided by this method, analyze special benchmark experiments to estimate transcript related expression measures and illustrate the potency of the method to detect and to quantify the quality of a particular hybridization. It is shown that our single-chip approach provides expression measures responding linearly on changes of the transcript concentration over three orders of magnitude. In addition, the method calculates a detection call judging the relation between the signal and the detection limit of the particular measurement. The performance of the method in the context of different chip generations and probe set assignments is illustrated. The hook method characterizes the RNA-quality in terms of the 3'/5'-amplification bias and the sample-specific calling rate. We show that the proper judgement of these effects requires the disentanglement of non-specific and specific hybridization which, otherwise, can lead to misinterpretations of expression changes. The consequences of modifying probe/target interactions by either changing the labelling protocol or by substituting RNA by DNA targets are demonstrated. Conclusion The single-chip based hook-method provides accurate expression estimates and chip-summary characteristics

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

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Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis

Gene expression profiling of two distinct neuronal populations in the rodent spinal cord.

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Jesper Ryge

Full Text Available BACKGROUND: In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. METHODOLOGY/PRINCIPAL FINDINGS: We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. CONCLUSIONS/SIGNIFICANCE: We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional

Vaginal Gene Expression During Treatment With Aromatase Inhibitors.

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Kallak, Theodora Kunovac; Baumgart, Juliane; Nilsson, Kerstin; Åkerud, Helena; Poromaa, Inger Sundström; Stavreus-Evers, Anneli

2015-12-01

Aromatase inhibitor (AI) treatment suppresses estrogen biosynthesis and causes genitourinary symptoms of menopause such as vaginal symptoms, ultimately affecting the quality of life for many postmenopausal women with breast cancer. Thus, the aim of this study was to examine vaginal gene expression in women during treatment with AIs compared with estrogen-treated women. The secondary aim was to study the presence and localization of vaginal aromatase. Vaginal biopsies were collected from postmenopausal women treated with AIs and from age-matched control women treated with vaginal estrogen therapy. Differential gene expression was studied with the Affymetrix Gene Chip Gene 1.0 ST Array (Affymetrix Inc, Santa Clara, CA) system, Ingenuity pathway analysis, quantitative real-time polymerase chain reaction, and immunohistochemistry. The expression of 279 genes differed between the 2 groups; AI-treated women had low expression of genes involved in cell differentiation, proliferation, and cell adhesion. Some differentially expressed genes were found to interact indirectly with the estrogen receptor alpha. In addition, aromatase protein staining was evident in the basal and the intermediate vaginal epithelium layers, and also in stromal cells with a slightly stronger staining intensity found in AI-treated women. In this study, we demonstrated that genes involved in cell differentiation, proliferation, and cell adhesion are differentially expressed in AI-treated women. The expression of vaginal aromatase suggests that this could be the result of local and systemic inhibition of aromatase. Our results emphasize the role of estrogen for vaginal cell differentiation and proliferation and future drug candidates should be aimed at improving cell differentiation and proliferation. Copyright © 2015 Elsevier Inc. All rights reserved.

Gene-expression profiling after exposure to C-ion beams

International Nuclear Information System (INIS)

Saegusa, Kumiko; Furuno, Aki; Ishikawa, Kenichi; Ishikawa, Atsuko; Ohtsuka, Yoshimi; Kawai, Seiko; Imai, Takashi; Nojima, Kumie

2005-01-01

It is recognized that carbon-ion beam kills cancer cells more efficiently than X-ray. In this study we have compared cellular gene expression response after carbon-ion beam exposure with that after X-ray exposure. Gene expression profiles of cultured neonatal human dermal fibroblasts (NHDF) at 0, 1, 3, 6, 12, 18, and 24 hr after exposure to 0.1, 2 and 5 Gy of X-ray or carbon-ion beam were obtained using 22K oligonucleotide microarray. N-way ANOVA analysis of whole gene expression data sets selected 960 genes for carbon-ion beam and 977 genes for X-ray, respectively. Interestingly, majority of these genes (91% for carbon-ion beam and 88% for X-ray, respectively) were down regulated. The selected genes were further classified by their dose-dependence or time-dependence of gene expression change (fold change>1.5). It was revealed that genes involved in cell proliferation had tendency to show time-dependent up regulation by carbon-ion beam. Another N-way ANOVA analysis was performed to select 510 genes, and further selection was made to find 70 genes that showed radiation species-dependent gene expression change (fold change>1.25). These genes were then categorized by the K-Mean clustering method into 4 clusters. Each cluster showed tendency to contain genes involved in cell cycle regulation, cell death, responses to stress and metabolisms, respectively. (author)

Expression of novel Alzheimer's disease risk genes in control and Alzheimer's disease brains.

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Celeste M Karch

Full Text Available Late onset Alzheimer's disease (LOAD etiology is influenced by complex interactions between genetic and environmental risk factors. Large-scale genome wide association studies (GWAS for LOAD have identified 10 novel risk genes: ABCA7, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, MS4A6A, MS4A6E, and PICALM. We sought to measure the influence of GWAS single nucleotide polymorphisms (SNPs and gene expression levels on clinical and pathological measures of AD in brain tissue from the parietal lobe of AD cases and age-matched, cognitively normal controls. We found that ABCA7, CD33, and CR1 expression levels were associated with clinical dementia rating (CDR, with higher expression being associated with more advanced cognitive decline. BIN1 expression levels were associated with disease progression, where higher expression was associated with a delayed age at onset. CD33, CLU, and CR1 expression levels were associated with disease status, where elevated expression levels were associated with AD. Additionally, MS4A6A expression levels were associated with Braak tangle and Braak plaque scores, with elevated expression levels being associated with more advanced brain pathology. We failed to detect an association between GWAS SNPs and gene expression levels in our brain series. The minor allele of rs3764650 in ABCA7 is associated with age at onset and disease duration, and the minor allele of rs670139 in MS4A6E was associated with Braak tangle and Braak plaque score. These findings suggest that expression of some GWAS genes, namely ABCA7, BIN1, CD33, CLU, CR1 and the MS4A family, are altered in AD brains.

AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data

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Xia Yuannan

2006-12-01

Full Text Available Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity; however, qualitative data are also important parameters in detecting differentially expressed genes. Results AffyMiner is a tool developed for detecting differentially expressed genes in Affymetrix GeneChip microarray data and for associating gene annotation and gene ontology information with the genes detected. AffyMiner consists of the functional modules, GeneFinder for detecting significant genes in a treatment versus control experiment and GOTree for mapping genes of interest onto the Gene Ontology (GO space; and interfaces to run Cluster, a program for clustering analysis, and GenMAPP, a program for pathway analysis. AffyMiner has been used for analyzing the GeneChip data and the results were presented in several publications. Conclusion AffyMiner fills an important gap in finding differentially expressed genes in Affymetrix GeneChip microarray data. AffyMiner effectively deals with multiple replicates in the experiment and takes into account both quantitative and qualitative data in identifying significant genes. AffyMiner reduces the time and effort needed to compare data from multiple arrays and to interpret the possible biological implications associated with significant changes in a gene's expression.

Microarray gene expression profiling and analysis in renal cell carcinoma

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Sadhukhan Provash

2004-06-01

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

Regulation of Gene Expression in Protozoa Parasites

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Consuelo Gomez

2010-01-01

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

Regulation of gene expression in protozoa parasites.

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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.

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

DEFF Research Database (Denmark)

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

2012-01-01

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood...... of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co......, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes...

Divergent and nonuniform gene expression patterns in mouse brain

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Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

2010-01-01

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

Rethinking cell-cycle-dependent gene expression in Schizosaccharomyces pombe.

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Cooper, Stephen

2017-11-01

Three studies of gene expression during the division cycle of Schizosaccharomyces pombe led to the proposal that a large number of genes are expressed at particular times during the S. pombe cell cycle. Yet only a small fraction of genes proposed to be expressed in a cell-cycle-dependent manner are reproducible in all three published studies. In addition to reproducibility problems, questions about expression amplitudes, cell-cycle timing of expression, synchronization artifacts, and the problem with methods for synchronizing cells must be considered. These problems and complications prompt the idea that caution should be used before accepting the conclusion that there are a large number of genes expressed in a cell-cycle-dependent manner in S. pombe.

G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

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Lemay Danielle G

2012-09-01

Full Text Available Abstract Background In previous studies, gene neighborhoods—spatial clusters of co-expressed genes in the genome—have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously. Results Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods. Conclusions Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The