Genetic profiles of gastroesophageal cancer: combined analysis using expression array and tiling array--comparative genomic hybridization

DEFF Research Database (Denmark)

Isinger-Ekstrand, Anna; Johansson, Jan; Ohlsson, Mattias

2010-01-01

15, 13q34, and 12q13, whereas different profiles with gains at 5p15, 7p22, 2q35, and 13q34 characterized gastric cancers. CDK6 and EGFR were identified as putative target genes in cancers of the esophagus and the gastroesophageal junction, with upregulation in one quarter of the tumors. Gains......We aimed to characterize the genomic profiles of adenocarcinomas in the gastroesophageal junction in relation to cancers in the esophagus and the stomach. Profiles of gains/losses as well as gene expression profiles were obtained from 27 gastroesophageal adenocarcinomas by means of 32k high......-resolution array-based comparative genomic hybridization and 27k oligo gene expression arrays, and putative target genes were validated in an extended series. Adenocarcinomas in the distal esophagus and the gastroesophageal junction showed strong similarities with the most common gains at 20q13, 8q24, 1q21-23, 5p...

Simple method for assembly of CRISPR synergistic activation mediator gRNA expression array.

Science.gov (United States)

Vad-Nielsen, Johan; Nielsen, Anders Lade; Luo, Yonglun

2018-05-20

When studying complex interconnected regulatory networks, effective methods for simultaneously manipulating multiple genes expression are paramount. Previously, we have developed a simple method for generation of an all-in-one CRISPR gRNA expression array. We here present a Golden Gate Assembly-based system of synergistic activation mediator (SAM) compatible CRISPR/dCas9 gRNA expression array for the simultaneous activation of multiple genes. Using this system, we demonstrated the simultaneous activation of the transcription factors, TWIST, SNAIL, SLUG, and ZEB1 a human breast cancer cell line. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2013-01-01

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

ArrayExpress update--trends in database growth and links to data analysis tools.

Science.gov (United States)

Rustici, Gabriella; Kolesnikov, Nikolay; Brandizi, Marco; Burdett, Tony; Dylag, Miroslaw; Emam, Ibrahim; Farne, Anna; Hastings, Emma; Ison, Jon; Keays, Maria; Kurbatova, Natalja; Malone, James; Mani, Roby; Mupo, Annalisa; Pedro Pereira, Rui; Pilicheva, Ekaterina; Rung, Johan; Sharma, Anjan; Tang, Y Amy; Ternent, Tobias; Tikhonov, Andrew; Welter, Danielle; Williams, Eleanor; Brazma, Alvis; Parkinson, Helen; Sarkans, Ugis

2013-01-01

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is one of three international functional genomics public data repositories, alongside the Gene Expression Omnibus at NCBI and the DDBJ Omics Archive, supporting peer-reviewed publications. It accepts data generated by sequencing or array-based technologies and currently contains data from almost a million assays, from over 30 000 experiments. The proportion of sequencing-based submissions has grown significantly over the last 2 years and has reached, in 2012, 15% of all new data. All data are available from ArrayExpress in MAGE-TAB format, which allows robust linking to data analysis and visualization tools, including Bioconductor and GenomeSpace. Additionally, R objects, for microarray data, and binary alignment format files, for sequencing data, have been generated for a significant proportion of ArrayExpress data.

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.

Tyrosine Kinase Gene Expression Profiling in Prostate Cancer

National Research Council Canada - National Science Library

Weier, Heinz-Ulrich

2001-01-01

... of these genes parallels the progression of tumors to a more malignant phenotype. We developed a DNA micro-array based screening system to monitor the level of expression of tyrosine kinase (tk...

Tyrosine Kinase Gene Expression Profiling in Prostate Cancer

National Research Council Canada - National Science Library

Weier, Heinz-Ulrich

2002-01-01

... of these genes parallels the progression of tumors to a more malignant phenotype. We developed a DNA micro-array based screening system to monitor the level of expression of tyrosine kinase (tk...

Altered Gene Expression by Low-Dose Arsenic Exposure in Humans and Cultured Cardiomyocytes: Assessment by Real-Time PCR Arrays

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Judy Mumford

2011-06-01

Full Text Available Chronic arsenic exposure results in higher risk of skin, lung, and bladder cancer, as well as cardiovascular disease and diabetes. The purpose of this study was to investigate the effects on expression of selected genes in the blood lymphocytes from 159 people exposed chronically to arsenic in their drinking water using a novel RT-PCR TaqMan low-density array (TLDA. We found that expression of tumor necrosis factor-α (TNF-α, which activates both inflammation and NF-κB-dependent survival pathways, was strongly associated with water and urinary arsenic levels. Expression of KCNA5, which encodes a potassium ion channel protein, was positively associated with water and toe nail arsenic levels. Expression of 2 and 11 genes were positively associated with nail and urinary arsenic, respectively. Because arsenic exposure has been reported to be associated with long QT intervals and vascular disease in humans, we also used this TLDA for analysis of gene expression in human cardiomyocytes exposed to arsenic in vitro. Expression of the ion-channel genes CACNA1, KCNH2, KCNQ1 and KCNE1 were down-regulated by 1-mM arsenic. Alteration of some common pathways, including those involved in oxidative stress, inflammatory signaling, and ion-channel function, may underlay the seemingly disparate array of arsenic-associated diseases, such as cancer, cardiovascular disease, and diabetes.

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

Development of multitissue microfluidic dynamic array for assessing changes in gene expression associated with channel catfish appetite, growth, metabolism, and intestinal health

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Large-scale, gene expression methods allow for high throughput analysis of physiological pathways at a fraction of the cost of individual gene expression analysis. Systems, such as the Fluidigm quantitative PCR array described here, can provide powerful assessments of the effects of diet, environme...

A pilot trial assessing urinary gene expression profiling with an mRNA array for diabetic nephropathy.

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Min Zheng

Full Text Available BACKGROUND: The initiation and progression of diabetic nephropathy (DN is complex. Quantification of mRNA expression in urinary sediment has emerged as a novel strategy for studying renal diseases. Considering the numerous molecules involved in DN development, a high-throughput platform with parallel detection of multiple mRNAs is needed. In this study, we constructed a self-assembling mRNA array to analyze urinary mRNAs in DN patients with aims to reveal its potential in searching novel biomarkers. METHODS: mRNA array containing 88 genes were fabricated and its performance was evaluated. A pilot study with 9 subjects including 6 DN patients and 3 normal controls were studied with the array. DN patients were assigned into two groups according to their estimate glomerular rate (eGFR: DNI group (eGFR>60 ml/min/1.73 m(2, n = 3 and DNII group (eGFR<60 ml/min/1.73 m(2, n = 3. Urinary cell pellet was collected from each study participant. Relative abundance of these target mRNAs from urinary pellet was quantified with the array. RESULTS: The array we fabricated displayed high sensitivity and specificity. Moreover, the Cts of Positive PCR Controls in our experiments were 24±0.5 which indicated high repeatability of the array. A total of 29 mRNAs were significantly increased in DN patients compared with controls (p<0.05. Among these genes, α-actinin4, CDH2, ACE, FAT1, synaptopodin, COL4α, twist, NOTCH3 mRNA expression were 15-fold higher than those in normal controls. In contrast, urinary TIMP-1 mRNA was significantly decreased in DN patients (p<0.05. It was shown that CTGF, MCP-1, PAI-1, ACE, CDH1, CDH2 mRNA varied significantly among the 3 study groups, and their mRNA levels increased with DN progression (p<0.05. CONCLUSION: Our pilot study demonstrated that mRNA array might serve as a high-throughput and sensitive tool for detecting mRNA expression in urinary sediment. Thus, this primary study indicated that mRNA array probably could be a

Application of four dyes in gene expression analyses by microarrays

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van Schooten Frederik J

2005-07-01

Full Text Available Abstract Background DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

Lineage relationship of prostate cancer cell types based on gene expression

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Ware Carol B

2011-05-01

Full Text Available Abstract Background Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells. Methods Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology and pattern 4 (aglandular sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype and LuCaP 49 (neuroendocrine/small cell carcinoma grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts. Results Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness. Conclusions Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.

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.

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

Science.gov (United States)

Khan, Haseeb Ahmad

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

High-throughput Microarray Detection of Vomeronasal Receptor Gene Expression in Rodents

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Xiaohong Zhang

2010-11-01

Full Text Available We performed comprehensive data mining to explore the vomeronasal receptor (V1R & V2R repertoires in mouse and rat using the mm5 and rn3 genome, respectively. This bioinformatic analysis was followed by investigation of gene expression using a custom designed high-density oligonucleotide array containing all of these receptors and other selected genes of interest. This array enabled us to detect the specific expression of V1R and V2Rs which were previously identified solely based on computational prediction from gene sequence data, thereby establishing that these genes are indeed part of the vomeronasal system, especially the V2Rs. 168 V1Rs and 98 V2Rs were detected to be highly enriched in mouse vomeronasal organ (VNO, and 108 V1Rs and 87 V2Rs in rat VNO. We monitored the expression profile of mouse VR genes in other non-VNO tissues with the result that some VR genes were re-designated as VR-like genes based on their non-olfactory expression pattern. Temporal expression profiles for mouse VR genes were characterized and their patterns were classified, revealing the developmental dynamics of these so-called pheromone receptors. We found numerous patterns of temporal expression which indicate possible behavior-related functions. The uneven composition of VR genes in certain patterns suggests a functional differentiation between the two types of VR genes. We found the coherence between VR genes and transcription factors in terms of their temporal expression patterns. In situ hybridization experiments were performed to evaluate the cell number change over time for selected receptor genes.

Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

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Roshan Ramanathan

2011-05-01

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

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.

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

Science.gov (United States)

Shirahata, Mitsuaki; Iwao-Koizumi, Kyoko; Saito, Sakae; Ueno, Noriko; Oda, Masashi; Hashimoto, Nobuo; Takahashi, Jun A; Kato, Kikuya

2007-12-15

Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

CGI: Java software for mapping and visualizing data from array-based comparative genomic hybridization and expression profiling.

Science.gov (United States)

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong

2007-10-06

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

CGI: Java Software for Mapping and Visualizing Data from Array-based Comparative Genomic Hybridization and Expression Profiling

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Joyce Xiuweu-Xu Gu

2007-01-01

Full Text Available With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator that matches the BAC clones from array-based comparative genomic hybridization (aCGH to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specifi c BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

Finding gene regulatory network candidates using the gene expression knowledge base.

Science.gov (United States)

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

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. ©

Recovery and evolutionary analysis of complete integron gene cassette arrays from Vibrio

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Gillings Michael R

2006-01-01

Full Text Available Abstract Background Integrons are genetic elements capable of the acquisition, rearrangement and expression of genes contained in gene cassettes. Gene cassettes generally consist of a promoterless gene associated with a recombination site known as a 59-base element (59-be. Multiple insertion events can lead to the assembly of large integron-associated cassette arrays. The most striking examples are found in Vibrio, where such cassette arrays are widespread and can range from 30 kb to 150 kb. Besides those found in completely sequenced genomes, no such array has yet been recovered in its entirety. We describe an approach to systematically isolate, sequence and annotate large integron gene cassette arrays from bacterial strains. Results The complete Vibrio sp. DAT722 integron cassette array was determined through the streamlined approach described here. To place it in an evolutionary context, we compare the DAT722 array to known vibrio arrays and performed phylogenetic analyses for all of its components (integrase, 59-be sites, gene cassette encoded genes. It differs extensively in terms of genomic context as well as gene cassette content and organization. The phylogenetic tree of the 59-be sites collectively found in the Vibrio gene cassette pool suggests frequent transfer of cassettes within and between Vibrio species, with slower transfer rates between more phylogenetically distant relatives. We also identify multiple cases where non-integron chromosomal genes seem to have been assembled into gene cassettes and others where cassettes have been inserted into chromosomal locations outside integrons. Conclusion Our systematic approach greatly facilitates the isolation and annotation of large integrons gene cassette arrays. Comparative analysis of the Vibrio sp. DAT722 integron obtained through this approach to those found in other vibrios confirms the role of this genetic element in promoting lateral gene transfer and suggests a high rate of gene

Xylella fastidiosa gene expression analysis by DNA microarrays

OpenAIRE

Travensolo,Regiane F.; Carareto-Alves,Lucia M.; Costa,Maria V.C.G.; Lopes,Tiago J.S.; Carrilho,Emanuel; Lemos,Eliana G.M.

2009-01-01

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcrip...

The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

DEFF Research Database (Denmark)

Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

2006-01-01

be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate cancer progression

International Nuclear Information System (INIS)

Oudes, Asa J; Roach, Jared C; Walashek, Laura S; Eichner, Lillian J; True, Lawrence D; Vessella, Robert L; Liu, Alvin Y

2005-01-01

Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases

Emerging use of gene expression microarrays in plant physiology.

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Wullschleger, Stan D; Difazio, Stephen P

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

Classification of Dukes' B and C colorectal cancers using expression arrays

DEFF Research Database (Denmark)

Frederiksen, C.M.; Knudsen, Steen; Laurberg, S.

2003-01-01

Purpose. Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene...... expression microarrays could be used to classify colorectal tumors. Methods. We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each...... expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays....

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.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

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Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Subclassification and Detection of New Markers for the Discrimination of Primary Liver Tumors by Gene Expression Analysis Using Oligonucleotide Arrays.

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Hass, Holger G; Vogel, Ulrich; Scheurlen, Michael; Jobst, Jürgen

2017-12-26

The failure to correctly differentiate between intrahepatic cholangiocarcinoma [CC] and hepatocellular carcinoma [HCC] is a significant clinical problem, particularly in terms of the different treatment goals for both cancers. In this study a specific gene expression profile to discriminate these two subgroups of liver cancer was established and potential diagnostic markers for clinical use were analyzed. To evaluate the gene expression profiles of HCC and intrahepatic CC, Oligonucleotide arrays ( Affymetrix U133A) were used. Overexpressed genes were checked for their potential use as new markers for discrimination and their expression values were validated by reverse transcription polymerase chain reaction and immunohistochemistry analyses. 695 genes/expressed sequence tags (ESTs) in HCC (245 up-/450 down-regulated) and 552 genes/ESTs in CC (221 up-/331 down-regulated) were significantly dysregulated (p〈0.05, fold change >2, ≥70%). Using a supervised learning method, and one-way analysis of variance a specific 270-gene expression profile that enabled rapid, reproducible differentiation between both tumors and non-malignant liver tissues was established. A panel of 12 genes (e.g. HSP90β, ERG1, GPC3, TKT, ACLY, and NME1 for HCC; SPT2, T4S3, CNX43, TTD1, HBD01 for CC) were detected and partly described for the first time as potential discrimination markers. A specific gene expression profile for discrimination of primary liver cancer was identified and potential marker genes with feasible clinical impact were described.

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

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Xu Jia

2010-11-01

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

Breast Carcinoma Cells in Primary Tumors and Effusions Have Different Gene Array Profiles

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Sophya Konstantinovsky

2010-01-01

Full Text Available The detection of breast carcinoma cells in effusions is associated with rapidly fatal outcome, but these cells are poorly characterized at the molecular level. This study compared the gene array signatures of breast carcinoma cells in primary carcinomas and effusions. The genetic signature of 10 primary tumors and 10 effusions was analyzed using the Array-Ready Oligo set for the Human Genome platform. Results for selected genes were validated using PCR, Western blotting, and immunohistochemistry. Array analysis identified 255 significantly downregulated and 96 upregulated genes in the effusion samples. The majority of differentially expressed genes were part of pathways involved in focal adhesion, extracellular matrix-cell interaction, and the regulation of the actin cytoskeleton. Genes that were upregulated in effusions included KRT8, BCAR1, CLDN4, VIL2, while DCN, CLDN19, ITGA7, and ITGA5 were downregulated at this anatomic site. PCR, Western blotting, and immunohistochemistry confirmed the array findings for BCAR1, CLDN4, VIL2, and DCN. Our data show that breast carcinoma cells in primary carcinomas and effusions have different gene expression signatures, and differentially express a large number of molecules related to adhesion, motility, and metastasis. These differences may have a critical role in designing therapy and in prognostication for patients with metastatic disease localized to the serosal cavities.

Demonstration of diet-induced decoupling of fatty acid and cholesterol synthesis by combining gene expression array and 2H2O quantification.

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Jensen, Kristian K; Previs, Stephen F; Zhu, Lei; Herath, Kithsiri; Wang, Sheng-Ping; Bhat, Gowri; Hu, Guanghui; Miller, Paul L; McLaren, David G; Shin, Myung K; Vogt, Thomas F; Wang, Liangsu; Wong, Kenny K; Roddy, Thomas P; Johns, Douglas G; Hubbard, Brian K

2012-01-15

The liver is a crossroad for metabolism of lipid and carbohydrates, with acetyl-CoA serving as an important metabolic intermediate and a precursor for fatty acid and cholesterol biosynthesis pathways. A better understanding of the regulation of these pathways requires an experimental approach that provides both quantitative metabolic flux measurements and mechanistic insight. Under conditions of high carbohydrate availability, excess carbon is converted into free fatty acids and triglyceride for storage, but it is not clear how excessive carbohydrate availability affects cholesterol biosynthesis. To address this, C57BL/6J mice were fed either a low-fat, high-carbohydrate diet or a high-fat, carbohydrate-free diet. At the end of the dietary intervention, the two groups received (2)H(2)O to trace de novo fatty acid and cholesterol synthesis, and livers were collected for gene expression analysis. Expression of lipid and glucose metabolism genes was determined using a custom-designed pathway focused PCR-based gene expression array. The expression analysis showed downregulation of cholesterol biosynthesis genes and upregulation of fatty acid synthesis genes in mice receiving the high-carbohydrate diet compared with the carbohydrate-free diet. In support of these findings, (2)H(2)O tracer data showed that fatty acid synthesis was increased 10-fold and cholesterol synthesis was reduced by 1.6-fold in mice fed the respective diets. In conclusion, by applying gene expression analysis and tracer methodology, we show that fatty acid and cholesterol synthesis are differentially regulated when the carbohydrate intake in mice is altered.

Assessment of a novel multi-array normalization method based on spike-in control probes suitable for microRNA datasets with global decreases in expression.

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Sewer, Alain; Gubian, Sylvain; Kogel, Ulrike; Veljkovic, Emilija; Han, Wanjiang; Hengstermann, Arnd; Peitsch, Manuel C; Hoeng, Julia

2014-05-17

High-quality expression data are required to investigate the biological effects of microRNAs (miRNAs). The goal of this study was, first, to assess the quality of miRNA expression data based on microarray technologies and, second, to consolidate it by applying a novel normalization method. Indeed, because of significant differences in platform designs, miRNA raw data cannot be normalized blindly with standard methods developed for gene expression. This fundamental observation motivated the development of a novel multi-array normalization method based on controllable assumptions, which uses the spike-in control probes to adjust the measured intensities across arrays. Raw expression data were obtained with the Exiqon dual-channel miRCURY LNA™ platform in the "common reference design" and processed as "pseudo-single-channel". They were used to apply several quality metrics based on the coefficient of variation and to test the novel spike-in controls based normalization method. Most of the considerations presented here could be applied to raw data obtained with other platforms. To assess the normalization method, it was compared with 13 other available approaches from both data quality and biological outcome perspectives. The results showed that the novel multi-array normalization method reduced the data variability in the most consistent way. Further, the reliability of the obtained differential expression values was confirmed based on a quantitative reverse transcription-polymerase chain reaction experiment performed for a subset of miRNAs. The results reported here support the applicability of the novel normalization method, in particular to datasets that display global decreases in miRNA expression similarly to the cigarette smoke-exposed mouse lung dataset considered in this study. Quality metrics to assess between-array variability were used to confirm that the novel spike-in controls based normalization method provided high-quality miRNA expression data

Tumour metastasis-associated gene profiling using one-dimensional microfluidic beads array

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Great efforts have been made on the early diagnosis and molecular mechanism research of tumour metastasis in recent years. In this paper, based on the one-dimensional microfluidic beads array, a novel platform for tumour metastasis-associated genes profiling has been developed by depositing nucleic acids functional beads in the microchannel. This platform is sensitive (limit of detection: 0.02 nmol/L) and can perform mRNAs analysis without PCR. Two human colon cancer cell lines (primary and metastatic) from the same patient were used as a model, and transcriptional expression profiling of multiple tumour metastasis-associated genes in these two cell lines was successfully achieved. Furthermore, the results obtained on the beads array were validated by RT-PCR. This novel beads array has advantages of high sensitivity, little sample consumption, short assay time, low cost and high throughput capability. It holds the potential in early diagnosis and mechanism research of tumour metastasis.

Ebola virus infection induces irregular dendritic cell gene expression.

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Melanson, Vanessa R; Kalina, Warren V; Williams, Priscilla

2015-02-01

Filoviruses subvert the human immune system in part by infecting and replicating in dendritic cells (DCs). Using gene arrays, a phenotypic profile of filovirus infection in human monocyte-derived DCs was assessed. Monocytes from human donors were cultured in GM-CSF and IL-4 and were infected with Ebola virus Kikwit variant for up to 48 h. Extracted DC RNA was analyzed on SuperArray's Dendritic and Antigen Presenting Cell Oligo GEArray and compared to uninfected controls. Infected DCs exhibited increased expression of cytokine, chemokine, antiviral, and anti-apoptotic genes not seen in uninfected controls. Significant increases of intracellular antiviral and MHC I and II genes were also noted in EBOV-infected DCs. However, infected DCs failed to show any significant difference in co-stimulatory T-cell gene expression from uninfected DCs. Moreover, several chemokine genes were activated, but there was sparse expression of chemokine receptors that enabled activated DCs to home to lymph nodes. Overall, statistically significant expression of several intracellular antiviral genes was noted, which may limit viral load but fails to stop replication. EBOV gene expression profiling is of vital importance in understanding pathogenesis and devising novel therapeutic treatments such as small-molecule inhibitors.

Xylella fastidiosa gene expression analysis by DNA microarrays

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Regiane F. Travensolo

2009-01-01

Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Disease gene characterization through large-scale co-expression analysis.

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Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

Emerging Use of Gene Expression Microarrays in Plant Physiology

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Stephen P. Difazio

2006-04-01

Full Text Available Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

Three gangliogliomas: results of GTG-banding, SKY, genome-wide high resolution SNP-array, gene expression and review of the literature.

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Xu, Li-Xin; Holland, Heidrun; Kirsten, Holger; Ahnert, Peter; Krupp, Wolfgang; Bauer, Manfred; Schober, Ralf; Mueller, Wolf; Fritzsch, Dominik; Meixensberger, Jürgen; Koschny, Ronald

2015-04-01

According to the World Health Organization gangliogliomas are classified as well-differentiated and slowly growing neuroepithelial tumors, composed of neoplastic mature ganglion and glial cells. It is the most frequent tumor entity observed in patients with long-term epilepsy. Comprehensive cytogenetic and molecular cytogenetic data including high-resolution genomic profiling (single nucleotide polymorphism (SNP)-array) of gangliogliomas are scarce but necessary for a better oncological understanding of this tumor entity. For a detailed characterization at the single cell and cell population levels, we analyzed genomic alterations of three gangliogliomas using trypsin-Giemsa banding (GTG-banding) and by spectral karyotyping (SKY) in combination with SNP-array and gene expression array experiments. By GTG and SKY, we could confirm frequently detected chromosomal aberrations (losses within chromosomes 10, 13 and 22; gains within chromosomes 5, 7, 8 and 12), and identify so far unknown genetic aberrations like the unbalanced non-reciprocal translocation t(1;18)(q21;q21). Interestingly, we report on the second so far detected ganglioglioma with ring chromosome 1. Analyses of SNP-array data from two of the tumors and respective germline DNA (peripheral blood) identified few small gains and losses and a number of copy-neutral regions with loss of heterozygosity (LOH) in germline and in tumor tissue. In comparison to germline DNA, tumor tissues did not show substantial regions with significant loss or gain or with newly developed LOH. Gene expression analyses of tumor-specific genes revealed similarities in the profile of the analyzed samples regarding different relevant pathways. Taken together, we describe overlapping but also distinct and novel genetic aberrations of three gangliogliomas. © 2014 Japanese Society of Neuropathology.

Streptococcus pneumoniae Supragenome Hybridization Arrays for Profiling of Genetic Content and Gene Expression.

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Kadam, Anagha; Janto, Benjamin; Eutsey, Rory; Earl, Joshua P; Powell, Evan; Dahlgren, Margaret E; Hu, Fen Z; Ehrlich, Garth D; Hiller, N Luisa

2015-02-02

There is extensive genomic diversity among Streptococcus pneumoniae isolates. Approximately half of the comprehensive set of genes in the species (the supragenome or pangenome) is present in all the isolates (core set), and the remaining is unevenly distributed among strains (distributed set). The Streptococcus pneumoniae Supragenome Hybridization (SpSGH) array provides coverage for an extensive set of genes and polymorphisms encountered within this species, capturing this genomic diversity. Further, the capture is quantitative. In this manner, the SpSGH array allows for both genomic and transcriptomic analyses of diverse S. pneumoniae isolates on a single platform. In this unit, we present the SpSGH array, and describe in detail its design and implementation for both genomic and transcriptomic analyses. The methodology can be applied to construction and modification of SpSGH array platforms, as well to other bacterial species as long as multiple whole-genome sequences are available that collectively capture the vast majority of the species supragenome. Copyright © 2015 John Wiley & Sons, Inc.

Visualization of the Dynamics of Gene Expression in the Living Mouse

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Amy Ryan

2004-01-01

Full Text Available Reporter genes can monitor the status and activity of recombinant genomes in a diverse array of organisms, from bacteria and yeast to plants and animals. We have combined luciferase reporter genes with a conditional gene expression system based on regulatory elements from the lac Operon of Escherichia coli to visualize the dynamics of gene expression in realtime in the living mouse. Using this technology, we have determined the rate of gene induction and repression, the level of target gene activity in response to different doses of inducer, and the schedule of induction during early embryogenesis of both the endogenous and the experimentally manipulated programs of mammalian gene expression associated with the HD/Hdh locus. The combination of in vivo imaging and lac regulation is a powerful tool for generating conditional transgenic mice that can be screened rapidly for optimal regulation and expression patterns, and for monitoring the induction and repression of regulated genes noninvasively in the living animal.

Comparative gene expression profiles between heterotic and non-heterotic hybrids of tetraploid Medicago sativa

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Nettleton Dan

2009-08-01

Full Text Available Abstract Background Heterosis, the superior performance of hybrids relative to parents, has clear agricultural value, but its genetic control is unknown. Our objective was to test the hypotheses that hybrids expressing heterosis for biomass yield would show more gene expression levels that were different from midparental values and outside the range of parental values than hybrids that do not exhibit heterosis. Results We tested these hypotheses in three Medicago sativa (alfalfa genotypes and their three hybrids, two of which expressed heterosis for biomass yield and a third that did not, using Affymetrix M. truncatula GeneChip arrays. Alfalfa hybridized to approximately 47% of the M. truncatula probe sets. Probe set signal intensities were analyzed using MicroArray Suite v.5.0 (MAS and robust multi-array average (RMA algorithms. Based on MAS analysis, the two heterotic hybrids performed similarly, with about 27% of genes showing differential expression among the parents and their hybrid compared to 12.5% for the non-heterotic hybrid. At a false discovery rate of 0.15, 4.7% of differentially expressed genes in hybrids (~300 genes showed nonadditive expression compared to only 0.5% (16 genes in the non-heterotic hybrid. Of the nonadditively expressed genes, approximately 50% showed expression levels that fell outside the parental range in heterotic hybrids, but only one of 16 showed a similar profile in the non-heterotic hybrid. Genes whose expression differed in the parents were three times more likely to show nonadditive expression than genes whose parental transcript levels were equal. Conclusion The higher proportions of probe sets with expression level that differed from the parental midparent value and that were more extreme than either parental value in the heterotic hybrids compared to a non-heterotic hybrid were also found using RMA. We conclude that nonadditive expression of transcript levels may contribute to heterosis for biomass

A user-friendly workflow for analysis of Illumina gene expression bead array data available at the arrayanalysis.org portal.

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Eijssen, Lars M T; Goelela, Varshna S; Kelder, Thomas; Adriaens, Michiel E; Evelo, Chris T; Radonjic, Marijana

2015-06-30

Illumina whole-genome expression bead arrays are a widely used platform for transcriptomics. Most of the tools available for the analysis of the resulting data are not easily applicable by less experienced users. ArrayAnalysis.org provides researchers with an easy-to-use and comprehensive interface to the functionality of R and Bioconductor packages for microarray data analysis. As a modular open source project, it allows developers to contribute modules that provide support for additional types of data or extend workflows. To enable data analysis of Illumina bead arrays for a broad user community, we have developed a module for ArrayAnalysis.org that provides a free and user-friendly web interface for quality control and pre-processing for these arrays. This module can be used together with existing modules for statistical and pathway analysis to provide a full workflow for Illumina gene expression data analysis. The module accepts data exported from Illumina's GenomeStudio, and provides the user with quality control plots and normalized data. The outputs are directly linked to the existing statistics module of ArrayAnalysis.org, but can also be downloaded for further downstream analysis in third-party tools. The Illumina bead arrays analysis module is available at http://www.arrayanalysis.org . A user guide, a tutorial demonstrating the analysis of an example dataset, and R scripts are available. The module can be used as a starting point for statistical evaluation and pathway analysis provided on the website or to generate processed input data for a broad range of applications in life sciences research.

Transcriptional expression of type I interferon response genes and stability of housekeeping genes in the human endometrium and endometriosis

DEFF Research Database (Denmark)

Vestergaard, Anna L; Knudsen, Ulla B; Munk, Torben

2011-01-01

Endometriosis is a painful chronic female disease defined by the presence of endometrial tissue implants in ectopic locations. The pathogenesis is much debated, and type I interferons could be involved. The expression of genes of the type I interferon response were profiled by a specific PCR Array...... of RNA obtained from ectopic and eutopic endometrium collected from 9 endometriosis patients and 9 healthy control women. Transcriptional expression levels of selected interferon-regulated and housekeeping genes were investigated by real-time quantitative reverse transcriptase PCR (qRT-PCR). Stably...... expressed housekeeping genes for valid normalization of transcriptional studies of endometrium and endometriosis have not yet been published. Here, seven housekeeping genes were evaluated for stability using the GeNorm and NormFinder software. A normalization factor based on HMBS, TBP, and YWHAZ expression...

The National NeuroAIDS Tissue Consortium brain gene array: two types of HIV-associated neurocognitive impairment.

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Benjamin B Gelman

Full Text Available The National NeuroAIDS Tissue Consortium (NNTC performed a brain gene expression array to elucidate pathophysiologies of Human Immunodeficiency Virus type 1 (HIV-1-associated neurocognitive disorders.Twenty-four human subjects in four groups were examined A Uninfected controls; B HIV-1 infected subjects with no substantial neurocognitive impairment (NCI; C Infected with substantial NCI without HIV encephalitis (HIVE; D Infected with substantial NCI and HIVE. RNA from neocortex, white matter, and neostriatum was processed with the Affymetrix® array platform.With HIVE the HIV-1 RNA load in brain tissue was three log(10 units higher than other groups and over 1,900 gene probes were regulated. Interferon response genes (IFRGs, antigen presentation, complement components and CD163 antigen were strongly upregulated. In frontal neocortex downregulated neuronal pathways strongly dominated in HIVE, including GABA receptors, glutamate signaling, synaptic potentiation, axon guidance, clathrin-mediated endocytosis and 14-3-3 protein. Expression was completely different in neuropsychologically impaired subjects without HIVE. They had low brain HIV-1 loads, weak brain immune responses, lacked neuronally expressed changes in neocortex and exhibited upregulation of endothelial cell type transcripts. HIV-1-infected subjects with normal neuropsychological test results had upregulation of neuronal transcripts involved in synaptic transmission of neostriatal circuits.Two patterns of brain gene expression suggest that more than one pathophysiological process occurs in HIV-1-associated neurocognitive impairment. Expression in HIVE suggests that lowering brain HIV-1 replication might improve NCI, whereas NCI without HIVE may not respond in kind; array results suggest that modulation of transvascular signaling is a potentially promising approach. Striking brain regional differences highlighted the likely importance of circuit level disturbances in HIV/AIDS. In

Feasibility of RNA and DNA Extraction from Fresh Pipelle and Archival Endometrial Tissues for Use in Gene Expression and SNP Arrays

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Heather D. Kissel

2013-01-01

Full Text Available Identifying molecular markers of endometrial hyperplasia (neoplasia progression is critical to cancer prevention. To assess RNA and DNA quantity and quality from routinely collected endometrial samples and evaluate the performance of RNA- and DNA-based arrays across endometrial tissue types, we collected fresh frozen (FF Pipelle, FF curettage, and formalin-fixed paraffin-embedded (FFPE hysterectomy specimens (benign indications from eight women. Additionally, neoplastic and uninvolved tissues from 24 FFPE archival hysterectomy specimens with endometrial hyperplasias and carcinomas were assessed. RNA was extracted from 15 of 16 FF and 51 of 51 FFPE samples, with yields >1.2 μg for 13/15 (87% FF and 50/51 (98% FFPE samples. Extracted RNA was of high quality; all samples performed successfully on the Illumina whole-genome cDNA-mediated annealing, selection, extension, and ligation (WG-DASL array and performance did not vary by tissue type. While DNA quantity from FFPE samples was excellent, quality was not sufficient for successful performance on the Affymetrix SNP Array 6.0. In conclusion, FF Pipelle samples, which are minimally invasive, yielded excellent quantity and quality of RNA for gene expression arrays (similar to FF curettage and should be considered for use in genomic studies. FFPE-derived DNA should be evaluated on new rapidly evolving sequencing platforms.

High-throughput analysis of candidate imprinted genes and allele-specific gene expression in the human term placenta

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Clark Taane G

2010-04-01

Full Text Available Abstract Background Imprinted genes show expression from one parental allele only and are important for development and behaviour. This extreme mode of allelic imbalance has been described for approximately 56 human genes. Imprinting status is often disrupted in cancer and dysmorphic syndromes. More subtle variation of gene expression, that is not parent-of-origin specific, termed 'allele-specific gene expression' (ASE is more common and may give rise to milder phenotypic differences. Using two allele-specific high-throughput technologies alongside bioinformatics predictions, normal term human placenta was screened to find new imprinted genes and to ascertain the extent of ASE in this tissue. Results Twenty-three family trios of placental cDNA, placental genomic DNA (gDNA and gDNA from both parents were tested for 130 candidate genes with the Sequenom MassArray system. Six genes were found differentially expressed but none imprinted. The Illumina ASE BeadArray platform was then used to test 1536 SNPs in 932 genes. The array was enriched for the human orthologues of 124 mouse candidate genes from bioinformatics predictions and 10 human candidate imprinted genes from EST database mining. After quality control pruning, a total of 261 informative SNPs (214 genes remained for analysis. Imprinting with maternal expression was demonstrated for the lymphocyte imprinted gene ZNF331 in human placenta. Two potential differentially methylated regions (DMRs were found in the vicinity of ZNF331. None of the bioinformatically predicted candidates tested showed imprinting except for a skewed allelic expression in a parent-specific manner observed for PHACTR2, a neighbour of the imprinted PLAGL1 gene. ASE was detected for two or more individuals in 39 candidate genes (18%. Conclusions Both Sequenom and Illumina assays were sensitive enough to study imprinting and strong allelic bias. Previous bioinformatics approaches were not predictive of new imprinted genes

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

Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data

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Tu Kang

2007-06-01

Full Text Available Abstract Background The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene expression. The increased knowledge that one gene may have multiple transcript variants clearly brings up the necessity of updating this gene-level annotation to a refined transcript-level. Results Through performing rigorous alignments of the Affymetrix probe sequences against a comprehensive pool of currently available transcript sequences, and further linking the probesets to the International Protein Index, we generated transcript-level or protein-level annotation tables for two popular Affymetrix expression arrays, Mouse Genome 430A 2.0 Array and Human Genome U133A Array. Application of our new annotations in re-examining existing expression data sets shows increased expression consistency among synonymous probesets and strengthened expression correlation between interacting proteins. Conclusion By refining the standard Affymetrix annotation of microarray probesets from the gene level to the transcript level and protein level, one can achieve a more reliable interpretation of their experimental data, which may lead to discovery of more profound regulatory mechanism.

Gene organization in rice revealed by full-length cDNA mapping and gene expression analysis through microarray.

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Kouji Satoh

Full Text Available Rice (Oryza sativa L. is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE genes, 33K annotated non-expressed (ANE genes, and 5.5K non-annotated expressed (NAE genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria.

Microarray-based screening of differentially expressed genes in glucocorticoid-induced avascular necrosis

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Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

2017-01-01

The underlying mechanisms of glucocorticoid (GC)-induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC-induced ANFH. E-MEXP-2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid-induced ANFH rats compared with 5 placebo-treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC-induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25-Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α-2-macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC-induced ANFH via interacting with VDR. A2M may also be involved in the development of GC-induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC-induced ANFH may provide novel targets for diagnostics and therapeutic treatment. PMID:28393228

Microarray‑based screening of differentially expressed genes in glucocorticoid‑induced avascular necrosis.

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Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

2017-06-01

The underlying mechanisms of glucocorticoid (GC)‑induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC‑induced ANFH. E‑MEXP‑2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid‑induced ANFH rats compared with 5 placebo‑treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC‑induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25‑Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α‑2‑macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC‑induced ANFH via interacting with VDR. A2M may also be involved in the development of GC‑induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC‑induced ANFH may provide novel targets for diagnostics and therapeutic treatment.

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

Global gene expression analysis of apple fruit development from the floral bud to ripe fruit

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McArtney Steve

2008-02-01

Full Text Available Abstract Background Apple fruit develop over a period of 150 days from anthesis to fully ripe. An array representing approximately 13000 genes (15726 oligonucleotides of 45–55 bases designed from apple ESTs has been used to study gene expression over eight time points during fruit development. This analysis of gene expression lays the groundwork for a molecular understanding of fruit growth and development in apple. Results Using ANOVA analysis of the microarray data, 1955 genes showed significant changes in expression over this time course. Expression of genes is coordinated with four major patterns of expression observed: high in floral buds; high during cell division; high when starch levels and cell expansion rates peak; and high during ripening. Functional analysis associated cell cycle genes with early fruit development and three core cell cycle genes are significantly up-regulated in the early stages of fruit development. Starch metabolic genes were associated with changes in starch levels during fruit development. Comparison with microarrays of ethylene-treated apple fruit identified a group of ethylene induced genes also induced in normal fruit ripening. Comparison with fruit development microarrays in tomato has been used to identify 16 genes for which expression patterns are similar in apple and tomato and these genes may play fundamental roles in fruit development. The early phase of cell division and tissue specification that occurs in the first 35 days after pollination has been associated with up-regulation of a cluster of genes that includes core cell cycle genes. Conclusion Gene expression in apple fruit is coordinated with specific developmental stages. The array results are reproducible and comparisons with experiments in other species has been used to identify genes that may play a fundamental role in fruit development.

Gene expression and gene therapy imaging

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Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

2007-01-01

The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

Can intrinsic human tissue radiosensitivity be correlated with late responding gene RNA expression in white blood cells using a 96 gene micro-array?

International Nuclear Information System (INIS)

Schmidt, D.; Streeter, O.; Dagliyan, G.; Hill, C.K.; Williams-Hill, D.M.

2003-01-01

Radiation is widely used in the treatment of cancers. It is generally believed there is a sigmoid relationship between radiation dose and probability of cure. There is also a sigmoid relationship between radiation dose and normal tissue response. Generally total radiation dose to a tumor is limited by normal tissue tolerance. It has been postulated that up to 70% of inter-individual differences in radiosensitivity may be due to genetic predisposition (Tureson I. Et al, IJROBP, 1996;36:1065). However, to date, clinicians have no way of estimating or predicting an individual's normal tissue response to radiation exposure. Thus the prescribed dose cannot be tailored to an individuals actual expected response but is an empirically derived compromise based on experience. Although a number of studies using cellular techniques have shown that human cell radiosensitivity can be measured, none of these can be performed quick enough to be used in the clinic. In this study we are looking at gene expression that occurs some 24 hours after an exposure compared to expression before any exposure in peripheral white blood cells from patients undergoing radiotherapy for various tumors. The patients will be followed for overt radiation sensitivity by standard criteria by clinicians in the Department. The main aims are: does RNA expression level in a 96 gene micro-array vary before and after radiation and do these changes in RNA expression correlate with the objective measurements of acute radiation response observed by the clinicians in the patients. The USC IRB recently approved the protocol and human consent for this study to enter 50 patients in the next 12 months using mostly head and neck and endometrial cancer patients where we can get a normal tissue sample to examine as well as the blood sample. We will present the rationale, protocol, methods and early results in detail

Creation of a Human Secretome: A Novel Composite Library of Human Secreted Proteins: Validation Using Ovarian Cancer Gene Expression Data and a Virtual Secretome Array.

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Vathipadiekal, Vinod; Wang, Victoria; Wei, Wei; Waldron, Levi; Drapkin, Ronny; Gillette, Michael; Skates, Steven; Birrer, Michael

2015-11-01

To generate a comprehensive "Secretome" of proteins potentially found in the blood and derive a virtual Affymetrix array. To validate the utility of this database for the discovery of novel serum-based biomarkers using ovarian cancer transcriptomic data. The secretome was constructed by aggregating the data from databases of known secreted proteins, transmembrane or membrane proteins, signal peptides, G-protein coupled receptors, or proteins existing in the extracellular region, and the virtual array was generated by mapping them to Affymetrix probeset identifiers. Whole-genome microarray data from ovarian cancer, normal ovarian surface epithelium, and fallopian tube epithelium were used to identify transcripts upregulated in ovarian cancer. We established the secretome from eight public databases and a virtual array consisting of 16,521 Affymetrix U133 Plus 2.0 probesets. Using ovarian cancer transcriptomic data, we identified candidate blood-based biomarkers for ovarian cancer and performed bioinformatic validation by demonstrating rediscovery of known biomarkers including CA125 and HE4. Two novel top biomarkers (FGF18 and GPR172A) were validated in serum samples from an independent patient cohort. We present the secretome, comprising the most comprehensive resource available for protein products that are potentially found in the blood. The associated virtual array can be used to translate gene-expression data into cancer biomarker discovery. A list of blood-based biomarkers for ovarian cancer detection is reported and includes CA125 and HE4. FGF18 and GPR172A were identified and validated by ELISA as being differentially expressed in the serum of ovarian cancer patients compared with controls. ©2015 American Association for Cancer Research.

A functional gene array for detection of bacterial virulence elements

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Jaing, C

2007-11-01

We report our development of the first of a series of microarrays designed to detect pathogens with known mechanisms of virulence and antibiotic resistance. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. To validate our approach, we developed a first generation array targeting genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for microorganism detection and discrimination, measured the required target concentration, and assessed tolerance for mismatches between probe and target sequences. Mismatch tolerance is a priority for this application, due to DNA sequence variability among members of gene families. Arrays were created using the NimbleGen Maskless Array Synthesizer at Lawrence Livermore National Laboratory. Purified genomic DNA from combinations of one or more of the four target organisms, pure cultures of four related organisms, and environmental aerosol samples with spiked-in genomic DNA were hybridized to the arrays. Based on the success of this prototype, we plan to design further arrays in this series, with the goal of detecting all known virulence and antibiotic resistance gene families in a greatly expanded set of organisms.

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

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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.

Correlation of Dynamic PET and Gene Array Data in Patients with Gastrointestinal Stromal Tumors

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Ludwig G. Strauss

2012-01-01

Full Text Available Introduction. The results obtained with dynamic PET (dPET were compared to gene expression data obtained in patients with gastrointestinal stromal tumors (GIST. The primary aim was to assess the association of the dPET results and gene expression data. Material and Methods. dPET was performed following the injection of F-18-fluorodeoxyglucose (FDG in 22 patients with GIST. All patients were examined prior to surgery for staging purpose. Compartment and noncompartment models were used for the quantitative evaluation of the dPET examinations. Gene array data were based on tumor specimen obtained by surgery after the PET examinations. Results. The data analysis revealed significant correlations for the dPET parameters and the expression of zinc finger genes (znf43, znf85, znf91, znf189. Furthermore, the transport of FDG (k1 was associated with VEGF-A. The cell cycle gene cyclin-dependent kinase inhibitor 1C was correlated with the maximum tracer uptake (SUVmax in the tumors. Conclusions. The data demonstrate a dependency of the tracer kinetics on genes associated with prognosis in GIST. Furthermore, angiogenesis and cell proliferation have an impact on the tracer uptake.

Frequency-based time-series gene expression recomposition using PRIISM

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Rosa Bruce A

2012-06-01

Full Text Available Abstract Background Circadian rhythm pathways influence the expression patterns of as much as 31% of the Arabidopsis genome through complicated interaction pathways, and have been found to be significantly disrupted by biotic and abiotic stress treatments, complicating treatment-response gene discovery methods due to clock pattern mismatches in the fold change-based statistics. The PRIISM (Pattern Recomposition for the Isolation of Independent Signals in Microarray data algorithm outlined in this paper is designed to separate pattern changes induced by different forces, including treatment-response pathways and circadian clock rhythm disruptions. Results Using the Fourier transform, high-resolution time-series microarray data is projected to the frequency domain. By identifying the clock frequency range from the core circadian clock genes, we separate the frequency spectrum to different sections containing treatment-frequency (representing up- or down-regulation by an adaptive treatment response, clock-frequency (representing the circadian clock-disruption response and noise-frequency components. Then, we project the components’ spectra back to the expression domain to reconstruct isolated, independent gene expression patterns representing the effects of the different influences. By applying PRIISM on a high-resolution time-series Arabidopsis microarray dataset under a cold treatment, we systematically evaluated our method using maximum fold change and principal component analyses. The results of this study showed that the ranked treatment-frequency fold change results produce fewer false positives than the original methodology, and the 26-hour timepoint in our dataset was the best statistic for distinguishing the most known cold-response genes. In addition, six novel cold-response genes were discovered. PRIISM also provides gene expression data which represents only circadian clock influences, and may be useful for circadian clock studies

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

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Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P

2017-11-23

The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In

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

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Jun Seita

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

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.

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

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Liu, Xiao; Shi, Jun; Wang, Congzhi

2015-01-01

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

Amplification biases: possible differences among deviating gene expressions

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Piumi Francois

2008-01-01

Full Text Available Abstract Background Gene expression profiling has become a tool of choice to study pathological or developmental questions but in most cases the material is scarce and requires sample amplification. Two main procedures have been used: in vitro transcription (IVT and polymerase chain reaction (PCR, the former known as linear and the latter as exponential. Previous reports identified enzymatic pitfalls in PCR and IVT protocols; however the possible differences between the sequences affected by these amplification defaults were only rarely explored. Results Screening a bovine cDNA array dedicated to embryonic stages with embryonic (n = 3 and somatic tissues (n = 2, we proceeded to moderate amplifications starting from 1 μg of total RNA (global PCR or IVT one round. Whatever the tissue, 16% of the probes were involved in deviating gene expressions due to amplification defaults. These distortions were likely due to the molecular features of the affected sequences (position within a gene, GC content, hairpin number but also to the relative abundance of these transcripts within the tissues. These deviating genes mainly encoded housekeeping genes from physiological or cellular processes (70% and constituted 2 subsets which did not overlap (molecular features, signal intensities, gene ID. However, the differential expressions identified between embryonic stages were both reliable (minor intersect with biased expressions and relevant (biologically validated. In addition, the relative expression levels of those genes were biologically similar between amplified and unamplified samples. Conclusion Conversely to the most recent reports which challenged the use of intense amplification procedures on minute amounts of RNA, we chose moderate PCR and IVT amplifications for our gene profiling study. Conclusively, it appeared that systematic biases arose even with moderate amplification procedures, independently of (i the sample used: brain, ovary or embryos, (ii

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

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

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

The application of DNA microarrays in gene expression analysis.

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van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

2000-03-31

DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

Large-scale analysis of antisense transcription in wheat using the Affymetrix GeneChip Wheat Genome Array

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Settles Matthew L

2009-05-01

Full Text Available Abstract Background Natural antisense transcripts (NATs are transcripts of the opposite DNA strand to the sense-strand either at the same locus (cis-encoded or a different locus (trans-encoded. They can affect gene expression at multiple stages including transcription, RNA processing and transport, and translation. NATs give rise to sense-antisense transcript pairs and the number of these identified has escalated greatly with the availability of DNA sequencing resources and public databases. Traditionally, NATs were identified by the alignment of full-length cDNAs or expressed sequence tags to genome sequences, but an alternative method for large-scale detection of sense-antisense transcript pairs involves the use of microarrays. In this study we developed a novel protocol to assay sense- and antisense-strand transcription on the 55 K Affymetrix GeneChip Wheat Genome Array, which is a 3' in vitro transcription (3'IVT expression array. We selected five different tissue types for assay to enable maximum discovery, and used the 'Chinese Spring' wheat genotype because most of the wheat GeneChip probe sequences were based on its genomic sequence. This study is the first report of using a 3'IVT expression array to discover the expression of natural sense-antisense transcript pairs, and may be considered as proof-of-concept. Results By using alternative target preparation schemes, both the sense- and antisense-strand derived transcripts were labeled and hybridized to the Wheat GeneChip. Quality assurance verified that successful hybridization did occur in the antisense-strand assay. A stringent threshold for positive hybridization was applied, which resulted in the identification of 110 sense-antisense transcript pairs, as well as 80 potentially antisense-specific transcripts. Strand-specific RT-PCR validated the microarray observations, and showed that antisense transcription is likely to be tissue specific. For the annotated sense

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.

Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

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Kilpinen Sami

2010-05-01

Full Text Available Abstract Background Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s. Results In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42% neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis and to those with no MYCN amplification or 12q24.31 gain (good prognosis (P = 0.001. Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC

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.

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.

Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

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Jing Zhao

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

ArrayVigil: a methodology for statistical comparison of gene signatures using segregated-one-tailed (SOT) Wilcoxon's signed-rank test.

Science.gov (United States)

Khan, Haseeb Ahmad

2005-01-28

Due to versatile diagnostic and prognostic fidelity molecular signatures or fingerprints are anticipated as the most powerful tools for cancer management in the near future. Notwithstanding the experimental advancements in microarray technology, methods for analyzing either whole arrays or gene signatures have not been firmly established. Recently, an algorithm, ArraySolver has been reported by Khan for two-group comparison of microarray gene expression data using two-tailed Wilcoxon signed-rank test. Most of the molecular signatures are composed of two sets of genes (hybrid signatures) wherein up-regulation of one set and down-regulation of the other set collectively define the purpose of a gene signature. Since the direction of a selected gene's expression (positive or negative) with respect to a particular disease condition is known, application of one-tailed statistics could be a more relevant choice. A novel method, ArrayVigil, is described for comparing hybrid signatures using segregated-one-tailed (SOT) Wilcoxon signed-rank test and the results compared with integrated-two-tailed (ITT) procedures (SPSS and ArraySolver). ArrayVigil resulted in lower P values than those obtained from ITT statistics while comparing real data from four signatures.

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.

Classification of genes and putative biomarker identification using distribution metrics on expression profiles.

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Hung-Chung Huang

Full Text Available BACKGROUND: Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic, and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as 'brain group' and 'non-brain group'; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. CONCLUSIONS/SIGNIFICANCE: The methodology employed here may be used to facilitate disease-specific biomarker discovery.

Tandemly Arrayed Genes in Vertebrate Genomes

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Deng Pan

2008-01-01

Full Text Available Tandemly arrayed genes (TAGs are duplicated genes that are linked as neighbors on a chromosome, many of which have important physiological and biochemical functions. Here we performed a survey of these genes in 11 available vertebrate genomes. TAGs account for an average of about 14% of all genes in these vertebrate genomes, and about 25% of all duplications. The majority of TAGs (72–94% have parallel transcription orientation (i.e., they are encoded on the same strand in contrast to the genome, which has about 50% of its genes in parallel transcription orientation. The majority of tandem arrays have only two members. In all species, the proportion of genes that belong to TAGs tends to be higher in large gene families than in small ones; together with our recent finding that tandem duplication played a more important role than retroposition in large families, this fact suggests that among all types of duplication mechanisms, tandem duplication is the predominant mechanism of duplication, especially in large families. Finally, several species have a higher proportion of large tandem arrays that are species-specific than random expectation.

Optimised 'on demand' protein arraying from DNA by cell free expression with the 'DNA to Protein Array' (DAPA) technology.

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Schmidt, Ronny; Cook, Elizabeth A; Kastelic, Damjana; Taussig, Michael J; Stoevesandt, Oda

2013-08-02

We have previously described a protein arraying process based on cell free expression from DNA template arrays (DNA Array to Protein Array, DAPA). Here, we have investigated the influence of different array support coatings (Ni-NTA, Epoxy, 3D-Epoxy and Polyethylene glycol methacrylate (PEGMA)). Their optimal combination yields an increased amount of detected protein and an optimised spot morphology on the resulting protein array compared to the previously published protocol. The specificity of protein capture was improved using a tag-specific capture antibody on a protein repellent surface coating. The conditions for protein expression were optimised to yield the maximum amount of protein or the best detection results using specific monoclonal antibodies or a scaffold binder against the expressed targets. The optimised DAPA system was able to increase by threefold the expression of a representative model protein while conserving recognition by a specific antibody. The amount of expressed protein in DAPA was comparable to those of classically spotted protein arrays. Reaction conditions can be tailored to suit the application of interest. DAPA represents a cost effective, easy and convenient way of producing protein arrays on demand. The reported work is expected to facilitate the application of DAPA for personalized medicine and screening purposes. Copyright © 2013 Elsevier B.V. All rights reserved.

Theobroma cacao L. pathogenesis-related gene tandem array members show diverse expression dynamics in response to pathogen colonization.

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Fister, Andrew S; Mejia, Luis C; Zhang, Yufan; Herre, Edward Allen; Maximova, Siela N; Guiltinan, Mark J

2016-05-17

The pathogenesis-related (PR) group of proteins are operationally defined as polypeptides that increase in concentration in plant tissues upon contact with a pathogen. To date, 17 classes of highly divergent proteins have been described that act through multiple mechanisms of pathogen resistance. Characterizing these families in cacao, an economically important tree crop, and comparing the families to those in other species, is an important step in understanding cacao's immune response. Using publically available resources, all members of the 17 recognized pathogenesis-related gene families in the genome of Theobroma cacao were identified and annotated resulting in a set of ~350 members in both published cacao genomes. Approximately 50 % of these genes are organized in tandem arrays scattered throughout the genome. This feature was observed in five additional plant taxa (three dicots and two monocots), suggesting that tandem duplication has played an important role in the evolution of the PR genes in higher plants. Expression profiling captured the dynamics and complexity of PR genes expression at basal levels and after induction by two cacao pathogens (the oomycete, Phytophthora palmivora, and the fungus, Colletotrichum theobromicola), identifying specific genes within families that are more responsive to pathogen challenge. Subsequent qRT-PCR validated the induction of several PR-1, PR-3, PR-4, and PR-10 family members, with greater than 1000 fold induction detected for specific genes. We describe candidate genes that are likely to be involved in cacao's defense against Phytophthora and Colletotrichum infection and could be potentially useful for marker-assisted selection for breeding of disease resistant cacao varieties. The data presented here, along with existing cacao-omics resources, will enable targeted functional genetic screening of defense genes likely to play critical functions in cacao's defense against its pathogens.

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

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

2009-01-01

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

Cell array-based intracellular localization screening reveals novel functional features of human chromosome 21 proteins

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Kahlem Pascal

2006-06-01

Full Text Available Abstract Background Trisomy of human chromosome 21 (Chr21 results in Down's syndrome, a complex developmental and neurodegenerative disease. Molecular analysis of Down's syndrome, however, poses a particular challenge, because the aneuploid region of Chr21 contains many genes of unknown function. Subcellular localization of human Chr21 proteins may contribute to further understanding of the functions and regulatory mechanisms of the genes that code for these proteins. Following this idea, we used a transfected-cell array technique to perform a rapid and cost-effective analysis of the intracellular distribution of Chr 21 proteins. Results We chose 89 genes that were distributed over the majority of 21q, ranging from RBM11 (14.5 Mb to MCM3AP (46.6 Mb, with part of them expressed aberrantly in the Down's syndrome mouse model. Open reading frames of these genes were cloned into a mammalian expression vector with an amino-terminal His6 tag. All of the constructs were arrayed on glass slides and reverse transfected into HEK293T cells for protein expression. Co-localization detection using a set of organelle markers was carried out for each Chr21 protein. Here, we report the subcellular localization properties of 52 proteins. For 34 of these proteins, their localization is described for the first time. Furthermore, the alteration in cell morphology and growth as a result of protein over-expression for claudin-8 and claudin-14 genes has been characterized. Conclusion The cell array-based protein expression and detection approach is a cost-effective platform for large-scale functional analyses, including protein subcellular localization and cell phenotype screening. The results from this study reveal novel functional features of human Chr21 proteins, which should contribute to further understanding of the molecular pathology of Down's syndrome.

Global Expression Patterns of Three Festuca Species Exposed to Different Doses of Glyphosate Using the Affymetrix GeneChip Wheat Genome Array

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Ozge Cebeci

2009-01-01

Full Text Available Glyphosate has been shown to act as an inhibitor of an aromatic amino acid biosynthetic pathway, while other pathways that may be affected by glyphosate are not known. Cross species hybridizations can provide a tool for elucidating biological pathways conserved among organisms. Comparative genome analyses have indicated a high level of colinearity among grass species and Festuca, on which we focus here, and showed rearrangements common to the Pooideae family. Based on sequence conservation among grass species, we selected the Affymetrix GeneChip Wheat Genome Array as a tool for the analysis of expression profiles of three Festuca (fescue species with distinctly different tolerances to varying levels of glyphosate. Differences in transcript expression were recorded upon foliar glyphosate application at 1.58 mM and 6.32 mM, representing 5% and 20%, respectively, of the recommended rate. Differences highlighted categories of general metabolic processes, such as photosynthesis, protein synthesis, stress responses, and a larger number of transcripts responded to 20% glyphosate application. Differential expression of genes encoding proteins involved in the shikimic acid pathway could not be identified by cross hybridization. Microarray data were confirmed by RT-PCR and qRT-PCR analyses. This is the first report to analyze the potential of cross species hybridization in Fescue species and the data and analyses will help extend our knowledge on the cellular processes affected by glyphosate.

A Fisheye Viewer for microarray-based gene expression data.

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Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

2006-10-13

Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

Supervised classification of combined copy number and gene expression data

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Riccadonna S.

2007-12-01

Full Text Available In this paper we apply a predictive profiling method to genome copy number aberrations (CNA in combination with gene expression and clinical data to identify molecular patterns of cancer pathophysiology. Predictive models and optimal feature lists for the platforms are developed by a complete validation SVM-based machine learning system. Ranked list of genome CNA sites (assessed by comparative genomic hybridization arrays – aCGH and of differentially expressed genes (assessed by microarray profiling with Affy HG-U133A chips are computed and combined on a breast cancer dataset for the discrimination of Luminal/ ER+ (Lum/ER+ and Basal-like/ER- classes. Different encodings are developed and applied to the CNA data, and predictive variable selection is discussed. We analyze the combination of profiling information between the platforms, also considering the pathophysiological data. A specific subset of patients is identified that has a different response to classification by chromosomal gains and losses and by differentially expressed genes, corroborating the idea that genomic CNA can represent an independent source for tumor classification.

Differential Gene Expression of Fibroblasts: Keloid versus Normal

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Michael F. Angel

2002-11-01

Full Text Available Abstract: This study investigated gene regulation and unique gene products in both keloid (KDF and normal (NDF dermal fibroblasts in established cell lines. For gene regulation, NDF versus KDF were compared using Clontech's Atlas™ Human cDNA Expression Array while unique gene products were studied using RNA Fingerprinting Kit. RNA from each sample was converted to cDNA using oligo-dT primers. Down-regulated genes using Atlas Array in KDF were 1 60 S ribosomal protein, 2 Thioredoxin dependent peroxidase, 3 Nuclease sensitive element DNA binding protein, 4 c-myc purine-binding transcription factor, 5 c-AMP dependent protein kinase, and, 6 Heat Shock Protein 90 kDa. Genes that are up regulated in KDF were 1 Tubulin and 2 Heat Shock Protein 27 kDa. With the differential display, we found 17 bands unique to both KDF and NDF. The specific gene and the manner in which they were differentially regulated have direct implications to understanding keloid fibroblast proliferation.

DNA array analysis of gene expression changes by Choto-san in the ischemic rat brain

OpenAIRE

Tohda, Michihisa; Matsumoto, Kinzo; Hayashi, Hisae; Murakami, Yukihisa; Watanabe, Hiroshi

2004-01-01

The effects of Choto-san on gene expression in the dementia model rat brain were studied using a DNA microarray system. Choto-san inhibited the expression of 181 genes that has been enhanced by permanent occlusion of the bilateral common carotid arteries (2VO). Choto-san also reversed the expression inhibition of 32 genes induced by 2VO. These results may suggest that Choto-san, which has been therapeutically used as an antidementive drug, shows therapeutic effects through gene expression cha...

Imaging gene expression in gene therapy

International Nuclear Information System (INIS)

Wiebe, Leonard I.

1997-01-01

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

Nitrate-induced genes in tomato roots. Array analysis reveals novel genes that may play a role in nitrogen nutrition.

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Wang, Y H; Garvin, D F; Kochian, L V

2001-09-01

A subtractive tomato (Lycopersicon esculentum) root cDNA library enriched in genes up-regulated by changes in plant mineral status was screened with labeled mRNA from roots of both nitrate-induced and mineral nutrient-deficient (-nitrogen [N], -phosphorus, -potassium [K], -sulfur, -magnesium, -calcium, -iron, -zinc, and -copper) tomato plants. A subset of cDNAs was selected from this library based on mineral nutrient-related changes in expression. Additional cDNAs were selected from a second mineral-deficient tomato root library based on sequence homology to known genes. These selection processes yielded a set of 1,280 mineral nutrition-related cDNAs that were arrayed on nylon membranes for further analysis. These high-density arrays were hybridized with mRNA from tomato plants exposed to nitrate at different time points after N was withheld for 48 h, for plants that were grown on nitrate/ammonium for 5 weeks prior to the withholding of N. One hundred-fifteen genes were found to be up-regulated by nitrate resupply. Among these genes were several previously identified as nitrate responsive, including nitrate transporters, nitrate and nitrite reductase, and metabolic enzymes such as transaldolase, transketolase, malate dehydrogenase, asparagine synthetase, and histidine decarboxylase. We also identified 14 novel nitrate-inducible genes, including: (a) water channels, (b) root phosphate and K(+) transporters, (c) genes potentially involved in transcriptional regulation, (d) stress response genes, and (e) ribosomal protein genes. In addition, both families of nitrate transporters were also found to be inducible by phosphate, K, and iron deficiencies. The identification of these novel nitrate-inducible genes is providing avenues of research that will yield new insights into the molecular basis of plant N nutrition, as well as possible networking between the regulation of N, phosphorus, and K nutrition.

Defects in rhizobial cyclic glucan and lipopolysaccharide synthesis alter legume gene expression during nodule development

DEFF Research Database (Denmark)

D'Antuono, Alejandra L; Ott, Thomas; Krusell, Lene

2008-01-01

cDNA array technology was used to compare transcriptome profiles of Lotus japonicus roots inoculated with a Mesorhizobium loti wild-type and two mutant strains affected in cyclic beta(1-2) glucan synthesis (cgs) and in lipopolysaccharide synthesis (lpsbeta2). Expression of genes associated...... with the development of a fully functional nodule was significantly affected in plants inoculated with the cgs mutant. Array results also revealed that induction of marker genes for nodule development was delayed when plants were inoculated with the lpsbeta2 mutant. Quantitative real-time reverse......-transcriptase polymerase chain reaction was used to quantify gene expression of a subset of genes involved in plant defense response, redox metabolism, or genes that encode for nodulins. The majority of the genes analyzed in this study were more highly expressed in roots inoculated with the wild type compared with those...

Blood-based gene-expression predictors of PTSD risk and resilience among deployed marines: a pilot study.

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Glatt, Stephen J; Tylee, Daniel S; Chandler, Sharon D; Pazol, Joel; Nievergelt, Caroline M; Woelk, Christopher H; Baker, Dewleen G; Lohr, James B; Kremen, William S; Litz, Brett T; Tsuang, Ming T

2013-06-01

Susceptibility to PTSD is determined by both genes and environment. Similarly, gene-expression levels in peripheral blood are influenced by both genes and environment, and expression levels of many genes show good correspondence between peripheral blood and brain. Therefore, our objectives were to test the following hypotheses: (1) pre-trauma expression levels of a gene subset (particularly immune-system genes) in peripheral blood would differ between trauma-exposed Marines who later developed PTSD and those who did not; (2) a predictive biomarker panel of the eventual emergence of PTSD among high-risk individuals could be developed based on gene expression in readily assessable peripheral blood cells; and (3) a predictive panel based on expression of individual exons would surpass the accuracy of a model based on expression of full-length gene transcripts. Gene-expression levels were assayed in peripheral blood samples from 50 U.S. Marines (25 eventual PTSD cases and 25 non-PTSD comparison subjects) prior to their deployment overseas to war-zones in Iraq or Afghanistan. The panel of biomarkers dysregulated in peripheral blood cells of eventual PTSD cases prior to deployment was significantly enriched for immune genes, achieved 70% prediction accuracy in an independent sample based on the expression of 23 full-length transcripts, and attained 80% accuracy in an independent sample based on the expression of one exon from each of five genes. If the observed profiles of pre-deployment mRNA-expression in eventual PTSD cases can be further refined and replicated, they could suggest avenues for early intervention and prevention among individuals at high risk for trauma exposure. Copyright © 2013 Wiley Periodicals, Inc.

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

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.

Array-based techniques for fingerprinting medicinal herbs

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Xue Charlie

2011-05-01

Full Text Available Abstract Poor quality control of medicinal herbs has led to instances of toxicity, poisoning and even deaths. The fundamental step in quality control of herbal medicine is accurate identification of herbs. Array-based techniques have recently been adapted to authenticate or identify herbal plants. This article reviews the current array-based techniques, eg oligonucleotides microarrays, gene-based probe microarrays, Suppression Subtractive Hybridization (SSH-based arrays, Diversity Array Technology (DArT and Subtracted Diversity Array (SDA. We further compare these techniques according to important parameters such as markers, polymorphism rates, restriction enzymes and sample type. The applicability of the array-based methods for fingerprinting depends on the availability of genomics and genetics of the species to be fingerprinted. For the species with few genome sequence information but high polymorphism rates, SDA techniques are particularly recommended because they require less labour and lower material cost.

Imaging gene expression in gene therapy

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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

A fisheye viewer for microarray-based gene expression data

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Munson Ethan V

2006-10-01

Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

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.

Gene array analysis of PD-1H overexpressing monocytes reveals a pro-inflammatory profile

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Preeti Bharaj

2018-02-01

Full Text Available We have previously reported that overexpression of Programmed Death -1 Homolog (PD-1H in human monocytes leads to activation and spontaneous secretion of multiple pro inflammatory cytokines. Here we evaluate changes in monocytes gene expression after enforced PD-1H expression by gene array. The results show that there are significant alterations in 51 potential candidate genes that relate to immune response, cell adhesion and metabolism. Genes corresponding to pro-inflammatory cytokines showed the highest upregulation, 7, 3.2, 3.0, 5.8, 4.4 and 3.1 fold upregulation of TNF-α, IL-1 β, IFN-α, γ, λ and IL-27 relative to vector control. The data are in agreement with cytometric bead array analysis showing induction of proinflammatory cytokines, IL-6, IL-1β and TNF-α by PD-1H. Other genes related to inflammation, include transglutaminase 2 (TG2, NF-κB (p65 and p50 and toll like receptors (TLR 3 and 4 were upregulated 5, 4.5 and 2.5 fold, respectively. Gene set enrichment analysis (GSEA also revealed that signaling pathways related to inflammatory response, such as NFκB, AT1R, PYK2, MAPK, RELA, TNFR1, MTOR and proteasomal degradation, were significantly upregulated in response to PD-1H overexpression. We validated the results utilizing a standard inflammatory sepsis model in humanized BLT mice, finding that PD-1H expression was highly correlated with proinflammatory cytokine production. We therefore conclude that PD-1H functions to enhance monocyte activation and the induction of a pro-inflammatory gene expression profile.

HuMiChip: Development of a Functional Gene Array for the Study of Human Microbiomes

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Tu, Q.; Deng, Ye; Lin, Lu; Hemme, Chris L.; He, Zhili; Zhou, Jizhong

2010-05-17

Microbiomes play very important roles in terms of nutrition, health and disease by interacting with their hosts. Based on sequence data currently available in public domains, we have developed a functional gene array to monitor both organismal and functional gene profiles of normal microbiota in human and mouse hosts, and such an array is called human and mouse microbiota array, HMM-Chip. First, seed sequences were identified from KEGG databases, and used to construct a seed database (seedDB) containing 136 gene families in 19 metabolic pathways closely related to human and mouse microbiomes. Second, a mother database (motherDB) was constructed with 81 genomes of bacterial strains with 54 from gut and 27 from oral environments, and 16 metagenomes, and used for selection of genes and probe design. Gene prediction was performed by Glimmer3 for bacterial genomes, and by the Metagene program for metagenomes. In total, 228,240 and 801,599 genes were identified for bacterial genomes and metagenomes, respectively. Then the motherDB was searched against the seedDB using the HMMer program, and gene sequences in the motherDB that were highly homologous with seed sequences in the seedDB were used for probe design by the CommOligo software. Different degrees of specific probes, including gene-specific, inclusive and exclusive group-specific probes were selected. All candidate probes were checked against the motherDB and NCBI databases for specificity. Finally, 7,763 probes covering 91.2percent (12,601 out of 13,814) HMMer confirmed sequences from 75 bacterial genomes and 16 metagenomes were selected. This developed HMM-Chip is able to detect the diversity and abundance of functional genes, the gene expression of microbial communities, and potentially, the interactions of microorganisms and their hosts.

Patterns of Bacterial and Archaeal Gene Expression through the Lower Amazon River

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Brandon M. Satinsky

2017-08-01

Full Text Available Analysis of metatranscriptomic and metagenomic datasets from the lower reaches of the Amazon River between Óbidos and the river mouth revealed microbial transcript and gene pools dominated by Actinobacteria, Thaumarchaeota, Bacteroidetes, Acidobacteria, Betaproteobacteria, and Planctomycetes. Three mainstem stations spanning a 625 km reach had similar gene expression patterns (transcripts gene copy−1 across a diverse suite of element cycling genes, but two tributary-influenced stations at the mouth of the Tapajós River and near the Tocantins River at Belém had distinct transcriptome composition and expression ratios, particularly for genes encoding light-related energy capture (higher and iron acquisition and ammonia oxidation (lower. Environmental parameters that were useful predictors of gene expression ratios included concentrations of lignin phenols, suspended sediments, nitrate, phosphate, and particulate organic carbon and nitrogen. Similar to the gene expression data, these chemical properties reflected highly homogeneous mainstem stations punctuated by distinct tributary-influenced stations at Tapajós and Belém. Although heterotrophic processes were expected to dominate in the lower Amazon, transcripts from photosynthetic bacteria were abundant in tributary-influenced regions, and transcripts from Thaumarcheota taxa genetically capable of chemosynthetic ammonia oxidation accounted for up to 21% of the transcriptome at others. Based on regressions of transcript numbers against gene numbers, expression ratios of Thaumarchaeota populations were largely unchanged within the mainstem, suggesting a relatively minor role for gene regulation. These quantitative gene and transcript inventories detail a diverse array of energy acquisition strategies and metabolic capabilities for bacteria and archaea populations of the world's largest river system.

Patterns of Bacterial and Archaeal Gene Expression through the Lower Amazon River

Energy Technology Data Exchange (ETDEWEB)

Satinsky, Brandon M.; Smith, Christa B.; Sharma, Shalabh; Ward, Nicholas D.; Krusche, Alex V.; Richey, Jeffrey E.; Yager, Patricia L.; Crump, Byron C.; Moran, Mary Ann

2017-08-08

Analysis of metatranscriptomic and metagenomic datasets from the lower reaches of the Amazon River between Obidos and the river mouth revealed microbial transcript and gene pools dominated by Actinobacteria, Thaumarchaeota, Bacteroidetes, Acidobacteria, Betaproteobacteria, and Planctomycetes. Three mainstem stations spanning a 625 km reach had similar gene expression patterns (transcripts gene copy-1) across a diverse suite of element cycling genes, but two tributary-influenced stations at the mouth of the Tapajos River and near the Tocantins River at Belem had distinct transcriptome composition and expression ratios, particularly for genes encoding light-related energy capture (higher) and iron acquisition and ammonia oxidation (lower). Environmental parameters that were useful predictors of gene expression ratios included concentrations of lignin phenols, suspended sediments, nitrate, phosphate, and particulate organic carbon and nitrogen. Similar to the gene expression data, these chemical properties reflected highly homogeneous mainstem stations punctuated by distinct tributary- influenced stations at Tapajos and Belem. Although heterotrophic processes were expected to dominate in the lower Amazon, transcripts from photosynthetic bacteria were abundant in tributary-influenced regions, and transcripts from Thaumarcheota taxa genetically capable of chemosynthetic ammonia oxidation accounted for up to 21% of the transcriptome at others. Based on regressions of transcript numbers against gene numbers, expression ratios of Thaumarchaeota populations were largely unchanged within the mainstem, suggesting a relatively minor role for gene regulation. These quantitative gene and transcript inventories detail a diverse array of energy acquisition strategies and metabolic capabilities for bacteria and archaea populations of the world’s largest river system.

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...

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

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

2016-01-01

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

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

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Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

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

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

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Samuel Sunghwan Cho

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

Large-scale image-based profiling of single-cell phenotypes in arrayed CRISPR-Cas9 gene perturbation screens.

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de Groot, Reinoud; Lüthi, Joel; Lindsay, Helen; Holtackers, René; Pelkmans, Lucas

2018-01-23

High-content imaging using automated microscopy and computer vision allows multivariate profiling of single-cell phenotypes. Here, we present methods for the application of the CISPR-Cas9 system in large-scale, image-based, gene perturbation experiments. We show that CRISPR-Cas9-mediated gene perturbation can be achieved in human tissue culture cells in a timeframe that is compatible with image-based phenotyping. We developed a pipeline to construct a large-scale arrayed library of 2,281 sequence-verified CRISPR-Cas9 targeting plasmids and profiled this library for genes affecting cellular morphology and the subcellular localization of components of the nuclear pore complex (NPC). We conceived a machine-learning method that harnesses genetic heterogeneity to score gene perturbations and identify phenotypically perturbed cells for in-depth characterization of gene perturbation effects. This approach enables genome-scale image-based multivariate gene perturbation profiling using CRISPR-Cas9. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Cytomegalovirus replicon-based regulation of gene expression in vitro and in vivo.

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Hermine Mohr

Full Text Available There is increasing evidence for a connection between DNA replication and the expression of adjacent genes. Therefore, this study addressed the question of whether a herpesvirus origin of replication can be used to activate or increase the expression of adjacent genes. Cell lines carrying an episomal vector, in which reporter genes are linked to the murine cytomegalovirus (MCMV origin of lytic replication (oriLyt, were constructed. Reporter gene expression was silenced by a histone-deacetylase-dependent mechanism, but was resolved upon lytic infection with MCMV. Replication of the episome was observed subsequent to infection, leading to the induction of gene expression by more than 1000-fold. oriLyt-based regulation thus provided a unique opportunity for virus-induced conditional gene expression without the need for an additional induction mechanism. This principle was exploited to show effective late trans-complementation of the toxic viral protein M50 and the glycoprotein gO of MCMV. Moreover, the application of this principle for intracellular immunization against herpesvirus infection was demonstrated. The results of the present study show that viral infection specifically activated the expression of a dominant-negative transgene, which inhibited viral growth. This conditional system was operative in explant cultures of transgenic mice, but not in vivo. Several applications are discussed.

Allele-specific expression in the germline of patients with familial pancreatic cancer: An unbiased approach to cancer gene discovery

OpenAIRE

Tan, Aik Choon; Fan, Jian-Bing; Karikari, Collins; Bibikova, Marina; Garcia, Eliza Wickham; Zhou, Lixin; Barker, David; Serre, David; Feldmann, Georg; Hruban, Ralph H.; Klein, Alison P.; Goggins, Michael; Couch, Fergus J.; Hudson, Thomas J.; Winslow, Raimond L.

2007-01-01

Physiologic allele-specific expression (ASE) in germline tissues occurs during random X-chromosome inactivation1 and in genomic imprinting,2 wherein the two alleles of a gene in a heterozygous individual are not expressed equally. Recent studies have confirmed the existence of ASE in apparently non-imprinted autosomal genes;3–14 however, the extent of ASE in the human genome is unknown. We explored ASE in lymphoblastoid cell lines of 145 individuals using an oligonucleotide array based assay....

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.

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.

Modeling gene expression measurement error: a quasi-likelihood approach

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Strimmer Korbinian

2003-03-01

Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also

Differential gene expression in anterior pituitary glands from anestrous and cycling postpartum beef cows

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Oligionucleotide microarrays (GeneChip Bovine Genome Arrays, Affymetrix Inc., Santa Clara, CA) were used to evaluate gene expression profiles in anterior pituitary glands collected from 4 anestrous and 4 cycling postpartum primiparous beef cows to provide insight into genes associated with transitio...

Oxygen and tissue culture affect placental gene expression.

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Brew, O; Sullivan, M H F

2017-07-01

Placental explant culture is an important model for studying placental development and functions. We investigated the differences in placental gene expression in response to tissue culture, atmospheric and physiologic oxygen concentrations. Placental explants were collected from normal term (38-39 weeks of gestation) placentae with no previous uterine contractile activity. Placental transcriptomic expressions were evaluated with GeneChip ® Human Genome U133 Plus 2.0 arrays (Affymetrix). We uncovered sub-sets of genes that regulate response to stress, induction of apoptosis programmed cell death, mis-regulation of cell growth, proliferation, cell morphogenesis, tissue viability, and protection from apoptosis in cultured placental explants. We also identified a sub-set of genes with highly unstable pattern of expression after exposure to tissue culture. Tissue culture irrespective of oxygen concentration induced dichotomous increase in significant gene expression and increased enrichment of significant pathways and transcription factor targets (TFTs) including HIF1A. The effect was exacerbated by culture at atmospheric oxygen concentration, where further up-regulation of TFTs including PPARA, CEBPD, HOXA9 and down-regulated TFTs such as JUND/FOS suggest intrinsic heightened key biological and metabolic mechanisms such as glucose use, lipid biosynthesis, protein metabolism; apoptosis, inflammatory responses; and diminished trophoblast proliferation, differentiation, invasion, regeneration, and viability. These findings demonstrate that gene expression patterns differ between pre-culture and cultured explants, and the gene expression of explants cultured at atmospheric oxygen concentration favours stressed, pro-inflammatory and increased apoptotic transcriptomic response. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2008-01-01

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

Influence of high-frequency electromagnetic fields on different modes of cell death and gene expression.

Science.gov (United States)

Port, M; Abend, M; Römer, B; Van Beuningen, D

2003-09-01

International thresholds for exposure to non-ionizing radiation leading to non-thermal effects were conservatively set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The aim of this study was to examine whether biological effects such as different modes of cell death and gene expression modifications related to tumorgenesis are detectable above the threshold defined. Human leukaemia cells (HL-60) grown in vitro were exposed to electromagnetic fields (EMF; t 1/2(r) about 1 ns; field strength about 25 times higher than the ICNIRP reference levels for occupational exposure) leading to non-thermal effects using a high-voltage-improved GTEM cell 5302 (EMCO) connected to a pulse generator NP20 (C = 1 nF, U(Load) = 20kV). HL-60 cells were harvested at 0, 24, 48 and 72 h after radiation exposure. Micronuclei, apoptosis and abnormal cells (e.g. necrosis) were determined using morphological criteria. In parallel, the expression of 1176 genes was measured using Atlas Human 1.2. Array. Based on high data reproducibility calculated from two independent experiments (> 99%), array analysis was performed. No significant change in apoptosis, micronucleation, abnormal cells and differential gene expression was found. Exposure of HL-60 cells to EMFs 25 times higher than the ICNIRP reference levels for occupational exposure failed to induce any changes in apoptosis, micronucleation, abnormal morphologies and gene expression. Further experiments using EMFs above the conservatively defined reference level set by the ICNIRP may be desirable.

Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

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Lee Yun-Shien

2008-03-01

Full Text Available Abstract Background The hierarchical clustering tree (HCT with a dendrogram 1 and the singular value decomposition (SVD with a dimension-reduced representative map 2 are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures. Results This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose seriation by Chen 3 as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends. Conclusion We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at http://gap.stat.sinica.edu.tw/Software/GAP.

Cancer Outlier Analysis Based on Mixture Modeling of Gene Expression Data

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Keita Mori

2013-01-01

Full Text Available Molecular heterogeneity of cancer, partially caused by various chromosomal aberrations or gene mutations, can yield substantial heterogeneity in gene expression profile in cancer samples. To detect cancer-related genes which are active only in a subset of cancer samples or cancer outliers, several methods have been proposed in the context of multiple testing. Such cancer outlier analyses will generally suffer from a serious lack of power, compared with the standard multiple testing setting where common activation of genes across all cancer samples is supposed. In this paper, we consider information sharing across genes and cancer samples, via a parametric normal mixture modeling of gene expression levels of cancer samples across genes after a standardization using the reference, normal sample data. A gene-based statistic for gene selection is developed on the basis of a posterior probability of cancer outlier for each cancer sample. Some efficiency improvement by using our method was demonstrated, even under settings with misspecified, heavy-tailed t-distributions. An application to a real dataset from hematologic malignancies is provided.

DNA micro array analysis of yeast global genome expression in response to ELF-MF exposure

International Nuclear Information System (INIS)

Shimizu, K.; Yamamoto, T.; Ishibashi, T.; Kyoh, B.

2002-01-01

There is wide spread public concern over the possible health risk of ELF-MF. Electromagnetic fields may produce a variety of effects in several biological systems, including the elevation of cancer risk and reduction of cell growth. Epidemiological studies have shown weak correlations between the exposure to ELF and the incidence of several cancers, but negative studies have also been reported. Moreover, there are some reports that basic biological events such as the cell cycle and DNA replication were affected by exposure to MF. However, to date the molecular mechanism of the MF effect on living organism is not clear. In this study, we used yeast DNA micro array to examine the transcriptional profile of all genes in response to ELF-MF. A few years ago it was difficult to carry out a global gene expression study to identify important genes regarding ELF-MF, however, today DNA micro arrays allow gene regulation in response to high density ELF-MF exposure. Thus we used micro array to analyze changes in mRNA abundance during ELF-MF exposure

Linear Energy Transfer-Dependent Change in Rice Gene Expression Profile after Heavy-Ion Beam Irradiation.

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Ishii, Kotaro; Kazama, Yusuke; Morita, Ryouhei; Hirano, Tomonari; Ikeda, Tokihiro; Usuda, Sachiko; Hayashi, Yoriko; Ohbu, Sumie; Motoyama, Ritsuko; Nagamura, Yoshiaki; Abe, Tomoko

2016-01-01

A heavy-ion beam has been recognized as an effective mutagen for plant breeding and applied to the many kinds of crops including rice. In contrast with X-ray or γ-ray, the heavy-ion beam is characterized by a high linear energy transfer (LET). LET is an important factor affecting several aspects of the irradiation effect, e.g. cell survival and mutation frequency, making the heavy-ion beam an effective mutagen. To study the mechanisms behind LET-dependent effects, expression profiling was performed after heavy-ion beam irradiation of imbibed rice seeds. Array-based experiments at three time points (0.5, 1, 2 h after the irradiation) revealed that the number of up- or down-regulated genes was highest 2 h after irradiation. Array-based experiments with four different LETs at 2 h after irradiation identified LET-independent regulated genes that were up/down-regulated regardless of the value of LET; LET-dependent regulated genes, whose expression level increased with the rise of LET value, were also identified. Gene ontology (GO) analysis of LET-independent up-regulated genes showed that some GO terms were commonly enriched, both 2 hours and 3 weeks after irradiation. GO terms enriched in LET-dependent regulated genes implied that some factor regulates genes that have kinase activity or DNA-binding activity in cooperation with the ATM gene. Of the LET-dependent up-regulated genes, OsPARP3 and OsPCNA were identified, which are involved in DNA repair pathways. This indicates that the Ku-independent alternative non-homologous end-joining pathway may contribute to repairing complex DNA legions induced by high-LET irradiation. These findings may clarify various LET-dependent responses in rice.

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

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Skubitz Amy PN

2008-05-01

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

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...

Gene expression profiling of brakeless mutant Drosophila embryos.

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Crona, Filip; Singla, Bhumica; Mannervik, Mattias

2015-12-01

The transcriptional co-regulator Brakeless performs many important functions during Drosophila development, but few target genes have been identified. Here we use Affymetrix microarrays to identify Brakeless-regulated genes in 2-4 h old Drosophila embryos. Robust multi-array analysis (RMA) and statistical tests revealed 240 genes that changed their expression more than 1.5 fold. We find that up- and down-regulated genes fall into distinct gene ontology categories. In our associated study [2] we demonstrate that both up- and down-regulated genes can be direct Brakeless targets. Our results indicate that the co-repressor and co-activator activities of Brakeless may result in distinct biological responses. The microarray data complies with MIAME guidelines and is deposited in GEO under accession number GSE60048.

Can subtle changes in gene expression be consistently detected with different microarray platforms?

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Kuiper Rowan

2008-03-01

Full Text Available Abstract Background The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Results Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms. Quantitative RT-PCR analysis confirmed 20 out of 28 of the genes detected by two or more platforms and 8 out of 15 of the genes detected by Agilent only. We observed improved correlations between platforms when ranking the genes based on the significance level than with a fixed statistical cut-off. We demonstrate significant overlap in the affected gene sets identified by the different platforms, although biological processes were represented by only partially overlapping sets of genes. Aberrances in GABA-ergic signalling in the transgenic mice were consistently found by all platforms. Conclusion The different microarray platforms give partially complementary views on biological processes affected. Our data indicate that when analyzing samples with only subtle differences in gene expression the use of two different platforms might be more attractive than increasing the number of replicates. Commercial two-color platforms seem to

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

International Nuclear Information System (INIS)

Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

2008-01-01

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

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Ergul Gulusan

2008-12-01

Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

Correlation of mRNA and protein levels: Cell type-specific gene expression of cluster designation antigens in the prostate

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Deutsch Eric W

2008-05-01

Full Text Available Abstract Background: Expression levels of mRNA and protein by cell types exhibit a range of correlations for different genes. In this study, we compared levels of mRNA abundance for several cluster designation (CD genes determined by gene arrays using magnetic sorted and laser-capture microdissected human prostate cells with levels of expression of the respective CD proteins determined by immunohistochemical staining in the major cell types of the prostate – basal epithelial, luminal epithelial, stromal fibromuscular, and endothelial – and for prostate precursor/stem cells and prostate carcinoma cells. Immunohistochemical stains of prostate tissues from more than 50 patients were scored for informative CD antigen expression and compared with cell-type specific transcriptomes. Results: Concordance between gene and protein expression findings based on 'present' vs. 'absent' calls ranged from 46 to 68%. Correlation of expression levels was poor to moderate (Pearson correlations ranged from 0 to 0.63. Divergence between the two data types was most frequently seen for genes whose array signals exceeded background (> 50 but lacked immunoreactivity by immunostaining. This could be due to multiple factors, e.g. low levels of protein expression, technological sensitivities, sample processing, probe set definition or anatomical origin of tissue and actual biological differences between transcript and protein abundance. Conclusion: Agreement between these two very different methodologies has great implications for their respective use in both molecular studies and clinical trials employing molecular biomarkers.

Gene expression profiling of three different stressors in the water flea Daphnia magna.

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Jansen, Mieke; Vergauwen, Lucia; Vandenbrouck, Tine; Knapen, Dries; Dom, Nathalie; Spanier, Katina I; Cielen, Anke; De Meester, Luc

2013-07-01

Microarrays are an ideal tool to screen for differences in gene expression of thousands of genes simultaneously. However, often commercial arrays are not available. In this study, we performed microarray analyses to evaluate patterns of gene transcription following exposure to two natural and one anthropogenic stressor. cDNA microarrays compiled of three life stage specific and three stressor-specific EST libraries, yielding 1734 different EST sequences, were used. We exposed juveniles of the water flea Daphnia magna for 48, 96 and 144 h to three stressors known to exert strong selection in natural populations of this species i.e. a sublethal concentration of the pesticide carbaryl, infective spores of the endoparasite Pasteuria ramosa, and fish predation risk mimicked by exposure to fish kairomones. A total of 148 gene fragments were differentially expressed compared to the control. Based on a PCA, the exposure treatments were separated into two main groups based on the extent of the transcriptional response: a low and a high (144 h of fish or carbaryl exposure and 96 h of parasite exposure) stress group. Firstly, we observed a general stress-related transcriptional expression profile independent of the treatment characterized by repression of transcripts involved in transcription, translation, signal transduction and energy metabolism. Secondly, we observed treatment-specific responses including signs of migration to deeper water layers in response to fish predation, structural challenge of the cuticle in response to carbaryl exposure, and disturbance of the ATP production in parasite exposure. A third important conclusion is that transcription expression patterns exhibit stress-specific changes over time. Parasite exposure shows the most differentially expressed gene fragments after 96 h. The peak of differentially expressed transcripts came only after 144 h of fish exposure, while carbaryl exposure induced a more stable number of differently expressed gene

Dysregulation of gene expression within the peroxisome proliferator activated receptor pathway in morbidly obese patients.

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Hindle, A Katharine; Koury, Jadd; McCaffrey, Tim; Fu, Sidney W; Brody, Fred

2009-06-01

The causes of obesity are multifactorial but may include dysregulation of a family of related genes, such as the peroxisome proliferator activated receptor gamma (PPARgamma). When activated, the PPARgamma pathway promotes lipid metabolism. This study used microarray technology to evaluate differential gene expression profiles in obese patients undergoing bariatric surgery. The study enrolled six morbidly obese patients with a body mass index (BMI) exceeding 35 and four nonobese individuals. Blood samples were stabilized in PaxGene tubes (PreAnalytiX), and total RNA was extracted. Next, 100 ng of total RNA was amplified and labeled using the Ovation RNA Amplification System V2 with the Ovation whole-blood reagent (NuGen) before it was hybridized to an Affymetrix (Santa Clara, CA) focus array containing more than 8,500 verified genes. The data were analyzed using an analysis of variance (ANOVA) (p < 0.05) in the GeneSpring program, and potential pathways were identified with the Ingenuity program. Real-time quantitative reverse transcriptase-polymerase chain reaction was used to validate the array data. A total of 97 upregulated genes and 125 downregulated genes were identified. More than a 1.5-fold change was identified between the morbidly obese patients and the control subjects for a cluster of dysregulated genes involving pathways regulating cell metabolism and lipid formation. Specifically, the PPARgamma pathway showed a plethora of dysregulated genes including tumor necrosis factor-alpha (TNFalpha). In morbidly obese patients, TNFalpha expression was increased (upregulated) 1.6-fold. These findings were confirmed using quantitative polymerase chain reaction with a 2.8-fold change. Microarrays are a powerful tool for identifying biomarkers indicating morbid obesity by analyzing differential gene expression profiles. This study confirms the association of PPARgamma with morbid obesity. Also, these findings in blood support previous work documented in tissue

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

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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.

Impact of elevated plasma serotonin on global gene expression of murine megakaryocytes.

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Charles P Mercado

Full Text Available Serotonin (5-HT is a biogenic amine that also acts as a mitogen and a developmental signal early in rodent embryogenesis. Genetic and pharmacological disruption of 5-HT signaling causes various diseases and disorders via mediating central nervous system, cardiovascular system, and serious abnormalities on a growing embryo. Today, neither the effective modulators on 5-HT signaling pathways nor the genes affected by 5-HT signal are well known yet.In an attempt to identify the genes altered by 5-HT signaling pathways, we analyzed the global gene expression via the Illumina array platform using the mouse WG-6 v2.0 Expression BeadChip containing 45,281 probe sets representing 30,854 genes in megakaryocytes isolated from mice infused with 5-HT or saline. We identified 723 differentially expressed genes of which 706 were induced and 17 were repressed by elevated plasma 5-HT.Hierarchical gene clustering analysis was utilized to represent relations between groups and clusters. Using gene ontology mining tools and canonical pathway analyses, we identified multiple biological pathways that are regulated by 5-HT: (i cytoskeletal remodeling, (ii G-protein signaling, (iii vesicular transport, and (iv apoptosis and survival. Our data encompass the first extensive genome-wide based profiling in the progenitors of platelets in response to 5-HT elevation in vivo.

Development of a novel ozone- and photo-stable HyPer5 red fluorescent dye for array CGH and microarray gene expression analysis with consistent performance irrespective of environmental conditions

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Kille Peter

2008-11-01

Full Text Available Abstract Background Array-based comparative genomic hybridization (CGH and gene expression profiling have become vital techniques for identifying molecular defects underlying genetic diseases. Regardless of the microarray platform, cyanine dyes (Cy3 and Cy5 are one of the most widely used fluorescent dye pairs for microarray analysis owing to their brightness and ease of incorporation, enabling high level of assay sensitivity. However, combining both dyes on arrays can become problematic during summer months when ozone levels rise to near 25 parts per billion (ppb. Under such conditions, Cy5 is known to rapidly degrade leading to loss of signal from either "homebrew" or commercial arrays. Cy5 can also suffer disproportionately from dye photobleaching resulting in distortion of (Cy5/Cy3 ratios used in copy number analysis. Our laboratory has been active in fluorescent dye research to find a suitable alternative to Cy5 that is stable to ozone and resistant to photo-bleaching. Here, we report on the development of such a dye, called HyPer5, and describe its' exceptional ozone and photostable properties on microarrays. Results Our results show HyPer5 signal to be stable to high ozone levels. Repeated exposure of mouse arrays hybridized with HyPer5-labeled cDNA to 300 ppb ozone at 5, 10 and 15 minute intervals resulted in no signal loss from the dye. In comparison, Cy5 arrays showed a dramatic 80% decrease in total signal during the same interval. Photobleaching experiments show HyPer5 to be resistant to light induced damage with 3- fold improvement in dye stability over Cy5. In high resolution array CGH experiments, HyPer5 is demonstrated to detect chromosomal aberrations at loci 2p21-16.3 and 15q26.3-26.2 from three patient sample using bacterial artificial chromosome (BAC arrays. The photostability of HyPer5 is further documented by repeat array scanning without loss of detection. Additionally, HyPer5 arrays are shown to preserve sensitivity and

A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

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Mingguang Shi

Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network-based

Global transgenerational gene expression dynamics in two newly synthesized allohexaploid wheat (Triticum aestivum lines

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Qi Bao

2012-01-01

Full Text Available Abstract Background Alteration in gene expression resulting from allopolyploidization is a prominent feature in plants, but its spectrum and extent are not fully known. Common wheat (Triticum aestivum was formed via allohexaploidization about 10,000 years ago, and became the most important crop plant. To gain further insights into the genome-wide transcriptional dynamics associated with the onset of common wheat formation, we conducted microarray-based genome-wide gene expression analysis on two newly synthesized allohexaploid wheat lines with chromosomal stability and a genome constitution analogous to that of the present-day common wheat. Results Multi-color GISH (genomic in situ hybridization was used to identify individual plants from two nascent allohexaploid wheat lines between Triticum turgidum (2n = 4x = 28; genome BBAA and Aegilops tauschii (2n = 2x = 14; genome DD, which had a stable chromosomal constitution analogous to that of common wheat (2n = 6x = 42; genome BBAADD. Genome-wide analysis of gene expression was performed for these allohexaploid lines along with their parental plants from T. turgidum and Ae. tauschii, using the Affymetrix Gene Chip Wheat Genome-Array. Comparison with the parental plants coupled with inclusion of empirical mid-parent values (MPVs revealed that whereas the great majority of genes showed the expected parental additivity, two major patterns of alteration in gene expression in the allohexaploid lines were identified: parental dominance expression and non-additive expression. Genes involved in each of the two altered expression patterns could be classified into three distinct groups, stochastic, heritable and persistent, based on their transgenerational heritability and inter-line conservation. Strikingly, whereas both altered patterns of gene expression showed a propensity of inheritance, identity of the involved genes was highly stochastic, consistent with the involvement of diverse Gene Ontology (GO

Interaction between scene-based and array-based contextual cueing.

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Rosenbaum, Gail M; Jiang, Yuhong V

2013-07-01

Contextual cueing refers to the cueing of spatial attention by repeated spatial context. Previous studies have demonstrated distinctive properties of contextual cueing by background scenes and by an array of search items. Whereas scene-based contextual cueing reflects explicit learning of the scene-target association, array-based contextual cueing is supported primarily by implicit learning. In this study, we investigated the interaction between scene-based and array-based contextual cueing. Participants searched for a target that was predicted by both the background scene and the locations of distractor items. We tested three possible patterns of interaction: (1) The scene and the array could be learned independently, in which case cueing should be expressed even when only one cue was preserved; (2) the scene and array could be learned jointly, in which case cueing should occur only when both cues were preserved; (3) overshadowing might occur, in which case learning of the stronger cue should preclude learning of the weaker cue. In several experiments, we manipulated the nature of the contextual cues present during training and testing. We also tested explicit awareness of scenes, scene-target associations, and arrays. The results supported the overshadowing account: Specifically, scene-based contextual cueing precluded array-based contextual cueing when both were predictive of the location of a search target. We suggest that explicit, endogenous cues dominate over implicit cues in guiding spatial attention.

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.

Integration of gene dosage and gene expression in non-small cell lung cancer, identification of HSP90 as potential target.

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Mariëlle I Gallegos Ruiz

Full Text Available BACKGROUND: Lung cancer causes approximately 1.2 million deaths per year worldwide, and non-small cell lung cancer (NSCLC represents 85% of all lung cancers. Understanding the molecular events in non-small cell lung cancer (NSCLC is essential to improve early diagnosis and treatment for this disease. METHODOLOGY AND PRINCIPAL FINDINGS: In an attempt to identify novel NSCLC related genes, we performed a genome-wide screening of chromosomal copy number changes affecting gene expression using microarray based comparative genomic hybridization and gene expression arrays on 32 radically resected tumor samples from stage I and II NSCLC patients. An integrative analysis tool was applied to determine whether chromosomal copy number affects gene expression. We identified a deletion on 14q32.2-33 as a common alteration in NSCLC (44%, which significantly influenced gene expression for HSP90, residing on 14q32. This deletion was correlated with better overall survival (P = 0.008, survival was also longer in patients whose tumors had low expression levels of HSP90. We extended the analysis to three independent validation sets of NSCLC patients, and confirmed low HSP90 expression to be related with longer overall survival (P = 0.003, P = 0.07 and P = 0.04. Furthermore, in vitro treatment with an HSP90 inhibitor had potent antiproliferative activity in NSCLC cell lines. CONCLUSIONS: We suggest that targeting HSP90 will have clinical impact for NSCLC patients.

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

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Anders E. Berglund

2017-01-01

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

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

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Gambetta, Gregory A; McElrone, Andrew J; Matthews, Mark A

2013-07-01

Many studies in which gene expression is quantified by polymerase chain reaction represent the expression of a gene of interest (GOI) relative to that of a reference gene (RG). Relative expression is founded on the assumptions that RG expression is stable across samples, treatments, organs, etc., and that reaction efficiencies of the GOI and RG are equal; assumptions which are often faulty. The true variability in RG expression and actual reaction efficiencies are seldom determined experimentally. Here we present a rapid and robust method for absolute quantification of expression in Vitis where varying concentrations of genomic DNA were used to construct GOI standard curves. This methodology was utilized to absolutely quantify and determine the variability of the previously validated RG ubiquitin (VvUbi) across three test studies in three different tissues (roots, leaves and berries). In addition, in each study a GOI was absolutely quantified. Data sets resulting from relative and absolute methods of quantification were compared and the differences were striking. VvUbi expression was significantly different in magnitude between test studies and variable among individual samples. Absolute quantification consistently reduced the coefficients of variation of the GOIs by more than half, often resulting in differences in statistical significance and in some cases even changing the fundamental nature of the result. Utilizing genomic DNA-based absolute quantification is fast and efficient. Through eliminating error introduced by assuming RG stability and equal reaction efficiencies between the RG and GOI this methodology produces less variation, increased accuracy and greater statistical power. © 2012 Scandinavian Plant Physiology Society.

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

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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. 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

Gene expression analysis after low dose ionising radiation exposure of the developing organism

International Nuclear Information System (INIS)

Abderrafi Benotmane, M.

2007-01-01

Measuring gene expression using microarrays is relevant to many areas of biology and medicine, such as follow up of developmental stages and diseases onset, and treatment study. Since there can be tens of thousands of distinct probes on an array, each micro array experiment can accomplish the equivalent number of genetic tests in parallel. Arrays have therefore dramatically accelerated many types of investigations. For example, microarrays can be used to identify stress response genes by comparing gene expression in challenged versus normal cells. In the Molecular and Cellular Biology lab (MCB), the micro array experiments are performed within the Genomic Platform, fully equipped to analyse either the behaviour of bacteria during long space flight, the effect of low dose ionising radiation on the developing organism in mice, or the human individual radiation sensitivity. For the low dose effect, two main stages of development are of interest; 1) the gastrula stage at which ionizing radiation can induce several malformations. 2) the organogenesis. During brain development, epidemiological studies of the atomic bomb survivors of Hiroshima/Nagasaki showed increased risk of mental retardation in children of women exposed between weeks 8-15 of pregnancy or at a lower extend between weeks 15 to 25

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

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Seoghyun Lee

2016-01-01

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

The defense-responsive genes showing enhanced and repressed expression after pathogen infection in rice (Oryza sativa L.)

Institute of Scientific and Technical Information of China (English)

ZHOU; Bin(周斌); PENG; Kaiman(彭开蔓); CHU; Zhaohui(储昭晖); WANG; Shiping(王石平); ZHANG; Qifa(张启发)

2002-01-01

Despite large numbers of studies about defense response, processes involved in the resistance of plants to incompatible pathogens are still largely uncharacterized. The objective of this study was to identify genes involved in defense response by cDNA array analysis and to gain knowledge about the functions of the genes involved in defense response. Approximately 20000 rice cDNA clones were arrayed on nylon filters. RNA samples isolated from different rice lines after infection with incompatible strains or isolates of Xanthomonas oryzae pv. oryzae or Pyricularia grisea, respectively, were used to synthesize cDNA as probes for screening the cDNA arrays. A total of 100 differentially expressed unique sequences were identified from 5 pathogen-host combinations. Fifty-three sequences were detected as showing enhanced expression and 47 sequences were detected as showing repressed expression after pathogen infection. Sequence analysis revealed that most of the 100 sequences had various degrees of homology with genes in databases which encode or putatively encode transcription regulating proteins, translation regulating proteins, transport proteins, kinases, metabolic enzymes, and proteins involved in other functions. Most of the genes have not been previously reported as being involved in the disease resistance response in rice. The results from cDNA arrays, reverse transcription-polymerase chain reaction, and RNA gel blot analysis suggest that activation or repression of most of these genes might occur commonly in the defense response.

Stress amplifies sex differences in primate prefrontal profiles of gene expression.

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Lee, Alex G; Hagenauer, Megan; Absher, Devin; Morrison, Kathleen E; Bale, Tracy L; Myers, Richard M; Watson, Stanley J; Akil, Huda; Schatzberg, Alan F; Lyons, David M

2017-11-02

Stress is a recognized risk factor for mood and anxiety disorders that occur more often in women than men. Prefrontal brain regions mediate stress coping, cognitive control, and emotion. Here, we investigate sex differences and stress effects on prefrontal cortical profiles of gene expression in squirrel monkey adults. Dorsolateral, ventrolateral, and ventromedial prefrontal cortical regions from 18 females and 12 males were collected after stress or no-stress treatment conditions. Gene expression profiles were acquired using HumanHT-12v4.0 Expression BeadChip arrays adapted for squirrel monkeys. Extensive variation between prefrontal cortical regions was discerned in the expression of numerous autosomal and sex chromosome genes. Robust sex differences were also identified across prefrontal cortical regions in the expression of mostly autosomal genes. Genes with increased expression in females compared to males were overrepresented in mitogen-activated protein kinase and neurotrophin signaling pathways. Many fewer genes with increased expression in males compared to females were discerned, and no molecular pathways were identified. Effect sizes for sex differences were greater in stress compared to no-stress conditions for ventromedial and ventrolateral prefrontal cortical regions but not dorsolateral prefrontal cortex. Stress amplifies sex differences in gene expression profiles for prefrontal cortical regions involved in stress coping and emotion regulation. Results suggest molecular targets for new treatments of stress disorders in human mental health.

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

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

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

Signaling pathway-focused gene expression profiling in pressure overloaded hearts

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Marco Musumeci

2011-01-01

Full Text Available The β-blocker propranolol displays antihypertrophic and antifibrotic properties in the heart subjected to pressure overload. Yet the underlying mechanisms responsible for these important effects remain to be completely understood. The purpose of this study was to determine signaling pathway-focused gene expression profile associated with the antihypertrophic action of propranolol in pressure overloaded hearts. To address this question, a focused real-time PCR array was used to screen left ventricular RNA expression of 84 gene transcripts representative of 18 different signaling pathways in C57BL/6 mice subjected to transverse aortic constriction (TAC or sham surgery. On the surgery day, mice received either propranolol (80 mg/kg/day or vehicle for 14 days. TAC caused a 49% increase in the left ventricular weight-to-body weight (LVW/BW ratio without changing gene expression. Propranolol blunted LVW/BW ratio increase by approximately 50% while causing about a 3-fold increase in the expression of two genes, namely Brca1 and Cdkn2a, belonging to the TGF-beta and estrogen pathways, respectively. In conclusion, after 2 weeks of pressure overload, TAC hearts show a gene expression profile superimposable to that of sham hearts. Conversely, propranolol treatment is associated with an increased expression of genes which negatively regulate cell cycle progression. It remains to be established whether a mechanistic link between gene expression changes and the antihypertrophic action of propranolol occurs.

Linear Energy Transfer-Dependent Change in Rice Gene Expression Profile after Heavy-Ion Beam Irradiation.

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Kotaro Ishii

Full Text Available A heavy-ion beam has been recognized as an effective mutagen for plant breeding and applied to the many kinds of crops including rice. In contrast with X-ray or γ-ray, the heavy-ion beam is characterized by a high linear energy transfer (LET. LET is an important factor affecting several aspects of the irradiation effect, e.g. cell survival and mutation frequency, making the heavy-ion beam an effective mutagen. To study the mechanisms behind LET-dependent effects, expression profiling was performed after heavy-ion beam irradiation of imbibed rice seeds. Array-based experiments at three time points (0.5, 1, 2 h after the irradiation revealed that the number of up- or down-regulated genes was highest 2 h after irradiation. Array-based experiments with four different LETs at 2 h after irradiation identified LET-independent regulated genes that were up/down-regulated regardless of the value of LET; LET-dependent regulated genes, whose expression level increased with the rise of LET value, were also identified. Gene ontology (GO analysis of LET-independent up-regulated genes showed that some GO terms were commonly enriched, both 2 hours and 3 weeks after irradiation. GO terms enriched in LET-dependent regulated genes implied that some factor regulates genes that have kinase activity or DNA-binding activity in cooperation with the ATM gene. Of the LET-dependent up-regulated genes, OsPARP3 and OsPCNA were identified, which are involved in DNA repair pathways. This indicates that the Ku-independent alternative non-homologous end-joining pathway may contribute to repairing complex DNA legions induced by high-LET irradiation. These findings may clarify various LET-dependent responses in rice.

Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

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Ma, W; Zhang, T-F; Lu, P; Lu, S H

2014-01-01

Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

Genome-wide gene copy number and expression analysis of primary gastric tumors and gastric cancer cell lines

International Nuclear Information System (INIS)

Junnila, Siina; Kokkola, Arto; Karjalainen-Lindsberg, Marja-Liisa; Puolakkainen, Pauli; Monni, Outi

2010-01-01

Gastric cancer is one of the most common malignancies worldwide and the second most common cause of cancer related death. Gene copy number alterations play an important role in the development of gastric cancer and a change in gene copy number is one of the main mechanisms for a cancer cell to control the expression of potential oncogenes and tumor suppressor genes. To highlight genes of potential biological and clinical relevance in gastric cancer, we carried out a systematic array-based survey of gene expression and copy number levels in primary gastric tumors and gastric cancer cell lines and validated the results using an affinity capture based transcript analysis (TRAC assay) and real-time qRT-PCR. Integrated microarray analysis revealed altogether 256 genes that were located in recurrent regions of gains or losses and had at least a 2-fold copy number- associated change in their gene expression. The expression levels of 13 of these genes, ALPK2, ASAP1, CEACAM5, CYP3A4, ENAH, ERBB2, HHIPL2, LTB4R, MMP9, PERLD1, PNMT, PTPRA, and OSMR, were validated in a total of 118 gastric samples using either the qRT-PCR or TRAC assay. All of these 13 genes were differentially expressed between cancerous samples and nonmalignant tissues (p < 0.05) and the association between copy number and gene expression changes was validated for nine (69.2%) of these genes (p < 0.05). In conclusion, integrated gene expression and copy number microarray analysis highlighted genes that may be critically important for gastric carcinogenesis. TRAC and qRT-PCR analyses validated the microarray results and therefore the role of these genes as potential biomarkers for gastric cancer

Investigation of the effect of ionizing radiation on gene expression variation by the 'DNA chips': feasibility of a biological dosimeter

International Nuclear Information System (INIS)

Gruel, G.

2005-01-01

After having described the different biological effects of ionizing radiation and the different approaches to biological dosimetry, and introduced 'DNA chips' or DNA micro-arrays, the author reports the characterization of gene expression variations in the response of cells to a gamma irradiation. Both main aspects of the use DNA chips are investigated: fundamental research and diagnosis. This research thesis thus proposes an analysis of the effect of ionizing radiation using DNA chips, notably by comparing gene expression modifications measured in mouse irradiated lung, heart and kidney. It reports a feasibility study of bio-dosimeter based on expression profiles

Global impact of mature biofilm lifestyle on Escherichia coli K-12 gene expression

DEFF Research Database (Denmark)

Beloin, C.; Valle, J.; Latour-Lambert, P.

2004-01-01

The formation of biofilm results in a major lifestyle switch that is thought to affect the expression of multiple genes and operons. We used DNA arrays to study the global effect of biofilm formation on gene expression in mature Escherichia coli K-12 biofilm. We show that, when biofilm is compared...... that 20 of these genes are required for the formation of mature biofilm. This group includes 11 genes of previously unknown function. These results constitute a comprehensive analysis of the global transcriptional response triggered in mature E. coli biofilms and provide insights into its physiological...

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

Improving the scaling normalization for high-density oligonucleotide GeneChip expression microarrays

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Lu Chao

2004-07-01

Full Text Available Abstract Background Normalization is an important step for microarray data analysis to minimize biological and technical variations. Choosing a suitable approach can be critical. The default method in GeneChip expression microarray uses a constant factor, the scaling factor (SF, for every gene on an array. The SF is obtained from a trimmed average signal of the array after excluding the 2% of the probe sets with the highest and the lowest values. Results Among the 76 U34A GeneChip experiments, the total signals on each array showed 25.8% variations in terms of the coefficient of variation, although all microarrays were hybridized with the same amount of biotin-labeled cRNA. The 2% of the probe sets with the highest signals that were normally excluded from SF calculation accounted for 34% to 54% of the total signals (40.7% ± 4.4%, mean ± sd. In comparison with normalization factors obtained from the median signal or from the mean of the log transformed signal, SF showed the greatest variation. The normalization factors obtained from log transformed signals showed least variation. Conclusions Eliminating 40% of the signal data during SF calculation failed to show any benefit. Normalization factors obtained with log transformed signals performed the best. Thus, it is suggested to use the mean of the logarithm transformed data for normalization, rather than the arithmetic mean of signals in GeneChip gene expression microarrays.

Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

Energy Technology Data Exchange (ETDEWEB)

Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

2004-05-18

Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

Different Array CGH profiles within hereditary breast cancer tumors associated to BRCA1 expression and overall survival

International Nuclear Information System (INIS)

Alvarez, Carolina; Aravena, Andrés; Tapia, Teresa; Rozenblum, Ester; Solís, Luisa; Corvalán, Alejandro; Camus, Mauricio; Alvarez, Manuel; Munroe, David; Maass, Alejandro; Carvallo, Pilar

2016-01-01

Array CGH analysis of breast tumors has contributed to the identification of different genomic profiles in these tumors. Loss of DNA repair by BRCA1 functional deficiency in breast cancer has been proposed as a relevant contribution to breast cancer progression for tumors with no germline mutation. Identifying the genomic alterations taking place in BRCA1 not expressing tumors will lead us to a better understanding of the cellular functions affected in this heterogeneous disease. Moreover, specific genomic alterations may contribute to the identification of potential therapeutic targets and offer a more personalized treatment to breast cancer patients. Forty seven tumors from hereditary breast cancer cases, previously analyzed for BRCA1 expression, and screened for germline BRCA1 and 2 mutations, were analyzed by Array based Comparative Genomic Hybridization (aCGH) using Agilent 4x44K arrays. Overall survival was established for tumors in different clusters using Log-rank (Mantel-Cox) Test. Gene lists obtained from aCGH analysis were analyzed for Gene Ontology enrichment using GOrilla and DAVID tools. Genomic profiling of the tumors showed specific alterations associated to BRCA1 or 2 mutation status, and BRCA1 expression in the tumors, affecting relevant cellular processes. Similar cellular functions were found affected in BRCA1 not expressing and BRCA1 or 2 mutated tumors. Hierarchical clustering classified hereditary breast tumors in four major, groups according to the type and amount of genomic alterations, showing one group with a significantly poor overall survival (p = 0.0221). Within this cluster, deletion of PLEKHO1, GDF11, DARC, DAG1 and CD63 may be associated to the worse outcome of the patients. These results support the fact that BRCA1 lack of expression in tumors should be used as a marker for BRCAness and to select these patients for synthetic lethality approaches such as treatment with PARP inhibitors. In addition, the identification of specific

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.

Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH) genes in multiple human solid tumors: A systematic expression analysis

International Nuclear Information System (INIS)

Hamm, Alexander; Knuechel, Ruth; Dahl, Edgar; Veeck, Juergen; Bektas, Nuran; Wild, Peter J; Hartmann, Arndt; Heindrichs, Uwe; Kristiansen, Glen; Werbowetski-Ogilvie, Tamra; Del Maestro, Rolando

2008-01-01

The inter-alpha-trypsin inhibitors (ITI) are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by AMBP – and five homologous heavy chains (encoded by ITIH1, ITIH2, ITIH3, ITIH4, and ITIH5), contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis. We systematically investigated differential gene expression of the ITIH gene family, as well as AMBP and the interacting partner TNFAIP6 in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas) using cDNA dot blot analysis (Cancer Profiling Array, CPA), semiquantitative RT-PCR and immunohistochemistry. We found that ITIH genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, ITIH genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose ITIH2 expression in human breast cancer. Loss of ITIH2 expression in 70% of cases (n = 50, CPA) could be confirmed by real-time PCR in an additional set of breast cancers (n = 36). Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p < 0.001) between ITIH2 expression and estrogen receptor (ER) expression indicating that ER may be involved in the regulation of this ECM molecule. Altogether, this is the first systematic analysis on the differential expression of ITIH genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies

Screening key genes for abdominal aortic aneurysm based on gene expression omnibus dataset.

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Wan, Li; Huang, Jingyong; Ni, Haizhen; Yu, Guanfeng

2018-02-13

Abdominal aortic aneurysm (AAA) is a common cardiovascular system disease with high mortality. The aim of this study was to identify potential genes for diagnosis and therapy in AAA. We searched and downloaded mRNA expression data from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) from AAA and normal individuals. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, transcriptional factors (TFs) network and protein-protein interaction (PPI) network were used to explore the function of genes. Additionally, immunohistochemical (IHC) staining was used to validate the expression of identified genes. Finally, the diagnostic value of identified genes was accessed by receiver operating characteristic (ROC) analysis in GEO database. A total of 1199 DEGs (188 up-regulated and 1011 down-regulated) were identified between AAA and normal individual. KEGG pathway analysis displayed that vascular smooth muscle contraction and pathways in cancer were significantly enriched signal pathway. The top 10 up-regulated and top 10 down-regulated DEGs were used to construct TFs and PPI networks. Some genes with high degrees such as NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16 and FOXO1 were identified to be related to AAA. The consequences of IHC staining showed that CCR7 and PDGFA were up-regulated in tissue samples of AAA. ROC analysis showed that NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA had the potential diagnostic value for AAA. The identified genes including NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA might be involved in the pathology of AAA.

Gene expression

International Nuclear Information System (INIS)

Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

1983-01-01

We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

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

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Simpson David

2006-03-01

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

Pervasive Effects of Aging on Gene Expression in Wild Wolves

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Charruau, Pauline; Johnston, Rachel A.; Stahler, Daniel R.; Lea, Amanda; Snyder-Mackler, Noah; Smith, Douglas W.; vonHoldt, Bridgett M.; Cole, Steven W.; Tung, Jenny; Wayne, Robert K.

2016-01-01

Abstract Gene expression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on gene expression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with gene expression levels, whereas other examined factors have minimal effects on gene expression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on gene expression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species’ high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. PMID:27189566

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.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

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Wang, Xi; Gardiner, Erin J; Cairns, Murray J

2015-05-01

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

In vitro analysis of integrated global high-resolution DNA methylation profiling with genomic imbalance and gene expression in osteosarcoma.

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Bekim Sadikovic

Full Text Available Genetic and epigenetic changes contribute to deregulation of gene expression and development of human cancer. Changes in DNA methylation are key epigenetic factors regulating gene expression and genomic stability. Recent progress in microarray technologies resulted in developments of high resolution platforms for profiling of genetic, epigenetic and gene expression changes. OS is a pediatric bone tumor with characteristically high level of numerical and structural chromosomal changes. Furthermore, little is known about DNA methylation changes in OS. Our objective was to develop an integrative approach for analysis of high-resolution epigenomic, genomic, and gene expression profiles in order to identify functional epi/genomic differences between OS cell lines and normal human osteoblasts. A combination of Affymetrix Promoter Tilling Arrays for DNA methylation, Agilent array-CGH platform for genomic imbalance and Affymetrix Gene 1.0 platform for gene expression analysis was used. As a result, an integrative high-resolution approach for interrogation of genome-wide tumour-specific changes in DNA methylation was developed. This approach was used to provide the first genomic DNA methylation maps, and to identify and validate genes with aberrant DNA methylation in OS cell lines. This first integrative analysis of global cancer-related changes in DNA methylation, genomic imbalance, and gene expression has provided comprehensive evidence of the cumulative roles of epigenetic and genetic mechanisms in deregulation of gene expression networks.

Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

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Zhou, Xionghui; Liu, Juan

2014-01-01

Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

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

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Zaldivar, Andrew; Krichmar, Jeffrey L

2014-01-01

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

Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

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Andrew eZaldivar

2014-05-01

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

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.

Comparative gene expression of intestinal metabolizing enzymes.

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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.

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

Probe design for expression arrays using OligoWiz

DEFF Research Database (Denmark)

Wernersson, Rasmus

2014-01-01

Since all measurements from a DNA microarray is dependant on the probes used, a good choice of probes is of vital importa nce when designing custom micro-arrays. This chapter describes how to de sign expression arrays using the “ OligoWiz ” software suite. The general desired features of good...... probes and the issues which probe design must address are introduced and a conceptual (rather than mathematical) description of how OligoWiz scores the quality of th e potential probes is presented. This is followed by a detailed step-by-step guide to designing expression arrays with OligoWiz....

Survivin Expression in Colorectal Adenocarcinoma Using Tissue Micro array

International Nuclear Information System (INIS)

Abd El-Hamed, A.

2005-01-01

The additional prognostic information closely related to tumor cell biology is essential for the identification of patients with poor prognosis. Survivin, an identified inhibitor of apoptosis, is unique for its expression in human malignancies but not in normal adult cells. This study examined the expression, and potential prognostic value of survivin in colorectal adenocarcinoma (CRC) on tissue micro array (TMA) sections. Analysis of large numbers of tissue samples, improved tissue salvage, cost reduction, ease of interpretation, and significant time saving were realized by using the arrays. Material and Methods: Two-hundred and eighty cases of colorectal adenocarcinoma were arrayed. Immunohistochemical stains of TMA sections were performed for survivin, bcl-2, and p53. Cases were followed up for 5 years. Survivin was detected in 147 of 230 cases (63.9%). No expression of survivin was observed in normal tissues. There was no correlation between survivin immunoreactivity and age, sex, tumor site, tumor size, histopathologic subtype, tumor grade and clinical stage(ρ> 0.05). Prevalence of survivin expression was significantly higher in bcl-2 positive than in bcl-2 negative cases (88.1 % versus 42.1 %, (ρ<0.0001), but was not associated with p53 ((ρ=0.09). The 5-year disease free survival (DFS) for patients with survivin positive colorectal adenocarcinoma was significantly lower than that for patients with survivin negative tumors (46% versus 68.7%, (ρ<0.001). Survivin expression in colorectal adenocarcinoma provides an important prognostic parameter and targeted antagonists of survivin may be beneficial as apoptosis-based therapy for colon cancer

Neighboring Genes Show Correlated Evolution in Gene Expression

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Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Dynamic gene expression response to altered gravity in human T cells.

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Thiel, Cora S; Hauschild, Swantje; Huge, Andreas; Tauber, Svantje; Lauber, Beatrice A; Polzer, Jennifer; Paulsen, Katrin; Lier, Hartwin; Engelmann, Frank; Schmitz, Burkhard; Schütte, Andreas; Layer, Liliana E; Ullrich, Oliver

2017-07-12

We investigated the dynamics of immediate and initial gene expression response to different gravitational environments in human Jurkat T lymphocytic cells and compared expression profiles to identify potential gravity-regulated genes and adaptation processes. We used the Affymetrix GeneChip® Human Transcriptome Array 2.0 containing 44,699 protein coding genes and 22,829 non-protein coding genes and performed the experiments during a parabolic flight and a suborbital ballistic rocket mission to cross-validate gravity-regulated gene expression through independent research platforms and different sets of control experiments to exclude other factors than alteration of gravity. We found that gene expression in human T cells rapidly responded to altered gravity in the time frame of 20 s and 5 min. The initial response to microgravity involved mostly regulatory RNAs. We identified three gravity-regulated genes which could be cross-validated in both completely independent experiment missions: ATP6V1A/D, a vacuolar H + -ATPase (V-ATPase) responsible for acidification during bone resorption, IGHD3-3/IGHD3-10, diversity genes of the immunoglobulin heavy-chain locus participating in V(D)J recombination, and LINC00837, a long intergenic non-protein coding RNA. Due to the extensive and rapid alteration of gene expression associated with regulatory RNAs, we conclude that human cells are equipped with a robust and efficient adaptation potential when challenged with altered gravitational environments.

Improving sensitivity of linear regression-based cell type-specific differential expression deconvolution with per-gene vs. global significance threshold.

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Glass, Edmund R; Dozmorov, Mikhail G

2016-10-06

The goal of many human disease-oriented studies is to detect molecular mechanisms different between healthy controls and patients. Yet, commonly used gene expression measurements from blood samples suffer from variability of cell composition. This variability hinders the detection of differentially expressed genes and is often ignored. Combined with cell counts, heterogeneous gene expression may provide deeper insights into the gene expression differences on the cell type-specific level. Published computational methods use linear regression to estimate cell type-specific differential expression, and a global cutoff to judge significance, such as False Discovery Rate (FDR). Yet, they do not consider many artifacts hidden in high-dimensional gene expression data that may negatively affect linear regression. In this paper we quantify the parameter space affecting the performance of linear regression (sensitivity of cell type-specific differential expression detection) on a per-gene basis. We evaluated the effect of sample sizes, cell type-specific proportion variability, and mean squared error on sensitivity of cell type-specific differential expression detection using linear regression. Each parameter affected variability of cell type-specific expression estimates and, subsequently, the sensitivity of differential expression detection. We provide the R package, LRCDE, which performs linear regression-based cell type-specific differential expression (deconvolution) detection on a gene-by-gene basis. Accounting for variability around cell type-specific gene expression estimates, it computes per-gene t-statistics of differential detection, p-values, t-statistic-based sensitivity, group-specific mean squared error, and several gene-specific diagnostic metrics. The sensitivity of linear regression-based cell type-specific differential expression detection differed for each gene as a function of mean squared error, per group sample sizes, and variability of the proportions

Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis: a cohort study

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Skoog Lambert

2006-06-01

Full Text Available Abstract Background Postmenopausal hormone-replacement therapy (HRT increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood. Methods We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women. Results HRT use in patients with estrogen receptor (ER protein positive tumors (n = 72 was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen. Conclusion Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.

Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH genes in multiple human solid tumors: A systematic expression analysis

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Werbowetski-Ogilvie Tamra

2008-01-01

Full Text Available Abstract Background The inter-alpha-trypsin inhibitors (ITI are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by AMBP – and five homologous heavy chains (encoded by ITIH1, ITIH2, ITIH3, ITIH4, and ITIH5, contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis. Methods We systematically investigated differential gene expression of the ITIH gene family, as well as AMBP and the interacting partner TNFAIP6 in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas using cDNA dot blot analysis (Cancer Profiling Array, CPA, semiquantitative RT-PCR and immunohistochemistry. Results We found that ITIH genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, ITIH genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose ITIH2 expression in human breast cancer. Loss of ITIH2 expression in 70% of cases (n = 50, CPA could be confirmed by real-time PCR in an additional set of breast cancers (n = 36. Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p Conclusion Altogether, this is the first systematic analysis on the differential expression of ITIH genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies.

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.

Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species

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Townsend Henrik J

2005-11-01

Full Text Available Abstract High-density oligonucleotide (oligo arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L. Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ and may be used to facilitate transcriptomic analyses of a wide range of plant and animal

Array design and expression evaluation in POOMA II

Energy Technology Data Exchange (ETDEWEB)

Karmesin, S.; Crotinger, J.; Cummings, J.; Haney, S.; Humphrey, W.; Reynders, J.; Smith, S.; Williams, T.J.

1998-12-31

POOMA is a templated C++ class library for use in the development of large-scale scientific simulations on serial and parallel computers. POOMA II is a new design and implementation of POOMA intended to add richer capabilities and greater flexibility to the framework. The new design employs a generic Array class that acts as an interface to, or view on, a wide variety of data representation objects referred to as engines. This design separates the interface and the representation of multidimensional arrays. The separation is achieved using compile-time techniques rather than virtual functions, and thus code efficiency is maintained. POOMA II uses PETE, the Portable Expression Template Engine, to efficiently represent complex mathematical expressions involving arrays and other objects. The representation of expressions is kept separate from expression evaluation, allowing the use of multiple evaluator mechanisms that can support nested where-block constructs, hardware-specific optimizations and different run-time environments.

Citrus plastid-related gene profiling based on expressed sequence tag analyses

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Tercilio Calsa Jr.

2007-01-01

Full Text Available Plastid-related sequences, derived from putative nuclear or plastome genes, were searched in a large collection of expressed sequence tags (ESTs and genomic sequences from the Citrus Biotechnology initiative in Brazil. The identified putative Citrus chloroplast gene sequences were compared to those from Arabidopsis, Eucalyptus and Pinus. Differential expression profiling for plastid-directed nuclear-encoded proteins and photosynthesis-related gene expression variation between Citrus sinensis and Citrus reticulata, when inoculated or not with Xylella fastidiosa, were also analyzed. Presumed Citrus plastome regions were more similar to Eucalyptus. Some putative genes appeared to be preferentially expressed in vegetative tissues (leaves and bark or in reproductive organs (flowers and fruits. Genes preferentially expressed in fruit and flower may be associated with hypothetical physiological functions. Expression pattern clustering analysis suggested that photosynthesis- and carbon fixation-related genes appeared to be up- or down-regulated in a resistant or susceptible Citrus species after Xylella inoculation in comparison to non-infected controls, generating novel information which may be helpful to develop novel genetic manipulation strategies to control Citrus variegated chlorosis (CVC.

Dynamic Network Reconstruction from Gene Expression Data Describing the Effect of LiCl Stimulation on Hepatocytes

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Zellmer Sebastian

2005-12-01

Full Text Available Wnt/β-catenin signalling plays an important role in zonation of liver parenchyma and in patterning of hepatocyte heterogeneity. A characteristic marker of this heterogeneity is glutamine synthetase, which is expressed only in a subset of pericentrally located hepatocytes. To investigate, whether and how the Wnt/β-catenin signalling pathway is involved a culture of hepatocytes was stimulated by LiCl. This resulted in an increase in the specific GS activity, indicating that the Wnt/β-catenin pathway may participate in regulating GS levels. Affymetrix GeneChip oligonucleotide arrays were used to monitor the gene expression changes during a period from 2 to 24 hours after stimulation by LiCl. Samples from a cultivation without stimulation were used as controls. Based on the gene expression profiles a hypothetic signal transduction network was constructed by a reverse engineering algorithm. The network robustness was tested and the most stable structure was identified.

Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

International Nuclear Information System (INIS)

Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon

2001-01-01

Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with 33 P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells

Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

Energy Technology Data Exchange (ETDEWEB)

Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon [College of Medicine, Korea Univ., Seoul (Korea, Republic of)

2001-07-01

Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with {sup 33}P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells.

Gene expression profiling in gastric mucosa from Helicobacter pylori-infected and uninfected patients undergoing chronic superficial gastritis.

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Ze-Min Yang

Full Text Available Helicobacter pylori infection reprograms host gene expression and influences various cellular processes, which have been investigated by cDNA microarray using in vitro culture cells and in vivo gastric biopsies from patients of the Chronic Abdominal Complaint. To further explore the effects of H. pylori infection on host gene expression, we have collected the gastric antral mucosa samples from 6 untreated patients with gastroscopic and pathologic confirmation of chronic superficial gastritis. Among them three patients were infected by H. pylori and the other three patients were not. These samples were analyzed by a microarray chip which contains 14,112 cloned cDNAs, and microarray data were analyzed via BRB ArrayTools software and Ingenuity Pathways Analysis (IPA website. The results showed 34 genes of 38 differentially expressed genes regulated by H. pylori infection had been annotated. The annotated genes were involved in protein metabolism, inflammatory and immunological reaction, signal transduction, gene transcription, trace element metabolism, and so on. The 82% of these genes (28/34 were categorized in three molecular interaction networks involved in gene expression, cancer progress, antigen presentation and inflammatory response. The expression data of the array hybridization was confirmed by quantitative real-time PCR assays. Taken together, these data indicated that H. pylori infection could alter cellular gene expression processes, escape host defense mechanism, increase inflammatory and immune responses, activate NF-κB and Wnt/β-catenin signaling pathway, disturb metal ion homeostasis, and induce carcinogenesis. All of these might help to explain H. pylori pathogenic mechanism and the gastroduodenal pathogenesis induced by H. pylori infection.

Embryo quality predictive models based on cumulus cells gene expression

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Devjak R

2016-06-01

Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

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Xiaobo Guo

Full Text Available Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs. It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC curve and the precision-recall (PR curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

Transcriptional interference networks coordinate the expression of functionally related genes clustered in the same genomic loci.

Science.gov (United States)

Boldogköi, Zsolt

2012-01-01

The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organization, transcription, various post-transcriptional processes, and translation. In this study, the Transcriptional Interference Network (TIN) hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighboring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronized cascade of gene expression in functionally linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular organisms too.

Transcriptional interference networks coordinate the expression of functionally-related genes clustered in the same genomic loci

Directory of Open Access Journals (Sweden)

Zsolt eBoldogkoi

2012-07-01

Full Text Available The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organisation, transcription, various post-transcriptional processes and translation. In this study, the Transcriptional Interference Network (TIN hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighbouring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally-linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly-arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely-oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronised cascade of gene expression in functionally-linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular

Identification of potential crucial genes associated with steroid-induced necrosis of femoral head based on gene expression profile.

Science.gov (United States)

Lin, Zhe; Lin, Yongsheng

2017-09-05

The aim of this study was to explore potential crucial genes associated with the steroid-induced necrosis of femoral head (SINFH) and to provide valid biological information for further investigation of SINFH. Gene expression profile of GSE26316, generated from 3 SINFH rat samples and 3 normal rat samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using LIMMA package. After functional enrichment analyses of DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted based on the STRING database and cytoscape. In total, 59 up-regulated DEGs and 156 downregulated DEGs were identified. The up-regulated DEGs were mainly involved in functions about immunity (e.g. Fcer1A and Il7R), and the downregulated DEGs were mainly enriched in muscle system process (e.g. Tnni2, Mylpf and Myl1). The PPI network of DEGs consisted of 123 nodes and 300 interactions. Tnni2, Mylpf, and Myl1 were the top 3 outstanding genes based on both subgraph centrality and degree centrality evaluation. These three genes interacted with each other in the network. Furthermore, the significant network module was composed of 22 downregulated genes (e.g. Tnni2, Mylpf and Myl1). These genes were mainly enriched in functions like muscle system process. The DEGs related to the regulation of immune system process (e.g. Fcer1A and Il7R), and DEGs correlated with muscle system process (e.g. Tnni2, Mylpf and Myl1) may be closely associated with the progress of SINFH, which is still needed to be confirmed by experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

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...

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

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Saurav Mallik

2017-12-01

Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

Science.gov (United States)

Mallik, Saurav; Zhao, Zhongming

2017-12-28

For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

Global analysis of aberrant pre-mRNA splicing in glioblastoma using exon expression arrays

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Nixon Tamara J

2008-05-01

Full Text Available Abstract Background Tumor-predominant splice isoforms were identified during comparative in silico sequence analysis of EST clones, suggesting that global aberrant alternative pre-mRNA splicing may be an epigenetic phenomenon in cancer. We used an exon expression array to perform an objective, genome-wide survey of glioma-specific splicing in 24 GBM and 12 nontumor brain samples. Validation studies were performed using RT-PCR on glioma cell lines, patient tumor and nontumor brain samples. Results In total, we confirmed 14 genes with glioma-specific splicing; seven were novel events identified by the exon expression array (A2BP1, BCAS1, CACNA1G, CLTA, KCNC2, SNCB, and TPD52L2. Our data indicate that large changes (> 5-fold in alternative splicing are infrequent in gliomagenesis ( Conclusion While we observed some tumor-specific alternative splicing, the number of genes showing exclusive tumor-specific isoforms was on the order of tens, rather than the hundreds suggested previously by in silico mining. Given the important role of alternative splicing in neural differentiation, there may be selective pressure to maintain a majority of splicing events in order to retain glial-like characteristics of the tumor cells.

Obesity in BSB mice is correlated with expression of genes foriron homeostasis and leptin

Energy Technology Data Exchange (ETDEWEB)

Farahani, Poupak; Chiu, Sally; Bowlus, Christopher L.; Boffelli,Dario; Lee, Eric; Fisler, Janis S.; Krauss, Ronald M.; Warden, Craig H.

2003-04-01

Obesity is a complex disease. To date, over 100 chromosomal loci for body weight, body fat, regional white adipose tissue weight, and other obesity-related traits have been identified in humans and in animal models. For most loci, the underlying genes are not yet identified; some of these chromosomal loci will be alleles of known obesity genes, whereas many will represent alleles of unknown genes. Microarray analysis allows simultaneous multiple gene and pathway discovery. cDNA and oligonucleotide arrays are commonly used to identify differentially expressed genes by surveys of large numbers of known and unnamed genes. Two papers previously identified genes differentially expressed in adipose tissue of mouse models of obesity and diabetes by analysis of hybridization to Affymetrix oligonucleotide chips.

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.

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...

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.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae.

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Ido Yofe

2014-06-01

Full Text Available Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.

Genome-wide gene expression array identifies novel genes related to disease severity and excessive daytime sleepiness in patients with obstructive sleep apnea.

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Yung-Che Chen

Full Text Available We aimed to identify novel molecular associations between chronic intermittent hypoxia with re-oxygenation and adverse consequences in obstructive sleep apnea (OSA. We analyzed gene expression profiles of peripheral blood mononuclear cells from 48 patients with sleep-disordered breathing stratified into four groups: primary snoring (PS, moderate to severe OSA (MSO, very severe OSA (VSO, and very severe OSA patients on long-term continuous positive airway pressure treatment (VSOC. Comparisons of the microarray gene expression data identified eight genes up-regulated with OSA and down-regulated with CPAP treatment, and five genes down-regulated with OSA and up-regulated with CPAP treatment. Protein expression levels of two genes related to endothelial tight junction (AMOT P130, and PLEKHH3, and three genes related to anti-or pro-apoptosis (BIRC3, ADAR1 P150, and LGALS3 were all increased in the VSO group, while AMOT P130 was further increased, and PLEKHH3, BIRC3, and ADAR1 P150 were all decreased in the VSOC group. Subgroup analyses revealed that AMOT P130 protein expression was increased in OSA patients with excessive daytime sleepiness, BIRC3 protein expression was decreased in OSA patients with hypertension, and LGALS3 protein expression was increased in OSA patients with chronic kidney disease. In vitro short-term intermittent hypoxia with re-oxygenation experiment showed immediate over-expression of ADAR1 P150. In conclusion, we identified a novel association between AMOT/PLEKHH3/BIRC3/ADAR1/LGALS3 over-expressions and high severity index in OSA patients. AMOT and GALIG may constitute an important determinant for the development of hypersomnia and kidney injury, respectively, while BIRC3 may play a protective role in the development of hypertension.

EPConDB: a web resource for gene expression related to pancreatic development, beta-cell function and diabetes.

Science.gov (United States)

Mazzarelli, Joan M; Brestelli, John; Gorski, Regina K; Liu, Junmin; Manduchi, Elisabetta; Pinney, Deborah F; Schug, Jonathan; White, Peter; Kaestner, Klaus H; Stoeckert, Christian J

2007-01-01

EPConDB (http://www.cbil.upenn.edu/EPConDB) is a public web site that supports research in diabetes, pancreatic development and beta-cell function by providing information about genes expressed in cells of the pancreas. EPConDB displays expression profiles for individual genes and information about transcripts, promoter elements and transcription factor binding sites. Gene expression results are obtained from studies examining tissue expression, pancreatic development and growth, differentiation of insulin-producing cells, islet or beta-cell injury, and genetic models of impaired beta-cell function. The expression datasets are derived using different microarray platforms, including the BCBC PancChips and Affymetrix gene expression arrays. Other datasets include semi-quantitative RT-PCR and MPSS expression studies. For selected microarray studies, lists of differentially expressed genes, derived from PaGE analysis, are displayed on the site. EPConDB provides database queries and tools to examine the relationship between a gene, its transcriptional regulation, protein function and expression in pancreatic tissues.

Effects of in ovo electroporation on endogenous gene expression: genome-wide analysis

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Chambers David

2011-04-01

Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous gene expression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous gene expression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in gene expression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on gene expression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.

Nonparametric testing for DNA copy number induced differential mRNA gene expression

NARCIS (Netherlands)

van Wieringen, W.N.; van de Wiel, M.A.

2009-01-01

The central dogma of molecular biology relates DNA with mRNA. Array CGH measures DNA copy number and gene expression microarrays measure the amount of mRNA. Methods that integrate data from these two platforms may uncover meaningful biological relationships that further our understanding of cancer.

Clinical array-based karyotyping of breast cancer with equivocal HER2 status resolves gene copy number and reveals chromosome 17 complexity

International Nuclear Information System (INIS)

Gunn, Shelly; Gorre, Mercedes; Mohammed, Mansoor; Yeh, I-Tien; Lytvak, Irina; Tirtorahardjo, Budi; Dzidic, Natasha; Zadeh, Soheila; Kim, Jaeweon; McCaskill, Chris; Lim, Lony

2010-01-01

HER2 gene copy status, and concomitant administration of trastuzumab (Herceptin), remains one of the best examples of targeted cancer therapy based on understanding the genomic etiology of disease. However, newly diagnosed breast cancer cases with equivocal HER2 results present a challenge for the oncologist who must make treatment decisions despite the patient's unresolved HER2 status. In some cases both immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) are reported as equivocal, whereas in other cases IHC results and FISH are discordant for positive versus negative results. The recent validation of array-based, molecular karyotyping for clinical oncology testing provides an alternative method for determination of HER2 gene copy number status in cases remaining unresolved by traditional methods. In the current study, DNA extracted from 20 formalin fixed paraffin embedded (FFPE) tissue samples from newly diagnosed cases of invasive ductal carcinoma referred to our laboratory with unresolved HER2 status, were analyzed using a clinically validated genomic array containing 127 probes covering the HER2 amplicon, the pericentromeric regions, and both chromosome 17 arms. Array-based comparative genomic hybridization (array CGH) analysis of chromosome 17 resolved HER2 gene status in [20/20] (100%) of cases and revealed additional chromosome 17 copy number changes in [18/20] (90%) of cases. Array CGH analysis also revealed two false positives and one false negative by FISH due to 'ratio skewing' caused by chromosomal gains and losses in the centromeric region. All cases with complex rearrangements of chromosome 17 showed genome-wide chromosomal instability. These results illustrate the analytical power of array-based genomic analysis as a clinical laboratory technique for resolution of HER2 status in breast cancer cases with equivocal results. The frequency of complex chromosome 17 abnormalities in these cases suggests that the two

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

International Nuclear Information System (INIS)

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

2010-01-01

Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 ± 1.72 nm; 1.91 x 10 7 particles/cm 3 ) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

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

Energy Technology Data Exchange (ETDEWEB)

Lee, Hye-Young; Choi, You-Jin; Jung, Eun-Jung; Yin, Hu-Quan [Seoul National University, College of Pharmacy and Research Institute of Pharmaceutical Sciences (Korea, Republic of); Kwon, Jung-Taek; Kim, Ji-Eun; Im, Hwang-Tae; Cho, Myung-Haing [Seoul National University, College of Veterinary Medicine (Korea, Republic of); Kim, Ju-Han [Seoul National University, College of Medicine (Korea, Republic of); Kim, Hyun-Young [Occupational Safety and Health Research Institute, Chemical Safety and Health Research Center (Korea, Republic of); Lee, Byung-Hoon, E-mail: lee@snu.ac.k [Seoul National University, College of Pharmacy and Research Institute of Pharmaceutical Sciences (Korea, Republic of)

2010-06-15

Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 {+-} 1.72 nm; 1.91 x 10{sup 7} particles/cm{sup 3}) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

Toll like receptors gene expression of human keratinocytes cultured of severe burn injury.

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Cornick, Sarita Mac; Noronha, Silvana Aparecida Alves Corrêa de; Noronha, Samuel Marcos Ribeiro de; Cezillo, Marcus V B; Ferreira, Lydia Masako; Gragnani, Alfredo

2014-01-01

To evaluate the expression profile of genes related to Toll Like Receptors (TLR) pathways of human Primary Epidermal keratinocytes of patients with severe burns. After obtaining viable fragments of skin with and without burning, culture hKEP was initiated by the enzymatic method using Dispase (Sigma-Aldrich). These cells were treated with Trizol(r) (Life Technologies) for extraction of total RNA. This was quantified and analyzed for purity for obtaining cDNA for the analysis of gene expression using specific TLR pathways PCR Arrays plates (SA Biosciences). After the analysis of gene expression we found that 21% of these genes were differentially expressed, of which 100% were repressed or hyporegulated. Among these, the following genes (fold decrease): HSPA1A (-58), HRAS (-36), MAP2K3 (-23), TOLLIP (-23), RELA (-18), FOS (-16), and TLR1 (-6.0). This study contributes to the understanding of the molecular mechanisms related to TLR pathways and underlying wound infection caused by the burn. Furthermore, it may provide new strategies to restore normal expression of these genes and thereby change the healing process and improve clinical outcome.

Gene expression analysis of matched ovarian primary tumors and peritoneal metastasis

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Malek Joel A

2012-06-01

Full Text Available Abstract Background Ovarian cancer is the most deadly gynecological cancer due to late diagnosis at advanced stage with major peritoneal involvement. To date most research has focused on primary tumor. However the prognosis is directly related to residual disease at the end of the treatment. Therefore it is mandatory to focus and study the biology of meatastatic disease that is most frequently localized to the peritoneal caivty in ovarian cancer. Methods We used high-density gene expression arrays to investigate gene expression changes between matched primary and metastatic (peritoneal lesions. Results Here we show that gene expression profiles in peritoneal metastasis are significantly different than their matched primary tumor and these changes are affected by underlying copy number variation differences among other causes. We show that differentially expressed genes are enriched in specific pathways including JAK/STAT pathway, cytokine signaling and other immune related pathways. We show that underlying copy number variations significantly affect gene expression. Indeed patients with important differences in copy number variation displayed greater gene expression differences between their primary and matched metastatic lesions. Conclusions Our analysis shows a very specific targeting at both the genomic and transcriptomic level to upregulate certain pathways in the peritoneal metastasis of ovarian cancer. Moreover, while primary tumors use certain pathways we identify distinct differences with metastatic lesions. The variation between primary and metastatic lesions should be considered in personalized treatment of ovarian cancer.

Radioactive cDNA microarrys for gene expression profiles in antidepressant therapy

International Nuclear Information System (INIS)

Lee, M. S.; Han, B. J.; Cha, J. H.; Ryu, Y. M.; Shin, E. K.; Park, J. H.; Park, Y. H.; Kim, M. K.

2002-01-01

Using radioactive cDNA microarray, we investigated a pattern of gene regulation under treatment of antidepressant on patients of depressive disoder. Basic microarray technology was performed as previously described in our research. The bioinformatic selection of human cDNAs, which is specifically designed for psychiatry, neurology, and signal transduction, were arrayed on nylon membranes. Using with 33P-labeled probes, this method provided highly sensitive gene expression profiles of our interest including brain receptors, drug metabolism, and cellular signalings. Gene expression profiles were also classified into several categories in accordance with the gene-regulation of antidepressant. The gene profiles of our interest were significantly up- (16 genes, >2.0 of Z-ratio) or down- (24 genes, <-2.0 of Z ratio) regulated when compared the good responsed group with the bad-responsed one. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

Clustering gene expression data based on predicted differential effects of GV interaction.

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Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

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

OpenAIRE

Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris

2016-01-01

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

Detection of growth hormone doping by gene expression profiling of peripheral blood.

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Mitchell, Christopher J; Nelson, Anne E; Cowley, Mark J; Kaplan, Warren; Stone, Glenn; Sutton, Selina K; Lau, Amie; Lee, Carol M Y; Ho, Ken K Y

2009-12-01

GH abuse is a significant problem in many sports, and there is currently no robust test that allows detection of doping beyond a short window after administration. Our objective was to evaluate gene expression profiling in peripheral blood leukocytes in-vivo as a test for GH doping in humans. Seven men and thirteen women were administered GH, 2 mg/d sc for 8 wk. Blood was collected at baseline and at 8 wk. RNA was extracted from the white cell fraction. Microarray analysis was undertaken using Agilent 44K G4112F arrays using a two-color design. Quantitative RT-PCR using TaqMan gene expression assays was performed for validation of selected differentially expressed genes. GH induced an approximately 2-fold increase in circulating IGF-I that was maintained throughout the 8 wk of the study. GH induced significant changes in gene expression with 353 in women and 41 in men detected with a false discovery rate of less than 5%. None of the differentially expressed genes were common between men and women. The maximal changes were a doubling for up-regulated or halving for down-regulated genes, similar in magnitude to the variation between individuals. Quantitative RT-PCR for seven target genes showed good concordance between microarray and quantitative PCR data in women but not in men. Gene expression analysis of peripheral blood leukocytes is unlikely to be a viable approach for the detection of GH doping.

Two-pass imputation algorithm for missing value estimation in gene expression time series.

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Tsiporkova, Elena; Boeva, Veselka

2007-10-01

Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene expression data require a complete matrix of gene array values. Therefore, the accurate estimation of missing values in such datasets has been recognized as an important issue, and several imputation algorithms have already been proposed to the biological community. Most of these approaches, however, are not particularly suitable for time series expression profiles. In view of this, we propose a novel imputation algorithm, which is specially suited for the estimation of missing values in gene expression time series data. The algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles, and subsequently selects for each gene expression profile with missing values a dedicated set of candidate profiles for estimation. Three different DTW-based imputation (DTWimpute) algorithms have been considered: position-wise, neighborhood-wise, and two-pass imputation. These have initially been prototyped in Perl, and their accuracy has been evaluated on yeast expression time series data using several different parameter settings. The experiments have shown that the two-pass algorithm consistently outperforms, in particular for datasets with a higher level of missing entries, the neighborhood-wise and the position-wise algorithms. The performance of the two-pass DTWimpute algorithm has further been benchmarked against the weighted K-Nearest Neighbors algorithm, which is widely used in the biological community; the former algorithm has appeared superior to the latter one. Motivated by these findings, indicating clearly the added value of the DTW techniques for missing value estimation in time series data, we have built an optimized C++ implementation of the two-pass DTWimpute algorithm. The software also provides for a choice between three different

Concurrent array-based queue

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Heidelberger, Philip; Steinmacher-Burow, Burkhard

2015-01-06

According to one embodiment, a method for implementing an array-based queue in memory of a memory system that includes a controller includes configuring, in the memory, metadata of the array-based queue. The configuring comprises defining, in metadata, an array start location in the memory for the array-based queue, defining, in the metadata, an array size for the array-based queue, defining, in the metadata, a queue top for the array-based queue and defining, in the metadata, a queue bottom for the array-based queue. The method also includes the controller serving a request for an operation on the queue, the request providing the location in the memory of the metadata of the queue.

Prediction of highly expressed genes in microbes based on chromatin accessibility

DEFF Research Database (Denmark)

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...

Gene expression pattern at different time points following ALA-PDT

International Nuclear Information System (INIS)

Verwanger, T.; Sanovic, R.; Ruhdorfer, S.; Aberger, F.; Frischauf, A.; Krammer, B.

2003-01-01

Full text: The photo sensitizer protoporphyrin IX, endogenously accumulated from the precursor aminolevulinic acid (ALA), is a successful agent in photodynamic tumor therapy. In spite of encouraging clinical results, the basic mechanisms leading to cell death are not fully understood. We therefore set out to analyze the alteration of the gene expression pattern in the squamous cell carcinoma cell line A-431 at different time points after photodynamic treatment with endogenous protoporphyrin IX by cDNA-array technique. Cells were incubated for 16 hours with 100 μg/ml ALA and irradiated with a fluence of 3.5 J/cm 2 resulting in 50 % survival until 8 hours post treatment. RNA was isolated at 1.5, 3, 5 and 8 hours post treatment as well as of 3 controls (untreated, light only and dark), radioactively labelled by reverse transcription with 33P-dCTP and hybridized onto macroarray PCR filters containing PCR products of 2135 genes, which were selected for relevance in tumors, stress response and signal transduction. Verification of observed expression changes was carried out by real time PCR. We found a strong induction of expression of immediate early genes like c-fos as well as decreased expression of genes involved in proliferation like myc and the proliferating cell nuclear antigen (PCNA). (author)

University of Texas Southwestern Medical Center: Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

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The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

Identification of differentially expressed genes between developing seeds of different soybean cultivars

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Rongshuang Lin

2015-12-01

Full Text Available Soybean is a major source of protein and oil and a primary feedstock for biodiesel production. Research on soybean seed composition and yield has revealed that protein, oil and yield are controlled quantitatively and quantitative trait loci (QTL have been identified for each of these traits. However, very limited information is available regarding the genetic mechanisms controlling seed composition and yield. To help address this deficiency, we used Affymetrix Soybean GeneChips® to identify genes that are differentially expressed between developing seeds of the Minsoy and Archer soybean cultivars, which differ in seed weight, yield, protein content and oil content. A total of 700 probe sets were found to be expressed at significantly different (defined as having an adjusted p-value below or equal to 0.05 and an at least 2-fold difference levels between the two cultivars at one or more of the three developmental stages and in at least one of the two years assayed. Comparison of data from soybeans collected in two different years revealed that 97 probe sets were expressed at significantly different levels in both years. Functional annotations were assigned to 78% of these 97 probe sets based on the SoyBase Affymetrix™ GeneChip® Soybean Genome Array Annotation. Genes involved in receptor binding/activity and protein binding are overrepresented among the group of 97 probe sets that were differentially expressed in both years assayed. Probe sets involved in growth/development, signal transduction, transcription, defense/stress response and protein and lipid metabolism were also identified among the 97 probe sets and their possible implications in the regulation of agronomic traits are discussed. As the Minsoy and Archer soybean cultivars differ with respect to seed size, yield, protein content and lipid content, some of the differentially expressed probe sets identified in this study may thus play important roles in controlling these traits

Spatial analysis of biomineralization associated gene expression from the mantle organ of the pearl oyster Pinctada maxima

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2011-01-01

Background Biomineralization is a process encompassing all mineral containing tissues produced within an organism. One of the most dynamic examples of this process is the formation of the mollusk shell, comprising a variety of crystal phases and microstructures. The organic component incorporated within the shell is said to dictate this architecture. However general understanding of how this process is achieved remains ambiguous. The mantle is a conserved organ involved in shell formation throughout molluscs. Specifically the mantle is thought to be responsible for secreting the protein component of the shell. This study employs molecular approaches to determine the spatial expression of genes within the mantle tissue to further the elucidation of the shell biomineralization. Results A microarray platform was custom generated (PmaxArray 1.0) from the pearl oyster Pinctada maxima. PmaxArray 1.0 consists of 4992 expressed sequence tags (ESTs) originating from mantle tissue. This microarray was used to analyze the spatial expression of ESTs throughout the mantle organ. The mantle was dissected into five discrete regions and analyzed for differential gene expression with PmaxArray 1.0. Over 2000 ESTs were determined to be differentially expressed among the tissue sections, identifying five major expression regions. In situ hybridization validated and further localized the expression for a subset of these ESTs. Comparative sequence similarity analysis of these ESTs revealed a number of the transcripts were novel while others showed significant sequence similarities to previously characterized shell related genes. Conclusions This investigation has mapped the spatial distribution for over 2000 ESTs present on PmaxArray 1.0 with reference to specific locations of the mantle. Expression profile clusters have indicated at least five unique functioning zones in the mantle. Three of these zones are likely involved in shell related activities including formation of nacre

Time warping of evolutionary distant temporal gene expression data based on noise suppression

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Papatsenko Dmitri

2009-10-01

Full Text Available Abstract Background Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution. Results We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (Saccharomyces cerevisiae and fission (Schizosaccharomyces pombe yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment. Conclusion Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.

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.

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

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Shohag Barman

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

[Analysis of tissue-specific differentially methylated genes with differential gene expression in non-small cell lung cancer].

Science.gov (United States)

Yin, L G; Zou, Z Q; Zhao, H Y; Zhang, C L; Shen, J G; Qi, L; Qi, M; Xue, Z Q

2014-01-01

Adenocarcinoma (ADC) and squamous cell carcinomas (SCC) are two subtypes of non-small cell lung carcinomas which are regarded as the leading cause of cancer-related malignancy worldwide. The aim of this study is to detect the differentially methylated loci (DMLs) and differentially methylated genes (DMGs) of these two tumor sets, and then to illustrate the different expression level of specific methylated genes. Using TCGA database and Illumina HumanMethylation 27 arrays, we first screened the DMGs and DMLs in tumor samples. Then, we explored the BiologicalProcess terms of hypermethylated and hypomethylated genes using Functional Gene Ontology (GO) catalogues. Hypermethylation intensively occurred in CpG-island, whereas hypomethylation was located in non-CpG-island. Most SCC and ADC hypermethylated genes involved GO function of DNA dependenit regulation of transcription, and hypomethylated genes mainly 'enriched in the term of immune responses. Additionally, the expression level of specific differentially methylated genesis distinctbetween ADC and SCC. It is concluded that ADC and SCC have different methylated status that might play an important role in carcinogenesis.

Analysis of genomic imbalances and gene expression changes in transformed follicular lymphoma (FL)

DEFF Research Database (Denmark)

Obel, G.; Farinha, P.; Lam, W.

2005-01-01

American patients with transformed FL. Methods: High-resolution BAC-array comparative genomic hybridisation (CGH) was used to detect genomic imbalances. Gene expression profiling was performed using cDNA microarrays (Affymetrix). Results: Of 9 biopsy pairs identified so far, analysis results of the first 4...

University of Texas Southwestern Medical Center (UTSW): Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

Science.gov (United States)

The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

Effect of p53 genotype on gene expression profiles in murine liver

International Nuclear Information System (INIS)

Morris, Suzanne M.; Akerman, Gregory S.; Desai, Varsha G.; Tsai, Chen-an; Tolleson, William H.; Melchior, William B.; Lin, Chien-Ju; Fuscoe, James C.; Casciano, Daniel A.; Chen, James J.

2008-01-01

The tumor suppressor protein p53 is a key regulatory element in the cell and is regarded as the 'guardian of the genome'. Much of the present knowledge of p53 function has come from studies of transgenic mice in which the p53 gene has undergone a targeted deletion. In order to provide additional insight into the impact on the cellular regulatory networks associated with the loss of this gene, microarray technology was utilized to assess gene expression in tissues from both the p53 -/- and p53 +/- mice. Six male mice from each genotype (p53 +/+ , p53 +/- , and p53 -/- ) were humanely killed and the tissues processed for microarray analysis. The initial studies have been performed in the liver for which the Dunnett test revealed 1406 genes to be differentially expressed between p53 +/+ and p53 +/- or between p53 +/+ and p53 -/- at the level of p ≤ 0.05. Both genes with increased expression and decreased expression were identified in p53 +/- and in p53 -/- mice. Most notable in the gene list derived from the p53 +/- mice was the significant reduction in p53 mRNA. In the p53 -/- mice, not only was there reduced expression of the p53 genes on the array, but genes associated with DNA repair, apoptosis, and cell proliferation were differentially expressed, as expected. However, altered expression was noted for many genes in the Cdc42-GTPase pathways that influence cell proliferation. This may indicate that alternate pathways are brought into play in the unperturbed liver when loss or reduction in p53 levels occurs

Gene expression profiling in Ishikawa cells: A fingerprint for estrogen active compounds

International Nuclear Information System (INIS)

Boehme, Kathleen; Simon, Stephanie; Mueller, Stefan O.

2009-01-01

Several anthropogenous and naturally occurring substances, referred to as estrogen active compounds (EACs), are able to interfere with hormone and in particular estrogen receptor signaling. EACs can either cause adverse health effects in humans and wildlife populations or have beneficial effects on estrogen-dependent diseases. The aim of this study was to examine global gene expression profiles in estrogen receptor (ER)-proficient Ishikawa plus and ER-deficient Ishikawa minus endometrial cancer cells treated with selected well-known EACs (Diethylstilbestrol, Genistein, Zearalenone, Resveratrol, Bisphenol A and o,p'-DDT). We also investigated the effect of the pure antiestrogen ICI 182,780 (ICI) on the expression patterns caused by these compounds. Transcript levels were quantified 24 h after compound treatment using Illumina BeadChip Arrays. We identified 87 genes with similar expression changes in response to all EAC treatments in Ishikawa plus. ICI lowered the magnitude or reversed the expression of these genes, indicating ER dependent regulation. Apart from estrogenic gene regulation, Bisphenol A, o,p'-DDT, Zearalenone, Genistein and Resveratrol displayed similarities to ICI in their expression patterns, suggesting mixed estrogenic/antiestrogenic properties. In particular, the predominant antiestrogenic expression response of Resveratrol could be clearly distinguished from the other test compounds, indicating a distinct mechanism of action. Divergent gene expression patterns of the phytoestrogens, as well as weaker estrogenic gene expression regulation determined for the anthropogenous chemicals Bisphenol A and o,p'-DDT, warrants a careful assessment of potential detrimental and/or beneficial effects of EACs. The characteristic expression fingerprints and the identified subset of putative marker genes can be used for screening chemicals with an unknown mode of action and for predicting their potential to exert endocrine disrupting effects

Transcriptomic analyses reveal novel genes with sexually dimorphic expression in the zebrafish gonad and brain.

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Rajini Sreenivasan

Full Text Available BACKGROUND: Our knowledge on zebrafish reproduction is very limited. We generated a gonad-derived cDNA microarray from zebrafish and used it to analyze large-scale gene expression profiles in adult gonads and other organs. METHODOLOGY/PRINCIPAL FINDINGS: We have identified 116638 gonad-derived zebrafish expressed sequence tags (ESTs, 21% of which were isolated in our lab. Following in silico normalization, we constructed a gonad-derived microarray comprising 6370 unique, full-length cDNAs from differentiating and adult gonads. Labeled targets from adult gonad, brain, kidney and 'rest-of-body' from both sexes were hybridized onto the microarray. Our analyses revealed 1366, 881 and 656 differentially expressed transcripts (34.7% novel that showed highest expression in ovary, testis and both gonads respectively. Hierarchical clustering showed correlation of the two gonadal transcriptomes and their similarities to those of the brains. In addition, we have identified 276 genes showing sexually dimorphic expression both between the brains and between the gonads. By in situ hybridization, we showed that the gonadal transcripts with the strongest array signal intensities were germline-expressed. We found that five members of the GTP-binding septin gene family, from which only one member (septin 4 has previously been implicated in reproduction in mice, were all strongly expressed in the gonads. CONCLUSIONS/SIGNIFICANCE: We have generated a gonad-derived zebrafish cDNA microarray and demonstrated its usefulness in identifying genes with sexually dimorphic co-expression in both the gonads and the brains. We have also provided the first evidence of large-scale differential gene expression between female and male brains of a teleost. Our microarray would be useful for studying gonad development, differentiation and function not only in zebrafish but also in related teleosts via cross-species hybridizations. Since several genes have been shown to play similar

[Gene Expression Profile of Apoptosis in Leukemia Cells Induced by Hsp90 Selective inhibitor 17-AAG].

Science.gov (United States)

Wang, Na-Na; Li, Zhi-Heng; Tao, Yan-Fang; Xu, Li-Xiao; Pan, Jian; Hu, Shao-Yan

2016-06-01

To investigate the apoptotic effects of Hsp90 selective inhibitor 17-AAG on human leukemia HL-60 and NB4 cells and analyse its possible mechanism. CCK-8 assay was used to quantify the growth inhibition of cells after exposure to 17-AAG for 24 hours. Flow cytometrve with annexin V/propidium iodide staining was used to detect apoptosis of leukemia cells. Then Western blot was used to detect the activation of apoptosis related protein caspase-3 and PARP level. Gene expression profile of NB4 cells treated with 17-AAG was analyzed with real-time PCR arrays. The inhibition of leukemia cell proliferation displayed a dose-dependent manner. Annexin V assay, cell cycle analysis and activation of PARP demonstrate that 17-AAG induced apoptosis leukemia cells. Real-time PCR array analysis showed that expression of 56 genes significantly up-regulated and expression of 23 genes were significantly down-regulated after 17-AAG treatment. The 17-AAG can inhibit the proliferation and induce the apoptosis of leukemia cells. After leukemia cells are treated with 17-AAG, the significant changes of apoptosis-related genes occured, and the cell apoptosis occurs via activating apoptosis related signaling pathway.

Altered Gene Expressions and Cytogenetic Repair Efficiency in Cells with Suppressed Expression of XPA after Proton Exposure

Science.gov (United States)

Zhang, Ye; Rohde, Larry H.; Gridley, Daila S.; Mehta, Satish K.; Pierson, Duane L.; Wu, Honglu

2009-01-01

Cellular responses to damages from ionizing radiation (IR) exposure are influenced not only by the genes involved in DNA double strand break (DSB) repair, but also by non- DSB repair genes. We demonstrated previously that suppressed expression of several non-DSB repair genes, such as XPA, elevated IR-induced cytogenetic damages. In the present study, we exposed human fibroblasts that were treated with control or XPA targeting siRNA to 250 MeV protons (0 to 4 Gy), and analyzed chromosome aberrations and expressions of genes involved in DNA repair. As expected, after proton irradiation, cells with suppressed expression of XPA showed a significantly elevated frequency of chromosome aberrations compared with control siRNA treated (CS) cells. Protons caused more severe DNA damages in XPA knock-down cells, as 36% cells contained multiple aberrations compared to 25% in CS cells after 4Gy proton irradiation. Comparison of gene expressions using the real-time PCR array technique revealed that expressions of p53 and its regulated genes in irradiated XPA suppressed cells were altered similarly as in CS cells, suggesting that the impairment of IR induced DNA repair in XPA suppressed cells is p53-independent. Except for XPA, which was more than 2 fold down regulated in XPA suppressed cells, several other DNA damage sensing and repair genes (GTSE1, RBBP8, RAD51, UNG and XRCC2) were shown a more than 1.5 fold difference between XPA knock-down cells and CS cells after proton exposure. The possible involvement of these genes in the impairment of DNA repair in XPA suppressed cells will be further investigated.

Medicago truncatula and Glomus intraradices gene expression in cortical cells harboring arbuscules in the arbuscular mycorrhizal symbiosis

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Tang Yuhong

2009-01-01

Full Text Available Abstract Background Most vascular flowering plants have the capacity to form symbiotic associations with arbuscular mycorrhizal (AM fungi. The symbiosis develops in the roots where AM fungi colonize the root cortex and form arbuscules within the cortical cells. Arbuscules are enveloped in a novel plant membrane and their establishment requires the coordinated cellular activities of both symbiotic partners. The arbuscule-cortical cell interface is the primary functional interface of the symbiosis and is of central importance in nutrient exchange. To determine the molecular events the underlie arbuscule development and function, it is first necessary to identify genes that may play a role in this process. Toward this goal we used the Affymetrix GeneChip® Medicago Genome Array to document the M. truncatula transcript profiles associated with AM symbiosis, and then developed laser microdissection (LM of M. truncatula root cortical cells to enable analyses of gene expression in individual cell types by RT-PCR. Results This approach led to the identification of novel M. truncatula and G. intraradices genes expressed in colonized cortical cells and in arbuscules. Within the arbuscule, expression of genes associated with the urea cycle, amino acid biosynthesis and cellular autophagy was detected. Analysis of gene expression in the colonized cortical cell revealed up-regulation of a lysine motif (LysM-receptor like kinase, members of the GRAS transcription factor family and a symbiosis-specific ammonium transporter that is a likely candidate for mediating ammonium transport in the AM symbiosis. Conclusion Transcript profiling using the Affymetrix GeneChip® Medicago Genome Array provided new insights into gene expression in M. truncatula roots during AM symbiosis and revealed the existence of several G. intraradices genes on the M. truncatula GeneChip®. A laser microdissection protocol that incorporates low-melting temperature Steedman's wax, was

Altered Gene Expression Profile in Mouse Bladder Cancers Induced by Hydroxybutyl(butylnitrosamine

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Ruisheng Yao

2004-09-01

Full Text Available A variety of genetic alterations and gene expression changes are involved in the pathogenesis of bladder tumor. To explore these changes, oligonucleotide array analysis was performed on RNA obtained from carcinogen-induced mouse bladder tumors and normal mouse bladder epithelia using Affymetrix (Santa Clara, CA MGU74Av2 GeneChips. Analysis yielded 1164 known genes that were changed in the tumors. Certain of the upregulated genes included EGFR-Ras signaling genes, transcription factors, cell cycle-related genes, and intracellular signaling cascade genes. However, downregulated genes include mitogen-activated protein kinases, cell cycle checkpoint genes, Rab subfamily genes, Rho subfamily genes, and SH2 and SH3 domains-related genes. These genes are involved in a broad range of different pathways including control of cell proliferation, differentiation, cell cycle, signal transduction, and apoptosis. Using the pathway visualization tool GenMAPP, we found that several genes, including TbR-l, STAT1, Smad1, Smad2, Jun, NFκB, and so on, in the TGF-β signaling pathway and p115 RhoGEF, RhoGDl3, MEKK4A/MEKK4B, P13KA, and JNK in the G13 signaling pathway were differentially expressed in the tumors. In summary, we have determined the expression profiles of genes differentially expressed during mouse bladder tumorigenesis. Our results suggest that activation of the EGFR-Ras pathway, uncontrolled cell cycle, aberrant transcription factors, and G13 and TGF-β pathways are involved, and the cross-talk between these pathways seems to play important roles in mouse bladder tumorigenesis.

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

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Guo Zheng

2006-01-01

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

Gene Expression Measurement Module (GEMM) - A Fully Automated, Miniaturized Instrument for Measuring Gene Expression in Space

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Pohorille, Andrew; Peyvan, Kia; Karouia, Fathi; Ricco, Antonio

2012-01-01

The capability to measure gene expression on board spacecraft opens the door to a large number of high-value experiments on the influence of the space environment on biological systems. For example, measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, and determine the metabolic bases of microbial pathogenicity and drug resistance. These and other applications hold significant potential for discoveries in space biology, biotechnology, and medicine. Supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measurement of expression of several hundreds of microbial genes from multiple samples. The instrument will be capable of (1) lysing cell walls of bacteria sampled from cultures grown in space, (2) extracting and purifying RNA released from cells, (3) hybridizing the RNA on a microarray and (4) providing readout of the microarray signal, all in a single microfluidics cartridge. The device is suitable for deployment on nanosatellite platforms developed by NASA Ames' Small Spacecraft Division. To meet space and other technical constraints imposed by these platforms, a number of technical innovations are being implemented. The integration and end-to-end technological and biological validation of the instrument are carried out using as a model the photosynthetic bacterium Synechococcus elongatus, known for its remarkable metabolic diversity and resilience to adverse conditions. Each step in the measurement process-lysis, nucleic acid extraction, purification, and hybridization to an array-is assessed through comparison of the results obtained using the instrument with

Differential gene expression between African American and European American colorectal cancer patients.

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Biljana Jovov

Full Text Available The incidence and mortality of colorectal cancer (CRC is higher in African Americans (AAs than other ethnic groups in the U. S., but reasons for the disparities are unknown. We performed gene expression profiling of sporadic CRCs from AAs vs. European Americans (EAs to assess the contribution to CRC disparities. We evaluated the gene expression of 43 AA and 43 EA CRC tumors matched by stage and 40 matching normal colorectal tissues using the Agilent human whole genome 4x44K cDNA arrays. Gene and pathway analyses were performed using Significance Analysis of Microarrays (SAM, Ten-fold cross validation, and Ingenuity Pathway Analysis (IPA. SAM revealed that 95 genes were differentially expressed between AA and EA patients at a false discovery rate of ≤5%. Using IPA we determined that most prominent disease and pathway associations of differentially expressed genes were related to inflammation and immune response. Ten-fold cross validation demonstrated that following 10 genes can predict ethnicity with an accuracy of 94%: CRYBB2, PSPH, ADAL, VSIG10L, C17orf81, ANKRD36B, ZNF835, ARHGAP6, TRNT1 and WDR8. Expression of these 10 genes was validated by qRT-PCR in an independent test set of 28 patients (10 AA, 18 EA. Our results are the first to implicate differential gene expression in CRC racial disparities and indicate prominent difference in CRC inflammation between AA and EA patients. Differences in susceptibility to inflammation support the existence of distinct tumor microenvironments in these two patient populations.

Muscle fiber type specific induction of slow myosin heavy chain 2 gene expression by electrical stimulation

International Nuclear Information System (INIS)

Crew, Jennifer R.; Falzari, Kanakeshwari; DiMario, Joseph X.

2010-01-01

Vertebrate skeletal muscle fiber types are defined by a broad array of differentially expressed contractile and metabolic protein genes. The mechanisms that establish and maintain these different fiber types vary throughout development and with changing functional demand. Chicken skeletal muscle fibers can be generally categorized as fast and fast/slow based on expression of the slow myosin heavy chain 2 (MyHC2) gene in fast/slow muscle fibers. To investigate the cellular and molecular mechanisms that control fiber type formation in secondary or fetal muscle fibers, myoblasts from the fast pectoralis major (PM) and fast/slow medial adductor (MA) muscles were isolated, allowed to differentiate in vitro, and electrically stimulated. MA muscle fibers were induced to express the slow MyHC2 gene by electrical stimulation, whereas PM muscle fibers did not express the slow MyHC2 gene under identical stimulation conditions. However, PM muscle fibers did express the slow MyHC2 gene when electrical stimulation was combined with inhibition of inositol triphosphate receptor (IP3R) activity. Electrical stimulation was sufficient to increase nuclear localization of expressed nuclear-factor-of-activated-T-cells (NFAT), NFAT-mediated transcription, and slow MyHC2 promoter activity in MA muscle fibers. In contrast, both electrical stimulation and inhibitors of IP3R activity were required for these effects in PM muscle fibers. Electrical stimulation also increased levels of peroxisome-proliferator-activated receptor-γ co-activator-1 (PGC-1α) protein in PM and MA muscle fibers. These results indicate that MA muscle fibers can be induced by electrical stimulation to express the slow MyHC2 gene and that fast PM muscle fibers are refractory to stimulation-induced slow MyHC2 gene expression due to fast PM muscle fiber specific cellular mechanisms involving IP3R activity.

Innate and adaptive immunity gene expression of human keratinocytes cultured of severe burn injury.

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Noronha, Silvana Aparecida Alves Corrêa de; Noronha, Samuel Marcos Ribeiro de; Lanziani, Larissa Elias; Ferreira, Lydia Masako; Gragnani, Alfredo

2014-01-01

Evaluate the expression profile of genes related to Innate and Adaptive Immune System (IAIS) of human Primary Epidermal keratinocytes (hPEKP) of patients with severe burns. After obtaining viable fragments of skin with and without burning, culture hKEP was initiated by the enzymatic method using Dispase (Sigma-Aldrich). These cells were treated with Trizol(r) (Life Technologies) for extraction of total RNA. This was quantified and analyzed for purity for obtaining cDNA for the analysis of gene expression using specific IAIS PCR Arrays plates (SA Biosciences). After the analysis of gene expression we found that 63% of these genes were differentially expressed, of which 77% were repressed and 23% were hyper-regulated. Among these, the following genes (fold increase or decrease): IL8 (41), IL6 (32), TNF (-92), HLA-E (-86), LYS (-74), CCR6 (- 73), CD86 (-41) and HLA-A (-35). This study contributes to the understanding of the molecular mechanisms underlying wound infection caused by the burn. Furthermore, it may provide new strategies to restore normal expression of these genes and thereby change the healing process and improve clinical outcome.

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.

Urinary exosomes: a novel means to non-invasively assess changes in renal gene and protein expression.

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Silvia Spanu

Full Text Available BACKGROUND: In clinical practice, there is a lack of markers for the non-invasive diagnosis and follow-up of kidney disease. Exosomes are membrane vesicles, which are secreted from their cells of origin into surrounding body fluids and contain proteins and mRNA which are protected from digestive enzymes by a cell membrane. METHODS: Toxic podocyte damage was induced by puromycin aminonucleoside in rats (PAN. Urinary exosomes were isolated by ultracentrifugation at different time points during the disease. Exosomal mRNA was isolated, amplified, and the mRNA species were globally assessed by gene array analysis. Tissue-specific gene and protein expression was assessed by RT-qPCR analysis and immunohistochemistry. RESULTS: Gene array analysis of mRNA isolated from urinary exosomes revealed cystatin C mRNA as one of the most highly regulated genes. Its gene expression increased 7.5-fold by day 5 and remained high with a 1.9-fold increase until day 10. This was paralleled by a 2-fold increase in cystatin C mRNA expression in the renal cortex. Protein expression in the kidneys also dramatically increased with de novo expression of cystatin C in glomerular podocytes in parts of the proximal tubule and the renal medulla. Urinary excretion of cystatin C increased approximately 2-fold. CONCLUSION: In this proof-of-concept study, we could demonstrate that changes in urinary exosomal cystatin C mRNA expression are representative of changes in renal mRNA and protein expression. Because cells lining the urinary tract produce urinary exosomal cystatin C mRNA, it might be a more specific marker of renal damage than glomerular-filtered free cystatin C.

Alterations in gene expression profiles between radioresistant and radiosensitive cell lines

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Zhou Fuxiang; Zhou Yunfeng; Xie Conghua; Dai Jing; Cao Zhen; Yu Haijun; Liao Zhengkai; Luo Zhiguo

2007-01-01

Objective: To study the-difference of gene expressions by the contrastive model including the cells with same pathological origin and genetic background, but definitely different radioresponse, and to find the main molecular targets related to radiosensitivity. Methods: Human larynx squamous carcinoma cell, Hep -2 was irradiated with dose of 637 cGy repeatedly to establish a radioresistant daughter cell line. The radiobiology characteristics were obtained using clone forming assay. The difference of gene expression between parent and daughter cells was detected by cDNA microarray using two different arrays including 14000 genes respectively. Results: A radioresistant cell strain Hep-2R was isolated from its parental strain Hep-2 cell. The SF 2 , D 0 , α, β for Hep-2R cell line were 0.6798, 3.24, 0.2951 and 0.0363, respectively, while 0.4148, 2.06, 0.1074 and 0.0405 for Hep-2, respectively (for SF 2 , χ 2 =63.957, P<0.001). Compared with Hep-2 cells, the expressions of 41 genes were significantly altered in the radioresistant Hep-2R cells, including 22 genes up-regulated and 19 genes down-regulated, which were involved in DNA repair, regulation of the cell cycle, cell proliferation, cytoskeleton, protein synthesis, cellular metabolism and especially apoptosis which is responsible for the different radiosensitivity between these two larynx cancer cells. The telomere protection protein gene, POT1, was the mostly up-regulated by 3.348 times. Conclusions: There is difference of gene expression between the radioresistant contrastive models. POT1 gene may be the target of radiosensitization. (authors)

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin

2016-01-01

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato

2016-08-25

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

Microarray analysis of altered gene expression in murine fibroblasts transformed by nickel(II) to nickel(II)-resistant malignant phenotype

International Nuclear Information System (INIS)

Kowara, Renata; Karaczyn, Aldona; Cheng, Robert Y.S.; Salnikow, Konstantin; Kasprzak, Kazimierz S.

2005-01-01

B200 cells are Ni(II)-transformed mouse BALB/c-3T3 fibroblasts displaying a malignant phenotype and increased resistance to Ni(II) toxicity. In an attempt to find genes whose expression has been altered by the transformation, the Atlas Mouse Stress/Toxicology cDNA Expression Array (Clontech Laboratories, Inc., Palo Alto, CA) was used to analyze the levels of gene expression in both parental and Ni(II)-transformed cells. Comparison of the results revealed a significant up- or downregulation of the expression of 62 of the 588 genes present in the array (approximately 10.5%) in B200 cells. These genes were assigned to different functional groups, including transcription factors and oncogenes (9/14; fractions in parentheses denote the number of up-regulated versus the total number of genes assigned to this group), stress and DNA damage response genes (11/12), growth factors and hormone receptors (6/9), metabolism (7/7), cell adhesion (2/7), cell cycle (3/6), apoptosis (3/4), and cell proliferation (2/3). Among those genes, overexpression of beta-catenin and its downstream targets c-myc and cyclin D1, together with upregulated cyclin G, points at the malignant character of B200 cells. While the increased expression of glutathione (GSH) synthetase, glutathione-S-transferase A4 (GSTA4), and glutathione-S-transferase theta (GSTT), together with high level of several genes responding to oxidative stress, suggests the enforcement of antioxidant defenses in Ni-transformed cells

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

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Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

Intracellular Protein Delivery and Gene Transfection by Electroporation Using a Microneedle Electrode Array

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Choi, Seong-O; Kim, Yeu-Chun; Lee, Jeong Woo; Park, Jung-Hwan

2012-01-01

The impact of many biopharmaceuticals, including protein- and gene-based therapies, has been limited by the need for better methods of delivery into cells within tissues. Here, we present intracellular delivery of molecules and transfection with plasmid DNA by electroporation using a novel microneedle electrode array designed for targeted treatment of skin and other tissue surfaces. The microneedle array is molded out of polylactic acid. Electrodes and circuitry required for electroporation are applied to the microneedle array surface by a new metal-transfer micromolding method. The microneedle array maintains mechanical integrity after insertion into pig cadaver skin and is able to electroporate human prostate cancer cells in vitro. Quantitative measurements show that increasing electroporation pulse voltage increases uptake efficiency of calcein and bovine serum albumin, whereas increasing pulse length has lesser effects over the range studied. Uptake of molecules by up to 50 % of cells and transfection of 12 % of cells with a gene for green fluorescent protein is demonstrated at high cell viability. We conclude that the microneedle electrode array is able to electroporate cells, resulting in intracellular uptake of molecules, and has potential applications to improve intracellular delivery of proteins, DNA and other biopharmaceuticals. PMID:22328093

Increased expression of electron transport chain genes in uterine leiomyoma.

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Tuncal, Akile; Aydin, Hikmet Hakan; Askar, Niyazi; Ozkaya, Ali Burak; Ergenoglu, Ahmet Mete; Yeniel, Ahmet Ozgur; Akdemir, Ali; Ak, Handan

2014-01-01

The etiology and pathophysiology of uterine leiomyomas, benign smooth muscle tumors of the uterus, are not well understood. To evaluate the role of mitochondria in uterine leiomyoma, we compared electron transport gene expressions of uterine leiomyoma tissue with myometrium tissue in six uterine leiomyoma patients by RT-PCR array. Our results showed an average of 1.562 (±0.445) fold increase in nuclear-encoded electron transport genes. These results might suggest an increase in size, number, or activity of mitochondria in uterine leiomyoma that, to our knowledge, has not been previously reported. © 2014 by the Association of Clinical Scientists, Inc.

Brain region-specific altered expression and association of mitochondria-related genes in autism.

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Anitha, Ayyappan; Nakamura, Kazuhiko; Thanseem, Ismail; Yamada, Kazuo; Iwayama, Yoshimi; Toyota, Tomoko; Matsuzaki, Hideo; Miyachi, Taishi; Yamada, Satoru; Tsujii, Masatsugu; Tsuchiya, Kenji J; Matsumoto, Kaori; Iwata, Yasuhide; Suzuki, Katsuaki; Ichikawa, Hironobu; Sugiyama, Toshiro; Yoshikawa, Takeo; Mori, Norio

2012-11-01

Mitochondrial dysfunction (MtD) has been observed in approximately five percent of children with autism spectrum disorders (ASD). MtD could impair highly energy-dependent processes such as neurodevelopment, thereby contributing to autism. Most of the previous studies of MtD in autism have been restricted to the biomarkers of energy metabolism, while most of the genetic studies have been based on mutations in the mitochondrial DNA (mtDNA). Despite the mtDNA, most of the proteins essential for mitochondrial replication and function are encoded by the genomic DNA; so far, there have been very few studies of those genes. Therefore, we carried out a detailed study involving gene expression and genetic association studies of genes related to diverse mitochondrial functions. For gene expression analysis, postmortem brain tissues (anterior cingulate gyrus (ACG), motor cortex (MC) and thalamus (THL)) from autism patients (n=8) and controls (n=10) were obtained from the Autism Tissue Program (Princeton, NJ, USA). Quantitative real-time PCR arrays were used to quantify the expression of 84 genes related to diverse functions of mitochondria, including biogenesis, transport, translocation and apoptosis. We used the delta delta Ct (∆∆Ct) method for quantification of gene expression. DNA samples from 841 Caucasian and 188 Japanese families were used in the association study of genes selected from the gene expression analysis. FBAT was used to examine genetic association with autism. Several genes showed brain region-specific expression alterations in autism patients compared to controls. Metaxin 2 (MTX2), neurofilament, light polypeptide (NEFL) and solute carrier family 25, member 27 (SLC25A27) showed consistently reduced expression in the ACG, MC and THL of autism patients. NEFL (P = 0.038; Z-score 2.066) and SLC25A27 (P = 0.046; Z-score 1.990) showed genetic association with autism in Caucasian and Japanese samples, respectively. The expression of DNAJC19, DNM1L, LRPPRC

Brain region-specific altered expression and association of mitochondria-related genes in autism

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Anitha Ayyappan

2012-11-01

Full Text Available Abstract Background Mitochondrial dysfunction (MtD has been observed in approximately five percent of children with autism spectrum disorders (ASD. MtD could impair highly energy-dependent processes such as neurodevelopment, thereby contributing to autism. Most of the previous studies of MtD in autism have been restricted to the biomarkers of energy metabolism, while most of the genetic studies have been based on mutations in the mitochondrial DNA (mtDNA. Despite the mtDNA, most of the proteins essential for mitochondrial replication and function are encoded by the genomic DNA; so far, there have been very few studies of those genes. Therefore, we carried out a detailed study involving gene expression and genetic association studies of genes related to diverse mitochondrial functions. Methods For gene expression analysis, postmortem brain tissues (anterior cingulate gyrus (ACG, motor cortex (MC and thalamus (THL from autism patients (n=8 and controls (n=10 were obtained from the Autism Tissue Program (Princeton, NJ, USA. Quantitative real-time PCR arrays were used to quantify the expression of 84 genes related to diverse functions of mitochondria, including biogenesis, transport, translocation and apoptosis. We used the delta delta Ct (∆∆Ct method for quantification of gene expression. DNA samples from 841 Caucasian and 188 Japanese families were used in the association study of genes selected from the gene expression analysis. FBAT was used to examine genetic association with autism. Results Several genes showed brain region-specific expression alterations in autism patients compared to controls. Metaxin 2 (MTX2, neurofilament, light polypeptide (NEFL and solute carrier family 25, member 27 (SLC25A27 showed consistently reduced expression in the ACG, MC and THL of autism patients. NEFL (P = 0.038; Z-score 2.066 and SLC25A27 (P = 0.046; Z-score 1.990 showed genetic association with autism in Caucasian and Japanese samples, respectively. The

Pretransplant Immune- and Apoptosis-Related Gene Expression Is Associated with Kidney Allograft Function

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Dorota Kamińska

2016-01-01

Full Text Available Renal transplant candidates present immune dysregulation, caused by chronic uremia. The aim of the study was to investigate whether pretransplant peripheral blood gene expression of immune factors affects clinical outcome of renal allograft recipients. Methods. In a prospective study, we analyzed pretransplant peripheral blood gene expression in87 renal transplant candidates with real-time PCR on custom-designed low density arrays (TaqMan. Results. Immediate posttransplant graft function (14-day GFR was influenced negatively by TGFB1 (P=0.039 and positively by IL-2 gene expression (P=0.040. Pretransplant blood mRNA expression of apoptosis-related genes (CASP3, FAS, and IL-18 and Th1-derived cytokine gene IFNG correlated positively with short- (6-month GFR CASP3: P=0.027, FAS: P=0.021, and IFNG: P=0.029 and long-term graft function (24-month GFR CASP3: P=0.003, FAS: P=0.033, IL-18: P=0.044, and IFNG: P=0.04. Conclusion. Lowered pretransplant Th1-derived cytokine and apoptosis-related gene expressions were a hallmark of subsequent worse kidney function but not of acute rejection rate. The pretransplant IFNG and CASP3 and FAS and IL-18 genes’ expression in the recipients’ peripheral blood is the possible candidate for novel biomarker of short- and long-term allograft function.

Cigarette smoke modulates expression of human rhinovirus-induced airway epithelial host defense genes.

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David Proud

Full Text Available Human rhinovirus (HRV infections trigger acute exacerbations of chronic obstructive pulmonary disease (COPD and asthma. The human airway epithelial cell is the primary site of HRV infection and responds to infection with altered expression of multiple genes, the products of which could regulate the outcome to infection. Cigarette smoking aggravates asthma symptoms, and is also the predominant risk factor for the development and progression of COPD. We, therefore, examined whether cigarette smoke extract (CSE modulates viral responses by altering HRV-induced epithelial gene expression. Primary cultures of human bronchial epithelial cells were exposed to medium alone, CSE alone, purified HRV-16 alone or to HRV-16+ CSE. After 24 h, supernatants were collected and total cellular RNA was isolated. Gene array analysis was performed to examine mRNA expression. Additional experiments, using real-time RT-PCR, ELISA and/or western blotting, validated altered expression of selected gene products. CSE and HRV-16 each induced groups of genes that were largely independent of each other. When compared to gene expression in response to CSE alone, cells treated with HRV+CSE showed no obvious differences in CSE-induced gene expression. By contrast, compared to gene induction in response to HRV-16 alone, cells exposed to HRV+CSE showed marked suppression of expression of a number of HRV-induced genes associated with various functions, including antiviral defenses, inflammation, viral signaling and airway remodeling. These changes were not associated with altered expression of type I or type III interferons. Thus, CSE alters epithelial responses to HRV infection in a manner that may negatively impact antiviral and host defense outcomes.

Codon usage and amino acid usage influence genes expression level.

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Paul, Prosenjit; Malakar, Arup Kumar; Chakraborty, Supriyo

2018-02-01

Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

High-Throughput Screening to Identify Regulators of Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

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Kassir, Yona

2017-01-01

Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.

Genome-Wide Constitutively Expressed Gene Analysis and New Reference Gene Selection Based on Transcriptome Data: A Case Study from Poplar/Canker Disease Interaction

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Jiaping Zhao

2017-10-01

Full Text Available A number of transcriptome datasets for differential expression (DE genes have been widely used for understanding organismal biology, but these datasets also contain untapped information that can be used to develop more precise analytical tools. With the use of transcriptome data generated from poplar/canker disease interaction system, we describe a methodology to identify candidate reference genes from high-throughput sequencing data. This methodology will improve the accuracy of RT-qPCR and will lead to better standards for the normalization of expression data. Expression stability analysis from xylem and phloem of Populus bejingensis inoculated with the fungal canker pathogen Botryosphaeria dothidea revealed that 729 poplar transcripts (1.11% were stably expressed, at a threshold level of coefficient of variance (CV of FPKM < 20% and maximum fold change (MFC of FPKM < 2.0. Expression stability and bioinformatics analysis suggested that commonly used house-keeping (HK genes were not the most appropriate internal controls: 70 of the 72 commonly used HK genes were not stably expressed, 45 of the 72 produced multiple isoform transcripts, and some of their reported primers produced unspecific amplicons in PCR amplification. RT-qPCR analysis to compare and evaluate the expression stability of 10 commonly used poplar HK genes and 20 of the 729 newly-identified stably expressed transcripts showed that some of the newly-identified genes (such as SSU_S8e, LSU_L5e, and 20S_PSU had higher stability ranking than most of commonly used HK genes. Based on these results, we recommend a pipeline for deriving reference genes from transcriptome data. An appropriate candidate gene should have a unique transcript, constitutive expression, CV value of expression < 20% (or possibly 30% and MFC value of expression <2, and an expression level of 50–1,000 units. Lastly, when four of the newly identified HK genes were used in the normalization of expression data for 20

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.

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

Gene expression profiling of acute myeloid leukemia samples from adult patients with AML-M1 and -M2 through boutique microarrays, real-time PCR and droplet digital PCR.

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Handschuh, Luiza; Kaźmierczak, Maciej; Milewski, Marek C; Góralski, Michał; Łuczak, Magdalena; Wojtaszewska, Marzena; Uszczyńska-Ratajczak, Barbara; Lewandowski, Krzysztof; Komarnicki, Mieczysław; Figlerowicz, Marek

2018-03-01

Acute myeloid leukemia (AML) is the most common and severe form of acute leukemia diagnosed in adults. Owing to its heterogeneity, AML is divided into classes associated with different treatment outcomes and specific gene expression profiles. Based on previous studies on AML, in this study, we designed and generated an AML-array containing 900 oligonucleotide probes complementary to human genes implicated in hematopoietic cell differentiation and maturation, proliferation, apoptosis and leukemic transformation. The AML-array was used to hybridize 118 samples from 33 patients with AML of the M1 and M2 subtypes of the French-American‑British (FAB) classification and 15 healthy volunteers (HV). Rigorous analysis of the microarray data revealed that 83 genes were differentially expressed between the patients with AML and the HV, including genes not yet discussed in the context of AML pathogenesis. The most overexpressed genes in AML were STMN1, KITLG, CDK6, MCM5, KRAS, CEBPA, MYC, ANGPT1, SRGN, RPLP0, ENO1 and SET, whereas the most underexpressed genes were IFITM1, LTB, FCN1, BIRC3, LYZ, ADD3, S100A9, FCER1G, PTRPE, CD74 and TMSB4X. The overexpression of the CPA3 gene was specific for AML with mutated NPM1 and FLT3. Although the microarray-based method was insufficient to differentiate between any other AML subgroups, quantitative PCR approaches enabled us to identify 3 genes (ANXA3, S100A9 and WT1) whose expression can be used to discriminate between the 2 studied AML FAB subtypes. The expression levels of the ANXA3 and S100A9 genes were increased, whereas those of WT1 were decreased in the AML-M2 compared to the AML-M1 group. We also examined the association between the STMN1, CAT and ABL1 genes, and the FLT3 and NPM1 mutation status. FLT3+/NPM1- AML was associated with the highest expression of STMN1, and ABL1 was upregulated in FLT3+ AML and CAT in FLT3- AML, irrespectively of the NPM1 mutation status. Moreover, our results indicated that CAT and WT1

Comparison of immunological characteristics of peripheral, splenic and tonsilar naïve B cells by differential gene expression meta-analyses.

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Chokeshai-u-saha, Kaj; Lepoivre, Cyrille; Grieco, Luca; Nguyen, Catherine; Ruxrungtham, Kiat

2012-12-01

Naïve B cells isolated from peripheral blood, spleen and tonsil are commonly used in human B cell studies. However, little has been written about their possible variations in immunological properties. This study compared differential gene expression in human naive B subsets by meta-analysis using expression data available in Gene Expression Onimbus (GEO). Gene expression files of the Affymetrix Human Genome U133A Array (Affymetrix) were downloaded to collect 21 total array data samples of peripheral naïve B cells (n=10), splenic naïve B cells (n=2), tonsilar naïve B cells (n=3), peripheral memory B cells (n=4) and splenic memory B cells (n=2). Prior to differential gene expression analyses, data were normalized in order to reduce non-biological variation among the datasets. Comparisons of peripheral naive B cells with their splenic and tonsilar counterparts showed remarkable differences in terms of gene expression (29 and 202 genes, respectively). However, only minor differences were detected between splenic and tonsilar naive B cells (10 genes), consistent with the clustering results classifying both of them as lymphoid naive B cells. Differential gene expression results also implied higher stimulating states of lymphoid naive B cells when compared with peripheral blood naive B cells. These included enhanced expressions of CD27, CR2, EGR1, GADD45B, ICAM1, ICOSLG, IGHA, IL6, MMP9, SAMSN1, SMAD7, TNFAIP3, but reduced HLA-DOB expression. Our findings suggest that results generated from peripheral naive B cells may not always be applicable to the biological activities of other lymphoid naïve B cells. Nonetheless, further biological study is warranted.

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.

Hox gene expression leads to differential hind leg development between honeybee castes.

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Bomtorin, Ana Durvalina; Barchuk, Angel Roberto; Moda, Livia Maria; Simoes, Zila Luz Paulino

2012-01-01

Beyond the physiological and behavioural, differences in appendage morphology between the workers and queens of Apis mellifera are pre-eminent. The hind legs of workers, which are highly specialized pollinators, deserve special attention. The hind tibia of worker has an expanded bristle-free region used for carrying pollen and propolis, the corbicula. In queens this structure is absent. Although the morphological differences are well characterized, the genetic inputs driving the development of this alternative morphology remain unknown. Leg phenotype determination takes place between the fourth and fifth larval instar and herein we show that the morphogenesis is completed at brown-eyed pupa. Using results from the hybridization of whole genome-based oligonucleotide arrays with RNA samples from hind leg imaginal discs of pre-pupal honeybees of both castes we present a list of 200 differentially expressed genes. Notably, there are castes preferentially expressed cuticular protein genes and members of the P450 family. We also provide results of qPCR analyses determining the developmental transcription profiles of eight selected genes, including abdominal-A, distal-less and ultrabithorax (Ubx), whose roles in leg development have been previously demonstrated in other insect models. Ubx expression in workers hind leg is approximately 25 times higher than in queens. Finally, immunohistochemistry assays show that Ubx localization during hind leg development resembles the bristles localization in the tibia/basitarsus of the adult legs in both castes. Our data strongly indicate that the development of the hind legs diphenism characteristic of this corbiculate species is driven by a set of caste-preferentially expressed genes, such as those encoding cuticular protein genes, P450 and Hox proteins, in response to the naturally different diets offered to honeybees during the larval period.

Genomewide Analysis of Aryl Hydrocarbon Receptor Binding Targets Reveals an Extensive Array of Gene Clusters that Control Morphogenetic and Developmental Programs

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Sartor, Maureen A.; Schnekenburger, Michael; Marlowe, Jennifer L.; Reichard, John F.; Wang, Ying; Fan, Yunxia; Ma, Ci; Karyala, Saikumar; Halbleib, Danielle; Liu, Xiangdong; Medvedovic, Mario; Puga, Alvaro

2009-01-01

Background The vertebrate aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that regulates cellular responses to environmental polycyclic and halogenated compounds. The naive receptor is believed to reside in an inactive cytosolic complex that translocates to the nucleus and induces transcription of xenobiotic detoxification genes after activation by ligand. Objectives We conducted an integrative genomewide analysis of AHR gene targets in mouse hepatoma cells and determined whether AHR regulatory functions may take place in the absence of an exogenous ligand. Methods The network of AHR-binding targets in the mouse genome was mapped through a multipronged approach involving chromatin immunoprecipitation/chip and global gene expression signatures. The findings were integrated into a prior functional knowledge base from Gene Ontology, interaction networks, Kyoto Encyclopedia of Genes and Genomes pathways, sequence motif analysis, and literature molecular concepts. Results We found the naive receptor in unstimulated cells bound to an extensive array of gene clusters with functions in regulation of gene expression, differentiation, and pattern specification, connecting multiple morphogenetic and developmental programs. Activation by the ligand displaced the receptor from some of these targets toward sites in the promoters of xenobiotic metabolism genes. Conclusions The vertebrate AHR appears to possess unsuspected regulatory functions that may be potential targets of environmental injury. PMID:19654925

Alteration of gene expression profiling including GPR174 and GNG2 is associated with vasovagal syncope.

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Huang, Yu-Juan; Zhou, Zai-wei; Xu, Miao; Ma, Qing-wen; Yan, Jing-bin; Wang, Jian-yi; Zhang, Quo-qin; Huang, Min; Bao, Liming

2015-03-01

Vasovagal syncope (VVS) causes accidental harm for susceptible patients. However, pathophysiology of this disorder remains largely unknown. In an effort to understanding of molecular mechanism for VVS, genome-wide gene expression profiling analyses were performed on VVS patients at syncope state. A total of 66 Type 1 VVS child patients and the same number healthy controls were enrolled in this study. Peripheral blood RNAs were isolated from all subjects, of which 10 RNA samples were randomly selected from each groups for gene expression profile analysis using Gene ST 1.0 arrays (Affymetrix). The results revealed that 103 genes were differently expressed between the patients and controls. Significantly, two G-proteins related genes, GPR174 and GNG2 that have not been related to VVS were among the differently expressed genes. The microarray results were confirmed by qRT-PCR in all the tested individuals. Ingenuity pathway analysis and gene ontology annotation study showed that the differently expressed genes are associated with stress response and apoptosis, suggesting that the alteration of some gene expression including G-proteins related genes is associated with VVS. This study provides new insight into the molecular mechanism of VVS and would be helpful to further identify new molecular biomarkers for the disease.

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.

Mitochondrial Gene Expression Profiles and Metabolic Pathways in the Amygdala Associated with Exaggerated Fear in an Animal Model of PTSD.

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Li, He; Li, Xin; Smerin, Stanley E; Zhang, Lei; Jia, Min; Xing, Guoqiang; Su, Yan A; Wen, Jillian; Benedek, David; Ursano, Robert

2014-01-01

The metabolic mechanisms underlying the development of exaggerated fear in post-traumatic stress disorder (PTSD) are not well defined. In the present study, alteration in the expression of genes associated with mitochondrial function in the amygdala of an animal model of PTSD was determined. Amygdala tissue samples were excised from 10 non-stressed control rats and 10 stressed rats, 14 days post-stress treatment. Total RNA was isolated, cDNA was synthesized, and gene expression levels were determined using a cDNA microarray. During the development of the exaggerated fear associated with PTSD, 48 genes were found to be significantly upregulated and 37 were significantly downregulated in the amygdala complex based on stringent criteria (p metabolism, one with transcriptional factors, and one with chromatin remodeling. Thus, informatics of a neuronal gene array allowed us to determine the expression profile of mitochondrial genes in the amygdala complex of an animal model of PTSD. The result is a further understanding of the metabolic and neuronal signaling mechanisms associated with delayed and exaggerated fear.

Gene expression in the mouse brain following early pregnancy exposure to ethanol

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Christine R. Zhang

2016-12-01

Full Text Available Exposure to alcohol during early embryonic or fetal development has been linked with a variety of adverse outcomes, the most common of which are structural and functional abnormalities of the central nervous system [1]. Behavioural and cognitive deficits reported in individuals exposed to alcohol in utero include intellectual impairment, learning and memory difficulties, diminished executive functioning, attention problems, poor motor function and hyperactivity [2]. The economic and social costs of these outcomes are substantial and profound [3,4]. Improvement of neurobehavioural outcomes following prenatal alcohol exposure requires greater understanding of the mechanisms of alcohol-induced damage to the brain. Here we use a mouse model of relatively moderate ethanol exposure early in pregnancy and profile gene expression in the hippocampus and caudate putamen of adult male offspring. The effects of offspring sex and age on ethanol-sensitive hippocampal gene expression were also examined. All array data are available at the Gene Expression Omnibus (GEO repository under accession number GSE87736.

Gene expression profile and genomic alterations in colonic tumours induced by 1,2-dimethylhydrazine (DMH) in rats

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Femia, Angelo Pietro; Luceri, Cristina; Toti, Simona; Giannini, Augusto; Dolara, Piero; Caderni, Giovanna

2010-01-01

Azoxymethane (AOM) or 1,2-dimethylhydrazine (DMH)-induced colon carcinogenesis in rats shares many phenotypical similarities with human sporadic colon cancer and is a reliable model for identifying chemopreventive agents. Genetic mutations relevant to human colon cancer have been described in this model, but comprehensive gene expression and genomic analysis have not been reported so far. Therefore, we applied genome-wide technologies to study variations in gene expression and genomic alterations in DMH-induced colon cancer in F344 rats. For gene expression analysis, 9 tumours (TUM) and their paired normal mucosa (NM) were hybridized on 4 × 44K Whole rat arrays (Agilent) and selected genes were validated by semi-quantitative RT-PCR. Functional analysis on microarray data was performed by GenMAPP/MappFinder analysis. Array-comparative genomic hybridization (a-CGH) was performed on 10 paired TUM-NM samples hybridized on Rat genome arrays 2 × 105K (Agilent) and the results were analyzed by CGH Analytics (Agilent). Microarray gene expression analysis showed that Defcr4, Igfbp5, Mmp7, Nos2, S100A8 and S100A9 were among the most up-regulated genes in tumours (Fold Change (FC) compared with NM: 183, 48, 39, 38, 36 and 32, respectively), while Slc26a3, Mptx, Retlna and Muc2 were strongly down-regulated (FC: -500; -376, -167, -79, respectively). Functional analysis showed that pathways controlling cell cycle, protein synthesis, matrix metalloproteinases, TNFα/NFkB, and inflammatory responses were up-regulated in tumours, while Krebs cycle, the electron transport chain, and fatty acid beta oxidation were down-regulated. a-CGH analysis showed that four TUM out of ten had one or two chromosomal aberrations. Importantly, one sample showed a deletion on chromosome 18 including Apc. The results showed complex gene expression alterations in adenocarcinomas encompassing many altered pathways. While a-CGH analysis showed a low degree of genomic imbalance, it is interesting to