Noise minimization in eukaryotic gene expression

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

2004-01-01

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

Multiscale Embedded Gene Co-expression Network Analysis.

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Won-Min Song

2015-11-01

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

Multiscale Embedded Gene Co-expression Network Analysis.

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Song, Won-Min; Zhang, Bin

2015-11-01

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

Analysis and visualization of gene expression data using ...

African Journals Online (AJOL)

Several clustering and biclustering methods have been introduced to analyze the gene expression data by identifying the similar patterns and grouping genes into subsets that share biological significance. However, it is not clear how the different methods compare with each other with respect to the biological relevance of ...

Genomic instability of osteosarcoma cell lines in culture: impact on the prediction of metastasis relevant genes.

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Roman Muff

Full Text Available Osteosarcoma is a rare but highly malignant cancer of the bone. As a consequence, the number of established cell lines used for experimental in vitro and in vivo osteosarcoma research is limited and the value of these cell lines relies on their stability during culture. Here we investigated the stability in gene expression by microarray analysis and array genomic hybridization of three low metastatic cell lines and derivatives thereof with increased metastatic potential using cells of different passages.The osteosarcoma cell lines showed altered gene expression during in vitro culture, and it was more pronounced in two metastatic cell lines compared to the respective parental cells. Chromosomal instability contributed in part to the altered gene expression in SAOS and LM5 cells with low and high metastatic potential. To identify metastasis-relevant genes in a background of passage-dependent altered gene expression, genes involved in "Pathways in cancer" that were consistently regulated under all passage comparisons were evaluated. Genes belonging to "Hedgehog signaling pathway" and "Wnt signaling pathway" were significantly up-regulated, and IHH, WNT10B and TCF7 were found up-regulated in all three metastatic compared to the parental cell lines.Considerable instability during culture in terms of gene expression and chromosomal aberrations was observed in osteosarcoma cell lines. The use of cells from different passages and a search for genes consistently regulated in early and late passages allows the analysis of metastasis-relevant genes despite the observed instability in gene expression in osteosarcoma cell lines during culture.

Genomic instability of osteosarcoma cell lines in culture: impact on the prediction of metastasis relevant genes.

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Muff, Roman; Rath, Prisni; Ram Kumar, Ram Mohan; Husmann, Knut; Born, Walter; Baudis, Michael; Fuchs, Bruno

2015-01-01

Osteosarcoma is a rare but highly malignant cancer of the bone. As a consequence, the number of established cell lines used for experimental in vitro and in vivo osteosarcoma research is limited and the value of these cell lines relies on their stability during culture. Here we investigated the stability in gene expression by microarray analysis and array genomic hybridization of three low metastatic cell lines and derivatives thereof with increased metastatic potential using cells of different passages. The osteosarcoma cell lines showed altered gene expression during in vitro culture, and it was more pronounced in two metastatic cell lines compared to the respective parental cells. Chromosomal instability contributed in part to the altered gene expression in SAOS and LM5 cells with low and high metastatic potential. To identify metastasis-relevant genes in a background of passage-dependent altered gene expression, genes involved in "Pathways in cancer" that were consistently regulated under all passage comparisons were evaluated. Genes belonging to "Hedgehog signaling pathway" and "Wnt signaling pathway" were significantly up-regulated, and IHH, WNT10B and TCF7 were found up-regulated in all three metastatic compared to the parental cell lines. Considerable instability during culture in terms of gene expression and chromosomal aberrations was observed in osteosarcoma cell lines. The use of cells from different passages and a search for genes consistently regulated in early and late passages allows the analysis of metastasis-relevant genes despite the observed instability in gene expression in osteosarcoma cell lines during culture.

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

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

2016-05-01

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

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.

GOBO: gene expression-based outcome for breast cancer online.

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Markus Ringnér

Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Mining gene expression data by interpreting principal components

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Mortazavi Ali

2006-04-01

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

Seasonal alteration in amounts of lignans and their glucosides and gene expression of the relevant biosynthetic enzymes in the Forsythia suspense leaf.

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Morimoto, Kinuyo; Satake, Honoo

2013-01-01

Lignans of Forsythia spp. are essential components of various Chinese medicines and health diets. However, the seasonal alteration in lignan amounts and the gene expression profile of lignan-biosynthetic enzymes has yet to be investigated. In this study, we have assessed seasonal alteration in amounts of major lignans, such as pinoresinol, matairesinol, and arctigenin, and examined the gene expression profile of pinoresinol/lariciresinol reductase (PLR), pinoresinol-glucosylating enzyme (UGT71A18), and secoisolariciresinol dehydrogenase (SIRD) in the leaf of Forsythia suspense from April to November. All of the lignans in the leaf continuously increased from April to June, reached the maximal level in June, and then decreased. Ninety percent of pinoresinol and matairesinol was converted into glucosides, while approximately 50% of arctigenin was aglycone. PLR was stably expressed from April to August, whereas the PLR expression was not detected from September to November. In contrast, the UGT71A18 expression was found from August to November, but not from April to July. The SIRD expression was prominent from April to May, not detected in June to July, and then increased again from September to November. These expression profiles of the lignan-synthetic enzymes are largely compatible with the alteration in lignan contents. Furthermore, such seasonal lignan profiles are in good agreement with the fact that the Forsythia leaves for Chinese medicinal tea are harvested in June. This is the first report on seasonal alteration in lignans and the relevant biosynthetic enzyme genes in the leaf of Forsythia species.

Genetics of sputum gene expression in chronic obstructive pulmonary disease.

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Weiliang Qiu

Full Text Available Previous expression quantitative trait loci (eQTL studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs. The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5, the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus.

Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

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Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

2011-01-01

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

Repressor-mediated tissue-specific gene expression in plants

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Meagher, Richard B [Athens, GA; Balish, Rebecca S [Oxford, OH; Tehryung, Kim [Athens, GA; McKinney, Elizabeth C [Athens, GA

2009-02-17

Plant tissue specific gene expression by way of repressor-operator complexes, has enabled outcomes including, without limitation, male sterility and engineered plants having root-specific gene expression of relevant proteins to clean environmental pollutants from soil and water. A mercury hyperaccumulation strategy requires that mercuric ion reductase coding sequence is strongly expressed. The actin promoter vector, A2pot, engineered to contain bacterial lac operator sequences, directed strong expression in all plant vegetative organs and tissues. In contrast, the expression from the A2pot construct was restricted primarily to root tissues when a modified bacterial repressor (LacIn) was coexpressed from the light-regulated rubisco small subunit promoter in above-ground tissues. Also provided are analogous repressor operator complexes for selective expression in other plant tissues, for example, to produce male sterile plants.

Gene expression

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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

Clock Genes Influence Gene Expression in Growth Plate and Endochondral Ossification in Mice*

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Takarada, Takeshi; Kodama, Ayumi; Hotta, Shogo; Mieda, Michihiro; Shimba, Shigeki; Hinoi, Eiichi; Yoneda, Yukio

2012-01-01

We have previously shown transient promotion by parathyroid hormone of Period-1 (Per1) expression in cultured chondrocytes. Here we show the modulation by clock genes of chondrogenic differentiation through gene transactivation of the master regulator of chondrogenesis Indian hedgehog (IHH) in chondrocytes of the growth plate. Several clock genes were expressed with oscillatory rhythmicity in cultured chondrocytes and rib growth plate in mice, whereas chondrogenesis was markedly inhibited in stable transfectants of Per1 in chondrocytic ATDC5 cells and in rib growth plate chondrocytes from mice deficient of brain and muscle aryl hydrocarbon receptor nuclear translocator-like (BMAL1). Ihh promoter activity was regulated by different clock gene products, with clear circadian rhythmicity in expression profiles of Ihh in the growth plate. In BMAL1-null mice, a predominant decrease was seen in Ihh expression in the growth plate with a smaller body size than in wild-type mice. BMAL1 deficit led to disruption of the rhythmic expression profiles of both Per1 and Ihh in the growth plate. A clear rhythmicity was seen with Ihh expression in ATDC5 cells exposed to dexamethasone. In young mice defective of BMAL1 exclusively in chondrocytes, similar abnormalities were found in bone growth and Ihh expression. These results suggest that endochondral ossification is under the regulation of particular clock gene products expressed in chondrocytes during postnatal skeletogenesis through a mechanism relevant to the rhythmic Ihh expression. PMID:22936800

Global gene expression in Escherichia coli biofilms

DEFF Research Database (Denmark)

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

2003-01-01

It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance to antimicr......It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance...... the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered...... in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces....

GeneBins: a database for classifying gene expression data, with application to plant genome arrays

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Weiller Georg

2007-03-01

Full Text Available Abstract Background To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms. Results We developed a bioinformatics system to assign the probe set sequences of any organism to a hierarchical functional classification modelled on KEGG ontology. The GeneBins database currently supports the functional classification of expression data from four Affymetrix arrays; Arabidopsis thaliana, Oryza sativa, Glycine max and Medicago truncatula. An online analysis tool to identify relevant functions is also provided. Conclusion GeneBins provides resources to interpret gene expression results from microarray experiments. It is available at http://bioinfoserver.rsbs.anu.edu.au/utils/GeneBins/

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

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.

Changes in Histopathology, Enzyme Activities, and the Expression of Relevant Genes in Zebrafish (Danio rerio) Following Long-Term Exposure to Environmental Levels of Thallium.

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Hou, Li-Ping; Yang, Yang; Shu, Hu; Ying, Guang-Guo; Zhao, Jian-Liang; Chen, Yi-Bing; Chen, Yong-Heng; Fang, Gui-Zhen; Li, Xin; Liu, Ji-Sheng

2017-11-01

Thallium is a rare-earth element, but widely distributed in water environments, posing a potential risk to our health. This study was designed to investigate the chronic effects of thallium based on physiological responses, gene expression, and changes in the activity of relevant enzymes in adult zebra fish exposed to thallium at low doses. The endpoints assessed include mRNA expression of metallothionein (MT)2 and heat shock protein HSP70; enzymatic activities of superoxide dismutase (SOD) and Na + /K + -ATPase; and the histopathology of gill, gonad, and liver tissues. The results showed significant increases in HSP70 mRNA expression following exposure to 100 ng/L thallium and in MT2 expression following exposure to 500 ng/L thallium. Significantly higher activities were observed for SOD in liver and Na + /K + -ATPase activity in gill in zebra fish exposed to thallium (20 and 100 ng/L, respectively) in comparison to control fish. Gill, liver, and gonad tissues displayed different degrees of damage. The overall results imply that thallium may cause toxicity to zebra fish at environmentally relevant aqueous concentrations.

The expression of antibiotic resistance genes in antibiotic-producing bacteria.

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Mak, Stefanie; Xu, Ye; Nodwell, Justin R

2014-08-01

Antibiotic-producing bacteria encode antibiotic resistance genes that protect them from the biologically active molecules that they produce. The expression of these genes needs to occur in a timely manner: either in advance of or concomitantly with biosynthesis. It appears that there have been at least two general solutions to this problem. In many cases, the expression of resistance genes is tightly linked to that of antibiotic biosynthetic genes. In others, the resistance genes can be induced by their cognate antibiotics or by intermediate molecules from their biosynthetic pathways. The regulatory mechanisms that couple resistance to antibiotic biosynthesis are mechanistically diverse and potentially relevant to the origins of clinical antibiotic resistance. © 2014 John Wiley & Sons Ltd.

Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

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Xi Wang

2015-05-01

Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

A compendium of canine normal tissue gene expression.

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Joseph Briggs

Full Text Available BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. CONCLUSIONS/SIGNIFICANCE: These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large.

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

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Madeira Sara C

2009-06-01

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

Imaging gene expression in gene therapy

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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

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.

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 ...

Imaging gene expression in gene therapy

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-31

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

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

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Pugalendhi Ganesh Kumar

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

Environmental history impacts gene expression during diapause development in the alfalfa leafcutting bee, Megachile rotundata

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Our understanding of the mechanisms controlling insect diapause has increased dramatically with the introduction of global gene expression techniques, such as RNAseq. However, little attention has been given to how ecologically relevant field conditions may affect gene expression during diapause dev...

The Fanconi anemia/BRCA gene network in zebrafish: Embryonic expression and comparative genomics

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Titus, Tom A.; Yan Yilin; Wilson, Catherine; Starks, Amber M.; Frohnmayer, Jonathan D.; Bremiller, Ruth A.; Canestro, Cristian; Rodriguez-Mari, Adriana; He Xinjun [Institute of Neuroscience, University of Oregon, 1425 E. 13th Avenue, Eugene, OR 97403 (United States); Postlethwait, John H., E-mail: jpostle@uoneuro.uoregon.edu [Institute of Neuroscience, University of Oregon, 1425 E. 13th Avenue, Eugene, OR 97403 (United States)

2009-07-31

Fanconi anemia (FA) is a genetic disease resulting in bone marrow failure, high cancer risks, and infertility, and developmental anomalies including microphthalmia, microcephaly, hypoplastic radius and thumb. Here we present cDNA sequences, genetic mapping, and genomic analyses for the four previously undescribed zebrafish FA genes (fanci, fancj, fancm, and fancn), and show that they reverted to single copy after the teleost genome duplication. We tested the hypothesis that FA genes are expressed during embryonic development in tissues that are disrupted in human patients by investigating fanc gene expression patterns. We found fanc gene maternal message, which can provide Fanc proteins to repair DNA damage encountered in rapid cleavage divisions. Zygotic expression was broad but especially strong in eyes, central nervous system and hematopoietic tissues. In the pectoral fin bud at hatching, fanc genes were expressed specifically in the apical ectodermal ridge, a signaling center for fin/limb development that may be relevant to the radius/thumb anomaly of FA patients. Hatching embryos expressed fanc genes strongly in the oral epithelium, a site of squamous cell carcinomas in FA patients. Larval and adult zebrafish expressed fanc genes in proliferative regions of the brain, which may be related to microcephaly in FA. Mature ovaries and testes expressed fanc genes in specific stages of oocyte and spermatocyte development, which may be related to DNA repair during homologous recombination in meiosis and to infertility in human patients. The intestine strongly expressed some fanc genes specifically in proliferative zones. Our results show that zebrafish has a complete complement of fanc genes in single copy and that these genes are expressed in zebrafish embryos and adults in proliferative tissues that are often affected in FA patients. These results support the notion that zebrafish offers an attractive experimental system to help unravel mechanisms relevant not only

The Fanconi anemia/BRCA gene network in zebrafish: embryonic expression and comparative genomics.

Science.gov (United States)

Titus, Tom A; Yan, Yi-Lin; Wilson, Catherine; Starks, Amber M; Frohnmayer, Jonathan D; Bremiller, Ruth A; Cañestro, Cristian; Rodriguez-Mari, Adriana; He, Xinjun; Postlethwait, John H

2009-07-31

Fanconi anemia (FA) is a genetic disease resulting in bone marrow failure, high cancer risks, and infertility, and developmental anomalies including microphthalmia, microcephaly, hypoplastic radius and thumb. Here we present cDNA sequences, genetic mapping, and genomic analyses for the four previously undescribed zebrafish FA genes (fanci, fancj, fancm, and fancn), and show that they reverted to single copy after the teleost genome duplication. We tested the hypothesis that FA genes are expressed during embryonic development in tissues that are disrupted in human patients by investigating fanc gene expression patterns. We found fanc gene maternal message, which can provide Fanc proteins to repair DNA damage encountered in rapid cleavage divisions. Zygotic expression was broad but especially strong in eyes, central nervous system and hematopoietic tissues. In the pectoral fin bud at hatching, fanc genes were expressed specifically in the apical ectodermal ridge, a signaling center for fin/limb development that may be relevant to the radius/thumb anomaly of FA patients. Hatching embryos expressed fanc genes strongly in the oral epithelium, a site of squamous cell carcinomas in FA patients. Larval and adult zebrafish expressed fanc genes in proliferative regions of the brain, which may be related to microcephaly in FA. Mature ovaries and testes expressed fanc genes in specific stages of oocyte and spermatocyte development, which may be related to DNA repair during homologous recombination in meiosis and to infertility in human patients. The intestine strongly expressed some fanc genes specifically in proliferative zones. Our results show that zebrafish has a complete complement of fanc genes in single copy and that these genes are expressed in zebrafish embryos and adults in proliferative tissues that are often affected in FA patients. These results support the notion that zebrafish offers an attractive experimental system to help unravel mechanisms relevant not only

The Fanconi anemia/BRCA gene network in zebrafish: Embryonic expression and comparative genomics

International Nuclear Information System (INIS)

Titus, Tom A.; Yan Yilin; Wilson, Catherine; Starks, Amber M.; Frohnmayer, Jonathan D.; Bremiller, Ruth A.; Canestro, Cristian; Rodriguez-Mari, Adriana; He Xinjun; Postlethwait, John H.

2009-01-01

Fanconi anemia (FA) is a genetic disease resulting in bone marrow failure, high cancer risks, and infertility, and developmental anomalies including microphthalmia, microcephaly, hypoplastic radius and thumb. Here we present cDNA sequences, genetic mapping, and genomic analyses for the four previously undescribed zebrafish FA genes (fanci, fancj, fancm, and fancn), and show that they reverted to single copy after the teleost genome duplication. We tested the hypothesis that FA genes are expressed during embryonic development in tissues that are disrupted in human patients by investigating fanc gene expression patterns. We found fanc gene maternal message, which can provide Fanc proteins to repair DNA damage encountered in rapid cleavage divisions. Zygotic expression was broad but especially strong in eyes, central nervous system and hematopoietic tissues. In the pectoral fin bud at hatching, fanc genes were expressed specifically in the apical ectodermal ridge, a signaling center for fin/limb development that may be relevant to the radius/thumb anomaly of FA patients. Hatching embryos expressed fanc genes strongly in the oral epithelium, a site of squamous cell carcinomas in FA patients. Larval and adult zebrafish expressed fanc genes in proliferative regions of the brain, which may be related to microcephaly in FA. Mature ovaries and testes expressed fanc genes in specific stages of oocyte and spermatocyte development, which may be related to DNA repair during homologous recombination in meiosis and to infertility in human patients. The intestine strongly expressed some fanc genes specifically in proliferative zones. Our results show that zebrafish has a complete complement of fanc genes in single copy and that these genes are expressed in zebrafish embryos and adults in proliferative tissues that are often affected in FA patients. These results support the notion that zebrafish offers an attractive experimental system to help unravel mechanisms relevant not only

Identification of highly synchronized subnetworks from gene expression data.

Science.gov (United States)

Gao, Shouguo; Wang, Xujing

2013-01-01

There has been a growing interest in identifying context-specific active protein-protein interaction (PPI) subnetworks through integration of PPI and time course gene expression data. However the interaction dynamics during the biological process under study has not been sufficiently considered previously. Here we propose a topology-phase locking (TopoPL) based scoring metric for identifying active PPI subnetworks from time series expression data. First the temporal coordination in gene expression changes is evaluated through phase locking analysis; The results are subsequently integrated with PPI to define an activity score for each PPI subnetwork, based on individual member expression, as well topological characteristics of the PPI network and of the expression temporal coordination network; Lastly, the subnetworks with the top scores in the whole PPI network are identified through simulated annealing search. Application of TopoPL to simulated data and to the yeast cell cycle data showed that it can more sensitively identify biologically meaningful subnetworks than the method that only utilizes the static PPI topology, or the additive scoring method. Using TopoPL we identified a core subnetwork with 49 genes important to yeast cell cycle. Interestingly, this core contains a protein complex known to be related to arrangement of ribosome subunits that exhibit extremely high gene expression synchronization. Inclusion of interaction dynamics is important to the identification of relevant gene networks.

Development of Gene Expression Signatures for Practical Radiation Biodosimetry

International Nuclear Information System (INIS)

Paul, Sunirmal; Amundson, Sally A.

2008-01-01

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

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

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Sahra Uygun

2016-12-01

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

Radiation-modulated gene expression in C. elegans

International Nuclear Information System (INIS)

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

2003-01-01

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

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

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Kleinjans Jos

2008-09-01

Full Text Available Abstract Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh, is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution.

Science.gov (United States)

Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

2008-09-02

In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that

Caffeine exposure alters cardiac gene expression in embryonic cardiomyocytes

Science.gov (United States)

Fang, Xiefan; Mei, Wenbin; Barbazuk, William B.; Rivkees, Scott A.

2014-01-01

Previous studies demonstrated that in utero caffeine treatment at embryonic day (E) 8.5 alters DNA methylation patterns, gene expression, and cardiac function in adult mice. To provide insight into the mechanisms, we examined cardiac gene and microRNA (miRNA) expression in cardiomyocytes shortly after exposure to physiologically relevant doses of caffeine. In HL-1 and primary embryonic cardiomyocytes, caffeine treatment for 48 h significantly altered the expression of cardiac structural genes (Myh6, Myh7, Myh7b, Tnni3), hormonal genes (Anp and BnP), cardiac transcription factors (Gata4, Mef2c, Mef2d, Nfatc1), and microRNAs (miRNAs; miR208a, miR208b, miR499). In addition, expressions of these genes were significantly altered in embryonic hearts exposed to in utero caffeine. For in utero experiments, pregnant CD-1 dams were treated with 20–60 mg/kg of caffeine, which resulted in maternal circulation levels of 37.3–65.3 μM 2 h after treatment. RNA sequencing was performed on embryonic ventricles treated with vehicle or 20 mg/kg of caffeine daily from E6.5-9.5. Differential expression (DE) analysis revealed that 124 genes and 849 transcripts were significantly altered, and differential exon usage (DEU) analysis identified 597 exons that were changed in response to prenatal caffeine exposure. Among the DE genes identified by RNA sequencing were several cardiac structural genes and genes that control DNA methylation and histone modification. Pathway analysis revealed that pathways related to cardiovascular development and diseases were significantly affected by caffeine. In addition, global cardiac DNA methylation was reduced in caffeine-treated cardiomyocytes. Collectively, these data demonstrate that caffeine exposure alters gene expression and DNA methylation in embryonic cardiomyocytes. PMID:25354728

Differential Effect of Active Smoking on Gene Expression in Male and Female Smokers

Science.gov (United States)

Paul, Sunirmal; Amundson, Sally A

2015-01-01

Smoking is the second leading cause of preventable death in the United States. Cohort epidemiological studies have demonstrated that women are more vulnerable to cigarette-smoking induced diseases than their male counterparts, however, the molecular basis of these differences has remained unknown. In this study, we explored if there were differences in the gene expression patterns between male and female smokers, and how these patterns might reflect different sex-specific responses to the stress of smoking. Using whole genome microarray gene expression profiling, we found that a substantial number of oxidant related genes were expressed in both male and female smokers, however, smoking-responsive genes did indeed differ greatly between male and female smokers. Gene set enrichment analysis (GSEA) against reference oncogenic signature gene sets identified a large number of oncogenic pathway gene-sets that were significantly altered in female smokers compared to male smokers. In addition, functional annotation with Ingenuity Pathway Analysis (IPA) identified smoking-correlated genes associated with biological functions in male and female smokers that are directly relevant to well-known smoking related pathologies. However, these relevant biological functions were strikingly overrepresented in female smokers compared to male smokers. IPA network analysis with the functional categories of immune and inflammatory response gene products suggested potential interactions between smoking response and female hormones. Our results demonstrate a striking dichotomy between male and female gene expression responses to smoking. This is the first genome-wide expression study to compare the sex-specific impacts of smoking at a molecular level and suggests a novel potential connection between sex hormone signaling and smoking-induced diseases in female smokers. PMID:25621181

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

Pattern of expression of immune-relevant genes in the gonad of a teleost, the gilthead seabream (Sparus aurata L.).

Science.gov (United States)

Chaves-Pozo, E; Liarte, S; Fernández-Alacid, L; Abellán, E; Meseguer, J; Mulero, V; García-Ayala, A

2008-05-01

Immune responses in the testis are regulated in a way that provides protection for the developing male germ cells, while permitting qualitatively normal inflammatory responses and protection against infection. In addition, germ cells are potent targets for the growth factors and cytokines which regulate the reproductive process. Our study analyzes for the first time the pattern of expression of several immune-relevant genes in the gonad of a seasonal breeding teleost fish. The immune molecules analyzed include (i) inflammatory molecules, such as interleukin-1b (il1b), il6, tumor necrosis factor-a (tnfa), cyclooxygenase-2 (cox2) and the NADPH oxidase subunit p40(phox) (ncf4 gene); (ii) the anti-inflammatory cytokine transforming growth factor-b1 (tgfb1) and its type 2 receptor tgfbr2; (iii) innate immune receptors, including toll-like receptor 9 (tlr9), tlr5, tlr22 and macrophage-colony stimulating factor receptor (mcsfr); (iv) lymphocyte receptors, such as the beta subunit of T-cell receptor (Tcrb) and the heavy chain of immunoglobulin M (ighm); (v) the anti-bacterial molecules lysozyme (lyz), hepcidin (hamp) and complement component 3 (c3); (vi) the anti-viral molecule myxovirus (influenza) resistance protein (mx); and (vii) molecules related to leukocyte infiltration, including the CC chemokine ccl4, the CXC chemokine il8 and the leukocyte adhesion molecule E-selectin (Sele). Notably, all of them show a pattern of expression that depends on the reproductive stage of the first two reproductive cycles when the fish develop and function as males. Furthermore, we demonstrate that some of these immune-relevant molecules, such as Il1b and Mcsfr, are produced by germ cells (Il1b) and ovarian and testicular somatic cells (Mcsfr). These data suggest that, as occurs in mammals, there is a critical balance between immune molecules and that these may play an essential role in the orchestration of gametogenesis and the maintenance of gonad tissue homeostasis in fish.

Gene Expression by PBMC in Primary Sclerosing Cholangitis: Evidence for Dysregulation of Immune Mediated Genes

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Christopher A. Aoki

2006-01-01

Full Text Available Primary sclerosing cholangitis (PSC is a chronic disease of the bile ducts characterized by an inflammatory infiltrate and obliterative fibrosis. The precise role of the immune system in the pathogenesis of PSC remains unknown. We used RNA microarray analysis to identify immune-related genes and pathways that are differentially expressed in PSC. Messenger RNA (mRNA from peripheral blood mononuclear cells (PBMC was isolated from both patients with PSC and age and sex matched healthy controls. Samples from 5 PSC patients and 5 controls were analyzed by microarray and based upon rigorous statistical analysis of the data, relevant genes were chosen for confirmation by RT-PCR in 10 PSC patients and 10 controls. Using unsupervised hierarchical clustering, gene expression in PSC was statistically different from our control population. Interestingly, genes within the IL-2 receptor beta, IL-6 and MAP Kinase pathways were found to be differently expressed in patients with PSC compared to controls. Further, individual genes, TNF-α induced protein 6 (TNFaip6 and membrane-spanning 4-domains, subfamily A (ms4a were found to be upregulated in PSC while similar to Mothers against decapentaplegic homolog 5 (SMAD 5 was downregulated. In conclusion, several immune-related pathways and genes were differentially expressed in PSC compared to control patients, giving further evidence that this disease is systemic and immune-mediated.

A chronological expression profile of gene activity during embryonic mouse brain development.

Science.gov (United States)

Goggolidou, P; Soneji, S; Powles-Glover, N; Williams, D; Sethi, S; Baban, D; Simon, M M; Ragoussis, I; Norris, D P

2013-12-01

The brain is a functionally complex organ, the patterning and development of which are key to adult health. To help elucidate the genetic networks underlying mammalian brain patterning, we conducted detailed transcriptional profiling during embryonic development of the mouse brain. A total of 2,400 genes were identified as showing differential expression between three developmental stages. Analysis of the data identified nine gene clusters to demonstrate analogous expression profiles. A significant group of novel genes of as yet undiscovered biological function were detected as being potentially relevant to brain development and function, in addition to genes that have previously identified roles in the brain. Furthermore, analysis for genes that display asymmetric expression between the left and right brain hemispheres during development revealed 35 genes as putatively asymmetric from a combined data set. Our data constitute a valuable new resource for neuroscience and neurodevelopment, exposing possible functional associations between genes, including novel loci, and encouraging their further investigation in human neurological and behavioural disorders.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

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Anna A. Igolkina

2018-06-01

Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

Stress associated gene expression in blood cells is related to outcome in radiotherapy treated head and neck cancer patients

International Nuclear Information System (INIS)

Bøhn, Siv K; Blomhoff, Rune; Russnes, Kjell M; Sakhi, Amrit K; Thoresen, Magne; Holden, Marit; Moskaug, JanØ; Myhrstad, Mari C; Olstad, Ole K; Smeland, Sigbjørn

2012-01-01

We previously observed that a radiotherapy-induced biochemical response in plasma was associated with favourable outcome in head and neck squamous carcinoma cancer (HNSCC) patients. The aim of the present study was to compare stress associated blood cell gene expression between two sub-groups of HNSCC patients with different biochemical responses to radiotherapy. Out of 87 patients (histologically verified), 10 biochemical ‘responders’ having a high relative increase in plasma oxidative damage and a concomitant decrease in plasma antioxidants during radiotherapy and 10 ‘poor-responders’ were selected for gene-expression analysis and compared using gene set enrichment analysis. There was a significant induction of stress-relevant gene-sets in the responders following radiotherapy compared to the poor-responders. The relevance of the involvement of similar stress associated gene expression for HNSCC cancer and radioresistance was verified using two publicly available data sets of 42 HNSCC cases and 14 controls (GEO GSE6791), and radiation resistant and radiation sensitive HNSCC xenografts (E-GEOD-9716). Radiotherapy induces a systemic stress response, as revealed by induction of stress relevant gene expression in blood cells, which is associated to favourable outcome in a cohort of 87 HNSCC patients. Whether these changes in gene expression reflects a systemic effect or are biomarkers of the tumour micro-environmental status needs further study. Raw data are available at ArrayExpress under accession number E-MEXP-2460

Gene Expression in the Human Brain: The Current State of the Study of Specificity and Spatiotemporal Dynamics

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Naumova, Oksana Yu.; Lee, Maria; Rychkov, Sergei Yu.; Vlasova, Natalia V.; Grigorenko, Elena L.

2013-01-01

Gene expression is one of the main molecular processes regulating the differentiation, development, and functioning of cells and tissues. In this review a handful of relevant terms and concepts are introduced and the most common techniques used in studies of gene expression/expression profiling (also referred to as studies of the transcriptome or…

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

DEFF Research Database (Denmark)

Manijak, Mieszko P.; Nielsen, Henrik Bjørn

2011-01-01

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

Gene expression patterns associated with p53 status in breast cancer

International Nuclear Information System (INIS)

Troester, Melissa A; Herschkowitz, Jason I; Oh, Daniel S; He, Xiaping; Hoadley, Katherine A; Barbier, Claire S; Perou, Charles M

2006-01-01

Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors. Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data. In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes

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

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

2015-01-27

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

Early passage bone marrow stromal cells express genes involved in nervous system development supporting their relevance for neural repair

NARCIS (Netherlands)

Nandoe Tewarie, R.D.S.; Bossers, K.; Ritfeld, G.J.; Blits, B.; Grotenhuis, J.A.; Verhaagen, J.; Oudega, M.

2011-01-01

PURPOSE: The assessment of the capacity of bone marrow stromal cells (BMSC) to repair the nervous system using gene expression profiling. The evaluation of effects of long-term culturing on the gene expression profile of BMSC. METHODS: Fourty four k whole genome rat microarrays were used to study

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

Epigenetics and gene expression profile in first-episode psychosis: The role of childhood trauma.

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Tomassi, Simona; Tosato, Sarah

2017-12-01

Childhood Trauma (CT) mediation of the epigenome and its impact on gene expression profile could provide a mechanism for the gene-environment interaction underling psychosis. We reviewed the evidence concerning epigenetic and gene expression modifications associated with CT in both First-Episode Psychosis (FEP) and healthy subjects. In order to explore the relative role of psychosis itself in determining these modifications, evidence about FEP and epigenetics/gene expression was also summarized. We performed a systematic search on PubMed, last updated in December 2016. Out of 2966 potentially relevant records, only 41 studies were included. CT resulted associated: in FEP subjects, with global DNA hypo-methylation and reduced BDNF gene-expression; in healthy subjects, with hyper-methylation of SLC6A4, NR3C1, KITLG, and OXTR; hypo-methylation of FKBP5, IL-6, and BDNF; increased IL1B, IL8, and PTGS gene expression; and decreased SLC6A4 gene expression. FEP showed global DNA hypo-methylation; increased methylation and reduced gene expression of GCH1; hyper-expression of MPB, NDEL1, AKT1, and DICER1; and hypo-expression of DROSHA, COMT, and DISC1 in comparison with healthy controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Changes in gene expression linked to methamphetamine-induced dopaminergic neurotoxicity.

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Xie, Tao; Tong, Liqiong; Barrett, Tanya; Yuan, Jie; Hatzidimitriou, George; McCann, Una D; Becker, Kevin G; Donovan, David M; Ricaurte, George A

2002-01-01

The purpose of these studies was to examine the role of gene expression in methamphetamine (METH)-induced dopamine (DA) neurotoxicity. First, the effects of the mRNA synthesis inhibitor, actinomycin-D, and the protein synthesis inhibitor, cycloheximide, were examined. Both agents afforded complete protection against METH-induced DA neurotoxicity and did so independently of effects on core temperature, DA transporter function, or METH brain levels, suggesting that gene transcription and mRNA translation play a role in METH neurotoxicity. Next, microarray technology, in combination with an experimental approach designed to facilitate recognition of relevant gene expression patterns, was used to identify gene products linked to METH-induced DA neurotoxicity. This led to the identification of several genes in the ventral midbrain associated with the neurotoxic process, including genes for energy metabolism [cytochrome c oxidase subunit 1 (COX1), reduced nicotinamide adenine dinucleotide ubiquinone oxidoreductase chain 2, and phosphoglycerate mutase B], ion regulation (members of sodium/hydrogen exchanger and sodium/bile acid cotransporter family), signal transduction (adenylyl cyclase III), and cell differentiation and degeneration (N-myc downstream-regulated gene 3 and tau protein). Of these differentially expressed genes, we elected to further examine the increase in COX1 expression, because of data implicating energy utilization in METH neurotoxicity and the known role of COX1 in energy metabolism. On the basis of time course studies, Northern blot analyses, in situ hybridization results, and temperature studies, we now report that increased COX1 expression in the ventral midbrain is linked to METH-induced DA neuronal injury. The precise role of COX1 and other genes in METH neurotoxicity remains to be elucidated.

Eukaryotic snoRNAs: a paradigm for gene expression flexibility.

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Dieci, Giorgio; Preti, Milena; Montanini, Barbara

2009-08-01

Small nucleolar RNAs (snoRNAs) are one of the most ancient and numerous families of non-protein-coding RNAs (ncRNAs). The main function of snoRNAs - to guide site-specific rRNA modification - is the same in Archaea and all eukaryotic lineages. In contrast, as revealed by recent genomic and RNomic studies, their genomic organization and expression strategies are the most varied. Seemingly snoRNA coding units have adopted, in the course of evolution, all the possible ways of being transcribed, thus providing a unique paradigm of gene expression flexibility. By focusing on representative fungal, plant and animal genomes, we review here all the documented types of snoRNA gene organization and expression, and we provide a comprehensive account of snoRNA expressional freedom by precisely estimating the frequency, in each genome, of each type of genomic organization. We finally discuss the relevance of snoRNA genomic studies for our general understanding of ncRNA family evolution and expression in eukaryotes.

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

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Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-12-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

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

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Benjamin Mayne

2016-10-01

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

Gene expression profiles in prostate cancer: identification of candidate non-invasive diagnostic markers.

Science.gov (United States)

Mengual, L; Ars, E; Lozano, J J; Burset, M; Izquierdo, L; Ingelmo-Torres, M; Gaya, J M; Algaba, F; Villavicencio, H; Ribal, M J; Alcaraz, A

2014-04-01

To analyze gene expression profiles of prostate cancer (PCa) with the aim of determining the relevant differentially expressed genes and subsequently ascertain whether this differential expression is maintained in post-prostatic massage (PPM) urine samples. Forty-six tissue specimens (36 from PCa patients and 10 controls) and 158 urine PPM-urines (113 from PCa patients and 45 controls) were collected between December 2003 and May 2007. DNA microarrays were used to identify genes differentially expressed between tumour and control samples. Ten genes were technically validated in the same tissue samples by quantitative RT-PCR (RT-qPCR). Forty two selected differentially expressed genes were validated in an independent set of PPM-urines by qRT-PCR. Multidimensional scaling plot according to the expression of all the microarray genes showed a clear distinction between control and tumour samples. A total of 1047 differentially expressed genes (FDR≤.1) were indentified between both groups of samples. We found a high correlation in the comparison of microarray and RT-qPCR gene expression levels (r=.928, P<.001). Thirteen genes maintained the same fold change direction when analyzed in PPM-urine samples and in four of them (HOXC6, PCA3, PDK4 and TMPRSS2-ERG), these differences were statistically significant (P<.05). The analysis of PCa by DNA microarrays provides new putative mRNA markers for PCa diagnosis that, with caution, can be extrapolated to PPM-urines. Copyright © 2013 AEU. Published by Elsevier Espana. All rights reserved.

Gene co-expression networks shed light into diseases of brain iron accumulation.

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Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M; Botía, Juan A; Collingwood, Joanna F; Hardy, John; Milward, Elizabeth A; Ryten, Mina; Houlden, Henry

2016-03-01

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

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

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

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Elias, Dwayne A.; Mukhopadhyay, Aindrila; Joachimiak, Marcin P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Keasling, Jay D.; Wall, Judy D.

2008-10-27

Hypothetical and conserved hypothetical genes account for>30percent of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved hypothetical (9.5percent) along with 887 hypothetical genes (24.4percent). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 hypothetical and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC-MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. 1212 of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.

Comparative gene expression analysis throughout the life cycle of Leishmania braziliensis: diversity of expression profiles among clinical isolates.

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Vanessa Adaui

Full Text Available BACKGROUND: Most of the Leishmania genome is reported to be constitutively expressed during the life cycle of the parasite, with a few regulated genes. Inter-species comparative transcriptomics evidenced a low number of species-specific differences related to differentially distributed genes or the differential regulation of conserved genes. It is of uppermost importance to ensure that the observed differences are indeed species-specific and not simply specific of the strains selected for representing the species. The relevance of this concern is illustrated by current study. METHODOLOGY/PRINCIPAL FINDINGS: We selected 5 clinical isolates of L. braziliensis characterized by their diversity of clinical and in vitro phenotypes. Real-time quantitative PCR was performed on promastigote and amastigote life stages to assess gene expression profiles at seven time points covering the whole life cycle. We tested 12 genes encoding proteins with roles in transport, thiol-based redox metabolism, cellular reduction, RNA poly(A-tail metabolism, cytoskeleton function and ribosomal function. The general trend of expression profiles showed that regulation of gene expression essentially occurs around the stationary phase of promastigotes. However, the genes involved in this phenomenon appeared to vary significantly among the isolates considered. CONCLUSION/SIGNIFICANCE: Our results clearly illustrate the unique character of each isolate in terms of gene expression dynamics. Results obtained on an individual strain are not necessarily representative of a given species. Therefore, extreme care should be taken when comparing the profiles of different species and extrapolating functional differences between them.

ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.

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Brett A McKinney

Full Text Available Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k for each gene to optimize the Relief-F test statistics (importance scores for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to

Differential Gene Expression and Aging

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Laurent Seroude

2002-01-01

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

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

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

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

2017-02-16

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

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

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Ang Cui

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

Gene expression profiles of fin regeneration in loach (Paramisgurnus dabryanu).

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Li, Li; He, Jingya; Wang, Linlin; Chen, Weihua; Chang, Zhongjie

2017-11-01

Teleost fins can regenerate accurate position-matched structure and function after amputation. However, we still lack systematic transcriptional profiling and methodologies to understand the molecular basis of fin regeneration. After histological analysis, we established a suppression subtraction hybridization library containing 418 distinct sequences expressed differentially during the process of blastema formation and differentiation in caudal fin regeneration. Genome ontology and comparative analysis of differential distribution of our data and the reference zebrafish genome showed notable subcategories, including multi-organism processes, response to stimuli, extracellular matrix, antioxidant activity, and cell junction function. KEGG pathway analysis allowed the effective identification of relevant genes in those pathways involved in tissue morphogenesis and regeneration, including tight junction, cell adhesion molecules, mTOR and Jak-STAT signaling pathway. From relevant function subcategories and signaling pathways, 78 clones were examined for further Southern-blot hybridization. Then, 17 genes were chosen and characterized using semi-quantitative PCR. Then 4 candidate genes were identified, including F11r, Mmp9, Agr2 and one without a match to any database. After real-time quantitative PCR, the results showed obvious expression changes in different periods of caudal fin regeneration. We can assume that the 4 candidates, likely valuable genes associated with fin regeneration, deserve additional attention. Thus, our study demonstrated how to investigate the transcript profiles with an emphasis on bioinformatics intervention and how to identify potential genes related to fin regeneration processes. The results also provide a foundation or knowledge for further research into genes and molecular mechanisms of fin regeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations

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Parmigiani Giovanni

2009-08-01

Full Text Available Abstract Background A major challenge in computational biology is to extract knowledge about the genetic nature of disease from high-throughput data. However, an important obstacle to both biological understanding and clinical applications is the "black box" nature of the decision rules provided by most machine learning approaches, which usually involve many genes combined in a highly complex fashion. Achieving biologically relevant results argues for a different strategy. A promising alternative is to base prediction entirely upon the relative expression ordering of a small number of genes. Results We present a three-gene version of "relative expression analysis" (RXA, a rigorous and systematic comparison with earlier approaches in a variety of cancer studies, a clinically relevant application to predicting germline BRCA1 mutations in breast cancer and a cross-study validation for predicting ER status. In the BRCA1 study, RXA yields high accuracy with a simple decision rule: in tumors carrying mutations, the expression of a "reference gene" falls between the expression of two differentially expressed genes, PPP1CB and RNF14. An analysis of the protein-protein interactions among the triplet of genes and BRCA1 suggests that the classifier has a biological foundation. Conclusion RXA has the potential to identify genomic "marker interactions" with plausible biological interpretation and direct clinical applicability. It provides a general framework for understanding the roles of the genes involved in decision rules, as illustrated for the difficult and clinically relevant problem of identifying BRCA1 mutation carriers.

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)

Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

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List Markus

2014-06-01

Full Text Available Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.

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.

The use of general and specific combining abilities in a context of gene expression relevant to plant breeding

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Vuylsteke, M.; Eeuwijk, van F.A.

2008-01-01

Many common traits are believed to be a composite reflection of multiple genetic and environmental factors. Recent advances suggest that subtle variations in the regulation of gene expression may contribute to quantitative traits. The nature of sequence variation affecting the regulation of gene

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

Extracting biologically significant patterns from short time series gene expression data

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McGinnis Thomas

2009-08-01

Full Text Available Abstract Background Time series gene expression data analysis is used widely to study the dynamics of various cell processes. Most of the time series data available today consist of few time points only, thus making the application of standard clustering techniques difficult. Results We developed two new algorithms that are capable of extracting biological patterns from short time point series gene expression data. The two algorithms, ASTRO and MiMeSR, are inspired by the rank order preserving framework and the minimum mean squared residue approach, respectively. However, ASTRO and MiMeSR differ from previous approaches in that they take advantage of the relatively few number of time points in order to reduce the problem from NP-hard to linear. Tested on well-defined short time expression data, we found that our approaches are robust to noise, as well as to random patterns, and that they can correctly detect the temporal expression profile of relevant functional categories. Evaluation of our methods was performed using Gene Ontology (GO annotations and chromatin immunoprecipitation (ChIP-chip data. Conclusion Our approaches generally outperform both standard clustering algorithms and algorithms designed specifically for clustering of short time series gene expression data. Both algorithms are available at http://www.benoslab.pitt.edu/astro/.

Haloperidol induces pharmacoepigenetic response by modulating miRNA expression, global DNA methylation and expression profiles of methylation maintenance genes and genes involved in neurotransmission in neuronal cells.

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Swathy, Babu; Banerjee, Moinak

2017-01-01

were observed to be upregulated while CHRM2 gene expression was down regulated. Haloperidol can influence methylation traits thereby inducing a pharmacoepigenomic response, which seems to be regulated by DNMTs and their putative miRNA expression. Increased methylation seems to influence CHRM2 gene expression while microRNA could influence neurotransmission, pharmacogene expression and methylation events. Altered expression of various therapeutically relevant genes and miRNA expression, could account for their role in therapeutic response or side effects.

Haloperidol induces pharmacoepigenetic response by modulating miRNA expression, global DNA methylation and expression profiles of methylation maintenance genes and genes involved in neurotransmission in neuronal cells.

Directory of Open Access Journals (Sweden)

Babu Swathy

neurotransmission were observed to be upregulated while CHRM2 gene expression was down regulated.Haloperidol can influence methylation traits thereby inducing a pharmacoepigenomic response, which seems to be regulated by DNMTs and their putative miRNA expression. Increased methylation seems to influence CHRM2 gene expression while microRNA could influence neurotransmission, pharmacogene expression and methylation events. Altered expression of various therapeutically relevant genes and miRNA expression, could account for their role in therapeutic response or side effects.

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

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

2008-01-01

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

cis sequence effects on gene expression

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Jacobs Kevin

2007-08-01

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

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

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Paules Richard S

2007-11-01

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

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

Use of keyword hierarchies to interpret gene expression patterns.

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Masys, D R; Welsh, J B; Lynn Fink, J; Gribskov, M; Klacansky, I; Corbeil, J

2001-04-01

High-density microarray technology permits the quantitative and simultaneous monitoring of thousands of genes. The interpretation challenge is to extract relevant information from this large amount of data. A growing variety of statistical analysis approaches are available to identify clusters of genes that share common expression characteristics, but provide no information regarding the biological similarities of genes within clusters. The published literature provides a potential source of information to assist in interpretation of clustering results. We describe a data mining method that uses indexing terms ('keywords') from the published literature linked to specific genes to present a view of the conceptual similarity of genes within a cluster or group of interest. The method takes advantage of the hierarchical nature of Medical Subject Headings used to index citations in the MEDLINE database, and the registry numbers applied to enzymes.

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...

Microenvironment alters epigenetic and gene expression profiles in Swarm rat chondrosarcoma tumors

International Nuclear Information System (INIS)

Hamm, Christopher A; Wang, Deli; Malchenko, Sergey; Fatima Bonaldo, Maria de; Casavant, Thomas L; Hendrix, Mary JC; Soares, Marcelo B; Stevens, Jeff W; Xie, Hehuang; Vanin, Elio F; Morcuende, Jose A; Abdulkawy, Hakeem; Seftor, Elisabeth A; Sredni, Simone T; Bischof, Jared M

2010-01-01

Chondrosarcomas are malignant cartilage tumors that do not respond to traditional chemotherapy or radiation. The 5-year survival rate of histologic grade III chondrosarcoma is less than 30%. An animal model of chondrosarcoma has been established - namely, the Swarm Rat Chondrosarcoma (SRC) - and shown to resemble the human disease. Previous studies with this model revealed that tumor microenvironment could significantly influence chondrosarcoma malignancy. To examine the effect of the microenvironment, SRC tumors were initiated at different transplantation sites. Pyrosequencing assays were utilized to assess the DNA methylation of the tumors, and SAGE libraries were constructed and sequenced to determine the gene expression profiles of the tumors. Based on the gene expression analysis, subsequent functional assays were designed to determine the relevancy of the specific genes in the development and progression of the SRC. The site of transplantation had a significant impact on the epigenetic and gene expression profiles of SRC tumors. Our analyses revealed that SRC tumors were hypomethylated compared to control tissue, and that tumors at each transplantation site had a unique expression profile. Subsequent functional analysis of differentially expressed genes, albeit preliminary, provided some insight into the role that thymosin-β4, c-fos, and CTGF may play in chondrosarcoma development and progression. This report describes the first global molecular characterization of the SRC model, and it demonstrates that the tumor microenvironment can induce epigenetic alterations and changes in gene expression in the SRC tumors. We documented changes in gene expression that accompany changes in tumor phenotype, and these gene expression changes provide insight into the pathways that may play a role in the development and progression of chondrosarcoma. Furthermore, specific functional analysis indicates that thymosin-β4 may have a role in chondrosarcoma metastasis

Microenvironment alters epigenetic and gene expression profiles in Swarm rat chondrosarcoma tumors

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Hamm Christopher A

2010-09-01

Full Text Available Abstract Background Chondrosarcomas are malignant cartilage tumors that do not respond to traditional chemotherapy or radiation. The 5-year survival rate of histologic grade III chondrosarcoma is less than 30%. An animal model of chondrosarcoma has been established - namely, the Swarm Rat Chondrosarcoma (SRC - and shown to resemble the human disease. Previous studies with this model revealed that tumor microenvironment could significantly influence chondrosarcoma malignancy. Methods To examine the effect of the microenvironment, SRC tumors were initiated at different transplantation sites. Pyrosequencing assays were utilized to assess the DNA methylation of the tumors, and SAGE libraries were constructed and sequenced to determine the gene expression profiles of the tumors. Based on the gene expression analysis, subsequent functional assays were designed to determine the relevancy of the specific genes in the development and progression of the SRC. Results The site of transplantation had a significant impact on the epigenetic and gene expression profiles of SRC tumors. Our analyses revealed that SRC tumors were hypomethylated compared to control tissue, and that tumors at each transplantation site had a unique expression profile. Subsequent functional analysis of differentially expressed genes, albeit preliminary, provided some insight into the role that thymosin-β4, c-fos, and CTGF may play in chondrosarcoma development and progression. Conclusion This report describes the first global molecular characterization of the SRC model, and it demonstrates that the tumor microenvironment can induce epigenetic alterations and changes in gene expression in the SRC tumors. We documented changes in gene expression that accompany changes in tumor phenotype, and these gene expression changes provide insight into the pathways that may play a role in the development and progression of chondrosarcoma. Furthermore, specific functional analysis indicates that

Elucidating gene function and function evolution through comparison of co-expression networks in plants

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Marek eMutwil

2014-08-01

Full Text Available The analysis of gene expression data has shown that transcriptionally coordinated (co-expressed genes are often functionally related, enabling scientists to use expression data in gene function prediction. This Focused Review discusses our original paper (Large-scale co-expression approach to dissect secondary cell wall formation across plant species, Frontiers in Plant Science 2:23. In this paper we applied cross-species analysis to co-expression networks of genes involved in cellulose biosynthesis. We show that the co-expression networks from different species are highly similar, indicating that whole biological pathways are conserved across species. This finding has two important implications. First, the analysis can transfer gene function annotation from well-studied plants, such as Arabidopsis, to other, uncharacterized plant species. As the analysis finds genes that have similar sequence and similar expression pattern across different organisms, functionally equivalent genes can be identified. Second, since co-expression analyses are often noisy, a comparative analysis should have higher performance, as parts of co-expression networks that are conserved are more likely to be functionally relevant. In this Focused Review, we outline the comparative analysis done in the original paper and comment on the recent advances and approaches that allow comparative analyses of co-function networks. We hypothesize that, in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions. Finally, by combining comparative analysis with genomic information of green plants, we propose a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution.

Genome-Wide Identification of Genes Probably Relevant to the Uniqueness of Tea Plant (Camellia sinensis and Its Cultivars

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Yan Wei

2015-01-01

Full Text Available Tea (Camellia sinensis is a popular beverage all over the world and a number of studies have focused on the genetic uniqueness of tea and its cultivars. However, molecular mechanisms underlying these phenomena are largely undefined. In this report, based on expression data available from public databases, we performed a series of analyses to identify genes probably relevant to the uniqueness of C. sinensis and two of its cultivars (LJ43 and ZH2. Evolutionary analyses showed that the evolutionary rates of genes involved in the pathways were not significantly different among C. sinensis, C. oleifera, and C. azalea. Interestingly, a number of gene families, including genes involved in the pathways synthesizing iconic secondary metabolites of tea plant, were significantly upregulated, expressed in C. sinensis (LJ43 when compared to C. azalea, and this may partially explain its higher content of flavonoid, theanine, and caffeine. Further investigation showed that nonsynonymous mutations may partially contribute to the differences between the two cultivars of C. sinensis, such as the chlorina and higher contents of amino acids in ZH2. Genes identified as candidates are probably relevant to the uniqueness of C. sinensis and its cultivars should be good candidates for subsequent functional analyses and marker-assisted breeding.

Using gene expression noise to understand gene regulation

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

2012-01-01

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

ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data.

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Daniel L Roden

Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.

Gene expression profiles in Parkinson disease prefrontal cortex implicate FOXO1 and genes under its transcriptional regulation.

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Alexandra Dumitriu

2012-06-01

Full Text Available Parkinson disease (PD is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9 of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1 transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR-significant group of genes (177 genes covered by 189 probes, suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs selected from a recent meta-analysis of PD genome-wide association studies (GWAS were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression-SNP (eSNP analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK gene and a probe in the spermine oxidase (SMOX gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD-relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms.

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

DEFF Research Database (Denmark)

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

2010-01-01

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

Regulation of eucaryotic gene expression

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Brent, R.; Ptashne, M.S

1989-05-23

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

Developmental programming: gestational bisphenol-A treatment alters trajectory of fetal ovarian gene expression.

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Veiga-Lopez, Almudena; Luense, Lacey J; Christenson, Lane K; Padmanabhan, Vasantha

2013-05-01

Bisphenol-A (BPA), a ubiquitous environmental endocrine disrupting chemical, is a component of polycarbonate plastic and epoxy resins. Because of its estrogenic properties, there is increasing concern relative to risks from exposures during critical periods of early organ differentiation. Prenatal BPA treatment in sheep results in low birth weight, hypergonadotropism, and ovarian cycle disruptions. This study tested the hypothesis that gestational exposure to bisphenol A, at an environmentally relevant dose, induces early perturbations in the ovarian transcriptome (mRNA and microRNA). Pregnant Suffolk ewes were treated with bisphenol A (0.5 mg/kg, sc, daily, produced ∼2.6 ng/mL of unconjugated BPA in umbilical arterial samples of BPA treated fetuses approaching median levels of BPA measured in maternal circulation) from days 30 to 90 of gestation. Expression of steroidogenic enzymes, steroid/gonadotropin receptors, key ovarian regulators, and microRNA biogenesis components were measured by RT-PCR using RNA derived from fetal ovaries collected on gestational days 65 and 90. An age-dependent effect was evident in most steroidogenic enzymes, steroid receptors, and key ovarian regulators. Prenatal BPA increased Cyp19 and 5α-reductase expression in day 65, but not day 90, ovaries. Fetal ovarian microRNA expression was altered by prenatal BPA with 45 down-regulated (>1.5-fold) at day 65 and 11 down-regulated at day 90 of gestation. These included microRNAs targeting Sry-related high-mobility-group box (SOX) family genes, kit ligand, and insulin-related genes. The results of this study demonstrate that exposure to BPA at an environmentally relevant dose alters fetal ovarian steroidogenic gene and microRNA expression of relevance to gonadal differentiation, folliculogenesis, and insulin homeostasis.

Finding biological process modifications in cancer tissues by mining gene expression correlations

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Storari Sergio

2006-01-01

Full Text Available Abstract Background Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This technology yields a global view of gene expression that can be used in several ways. Functional insight into expression profiles is routinely obtained by using Gene Ontology terms associated to the cellular genes. In this paper, we deal with functional data mining from expression profiles, proposing a novel approach that studies the correlations between genes and their relations to Gene Ontology (GO. By using this "functional correlations comparison" we explore all possible pairs of genes identifying the affected biological processes by analyzing in a pair-wise manner gene expression patterns and linking correlated pairs with Gene Ontology terms. Results We apply here this "functional correlations comparison" approach to identify the existing correlations in hepatocarcinoma (161 microarray experiments and to reveal functional differences between normal liver and cancer tissues. The number of well-correlated pairs in each GO term highlights several differences in genetic interactions between cancer and normal tissues. We performed a bootstrap analysis in order to compute false detection rates (FDR and confidence limits. Conclusion Experimental results show the main advantage of the applied method: it both picks up general and specific GO terms (in particular it shows a fine resolution in the specific GO terms. The results obtained by this novel method are highly coherent with the ones proposed by other cancer biology studies. But additionally they highlight the most specific and interesting GO terms helping the biologist to focus his/her studies on the most relevant biological processes.

Clinically Relevant Subsets Identified by Gene Expression Patterns Support a Revised Ontogenic Model of Wilms Tumor: A Children's Oncology Group Study

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Samantha Gadd

2012-08-01

Full Text Available Wilms tumors (WT have provided broad insights into the interface between development and tumorigenesis. Further understanding is confounded by their genetic, histologic, and clinical heterogeneity, the basis of which remains largely unknown. We evaluated 224 WT for global gene expression patterns; WT1, CTNNB1, and WTX mutation; and 11p15 copy number and methylation patterns. Five subsets were identified showing distinct differences in their pathologic and clinical features: these findings were validated in 100 additional WT. The gene expression pattern of each subset was compared with published gene expression profiles during normal renal development. A novel subset of epithelial WT in infants lacked WT1, CTNNB1, and WTX mutations and nephrogenic rests and displayed a gene expression pattern of the postinduction nephron, and none recurred. Three subsets were characterized by a low expression of WT1 and intralobar nephrogenic rests. These differed in their frequency of WT1 and CTNNB1 mutations, in their age, in their relapse rate, and in their expression similarities with the intermediate mesoderm versus the metanephric mesenchyme. The largest subset was characterized by biallelic methylation of the imprint control region 1, a gene expression profile of the metanephric mesenchyme, and both interlunar and perilobar nephrogenic rests. These data provide a biologic explanation for the clinical and pathologic heterogeneity seen within WT and enable the future development of subset-specific therapeutic strategies. Further, these data support a revision of the current model of WT ontogeny, which allows for an interplay between the type of initiating event and the developmental stage in which it occurs.

Differential gene expression and Hog1 interaction with osmoresponsive genes in the extremely halotolerant black yeast Hortaea werneckii

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Plemenitaš Ana

2007-08-01

Full Text Available Abstract Background Fluctuations in external salinity force eukaryotic cells to respond by changes in the gene expression of proteins acting in protective biochemical processes, thus counteracting the changing osmotic pressure. The high-osmolarity glycerol (HOG signaling pathway is essential for the efficient up-regulation of the osmoresponsive genes. In this study, the differential gene expression of the extremely halotolerant black yeast Hortaea werneckii was explored. Furthermore, the interaction of mitogen-activated protein kinase HwHog1 and RNA polymerase II with the chromatin in cells adapted to an extremely hypersaline environment was analyzed. Results A cDNA subtraction library was constructed for H. werneckii, adapted to moderate salinity or an extremely hypersaline environment of 4.5 M NaCl. An uncommon osmoresponsive set of 95 differentially expressed genes was identified. The majority of these had not previously been connected with the adaptation of salt-sensitive S. cerevisiae to hypersaline conditions. The transcriptional response in hypersaline-adapted and hypersaline-stressed cells showed that only a subset of the identified genes responded to acute salt-stress, whereas all were differentially expressed in adapted cells. Interaction with HwHog1 was shown for 36 of the 95 differentially expressed genes. The majority of the identified osmoresponsive and HwHog1-dependent genes in H. werneckii have not been previously reported as Hog1-dependent genes in the salt-sensitive S. cerevisiae. The study further demonstrated the co-occupancy of HwHog1 and RNA polymerase II on the chromatin of 17 up-regulated and 2 down-regulated genes in 4.5 M NaCl-adapted H. werneckii cells. Conclusion Extremely halotolerant H. werneckii represents a suitable and highly relevant organism to study cellular responses to environmental salinity. In comparison with the salt-sensitive S. cerevisiae, this yeast shows a different set of genes being expressed at

Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

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Klopfleisch, Robert; Lenze, Dido; Hummel, Michael; Gruber, Achim D

2010-01-01

Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs are in some aspects suitable as a

Global similarity and local divergence in human and mouse gene co-expression networks

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Koonin Eugene V

2006-09-01

Full Text Available Abstract Background A genome-wide comparative analysis of human and mouse gene expression patterns was performed in order to evaluate the evolutionary divergence of mammalian gene expression. Tissue-specific expression profiles were analyzed for 9,105 human-mouse orthologous gene pairs across 28 tissues. Expression profiles were resolved into species-specific coexpression networks, and the topological properties of the networks were compared between species. Results At the global level, the topological properties of the human and mouse gene coexpression networks are, essentially, identical. For instance, both networks have topologies with small-world and scale-free properties as well as closely similar average node degrees, clustering coefficients, and path lengths. However, the human and mouse coexpression networks are highly divergent at the local level: only a small fraction ( Conclusion The dissonance between global versus local network divergence suggests that the interspecies similarity of the global network properties is of limited biological significance, at best, and that the biologically relevant aspects of the architectures of gene coexpression are specific and particular, rather than universal. Nevertheless, there is substantial evolutionary conservation of the local network structure which is compatible with the notion that gene coexpression networks are subject to purifying selection.

Inferring gene expression dynamics via functional regression analysis

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Leng Xiaoyan

2008-01-01

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

Synthetic promoter libraries- tuning of gene expression

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

2006-01-01

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

Dualism of gene GC content and CpG pattern in regard to expression in the human genome: magnitude versus breadth.

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Vinogradov, Alexander E

2005-12-01

In this article, I show that, in the human genome, the GC content in genes (but not the CpG island in the promoter) is related to the maximum level of gene expression among tissues, whereas the promoter CpG island and gene CpG level are more strongly related to the breadth of expression among tissues. The relevance of gene GC content to expression cannot be a consequence (i.e. a byproduct) of transcription because it does not correlate with expression in the germline. The variation of GC content and CpG level can determine the characteristics of gene expression in a synergistic interplay with transcription-factor-binding sites (mediated by chromatin condensation).

“Zebrafishing” for Novel Genes Relevant to the Glomerular Filtration Barrier

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Nils Hanke

2013-01-01

Full Text Available Data for genes relevant to glomerular filtration barrier function or proteinuria is continually increasing in an era of microarrays, genome-wide association studies, and quantitative trait locus analysis. Researchers are limited by published literature searches to select the most relevant genes to investigate. High-throughput cell cultures and other in vitro systems ultimately need to demonstrate proof in an in vivo model. Generating mammalian models for the genes of interest is costly and time intensive, and yields only a small number of test subjects. These models also have many pitfalls such as possible embryonic mortality and failure to generate phenotypes or generate nonkidney specific phenotypes. Here we describe an in vivo zebrafish model as a simple vertebrate screening system to identify genes relevant to glomerular filtration barrier function. Using our technology, we are able to screen entirely novel genes in 4–6 weeks in hundreds of live test subjects at a fraction of the cost of a mammalian model. Our system produces consistent and reliable evidence for gene relevance in glomerular kidney disease; the results then provide merit for further analysis in mammalian models.

Adaptive Evolution of Gene Expression in Drosophila.

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

2017-08-08

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

Adaptive Evolution of Gene Expression in Drosophila

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Armita Nourmohammad

2017-08-01

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

Dynamic gene expression for metabolic engineering of mammalian cells in culture.

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Le, Huong; Vishwanathan, Nandita; Kantardjieff, Anne; Doo, Inseok; Srienc, Michael; Zheng, Xiaolu; Somia, Nikunj; Hu, Wei-Shou

2013-11-01

Recombinant mammalian cells are the major hosts for the production of protein therapeutics. In addition to high expression of the product gene, a hyper-producer must also harbor superior phenotypic traits related to metabolism, protein secretion, and growth control. Introduction of genes endowing the relevant hyper-productivity traits is a strategy frequently used to enhance the productivity. Most of such cell engineering efforts have been performed using constitutive expression systems. However, cells respond to various environmental cues and cellular events dynamically according to cellular needs. The use of inducible systems allows for time dependent expression, but requires external manipulation. Ideally, a transgene's expression should be synchronous to the host cell's own rhythm, and at levels appropriate for the objective. To that end, we identified genes with different expression dynamics and intensity ranges using pooled transcriptome data. Their promoters may be used to drive the expression of the transgenes following the desired dynamics. We isolated the promoter of the Thioredoxin-interacting protein (Txnip) gene and demonstrated its capability to drive transgene expression in concert with cell growth. We further employed this Chinese hamster promoter to engineer dynamic expression of the mouse GLUT5 fructose transporter in Chinese hamster ovary (CHO) cells, enabling them to utilize sugar according to cellular needs rather than in excess as typically seen in culture. Thus, less lactate was produced, resulting in a better growth rate, prolonged culture duration, and higher product titer. This approach illustrates a novel concept in metabolic engineering which can potentially be used to achieve dynamic control of cellular behaviors for enhanced process characteristics. © 2013 Published by Elsevier Inc.

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

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Karacali Bilge

2007-10-01

Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

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Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Chemotherapy modulates intestinal immune gene expression including surfactant Protein-D and deleted in malignant brain tumors 1 in piglets

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Rathe, Mathias; Thomassen, Mads; Shen, René L.

2016-01-01

Background: Information about chemotherapy-induced intestinal gene expression may provide insight into the mechanisms underlying gut toxicity and help identify biomarkers and targets for intervention. Methods: We analyzed jejunal tissue from piglets subjected to two different, clinically relevant...... the upregulated genes for both treatments. Conclusion: In the developing intestine, chemotherapy increases the expression of genes related to innate immune functions involved in surveillance, protection, and homeostasis of mucosal surfaces....

Classification between normal and tumor tissues based on the pair-wise gene expression ratio

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Yap, YeeLeng; Zhang, XueWu; Ling, MT; Wang, XiangHong; Wong, YC; Danchin, Antoine

2004-01-01

Precise classification of cancer types is critically important for early cancer diagnosis and treatment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. However, reliable cancer-related signals are generally lacking. Using recent datasets on colon and prostate cancer, a data transformation procedure from single gene expression to pair-wise gene expression ratio is proposed. Making use of the internal consistency of each expression profiling dataset this transformation improves the signal to noise ratio of the dataset and uncovers new relevant cancer-related signals (features). The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio). Classification results were compared to the original datasets for up to 10-feature model classifiers. 82 and 262 genes that have high correlation to tissue phenotype were selected from the colon and prostate datasets respectively. Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes. The transformed dataset exhibited lower CV when compared to that of single gene expression. In the colon cancer set, the minimum CV decreased from 45.3% to 16.5%. In prostate cancer, comparable CV was achieved with and without transformation. This improvement in CV, coupled with the improved correlation between the pair-wise gene expression ratio and tissue phenotypes, yielded higher classification efficiency, especially with the colon dataset – from 87.1% to 93.5%. Over 90% of the top ten discriminating axes in both datasets showed significant improvement after data transformation. The high classification efficiency achieved suggested

LPS challenge regulates gene expression and tissue localization of a Ciona intestinalis gene through an alternative polyadenylation mechanism.

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Aiti Vizzini

Full Text Available A subtractive hybridization strategy for the identification of differentially expressed genes was performed between LPS-challenged and naive Ciona intestinalis. This strategy allowed the characterization of two transcripts (Ci8short and Ci8long generated by the use of two Alternative Polyadenylation sites. The Ci8long transcript contains a protein domain with relevant homology to several components of the Receptor Transporting Protein (RTP family not present in the Ci8short mRNA. By means of Real Time PCR and Northern Blot, the Ci8short and Ci8long transcripts showed a different pattern of gene expression with the Ci8short mRNA being strongly activated after LPS injection in the pharynx. In situ hybridization analysis demonstrated that the activation of the APA site also influenced the tissue localization of the Ci8short transcript. This analysis showed that the Ci8long mRNA was expressed in hemocytes meanwhile the Ci8short mRNA was highly transcribed also in vessel endothelial cells and in the epithelium of pharynx. These findings demonstrated that regulation of gene expression based on different polyadenylation sites is an ancestral powerful strategy influencing both the level of expression and tissue distribution of alternative transcripts.

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

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Xu, Pingzhen

2018-01-01

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

Cytotoxicity and gene expression profiling of polyhexamethylene guanidine hydrochloride in human alveolar A549 cells.

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Jung, Ha-Na; Zerin, Tamanna; Podder, Biswajit; Song, Ho-Yeon; Kim, Yong-Sik

2014-06-01

In Korea, lung disease of children and pregnant women associated with humidifier disinfectant use has become a major concern. A common sterilizer is polyhexamethylene guanidine (PHMG), a member of the guanidine family of antiseptics. This study was done to elucidate the putative cytotoxic effect of PHMG and the PHMG-mediated altered gene expression in human alveolar epithelial A549 cells in vitro. Cell viability analyses revealed the potent cytotoxicity of PHMG, with cell death evident at as low as 5 μg/mL. Death was dose- and time-dependent, and was associated with formation of intracellular reactive oxygen species, and apoptosis significantly, at even 2 μg/mL concentration. The gene expression profile in A549 cells following 24 h exposure to 5 μg/mL of PHMG was investigated using DNA microarray analysis. Changes in gene expression relevant to the progression of cell death included induction of genes related to apoptosis, autophagy, fibrosis, and cell cycle. However, the expressions of genes encoding antioxidant and detoxifying enzymes were down-regulated or not affected. The altered expression of selected genes was confirmed by quantitative reverse transcription-polymerase chain reaction and Western blot analyses. The collective data suggest that PHMG confers cellular toxicity through the generation of intracellular reactive oxygen species and alteration of gene expression. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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Boris P Hejblum

2015-06-01

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

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

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Qi Bao

2012-01-01

terms. Nonetheless, those genes showing non-additive expression exhibited a significant enrichment for vesicle-function. Conclusions Our results show that two patterns of global alteration in gene expression are conditioned by allohexaploidization in wheat, that is, parental dominance expression and non-additive expression. Both altered patterns of gene expression but not the identity of the genes involved are likely to play functional roles in stabilization and establishment of the newly formed allohexaploid plants, and hence, relevant to speciation and evolution of T. aestivum.

Gene expression profiling gut microbiota in different races of humans

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Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong

2016-03-01

The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome.

A comparative analysis of biclustering algorithms for gene expression data

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Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V.

2013-01-01

The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837

Differential cytokine gene expression according to outcome in a hamster model of leptospirosis.

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Frédérique Vernel-Pauillac

Full Text Available BACKGROUND: Parameters predicting the evolution of leptospirosis would be useful for clinicians, as well as to better understand severe leptospirosis, but are scarce and rarely validated. Because severe leptospirosis includes septic shock, similarities with predictors evidenced for sepsis and septic shock were studied in a hamster model. METHODOLOGY/PRINCIPAL FINDINGS: Using an LD50 model of leptospirosis in hamsters, we first determined that 3 days post-infection was a time-point that allowed studying the regulation of immune gene expression and represented the onset of the clinical signs of the disease. In the absence of tools to assess serum concentrations of immune effectors in hamsters, we determined mRNA levels of various immune genes, especially cytokines, together with leptospiraemia at this particular time-point. We found differential expression of both pro- and anti-inflammatory mediators, with significantly higher expression levels of tumor necrosis factor alpha, interleukin 1alpha, cyclo-oxygenase 2 and interleukin 10 genes in nonsurvivors compared to survivors. Higher leptospiraemia was also observed in nonsurvivors. Lastly, we demonstrated the relevance of these results by comparing their respective expression levels using a LD100 model or an isogenic high-passage nonvirulent variant. CONCLUSIONS/SIGNIFICANCE: Up-regulated gene expression of both pro- and anti-inflammatory immune effectors in hamsters with fatal outcome in an LD50 model of leptospirosis, together with a higher Leptospira burden, suggest that these gene expression levels could be predictors of adverse outcome in leptospirosis.

Environmental history impacts gene expression during diapause development in the alfalfa leafcutting bee, Megachile rotundata.

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Yocum, George D; Childers, Anna K; Rinehart, Joseph P; Rajamohan, Arun; Pitts-Singer, Theresa L; Greenlee, Kendra J; Bowsher, Julia H

2018-05-10

Our understanding of the mechanisms controlling insect diapause has increased dramatically with the introduction of global gene expression techniques, such as RNA-seq. However, little attention has been given to how ecologically relevant field conditions may affect gene expression during diapause development because previous studies have focused on laboratory reared and maintained insects. To determine whether gene expression differs between laboratory and field conditions, prepupae of the alfalfa leafcutting bee, Megachile rotundata , entering diapause early or late in the growing season were collected. These two groups were further subdivided in early autumn into laboratory and field maintained groups, resulting in four experimental treatments of diapausing prepupae: early and late field, and early and late laboratory. RNA-seq and differential expression analyses were performed on bees from the four treatment groups in November, January, March and May. The number of treatment-specific differentially expressed genes (97 to 1249) outnumbered the number of differentially regulated genes common to all four treatments (14 to 229), indicating that exposure to laboratory or field conditions had a major impact on gene expression during diapause development. Principle component analysis and hierarchical cluster analysis yielded similar grouping of treatments, confirming that the treatments form distinct clusters. Our results support the conclusion that gene expression during the course of diapause development is not a simple ordered sequence, but rather a highly plastic response determined primarily by the environmental history of the individual insect. © 2018. Published by The Company of Biologists Ltd.

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

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Gutiérrez Rodrigo A

2008-09-01

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

The Schizophrenia-Associated BRD1 Gene Regulates Behavior, Neurotransmission, and Expression of Schizophrenia Risk Enriched Gene Sets in Mice.

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Qvist, Per; Christensen, Jane Hvarregaard; Vardya, Irina; Rajkumar, Anto Praveen; Mørk, Arne; Paternoster, Veerle; Füchtbauer, Ernst-Martin; Pallesen, Jonatan; Fryland, Tue; Dyrvig, Mads; Hauberg, Mads Engel; Lundsberg, Birgitte; Fejgin, Kim; Nyegaard, Mette; Jensen, Kimmo; Nyengaard, Jens Randel; Mors, Ole; Didriksen, Michael; Børglum, Anders Dupont

2017-07-01

The schizophrenia-associated BRD1 gene encodes a transcriptional regulator whose comprehensive chromatin interactome is enriched with schizophrenia risk genes. However, the biology underlying the disease association of BRD1 remains speculative. This study assessed the transcriptional drive of a schizophrenia-associated BRD1 risk variant in vitro. Accordingly, to examine the effects of reduced Brd1 expression, we generated a genetically modified Brd1 +/- mouse and subjected it to behavioral, electrophysiological, molecular, and integrative genomic analyses with focus on schizophrenia-relevant parameters. Brd1 +/- mice displayed cerebral histone H3K14 hypoacetylation and a broad range of behavioral changes with translational relevance to schizophrenia. These behaviors were accompanied by striatal dopamine/serotonin abnormalities and cortical excitation-inhibition imbalances involving loss of parvalbumin immunoreactive interneurons. RNA-sequencing analyses of cortical and striatal micropunches from Brd1 +/- and wild-type mice revealed differential expression of genes enriched for schizophrenia risk, including several schizophrenia genome-wide association study risk genes (e.g., calcium channel subunits [Cacna1c and Cacnb2], cholinergic muscarinic receptor 4 [Chrm4)], dopamine receptor D 2 [Drd2], and transcription factor 4 [Tcf4]). Integrative analyses further found differentially expressed genes to cluster in functional networks and canonical pathways associated with mental illness and molecular signaling processes (e.g., glutamatergic, monoaminergic, calcium, cyclic adenosine monophosphate [cAMP], dopamine- and cAMP-regulated neuronal phosphoprotein 32 kDa [DARPP-32], and cAMP responsive element binding protein signaling [CREB]). Our study bridges the gap between genetic association and pathogenic effects and yields novel insights into the unfolding molecular changes in the brain of a new schizophrenia model that incorporates genetic risk at three levels: allelic

Gene expression profiles in primary pancreatic tumors and metastatic lesions of Ela-c-myc transgenic mice

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Liao Dezhong J

2008-01-01

Full Text Available Abstract Background Pancreatic carcinoma usually is a fatal disease with no cure, mainly due to its invasion and metastasis prior to diagnosis. We analyzed the gene expression profiles of paired primary pancreatic tumors and metastatic lesions from Ela-c-myc transgenic mice in order to identify genes that may be involved in the pancreatic cancer progression. Differentially expressed selected genes were verified by semi-quantitative and quantitative RT-PCR. To further evaluate the relevance of some of the selected differentially expressed genes, we investigated their expression pattern in human pancreatic cancer cell lines with high and low metastatic potentials. Results Data indicate that genes involved in posttranscriptional regulation were a major functional category of upregulated genes in both primary pancreatic tumors (PT and liver metastatic lesions (LM compared to normal pancreas (NP. In particular, differential expression for splicing factors, RNA binding/pre-mRNA processing factors and spliceosome related genes were observed, indicating that RNA processing and editing related events may play critical roles in pancreatic tumor development and progression. High expression of insulin growth factor binding protein-1 (Igfbp1 and Serine proteinase inhibitor A1 (Serpina1, and low levels or absence of Wt1 gene expression were exclusive to liver metastatic lesion samples. Conclusion We identified Igfbp1, Serpina1 and Wt1 genes that are likely to be clinically useful biomarkers for prognostic or therapeutic purposes in metastatic pancreatic cancer, particularly in pancreatic cancer where c-Myc is overexpressed.

Gene expression profiles in primary pancreatic tumors and metastatic lesions of Ela-c-myc transgenic mice.

Science.gov (United States)

Thakur, Archana; Bollig, Aliccia; Wu, Jiusheng; Liao, Dezhong J

2008-01-24

Pancreatic carcinoma usually is a fatal disease with no cure, mainly due to its invasion and metastasis prior to diagnosis. We analyzed the gene expression profiles of paired primary pancreatic tumors and metastatic lesions from Ela-c-myc transgenic mice in order to identify genes that may be involved in the pancreatic cancer progression. Differentially expressed selected genes were verified by semi-quantitative and quantitative RT-PCR. To further evaluate the relevance of some of the selected differentially expressed genes, we investigated their expression pattern in human pancreatic cancer cell lines with high and low metastatic potentials. Data indicate that genes involved in posttranscriptional regulation were a major functional category of upregulated genes in both primary pancreatic tumors (PT) and liver metastatic lesions (LM) compared to normal pancreas (NP). In particular, differential expression for splicing factors, RNA binding/pre-mRNA processing factors and spliceosome related genes were observed, indicating that RNA processing and editing related events may play critical roles in pancreatic tumor development and progression. High expression of insulin growth factor binding protein-1 (Igfbp1) and Serine proteinase inhibitor A1 (Serpina1), and low levels or absence of Wt1 gene expression were exclusive to liver metastatic lesion samples. We identified Igfbp1, Serpina1 and Wt1 genes that are likely to be clinically useful biomarkers for prognostic or therapeutic purposes in metastatic pancreatic cancer, particularly in pancreatic cancer where c-Myc is overexpressed.

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.

Expression of Sox genes in tooth development.

Science.gov (United States)

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

2015-01-01

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

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

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

2016-12-05

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

Catecholamine-related gene expression in blood correlates with tic severity in tourette syndrome.

Science.gov (United States)

Gunther, Joan; Tian, Yingfang; Stamova, Boryana; Lit, Lisa; Corbett, Blythe; Ander, Brad; Zhan, Xinhua; Jickling, Glen; Bos-Veneman, Netty; Liu, Da; Hoekstra, Pieter; Sharp, Frank

2012-12-30

Tourette syndrome (TS) is a heritable disorder characterized by tics that are decreased in some patients by treatment with alpha adrenergic agonists and dopamine receptor blockers. Thus, this study examines the relationship between catecholamine gene expression in blood and tic severity. TS diagnosis was confirmed using Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria and tic severity measured using the Yale Global Tic Severity Scale (YGTSS) for 26 un-medicated subjects with TS. Whole blood was collected and Ribonucleic acid (RNA) processed on Affymetrix Human Exon 1.0 ST arrays. An Analysis of Covariance (ANCOVA) identified 3627 genes correlated with tic severity (pdisorders, Attention Deficit Hyperactivity Disorder (ADHD), and Obsessive-Compulsive Disorder (OCD). Correlation of gene expression in peripheral blood with tic severity may allow inferences about catecholamine pathway dysfunction in TS subjects. Findings built on previous work suggest that at least some genes expressed peripherally are relevant for central nervous system (CNS) pathology in the brain of individuals with TS. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Profiling Gene Expression in Germinating Brassica Roots.

Science.gov (United States)

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

2014-01-01

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

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

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Lucie Kosinová

Full Text Available The use of RT-qPCR provides a powerful tool for gene expression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of gene expression. Despite of this, freshly isolated islets frequently serve as a control in various gene expression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3 in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for gene expression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for gene expression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information

Complex nature of SNP genotype effects on gene expression in primary human leucocytes

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Dinesen Lotte C

2009-01-01

Full Text Available Abstract Background Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown. Methods We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110 from individuals with celiac disease – a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90, and performed a meta-analysis to increase power to detect non-tissue specific effects. Results In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (cis expression quantitative trait loci, eQTLs. 135 of the detected SNP-probe effects (reflecting 51 unique probes were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed cis-eQTLs. Celiac associated risk variants from two regions, containing genes IL18RAP and CCR3, showed significant cis genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected. Conclusion In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.

Characterizing bacterial gene expression in nitrogen cycle metabolism with RT-qPCR.

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Graham, James E; Wantland, Nicholas B; Campbell, Mark; Klotz, Martin G

2011-01-01

Recent advances in DNA sequencing have greatly accelerated our ability to obtain the raw information needed to recognize both known and potential novel modular microbial genomic capacity for nitrogen metabolism. With PCR-based approaches to quantifying microbial mRNA expression now mainstream in most laboratories, researchers can now more efficiently propose and test hypotheses on the contributions of individual microbes to the biological accessibility of nitrogen upon which all other life depends. We review known microbial roles in these key nitrogen transformations, and describe the necessary steps in carrying out relevant gene expression studies. An example experimental design is then provided characterizing Nitrosococcus oceani mRNA expression in cultures responding to ammonia. The approach described, that of assessing microbial genome inventory and testing putative modular gene expression by mRNA quantification, is likely to remain an important tool in understanding individual microbial contributions within microbial community activities that maintain the Earth's nitrogen balance. Copyright © 2011 Elsevier Inc. All rights reserved.

Melatonin improves the quality of in vitro produced (IVP bovine embryos: implications for blastocyst development, cryotolerance, and modifications of relevant gene expression.

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Feng Wang

Full Text Available To evaluate the potential effects of melatonin on the kinetics of embryo development and quality of blastocyst during the process of in vitro bovine embryo culture. Bovine cumulus-oocyte complexes (COCs were fertilized after in vitro maturation. The presumed zygotes were cultured in in vitro culture medium supplemented with or without 10(-7 M melatonin. The cleavage rate, 8-cell rate and blastocyst rate were examined to identify the kinetics of embryo development. The hatched blastocyst rate, mortality rate after thawing and the relevant transcript abundance were measured to evaluate the quality of blastocyst. The results showed that melatonin significantly promoted the cleavage rate and 8-cell embryo yield of in vitro produced bovine embryo. In addition, significantly more blastocysts were observed by Day 7 of embryo culture at the presence of melatonin. These results indicated that melatonin accelerated the development of in vitro produced bovine embryos. Following vitrification at Day 7 of embryo culture, melatonin (10(-7 M significantly increased the hatched blastocyst rate from 24 h to 72 h and decreased the mortality rate from 48 h to 72 h after thawing. The presence of melatonin during the embryo culture resulted in a significant increase in the gene expressions of DNMT3A, OCC, CDH1 and decrease in that of AQP3 after thawing. In conclusion, melatonin not only promoted blastocyst yield and accelerated in vitro bovine embryo development, but also improved the quality of blastocysts which was indexed by an elevated cryotolerance and the up-regulated expressions of developmentally important genes.

Comprehensive analysis of gene expression patterns of hedgehog-related genes

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Baillie David

2006-10-01

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

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

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Hala Alshamlan

2015-01-01

Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

Science.gov (United States)

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

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

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

2018-04-16

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

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

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

2012-05-01

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

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy; Bachkirova, Elena; Rey, Michael

2013-10-01

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

Epigenetic editing using programmable zinc ginger proteins : inherited silencing of endogenous gene expression by targeted DNA methylation

NARCIS (Netherlands)

Stolzenburg, Sabine

2014-01-01

Cancer development is not only the result of genetic mutations but also stems from modifications in the epigenetic code leading to an aberrant expression of genes relevant for cancer. The most studied epigenetic mark is DNA methylation of cytosines in the promoters of genes, which is associated with

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...

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

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Park Hong-Seog

2006-06-01

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

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

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Evi Berchtold

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

Genetic components for radiosensitivity. Gene expression in radiosensitive monocygotic twins. Final report

International Nuclear Information System (INIS)

Dikomey, Ekkehard

2012-01-01

The underlying hypothesis of this project was that the variation of individual radiosensitivity is determined by the different expression of single gens. This concept was tested using 60 monozygotic twin pairs, followed by an evaluation with 80 prostate cancer patients. Radiosensitivity was assessed for both G0- as well as G2-phase using chromosomal assays. G0- radiosensitivity is determined by lethal chromosomal aberrations and reflects the individual amount of cell killing, while G2-sensitivity is determined by chromatid breaks and is taken as an indicator of individual cancer risk. For both populations, G0- and G2-radiosensitivity are characterized by substantial variation with a CV of 11 and 14% or 27 and 21%, respectively. While the mean G0-sensitivity is the same for both populations, there is a slight difference for G2. The slightly higher value of G2-sensitivity found for prostate cancer patients might result from the higher age of this group. For both populations gene expression profiles were determined using the Affymetrix chip HG-U133+2.0. Overall gene expression was characterized by a huge variation covering more than four decades. However, for single genes, expression showed little variation with CV generally ranging only between 2 and 8%. Analysis of data using several different methods revealed that variation of both G0- as well as G2-radiosensitivity cannot be ascribed to the different expression of single genes. For twins, random forests can be used to identify 8 to 10 genes than are relevant either for G0- or G2-radiosensitivity. However, these genes cannot be confirmed by an evaluation with 80 prostate cancer patients. This finding clearly demonstrates that the hypothesis, due to which variation of individual radiosensitivity is caused by different expression of single genes, has to be rejected. It appears more likely that this parameter is determined by complex interactions of several genes in functional networks. (orig.)

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

KAUST Repository

Horiuchi, Youko

2015-12-23

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

Social Regulation of Gene Expression in Threespine Sticklebacks.

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Anna K Greenwood

Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

Functional imaging: monitoring heme oxygenase-1 gene expression in vivo

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Zhang, Weisheng; Reilly-Contag, Pamela; Stevenson, David K.; Contag, Christopher H.

1999-07-01

The regulation of genetic elements can be monitored in living animals using photoproteins as reporters. Heme oxygenase (HO) is the key catabolic enzyme in the heme degradation pathway. Here, HO expression serves as a model for in vivo functional imaging of transcriptional regulation of a clinically relevant gene. HO enzymatic activity is inhibited by heme analogs, metalloporphyrins, but many members of this family of compounds also activate transcription of the HO-1 promoter. The degree of transcriptional activation by twelve metalloporphyrins, differing at the central metal and porphyrin ring substituents, was evaluated in both NIH 3T3 stable lines and transgenic animals containing HO-1 promoter-luciferase gene fusions. In the correlative cell culture assays, the metalloporphyrins increased transcription form the full length HO promoter fusion to varying degrees, but none increased transcription from a truncated HO-1 promoter. These results suggested that one or both of the two distal enhancer elements located at -4 and -10 Kb upstream from transcriptional start are required for HO-1 induction by heme and its analogs. The full-length HO-1-luc fusion was then evaluated as a transgene in mice. It was possible to monitor the effects of the metalloporphyrins, SnMP and ZnPP, in living animals over time. This spatiotemporal analyses of gene expression in vivo implied that alterations in porphyrin ring substituents and the central metal may affect the extent of gene activation. These data further indicate that using photoprotein reporters, subtle differences in gene expression can be monitored in living animals.

Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

International Nuclear Information System (INIS)

Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

2008-01-01

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

A constructive approach to gene expression dynamics

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

2004-01-01

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

Stably Expressed Genes Involved in Basic Cellular Functions.

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Kejian Wang

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

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

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

1989-01-01

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

Genome-Wide Identification of the Alba Gene Family in Plants and Stress-Responsive Expression of the Rice Alba Genes.

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Verma, Jitendra Kumar; Wardhan, Vijay; Singh, Deepali; Chakraborty, Subhra; Chakraborty, Niranjan

2018-03-28

Architectural proteins play key roles in genome construction and regulate the expression of many genes, albeit the modulation of genome plasticity by these proteins is largely unknown. A critical screening of the architectural proteins in five crop species, viz., Oryza sativa , Zea mays , Sorghum bicolor , Cicer arietinum , and Vitis vinifera , and in the model plant Arabidopsis thaliana along with evolutionary relevant species such as Chlamydomonas reinhardtii , Physcomitrella patens , and Amborella trichopoda , revealed 9, 20, 10, 7, 7, 6, 1, 4, and 4 Alba (acetylation lowers binding affinity) genes, respectively. A phylogenetic analysis of the genes and of their counterparts in other plant species indicated evolutionary conservation and diversification. In each group, the structural components of the genes and motifs showed significant conservation. The chromosomal location of the Alba genes of rice ( OsAlba ), showed an unequal distribution on 8 of its 12 chromosomes. The expression profiles of the OsAlba genes indicated a distinct tissue-specific expression in the seedling, vegetative, and reproductive stages. The quantitative real-time PCR (qRT-PCR) analysis of the OsAlba genes confirmed their stress-inducible expression under multivariate environmental conditions and phytohormone treatments. The evaluation of the regulatory elements in 68 Alba genes from the 9 species studied led to the identification of conserved motifs and overlapping microRNA (miRNA) target sites, suggesting the conservation of their function in related proteins and a divergence in their biological roles across species. The 3D structure and the prediction of putative ligands and their binding sites for OsAlba proteins offered a key insight into the structure-function relationship. These results provide a comprehensive overview of the subtle genetic diversification of the OsAlba genes, which will help in elucidating their functional role in plants.

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

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Hu Xiaohua

2011-07-01

Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

Standardized Cannabis sativa extract attenuates tau and stathmin gene expression in the melanoma cell line.

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Vaseghi, Golnaz; Taki, Mohamad Javad; Javanmard, Shaghayegh Haghjooy

2017-10-01

Metastasis is the main cause of death in patients with melanoma. Cannabis-based medicines are effective adjunctive drugs in cancer patients. Tau and Stathmin proteins are the key proteins in cancer metastasis. Here we have investigated the effect of a standardized Cannabis sativa extract on cell migration and Tau and Stathmin gene expression in the melanoma cell line. In the treatment group, melanoma (B1617) was treated 48 hr with various concentrations of standardized C. sativa extract. Cells with no treatment were considered as the control group, then study was followed by Quantitative RT-Real Time PCR assay. Relative gene expression was calculated by the ΔΔct method. Migration assay was used to evaluate cancer metastasis. Tau and stathmin gene expression was significantly decreased compared to the control group. Cell migration was also significantly reduced compared to controls. C. sativa decreased tau and stathmin gene expression and cancer metastasis. The results may have some clinical relevance for the use of cannabis-based medicines in patients with metastatic melanoma.

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

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Castro Rosa MRPS

2009-05-01

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

Gene Expression Differences in Peripheral Blood of Parkinson's Disease Patients with Distinct Progression Profiles.

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Raquel Pinho

Full Text Available The prognosis of neurodegenerative disorders is clinically challenging due to the inexistence of established biomarkers for predicting disease progression. Here, we performed an exploratory cross-sectional, case-control study aimed at determining whether gene expression differences in peripheral blood may be used as a signature of Parkinson's disease (PD progression, thereby shedding light into potential molecular mechanisms underlying disease development. We compared transcriptional profiles in the blood from 34 PD patients who developed postural instability within ten years with those of 33 patients who did not develop postural instability within this time frame. Our study identified >200 differentially expressed genes between the two groups. The expression of several of the genes identified was previously found deregulated in animal models of PD and in PD patients. Relevant genes were selected for validation by real-time PCR in a subset of patients. The genes validated were linked to nucleic acid metabolism, mitochondria, immune response and intracellular-transport. Interestingly, we also found deregulation of these genes in a dopaminergic cell model of PD, a simple paradigm that can now be used to further dissect the role of these molecular players on dopaminergic cell loss. Altogether, our study provides preliminary evidence that expression changes in specific groups of genes and pathways, detected in peripheral blood samples, may be correlated with differential PD progression. Our exploratory study suggests that peripheral gene expression profiling may prove valuable for assisting in prediction of PD prognosis, and identifies novel culprits possibly involved in dopaminergic cell death. Given the exploratory nature of our study, further investigations using independent, well-characterized cohorts will be essential in order to validate our candidates as predictors of PD prognosis and to definitively confirm the value of gene expression

Replication error deficient and proficient colorectal cancer gene expression differences caused by 3'UTR polyT sequence deletions

DEFF Research Database (Denmark)

Wilding, Jennifer L; McGowan, Simon; Liu, Ying

2010-01-01

, and have distinct pathologies. Regulatory sequences controlling all aspects of mRNA processing, especially including message stability, are found in the 3'UTR sequence of most genes. The relevant sequences are typically A/U-rich elements or U repeats. Microarray analysis of 14 RER+ (deficient) and 16 RER......- (proficient) colorectal cancer cell lines confirms a striking difference in expression profiles. Analysis of the incidence of mononucleotide repeat sequences in the 3'UTRs, 5'UTRs, and coding sequences of those genes most differentially expressed in RER+ versus RER- cell lines has shown that much...... of this differential expression can be explained by the occurrence of a massive enrichment of genes with 3'UTR T repeats longer than 11 base pairs in the most differentially expressed genes. This enrichment was confirmed by analysis of two published consensus sets of RER differentially expressed probesets for a large...

Stochastic gene expression in Arabidopsis thaliana.

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

2017-12-14

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

Deriving Trading Rules Using Gene Expression Programming

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Adrian VISOIU

2011-01-01

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

Using PCR to Target Misconceptions about Gene Expression

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Leslie K. Wright

2013-02-01

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

Differential gene expression during Trypanosoma cruzi metacyclogenesis

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Marco Aurelio Krieger

1999-09-01

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

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

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Hackett Perry B

2006-06-01

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

Analysis of multiplex gene expression maps obtained by voxelation

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Smith Desmond J

2009-04-01

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

Analysis of multiplex gene expression maps obtained by voxelation.

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

2009-04-29

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

A comparative gene expression database for invertebrates

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Ormestad Mattias

2011-08-01

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

Genetic Variants Contribute to Gene Expression Variability in Humans

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Hulse, Amanda M.; Cai, James J.

2013-01-01

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

Correction of gene expression data

DEFF Research Database (Denmark)

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

2014-01-01

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

Gene expression in colorectal cancer

DEFF Research Database (Denmark)

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

2002-01-01

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

Gene and protein expression following exposure to radiofrequency fields from mobile phones.

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Vanderstraeten, Jacques; Verschaeve, Luc

2008-09-01

Since 1999, several articles have been published on genome-wide and/or proteome-wide response after exposure to radiofrequency (RF) fields whose signal and intensities were similar to or typical of those of currently used mobile telephones. These studies were performed using powerful high-throughput screening techniques (HTSTs) of transcriptomics and/or proteomics, which allow for the simultaneous screening of the expression of thousands of genes or proteins. We reviewed these HTST-based studies and compared the results with currently accepted concepts about the effects of RF fields on gene expression. In this article we also discuss these last in light of the recent concept of microwave-assisted chemistry. To date, the results of HTST-based studies of transcriptomics and/or proteomics after exposure to RF fields relevant to human exposure are still inconclusive, as most of the positive reports are flawed by methodologic imperfections or shortcomings. In addition, when positive findings were reported, no precise response pattern could be identified in a reproducible way. In particular, results from HTST studies tend to exclude the role of a cell stressor for exposure to RF fields at nonthermal intensities. However, on the basis of lessons from microwave-assisted chemistry, we can assume that RF fields might affect heat-sensitive gene or protein expression to an extent larger than would be predicted from temperature change only. But in all likelihood, this would concern intensities higher than those relevant to usual human exposure. The precise role of transcriptomics and proteomics in the screening of bioeffects from exposure to RF fields from mobile phones is still uncertain in view of the lack of positively identified phenotypic change and the lack of theoretical, as well as experimental, arguments for specific gene and/or protein response patterns after this kind of exposure.

Comparison of global brain gene expression profiles between inbred long-sleep and inbred short-sleep mice by high-density gene array hybridization.

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Xu, Y; Ehringer, M; Yang, F; Sikela, J M

2001-06-01

Inbred long-sleep (ILS) and short-sleep (ISS) mice show significant central nervous system-mediated differences in sleep time for sedative dose of ethanol and are frequently used as a rodent model for ethanol sensitivity. In this study, we have used complementary DNA (cDNA) array hybridization methodology to identify genes that are differentially expressed between the brains of ILS and ISS mice. To carry out this analysis, we used both the gene discovery array (GDA) and the Mouse GEM 1 Microarray. GDA consists of 18,378 nonredundant mouse cDNA clones on a single nylon filter. Complex probes were prepared from total brain mRNA of ILS or ISS mice by using reverse transcription and 33P labeling. The labeled probes were hybridized in parallel to the gene array filters. Data from GDA experiments were analyzed with SQL-Plus and Oracle 8. The GEM microarray includes 8,730 sequence-verified clones on a glass chip. Two fluorescently labeled probes were used to hybridize a microarray simultaneously. Data from GEM experiments were analyzed by using the GEMTools software package (Incyte). Differentially expressed genes identified from each method were confirmed by relative quantitative reverse transcription-polymerase chain reaction (RT-PCR). A total of 41 genes or expressed sequence tags (ESTs) display significant expression level differences between brains of ILS and ISS mice after GDA, GEM1 hybridization, and quantitative RT-PCR confirmation. Among them, 18 clones were expressed higher in ILS mice, and 23 clones were expressed higher in ISS mice. The individual gene or EST's function and mapping information have been analyzed. This study identified 41 genes that are differentially expressed between brains of ILS and ISS mice. Some of them may have biological relevance in mediation of phenotypic variation between ILS and ISS mice for ethanol sensitivity. This study also demonstrates that parallel gene expression comparison with high-density cDNA arrays is a rapid and

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

Science.gov (United States)

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

2014-08-01

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

Vascular Gene Expression: A Hypothesis

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Angélica Concepción eMartínez-Navarro

2013-07-01

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

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

Science.gov (United States)

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

2018-01-01

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

The evolution of gene expression in primates

OpenAIRE

Tashakkori Ghanbarian, Avazeh

2015-01-01

The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes in extant taxa. Indeed, in all eukaryotic genomes, genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their e...

IGF-1 modulates gene expression of proteins involved in inflammation, cytoskeleton, and liver architecture.

Science.gov (United States)

Lara-Diaz, V J; Castilla-Cortazar, I; Martín-Estal, I; García-Magariño, M; Aguirre, G A; Puche, J E; de la Garza, R G; Morales, L A; Muñoz, U

2017-05-01

Even though the liver synthesizes most of circulating IGF-1, it lacks its receptor under physiological conditions. However, according to previous studies, a damaged liver expresses the receptor. For this reason, herein, we examine hepatic histology and expression of genes encoding proteins of the cytoskeleton, extracellular matrix, and cell-cell molecules and inflammation-related proteins. A partial IGF-1 deficiency murine model was used to investigate IGF-1's effects on liver by comparing wild-type controls, heterozygous igf1 +/- , and heterozygous mice treated with IGF-1 for 10 days. Histology, microarray for mRNA gene expression, RT-qPCR, and lipid peroxidation were assessed. Microarray analyses revealed significant underexpression of igf1 in heterozygous mice compared to control mice, restoring normal liver expression after treatment, which then normalized its circulating levels. IGF-1 receptor mRNA was overexpressed in Hz mice liver, while treated mice displayed a similar expression to that of the controls. Heterozygous mice showed overexpression of several genes encoding proteins related to inflammatory and acute-phase proteins and underexpression or overexpression of genes which coded for extracellular matrix, cytoskeleton, and cell junction components. Histology revealed an altered hepatic architecture. In addition, liver oxidative damage was found increased in the heterozygous group. The mere IGF-1 partial deficiency is associated with relevant alterations of the hepatic architecture and expression of genes involved in cytoskeleton, hepatocyte polarity, cell junctions, and extracellular matrix proteins. Moreover, it induces hepatic expression of the IGF-1 receptor and elevated acute-phase and inflammation mediators, which all resulted in liver oxidative damage.

Differences in gene expression profiles and signaling pathways in rhabdomyolysis-induced acute kidney injury.

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Geng, Xiaodong; Wang, Yuanda; Hong, Quan; Yang, Jurong; Zheng, Wei; Zhang, Gang; Cai, Guangyan; Chen, Xiangmei; Wu, Di

2015-01-01

Rhabdomyolysis is a threatening syndrome because it causes the breakdown of skeletal muscle. Muscle destruction leads to the release of myoglobin, intracellular proteins, and electrolytes into the circulation. The aim of this study was to investigate the differences in gene expression profiles and signaling pathways upon rhabdomyolysis-induced acute kidney injury (AKI). In this study, we used glycerol-induced renal injury as a model of rhabdomyolysis-induced AKI. We analyzed data and relevant information from the Gene Expression Omnibus database (No: GSE44925). The gene expression data for three untreated mice were compared to data for five mice with rhabdomyolysis-induced AKI. The expression profiling of the three untreated mice and the five rhabdomyolysis-induced AKI mice was performed using microarray analysis. We examined the levels of Cyp3a13, Rela, Aldh7a1, Jun, CD14. And Cdkn1a using RT-PCR to determine the accuracy of the microarray results. The microarray analysis showed that there were 1050 downregulated and 659 upregulated genes in the rhabdomyolysis-induced AKI mice compared to the control group. The interactions of all differentially expressed genes in the Signal-Net were analyzed. Cyp3a13 and Rela had the most interactions with other genes. The data showed that Rela and Aldh7a1 were the key nodes and had important positions in the Signal-Net. The genes Jun, CD14, and Cdkn1a were also significantly upregulated. The pathway analysis classified the differentially expressed genes into 71 downregulated and 48 upregulated pathways including the PI3K/Akt, MAPK, and NF-κB signaling pathways. The results of this study indicate that the NF-κB, MAPK, PI3K/Akt, and apoptotic pathways are regulated in rhabdomyolysis-induced AKI.

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-01-20

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

Widespread ectopic expression of olfactory receptor genes

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Yanai Itai

2006-05-01

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

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

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Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

2013-01-01

The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

Microarray Analysis of Iris Gene Expression in Mice with Mutations Influencing Pigmentation

Science.gov (United States)

Trantow, Colleen M.; Cuffy, Tryphena L.; Fingert, John H.; Kuehn, Markus H.

2011-01-01

Purpose. Several ocular diseases involve the iris, notably including oculocutaneous albinism, pigment dispersion syndrome, and exfoliation syndrome. To screen for candidate genes that may contribute to the pathogenesis of these diseases, genome-wide iris gene expression patterns were comparatively analyzed from mouse models of these conditions. Methods. Iris samples from albino mice with a Tyr mutation, pigment dispersion–prone mice with Tyrp1 and Gpnmb mutations, and mice resembling exfoliation syndrome with a Lyst mutation were compared with samples from wild-type mice. All mice were strain (C57BL/6J), age (60 days old), and sex (female) matched. Microarrays were used to compare transcriptional profiles, and differentially expressed transcripts were described by functional annotation clustering using DAVID Bioinformatics Resources. Quantitative real-time PCR was performed to validate a subset of identified changes. Results. Compared with wild-type C57BL/6J mice, each disease context exhibited a large number of statistically significant changes in gene expression, including 685 transcripts differentially expressed in albino irides, 403 in pigment dispersion–prone irides, and 460 in exfoliative-like irides. Conclusions. Functional annotation clusterings were particularly striking among the overrepresented genes, with albino and pigment dispersion–prone irides both exhibiting overall evidence of crystallin-mediated stress responses. Exfoliative-like irides from mice with a Lyst mutation showed overall evidence of involvement of genes that influence immune system processes, lytic vacuoles, and lysosomes. These findings have several biologically relevant implications, particularly with respect to secondary forms of glaucoma, and represent a useful resource as a hypothesis-generating dataset. PMID:20739468

Bayesian nonparametric variable selection as an exploratory tool for discovering differentially expressed genes.

Science.gov (United States)

Shahbaba, Babak; Johnson, Wesley O

2013-05-30

High-throughput scientific studies involving no clear a priori hypothesis are common. For example, a large-scale genomic study of a disease may examine thousands of genes without hypothesizing that any specific gene is responsible for the disease. In these studies, the objective is to explore a large number of possible factors (e.g., genes) in order to identify a small number that will be considered in follow-up studies that tend to be more thorough and on smaller scales. A simple, hierarchical, linear regression model with random coefficients is assumed for case-control data that correspond to each gene. The specific model used will be seen to be related to a standard Bayesian variable selection model. Relatively large regression coefficients correspond to potential differences in responses for cases versus controls and thus to genes that might 'matter'. For large-scale studies, and using a Dirichlet process mixture model for the regression coefficients, we are able to find clusters of regression effects of genes with increasing potential effect or 'relevance', in relation to the outcome of interest. One cluster will always correspond to genes whose coefficients are in a neighborhood that is relatively close to zero and will be deemed least relevant. Other clusters will correspond to increasing magnitudes of the random/latent regression coefficients. Using simulated data, we demonstrate that our approach could be quite effective in finding relevant genes compared with several alternative methods. We apply our model to two large-scale studies. The first study involves transcriptome analysis of infection by human cytomegalovirus. The second study's objective is to identify differentially expressed genes between two types of leukemia. Copyright © 2012 John Wiley & Sons, Ltd.

Dynamic association rules for gene expression data analysis.

Science.gov (United States)

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

2015-10-14

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

Gene expression in periodontal tissues following treatment

Directory of Open Access Journals (Sweden)

Eisenacher Martin

2008-07-01

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

STAT3 Target Genes Relevant to Human Cancers

International Nuclear Information System (INIS)

Carpenter, Richard L.; Lo, Hui-Wen

2014-01-01

Since its discovery, the STAT3 transcription factor has been extensively studied for its function as a transcriptional regulator and its role as a mediator of development, normal physiology, and pathology of many diseases, including cancers. These efforts have uncovered an array of genes that can be positively and negatively regulated by STAT3, alone and in cooperation with other transcription factors. Through regulating gene expression, STAT3 has been demonstrated to play a pivotal role in many cellular processes including oncogenesis, tumor growth and progression, and stemness. Interestingly, recent studies suggest that STAT3 may behave as a tumor suppressor by activating expression of genes known to inhibit tumorigenesis. Additional evidence suggested that STAT3 may elicit opposing effects depending on cellular context and tumor types. These mixed results signify the need for a deeper understanding of STAT3, including its upstream regulators, parallel transcription co-regulators, and downstream target genes. To help facilitate fulfilling this unmet need, this review will be primarily focused on STAT3 downstream target genes that have been validated to associate with tumorigenesis and/or malignant biology of human cancers

Temporal gene expression profiling of the rat knee joint capsule during immobilization-induced joint contractures.

Science.gov (United States)

Wong, Kayleigh; Sun, Fangui; Trudel, Guy; Sebastiani, Paola; Laneuville, Odette

2015-05-26

Contractures of the knee joint cause disability and handicap. Recovering range of motion is recognized by arthritic patients as their preference for improved health outcome secondary only to pain management. Clinical and experimental studies provide evidence that the posterior knee capsule prevents the knee from achieving full extension. This study was undertaken to investigate the dynamic changes of the joint capsule transcriptome during the progression of knee joint contractures induced by immobilization. We performed a microarray analysis of genes expressed in the posterior knee joint capsule following induction of a flexion contracture by rigidly immobilizing the rat knee joint over a time-course of 16 weeks. Fold changes of expression values were measured and co-expressed genes were identified by clustering based on time-series analysis. Genes associated with immobilization were further analyzed to reveal pathways and biological significance and validated by immunohistochemistry on sagittal sections of knee joints. Changes in expression with a minimum of 1.5 fold changes were dominated by a decrease in expression for 7732 probe sets occurring at week 8 while the expression of 2251 probe sets increased. Clusters of genes with similar profiles of expression included a total of 162 genes displaying at least a 2 fold change compared to week 1. Functional analysis revealed ontology categories corresponding to triglyceride metabolism, extracellular matrix and muscle contraction. The altered expression of selected genes involved in the triglyceride biosynthesis pathway; AGPAT-9, and of the genes P4HB and HSP47, both involved in collagen synthesis, was confirmed by immunohistochemistry. Gene expression in the knee joint capsule was sensitive to joint immobility and provided insights into molecular mechanisms relevant to the pathophysiology of knee flexion contractures. Capsule responses to immobilization was dynamic and characterized by modulation of at least three

Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

KAUST Repository

Permina, Elizaveta A.

2013-01-01

Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.

Gene expression profiles in skeletal muscle after gene electrotransfer

DEFF Research Database (Denmark)

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

2007-01-01

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

Comparative gene expression between two yeast species

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Guan Yuanfang

2013-01-01

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

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

A gene expression analysis of cell wall biosynthetic genes in Malus × domestica infected by ‘Candidatus Phytoplasma mali’

Science.gov (United States)

Guerriero, Gea; Giorno, Filomena; Ciccotti, Anna Maria; Schmidt, Silvia; Baric, Sanja

2016-01-01

Apple proliferation (AP) represents a serious threat to several fruit-growing areas and is responsible for great economic losses. Several studies have highlighted the key role played by the cell wall in response to pathogen attack. The existence of a cell wall integrity signaling pathway which senses perturbations in the cell wall architecture upon abiotic/biotic stresses and activates specific defence responses has been widely demonstrated in plants. More recently a role played by cell wall-related genes has also been reported in plants infected by phytoplasmas. With the aim of shedding light on the cell wall response to AP disease in the economically relevant fruit-tree Malus × domestica Borkh., we investigated the expression of the cellulose (CesA) and callose synthase (CalS) genes in different organs (i.e., leaves, roots and branch phloem) of healthy and infected symptomatic outdoor-grown trees, sampled over the course of two time points (i.e., spring and autumn 2011), as well as in in vitro micropropagated control and infected plantlets. A strong up-regulation in the expression of cell wall biosynthetic genes was recorded in roots from infected trees. Secondary cell wall CesAs showed up-regulation in the phloem tissue from branches of infected plants, while either a down-regulation of some genes or no major changes were observed in the leaves. Micropropagated plantlets also showed an increase in cell wall-related genes and constitute a useful system for a general assessment of gene expression analysis upon phytoplasma infection. Finally, we also report the presence of several ‘knot’-like structures along the roots of infected apple trees and discuss the occurrence of this interesting phenotype in relation to the gene expression results and the modalities of phytoplasma diffusion. PMID:23086810

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

NARCIS (Netherlands)

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

2008-01-01

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

Serial analysis of gene expression (SAGE)

NARCIS (Netherlands)

van Ruissen, Fred; Baas, Frank

2007-01-01

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

An Interactive Database of Cocaine-Responsive Gene Expression

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Willard M. Freeman

2002-01-01

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

CDX2 gene expression in acute lymphoblastic leukemia

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments

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Kohlbacher Oliver

2008-12-01

Full Text Available Abstract Background High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline. Results Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms. Conclusion Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.

2013-07-18

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

Reference Gene Screening for Analyzing Gene Expression Across Goat Tissue

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Yu Zhang

2013-12-01

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

Dynamics of Protein Phosphatase Gene Expression in Corbicula fluminea Exposed to Microcystin-LR and to Toxic Microcystis aeruginosa Cells

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Vitor Vasconcelos

2011-12-01

Full Text Available This study investigated the in vivo effects of microcystins on gene expression of several phosphoprotein phosphatases (PPP in the freshwater clam Corbicula fluminea with two different exposure scenarios. Clams were exposed for 96 h to 5 µg L−1 of dissolved microcystin-LR and the relative changes of gene expression of three different types of PPP (PPP1, 2 and 4 were analyzed by quantitative real-time PCR. The results showed a significant induction of PPP2 gene expression in the visceral mass. In contrast, the cyanotoxin did not cause any significant changes on PPP1 and PPP4 gene expression. Based on these results, we studied alterations in transcriptional patterns in parallel with enzymatic activity of C. fluminea for PPP2, induced by a Microcystis aeruginosa toxic strain (1 × 105 cells cm−3 during 96 h. The relative changes of gene expression and enzyme activity in visceral mass were analyzed by quantitative real-time PCR and colorimetric assays respectively. The clams exhibited a significant reduction of PPP2 activity with a concomitant enhancement of gene expression. Considering all the results we can conclude that the exposure to an ecologically relevant concentration of pure or intracellular microcystins (-LR promoted an in vivo effect on PPP2 gene expression in C. fluminea.

A three-gene expression signature model for risk stratification of patients with neuroblastoma.

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Garcia, Idoia; Mayol, Gemma; Ríos, José; Domenech, Gema; Cheung, Nai-Kong V; Oberthuer, André; Fischer, Matthias; Maris, John M; Brodeur, Garrett M; Hero, Barbara; Rodríguez, Eva; Suñol, Mariona; Galvan, Patricia; de Torres, Carmen; Mora, Jaume; Lavarino, Cinzia

2012-04-01

Neuroblastoma is an embryonal tumor with contrasting clinical courses. Despite elaborate stratification strategies, precise clinical risk assessment still remains a challenge. The purpose of this study was to develop a PCR-based predictor model to improve clinical risk assessment of patients with neuroblastoma. The model was developed using real-time PCR gene expression data from 96 samples and tested on separate expression data sets obtained from real-time PCR and microarray studies comprising 362 patients. On the basis of our prior study of differentially expressed genes in favorable and unfavorable neuroblastoma subgroups, we identified three genes, CHD5, PAFAH1B1, and NME1, strongly associated with patient outcome. The expression pattern of these genes was used to develop a PCR-based single-score predictor model. The model discriminated patients into two groups with significantly different clinical outcome [set 1: 5-year overall survival (OS): 0.93 ± 0.03 vs. 0.53 ± 0.06, 5-year event-free survival (EFS): 0.85 ± 0.04 vs. 0.042 ± 0.06, both P model was an independent marker for survival (P model robustly classified patients in the total cohort and in different clinically relevant risk subgroups. We propose for the first time in neuroblastoma, a technically simple PCR-based predictor model that could help refine current risk stratification systems. ©2012 AACR.

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.

Standardized Cannabis sativa extract attenuates tau and stathmin gene expression in the melanoma cell line

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Golnaz Vaseghi

2017-10-01

Full Text Available Objective(s: Metastasis is the main cause of death in patients with melanoma. Cannabis-based medicines are effective adjunctive drugs in cancer patients. Tau and Stathmin proteins are the key proteins in cancer metastasis. Here we have investigated the effect of a standardized Cannabis sativa extract on cell migration and Tau and Stathmin gene expression in the melanoma cell line. Materials and Methods: In the treatment group, melanoma (B1617 was treated 48 hr with various concentrations of standardized C. sativa extract. Cells with no treatment were considered as the control group, then study was followed by Quantitative RT-Real Time PCR assay. Relative gene expression was calculated by the ΔΔct method. Migration assay was used to evaluate cancer metastasis. Results: Tau and stathmin gene expression was significantly decreased compared to the control group. Cell migration was also significantly reduced compared to controls.  Conclusion: C. sativa decreased tau and stathmin gene expression and cancer metastasis.  The results may have some clinical relevance for the use of cannabis-based medicines in patients with metastatic melanoma.

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

DEFF Research Database (Denmark)

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

2011-01-01

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

Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells

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Montalescot Gilles

2008-06-01

Full Text Available Abstract Background In this study we assessed the respective ability of Affymetrix and Illumina microarray methodologies to answer a relevant biological question, namely the change in gene expression between resting monocytes and macrophages derived from these monocytes. Five RNA samples for each type of cell were hybridized to the two platforms in parallel. In addition, a reference list of differentially expressed genes (DEG was generated from a larger number of hybridizations (mRNA from 86 individuals using the RNG/MRC two-color platform. Results Our results show an important overlap of the Illumina and Affymetrix DEG lists. In addition, more than 70% of the genes in these lists were also present in the reference list. Overall the two platforms had very similar performance in terms of biological significance, evaluated by the presence in the DEG lists of an excess of genes belonging to Gene Ontology (GO categories relevant for the biology of monocytes and macrophages. Our results support the conclusion of the MicroArray Quality Control (MAQC project that the criteria used to constitute the DEG lists strongly influence the degree of concordance among platforms. However the importance of prioritizing genes by magnitude of effect (fold change rather than statistical significance (p-value to enhance cross-platform reproducibility recommended by the MAQC authors was not supported by our data. Conclusion Functional analysis based on GO enrichment demonstrates that the 2 compared technologies delivered very similar results and identified most of the relevant GO categories enriched in the reference list.

Experimental and Modeling Approaches for Understanding the Effect of Gene Expression Noise in Biological Development

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David M. Holloway

2018-04-01

Full Text Available Biological development involves numerous chemical and physical processes which must act in concert to reliably produce a cell, a tissue, or a body. To be successful, the developing organism must be robust to variability at many levels, such as the environment (e.g., temperature, moisture, upstream information (such as long-range positional information gradients, or intrinsic noise due to the stochastic nature of low concentration chemical kinetics. The latter is especially relevant to the regulation of gene expression in cell differentiation. The temporal stochasticity of gene expression has been studied in single celled organisms for nearly two decades, but only recently have techniques become available to gather temporally-resolved data across spatially-distributed gene expression patterns in developing multicellular organisms. These demonstrate temporal noisy “bursting” in the number of gene transcripts per cell, raising the question of how the transcript number defining a particular cell type is produced, such that one cell type can reliably be distinguished from a neighboring cell of different type along a tissue boundary. Stochastic spatio-temporal modeling of tissue-wide expression patterns can identify signatures for specific types of gene regulation, which can be used to extract regulatory mechanism information from experimental time series. This Perspective focuses on using this type of approach to study gene expression noise during the anterior-posterior segmentation of the fruit fly embryo. Advances in experimental and theoretical techniques will lead to an increasing quantification of expression noise that can be used to understand how regulatory mechanisms contribute to embryonic robustness across a range of developmental processes.

Expression variation: its relevance to emergence of chronic disease and to therapy.

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Anatoly L Mayburd

Full Text Available BACKGROUND: Stochastic fluctuations in the protein turnover underlie the random emergence of neural precursor cells from initially homogenous cell population. If stochastic alteration of the levels in signal transduction networks is sufficient to spontaneously alter a phenotype, can it cause a sporadic chronic disease as well -- including cancer? METHODS: Expression in >80 disease-free tissue environments was measured using Affymetrix microarray platform comprising 54675 probe-sets. Steps were taken to suppress the technical noise inherent to microarray experiment. Next, the integrated expression and expression variability data were aligned with the mechanistic data covering major human chronic diseases. RESULTS: Measured as class average, variability of expression of disease associated genes measured in health was higher than variability of random genes for all chronic pathologies. Anti-cancer FDA approved targets were displaying much higher variability as a class compared to random genes. Same held for magnitude of gene expression. The genes known to participate in multiple chronic disorders demonstrated the highest variability. Disease-related gene categories displayed on average more intricate regulation of biological function vs random reference, were enriched in adaptive and transient functions as well as positive feedback relationships. CONCLUSIONS: A possible causative link can be suggested between normal (healthy state gene expression variation and inception of major human pathologies, including cancer. Study of variability profiles may lead to novel diagnostic methods, therapies and better drug target prioritization. The results of the study suggest the need to advance personalized therapy development.

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

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Jean-François Gout

2010-05-01

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

Adult rat bone marrow stromal cells express genes associated with dopamine neurons

International Nuclear Information System (INIS)

Kramer, Brian C.; Woodbury, Dale; Black, Ira B.

2006-01-01

An intensive search is underway to identify candidates to replace the cells that degenerate in Parkinson's disease (PD). To date, no suitable substitute has been found. We have recently found that adult rat bone marrow stromal cells (MSCs) can be induced to assume a neuronal phenotype in vitro. These findings may have particular relevance to the treatment of PD. We now report that adult MSCs express multiple dopaminergic genes, suggesting that they are potential candidates for cell therapy. Using RT-PCR, we have examined families of genes that are associated with the development and/or survival of dopaminergic neurons. MSCs transcribe a variety of dopaminergic genes including patched and smoothened (components of the Shh receptor), Gli-1 (downstream mediator of Shh), and Otx-1, a gene associated with formation of the mesencephalon during development. Furthermore, Shh treatment elicits a 1.5-fold increase in DNA synthesis in cultured MSCs, suggesting the presence of a functional Shh receptor complex. We have also found that MSCs transcribe and translate Nurr-1, a nuclear receptor essential for the development of dopamine neurons. In addition, MSCs express a variety of growth factor receptors including the glycosyl-phosphatidylinositol-anchored ligand-binding subunit of the GDNF receptor, GFRα1, as well as fibroblast growth factor receptors one and four. The expression of genes that are associated with the development and survival of dopamine neurons suggests a potential role for these cells in the treatment of Parkinson's disease

Positive selection on gene expression in the human brain

DEFF Research Database (Denmark)

Khaitovich, Philipp; Tang, Kun; Franz, Henriette

2006-01-01

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

A stochastic approach to multi-gene expression dynamics

International Nuclear Information System (INIS)

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

2005-01-01

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

Assays for noninvasive imaging of reporter gene expression

International Nuclear Information System (INIS)

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

1999-01-01

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

PRAME gene expression profile in medulloblastoma

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Tânia Maria Vulcani-Freitas

2011-02-01

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

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

Science.gov (United States)

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

2017-09-01

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

Gene expression and functional studies of the optic nerve head astrocyte transcriptome from normal African Americans and Caucasian Americans donors.

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Haixi Miao

2008-08-01

Full Text Available To determine whether optic nerve head (ONH astrocytes, a key cellular component of glaucomatous neuropathy, exhibit differential gene expression in primary cultures of astrocytes from normal African American (AA donors compared to astrocytes from normal Caucasian American (CA donors.We used oligonucleotide Affymetrix microarray (HG U133A & HG U133A 2.0 chips to compare gene expression levels in cultured ONH astrocytes from twelve CA and twelve AA normal age matched donor eyes. Chips were normalized with Robust Microarray Analysis (RMA in R using Bioconductor. Significant differential gene expression levels were detected using mixed effects modeling and Statistical Analysis of Microarray (SAM. Functional analysis and Gene Ontology were used to classify differentially expressed genes. Differential gene expression was validated by quantitative real time RT-PCR. Protein levels were detected by Western blots and ELISA. Cell adhesion and migration assays tested physiological responses. Glutathione (GSH assay detected levels of intracellular GSH.Multiple analyses selected 87 genes differentially expressed between normal AA and CA (P<0.01. The most relevant genes expressed in AA were categorized by function, including: signal transduction, response to stress, ECM genes, migration and cell adhesion.These data show that normal astrocytes from AA and CA normal donors display distinct expression profiles that impact astrocyte functions in the ONH. Our data suggests that differences in gene expression in ONH astrocytes may be specific to the development and/or progression of glaucoma in AA.

SIGNATURE: A workbench for gene expression signature analysis

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Chang Jeffrey T

2011-11-01

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

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.

Plasticity-Related Gene Expression During Eszopiclone-Induced Sleep.

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

2017-07-01

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

Evaluation of suitable reference genes for gene expression studies in bovine muscular tissue

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Dunner Susana

2008-09-01

Full Text Available Abstract Background Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RTqPCR is a technique used to measure mRNA species copy number as a way to determine key genes involved in different biological processes. However, the expression level of these key genes may vary among tissues or cells not only as a consequence of differential expression but also due to different factors, including choice of reference genes to normalize the expression levels of the target genes; thus the selection of reference genes is critical for expression studies. For this purpose, ten candidate reference genes were investigated in bovine muscular tissue. Results The value of stability of ten candidate reference genes included in three groups was estimated: the so called 'classical housekeeping' genes (18S, GAPDH and ACTB, a second set of genes used in expression studies conducted on other tissues (B2M, RPII, UBC and HMBS and a third set of novel genes (SF3A1, EEF1A2 and CASC3. Three different statistical algorithms were used to rank the genes by their stability measures as produced by geNorm, NormFinder and Bestkeeper. The three methods tend to agree on the most stably expressed genes and the least in muscular tissue. EEF1A2 and HMBS followed by SF3A1, ACTB, and CASC3 can be considered as stable reference genes, and B2M, RPII, UBC and GAPDH would not be appropriate. Although the rRNA-18S stability measure seems to be within the range of acceptance, its use is not recommended because its synthesis regulation is not representative of mRNA levels. Conclusion Based on geNorm algorithm, we propose the use of three genes SF3A1, EEF1A2 and HMBS as references for normalization of real-time RTqPCR in muscle expression studies.

Classification across gene expression microarray studies

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Kuner Ruprecht

2009-12-01

Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

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Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

2017-02-02

Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

Expression profiling identifies genes involved in emphysema severity

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Bowman Rayleen V

2009-09-01

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

Altered Expression of Endoplasmic Reticulum Stress Associated Genes in Hippocampus of Learned Helpless Rats: Relevance to Depression Pathophysiology

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Matthew A. Timberlake

2016-01-01

Full Text Available The unfolded protein response (UPR is an evolutionarily conserved defensive mechanism that is used by cells to correct misfolded proteins that accumulate in the endoplasmic reticulum. These proteins are misfolded as a result of physical stress on a cell and initiate a host of downstream effects that govern processes ranging from inflammation to apoptosis. To examine whether UPR system plays a role in depression, we examined the expression of genes that are part of the three different pathways for UPR activation, namely GRP78, GRP94, ATF6, XBP-1, ATF4 and CHOP using an animal model system that distinguishes vulnerability (learned helpless, LH from resistance (non-learned helpless, NLH to develop depression. Rats were exposed to inescapable shock on day 1 and day 7 and were tested for escape latency on day 14. Rats not given shock but tested for escape latency were used as tested control (TC. Plasma corticosterone levels were measured. Expression levels of various UPR associated genes were determined in hippocampus using qPCR. We found that the corticosterone level was higher in LH rats compared with TC and NLH rats. Expression of GRP78, GRP94, ATF6 and XBP-1 were significantly upregulated in LH rats compared with TC or NLH rats, whereas NLH rats did not show such changes. Expression levels of ATF4 and CHOP showed trends towards upregulation but were not significantly altered in LH or NLH group. Our data show strong evidence of altered UPR system in depressed rats, which could be associated with development of depressive behavior.

Decoupling Linear and Nonlinear Associations of Gene Expression

KAUST Repository

Itakura, Alan

2013-05-01

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

Decoupling Linear and Nonlinear Associations of Gene Expression

KAUST Repository

Itakura, Alan

2013-01-01

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

Acute and repeated ECS treatment increases CRF, POMC and PENK gene expression in selected regions of the rat hypothalamus.

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Garcia-Garcia, L; Llewellyn-Jones, V; Fernandez Fernandez, I; Fuentes, J A; Manzanares, J

1998-01-05

The purpose of this study was to investigate the effects of acute and repeated electroconvulsive shock (ECS) on corticotropin releasing factor (CRF), proopiomelanocortin (POMC) and proenkephalin (PENK) gene expression in selected regions of the brain and pituitary of the rat. Acute ECS increased CRF gene expression in the paraventricular nucleus (PVN) by 20%, an effect that was further enhanced to 38% when rats received repeated ECS treatment. Acute and repeated ECS increased POMC gene expression in the arcuate nucleus (ARC) by 49-59% but failed to alter these mRNA levels in the anterior lobe (AL) of the pituitary gland. PENK gene expression was increased by 35% in the nucleus accumbens (NA) and by 180% the ventromedial nucleus (VMN) after acute or repeated ECS treatment but no significant changes were found in the PVN or striatum (ST). Taken together, these results indicate a differential CRF and opioid gene expression regulation after acute or repeated ECS treatment that may be relevant to their therapeutic or side effects in depression.

Bayesian assignment of gene ontology terms to gene expression experiments

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Sykacek, P.

2012-01-01

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

Bayesian assignment of gene ontology terms to gene expression experiments.

Science.gov (United States)

Sykacek, P

2012-09-15

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

Gene expression profile data for mouse facial development

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Sonia M. Leach

2017-08-01

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

Integrated olfactory receptor and microarray gene expression databases

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Crasto Chiquito J

2007-06-01

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

Gene expression analysis of flax seed development

Science.gov (United States)

2011-01-01

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

Gene expression analysis of flax seed development

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Sharpe Andrew

2011-04-01

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

Dysregulation of gene expression in the striatum of BACHD rats expressing full-length mutant huntingtin and associated abnormalities on molecular and protein levels.

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Yu-Taeger, Libo; Bonin, Michael; Stricker-Shaver, Janice; Riess, Olaf; Nguyen, Hoa Huu Phuc

2017-05-01

Huntington disease (HD) is an autosomal dominantly inherited neurodegenerative disorder caused by a CAG repeat expansion in the gene coding for the huntingtin protein (HTT). Mutant HTT (mHTT) has been proposed to cause neuronal dysfunction and neuronal loss through multiple mechanisms. Transcriptional changes may be a core pathogenic feature of HD. Utilizing the Affymetrix platform we performed a genome-wide RNA expression analysis in two BACHD transgenic rat lines (TG5 and TG9) at 12 months of age, both of which carry full-length human mHTT but with different expression levels. By defining the threshold of significance at p < 0.01, we found 1608 genes and 871 genes differentially expressed in both TG5 and TG9 rats when compared to the wild type littermates, respectively. We only chose the highly up-/down-regulated genes for further analysis by setting an additional threshold of 1.5 fold change. Comparing gene expression profiles of human HD brains and BACHD rats revealed a high concordance in both functional and IPA (Ingenuity Pathway Analysis) canonical pathways relevant to HD. In addition, we investigated the causes leading to gene expression changes at molecular and protein levels in BACHD rats including the involvement of polyQ-containing transcription factors TATA box-binding protein (TBP), Sp1 and CBP as well as the chromatin structure. We demonstrate that the BACHD rat model recapitulates the gene expression changes of the human disease supporting its role as a preclinical research animal model. We also show for the first time that TFIID complex formation is reduced, while soluble TBP is increased in an HD model. This finding suggests that mHTT is a competitor instead of a recruiter of polyQ-containing transcription factors in the transcription process in HD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Anhedonic behavior in cryptochrome 2-deficient mice is paralleled by altered diurnal patterns of amygdala gene expression.

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Savalli, Giorgia; Diao, Weifei; Berger, Stefanie; Ronovsky, Marianne; Partonen, Timo; Pollak, Daniela D

2015-07-01

Mood disorders are frequently paralleled by disturbances in circadian rhythm-related physiological and behavioral states and genetic variants of clock genes have been associated with depression. Cryptochrome 2 (Cry2) is one of the core components of the molecular circadian machinery which has been linked to depression, both, in patients suffering from the disease and animal models of the disorder. Despite this circumstantial evidence, a direct causal relationship between Cry2 expression and depression has not been established. Here, a genetic mouse model of Cry2 deficiency (Cry2 (-/-) mice) was employed to test the direct relevance of Cry2 for depression-like behavior. Augmented anhedonic behavior in the sucrose preference test, without alterations in behavioral despair, was observed in Cry2 (-/-) mice. The novelty suppressed feeding paradigm revealed reduced hyponeophagia in Cry2 (-/-) mice compared to wild-type littermates. Given the importance of the amygdala in the regulation of emotion and their relevance for the pathophysiology of depression, potential alterations in diurnal patterns of basolateral amygdala gene expression in Cry2 (-/-) mice were investigated focusing on core clock genes and neurotrophic factor systems implicated in the pathophysiology of depression. Differential expression of the clock gene Bhlhe40 and the neurotrophic factor Vegfb were found in the beginning of the active (dark) phase in Cry2 (-/-) compared to wild-type animals. Furthermore, amygdala tissue of Cry2 (-/-) mice contained lower levels of Bdnf-III. Collectively, these results indicate that Cry2 exerts a critical role in the control of depression-related emotional states and modulates the chronobiological gene expression profile in the mouse amygdala.

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

KAUST Repository

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

2015-01-01

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

Analysis of gene expression in prostate cancer epithelial and interstitial stromal cells using laser capture microdissection

International Nuclear Information System (INIS)

Gregg, Jennifer L; Brown, Kathleen E; Mintz, Eric M; Piontkivska, Helen; Fraizer, Gail C

2010-01-01

distinct cell populations to better understand their potential interactions. In the present study, LCM and microarray analysis were used to identify novel gene expression patterns in prostate cell populations, including identification of WT1 expression in epithelial cells. The relevance of WT1 expression in prostate cancer was confirmed by analysis of tumor tissue and cell lines, suggesting a potential role for WT1 in prostate tumorigenesis

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

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Mariana Ferreira Leal

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

Detecting microRNA activity from gene expression data

LENUS (Irish Health Repository)

Madden, Stephen F

2010-05-18

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

Detecting microRNA activity from gene expression data.

LENUS (Irish Health Repository)

Madden, Stephen F

2010-01-01

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

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

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Øvstebø Reidun

2010-05-01

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

Differentially expressed genes in iron-induced prion protein conversion

International Nuclear Information System (INIS)

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

2016-01-01

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

Regulation of meiotic gene expression in plants

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Adele eZhou

2014-08-01

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

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

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Tintle Nathan L

2012-08-01

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

Identification of a new gene regulatory circuit involving B cell receptor activated signaling using a combined analysis of experimental, clinical and global gene expression data

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Schrader, Alexandra; Meyer, Katharina; Walther, Neele; Stolz, Ailine; Feist, Maren; Hand, Elisabeth; von Bonin, Frederike; Evers, Maurits; Kohler, Christian; Shirneshan, Katayoon; Vockerodt, Martina; Klapper, Wolfram; Szczepanowski, Monika; Murray, Paul G.; Bastians, Holger; Trümper, Lorenz; Spang, Rainer; Kube, Dieter

2016-01-01

To discover new regulatory pathways in B lymphoma cells, we performed a combined analysis of experimental, clinical and global gene expression data. We identified a specific cluster of genes that was coherently expressed in primary lymphoma samples and suppressed by activation of the B cell receptor (BCR) through αIgM treatment of lymphoma cells in vitro. This gene cluster, which we called BCR.1, includes numerous cell cycle regulators. A reduced expression of BCR.1 genes after BCR activation was observed in different cell lines and also in CD10+ germinal center B cells. We found that BCR activation led to a delayed entry to and progression of mitosis and defects in metaphase. Cytogenetic changes were detected upon long-term αIgM treatment. Furthermore, an inverse correlation of BCR.1 genes with c-Myc co-regulated genes in distinct groups of lymphoma patients was observed. Finally, we showed that the BCR.1 index discriminates activated B cell-like and germinal centre B cell-like diffuse large B cell lymphoma supporting the functional relevance of this new regulatory circuit and the power of guided clustering for biomarker discovery. PMID:27166259

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

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

2017-08-01

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

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

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Qiusheng Kong

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

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

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

2015-01-01

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

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

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Holec, Matěj; Kuželka, Ondřej; Železný, Filip

2015-10-28

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

Differential neutrophil gene expression in early bovine pregnancy

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Kizaki Keiichiro

2013-02-01

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

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

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Meizhen eWang

2016-01-01

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

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

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

2014-10-01

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

Clinical characteristics of inflammation-associated depression: Monocyte gene expression is age-related in major depressive disorder.

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Grosse, Laura; Carvalho, Livia A; Wijkhuijs, Annemarie J M; Bellingrath, Silja; Ruland, Tillmann; Ambrée, Oliver; Alferink, Judith; Ehring, Thomas; Drexhage, Hemmo A; Arolt, Volker

2015-02-01

Increased inflammatory activation might only be present in a subgroup of depressed individuals in which immune processes are especially relevant to disease development. We aimed to analyze demographic, depression, and trauma characteristics of major depressive disorder (MDD) patients with regard to inflammatory monocyte gene expression. Fifty-six naturalistically treated MDD patients (32 ± 12 years) and 57 healthy controls (HC; 31 ± 11 years) were analyzed by the Inventory of Depressive Symptomatology (IDS) and by the Childhood Trauma Questionnaire (CTQ). We determined the expression of 38 inflammatory and immune activation genes including the glucocorticoid receptor (GR)α and GRβ genes in purified CD14(+) monocytes using quantitative-polymerase chain reaction (RT-qPCR). Monocyte gene expression was age-dependent, particularly in MDD patients. Increased monocyte gene expression and decreased GRα/β ratio were only present in MDD patients aged ⩾ 28 years. Post hoc analyses of monocyte immune activation in patients depression (recurrent type, onset depression, onset ⩾15 years) - additionally characterized by the absence of panic symptoms - that exhibited a strongly reduced inflammatory monocyte activation compared to HC. In conclusion, monocyte immune activation was not uniformly raised in MDD patients but was increased only in patients of 28 years and older. Copyright © 2014 Elsevier Inc. All rights reserved.

Cell-Specific PEAR1 Methylation Studies Reveal a Locus that Coordinates Expression of Multiple Genes

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Benedetta Izzi

2018-04-01

Full Text Available Chromosomal interactions connect distant enhancers and promoters on the same chromosome, activating or repressing gene expression. PEAR1 encodes the Platelet-Endothelial Aggregation Receptor 1, a contact receptor involved in platelet function and megakaryocyte and endothelial cell proliferation. PEAR1 expression during megakaryocyte differentiation is controlled by DNA methylation at its first CpG island. We identified a PEAR1 cell-specific methylation sensitive region in endothelial cells and megakaryocytes that showed strong chromosomal interactions with ISGL20L2, RRNAD1, MRLP24, HDGF and PRCC, using available promoter capture Hi-C datasets. These genes are involved in ribosome processing, protein synthesis, cell cycle and cell proliferation. We next studied the methylation and expression profile of these five genes in Human Umbilical Vein Endothelial Cells (HUVECs and megakaryocyte precursors. While cell-specific PEAR1 methylation corresponded to variability in expression for four out of five genes, no methylation change was observed in their promoter regions across cell types. Our data suggest that PEAR1 cell-type specific methylation changes may control long distance interactions with other genes. Further studies are needed to show whether such interaction data might be relevant for the genome-wide association data that showed a role for non-coding PEAR1 variants in the same region and platelet function, platelet count and cardiovascular risk.

Improved gene expression signature of testicular carcinoma in situ

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

2007-01-01

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

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

International Nuclear Information System (INIS)

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

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

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

2011-02-01

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

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

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Neutelings Godfrey

2010-04-01

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

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

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Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

2010-04-19

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

The Medicago truncatula gene expression atlas web server

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Tang Yuhong

2009-12-01

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

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

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Simone de Jong

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

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.

Gene expression of transporters and phase I/II metabolic enzymes in murine small intestine during fasting

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van der Meijde Jolanda

2007-08-01

Full Text Available Abstract Background Fasting has dramatic effects on small intestinal transport function. However, little is known on expression of intestinal transport and phase I/II metabolism genes during fasting and the role the fatty acid-activated transcription factor PPARα may play herein. We therefore investigated the effects of fasting on expression of these genes using Affymetrix GeneChip MOE430A arrays and quantitative RT-PCR. Results After 24 hours of fasting, expression levels of 33 of the 253 analyzed transporter and phase I/II metabolism genes were changed. Upregulated genes were involved in transport of energy-yielding molecules in processes such as glycogenolysis (G6pt1 and mitochondrial and peroxisomal oxidation of fatty acids (Cact, Mrs3/4, Fatp2, Cyp4a10, Cyp4b1. Other induced genes were responsible for the inactivation of the neurotransmitter serotonin (Sert, Sult1d1, Dtd, Papst2, formation of eicosanoids (Cyp2j6, Cyp4a10, Cyp4b1, or for secretion of cholesterol (Abca1 and Abcg8. Cyp3a11, typically known because of its drug metabolizing capacity, was also increased. Fasting had no pronounced effect on expression of phase II metabolic enzymes, except for glutathione S-transferases which were down-regulated. Time course studies revealed that some genes were acutely regulated, whereas expression of other genes was only affected after prolonged fasting. Finally, we identified 8 genes that were PPARα-dependently upregulated upon fasting. Conclusion We have characterized the response to fasting on expression of transporters and phase I/II metabolic enzymes in murine small intestine. Differentially expressed genes are involved in a variety of processes, which functionally can be summarized as a increased oxidation of fat and xenobiotics, b increased cholesterol secretion, c increased susceptibility to electrophilic stressors, and d reduced intestinal motility. This knowledge increases our understanding of gut physiology, and may be of relevance

Dual DNA methylation patterns in the CNS reveal developmentally poised chromatin and monoallelic expression of critical genes.

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Jinhui Wang

Full Text Available As a first step towards discovery of genes expressed from only one allele in the CNS, we used a tiling array assay for DNA sequences that are both methylated and unmethylated (the MAUD assay. We analyzed regulatory regions of the entire mouse brain transcriptome, and found that approximately 10% of the genes assayed showed dual DNA methylation patterns. They include a large subset of genes that display marks of both active and silent, i.e., poised, chromatin during development, consistent with a link between differential DNA methylation and lineage-specific differentiation within the CNS. Sixty-five of the MAUD hits and 57 other genes whose function is of relevance to CNS development and/or disorders were tested for allele-specific expression in F(1 hybrid clonal neural stem cell (NSC lines. Eight MAUD hits and one additional gene showed such expression. They include Lgi1, which causes a subtype of inherited epilepsy that displays autosomal dominance with incomplete penetrance; Gfra2, a receptor for glial cell line-derived neurotrophic factor GDNF that has been linked to kindling epilepsy; Unc5a, a netrin-1 receptor important in neurodevelopment; and Cspg4, a membrane chondroitin sulfate proteoglycan associated with malignant melanoma and astrocytoma in human. Three of the genes, Camk2a, Kcnc4, and Unc5a, show preferential expression of the same allele in all clonal NSC lines tested. The other six genes show a stochastic pattern of monoallelic expression in some NSC lines and bi-allelic expression in others. These results support the estimate that 1-2% of genes expressed in the CNS may be subject to allelic exclusion, and demonstrate that the group includes genes implicated in major disorders of the CNS as well as neurodevelopment.

Hepatic gene expression of Caucasian and African-American patients with obesity-related non-alcoholic fatty liver disease.

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Stepanova, Maria; Hossain, Noreen; Afendy, Arian; Perry, Kellie; Goodman, Zachary D; Baranova, Ancha; Younossi, Zobair

2010-05-01

There is increasing data suggesting that African Americans with NAFLD tend to have less progressive liver disease. The aim of this study is to assess differences in the hepatic gene expression of African-American and Caucasian patients with NAFLD who had undergone bariatric surgery. A total of 94 patients (81 NAFLD and 13 weight-matched controls with normal liver biopsy) were included. Of the entire cohort, 73 were Caucasians and 21 were African Americans. All patients were undergoing bariatric surgery. Two liver biopsies were obtained at the time of surgery. One biopsy was snap-frozen for gene expression and the other biopsy was stained for pathologic assessment. Liver biopsy confirmed that 24 patients from our cohort had NASH while 57 had only simple steatosis. Snap-frozen liver biopsy specimens of these patients were then used for the RNA extraction. cDNA probes were hybridized with customized microarray gene chips containing 5,220 relevant genes. Gene expression profiles were compared between groups using significance analysis of microarrays algorithm. In comparison to all Caucasian patients, African-American patients had over-expression of EPB41L1, IGF2, FAH, ACSL4, FUT4, CYP3A (q values < 10(-4)). In comparison to Caucasian NAFLD patients, African-American NAFLD patients showed over-expression of EPB41L1 and ACSL4 genes. Finally, in comparison to Caucasian NASH patients, African-American NASH patients showed over-expression of GSTM 2, GSTM4 and GSTM5 as well as FH and ASCL4 genes. Some genes highlighted by this analysis, particularly cytochrome CYP3A and glutathione transferases GSTM2, 4, 5, were previously implicated in the pathogenesis of NASH. African-American patients with biopsy-proven obesity-related NAFLD and NASH have a specific hepatic gene expression pattern that may explain their differences from Caucasian patients with NAFLD in developing progressive liver disease.

Positron emission tomography imaging of gene expression

International Nuclear Information System (INIS)

Tang Ganghua

2001-01-01

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

Understanding gene expression in coronary artery disease through ...

Indian Academy of Sciences (India)

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

ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.

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Dvorak, Pavel; Pesta, Martin; Soucek, Pavel

2017-05-01

Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various

Gene expression profile of pulpitis.

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

2016-06-01

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

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

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

2010-10-01

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