Tool For Analysis Of Gene Expression Research Articles

LIBGS: A MATLAB software package for gene selection

Many gene selection algorithms have been applied in gene expression data analysis successfully. To solve different developing environments of these toolkits, such as rankgene (Su et al., 2003), and mRMR (http://research.janelia.org/peng/proj/mrmr/index.htm), perform data analysis and make algorithm comparison more flexible, we have developed a software package LIBGS including: 1) Seven new gene selection algorithms implemented using MATLAB. 2) MATLAB interface for Rankgene. 3) MATLAB interface for LIBSVM and WEKA. 4) Programs for converting data formats. 5) A collection of six popular gene expression data sets. These features make LIBGS a useful tool in gene expression analysis and feature selection.

Structural and functional-annotation of an equine whole genome oligoarray

BackgroundThe horse genome is sequenced, allowing equine researchers to use high-throughput functional genomics platforms such as microarrays; next-generation sequencing for gene expression and proteomics. However, for researchers to derive value from these functional genomics datasets, they must be able to model this data in biologically relevant ways; to do so requires that the equine genome be more fully annotated. There are two interrelated types of genomic annotation: structural and functional. Structural annotation is delineating and demarcating the genomic elements (such as genes, promoters, and regulatory elements). Functional annotation is assigning function to structural elements. The Gene Ontology (GO) is the de facto standard for functional annotation, and is routinely used as a basis for modelling and hypothesis testing, large functional genomics datasets.ResultsAn Equine Whole Genome Oligonucleotide (EWGO) array with 21,351 elements was developed at Texas A&M University. This 70-mer oligoarray was designed using the approximately 7× assembled and annotated sequence of the equine genome to be one of the most comprehensive arrays available for expressed equine sequences. To assist researchers in determining the biological meaning of data derived from this array, we have structurally annotated it by mapping the elements to multiple database accessions, including UniProtKB, Entrez Gene, NRPD (Non-Redundant Protein Database) and UniGene. We next provided GO functional annotations for the gene transcripts represented on this array. Overall, we GO annotated 14,531 gene products (68.1% of the gene products represented on the EWGO array) with 57,912 annotations. GAQ (GO Annotation Quality) scores were calculated for this array both before and after we added GO annotation. The additional annotations improved the meanGAQ score 16-fold. This data is publicly available at AgBase http://www.agbase.msstate.edu/.ConclusionProviding additional information about the public databases which link to the gene products represented on the array allows users more flexibility when using gene expression modelling and hypothesis-testing computational tools. Moreover, since different databases provide different types of information, users have access to multiple data sources. In addition, our GO annotation underpins functional modelling for most gene expression analysis tools and enables equine researchers to model large lists of differentially expressed transcripts in biologically relevant ways.

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction

BackgroundIn the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches.ResultsIn our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis – GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value.ConclusionThis approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at:

Ultrasound-induced apoptosis in the presence of Sonazoid and associated alterations in gene expression levels: A possible therapeutic application

Ultrasound (US) has been shown to induce apoptosis and cell lysis in cancer cells. In this study, we report on the potential of using Sonazoid, a new echo-contrast agent, that is chemically more stable and US-resistant in combination with US in cancer therapy. The biological effects and their mechanisms in the presence or absence of ultrasonic exposure in vitro were investigated. In addition, the impact of the agent on the expression levels of genes responsive to US was studied using global-scale microarrays and computational gene expression analysis tools. Our results show that the combination led to enhanced cell killing in the presence of 1 MHz acoustic field. The apoptosis induction was shown to be mediated by the mitochondrial pathway. The occurrence of US-induced DNA damage was also observed. Despite these findings, the agent at concentrations similar to those clinically used can be considered as well tolerated. Furthermore, Sonazoid enhanced expression of genes that related to apoptosis and are responsive to US, although it alone had almost no effect. These results indicate the potential of Sonazoid for US contrast enhancement as well as the possibility of its use in US-aided therapies.

Orymold: ontology based gene expression data integration and analysis tool applied to rice

BackgroundIntegration and exploration of data obtained from genome wide monitoring technologies has become a major challenge for many bioinformaticists and biologists due to its heterogeneity and high dimensionality. A widely accepted approach to solve these issues has been the creation and use of controlled vocabularies (ontologies). Ontologies allow for the formalization of domain knowledge, which in turn enables generalization in the creation of querying interfaces as well as in the integration of heterogeneous data, providing both human and machine readable interfaces.ResultsWe designed and implemented a software tool that allows investigators to create their own semantic model of an organism and to use it to dynamically integrate expression data obtained from DNA microarrays and other probe based technologies. The software provides tools to use the semantic model to postulate and validate of hypotheses on the spatial and temporal expression and function of genes. In order to illustrate the software's use and features, we used it to build a semantic model of rice (Oryza sativa) and integrated experimental data into it.ConclusionIn this paper we describe the development and features of a flexible software application for dynamic gene expression data annotation, integration, and exploration called Orymold. Orymold is freely available for non-commercial users from

Construction and characterization of a cDNA library from head kidney of Japanese sea bass (Lateolabrax japonicus)

In this paper, a cDNA expression library from head kidney of Japanese sea bass (Lateolabrax japonicus) was constructed for the first time. The first-strand cDNA was synthesized with Moloney Murine Leukaemia virus reverse transcriptase and the double-stranded cDNA was digested by Xho I enzyme. Size fractionation was performed on CHROMA SPIN-400 columns. cDNA fragments longer than 500 bps were ligated into the lambdaZAPExpress vector. The recombinant DNA was packaged in vitro with Gigapack III gold packaging extract. The titers of the primary and amplified library were 1.0 x 10(5) and 5.0 x 10(9) pfu/ml, respectively. To characterize the constructed cDNA library, 15 phage plaques were selected randomly to test the inserted fragments. The results showed that the inserts were mostly longer than 500 bps. To test the utility, the library was screened with primers designed for three immune-related genes of, Myxovirus resistant (Mx), tumor necrosis factor-alpha (TNF-alpha) and Toll-like receptor (TLR). Results of Blastn and alignment showed that they are members of Mx, TNF-alpha and TLR gene families, respectively, which meets our anticipates for this cDNA library as an immune-related one. These results confirmed that the cDNA library constructed will provide a useful tool for gene cloning and expression analysis in immune system of Japanese sea bass.

Genetic networks responsive to low-intensity pulsed ultrasound in human lymphoma U937 cells

To clarify the detailed molecular mechanism underlying cellular responses to nonthermal low-intensity pulsed ultrasound (LIPUS), gene expression patterns and genetic networks in human lymphoma U937 cells were examined using global-scale microarrays and computational gene expression analysis tools. Six hours after LIPUS treatment (0.3 W/cm 2 for 1 min), apoptosis (14 ± 3.8%, mean ± SD) without no cell lysis was observed. Of 22,283 probe sets analyzed, LIPUS down-regulated 193 genes and up-regulated 201 genes by >1.5-fold. For down-regulated genes, the significant genetic network D was associated with cellular growth and proliferation, gene expression, or cellular development. For up-regulated genes, the significant genetic network U was associated with cellular movement, cell morphology, and cell death. The present results indicate that LIPUS affects the expression of many genes and will provide novel insight into the biomolecular mechanisms of LIPUS in therapeutic application for cancer therapy.

Curidium Medica, plc.

Curidium Medica, plc is a personalized medicine company intent on developing targeted medicines and their associated companion diagnostics to treat patients more effectively and safely. Through the use of its proprietary gene-expression analysis tool, Homomatrix®, Curidium aims to reveal different patient subgroups characterized by distinct underlying disease mechanisms. This is anticipated to lead to the identification of diagnostics to subclassify patients within heterogeneous disease populations and improved therapies for different patient subgroups, ultimately resulting in the development of personalized medicines using companion diagnostics and targeted treatments. The company's initial focus on diseases of the CNS has resulted in the identification of a blood diagnostic tool, PsychINDx™, which classifies patients with schizophrenia/bipolar disorder into four subgroups. PsychINDx may have the potential to improve the treatment of patients with schizophrenia/bipolar disorder. Curidium aims to continue to use this approach to improve patient treatments in a variety of therapeutic areas and heterogeneous diseases. The first such additional application using Homomatrix has been initiated within a strategic research alliance with Takeda (Osaka, Japan) in the area of major depressive disorder.

At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in Arabidopsis thaliana

A developmental expression atlas, At-TAX, based on whole-genome tiling arrays, is presented along with associated analysis methods.

Genes and genetic networks responsive to mild hyperthermia in human lymphoma U937 cells

In this study, to better understand the molecular mechanism underlying cellular responses to mild hyperthermia, we investigated gene expression patterns and genetic networks in human myelomonocytic lymphoma U937 cells using high-density oligonucleotide microarrays and computational gene expression analysis tools. The cells were incubated at 41°C for 30 min (mild hyperthermia treatment) and then at 37°C for 0–6 h. Although the mild hyperthermia treatment of the cells did not induce apoptosis, significant increases in the protein expression levels of heat shock proteins (HSPs), namely, Hsp27, Hsp40 and Hsp70, were observed following the activation of heat shock factor-1. Of the 22,283 probe sets analyzed, 423 probe sets were up-regulated and 515 probe sets were down-regulated by >1.5-fold in the cells 3 h post-treatment. Computational gene network analysis demonstrated that the significant genetic network A that contained many HSPs such as DNAJB1, HSPA1A, and HSPA1B was associated with cellular function and maintenance, post-transcriptional modification, or protein folding. Moreover, the significant genetic network B whose core contained v-myc myelocytomatosis viral oncogene homolog (MYC) was associated with cell morphology, cell cycle, and cellular development. The expression levels of nine selected genes were comparable to those determined by microarray analysis with real-time quantitative PCR assay. The present results indicate that mild hyperthermia affects the expression of a large number of genes and provides additional novel insights into the molecular basis of mild hyperthermia in cells.

Molecular mechanism of apoptosis and gene expressions in human lymphoma U937 cells treated with anisomycin

Anisomycin is known as a potent apoptosis inducer by activating JNK/SAPK and inhibiting protein synthesis during translation. However, only few details are known about the mechanism of apoptosis induced by this compound. The present study was undertaken to further elucidate the molecular mechanism of apoptosis and the changes of gene expression elicited by anisomycin using DNA microarrays and computational gene-expression analysis tools in human lymphoma U937 cells. Anisomycin was found to induce apoptosis in time- and concentration-dependent manner as confirmed by phosphatidylserine externalization and DNA fragmentation analysis. Furthermore, anisomycin-treated cells also showed caspase-8 activation, mitochondrial membrane potential collapse, Bid activation, caspase-3 cleavage and cytochrome c release into the cytosol. In the gene-expression analysis, six gene clusters were detected. From clusters I and II, three significant genetic networks were identified. Interestingly, many bZIP family transcription factors were observed in the up-regulated genetic networks. Moreover, the expression of protein-synthesis-related genes, such as EIF4 family proteins and ribosomal proteins, were inhibited. This finding could explain the reason why anisomycin inhibits the protein synthesis at the translation steps. These results provide novel information for understanding the molecular mechanism of apoptosis induced by anisomycin.

Genomic resources for songbird research and their use in characterizing gene expression during brain development

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3' ends. A web-based database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30-50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis.

Identification of genes responsive to paeoniflorin, a heat shock protein-inducing compound, in human leukemia U937 cells

Purpose and background: Paeoniflorin (PF) isolated from peony root (Paeoniae radix) has been used as a herbal medicine in East Asia for its anti-allergic, anti-inflammatory, and immunoregulatory effects. PF is known to cause apoptosis and to be a chemical heat shock protein (HSP) inducer. With this information, the effects on the gene expression in human leukemia U937 cells treated with PF were investigated.Methods: U937 cells, a human myelomonocytic cell line, were treated with PF at different concentrations (0–640 µg/ml). Expression level of Hsp70 was monitored by Western blotting. Gene expression was evaluated using high-density oligonucleotide microarrays and computational gene expression analysis tools and the results were verified by real-time quantitative PCR.Results: Although cell viability was not affected after PF treatment at a high concentration of 640 µg/ml, PF treatment (80–640 µg/ml) significantly elevated Hsp70 expression in a concentration-dependent manner. When the cells were treated with PF (160 µg/ml; 30 min), 35 up-regulated and 29 down-regulated genes were identified. Among the differentially expressed genes, a significant genetic network containing CDC2, FOSL1 and EGR1 was associated with biological functions such as cell death, gene expression or cellular growth and proliferation.Conclusion: The present results indicate that PF affects the expression of many genes including Hsp70 and will provide a better understanding on the molecular mechanism of action of this compound in inducing HSPs in cells.

Robust Sequence Selection Method Used To Develop the FluChip Diagnostic Microarray for Influenza Virus

DNA microarrays have proven to be powerful tools for gene expression analyses and are becoming increasingly attractive for diagnostic applications, e.g., for virus identification and subtyping. The selection of appropriate sequences for use on a microarray poses a challenge, particularly for highly mutable organisms such as influenza viruses, human immunodeficiency viruses, and hepatitis C viruses. The goal of this work was to develop an efficient method for mining large databases in order to identify regions of conservation in the influenza virus genome. From these regions of conservation, capture and label sequences capable of discriminating between different viral types and subtypes were selected. The salient features of the method were the use of phylogenetic trees for data reduction and the selection of a relatively small number of capture and label sequences capable of identifying a broad spectrum of influenza viruses. A detailed experimental evaluation of the selected sequences is described in a companion paper. The software is freely available under the General Public License at http://www.colorado.edu/chemistry/RGHP/software/.

STEM: a tool for the analysis of short time series gene expression data

BackgroundTime series microarray experiments are widely used to study dynamical biological processes. Due to the cost of microarray experiments, and also in some cases the limited availability of biological material, about 80% of microarray time series experiments are short (3–8 time points). Previously short time series gene expression data has been mainly analyzed using more general gene expression analysis tools not designed for the unique challenges and opportunities inherent in short time series gene expression data.ResultsWe introduce the Short Time-series Expression Miner (STEM) the first software program specifically designed for the analysis of short time series microarray gene expression data. STEM implements unique methods to cluster, compare, and visualize such data. STEM also supports efficient and statistically rigorous biological interpretations of short time series data through its integration with the Gene Ontology.ConclusionThe unique algorithms STEM implements to cluster and compare short time series gene expression data combined with its visualization capabilities and integration with the Gene Ontology should make STEM useful in the analysis of data from a significant portion of all microarray studies. STEM is available for download for free to academic and non-profit users at .

Gene Expression Analysis of Human Tissue from Patients with Cardiomyopathies: A New Tool for Guiding Therapies in the Future?

The complete sequencing of the human genome led to the development of a number of new molecular technologies. DNA microarrays represent an exciting new tool for gene expression analysis in human tissue. Measurements of the expressions of many thousands of genes in parallel is possible now. Microarrays may be used for various applications in medicine. They can be used to find novel prognostic and predictive markers as well as new disease classifications into clinically relevant subgroups. While there has been great progress in cancer research in this field, there are significantly less expression data available concerning the heart. In order to identify genes and pathways involved in the pathogenesis of cardiomyopathies, we have looked recently for alterations at cellular and molecular levels in heart tissue from cardiomyopathy patients. We showed that a special group of genes is differentially regulated in dilated cardiomyopathy. The first results in hypertrophic cardiomyopathy also showed similar findings. The surgeon's role in the clinical application of gene expression profiling is crucial. He provides a link between the patient and the laboratory scientists playing a significant role in focusing research on the clinically relevant problems. Gene expression profiles may help to better characterize the course and prognosis of the individual patient in the future. The long-term goal is to find a tool that will help to guide medical and surgical therapies in cardiomyopathies and other heart diseases.

Small Interfering RNA and Gene Expression Analysis Using a Multiplex Branched DNA Assay without RNA Purification

The authors have developed a novel multiplex detection system that quantitatively measures the expression level of 11 messenger RNAs (mRNAs) directly from cell lysates or tissue homogenates without RNA purification. The system incorporates branched DNA (bDNA) technology from Bayer and a multiplex bead array platform from Luminex. In this study, a 21-nt synthetic small interfering RNA (siRNA; specifically designed to knockdown interleukin-8 [IL-8] expression) was delivered into HeLa cells. Using the multiplex bDNA assay, gene expression levels were measured simultaneously from cell lysates for 11 genes. After treating the HeLa cells for 20 h with phorbol myristate acetate (PMA), IL-8 mRNA levels were induced by almost 50-fold; transfection with 30 nM IL-8-specific siRNA reduced the PMA-induced IL-8 mRNA by 80%. In addition, PMA induced mRNA expression in IL-1alpha (3-fold) and IL-6 (4-fold); however, the IL-8 siRNA did not affect the expression of either of these 2 cytokine genes, indicating that the siRNA was selective for IL-8 mRNA expression. Three housekeeping genes' expression levels were measured under all conditions tested. The multiplex bDNA assay provides a powerful tool for quantitative multiplex gene expression analysis directly from cell lysates, which could be extremely valuable for conservation of rare or difficult-to-obtain samples.

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

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

Genetic dissection of gene expression observed in whole blood samples of elderly Danish twins

The microarray technique is an important tool in gene expression analysis to study the activities of thousands of genes measured by their transcript levels under disease or laboratory controlled experimental conditions. Recent studies have suggested a genetic component in the variations of gene expression thus indicating the important role of genetic control over gene activities. In this study, we analyze and report the twin correlation on gene expression in whole blood samples of six female Danish twin pairs aged from 81 to 85 years. We studied the expression phenotype by treating the measured gene expression as a quantitative trait and introducing analytical approaches including the traditional twin methods in population genetics and the multivariate statistical methods. Using this combinatory approach, we were able to estimate and compare the twin correlation on the expression phenotype while accounting for systematic influence in microarray experiments. Analyses on our twin data detected a significant correlation on the expression levels of the actively regulated genes in both monozygotic and dizygotic twins, which is more pronounced in monozygotic twins. Gene ontology analysis has shown that these actively regulated genes are predominantly involved in defense and immune responses against antigenic stimulus. In conclusion, the correlation patterns revealed in our twin data provide evidence of the existence of a heritable mechanism in gene expression regulation persistently functioning even in aged subjects.

Microgenomics: gene expression analysis at the tissue-specific and single-cell levels

Plant organs are composed of many different cell types and the analysis of 'bulk' material results in the average of all information in these cells. Therefore, this does not reflect any individuality of the tissues present in plants. This review briefly summarizes different sampling methods which provide tissue- and cell-specific samples, respectively. In addition, gene expression analysis tools that allow the analysis of transcripts in minute samples are discussed in detail. The combination of both approaches results in high resolution gene expression data, which increases understanding of plant physiology in such diverse areas as primary and secondary metabolism, plant defence or stress response.