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PubMed2007

Gene expression analysis of TFII-I modulated genes in mouse embryonic fibroblasts.

TFII-I is a founding member of a family of helix-loop-helix transcription factors involved in modulation of genes through interaction with various nuclear factors and chromatin remodeling complexes. Recent studies indicate that TFII-I performs important function in cell physiology and mouse embryogenesis. In order to understand its molecular role, TFII-I was overexpressed in primary mouse embryonic fibroblasts (MEFs) and alterations in gene expression were monitored with a mouse 16 K oligonucleotide microarray. These studies allowed us to identify genes that lie downstream of TFII-I-dependent pathways. Among the modulated candidates were genes involved in the immunity response, catalytic activity, signaling pathways and transcriptional regulation. Expression of several candidates including those for the interferon-stimulated protein (G1p2), small inducible cytokine A7 (Ccl7), ubiquitin-conjugating enzyme 8 (Ube2l6), cysteine-rich protein (Csrp2) and Drosophila delta-like 1 homolog (Dlk1) were confirmed by real-time PCR. The obtained results suggest that TFII-I participates in multiple signaling and regulatory pathways in MEFs.

Animals↗
PubMed1997

Switching of gene expression: analysis of the factors that spatially and temporally regulate plant gene expression.

In this chapter, we have reviewed the present research and understanding of several families of transcription factors in plants. From this information, it appears there is good conservation between the types of transcription factors in plants and animals. However, there are several types of factors which have been isolated in plants that remain to be documented in animals (e.g., HD-Zip and GT). These as well as the presence of two types of TATA-binding proteins (TBPs) in plants suggest that although transcription in eukaryotes is highly conserved, fundamental differences may exist. Despite the differences, the modes of regulating transcription are well conserved. Figure 3 summarizes these modes of regulation. In recent years, the role of chromatin structure as well as subcellular localization have been the focus of a vast amount of research in mammals, Drosophila and yeast. However, very little research in these areas has been done in plants. Isolation of genes such as Curly leaf suggest a conservation of genes that influence the formation of heterochromatin-like structures. Whether or not this gene influences chromatin/heterochromatin structure in plants, however, remains to be tested. The study of nuclear localization of factors such as COP1 and KN1 is now leading to models for regulating nuclear transport as well as intercellular transport of transcription factors. Further study of the inter- and intracellular movement of these and other transcription factors may provide information on new modes of regulating transcription. In addition to understanding the role chromatin structure and subcellular localization of transcription factors may have on transcription initiation, the biological role of many plant transcription factors remains to be identified. Several approaches may be taken to understand the mechanisms by which transcription factors influence biochemical and physiological processes in the plant. These steps include 1) identification of the DNA-binding sites of the factors as well as the promoter regions which contain these sites. Presently, this approach is limiting in that not many non-coding regions have been sequenced and characterized in detail. Furthermore, the presence of a putative binding site within a promoter does not necessarily indicate that the factor will bind to the site in vivo. 2) Analysis of the binding affinity for a particular factor to a binding site in comparison to other related factors, via in vitro competition assays and quantitative titrations. This will provide information on how strongly these factors are binding to the sites, but without knowledge of all the factors present in a single cell it is difficult to recreate the in vivo conditions. 3) Generation of transgenic plants or microinjection of DNA/RNA to express a particular factor ectopically, reduce expression of the factor via antisense expression, and creation of dominant negative mutants by overexpression of key dimerization domains may provide information concerning what biological pathways these factors influence. 4) Isolation of mutations in particular transcription factors has been extremely informative in floral development. However, this approach usually entails isolation of a mutant due to a phenotype and eventual mutated locus. The cloning of the locus may or may not involve a transcription factor. 5) Many plant transcription factors have been isolated via sequence similarity to other previously identified and/or characterized transcription factors. However, the biological role of may of these factors is not known. In addition to ectopic expression of these factors by creating transgenic plants, isolation of a loss-of-function mutation may provide valuable information concerning the role of this factor in vivo. Many loss-of-function mutations in MADS box genes have led to a better understanding of how the MADS domain proteins interact with one another as well as how they influence floral development. (ABSTRACT TRUNCATED)

Cell Compartmentation↗
PubMed2005

Gene expression analysis using a modified HiCEP method applicable to prokaryotes: a study of the response of Rhodococcus to isoniazid and ethambutol.

We established a novel method to analyze the gene expression of prokaryotes by modifying and optimizing the HiCEP (high coverage gene expression analysis) method, which was originally developed for eukaryotic gene expression profiling. Following the removal of abundant rRNA, the mRNA of prokaryotic cells was enzymatically polyadenylated and subjected to HiCEP analysis. This method was highly reproducible due to selective PCR that was performed by using adaptor specific primers. We confirmed induction of tipA and induction or suppression of cspA, which are genes that are obtained from distinctive actinomycetes and responded to thiostrepton and temperature stress, respectively. Further, we applied this method to explore the gene expression profile of Rhodococcus erythropolis in response to drugs that inhibit cell wall synthetic pathways, and we were able to identify 35 upregulated genes. Among these genes, we confirmed the upregulation of 22 genes by using RT-PCR (reverse transcriptase-polymerase chain reaction). Some of these genes are involved in the synthesis of mycolic acid and arabinogalactan, suggesting a cell response to drug treatment by regulation of the genes involved in cell wall synthesis. This method could prove to be a useful technique for gene expression analysis of prokaryotes, particularly nonmodel strains with unknown genome sequences.

Antitubercular Agents↗
PubMed2002

Large-scale gene expression analysis in molecular target discovery.

The evolution of simple arrays consisting of a few genes to ones composed of thousands of genes and/or ESTs has allowed investigators unprecedented views of the molecular mechanisms within cells. Due to the enormous quantities of information derived from microarray analysis, new types of problems have surfaced, such as where to store all of the data. The ability to solve database or statistical problems has required the bench biologist to collaborate with database developers, software designers and statisticians to determine solutions for storage, analysis and interpretation of microarray data. The collaborative effort between these extremely diverse disciplines has led to the development of creative database query and gene expression analysis tools, producing significant reductions in the time required by researchers to filter through the datasets and discover the key processes perturbed by the diseases of interest. Both unsupervised and supervised analysis methods have been applied to gene expression data leading to the discovery of novel therapeutic targets and diagnostic markers. Furthermore, tumor classification based on their respective molecular fingerprints has led to the classification of cancer subtypes and the discovery of novel molecular taxonomies that may eventually lead to improved patient stratification and superior therapeutic strategies.

Databases, Factual↗
PubMed2004

Genome-wide gene expression analysis for induced ischemic tolerance and delayed neuronal death following transient global ischemia in rats.

Genome-wide gene expression analysis of the hippocampal CA1 region was conducted in a rat global ischemia model for delayed neuronal death and induced ischemic tolerance using an oligonucleotide-based DNA microarray containing 8,799 probes. The results showed that expression levels of 246 transcripts were increased and 213 were decreased following ischemia, corresponding to 5.1% of the represented probe sets. These changes were divided into seven expression clusters using hierarchical cluster analysis, each with distinct conditions and time-specific patterns. Ischemic tolerance was associated with transient up-regulation of transcription factors (c-Fos, JunB Egr-1, -2, -4, NGFI-B), Hsp70 and MAP kinase cascade-related genes (MKP-1), which are implicated cell survival. Delayed neuronal death exhibited complex long-lasting changes of expression, such as up-regulation of proapoptotic genes (GADD153, Smad2, Dral, Caspase-2 and -3) and down-regulation of genes implicated in survival signaling (MKK2, and PI4 kinase, DAG/PKC signaling pathways), suggesting an imbalance between death and survival signals. Our study provides a differential gene expression profile between delayed neuronal death and induced ischemic tolerance in a genome-wide analysis, and contributes to further understanding of the complex molecular pathophysiology in cerebral ischemia.

Animals↗
PubMed2004

Multi-tissue gene-expression analysis in a mouse model of thyroid hormone resistance.

BACKGROUND: Resistance to thyroid hormone (RTH) is caused by mutations of the thyroid hormone receptor beta (TRbeta) gene. To understand the transcriptional program underlying TRbeta mutant-induced phenotypic expression of RTH, cDNA microarrays were used to profile the expression of 11,500 genes in a mouse model of human RTH. RESULTS: We analyzed transcript levels in cerebellum, heart and white adipose tissue from a knock-in mouse (TRbetaPV/PV mouse) that harbors a human mutation (referred to as PV) and faithfully reproduces human RTH. Because TRbetaPV/PV mice have elevated thyroid hormone (T3), to define T3-responsive genes in the context of normal TRbeta, we also analyzed T3 effects in hyperthyroid wild-type gender-matched littermates. Microarray analysis revealed 163 genes responsive to T3 treatment and 187 genes differentially expressed between TRbetaPV/PV mice and wild-type littermates. Both the magnitude and gene make-up of the transcriptional response varied widely across tissues and conditions. We identified genes modulated in T3-dependent PV-independent, T3- and PV-dependent, and T3-independent PV-dependent pathways that illuminated the biological consequences of PV action in vivo. Most T3-responsive genes that were dysregulated in the heart and white adipose tissue of TRbetaPV/PV mice were repressed in T3-treated wild-type mice and upregulated in TRbetaPV/PV mice, suggesting the inappropriate activation of T3-suppressed genes in RTH. CONCLUSIONS: Comprehensive multi-tissue gene-expression analysis uncovered complex multiple signaling pathways that mediate the molecular actions of TRbeta mutants in vivo. In particular, the T3-independent mutant-dependent genomic response unveiled the contribution of a novel 'change-of-function' of TRbeta mutants to the pathogenesis of RTH. Thus, the molecular actions of TRbeta mutants are more complex than previously envisioned.

Adipose Tissue↗
PubMed2006

Identification of genes responsive to gamma radiation in rat hepatocytes and rat liver by cDNA array gene expression analysis.

The mechanisms underlying hepatocellular damage after irradiation are obscure. We identified genes induced by radiation in isolated rat hepatocytes in vitro by cDNA array gene expression analysis and then screened in vivo experiments with those same genes using real-time PCR and Western blotting. Hepatocytes were irradiated and cDNA array analyses were performed 6 h after irradiation. The mRNA of differentially expressed genes was quantitatively analyzed by real-time PCR. cDNA array analyses showed an up-regulation of 10 genes in hepatocytes 6 h after irradiation; this was confirmed by real-time PCR. In vivo, rat livers were irradiated selectively. Treated and sham-irradiated controls were killed humanely 1, 3, 6, 12, 24 and 48 h after irradiation. Liver RNA was analyzed by real-time PCR; expression of in vivo altered genes was also analyzed at the protein level by Western blotting. Up-regulation was confirmed for three of the in vitro altered genes (multidrug resistance protein, proteasome component C3, eukaryotic translation initiation factor 2). Histologically, livers from irradiated animals were characterized by steatosis of hepatocytes. Thus we identified genes that may be involved in liver steatosis after irradiation. The methods shown in this work should help to further clarify the consequences of radiation exposure in the liver.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2004

Global gene expression analysis of the developing postnatal mouse retina.

PURPOSE: Postnatal mouse retinal development involves glial and neuronal differentiation, vascularization, and the onset of vision. In the current study, the gene expression profiles of thousands of genes in the developing postnatal mouse retina were analyzed and compared in a large-scale, unbiased microarray gene expression analysis. METHODS: For each of eight different time points during postnatal mouse retinal development, two separate sets of 30 retinas were pooled for RNA isolation, and gene expression was analyzed by hybridization to gene chips in triplicate (Mu74Av2; Affymetrix, Santa Clara, CA). Genes were sorted into clusters based on their expression profiles and intensities. Validation was accomplished by comparing the microarray expression profiles with real-time RT-PCR analysis of selected genes and by comparing selected expression profiles with predicted profiles based on previous studies. RESULTS: The Mu74Av2 chip contains more than 6000 known genes and 6500 estimated sequence tags (ESTs) from the mouse Unigene database. Of these, 2635 known gene sequences and 2794 ESTs were expressed at least threefold above background levels during retinal development. Expressed genes were clustered based on expression profiles allowing potential functions for specific genes during retinal development to be inferred by comparison to developmental events occurring at each time point. Specific data and potential functions for genes with various profiles are discussed. All data can be viewed online at http://www.scripps.edu/cb/friedlander/gene_expression/. CONCLUSIONS: Expression analysis of thousands of different genes during normal postnatal mouse retinal development as reported in this study demonstrates that such an approach can be used to correlate gene expression with known functional differentiation, presenting the opportunity to infer functional correlates between gene expression and specific postnatal developmental events.

Animals↗
PubMed2004

Gene expression analysis of the late embryonic mouse cerebral cortex using DNA microarray: identification of several region- and layer-specific genes.

The mammalian neocortex develops layer organizations with regional differences represented by expression of multiple genes at embryonic stages. These genes could play important roles in the formation of areal cyto-architecture, yet, the number of genes identified so far is not sufficient to explain such intricate processes. Here we collected five regions--the medial, dorsal, lateral, rostral and occipital--from the dissected E16.5 mouse cerebral cortex and performed extensive gene expression analysis using the Affymetrix U74Av2 array with probes for 12,500 genes. After relative quantitative analysis, 34, 33 and 15 genes were selected as highly expressed genes in the medial, dorsal and lateral regions, respectively. The combination of GeneChip system, real-time quantitative reverse transcription polymerase chain reaction and in situ hybridization analyses allowed the successful identification of seven genes from the dorsal region (Neuropeptide Y, Wnt7b, TGF-beta RI, Nrf3, Bcl-6, MT4-MMP and Rptp kappa), three genes from the medial region (Hop-pending, HtrA and Crystallin), and three genes from the lateral region (Somatostatin, Ngef and Fxyd7). Particularly, all seven genes identified in the dorsal region demarcated the future somatosensory and auditory areas in the cortical plate with high rostrolateral-low caudomedial gradation. Their expression patterns were not uniform, but delineated either the superficial or the deep layer in the cortical plate. Furthermore, the regional expression pattern of Neuropeptide Y was shifted rostrally and the layer specificity was disorganized in the Pax6-deficient mice. Our results provide new information about a subclass of regionally expressed genes in the cortical plate at the late embryonic stage, which may help understand the molecular mechanisms of neocortical arealization.

Animals↗
PubMed2006

Gene expression analysis of cardiovascular diseases: novel insights into biology and clinical applications.

Although the contribution of genetics to complex cardiovascular diseases such as atherosclerosis has been accepted for quite some time, full and detailed knowledge of the individual causative genes has been elusive. With the advent of genomic technologies and methods, the necessary tools are now available to begin pinpointing the genes that contribute to disease susceptibility and progression. One approach being applied extensively in candidate gene discovery is gene expression analysis of human and animal tissues using microarrays. The genes identified by these genomic studies provide valuable insight into disease biology and represent the initial steps toward the development of diagnostic tests and therapeutic strategies that will substantially improve human health. This paper highlights the progress that has been made in using gene expression analysis cardiovascular genomic research and the potential for applying these findings in clinical medicine.

Animals↗
PubMed2001

An integrated approach for genome-wide gene expression analysis.

Since efficient and relatively cheap methods were developed for determining biosequences, a lot of biosequence data has been generated. As the main problem in molecular biology is the analysis of the data instead of the data acquisition, part of the study of computational biology is to extract all kinds of meaningful information from the sequences. Computer-assisted methods have become very important in analyzing biosequence data. However, most of the current computer-assisted methods are limited to finding motifs. Genes can be regulated in many ways, including combinations of regulatory elements. This research is aimed at developing a new integrated system for genome-wide gene expression analysis. This research begins with a new motif-finding method, using a new objective function combining multiple well defined components and an improved stochastic iterative sampling strategy. Combinatorial motif analysis is accomplished by constructive induction that analyzes potential motif combinations. We then apply standard inductive learning algorithms to generate hypotheses for different gene behaviors. A genome-wide gene expression analysis demonstrated the value of this novel integrated system.

Algorithms↗
PubMed1997

Yeast microarrays for genome wide parallel genetic and gene expression analysis.

We have developed high-density DNA microarrays of yeast ORFs. These microarrays can monitor hybridization to ORFs for applications such as quantitative differential gene expression analysis and screening for sequence polymorphisms. Automated scripts retrieved sequence information from public databases to locate predicted ORFs and select appropriate primers for amplification. The primers were used to amplify yeast ORFs in 96-well plates, and the resulting products were arrayed using an automated micro arraying device. Arrays containing up to 2,479 yeast ORFs were printed on a single slide. The hybridization of fluorescently labeled samples to the array were detected and quantitated with a laser confocal scanning microscope. Applications of the microarrays are shown for genetic and gene expression analysis at the whole genome level.

Cold Temperature↗
PubMed2004

Gene expression analysis of an integrin family of genes by systematic multiplex reverse transcription-polymerase chain reaction.

We have established the systematic multiplex reverse transcription-polymerase chain reaction (SM RT-PCR) system of 26 members of the integrin family of genes, and used this system to investigate their expression in 25 different kinds of human adult tissues. A hierarchical clustering analysis of the tissue expression data illustrated clustering of functionally related tissues. Although the correlation was weak, bone marrow, thymus, and spleen were clustered, potentially confirming the role of certain integrin molecules in the immune response. We also investigated changes in integrin gene expression in cancer. Several differences were observed between normal and tumor, as well as between normal and cancer cell lines. The SM RT-PCR experiments for the study of alternative splicing showed that most of the integrin genes analyzed exhibited fixed ratios of differentially spliced transcripts probably due to a tissue-independent mechanism of splicing predetermined by the nucleotide sequences around the splicing donor and acceptor sites.

Animals↗
PubMed2002

Gene expression analysis reveals chemical-specific profiles.

The articles highlighted in this issue are "Gene Expression Analysis Reveals Chemical-Specific Profiles" by Hisham K. Hamadeh, Pierre R. Bushel, Supriya Jayadev, Karla Martin, Olimpia DiSorbo, Stella Sieber, Lee Bennett, Raymond Tennant, Raymond Stoll, J. Carl Barrett, Kerry Blanchard, Richard S. Paules, and Cynthia A. Afshari (pp. 219-231) and "Prediction of Compound Signature Using High Density Gene Expression Profiling" by Hisham K. Hamadeh, Pierre R. Bushel, Supriya Jayadev, Olimpia DiSorbo, Leping Li, Raymond Tennant, Raymond Stoll, J. Carl Barrett, Richard S. Paules, Kerry Blanchard, and Cynthia A. Afshari (pp. 232-240).

Animals↗
PubMed2003

Role of immunoreactions and mast cells in pathogenesis of human endometriosis--morphologic study and gene expression analysis.

STUDY OBJECTIVES: To investigate the pathophysiology of human endometriosis, we examined by morphological and molecular biological methods. METHODS: Samples of ovarian endometriosis and normal ovarian tissues were obtained laparoscopically after informed consent. A morphological study by toluidine blue staining, immunohistochemistry of c-kit and electron microscopy demonstrated the localization of mast cells in the stromal lesions of endometriosis. Oligonucleotide microarrays were used for gene expression analysis. RESULTS: Infiltration of numerous mast cells and development of fibrosis was observed throughout the stromal lesions. Gene expression analysis by oligonucleotide microarrays indicated inflammatory immunoreactions in the lesions. Expressions of the FCER1G and PGDS, which are considered to be mast cell-specific genes, were upregulated in the ovarian endometriotic lesions as compared to the normal ovarian tissues. Furthermore, expressions of genes associated with immunological inflammation, such as IL-8, GRO1, GRO2, CXCR4, MCP1, and those related to tissue remodeling (MMP, COL4A2, and COL5A2) were also higher in endometriotic lesions than in the normal ovarian tissue. CONCLUSIONS: Thus it is likely that mast cells and their related inflammatory immunoreactions via chemokines play important roles in producing fibrosis and adhesions in endometriotic lesions.

Chemokines↗
PubMed2002

Comprehensive gene expression analysis of prostate cancer reveals distinct transcriptional programs associated with metastatic disease.

The identification of genes that contribute to the biological basis for clinical heterogeneity and progression of prostate cancer is critical to accurate classification and appropriate therapy. We performed a comprehensive gene expression analysis of prostate cancer using oligonucleotide arrays with 63,175 probe sets to identify genes and expressed sequences with strong and uniform differential expression between nonrecurrent primary prostate cancers and metastatic prostate cancers. The mean expression value for >3,000 tumor-intrinsic genes differed by at least 3-fold between the two groups. This includes many novel ESTs not previously implicated in prostate cancer progression. Many differentially expressed genes participate in biological processes that may contribute to the clinical phenotype. One example was a strong correlation between high proliferation rates in metastatic cancers and overexpression of genes that participate in cell cycle regulation, DNA replication, and DNA repair. Other functional categories of differentially expressed genes included transcriptional regulation, signaling, signal transduction, cell structure, and motility. These differentially expressed genes reflect critical cellular activities that contribute to clinical heterogeneity and provide diagnostic and therapeutic targets.

Adult↗
PubMed2004

Global gene expression analysis by combinatorial optimization.

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Res. 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

Algorithms↗
PubMed2002

Gene expression analysis of prostate cancers.

Prostate cancer is a biologically heterogeneous disease with considerable variation in clinical aggressiveness. The behavior of prostate cancer can be considered a direct or indirect result of aberrant alterations of gene expression in prostate epithelial cells. Identification of the patterns of gene-expression alterations that are related to the aggressiveness of prostate cancers will greatly assist the development of tools for early detection of prostate cancers with poor clinical outcome and identification of targets for future therapeutic intervention. To detect the patterns of gene-expression alterations of prostate cancers, we performed a comprehensive gene-expression analysis on 30 prostate tissues of various levels of invasiveness (ranging from those confined to the organ to distant metastases) and Gleason grades (combined scores 4-9), using the Affymetrix chip set Hu35k (A-D) and U95a. Following three sequential selection screens, we identified 84 largely novel genes and expressed sequence tag (EST) sequences whose expression levels were altered significantly in prostate cancer samples compared with control normal tissues. In addition, the expression levels of a group of 12 genes and EST sequences was found to be altered significantly in aggressive type of prostate cancers but not in organ-confined prostate cancers. Cluster analysis using the 84-gene list showed that the highly aggressive prostate cancers contained gene-expression patterns that were distinct from organ-confined prostate cancers.

Cluster Analysis↗