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At least 613 records · Page 34Linked to original sources
PubMed2003

A new tool for rheumatology: large-scale analysis of gene expression.

Large-scale analysis of gene expression with cDNA arrays is spreading over many biological fields, including rheumatology. In this report, we wish to explain the principle and main advantages of this tool in the context of our discipline. Until 1995, analysis of gene expression was conducted for a few genes at a time but DNA chips now allow one to monitor the expression of thousands of genes in a single experiment and analyze the transcriptome, i.e. the whole of the transcripts in a given cell or tissue. Whatever the platform used (macro- or microarrays, oligo-chips), this technology rests upon the hybridization of i) a set of cDNA clones tethered to a solid support (nylon or glass) as probes, and ii) labelled cDNAs that are reverse-transcribed from bulk mRNAs extracted from a cell or tissue sample as a target. The end result is information on the relative abundance of every mRNA between two or more samples. The transcriptome analysis has two main objectives in rheumatology: i) identifying a gene expression profile that is a hallmark of a pathology and using it for a diagnostic or prognostic purpose, and ii) gathering genes with similar changes of expression, which allows one to specify the identity of novel proteins involved in a well-known intracellular cascade of regulation or even to identify new cascades.

Arthritis, Rheumatoid↗
PubMed2005

cDNA expression array analysis of gene expression in human hepatocarcinoma Hep3B cells induced by BNIPL-1.

Bcl-2/adenovirus E1B 19 kDa interacting protein 2 like-1 (BNIPL-1) is a novel human protein identified in our laboratory, which can interact with Bcl-2 and Cdc42GAP and induce apoptosis via the BNIP-2 and Cdc42GAP homology (BCH) domain. In the present study, we established the Hep3B-Tet-on stable cell line in which expression of BNIPL-1 can be induced by doxycycline. The cell proliferation activity assay showed that the overexpression of BNIPL-1 suppresses Hep3B cell growth in vitro. The differential expression profiles of 588 known genes from BNIPL-1-transfected Hep3B-Tet-on and vector control cells were determined using the Atlas human cDNA expression array. Fifteen genes were differentially expressed between these two cell lines, among which seven genes were up-regulated and eight genes were down-regulated by BINPL-1. Furthermore, the differential expression result was confirmed by semiquantitative RT-PCR. Among these differentially expressed genes, p16INK4, IL-12, TRAIL and the lymphotoxin beta gene involved in growth suppression or cell apoptosis were up-regulated, and PTEN involved in cell proliferation was down-regulated by BNIPL-1. These results suggest that BNIPL-1 might inhibit cell growth though cell cycle arrest and/or apoptotic cell death pathway(s).

Carcinoma, Hepatocellular↗
PubMedDate not supplied

Gene expression profiling of human diseases by serial analysis of gene expression.

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.

Gene Expression↗
PubMed2004

Gene expression profiling of human erythroid progenitors by micro-serial analysis of gene expression.

We compared the expression profiles of highly purified human CD34+ cells and erythroid progenitor cells by micro-serial analysis of gene expression (microSAGE). Human CD34+ cells were purified from granulocyte colony-stimulating factor-mobilized blood stem cells, and erythroid progenitors were obtained by cultivating these cells in the presence of stem cell factor, interleukin 3, and erythropoietin. Our 10,202 SAGE tags allowed us to identify 1354 different transcripts appearing more than once. Erythroid progenitor cells showed increased expression of LRBA, EEF1A1, HSPCA, PILRB, RANBP1, NACA, and SMURF. Overexpression of HSPCA was confirmed by real-time polymerase chain reaction analysis. MicroSAGE revealed an unexpected preferential expression of several genes in erythroid progenitor cells in addition to the known functional genes, including hemoglobins. Our results provide reference data for future studies of gene expression in various hematopoietic disorders, including myelodysplastic syndrome and leukemia.

Antigens, CD34↗
PubMed2006

Microarray analysis distinguishes differential gene expression patterns from large and small colony Thymidine kinase mutants of L5178Y mouse lymphoma cells.

BACKGROUND: The Thymidine kinase (Tk) mutants generated from the widely used L5178Y mouse lymphoma assay fall into two categories, small colony and large colony. Cells from the large colonies grow at a normal rate while cells from the small colonies grow slower than normal. The relative proportion of large and small colonies after mutagen treatment is associated with a mutagen's ability to induce point mutations and/or chromosomal mutations. The molecular distinction between large and small colony mutants, however, is not clear. RESULTS: To gain insights into the underlying mechanisms responsible for the mutant colony phenotype, microarray gene expression analysis was carried out on 4 small and 4 large colony Tk mutant samples. NCTR-fabricated long-oligonucleotide microarrays of 20,000 mouse genes were used in a two-color reference design experiment. The data were analyzed within ArrayTrack software that was developed at the NCTR. Principal component analysis and hierarchical clustering of the gene expression profiles showed that the samples were clearly separated into two groups based on their colony size phenotypes. The Welch T-test was used for determining significant changes in gene expression between the large and small colony groups and 90 genes whose expression was significantly altered were identified (p < 0.01; fold change > 1.5). Using Ingenuity Pathways Analysis (IPA), 50 out of the 90 significant genes were found in the IPA database and mapped to four networks associated with cell growth. Eleven percent of the 90 significant genes were located on chromosome 11 where the Tk gene resides while only 5.6% of the genes on the microarrays mapped to chromosome 11. All of the chromosome 11 significant genes were expressed at a higher level in the small colony mutants compared to the large colony mutants. Also, most of the significant genes located on chromosome 11 were disproportionally concentrated on the distal end of chromosome 11 where the Tk mutations occurred. CONCLUSION: The results indicate that microarray analysis can define cellular phenotypes and identify genes that are related to the colony size phenotypes. The findings suggest that genes in the DNA segment altered by the Tk mutations were significantly up-regulated in the small colony mutants, but not in the large colony mutants, leading to differential expression of a set of growth regulation genes that are related to cell apoptosis and other cellular functions related to the restriction of cell growth.

Animals↗
PubMed2003

Characterization of the gene expression profile of neuroblastoma cell line IMR-5 using serial analysis of gene expression.

The serial analysis of gene expression (SAGE) technique was used to generate a database of the most abundant transcripts of the MYCN-amplified neuroblastoma cell line IMR-5. A total of 8568 tags were sequenced and shown to represent 4034 unique tags, each of which corresponds to an individual transcript. Expression levels of genes are reflected by the frequency of occurrence of the respective tags. To validate fidelity of SAGE data, relative abundances of seven transcripts were evaluated by semiquantitative reverse transcriptase-polymerase chain reaction. Transcripts that were detected nine times or more (>0.1% of the total tag population) accounted for 36% of the total messenger RNA mass but only 3% of the total number of individual transcripts. A strong preponderance of genes involved in protein synthesis, in particular those encoding for ribosomal proteins, were observed among these high-abundance transcripts. Tags corresponding to the amplified gene DDX1 were conspicuously overrepresented in comparison to the other amplified genes MYCN, neuroblastoma amplified gene and MEIS1, which suggests an additional mechanism apart from genomic amplification contributing to the strong upregulation of this gene. This study provides a comprehensive gene expression profile of neuroblastoma cell line IMR-5 and may be used as a reference database for identification of candidate genes that are involved in etiology and pathogenesis of neuroblastoma.

Databases as Topic↗
PubMed2004

Incidence of "quasi-ditags" in catalogs generated by Serial Analysis of Gene Expression (SAGE).

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files; however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags ("quasi-ditags"). RESULTS: We provide examples of quasi-ditags that originate from cloning and sequencing artifacts (i.e. genomic contamination or random combinations of nucleotides) that are included in SAGE libraries. We have employed a mathematical model to predict the frequency of quasi-ditags in random nucleotide sequences, and our data show that clones containing less than or equal to 2 ditags (which include chromosomal cloning artifacts) should be excluded from the analysis of SAGE catalogs. CONCLUSIONS: Cloning and sequencing artifacts contaminating SAGE libraries could be eliminated using simple pre-screening procedure to increase the reliability of the data.

Animals↗
PubMed2004

Cloning of apoptosis-related genes by representational difference analysis of cDNA.

Apoptosis is frequently triggered by events that alter the expression of key target genes. Under these circumstances, the genes involved can be identified by techniques that analyze gene expression. Researchers now have a choice of reliable and effective methods for differential gene expression analysis. Comparative approaches, including gene microarray analysis, serial analysis of gene expression, and differential display provide global information about expression levels. Subtractive approaches like complementary DNA representational difference analysis (cDNA RDA) and suppression subtraction polymerase chain reaction identify a focused set of differentially expressed genes. The most suitable technique to apply depends on individual circumstances. cDNA RDA is particularly useful in nonstandard model organisms for which comprehensive gene microarrays are not available and is best used for the identification of genes with a large difference in expression levels between two populations. The technique involves the generation of amplified mixtures of cDNA fragments that are typically smaller than 1000 base pairs and represent >86% of mRNA species from each starting population. Transcriptional differences between two populations can then be identified by subtraction of cDNA amplicons followed by further polymerase chain reaction amplification. The technique is capable of detecting differences for genes expressed at less than one copy per cell and is achievable using standard laboratory apparatus. cDNA RDA can identify genes not previously described in the database, can detect low abundance transcripts (e.g., from mixed cell populations), and is best applied in experiments where relatively few differentially expressed genes are expected. Here, we describe the application of cDNA RDA to the identification of apoptosis-related genes.

Animals↗
PubMed2005

Genome-wide differences between microsatellite stable and unstable colorectal tumors.

Genomic copy number changes are frequently found in cancers and they have been demonstrated to contribute to carcinogenesis; and it is widely accepted that tumors with microsatellite instability (MSI) are genetically stable and mostly diploid. In the present study we compared the copy number alterations and the gene-expression profiles of microsatellite stable (MSS) and MSI colorectal tumors. A total number of 31 fresh-frozen primary tumors (16 MSS and 15 MSI) were used. Twenty-eight samples (15 MSS and 13 MSI) were analyzed with metaphase comparative genomic hybridization (CGH), nine of which plus one additional sample (4 MSS and 6 MSI) were further analyzed by cDNA-based array-CGH. Gene expression analysis was performed with six samples [3 MSS and 3 MSI, four of these used in metaphase CGH (mCGH) analysis] to identify differentially expressed genes possibly located in the lost or amplified regions found by CGH, stressing the biological significance of copy number changes. Metaphase and array-CGH analysis of two colon cancer cell lines (HTC116 and SW480, reported as MSI and MSS archetypes) gave comparable results. Alterations found by mCGH in MSS tumors were +20, +8q, -8p and -18q. Interestingly, 1p22, 4q26 and 15q21 were found deleted preferentially in MSS tumors, while 22q13 was found gained in MSI tumors. The regions of alterations identified by array-CGH were gains at 8q24, 16q24.3 and 20q13, and the loss of 5q21, appearing in the both types of tumors. Gene expression analysis revealed genes with specific associations with the copy number changes of the corresponding genomic regions. As a conclusion, colorectal cancer is a heterogeneous disease, demonstrated by the genomic profiles of individual samples. However, our data shows that copy number changes do not occur exclusively in the MSS phenotypes.

Aged↗
PubMed2005

Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays.

Global analysis of gene expression by using DNA microarrays is employed increasingly to search for differences in biological properties between normal and diseased tissue. In such studies, expression that deviates from defined thresholds commonly is used for creating genetic signatures that characterize disease vs. normality. Although it is axiomatic that the threshold parameters applied to microarray analysis will alter the contents of such genetic signatures, the extent to which threshold choice can affect the fundamental conclusions made from microarray-based studies has not been elucidated. We used GABRIEL (Genetic Analysis By Rules Incorporating Expert Logic), a platform of knowledge-based algorithms for the global analysis of gene expression, together with conventional statistical approaches, to examine the sensitivity of conclusions to threshold choice in recently published microarray-based studies. An analysis of the effects of threshold decisions in one of these studies [Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. (2003) Nat. Genet. 33, 49-54], which arrived at the important conclusion that the metastatic potential of primary tumors is encoded by the bulk of cells in the tumor, is the focus of this article. We discovered that support for this conclusion highly depends on the threshold used to create gene expression signatures. We also found that threshold choice dramatically affected the gene function categories represented nonrandomly in signatures. Our results suggest that the robustness of biological conclusions made by using microarray analysis should be routinely assessed by examining the validity of the conclusions by using a range of threshold parameters.

Adenocarcinoma↗
PubMed2004

Mouse testis transcriptome revealed using serial analysis of gene expression.

We applied serial analysis of gene expression (SAGE) to the mouse testis to reveal the global gene expression profile and to identify senescence-dependent changes in that profile. A total of 61,929 SAGE tags, including 19,323 unique tags, were obtained from 3- and 29-month-old BDF1 mice and 14-month-old SAMP1 mice. Genes highly expressed in the testis included those associated with spermatogenesis, protein metabolism, energy metabolism, growth and differentiation, and signal transduction. Testes from old mice of both strains appeared atrophied. Morphological examination of aged testes revealed extremely thin seminiferous epithelia and significantly decreased numbers of spermatids and spermatocytes. Despite the physical deterioration, no gross changes in the gene expression profile were apparent in the testes of old BDF1 mice. However, in 14-month-old SAMP1 mice, protamine 2 gene transcription was approximately 50% lower than in BDF1 mice. This reduction may be associated with the oligozoospermia and early decline in reproductive performance of SAMP1 mice. Our SAGE results are the first quantitative gene expression profile of the mouse testis and provide a reliable transcriptome reference for this organ.

Age Factors↗
PubMed2001

Use of serial analysis of gene expression (SAGE) technology.

Serial analysis of gene expression, or SAGE, is an experimental technique designed to gain a direct and quantitative measure of gene expression. The SAGE method is based on the isolation of unique sequence tags (9-10 bp in length) from individual mRNAs and concatenation of tags serially into long DNA molecules for a lump-sum sequencing. The SAGE method can be applied to the studies exploring virtually any kinds of biological phenomena in which the changes in cellular transcription are responsible. SAGE is a highly competent technology that can not only give a global gene expression profile of a particular type of cell or tissue, but also help us identify a set of specific genes to the cellular conditions by comparing the profiles constructed for a pair of cells that are kept at different conditions. In this review, we present an outline of the original method, several studies achieved by using the method as a major strategic tool, technological difficulties and intrinsic problems that emerged, and improvements and modifications of the method to cope with these drawbacks. We then present our modified SAGE procedure that generates longer sequence tags (14 bp) rather in detail, and the profile (80K profile) derived from HeLa cells that is composed of 80000 tags obtained from a single library. In addition, a series of smaller profiles (2, 4, 10, 20 and 40K) was made by dividing the 80K profile. When we compared these smaller profiles with respect to tag counts for a number of genes, it became apparent that counts of most gene tags increase stably and constantly as the size of profiles increase, while several genes do not. This may be another problem we have to keep in mind, when the profiles are compared for the identification of 'specific genes'.

Animals↗
PubMed1998

Enhanced concatemer cloning-a modification to the SAGE (Serial Analysis of Gene Expression) technique.

The Serial Analysis of Gene Expression (SAGE) method, described in 1995 by Velculescu et al ., represents a powerful means to compare gene expression between two mRNA populations. An improvement to SAGE that removes contaminating linker molecules, which compromise the efficiency of the method, has been developed. This modification utilises biotinylated PCR primers, which generate biotinylated linkers at an early stage in the SAGE protocol, thus allowing removal of the unwanted linkers by binding to streptavidin-coated magnetic beads at a later stage. The application of this modification resulted in the rapid generation of high ditag yields and clones with large average insert sizes.

Base Sequence↗
PubMed2003

Gene expression profiling of resting and activated vascular smooth muscle cells by serial analysis of gene expression and clustering analysis.

Migration and proliferation of vascular smooth muscle cells (SMCs) are key events in atherosclerosis. However, little is known about alterations in gene expression upon transition of the quiescent, contractile SMC to the proliferative SMC. We performed serial analysis of gene expression (SAGE) of cultured, human SMCs, either grown under resting circumstances or activated with an atherogenic stimulus. Analysis of tags, representing 47,209 and 47,259 mRNAs from a library of resting and activated SMCs, respectively, identified 105 tags induced and 52 tags repressed greater than fivefold. To evaluate the relevance in SMC biology of unmatched, regulated tags, we performed hierarchical clustering analysis, based on their expression profiles in public SAGE databases, and clustered these novel genes in distinct groups. The regulation in SMCs was confirmed by Northern blotting for representative genes of these groups. Plasminogen activator inhibitor-2 has not been associated with atherosclerosis before and was localized to atherosclerotic lesions.

Gene Expression↗
PubMed1999

Serial analysis of gene expression: rapid RT-PCR analysis of unknown SAGE tags.

In a pilot study on SAGE on Reed-Sternberg cells we have sequenced 1055 tags representing 701 genes. Screening of the GenBank database resulted in the identification of a corresponding gene or EST for 490 of them. For 211 of the tags no homology could be detected. A major problem of the serial analysis of gene expression (SAGE) approach is how to further analyse the unknown tags. We have developed an RT-PCR-based method, rapid analysis of unknown SAGE tags (RAST-PCR), to analyse the expression of the corresponding genes. This approach can be used as a screening method to investigate whether or not the gene is differentially expressed between several cell types of interest.

Cell Line↗
PubMed2002

Correct identification of genes from serial analysis of gene expression tag sequences.

SAGE (serial analysis of gene expression) is a remarkable technique for genome-wide analysis of gene expression. It is crucial to understand the extent to which SAGE can accurately indicate a gene or expressed sequence tag (EST) with a single tag. We analyzed the effect of the size of SAGE tag on gene identification. Our observation indicates that SAGE tags are in general not long enough to achieve the degree of uniqueness of identification originally envisaged. Our observations also indicate that the limitation of using SAGE tag to identify a gene can be overcome by converting SAGE tags into longer 3' EST sequences with the generation of longer cDNA fragments from SAGE tages for gene identification (GLGI) method.

Expressed Sequence Tags↗
PubMed1999

Rapid analysis of gene expression (RAGE) facilitates universal expression profiling.

Current techniques for analysis of gene expression either monitor one gene at a time, for example northern hybridization or RT-PCR methods, or are designed for the simultaneous analysis of thousands of genes, for example microarray hybridization or serial analysis of gene expression. To provide a flexible, intermediate scale alternative, a PCR-based method for the rapid analysis of gene expression has been developed which allows expression changes to be determined in either a directed search of known genes, or an undirected survey of unknown genes. A single set of reagents and reaction conditions allows analyses of most genes in any eukaryote. The method is useful for assaying on the order of tens to hundreds of genes in multiple samples. Control experiments indicate reliable detection of changes in gene expression 2-fold and greater, and sensitivity of detection better than 1 in 10 000. Analyses of over 400 genes in a mouse system transgenic for the E2F1 gene have identified several new downstream targets of E2F1, including Brca1 and Cdk7, in addition to several unidentified genes that are upregulated in the transgenic mice. Changes in expression of several genes related to apoptosis suggest a possible potentiation of apoptotic pathways in the transgenic keratinocytes.

Animals↗
PubMed2002

Microarray analysis of gene expression in the aging human retina.

PURPOSE: To develop gene expression profiles of young and elderly human retinas and identify candidate genes for aging-associated retinal diseases. METHODS: Gene microarray slides containing 2400 human genes (primarily neuronal) were hybridized to biotin or dinitrophenyl (DNP)-labeled target cDNAs that were synthesized using total RNAs from young (13-14 years) and elderly (62-74 years) human retinas. Hybridization signals were visualized with cyanine (Cy)-5 or Cy-3 fluorescent reporter molecules, and the fluorescence intensities of the images were analyzed by computer. Northern blot analysis and real-time quantitative reverse transcription PCR (qRT-PCR) were performed to validate the microarray results. RESULTS: Of the 2400 genes represented on the microarray slides, more than 50% hybridized to the retinal cDNA targets. Expression of a majority of these genes was not altered during aging; nonetheless, changes in the expression of 24 genes were detected between young and elderly retinas. These genes could be clustered into four categories: energy metabolism, stress response, cell growth, and neuronal transmission/signaling. Northern blot analysis and qRT-PCR results confirmed the changes in expression of 8 of 10 genes examined. CONCLUSIONS: Using commercially available slide microarrays, the authors show that aging of the human retina is associated with changes in patterns of gene expression. This analysis suggests that pathways involved in stress response and energy metabolism play key roles in retinal aging. These studies demonstrate the utility of gene microarrays in identifying global patterns of retinal gene expression and lay the foundation for future studies defining the genetic basis of aging-associated retinal diseases, such as age-related macular degeneration.

Adolescent↗