DNA microarrays and papillary thyroid carcinoma gene expression profile

The paper presents gene expression profile analysis with DNA microarrays and compares two core technological platforms used for this purpose - high density oligonucleotide microarrays and cDNA microarrays. With this background recent results of papillary thyroid carcinoma analysis with DNA microarrays are presented.     

Comparison of gene expression measurements from cDNA and 60-mer oligonucleotide microarrays

As the data generated by microarray technology continue to amass, it is necessary to compare and combine gene expression data from different platforms. To evaluate the performance of cDNA and long oligonucleotide (60-mer) arrays, we generated gene expression profiles for two cancer cell lines and compared the data between the two platforms. All 6182 unique genes represented on both platforms were included in the analysis. A limited correlation (r = 0.4708) was obtained and the difference in measurement of low-expression genes was considered to contribute to the limited correlation. Further restriction of the data set to differentially expressed genes detected in cDNA microarrays (1205 genes) and oligonucleotide arrays (1325 genes) showed modest correlations of 0.7076 and 0.6441 between the two platforms. Quantitative real-time PCR measurements of a set of 10 genes showed better correlation with oligonucleotide arrays. Our results demonstrate that there is substantial variation in the data generated from cDNA and 60-mer oligonucleotide arrays. Although general agreement was observed in measurements of differentially expressed genes, we suggest that data from different platforms could not be directly amassed.     

Selenium stimulates pancreatic beta-cell gene expression and enhances islet function

The present study investigated the role of selenium in the regulation of pancreatic beta-cell function. Utilising the mouse beta-cell line Min6, we have shown that selenium specifically upregulates Ipf1 (insulin promoter factor 1) gene expression, activating the -2715 to -1960 section of the Ipf1 gene promoter. Selenium increased both Ipf1 and insulin mRNA levels in Min6 cells and stimulated increases in insulin content and insulin secretion in isolated primary rat islets of Langerhans. These data are the first to implicate selenium in the regulation of specific beta-cell target genes and suggest that selenium potentially promotes an overall improvement in islet function.     

Genome analysis with gene expression microarrays

Advances in biochemistry, chemistry and engineering have enabled the development of a new gene expression assay. This ‘chip-based’ approach utilizes microscopic arrays of cDNAs printed on glass as high-density hybridization targets. Fluorescent probe mixtures derived from total cellular messenger RNA (mRNA) hybridize to cognate elements on the array, allowing accurate measurement of the expression of the corresponding genes. Array densities of >1,000 cDNAs per cm² enable quantitative expression monitoring of a large number of genes in a single hybridization. A two-color fluorescence detection scheme allows rapid and simultaneous differential expression analysis of independent biological samples. Mass-produced microarrays provide a new tool for genome expression analysis that may revolutionize genetic dissection, drug discovery and human disease diagnostics.     

Meta-analysis of gene expression microarrays with missing replicates

Background  

Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as incomplete genes, may also be informative and useful.     

Genetic heterogeneity of stably transfected cell lines revealed by expression profiling with oligonucleotide microarrays

Large-scale gene expression measurements with oligonucleotide microarrays have contributed tremendously to biological research. However, to distinguish between relevant expression changes and falsely identified positives, the source and magnitude of errors must be understood. Here, we report a source of biological variability in microarray experiments with stably transfected cell lines. Mouse embryonic fibroblast (MEF/3T3) and rat schwannoma (RT4) cell lines were generated to provide regulatable schwannomin expression. The expression levels of 29 samples from five different mouse embryonic fibroblast clonal cell lines and 18 samples from 3 RT4 cell lines were monitored with oligonucleotide microarrays. Using hierarchical clustering, we determined that the changes in gene expression induced by schwannomin overexpression were subtle when compared with those detected as a consequence of clonal selection during generation of the cell lines. The hierarchical clustering implies that significant alterations of gene expression were introduced during the transfection and selection processes. A total of 28 genes were identified by Kruskal-Wallis rank test that showed significant variation between clonal lines. Most of them were related to cytoskeletal function and signaling pathways. Based on these analyses, we recommend that replications of experiments with several selected cell lines are necessary to assess biological effects of induced gene expression.     

Profiling changes in gene expression during differentiation and maturation of monocyte-derived dendritic cells using both oligonucleotide microarrays and proteomics

Dendritic cells (DCs) are antigen-presenting cells that play a major role in initiating primary immune responses. We have utilized two independent approaches, DNA microarrays and proteomics, to analyze the expression profile of human CD14(+) blood monocytes and their derived DCs. Analysis of gene expression changes at the RNA level using oligonucleotide microarrays complementary to 6300 human genes showed that approximately 40% of the genes were expressed in DCs. A total of 255 genes (4%) were found to be regulated during DC differentiation or maturation. Most of these genes were not previously associated with DCs and included genes encoding secreted proteins as well as genes involved in cell adhesion, signaling, and lipid metabolism. Protein analysis of the same cell populations was done using two-dimensional gel electrophoresis. A total of 900 distinct protein spots were included, and 4% of them exhibited quantitative changes during DC differentiation and maturation. Differentially expressed proteins were identified by mass spectrometry and found to represent proteins with Ca(2+) binding, fatty acid binding, or chaperone activities as well as proteins involved in cell motility. In addition, proteomic analysis provided an assessment of post-translational modifications. The chaperone protein, calreticulin, was found to undergo cleavage, yielding a novel form. The combined oligonucleotide microarray and proteomic approaches have uncovered novel genes associated with DC differentiation and maturation and has allowed analysis of post-translational modifications of specific proteins as part of these processes.     

Indirect measurements of differential gene expression with cDNA microarrays

The use of universal RNA reference sets is an increasingly common approach to molecular classification studies with cDNA microarrays. Here we evaluated the reliability of indirect measurements of fluorescence ratios with a common RNA reference as a means of identifying differentially expressed genes. Comparisons of direct and indirect measures of differential gene expression showed a strong overall correlation in fluorescence ratio measurements but also a high degree of false positives in our indirect measurements. These results indicated that the application of more stringent ratio filters may be required when assessing differential gene expression utilizing a common RNA reference in classification studies.     

Improving signal intensities for genes with low-expression on oligonucleotide microarrays

Background  

DNA microarrays using long oligonucleotide probes are widely used to evaluate gene expression in biological samples. These oligonucleotides are pre-synthesized and sequence-optimized to represent specific genes with minimal cross-hybridization to homologous genes. Probe length and concentration are critical factors for signal sensitivity, particularly when genes with various expression levels are being tested. We evaluated the effects of oligonucleotide probe length and concentration on signal intensity measurements of the expression levels of genes in a target sample.     

Specific and nonspecific hybridization of oligonucleotide probes on microarrays

Gene expression analysis by means of microarrays is based on the sequence-specific binding of RNA to DNA oligonucleotide probes and its measurement using fluorescent labels. The binding of RNA fragments involving sequences other than the intended target is problematic because it adds a chemical background to the signal, which is not related to the expression degree of the target gene. The article presents a molecular signature of specific and nonspecific hybridization with potential consequences for gene expression analysis. We analyzed the signal intensities of perfect match (PM) and mismatch (MM) probes of GeneChip microarrays to specify the effect of specific and nonspecific hybridization. We found that these events give rise to different relations between the PM and MM intensities as function of the middle base of the PM, namely a triplet-like (C > G approximately T > A > 0) and a duplet-like (C approximately T > 0 > G approximately A) pattern of the PM-MM log-intensity difference upon binding of specific and nonspecific RNA fragments, respectively. The systematic behavior of the intensity difference can be rationalized on the level of basepairings of DNA/RNA oligonucleotide duplexes in the middle of the probe sequence. Nonspecific binding is characterized by the reversal of the central Watson-Crick (WC) pairing for each PM/MM probe pair, whereas specific binding refers to the combination of a WC and a self-complementary (SC) pairing in PM and MM probes, respectively. The Gibbs free energy contribution of WC pairs to duplex stability is asymmetric for purines and pyrimidines of the PM and decreases according to C > G approximately T > A. SC pairings on the average only weakly contribute to duplex stability. The intensity of complementary MM introduces a systematic source of variation which decreases the precision of expression measures based on the MM intensities.     

Robotic spotting of cDNA and oligonucleotide microarrays

DNA microarrays are a uniquely efficient method for simultaneously assessing the expression levels of thousands of genes. Owing to their flexibility and value, mechanically spotted microarrays remain the most popular platform. Here, we review recent technological advances with a focus on spotted arrays. Robotic spotting still poses numerous technical challenges. To reduce artefacts, many laboratories have recently investigated ways of improving the spotting process. We compare alternative options and discuss implications for next-generation systems. Together with modern approaches to data analysis, such developments bring greatly improved reliability to individual microarray experiments. Advancing towards the ultimate goal of delivering calibrated, truly quantitative gene-expression measurements on a genomic scale, microarray technology remains at the forefront of post-genomic systems biology.     

Comparative gene expression profiles in pancreatic islets associated with agouti yellow mutation and PACAP overexpression in mice

In diabetes mellitus, pituitary adenylate cyclase-activating polypeptide (PACAP) has insulinotropic and glucose-lowering properties. We previously demonstrated that transgenic mice overexpressing PACAP in pancreatic β-cells (PACAP-Tg) show attenuated pancreatic islet hyperplasia and hyperinsulinemia in type 2 diabetic models. To explore the underlying mechanisms, here we crossed PACAP-Tg mice with lethal yellow agouti (KKAy) diabetic mice, and performed gene chip analysis of laser capture microdissected pancreatic islets from four F₁ offspring genotypes (wild-type, PACAP-Tg, KKAy, and PACAP-Tg:KKAy). We identified 1371 probes with >16-fold differences between at least one pair of genotypes, and classified the probes into five clusters with characteristic expression patterns. Gene ontology enrichment analysis showed that genes involved in the terms ribosome and intracellular organelles such as ribonucleoprotein complex, mitochondrion, and chromosome organization were significantly enriched in clusters characterized by up-regulated genes in PACAP-Tg:KKAy mice compared with KKAy mice. These results may provide insight into the mechanisms of diabetes that accompany islet hyperplasia and amelioration by PACAP.