Analysis of repeatability in spotted cDNA microarrays

Jenssen, Tor Kristian; Langaas, Mette; Kuo, Winston Patrick; Smith‐Sørensen, Birgitte; Myklebost, Ola; Hovig, Eivind

doi:10.1093/nar/gkf441

Cited by 53 publications

(39 citation statements)

References 13 publications

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“…For example, the reported Pearson correlation coefficient between technical replicates can range between the disappointing level of 0.5 and the more reassuring level of 0.95. [148][149][150] Cross-platform reproducibility studies undertaken so far 148,149,151 have identified two main problems. First, microarrays are not able to accurately measure genes expressed at low levels.…”

Section: Reproducibilitymentioning

confidence: 99%

Analysis of microarray experiments of gene expression profiling

Tarca

Romero

Drăghici³

2006

American Journal of Obstetrics and Gynecology

259

150

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The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature.

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Section: Reproducibilitymentioning

confidence: 99%

Analysis of microarray experiments of gene expression profiling

Tarca

Romero

Drăghici³

2006

American Journal of Obstetrics and Gynecology

259

150

View full text Add to dashboard Cite

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“…Several methods for analysis of differential gene expression exist, including microarrays, LuxArray, and differential fluorescence induction. Complications of microarray analysis include its reproducibility and standardization (9,10,21,24,27,44). Differential fluorescence induction uses flow cytometry to select bacteria containing transcriptionally active regulatory regions cloned upstream of a promoterless green fluorescence protein (GFP) reporter gene (29,43,(48)(49)(50); however, there are technical challenges associated with sorting bacteria.…”

mentioning

confidence: 99%

Genomic Profiling of Iron-Responsive Genes in Salmonella enterica Serovar Typhimurium by High-Throughput Screening of a Random Promoter Library

Bjarnason¹,

Southward²,

2003

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The importance of iron to bacteria is shown by the presence of numerous iron-scavenging and transport systems and by many genes whose expression is tightly regulated by iron availability. We have taken a global approach to gene expression analysis of Salmonella enterica serovar Typhimurium in response to iron by combining efficient, high-throughput methods with sensitive, luminescent reporting of gene expression using a random promoter library. Real-time expression profiles of the library were generated under low-and high-iron conditions to identify iron-regulated promoters, including a number of previously identified genes. Our results indicate that approximately 7% of the genome may be regulated directly or indirectly by iron. Further analysis of these clones using a Fur titration assay revealed three separate classes of genes; two of these classes consist of Fur-regulated genes. A third class was Fur independent and included both negatively and positively iron-responsive genes. These may reflect new iron-dependent regulons. Iron-responsive genes included iron transporters, iron storage and mobility proteins, iron-containing proteins (redox proteins, oxidoreductases, and cytochromes), transcriptional regulators, and the energy transducer tonB. By identifying a wide variety of iron-responsive genes, we extend our understanding of the global effect of iron availability on gene expression in the bacterial cell.

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“…A 60% similarity in the reproducibility of the technical replicates was proposed acceptable in other studies, and it has been reported that the correlation coefficient can range between 0.5 and 0.95 (this corresponds to 50 -95%) (Bammler et al, 2005) (Jarvinen et al, 2004) (Jenssen et al, 2002) (Carter et al, 2005).…”

Section: Section 431 Optimization Of the Microarray Techniquementioning

confidence: 83%

Mechanism of action of liver growth induced by peroxisome proliferators

Amer

2010

Toxicology

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Humans are ubiquitously exposed to peroxisome proliferators including hypolipidemic agents, industrial solvents and natural products. Because of this and the fact that peroxisome proliferators cause non-genotoxic hepatocarcinogenesis in rodents, it is of importance to elucidate the mechanism of action of the peroxisome proliferators in order to provide an assessment of the hazard, if any, of these compounds to humans. It is also known that the peroxisome proliferators begin their actions by inducing hepatic DNA synthesis. Thus, the aim of this thesis was to find genes that could be responsible for triggering the induction of hepatic DNA synthesis caused by peroxisome proliferators, specifically ciprofibrate.First, it was important to indicate when the induction of hepatic DNA synthesis actually happens. This was done with BrdU immunohistochemical procedures. The induction of hepatic DNA synthesis with ciprofibrate in mice was observable only after 4 days making it difficult to specify when the induction actually happened. In rats the induction of hepatic DNA synthesis was found to peak at 24 hours and this system gave the better opportunity to find the genes responsible. The difference in the timing of induced hepatic DNA synthesis between mice and rats implied that there could be a species difference in the mechanism of each species' response to PPAR. With immunohistochemistry it was noticed that there was a difference in the lobular localization of hepatic DNA synthesis in the liver tissues of rats and mice dosed with different inducers, with the rat livers exhibiting periportal distribution while hepatic DNA synthesis in the mice seemed to be distributed throughout the liver tissue.The effects of ciprofibrate or cyproterone acetate on liver gene expression in rats were studied, using cDNA microarrays, transcriptome sequencing and quantitative real-time PCR. A 1-5 hour treatment period was chosen to detect the immediate early gene response, while a 24 hour time point was chosen to elucidate the confounding effects from the hepatic DNA synthesis seen Abeer Amer Page 2 during the 24 hour stimulation. The results showed that ciprofibrate altered the expression of numerous genes including previously known PPARa agonist-responsive genes involved in processes such as PPAR signalling pathways, fatty acid metabolic pathway, cell cycle, palmitoylCoA hydrolase activity, lipid metabolism, inflammatory responses, and stress responses, in addition to a large number of novel candidate genes.Three novel induced genes G0s2, Ccnd1 and Scd1, (and two marker genes CYP4A1 and CYP3A1) were confirmed with quantitative real-time PCR. The G0s2, Ccnd1 and Scd1 were found to be up-regulated at the hours 1 and 3 after dosing and not 24 hours, and the G0s2 and Scd1 were specific for the ciprofibrate suggesting they were involved in a distinct PPARa pathway responsible for the hepatic DNA synthesis. The complete database of the transcriptional response provided here opens doors of opportunity for further research to identify genes...

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Analysis of repeatability in spotted cDNA microarrays

Cited by 53 publications

References 13 publications

Analysis of microarray experiments of gene expression profiling

Analysis of microarray experiments of gene expression profiling

Genomic Profiling of Iron-Responsive Genes in Salmonella enterica Serovar Typhimurium by High-Throughput Screening of a Random Promoter Library

Mechanism of action of liver growth induced by peroxisome proliferators

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