Article

A common reference for cDNA microarray hybridizations.

Center for Human and Clinical Genetics, Leiden University Medical Center, Wassenaarseweg 72, 2333AL Leiden, Nederland.
Nucleic Acids Research (Impact Factor: 9.11). 12/2002; 30(21):e116.
Source: PubMed

ABSTRACT

Comparisons of expression levels across different cDNA microarray experiments are easier when a common reference is co-hybridized to every microarray. Often this reference consists of one experimental control sample, a pool of cell lines or a mix of all samples to be analyzed. We have developed an alternative common reference consisting of a mix of the products that are spotted on the array. Pooling part of the cDNA PCR products before they are printed and their subsequent amplification towards either sense or antisense cRNA provides an excellent common reference. Our results show that this reference yields a reproducible hybridization signal in 99.5% of the cDNA probes spotted on the array. Accordingly, a ratio can be calculated for every spot, and expression levels across different hybridizations can be compared. In dye-swap experiments this reference shows no significant ratio differences, with 95% of the spots within an interval of +/-0.2-fold change. The described method can be used in hybridizations with both amplified and non-amplified targets, is time saving and provides a constant batch of common reference that lasts for thousands of hybridizations.

Download full-text

Full-text

Available from: Judith M Boer, Feb 07, 2014
  • Source
    • "Therefore, microarray hybridisations were performed for each treatment (control, WC 30 μg/ml, WC-Co 33 μg/ml, CoCl2 3 μg/ml; 3 h and 3 d exposure each) with 5 independent biological replicates. All hybridisations were performed against a common reference RNA [72] consisting of a mixture of equal amounts of RNA from all treatments. Synthesis of cDNA, cRNA and cRNA-labeling was performed with the Agilent Low RNA Input Linear Amplification Kit according to the manufacturer's instructions. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Tungsten carbide (WC) and tungsten carbide cobalt (WC-Co) nanoparticles are of occupational health relevance because of the increasing usage in hard metal industries. Earlier studies showed an enhanced toxic potential for WC-Co compared to WC or cobalt ions alone. Therefore, we investigated the impact of these particles, compared to cobalt ions applied as CoCl(2), on the global gene expression level in human keratinocytes (HaCaT) in vitro. WC nanoparticles exerted very little effects on the transcriptomic level after 3 hours and 3 days of exposure. In contrast, WC-Co nanoparticles caused significant transcriptional changes that were similar to those provoked by CoCl(2). However, CoCl(2) exerted even more pronounced changes in the transcription patterns. Gene set enrichment analyses revealed that the differentially expressed genes were related to hypoxia response, carbohydrate metabolism, endocrine pathways, and targets of several transcription factors. The role of the transcription factor HIF1 (hypoxia inducible factor 1) is particularly highlighted and aspects of downstream events as well as the role of other transcription factors related to cobalt toxicity are considered. This study provides extensive data useful for the understanding of nanoparticle and cobalt toxicity. It shows that WC nanoparticles caused low transcriptional responses while WC-Co nanoparticles are able to exert responses similar to that of free cobalt ions, particularly the induction of hypoxia-like effects via interactions with HIF1alpha in human keratinocytes. However, the enhanced toxicity of WC-Co particles compared to CoCl(2) could not be explained by differences in gene transcription.
    Full-text · Article · Jan 2010 · BMC Genomics
  • Source
    • "One sample is prepared from a reference mRNA and the other from mRNA isolated from the experimental cells. The common reference, or universal control, is collected from a pool of cell lines or a mix of all analysed samples [26] [9]. The initial data arising from cDNA microarray experiments are relative mRNA levels – experiment to control ratios. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The clustering coefficient has been used successfully to summarise important features of unweighted, undirected networks across a wide range of applications in complexity science. Recently, a number of authors have extended this concept to the case of networks with non-negatively weighted edges. After reviewing various alternatives, we focus on a definition due to Zhang and Horvath that can be traced back to earlier work of Grindrod. We give a natural and transparent derivation of this clustering coefficient and then analyse its properties. One attraction of this version is that it deals directly with weighted edges and avoids the need to discretise, that is, to round weights up to 1 or down to 0. This has the advantages of (a) retaining all edge weight information, and (b) eliminating the requirement for an arbitrary cutoff level. Further, the extended definition is much less likely to break down due to a ‘divide-by-zero’. Using our new derivation and focusing on some special cases allows us to gain insights into the typical behaviour of this measure. We then illustrate the idea by computing the generalised clustering coefficients, along with the corresponding weighted degrees, for pairwise correlation gene expression data arising from microarray experiments. We find that the weighted clustering and degree distributions reveal global topological differences between normal and tumour networks.
    Full-text · Article · Jan 2007 · Ai Communications
  • Source
    • "A second method of creating a universal reference from the characteristics of the clone is described by Sterreburg et al. [14]. Briefly, they suggest pooling all clones together in a single tube, performing a PCR reaction to create in vitro transcription template for all of the cDNA inserts, in vitro transcription of the PCR product, DNase treatment, reverse transcription, and labeling. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Using microarrays by co-hybridizing two samples labeled with different dyes enables differential gene expression measurements and comparisons across slides while controlling for within-slide variability. Typically one dye produces weaker signal intensities than the other often causing signals to be undetectable. In addition, undetectable spots represent a large problem for two-color microarray designs and most arrays contain at least 40% undetectable spots even when labeled with reference samples such as Stratagene's Universal Reference RNAs. We introduce a novel universal reference sample that produces strong signal for all spots on the array, increasing the average fraction of detectable spots to 97%. Maximizing detectable spots on the reference image channel also decreases the variability of microarray data allowing for reliable detection of smaller differential gene expression changes. The reference sample is derived from sequence contained in the parental EST clone vector pT7T3D-Pac and is called vector RNA (vRNA). We show that vRNA can also be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This reference sample can be made inexpensively in large quantities as a renewable resource that is consistent across experiments. Results of this study show that vRNA provides a useful universal reference that yields high signal for almost all spots on a microarray, reduces variation and allows for comparisons between experiments and laboratories. Further, it can be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This type of reference allows for detection of small changes in differential expression while reference designs in general allow for large-scale multivariate experimental designs. vRNA in combination with reference designs enable systems biology microarray experiments of small physiologically relevant changes.
    Full-text · Article · Feb 2006 · BMC Genomics
Show more