Using expression arrays for copy number detection: an example from E. coli.

BACKGROUND: The sequencing of many genomes and tiling arrays consisting of millions of DNA segments spanning entire genomes have made high-resolution copy number analysis possible. Microarray-based comparative genomic hybridization (array CGH) has enabled the high-resolution detection of DNA copy number aberrations. While many of the methods and algorithms developed for the analysis microarrays have focused on expression analysis, the same technology can be used to detect genetic alterations, using for example standard commercial Affymetrix arrays. Due to the nature of the resultant data, standard techniques for processing GeneChip expression experiments are inapplicable. RESULTS: We have developed a robust and flexible methodology for high-resolution analysis of DNA copy number of whole genomes, using Affymetrix high-density expression oligonucleotide microarrays. Copy number is obtained from fluorescence signals after processing with novel normalization, spatial artifact correction, data transformation and deletion/duplication detection. We applied our approach to identify deleted and amplified regions in E. coli mutants obtained after prolonged starvation. CONCLUSION: The availability of Affymetrix expression chips for a wide variety of organisms makes the proposed array CGH methodology useful more generally.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Experimental Comparison and Evaluation of the Affymetrix Exon and U133Plus2 GeneChip Arrays

Affymetrix exon arrays offer scientists the only solution for exon-level expression profiling at the whole-genome scale on a single array. These arrays feature a new chip design with no mismatch probes and a radically new random primed protocol to generate sense DNA targets along the entire length of the transcript. In addition to these changes, a limited number of validating experiments and virtually no experimental data to rigorously address the comparability of all-exon arrays with conventional 3'-arrays result in a natural reluctance to replace conventional expression arrays with the new all-exon platform.Using commercially available Affymetrix arrays, we assess the performance of the Human Exon 1.0 ST (HuEx) and U133 Plus 2.0 (U133Plus2) platforms directly through a series of 'spike-in' hybridizations containing 25 transcripts in the presence of a fixed eukaryotic background. Specifically, we compare the measures of expression for HuEx and U133Plus2 arrays to evaluate the precision of these measures as well as the specificity and sensitivity of the measures' ability to detect differential expression.This study presents an experimental comparison and systematic cross-validation of Affymetrix exon arrays and establishes high comparability of expression changes and probe performance characteristics between Affymetrix conventional and exon arrays. In addition, this study offers a reliable benchmark data set for the comparison of competing exon expression measures, the selection of methods suitable for mapping exon array measures to the wealth of previously generated microarray data, as well as the development of more advanced methods for exon- and transcript-level expression summarization

Real-time DNA microarray analysis

We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays

Overestimation of alternative splicing caused by variable probe characteristics in exon arrays

In higher eukaryotes, alternative splicing is a common mechanism for increasing transcriptome diversity. Affymetrix exon arrays were designed as a tool for monitoring the relative expression levels of hundreds of thousands of known and predicted exons with a view to detecting alternative splicing events. In this article, we have analyzed exon array data from many different human and mouse tissues and have uncovered a systematic relationship between transcript-fold change and alternative splicing as reported by the splicing index. Evidence from dilution experiments and deep sequencing suggest that this effect is of technical rather than biological origin and that it is driven by sequence features of the probes. This effect is substantial and results in a 12-fold overestimation of alternative splicing events in genes that are differentially expressed. By cross-species exon array comparison, we could further show that the systematic bias persists even across species boundaries. Failure to consider this effect in data analysis would result in the reproducible false detection of apparently conserved alternative splicing events. Finally, we have developed a software in R called COSIE (Corrected Splicing Indices for Exon arrays) that for any given set of new exon array experiments corrects for the observed bias and improves the detection of alternative splicing (available at www.fmi.ch/groups/gbioinfo)

Non-linear analysis of GeneChip arrays

The application of microarray hybridization theory to Affymetrix GeneChip data has been a recent focus for data analysts. It has been shown that the hyperbolic Langmuir isotherm captures the shape of the signal response to concentration of Affymetrix GeneChips. We demonstrate that existing linear fit methods for extracting gene expression measures are not well adapted for the effect of saturation resulting from surface adsorption processes. In contrast to the most popular methods, we fit background and concentration parameters within a single global fitting routine instead of estimating the background before obtaining gene expression measures. We describe a non-linear multi-chip model of the perfect match signal that effectively allows for the separation of specific and non-specific components of the microarray signal and avoids saturation bias in the high-intensity range. Multimodel inference, incorporated within the fitting routine, allows a quantitative selection of the model that best describes the observed data. The performance of this method is evaluated on publicly available datasets, and comparisons to popular algorithms are presented

Transcriptional profiling of MnSOD-mediated lifespan extension in Drosophila reveals a species-general network of aging and metabolic genes.

BACKGROUND: Several interventions increase lifespan in model organisms, including reduced insulin/insulin-like growth factor-like signaling (IIS), FOXO transcription factor activation, dietary restriction, and superoxide dismutase (SOD) over-expression. One question is whether these manipulations function through different mechanisms, or whether they intersect on common processes affecting aging. RESULTS: A doxycycline-regulated system was used to over-express manganese-SOD (MnSOD) in adult Drosophila, yielding increases in mean and maximal lifespan of 20%. Increased lifespan resulted from lowered initial mortality rate and required MnSOD over-expression in the adult. Transcriptional profiling indicated that the expression of specific genes was altered by MnSOD in a manner opposite to their pattern during normal aging, revealing a set of candidate biomarkers of aging enriched for carbohydrate metabolism and electron transport genes and suggesting a true delay in physiological aging, rather than a novel phenotype. Strikingly, cross-dataset comparisons indicated that the pattern of gene expression caused by MnSOD was similar to that observed in long-lived Caenorhabditis elegans insulin-like signaling mutants and to the xenobiotic stress response, thus exposing potential conserved longevity promoting genes and implicating detoxification in Drosophila longevity. CONCLUSION: The data suggest that MnSOD up-regulation and a retrograde signal of reactive oxygen species from the mitochondria normally function as an intermediate step in the extension of lifespan caused by reduced insulin-like signaling in various species. The results implicate a species-conserved net of coordinated genes that affect the rate of senescence by modulating energetic efficiency, purine biosynthesis, apoptotic pathways, endocrine signals, and the detoxification and excretion of metabolites.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Explaining differences in saturation levels for Affymetrix GeneChip® arrays

The experimental spike-in studies of microarray hybridization conducted by Affymetrix demonstrate a nonlinear response of fluorescence intensity signal to target concentration. Several theoretical models have been put forward to explain these data. It was shown that the Langmuir adsorption isotherm recapitulates a general trend of signal response to concentration. However, this model fails to explain some key properties of the observed signal. In particular, according to the simple Langmuir isotherm, all probes should saturate at the same intensity level. However, this effect was not observed in the publicly available Affymetrix spike-in data sets. On the contrary, it was found that the saturation intensities vary greatly and can be predicted based on the probe sequence composition. In our experimental study, we attempt to account for the unexplained variation in the observed probe intensities using customized fluidics scripts. We explore experimentally the effect of the stringent wash, target concentration and hybridization time on the final microarray signal. The washing effect is assessed by scanning chips both prior to and after the stringent wash. Selective labeling of both specific and non-specific targets allows the visualization and investigation of the washing effect for both specific and non-specific signal components. We propose a new qualitative model of the probe-target hybridization mechanism that is in agreement with observed hybridization and washing properties of short oligonucleotide microarrays. This study demonstrates that desorption of incompletely bound targets during the washing cycle contributes to the observed difference in saturation levels

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