Abstract

BackgroundDNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA) contain probes for annotated open reading frames (ORF) and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA) have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts.ResultsWe extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF) in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress.ConclusionsWe show that the information derived from TMA hybridization can be processed simultaneously for high-resolution qualitative and quantitative analysis of the differential expression of well-characterized genes and of previously non-annotated and antisense transcripts. The consistency of the performance of TMA, their genome-wide coverage and adaptability to updated genome annotations, and the possibility of measuring strand-specific differential expression makes them a tool of choice for the analysis of gene expression in any organism for which TMA platforms are available.

Highlights

  • DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale

  • Generation of custom Chip Description Files (CDF) for expression analyses Analysis of differential gene expression using microarrays requires the generation of a Chip Description File (CDF), which links each position in the microarray to a specific gene

  • Genes represented by less than four probes in tiling microarrays (TMA) or Expression microarrays (EMA) were not incorporated into the final CDFs because this has been reported to be the lowest number of probes able to provide statistically significant results [14]

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Summary

Introduction

DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. The generation of high-resolution transcription maps by hybridizing total RNA to TMAs has uncovered the existence of a large variety of RNAs, many of which are non-coding, in a range of organisms that include Bacillus subtilis [3], Saccharomyces cerevisiae [4], Schizosaccharomyces pombe [5], Caenorhabditis elegans [6], Drosophila [7], human [8] and Arabidopsis [9] This unprecedented view of the transcriptional landscape of the genome derives mainly from a qualitative interpretation of TMA analysis, and raises the challenge of establishing the putative biological role of non-annotated transcriptionally active regions. The number of probes in EMAs is at least one order of magnitude lower; they are unambiguously ascribed to specific genes, and the processing and summarization of their hybridization signal is relatively straightforward

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