Dataset Information

Custom design and analysis of high-density oligonucleotide bacterial tiling microarrays.

ABSTRACT:

Background

High-density tiling microarrays are a powerful tool for the characterization of complete genomes. The two major computational challenges associated with custom-made arrays are design and analysis. Firstly, several genome dependent variables, such as the genome's complexity and sequence composition, need to be considered in the design to ensure a high quality microarray. Secondly, since tiling projects today very often exceed the limits of conventional array-experiments, researchers cannot use established computer tools designed for commercial arrays, and instead have to redesign previous methods or create novel tools.

Principal findings

Here we describe the multiple aspects involved in the design of tiling arrays for transcriptome analysis and detail the normalisation and analysis procedures for such microarrays. We introduce a novel design method to make two 280,000 feature microarrays covering the entire genome of the bacterial species Escherichia coli and Neisseria meningitidis, respectively, as well as the use of multiple copies of control probe-sets on tiling microarrays. Furthermore, a novel normalisation and background estimation procedure for tiling arrays is presented along with a method for array analysis focused on detection of short transcripts. The design, normalisation and analysis methods have been applied in various experiments and several of the detected novel short transcripts have been biologically confirmed by Northern blot tests.

Conclusions

Tiling-arrays are becoming increasingly applicable in genomic research, but researchers still lack both the tools for custom design of arrays, as well as the systems and procedures for analysis of the vast amount of data resulting from such experiments. We believe that the methods described herein will be a useful contribution and resource for researchers designing and analysing custom tiling arrays for both bacteria and higher organisms.

SUBMITTER: Thomassen GO

PROVIDER: S-EPMC2691959 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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.