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Antisense artifacts in transcriptome microarray experiments are resolved by actinomycin D.

ABSTRACT: Recent transcription profiling studies have revealed an unanticipatedly large proportion of antisense transcription across eukaryotic and bacterial genomes. However, the extent and significance of antisense transcripts is controversial partly because experimental artifacts are suspected. Here, we present a method to generate clean genome-wide transcriptome profiles, using actinomycin D (ActD) during reverse transcription. We show that antisense artifacts appear to be triggered by spurious synthesis of second-strand cDNA during reverse transcription reactions. Strand-specific hybridization signals obtained from Saccharomyces cerevisiae tiling arrays were compared between samples prepared with and without ActD. Use of ActD removed about half of the detectable antisense transcripts, consistent with their being artifacts, while sense expression levels and about 200 antisense transcripts were not affected. Our findings thus facilitate a more accurate assessment of the extent and position of antisense transcription, towards a better understanding of its role in cells.

SUBMITTER: Perocchi F

PROVIDER: S-EPMC2095812 | biostudies-other | 2007

REPOSITORIES: biostudies-other

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Antisense artifacts in transcriptome microarray experiments are resolved by actinomycin D.

Perocchi Fabiana F Xu Zhenyu Z Clauder-Münster Sandra S Steinmetz Lars M LM

Nucleic acids research 20070926 19

Recent transcription profiling studies have revealed an unanticipatedly large proportion of antisense transcription across eukaryotic and bacterial genomes. However, the extent and significance of antisense transcripts is controversial partly because experimental artifacts are suspected. Here, we present a method to generate clean genome-wide transcriptome profiles, using actinomycin D (ActD) during reverse transcription. We show that antisense artifacts appear to be triggered by spurious synthe ...[more]

PMID: 17897965

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Project description:BACKGROUND: High-throughput, parallel gene expression analysis by means of microarray technology has become a widely used technique in recent years. There are currently two main dye-labelling strategies for microarray studies based on custom-spotted cDNA or oligonucleotides arrays: (I) Dye-labelling of a single target sample with a particular dye, followed by subsequent hybridisation to a single microarray slide, (II) Dye-labelling of two different target samples with two different dyes, followed by subsequent co-hybridisation to a single microarray slide. The two dyes most frequently used for either method are Cy3 and Cy5. We propose and evaluate a novel experiment set-up utilising three differently labelled targets co-hybridised to one microarray slide. In addition to Cy3 and Cy5, this incorporates Alexa 594 as a third dye-label. We evaluate this approach in line with current data processing and analysis techniques for microarrays, and run separate analyses on Alexa 594 used in single-target, dual-target and the intended triple-target experiment set-ups (a total of 18 microarray slides). We follow this by pointing out practical applications and suitable analysis methods, and conclude that triple-target microarray experiments can add value to microarray research by reducing material costs for arrays and related processes, and by increasing the number of options for pragmatic experiment design. RESULTS: The addition of Alexa 594 as a dye-label for an additional--third--target sample works within the framework of more commonplace Cy5/Cy3 labelled target sample combinations. Standard normalisation methods are still applicable, and the resulting data can be expected to allow identification of expression differences in a biological experiment, given sufficient levels of biological replication (as is necessary for most microarray experiments). CONCLUSION: The use of three dye-labelled target samples can be a valuable addition to the standard repertoire of microarray experiment designs. The method enables direct comparison between two experimental populations as well as measuring these two populations in relation to a third reference sample, allowing comparisons within the slide and across slides. These benefits are only offset by the added level of consideration required in the experimental design and data processing of a triple-target study design. Common methods for data processing and analysis are still applicable, but there is scope for the development of custom models for triple-target data. In summary, we do not consider the triple-target approach to be a new standard, but a valuable addition to the existing microarray study toolkit.

Dataset Information

Antisense artifacts in transcriptome microarray experiments are resolved by actinomycin D.

Publications

Antisense artifacts in transcriptome microarray experiments are resolved by actinomycin D.

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