Dataset Information

Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays.

ABSTRACT: Gene expression analysis using microarrays of synthetic long oligonucleotides is limited in that it requires substantial amounts of RNA. To obtain these quantities from minute amounts of starting material, protocols were developed that linearly amplify mRNA by cDNA synthesis and in vitro transcription. Since orientation of the product is antisense (aRNA), it is inapplicable for dye-labelling by reverse transcription and hybridization to sense-oriented oligonucleotide arrays. Here, we introduce a novel protocol in which aRNA labelling is achieved by a combination of two reverse and one forward transcription reactions followed by dye-incorporation using Klenow fragment, generating fluorescent antisense cDNA. We demonstrate high fidelity in arrays using up to 10(5)-fold amplification, starting from 2 ng total RNA. The generated data are highly reproducible and maintain relative gene expression levels between samples. These results demonstrate that our protocol describes an efficient and reliable technique to expand the applicability of oligonucleotide arrays to studies where RNA is the limited source material.

SUBMITTER: Schlingemann J

PROVIDER: S-EPMC549428 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays.

Schlingemann Joerg J Thuerigen Olaf O Ittrich Carina C Toedt Grischa G Kramer Heidi H Hahn Meinhard M Lichter Peter P

Nucleic acids research 20050217 3

Gene expression analysis using microarrays of synthetic long oligonucleotides is limited in that it requires substantial amounts of RNA. To obtain these quantities from minute amounts of starting material, protocols were developed that linearly amplify mRNA by cDNA synthesis and in vitro transcription. Since orientation of the product is antisense (aRNA), it is inapplicable for dye-labelling by reverse transcription and hybridization to sense-oriented oligonucleotide arrays. Here, we introduce a ...[more]

PMID: 15718295

Similar Datasets

Project description:BackgroundRNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.0ST arrays. The use of Exon arrays makes it possible to assess the performance of RNA-Seq in two key areas: detection of expression at the granularity of individual exons, and discovery of transcription outside annotated loci.ResultsWe found a high degree of correspondence between the two platforms in terms of exon-level fold changes and detection. For example, over 80% of exons detected as expressed in RNA-Seq were also detected on the Exon array, and 91% of exons flagged as changing from Absent to Present on at least one platform had fold-changes in the same direction. The greatest detection correspondence was seen when the read count threshold at which to flag exons Absent in the SOLiD data was set to t<1 suggesting that the background error rate is extremely low in RNA-Seq. We also found RNA-Seq more sensitive to detecting differentially expressed exons than the Exon array, reflecting the wider dynamic range achievable on the SOLiD platform. In addition, we find significant evidence of novel protein coding regions outside known exons, 93% of which map to Exon array probesets, and are able to infer the presence of thousands of novel transcripts through the detection of previously unreported exon-exon junctions.ConclusionsBy focusing on exon-level expression, we present the most fine-grained comparison between RNA-Seq and microarrays to date. Overall, our study demonstrates that data from a SOLiD RNA-Seq experiment are sufficient to generate results comparable to those produced from Affymetrix Exon arrays, even using only a single replicate from each platform, and when presented with a large genome.

Dataset Information

Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays.

Publications

Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets