Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-7760 - Exon Level Expression Profiling: a Novel Unbiased Transcriptome Analysis for Body Fluids
Released on 19 May 2008, last updated on 22 June 2012
Transcriptome analysis of partially degraded and fragmented RNA samples from body fluids Global gene expression profiling has shown great promise in high-throughput biomarker discovery for early disease detection in body fluids such as saliva, which is accessible, cost-effective, and non-invasive. However, this goal has not been fully realized because saliva, like many clinical samples, contains partially fragmented and degraded RNAs that are difficult to amplify and detect with prevailing technologies. Here, using nanogram scale salivary RNA as a proof-of-principle example, we describe our progress with a novel poly-A tail independent mRNA amplification strategy combined with the Affymetrix GeneChip Exon arrays. We defined a Salivary Exon Core Transcriptome (SECT) with highly similar expression profiles in healthy individuals verified by quantitative PCR. Informatics analysis of SECT provided important mechanistic insight to their potential origin and function. Finally we demonstrated the diagnostic potential of true exon level expression profiling approach with salivary exon biomarkers that accurately discriminated gender in healthy individuals. We analyzed saliva from 18 healthy subjects (7 males, 11 females) using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by Affymetrix Exon Array Computational Tool. No techinical replicates were performed.
transcription profiling by array
David T.W. Wong <email@example.com>, Bernhard G Zimmermann, Bradley S Henson, David Elashoff, David T Wong, Guido Krupp, Hui Zhou, Weixia Yu, Zhanzhi Hu
Exon-level expression profiling: a comprehensive transcriptome analysis of oral fluids. Hu Z, Zimmermann BG, Zhou H, Wang J, Henson BS, Yu W, Elashoff D, Krupp G, Wong DT. , PMID:18356245