Dataset Information

Transcript-specific expression profiles derived from sequence-based analysis of standard microarrays.

ABSTRACT: Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the re-analysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression levels of specific transcripts.In the present study alignment of probe sequences of the Affymetrix microarray HG-U133A with Ensembl transcript sequences was performed to define transcript-specific probe sets. Out of a total of 247,965 perfect match probes, 95,008 were designated "transcript-specific", i.e. showing complete sequence alignment, no cross-hybridization, and transcript-, not only gene-specificity. These probes were grouped into 7,941 transcript-specific probe sets and 15,619 gene-specific probe sets, respectively. The former were used to differentiate 445 alternative transcripts of 215 genes. For selected transcripts, predicted by this analysis to be differentially expressed in the human kidney, confirmatory real-time RT-PCR experiments were performed. First, the expression of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was determined by the transcript-specific array analysis and confirmed by real-time RT-PCR. Secondly, disease-specific differential expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and Q5VYS0_HUMAN) was computed from the available array data sets and confirmed by transcript-specific real-time RT-PCR.Transcript-specific analysis of microarray experiments can be employed to study gene-regulation on the transcript level using conventional microarray data. In this study, predictions based on sufficient probe set size and fold-change are confirmed by independent means.

SUBMITTER: Moll AG

PROVIDER: S-EPMC2650090 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Transcript-specific expression profiles derived from sequence-based analysis of standard microarrays.

Moll Anton G AG Lindenmeyer Maja T MT Kretzler Matthias M Nelson Peter J PJ Zimmer Ralf R Cohen Clemens D CD

PloS one 20090311 3

<h4>Background</h4>Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the re-analysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression ...[more]

PMID: 19277110

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Project description:BACKGROUND: Arabidopsis thaliana transcript profiles indicate effects of abiotic and biotic stresses and tissue-specific and cell-specific gene expression. Organizing these datasets could reveal the structure and mechanisms of responses and crosstalk between pathways, and in which cells the plants perceive, signal, respond to, and integrate environmental inputs. RESULTS: We clustered Arabidopsis transcript profiles for various treatments, including abiotic, biotic, and chemical stresses. Ubiquitous stress responses in Arabidopsis, similar to those of fungi and animals, employ genes in pathways related to mitogen-activated protein kinases, Snf1-related kinases, vesicle transport, mitochondrial functions, and the transcription machinery. Induced responses to stresses are attributed to genes whose promoters are characterized by a small number of regulatory motifs, although secondary motifs were also apparent. Most genes that are downregulated by stresses exhibited distinct tissue-specific expression patterns and appear to be under developmental regulation. The abscisic acid-dependent transcriptome is delineated in the cluster structure, whereas functions that are dependent on reactive oxygen species are widely distributed, indicating that evolutionary pressures confer distinct responses to different stresses in time and space. Cell lineages in roots express stress-responsive genes at different levels. Intersections of stress-responsive and cell-specific profiles identified cell lineages affected by abiotic stress. CONCLUSION: By analyzing the stress-dependent expression profile, we define a common stress transcriptome that apparently represents universal cell-level stress responses. Combining stress-dependent and tissue-specific and cell-specific expression profiles, and Arabidopsis 5'-regulatory DNA sequences, we confirm known stress-related 5' cis-elements on a genome-wide scale, identify secondary motifs, and place the stress response within the context of tissues and cell lineages in the Arabidopsis root.

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.

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Transcript-specific expression profiles derived from sequence-based analysis of standard microarrays.

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Transcript-specific expression profiles derived from sequence-based analysis of standard microarrays.

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