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TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes

BACKGROUND: Standard 3′ Affymetrix gene expression arrays have contributed a significantly higher volume of existing gene expression data than other microarray platforms. These arrays were designed to identify differentially expressed genes, but not their alternatively spliced transcript forms. No r...

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Detalles Bibliográficos
Autores principales: Chitturi, Neelima, Balagannavar, Govindkumar, Chandrashekar, Darshan S, Abinaya, Sadashivam, Srini, Vasan S, Acharya, Kshitish K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3884118/
https://www.ncbi.nlm.nih.gov/pubmed/24373374
http://dx.doi.org/10.1186/1471-2164-14-922
Descripción
Sumario:BACKGROUND: Standard 3′ Affymetrix gene expression arrays have contributed a significantly higher volume of existing gene expression data than other microarray platforms. These arrays were designed to identify differentially expressed genes, but not their alternatively spliced transcript forms. No resource can currently identify expression pattern of specific mRNA forms using these microarray data, even though it is possible to do this. RESULTS: We report a web server for expression profiling of alternatively spliced transcripts using microarray data sets from 31 standard 3′ Affymetrix arrays for human, mouse and rat species. The tool has been experimentally validated for mRNAs transcribed or not-detected in a human disease condition (non-obstructive azoospermia, a male infertility condition). About 4000 gene expression datasets were downloaded from a public repository. ‘Good probes’ with complete coverage and identity to latest reference transcript sequences were first identified. Using them, ‘Transcript specific probe-clusters’ were derived for each platform and used to identify expression status of possible transcripts. The web server can lead the user to datasets corresponding to specific tissues, conditions via identifiers of the microarray studies or hybridizations, keywords, official gene symbols or reference transcript identifiers. It can identify, in the tissues and conditions of interest, about 40% of known transcripts as ‘transcribed’, ‘not-detected’ or ‘differentially regulated’. Corresponding additional information for probes, genes, transcripts and proteins can be viewed too. We identified the expression of transcripts in a specific clinical condition and validated a few of these transcripts by experiments (using reverse transcription followed by polymerase chain reaction). The experimental observations indicated higher agreements with the web server results, than contradictions. The tool is accessible at http://resource.ibab.ac.in/TIPMaP. CONCLUSION: The newly developed online tool forms a reliable means for identification of alternatively spliced transcript-isoforms that may be differentially expressed in various tissues, cell types or physiological conditions. Thus, by making better use of existing data, TIPMaP avoids the dependence on precious tissue-samples, in experiments with a goal to establish expression profiles of alternative splice forms – at least in some cases.