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          Institute: MPI für molekulare Genetik     Collection: Department of Computational Molecular Biology     Display Documents



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ID: 226532.0, MPI für molekulare Genetik / Department of Computational Molecular Biology
Strengths and weaknesses of EST-based prediction of tissue-specific alternative splicing
Authors:Gupta, Shobhit; Zink, Dorothea; Korn, Bernhard; Vingron, Martin; Haas, Stefan A
Language:English
Date of Publication (YYYY-MM-DD):2004-09-28
Title of Journal:BMC Genomics
Volume:5
Start Page:72
End Page:72
Copyright:© 2004 Gupta et al
Review Status:not specified
Audience:Experts Only
Abstract / Description:Background:
Alternative splicing contributes significantly to the complexity of the human transcriptome and proteome. Computational prediction of alternative splice isoforms are usually based on EST sequences that also allow to approximate the expression pattern of the related transcripts. However, the limited number of tissues represented in the EST data as well as the different cDNA construction protocols may influence the predictive capacity of ESTs to unravel tissue-specifically expressed transcripts.
Methods:
We predict tissue and tumor specific splice isoforms based on the genomic mapping (SpliceNest) of the EST consensus sequences and library annotation provided in the GeneNest database. We further ascertain the potentially rare tissue specific transcripts as the ones represented only by ESTs derived from normalized libraries. A subset of the predicted tissue and tumor specific isoforms are then validated via RT-PCR experiments over a spectrum of 40 tissue types.
Results:
Our strategy revealed 427 genes with at least one tissue specific transcript as well as 1120 genes showing tumor specific isoforms. While our experimental evaluation of computationally predicted tissue-specific isoforms revealed a high success rate in confirming the expression of these isoforms in the respective tissue, the strategy frequently failed to detect the expected restricted expression pattern. The analysis of putative lowly expressed transcripts using normalized cDNA libraries suggests that our ability to detect tissue-specific isoforms strongly depends on the expression level of the respective transcript as well as on the sensitivity of the experimental methods. Especially splice isoforms predicted to be disease-specific tend to represent transcripts that are expressed in a set of healthy tissues rather than novel isoforms.
Conclusions:
We propose to combine the computational prediction of alternative splice isoforms with experimental validation for efficient delineation of an accurate set of tissue-specific transcripts.
External Publication Status:published
Document Type:Article
Communicated by:Martin Vingron
Affiliations:MPI für molekulare Genetik
External Affiliations:German Resource Center for Genome Research, INF 580, 69120 Heidelberg, Germany.
Identifiers:ISSN:1471-2164
DOI:10.1186/1471-2164-5-72
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