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      SpliceCenter: A suite of web-based bioinformatic applications for evaluating the impact of alternative splicing on RT-PCR, RNAi, microarray, and peptide-based studies

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          Abstract

          Background

          Over 60% of protein-coding genes in vertebrates express mRNAs that undergo alternative splicing. The resulting collection of transcript isoforms poses significant challenges for contemporary biological assays. For example, RT-PCR validation of gene expression microarray results may be unsuccessful if the two technologies target different splice variants. Effective use of sequence-based technologies requires knowledge of the specific splice variant(s) that are targeted. In addition, the critical roles of alternative splice forms in biological function and in disease suggest that assay results may be more informative if analyzed in the context of the targeted splice variant.

          Results

          A number of contemporary technologies are used for analyzing transcripts or proteins. To enable investigation of the impact of splice variation on the interpretation of data derived from those technologies, we have developed SpliceCenter. SpliceCenter is a suite of user-friendly, web-based applications that includes programs for analysis of RT-PCR primer/probe sets, effectors of RNAi, microarrays, and protein-targeting technologies. Both interactive and high-throughput implementations of the tools are provided. The interactive versions of SpliceCenter tools provide visualizations of a gene's alternative transcripts and probe target positions, enabling the user to identify which splice variants are or are not targeted. The high-throughput batch versions accept user query files and provide results in tabular form. When, for example, we used SpliceCenter's batch siRNA-Check to process the Cancer Genome Anatomy Project's large-scale shRNA library, we found that only 59% of the 50,766 shRNAs in the library target all known splice variants of the target gene, 32% target some but not all, and 9% do not target any currently annotated transcript.

          Conclusion

          SpliceCenter http://discover.nci.nih.gov/splicecenter provides unique, user-friendly applications for assessing the impact of transcript variation on the design and interpretation of RT-PCR, RNAi, gene expression microarrays, antibody-based detection, and mass spectrometry proteomics. The tools are intended for use by bench biologists as well as bioinformaticists.

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          Most cited references18

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          p53 isoforms can regulate p53 transcriptional activity.

          The recently discovered p53-related genes, p73 and p63, express multiple splice variants and N-terminally truncated forms initiated from an alternative promoter in intron 3. To date, no alternative promoter and multiple splice variants have been described for the p53 gene. In this study, we show that p53 has a gene structure similar to the p73 and p63 genes. The human p53 gene contains an alternative promoter and transcribes multiple splice variants. We show that p53 variants are expressed in normal human tissue in a tissue-dependent manner. We determine that the alternative promoter is conserved through evolution from Drosophila to man, suggesting that the p53 family gene structure plays an essential role in the multiple activities of the p53 family members. Consistent with this hypothesis, p53 variants are differentially expressed in human breast tumors compared with normal breast tissue. We establish that p53beta can bind differentially to promoters and can enhance p53 target gene expression in a promoter-dependent manner, while Delta133p53 is dominant-negative toward full-length p53, inhibiting p53-mediated apoptosis. The differential expression of the p53 isoforms in human tumors may explain the difficulties in linking p53 status to the biological properties and drug sensitivity of human cancer.
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            AceView: a comprehensive cDNA-supported gene and transcripts annotation

            Background Regions covering one percent of the genome, selected by ENCODE for extensive analysis, were annotated by the HAVANA/Gencode group with high quality transcripts, thus defining a benchmark. The ENCODE Genome Annotation Assessment Project (EGASP) competition aimed at reproducing Gencode and finding new genes. The organizers evaluated the protein predictions in depth. We present a complementary analysis of the mRNAs, including alternative transcript variants. Results We evaluate 25 gene tracks from the University of California Santa Cruz (UCSC) genome browser. We either distinguish or collapse the alternative splice variants, and compare the genomic coordinates of exons, introns and nucleotides. Whole mRNA models, seen as chains of introns, are sorted to find the best matching pairs, and compared so that each mRNA is used only once. At the mRNA level, AceView is by far the closest to Gencode: the vast majority of transcripts of the two methods, including alternative variants, are identical. At the protein level, however, due to a lack of experimental data, our predictions differ: Gencode annotates proteins in only 41% of the mRNAs whereas AceView does so in virtually all. We describe the driving principles of AceView, and how, by performing hand-supervised automatic annotation, we solve the combinatorial splicing problem and summarize all of GenBank, dbEST and RefSeq into a genome-wide non-redundant but comprehensive cDNA-supported transcriptome. AceView accuracy is now validated by Gencode. Conclusion Relative to a consensus mRNA catalog constructed from all evidence-based annotations, Gencode and AceView have 81% and 84% sensitivity, and 74% and 73% specificity, respectively. This close agreement validates a richer view of the human transcriptome, with three to five times more transcripts than in UCSC Known Genes (sensitivity 28%), RefSeq (sensitivity 21%) or Ensembl (sensitivity 19%).
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              Alternative splicing in disease and therapy.

              Alternative splicing is the major source of proteome diversity in humans and thus is highly relevant to disease and therapy. For example, recent work suggests that the long-sought-after target of the analgesic acetaminophen is a neural-specific, alternatively spliced isoform of cyclooxygenase 1 (COX-1). Several important diseases, such as cystic fibrosis, have been linked with mutations or variations in either cis-acting elements or trans-acting factors that lead to aberrant splicing and abnormal protein production. Correction of erroneous splicing is thus an important goal of molecular therapies. Recent experiments have used modified oligonucleotides to inhibit cryptic exons or to activate exons weakened by mutations, suggesting that these reagents could eventually lead to effective therapies.
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                Author and article information

                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central
                1471-2105
                2008
                18 July 2008
                : 9
                : 313
                Affiliations
                [1 ]Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
                [2 ]Tiger Team Consulting, Fairfax, VA, USA
                [3 ]Gene Silencing Section, Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
                [4 ]Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, DC, USA
                [5 ]Department of Bioinformatics and Computational Biology, M. D. Anderson Cancer Center, Houston, TX, USA
                Article
                1471-2105-9-313
                10.1186/1471-2105-9-313
                2491637
                18638396
                e86d5a22-3f9e-4817-b813-4c6edfec3a06
                Copyright © 2008 Ryan et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 March 2008
                : 18 July 2008
                Categories
                Database

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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