ArticleMolecular & cellular proteomics : MCP2014
SpliceVista, a tool for splice variant identification and visualization in shotgun proteomics data.
Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Proteomic Profiling Towards a Better Understanding of Genetic Based Muscular Diseases: The Current Picture and a Look to the Future.Biomolecules · 2025Review
- Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.Nature communications · 2022Article
- Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation.Molecular systems biology · 2020Article
- pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework.Bioinformatics (Oxford, England) · 2019Article
- Integrated Identification and Quantification Error Probabilities for Shotgun Proteomics.Molecular & cellular proteomics : MCP · 2019Article
- Splicing of platelet resident pre-mRNAs upon activation by physiological stimuli results in functionally relevant proteome modifications.Scientific reports · 2018Article
- Analysis of Genes with Alternatively Spliced Transcripts in the Leaf, Root, Panicle and Seed of Rice Using a Long Oligomer Microarray and RNA-Seq.Molecules and cells · 2017Article
- Alternative splicing shapes transcriptome but not proteome diversity in Physcomitrella patens.Scientific reports · 2017Article
- Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences.Molecular & cellular proteomics : MCP · 2017Article
- Proteoform-Specific Insights into Cellular Proteome Regulation.Molecular & cellular proteomics : MCP · 2016Article
- Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation.Annual review of analytical chemistry (Palo Alto, Calif.) · 2016Review
- Global Profiling of the Cellular Alternative RNA Splicing Landscape during Virus-Host Interactions.PloS one · 2016Article
- Exploring the potential of public proteomics data.Proteomics · 2016Review
- Quantitative comparison of CrkL-SH3 binding proteins from embryonic murine brain and liver: Implications for developmental signaling and the quantification of protein species variants in bottom-up proteomics.Journal of proteomics · 2015Article
- Making proteomics data accessible and reusable: current state of proteomics databases and repositories.Proteomics · 2015Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alternative splicing is a pervasive process in eukaryotic organisms. More than 90% of human genes have alternatively spliced products, and aberrant splicing has been shown to be associated with many diseases. Current methods employed in the detection of splice variants include prediction by clustering of expressed sequence tags, exon microarray, and mRNA sequencing, all methods focusing on RNA-level information. There is a lack of tools for analyzing splice variants at the protein level. Here, we present SpliceVista, a tool for splice variant identification and visualization based on mass spectrometry proteomics data. SpliceVista retrieves gene structure and translated sequences from alternative splicing databases and maps MS-identified peptides to splice variants. The visualization module plots the exon composition of each splice variant and aligns identified peptides with transcript positions. If quantitative mass spectrometry data are used, SpliceVista plots the quantitative patterns for each peptide and provides users with the option to cluster peptides based on their quantitative patterns. SpliceVista can identify splice-variant-specific peptides, providing the possibility for variant-specific analysis. The tool was tested on two experimental datasets (PXD000065 and PXD000134). In A431 cells treated with gefitinib, 2983 splice-variant-specific peptides corresponding to 939 splice variants were identified. Through comparison of splice-variant-centric, protein-centric, and gene-centric quantification, several genes (e.g. EIF4H) were found to have differentially regulated splice variants after gefitinib treatment. The same discrepancy between protein-centric and splice-centric quantification was detected in the other dataset, in which induced pluripotent stem cells were compared with parental fibroblast and human embryotic stem cells. In addition, SpliceVista can be used to visualize novel splice variants inferred from peptide-level evidence. In summary, SpliceVista enables visualization, detection, and differential quantification of protein splice variants that are often missed in current proteomics pipelines.
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