Protein Identification Using Customized Protein Sequence Databases Derived from RNA-Seq Data
Open accessAbstract
The standard shotgun proteomics data analysis strategy relies on searching MS/MS spectra against a context-independent protein sequence database derived from the complete genome sequence of an organism. Because transcriptome sequence analysis (RNA-Seq) promises an unbiased and comprehensive picture of the transcriptome, we reason that a sample-specific protein database derived from RNA-Seq data can better approximate the real protein pool in the sample and thus improve protein identification. In this study, we have developed a two-step strategy for building sample-specific protein databases from RNA-Seq data. First, the database size is reduced by eliminating unexpressed or lowly expressed genes according to transcript quantification. Second, high-quality nonsynonymous coding single nucleotide variations (SNVs) are identified based on RNA-Seq data, and corresponding protein variants are added to the database. Using RNA-Seq and shotgun proteomics data from two colorectal cancer cell lines SW480 and RKO, we demonstrated that customized protein sequence databases could significantly increase the sensitivity of peptide identification, reduce ambiguity in protein assembly, and enable the detection of known and novel peptide variants. Thus, sample-specific databases from RNA-Seq data can enable more sensitive and comprehensive protein discovery in shotgun proteomics studies.
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RNA sequencing can build sample-specific proteoform databases that capture genetic variation and splicing patterns, allowing the strategy to be extended to mammalian genomes.
“To extend the strategy to mammalian genomes, RNA sequencing can be used to construct sample-specific proteoform databases that capture the genetic variation and extent of splicing patterns in the sample (10, 11).”
From Proteoforms as the next proteomics currency (2018) · cites this paper as [10]
There has been recent interest in leveraging RNA-seq sequence variants to improve peptide identification, resulting in basic software tools for integration.
“Additionally, there has been some recent interest in leveraging sequence variants obtained from RNA-seq to improve peptide identification99,100, which have in turn resulted in the production of somewhat basic software tools for integration of such datasets101.”
From Decoding neuroproteomics: integrating the genome, translatome and functional anatomy (2014) · cites this paper as [100]
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- Authors
- Wang, X., Slebos, R. J. C., Wang, D., Halvey, P. J., Tabb, D. L., Liebler, D. C., & Zhang, B.
- Affiliations
- Vanderbilt University (US)
- Corresponding author
- Zhang, Bing
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-12-14
- Volume
- 11
- Issue
- 2
- Pages
- 1009-1017
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- PMC
- PMC3727138
- OpenAlex
- W2042228684
- Cited by
- 173
- References
- 47
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 5 · 2023: 13 · 2022: 9 · 2021: 8 · 2020: 12 · 2019: 11 · 2018: 10 · 2017: 18 · 2016: 15 · 2015: 17 · 2014: 30 · 2013: 11 · 2012: 9
- FWCI
- 7.25
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Journal of Proteome Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01ca126218-05)
- National Cancer Institute (R01-CA-126218, U24CA126479)
- National Institute of General Medical Sciences (R01GM088822)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- peptide identification, single nucleotide variants, protein variants, transcript quantification, lowly expressed genes, protein assembly, colorectal cancer cell lines, SW480 cells
- MeSH terms
- Amino Acid Sequence, Base Sequence, Humans, Molecular Sequence Data, Peptide Mapping, Peptides, Proteins, RNA, Sequence Analysis, RNA, Computational Biology, Gene Expression Profiling, Databases, Protein, Cell Line, Tumor, Transcriptome
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