Peptide Correlation Analysis (PeCorA) Reveals Differential Proteoform Regulation
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Abstract
Shotgun proteomics techniques infer the presence and quantity of proteins using peptide proxies produced by cleavage of the proteome with a protease. Most protein quantitation strategies assume that multiple peptides derived from a protein will behave quantitatively similar across treatment groups, but this assumption may be false due to (1) heterogeneous proteoforms and (2) technical artifacts. Here we describe a strategy called peptide correlation analysis (PeCorA) that detects quantitative disagreements between peptides mapped to the same protein. PeCorA fits linear models to assess whether a peptide's change across treatment groups differs from all other peptides assigned to the same protein. PeCorA revealed that ∼15% of proteins in a mouse microglia stress data set contain at least one discordant peptide. Inspection of the discordant peptides shows the utility of PeCorA for the direct and indirect detection of regulated post-translational modifications (PTMs) and also for the discovery of poorly quantified peptides. The exclusion of poorly quantified peptides before protein quantity summarization decreased false-positives in a benchmark data set. Finally, PeCorA suggests that the inactive isoform of prothrombin, a coagulation cascade protease, is more abundant in plasma from COVID-19 patients relative to non-COVID-19 controls. PeCorA is freely available as an R package that works with arbitrary tables of quantified peptides.
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Outlier-exclusion methods improve protein concentration estimates but still report only one protein quantity and ignore peptides that do not agree with that value.
“While these all demonstrate improved protein concentration estimates, they still only report a single protein quantity and ignore peptides that do not agree with that single value.”
From Putting humpty dumpty back together again: what does protein quantification mean in bottom-up proteomics? (2022) · cites this paper as [33]
Several proposed methods exclude peptide measurements from the aggregate protein quantity when they are outliers relative to other peptides mapping to the same protein-coding gene.
“The approach of several proposed methods focuses on the exclusion of peptide measurements from inclusion in the aggregate protein quantity if they are outliers from other peptide measurements mapping to the same protein coding gene.(28–33)”
From Putting humpty dumpty back together again: what does protein quantification mean in bottom-up proteomics? (2022) · cites this paper as [33]
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Systematic detection of functional proteoform groups from bottom-up proteomic datasets
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- Authors
- Dermit, M., Peters-Clarke, T. M., Shishkova, E., & Meyer, J. G.
- Affiliations
- Queen Mary University of London (GB)
- University of Wisconsin–Madison (US)
- Corresponding author
- Meyer, Jesse G.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-12-16
- Volume
- 20
- Issue
- 4
- Pages
- 1972-1980
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- PMC
- PMC8592057
- OpenAlex
- W3112512988
- Cited by
- 40
- References
- 42
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 10 · 2023: 9 · 2022: 4 · 2021: 5
- FWCI
- 1.72
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Journal of Proteome Research (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Human Genome Research Institute (T32HG002760)
- National Institute of General Medical Sciences (P41GM108538)
- U.S. National Library of Medicine (T15LM007359)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- protein quantification, post-translational modification, mice, proteomics data analysis
- MeSH terms
- COVID-19, Animals, Humans, Peptides, Protein Processing, Post-Translational, Prothrombin, Microglia, Proteome, Proteomics, Mice
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