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Cited by 436Genomics and Rare DiseasesCancer Genomics and DiagnosticsGenetic Associations and Epidemiology

Multiplex assessment of protein variant abundance by massively parallel sequencing

Open access
Matreyek, Kenneth A., Starita, Lea M., Stephany, Jason J., Martin, Beth, Chiasson, Melissa A., Gray, Vanessa E., Kircher, Martin, Khechaduri, Arineh +8 more·2018·Nature Genetics
DOI 10.1038/s41588-018-0122-zPMC PMC5980760

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Abstract

Determining the pathogenicity of genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes requires generalizable, scalable assays. We describe variant abundance by massively parallel sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance simultaneously. We apply VAMP-seq to quantify the abundance of 7,801 single-amino-acid variants of PTEN and TPMT, proteins in which functional variants are clinically actionable. We identify 1,138 PTEN and 777 TPMT variants that result in low protein abundance, and may be pathogenic or alter drug metabolism, respectively. We observe selection for low-abundance PTEN variants in cancer, and show that p.Pro38Ser, which accounts for ~10% of PTEN missense variants in melanoma, functions via a dominant-negative mechanism. Finally, we demonstrate that VAMP-seq is applicable to other genes, highlighting its generalizability.

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  • Abundance-based assays such as VAMP-seq showed lower classification performance (ROC AUC ∼0.70-0.78).

    “In contrast, abundance-based assays such as VAMP-seq showed lower classification performance (ROC AUC ∼0.70–0.78), suggesting that assays measuring protein function directly generally provide larger effect sizes and improved variant discrimination compared to stability or abundance assay (70).”

    From Massively parallel functional genomic assays in endocrinology: from promise to delivery (2026) · cites this paper as [70]

    The Discussion identifies VAMP-seq as an assay of protein variant abundance, and the Online Methods describe how it classifies variants. Neither section reports a ROC AUC of approximately 0.70–0.78; the searched passages also do not establish that its classification performance is lower than that of direct-function assays. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Assays measuring protein function directly generally provide larger effect sizes and improved variant discrimination compared to stability or abundance assays.

    “In contrast, abundance-based assays such as VAMP-seq showed lower classification performance (ROC AUC ∼0.70–0.78), suggesting that assays measuring protein function directly generally provide larger effect sizes and improved variant discrimination compared to stability or abundance assay (70).”

    From Massively parallel functional genomic assays in endocrinology: from promise to delivery (2026) · cites this paper as [70]

    The Results (‘New, potentially pathogenic low-abundance PTEN variants’; page unavailable) report that some pathogenic PTEN variants retain normal abundance despite being inactive, supporting a limitation of abundance-based discrimination. The paper identifies VAMP-seq as an abundance assay, but our copy does not report the cited ROC AUC range or establish that direct-function assays generally produce larger effect sizes or better variant discrimination. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • VAMP-seq has been optimised and validated across multiple targets.

    “Common strategies involve fusion of the gene of interest to a gene encoding a fluorescent protein, with fluorescence used as a surrogate for expression of the target protein, in the assay subtype known as VAMP-seq (variant abundance by massively parallel sequencing), which has been optimised and validated across multiple targets (70).”

    From Massively parallel functional genomic assays in endocrinology: from promise to delivery (2026) · cites this paper as [70]

    The Results section validates VAMP-seq abundance measurements for PTEN and TPMT against individual experiments and western blots. It also reports preliminary applicability tests for five additional proteins, but not comparable validation or optimisation across those targets; two other proteins tested were unsuitable. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • HEK293 cells have been modified to optimise variant library integration, rendering them particularly useful for generic functional assays such as VAMP-seq, which determines variant effects on protein abundance.

    “HEK293 cells have moreover been modified to optimise variant library integration, rendering them particularly useful for generic functional assays such as VAMP-seq, which determines variant effects on protein abundance (70, 71).”

    From Massively parallel functional genomic assays in endocrinology: from promise to delivery (2026) · cites this paper as [70]

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Authors
Matreyek, K. A., Starita, L. M., Stephany, J. J., Martin, B., Chiasson, M. A., Gray, V. E., Kircher, M., Khechaduri, A., Dines, J. N., Hause, R. J., Bhatia, S., Evans, W. E., Relling, M. V., Yang, W., Shendure, J., & Fowler, D. M.
Affiliations
  • University of Washington (US)
  • University of Alabama at Birmingham (US)
  • St. Jude Children's Research Hospital (US)
  • Howard Hughes Medical Institute (US)
  • Canadian Institute for Advanced Research (CA)
Corresponding author
  • Shendure, Jay
  • Fowler, Douglas M.
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2018-05-21
Volume
50
Issue
6
Pages
874-882
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-018-0122-z
PMC
PMC5980760
OpenAlex
W2950629294
Cited by
436
References
7
Citations by year
2026: 67 · 2025: 47 · 2024: 75 · 2023: 49 · 2022: 42 · 2021: 53 · 2020: 54 · 2019: 41 · 2018: 8
FWCI
23.55
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature Genetics (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Howard Hughes Medical Institute
  • American Association for Cancer Research
  • University of Washington
  • National Institutes of Health (CA21765))
  • National Human Genome Research Institute (DP1HG007811)
  • National Cancer Institute (R01CA036401, R01CA096670, CA21765, P30CA021765, T32CA080416)
  • National Institute of General Medical Sciences (R01GM109110, P50GM115279, R24GM115277, CA21765, T32GM007454)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
missense mutations, PTEN, thiopurine S-methyltransferase, pathogenicity classification, protein abundance, melanoma, dominant-negative mechanism, drug metabolism, functional genomics
MeSH terms
Amino Acids, Cell Line, Humans, Sequence Analysis, DNA, Mutation, Missense, PTEN Phosphohydrolase, HEK293 Cells, High-Throughput Nucleotide Sequencing

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