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Nat Genet. 2018 Jun;50(6):874-882. doi: 10.1038/s41588-018-0122-z. Epub 2018 May 21.

Multiplex assessment of protein variant abundance by massively parallel sequencing.

Author information

1
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
2
Department of Medical Genetics, University of Washington, Seattle, WA, USA.
3
School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
4
Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, USA.
5
Department of Genome Sciences, University of Washington, Seattle, WA, USA. shendure@u.washington.edu.
6
Howard Hughes Medical Institute, Seattle, WA, USA. shendure@u.washington.edu.
7
Department of Genome Sciences, University of Washington, Seattle, WA, USA. dfowler@uw.edu.
8
Department of Bioengineering, University of Washington, Seattle, WA, USA. dfowler@uw.edu.
9
Genetic Networks Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada. dfowler@uw.edu.

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.

PMID:
29785012
PMCID:
PMC5980760
DOI:
10.1038/s41588-018-0122-z
[Indexed for MEDLINE]
Free PMC Article

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