Biology

Gene

Parallel computing

Massively parallel

Massive parallel sequencing

Computer science

DNA sequencing

Computational biology

Multiplex

Genetics

Nature Genetics

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. VAMP-seq is a scalable assay that measures the effects of missense variants on intracellular protein abundance. Applying VAMP-seq to thousands of PTEN and TPMT variants helps to classify them as pathogenic or benign.

Multiplex assessment of protein variant abundance by massively parallel sequencing