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Gray, V. E.

Publications and source records attributed to Gray, V. E..

2 recordsLinked to original sources

Multiplex Assessment of Protein Variant Abundance by Massively Parallel Sequencing

Determining the pathogenicity of human 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 will likely require generalizable, scalable assays. Here 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 in a single experiment. We apply VAMP-seq to quantify the abundance of 7,595 single amino acid variants of two proteins, PTEN and TPMT, in which functional variants are clinically actionable. We identify 1,079 PTEN and 805 TPMT single amino acid 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 our abundance data suggest that a PTEN variant accounting for ~10% of PTEN missense variants in melanomas functions via a dominant negative mechanism. Finally, we demonstrate that VAMP-seq can be applied to other genes, highlighting its potential as a generalizable assay for characterizing missense variants.

genetics

Using Large-Scale Mutagenesis To Guide Single Amino Acid Scanning Experiments

Alanine scanning mutagenesis is a widely-used method for identifying protein positions that are important for function or ligand binding. Alanine was chosen because it is physicochemically innocuous and constitutes a deletion of the side chain at the {beta}- carbon. Alanine is also thought to best represent the effects of other mutations; however, this assumption has not been formally tested. To determine whether alanine substitutions are always the best choice, we analyzed 34,373 mutations in fourteen proteins whose effects were measured using large-scale mutagenesis approaches. We found that several substitutions, including histidine and asparagine, are better at recapitulating the effects of other substitutions. Histidine and asparagine also correlated best with the effects of other substitutions in different structural contexts. Furthermore, we found that alanine is among the worst substitutions for detecting ligand interface positions, despite its frequent use for this purpose. Our work highlights the utility of large-scale mutagenesis data and can help to guide future single substitution mutational scans.

molecular biology