Abstract
Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin‐like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.
Highlights
We routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact
We describe a framework for comprehensively mapping functional missense variation, organized into six stages: (i) mutagenesis; (ii) generation of a variant library; (iii) selection of functional variants; (iv) readout of the selection results and analysis to produce an initial sequence-function map; (iv) computational analysis to impute missing values; and (vi) computational analysis to refine measured values via machine learning
We scaled up a previous mutagenesis protocol (Seyfang & Huaqian Jin, 2004) to develop Precision OligoPool based Code Alteration (POPCode), which yields random codon replacements
Summary
We routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. We developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin-like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could map functional variation for all human disease genes.
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