| Institution: | 1. Lunenfeld‐Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada;2. The Donnelly Centre, University of Toronto, Toronto, ON, Canada;3. Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada;4. SeqWell Inc, Boston, MA, USA;5. Department of Computer Science, University of Toronto, Toronto, ON, Canada;6. Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain;7. Invitae Corp., San Francisco, CA, USA;8. Department of Genome Sciences, University of Washington, Seattle, WA, USA;9. Fred Hutchinson Research Center, Seattle, WA, USA;10. Center for Cancer Systems Biology (CCSB), Dana‐Farber Cancer Institute, Boston, MA, USA;11. Department of Genetics, Harvard Medical School, Boston, MA, USA;12. Institució Catalana de Recerca I Estudis Avan?ats (ICREA), Barcelona, Catalonia, Spain;13. Canadian Institute for Advanced Research, Toronto, ON, Canada |
| 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. |
