Open AccessA framework for exhaustively mapping functional missense variants
Author(s) -
Weile Jochen,
Sun Song,
Cote Atina G,
Knapp Jennifer,
Verby Marta,
Mellor Joseph C,
Wu Yingzhou,
Pons Carles,
Wong Cassandra,
Lieshout Natascha,
Yang Fan,
Tasan Murat,
Tan Guihong,
Yang Shan,
Fowler Douglas M,
Nussbaum Robert,
Bloom Jesse D,
Vidal Marc,
Hill David E,
Aloy Patrick,
Roth Frederick P
Publication year - 2017
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.15252/msb.20177908
Subject(s) - biology , missense mutation , computational biology , genetics , evolutionary biology , mutation , gene
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: UBE 2I (encoding SUMO E2 conjugase), SUMO 1 (small ubiquitin‐like modifier), TPK 1 (thiamin pyrophosphokinase), and CALM 1/2/3 (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.