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Cited by 187Genomics and Rare DiseasesCRISPR and Genetic EngineeringCancer Genomics and Diagnostics

A framework for exhaustively mapping functional missense variants

Open access
Weile, Jochen, Sun, Song, Cote, Atina G, Knapp, Jennifer, Verby, Marta, Mellor, Joseph C, Wu, Yingzhou, Pons, Carles +13 more·2017·Molecular Systems Biology
DOI 10.15252/msb.20177908PMC PMC5740498

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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.

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  • TileSeqMave v1.0 is commonly used in MAVEs employing a direct/tile sequence approach.

    “Examples include TileSeqMave v1.0 (47), commonly used in MAVEs employing a direct/tile sequence approach, and Enrich2 (100), widely adopted for MAVEs utilising barcode sequencing (89).”

    From Massively parallel functional genomic assays in endocrinology: from promise to delivery (2026) · cites this paper as [47]

    The Results section ('A tiled-region strategy for mapping functional variation'; page unavailable) describes direct sequencing of tiled amplicons for DMS-TileSeq, and 'Code and data availability' lists a TileSeq sequence analysis pipeline. Our copy does not identify that pipeline as 'TileSeqMave v1.0' or establish that it is commonly used across MAVEs. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Yeast models have been used to screen human disease genes in complementation assays, where the human gene functionally replaces a homologous yeast gene essential for growth, as well as protein-protein and protein-DNA interactions.

    “Yeast models have also been used to screen human disease genes in complementation assays, where the human gene functionally replaces a homologous yeast gene essential for growth (47), as well as protein–protein and protein–DNA interactions (67, 68).”

    From Massively parallel functional genomic assays in endocrinology: from promise to delivery (2026) · cites this paper as [47]

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Authors
Weile, J., Sun, S., Cote, A. G., Knapp, J., Verby, M., Mellor, J. C., Wu, Y., Pons, C., Wong, C., van Lieshout, N., Yang, F., Tasan, M., Tan, G., Yang, S., Fowler, D. M., Nussbaum, R., Bloom, J. D., Vidal, M., Hill, D. E., Aloy, P., & Roth, F. P.
Affiliations
  • Mount Sinai Hospital (CA)
  • Uppsala University (SE)
  • University of Toronto (CA)
  • Institute for Research in Biomedicine (ES)
  • Invitae (United States) (US)
  • University of Washington (US)
  • Fred Hutch Cancer Center (US)
  • Harvard University (US)
  • Dana-Farber Cancer Institute (US)
  • Institució Catalana de Recerca i Estudis Avançats (ES)
  • Canadian Institute for Advanced Research (CA)
ORCID
Venue
Molecular Systems Biology
Publisher
Springer Science and Business Media LLC
Published
2017-12-01
Volume
13
Issue
12
Pages
957-957
ISSN
1744-4292 (ISSN-L)
DOI
10.15252/msb.20177908
PMC
PMC5740498
OpenAlex
W2781028774
Cited by
187
References
3
Citations by year
2026: 21 · 2025: 23 · 2024: 26 · 2023: 26 · 2022: 20 · 2021: 26 · 2020: 18 · 2019: 14 · 2018: 11 · 2017: 2
FWCI
7.98
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Systems Biology (publishedVersion, other-oa)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • NIH/NHGRI Center of Excellence in Genomic Science (HG004233)
  • the Canadian Excellence Research Chairs Program
  • the Ontario Ministry of Research and Innovation
  • Swedish Research Council International Postdoc Grant
  • One Brave Idea Fund
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Keywords
deep mutational scanning, missense mutations, variant imputation, Ubc9, SUMO1, TPK1, calmodulin, pathogenic variants, human disease genes
MeSH terms
Machine Learning, Ubiquitin-Conjugating Enzyme UBC9, Calmodulin, Disease, DNA Mutational Analysis, Humans, Phenotype, Phylogeny, Reproducibility of Results, Mutation, Missense, SUMO-1 Protein, Ubiquitin-Conjugating Enzymes

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