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A framework for exhaustively mapping functional missense variants
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 mutagenesi...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740498/ https://www.ncbi.nlm.nih.gov/pubmed/29269382 http://dx.doi.org/10.15252/msb.20177908 |
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author | Weile, Jochen Sun, Song Cote, Atina G Knapp, Jennifer Verby, Marta Mellor, Joseph C Wu, Yingzhou Pons, Carles Wong, Cassandra van 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 |
author_facet | Weile, Jochen Sun, Song Cote, Atina G Knapp, Jennifer Verby, Marta Mellor, Joseph C Wu, Yingzhou Pons, Carles Wong, Cassandra van 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 |
author_sort | Weile, Jochen |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5740498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57404982018-01-02 A framework for exhaustively mapping functional missense variants Weile, Jochen Sun, Song Cote, Atina G Knapp, Jennifer Verby, Marta Mellor, Joseph C Wu, Yingzhou Pons, Carles Wong, Cassandra van 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 Mol Syst Biol Methods 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. John Wiley and Sons Inc. 2017-12-21 /pmc/articles/PMC5740498/ /pubmed/29269382 http://dx.doi.org/10.15252/msb.20177908 Text en © 2017 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Weile, Jochen Sun, Song Cote, Atina G Knapp, Jennifer Verby, Marta Mellor, Joseph C Wu, Yingzhou Pons, Carles Wong, Cassandra van 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 A framework for exhaustively mapping functional missense variants |
title | A framework for exhaustively mapping functional missense variants |
title_full | A framework for exhaustively mapping functional missense variants |
title_fullStr | A framework for exhaustively mapping functional missense variants |
title_full_unstemmed | A framework for exhaustively mapping functional missense variants |
title_short | A framework for exhaustively mapping functional missense variants |
title_sort | framework for exhaustively mapping functional missense variants |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740498/ https://www.ncbi.nlm.nih.gov/pubmed/29269382 http://dx.doi.org/10.15252/msb.20177908 |
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