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Prospective functional classification of all possible missense variants in PPARG
Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty1,2. For example, mutations in PPARG cause Mendelian lipodystrophy3,4 and increase risk of type 2 diabetes (T2D)5. While a...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131844/ https://www.ncbi.nlm.nih.gov/pubmed/27749844 http://dx.doi.org/10.1038/ng.3700 |
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author | Majithia, Amit R. Tsuda, Ben Agostini, Maura Gnanapradeepan, Keerthana Rice, Robert Peloso, Gina Patel, Kashyap A. Zhang, Xiaolan Broekema, Marjoleine F. Patterson, Nick Duby, Marc Sharpe, Ted Kalkhoven, Eric Rosen, Evan D. Barroso, Inês Ellard, Sian Kathiresan, Sekar O’Rahilly, Stephen Chatterjee, Krishna Florez, Jose C. Mikkelsen, Tarjei Savage, David B. Altshuler, David |
author_facet | Majithia, Amit R. Tsuda, Ben Agostini, Maura Gnanapradeepan, Keerthana Rice, Robert Peloso, Gina Patel, Kashyap A. Zhang, Xiaolan Broekema, Marjoleine F. Patterson, Nick Duby, Marc Sharpe, Ted Kalkhoven, Eric Rosen, Evan D. Barroso, Inês Ellard, Sian Kathiresan, Sekar O’Rahilly, Stephen Chatterjee, Krishna Florez, Jose C. Mikkelsen, Tarjei Savage, David B. Altshuler, David |
author_sort | Majithia, Amit R. |
collection | PubMed |
description | Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty1,2. For example, mutations in PPARG cause Mendelian lipodystrophy3,4 and increase risk of type 2 diabetes (T2D)5. While approximately one in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning (http://miter.broadinstitute.org). When applied to 55 novel missense variants identified in population-based and clinical sequencing, the classifier annotated six as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes. |
format | Online Article Text |
id | pubmed-5131844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
record_format | MEDLINE/PubMed |
spelling | pubmed-51318442017-04-17 Prospective functional classification of all possible missense variants in PPARG Majithia, Amit R. Tsuda, Ben Agostini, Maura Gnanapradeepan, Keerthana Rice, Robert Peloso, Gina Patel, Kashyap A. Zhang, Xiaolan Broekema, Marjoleine F. Patterson, Nick Duby, Marc Sharpe, Ted Kalkhoven, Eric Rosen, Evan D. Barroso, Inês Ellard, Sian Kathiresan, Sekar O’Rahilly, Stephen Chatterjee, Krishna Florez, Jose C. Mikkelsen, Tarjei Savage, David B. Altshuler, David Nat Genet Article Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty1,2. For example, mutations in PPARG cause Mendelian lipodystrophy3,4 and increase risk of type 2 diabetes (T2D)5. While approximately one in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning (http://miter.broadinstitute.org). When applied to 55 novel missense variants identified in population-based and clinical sequencing, the classifier annotated six as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes. 2016-10-17 2016-12 /pmc/articles/PMC5131844/ /pubmed/27749844 http://dx.doi.org/10.1038/ng.3700 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Majithia, Amit R. Tsuda, Ben Agostini, Maura Gnanapradeepan, Keerthana Rice, Robert Peloso, Gina Patel, Kashyap A. Zhang, Xiaolan Broekema, Marjoleine F. Patterson, Nick Duby, Marc Sharpe, Ted Kalkhoven, Eric Rosen, Evan D. Barroso, Inês Ellard, Sian Kathiresan, Sekar O’Rahilly, Stephen Chatterjee, Krishna Florez, Jose C. Mikkelsen, Tarjei Savage, David B. Altshuler, David Prospective functional classification of all possible missense variants in PPARG |
title | Prospective functional classification of all possible missense variants in PPARG |
title_full | Prospective functional classification of all possible missense variants in PPARG |
title_fullStr | Prospective functional classification of all possible missense variants in PPARG |
title_full_unstemmed | Prospective functional classification of all possible missense variants in PPARG |
title_short | Prospective functional classification of all possible missense variants in PPARG |
title_sort | prospective functional classification of all possible missense variants in pparg |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131844/ https://www.ncbi.nlm.nih.gov/pubmed/27749844 http://dx.doi.org/10.1038/ng.3700 |
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