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Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes
Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing pot...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575292/ https://www.ncbi.nlm.nih.gov/pubmed/28851873 http://dx.doi.org/10.1038/s41467-017-00443-5 |
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author | Balasubramanian, Suganthi Fu, Yao Pawashe, Mayur McGillivray, Patrick Jin, Mike Liu, Jeremy Karczewski, Konrad J. MacArthur, Daniel G. Gerstein, Mark |
author_facet | Balasubramanian, Suganthi Fu, Yao Pawashe, Mayur McGillivray, Patrick Jin, Mike Liu, Jeremy Karczewski, Konrad J. MacArthur, Daniel G. Gerstein, Mark |
author_sort | Balasubramanian, Suganthi |
collection | PubMed |
description | Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes. |
format | Online Article Text |
id | pubmed-5575292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55752922017-09-01 Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes Balasubramanian, Suganthi Fu, Yao Pawashe, Mayur McGillivray, Patrick Jin, Mike Liu, Jeremy Karczewski, Konrad J. MacArthur, Daniel G. Gerstein, Mark Nat Commun Article Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes. Nature Publishing Group UK 2017-08-29 /pmc/articles/PMC5575292/ /pubmed/28851873 http://dx.doi.org/10.1038/s41467-017-00443-5 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Balasubramanian, Suganthi Fu, Yao Pawashe, Mayur McGillivray, Patrick Jin, Mike Liu, Jeremy Karczewski, Konrad J. MacArthur, Daniel G. Gerstein, Mark Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes |
title | Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes |
title_full | Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes |
title_fullStr | Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes |
title_full_unstemmed | Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes |
title_short | Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes |
title_sort | using aloft to determine the impact of putative loss-of-function variants in protein-coding genes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575292/ https://www.ncbi.nlm.nih.gov/pubmed/28851873 http://dx.doi.org/10.1038/s41467-017-00443-5 |
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