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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...

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Autores principales: Balasubramanian, Suganthi, Fu, Yao, Pawashe, Mayur, McGillivray, Patrick, Jin, Mike, Liu, Jeremy, Karczewski, Konrad J., MacArthur, Daniel G., Gerstein, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
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.
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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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