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Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes
A central challenge in interpreting personal genomes is determining which mutations most likely influence disease. Although progress has been made in scoring the functional impact of individual mutations, the characteristics of the genes in which those mutations are found remain largely unexplored....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3749936/ https://www.ncbi.nlm.nih.gov/pubmed/23990802 http://dx.doi.org/10.1371/journal.pgen.1003709 |
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author | Petrovski, Slavé Wang, Quanli Heinzen, Erin L. Allen, Andrew S. Goldstein, David B. |
author_facet | Petrovski, Slavé Wang, Quanli Heinzen, Erin L. Allen, Andrew S. Goldstein, David B. |
author_sort | Petrovski, Slavé |
collection | PubMed |
description | A central challenge in interpreting personal genomes is determining which mutations most likely influence disease. Although progress has been made in scoring the functional impact of individual mutations, the characteristics of the genes in which those mutations are found remain largely unexplored. For example, genes known to carry few common functional variants in healthy individuals may be judged more likely to cause certain kinds of disease than genes known to carry many such variants. Until now, however, it has not been possible to develop a quantitative assessment of how well genes tolerate functional genetic variation on a genome-wide scale. Here we describe an effort that uses sequence data from 6503 whole exome sequences made available by the NHLBI Exome Sequencing Project (ESP). Specifically, we develop an intolerance scoring system that assesses whether genes have relatively more or less functional genetic variation than expected based on the apparently neutral variation found in the gene. To illustrate the utility of this intolerance score, we show that genes responsible for Mendelian diseases are significantly more intolerant to functional genetic variation than genes that do not cause any known disease, but with striking variation in intolerance among genes causing different classes of genetic disease. We conclude by showing that use of an intolerance ranking system can aid in interpreting personal genomes and identifying pathogenic mutations. |
format | Online Article Text |
id | pubmed-3749936 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37499362013-08-29 Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes Petrovski, Slavé Wang, Quanli Heinzen, Erin L. Allen, Andrew S. Goldstein, David B. PLoS Genet Research Article A central challenge in interpreting personal genomes is determining which mutations most likely influence disease. Although progress has been made in scoring the functional impact of individual mutations, the characteristics of the genes in which those mutations are found remain largely unexplored. For example, genes known to carry few common functional variants in healthy individuals may be judged more likely to cause certain kinds of disease than genes known to carry many such variants. Until now, however, it has not been possible to develop a quantitative assessment of how well genes tolerate functional genetic variation on a genome-wide scale. Here we describe an effort that uses sequence data from 6503 whole exome sequences made available by the NHLBI Exome Sequencing Project (ESP). Specifically, we develop an intolerance scoring system that assesses whether genes have relatively more or less functional genetic variation than expected based on the apparently neutral variation found in the gene. To illustrate the utility of this intolerance score, we show that genes responsible for Mendelian diseases are significantly more intolerant to functional genetic variation than genes that do not cause any known disease, but with striking variation in intolerance among genes causing different classes of genetic disease. We conclude by showing that use of an intolerance ranking system can aid in interpreting personal genomes and identifying pathogenic mutations. Public Library of Science 2013-08-22 /pmc/articles/PMC3749936/ /pubmed/23990802 http://dx.doi.org/10.1371/journal.pgen.1003709 Text en © 2013 Petrovski et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Petrovski, Slavé Wang, Quanli Heinzen, Erin L. Allen, Andrew S. Goldstein, David B. Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes |
title | Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes |
title_full | Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes |
title_fullStr | Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes |
title_full_unstemmed | Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes |
title_short | Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes |
title_sort | genic intolerance to functional variation and the interpretation of personal genomes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3749936/ https://www.ncbi.nlm.nih.gov/pubmed/23990802 http://dx.doi.org/10.1371/journal.pgen.1003709 |
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