Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics.
There is broad agreement that genetic mutations occurring outside of the protein-coding regions play a key role in human disease. Despite this consensus, we are not yet capable of discerning which portions of non-coding sequence are important in the context of human disease. Here, we present Orion,...
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doaj-77957e0e6431494b96c88130183042b42021-03-04T11:27:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01128e018160410.1371/journal.pone.0181604Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics.Ayal B GussowBrett R CopelandRyan S DhindsaQuanli WangSlavé PetrovskiWilliam H MajorosAndrew S AllenDavid B GoldsteinThere is broad agreement that genetic mutations occurring outside of the protein-coding regions play a key role in human disease. Despite this consensus, we are not yet capable of discerning which portions of non-coding sequence are important in the context of human disease. Here, we present Orion, an approach that detects regions of the non-coding genome that are depleted of variation, suggesting that the regions are intolerant of mutations and subject to purifying selection in the human lineage. We show that Orion is highly correlated with known intolerant regions as well as regions that harbor putatively pathogenic variation. This approach provides a mechanism to identify pathogenic variation in the human non-coding genome and will have immediate utility in the diagnostic interpretation of patient genomes and in large case control studies using whole-genome sequences.https://doi.org/10.1371/journal.pone.0181604 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ayal B Gussow Brett R Copeland Ryan S Dhindsa Quanli Wang Slavé Petrovski William H Majoros Andrew S Allen David B Goldstein |
spellingShingle |
Ayal B Gussow Brett R Copeland Ryan S Dhindsa Quanli Wang Slavé Petrovski William H Majoros Andrew S Allen David B Goldstein Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics. PLoS ONE |
author_facet |
Ayal B Gussow Brett R Copeland Ryan S Dhindsa Quanli Wang Slavé Petrovski William H Majoros Andrew S Allen David B Goldstein |
author_sort |
Ayal B Gussow |
title |
Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics. |
title_short |
Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics. |
title_full |
Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics. |
title_fullStr |
Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics. |
title_full_unstemmed |
Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics. |
title_sort |
orion: detecting regions of the human non-coding genome that are intolerant to variation using population genetics. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2017-01-01 |
description |
There is broad agreement that genetic mutations occurring outside of the protein-coding regions play a key role in human disease. Despite this consensus, we are not yet capable of discerning which portions of non-coding sequence are important in the context of human disease. Here, we present Orion, an approach that detects regions of the non-coding genome that are depleted of variation, suggesting that the regions are intolerant of mutations and subject to purifying selection in the human lineage. We show that Orion is highly correlated with known intolerant regions as well as regions that harbor putatively pathogenic variation. This approach provides a mechanism to identify pathogenic variation in the human non-coding genome and will have immediate utility in the diagnostic interpretation of patient genomes and in large case control studies using whole-genome sequences. |
url |
https://doi.org/10.1371/journal.pone.0181604 |
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