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Genetic interactions affecting human gene expression identified by variance association mapping
Non-additive interaction between genetic variants, or epistasis, is a possible explanation for the gap between heritability of complex traits and the variation explained by identified genetic loci. Interactions give rise to genotype dependent variance, and therefore the identification of variance qu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017648/ https://www.ncbi.nlm.nih.gov/pubmed/24771767 http://dx.doi.org/10.7554/eLife.01381 |
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author | Brown, Andrew Anand Buil, Alfonso Viñuela, Ana Lappalainen, Tuuli Zheng, Hou-Feng Richards, J Brent Small, Kerrin S Spector, Timothy D Dermitzakis, Emmanouil T Durbin, Richard |
author_facet | Brown, Andrew Anand Buil, Alfonso Viñuela, Ana Lappalainen, Tuuli Zheng, Hou-Feng Richards, J Brent Small, Kerrin S Spector, Timothy D Dermitzakis, Emmanouil T Durbin, Richard |
author_sort | Brown, Andrew Anand |
collection | PubMed |
description | Non-additive interaction between genetic variants, or epistasis, is a possible explanation for the gap between heritability of complex traits and the variation explained by identified genetic loci. Interactions give rise to genotype dependent variance, and therefore the identification of variance quantitative trait loci can be an intermediate step to discover both epistasis and gene by environment effects (GxE). Using RNA-sequence data from lymphoblastoid cell lines (LCLs) from the TwinsUK cohort, we identify a candidate set of 508 variance associated SNPs. Exploiting the twin design we show that GxE plays a role in ∼70% of these associations. Further investigation of these loci reveals 57 epistatic interactions that replicated in a smaller dataset, explaining on average 4.3% of phenotypic variance. In 24 cases, more variance is explained by the interaction than their additive contributions. Using molecular phenotypes in this way may provide a route to uncovering genetic interactions underlying more complex traits. DOI: http://dx.doi.org/10.7554/eLife.01381.001 |
format | Online Article Text |
id | pubmed-4017648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-40176482014-05-22 Genetic interactions affecting human gene expression identified by variance association mapping Brown, Andrew Anand Buil, Alfonso Viñuela, Ana Lappalainen, Tuuli Zheng, Hou-Feng Richards, J Brent Small, Kerrin S Spector, Timothy D Dermitzakis, Emmanouil T Durbin, Richard eLife Genes and Chromosomes Non-additive interaction between genetic variants, or epistasis, is a possible explanation for the gap between heritability of complex traits and the variation explained by identified genetic loci. Interactions give rise to genotype dependent variance, and therefore the identification of variance quantitative trait loci can be an intermediate step to discover both epistasis and gene by environment effects (GxE). Using RNA-sequence data from lymphoblastoid cell lines (LCLs) from the TwinsUK cohort, we identify a candidate set of 508 variance associated SNPs. Exploiting the twin design we show that GxE plays a role in ∼70% of these associations. Further investigation of these loci reveals 57 epistatic interactions that replicated in a smaller dataset, explaining on average 4.3% of phenotypic variance. In 24 cases, more variance is explained by the interaction than their additive contributions. Using molecular phenotypes in this way may provide a route to uncovering genetic interactions underlying more complex traits. DOI: http://dx.doi.org/10.7554/eLife.01381.001 eLife Sciences Publications, Ltd 2014-04-25 /pmc/articles/PMC4017648/ /pubmed/24771767 http://dx.doi.org/10.7554/eLife.01381 Text en Copyright © 2014, Brown et al http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Genes and Chromosomes Brown, Andrew Anand Buil, Alfonso Viñuela, Ana Lappalainen, Tuuli Zheng, Hou-Feng Richards, J Brent Small, Kerrin S Spector, Timothy D Dermitzakis, Emmanouil T Durbin, Richard Genetic interactions affecting human gene expression identified by variance association mapping |
title | Genetic interactions affecting human gene expression identified by variance association mapping |
title_full | Genetic interactions affecting human gene expression identified by variance association mapping |
title_fullStr | Genetic interactions affecting human gene expression identified by variance association mapping |
title_full_unstemmed | Genetic interactions affecting human gene expression identified by variance association mapping |
title_short | Genetic interactions affecting human gene expression identified by variance association mapping |
title_sort | genetic interactions affecting human gene expression identified by variance association mapping |
topic | Genes and Chromosomes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017648/ https://www.ncbi.nlm.nih.gov/pubmed/24771767 http://dx.doi.org/10.7554/eLife.01381 |
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