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Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”

BACKGROUND: The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interaction...

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Autores principales: Rau, Christoph D., Gonzales, Natalia M., Bloom, Joshua S., Park, Danny, Ayroles, Julien, Palmer, Abraham A., Lusis, Aldons J., Zaitlen, Noah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644088/
https://www.ncbi.nlm.nih.gov/pubmed/33104702
http://dx.doi.org/10.1371/journal.pgen.1009165
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author Rau, Christoph D.
Gonzales, Natalia M.
Bloom, Joshua S.
Park, Danny
Ayroles, Julien
Palmer, Abraham A.
Lusis, Aldons J.
Zaitlen, Noah
author_facet Rau, Christoph D.
Gonzales, Natalia M.
Bloom, Joshua S.
Park, Danny
Ayroles, Julien
Palmer, Abraham A.
Lusis, Aldons J.
Zaitlen, Noah
author_sort Rau, Christoph D.
collection PubMed
description BACKGROUND: The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors. RESULTS: We applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection. CONCLUSIONS: Unlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.
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spelling pubmed-76440882020-11-16 Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis” Rau, Christoph D. Gonzales, Natalia M. Bloom, Joshua S. Park, Danny Ayroles, Julien Palmer, Abraham A. Lusis, Aldons J. Zaitlen, Noah PLoS Genet Research Article BACKGROUND: The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors. RESULTS: We applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection. CONCLUSIONS: Unlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast. Public Library of Science 2020-10-26 /pmc/articles/PMC7644088/ /pubmed/33104702 http://dx.doi.org/10.1371/journal.pgen.1009165 Text en © 2020 Rau 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rau, Christoph D.
Gonzales, Natalia M.
Bloom, Joshua S.
Park, Danny
Ayroles, Julien
Palmer, Abraham A.
Lusis, Aldons J.
Zaitlen, Noah
Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”
title Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”
title_full Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”
title_fullStr Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”
title_full_unstemmed Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”
title_short Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”
title_sort modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: evidence for “polygenic epistasis”
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644088/
https://www.ncbi.nlm.nih.gov/pubmed/33104702
http://dx.doi.org/10.1371/journal.pgen.1009165
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