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Title: Genetic background effects in quantitative genetics: gene-by-system interactions

Abstract

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype–phenotype relationships across individuals.

Authors:
 [1];  [2]
  1. Univ. of Wisconsin, Madison, WI (United States). Great Lakes Bioenergy Research Center
  2. Univ. of Wisconsin, Madison, WI (United States). Great Lakes Bioenergy Research Center, and Lab. of Genetics
Publication Date:
Research Org.:
Univ. of Wisconsin, Madison, WI (United States). Great Lakes Bioenergy Research Center
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1459533
Grant/Contract Number:
SC0018409
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Current Genetics
Additional Journal Information:
Journal Name: Current Genetics; Journal ID: ISSN 0172-8083
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; Genetic architecture; Epistasis; Quantitative genetics; Biofuels; Stress tolerance

Citation Formats

Sardi, Maria, and Gasch, Audrey P. Genetic background effects in quantitative genetics: gene-by-system interactions. United States: N. p., 2018. Web. doi:10.1007/s00294-018-0835-7.
Sardi, Maria, & Gasch, Audrey P. Genetic background effects in quantitative genetics: gene-by-system interactions. United States. doi:10.1007/s00294-018-0835-7.
Sardi, Maria, and Gasch, Audrey P. Wed . "Genetic background effects in quantitative genetics: gene-by-system interactions". United States. doi:10.1007/s00294-018-0835-7.
@article{osti_1459533,
title = {Genetic background effects in quantitative genetics: gene-by-system interactions},
author = {Sardi, Maria and Gasch, Audrey P.},
abstractNote = {Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype–phenotype relationships across individuals.},
doi = {10.1007/s00294-018-0835-7},
journal = {Current Genetics},
number = ,
volume = ,
place = {United States},
year = {Wed Apr 11 00:00:00 EDT 2018},
month = {Wed Apr 11 00:00:00 EDT 2018}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on April 11, 2019
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