The complex underpinnings of genetic background effects

Abstract

Genetic interactions between mutations and standing polymorphisms can cause mutations to show distinct phenotypic effects in different individuals. To characterize the genetic architecture of these so-called background effects, we genotype 1411 wild-type and mutant yeast cross progeny and measure their growth in 10 environments. Using these data, we map 1086 interactions between segregating loci and 7 different gene knockouts. Each knockout exhibits between 73 and 543 interactions, with 89% of all interactions involving higher-order epistasis between a knockout and multiple loci. Identified loci interact with as few as one knockout and as many as all seven knockouts. In mutants, loci interacting with fewer and more knockouts tend to show enhanced and reduced phenotypic effects, respectively. Cross–environment analysis reveals that most interactions between the knockouts and segregating loci also involve the environment. These results illustrate the complicated interactions between mutations, standing polymorphisms, and the environment that cause background effects.

The impact of the genetic background on gene deletion phenotypes in Saccharomyces cerevisiae

“…The S288C strain has genetic variants that render it unable to grow well in maltose and therefore, in this condition, becomes reliant on genes required for nonfermentable growth. It remains a challenge to find similar justifications for how the genetic background interacts with the gene deletions for other conditions, but those identified here could be further studied using a segregant analysis as previously done by Mullis and colleagues (Mullis et al , ). Analysing a larger number of such genetic interactions will be fundamental for deriving general principles for how gene deletion phenotypes change across genetic backgrounds.…”

“…monogenic disorders), incomplete penetrance is frequent, presumably due to differences in the genetic background (Kammenga, ; Hou et al , ). Modulators of penetrance of disease‐causing variants have been identified for many human diseases (Cohen et al , ; Flannick et al , ; Chen et al , ) and loss‐of‐function (LoF) mutations in different model organisms (Hamilton & Yu, ; Chari & Dworkin, ; Vu et al , ; Chow et al , ; Mullis et al , ). This impact of the genetic background on the phenotypic consequence of LoF mutations affects our ability to predict phenotypes based on genetic variants.…”

The impact of the genetic background on gene deletion phenotypes inSaccharomyces cerevisiae

“…The S288C strain, has genetic variants that cause it to not be able to grow well in maltose and therefore, in this condition, becomes reliant on genes required for non-fermentable growth. It remains a challenge to be able to find similar justifications for how the genetic background interacts with the gene deletions for other conditions but those identified here could be further studied using a segregant analysis as previously done by Mullis and colleagues (Mullis et al 2018) .…”

“…monogenic disorders) incomplete penetrance is frequent, presumably due to differences in the genetic background (Kammenga 2017;Hou et al 2018) . Modulators of penetrance of disease causing variants have been identified for many human diseases (Cohen et al 2005;Flannick et al 2014;Chen et al 2016) as well as loss-of-function (LoF) mutations in different model organisms (Hamilton & Yu 2012;Chari & Dworkin 2013;Vu et al 2015;Chow et al 2016;Mullis et al 2018) . This impact of the genetic background on the phenotypic consequence of LoF mutations affects our ability to predict phenotypes based on genetic variants.…”

“…While there are many known examples of background dependencies on LoF mutations few comprehensive studies have addressed this phenomenon. Studies in S. cerevisiae have shown that 5% of essential genes are dispensable between two closely related strains (Ryan et al 2012) and that deletion phenotypes of 7 chromatin-associated genes show quantitative differences across 2 genetic backgrounds that could be mapped via segregant analysis (Mullis et al 2018) . In a systematic RNAi studies in C. elegans , 20% of the 1,400 genes tested had different mutant phenotypes across two backgrounds and natural variation in gene expression accounted for some of the observed differences (Vu et al 2015) .…”