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

Christoph D. Rau, Natalia M. Gonzales, Joshua S. Bloom, Danny Park, Julien Ayroles, Abraham A. Palmer, Aldons J. Lusis, Noah Zaitlen

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Article numbere1009165
JournalPLoS genetics
Issue number10
StatePublished - Oct 26 2020

All Science Journal Classification (ASJC) codes

  • Genetics(clinical)
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Cancer Research


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