Epistasis dominates the genetic architecture of Drosophila quantitative traits

Wen Huang, Stephen Richards, Mary Anna Carbone, Dianhui Zhu, Robert R.H. Anholt, Julien F. Ayroles, Laura Duncan, Katherine W. Jordan, Faye Lawrence, Michael M. Magwire, Crystal B. Warner, Kerstin Blankenburg, Yi Han, Mehwish Javaid, Joy Jayaseelan, Shalini N. Jhangiani, Donna Muzny, Fiona Ongeri, Lora Perales, Yuan Qing WuYiqing Zhang, Xiaoyan Zou, Eric A. Stone, Richard A. Gibbs, Trudy F.C. Mackay

Research output: Contribution to journalArticlepeer-review

271 Scopus citations


Epistasis - nonlinear genetic interactions between polymorphic loci-is the genetic basis of canalization and speciation, and epistatic interactions can be used to infer genetic networks affecting quantitative traits. However, the role that epistasis plays in the genetic architecture of quantitative traits is controversial. Here, we compared the genetic architecture of three Drosophila life history traits in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and a large outbred, advanced intercross population derived from 40 DGRP lines (Flyland). We assessed allele frequency changes between pools of individuals at the extremes of the distribution for each trait in the Flyland population by deep DNA sequencing. The genetic architecture of all traits was highly polygenic in both analyses. Surprisingly, none of the SNPs associated with the traits in Flyland replicated in the DGRP and vice versa. However, the majority of these SNPs participated in at least one epistatic interaction in the DGRP. Despite apparent additive effects at largely distinct loci in the two populations, the epistatic interactions perturbed common, biologically plausible, and highly connected genetic networks. Our analysis underscores the importance of epistasis as a principal factor that determines variation for quantitative traits and provides a means to uncover genetic networks affecting these traits. Knowledge of epistatic networks will contribute to our understanding of the genetic basis of evolutionarily and clinically important traits and enhance predictive ability at an individualized level in medicine and agriculture.

Original languageEnglish (US)
Pages (from-to)15553-15559
Number of pages7
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number39
StatePublished - Sep 25 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General


  • Chill coma recovery
  • Genetic interaction networks
  • Genome-wide association studies
  • Startle response
  • Starvation resistance


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