Epistasis dominates the genetic architecture of <i>Drosophila</i> quantitative traits

TLDR

Epistasis, the nonlinear interaction between loci, underlies canalization and speciation and can reveal genetic networks, yet its contribution to quantitative trait architecture remains debated. The study aimed to compare the genetic architecture of three Drosophila life‑history traits in the DGRP and an advanced intercross population and to demonstrate how epistatic networks inform evolutionary and applied genetics. Allele frequency shifts at trait extremes were measured by deep sequencing of pooled individuals from the Flyland intercross, enabling comparison with the DGRP. Both populations exhibited highly polygenic architectures, with no SNPs replicating across them, yet most associated loci engaged in epistatic interactions that disrupted shared, biologically plausible networks, underscoring epistasis as a key determinant of quantitative trait variation.

Abstract

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.