Natural variation in gene expression is pervasive within and between species, and it likely explains a significant fraction of phenotypic variation between individuals. Phenotypic variation in acute systemic responses can also be leveraged to reveal physiological differences in how individuals perceive and respond to environmental perturbations. We previously found extensive variation in the transcriptomic response to acute ethanol exposure in two wild isolates and a common laboratory strain of Saccharomyces cerevisiae. Many expression differences persisted across several modules of coregulated genes, implicating trans-acting systemic differences in ethanol sensing and/or response. Here, we conducted expression QTL mapping of the ethanol response in two strain crosses to identify the genetic basis for these differences. To understand systemic differences, we focused on "hotspot" loci that affect many transcripts in trans. Candidate causal regulators contained within hotspots implicate upstream regulators as well as downstream effectors of the ethanol response. Overlap in hotspot targets revealed additive genetic effects of trans-acting loci as well as "epihotspots," in which epistatic interactions between two loci affected the same suites of downstream targets. One epi-hotspot implicated interactions between Mkt1p and proteins linked to translational regulation, prompting us to show that Mkt1p localizes to P bodies upon ethanol stress in a strain-specific manner. Our results provide a glimpse into the genetic architecture underlying natural variation in a stress response and present new details on how yeast respond to ethanol stress. N ATURAL variation in gene expression is hypothesized to be a major source of phenotypic variation between individuals (King and Wilson 1975;Oleksiak et al. 2002). Gene expression variation underlies differences in susceptibility to infectious disease (Li et al. 2010;Barreiro et al. 2012), drug sensitivity (Fay et al. 2004;Kvitek et al. 2008;Maranville et al. 2011;Hodgins-Davis et al. 2012;Chang et al. 2013), inflammation (Gargalovic et al. 2006Orozco et al. 2012), cardiovascular disease (Romanoski et al. 2010), metabolism (Fraser et al. 2010Rossouw et al. 2012;Skelly et al. 2013), morphology (Yvert et al. 2003Chin et al. 2012;Skelly et al. 2013), and even behavior (Ziebarth et al. 2012). Still, identifying the genetic and molecular mechanisms that underlie the expression variation is a major challenge.Expression quantitative trait loci (eQTL) mapping (reviewed in Gilad et al. 2008) is a powerful approach to dissect the genetic basis of expression differences. Transcript abundance is treated as a quantitative trait whose genetic determinants can be implicated by well-established linkage mapping techniques. The first eQTL studies in yeast illuminated the genetic landscape of gene expression-variation determinants under standard growth conditions (Brem et al. 2002;Yvert et al. 2003). Subsequent eQTL studies surveyed the genetic control of transcript abundance in Arabidopsi...