Genetic Architecture of Ethanol-Responsive Transcriptome Variation in Saccharomyces cerevisiae Strains

Abstract

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...

Membrane fluidification by ethanol stress activates unfolded protein response in yeasts

“…Activation of key target genes agrees with changes observed in previous studies upon RE stress (Travers et al ., ; Kimata et al ., ). Some of these genes have also been observed in other transcriptomic studies related to ethanol stress, such as INO1 (Dinh et al ., ; Lewis et al ., ; Navarro‐Tapia et al ., ), ERO1 (Alexandre et al ., ; Dinh et al ., ; Lewis et al ., ), LHS1 (Alexandre et al ., ; Lewis et al ., ) and HAC1 (Navarro‐Tapia et al ., ). The strong INO1 activation that we observed has been described in other studies (Dinh et al ., ; Lewis et al ., ; Navarro‐Tapia et al ., ).…”

Natural gene expression variation studies in yeast

“…Nevertheless, most of these studies have been merely descriptive about the genetic differences between isolates without further insights into the individual's biology or responsiveness when exposed to other environments. In this context, the extent to which cis ‐ and trans ‐acting factors respond to environmental perturbations (G × E) in yeast has recently been explored (Gagneur et al ., ; Lewis et al ., ; Smith and Kruglyak, ). Genes can coordinately react to environmental stimuli, altering the cis and trans response (Kliebenstein, ).…”

Different contributions of local- and distant-regulatory changes to transcriptome divergence between stickleback ecotypes

“…; Lewis et al. ). Although local eQTL indicates cis‐ regulatory (e.g., sequence variation in promoters, enhancers, and silencers) and/or trans ‐regulatory changes (e.g., upstream physiological differences and changes in transcription factors) located near or within target genes (autoregulation), distant eQTL suggests the presence of trans ‐regulatory mutations (Albert and Kruglyak ).…”

“…; Lewis et al. ). Based on theoretical studies (Schlichting and Pigliucci ; Schluter ), a substitution that simultaneously changes multiple transcripts may facilitate adaptive evolution if changes in the majority of target genes are favorable.…”

“…; Lewis et al. ). Condition dependency of gene actions indicates that some loci are exposed to selection in one environment, but may be neutral in another environment (Van Dyken and Wade ; Anderson et al.…”