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. 2008 Oct;4(10):e1000223.
doi: 10.1371/journal.pgen.1000223. Epub 2008 Oct 17.

Variations in stress sensitivity and genomic expression in diverse S. cerevisiae isolates

Affiliations

Variations in stress sensitivity and genomic expression in diverse S. cerevisiae isolates

Daniel J Kvitek et al. PLoS Genet. 2008 Oct.

Abstract

Interactions between an organism and its environment can significantly influence phenotypic evolution. A first step toward understanding this process is to characterize phenotypic diversity within and between populations. We explored the phenotypic variation in stress sensitivity and genomic expression in a large panel of Saccharomyces strains collected from diverse environments. We measured the sensitivity of 52 strains to 14 environmental conditions, compared genomic expression in 18 strains, and identified gene copy-number variations in six of these isolates. Our results demonstrate a large degree of phenotypic variation in stress sensitivity and gene expression. Analysis of these datasets reveals relationships between strains from similar niches, suggests common and unique features of yeast habitats, and implicates genes whose variable expression is linked to stress resistance. Using a simple metric to suggest cases of selection, we found that strains collected from oak exudates are phenotypically more similar than expected based on their genetic diversity, while sake and vineyard isolates display more diverse phenotypes than expected under a neutral model. We also show that the laboratory strain S288c is phenotypically distinct from all of the other strains studied here, in terms of stress sensitivity, gene expression, Ty copy number, mitochondrial content, and gene-dosage control. These results highlight the value of understanding the genetic basis of phenotypic variation and raise caution about using laboratory strains for comparative genomics.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Phylogeny of Saccharomyces strains used in this study.
The phylogeny was inferred from 13,061 bp of coding and non-coding sequence generated by and this study, using the program MrBayes . Nodes with a posterior probability<0.9 are collapsed. Strains are color coded according to the niche from which they were originally isolated, as shown in the key at the bottom of the figure.
Figure 2
Figure 2. Phenotypic variation in diverse Saccharomyces strains.
The viability of 52 Saccharomyces strains and species grown under 14 different environmental conditions was measured. Strains were grown in at least duplicate on solid agar plates containing 1–3 doses of each environmental variable, as described in Materials and Methods. Each row on the plot represents a different strain and each column indicates a given environment. Colored boxes represent the average growth score of each strain grown in each environment, according to the key shown at the lower right. Strains and conditions were organized by hierarchical clustering using the Pearson correlation as a similarity metric.
Figure 3
Figure 3. Variation in gene expression in S. cerevisiae isolates.
The diagrams show the average log2 expression differences measured in the denoted strains. Each row represents a given gene and each column represents a different strain, color-coded as described in Figure 1. (A) Expression patterns of 2,680 genes that varied significantly (FDR = 0.01, paired t-test) in at least one strain compared to S288c. (B) Expression patterns of 953 genes that varied significantly in at least one strain compared to strain YPS163 (FDR = 0.01, unpaired t-test). For (A) and (B), a red color indicates higher expression and a green color represents lower expression in the denoted strain compared to S288c, according to the key. (C) Expression patterns of 1,330 genes that varied significantly (FDR = 0.01, paired t-test) in at least one strain compared to the mean expression of all 17 strains. Here, red and green correspond to higher and lower expression, respectively, compared to the mean expression of that gene in all strains. Genes were organized independently in each plot by hierarchical clustering.

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