Identification of gene expression differences in the presence and absence of copper sulfate
Expression levels were measured using DNA microarrays in the nine strains during exponential growth in rich medium and in rich medium supplemented with copper sulfate (see Materials and methods). The microarrays used in this study are composed of oligonucleotides of 70 base pairs (bp) that are perfect matches to the S288C sequence. Although cDNA prepared from the other eight strains will not always be a perfect match to the sequence on the microarray, we expect fewer than 0.2 differences per 70 bp on average (see Materials and methods), and therefore do not expect the sequence differences to affect our measurements. A reference design was used whereby the RNA of each strain grown in rich medium and rich medium supplemented with copper sulfate was compared to the pooled RNA from all nine strains grown in rich medium and copper sulfate medium, respectively. Using three replicate experiments, four statistical tests were used to identify differentially expressed genes. From an analysis of variance, 194 genes showed significant expression differences among strains grown in copper sulfate medium, 241 genes showed significant expression differences among strains grown in rich medium, and 516 genes showed significant expression differences across both conditions (p < 0.01). One hundred and thirty-one genes showed significant differences between the rich medium and copper sulfate medium reference pools (t-test, p < 0.01). Because an analysis of variance assumes errors are independent and identically distributed, we estimated the rate of false positives using a nonparametric permutation resampling method (see Materials and methods). The estimated number of false positives was 57, 64, 55 and 71, for the test of gene-expression differences among strains in copper sulfate medium, in rich medium, in both media, and between the two reference pools, respectively. We chose a p-value cutoff of 0.01, as empirically, many significant genes are missed using a p-value cutoff of 0.001 and numerous false positives are generated using a p-value cutoff of 0.05 (see Materials and methods).
A total of 731 genes showed significant expression differences by one or more of the four tests. These genes were hierarchically clustered on the basis of the centered correlation coefficient and are presented with their p-values in Figure . Most genes show similar expression patterns in rich medium and copper sulfate medium. Of the 633 genes that were found to be differentially expressed among strains in either one or both treatments, 79 genes and 36 genes were only significant in rich medium and copper sulfate medium, respectively. Manual inspection of these genes revealed that many of the expression patterns significant in one medium showed a similar, although nonsignificant, expression pattern in the other medium. Through a separate analysis of variance, we found 56 genes specifically differ in their pattern of expression in rich medium compared to copper sulfate medium (see Materials and methods).
Figure 2 Hierarchical clustering of differentially expressed genes. Genes with significant expression differences among strains in both media (strain), in copper-sulfate medium (strain*CuSO4), in rich medium (strain*YPD), and between copper sulfate and rich medium (more ...)
Differentially expressed genes correlated with growth rate in the presence of copper sulfate function in response to oxidative stress
To identify gene-expression differences correlated with resistance to copper sulfate, we measured the correlation between the differentially expressed genes and sensitivity to copper sulfate. In liquid medium M34 and YPS163 were sensitive to copper sulfate (ANOVA, p = 0.00022), whereas no significant differences were measured in rich medium alone (ANOVA, p = 0.159; see Materials and methods and Figure ). Genes correlated with sensitivity to copper sulfate are presented in Figure (see Materials and methods). We used a correlation cutoff of 0.80, which corresponds to a significance of p < 0.01. Permutation resampling of the expression differences showed that only 13 expression differences are expected to reach a correlation of 0.80 or above (see Materials and methods). Of those genes correlated with sensitivity to copper sulfate, eight are expressed at a higher level in the presence of copper sulfate while fewer than one (20 × 131/6,144) is expected (exact test, p < 10-7). Thus, there are more genes that are correlated with sensitivity to copper sulfate and that change in response to copper sulfate than expected by chance.
The average growth rates from three replicates of strains in rich medium and rich medium with 1 mM copper sulfate. Relative growth rates were measured by the slope of the linear regression of cell density on time.
Figure 4 Genes associated with resistance to copper sulfate. (a) Genes correlated with sensitivity to copper sulfate (r > 0.8, p < 0.01) that are differentially expressed among strains in the presence of copper sulfate or between the rich medium (more ...)
Genes expressed at higher levels in copper-sensitive (M34 and YPS163) compared to resistant strains are known to function in response to oxidative stress. At high concentrations, copper causes oxidative stress resulting in lipid peroxidation, aggregation and fragmentation of proteins and DNA damage [22
]. Thioredoxin peroxidase (TSA1
) and thioredoxin (TRX2
) function in redox homeostasis and are regulated by the transcription factors Yap1p and Skn7p [23
]. The heat-shock proteins encoded by SSA1
are also regulated by Yap1p and Skn7p and function in protein folding and translocation of misfolded proteins [25
]. Sti1p is a member of the Hsp82 protein complex [26
]. Kar2p interacts with Ire1p [27
] to activate the unfolded protein response, including protein disulfide isomerase, PDI1 [28
], which is required for oxidative protein folding in the endoplasmic reticulum [29
]. These genes, in addition to functioning in oxidative stress and protein folding, had higher levels of expression in the copper sulfate compared to rich medium reference pool (Figure ).
Genes expressed at lower levels in strains sensitive to copper sulfate were expressed at lower levels in the copper sulfate compared to the rich medium reference pool and function in RNA processing. RFX1
encodes a repressor of RNA polymerase II (Pol II) promoters [30
encodes a small nucleolar RNA-binding protein involved in rRNA processing [31
]. In addition, both YJL010C and YLL034C show changes in gene expression similar to other RNA-processing genes [32
], which together form a major component of the environmental stress response [33
]. The expression of RNA-processing genes may be related to a general stress response and/or the reduced growth rate of copper-sulfate-sensitive strains.
Expression differences weakly correlated with resistance to copper sulfate may also be relevant to understanding the molecular basis of the trait, especially if it is complex. To identify relevant expression differences weakly correlated with resistance to copper sulfate we examined genes annotated as functioning in copper homeostasis, protein folding or oxidative stress (Figure ), as well as all genes expressed at higher or lower levels as a result of the presence of copper sulfate (Figure ). Some genes show a weak correlation with resistance to copper sulfate. For instance, the superoxide dismutase gene SOD2
was found expressed at higher levels in the copper sulfate reference pool, and at higher levels in M13 and M34, two of the three most copper-sensitive strains (Figure ). Also, the copper, zinc superoxide dismutase SOD1 was found expressed at intermediate levels in M13 and at higher levels in YPS163 and M34 (Figure ), in correspondence with the strains' sensitivity to copper sulfate (Figure ). Superoxide dismutases protect cells against reactive oxygen species and are induced in response to oxidative stress [22
Genes with different expression levels in the copper sulfate compared to the rich medium reference pool. Groups of genes enriched for functions in protein folding (red bar) and stress response and metabolism (blue bar) are shown.
Of those genes found to change in response to copper sulfate (Figure ), the genes expressed at lower levels in the presence of copper sulfate are not functionally related, and the genes expressed at higher levels in the presence of copper sulfate are significantly enriched in genes known to function in protein folding, stress response and metabolism (see Materials and methods). Of the 131 genes, 24 were expressed at twofold or higher levels in the presence of copper sulfate and one, ZRT1, encoding a high-affinity zinc transporter, was expressed at half the level in the presence of copper sulfate. Of these 24 genes, seven are known to function in the stress response (ALD3, DDR2, HSP12, HSP104, TSL1, YGP1, YRO2), four in protein folding (SSA1, SSA2, SSA4, SIS1), four in metabolism (ALD4, GLK1, HXK1, PGM2), five in copper homeostasis (CUP1-1, CUP1-2, FET3, FTR1, SOD1), two are uncharacterized (YHR087W, YMR315W), one encodes a lipid-binding protein (TFS1), and one gene is involved in meiotic sister-chromatid recombination (MSC1).
Of those genes expressed at higher levels in the presence of copper sulfate, many are also expressed at higher levels in YPS163 and M34 (Figure ). However, the response differs among the copper-sulfate-resistant strains. The expression pattern in the copper-resistant strains delineates two major clusters enriched for genes known to function in protein folding (Figure , red bars) and stress response and metabolism (Figure , blue bars). The group enriched for genes functioning in protein folding tends to be expressed at higher levels in YPS163, M34 and, to some extent, M5. Whereas M5 is resistant to copper in rich medium, it is quite sensitive in SD or SC medium (see Additional data file 1). One of the genes expressed at higher levels in M5, YPS163 and M34 is SIS1
, encoding an HSP40 family chaperone required for the initiation of translation [34
], and known to regulate the protein-folding activity of the heat-shock protein Ssa1p [35
]. The group enriched for genes functioning in the stress response and carbohydrate metabolism tends to be expressed at higher levels in the two copper-sensitive strains, YPS163 and M34, but also tends to be expressed in S288C and M32, two of the three most resistant strains.
Genes that respond to the presence of copper sulfate show no correlation with sequence divergence between strains
Most expression differences are not associated with either resistance to copper sulfate or rust coloration in the presence of copper sulfate. The differential expression of these genes could be due to a lack of selective constraint on their expression levels or could be due to some form of natural selection. For instance, they may be present due to a balance between mutation and purifying selection or diversifying selection due to environmental heterogeneity. One common method of testing whether a phenotype has been driven by natural selection is to test whether phenotypic differences among species conflict with their known phylogenetic relationship [39
]. We sequenced three genes to determine the phylogenetic relationship among the strains used in this study (Figure ). While the three genes show similar levels of divergence among strains, their phylogeny cannot be resolved, as expected for a species with sexual recombination. However, even if multiple genealogies exists across the genome, expression differences are expected to accumulate monotonically as a function of time and mutation rate under an infinite allele model for both single-gene and polygenic characters [43
]. Thus, we expect neutral differences in gene expression to be correlated with divergence time between strains.
Figure 8 DNA sequence differences found in three genes (SUP35, MBP1, HHT2). Intergenic (i), amino-acid-altering (a), and synonymous (s) polymorphic sites are shown in reference to the S. paradoxus sequence. d indicates an insertion or deletion and N indicates (more ...)
The number of pairwise gene-expression differences found between strains is significantly correlated with the estimated time to coalescence, measured by the number of pairwise sequence differences found in three genes (see Materials and methods and Figure ). Because pairwise measures of divergence are not independent of one another, the correlation may be spurious. A Mantel test is a nonparametric test of association between two dissimilarity matrices that accounts for this nonindependence [45
]. Using this test, a significant association was found between divergence in gene expression and DNA sequence divergence (p
= 0.043). If the expression of genes that respond to the presence of copper sulfate were driven by adaptive evolution, the correlation between divergence in gene expression and DNA sequence divergence may be weaker or even not present. In contrast to overall patterns of gene expression, the expression of genes that respond to the presence of copper sulfate (Figure ) was not found associated with DNA sequence differences among strains (Figure ).
Figure 9 Pairwise differences in gene expression compared to pairwise DNA sequence divergence. (a) Genes differentially expressed among strains, and (b) genes different between copper-sulfate and rich medium. Distances with S288C (green) and with YPS163 (red) (more ...)