* ICAPB, University of Edinburgh Ashworth Labs, Edinburgh, UK
Department of Plant and Soil Sciences, University of Delaware
Correspondence: E-mail: stephenw{at}yorku.ca.
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Abstract |
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Key Words: Arabidopsis thaliana Arabidopsis lyrata tRNA MPSS codon bias, protein evolution
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Introduction |
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Recently, an effect of gene expression on rates of amino acid substitution has also been detected in several taxa (Pal, Papp, and Hurst 2001; Duret and Mouchiroud 2000; Iida and Akashi 2000; Zhang, Vision, and Gaut 2002; Wright, Lauga, and Charlesworth 2002), but the underlying cause of these patterns remains uncertain. One hypothesis is that genes that experience a higher complexity and diversity of biochemical environments will be subject to stronger selective constraints (Hastings 1996; Kuma, Iwabe, and Miyata 1995). Alternatively, mutations that affect proteins expressed in a greater number of tissues may on average have larger effects on fitness (Duret 2000). Translational selection may also be acting on amino acid composition to optimize protein synthesis (Akashi 2003), which should be more intense in highly expressed genes, given the higher level of translation of each amino acid. Finally, the degree to which the observed effect of gene expression on amino acid substitution rate is driven by inherent differences in selective constraint among genes of different function is unclear, because the functional categories differ, on average, in their relative abundance among different expression levels (Akashi 2001).
In this study, we investigate the interaction between gene expression and the effectiveness of natural selection at replacement and synonymous sites in Arabidopsis thaliana and its outcrossing congener A. lyrata. Although a positive correlation between preferred synonymous codon frequencies and gene expression has been detected in A. thaliana and close relatives (Duret and Mouchiroud 1999; Wright, Lauga, and Charlesworth 2002), the corresponding correlation coefficients are weak, and codon preferences have been defined solely by use of genome-wide multivariate analysis of codon usage, by identifying codon preferences in genes at the extreme of the first axis of correspondence analysis (Chiapello et al. 1998). Thus, little independent evidence remains in either Arabidopsis species that the identified "preferred" codons are explained by translational selection. Preliminary evidence for a positive correlation between rates of amino acid substitution and EST-based estimates of gene expression level has also been found in Arabidopsis, both between duplicated genes within the A. thaliana genome (Zhang, Vision, and Gaut 2002) and for orthologous genes between A. thaliana and A. lyrata (Wright et al. 2002). However, because EST-based estimates represent fairly crude indices of gene expression, the attempt to uncouple the underlying causes of this correlation in these studies was difficult.
We use genome-wide data from Arabidopsis thaliana and sequence data from 83 genes in Arabidopsis lyrata to investigate the effects of gene expression on substitution patterns and synonymous codon usage in Arabidopsis. We take advantage of new fine-scale estimates of gene expression in A. thaliana provided by Massively Parallel Signature Sequencing (MPSS [Brenner et al. 2000]) and data on tRNA gene abundance in the A. thaliana genome (http://rna.wustl.edu/GtRDB/At/). We use these data to address two primary questions: (1) Does translational selection act on codon bias in Arabidopsis? (2) What is the role of gene expression on the rate of protein evolution in Arabidopsis?
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Methods |
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Data Analysis
Calculations of rates of synonymous and nonsynonymous substitutions in each species were made by DnaSP version 3.95 (Rozas and Rozas 1999). To investigate codon preferences, we conduct correspondence analysis of relative synonymous codon usage (RSCU) of the sequenced A. lyrata genes, by application of the program CodonW (http://www.molbiol.ox.ac.uk/cu/culong.html). We exclude all gene fragments with less than 100 synonymous sites for this analysis, because small sequences give poor estimates of codon usage (e.g., Novembre 2002). Following the approach of Chiapello et al. (1998) for A. thaliana, preferred codons were detected by comparing codon frequencies of the highest-biased and lowest-biased genes, defined by the two extremes of the first axis of the correspondence analysis. Chi-square analysis was implemented in CodonW to test the null hypothesis that the relative frequencies of individual codons are the same in the highest-biased and lowest-biased 30 genes against the alternative hypothesis of an increase in frequency. We compared these results with the genome-wide identification of codon preferences in A. thaliana. For further comparison, we also performed correspondence analysis in A. thaliana on the orthologous loci we examined in A. lyrata, to evaluate the assessment of codon preferences in this subset of genes. CodonW was also used to estimate Fop, the frequency of optimal codons (Stenico, Lloyd, and Sharp 1994) for each gene.
Data on tRNA gene abundance in the complete genome of A. thaliana was obtained from the genomic tRNA database (http://rna.wustl.edu/tRNAdb/). To compare with preferred codon frequencies, we group codons by their predicted major tRNA species, following the revised wobble rules for eukaryotic genomes (Percudani 2001). These rules assume that GNN tRNAs pair with both C-ending and U-ending codons, whereas ANN tRNA genes are modified to inosine and decode both U-ending and G-ending codons. Identified tRNA genes in A. thaliana generally adhere to these wobble rules, because almost every codon can only be decoded by a single class of tRNA (see table 1). However, three exceptions exist of single unexpected tRNA genes (Gly GGU, Ser GGA, Leu GAG [shown in table 1]), which have been hypothesized to represent pseudogenes or sequencing errors (Wang, Shi, and Hao 2002). For our estimates of relative tRNA abundance, we ignore these exceptional genes, although their inclusion does not change the rank order of tRNA gene frequencies. tRNA gene abundance has been found to correlate strongly with the corresponding tRNA abundance in a number of prokaryotic and eukaryotic genomes (Kanaya et al. 2001), which suggests that it is a good proxy for relative tRNA abundance in the genome. In accordance with this prediction, we find a moderately significant positive correlation between codon number in the high-biased genes from Chiapello et al. (1998) and the number of isoaccepting tRNAs (r = 0.40, P < 0.01). When we remove three outliers with the highest tRNA gene copy numbers, the correlation improves substantially (r = 0.84, P << 0.001).
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Results and Discussion |
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Evidence for Translational Selection Favoring Preferred Codons
To test the hypothesis that the identified preferred codons are under translational selection, we investigated the correspondence between codon preferences and tRNA gene abundance in the A. thaliana genome. tRNA gene numbers, relative codon frequencies between high-biased and low-biased genes, and absolute frequencies in highly biased genes are shown in table 1. By combining codons on the basis of the same tRNA isoacceptor, we found a perfect correspondence between the most abundant tRNA gene class and codon classes that show the highest relative frequencies in high-biased genes.
Furthermore, with the exception of two sixfold degenerate codons (Leu and Arg), the rank order of codon frequencies corresponds exactly with the rank order of tRNA abundance. This result provided strong support for the hypothesis that the preferred codons are favored by translational selection. Interestingly, four of the five preferred codons that did not show an increase in frequency in our smaller data set of 83 sequences also studied in A. lyrata (AAG, CAG, GAG, and AGG) had only slight differences in tRNA abundance. This finding suggests that, as would be expected a priori, the smaller data set has less power to detect subtler differences in selection.
For codons recognized by the same tRNA, Ikemura (1985 ["rule 4"]) proposed that because of weak pairing interactions, tRNAs pairing with (A/U)-(A/U)-pyrimidine codons should favor C-ending codons. This rule appears to hold in the A. thaliana genome, which supports the hypothesis of preference for the C-ending codons in Asn, Tyr, Phe, and Ile (table 1). However, in other cases (Val, Ser, Thr, Pro, His, and Cys), an apparent preference of C-ending over U-ending codons occurs that is not expected according to these rules. Furthermore, in several other similar cases, the preferred and unpreferred codons identified by Chiapello et al. (1998) did not match precisely with the expectations based on tRNA abundance (Arg, Leu, Pro, and Ala [see table 1]). Because low-biased genes are generally AT rich (table 1), these apparent disagreements could represent artifacts of defining preferred codons as those that show a significant increase in frequency at one extreme of the first multivariate axis of correspondence analysis. Because the first multivariate axis maximizes the differences between genes in codon usage, it may be influenced by base composition as well as selection. For example, when the absolute frequencies of GCT, GTT, TCT, ACT, and CCT in high-biased genes are examined, no such preference for C-ending over U-ending codons is apparent (in contrast with the ratio of usage in high-biased versus low-biased genes). Thus, identification of preferred and unpreferred codons by multivariate analysis could possibly lead to the misidentification of some codons, because of the additional contribution of mutational biases. Alternatively, an additional selection pressure may be favoring C-ending codons, such as mRNA secondary structure. This possibility has been hypothesized for Drosophila melanogaster to explain the strong preference for C-ending codons (Carlini, Chen, and Stephan 2001), which is not always expected from information on tRNA gene abundance (Kanaya et al. 2001).
To further test this data set for the action and nature of translational selection, we examined the relationship between gene expression level and codon bias, with the expectation that codon bias indices that more accurately reflect translational selection should show a stronger correlation with gene expression. To investigate this hypothesis, we used estimates of gene expression level based on EST data and estimates based on the abundance of short sequence tags (MPSS [see Methods]). These latter estimates should represent more accurate estimates of gene expression (Meyers et al., unpublished data), because they do not use normalized expression libraries, and they are based on many more counts of mRNA abundance than are EST projects. Furthermore, we used two estimates of the frequency of optimal codons: one based on codon preferences identified in Chiapello et al. (1998) utilized multivariate analysis (Fopmult) and a second based on expectations derived from tRNA gene relative abundance (FoptRNA). For this latter measure, we identify preferred codon classes as those with the highest relative tRNA abundance for each amino acid. We also followed Ikemura's (1985) rule 4 and assumed a preference of C over T for (A/U)-(A/U)-pyrimidine codons. Preferred codons defined by these rules are shown in bold in table 1. Correlation analysis between three measures of gene expression, these two estimates of Fop, and the GC content at third codon positions (GC3) is shown in table 2. First, as expected, FoptRNA shows a weaker correlation with GC3 (r = 0.51) than Fopmult (r = 0.87) because of the higher proportion of A/T-ending preferred codons. For all three measures of codon usage, MPSS estimates of gene expression tend to show a slightly higher correlation with codon bias than EST-based estimates, as expected from more accurate estimates of gene expression.
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Note that these results also suggest that the codon preferences identified by tRNA relative abundance may more accurately reflect those codons favored by translational selection than those identified by multivariate analysis and that codon preferences identified solely by correspondence analysis should be treated with caution. Codon preferences have also been identified by explicitly comparing codon frequencies in genes with contrasting expression levels (e.g., Duret and Mouchiroud 1999). For several amino acids (Leu, Ala, and Thr), the identification of codon preferences by comparison of genes of highest and lowest expression are more similar to those expected on the basis of tRNA abundance and pairing rules (last two columns of table 1), which suggests that this method might provide more accurate identification of codon preferences. However, this approach generates an inherent circularity when testing for the action of translational selection (Duret and Mouchiroud 1999), and by using explicit a priori hypotheses based on isoaccepting tRNA abundance, we appear to have identified the codon preferences most directly relevant to selection on codon usage.
Figure 1 summarizes the relationship between MPSS-based gene expression classes and total FoptRNA across expression classes. In contrast with previous results based on EST estimates of gene expression (Duret and Mouchiroud 1999), we see a considerable increase (30%) in the frequency of preferred codons across expression classes, and variation in gene expression level explains a low but nontrivial percentage of the variance in FoptRNA among individual genes (approximately 10% [see table 2]) and a high percentage of the variance in FoptRNA across the gene expression classes shown in figure 1 (82%). However, a strong increase in codon bias appears to be primarily restricted to the very highest expression classes (fig. 1). This finding suggests that, unlike in other taxa (Akashi 2003; Duret and Mouchiroud 1999), selection may be acting on codon usage only on the most highly expressed genes and that selection on codon usage may be generally weaker in A. thaliana than in other systems, perhaps because high levels of self-fertilization are reducing the effectiveness of natural selection on slightly deleterious mutations (Wright, Lauga, and Charlesworth 2002). As previously found (Duret and Mouchiroud 1999), a significant negative correlation also exists between gene length and FoptRNA (Pearson's r = 0.251, P < 0.01), even once the effect of gene expression is factored out (partial r = 0.239, P < 0.01). Together, gene expression and gene length explain approximately 15% of the variation in codon usage across individual genes. Other factors that may be important in driving variation in codon usage include genetic drift, local mutational biases, and the rate of amino acid substitution (Marais, Charlesworth, and Wright 2004), although the current data set provides no evidence for a role of amino acid substitution on codon bias (see below).
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Forces Driving Rates of Nucleotide Substitution
Table 3 shows a summary of the average rates of substitution and the effects of gene expression on substitution rates between A. thaliana and A. lyrata. Consistent with previous results (Wright, Lauga, and Charlesworth 2002), we find no correlation between either gene expression or codon bias and the rate of synonymous substitution (Ks), by application of the new measures of gene expression (MPSS) and codon bias (FoptRNA). Although a significant correlation with Ks is expected when natural selection on codon usage is strong, theoretical work has shown that weak selection on codon bias has very little effect on the rate of synonymous substitution (McVean and Vieira 2001), despite significant effects on codon usage. These results are, therefore, still consistent with the interpretation that weak translational selection on codon usage occurs in Arabidopsis. In contrast with observations from Drosophila (e.g., Bettancourt and Presgraves 2002), we also find no evidence for a correlation between the rate of amino acid substitution and the level of codon bias (table 3).
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Acknowledgements |
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Footnotes |
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Michael Nachman, Associate Editor
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