Department of Biology, Duke University
Correspondence: E-mail: mrausher{at}duke.edu.
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Abstract |
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Key Words: anthocyanin pathway nucleotide substitution rates positive selection codon usage rate variation
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Introduction |
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In a previous analysis of rates of anthocyanin structural gene evolution, Rausher, Miller, and Tiffin (1999) demonstrated that, over a broad taxonomic distance involving comparisons among monocots and dicots, proteins in the upstream portion of the pathway evolved more slowly than proteins in the downstream portion. One possible explanation for this pattern is that the upstream enzymes are under greater selective constraint than the downstream enzymes. Greater constraint may arise because the upstream enzymes participate in the biosynthesis of a number of different types of flavonoids in addition to anthocyanins (Koes, Quattrocchio, and Mol 1994; Shirley 1996; Sakuda 2000). Flavonoids are believed to serve a number of physiological and ecological functions in plants, including protection from ultraviolet radiation and from natural enemies, facilitating interactions with mycorrhizal symbionts, and mediating pollenstigma interactions. By contrast, the downstream enzymes are responsible for the production of only anthocyanins (Koes, Quattrocchio, and Mol 1994). It thus seems possible that deleterious mutations affecting enzyme kinetics in upstream genes would have a greater overall effect on fitness than similar mutations on downstream genes. Such mutations in downstream genes would then be more likely to be effectively neutral, causing the downstream genes to experience reduced selective constraint.
Because of the wide taxonomic comparison used in our previous analysis, for many of the genes examined, synonymous substitutions were saturated or close to saturation. Therefore, it was not possible to estimate accurately and compare Ka/Ks ratios for the different anthocyanin structural genes. The observed differences among the genes in nonsynonymous substitution rates could thus have been due to differences in processes (e.g., mutation rates) that affect synonymous and nonsynonymous rates similarly, and not to differences in the degree of selective constraint or the frequency of positive selection. In view of these uncertainties, we have undertaken a new analysis focusing on a taxonomically more restricted set of species within the genus Ipomoea. In this analysis, we addressed the following three questions: Is the greater rate of nonsynonymous substitution characteristic of the downstream enzymes detected by Rausher, Miller, and Tiffin (1999) also detectable in comparisons at lower taxonomic levels? If so, can differences in mutation rates be ruled out as the cause of the difference in evolutionary rates between upstream and downstream enzymes? Do downstream enzymes exhibit evidence of more frequent positive selection as a cause of their elevated evolutionary rates?
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Materials and Methods |
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Sequences of CHS-D, ANS, and UFGT were obtained from six species chosen to represent much of the diversity within the genus Ipomoea, subject to the constraint that we wished to compare pairs of species separated by a range of genetic distances (table 1). Twelve of the 18 Ipomoea sequences compared were newly obtained in this study (see table 1 for accession numbers). I. hederacea was sampled from a natural population near Petersburg, Virginia, and I. purpurea came from Lee County, N.C. I. alba sequences are from a commercial strain. The National Center for Genetic Resources Preservation of the U.S. Department of Agriculture at Colorado provided seeds for I. nil (accession number NSL59662), and the Plant Genetic Resources Conservation Unit provided seeds for I. trifida (accession numbers PI 561547 and PI561543).
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Comparing Ka and Ks Among Genes
Sequences were initially aligned using MegAlign (DNAstar, Inc), and the resulting alignments were visually adjusted. The best substitution model (F84 with a molecular clock; Felsenstein 1984) for our sequences was determined by comparing the likelihoods of commonly used models using the BaseML feature of PAML 3.13 (Yang 1997). We estimated Ka and Ks using Nei and Gobojori's method as implemented in DnaSP version 3.51 (Rozas and Rozas 1999).
To determine whether the rates of synonymous or nonsynonymous substitutions differed among genes, we compared the slopes of the relationships between Ka or Ks and genetic distance for the three genes. The rationale for this comparison is that, for a given gene, Ka for two species should be proportional to time since speciation. If genes differ in Ka (or Ks), the proportionality constant should differ, and this variation should be reflected in a difference in slope between Ka and time. We used genetic distance as a surrogate for separation time, and because separation times should be the same for all genes, the same measure of genetic distance was used for all genes. Genetic distances were estimated from the branch lengths of the maximum-likelihood phylogeny of the combined sequence of the three genes, using the F84 model with a molecular clock and PAML version 3.13 (Yang 1997). The topology (fig. 1) was first derived from previous studies (Miller, Rausher, and Manos 1999; Huang and Sun 2000; Manos, Miller, and M. D. Rausher. 2001) and is well supported by our new data.
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Comparing Ka/Ks Among Genes
We compared Ka/Ks ratios for the three genes using two different methods. The first method estimates Ka/Ks from the ratio of slopes of regressions of Ka and Ks on genetic distance obtained from the analysis described in the previous section. The second method uses estimates of the parameter generated by the program CodeML of the PAML software package (Yang 1997). For this analysis, a single value of Ka/Ks was obtained for each gene using the model M0 of CodeML. The significance of differences in Ka/Ks between genes was assessed by comparing the likelihood of the model using the estimated value of Ka/Ks to the likelihoods of the same model using Ka/Ks constrained to various values. In particular, we sought to determine whether there existed a value of Ka/Ks such that (1) that value is between the Ka/Ks ratios for the two genes being compared and (2) that value is significantly different from the value for each gene. If such a value is found, it indicates that the confidence intervals (or support regions, sensu Edwards 1972) for the Ka/Ks values of the two genes do not overlap, and thus the values are significantly different. Similarly, if a value of Ka/Ks can be found that lies between the values of Ka/Ks for two genes, and if that value is not significantly different from the value for either gene, then a single Ka/Ks is compatible with both genes and the genes can be inferred not to have significantly different Ka/Ks values. Significance was assessed using standard likelihood-ratio statistics (Weir 1990). Results are reported for a model that implements a molecular clock. Results from a model that does not implement a clock were quantitatively almost identical and are therefore are not reported.
Estimates of Codon Use Bias
We computed effective number of codons (ENC; Wright 1990) for the three genes using DNAsp version 3.51 (Rozas and Rozas 1999); ENC is a measure of the degree to which codon usage deviates from equal use of the 61 possible sense codons. Because codon bias is correlated with GC content (Ikemura 1985), and because GC content is higher in CHS-D than in ANS and UFGT (table 1), direct comparisons of the ENCs among the three genes may be confounded by mutation bias (Foster, Eisenstadt, and Cairns 1982). To control for mutation bias, we compared the observed value of ENC for each gene to the value expected for that gene's third-position GC content using the Nc-plot technique of Wright (1990).
Detecting Positive Selection
We employed a codon-based approach to detect amino-acid sites that have undergone positive selection and to determine whether the proportion of such sites differed among the three genes. To implement this approach, we used the program CodeML of the PAML software package (Yang 1997). A comparison of the Ka/Ks ratio was first performed across lineages to verify that lineages did not differ. Subsequently, using the known phylogenetic topology (fig. 1), we determined for each gene separately the number of codons exhibiting evidence of positive selection by comparing models M7 and M8, as recommended by Yang et al. (2000). Model M7 fits codon variation in Ka/Ks with a beta distribution, with Ka/Ks constrained to be equal to or less than one. Model M8, however, includes an additional class of codons that may be positively selected (i.e., with Ka/Ks > 1) and estimates both the proportion of such codons in the gene and their average Ka/Ks ratio. Comparison of the two models by standard likelihood techniques assesses whether the inclusion of positively selected sites in the model provides a significantly better fit to the data (Yang et al. 2000).
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Results |
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Comparing Ka and Ks Among Genes
As is expected with the operation of a molecular clock, the relationship between Ka and genetic distance is linear (fig. 2a). The rate at which Ka increases with genetic distance is lowest for CHS-D, the most upstream gene, intermediate for ANS, and highest for UFGT (fig. 2a), a pattern that is identical with that reported earlier for nonsynonymous substitutions in these genes across angiosperms (Rausher, Miller, and Tiffin 1999). A generalized least-squares analysis indicates that the slopes of Ka versus genetic distance differ significantly among the three genes (F2,24 = 143.5, P < 0.0001). Pairwise comparisons using a similar analysis reveals that for all three gene pairs, the slopes differ significantly (CHS-D vs. ANSF1,16 = 574.6, P < 0.0001; CHS-D vs. UFGTF1,16 = 909.9, P < 0.0001; ANS vs. UFGTF1,16 = 52.2, P < 0.001).
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Because the same data were used to estimate Ka, Ks, and genetic distance, the dependent and independent variables used in this analysis are not statistically independent and the calculated significance levels may therefore be inflated. To assess the magnitude of this potential problem, we examined the correlations between genetic distance and pairwise differences in Ka (or Ks) for the three genes. As described in the Appendix, this correlation is expected to be zero under the null hypothesis that Ka (or Ks) is equal for the two genes. For this analysis, we again used the generalized least-squares approach by transforming both genetic distance and difference in Ka (or Ks, see Appendix).
This analysis produces results qualitatively similar to the results of the previous analysis, although as expected, some comparisons are no longer significant. The comparison between CHS-D and UFGT yielded a highly significant correlation (r = 0.90, P < 0.005, df = 8), indicating that Ka is significantly lower for CHS-D than for UFGT. The comparison between CHS-D and ANS did not yield a significant correlation (r = 0.28, P > 0.1, df = 8). However, we note that for all 15 species pairs, the Ka value for CHS-D is less than that for ANS (fig. 2), suggesting that Ka is lower for ANS and that the nonsignificance of the correlation is likely due to lack of power to detect a difference in the slopes of the relationship between Ka and genetic distance for these two genes. There was also no detectable difference in Ka between ANS and UFGT (r = 0.525, P > 0.05). The rate of synonymous substitution, Ks, was significantly greater for CHS-D than for ANS or UFGT (r = 0.97 and 0.98, P < 0.001 in both cases), but did not differ between ANS and UFGT (r = 0.131, P > 0.1).
Comparing Ka/Ks Among Genes
The Ka/Ks ratios calculated for ANS and UFGT from the ratio of regression slopes obtained in the previous analysis are similar to each other but are approximately four times the analogous ratio for CHS-D (table 3). The small standard errors of the estimates indicate that this difference between CHS-D and the downstream genes is statistically significant, while the difference between ANS and UFGT is not. Moreover, statistical significance of the difference between CHS-D and the downstream genes is indicated by the fact that CHS-D has both a significantly lower Ka and a significantly higher Ks, compared to the other genes, as described above.
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Codon Use Bias
The three genes examined here differed substantially in degree of codon bias, as measured by the ENC. The gene with the lowest rate of nonsynonymous substitution, CHS-D, exhibited substantial codon bias, with a mean ENC across all six species of 43.7, indicating that in this gene 17 codons are effectively unused. By contrast, the gene with the highest nonsynonymous substitution rate, UFGT, exhibited little bias (mean ENC = 60.2); finally, ANS, with an intermediate nonsynonymous substitution rate, also exhibited an intermediate degree of codon bias (mean ENC = 52.0). Within each gene, there is very little variation in codon bias across species (fig. 1), indicating that the magnitude of codon bias has undergone little change during most of the diversification of the genus Ipomoea. This lack of evolutionary change suggests that degree of codon bias has reached a different evolutionary equilibrium for each gene, or that the rate of evolutionary change in ENC is very slow.
The three genes also differ in GC content at the third codon position, with CHS-D having the highest GC content and UFGT having the lowest (table 1). One possible explanation for this difference is that CHS is under more intense selection for codon-use bias, because in many species most preferred codons end in G and C (Fennoy and Bailey-Seres 1993; Chiapello et al. 1998). Nevertheless, because differences in GC content can be caused by processes other than selection for codon bias (e.g., mutation bias), and because differences in GC content can by themselves cause differences in ENC even in the absence of selection for codon bias, we asked whether ENC for each gene deviated from expectation based simply on the gene's GC content. In figure 3, the solid line portrays this expectation as a function of third-position GC content (Wright 1990). For UFGT, the points for all six species lie on or above this expectation. For ANS, the points for all six species lie just below the expectation line, and for CHS-D, the points for all species lie below the expectation and several lie substantially below that level. This pattern is consistent with historical selection for codon bias in CHS-D, perhaps weaker selection for codon bias in ANS, and the absence of such selection in UFGT.
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Discussion |
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Although in this study we examined only three of the six core pathway enzymes, we found the pattern of nonsynonymous rate variation across the genus Ipomoea to be consistent with the pattern documented by Rausher, Miller, and Tiffin (1999). Specifically, in both studies, the most upstream gene in the pathway, CHS-D, had the lowest nonsynonymous rate, while the most downstream, UFGT, had the highest rate. And in both studies, the rate for ANS was intermediate between those of the other two genes. This similarity indicates that the pattern exhibited across angiosperms is also detectable at a much finer taxonomic scale.
One possible explanation for this difference in nonsynonymous substitution rates is that, for some reason, downstream genes have higher mutation rates than upstream genes. Although there is no a priori reason to expect this hypothesis to be true, Rausher, Miller, and Tiffin (1999) could not rule it out because nonsynonymous substitutions were nearly saturated for the distantly related species they examined. It was therefore impossible to determine whether synonymous substitution rates were lower for upstream genes, as this hypothesis would predict. Because of the narrower taxonomic focus of the present study, we were able to obtain reliable estimates of synonymous substitution rates, and thus resolve this issue. Like the nonsynonymous rates, the synonymous rates also differ among the three genes examined. Somewhat surprisingly, however, the upstream gene (CHS-D) had a substantially higher rate of synonymous substitution than the two downstream genes (fig. 2). The higher rates of amino-acid substitution in the downstream genes cannot, therefore, be due to an elevated mutation rate.
Our failure to detect more than minimal positive selection on any of the three genes examined suggests that the increased rate of nonsynonymous substitution in the downstream enzymes is more likely to be due to relaxed constraint on these enzymes than to increased rates of positive selection. This interpretation is also consistent with indel patterns and with the differences among genes in the degree of codon bias. If downstream genes were under reduced selective constraint, they would be expected to tolerate more indels than upstream genes. Corresponding to this expectation, the most downstream gene, UFGT, exhibited seven identifiable insertion/deletion events during the divergence of the species examined. By contrast, the most upstream gene, CHS-D, exhibited only one indel. Interpretation of this pattern is complicated by the fact that the downstream gene ANS also exhibited only 1 indel, but when averaged together, the two downstream genes still exhibited four times as many indels per gene as CHS-D.
The magnitude of codon bias in a gene is also often taken to reflect the degree to which that gene is subject to selective constraint, for several reasons. First, codon bias is believed to reflect selection for translation efficiency in highly expressed genes (Bennetzen and Hall 1982; Sharp and Li 1987; Powell and Moriyama 1997). Because highly expressed genes are likely to be more "critical" to an organism, they are also likely to be subject to greater selective constraint. Second, Akashi (1994) demonstrated that highly functional and evolutionarily conserved amino acids within genes had greater codon bias than less conserved amino acids, presumably because of selection for translational accuracy. This result suggests that genes with a greater fraction of constrained amino acid sites will also exhibit a greater average degree of codon bias. Finally, Comeron and Kreitman (1998) demonstrate an excess of doubly substituted codons in Drosophila and argue that the best explanation for this effect is relaxed selection on the codons involved, which would tend to decrease codon bias. These arguments suggest that our finding of reduced codon bias in downstream genes is due to relaxed constraint in these genes.
One potentially puzzling result of our analyses is that the gene with the greatest codon bias (lowest ENC), CHS-D, is also the gene with the highest rate of synonymous substitution, contrary to the pattern reported for other genes (e.g., Fitch and Strausbaugh 1993; Zhang, Vision, and Gaut. 2002; but see also Kusumi et al. 2002). It might be expected that at codon-bias equilibrium, more intense selection for codon bias would decrease synonymous substitution rates. This expectation is reasonable for genes that have a similar underlying synonymous mutation rate, because once codon bias reaches equilibrium, selection to maintain bias is essentially a form of purifying selection. Consequently, the stronger the selection for bias, the greater the selective constraint, and the lower the expected substitution rate. However, if for CHS-D the underlying synonymous mutation rate is substantially higher than for ANS or UFGT, then the synonymous substitution rate for CHS-D will be elevated compared to the other genes, and that gene's turnover rate of preferred and nonpreferred codons will increase, but the equilibrium codon bias should not be affected. We thus suggest that the association of high codon bias with high rates of nonsynonymous substitution in CHS-D can be explained as resulting from a relatively elevated mutation rate at this locus.
In conclusion, it appears that the three independent types of evidence obtained in this study are consistent with the hypothesis that amino acid substitutions occur more frequently in downstream anthocyanin genes because of reduced constraint, rather than as a result of enhanced positive selection. One caveat must be added to this conclusion, however. Betancourt and Presgraves (2002) recently demonstrated in Drosophila that strongly selected amino acid sites exhibit reduced codon bias, presumably as a result of selective interference. If this effect were strong in the Ipomoea genes examined here, that would imply that the downstream genes experience a greater frequency of positively selected substitutions than the upstream genes. This expectation is inconsistent, however, with our failure to detect any evidence of substantial positive selection on the downstream genes.
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Appendix |
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Under the generalized least-squares framework, the statistical model for the relationship between Ka and genetic distance, D, is given by
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As shown below, if all 15 species pairs are included in the analysis, is singular. However, there are sets of nine species pairs for which covariances are linearly independent and which thus yield a
matrix that is non-singular and positive-definite. The remaining analysis pertains to such a subset of species pairs.
Let C be the matrix of normalized eigenvectors of and let
be a diagonal matrix of the corresponding eigenvalues. Then, because
is positive-definite,
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If we let A = C
, then
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Because this transformed model meets the independence assumptions of ordinary least squares (Searle 1971), the transformed variables Ka' and D' can then be used with standard analysis of covariance approaches to test for differences in slope among genes. In particular, we employed the test for homogeneous slopes described by Timm (1975) to test whether b differed among the three genes examined.
This approach requires an estimate of the expectation of the original variance-covariance matrix . In this matrix, the diagonal element
ii is the expected variance of Ka for species pair i, while the off-diagonal element
ij is the expected covariance for Ka between species pairs i and j. These expected values may be determined as follows: Under the assumption of constant (Poisson) substitution rates (molecular clock), the expected number of substitutions per site, sk, along any branch k of a phylogeny is proportional to the length of the branch, lk; i.e.,
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Because Var[Kai] represents the ith diagonal element of and Cov[Kai, Kaj] represents the i,jth off-diagonal element, the expected value of
is
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A complication arises in applying this analysis if the data used to estimate genetic distances are not independent of the data used to estimate Ka and Ks, as is true in this study. This lack of independence is manifested in an expected covariance between, say, Kaij and genetic distance, Di, for species pair i and gene j. With sequences of approximately the same length, n, this covariance is
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As described above, Var (Nij) = j li, where
j is the rate of nonsynonymous substitution at gene j. Consequently,
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One way to remove this dependence is to examine the relationship between genetic distance and pairwise between-species differences in Ka. For example, for genes 1 and 2, this pairwise difference is
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Under the null hypothesis that the rates of nonsynonymous substitutions are equal for genes 1 and 2 (i.e., that Ka is the same for the two genes), 1 =
2 and Cov (
i,12, Di) = 0. This null hypothesis may thus be rejected if there is a significant correlation between
i,12 and genetic distance. A similar argument, substituting (1
) for
, applies to the covariance between genetic distance and the difference in Ks between two genes.
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Acknowledgements |
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Footnotes |
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