Station de Pathologie Végétale, Institut National de la Recherche Agronomique, Montfavet Cedex, France
Correspondence: E-mail: moury{at}avignon.inra.fr.
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Abstract |
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Key Words: positive selection cucumber mosaic virus Cucumovirus insect transmission epidemiology
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Introduction |
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By measuring the selective pressure exerted on the proteins encoded by the CMV genome, I show here that rapid amino acid substitutions also contribute to CMV evolution. Comparing the evolution patterns of the different subgroups of CMV suggests that selective constraints are exerted differently on them. This study also illustrates that such analyses, yet rarely conducted with plant viruses, can establish bridges between diversity and phylogenetic data, usually mainly descriptive, and the study of protein function and structure, as well as virus epidemiology.
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Materials and Methods |
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Estimation of the Selective Pressures on Proteins
The method used for measuring the selective pressure on protein-coding sequences was previously described (Yang and Bielawski 2000; Hurst 2002; Moury et al. 2002). The ratio () of nonsynonymous (amino acidaltering) to synonymous (silent) substitution rates provides an estimate of the selective pressure on the encoded protein (Kimura 1983). A maximum-likelihood (ML) method that utilizes models of sequence evolution can be employed to calculate
ratios and to identify amino acid sites as conserved, neutral, or positively selected (Yang et al. 2000). Instead of averaging
across all codon sites, Yang et al.'s (2000) method allows estimations of
on a codon-by-codon basis. This method originally employed 14 models that use statistical distributions to account for variable
ratios among codon sites. Models M0, M1, M2, M3, M7, and M8 were shown to be sufficient for accurate selection analysis (Yang et al. 2000). Models M0, M1, and M7 do not allow for the existence of positively selected sites. M0 calculates a single
ratio (between 0 and 1) averaged over all sites, M1 accounts for neutral evolution by estimating the proportion of conserved (
= 0) and neutral (
= 1) sites, and M7 uses a discrete beta distribution between 0 and 1 to model different
ratios between sites. Alternatively, models M2, M3, and M8 account for positive selection by using parameters that can estimate
> 1. Models M2 and M8 extend M1 and M7, respectively, through the addition of two parameters that have the potential to estimate
> 1 for an extra class of sites. M3 provides the most sensitive test for positive selection by estimating an
ratio for a predetermined number of classes (three in these analyses). The first step in identifying amino acid sites under positive selection is to test whether sites exist with
> 1 by application of likelihood ratio tests (LRTs) to compare nested models. M0 and M1 are both special cases of M2 and M3, and M7 is a special case of M8. Such nested models can be compared by LRTs. Once positively selected sites have been shown to exist, the second step is to use Bayesian methods to locate their position. Sites having high posterior probabilities (P > 90%) of belonging to a site class with
> 1 are good candidates for positively selected sites. The methods and models described here were implemented within the CODEML program of the PAML version 3.0c package (Yang 1997). To avoid artifactual detection of positive selection, occurrence of substitution saturation at the three positions in the codons and recombination events within the different ORFs were checked, as previously described (Moury et al. 2002), and each program was run at least three times with different initial values for
to avoid local ML estimates.
Evolutionary Rate Shifts Among CMV Subgroups
The LRT developed by Knudsen and Miyamoto (2001) was used to detect specific amino acid or nucleotide sites that evolve at different rates in different subgroups of CMV sequences. A significant rate difference between two subgroups at a given site would, thereby, mean that the function of this position could be different in the two groups and/or that evolutionary constraints differ between CMV subgroups. The likelihood of the null hypothesis assuming that a given position evolves with different rates in the two sequence subgroups is compared with the likelihood of the alternative hypothesis (same rate in the two subgroups). The number of sites with rate differences detected by the LRT at a given P significance level can be compared with the number of sites expected by chance (P x l; l is the length of the alignment) to assess the number of positions with significantly different rates. Because of limited numbers of sequences in some data sets, pairwise comparisons between CMV subgroups were performed on nucleotide and amino acid sequences of the CP and 3a protein only. The program is available at www.daimi.au.dk/compbio/rateshift and allows analysis of 30 sequences at the same time. Consequently, for the CP of subgroup IA CMV strains, two random subsets of 30 sequences (among 44) were analyzed and revealed only a few differences.
Nucleotide Frequencies and Codon Usage
Nucleotide, dinucleotide, and codon frequencies in the CP sequences of the CMV strains in subgroups IA and IB were calculated by use of DAMBE version 4.0.75 (Xia and Xie 2001). The theoretical codon distributions for each amino acid within each codon site affected by evolutionary rate shift between subgroups IA and IB was calculated along with the average codon frequencies in each subgroup. For each amino acid at these sites, deviation of the observed codon distribution in the two CMV subgroups from the theoretical distribution was evaluated by a 2 test.
RNA Structural Constraints
The secondary structure of the CP-coding sequences and of the corresponding subgenomic RNA 4 sequences of five IA and five IB strains were predicted by use of the mFOLD version 3.1 program (Zucker 1989) with the temperature parameter set at 30°C. Based on free energy values, the three most stable structures were examined for each sequence. Secondary-structure predictions can be independently supported by occurrence of nucleotide covariation, in which a nucleotide substitution of a base-paired sequence is matched by a substitution in the paired sequence that preserves binding. For each nucleotide site of the CP-coding sequence potentially affected by evolutionary rate shifts between subgroups IA and IB of CMV, I searched for covarying nucleotide sites in the alignment of the CP ORF. This search was done by hand with the help of Microsoft EXCEL.
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Results |
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Selection Analysis of ORFs 1a, 2a, 2b, and 3a
Selection analysis of ORFs 2b and 3a data sets did not identify any positively selected site (table 1). In contrast, positive selection was identified in ORFs 1a and 2a data sets with models M3 and M8. For both ORFs, M2 was unable to detect a positively selected class, because its extra parameters were used to account for a relatively large class (29% for ORF 1a and 33% for ORF 2a) of fairly conserved amino acid sites ( = 0.1 for ORF 1a and 0.2 for ORF 2a). For both ORFs, M3 detected about 1% of sites under weak positive selection (
2), M3 was able to reject M0 and M1 in LRTs but was unable to reject M2. M8, which also predicted a small proportion of sites with similar positive selection, was able to reject M7, which confirms the significance of positive selection in both ORFs. M8 predicted that eight sites in ORF 1a (aligning with amino acid sites 249, 256, 259, 448, 550, 551, 553, and 697 of strain Fny [accession number D00356]) and that two sites in ORF 2a (aligning with amino acid sites 270 and 851 of strain Fny [accession number D00355]) belonged to the positively selected class with P > 90%, whereas M3 predicted that sites 249, 256, 259, 448, 553, and 697 in ORF 1a and site 270 in ORF 2a were positively selected with P > 90% (table 6 and fig. 1).
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Discussion |
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On the average, the evolutionary constraints exerted on proteins 1a, 2a, and 3a are larger than those exerted on proteins 2b and 3b. These conclusions agree with those of Roossinck (2002) based on the topology of the trees representing these ORFs. The different proteins encoded by the CMV genome play different roles in the infection cycle of the virus. They are all involved in different steps of infection within the plant (replication, movement, or seed infection) and the CP also interacts with the aphid vectors, which allows plant-to-plant transmission of the virus. Regarding this diversity of function and of interaction, it is not surprising that evolutionary constraints vary between these proteins. What is surprising is that the evolutionary constraints also varied between subgroups of CMV. The average selective pressure on the CP differed largely between the three subgroups (table 3). Confirming this finding is the fact that a small proportion of amino acid sites were shown to be under strong positive selection in subgroups IA and II, whereas only weak positive selection was shown in subgroup IB. Moreover, the positively selected sites are different in the three subgroups, belong to different structural domains of the CP (Wikoff et al. 1997; Smith et al. 2000); and almost all of them were indeed shown to evolve faster in one subgroup than in others (table 5). CMV strains belonging to subgroups IA and II are distributed worldwide but can show host preferences (Quiot et al. 1979) and different temperature sensitivities (Douine et al. 1979). Twenty-three out of the 25 strains in CMV subgroup IB were collected in East Asia. These biological differences and/or these distribution variations could be the reasons for different evolution patterns.
Although CMV can be transmitted by a very large number of aphid species (Edwardson and Christie 1991), and although it shows an extremely wide host range, some degree of specificity exists both for transmission (Perry, Zhang, and Palukaitis 1998) and plant infection (Leroux et al. 1979; Shintaku, Zhang, and Palukaitis 1992; Suzuki et al. 1995; Szilassy, Salánki, and Balázs 1999; Takeshita, Suzuki, and Takanami 2001; Kobori et al. 2002). Adaptation to the plant or to the vector could then explain why diversifying selection affects several sites in the CMV genome. Also, concerted evolution between the CMV proteins or between amino acids within a protein could be internal constraints that drive such rapid amino acid substitutions. No particular functions have been attributed to the positively selected sites in proteins 1a and 2a of CMV. Two clusters of three positively selected sites are noticeable in protein 1a (at positions 249, 256, and 259 and at positions 550, 551, and 553). The comparison of protein 1a of CMV with the structure of the corresponding protein of brome mosaic virus (BMV) (O'Reilly and Kao 1998), which belongs also to the family Bromoviridae, indicates that positively selected amino acid sites 249, 256, 259, and 448 belong to the methyltransferase-like domain, that sites 550, 551, and 553 are located in a putative flexible hinge that separates the methyltransferase-like and the helicase-like domains, and that site 697 belongs to the helicase-like domain. Analogy to a functional model proposed for protein 1a of BMV by O'Reilly et al. (1998) further suggests that variations of the positively selected amino acids located in the methyltransferase-like or helicase-like domains can affect physical interactions at different levels (between domains of a single 1a protein, between two different 1a proteins, or between proteins 1a and 1b). The amino acids located between the methyltransferase-like and helicase-like domains could be directly involved in binding with viral or nonviral ligands because they are exposed on the surface of the RNA-dependent RNA polymerase complex of BMV (Dohi et al. 2002). However, the lack of covariation between amino acids subjected to positive selection within protein 1a, between proteins 1a and 2a, or between protein 1a and the CP (data not shown) suggests that these amino acids could be involved in adaptation of CMV through interaction with nonviral ligands.
For the CP, almost all amino acids subjected to positive selection (except amino acids 76, 82, and 137) are buried in the folded CP or between subunits in assembled virions (Smith et al. 2000). Variations at these positions may indirectly affect the CP structure and CMV fitness. Amino acids 25, 76, and 214 are subjected to positive selection in subgroups IA and/or IB and were shown to affect transmission by aphids (Perry, Zhang, and Palukaitis 1998). Substitutions at these three amino acid positions affected transmission efficiency by Myzus persicae rather than by Aphis gossypii (Perry, Zhang, and Palukaitis 1998). In this study, rapid evolution of amino acid at position 25 in the CP was detected in all independent analyses with high significance. In subgroups IA and IB, amino acid 25 is a serine or a proline, the substitution of which may imply a substantial structural change in the protein. The fact that this position aligns with a one-amino-acid gap in the CP of subgroup II strains (data not shown) strengthens the flexibility of this region. These data suggest that aphid transmission could be a major evolutionary constraint on the CP of CMV. At least two mechanisms can account for differential selection through nonpersistent aphid transmission: (1) different aphid species or populations can select and propagate different components in virus populations because of different affinities in binding to different CMV virions, or (2) even with identical affinities between aphids and CMV variants, tradeoffs between aphid transmissibility and accumulation within host plants can accelerate diversifying selection in the CMV genome. The first mechanism was shown with strains and mutants of CMV obtained in the laboratory with two different aphid species (Perry, Zhang, and Palukaitis 1998). These different CMV variants did not seem, however, to accumulate at different titers in the plants (Perry, Zhang, and Palukaitis 1998). Conversely, amino acids that are exposed on the surface of the virus and whose variation drastically affect aphid transmission (Perry, Zhang, and Palukaitis 1998; Liu et al. 2002) were not detected by positive selection analyses, which suggests that variations at these sites confer too large fitness penalties in natural populations of CMV.
Amino acid positions in the CP or other ORFs that were previously associated with plant host adaptation or symptom variations, namely amino acid positions 129, 162, and 193 of the CP (Shintaku, Zhang, and Palukaitis 1992; Suzuki et al. 1995; Ryu, Kim, and Palukaitis 1998; Szilassy, Salánki, and Balázs 1999; Takeshita, Suzuki, and Takanami 2001; Kobori et al. 2002), amino acid positions 51 and 240 of protein 3a (Kaplan, Gal-On, and Palukaitis 1997; Takeshita, Suzuki, and Takanami 2001), and amino acid positions 631 and 641 of protein 2a (Kim and Palukaitis 1997) did not belong to positively selected classes of amino acids. This finding suggests that infection of plants belonging to a wide diversity of species does not, on the whole, shape CMV evolution.
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Supplementary Material |
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Acknowledgements |
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Footnotes |
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