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1 Laboratory of Plant Virology, Faculty of Agriculture, Saga University, Saga 840-8502, Japan
2 Statistical Consulting Unit, Graduate School, Australian National University, Canberra, ACT 0200, Australia
3 7 Hutt Street, Yarralumla, ACT 2600, Australia
Correspondence
Kazusato Ohshima
ohshimak{at}cc.saga-u.ac.jp
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The GenBank/EMBL/DDBJ accession numbers for the sequences determined in this work are AB252094–AB252143.
Present address: National Research Institute of Brewing, Hiroshima Office, Higashi-hiroshima, Hiroshima 739-0046, Japan. 
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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; Urcuqui-Inchima et al., 2001). Turnip mosaic virus (TuMV) infects a wide range of plant species, primarily from the family Brassicaceae. It is probably the most widespread and important virus infecting both crop and ornamental species of this family and occurs throughout the world (Provvidenti, 1996). TuMV was ranked second only to Cucumber mosaic virus as the most important virus infecting field-grown vegetables in a survey of virus diseases in 28 countries and regions (Tomlinson, 1987; Walsh & Jenner, 2002). TuMV belongs to the genus Potyvirus. This is the largest genus of the largest family of plant viruses, the Potyviridae (Shukla et al., 1994; Fauquet et al., 2005), which itself belongs to the picorna-like supergroup of viruses. TuMV, like other potyviruses, is transmitted by aphids in a non-persistent manner (Hamlyn, 1953). Based on genomic sequence differences, TuMV is subdivided into four ‘genogroups' termed basal-B, basal-BR, Asian-BR and world-B (Ohshima et al., 2002).
Studies of the molecular evolutionary history of viruses help to provide an understanding of important features of their biology such as changes in virulence and geographical ranges and their ‘emergence’ as new epidemics, information that is essential for designing strategies for controlling viruses. Such studies are very complex as they involve understanding variation caused by mutation, recombination, selection and adaptation (Simon & Bujarski, 1994; Roossinck, 1997; Bousalem et al., 2000; García-Arenal et al., 2001; Rubio et al., 2001; Bateson et al., 2002; Chen et al., 2002a; Monci et al., 2002; Moury et al., 2002; Ohshima et al., 2002; Stenger et al., 2002; Jenner et al., 2003; Tomimura et al., 2003, 2004; Glasa et al., 2004; Moreno et al., 2004; Tan et al., 2004, 2005; Delatte et al., 2005; Vives et al., 2005). Recombination is common in RNA viruses of both animals and plants. It is also considered to be a major determinant of change in viral virulence and has been implicated in the emergence of new viral strains (Worobey & Holmes, 1999, 2001).
The evolution of potyviruses is still poorly understood and it is unclear whether it mostly depends on the accumulation of mutational changes or on homologous recombination, or on a combination of these processes. There have been few reports of studies to identify recombination sites in the genomes of potyviruses, perhaps because potyvirus genomic RNAs are around 10 kb in length and hence their sequencing still represents a significant task for most plant virology laboratories. Potato virus Y and TuMV are the only potyviruses for which the complete genomic sequences of a significant number of isolates, approximately 40, have been reported.
In our earlier studies, we attempted to assess the extent of homologous recombination in chosen regions of TuMV genomic sequences (Ohshima et al., 2002; Tan et al., 2004; Tomimura et al., 2004) or in complete genomic sequences (Tomimura et al., 2003) using the distance and phylogenetic methods PHYLPRO (Weiller, 1998) and SISCAN (Gibbs et al., 2000). Eight recombination patterns were found in 38 complete genomic sequences. Many programs that detect recombination by sequence comparisons have been developed using different algorithms during the last 15 years. The performance of these methods has been evaluated (Posada & Crandall, 2001; Posada, 2002). However, there have been few reports of studies using them to understand the recombination of plant RNA viruses. The possibility of carrying out independent checks on the precise position of recombination crossover sites has come from reports that homologous recombination based upon copy choice and template-switching mechanisms strongly depends on composition and RNA secondary structure (Nagy & Burjarski, 1996, 1997). We know of no reports where ‘sequence comparison’ and ‘composition’ methods have been combined to enhance the precision with which crossover sites are identified. Here, we report on studies using these combined methods to analyse 42 complete genomic sequences of TuMV isolates from the international gene sequence databases, as well as 50 complete genomic sequences generated from TuMV-infected plants. We found that recombination occurred throughout the TuMV genome, but especially in particular ‘hotspots’. TuMV evolution is discussed in the light of our evidence of recombination.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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, together with the same details for the isolates for which the complete genomic sequences have already been reported (Tomimura et al., 2003; Chen et al., 2003b; Suehiro et al., 2004; GenBank accession numbers AF394601
[GenBank]
, AF394602
[GenBank]
, AY134473
[GenBank]
and AF530055
[GenBank]
). All of the isolates were inoculated on to Chenopodium quinoa and serially cloned through single lesions at least three times. They were propagated in Brassica rapa cv. Hakatasuwari or Nicotiana benthamiana plants. Plants infected systemically with each of the TuMV isolates were homogenized in 0.01 M potassium phosphate buffer (pH 7.0) and mechanically inoculated on to young plants of B. rapa cv. Hakatasuwari, Brassica pekinensis cv. Nozaki-1go, B. napus cv. Norin-32go and Raphanus sativus cvs Taibyo-sobutori and Akimasari. Inoculated plants were kept for at least 4 weeks in a glasshouse at 25 °C.
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) or TuMV-infected B. rapa and N. benthamiana leaves using Isogen (Nippon Gene). The RNAs were reverse transcribed and amplified using high-fidelity Platinum Pfx DNA polymerase (Invitrogen). cDNAs were separated by electrophoresis in agarose gels and purified using a QIAquick Gel Extraction kit (Qiagen). Purified cDNAs were cloned into pBluescript II SK+. Plasmids were maintained in Escherichia coli XL-1 Blue (Stratagene). Sequences from each isolate were determined using three or four overlapping independent RT-PCR products and cloned plasmids to cover the complete genome. The sequences of the RT-PCR products or cloned fragments of adjacent regions of the genome overlapped by at least 100 bp to ensure that they were from the same genome and were not from different components of a genome mixture. Each cloned plasmid and RT-PCR product was sequenced by primer walking in both directions using a BigDye Terminator v3.0 or v3.1 Cycle Sequencing Ready Reaction kit (Applied Biosystems) and an Applied Biosystems Genetic Analyser DNA model 310; ambiguous nucleotides in any sequence were checked in sequences obtained from at least five other independent plasmids. Sequence data were assembled using BioEdit version 5.0.9 (Hall, 1999).
Recombination analyses.
All sequence analyses were done on a PC (Dell, Dimension 8300, 3.2 GHz). The genomic sequences of the 92 isolates were used for evolutionary analyses. Two sequences of Japanese yam mosaic virus (JYMV) (Fuji & Nakamae, 1999, 2000), one of Scallion mosaic virus (ScMV) (Chen et al., 2002b) and one of Narcissus yellow stripe virus (NYSV) (Chen et al., 2003a) were used to align the TuMV genomic sequences, as BLAST searches had shown them to be the sequences in the international sequence databases most closely and consistently related to those of TuMV; TuMV protein 1 (P1) genes were more closely related to those of JYMV than ScMV, whereas for some other genomic regions between the helper-component proteinase protein (HC-Pro) and nuclear inclusion b protein (NIb) sequences the converse was true, except that the TuMV coat protein (CP) gene was most closely related to that of NYSV. We therefore aligned all 92 P1 sequences with those of two JYMV isolates as the outgroup, the CP sequences with that of NYSV and the remaining sequences with those of JYMV and ScMV using CLUSTAL X (Jeanmougin et al., 1998). However, this procedure resulted in some gaps that were not in multiples of three nucleotides. Therefore, the amino acid sequences corresponding to individual regions were aligned with the appropriate outgroups indicated above using CLUSTAL X with TRANSALIGN (kindly supplied by Georg Weiller, Australian National University, Canberra, Australia) to maintain the degapped alignment of the encoded amino acids and the aligned sub-sequences were then reassembled to form complete sequences of 9321 nt. The aligned sequences were checked for incongruent relationships that might have resulted from recombination, using RDP (Martin & Rybicki, 2000), GENECONV (Sawyer, 1999), BOOTSCAN (Salminen et al., 1995), MAXCHI (Maynard Smith, 1992), CHIMAERA (Posada & Crandall, 2001) and SISCAN programs (Gibbs et al., 2000) in RDP2 (Martin et al., 2005) and PHYLPRO (Weiller, 1998), SISCAN version 2 (Gibbs et al., 2000) and SISCAN M (kindly provided by M. J. Gibbs & J. S. Armstrong, Australian National University, Canberra, Australia) programs. First, we checked for incongruent relationships using the programs in RDP2. These analyses were done using default settings for the different detection programs and a Bonferroni corrected P-value cut-off of 0.05 or 0.01. Next, all sequences that had been identified as likely recombinants, together with all those used in this study, were checked again using the original PHYLPRO and SISCAN version 2, not only with all nucleotide sites, but also with synonymous and non-synonymous sites separately. We checked 100 and 50 nt slices of all sequences for evidence of recombination using these programs. These analyses also assessed which non-recombinant sequences had regions that were closest to regions of the recombinant sequences and hence indicated the likely lineages that provided those regions of the recombinant genomes. For simplicity, we called these the ‘parental isolates' of recombinants, although in reality they were just the most closely related sequences in the set we were analysing. Finally, the location of each recombination site was defined as precisely as possible by comparing the compositions of the 5' and 3' sequences around the site where the exchange probably occurred.
Recombination site distribution.
The distribution of recombination sites within the genome was tested statistically. If it is assumed that every observed recombination site is independent of the others, then the intersite distances will have a geometric distribution. A Kolmogorov statistic (Conover, 1999) was used to test the maximum difference between the observed cumulative distribution of intersite distances and the theoretical distribution under randomness for the observed number of recombinations. The significance of the statistic was assessed by allocating recombination sites at random and recalculating the test statistic 9999 times. The percentage of calculated values (including the observed value) greater than or equal to the observed value was taken to be its significance level.
Phylogenetic analyses.
The phylogenetic relationships of the sequences were determined by two methods: the maximum-likelihood (ML) algorithm of TREEPUZZLE version 5.0 (Strimmer & von Haeseler, 1996; Strimmer et al., 1997) and the neighbour-joining (NJ) algorithm of PHYLIP version 3.5 (Felsenstein, 1993). For ML analyses, 1000 puzzling steps were calculated using the Hasegawa–Kishino–Yano model of substitution (Hasegawa et al., 1985). For NJ analyses, distance matrices were calculated by DNADIST with the Kimura two-parameter option (Kimura, 1980) and trees were constructed from these matrices by the NJ method (Saitou & Nei, 1987). A bootstrap value for each internal node of the NJ trees was calculated using 1000 random resamplings with SEQBOOT (Felsenstein, 1985). The calculated trees were displayed using TREEVIEW (Page, 1996). One ScMV and two JYMV sequences were used as the outgroups to construct a phylogenetic tree of the concat regions, as the CP sequence of only one NYSV isolate was available. The JYMV and ScMV sequences corresponding to individual gene regions within the genomes were aligned as the encoded amino acids using CLUSTAL X with TRANSALIGN to maintain the degapped alignment of the nucleotides and then reassembled to form sequences of 8988 nt. The nucleotide and amino acid similarities were estimated using the Kimura two-parameter method (Kimura, 1980) and the Dayhoff PAM 250 matrix (Dayhoff et al., 1983), respectively.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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. Twenty-one of the European and five of the Asian isolates infected most Brassica plants systemically but did not infect R. sativus. Thus, most of these isolates, despite minor differences in pathogenicity for some of the tested Brassica hosts (data not shown), were of the Brassica (B)-infecting host type. Only three of the European isolates infected R. sativus systemically and were therefore of the Brassica/Raphanus (BR) host type; these were isolates Cal1, ITA 7 and PV0104, which had been collected in Italy and Germany from Calendula officinalis, R. raphanistrum and Lactuca sativa, respectively. In contrast, approximately 90 % of isolates from Asia were BR host type.
Fifty TuMV genomes sequenced in this study were analysed, as well as 42 sequences obtained from the international gene sequence databases. Most were 9798 nt excluding the 5' end 35 nt primer sequence; those of the St48 and Al isolates were 9797 nt and were 1 nt shorter in the 3' non-coding region (NCR). For analysis, the terminal primer sequences were omitted. The regions encoding the P1, HC-Pro, protein 3 (P3), 6 kDa 1 protein (6K1), cylindrical inclusion protein (CI), 6 kDa 2 protein (6K2), genome-linked viral protein (VPg), nuclear inclusion-proteinase protein (NIa-Pro), NIb and CP genes were 1086, 1374, 1065, 156, 1932, 159, 576, 729, 1551 and 864 nt respectively. The CI genes of the Canadian Q-Ca and Taiwanese C1 isolates previously reported by Nicolas & Laliberté (1992) and GenBank accession no. AF394601
[GenBank]
are 1929 nt and hence 3 nt shorter than the genomes of the other isolates. All of the motifs reported in potyvirus genes and encoded proteins were found.
The pairwise nucleotide and encoded amino acid similarities were calculated for each gene, and for the intact genomic sequences, of the 24 non-recombinant sequences (data not shown). The P1 gene and the protein it encodes were the most variable and had only a few totally conserved residues, but these were not clustered as a compact motif. The P3 gene and protein were almost as variable as those of the P1 gene.
Recombination sites identified by sequence comparison programs
We looked for evidence of recombination in the genomes. We examined the polyprotein sequences and omitted the 5' and 3' NCRs because we wished to examine not only all of the nucleotide sites, but also the synonymous and non-synonymous sites separately using SISCAN version 2. After all gaps and codons homologous to them had been removed, the likely recombination sites were assessed using RDP2. When the recombination detection programs RDP, GENECONV, BOOTSCAN, MAXCHI, CHIMAERA and SISCAN in RDP2 were used with default settings and a Bonferroni corrected P-value cut-off of 0.05 or 0.01 for the 92 aligned sequences, the number of potential recombination sites detected in individual genes was ranked as CI>P1>VPg>HC-Pro>P3>CP>NIb>NIa-Pro and the number detected by each program was in the order SISCAN>MAXCHI>GENCONV>CHIMAERA>BOOTSCAN>RDP. We analysed each of the identified sites individually and used a phylogenetic approach to verify the parent/donor assignments made by RDP2. Having examined all sites with an associated P value of <1.0x10–6 (i.e. the most obvious events), we focused on the intralineage recombinants and removed the interlineage recombinants by treating the identified recombination sites as missing data in subsequent analyses. Moreover, the ‘phylogenetic profiles' of the polyprotein sequences were examined by PHYLPRO and SISCAN M, and SISCAN version 2 programs were then used to check for evidence of recombination, not only in the total nucleotide sites, but also in synonymous and non-synonymous sites separately. This complex approach was adopted to find not only all of the recombination sites, but also to decrease the possibility of obtaining false evidence of recombination sites. Table 2 lists the likely recombinants and their recombination sites as indicated by the programs, together with the sequences most closely related to their parents (‘parental sequences’). Only 24 out of 92 genomes (26 %) showed no evidence of recombination.
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HC-Pro gene.
There were seven recombination sites (8–14) in HC-Pro genes. Most were identified by several methods, except that the recombination site at nt 1543–1544 of isolate Rn98 was only identified by MAXCHI and CHIMAERA. This interlineage world-B and basal-BR recombination site was not supported by a Z value greater than three in SISCAN version 2, nor were the two other interlineage recombination sites.
P3 gene.
The P3 and P1 genes are the most variable potyvirus protein genes (Urcuqui-Inchima et al., 2001). However, only two recombination sites (15 and 16) were found in the P3 gene, in isolates FD27J and TD88J. These were interlineage and were identified and supported by most of the programs.
6K1 gene.
No recombination sites were found.
CI gene.
Most of the 11 recombination sites (17–27) found in the CI gene were in its C-terminal half. Some were intralineage, others were interlineage. Six of the eight interlineage recombination sites were derived from Asian-BR (5' upstream) and world-B (3' downstream) parents. Many, but not all, of the recombination sites were identified by at least two recombination-detecting programs and all were clearly supported by P and Z values.
6K2 gene.
There were at least two interlineage recombination sites (28 and 29) in the 6K2 gene. The sites were identified by most programs and both were interlineage recombination sites.
VPg gene.
The six recombination sites (30–35) were located throughout the VPg gene and most were detected by several methods. Recombination site 35 was derived from intralineage world-B parents, whereas the other recombination sites were from interlineage parents.
NIa-Pro gene.
The NIa-Pro gene had at least three recombination sites (36–38) located at the N terminus of the gene. These recombination sites were identified by many of the recombination-detecting programs and, although the recombination site of FKH122J was poorly supported (Z values of less than 3), both NDJ and NID119J were supported by SISCAN version 2 using synonymous sites.
NIb gene.
Two recombination sites (39 and 40) were found in the NIb gene. The recombination site at nt 8006–8016 was detected by several programs, whereas another site at nt 7406–7416 was detected by only a few programs. This recombination site was derived from parents of the same lineages of world-B. Neither recombination site was supported (Z values less than 3) by synonymous site analysis using SISCAN version 2.
CP gene.
There were at least four recombination sites (41–44) in the CP gene. Three of the four recombination sites were identified as recombinants by several recombination-detecting programs, whilst the fourth (nt 9188–9228) was identified by only three methods and was not supported by synonymous site analysis in SISCAN version 2.
In summary, a total of 44 recombination sites was found in the TuMV sequences. In general, interlineage recombination sites seemed to be supported by smaller P values and greater Z values than those with intralineage parents. The intralineage recombinants were derived from parents of different sublineages of the world-B group (data not shown). The recombination-detecting programs seemed to have trouble detecting rare recombination events, especially when the parental sequences differed by less than 5 %. Most of the TuMV recombination sites were clearly supported by recombination-detecting programs based on conceptually different methods.
Identification of recombination sites by sequence composition features
Recombination detecting programs that compare sequences only identify the approximate position of recombination sites. We therefore attempted to define each recombination site more accurately by examining the composition of the sequence on either side (
50 nt) of the site (Table 3). It can be seen that sequences located upstream (5') of most detected recombination sites had a higher GC content than the downstream (3') sequences, which were AU-rich. For instance, sequences located upstream of recombination site 1 at nt 700 had 80 % GC, whereas downstream they had 60 % AU. At all recombination sites, the GC- and AU-rich sequences were similar in length.
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shows the 37 different patterns of 44 recombination sites found in the recombinants and Table 4 lists the isolates in which those patterns were found. Twelve recombination patterns (2–11, 33 and 34) seemed to be derived from parents from the same major lineages, whilst the others were derived from parents of different major lineages. All of the intralineage recombinants were from world-B parents, whereas the interlineage recombinants were from parents of world-B and Asian-BR sequences, and many of these had recombination sites in the centre of the P1 gene and from the C-terminal half of CI to the N terminus of the VPg gene. Several genomes were multiply recombinant and had Asian-BR sequences between the P1 gene and the C terminus of CI gene and originated in East Asia. Many of the patterns were found in only one isolate, but a few were found in several, although they showed no particular distribution of provenance. For instance, isolates with pattern 3 were collected in China, Taiwan, Japan, Greece, The Netherlands, the UK and Kenya.
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summarizes the estimated positions of the 44 recombination sites in all of the genomes examined. It can be seen that there were more recombination sites in some genes than in others, especially the larger ones and notably the P1, HC-Pro, CI and VPg genes. However, it was also clear that many of the recombination sites formed two clusters, one in the P1 gene region and the other in the CI/6K2/VPg region. We therefore tested whether this clustering was more than would be expected by chance using a Kolmogorov-type statistic. The intersite distribution of recombination sites was compared with the distribution of 9999 sets of sites generated randomly. It can be seen (Fig. 2) that there were more clustered sites (i.e. small intersite distances) and fewer sites at greater intersite distances than in the randomly generated distribution. The Kolmogorov statistic for the observed distribution was exceeded in less than 5 % of the random distributions.
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). The isolates with patterns 1, 2, 4, 6 and 7 were B host type and most were intralineage recombinants, whereas the isolates with patterns 5, 9, 10 and 12–37 were BR host type and a mixture of intralineage and interlineage recombinants, and these interlineage recombinants had Asian-BR sequence(s). The isolates with patterns 3 and 8 were a mixture of B and BR host type and ‘tentative’ world-B intralineage recombinants.
Phylogenetic relationships
We initially calculated trees from the genomes of the 92 isolates, including all of the recombinants identified in this study. However, there were inconsistencies in, and poor bootstrap support for, some lineages in the resulting trees, as found previously (Ohshima et al., 2002). We therefore recalculated trees from the genomes of only 58 isolates, omitting the interlineage recombinants. The relationships of these isolates were investigated by ML and NJ methods (data not shown) and the ML tree is shown in Fig. 3. All of the trees partitioned most of the sequences into the same four consistent groups, as reported previously (Ohshima et al., 2002). The basal-B group was a sister group to all others in the ML and NJ phylogenies and was supported by high bootstrap values. However, the NJ tree, but not the ML tree, had an Asian sublineage in the world-B group, as described previously (Tomimura et al., 2003; Tomitaka & Ohshima, 2006).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The accurate detection of recombination sites in viral sequences is important and a number of programs have been developed for this purpose. BOOTSCAN, RDP and SISCAN are phylogenetic methods, GENECONV, MAXCHI and CHIMAERA are substitution methods and PHYLPRO is a distance comparison method. Posada & Crandall (2001) evaluated the performance of 14 different recombination-detecting programs, not including the SISCAN program, and showed that the performance of different recombination methods depended on the amount of recombination, their genetic diversity and on rate variation. Fortunately, they concluded that most recombination methods did not infer many false positives, but they also concluded that one should not rely too much on a single method. In this study, we therefore used six programs representing the three different types of methods – phylogenetic, substitution and distance – to assess evidence of recombination. Many, but not all, interlineage recombinants were identified by most programs; in contrast, some intralineage recombinants, for instance recombination site 35 in the VPg gene, were most clearly detected by two programs, MAXCHI and CHIMAERA, and recombination site 39 in the NIb gene was most clearly detected by RDP, BOOTSCAN and SISCAN. It seems that programs of the same type agreed in the detection of recombination sites that had weakest support. However, most of the recombination sites identified in the P1, VPg, NIa-Pro and CP genes in this study were the same as those identified in earlier studies (Tan et al., 2004; Tomimura et al., 2004), except for one, a recombination site at nt 6121 in VPg of Asian-BR lineage sequences and only identified by SISCAN (Tan et al., 2004), so we conclude that this may be a false positive.
To summarize the results of these comparisons, we classified recombination sites into two types: ‘clear recombination sites’, detected by four or more different programs and two or more types of method, and ‘tentative recombination sites’, detected by three or fewer programs and only one or two types of method (Fig. 1). Using this way to summarize the results, most of the recombination sites identified in TuMV genomes were ‘clear recombination sites' (see P values in Table 2).
Studies of homologous recombination in bromovirus, tombusvirus and carmovirus genomes (White & Morris, 1994; Nagy & Burjarski, 1995; Nagy et al., 1999b) have shown that, in viral sequences having near-equal GC and AU content, a recombination occurs more often between a GC-rich (60 % GC content) region and a downstream (3') AU-rich region (60 % AU). Moreover, similar lengths of GC- and AU-rich sequences enhance recombination. Sequences displaying all of these features were termed ‘homologous recombination activators' (Nagy et al., 1999a) and this feature was shown in recombination sites of the sequences from a natural population of Citrus tristeza virus (Vives et al., 2005). The authors postulated that sequence similarity may not by itself support homologous recombination in Brome mosaic virus (Nagy & Burjarski, 1996), but may require additional structural features in the recombination site. In our study of TuMV, the composition of 50 nt on either side of identified recombination sites was compared. Sequences upstream of the recombination sites had higher GC content than those downstream in most, but not all, recombination sites (Table 3). Hence, many of the recombination sites in TuMV populations showed characteristics of previously reported homologous recombination activators.
There have been reports associating recombination with increases in pathogenicity, extended host ranges and the ability to overcome resistance in crop varieties (García-Arenal & McDonald, 2003). In an earlier study reported by our laboratory, an isolate of TuMV of B host type (i.e. isolate UK1) was adapted to infect almost insusceptible R. sativus. Many mutations were found in the adapted strain in the centre of the genomic region between the P3 and CI genes (Tan et al., 2005), whereas in this study the clusters of recombination sites were found in the P1 gene and in the CI/6K2/VPg genes. We do not know whether this difference is significant or reflects the relatively small number of samples we examined; it is possible that the clusters of recombinants we found indicate the regions of the genome where recombination mostly produces no selectable phenotypic effect, whereas recombination in other regions has a larger phenotypic effect and is therefore more actively selected. In the present study, many interlineage recombinants with the host type of BR isolates (Table 4) had world-B (5' end)xAsian-BR (central part)xworld-B (3' end) regions of their genomes or sometimes an Asian-BR region situated between P1 and VPg genes (Fig. 1). In addition, all of these interlineage recombinants (patterns 12–21, 25–32, 36 and 37) had Ile at aa 1100 in the P3 gene, which has been linked with the initial stages of adaptation of TuMV to R. sativus. Hence, these recombination events may extend the host range of TuMV to generate the BR host type, which is found mainly in Asian countries. Interestingly, these recombinants generally had Asian-BR lineage regions not only in the P3–CI region but also in the HC-Pro gene, which is known to be an RNA silencing suppressor of potyviruses (Roth et al., 2004). On the other hand, many isolates of the world-B intralineage recombinants and non-recombinants (Fig. 1 and Table 4, recombination type 3) were also of BR host type. It is possible, of course, that some world-B non-recombinants of BR host type were in fact intralineage recombinants, as most recombination-detecting programs had trouble detecting such recombination events (Posada & Crandall, 2001) and also point mutations may generate new phenotypes of this sort.
It is probable that both recombination and mutation are required to produce new phenotypes during TuMV evolution. The obvious selective benefits of recombination in RNA viruses is that potentially advantageous genotypes covering a much larger ‘evolutionary space’ can be generated than by the sequential mutation of clonal populations. In addition, deleterious mutations can be removed by recombination of the error-free parts of co-infecting genomes. However, it is evident that physical and/or ecological factors also influence the rate of recombination in many RNA viruses, so that it may not always be a selectively advantageous trait (Chare & Holmes, 2006).
In conclusion, recombination occurs in the TuMV genome naturally and frequently, and provides new genotypes exposed to host and ecological constraints. The detailed analysis of representative numbers of genomic sequences for recombination is giving us new information about their evolution.
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ACKNOWLEDGEMENTS |
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pak (Academy of Science of the Czech Republic, Czech Republic) for supplying TuMV isolates. This work was supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science. |
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Received 28 June 2006;
accepted 7 September 2006.
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