Rega Institute for Medical Research, KULeuven, Leuven, Belgium
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Abstract |
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Introduction |
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In contrast with the human immunodeficiency virus (HIV), the third human retrovirus known, HTLV-I and HTLV-II are poorly replicative, with a remarkably stable genome. It has been estimated that the evolutionary rate of HTLV-II in IDUs is around 10-4/10-5 nucleotide substitutions per site per year (Salemi et al. 1998a
), which is one of the lowest evolutionary rates reported for a retrovirus so far (rates generally range between 10-2 and 10-4 nucleotide substitutions per site per year). The molecular mechanisms of this slow evolution could be explained in part by the observation that in HTLV-infected individuals with high proviral loads, a large part of the provirus is produced by clonal expansion of infected cells and not by viral replication (Wattel et al. 1995
; Cimarelli et al. 1996
).
HTLV-Irelated simian viruses, called STLV-I's, have been discovered in several nonhuman primates in Africa and in Asia (Watanabe et al. 1986
; Song et al. 1994
; Ibrahim, De Thé, and Gessain 1995
), and they are also characterized by high genomic stability. African HTLV-I's and STLV-I's cannot be separated into distinct phylogenetic lineages according to their species of origin, but, rather, seem to be related according to the geographic origin of their host (Vandamme, Salemi, and Desmyter 1998
). The term "primate T-lymphotropic virus type I" (PTLV-I) was introduced to describe this group of viruses. Liu et al. (1996)
showed that the three human subtypes Ia, Ib, and Ic arose from three geographically distinct simian reservoirs in West and Central Africa and in Indonesia, respectively. The new HTLV-Id, HTLV-Ie, and HTLV-If subtypes also seem to have arisen from recent simian-to-human transmissions in Africa (Mahieux et al. 1998
; Salemi et al. 1998b
). The closest simian relative of HTLV-II, called STLV-II in analogy with HTLV-I/STLV-I, was isolated from African bonobos (Pan paniscus) (Liu et al. 1994
; Giri et al. 1994
). In contrast to HTLV-I/STLV-I, STLV-II clearly lies in a distinct phylogenetic lineage with respect to HTLV-II, suggesting either an ancient interspecies transmission in Africa or a coevolution of STLV-II/HTLV-II with their host species (Vandamme et al. 1996
). Finally, a new simian T-lymphotropic virus, STLV-L, equidistantly related to HTLV-I/STLV-I and HTLV-II/STLV-II, was isolated from an African baboon (Papio hamadryas) (Goubau et al. 1994
; Van Brussel et al. 1997
). A human counterpart of STLV-L is not known. For simplicity, in this paper we will refer to HTLV and STLV strains in general as primate T-lymphotropic viruses (PTLVs).
The evolutionary history of PTLVs is interesting for both theoretical and practical reasons. HTLV-I is an important human pathogen. Phylogenetic analyses of the DNA sequences, using a good model of nucleotide substitution, can be used to answer different epidemiological questions, such as those regarding the global spread of the different genetic subtypes. Moreover, recent reports seem to suggest that STLV infections are more widespread than previously thought; in light of the growing interest in xenotransplantation, the investigation of their origin, evolution, and capacity for interspecies transmission should be considered with great attention. Other questions on the evolution of human and simian retroviruses have a theoretical interest. Which model of nucleotide substitution can better describe their evolution? Is the rate of nucleotide substitution constant among sites? Are the different lineages evolving more or less at a constant evolutionary rate, following the molecular-clock hypothesis? Did HTLVs and STLVs coevolve with their hosts? Could we use phylogenetic relationships among PTLV strains to fill gaps in the historical records of some of the host species?
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Materials and Methods |
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Sequence Alignments
The 20 PTLV strains were aligned using the GeneWorks software (Intelligenetics, Oxford, England), followed by minimum manual editing. The LTR and proximal pX regions were excluded from the alignment, since DNA dot matrices showed that between HTLV-I, HTLV-II, and STLV-L the similarity in these regions is too low to allow unambiguous alignment. Another alignment, including the bovine leukemia virus (BLV), was obtained using amino acid sequences of the entire gag, pol, and env regions, just excluding the overlapping sequences between gag and pol and between pol and env.
Analysis of the Phylogenetic Signal
The presence of saturation at different codon positions (cdp's) of the PTLV full-genome alignment was tested by comparing the saturation index expected when assuming full saturations with the observed saturation index. Statistical significance was assessed employing a t-test with infinite degrees of freedom. Expected and observed saturation indices were calculated with the program DAMBE (Xia 1999
). The presence of phylogenetic signal in the data set was also investigated with the Hillis and Huelsenbeck (1992)
method based on the skewness of tree length distribution. Given a data set, the tree length under a maximum-parsimony criterion for all possible topologies (or a random sample of them) is computed. If there is no phylogenetic signal in the data, the distribution tends to be symmetric. If there is phylogenetic signal, the distribution tends to be (left) skewed (Hillis and Huelsenbeck 1992
). Since about 1020 unrooted possible trees exist for 20 taxa, we estimated the tree length distribution of 1,000,000 random trees for the 20 PTLV strains using the option "Evaluate Random Trees ..." of PAUP*, version 4.0d65, written by David Swofford. Four separate tree length distributions were obtained, employing the first, second, first + second, and third cdp's, respectively, and their skewness was statistically evaluated.
Another way to visualize the presence of phylogenetic noise in a particular data set of aligned sequences is to perform a likelihood mapping analysis investigating groups of four randomly chosen sequences, called quartets (Strimmer and Von Haeseler 1997
). For a quartet, just three unrooted tree topologies are possible. The likelihood of each topology can be estimated with the maximum-likelihood (ML) method, and the three likelihoods can be reported as dots in an equilateral triangle (see fig. 1 ). For N sequences, N!/4! possible quartets exist and the distribution of the dots in the triangle can give an overall impression of the treelikeness of the data. When the N sequences are not clustered, the order of the sequences is not relevant, and the question of which of the possible tree topologies is supported by any cluster is meaningless. Thus, we can distinguish three main different areas in the equilateral triangle (Strimmer and Von Haeseler 1997
; Nieselt-Struve 1998
): (1) the tree corners representing fully resolved tree topologies, i.e., the presence of treelike phylogenetic signal in the data; (2) the center, which is the area of starlike phylogeny, representing phylogenetic noise; and (3) the three areas on the sides, where it is not possible to decide between two different tree topologies, representing netlike phylogeny. The percentage of dots belonging to each area can give an idea about the mode of evolution in the data set under investigation. Likelihood mapping analyses were performed with the program PUZZLE (Strimmer and Von Haeseler 1997
) employing the first, second, and third cdp's, respectively, of the PTLV genes. For each analysis, all 4,845 possible quartets for the 20 PTLV strains were evaluated.
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Root of the PTLV Tree
Phylogenetic trees were constructed from BLV-PTLV amino acid alignments, assuming BLV as outgroup, with the NJ, Fitch, and wpars methods. The protein distance matrix for the amino acid alignment was estimated in PUZZLE using the Blosum62 model of amino acid substitution. For each method, 1,000 bootstrap replicates were performed to assess statistical significance. The likelihood mapping method was also used to locate the root of the tree. The 21 strains were divided into four groups: BLV (the CG strain), PTLV-I (including all of the HTLV-I and STLV-I strains), PTLV-II (including all of the HTLV-II and STLV-II strains), and STLV-L (the PH969 strain). The likelihood mapping analysis, implemented in PUZZLE, was performed to evaluate the likelihood of the three possible topologies of a tree joining four different groups of taxa (Strimmer and Von Haeseler 1997
).
Models of Nucleotide Substitution and Likelihood Ratio Test
Employing the tree obtained for the 20 PTLV strains, different parametric models assuming eight discrete categories of -distributed rates among sites were evaluated according to the likelihood ratio test (Huelsenbeck and Rannala 1997
): JC69 (Jukes and Cantor 1969
), K80 (Kimura 1980
), F81 (Felsenstein 1981
), HKY85 (Hasegawa, Kishino and Yano 1985
), TN93 (Tamura and Nei 1993
), and REV (Yang 1993
). The program baseml implemented in the PAML, version 1.4, software package (Yang 1997
) was used for the calculations. Successively, more sophisticated models were used to investigate in detail the substitution rate heterogeneity among sites in coding regions of the PTLV genome, as described in the Results section.
The molecular-clock hypothesis was tested on the PTLV tree with the likelihood ratio test for the clock hypothesis implemented in PUZZLE (Strimmer and Von Haeseler 1997
) and the best-fitting nucleotide substitution model. The clock was tested employing only the first and second cdp's or only the third cdp's of each nonoverlapping gene of the PTLV genome.
Test for Positive or Purifying Selection
The numbers of nonsynonymous and synonymous substitutions, indicated (KA and KS, respectively) were computed for PTLV-I and PTLV-II strains separately. A KA/KS ratio significantly lower than 1 indicates the presence of purifying selection, whereas ratios greater than 1 indicate positive selection. KA and KS values were estimated for the gag, pro, pol, env, and tax regions separately by comparing each of the 10 PTLV-I strains with one another using the method of Nei and Gojobori (1986) implemented in the program MEGA, and their averages were used to compute KA/KS ratios for each coding region. The same was done for the nine PTLV-II strains. The presence of selection across the PTLV genome (using only first and second cdp's) was also tested with the program PLATO (Grassly and Rambaut 1998
). A sliding window of 5 nt looks for regions of the alignment which do not fit with a global (null) hypothesis of neutral evolution, represented by the ML tree calculated assuming constant nucleotide substitution rates across sites. When a substitution model and a phylogeny are specified for an alignment, PLATO calculates the likelihood of this null hypothesis for each site along the alignment. Those regions of the alignment which have the lowest average likelihoods are then tested for significant departure from the null hypothesis using Monte Carlo simulation. Significance indicates failure of the null model to explain the observed data and, depending on the null model, can indicate the importance of recombination or selection (Grassly and Rambaut 1998
). A distribution of 1,000 simulated DNA data sets (option -r1000 in PLATO) for the Monte Carlo procedure was used.
Timescale of PTLV Evolution
To estimate divergence times in cases of rejection of the molecular clock, we used the method of Li et al. (1987)
. Consider three homologous sequences with unequal evolutionary rates: a and b, which diverged T1 years ago, and c, which diverged from a and b T2 years ago (T2 > T1), having nucleotide distances kab, kac, and kbc, respectively, and the nucleotide distances kaR, kbR, and kcR between an outgroup R and each of the three sequences. Under a "perfect" molecular clock, we should have:
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Results |
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We used BLV as outgroup in an attempt to determine the root of the general PTLV tree reported in figure 1 . In figure 2 , the likelihood mapping method using the amino acid alignment of the BLV/PTLV sequences (see Materials and Methods) is shown. 85.6% of quartets support the clustering between STLV-L and the PTLV-II strains. Except for the low bootstrap support with the parsimony method for protein (Protpars) implemented in PAUP* (see fig. 2 ), the STLV-L clustering with PTLV-II was also present in the NJ, Fitch, and ML trees (data not shown) supported by robust bootstrap values (see fig. 2 ). In conclusion, the root of the PTLV tree can be placed on the branch leading to PTLV-I.
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The rate parameters estimated for each class of sites are reported in table 4 . The first cdp of gag was chosen as a reference (substitution rate = 1); relative rates for the other classes of sites are shown in the table. In each gene, the first cpd tends to change about two times as fast as the second cpd, whereas the third cpd changes about eight times as fast as the first one. On average, among the nonoverlapping genes, pro shows the highest nucleotide substitution rate and tax shows the lowest (see table 4 ). In the tax/rex overlapping region, sites relative to different tax and rex cdp's tend to change more slowly with respect to cdp's in other genes. One exception is the second cdp of rex, which is also the third cdp of tax, changing around five times as fast as the second cdp's of other genes (see table 4 ). Finally, different PTLV genes generally show a strong transition transversion bias at third cdp's, whereas purine transitions occur about two times more often than pyrimidine transitions at second cdp's (data not shown).
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The third cdp's of STLV-L, PTLV-I, and PTLV-II coding regions evolve at constant rates (see table 5
). A rooted PTLV tree with clocklike branch lengths was constructed based on the third cdp's, excluding HTLV-II IDU strains, for which the clock does not hold (see table 4
) (Salemi et al. 1999
), with the TN93 model with
-distributed rates across sites (estimated
= 4.34). On this tree, employing the host migration time described above as a lower limit of the virus divergence time, we estimated an evolutionary rate for the third cdp of not more than 1.67 ± 0.17 x 10-6 nucleotide substitutions per site per year, which was then further used to date all other nodes of the tree, on both the PTLV-I and the PTLV-II parts, except for the separation between PTLV-I and STLV-L/PTLV-II. In fact, despite the observation that the third cdp's of the PTLV coding regions appear to be saturated when all the strains are included, considering only PTLV-I or only PTLV-II and STLV-L strains, third positions do not show evidence of saturation (see table 1
). Thus, while we can use the clock to date closely related lineages, estimation of divergence times between more divergent lineages, such as PTLV-I and PTLV-II, cannot be reliably based on the clock at the third cdp. We used the BLV/PTLV protein alignment and the method of Li et al. (1987)
(see Materials and Methods) to get an estimate of the separation between PTLV-I and PTLV-II/STLVL corresponding to the deepest branch, which is the origin of PTLV. Amino acid distances were calculated with the Blosum62 substitution model taking into account rate heterogeneity across sites (estimated
= 0.9). Finally, the separation between HTLV-IIa and HTLV-IIb, for which the clock does not hold, was estimated on the general PTLV tree, also including the HTLV-II IDU strains, and using third cdp's and the TN93 model with
-distributed rates across sites (estimated
= 5.2) with the Li et al. (1987)
method. As a starting date, we employed the estimated separation of the HTLV-IId Efe2 pygmy strain from the other HTLV-II strains, which was calculated using the evolutionary rate at third cdp's for the general PTLV tree (see above). The timescale of PTLV evolution is summarized in figure 3
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As discussed above, all the dates estimated here are upper limits, since the date from which calculations were started (60,000 years ago) is also an upper limit, considering the possible difference between a gene tree and a population tree, with the separations in a gene tree generally preceding those in a population tree (Li 1997
).
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Discussion |
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Phylogenetic relationships among STLV-L, PTLV-I, and PTLV-II were already largely known, but some ambiguity still persisted on the root of the PTLV tree. We clearly demonstrated that the root of the PTLV tree lies on the branch leading to PTLV-I, with STLV-L and PTLV-II clustering together. The TN93 model with -distributed rates among sites appears to be the best-fitting model for our PTLV strain data set. As a consequence, we have to assume that during PTLV evolution, not only transitions and transversions, but also pyrimidine transitions and purine transitions occurred with different biases. Thus, we suggest the use of this model, implemented in several programs like PUZZLE, PAML, and MEGA, for future investigations of the phylogeny of primate T-lymphotropic viruses in coding regions.
The observation of nucleotide substitution rate heterogeneity across sites of the PTLV full-genome sequences was expected, since it is known that synonymous and nonsynonymous sites can evolve at different rates. However, a more detailed analysis of relative nucleotide substitution rates suggest that third cdp's change at more or less the same rate among different genes and about eight times as fast as rates at first cdp's. On the other hand, substitution rates at first and second cdp's show greater heterogeneity. Biologically, this can be explained by considering that different genes can have different selective pressures. In this regard, the gag gene appears to be the one with the strongest purifying selection, since it has the lowest substitution rate at the first and second cdp's, whereas the pro gene is the fastest-evolving one. A special case is presented by the overlapping tax/rex region. In this region, the first, second, and third cdp's of Tax and the first and third cdp's of Rex appear to change particularly slowly, whereas the second cdp of the 5' end of Rex changes faster than second cdp's of other genes. Since the Rex second cdp is also the Tax third cdp, it can be suggested that the higher neutral mutation rate of Tax speeds up the nonsynonymous mutation rate in Rex. At the 3' end of Tax, which does not overlap with another reading frame, first, second, and third cdp's have the usual low value. In spite of the presence of purifying selection across the PTLV-I and PTLV-II genomes, as attested to by KA/KS values significantly lower than 1 in each gene region, we detected a small fragment in the surface gp46 protein subjected to positive selection. The fragment does not correspond to any immunodominant epitope, and since the three-dimensional structure of the protein is not known, it is difficult to find a biological explanation. It might be an interesting goal in the future to look for links of the amino acid sequences in this region with immunological or structural properties of the surface protein. KA and KS values between PTLV-I and PTLV-II are not shown, since the observed saturation at third cdp's could lead to artifactual KS values when the deepest branches of the PTLV trees are compared.
The assumption of a constant evolutionary clock for HTLVs and STLVs always significantly decreases the likelihood of the tree when we consider the first and second cdp's. It is already known that evolutionary rates calculated for some mammalian genes are not constant (Wu and Li 1985
) and rates slow down in higher primates (Li and Tanimura 1987
). Interspecies transmissions among simians and between simians and humans challenge the same virus lineage with different hosts and different immune systems. This phenomenon most probably contributes to the changing molecular clocks of these viruses. On the other hand, when we exclude HTLV-II IDU strains, PTLVs evolve following a molecular clock at the third cdp's. The overall evolutionary rate of the PTLV genes at third cdp's was estimated to be not higher than 1.67 ± 0.17 x 10-6 nucleotide substitutions per site per year. The clock was calibrated employing the earliest human migration from Asia to Melanesia, 60,000 years ago, as the lower limit for the node separating HTLV-Ic from the other HTLV-I subtypes. We are aware of the fact that the divergence times in the PTLV gene tree could have preceded those of the population tree of the host species, implying that the evolutionary rate was overestimated. However, we believe that the real rate of PTLV evolution cannot be much slower than our estimate for two reasons. First, evolutionary rates of retroviruses usually range between 10-1 and 10-4 nucleotide substitutions per site per year due to their fast replication rates and their error-prone reverse transcriptases (Domingo and Holland 1994
). At present, there are no experimental data on the fidelity of HTLV reverse transcriptase, but comparison of structural models with HIV-1 reverse transcriptase does not suggest the presence of any particular feature, such as proofreading activity, in the HTLV enzyme that could be responsible for an exceptionally high fidelity (unpublished data). The PTLV evolutionary rate proposed in this paper is already 100 times slower than the rate of the slowest-evolving retrovirus known to date. It is unlikely for the real rate to be still 10100 times slower than 1.67 x 10-6, since we would then have to assume that PTLVs are evolving at a rate comparable with those of cellular genes. Second, in a previous paper published by our group (Liu et al. 1994
), HTLV-I sequences were isolated from seven family members infected by parental transmission. We sequenced 1,031 nt in the LTR and gp21 env regions. All sequences from each member but one, with a singlebase pair substitution in the LTR, were identical. An estimate of the evolutionary rate of the virus in this family gives
3.3 x 10-6 nucleotide substitutions per site per year (Van Dooren et al., personal communication). This is still an upper limit, but the fact that it is so close to the rate estimated in the present paper strengthens our confidence in the results. However, we are aware that a sightly lower evolutionary rate than our estimate is still possible, and thus dates given in figure 3
are reported as upper limits.
In any case, the PTLV evolutionary rate estimated here at third cdp's is much slower than the one calculated in the LTR region of HTLV-II strains infecting IDUs (Salemi et al. 1998a
), but it is of the same order as the one calculated for HTLV-II LTR in endemically infected populations (Salemi et al. 1999
). It could be suggested that the evolutionary rates of HTLVs depend on the way of transmission, which is different in different populations: mainly, mother-to-child transmission via breast feeding in endemically infected tribes or transmission via needle sharing among IDUs (Salemi et al. 2000). Indeed, in HTLV-I or HTLV-IIinfected individuals with high proviral loads, a large part of the provirus is produced by clonal expansion of infected cells and not by viral replication via reverse transcriptase (Wattel et al. 1995
; Cimarelli et al. 1996
). Because of the clonal expansion of the provirus, the reverse transcription step is less necessary for the virus to maintain its population in the host during its lifetime, while it might be considered necessary for the infection of a new host. Consequently, the possibility exists that the evolutionary rate of HTLVs is increasing with the transmission rate which is much higher in IDUs than in endemically infected tribes (Salemi et al. 1999
).
The lower limit for the PTLV time of origin was estimated to be about 1,300,000 years ago when starting from the PTLV-II part of the tree in figure 3
, or about 800,000 years ago when starting from the PTLV-I part of the tree. The fact that the two dates with overlapping confidence intervals roughly agree increases our confidence on these divergence time estimations. HTLV-II separated from STLV-II not much earlier than 400,000 years ago, which is much later than the separation between bonobos and humans, dated at least 5,000,000 years ago based on both paleontological and molecular biology data (Sarich and Wilson 1967
; Pilbeam 1984). Thus, human and simian lineages of the primate T-lymphotropic viruses did not separate following the speciation of their hosts, but probably arose from ancient interspecies transmissions. Very shortly after the origin of PTLV, the virus was present in Africa, since the African STLV-L and PTLV-II diverged from each other in Africa not much earlier than 1,000,000 years ago. The recent isolation of the divergent STLV-I marcI in an Asian Macaca arctoides suggests that the PTLV-I origin could be placed in Asia (Mahieux, Pecon-Slattery, and Gessain 1997
). Because the two lineages, starting from the root node of the PTLV tree, evolved on different continents, the place of the origin of the PTLV common ancestor remains open; it is either Asia or Africa. Assuming an Asian origin for PTLV, a simian migration from Asia to Africa after the PTLV origin has to be postulated in order to spread the virus on the second continent. No such migration has been reported to date. Assuming an African origin, a simian migration from Africa to Asia has to be postulated. As a consequence, the African origin of PTLV could be supported by the documented migration of macaques from Africa to Asia around 2,000,000 years ago (Fa 1989
) if we consider that the upper limit of the 95% confidence interval for the PTLV origin is 1,995,000 or 3,000,000 years ago, depending on which part of the tree in figure 3
is used for dating.
The separation between the Indonesian STLV-I and the other PTLV-I strains occurred much later than the STLV-II/HTLV-II one, not much earlier than 93,000 years ago (see fig. 3
). The earliest node in the PTLV tree leading to the African STLV-I and HTLV-I strains is dated 19,500 years ago, while the HTLV-I cosmopolitan subtype, which today is spread all over the world, arose just over 12,700 years ago. The presence of these viruses on the African continent should be seen as a later introduction due to simian and/or human movements during prehistoric times between 19,500 (the latest date for the radiation in Africa) and not much earlier than 60,000 (the earliest date for a common Asian ancestor) years ago. The migration from Indonesia to Madagascar around 1,200 years ago (Kent 1962
) came too late to explain the origin of HTLV-I infection on the African continent, as previously suggested (Saksena et al. 1992
). Moreover, several human-to-simian transmissions would then have to be assumed, which does not seem very likely. Thus, the date of the STLV-I introduction in Africa might correspond to an ancient movement of simians (possibly as pets of humans) "back to Africa," for which evidence could be investigated in the archaeological records.
Finally, it is interesting to note that according to our calculations, the separation between HTLV-IIa and HTLV-IIb occurred not much earlier than 22,000 years ago, with a confidence interval from 12,000 to 38,000 years ago. This range is consistent with the time frame proposed for the settling of the Americas through the Bering land bridge migrations 15,000 to 35,000 years ago (Greenberg, Turner, and Zegura 1986
; Cavalli-Sforza, Menozzi, and Piazza 1994
). Thus, our data might support the suggestion of several investigators, based on epidemiological data, that HTLV-II among Amerindian tribes was originally brought from Asia into the Americas along with the migration of the HTLV-IIinfected Asian populations over the Bering land bridge (Neel, Biggar, and Suzernik 1994
; Biggar et al. 1996
; Suzuki and Gojobori 1998
).
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Acknowledgements |
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Footnotes |
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1 Abbreviations: BLV, bovine leukemia virus; cdp, codon position; Fitch, Fitch and Margoliash method; HTLV, human T-cell lymphotropic virus; IDUs, injecting drug users; ML, maximum likelihood; NJ, neighbor joining; Protpars, parsimony method for proteins; PTLV, primate T-cell lymphotropic virus; STLV, simian T-cell lymphotropic virus; TN93, Tamura and Nei model assuming discrete -distributed rates across sites; wpars, weighted parsimony method.
2 Keywords: HTLV-I
HTLV-II
STLV-I
STLV-II
molecular clock
evolutionary models
3 Address for correspondence and reprints: M. Salemi, Rega Institute for Medical Research, Minderbroedersstraat 10, B-3000 Leuven, Belgium. E-mail: marco.salemi{at}uz.kuleuven.ac.be
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