Analysis of the origin and evolutionary history of HIV-1 CRF28_BF and CRF29_BF reveals a decreasing prevalence in the AIDS epidemic of Brazil.

Abstract

HIV-1 subtype B and subtype F are prevalent in the AIDS epidemic of Brazil. Recombinations between these subtypes have generated at least four BF circulating recombinant forms (CRFs). CRF28_BF and CRF29_BF are among the first two BF recombinants being identified in Brazil and they contributed significantly to the epidemic. However, the evolution and demographic histories of the CRFs are unclear.
A collection of gag and pol sequences sampled within Brazil was screened for CRF28_BF-like and CRF29_BF-like recombination patterns. A Bayesian coalescent framework was employed to delineate the phylogenetic, divergence time and population dynamics of the virus having CRF28_BF-like and CRF29_BF-like genotype. These recombinants were phylogenetically related to each other and formed a well-supported monophyletic clade dated to 1988-1989. The effective number of infections by these recombinants grew exponentially over a five-year period after their emergence, but then decreased toward the present following a logistic model of population growth. The demographic pattern of both recombinants closely resembles those previously reported for CRF31_BC.
We revealed that HIV-1 recombinants of the CRF28_BF/CRF29_BF clade are still circulating in the Brazilian population. These recombinants did not exhibit a strong founder effect and showed a decreasing prevalence in the AIDS epidemic of Brazil. Our data suggested that multiple URFs may also play a role in shaping the epidemic of recombinant BF HIV-1 in the region.

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Analysis of the Origin and Evolutionary History of HIV-1
CRF28_BF and CRF29_BF Reveals a Decreasing
Prevalence in the AIDS Epidemic of Brazil
Natalia Ristic1, Jean Zukurov2, Wagner Alkmim3, Ricardo Sobhie Diaz2, Luiz Mario Janini3, Mario P. S.
Chin1*
1Aaron Diamond AIDS Research Center, The Rockefeller University, New York, New York, United States of America, 2Department of Medicine, Federal University of Sao
Paulo, Sao Paulo, Brazil, 3Department of Microbiology, Immunology, and Parasitology, Federal University of Sao Paulo, Sao Paulo, Brazil
Abstract
Background: HIV-1 subtype B and subtype F are prevalent in the AIDS epidemic of Brazil. Recombinations between these
subtypes have generated at least four BF circulating recombinant forms (CRFs). CRF28_BF and CRF29_BF are among the first
two BF recombinants being identified in Brazil and they contributed significantly to the epidemic. However, the evolution
and demographic histories of the CRFs are unclear.
Methodology/Principal Findings: A collection of gag and pol sequences sampled within Brazil was screened for CRF28_BF-
like and CRF29_BF-like recombination patterns. A Bayesian coalescent framework was employed to delineate the
phylogenetic, divergence time and population dynamics of the virus having CRF28_BF-like and CRF29_BF-like genotype.
These recombinants were phylogenetically related to each other and formed a well-supported monophyletic clade dated to
1988–1989. The effective number of infections by these recombinants grew exponentially over a five-year period after their
emergence, but then decreased toward the present following a logistic model of population growth. The demographic
pattern of both recombinants closely resembles those previously reported for CRF31_BC.
Conclusions: We revealed that HIV-1 recombinants of the CRF28_BF/CRF29_BF clade are still circulating in the Brazilian
population. These recombinants did not exhibit a strong founder effect and showed a decreasing prevalence in the AIDS
epidemic of Brazil. Our data suggested that multiple URFs may also play a role in shaping the epidemic of recombinant BF
HIV-1 in the region.
Citation: Ristic N, Zukurov J, Alkmim W, Diaz RS, Janini LM, et al. (2011) Analysis of the Origin and Evolutionary History of HIV-1 CRF28_BF and CRF29_BF Reveals
a Decreasing Prevalence in the AIDS Epidemic of Brazil. PLoS ONE 6(3): e17485. doi:10.1371/journal.pone.0017485
Editor: Jean-Pierre Vartanian, Institut Pasteur, France
Received August 19, 2010; Accepted February 5, 2011; Published March 1, 2011
Copyright: ? 2011 Ristic et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by internal funds of Aaron Diamond AIDS Research Center and National Institutes of Health grant DA026293. The funders had
no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: mchin@adarc.org
Introduction
HIV-1 is classified into Group M, O, N and P. Group M HIV-1
dominates the AIDS pandemic with at least nine subtypes and
multiple intersubtype recombinants currently identified [1]. The
intersubtype recombinants are the result of recombination among
the subtypes of HIV-1. Furthermore, these intersubtype recom-
binants can also recombine with HIV-1 of the same or different
subtypes or with other recombinants to generate more complex
recombinants. They emerge in almost every region of the world
where more than one HIV-1 subtype is present. Currently, 48
circulating recombinant forms (CRFs) and a large number of
unique recombinant forms (URFs) have been identified. These
CRFs and URFs accounted for almost 18% of new infections in
2004 [2] and they continue to play an increasingly important role
in shaping the AIDS pandemic.
It is reported that there are more than 545,000 AIDS cases in
Brazil[3].Theepidemicisparticularlysevereinthesoutheasternpart
of the country, where large urban centers such as Rio de Janeiro and
Sao Paulo are situated. At the end of 2008, the southeastern states
(Espirito Santo, Minas Gerais, Rio de Janeiro and Sao Paulo)
reported at least 323,000 diagnosed AIDS cases (59.3% of all cases in
the country) with approximately 19.2 AIDS cases per 100,000 people
[3]. The epidemic in the southeastern region of the country is
complicated by multiple subtypes and recombinants of HIV-1
circulatinginthepopulation.ForinstanceinthecityofSaoPaulo,the
major subtypes are subtype B (79%–88%) and subtype F (4%–11%)
[4,5]. Such a dense transmission network, with a high HIV-1
incidence rate and multiple subtypes present in the region, provides a
perfect breeding ground for new HIV-1 recombinants. Indeed, HIV-
1 recombinants between subtype B and subtype F have been
frequently identified since the introduction of subtype F in Brazil
[6,7,8,9,10,11,12]. Studies have shown that up to 9% of the HIV-1
isolated in Sao Paulo have a mosaic B/F pol genome [4,5]; in
particular, the CRF28_BF and CRF29_BF recombinants were
identified in the region in 1999 [13,14].
CRF28_BF and CRF29_BF were identified in patients at the
Counseling and Testing Centers in Santos, which is a port city
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located 80 km from the city of Sao Paulo [14]. CRF29_BF
were also identified in patients from Sao Paulo and Rio de
Janeiro [6,13]. These CRFs are genetically distinct from
CRF12_BF, which was first detected and subsequently found
to be widely circulating in Argentina [15,16,17]. The majority
of the CRF28_BF and CRF29_BF genome belongs to subtype
B and is closely related to the subtype B HIV-1 circulating in
Brazil (Figure 1A) [14]. The subtype F regions are phyloge-
netically linked to the Brazilian subtype F1. CRF29_BF and
CRF28_BF share similar recombination breakpoints in the gag
and pol genes at nucleotide (nt) positions 1,322 and 2,571
(HXB2 numbering). CRF29_BF has an additional subtype F
region spanning from nt 3,682 to 5,462, creating additional
breakpoints in the pol and vif genes. Owing to the common
recombination breakpoints that the recombinants share, it is
possible that a common ancestor of the BF recombinants
emerged early in the epidemic and has evolved through
subsequent recombination events.
Figure 1. Mapping the recombination breakpoints of CRF. (A) Recombination patterns of the CRF28_BF and CRF29_BF genomes. The number
at each recombination breakpoint indicates the nucleotide position according to HXB2 numbering. Blue, subtype B; Green, subtype F1. Black bars
above the HIV-1 genome indicate the gag (1,087–1,560) and pol (2,265–3,904) regions analyzed in this study and in the subsequent bootscanning
analyses. (B) The bootscanning of CRF28_BF, CRF29_BF and CRF28/29_BF-like recombinant genomes revealed a similar recombination breakpoint.
The recombinant sequences identified in RIP were subjected to bootscanning, and representative results are shown. The query sequence was
compared with subtype B, F1 and K consensuses obtained from RIP, and plots of percentages of permuted trees against nucleotide positions are
shown. Red, subtype B; green, subtype F1, grey, subtype K. A window/step size of 200/10 was used to analyze the sequences.
doi:10.1371/journal.pone.0017485.g001
Phylodynamics of CRF28_BF and CRF29_BF
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Although several studies have been carried out to characterize
the epidemiology and phylogenetics of subtype B and subtype F
HIV-1, and BF URFs in Brazil [4,5,6,7,8,9,10,11,13,18], little is
known about the evolutionary and demographic histories, and the
epidemic potential of the CRF28_BF and CRF29_BF. Here, we
reconstructed the evolutionary history of the CRF28_BF and
CRF29_BF by coalescent inference to delineate their origins and
population dynamics. Our data showed that since the emergence
of the CRF28_BF and CRF29_BF in the late 1980s, both CRFs
underwent rapid population growth; however, the growth rate has
slowed in recent years. Both CRFs did not exhibit a strong founder
effect, which suggested that multiple URFs may also play a role in
shaping the recombinant BF HIV-1 epidemic in the region. Our
study provides important insights into the contributions of HIV-1
recombinants to the AIDS epidemic in South America.
Methods
Study population and data preparation
Two regions of the HIV-1 genome encompassing the
recombination breakpoints in pol (nt position 2,572) and gag (nt
position 1,323) of CRF28_BF and CRF29_BF were analyzed
(Figure 1A) [13,14]. For the pol region, we studied a set of 111
HIV-1 sequences obtained from patients attending HIV/AIDS
treatment centers in Sao Paulo [13]. An 830-bp-long pol region
covering part of the protease and reverse transcriptase genes (nt
positions 2,265–3,094) was sequenced as previously described [13].
Sequences were analyzed together with 433 subtype B, 61
recombinant BF, three CRF28_BF and four CRF29_BF sequenc-
es isolated in Brazil with known sampling dates retrieved from the
Los Alamos HIV Sequence Database. This resulted in a dataset
consisting of 612 pol sequences collected between 1989 and 2007.
Similarly, we obtained 184 HIV-1 gag sequences isolated in Brazil
with known sampling dates from the Los Alamos HIV Sequence
Database, covering parts of the matrix and capsid genes (nt
positions 1,087–1,560). This dataset consisted of 127 subtype B, 50
recombinant BF, three CRF28_BF and four CRF29_BF sequenc-
es collected between 1989 and 2006. The nucleotide sequences
were aligned using Clustal X [19], and alignment gaps were
excluded from the analyses.
Identification of the CRF28/29_BF-like HIV-1
The workflow for identifying recombination in HIV-1 was
described previously [20]. The sequences in the pol and gag
datasets were first analyzed using the Recombination Identifica-
tion Program (RIP) 3.0 of the Los Alamos HIV Sequence
Database to identify subtype B and CRF28/29_BF-like sequenc-
es. In the analysis, each individual query sequence was compared
with subtype B and subtype F1 consensuses using a window size
of 200 bp. Any query sequence that had a value of 0.9 or higher
in the s-distance with the subtype B consensus, free of
recombination breakpoints, was classified as subtype B. The
sequences having a recombination pattern identical to those of
CRF28_BF and CRF29_BF were regarded as CRF28/29_BF-
like. The recombinant sequences were compared with the
subtype B, subtype F1 and subtype K consensus sequences
obtained from RIP in a bootscanning analysis using SimPlot to
confirm their genetic identity [21]. Based on the analyses, we
then compiled a refined dataset consisting of pol sequences of a
selection of subtype B and all of the identified CRF28/29_BF-
like, three CRF28_BF and four CRF29_BF sequences with a
compromise between wide sampling date and a realistic size of
the dataset. A refined dataset with the gag sequence was also
constructed using the same approach.
Bayesian evolutionary analysis by sampling phylogenetic
trees of subtype B and CRF28/29_BF-like HIV-1
We performed phylogenetic analysis on the two refined datasets
of pol and gag sequences using a Bayesian approach with the
SRD06 nucleotide substitution model [22]. The purpose of this
phylogenetic analysis was to identify the overall topology and
confirm the relationship between the subtype B and the CRF28/
29_BF-like HIV-1. A Bayesian Markov Chain Monte Carlo
(MCMC) analysis, as implemented in the program BEAST v1.5.4
[23], was carried out for 10 million generations to produce 10,000
trees for each dataset. The maximum clade credibility phyloge-
netic tree was determined in TreeAnnotator v1.5.4 after excluding
an initial 10% of the sample.
Estimation of nucleotide substitution rate, demographic
history and time of divergence
We used an MCMC method, as implemented in the program
BEAST v1.5.4 [23], to estimate the rate of nucleotide substitution.
The refined pol and gag datasets were analyzed with the codon-
based SRD06 nucleotide substitution model [22]. Three clock
models were used in the analyses: the strict clock model assumes a
single evolutionary rate for all the lineages; and the uncorrelated
exponential relaxed clock and the uncorrelated lognormal relaxed
clock allow evolutionary rates to vary among lineages within
exponential and lognormal distributions, respectively [24]. These
three clock models were statistically compared for each dataset
using a Bayes Factor test to find the best fit [25]. We used the best
fit clock model to estimate a posterior distribution for the rate of
nucleotide substitution and then used as an empirical prior
distribution in the coalescent analyses that follow.
The CRF28/29_BF-like sequences were analyzed using a
nonparametric model (Bayesian skyline plot) to estimate the
change in the effective population size through time and to infer
demographic information within the lineage [26]. Four demo-
graphic models were compared to select the model that best
described the epidemiological history of the CRF28/29_BF-like
HIV-1. The models tested in this study were as follows: constant
population size, exponential growth, logistic growth and expansion
growth [27]. The Bayes Factor test was used to evaluate the
demographic models for each dataset [25]. We performed three
independent Bayesian MCMC runs for 10 million generations to
produce 10,000 trees for each analysis. The convergence of
parameters was assessed through the effective sampling size, with
all parameters for each run having values .100 indicating a
sufficient level of sampling. The mean time to the most recent
common ancestor (TMRCA) and the maximum clade credibility
of the phylogenetic trees were then calculated after the removal of
10% of the samples following visual inspection in the programs
Tracer v1.5 and FigTree v1.3.1.
Recombination between CRF28/29_BF-like recombinants and
the recombination breakpoints in the gag and pol sequences may
cause biases in the estimation of nucleotide substitution rate and
TMRCA [28,29]. To test the possible effects of recombination on
the current analysis, we employed an unlinked multilocus model in
BEAST, which allows independent coalescent pathways for
different gene loci [30]. In this model, the linked recombinant pol
gene was divided into two unlinked loci of subtype F (nt positions
2,265–2,572) and subtype B (nt positions 2,573–3,094) sequences.
The nucleotide substitution rates, demographic histories and times
of divergence of the two unlinked loci were estimated in the
Bayesian coalescent framework. Similar approach was applied to
the subtype B loci (nt positions 1,087–1,323) and subtype F loci (nt
positions 1,324–1,560) of the recombinant gag gene.
Phylodynamics of CRF28_BF and CRF29_BF
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Results
Identification of CRF28/29_BF-like recombination
breakpoints in HIV-1
We analyzed the 612 sequences of the pol dataset using RIP to
identify recombination breakpoints similar to those of CRF28_BF
and CRF29_BF. Of the 433 subtype B pol sequences in the dataset,
we found four sequences retrieved from the HIV Sequence
Database that had recombination breakpoints similar to those of
CRF28/29_BF (Figure 1B). The accession numbers of these four
sequences are AF112891, AF112898, AF112953 and AY213549.
In addition, we identified CRF28/29_BF-like recombination
breakpoints in the pol gene of two sequences from the 111 patient
samples sequenced in this study. Among the 61 recombinant BF
sequences from the HIV Sequence Database, 21 of them possessed
CRF28/29_BF-like recombination breakpoints. Based on the
recombination breakpoint analysis, we compiled a refined pol
dataset with 102 sequences consisting of 66 Brazilian subtype B, 27
CRF28/29_BF-like, 3 CRF28_BF and 4 CRF29_BF sequences
sampled between 1989 and 2007.
The 184 sequences of the gag dataset were analyzed using a
similar approach. We found that there were three sequences
(U86560, AY071973 and AY071985) in the 127 subtype B
sequences that had CRF28/29_BF-like recombination break-
points (Figure 1B). We also identified 32 CRF28/29_BF-like
recombinant sequences from the 50 BF recombinant sequences.
We then compiled a refined dataset of 90 gag sequences
containing 48 Brazilian subtype B, 35 CRF28/29_BF-like, three
CRF28_BF and four CRF29_BF sequences sampled between
1989 and 2006.
Bayesian phylogeny of Brazilian subtype B and CRF28/
29_BF-like HIV-1
A total of 102 pol sequences, consisting of 66 subtype B and 27
CRF28/29_BF-like HIV-1, were aligned with the reference
sequences of CRF28_BF and CRF29_BF. A Bayesian analysis
was used to infer the phylogenetic relationships of the isolates. The
resulting tree showed that the CRF28/29_BF-like sequences form
a well-supported monophyletic group (posterior probability=1)
distinct from the subtype B sequences (Figure 2). All of the
sequences in the CRF28/29_BF-like lineage have recombination
breakpoints similar to those of CRF28_BF and CRF29_BF
(Figure 1B). Remarkably, the CRF28_BF and the CRF29_BF
references did not form a distinct group, and both references were
scattered in different branches of the CRF28/29_BF-like lineage,
suggesting that the two strains share a common ancestry.
The Bayesian analysis of the refined dataset of gag sequences,
which consisted of 48 subtype B, 35 CRF28/29_BF-like, three
CRF28_BF and four CRF29_BF sequences, revealed a similar
topology to the pol phylogenetic tree (Figure 2). The CRF28/
29_BF-like sequences formed a distinct lineage with high support,
and all of the sequences within had a similar recombination profile
as the reference CRF28_BF and CRF29_BF (Figure 1B). The
phylogenies inferred from the gag and pol datasets indicated that
CRF28_BF and CRF29_BF are closely related and have co-
evolved since their emergence.
Figure 2. Bayesian evolutionary analysis by sampling phylogenetic trees of Brazilian subtype B and CRF28/29_BF-like HIV-1. The
maximum clade credibility phylogenetic trees of the pol and gag genes are shown. The brackets indicate the monophyletic group formed by each
lineage. The subtype B lineage is in black, and the CRF28/29_BF-like lineage is in red. Positions of the CRF28_BF and CRF29_BF references are
indicated. Posterior probability values greater than 0.8 are shown at nodes.
doi:10.1371/journal.pone.0017485.g002
Phylodynamics of CRF28_BF and CRF29_BF
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Estimation of the evolution rate of the Brazilian CRF28/
29_BF-like HIV-1
Bayesian MCMC analyses under a skyline tree prior were used
to estimate the rate of evolution of the Brazilian CRF28/29_BF-
like HIV-1. We first evaluated the marginal likelihood of the three
clock models employed in this study to determine the best clock
model for estimating the evolution rate of the pol gene. Analysis of
the Bayes Factor showed that the model using a lognormal relaxed
clock fit the dataset better than the models assuming an
exponential relaxed clock or a strict clock (Table S1). Under the
lognormal relaxed clock model, the estimated mean rate of
evolution of the pol gene was 2.6061023substitutions per
nucleotide site per year (Table 1).
Similarly, we determined the best clock model for estimating the
evolution rate of the gag gene. The Bayes Factor test of the clock
model showed that the lognormal relaxed clock most appropriately
described the data, indicating that the substitution rate varies
among branches (Table S1). The evolution rate assuming a
lognormal relaxed clock was 1.9461023
nucleotide site per year (Table 1). In comparison, previous
estimates of the evolution rate of HIV-1 pol have ranged from
1.561023to 2.661023substitutions per nucleotide site per year
[31,32,33,34]. Our estimate is consistent with the order of
magnitude of 1023expected for the HIV-1 pol gene.
To evaluate the possible effect of the recombination breakpoints
in the pol and gag genes on the estimation of nucleotide substitution
rate, we applied a multilocus model that assumes different
genealogies for each of the unlinked subtype B and subtype F
loci [30]. Bayesian MCMC analyses revealed that the estimated
substitute rate for the unlinked loci were not significantly different
from those of the linked loci. The rates of the unlinked pol loci
ranged from 2.5561023to 2.6961023substitutions per nucleotide
site per year and those of the unlinked gag loci were 1.9561023
and 2.0261023substitutions per nucleotide site per year. Thus the
presence of recombination breakpoint in the dataset does not have
a significant effect on the evolution rate estimations. Based on the
above investigation, the rates of nucleotide substitution for the pol
(2.6061023) and gag (1.9461023) genes were used as empirical
prior distributions in the subsequent coalescent analyses.
substitutions per
Demographic history and epidemic parameter of the
Brazilian CRF28/29_BF-like HIV-1
The nonparametric Bayesian skyline method with a lognor-
mal relaxed clock model was used to simultaneously estimate
the demographic history and TMRCA of the CRF28/29_BF-
like strains. The empirical prior of 2.6061023substitutions per
nucleotide site per year was used to analyze the pol gene. The
Bayesian skyline plot of the epidemic history of the CRF28/
29_BF-like strains, with appropriate confidence intervals, is
shown in Figure 3. The change in the effective number of
infections over time appears to follow the model of logistic
population growth. A similar observation was inferred from the
nonparametric reconstruction of the epidemic history of the
CRF28/29_BF-like strains using the gag gene and an empirical
prior of 1.9461023substitutions per nucleotide site per year
(Figure 3). We used a Bayes Factor test to determine the
likelihoods of the various population growth models. Among
the four models tested, the logistic growth model best fit the
demographic information contained in both tree topologies
thus confirming the epidemic history of the CRF28/29_BF-like
strains is best described by the logistic growth model (Table
S2).
The evolutionary and demographic parameters associated with
the CRF28/29_BF epidemic are shown in Table 1. Our
estimates suggest that the CRF28/29_BF lineage originated in
the late 1980s. The TMRCA of the CRF28/29_BF-like HIV-1
determined from the pol genes was 1989 and that determined
from the gag genes was 1988. Soon after the emergence of the
CRF28/29_BF-like HIV-1, the recombinant virus grew at an
exponential rate (Figure 3). The estimated growth rate inferred
from the pol gene was 1.18 per year, with an epidemic doubling
time of seven months. The number of effective infections in 2007
was 2,537. Similar parameters were estimated from the gag gene
of the CRF28/29_BF-like strains. The inferred growth rate was
1.20 per year, which corresponds to a doubling time of
approximately seven months. The number of effective infections
in 2006 was 1,778. We then applied the aforementioned
nonparametric Bayesian skyline method to the unlinked loci of
pol and gag genes to rule out the possibility that recombination
breakpoint may have an effect on estimating the evolutionary and
demographic parameters. The resulting estimates for the
TMRCA and demographic parameters are listed in Table 1.
The TMRCA, growth rate and doubling time estimates are
highly consistent among the different linked and unlinked loci of
the pol or gag gene. This confirms previous studies [30,35]
showing that quantitative effect of recombination on evolutionary
analyses of HIV-1 may be less severe than initially proposed
[28,29].
Table 1. Population dynamics estimates for the CRF28/29_BF epidemic.a
Gene
m, site21year21
Origin of the
lineage
Number of effective
infections
r, year21
l, month
pol
Linked locus [nt 2265–3094]2.6061023(1.7261023–3.4661023) 1989 (1987–1993)2537 (405–15320)1.18 (0.64–1.38) 7.05 (6.00–12.96)
Unlinked F locus [nt 2265–2572]2.6961023(1.7861023–3.5461023)1991 (1988–1994)3176 (651–18028) 1.25 (0.78–1.55) 6.68 (5.37–10.66)
Unlinked B locus [nt 2573–3094] 2.5561023(1.9161023–3.3361023)1989 (1986–1992)2415 (367–13994)1.13 (0.61–1.26) 7.36 (6.65–13.64)
gag
Linked locus [nt 1087–1560]1.9461023(0.9161023–3.0661023) 1988 (1984–1992)1778 (191–10212) 1.20 (0.59–1.47)6.93 (5.66–14.10)
Unlinked B locus [nt 1087–1323]2.0261023(0.8261023–3.2461023) 1989 (1986–1994)2092 (322–12273)1.27 (0.67–1.61) 6.55 (5.17–12.42)
Unlinked F locus [nt 1324–1560]1.9561023(0.8561023–3.1761023) 1988 (1983–1991)1619 (152–9867) 1.15 (0.55–1.42)7.24 (5.86–15.12)
aNumbers in parentheses are the range of the 95% upper and lower high posterior density. m, rate of nucleotide substitution; r, median rate of exponential growth; l,
epidemic doubling time.
doi:10.1371/journal.pone.0017485.t001
Phylodynamics of CRF28_BF and CRF29_BF
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