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Journal of Virology, July 1999, p. 5787-5794, Vol. 73, No. 7
0022-538X/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Structural Constraints on RNA Virus
Evolution
P.
Simmonds* and
D. B.
Smith
Department of Medical Microbiology,
University of Edinburgh, Edinburgh EH8 9AG, United Kingdom
Received 8 February 1999/Accepted 8 April 1999
 |
ABSTRACT |
The recently discovered hepatitis G virus (HGV) or GB virus C
(GBV-C) is widely distributed in human populations, and homologues such
as HGV/GBV-CCPZ and GBV-A are found in a variety of
different primate species. Both epidemiological and phylogenetic
analyses support the hypothesis that GB viruses coevolved with their
primate hosts, although their degree of sequence similarity appears
incompatible with the high rate of sequence change of HGV/GBV-C over
short observation periods. Comparison of complete coding sequences
(8,500 bases) of different genotypes of HGV/GBV-C showed an excess of invariant synonymous sites (at 23% of all codons) compared with the
frequency expected by chance (10%). To investigate the hypothesis that
RNA secondary-structure formation through internal base pairing limited
sequence variability at these sites, an algorithm was developed to
detect covariant sites among HGV/GBV-C sequences of different
genotypes. At least 35 covariant sites that were spatially associated
with potential stem-loop structures were detected, whose positions
correlated with positions in the genome that showed reductions in
synonymous variability. Although the functional roles of the predicted
secondary structures remain unclear, the restriction of sequence change
imposed by secondary-structure formation provides a mechanism for
differences in net rate of accumulation of nucleotide substitutions at
different sites. However, the resulting disparity between short- and
long-term rates of sequence change of HGV/GBV-C violates the
assumptions of the "molecular clock." This places a major
restriction on the use of nucleotide or amino acid sequence comparisons
to calculate times of divergence of other viruses evolving under the
same structural constraints as GB viruses.
 |
INTRODUCTION |
Although the flavivirus hepatitis G
virus (HGV) or GB virus C (GBV-C) is newly discovered (17,
19), several observations suggest that it may have always
infected humans and originated through coevolution with its primate
hosts. First, it is widely distributed in human populations, with
frequencies of active or past infection ranging from 5 to 15%, and its
distribution extends even to highly isolated populations, such as
indigenous tribes in Papua New Guinea and Central and South America.
Second, although infection is frequently persistent and associated with
high levels of circulating viremia, no evidence links HGV/GBV-C to any
identifiable hepatic or nonhepatic disease, consistent with a process
of mutual adaptation. Third, the geographical distribution of HGV/GBV-C variants reflects that of ancient human migrations (14). For example, sequences from the Far East are almost invariably genotype 3, and this genotype is otherwise found only in native inhabitants of
North and South America. In contrast, Caucasian and other populations from India westward including Northern Africa are infected with genotype 2. Genotype 1 is confined to sub-Saharan Africa and shows the
greatest overall sequence diversity (22, 25); particularly divergent variants have been recovered from Pygmy and other
African populations (27a, 28). These genotype distributions
can potentially be mapped to the emergence and migration of modern
humans out of Africa 100,000 years ago (7, 28).
Finally, viruses closely related to HGV/GBV-C have been found in
a variety of Old World and New World primate species,
and their phylogenetic relationships mirror those of their hosts. HGV/GBV-C variants in wild-caught chimpanzees from Central and West
Africa show around 27% nucleotide (15% amino acid) sequence divergence from HGV/GBV-C (1, 3). Distinct variants of
HGV/GBV-CCPZ, recovered from different subspecies of
chimpanzees, differed at 19% of nucleotide sites (9.5% of amino acid
sites) in NS5, a level of diversity greater than that found between the
most divergent genotypes of HGV/GBV-C in humans (11% nucleotide and
3.3% amino acid divergence) and consistent with their likely greater
population age. Even more divergent homologues of
HGV/GBV-C, described as GBV-A, have been recovered from
several species of New World primates, with 42% nucleotide (38%
amino acid) sequence divergence in the NS5 region from homologous
sequences of HGV/GBV-C from humans and chimpanzees (4,
16). Again mirroring host relationships, genetic
variants of GBV-A differing from each other by around 25% are closely associated with different new world primate
species (4, 5, 16). Observations of congruent
sequence relationships between GB viruses and their primate host
species are consistent with their coevolution.
However, this hypothesis is difficult to reconcile with the high
short-term rate of sequence change of HGV/GBV-C, estimated at 3.9 × 10
4 site/year over the whole genome (23), a
rate comparable to that of other RNA viruses (e.g., 4 × 10
4 in hepatitis C virus NS5 [26]). This
rate appears incompatible with the lack of sequence diversity between
HGV/GBV-C isolates in human populations, if the current distribution of
genotypes derives from the migration of modern humans out of Africa.
The rate of sequence change is also inconsistent with sequence
relationships between human GB viruses and those found in other primate
species. However, if GB viruses did not coevolve with their hosts,
their current distribution can have originated only through multiple cross-racial and cross-species transmissions over the last few hundred
years. This latter hypothesis does not accord with the geographical
distribution of HGV/GBV-C genotypes in humans or with the congruent
virus and host phylogenies. This explanation is also inconsistent
with the recently described species barriers (GBV-A cannot be
transmitted to chimpanzees, and HGV/GBV-C cannot be transmitted to New
World primates [4a]).
A more radical explanation of the current data is that there are major
differences between GB viruses and higher organisms in the constraints
operating on sequence change. For vertebrates and other eukaryotes,
there is a close concordance between fossil-based estimates of the
times of species separation and the extent of divergence of nucleotide
and amino acid sequences in a wide variety of nuclear genes
(15). In contrast, restrictions on variability at certain
sites in the HGV/GBV-C genome may prevent the accumulation of
substitutions that limit the extent to which HGV/GBV-C can diversify
over time. In the present study, we have compared sequences of
different genotypes of HGV/GBV-C to identify such restrictions and to
investigate whether these can be explained by mechanisms such as RNA
secondary-structure formation.
 |
MATERIALS AND METHODS |
Nucleotide sequences.
Currently available complete genomic
sequences of HGV/GBV-C sequences of genotypes 1 to 3 (GenBank/EMBL
accession numbers in parentheses) include the type 1 sequence, GBV-C
(U36380); the type 2a sequences PNF2161 (U44402), R10291 (U45966), HGV-Iw (D87255), HGV-1539 (AF031829), GT110 (D90600), and CG01BD
(AB003289); the type 2b sequence GBV-C(EA) (U63715); the type 3 sequences GT230 (D90601), CG07BD (AB003290), HGV-IM71 (AB008342), GSI85
(D87262), G13HC (AB003293), HCV-GD (AF006500), HGVCN (U94695), BG1HC
(AB003288), HGVC-964 (U75356), and D87708 to D87715 (13);
and sequences of unclassified genotype, i.e., CG12LC (AB003291) and
G05BD (AB003292). Sequences were numbered from the start of the coding region after alignment. HGV/GBV-C homologues in primate sequences were
from chimpanzees (AF068910 to AF068913 [3]) and the
New World primate species Sanguinis mystax, S. labiatus, and Aotus trivirgatus (U94421, AF023424, and
AF023425).
Coding sequences of serum albumin were obtained from the following
mammalian species (GenBank accession numbers in parentheses): cow
(Y17769), sheep (X17055), cat (X84842), gerbil (AB006197), horse
(X74045), human (V00494), macaque (M90463), rabbit (U18344), and
rat (V01222). Alpha globin sequences compared included gibbon
(M94634), human (V00493), rhesus (J04495), baboon (X05289), lemur
(M29648), horse (M17902), rabbit (J00658), seal (M73996),
mouse (L75940), rat (M17083), hamster (X57029), and sheep (X70213).
Generation of simulated sequence data sets.
The expected
stochastic frequencies of invariant and variable codons and of
covariant substitutions were determined by using control sequence data
sets containing the same number of sequences generated in the following ways.
(i) Control set A.
Nucleotide changes were introduced at
random positions into a representative HGV/GBV-C sequence (R10291) for
the 17 representative sequences of types 1 to 3, and GT320 as a control
for type 3 sequences) at a prespecified frequency (nucleotide
divergence × length of sequence). The introduced substitutions
reproduced the relative frequency of synonymous and nonsynonymous
substitutions (30:1), the relative frequency of transitions and
transversions (2:1), and the base composition at synonymous sites
(12.9% A, 31.7% C, 35.8% G, and 19.9% U) observed upon comparison
of 17 representative HGV/GBV-C sequences. Retention of the observed
transition/transversion ratio was essential because two of the four
transitions preserve base pairing through the possibility of G-U base
pairs, whereas all transversions disrupt base pairing. All distances
(Jukes-Cantor [J-C], synonymous [dS] and
nonsynonymous [dN], transitions
[Ts], transversions
[Tv]) and base composition at synonymous sites
in the simulated data set were within 10% of the values of the data set to be emulated. Control set A was used to determine whether there
was an excess frequency of invariant synonymous positions and of
potential covariant sites among HGV/GBV-C sequences.
(ii) Control set B.
The nucleotide identity of all bases in
the representative and type 3 data sets was changed
(G
C
U
A
G). The resulting sequences retain the phylogenetic
relationships of the original sequences and the distribution of
variability across the genome and within codons, but all base pairings
(G-C, A-U, and G-U) contributing to secondary structure were disrupted.
However this control could not be used to explore the expected
frequency of covariant sites since the G+C content of synonymous sites
was reduced from 67 to 52%, resulting in a reduction from 40.0 to
33.7% in the number of potential base pairings in the shifted data set
that occur by chance.
(iii) Control set C.
Each codon within the virus data sets
was randomly assigned to a new position. Control set C retains the
phylogenetic relationships between sequences and does not alter
dN, dS,
Ts, or Tv distances or
the number of covariant sites. The data set was used to evaluate the
stochastic association between covariant sites and surrounding stem-loop base pairing. Since this control data set disrupts potential base pairings, it allowed an evaluation of the association
between covariant sites and the size and position of potential
stem-loops.
(iv) Control set D.
The order of nucleotides in
representative sequences was randomized to determine the contribution
of sequence order to the free energy on folding in the program RNADraw,
v. 1.0 (provided by O. Matzura).
Measurement of codon variability.
Aligned data sets of
nucleotide sequences were compared codon by codon. At each site, only
sequences coding for the most frequent amino acid were analyzed for
synonymous variability. At each site, the mean number of synonymous
differences between codons was calculated and normalized by correcting
for multiple substitution so that sites at equilibrium would have a
mean divergence of 1.0. For two-, three-, four-, and
sixfold-degenerate sites, the mean distances were
therefore corrected by factors of 2, 1.5, 1.333, and 1.2, respectively.
Variability across the genome was calculated by using the mean
diversity of sites in a sliding window of 50 codon positions. Control
data set A was used to estimate the frequency of invariant
synonymous sites arising by chance.
Detection of covariance.
Each base position in sequence
alignments of HGV/GBV-C was screened for covariance by comparison with
each downstream base. Sequences were scanned for downstream potential
base pairings to each variable nucleotide position in the alignment, in
which nucleotide substitutions in one sequence were matched and
contributed to base pairing with the complementary site. G · U
pairing were scored as 0.8 of Watson-Crick pairing, and the
identification of a match required a mean score of 0.84 per sequence.
After identification of complementary covariant sites, the maximum
number of base pairings between nucleotides surrounding the site was
scored using a sliding window of 7 bases from positions
7 to +7 from
the site. Five or more consecutive complementary sites could
potentially form stem-loop structures.
Sequence software.
All sequence randomization and nucleotide
distance measurements were performed with the Simmonic 2000 package.
Programs for measurement of synonymous variability and for covariance
screening are available from the authors.
 |
RESULTS |
Relationship between rate of sequence change and divergence.
If HGV/GBV-C and related viruses in primates have evolved in concert
with their hosts, then rates of sequence change could be calculated
from known times of human population movements and from paleontological
estimates of the timing of primate species divergence. However, these
inferred rates differ markedly for different estimated times of
divergence. For example, the accumulated rate of sequence change of
5.6 × 10
6 nucleotide substitution per site per year
over 100,000 years (0.1 Myr) between different human populations was
approximately 100 times lower than the rate measured over 8.4 years
(4 × 10
4 per year [23]). Rates of
synonymous change showed a similar decline over this period (3.2 × 10
6 per year compared with 6.5 × 10
4 per year over 8.4 years). Even greater differences
were observed when more distantly related species were compared (Fig.
1). These changes in net rate occur even
though neither the nucleotide divergence, corrected for multiple
substitutions between human and chimpanzee GB viruses (0.36), nor the
synonymous distances between human isolates (0.64) approached
saturation.

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FIG. 1.
Relationship of rates of nucleotide and amino acid
sequence change to sequence divergence, using the hypothesis that
HGV/GBV-C and related viruses in primates have cospeciated with their
hosts. Datum points ( ) from left to right represent the following
divergence times: 8.4 years (time course in HGV/GBV-C-infected
individual) (23), 100,000 years (divergence of modern
humans), 1.6 Myr (divergence of troglodytes and
verus subspecies of chimpanzees) (Pan troglodytes
[21]), 7 Myr (divergence of humans and chimpanzees
12, 21), and 35 Myr (divergence of Old World [human
and chimpanzees] and New world [Sanguinis mystax, S. labiatus, and Aotus trivirgatus] primates
[12]). The sequences compared were from the NS5 region
of the genome (amino acid positions 2498 to 2561 in sequence PNF2161
[U44402]), with divergences and rates based on J-C distances. For
comparison, rates of substitution of nucleotide sequences of alpha
globin of mammals, placentals, and birds are plotted ( ), using times
of divergence estimated from paleontological records (15).
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In contrast to HGV/GBV-C, little change in the rate of nucleotide
substitution was evident upon comparison of eukaryotic genes.
For
example, the rate predicted from comparison of human and chimpanzee
alpha globin sequences (1.1 × 10
9 substitution per
site per year) was similar to rates calculated
from more distantly
related animals (e.g., human and duck, 0.55
× 10
9/year). Overall, pairwise comparisons between 16 mammalian, placental,
and avian species produced rates ranging from
0.47 to 1.7 × 10
9 per year. These rates were
calculated over a range of corrected
nucleotide sequence distances
(0.012 to 0.42) in which the rate
of sequence change of HGV/GBV-C
declined by at least 100,000-fold
(Fig.
1) (
15).
Frequency and distribution of variability at synonymous sites.
Hypotheses to explain differences in the rate of sequence change of
HGV/GBV-C would not only have to account for the much greater
constraint on the encoded amino acid sequences but also provide a
mechanism that would inhibit the accumulation of substitutions at
synonymous sites which are usually regarded as selectively neutral.
Evidence for a restriction in variability at synonymous sites was
provided by analysis of the distribution of variable and invariant
nucleotide positions in HGV/GBV-C sequences (Fig. 2A). Among 17 HGV/GBV-C sequences of
genotypes 1, 2, and 3, a total of 622 codons were invariant at
synonymous sites (23%) compared with a mean of 277 (10.0% ± 0.6%)
between 10 independently generated simulated data sets of descendants
of the HGV/GBV-C sequence, R10291 (control set A; Fig. 2B). These
sequences had the same overall degree of divergence (J-C
distance, 0.139; dN, 0.017; dS, 0.62;
Ts/Tv ratio, 2.0) and had
similar codon usage and base compositions biases at the codon
positions 1, 2, and 3. In a second dataset of 17 genotype 3 sequences,
the mean variability was lower (J-C distance, 0.10;
dN, 0.016; dS, 0.43) and
30.3% codons were invariant at synonymous controls (Fig. 2C), 2.3 times the value in its matched control sequence data set. In contrast,
comparisons of the mammalian coding sequences of alpha globin and
albumin produced no evidence for a significant excess of invariant
codon positions with respect to that expected by chance (ratios of
1.15 and 1.26, respectively, with respect to values of randomized
control sequences).

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FIG. 2.
Frequency histograms of variability at synonymous sites
in 17 HGV/GBV-C sequences of genotypes 1, 2, and 3 (A), of expected
distribution of synonymous variability arising by chance (control data
set A) (B), and of variability in 17 HGV/GBV-C sequences of genotype 3 (C).
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Unequal codon usage does not explain the excess number of invariant
synonymous sites in HGV/GBV-C sequences, because such
biases are
frequently more extreme in eukaryotic gene sequences
such as alpha
globin. For example, 36% of third-base sites among
HGV/GBV-C sequences
were G and 32% were C (total G+C content,
68%), compared with the
more biased frequencies in alpha globin
sequences of 32 and 51% (G+C
content, 83%).
The distribution of invariant synonymous sites in the genome of
HGV/GBV-C was not random (Fig.
3). Mean
synonymous diversity
over a sliding window of 50 codons ranged from
0.159 to 0.716,
with extreme suppression of variability around
nucleotide positions
1300, 4600, 6300, and 6700 (Fig.
3A). A much more
restricted range
of variability was observed in a matched simulated
data set (control
set A; range, 0.363 to 0.564 [Fig.
3B]). The
pattern of variability
across the genome was reproduced in a separate
sequence data set
of type 3 sequences, even though the underlying
degree of sequence
variability was lower (Fig.
3C). There was no
evidence for the
existence of evolutionarily conserved potential coding
sequences
(containing initiating methionine and stop codons) in
either the
+2 or +3 reading frames of the positive-sense genome or the
+1
or +3 frames of the antisense genome, either in the parts of the
genome showing low variability at synonymous sites or elsewhere
(data
not shown).



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FIG. 3.
Mean synonymous diversity over HGV/GBV-C genome,
averaged over a sliding window of 50 codons in 17 HGV/GBV-C
sequences of genotypes 1, 2, and 3 (A), control data set A (B), and 17 HGV/GBV-C sequence of genotype 3 (C). Predicted or experimentally
determined sites of cleavage of HGV/GBV-C polyprotein (2,
18), sites of nucleotide substitution over 8.4 years
(23), and positions of predicted stem-loop binding predicted
by covariance algorithm are shown above panel A.
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Secondary structure of RNA.
The genomes of many RNA viruses,
including HGV/GBV-C and HCV, contain regions that form internally
base-paired stem-loop structures that play a role in RNA replication
and translation through ribosomal binding to an internal ribosome entry
site. While current descriptions of structured regions of viral genomes
are generally confined to the untranslated regions at the extreme ends
of viral genomes, there is also evidence for a series of stem-loop
structures in the core gene of HCV (27), which may play a
direct role in the translation of the HCV polyprotein (24).
Secondary structures in the HCV core gene would also account for the
marked suppression of synonymous substitutions in this region of the
genome in the absence of convincing evidence for an overlapping reading
frame (10, 24). More extensive internal base pairing might
therefore underlie the greater than expected frequency of invariant
synonymous sites observed in the HGV/GBV-C genome.
Conventional methods for predicting RNA secondary structures are
computationally intensive and are often based upon the calculation
of
minimum free energies (greatest internal base pairing) for
each
possible configuration of an RNA sequence. These secondary-structure
predictions are sometimes independently supported by the occurrence
of
covariance, where a nucleotide substitution of an internally
base-paired sequence is matched by a substitution in the paired
sequence that preserves binding. However, to date, formal statistical
methods to analyze the contribution of covariance detection in
the
identification of particular secondary-structure prediction
have not
been described, although recently a method was described
in which
thermodynamic structure prediction was combined with
phylogenetic
information to search for conserved structures in
human
immunodeficiency virus and HCV (
9).
The length of the coding region of the HGV/GBV-C genome (8,500 bases)
clearly poses problems for methods based only upon free-energy
calculation because the number of possible internal base-paired
combinations would be extremely large and similar in free energy.
However, the existence of multiple divergent genomic sequences
without
substantial phylogenetic structure suggested to us that
covariance
might be used in place of free-energy calculations
as the primary
method to detect internal base pairings. An algorithm
was used in which
alignments of HGV/GBV-C sequences were systematically
scanned for
potential base pairings between variable sites and
scored by the number
of paired substitutions from the upstream
and downstream consensus
bases that maintained base pairing (covariance
score). Candidate
covariant sites were additionally scored on
the length of sequence
either side of the site that was capable
of forming a stem-loop
structure (Table
1). Analysis of a
representative
data set of 17 HGV/GBV-C sequences of all genotypes
identified
a numerical excess of sites (approximately 35 sites) with
high
combined covariance and stem-loop scores over the number detected
in control sequences whose codon positions were randomly reordered
to break any stem-loop structure (control set C), or sequences
with
randomly introduced variability at an equivalent level to
that between
epidemiologically unlinked HGV/GBV-C sequences (control
set A). A
separate analysis of a second data set containing 17
type 3 sequences
also showed a similar excess of sites (30 sites)
with high covariance
and stem-loop values over control sequences
(data not shown).
Five lines of evidence argue for the biological reality of these
proposed structures. First, the spacing between covariant
sites in
HGV/GBV-C was nonrandom, since high covariance values
were strongly
associated with separations between upstream and
downstream sites of
less than 500 bases (Fig.
4A). The same
association
between spacing and covariance value was observed in a
separate
analysis of type 3 HGV/GBV-C sequences (data not shown) but
was
absent in control data sets A, B, or C (Fig.
4B; data not shown).
Second, multiple covariant sites were frequently found in the
same
stem-loop structure, more often than expected by chance;
an example of
a stem-loop containing four covariant sites is shown
in Fig.
5. Third, proposed structures in
HGV/GBV-C sequences were
found in homologous positions in the more
distantly related HGV/GBV-C
TRO and GBV-A sequences by using
a minimum-energy algorithm to predict
RNA secondary structures
between base positions 1 and 1,500 of
their coding regions (RNADraw)
(Fig.
6). Covariant sites between
the
available GBV-A sequences were found in this region. These
structures were conserved despite the low degree of nucleotide
sequence
similarity between the GB viruses in this part of the
E1 gene (the
nucleotide sequence divergence ranged from 43 to
53% between positions
263 and 309 in the
R10291 genome). Third-base
positions in the
predicted stem-loops for human HGV/GBV-C sequences
and GBV-A were
paired, and all covariant substitutions in the
loop were synonymous.

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FIG. 4.
Frequency histogram of covariance scores between paired
nucleotide sites according to their separation in the genome of 17 HGV/GBV-C sequences of genotypes 1, 2, and 3 (A) and control data set C
(B). Solid bars represent frequencies of nucleotide pairs with
covariance scores of 6 or greater. Frequencies were adjusted to account
for the number of pairs compared.
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FIG. 5.
Example of a potential stem-loop structure identified by
covariance screening of 17 HGV/GBV-C sequences of genotypes 1 to 3. Covariant sites are indicated by numbering. Analogous structures were
detected by analysis of type 3 sequences only (data not shown). All
changes from consensus nucleotide sequence were synonymous except for
those marked in bold. Vertical lines indicate Watson-Crick base
pairing; asterisks indicate GU base pairing.
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FIG. 6.
(A) Stem-loop structure in the E1 genes of HGV/GBV-C (A)
and likely homologues in HGV/GBV-CTRO (B) and GBV-A (C)
sequences. Covariant sites in panels A and C are boxed.
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Fourth, while potential stem-loop structures detected by the covariance
algorithm were distributed throughout the HGV/GBV-C
genome (Fig.
3A and
C), there was a close correlation between
these sites and regions where
synonymous site variability was
suppressed. For example, the region
from positions 3000 to 3950
showed the greatest synonymous variability
(peak value, >0.7)
and was uninterrupted by detectable covariant
sites. This region
was bounded by the predicted stem-loop structures
between positions
2964 and 3114 and positions 2958 and 3120 (5' end)
and between
positions 3894 and 3930 and positions 3897 and 3927 (3' end),
and these coincided with steep declines in mean
synonymous variability.
There was no obvious association between
synonymous variability
and sites of cleavage of the HGV/GBV-C
polyprotein (Fig.
3A).
Together, stem-loop structures predicted from
covariant sites
detected in both HGV/GBV-C sequence data sets accounted
for at
least 20% of the HGV/GBV-C genome. The 24 synonymous nucleotide
substitutions observed in the longitudinal study of HGV/GBV-C
sequence
change over 8.4 years (
23) were more frequently found
in
areas of the genome with higher mean synonymous variability
(Fig.
3A).
Finally, the proposed extensive RNA secondary structure of the
HGV/GBV-C genome was independently supported by the high free
energies predicted by RNA folding. Although the formation of RNA
secondary structures was favoured by the high G+C content of the
genome
(32% G and 27% C) and the excess of U over A residues (23
and 18%,
respectively), the order of bases also contributed additionally
to the
high free energy values observed for subgenomic regions.
The mean free
energy of eight overlapping 1,500-base fragments
of the
R10291
HGV/GBV-C sequence was 293 kJ/mol lower (range,
207 to 426 kJ/mol) than that of the same sequences in which nucleotides
were
randomly reordered (control set D). A similar difference
in free energy
was observed for the chimpanzee HGV/GBV-C
TRO sequence
(mean
reduction, 301 kJ/mol; range, 225 to 399 kJ) or upon comparison
of
shorter subgenomic regions of
R10291 (e.g., mean of 89 kJ/mol
and range
of 23 to 185 kJ/mol over a sequence length of 500 bases).
In contrast,
no significant difference in free energy was observed
upon
randomization of base order for 1,500 base regions of sequences
where
the identity of nucleotides was altered to change base pairing
(G

C

U

A

G [control set B]). Similarly, no significant
reduction
was observed upon reordering the human gene sequences of
alpha
globin (

13 kJ/mol over a sequence length of 429 bases) or
albumin
(+13 kJ/mol over 1,845
bases).
Nucleotide order randomization also lowered the free energy for the
reverse complement of the first 1,500 bases of the HGV/GBV-C
genome (

119 kJ/mol), but to a lesser extent than that of the
sense sequence (

294 kJ/mol), suggesting that the secondary structure
of the positive strand was more relevant biologically.
Secondary-structure
predictions based on free energy provided
independent evidence
for the majority of the short-range stem-loop
structures identified
by covariance screening (Fig.
6) but did not
support structures
in which covariant sites were separated by more than
100
bases.
 |
DISCUSSION |
This study provides evidence for marked restrictions on the
sequence variability of HGV/GBV-C that may limit the extent to which virus genome sequences can diverge over time. In contrast to
mammalian genes, HGV/GBV-C sequences showed an increased
frequency of invariant synonymous sites over that expected by chance,
suggesting a functional role of certain nucleotide positions that was
independent of the coding capacity for the HGV/GBV-C polyprotein and
which did not result from the presence of overlapping gene sequences in
other reading frames. A similar although less marked excess of
invariant synonymous sites was recently reported in a separate analysis
of swine vesicular disease virus and foot-and-mouth disease viruses
sequences (8). The contribution of secondary-structure formation to the observed restricted variability of HGV/GBV-C was
supported not only by the spatial association between covariant sites
and stem-loop structures (Fig. 4; Table 1) but also by the contribution
of base order to free-energy calculations of RNA folding. Similarly,
randomization of the nucleotide order of swine vesicular disease virus
3B/C sequences led to a consistent although proportionately smaller
reduction in free energy on folding (mean 7.6% reduction over 641 bases [24a], compared with 16% over an equivalent
length of HGV/GBV-C).
In a folded genome, sequence change in regions that are internally base
paired would require simultaneous nucleotide substitutions on both
sides of potential stem-loop structures to maintain base pairing and
would lead to a much lower frequency of sequence change than in
unpaired sites. The preferential accumulation of nucleotide changes at
nonpaired sites may therefore account for the rapid sequence change of
HGV/GBV-C over short periods, while further divergence, such as between
different isolates of HGV/GBV-C or between different primate species,
may occur only through covariant substitutions, which accumulate more
slowly over longer periods (Fig. 1). For example, the substitution rate
of HGV/GBV-C over 8.4 years, 4 × 10
4 per site per
year (23), predicts a frequency of covariant substitutions less than 1.5 × 10
7, which is comparable to the
long-term rate of substitution observed between viruses infecting
different primate species (such between HGV/GBV-C and GBV-A sequences
[Fig. 1]). An even greater differential frequency (1.1 × 10
5 unpaired and 1 × 10
10 at
covariant sites) would occur at nonsynonymous sites, and this greater
restriction on nonsynonymous-sequence change may contribute to the
extreme dN/dS ratio observed between HGV/GBV-C
sequences (0.033) compared with that for coding sequences of other
viruses and eukaryotes.
More precise matching of variable and nonvariable sites in the
HGV/GBV-C genome with unpaired and paired nucleotides will require the
completion of a model of its secondary structure. These investigations
would include determining the relationship between secondary structure
and the sites of nucleotide substitution in the HGV/GBV-C over short
observation periods where high frequencies of sequence change at
synonymous sites was observed (Fig. 4) (23). The base
pairings predicted by covariance scanning will contribute to future
attempts to determine the overall structure of HGV/GBV-C genome, since
they restrict the remaining structure prediction by free-energy
calculation to relatively short lengths of sequence. Such analyses
would be assisted by the observation that all of the sites identified
by covariance were relatively closely spaced (<500 bases); this may be
a general feature of HGV/GBV-C genomic RNA structure.
Structural constraints on sequence change independent of coding
capacity may inhibit sequence change in other viruses with single-stranded genomes. For example, separate genotypes of
simian immunodeficiency virus (SIVAGM) are associated with
different subspecies of African green monkeys (11), while a
similar association between genetic variants of SIVCPZ
in different chimpanzee subspecies (Pan troglodytes
troglodytes and P. troglodytes schweinfurthii has
recently been reported (6). If these associations also represent coevolution of viruses with their hosts, there is a similar
discrepancy between their long- and short-term rates of sequence
change. In the second example, the 37.7% sequence divergence which
accumulated over a period of at least 0.5 million years between SIV
variants infecting the troglodytes
(SIVCPZ-US and SIVCPZ-GAB) and
schweinfurthii (SIVCPZ-ANT) subspecies
(21) represents a net rate of sequence change of 3.4 × 10
7 per site per year. This rate is approximately 5,000 times lower than the rate (1.4 × 10
4 per site per
year) inferred from comparison of different subtypes in the main (M)
group of human immunodeficiency variants, which are considered to have
originated over the last 50 years (based on a mean pairwise distance
between single representative sequences of types A to J of 14.2%
[29]). Despite the genetic and structural differences between flaviviruses and lentiviruses, the absolute values
and differential between short- and long-term rates of sequence change
of human immunodeficiency virus type 1 and SIVCPZ were
remarkably similar to those predicted for HGV/GBV-C.
The functional role of the predicted RNA secondary structures in
HGV/GBV-C remains unclear. Among several possibilities that may apply
equally to other single-stranded RNA viruses, RNA folding may be
required for packaging of the genome into the viral nucleocapsid or to
protect the genome from RNA-degrading enzymes or it may be involved in
the regulation of transcription or translation in analogous ways to the
function of internal ribosome entry site structures in
flaviviruses and picornaviruses. Recently, an internal stem-loop structure in the coding part of the human rhinovirus 14 genome sequence, comparable in size and free energy to those detected
in HGV/GBV-C, was shown to be essential for human
rhinovirus 14 negative-strand transcription (20).
The long-range interactions between different genomic
regions implied by these observations suggest an organized overall
structure of the RNA genome, in which stem-loop structures may play an
important structural or catalytic role in virus replication.
Irrespective of its functional significance, the evidence for markedly
different substitution frequencies at different sites puts a
fundamental limitation on the use of sequence divergence in the timing
of virus origins. While the species association of HGV/GBV-C and
related viruses in primates provides indirect evidence for their
long-term rates of change, such inferences cannot be made for viruses
with less close host associations. While it is possible that much of
the genetic heterogeneity of RNA viruses originated very recently, our
inability to measure long-term rates of sequence change or to
understand the restrictions on sequence variability currently leaves
open the possibility of very ancient origins of many RNA viruses. These
findings suggest that the molecular clock, which has been of major
value in the reconstruction of vertebrate and other eukaryotic
phylogenies, cannot be simply applied to viruses with more unusual
genomic structures.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Medical Microbiology, University of Edinburgh, Teviot Place, Edinburgh EH8 9AH, United Kingdom. Phone: 44 131 650 3138. Fax: 44 131 650 6531. E-mail: Peter.Simmonds{at}ed.ac.uk.
 |
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0022-538X/99/$04.00+0
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