Copy Number Variation of CCL3-like Genes Affects Rate
of Progression to Simian-AIDS in Rhesus Macaques
Jeremiah D. Degenhardt1, Paola de Candia2, Adrien Chabot2, Stuart Schwartz2, Les Henderson2, Binhua
Ling3, Meredith Hunter3, Zhaoshi Jiang4, Robert E. Palermo5, Michael Katze5, Evan E. Eichler4, Mario
Ventura6, Jeffrey Rogers7, Preston Marx3, Yoav Gilad2.*, Carlos D. Bustamante1.*
1Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America, 2Department of Human Genetics, University of Chicago,
Chicago, Illinois, United States of America, 3Tulane National Primate Research Center, Covington, Louisiana, United States of America, 4Department of Genome Sciences,
University of Washington, Seattle, Washington, United States of America, 5Department of Microbiology, University of Washington, Seattle, Washington, United States of
America, 6Dipartimento di Genetica e Microbiologia, Universita’ degli Studi di Bari, Bari, Italy, 7Department of Genetics, Southwest Foundation for Biomedical Research,
and Southwest National Primate Research Center, San Antonio, Texas, United States of America
Variation in genes underlying host immunity can lead to marked differences in susceptibility to HIV infection among
humans. Despite heavy reliance on non-human primates as models for HIV/AIDS, little is known about which host factors
are shared and which are unique to a given primate lineage. Here, we investigate whether copy number variation (CNV) at
CCL3-like genes (CCL3L), a key genetic host factor for HIV/AIDS susceptibility and cell-mediated immune response in
humans, is also a determinant of time until onset of simian-AIDS in rhesus macaques. Using a retrospective study of 57
rhesus macaques experimentally infected with SIVmac, we find that CCL3L CNV explains approximately 18% of the variance
in time to simian-AIDS (p,0.001) with lower CCL3L copy number associating with more rapid disease course. We also find
that CCL3L copy number varies significantly (p,1026) among rhesus subpopulations, with Indian-origin macaques having,
on average, half as many CCL3L gene copies as Chinese-origin macaques. Lastly, we confirm that CCL3L shows variable copy
number in humans and chimpanzees and report on CCL3L CNV within and among three additional primate species. On the
basis of our findings we suggest that (1) the difference in population level copy number may explain previously reported
observations of longer post-infection survivorship of Chinese-origin rhesus macaques, (2) stratification by CCL3L copy
number in rhesus SIV vaccine trials will increase power and reduce noise due to non-vaccine-related differences in survival,
and (3) CCL3L CNV is an ancestral component of the primate immune response and, therefore, copy number variation has
not been driven by HIV or SIV per se.
Citation: Degenhardt JD, de Candia P, Chabot A, Schwartz S, Henderson L, et al. (2009) Copy Number Variation of CCL3-like Genes Affects Rate of Progression to
Simian-AIDS in Rhesus Macaques (Macaca mulatta). PLoS Genet 5(1): e1000346. doi:10.1371/journal.pgen.1000346
Editor: Harmit S. Malik, Fred Hutchinson Cancer Research Center, United States of America
Received September 23, 2008; Accepted December 17, 2008; Published January 23, 2009
Copyright: ? 2009 Degenhardt 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 National Institutes of Health grant GM077959 to YG and CDB and National Science Foundation grant NSF0516310 to CDB.
YG and CDB are Alfred Sloan fellows.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com (YG); firstname.lastname@example.org (CDB)
. These authors contributed equally to this work.
Rhesus macaques are the most widely used non-human-primate
model of HIV/AIDS . We and several other research groups
have reported substantial inter-individual variation in progression
rates to simian-AIDS as well as population level differences
between Chinese- and Indian-origin macaques [2–5]. Under-
standing the genetic basis of these individual and population
differences is critical to building reliable animal models of human
HIV infection and AIDS progression.
In humans, an important host factor for HIV susceptibility is
copy number variation at CCL3L1, a paralog of the CCL3 gene [6–
12]. CCL3L1 is thought to have been generated through a
segmental duplication of a genomically unstable region located on
human chromosome 17q11-17q12 [6–12]. We and others have
shown that, in humans, the q arm of chromosome 17 has multiple
regions of genomic instability where gene duplications, chromo-
somal rearrangements and copy number variation are common
[13,14]. As well, this region shows additional areas of duplication
in the rhesus macaque reference genome (see Figure 1B). CCL3
and CCL3L1 encode chemokine ligands of CCR5, the main co-
receptor used by HIV-1 for entry into host cells [10,11].
After the discovery of copy number variation of CCL3-like
genes, there have been a large number of studies in humans,
expanding our understanding of the role of this variation in
differential HIV susceptibility and progression. It has been shown
that CCL3-like gene CNV plays a role in the level of chemokine
production and chemotaxis [9,15], controlling viral load [15,16],
cell-mediated immune response , and most recently, HIV-
specific gag response . Several studies have reported findings
showing a significant role of CCL3-like gene CNV in HIV
resistance and disease progression. In particular, findings indicate
PLoS Genetics | www.plosgenetics.org1 January 2009 | Volume 5 | Issue 1 | e1000346
that reduced CCL3L1 copy number relative to the population
median correlates with increased risk of acquiring HIV ,
increased progression rate to AIDS , and increased risk of
maternal-fetal HIV transmission [15,19,20]. Other studies,
however, have found no, or limited, association between CCL3-
like gene CNV and HIV/AIDS [21–23]. In addition, it is
currently not known whether copy number variation of CCL3-like
genes plays a role in S/HIV immunity in other primates, although
it has been shown that copy number variation exists at these loci in
chimpanzees  and that this locus is duplicated in a rhesus
To investigate whether CCL3-like genes show variable copy
number in rhesus macaque populations and, more specifically, to
study the role of the CCL3-like genes in SIV survivorship among
rhesus macaques, we assayed copy number variation at these genes
in a cohort of 37 Indian-origin and 20 Chinese-origin animals
previously infected with SIVmac at the Tulane National Primate
Research Center. Individual animals were included in our
retrospective study only if the clinical results of a necropsy
confirmed health complications due to simian-AIDS at the time of
euthanasia or if the animal remained AIDS free for at least 18
months post-infection (see Methods and Table S1).
An analysis of the shotgun and BAC reads of the CCL3 and
CCL3-like gene regions of the macaque genome revealed no fixed
differences that would enable us to design a CCL3-like gene-
specific primer or probe in this species (results not shown but see
Methods). Therefore, our assay, as designed, will detect both CCL3
and all CCL3-like gene paralogs in rhesus as well as in chimpanzee
and human cells, and we refer to the combined loci detected as
In order to estimate CCL3L copy numbers we used real-time
PCR (rtPCR), and determined absolute copy numbers using two
reference samples (see Text S1 and Figure S1 for calibration curve,
and Methods for more details). The first is the human cell line
A431, which has two copies per diploid genome of CCL3 and two
copies of CCL3L1 (by fluorescent in-situ hybridization (FISH);
Figure 1A; Figure S1; see also reference ). The second reference
sample is the rhesus macaque genome donor, which whole-
genome shotgun sequencing analysis (WGSA) found to have
between six and eight copies per diploid genome of CCL3L
(Figure 1B and Methods). The use of two independent references
allowed us to cross-validate our copy number estimates. Support
for our CNV estimates also comes from a comparison of the
rtPCR result to interphase FISH of a macaque cell line (MMU2
9133) (see Figure 1C and 1D).
Using the rtPCR assay, we observed extensive variation in copy
number of the CCL3L region among animals in our study, with a
range of 5 to 31 copies per diploid genome (median 10; mean
11.0565.16 [sd]; Figure 2). Tables 1 and 2 summarize the results
of Cox proportional hazard models  for the survivorship data
using CCL3L copy number and population-of-origin as potential
covariates (see Methods). Overall, we found strong evidence that
reduced CCL3L copy number correlates with increased rate of
progression to simian AIDS. Specifically, a model that includes
CCL3L as a covariate (m1) provides a significantly better fit to the
data than the model (m0) without CCL3L (LRTm0 v. m1=11.6;
p,0.001; Table 1; Figure 3A).
Population substructure is a potential confounding variable for
our analysis as it has previously been shown that Chinese-origin
animals tend to exhibit slower progression rates post-infection than
Indian-origin animals [2–5]. In order to address this issue, we first
validated population assignments of all individuals in our sample
by genotyping 53 unlinked microsatellites and analyzing the data
using the Bayesian clustering algorithm STRUCTURE  and
Principle Component Analysis (see Text S1; Figures S2 and S3).
Both analyses clearly suggest two (and only two) sub-populations in
our data with no evidence of admixture. We also calculated
Queller-Goodnight [27,28] estimates of genetic relatedness from
the microsatellite data and found only low levels of cryptic
relatedness within both populations (see Text S1; Figure S4). The
finding that there is some level of relatedness is expected given that
the animals used in our study were sampled from US colonies,
however, genomic control analysis of the microsatellite data
suggests that these low levels of cryptic relatedness do not
markedly affect our p-value estimates (see Text S1; Figure S5).
Once population assignments for all individuals had been
confirmed, we considered several statistical models for the
progression data that included population-of-origin as a potential
covariate. When considered alone, we found that population-of-
origin impacts survivorship with Indian-origin, correlating with
increased rate of progression to simian-AIDS as previously
reported (LRTm0 v. m2=8.37; p,0.01; Table 1). However, once
CCL3L is included in the model, population-of-origin makes only a
marginally significant improvement (LRTm1 v. m3=3.25; p=0.071;
Table 1). This analysis suggests that CCL3L is the predominant
factor impacting survivorship differences among individuals, and
predicts that differences in the distribution of CCL3L copy number
among Indian and Chinese populations may explain the
population-level differences in survivorship.
We further tested the impact of population substructure by
repeating our analysis using only Indian-origin rhesus macaques.
(The sample size and proportion of censored data in the Chinese-
origin sample rendered the power of the test too low to detect a
significant result; see Text S1, Figure S6). We found that including
CCL3L CNV in the model explains a significant proportion of the
survival time variation among Indian-origin macaques alone
(R2=15.6%; p=0.0122), confirming that CCL3L CNV is contrib-
uting to the observed effect and that the effect is not likely to be
explained by systematic variation at an additional allele due to
population substructure. Additionally, the estimated effect size of
CCL3L copy-number variation (b) on survivorship is highly
comparable across subsets of the data (see Table 2 and 95%
confidence intervals for exp(b)). This observation suggests that
CCL3L CNV has a similar effect across both populations, whereby
each copy of CCL3L decreases the baseline risk by a constant
factor of approximately exp(b)=0.907 relative to the mean of 11
Development of vaccines for HIV/AIDS is a pressing global
issue. The rhesus monkey remains the primary model for
testing potential human vaccines; however, little is known
about similarities and differences in host genes involved in
HIV/AIDS response in humans and rhesus monkeys.
Understanding these similarities and/or differences should
allow more efficient testing of vaccines beneficial to
humans. Here we describe the role that variation in the
number of copies of CCL3-like genes (CCL3L) plays in SIV
progression rates in rhesus monkeys. Copy number
variation (CNV) of these genes has previously been shown
to play a role in susceptibility and progression of HIV in
humans. Our results suggest that individual monkeys with
lower CCL3L copy number progress more rapidly. Account-
ing for CCL3L CNV in rhesus vaccine trials will improve
researchers’ abilities to interpret survival data.
CCL3L CNV and SIV progression in M. mulatta
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Figure 1. Calibration and verification of rtPCR copy number. (A) Metaphase FISH image of A431 cell line confirming diploid copy number of
two CCL3L1 genes (Note: Therefore using our assay we consider the A431 cell line to have a diploid copy number of four genes since it also contains
two copies of CCL3). (B) Whole-genome shotgun read depth analysis showing estimation of CCL3L copy number in the rhesus macaque genome
CCL3L CNV and SIV progression in M. mulatta
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Figure 2. Histogram of copy number estimates. Histogram of the rtPCR estimated copy number of CCL3-like genes for the 57 retrospective
samples of rhesus macaque. The histogram shows a large range of copy numbers found in this sample with copy number estimates from 5 to 31
copies per diploid genome.
Table 1. Likelihood ratio test statistics for analysis of multiple variables contributing to survivorship based on Cox proportional
Model ComparisonLRT statisticp-value
Combined (n=57)m0: No covariates
2155.9131-- ---- --
m1: CCL3L copy number
2150.140018.3% M1 vs. M0 (df=1)11.6
m2: Population of origin
m3: CCL3L copy number + Population
2151.728613.7%M2 vs. M0 (df=1) 8.37 0.0038
2148.512022.9% M3 vs. M0 (df=2) 14.8 0.0006
M3 vs. M1 (df=1)3.25 0.0710
M3 vs . M2 (df=1)6.43 0.0110
Indian-only (n=37)m0: No covariates
m1: CCL3L copy number
293.01357 15.6%M1 vs. M0 (df=1) 6.280.0122
Chinese-only (n=20)m0: No covariates
m1: CCL3L copy number
230.07515 4.7%M1 vs. M0 (df=1)0.95 0.3290
The test statistics are asymptotically x2distributed.
donor as 6 copies per diploid genome based on rheMac2 assembly. Green and orange lines denote shotgun reads aligned to CCL3L region of the
January 2006 assembly of the rhesus macaque reference genome with orange lines showing those that likely represent regions of duplications based
on the read-depth analysis (See Methods). (C) Interphase FISH image of the MMU2 9133 rhesus macaque cell line, which has an estimated diploid
copy number of 10 copies of CCL3L. (D) Validation of rtPCR estimates of CCL3L copy number. Black dots represent rtPCR copy number estimates for
the A431 human cell line, the rhesus genome donor, and MMU2 9133 rhesus cell line. Red dots represent an independent estimate of copy number
for all three samples based on either FISH or WGS analysis. See supplemental material for additional information regarding the copy number
CCL3L CNV and SIV progression in M. mulatta
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copies (e.g., having 16 copies decreases the hazard by a factor of
0.9075=0.61, and having 8 copies increases the hazard by a
Further support for the protective effects of increased CCL3-like
gene copy number is provided by Harrington-Fleming tests of
equality for Kaplan-Meier survival curves . Comparisons of
the survival curves across all observed CCL3L copy number levels
clearly reject equality, whether analyzing all individuals together
(X2=51.3; p,0.001, df=17) or stratifying by population of origin
(X2=48.1; p,0.001, df=17). Additionally, we considered dividing
the data into qualitative copy-number categories as identified by
K-means clustering with K=3 for the observed CCL3L CNV
distribution: ‘‘low’’ having less than 9 CCL3L copies per diploid
genome (pdg), ‘‘intermediate’’ having 9–14 CCL3L copies pdg, and
‘‘high’’ having greater than 14 CCL3L copies pdg. We also
considered a two-class classification that combined the ‘‘interme-
diate’’ and ‘‘high’’ copy number classes into a single class. Overall,
we observe a highly significant difference in survivorship between
CCL3L copy classes in the combined data stratified by origin
(p=0.0045 for two categories and p=0.0174 for three categories;
see Figure 3D and 3E). Likewise, if we consider survivorship curves
within each population separately, a significant difference is
observed between animals with low copy number relative to those
with intermediate or high copy number (p=0.0231 for Indian;
p=0.0484 for Chinese; see Figure 3F and 3H). The above analysis
is robust to how the copy-number categories are chosen. For
Table 2. Regression coefficient estimates (b), standard errors on the regression coefficient estimates, confidence intervals, and
significance for terms in the Cox proportional hazard models summarized in Table 1.
VariableData Other factors in model
RHse (b) 95% CI on Exp(b) p-value
20.119 0.8880.04 (0.82, 0.96)0.0038
20.149 0.861 0.07 (0.76, 0.98)0.0260
20.097 0.907 0.04(0.84, 0.99)0.0220
21.100.3330.32 (0.18, 0.62)0.0006
21.12 0.3270.44 (0.14, 0.77)0.0110
20.930.393 0.34 (0.20, 0.76)0.0055
20.920.398 0.34(0.21, 0.77) 0.0064
20.610.54 0.35 (0.27, 1.08)0.0830
20.58 0.56 0.35 (0.20, 0.76)0.1000
‘‘Variable’’ refers to a particular term in the regression model (i.e., CCL3L copy number, log of CCL3L copy number, or population of origin), ‘‘Data’’ refers to which subset
of the data is considered (i.e., Combined=Indian-+Chinese-origin animals or Indian animals alone), and ‘‘Other factors in the model’’ refer to whether the regression
coefficient is estimated alone or in the presence of other terms.
Figure 3. Rhesus macaque survival analysis. (A) Scatter plot of post SIV infection survival time (or censor time if animal is alive) by CCL3L copy
number. Blue dots represent Chinese-origin rhesus macaques while green dots represent Indian origin. Filled in dots represent animals still alive at
time of sampling. Fitted regression curve, p-value and relative-hazard (RH) from Cox proportional hazard model (model 1 in text). (B,C) Boxplots of
CCL3L copy-number defining ‘‘low’’ copy number to be fewer than or equal to 8 copies per diploid genome, ‘‘intermediate’’ to be 9 and 14, and
‘‘high’’ to be more than 14 copies or low vs. intermediate+high. D-I) Estimated Kaplan-Meier survival curve for SIV-infected macaques with time
measured from date of infection. The black curve represents ‘‘low’’, the red curve ‘‘intermediate’’ or ‘‘intermediate+high’’, and the blue curve ‘‘high’’
copy number for KM curves based on all animals (D,E), Indian-origin only (F,G), and Chinese-origin only (H,I). The p-values correspond to Harrington-
Fleming tests of equality for survivorship curve using r=0 which is equivalent to a log-rank or Mantel-Haenszel test. Relative-hazard (RH) for
equivalent Cox proportional hazard model are also presented.
CCL3L CNV and SIV progression in M. mulatta
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example, using the population specific or overall first and third
quartiles gives similar results (results not shown). These results,
taken together, suggest that it is low CCL3L copy number, in
particular, that is correlated with increased rate of progression.
Next we investigated whether differences in the distribution of
CCL3L copy number alleles between populations could explain the
previously reported slower simian-AIDS progression rates of
Chinese-origin animals [2–5]. That is, given the association
between higher CCL3L copy number and slower progression, we
would expect Indian-origin macaques to have, on average, lower
CCL3L copy numbers as compared with Chinese-origin macaques.
Within the samples used for the retrospective study, animals
designated as Indian-origin did, in fact, have a significantly lower
s.e.m=0.587), than those designated as Chinese-origin (medi-
an=12.5, mean 13.90, sd=6.41, s.e.m=1.43) as measured by a
Mann-Whitney U test using either relative copy number estimates
from rtPCR (p=0.0088) or binned and rounded CNV calls
(p=0.0077; see also Figure 4A). We also assayed CCL3L CNV in
an independent panel of SIV-free Indian-origin and Chinese-
origin rhesus macaques to ensure that the relationship between
origin and CCL3L was not a peculiar artifact of the animals we
utilized from the SIV vaccine trials. This independent panel
included 15 wild-caught Chinese-origin macaque samples collect-
ed as part of the Rhesus Macaque Genome project  and 16
colony-born Indian-origin macaques provided by Yerkes National
copy number(median=9, mean=9.51,sd=3.57,
Figure 4. Population and species level copy number variation. (A) Histograms and boxplots of CCL3L copy number distribution among the
n=57 animals used in the retrospective study as well as for a sample SIV-free Indian-origin (n=16) and Chinese-origin rhesus macaques (n=15). Red
and light-red bars indicate Indian origin for the SIV and SIV-free populations, and blue and light-blue bars indicate the analogous for Chinese-origin
animals. B) Box plot of copy number variation for 6 primate species: Human, Chimpanzee (Pan troglodytes), Orangutan (Pongo pygmaeus), Rhesus
macaque (Macaca mulatta), African green monkey (Cercocebus aethiops), and Sooty mangabey (Chlorocebus atys). Whiskers indicate the upper and
lower quartile with dots showing outliers. Estimates of species divergence times are from reference .
CCL3L CNV and SIV progression in M. mulatta
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Primate Center. In this second panel, we found an even higher
difference in CCL3L CNV between the two populations
(p,961027Mann-Whitney U test; also see Figure 3A). Chinese-
origin animals had, on average, twice as many copies of CCL3L as
Indian-origin animals (Chinese-origin mean=17.6, s.d.=3.56,
s.e.m=0.91; Indian-origin mean=9.41, s.d=3.4, s.e.m=0.91),
consistent with the average slower progression rates of Chinese vs.
Analysis of the retrospective data provides strong support for the
hypothesis that CCL3L CNV affects individual level SIV
progression rates in rhesus macaques. This is particularly evident
in the Indian-origin rhesus macaque where lower copy numbers of
CCL3L are more common, putatively leading to an overall
increase in progression rates in this population. Due to the limited
power in our analysis of the Chinese-only sample, we recommend
further studies to confirm the role of CCL3L in this population. To
our knowledge, the current study provides the first example of an
association between copy number variation and disease in a non-
human primate. These results broaden our understanding of the
role copy number variation in disease susceptibility and point to
the importance of utilizing methods which allow for detecting this
type of variation in genome-wide scans of disease association.
When taken together with the results of the retrospective
progression study, the population level analysis suggests that
differences in the distribution of CCL3L copy number may explain
a large portion of the differences in progression rates between
Indian- and Chinese-origin macaques. This result is in contrast to
that found in humans, where population level differences in
CCL3L1 copy number did not translate into population level
differences in progression . We suggest further studies of both
rhesus and human progression data is necessary to elucidate the
factors contributing to these differences. Using the results of the
Cox proportional hazard model, and the observed CCL3L
distribution between subpopulations, we have generated predic-
tions for expected survivorship at different levels of CCL3L copy-
number variation and population-of-origin designation (provided
in Text S1; Figure S7). These calculations may prove useful in the
efficient design of vaccine trials. For example, we predict less than
15–20% of Indian or Chinese-origin animals with six or fewer
copies of CCL3L will survive past 24 months post-SIV infection. In
contrast, the vast majority of animals with 25 or more copies are
expected to survive well past 36 months, regardless of whether
they are of Indian or Chinese origin.
In this context, it is important to note that the determination of
absolute copy numbers using rtPCR completely depends on the
quality of the reference. Moreover, determination of absolute high
copy numbers is less accurate than low copy number because noise
accumulates during the progression of the amplification reaction.
That said, since our absolute copy number results are based on
two validated references, it is likely that they are accurate. In
addition, importantly, we note that the conclusions of this study
are not contingent on obtaining accurate absolute copy numbers for
each sample. Rather, our conclusions are based on the relative copy
number of CCL3L between samples, a measure that qualitatively is
not sensitive to the specific reference used. Specifically, our results
are robust with respect to how CCL3L copy number is defined. In
other words, if we consider log2of CCL3L copy number, or relative
estimates of CCL3L copy numbers instead of absolute copy
numbers, our conclusions are unchanged (Table 2).
Our findings, together with previous observations [15–20],
suggest that CCL3L copy number variation is a shared genetic
mechanism impacting disease progression between humans and
macaques. This result is surprising given the long evolutionary
time separating the two species. Population genetic theory suggests
that little genetic variation currently in the human population
should be shared ancestrally with rhesus macaques, so there is no a
priori reason to suspect a shared mechanism due to a common
polymorphism. As a preliminary test to determine if CCL3L CNV
is indeed shared ancestrally, we examined CCL3L copy number in
five other primate species: African green monkey [AGM]
(Chlorocebus atheops, n=12), sooty mangabey [SM] (Cercocebus atys,
n=10), orangutan [PP] (Pongo pygmaeus, n=7), chimpanzee [PT]
(Pan troglodytes, n=12), and humans [HS] (8 Yoruban, 4 Chinese
and 4 Japanese from the phase I HapMap set). The rtPCR was
conducted using a common primer/probe set designed for the
rhesus macaque. We chose to use this primer/probe set, as
genomic sequence is not available for the sooty mangabey or
African green monkey. Our results confirm a previous observation
 and reveal the presence of extensive variability in CCL3L copy
number in all primate species examined (Table 1; Figure 4B),
suggesting that CCL3L CNV has likely been segregating in Old
World monkeys and apes for at least 25 million years through
recurrent duplication, deletion, and gene conversion of the locally
unstable genomic segments containing the CCL3L genes.
We note, however, that due to the use of a common primer/
probe set in all species, the determination of absolute copy number
may be biased by fixed differences between species in these
regions. This is in contrast to the observation that copy number is
variable within each species, which should be robust to such fixed
differences. We also note that our results differ from those of a
recent study of genomic copy number variation in chimpanzees
and humans, which found low CCL3L copy numbers in
chimpanzees . It is important to highlight that there are likely
differences in the subspecies of chimpanzee used between the
studies and in the resolution of the CNV detection methods
utilized. These experimental design differences make it difficult to
draw conclusions regarding the biological significance of the
differing observations. We therefore suggest that more research is
needed to resolve the evolutionary history of this genomic region,
and in particular to estimate the distribution of CCL3L copy
number variation in chimpanzees.
In summary, our findings further support the hypothesis that
CCL3L copy number variation is an important host factor for
explaining variation in HIV/SIV progression rates [15–20]. Our
results also provide an example of a common mechanism of
increased survival time after infection with HIV or SIV in humans
and another primate species respectively. There are two immediate
predictions from our observations. First, stratifying by CCL3-like
gene copynumber inmacaquevaccine studies willallow researchers
to remove CCL3L as a confounding effect, thereby increasing the
power of vaccine trials. Second, based on our observations, we
suggest that rhesus macaque is a valuable model organism for
further studies of the specific mechanism by which CCL3-like gene
copy number affects rates of HIV progression in humans.
Finally, it is important to note somecaveats of our work. First, the
current study is based on a relatively small sample of rhesus
macaques, pooled across several SIV studies. Additional data is
needed to fully understand the role of CCL3L in rhesus macaque
SIV progression. For example, further analysis investigating the role
of CCL3L on viral load and CD4-T cell count levels would be
beneficial. Unfortunately, complete and consistently taken mea-
surements are not available for these data as the samples were
pooled across several experiments. Second, as with all studies using
rtPCR technology, it is possible that polymorphisms in the primer
and probe sites could affect copy number estimation–although our
CCL3L CNV and SIV progression in M. mulatta
PLoS Genetics | www.plosgenetics.org7 January 2009 | Volume 5 | Issue 1 | e1000346
sequencing effort of the PCR products from four samples suggests
that the presence of such polymorphisms is unlikely. Additionally,
the presence of pseudogeninzed copies may bias our results.
Unfortunately, without complete knowledge of the presence and
distribution of pseudogenes for each individual, it is difficult to
address how the presence of pseudogenes would impact the power
of the analysis. Forexample,if foreachmonkey1–2copiesof CCL3-
likegenesarepseudogenized,thiswould havelittle (orno)impacton
the power of the tests. However, if for example, as copy number
increases, the probability of having more pseudogenized copies also
increases, this would adversely impact the power of the test.
Third, we have used a candidate gene approach in our analysis
of the association of genetic variation with simian-AIDS
progression. Therefore, it is possible that genetic variants at other
loci may account for even larger portion of the variance in
survival. One possible example is variation at MHC class I genes,
which has been shown to be associated with SIV progression rate
in Indian-origin rhesus macaques and explains at least 48% of the
variance in that study . We have addressed this to some extent
by conducting replicate association analyses with the 53 genome-
wide, unlinked microsatellite loci (see Text S1; Figure S5). We find
that copy number variation at the CCL3L locus falls in the 1% tail
of this distribution (after accounting for population substructure)
and is therefore, likely a true positive. It is important to remember
that there are many other host factors aside from chemokines and
their receptors known to influence HIV susceptibility and
pathogenesis in humans [32,33]. We believe these other factors
should be characterized in rhesus along with discovery of rhesus-
specific genetic variation before conclusions can be drawn on the
relative importance of shared versus species-specific factors
influencing retroviral susceptibility and disease progression.
Retrospective Progression Samples
The rhesus macaques used in the retrospective analysis were all
inoculated with SIVmac as part of previous SIV research
programs at the Tulane National Primate Research Center. All
macaques were infected with SIVmac239 or SIVmac251 with SIV
inoculum given under a standard protocol and at similar mid-level
dose. Doses in this range and the strain used have been previously
shown not to affect the outcome of disease course .
All animals used in our study were euthanized under the same
set of guidelines if they did not remain healthy after infection.
Specifically, euthanasia was carried out if life threatening clinical
conditions indicated that the life expectancy of the animal was less
than 7 days. Following euthanasia, a necropsy was performed, and
animals were only included in the current study if the necropsy
confirmed SIV as the underlying cause of the clinical state.
Animals were excluded only if they were euthanized and illness
could not be confirmed to be AIDS related. Because the results of
the necropsy were inconclusive with respect to the cause of the
illness in these cases (SIV or not) we chose to exclude them.
Conducting the analyses with these animals included as either
censored data or non-censored data did not change the results of
the analysis. Under these protocols, the time of euthanasia will give
a reasonable approximation to both time to progression to simian-
AIDS and survival time, as the presence of AIDS defining illnesses
met the criterion for euthanasia. (See Table S1 for clinical findings
of necropsy and Text S1).
Additional Primate Samples
DNA extractions from the uninfected Chinese-origin rhesus
samples were obtained from the Rhesus macaque genome
consortium. The chimpanzee, orangutan, sooty mangabey, and
uninfected Indian-origin rhesus macaque DNA samples were
obtained from the Yerkes National Primate Research Center and
the African green monkey DNA samples were obtained from the
University of California Los Angeles.
Real-Time PCR CCL3L Copy Number Estimation
CCL3L gene copy number was determined using real-time
quantitative PCR (rtPCR) on a 7900HT Fast Real-Time PCR
System (Applied Biosystems Inc.) with the JumpStart Taq Ready-
Mix (SIGMA) and TaqMan probes. The PCR included 18 ng total
genomic DNA. Cycling conditions were: initial denaturation at
94uC for 2 min; followed by 40 cycles of 15 sec denaturation at
94uC and 1 minute annealing/extension at 60uC. The Stat6 gene,
found to be present in a single copy, per haploid genome, in rhesus
macaque, chimpanzee and human reference genomes, was used as
the internal control. Oligonucleotide sequences used for CCL3L
were: Forward: 59-CCAGTGCTTAACCTTCCTCC-39, Re-
AGGCCGGCAGGTCTGTGCTGACC-39. For Stat6, sequences
were: Forward: 59-CCAGATGCCTACCATGGTGC-39, Re-
CTGATTCCTCCATGAGCATGCAGCTT-39. This primer set
does not distinguish between CCL3 and the CCL3-like gene
paralogs, as we did not observe sufficient fixed differences between
these paralogs in rhesus macaque references genome to design a
specific assay. It is also unknown whether any pseudogenized
copies of CCL3L genes exist in the rhesus macaque populations. As
such, we here refer to CCL3 and its paralogs as CCL3L. PCR
results were analyzed using SDS v2.2.1 software package (Applied
Biosystems Inc.). We performed rtPCR for each individual in
triplicate and determined the normalized relative copy number by
generating a standard curve and then normalizing across samples
by the results of the Stat6 control gene and dividing the value
obtained by one of the reference individuals.
Analysis of CCL3L Copy Number Based on Reference
To estimate the absolute CCL3L copy number for each sample
based on the rtPCR results described above, we used two reference
samples: the A431 human cell line and the rhesus genome donor
individual. The A431 cell line was chosen as it has previously been
shown to have two copies of CCL3L1 and two copies of CCL3 pdg
, for a total copy number of four CCL3L using the rtPCR assay
described above. To confirm the CCL3L1 copy number of the
particular A431 cell line culture used here, we performed
florescent in situ hybridization (FISH) of metaphase chromosomes
using the human fosmid probes WIBR2-3688L07 (CCL3L1
specific; green spots on Figure 1A) and WI2-653M1 (chr. 17
single copy control; red spots on Figure 1A). Visualization of the
FISH assay clearly shows that this cell line extract had 2 copies of
The second reference sample was the rhesus macaque genome
donor sample. Copy number of the CCL3L locus for this sample
was determined using whole genome shotgun (WGS) read depth
analysis [24,35]. Read depth analysis was performed by aligning
all fragments of minimum 150 bp of non-repeat masked sequence
to the to the macaque CCL3L1 locus with a 95% identity
threshold. We compared the average depth of WGS sequence
coverage for unique (not-duplicated) sequence in 5kb windows
with the depth of coverage to the CCL3L1 locus to estimate copy-
number of the locus (Figure 1B). The experiment was repeated
using the human CCL3L locus as a reference with an 88% identity
threshold (results not shown). From these analyses, we predicted
CCL3L CNV and SIV progression in M. mulatta
PLoS Genetics | www.plosgenetics.org8 January 2009 | Volume 5 | Issue 1 | e1000346
the CCL3L copy number for the genome donor macaque to be 6–8
copies of CCL3L pdg depending on whether the rhesus or human
genome is used for alignment. The difference in estimated copy
number between the alignment to the rhesus genome and that of
the human genome is likely due to alignment of non-CCL3L genes.
Due to this, alignment to the rhesus genome is likely a better
predictor of CCL3L copy number for this individual because it is
less likely to include non-CCL3-like gene paralogs.
We determined the absolute CCL3L copy number in each
sample by comparing rtPCR results between samples and the
references. Specifically, the normalized rtPCR values were
averaged across the three replicates for each individual and
divided by the averaged rtPCR results for one of the reference
samples and multiplied by 4 (the diploid copy number of the A431
cell line including CCL3L1 and CCL3) or 7 (the average diploid
copy number of the rhesus macaque donor individual). The
resulting number was then rounded to the nearest integer value to
estimate absolute copy number. In Figure S1, we report the
calibration curves for the A431 reference samples and demarca-
tion of inferred copy number pdg for each sample. All statistical
analyses were conducted using the rounded as well as the raw
Confirmation of rtPCR CCL3L Copy Number Estimate
To confirm that the rtPCR absolute copy number estimates
were accurate we estimated CCL3L copy number for an additional
rhesus macaque cell line using both rtPCR and interphase FISH
(Figure 1C). The rtPCR estimated diploid copy number for this
macaque cell line is 9 using either reference sample. The estimated
CCL3L copy number from the FISH experiment is 10.3463.00
(mean6standard error based on 54 replicate FISH experiments).
The slight discrepancy between the rtPCR and FISH is likely due
to the fact that the FISH probe used contains other, known,
structural variants which show higher copy number in the
macaque reference genome (visible in WGS read depth analysis
see Figure 1C). As well, the proximity of the CCL3L gene copies
renders it difficult to distinguish distinct copies in some of the
Primers in Additional Species
The same rtPCR primers and probe were used in all primate
species. These primers are not specific to the other species and
differences in both the chimpanzee and human reference priming
sequences were observed. We note that at the time of this study no
reference sequences were available for the sooty mangabey or the
African green monkey on which to design species-specific probes.
While this may lead to slight biases in the determination of the
absolute copy number for any particular individual or species, it
does not effect the overall conclusions of the study that all species
surveyed show population level variation in copy numbers.
All statistical analysis was conducted using the R statistics
package. Significance of copy number differences between Indian-
origin and Chinese-origin populations of SIV and non-SIV
infected rhesus macaque was evaluated using a Mann-Whitney
U test. Survival analyses of the SIV infected macaque data were
conducted using the survival package in R.
The Cox proportional hazard model was chosen, as it is a
flexible semi-parametric regression model that accounts censored
data. Let i=1…n index individuals and j=1…p index variables of
the regression model. The Cox proportional hazard rate of
individual i at time t has the form:
hi t ð Þ~h0t ð Þ exp
where h0(t) is the base line hazard function, the xij’s for j=1…p are
the covariates for individual i, and the bj’s are regression
coefficients. An underlying assumption of this model is that the
covariates act additively on the log of the hazard function and that
the log hazard function changes linearly with the b terms. These
are referred to as the proportionality assumptions. We tested this
assumption using the method proposed by Grambsch and
Therneau  as implemented in the survival package in R
and found that the assumption holds for these data. It is important
to note that there no assumption is made regarding the functional
form of base line hazard function h0(t). The reason for this is that
our object of analysis is the proportional hazards among individuals
that at time t are independent of h0. For example, considering a
pair of individuals i and i9, the hazard ratios are:
hit ð Þ
hi’t ð Þ~
The model parameters b1…bpare estimated given the ranked
observed failure times y1,y2,…,ynusing the partial likelihood
method proposed by Cox  as implemented in the coxph
function in R. Since some data are censored, we introduce n9 to
denote the number of uncensored observations. The partial
likelihood is given by:
L b yi,:::,yn
Four models are considered; m0, which includes no covariates;
m1, which includes only CCL3L copy number as a potential
covariate; m2, which considers only population-of-origin as a
factor, and m3, which considers both CCL3L copy number and
population of origin. To choose among nested regression models
for the SIV infected macaque survival data, we used twice the
difference in log-likelihood and assessed significance using
The Harrington and Fleming procedure was used to assess
differences among Kaplan-Meier survival curve. This method was
also implemented in the survdiff function of the R survival
package. All analysis labeled ‘‘stratified’’ were conducted by
including the term strata(origin) in the right hand side of the
regression equation where origin is an indicator variable of
Chinese-origin (i.e., 1 if Chinese, 0 if Indian). The survfit
routine to generate predicted Kaplan-Meir survival curves as a
function of CCL3L copy number and population-of-origin. All R
scripts used for analysis and production of figures are available
from the investigators upon request.
line as a standard. Since the A431 cell line has four copies of
Calibration curve for rtPCR assay using A431 cell
CCL3L CNV and SIV progression in M. mulatta
PLoS Genetics | www.plosgenetics.org9 January 2009 | Volume 5 | Issue 1 | e1000346
CCL3L (see Figure 1A), CCL3L copy number is inferred as the
relative rtPCR level for a sample, multiplied by 4 and rounded to
the nearest integer. Each color represents a transition in copy
number variation call (i.e., the break between 5 copies and 6
copies is denoted by a transition of red to green, and the break
between 6 and 7 copies by a transition from green to dark blue).
Found at: doi:10.1371/journal.pgen.1000346.s001 (0.81 MB TIF)
the 53 microsatellite loci sorted by assumed population. Red are
Indian origin animals and blue are Chinese origin animals.
Found at: doi:10.1371/journal.pgen.1000346.s002 (1.07 MB TIF)
Structure results of the retrospective individuals from
Indian origin and blue are Chinese origin. (A) Box-plot of PC1
values. (B) Bi-plot of PC1 vs. PC2 showing distinct clustering of
animals into proper sub-populations.
Found at: doi:10.1371/journal.pgen.1000346.s003 (1.19 MB TIF)
PCA results for the retrospective sample. Red are
sample based on 53 unlinked microsattelite loci. (A) Pearson
product-moment correlation of genotypic state for all individuals
in the sample; (B) Queller-Goodnight r distance between pairs of
individuals in the Indian-origin sample; (C) QG distances for
individuals in the Chinese-origin sample.
Found at: doi:10.1371/journal.pgen.1000346.s004 (4.89 MB TIF)
Heat plots summarizing genetic relatedness in the
distribution from the 53 unlinked microsatellites versus that
expected under a uniform distribution. (B) Histogram of the
2log10 p-values from the microsatellite data with arrow showing
the position of the p-value for the association with log2 CCL3L
copy number and survival.
Found at: doi:10.1371/journal.pgen.1000346.s005 (1.00 MB TIF)
(A) Quantile-Quantile plot of the empirical p-value
proportional hazard regression of survivorship on CCL3L copy
number applied to each population separately.
Found at: doi:10.1371/journal.pgen.1000346.s006 (0.57 MB TIF)
Bootstrap simulations to assess power of Cox
Cox Proportional hazard model of post-SIV survivorship includ-
ing CCL3L copy number and population-of-origin as covariates.
Predicted Kaplan-Meier survival curves based on
Dashed lines indicate 95% prediction intervals based on
application of the function survfit in the survival R package.
Found at: doi:10.1371/journal.pgen.1000346.s007 (0.88 MB TIF)
Found at: doi:10.1371/journal.pgen.1000346.s008 (0.06 MB PDF)
Results of necropsy results for 57 animals used in the
probe/individual for CCL3L rtPCR assay. CH1 and CH2 are two
macaque individuals of Chinese origin. IN1 and IN2 are Indian-
Found at: doi:10.1371/journal.pgen.1000346.s009 (0.04 MB PDF)
Total number of polymorphic sites found per primer/
tion among primate species and populations.
Found at: doi:10.1371/journal.pgen.1000346.s010 (0.05 MB PDF)
Summary statistics for CCL3L copy number distribu-
retrospective sample, and heterozygosity for the 53 typed
Found at: doi:10.1371/journal.pgen.1000346.s011 (0.04 MB PDF)
Microsatellite id, number of alleles found in the
primers and probes, analysis of microsatellite data, and power
Found at: doi:10.1371/journal.pgen.1000346.s012 (0.05 MB
Additional methods describing validation of rtPCR
We would like to thank the Yerkes National Primate Research Center,
Baylor Human Sequencing Center, UCLA National Primate Research
Center and the Tulane National Primate Research Center for providing
DNA samples and tissues. We would also like to thank A. Boyko, K.
Lohmueller, A. Stevenson, and several anonymous reviewers for useful
comments on earlier drafts of this manuscript.
Conceived and designed the experiments: JDD. Performed the experi-
ments: PdC AC SS LH ZJ MV. Analyzed the data: JDD EEE CDB.
Contributed reagents/materials/analysis tools: BL MH REP MK EEE JR
PM YG. Wrote the paper: JDD YG CDB.
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