A quantitative trait locus for variation in dopamine
metabolism mapped in a primate model using
reference sequences from related species
Nelson B. Freimer*†‡§, Susan K. Service*, Roel A. Ophoff*†‡¶, Anna J. Jasinska*, Kevin McKee?, Amelie Villeneuve**,
Alexandre Belisle**, Julia N. Bailey†‡, Sherry E. Breidenthal†‡, Matthew J. Jorgensen†‡, J. John Mann††, Rita M. Cantor‡‡,
Ken Dewar?**§§, and Lynn A. Fairbanks†‡
*Center for Neurobehavioral Genetics,†The Jane and Terry Semel Institute for Neuroscience and Human Behavior, Departments of‡Psychiatry and
Biobehavioral Sciences and‡‡Human Genetics and Pediatrics, David Geffen School of Medicine,University of California, Los Angeles, CA 90095;
¶Department of Medical Genetics and Rudolf Magnus Institute, University Medical Center, 3584CG, Utrecht, The Netherlands;?Research
Institute of the McGill University Health Centre, **McGill University and Ge ´nome Que ´bec Innovation Centre, and§§Departments
of Human Genetics and Experimental Medicine, 740 Dr-Penfield Avenue, Montreal, PQ, Canada H3A 1A1; and††Division of
Neuroscience, Department of Psychiatry, Columbia University, New York State Psychiatric Institute, New York, NY 10032
Communicated by David E. Housman, Massachusetts Institute of Technology, Cambridge, MA, August 13, 2007 (received for review May 1, 2007)
Non-human primates (NHP) provide crucial research models. Their
strong similarities to humans make them particularly valuable for
understanding complex behavioral traits and brain structure and
function. We report here the genetic mapping of an NHP nervous
system biologic trait, the cerebrospinal fluid (CSF) concentration of
the dopamine metabolite homovanillic acid (HVA), in an extended
inbred vervet monkey (Chlorocebus aethiops sabaeus) pedigree.
CSF HVA is an index of CNS dopamine activity, which is hypothe-
sized to contribute substantially to behavioral variations in NHP
and humans. For quantitative trait locus (QTL) mapping, we carried
out a two-stage procedure. We first scanned the genome using a
first-generation genetic map of short tandem repeat markers.
Subsequently, using >100 SNPs within the most promising region
identified by the genome scan, we mapped a QTL for CSF HVA at
a genome-wide level of significance (peak logarithm of odds score
>4) to a narrow well delineated interval (<10 Mb). The SNP
discovery exploited conserved segments between human and
rhesus macaque reference genome sequences. Our findings dem-
onstrate the potential of using existing primate reference genome
sequences for designing high-resolution genetic analyses applica-
ble across a wide range of NHP species, including the many for
which full genome sequences are not yet available. Leveraging
genomic information from sequenced to nonsequenced species
should enable the utilization of the full range of NHP diversity in
behavior and disease susceptibility to determine the genetic basis
of specific biological and behavioral traits.
comparative genomics ? genetic mapping ? homovanillic acid ? vervet
opment, degeneration, and structure of the human brain and the
biological basis of human behavior. Like humans, NHPs expe-
rience a prolonged period of postnatal development, together
with strong family ties and complex social relationships. Fur-
thermore, most features of human behavior have recognizable
counterparts in NHPs, enabling the examination of traits such as
anxiety and impulsivity, which are central components of human
behavioral disorders. The pronounced interindividual variability
observed in such traits within pedigreed primate colonies has
stimulated interest in identifying genetic variants associated with
these variable traits.
There are several advantages in genetically investigating be-
havior-related traits in NHPs compared with humans. It is
feasible to assess systematically a given trait in all members of
large multigenerational NHP pedigrees, providing power to
detect genetic variants of relatively small effect. It is also possible
to obtain measures related to brain structure and function in
he genetic investigation of non-human primates (NHPs) has
the potential to generate enormous insights into the devel-
NHPs that would be infeasible to collect in human subjects;
examples include brain sampling for measurement of gene
expression patterns or cerebrospinal fluid (CSF) samples, as in
the current study. Perhaps most importantly, although studies of
humans must account for uncontrolled and unmeasured envi-
ronmental variation and gene-environment correlations that can
bias or obscure genetic effects on complex traits (1), captive
NHP populations provide the opportunity to control and ma-
nipulate the environment, independent of genotype (2).
The limited DNA sequence divergence between higher pri-
mates has permitted the generation of genome-wide genetic
linkage maps in widely investigated Old World monkey (OWM)
species, including rhesus macaques, baboons, and vervets, based
on the adaptation of human short tandem repeat (STR) se-
quences (3–6). The availability of these maps has in turn spurred
genetic mapping studies of complex traits in these OWMs. Such
studies are further facilitated by the availability of genome
resources, such as BAC libraries, which are now available for at
least 18 primate species (http://bacpac.chori.org), and the refer-
ence genome sequences of human, chimpanzee, and rhesus
(7–9), which permit comparative genomic analyses.
The relative genetic homogeneity of some captive NHP pop-
ulations, as exemplified by the Vervet Research Colony (VRC)
at the University of California, Los Angeles, is another factor
spurring interest in using such populations for genetic mapping
of complex traits. Vervets, also called African green monkeys,
are among the most widely dispersed OWMs, inhabiting much of
subSaharan Africa. In the 1600s, a small number of vervets
colonized the Caribbean islands of St. Kitts, Nevis, and Barba-
dos, as travelers on ships involved in the African slave trade (10).
This emigration marked the first bottleneck of the ancestral
VRC population. Vervets adapted well to the environment of
the West Indies, and their populations grew rapidly absent any
non-human predators. The current VRC population (?500
Author contributions: N.B.F., R.A.O., M.J.J., K.D., and L.A.F. designed research; A.J.J., A.V.,
A.B., J.N.B., S.E.B., M.J.J., J.J.M., and L.A.F. performed research; S.K.S., K.M., J.N.B., R.M.C.,
and L.A.F. analyzed data; and N.B.F., S.K.S., A.J.J., R.M.C., K.D., and L.A.F. wrote the paper.
The authors declare no conflict of interest.
Freely available online through the PNAS open access option.
Colony; MA, monoamine; HVA, homovanillic acid; 5-HIAA, 5-hydroxyindolacetic acid;
MHPG, 3-hydroxy-4-methoxyphenylglycol; CSF, cerebrospinal fluid; STR, short tandem
repeat; QTL, quantitative trait locus; lod, logarithm of odds.
§To whom correspondence should be addressed. E-mail: email@example.com.
This article contains supporting information online at www.pnas.org/cgi/content/full/
© 2007 by The National Academy of Sciences of the USA
October 2, 2007 ?
vol. 104 ?
no. 40 ?
individuals) descends from 57 wild-caught vervets (29 females
and 28 males) trapped on St. Kitts between 1975 and 1987, with
24 of the original matrilines now in their third to eighth
generations. The founding of the VRC represented a second
bottleneck for this population (11). The VRC vervets can be
connected into one large inbred pedigree (see Methods).
Several heritable behavioral traits have been assessed over
multiple generations within the VRC pedigree, including mea-
sures of impulsivity, aggressiveness, and anxiety that are assessed
in a social challenge test (12). In addition to such heritable
behaviors, the VRC pedigree has been phenotyped for biochem-
ical measures that correlate with behavioral traits, such as
cisternal CSF levels of the dopamine, serotonin, and norepi-
nephrine metabolites homovanillic acid (HVA), 5-hydroxyin-
dolacetic acid (5-HIAA), and 3-hydroxy-4-methoxyphenylglycol
(MHPG), respectively (12, 13). These measures are markers for
monoamine (MA) turnover in the CNS (14), which is centrally
important in behavioral neuroscience and psychiatry, because
most commonly used psychotropic drugs alter one or more MA
systems (15, 16).
Natural variation in levels of 5-HIAA, in cisternal CSF of
vervets (and other OWM) has been associated with impulsive,
aggressive, and risk-taking behavior (13, 17–20). Levels of HVA
have been related to aggressive behavior, wounding, sexual
23). Numerous studies suggest associations between CSF MA
metabolite concentrations and various human behavioral disor-
ders (15, 24, 25), but other than relationships of CSF 5-HIAA to
suicidal and aggressive behaviors (26), these associations remain
mostly equivocal and nonreplicated, in part because of the
difficulty in obtaining CSF from sufficient human subjects. In
addition, human studies, in contrast to those in NHPs, rely on
lumbar CSF, which may less accurately reflect brain MA levels
than cisternal CSF (27).
There is much stronger evidence for the heritability of MA
metabolite levels in NHPs than in humans, presumably because
of the small sample sizes available for human studies. In humans,
a relatively small twin study (28) demonstrated high heritability
for MHPG (h2? 0.74) but could not find unequivocal herita-
bility for the other metabolites. Significant genetic contributions
to variation in HVA and 5-HIAA have been observed in rhesus
macaques, in comparisons of sire families (29, 30). A study of 271
captive baboons in multigenerational pedigrees showed clear
heritability of all three of the CSF MA metabolites measured
[5-HIAA, h2? 0.30 (SE 0.17); MHPG, h2? 0.36 (SE 0.16); and
HVA, h2? 0.50 (SE 0.19) (31)]. Several studies in humans have
found only nominal associations between CSF levels of MA
metabolites and variants in hypothesis-based candidate genes
(32–34). In this study, we demonstrate the heritability of these
metabolites within the VRC pedigree and genetically map a
quantitative trait locus (QTL) for HVA. We hypothesize that
identification of sequence variants associated with HVA level in
vervets may permit more precise delineation of the relationship
between dopamine systems and a wide range of behavioral
MA Metabolites in CSF in VRC Pedigree Samples.Theconcentrations
of MA metabolites in the CSF of 347 vervets from the VRC are
shown in Table 1. Each of these metabolites is heritable in this
pedigree, with HVA displaying the highest estimated narrow
sense heritability (Table 1). The mean levels of all three MA
metabolites were higher in females than in males. HVA and
5-HIAA levels declined with age, whereas MHPG increased
with age. There was a significant interaction between age and sex
and mean levels of 5-HIAA and MHPG, but not HVA.
The predicted level of HVA for an individual vervet in the
VRC was estimated to be HVApredicted ? ?0.17 ?
0.38F?0.18(A?5.4), where F takes the value 1 if the individual
is female and 0 if male, and A is the observed age category for
the individual (age category is centered by subtracting the mean
age category of 5.4 from the observed category for an individual;
see Methods for more details of these categories).
The predicted level of 5-HIAA for an individual vervet in the
VRC was estimated to be 5-HIAApredicted ? ?0.10 ?
0.10F?0.34(J?1.8) ? 0.69F(J?1.8), where F takes the value 1 if
the individual is female and 0 if male, and J takes the value 1 for
a juvenile and 2 for an adult (the juvenile/adult age category is
centered by subtracting the mean of 1.8 from the observed
category for an individual). The interaction between sex and age
resulted in higher predicted levels of 5-HIAA for adults than for
juveniles and for female but not males.
The predicted level of MHPG for an individual vervet in the
VRC was estimated to be MHPGpredicted? ?0.44 ? 0.59F ?
value 1 if the individual is female and 0 if male, and A is the
observed age category for the individual (age category is cen-
tered by subtracting the mean age category of 5.4 from the
observed category for an individual). The interaction between
sex and the square of age category resulted in lower predicted
Genome Scan for QTL. Given the significant heritability estimates
for MA metabolites in the VRC, we undertook a genome scan
to identify QTL for these metabolites, using 324 markers from
the vervet scaffold autosomal genetic map (6). Two-point anal-
ysis using the quantitative trait variance component linkage
analysis program SOLAR (35) revealed suggestive linkage of
HVA levels to two markers that are separated from one another
by ?13 cM (and ordered with odds of ?1,000:1) on vervet
chromosome 9p (Fig. 1, D10S585, logarithm of odds (lod) score
of 2.3, accounted for 26% of heritable trait variance in HVA and
D10S1477, lod score of 1.9, accounted for 24% of heritable trait
variance [see supporting information (SI) Dataset 1 for more
complete marker orders in this region]. An additional marker
from this region (D101779) showed much weaker evidence for
linkage but is not as well ordered and displays a lower observed
heterozygosity compared with the former two markers. No lod
scores ?2 were observed for 5-HIAA and MHPG; therefore, we
focused our mapping efforts on the QTL for HVA. Complete
QTL results for all of the MA metabolites are in SI Dataset 1.
Table 1. Distribution and estimated heritability of CSF MA metabolite levels of VRC vervets
Mean (?SD), pmol/mlRange Kurtosis Significant covariates
Sex, age*0.52 (0.11)
P ? 1.4 ? 10?9
P ? 2.3 ? 10?6
P ? 8.3 ? 10?6
Sex, ageb‡, ageb ? sex
Sex, age, age2sex ? age2
*Age, age in years categorized as 3, 3–4, 4–5, 5–6, 6–10, 10?.
†P value testing the null hypothesis that h2? 0.
‡Ageb, age categorized as adolescent (3–4) or adult (5?).
www.pnas.org?cgi?doi?10.1073?pnas.0707640104Freimer et al.
Generation of SNPs for Fine Mapping the HVA QTL. To provide
support for the linkage signal and to better define the QTL, we
performed high-resolution genotyping of the same vervets with
additional markers from the QTL region of vervet chromosome
9p. We did not identify any additional human STR markers that
map to this chromosomal region, that could be amplified in
vervet, and that are polymorphic in the VRC. Therefore, we
reasoned that high-resolution mapping could be best achieved by
identifying and typing large numbers of vervet SNPs. Because
there is no vervet reference genome sequence, we used human
and rhesus genome assemblies to drive vervet SNP discovery
(Fig. 2). We first aligned the orthologous human and rhesus
genomic sequences to identify invariant sequences. We hypoth-
esized that these invariant sequences would also be conserved in
vervet and thus could be used for SNP discovery PCR amplicon
design, because (i) rhesus and vervet are members of the same
subfamily (Cercopithecinae), and both are about equidistantly
related to humans; (ii) our genetic map construction had shown
a very high degree of conservation of marker orders between
vervet and rhesus throughout the genome (6); and (iii) vervet
chromosome 9p collinearity was further supported by paired
BAC end sequence analysis.
to enrich for successful primers, which could be used to amplify
regions potentially harboring vervet SNPs. The analysis of the
proximal 35 Mb of human chromosome 10 and its orthologous
region in rhesus yielded 70,076 segments of at least 50 consec-
utive nucleotides showing 100% identity between human and
rhesus. Of these segments, we observed 33,381 cases where the
neighboring invariant primer sites were separated by 100–600 nt
of polymorphic sequence. The largest distance between these
candidate amplicon sites (invariant primer, polymorphic se-
quence, and invariant primer) was ?70 kb, indicating we could
design PCR assays for SNP discovery at high resolution across
the entire region. We generated amplicons in a hierarchical
manner by designing assays in 24 clusters where each cluster was
separated by an average physical distance of 1.25 Mb. At each
cluster, four independent assays were designed, where each assay
of ?50 kb. Each assay was analyzed for sequence polymorphism
on a test set of four to six unrelated vervet monkeys. In total, we
identified 105 SNPs, which were then genotyped in all animals
for which data on HVA levels were available.
Fine-Mapping Analyses. As with the original scan, the size and
complexity of the VRC pedigree precluded multipoint analyses,
and thus only two-point QTL analyses for HVA were conducted
on the 105 SNPs (Fig. 2); two SNPs, DHs36-12 and DHs48-08-6,
These SNPs accounted for 60% and 56% of HVA heritable trait
variance, respectively. Within this QTL, seven markers showed
RefSeq database. Most of the SNPs that did not provide
evidence for linkage of HVA to this region were uninformative
in the VRC sample.
CSF HVA concentration exemplifies a behavior-related trait,
amenable to genetic investigation in NHPs but difficult or
impossible to study in large human samples because of the
invasiveness of the sampling that is required. With a large NHP
pedigree, we were able to first identify suggestive linkage, using
the vervet STR map, and then, using SNPs, identify a well
delineated QTL for this trait on vervet chromosome 9, syntenic
with human chromosome 10p. This QTL exceeds the genome-
wide threshold for significance in a two-stage linkage study (36).
Linkage has been observed for human disorders in the region
on human chromosome 10 syntenic to the vervet HVA QTL
region, including traits hypothesized to involve abnormalities of
dopamine systems, such as schizophrenia and bipolar disorder
(37). There are no obvious candidate genes within the HVA
QTL, based on the criterion of a known direct involvement in
dopamine metabolism, but several genes in this region could
contribute to pathways involved in its regulation. The peak of the
QTL (between SNPs DHs36-12 and DHs48-08-6, at locations
10.5 and 14.4 Mb, respectively) includes genes for huntingtin-
interacting protein, optineurin, which contributes to metabo-
tropic glutamate receptor desensitization (38), and CUGBP2.
The latter gene regulates alternative splicing of several known
● ● ● ●● ●●●
● ● ● ● ● ● ● ● ●
● ● ●
● ● ●
● ● ●
● ● ● ●
0 1 2 3 4
Position in Mb in Human
SNP Low Homozygosity
SNP High Homozygosity
of the marker, in megabases, taken from the human physical map, and on the vertical axis is the lod score for the test of the null hypothesis that a QTL is at a
given position. SNPs with low observed homozygosity (?75% of vervets homozygous) are indicated with open circles, SNPs with high observed homozygosity
contained both informative and noninformative markers, indicating that the lack of a linkage signal in these regions was not likely because of a lack of
Mapping of the HVA QTL. lod scores for SNP and STR markers in the putative QTL region on vervet 9p are shown. On the horizontal axis is the position
Freimer et al. PNAS ?
October 2, 2007 ?
vol. 104 ?
no. 40 ?
CNS targets (39), and among its putative targets is frequenin
(FREQ or neuronal calcium sensor 1 gene, NCS-1) (40), which
inhibits dopamine-induced D2 receptor internalization (41).
GATA3, located ?2.3 Mb telomeric to SNP DHs36–12 partic-
ipates in transcriptional regulation of serotonergic neuron dif-
ferentiation in caudal raphe nuclei (42) and transactivation of
genes involved in peripheral MA metabolism (43).
Most of the HVA QTL region overlaps an ?3-Mb gene desert
between GATA3 and CUGBP2, which, in addition to one locus
for a hypothetical protein, contains three evolutionary con-
served regions (minimum of 200 bp with ?99% identity between
human and rodents; http://ecrbrowser.dcode.org) and a genomic
element in which evolution was accelerated in the human lineage
(44). These observations suggest that this gene-poor region
RNA or for a cis-acting regulator involved in expression of more
The mapping results reported here do not preclude other loci
playing a role in HVA. Similarly, although neither the analysis
of MHPG and 5-HIAA nor the analysis of ratios of the various
MA measures gave significant QTL results, additional genetic-
mapping studies of these traits may be warranted either through
linkage analysis of an expanded pedigree sample or through
association analyses of independent vervets once sufficient
mapped SNPs are available.
The two-stage mapping strategy used here succeeded despite
the complexity of the pedigree structure and extensive inbreed-
ing (45) in the VRC, which made multipoint linkage analysis
unfeasible, and our initial fine-mapping strategy based on clus-
tering of closely spaced SNPs to form multialleic ‘‘supermark-
ers’’ impractical. However, our success using two-point analyses
suggests that the power of very extended pedigrees such as the
VRC may be sufficient for QTL analyses more generally, pro-
viding that one can identify and genotype a large number of
SNPs. As we observed (Fig. 2), with enough SNPs, some of them
will be reasonably informative within such a pedigree, even while
most of the markers typed display low heterozygosity and thus
generate little information regarding linkage.
We hypothesize that the combination of the demographic
history and the size and structure of the VRC pedigree enabled
us to obtain significant linkage evidence for HVA with a high
locus-specific heritability. Linkage analysis in extended NHP
pedigrees may be a powerful alternative to genome-wide asso-
ciation analysis for mapping behavior-related QTL. Further-
more, the world-wide availability of samples of independent
NHPs, suggests that for many behavior-related traits, it may be
possible to conduct association analyses with densely spaced
SNPs, to identify the variants contributing to the QTL. For
example, such a strategy can be pursued for HVA using CSF
samples collected from independent vervets living on St. Kitts.
The mapping of complex behavior-related traits in NHPs has
been hampered by a combination of insufficient genetic markers
and phenotyping on too few samples. In this report, we describe
a method to generate additional genetic markers in a focused
manner. Not only can we target specific genomic regions, but we
can also develop markers at a desired density and spacing. Our
comparative approach used cross-species sequence alignments
for three purposes: to identify invariant sequences as a guide for
primer design, to identify polymorphic sequences as a guide for
SNP discovery, and to use BAC paired end sequences as a guide
that SNPs could be used successfully to reproduce and refine
alignments and inferred BAC clone orthologous relationships are also shown. A total of 315 BAC clones displaying appropriate end sequence orientations and
four clones (in red) with one end aligning to human chromosome 10 and the other to human chromosome 19 (in red); three clones with both ends aligning to
and two clones (in red) with one end aligning to human chromosome 10 and the other to a different human chromosome. Vervet-mapping STRs are presented
in black, and the positions of SNP clusters are shown in red. Known genes are shown in a dense format, highlighting the scarcity of known genes in the
D10S1779–D10S585 interval within the area of significant linkage.
Vervet and human genome collinearity. The 15-Mb human region (hg18 chr10:5,000,000–20,000,000) encompassing to the area of highest lod scores
www.pnas.org?cgi?doi?10.1073?pnas.0707640104Freimer et al.
STR-based mapping results, and that a targeted region in the
vervet genome is expected to show strong synteny and similar
gene content to the orthologous region of humans.
The use of comparative genomics information can also be
applied more broadly to investigate complex traits in other NHP
species. Just as we used the rhesus genome assembly as a
surrogate for the vervet, it should be equally applicable for other
OWM. Outside of the OWM, the reference genomes of a small
set of key species could similarly act as references for each entire
clade. Alternatively, a species lying at the base of the primate
phylogenetic tree could be used as the reference for the entire
order. To illustrate this possibility we examined alignments of
gray mouse lemur (Microcebus murinus) genomic sequence to
human across a 1.6-Mb segment of the Encode ENm001 region
(human hg18: chr7:115,597,757–117,475,182). If this region is
representative of these two genomes, we calculate it would be
feasible to produce amplicons at an average spacing of 50 kb,
with 94% of amplicons being separated from each other by ?200
kb. This amplicon set could thus support SNP discovery and
high-resolution analysis for virtually all NHPs.
Our study also provides evidence of a very high degree of
genome collinearity between vervet and human. This observa-
tion further supports presumptions of marker order and spacing
based on the reference genome, especially because large rear-
rangements can be subsequently identified after genotyping and
genetic mapping. It also accelerates candidate gene analysis,
because the reference genome gene set likely represents the vast
majority of genes in the region in the species of interest. If
genome collinearity tends to hold true for all NHP species at a
regional scale (1–10 Mb), then generation of SNP markers can
become further simplified to take advantage of massively par-
allel sequencing strategies and an assumption of conserved
marker order. For example, in a currently available scenario, a
single experiment to produce 400,000 reads of 250 bp would
randomly produce sequence reads at an average of 8 kb across
the genome. These sequences could be generated directly from
the species or even individuals of choice. Primer design for
subsequent SNP discovery assays would be simplified, although
the sequences could still be evaluated for evolutionary conser-
vation to enrich for assays flanking polymorphic regions.
Subjects. The VRC vervets can be connected into one large
pedigree. The pedigree used in the current study contained 673
vervets, including 92 ‘‘dummy’’ parents to take the place of
unknown fathers for statistical analysis. Most matings between
vervets in this pedigree resulted in only one offspring; however,
of 363 matings between two known vervets, 70 produced full
siblings. There is extensive inbreeding in the VRC. The average
inbreeding coefficient, the probability that a subject receives two
alleles at a locus that are identical by descent, for the entire
pedigree, is 0.00639. There are 84 individuals with nonzero
inbreeding coefficients, and the average inbreeding coefficient
among this subset is 0.05122 (range: 0.004–0.25). To put these
values in perspective, the average inbreeding coefficient for
children born after 1950 from consanguineous marriages in the
Old Order Amish is 0.012 (46). There are 107 unique fathers in
the pedigree, with an average (range) number of 3.4 (1–11)
mates, and an average (range) number of 4.2 (1–17) offspring.
There are 182 unique mothers in the pedigree, with an average
(range) number of 2 (1–5) mates and an average (range) number
of 2.8 (1–11) offspring. There was an average of 4.7 alleles for
each STR marker (range, 2–10). The average expected heterozy-
gosity for the markers was 0.64 (range, 0.02–0.84). A partial
depiction of the pedigree is included in SI Fig. 3.
MA concentrations were measured in 347 vervet monkeys
(128 males and 219 females), 3–23 years of age, who were
were mother-reared and socially housed in large outdoor cages.
The phenotyped sample includes the following relative pairs:
parent–offspring (n ? 240), full siblings (n ? 45), and half
siblings (n ? 920), in addition to other classes of relative pairs.
to reflect the natural social composition of vervet groups in the
wild. All animals are reared by their mothers in large outdoor
enclosures. Infants and juveniles remain in the natal group with
their mothers and female kin. Males are removed at adolescence
and transferred to other groups, and adult males are rotated
between groups at 3- to 4-year intervals, to mimic natural
processes of emigration and immigration. These policies are
intended to promote normal development and provide oppor-
tunities for animals to express age- and sex-appropriate species-
typical behavior. The maintenance of the population in stable
matrilineal groups allows the study of naturally occurring indi-
and social context that is within the normal range for the species.
CSF Sampling and MA Measurements. These procedures were car-
ried out under a protocol approved by the Animal Research
Committee at University of California, Los Angeles. Animals
were captured and anesthetized with 8–10 mg/kg ketamine
the nape of the neck, the skin was scrubbed with betadine and
isopropyl alcohol, and ?1 cc of CSF was withdrawn from the
cisterna magna, within 30 min of anesthesia.
amber Eppendorf tubes and placed on wet ice. Samples were
centrifuged at 4°C for 15 min at 1,800 ? g to remove blood cells,
and the supernatant was transferred to new amber cryogenic
tubes and frozen at ?80°C. All sample collections were per-
formed between mid-December and mid-March. Two-thirds
(n ? 245) of the animals were sampled in 2 successive years. The
remaining third (n ? 102) was sampled in 1 of the 2 years.
The samples were assayed for MA metabolites by HPLC with
an electrochemical detector (47). A measured aliquot of each
sample was mixed with an equal volume of cold mobile phase,
the mixture was filtered at centrifugation (6,000 ? g for 40 min
at 4°C), and part of the filtrate was transferred to a 300-FL
microinjection insert. This material was then analyzed by HPLC
with electrical detection to allow simultaneous measurement of
HVA, 5-HIAA, and MHPG.
To control for annual variation in the results of the MA
metabolite assays, the data for each year were standardized by
subtracting each subject’s value from the mean and dividing by
the standard deviation for that year. The mean standardized
scores for HVA, 5-HIAA, and MHPG were calculated for the
subjects with data from both years.
Heritability Estimates. The heritability of quantitative CSF phe-
notypes was estimated by using a variance component approach
as modeled in the software package SOLAR (35). Covariates of
sex and age at the time the phenotypes were measured were
included in all analyses, using stepwise regression. For HVA and
MHPG, age was coded as an ordered categorical variable with
6 (vervets born from 1991 to 1994), age categories 5–2 (vervets
born between 1998 and 1995, respectively), and age category 1
(vervets too young for CSF sampling). For 5-HIAA, a binary age
variable was constructed, indicating whether an individual was
juvenile or adult. The analysis of 5-HIAA included an interac-
tion term for sex and age, and the analysis of MHPG included
a term for the age–sex interaction, a term for age category
squared, and a term for the sex and age category squared
interaction. Additive genetic heritability (also called narrow-
sense heritability) of the CSF phenotypes was estimated, using
the pedigree structure and correlation in trait values between
Freimer et al. PNAS ?
October 2, 2007 ?
vol. 104 ?
no. 40 ?
pairs of relatives. No dominance effects were modeled. Exam- Download full-text
ination of plots of the residuals from all models including the
covariates indicated above showed no unusual patterns, and the
distribution of the residuals did not deviate substantially from a
Marker Development and Genotyping. We used the human genome
(hg17 assembly; National Center for Biotechnology Information
build35) and rhesus genome (rheMac2) assemblies and alignments
(available at http://genome.ucsc.edu) to identify invariant se-
quences along human chromosome 10p, syntenic to vervet chro-
mosome 9. Pairs of invariant sequences separated by 100–600 nt of
polymorphic sequence were subjected to primer design criteria to
control for melting temperature and predicted amplicon length.
at ?1.25-Mb intervals along human chromosome 10p. For each
cluster, a window of 25–50 kb was identified for which four
amplicons could be selected, with each amplicon ?5 kb distant
from its neighbor. The 96 amplicons were assayed on genomic
DNAs of four to six unrelated vervet monkeys from the VRC and
subjected to DNA sequencing on both strands.
A set of 114 SNPs were genotyped on 347 vervet monkey
genomic DNAs by using a Sequenom procedure, giving rise to
genotyping data for 105 SNPs from 22 of the 24 clusters. All
genome (hg18 assembly; National Center for Biotechnology
Information build 36.1) to reconfirm marker order and positions.
QTL Mapping. Human STR markers genotyped in the vervet
pedigree had previously been placed in a scaffold genetic map
(6). In these STR data, 455 of the 673 vervets are genotyped for
at least one marker, and in the SNP data, 367 of the 673 vervets
are genotyped. Maximum-likelihood estimates of marker allele
frequencies were calculated by using the SOLAR software,
accounting for relationships among individuals. Conditional
kinship coefficients, estimating the probability of sharing one or
two marker alleles identical by descent, were calculated for each
marker, using the observed genotype data and pedigree struc-
ture. Two-point linkage analysis compared the likelihood of the
at the marker locus was zero against the alternative that it was
not zero. The effects of additional, unmeasured QTL on the
HVA outcome were absorbed into the residual component of
variance. Two-point linkage was performed on 324 autosomal
markers. Complete results are in SI Dataset 1.
We thank Jessica Wasserscheid for physical map bioinformatics and
Gary Leveque and Corina Nagy for BAC end sequencing. This work was
supported in part by National Institutes of Health Grants MH061852 and
RR019963 (to L.A.F.) and RR016300 (to N.B.F.), by Conte Neuro-
science Center Grant 5P50 MH62185 (to J.J.M.), and by funds from the
University of California, Los Angeles, Semel Institute. K.D. is supported
by funding from the National Institutes of Health, Genome Canada, and
Genome Que ´bec.
1. Kendler KS, Baker JH (2006) Psychol Med 19:1–12.
2. Suomi SJ, Higley JD (1991) NIDA Res Monogr 114:291–302.
3. Rogers J, Mahaney MC, Witte SM, Nair S, Newman D, Wedel S, Rodriguez
LA, Rice KS, Slifer SH, Perelygin A, et al. (2000) Genomics 67:237–247.
4. Rogers J, Garcia R, Shelledy W, Kaplan J, Arya A, Johnson Z, Bergstrom M,
Novakowski L, Nair P, Vinson A, et al. (2006) Genomics 87:30–38.
5. Cox LA, Mahaney MC, Vandeberg JL, Rogers J (2006) Genomics 88:274–281.
6. Jasinska AJ, Service SK, Levinson M, Slaten E, Lee O, Sobel E, Fairbanks LA,
Bailey JN, Jorgensen MJ, Breidenthal SE, et al. (2007) Mamm Genome
7. International Human Genome Sequencing Consortium (2004) Nature 431:931–
8. Chimpanzee Sequencing and Analysis Consortium (2005) Nature 437:69–87.
10. McGuire MT (1974) Contributions to Primatology (Karger, Basel), Vol 1.
11. Newman TK, Fairbanks LA, Pollack D, Rogers J (2002) Am J Primatol
12. Fairbanks LA, Newman TK, Bailey JN, Jorgensen MJ, Breidenthal SE, Ophoff
RA, Comuzzie AG, Martin LJ, Rogers J (2004) Biol Psychiatry 55:642–647.
13. Fairbanks LA, Melega WP, Jorgensen MJ, Kaplan JR, McGuire MT (2001)
14. Kaplan JR, Phillips-Conroy J, Fontenot MB, Jolly CJ, Fairbanks LA, Mann JJ
(1999) Neuropsychopharmacology 20:517–524.
15. Castellanos FX, Elia J, Kruesi MJ, Marsh WL, Gulotta CS, Potter WZ, Ritchie
GF, Hamburger SD, Rapoport JL (1996) Neuropsychopharmacology 14:125–
16. Scheepers FE, Gispen-de Wied CC, Westenberg HG, Kahn RS (2001) Neu-
17. Higley JD, Linnoila M (1997) Rec Dev Alcohol 13:191–219.
18. Higley JD, Linnoila M (1997) Ann NY Acad Sci 836:39–56.
19. Fairbanks LA, Fontenot MB, Phillips-Conroy JE, Jolly CJ, Kaplan JR, Mann
JJ (1999) Brain Behav Evol 53:305–312.
20. Mehlman PT, Higley JD, Faucher I, Lilly AA, Taub DM, Vickers J, Suomi SJ,
Linnoila M (1994) Am J Psychiatry 151:1485–1491.
21. Kaplan JR, Manuck SB, Fontenot MB, Mann JJ (2002) Neuropsychopharma-
22. Mehlman PT, Higley JD, Fernald BJ, Sallee FR, Suomi SJ, Linnoila M, (1997)
Psychiatry Res 72:89–102.
23. Howell S, Westergaard G, Hoos B, Chavanne TJ, Shoaf SE, Cleveland A, Snoy
PJ, Suomi SJ, Higley JD (2007) Am J Primatol 69:1–15.
24. Swann AC, Secunda S, Davis JM, Robins E, Hanin I, Koslow SH, Maas JW
(1983) Am J Psychiatry 140:396–400.
25. Roy A, Pickar D, Linnoila M, Doran AR, Paul SM (1986) Arch Gen Psychiatry
26. Sher L, Oquendo MA, Li S, Huang Y, Grunebaum MF, Burke AK, Malone
KM, Mann JJ (2003) Neuropsychopharmacology 28:1712–1719.
27. Blennow K, Wallin A, Gottfries CG, Månsson J-E, Svennerholm L (1993)
J Neural Trans 3:1435–1463.
28. Oxenstierna G, Edman G, Iselius L, Oreland L, Ross SB, Sedvall G (1986)
J Psychiatr Res 20:19–29.
29. Higley JD, Thompson WW, Champoux M, Goldman D, Hasert MF, Kraemer
GW, Scanlan JM, Suomi SJ, Linnoila M (1993) Arch Gen Psychiatry 50:615–
30. Clarke AS, Kammerer CM, George KP, Kupfer DJ, McKinney WT, Spence
MA, Kraemer GW (1995) Biol Psychiatry 38:572–577.
31. Rogers J, Martin LJ, Comuzzie AG, Mann JJ, Manuck SB, Leland M, Kaplan
JR (2004) Biol Psychiatry 55:739–744.
32. Jonsson EG, Nothen MM, Gustavsson JP, Neidt H, Bunzel R, Propping P,
Sedvall GC (1998) Psychiatry Res 79:1–9.
33. Jonsson EG, Bah J, Melke J, Abou Jamra R, Schumacher J, Westberg L, Ivo
R, Cichon S, Propping P, Nothen MM, et al. (2004) BMC Psychiatry 4:4.
34. Bennett AJ, Lesch KP, Heils A, Long JC, Lorenz JG, Shoaf SE, Champoux M,
Suomi SJ, Linnoila MV, Higley JD (2002) Mol Psychiatry 7:118–122.
35. Almasy L, Blangero J (1998) Am J Hum Genet 62:1198–1211.
36. Kruglyak L, Daly MJ (1998) Am J Hum Genet 62:994–996.
37. Wildenauer DB, Schwab SG, Maier W, Detera-Wadleigh SD (1999) Schizophr
38. Anborgh PH, Godin C, Pampillo M, Dhami GK, Dale LB, Cregan SP, Truant
R, Ferguson SS (2005) J Biol Chem 280:34840–34848.
39. Zhang W, Liu H, Han K, Grabowski PJ (2002) RNA 8:671–685.
40. Faustino NA, Cooper TA (2005) Mol Cell Biol 25:879–887.
41. Kabbani N, Negyessy L, Lin R, Goldman-Rakic P, Levenson R (2002)
J Neurosci 22:8476–8486.
42. van Doorninck JH, van Der Wees J, Karis A, Goedknegt E, Engel JD,
Coesmans M, Rutteman M, Grosveld F, De Zeeuw CI (1999) J Neurosci
43. Lim KC, Lakshmanan G, Crawford SE, Gu Y, Grosveld F, Engel JD (2000) Nat
44. Pollard KS, Salama SR, King B, Kern AD, Dreszer T, Katzman S, Siepel A,
Pedersen JS, Bejerano G, Baertsch R, et al. (2006) PLoS Genet 2:e168.
45. Wijsman EM, Rothstein JH, Thompson EA (2006) Am J Hum Genet 79:846–
46. Khoury MJ, Cohen BH, Diamond EL, Chase GA, McKusick VA (1987) Am J
www.pnas.org?cgi?doi?10.1073?pnas.0707640104Freimer et al.