Copyright ? 2009 by the Genetics Society of America
Genetic Architecture of Tameness in a Rat Model of Animal Domestication
Frank W. Albert,*,1O¨rjan Carlborg,†Irina Plyusnina,‡Francois Besnier,†Daniela Hedwig,*
Susann Lautenschla ¨ger,* Doreen Lorenz,* Jenny McIntosh,* Christof Neumann,*
Henning Richter,* Claudia Zeising,* Rimma Kozhemyakina,‡Olesya Shchepina,‡
Ju ¨rgen Kratzsch,§Lyudmila Trut,‡Daniel Teupser,§Joachim Thiery,§
Torsten Scho ¨neberg,** Leif Andersson†,††and Svante Pa ¨a ¨bo*,‡‡
*Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany,†Department of Animal
Breeding and Genetics, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden,‡Institute of Cytology and Genetics, Siberian
Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia,§Institute of Laboratory Medicine, Clinical Chemistry and
Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany, **Institute of Biochemistry, Molecular Biochemistry,
Medical Faculty, University of Leipzig, 04103 Leipzig, Germany,††Department of Medical Biochemistry and Microbiology,
Uppsala University, Uppsala, Sweden and‡‡Department of Genetics and Pathology, Rudbeck
Laboratory, Uppsala University, 75123 Uppsala, Sweden
Manuscript received February 25, 2009
Accepted for publication April 3, 2009
A common feature of domestic animals is tameness—i.e., they tolerate and are unafraid of human
presence and handling. To gain insight into the genetic basis of tameness and aggression, we studied an
and increased aggression against humans, respectively. We measured 45 traits, including tameness and
aggression, anxiety-related traits, organ weights, and levels of serum components in .700 rats from an
intercross population. Using 201 genetic markers, we identifiedtwo significant quantitative trait loci (QTL)
for tameness. These loci overlap with QTL for adrenal gland weight and for anxiety-related traits and are
part of a five-locus epistatic network influencing tameness. An additional QTLinfluences the occurrence of
whitecoat spots, but shows nosignificanteffectontameness. The loci describedhere are important starting
were domesticated (Troy et al. 2001; Vila et al. 2001;
2007; Eriksson et al. 2008; Naderi et al. 2008). With the
exception of coat color (e.g., Pielberg et al. 2008) and
skin pigmentation (Eriksson et al. 2008), little is known
about what occurred genetically during animal domes-
would-be practitioners of animal husbandry? Although
domestic animals differ from each other in many ways,
they all share the trait of tameness—i.e., they tolerate
and sometimes even seek human presence and han-
dling. Almost nothing is currently known about the
genetic basis of tameness.
NIMAL domestication marked a turning point in
human prehistory (Diamond 2002), and domestic
In a series of studies initiated by D. K. Belyaev,
researchers at the Institute for Cytology and Genetics
in Novosibirsk (Russia) have subjected several mamma-
lian species to a process of experimental domestication
(Trut 1999). These studies, some of them ongoing for
several decades, involve selection for tame and aggres-
sive behavior in lines of animals derived from wild
populations. They include a fox population that has
been ‘‘domesticated’’ to such an extent that the tame
foxes are now similar to dogs in some respects (Hare
et al. 2005). They also include a population of wild-
caught rats (Rattus norvegicus) that was selected for
either reduced or enhanced aggression toward humans
select the animals, their response to an approaching
human hand was observed, and the rats showing the
least and the most aggressive behavior were allowed to
mate within the two lines, respectively. The initial
response to selection was rapid and then slowed, so
that little change in behavior from generation to
generation has been observed in the last 10–15 gen-
erations, although the selection regime has been
continued to the present. Today, the ‘‘tame’’ rats are
completely unafraid of humans, they tolerate handling
1Corresponding author: Max Planck Institute for Evolutionary Anthro-
pology, Evolutionary Genetics, Deutscher Platz 6, 04103 Leipzig,
Germany. E-mail: email@example.com
Genetics 182: 541–554 (June 2009)
and being picked up, and they sometimes approach a
human in a nonaggressive manner. By contrast, the
‘‘aggressive’’ rats ferociously attack or flee from an
approaching human hand.
To study the genetic basis of tameness we have
established populations of both rat lines in Leipzig. In
their new environment, the rats maintained their
behavioral differences in response to humans, and
these differences were not influenced by postnatal
maternal factors (Albert et al. 2008). In addition, the
rat lines differ in a number of other behavioral,
anatomical, and physiological traits, raising the ques-
tion whether these traits are influenced by the same loci
as tameness and aggression toward humans.
Many domestic animals display conspicuous coat
color variations not found in their wild relatives.
Prominent examples include the white color variants
in dogs, pigs, cows, horses, and chickens. In laboratory
rats, it has been proposed that ‘‘coat color genes’’ may
account for many of the differences associated with
domestication (Keeler and King 1942). It is thus
interesting that individuals with white spots appeared
in both the tame foxes (Trut 1999) and the tame rats
(Trut et al. 2000) at higher frequency than in the
corresponding aggressive lines, although they were
absent or rare in the founding fox and rat populations,
and although they were not selected for. The rat
populations studied here provide an excellent oppor-
same loci as white coat spotting.
In this study, we crossed the two rat lines and bred
.700 intercross animals. A broad set of behavioral,
genomewide set of genetic markers was used to identify
genomic regions (quantitative trait loci, QTL) that
influence tameness as well as other traits that differ
between the lines, including white spots.
MATERIALS AND METHODS
Additional materials and methods, as well as data files
containing genotype and phenotype data collected for this
study, can be found in the accompanying supporting in-
formation, File S1 and File S2.
Animals: The tame and the aggressive rat (R. norvegicus)
been bidirectionally selected at every generation since 1972 at
the Institute of Cytology and Genetics at the Siberian Branch
of the Russian Academy of Sciences in Novosibirsk, Russia.
About 30% of the animals from each generation were selected
on the basis of the level of tameness and defensive aggression
they displayed in response to humans on a five-point scale
(Naumenko et al. 1989; Plyusnina and Oskina 1997). In-
breeding was kept at a minimum by avoiding mating closely
The pedigree described in this study was initiated from four
tame and four aggressive individuals (2 females each; the ‘‘F
minus one’’, or ‘‘F?1’’, generation) from the 64th generation
of selection. The F?1animals did not have common parents
and at most one common grandparent. They were mated
within line to yield 11 (5 tame and 6 aggressive rats, one male
each) F0animals. These were crossed reciprocally, and six
hybrid F1males were repeatedly mated to 37 F1females to
produce 733 F2rats (383 females). A separate set of 47 F1
animals (25 females) derived from different F0crosses was
used for characterizing the F1generation in behavioral tests.
Phenotypic data from F0animals discussed in this article are
the same as presented in Albert et al. (2008). Animals were
maintained under standard laboratory conditions, under an
artificial 12-hr light cycle (lights off at 1:00 pm). The light cycle
allowed behavioral testing during the dark phase, when rats
are more active. Cages were equipped with sliding doors to
allow for transfer without handling. During all caretaking
generations were treated identically. The study was approved
by the regional government of Saxony (TVV Nr. 29/05).
Behavioral testing: F2rats were tested in a standardized
series of behavioral paradigms. We measured the animals’
level of tameness/aggression with the ‘‘glove test,’’ by con-
fronting themwith an approachinghumanhandandattempt-
ing to handle them (see Albert et al. 2008 for details on the
testing procedure). Beginning 2 weeks after the glove test, rats
performed an open-field test, a light–dark test, and a startle
response test, which provide various measures of exploratory
performed a second glove test trial. F1rats were tested once
with the glove test at 12–14 weeks of age and then followed the
testing schedule described in Albert et al. (2008). All tests
were performed with minimal handling following procedures
described in Albert et al. (2008). Glove test trials were
videotaped and later analyzed by two independent observers
(5% of trials only by one observer). Experimenters and
data processing. A set of 11 behaviors (e.g., ‘‘attack’’ or
‘‘tolerate handling’’) was scored (see Albert et al. 2008 for
detailed descriptions of the behaviors), and each score was
converted to a numeric measure (e.g., ‘‘number of occurren-
ces’’ or ‘‘duration in seconds’’; Table 1).
Blood and tissue sampling: Dissections were performed on
733 F2(383 females) and 37 F1animals (16 females). Within
2 weeks after the last behavioral test, animals were killed
between 2:00 and 6:00 pm. F2animals had been starved for 24
hr prior to dissection. Animals were weighed, anesthetized
with CO2, and killed by cervical dislocation. Blood was
collected rapidly after death by heart puncture and separated
into serum and blood cells by centrifugation 30 min after
sampling. Serum was stored at ?20? and later transferred to
?80? until analysis. Liver (small section, not weighed), spleen,
kidney, adrenal gland, lung, and heart were removed rapidly,
weighed, snap-frozen in liquid N2, and stored at ?80?. From
F1animals, kidney and spleen were weighed and stored.
Serological phenotypes: Serum was analyzed in 684 F2rats
(357 females). Electrolytes, metabolites, immunological pa-
rameters, enzymes, and hormones were analyzed in serum
according to the guidelines of the German Society of Clinical
Chemistry and Laboratory Medicine. Measurements for all
serum traits but corticosterone were performed using a
Hitachi PPE-Modular analyzer (Roche Diagnostics, Man-
nheim, Germany). Corticosterone was measured using a
commercial ELISA assay (IDS, Frankfurt, Germany).
Statistical phenotype analyses: We sought to control for
possibleconfounding effects,suchasobserver intheglovetest
or an animal’s litter. We constructed mixed linear models of
the phenotypes, estimated effect sizes using restricted maxi-
mum likelihood, and adjusted the phenotypes for the re-
spective effects specified in Table S1. Sex and covariates were
QTL analyses. For glove test measures, we separately adjusted
542F. W. Albert et al.
observations from different trials and observers and then
averaged the available observations from each rat. To summa-
rize a rat’s behavior in the glove test, we performed principal
component analysis (PCA) on the individual glove test
measures. We used only F2animals in the PCA and calculated
scores of F0and F1animals on the basis of the obtained
Comparisons of non-glove test phenotypes between the F0,
F1, and F2generations, as well as tests for sex differences
(Wilcoxon’s rank test), were performed on phenotypes
calculated using Pearson’s product-moment correlation, on
phenotypes adjusted for all effects (including sex and cova-
riates) listed in Table S1. All analyses were performed using
the software R (R Development Core Team 2008) and the
nlme (Pinheiro et al. 2008) and lme4 (Bates 2007) packages.
Genotyping: Animals were genotyped with 152 microsatel-
lite and 49 single-nucleotide polymorphism (SNP) markers.
Markers were selected for maximum allele frequency differ-
ences between the outbred rat lines, as determined from
preliminary genotyping of a panel of F0animals. Preliminary
genotyping of microsatellites was performed as described
below, while SNPs were screened as described in Saar et al.
(2008). All markers used in the QTL mapping are listed in
Table S2. DNA was isolated either from lung or from spleen
tissue. Polymerase chain reaction (PCR) for microsatellite
markers was performed using the M13-primer PCR system
(Schuelke 2000) and analyzed on an ABI3730 DNA Analyzer
(Applied Biosystems, Foster City, CA). Microsatellite geno-
types were determined using the software GeneMapper
Version 4.0 (Applied Biosystems), and all genotypes were
manually double checked. SNPs were genotyped using Taq-
Man chemistry (Applied Biosystems). SNP genotypes were
called automatically as part of the scanning process, and
genotype plots were inspected visually.
Pedigree construction: Genotype data for individual
markers were tested for Mendelian pedigree errors, using
the program PedCheck (O’Connell and Weeks 1998). Allele
calls for inconsistent genotypes were rechecked manually and
either they were corrected for obvious genotyping errors or
the marker was excluded from further analysis if genotypes
could not be determined unambiguously. Wefound that some
rats yielded inconsistent genotypes for several markers,
although the respective genotypes appeared to have been
called correctly. We interpreted these individuals as having
incorrect pedigree records. Initially, genotypes had been
obtained from F0and F2animals. To clarify the pedigree
structure, we typed all markers in all F?1and F1animals for
which samples were available, as well as in an extended panel
of F0animals. Using the software ‘‘Cervus’’ 3.0 (Kalinowski
et al. 2007), we determined the most likely parental pair for all
genotyped F0, F1, and F2individuals, on the basis of a subset of
107 microsatellite markers with unambiguous genotype pat-
terns. Rats for which the inferred parents differed from those
in our records were either reassigned to the inferred parents
or excluded from further analysis if no unique parental pair
could be identified. The final pedigree used in the QTL
analyses showed no Mendelian errors and comprised 8 F?1
rats (all genotyped), 11 F0rats (8 genotyped), 43 F1rats (30
genotyped), and 706 F2rats (all genotyped).
Linkage map construction: We constructed a sex-averaged
linkage map, using a version of the program crimap (Green
et al. 1990) modified to handle large pedigrees by the
University of California Davis, Veterinary Genetics Laboratory.
On chromosome 6, we found the markers D6rat213 and
D6rat68 to be inverted on our linkage map relative to their
physical positions. On chromosome 13, the markers D13rat5
and D13rat64 were found to be inverted and to map very
closely(1.2 cM) toeach other, despitea physical distance of21
Mb. These cases may reflect chromosomal rearrangements in
inbred Brown Norway laboratory strain (Gibbs et al. 2004). We
used our inferred linkage maps in further analyses (Table S2).
We estimated information content at autosomal marker
positions on the basis of the fraction of individuals whose
alleles could be unambiguously traced to the F?1generation.
Single-QTL mapping: A standard model of a phenotype y
influenced by a single QTL can be written as
y ¼ b01FZ 1b1jaj1b2jdj1ej;
where b0is the population mean, F is a matrix of regression
coefficients for fixed effects and covariates (see Table S1 for
the effects we included in the QTL models for various
phenotypes), Z is an incidence matrix relating observations
in F to individual observations, b1jand b2jare the additive and
variables relating these genetic effects to individuals, and ejis
the residual error. We estimated the parameters b0, b1, and b2
using a variation of the least-squares regression framework
(Haley and Knott 1992; Haley et al. 1994). In this frame-
work, F2animals are grouped at a given genomic position
according to whether they carry two, one, or zero alleles
originated from the tame (allele ‘‘T’’) or aggressive (allele
‘‘A’’) line, forming the genotype classes TT, TA, and AA.
Missing F0genotypes can lead to a loss of power because some
alleles in F2animals might not be reliably traced to parental
lines. This limitation can be overcome by including the
genotyped parents of F0animals (the F?1) in the analysis
and by tracing alleles back to them. Hence, we inferred
missing genotypes of F0and F1animals on the basis of their
ancestors’ and offspring genotypes (File S1). Next, we calcu-
lated,in steps of 1 cM throughout the genome, theprobability
of an F2animal belonging to the TT, TA, or AA genotype
classes on the basis of genotypes of flanking markers, using
methods described in Pong-Wong et al. (2001) and Besnier
and Carlborg (2007). The genotype probabilities were used
to compute the indicator variables ajand dj(Haley et al.
1994). Finally, we fitted the parameters b0, b1, and b2using
least-squares regression. High F-values obtained from the
regression point to the presence of a putative QTL at the
respective location. The difference in mean between the two
homozygous classes TT and AA corresponds to twice the
additive effect b1 of the QTL, while the deviation of the
heterozygous TA class from the mean of the TTand AA classes
measures the degree of dominance b2. We searched for QTL
by following a forward selection procedure (Figure S1). After
significant QTL that reached genomewide significance as a
fixed effect in the model. The scan was then repeated, and
QTL were added until no additional significant QTL were
identified. For each phenotype, we performed 1000 permuta-
tionsofphenotypes withregard togenotypes todeterminethe
F-value threshold that corresponds to a genomewide signifi-
cance level of P ¼ 0.05 (Churchill and Doerge 1994). We
express variance componentsattributable toQTLas afraction
of the residual phenotypic variance, i.e., the variance in
phenotype after fixed effects and covariates have been
We analyzed the X chromosome using the software QxPak
(Perez-Enciso and Misztal 2004) (see File S1 for details).
Since the permutation-based significance thresholds derived
for the autosomes cannot be directly applied to the X chromo-
some,we assumed QTLwith a nominal P-value ,0.001 (0.005)
to be significant (suggestive) at a genomewide level, as
suggested in the QxPak manual. We tested for linkage to the
Y chromosome, using ANOVA as described in File S1.
Genetic Architecture of Tameness 543
Mapping of epistatic QTL: We searched for epistatic QTL
using an extension of the least-squares regression model for
single QTL, following a search strategy described and applied
earlier (Carlborg and Andersson 2002; Carlborg et al.
2003, 2004, 2006; Wright et al. 2006). Here, we first describe
the regression model underlying our epistatic analyses and
then go through the steps of the search strategy. A schematic
representation of the approach is shown in Figure S1.
The standard extension of the model for a single QTL to
incorporate two epistatic QTL is
y ¼b01FZ 1b1jaj1b2jdj1b3kak1b4kdk1b5jkaajk
The additional parameters are the additive (b3k) and domi-
nance effects (b4k) of the second QTL at position k, the
epistatic effects between the two loci (b5jk–b8jk), and the
corresponding indicator variables. The indicator variables
for the interaction terms (aajk, adjk, dajk, ddjk) were computed
by multiplying the respective additive and dominance in-
We estimated the effects b0–b8at a given pair of loci using
The search strategy to find epistatic pairs of QTL involves
details). First, we searched for single QTL as described above.
Second, we performed a genomewide search for putative
epistatic pairs of loci. Third, each pair is tested for the
existence of epistasis.
assigned significance in one of three ways. If both loci were
testing is necessary, and the pair is declared significant. If one
locusintheputative pair wasasignificantsingle QTL,weneed
to test only whether the second locus is significant (i.e.,
whether its inclusion in the model already containing the
first locus improves model fit). To derive the corresponding
threshold, we created, for each single QTL, 1000 randomized
data sets by permuting only the indicator variables of the
second QTL (ak, dk), as well as those of the interaction effects
(aajk, adjk, dajk, ddjk), while the first QTL was kept in the model
as a fixed effect (permutation test ‘‘Type I’’ in Figure S1). In
each permuted data set, we searched for the best fitting pair
including the known QTL and a second QTL. We then
compared the model fit obtained from the putative pair with
the model fits obtained from the permutations. Finally, if
neither QTL in the putative pair was significant as a single
QTL, we need to test whether the joint inclusion of both loci
improves the model fit significantly. We performed 1000
phenotype/genotype permutations and searched each ran-
domized data set for its best fitting pair (permutation test
‘‘Type II’’ in Figure S1). For increased efficiency, this was done
using a genetic search algorithm (Carlborg et al. 2000).
Significance of the putative pair was assigned by comparing its
So far, we have detected pairs of QTL, but not yet tested
given pair. To do this,we generated1000 randomized data sets
for each pair by permuting only the interaction indicator
variables (aajk, adjk, dajk, ddjk), while keeping the additive and
dominance effects of the two loci in the pair constant
(Carlborg and Andersson 2002) (permutation test ‘‘Type
III’’ in Figure S1). Epistasis is assumed if the putative epistatic
pair is in the top 5% of model fits obtained from the
To construct the network influencing tameness, we consider
loci (single or as part of a pair) with overlapping confidence
intervals to be the same locus. We show these loci as circles
in Figure 5, with lines between them indicating significant
epistatic interactions for that given pair. We did not fit a
model incorporating interactions between more than two
loci. To visualize the directions of the epistatic interactions
(Figure 5, B–F), we grouped F2animals according to their
two-locus genotype groups, we calculated the mean and the
standard error of the mean of the respective animals’ level of
Becausesomeloci inthetamenessnetworkarepart ofmore
adding up the variances explained by the respective pairs
(Table 4). Instead, we used the NOIA model of genetic effects
Rouzic and Alvarez-Castro (2008), with analyses restricted
to at most pairwise interactions. NOIA is specifically designed
to estimate parameters, including genetic variances, in multi-
locus networks (Alvarez-Castro and Carlborg 2007).
A cross between tame and aggressive rats: To create
an intercross between the tame and aggressive rats, we
mated one tame and one aggressive male to 5 aggressive
and 4 tame females, respectively. In the resulting F1
37 females to produce an F2population of 733 animals
(362 females). Details of the mating scheme are de-
scribed in materials and methods.
Analyses of phenotypes: We recorded a total of 45
phenotypic traits in the F2animals, including measures
from four behavioral tests, anatomical parameters, and
serum levels of hormones, enzymes, and other serum
and aggression, we used a paradigm that closely mimics
the test used to select the two rat lines over the past
36 years. In this ‘‘glove test,’’ a gloved human hand
approaches a rat in an experimental cage and attempts
to touch it and to pick it up (Figure 1A). Various aspects
of the rat’s behavior are recorded (Albert et al. 2008).
When testing F1animals in this test, we found that the
extreme levels of tameness and aggression observed in
the original F0 lines were absent (Figure S2). By
found in the original lines (Figure S2). A few F2animals
even exceeded the levels of tameness and aggression
observed in the tame and aggressive lines.
A PCA of the behaviors recorded in the glove tests of
the F2animals confirms these observations. The first
principal component (PC1) corresponds to behaviors
such as attacks, screaming, and (with inverse loading)
the toleration of touch or handling (Table 2). PC1
explains 26% of the variance in behavior of F2rats. Of
the PCs explaining .10% of the variance, PC1 most
clearly separates the tame from the aggressive F0
animals (Wilcoxon’s rank test: PC1, P , 10?15; PC2,
P ¼ 0.003; PC3, P ¼ 0.07), although these animals were
not includedinthePCA (seematerialsandmethods).
544F. W. Albert et al.
Traits measured in F2animals
Higher trait valueComments
Move and leave
Open field test
Time spent in center
Time spent in corner
Time spent moving
Time spent rearing
Time spent in light compartment
Time spent moving
Time spent rearing
Locomotion speed in light compartment
Startle response test
Adrenal gland weight
White coat spotting
No. of occurrences
No. of occurrences
No. of occurrences
No. of occurrences
No. of occurrences
No. of occurrences
g AggressiveMean startle response across 10 trials
ALAT, alanine aminotransferase; AP, alkaline phosphatase; ASAT, aspartate aminotransferase; fT3, free triiodthyronine; fT4,
Genetic Architecture of Tameness545
Of the F1rats, 94% (44/47) had PC1 scores between the
medians of the tame and the aggressive rats. Of the F2
rats, 79% (551/700), fell into this intermediate range,
while 6% (43) of the F2rats had more tame and 16%
(109) had more aggressive PC1 scores than defined by
the respective F0medians (Figure 1B). This indicates
that there is substantial variation in tameness in the F2
rats and suggests that PC1 is a useful measure of this
variation. The glove tests were repeated in 470 F2rats
(materials and methods). The correlation between
the PC1 scores obtained for the two trials was 0.44
(Pearson’s r, P , 10?15).
We also performed an open-field test, a light–dark
test, and a startle response test, which measure traits
related to anxiety and fear as well as general activity
(Table 1). The values of all these traits in F2animals
overlapped substantially with those in F0animals (Fig-
ure S3). This was also true for body weight, for the
weight of six organs, and for 8 of 14 serum traits (Figure
S4 and Figure S5). By contrast, .75% of the F2rats had
higher (corticosterone, creatinine, glucose, chloride)
or lower (alanine aminotransferase, ALAT; alkaline
phosphatase, AP) values in these measures than .75%
of the tame and aggressive rats (Figure S5).
Sex differences were apparent for many traits in the
F2animals (Table S3). When males and females were
considered separately, most phenotypes were approxi-
mately normally distributed in the F2 generation
(Figure S6, Figure S7, Figure S8, and Figure S9). By
contrast, raw glove test measures had highly skewed
distributions, with prominent peaks at zero counts/
Correlations between phenotypes: Earlier work re-
vealed a multitude of phenotypic differences between
the tame and the aggressive rats, including behavioral,
anatomical, hormonal, and neurochemical differences
(Naumenko et al. 1989; Plyusnina and Oskina 1997;
Popova et al. 2005; Albert et al. 2008). If these differ-
ences are caused by the same genetic loci, they should
be correlated in the F2 animals. We did observe
significant correlations among parameters recorded in
the same test. For example, correlations between
different measures in the glove test are reflected in
their contributions to PC1 (Table 2). In contrast,
parameters from different tests were generally not, or
only weakly, correlated (Figure 2, Table S4). Notably,
in the light compartment of the light–dark test and the
were not correlated (r ¼ 0.03, P ¼ 0.48). There were
significant but weak correlations between tameness and
High levels of tameness were also correlated with low
corticosterone levels (r ¼ ?0.08, P ¼ 0.04), but not with
the weight of the adrenal glands (r ¼ ?0.06, P ¼ 0.10).
QTL for tameness and associated traits: We typed
the animals in the pedigree for 201 genetic markers
(152 microsatelites and 49 single-nucleotide polymor-
phisms) that were selected to be polymorphic between
the parental strains and to provide coverage of most of
the genome (materials and methods).
Principal component analysis of behavior of F2animals
in the glove test
Boxing posture (duration)
Move and leave (count)
Tolerate handling (duration)
Tolerate touch (duration)
% variance 2615 11
The loadings shown for the respective principal compo-
nents (PCs) indicate the degree to which a trait contributes
to the respective PC. Only PCs that explain $10% of the var-
iance and loadings with absolute values $0.3 are shown.
Figure 1.—Behavior in the glove test. (A) The glove test
measures the level of tameness or aggression toward an ap-
proaching hand. (B) PCA scores derived from glove test be-
haviors of tame F0(blue), aggressive F0(red), F1(purple),
and F2(black) animals. Circles, females; squares, males.
546F. W. Albert et al.
The phenotypic and genetic data were used to
identify QTL for the traits measured in the F2animals.
A total of 23 significant and 125 suggestive autosomal
QTL, and one significant QTL on the X chromosome,
were identified when analyzing both sexes together
(Table 3 and Table S5 and Table S6). All but two serum
traits (fT3 and calcium levels) showed at least suggestive
overlapping QTL, as well as one QTL for coat color.
Two significant QTL for tameness (measured as PC1)
were identified (Figure 3A). The strongest of these
(termed ‘‘Tame-1’’) is located at 58 cM on chromosome
1. The difference in tameness between homozygous
genotypes at Tame-1 corresponds to ?20% of the differ-
units of PC1). Tame-1 explains 5.1% of the phenotypic
variance in tameness. The second locus (‘‘Tame-2’’) is
located at 78 cM on chromosome 8. Both the tameness
difference between homozygous genotypes (?10% of
the line difference) and the portion of residual pheno-
typic variance in tameness it explains (2.3%, are about
half of those of Tame-1.
The region encompassed by Tame-1 also contains
significant QTL for rearing in the open field and for
adrenal gland weight, as well as a suggestive QTL for the
time spent moving in the open field (Figure 3B). The
effects of these QTL are in the expected direction—i.e.,
direction expected from the comparison between tame
and aggressive animals (e.g., causing higher tameness
scores and lower adrenal gland weight). However, Tame-1
also overlaps with a significant QTL that influences
spleen weight. This QTL is transgressive—i.e., the alleles
from the tame line reduce spleen weight although the
rats from the tame line have 30% heavier spleens on
average (Albert et al. 2008).
Figure 2.—Correlations between phenotypes. Positive correlation coefficients are shown in red and negative ones in blue. Red
boxes mark correlations within the same test or group of traits.
Genetic Architecture of Tameness 547
In the proximity of Tame-2 several other QTL are
found, two of which are significant. At these QTL, the
alleles from the tame line increase body weight and
decrease the time an animal spent in the corners of the
open field, respectively. These effects are in the ex-
spent in the center, time spent moving and the number
of rears in the open field, kidney weight, and serum
aspartate aminotransferase (ASAT) all have effects in
the expected direction. There were also two transgres-
sive suggestive QTL, where the tame allele increases
adrenal gland weight and the magnitude of the startle
We found white coat spotting to be linked to a
significant QTL on chromosome 14, but no aspect of
tameness mapped to this region (Figure 4). White coat
spotting did not show association to Tame-1, Tame-2
(Figure S10), or any other QTL for behavior during the
glove test. Further, the tameness levels of individuals
carrying white ventral spots did not differ significantly
from those without them (t-test, P ¼ 0.17, Figure 4A).
To assess whether the QTL we identified might be
specific to one sex, we analyzed all traits using only
female or male F2animals, respectively (Table 3 and
Table S5 and Table S7). For tameness, Tame-1 reached
genomewide significance in females and chromosome-
wide significance in males, where the F-value (8.6) was
close to the genomewide significance threshold (8.8).
Tame-2 reached chromosomewide significance only in
males. The QTL for adrenal gland weight on chromo-
some 1 and for white spotting on chromosome 14 were
both sexes (e.g., spleen weight on chromosomes 1 and
10), whereas for several others we found significant or
suggestive linkage only in one sex. All individual
behaviors in the glove test, but not PC1, fall in the latter
category. For example, at Tame-1, only males showed a
significant QTL for screaming, whereas only females
had significant QTL for flights and toleration of touch.
Toleration of touch yielded one additional significant
sex-specific QTL in females and males, respectively
Epistatic interactions: Epistatic interactions can have
large effects on phenotypic traits. Hence, we searched
the genome for interacting pairs of loci for all traits
described in this study. Fifteen epistatic pairs affecting
Autosomal QTL identified at genomewide significance
TraitChraPeakb1 LOD C.I.b,c
Additive effect Dominance% varianced
Other behavioral tests
Time in corner (OF)
8 ?0.060 mkat/liter 0.008 mkat/liter
11 1.3 mmol/liter
2 0.3 mkat/liter
OF, open field test.
dResidual phenotypic variance explained after accounting for fixed effects.
eSignificance level when analyzing females/males separately.
548F. W. Albert et al.
9 traits reached genomewide significance (P , 0.05),
exceeding the random expectation of ,3 pairs for 48
analyzed traits. Most pairs were found for tameness,
forming an interconnected network of 5 loci (Figure
5A). The network explained 14% of the residual
phenotypic variance, compared to 7.4% explained by
Tame-1 and Tame-2 individually. It is discussed below,
while epistatic pairs for the remaining traits are given in
The tameness network comprises five pairwise inter-
actions between five loci (Figure 5A). Two loci in the
network had significant individual effects (Tame-1 and
Tame-2). When considering these loci simultaneously,
the tame allele (T) at locus Tame-1 increases tameness
regardless of the Tame-2 genotype (Figure 5D). The
effect is, however, strongest when Tame-2 is homozygous
(AA) for the allele from the aggressive line (A). The
is homozygous for the allele from the tame line (TT),
where the difference between the three Tame-2 geno-
types (AA, AT, and TT) is not significant.
Both Tame-1 and Tame-2 interact with a locus on
chromosome 19 (denoted Tame-3) that reached only
suggestive significance in the scan for single QTL. The
only in a heterozygous (AT) background of Tame-3
(Figure 5B). There is no additive effect of Tame-3 on
tameness, but strong overdominance for aggression in
the Tame-1 AA genetic background and a strong over-
dominance for tameness in the Tame-1 TT genetic
background. This interesting shift in the direction of
the dominance effect deserves further investigation.
When considering Tame-3 and Tame-2 together, the only
genotype with a deviating phenotype is the AAAA
double homozygote that significantly increases aggres-
sion (Figure 5C). In addition, Tame-1 and Tame-2 in-
teract significantly with one additional locus each. The
effect of the tame allele at Tame-1 is strongest when a
only in the AA Tame-1 genotype (Figure 5E). In this
background, it is transgressive, increasing aggression.
The Tame-2 genotype also has a major effect on a locus
on chromosome 6 (denoted Tame-5), in that Tame-5
affects tameness only when Tame-2 is AA (Figure 5F).
A polygenic basis for tameness: To uncover the
genetic basis for tameness, we analyzed.700 F2animals
Figure 3.—QTL for tameness and aggression. (A) Evidence for linkage to tameness across the genome. High F-values indicate
the presence of a QTL. The dashed horizontal line represents the genomewide significance threshold. Solid horizontal bars are 2-
LOD drop confidence intervals for QTL position. Chromosome boundaries are indicated by upward tick marks on the x-axis. (B)
Several traits map to the two QTL for tameness. Only significant QTL are shown. Black and red upward tick marks are micro-
satellite and SNP marker positions, respectively.
Genetic Architecture of Tameness549
as measured by the glove test in the F1and F2rats,
approximate a normal distribution with the mean
centered between those of the parental lines (Figure
1), suggesting a polygenic basis for tameness and
aggression in the rats (Lynch and Walsh 1998).
The linkage study confirms this. The largest QTL,
Tame-1, explains 5.1% of the residual phenotypic vari-
ance, while the remaining loci each explain smaller
fractions when considered individually. These estimates
are in line with the generally small effect sizes reported
for QTL for other rodent behaviors (Flint 2003).
Across 45 measures and three principal component
scores, our study identified 23 significant and 125
suggestive QTL. We note that this greatly exceeds the
number of QTL expected to be observed by chance. For
significance level of 5% and 48 suggestive QTL with a
significance level of 5% at each of 20 chromosomes.
Given thesample size of .700 F2animals, we consider it
unlikely that other unidentified loci with large individ-
ual effects exist in these lines.
Overlap of QTL for tameness-associated traits: Pre-
vious studies have identified a multitude of phenotypic
differencesbetweenthetameand theaggressivelines of
rats (Naumenko et al. 1989; Plyusnina and Oskina
1997; Popova et al. 2005; Albert et al. 2008). However,
the behavioral response to humans was the only
criterionused during selection. Are the lociinfluencing
the nonselected traits the same as those contributing to
the difference in tameness?
If phenotypic traits are influenced by the same loci
one would expect them to show some degree of
correlation. It is thus noteworthy that correlations
between the traits we measured in the F2population
were weak at best, often failing to reach significance in
spite of the fact that hundreds of animals were analyzed
and that some of the uncorrelated traits were markedly
different between the parental strains (Albert et al.
2008). However, the power to detect a correlation
caused by shared loci may be limited given that the
effect sizes associated with the alleles are small and
perhaps obscured by nongenetic influences.
In the QTL analyses, a number of traits mapped to
the same regions. This is especially obvious on chro-
mosome 1 where weight of the adrenal gland maps to a
region overlapping Tame-1 with virtually identical
confidence intervals (Figure 3B). It thus seems plausi-
ble that alleles of a single gene with pleiotropic effects
underlie both Tame-1 and adrenal gland size variation.
Alternatively, a causal relationship might exist between
tameness and adrenal gland size. For example, sudden
increases of plasma corticosterone, which is produced
by the adrenal cortex, promote aggressive behavior in
rats (Kruk et al. 2004), while chronically high levels of
glucocorticoids seem to inhibit aggressive behavior in
several vertebrate species (Summers et al. 2005).
However, postmortem corticosterone levels did not
map to any locus linked to tameness or aggression. It
is thus equally possible that other hormonal activities
the alleles that affect tameness in the rats. The
identification of the gene or genes underlying Tame-1
as well as adrenal gland size variation will eventually
score summarizing, among other traits, attacks, scream-
that, at Tame-1, these individual behaviors yielded QTL
apparently specific to one sex (Table 3) may suggest that
the causative alleles underlying Tame-1 influence the two
Figure 4.—White coat spotting and tameness. (A) Tame-
ness level of F2animals with (n ¼ 190) and without (n ¼
393) white ventral coat spots. (B) A QTL for spotting (black
line) does not show linkage to tameness (red line). The ver-
tical dashed line indicates the location of the Kit gene. Black
and red upward tick marks are microsatellite and SNP posi-
550F. W. Albert et al.
component at Tame-1 is found in both sexes, it may be the
case that the absence of signals for the individual traits
reflects lower power due to using half the number of
individuals. In addition, individual traits are likely to have
less power than the principal component they contribute
other loci truly act in a sex-specific manner.
To our knowledge, this study is the first genetic
mapping of tameness and defensive aggression against
humans in any species. However, several studies in rats
have identifiedQTL for traits potentially related tothose
studied here. Tame-1 overlapswithearlieridentified QTL
influencing several anxiety-related traits (Terenina-
Rigaldie et al. 2003), rearing behavior (Fernandez-
Teruelet al. 2002), and adrenal gland weight (Solberg
et al. 2006).Tame-2 overlapswith two QTL for activity and
anxiety-related behaviors (Terenina-Rigaldie et al.
2003; Conti et al. 2004). It is reassuring that phenotypes
similar to some of those studied here show linkage to
similar genomic locations. However, in the absence of
information on the molecular basis of these QTL, it
cannot presently be determined whether alleles at the
same genes are responsible.
A genetic network for tameness: Epistasis affects the
expression of numerous traits (Phillips 2008). For
behavioral quantitative traits, however, epistatic net-
works identified by genome scans remain rare (for
exceptions, see Wright et al. 2006; Bailey et al. 2008).
In this cross, a network of Tame-1 and Tame-2 and three
additional loci that were identified only as part of these
epistatic pairs influence tameness (Figure 5A).
The additive effect of Tame-1 was robust across genetic
Figure 5.—An epistatic network for tameness. (A) Overview of QTL (circles) and epistatic interactions (lines). Only QTL in
pairs with significant epistatic interactions are shown. Bold (nonbold) solid circles: the QTL was significant (suggestive) in the
scan for single loci. Dashed circles: the QTL was significant only as part of an epistatic pair. Numbers in circles indicate QTL
chromosome and position (centimorgans). (B–F) Phenotypes for two-locus genotypes. Circles indicate the mean phenotype
for the respective two-locus genotypes; error bars show the standard error of the mean. The strength of the QTL effect at the
first locus in the pair is indicated by the slope of the line connecting the homozygous genotypes [both alleles from the tame line
(TT) vs. both alleles from the aggressive line (AA)]. An effect at the second locus in the pair is indicated by nonoverlapping allele
effects at a given genotype of the first locus.
Genetic Architecture of Tameness551
locus influencing tameness. In contrast, Tame-2 seems to
of all three loci it interacts with (Figure 5, C, D, and F).
This is reminiscent of epistatic loci underlying growth in
background, i.e., where the other loci are homozygous
for the allele from the tame line, Tame-2 has at most a
small effect on tameness.
The epistatic network raises interesting questions
about the role of Tame-1 and Tame-2 during selection
for tameness and aggression. Due to the relatively
invariant effect of Tame-1, it can be selected for in many
genetic backgrounds, driving alternative alleles rapidly
to fixation. On the other hand, the homozygous
aggressive genotype at Tame-2 might have had an initial
role in selection by magnifying the effects of other loci,
allowing them to become more prominent targets of
decreased the response of other loci to selection. The
increased frequency of homozygous tame genotypes at
loci other than Tame-2 will, however, decrease the
selective advantage of the tame allele at Tame-2, due to
its small effect in this background. Given the intricate
interactions between Tame-2 and the other loci, it is an
intriguing possibility that Tame-2 might harbor multiple
the single tame and aggressive alleles might in fact be
average effects across several alleles. A more in-depth
analysis of patterns of polymorphism at Tame-2 and
other loci might shed light on this.
White coat color and tameness: Many domestic ani-
their wild relatives by conspicuous coat color variants.
Possible explanations include direct selection for coat
color variants by humans (e.g., Pielberg et al. 2008) and
of alleles influencing other traits and particularly behav-
ior, including the level of tameness (Keeler and King
1942; Cottle and Price 1987; Hayssen 1997).
The F2rats provide an excellent opportunity to test
whether loci influencing tameness also affect white coat
spotting. If the same genes are responsible, F2animals
carrying coat spots should be more tame than those
without. However, this was not observed (see results).
Similarly, the QTL for coat spotting shows no linkage to
tameness or any other trait (Figure 4B), and neither
Tame-1 nor Tame-2 is linked to coat spotting (Figure
S10). Hence, we find no evidence for white spotting
being caused by the same loci that contribute to
tameness. Pleiotropic effects linking tameness and coat
color may occur in other species, or even in other lines
of rats, but such scenarios are clearly not strengthened
by these results.
It is noteworthy that the QTL for white coat spots on
chromosome 14 contains at its center the Kit gene
Epistatic pairs of QTL identified at genomewide significance
Locus 1Locus 2
Flight1 4543–4898 0–14 6.9
Time spent moving (LDT)886 83–8898482–845.4
Fecal boli (LDT)1
Adrenal gland weight30 0–2114338–485.2
Corticosterone5 25 18–356 8273–926.2
LDT: light–dark test.
cResidual phenotypic variance explained after accounting for fixed effects.
552F. W. Albert et al.
(RefSeq NM_022264), which encodes a tyrosine-kinase
receptor involved in melanoblast migration (Yoshida
et al. 2001). Allelic variants of homologs of rat Kit, or of
the gene for the Kit ligand (Kitl; RefSeq NM_021843),
are known to cause white coat color variants in mice
(Jackson 1994), pigs (Marklund et al. 1998), horses
(Haase et al. 2007), and stickleback fish (Miller et al.
2007). Thus, Kit is an excellent candidate for causing
the white coat spots in the rats studied here.
Conclusions: We present a genetic analysis of traits
associated with tameness in a rat model of animal
domestication. Tameness is found to be influenced by
two major loci, which are part of a five-locus epistatic
network. A possibility not explored here are epistatic
interactions involving more than two loci. Such inter-
actions are, however, very difficult to detect given the
sample size limitations in mammals.
The confidence intervals for the two tameness loci
contain 744 (Tame-1) and 339 (Tame-2) genes annotated
in the Ensembl database, respectively. Since few genes
underlying QTL for any behavior have been identified
(for two notable exceptions, see Yalcin et al. 2004 and
Watanabe et al. 2007), and none of them are located in
Tame-1 or Tame-2, it seems premature to speculate about
what genes underlie Tame-1 and Tame-2. Rather, fine-
mapping approaches such as advanced intercross lines,
as well as other approaches, are needed to clarify what
genes are involved.
This work greatly benefited from SNP genotyping courteously pro-
vided by Ivo Gut and Marc Lathrop at the Centre National de
Genotypage, Genome Institute of the French Atomic Energy Commis-
sion, Evry, France. We are indebted to Lysann Wagner and Claudia
and Gudrun Lemm for assistance with animal maintenance; and to
Inger Jonasson, Jenny Jonsson, Katarina Davidsson, and Ulf Gyllensten
at the Uppsala Genome Center for help with genotyping and for being
their constructive comments on the manuscript. This work was funded
by the Max Planck Society. Thework by O ¨.C. and F.B. wasfundedby the
Swedish Foundation for Strategic Research and the Swedish Research
Council for Environment, Agricultural Sciences and Spatial Planning.
Albert, F. W., O. Shchepina, C. Winter, H. Ro ¨mpler, D. Teupser
et al., 2008 Phenotypic differences in behavior, physiology and
neurochemistry between rats selected for tameness and for defen-
sive aggression towards humans. Horm. Behav. 53: 413–421.
Alvarez-Castro, J. M., and O. Carlborg, 2007
for functional and statistical epistasis and its application in quan-
titative trait loci analysis. Genetics 176: 1151–1167.
Bailey, J. S., L. Grabowski-Boase, B. M. Steffy, T. Wiltshire, G. A.
Churchill et al., 2008Identification of quantitative trait loci
for locomotor activation and anxiety using closely related inbred
strains. Genes Brain Behav. 7: 761–769.
Bates, D., 2007
lme4: Linear Mixed-Effects Models Using S4 Classes. R pack-
age version 0.99875–9. http:/ /cran.r-project.org/web/packages/
Belyaev, D. K., and P. M. Borodin, 1982
on variation and its role in evolution. Biol. Zent. Bl. 100: 705–
A unified model
The influence of stress
Besnier, F., and O. Carlborg, 2007
for estimating continuous IBD functions for use in genome scans
for QTL. BMC Bioinformatics 8: 440.
Carlborg, O., and L. Andersson, 2002
ing to detect multiple epistatic QTLs. Genet. Res. 79: 175–184.
Carlborg, O¨., L. Andersson and B. Kinghorn, 2000
genetic algorithm for simultaneous mapping of multiple inter-
acting quantitative trait loci. Genetics 155: 2003–2010.
Carlborg, O., S. Kerje, K. Schutz, L. Jacobsson, P. Jensen et al.,
2003 A global search reveals epistatic interaction between
QTL for early growth in the chicken. Genome Res. 13: 413–421.
Carlborg, O., P. M. Hocking, D. W. Burt and C. S. Haley,
2004 Simultaneous mapping of epistatic QTL in chickens re-
veals clusters of QTL pairs with similar genetic effects on growth.
Genet. Res. 83: 197–209.
Carlborg, O., L. Jacobsson, P. Ahgren, P. Siegel and L. Andersson,
2006Epistasis and the release of genetic variation during long-
term selection. Nat. Genet. 38: 418–420.
Churchill, G. A., and R. W. Doerge, 1994
value for quantitative trait mapping. Genetics 138: 963–971.
Conti, L. H., M. Jirout, L. Breen, J. J. Vanella, N. J. Schork et al.,
2004Identification of quantitative trait loci for anxiety and lo-
comotion phenotypes in rat recombinant inbred strains. Behav.
Genet. 34: 93–103.
Cottle, C. A., and E. O. Price, 1987
color allele on the behavior of captive wild Norway rat (Rattus nor-
vegicus). J. Comp. Psychol. 101: 390–394.
Ed. 1. John Murray, London.
Diamond, J., 2002 Evolution, consequences and future of plant and
animal domestication. Nature 418: 700–707.
Driscoll, C. A., M. Menotti-Raymond, A. L. Roca, K. Hupe, W. E.
Johnson et al., 2007The Near Eastern origin of cat domestica-
tion. Science 317: 519–523.
Eriksson, J., G. Larson, U. Gunnarsson, B. Bed’hom, M. Tixier-
Boichard et al., 2008Identification of the Yellow skin gene
reveals a hybrid origin of the domestic chicken. PLoS Genet.
Fernandez-Teruel, A., R. M. Escorihuela, J. A. Gray, R. Aguilar,
L. Gil et al., 2002 A quantitative trait locus influencing anxiety
in the laboratory rat. Genome Res. 12: 618–626.
Flint, J., 2003 Analysis of quantitative trait loci that influence ani-
mal behavior. J. Neurobiol. 54: 46–77.
Gibbs, R. A., G. M. Weinstock, M. L. Metzker, D. M. Muzny, E. J.
Sodergren et al., 2004 Genome sequence of the Brown Norway
ratyieldsinsights intomammalianevolution.Nature428: 493–521.
Green, S., K. Falls and S. Crooks, 1990
v2.4. Washington University School of Medicine, St. Louis.
Haase, B., S. A. Brooks, A. Schlumbaum, P. J. Azor, E. Bailey et al.,
2007 Allelic heterogeneity at the equine KIT locus in dominant
white (W) horses. PLoS Genet. 3: 2101–2108.
Haley, C. S., and S. A. Knott, 1992
mapping quantitative trait loci in line crosses using flanking
markers. Heredity 69: 315–324.
Haley, C. S., S. A. Knott and J.-M. Elsen, 1994
tive trait loci in crosses between outbred lines using least-squares.
Genetics 136: 1195–1207.
Hare, B., I. Z. Plyusnina, N. Ignacio, O. Schepina, A. Stepika et al.,
2005 Social cognitive evolution incaptive foxes is a correlated by-
product of experimental domestication. Curr. Biol. 15: 226–230.
Hayssen, V., 1997 Effects of the nonagouti coat-color allele on be-
havior of deer mice (Peromyscus maniculatus): a comparison with
Norway rats (Rattus norvegicus). J. Comp. Psychol. 111: 419–423.
Jackson, I. J., 1994 Molecular and developmental genetics of mouse
coat color. Annu. Rev. Genet. 28: 189–217.
the computer program CERVUS accommodates genotyping error
increases success in paternity assignment. Mol. Ecol. 16: 1099–1106.
Keeler, C. E., and H. D. King, 1942
genes in the Norway rat, with special reference to temperament
and domestication. J. Comp. Psychol. 34: 241–250.
Kruk, M. R., J. Hala ´sz, W. Meelis and J. Haller, 2004
feedback between the adrenocortical stress response and a brain
mechanism involved in aggressive behavior. Behav. Neurosci.
A general and efficient method
Use of randomization test-
The use of a
Effects of the nonagouti pelage-
Documentation for CRI-MAP
A simple regression method for
Multiple effects of coat color
Genetic Architecture of Tameness553
Larson, G., K. Dobney, U. Albarella, M. Fang, E. Matisoo-Smith
et al., 2005Worldwide phylogeography of the wild boar reveals
multiple centers of pig domestication. Science 307: 1618–1621.
Le Rouzic, A., and J. M. Alvarez-Castro, 2008
netic effects and genotype-phenotype maps. Evol. Bioinform.
Online 4: 225–235.
Lynch, M., and B. Walsh, 1998
Traits. Sinauer Associates, Sunderland, MA.
Marklund, S., J. Kijas, H. Rodriguez-Martinez, L. Ronnstrand,
K. Funaet al., 1998Molecular basisfor the dominantwhite phe-
notype in the domestic pig. Genome Res. 8: 826–833.
Miller, C. T., S. Beleza, A. A. Pollen, D. Schluter, R. A. Kittles
et al., 2007 cis-regulatory changes in kit ligand expression and
parallel evolution of pigmentation in sticklebacks and humans.
Cell 131: 1179–1189.
Naderi, S., H.-R. Rezaei, F. Pompanon, M. G. B. Blum, R. Negrini
et al., 2008The goat domestication process inferred from
large-scale mitochondrial DNA analysis of wild and domestic in-
dividuals. Proc. Natl. Acad. Sci. USA 105: 17659–17664.
Naumenko, E. V., N. K. Popova, E. M. Nikulina, N. N. Dygalo, G.
T. Shishkina et al., 1989Behavior, adrenocortical activity,
and brain monoamines in norway rats selected for reduced ag-
gressiveness towards man. Pharmacol. Biochem. Behav. 33:
O’Connell, J. R., and D. E. Weeks, 1998
identification of genotype incompatibilities in linkage analysis.
Am. J. Hum. Genet. 63: 259–266.
Perez-Enciso, M., and I. Misztal, 2004
model application for genetical genomics and QTL analyses.
Bioinformatics 20: 2792–2798.
Phillips, P. C., 2008 Epistasis—the essential role of gene interac-
tions in the structure and evolution of genetic systems. Nat.
Rev. Genet. 9: 855–867.
Pielberg, G. R., A. Golovko, E. Sundstrom, I. Curik, J. Lennartsson
et al., 2008A cis-acting regulatorymutation causes premature hair
Pinheiro, J., D. Bates, S. DebRoy, D. Sarkar and The R Core Team,
nlme: Linear and Nonlinear Mixed Effects Models. R package
version 3.1–87. http://cran.r-project.org/web/packages/nlme/
Plyusnina, I. Z., and I. Oskina, 1997
responses to open-field test in rats selected for reduced aggres-
siveness toward humans. Physiol. Behav. 61: 381–385.
Pong-Wong, R., A. W. George, J. A. Woolliams and C. S. Haley,
2001A simple and rapid method for calculating identity-by-
descent matrices using multiple markers. Genet. Sel. Evol.
Popova, N. K., V. S. Naumenko, I. Z. Plyusnina and A. V. Kulikov,
2005 Reduction in 5-HT1A receptor density, 5-HT1A mRNA ex-
pressionand functional correlatesfor 5-HT1Areceptors in genet-
ically defined aggressive rats. J. Neurosci. Res. 80: 286–292.
Estimation of ge-
Genetics and Analysis of Quantitative
PedCheck: a program for
Qxpak: a versatile mixed
Behavioral and adrenocortical
R DevelopmentCore Team, 2008
Statistical Computing. R Foundation for Statistical Computing,
Saar, K., A. Beck, M. T. Bihoreau, E. Birney, D. Brocklebank et al.,
2008SNP and haplotype mapping for genetic analysis in the
rat. Nat. Genet. 40: 560–566.
Savolainen, P., Y.-p. Zhang, J. Luo, J. Lundeberg and T. Leitner,
2002Genetic evidence for an East Asian origin of domestic
dogs. Science 298: 1610–1613.
Schuelke, M., 2000An economic method for the fluorescent label-
ing of PCR fragments. Nat. Biotechnol. 18: 233–234.
Solberg, L. C., A. E. Baum, N. Ahmadiyeh, K. Shimomura, R. H. Li
et al., 2006 Genetic analysis of the stress-responsive adrenocor-
tical axis. Physiol. Genomics 27: 362–369.
et al., 2005 Glucocorticoid interaction with aggression in non-
mammalian vertebrates: reciprocal action. Eur. J. Pharmacol.
Terenina-Rigaldie, E., M. P. Moisan, A. Colas, F. Beauge, K. V.
Shah et al., 2003Genetics of behaviour: phenotypic and molec-
ular study of rats derived from high- and low-alcohol consuming
lines. Pharmacogenetics 13: 543–554.
Troy, C. S., D. E. MacHugh, J. F. Bailey, D. A. Magee, R. T. Loftus
et al., 2001Genetic evidence for Near-Eastern origins of Euro-
pean cattle. Nature 410: 1088–1091.
Trut, L. N., 1999Early canid domestication: the farm-fox experi-
ment. Am. Sci. 87: 160–169.
Trut, L. N., I. Z. Plyusnina and L. A. Prasolova, 2000
hooded and nonagouti in the Norway rat Rattus norvegicus: ef-
fects of selection for behavior and photoperiod. Russ. J. Genet.
Vila, C., J. A. Leonard, A. Gotherstrom, S. Marklund, K. Sandberg
et al., 2001Widespread origins of domestic horse lineages. Sci-
ence 291: 474–477.
Watanabe, A., T. Toyota, Y. Owada, T. Hayashi, Y. Iwayama et al.,
2007Fabp7 maps to a quantitative trait locus for a schizophre-
nia endophenotype. PLoS Biol. 5: 2469–2483.
Wright, D., R. K. Butlin and O ¨. Carlborg, 2006
tion of behaviouraland morphological traits in the zebrafish (Da-
nio rerio). Behav. Genet. 36: 914–922.
Yalcin, B., S. A. G. Willis-Owen, J. Fullerton, A. Meesaq, R. M.
Deacon et al., 2004 Genetic dissection of a behavioral quantita-
tive trait locus shows that Rgs2 modulates anxiety in mice. Nat.
Genet. 36: 1197–1202.
Yoshida, H., T. Kunisada, T. Grimm, E. K. Nishimura, E. Nishioka
et al., 2001Review: melanocyte migration and survival controlled
by SCF/c-kit expression. J. Invest. Dermatol. Symp. Proc. 6: 1–5.
R: A Language and Environment for
Communicating editor: A. D. Long
554 F. W. Albert et al.
Genetic Architecture of Tameness in a Rat Model
of Animal Domestication
Frank W. Albert, Örjan Carlborg, Irina Plyusnina, Francois Besnier, Daniela Hedwig,
Susann Lautenschläger, Doreen Lorenz, Jenny McIntosh, Christof Neumann,
Henning Richter, Claudia Zeising, Rimma Kozhemyakina, Olesya Shchepina,
Jürgen Kratzsch, Lyudmila Trut, Daniel Teupser, Joachim Thiery, Torsten Schöneberg,
Leif Andersson and Svante Pääbo
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