genetic analysis of stress responsiveness in a mouse model

7
Genetic analysis of stress responsiveness in a mouse model MARK MURPHY 1 , REBECCA E. NEWMAN 1 , MAGDALENA KITA 1 , YVETTE M. WILSON 1 , SASH LOPATICKI 2 , & GRANT MORAHAN 2 1 Department of Anatomy and Cell Biology, University of Melbourne, Melbourne, Victoria, Australia and 2 Walter and Eliza Hall Institute of Medical Research, Royal Melbourne Hospital, Melbourne, Victoria, Australia Abstract The purpose of the present paper was to look for genes that might be involved in anxiety-related behaviours by undertaking a genetic analysis of a simple mouse model of stress responsiveness. Two inbred mouse strains have been identified that show either high or low stress responsiveness. These strains were crossed to generate F1 progeny, which were then crossed to generate F2 progeny, and in which there is segregation of genotype within individual animals. DNA was isolated from these animals and a genome scan was conducted in order to find regions on the genome that correlate with the stress responsiveness. Several regions on the mouse genome show significant linkage with the stress phenotype. One region in particular, on chromosome 12, was further characterised and the most significant linkage was found between 32.8 and 44.8 cM. These chromosomal regions may contain genes encoding proteins that are involved in the underlying neural circuitry involved in stress responsiveness. The stress response is a very important and natural aspect of human behaviour and, in a healthy individual, is a natural and necessary response to external stimuli. However, chronic or extreme reactions to stress are directly related to anxiety and can lead to pathological conditions such as long- term anxiety states, depression and panic disorders (Gold & Chrousos, 2002; Jetty, Charney, & God- dard, 2001; Kendler, Kessler et al., 1995; Lopez, Akil, & Watson, 1999). Stress-related disease is not limited to psychopathologies, but also contributes to other major health problems such as hypertension, atherosclerosis, and disorders of the immune system (Vanitallie, 2002). These disease states include some of the major medical problems of our times and stress-related illnesses affect at least 25% of the population. In the next 20 years just one of these diseases, generalised depression, is predicted to become the second greatest cause of death and disability in the world, whereas ischaemic heart disease, which is directly associated with hyperten- sion and atherosclerosis, will become the greatest cause of death and disability (Murray & Lopez, 1996). It is now becoming increasingly clear that a significant part of the individual variation in the stress response has a genetic component (Bouchard, 1994; Eley & Plomin, 1997). In twin studies, the genetic component for the stress-related personality trait, neuroticism, is estimated to be 40 – 50% (Bouchard, 1994; Pedersen, Plomin, McClearn, & Friberg, 1988). Furthermore, there is significant comorbidity for the anxiety-related traits and depression, suggesting direct causal links between these disorders (Kaufman & Charney, 2000). However, there is no clear genetic picture emerging to show that one set of genes may underpin all of these pathologies (Kendler, Walters et al., 1995). Analysis of genetics of these disorders in humans is complicated by many factors, including accuracy of diagnosis, the likely multifactorial inheritance, and influence of environment. This may make it particularly difficult to identify genes that are associated with these disorders using conventional genetic linkage analysis. Attempts to undertake such analyses for other complex psychiatric disorders, such as bipolar disorder and schizophrenia, have so far had limited success (Baron, 2002; Moller, 2003; Correspondence: M. Murphy, Department of Anatomy and Cell Biology, University of Melbourne, Melbourne, Vic. 3010, Australia. Tel.: + 61 3 8344 5785. Fax: + 61 3 9347 5219. E-mail: [email protected] Australian Journal of Psychology, Vol. 56, No. 2, September 2004, pp. 108 – 114. ISSN 0004-9530 print/ISSN 1742-9536 online # The Australian Psychological Society Ltd Published by Taylor & Francis Ltd DOI: 10.1080/00049530410001734883

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Page 1: Genetic analysis of stress responsiveness in a mouse model

Genetic analysis of stress responsiveness in a mouse model

MARK MURPHY1, REBECCA E. NEWMAN1, MAGDALENA KITA1, YVETTE M. WILSON1,

SASH LOPATICKI2, & GRANT MORAHAN2

1Department of Anatomy and Cell Biology, University of Melbourne, Melbourne, Victoria, Australia and 2Walter and Eliza

Hall Institute of Medical Research, Royal Melbourne Hospital, Melbourne, Victoria, Australia

AbstractThe purpose of the present paper was to look for genes that might be involved in anxiety-related behaviours by undertaking agenetic analysis of a simple mouse model of stress responsiveness. Two inbred mouse strains have been identified that showeither high or low stress responsiveness. These strains were crossed to generate F1 progeny, which were then crossed togenerate F2 progeny, and in which there is segregation of genotype within individual animals. DNA was isolated from theseanimals and a genome scan was conducted in order to find regions on the genome that correlate with the stressresponsiveness. Several regions on the mouse genome show significant linkage with the stress phenotype. One region inparticular, on chromosome 12, was further characterised and the most significant linkage was found between 32.8 and44.8 cM. These chromosomal regions may contain genes encoding proteins that are involved in the underlying neuralcircuitry involved in stress responsiveness.

The stress response is a very important and natural

aspect of human behaviour and, in a healthy

individual, is a natural and necessary response to

external stimuli. However, chronic or extreme

reactions to stress are directly related to anxiety

and can lead to pathological conditions such as long-

term anxiety states, depression and panic disorders

(Gold & Chrousos, 2002; Jetty, Charney, & God-

dard, 2001; Kendler, Kessler et al., 1995; Lopez,

Akil, & Watson, 1999). Stress-related disease is not

limited to psychopathologies, but also contributes to

other major health problems such as hypertension,

atherosclerosis, and disorders of the immune system

(Vanitallie, 2002). These disease states include some

of the major medical problems of our times and

stress-related illnesses affect at least 25% of the

population. In the next 20 years just one of these

diseases, generalised depression, is predicted to

become the second greatest cause of death and

disability in the world, whereas ischaemic heart

disease, which is directly associated with hyperten-

sion and atherosclerosis, will become the greatest

cause of death and disability (Murray & Lopez,

1996).

It is now becoming increasingly clear that a

significant part of the individual variation in the

stress response has a genetic component (Bouchard,

1994; Eley & Plomin, 1997). In twin studies, the

genetic component for the stress-related personality

trait, neuroticism, is estimated to be 40 – 50%

(Bouchard, 1994; Pedersen, Plomin, McClearn, &

Friberg, 1988). Furthermore, there is significant

comorbidity for the anxiety-related traits and

depression, suggesting direct causal links between

these disorders (Kaufman & Charney, 2000).

However, there is no clear genetic picture emerging

to show that one set of genes may underpin all of

these pathologies (Kendler, Walters et al., 1995).

Analysis of genetics of these disorders in humans is

complicated by many factors, including accuracy of

diagnosis, the likely multifactorial inheritance, and

influence of environment. This may make it

particularly difficult to identify genes that are

associated with these disorders using conventional

genetic linkage analysis. Attempts to undertake such

analyses for other complex psychiatric disorders,

such as bipolar disorder and schizophrenia, have so

far had limited success (Baron, 2002; Moller, 2003;

Correspondence: M. Murphy, Department of Anatomy and Cell Biology, University of Melbourne, Melbourne, Vic. 3010, Australia. Tel.: + 61 3 8344 5785.

Fax: + 61 3 9347 5219. E-mail: [email protected]

Australian Journal of Psychology, Vol. 56, No. 2, September 2004, pp. 108 – 114.

ISSN 0004-9530 print/ISSN 1742-9536 online # The Australian Psychological Society Ltd

Published by Taylor & Francis Ltd

DOI: 10.1080/00049530410001734883

Page 2: Genetic analysis of stress responsiveness in a mouse model

Pulver, 2000), even given that there is evidence for

a strong genetic contribution to both of these

disorders.

Because of the difficulties associated with human

analysis, an attractive alternative is to use animal

models of reactivity to stress, often termed emotion-

ality (Eley & Plomin, 1997). The studies of genetics

of emotionality often involve the use of inbred

strains of mice, where each animal within an inbred

strain is genetically identical, but different strains

are genetically different. If there are significant

differences in behaviour between inbred strains

raised in the same environment, then these have a

genetic basis. A number of studies have used inbred

strains for the genetic analysis of emotionality (Flint

et al., 1995; Talbot et al., 1999; Talbot et al., 2003;

Tarricone, Hingtgen, Belknap, Mitchell, & Nurn-

berger, 1995). These studies have often used the

Open Field Activity (OFA) test as a measure of

fearfulness or emotionality and have established

genetic linkage between this phenotype and a

number of regions on different mouse chromo-

somes.

In this study we have used a similar approach to

analyse the genetics of emotionality. We have used a

modification of the OFA test, an elevated OFA

(eOFA), to look for differences in emotionality

between two different mouse strains, C57/Bl6 (B6)

and DBA2/J (D2). We find very significant differ-

ences in locomotion between these strains. We have

undertaken a genetic analysis in an F2 cross of these

two strains, and find several regions of the mouse

genome that show significant association with this

phenotype.

Methods

Animals and breeding.

The inbred mouse strains, B6 and D2, were obtained

from the Walter and Eliza Hall Institute Animal

Production Facility (Kew, Victoria, Australia). Upon

weaning, all animals were housed in same-sex groups

at the Departments of Anatomy and Cell Biology/

Pathology Animal Facility at the University of

Melbourne. The mouse room was maintained at a

temperature of 22+ 18C with a 12:12 light – dark

cycle. The mice had feed (standard rodent feed

GR2+ , Barastoc, Vic., Australia) and water available

at all times. All animal care was conducted according

to the Australian Code of Practice for the Care and

the Use of Animals for Scientific Purposes, 1997.

An outcross between B6 female mice and D2 male

mice was conducted to generate first filial (denoted

B6D2F1) progeny, and these animals were subse-

quently crossed to generate second filial progeny

(B6D2F2) for mapping studies.

Elevated Open Field Activity test

All behavioural testing was conducted between 10:00

and 17:00 hours. The animals to be tested were taken

to the Behavioural Laboratory, within the Depart-

ment of Anatomy and Cell Biology, at least 1 hr prior

to testing. We used a modification of the OFA test,

the eOFA. In this test, OFA was measured under

intense white light (2 6 250 W) for 3 min upon a

rectangular arena (766 102 cm), 74.0 cm above the

floor and with grid lines drawn in 20.0 6 20.0-cm

sections. The 80 – 85-day-old mice were individually

placed into a cylindrical chamber (11.3 cm diameter,

11.4 cm height) in the center of the arena. The 3-min

trial commenced once the chamber was lifted via a

pulley system by the experimenter and its shadow was

free from the arena. The parameters measured were

total time each mouse was exploring the arena, the

total number of section boundaries crossed and the

number of faecal boli deposited by the mouse during

the 3-min trial. After each trial the arena was wiped

clean with a damp cloth to eliminate any olfactory

cues affecting the behaviour of subsequently tested

mice.

The animals were given an overall stress score,

which combined three measures of OFA: time

moving, grid crossings and rate (grid crossings/time

moved). For each of these values, the means for B6

mice were assigned a value of 0, and for D2 mice, a

value of 1. There was a negative correlation for time

moved and grid crossings, and a positive correlation

with rate. Defecation rate was excluded from the

overall score because it showed no correlation with

the other measures of stress responsiveness in the F2

cross. Initially 460 F2 animals were generated and

phenotyped using the OFA. These animals were

divided into two groups of 230 and DNA from 30 of

the most D2-like and 30 of the most B6-like animals

from one of the cohorts of 230 animals were subject

to a genome scan.

DNA preparation and genome scan

DNA was prepared from animals’ tails by incubation

in 100 ml 25 mM NaOH/0.2 mM ethylenediamine

tetraacetic acid (EDTA), pH 12.0 at 958C for

60 min. After incubation the tails were left to cool

at room temperature for approximately 2 min and

then shaken vigorously to release the DNA into the

solution. Finally, 100 ml 40 mM Tris-HCl, pH 5.0

was aliquoted into each eppendorf tube. For

genotyping, initially 140 MapPrimerTM pairs (Re-

search Genetics, Huntsville, Alabama, USA) were

selected from the Whitehead/Mit mouse genome

databases to scan the whole genome at approximately

10 – 15-cM intervals. All primer pairs generated

products of different sizes in B6 or D2 mice, allowing

Genetics of stress-responsiveness 109

Page 3: Genetic analysis of stress responsiveness in a mouse model

the assignment of a particular region of the mouse

genome to either of these parental strains. Different-

sized microsatellite products were generated by

polymerase chain reaction (PCR) in a volume of

10 ml where 5 ml was diluted DNA solution. The

remaining 5 ml consisted of 66-nM primer; 16 PCR

Buffer (minus Mg2+ , GibcoBRL); 2 mM MgCl;

0.1 mM deoxynucleotide triphosphates (dNTPs);

0.015 MBq [a32P] deoxyadenosine triphosphate

(dATP) and 0.2 U Taq polymerase (GibcoBRL).

After an initial denaturation at 948C for 1 min, the

reaction conditions were 35 cycles at 958C for 20 s,

538C for 20 s, 728C for 20 s and a final cycle of 728Cfor 2 min and 258C for 2 min. The PCR products

were resolved on 5% polyacrylamide gels and

products detected by autoradiography. The data

generated from this genotyping were analysed for

linkage using the nonparametric MAPMAKER/QTL

program (Whitehead/MIT Center for Genome Re-

search, Cambridge, MA).

Further genotyping at a subregion of chromosome

12 of the B6D2F2 animals was undertaken in order

to do further linkage analysis with the stress

phenotype (as well as a nonstress phenotype). This

was done by selecting both samples that had either

high or low stress scores from both cohorts of 230

B6D2F2 animals and genotyping them as above for

markers lying only in chromosome 12.

Linkage analysis

A chi-square contingency table was utilised to

observe if a specified genotype on chromosome 12

correlated to either high stress or low stress (stress

nonresponsive).

Results

Activity of mouse strains on elevated open field activity

test

In initial observations of B6 and D2 mice, clear

qualitative differences in behaviour were observed.

The B6 mice were relatively easy to pick up and

did not show any signs of internal shaking of

shivering. In comparison, D2 were more difficult

to pick up in their cages, running quickly around

the cage and flattening their bodies to the walls of

the cage. They also appeared to have a shiver as

well as constant head movements and appeared

hyperactive. We thus believed that they could have

been stress prone or highly stress responsive, and

tested them in an eOFA. The OFA is an example

of measuring rodent behaviour in a novel environ-

ment. The open field arena, being white and well

lit, produces an unwelcoming and potentially

frightening environment for rodents (Archer,

1973; Flint et al., 1995). Therefore exploratory

activity upon the open field is a useful measure for

stress responsiveness.

We tested both strains on our eOFA, which is

somewhat different to the OFA test used by others in

that the arena is raised above the floor and has no

sides. It may be more threatening than a sided open

field test because there is nowhere to hide. To

determine the behaviour of different strains of mice

on this arena, we placed them in the centre of the

open field, in an enclosed cylinder, and then

removed the cylinder and observed their behaviour.

The B6 mice moved freely on the open field and

constantly investigated the entire arena, including

the edges. In comparison, most D2 mice moved very

reluctantly from the centre of the arena, as indicated

by repeated back and forward movements of their

upper bodies and heads, and investigated much less.

When they did move, they were inclined to move in

rapid bursts. A comparison of time moved and grids

crossed showed that B6 mice moved 4 – 5 times more

than D2. In addition, the rate of movement of the D2

mice was significantly higher than that of B6 (Table

I), which is consistent with the D2 animals moving in

quick bursts. The number of defecations was also

significantly greater in the D2 animals, which is

another indicator of stress in the animals.

Generation of F1 and F2 mice

D2 and B6 mice were mated to generate F1 mice and

subsequently these F1 mice were mated to generate

460 F2 mice. The eOFA tests were undertaken on

both sets of animals. Analysis of the F1 mice showed

an intermediate distribution of movement, between

that observed for B6 and D2 animals (Figure 1).

However, the mean activity was closer to that

observed for D2 animals than B6, suggesting that

the low movement, or stress phenotype was semi-

dominant. An analysis of the distribution of OFA in

the F2 mice revealed an extensive variability in

movement, from no movement at all through to

movement above that of parental B6 animals.

However, the frequency distribution was very skewed

towards low movement times (Figure 1), similar to

the D2 animals, which further indicated that the low

Table I Quantification of activity of mouse strains B6 and D2 on

the elevated open field

B6 D2

Time moved (s/3 min) 110+ 14 22+ 25

Grid crossings 50+ 9 17+ 12

Rate (no. grid crossings/

time moved)

0.46+ 0.09 0.87+ 0.32

Defecations 0.1+ 0.32 2.4+ 1.78

110 M. Murphy et al.

Page 4: Genetic analysis of stress responsiveness in a mouse model

OFA-stress phenotype was dominant. There were

few F2 mice with high OFA scores.

Genome scan

A genome scan was conducted on DNA from a

group of 30 F2 mice that had the lowest OFA scores

and 30 F2 mice that had the highest OFA scores

from a cohort of 230 of the F2 animals, to look for

quantitative trait loci (QTL) on the mouse genome

associated with stress-like behaviour on eOFA. A

number of QTLs were found that showed either

suggestive or significant linkage to stress-related

behavior (Table II). In particular, two loci, on

chromosomes 5 and 12 showed significant linkage

(LOD score 4 4.3). Of these, the locus on chromo-

some 12 gave the highest LOD score.

Analysis of quantitative trait loci on chromosome 12

The significant QTL seen for a locus on chromo-

some 12 and the stress phenotype was further

analysed with a greater number of mice and more

markers covering chromosome 12. High-stress F2

animals were selected from the entire 460 F2 animals

for further analysis. Table III shows the chi-square

contingency table, which compares the observed

genotypes with the expected genotypes of the

B6D2F2 animals that exhibited high stress respon-

siveness. It can be seen that there is significant

linkage with several D2 alleles across chromosome

12; in particular at the proximal end at 17.5 cM, and

at the distal end, from 41.5 cM to 51.4 cM.

In addition, we separately analysed mice that were

low stress responsive in the F2 population. We

reasoned that because these mice represented such a

low proportion of the F2 population, then a more

limited number of possible genotypes would be

responsible for low stress responsiveness than for

high stress responsiveness. Thus, if a particular B6

allele(s) on chromosome 12 were involved in low

stress responsiveness, it would be more likely to be

present in low-stress F2 animals compared to D2

alleles at the same locus in the high-stress popula-

tion. Table IV shows the results of this analysis. It

can be seen that there is significant linkage across a

contiguous region of chromosome 12 from 17.5 cM

to 44.8 cM. Furthermore, the p values are generally

more significant compared to those seen in the high-

stress analysis (cf. Table III with Table IV). In

particular, there are highly significant loci at 32.8 –

44.8 cM (Table IV). These data provide strong

support that a region on chromosome 12 is involved

with the stress phenotype in these strains of mice.

Discussion

In our initial studies on the characterisation of

different strains of mice, we looked for mice that

may have had multiple behavioural characteristics.

One of the tests we undertook was the Barnes

circular maze (Barnes, 1979), which involves mice

learning the location of an escape box under a hole

in a spatially defined location. Whereas B6 mice

learned this test relatively easily and were able to

solve the test using spatial cues, the D2 mice were

unable to solve this test. The D2 mice, when

released on the arena of the Barnes maze, moved

very quickly or not at all (Murphy, 1997). They

developed a stereotypic behaviour on the arena

over successive trials, which involved running

Figure 1. Frequency distribution of open field activity (OFA) in

B6D2F2 mice. Shown are the distribution of animals versus time

moved on the elevated OFA test (eOFA) for the first cohort of 230

B6D2F2 animals generated. Also shown are M+SD for both

parental strains, B6 and D2, as well as M+SD for a group of 30

B6D2F1 animals.

Table II Quantitative trait loci for different measures of activity

associated with open field activity

Phenotypes showing

linkage Chromosome

LOD score for

Stress phenotype

Stress and time moved 1 3.0

Stress and grids crossed 2 2.9

Stress and time moved 3 3.3

Stress and rate 5 4.39

Stress, rate and time moved 12 4.86

Note. Qote: QTL=quantitative trait loci; LOD score= logarithm

of the likelihood for the presence of a QTL.

LOD scores shown are those associated with the composite stress

score for each animal. Stress was a composite comprising open

field time moving, grid crossings, and rate of grid crossings, as

described in Methods. In addition, a number of these loci also

showed linkage to the individual components of the stress score, as

indicated.

Genetics of stress-responsiveness 111

Page 5: Genetic analysis of stress responsiveness in a mouse model

around the edge of the arena very quickly, so

quickly that in most cases they were unable to

determine which hole in the arena led to an escape

box. In some cases, the mice become so agitated

that they fell off the arena. Further, a significant

proportion of the mice underwent a mild seizure

on the Barnes maze arena, which lasted for approx

1 min, and was followed by recovery. Other data

indicate that the D2 mice are anxiogenic. Thus in

both light – dark exploration and in elevated plus

maze, this strain shows moderate to high levels of

anxiogenic behavior (Crawley et al., 1997).

We then developed a modified form of the OFA

test that was similar to a conventional open field

test, but was elevated and unenclosed, similar to the

Barnes maze. Using this test, we found significant

differences in activity between B6 and D2 mice. In

particular, the D2 mice moved very little on the

open field, in contrast to their behavior both on the

Barnes maze and in their home cages. When they

did move, they did so in quick bursts. We suggest

that these behaviours reflect a stress-proneness in

the D2 mice, which, under the conditions of the

Barnes maze, results in hyperactivity and sometimes

seizure, and in the eOFA results in freezing or little

movement. Although our eOFA is highly reflective

of conventional OFA, it is also possible that it is

detecting other behaviours in addition to stress-

proneness, such as stress-independent ambulatory

activity. It is interesting to note that the D2 mice

are also susceptible to audiogenic seizure, although

this has been observed only between 3 and 5 weeks

of age (Seyfried, 1979). It is possible that the

seizure induced by the conditions experienced on

the Barnes maze, and that induced by audiogenic

stress, have similar or related underlying genetic

mechanisms.

There is evidence that low levels of exploratory

activity on the open field arena correlate with high

blood concentrations of corticotropin-releasing hor-

mone (CRH), adrenocorticotropic hormone

(ACTH) and corticosterone (Sternberg et al.,

1992). In addition, high levels of these hormones

have been correlated to high levels of stress respon-

siveness in humans. The OFA has been used for

many years in behavioural research to look for stress-

related behaviours (Sutanto & de Kloet, 1994) and

has been utilised as the animal model to test drugs

for anxiolytic effects, because it would be expected

that these drugs would induce an increase in

exploratory activity in fear-prone animals (Radcliffe

& Erwin, 1998).

Stress-responsiveness shares phenotypic and genetic

similarity with emotionality as open field activity is the

common parameter measured

The results of this study suggest that high stress

responsiveness is a dominant trait in the B6 6 D2

cross, with the exception of the defecation rate

component. The F1 generation displayed total

exploratory time, sections crossed and rate means

similar to the D2 parental strain, supporting the

notion that stress responsiveness is a dominant trait.

With defecation rate the F1 generation exhibited an

intermediate mean to the B6 and D2 parental strains,

suggesting that the presence of D2 alleles additively

influence defecation rate.

Previous studies of emotionality have linked OFA

with defecation rate (Archer, 1973). Emotionality is

a term used to describe rodent behavioural responses

in novel environments, such as the open field arena

(Archer, 1973), and this trait is similar to the stress

responsiveness trait investigated in this study. High

emotionality has been proposed to be characterised

as low open field exploratory activity coupled with a

high defecation rate and therefore a negative

correlation would be expected between these two

measures (Flint et al., 1995). Our study did not find

this for the B6 6 D2 F2 cross, and there was no

Table III Chi-square analysis for high stress responsiveness in F2 mice of B66D2 cross and in loci on chromosome 12

Marker 182 172 34 158 239 121 99 17

Chromosomal

location

2.2 17.5 23 32.8 39.3 41.5 44.8 51.4

Observed Het 28 31 13 28 25 21 30 39

DD 22 26 8 14 15 18 15 25

BB 13 10 4 9 10 5 5 9

Total 63 67 25 51 50 44 50 73

Expected Het 31.5 33.5 12.5 25.5 25 22 25 36.5

DD 15.75 16.75 6.25 12.75 12.5 11 12.5 18.25

BB 15.75 16.75 6.25 12.75 12.5 11 12.5 18.25

w2 p 0.187 0.018 0.51 0.47 0.6 0.02 0.049 0.025

Note. Het=heterozygous; DD=homozygous for D2; BB=homozygous for B6.

112 M. Murphy et al.

Page 6: Genetic analysis of stress responsiveness in a mouse model

correlation between defecation and other aspects of

the OFA (data not shown).

Flint et al. (1995) employed a B6 6 BALB/c (an

albino mouse strain) cross to identify loci associated

with the emotionality trait, where BALB/c mice are

classified as displaying high emotionality. In that

study, three loci were found that showed significant

linkage with high emotionality, on chromosomes 1,

12 and 15. To date, the genes at these loci have not

been identified. For the chromosome 12 locus the

linked markers span a region 13.1 – 31.7 cM from

the centromere. This coincides with the region

identified in our studies. It is thus quite possible

that these two studies have identified the same locus

for stress responsiveness/emotionality. Likewise, our

initial genome scan identified a region on chromo-

some 1, which could be analogous to that found by

the Flint group as well as to that of other studies

(Caldarone et al., 1997; Gershenfeld et al., 1997;

Tarricone et al., 1995)

A subsequent study from the Flint group (Talbot

et al., 1999) further supported, from an eight-way

cross with different inbred mouse strains (three of

these being B6, D2 and BALB/c), that there was

significant linkage between chromosome 12 and high

emotionality. The most highly linked marker,

D12Mit190, in that study corresponds to approxi-

mately 22 cM in chromosome 12. The Flint group

concluded that this locus was different to the one

found in the initial B6 6 BALB/c genome scan

because the linked marker does not distinguish

between BALB/c and B6 alleles (Talbot et al.,

1999). The implication is that there must be two

loci influencing emotionality with this region of

chromosome 12 (13.1 – 31.7 cM). However, this

marker actually can distinguish between B6 and D2

alleles (128 bp and 114 bp, respectively; Whitehead

Institute/MIT Center for Genome Research, Genet-

ics and Physical Maps for the Mouse Genome: http://

carbon.wi.mit.edu:8000/cgi-bin/mouse/index).

Thus, the detected linkage by (Talbot et al., 1999)

on chromosome 12 may be due to the detection of

D2 alleles in their eight-way cross and is a similar

region to that detected in our initial B6 6 D2

genome scan. It follows that the region responsible

for this linkage may be a single locus. Overall this

evidence suggests that a region on chromosome 12 is

associated with OFA, because this is the common

parameter in stress responsiveness and emotionality.

In humans, there have been a limited number of

studies that have addressed the genetic basis of

stress. The most significant finding is from a

candidate gene approach (Lesch et al., 1996), which

found that polymorphisms in the regulatory region of

the serotonin transporter gene, and which result in

decreased expression of this gene, can account for up

to 9% of the genetic component of the anxiety-

related trait of neuroticism in that group of subjects.

This is a very exciting finding, but it leaves open the

way for the discovery of genes that underlie the great

majority of the trait for neuroticism and related

anxiety-associated traits.

References

Archer, J. (1973). Tests for emotionality in rats and mice: A

review. Animal Behavior, 21, 205 – 235.

Barnes, C. A. (1979). Memory deficits associated with senescence:

A neurophysiological and behavioral study in the rat. Journal of

Comparitive Physiology and Psychologyl, 93, 74 – 104.

Baron, M. (2002). Manic-depression genes and the new millen-

nium: poised for discovery. Molecular Psychiatry, 7, 342 – 358.

Bouchard, T. J., Jr. (1994). Genes, environment, and personality.

Science, 264, 1700 – 1701.

Caldarone, B., Saavedra, C., Tartaglia, K., Wehner, J. M., Dudek,

B. C., & Flaherty, L. (1997). Quantitative trait loci analysis

affecting contextual conditioning in mice. Nature Genetics, 17,

335 – 337.

Crawley, J. N., Belknap, J. K., Collins, A., Crabbe, J. C., Frankel,

W., Henderson, N., et al. (1997). Behavioral phenotypes of

inbred mouse strains: Implications and recommendations for

molecular studies. Psychopharmacology (Berl), 132, 107 – 124.

Table IV Chi-square analysis for low stress responsiveness in F2 mice of B6 6 D2 cross and in loci on chromosome 12

Marker 182 172 34 158 239 99 17

Chromosomal

location

2.2 17.5 23 32.8 39.3 44.8 51.4

Observed Het 20 18 11 22 24 25 18

BB 10 14 13 22 22 22 12

DD 5 3 4 9 7 5 5

Total 35 35 28 53 53 52 35

Expected Het 17.5 17.5 14 21.5 21.5 21 17.5

BB 8.75 8.75 7 10.75 10.75 10.5 8.75

DD 8.75 8.75 7 10.75 10.75 10.5 8.75

w2 p 0.342 0.031 0.029 0.002 0.0012 0.00029 0.25

Note. Het=heterozygous; DD=homozygous for D2; BB=homozygous for B6.

Genetics of stress-responsiveness 113

Page 7: Genetic analysis of stress responsiveness in a mouse model

Eley, T. C., & Plomin, R. (1997). Genetic analyses of emotion-

ality. Current Opinions in Neurobiology, 7, 279 – 284.

Flint, J., Corley, R., DeFries, J. C., Fulker, D. W., Gray, J. A.,

Miller, S., et al. (1995). A simple genetic basis for a complex

psychological trait in laboratory mice. Science, 269, 1432 –

1435.

Gershenfeld, H. K., Neumann, P. E., Mathis, C., Crawley, J. N.,

Li, X., & Paul, S. M. (1997). Mapping quantitative trait loci for

open-field behavior in mice. Behavior Genetics, 27, 201 – 210.

Gold, P. W., & Chrousos, G. P. (2002). Organization of the stress

system and its dysregulation in melancholic and atypical

depression: High vs low CRH/NE states. Molecular Psychiatry,

7, 254 – 275.

Jetty, P. V., Charney, D. S., & Goddard, A. W. (2001).

Neurobiology of generalized anxiety disorder. Psychiatric Clinics

of North America, 24, 75 – 97.

Kaufman, J., & Charney, D. (2000). Comorbidity of mood and

anxiety disorders. Depression and Anxiety, 12(Supplement 1),

69 – 76.

Kendler, K. S., Kessler, R. C., Walters, E. E., MacLean, C.,

Neale, M. C., Heath, A. C., et al. (1995). Stressful life events,

genetic liability, and onset of an episode of major depression in

women. American Journal of Psychiatry, 152, 833 – 842.

Kendler, K. S., Walters, E. E., Neale, M. C., Kessler, R. C.,

Heath, A. C., & Eaves, L. J. (1995). The structure of the

genetic and environmental risk factors for six major psychiatric

disorders in women. Phobia, generalized anxiety disorder,

panic disorder, bulimia, major depression, and alcoholism.

Archives of General Psychiatry, 52, 374 – 383.

Lesch, K. P., Bengel, D., Heils, A., Sabol, S. Z., Greenberg, B.

D., Petri, S., et al. (1996). Association of anxiety-related traits

with a polymorphism in the serotonin transporter gene

regulatory region. Science, 274, 1527 – 1531.

Lopez, J. F., Akil, H., & Watson, S. J. (1999). Neural circuits

mediating stress. Biological Psychiatry, 46, 1461 – 1471.

Moller, H. J. (2003). Bipolar disorder and schizophrenia: Distinct

illnesses or a continuum? Journal of Clinical Psychiatry,

64(Supplement 6), 23 – 27.

Murphy, M. (1997). [Behavior of different strains of inbred mice

on the Barnes maze]. Unpublished raw data.

Murray, C. J., & Lopez, A. D. (1996). Evidence-based health

policy: Lessons from the Global Burden of Disease Study.

Science, 274, 740 – 743.

Pedersen, N. L., Plomin, R., McClearn, G. E., & Friberg, L.

(1988). Neuroticism, extraversion, and related traits in adult

twins reared apart and reared together. Journal of Personality

and Social Psychology, 55, 950 – 957.

Pulver, A. E. (2000). Search for schizophrenia susceptibility genes.

Biological Psychiatry, 47, 221 – 230.

Radcliffe, R. A., & Erwin, V. G. (1998). Genetic relationship

between central beta-endorphin and novelty-induced locomo-

tor activity. Pharmacology Biochemistry and Behavior, 60, 709 –

718.

Seyfried, T. N. (1979). Audiogenic seizures in mice. Federation

Proceedings, 38, 2399 – 2404.

Sternberg, E. M., Glowa, J. R., Smith, M. A., Calogero, A. E.,

Listwak, S. J., Aksentijevich, S., et al. (1992). Corticotropin

releasing hormone related behavioral and neuroendocrine

responses to stress in Lewis and Fischer rats. Brain Research,

570, 54 – 60.

Sutanto, W., & de Kloet, E. R. (1994). The use of various animal

models in the study of stress and stress-related phenomena.

Laboratory Animals, 28, 293 – 306.

Talbot, C. J., Nicod, A., Cherny, S. S., Fulker, D. W., Collins, A.

C., & Flint, J. (1999). High-resolution mapping of quantitative

trait loci in outbred mice. Nature Genetics, 21, 305 – 308.

Talbot, C. J., Radcliffe, R. A., Fullerton, J., Hitzemann, R.,

Wehner, J. M., & Flint, J. (2003). Fine scale mapping of a

genetic locus for conditioned fear. Mammalian Genome, 14,

223 – 230.

Tarricone, B. J., Hingtgen, J. N., Belknap, J. K., Mitchell, S. R., &

Nurnberger, J. I., Jr. (1995). Quantitative trait loci associated

with the behavioral response of B 6 D recombinant inbred

mice to restraint stress: A preliminary communication.

Behavior Genetics, 25, 489 – 495.

Vanitallie, T. B. (2002). Stress: A risk factor for serious illness.

Metabolism, 51(6 Supplement 1), 40 – 45.

114 M. Murphy et al.