gene polymorphisms associated with temperament in merino ...methods section of my journal paper, and...
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Gene polymorphisms associated with temperament in
Merino sheep
Xiaoyan Qiu BSc MSc
The thesis is presented for the degree of
Doctor of Philosophy
2015
The University of Western Australia
Faculty of Natural and Agricultural Sciences
School of Animal Biology
Declaration
The work presented in this thesis is original work of the author, and none of the material
in this thesis has been submitted either in full, or part, for a degree at this or any other
university or institution. The experiments and manuscript preparation were carried out
by myself after discussion with my supervisors, Dr. Dominique Blache, Professor
Graeme B. Martin and Dr. Shimin Liu.
Xiaoyan Qiu
September 2015
i i
Table of Contents (Detailed indices are provided at the start of each chapter)
Page
Summary ii
Acknowledgements iv
Publications vi
List of abbreviations vii
Chapter 1: General introduction 1
Chpater 2: Literature review 4
Chapter 3: General materials and methods 36
Chapter 4: Associations between temperament and gene polymorphisms 48
in the dopaminergic system and adrenal gland in sheep
Chapter 5: The association of CYP17 SNP628 and DRD2 SNP939 genotypes 64
with behavioural and physiological cortisol response
Chapter 6: Heritability of behavioural reactivity to isolation based on DRD2 78
SNP939 and CYP17 SNP628 genotypes associated with sheep
temperament phenotype
Chapter 7: Cognitive learning ability in Merino sheep with different DRD2 91
SNP939 genotypes Chapter 8: General discussion 110
References 115
ii
Summary
When individuals are exposed to stressful environmental challenges, the response varies
widely in one or more of three components of the stress response: psychological
(emotional), behavioural and physiological. This variability among individuals can be
defined as temperament. Temperament affects not only the perception and responses to
the stressor, but also can affect cognition. The genetic basis of temperament is not
clearly understood, but it could be explained by polymorphisms in genes that regulate
brain activity and glucocorticoid synthesis. In this thesis, I tested the general hypothesis
that polymorphisms of specific genes will be associated with the difference in
behavioural reactivity and physiological response in sheep of known temperament
(nervous or calm). I mainly used sheep from the UWA Merino flock that had been
selected over 20 generations for two temperaments: a nervous line and a calm line,
based on high or low reactivity to humans and social isolation.
Firstly, using nervous (n = 58) or calm (n = 59) ewes from lines that had been selected for
temperament for 20 generations, we identified polymorphisms in a specific gene
responsible for cortisol production (CYP17), and in three specific genes associated with
personality and behavioural traits: dopamine receptors 2 and 4 (DRD2, DRD4), and
monoamine oxidase A (MAOA). The frequencies of CYP17 SNP628 and DRD2 SNP939
differed significantly between the two temperament lines, but those for DRD2 SNP483
and the 2 MAOA SNP genotypes did not.
To validate the correctness of the two SNPs associated with temperament (CYP17
SNP628 and DRD2 SNP939) as genetic markers for prediction of sheep temperament,
we genotyped 278 non-selected sheep for the DRD2 SNP939 and CYP17 SNP628
polymorphisms. We then tested their behavioural response to the challenges used to
assess temperament) and their cortisol response to exogenous ACTH. The results
showed that responses to the behavioural tests (‘arena test’ and ‘isolation box’ test) were
affected by the DRD2 SNP939 genotype and the cortisol response to ACTH challenge
was affected by the CYP17 SNP628 genotype. We concluded that, for sheep, a
combination of the DRD2 SNP939 C allele and the CYP17 SNP628 A/A genotype
could be a genetic marker for prediction of nervous temperament, and that a
combination of DRD2 SNP939 T/T and CYP17 SNP628 G/G could be a genetic marker
iii
for prediction of calm temperament.
We then calculated the heritability of behavioural reactivity to isolation (one
measurement of temperament) based on the 2 SNPS genotypes associated with
temperament phenotype. The outcome suggested that the phenotypic heritability of
reactivity to social isolation, as measured by the agitation score, can be improved by
genetic selection based on these 2 SNPs genotypes, and that the combination of the 2
SNPs genotypes was associated with the highest heritability. This result confirmed the
above conclusions that DRD2 SNP939 and CYP17 SNP628 genotypes are associated
with the two temperaments.
In addition to the association of emotional reactivity (or ‘temperament’) with
behavioural and physiological responses, previous studies have suggested that
temperament is associated with cognition. Moreover, polymorphism in DRD2 has been
implicated in variability in cognitive functions in humans. However, the effect of the
interaction between emotional reactivity and DRD2 polymorphism on cognitive
function is poorly understood. Therefore, we investigated the association of our
temperament-associated DRD2 SNP939 genotypes with cognitive learning abilities in
sheep and found that the ‘calm’ temperament-associated DRD2 SNP939 T/T genotype
was linked to a greater ability in reversal learning of spatial discrimination than the
‘nervous’ temperament-associated C/C +C/T genotype.
In conclusion, this thesis is a first step in the identification of potential genetic markers
for prediction of calm or nervous temperament in sheep. The DRD2 SNP939 is
specifically associated with behavioural reactivity and cognitive learning ability, and the
CYP17 SNP628 is specifically associated with the physiological cortisol response. The
combination of these 2 SNPs could be used as a genetic marker for the temperament
prediction. However, many other genes involved in brain neurotransmitter systems and
in hypothalamic-pituitary-adrenal axis could also be associated with sheep temperament,
so, perhaps using genome-wide association study (GWAS), we need to investigate the
association of other genes with sheep temperament.
iv
Acknowledgements
It was a great opportunity to conduct my PhD study at the School of Animal Biology in
Institute of Agriculture of the University of Western Australia (UWA), funded by
Scholarship for International Research Fees (SIRF). My PhD experience has been a
long journey with many challenges. I could not have completed all the experiments
presented in this thesis without the generous help and support of the following people.
I want to express my warmest and deepest thanks to my supervisors A/ Prof. Dominique
Blache, Prof.Graeme Martin and Dr. Shimin Liu for their invaluable advice and
guidance, great support and patience, productive discussions and meticulous corrections
of each manuscript of my journal papers and thesis. They are always willing to help me
in experiments and in daily life. Many thanks to Dominique Blache who gave me great
help and patient guidance for all the experiments.
I would like to give special thanks to Jason Ledger. I could not start my molecular
experiments without his guidance in my initial stages. He generously allowed me to use
some of his experimental materials and DNA extraction kits, helped me to correct the
methods section of my journal paper, and gave me great support in my experiments.
I also want to express my heartfelt appreciation to our Graduate Students Coordinator,
Dr. Harriet Mills, who helped me to get the approval from UWA Graduate Research
School of my emergency leave so I could return to China when my mother was
seriously sick.
I also want to express my sincere gratitude to those people who have contributed to all
of my work. I especially would like to express my thanks to Margaret Blackberry for
her excellent and meticulous technical assistance for cortisol assay; Stacey Rietema and
Lorelle Barrett for their kind help in collecting blood samples and cannulating sheep;
other staff and postgraduate students, including Gary Cass, Prof. Philip Vercoe, Dr.
Zoey Durmic, Joy Vadhanabhuti, Cesar Rosales-Nieto, Xixi Li, Kelsie Moore, Joe Steer,
Kirrin Lund, Mikaela Ciprian, Yongjuan Guan, Umar Farooq, Stephanie Payne and
Anna Amir for their willingness to share their experience with me and for their
v
contributions to pleasant atmosphere in the Animal Production Group at Floreat.
Last but not least, I would like to give many thanks to my parents and my husband
Yuemin Li for lifting me up when I was depressed and stressed. Thanks for your
enduring love, encouragement, and support for me. Special thanks to my lovely
five-year-old son. During the long journey of my PhD, when I missed him indescribably,
I was kept going by his voice and laughter on the Skype phone every evening.
vi
Publications
Peer-reviewed papers
1. Qiu, X. Y., Ledger, J., Zheng, C., Martin, G. B., Blache, D. (2016). Associations
between temperament and gene polymorphisms in the dopaminergic system and
adrenal gland in sheep. Physiology and Behaviour, 153:19-27.
2. Qiu, X. Y., Grant, E., Zheng, C., Martin, G. B., Blache, D. (2015). Cognitive
learning ability in Merino sheep with different DRD2 SNP939 genotypes. Animal
Cognition (submitted).
Conference Contributions
1. Qiu, X. Y., Ledger, J., Martin, G. B., Blache, D. (2013). Gene polymorphisms
associated with temperament in Merino sheep. The Annual Scientific Meeting of the
Endocrine Society of Australia and the Society for Reproductive Biology, 25th -
28th August, 2013, Sydney Convention and Exhibition Centre.
2. Qiu, X. Y., Ledger, J., Martin, G. B., Blache, D. (2013). Gene polymorphisms
associated with temperament in Merino sheep. WA Endocrine and Reproductive
Sciences Symposium, 14th August, 2013, CSIRO Centre for Environment and Life
Sciences, Perth.
3. Qiu, X. Y., Ledger, J., Zheng, C., Martin, G. B., Liu, S., Blache, D. (2015). Gene
polymorphisms associated with temperament in Merino sheep. Symposium for
Western Australian Neurosciences, 9th April, 2015, Western Australian
Neuroscience Research Institute, Perth.
vii
List of abbreviations
AADC aromatic amino-acid decarboxylase
ACTH adrenocorticotrophic hormone
ADHD attention deficit hyperactivity disorders
ADR2A adrenergic receptor 2A
AUCG area under the curve calculated to ground
AUCB area under the curve calculated to baseline
AVP arginine vasopressin
BDNF brain-derived neurotrophic factor
COMT catechol-O-methyltransferase
CRH corticotrophin- releasing hormone
CRH-R1 CRH receptor 1
CYP17 cytocrome P450 17
DAT dopamine transporter
DBH dopamineβ-hydroxylase
DNA deoxyribonucleic acid
DOPA dihydroxyphenylalanine
DRD1 dopamine receptor 1
DRD2 dopamine receptors 2
DRD4 dopamine receptors 4
EDS extradimensionalshifts
GWAS genome-wide association study
HPA hypothalamo-pituitary adrenal
5-HT 5-serotonin
5-HTP 5-hydroxy tryptophan
5-HTT 5-serotonin transporter
IBT isolation box test
IDS intradimensional shifts
MAO monoamine oxidases
MAOA monoamine oxidase A
NET norepinephrine transporter
NO nitric oxide
17-OHPREG 17-hydroxypregnenolone
vii 17-OHPROG 17-hydroxyprogesterone
PCR polymerase chain reaction
PREG pregnenolone
PROG progesterone
RFLP restriction fragment length polymorphism
PVN paraventricular nucleus
RIA radioimmunoassay
SNPs single nucleotide polymorphisms
TCI temperament character inventory
TH dihydroxyphenylalanine
TPH tryptophan hydroxylase
VMAT vesicular monoamine transporter
VNTRs variable number of tandem repeats
Chapter 1 General Introduction 1
Chapter 1
General Introduction
When individual humans or animals are exposed to a stimulus, they first evaluate the
situation on the basis of parameters such as suddenness, familiarity and pleasantness
through brain processing (Boissy 1995). After this evaluation, they build and express
psychological, behavioural and physiological responses (Corr 2009). In animals, only
the behavioural and physiological responses can be directly measured and assessed. The
usual indicator of the physiological response is cortisol secretion (Corr 2009). The
behavioural response varies among individual animals exposed to the same stimulus,
and this variability is known as temperament (Strelau 1987; Rothbart et al., 2000;
Mervielde et al., 2005; Shiner and DeYoung 2011; Blache and Bickell 2010, 2011).
Variation among individuals in temperament is the result of variation in genetics
(Strelau 1987; Rothbart et al., 2000; Mervielde et al., 2005; Saudino 2005; Krueger and
Johnson 2008) and in life experience (Rothbart et al., 2000; Krueger and Johnson 2008).
Sheep of calm or nervous temperament show different physiological responses (cortisol
secretion) and behavioural responses (motor activity) following exposure to stressors
such as novelty and isolation. The genetic basis of temperament has been confirmed in
these animals, but the physiological mechanisms that implement the effects of
temperament on physiological and behavioural responses to a stimulus are not
understood. Hypothetically, the genes associated with temperament could be involved in i)
the perception or the process of evaluation at brain level, before responses are elicited;
or ii) the modulation of the physiological response (cortisol production as a result of
activation of the HPA axis) or the behavioural response.
At the brain level, human personality traits (such as temperament) have been linked to
neurotransmitter systems (Cloninger 1987) and genetic differences in these systems
could be the neurological basis of temperament. For example, in humans,
polymorphisms of genes encoding for dopamine receptors (DRD4, DRD2) and
monoamine oxidase A (MAOA), an enzyme responsible for the metabolism of
5-serotonin, dopamine as well as norepinephrine, have all been studied and found to be
Chapter 1 General Introduction 2 associated with psychological disorders and behavioural traits. Similarly, genetic
differences in enzymes involved in the HPA axis could explain the effect of
temperament on glucocorticoid production. Indeed, it has been shown that the amplitude
of the cortisol response is affected by temperament (behaviour) in humans, monkeys,
dogs, cattle and sheep. Moreover, in the South African Angora goat, polymorphisms of
CYP17, an enzyme involved in the synthesis of adrenal cortisol (Nakajin et al., 1981;
Vander et al., 2001), affect its activity and, consequently, cortisol production in response
to a metabolic stress (Storbeck et al., 2007). However, the existence of this
polymorphism and its potential role as a mediator of the effect of temperament on
cortisol secretion have never been investigated.
In addition to the association of emotional reactivity (‘temperament’) with the
behavioural and physiological responses, previous studies have suggested that
temperament is also associated with cognition. Lower levels of emotional activity were
found to be linked with better performance in cognitive tasks, including spatial learning,
discrimination and recognition (Mendl 1999; Erhard et al., 2004; Lansade and Simon
2010; Bickell et al., 2011; Butts et al., 2013). In addition, polymorphism in the DRD2
has been implicated in variability in cognitive function in humans and animals (Smith et
al., 1999; Kruzich and Grandy 2004; Lee et al., 2007; Jocham et al., 2009). However,
the effects of interactions between emotional reactivity and DRD2 polymorphism on
cognitive function are poorly understood.
The general hypothesis of this thesis is that polymorphisms of specific genes will be
associated with differences in behavioural reactivity and in physiological response to
stressors in sheep of known temperament (calm or nervous). The general aim of this
thesis is to identify a genetic marker for temperament (calm and nervous) that can be
used for selection in sheep. A step towards the identification of this genetic marker will
provide useful information for sheep reproduction, evolution, welfare, conservation in the
wild, and future breeding programs. To achieve this aim, four experiments were
conducted:
1) Investigation of the association of polymorphisms of four candidate genes (CYP17,
DRD4, DRD2, MAOA) with temperament (calm and nervous) in Merino sheep
(Chapter 4);
2) Verification that the polymorphisms (identified in Chapter 4) affect the behavioural
Chapter 1 General Introduction 3
responses and physiological responses of sheep of unknown temperament (Chapter
5);
3) Calculation of the phenotypic heritability of temperament measured by the reactivity
to social isolation (IBT) based on the polymorphisms (identified in Chapters 4 and 5)
associated with temperament (Chapter 6);
4) Investigation of the association of temperament-associated polymorphisms
(indentified in Chapters 4 and 5) with temperament-associated variation in cognitive
learning ability (Chapter 7).
Chapter 2 Literature Review 4
Chapter 2
Literature Review
Page
2.1 Introduction of temperament 5
2.1.1 The definition of temperament 5
2.1.2 The dimensions of temperament 6
2.1.3 The importance of temperament 6
2.2 The impact of temperament on behavioural response to stressors 7
2.2.1 The individual variance in behaviours 8
2.2.2 Neurophysiological basis of behavioural response (temperament) 9
Dopamine
Serotonin
2.3 The impact of temperament on physiological response to stressors 15
2.3.1 The physiological mechanism in stress response 15
2.3.2 Individual variance in cortisol or corticosterone response 17
2.4 The impact of temperament on cognition 19
2.4.1 The individual variance in cognition 19
2.4.2 The mechanism involved in the cognition 20
2.5 The genetic basis of temperament 21
2.5.1 Molecular genetics 21
Gene structure
Gene polymorphisms
Methods for genetic studies
2.5.2 Candidate genes involved in temperament 23
Candidate genes involved in the variability in behaviours
Candidate genes involved in the variability along the HPA axis
Gene polymorphism and cognition
2.6 The animal model – our temperament sheep flock 32
2.7 Summary 34
Chapter 2 Literature Review 5 Animals of different temperament show different physiological responses (eg, cortisol
secretion) and behavioural responses (eg, motor activity) to exposure to stressors such as
novelty and isolation. The genetic basis of these differences is not understood and is
therefore the focus of the work described in this thesis. After discussing the nature of
temperament and the associated physiological and behavioural traits, this review of
literature focuses on the neuroendocrine and genetic basis of temperament, considers
candidate genes that could be used as genetic markers for temperament, and outlines
phenotype tests for the validation of genetic results.
2.1 Introduction of temperament
2.1.1 Definition of temperament
The very existence of emotion in animals has long been debated until, in 1872, Darwin
recognized the existence of emotion in animals and suggested that that animals can
experience different responses, including both positive and negative reactivity,
displayed in terms of pleasure or fearful behaviours, when exposed to triggering
psychological, physical or physiological situations. Boissy (1995) drew on the previous
centuries of research and concluded that animals had a strong fearful response when
exposed to unfamiliar situation or threatening circumstances, in similar ways to humans.
A recent study showed that when sheep are exposed to unfamiliar and threatening
circumstances, they display fear or anger responses dependent on whether or not the
situation was under their control (Greiveldinger 2007). These responses in sheep are
somewhat similar to those observed in humans in both their nature and their individual
variability (Boissy 1995). When individual humans are provoked by a stimulus or a
response-eliciting situation, they evaluate the situation on the basis of seven different
parameters: suddenness, familiarity, pleasantness, controllability, predictability,
expectations, and social norms. For animals, all of the the first six parameters are
demonstrable (Boissy 1995). After evaluation of the situation, the response has three
aspects (Corr 2009): 1) The psychological response or feelings, including positive and
negative feelings; 2) The behavioural response; and 3) The physiological response that
involves changes in, for example, adrenaline, noradrenaline, serotonin, dopamine and
cortisol (Deckersbach 2006; Haas 2007; Corr 2009). Cortisol is usually used as the
indicator of physiological response (Corr 2009). A combination of all of these responses
constitutes the emotional reactivity to stressors or eliciting situations. Differences
among individuals in the overall evaluation are the basis of variability in individual
Chapter 2 Literature Review 6 emotional reactivity, and this variability among individuals is called temperament
(Strelau 1987; Rothbart et al., 2000; Mervielde et al., 2005; Blache and Bickell 2010,
2011; Shiner and DeYoung 2011). During the past 20 years at UWA, a flock of Merino
sheep has been selected to generate two lines according to their different responses to
stimuli: i) The "calm" line is less fearful of humans and less reactive to isolation; ii) The
"nervous" line displays more fearful responses. These two lines have proven to be a
most valuable model for experimentation on productivity and on the behaviour and
physiology of stress.
2.1.2 The dimensions of temperament
In humans, it is thought that the temperament system is an important sub-system of
personality (Corr 2009). Thomas and Chess (1977) conceptualized temperament in nine
broad dimensions: level of activity, approach/withdrawal, intensity, threshold,
adaptability, rhythmicity, mood, persistence of attention span, and distractibility. This
array is similar to the classic ‘big five’ personality factors (N, E, O, A, C) defined by
McCrae and colleagues (McCrae and Costa 1986, 1987; McCrae and John 1992):
Neuroticism (N), the tendency to be anxious, nervous, self-pity, hostile, impulsive,
self-conscious, irrational, depressed, and low self-esteemed; Extraversion (E), the
tendency to be positive, assertive, energetic, social, talkative, and warm; Openness (O),
the tendency to be curious, artistic, insightful, flexible, intellectual and original;
Agreeableness (A), the tendency to be forgiving, kind, generous, trusting, sympathetic,
compliant, altruistic, and trustworthy; and Conscientiousness (C), the tendency to be
organized, efficient, reliable, self-disciplined, achievement-oriented, rational, and
deliberate. Similar arrays can be used for animals (Rothbart 2007). These dimensions of
temperament can be linked to processes and reactions, related to stress and emotion, that
are induced by exposure to stressors and displayed in various psychological disorders or
behavioural traits, including depression, anxiety, fear, panic, neuroticism, schizophrenia,
obesity, substance dependence and abuse, pathologic gambling, impulsivity, aggression,
violence, suicidal behavior, child abuse behavior, youth progression, novelty seeking
and attention deficit hyperactivity disorder (McCrae and Costa 1986; Hooker, Frazier
and Monahan 1994).
2.1.3 The importance of temperament
There is a large body of evidence for a strong relationship between animal temperament
Chapter 2 Literature Review 7 and reproductive performance, production traits and animal welfare.
In sheep, studies have shown that temperament affects reproductive performance
(Price 2002; Gelez et al., 2003; Hart et al., 2006, 2008; Bickell et al., 2009a). In the
UWA flock, calm ewes show an increased proceptivity during the mating period, a
higher spontaneous ovulation rate, a higher ovulation rate in response to oestrus
synchronization, better embryo survival and organ development, a higher twin-bearing
percentage and a higher survival rate of lambs compared to nervous ewes (Gelez et al.,
2003; Hart et al., 2006; Hart et al., 2008; Hart et al., 2008; Bickell et al., 2009a; Blache
and Bickell 2010). It has been also suggested that calm animals had higher daily weight
gains, improved ease of milking, increased quantity of milk production, higher
concentration of protein in milk and also lower production costs (less feed required and
less incidence of illness) compared to nervous animals (Burrow 1997; Murray et al.,
2009; Pajor et al., 2010; Horton and Miller 2011).
In addition to reproductivity and production traits, selection for temperament could
improve the welfare of sheep.Animals in a state of good welfare can show better
adaptation to their environment and this is beneficial to their reproductive performance
and production traits under intensive farm conditions, whereas animals in a state of poor
welfare usually suffer and do not produce as well (Veissier and Boissy 2007). In
addition, animals that are more fearful of humans and more reactive to a stimulus
(nervous) show poor ability to adapt to their captive environment and therefore have a
more stressful experience, reducing their level of welfare (Bickell et al., 2009).
Reducing stress in farm animals can be achieved by improving farm management or
implementing pharmacological treatment. Selection for temperament offers an
alternative by modifying behavioural reactivity.
2.2 The impact of temperament on behavioural response to stressors
Stress is defined as a challenge to, or disruption of, homeostasis. Tilbrook and Clarke
(2006) added more detail by defining stress as “a complex physiological state that
embodies a range of integrative physiological and behavioral processes that occur when
there is a real or perceived threat to homeostasis”. There are two types of stressor (acute
or chronic) depending on intensity and timing. Acute stressors induce the release of
catecholamines in both the sympathetic and central nervous systems. By contrast,
responses to chronic or intermittent stressors involve the activation of the
hypothalamic-pituitary-adrenal axis (Greenberg, Carr and Summers 2002). The
Chapter 2 Literature Review 8 responses to stressors are not only physiological but also include both psychological and
behavioural components.
2.2.1 Individual variability of behavioural response
It is clear that there is variability in the behavioural response to the same stimulus or in
the same eliciting situation between individuals, which is the basis that the temperament
is defined. For example, in humans, this variance between individuals were indicated in
many emotional reactivity and behavioural traits including depression, anxiety, fear,
panic, substance dependence and abuse, impulsivity, aggression, violence, suicidal
behaviour, child abuse behaviour, youth progression, novelty seeking and attention
deficit hyperactivity (Rothbart et al., 1994; Corr 2009). Similar results were also
observed in animal species (Table 2.1).
Table 2.1 The investigations of variance in behavioural response to stressors in animal species
Species Behaviours Stressors References
Monkey alcohol consumption separation Barr et al., 2009
novelty-seeking novelty Bailey and Julia 2007
agitation separation Spinelli et al., 2007
aggression food/cage competition Newman et al., 2005;
Wendland et al., 2006
Horse curiosity and vigilance novelty Momozawa et al., 2005
locomotion/restlessness novelty and handling Visser et al., 2003
Bird early exploratory behaviour novelty Fidler et al., 2007
Dog aggression strangers Ito et al., 2004; Duffy et
al., 2008
fear and aggression threatening situations Netto and Planta 1997;
Svartberg 2006
shyness-boldness spatial separation Svartberg 2002
Chicken cowardly behavior fear-eliciting situation Hong et al., 2008b
Rat anxiety conflict conditions:
handling, novelty, shock
Fernandez-Teruel et al.,
1991, 1992; Ferre et al.,
1995
novelty-seeking novelty Giorgi et al., 1997
Sheep fear presence of human Blache and Ferguson
2005; Blache and Bickell
2010, 2011; Hough 2012
Chapter 2 Literature Review 9 agitation social isolation Blache and Ferguson
2005; Blache and Bickell
2010, 2011
sexual behavior ram Gelez et al., 2003
2.2.2 Neurophysiological basis
It has been suggested that the individual variance in behavioural response depends on
the variance in the perception or evaluation of the situation before the response
happened (Boissy 1995). Lazarus and his colleagues (Lazarus and Fblkman 1984) have
argued that the major determinant of coping responses is the perception of the situation
by the individual. Therefore, the perception or evaluation process in the brain is mainly
responsible for the variance of behavioural response to stimulus. It has been long
acknowledged that the dopaminergic and serotonergic systems are the two main central
nervous systems that are involved in the perception or evaluation process in brain and
are most widely implicated in the regulation of various psychological disorders or
behavioural traits (Reif and Lesch 2003; Noblett and Coccaro 2005; Tilbrook and
Clarke 2006; Turner et al., 2012).
The dopaminergic pathway
Dopamine
Since the first study suggesting that human personality traits are linked to
neurotransmitter systems (Cloninger 1987), the dopaminergic system has become the
subject of intensifying focus. Dopamine is one of the catecholamine neurotransmitters
and is found in humans and animals, including invertebrates. Dopaminergic neurons
project to many regions of brain, including prefrontal cortex, striatum, nucleus
accumbens and olfactory tubercle and pre-synaptic membrane in limbic area (Moore
and Bloom 1978; Swanson 1982; Sobel and Corbett 1984; Goldman-Rakic 1987;
Tzschentke 2001; Gong et al., 2012). Dopamine exerts its function by binding to its
specific membrane receptors. So far, five dopamine receptors named as DRD1-DRD5
have been isolated. DRD1 and DRD5 are mainly distributed at cerebral cortex,
amygdala, hippocampus and in the parafascicular nucleus of the thalamus; DRD2 is
mainly located in the striatum, olfactory tubercle and nucleus accubens; DRD3 is
mainly distributed at pre-synaptic membrane in limbic area; and DRD4 is mainly
distributed at the prefrontal cortex, midbrain and the medulla (Vallone et al., 2000).
Chapter 2 Literature Review 10 Among these regions, the prefrontal cortex and the striatum have been widely
acknowledged to be involved in the mediation of various psychological disorders or
behavioural traits including depression, anxiety, fear, panic, ADHD (attention deficit
hyperactivity disorders), impulsive and aggression related behaviours (Goldman-Rakic
1987, 1990; Wise and Rompre 1989; Tzschentke 2001). Therefore, DRD2 (main
distribution in the striatum) and DRD4 (main distribution in the prefrontal cortex) have
been investigated in depth to be involved in the mediation of various psychological
disorders or behavioural traits in humans and other species (Table 2.2).
Synthesis and catabolism of dopamine
The synthesis and catabolism of dopamine is illustrated in Figure 2.1. Tyrosine, the
precursor, enters the brain from the blood with the aid of a specific amino acid
transporter. In dedicated neurons, tyrosine is converted into dihydroxyphenylalanine
(DOPA) by tyrosine hydroxylase (TH), a step that is believed to be rate-limiting in
dopamine synthesis. Dopamine is synthesized from DOPA by aromatic amino-acid
decarboxylase (AADC) and then transported into vesicles via vesicular monoamine
transporter (VMAT) and stored in the terminals before being released into the synaptic
cleft during activation of the neuron by electrical impulses. A dopamine transporter
(DAT) can re-uptake dopamine from the synaptic cleft and return it into the nerve
terminals. Dopamine is degraded by the monoamine oxidases (MAO) for which there
are two isoforms, MAOA and MAOB (Lan et al., 1989), with MAOA being most
important and playing a role regulation of psychological disorders and behaviours as
depression, alcoholism and impulsive behaviours (Sullivan et al., 1990; Brunner et al.,
1993; Devor et al., 1993; Faraj et al., 1994; Verkes et al., 1998; Eensoo et al., 2005;
Nilsson et al., 2006).
Chapter 2 Literature Review 11 Table 2.2 The investigations of DRD2 and DRD4 involved in the variance of behaviours in
human and animal species
Receptor Behaviours Species Reference
DRD2 schizoid/avoidant behaviour human Blum et al., 1997
pathological gambling human Comings et al., 1996a
ADHD human Comings et al., 1996b
extraversion/agreeableness human Jonsson et al., 2003
impulsivity/sensation-seeking human Hamidovic et al., 2009;
Esposito-Smythers et al., 2009;
Kawamura et al., 2013
childhood aggression human Zai et al., 2012
substance addiction
hedonic/reward
human
human
rats
Noble et al., 1991, 1994a, b;
Lawford et al., 1997; Sullivan et
al., 2013; Wang et al., 2013
Han et al., 2007; Blum et al.,
2011
Johnson and Kenny 2010
DRD4 impulsive behaviour human Kirley et al., 2004; Congdon et
al., 2008; Reiner and Spangler
2011
novelty seeking human Ono et al., 1997; Noble et al.,
1998; Strobel et al., 1999;
Keltikangas-Jarvinen et al., 2003
ADHD human LaHoste et al., 1996; Rowe et
al., 1998; Smalley et al., 1998;
Swanson et al., 1998; Faraone et
al., 1999; Miglia et al., 2000;
Holmes et al., 2000; Sunohara et
al., 2000; Tahir et al., 2000;
Roman et al., 2001; Curran et
al., 2001; Mill et al., 2001;
Kramer et al., 2009
novelty-seeking monkey Bailey and Julia 2007
curiosity and vigilance
aggressiveness
early exploratory behaviour
horse
dog
bird
Momozawa et al., 2005
Ito et al., 2004
Fidler et al., 2007
Chapter 2 Literature Review 12
Figure 2.1 Overview of the dopaminergic synthesis and catabolism (adapted from Bah Rosman
2008).TH= Tyrosine hydroxylase; AADC= Aromatic amino acid decarboxylase; DOPA=
Dihydroxyphenylalanine; DA=Dopamine; VMAT= Vesicular monoamine transporter;
DAT=Dopamine transporter; MAO=Monoamine oxidase
The serotonergic pathway
Serotonin
Since the initial time of the identification of serotonin by Rapport et al. (1948), there has
been a major increase in investigations of its anatomic location and functions in brain.
Chapter 2 Literature Review 13 Some studies suggested that there is projection of 5-serotonin (5-HT) to the prefrontal
cortex (Lewis et al., 1986) where there is an overlap of dopamine and serotonin
receptors (Goldman-Rakic et al., 1990), the main innervation targets for 5-HT neuron
seem to be the brain stem and spinal cord (Jacobs and Klemfuss 1975; Goldman-Rakic
1987; Tork 1990; Mann 1999; Muller 2009). Over the last 30 years, a variety of studies
with 5-HT receptor agonists has established the role of serotonin in the psychiatric
related disorders and behaviours, including major depression, anxiety, schizophrenia,
substance dependence and abuse, eating disorders in humans and rats (Tork 1990;
Jacobs and Azmitia 1992; Schreiber and De Vry 1993; Baldwin and Rudge 1995; Mann
1999; Muller 2009). The effect of serotonin on the cell or neurons targets is mediated by
serotonin receptors. So far, 14 sub-types (labeled 5-HT1-14) have been identified
(Hoyer and Martin 1996). Of these, 5-HT1, 5-HT2 and 5-HT7 have been investigated in
depth to be involved in psychiatric disorders related behaviours including anxiety,
depression, schizophrenia and substance dependence in humans, mice and rats (Table
2.3).
Synthesis and Metabolism of 5-serotonin
As shown in Figure 2.2, tryptophan is the precursor for serotonin synthesis and is also
transported from the blood into the brain via a specific amino acid transporter. In
dedicated neurons, tryptophan is converted into 5-hydroxy tryptophan (5-HTP) by
tryptophan hydroxylase (TPH), a step that is believed to be rate-limiting in serotonin
synthesis. Aromatic amino-acid decarboxylase (AADC) also converts 5-HTP into
5-serotonin (5-HT) that is then transported into vesicles via vesicular monoamine
transporter (VMAT) and stored in the terminals before being released into the synaptic
cleft during activation of the neuron by electrical impulses. A 5-serotonin transporter
(5-HTT) can re-uptake 5-HT from the synaptic cleft, thus returning it into the nerve
terminal. As with dopamine, 5-HT is degraded by MAOA and MAOB (Lan et al., 1989)
and, again, MAOA is most important role and thought to play an important role
regulation of psychological disorders and behaviours (Sullivan et al., 1990; Brunner et
al., 1993; Devor et al., 1993; Faraj et al., 1994; Verkes et al., 1998; Eensoo et al., 2005).
Chapter 2 Literature Review 14
Table 2.3 The investigations of 5-HT1, 5-HT2 and 5-HT7 involved in psychiatric disorder
related behaviours in human and animals
Serotonin
receptor
Behaviours Species References
5-HT1 anxiety human Jin et al., 1992; Huang et al.,
2004
mouse Heisler et al., 1998; Parks et al.,
1998; Ramboz et al., 1998; Toth
2003
depression human Blier and Ward 2003;
rat Przegalinski et al., 1995;
Overstreet et al., 2003
substance dependence human Lappalainen et al., 1998
mouse Brunner and Hen 1997; Rocha et
al., 1998
5-HT2 schizophrenia human Williams et al., 1996, 1997;
Tsuang et al., 2013
food intake human Lappalainen et al., 1995
mouse Tecott et al., 1995
substance dependence human Holmes et al., 1998; Virkkunen
et al., 2008
5-HT7 depression mouse Guscott et al., 2005
rat Wesołowska et al., 2006
anxiety mouse Wesołowska et al., 2006
In summary, the two nervous systems (dopaminergic and serotonergic systems)
including dopamine and serotonin synthesis and metabolism process and their receptors
are involved in above mentioned various psychological disorders and behaviours.
Serotonergic system is more linked to psychological disorders related behaviours like
depression, anxiety, schizophrenia, food intake and substance abuse, whereas
dopaminergic system is more linked to the behavioural reactivity including fear, ADHD,
impulsivity and aggression related behaviours.
Chapter 2 Literature Review 15
Figure 2.2 Overview of the serotonergic synthesis and catabolism (Bah Rosman 2008).
TPH= Tryptophan hydroxylase; AADC= Aromatic amino acid decarboxylase; 5-HTP=
5-hydroxytryptophan; 5-HT=5-serotonin; VMAT= Vesicular monoamine transporter;
5-HTT=5-serotonin transporter; MAO=Monoamine oxidase
2.3 The impact of temperament on physiological response to stressors
2.3.1 The physiological mechanism in stress response
The hypothalamo-pituitary adrenal (HPA) axis, a classic neuroendocrine system, is the
primary mediator of physiological responses to stressors so it is often considered to be
Chapter 2 Literature Review 16 the main ‘stress system’. The HPA axis controls the production of glucocorticoids
(Figure 2.3).
Figure 2.3 Schematic diagram of the HPA axis (Tilbrook and Clarke 2006).
Its essential role was understood early in the development of modern endocrinology
after it was realized that the adrenal gland was important for dealing with stress (Selye
1946). The adrenal activity is controlled and regulated by signals from the
hypothalamus that are translated and magnified by the anterior pituitary gland. Exposure
to a stressor leads to the secretion of corticotrophin- releasing hormone (CRH) and
arginine vasopressin (AVP) by neurons located paraventricular nucleus (PVN) that
project their terminals in the median eminence. CRH and AVP are released into the
hypophyseal portal system, a specialized circulatory system connecting the
hypothalamus to anterior pituitary gland, and then reach the anterior pituitary. In the
anterior pituitary gland, CRH and AVP stimulate the responsive and specialised cells,
the corticotrophs, to produce the adrenocorticotrophic hormone (ACTH). ACTH acts on
the adrenal cortex to stimulate the synthesis of glucocorticoids. Glucocorticoids regulate
Chapter 2 Literature Review 17 the secretion of CRH, AVP and ACTH through negative feedback actions in the brain,
to ultimately inhibit the synthesis and secretion of CRH and AVP, and anterior pituitary
gland, where corticotrophs become less responsive to CRH and AVP. The nature of the
glucocorticoids varies between species but cortisol and corticosterone are the main
active glucocorticoids (Tilbrook and Clarke 2006). In rodents and avian species, the
predominant glucocorticoid is corticosterone, whereas in humans and many mammalian
species, the predominant glucocorticoid is cortisol.
Therefore, the cortisol or corticosterone, as the final effector of HPA axis, is known to
play an important role in stress responses, hence its frequent use as an indicator of the
physiological response to stressors (Corr 2009).
2.3.2 Individual variance in cortisol or corticosterone response
A large body of studies has reported that different temperaments can result in the
differences in the amplitude of the increase in plasma concentrations of cortisol in
humans, monkeys, dogs and cattle and also differences in plasma concentrations of
corticosterone in avian species (Table 2.4). In sheep, the cortisol response to stressors
has been studied to be different in two lines selected for divergence in temperament
(calm and nervous; Hawken et al., 2013) and in two lines selected for or against ability
to rear multiple offspring (Vander Walt et al., 2009; Hough et al., 2013).
Therefore, temperament can affect the physiological response to stressors and the
variation in the physiological response could be linked to the variations in temperament.
Chapter 2 Literature Review 18 Table 2.4 The investigations of variance in cortisol/corticosterone response to stressors between
individuals with different temperament in human and animals
Glucocorticoid Species Stressor (Challenge) References
Cortisol human completion Donzella et al., 2000
social competence Gunnar et al., 1997,
2003; Tout et al., 1998;
Dettling et al., 1999
dog restraint, noise, shock Beerda et al., 1998
social and spatial restriction Beerda et al., 1999;
Hennessy et al., 2001;
De Palma et al., 2005
novelty King et al.,2003
monkey fearful eliciting situation Kalin et al., 1998
cattle ACTH Curley et al., 2008
transportation Burdick et al., 2010
sheep restraint, human presence,
dog barking
Hawken et al., 2013
insulin challenge Vander Walt et al., 2009;
Hough et al., 2013
Corticosterone bird handling Cockrem and Silverin
2002; Fraisse and
Cockrem 2006
restraint Satterlee and Johnson
1988; Jones et al., 1992;
1994a, 1994b
social conflict Carere et al., 2003
chicken handling Fraisse and Cockrem
2006
restraint Beuving et al., 1989;
Jones et al., 1995; Korte
et al., 1997
Chapter 2 Literature Review 19 2.4 The impact of temperament on cognition
2.4.1 Individual variance in cognition
In a challenging or continuously changing environment, the ability of individuals to
learn and memorise associations between stimuli and actions, make the appropriate
decision and adapt with the appropriate behaviours, is a vital determinants of survival
(Provenza 1995; Shettleworth 2001). Previous studies have suggested that there is
variability in this ability between individuals with different emotional reactivity (or
called temperament) in humans and animal species (Table 2.5). Lower levels of
emotional reactivity are associated with better performance in various cognitive tasks,
including spatial learning, discrimination and recognition tasks (Mendl 1999; Erhard et
al., 2004; Lansade and Simon, 2010; Bickell et al., 2011; Butts et al., 2013).
Table 2.5 The investigations of variance in cognitive function between individuals with
different emotional reactivity in animal species
Species Cognitive function References
Horse instrumental learning Lindberg et al., 1999; Visser et al.,
2003; Lansade and Simon, 2010
spatial learning Heird et al., 1986
visual discrimination Fiske and Potter 1979; Mader and
Price 1980
Bird avoidance learning Richard et al., 2000
Cattle decision-making Grandin et al., 1994
Rat spatial learning Brush et al., 1985; Teskey et al.,
1998; Herrero et al., 2006
cognitive flexibility Butts et al., 2013
Dog spatial learning Svartberg 2002
Sheep decision-making Rushen, 1986b
cognitive flexibility Erhard et al., 2004
face discrimination Bickell et al., 2011
Deer decision-making Pollard et al., 1994
Pig decision-making Van Rooijen and Metz 1987
spacial learning Mendl et al., 1997
Chicken memory Regolin et al., 1995
Chapter 2 Literature Review 20 2.4.2 The mechanism involved in the cognition
The neurobiology of the cognitive functions is complex, but the location of the brain
regions and neuronal pathways involved starting to be understood. The prefrontal loop
and striatum are mainly responsible for attention and directing the behaviour toward a
given goal in a given situation (Posner and Petersen 1990). Studies suggest that the
dysregulation of the brain prefrontal cortex and striatum activity may underlie many of
the behavioural disorders of executive attention (Sagvolden and Sergeant 1998; Rubia et
al., 1999; Castellanos and Tannock 2002; Johansen et al., 2002). It has been shown that
dopamine exerts a strong regulatory effect on prefrontal cortex and striatum neuronal
activity (Missale et al., 1998; Haber et al., 2000; Schultz 2002), with many studies in
humans, monkeys and rats implicating the activity of midbrain dopaminergic neurons
and their projections to the prefrontal cortex and striatum has been implicated in a
variety of cognitive and executive functions in human, monkeys, and rats, including
working memory (Brozoski et al., 1979; Sahakian et al., 1985; Cai and Arnsten 1997;
Floresco and Phillips 2001; Cools et al., 2002), behavioural flexibility (reversal learning
and shifting of attentional set including extradimensionalshifts (EDS) and
intradimensional shifts (IDS) of attention) (Owen et al., 1991, 1993; Roberts et al., 1994;
Birrell and Brown 2000; McAlonan and Brown 2003; Yang et al., 2004) and
decision-making (Bechara et al., 2001; Ersche et al., 2005; Shurman et al., 2005; Denk
et al., 2005; Winstanley et al., 2006). Dopamine exerts its effects on prefrontal cortex
and striatum neural activity via multiple receptor subtypes, with dopamine receptor 1
(DRD1) and receptor 2 (DRD2) being suggested as mediating the cognitive learning
abilities in human and mice (Smith et al., 1999; Kruzich and Grandy 2004; Floresco and
Magyar 2006; Lee et al., 2007; Jocham et al., 2009). For example, DRD2 knockout
mice had impaired ability to acquire odor-driven discrimination (Kruzich and Grandy
2004).
In summary, there is variance in behaviours, physiological cortisol response, and
cognition between individuals with different emotional reactivity or temperament. The
HPA axis is mainly responsible for the physiological response; the serotonergic system
is more linked to the variance in psychological disorders related behaviours like
depression, anxiety, schizophrenia and substance abuse, whereas dopaminergic system
is more linked to the variance in behavioural reactivities including fear, ADHD,
impulsivity and aggression related behaviours and cognition. The question is: does such
Chapter 2 Literature Review 21 variance have a genetic component?
2.5 The genetic basis of temperament
Variation in temperament could be caused by differences in genetics (Strelau 1987;
Rothbart et al., 2000; Mervielde et al., 2005; Saudino 2005; Krueger and Johnson 2008;
Bickell et al., 2009b) or environment (Rothbart et al., 2000; Krueger and Johnson 2008).
However, the shaping of individual temperament by the complex interactions between
genetic and environmental factors is not well understood and little studied. One study
indicated that early experience and 5HTT gene variation interact to have a mutual
influence on the aggressive behaviors in rhesus macaques (Bennett et al., 2002). It was
suggested that variation in 5HTT was associated with aggressive behaviours, but the
behaviours of offspring were influenced by genotype in paternal-reared individuals but
not for maternal-reared subjects,. By contrast, in sheep, a study using a cross-fostering
procedure has suggested that sheep temperament is caused by genetic inheritance rather
than learned behaviours (Bickell et al., 2009b). Newborn lambs born to calm ewes were
fostered to either other calm ewes or to nervous ewes and, lambs from nervous ewes
were fostered to other nervous ewes or to calm ewes, and their emotional reactivity was
measured. Lambs born from calm ewes, even if fostered by nervous ewes, were still
calm and showed little fear response, whereas lambs born from nervous ewes, even if
raised by calm ewes, still displayed fearful responses similar to those of nervous lambs.
The clear conclusion was that temperament in Merino sheep is mainly determined by
genetic transmission of the trait rather than from behaviour learned from the mother.
Therefore, although there are complex cross-connections between nature and nurture, in
general, it seems likely that sheep temperament is at least partially determined by
genetics.
2.5.1 Molecular genetics
Gene structure
The genome comprises a very large number of genes, each of which is a segment of
deoxyribonucleic acid (DNA) composed of 4 different nucleotides (or bases): adenine
(A), cytosine (C), guanine (G) and thymine (T) assembling in a double helix (Watson
and Crick, 1953). The 4 bases are matched in a specific way – A with T and C with G
Chapter 2 Literature Review 22 –allowing the DNA replication occurs in an unique way using one strand as template of
the other one. Three bases constitute a codon. A specific amino acid is usually encoded
by one codon or different codons in some instance due to total 64 possible codons but
only 20 amino acids. A specific gene is composed of coding region called exons and
non-coding sequence called introns. ATG is the start codon and TGA is the stop codon
which are responsible for the initiation and termination of the translation of protein
respectively. The promoter region is a special non-coding sequence located before
coding region which is responsible for the start of DNA transcription.
Gene polymorphisms
Gene polymorphisms (or mutations) refer to the base changes in the DNA sequence, of
which there are several different types:
1) Single nucleotide polymorphisms (SNPs), in which one base is mutated into
another base (Brookes 1999), is the most common form with, to date, over 11
million available in two databases including dbSNP (http://www.ncbi.nlm.
nih.gov/SNP/) and UCSC (http://genome.ucsc.edu/);
2) Insertions and deletions (I/D) in which base-pairs (from 1 to several thousand)
are added or removed from the DNA sequence;
3) Restriction fragment length polymorphism (RFLP), a difference in homologous
DNA sequences that can be detected by the presence of fragments of different
lengths after digestion of the DNA with specific restriction endonucleases
(Tanksley et al., 1989);
4) Repeat polymorphisms in which there is a variable number of repeats of a
certain fragment, usually in one of two main patterns: microsatellites (small di-
or tri-nucleotide repeats; Jeffreys et al., 1985), or a variable number of tandem
repeats (VNTRs) of up to100 nucleotides (Nakamura et al., 1987);
5) Copy number polymorphisms, comprising larger deletions and duplications (>1
kbp in size).
Whether the polymorphism can affect the phenotype depends on its location in the DNA
sequence. A polymorphism located in coding regions can cause amino acid substitutions
and will thus be be functional. However, even if it is located in non-coding regions, a
polymorphism can affect transcription rates by, for example, being located within the
promoter region, or at the binding sites of transcription factors.
Chapter 2 Literature Review 23
Methods for genetic studies
Psychological characteristics can vary between individuals because of genotype, as
illustrated by genetic variation in personalities and temperaments and differences in the
response of individuals to the same stimulus. An increasing body of work is focused on
the association of genetics with personality, psychological disorders and behavioural
traits. Some diseases, such as Huntington’s disease, are ‘monogenic’, having been found
to be the result of a single mutation in a single gene (Gusella et al., 1983). However,
complex behavioural disorders such as attention deficit hyperactivity disorder (ADHD),
Tourette’s syndrome, depression, and substance addiction, and some behavioural traits
such as aggression, impulsiveness, novelty seeking, harm avoidance, are believed to be
determined by multiple genes rather than a single gene, so are ‘polygenic’ (Bah Rosman
2008; Corr 2009). In polygenic disorders, it is a difficult to identify and associations
with specific gene(s).
One method for identifying specific genes associated with personality, psychological
disorders and behavioural traits is ‘association studies’ (Glazier et al., 2002; Bah Rosman
2008) which assume that the underlying pathological and physiological mechanisms of
your target phenotype disorder or behaviour is well understood. Candidate genes can
thus be investigated for mutation, usually with a classical Case-Control experimental
design, where individuals with the target disorder or behaviour (Case) and individuals
without the discorder or behaviour (Control) are compared. Allele and genotype
frequencies of polymorphisms in the candidate genes are detected, measured and
compared between the case and control groups, as in the present study.
2.5.2 Candidate genes involved in temperament
Candidate genes involved in the variability in behaviours
As mentioned above, the dopaminergic and serotonergic systems, in particular the
receptors and the catabolic enzymes (MOA) are involved in expression and variability
of behaviour linked to personality disorders and other phenotypic traits related to
temperament. In the following section, I will review the literature concerning
polymorphisms in the genes encoding expression of monoamines receptors and
monoamine oxidase and their relationships with expression of phenotypic traits related
Chapter 2 Literature Review 24 to temperament and their variability among individuals.
Gene polymorphisms in the dopaminergic pathway
TH and DAT genes
In humans, to date, there have been few studies of the TH gene in the context of
psychological disorders and behavioural traits, the most relevant being the discovery of
a functional tetranucleotide VNTR (variable number of tandem repeats) polymorphism
(TCATn) that is related to neuroticism (Persson et al., 2000). Similarly, for the gene
controlling DAT, and thus the re-uptake of dopamine, there is also little information
linking polymorphisms to personality traits, although a VNTR polymorphism with
40-bp repeat unit has been identified and proposed to play a role in substance addiction
and attention-deficit/hyperactivity disorder in humans (Parsian and Zhang 1997; Sabol
et al., 1999; Ueno et al., 1999; Daly et al., 1999; Barr et al., 2001).
DRD4 and DRD2 genes
In contrast with the TH and DAT genes, the genes for DRD4 and DRD2 have been
investigated in depth. Three polymorphisms of the DRD4 gene has been identified in
the human: i) a VNTR polymorphism with 48-bp repeat unit in the third intracellular
loop of the receptor molecule; ii) 2 SNPs (-616 C/G and -521 C/T) in the promoter
region; and iii) a VNTR polymorphism with repeats of 120-bp in the 5' un-translated
region (Cichon et al., 1995; Liu et al., 1996). Among them, the VNTR polymorphism
with 48-bp repeats has been the subject of many studies and the consensus is that it is
associated with impulsive behaviour, novelty-seeking and attention deficit/hyperactivity
disorder (Lahoste et al., 1996; Ono et al., 1997; Noble et al., 1998; Rowe et al., 1998;
Smalley et al., 1998; Swanson et al., 1998; Faraone et al., 1999; Holmes et al., 2000;
Sunohara et al., 2000; Miglia et al., 2000; Tahir et al., 2000; Roman et al., 2001; Curran
et al., 2001; Mill et al., 2001; Kirley et al., 2004; Keltikangas-Jarvinen et al., 2004;
Congdon et al., 2008; Kramer et al., 2009; Reiner and Spangler 2011). In addition, the
VNTR polymorphism has been detected in the same region in other species, although
the repeat base pair unit and the number of repetitions differes with the species. In
monkeys, the VNTR polymorphism (48-bp repeat unit) was found to be associated with
novelty-seeking behaviour (Bailey and Julia 2007). In dogs, on the other hand, two
VNTR polymorphisms (with 12-bp or 39-bp repeat unit) were detected and found to be
associated with aggressiveness (Ito et al., 2004).
Chapter 2 Literature Review 25 For DRD2, several polymorphisms have been studied, the most common being two
forms of a TaqI RFLP, TaqI A and TaqI B (Reif and Lesch 2003). In addition, a SNP in
intron 6 with a Ser-Cys mutation and a -141C ins/del variant in the promoter region
have also been detected (Jonsson et al., 2003; Reif and Lesch 2003). The DRD2 TaqI A
RFLP was found be linked to dopaminergic activity and to the quantity of D2 dopamine
receptors in brain tissue, as well as to responses to stress, dopamine -related disorders
and variation in personality traits and behaviours including behavioural inhibition and
impulsivity, novelty-seeking and attention deficit/ hyperactivity disorder (Noble et al.,
1991; Noble et al., 1994 a,b,c,d; Comings et al., 1996a,b; Noble et al., 1997; Lawford et
al., 1997; Blum et al., 1997; Berman and Noble, 1997; Noble et al., 1998; Lee et al.,
2007). The DRD2 polymorphism in the promotor, -141C ins/del, was suggested to be
related to personality detachment in terms of extraversion and agreeableness (Jonsson et
al., 2003). Two SNPs of DRD2 (rs4648317 and rs12364283) are associated with
behavioural inhibition and impulsivity/sensation-seeking (Hamidovic et al., 2009) and
three DRD2 polymorphisms (2 SNPs, -241A/G and rs1079598, and a TaqIA RFLP) are
associated with childhood aggression (Zai et al., 2012).
In summary, polymorphisms of the TH and DAT genes are linked to substance
addiction, attention-deficit/hyperactivity disorder and neuroticism rather than
personality or temperament traits. By contrast, polymorphisms of DRD4 and DRD2
genes are found in different regions for different species yet seem to be associated with
the level of behavioural reactivity, including impulsive behaviour and aggression, a trait
that is closely related to the phenotype of temperament and personality.
Gene polymorphisms in the serotonergic pathway
TPH and 5-HTT genes
For the human TPH gene, polymorphisms have been detected in various different
regions. A SNP (labeled alleles U and L) has been identified in Intron 7 at Position 218
(-218A/C). The L allele has been linked with suicidality, alcoholism and aggression
(Nielsen et al., 1994, 1997, 1998; New et al., 1998; Nolan et al., 2000). In addition,
SNPs in the promoter region of TPH gene were found to be associated with suicidal
behaviour in a Chinese population (Liu et al., 2006). However, other studies failed to
detect an association between TPH polymorphism and suicidality (Bennett et al., 2000)
or with scores in temperament character inventory (TCI), a general assessment of
personality traits (Ham et al., 2004). It is feasible that TPH polymorphisms play a role
Chapter 2 Literature Review 26 in predisposition to some temperament characteristics and behavioural traits, but further
studies are needed for clarification.
With respect to serotonin re-uptake, three polymorphisms have been identified for the
gene encoding for 5-serotonin transporter (5-HTT) (De Mel et al., 2012). One
polymorphism is a VNTR polymorphism within intron 2 and the other two are both
located in the promoter area, the most extensively studied one being a VNTR
polymorphism (named 5-HTTLPR) with a long variant (L: 16 copies of 22 bp repeat
unit) and a short variant (S: 14 copies of 22 bp repeat unit. Within this VNTR
polymorphism in promoter area, a SNP (A/G) has also been detected. The 5-HTTLPR
L/S polymorphism has been the main target main of investigation and appears, in
humans, to be strongly associated with behaviours related to psychiatric disorders,
including schizophrenia, substance dependence and abuse, eating disorders, anxiety and
depression, fear and panic, comorbid dysthymia and suicidal behaviour (Lesch et al.,
1996; Rotondo et al., 2002; Golimbet et al., 2004; Retz et al., 2004; Baca-Garcia et al.,
2005; Kilpatrick et al., 2007; Lonsdorf et al., 2009; Verhagen et al., 2009; Klumpers et
al., 2012).
5-HT receptor genes
Fourteen sub-types (labeled 5-HT1-14) have been identified for the 5HT receptor
(Hoyer and Martin 1996). Both 5-HT1 and 5-HT2 have been reported to be involved in
behaviours related to personality and physiological disorders in the human (Roth 1994).
A SNP of the 5HT1B gene (-861G/C) is associated with alcoholism (Lappalainen et al.,
1998) and 2 SNPs (-102T/C and -14238A/G) in the 5HT2A gene have been linked to
schizophrenia and post-traumatic stress disorder (Williams et al., 1996, 1997; Lee et al.,
2007). A SNP of the 5HT2C gene (Cys23Ser) appears to be been related to Alzheimer’s
disease and alcoholism (Holmes et al., 1998).
In summary, the gene polymorphisms involved in serotonergic system seemed to be
more linked to psychiatric disorders, including schizophrenia, substance dependence
and abuse (alcoholism), eating disorders, anxiety and depression rather than personality
or temperament traits.
Gene polymorphisms in MAO
Of the two isoforms, MAO-A and MAO-B, MAOA is thought to be the prevailing and
essential isoform in the brain (Weyler 1990; Shih 1999) where it plays an important role
Chapter 2 Literature Review 27 in the genetic regulation of psychological disorders and behaviours. Low levels or
abnormalities in MAOA activity are implicated in psychiatric disorders such as
depression, alcoholism and impulsive behaviours (Sullivan et al., 1990; Brunner et al.,
1993; Devor et al., 1993; Faraj et al., 1994; Verkes et al., 1998; Eensoo et al., 2005).
Abnormalities in MAOA activity that are apparently associated with mutations in
MAOA gene (Sabol et al., 1998; Deckert et al., 1999) seem to cause various psychiatric
disorders, such as impulsive or aggressive behaviour and attempted suicide (Brunner et
al., 1993a, b). In humans, the most common polymorphism, a 30-bp VNTR, is in the
promotor region and is associated with panic and fear behaviours, depression,
aggressiveness and impulsiveness (Deckert et al., 1999; Schulze et al., 2000; Manuck et
al., 2000, 2002; Du et al., 2002; Parsian et al., 2003; Ito et al., 2003). In rhesus monkeys
and in Macaques (Newman et al., 2005; Wendland et al., 2006), the repeat
polymorphism in MAOA promoter region has been found to be associated with
aggression-related behaviour. In chickens, there is breed difference in two
microsatellites polymorphisms for MAOA in Intron 4 (a thymine repeat, named
CMin4T) and Intron 9 (a adenine repeat, named CMin9A), and a 128-bp allele in Intron
4 was observed, only in the Nagoya breed that shows very cowardly behaviour (Hong et
al., 2008b).
Therefore, although the polymorphisms differed in different regions and also differed
among the species, the polymorphism of MAOA gene seemed to be associated with the
level of behavioural reactivity including fear, impulsive and aggressive behaviours that
are closely related to the phenotype of temperament and personality.
In summary, polymorphisms of the TH and DAT genes involved in dopaminergic
system and the gene polymorphisms involved in serotonergic system seemed to be more
linked to psychiatric disorders, which appear to differ fundamentally from the
phenotype of our temperament. By contrast, although their polymorphisms differed in
different regions and also differed among the species, the polymorphism of DRD2,
DRD4 and MAOA genes seemed to be associated with the level of behavioural
reactivity including fear, impulsive and aggression that are closely related to our
temperament phenotype.
Candidate genes involved in the variability along the HPA axis
Chapter 2 Literature Review 28 As outlined above, variation in the genes involved in the regulation of the HPA axis,
including the production of CRH in hypothalamus and the production of cortisol in
adrenal cortex, can probably explain variations in temperament. Here we will explore
this hypothesis.
Gene polymorphisms related to hypothalamus CRH production
The studies have suggested that gene polymorphisms related to CRH production is
linked to some psychological disorders related behaviours in humans and monkeys. In
humans, a SNP (-201 C/T) in the promoter region of CRH gene appears to increase the
alcohol consumption in humans (Baerwald et al., 1999). The same SNP (-248C/T) was
also detected in the corresponding region of the monkey CRH gene, also apparently
related to increased risk for disorders of alcohol-use in stress-exposed individuals (Barr
et al., 2009). In addition, the SNP in the gene of CRH receptor-1 (CRH-R1) has been
found to be associated with psychological disorders related behaviours in humans,
including depression, alcohol consumption and suicidal behaviour (Licinio et al., 2004;
Keck 2006; Liu et al., 2006, 2007; Keck et al., 2008; Bradley et al., 2008; Blomeyer et
al., 2008; Wasserman et al., 2008, 2009; Schmid et al., 2010; Binder and Nemeroff
2010).
Therefore, the gene polymorphisms related to CRH production seemed to be more
linked to psychiatric disorders, including schizophrenia, substance dependence and
abuse (alcoholism), anxiety and depression, which not directly relevant to the phenotype
expression of temperament. So far, few studies investigate the ACTH related gene
polymorphisms and behaviours.
Gene polymorphisms involved in adrenal cortisol production
As mentioned above, differences in the amplitude of the cortisol response have been
reported to be associated to temperament in humans, monkeys, dogs and cattle. The
gene CYP17 plays a central role in the regulation of cortisol production in the
mammalian adrenal cortex (Nakajin et al., 1981) in both of the two principal pathways
–Δ5 and Δ4 (Figure 2.4). Pregnenolone (PREG) is the specific substrate for Δ5 pathway
while progesterone (PROG) is the specific substrate for the Δ4 pathway. The
hydroxylation activity of CYP17 causes 17-hydroxylation of PREG (Δ5) to
17-hydroxypregnenolone (17-OHPREG) and PROG (Δ4) to 17-hydroxyprogesterone
Chapter 2 Literature Review 29 (17-OHPROG). The 17, 20-lyase activity of CYP17 converts 17-OHPREG (Δ5) to
dehydroepiandrosterone (DHEA) and 17-OHPROG (Δ4) to androstenedione (A4), two
androgen precursors (Figure 2.4).
Figure 2.4 The Δ5 and Δ4 pathways catalysed by CYP17 responsible for the production of
androgens or glucocorticoids by the adrenal gland.
Differences in the hydroxylase and the lyase activities give CYP17 its crucial role in the
determination of the direction of steroidogenesis towards the production of
mineralocorticoids, glucocorticoids or androgens by the adrenal gland, and these
differences seem to depend on the CYP17 genes. In African Angora goats, Boer goats
and Merino sheep, certain CYP17 genotypes are strongly associated with the cortisol
response to stressors (Storbeck et al., 2007, 2008, 2009). The Angora and Boer goats
have different physiological characteristics that are linked to the high mortality rate in
Angoras when they are exposed to cold stress (Wentzel et al., 1979). In addition, the
plasma cortisol concentrations are lower and the cortisol response to CRF is smaller in
Angora than in Boer goats or Merino sheep (Herselman and Vanloggerenberg 1995). It
was therefore suggested that, in Angora goats, but not Boer goats or Merino sheep,
CYP17 was primarily involved the Δ5 pathway and conversion of PREG to DHEA
rather than the Δ4 pathway leading to the production of cortisol (Engelbrecht and Swart
2000). Two CYP17 isoforms, CYP17 ACS− and CYP17 ACS+ with four single
nucleotide differences have been identified in goats (Slabbert 2003). Interestingly, of the
83 Angora goats that were genotyped, 24 were ACS−/ACS−, the remaining 59 were
ACS−/ACS+ and no goats with ACS+/ ACS+ were detected, whereas all Boer goats
were ACS−/ACS+ (Slabbert 2003). The two alleles (ACS− and ACS+) were found to be
located on different genes: in Angora goats, the ACS−/ACS− genotype is located on one
Chapter 2 Literature Review 30 CYP17 gene (ACS−) whereas, in Boer goats, the ACS+/ACS− genotype is located on
two different CYP17 genes (ACS+ and ACS−; Storbeck et al., 2007; Vander Walt et al.,
2009). Therefore, ACS+ was always present with ACS−, and ACS+/ACS+ could not be
found. When the ACS− and ACS+ genes were cloned, they displayed similar
17-hydroxylase activity but the ACS− isoform had a greater 17, 20-lyase activity,
leading to greater androgen production and smaller glucocorticoid production (Storbeck
et al., 2007), probably explaining the hypocortisolism observed in Angora goats with
their extra ACS−. These observations agree with those of Engelbrecht and Swart (2000)
who showed that the Angora produced significantly less glucocorticoid precursors, but
more androgens. In summary, the CYP17 isoform has a strong association with cortisol
production in South African Angora goats, with the ACS− isoform leading to lower
cortisol outputs.
In addition, two CYP17 isoforms (WT1 and WT2) that differ by two single nucleotides
were detected in South African Merino sheep by Storbeck et al. (2007). The sheep were
from two divergent lines selected for Low (L-line) or high (H-line) ability to rearing
single or multiple litters (Vander Walt et al., 2009). The H and L lines differ in their
cortisol response to insulin injection, with H-line having an earlier cortisol peak and
quicker glucose recovery (Vander Walt et al., 2009). However, the frequency
distributions of WT1 and WT2 did not differ significantly between the two lines, and
homozygous WT2 was not detected (Table 2.6). The difference between L-line and the
H-line in the cortisol response to insulin challenge suggested that, in addition to CYP17,
other genes are associated with the cortisol response in Merino sheep, so we have also
explored other candidate genes.
Table 2.6 Frequency of the 3 CYP17 genotypes in sheep from the H-line and L-line
(from Vander Walt D et al., 2009)
Line
Homozygous WT1 Heterozygous WT1/WT2 Homozygous WT2
Number of sheep % Number of sheep % Number of sheep %
H-line 15 14.3 90 85.7 0 0
L-line 5 16.1 26 83.9 0 0
In summary, polymorphisms in the gene for CRH are more likely linked to the
behaviours related to psychiatric disorders including depression, alcohol addiction and
Chapter 2 Literature Review 31 suicidal behaviours that relevant to the phenotype expression of temperament. On the
other hand, polymorphisms in CYP17 are linked to differences in the cortisol response
to exposure to stressors, so CYP17 is a good candidate as a genetic marker for
temperament, especially because secretion of cortisol differs with different phenotypic
traits for temperament in sheep (Hawken et al., 2013).
Besides the gene polymorphisms, reviewed above, in the dopaminergic and serotonergic
system, and in the HPA axis, several other genes have also been associated with
behaviour. For example, in the noradrenergic pathways, genes encoding for
dopamineβ-hydroxylase (DBH; responsible for norepinephrine synthesis), the
adrenergic receptor (ADRA2A), and norepinephrine transporter (NET1), have been
suggested to play a role in ‘fight or flight’ response (Major et al., 1980). Similarly,
within the GABAergic pathway, the GABA-A receptor gene has been shown to be
involved in anxiety disorders (Crestani et al., 1999). Another example is the gene
encoding for Nitric oxide (NO) synthase which has been proposed to be associated with
aggressive and sexual behaviour (Nelson et al., 1995). However, very few studies have
investigated these relationship in detail.
Gene polymorphism and cognition
Dopamine in the prefrontal cortex and striatum influences neural activity via multiple
receptor subtypes that have been suggested to mediate cognitive learning abilities,
including working memory and behavioural flexibility. In both human and nonhuman
primates, memory has been linked to the actions of DRD1 receptors, with the
antagonism or inhibition of DRD1 can improve memory ability (Sawaguchi and
Goldman-Rakic 1991, 1994; Williams and Goldman-Rakic 1995; Murphy et al., 1996;
Muller et al., 1998). By contrast, the behavioural flexibility has been suggested to be
associated with DRD2 receptors and their polymorphisms (Ridley et al., 1981;
Taghzouti et al., 1985; Farde et al., 1987; Goldman-Rakic et al., 1990; Lidow et al.,
1991; Smith et al., 1999; Kruzich and Grandy 2004; Lee et al., 2007; Cools et al., 2001,
2007; Jocham et al., 2009; Gong et al., 2012). Potentially, therefore, DRD2
polymorphisms could help explain the variability in learning performance associated
with different temperaments.
In summary, the gene polymorphisms including TH, DAT, DRD2, DRD4, TPH, 5-HTT,
Chapter 2 Literature Review 32 5-HT receptors, MAOA, CRH, CYP17, DBH, ADRA2A, NET1, GABA-A receptor and
NO all could be linked to the various dimensions of temperament, such as psychiatric
disorders, substance addiction, attention-deficit/hyperactivity disorder, neuroticism, and
behavioural reactivity (including fearfulness, impulsiveness and aggression). Genes or
gene polymorphisms in TH, DAT, TPH, 5-HTT, 5-HT receptors and CRH seem to be
more linked to psychiatric disorders, which appear to differ fundamentally from the
phenotype of our temperament flock. By contrast, although their polymorphisms
differed in different regions and also differed among the species, the polymorphism of
DRD2, DRD4, MAOA and CYP17 genes seemed to be more associated with the level
of behavioural reactivity including fearfulness, impulsiveness and aggression that are
closely related to our temperament phenotype, while the associations of genes DBH,
ADRA2A, NET1, GABA-A receptor and NO are not strong because they have been
rarely studied. Therefore, considering the characteristics of our two temperament
phenotypes, 4 genes (DRD2, DRD4, MAOA and CYP17) were chosen as candidates
most likely associated with our two sheep temperaments.
2.6 The model of temperament flock
During the past 20 years at UWA, a flock of Merino sheep has been selected to generate
two lines according to their different behavioural responses to the presence of human
and social isolation, using two behavioural phenotype tests, the Arena test and the
Isolation Box test (Murphy et al., 1994; Murphy 1999; Blache and Ferguson 2005). The
two lines are labeled "calm" for sheep that are less fearful of humans and less reactive to
isolation and "nervous" for sheep that display more fearful and more reactive responses.
In this section, I will describe the two behavioural tests used to assess the phenotype of
temperament.
Arena test
The arena test measures the behavioural response of sheep exposed to the challenge of
having to pass a human to gain access to a pen of flock mates. The surface of the pens is
divided into 4 sections by lines drawn on the ground (Figure 2.5). Flockmates are kept
in a pen at the end of the arena with a human in front of them. A single test sheep is
gently pushed in the arena through the entry door (Figure 2.5), where it experiences a
conflict avoidance situation because it has to pass the human to approach the flockmates.
The behavioural response is measured by quantifying locomotor activity by counting
Chapter 2 Literature Review 33 the number of lines crossed over a period of 3 min (TOTAL CROSS). A high level of
locomotor activity indicates a high degree of fear (Blache and Ferguson 2005). However,
in this arena test, there is some ambiguity in the interpretation of the behaviour. It has
been argued that immobilization might reflect an absence of fear in one situation, such
as the presence of a human, and but it can also reflect a high degree of disturbance and
nervousness in another situation (Vandenheede et al., 1998), and the inhibition of
locomotor and vocal behaviour can be interpreted as a reaction towards a predator and
thus can represent a higher degree of fear (Romeyer et al., 1992). Therefore, second test,
the isolation box test, is used to complete the assessment of sheep temperament.
Figure 2.5 Schematic diagram of the arena test (Blache and Bickell 2011).
Isolation box test
The test sheep is isolated in a 1.5 x 1.5 x 1.5 m solid box (Figure 2.6) without visual
contact. A digital agitation meter, calibrated for reflection of low, medium and high
agitation levels before the test (Blache and Ferguson 2005), is used to record the
vocalisations and agitation of the test animal and a score (BOX) is read after 1 min of
isolation. The agitation score is an indicator of the inherent fear and ability to adapt to
isolation (Blache and Ferguson 2005), with a high score indicating a high degree of fear.
Chapter 2 Literature Review 34
Figure 2.6 Schematic diagram of the isolation box test (Blache and Bickell 2011).
Selection index
The level of vocalisation and locomotor activity of sheep exposed to various fear
eliciting situations can be used as an indicator of their levels of fear (Romeyer et al.,
1992; Vandenheede et al., 1998). An overall selection index (i) can thus be calculated
based on the TOTAL CROSS and BOX measured in the two tests, according to the
following equation (Murphy et al., 1994; Murphy 1999):
i = individual score, x = flock mean, sd = standard deviation of mean
High and low values for the selection index are used to classify behavioural reactivity,
wit the high-index sheep labeled ‘nervous’ and the low-index sheep labeled ‘calm’.
2.7 Summary
Individuals display different behavioural and physiological responses to the same
stimulus and this variability is called temperament. Sheep of calm or nervous
temperament show different physiological responses (cortisol secretion) and behavioural
responses (motor activity) following exposure to stressors such as novelty and isolation
(the method for temperament assessment). In our model, the genetic basis is not
understood. This thesis focuses on two systems that could be involved in the expression
of temperament and in the consequences of differences in temperament on adrenal
activity and on cognitive capacity. The experimental work aimed to explore the genes
involved in the regulation of the activity of the dopamine and serotonin neurotransmitter
systems, as well as a gene involved in the regulation of the HPA axis.
Chapter 2 Literature Review 35
The serotonergic system and its related gene polymorphisms is more linked to the
psychological disorders related behaviours like depression, anxiety, schizophrenia, and
substance abuse, which are not directly relevant to the phenotype expression of
personality or temperament; whereas, dopaminergic system and its related gene
polymorphisms, although differed in different regions and also differed among the
species, is more linked to the behavioural reactivity including fear, ADHD, impulsivity
and aggression related behaviours and cognitive capacity, which are closely related to
our temperament phenotype. The polymorphism of CYP17 gene is linked to differences
in cortisol response to stressors which was tested to be different in sheep with different
phenotypic traits for temperament. Therefore, taking into consideration of the phenotype
trait of the model of our temperament flock, the genes DRD2, DRD4, MAOA and
CYP17 are good candidates to look at the association of their polymorphisms with
temperament.
The aim of this thesis is to contribute to the undersanding of the genetic basis of
temperament using the UWA flock, by examining:
1) The association of temperament with the polymorphisms of genes potentially
involved in the perception and responses to stressors (Chapter 4);
2) The response to stressor of animals carrying combination of the identified
polymorphisms (Chapter 5) ;
3) The heritability of behavioural reactivity to isolation (one measurement of
temperament) of animals carrying the identified polymorphisms (Chapter 6);
4) The differences in cognitive ability of animals carrying the identified
polymorphisms (Chapter 7).
Chapter 3 General Materials and Methods 36
Chapter 3
General Materials and Methods
Page
3.1 Experimental location 37
3.2 Experimental materials and animals 37
3.3 Molecular techniques 37
3.4 Jugular Cannulation 40
3.5 ACTH Test 41
3.6 Hormone assays for cortisol 41
3.7 Behavioural test 42
3.7.1 Arena test 42
3.7.2 Isolation test 43
3.8 Cognitive learning and memory ability tests 43
3.8.1 Simple visual test (discrimination of colour) 44
3.8.2 Y-maze test (left-right spatial discrimination) 46
Chapter 3 General Materials and Methods 37 The materials and methods described in this chapter were used in several different
experimental chapters, although some are repeated in experimental chapters that were
written as journal manuscripts. Treatments and analyses that are specific to particular
experiments are described in detail in the relevant experiment chapter. All experiments
were conducted in accordance with the Australian Code of Practice for the Care and Use
of Animals for Scientific Purposes (7th Edition, 2004) and were approved by the Animal
Ethics Committee of UWA (Approval number RA/3/100/1252).
3.1 Experimental location The laboratory experiments were conducted at the University of Western Australia
(UWA), Perth, Western Australia. Animal experiments were conducted at UWA Farm
Ridgefield, a 1588-hectares farm near Pingelly, Western Australia (32°30’23’’ S,
116°59’31’’E) where the UWA Future Farm 2050 project is located. The climate is
Mediterranean-type with 425 mm annual average rainfall, with mild wet winters and hot
dry summers. Daylength ranges from 10 h to 14 h.
3.2 Experimental materials and animals
In Chapter 4, we used whole blood samples collected into EDTA vacutainers (Greiner
Bio-One, Australia) from sheep from the two lines in the UWA Temperament Flock.
This flock of Merino has been selected for 20 generations on the basis of the behavioural
reactivities of lambs after weaning (at approximately 16 weeks of age) to humans and
social isolation using two behavioural tests (Murphy et al., 1994; Murphy 1999; Blache
and Ferguson 2005) described in Section 3.7. In Chapter 5, we used ewes of unknown
temperament from a commercial flock kept at UWA Farm Ridgefield. In Chapter 6, the
blood samples were obtained for another project (Blache and Ferguson 2009) from ewes
and lambs that had been selected on the basis of the accuracy of their parentage. In
Chapter 7, we used the Merino ewes with known DRD2 SNP939 genotypes.
3.3 Molecular techniques
Blood genomic DNA extraction protocol
Genomic DNA was isolated using the DNeasy Blood and Tissue Kit (Qiagen, Germany)
according to the instructions provided by the manufacturer.
1) 20 μL proteinase K pipetted into a 1.5 mL microcentrifuge tube; 100 μL blood
sample added, followed by 100 μL PBS.
Chapter 3 General Materials and Methods 38 2) 200 μL Buffer AL added (without added ethanol); reagents mixed thoroughly by
vortexing, and incubated at 56°C for 10 min. We ensured that ethanol had not been
added to Buffer AL. It was essential that the sample and Buffer AL were mixed
immediately and thoroughly by vortexing to yield a homogeneous solution.
3) 200 μL ethanol (96-100%) added to the tube, and mixed thoroughly by vortexing. It
was important that the sample and the ethanol were mixed thoroughly to yield a
homogeneous solution.
4) The mixture from previous step was pipetted into the DNeasy Mini spin column
placed in a 2 mL collection tube; after centrifugation at 8000 rpm for 1 min,
flow-through and collection tube were discarded.
5) the DNeasy Mini spin column was placed in a new 2 mL collection tube and 500 μL
Buffer AW1 was added; after centrifugation for 1 min at 8000 rpm, the
flow-through and collection tube were discarded.
6) The DNeasy Mini spin column was placed in a new 2 mL collection tube and 500
μL Buffer AW2 was added. The DNeasy membrane was dried by centrifugation for
3 min at 14,000 rpm, and the flow-through and collection tube were discarded. It
was important to dry the membrane of the DNeasy Mini spin column, since residual
ethanol may interfere with subsequent reactions. This centrifugation step ensured
that no residual ethanol would be carried over during the following elution. The
DNeasy Mini spin column was then removed carefully so that the column did not
come into contact with the flow-through, since this would have resulted in carryover
of ethanol.
7) The DNeasy Mini spin column was then placed in a clean 1.5 mL microcentrifuge
tube, and 200 μL Buffer AE was pipetted directly onto the DNeasy membrane. After
incubation at room temperature for 1 min, it was centrifuged for 1 min at 8000 rpm
to elute.
Polymerase Chain Reaction (PCR)
Fragments of the CYP17 and DRD4 genes were amplified by standard PCR.
Amplification reactions (10 µL) contained 2 µL of 5×PCR buffer including 0.2 mM
dNTPs (Fisher Biotec, Australia), 2.5 mM MgCl2 (Fisher Biotec, Australia), 0.3 µM
each of forward and reverse primers (GeneWorks, Australia), 1.1 U Taq DNA
polymerase (5.5 U/µL; Fisher Biotec, Australia) and 20 ng genomic DNA.
Chapter 3 General Materials and Methods 39 Fragments of the DRD2 and MAOA genes were amplified by Hotstar PCR.
Amplification reactions (50 µL) contained 5 µL of 10×Faststart PCR buffer including 2
mM MgCl2 (Roche, Germany), 0.2mM dNTP mix (Roche, Germany), 0.3 µM each of
forward and reverse primers (GeneWorks, Australia), 2 U Faststart Taq DNA
polymerase (5 U/µL; Roche, Germany) and 80 ng genomic DNA. åThe protocols for
each fragment see Table 3.1.
Table 3.1 The PCR amplification protocol for each fragment.
Fragment Initial denaturation 35 cycles Final extension
CYP17 SNP628
DRD4 conserved
Exon1
Exon2
Exon3
DRD2 Exon4
Exon5
Exon6
Exon7
Exon1
MAOA Exon8
Exon15
94°C 5min
94°C 5min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
95°C 6min
94°C 30s
94°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
95°C 30s
58°C 30s
68°C 30s
68°C 30s
60°C 30s
60°C 30s
60°C 30s
60°C 30s
68°C 30s
68°C 30s
68°C 30s
60°C 30s
68°C 30s
72°C 15s
72°C 15s
72°C 45s
72°C 20s
72°C 25s
72°C 25s
72°C 20s
72°C 45s
72°C 45s
72°C 42s
72°C 15s
72°C 42s
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
72°C 7min
Gel electrophoresis of PCR products
The electrophoresis of PCR products was performed on 1.5% agarose gel. The gel was
prepared by melting 1.5g agarose with 100 mL 1×TAE solution in a microwave oven,
cooling it to 60 °C, and then pouring it into the electrophoresis tank and inserting the
comb. After 0.5 h, a mixture of 4 µl PCR product and 1 µl loading buffer was loaded
into each pole. The gel was run at 120V for 30 min and then stained with ethidium
bromide (0.5 µg mL-1) for 20-30 min and then placed on a UV-light transilluminator to
be photographed.
Genotyping by real-time PCR method
Real-time PCR-based genotyping was carried out using an Applied Biosystems
(California, USA) Vii7TM instrument. Amplification reactions (10 µL) were performed
using 5 µL TaqMan® Genotyping Master Mix (2×) (Applied Biosystems, California,
USA), 0.5 µL of custom TaqMan® SNP genotyping Assay (20×) containing two primers
Chapter 3 General Materials and Methods 40 and two labelled probes (Applied Biosystems, California, USA) and 20 ng genomic DNA.
The thermal profile is presented in Table 3.2. There was an extra step in the 40 cycles
for CYP17 SNP628 with cooling to 52°C with a 30s hold before going to 60°C due to
the lower annealing temperature of its primer. The transition rate between all steps was
1.6°C/s. Data were collected by the Vii7TM software. The VIC®-labelled sensor probe
and the FAMTM-labelled anchor probe were designed to be a perfect match for two
allele sequences for each SNP. A no-template control (negative control) was also
included in each assay. Each sample was done in triplicate on the 96-well plate.
Table 3.2 The real-time PCR thermal profile for CYP17 SNP628 and DRD2 SNP939
Fragment Pre-Read Denaturation 40 cycles Post-Read
DRD2 SNP939
CYP17 SNP628
60°C 30s
60°C 30s
95°C 10min
95°C 10min
95°C 15s 60°C 30s
95°C 15s 52°C 30s 60°C 30s
60°C 30s
60°C 30s
3.4 Cannulation of the jugular vein for serial blood collection
Animal Preparation
a. Wool was clipped close to the skin over over the jugular vein, providing an area big
enough to allow easy visualisation of and access to the jugular vein;
b. Local anaesthetic cream was applied (EmLa®; lignocaine 25mg/g, prilocaine 25
mg/kg) to the area –the time of application was noted;
c. The animal was then injected with sedative (ilium xylazil; 0.1mg/kg i.m.);
d. Approximately 30 min after application of the local anaesthetic cream, the animal
was restrained in a standing position.
Site Preparation
a. On cannulation trolley, all needles, tubing and equipment are kept in 70% ethanol.
b. The shaved window was scrubbed with betadine surgical scrub.
c. The vein was clearly located by occlusion plus visualization of rise and fall with
pressure and release, before moving on to the next step.
d. A small incision was made in the skin above the vein using a scalpel.
e. A 13G luer lock needle was inserted into the jugular vein and the cannula tubing
was quickly fed into the lumen of the vein.
f. The needle was slid off the tubing and a 3-way tap was attached to the end of the
cannula.
g. Blood flow was verified using a syringe filled with sterile, heparinised (40 iu/ml)
Chapter 3 General Materials and Methods 41
0.9% saline; the lumen of the cannula was rinsed by injection of 2-3 mL
heparinised saline.
h. A piece of fabric tape was wrapped around the tubing at the point where it enters
the skin, leaving two ‘wings’ on either side that could be sutured to the skin to
secure the cannula in place.
i. Another piece of fabric tape was wrapped around the junction between the tap and
tubing to reduce the risk of kinking and perforation of the tubing.
j. The cannula and tap were laid on the neck of the sheep and 2-3 layers of packing
tape were wrapped around the neck to ensure that the cannula and tap were
covereved, with care taken that breathing was not restricted.
k. At the end of the experiment, the cannula was removed and the cannulation site
checked for bleeding.
3.5 ACTH Test
Hormone injection and blood sampling were all done via indwelling jugular catheter
that had been inserted one day before the test. The ACTH stimulation test was used to
obtain a cortisol profile. The endogenously driven secretion of cortisol was blocked
using dexamethasone, a synthetic glucocorticoid that acts at hypothalamic level to
inhibit the secretion of ACTH (Beaven et al., 1964). With a low background
concentration of cortisol, tests using exogenous ACTH to elicit a cortisol response from
the adrenal glands become far more predictable, allowing robust comparison of groups
of sheep. Each sheep was treated with 0.125 mg/kg (i.v.) dexamethasone, a dose chosen
from previous studies showing complete suppression of endogenous ACTH release
(Beaven et al., 1964; Espiner et al, 1972). The exogenous ACTH (0.2 iu i.v.) was
injected 90 min after the dexamethasone treatment. Blood (3 mL per sample) was
sampled 30 min after dexamethasone treatment, then every 30 min until ACTH injection,
and then every 20 min until 3 h after the injection. Saline was used as control in an
identical protocol for injection and sampling. All blood samples were immediately
transferred into 5 mL plastic tubes containing 50 IU of heparin and polystyrene granules
(Techno-plas, WA, Australia) before centrifugation at 2000 g for 10 min to obtain
plasma for cortisol assay. The plasma was separated and stored at –20 °C until assay.
The duration and size of the cortisol response were measured.
3.6 Hormone assays for cortisol
Chapter 3 General Materials and Methods 42 Plasma concentration of cortisol was measured in duplicate by antibody
radioimmunoassay (RIA) using the ImmuchemTM Coated Tube Cortisol 125I RIA Kit
(MP Biomedicals, Belgium).
Assay preparation
1) Standards: 100ug/dL standard from the commercial kit was diluted using a pol of
cortisol-free plasma into following concentrations: 50, 25, 12.5, 6.25, 3.125, 1.56,
0.78, 0.39 and 0.2 µg/dL, with cortisol-free plasma used as zero (0 µg/dL).
2) All standards, quality controls, coated tubes and I125-tracer were brought to room
temperature prior to use. Quality was controlled with two sheep plasma samples,
obtained from stressed and non-stressed sheep, tht are routinely used as quality
control in our laboratories. The quality controls were refrozen (–15°C) between uses,
and the standards refrigerated (4°C).
Assay protocol
a) 25 µL of each standard, control and unknown samples were pipetted into the coated
tubes.
b) 1.0 mL of I125-tracer was added to all tubes and the tubers vortexed briefly.
c) All tubes were incubated in a water bath (37°C) for 45 min.
d) Tubes were decanted in the same order as they were pipetted; the rim of the test
tube was blotted dry on absorbent paper before being turned upright;
e) The tubes were counted in a gamma counter (90 sec).
f) Concentration of cortisol in each unknown sample was estimated from the standard
curve using “AssayZap Universal Calculator” software (Elsevier-Biosoft, UK).
3.7 Behavioural tests
It has been reported that the levels of vocalisations and locomotor activities of sheep
when exposed to various fear-eliciting situations can be used as the indicator of their
levels of fear (Romeyer et al., 1992; Vandenheede et al., 1998).
3.7.1 Arena test
An arena test was used to measure the locomotor activity of sheep exposed to the
conflicting challenge of having to pass a human to gain access to a pen of flock mates
(Blache and Ferguson 2005). A single test sheep entered a rectangular arena while its
flock-mates were kept in a pen at the opposite end of the arena with a human in front of
them (Fig. 2.5). Locomotor activity was quantified by counting the number of times the
Chapter 3 General Materials and Methods 43 test sheep crossed line on the floor of the arena (‘TOTAL CROSS’). Each test lasted for
3 min and the test sheep exited through a door located on the side the arena.
3.7.2 Isolation test
Each sheep was isolated without visual communication with its companions by being
placed for 1 min in a 1.5×1.5×0.7 m solid enclosed box (Fig. 2.6; Blache and Ferguson
2005). A digital agitation meter that measured vibrations produced by movements and
loud vocalisations was used to assess the reactivity of the sheep to isolation. The
agitation meter was calibrated before the test at low, medium and high agitation levels
using a mechanical device that producing a ‘stomping’ vibration (Blache and Ferguson
2005). An agitation score (‘BOX’) from the digital agitation meter was used as an
indicator of the inherent fear and adapt ability exposure to isolation (Blache and
Ferguson 2005).
An overall score
An overall selection score was calculated based on the values for TOTAL CROSS and
BOX from the above two tests, according to the following equation (Murphy et al., 1994;
Murphy 1999).
i = individual score, x = flock mean, sd = standard deviation of mean
A high or low overall score was used to classify animals as having high or low reactivity.
Sheep with a high overall score were labeled ‘nervous’ and sheep with a low score were
labeled ‘calm’.
3.8 Cognitive learning and memory ability tests
To date, studies of cognitive learning and executive function have been done with
human and non-human primates (Brozoski et al., 1979; McAlonan and Brown 2003;
Dowson et al., 2004; Mehta et al., 2004). Two simple discriminations (visual and spatial)
have been used to test the function and impairment of the prefrontal cortex and assess
learning and short-term memory abilities in humans, monkeys and rats (Owen et al.,
1991; Birrell and Brown 2000; Conrad 2010; Johnson et al., 2012). In my study, two
maze systems were utilized: an executive functioning maze apparatus described by
Chapter 3 General Materials and Methods 44 Morton and Avanzo (2011) to assess the learning abilities based on visual cues (visual
discrimination - color); and a Y-maze to test short-term memory capabilities based on
spatial discrimination.
3.8.1 Visual Discrimination - colour
Testing apparatus
Two identical testing units (each unit: 2.4 m × 7.2 m) were used to test whether sheep
could learn one color out of a choice of two. The two pens were assembled back to back,
so each sheep could be tested multiple times by cycling between the two units. The
outsides of the units and testing pen were covered with hessian to isolate the animal
from external visual stimuli. Each unit comprised a starting gate located in the middle of
the front panel and a testing area divided longitudinally into two sections by a metal
hurdle so the sheep could enter into the decision area using a rotating gate. The sheep
exit the pen by the doors located at the end of the decision area (Figure 3.1).
Figure 3.1 Schematics of the testing apparatus for simple discrimination of colour (top: top
view, bottom: side view) based on the design of Morton and Avanzo (2011). Two areas (2.4 m ×
7.2 m) are adjacent to each other and set in opposite direction (grey area marked the testing area
in the top testing pen). Each testing pen comprises a central starting gate, and two
discrimination test areas are divided longitudinally by a metal hurdle. One the sheep has made
Chapter 3 General Materials and Methods 45 the choice (one side), the gate is closed behind the sheep. After consuming the reward (or after 1
min) the sheep exits through the exit gates located at the end of the pen. The sheep is pushed
into the end pen corridor and start the next discrimination test in the adjacent pen. The two
discrimination stimuli (S) are located at the end of the pen.
Testing precedure
Testing was conducted using the stimuli shown in Table 3.3, starting with a simple
discrimination (SD). The pairs of stimuli were presented at random, and designated S+
(correct) and S- (incorrect). The task required the sheep to discriminate between the
colours of blue and yellow, and later, if sheep learnt to learn the reversal. A food reward
(a ration of lupin grain) was presented for the correct choice. For each discrimination, a
pair of stimuli (blue and yellow card) was placed on either side of the dividing hurdle at
the end of each pen, with the correct and incorrect colours (S+ and S-). For all parts of
this experiment, the food reward was placed in a feed bucket under the S+ card. The test
started when the sheep entered the start gate from where the S+ and S- cards can clearly
be seen. The animals were free to move in the test area towards either of the stimuli and,
once past a designated line (1 meter from the stimuli), the decision was recorded,
together with delay to the decision (seconds). Behavioural observations (bleating,
jumping, stomping) were also recorded for all discriminations. Initially, during the
training phase if the animal chose incorrectly (S-), they were ushered into the correct
side (S+), being allowed one minute to identify the presence of the food reward. The
training phase continued until all sheep knew the reward was under the S+ stimulus,
after which they were either allowed 1 min to eat the reward if S+ was chosen or had to
wait 20 seconds if S- was chosen, before being ushered onto the next discrimination test.
Between each discrimination test, we swapped the stimuli (together with the food
bucket) so as to control for biases towards the left or right side of the pen. A
performance criterion was set at 75% correct over 8 consecutive discriminations, plus
75% of the individuals in each experimental group passing the test. Once sheep reached
this criterion, they were considered as having learnt the test and were passed onto the
reversal test, where the reward contingency was reversed. All sheep within each
experimental group performed the same number of discriminations (4 to 8
discriminations each day).
Table 3.3 The simple discrimination and its reversal, with the designated S+ and S-
Chapter 3 General Materials and Methods 46
Discriminations Relevant dimension Correct (S+) Incorrect (S-)
Simple Discrimination (SD)
Simple Reversal (SR)
Colour
Colour
Blue
Yellow
Yellow
Blue
3.8.2 Y-maze test (spatial discrimination)
Testing apparatus
The Y-maze test apparatus comprised a starting gate, leading into a run (2.4 m long;
Zone ‘A’, Figure 3.2) that bisected into the two arms of the maze (each 2.4 m long;
Zones ‘B’ and ‘C’), with two gates located at the ending of the two arms. All the sides
of the Y-maze were covered with hessian to isolate the animal from external visual
stimuli.
Testing procedure
For all parts of this experiment, the food reward was placed in a feed bucket on the
maze arm designated S+, with an empty feed bucket placed on the incorrect arm (S-).
The test started when the sheep passed the starting gate into Zone A, from which they
had to make a choice within one minute toward the left (B) or right (C) arms of the
maze. The animals were free to move around the maze through the different zones. We
recorded the time sheep took to find and eat the food and the number of times the sheep
crossed the boundaries into different zones until it had found and started eating the food
reward in the S+ arm. After 24 trials, the test was reversed by swapping the bucket
containing the reward bucket with the empty bucket, so as to control for olfactory
recognition of food rather than left-right learning with associated reward. For each
group of sheep, one half was trained to find one side of maze and the other half trained
to the other side. All trials were video recorded to facilitate the behavioural analysis.
A sheep was considered to have achieved spatial discrimination (or to have learned to
take the correct side) once it had made the correct choice over 4 consecutive tests
without error. Having met the criteria, the sheep were tested for reversal spatial
discrimination. The reversal spatial test was similar to the spatial discrimination test but
the side with the food reward (S+) was swapped to the opposite side; sheep previously
learned to find rewards on the left were tested with the food reward located on the right.
Chapter 3 General Materials and Methods 47 All sheep were subjected to the same total number of trials during the spatial
discrimination test.
Figure 3.2 Schematics of the testing apparatus used to conduct the Y-maze test adapted from the
design of Kendrick et al. (1995). The maze is divided in 3 zones (A, B, C). The feeder with food
reward and the empty feeder are placed at the end of the two arms (zones ‘B’ and ‘C’).
Chapter 4 Gene polymorphisms associated with temperament 48
Chapter 4
Associations between temperament and gene polymorphisms in the
dopaminergic system and adrenal gland in sheep
Page
4.1 Abstract 49
4.2 Introduction 50
4.3 Materials and Methods 52
4.3.1 Animals 52
4.3.2 Genomic DNA isolation 52
4.3.3 Detection of polymorphisms of CYP17, DRD4, DRD2 and MAOA 53
4.3.4 Real-time genotyping 55
4.4 Statistical analysis 56
4.5 Results 57
4.5.1 Identification of the gene polymorphisms (5 SNPs) 57
4.5.2 Genotypes called by real-time genotyping 57
4.5.3 Frequency of polymorphism in each temperament line 59
4.6 Discussion 60
4.7 Conclusion 63
Chapter 4 Gene polymorphisms associated with temperament 49
4.1 Abstract
Sheep of calm or nervous temperament differ in their physiological (cortisol secretion)
and behavioural (motor activity) responses to stressors, perhaps due to variation in genes
that regulate glucocorticoid synthesis or brain dopamine activity. Using ewes that had
been selected over 20 generations for nervous (n = 58) or calm (n = 59) temperament,
we confirmed the presence of a polymorphism in a gene involved for cortisol
production (CYP17), and identified polymorphisms in three genes associated with
personality and behavioural traits: dopamine receptors 2 and 4 (DRD2, DRD4), and
monoamine oxidase A (MAOA). The calm and nervous lines differed in their
frequencies of CYP17 SNP628 (single nucleotide A-G mutation at the position 628)
(A/A: Nervous 31.0% vs Calm 10.2%, P < 0.01; G/G: Nervous 27.6% vs Calm 47.5%, P
< 0.05) and DRD2 SNP939 (single nucleotide T-C mutation at the position 939) (T/T:
Nervous 25.9% vs Calm 59.3%, P < 0.01; T/C: Nervous 55.7% vs Calm 33.9%, P <
0.05; C/C: Nervous 19.0% vs Calm 6.8%, P < 0.05), but those for DRD2 SNP483 and
the 2 MAOA SNP genotypes did not. We conclude that, for sheep, a combination of the
DRD2 SNP939 C allele and the CYP17 SNP628 A/A genotype could be used as a
potential genetic marker for nervous temperament prediction, and that a combination of
DRD2 SNP939 T/T and CYP17 SNP628 G/G could be used as a potential genetic
marker for calm temperament.
Key words: Dopamine receptor, Monoamine oxidase, Glucocorticoid, CYP17, Stress
Chapter 4 Gene polymorphisms associated with temperament 50
4.2 Introduction
Humans and animals exposed to a stimulus initially evaluate the situation at brain level
on the basis of a variety of parameters such as suddenness, familiarity, pleasantness,
controllability, predictability, expectations, and social norms (Boissy 1995). Their
subsequent emotional responses involve three components (Corr 2009): 1) a
psychological response, such as positive and negative feelings, that cannot be directly
assessed in animals; 2) a behavioural response; and 3) a physiological response that
involves changes in, for example, adrenaline, noradrenaline, serotonin, dopamine and
cortisol (Deckersbach 2006; Haas 2007; Corr 2009). Individuals exposed to the same
stimulus can show differences in all three components, and this variability is called
temperament (Strelau 1987; Mervielde et al., 2005; Blache and Bickell 2010, 2011;
Shiner and DeYoung 2011).
We have been investigating temperament in a flock of sheep that has been been
genetically selected for 20 generations on the basis of behavioural responses to isolation
and human presence. As a result, the two lines were produced, one is hypo-responsive
(‘calm’) and the other one is hyper-responsive (‘nervous’) to the stressors (Murphy et al.,
1994; Blache and Ferguson 2005), that present a useful model for studying the genetic
basis of the relationships between temperament, behaviour and physiology. The
temperament of an individual depends on genetic background (Strelau 1987; Saudino
2005; Mervielde et al., 2005; Krueger et al., 2008; Bickell et al., 2009) and life
experience (Krueger et al., 2008). Genetic associations with personality, psychological
disorders and behavioural traits are supported by an increasing body of evidence from a
variety of animal models, including monkeys, birds, rodents, cattle, dogs and horses
(Rubinstein et al., 1997; Niimi et al., 1999; Sugiyama et al., 2004; Momozawa et al.,
2005; Bailey et al., 2007; Fidler et al., 2007; Glenske et al., 2011). The genes involved
could affect the perception or the process of evaluation at brain level, or the modulation
of the physiological response at the level of the hypothalamic-pituitary-adrenal (HPA)
axis.
At brain level, human personality traits, including temperament, have been linked to
genetic differences in neurotransmitter systems (Cloninger 1994). In humans and
non-human primates, polymorphisms in genes encoding for tyrosine hydroxylase (TH),
dopamine transporter (DAT), dopamine receptors 2, 3 and 4, tryptophan hydroxylase
Chapter 4 Gene polymorphisms associated with temperament 51
(TPH), monoamine oxidase A (MAOA, an enzyme responsible for the catabolism of
5-serotonin and dopamine), serotonin transporter (5-HTT) and serotonin receptors, have
all been linked with personality, psychiatric disorders (neuroticism, schizophrenia),
substance dependence and abuse, eating disorders, depression, anxiety, child abuse and
suicidal behaviour (Reif and Lesch 2003). Moreover, polymorphisms in dopamine
receptors 2 and 4 (DRD2, DRD4) and in MAOA (Shih and Thompson 1999) have often
been associated with impulsivity, aggression, fear and panic-related behaviours in
humans (Noble et al., 1998; Rowe et al., 1999; Deckert et al., 1999; Manuck et al., 2000;
Curran et al., 2001; Contini et al., 2006; Eisenberg et al., 2007; Eisenberg et al., 2007;
Congdon et al., 2008; Munafo et al., 2008; White et al., 2009; Kramer et al., 2009;
Hamidovic et al., 2009; Zai et al., 2012; Pappa et al., 2014). These behavioural
phenotypes are similar to those used to define temperament in our ‘calm’ and ‘nervous’
lines (fear, behavioural reactivity in response to the isolation (Murphy et al., 1994;
Blache and Ferguson 2005), so it is feasible that the same genes could be involved.
In the HPA axis, cortisol is the final effector and variation in the amplitude of the
stressor-induced response in plasma cortisol concentrations has been associated with
temperament in humans, monkeys, dogs, cattle, and sheep (Gunnar et al., 1997; Beerda
et al., 1998; Kalin et al., 1998; Hennessy et al., 2001; De Palma et al., 2005; Burdick et
al., 2010; Hawken et al., 2013). The full range of adrenal steroid hormones are
synthesised in the adrenal cortex from the same precursor, and preference for cortisol
over mineralocorticoids and androgens is controlled by several enzymes, with CYP17
(cytochrome P450 17α-hydroxylase/17,20-lyase) being a key branch-point enzyme
(Nakajin et al., 1981). Polymorphism in the gene for CYP17 affects CYP17 enzyme
activity and the cortisol response to a stressor in South African Angora goats and
Merino sheep (Storbeck et al., 2007, 2008; Hough et al., 2013). Moreover, the cortisol
response to stressors differs between our ‘calm’ and ‘nervous’ sheep (Hawken et al.,
2013), so CYP17 is an obvious candidate gene.
Therefore, the present study aimed to identify polymorphisms associated with
temperament for potential use in marker assisted selection. The physiological and
behavioural differences between our ‘calm’ and ‘nervous’ lines of sheep have been well
characterised, so we used an association study (Glazier et al., 2002; Bah Rosman 2008)
to look at the association of candidate genes with those differences. This approach is
Chapter 4 Gene polymorphisms associated with temperament 52
more appropriate than ‘whole-genome association analysis’ or ‘linkage analysis’, both
of which are preferable when the underlying pathophysiological mechanisms are not
known and false positive results are likely (Fan et al., 2006; Bah Rosman 2008).
Therefore, in this chapter, we tested the hypothesis that polymorphisms of specific
genes will be distributed differently between the two lines of sheep that had been
selected for calm or nervous temperament by quantifying 4 genes (DRD4, DRD2,
MAOA, CYP17) in both phenotypic lines.
4.3 Materials and Methods
This experiment was carried out in accordance with the Australian Code of Practice for
the Care and Use of Animals for Scientific Purposes (8th Edition, 2013) and was
approved by the Animal Ethics Committee of The University of Western Australia under
RA/3/100/1252.
4.3.1 Animals
We used a flock of Merino sheep that had been selected for over 20 generations on
criteria that reflect emotional reactivity. At approximately 16 weeks of age, within 2
weeks after weaning, the behavioural reactions of lambs to humans measured in an
‘arena test’ and their reactions to social isolation were measured in an ‘isolation box test’
(Murphy et al., 1994; Blache and Ferguson 2005). The two tests are described in
‘general materials and methods’ chapter. All animals were assigned an overall selection
score that combined these two tests, allowing them to be classified as ‘nervous’ or ‘calm’
on the basis of expression of high or low levels of movement or vocalisation. The
‘nervous’ line is more reactive to contact with humans and with isolation, whereas the
‘calm’ line is less reactive to humans and to isolation (Blache and Ferguson 2005). For
the first part of this study, we used 58 ewes from the ‘nervous’ line and 59 ewes from
the ‘calm’ line, all 16 weeks old and of similar live weight (20 ± 1.6 kg). The animals in
the two lines were always managed together except at mating and lambing.
4.3.2 Genomic DNA isolation
Whole blood was sampled by jugular venepuncture into EDTA vacutainers (Greiner
Bio-One, Australia). Genomic DNA was isolated using the DNeasy Blood and Tissue Kit
(Qiagen, Germany) according to the instructions provided by the manufacturer. The
success of the isolation was confirmed by gel electrophoresis and the concentration of
Chapter 4 Gene polymorphisms associated with temperament 53
genomic DNA was measured using BioPhotometer Plus (Eppendorf, Hamburg,
Germany).
4.3.3 Detection of polymorphisms of CYP17, DRD4, DRD2 and MAOA
The primers used to amplify the single nucleotide polymorphism (SNP) located on
position 628 (SNP628) fragment of CYP17 had previously been described for South
African Merino sheep (Hough 2012; Table 4.1). The other primers were designed using
Primer Premier software (Version 5.0, PREMIER Biosoft, Palo Alto, CA, USA) to
amplify a highly conserved fragment of DRD4, all 7 exons of DRD2, and 3 exons of
MAOA, based on sequences obtained from Genebank (Table 4.1). All primers were
synthetised by GeneWorks, Australia.
Fragments of the CYP17 and DRD4 genes were amplified by PCR. Amplification
reactions (in 10 µL) contained 2 µL of 5×PCR buffer including 0.2 mM dNTPs (Fisher
Biotec, Australia), 2.5 mM MgCl2 (Fisher Biotec, Australia), 0.3 µM each of forward
and reverse primers (GeneWorks, Australia), 1.1 U Taq DNA polymerase (5.5 U/µL;
Fisher Biotec, Australia) and 20 ng genomic DNA. The fragments of CYP17 SNP628
and DRD4 were amplified at an initial denaturation at 94 °C for 5 min, followed by 35
cycles of 94 °C for 30 s, 58 °C for 30 s, 72 °C for 15 s, and a final extension at 72 °C for
7 min.
Fragments of the DRD2 and MAOA genes were amplified by PCR in 50 µL: 5 µL of
10×Faststart PCR buffer (Roche, Germany), 2 mM MgCl2 (Roche, Germany), 0.2mM
dNTP mix (Roche, Germany), 0.3 µM each of forward and reverse primers (GeneWorks,
Australia), 2 U Faststart Taq DNA polymerase (5 U/µL; Roche, Germany) and 80 ng
genomic DNA. DRD2 exon2 and exon5 were amplified at an initial denaturation at
95 °C for 6 min, followed by 35 cycles of 95 °C for 30 s, 60 °C for 30 s, 72 °C for 20 s,
and a final extension at 72 °C for 7 min. For DRD2, exons 1, 6 and 7 were amplified at
an initial denaturation at 95 °C for 6 min, followed by 35 cycles of 95 °C for 30 s, 68 °C
for 30 s, 72 °C for 42 s, and a final extension at 72 °C for 7 min. DRD2 exons 3 and 4
were amplified at an initial denaturation at 95 °C for 6 min, followed by 35 cycles of
95 °C for 30 s, 60 °C for 30 s, 72 °C for 25 s, and a final extension at 72 °C for 7 min.
MAOA exon 8 was amplified at an initial denaturation at 95°C for 6 min, followed by
35 cycles of 95 °C for 30 s, 60 °C for 30 s, 72 °C for 15 s, and a final extension at 72 °C
for 7 min. MAOA exons 1 and 15 were amplified at an initial denaturation at 95°C for 6
min, followed by 35 cycles of 95 °C for 30 s, 68 °C for 30 s, 72 °C for 42 s, and a final
Chapter 4 Gene polymorphisms associated with temperament 54
extension at 72 °C for 7 min.
Table 4.1 Oligonucleotide primers used in PCR amplification for cytochrome P450
17α-hydroxylase/17,20-lyase (CYP17), dopamine receptors 2 and 4 (DRD2, DRD4) and
monoamine oxidase A (MAOA). Accession numbers from Genebank are NC_019479 for
CYP17 mRNA, XM_004016032 for DRD2 mRNA, and XM_004022016 for MAOA mRNA.
Note: CYP17 SNP628 has been reported previously (Hough 2012).
Gene Fragment Gene Oligonucleotide sequences (5'- to 3'-)
CYP17
SNP628 F: CCTGAAGGCCATACAAA
R: GGATACTGTCAGGGTGTG
DRD4 Conserved fragment F: TGCTCTGCTGGACGCCCT TCT TC
R: GTGCGG AACTCGGCGTTGAAGAC
DRD2 Exon 1 F: TCCGCTGAACCTGTCCTGGTATGAT
R: TGAGATGGCACGCTCTTGAGGGGT
Exon 2 F: CCACCCATTATGTTGCTTTGTCT
R: AAGGTGGTTGGTCTGGGTTG
Exon 3 F: CAAAGTGGGGTGTCTCTGTGG
R: CCAGGAGGACAGAGGCAGGACT
Exon 4 F: GGCTTTCTTCCTCCTCCCCA
R: CAGAGACATTGGGGGAGAGTGGT
Exon 5 F: GTTTCTGTTCTCACCCGCCTC
R: GTCCCTGACCTGAACACTTACCAC
Exon 6 F:AGGAGATAAGGGAGCCTGAGTGAG
R: CCTGTATTGCTGGGTCCGTCG
Exon 7 F: CTCCCGCAGGTGTGTTCAT
R: CAAGGACATGGCCGAGGCT
MAOA Exon 1 F: GCTCAACCCCCGAATTCCCC
R: CCCCCAAACGCCACTTTCAGA
Exon 8 F: GCTTCCATCAGAGCGAAACCA
R: TAAACACAGCCTACCCTTTTTCTTC
Exon 15 F: CTCTGATGTCTTTGTAGATGCCACT
R: TGAGCATGTCAACTTTAACTTCTTG
The polymorphisms for each gene fragment were checked after sanger sequencing by
the Australian Genome Research Facility (Western Australia). Each gene fragment was
Chapter 4 Gene polymorphisms associated with temperament 55
amplified and sequenced in a subset of 5 nervous and 5 calm sheep and the sequences
were aligned using BioEdit Sequence Alignment Editor software (version
7.0.5.2©1997-2007, T. Hall).
4.3.4 Real-time genotyping
The probes used to genotype the SNP628 fragment of CYP17 have also been published
for South African sheep (Hough 2012; Table 4.2). The specific primers and Taqman
MGB probes for other fragments (Table 4.2) were designed according to the
polymorphisms identified above and used to genotype each ewe using a Taqman MGB
probe assay. Each sample was genotyped in triplicate using a Vii7TM Real-Time
instrument from Applied Biosystems (California, USA). Amplification reactions (10 µL)
were performed using 5µL of 2×TaqMan® Genotyping Master Mix (Applied Biosystems,
California, USA), 0.5 µL of custom TaqMan® SNP genotyping Assay (20×) containing
two primers and two labelled probes (Applied Biosystems, California, USA) and 20 ng
genomic DNA. The thermal cycle included a pre-read stage at 60 °C for 30 s, a hold
stage for denaturation at 95°C for 10 min to activate the AmpliTaq Gold®DNA
polymerase, followed by 40 cycles of 95 °C for 15 s, 60 °C for 60 s (with the additional
step of cooling to 52 °C for 30 s prior to 60 °C extension for CYP17 SNP628 due to the
lower annealing temperature of the primers) and a post-read stage at 60 °C for 30 s. The
transition rate between all steps was 1.6 °C/s.
The data were collected using the Allelic Discrimination Plot of Vii7TM software. A
no-template control (negative control) was also included in each assay. Accuracy of
real-time genotyping results was confirmed by direct sequence analysis by the
Australian Genome Research Facility (Western Australia). Sequencing results were
analysed with BioEdit Sequence Alignment Editor software (version 7.0.5.2©
1997-2007, T. Hall).
Chapter 4 Gene polymorphisms associated with temperament 56
Table 4.2 Nucleotide sequences of primers and probes used in real-time PCR
genotyping for cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17), dopamine
receptors 2 and 4 (DRD2, DRD4) and monoamine oxidase A (MAOA). Note: CYP17
SNP628 has been reported previously (Hough 2012).
Gene SNP Oligonucleotide sequence (5'- to 3'-)
CYP17 SNP628 Forward primer
Reverse primer
Sensor probe
Anchor probe
CCTGAAGGCCATACAAA
GGATACTGTCAGGGTGTG
(VIC®-labelled): CTTCCTTGCTCAGAACC
(FAMTM-labelled):TCCTTGCCCAGAACC
DRD2 SNP483 Forward primer
Reverse primer
Sensor probe
Anchor probe
CGGTCATGATCGCCATCGT
GAGCATCGGGCAGGAGAT
(VIC®-labelled): TGAAGGACAGGACCCAG
(FAMTM-labelled):AAGGACAGAACCCAG
SNP939 Forward primer
Reverse primer
Sensor probe
Anchor probe
ACCCTCCCCGACCCA
GGCATGCCCGTTCTTCTCT
(VIC®-labelled): TCCCACCATGGCCTC
(FAMTM-labelled): CCACCACGGCCTC
MAOA SNP189 Forward primer
Reverse primer
Sensor probe
Anchor probe
GCATGGAGAGTCTGCAGAAGA
GTGCTACGGTCCACACTGA
(VIC®-labelled): TCGAACATCTGGCCCGC
(FAMTM-labelled): TCGAACATCTGACCCGC
SNP219 Forward primer
Reverse primer
Sensor probe
Anchor probe
GCATGGAGAGTCTGCAGAAGA
GTGCTACGGTCCACACTGA
(VIC®-labelled): TGAGATGCCGCCTCCT
(FAMTM-labelled): TGAGATGCCACCTCCT
4.4 Statistical analysis
BioEdit Sequence Alignment Editor software (version 7.0.5.2©1997-2007, T. Hall) was
used to identify gene polymorphisms (SNPs) in individual sheep, and Vii7TM software
(Applied Biosystems, California, USA) was used to collect the genotypes of each SNP.
For each SNP, differences between temperament lines in genotype frequency were
compared using Chi-square tests and the reliability of the data was tested using the
Hardy-Weinberg equilibrium. Differences were considered significant at P < 0.05 and
Chapter 4 Gene polymorphisms associated with temperament 57
very significant at P < 0.01.
4.5 Results
4.5.1 Identification of the gene polymorphisms (5 SNPs).
There was no variation in nucleotide sequence in the conserved fragment of DRD4, but
two SNPs were detected in the DRD2 gene: a C/T SNP at position 483 in exon 3 and a
T/C SNP in position 939 in exon 6 (Table 4.3). All three genotypes were obtained by
genotyping. For the sequenced MAOA gene fragments, two C/T mutations were
detected in exon 1, one at position 189 and one at position 219. Again, all three
genotypes were obtained by genotyping (Table 4.3). For CYP17, we detected the same
A/G mutation, SNP628, that had been described in South African sheep (Storbeck et al.,
2008).
Table 4.3 SNPs detected in the three candidate genes that control glucocorticoid synthesis
(CYP17), dopamine receptor 2 (DRD2) and monoamine oxidase A (MAOA). Note: for CYP17,
this is a confirmation of SNP628 reported previously (Storbeck et al., 2008)
Gene SNP Oligonucleotide sequence (5'- to3')
CYP17 SNP628 AAGGAACGA
AAGGAACGG
DRD2 SNP483 CTGGGTCCTGTCCTT
CTGGGTTCTGTCCTT
SNP939 CACCATGGCCTCCA
CACCACGGCCTCCA
MAOA SNP189 GGGCCAGATGTTCGA
GGGTCAGATGTTCGA
SNP219 GTGATAGGAGGCG
GTGATAGGAGGTG
4.5.2 Genotypes called by real-time genotyping
Three genotypes (Allele1/Allele1; Allele2/Allele2; Allel1/Allel2) for above detected
each SNP were identified according to the Allelic Discrimination Plot (Figure 4.1). The
clustering of datapoints along horizontal axis call homozygous Allele1/Allele1 genotype
(A/A for CYP17 SNP628; C/C for DRD2 SNP483; T/T for DRD2 SNP939; C/C for
MAOA SNP189 and SNP219), the clustering of datapoints along vertical axis call
homozygous Allele2/Allele2 genotype (G/G for CYP17 SNP628; T/T for DRD2
Chapter 4 Gene polymorphisms associated with temperament 58
SNP483; C/C for DRD2 SNP939; T/T for MAOA SNP189 and SNP219) and the
clustering of datapoints along diagonal call heterozygous Allel1/Allel2 genotype (A/G
for CYP17 SNP628; C/T for DRD2 SNP483; T/C for DRD2 SNP939; C/T for MAOA
SNP189 and SNP219).
Fig 4.1 The Allelic Discrimination Plot results for the three genotypes.
Chapter 4 Gene polymorphisms associated with temperament 59
4.5.3 Frequency of polymorphism in each temperament line
Individual genes
The CYP17 SNP628 A/A genotype was about three-fold more frequent (P < 0.01) in the
nervous line than in the calm line, whereas the G/G genotype was about twice as frequent
(P < 0.05) in the calm line than in the nervous line (Table 4.4). There were no differences
between the lines for the frequencies of the A/G genotype of CYP17 SNP628 (Table 4.4)
or any of the three genotypes of DRD2 SNP483 (Table 4.4). By contrast, for the DRD2
SNP939, the T/T genotype was twice as frequent in the calm line than in the nervous line
(P < 0.01), whereas the T/C and C/C genotypes were more frequent in nervous than in
calm animals (P < 0.05; Table 4.4). The frequencies of all three genotypes for MAOA
SNP189 and SNP219 were similar for calm and nervous sheep (Table 4.4).
Combinations of genes
The genotype frequencies of only two genes (CYP17 SNP628 and DRD2 SNP939)
differed significantly between the calm and nervous lines, so we analysed the
relationships between gene frequency combinations and temperament (Table 4.4). In the
nervous line, 17/18 sheep (94%) with the CYP17 SNP628 A/A genotype also had the
DRD2 SNP939 C/T and C/C genotypes. In the calm line, 15/35 sheep (43%) with the
DRD2 SNP939 T/T genotype also carried the CYP17 SNP628 G/G genotype, but only
4/35 sheep (11%) carried the CYP17 SNP628 A/A genotype.
Chapter 4 Gene polymorphisms associated with temperament 60
Table 4.4 Frequency distribution of the SNPs of target genes in the control of glucocorticoid
synthesis (CYP17), dopamine receptor 2 (DRD2) and monoamine oxidase A (MAOA) in
nervous (n = 58) and calm (n = 59) lines of sheep. Different superscripts in the same column
within SNP indicate significant difference between lines: P < 0.01 for uppercase, P < 0.05 for
lowercase.
Selection line Gene SNP Genotypes
CYP17 SNP628 A/A G/G A/G
N % N % N %
Nervous 18 A 31.0 16 a 27.6 24 a 41.4
Calm 6 B 10.2 28 b 47.5 25 a 42.4
DRD2 SNP483 C/C T/T C/T
N % N % N %
Nervous 32 a 55.2 1 a 1.7 25 a 43.1
Calm 36 a 61.0 4 a 6.8 19 a 32.2
SNP939 T/T C/C T/C
N % N % N %
Nervous 15 A 25.9 11 a 19.0 32 a 55.2
Calm 35 B 59.3 4 b 6.8 20 b 33.9
MAOA SNP189 C/C T/T C/T
N % N % N %
Nervous 40 a 69.0 9 a 15.5 9 a 15.5
Calm 34 a 57.6 14 a 23.7 11 a 18.6
SNP219 C/C T/T C/T
N % N % N %
Nervous 40 a 69.0 9 a 15.5 9 a 15.5
Calm 34 a 57.6 14 a 23.7 11 a 18.6
4.6 Discussion
Polymorphisms of two specific genes, one controlling glucocorticoid synthesis (CYP17)
that has previously been described in South African sheep (Storbeck et al., 2008), and
the other controlling dopamine receptor 2 (DRD2), are associated with temperament
phenotype (calm or nervous) in Australian Merino sheep.
Chapter 4 Gene polymorphisms associated with temperament 61
For CYP17 SNP628, we detected three genotypes (A/A, A/G, G/G) in the two
temperament lines whereas, in South African sheep, only two genotypes (A/A, A/G)
were detected (Storbeck et al., 2008). Moreover, the frequency of A/A and G/G
genotypes differed between our calm and nervous temperament lines whereas, in South
African sheep, the frequency of A/A and A/G genotypes were similar in the rearing
ability lines (Vander Walt et al., 2009). The presence or absence of the homozygous G/G
genotype might be explained by differences in the historical origins of the Australian
and South African Merino sheep, or by differences in the genetic selection criteria used
in the two studies.
The origin of the South African Merino is not clear but could explain the absence of the
homozygous G/G. It has also been suggested that, South African Merino sheep are
mixed Merino breed with different Merino types from around the world (Ryder 1984;
Mason 1996; Anon. 2005). Two Spanish rams and four Spanish ewes would have been
introduced into South Africa in 1789 (Ryder 1984), and then from 1891, American
Vermont type Merinos were introduced into South Africa (Mason 1996), and then,
Australian Merinos were imported before 1929 (Ryder 1984). South African Merinos
are a mixed genetic background which is different from that of Australian Merinos
which came from Spanish Merinos only. It was suggested (Cottle 2010) that in 1797, the
Spanish Merino sheep were first introduced into Australia, and the Australian Merinos
were then introduced into South Africa before 1929 (Ryder 1984). A possibility is that
the genotype of CYP17 SNP628 of all the rams or all the ewes introduced into South
Africa from Australia was accidently A/A, therefore, whatever was the genotypes of the
ewes or rams (A/A, A/G or G/G), the offspring could not be G/G.
Our results show that G/G genotype is strongly associated with the phenotype for calm
temperament (in our selected flock) and that its percentage in nervous group was small
(27.59%). Since the two temperament lines have been selected for over 20 generations,
the probability of a homozygous G/G genotype is higher in animals that are calm
(47.46%) than in a random population as suggested by the percentage of homozygous
G/G (13.31%) detected in the non selected flock. The sheep used in South African
Merino sheep were from two different lines (H-line and L-line) selected for the ability
of ewes to rear multiple offspring, not for temperament as such and since probability to
detect G/G can be low, the homozygote genotype G/G for CYP 17 SNP628 was not
Chapter 4 Gene polymorphisms associated with temperament 62
present in the 136 South African Merino sheep genotyped in the study by Vander Walt
et al. (2009).
For the DRD2 gene, we detected two SNPs that are novel for Australian Merino sheep,
SNP939 (exon 6) and SNP483 (exon 3), but only SNP939 is associated with
temperament phenotype. The difference between the two alleles is not surprising
because SNP483 is a synonymous mutation (GTC-GTT) with both versions encoding
for valine, whereas SNP939 (ATG-ACG) causes a change from methionine to threonine
that has the potential to influence phenotype. Interestingly, a DRD2 polymorphism has
also been associated with personality traits and behaviours in humans (Noble et al.,
1998; Rowe et al., 1999; Eisenberg et al., 2007; Eisenberg et al., 2007; Hamidovic et al.,
2009; White et al., 2009; Zai et al., 2012). These observations also agree with the
presence of large numbers of DRD2 in brain tissue (Muly et al., 1998) in dopaminergic
pathways that are involved in the expression of behaviours related to fear, aggression
and novelty-seeking (Jonsson et al., 2003; Zai et al., 2012).
In contrast to CYP17 and DRD2, we did not detect polymorphisms in the fragments of
DRD4 or MAOA that we targeted, so it seems unlikely that DRD4 or MAOA are
associated with temperament in sheep. On the other hand, it is feasible that important
polymorphisms are located on other parts of the genes. In the absence of a published
mRNA sequence for ovine DRD4, we selected a highly conserved fragment that had
been published for other species and aligned well with the sheep genome. For the ovine
MAOA gene, we investigated only the three longest known exons (exons 1, 8, 15) and
neither of the two SNPs detected in exon 1 were associated with temperament. Again,
this is to be expected because they were both synonymous mutations, with both variants
of SNP189 (GGC and GGT) encoding for glycine and both variants of SNP219 (GTT
and GTC) encoding for valine.
The lack of association between MAOA polymorphisms and temperament phenotype
agrees with observations on humans where MAOA polymorphisms are associated with
psychological disorders and substance addiction, rather than behavioural reactivity
(Schulze et al., 2000; Du et al., 2002). However, there is an important difference in
methodology. In humans, the phenotype is measured using clinical interview or
diagnosis, in marked contrast to the measurement of temperament in sheep using
Chapter 4 Gene polymorphisms associated with temperament 63
behavioural challenges. Nevertheless, where an association between MAOA genotype
and phenotype has been found in humans, the phenotype was antisocial behaviours that
are assessed using methods analogous to our behavioural tests, with scores allowing a
segregation between high and low levels of impulsiveness, aggression and irritability
(Jorm et al., 2000; Koller et al., 2003). In addition, MAOA activity seems to differ
between genders (Murphy et al., 1976) and we only used female sheep, a factor that
might also explain the lack of association with temperament. In all but one study of
humans, an association between MAOA polymorphism and behavioural reactivity was
detected in males rather than females. The exception was the work on females by
Deckert et al. (1999), but they assessed phenotype by structured clinical interview. In
our breeding flock, we retain very few males so we could not include gender in the
design. The present study is the first investigation of MAOA polymorphisms in sheep
and their association with temperament, and it was clearly not exhaustive, so the
remaining 12 exons need to be explored, as does the issue of gender.
4.7 Conclusion
A total of 5 polymorphisms were identified in sheep that affect glucocorticoid synthesis
(CYP17), dopamine receptor 2 (DRD2) and monoamine oxidase A (MAOA). Of these,
one for CYP17 (SNP628) and one for DRD2 (SNP939) were distributed significantly
different between the calm and nervous lines. The data suggest that DRD2 SNP939 C
allele combined with CYP17 SNP628 A/A genotype could be used as a potential genetic
marker for nervous temperament prediction, whereas the combination of DRD2
SNP939 T/T plus CYP17 SNP628 G/G genotypes could be used as a potential genetic
marker for calm temperament in Merino sheep. The validation of their correctness as the
genetic marker will to be explored in next chapter.
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 64
Chapter 5
The association of CYP17 SNP628 and DRD2 SNP939 genotypes with
behavioural and physiological cortisol responses Validation of the correctness of the two SNPs as genetic markers
Page
5.1 Abstract 65
5.2 Introduction 66
5.3 Materials and Methods 67
5.3.1 Animals 67
5.3.2 Blood sampling for genotypes screening 67
5.3.3 Phenotyping 68
5.4 Statistical analysis 69
5.5 Results 70
5.5.1 Frequency of each genotype and combination of genotypes 70
in non-selected sheep
5.5.2 Behavioural phenotype 71
5.5.3 Cortisol response 72
5.6 Discussion 75
5.7 Conclusion 77
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 65
5.1 Abstract
To validate the two SNPs obtained in Chapter 4 as genetic markers for prediction of
sheep temperament, we genotyped a large non-selected flock of 268 ewes of unknown
temperament for the DRD2 SNP939 and CYP17 SNP628 polymorphisms. We tested
whether these two SNPs were associated with the two phenotypes of temperament, the
physiological (cortisol) phenotype and the behavioural phenotype (reactivity). The
results showed that behavioural responses to the ‘arena test’ and ‘isolation box’ tests
were affected by DRD2 SNP939 genotype and that the response to ACTH challenge
was affected by CYP17 SNP628 genotype. The sheep carrying the DRD2 SNP939 calm
genotype had lower behavioural scores than those carrying the SNP939 nervous
genotype (P < 0.05). After ACTH administration, sheep with CYP17 SNP628 nervous
genotype had higher values for maximum cortisol concentration, amplitude and area
under the curve (AUCI) than sheep with CYP17 SNP628 calm genotype (P < 0.05).
Therefore, considering the results presented here alongside those in Chapter 4, we
conclude that the combination of the DRD2 SNP939 C allele plus the CYP17 SNP628
A/A genotype could be used as a genetic marker for nervous temperament, whereas the
combination of the DRD2 SNP939 T/T plus the CYP17 SNP628 G/G genotype could be
used as a genetic marker for calm temperament in Merino sheep.
Key words: Genetic marker; Validation; Behavioural response; Physiological response
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 66
5.2 Introduction
In Chapter 4, we described the detection of DRD2 SNP939 and CYP17 SNP628
genotypes and their association with temperament in sheep: it appears that the DRD2
SNP939 C allele can be combined with the CYP17 SNP628 A/A genotype to provide a
genetic marker for prediction of nervous temperament, whereas the DRD2 SNP939 T/T
genotype can be combined with the CYP17 SNP628 G/G genotype to provide a genetic
marker for prediction of calm temperament. However, this conclusion is a statistical
association so we need to validate these two SNPs as genetic markers with a phenotype
verification experiment. Therefore, in this chapter, we will use a non-selected flock to
test the association of the SNP genotypes with the two phenotypes of temperament, the
physiological response (cortisol) and the behavioural response (reactivity).
The CYP17 gene encodes P450c17, an enzyme that is predominantly expressed in the
mammalian adrenal cortex where it plays a central role in the production of cortisol
(Nakajin et al., 1981). This enzyme catalyses two reactions, 17-hydroxylation and 17,
20-lyase, both of which are important for synthesis of mineralocorticoids, glucocorticoids
and androgens. Of all the cytochrome P450 enzymes involved in steroidogenesis, only
P450c17 possesses dual hydroxylase and lyase activities, so CYP17 sits at a critical
branch point where it determines the synthesis of cortisol in preference to
mineralocorticoids and androgens from the same precursors (Nakajin et al., 1981).
A study of South African sheep has suggested that the same SNP in the CYP17 gene is
associated with the cortisol response to stressor (Hough et al., 2013). We therefore used
the physiological ACTH stimulation test to assess the relationship of the CYP17 SNP628
genotype with the cortisol response in non-selected Merino sheep.
Large numbers of DRD2 are located in the prefrontal cortex (Sesack et al., 1995; Muly
et al., 1998) and are involved in the evaluation of stimuli by the brain, a process that
precedes any behavioural response. Previous studies have suggested that
polymorphisms in the gene for DRD2 are linked to dopaminergic activity, the quantity
of brain D2 dopamine receptors, and variation in some personality and behaviour traits
such as extraversion, agreeableness impulsivity/sensation-seeking and aggression
(Noble et al., 1991, 1994a, 1998; Berman and Noble 1997; Blum et al., 1997; Jonsson et
al., 2003; Lee et al., 2007; Ajna et al., 2009; Zai et al., 2012).
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 67
Therefore, in this chapter, we investigated the association between DRD2 SNP939
polymorphism and behavioural response to stressors in non-selected merino sheep. We
used the same two behavioural challenges (Arena test and Isolation box test; Murphy et
al., 1994; Murphy, 1999; Blache and Ferguson, 2005) that measure the reactivities to
novelty and isolation that we have been using for more than 20 years to generate the
UWA Temperament Flock.
5.3 Materials and Methods
This experiment was carried out in accordance with the Australian Code of Practice for
the Care and Use of Animals for Scientific Purposes (7th Edition, 2004) and was
approved by the Animal Ethics Committee of The University of Western Australia
(Approval RA/3/100/1252).
5.3.1 Animals
The study described in Chapter 4 indicated that DRD2 SNP939 and CYP17 SNP628
were the most promising genetic markers for calm and nervous temperaments. Here, we
genotyped 278 14-month-old ewes of unknown temperament from a commercial flock
at UWA Farm Ridgefield (Pingelly, Western Australia). The aim was to identify ewes
that represent each of the four possible combinations of the two SNPs then use those
animals to assess the association between the possible combinations of SNP genotypes
and the behavioural and physiological phenotypes associated with temperament.
5.3.2 Blood sampling for genotypes screening
Whole jugular blood (3 mL) was collected into EDTA-coated tubes (Greiner Bio-One,
Australia) from each of the 278 sheep. After genotyping, we selected four groups of 12
ewes with similar live weight (42.8 ± 2.1 kg) that represented the four combinations of
the two SNPs: Group 1 carried the combination of polymorphisms most associated
with nervous temperament (DRD2 SNP939 C alleles T/C and C/C, plus CYP17
SNP628 A/A); Group 2 carried the DRD2 polymorphism most associated with nervous
temperament (SNP939 C allele T/C and C/C) plus the CYP17 polymorphism that was
most associated with calm temperament (SNP628 G/G); Group 3 carried the DRD2
polymorphism that was most associated with calm temperament (SNP939 T/T) plus the
CYP17 polymorphism that was most associated with nervous temperament (SNP628
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 68
A/A); Group 4 carried the combination of polymorphisms that were most associated
with calm temperament (DRD2 SNP939 T/T plus CYP17 SNP628 G/G).
5.3.3 Phenotyping
The behavioural phenotypic traits of the 48 ewes were measured using the same
isolation box and arena tests that have been used routinely for assessment of sheep
temperament (Murphy et al., 1994; Blache and Ferguson 2005).
Isolation Box Test (IBT)
Each sheep was visually isolated from any other sheep for 1 min in a solid enclosed box
(L = 1.5 m, W = 0.7 m, H = 1.5m). Agitations and high-pitched calls were quantified
using an electronic agitation meter, fixed on the side of the isolation box (Blache and
Ferguson 2005; Brown et al., 2015). The agitation meter had previously been calibrated
for reflection of low, medium and high agitation levels using a ‘mechanical sheep’
(Blache and Ferguson 2005; Brown et al., 2015). The agitation score (arbitrary units)
read from the meter indicated the individual degree of inherent fear or adaptability to
isolation (Blache and Ferguson 2005; Brown et al., 2015). A high score indicating high
behavioural reactivity to isolation is considered to reflect nervous temperament,
whereas a low score is considered to reflect calm temperament.
Open-Field Arena Test
This test measures the locomotor activity and the number of bleats in sheep exposed to a
conflicting situation inherent in the need to approach a human to gain access to
conspecifics. The test pen was 3.3 m wide and 7.0 m long and divided into four sectors
of identical size. Briefly, each sheep entered the test arena from a door situated at the
end opposite to a pen containing a group of sheep that was visible from anywhere in the
arena. A human stood motionless in front of the pen of conspecifics, and the locomotor
activity of the test animal was measured by counting the number of times it entered each
sector (‘crosses’) during a 3 min period. A high level of locomotor activity indicated a
high level of reactivity to the conflicting situation.
Cortisol response to ACTH
The physiological phenotypic trait, adrenal responsiveness, was measured with an
ACTH challenge. All 48 sheep were habituated to the indoor conditions and contact
with people for one week. The 48 sheep were divided into 3 blocks of 16 with equal
numbers of ewes from each of the four genotypes (4 sheep from each genotype). For
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 69
each block, one day before the start of the experiment, the animals were fitted with an
in-dwelling jugular cannula made of plastic tubing (ID 18 G, OD 14 G, Techno-plas,
Western Australia) connected to a three-way tap (BD, Mexico). The 16 sheep received
either saline injection or ACTH injection following a latin square design with each
repeat conducted over two days at 2-day intervals. On each repeat, 2 sheep from each
genotype received a 3 mL intravenous injection of either saline (vehicle control) or
saline containing 0.2 iu ACTH (Polypeptide, Strasbourg, France). Every sheep had been
injected with dexamethasone (0.125 mg/kg i.v., Provet, WA, Australia) to suppress
endogenous ACTH release (Beaven et al., 1964) and the saline or ACTH was injected
90 min later (time = 0). Blood (3 mL) was sampled 90, 60, 30 and 0 min before
injection of saline or ACTH and then every 20 min for 3 h. Samples were immediately
transferred into plastic tubes containing 50 i.u. heparin and polystyrene granules
(Techno-plas, Western Australia), and then centrifuged at 2000 g for 10 min. The plasma
was separated and stored at –20 °C until assay.
Cortisol assay
Plasma concentrations of cortisol were measured in duplicate by radioimmunoassay
using the ImmuchemTM Coated Tube Cortisol 125I RIA Kit (MP Biomedicals, Belgium).
The limit of detection was 1.7 ng/mL. Quality control samples (30.5 ng/mL and 13.5
ng/mL) were used to estimate inter- (5.6 % and 5.0 %) and intra-assay (7.9 % and 8.4 %)
coefficients of variation.
5.4 Statistical analysis
For the behavioural tests, the data were analysed using the Univariate procedure of the
General Linear Model in SPSS (SPSS 16.0 V), with DRD2 genotype as Factor A
(Nervous genotype-A1, Calm genotype-A2) and CYP17 genotype as Factor B (Nervous
genotype-B1, Calm genotype-B2). Prior to analysis, all data were assessed for normality
using the Shapiro-Wilk test and for variance homogeneity using Bartlett’s test. When
the variance was homogenous, the data were compared using Tukey’s post-hoc tests.
When the variance was not homogenous, the data were compared using Tamhane’s tests.
Differences were considered significant at P < 0.05 and very significant at P < 0.01. For
the cortisol response, data were analyzed using ANOVA for repeated measurements of
the General Linear Model in SPSS (SPSS 16.0 V), with time as the repeated measure
and genotype as the factor. The parameters of the cortisol response that were analysed
included the maximum (peak) concentration, amplitude of response, rate of increase,
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 70
delay to peak, and delay in return from peak to baseline concentration (calculated as the
average cortisol concentration for samples taken at –30 min and 0 min before injection
with ACTH or vehicle) and the area under the response curve calculated relative to
baseline (AUCB) as described by Pruessner et al. (2003). The values for cortisol
measured at –90 and –60 min were omitted because, with the low dose of
dexamethasone, the endogenous secretion of ACTH/cortisol was not fully suppressed
until –30 min. Each parameter of the cortisol response was analysed using the
Univariate procedure of the General Linear Model in SPSS (SPSS 16.0 V), with DRD2
genotype as Factor A (Nervous genotype-A1, Calm genotype-A2) and CYP17 genotype
as Factor B (Nervous genotype-B1, Calm genotype-B2) and order of injection (first or
second repeat) or day of ACTH injection as blocking factors. Order and day of ACTH
injection did not have an effect on any parameterof the response to ACTH. Prior to
analysis, all data were assessed for normality using the Shapiro-Wilk test and for
variance homogeneity using Bartlett’s test. The data did not require transformation.
Differences were considered significant at P < 0.05 and very significant at P < 0.01.
5.5 Results
5.5.1 Frequency of each genotype and combination of genotypes in non-selected
sheep
In the non-selected sheep, the highest frequencies were for CYP17 SNP628 A/G and
DRD2 SNP939 T/C, so the frequency of the combination of these two SNPs was
highest among the 6 possible combinations (Table 5.1). For CYP17 SNP628, the A/A
genotype was the least frequent. For DRD2 SNP939, the T/C and C/C genotypes were
both associated with nervous temperament so they were combined, and the combination
was more frequent than the calm T/T genotype. Therefore, when the two genes were
considered in combination, the frequency of the combination SNP628 A/A and SNP939
T/T was lowest among the 6 combinations (Table 5.1). For the combinations of DRD2
plus CYP17 genotypes, the frequencies were low for both the calm and the nervous
phenotypes (Table 5.1).
Table 5.1 Frequencies of individual and combinations of genotypes in 278 non-selected sheep
for genes that control glucocorticoid synthesis (CYP17), dopamine receptor 2 (DRD2) and
monoamine oxidase A (MAOA).
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 71
Gene SNP Genotype and associated phenotype
DRD2 SNP939 T/T
(calm)
T/C
(nervous)
C/C
(nervous)
N 174 91 13
% 62.6 32.7 4.7
CYP17 SNP628 A/A
(nervous)
G/G
(calm)
A/G
(un.)
N 100 37 141
% 36.0 13.3 50.7
Combined
DRD2 + SNP939 T/C + C/C
(nervous)
T/C + C/C
(nervous)
T/C + C/C
(nervous)
T/T
(calm)
T/T
(calm)
T/T
(calm)
CYP17 SNP628 A/A
(nervous)
G/G
(calm)
A/G
(un.)
A/A
(nervous)
G/G
(calm)
A/G
(un.)
N 40 12 52 60 25 89
% 14.4 4.3 18.7 21.6 9.0 32.0
5.5.2 Behavioural phenotype
There were no interactions between the DRD2 and CYP17 genotypes for any of the
variables measured. There was a main effect of the DRD2 SNP939 genotype, with the
nervous genotype (T/C + C/C) showing a higher isolation box score and more crosses
than the calm genotype (T/T), although the number of bleats was similar (Table 5.2).
There was no effect of CYP17 SNP628 genotype on IBT scores and crosses of the
behavioural phenotypes (Table 5.2), but there was a tendency for the number of bleats to
be affected by CYP17 SNP628 genotype (P = 0.077, Table 5.2).
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 72
Table 5.2 The effect of genotypes for glucocorticoid synthesis (CYP17) and dopamine receptor
2 (DRD2) on behaviour (IBT score, Bleats, Crosses) in sheep.
Item IBT score Bleats Crosses
DRD2 SNP939 T/C+C/C
CYP17 SNP628 A/A 101.1 ± 6.26 5.2 ± 0.92 8.4 ± 0.66
CYP17 SNP628 G/G 97.2 ± 8.34 1.4 ± 0.51 7.0 ± 1.22
DRD2 SNP939 T/T
CYP17 SNP628 A/A 46.5 ± 4.54 4.1 ± 0.79 5.9 ± 0.55
CYP17 SNP628 G/G 35.3 ± 3.77 1.6 ± 0.47 5.9 ± 0.52
DRD2 SNP939 T/C+C/C 100.2 ± 5.10 A 4.2 ± 0.74 8.1 ± 0.58 a
DRD2 SNP939 T/T 43.3 ± 3.44 B 3.3 ± 0.37 5.9 ± 0.41 b
CYP17 SNP628 A/A 67.2 ± 4.57 4.5 ± 0.60 6.8 ± 0.44
CYP17 SNP628 G/G 55.9 ± 6.15 1.5 ± 0.35 6.3 ± 0.53
P value
DRD2 SNP939 0.001 0.915 0.024
CYP17 SNP628 0.263 0.077 0.377
DRD2 SNP939×CYP17 SNP628 0.592 0.498 0.381
Different uppercase superscripts in the same column indicate difference at P < 0.01.
Different lowercase superscripts in the same column indicate difference at P < 0.05.
5.5.3 Cortisol response
There was no change in plasma concentrations of cortisol following the injection of the
saline vehicle (data not shown). There was no genotype×time interaction (DRD2
SNP939 genotype×time: P = 0.461; CYP17 SNP628 genotype×time: P = 0.112). There
was a main genotype effect of CYP17 SNP628 (P = 0.039), but no genotype effect of
DRD2 SNP939 (P = 0.377). For all parameters of cortisol response, there was no effect
of any interaction between DRD2 SNP939 and CYP17 SNP628 genotypes (Table 5.3, P >
0.05), and no main effect of DRD2 SNP939 genotype for any parameter (Table 5.3, P >
0.05), but there was a main effect of CYP17 SNP628 genotype on the maximum value
(P = 0.040), amplitude (P = 0.048) and AUCB (P = 0.041) (Table 5.3), with higher
values observed in the CYP17 SNP628 A/A nervous genotype (Figure 5.1 a,b) than in
the CYP17 SNP628 G/G calm genotype (Figure 5.1 c,d). There was no effect of CYP17
SNP628 genotype on the other parameters (Table 5.3, P > 0.05).
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 73
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 74
Figure 5.1 Plasma concentrations of cortisol (mean ± s.e.m) before and after intravenous
injection of 0.2 iu ACTH1–24 in Australian Merino sheep carrying: a) both genotypes associated
with nervousness (CYP17 SNP628 A/A and DRD2 SNP939 C allele); b) the CYP17 SNP628
genotype associated with nervousness (A/A) and the DRD2 SNP939 genotype associated with
calmness (T/T); c) the CYP17 SNP628 genotype associated with calmness (G/G) and the DRD2
SNP939 genotype associated with nervousness (C allele); d) both genotypes associated with
calmness (CYP17 SNP628 G/G and DRD2 SNP939 T/T). The animals were injected with
dexamethasone (0.125 mg/kg) 90 min before the injection of ACTH to suppress the endogenous
secretion of cortisol. The dotted line represents the baseline of cortisol concentrations (see
Materials and Methods).
5.6 Discussion
The DRD2 SNP939 was specifically associated with behavioural phenotype, as
measured by tests of behavioural reactivity, and the CYP17 SNP628 was specifically
associated with physiological phenotype, as measured by the cortisol response to ACTH,
thus verifying the association of these two SNPs with temperament in sheep.
In sheep genotyped for CYP17, the amplitude of the response to ACTH was similar to
that observed in sheep responding to hypoglycaemic stress (Graybeal and Fang 1985),
suggesting that the dose of ACTH we used was within the physiologically-relevant
range. The cortisol response to ACTH was linked to polymorphism CYP17 SNP628
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 75
(A/A and G/G). We did not challenge the sheep from the calm and the nervous lines in
the UWA Temperament Flock with ACTH, but these two lines do present different
frequencies for SNP628 A/A and G/G so their responses to ACTH would probably
differ in the same way. Indeed, the sheep of the nervous line had a greater cortisol
response with higher maximum and longer duration to layered stressors (eg, isolation,
human presence, restraint) than the sheep of the calm line (Hawken et al., 2013). The
same polymorphism, SNP628, has been shown to affect the cortisol response to stress in
South African Merino sheep (Hough et al., 2013). In Angora goats, a different type of
CYP17 mutation, that nevertheless causes amino acid substitution, is also associated
with variation in the cortisol response to stress (Engelbrecht et al., 2000; Storbeck et al.,
2007). Despite differences in the location and the nature of the polymorphisms among
our sheep, South African sheep, and goats, the consistent observation is that CYP17
polymorphisms can affect on adrenal responsiveness to exposure to stressors.
In our study, the plasma cortisol concentration of all 4 groups of sheep reached the peak
very quickly (20 min) after injection of a low dose of ACTH (3 µg/sheep), then
decreased rapidly after 20 min, and had returned to baseline values by about 2 h after
ACTH injection. However, in other studies with sheep, there was a longer duration in
the cortisol response to ACTH and a later peak value (60 min after ACTH) before the
rapid decrease began (Engelbrecht et al., 2000; van Lier et al., 2014). This difference
between studies can be explained by the dose-dependency of the cortisol response to
ACTH stimulation (Daidoh et al., 1995). In the other studies, the dose was 10 µg/kg or
500 µg per sheep (Engelbrecht et al., 2000; van Lier et al., 2014), both much greater
than the dose (around 3 µg/sheep) that we used. It was proposed long ago that the dose
of exogenous ACTH required to obtain plasma cortisol levels similar to those recorded
after induction of physiological stress (insulin) was 0.2 ug/kg (Graybeal and Fang,
1985), or about 10 µg/sheep. Several investigators have since confirmed the usefulness
of low doses of ACTH for estimation of adrenocortical function, and they have defined
the lowest dose of ACTH capable of eliciting a maximum response as 500 ng/1.73 m2
(Crowley et al., 1991; 1993) or 1 µg per sheep (Dickstein et al., 1991). In fact, all of
these doses are within the physiological range. The low dose of ACTH (0.1-5 µg) and
the standard dose of 250 µg have been compared and it was found that the low dose of
ACTH elicited very rapid cortisol peak level at 20 min after ACTH administration,
consistent with our observartions, whereas the standard dose did not elicit the cortisol
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 76
peak before 60 min. Similar results have been obtained in studies on humans (Park et al.,
1999), calves (Safwate et al., 1982; Veissier and Le Neindre 1988; Lay et al., 1996;
Negra et al., 2004), pigs (Parrott et al., 1989) and dogs (Vincent and Michell 1992). In
general, the cortisol peak is earlier with lower the doses of ACTH than with higher
doses, for reasons that are not clear. In summary, the dose of ACTH that we used seems
to be the most appropriate for testing adrenal responsiveness.
It is important to note that, although our results suggest that SNP628 can explain
differences between the temperament lines in cortisol secretion, other components of the
HPA axis, such as ACTH production, adrenal responsiveness to ACTH, and
steroidogenic enzymes other than CYP17, could also play a role (Vander Walt et al.,
2009; Hough et al., 2015). For example, CYP17 17, 20-lyase activity is strongly
affected by cytochrome B5 and this interaction contributes to the production of cortisol
in South African sheep (Hough et al., 2013). These issues require further investigation.
In contrast to the link between CYP17 polymorphism and adrenal responsiveness, IBT
score and number of crosses were similar between homozygous CYP17 genotypes
(calm and nervous). Interestingly, there was a tendency for the number of bleats to be
higher in the sheep carrying the CYP17 A/A genotype (nervous) than in the sheep
carrying the CYP17 G/G genotype (calm). Similarly, South African Merino sheep
carrying the CYP17 A/G genotype exhibited a greater number of bleats and lines
crossed in the arena test than the sheep carrying the A/A genotype (Hough 2012). In our
study, the sheep were visually isolated from their conspecifics but were potentially able
to hear them from a distance, so the test conditions might not have allowed us to detect
a difference in bleating between the two homozygous CYP17 genotypes. In addition, we
only used female sheep, whereas the South African study used only rams. Gender could
affect the relationship between CYP17 SNP628 genotypes and behavioural reactivity, in
the same way that it affects the relationship between MAOA polymorphism and
behavioural reactivity (Murphy et al., 1976; Deckert et al., 1999). Finally, our Merino
sheep could differ from South African Merino sheep, in which the CYP17 genotype is
associated with both behavioural and physiological reactivity, but one homozygous
genotype appears to be absent. At this stage, therefore, we are assuming that the CYP17
SNP628 polymorphism affects the adrenocortical cortisol response to ACTH whereas
the DRD2 polymorphism independently affects behavioural response (agitation).
Chapter 5 Association of the 2 SNPs with the two phenotypes of temperament 77
5.7 Conclusion
DRD2 SNP939 genotypes were specifically associated with behavioural phenotype as
measured by tests of behavioural reactivity, and CYP17 SNP628 genotypes were
specifically associated with the physiological phenotype as measured by cortisol
response to ACTH. These observations clearly validated the statistics-based results
presented in Chapter 4 and add great support to the conclusion that DRD2 SNP939 C
allele combined with CYP17 SNP628 A/A genotype could be used as a genetic marker
for nervous temperament, whereas the combination of DRD2 SNP939 T/T plus CYP17
SNP628 G/G genotypes could be used as a genetic marker for calm temperament in
Merino sheep. The heritability of these genotypes as well as their impact on other
aspects of temperament (cognition) will be explored in next chapters.
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 78
Chapter 6
Heritability of behavioural reactivity to isolation based on DRD2
SNP939 and CYP17 SNP628 genotypes associated with sheep
temperament phenotype
Page
6.1 Abstract 79
6.2 Introduction 80
6.3 Materials and Methods 81
6.3.1 Animals 81
6.3.2 Parentage assignment 81
6.3.3 Genomic DNA isolation 81
6.3.4 Genotyping 82
6.4 Data analysis 83
6.5 Results 84
6.5.1 Distribution of the 2 SNPs genotypes in the 84
temperament lines
6.5.2 Effects of farms and genotypes on behavioural reactivity 86
(isolation box test) in the F0 and F1
6.5.3 Heritability estimates 86
6.6 Discussion 88
6.7 Conclusion 90
Chapter 6 Heritability estimate based on the 2 SNPs genotype 79 6.1 Abstract
The estimate of heritability of temperament in sheep, based on phenotypic
measurements, is known to be moderate to high, but we do not have an estimate of
heritability based on genotypic measurement. In a previous Chapter, we have described
2 SNP genotypes (DRD2 SNP939 and CYP17 SNP628) that are associated with
temperament. Therefore, in the present study of a small number of animals, we used
these two SNPs genotypes to make a preliminary estimate of heritability for
temperament as measured by reactivity to isolation (IBT). We studied 116 parents and
offspring from 3 farms, including 56 phenotypic nervous and 60 phenotypic calm sheep,
and 7 phenotypic nervous and 6 phenotypic calm sires. The heritability of reactivity to
social isolation, measured by the agitation score (IBT), was 0.45 based on the
phenotypic selection, 0.50-0.60 for sheep carrying the DRD2 SNP939 genotypes,
0.36-0.48 for sheep carrying the CYP17 SNP628 genotypes, and 0.62-0.76 for sheep
carrying the combination of the two SNP genotypes. These results suggest that the
heritability of reactivity to social isolation could be improved by selection based on the
2 SNP genotypes, but validation using a larger number of animals is needed.
Keywords: Sheep temperament; Phenotype; Genotype; Heritability; CYP17 SNP628;
DRD2 SNP939
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 80
6.2 Introduction
Animal temperament can be defined as the variability of emotional or behavioural
activity in response to a stimulus (Blache and Bickell 2010, 2011; Dodd et al, 2012). In
livestock, behavioural activity is related to the efficiency of routine farm practices,
animal welfare and productivity (Turner et al., 2011). Temperament is heritable (Burrow
et al., 1988; Krueger and Johnson 2008; Quinn et al., 2009; Bickell et al., 2009b; Turner
et al., 2011) and, in sheep, a cross-fostering experiment has suggested that temperament
is mainly determined by genetic inheritance (Bickell et al., 2009b). Similar conclusions
have been drawn for cattle using similar approaches (Phocas et al., 2006). However, the
current methods used to select for temperament are based behavioural tests, such as the
isolation box test or flight speed, that measure phenotypic traits. They are not always
repeatable and they are very time-consuming (Murphy et al., 1994; Blache and
Ferguson 2005; Dodd et al., 2012, 2014) so the challenge is to find an easier method for
assessing temperament that can be used as a selection tool (Turner et al., 2011).
The estimate of heritability of temperament, based on phenotypic measurement (the
reactivity to isolation, IBT), is moderate to high in sheep (h2 = 0.41, Blache and
Ferguson 2005; h2 = 0.48, Boissy et al., 2005; h2 = 0.31, Zambra et al., 2015; h2 =
0.30-0.36, Brown et al., 2015). Recently, we have shown that a single nucleotide
polymorphism (SNP) located at nucleotide position 939 of DRD2 (DRD2 SNP939) and
a single nucleotide polymorphism located at nucleotide position 628 of CYP17 (CYP17
SNP628) are associated with the behavioural response and the cortisol response, and
can define temperament in sheep (chapter 4 and 5). However, we still do not have an
estimate of heritability of temperament based on genotypic measurements, or a
comparison of the heritabilities from between phenotypic and genotypic measurements.
Here we describe a preliminary study, using the two SNPs genotypes associated with
temperament (DRD2 SNP939 and CYP17 SNP628), with a small number of animals
from two generations of sheep, in which we have calculated the heritability of reactivity
to isolation (IBT) based on these two SNPs genotypes and compared the outcome with
the estimate of phenotypic heritability. To estimate the heritability, we used two
common methods: the parent-offspring regression and the paternal half-sib correlation
(Smith and Kinman 1965; Van Vleck and Bradford 1965; Dickerson 1969).
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 81
6.3 Materials and Methods
6.3.1 Animals
Samples used in the present study were obtained from animals generated in another
project (Blache and Ferguson 2009). Ewes and lambs were selected on the basis of the
accuracy of their parentage. Briefly, the F0 was generated from a flock of 800-1000
ewes on 3 farms (Billandri, Merinotech and Grindon) located in Western Australia and
the animals were tested for temperament using the isolation box test (IBT); the 200-300
ewes with the lowest and highest IBT scores were selected as the good and poor
temperament groups, respectively. Blood (3 mL) was sampled from the ewes using
EDTA vacutainers (BD Diagnostics, Franklin Lakes, NJ, USA) and later analysed for
DNA to assign the parentage of their lambs. A total of 1609 ewes were subsequently
artificially inseminated to selected sires. An associative mating program was used where
802 ewes from the good temperament group were mated to one of 6 sires with low
estimated breeding values (Mean EBV (± SD): 40.3 ± 14.18) for IBT agitation score (ie.
good temperament). Similarly, 7 sires with high EBVs for the trait (EBV: –34.3 ± 5.74;
ie. poor temperament) were mated to the 807 poor temperament ewes. The behavioural
reactivity of the subsequent lambs to social isolation was measured using the Isolation
Box Test, within two weeks of weaning (14 weeks of age; Murphy et al., 1994; Blache
and Ferguson 2005). Blood was sampled after the behavioural test, as described above.
Live weight was similar for the two temperament lines in both F0 (50.7 kg ± 5.9 kg) and
F1 (18.4 ± 2.0 kg).
6.3.2 Parentage assignment
DNA was extracted using a DNeasy Blood and Tissue Kit (Qiagen, Germany) according
to the procedures of the manufacturer. A sample of blood from each ewe and lamb was
used for parentage assignment using the Shepherd® DNA-based Parentage System from
Catapult Genetics (Dunedin, New Zealand). Only a subset of animals was used in this
project because blood samples were no longer available for all animals at the time of the
study. In total, 116 parents (F0) and offspring (F1) were identified including 56
phenotypic nervous and 60 phenotypic calm sheep.
6.3.3 Genomic DNA isolation
Genomic DNA was isolated from the whole blood samples using the DNeasy Blood and
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 82
Tissue Kit (Qiagen, Germany) according to the instructions provided by the
manufacturer. DNA concentration was determined by visualization after gel
electrophoresis.
6.3.4 Genotyping
DRD2 SNP939 and CYP17 SNP628 genotypes were genotyped in F0 and F1 using the
method described in Chapter 4, using Taqman MGB probe assays (Table 6.1). All of the
study sheep were genotyped using a Vii7TM Real-Time instrument (Applied Biosystems,
California, USA). Amplification reactions (10 µL) were performed using 5 µL TaqMan®
Genotyping Master Mix (2×) (Applied Biosystems, California, USA), 0.5 µL custom
TaqMan® SNP genotyping Assay (20×) containing two primers and two labelled probes
(Applied Biosystems, California, USA) and 20 ng genomic DNA. The thermal cycle
included a pre-read stage at 60 °C for 30 s, a hold stage for denaturation at 95°C for 10
min to activate the AmpliTaq Gold®DNA polymerase, followed by 40 cycles of 95 °C
for 15 s, 60 °C for 60 s (with the additional step of cooling to 52 °C for 30 s prior to
60 °C extension for CYP17 SNP628 due to the lower annealing temperature of the
primers) and a post-read stage at 60 °C for 30 s. The transition rate between all steps was
1.6 °C/s. The data were collected using the Allelic Discrimination Plot of Vii7TM
software (Applied Biosystems, California, USA). A no-template control (negative
control) was also included in each assay.
Table 6.1 Nucleotide sequences of primers and probes used in real-time PCR genotyping. Note:
The primers and probes for CYP17 SNP628 were from Hough (2012).
Gene SNP Oligonucleotide sequence (5'- to 3'-)
CYP17 SNP628 forward primer
reverse primer
sensor probe
anchor probe
CGGTCATGATCGCCATCGT
GAGCATCGGGCAGGAGAT
(VIC®-labelled): TGAAGGACAGGACCCAG
FAMTM-labelled):AAGGACAGAACCCAG
DRD2 SNP939 forward primer
reverse primer
sensor probe
anchor probe
ACCCTCCCCGACCCA
GGCATGCCCGTTCTTCTCT
(VIC®-labelled): TCCCACCATGGCCTC
(FAMTM-labelled): CCACCACGGCCTC
Accuracy of real-time genotyping results was confirmed by direct sequence analysis
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 83
(AGRF). Sequencing results were analyzed with BioEdit Sequence Alignment Editor
software (version 7.0.5.2©1997-2007, T. Hall).
6.4 Data analysis
Frequency distribution of the 2 SNP genotypes in the temperament lines
The frequency distributions of each genotype were compared for the Nervous (n = 56)
and Calm lines (n = 60), in both the F0 and F1 generations, using Chi-square test. The
reliability of the data was tested using the Hardy-Weinberg equilibrium.
Effects of farm and genotype on temperament phenotype
The associations of farm of origin and genotype with temperament (IBT scores) were
tested in both F0 and F1. Our previous study (Chapter 5) has shown a main effect of the
DRD2 SNP939 genotype but no effect of CYP17 SNP628 genotype on IBT score. We
therefore only tested the association of temperament (IBT) with DRD2 SNP939
genotype and farm of origin. The data were analysed using the Univariate procedure
from the General Linear Model in SPSS (SPSS 16.0 V), with DRD2 genotype as a
factor (Calm genotype, Nervous genotype) and farm of origin as a factor (Billandri,
Merinotech, Grindon). Prior to analysis, all data were assessed for normality using the
Shapiro-Wilk test and for variance homogeneity using Bartlett’s test. The data in F0 and
F1 did not require transformation. Differences were considered significant at P < 0.05
and very significant at P < 0.01.
Heritability estimates of the two SNP genotypes for offspring temperament
The heritability of reactivity to isolation, as measured by isolation box test (IBT) score
(temperament phenotype), was analyzed according to the selection lines or on the basis
of the individual or combined genotypes for the DRD2 and CYP17 SNPs.
Parent-offspring regression and paternal half-sib correction were used to estimate the
heritability in the narrow sense.
Parent-offspring regression
: parent-offspring regression
O: values of offspring
: mid-parent value
h2 = = 2bOP (Dam-offspring regression)
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 84
Paternal half-sib correction
C=(ΣΣx)2/N
h2=4t
t: paternal half-sib correction
MSb: inter-group mean square
MSw: intra-group mean square
k0: weighted average
n：number of groups
k：number of offspring in each group i：1,2,…n
N: total number of offspring C: corrected value
df = degree of freedom
dftotal = N-1
df inter-group = n-1
df intra-group = dftotal - df inter-group = N-n
6.5 Results
6.5.1 Distribution of the two SNPs genotypes in the temperament lines
The distributions of sheep carrying each genotype in both the F0 and F1 generations
were similar for all 3 farms, so we compared genotype frequencies for the two
temperament lines across farms (Tables 6.2 and 6.3). In the F0, except for DRD2
SNP939 C/C for which the frequency was significantly higher in nervous group than
that in calm group, the frequencies of the other genotypes were similar between two
temperament lines (Tables 6.2 and 6.3). In the F1, the DRD2 SNP939 T/T genotype
wb
wb
MSkMSMSMSt
)1( 0
)(
11 2
0
i
ii k
kk
nk
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 85
frequency in the calm line was double that in nervous line, and the T/C and C/C
genotype frequencies in the nervous line were both significantly higher than that in calm
line (Tables 6.2 and 6.3). The combined percentage of T/C and C/C genotypes was
around 70% (57.1%+14.3%) in nervous group. The CYP17 SNP628 A/A genotype
frequency in the nervous line was double that in calm line (Tables 6.2 and 6.3).
Table 6.2 The distribution of sheep with different genotypes for DRD2 SNP939 and CYP17
SNP628 in F0 calm and nervous phenotype groups from 3 different farms. Different lowercase
superscripts in the same line indicate difference at P < 0.05.
Nervous (n=56)
Calm (n=60)
Gene SNP Genotype Overall #1Farm #2Farm #3Farm
Overall #1Farm #2Farm #3Farm
N % N N N
N % N N N
DRD2 SNP939
T/T 19 33.93a 5 8 6 28 46.67a 7 13 8
T/C 23 41.07a 6 7 10 29 48.33a 13 8 8
C/C 14 25.00a 6 5 3
3 5.00b 0 1 2
CYD17 SNP628
A/A 19 33.93a 6 6 7
14 23.33a 5 6 3
A/G 29 51.79a 9 11 9
34 56.67a 13 9 12
G/G 8 14.29a 3 3 2
12 20.00a 5 4 3
Table 6.3 The distribution of sheep with different genotypes for DRD2 SNP939 and CYP17
SNP628 in F1 calm and nervous phenotype groups from 3 different farms. Different lowercase
superscripts in the same line indicate difference at P<0.05.
Nervous (n=56)
Calm (n=60)
Gene SNP Genotype Overall #1Farm #2Farm #3Farm
Overall #1Farm #2Farm #3Farm
N % N N N
N % N N N
DRD2 SNP939
T/T 16 28.57a 6 5 5 36 60.00b 14 13 9
T/C 32 57.14a 10 12 10 23 38.33b 9 7 7
C/C 8 14.29a 2 3 3
1 1.67b 0 1 0
CYP17 SNP628
A/A 20 35.71a 5 9 6
11 18.33b 3 4 4
A/G 30 53.57a 12 8 10
34 56.67a 13 12 9
G/G 6 10.71a 1 3 2
15 25.00b 7 5 3
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 86
6.5.2 Effects of farm and genotype on behavioural reactivity (isolation box test) in
the F0 and F1 generations
There were no interactions between the DRD2 SNP939 genotype and farm of origin for
the isolation box test result (IBT) in either the F0 or F1 generation (P > 0.05; Table 6.4).
There was also no effect of farm of origin on IBT score in either F0 or F1 (P > 0.05;
Table 6.4). There was no main effect of DRD2 genotype in the F0 generation (P > 0.05;
Table 6.4) but there was a main effect of the DRD2 SNP939 genotype in the F1, with
higher isolation box scores in the sheep carrying nervous genotype (T/C + C/C) than the
sheep carrying calm genotype (T/T) (P < 0.05; Table 6.4).
Table 6.4 Effect of farm of origin and genotype on reactivity to isolation (IBT, mean ± s.e.) in
two generations of sheep (n = 116).
Item F0 F1
DRD2 SNP939 genotype
Calm 26.7 ± 3.6 22.6 ± 2.7 a
Nervous 32.1 ± 3.1 60.1 ± 3.3 b
Farm
Billandri 28.9 ± 3.2 35.5 ± 4.1
Merinotech
Grindon
28.7 ± 3.3
30.6 ± 3.0
41.6 ± 4.1
47.0 ± 4.6
P value
Genotype 0.263 0.010
Farm 0.944 0.175
Genotype × Farm 0.227 0.144
Different lowercase superscripts in the same column indicate difference at P < 0.05.
6.5.3 Heritability estimates
The heritability of reactivity to social isolation measured by the agitation score (IBT)
based on the phenotypic selection was 0.45. The heritability of reactivity to social
isolation was 0.50-0.60 for sheep carrying the DRD2 SNP939 genotype, 0.36-0.48 for
sheep carrying the CYP17 SNP628 genotype, and 0.62-0.76 for sheep carrying the
combination of the two SNPs (Table 6.5). Because all the sires were carrying the
CYP17 A/G genotype that is not associated with the temperament (Chapter 4), we only
estimated the heritability of DRD2 SNP939 genotypes from a sire perspective (Table
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 87
6.6), and found that it was similar to estimates from a dam perspective (Table 6.5).
Table 6.5 Heritability, estimated by Dam-Offspring Regression, of the reactivity to social
isolation measured by the agitation score (IBT) based on the DRD2 SNP939 and CYP17
SNP628 genotypes.
Genotypes
Gene F0 (Dam) F1 N ΣOP ΣO ΣP ΣP2 h2
DRD2 T/T (calm) T/T (calm) 24 23396 785 623 26234 0.60
SNP939 C/T or C/C
(nervous)
C/T or C/C
(nervous)
41 117403 2119 2177 134781 0.50
T/T(calm) C/T (nervous) 12 23138 593 427 31407 0.24
C/T (nervous) T/T (calm) 11 12493 269 485 32263 0.12
CYP17
SNP628
A/A (nervous) A/A (nervous) 17 62092 1253 797 55559 0.36
G/G (calm) G/G (calm) 8 1128 94 113 2439 0.48
SNP939
+
SNP628
C/T or C/C
(nervous) +
A/A (nervous)
C/T or C/C
(nervous) +
A/A (nervous)
17 90430 1068 1278 122548 0.76
T/T (calm) +
G/G (calm)
T/T (calm) +
G/G (calm)
10
6355 239 215 8585 0.62
C/T (nervous) +
A/A (nervous)
T/T (calm) +
A/G (un.)
6 4787 93 294 19904 0.08
T/T (calm) +
G/G (calm)
C/T (nervous)
+ A/G (un.)
1 - - - - -
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 88
Table 6.6 Heritability, estimated by Paternal half-sib correction, of the reactivity to social
isolation measured by the agitation score (IBT) based on the DRD2 SNP939 genotype.
Genotypes
Sires F1 n N ΣΣx ΣΣx2 Σ (Σx)2/ki h2
T/T(calm) T/T (calm) 5 33 676 20640 15462 0.60
C/T or C/C (nervous) C/T or C/C (nervous) 6 45 2596 163876 150508 0.56
T/T (calm) C/T (nervous) 5 14 570 40562 29640 0.40
C/T (nervous) T/T (calm) 6 19 597 21229 19464 0.36
6.6 Discussion
This study supports our general hypothesis that the phenotypic heritability of the
reactivity to social isolation, as measured by the agitation score (IBT), can be improved
by genetic selection based on the two SNP genotypes associated with temperament.
There was no effect of farm of origin on temperament (IBT) in either the F0 or F1
generations, an observation that is consistent with previous results showing little
influence of early management in extensive or semi-intensive farm systems on the
behaviours of lambs in the arena test (Goddard et al., 2000). In addition, environmental
influences during early rearing have been showed to have little effect on emotional
reactivity as measured by the isolation box test and arena test (Boissy et al., 2005).
However, early environmental conditions, particularly routine farm management
procedures such as shearing, vaccination, herding and handling, are known to be
stressful to gregarious livestock (Boissy and Neindre 1990; Bouissou et al., 2001; Fisher
and Matthews 2001) and can elicit fear and anxiety (Hargreaves and Hutson 1990a,
1990b; Wohlt et al., 1994; Boissy et al., 2005) during the procedures. They can also
influence the emotional reactivities or behaviours of sheep to other stressors
(Hargreaves and Hutson 1990b; Mateo et al., 1991; Markowitz et al., 1998). The
absence of a farm effect might reflect the fact that the livestock management systems
were essentially similar among the three farms. Moreover, previous studies have shown
that temperament is driven by genetic inheritance rather than by the environmental
influence in sheep (Bickell et al., 2009b) and also cattle (Phocas et al., 2006).
The estimated heritability of the reactivity to social isolation measured by the agitation
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 89
score (IBT) based on the phenotypical selection (h2 = 0.45) was similar to that found
previously in animals that had also been selected for phenotype divergence in a
temperament trait in sheep (h2 = 0.41, Blache and Ferguson 2005), dairy cattle
(h2 = 0.40: O’Blesness et al., 1960, 0.45: Sato 1981, 0.53: Dickson et al., 1970), and
beef cattle (0.40: Shrode and Hammack 1971, 0.44-0.48: Stricklin et al., 1980).
However, other studies have reported lower values for sheep (h2 = 0.16: Hocking
Edwards et al., 2011, 0.20: Plush et al., 2011; Dodd et al., 2014) and cattle (0.22: Morris
et al., 1994; Neindre et al., 1995, 0.30-0.35: Burrow and Corbet 2000), mostly based on
unselected groups of animals.
This variation among studies in the heritability estimates could be explained by
differences in experimental design, behavioural tests and scoring systems, previous
experience of the animals, and the breeds used (Broucek et al., 2008). For example, in
the study by Boissy et al. (2005), the heritability estimate for the number of
vocalizations by sheep in response to isolation was 0.48 – a value close to our result
(h2 = 0.45) which is based on an agitation score that also includes vocalizations in
response to isolation. Some of the variation in the estimates of heritability could be
explained by the impact of environmental factors on the behavioural responses of the
animals. For example, the heritability of fear of humans was estimated to be 0.35 if the
fear of humans was measured by the flight speed upon exit from a handling chute,
whereas the heritability was 0.30 when fear of human was measured by the agitation
score in the chute (Burrow and Corbet 2000). Finally, the estimate heritability can be
affected by the age of the animal – in cattle, for example, the heritability of flight speed
in response to the fear of humans was 0.54 at 6 months and only 0.26 at 18 months of
age (Burrow et al., 1988).
To our knowledge, there have been no estimates of the heritability of temperament traits
based on SNP genotype. The present study suggests that genotypic selection can further
improve the heritability of this trait (agitation score, response to isolation). Indeed
selection based on the combination of DRD2 SNP939 and CYP17 SNP628 genotypes
was associated with the highest heritability. This outcome is not surprising because the
results verified yet again that DRD2 SNP939 and CYP17 SNP628 genotypes are
associated with the two temperaments. However, the heritability estimates in this study
were calculated on a small number of animals, so a larger study will be needed for full
Chapter 6 Heritability of behavioural reactivity to isolation based on the 2 SNPs 90
validation.
6.7 Conclusion
Compared to the phenotypic method for selection for temperament in sheep, the
genotypic method based on CYP17 SNP628 and DRD2 SNP939 appears to improve the
estimates of heritability. Our preliminary results support the conclusion that CYP17
SNP628 and DRD2 SNP939 could be used as the potential genetic markers for sheep
temperament selection.
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 91
Chapter 7
Cognitive learning ability in Merino sheep with different DRD2
SNP939 genotypes
Page
7.1 Abstract 92
7.2 Introduction 93
7.3 Materials and Methods 94
7.3.1 Animals 94
7.3.2 Color visual discrimination 95
7.3.3 Spatial discrimination 96
7.4 Data analysis 97
7.5 Results 98
7.5.1 Color visual discrimination 98
7.5.2 Spatial discrimination 100
7.5.3 Behavioural reactivity during the tests 103
7.6 Discussion 103
7.7 Conclusion 109
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 92
7.1 Abstract
Polymorphism in the D2 dopamine receptor (DRD2) has been implicated in variability
in cognitive function, such as behavioural flexibility and decision-making in humans.
Similarly, cognition is known to vary with emotional reactivity (temperament).
However, the effect of the interaction between emotional reactivity and DRD2
polymorphism on cognitive function is poorly understood. Using a sheep model in
which animals of ‘calm’ and ‘nervous’ temperament carry two different DRD2 SNP939
polymorphisms, we assessed cognitive capacity by simple visual discrimination, simple
spatial discrimination, and reversal learning of spatial discrimination. Neither genotype
was able to learn color visual discrimination within 48 discriminations, but both were
able to learn left-right spatial discrimination within 10 discriminations. Sheep with
DRD2 SNP939 T/T (‘calm’) genotype performed better in reverse spatial discrimination,
taking less time to learn the reversal task and committing significantly fewer errors, than
the sheep with DRD2 SNP939 C/C+C/T (‘nervous’) genotypes. The results suggest that,
in sheep, DRD2 SNP939 is involved in the behavioural flexibility that underpins spatial
learning, but is not involved in visual learning.
Key words: Merino sheep; DRD2 polymorphism; cognitive learning; DRD2 SNP939
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 93
7.2 Introduction
In a challenging and continuously changing environment, a vital determinant of survival
is the ability to learn and memorize associations between a stimuli and actions, to make
appropriate decisions, and to adapt with appropriate behaviours (Provenza 1995;
Shettleworth 2001). The mechanisms that underpin these cognitive functions are
complex but there is increasing knowledge of the location of the brain regions and
neuronal pathways involved (Keil and Wilson 2000). The prefrontal lobe and striatum
are mainly responsible for attention and for directing the behaviour toward a given goal
in a given situation (Posner and Petersen 1990), so dys-regulation of these brain regions
is associated with cognitive disorders (Rubia et al., 1999; Castellanos and Tannock 2002;
Johansen et al., 2002). With respect to the neurotransmitters involved, dopamine is
considered important because it exerts a strong regulatory effect on neuronal activity in
the prefrontal cortex and striatum (Missale et al., 1998; Haber et al., 2000; Schultz
2002). Moreover, in humans, monkeys and rats, midbrain dopaminergic neurons that
project to the prefrontal cortex and striatum have been implicated in a variety of
cognitive and executive functions, including working memory (Cai and Arnsten 1997;
Floresco and Phillips 2001), behavioural flexibility (reversal learning and shifting of
attentional set; Owen et al., 1991, 1993; Birrell and Brown 2000) and decision-making
(Bechara et al., 2001; Winstanley et al., 2006). In the prefrontal cortex and striatum,
dopamine acts via several subtypes of receptor, with each subtype suggested to play a
specific role in various aspects of cognitive learning ability (Floresco and Magyar 2006).
In particular, subtype DRD2 and its polymorphisms have been linked to variability
amongst individual human and mice in decision-making, attention shifting, cognitive
learning and reversal learning (Smith et al., 1999; Kruzich and Grandy 2004; Lee et al.,
2007; Jocham et al., 2009).
Cognition is also thought to depend on emotional reactivity (or ‘temperament’; Mendl
1999; Erhard et al., 2004; Lansade and Simon 2010; Butts et al., 2013), with lower
levels of emotional activity associated with better performance in cognitive tasks such
as spatial learning, discrimination and recognition. However, the role of the dopamine
pathways in this interaction has never been tested. In the present study, we have
addressed the problem with the sheep model because it has: 1) a large brain with
human-like basal ganglia and a well-developed cerebral cortex (Jacobsen et al., 2010); 2)
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 94
good visual and spatial discrimination and memory (Kendrick et al., 2001; Lee and
Fisher 2006; Morton and Avanzo 2011); and 3) a polymorphism in DRD2 that is
associated with temperament (Chapter 4 and 5).
In sheep, temperament is assessed with tests that quantify the behavioural responses to
the presence of a human and to social isolation (Murphy et al., 1994; Blache and
Ferguson 2005). These tests have allowed the definition of two phenotypes: ‘calm’
animals with a low behavioural reactivity and ‘nervous’ animals with high behavioural
reactivity (Murphy et al., 1994; Blache and Ferguson 2005; Beausoleil et al., 2008). We
have shown that the DRD2 SNP939 T/T genotype is preferentially associated with
‘calm’ temperament and the DRD2 SNP939 C/C and C/T genotypes are preferentially
associated ‘nervous’ temperament (Chapter 4 and 5), but we have not yet investigated
the effects of these polymorphisms on cognitive function.
We have therefore tested whether, for sheep carrying the DRD2 SNP939, the T/T
genotype, associated with ‘calm’ temperament, is better at learning than the ‘nervous’
C/C+C/T genotype. We used three paradigms: simple visual discrimination, simple
spatial discrimination, and reverse spatial learning. All of these tests have previously
been used to assess learning and short-term memory abilities in rats as well as sheep
(Conrad et al., 1996; Morton and Avanzo 2011; Johnson et al., 2012).
7.3 Materials and Methods
This experiment was carried out in accordance with the Australian Code of Practice for
the Care and Use of Animals for Scientific Purposes (8th Edition, 2013) and was
approved by the Animal Ethics Committee of The University of Western Australia under
RA/3/100/1252.
7.3.1 Animals
We used female Merino sheep (age 14 months; body mass 42.8 ± 2.1 kg) with known
DRD2 SNP939 genotypes: 12 sheep carried the DRD2 SNP939 C/C+C/T genotypes
associated with nervous temperament and 12 sheep carried the DRD2 SNP939 T/T
genotype associated with calm temperament. The sheep were housed at the UWA Farm
Ridgefield in a paddock-feedlot system where they had free access to food and water
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 95
and could graze before and after testing, and throughout non-testing days.
7.3.2 Color visual discrimination
An apparatus comprising two identical testing units, previously described by Morton
and Avanzo (2011), was used to measure the capacity of an animal to learn one color out
of a choice of two (Figure 7.1). Each unit measured 2.4 × 7.2 m and comprised a
starting gate located in the middle of the front panel, and a testing area divided
longitudinally into two decision areas by a metal hurdle. The sheep could be locked in
the decision area using a rotating gate. The sheep exit the pen by the doors located at the
end of each decision area. At the end of each decision area, an A4 colored sheet of
cardboard was displayed 10 cm above a small feed trough (20 × 15 × 20 cm). The two
identical testing units were assembled back to front, so each sheep could be tested
multiple times by circling through the two units using corridors located at each end of
the block of units. The outsides of the units and testing pen were covered with hessian
to isolate the animal from external visual stimuli (Figure 7.1).
Figure 7.1 Top and side views of the design of the apparatus for testing the discrimination of
colour (based on Morton and Avanzo 2011). Two of the 2.4 m × 7.2 m areas were constructed
adjacent to each other but the testing areas (the grey in the top schema) were set at opposite ends.
Each testing pen comprised a central starting gate and two discrimination test areas divided
SS
SS
Entrance
Exit
Gate
7.2 m3 m1 m1 m
2.4 m2.4 m
GateStart pen Hurdle End pen
Discrimination test area
gate
Start door
Start door
Exit door
Exit doorExit
door
Exit door
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 96
longitudinally by a metal barrier. The two discrimination stimuli (S) are located at the end of the
pen. After a sheep has made its choice (one side), the gate was closed behind it. After
consuming the reward (or after 1 min), the sheep exited through the exit gates located at the end
of the pen and was pushed into the end corridor so it start the next discrimination test in the
adjacent pen.
During the visual discrimination testing procedure, a pair of colored stimulus cards
(blue and yellow) was used, as previously described by Morton and Avanzo (2011). For
each individual sheep, one color was randomly associated with a food reward (25 g
lupin grain). Between discrimination trials, the stimulus cards were swapped to control
for biases towards the left or right side of the pen. The test began when the sheep
entered the start gate from where both stimuli could clearly be seen. The animals were
free to move in the test area towards either of the stimuli and, once past a designated
line (1 m from the stimulus cards), their decision was recorded, together with the delay
taken to the decision (seconds). Each sheep was tested for one minute (Morton and
Avanzo 2011) during which all behaviours (bleating, jumping, stamping) were recorded.
During the first 8 discrimination trials, animals that chose incorrectly (not the rewarded
color) were allowed to make a correction and then gently ushered to the correct side so
they could collect the food reward. In the following trials, once the choice had been
made, the gate was closed behind the sheep it was either allowed to eat the reward, if
the correct choice was chosen, or wait 20 seconds if the incorrect choice was chosen,
before being ushered onto the next discrimination trial. All sheep in both experimental
groups were subjected to 6 testing sessions of 8 discriminations. Sheep were considered
to have learned to discriminate when they reached 75% correct choice over 8
consecutive discriminations (one testing session), and at least 75% of the animals in
each group reached this criterion before commencing the reversal.
7.3.3 Spatial discrimination
This test made use of a Y-maze apparatus (Figure 7.2) with a starting gate leading into a
straight run (2.4 m long; Zone ‘A’) that split into two arms (each 2.4 m long; Zone ‘B’
and ‘C’), each with an exit gate located at the end.
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 97
Figure 7.2 Schema of the Y-maze apparatus, adapted from the design of Kendrick et al. (1995).
The maze is divided in 3 zones (A, B and C). Feeders, either empty or containing the food
reward, were placed at the end of the two arms (zones ‘B’ and ‘C’).
Every side of the Y-maze was covered with hessian to isolate the animal from external visual
stimuli. The food reward was always placed in a feed bucket on the maze arm designated S+,
with an empty feed bucket placed on the incorrect arm (S–).
The test started when the sheep passed the starting gate into the run (A), from which it
had to make a choice within 1 min toward the left (B) or right (C) arms of the maze. The
animals were free to move around the maze through the different zones. We recorded
the time taken by the sheep to find and eat the food reward and the number of times the
sheep crossed the boundaries into different zones until it had found and started eating
the reward. One half of each treatment group was trained to find the reward on one side
of maze and the other half trained to find it on the other side. A sheep was considered to
have achieved spatial discrimination (or to have learned to take the correct side) when it
had made 4 consecutive correct choices. Each animal was allowed a maximum of 24
attempts. After at least 80% of each group had reached the criterion for success, the
animals were tested for reverse spatial discrimination by swapping the location of the
reward. The same criterion was used to assess success in the reversal discrimination.
7.4 Data analysis
Data were analyzed using SPSS (16.0 V). A two-factor ANOVA for repeated
measurements in the General Linear Model was used to analyze the data with trials as
Start box
Exit gate
Gate
Zone A
Zone B
Zone C
Left feeder
2.4m
2.4m
0.7m
Right feeder
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 98
the repeated measure, genotype as a factor and order and day of trial as blocking factors.
Prior to analysis, all data were assessed for normality using the Shapiro-Wilk test and
for homogeneity of variance using Bartlett’s test. Where data were normally distributed
and where variance was homogenous, the data were compared using Tukey’s post-hoc
tests. The data for total time (s) in the spatial discrimination test was transformed using
a cosine function and the other sets of data (average delays (s) to decision in the simple
visual discrimination test, total time in the spatial reversal test, number of errors in the
spatial and reversal tests) were transformed using Blom’s formula in the transformation
program in the software. Given the observed differences in standard deviations across
the conditions, Maulchy's test of sphericity was used to test whether variances and
covariances of the within-subject variables were equal. If the test was significant (P <
0.05) for each factor and for the interactions, it indicated a violation of the ANOVA
assumption for compound symmetry, and a more conservative Greenhouse-Geisser
(G-G) F-test was used. Differences were considered significant at P < 0.05 and highly
significant at P < 0.01.
7.5 Results
7.5.1 Color visual discrimination
Neither group reached the criterion of 75% correct choice within 48 discriminations
(Figure 7.3) so, under the 75% criterion, neither would be classified as successful at
color visual discrimination, although the percentages of correct choices for the two
groups differed (53 ± 2.6% vs 39 ± 2.1%; F1,10 = 5.188; P = 0.035).
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 99
Figure 7.3 Performance of sheep either carrying the DRD2 variant C/C+C/T (black circle) or
the T/T (open circle) at nucleotide position 929 in the two-choice colour discrimination task.
Each point represents the mean (± S.E.; N = 12) number of correct choices made in a testing
sessions comprising 8 discrimination trials.
The average delays to decision were similar for the two genotypes in each session of 8
discrimination trials (P > 0.05; Table 7.1). There was no genotype effect (F1, 142
(Greenhouse-Geisser) = 0.000; P = 0.997) and no interaction between time (session) and
genotype (F5, 138 (Greenhouse-Geisser) = 0.565; P = 0.685). However, there was an
effect of time (trials) within group (C/C+C/T: F5, 66 = 4.628, P = 0.041; T/T: F5, 66 =
4.021, P = 0.045; Table 7.1), with both groups performing the task significantly faster in
the last session (Session 6) than in the first session.
Table 7.1 The effect of DRD2 SNP939 genotype on the average delay (s) to decision during the
visual discrimination test (mean ± S.E.; N = 12). Lowercase subscripts that differ between
testing sessions within group (in the same column) indicate P < 0.05 (each session = 8
discriminations).
Cor
rect
cho
ice
(%)
Test session
100
90
80
70
60
50
40
30
20
01 2 3 4 5 6
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 100
DRD2 SNP939 Genotype
Test session C/C/+C/T T/T F1, 22 P
1 8.6 ± 1.99a 8.0 ± 1.83a 0.178 0.687
2 5.3 ± 0.73ab 5.9 ± 1.00ab 0.262 0.602
3 4.5 ± 0.75ab 5.1 ± 0.75ab 0.608 0.405
4 4.7 ± 0.75ab 6.3 ± 1.55ab 1.182 0.284
5 4.7 ± 0.99ab 4.4 ± 1.03ab 0.031 0.865
6 2.8 ± 0.11b 2.9 ± 0.21b 0.402 0.534
F5, 66 4.628 4.021
P 0.041 0.045
7.5.2 Spatial discrimination
Two sheep from each group did not reach the criterion of spatial discrimination so we
analyzed the data for 10 sheep per group. There was no genotype effect (F1, 198
(sphericity assumed) = 1.366; P = 0.265) and no interaction between time (trial) and
genotype (F9, 190 (sphericity assumed) = 0.373; P = 0.946) for the total time (s) taken to
complete the initial spatial discrimination test. With all trials combined, there were no
differences between the two genotypes in the time taken to complete the test (P > 0.05;
Table 7.2). However, there was an effect of trial within genotype (C/C+C/T: F9,90 =
5.208, P = 0.033; T/T: F9,90 = 6.081, P = 0.025; Table 7.2) in both groups, with less time
taken to complete the task in Trial 4 than in Trial 1 (Table 7.2). There was no genotype
effect (F1, 198 (Greenhouse-Geisser) = 0.028; P = 0.870) and no interaction between time
(trial) and genotype (F9, 190 (Greenhouse-Geisser) = 2.361; P = 0.071) for the number of
choice errors in the test. Apart from the first trial, there were no differences between
genotypes in the number of error choices (P > 0.05; Table 7.2). In Trial 7, sheep with
C/C+C/T genotype reached the learning criterion (error choice = 0) because they ran
straight toward the correct side (Table 7.2), whereas sheep with the T/T genotype
reached the learning criterion in Trial 6 (Table 7.2),
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 101
Table 7.2 The effect of DRD2 SNP939 genotype (C/C/+C/T versus T/T) on the total time (s)
taken to complete the spatial discrimination test and the number of choice errors (mean ± S.E.;
N = 10). Different uppercase superscripts in the same line (between the two groups for each trial)
indicate P < 0.05. Different lowercase superscripts in the same column (between trials within
each group) indicate P < 0.05.
Time (s) Number of Errors
Trial C/C/+C/T T/T F1, 18 P C/C/+C/T T/T F1, 18 P
1 19.7 ± 4.74a 25.1 ± 5.43a 0.498 0.491 0.6 ± 0.16bA 1.3 ± 0.26aB 5.188 0.035
2 11.2 ± 2.99ab 14.0 ± 6.43ab 0.126 0.728 0.5 ± 0.27b 0.5 ± 0.34b 0.000 1.000
3 11.6 ± 4.78ab 14.0 ± 9.12ab 0.052 0.823 0.4 ± 0.31b 0.1 ± 0.10b 0.871 0.363
4 7.4 ± 1.89b 7.7 ± 2.05b 0.012 0.915 0.0 ± 0.00b 0.1 ± 0.10b 1.000 0.331
5 4.1 ± 0.16b 5.2 ± 0.51b 1.531 0.235 0.2 ± 0.13b 0.1 ± 0.10b 1.110 0.306
6 4.6 ± 0.27b 4.4±0.12b 0.792 0.388 0.2 ± 0.13b 0.0 ± 0.00b 2.250 0.151
7 4.8 ± 0.25b 5.5±0.37b 1.612 0.220 0.0 ± 0.00b 0.0 ± 0.00b
8 4.9 ± 0.22b 5.9±0.34b 2.723 0.116 0.0 ± 0.00b 0.0 ± 0.00b
9 4.9 ± 0.42b 5.9 ± 0.79b 1.282 0.272 0.0 ± 0.00b 0.0 ± 0.00b
10 4.7 ± 0.31b 4.7 ± 0.21b 0.003 0.956 0.0 ± 0.00b 0.0 ± 0.00b
F9,90 5.208 6.081 1.332 5.208
P 0.033 0.025 0.267 0.033
Reverse spatial discrimination
Two sheep from each group failed to reach the criterion for the reverse spatial
discrimination test, so we analyzed the data for 8 sheep per group. The sheep with
DRD2 SNP939 T/T genotype learned ran straight to the correct side with no error by
Trial 10, one trial earlier than the sheep with C/C+C/T genotype (Trial 11; Table 7.3).
There was a main effect of genotype (F1, 286 (Greenhouse-Geisser) = 8.423; P = 0.027)
and an interaction between time (trial) and genotype (F17, 270 (Greenhouse-Geisser) =
3.517; P = 0.035) for the time (s) taken to complete the task. Before Trial 10, in Trials 4,
5, 8 and 9, the two genotype groups differed in the time taken to complete the task (P <
0.05; Table 7.3).
There was an effect of trial within genotype (P < 0.05; Table 7.3): compared to the first
3 trials, the time taken to complete the task was shorter by Trial 5 in the SNP939 T/T
genotype, but did not become shorter until Trial 10 for the SNP939 C/C+C/T genotype.
There was a main effect of genotype (F1, 286 (Greenhouse-Geisser) = 6.569; P = 0.023)
and interaction between time (trial) and genotype (F17, 270 (Greenhouse-Geisser) = 2.646;
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 102
P = 0.031) for the number of error choices in the test. The genotypes differed in the
number of errors in Trials 5, 6 and 7 (P < 0.05; Table 7.3). Compared the first 3 trials,
the number of errors fell by Trial 5 in the DRD2 SNP939 T/T genotype (P < 0.05; Table
3) but not until Trial 10 in the C/C+C/T genotype (P < 0.05; Table 7.3).
Table 7.3 The effect of DRD2 SNP939 genotype (C/C/+C/T versus T/T) on the time (s) taken to
complete the reverse spatial discrimination test and the number of error choices (mean ± S.E.; N
= 8). Different uppercase superscripts in the same line (between the two groups for each trial)
indicate P < 0.05. Different lowercase superscripts in the same column (between trials within
each group) indicate P < 0.05.
Time (s) Number of Errors
Trial C/C/+C/T T/T F1, 14 P C/C/+C/T T/T F1, 14 P
1 35.9 ± 2.06a 25.2 ± 3.80a 2.524 0.131 1.6 ± 0.32a 1.6 ± 0.26a 0.000 1.000
2 20.7 ± 4.55b 16.0 ± 2.68b 0.521 0.453 1.1 ± 0.12ab 1.1 ± 0.29ab 0.000 1.000
3 15.7 ± 3.26bc 14.5 ± 3.22bc 0.053 0.822 0.8 ± 0.16bc 0.9 ± 0.23bc 0.198 0.662
4 11.9 ± 1.03bcdA 7.9 ± 1.34cdB 5.228 0.031 0.8 ± 0.16bc 0.4 ± 0.18cd 2.328 0.149
5 10.2 ± 1.24cdA 5.8 ± 0.94dB 6.828 0.014 0.8 ± 0.16bcA 0.1 ± 0.12dB 6.348 0.019
6 9.6 ± 1.43cd 7.1 ± 1.29d 1.569 0.230 0.6 ± 0.18bcdA 0.1 ± 0.12dB 4.628 0.041
7 10.5 ± 1.37bcd 6.1 ± 0.86d 3.029 0.104 0.6 ± 0.18bcdA 0.1 ± 0.12dB 4.628 0.041
8 11.9 ± 1.60bcdA 6.1 ± 0.88dB 5.158 0.038 0.5 ± 0.19bcd 0.1 ± 0.12d 2.647 0.120
9 11.7 ± 2.07bcdA 5.4 ± 1.04dB 6.668 0.017 0.6 ± 0.18bcd 0.2 ± 0.16d 2.328 0.149
10 5.5 ± 0.44d 4.3 ± 0.35d 0.578 0.422 0.1 ± 0.12d 0.0 ± 0.00d 0.981 0.334
11 4.9 ± 0.48d 4.8 ± 0.30d 0.029 0.895 0.0 ± 0.00d 0.0 ± 0.00d
12 5.4 ± 0.48d 4.7 ± 0.28d 1.601 0.226 0.0 ± 0.00d 0.0 ± 0.00d
13 4.8 ± 0.36d 4.9 ± 0.48d 0.020 0.907 0.0 ± 0.00d 0.0 ± 0.00d
14 4.7 ± 0.37d 4.6 ± 0.21d 0.025 0.883 0.0 ± 0.00d 0.0 ± 0.00d
15 4.5 ± 0.27d 4.8 ± 0.27d 0.561 0.424 0.0 ± 0.00d 0.0 ± 0.00d
16 4.5 ± 0.28d 4.5 ± 0.33d 0.001 0.991 0.0 ± 0.00d 0.0 ± 0.00d
17 4.1 ± 0.17d 4.7 ± 0.39d 2.050 0.179 0.0 ± 0.00d 0.0 ± 0.00d
18 4.4 ± 0.38d 4.6 ± 0.30d 0.379 0.637 0.0 ± 0.00d 0.0 ± 0.00d
F17, 126 9.058 7.412 6.347 8.439
P 0.008 0.012 0.019 0.010
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 103
7.5.3 Behavioural reactivity during the tests
The C/C+C/T genotype paced significantly more than the T/T genotype during the
visual discrimination test (P < 0.05; Table 7.4) and bleated significantly more during the
reverse spatial discrimination test (P < 0.05; Table 7.4). Both genotype groups showed
higher frequencies of jumping, stamping, pacing and, in particular, bleats during the
visual discrimination test than during both the initial spatial discrimination test and the
reverse spatial discrimination test (P < 0.05; Table 7.4). Compared to the initial spatial
discrimination test, sheep in the reverse spatial discrimination test showed more staring,
stamping, pacing and, in particular, more bleating (P < 0.05; Table 7.4). In the reverse
spatial discrimination test, there were more bleats in the C/C+C/T genotype than in the
T/T genotype (P < 0.05; Table 7.4), but the genotypes were similar in the initial spatial
discrimination test (P > 0.05; Table 7.4).
Table 7.4 The mean (± S.E.) frequency of behaviours in the two genotypes during the visual
discrimination test (N = 12), the initial spatial discrimination test (N = 10) and the reverse
spatial discrimination test (N = 8). Different lowercase superscripts in the same line (between
tests for each behaviour) indicate P < 0.05. Different uppercase superscripts in the same column
(between genotype groups within each test) indicate P < 0.05.
Behaviours
(items/min)
Visual
Discrimination
Spatial
discrimination
Reverse spatial
discrimination
DRD2 C/C+C/T
Bleating 7.9 ± 1.98a 0.7 ± 0.33b 3.2 ± 0.81Ac
Jumping 1.5 ± 1.06 0.0 ± 0.00 0.0 ± 0.00
Stamping 1.3 ± 1.16 0.0 ± 0.00 0.0 ± 0.00
Staring 0.3 ± 0.25 0.0 ± 0.00 0.3 ± 0.16
Pacing 3.0 ± 0.69Aa 0.3 ± 0.21b 0.5 ± 0.26b
DRD2 T/T
Bleating 5.3 ± 1.89a 0.0 ± 0.00b 1.00 ± 0.86Bb
Jumping 0.8 ± 0.32 0.3 ± 0.30 0.0 ± 0.00
Stamping 0.4 ± 0.33 0.0 ± 0.00 0.1 ± 0.12
Staring 0.5 ± 0.41 0.0 ± 0.00 0.0 ± 0.00
Pacing 0.5 ± 0.23B 0.2 ± 0.13 0.4 ± 0.18
7.6 Discussion
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 104
The SNP DRD2 (SNP939) receptor appears to influence learning ability in animals with
different phenotypes for temperament. Both DRD2 genotypes were able to learn the
initial left-right spatial discrimination and the reverse spatial discrimination tasks, and
they both performed similarly in left-right spatial discrimination test, but sheep carrying
a T/T (calm) genotype performed better in reverse spatial discrimination, taking less
time to learn the task and committing fewer errors, than the sheep with C/C+C/T
(nervous) genotype. On the other hand, neither genotype was able to learn color visual
discrimination within 48 attempts. In no situation did the C/C+C/T (nervous) genotype
perform better than the T/T (calm) genotype, but the fact that the sheep were not able to
learn visual discrimination, yet were able to learn spatial discrimination, suggests that
we need to consider the adequacy of some of the tests in the context of this animal
model.
Similar differences in capacity to learn spatial and visual discrimination have been
reported for studies with pigs, cattle and horses (Wesley and Klopfer 1962; Rehkamper
and Gorlach 1997; Moustgaard et al., 2004; Murphy and Arkins 2007), and well as
earlier studies for sheep (Tanaka et al., 1995; Johnson et al, 2012). On the other hand,
several other studies from a variety of laboratories, including our own, have shown that
sheep can discriminate colors (Bazely and Ensor 1989; Bickell et al., 2011; Morton and
Avanzo 2011; Howery et al., 2013; Sena et al., 2013). The discrepancy among these
studies might be explained by: i) differences in behavioural reactivity when exposed to
stressors; ii) relevance of the stimulus; iii) attention towards the reward; iv) training
conditions. Below we consider each of these possibilities.
i) Behavioural reactivity when exposed to stressors
The behaviour of individuals, including cognitive learning, can be disrupted when
they are exposed to high levels of stress (Lyons et al., 1993; Boissy and Bouissou 1995;
Kleen et al., 2006; Conrad 2010; Simitzis et al., 2012; Sena et al., 2013). During testing
in the present study, the sheep were isolated from their flock-mates, one of the most
stressful situations for a social species and a factor known to influence performance in
cognitive tasks (Lyons et al., 1993; Boissy and Bouissou 1995). In addition, the sheep in
the present study had some contact with human investigators, another known stressor
(Romeyer and Bouissou 1992; Lyons et al., 1993; Boissy and Bouissou 1995).
Moreover, there could be an interaction between these two sources of stress because
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 105
Lyons et al. (1993) found that sheep are more likely to react to human presence when
they are isolated from their conspecifics. It therefore seems likely that, during our visual
discrimination test, the sheep perceived significant potential threats, an explanation
supported by the locomotion and vocalization behaviours that we observed: jumping,
stamping, pacing and, especially, the large number of bleats. This raises the question of
why the same two groups were able to learn spatial discrimination. The spatial
discrimination testing followed visual discrimination testing, allowing the sheep a few
weeks of contact with the human (the same investigator), perhaps increasing familiarity
and reducing fear of both human presence and the novel environment. There is evidence
in the present study for this adaptation in the fear-related behaviours: in both genotype
groups, there was far less jumping, pacing, and bleating in the spatial discrimination
tests than in the visual discrimination test. Therefore, the high behavioural reactivities
elicited by the exposure to novelty (human, surroundings) and isolation from their
conspecifics is probably the main reason for their inability to learn the visual
discrimination. Further study is therefore needed with a modified test conducted in the
presence of conspecifics, in familiar surroundings, and thus without stress.
ii) Relevance of the stimulus
Many studies have suggested that sheep can visually discriminate among stimuli
that are highly relevant to survival, such as toxic and non-toxic food, and the distinctive
characteristics of their mates (Nowak and Lindsay 1992; Kendrick et al., 2001; Bickell
et al., 2011; Howery et al., 2013). It is also known that sheep can live in a small area
without the need for confinement by fences and then return to that area instinctively
after lambing and shearing (Hunter 1962; Gray 1996), suggesting that they have good
spatial memory. Good spatial memory is probably linked to survival and could explain
why the sheep in the present study were able to learn spatial discrimination within 10
trials, regardless of their DRD2 genotype. By contrast, the blue and yellow cards used in
the visual discrimination task might not be very relevant cues for sheep so an
association with the food reward was difficult for them to learn. However, in the study
by Morton and Avanzo (2011), the sheep could discriminate between blue and yellow,
the test colors used in the present study, and also green and purple, even when presented
in different shapes. The disagreements between the two studies could be explained by
differences in the breed. Morton and Avanzo (2011) used Welsh Mountain sheep while
we used Merino sheep and the breeds often differ in their behavioural characteristics
(Scott and Fuller 1965). Sheep breeds also differ in cognition, including the ability to
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 106
discriminate between ewes and lambs (Shillito and Alexander 1975; Alexander 1977;
Nowak et al., 1987; Walser and Walters 1987; Nowak and Lindsay 1990).
iii) Attention towards the reward
It has been suggested that the amount of attention paid to a stimulus plays a vital
role in the learning of a cognitive task (Mendl 1999; Moustgaard et al., 2004). The key
element of any reward-based discrimination task is the motivation of the animal to
obtain the reward, so a highly motivational stimulus with little risk of distraction is
essential (Conrad 2010; Sena et al., 2013). Furthermore, the effectiveness of a food
reward as motivation can be diminished when the animal experiences stress or fear
(Hutson 1985). Mendl (1999) proposed that the most fearful animals shift their attention
away from their tasks, resulting in poor performance in those tasks. During the visual
discrimination test in the present study, the animals were agitated, judging from their
behaviour, so their attention appeared to be more focused on stressors (isolation, human
presence) than on the food reward. We were unable to control external auditory stimuli
because of the design of the test facility so the sheep were visually isolated from their
conspecifics but were nevertheless able to hear them in the background. This distraction
might have limited the test animal’s focus on the stimulus and the food reward.
iv) Training conditions
It seems that sheep need a great deal of training if they are to learn a visual
discrimination task, and that they might never learn. Johnson et al. (2012) found that
even 5 weeks of training was insufficient for them to learn visual discrimination, and
Tanaka et al. (1995) found that sheep needed 7 sessions of 30 discrimination trials (210
in total) to pass a criterion for shape discrimination. We trained our sheep for 48 trials,
so a longer training period might be needed to, for example, assess DRD2 genotypes. In
addition to the duration of training, habituation to the test environment might play a role.
Morton and Avanzo (2011) handled their sheep intermittently for 4 months and
habituated them to the test apparatus before they began formal testing, so their testing
environment was not novel. We could not follow this protocol because of the potential
effect of the DRD2 polymorphisms on novelty-seeking and fear-related behaviour.
Perception of our testing apparatus as novel by our sheep might explain their inability to
learn visual discrimination.
DRD2 polymorphism affected performance in the reversal of spatial learning test but
not the initial spatial memory task. This outcome could be explained by the specific
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 107
association of different types of cognition (memory and reversal learning) with DRD1
and DRD2 subtypes of dopamine receptors, and the effect of a challenging environment
on individual differences in cognition learning.
DRD1 receptors and their polymorphisms have been linked to memory ability in
primates (Sawaguchi and Goldman-Rakic 1991, 1994; Williams and Goldman-Rakic
1995; Murphy et al., 1996; Muller et al., 1998). By contrast, in rodents, DRD2 receptors
and their polymorphisms are mainly associated with reversal learning (Ridley et al.,
1981; Smith et al., 1999; Kruzich and Grandy 2004; Lee et al., 2007; Cools et al., 2001,
2007; Jocham et al., 2009). Where DRD2 receptor polymorphisms have been shown to
be linked with working memory in mice and humans (Kellendonk et al., 2006; Xu et al.,
2007), the polymorphism loci differed from those described in our study. It seems that
the polymorphisms that we have been studying induce greater differences in reversal
learning capacity than in memory ability. In addition, individual differences in
behavioural response to environmental stimuli often become more evident when
individuals are presented with a more challenging environment (Broom 2001; Koolhaas
et al., 2010; Carere et al., 2010). The learning task in our spatial memory test was not as
challenging as the reverse spatial test, and the effect of polymorphisms on cognitive
function might have been expressed only during the more challenging reversal situation.
This would suggest that DRD2 polymorphisms might be involved in behavioural
flexibility (ie, the reversal task) in sheep, as indicated for humans (Jocham et al., 2009).
The sheep with SNP939 T/T genotype performed better in the spatial reversal task,
taking less time to learn and committing fewer errors, than the sheep carrying the
SNP939 C/C+C/T genotype. We interpret this outcome as being caused by the specific
association between the polymorphisms and temperament because temperament can
affect cognitive function (Mendl 1999; Erhard et al., 2004). The SNP939 T/T genotype
is associated with a lower level of behavioural reactivity to isolation and to presence of
a human (‘calm’), compared to the SNP939 C/C+C/T genotype (‘nervous’ sheep;
Chapter 4 and 5). The better learning performance of the SNP939 T/T genotype could
be due to their relative calmness since lower levels of emotional activity are associated
with better performance on cognitive tasks such as spatial learning, discrimination and
recognition (Mendl 1999; Erhard et al., 2004; Lansade and Simon 2010; Bickell et al.,
2011; Butts et al., 2013).
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 108
In a stressful situation, nervous individuals may adopt an ‘active’ strategy characterized
by higher levels of locomotor activity and vocalizations, and higher activation of the
sympathetic-adrenal medullary and hypothalamic-pituitary-adrenal (HPA) systems, than
calm individuals (Clark et al., 1997; Beausoleil et al., 2008). The activation of the HPA
system under stress results in increased vigilance and, for example, increased scanning
of the environment (Dukas and Clark 1995; Boissy et al., 2005). Compared to the calm
T/T genotype sheep, the nervous C/C+C/T genotype sheep appeared to show a higher
level of activity and poorer ability to maintain attention on the task, as indicated by
longer time to learn the reversal task and the commitment of more errors.
The difference between the two genotypes in the activation of the HPA system could
have also contributed to the difference in performance during the reversal task because
an increase in cortisol secretion is associated with impaired memory and learning in
both humans and animals (de Quervain et al., 1998; Heffelfinger and Newcomer 2001;
Erhard et al., 2004). We did not measure cortisol during the present study because we
needed to avoid the disturbance of blood sampling, but we have previously shown that
nervous sheep have a greater cortisol response to exposure to accumulated stressors than
calm sheep (Hawken et al., 2013).
Finally, temperament involves the way in which individuals perceive and react to
fear-eliciting events (Boissy and Bouissou 1995; Broom 2001; Carere et al., 2010), so it
is logical that a similarly challenging environment is needed to reveal differences
between temperament groups in cognitive ability. In the present study, the reverse
spatial test in fits the classification of ‘challenging’, as evidenced by the ‘nervous’
C/C+C/T genotype sheep emitting more bleats than the ‘calm’ T/T genotype sheep,
whereas the two genotypes emitted similar numbers of bleats in the initial spatial
discrimination test.
In recent years, polymorphisms in two other genes, BDNF (brain-derived neurotrophic
factor) and COMT (catechol-O-methyltransferase), have been associated with cognitive
function in humans (Rybakowski et al., 2003; Barnett et al., 2008; Miyajima et al., 2008;
de Frias et al., 2010). BDNF is a potent modulator of synaptic transmission and
plasticity in the central nervous system (Barnett et al., 2008) and COMT is an enzyme
Chapter 7 Cognitive learning ability in sheep with DRD2 genotypes 109
involved in the metabolic degradation of released dopamine (Rybakowski et al., 2003).
Our study strongly suggests a role for DRD2 polymorphism in reversal learning, but
roles for polymorphisms of COMT and BDNF, and possibly other genes, in cognition in
sheep still remain to be investigated.
7.7 Conclusion
In sheep, it was technically difficult to measure or demonstrate differences between
DRD2 SNP939 genotypes with our simple test of visual discrimination, but our test of
reverse spatial learning, a challenging situation, clearly indicated an association between
DRD2 SNP939 genotype and cognitive learning ability. Sheep with the DRD2 SNP939
T/T genotype, associated with a ‘calm’ temperament, adapt better to spatial challenges
in their environment than sheep with the DRD2 SNP939 C/C+C/T genotype, associated
with a ‘nervous’ temperament.
Chapter 8 General Discussion 110
Chapter 8
General Discussion
This thesis supports the general hypothesis that polymorphisms of specific genes are
associated with differences in behavioural reactivity and physiological response
(cortisol secretion) in sheep of calm and nervous temperament. First, in the UWA
Merino temperament flock, for the four candidate genes, I detected five SNPs and
identified two of them are associated with temperament. One SNP controls
glucocorticoid synthesis (CYP17 SNP628) and has previously been described in South
African sheep (Storbeck et al., 2009); the other SNP controls dopamine receptor 2 (DRD2
SNP939). Using a flock of sheep that had not been selected on temperament phenotype,
I verified that these two SNPs are actually associated with differences in behavioural
reactivity and physiological response. Finally, I estimated the heritability of the
reactivity to isolation (one measurement of temperament) based on these two SNPs and
looked at the association of DRD2 SNP939 with cognitive learning ability, and was able
to further verify that the two SNPs can be used as genetic markers for prediction of
temperament in sheep.
Temperament affects reproduction, production and welfare in sheep, so selection for
temperament could improve the productivity of the wool and sheep-meat industries.
Compared to the current phenotypic selection method, a complex and time-consuming
process, a genotypic method is quicker and easier and will therefore save time and
labour. Moreover, genotype selection will provide useful contributions to our
understanding of animal breeding, welfare, and conservation, for animals in the wild as
well as those in production systems. However, before launching into an industry-wide
breeding program, some issues need to be clarified. Most importantly, the results of
genetic association study can be affected by uncontrolled factors, such as gender,
methodology, gene-gene and gene-environment interactions.
Gender has always been seen as an important factor because most studies have shown
that gender can affect personality and temperament, and behavioural reactivity to
stressors, as shown for humans and rats (Cailhol and Mormede 1999; Costa Jr et al.,
Chapter 8 General Discussion 111
2001; Louvart et al., 2005; Slotten et al., 2006; Else-Quest et al., 2006). Some studies
disagree (Desautes et al., 1997; McManis et al., 2001; Weiss et al., 2004) but the general
consensus is that gender must be considered. In our breeding program, we retain very
few males so we could not include gender in the design. We thus only investigated
female sheep and this might explain we failed to find an association between our
MAOA SNPs and temperament. Indeed, MAOA activity seems to differ between
genders (Murphy et al., 1976): except for one study (Deckert et al., 1999), an
association between MAOA polymorphism and behavioural reactivity has been detected
in males but not females (Hsu et al., 1996; Manuck et al., 2000; Caspi et al., 2002; Saito
et al., 2002; Cohen et al., 2003; Newman et al., 2005; Jin et al., 2006; Nilsson et al.,
2006, 2007; Roohi et al., 2009). Gender could also affect the association between
CYP17 SNP628 genotypes and behavioural reactivity in the same way, thus explaining
the lack of such association in our female sheep and its presence in rams (Hough 2012).
Therefore, it is very important to test the effect of gender on the association of the two
SNPs with behavioural reactivity in future.
We detected our five SNPs only on basis of the mRNA sequence of the candidate genes.
Other regions of each gene, including the promoter region, the 5’- and 3’- untranslated
regions, and the introns could also affect the phenotype. For example, the previously
mentioned SNP218 (A/C) in Intron 7 and the SNPs in the promoter region of the TPH
gene, the -141C insertion/deletion in the promotor of DRD2 gene, the 30 bp repeats
polymorphism in the promoter, and a 128-bp allele in Intron 4 of the MAOA gene, have
all been found to be associated with substance addiction, aggressiveness, impulsiveness,
panic disorder, depression and antisocial behaviours (Nolan et al., 2000; Jonsson et al.,
2003; Newman et al., 2005; Liu et al., 2006; Wendland et al., 2006; Hong et al., 2008b;
Beaver et al., 2013; Gallardo-Pujol et al., 2013). Our study is a major step towards an
understanding of the association of polymorphisms in the candidate genes with the
temperament, but polymorphisms in other regions of the same genes now need to be
investigated.
In humans, temperament is thought to be an important sub-system of personality (Corr
2009) and is conceptualized in nine broad dimensions: level of activity,
approach/withdrawal, intensity, threshold, adaptability, rhythmicity, mood, persistence
of attention span, and distractibility (Thomas and Chess 1977). A similar sub-system
Chapter 8 General Discussion 112
could exist in animal personality (Reale et al., 2007; Gosling 2008; Weinstein et al.,
2008). Temperament has complex traits that include perception, emotion and behaviours
in both humans and animals. With respect to the effect of genes on emotional disorders
or behaviours, except for Huntington’s disease which is known to be single-gene effect
(Gusella et al., 1983), polygenic effects determine emotional disorders or behaviours,
including attention deficit hyperactivity, depression, substance addiction, aggression,
impulsiveness and novelty seeking, all of which are included under the temperament
‘umbrella’ (Bah Rosman 2008; Corr 2009).
In this thesis, we used an association study to investigate the four candidate genes that
were most likely to be associated with the well-characterised physiological and
behavioural differences between the ‘calm’ and ‘nervous’ lines that we have been
studying for many years. We found only two SNPs that were associated with the
temperament phenotype, so an obvious question is whether there are other genes or gene
polymorphisms associated the temperament. In addition to the genes in the HPA axis
and central neural system that we have focused on, others have been shown to be
involved in personality or temperament (Reif and Lesch 2003), but they have rarely
been studied in detail:
1) Noradrenergic genes – dopamineβ-hydroxylase (DBH; responsible for
norepinephrine synthesis), adrenergic receptor (ADRA2A) and norepinephrine
transporter (NET1), all suggested to play a role in ‘fight or flight’ response
(Major et al., 1980);
2) GABAergic genes – the GABA-A receptor gene has been shown to be involved
in anxiety disorders (Crestani et al., 1999);
3) Nitric oxide (NO) synthase – the gene has been proposed to be associated with
aggressive and sexual behaviour (Nelson et al., 1995);
4) Human transcription factor (AP-2β) has shown to be related to aggression
(Damberg et al., 2000).
So these genes remain attractive as candidates for further research. As an approach, it
would probably be best to use a genome-wide association study (GWAS) to target the
whole genome as a means to identify and investigate more functionally relevant
polymorphisms. This is our future goal for improving our knowledge of the specific
genes associated with temperament.
Chapter 8 General Discussion 113
There is an increasing number of studies investigating the relative contributions of
genes, environment and other factors to phenotype variance. Gartner (1990) was able to
show that some non-genetic variability was due to an epigenetic modification.
Epigenetic mechanisms, in which genes are modified by methylation and acetylation
without changing the DNA sequence, might also change gene expression in a way that
affects temperament phenotype. Evidence of the epigenetic mediated sources of
variation in genetically identical organisms can be found in the examples of human
twins (Fraga et al., 2005) and in isogenic mice (Morgan et al., 1999; Rakyan et al.,
2003). Traditionally, it has been thought that the epigenetic modification is set up
during cell differentiation and embryonic morphogenesis before birth, and after birth,
during the maturation of the germ line, gametes re-program their epigenetic status by
erasing the old and re-establishing a new epigenetic profile (Monk et al., 1987; Oswald
et al., 2000; Mayer et al., 2000; Surani 2001; Wong et al., 2005). Therefore, both
prenatal and postnatal challenges could induce epigenetic changes (Jablonka and Lamb
1995; Surani 2001; Sutherland and Costa 2003; Waterland and Jirtle 2003). A study by
Weaver et al. (2004) indicated that maternal behaviour can induce the epigenetic
modification (DNA methylation) of the gene for the cortisol receptor and therefore
affect the stress response in the offspring. Other studies have produced evidence that
epigenetic regulation of the expression of genes for the key steroidogenic enzymes (e.g.
CYP17) can affect steroid hormone biosynthesis and action (Martinez-Arguelles and
Papadopoulos 2010). In addition, there are indications that epigenetic modification
(DNA methylation) of the DRD2 gene plays a role in the regulation of DRD2
expression (Popendikyte et al., 1999; Frieling et al., 2010) and that such modifications
are associated with the psychiatric disorders and behaviours, such as schizophrenia,
bipolar disorder, eating disorder (Abdolmaleky et al., 2005, 2008; Frieling et al., 2010).
Therefore, we need to explore whether epigenetic modification of the two genes
associated with temperament in our sheep, CYP17 and DRD2, is associated with the
cortisol response and behavioural reactivity (temperament).
In conclusion, CYP17 SNP628 and DRD2 SNP939 are associated with temperament in
sheep. The DRD2 variant is specifically associated with behavioural reactivity and
cognitive learning ability, and the CYP17 variant is specifically associated with the
physiological cortisol response. These observations lead to the conclusion that the
Chapter 8 General Discussion 114
combination of DRD2 SNP939 C allele and the CYP17 SNP628 A/A genotype could be
used as a genetic marker for prediction of nervous temperament, whereas the
combination of DRD2 SNP939 T/T and CYP17 SNP628 G/G could be used as a genetic
marker for calm temperament. With these two SNPs, calm animals could be selected
and potentially be better adapted to intensive conditions whereas nervous animals could
be selected as better adapted to an extensive environment. Therefore, it is possible to
select sheep for temperament using a genotypic method instead of the complex and
time-consuming phenotypic method. Future studies using GWAS are needed to
investigate the association of other regions of these candidate genes, or other genes
along the HPA axis and central nervous systems, with temperament in sheep so we can
better understand the genetic association with temperament.
Reference 115
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