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Genetic Characterisation of Dog Personality Traits

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Genetic Characterisation of Dog Personality Traits Genetics: Early Online, published on April 10, 2017 as 10.1534/genetics.116.192674 1 Genetic characterisation of dog personality traits 2 3 Joanna Ilska1 4 Marie J. Haskell1 5 Sarah C. Blott2 6 Enrique Sánchez-Molano3 7 Zita Polgar3 8 Sarah E. Lofgren4 9 Dylan N. Clements3 10 Pamela Wiener3 11 12 1. Scotland’s Rural College, Edinburgh, Scotland, UK 13 2. University of Nottingham, Sutton Bonington, England, UK 14 3. The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of 15 Edinburgh, Easter Bush, Scotland, UK 16 4. Youth Science Institute, Los Gatos, California, USA 17 1 Copyright 2017. 18 Abstract 19 The genetic architecture of behavioural traits in dogs is of great interest to owners, breeders 20 and professionals involved in animal welfare, as well as to scientists studying the genetics of 21 animal (including human) behaviour. The genetic component of dog behaviour is supported 22 by between-breed differences and some evidence of within-breed variation. However, it is a 23 challenge to gather sufficiently large datasets to dissect the genetic basis of complex traits 24 such as behaviour, which are both time-consuming and logistically difficult to measure, and 25 known to be influenced by non-genetic factors. In this study, we exploited the knowledge that 26 owners have of their dogs to generate a large dataset of personality traits in Labrador 27 Retrievers. While accounting for key environmental factors, we demonstrate that genetic 28 variance can be detected for dog personality traits assessed using questionnaire data. We 29 identified substantial genetic variance for several traits, including fetching tendency and fear 30 of loud noises, while other traits revealed negligibly small heritabilities. Genetic correlations 31 were also estimated between traits, however, due to fairly large standard errors, only a 32 handful of trait pairs yielded statistically significant estimates. Genomic analyses indicated 33 that these traits are mainly polygenic, such that individual genomic regions have small 34 effects, and suggested chromosomal associations for six of the traits. The polygenic nature of 35 these traits is consistent with previous behavioural genetics studies in other species, for 36 example in mouse, and confirms that large datasets are required to quantify the genetic 37 variance and to identify the individual genes that influence behavioural traits. 38 39 Key words: canine genetics, dog, temperament, personality, heritability, genome-wide 40 association 2 41 Introduction 42 Dogs play important roles as companions and helpers for humans and dog personality 43 influences their ability to carry out these functions (Jones & Gosling 2005), where personality 44 refers to individual consistency in behavioural responsiveness to stimuli and situations. The 45 distinct behavioural predispositions of individual dog breeds clearly indicate a strong genetic 46 component to dog personality, which is further strengthened by estimates of substantial 47 within-breed genetic variance found for a variety of dog behavioural traits across studies (e.g. 48 Wilsson & Sundgren 1997; Saetre et al. 2006; Meyer et al. 2012; Arvelius et al. 2014a; 49 Persson et al. 2015). 50 The majority of dog behaviour studies have been carried out on working dogs and have used 51 standardised tests, where the effects of the environment at the time of the test could be clearly 52 characterised. These standardised tests in controlled environments provide estimates of 53 moderate heritability for some tested behaviours, e.g. heritability of “gun shyness” has been 54 estimated at 0.56 (SE 0.09) in Labrador Retrievers (van der Waaij et al. 2008). However, the 55 majority of the reported heritability estimates for these traits fall below 0.4 (e.g. Wilsson & 56 Sundgren 1997; Saetre et al. 2006; van der Waaij et al. 2008; Arvelius et al. 2014b), with 57 various management and lifestyle factors (e.g. training practices, Haverbeke et al. 2010) 58 shown to affect behaviour. Thus, large datasets are required for accurate decomposition of the 59 variance in these traits into genetic and non-genetic components. Generating such datasets 60 requires substantial infrastructure which, in practice, may be unattainable for most pet dog 61 populations. Thus, even though personality traits are extremely important for the well-being 62 of both the dog and its owner, their heritabilities for pet dogs, usually not subjected to any 63 formalized behaviour testing, are still largely unknown. 64 Genomic methodologies like GWAS that assess markers across the genome have been used 65 to determine associations between traits and particular genetic variants. However, again 66 substantial datasets are required to identify genomic associations or to obtain genomic 67 predictions when a large number of small genetic effects are involved, as is expected to be 68 the case for behavioural traits (Willis-Owen & Flint 2006). As a result, few genomic analyses 69 have been applied to dog behaviour traits so far and thus, little is known about their genetic 70 architecture or the individual genes involved. Variation in a few functional candidate genes 71 (e.g. DRD4, TH, OXTR, SLC6A) has been shown to be associated with behaviour in dogs 72 (Våge et al. 2010; Kubinyi et al. 2012; Wan et al. 2013; Kis et al. 2014). However, these 3 73 detected associations are only a starting point in the process of understanding the molecular 74 genetic basis of dog behaviour. 75 Thus, the size of available datasets is a limiting factor to the dissection of the variance 76 components of behavioural traits as well as to the characterisation of their genetic 77 architecture. An alternative approach to using data from standardised tests would be to 78 exploit the knowledge that pet owners and dog breeders have of their own dogs in everyday 79 situations, in order to accumulate sufficiently large datasets. The size of these datasets could 80 then overcome the lack of standardised assessment and at the same time, avoid possible 81 interactions between the behaviour and the somewhat artificial conditions of the test 82 environment. 83 A survey-based approach has been now utilized in a number of studies on dog behaviour, 84 where the dog owner’s answers to validated questionnaires, such as Canine Behavioral 85 Assessment and Research Questionnaire (C-BARQ), were used to assess the personality traits 86 of the dog. C-BARQ was developed at the University of Pennsylvania originally as a method 87 for evaluating and predicting the success of guide dogs (Serpell & Hsu 2001). The reliability 88 and validity of C-BARQ demonstrated by the developers of the method and others (e.g. Hsu 89 & Serpell 2003; Svartberg 2005; Duffy & Serpell 2012) as well as the relationship between 90 C-BARQ responses and standardised test scores (Arvelius et al. 2014a) support its use as a 91 tool in behavioural research (Wiener & Haskell, 2016). Subsequently, it has been applied in 92 studies of dog behaviour by various groups (e.g. Liinamo et al. 2007; Kutsumi et al. 2013). 93 The C-BARQ survey contains 101 questions regarding the dog’s behavioural response to 94 various situations, with answers marked on a 5-step scale. The particular items of the 95 C-BARQ questionnaires are then typically grouped into factors describing a personality trait. 96 In most studies (e.g. Arvelius et al. 2014a; Asp et al. 2015), the grouping of questions and 97 number of resulting traits are largely based on the definitions derived by the developers of the 98 questionnaire (Hsu & Serpell 2003; Duffy & Serpell 2012), who used factor analysis to 99 define 11 (and later, 14) behavioural traits. In a previous study of Labrador Retrievers, we 100 used multivariate statistical techniques to define 12 personality traits from C-BARQ data 101 (Lofgren et al. 2014), some of which overlapped the previous grouping while others were 102 novel. 4 103 In this paper we used quantitative genetic and genomic approaches to investigate the genetic 104 contribution to everyday life behaviour, as assessed by C-BARQ data, in the Labrador 105 Retriever breed. 106 107 Methods 108 Personality trait characterisation 109 The data used in the study were a subset of a larger study on genetics of complex traits in 110 dogs, and consisted of owner-supplied responses to C-BARQ as well as a separate 111 demographic questionnaire. The dataset was limited to UK Kennel Club-registered Labrador 112 Retrievers. We previously applied a combination of Principal Components Analysis and 113 correlation structure to derive 12 behaviour traits (subsequently referred to as “SetA traits”): 114 Agitated when Ignored (Agitated), Attention-seeking (Attention), Barking Tendency 115 (Barking), Excitability, Fetching, Human and Object Fear (HOFear), Noise Fear (NoiseFear), 116 Non-owner-directed Aggression (NOAggression), Owner-directed Aggression 117 (OAggression), Separation Anxiety (SepAnxiety), Trainability and Unusual Behaviour 118 (Unusual) (Lofgren et al. 2014). The 12 trait values were calculated as averages of the 119 responses observed in each associated group, where the number of questions in the group 120 ranged from 1 (Barking, Fetching) to 20 (Unusual) (Supplementary Table 3 in Lofgren et al. 121 2014), as long as at least half of the questions were answered (otherwise, the dog’s record for 122 that trait was treated as missing). The final dataset used in the current analyses included 1,975 123 animals. The numbers of observations and the range of scores observed for each of the SetA 124 traits are presented in Table 1. Two of the traits (OAggression and SepAnxiety) showed 125 highly skewed distributions, with most dogs showing no evidence of these behavioural 126 characteristics. For comparison, we also calculated values for the 14 traits previously defined 127 for C-BARQ data (subsequently referred to as “SetB traits”) (Hsu & Serpell 2003; Duffy & 128 Serpell 2012), for the same dogs as in SetA.
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