genetic variation in the social environment affects ... › content › 10.1101 ›...

1

Genetic variation in the social environment affects behavioral 1

phenotypes of oxytocin receptor mutants in zebrafish 2

Ribeiro, D. 1, Nunes, A.R.

1, Teles, M.C.

1, Anbalagan, S.

2,3, Blechman, J.

2, 3

Levkowitz, G.2, Oliveira, R.F.

1,4,5,* 4

1Instituto Gulbenkian de Ciência, Oeiras, Portugal;

2Weizmann Institute of Science, 5

Rohovot, Israel; 3 ReMedy-International Research Agenda Unit, Centre of New 6

Technologies, University of Warsaw, Warsaw, Poland. 4ISPA – Instituto 7

Universitário, Lisboa, Portugal; 5Champalimaud Research, Lisboa, Portugal; 8

* E-mail: [email protected] 9

10

Abstract 11

Oxytocin-like peptides have been implicated in the regulation of a wide range of 12

social behaviors across taxa. On the other hand, the social environment, which is 13

composed of conspecifics genotypes, is also known to influence the development of 14

social behavior, creating the possibility for indirect genetic effects. Here we used a 15

knockout line for the oxytocin receptor in zebrafish to investigate how the genotypic 16

composition of the social environment (Es) interacts with the oxytocin genotype (G) 17

of the focal individual in the regulation of its social behavior. For this purpose, we 18

have raised wild-type or knock-out zebrafish in either wild-type or knock-out shoals 19

and tested different components of social behavior in adults. GxEs effects were 20

detected in some behaviors, highlighting the need to control for GxEs effects when 21

interpreting results of experiments using genetically modified animals, since the 22

social environment can either rescue or promote phenotypes associated with specific 23

genes. 24

25

Keywords: social genetic effects, indirect genetic effects, GxE interaction, oxytocin, 26

social behavior, zebrafish 27

28

29

30

.CC-BY 4.0 International license(which was not certified by peer review) is the author/funder. It is made available under aThe copyright holder for this preprintthis version posted March 26, 2020. . https://doi.org/10.1101/2020.03.23.002873doi: bioRxiv preprint

https://doi.org/10.1101/2020.03.23.002873

http://creativecommons.org/licenses/by/4.0/

2

Introduction 31

Social genetic effects (aka indirect genetic effects) occur when the phenotype of an 32

organism is influenced by the genotypes of conspecifics. Previous work has 33

highlighted the major potential evolutionary consequences of social genetic 34

effects(1,2), with evidence for such effects to be present both in interactions between 35

related (e.g. mothers and offspring(3,4)) and unrelated individuals (e.g. sexual 36

displays(5), aggression (6–8)). More recently the importance of social genetic effects 37

for health and disease has also been recognized (9), which may explain the 38

pervasiveness of the social environment as a mortality risk in humans (10,11). 39

Interestingly, the potential consequences of social genetic effects for the interpretation 40

of research results using genetically modified organisms (GMO) has been greatly 41

neglected. GMOs have been widely used in behavioral neuroscience to investigate the 42

causal role of candidate genes and behavioral phenotypes. Typically Knock-in and 43

Knock-out transgenics and mutants have been used to causally link the gain or loss of 44

behavioral function to a specific gene (12). In recent years the development of 45

genome editing techniques, such as CRISPR-Cas9-and TALEN- induced mutations, 46

have increased the interest in this approach and opened the door to studying the 47

genetic basis of behavior in non-model organism (13). However, most studies using 48

GMO in behavioral neuroscience have ignored the potential contribution of the 49

environment to the behavioral phenotype studied. This is because it has been assumed 50

that if the genetic background of these mutants is identical and their environment has 51

been kept constant, any phenotypic differences must come from the genetic 52

manipulation. However, when GMOs are incrossed or visually screened at a very 53

young age (e.g. using reporter genes, GFP) and thereafter raised and housed together 54

until used in experiments, changes in their behavior might be affected by divergent 55

social environments experienced by these mutants. In other words, modified behavior 56

might be as a result of growing with their peer mutants, rather than the canonical 57

social environment provided by wild type conspecifics. Such problem is particularly 58

relevant when studying social behavior. For example, mutant Drosophila males that 59

lack the fruitless gene (fruM

) do not express courtship behavior when held in isolation, 60

but acquire the potential to court females when grouped with other flies (14), 61

suggesting the occurrence of a combined gene (G) and social environment (Es) effect 62

(aka, GxEs). Thus, given the rising interest in the study of social behavior in model 63

organisms from worms to higher vertebrates, an assessment of potential gene by 64


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social environment effects on the behavioral phenotype of interest in GMOs used in 65

social neuroscience is crucial). 66

Despite the wide variety of species-specific social behaviors, a wealth of 67

evidence has implicated the paralog nonapeptides vasopressin (VP) and oxytocin 68

(OXT) and their receptors in the regulation of different aspects of social behavior 69

across vertebrates(15,16), suggesting a genetic toolkit role for these nonapeptides in 70

social behavior. Nonapeptides are an ancestral neuropeptide family found both in 71

vertebrates and invertebrates, that derived from a VP-like peptide, and that evolved 72

along two parallel clades of VP- and OXT-like peptides derived from the duplication 73

of the VP gene in early jawed fish (ca. 500 Mya). Both peptides have been implicated 74

in the regulation of behavior and physiology across different taxa, with VP being 75

more involved in aggression and agonistic behaviors and OXT-like peptides 76

consistently acting in affiliative behaviors and species-specific social behaviors across 77

diverse taxa (i.e. sexual behavior, social interactions) (17,18). Despite this wealth of 78

evidence on the direct genetic effects of OXT on social behavior, social genetic 79

effects of OXT genotypes have never been studied. 80

In this study we aimed to provide a proof of principle for GxEs effects in 81

behavioral phenotypes observed in GMO by assessing the occurrence of such effects 82

in a knockout line for the OXT receptor in zebrafish, a commonly used model species 83

in behavioral neuroscience (19). For this purpose, we studied the GxEs interaction in 84

the effects of the OXT gene (oxtr) in different aspects of social behavior, namely: 85

social preference (i.e. social approach); social habituation; social recognition; and 86

shoaling behavior. For this purpose, we have raised individual zebrafish of the WT 87

(oxtr(+/+)

) or knock-out genotype (oxtr(-/-)

) in different social environments (i.e. oxtr(+/+)

88

shoal or oxtr(-/-)

shoal; Figure 1A). 89

90

Results and Discussion 91

Adult zebrafish, like many other social animals, express a tendency to approach and 92

interact with conspecifics (social preference, Figure 1B) (20). Here we show that there 93

was no significant effect of either genotype, environment or GxEs interaction on 94

social preference (Table 1; Figure 1C). However, when fish were presented for a 95

second time to a shoal to measure social habituation (i.e. expected reduction in social 96

preference), we found a GxEs interaction, where oxtr(-/-)

individuals raised in oxtr(-/-)

97


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shoals express enhanced social habituation (F1,44 = 5.642, p = 0.022; Figure 1D). In 98

contrast, when we tested social recognition, which is a form of social memory needed 99

for individuality in social interactions (i.e. differential expression of social behavior 100

depending on identity of interacting individual), that is known to be modulated by 101

oxytocin both in mammals and zebrafish (21,22), we observed that oxtr(-/-)

individuals 102

exhibit a deficit in acquisition and retention of social recognition irrespective of the 103

social environment (oxtr(-/-)

or oxtr(+/+)

) in which they were raised (F1,44 = 7.600, p = 104

0.008; Figure 1F). 105

Given that social behavior of zebrafish mainly occurs in the context of 106

shoaling we have also investigated two shoaling behavior parameters: (1) social 107

integration – how well the focal individual integrates in the shoal, as measured by its 108

average distance to the centroid of the shoal (Figure 1G,H); and (2) social influence – 109

how the focal individual affects the shoaling behavior of the remaining shoal 110

members, by measuring the shoal dispersion as defined by the perimeter of the other 111

shoal members (Figure 1I,J). A GxEs interaction was found for social integration: 112

oxtr(-/-)

individuals raised in oxtr(-/-)

shoals exhibit a significantly lower social 113

integration than oxtr(-/-)

individuals raised in oxtr(+/+)

shoals; in contrast, oxtr(+/+)

114

individuals exhibit high levels of social integration irrespective of the shoal type in 115

which they were raised (Table 1; Figure 1H). Finally, the presence of a single WT 116

(oxtr(+/+)

) individual in a oxtr(-/-)

shoal was enough to increase its dispersion, whereas 117

the presence of a single oxtr(-/-)

individual in a oxtr(+/+)

shoal did not affect its 118

dispersion (Table 1; Figure 1J). 119

In summary, we show that distinct components of social behavior are 120

differentially affected by the genetic composition of the social environment versus the 121

oxtr genotype of the focal individual. Social recognition exhibited a pure effect of the 122

genotype. However, clear GxEs interactions were observed in the cases of social 123

habituation and social integration, and social influence had a major contribution of the 124

social environment. Thus, we demonstrated that genetic variation in the social 125

environment interacts with individual genotype during the developmental acquisition 126

of social behavior. In other words, the social environment can revert phenotypes 127

associated with specific genes. These results are in line with reported interactions 128

between the social environment and oxytocin receptor genotype in the determination 129

of social behavior phenotypes in human populations (23–25). Our results suggest that 130

more caution is needed in the interpretation of studies using transgenic or mutant 131


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individuals that are raised in cohorts of the same genotype, and that some phenotypes 132

observed in transgenic or mutant lines may in fact result from GxES interactions. 133

134

Materials and Methods 135

Zebrafish lines and maintenance 136

Zebrafish were raised and bred according to standard protocols and all experimental 137

procedures were approved by the host institution, Instituto Gulbenkian de Ciência, 138

and by the National Veterinary Authority (DGAV, Portugal; permit number 139

0421/000/000/2013). OXTR mutant zebrafish line (ZFIN ID: ZDB-ALT-190830-1) 140

was generated and provided by Dr. Gil Levkowitz (Weizmann Institute of Science) 141

using a TALEN-based genome editing system. The characterization of this line has 142

been described in Nunes et al. (26). 143

All the experimental groups were formed at 4 days post-fertilization, based on 144

the genotype of the progenitors, before they imprint for olfactory and visual kin 145

recognition (27,28). To evaluate genotype-environment effects, fish were raised in 146

groups according to the experimental design in Figure 1A and both female and males 147

tested in adulthood (3 months old). 148

149

Genotyping 150

At 3 months old, before behavioural screenings, genomic DNA was extracted from 151

adult fin clips using the HotSHOT protocol (29). The genomic region of interest was 152

amplified by PCR and sequenced to identify the focal fish in each group. The 153

following primers were used: sense 5’-TGCGCGAGGAAAACTAGTT-3’, antisense 154

5’-AGCAGACACTCAGAATGGTCA-3’. 155

156

Behavioural assays 157

Video acquisition 158

Fish were in a tank placed on top of an infrared lightbox and video-recorded either 159

from above (shoal preference and social recognition tests) or laterally (group 160

behaviour tests). Video acquisition was done with software Pinnacle Studio 14 (Corel 161


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Corporation, Ottawa, Canada). Shoal preference, social habituation and social 162

recognition analyses were performed with EthoVision video tracking system (Noldus 163

Information Technologies, Wageningen, The Netherlands) and group behaviour 164

analyses were done with the open source FIJI image-processing package (30). 165

166

Social preference and social habituation 167

The social preference test assesses the individual’s sociability by observing the 168

interactions between conspecifics (22): a focal fish was placed in a central 169

compartment (30x15x10 cm) of a three-compartment tank, separated by transparent 170

and sealed partitions. A shoal of fish was placed in one of the lateral compartments 171

(15x10x10 cm), while the other contained only water. To avoid any side bias the 172

stimuli were balanced across trials. After an acclimatization period (10 min), the focal 173

fish was released from a start box and allowed to explore the tank, while its behaviour 174

was video-recorded for 10 min. The time spent by the focal fish near (less than two 175

body lengths) each compartment was quantified and used to calculate the social 176

preference score (SP = Time near shoal/ [Time near shoal + Time near empty]). A 177

score above 0.5 indicates a preference for the shoal. 178

The social preference test was performed twice, with 24 hrs in between, and social 179

preference scores of both tests were used to calculate the habituation index (Hab. 180

Score = 1- [SPTrial2]/[SPTrial1 + SPTrial2]). A score above 0.5 reveal a decrease in 181

preference to associate with conspecifics. 182

183

Social recognition 184

The social recognition assay to evaluate short-term (i.e. 10 min retention) social 185

memory was adapted from the procedure already developed in our lab for long-term 186

(i.e. 24h retention) social memory in zebrafish (31), and has already been used 187

successfully in a previous study (22). A focal fish was placed for 10 min in the central 188

compartment of a three-compartment tank, separated by transparent and sealed 189

partitions, to acclimatize. The focal fish was allowed to interact visually across 190

partitions with 2 novel conspecifics for 10 min. After, both stimuli were removed, one 191

was placed in the same compartment (familiar conspecific stimulus), while a novel 192

conspecific was placed in the other compartment (novel conspecific stimulus). In a 193


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second 10 min interaction the time spent by the focal fish near each compartment 194

(termed novel cue or familiar cue) was quantified and used to measure the preference 195

for the novel (Disc.Score= Time near Novel/[Time near Novel + Time near 196

Familiar]). A discrimination score of 0.5 indicates no preference between novel or 197

familiar conspecifics. 198

199

Shoaling behaviour 200

Shoaling behaviour is a common behaviour present in fish models and allows to 201

determine complex interactions between individuals. Both focal fish and social 202

partners were recorded in the home tanks (3.5L tank). Focal fish were tagged with fin 203

clips for easy identification. The behaviours were video-recorded from side view for 204

10 min. Two components of shoaling behaviour were analysed in time bins of 8 205

seconds: (1) focal fish distance to the group centroid (social integration); and (2) the 206

dispersion of the remaining shoal members as measured by their perimeter (social 207

influence). 208

209

Data analysis 210

Data were analysed using SPSS 25.0. All data sets were tested for departures from 211

normality with Shapiro-Wilks test. Two factor univariate ANOVA were used for 212

comparing multiple groups. All data sets were corrected for multiple comparisons. 213

Tukey’s Test comparisons were used as post-hocs. Graphs were performed with 214

GraphPad software. 215

216

Ethical Approval 217

All experiments were performed in accordance with the relevant guidelines and 218

regulations for the care and use of animals in research and approved by the competent 219

Portuguese authority (Direccao Geral de Alimentacao e Veterinaria, permit 220

0421/000/000/2017). 221

222

223


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224

Acknowlegdements 225

We thank IGC Fish Facility for assistance on fish maintenance and Peter McGregor 226

for comments and discussion on an earlier version of the manuscript. The authors 227

declare no conflicts of interest related to this work. This work was funded by a 228

Fundação para a Ciência e a Tecnologia (FCT) research grant (PTDC/BIA-229

ANM/0810/2014) and a FEDER grant (Lisboa-01-0145-FEDER-030627) awarded to 230

RFO. ARN and MST were supported by Post-doc fellowships from Fundação para a 231

Ciência e a Tecnologia (FCT, ARN: SFRH/BPD/93317/2013). Congento LISBOA-232

01-0145-FEDER-022170, co-financed by FCT (Portugal) and Lisboa2020, under the 233

PORTUGAL2020 agreement (European Regional Development Fund). The authors 234

declare no competing interests. 235

236

Author contributions 237

R.F.O. and D.R. designed the research; D.R. and A.R.N. performed the research; 238

D.R., A.R.N. and M.S.T. carried out the molecular lab work; A.S., J.B. and G.L. 239

developed and validated the mutant zebrafish line; D.R. and M.S.T. carried out the 240

statistical analyses; D.R. and R.F.O. wrote the paper and all authors critically revised 241

the manuscript. 242

243

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Figure legends 330

331

Figure 1. The contribution of the social environment (Es) and genotype (G) to the 332

expression of behavioral phenotypes in zebrafish was assessed by raising oxytocin 333

receptor mutant fish and wild types (focal fish marked with *) in shoals of either 334

mutants or wild types (A). Social preference, measured by the time spend near a shoal 335

in a choice test (B), showed no effect of either G or Es (C). Social habituation, which 336

consisted on a consecutive social preference test exhibited a GxEs effect (D). Social 337

recognition, measured as the discrimination between a novel and a familiar 338

conspecific (E), shows a pure G effect (F). Social integration, measured as distance to 339

the centroid of the shoal (G), showed a GxEs effect (H). Social influence, measured by 340

the cohesion of the remaining shoal members (I), also showed a GxEs effect (J). Data 341

is presented as mean ± standard error of the mean (SEM). Sample sizes are 9 for 342

heterogeneous groups (i.e. focal individual with different genotype from the 343

remaining individuals in the shoal; mutant focal in WT shoals and WT focal in mutant 344

shoals) and 15 for homogeneous groups (i.e. focal individual with the same genotype 345

of the remaining individuals in the shoal; mutant focal in mutant shoals and WT focal 346

in WT shoals). Different letters indicate significant differences (p<0.05) between 347

treatments as assessed by Two-Way ANOVA followed by post-hoc tests (see Table 348

1). 349

350


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Tables 351

352

Table 1. Two-way ANOVA for ‘genotype’, ‘environment’ and their interaction 353

(‘genotype’ x ‘environment’) was analysed for each behavioural essay. * indicates p < 354

0.05, ** indicates p < 0.01, *** indicates p < 0.001. 355

Social Preference

d.f. Mean Squares F Significance

Genotype (G) 1 0.023 1.731 0.195

Environment

(E) 1

0.050 3.788 0.058

G x E 1 0.001 0.049 0.825

Error 44 0.013

Habituation


G 1 0.058 13.927 0.001 **

E 1 0.008 1.936 0.171

G x E 1 0.024 5.642 0.022 *

Error 44 0.004

Social Recognition


G 1 0.213 7.600 0.008 **

E 1 0.005 0.189 0.666

G x E 1 0.001 0.041 0.841

Error 44 0.028

Social Competence


G 1 39.486 24.370 <0.001 ***

E 1 12.565 7.755 0.008 **

G x E 1 12.811 7.907 0.007 **

Error 44 1.620

Social Group Dispersion


G 1 174.366 4.309 0.044 *

E 1 657.221 16.240 <0.001 ***

G x E 1 122.980 3.039 0.088

Error 44 40.469

356


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A B C

D E F

G H I J


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