Skip to main content
NCBI home page
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2023 Jul 26.
Published in final edited form as: Eur J Neurosci. 2021 Nov 2;54(10):7733–7748. doi: 10.1111/ejn.15500

Experiential modulation of social dominance in a SYNGAP1 rat model of ASD

E Harris 1,*, H Myers 1,*, K Saxena 1,2,*, R Mitchell-Heggs 1, P Kind 1,2, S Chattarji 2,3, RGM Morris 1,2,✉
PMCID: PMC7614819  EMSID: EMS177466  PMID: 34672048

Abstract

Advances in the understanding of developmental brain disorders such as autism spectrum disorders (ASD) is being achieved through human neurogenetics such as, for example, identifying de novo mutations in SYNGAP1 as one relatively common cause of ASD. A recently developed rat line lacking the calcium/lipid binding (C2) and GTPase activation protein (GAP) domain may further help uncover the neurobiological basis of deficits in children with ASD. This study focused on social dominance in the tube test using Syngap+/Δ-GAP (rats heterozygous for the C2/GAP domain deletion) as alterations in social behaviour are a key facet of the human phenotype. Male animals of this line living together formed a stable intra-cage hierarchy, but they were submissive when living with WT cage-mates thereby modelling the social withdrawal seen in ASD. The study includes a detailed analysis of specific behaviours expressed in social interactions by WT and mutant animals, including the observation that when the Syngap+/Δ-GAP mutants which had been living together had separate dominance encounters with WT animals from other cages, the two higher ranking Syngap+/Δ-GAP rats remained dominant whereas the two lower ranking mutants were still submissive. While only observed in a small subset of animals, these findings support earlier observations with a rat model of Fragile-X indicating that their experience of winning or losing dominance encounters has a lasting influence on subsequent encounters with others. Our results highlight and model that even with single-gene mutations, dominance phenotypes reflect an interaction between genotypic and environmental factors.

Keywords: Social neuroscience, autism spectrum disorders, social dominance, tube-test, cognitive compensation

Introduction

According to the World Health Organisation, as of 2019, 1 in 160 children worldwide develop autism spectrum disorder (ASD) (https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders). This neurodevelopmental disorder is characterised by early onset of impairments in social interaction and communication, limited interest in others, and the presence of repetitive or stereotypical behaviours (Parishak et al, 2013; Yoo, 2015). Multiple studies have identified de novo mutations in the Synaptic Ras GTPase-activating protein 1 (Syngap1) gene as a risk factor for ASD (Hamdan et al. 2011; O’Roak et al. 2014; Berryer et al. 2012).

The SYNGAP1 gene codes for a postsynaptic density protein primarily expressed in excitatory neurons (Walkup et al, 2016). The SYNGAP protein interacts with N-methyl-D-aspartate (NMDA) receptors and negatively regulates both Ras and Rap GTPase. Ras signalling activates the MAPK/ERK cascade, important for the induction and maintenance of long-term potentiation (LTP) via insertion of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors into the postsynaptic membrane. The Rap pathway mediates long-term depression (LTD) via p38MAPK. Hence, SYNGAP is expected to play an essential role in normal synaptic function and plasticity (Komiyama et al. 2002; Kim et al. 2003). Heterozygous Syngap+/Δ-GAP mice display strong excitatory/inhibitory imbalance in hippocampal and forebrain neural networks (Clement et al. 2012; Ozkan et al. 2014), an imbalance that has been proposed to be a contributor to the social deficits seen in ASD and other neuropsychiatric disorders (Yizhar et al. 2011). These neurobiological disruptions are associated with behavioural and cognitive phenotypes in murine models that mimic symptoms of the human condition such as elevated locomotor activity (hyperexcitability), impaired working and spatial memory, and a decreased sensitivity to painful stimuli (Guo et al. 2009; Muhia et al. 2010; Clement et al. 2012; Nakajima et al. 2019). The implicit supposition behind this animal work is that a single-gene mutation would primarily have a genetically deterministic effect on phenotype.

Few studies have addressed the altered sociability of Syngap mutations in rodents. A study looking at schizophrenic-like symptoms in mutant mice found Syngap+/- animals had reduced social memory (Guo et al, 2009). Specifically, while they gave similar results to wildtype (WT) mice in the three-chambered sociability test, they failed to distinguish between a familiar and novel conspecific mouse. Furthermore, in the laboratory, Syngap mutants are reported to spend more time alone than interacting with other animals (novel or familiar), and less social interaction in both novel and home environments compared to WT animals (Guo et al. 2009; Nakajima et al. 2019). As ASD is primarily a social communication disorder, further characterisation of social interaction in animals modelling SYNGAP mutations would be valuable. This new study is conducted using rats rather than mice, that are central to a wide-ranging Simons funded programme of research at Edinburgh.

The primary aim was to establish whether Syngap+/Δ-GAP rats are socially submissive and display a distinct profile of specific behaviours in social dominance interactions than WTs. Establishing a dominance hierarchy requires recognising social cues. Once established, a hierarchy usefully determines access to resources while minimising the need for aggressive conflict (Cummins, 2000; Fan et al. 2019). We used the dominance tube-test which is a behavioural assay of social dominance (Wang et al. 2014). It has been widely used as an assay of social hierarchy, such as to examine the relative dominance of different mouse strains (Kunkel & Wang, 2018), the neural circuits underlying dominance behaviour (Wang et al. 2011; Zhou et al. 2017), neuropsychiatric disorders such as major depression (Yang et al. 2014) and ASD-like syndromes (Huang et al. 2018; Saxena et al. 2018). With analogous results to other dominance tests, with which rankings correlate, it has been suggested as an accurate measure of social dominance (Wang et al. 2011). Mouse models have been used predominantly, but even they have been shown to reveal similar weanling dominance patterns to those of children (Chou et al, 2021).

A secondary facet of the study concerns the opportunity in social dominance interactions to learn about and remember the other animal/person - a dimension of social experience. One might then expect deficits arising from failures of social memory (e.g. about the identity or social status of another animal). However, that very deficit may indirectly foster the development of motor habits in social interactions that are less demanding on day-to-day memory but reflect learned patterns of dominance or submissive behaviour. Such habits are likely more inflexible such that, once learned, they would be expressed repetitively even in inappropriate situations. Accordingly, after the initial phase of testing interactions within each cage, we examined contests between animals from different cages that had by then assumed a particular intra-cage rank.

Rats are a species that is inherently social which has evolved a complex social repertoire (Lore and Flannelly 1977), and the outbred nature of the rats we used more closely mimics the genetic variation seen in humans. They may, therefore, be an appropriate model for the study of human psychiatric disorders characterised by deficits in social cognition (Ellenbroek & Youn, 2016). Saxena et al. (2018) studied FMR1 knockout (Fmr1-/y) rats as a model for Fragile-X Syndrome (FXS), another monogenic cause of autism that shares many of the behavioural deficits seen in Syngap+/- animals (Spencer et al. 2005; Kazdoba et al. 2014; Ding et al. 2014; McNaughton et al. 2008). As expected, male knockout rats were submissive to WT animals in mixed-line groups living together, a finding that makes sense in terms of model “validity”. However, a small number of high- and low-ranking FXS mutants who had lived together and formed an intra-cage hierarchy went on to display the same phenotype in inter-cage contests. Specifically, they won (or lost) social dominance contests against stranger animals regardless of stranger rank. This study explored social dominance in Syngap+/Δ-GAP mutants using the same experimental protocols as in our earlier study of FXS mutants (Saxena et al. 2018).

Materials and Methods

Subjects

Adult (>12 weeks, n=16) male Long-Evans hooded rats were used, weighing 500g to 600g. The rats were cohoused in groups of 4 per cage, from weaning, with ad libitum food/water and a 12h light/dark cycle. The cages contained a 25 cm long section of Perspex tube similar to the one used in the actual tube-test to allow the animals to become used to being inside such a tube. The colony founders were produced by Sigma Advanced Genetic Engineering (SAGE) labs (St. Louis, MO, US) using the zinc finger nuclease mediated deletion (Gurts et al. 2009) of the GAP domain of Syngap. Later rats for the experiments were bred in-house, the Syngap+/Δ-GAP rats were generated by mating female Syngap heterozygous rats with male WT Long-Evans hooded rats acquired from Charles River Labs, hereafter called ‘Het’. The WT animals used as controls were littermates. There was one WT single-line cage (n=4), one Het cage (n=4), and two mixed cages (nWT=2, nHet=2 per cage; overall n=8). All experiments were done blind to genotype, with animals being given a cage number on their tail and a coloured spot on their fur (using animal paint, red, green, blue, purple) to identify them, the colouring is random. The code was retained by someone independent of the study and only broken when all procedures had been completed. The genotype of the animals was confirmed externally before and after finishing the experiments by a company (Transnetyx).

Ethics and Legal Statement

The studies conducted were all behavioural and did not involve surgery or the administration of drugs. We monitored the animals carefully at all stages of handling and experimentation, particularly in Phase 2 (below) when animals from different cages were tested together. The study was conducted according to the regulations of the Animals (Scientific Procedures) Act 1986, a U.K. Project Licence held by RGMM (I49398628), and under the supervision of the named veterinary surgeons of the University of Edinburgh.

Apparatus

The tube-test assay was the same as used in Saxena et al. (2018). A transparent perspex tube, 1 m long and 7 cm diameter, served to connect two holding boxes (Fig. 1A). In each box, bedding was placed from the home cage of the animals to help reduce anxiety (Fig. 1B). The tube was large enough for the rats to move freely, but not to cross past each other or turn around. A removable metal grid was placed in the middle of the tube, this being lifted to start an encounter that ended when one animal retreated (Fig. 1C). A camera provided a direct view of the tube to record the trials using OBS recording software (https://obsproject.com/). The entire apparatus was connected to custom-made-Arduino-based hardware, and we used its serial reader functionality for reading the button-presses denoting the start/stop times of the trials.

Figure 1. Tube Test Apparatus and Protocol.

Figure 1

Open in a new tab

A, B) The plastic, transparent tube in which dominance interactions took place (arrow 1). A small metal grid barrier inserted at the tube centre point is used to separate the rats before the start of every trial (arrow 2). One of two holding boxes, filled with bedding from the rats’ home cages (3). C) Rats were placed at either end of the tube and they readily moved towards the centre point. When both rats reached the central grid barrier, the barrier was lifted and the start button pressed to begin the trial. The rats competed for dominance until the head of the “losing rat” moved past the entrance at either end of the tube. See supplementary movie. D) The two-phases of training. Phase 1 involved contests between all animals in each cage, this being repeated across 10 sessions to secure a mean measure of within-cage ranking. Cartoon depicts all 6 inter-animal contests. Phase 2 consisted of competitions between cages and involved all the animals of one cage and all the animals of the other cage (4 animals (cage1) x 4animal (cage 2) = 16 animal pairs). For clarity, the cartoon depicts only one exemplar rat (green) competing against all rats of the other cage. In phase 2, there were in 4 cages in total that competed against each other.

Behaviour Protocols

The training protocol consisted of Habituation, Phase 1 Contests between animals within a cage (intra-cage), and a Phase 2 Competition involving all animals in one cage against all the other cages (Fig. 1D; inter-cage). The experiments were performed between 9 am to 4 PM. There were a total of 2640 competitions between individual animals.

Habituation

Each animal was handled for 3 days and allowed to run freely in the apparatus (alone) for at least 10 min per day. See details of procedure in Saxena et al (2018).

Phase 1 Intra-Cage Contests

The basic tube-test consisted of two rats being placed in the holding boxes, one on each side. The rats then entered the tube and met in the middle with the metal grid present and acting as a barrier. The trial started when the barrier was removed. During the trial, the rats competed for dominance during which a variety of behaviours were observed. Typically, the animals were together, their heads side-by-side and relatively still for a few sec. Thereafter, either one rat pushed the subordinate to retreat out of the tube (dominant), or the other rat withdrew of its own accord (subordinate). A trial was defined as ending when one rat backed out into the holding box from which it started. This rat was recorded as the “loser” and the other as the “winner”. Each pair of rats underwent 5 trials each session to obtain a secure measure of dominance (3:2, 4:1 or 5:0), alternating their starting positions between left or right. All cages were tested on the same day, with the 10 sessions of 5 trials on consecutive days. The order in which the cages were trained each day was randomised in counterbalanced order.

To observe and measure intra-cage hierarchies, each animal competed against all the other animals in its cage (5 runs per pair, 6 competitions/cage). Cage ranks were determined by adding up the number of wins or losses for each animal across all six encounters (of 5 trials) within a cage. The animal with the most wins was denoted as 1st rank. The following ranks correspond to increasing number of losses with the 4th rank animal being the one losing the most. If two animals had the same number of losses, the relative rank was determined by which animal lost most of that pair. This daily tube-test assay was repeated over 10 sessions. There were, therefore, 4 cages x 6 encounters x 5 runs x 10 sessions (= 1200). Trial latency was taken as the time (sec) to complete one trial.

Phase 2 Inter-Cage competitions

The procedure to conduct tube-tests was exactly as above, but the animals now competed against animals in the other cages who were, effectively, stranger opponents. Each animal competed against all four animals from the other 3 cages. Each trial between a pair was repeated 5 times and all trials were repeated over 3 sessions. This comes up to a total of 1440 trials (6 cage interactions × 16 encounters × 5 runs × 3 sessions). We analysed only the 1st and the 3rd sessions for the detailed video analysis of behaviour, giving 6 × 16 × 5 × 2 contests (= 960). The sequence of pairs and cages was randomised across the 3 sessions.

Video Analysis

Recordings from sessions 1 and 10 of Phase 1 and sessions 1 and 3 of Phase 2 were analysed, on a frame-by-frame basis (1/20th sec resolution per frame) using Behavioural Observation Research Interactive Software (BORIS) Friard & Gamba (2016), with these sessions chosen for this detailed analysis as the beginning and end of each phase. Behaviours were logged for each animal as follows: PUSH (included any form of pushing, with paws, nose or body and biting), RESIST (resisting a push from an opponent), MOVE FORWARD, STILLNESS (when no displacement of the body was seen, but including other stationary activities such as sniffing or grooming), RETREAT (backing out of the tube by being pushed) and WITHDRAWAL (voluntarily backing out of the tube). It proved easy to distinguish PUSH and RESIST despite being quite similar in terms of effort.

Statistical analysis

For all statistical analyses, we chose tests based on the data secured (wins, latency, behaviour occurrences). Values computed include total number (e.g. of wins), from which rank was derived, and means (latency, rank), occurrences of specific behaviours, and measures of variability of rank (stability/variance). Stability was computed by counting the number of times an individual rat changed rank during phase 1 without regard to whether it changed by one position of rank or more, and these data were normalised (100% stable meaning no changes in rank across the 10 sessions, 0% meaning a change every session). Variance was a similar measure and computed as the true variance of the rank scores across all 10 sessions of phase 1. For latency and behaviour occurrences, we computed mean and standard error of the mean. For all parametric tests, the data fitted the assumptions of equal variance and were normally distributed (ANOVA and t-tests). For non-parametric tests, Mann-Whitney, Chi-squared or a Fisher’s exact test were used. The behavioural occurrences analysis for both Phase 1 and 2 required a Two-way repeated measures ANOVA, with the different behaviours treated as a ‘repeated measures’ within subject variable. This was paired with a Sidak’s multiple comparison test. The value computed in each test (e.g. F-ratio), significance levels and degrees of freedom are reported. GraphPad Prism v7 was used for preparing the graphs and statistics, and then displayed using Adobe Illustrator.

Results

Qualitatively, all animals explored the tube readily during habituation, and walked through it without hesitation during dominance contests. We anticipated that frequent losers might become hesitant to enter or walk through the tube over time but, surprisingly, this did not happen. We observed no signs of overt inter-animal aggression, even in contests across cages, and its absence may have contributed to the success in training of both phases of the study. All encounters were conducted and evaluated “blind” to genotype, and the occupants of each cage was unknown to the experimenters. Although the number of animals in the study was modest (n=16; WT, n=8, Syngap+/Δ-GAP n=8), the number of contests observed was extensive (n=2160).

Phase 1 Contests

The first question was whether single-line WT animals living together, and Syngap+/Δ-GAP animals likewise (hereafter called ‘Het’), would each form a hierarchy. Ranks of individual animals in single-line cages are shown in Fig. 2A, with both the WTs (as expected) and Hets forming a hierarchy. The 1st ranked Het rat stayed at the top over all 10 sessions, all other ranks stabilising by session 7. The mean rank was calculated from the ranks of each animal over all 10 sessions. A clear hierarchy was seen in both cages (Fig. 2B), there was a statistically significant difference between ranks as determined by one-way ANOVA (WT: F(3,39) = 33.45, p = 0.0001; Het (F(3,39) = 27.89), p = 0.0002). No differences were observed in normalised stability (unpaired t-test, t=0.134, df=6 p=0.898, Fig. 2C) or variance of rank between WT and Het animals over the 10 sessions (Mann-Whitney test, p=0.829).

Figure 2. Phase 1 - Establishment of intra-cage hierarchy in single line cages.

Figure 2

Open in a new tab

A) Cage hierarchies: Plot of individual animal rank across all 10 sessions for WT and Het single-line cages. The 4 colours represent each cage individual, the colour code plotted in accordance with average rank across all 10 sessions. B) Mean ranks and individual data points (for each session) of the WT cage (blue) and Syngap ‘Het’ cage (Orange) showed significant hierarchies in both cages (WT: F (1.378, 12.40)=33.45, p=<0.0001, with Greenhouse-Geisser correction for degrees of freedom; Het: F (1.138, 10.24)=27.89, p=0.0002). C) No significant differences were observed between WT and Het lines with respect to either Stability (two-tailed, unpaired t-test, t(6)=0.195, p=0.852, n=4) or Variance. (t-test, t(6)=0.193, p=0.853, n=4). Means ± 1 SEM. * indicates p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, in Tukey’s multiple comparison test. See main text for details.

The next step was to examine the hierarchies formed in each of the two mixed-line cages. Both cages showed an overall hierarchy (Fig. 3a). Het rats in mixed cages won less contests than the WT animals (Chi-squared test of independence, X2=68.06, df=1, p<0.0001; Fig.3B). Het animals also had a lower average rank of 3.18 ± 0.15 over 10 sessions compared to WT animals with an average rank of 1.83 ± 0.13 (unpaired t-test, t=6.69, df=78, p<0.0001, Fig. 3B; the highest rank score = 1). Both comparisons were highly significant. Averaged across the two cages, there was no overlap of mean rank between the WT and Het rats (Fig. 3A). With respect to trial-to-trial variability, no significant difference was detected between WT and Het animals on measures of rank stability (unpaired t-test, t=1.32, df=6, p=0.235, Fig. 3C) or variance (unpaired t-test, t=1.12, df=6, p=0.304, Fig. 3C).

Figure 3. Phase 1 - Establishment of intra-cage hierarchy in mixed-line cages.

Figure 3

Open in a new tab

A) Cage hierarchies: Plot of individual animal rank across all 10 sessions for WT and Het single-line cages. The 4 colours represent each cage individual, the colour code plotted in accordance with average rank across all 10 sessions. There was no overlap between the more dominant WT (blue) and more submissive Het animals (Orange), although the three submissive WTs were broadly comparable to the most dominant Het. B) Contest wins and average rank in the mixed cages: There were highly significant differences between the number of wins (X2=68.06, df=1, p<0.0001) and average rank of WT and Het animals (t=6.73, df=78, p<0.0001). C) As in the single-line cages, there was no differences were observed with respect to either Stability (unpaired t-test, t(6)=1.321, p=0.235) or Variance (t(6)=1.124, p=0.304). Means ± 1 SEM. **** p<0.0001.

The pair-wise competitions took time (Fig. 4). Competitions took longer at the beginning of the series of 10 sessions, averaging 19.5 ± 4.84 s from the moment the barrier between the two animals in the tube was raised and the point when one of them fully retreated, but this time declined to less than 10 s by session 3 (8.27 ± 0.74 s; Fig. 4A) and then stabilised. This overall decline was significant (One-way repeated measures ANOVA, F9.207=4.92, p=0.0094, Fig. 4a). The pattern for latencies for the 50% subset of mixed-line cages was much the same (One-way repeated measures ANOVA, F9.99=5.08, p=0.032, Fig. 4b). For the single-line cages, Het animals displayed longer latencies than WT (Two-way repeated measures ANOVA, F1.6=12.3, p=0.0056, Fig. 4c).

Figure 4. Phase 1 - Time taken to complete individual contests (Latency).

Figure 4

Open in a new tab

A) Average latency of trials (s) from all pairs of rats from all cages over 10 sessions (n=16). B,C) Average latency for mixed cages (n=8) and single line cages (n=8). Note longer time taken by Het animals in the single-line cages. For all graphs, individual latency data points for each pairing are not shown in order to increase clarity of results. Means ± 1 SEM.

A key next question was whether the specific patterns of behaviour (e.g. PUSH, RETREAT) displayed during dominance encounters differed as a function of dominance or genotype. The video analysis showed a clear interaction between rank and behaviour occurrences (Two-way repeated measures ANOVA, F5.70=4.54, p=0.0012, Fig. 5a). The trend shows High-Rank animals were more likely to PUSH and MOVE FORWARD compared to the Low-Rank animals who executed more RETREAT and WITHDRAWAL. In certain respects, such a pattern must occur by definition. However, the high occurrences of STILLNESS in High-Rank animals was not expected a priori. One complication in quantifying the “occurrences” of such behaviours is that PUSH behaviour may occur several times during a trial, often met by RESIST behaviour from the other animal. However, RETREAT happens less frequently and may, in the limit, happen only once to resolve a contest. Attempting to “normalise” their relative behaviours to create a numerical “level playing field” by examining occurrences over durations of time in order to calculate a measure of frequency does not help, as pushing can start and stop throughout a trial and thus the full duration of the trial would have to be considered the duration; but equally, retreat can happen at any time, even if only once, and thus the duration of time for calculating frequency is the same. However, the overall higher behaviour occurrences of the single-line Het cage than the single-line WT cage (Fig. 5b,c) is consistent with the latency data of Fig. 4. Moreover, the significant interaction between rank and behaviour (Two-way repeated measures ANOVA, F5.30=4.46, p=0.0037, Fig. 5d) was observed only in the mixed-line cages in which the high-rank animals were, in practice, WT rats.

Figure 5. Phase 1 - Patterns of behaviour observed during contests.

Figure 5

Open in a new tab

A) Sum of occurrences of various behaviours by individual animals plotted as a function of overall rank, together with individual animal data (n=16). High rank is animals in Ranks 1 or 2 of a cage (green), Low-Rank is animals in Ranks 3 and 4 of a cage (red). B) Sum of occurrences of behaviours by WT animals living together (n=4). C) Sum of occurrences of behaviours by Het animals living together (n=4). Note high occurrence of “STILLNESS” in this cage (>40) but not the WT cage (<20). D) Sum of occurrences of behaviours by high- and low-rank WT and Het animals living together in mixed cages (n=8). Note that STILLNESS is again high, but in these cages restricted to the High-Rank animals (i.e. the WT rats). For all graphs, behavioural occurrences were taken as an overall count of each behaviour for each animal over 240 trials from Phase 1, sessions 1 and 10. Means ± 1 SEM.

With respect to STILLNESS behaviour, frequently occurring while the two animals are in close contact and during which dominance “decisions” may be being made, single-line Het rats animals had a significantly higher STILLNESS occurrences than single-line WT animals (Sidak’s multiple comparison test, p=0.0131; compare Fig 5c with 5b). This was not observed in the mixed cages (unpaired t-test, t=0.732, df=6, p=0.492; data not shown), for which the primary determinant of STILLNESS was rank (Fig. 5d).

Phase 2 Inter-Cage Competitions

The second phase of testing was an inter-cage tournament in which the animals underwent tube-test competitions against all animals from the other cages. In contrast to Phase 1 in which WT animals were clearly dominant, the phenotype now reflected some facets of the rank of the animals in Phase 1. Intriguingly, Het animals now won as equally often as WT rats (Fisher’s exact test, p=0.553, Fig. 6a). In fact, the Hets in single-line cages won significantly more competitions against single-line WT animals from different cages (Fisher’s exact test, p=0.0321, Fig. 6b), whereas Mixed-cage Het rats lost more contests against stranger mixed-cage WT animals (Fisher’s exact test, p=0.0152, Figure 6c). These changes are identical to what was observed by Saxena et al (2018) in a rat model of FXS.

Figure 6. Phase 2 - Competitions between animals from different cages as a function of genotype and rank predicted from Phase 1.

Figure 6

Open in a new tab

A) The overall phenotype of WT dominance phenotype of Phase 1 was lost in Phase 2 - WT and Het animals won an equivalent number of contests. B, C) Contests won by WT and Het animals that had lived in single-line cages (B, n=4 per cage) or Mixed-Line cages (C, n=4 per cage). Note that Het animals from single-line cages won more contests in Phase 2, whereas WT animals from Mixed-line cages won more contests. D) Predictive rank: when wins and losses in Phase 2 are plotted as a function of Rank secured by animals in Phase 1 (High vs. Low), the phase 1 rank is predictive of the outcome of contests in Phase 2. E) In contests between High-rank animals (n=6, WT; n=2 Het), the Het animals won far more contests. F) In contests between Low-rank animals (n=2 WT, n=6 Het), the total number of wins was equivalent. Means ± 1 SEM. * p<0.05, *** = p<0.001, indicates p<0.0001. See text for details and comments on numbers of animals.

One possibility is that rank was simply unstable between Phases 1 and 2 and, that there are major reliability issues with the measures being quantified and the experimental approach being taken. However, rank in Phase 1 (regardless of genotype) was predictive of winning/losing in Phase 2 (Fig. 6d). That is, the overall number of wins in Phase 2 by animals that were High-Rank in Phase 1 was significantly higher than those of Phase 1 Low-Rank animals (Fisher’s exact test, p<0.0001). This indicates that previous experience of winning or losing can be predictive of the outcome of competing against a stranger.

Logic then required us to distinguish high-rank and low-rank animals as a function of genotype. In a single-line cage, there will be two animals in ranks 1 and 2 which we shall refer as “high rank” and the other two animals (ranks 3 and 4) as “low-rank”; this is also true of the Het single-line cage than of the WT single-line cage. One possibility is that a Het winner may “get used” to winning and a Het loser “get used” to losing - i.e. their social dominance interactions become habits, possibly because of a deficit in social perception or memory. The ten sessions of 5 encounters per session in Phase 1 provided 50 trials between a pair in which to develop habits in the tube-test, such as habits of pushing or retreating etc. Interestingly from the perspective of habit vs. memory, High-Rank Het animals won significantly more competitions against High-Rank WT rats (Fisher’s exact test, p=0.0009, Fig. 6e), whereas Low-Rank Hets performed equivalently to Low-Rank WT rats when competing against them (Fisher’s exact test, p>0.99, Fig. 6F). By the same argument, Het animals living in mixed-cages (generally in ranks 3 and 4) would be expected to be submissive to single-line WTs - which they were (Fisher’s exact test, p=0.0321), having a developed a habit of withdrawal and retreat.

These findings in Phase 2 are statistically significant, but modest, as they entail comparisons between subsets of animals with an “n” of only 2, 4 and 6. Nonetheless, they raise the possibility that there may be a difference between winning when you can process social cues effectively and winning when you cannot. Variations in the occurrences of distinct behaviours in the tube may reflect these differing states of affairs. Overall, behaviour and rank interacted significantly to affect the behavioural occurrences (Two-way repeated measures ANOVA, F5.70=4.40, p=0.0015, Fig. 7a), but there was no significant interaction between behaviour and genotype (Two-way repeated measures ANOVA, F5.70=0.39, p=0.854, Fig. 7b). This data suggests that, in the inter-cage contests of Phase 2, previous experience determines future behaviour more than genotype.

Figure 7. Phase 2 - Patterns of behaviour observed during contests (sessions 1 and 3).

Figure 7

Open in a new tab

A) In Phase 2, there was modest but a significant difference between rank and behaviour subtypes. The trends suggest high-ranking animals showed more moving forward and stillness but less retreat. B) No significant difference in behaviour subtypes were observed when WT animals were compared with Het. C) Analysis of only the contests between high-ranking WT and Het animals revealed striking interaction was found between high-ranking WT and Het animals and social behaviour subtype (ANOVA; F(5,30)=8.807, p=<0.001). The data reveals high-ranking Het displayed more of every behaviour subtype except withdrawal. D) The opposite pattern prevailed for trials only involving the contests between low-ranking WT and Het animals: (ANOVA; F(5,30)=18.99, p=<0.001). For all graphs, behavioural occurrences were taken as an overall count of each behaviour for each animal over the 960 trials of sessions 1 and 3 of Phase 2. Means ± 1 SEM. ** indicates p<0.01, **** indicates p<0.0001.

As the data on combined effect of rank and genotype was revealing with respect to dominance, it might also have affected behaviour occurrences. For trials between high-ranking animals, genotype interacted significantly with behaviour (Two-way repeated measures ANOVA, F5.30=8.81, p<0.0001, Fig. 7c), with genotype accounting for a significant amount of the variance seen in the behavioural occurrences (Two-way repeated measures ANOVA, F1.6=42.57, p=0.006). A trend reveals that high-ranking Het animals had a higher occurrence of PUSH, MOVE FORWARD, STILLNESS and RESIST behaviours compared to High-Rank WT. This indeed complements the findings in Fig. 6e as an increase in these behaviours would explain the increased number of wins. For competitions between low-ranking rats, there was also a significant interaction between genotype and behaviour but in the opposite direction (Two-way repeated measures ANOVA, F5.30=19.0, p<0.0001, Fig. 7d). The overall behavioural occurrence was now relatively higher in WTs (Two-way mixed-model ANOVA, F1.6=78.7, p=0.0001, Figure 7d), and specifically, Low-Rank WT animals had a higher occurrence of PUSH behaviour (mean ± SE = 68.0 ± 1.41) than Low-Rank Het animals (mean ± SE = 21.7 ± 2.26) (Sidak’s multiple comparison test, p<0.0001, Fig. 7d). This would suggest the WT should be dominant over the Het animals but, as shown in Fig. 6f was not the case. The reason may be that Low-Rank WT animals also had a high RETREAT occurrence (Sidak’s multiple comparison test, p=0.0091).

Discussion

The aim of this study was to examine the generality of the idea that ASD model animals would show consistent changes in social dominance relative to WT animals. Using a social dominance tube-test paradigm, we observed that male Het Syngap+/Δ-GAP animals living together form a stable hierarchy but, when living with WT animals, have a submissive phenotype compared to their WT cage-mates. This models social withdrawal and is analogous to what we observed with FXS mutants (Saxena et al, 2018). Specific behaviours exhibited during the tube-test included expected facets (such as greater PUSH behaviour by dominant animals), but also a striking increase in STILLNESS behaviour by the Het animals housed in the single-line cage and a higher latency to resolve conflicts when two Het animals competed, both suggestive of a social processing deficit. We also found that social dominance experience affects subsequent interactions, interacting in a subset of animals in a surprising way with genotype. Het animals (n=2) that were previously dominant in single-line cages in the intra-cage analyses (Phase 1) of the study were, in the inter-cage (Phase 2) tournaments, also dominant against all animals from other cages including previously dominant WT rats (n=6). Het animals (n=6) that were previously submissive continued to be largely submissive. These observations are subject to the qualification of small “n” (2 and 6 respectively), but they do replicate in another ASD line the paradoxical reversal of phenotype observed in a much larger number of FXS mutants by Saxena et al (2018). They also add to earlier observations of some similarities between Syngap and FXS mutant mice despite various differences (Barnes et al, 2015). We shall argue that these data collectively point to a reduced ability of Syngap+/Δ-GAP animals to process social cues.

The patterns we observed resemble behaviours observed in ASD children. More severely impaired individuals show rigid operant learning in which they continue to use a previously learned strategy, even across different contexts (Stanfield, A. pers. comm). Moreover, children with autism are both more likely to be “bullied” by their siblings but also to “bully” them back (Toseeb et al. 2018). Perhaps these behaviours, once they develop, become inflexible habits. The dual phenotype of Syngap+/Δ-GAP behaviour we observed, from the submissive Het animals living in the mixed cages through to the suggestion of dominant single-line Hets winning novel encounters, may model this facet of the apparently opposing behaviours seen in ASD children. In Katsanevaki et al’s (2020) original study of this line of Syngap+/Δ-GAP rats, they observed a failure to extinguish a conditioned fear response despite many sessions of “extinction”. They saw normal sociability as measured by proximity, but the mutants showed a striking decrease in active sniffing of the other animal. Interestingly, in a study of both children and weanling mice, Chou et al (2021) show that (normal) children who are less persistent in games, have low emotional intensity and withdraw from social encounters easily, are more likely to be subordinate. They go on to show, in a demonstration of face-validity, that tube-test contests between mice tend to be resolved most often by loser withdrawal. Collectively, these results highlight and model the current belief that ASD reflects environmental interactions with a genetic predisposition (Chaste & Leboyer, 2012). Thus, depending on their rearing environment and previous social history in competitive interactions, children and animals with an ASD mutation (FMR1, SYNGAP1) may present different behavioural phenotypes.

The pattern of behavioural findings

Syngap1 mutations in mice lead to severe cognitive impairment, including deficits in social memory (Guo et al. 2009; Komiyama et al. 2002; Muhia et al. 2010; Ozkan et al. 2014). The Syngap+/Δ-GAP animals living in mixed cages were clearly submissive to their WT cage-mates, and thus both WTs were in ranks 1 and 2. This is a similar phenotype to the Fmr1-/y rats of Saxena et al (2018).

We also reasoned that Syngap+/Δ-GAP rats would be able to form a hierarchy but that it would be less stable than WT animals, as seen in the Fmr1-/y model of ASD (Saxena et al. 2018). We found, however, that the Het rats were not only able to form a hierarchy, but did so with statistically similar stability and variance of rank to WT. Although there are some exceptions (e.g. the purple rat in the WT single line cage that changed its rank 7 out of 9 times, and the red animal in the Mixed cages 1 and cage 2), some of the Het rats were more stable than the WTs in the mixed cages. These results suggest that Het animals may have enough social memory to distinguish between the ranks of the conspecifics with whom they are living. It is possible that rank stability observed in Hets reflects a lack of motivation, or a tendency to “give up” easily by rats in the lower order of hierarchy.

The Syngap+/Δ-GAP animals living in mixed cages being submissive to their WT cage-mates, during encounters against novel conspecifics (the inter-cage assessments in Phase 2), we found that High-Rank Syngap+/Δ-GAP animals won over the High-Rank WTs whereas Low-Rank Syngap+/Δ-GAP animals showed a different pattern. In presenting these results, we noted the qualification that the numbers of animals in these comparisons (2 and 6) were small, but it should be recognised that the number of competitions they undertook was quite large. What is suggestive is that these are very similar results to Saxena et al’s (2018) FXS model, raising the possibility that both Fmr1-/y and Syngap+/Δ-GAP rats are poorer in detecting social cues relating to the dominance status of an opponent. Faced with this cognitive deficit, they may therefore develop habits of repetitive behaviour during Phase 1 that serve them well. Specifically, High-Rank Syngap+/Δ-GAP animals would have won more frequently against Low-Rank animals in their single-line cage (10 sessions of 5 trials per inter-animal encounter (i.e. 100 trials for the 2 animals in each sub-group). This training may have been sufficient to develop habits such as extensive pushing, or resisting against pushes by the other animal, and that once learned, these behaviours would have continued into Phase 2. Such habitual patterns might also have been acquired by dominant WT animals but they could, each time, better appraise their opponent by providing and receiving social cues. Repetitive behaviours have been observed in Syngap+/Δ-GAP mice, with the animals having a higher stereotypic count in an open field test than WT (Guo et al. 2009). In our study, High-Rank Syngap+/Δ-GAP animals PUSHED significantly more than the High-Rank WT suggesting they simply repeated a learned PUSH behaviour, whereas the WT rats adapt flexibly to the changing social environment.

An additional point is that Syngap+/Δ-GAP animals in single-line cages showed significantly increased STILLNESS occurrence (Fig 5d), a pattern that carried over to the inter-cage tournaments for the high-rank animals. Alterations in these animals’ ability to detect social cues could be a cause of both the high STILLNESS occurrence and the longer latencies to resolve competitions when confronted by another Syngap+/Δ-GAP animal. We recognise that it is speculative to relate these findings to the work on bullying by Toseeb et al (2018), but worth noting nonetheless.

Neurobiological considerations

The medial prefrontal cortex (mPFC) and adjacent anterior cingulate gyrus have been implicated in decision-making during dominance encounters (Zhou et al, 2017; Nelson et al, 2020). Decreased connectivity between mPFC and the primary somatosensory cortex has been previously observed in Het animals (Aceti et al. 2015). A separate study noted Syngap+/Δ-GAP mice had lowered excitability in the upper lamina somatosensory neurons which encode touch-information (Michaelson et al. 2018). Syngap+/Δ-GAP animals also have altered volume of cortical areas related to visual system processing (Kilinc et al. 2018). These findings suggest that Syngap mutants may have decreased sensory perception and processing that affects their social communication.

Accelerated maturation during development leads to enlarged mushroom shaped spines with clusters of AMPA receptors (Kim et al. 2003; Vazquez, 2004; Aceti et al. 2015; Clement et al. 2012). In addition, they have a more than 50% reduction in the SYNGAP protein known to be important in synaptic transmission (Komiyama et al. 2002, Jeyabalan & Clement, 2016). Interestingly, striking observations have been made in hIPSC derived human neurons in which Syngap1 was deleted using CRISPR/Cas9 technology (Llamosas et al, 2020). Previous studies in normal WT mice have suggested that increased synaptic strength in the mPFC leads to more dominant behaviour and that it may be the “neurobiological foundation for dominance-associated personality traits” (Wang et al. 2011, McMahon et al, 2012, Zhou et al. 2017). We therefore wonder whether Syngap+/Δ-GAP rats have defective synapses in association with their submissive phenotype. It cannot, however, be a simple reduction in strength or efficacy as Syngap+/Δ-GAP adult mice have been found to have higher occurrence and amplitude of miniature excitatory post-synaptic currents (mEPSCs) in layer 2/3 mPFC neuron slices, pointing to an increase in unitary synaptic strength (Ozkan et al. 2014). Were this to be seen also in mPFC, Zhou et al’s (2017) data predicts these animals might even be more dominant. Based on these findings, Syngap+/Δ-GAP animals may sometimes be capable of displaying a more dominant phenotype.

One possible explanation for this contradiction is that the submissive Syngap+/Δ-GAP phenotype is caused by reduced LTP at mPFC synapses. Wang et al. (2011) found that transgenic manipulations that increase AMPA receptor trafficking to the post synaptic membrane led to an increase in rank in the tube-test whereas reducing it led to a decrease. Subsequently, Zhou et al. (2017) described the “winner effect” wherein repeated winning in the dominance tube-test caused strengthening of mPFC synapses via LTP and changed the rank of an animal, an effect that could be mimicked by optogenetic activation of thalamic inputs to mPFC. This suggests that an LTP-like process can be important in establishing dominance in normal animals. Multiple studies have found reduced LTP in CA1 hippocampal regions of Syngap+/Δ-GAP rodents, associated with elevated basal levels of Ras signalling in Syngap mutants which prevents further Ras activation upon synaptic stimulation and thereby inhibits LTP (Komiyama et al. 2002; Kim et al. 2003; Ozkan et al. 2014; Kilinc et al. 2018). If these findings from hippocampus synapses generalise to other brain regions, Syngap+/Δ-GAP animals could have reduced LTP in other regions including the mPFC. This deficit could limit their ability to adjust their behaviour flexibly in response to experience and so cause them to fall back on well-learned habits.

Limitations and future directions

This study builds upon previous research addressing Syngap mutant rodents as models for ASD, but is not without limitations. First, it would be valuable to train additional cohorts of Syngap animals as they become available. Second, in keeping with the 3Rs (reduction, refinement and replacement), we used a small but not inappropriate number of animals in the present study which were all male. Although the full data set was large and many facets of the statistical findings are robust, reproducing these experiments with both genders and multiple cages might allow higher confidence in the findings. They are, nonetheless, in line with the behavioural phenotype of Syngap mutant mice in revealing social withdrawal, repetitive behaviour and hyperactivity. Third, additional dominance tests, using different sensory or motor properties, need to be done to be conclusive about the generality of the dominance phenotype of Syngap+/Δ-GAP rats (Wang et al. 2014; Fan et al. 2019). Such investigations should include examining the development of habits that compensate for the loss of social flexibility. Fourth, we have relied on published data in mice with respect to three-chamber tests of social novelty to claim that Syngap+/Δ-GAP rats may have a deficit in social memory. Clearly this should be tested directly in rats also, but the test should not only include this classic test of social memory (Crawley, 2006) but also some way of assessing whether animals can encode and remember the dominance status of a novel opponent (and not just its identity). Finally, one interesting future test would be to examine whether changes in rank can be induced by artificial induction of winning in subordinate Syngap+/Δ-GAP animals. This could be done by optogenetic activation in the thalamic to prefrontal cortex pathway, as seen in Zhou et al’s (2017) study. Such a study might be conducted in conjunction with a therapeutic intervention, such as by the reintroduction of Syngap protein in a Syngap+/Δ-GAP line of rats, in the manner of classic “genetic rescue” studies of Rett syndrome (Guy et al, 2007). Alternatively, it might be done pharmacologically such as by restoring Ras signalling which is reported to improve cognitive deficits in mouse models associated with ASD (Ogden et al. 2016; Asiminas et al, 2019).

Abbreviation List

ASD

Autism Spectrum Disorder

BLIND

when experiments are conducted without the experimenter knowing the genotype or other information about the subjects or protocol that could bias their observations (an aspect of unconscious bias)

BORIS

Behavioural Observation Research Interactive Software

C2

calcium lipid binding protein

FMR1

The gene Fragile C mental retardation 1

FXS

Fragile X

GAP

GTPase activation protein. GTPases are a large family of hydrolase enzymes that bind to the nucleotide guanosine triphosphate (GTP) and hydrolyze it to guanosine diphosphate (GDP)

Het

heterozygous knock-out animal (in this case Syngap+/Δ-GAP)

LTP

Long term potentiation

MAPK/ERK

Mitogen-activated protein kinases and extracellular signal-regulated kinases mEPSC - miniature excitatory post-synaptic current

mPFC

medial prefrontal cortex

NMDA

N-methyl-D-aspartate

Rap

A protein named after “Rat sarcoma virus” that belongs to a class of protein called small GTPase which are involved in transmitting signals within cells (cellular signal transduction)

Ras

also a GTPase which is similar in structure to Rap

SAGE

Sigma Advanced Genetic Engineering

SYNGAP1

a gene that makes a protein called SynGAP which is found at the junctions (aka ‘gaps’) between synapses

Syngap+/Δ-GAP

(rats heterozygous for the C2/GAP domain deletion)

WHO

World Health Organisation

WT

wild-type

Footnotes

Conflict of Interest

All authors declare no conflicts of interest regarding this work.

Roles

Emma Harris – conducted the study and prepared first drafts of figures.

Honor Myers – conducted the study and prepared first drafts of figures.

Kapil Saxena – set up the apparatus, secured the animals and provided day-to-day supervision.

Rufus Mitchell-Heggs – advised on suitable analyses and contributed to the text.

Peter Kind – grant holder and commented on drafts of the text.

Shona Chattarji – grant holder and commented on drafts of the text.

Richard Morris – laboratory principal investigator, designed the study, modified the figures, and wrote the manuscript.

Supplementary Video

The videos are accessible at: https://datashare.ed.ac.uk/handle/10283/4005

Acknowledgements

The authors thank Patrick Spooner for building the apparatus and to the Simons Foundation for the Developing Brain (Edinburgh) for funding.

Data availability

Raw data for all figures (Excel), the details of all of the statistics done along with an example video is uploaded in a data repository (https://datashare.ed.ac.uk/submit?workspaceID=6884).

References

  1. Aceti M, Creson T, Vaissiere T, Rojas C, Huang W, Wang Y, Petralia R, Page D, Miller C, Rumbaugh G. Syngap1 Haploinsufficiency Damages a Postnatal Critical Period of Pyramidal Cell Structural Maturation Linked to Cortical Circuit Assembly. Biological Psychiatry. 2015;77(9):805–815. doi: 10.1016/j.biopsych.2014.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Asiminas A, Jackson AD, Louros SR, Till SM, Spano T, Dando O, Bear MF, Chattarji S, Hardingham GE, Osterweil EK, Wyllie DJA, et al. Sustained correction of associative learning deficits after brief, early treatment in a rat model of Fragile X Syndrome. Science Translational Medicine. 2019;11:eaao0498. doi: 10.1126/scitranslmed.aao0498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Berryer M, Hamdan F, Klitten L, Møller R, Carmant L, Schwartzentruber J, Patry L, Dobrzeniecka S, Rochefort D, Neugnot-Cerioli M, Lacaille J, et al. Mutations inSYNGAP1Cause Intellectual Disability, Autism, and a Specific Form of Epilepsy by Inducing Haploinsufficiency. Human Mutation. 2012;34(2):385–394. doi: 10.1002/humu.22248. [DOI] [PubMed] [Google Scholar]
  4. Chaste P, Leboyer M. Autism risk factors: genes, environment, and gene-environment interactions. Dialogues in clinical neuroscience. 2012;14(3):281–292. doi: 10.31887/DCNS.2012.14.3/pchaste. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chou Y-J, Lu Y-H, Ma Y-K, Su Y-S, Kuo T-H. The decisive role of subordination in social hierarchy in weanling mice and young children. iScience. 2021;24:102073. doi: 10.1016/j.isci.2021.102073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Clement J, Aceti M, Creson T, Ozkan E, Shi Y, Reish N, Almonte A, Miller B, Wiltgen B, Miller C, Xu X, et al. Pathogenic SYNGAP1 Mutations Impair Cognitive Development by Disrupting Maturation of Dendritic Spine Synapses. Cell. 2012;151(4):709–723. doi: 10.1016/j.cell.2012.08.045. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Crawley JN. What’s wrong with my mouse? Second Edition. Wiley; New York: 2006. [Google Scholar]
  8. Creson T, Rojas C, Hwaun E, Vaissiere T, Kilinc M, Jimenez-Gomez A, Holder J, Tang J, Colgin L, Miller C, Rumbaugh G. Re-expression of Syngap protein in adulthood improves translatable measures of brain function and behavior. eLife. 2019;8 doi: 10.7554/eLife.46752. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Cummins D. How the Social Environment Shaped the Evolution of Mind. Synthese. 2000;122(1/2):3–28. [Google Scholar]
  10. Ding Q, Sethna F, Wang H. Behavioral analysis of male and female Fmr1 knockout mice on C57BL/6 background. Behavioural Brain Research. 2014;271:72–78. doi: 10.1016/j.bbr.2014.05.046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Ellenbroek B, Youn J. Rodent models in neuroscience research: is it a rat race? Disease Models Mechanisms. 2016;9(10):1079–1087. doi: 10.1242/dmm.026120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fan Z, Zhu H, Zhou T, Wang S, Wu Y, Hu H. Using the tube test to measure social hierarchy in mice. Nature Protocols. 2019;14(3):819–831. doi: 10.1038/s41596-018-0116-4. [DOI] [PubMed] [Google Scholar]
  13. Friard O, Gamba M. BORIS: a free, versatile open-source event-logging software for video/audio coding and live observations. Methods in Ecology and Evolution. 2016;7:1325–1330. [Google Scholar]
  14. Gurts AM, Cost GJ, Freyvert Y, Zeitler B, Miller JC, Choi VM, Jenkins SS, Wood A, Cui X, Meng X, Vincent A, et al. Knockout rats via embryo microinjection of zinc-finger nucleases. Science (New York, NY) 2009;325:433. doi: 10.1126/science.1172447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Guo X, Hamilton P, Reish N, Sweatt J, Miller C, Rumbaugh G. Reduced Expression of the NMDA Receptor-Interacting Protein Syngap Causes Behavioral Abnormalities that Model Symptoms of Schizophrenia. Neuropsychopharmacology. 2009;34(7):1659–1672. doi: 10.1038/npp.2008.223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Guy J, Gan J, Selfridge J, Cobb S, Bird A. Reversal of neurological defects in a mouse model of Rett syndrome. Science. 2007;315:1143–7. doi: 10.1126/science.1138389. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Hamdan F, Daoud H, Piton A, Gauthier J, Dobrzeniecka S, Krebs M, Joober R, Lacaille J, Nadeau A, Milunsky J, Wang Z, et al. De Novo SYNGAP1 Mutations in Nonsyndromic Intellectual Disability and Autism. Biological Psychiatry. 2011;69(9):898–901. doi: 10.1016/j.biopsych.2010.11.015. [DOI] [PubMed] [Google Scholar]
  18. Huang W, Wang D, Allen W, Klope M, Hu H, Shamloo M, Luo L. Early adolescent Rai1 reactivation reverses transcriptional and social interaction deficits in a mouse model of Smith-Magenis syndrome. Proceedings of the National Academy of Sciences. 2018;115(42):10744–10749. doi: 10.1073/pnas.1806796115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Jeyabalan N, Clement J. SYNGAP1: Mind the Gap. Frontiers in Cellular Neuroscience. 2016;10:1–32. doi: 10.3389/fncel.2016.00032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kalueff A, Stewart A, Song C, Berridge K, Graybiel A, Fentress J. Neurobiology of rodent self-grooming and its value for translational neuroscience. Nature Reviews Neuroscience. 2015;17(1):45–59. doi: 10.1038/nrn.2015.8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Katsanevaki D, Till SM, Buller-Peralta I, Watson TC, Nawaz MS, Arkell D, Tiwari S, Kapgal V, Biswal S, Smith JAB, Anstey NJ, et al. Heterozygous deletion of SYNGAP enzymatic domains in rats causes selective learning, social and seizure phenotypes. bioRxiv. 2020:2020.2010.2014.339192 [Google Scholar]
  22. Kazdoba T, Leach P, Silverman J, Crawley J. Modeling fragile X syndrome in the Fmr1 knockout mouse. Intractable Rare Diseases Research. 2014;3(4):118–133. doi: 10.5582/irdr.2014.01024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kilinc M, Creson T, Rojas C, Aceti M, Ellegood J, Vaissiere T, Lerch J, Rumbaugh G. Species-conserved SYNGAP1 phenotypes associated with neurodevelopmental disorders. Molecular and Cellular Neuroscience. 2018;91:140–150. doi: 10.1016/j.mcn.2018.03.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kim J, Lee H, Takamiya K, Huganir R. The Role of Synaptic GTPase-Activating Protein in Neuronal Development and Synaptic Plasticity. The Journal of Neuroscience. 2003;23(4):1119–1124. doi: 10.1523/JNEUROSCI.23-04-01119.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Komiyama N, Watabe A, Carlisle H, Porter K, Charlesworth P, Monti J, Strathdee D, O’Carroll C, Martin S, Morris R, O’Dell T, et al. Syngap Regulates ERK/MAPK Signaling, Synaptic Plasticity, and Learning in the Complex with Postsynaptic Density 95 and NMDA Receptor. The Journal of Neuroscience. 2002;22(22):9721–9732. doi: 10.1523/JNEUROSCI.22-22-09721.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kunkel T, Wang H. Socially dominant mice in C57BL6 background show increased social motivation. Behavioural Brain Research. 2018;336:173–176. doi: 10.1016/j.bbr.2017.08.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Llamosas N, Arora V, Vij R, Kilinc M, Bijoch L, Rojas C, Reich A, Sridharan B, Willems E, Piper DR, Scampavia L, et al. SYNGAP1 Controls the Maturation of Dendrites, Synaptic Function, and Network Activity in Developing Human Neurons. The Journal of Neuroscience. 2020;40:7980–7994. doi: 10.1523/JNEUROSCI.1367-20.2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Lore R, Flannelly K. Rat Societies. Scientific American. 1977;236(5):106–118. doi: 10.1038/scientificamerican0577-106. [DOI] [PubMed] [Google Scholar]
  29. McMahon A, Barnett M, O’Leary T, Stoney P, Collins M, Papadia S, Choudhary J, Komiyama N, Grant S, Hardingham G, Wyllie D, et al. Syngap isoforms exert opposing effects on synaptic strength. Nature Communications. 2012;3(900):1–9. doi: 10.1038/ncomms1900. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. McNaughton C, Moon J, Strawderman M, Maclean K, Evans J, Strupp B. Evidence for social anxiety and impaired social cognition in a mouse model of fragile X syndrome. Behavioral Neuroscience. 2008;122(2):293–300. doi: 10.1037/0735-7044.122.2.293. [DOI] [PubMed] [Google Scholar]
  31. Michaelson S, Ozkan E, Aceti M, Maity S, Llamosas N, Weldon M, Mizrachi E, Vaissiere T, Gaffield M, Christie J, Holder J, Miller C, et al. SYNGAP1 heterozygosity disrupts sensory processing by reducing touch-related activity within somatosensory cortex circuits. Nature Neuroscience. 2018;21(12):1–13. doi: 10.1038/s41593-018-0268-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Miczek KA, de Boer SF. In: The behavior of the laboratory rat: A handbook with tests. Whishaw IQ, Kolb B, editors. Oxford University Press; 2005. Aggressive, Defensive, and Submissive Behavior; pp. 344–352. [Google Scholar]
  33. Muhia M, Yee B, Feldon J, Markopoulos F, Knuesel I. Disruption of hippocampus-regulated behavioural and cognitive processes by heterozygous constitutive deletion of Syngap. European Journal of Neuroscience. 2010;31(3):529–543. doi: 10.1111/j.1460-9568.2010.07079.x. [DOI] [PubMed] [Google Scholar]
  34. Nakajima R, Takao K, Hattori S, Shoji H, Komiyama N, Grant S, Miyakawa T. Comprehensive behavioral analysis of heterozygous Syngap1 knockout mice. Neuropsychopharmacology Reports. 2019;39(3):223–237. doi: 10.1002/npr2.12073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Nelson AC, Kapoor V, Vaughn E, Gnanasegaram JA, Rubinstein ND, Murthy VN, Dulac C. Molecular and Circuit Architecture of Social Hierarchy. bioRxiv. 2020 doi: 10.1101/838664. [DOI] [Google Scholar]
  36. Ogden K, Ozkan E, Rumbaugh G. Prioritizing the development of mouse models for childhood brain disorders. Neuropharmacology. 2016;100:2–16. doi: 10.1016/j.neuropharm.2015.07.029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. O’Roak B, Stessman H, Boyle E, Witherspoon K, Martin B, Lee C, Vives L, Baker C, Hiatt J, Nickerson D, Bernier R, et al. Recurrent de novo mutations implicate novel genes underlying simplex autism risk. Nature Communications. 2014;5(1):1–6. doi: 10.1038/ncomms6595. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Ozkan E, Creson T, Kramár E, Rojas C, Seese R, Babyan A, Shi Y, Lucero R, Xu X, Noebels J, Miller C, et al. Reduced Cognition in Syngap1 Mutants Is Caused by Isolated Damage within Developing Forebrain Excitatory Neurons. Neuron. 2014;82(6):1317–1333. doi: 10.1016/j.neuron.2014.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Parikshak Neelroop N, Luo R, Zhang A, Won H, Lowe Jennifer K, Chandran V, Horvath S, Geschwind Daniel H. Integrative Functional Genomic Analyses Implicate Specific Molecular Pathways and Circuits in Autism. Cell. 2013;155:1008–1021. doi: 10.1016/j.cell.2013.10.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Saxena K, Webster J, Hallas-Potts A, Mackenzie R, Spooner P, Thomson D, Kind P, Chatterji S, Morris R. Experiential contributions to social dominance in a rat model of fragile-X syndrome. Proceedings of the Royal Society B: Biological Sciences. 2018;285(1880):20180294. doi: 10.1098/rspb.2018.0294. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Spencer C, Alekseyenko O, Serysheva E, Yuva-Paylor L, Paylor R. Altered anxiety-related and social behaviors in the Fmr1 knockout mouse model of fragile X syndrome. Genes, Brain and Behavior. 2005;4(7):420–430. doi: 10.1111/j.1601-183X.2005.00123.x. [DOI] [PubMed] [Google Scholar]
  42. Spigel I, Trivett S, Fraser D. Grooming behavior and competitive dominance in the albino rat. Journal of Comparative and Physiological Psychology. 1972;78(3):409–411. [Google Scholar]
  43. Toseeb U, McChesney G, Wolke D. The Prevalence and Psychopathological Correlates of Sibling Bullying in Children with and without Autism Spectrum Disorder. Journal of Autism and Developmental Disorders. 2018;48(7):2308–2318. doi: 10.1007/s10803-018-3484-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Vazquez L. Syngap Regulates Spine Formation. Journal of Neuroscience. 2004;24(40):8862–8872. doi: 10.1523/JNEUROSCI.3213-04.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Walkup WGIV, Mastro TL, Schenker LT, Vielmetter J, Hu R, Iancu A, Reghunathan M, Bannon BD, Kennedy MB. A model for regulation by SynGAP-α1 of binding of synaptic proteins to PDZ-domain ‘Slots’ in the postsynaptic density. eLife. 2016;5:e16813. doi: 10.7554/eLife.16813. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Wang F, Kessels H, Hu H. The mouse that roared: neural mechanisms of social hierarchy. Trends in Neurosciences. 2014;37(11):674–682. doi: 10.1016/j.tins.2014.07.005. [DOI] [PubMed] [Google Scholar]
  47. Wang F, Zhu J, Zhu H, Zhang Q, Lin Z, Hu H. Bidirectional Control of Social Hierarchy by Synaptic Efficacy in Medial Prefrontal Cortex. Science. 2011;334(6056):693–697. doi: 10.1126/science.1209951. [DOI] [PubMed] [Google Scholar]
  48. Wesson D. Sniffing Behavior Communicates Social Hierarchy. Current Biology. 2013;23(7):575–580. doi: 10.1016/j.cub.2013.02.012. [DOI] [PubMed] [Google Scholar]
  49. Yang C, Bai Y, Ruan C, Zhou H, Liu D, Wang X, Shen L, Zheng H, Zhou X. Enhanced Aggressive Behaviour in a Mouse Model of Depression. Neurotoxicity Research. 2014;27(2):129–142. doi: 10.1007/s12640-014-9498-4. [DOI] [PubMed] [Google Scholar]
  50. Yizhar O, Fenno L, Prigge M, Schneider F, Davidson T, O’Shea D, Sohal V, Goshen I, Finkelstein J, Paz J, Stehfest K, et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature. 2011;477(7363):171–178. doi: 10.1038/nature10360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Yoo H. Genetics of Autism Spectrum Disorder: Current Status and Possible Clinical Applications. Experimental Neurobiology. 2015;24(4):257–272. doi: 10.5607/en.2015.24.4.257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Zhou T, Zhu H, Fan Z, Wang F, Chen Y, Liang H, Yang Z, Zhang L, Lin L, Zhan Y, Wang Z, et al. History of winning remodels thalamo-PFC circuit to reinforce social dominance. Science. 2017;357(6347):162–168. doi: 10.1126/science.aak9726. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Raw data for all figures (Excel), the details of all of the statistics done along with an example video is uploaded in a data repository (https://datashare.ed.ac.uk/submit?workspaceID=6884).

RESOURCES