A medium density genetic map and QTL for behavioral and production traits in Japanese quail

Groups of animals are often large in modern poultry breeding conditions, resulting in repeated group disruption and encouraging the expression of aggressive behaviors [1]. Studies on the social dynamics induced by breeding in large groups have shown that the size of the group is not the only factor behind the appearance of aggressive behaviors. The space available per individual and therefore the distance between individuals also have a role [2-5]. Bird sociability is another aspect to consider in adaptation to the group. Studies on two lines of Japanese Quail divergently selected for their social reinstatement behavior [6], showed that quail with a higher level of social reinstatement (HSR) were quicker to rejoin conspecifics and formed shorter distances between individuals than those with a lower level of social reinstatement behavior (LSR) at a young age, before becoming similar at adult age [7]. Moreover, the HSR line seemed to be more tolerant of group disruption (social isolation followed by reintroduction of familiar or unfamiliar conspecifics in groups) than the LSR line [8]. These results highlight the importance of social motivation as a factor contributing to the ability of a bird to adapt to modern breeding conditions.

In a previous study [9], we used a second generation (F2) cross between two lines of quail divergently selected for their social reinstatement [6] to estimate the genetic parameters of social motivation and its relationships with other important behaviors (such as aggression, sexual motivation, emotional reactivity) and production traits. Our results showed a significant genetic contribution to the phenotypic variability of behavioral traits. This has also been demonstrated at the molecular level, as QTLs were detected for the duration of tonic immobility in the chicken [10] and in Japanese Quail [11,12], for emotional reactivity in open-field [13] and for the propensity to receive or perform feather pecking [14,15] in the chicken. Possible genetic links between emotional reactivity and production traits were also evidenced in an F2 cross between the Red Junglefowl and the White Leghorn, where the two most significant growth QTL (Growth1 and Growth2 loci) were co-located with tonic immobility or response to a novel object QTL [10,16]. It was later shown that chickens with alternative homozygous genotypes at the Growth1 locus differed in several emotional and social reactions [17].

The aim of the present study was to investigate further the genetic control of social and emotional behaviors, and their relationships with production traits, by genome-wide QTL detection in the F2 cross between two lines of quail divergently selected for social reinstatement, i.e. the distance run on a treadmill to rejoin conspecifics [6]. As no whole-genome marker panel is publicly available in Japanese Quail, and as only a few low density genetic maps have been constructed with AFLP markers [18], microsatellites [19] or both types of marker [20], informative markers were also developed through high-throughput sequencing of the divergent lines to construct the first genetic map of the whole genome based on SNP markers.

Quail show social behaviors close to those observed in the chicken. Moreover, Japanese Quail and chickens have the same number of chromosomes despite showing several morphological differences [39]. As such, the Japanese Quail can be considered as a reliable model for the chicken in the field of genetics [40]. However, a previous study by Inoue-Murayama et al. [41] showed that genetic markers used in the genetic mapping for the chicken were ineffective in Japanese Quail, which highlighted the need to develop quail-specific markers. Consequently several maps were developed using AFLP markers [18], microsatellite markers [19] and both [20]. Comparisons between the information from the quail genetic map and from the assembled chicken sequence showed that the macrochromosomes of the two species had a highly conserved synteny [42]. Similarly, cytogenetic comparisons by Shibusawa et al. [43], showed conservation of the chromosomal organization between the two species. Nevertheless, Kayang et al. [42] observed rearrangements on CJA1, CJA2 and CJA5 and Shibusawa et al. [43] on CJA1, CJA2, CJA4 and CJA8, although the inverted regions on CJA1 and CJA2 were not the same in the two studies. FISH analyses performed by Kayang et al. [42] confirmed the results of Shibusawa et al. [43] on CJA1 and CJA4. Moreover, a study by Sasazaki et al. [44] comparing the positions of orthologous genes between the two species showed a chromosomal rearrangement on CJA2 (in a similar position to that of Shibusawa et al. [43]) and on CJA5 (in a similar position to that of Kayang et al. [42]). It also showed new rearrangements on CJA3 and CJA7. Interestingly, our results were consistent with those of Shibusawa et al. [43] for CJA1, CJA2 and CJA8 and of Sasazaki et al. [44] for CJA3. We also confirmed the inverted region on CJA5 reported by Kayang et al. [42] and Sasazaki et al. [44]. Surprisingly, we did not observe the inverted region described by Shibusawa et al. [43] and Kayang et al. [42] on CJA4. This might have originated from a lack of information from the markers present in the region, preventing identification of the chromosomal rearrangement. We also observed an inverted region on CJA6 never previously reported. Findings by Shibusawa et al. [43] seem to indicate a lack of cytogenetic markers in the rearranged region, which could explain the impossibility of confirming the existence of chromosomal rearrangement on CJA6 by cytogenetic means. In conclusion, the map constructed for this study should accurately represent the genetic organization of the quail genome. With the exception of a few regions, the marker order was conserved between the Japanese Quail and the chicken, which confirmed conserved synteny and supported the relevance of the Japanese Quail as a model for the chicken.

In order to confirm the similarity between QTLs observed in the quail and the chicken, we used the chicken QTL Database [36,37]. We first undertook these comparisons on widely studied traits such as body weight. In the present study, we detected several QTLs for body weight at a juvenile age (W17) and at a sexually mature age (W65). Interestingly, QTLs controlling these two traits co-localized on CJA1 (316 to 328 cM) and CJA5 (56 to 115 cM), suggesting the existence of regions controlling the overall growth of the animal. As shown in Additional file 1: Table S1, growth-related QTLs were discovered in the homologous regions of the chicken by several studies at a juvenile age but more rarely at a mature age. Similarly, body weight QTLs in the chicken were found in the homologous regions of W65 QTL on CJA3 (148–165 cM) and W17 QTL on CJA8 (37–60 cM). These results showed that several QTLs were consistent for similar traits between the chicken and the quail, although we do not have any indication that they are governed by common genes. By contrast, egg trait-related QTLs were rarely identified in the chicken. Only one QTL for WEgg on CJA3 (52.6 to 56.7 Mb) showed coordinates overlapping with an egg weight QTL detected on GGA3 (49.0 to 81.4 Mb) by Tuiskula-Haavisto et al. [45]. One hypothesis is that the genetic determinism of egg production traits is not as conserved between the quail and the chicken as the determinism of body weight; our population may also lack the genetic variability in the QTL regions identified in the chicken. Another explanation may be that our experimental scheme was less powerful for the egg production traits, which were measured in only half of the birds. Interestingly, our results indicated the existence of putative pleiotropic loci affecting both weight and egg traits. This was the case on CJA3 where a WEgg QTL co-localized with a W65 QTL. Physiologically, it has been shown that the average egg weight roughly represents 8% of the female bodyweight in the quail and 3% in the chicken [46]. This candidate region could underlie the genetic correlation already observed in the quail between these two traits [47-50]. The W65 QTL and NEgg QTL identified on CJA18 suggested another candidate region which might partly explain the unfavorable genetic correlation in the quail between these two traits reported by Silva et al. [48].

As only a few studies have focused on the detection of behavioral QTL in either the quail [11,12] or the chicken [10,13-15,51-53], comparison with previous studies is less comprehensive than for production traits. Interestingly, the AgrP QTL on CJA1 corresponded to the homologous region (around 109 Mb to 127 Mb) in the chicken harboring a QTL controlling the number of feather pecks an individual received [14]. The effect of this locus was recently confirmed by Biscarini et al. [51] who showed a significant effect of SNP rs1530785 on the number of pecks received on the dorsal and ventral parts of the body. This behavioral QTL was shown to contain the gene coding for the isoenzyme MAOA (Mono-Amine Oxidase A), while two studies showed increased aggressive behavior in MAOA knockout mice [54,55]. Indeed, MAOA regulates the concentration of several substrates such as serotonin, dopamine and the norepinephrine [56]. One of these substrates, serotonin, has been shown to affect several behavioral processes such as cooperation between individuals, hierarchy establishment and aggressiveness (see [57] for review). Furthermore, the study by van Hierden et al. [58] demonstrated that lines of chicken divergently selected for their feather pecking propensity showed a different serotonin turnover with a slower degradation of serotonin in the HFP (High Feather Pecking) than in the LFP lines (Low Feather Pecking). Moreover, Wysocki et al. [59] studied MAOA expression in brain tissue of HFP and LFP lines and suggested that it could possibly be downgraded in HFP. However, the observation on micro-arrays could not be confirmed by qPCR. Further research is needed to investigate the variability of this gene in the HSR and LSR lines, which also differed in terms of aggressiveness [60,61]. Another QTL for AgrP (46.6 Mb) was observed on CJA2 which co-localized with a QTL for the number of severe feather pecks given by a chick (46.0 to 51.3 Mb) identified by Buitenhuis et al. [15]. When considering the extent of our confidence interval, it seems that we identified a more refined region than that described by Buitenhuis et al. [15]. In addition, the chromosomal rearrangement we observed in the quail brought the AgrP-QTL and DistSR-QTL observed on CJA2 closer, suggesting a possible pleiotropic effect of this region. The coordinates of the DistSR QTL (79.2 to 79.4 Mb and 81.1 to 81.4 Mb for the Sire and Sire-Dam models, respectively) co-localized with a suggestive QTL for the number of Gentle Feather Pecks given by an individual (67 to 85 Mb) identified by Buitenhuis et al. [15]. Previous reports on the HSR and LSR lines showed that, in cases of group disruption, HSR birds manifested increased explorative behavior of unfamiliar conspecifics such as gentle peckings [62], which reinforces this QTL co-localization.

Interestingly, the TI-QTL on CJA11 showed coordinates (3.3 to 3.7 Mb and 0.5 to 2.8 Mb for the Sire and Sire-Dam models, respectively) corresponding to a QTL controlling the frequency of defecation in an Open-Field (0.5 to 5.0 Mb) identified by Buitenhuis et al. [13] in the chicken. These co-localizations suggest an effect of this region on some aspects of emotional reactivity of an animal as the duration of tonic immobility after restraint and the frequency of defecation in Open-Field are both behavioral responses expressed during stressful events [63,64]. Our results also highlighted putative pleiotropic regions controlling emotional reactivity and body-weight. This was the case for CJA5 for a region (spanning 38 to 75 cM) which harbored a genome-wide significant QTL for W17 and a chromosome-wide significant QTL for TI. It was also the case for CJA8 where QTLs for HeadNO and W17 overlapped. A genetic link between a bird’s growth and its emotional reactivity or sociability has already been evidenced by studying the Growth 1 region in the chicken [10,17] and several candidate genes affecting the sociability or the emotional reactivity in this region have been suggested (AVRP1, AVRP2, NRCAM) by Wiren et al. [65]. A pleiotropic role of the Growth 2 region [16] was also suggested as it co-localized with a QTL controlling the reaction to a novel object [10]. We also identified a putative pleiotropic QTL for AFEgg and DistIso on CJA19. Moreover, it is interesting to note that DistSR QTL on CJA13 had overlapping coordinates (1.6 to 1.8 Mb) with an AFEgg QTL (0.6 to 16.0 Mb) identified by Podisi et al. [66] on GGA13, although the latter is very wide. An unfavorable correlation between growth and fearfulness has already been reported in poultry, as in this F2 experimental design [9,67]. At the same time, favorable genetic relationships between sociability or emotional reactivity and egg traits (age at first egg and number of eggs) have been reported [9]. As the confidence intervals of our QTLs remain large, further research will be needed to confirm the pleiotropic effects of the QTL regions we identified, and to look for candidate genes underlying the relationship between production and behavior. Identification of these molecular factors should help to understand whether production can be improved without impairing emotional and social behavior, which remains a vexing question for poultry production.

With a total of 15 QTLs obtained by the two models, the most numerous regions involved the social motivation traits (i.e. DistSR and DistIso), which highlighted the interest of divergent lines selected on social motivation for QTL detection. This study is the first to date to identify social motivation QTL across the whole genome, as previous studies focused either on a selected QTL region [65] or considered composite traits obtained by Principal Component Analysis [53]. The eight regions we identified for DistSR did not co-localize with the seven found for DistIso. This finding is consistent with the low phenotypic and genetic correlations we observed between DistSR and DistIso with the same design [9] and suggests that these two traits are under different genetic control and measure different components of social motivation, probably depending on whether the animals are in visual and auditory contact with conspecifics or not. Although the confidence intervals of the social motivation QTLs were relatively wide and the identification of candidate genes rather speculative at this stage, the use of Ingenuity Pathway Analysis [68] revealed two interesting genes related to behavior establishment. The first (located in the DistSR QTL on CJA2) is the dopa-decarboxylase gene (DDC) which encodes the aromatic L-amino acid decarboxylase (AADC). This enzyme allows conversion of L-DOPA to dopamine and L-5 hydroxytryptophan to serotonin. Genetic variations in the DDC gene have been reported to be associated with the defective attention and disorders such as Attention Deficit Hyperactivity [69] in humans. The second (located in the DistSR QTL on CJA9) is the serotonin receptor 2B gene (HTR2B). Studies in the field of personality traits were recently conducted on HTR2B. HTR2B knockout mice showed increased impulsive behavior and novelty seeking [70]. Moreover, an association between HTR2B polymorphism and a personality trait of fun seeking has been found in humans [71].

This study identified several QTL regions for social and emotional behaviors in the quail. Further research will be needed to refine these regions and confirm or refute the role of candidate genes, such as the neurotransmitters genes. Our genetic map confirmed a well conserved synteny while the linkage analysis suggested some putative common QTLs between the quail and the chicken. It is to be hoped that the discovery of genes and polymorphisms related to behavioral traits in the quail will have further applications for the chicken and will contribute to solving the animal welfare issues encountered in poultry production.