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The Effects of In Ovo Cortisol Exposure on Behaviour and Stress Axis Organization in the Threespine Stickleback… Kingwell, Callum Apr 30, 2013

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The Effects of In Ovo Cortisol Exposure on Behaviour and Stress Axis Organization in the Threespine Stickleback Gasterosteus aculeatus By Callum Kingwell  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF BACHELOR OF SCIENCE in THE FACULTY OF SCIENCE (Honours Biology) THE UNIVERSITY OF BRITISH COLUMBIA April 2013  We accept this thesis as conforming to the required standard ______________________________ ______________________________ ______________________________ ______________________________ ______________________________ © Acknowledgements	I	would	first	like	to	thank	the	examining	committee,	Dr’s	Carol	Pollock,	Dolph	Schluter,	and	Patricia	Schulte	for	reviewing	the	thesis	and	for	participating	in	the	defense.		I	would	also	like	to	thank	Dr.	Phillipe	Tortell	for	invigilating	the	defense,	and	for	his	helpful	comments	on	early	drafts	of	the	thesis.		This	project	would	not	have	been	possible	without	the	support	of	my	supervisor	Dolph	and	his	students;	Sara	Miller,	Diana	Rennison,	Seth	Rudman,	Kieran	Samuk,	Gina	Conte,	and	Thor	Veen	all	provided	helpful	comments,	thoughts,	and	assistance	with	laboratory	techniques	which	were	much	appreciated.		Narina	Jabari	donated	a	weekend	of	her	time	to	collecting	fish	and	to	setting	up	experimental	treatments	–	this	is	also	very	much	appreciated.		I	would	like	to	thank	Dr.	Schulte	for	the	use	of	her	laboratory	and	reagents,	for	her	input	during	the	planning	stage	of	the	project,	and	for	supplying	her	vast	knowledge	of	fish	physiology.		Her	students	Tim	Healy	and	Dave	Metzger	also	provided	invaluable	support	with	molecular	assays	and	general	lab	techniques	for	which	I	am	grateful.								 2 Abstract Amongst vertebrates, transfer of maternal glucocorticoid (GC) stress hormones to developing embryos through egg yolk (in ovo) or in utero is documented in a variety of species.  This phenomenon has attracted attention in recent years because of the significant physiological and behavioural consequences of this early-life GC exposure and their potential relevance to human health and disease progression.  Prenatal programming by maternal glucocorticoid exposure has also been proposed to play a role in adaptation, although natural systems in which to test this hypothesis are lacking. In this study, in ovo cortisol treatment of threespine stickleback eggs at physiologically significant levels is used to test the effects of maternal glucocorticoids on juvenile brain expression levels of three candidate stress-axis genes (GR1, GR2, and POMC), and on three stress-linked behaviours thought to be sensitive to maternal GC levels (aggression, boldness, and shoaling). In rats, glucocorticoid receptor (GR) down-regulation leading to reduced glucocorticoid feedback sensitivity and a subsequent increase in stress-axis reactivity is thought to explain decreases in aggression and boldness that often follow maternal GC elevation in that species. I report that, contrary to the bulk of findings in mammalian studies, GR1 and GR2 expression levels in cortisol-treated fish are higher than those seen in untreated fish.  Although cortisol treatment influenced gene expression, neither shoaling, aggression nor boldness were strongly influenced by treatment.  Sex differences in boldness and aggression levels matched previously described results, which suggests behavioural assaysthat GC-mediated maternal effects on offspring behaviour may not be attributable exclusively to yolk cortisol increases, or perhaps that behavioural changes may have been too subtle to be detected at the dosage used.  Ultimately, this study identifies persistent offspring GR up-regulation as a potential consequence of elevated maternal glucocorticoid levels in fish.  The diverse roles of GR in physiological and behavioural regulation suggest that the consequences of this up-regulation for survival outcomes are probably complex, a fact that future studies investigating the adaptive significance of glucocorticoid-mediated maternal effects in fish should take care to consider.  3 Introduction Broadly defined, maternal effects occur when the environmental experience or phenotype (considered broadly) of the mother induce non-genetic effects on offspring phenotype.  These effects can be diverse, and examples include oviposition and feeding behaviours, maternal care, mate choice, as well as egg size and quality (Mousseau and Fox 1998).  In a variety of vertebrate groups, transfer of maternal stress hormones (such as cortisol) to developing embryos through egg yolk (in ovo) or in utero is a well documented phenomenon (Van den Bergh et al. 2005; Giesing et al. 2011; Henriksen et al. 2011). This early-developmental exposure to cortisol has been shown to influence aggression, social rank, shoal density, and problem solving ability later in life in a number of fish species (Sloman 2010; Giesing et al. 2011; Burton et al. 2011; Roche et al. 2012).  The physiological consequences of this exposure have been shown to include changes to metabolism that result in increased oxygen consumption and ammonia excretion rates, altered hatching times, changes in the dynamics of the glucocorticoid (GC) response following stress, and increased morphological asymmetry (Auperin and Geslin 2008; Gagliano and Mccormick 2009; Li et al. 2010).  These effects appear to be driven by aspects of maternal phenotype (stress level) which are environmentally-influenced and at least not entirely determined by maternal genotype, and so match the general definition of a ‘maternal effect’. The mechanistic details of these glucocorticoid-mediated maternal effects are not entirely clear, but it appears likely that they arise from long-term organizational changes to the stress-response axis which are enacted early in development (Kapoor et al. 2006; Nesan and Vijayan 2012). This ‘axis’ is comprised of three main organs (the hypothalamus, pituitary, and the adrenal gland) whose secretions and interactions are responsible for regulating the physiological stress response.  Whereas the adrenal gland is responsible for cortisol secretion in mammals (as part of the ‘HPA-axis’), interrenal cells located near the anterior kidney are responsible for cortisol synthesis and secretion in teleost fish (as part of the ‘HPI-axis’).  Few studies have looked at the effects of early cortisol exposure on HPI-axis structure at  4 a molecular level in fish, although significant insight has been gained through studies in mammalian models.  Prenatal GC administration has been shown to alter the expression levels (mRNA abundance) of key HPA-axis genes in adult rats (Welberg et al. 2001).  One commonly observed effect of this treatment is a reduction in glucocorticoid receptor (GR) density and mRNA production in a number of specific brain regions (Welberg and Seckl 2001).  This GR down-regulation in GC exposed individuals is thought to decrease the efficacy of HPA-axis negative feedback that is regulated by GR receptors located in the hypothalamus (O'Donnell et al. 1994; Liu et al. 1997).  Negative feedback on the synthesis of hypothalamic releasing factors for corticotropin (ACTH), predominantly directed towards corticotropin-releasing hormone (CRH) and arginine vasopressin (AVP), occurs at a number of neural sites following binding of glucocorticoids to GRs (Bernier et al. 2009).  As in humans, the predominant glucocorticoid in fish is the steroid hormone cortisol.  It is currently unknown whether GC-mediated maternal effects in teleost fish alter brain expression levels of GR’s as they do in rats.  However, recent work linking HPI-axis gene expression with boldness and aggression – behaviours which appear to be influenced by maternal glucocorticoid levels – suggests that this may be the case (Aubin-Horth et al. 2012).       A correlation between boldness and aggression behaviours has been identified in a great number of vertebrate species, and the ubiquity of this association has led to its description as the ‘boldness-aggression behavioural syndrome’ (Sih et al. 2004). Inter-individual variation in this behavioural syndrome – whether individuals display passive and shy or bold and aggressive phenotypes – is thought to be linked to differences in the physiological stress response.  Passivity and shyness are associated with a ‘reactive’ stress coping strategy typified by high parasympathetic and hypothalamic-pituitary-adrenal/interrenal (HPA/HPI) activation, while boldness and aggression form part of a ‘proactive’ stress coping strategy typified by relatively high sympathetic and low HPA/HPI activation (Koolhaas et al. 1999). In fish, cortisol secretion by the interrenal cells is regulated by two main secretogogues: CRH (corticotropin-releasing hormone) is released by neurons of the  5 hypothalamus in response to stress, while ACTH (adrenocorticotropic hormone) is released by the anterior pituitary in response to elevated CRH levels (Bonga 1997; Mommsen et al. 1999).  In the threespine stickleback, available data similarly support a link between HPI-axis function and the aggression-boldness behavioural syndrome.  In particular, increased expression of three genes involved in HPI-axis function (GR1, GR2, and POMC) demonstrate a positive correlation with aggression and boldness in adult male stickleback, while plasma cortisol levels show a negative correlation with aggression (Aubin-Horth et al. 2012).  POMC is a hormone precursor that is cleaved into a number of bioactive peptides, including ACTH, whose release stimulates glucocorticoid secretion at the interrenal cells.  Similar evidence supporting a link between the HPI-axis and behaviour is available from other fish species; in zebrafish, a bold behavioural phenotype has been linked to the transcriptional attenuation of several stress response axis genes (Oswald et al. 2012).  Interestingly, recent findings have demonstrated that these behavioural traits are sensitive not only to genetic variation in stress response axis structure, but also to maternal effects acting via intergenerational transmission of GC hormones.  In rats and mice, elevated maternal stress levels are found consistently to have a negative effect on boldness and aggression levels, although these effects are sometimes sex-specific (Kinsley and Svare 1986; Weinstock et al. 1992; Patin et al. 2005).  In fish, two studies of juvenile brown trout hatched from eggs exposed to elevated cortisol found changes in treated relative to untreated individuals in both social rank and the frequency of aggressive behaviours directed towards conspecifics (Burton et al. 2011).  The direction of these apparently GC-mediated effects on aggression differed in these two studies, highlighting the fact that the specific effects of early-life GC exposure on teleost fish behaviour are not well understood.  Experimental studies of prenatal GC exposure in other vertebrates have also demonstrated lasting effects on the function and organization of the HPA axis.  Japanese Quail (Coturnix japonica) mothers with elevated cortiscosterone levels lay eggs with higher yolk cortiscosterone, and the chicks that hatch from those eggs release a relatively higher  6 concentration of cortiscosterone following handling and restraint stress than chicks from mothers with low cortiscosterone levels (Hayward and Wingfield 2004).  Experimental treatment of eggs with cortiscosterone showed the same effect, although in this case it was observed only in female offspring (Hayward et al. 2006).  This study is one of many providing evidence of sex-specific effects of glucocorticoid hormones in vertebrates (McCormick et al. 1995; Liu et al. 2001; Love et al. 2005).   The profound effects on behaviour, physiology, and morphology that result following maternal glucocorticoid exposure have led to the suggestion that maternal hormones may have an adaptive role in ‘programming’ of offspring phenotype (Dufty 2002).  Currently, there is little evidence to suggest that maternal glucocorticoids in vertebrates result in adaptive changes to offspring phenotype (Gagliano and Mccormick 2009; McGhee et al. 2012).  One problem faced by researchers attempting to test the contribution of maternal GCs to survival outcomes is a lack of accessible model systems, particularly ones that can be utilized in natural settings  (Rasanen and Kruuk 2007).  The threespine stickleback (Gasterosteus aculeatus), with an expansive geographic distribution throughout aquatic environments presenting a diversity of environmental stressors, represents an ideal species through which to explore the potential adaptive role of glucocorticoid-mediated maternal effects.  Furthermore, the ease with which GC levels in externally fertilized fish eggs can be experimentally manipulated makes this species an ideal candidate for phenotypic engineering studies which may be used to specifically test the adaptive value of the organizational changes imposed by early-life cortisol exposure (Ketterson et al. 1996; Groothuis et al. 2005).  This same convenience has led to the common use of trout (Salmo trutta or Oncorhynchus clarki) in experimental studies of the physiological and behavioural consequences of in ovo exposure to maternal glucocorticoids (Sloman 2010; Li et al. 2010).  However, the ecological selection pressures operating on behaviour in trout are less clear than they are in stickleback populations, where a central role of predation-imposed selection on both behaviour and morphology is particularly well established (Reimchen 1994; Huntingford et al. 1994).  Population-level differences in shoaling  7 tendency, predator inspection frequency, boldness, exploratory behaviour, and aggression have all been shown to co-vary predictably with local predation intensities (Huntingford 1982; Huntingford et al. 1994; Alvarez and Bell 2007; Dingemanse et al. 2007).  Furthermore, a recent study of a California population of threespine stickleback found higher cortisol levels in eggs of stressed mothers, and also showed that their offspring demonstrated tighter shoaling behaviour relative to those from unstressed mothers (Giesing et al. 2011).  Because shoaling is an important anti-predator trait, this finding suggests that glucocorticoid mediated maternal effects in threespine stickleback could be have significant fitness contributions.   In this study, threespine stickleback eggs are used to investigate the downstream developmental effects of an experimental in ovo cortisol exposure treatment at physiologically significant levels.  Specifically, the study examined brain expression levels of three candidate stress-response axis genes and levels of aggression, boldness, and shoaling behaviour at the juvenile stage of development.  The genes of interest encode two glucocorticoid receptor isoforms (GR1, GR2) and a protein precursor regulating the production and release of corticosteroids (POMC) whose brain expression levels associates with the boldness-aggression behavioural syndrome (Aubin-Horth et al. 2012; Oswald et al. 2012).  I first test whether expression patterns of glucocorticoid receptor mRNA following prenatal glucocorticoid exposure are similar to those seen in rats.  With no compelling reasons to suspect otherwise, stickleback and rats are expected to show similar patterns and decreased brain GR1 and GR2 expression are expected amongst treated individuals.  Because GR and POMC expression have a demonstrated correlation in stickleback brains, a similar decrease in POMC mRNA is predicted.  The effects of prenatal GC exposure on boldness, aggression, and shoaling behaviour are also tested in this study.  Under the hypothesis that GR expression and aggression-boldness are linked, and given the observation that GR down-regulation and low aggression-boldness scores typically follow early GC exposure in mammals, a decrease in aggression and boldness is predicted in exposed individuals.  Based on  8 findings in a previous study, an increase in shoal density is predicted in cortisol treated groups (Giesing et al. 2011).  Also based on past findings, GR1 and GR2 expression levels are expected to show a positive correlation, as are aggression and boldness (Aubin-Horth et al. 2012).  By examining a selection of physiological and behavioural traits with a hypothesized developmental sensitivity to early-life cortisol exposure, this study aims to contribute to what little is known about the long term organizational effects of maternal glucocorticoid exposure in teleosts, and to provide direction for future studies examining the potential role of maternal glucocorticoids in facilitating adaptation.               9 Methods Animal Collection, Crosses and Treatment The fish used in this study were obtained from crosses made in the field using adult fish collected at Trout Lake on the Sechelt peninsula, British Columbia (GPS: 49°30’29’’N, 123°52’34’’W).  Adults were collected in wire minnow traps left overnight near the lakeshore, and 24 pregnant females and 24 mature males were identified for use in crosses on the morning of collection. Females were weighed, stripped of eggs, and re-weighed to obtain an estimate of total clutch mass.  Females were then returned to the lake. Males were weighed, euthanized in MS-222, and their testes were dissected.  The crushed testes of a single male were combined with the total clutch of a single female in sterilized petri dishes to produce 24 genetically distinct families, with clutch sizes ranging from 23 to over 100 in egg number.  Clutches were split approximately in half following a 5 minute fertilization period, and each half was transferred to separate 50ml falcon tubes containing one of two solutions; treated clutches were immersed in lake water spiked with cortisol at a concentration of 50ng/ml, and control clutches were immersed in lake water lacking cortisol.    As a lipophilic steroid hormone, cortisol is not soluble in water, and so powdered hormone (Hydrocortisone, Sigma) was first dissolved in 95% ethanol before addition to the lakewater.  The control treatment contained an equivalent dosage of ethanol without added hydrocortisone.  Both immersions therefore contained a very small concentration of ethanol at about 1.62µM, which is well below levels known to cause developmental and behavioural defects in fish (Oxendine et al. 2006; Buske and Gerlai 2011).  Experimental cortisol exposure was designed to match expected exposure levels of ova to circulating maternal hormones in the body cavity: in the two studies that have compared plasma cortisol concentrations in relaxed and stressed threespine stickleback, females are consistent in showing a resting cortisol concentration of ~2-8 ng/g and a stressed concentration of ~50ng/g (Pottinger et al. 2002; Bell et al. 2007).  It is unknown whether the level of cortisol to which developing eggs in the body cavity are  10 exposed shows direct correspondence with circulating cortisol levels in adult females.  The one study available describing the cortisol content of eggs produced by experimentally stressed and unstressed threespine stickleback mothers found significantly different in ovo concentrations of 2ng/ml and 1.5ng/ml respectively (Giesing et al. 2011).  There are no data available describing absorbance of cortisol from surrounding water in threespine stickleback eggs post-fertilization, but data are available from an experiment in brown trout.  In this study, cortisol treatment at a dosage of 200 ng/ml post-fertilization increased the cortisol content of eggs from 11ng/g to 55ng/g (Burton et al. 2011).  The higher dosage used in this study as well as the higher baseline concentration of cortisol in untreated eggs reflect normal concentrations observed in salmonid fish (Stratholt et al. 1997).   Taking these previous studies into consideration, a 50ng/ml cortisol dosage is expected to reflect expected cortisol levels in stressed threespine stickleback females, while egg cortisol concentrations are expected to increase within physiologically relevant values given an absorption rate in freshwater that is well below 100%.   After an 8-hour exposure period during which time eggs were transferred to UBC’s freshwater aquatic facility, all treated and untreated egg masses were rinsed with de-chlorinated water in individual canning jars for 3 minutes. Eggs were then transferred to aerated mesh cups submerged in 100L tanks where they were left to complete their development.  Each treated or untreated half of a clutch developed in a single 100L tank.  Eggs were checked daily for fungal contamination, and any contaminated eggs (usually indicative of a failed fertilization) were removed from the cups.  Due to a fairly low rate of successful fertilization, possibly because eggs were collected relatively late in the breeding season, only 13 of the 24 in-field crosses successfully developed beyond the egg stage.  In two smaller clutches, only the cortisol-treated half of the clutch developed successfully.  Thus, the experiment consisted of 11 clutches divided into treated and untreated halves occupying twenty-two 100L tanks.  From 0 to ~90 days post-hatch (dph) the fish from these clutches were fed a mixture of live Artemia nauplii and microworms (Panagrellus redivivus) two times per day.  From about 90 dph to 180 dph, juvenile fish were  11 switched to a diet of chopped bloodworms delivered once daily.  At 120 dph, the number of fish in all tanks was reduced to 6 in an attempt to standardize the social environment in the two months leading up to analysis of gene expression and behaviour and to permit analysis of shoaling behaviour with overhead photographs.  This cull was not performed earlier than 120 dph because studies in other fish species have shown that the development of the HPI axis is sensitive to handling stress during early stages of development (Auperin and Geslin 2008).  After the cull there were six fish in each of 20 tanks (from ten clutches) and two fish in each of two additional tanks. This eleventh clutch consisted of only a very small number of eggs, and thus only two fish in each of the treated and untreated halves were available for the experiment.  A total of 124 individuals were included in behavioural assays.   Behavioural Assays Shoaling While juvenile fish were between 5 and 6 months of age, each 100L tank was photographed from above at a standard distance.  ImageJ (v. 1.45s) software was used to calculate the average nearest neighbor distance (NND), describing the average distance between each of the 6 fish in each tank.  This measure is calculated by determining the distance (cm) between each fish in the tank and it’s closest neighbor, then taking the average of this value for all fish in the tank. These photographs were taken on a bi-weekly basis during the last month of development, producing three repeated measures of NND that were averaged to provide an estimated value for each of the 20 tanks photographed (10 treated and 10 untreated).  As previously mentioned, one clutch contained only four fish in total and so was excluded from analysis of shoaling.  Boldness and Aggression  At approx. 180 dph, individual fish were taken from their home tanks and moved to individual 100L test tanks where assays for boldness and aggression were  12 performed.  These tanks were covered on all sides by opaque black plastic sheeting, which was pulled back from the front wall of the tank during behavioural observations.  On the first day of the three day testing period, one randomly selected fish was netted from group housing tanks and placed into opaque 16cm PVC tubes sealed closed at one end.  This tube was then covered at the other end by an opaque plastic trap door which completely covered the exit, and the entire assembly was then placed against the right wall of individual test tanks at about 10cm from the back.  After a 3 minute settling period, the trap door was removed from behind the tank (such that the experimenter was out of view of the test fish) while a video camera at the front of the tank recorded the time taken for the fish’s head to emerge from the PVC shelter.  If the fish did not leave the PVC within 10 minutes, a score of 600s was assigned.  This assay is similar to previously published assays used to assess boldness in other fish species, with bold individuals typically showing lower emergence times than shy individuals (Brown and Braithwaite 2004; Herczeg and Gonda 2009).  Aggression assays were performed on the second day of testing, after the fish had acclimated to the novel tank for 24 hours.  In this assay, a conspecific of similar size and age was introduced to the centre of the individual’s housing tank inside a transparent 1L glass bottle.  Following the introduction of the ‘intruder’ fish, the experimenter left the area and a video camera was left to record the activities of the resident fish for a 10 minute period.  Videos were scored for the 5 minute period beginning from the time that the resident fish first oriented towards and approached within one body length of the intruder.  The number of nips directed towards the intruder and the amount of time spent less than one body length away were recorded in JWatcher (V1.0) by an observer blind to the identity and treatment category of the resident fish.  Intruder fish used in the assay originated from untreated eggs collected at the same time as the experimental clutches, which meant that body size was fairly consistent between residents and intruders.  No individual intruder was used more than once on a single day of testing. This assay is similar to  13 others that have been used to quantify aggression in the threespine stickleback (Bell 2005; Lacasse and Aubin-Horth 2012).  Analysis of Gene Expression Approximately 24 hours after aggression assays were performed (on the third day of data collection), fish were sacrificed by immersion in an overdose of MS-222.  After the exterior of the body has been patted dry, the fish mass and standard length of each individual were recorded.  The entire brain was then rapidly dissected and flash frozen in liquid nitrogen, then moved to storage at -80°C before further analysis.  The body was re-weighed to provide an estimate of brain weight, then frozen at -80°C.  Gene expression data were gathered with the use of a real-time qPCR assay using cDNA synthesized from isolated brain RNA.  Only individuals in sets 1 and 2 of the behavioural trials were included in this analysis (n=42).   RNA Isolation and cDNA Synthesis To extract RNA from brain tissue, 700µl Trizol Reagent was added to 1.5 ml safe-lock Eppendorf tubes containing whole brain samples on ice.  These samples were homogenized for 30 seconds with a bead homogenizer (Bullet Blender, Next Advance inc.) using 5-7 Zirconium Oxide beads.  After a 5 minute incubation at room temperature (RT), 200µl Chloroform was added and tubes were shaken by hand to mix and incubated again for 3 minutes.  Tubes were then centrifuged at 12,000g (at 4oC) for 15 minutes.  The organic layer was removed to a fresh 1.5ml tube into which 500µl isopropyl alcohol was then added.  After mixing and a further 10 min RT incubation, tubes were centrifuged a second time at 12,000g and 4oC for 10 minutes to form an RNA precipitate at the base of the tube.  The supernatant was removed and the pellet washed with chilled 75% ethanol, then centrifuged once more at 7500g and 4oC for 5 minutes.  After removing ethanol, tubes were air dried at 37oC and RNA re-dissolved in 40µl pure water (DEPC water, Sigma).  Re-dissolved 1µl samples of RNA extracts were then checked for RNA presence and genomic DNA contamination on 1% Agarose gels with SYBR safe nucleic acid binding dye.  All 42  14 samples yielded gel staining patterns indicative of high RNA yields with very low genomic DNA contamination.   RNA yields were quantified through absorbance readings of dissolved RNA at 260 nm measured with a spectrophotometer.  All RNA samples were then diluted with pure water to a concentration of 68 ng/µl and frozen at minus 80oC prior to cDNA synthesis.  cDNA  was later reverse-transcribed from RNA in 200µl PCR reaction tubes containing 10µl diluted RNA samples in a total volume of 20µl prepared following manufacturers instructions (High-Capacity cDNA Reverse Transcription Kit, Applied Biosystems).  All reactions contained RNase inhibitor, and thermal cycler conditions similarly followed manufacturers recommendations.  All 42 samples were prepared using the same reagent mix and were performed simultaneously on the same thermal cycler (PT-200, MJ Research). Measuring Gene Expression by qPCR Primers specific to GR1, GR2, POMC, and GAPDH were designed using Primer Express 3.0 based on cDNA sequences for Gasterosteus aculeatus accessed through the Ensembl genome browser (v. 71.1).  Primer sequences are given in Chart 1.  The housekeeping gene GAPDH was chosen as a background control to normalize qPCR results because expression levels of GAPDH in the threespine stickleback brain and in other tissues are typically very consistent, a trend that persists even under chronic predation threat stress treatment (Sanogo et al. 2011; Thomson et al. 2011).  The qPCR reactions for each gene were carried out on a single 96-well plate containing duplicate sets of 42 samples, one blank, and five standard curve dilutions (1, 0.25, 0.04, 0.008, and 0.0016 X) of pooled cDNA from each of the 42 individuals.  To each well was added 20µl of a master mix containing SYBR® green (10µl), pure water (9.2µl), and forward and reverse primers (0.4µl each at 10µM) and 1µl of cDNA.  Reactions yielded mean Ct values (the first cycle number at which fluorescence is significantly greater than a defined background level) for each well which were compared against the standard curve to generate an expression value for each well relative to standards.  This value was averaged over the two duplicate  15 wells, which was then divided by GAPDH expression to provide a final expression level for each of the 42 individuals analyzed. Chart 1: Primers (5’ to 3’) used in qPCR gene expression assays.  Determining Sex DNA Extraction Genomic DNA was extracted from caudal fin clips which were collected following brain dissection and preserved in 95% EtOH. A phenol-chloroform extraction followed by precipitation in 95% EtOH and a wash in 70% EtOH was used to isolate DNA following overnight digestion of tissue in Proteinase K.  The precipitate was re-suspended in 50µl TE buffer (10mM Tris, pH 8.0; 1mM EDTA, pH 8.0) and stored at 4oC until later sampling.   PCR and Gel Reading PCR reactions targeting the IDH (isocitrate dehydrogenase) gene were performed on diluted (5ng/ul) DNA samples.  This locus shows a sex-chromosome specific polymorphism in the 3’ UTR which can be used to infer genetic sex with a high degree of confidence (Peichel et al. 2004).  After a PCR following conditions described in Peichel et al (2001), reaction products were separated for 2h on a 2% agarose gel with SYBR safe nucleic acid binding dye.  Reaction products from male Gene Forward Primer Reverse Primer Amplicon  GR1 CAGCGCCGTGTCTCTCAAC CGGCTAGCACCAGACTGTTCT 61 bp GR2 CAGCGGCTTGCTGAATGA CGTTGGTAGAGTTCAATTCTTTGC 60 bp POMC TGGGAACATCCAAGCTGTCA GCTCGACGCACTCCATCAT 59 bp GAPDH CAAACCGTTGGTGACAGTATTTG GCACTGAGCATAAGGACACATCTAA 69 bp  16 DNA display a characteristic 271 bp product, while both sexes show amplification of a 302 bp product.  Primers used were identical to those used by Peichel et al (2004).  Sex ratios (29F:33M) in treated and untreated groups were found to be identical, and at least one individual from each sex was found in each of the 11 clutches included in the study.  Statistical Analysis Maternal stress levels and parental genetics may be expected to influence brain gene expression levels as well as behavioural outcomes of interest.  To incorporate these potential sources of inter-clutch variation into the analyses, mixed-effect linear regression models incorporating clutch as a random effect (in the intercept) were used to test the effects of cortisol treatment and sex on boldness, aggression, and relative brain expression of GR1, GR2, and POMC.  This model was also used to test the assumption that GAPDH expression levels are insensitive to early-life cortisol treatment and sex, and was comparable in design to models used in similar  studies (McCairns and Bernatchez 2010; Marasco et al. 2012).  For behavioural outcomes, body mass was included as a covariate due to an anticipated contribution to aggression and boldness scores based on previous work (Travis 1994).  Distributions of all data analyzed with these models were visually inspected beforehand for normality and transformations were used when necessary.  To this end, emergence latency scores as well as expression ratios for GR1, GR2, and POMC were natural log-transformed, while aggression scores were square root transformed.  Residual plots for all linear mixed models were inspected for assumptions of normality and equal variance, and are presented in the appendix.  One individual (male, treated) was excluded from all gene expression analyses because expression for all genes (including GAPDH) was very low, likely due to problems in the cDNA synthesis step.  Furthermore, two individuals with extremely low POMC expression (possibly indicating problems in the quantitative PCR step) were excluded from the analysis of POMC data.  These individuals were both male  17 (one treated, one untreated) and did not show extraneous expression levels in GR1 or GR2.  To test the effect of treatment on average nearest neighbor distance, a paired t-test comparing treated and untreated halves of each clutch was used.  Spearman’s rank correlation tests were used to examine relationships between all brain gene expression levels and behavioural outcomes.  These correlation tests were carried out on mean family-level values for each of the outcomes in order to meet the assumption of independence between data points.  All statistical analyses were performed in PASW (SPSS) Statistics version 18.0, and all results are considered statistically significant at α=0.05.                18 Results Behavioural The distribution of log transformed emergence latency scores for all 122 individuals for which data were collected closely matched the assumption of normality (figure 1).  Mixed model analysis of these latency scores revealed a strong effect of sex (p=0.002), but no significant effect of treatment (p=0.559) or of body mass (p=0.974) (tables 1&2).  Three fish failed to emerge within the 600 second limit (treated female, untreated female, and treated male), and 2 fish escaped before the beginning of the assay and no data could be collected.   Male fish had significantly lower emergence latency scores (which are associated with higher boldness levels) than did female fish (figure 2).  No significant interaction between sex and treatment was found when an interaction term was incorporated into the model. In the assays for aggression, one individual failed to approach the intruder within 5 minutes of intrusion and so was not included in the analysis (male, untreated).  The distribution of aggression scores the remaining 123 individuals did not differ strongly from normality (figure 3).  The analysis of these scores revealed a similar effect of sex, with males showing higher levels of aggression than females (p= 0.017) (figure 4).  In addition, higher body mass was associated with lower aggression scores (p=0.025).  As was the case for boldness, there was no effect of cortisol treatment on aggression (p=0.382) (tables 3&4). Shoal density as measured by average NND did not differ significantly between treated and untreated halves of clutches (paired t-test, df=9, t=-0.45, p=0.66).   Gene Expression GAPDH expression among all fish included in the gene expression analyses (n=41) was distributed normally (figure 5).  Expression of this gene was not found to be significantly associated with sex (p=0.555), mass (p=0.396), or cortisol treatment (p=0.164) (table 5).    19 Natural log transformed GR1, GR2 and POMC relative expression levels for all individuals included in mixed model analysis were also normally distributed (figures 6-8).  Relative expression levels for each gene in each sex and treatment category are shown in table 6.  The mixed model analysis of relative GR1 expression revealed that sex did not contribute significantly to GR1 levels (p=0.333), but that treatment was modestly associated with increased expression (p=0.043) (table 7).  GR2 analysis found similar results, with no contribution of sex (p=0.229) and a moderate increase in relative expression amongst cortisol-treated individuals (p=0.054) (table 8).  In contrast, relative POMC expression was significantly lower in male fish compared to females (p=0.008), but no effect of cortisol treatment was detected (p=0.550) (table 9).  The inclusion of body mass as a covariate did not improve the fit or lead to a significant change in the coefficients of the other variables in the models for gene expression, nor did the inclusion of a treatment-by-sex interaction term. Within-clutch differences in GR1 expression between treated and untreated groups, and in POMC expression between females and males illustrate the findings of the mixed models (figures 9&10). Correlations Non-parametric family-level rank correlations (n=11) between exit latency and aggression scores revealed no significant association between the two behavioural measures (rho= -0.291, p=0.291, figure 11).  High GR2 expression was associated with low emergence latency scores (rho= 0.125, p=0.083, figure 12), as was GR1 expression (rho=-0.491, p=0.125), though neither relationship was significant.  There were no significant correlations between any of the genes of interest and aggression scores, nor were there any correlations detected between GR and POMC expression levels (table 10).  However, GR1 and GR2 expression levels were found to be tightly linked (rho=0.718, p=0.013, figure 13)     20 Discussion Gene Expression   The results of this study suggest that in-ovo cortisol treatment at physiologically relevant levels post-fertilization induces a mild increase in glucocorticoid receptor expression relative to background expression levels.  This effect is detectable in both GR1 and GR2, though the strong correlation between the two genes suggests that the effects on each are likely not independent despite their localization on separate chromosomes.   One noteworthy aspect of the apparent increase in GR expression is the fact that it shows the opposite effect from expectations based on glucocorticoid-mediated maternal effects in mammals.  In experimental studies in that taxon, down regulation of glucocorticoid receptors in response to fetal glucocorticoids, elevated stress levels in early development, and lack of maternal care is well supported (Liu et al. 1997; Seckl and Meaney 2004).  This down-regulation is thought to influence later-life physiological and behavioural outcomes because chronically low levels of GR diminish negative feedback of plasma glucocorticoid levels.  The function of GR in negative feedback is conserved in teleosts, leaving no immediate reason to expect that the effects of early-life glucocorticoid exposure on GR expression might oppose those described in rats and other mammal species (Bernier et al. 2009).       Expression of POMC did not show any sensitivity to cortisol treatment in this study, though it was significantly higher in females than in males.  POMC expression is significant for HPI axis functioning because it is spliced into ACTH (which promotes glucocorticoid release downstream) during post-translational modification.  The difference in POMC expression between males and females may thus suggest a role for POMC in establishing the behavioural differences between the sexes that were also observed in this study, because the lower aggression and boldness levels in females are indicative of a ‘reactive’ coping style typified by higher HPI activity  21 (Koolhaas et al. 1999).  However, the many roles of other POMC cleavage products make interpretation of these findings difficult.  For example, those other products include α- and β-MSH, hormones which interact with melanocortin receptors at various sites throughout the body to increase pigmentation, steroid production, aggression, and sexual activity, and to decrease inflammation, nociception, and food intake (Ducrest et al. 2008).  Though no sex differences in brain POMC expression have been reported for fish, estrogen suppression of POMC in rats is thought to explain lower expression levels in females (Wilcox and Roberts 1985; Aird et al. 1997).  As previously mentioned, the varied roles of the post-translational products of POMC make it difficult to gauge the significance of this pattern.  Gene-Behaviour Correlations Previous studies in fish and other vertebrates linking high levels of GR expression to higher boldness and aggression would lead to the expectation that the same correlation should be detected in this study (Schjolden et al. 2009; Piato et al. 2011; Aubin-Horth et al. 2012).  However, this was not observed.  Though both GR2 and GR1 had a weak positive association with boldness, this correlation in each case was not significant.  In addition, neither gene was associated strongly with aggression scores. One possible explanation for the lack of correlation is simply that a low sample size (n=11) prevented individual-level correlations between GR and behaviour from being detected.  However, another explanation is that the inherently complex relationship between gene expression and behaviour often means that, even with standard behavioural assays in well-studied species, attempts to find correlations between the two can be fruitless (Thomson et al. 2011).  In the case of the aggression assay in particular, it does appear that another ‘external’ factor contributed to measured outcomes and possibly increased within-family variance, leading to a lack of correlation  with GRs.   Specifically, the fact that lower body mass individuals showed significantly higher aggression levels suggests the possibility that inter-individual differences in hunger level may have confounded measurements.  This is probably because fish were not  22 fed during the two days of behavioural testing, which is one day longer than they would typically go without food.  In fish, hunger (over the short term) is known to increase territoriality as well as the rate and intensity of aggressive attacks (Symons 1968; Dill et al. 1981).  In addition, smaller individuals have fewer body fat reserves as well as higher metabolic demands and are expected to suffer the effects of food deprivation much more rapidly than are larger individuals (Krause et al. 1998).  This may explain the observed relationship between body mass and aggression that was found in this study, and also raises the possibility that an effect of food deprivation on aggression levels masked any influence of GR receptor expression on aggression.  This may have led to the deviation from expectations based on previous studies in which subjects were presumably well-fed.  It is worth noting that hunger is also linked with higher boldness in fish, which suggests that hunger was not a factor in boldness assays (Brown and Braithwaite 2004).  Since those assays were done on the first day of testing a few hours after being fed, this is not surprising.    Behaviour  The linear mixed model analysis of aggression and boldness data did not detect any effect of early cortisol treatment on either behavioural outcome.  Assuming momentarily that the lack of correlation between GRs and those behaviours in this study was due only to measurement error and that the typical correlation between expression and behaviour was conserved in these fish, this result is surprising.  If cortisol treated fish have up-regulated GR, the expectation based on previous studies would be that treated fish should be bolder and more aggressive than untreated fish.  These predictions would not match what is known based on mammalian (rat) studies, but recent experimental work in fish has raised the possibility that behavioural changes following early glucocorticoid exposure may differ between fish and mammals.  Unlike rats, cortisol treated fish (brown trout) were found to be more aggressive than untreated individuals, an effect which is magnified when treated fish occupy a dominant position in social hierarchies (Sloman 2010; Eriksen et al. 2011).  The increased GR expression seen in these fish – in opposition to the decreased GR expression seen in rats – may provide a  23 physiological explanation for the apparently divergent glucocorticoid-mediated behavioural changes seen in the two groups.  However, the lack of a treatment effect on aggression and boldness in this study does not directly lend support the argument that GR expression may underlie those opposing behavioural responses .  One possible reason that no relationship between cortisol treatment and behaviour was detected may be that the treatment methodology was insufficient to induce the long-term changes in aggression and boldness observed in similar studies.  Though the effects on gene expression suggest that at least some hormone entered the eggs, it is possible that higher concentrations of diffused cortisol or a more prolonged exposure inside the body of the mother are required to measurably alter behaviour.  The latter seems unlikely considering that previous post-fertilization treatments have altered behaviour in other fish species, and that maternal glucocorticoids appear unlikely to influence HPI-axis development until at least a few hours post-fertilization (Burton et al. 2011; Nesan and Vijayan 2012).   Another possibility is that the behavioural assays selected for this study were ineffective in measuring the behaviours they sought to describe.  In their defense, however, the assays were at least successful in detecting sex differences in aggression and boldness that mirror previous findings.  In juvenile stickleback, sex differences in aggression begin to emerge between 18 and 21 weeks of age, with males being the more aggressive of the sexes after this point (Bakker 1985).  Thus, the observed increase in aggression in males meets expectations for stickleback at  approximately 24 weeks of age.  Boldness is also commonly elevated in males relative to females, and similar emergence latency assays used to quantify boldness in Brachyrhaphis episcopi found that males were the bolder of the two sexes (Brown et al. 2007).  This difference is presumably due to differences in life-history priorities, with males commonly taking greater risks as a response to more intense reproductive competition (Wilson and Daly 1985).  The cortisol treatment did not replicate the results of a previous study showing that stressed stickleback mothers produce offspring with tighter shoaling behaviour  24 (Giesing et al. 2011).  This may indicate that changes in shoal density are not due to cortisol alone, or that cortisol interacts with other stress-related maternal inputs such as mRNA levels or egg size differences to induce those changes.  Alternatively, the difference in tank size (100 vs. 26.5 litres) used in this study may have influenced the development of shoaling behaviour leading to different outcomes.  Behavioural Correlations In teleost fish and other vertebrates, bold individuals are commonly more aggressive, spend more time in exposed areas, and recover from stressful stimuli more readily than shy individuals (Sneddon 2003; Sih et al. 2004).  Because this behavioural covariance is also reported in threespine sticklebacks, the lack of a significant correlation between boldness and aggression in this study is unexpected (Dingemanse et al. 2007).  Though the direction of the relationship between boldness and aggression matched predictions, a low sample size of 11 families may have contributed to the lack of significance.  Family-level differences in body mass (which appears to have influenced aggression but not boldness scores) may have also weakened the correlation if otherwise passive families displayed abnormally high aggression levels that were driven by hunger rather than ‘baseline’ personality traits.  However, some populations of stickleback have been seen to depart from the typical aggression-boldness behavioural syndrome; a decoupling that is thought to be driven by opposing selection pressures on the two behaviours (Bell 2005).  The possible nature of any divergent selection regime in the Trout Lake sample population is unclear, though the possibility remains that these behaviours could be decoupled in Trout Lake stickleback. Significance The apparent up-regulation of GR1 and GR2 receptors was an interesting and somewhat unexpected outcome of this study.  Most of the previous work on maternal glucocorticoid exposure has shown that, in rats at least, a GR down-regulation linked with reduced glucocorticoid feedback sensitivity and a prolonged physiological response to acute stress is the norm (Liu et al. 1997; Ladd et al. 2004).   25 Based on what is known about the roles of glucocorticoid receptors in fish, it is possible to draw a few predictions based on the findings in this study.  For one, the role of GRs in negative feedback sensitivity appears to be conserved between teleost fish and mammals (Bradford et al. 1992).  If feedback sensitivity is heightened in fish with early life glucocorticoid exposure, it is possible that individuals exposed to higher maternal cortisol levels may have a shorter period of glucocorticoid release following stressful stimuli when compared with individuals exposed to lower maternal cortisol concentrations.  Though this study focused on the downstream behavioural consequences of alterations to HPI-functioning, the roles of glucocorticoid hormones in other aspects of organismal physiology are diverse.  Based on these roles, a decrease in the magnitude and duration of glucocorticoid release following stress may have the effect of decreasing glucose availability following stress, but also of promoting the muscle growth, reproductive, and immune system functions which are impaired by heightened HPI-axis reactivity (Bonga 1997; Mommsen et al. 1999).  Interestingly, the increased exposure to cortisol of maternal origin during early development is thought to negatively impact both growth and immune functions in fish, which may imply that later-life reductions in glucocorticoid activity in highly exposed individuals could serve to partially offset the detrimental early life impacts of that exposure (Li and Leatherland 2012). Another consideration is the possibility that decreased glucocorticoid reactivity following stress could represent a form of adaptive developmental programming of the HPI-axis by maternal cortisol.  For example, the short term benefits of glucose release following stressful stimuli may be outweighed by the negative consequences of growth, reproductive, and immune divestment in environments where conditions are such that stress levels remain chronically high.  In those cases, a high maternal glucocorticoid level may signal to developing offspring that a reduction in HPI-axis reactivity may be beneficial.  The differences in GR expression following early glucocorticoid exposure between this study and previous rat studies may be indicative of alternative selection regimes operating in the two species.  If  26 environments are characterized by short-duration, high intensity rather than chronic stressors, increased HPI-axis reactivity may benefit animals by providing them with a more abundant plasma glucose stores following stress.  However, it should be said that the complex roles of glucocorticoids in both rats and fish may make these types of simplistic predictions inaccurate.  In addition, the lack of any observed phenotypic changes (other than GR increase) following early glucocorticoid exposure in this study highlights the need for further investigation into the hypothesized links between elevated GR expression, plasma cortisol levels, behaviour, and stress-induced glucose release rates following prenatal GC exposure in threespine stickleback.  Future experimental studies in natural environments comparing survival outcomes in individuals with differing glucocorticoid exposure levels may also help clarify whether maternal glucocorticoids have negative, positive, or neutral effects on offspring fitness.    Caveats One issue in the experimental design and subsequent interpretation of results is the fact that any effects due to tank – which includes any effects of early life social environment – are not accounted for in the linear model used to assess treatment and sex effects on gene expression and behaviour.  Though paired tanks (treated and untreated clutch halves) were placed near each other in space to minimize effects of tank, differences in temperature, light intensity, or unintentional variation in feeding may have impacted results.  Perhaps more likely, social conditions within tanks may have influenced results by altering gene expression and behavioural outcomes.  In fish, the influence of social interactions and the formation of dominance hierarchies on behaviour and brain expression levels can be significant (Fernald 2012).  For this reason, any observed effects due to treatment or to sex may have been influenced by tanks effects, or by their interactions with those tank effects.   The behavioural testing protocol presents another potential issue.  For one, stress incurred during the two-day behavioural assay sequence may have manipulated  27 gene expression levels.  In Zebrafish, high levels of stress have been shown to influence expression levels in at least some of genes of interest in this study (Piato et al. 2011; Oswald et al. 2012).  If this is the case, the observed difference in gene expression between treated and untreated groups may only reflect differences that emerge when animals are stressed.  It is also important to keep in mind that although the experimental cortisol exposure here is meant to mimic effects of maternal stress on offspring development, it does not incorporate all possible effects of that stress.  Other potentially important factors sensitive to maternal stress levels include differential deposition of maternal mRNAs, differences in yolk concentration of non-glucocorticoid hormones, egg size differences, as well as behavioural interactions with offspring post-hatch. Gene expression assays revealed a tight correlation between GR1 and GR2 expression in brain tissue which was similar in strength to that seen in a separate study of breeding adult male stickleback (Nadia Aubin-Horth, Personal Communication).  However, sequencing of PCR products would help rule out the possibility that primers used in real time PCR assays failed to differentiate between the two fairly conserved cDNA sequences of these genes. Finally, population differences in selective regimes may mean that response to glucocorticoid exposure, sex differences, as well as the strength of correlations between gene expression and behavioural outcomes may differ depending on the population under study.  For this reason, it is important to keep in mind that only a single population was utilized in this study, and that the results may not be representative of the species as a whole.  Future studies utilizing alternative populations of threespine stickleback would help determine how confidently results can be generalized. Future Directions A major goal of this research was to improve the utility of the threespine stickleback as a model organism for investigating the potential role of glucocorticoid-mediated maternal effects in adaptation and as a mechanism for transgenerational phenotypic  28 plasticity (Mousseau and Fox 1998). Though this study was able to produce some results that may assist future researchers investigating these themes, there are many remaining questions.  For one, it is unclear whether differences in GR mRNA are translated directly into higher receptor concentration, and where in the brain these differences might be manifested.  Receptor localization is particularly important for interpreting the consequences of expression changes following maternal stress exposure because the function of GRs can vary from region to region within the brain (Meaney et al. 1985; O'Donnell et al. 1994).  The specific roles of GR1 and GR2 have not been studied in threespine stickleback, which is similarly problematic for interpreting the significance of changes in expression because their function in teleosts appears to be species-specific (Alderman et al. 2012).  Future studies of the functions and tissue localizations of GR1 and GR2 in stickleback would be valuable.  In addition, the effect of GR expression on the magnitude and duration of cortisol release in fish requires further study, and future experiments could test the hypothesis that increased GR expression following early GC exposure leads to more abrupt elevations of plasma cortisol concentration following stress later in life. Further clarification of these physiological mechanisms would facilitate comparisons between wild stickleback populations experiencing different levels of natural and human imposed (e.g. environmental toxicants) stressors.  If maternal effects play a role in tailoring organizational responses to these stressors, it is possible that epigenetic signatures of glucocorticoid exposure and differences in GR expression could be detected in stressed populations.  In humans and rats, methylation of neuron-specific GR promoters has been found to accompany changes in GR expression that arise from differences in maternal care and childhood experience (Weaver et al. 2004; McGowan et al. 2009). It is unknown whether similar mechanisms operate in stickleback or other fish, and this is an open area for future investigations. Conclusion  29 This study shows that whole-brain expression of glucocorticoid receptors in threespine stickleback increases following a physiologically relevant in-ovo cortisol exposure.  This contradicts previous findings in mammalian models, and helps clarify the role of glucocorticoid mediated maternal effects in shaping offspring behaviour and physiology in fish.  Although cortisol treatment influenced gene expression, neither shoaling, aggression nor boldness were strongly affected by treatment.  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Males  Females Treated  Untreated Emergence Latency (s) 49 ± 13 114 ± 21 82 ± 17 77 ± 17 Ln [Emergence Latency] 3.09 ± 0.15 3.90 ± 0.19 3.41 ± 0.18 3.53 ± 0.17 N 65 57 61 61 Parameter  Estimate 95% CI  (lower,upper) Confidence Sex Female       Male             Referent -0.75    –  ( -1.22, -0.29 )     – 0.002 Treatment Untreated  Treated       Referent -0.14    – ( -0.60 , 0.32 )    – 0.559 Mass 0.032 ( -1.92, 1.98 ) 0.974   Table 3: Mean Aggression scores (± SE) in both untransformed and square-root transformed formats for groups of interest.    Table 4: Estimated effects of mixed model components on aggression scores (√(nips/minute)).  N=123.           Males Females Treated  Untreated Aggression  (nips/min) 8.32 ± 0.95 5.43 ± 0.72 7.82 ± 1.01 6.09 ± 0.69 √ Aggression  2.61 ± 0.15 2.07 ± 0.14 2.48 ± 0.16 2.23 ± 0.14 N 65 58 62 61 Parameter Estimate 95% CI  (lower,upper) Confidence Sex Female       Male             Referent 0.50   – ( 0.09 , 0.90 )    – 0.017 Treatment Untreated  Treated       Referent 0.18    – ( -0.23 , 0.59 )  – 0.382 Mass -1.85 ( -3.45 , -0.25 ) 0.025   Table 5: Estimated effects of mixed model components on GAPDH expression.  N=41.    Gene Male Female Treated  Untreated Overall GR1 1.31 ± 0.09 1.46 ± 0.13 1.50 ± 0.11 1.27 ± 0.10 1.38 ± 0.08 GR2 1.11 ± 0.06 1.22 ± 0.07 1.24 ± 0.07 1.09 ± 0.06 1.16 ± 0.05 NGR1&2 23 18 20 21 41 POMC 0.88 ± 0.09 1.23 ± 0.15 1.01 ± 0.09 1.08 ± 0.15 1.04 ± 0.09 NPOMC 21 18 19 20 39  Table 6: Mean expression levels (relative to GAPDH) of each gene of interest for each focal group ± standard error.  Sample sizes for GR (upper) and POMC (lower) expression are also provided.     Parameter Estimate 95% CI (lower,upper) Confidence Sex Female       Male             Referent 0.05   – ( -0.13 , 0.24 )    – 0.555 Treatment Untreated  Treated       Referent -0.13    – ( -0.32 , 0.06 )  – 0.164 Mass -0.33 ( -1.1 , 0.45 ) 0.396   Table 7: Estimated effects of mixed model components on relative GR1 expression (Ln[GR1/GAPDH]).     Table 8: Estimated effects of mixed model components on relative GR2 expression (Ln[GR2/GAPDH]).       Parameter Estimate 95% CI (lower,upper) Confidence Sex Female       Male             Referent -0.045   – ( -0.14 , 0.05 )    – 0.333 Treatment Untreated  Treated       Referent 0.096    – (0.003 , 0. 19 )  – 0.043 Parameter Estimate 95% CI  (lower,upper) Confidence Sex Female       Male             Referent -0.043   – ( -0.11 , 0.03)    – 0.229 Treatment Untreated  Treated       Referent 0.069    – ( -0.001 , 0.14 )  – 0.054   Table 9: Estimated effects of mixed model components on relative POMC expression (Ln[POMC/GAPDH]).     Aggression Boldness GR1 GR2 Aggression 1 – – – Boldness rho= -0.291 p= 0.385 1 – – GR1 rho= -0.091 p= 0.790 rho= -0.491 p= 0.125 1 – GR2 rho= -0.155 p= 0.650 rho= -0.545 p= 0.083 rho= 0.718 p= 0.013 1 POMC rho= -0.291 p= 0.958 rho= -0.027 p= 0.937 rho= 0.418 p= 0.201 rho= 0.309 p= 0.355  Table 10:  Correlation matrix for family-level averages for gene expression and behavioural outcomes.  Correlations are tested using Spearman’s rank correlation with n=11.  Variables are compared in the same units as for mixed linear regression model. Parameter Estimate 95% CI  (lower,upper) Confidence Sex Female       Male             Referent -0.157   – ( -0.27 , -0.04)    – 0.008 Treatment Untreated  Treated       Referent -0.033    – ( -0.15 , 0.08)  – 0.550 Figures     Figure 1: Distribution of emergence latency  scores (ln-transformed) with normal  distribution overlaid.  Mean=3.47, N=122,   s=1.39, SE=0.13.     Figure 2: Within-Clutch differences in emergence latency scores in ln[seconds]. Differences given as female average – male average          Figure 3: Distribution of aggression scores. Mean=2.36, N=123, s=1.19, SE=0.11.       Figure 4: Within-Clutch differences in Aggression scores (√nips/min). Differences given as male average – female average    Figure 5: Distribution Of GAPDH expression levels. Mean=0.83, N=41, s=0.28, SE=0.04        Figure 6: Distribution of relative GR1 expression levels.  Mean=0.85, N=41, s=0.194, SE=0.03.     Figure 7: Distribution of relative GR2 expression levels.  Mean=0.76, N=41, s=0.135, SE=0.02       Figure 8: Distribution of ln relative POMC expression. Mean=0.68, N=41, s=0.238, SE=0.04     Figure 9: Within-clutch differences in GR1 expression between treated and untreated halves.  Differences in Ln[GR1/GAPDH] are given as treated average – untreated average     Figure 10: Within-clutch sex differences in POMC expression.  Differences in Ln[POMC/GAPDH] are given as female average – male average.            Figure 11: Family-level ranked correlation between emergence latency and aggression scores. (rho= -0.291, p= 0.291)     Figure 12: Ranked family-level correlation between emergence latency and GR2 expression. (rho= 0.125, p=0.083)   Figure 13: Ranked family-level correlation between GR1 and GR2 expression levels. (rho= 0.718, p=0.013)  Appendix: Residual Plots for Linear Mixed Models          


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