Plastic sex-trait modulation by differential gene expression according to social environment in male red deer

Plastic sex-trait modulation by differential gene expression according to social environment in male red deer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Plastic sex-trait modulation by differential gene expression according to social environment in male red deer Camilla Broggini, Nieves Abril, Alberto Membrillo, Eva de la Peña, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4085936/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Mate competition encourages individuals to modulate characters involved in mating success. Adult Iberian red deer ( Cervus elaphus hispanicus ) males show a dark ventral patch (DVP) that plays a central role in mating rivalry, whose size and chemical compounds varied according to the level of male-male competition within the population. In the pigmentation of the DVP appears, after urinary excretion, a molecule called DOPEG originating from the metabolism of norepinephrine, leading us to investigate whether differential expression mechanisms of key genes (DBH and TH) encoding enzymes catalyzing the process can be sensitive to different competitive population situations and responsible for the plastic development of the DVP in red deer. We found that social environment with higher intrasexual competition, where male invest more in sexual traits, was associated with increased levels of DBH and TH transcripts, while Dopamine showed reversed values. We found alternative splicing for the TH gene, although differences between social environments appeared just related to expression levels. Our results support the internal cause of trait modulation based on differential gene expression in relation to the conditions of intrasexual competition in social environment. We propose the quantification of DBH transcripts as a molecular biomarker of male red deer reproductive activity. Biological sciences/Genetics Biological sciences/Molecular biology Cervus elaphus sexual traits mate competition dark ventral patch development real time PCR gene expression Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sexual selection promotes the development of traits related to intrasexual competition or mate choice [1]. Many of these sex-traits are costly, and selection pays individuals to modulate trait development leading to the evolution of adaptive plasticity [2, 3]. Phenotypic plasticity results in the production of a different phenotype depending on the environment the organism faces [4, 5 ]. Phenotypic variation in sex traits may be caused by production costs and constraints imposed by external (environmental) or internal (condition) variability [ 6 , 7 ]. But also, variation in trait development is expected according to the estimated benefits under specific strategies to cope with environmental variations [ 8 , 9 ]. For plastic bimodal traits, the shifting from one stage to another is accomplished by the existence of reaction norms and thresholds [10, 11]. Thresholds of change may affect a suite of physiological and behavioral processes, that can be influenced by environmental cues causing the modulation of genomic activity. Molecular technology has allowed the genomic perspective in the study of plasticity to greatly expand during the last decade [12]. Understanding the complex mechanisms in the interface between the DNA sequence and the phenotypes, involving biased candidate gene expression and associated processes within adaptive reaction norms, constitutes a growing area of research [13]. The success in terms of fitness of a given sex-trait production and associated reproductive strategy, should be highly dependent on the strategies used by other individuals in the population [14]. Specifically, the number of rivals with respect to potential mates in social environment, should directly affect the expected benefits from investing in a given trait that males use to outcompete others for the access to females [8]. The red deer ( Cervus elaphus ) is a good model species for sexual selection studies. It is a polygynous species in which adult males compete to hold harems or mating territories [15-17]. The mating strategy of male red deer includes the development of sex traits, either weapons or signals, such as the antlers [ 9 , 18] and the dark ventral patch [19, 20]. In this species, it has been shown that sex traits are flexibly modulated according to competition level in the social environment, i.e., the number of rivals with respect to mates in the population [9, 19]. Male red deer under conditions of low intra-sexual competition develop smaller antlers than males under conditions of high intra-sexual competition [ 9 ], and they also modulate the expression of volatile compounds that are present in the dark ventral patch according to high or low intra-sexual competition situations [19]. Likewise, fecal testosterone and cortisol metabolite levels are also associated with social environment being higher or lower depending on competition context [21]. The dark ventral patch is a quality signal that conveys information about the mating effort during the rut [19, 22]. Males with larger patches are more involved in the rut and achieve higher mating success than males with small patches [21]. Unlike antlers, which develop several months before the rutting season, the dark ventral patch can be modulated in the short term due to urine spraying behavior [22]. Previous studies [23] have shown that the mechanism responsible for the stained ventral patch is a catecholamine-based process of pigmentation associated with a urine spraying behavior in which urine is spread through the ventral body area. Certain compounds synthesized in the adrenal glands and excreted in the urine, such as catecholamines, are hormones that contribute to stress response and can be oxidized by air producing dark pigments. This is the case of DOPEG (DL-3,4-dihydroxyphenyl glycol), an alcoholic compound that appears in the urine and whose concentration was positively correlated with the size of the dark ventral patch [23]. In the metabolic pathway of catecholamines (Figure 1) the precursor of norepinephrine is the dopamine (DA). DA was not found in the urine of sampled individuals [23]; in contrast, unusually high concentration of norepinephrine was observed, leading to take under consideration the enzyme responsible of catalyzing the processes, the Dopamine B-hydroxylase (DBH). The release of catecholamines is a key initial event and it is followed by an increase or a decrease in the expression of genes that encode catecholamine-synthesizing enzymes [24]. Volatile compounds present in the hairs of the ventral patch vary with the level of mate competition (i.e., the abundance of male rivals in the population relative to females) [19], and we hypothesize that this could be due to gene-environment interactions. DNA encodes the potential for cellular behavior, but that potential is only realized if the gene is expressed - if its DNA is transcribed into RNA and translated into protein. Because RNA transcription shapes the protein complement of cells, and those proteins mediate cellular function, psychological regulation of gene expression implies that the social environment can remodel the functional characteristics of the body [25]. Since it has been shown that males under high competition conditions showed larger dark patches (and higher concentration of metabolite) comparing to males from low competition situations [19, 22], plastic modulation of gene expression according to the different social environmental conditions of sexual competition may affect individual concentration of metabolite depending on the conditions in which the animal lives. The aim of this work was to investigate the mechanism responsible for the plastic modulation of the dark ventral patch in male red deer according to variations in male-male competitive level in social environment. In particular, whether the development of an individual’s ventral patch is based on a differential gene expression mechanism that is sensitive to the competitive situation in the population. Specifically, our main objective was to quantify the expression of the DBH gene, as it encodes the dopamine beta-hydroxylase, the enzyme that catalyzes the hydroxylation of dopamine to produce norepinephrine, as the precursor to DOPEG, which has been demonstrated to be the responsible for the staining of hairs in the dark ventral patch during the rut [23]. We wanted to investigate whether DBH gene expression was related to the size of the dark ventral patch, and whether this gene expression varied according to the level of intrasexual mating competition in the population, as it has been shown for the size of the dark ventral patch [19, 22]. Additionally, we explored the link between expression of the TH gene and plasma dopamine levels, as a confirmatory checking of the results for DBH based on the relationships between compounds in the main metabolic pathway of catecholamine biosynthesis (Figure 1). Thus, we predicted higher TH and DBH expression levels in the high competition situation, where males should invest more in sexual traits, while plasma dopamine levels may present a reverse relationship, as it is depleted by the action of DBH to produce norepinephrine. Also, we expected higher TH and DBH expression levels in those individuals that developed larger dark ventral patches. Methods Study areas, competitive level of red deer populations The study was conducted on Iberian red deer ( Cervus e. hispanicus ) in southwestern Spain. In this study area, red deer occur in hunting estates under two types of different management systems that lead to neat differences in population structure and in the level of male intrasexual competition [26, 27]: specifically, males of all ages are hunted in open areas because they become a shared resource for neighboring estates, while in fenced estates only some adult males are hunted when they reach trophy ages [27]. Consequently, it leads to two contrasting populational situations: (1) nearly natural population structure, in fenced estates, with high intrasexual competition for mates (HC), and (2) female-biased populations with young males, in unfenced estates, with low competition between males (LC). No other remarkable features have been found to differ between these two types of estates, either in habitat, supplementary feeding or any other potential stressors, besides the level of male-male competition [26, 27]. Sample collection Since previous studies have shown that the mechanism of pigmentation is based on the excretion of high amounts of norepinephrine metabolite deposited on the fur by the urinating behavior during the rut [23], adrenal glands, being responsible for the synthesis and the secretion of norepinephrine, were collected from 45 Iberian male red deer culled during hunting seasons from 2018/2019 to 2021/2022 in south-western Spain. To investigate differences between males subjected to different populational conditions, 19 samples from four populations were collected in areas with high mating competition (HC) and 26 samples from five populations were collected in areas with low mating competition (LC). The distribution of the sampling across hunting seasons and months, and the number of samples collected each season in both conditions are summarize in Supplementary Table S1. For this study, all samples were collected from carcasses of individuals that did not show clinical signs of disease and that were hunted during ordinary hunting activities based on official hunting plans. This means that our study never provoked hunters to shoot additional animals specifically for the purpose of this research. For the dark ventral patch, longitudinal size from the penis to the end of the dark spot at the breast or the base of the neck was measured with a ruler [23]. Mandibles were collected for age determination in the laboratory, as in previous studies [28], by counting cementum growth marks at the interradicular pad under the first molar [29] and by checking eruption patterns in younger animals. Our access to the hunting estates was approved by their management authorities while ethical issues regarding this study were revised and agreed by the Wildlife Research Unit at the University of Cordoba (UIRCP-UCO). This study was carried out in line with ARRIVE guidelines as our methods and experiment were performed in accordance with relevant regulations. Once collected, the samples were cut into slices less than 0.5 cm thick and immediately immersed in a sufficient volume of RNAlater™ RNA Stabilization Reagent. Samples were kept at 4 °C in the field and then stored at − 20 °C till use. RNA isolation and cDNA synthesis RNA extraction from adrenal glands preserved in RNAlater™ was carried out using the commercial RNeasy Mini Kit (Qiagen) according to the manufacturer’s protocol. Total RNA was extracted from 30 mg of RNAlater™ stabilized tissue; we tried tissue disruption both with the Tissue-Lyser method and by using liquid nitrogen to find the best alternative. 600 μL of lysis buffer were added and after centrifugation (3 minutes; 16,000 xg), the whole supernatant was passed to a new tube. Next, 900 μL of 70% EtOH were added and after pipetting, a volume of 700 μL were transferred to a spin column and centrifugated for 15 s at 8,000 xg. Once discarded the first flow-through, centrifugation was repeated with the remaining volume using the same column. Removal of gDNA was performed by treating the RNA retained in the column with DNase I (QIAGEN) following the manufacturer protocol. Lastly, the Filter Cartridge was transferred to a new tube and the RNA eluted with 50 μL RNeasy-free water (preheated to ~75 °C), denatured by heating at 55–65 °C for 10 min, immediately cooled on ice for at least 5 min, and kept at -80 °C till use. Purity and concentration of isolated RNA preparation was determined spectrophotometrically using a Nanodrop® one spectrophotometer (Thermo Scientific) while its integrity was determined using an Agilent 2100 Bioanalyzer (Agilent Scientific Instruments) system, which assigned an RNA Integrity Number (RIN) from 1 (totally degraded) to 10 (completely intact) to each sample. The iScript cDNA Synthesis Kit (BIORAD) was used to generate cDNA according to manufacturer’s instructions. Primer design and qRT-PCR conditions Primer pairs for absolute quantification of the transcriptional levels of the dopamine beta hydroxylase (DBH) and the tyrosine hydroxylase (TH) genes were designed with the Oligo 7 software (Molecular Biology Insights) (Table 1). Table 1. Primers used in this work. Use GenBank Acc. Number Sequence 5´-3´ b Length c (bp) Amplification eficiency d (R 2 ) Reference Target a Determination of C. elaphus gene sequence e DBH NW_001493002.2 F: ACCCGGCAGCCTCCCGCTCACCAGG 421 na f This study R: AGGGGGAGTGAGCAGGGCGATGGGGGTC qRT-PCR quantification g DBH XM_043916405 F: GAGGCCATCAACACCTCCGGCTTGCAC 127 0,9979 (99,81%) This study R: TGAGGACATCGGGGGCGCGGATCTCCATG TH 10-11 OWK17426 F: CTGGGGCACGTGCCCATGCTCGCT 166 0,9897 (98,96%) This study R: AGGCCTTCACCTCCCCGTTCTGCTTGCAC TH 2-3 XM_043923566 F: GGCCAAGGGCTTCCGCCGGGCCGTC 173 0,9977 (99,56%) This study R: CCAGGCTGCCCGCCTCCCTGGGTTCCGAG Calibrator gene h A170 U57413 F: GGAAGAGAAGCCGCCTGACACCCACT 113 1.0001 (99.9%) [30] R: CCCGTCAGGTTTGCTGACTTCCGAAG a Gene symbols are according to the NCBI Gene database. b Sequence of forward (F) and reverse (R) primers. c PCR product size in base pair (bp). d The real-time PCR efficiencies (E) were calculated from each standard curve according to the equation E = 10 (-1/slope) -1. E is in the range from 0 (minimum value) to 1 (maximum and optimum), i.e., E = 1 is equal to 100% efficiency. e Primers based on Bos taurus sequence designed to determine the orthologous C. elaphus sequence. f Not applicable. g Primers based on C. elaphus sequences were designed for absolute quantification by real-time RT-PCR. h Inter-Run Calibrator gene: A170 transcripts are quantified in the same calibrator RNA sample included in each run to combine or compare data from different runs/experiments. We used primers previously designed (Pelayo et al ., 2012) against the Bos taurus DBH gene sequence (NW_001493002.2) to amplify the orthologous fragment in C. elaphus cDNA. With the obtained C. elaphus DBH sequences we designed specific primers to be used in qRT-PCR. Using the red deer gene sequence deposited in the GenBank database (NCBI, https://www.ncbi.nlm.nih.gov/genbank/ ) we designed TH primers. Since TH mRNA in other species like humans [31] has been shown to present alternative splicing, we designed two primer pairs to quantify TH mRNA isoforms. The primer pair TH 10-11 allows the quantification of any TH isoform variant; in contrast, the pair TH 2-3 only quantifies the splicing variants carrying the exon 2. All primers for qRT-PCR were targeted towards the protein-coding region of the mRNAs, having high melting temperature (Tm ≥73 °C) and optimal 3‘ΔG (≥ −6 kcal/mol) values, to obtain the highest specificity and performance. The specificity of the primers was evaluated using 1% agarose gel electrophoresis of their PCR amplicons, while their efficiency was assessed by amplifying a 10-fold dilution series (resulting in a concentration range from 20 to 2×10 5 pg) of a mixture of all cDNA samples in quadruplicate [32]. The slope of the standard curve achieved by plotting the obtained C T values against the RNA amount per well was used to calculate the efficiency according to the equation E=10(−1/slope) −1 [32]. Real-time PCRs were performed in quadruplicate (four technical replicates for each biological replicate and transcript) as detailed previously [ 3 0]. No primer dimers were detected, and the investigated transcripts showed optimal PCR efficiencies (from 0.98 to 1.00). The high Tm of the designed primers allowed a two-step protocol including a denaturation step (94°C, 15 s) and a hybridization/extension step (70ºC, 30 s) for each of the 40 cycles performed after the polymerase activation step (98°C, 4 minutes). Reactions were performed and fluorescence read in a CFX-96 Touch Real-Time PCR Detection System (Bio-Rad), using 50 ng of cDNA (2 μl) per reaction and the SSo Advanced Universal SYBR® Green Supermix (Bio-Rad) kit, according to the manufacturer’s instructions. After each PCR reaction, a melting curve analysis was run to ensure the specificity of amplification. After establishing the fluorescence threshold by using a calibrator gene [30, 33], the absence of signal in the negative control (non-template sample) was checked before reading the C T values. Then, the C T values were transferred to Microsoft Excel converted into absolute transcript numbers by using a calibration curve constructed with an external standard as previously described [ 3 0, 33 ] and normalized by using stable genes under our experimental conditions. Then, the mean of the transcript values obtained was calculated as the average of the four replicates if the SD was less than 20%; otherwise, the transcript value of the outlying sample was removed from the study and the remaining data (at least n = 3) were reanalyzed [34]. Selection of reference genes Primer pairs for performing stability analysis to identify genes to be used as normalizers (reference genes) in our qRT-PCR study have already been described [34]. Following the MIQE guidelines (https://www. gene-quantification.de/miqe-index.html) as previously described [35-37], we determined the C T values for each candidate gene (Pgk1, Rplp0 and Gapdh) in all adrenal gland mRNA samples, regardless of their provenance (fenced or unfenced farms). The obtained C T values were used in the free web tool RefFinder (www.heartcure.com.au/reffinder/?type=reference), which pointed out Pgk1 and Rplp0 as stable genes under our experimental conditions (Figure 2). Quality control for qRT-PCR We analyzed the expression at the transcriptional level of two genes, TH and DBH, involved in the catecholamines metabolic pathway, by using the qRT-PCR methodology according to the MIQE Guidelines [35-37]. To ensure RNA quality, adrenal glands samples were collected and conserved in RNAlater™ solution and kept frozen till use [34]. RNA was extracted with the RNeasy Mini Kit (Qiagen) following the manufacturer recommendations. RNA preparations were considered pure when their ratios of absorbance A 260 /A 280 and A 260 /A 230 were in the range of 2.0–2.2. RNA integrity was evaluated by using an Agilent 2100 Bioanalyzer: all RNA samples in this study were of sufficient quality to be used in transcript quantification by qRT-PCR [38]. The success of PCR is highly dependent on primer design, as primers are the main determinants of its specificity and sensitivity [34]. Primers to amplify the red deer TH and DBH genes were carefully designed to assure total specificity and efficiency in the amplification reactions, using the OLIGO 7 Primer Analysis Software (Molecular Biology Insights, Inc., http://www.oligo.net) as previously described [34]. After optimizing PCR conditions (annealing temperature and concentration) for each primer pair, primer’s specificity was experimentally evaluated by visualizing the PCR products in agarose gels, which were excised and sequenced and by carrying out melting curves at the end of the PCR reaction. In all cases, primer pairs targeting TH and DBH produced one specific amplicon of the expected size and sequence, exhibiting, in the melting curve, a single peak. Dopamine measurement Dopamine is an important compound in the DOPEG biosynthetic route (see Fig. 1 and below, Fig. 4) and it may be depleted by the action of DBH to produce norepinephrine. To measure plasma dopamine levels, blood samples were collected from the infraorbital sinus in 10 ml anticoagulant EDTA-containing tubes. Samples were kept on ice in the field and then centrifuged for 20 minutes at approximately 1,000xg; they were subsequently stored at -20°C for later use. We decided to work with 6 samples (3 HC and 3 LC) as a test to confirm our previous gene expression results. For quantitative measure of dopamine in serum, we used the Enzyme-Linked Immunosorbent Assay Kit (ELISA Cloud-Clone Corp.) following the manufacturer’s protocol. This pan-species assay has excellent specificity and elevated sensitivity for the detection of dopamine. It is a competitive inhibition enzyme immunoassay technique that allowed us to measure the concentration of dopamine in the samples. Every sample was duplicated, as recommended, at optimal sample dilution and at 1/6 dilution, obtaining repetitive results. Statistical analyses We used a linear mixed-effects model (LMM) using the identity link function to predict the link between DBH gene expression and the intrasexual mating competition level in the population (LC and HC) and the sexual trait development (dark ventral patch (small vs. large) controlling for the day of the year as covariable and population identity nested within hunting season, and hunting season, as random sources of variation. The size of the dark ventral patch has been shown to follow a bimodal distribution that reveals its role as a discrete sexual signal [22]. Hence, we used here as in previous works the size of the dark ventral patch (DVP) in two categories [21], small (corresponding to low trait expression, LTE, in previous papers) and large (corresponding to high trait expression, HTE). To ratify the results that arise from this first model, we also run another linear mixed model with the same structure but using the dark ventral patch size instead of the categorical variable (dark ventral patch expression). For TH, we performed a linear model for the most common isoform, but without random effects due to the small sample size that produced model singularity. For confirmatory checking of the role of TH transcripts and DA plasma concentrations in the metabolic route, unpaired Student’s t-tests were employed for comparisons, with significance level at two-tailed p<0.05. Population identity was introduced as random factor in models. The variables used in this study were age (in years), the month and the season when samples were collected, and the sizes (in centimeters) of the dark ventral area (Supplementary Table S1). We performed all statistical analyses in R version 4.2.1 [39], using the package lme4 [40] for mixed-effect models and ggeffects [41]. We calculated the significance of predictors using the ‘Anova’ function from the car package, performing likelihood ratio tests for linear mixed-effect models and F tests for linear models [42]. Normality of the residuals and homoscedasticity were confirmed by visual inspection and Shapiro–Wilk tests. To avoid multicollinearity between variables, we calculated the variance inflation factors (VIFs) [43] of each model using the package “usdm” [44]. We did not find any evidence of collinearity for any of the models (VIF < 3). Results DBH gene expression The expression levels of the gene encoding the dopamine beta-hydroxylase (DBH), the enzyme that catalyzes the hydroxylation of dopamine to produce norepinephrine (Figure 1), ranged from a minimum value of 8.48 transcripts/pg of total RNA to 548.75 transcripts/pg of total RNA as a maximum value. In agreement with the results obtained for the TH gene, we also found increased amounts of DBH transcripts, approximately higher than 65%, in red deer males under high-competitive conditions (HC), i.e., mean ± SD DBH expression values of 299.33 ± 130.60 while individuals in LC populations presented mean ± SD value of 181.35 ± 98.92. According to the dark ventral patch size (DVP), the mean ± SD expression of the DBH gene for large-DVP individuals was 255.98 ± 135.31 transcripts/pg of total RNA while for small-DVP individuals it was 200.14 ± 110.13 transcripts/pg of total RNA. When comparing the expression levels of red deer under LC versus HC situations, we found, as shown in Table 3, a significant relationship for the TH 10-11 variant. The mean for the longer isoform (amplified with TH 2-3 primers only) was 30% higher in HC animals. For the most abundant exon 2-free isoform, the mean number of transcripts was 64% higher for red deer in high (HC) compared to low (LC) mating-competition situations (see Figure 4 below). Focusing on the most abundant isoform, TH 10-11 (hereinafter TH), gene expression ranged from a minimum value of 369.6 transcripts/pg of total RNA to a maximum of 844.1 transcripts/pg of total RNA. Regarding the relationship between TH transcripts and the size of the dark ventral patch (DVP), we found that the mean ± SD of TH gene expression for individuals with large DVP was 658.43 ± 192.83 transcripts/pg of total RNA and for small-DVP individuals it was 633.88 ± 100.47 transcripts/pg of total RNA. We found that individuals from HC populations showed mean ± SD of TH gene expression of 754.38 ± 97.16 while individuals in LC populations presented 482.14 ± 100.46 mean ± SD of TH gene expression. The linear model exploring the factors that explained the differences in TH gene expression, showed a significant effect of the level of mate competition on TH expression, being higher in HC populations (Table 3). See also summarized results in Figure 4 (below). Table 3. Factors affecting TH 10-11 gene expression. LM model with logit as link function to explore the effect of the level of mating competition in the population (LC vs HC) and the sex trait dark ventral patch size (Small and Large) on the TH gene expression. Significant effects are showed in bold (p-value 0.001 Dark ventral patch (Small) -21.30 ± 88.38 0.058 0.809 Dopamine in blood samples As expected from the role of the DBH in eliminating dopamine synthetized from the product of TH activity, we found lower plasma levels of dopamine (DA) in red deer under HC conditions (see Figure 4). The mixed model performed to explore the potential effect of the mating competition level in the population and the development of the dark ventral patch expression on the DBH gene expression, revealed significant differences only between the two types of populations according to the mating-competition level (Table 2A). In populations with intense intrasexual competition for mates (HC), DBH gene expression was significantly higher than in low intrasexual-competition populations (LC). However, in our data, the dark ventral patch expression did not show significant relationships with DBH gene expression. Regarding the mixed model carried out to ratify these results by using the dark ventral patch size (continuous variable), we also found a significant relationship between the DBH gene expression and the mating competition level in the population (Table 2B). No significant results were found in both models for the day of the year in the DBH gene expression. See summarized results in Figure 4 (below). Table 2. Factors affecting DBH gene expression. LM model to explore the link between the DBH gene expression and both the mating competition level (LC vs HC) and the sex trait dark ventral patch size (Small and Large in A, and as continuous variable in B), controlling by the day of the year. Reference levels are shown in brackets. Significant effects are showed in bold (p-value < 0.05). Term Estimate ± S.E. p-value A) Fixed effects Intercept 196.75 ± 61.31 Day of year 10.32 ± 25.84 0.217 0.641 Mating competition (LC) 87.52 ± 29.30 8.922 0.002 Dark ventral patch (Small) 15.40 ± 25.84 0.355 0.551 B) Fixed effects Intercept 205.35 ± 59.51 Day of year 11.90 ± 22.32 0.580 0.594 Mating competition (LC) 87.22 ± 29.28 8.871 0.002 Dark ventral patch size (cm) 10.18 ± 13.37 0.580 0.446 TH transcript alternative splicing and factors affecting expression The two pairs of TH primers specifically amplified their target sequence (Figure 3) generating unique amplicons of 166 bp (TH 10-11 ) and 173 bp (TH 2-3 ) with Tm values of 88 ºC and 91 ºC, respectively. Thus, at least two TH mRNA isoforms exist in the adrenal gland of C. elaphus . Of these, the complete N-terminal isoform (which was only amplified by the TH 2-3 primer pair) was in the minority. The transcript containing the exon 2 (amplified only by TH 2-3 primers) was found to be 3.3-4.2 times less abundant than the exon-2 spliced version, in both LC and HC animals (see Figure 4 below). Discussion Our results supported the hypothesis of plastic modulation of the route responsible for the development of the dark ventral patch in male red deer, by the regulation of the expression levels of key genes. Transcription appeared upregulated in environments with high level of male intrasexual competition, thus suggesting the adaptive role of gene expression to shape the mating competitive strategy of male red deer. The social environment with high intrasexual competition for mates associated with higher transcript counts of TH and DBH genes, supported (within the metabolic pathway of catecholamine) the activation of the complete DOPEG biosynthetic route when males experienced the conditions of high intrasexual competition for mates. TH and DBH are enzymes that both contribute to the stimulation of DOPEG production; however, they have opposing roles with respect to dopamine, as DBH degrades dopamine synthetized from TH activity. To elucidate the biological implications of our transcriptional data, we measured the abundance of dopamine in the blood of the animals studied. Plasma levels of dopamine were lower in HC deer, according to the predictions from the route to DOPEG with DBH activity boosted in HC animals, in agreement with the increased transcript amounts of the DBH gene. Another interesting finding was that at least two TH mRNA isoforms exist in the adrenal gland of red deer. The use of two primer pairs targeted toward different exons allowed us to uncover the existence, and importance, of such splicing alternatives. TH encodes the rate-limiting enzyme in the biosynthesis of catecholamines. It catalyzes the hydroxylation of tyrosine to L-DOPA, a precursor of dopamine (DA), norepinephrine (NE), and epinephrine (EP), the hormone responsible for the fight-or-flight response. Catecholamines play significant roles as hormones and neurotransmitters in both the central and peripheral nervous systems [45]. These catechol monoamines are involved in various brain functions, including attention, memory, cognition, and emotion [46]. Therefore, imbalances in catecholamine levels can have numerous consequences, from hypertension to bipolar disorder or addiction [46] and the regulation of TH, the slowest enzyme in the pathway, is complex and tightly regulated [46-48]. RNA splicing is a key mediator of transcript and protein diversity, used to produce different isoforms of a protein from a particular gene and obtain a better functionality [49]. In humans, four isoforms are produced from a single TH gene by alternative mRNA splicing in the N-terminus, whereas two isoforms in monkeys and only a single protein has been described in other non-primate mammals [50]. These four isoforms are identical in their central catalytic domain (~ 300 amino acids, aa) and C-terminal tetramer-forming domain (~ 40 aa). However, they differ in their N-terminal regulatory domains, distinguished by 4 aa encoded by a 12 nt sequence at the 3′-terminus of exon 1 and 27 aa encoded by the 81 nt of exon 2 [50]. The presence/absence of the aa encoded by exon 1 and, mainly, exon 2, introduces some differences in the kinetic parameters of this forms regarding to TH consistent with the altered kinetics of phosphorylation and dephosphorylation. The importance of these differences remains elusive but is well known that phosphorylation in exon 2 results in an increase of the Ki value for dopamine [51]. For cattle ( Bos taurus ), which was used here as a reference organism for designing primers when the red deer sequence was not present in databases, the Ensembl database ( http://www.ensembl.org ) describes three different transcript isoforms that vary in the regulatory region. Among these variants, only transcript TH 2-3 retains exon 2, which contains two phosphorylation sites absent in the others, resulting more susceptible to inhibition by dopamine [51]. For red deer adrenal gland, we quantified separately the number of TH 10-12 transcripts and of those that retain exon 2 (TH 2-3 ), to analyze the possible correlation between populational conditions and the abundance of each splicing variant. The results (summarized in Figure 4) show higher amounts of both TH transcripts under high-competition environment, although the difference was significant only for the TH 10-12 isoform. In fact, this exon 2 free TH mRNA splicing variant (TH 10-12 ) was much more abundant (over three-fold) than the other. Favoring the TH variant that is less sensitive to dopamine inhibition [51] may enhance the synthesis of other catecholamines along the route leading to the development of DOPEG and hence the staining of hairs of the ventral patch [23]. TH has been found related to sexual activity in domestic rams [52] and TH transcripts were higher in sexually competitive male zebra finches [53]. An open question is whether TH expression is a cause or a consequence of such sexually competitive ability. Some studies suggest that TH expression may be the consequence of individual’s behavior during competition, although the question remains open [53-54]. In addition, it is known that under stress conditions, TH is regulated by enzyme induction at the transcriptional level [55]. A sexually competitive situation in red deer entails high stress conditions [21], which suggests that competitive stress may be a potential mechanism triggering gene expression related to the development of traits used in competition. In this sense, experiencing competition and the stress-related conditions may upregulate TH gene expression. Regardless this experience begins before and/or during the rutting season, it would contribute to cause-effect feedback relationships between male intrasexual competition and the development of flexible sexual traits. Thus, for a short-term flexible structure such as the dark ventral patch based on current urine deposits and oxidization, the link between TH gene expression and the sex trait with its related competitive behavior may be a continuous process of reinforcement during the duration of the rutting season. The increase in catecholamine biosynthesis that can occur in response to repeated or chronic exposure to a variety of stressors, is associated with elevated activity of the catecholamine-synthesizing enzymes [24]. Thus, animals experiencing such conditions would express distinctive amounts of TH, that catalyzes the conversion from tyrosine to dopamine and of DBH, the enzyme that catalyzes the conversion from dopamine to norepinephrine. This might lead to the, somehow odd, hypothesis that stress conditions would increase the development of the sexual signal. Against this hypothesis, the size of the dark ventral patch was found not related to cortisol level and even a negative relationship was true for young red deer (2-years-old) in our study area [20]. Therefore, the regulation of gene expression related to trait development should also be modulated by factors other than simple stress. Several papers have shown that variations in immediate environment can elicit rapid changes in hormones and behavior, and short-term changes in sex steroid release and hormone action may provide a mechanism for flexible multimodal display in response to fluctuating environmental conditions [56]. The mechanism suggested here for a flexible trait development and associated behavioral display [21] represents a rare example of adaptive regulation based on gene expression. DBH is an enzyme crucial to the balance of DA and NE in the body and it is required for the conversion of dopamine into norepinephrine. It has been described that TH is post-transcriptionally regulated during chronic stress by feedback inhibition by the final catecholamines product. This direct inhibition of TH requires high millimolar concentrations of dopamine and is impaired when the N-terminus of the protein is present and phosphorylated [55]. Neither of these two requirements seem to be achieved in the adrenal gland of deer under HC conditions. Results in Figure 4 show that dopamine is reduced in the plasma of HC deer. These data may be explained by increased levels of the enzyme DBH (Figure 4), which would catabolize DA to NE and other derivatives, thus releasing less DA into the blood, although increased DA uptake by the brain as part of male sexual behavior [57] cannot be ruled out. We know that the DVP is an important sexual signal, encoding chemical [19, 58] and visual information [22], related to the behavioral strategy of males [21]. However, an open question remains on whether this signal may be costly and reliable. Our results on DA, although scarce in sample size and hence preliminary, suggest a possible hypothesis. Dopamine is a neurotransmitter that contributes to general alertness and willingness to fight, so its presence should help success in competition. If the DVP signal is based on using dopamine to achieve the black spotting through the pathway to DOPEG, thereby decreasing the dopamine circulating levels available for other effects, we could be dealing with a handicap-type signal. That is, males with black spots that win fights would be demonstrating that they do so despite having less circulating dopamine. The DVP would be a reliable sign of dopamine “destruction”; dominant males with DVP may honestly indicate their quality because they become dominant despite destroying dopamine. Anyway, this is so far just a hypothesis, and we cannot rule out other possible costs related to TH or DBH production, so it would be necessary to conduct new work and desirably experimental design. Many regulatory mechanisms are orchestrated between the genome transcription and the translation of proteins, which are responsible for most of the phenotypic characteristics of an organism [59]. From earlier studies comparing mRNA with protein abundancy in some biological models [59], it was obvious the lack of full concordance. On the biological front, differences could be initially attributed to RNA splicing, differential RNA and protein turnover, post-translational modifications, allosteric protein interactions, and proteolytic processing events. As predicted, higher TH and DBH levels were achieved in the high-competition situation, where males should invest more in sexual traits. However, we also expected a positive relationship between TH and DBH transcripts and the size of the DVP as the focus genes were selected because of their relationship with the route that leads to key compounds of the DVP sexual signal. Despite the amounts of transcripts for both TH and DBH genes were higher in males with large DVP, the differences were not significant in the models. These results might have been affected by our limitations in the timing of sampling. The strongest relationship is expected during the rutting season, but our sampling depended on legal hunting of deer, which takes place after the rutting season. It is possible that, due to their flexible nature, the amounts of transcripts and the development of sexual traits may be decoupled after the rut. Indeed, although phenotypes and gene expression covary, both may not necessarily be in the same temporal phases [60]. Furthermore, the differences in DBH and TH amounts of transcripts between males under HC and LC conditions found for a sampling period shortly after the rutting season, may also suggest a possible benefit after the main sexual competition event, besides their role in the chemical constituents of the DVP. Rutting males typically eat very little during the mating period, which lasts nearly 20 days [61]. Consequently, they experience a significant decline in physical condition [62, 63] and immune response capacity [64], leading to an increase in mortality immediately following the mating period [18]. DBH is involved in the releasing of lactate from skeletal muscle, and the breaking down of amino acids, glycogen, and triglycerides to generate glucose, fatty acids, and ketone bodies [65], which may be important for maintaining functionality under poor nutritional conditions. For the immune response, we have previous evidence from our study area of a positive relationship of host parasitism levels and the size of the dark ventral patch, but this relationship depended on the intensity of male–male competition in the population, being only found under the high-competition scenario [66]. The effect of norepinephrine in the immune system is increasingly acknowledged in regulating immune cells response and the oxidative metabolism of immune cells [67], which suggests a possible role of DBH in the immune function of competitive males after the rut. In conclusion, we have shown that Iberian male red deer modulate the expression of TH and DBH genes according to the level of intrasexual competition that they experienced in their social environments. Males in high competition environments show a more competitive phenotype, including morphological and physiological changes, compared to males in low competition environments. Previous works with red deer demonstrated higher development of sex traits such as the antlers [9] or the dark ventral patch [19, 20, 22] and associated behavior [21] under conditions of high mate-competition. Our results in this study provide new insight into the mechanisms based on the differential expression of genes involved in the biosynthetic route that contributes to these phenotypic differences. Consequently, TH and DBH transcripts quantification may be a good molecular biomarker for red deer involvement in reproductive competition. Future work might focus on flexible changes throughout the rutting period and after it according to mating competition along with the experimental testing of the correlational relationships found. Declarations Acknowledgments Financial support for this work came from project PID2021-127823NB-I00 from Spanish Ministry of Science. Quality analysis of RNA was carried out by the genomics unit of the Central Services for Research Support of the University of Córdoba (SCAI). Author contributions Camilla Broggini contributed to sample collection. Camilla Broggini and Nieves Abril performed material preparation and laboratory work. Nieves Abril analyzed qRT-PCR data. Statistical analyses were carried out by Eva de la Peña. Camilla Broggini, Nieves Abril, Juan Carranza and Alberto Membrillo conceived the study and drafted the manuscript. All authors revised the text, agreed with the content, and gave final approval of the manuscript for publication. Data availability statement All relevant data supporting the results reported in the article are within the paper and its Supporting Information file. Competing Interests The authors declare no competing interests. References 1. Andersson, M. & Iwasa, Y. Sexual selection. Trends Ecol Evol 11 , 53–58 (1996). 2. Piersma, T. & Van Gils, J. A. The Flexible Phenotype: A Body-Centred Integration of Ecology, Physiology, and Behaviour . (Oxford university press, Oxford, 2010). 3. Draghi, J. Phenotypic variability can promote the evolution of adaptive plasticity by reducing the stringency of natural selection. J of Evolutionary Biology 32 , 1274–1289 (2019). 4. Pigliucci, M. Phenotypic Plasticity: Beyond Nature and Nurture . (Johns Hopkins University Press, 2001). 5. West-Eberhard, M. J. Developmental Plasticity and Evolution . (Oxford University Press, Oxford, 2003). 6. Johnstone, R. A. Sexual selection, honest advertisement and the handicap principle: reviewing the evidence. Biological Reviews 70 , 1–65 (1995). 7. Bonduriansky, R. The Evolution of Condition‐Dependent Sexual Dimorphism. The American Naturalist 169 , 9–19 (2007). 8. Gautier, P. et al. The Presence of Females Modulates the Expression of a Carotenoid-Based Sexual Signal. Behavioral Ecology and Sociobiology 62 , 1159–1166 (2008). 9. Carranza, J. et al. Social environment modulates investment in sex trait versus lifespan: red deer produce bigger antlers when facing more rivalry. Sci Rep 10 , 9234 (2020). 10. Schlichting, C. & Pigliucci, M. Phenotypic Evolution: A Reaction Norm Perspective . (Sinauer, 1998). 11. Aubin-Horth, N. & Renn, S. C. P. Genomic reaction norms: using integrative biology to understand molecular mechanisms of phenotypic plasticity. Mol Ecol 18 , 3763–3780 (2009). 12. Lafuente, E. & Beldade, P. Genomics of Developmental Plasticity in Animals. Front Genet 10 , 720 (2019). 13. Chevin, L.-M., Leung, C., Le Rouzic, A. & Uller, T. Using phenotypic plasticity to understand the structure and evolution of the genotype–phenotype map. Genetica 150 , 209–221 (2022). 14. Smith, J. M. Evolution and the Theory of Games . (Cambridge University Press, 1982). doi:10.1017/CBO9780511806292. 15. Carranza, J., Alvarez, F. & Redondo, T. Territoriality as a mating strategy in red deer. Animal Behaviour 40 , 79–88 (1990). 16. Carranza, J., Fernandez-Llario, P. & Gomendio, M. Correlates of Territoriality in Rutting Red Deer. Ethology 102 , 793–805 (1996). 17. Carranza, J. & Valencia, J. Red deer females collect on male clumps at mating areas. Behavioral Ecology 10 , 525–532 (1999). 18. Clutton-Brock, T. H., Guinness, F. E., Albon, S. D. & Barrett, P. Red Deer : Behavior and Ecology of Two Sexes / T.H. Clutton-Brock, F.E. Guinness, S.D. Albon ; with Original Drawings by Priscilla Barrett. (Edinburgh University Press, Edinburgh, 1982). 19. de la Peña, E., Martín, J. & Carranza, J. The intensity of male-male competition may affect chemical scent constituents in the dark ventral patch of male Iberian red deer. PLOS ONE 14 , e0221980 (2019). 20. de La Peña, E., Martín, J., Barja, I. & Carranza, J. Testosterone and the dark ventral patch of male red deer: the role of the social environment. Sci Nat 107 , 18 (2020). 21. de la Peña, E., Pérez-González, J., Martín, J., Vedel, G. & Carranza, J. The dark-ventral-patch of male red deer, a sexual signal that conveys the degree of involvement in rutting behavior. BMC Zoology 6 , 18 (2021). 22. Carranza, J. et al. The dark ventral patch: A bimodal flexible trait related to male competition in red deer. PLoS ONE 15 , e0241374 (2020). 23. Galván, I. et al. Unprecedented high catecholamine production causing hair pigmentation after urinary excretion in red deer. Cell Mol Life Sci 76 , 397–404 (2019). 24. Sabban, E. L. & Kvetňanský, R. Stress-triggered activation of gene expression in catecholaminergic systems: dynamics of transcriptional events. Trends in Neurosciences 24 , 91–98 (2001). 25. Cole, S. W. Social regulation of human gene expression. Curr Dir Psychol Sci 18 , 132–137 (2009). 26. Pérez-González, J. & Carranza, J. Female-biased dispersal under conditions of low male mating competition in a polygynous mammal. Mol Ecol 18 , 4617–4630 (2009). 27. Torres-Porras, J. The tragedy of the commons: unsustainable population structure of Iberian red deer in hunting estates. European Journal of Wildlife Research 60 , 351–357 (2014). 28. Carranza, J., Alarcos, S., Sánchez-Prieto, C. B., Valencia, J. & Mateos, C. Disposable-soma senescence mediated by sexual selection in an ungulate. Nature 432 , 215–218 (2004). 29. Mitchell, B. Growth Layers in Dental Cement for Determining the Age of Red Deer (Cervus elaphus L.). The Journal of Animal Ecology 36 , 279 (1967). 30. Prieto-Álamo, M.-J., Cabrera-Luque, J.-M. & Pueyo, C. Absolute Quantitation of Normal and ROS-Induced Patterns of Gene Expression: An In Vivo Real-Time PCR Study in Mice. gene expr 11 , 23–34 (2003). 31. Kobayashi, K. et al. Structure of the Human Tyrosine Hydroxylase Gene: Alternative Splicing from a Single Gene Accounts for Generation of Four mRNA Types1. The Journal of Biochemistry 103 , 907–912 (1988). 32. Svec, D., Tichopad, A., Novosadova, V., Pfaffl, M. W. & Kubista, M. How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments. Biomol Detect Quantif 3 , 9–16 (2015). 33. Jurado, J., Prieto-Álamo, M.-J., Madrid-Rísquez, J. & Pueyo, C. Absolute Gene Expression Patterns of Thioredoxin and Glutaredoxin Redox Systems in Mouse. Journal of Biological Chemistry 278 , 45546–45554 (2003). 34. Broggini, C., Abril, N., Carranza, J. & Membrillo, A. Evaluation of candidate reference genes for quantitative real-time PCR normalization in blood from red deer developing antlers. Sci Rep 12 , 16264 (2022). 35. Bustin, S. A. et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55 , 611–622 (2009). 36. Hellemans, J. & Vandesompele, J. Selection of Reliable Reference Genes for RT-qPCR Analysis. in Quantitative Real-Time PCR (eds. Biassoni, R. & Raso, A.) vol. 1160 19–26 (Springer New York, New York, NY, 2014). 37. Morales-Prieto, N., Ruiz-Laguna, J., Sheehan, D. & Abril, N. Transcriptome signatures of p,p´-DDE-induced liver damage in Mus spretus mice. Environmental Pollution 238 , 150–167 (2018). 38. Schroeder, A., Mueller, O., Stocker, S., Salowsky, R., Leiber, M., Gassmann, M., Lightfoot, S., Menzel, W., Granzow, M. & Ragg, T. The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Molecular Biol 7 , 3 (2006). 39. R Core Team. R: A language and environment for statistical computing. V.4.2.1. Vienna, Austria: R Foundation for Statistical Computing (2021). 40. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4 . J. Stat. Soft. 67 , (2015). 41. Lüdecke, D. ggeffects: Tidy Data Frames of Marginal Effects from Regression Models. JOSS 3 , 772 (2018). 42. Fox, J., & Weisberg, S. An R companion to applied regression. Sage publications (2018). 43. Alin, A. Multicollinearity: Multicollinearity. WIREs Comp Stat 2 , 370–374 (2010). 44. Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K. & Toxopeus, A. G. Where is positional uncertainty a problem for species distribution modelling? Ecography 37 , 191–203 (2014). 45. Lustberg, D. J. et al. Norepinephrine and dopamine contribute to distinct repetitive behaviors induced by novel odorant stress in male and female mice. Hormones and Behavior 144 , 105205 (2022). 46. Daubner, S. C., Le, T. & Wang, S. Tyrosine hydroxylase and regulation of dopamine synthesis. Archives of Biochemistry and Biophysics 508 , 1–12 (2011). 47. Cousins, D. A., Butts, K. & Young, A. H. The role of dopamine in bipolar disorder. Bipolar Disorders 11 , 787–806 (2009). 48. Koob, G. F. & Volkow, N. D. Neurocircuitry of Addiction. Neuropsychopharmacol 35 , 217–238 (2010). 49. Fisher, E. & Feng, J. RNA splicing regulators play critical roles in neurogenesis. WIREs RNA 13 , e1728 (2022). 50. Nagatsu, T. Catecholamines and Parkinson’s disease: tyrosine hydroxylase (TH) over tetrahydrobiopterin (BH4) and GTP cyclohydrolase I (GCH1) to cytokines, neuromelanin, and gene therapy: a historical overview. J Neural Transm (2023) doi:10.1007/s00702-023-02673-y. 51. Fitzpatrick, P. F. The aromatic amino acid hydroxylases: Structures, catalysis, and regulation of phenylalanine hydroxylase, tyrosine hydroxylase, and tryptophan hydroxylase. Archives of Biochemistry and Biophysics 735 , 109518 (2023). 52. Kramer, A. C., Mirto, A. J., Austin, K. J., Roselli, C. E. & Alexander, B. M. Tyrosine hydroxylase in the ventral tegmental area of rams with high or low libido—A role for dopamine. Animal Reproduction Science 187 , 152–158 (2017). 53. Eswine, S. L., Pontinen, J. K. & Heimovics, S. A. Competitive ability during mate competition relates to unique patterns of dopamine-related gene expression in the social decision-making network of male zebra finches. Neuroscience Letters 706 , 30–35 (2019). 54. Filipenko, M. L., Alekseyenko, O. V., Beilina, A. G., Kamynina, T. P. & Kudryavtseva, N. N. Increase of tyrosine hydroxylase and dopamine transporter mRNA levels in ventral tegmental area of male mice under influence of repeated aggression experience. Molecular Brain Research 96 , 77–81 (2001). 55. Skjevik, Å. A. et al. The N-Terminal Sequence of Tyrosine Hydroxylase Is a Conformationally Versatile Motif That Binds 14-3-3 Proteins and Membranes. Journal of Molecular Biology 426 , 150–168 (2014). 56. Eigerman, A. R. & Mangiamele, L. A. Mechanisms of multimodality: androgenic hormones and adaptive flexibility in multimodal displays. Animal Behaviour 184 , 149–156 (2022). 57. Melis, M. R., Sanna, F. & Argiolas, A. Dopamine, Erectile Function and Male Sexual Behavior from the Past to the Present: A Review. Brain Sciences 12 , 826 (2022). 58. Martín, J., Carranza, J., López, P., Alarcos, S. & Pérez-González, J. A new sexual signal in rutting male red deer: Age related chemical scent constituents in the belly black spot. Mammalian Biology 79 , 362–368 (2014). 59. Buccitelli, C. & Selbach, M. mRNAs, proteins and the emerging principles of gene expression control. Nat Rev Genet 21 , 630–644 (2020). 60. Rittschof, C. C. & Hughes, K. A. Advancing behavioural genomics by considering timescale. Nat Commun 9 , 489 (2018). 61. Mysterud, A., Bonenfant, C., Loe, L. E., Langvatn, R., Yoccoz, N. G. & Stenseth, N. C. Age‐specific feeding cessation in male red deer during rut. Journal of Zoology 275 , 407–412 (2008). 62. Yoccoz, N. G., Mysterud, A., Langvatn, R. & Stenseth, N. Chr. Age– and density–dependent reproductive effort in male red deer. Proc. R. Soc. Lond. B 269 , 1523–1528 (2002). 63. Apollonio, M., Merli, E., Chirichella, R., Pokorny, B., Alagić, A., Flajšman, K. & Stephens, P. A. Capital-Income Breeding in Male Ungulates: Causes and Consequences of Strategy Differences Among Species. Front. Ecol. Evol. 8 , 521767 (2020). 64. Vicente, J., Pérez-Rodríguez, L. & Gortazar, C. Sex, age, spleen size, and kidney fat of red deer relative to infection intensities of the lungworm Elaphostrongylus cervi. Naturwissenschaften 94 , 581 (2007). 65. Hartmann, C., Radermacher, P., Wepler, M. & Nußbaum, B. Non-Hemodynamic Effects of Catecholamines. Shock 48 , 390–400 (2017). 66. De La Peña, E., Martín, J., Barja, I., Pérez‐Caballero, R., Acosta, I. & Carranza, J. Immune challenge of mating effort: steroid hormone profile, dark ventral patch and parasite burden in relation to intrasexual competition in male Iberian red deer. Integr. Zool. 15 , 262–275 (2020). 67. Thoppil, J., Mehta, P., Bartels, B., Sharma, D. & Farrar, J. D. Impact of norepinephrine on immunity and oxidative metabolism in sepsis. Front. Immunol. 14 , 1271098 (2023). Additional Declarations The authors declare no competing interests. Supplementary Files Supplementaryinformationfinal.docx Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4085936","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":285141906,"identity":"b1efa22a-b88e-428f-b51a-11c60a399dcb","order_by":0,"name":"Camilla Broggini","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYDAC9uZjDIwNDAz8xGvhOZYG1iLZQLQWCR8zsBaDA8TqkJ/BYPa4csc9eeMbyQ8fMFTUEdbCOLsh3fDsmWLDbTfSjA0YzhwmrIVZ5sAxyca2hASzGzlsEoxtRDiPTSKxDazFeAZIyz8iHMYjkcwG1mIgAdLSwExYiwTPMXbDxjMJhjPOPDM2SDhGhF/k2/u/PWzckSDP3w4MsQ81RDgMFSSQqmEUjIJRMApGAXYAABoCN3TgbZ1vAAAAAElFTkSuQmCC","orcid":"","institution":"University of Córdoba","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Camilla","middleName":"","lastName":"Broggini","suffix":""},{"id":285141907,"identity":"78919632-b2de-4a57-a5e8-3f5330e59ab5","order_by":1,"name":"Nieves Abril","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nieves","middleName":"","lastName":"Abril","suffix":""},{"id":285141908,"identity":"ea139f04-4bf6-4fe3-b78a-48d99c836767","order_by":2,"name":"Alberto Membrillo","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Membrillo","suffix":""},{"id":285141909,"identity":"c15f245e-4dff-477e-b30c-01b9569267a3","order_by":3,"name":"Eva de la Peña","email":"","orcid":"","institution":"Institute for Game and Wildlife Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eva","middleName":"de la","lastName":"Peña","suffix":""},{"id":285141910,"identity":"84174dbf-375f-4401-bcd9-25bd55dfa25a","order_by":4,"name":"Juan Carranza","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Juan","middleName":"","lastName":"Carranza","suffix":""}],"badges":[],"createdAt":"2024-03-12 16:22:00","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-4085936/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-4085936/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66208732,"identity":"d5d0e926-71be-463f-bb42-fbcac4d20e6c","added_by":"auto","created_at":"2024-10-08 17:12:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85042,"visible":true,"origin":"","legend":"\u003cp\u003eMain metabolic pathway of catecholamine biosynthesis. The pathway begins with the hydroxylation of tyrosine to L-3,4- dihydroxyphenylalanine (DOPA), which is catalyzed by tyrosine hydroxylase (TH). DOPA decarboxylase (DDC) converts DOPA to dopamine (DA); then, the synthesis of norepinephrine (NE) from dopamine is catalyzed by dopamine B-hydroxylase (DBH). Norepinephrine is then metabolized by monoamine oxidase (MAO) into Norepinephrine aldehyde which is converted by Aldehyde reductase into DOPEG that is finally excreted in the urine.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4085936/v2/814eadfdd816ae57289af591.jpeg"},{"id":66208020,"identity":"66f470ef-7371-4485-9e9c-0fd27f527b14","added_by":"auto","created_at":"2024-10-08 17:04:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61643,"visible":true,"origin":"","legend":"\u003cp\u003eStability ranking of candidate reference genes. Determined by the RefFinder tool that uses and incorporates the results of the comparative ΔC\u003csub\u003eT\u003c/sub\u003e, BestKeeper, NormFinder and geNorm.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4085936/v2/701c13fc3f0d3c21695a9422.png"},{"id":66208016,"identity":"bf03f164-5708-4793-b6e5-4a320a6c3ba2","added_by":"auto","created_at":"2024-10-08 17:04:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":157877,"visible":true,"origin":"","legend":"\u003cp\u003eAlternative splicing in the \u003cem\u003eC. elaphus\u003c/em\u003e TH gene. (a) Location of the forward and reverse component of each primer pair. (b) Gel (agarose 2%) showing the specificity of the amplicons obtained with each TH primer pair in cDNA and gDNA; in both cases one band of the expected size, without or with the corresponding intron, was obtained. Original electrophoretic gel is presented in Supplementary Figure S2. (c) Amplification and melting curves obtained with each TH primer pair; only one sequence was generated in each case, with Tm values of 88 °C and 91 °C, respectively, for TH\u003csub\u003e10-11\u003c/sub\u003e (166 bp) and TH\u003csub\u003e2-3\u003c/sub\u003e (173 bp).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4085936/v2/418f004ede17605f4cd616ca.png"},{"id":66208021,"identity":"3059cd2f-0242-47ff-a1fc-d25db42280aa","added_by":"auto","created_at":"2024-10-08 17:04:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":45418,"visible":true,"origin":"","legend":"\u003cp\u003eSummarized results on the activation of the DOPEG biosynthetic route in red deer. (a) Absolute transcript counts per pg of total RNA for the expression of TH\u003csub\u003e10-11\u003c/sub\u003e and TH\u003csub\u003e2-3\u003c/sub\u003e splicing isoforms in the adrenal gland of male red deer from HC comparing to the reference group (LC). (b) Dopamine quantification (pmol/mL) in the plasma of the same animals. (c) Absolute quantification of DBH gene expression at the transcriptional levels. In each of the three cases bars represent mean ± SD of three independent determinations in at least three individuals per group; all samples were collected in the same year and in the same month. Small arrows aside the main route depict compound’s changes for HC compared to LC individuals. For statistical significance of the differences between HC and LC animals, p values are indicated as resulting from the linear models for TH\u003csub\u003e10-11\u003c/sub\u003e and DBH, otherwise significance is after unpaired Student t-tests.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4085936/v2/01d76fd3e17feaa615d874ba.png"},{"id":66209012,"identity":"43ed9ef7-d585-4b97-be63-c614bc17260e","added_by":"auto","created_at":"2024-10-08 17:20:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":968145,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4085936/v2/fca62a45-884b-466f-a226-9557ee79ed9a.pdf"},{"id":66208734,"identity":"bb4a8e79-f349-416b-b134-db880a414219","added_by":"auto","created_at":"2024-10-08 17:12:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":222544,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformationfinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-4085936/v2/8e8071211f2178429425057b.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePlastic sex-trait modulation by differential gene expression according to social environment in male red deer\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSexual selection promotes the development of traits related to intrasexual competition or mate choice [1]. Many of these sex-traits are costly, and selection pays individuals to modulate trait development leading to the evolution of adaptive plasticity [2,\u0026nbsp;3]. Phenotypic plasticity results in the production of a different phenotype depending on the environment the organism faces [4,\u0026nbsp;\u003ca href=\"#Quinto_titolo\"\u003e5\u003c/a\u003e]. Phenotypic variation in sex traits may be caused by production costs and constraints imposed by external (environmental) or internal (condition) variability [\u003ca href=\"#Sesto_titolo\"\u003e6\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#Settimo_titolo\"\u003e7\u003c/a\u003e]. But also, variation in trait development is expected according to the estimated benefits under specific strategies to cope with environmental variations [\u003ca href=\"#Ottavo_titolo\"\u003e8\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#Nono_titolo\"\u003e9\u003c/a\u003e]. For plastic bimodal traits, the shifting from one stage to another is accomplished by the existence of reaction norms and thresholds [10, 11]. Thresholds of change may affect a suite of physiological and behavioral processes, that can be influenced by environmental cues causing the modulation of genomic activity. Molecular technology has allowed the genomic perspective in the study of plasticity to greatly expand during the last decade [12]. Understanding the complex mechanisms in the interface between the DNA sequence and the phenotypes, involving biased candidate gene expression and associated processes within adaptive reaction norms, constitutes a growing area of research [13].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe success in terms of fitness of a given sex-trait production and associated reproductive strategy, should be highly dependent on the strategies used by other individuals in the population [14]. Specifically, the number of rivals with respect to potential mates in social environment, should directly affect the expected benefits from investing in a given trait that males use to outcompete others for the access to females [8].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe red deer (\u003cem\u003eCervus elaphus\u003c/em\u003e) is a good model species for sexual selection studies. It is a polygynous species in which adult males compete to hold harems or mating territories [15-17]. The mating strategy of male red deer includes the development of sex traits, either weapons or signals, such as the antlers [\u003ca href=\"#Nono_titolo\"\u003e9\u003c/a\u003e, 18] and the dark ventral patch [19, 20]. In this species, it has been shown that sex traits are flexibly modulated according to competition level in the social environment, i.e., the number of rivals with respect to mates in the population [9, 19]. Male red deer under conditions of low intra-sexual competition develop smaller antlers than males under conditions of high intra-sexual competition [\u003ca href=\"#Nono_titolo\"\u003e9\u003c/a\u003e], and they also modulate the expression of volatile compounds that are present in the dark ventral patch according to high or low intra-sexual competition situations [19]. Likewise, fecal testosterone and cortisol metabolite levels are also associated with social environment being higher or lower depending on competition context [21].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe dark ventral patch is a quality signal that conveys information about the mating effort during the rut [19, 22]. Males with larger patches are more involved in the rut and achieve higher mating success than males with small patches [21]. Unlike antlers, which develop several months before the rutting season, the dark ventral patch can be modulated in the short term due to urine spraying behavior [22]. Previous studies [23] have shown that the mechanism responsible for the stained ventral patch is a catecholamine-based process of pigmentation associated with a urine spraying behavior in which urine is spread through the ventral body area. Certain compounds synthesized in the adrenal glands and excreted in the urine, such as catecholamines, are hormones that contribute to stress response and can be oxidized by air producing dark pigments. This is the case of DOPEG (DL-3,4-dihydroxyphenyl glycol), an alcoholic compound that appears in the urine and whose concentration was positively correlated with the size of the dark ventral patch [23].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the metabolic pathway of catecholamines (Figure 1) the precursor of norepinephrine is the dopamine (DA). DA was not found in the urine of sampled individuals [23]; in contrast, unusually high concentration of norepinephrine was observed, leading to take under consideration the enzyme responsible of catalyzing the processes, the Dopamine B-hydroxylase (DBH). The release of catecholamines is a key initial event and it is followed by an increase or a decrease in the expression of genes that encode catecholamine-synthesizing enzymes [24].\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eVolatile compounds present in the hairs of the ventral patch vary with the level of mate competition (i.e., the abundance of male rivals in the population relative to females) [19], and we hypothesize that this could be due to gene-environment interactions. DNA encodes the potential for cellular behavior, but that potential is only realized if the gene is expressed - if its DNA is transcribed into RNA and translated into protein. Because RNA transcription shapes the protein complement of cells, and those proteins mediate cellular function, psychological regulation of gene expression implies that the social environment can remodel the functional characteristics of the body [25].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince it has been shown that males under high competition conditions showed larger dark patches (and higher concentration of metabolite) comparing to males from low competition situations [19, 22], plastic modulation of gene expression according to the different social environmental conditions of sexual competition may affect individual concentration of metabolite depending on the conditions in which the animal lives. The aim of this work was to investigate the mechanism responsible for the plastic modulation of the dark ventral patch in male red deer according to variations in male-male competitive level in social environment. In particular, whether the development of an individual\u0026rsquo;s ventral patch is based on a differential gene expression mechanism that is sensitive to the competitive situation in the population. Specifically, our main objective was to quantify the expression of the DBH gene, as it encodes the dopamine beta-hydroxylase, the enzyme that catalyzes the hydroxylation of dopamine to produce norepinephrine, as the precursor to DOPEG, which has been demonstrated to be the responsible for the staining of hairs in the dark ventral patch during the rut [23]. We wanted to investigate whether DBH gene expression was related to the size of the dark ventral patch, and whether this gene expression varied according to the level of intrasexual mating competition in the population, as it has been shown for the size of the dark ventral patch [19, 22]. Additionally, we explored the link between expression of the TH gene and plasma dopamine levels, as a confirmatory checking of the results for DBH based on the relationships between compounds in the main metabolic pathway of catecholamine biosynthesis (Figure 1). Thus, we predicted higher TH and DBH expression levels in the high competition situation, where males should invest more in sexual traits, while plasma dopamine levels may present a reverse relationship, as it is depleted by the action of DBH to produce norepinephrine. Also, we expected higher TH and DBH expression levels in those individuals that developed larger dark ventral patches.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch1\u003eStudy areas, competitive level of red deer populations\u003c/h1\u003e\n\u003cp\u003eThe study was conducted on Iberian red deer (\u003cem\u003eCervus e. hispanicus\u003c/em\u003e) in southwestern Spain. In this study area, red deer occur in hunting estates under two types of different management systems that lead to neat differences in population structure and in the level of male intrasexual competition [26, 27]: specifically, males of all ages are hunted in open areas because they become a shared resource for neighboring estates, while in fenced estates only some adult males are hunted when they reach trophy ages [27]. Consequently, it leads to two contrasting populational situations: (1) nearly natural population structure, in fenced estates, with high intrasexual competition for mates (HC), and (2) female-biased populations with young males, in unfenced estates, with low competition between males (LC). No other remarkable features have been found to differ between these two types of estates, either in habitat, supplementary feeding or any other potential stressors, besides the level of male-male competition [26, 27].\u003c/p\u003e\n\u003ch1\u003eSample collection\u003c/h1\u003e\n\u003cp\u003eSince previous studies have shown that the mechanism of pigmentation is based on the excretion of high amounts of norepinephrine metabolite deposited on the fur by the urinating behavior during the rut [23], adrenal glands, being responsible for the synthesis and the secretion of norepinephrine, were collected from 45 Iberian male red deer culled during hunting seasons from 2018/2019 to 2021/2022 in south-western Spain. To investigate differences between males subjected to different populational conditions, 19 samples from four populations were collected in areas with high mating competition (HC) and 26 samples from five populations were collected in areas with low mating competition (LC). The distribution of the sampling across hunting seasons and months, and the number of samples collected each season in both conditions are summarize in Supplementary Table S1. For this study, all samples were collected from carcasses of individuals that did not show clinical signs of disease and that were hunted during ordinary hunting activities based on official hunting plans. This means that our study never provoked hunters to shoot additional animals specifically for the purpose of this research. For the dark ventral patch, longitudinal size from the penis to the end of the dark spot at the breast or the base of the neck was measured with a ruler [23]. Mandibles were collected for age determination in the laboratory, as in previous studies [28], by counting cementum growth marks at the interradicular pad under the first molar [29] and by checking eruption patterns in younger animals.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur access to the hunting estates was approved by their management authorities while ethical issues regarding this study were revised and agreed by the Wildlife Research Unit at the University of Cordoba (UIRCP-UCO). This study was carried out in line with ARRIVE guidelines as our methods and experiment were performed in accordance with relevant regulations.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOnce collected, the samples were cut into slices less than 0.5 cm thick and immediately immersed in a sufficient volume of RNAlater\u0026trade; RNA Stabilization Reagent. Samples were kept at 4 \u0026deg;C in the field and then stored at \u0026minus; 20 \u0026deg;C till use.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eRNA isolation and cDNA synthesis\u003c/h1\u003e\n\u003cp\u003eRNA extraction from adrenal glands preserved in RNAlater\u0026trade; was carried out using the commercial RNeasy Mini Kit (Qiagen) according to the manufacturer\u0026rsquo;s protocol. Total RNA was extracted from 30 mg of RNAlater\u0026trade; stabilized tissue; we tried tissue disruption both with the Tissue-Lyser method and by using liquid nitrogen to find the best alternative. 600 \u0026mu;L of lysis buffer were added and after centrifugation (3 minutes; 16,000 xg), the whole supernatant was passed to a new tube. Next, 900 \u0026mu;L of 70% EtOH were added and after pipetting, a volume of 700 \u0026mu;L were transferred to a spin column and centrifugated for 15 s at 8,000 xg. Once discarded the first flow-through, centrifugation was repeated with the remaining volume using the same column. Removal of gDNA was performed by treating the RNA retained in the column with DNase I (QIAGEN) following the manufacturer protocol. Lastly, the Filter Cartridge was transferred to a new tube and the RNA eluted with 50 \u0026mu;L RNeasy-free water (preheated to ~75 \u0026deg;C), denatured by heating at 55\u0026ndash;65 \u0026deg;C for 10 min, immediately cooled on ice for at least 5 min, and kept at -80 \u0026deg;C till use. Purity and concentration of isolated RNA preparation was determined spectrophotometrically using a Nanodrop\u0026reg; one spectrophotometer (Thermo Scientific) while its integrity was determined using an Agilent 2100 Bioanalyzer (Agilent Scientific Instruments) system, which assigned an RNA Integrity Number (RIN) from 1 (totally degraded) to 10 (completely intact) to each sample. The iScript cDNA Synthesis Kit (BIORAD) was used to generate cDNA according to manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003ePrimer design and qRT-PCR conditions\u003c/h1\u003e\n\u003cp\u003ePrimer pairs for absolute quantification of the transcriptional levels of the dopamine beta hydroxylase (DBH) and the tyrosine hydroxylase (TH) genes were designed with the Oligo 7 software (Molecular Biology Insights) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Primers used in this work.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"767\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 101px;\"\u003e\n \u003cp\u003eUse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003eGenBank Acc. Number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 230px;\"\u003e\n \u003cp\u003eSequence 5\u0026acute;-3\u0026acute;\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003eLength\u003csup\u003ec\u003c/sup\u003e (bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003eAmplification eficiency\u003csup\u003ed\u003c/sup\u003e\u003cbr\u003e(R\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003eTarget\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"bottom\" style=\"width: 485px;\"\u003e\n \u003cp\u003eDetermination of \u003cem\u003eC. elaphus\u003c/em\u003e gene sequence\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eDBH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003eNW_001493002.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003eF:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 230px;\"\u003e\n \u003cp\u003eACCCGGCAGCCTCCCGCTCACCAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003ena\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eR:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 230px;\"\u003e\n \u003cp\u003eAGGGGGAGTGAGCAGGGCGATGGGGGTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"bottom\" style=\"width: 485px;\"\u003e\n \u003cp\u003eqRT-PCR quantification\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eDBH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003eXM_043916405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003eF:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 230px;\"\u003e\n \u003cp\u003eGAGGCCATCAACACCTCCGGCTTGCAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0,9979\u003cbr\u003e\u0026nbsp;(99,81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eR:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 230px;\"\u003e\n \u003cp\u003eTGAGGACATCGGGGGCGCGGATCTCCATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eTH\u003csub\u003e10-11\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003eOWK17426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003eF:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 230px;\"\u003e\n \u003cp\u003eCTGGGGCACGTGCCCATGCTCGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0,9897\u0026nbsp;\u003cbr\u003e\u0026nbsp;(98,96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eR:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 230px;\"\u003e\n \u003cp\u003eAGGCCTTCACCTCCCCGTTCTGCTTGCAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eTH\u003csub\u003e2-3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003eXM_043923566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003eF:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 230px;\"\u003e\n \u003cp\u003eGGCCAAGGGCTTCCGCCGGGCCGTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0,9977\u0026nbsp;\u003cbr\u003e\u0026nbsp;(99,56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eR:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 230px;\"\u003e\n \u003cp\u003eCCAGGCTGCCCGCCTCCCTGGGTTCCGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"bottom\" style=\"width: 485px;\"\u003e\n \u003cp\u003eCalibrator gene\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eA170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 107px;\"\u003e\n \u003cp\u003eU57413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003eF:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 230px;\"\u003e\n \u003cp\u003eGGAAGAGAAGCCGCCTGACACCCACT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.0001\u003cbr\u003e\u0026nbsp;(99.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e[30]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003eR:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 230px;\"\u003e\n \u003cp\u003eCCCGTCAGGTTTGCTGACTTCCGAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 230px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"top\" style=\"width: 767px;\"\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eGene symbols are according to the NCBI Gene database.\u003cbr\u003e\u003csup\u003eb\u003c/sup\u003eSequence of forward (F) and reverse (R) primers.\u003cbr\u003e\u003csup\u003ec\u003c/sup\u003ePCR product size in base pair (bp).\u003cbr\u003e\u003csup\u003ed\u003c/sup\u003eThe real-time PCR efficiencies (E) were calculated from each standard curve according to the equation E = 10\u003csup\u003e(-1/slope)\u003c/sup\u003e-1. E is in the range from 0 (minimum value) to 1 (maximum and optimum), i.e., E = 1 is equal to 100% efficiency.\u003cbr\u003e\u003csup\u003ee\u003c/sup\u003ePrimers based on \u003cem\u003eBos taurus\u003c/em\u003e sequence designed to determine the orthologous\u0026nbsp;\u003cem\u003eC. elaphus\u003c/em\u003e sequence.\u003cbr\u003e\u003csup\u003ef\u003c/sup\u003eNot applicable.\u003cbr\u003e\u003csup\u003eg\u003c/sup\u003ePrimers based on\u0026nbsp;\u003cem\u003eC. elaphus\u003c/em\u003e sequences were designed for absolute quantification by real-time RT-PCR.\u003cbr\u003e\u003csup\u003eh\u003c/sup\u003eInter-Run Calibrator gene: A170 transcripts are quantified in the same calibrator RNA sample included in each run to combine or compare data from different runs/experiments.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWe used primers previously designed (Pelayo \u003cem\u003eet al\u003c/em\u003e., 2012) against the \u003cem\u003eBos taurus\u003c/em\u003e DBH gene sequence (NW_001493002.2) to amplify the orthologous fragment in \u003cem\u003eC. elaphus\u003c/em\u003e cDNA. With the obtained \u003cem\u003eC. elaphus\u003c/em\u003e DBH sequences we designed specific primers to be used in qRT-PCR. Using the red deer gene sequence deposited in the GenBank database (NCBI,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/genbank/\"\u003ehttps://www.ncbi.nlm.nih.gov/genbank/\u003c/a\u003e) we designed TH primers.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince TH mRNA in other species like humans [31] has been shown to present alternative splicing, we designed two primer pairs to quantify TH mRNA isoforms. The primer pair TH\u003csub\u003e10-11\u003c/sub\u003e allows the quantification of any TH isoform variant; in contrast, the pair TH\u003csub\u003e2-3\u003c/sub\u003e only quantifies the splicing variants carrying the exon 2. All primers for qRT-PCR were targeted towards the protein-coding region of the mRNAs, having high melting temperature (Tm \u0026ge;73 \u0026deg;C) and optimal 3\u0026lsquo;\u0026Delta;G (\u0026ge;\u0026thinsp;\u0026minus;6 kcal/mol) values, to obtain the highest specificity and performance. The specificity of the primers was evaluated using 1% agarose gel electrophoresis of their PCR amplicons, while their efficiency was assessed by amplifying a 10-fold dilution series (resulting in a concentration range from 20 to 2\u0026times;10\u003csup\u003e5\u003c/sup\u003e pg) of a mixture of all cDNA samples in quadruplicate [32]. The slope of the standard curve achieved by plotting the obtained C\u003csub\u003eT\u003c/sub\u003e values against the RNA amount per well was used to calculate the efficiency according to the equation E=10(\u0026minus;1/slope)\u003csup\u003e\u0026nbsp;\u0026minus;1\u003c/sup\u003e [32]. Real-time PCRs were performed in quadruplicate (four technical replicates for each biological replicate and transcript) as detailed previously [\u003ca href=\"#Ventitreesimo_titolo\"\u003e3\u003c/a\u003e0]. No primer dimers were detected, and the investigated transcripts showed optimal PCR efficiencies (from 0.98 to 1.00).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe high Tm of the designed primers allowed a two-step protocol including a denaturation step (94\u0026deg;C, 15 s) and a hybridization/extension step (70\u0026ordm;C, 30 s) for each of the 40 cycles performed after the polymerase activation step (98\u0026deg;C, 4 minutes). Reactions were performed and fluorescence read in a CFX-96 Touch Real-Time PCR Detection System (Bio-Rad), using 50 ng of cDNA (2 \u0026mu;l) per reaction and the SSo Advanced Universal SYBR\u0026reg; Green Supermix (Bio-Rad) kit, according to the manufacturer\u0026rsquo;s instructions. After each PCR reaction, a melting curve analysis was run to ensure the specificity of amplification.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter establishing the fluorescence threshold by using a calibrator gene [30, 33], the absence of signal in the negative control (non-template sample) was checked before reading the C\u003csub\u003eT\u003c/sub\u003e values. Then, the C\u003csub\u003eT\u003c/sub\u003e values were transferred to Microsoft Excel converted into absolute transcript numbers by using a calibration curve constructed with an external standard as previously described [\u003ca href=\"#Ventitreesimo_titolo\"\u003e3\u003c/a\u003e0,\u0026nbsp;\u003ca href=\"#Trentaquattresimo_titolo\"\u003e33\u003c/a\u003e] and normalized by using stable genes under our experimental conditions. Then, the mean of the transcript values obtained was calculated as the average of the four replicates if the SD was less than 20%; otherwise, the transcript value of the outlying sample was removed from the study and the remaining data (at least n = 3) were reanalyzed [34].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eSelection of reference genes\u003c/h1\u003e\n\u003cp\u003ePrimer pairs for performing stability analysis to identify genes to be used as normalizers (reference genes) in our qRT-PCR study have already been described [34]. Following the MIQE guidelines (https://www. gene-quantification.de/miqe-index.html) as previously described [35-37], we determined the C\u003csub\u003eT\u003c/sub\u003e values for each candidate gene (Pgk1, Rplp0 and Gapdh) in all adrenal gland mRNA samples, regardless of their provenance (fenced or unfenced farms). The obtained C\u003csub\u003eT\u003c/sub\u003e values were used in the free web tool RefFinder (www.heartcure.com.au/reffinder/?type=reference), which pointed out Pgk1 and Rplp0 as stable genes under our experimental conditions (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality control for qRT-PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe analyzed the expression at the transcriptional level of two genes, TH and DBH, involved in the catecholamines metabolic pathway, by using the qRT-PCR methodology according to the MIQE Guidelines [35-37]. To ensure RNA quality, adrenal glands samples were collected and conserved in RNAlater\u0026trade; solution and kept frozen till use [34]. RNA was extracted with the RNeasy Mini Kit (Qiagen) following the manufacturer recommendations. RNA preparations were considered pure when their ratios of absorbance A\u003csub\u003e260\u003c/sub\u003e/A\u003csub\u003e280\u003c/sub\u003e and A\u003csub\u003e260\u003c/sub\u003e/A\u003csub\u003e230\u0026nbsp;\u003c/sub\u003ewere in the range of 2.0\u0026ndash;2.2. RNA integrity was evaluated by using an Agilent 2100 Bioanalyzer: all RNA samples in this study were of sufficient quality to be used in transcript quantification by qRT-PCR [38].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe success of PCR is highly dependent on primer design, as primers are the main determinants of its specificity and sensitivity [34]. Primers to amplify the red deer TH and DBH genes were carefully designed to assure total specificity and efficiency in the amplification reactions, using the OLIGO 7 Primer Analysis Software (Molecular Biology Insights, Inc., http://www.oligo.net) as previously described [34]. After optimizing PCR conditions (annealing temperature and concentration) for each primer pair, primer\u0026rsquo;s specificity was experimentally evaluated by visualizing the PCR products in agarose gels, which were excised and sequenced and by carrying out melting curves at the end of the PCR reaction. In all cases, primer pairs targeting TH and DBH produced one specific amplicon of the expected size and sequence, exhibiting, in the melting curve, a single peak.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eDopamine measurement\u003c/h1\u003e\n\u003cp\u003eDopamine is an important compound in the DOPEG biosynthetic route (see Fig. 1 and below, Fig. 4) and it may be depleted by the action of DBH to produce norepinephrine. To measure plasma dopamine levels, blood samples were collected from the infraorbital sinus in 10 ml anticoagulant EDTA-containing tubes. Samples were kept on ice in the field and then centrifuged for 20 minutes at approximately 1,000xg; they were subsequently stored at -20\u0026deg;C for later use. We decided to work with 6 samples (3 HC and 3 LC) as a test to confirm our previous gene expression results.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor quantitative measure of dopamine in serum, we used the Enzyme-Linked Immunosorbent Assay Kit (ELISA Cloud-Clone Corp.) following the manufacturer\u0026rsquo;s protocol. This pan-species assay has excellent specificity and elevated sensitivity for the detection of dopamine. It is a competitive inhibition enzyme immunoassay technique that allowed us to measure the concentration of dopamine in the samples.\u003c/p\u003e\n\u003cp\u003eEvery sample was duplicated, as recommended, at optimal sample dilution and at 1/6 dilution, obtaining repetitive results.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eStatistical analyses\u003c/h1\u003e\n\u003cp\u003eWe used a linear mixed-effects model (LMM) using the identity link function to predict the link between DBH gene expression and the intrasexual mating competition level in the population (LC and HC) and the sexual trait development (dark ventral patch (small vs. large) controlling for the day of the year as covariable and population identity nested within hunting season, and hunting season, as random sources of variation. The size of the dark ventral patch has been shown to follow a bimodal distribution that reveals its role as a discrete sexual signal [22]. Hence, we used here as in previous works the size of the dark ventral patch (DVP) in two categories [21], small (corresponding to low trait expression, LTE, in previous papers) and large (corresponding to high trait expression, HTE).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo ratify the results that arise from this first model, we also run another linear mixed model with the same structure but using the dark ventral patch size instead of the categorical variable (dark ventral patch expression). For TH, we performed a linear model for the most common isoform, but without random effects due to the small sample size that produced model singularity. For confirmatory checking of the role of TH transcripts and DA plasma concentrations in the metabolic route, unpaired Student\u0026rsquo;s t-tests were employed for comparisons, with significance level at two-tailed p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePopulation identity was introduced as random factor in models. The variables used in this study were age (in years), the month and the season when samples were collected, and the sizes (in centimeters) of the dark ventral area (Supplementary Table S1).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe performed all statistical analyses in R version 4.2.1 [39], using the package lme4 [40] for mixed-effect models and ggeffects [41]. We calculated the significance of predictors using the \u0026lsquo;Anova\u0026rsquo; function from the car package, performing likelihood ratio tests for linear mixed-effect models and F tests for linear models [42]. Normality of the residuals and homoscedasticity were confirmed by visual inspection and Shapiro\u0026ndash;Wilk tests. To avoid multicollinearity between variables, we calculated the variance inflation factors (VIFs) [43] of each model using the package \u0026ldquo;usdm\u0026rdquo; [44]. We did not find any evidence of collinearity for any of the models (VIF \u0026lt; 3).\u003c/p\u003e"},{"header":"Results","content":"\u003ch1\u003eDBH gene expression\u003c/h1\u003e\n\u003cp\u003eThe expression levels of the gene encoding the dopamine beta-hydroxylase (DBH), the enzyme that catalyzes the hydroxylation of dopamine to produce norepinephrine (Figure 1), ranged from a minimum value of 8.48 transcripts/pg of total RNA to 548.75 transcripts/pg of total RNA as a maximum value. In agreement with the results obtained for the TH gene, we also found increased amounts of DBH transcripts, approximately higher than 65%, in red deer males under high-competitive conditions (HC), i.e., mean \u0026plusmn; SD DBH expression values of 299.33 \u0026plusmn; 130.60 while individuals in LC populations presented mean \u0026plusmn; SD value of 181.35 \u0026plusmn; 98.92.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to the dark ventral patch size (DVP), the mean \u0026plusmn; SD expression of the DBH gene for large-DVP individuals was 255.98 \u0026plusmn; 135.31 transcripts/pg of total RNA while for small-DVP individuals it was 200.14 \u0026plusmn; 110.13 transcripts/pg of total RNA.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen comparing the expression levels of red deer under LC versus HC situations, we found, as shown in Table 3, a significant relationship for the TH\u003csub\u003e10-11\u003c/sub\u003e variant. The mean for the longer isoform (amplified with TH\u003csub\u003e2-3\u0026nbsp;\u003c/sub\u003eprimers only) was 30% higher in HC animals. For the most abundant exon 2-free isoform, the mean number of transcripts was 64% higher for red deer in high (HC) compared to low (LC) mating-competition situations (see Figure 4 below).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFocusing on the most abundant isoform, TH\u003csub\u003e10-11\u003c/sub\u003e (hereinafter TH), gene expression ranged from a minimum value of 369.6 transcripts/pg of total RNA to a maximum of 844.1 transcripts/pg of total RNA. Regarding the relationship between TH transcripts and the size of the dark ventral patch (DVP), we found that the mean \u0026plusmn; SD of TH gene expression for individuals with large DVP was 658.43 \u0026plusmn; 192.83 transcripts/pg of total RNA and for small-DVP individuals it was 633.88 \u0026plusmn; 100.47 transcripts/pg of total RNA. We found that individuals from HC populations showed mean \u0026plusmn; SD of TH gene expression of 754.38 \u0026plusmn; 97.16 while individuals in LC populations presented 482.14 \u0026plusmn; 100.46 mean \u0026plusmn; SD of TH gene expression.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe linear model exploring the factors that explained the differences in TH gene expression, showed a significant effect of the level of mate competition on TH expression, being higher in HC populations (Table 3). See also summarized results in Figure 4 (below).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Factors affecting TH\u003csub\u003e10-11\u003c/sub\u003e gene expression. LM model with logit as link function to explore the effect of the level of mating competition in the population (LC vs HC) and the sex trait dark ventral patch size (Small and Large) on the TH gene expression. Significant effects are showed in bold (p-value \u0026lt; 0.05).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.8479%;\"\u003e\n \u003cp\u003eTerm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5806%;\"\u003e\n \u003cp\u003eEstimate \u0026plusmn; S.E.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.4424%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.129%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.8479%;\"\u003e\n \u003cp\u003eFixed factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5806%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.4424%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.8479%;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5806%;\"\u003e\n \u003cp\u003e750.12 \u0026plusmn; 51.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.4424%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.8479%;\"\u003e\n \u003cp\u003eMating competition (LC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5806%;\"\u003e\n \u003cp\u003e275.08 \u0026plusmn; 79.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.4424%;\"\u003e\n \u003cp\u003e12.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.129%;\"\u003e\n \u003cp\u003e\u0026gt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.8479%;\"\u003e\n \u003cp\u003eDark ventral patch (Small)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5806%;\"\u003e\n \u003cp\u003e-21.30 \u0026plusmn; 88.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.4424%;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.129%;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eDopamine in blood samples\u003c/h1\u003e\n\u003cp\u003eAs expected from the role of the DBH in eliminating dopamine synthetized from the product of TH activity, we found lower plasma levels of dopamine (DA) in red deer under HC conditions (see Figure 4).\u003c/p\u003e\n\u003cp\u003eThe mixed model performed to explore the potential effect of the mating competition level in the population and the development of the dark ventral patch expression on the DBH gene expression, revealed significant differences only between the two types of populations according to the mating-competition level (Table 2A). In populations with intense intrasexual competition for mates (HC), DBH gene expression was significantly higher than in low intrasexual-competition populations (LC). However, in our data, the dark ventral patch expression did not show significant relationships with DBH gene expression. Regarding the mixed model carried out to ratify these results by using the dark ventral patch size (continuous variable), we also found a significant relationship between the DBH gene expression and the mating competition level in the population (Table 2B). No significant results were found in both models for the day of the year in the DBH gene expression. See summarized results in Figure 4 (below).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Factors affecting DBH gene expression. LM model to explore the link between the DBH gene expression and both the mating competition level (LC vs HC) and the sex trait dark ventral patch size (Small and Large in A, and as continuous variable in B), controlling by the day of the year. Reference levels are shown in brackets. Significant effects are showed in bold (p-value \u0026lt; 0.05).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"538\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eTerm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.5353%;\"\u003e\n \u003cp\u003eEstimate \u0026plusmn; S.E.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8885%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eFixed effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e196.75 \u0026plusmn; 61.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eDay of year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e10.32 \u0026plusmn; 25.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eMating competition (LC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e87.52 \u0026plusmn; 29.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e8.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eDark ventral patch (Small)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e15.40 \u0026plusmn; 25.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eFixed effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e205.35 \u0026plusmn; 59.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eDay of year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e11.90 \u0026plusmn; 22.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eMating competition (LC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e87.22 \u0026plusmn; 29.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e8.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40.5204%;\"\u003e\n \u003cp\u003eDark ventral patch size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.5353%;\"\u003e\n \u003cp\u003e10.18 \u0026plusmn; 13.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.0558%;\"\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.8885%;\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTH transcript alternative splicing and factors affecting expression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe two pairs of TH primers specifically amplified their target sequence (Figure 3) generating unique amplicons of 166 bp (TH\u003csub\u003e10-11\u003c/sub\u003e) and 173 bp (TH\u003csub\u003e2-3\u003c/sub\u003e) with Tm values of 88 \u0026ordm;C and 91 \u0026ordm;C, respectively. Thus, at least two TH mRNA isoforms exist in the adrenal gland of \u003cem\u003eC. elaphus\u003c/em\u003e. Of these, the complete N-terminal isoform (which was only amplified by the TH\u003csub\u003e2-3\u003c/sub\u003e primer pair) was in the minority. The transcript containing the exon 2 (amplified only by TH\u003csub\u003e2-3\u003c/sub\u003e primers) was found to be 3.3-4.2 times less abundant than the exon-2 spliced version, in both LC and HC animals (see Figure 4 below).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results supported the hypothesis of plastic modulation of the route responsible for the development of the dark ventral patch in male red deer, by the regulation of the expression levels of key genes. Transcription appeared upregulated in environments with high level of male intrasexual competition, thus suggesting the adaptive role of gene expression to shape the mating competitive strategy of male red deer.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe social environment with high intrasexual competition for mates associated with higher transcript counts of TH and DBH genes, supported (within the metabolic pathway of catecholamine) the activation of the complete DOPEG biosynthetic route when males experienced the conditions of high intrasexual competition for mates. TH and DBH are enzymes that both contribute to the stimulation of DOPEG production; however, they have opposing roles with respect to dopamine, as DBH degrades dopamine synthetized from TH activity. To elucidate the biological implications of our transcriptional data, we measured the abundance of dopamine in the blood of the animals studied. Plasma levels of dopamine were lower in HC deer, according to the predictions from the route to DOPEG with DBH activity boosted in HC animals, in agreement with the increased transcript amounts of the DBH gene.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother interesting finding was that at least two TH mRNA isoforms exist in the adrenal gland of red deer. The use of two primer pairs targeted toward different exons allowed us to uncover the existence, and importance, of such splicing alternatives. TH encodes the rate-limiting enzyme in the biosynthesis of catecholamines. It catalyzes the hydroxylation of tyrosine to L-DOPA, a precursor of dopamine (DA), norepinephrine (NE), and epinephrine (EP), the hormone responsible for the fight-or-flight response. Catecholamines play significant roles as hormones and neurotransmitters in both the central and peripheral nervous systems [45]. These catechol monoamines are involved in various brain functions, including attention, memory, cognition, and emotion [46]. Therefore, imbalances in catecholamine levels can have numerous consequences, from hypertension to bipolar disorder or addiction [46] and the regulation of TH, the slowest enzyme in the pathway, is complex and tightly regulated\u0026nbsp;[46-48]. RNA splicing is a key mediator of transcript and protein diversity, used to produce different isoforms of a protein from a particular gene and obtain a better functionality [49]. In humans, four isoforms are produced from a single TH gene by alternative mRNA splicing in the N-terminus, whereas two isoforms in monkeys and only a single protein has been described in other non-primate mammals [50]. These four isoforms are identical in their\u0026thinsp;central catalytic domain (~\u0026thinsp;300 amino acids, aa) and C-terminal\u0026thinsp;tetramer-forming domain (~\u0026thinsp;40 aa). However, they differ in their N-terminal regulatory domains, distinguished by 4 aa encoded by a 12 nt sequence at the 3\u0026prime;-terminus of exon 1 and 27 aa encoded by the 81 nt of exon 2 [50]. The presence/absence of the aa encoded by exon 1 and, mainly, exon 2, introduces some differences in the kinetic parameters of this forms regarding to TH consistent with the altered kinetics of phosphorylation and dephosphorylation. The importance of these differences remains elusive but is well known that phosphorylation in exon 2 results in an increase of the Ki value for dopamine [51].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor cattle (\u003cem\u003eBos taurus\u003c/em\u003e), which was used here as a reference organism for designing primers when the red deer sequence was not present in databases, the Ensembl database (\u003ca href=\"http://www.ensembl.org\"\u003ehttp://www.ensembl.org\u003c/a\u003e) describes three different transcript isoforms that vary in the regulatory region. Among these variants, only transcript TH\u003csub\u003e2-3\u003c/sub\u003e retains exon 2, which contains two phosphorylation sites absent in the others, resulting more susceptible to inhibition by dopamine [51]. For red deer adrenal gland, we quantified separately the number of TH\u003csub\u003e10-12\u003c/sub\u003e transcripts and of those that retain exon 2 (TH\u003csub\u003e2-3\u003c/sub\u003e), to analyze the possible correlation between populational conditions and the abundance of each splicing variant. The results (summarized in Figure 4) show higher amounts of both TH transcripts under high-competition environment, although the difference was significant only for the TH\u003csub\u003e10-12\u003c/sub\u003e isoform. In fact, this exon 2 free TH mRNA splicing variant (TH\u003csub\u003e10-12\u003c/sub\u003e) was much more abundant (over three-fold) than the other. Favoring the TH variant that is less sensitive to dopamine inhibition [51] may enhance the synthesis of other catecholamines along the route leading to the development of DOPEG and hence the staining of hairs of the ventral patch [23].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTH has been found related to sexual activity in domestic rams [52] and TH transcripts were higher in sexually competitive male zebra finches [53]. An open question is whether TH expression is a cause or a consequence of such sexually competitive ability. Some studies suggest that TH expression may be the consequence of individual\u0026rsquo;s behavior during competition, although the question remains open [53-54]. In addition, it is known that under stress conditions, TH is regulated by enzyme induction at the transcriptional level [55]. A sexually competitive situation in red deer entails high stress conditions [21], which suggests that competitive stress may be a potential mechanism triggering gene expression related to the development of traits used in competition. In this sense, experiencing competition and the stress-related conditions may upregulate TH gene expression. Regardless this experience begins before and/or during the rutting season, it would contribute to cause-effect feedback relationships between male intrasexual competition and the development of flexible sexual traits. Thus, for a short-term flexible structure such as the dark ventral patch based on current urine deposits and oxidization, the link between TH gene expression and the sex trait with its related competitive behavior may be a continuous process of reinforcement during the duration of the rutting season.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe increase in catecholamine biosynthesis that can occur in response to repeated or chronic exposure to a variety of stressors, is associated with elevated activity of the catecholamine-synthesizing enzymes [24]. Thus, animals experiencing such conditions would express distinctive amounts of TH, that catalyzes the conversion from tyrosine to dopamine and of DBH, the enzyme that catalyzes the conversion from dopamine to norepinephrine. This might lead to the, somehow odd, hypothesis that stress conditions would increase the development of the sexual signal. Against this hypothesis, the size of the dark ventral patch was found not related to cortisol level and even a negative relationship was true for young red deer (2-years-old) in our study area [20]. Therefore, the regulation of gene expression related to trait development should also be modulated by factors other than simple stress.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeveral papers have shown that variations in immediate environment can elicit rapid changes in hormones and behavior, and short-term changes in sex steroid release and hormone action may provide a mechanism for flexible multimodal display in response to fluctuating environmental conditions [56]. The mechanism suggested here for a flexible trait development and associated behavioral display [21] represents a rare example of adaptive regulation based on gene expression.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDBH is an enzyme crucial to the balance of DA and NE in the body and it is required for the conversion of dopamine into norepinephrine. It has been described that TH is post-transcriptionally regulated during chronic stress by feedback inhibition by the final catecholamines product. This direct inhibition of TH requires high millimolar concentrations of dopamine and is impaired when the N-terminus of the protein is present and phosphorylated [55]. Neither of these two requirements seem to be achieved in the adrenal gland of deer under HC conditions. Results in Figure 4 show that dopamine is reduced in the plasma of HC deer. These data may be explained by increased levels of the enzyme DBH (Figure 4), which would catabolize DA to NE and other derivatives, thus releasing less DA into the blood, although increased DA uptake by the brain as part of male sexual behavior [57] cannot be ruled out.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe know that the DVP is an important sexual signal, encoding chemical [19, 58] and visual information [22], related to the behavioral strategy of males [21]. However, an open question remains on whether this signal may be costly and reliable. Our results on DA, although scarce in sample size and hence preliminary, suggest a possible hypothesis. Dopamine is a neurotransmitter that contributes to general alertness and willingness to fight, so its presence should help success in competition. If the DVP signal is based on using dopamine to achieve the black spotting through the pathway to DOPEG, thereby decreasing the dopamine circulating levels available for other effects, we could be dealing with a handicap-type signal. That is, males with black spots that win fights would be demonstrating that they do so despite having less circulating dopamine. The DVP would be a reliable sign of dopamine \u0026ldquo;destruction\u0026rdquo;; dominant males with DVP may honestly indicate their quality because they become dominant despite destroying dopamine. Anyway, this is so far just a hypothesis, and we cannot rule out other possible costs related to TH or DBH production, so it would be necessary to conduct new work and desirably experimental design.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMany regulatory mechanisms are orchestrated between the genome transcription and the translation of proteins, which are responsible for most of the phenotypic characteristics of an organism [59]. From earlier studies comparing mRNA with protein abundancy in some biological models [59], it was obvious the lack of full concordance. On the biological front, differences could be initially attributed to RNA splicing, differential RNA and protein turnover, post-translational modifications, allosteric protein interactions, and proteolytic processing events. As predicted, higher TH and DBH levels were achieved in the high-competition situation, where males should invest more in sexual traits. However, we also expected a positive relationship between TH and DBH transcripts and the size of the DVP as the focus genes were selected because of their relationship with the route that leads to key compounds of the DVP sexual signal. Despite the amounts of transcripts for both TH and DBH genes were higher in males with large DVP, the differences were not significant in the models. These results might have been affected by our limitations in the timing of sampling. The strongest relationship is expected during the rutting season, but our sampling depended on legal hunting of deer, which takes place after the rutting season. It is possible that, due to their flexible nature, the amounts of transcripts and the development of sexual traits may be decoupled after the rut. Indeed, although phenotypes and gene expression covary, both may not necessarily be in the same temporal phases [60].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, the differences in DBH and TH amounts of transcripts between males under HC and LC conditions found for a sampling period shortly after the rutting season, may also suggest a possible benefit after the main sexual competition event, besides their role in the chemical constituents of the DVP. Rutting males typically eat very little during the mating period, which lasts nearly 20 days [61]. Consequently, they experience a significant decline in physical condition [62, 63] and immune response capacity [64], leading to an increase in mortality immediately following the mating period [18]. DBH is involved in the releasing of lactate from skeletal muscle, and the breaking down of amino acids, glycogen, and triglycerides to generate glucose, fatty acids, and ketone bodies [65], which may be important for maintaining functionality under poor nutritional conditions. For the immune response, we have previous evidence from our study area of a positive relationship of host parasitism levels and the size of the dark ventral patch, but this relationship depended on the intensity of male\u0026ndash;male competition in the population, being only found under the high-competition scenario [66]. The effect of norepinephrine in the immune system is increasingly acknowledged in regulating immune cells response and the oxidative metabolism of immune cells [67], which suggests a possible role of DBH in the immune function of competitive males after the rut.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn conclusion, we have shown that Iberian male red deer modulate the expression of TH and DBH genes according to the level of intrasexual competition that they experienced in their social environments. Males in high competition environments show a more competitive phenotype, including morphological and physiological changes, compared to males in low competition environments. Previous works with red deer demonstrated higher development of sex traits such as the antlers [9] or the dark ventral patch [19, 20, 22] and associated behavior [21] under conditions of high mate-competition. Our results in this study provide new insight into the mechanisms based on the differential expression of genes involved in the biosynthetic route that contributes to these phenotypic differences. Consequently, TH and DBH transcripts quantification may be a good molecular biomarker for red deer involvement in reproductive competition. Future work might focus on flexible changes throughout the rutting period and after it according to mating competition along with the experimental testing of the correlational relationships found.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinancial support for this work came from project PID2021-127823NB-I00 from Spanish Ministry of Science.\u003c/p\u003e\n\u003cp\u003eQuality analysis of RNA was carried out by the genomics unit of the Central Services for Research Support of the University of C\u0026oacute;rdoba (SCAI).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCamilla Broggini contributed to sample collection. Camilla Broggini and Nieves Abril performed material preparation and laboratory work. Nieves Abril analyzed qRT-PCR data. Statistical analyses were carried out by Eva de la Pe\u0026ntilde;a. Camilla Broggini, Nieves Abril, Juan Carranza and Alberto Membrillo conceived the study and drafted the manuscript. All authors revised the text, agreed with the content, and gave final approval of the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data supporting the results reported in the article are within the paper and its Supporting Information file.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1.\u0026nbsp; \u0026nbsp; \u0026nbsp;Andersson, M. \u0026amp; Iwasa, Y. Sexual selection. \u003cem\u003eTrends Ecol Evol\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 53\u0026ndash;58 (1996).\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp; \u0026nbsp;Piersma, T. \u0026amp; Van Gils, J. A. \u003cem\u003eThe Flexible Phenotype: A Body-Centred Integration of Ecology, Physiology, and Behaviour\u003c/em\u003e. (Oxford university press, Oxford, 2010).\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp; \u0026nbsp;Draghi, J. Phenotypic variability can promote the evolution of adaptive plasticity by reducing the stringency of natural selection. \u003cem\u003eJ of Evolutionary Biology\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 1274\u0026ndash;1289 (2019).\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp; \u0026nbsp; \u0026nbsp;Pigliucci, M. \u003cem\u003ePhenotypic Plasticity: Beyond Nature and Nurture\u003c/em\u003e. (Johns Hopkins University Press, 2001).\u003c/p\u003e\n\u003cp\u003e5.\u0026nbsp; \u0026nbsp; \u0026nbsp;West-Eberhard, M. J. \u003cem\u003eDevelopmental Plasticity and Evolution\u003c/em\u003e. (Oxford University Press, Oxford, 2003).\u003c/p\u003e\n\u003cp\u003e6.\u0026nbsp; \u0026nbsp; \u0026nbsp;Johnstone, R. A. Sexual selection, honest advertisement and the handicap principle: reviewing the evidence. \u003cem\u003eBiological Reviews\u003c/em\u003e \u003cstrong\u003e70\u003c/strong\u003e, 1\u0026ndash;65 (1995).\u003c/p\u003e\n\u003cp\u003e7.\u0026nbsp; \u0026nbsp; \u0026nbsp;Bonduriansky, R. The Evolution of Condition‐Dependent Sexual Dimorphism. \u003cem\u003eThe American Naturalist\u003c/em\u003e \u003cstrong\u003e169\u003c/strong\u003e, 9\u0026ndash;19 (2007).\u003c/p\u003e\n\u003cp\u003e8.\u0026nbsp; \u0026nbsp; \u0026nbsp;Gautier, P. \u003cem\u003eet al.\u003c/em\u003e The Presence of Females Modulates the Expression of a Carotenoid-Based Sexual Signal. \u003cem\u003eBehavioral Ecology and Sociobiology\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 1159\u0026ndash;1166 (2008).\u003c/p\u003e\n\u003cp\u003e9.\u0026nbsp; \u0026nbsp; \u0026nbsp;Carranza, J. \u003cem\u003eet al.\u003c/em\u003e Social environment modulates investment in sex trait versus lifespan: red deer produce bigger antlers when facing more rivalry. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 9234 (2020).\u003c/p\u003e\n\u003cp\u003e10.\u0026nbsp; \u0026nbsp;Schlichting, C. \u0026amp; Pigliucci, M. \u003cem\u003ePhenotypic Evolution: A Reaction Norm Perspective\u003c/em\u003e. (Sinauer, 1998).\u003c/p\u003e\n\u003cp\u003e11.\u0026nbsp; \u0026nbsp;Aubin-Horth, N. \u0026amp; Renn, S. C. P. Genomic reaction norms: using integrative biology to understand molecular mechanisms of phenotypic plasticity. \u003cem\u003eMol Ecol\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 3763\u0026ndash;3780 (2009).\u003c/p\u003e\n\u003cp\u003e12.\u0026nbsp; \u0026nbsp;Lafuente, E. \u0026amp; Beldade, P. Genomics of Developmental Plasticity in Animals. \u003cem\u003eFront Genet\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 720 (2019).\u003c/p\u003e\n\u003cp\u003e13.\u0026nbsp; \u0026nbsp;Chevin, L.-M., Leung, C., Le Rouzic, A. \u0026amp; Uller, T. Using phenotypic plasticity to understand the structure and evolution of the genotype\u0026ndash;phenotype map. \u003cem\u003eGenetica\u003c/em\u003e \u003cstrong\u003e150\u003c/strong\u003e, 209\u0026ndash;221 (2022).\u003c/p\u003e\n\u003cp\u003e14.\u0026nbsp; \u0026nbsp;Smith, J. M. \u003cem\u003eEvolution and the Theory of Games\u003c/em\u003e. (Cambridge University Press, 1982). doi:10.1017/CBO9780511806292.\u003c/p\u003e\n\u003cp\u003e15.\u0026nbsp; \u0026nbsp;Carranza, J., Alvarez, F. \u0026amp; Redondo, T. Territoriality as a mating strategy in red deer. \u003cem\u003eAnimal Behaviour\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 79\u0026ndash;88 (1990).\u003c/p\u003e\n\u003cp\u003e16.\u0026nbsp; \u0026nbsp;Carranza, J., Fernandez-Llario, P. \u0026amp; Gomendio, M. Correlates of Territoriality in Rutting Red Deer. \u003cem\u003eEthology\u003c/em\u003e \u003cstrong\u003e102\u003c/strong\u003e, 793\u0026ndash;805 (1996).\u003c/p\u003e\n\u003cp\u003e17.\u0026nbsp; \u0026nbsp;Carranza, J. \u0026amp; Valencia, J. Red deer females collect on male clumps at mating areas. \u003cem\u003eBehavioral Ecology\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 525\u0026ndash;532 (1999).\u003c/p\u003e\n\u003cp\u003e18.\u0026nbsp; \u0026nbsp;Clutton-Brock, T. H., Guinness, F. E., Albon, S. D. \u0026amp; Barrett, P. \u003cem\u003eRed Deer : Behavior and Ecology of Two Sexes / T.H. Clutton-Brock, F.E. Guinness, S.D. Albon ; with Original Drawings by Priscilla Barrett.\u003c/em\u003e (Edinburgh University Press, Edinburgh, 1982).\u003c/p\u003e\n\u003cp\u003e19.\u0026nbsp; \u0026nbsp;de la Pe\u0026ntilde;a, E., Mart\u0026iacute;n, J. \u0026amp; Carranza, J. The intensity of male-male competition may affect chemical scent constituents in the dark ventral patch of male Iberian red deer. \u003cem\u003ePLOS ONE\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, e0221980 (2019).\u003c/p\u003e\n\u003cp\u003e20.\u0026nbsp; \u0026nbsp;de La Pe\u0026ntilde;a, E., Mart\u0026iacute;n, J., Barja, I. \u0026amp; Carranza, J. Testosterone and the dark ventral patch of male red deer: the role of the social environment. \u003cem\u003eSci Nat\u003c/em\u003e \u003cstrong\u003e107\u003c/strong\u003e, 18 (2020).\u003c/p\u003e\n\u003cp\u003e21.\u0026nbsp; \u0026nbsp;de la Pe\u0026ntilde;a, E., P\u0026eacute;rez-Gonz\u0026aacute;lez, J., Mart\u0026iacute;n, J., Vedel, G. \u0026amp; Carranza, J. The dark-ventral-patch of male red deer, a sexual signal that conveys the degree of involvement in rutting behavior. \u003cem\u003eBMC Zoology\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 18 (2021).\u003c/p\u003e\n\u003cp\u003e22.\u0026nbsp; \u0026nbsp;Carranza, J. \u003cem\u003eet al.\u003c/em\u003e The dark ventral patch: A bimodal flexible trait related to male competition in red deer. \u003cem\u003ePLoS ONE\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, e0241374 (2020).\u003c/p\u003e\n\u003cp\u003e23.\u0026nbsp; \u0026nbsp;Galv\u0026aacute;n, I. \u003cem\u003eet al.\u003c/em\u003e Unprecedented high catecholamine production causing hair pigmentation after urinary excretion in red deer. \u003cem\u003eCell Mol Life Sci\u003c/em\u003e \u003cstrong\u003e76\u003c/strong\u003e, 397\u0026ndash;404 (2019).\u003c/p\u003e\n\u003cp\u003e24.\u0026nbsp; \u0026nbsp;Sabban, E. L. \u0026amp; Kvetňansk\u0026yacute;, R. Stress-triggered activation of gene expression in catecholaminergic systems: dynamics of transcriptional events. \u003cem\u003eTrends in Neurosciences\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 91\u0026ndash;98 (2001).\u003c/p\u003e\n\u003cp\u003e25.\u0026nbsp; \u0026nbsp;Cole, S. W. Social regulation of human gene expression. \u003cem\u003eCurr Dir Psychol Sci\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 132\u0026ndash;137 (2009).\u003c/p\u003e\n\u003cp\u003e26.\u0026nbsp; \u0026nbsp;P\u0026eacute;rez-Gonz\u0026aacute;lez, J. \u0026amp; Carranza, J. Female-biased dispersal under conditions of low male mating competition in a polygynous mammal. \u003cem\u003eMol Ecol\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 4617\u0026ndash;4630 (2009).\u003c/p\u003e\n\u003cp\u003e27.\u0026nbsp; \u0026nbsp;Torres-Porras, J. The tragedy of the commons: unsustainable population structure of Iberian red deer in hunting estates. \u003cem\u003eEuropean Journal of Wildlife Research\u003c/em\u003e \u003cstrong\u003e60\u003c/strong\u003e, 351\u0026ndash;357 (2014).\u003c/p\u003e\n\u003cp\u003e28.\u0026nbsp; \u0026nbsp;Carranza, J., Alarcos, S., S\u0026aacute;nchez-Prieto, C. B., Valencia, J. \u0026amp; Mateos, C. Disposable-soma senescence mediated by sexual selection in an ungulate. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e432\u003c/strong\u003e, 215\u0026ndash;218 (2004).\u003c/p\u003e\n\u003cp\u003e29.\u0026nbsp; \u0026nbsp;Mitchell, B. Growth Layers in Dental Cement for Determining the Age of Red Deer (Cervus elaphus L.). \u003cem\u003eThe Journal of Animal Ecology\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 279 (1967).\u003c/p\u003e\n\u003cp\u003e30.\u0026nbsp; \u0026nbsp;Prieto-\u0026Aacute;lamo, M.-J., Cabrera-Luque, J.-M. \u0026amp; Pueyo, C. Absolute Quantitation of Normal and ROS-Induced Patterns of Gene Expression: An In Vivo Real-Time PCR Study in Mice. \u003cem\u003egene expr\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 23\u0026ndash;34 (2003).\u003c/p\u003e\n\u003cp\u003e31.\u0026nbsp; \u0026nbsp;Kobayashi, K. \u003cem\u003eet al.\u003c/em\u003e Structure of the Human Tyrosine Hydroxylase Gene: Alternative Splicing from a Single Gene Accounts for Generation of Four mRNA Types1. \u003cem\u003eThe Journal of Biochemistry\u003c/em\u003e \u003cstrong\u003e103\u003c/strong\u003e, 907\u0026ndash;912 (1988).\u003c/p\u003e\n\u003cp\u003e32.\u0026nbsp; \u0026nbsp;Svec, D., Tichopad, A., Novosadova, V., Pfaffl, M. W. \u0026amp; Kubista, M. How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments. \u003cem\u003eBiomol Detect Quantif\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 9\u0026ndash;16 (2015).\u003c/p\u003e\n\u003cp\u003e33.\u0026nbsp; \u0026nbsp;Jurado, J., Prieto-\u0026Aacute;lamo, M.-J., Madrid-R\u0026iacute;squez, J. \u0026amp; Pueyo, C. Absolute Gene Expression Patterns of Thioredoxin and Glutaredoxin Redox Systems in Mouse. \u003cem\u003eJournal of Biological Chemistry\u003c/em\u003e \u003cstrong\u003e278\u003c/strong\u003e, 45546\u0026ndash;45554 (2003).\u003c/p\u003e\n\u003cp\u003e34.\u0026nbsp; \u0026nbsp;Broggini, C., Abril, N., Carranza, J. \u0026amp; Membrillo, A. Evaluation of candidate reference genes for quantitative real-time PCR normalization in blood from red deer developing antlers. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 16264 (2022).\u003c/p\u003e\n\u003cp\u003e35.\u0026nbsp; \u0026nbsp;Bustin, S. A. \u003cem\u003eet al.\u003c/em\u003e The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. \u003cem\u003eClin Chem\u003c/em\u003e \u003cstrong\u003e55\u003c/strong\u003e, 611\u0026ndash;622 (2009).\u003c/p\u003e\n\u003cp\u003e36.\u0026nbsp; \u0026nbsp;Hellemans, J. \u0026amp; Vandesompele, J. Selection of Reliable Reference Genes for RT-qPCR Analysis. in \u003cem\u003eQuantitative Real-Time PCR\u003c/em\u003e (eds. Biassoni, R. \u0026amp; Raso, A.) vol. 1160 19\u0026ndash;26 (Springer New York, New York, NY, 2014).\u003c/p\u003e\n\u003cp\u003e37.\u0026nbsp; \u0026nbsp;Morales-Prieto, N., Ruiz-Laguna, J., Sheehan, D. \u0026amp; Abril, N. Transcriptome signatures of p,p\u0026acute;-DDE-induced liver damage in Mus spretus mice. \u003cem\u003eEnvironmental Pollution\u003c/em\u003e \u003cstrong\u003e238\u003c/strong\u003e, 150\u0026ndash;167 (2018).\u003c/p\u003e\n\u003cp\u003e38.\u0026nbsp; \u0026nbsp;Schroeder, A., Mueller, O., Stocker, S., Salowsky, R., Leiber, M., Gassmann, M., Lightfoot, S., Menzel, W., Granzow, M. \u0026amp; Ragg, T. The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Molecular Biol \u003cstrong\u003e7\u003c/strong\u003e, 3 (2006).\u003c/p\u003e\n\u003cp\u003e39.\u0026nbsp; \u0026nbsp;R Core Team. R: A language and environment for statistical computing. V.4.2.1. Vienna, Austria: R Foundation for Statistical Computing (2021).\u003c/p\u003e\n\u003cp\u003e40.\u0026nbsp; \u0026nbsp;Bates, D., M\u0026auml;chler, M., Bolker, B. \u0026amp; Walker, S. Fitting Linear Mixed-Effects Models Using \u003cstrong\u003elme4\u003c/strong\u003e. J. Stat. Soft. \u003cstrong\u003e67\u003c/strong\u003e, (2015).\u003c/p\u003e\n\u003cp\u003e41.\u0026nbsp; \u0026nbsp;L\u0026uuml;decke, D. ggeffects: Tidy Data Frames of Marginal Effects from Regression Models. JOSS \u003cstrong\u003e3\u003c/strong\u003e, 772 (2018).\u003c/p\u003e\n\u003cp\u003e42. \u0026nbsp;\u0026nbsp;Fox, J., \u0026amp; Weisberg, S. An R companion to applied regression. Sage publications (2018).\u003c/p\u003e\n\u003cp\u003e43.\u0026nbsp; \u0026nbsp;Alin, A. Multicollinearity: Multicollinearity. WIREs Comp Stat \u003cstrong\u003e2\u003c/strong\u003e, 370\u0026ndash;374 (2010).\u003c/p\u003e\n\u003cp\u003e44.\u0026nbsp; \u0026nbsp;Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K. \u0026amp; Toxopeus, A. G. Where is positional uncertainty a problem for species distribution modelling? Ecography \u003cstrong\u003e37\u003c/strong\u003e, 191\u0026ndash;203 (2014).\u003c/p\u003e\n\u003cp\u003e45.\u0026nbsp; \u0026nbsp;Lustberg, D. J. \u003cem\u003eet al.\u003c/em\u003e Norepinephrine and dopamine contribute to distinct repetitive behaviors induced by novel odorant stress in male and female mice. \u003cem\u003eHormones and Behavior\u003c/em\u003e \u003cstrong\u003e144\u003c/strong\u003e, 105205 (2022).\u003c/p\u003e\n\u003cp\u003e46.\u0026nbsp; \u0026nbsp;Daubner, S. C., Le, T. \u0026amp; Wang, S. Tyrosine hydroxylase and regulation of dopamine synthesis. \u003cem\u003eArchives of Biochemistry and Biophysics\u003c/em\u003e \u003cstrong\u003e508\u003c/strong\u003e, 1\u0026ndash;12 (2011).\u003c/p\u003e\n\u003cp\u003e47.\u0026nbsp; \u0026nbsp;Cousins, D. A., Butts, K. \u0026amp; Young, A. H. The role of dopamine in bipolar disorder. \u003cem\u003eBipolar Disorders\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 787\u0026ndash;806 (2009).\u003c/p\u003e\n\u003cp\u003e48.\u0026nbsp; \u0026nbsp;Koob, G. F. \u0026amp; Volkow, N. D. Neurocircuitry of Addiction. \u003cem\u003eNeuropsychopharmacol\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 217\u0026ndash;238 (2010).\u003c/p\u003e\n\u003cp\u003e49.\u0026nbsp; \u0026nbsp;Fisher, E. \u0026amp; Feng, J. RNA splicing regulators play critical roles in neurogenesis. \u003cem\u003eWIREs RNA\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, e1728 (2022).\u003c/p\u003e\n\u003cp\u003e50.\u0026nbsp; \u0026nbsp;Nagatsu, T. Catecholamines and Parkinson\u0026rsquo;s disease: tyrosine hydroxylase (TH) over tetrahydrobiopterin (BH4) and GTP cyclohydrolase I (GCH1) to cytokines, neuromelanin, and gene therapy: a historical overview. \u003cem\u003eJ Neural Transm\u003c/em\u003e (2023) doi:10.1007/s00702-023-02673-y.\u003c/p\u003e\n\u003cp\u003e51.\u0026nbsp; \u0026nbsp;Fitzpatrick, P. F. The aromatic amino acid hydroxylases: Structures, catalysis, and regulation of phenylalanine hydroxylase, tyrosine hydroxylase, and tryptophan hydroxylase. \u003cem\u003eArchives of Biochemistry and Biophysics\u003c/em\u003e \u003cstrong\u003e735\u003c/strong\u003e, 109518 (2023).\u003c/p\u003e\n\u003cp\u003e52.\u0026nbsp; \u0026nbsp;Kramer, A. C., Mirto, A. J., Austin, K. J., Roselli, C. E. \u0026amp; Alexander, B. M. Tyrosine hydroxylase in the ventral tegmental area of rams with high or low libido\u0026mdash;A role for dopamine. \u003cem\u003eAnimal Reproduction Science\u003c/em\u003e \u003cstrong\u003e187\u003c/strong\u003e, 152\u0026ndash;158 (2017).\u003c/p\u003e\n\u003cp\u003e53.\u0026nbsp; \u0026nbsp;Eswine, S. L., Pontinen, J. K. \u0026amp; Heimovics, S. A. Competitive ability during mate competition relates to unique patterns of dopamine-related gene expression in the social decision-making network of male zebra finches. \u003cem\u003eNeuroscience Letters\u003c/em\u003e \u003cstrong\u003e706\u003c/strong\u003e, 30\u0026ndash;35 (2019).\u003c/p\u003e\n\u003cp\u003e54.\u0026nbsp; \u0026nbsp;Filipenko, M. L., Alekseyenko, O. V., Beilina, A. G., Kamynina, T. P. \u0026amp; Kudryavtseva, N. N. Increase of tyrosine hydroxylase and dopamine transporter mRNA levels in ventral tegmental area of male mice under influence of repeated aggression experience. \u003cem\u003eMolecular Brain Research\u003c/em\u003e \u003cstrong\u003e96\u003c/strong\u003e, 77\u0026ndash;81 (2001).\u003c/p\u003e\n\u003cp\u003e55.\u0026nbsp; \u0026nbsp;Skjevik, \u0026Aring;. A. \u003cem\u003eet al.\u003c/em\u003e The N-Terminal Sequence of Tyrosine Hydroxylase Is a Conformationally Versatile Motif That Binds 14-3-3 Proteins and Membranes. \u003cem\u003eJournal of Molecular Biology\u003c/em\u003e \u003cstrong\u003e426\u003c/strong\u003e, 150\u0026ndash;168 (2014).\u003c/p\u003e\n\u003cp\u003e56.\u0026nbsp; \u0026nbsp;Eigerman, A. R. \u0026amp; Mangiamele, L. A. Mechanisms of multimodality: androgenic hormones and adaptive flexibility in multimodal displays. \u003cem\u003eAnimal Behaviour\u003c/em\u003e \u003cstrong\u003e184\u003c/strong\u003e, 149\u0026ndash;156 (2022).\u003c/p\u003e\n\u003cp\u003e57.\u0026nbsp; \u0026nbsp;Melis, M. R., Sanna, F. \u0026amp; Argiolas, A. Dopamine, Erectile Function and Male Sexual Behavior from the Past to the Present: A Review. \u003cem\u003eBrain Sciences\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 826 (2022).\u003c/p\u003e\n\u003cp\u003e58.\u0026nbsp; \u0026nbsp;Mart\u0026iacute;n, J., Carranza, J., L\u0026oacute;pez, P., Alarcos, S. \u0026amp; P\u0026eacute;rez-Gonz\u0026aacute;lez, J. A new sexual signal in rutting male red deer: Age related chemical scent constituents in the belly black spot. \u003cem\u003eMammalian Biology\u003c/em\u003e \u003cstrong\u003e79\u003c/strong\u003e, 362\u0026ndash;368 (2014).\u003c/p\u003e\n\u003cp\u003e59.\u0026nbsp; \u0026nbsp;Buccitelli, C. \u0026amp; Selbach, M. mRNAs, proteins and the emerging principles of gene expression control. \u003cem\u003eNat Rev Genet\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 630\u0026ndash;644 (2020).\u003c/p\u003e\n\u003cp\u003e60.\u0026nbsp; \u0026nbsp;Rittschof, C. C. \u0026amp; Hughes, K. A. Advancing behavioural genomics by considering timescale. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 489 (2018).\u003c/p\u003e\n\u003cp\u003e61.\u0026nbsp; \u0026nbsp;Mysterud, A., Bonenfant, C., Loe, L. E., Langvatn, R., Yoccoz, N. G. \u0026amp; Stenseth, N. C. Age‐specific feeding cessation in male red deer during rut. Journal of Zoology \u003cstrong\u003e275\u003c/strong\u003e, 407\u0026ndash;412 (2008).\u003c/p\u003e\n\u003cp\u003e62.\u0026nbsp; \u0026nbsp;Yoccoz, N. G., Mysterud, A., Langvatn, R. \u0026amp; Stenseth, N. Chr. Age\u0026ndash; and density\u0026ndash;dependent reproductive effort in male red deer. Proc. R. Soc. Lond. B \u003cstrong\u003e269\u003c/strong\u003e, 1523\u0026ndash;1528 (2002).\u003c/p\u003e\n\u003cp\u003e63.\u0026nbsp; \u0026nbsp;Apollonio, M., Merli, E., Chirichella, R., Pokorny, B., Alagić, A., Flaj\u0026scaron;man, K. \u0026amp; Stephens, P. A. Capital-Income Breeding in Male Ungulates: Causes and Consequences of Strategy Differences Among Species. Front. Ecol. Evol. \u003cstrong\u003e8\u003c/strong\u003e, 521767 (2020).\u003c/p\u003e\n\u003cp\u003e64.\u0026nbsp; \u0026nbsp;Vicente, J., P\u0026eacute;rez-Rodr\u0026iacute;guez, L. \u0026amp; Gortazar, C. Sex, age, spleen size, and kidney fat of red deer relative to infection intensities of the lungworm Elaphostrongylus cervi. Naturwissenschaften \u003cstrong\u003e94\u003c/strong\u003e, 581 (2007).\u003c/p\u003e\n\u003cp\u003e65.\u0026nbsp; \u0026nbsp;Hartmann, C., Radermacher, P., Wepler, M. \u0026amp; Nu\u0026szlig;baum, B. Non-Hemodynamic Effects of Catecholamines. Shock \u003cstrong\u003e48\u003c/strong\u003e, 390\u0026ndash;400 (2017).\u003c/p\u003e\n\u003cp\u003e66.\u0026nbsp; \u0026nbsp;De La Pe\u0026ntilde;a, E., Mart\u0026iacute;n, J., Barja, I., P\u0026eacute;rez‐Caballero, R., Acosta, I. \u0026amp; Carranza, J. Immune challenge of mating effort: steroid hormone profile, dark ventral patch and parasite burden in relation to intrasexual competition in male Iberian red deer. Integr. Zool. \u003cstrong\u003e15\u003c/strong\u003e, 262\u0026ndash;275 (2020).\u003c/p\u003e\n\u003cp\u003e67.\u0026nbsp; \u0026nbsp;Thoppil, J., Mehta, P., Bartels, B., Sharma, D. \u0026amp; Farrar, J. D. Impact of norepinephrine on immunity and oxidative metabolism in sepsis. Front. Immunol. \u003cstrong\u003e14\u003c/strong\u003e, 1271098 (2023).\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cervus elaphus, sexual traits, mate competition, dark ventral patch development, real time PCR, gene expression","lastPublishedDoi":"10.21203/rs.3.rs-4085936/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4085936/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMate competition encourages individuals to modulate characters involved in mating success. Adult Iberian red deer (\u003cem\u003eCervus elaphus hispanicus\u003c/em\u003e) males show a dark ventral patch (DVP) that plays a central role in mating rivalry, whose size and chemical compounds varied according to the level of male-male competition within the population. In the pigmentation of the DVP appears, after urinary excretion, a molecule called DOPEG originating from the metabolism of norepinephrine, leading us to investigate whether differential expression mechanisms of key genes (DBH and TH) encoding enzymes catalyzing the process can be sensitive to different competitive population situations and responsible for the plastic development of the DVP in red deer. We found that social environment with higher intrasexual competition, where male invest more in sexual traits, was associated with increased levels of DBH and TH transcripts, while Dopamine showed reversed values. We found alternative splicing for the TH gene, although differences between social environments appeared just related to expression levels. Our results support the internal cause of trait modulation based on differential gene expression in relation to the conditions of intrasexual competition in social environment. We propose the quantification of DBH transcripts as a molecular biomarker of male red deer reproductive activity.\u003c/p\u003e","manuscriptTitle":"Plastic sex-trait modulation by differential gene expression according to social environment in male red deer","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2024-10-08 17:03:59","doi":"10.21203/rs.3.rs-4085936/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2024-03-28 20:29:35","doi":"10.21203/rs.3.rs-4085936/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d25e4e56-365d-4a00-b678-4fde271c84dc","owner":[],"postedDate":"October 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38277942,"name":"Biological sciences/Genetics"},{"id":38277943,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2024-08-02T07:00:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-08 17:03:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-4085936","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4085936","identity":"rs-4085936","version":["v2"]},"buildId":"CiT4i_kKBbxQbnFL0ufpk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}