Marine I Plumel

Margaux Benhaim-Delarbre

Magali Rompais

Danièle Thiersé

Gabriele Sorci

Alain Van Dorsselaer

François Criscuolo

Fabrice Bertile

Differential proteomics reveals age-dependent liver oxidative costs of immune activation in mice

Keywords: Immunosenescence, liver, proteomics, oxidative stress, ageing, mice

Individual response to an immune challenge results from the optimization of a trade-off between benefits and costs of immune cell activation. Immune-senescence can be viewed as the progressive loss of the fine-tuning of the immune system with age. Age-related immune complications may have several mechanistic bases, from immune cell defects to chronic pro-inflammatory status and oxidative imbalance, but we are still lacking experimental data showing the relative importance of each mechanism. Using a proteomic approach and subsequent biochemical validations of proteomics-derived hypotheses, we followed how 3-months and 1-year old-mice differed in their response to an acute innate immune challenge. Mice livers were collected 24 hours after immune priming and proteomic profiles were determined using 2D differential in-gel electrophoresis.

Intensity of fifteen protein spots was shown to vary with age and immune treatment. Subsequent principal component analyses revealed that old mice present a chronic up-regulation of several proteins implicated in pathways related to oxidative stress control. Interestingly, these pathways were weakly affected by the immune challenge in old compared to young individuals. In addition, old mice suffered from lower glutathione-S-transferase activity and from higher oxidative damage at the end of the experiment, thus suggesting that they paid a higher immune-related cost than young individuals. On the whole, our data showed that a significant part of the liver costs elicited by an activation of the immune system is effectively related to oxidative stress, and that ageing impairs the capacity of old individuals to control it.

Significance

Our paper tackled the open question of the cost of mounting an innate immune response.

Evolutionary biologists are familiar since a long time with the concept of trade-offs among key traits of an organism, trade-offs that shaped life history trajectories of species and individuals, ultimately in terms of reproduction and survival. On the other hands, medicine and molecular biologists studied the intimate mechanisms of immune senescence and underlined that oxidative imbalance is probably playing a key role in the progressive loss of immune function with age. This paper merges the two fields by exploring the nature of the cellular pathways that are mainly affected by age when the immune system is triggered. To do so, a proteomic approach was used to explore liver protein profiles and provide for the first time convincing data supporting the idea that oxidative stress constitutes a higher cost of immune response in old mice, possibly contributing to senescence.

Proteomics-derived hypotheses were furthermore validated using biochemical assays. This paper therefore illustrates the adding value of using proteomics to answer evolutionary biology questions, and opens a promising way to study the inter-specific variability in the rates of immune-senescence produced by evolution.

Introduction

Senescence is a multi-level phenomenon that has cell roots and whole-organism ultimate impacts. It has been defined as the accumulation of unrepaired damages on biomolecules and cells causing the progressive decline of both organism functions and reproductive and survival rates of individuals over time [START_REF] Finkel | Oxidants, oxidative stress and the biology of ageing[END_REF]. Among the physiological functions shown to be affected by age, senescence of the immune system has been largely studied [START_REF] Blasco | Immunosenescence phenotypes in the telomerase knockout mouse[END_REF][START_REF] Lasry | Senescence-associated inflammatory responses: aging and cancer perspectives[END_REF][START_REF] Miller | The aging immune system: primer and prospectus[END_REF], and old individuals are often characterized by chronic or repeated infections, inflammatory diseases or autoimmune disorders [START_REF] Caruso | Mechanisms of immunosenescence[END_REF]. In addition, the fact that senescent fibroblasts actually express inflammatory genes [START_REF] Shelton | Funk WD Microarray analysis of replicative senescence[END_REF], suggest that even non-immune cells may contribute to mal-adaptive immunity in old-age individuals.

Interestingly, several studies from the molecular biology and medicine fields recently underlined that tackling the question of immune-senescence from an evolutionary point of view may help to better understand which mechanisms are important in the progressive impairment of the system [7; 8], and also whether the decrease in the immune reactiveness with age is mal-adaptive or not. More particularly, the well-known evolutionary concept of antagonistic pleiotropy [START_REF] Williams | natural selection, and the evolution of senescence[END_REF] has been successfully applied to explain how some cell pathways may contribute to ageing. Those pathways have deleterious impact at old ages, but are still preserved by natural selection because of their beneficial effects on key life stages (in early life or during reproduction; e.g. TOR pathways, [START_REF] Blagosklonny | Revisiting the antagonistic pleiotropy theory of aging TOR-driven program and quasi-program[END_REF] and ultimately on overall individual fitness. Pleiotropy may also well explain why the control of the immune system is compromised with age, as strong responses are favoured by selection because of their efficiency in fighting parasites and diseases, but pro-inflammatory processes being also harmful in terms of colateral and auto-immune damage accumulation [START_REF] Licastro | Innate immunity and inflammation in ageing: a key for understanding age-related diseases[END_REF]. This idea of progressive accumulation of damage while growing old has also being theorized in the context of evolutionary biology, leading to the Disposable Soma theory [START_REF] Kirkwood | Evolution of ageing[END_REF]. While taking over the global idea of the Antagonistic Pleiotropy theory, Kirkwood gave a mechanistic explanation related to metabolism and direct negative impact of one function on another through the production of reactive oxygen species (ROS). ROS are inevitably produced by mitochondria when processing reduced co-enzymes to ATP. Because functions compete for limited resources, this may reduce the investment an organism is currently doing in somatic maintenance, for example in buffering oxidants. This is even more critical when the activated physiological functions entail an increase in energy expenditure or produce the self-production of reactive species, both putatively modulating oxidative balance and ultimately ageing [START_REF] Harman | Aging: a theory based on free radical and radiation chemistry[END_REF]. Such more or less clear relationships have been highlighted in laboratory and non-laboratory animal models [START_REF] Alonso-Alvarez | Increased susceptibility to oxidative stress as a proximate cost of reproduction[END_REF][START_REF] Alonso-Alvarez | Increased susceptibility to oxidative damage as a cost of accelerated somatic growth in zebra finches[END_REF][START_REF] Costantini | Omo G Effects of T-cell-mediated immune response on avian oxidative stress[END_REF][START_REF] Hamilton | Richardson A Does oxidative damage to DNA increase with age[END_REF][START_REF] Klandorf | Accelerated tissue aging and increased oxidative stress in broiler chickens fed allopurinol[END_REF][START_REF] Bourg | Oxidative stress, aging and longevity in Drosophila melanogaster[END_REF][START_REF] Wiersma | Birds sacrifice oxidative protection for reproduction[END_REF], leading to the idea that oxidative stress could be one of the mediating mechanisms sustaining life-history trade-offs such as those among reproduction, growth or somatic maintenance and longevity [START_REF] Monaghan | Torres R Oxidative stress as a mediator of life history trade-offs: mechanisms, measurements and interpretation[END_REF].

Within somatic maintenance, the immune system has a preponderant role. It preserves the organism both from external (pathogens) and internal (cancer) threatens. Because immune response potentially implies the production of ROS both via an increased energy expenditure [22; 23] or the activation of immune cells [24; 25], mounting an immune response is likely to be costly and to lead to energy and oxidative based trade-offs. For instance, innate immunity relies on production of nitric oxide and superoxide by macrophages [26; 27] which may have non-specific deleterious impact on host cells [START_REF] Lambeth | Clark RA NOX enzymes as novel targets for drug development[END_REF]. However, individuals are not paying an identical energy cost when responding to an immune challenge, suggesting that old individuals may have to face more critical immune-associated trade-offs [START_REF] Demas | Metabolic costs of mounting an antigen-stimulated immune response in adult and aged C57BL/6J mice[END_REF]. Such an observation suggests an ultimate cost of mounting an immune response, an idea further characterized in several taxa where individuals challenged with an immune treatment exhibit a reduced survival rate [29; 30], thereby underlying the key role of immune trade-off in shaping evolution patterns.

Senescence patterns are largely variable among species [START_REF] Vleck | Avian senescence: underlying mechanisms[END_REF] but also within species among individuals [START_REF] Bouwhuis | Sheldon BC Individual variation in rates of senescence: natal origin effects and disposable soma in a wild bird population[END_REF], and the underlying mechanistic bases for such variability remain to date largely undefined, even if oxidative stress is likely to be of key importance [START_REF] Bize | Senescence in cell oxidative status in two bird species with contrasting life expectancy[END_REF]. As already done in previous studies of immune response mechanisms [START_REF] Janeway | Medzhitov R Innate immune recognition[END_REF], we challenged here the immune system of mice using injections of lipopolysaccharide (LPS), a non-pathogen antigen, which is well known to trigger an innate inflammatory response. Previous studies in that field mostly considered measures at the circulating level, showing for instance increased pro-oxidant impact [START_REF] Bai | Persistent nuclear factor-kappa B activation in Ucp2-/-mice leads to enhanced nitric oxide and inflammatory cytokine production[END_REF], but also successfully characterizing proteomic specific patterns [START_REF] Oveland | Proteomic evaluation of inflammatory proteins in rat spleen interstitial fluid and lymph during LPS-induced systemic inflammation reveals increased levels of ADAMST1[END_REF]. Based on this knowledge, one objective was therefore to decipher here liver regulations that are elicited in response to an immune challenge in mice. Indeed, the liver is a key organ for metabolic homeostasis maintenance, but it also has to constantly deal with antigenic loads [37; 38], and oxidative stress plays an important role in the pathogenesis of many liver diseases [START_REF] Tanikawa | Studies on oxidative stress in liver diseases: important future trends in liver research[END_REF]. More particularly, the aim was to establish whether agerelated changes in protein profiles could support the idea that old individuals actually pay a higher cost in terms of deleterious reactions triggered upon activation of the immune system (e.g. like oxidative imbalance) than young individuals. To do so, we took advantage of the benefits a global analytical strategy like proteomics can bring in the evolutionary ecology field [START_REF] Diz | Proteomics in evolutionary ecology: linking the genotype with the phenotype[END_REF].

Materials and Methods

Experimental procedures

The experiment was conducted using eight 3 month-old (young) and eight one year-old (old) C57BL/6J male mice, reared in our laboratory under constant temperature (24 ± 2 °C) and photoperiod (13:11 L:D cycle), with free access to food (SAFE A03) and water. Each group was randomly divided in two subgroups (4 mice each in separated cages) where animals received a single intraperitoneal injection of 25 µg/kg body mass LPS (from E. Coli, serotype 055-B5, patch 011M400IV, Sigma Aldrich), or phosphate buffered solution (PBS). This dose is largely below the lethal dose for young and 1 year-old mice (see [START_REF] Belloni | Suppressing an anti-inflammatory cytokine reveals a strong age-dependent survival cost in mice[END_REF]). None of the injected mice died after the injection. Body mass (± 0.1 g) of individuals was measured just before the injection and animal death. Mice were sacrificed 24h after injection by cervical dislocation and their liver was quickly collected, snap-frozen in liquid nitrogen, and several sample aliquots were stored at -80°C until biochemical and proteomic analyses.

The study complied with legislation (L87-848) on animal experimentation in France and was done under the DEPE license obtained from the French Department of Veterinary Service (number G67-482-18). Dr François Criscuolo is the holder of an animal experimentation license (n°67-78) delivered by French authorities.

Liver proteomics

Unless otherwise specified, all chemicals and reagents were purchased from Sigma Aldrich (St. Louis, MO, USA).

Protein extraction. Frozen liver samples were first pulverized using a laboratory ball mill (Mikrodismembrator, Sartorius). 10mg of the grinded powders were then dissolved in 400 µL of a buffer composed of 8M Urea, 2M Thiourea, 4% Chaps, 1% dithiothreitol, Triton X100 0.5%, TLCK 0.05% and 0.02 to 2 mM protease inhibitors. After sonication on ice (10 s, 135 watts), 9 volumes of cold acetone were added, and samples were kept at -20°C during 16h. Proteins were pelleted by centrifugation (14 min, 4°C, 14000 g), vacuum-dried (Speedvac, Thermoscientific) after discarding supernatants, and then dissolved in a buffer composed of 7M Urea, 2M Thiourea, 30mM Tris (pH 8.5) and 4% Chaps buffer. After adjustment of the pH to 8.5, homogenization was finally completed by sonication on ice (10 s, 135 watts).

After determination of total protein concentrations using the Bio-Rad Protein Assay (BioRad, Hercules, CA, USA), protein integrity and similarity of electrophoretic protein profiles was checked prior to 2D-DIGE analysis. To do so, proteins were electrophoresed on a 12% SDS-PAGE acrylamide gel (20 µg loaded; 50 V for 30 min and then 100 V to complete migration) and stained with Coomassie blue.

2D-DIGE experiment. Protein samples were first labelled using a CyDye DIGE Fluor Minimal Dye Labeling Kit (GE HealthCare, Uppsala, Sweden). More precisely, 400 pmol of Cy3 and Cy5 were used to randomly label 50 µg of protein samples from the different groups, and 3.2 nmol of Cy2 were used to label 400 µg of proteins after having mixed all the samples (25µg each; internal standard). After incubation in the dark for 30 min on ice, protein labelling was quenched by addition of 10 mM lysine and incubation in the dark for 10 min on ice. Random distribution of samples from the 4 groups (i.e. young PBS, yound LPS, old PBS and old LPS) was by mixing and diluting 50 µg of Cy2, Cy3 and Cy5labelled protein samples in 400 µL of a buffer composed of 7M urea, 2M thiourea, 2% Chaps, 2% DTT, 2% ampholytes (Amersham Pharmacia-Biotech, Uppsala, Sweden), and a trace of bromophenol blue.

Loading onto 18cm pH3-10 non-linear immobilized pH gradient strips (IPG Ready strip, Biorad, Hercules, CA, USA), was then followed by passive rehydration over 2h30 in the dark prior to active rehydration overnight by applying a voltage of 50V using a Protean IEF cell (Biorad, Hercules, CA, USA). Isoelectric focusing (IEF) was afterwards performed until reaching a total focusing time of 85000 Vh, by applying voltage gradient steps (from 0 to 200V in 1h, from 200 to 1000 V in 4h, from 1000 to 5000 V in 16h, then 5000V for 7h). Focused proteins were then reduced and alkylated through a first incubation of IPG strips in a buffer composed of 1% DTT, 6M Urea, 50mM Tris pH 8.8, 30% glycerol and 2% SDS during 30 min, and a second incubation in a buffer composed of 2,5 % iodoacetamide, 6M Urea, 50mM Tris pH 8.8, 30% glycerol and 2% SDS during 30 min. IPG strips were then sealed onto 10% polyacrylamide SDS-PAGE gels (20 x 20 cm) with 0.5% agarose, and focused proteins were electrophoresed using a Protean II xi Cell (Biorad Hercules, CA, USA) by application of 5 mA per gel for 1h followed by 8mA per gel for 8h.

Another 2D-gel was run in parallel, on which a larger amount of proteins (i.e. 1 mg of the nonlabelled internal standard) was loaded. It was used to specifically improve quality of mass spectrometry-based protein identifications.

Quantitative analysis from 2D-gel images. After electrophoresis, gels were washed with water and gel images were acquired at 100 µm resolution (Ettan DIGE Imager, Ge Healthcare Uppsala, Sweden).

Using Progenesis Samespots (v4.5, Nonlinear dynamics, Newcastle, UK), image quality was first controlled and all images were automatically aligned, with subsequent minor "hand-made" adjustments to improve accuracy of alignments. Background subtraction was then followed by normalization of Cy3 and Cy5 spot volumes to those of corresponding Cy2 spots, and application of a correction based on 1) the calculation of the global distribution of all Cy3/Cy2 and Cy5/Cy2 ratios and 2) the determination of a global scaling factor for all gels. Hence, any possible inter-gel variations were eliminated and accurate quantitative data were obtained.

nanoLC-MS/MS analyses. After automatic excision of differential protein spots (see Statistics) using

an automated gel cutter (PROTEINEER sp, Bruker Daltonics, Bremen, Germany), a Massprep Station (Waters, MicroMass, Manchester, UK) was used first to apply 3 wash cycles (10 min each) in 50 µL of 25 mM NH 4 HCO 3 and 50 µL of acetonitrile, followed by a dehydration step (50 µL acetonitrile, 60°C, 5 min). Destaining was then followed by in-gel reduction (incubation at 60°C for 30 min in 50 µL of 10mM DTT, 25mM NH 4 HCO 3 ) and in-gel alkylation (incubation 30 min in 55mM iodoacetamide, 25 mM NH 4 HCO 3 ) of proteins using the same Massprep Station. A last washing step (10 min) in 50 µL of 25 mM NH 4 HCO 3 and 50 µL of acetonitrile, followed by gel spots dehydration during 15 min in 50 µL of acetonitrile were then carried out before in-gel protein digestion (5h at 37°C) using trypsin (Promega, Madison, WI, USA) diluted in 25 mM NH 4 HCO 3 . The resulting tryptic peptides were then extracted using 30µL of a 60% acetonitrile solution containing 0.1% of formic acid. Acetonitrile was removed by vacuum drying using a speedvac.

A 1200 series nanoHPLC-Chip system (Agilent Technologies, Palo Alto, CA, USA) coupled to an HCT™ Plus ion trap (Bruker Daltonics, Bremen, Germany) was used to analyze tryptic peptides. The solvent system consisted of 2% acetonitrile, 0.1% HCOOH in water (solvent A) and 2% water, 0.1% formic acid in acetonitrile (solvent B). After loading of 3 µL of samples onto the enrichment column (ZORBAX 300SB-C18, 40 nL, 4 mm, with a 5 µm particle size) at a flow rate of 3.75 µL / min with solvent B, elution was performed on a separation column (ZORBAX 300SB-C18, 43 mm x 75 µm, with a 5 µm particle size) at a flow rate of 300 nL/min, according to the following gradient steps: From 8% to 40% B in 7 min, then from 40% to 70% B in one min, then 70% B during 2 min.

The mass spectrometer was operated with automatic switching between MS and MS/MS modes. The following voltages were set up: -1800 V (inlet), +147. program (Open Mass Spectrometry Search Algorithm) [START_REF] Geer | Open mass spectrometry search algorithm[END_REF] was run using the MSDA software suite [START_REF] Carapito | a proteomics software suite for in-depth Mass Spectrometry Data Analysis using grid computing[END_REF]. Data were searched against a target-decoy version of the Mus musculus (Taxonomy 10090) protein database downloaded from NCBInr containing common contaminants like keratins and trypsin (July 2015, 410544 target+decoy entries), with a mass tolerance of 0.25 Da in MS and MS/MS modes, and allowing a maximum of one trypsin missed cleavage. Optional modifications were set as follows: carbamidomethylation of cysteine residues, oxidation of methionine residues, and acetylation of protein N-termini. Stringent filtering criteria based on probability-based scoring of the identified peptides were applied using Scaffold software v.3.0.7 (Proteome software Inc., Portland, OR, USA), to obtain a FDR < 1%. Hence, single peptide-based identifications were validated for MS/MS ion scores higher than 45 (Mascot) and -logE values higher than 5.3 (Omssa). Multiple peptide-based identifications were validated for MS/MS ion scores higher than 30 (Mascot) and -logE values higher than -0.05 (Omssa). Common contaminants such as keratin and trypsin were not considered.

When several different proteins were identified from analysis of a same protein spot, the so-called major ones (supposedly more abundant and responsible of possible spot intensity variation) were determined through a "peptide counting strategy" considering the percentage of experimentally detected peptides per protein (Mascot + Omssa) relative to the theoretical detectable number. To compute the theoretical number of detectable tryptic peptides, the possible presence of a Proline after a tryptic sites was considered, one missed cleavages was allowed, and the adequate size of peptides for their detection by mass spectrometry was determined directly from our data, which identified peptides composed of 5-33 amino acids. Hence, we calculated similar theoretical numbers of detectable tryptic peptides between major (69 ± 2) and minor (73 ± 3) proteins. Here, the proteins that were considered as major ones in a given protein spot were those to which about three times more peptides had been assigned versus minor ones (22 ± 1 % vs. only 8 ± 1 % of the possible tryptic peptides, respectively).

Body mass and biochemical validation of proteomic-derived hypothesis

Body mass loss (expressed in g) was recorded over the 24 hour treatment to evaluate energy cost of the immune response to the LPS injection. Biochemical measurements in liver samples were done in duplicate using assay kits purchased from Cayman Chemical (Ann Arbor, MI, USA). First, to confirm that variations in protein abundances were consistent with corresponding variations in protein activity, total glutathione S-transferase activity was assessed. To further validate the hypothesis on oxidative stress, reduced (GSH) and oxidized (GSSG) glutathione contents were measured in mice liver and liver protein carbonyl content was also measured as it is a commonly used marker of ROSinduced protein oxidation.

Statistical analysis

Body mass loss, biochemical and proteomic data were first checked for differences among groups using ANOVA with Age (young and old) and treatment (LPS and PBS) as fixed factors. In a second step, we then decided to run two Principal Component Analyses (PCA) with varimax rotation separately with a PCA conducted on the body mass loss and biochemical data (PCA1) and a PCA with only the restricted number of differential (i.e. significant) protein spots (PCA2). PCA resulted in two (PCA1) and three (PCA2) orthogonal variables (components, PCs) allowing easier comparisons of overall differences in liver biochemical and proteomic profiles among groups. Determinants of PCA1 and PCA2 were greater than 0.00001 (1.00 x 10 -3 and 1.89 x 10 -3 , respectively), Kaiser-Meyer-Olkin measures showed sample adequacy for the analysis (0.71 and 0.61, respectively), individual items KMO values were > 0.66 (PCA1) and > 0.53 (PCA2) and Bartlett's test of sphericity showed sufficiently large correlation among variables for PCA (χ 2 (10) = 97.898, P < 0.001, χ 2 (66) = 135.684, P < 0.001, respectively). Only components with eigenvalues which met the Kaiser's criterion of 1 were conserved to explain total variance of the data. Subsequently, PCA scores of each individual were analysed by using Generalized Linear Model with Age, treatment and Age x Treatment interaction to check for differences in response to LPS. When the interaction was found significant, posthoc comparisons were conducted using the same model but separated by Age or Treatment. Normality was tested for all models on residuals, using Kolmogorov-Smirnov test and checking linearity of QQ plots. Significance threshold is P < 0.054.

Results

Immune challenge-induced liver proteome changes

Multiple ANOVA analysis applied to relative intensities of 384 detected 2D-DIGE protein spots revealed that 17 of them exhibited significant differences among old and young mice treated with PBS or LPS (P < 0.05; Table 1). These 17 protein spots (Figure 1) contained 18 different proteins, which were unambiguously identified on the basis of mass spectrometry data analysis (see Supplementary Table 1 for details). Most of these 18 liver proteins are known to play key roles in the response to oxidative stress, in energy metabolism and in the response to immune challenges, which suggest involvement of these biological processes when immune system is activated.

To further understand phenotypic responses in immune-challenged (LPS) old and young mice, PCA analysis was run using only 15 of the 17 differential protein spots. Indeed, protein spots N°459 and N°510 were not considered here because they rendered the definite matrix non-positive. Three components (PC1, PC2, and PC3) with eigenvalues higher than 1, and explaining 79% of the total variance after rotation, were obtained (Table 2). Only protein loadings over 0.6 were considered due to relatively small sample size [START_REF]Field A Discovering Statistics Using SPSS[END_REF], which allowed changes in liver protein abundances to be attributed to either of the 3 principal components. Particular biological processes were then linked to each of the principal components, on the basis of GO ontologies (extracted using the MSDA software suite [START_REF] Carapito | a proteomics software suite for in-depth Mass Spectrometry Data Analysis using grid computing[END_REF]) and literature examination. Hence, our results suggest that PC1 is especially related to response to oxidative stress, PC2 to both response to oxidative stress and energy metabolism, and PC3 to both response to oxidative stress and immune challenge.

To better determine how the 3 components were altered by LPS immune challenge in old and young mice, generalized linear models were run (Table 3). A significant effect of Treatment (LPS or PBS) on PC1 and PC2 was found, while Age had a significant effect only on PC3. Interaction Age x Treatment was significant for PC1 and PC3. Thus, young and old mice responded differently to LPS injections with regard to PC1 (PC1 indices significantly decreased in young LPS mice while did not change in old mice; Figure 2). More precisely, levels of 3-hydroxyanthranilate 3,4-dioxygenase, Glutathione-S-transferase, Peroxiredoxin-6 and Carbonic anhydrase 3 being significantly reduced while those of 78 kDa glucose-regulated protein (GRP-78) were increased only in LPS-injected young mice vs. PBSinjected young mice (Table 2 andFigure 2). PC2 indices were higher in both old and young LPSinjected animals (Figure 2), thus suggesting that LPS injections had a comparable effect whatever the age of mice, levels of Glutathione synthetase, S-adenosylmethionine synthase isoform type-1, and Fibrinogen alpha polypeptide isoform 2 precursor + Propanoyl-CoA C-acyltransferase + NADPdependent malic enzyme being increased while those of Sorbitol dehydrogenase precursor are decreased in LPS-injected vs. PBS-injected mice (Table 2 and Figure 2). Finally, PC3 indices were globally higher in older mice (Figure 2), suggesting that levels of mitochondrial aldehyde dehydrogenase and Dihydrolipoyl dehydrogenase + Prolyl aminopeptidase + Fibrinogen beta chain are higher while those of Glycine N-methyltransferase are lower in old vs. young mice (Table 2). In addition, the significant interaction Age x Treatment indicated that old individuals, despite preserving higher PC3 values, exhibited a decrease after injection while young individuals significantly increased their PC3 levels (Table 3 and Figure 2). Thus, proteomics data analysis led to the hypothesis that oxidative balance is adjusted upon LPS treatment, but especially in young animals where response to endoplasmic reticulum (ER) stress would be higher. Proteomics data also indicate a stressed oxidative status in relation to immune challenge pre-exists in old mice before LPS injection. Altogether, these data strongly support that LPS treatment induces liver oxidative stress, but also that ageing is associated with different pre-and post-LPS injection oxidative status. To test this hypothesis, liver oxidative stress-related proxies were assessed.

Immune challenge-induced liver oxidative stress

For a given age, initial body masses were not different between LPS-and PBS-mice (GLM, F 1, 15 = 1.08, P = 0.319). Old individuals were shown to have a higher body mass than young individuals, irrespectively of the immune treatment (GLM, F 1, 15 = 5.00, P < 0.001; estimates 10.19 ± 2.04). PCA2 analysis using body mass loss and liver oxidative stress-related measurements produced two components (PC1 and PC2) with eigenvalues higher than 1, and explaining 87% of the total variance (Table 2). Considering only factor loadings over 0.6 (see above), we found that PC1 was related to body mass loss and levels of total GSH, GSSG and protein carbonyl. PC2 was here related to Glutathione-S-transferase activity.

Generalized linear models revealed a significant effect of Treatment (LPS or PBS) on PC1, while Age had a significant effect only on PC2 (Table 4). Interaction Age x Treatment was significant only for PC1. Thus, young and old mice responded differently to LPS injections with regard to PC1, PC1 indices being lower in LPS vs. PBS mice, but with a more marked drop in old LPS-treated animals (Figure 3). It means that body mass loss was more pronounced and levels of total GSH and GSSG were significantly more decreased in LPS-injected vs. PBS-injected old mice than in LPS-injected vs. PBS-injected young mice (Table 2 andFigure 3). In the same time, oxidative damages on liver proteins (protein carbonyl contents) were more markedly increased in older mice after LPS injection. PC2 indices were higher only in young PBS-injected mice (Figure 3), suggesting that old mice have lower Glutathione-Stransferase activity than younger individuals (Table 2 andFigure 3). Thus, our biochemical tests confirmed proteomics-driven hypothesis that LPS treatment induces liver oxidative stress, and that this effect is more marked in older mice due to a lack of antioxidant capacities.

Discussion

The present study strongly suggests that activation of the immune system in mice triggers several cellular and metabolic pathways that are all related to a response to oxidative stress. In addition, one other important conclusion is that 1 year-old individuals do not exhibit marked changes in their liver protein profiles 24-h after LPS injection, suggesting that they have lost part of their immune responsiveness. This is corroborated by the fact that old individuals had higher body mass loss after injection than young ones, which would indicate a slower cleaning-up of LPS by their immune system.

Consequently, LPS-challenged old-individuals pay a higher immune cost in terms of oxidative stress, as reflected by higher protein carbonyl levels and lower GST activity in liver homogenates. We also detected higher levels of proteins related to oxidative stress control in old individuals independently of immune treatment, suggesting constitutive costs associated to dysregulation of immune-related parameters even in the absence of pathogen. Our study therefore brings to the fore proteomic proofs that preserving immune efficiency at old age in mice may trigger oxidative imbalance.

Demonstrating that immune defence is costly in animals is still under debate [45; 46], despite some evidence for anti-parasite activities [47; 48]. The idea developed here is that immune activation is competing for limited energy resources, thereby entailing a cost for the host. Our proteomic data pointed out that abundance of several proteins was changed independently of age following LPS injection, with proteins related to oxidative stress and energy metabolism (PCA1, PC2), rather suggesting that carbohydrate (and possibly fatty acid) metabolism is enhanced (Tables 1 and2). It is interesting to note that fibrinogen alpha-2 precursor could also be positively affected by LPS injection, underlying that the preservation of hemostasis could be an important feature of the immune response. However, an experiment conducted on Blue Tit (Parus caeruleus) found rather weak energy cost of immune (antibody) response (<13% of the basal metabolic rate) and suggested that non-energetically driven trade-offs may be more constraining for the immune system [START_REF] Svensson | Energetic stress, immunosuppression and the costs of an antibody response[END_REF].

Among different possibilities (see [START_REF] Adamo | Competition between immune function and lipid transport for the protein apolipophorin III leads to stress-induced immunosuppression in crickets[END_REF] for an alternative explanation), the by-production of ROS either because of the increase in metabolic rate or directly by immune cells has been previously proposed to be particularly deleterious [START_REF] Sadd | Self-harm caused by an insect's innate immunity[END_REF]. For example, immune system regulation largely depends on the ability of a large number of cell types to produce nitric oxide (such as fibroblasts, macrophages, natural killer cells) either to regulate cell activation/proliferation (e.g. T lymphocytes) or to destroy infectious organisms [START_REF] Coleman | Nitric oxide in immunity and inflammation[END_REF]. The absence of tightly coordinated or well-balanced control of immune-induced ROS production may lead to damage accumulation, thereby accounting for immune trade-offs [53; 54]. Interestingly, this deleterious phenomenon may particularly take place when individuals are in bad conditions, either because of environmental energy constraints or of a decrease in organism functionality with age. Indeed, autoimmune (oxidative-derived) damage remains one of the main consequences of immune-senescence in old-individuals [START_REF] Sadd | Self-harm caused by an insect's innate immunity[END_REF]. In both young and old mice, proteomics data suggest that LPS treatment would trigger synthesis of glutathione, an important antioxidant [START_REF] Mari | Mitochondrial glutathione, a key survival antioxidant[END_REF], and of S-Adenosylmethionine, which can potentiate activity of antioxidant enzymes [56; 57]. Therefore, enhancing antioxidant capacities seems to be an important regulating feature when mounting an innate immune response. However, young and old mice did not respond identically. Old mice showed very little changes in their protein profiles related to response to oxidative stress. For instance, proteins like mitochondrial aldehyde dehydrogenase, peroredoxin-6 or glutathione-S-transferase were all mobilized in young individuals whereas they were not changed significantly in old LPS-treated animals. These proteins are either antioxidant enzymes or involved in mitochondrial protection against oxidative stress [START_REF] Ohsawa | Deficiency in a mitochondrial aldehyde dehydrogenase increases vulnerability to oxidative stress in PC12 cells[END_REF], suggesting that old mice have lost part of the antioxidant barrier that must come with immune response. Oxidative cost of badly tuned immune response could damage irreversibly some key ageing markers, with particular deleterious impact for immune cells themselves. Shortened telomere ends of linear chromosomes may reduce T-and Blymphocytes proliferative capacity, thereby contributing to defective immune response in oldindividuals [START_REF] Goronzy | immune aging and autoimmunity[END_REF]. We reach here one limitation of our study since we did not detect any specific immune markers to vary among groups, or target immune tissue for proteomic analysis. Therefore, weather macrophage, natural killers or lymphocytes populations in old mice have decreased cell proliferation because of enhanced senescence rate remains an open question for which proteomic has clearly a role to play. There are anyway two interesting points to note coming from our data.

First, that old animals, in addition to their weak protein response to LPS, also have basal higher protein carbonyl values than young individuals, indicating that oxidative stress related-pathways are chronically enhanced. Such age-related cost could partly be attributable to a putative high constitutive immune cost in aging animals, i.e. related to the maintenance of the immune system in the absence of pathogen [START_REF] Sandland | Costs of immune defense: an enigma wrapped in an environmental cloak?[END_REF]. Secondly, we found a chaperon protein, GRP-78 likely to be more expressed in young animals after LPS injection. This protein is associated at the cell surface with major histocompatibility class 1 molecule, suggesting a role in cell immune response [START_REF] Triantafilou | Major histocompatibility class one molecule associates with glucose regulated protein (GRP) 78 on the cell surface[END_REF]. In addition, GRP-78 may also fulfil a protective role against endoplasmic reticulum stress-induced cell death [START_REF] Rao | Coupling endoplasmic reticulum stress to the cell death program: role of the ER chaperone GRP78[END_REF].

This indicates an interesting mechanism linking immunity and body maintenance that should be more precisely studied in the context of trade-offs between immunity and other life history traits.

Conclusions

In the present study, we used a proteomic approach to further characterize in mice liver the protein pathways that may be differently affected by the trade-off between body maintenance and an innate immune response in relation with age. We highlighted that most of the differential protein spots contain proteins that are related to the control of the oxidative status of the individual. In old animals prior to the injection, those pathways appeared enhanced, and then were only weakly modified by the LPS challenge. This is likely to be associated to a higher oxidative stress paid as a cost of constitutive immune maintenance, as shown by our biochemical measurements. Interestingly, we also highlighted one new way through which immunity and lifespan may be trade-offed, via the regulation of the GRP-78 chaperon protein, illustrating the plus-value of applying proteomics to evolutionary biology questions. A coming step will be to both explore immune trade-offs in other organisms with contrasting lifespans (i.e. birds) using the same methodology, to better determine the nature of the mechanisms on which are based immune costs [47; 60; 63-65], and how they have been modified by species evolutionary history. Multiple ANOVA was conducted on proteomics-derived liver protein levels in old and young mice treated with PBS or LPS (n= 4 in each group). 17 differential protein spots were hence determined (P < 0.05), which were considered for subsequent PCA analyses. The biological processes in which each of the proteins from the 17 differential protein spots is involved in were computed using annotation explorer module of the MSDA software suite [START_REF] Carapito | a proteomics software suite for in-depth Mass Spectrometry Data Analysis using grid computing[END_REF] and complemented with literature examination. Spot N° refers to those reported in Fig 1. Principal Components Analyses were conducted on body mass loss values and liver oxidative proxies, and on proteomics-derived liver protein levels in old and young mice treated with PBS or LPS (n= 4 in each group). For protein levels, only differential 2D-DIGE protein spots (initially recognized on the basis of multiple ANOVA analysis; see Table 1) were considered. Nature of the variables forming the main axes (PC1, PC2 and PC3) allow phenotypic responses to an immune challenge (LPS) to be described compared between old and young mice. Spot N° refers to those reported in Fig 1 . Protein loadings over 0.6 (in bold) were considered and allowed principal components to be linked to particular biological processes. Young LPS 0.037  0.314 Generalized linear models were conducted to explain the variance in PC1, PC2 and PC3 determined from proteomics-derived liver protein levels (see Figure 3) in old and young mice treated with PBS or LPS (n=4 in each group). Because both treatment effects and interaction Age x treatment were significant for PC1, and both age effects and interaction age x treatment were significant for PC3, we further conducted post-hoc tests to better characterize differences between groups, by comparing Old PBS vs. Old LPS and Young PBS vs. Young LPS (in grey). Estimates and mean values are given ± SE and significant values are indicated in bold. Residuals for each models followed a normal distribution (checked using Kolmogorov-Smirnov test and QQ plot). 2) accounted for a total of 33% (PC1), 60% (PC1+PC2) and 79.7% (PC1+PC2+PC3) of the total variance. Ellipses and arrows indicate how old (black) and young (grey) mice reacted in response to LPS vs. PBS treatment. PCA was conducted on liver oxidative measurements and body mass loss recorded in old and young mice treated with PBS or LPS (n=4 in each group). Indicated by grey points, age and oxidative balance proxies (GST activity, protein carbonyl, total GSH and GSSG contents), as well as body mass loss are projected onto their first two principal components (see Table 2) accounting for a total of 63.6% (PC1) and 87.4% (PC1+PC2) of the total variance. Ellipses and arrows indicate how old (black) and young (grey) mice reacted in response to LPS vs. PBS treatment.

Tables

  3 V (outlet) and a skimmer voltage of +40V. For mass spectrometry data acquisition, the scan speed was set at 8100 m/z per sec in the MS mode and 26000 m/z per sec in the MS/MS mode. Mass range was set at 250-2000 m/z in the MS mode and 50-2800 m/z in the MS/MS mode. The 3 most intense ions (doubly charged) were selected for CID-based fragmentation, and exclusion was set at 1 min or 2 spectra. The system was fully controlled by ChemStation (Rev B.01.035R1) and EsquireControl (v5.3) software (Agilent technologies and Bruker Daltonics, respectively). MS/MS data analysis. Two different algorithms were used to analyze MS/MS data. The Mascot TM v2.3.02 program (Matrix Science, London, UK) was installed on a local server and the OMSSA v2.1.7

FiguresFigure 1 :

 1 Figures

Figure 2 :

 2 Figure 2 : PCA on proteomics-derived liver protein levels PCA was conducted on relative protein abundance values for differential 2D-DIGE protein spots (initially recognized on the basis of multiple ANOVA analysis) in old and young mice treated with PBS or LPS (n=4 in each group). Principal components (see Table2) accounted for a total of 33% (PC1), 60% (PC1+PC2) and 79.7% (PC1+PC2+PC3) of the total variance. Ellipses and arrows indicate how old (black) and young (grey) mice reacted in response to LPS vs. PBS treatment.

Figure 3 :

 3 Figure3: PCA on liver oxidative proxies and body mass loss PCA was conducted on liver oxidative measurements and body mass loss recorded in old and young mice treated with PBS or LPS (n=4 in each group). Indicated by grey points, age and oxidative balance proxies (GST activity, protein carbonyl, total GSH and GSSG contents), as well as body mass loss are projected onto their first two principal components (see Table2) accounting for a total of 63.6% (PC1) and 87.4% (PC1+PC2) of the total variance. Ellipses and arrows indicate how old (black) and young (grey) mice reacted in response to LPS vs. PBS treatment.

Table 1 . Multiple ANOVA analysis applied to 2D-DIGE protein spot relative intensities among old and young mice treated with PBS or LPS

 1

	Spot N°	Dependent variables	Acc. N°	Biological process	F	P
	110	78 kDa glucose-regulated	gi|2506545	Protein folding &	9.02	0.0021
		protein (GRP-78)		Response to ER stress
	180	Dihydrolipoyl dehydrogenase	gi|118572640	Carbohydrate metabolism	3.67	0.0437
		+ Prolyl aminopeptidase	gi|124028616	+ Proteolysis
		+ Fibrinogen beta chain	gi|67460959	+ hemostasis & Immune
				response
	214	Mitochondrial aldehyde	gi|1352250	Response to LPS	8.82	0.0023
		dehydrogenase
	271	Sorbitol dehydrogenase	gi|152031591 Carbohydrate metabolism	4.62	0.0227
		precursor
	341	3-hydroxyanthranilate 3,4-	gi|61211578	Tryptophan metabolism	4.24	0.0292
		dioxygenase
	360	Carbonic anhydrase 3	gi|30581036	Response to oxidative stress 4.57	0.0234
	362	Carbonic anhydrase 3	gi|30581036	Response to oxidative stress 7.05	0.0055
	375	Peroxiredoxin-6	gi|6671549	Response to oxidative stress 11.93 0.0007
	378	Glutathione-S-transferase	gi|121747	Response to oxidative stress 5.63	0.0121
	379	Glutathione-S-transferase	gi|121747	Response to oxidative stress 5.75	0.0112
	452	Fibrinogen alpha isoform 2	gi|33563252	Hemostasis & Immune	5.76	0.0112
		precursor		response
		+ Propanoyl-CoA C-	gi|32130432	+ bile acid biosynthesis &
		acyltransferase		fatty acid oxidation
		+ NADP-dependent malic	gi|162139827	+ Carbohydrate metabolism
		enzyme
	459	Haloacid dehalogenase-like	gi|81904469	unknown	10.31 0.0043
		hydrolase domain-containing
		protein 3
	469	Glutathione-S-transferase	gi|121747	Response to oxidative stress 4.97	0.0181
	491	Glutathione synthetase	gi|1708057	Response to oxidative stress 3.78	0.0403
	492	S-adenosylmethionine	gi|81902386	Response to oxidative stress	3.79	0.0402
		synthase isoform type-1		& methylation &
				S-adenosylmethionine
				metabolism
	507	Glycine N-methyltransferase	gi|55976615	Response to oxidative stress	4.45	0.0254
				& tumor suppression &
				S-adenosylmethionine
				metabolism & immune
				response
	510	Glycerol-3-phosphate	gi|121557	Carbohydrate metabolism	5.40	0.0139
		dehydrogenase [NAD(+)],
		cytoplasmic

Table 2 . Phenotypic responses in immune-challenged (LPS) old and young mice PC1 PC2 PC3 Liver oxidative proxies and body mass loss

 2

	Body mass loss

Table 3 . GLM applied to PC1, PC2 and PC3 determined for liver protein levels

 3

		Mean values	Estimates	D.F.	F	P
	PC1. Response to oxidative stress
	Age (old vs. young)		0.026  0.533	1.15	2.090	0.174
	Treatment (LPS vs. PBS)		-1.467  0.533	1.15	6.346	0.027
	Age x treatment			1.15	5.997	0.031
	Old PBS Old LPS	0.286  0.352 0.663  1.059		1.7	0.458	0.524
	Young PBS Young LPS	0.259  0.913 -1.208  0.436		1.7	8.407	0.027
	PC2. Response to oxidative stress and energy metabolism
	Age (old vs. young)		0.118  0.646	1.15	0.311	0.588
	Treatment (LPS vs. PBS)		1.395  0.646	1.15	5.014	0.045
	Age x treatment			1.15	0.667	0.430
	PC3. Response to oxidative stress and immune challenge
	Age (old vs. young)		2.341  0.369	1.15	25.831	< 0.001
	Treatment (LPS vs. PBS)		1.399  0.369	1.15	2.164	0.167
	Age x treatment			1.15	15.167	0.002
	Old PBS Old LPS	0.979  0.547 0.347  0.750		1.7	1.853	0.222
	Young PBS	-1.362  0.357		1.7	34.376	0.001

Acknowledgements

This work was supported by the CNRS and Strasbourg University (H2E project; IDEX UNISTRA), the French Proteomic Infrastructure (ProFI; ANR-10-INSB-08-03), and a CNRS "Projets Exploratoires Premier Soutien" (PEPS). We wish to thank Aurélie Hranitsky for her contribution with animal husbandry.

Supplementary data

Supplementary Table 1. List of identified proteins and their annotations from differential 2D-DIGE protein spots

Competing interest statement

The authors declare that they have no competing interests Generalized linear models were conducted to explain the variance in PC1 and PC2 determined from liver oxidative measurements and body mass loss (see Figure 2) in old and young mice treated with PBS or LPS (n=4 in each group). Because both treatment effects and interaction age x treatment were significant for PC1, we further conducted post-hoc tests to better characterize differences between groups, by comparing Old PBS vs. Young PBS and Old LPS vs. Young LPS (in grey). Estimates and mean values are given ± SE and significant values are indicated in bold. Residuals for each models followed a normal distribution (checked using Kolmogorov-Smirnov test and QQ plot).


Pauline Vuarin
email: pauline.vuarin@gmail.com

Alice Bouchard

Loïc Lesobre

Gwènaëlle Levêque

Toni Chalah

Michel Saint

Frédéric Lacroix

Yves Hingrat

Gabriele Sorci

No evidence for prezygotic

Keywords: cryptic female choice, inbreeding avoidance, inbreeding cost, parental relatedness, sperm selection, siring success

come

Introduction

Inbreeding, due to mating among close relatives, increases the homozygosity of offspring, allowing recessive alleles with potentially deleterious effects to be fully expressed, and reducing the expression of overdominance [START_REF] Charlesworth | The genetic basis of inbreeding depression[END_REF][START_REF] Charlesworth | The genetics of inbreeding depression[END_REF]. As a consequence, inbreeding is generally associated with impaired offspring fitness (i.e. inbreeding depression), directly through reduced survival and reproduction or indirectly, via increased vulnerability to environmental hazards [START_REF] Billing | Evidence of inbreeding depression but not inbreeding avoidance in a natural house sparrow population[END_REF][START_REF] Crnokrak | Inbreeding depression in the wild[END_REF][START_REF] Keller | Selection against inbred song sparrows during a natural population bottleneck[END_REF][START_REF] Keller | Inbreeding effects in wild populations[END_REF]Kruuk, Sheldon, & Merila, 2002). Therefore, inbreeding likely represents a major selective force that should promote the evolution of mechanisms of inbreeding avoidance.

The first mechanism of inbreeding avoidance consists in minimizing the probability to encounter a close relative when searching for mates [START_REF] Gandon | Kin competition, the cost of inbreeding and the evolution of dispersal[END_REF]. This is primarily achieved through sex-dependent dispersal from the natal site (Lebigre, Alatalo, & Siitari, 2010; M. [START_REF] Szulkin | Dispersal as a means of inbreeding avoidance in a wild bird population[END_REF]. In spatially structured, viscous populations, the potential for kin to encounter during the search for mates can be high [START_REF] Blyton | The effect of sex-biased dispersal on opposite-sexed spatial genetic structure and inbreeding risk[END_REF][START_REF] Geffen | Kin encounter rate and inbreeding avoidance in canids[END_REF][START_REF] Riehl | How cooperatively breeding birds identify relatives and avoid incest: New insights into dispersal and kin recognition[END_REF]. In this case, an additional mechanism of inbreeding avoidance is kin recognition [START_REF] Bateson | Preferences for cousins in Japanese quail[END_REF][START_REF] Hatchwell | Kin discrimination in cooperatively breeding long-tailed tits[END_REF][START_REF] Johnston | Individual odors and social communication: individual recognition, kin recognition, and scent over-marking[END_REF][START_REF] Krause | Olfactory kin recognition in a songbird[END_REF][START_REF] Penn | Kin recognition: an overview of conceptional issues, mechanisms and evolutionary theory[END_REF].

When females mate with multiple males, post-copulatory mechanisms (i.e. cryptic female choice; [START_REF] Eberhard | Female Control: Sexual Selection by Cryptic Female Choice[END_REF] of inbreeding avoidance might be particularly effective as females are thought to pay stronger costs of inbreeding than males [START_REF] Billing | Evidence of inbreeding depression but not inbreeding avoidance in a natural house sparrow population[END_REF], and therefore to be less tolerant to inbreeding [START_REF] Lehmann | Inbreeding avoidance through kin recognition: choosy females boost male dispersal[END_REF]. Cryptic female choice encompasses both pre-zygotic (i.e. selective storage [START_REF] Bretman | Promiscuous females avoid inbreeding by controlling sperm storage[END_REF][START_REF] Welke | Inbreeding avoidance through cryptic female choice in the cannibalistic orb-web spider Argiope lobata[END_REF] or use [START_REF] Firman | Gametic interactions promote inbreeding avoidance in house mice[END_REF] of sperm from unrelated mates) and post-zygotic (e.g. differential abortion or maternal investment; [START_REF] Firman | Postmating female control: 20 years of cryptic female choice[END_REF] mechanisms.

The idea that in sexually reproducing species, individuals should avoid mating with relatives essentially rests on the observation that inbred offspring have impaired fitness.

However, it has now become clear that pre-copulatory mechanisms promoting inbreeding avoidance also incur costs [START_REF] Bengtsson | Avoiding inbreeding: at what cost?[END_REF]. Dispersal and/or search for mates can be time/energy consuming and can expose to increased predation risk [START_REF] Bonte | Costs of dispersal[END_REF].

Further, refusing to mate with a close relative (kin recognition and avoidance) might imply no reproduction at all if unrelated mates are rare. In addition, coerced mating might leave little room for kin avoidance [START_REF] Parker | Sexual conflict over mating and fertilization: an overview[END_REF]. Finally, while inbreeding avoidance has some intrinsic costs, mating with kin can also provide benefits in terms of kin selection [START_REF] Kokko | When not to avoid inbreeding[END_REF]. Therefore, the net selection acting on inbreeding depends, not only on the costs associated with mating with kin, but also on its benefits and on the costs of kin avoidance [START_REF] Szulkin | Inbreeding avoidance, tolerance, or preference in animals?[END_REF].

Sexual promiscuity, and more specifically polyandry, is a widespread mating system in the animal kingdom [START_REF] Andersson | Sexual selection and mate choice[END_REF][START_REF] Pizzari | The polyandry revolution[END_REF]. Multiple mating during the same reproductive bout implies that sperm of different males compete for egg fertilization, and that females might modulate male fertilization success through covert processes operating within their genital tracts [START_REF] Birkhead | Postcopulatory sexual selection[END_REF][START_REF] Eberhard | Sexual selection by cryptic female choice on male seminal products -a new bridge between sexual selection and reproductive physiology[END_REF]. Sperm selection by females has been reported in several species and involves different mechanisms including gametic interactions, or interactions between sperm and ovarian fluids [START_REF] Firman | Gametic interactions promote inbreeding avoidance in house mice[END_REF][START_REF] Gasparini | Cryptic female preference for genetically unrelated males is mediated by ovarian fluid in the guppy[END_REF][START_REF] Løvlie | Cryptic[END_REF][START_REF] Wedekind | Non-random fertilization in mice correlates with the MHC and something else[END_REF]. While cryptic female choice is generally thought as a mechanism allowing promiscuous females to fertilize their eggs with the gametes of the most desirable males (supposedly improving offspring fitness), this might include genetically compatible (i.e., unrelated) mates. Postcopulatory mechanisms of inbreeding avoidance have been investigated in several species, and these studies have reported both positive (i.e., avoidance of fertilization by kin; [START_REF] Bretman | Molecular evidence of post-copulatory inbreeding avoidance in the field cricket Gryllus bimaculatus[END_REF][START_REF] Firman | Polyandry facilitates postcopulatory inbreeding avoidance in house mice[END_REF][START_REF] Fitzpatrick | Postcopulatory inbreeding avoidance in guppies[END_REF][START_REF] Tregenza | Polyandrous females avoid costs of inbreeding[END_REF] and negative (i.e., absence of avoidance of fertilization by kin; [START_REF] Denk | Paternity in mallards: Effects of sperm quality and female sperm selection for inbreeding avoidance[END_REF][START_REF] Evans | Does genetic relatedness of mates influence competitive fertilization success in guppies?[END_REF][START_REF] Stockley | No evidence of sperm selection by female common shrews[END_REF] results. These heterogeneous findings might be due to the intrinsic difficulty of properly testing for female post-copulatory choice based on kinship. For instance, when females mate with related and unrelated males it might be impossible to tease apart preand post-copulatory avoidance mechanisms. Similarly, if males can sense that a female is closely related, they might strategically adjust their investment into the ejaculate [START_REF] Pizzari | Sex-specific, counteracting responses to inbreeding in a bird[END_REF], which may affect siring success in the absence of any female cryptic choice. Therefore, only artificial inseminations offer the possibility to remove the effects of pre-copulatory choice and to isolate post-copulatory mechanisms [START_REF] Fitzpatrick | Postcopulatory inbreeding avoidance in guppies[END_REF].

Finally, siring success is usually assessed based on the genotyping of offspring and putative fathers. This might produce biased results if eggs fertilized by kin suffer from early developmental arrest that might go unnoticed. For this reason, a proper assessment of postcopulatory kin avoidance should also explicitly take into account differential embryo mortality.

Here, we used a promiscuous bird, the North African houbara bustard (Chlamydotis undulata undulata), to i) investigate whether females avoid fertilization with kin and ii) assess the cost of inbreeding. This species is a relevant model to study post-copulatory sexual selection since females mate with multiple males in the wild [START_REF] Lesobre | Absence of male reproductive skew, along with high frequency of polyandry and conspecific brood parasitism in the lekking houbara bustard Chlamydotis undulata undulata[END_REF]. We artificially inseminated females with a mix of sperm from triads of males with different levels of relatedness (unrelated, first cousin and half-sibling) and assessed male siring success within triads. Artificial inseminations ensured that any fertilisation bias would be the result of post-copulatory selection only. We assessed the cost of inbreeding by measuring life history traits (pre-and post-hatching survival, body mass, size and body condition at hatching, growth rate) of offspring produced by fertilizations with sperm from related or unrelated males.

Materials and methods

Mating system and reproductive biology of the houbara bustard

The North African houbara bustard is a bird species living in arid habitats, its range extends from Mauritania to Egypt, and the breeding season from January to June. Males express a conspicuous sexual display on dedicated but separated sites (explodedleks) [START_REF] Hingrat | Relationships between home-range size, sex and season with preference to the mating system of the houbara bustard Chlamydotis undulata undulata[END_REF](Hingrat et al. , 2007)); females mate with several males, as shown by the occurrence of multiple paternities within broods [START_REF] Lesobre | Absence of male reproductive skew, along with high frequency of polyandry and conspecific brood parasitism in the lekking houbara bustard Chlamydotis undulata undulata[END_REF], and can store sperm for several weeks [START_REF] Saint Jalme | Artificial insemination in Houbara bustards (Chlamydotis undulata): influence of the number of spermatozoa and insemination frequency on fertility and ability to hatch[END_REF]. Females typically lay a single clutch of one to three egg(s), but can produce a replacement clutch if the first one is lost [START_REF] Saint Jalme | Seasonal variation of LH, sex steroids, body mass, molt, display, and laying in two subspecies of Houbara bustard, Chlamydotis undulata macqueenii and Chlamydotis undulata undulata, housed in outdoor cages under natural conditions[END_REF]. Only females provide parental care, the contribution of males being restricted to the transfer of genetic material, and chicks remain with their mother for 6 to 10 weeks [START_REF] Hingrat | Mating system of the houbara bustard Chlamydotis undulata undulata in eastern Morocco[END_REF].

Experimental birds and breeding program management

All birds used in this study were part of the Emirates Center for Wildlife Propagation (ECWP), a conservation breeding program located in eastern Morocco, aiming at reinforcing natural populations of the houbara bustard. This program relies entirely on artificial inseminations [START_REF] Saint Jalme | Artificial insemination in Houbara bustards (Chlamydotis undulata): influence of the number of spermatozoa and insemination frequency on fertility and ability to hatch[END_REF], where pairing is designed to promote genetic diversity while avoiding inbreeding within the captive flock [START_REF] Lesobre | Conservation genetics of houbara bustard (Chlamydotis undulata undulata): Population structure and its implications for the reinforcement of wild populations[END_REF]. Ejaculates are routinely collected using a dummy female, and immediately transferred into a lab adjacent to the sperm collection site. Sperm motility is scored from 0 to 5 under a light microscope, using the following scale: (0) total lack of movement, (1) few motile sperm without forward movement, (2) less than 50% of sperm showing moderate activity, (3) above 50% motile sperm showing forward movement, (4) above 80% motile sperm showing fast forward movement, (5) almost all sperm showing fast forward movement with waves and whirlwinds [START_REF] Saint Jalme | Artificial insemination in Houbara bustards (Chlamydotis undulata): influence of the number of spermatozoa and insemination frequency on fertility and ability to hatch[END_REF]. Then, the volume (± 1 µL) of undiluted ejaculates is measured using a precision microliter pipette. After dilution with Lake 7.1 diluent [START_REF] Lake | Female-biased dispersal alone can reduce the occurrence of inbreeding in black grouse (Tetrao tetrix)[END_REF] the number of sperm in the ejaculate is assessed using a spectrophotometer and a specific calibration for the species [START_REF] Chargé | Male health status, signalled by courtship display, reveals ejaculate quality and hatching success in a lekking species[END_REF].

Females are regularly checked for reproductive status and start to be inseminated with freshly collected semen when ready to lay. Laying sequences are carefully recorded, so that inseminations are generally performed 3-6 days before clutch initiation, as to maximize fertility [START_REF] Saint Jalme | Artificial insemination in Houbara bustards (Chlamydotis undulata): influence of the number of spermatozoa and insemination frequency on fertility and ability to hatch[END_REF]. Freshly laid eggs are collected and incubated in large incubators at 37.7 °C for 22 days (eggs that do not hatch after 24 days of incubation are considered failed).

Artificial inseminations

The study was conducted during the 2016 breeding season. One hundred and one females (mean age 4.3 ± 1.5 years, min-max = 3-8 years) were used for this study. Each female was inseminated once with semen from a triad of males (mean age = 5.5 ± 1.6 years, min-max = 3-8 years, male age being homogeneously distributed across relatedness categories; Table S1). Sperm was slowly delivered inside the vagina using an insemination tube mounted on a pipette [START_REF] Saint Jalme | Artificial insemination in Houbara bustards (Chlamydotis undulata): influence of the number of spermatozoa and insemination frequency on fertility and ability to hatch[END_REF]. All birds in the captive flock have a known pedigree, therefore it was possible to choose triads of males based on their level of relatedness to the female. Triads were composed of an unrelated male (relatedness coefficient r = 0), a first cousin (r = 0.125) and a half-sibling (r = 0.25). In total, 140 different males were used to perform the inseminations, and the semen of each male was used 2.2 ± 1.9 times on average (min-max = 1-13 times). In heterospermic inseminations, sperm number is positively related to fertilization success (Martin et al. 1974) and embryo development in birds [START_REF] Hemmings | Polyspermy in birds: sperm numbers and embryo survival[END_REF]. Hence, we balanced the contribution of each male in terms of sperm number. In other words, in each triad, males equally contributed to the insemination by providing an equal number of sperm (mean number of sperm per insemination = 30.0 ± 8.0 x 10 6 sperm, each male contributing to the third of this overall sperm number).

Egg collection, incubation and fertility assessment

We collected up to five eggs per female (after a single insemination, the probability that eggs laid after the five first ones are fertilized being very low), giving a total number of 469 eggs (99 out of 101 inseminated females having laid at least one egg). Five eggs were found broken in the cage and thus could not been incubated. Thirty-one eggs had poor-quality shell, representing a sanitary risk for the other eggs in the incubator. These eggs were incubated apart for 5-6 days before opening them, allowing embryonic development to initiate and revealing whether they were fertile. A final number of 433 eggs were incubated following a standardized protocol. Incubated eggs were candled (using a light beam applied against the shell) at day 8 and 21 to check for embryo development. If candling showed either no sign of development or arrested development, eggs were removed from the incubator and opened.

Eggs whose yolk had a non-fertile appearance were further analyzed to discriminate between infertility and early embryo mortality, by revealing embryonic cells in division using a DNA-specific dye [START_REF] Birkhead | Unhatched eggs: Methods for discriminating between infertility and early embryo mortality[END_REF]. Briefly, we sampled a squared piece (1 x 1 cm) of perivitelline layer (PVL) containing the germinal disc (GD). After carefully washing the PVL through 3 consecutive baths in 1 mL of Hanks' balanced salt solution (Sigma-Aldrich), it was plunged for 15 min in 1 mL of a diluted dye solution (Hoechst 33342, Thermofisher, diluted into Hanks at a concentration of 10 µg.mL -1 ; based on a solution of dye previously diluted into Lake 7.1 at a concentration of 100 µg.mL -1 ) and kept under light cover. The piece of PVL was then spread on a slide and examined under a fluorescence microscope (Nikon) to search for fluorescent clusters corresponding to groups of embryonic cells. Candling of the 433 incubated eggs revealed embryonic development in 394 cases. Out of the remaining 39 eggs, fertility analyses revealed that only 6 eggs had not been fertilized, while for 33 eggs it was not possible to unambiguously assign them as fertile or not. Even including these uncertain eggs in the non-fertile category, the overall fertility rate was high (394 out of 433, 91.0%).

Offspring growth and survival under captive conditions

188 chicks hatched out of the 394 fertile eggs. Hatchlings were transferred into indoor facilities where they were kept in small plastic boxes (0.25 m², maximum 6 individuals per box) for 10 days. They were fed by hand with a mix of pellets (Evialis, 24% of protein content), fresh chopped alfalfa, mealworms and crickets. Then, they were kept in outdoor cages (16 m², maximum 6 individuals per cage) up to 40 days of age, and finally in large outdoor aviaries (270 m², maximum 12 individuals per aviary) where food was delivered once a day. Water was provided ad libitum. Chick body mass (± 1 g) and size, estimated through measurements of head-skull length using a manual caliper [from the tip of the beak to the back of the head with ± 0.5 mm precision), were measured at day 1, 9, 18, 26, 40, 60 and 90 post-hatching. Body mass and head-skull length were used to compute an index of body condition as the residuals of the linear regression of body mass against size (Schulte-Hostedde, [START_REF] Schulte-Hostedde | Restitution of mass-size residual: validating body condition indices[END_REF]. We also monitored daily survival of birds up to September 5 th , where all of them were at least 3 months old, i.e. when they reached adult size (mean age of 141 ± 17 days, min-max = 92-184 days).

Paternity analyses

DNA samples for microsatellite genotyping were either obtained from dead embryos by cutting off a small piece of chest muscle or from hatchlings by taking a small volume of blood (~100 µL) from the axillary vein, using a single-use sterilized needle and capillary tubes. Blood samples (~200 µL) from the brachial vein of the wing were also taken from all females and putative fathers, using a single-use 25-gauge insulin syringe. Samples were stored in 2 mL Eppendorf tubes containing 1.5 mL of absolute ethanol. DNA extraction and genotyping were carried out by GENOSCREEN (Lille, France), the detailed procedure being described elsewhere [START_REF] Lesobre | Absence of male reproductive skew, along with high frequency of polyandry and conspecific brood parasitism in the lekking houbara bustard Chlamydotis undulata undulata[END_REF]. We genotyped 13 microsatellite loci designed for the houbara bustard. Paternities were assigned using CERVUS 3.0, based on the following simulation parameters: 50000 cycles, 3 candidate fathers, 98.3% of fathers genotyped, 98.1% of loci typed and 0.05% of genotyping error rate. Individuals were included in parentage analyses whenever they were successfully genotyped at a minimum of 11 loci, and only paternities assigned with a confidence level of 95% were considered.

Among the 188 hatchlings, 187 were sampled for the genetic analyses, 185 were successfully genotyped and for 181 we could assign a father. For the 206 fertile eggs that did not hatch, only a small fraction (n = 63) provided sufficient genetic material (due to arrested embryo development at early stages), and we could successfully genotype 62 of them.

Paternity was then assigned for 60 chicks that did not hatch. We also had genotypes of 4 embryos from eggs that were incubated apart and we could assign paternity for all of them. All offspring that were successfully genotyped at a minimum number of 11 microsatellite loci (n = 251) had their paternity assigned. However, for 6 of them there was a mismatch with the genotype of their mother, suggesting possible mistakes in the labeling of the tubes. To be conservative these 6 offspring were removed from the analyses. Hence, paternity could be assigned for a final number of 245 offspring: 181 hatchlings and 64 failed embryos (see Table S2 and Fig. S1 in supporting information for a detailed description of sample sizes).

Ethical statement

The birds used in the present study were bred in captivity in agreement with Moroccan

Statistical analyses

All statistical analyses were performed with R 3.1.3. Paternity share was analysed using two metrics. First, based on the number of eggs with assigned paternity, we compared the probability to be sired by a half-sibling, a cousin or an unrelated male, using a test of equal proportions (the null hypothesis being that the proportion of offspring sired by each relatedness category should be 1/3). Second, we computed the within-triad siring success as the proportion of eggs sired by each male divided by the number of eggs with assigned paternity. Siring success was then analysed using a linear mixed effects model ('lmer' function of the 'lme4' package) with parental relatedness (unrelated, cousin, half-sibling) as a fixed effect, and male identity as a random variable to take into account the fact that the semen of some males was used more than once. Given that sperm motility has been shown to be a good predictor of fertilization success in several species (Tommaso [START_REF] Pizzari | Sperm competition and sperm phenotype[END_REF], including the houbara bustard, we also included it as a fixed term.

Hatching success was analyzed using a generalized linear mixed effects model with a binomial distribution of errors ('glmer' function of the 'lme4' package) that included parental relatedness, sperm storage duration and laying date as fixed effects. Maternal and paternal identities were included as random effects.

Offspring body mass, size and body condition at hatching were analyzed using linear mixed effects models. In all models, parental relatedness was included as a fixed effect, and laying date and sperm storage duration were also included as covariates. Maternal and paternal identities were included as random effects. When analyzing offspring growth during the first three months of life, we also included offspring age and its interaction with parental relatedness as fixed effects. We tested for linear, logarithmic and curvilinear effects of offspring on growth by comparing three models including age, log(age), or age and squared age, respectively, based on their AICc. A linear effect of age received the best statistical support for body mass, a quadratic effect of age for body size, and a logarithmic effect of age for body condition. Offspring identity nested into maternal identity was included as a random effect to account for the repeated measurements on the same chicks over time and the nonindependence of chicks produced by the same female. Paternal identity was also included as a random effect. An information theoretic model averaging approach was used to test for the significance of fixed effects as predictors of the response variables using the function 'dredge' of the 'MuMIn' package. Significance of each effect was based on the p-value of the corresponding conditional model-averaged coefficient.

Differences in post-hatching offspring survival among parental relatedness groups were analyzed using a mixed effects Cox-regression model (function 'coxme' of the 'coxme' package) that included maternal and paternal identities as random effects.

Results

Siring success

When using the number of eggs with assigned paternity, we found that paternity significantly deviated from the equal proportion of 1/3. Among the 245 offspring with assigned paternity, 103 were sired by males that were unrelated to the female (42.0%), 71 by cousins (29.0%) and 71 by half-siblings (29.0%) (χ² 2 = 12.539, df = 2, p = 0.002). This result would therefore suggest a cryptic female choice against related mates. However, when using the within-triad siring success, we did not find any evidence suggesting that females avoided the sperm of related males ( = -0.096 ± 0.223, t = -0.429, p = 0.541; Figure 1a). Sperm motility tended to be positively correlated with siring success, but the effect did not reach the significance threshold ( = 0.083 ± 0.045, t = 1.837, p = 0.059).

Two hundred and six chicks died before hatching, and we could assign paternity for only 60 of them (plus 4 embryos from eggs that were incubated apart). This raises the question of a possible skewed paternity of dead embryos towards kin, which would potentially change the actual paternity share across the three relatedness categories, and explain the discrepancy between the results obtained when using the overall number of eggs and the within-triad siring success. To address this issue, we performed two additional analyses. First, we computed the proportions of embryos that were sired by unrelated, cousin and half-sibling males among those that failed to hatch and used these proportions to allocate the 146 dead embryos with unknown paternity to males of the three relatedness categories (see supporting information for computational details). These new proportions no longer deviated from the 1/3 expectation (χ² = 2.530, df = 2, p = 0.282; Fig. S2), suggesting that the skewed paternity share towards unrelated males, found when considering the number of eggs with assigned paternity, might reflect differential embryo mortality rather than female sperm selection. Second, we ran a linear mixed effects model with within-triad siring success as the dependent variable and parental relatedness and sperm motility as fixed effects. This model also included hatching success and the interaction between parental relatedness and hatching success as fixed effects and male identity as a random effect. In agreement with the view that parental relatedness affected siring success depending on embryo mortality, we found a highly significant interaction between parental relatedness and hatching success (Table 1; Fig. 1b).

When clutches had a high hatching success (≥ 80%), within-triad siring success was significantly higher for unrelated males (mean ± se for unrelated males = 0.49 ± 0.09; cousins = 0.34 ± 0.08; half-siblings = 0.17 ± 0.06; t = -3.040, p = 0.003). On the contrary, when most of the eggs failed to hatch (≤ 20% hatching success), within-triad siring success was significantly higher for half-sibs (mean ± se for unrelated males = 0.19 ± 0.07; cousins = 0.27 ± 0.09; half-siblings = 0.53 ± 0.10; t = 2.793, p = 0.006).

Cost of inbreeding

A total of 188 chicks hatched out of 394 fertile eggs (47.7%). Among the 102 offspring that were sired by unrelated males, 88 hatched (86.3%), while hatching success of chicks sired by related males was substantially lower [cousins: 50 out of 69 (72.5%), halfsiblings: 43 out of 70 (61.4%)]. A generalized linear mixed effects model with a binomial distribution of errors and maternal and paternal identity declared as random effects, showed that the probability to hatch was strongly affected by parental relatedness, while neither laying date nor sperm storage duration explained hatching success (Table 2).

At hatching, chicks sired by unrelated males, cousins or half-siblings had similar body mass, size and condition (Table 3). However, growth rate (change in body mass, size and condition) during the first three months of age was significantly lower in chicks sired by cousins and even more so in chicks sired by half-siblings, as indicated by the significant age by parental relatedness interaction (Table 4, Fig. 2).

Survival was overall high (79%) under captive conditions. Nevertheless, there was a gradual decrease of survival across the three parental relatedness groups, with chicks sired by males unrelated to the female having the highest survival and chicks sired by half-siblings the lowest survival (mixed effects Cox-regression, parental relatedness:  = 4.492 ± 1.739, z = 2.58, p = 0.010) (Fig. 3).

Discussion

We found that females inseminated with a mix of sperm from unrelated, first cousin and half-sibling males had an apparently biased fertilization of their eggs towards unrelated males. Nonetheless, this paternity bias likely resulted from differential embryo mortality between offspring sired by related and unrelated males, rather than from differential siring success driven by female sperm selection. Offspring sired by males genetically related to the female suffered from higher pre-and post-hatching mortality, and reduced growth rate, compared to those sired by unrelated fathers. These results show that fertilization by close relatives incurs severe fitness costs, and that the magnitude of the costs progressively increased with increasing degree of parental relatedness.

It is now well established that, although inbreeding can undeniably incur costs, it can also confer benefits by improving inclusive fitness [START_REF] Kokko | When not to avoid inbreeding[END_REF][START_REF] Szulkin | Inbreeding avoidance, tolerance, or preference in animals?[END_REF].

Avoiding mating with close kin can also generate costs, and fertilization with genetically distant mates can disrupt the association of co-adapted genes (outbreeding cost) [START_REF] Rosengaus | Disease risk as a cost of outbreeding in the termite Zootermopsis angusticollis[END_REF]. Therefore, whether individuals should avoid, tolerate or favor inbreeding will depend on the net balance between the associated costs and benefits. We found that offspring resulting from the fertilization by sperm of close kin had severely impaired pre-and post-hatching survival, and reduced growth rate. These negative effects were expressed under the benign environmental conditions experienced in the captive breeding, and it can be easily expected that their magnitude would be higher in the wild [START_REF] Meagher | Male-male competition magnifies inbreeding depression in wild house mice[END_REF] where individuals face the full range of environmental threats. These high costs of inbreeding strongly suggest that selection should promote mechanisms of inbreeding avoidance because it seems unlikely that benefits of mating with kin and/or costs of inbreeding avoidance might outweigh the severe fitness costs reported here.

Costs of inbreeding are generally thought to be stronger for females than for males, and particularly so in species with no paternal care [START_REF] Lehmann | Inbreeding avoidance through kin recognition: choosy females boost male dispersal[END_REF]. Females and males differ in their relative investment into a given reproductive bout. Females produce large, costly gametes, and provide extensive parental care, which tremendously limits the number of reproductive bouts females can achieve per breeding season. Therefore, the cost of losing a brood due to inbred mating can be substantial for females. When male contribution to reproduction is limited to the transfer of gametes, the cost of inbreeding is expected to be lower because males can potentially mate multiply during each breeding season. This malefemale asymmetry can generate a sexual conflict over inbreeding avoidance, with females selected to avoid inbreeding and males to tolerate it [START_REF] Szulkin | Inbreeding avoidance, tolerance, or preference in animals?[END_REF]. The houbara bustard has a mating system that is compatible with the idea that males and females should have conflicting interests in terms of inbreeding avoidance. Lekking males only contribute through their gametes, can mate with several females and do not provide any parental care.

On the contrary, females raise a single brood per year, and mate with multiple males [START_REF] Lesobre | Absence of male reproductive skew, along with high frequency of polyandry and conspecific brood parasitism in the lekking houbara bustard Chlamydotis undulata undulata[END_REF] which potentially give them the opportunity to select sperm of desirable mates.

The ability to discriminate sperm based on relatedness would, therefore, represent an effective mechanism for polyandrous females to avoid the cost of inbreeding. One of the most prevalent hypothesis to explain the evolution of polyandry is that females seek genetic benefits from multiple mating [START_REF] Firman | Postmating female control: 20 years of cryptic female choice[END_REF][START_REF] Kempenaers | Mate choice and genetic quality: a review of the heterozygosity theory[END_REF]. Females would either select sperm carrying genes increasing offspring viability or attractiveness (i.e. "good genes"), or sperm carrying genetically compatible genes to their own (i.e. "compatible genes") [START_REF] Kempenaers | Mate choice and genetic quality: a review of the heterozygosity theory[END_REF]Mays et al. 2008). Both types of post-copulatory selection would require molecular and cellular mechanisms to assess sperm genetic quality or compatibility, respectively [START_REF] Tregenza | Genetic compatibility, mate choice and patterns of parentage: Invited Review[END_REF][START_REF] Zeh | The evolution of polyandry II: post-copulatory defences against genetic incompatibility[END_REF]. Despite the potential benefits of sperm selection by promiscuous females, experimental tests of post-copulatory kin avoidance have produced mixed results, with many studies failing to provide support to the hypothesis, including the present one [START_REF] Ala-Honkola | No evidence for postcopulatory inbreeding avoidance in Drosophila melanogaster[END_REF][START_REF] Denk | Paternity in mallards: Effects of sperm quality and female sperm selection for inbreeding avoidance[END_REF].

There are several explanations to this pattern. First, it is possible that females simply lack the possibility to discriminate between sperm. However, in an elegant experiment, [START_REF] Firman | Gametic interactions promote inbreeding avoidance in house mice[END_REF] realized competitive in vitro fertilizations of mouse oocytes with sperm of kin and non-kin and found a significant deviation from the ½ siring success expected in the absence of sperm selection. This shows that gametic interactions (that might include MHC receptors) can possibly provide a mechanism for sperm selection. In another study, we conducted an experiment where female houbara bustards were inseminated with a mix of sperm of young and old males (i.e. more than 12 years old; Vuarin et al. submitted). We found that young males sired a significantly higher fraction of offspring, even when early embryo mortality was taken into account. This strongly suggests that female houbara bustards do have the molecular and/or cellular mechanisms allowing them to bias fertilization towards sperm of desirable males.

The other possible explanation for the heterogeneity in the results of post-copulatory selection against kin resides in the intrinsic difficulty to properly test this hypothesis. First, when females naturally mate with related and unrelated males it is difficult to tease apart preand post-copulatory avoidance mechanisms and it might be impossible to control for differential transfer of sperm number. In the present study, we performed artificial inseminations where each male contributed an equal number of sperm, and we statistically controlled for variation in sperm motility, precluding any possible pre-copulatory mechanism (females and males were never in contact) and any possible paternity bias due to sperm competition. Second, testing the sperm selection hypothesis implies assessing whether related and unrelated sperm have different fertilization success. Using paternity assignment of successful offspring as a metric of fertilization success might be a correct approach if there is no differential embryo mortality between related and unrelated males. Differential early embryo mortality is among the recognized cost of inbreeding [START_REF] Kempenaers | Genetic similarity, inbreeding, and hatching failure in blue tits: are unhatched eggs infertile[END_REF] and therefore basing the assessment of skewed fertilization success on paternity assignment might provide erroneous results when testing for female sperm selection. Actually, when using the number of eggs with assigned paternity (mostly involving successful hatchlings), we did find that unrelated males sired a significantly higher proportion of offspring, and we might have concluded that females adaptively avoid fertilization with sperm from kin. However, when considering the large number of fertilized eggs that failed to hatch (and for which we could not assign paternity), we found similar fertilization success across all parental relatedness categories. We used the observed proportions of offspring sired by unrelated males, cousins, and half-siblings that failed to hatch to allocate dead embryos with unknown paternity to the three relatedness categories.

Although theoretical, this approach remains nevertheless meaningful when attempting to take into account differential embryo mortality. As a complement to the previous analyses, we also showed that within-triad siring success was positively or negatively correlated with hatching success, depending on the parental relatedness category. When most of the eggs in the clutch hatched, males in the unrelated category had the best siring success; on the contrary when most of the eggs failed to hatch, males in the half-sibling category had the highest siring success. This result therefore corroborates the view that differential mortality of embryo sired by related and unrelated males might account for apparently biased paternity towards unrelated fathers.

The pending question is why females do not select against sperm of related males despite very strong costs. It might be that close relatives never encounter in the wild, making the evolution of post-copulatory avoidance mechanisms useless. In the houbara bustard, natal dispersal is higher in males than females [START_REF] Hardouin | Determinants and costs of natal dispersal in a lekking species[END_REF] and this might be enough to reduce the risk of inbred mating. In addition, recent studies on communication behavior in houbara bustards showed that male vocalizations (booming) carry information on individual quality, identity and kinship, potentially used in male-male interactions within leks [START_REF] Cornec | The meaning of boom calls in a lekking bird: identity or quality information[END_REF][START_REF] Cornec | Individual signature in a lekking species: Visual and acoustic courtship parameters may help discriminating conspecifics in the houbara bustard[END_REF]. While the implication of this communication channel in male-female interactions has not been established yet, it represents a potential source of information for females in their mate choice (pre-copulatory selection) and their sperm storage strategy (post-copulatory selection). An alternative explanation for the absence of sperm selection observed here would be that cryptic female choice operates after fertilization, i.e. through post-zygotic mechanisms [START_REF] Firman | Postmating female control: 20 years of cryptic female choice[END_REF].

Females could invest differently on embryos depending on their relatedness to the sire, and inbred embryos would suffer from higher mortality as a result of lower maternal investment.

In conclusion, artificial inseminations revealed that females of a promiscuous bird species were not able to avoid fertilization with related sperm through post-copulatory mechanisms. Paternity share may be misinterpreted as the result of female cryptic choice when differential embryo mortality is not accounted for. Altogether, the lower hatching success and performance of offspring sired by related males, compared to those sired by unrelated males, support that inbred fertilization can lead to substantial fitness costs in this species.

female choice favours sperm from major histocompatibility complex-dissimilar males.

Proceedings

Tables and figures

Table 1. Effects of parental relatedness, hatching success, sperm motility and the interaction between parental relatedness and hatching success on within-triad siring success (i.e.

proportion of eggs sired by each of the three males within a given mix of sperm; n = 282).

Significant p values are in bold.

Within-triad siring success

  authorities: Ministère de l'Agriculture, Développement Rural et des Pêches Maritimes, Direction Provinciale de l'Agriculture de Boulemane, Service Véterinaire (Nu DPA/48/285/SV) under permit no. 01-16/VV; OAC/2007/E; Ac/Ou/Rn. All releases were recorded by the Haut Commissariat aux Eaux et Forêts et à la Lutte Contre la Désertification. Bird handling and sampling were performed by trained bird keepers or experimenters of the ECWP.

Figure 1 .

 1 Figure 1. Within-triad siring success for the three parental relatedness categories (unrelated, cousin or half-sibling), the dashed line representing the equal 1/3 siring success (a) and within-triad siring success as a function of hatching success (the proportion of hatched eggs per clutch) for the three relatedness categories (b). Siring success was calculated as the proportion of eggs sired by each of the three males within a given mix of sperm.

Figure 2 .

 2 Figure 2. Offspring body mass (a), size (b) and condition (c) according to parental relatedness (unrelated, cousin or half-sibling) during the first three months of age. Values are means ± s.d. of raw data for panels a and b, and means ± s.e. of residuals of the regression of body mass on body size for panel c.

Figure 3 .

 3 Figure 3. Offspring survival according to parental relatedness. The lines represent survival curves for offspring sired by males of each of the parental relatedness categories (unrelated, cousin or half-sibling), and the crosses represent censured observations (i.e., offspring that were still alive at the end of the monitoring period) (n = 181).

Acknowledgments

The Emirates Center for Wildlife Propagation (ECWP) provided the data and funding for this study, under the leadership of IFHC. We are grateful to H.H. Sheikh Mohammed bin Zayed Al Nahyan, Crown Prince of Abu Dhabi and Chairman of the International Fund for Houbara Conservation (IFHC) and H.E. Mohammed Al Bowardi Deputy Chairman of IFHC for their support. We are thankful to all ECWP employees who helped collecting the data, especially Charles Jabbour, Nourdine Abbou, Omar Elhassnaoui, Yann Le Galloudec, Emilie Arnoux and Jesse Gabbard who greatly contributed to the experiment. We are also grateful to Léo Bacon for his valuable advice regarding statistical analyses.

Data accessibility

The datasets supporting this article will be made available in the Dryad Digital Repository upon acceptance of the manuscript.

Author contributions

All authors designed the study. PV and AB conducted the experiments; PV performed statistical analyses and drafted out the manuscript, which was revised by LL, YH and GS. All authors gave final approval for publication. date and parental relatedness (unrelated, cousin or half-sibling) on hatching success.

Significant p values are in bold (n = 245).

Hatching success

Fixed