J'aimerais tout d'abord remercier chaleureusement Tatiana Zerjal et Andrea Rau pour m'avoir accueilli et encadré durant ces 5 mois. Leur aide m'a été précieuse pour mener à bien mon stage ainsi que pour la rédaction de ce rapport. Merci Tatiana pour ta disponibilité, ta patience et les nombreux conseils qui m'ont guidé durant mon stage. Merci Andrea pour ta disponibilité, grâce à laquelle mes nombreux questionnements statistiques ont pu rapidement trouver une réponse claire et pour ton enthousiasme communicatif. Merci à tous les membres de PSGen pour m'avoir accueilli, et pour leur disponibilité de chaque instant. Merci à Denis Laloë, pour son assistance en statistiques multivariées, pour ses qualités humaines qui illuminent chaque jour la vie de l'équipe, et pour son application à faire découvrir à tous la gastronomie de la région d'origine des stagiaires. Enfin, comment oublier les membres du « bureau des stagiaires » grâce auxquels ce stage a été ponctué de rires et de bêlements. Merci à Parsoran, maintenant docteur, pour avoir facilité notre intégration à l'équipe. Merci à Anna-Charlotte, que j'espère retrouver en thèse, et à Raphaëlle, à qui je souhaite le meilleur pour sa thèse. Leur humour et leur gentillesse ont fait de chaque jour un véritable plaisir.

Résumé long

Dans le présent rapport, nous étudions les effets d'un stress thermique chronique sur le transcriptome hépatique et le transcriptome sanguin de deux lignés de poules pondeuses en utilisant la technologie RNAseq.

Dans un contexte de changement climatique, il est nécessaire d'accroitre nos connaissances quant à l'adaptation des productions agronomiques à la hausse des températures. L'industrie volaillère (viande et oeufs) occupe une place importante dans la production et les échanges sur le marché mondial, et contribue à une grande partie des apports protéiques de l'alimentation humaine. Cette industrie est cependant particulièrement sensible à chaleur, notamment en raison de spécificités physiologiques des animaux. Une hausse des températures risque donc d'entrainer des pertes de production qui provoqueraient une hausse des prix du marché et mettrait en péril la sécurité alimentaire dans de nombreuses régions du monde. Étudier les mécanismes d'adaptation des volailles à travers le prisme de la génétique permettra une meilleure sélection d'animaux résistants au stress thermique.

Au cours de l'expérimentation, 16 animaux de deux lignées sélectionnées de façon divergente pour une consommation alimentaire résiduelle (CAR) faible (R-) et élevé (R+), ont été équitablement répartis dans 2 pièces dont les températures ont été maintenues constantes à 32°C (groupe stress thermique, ST) ou à 22°C (groupe contrôle, CT) pendant 4 semaines. Les R+ ont une CAR élevée, ce qui signifie qu'à niveau de production équivalent, leur consommation alimentaire est plus importante que celle des R-.

A l'issue des 4 semaines de stress, le foie et le sang des animaux de chaque groupe ont été prélevés, puis l'ARN total a été extrait et séquencé. L'analyse différentielle a ensuite été réalisée à l'aide du package R/Bioconductor edgeR dans sa version « robust ». Les gènes différentiellement exprimés (GDE) ont ensuite été analysés à l'aide des outils DAVID, IPA (Ingenuity Pathway Analysis) et STRING-db. Ces outils permettent, respectivement, de mettre en évidence les termes de « gene ontology » enrichis, les voies métaboliques altérées ainsi que les conséquences potentielles de ces altérations, et de représenter les interactions protéinesprotéines associées aux GDE. Lors de la période de stress, des données phénotypiques ont été collectées, sur les mêmes individus que ceux dont l'ARN a été séquencé, et nous présentons l'analyse de certaines de ces données, afin d'approfondir l'étude des transcriptomes hépatique et sanguin.

Nous avons mis en évidence 229 GDE dans le foie de ces animaux et 960 dans leur sang. Dans le foie, l'analyse des GDE a révélé une sous-expression de gènes liés au métabolisme lipidique, à celui des acides-aminés, aux mitochondries, elle a également mis en évidence un petit groupe de gènes liés au rythme circadien. Dans le sang, l'analyse a révélé une modification de l'expression de gènes dont les fonctions sont « liées à la cellule » (cycle cellulaire, différentiation, prolifération) et au métabolisme protéique. De plus, l'analyse de données phénotypiques a montré que le groupe ST avait une consommation alimentaire, un poids du corps et une masse totale d'oeufs pondus significativement plus faible que le groupe CT, de même que pour l'hématocrite, la concentration d'acide urique et la valeur de capacité de réduction ferrique du plasma.

Nos résultats indiquent une diminution de l'activité métabolique hépatique qui pourrait viser à diminuer la production de chaleur métabolique. Dans le sang, ils montrent une altération des fonctions « liées à la cellule » ainsi que du métabolisme protéique, associés à une diminution de l'hématocrite. Ces deux mécanismes pourraient viser à augmenter l'efficacité de la dissipation thermique.

Ces résultats permettent de mieux comprendre les mécanismes à l'oeuvre à l'échelle transcriptomique lors d'un stress thermique chronique chez la poule pondeuse, ce qui permettra de mieux orienter les schémas de sélection, améliorant aussi bien la production que le bien-être de ces animaux dans le contexte du changement climatique. Data collection ................................................................................................................ Differential expression analysis ....................................................................................... Gene Ontology analysis .................................................................................................. Other statistical analyses ................................................................................................ Ingenuity Pathway Analysis ............................................................................................. STRING gene network ...................................................................................................... GO-terms analysis of DEG ....................................................................................... b. Gene networks based on protein-protein interactions .............................................. c. Pathway analysis of the effects of heat-stress on the liver ... .................................. d. Downstream analysis ............................................................................................. e. Effects of heat-stress on three phenotypic traits ..................................................... heat-stress on lipid, protein metabolism and mitochondria ............................ Effect of the heat-stress on circadian rhythm ................................................................ Effects of the heat-stress on phenotypic traits ............................................................... Blood: impact of the heat-stress on genes expression and phenotypic traits .......... cell-related and protein metabolism pathways ......................... Effect of heat-stress on hematological parameters ........................................................

Table of contents

Results

Effects of heat

Effects of

Effect of heat-stress on

Conclusion

Introduction

Climate change has become a primary source of concern in today's society, affecting diverse areas, including politics, scientific communication with the public [START_REF] Pidgeon | The role of social and decision sciences in communicating uncertain climate risks[END_REF], public health, and food production.

With respect to the latter point, many consequences of climate change may be expected, both in tropical areas, where climate constraints are already important, as well as in temperate regions. Even though the nature and magnitude of climate change manifestations vary from one place to another, heat waves and drought are already affecting temperate and tropical regions, and are expected to become recurrent [START_REF] Thornton | Climate variability and vulnerability to climate change: a review[END_REF].

As a consequence, the adaptation of agronomic production to the effects of climate change, notably to higher ambient temperatures, is a necessity to guarantee the food supply for a growing human population, which, at its current growth rate, is predicted to reach almost 10 billion by 2050 (United Nations, 2015). Most of this population will be concentrated in what are currently the least developed regions of the world. These regions, because of their poverty and their geographic locations, are the most likely to suffer from the effects of climate change.

In particular, their food security, albeit in constant amelioration (FAO, 2015), is endangered: directly, through diminishing production, and indirectly, through an increase in global food market prices due decreased production in other countries.

Chicken meat and eggs are one of the major source of protein in human food all over the world.

In 2015, among meat sources, poultry was ranked second in terms of millions of metric tons produced worldwide (111×10 6 metric tons; pig meat: 117×10 6 metric tons) and first in terms of millions of tons traded (12.7×10 6 metric tons) according to the FAO Food Outlook (FAO, 2016). To these numbers must be added the more than 70 million metric tons of eggs produced, for almost 60% in the Asia-Pacific region [START_REF] Conway | Egg production breaks record[END_REF]. Economically, these 2 markets represented in 2013 about 26 billion US-dollars' worth of exportation worldwide (faostat).

Because of the animals' sensitivity to heat-stress, illustrated for example by the 15% drop in poultry production following the 2003 heat-wave in France [START_REF] De Bono | Impacts of summer 2003 heat wave in Europe[END_REF], the poultry industry is expected to be impacted by climate change. Three mains reasons can explain this sensitivity [START_REF] Wolfenson | Evaporative cooling of ventral regions of the skin in heat-stressed laying hens[END_REF]: (i) an elevated metabolic heat production; (ii) a weak heat dissipation by convection and radiation, because of the effective heat insulation provided by feathers; (iii) the lack of sweat glands combined with a weak respiratory water evaporation. Furthermore, public concern for animal welfare is widespread in developed countries, and is spreading in developing countries [START_REF] Barber | Nonhuman Animal Welfare in China: Evolving Rhetorical Strategies for Changing Law and Policy[END_REF]. Ill-adapted animals to high temperature will show a high death rate in case of a heat wave, which could increase public disapprobation toward industrial livestock farming, and, as all mass death of livestock, be harmful to farmer's psychological well-being [START_REF] Hall | Psychological Impact of the Animal-Human Bond in Disaster Preparedness and Response[END_REF] and their economic sustainability. Ventilation and cooling system should be considered and improved to face the rising temperatures. However, these systems are energy-consuming and require investments for their installation, also increasing farmers' economic burden.

Heat tolerance in chickens has been studied for many years, but a global understanding of the mechanisms of reaction and adaptation to heat stress in poultry is still incomplete. Studying these mechanisms through the prism of genetics may allow for a better selection of heat-adapted animals.

The aim of the present report is to study the effect of chronic heat exposure (4 weeks at 32°C) on the hepatic and blood transcriptome of two brown eggs chicken lines, hereafter denominated by R+ and R-.

These lines have been divergently selected since 1975 from a common Rhode Island Red population on their residual feed consumption (RFC) [START_REF] Bordas | Direct and correlated responses to divergent selection for residual food intake in Rhode Island Red laying hens[END_REF]. RFC is defined as the difference between the observed feed intake and a feed intake value predicted by a linear model that uses body weight, its variations, and the mass of eggs as explicative variables. The R+ line has a high RFC, which is reflected by the fact that at equal body weight and egg production, they consume 50% more food than their R-counterparts.

In the following, we will describe the effects of the heat-stress on the liver and blood transcriptomes of these two lines of laying hens. In birds, the liver is a central organ for lipids metabolism and transport, plays a major role in energy homeostasis and is the center of yolk precursor synthesis.

The blood is an interesting tissue to be studied. Unlike mammals, the nucleus is retained in the chicken's mature red blood cells, which possess a transcriptional activity. Moreover, blood sampling is easy and does not require the sacrifice of the animals, which thus enables repeated sampling at different time points on the same individuals, facilitating longitudinal studies.

This study is part of the "ChickStress" project, sponsored by the ANR program "BIOADAPT". It

Methods

Data collection

Laying hens were hatched in the INRA Pôle d'Expérimentation Avicole de Tours (PEAT) in Nouzilly, France. They were reared under standard farming conditions in floor pens until 18 weeks of age.

At that time, 92 R+ hens and 100 R-hens were equally distributed in two temperature-controlled chambers and reared in individual cages under thermo-neutral conditions (22°C), with a lighting regimen set at 14h of light per day and fed ad libitum a commercial diet.

At 27 weeks of age, the temperature of one chamber (the heat-stress (HS) chamber) was raised to 32°C during 4 weeks, while the temperature remained the same in the control (CT) chamber.

The lighting regimen and diet remained the same throughout.

At 31 weeks, 8 animals from each line and from each condition (8×2×2 = 32 animals) were slaughtered and diverse organs, including the liver were sampled. Blood samples from the same animals were collected the day before.

Total RNA from liver and blood was extracted and sequenced using an Illumina HiSeq3000 system yielding an average of 90 million 150 bp paired-end reads per sample. The reads were mapped to the Gallus gallus-5 reference genome using STAR (Spliced Transcript Alignment to a Reference; [START_REF] Dobin | STAR: ultrafast universal RNA-seq aligner[END_REF] and quantified using RSEM (RNA-Seq by Expectation Maximization; Li and Dewey, 2011) using the Ensembl v87 annotation.

As part of the "ChickStress" project, measurements were also taken on numerous phenotypic parameters. For the most part, these were studied in [START_REF] Tholance | Respone to heat stress in four lines of laying hens (UMR GABI -équipe PSGen)[END_REF]. However, some measurements were used in the present report to broaden the results obtained at the transcriptomic level. All statistical analyses on these data were performed by the author.

Differential expression analysis

Differential expression analysis was performed using the R/Bioconductor package edgeR (Robinson et al., 2010) version 3.12.1 with R version 3.3.2 (R Core Team, 2016). The Trimmed mean of M-values (TMM) method was used for library size normalization [START_REF] Robinson | A scaling normalization method for differential expression analysis of RNA-seq data[END_REF], the "edgeR-Robust" method was used to account for outliers and estimate pergene dispersion parameters [START_REF] Zhou | Robustly detecting differential expression in RNA sequencing data using observation weights[END_REF], and a generalized negative binomial model was used for model fitting.

The per-gene model used for each gene i was: log(Yij / sj) ~ groupj + floorj, were Yij is the expression level of a gene i for an individual j and sj represents the library size normalization factor for individual j. "group" is a factor with four levels, arising from each possible combination of genotype (R+ or R-) and treatment (HS or CT), and groupj represents the group corresponding to individual j. "floor" is a fixed effect accounting for the fact that the animals were reared on 3 superposed floors, and floorj represents the floor on which individual j was reared.

To account for multiple testing, raw p-values were adjusted using the Benjamini-Hochberg procedure [START_REF] Benjamini | Controlling the false discovery rate: A practical and powerful approach to multiple testing[END_REF], with a false discovery rate of 0.05.

A gene was thus considered to be differentially expressed (DE) when the adjusted p-value was smaller than or equal to 0.05.

Gene Ontology analysis

HUGO Gene Nomenclature Committee (HGNC) identifiers of differentially expressed genes (DEG) were submitted to DAVID [START_REF] Huang | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists[END_REF] functional annotation clustering tool, with species and background set to Homo sapiens, in order to group annotations based on their associated genes. Ontologies used were "ALL_*" where * is one of BP (Biological Process), MF (Molecular Function) and CC (Cellular Component).

Results from the functional annotation clustering tool were downloaded and clusters with an enrichment score lower than 2 were discarded. Enrichment score corresponds to the -log10 transformed geometric mean of the EASE-score associated to each term in the cluster. EASEscore is a modified, more conservative p-value associated with a Fisher's Exact test. An enrichment score of 2 corresponds to a mean EASE-score approximately equal to 0.01.

Gene Ontology (GO) identifiers of each cluster were then submitted to the REVIGO [START_REF] Supek | REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms[END_REF] online tool in order to remove redundant terms and help interpret the clusters.

Other statistical analyses

Feed intake, body weight and egg mass measured on the same animals used in the transcriptomic study were analyzed with R (version 3.3.2) using type II analysis of variance (ANOVA) with treatment, genotype as a fixed effect, and we corrected for a possible floor effect.

When data from several time points were available, the LME4 package version 1.1.12 [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF] was used to fit a linear mixed-effects model. Parameters of this model were the treatment (CT or HS), the time point (end of week 27 to 30), their interaction, and the individual as random effect to account for repeated measurement on the same individuals.

χ²-tests were used to assess the enrichment of down-regulated genes in clusters obtained from the Gene Ontology analysis. Results were considered significant for p ≤ 0.05.

Results were plotted using ggplot2 package [START_REF] Wickham | ggplot2[END_REF], version 2.2.1.

Ingenuity Pathway Analysis

Ingenuity Pathway Analysis (IPA) online software was used to study downstream consequences of the differential expression of liver genes, and to associate DEG from both the liver and the blood with pathways. Only canonical pathways with a -log10 (p-value) ≥ 2 were considered.

Pathways were then manually associated with global functions through color-coding.

STRING gene network

Genes network construction was realized by providing HGNC identifiers of DEG in liver to the STRING online tool [START_REF] Szklarczyk | STRING v10: protein-protein interaction networks, integrated over the tree of life[END_REF], version 10. For the representations, only "Experiments" and "Databases" were allowed as active interaction sources. The minimum required interaction score was set at 0.7 (described as "High confidence"), structure previews were disabled and disconnected nodes were hidden from the network.

Node layout was modified to facilitate readability of the figures.

Results

Identification of differentially expressed genes in the liver and blood of heat-stressed animals

We first looked for an interaction effect "condition × genotype". In our case, an interaction effect indicates that heat-stress-reacting genes do not have the same behavior depending on the genotype. We found 8 such genes in the liver and 0 in the blood. Functional analysis of these genes in the liver did not show any evidence of a clear implication in the stress response.

Because of this, and the fact that the expression correlation between R+ and R-animals from the same condition was over 0.95 for every pair of animals, we decided to omit the interaction term, thus hypothesizing that both genotypes reacted similarly to heat-stress.

Results for the treatment effect indicated that 229 of the 12, 828 expressed genes were DE in the liver of the animals from the HS group compared to the CT group, and 960 out of 11, 406 expressed genes were DE in the blood in the HS group compared to the CT group. The magnitude of mean normalized counts for DE genes ranged from 1.7 to 70, 000 in the liver and from 1.3 to 30, 000 in the blood (Figure 1a and1b).

In the liver, 45,4% of the DEG were over-expressed and 54,6% were under-expressed. 197 of the 229 identified genes had a HGNC identifiers. Among these 197 genes, the proportion between over and under expressed genes remained approximately the same.

In the blood, 960 genes were DE between the two groups, with a 1:1 ratio between over-and under-expressed genes. Of the 960 genes, 814 had a HGNC identifier, and the ratio between overand under-expressed remained the same.

We found 18 DEG common to the two tissues. Among them, 11 were differentially expressed in the same direction, and were linked to cell cycle, signaling and lipid metabolism. The seven other genes had functions related to cell cycle, Endoplasmic-reticulum-associated protein degradation or angiogenesis. 2. Effects of heat-stress on the liver transcriptome

a. GO-terms analysis of DEG

Using the DAVID online tool, we gathered and summarized GO-terms associated with liver DEG.

In total, we found 10 clusters with an enrichment score higher than 2, as shown in Table 1.

The three clusters with the highest enrichment score were related to lipid (cluster 1) or aminoacidic metabolic processes (cluster 2), with GO-terms associated with the catabolic aspect of these processes, and to the mitochondria (cluster 3), with terms associated to its membrane.

Interestingly, these 3 clusters gather a significantly higher proportion of under-expressed genes compared to the whole set of DEG. In the same fashion, cluster 10 ("alpha-amino acid catabolic process") was exclusively composed of terms associated with under-expressed genes.

Cluster 4 ("Organic substance transport") and cluster 9 ("Vesicle") grouped terms related to cellular transport or localization and to vesicle, respectively. This indicates that the heat-stress altered the movement of substances (e.g. molecules, ions) to, from, or within cells.

Clusters 5 ("Single-organism cellular process") and 6, ("Organelle part"), were made up of the majority of DEG from the analysis (respectively 178 and 181). Together, they indicate that heatstress affects processes occurring at the cellular level and involving organelles.

Cluster 7 ("Protein dimerization activity") grouped genes that are associated with a molecular function related to homo-or -heterodimerization.

Finally, cluster 8 ("Response to endogenous stimulus") was composed of stimulus-responding genes and is the only cluster where a significantly enrichment of overexpressed genes was detected.

b. Gene networks based on protein-protein interactions

The protein-protein interactions among the liver DEG were investigated using the STRING online tool, with parameters described in the Methods section. The network representation of these interactions is presented in Figure 2.

We distinguished 7 groups of genes, annotated a to g, to which we manually associated with representative functions.

c. Pathway analysis of the effects of heat-stress on the liver

We used the canonical pathway analysis tool IPA to identify the pathways significantly associated with the DEG. In total, 20 relevant pathways were identified (p ≤ 0.01), as shown in Figure 3.

Similarly to the GO-term enrichment analysis, pathways associated with lipid and amino-acids metabolisms together represented 70% of the identified pathways. Interestingly, catecholamine catabolism and cell-cycle related pathways were also affected by the heat-stress.

d. Downstream analysis

Following the canonical pathways analysis, we used IPA's "downstream effect analysis" to hypothesize the functional effects of the observed differential expressions. We provided the list of DEG to the tool, results from this analysis are presented in Figure 4.

In accordance with our previous results, the three main biological function impacted by differential expression are all related to lipids: concentration and transport of lipids, and fatty acid metabolism. e. Effects of heat-stress on three phenotypic traits

We investigated the effects of heat stress on three phenotypic traits: Feed Intake (FI), Body Weight (BW) and total mass of laid eggs. Liver is involved in the digestion and assimilation of nutrients, and in egg yolk proteins precursors synthesis.

FI was measured at the end of each week of the heat-stress period, and BW before the beginning and at the end of the stress. The total mass of laid eggs is the sum of the mass of all eggs laid during the heat-stress period.

At the end of the stress, the feed intake of the stressed group was significantly lower than that of the control group. In the control (CT) group, feed intake increased between the beginning and the end of the stress (p ≤ 0.001), whereas it remained the same in the heat stressed (HS) group (Figure 5a). This difference in feed intake resulted in a difference in body weight at the end of the stress. While no significant differences were observed between the two groups before stress,

CT group body weight increased by 5.2% between the beginning and the end of the stress, whereas HS body weight decreased by 6.9%. (Figure 5b).

The stress also led to a decrease of the total mass of laid eggs (Figure 5c); this was due to a significant difference in the number of laid eggs, but not in individual egg mass (data not shown).

Effects of heat-stress on the blood transcriptome a. GO-terms analysis of DEG

As for the liver, we used the DAVID online tool to gather and classify the GO-terms associated with blood DEG. We found 20 clusters with an enrichment score greater than 2 (Table 2).

Of these, 11 were related to biological processes, 3 to molecular functions and 6 to cellular component. Among the latter, cluster 1 ("Organelle part"), the cluster with the highest enrichment score (11.936), contains ~85% of the blood DEG and is significantly enriched in over-expressed genes. In addition, clusters 2 ("Membrane-enclosed lumen") and 18 ("Organelle membrane") also suggest that products of DEG are located in the lumen and membrane of organelles, including the nucleus.

The processes linked with cellular components assembly or disassembly are also affected by the stress (clusters 3 and 15, "Cellular component organization" and "Regulation of organelle organization"), including the "Endomembrane system organization" (cluster 20).

Clusters 8 and 14 ("Regulation of protein modification process" and "Proteolysis") are made up of terms suggesting a modification of protein metabolism, while clusters 4 and 11 ("Protein localization" and "Protein modification by small protein conjugation or removal") evoke a modification of protein localization and ubiquitination.

Clusters 13, 16, and 17 ("Macroautophagy", "Vesicle" and "Endosome") are related to lysosome and the recycling of cytoplasmic content and tend to be enriched in over-expressed genes. Together, they seem to indicate that chronic heat-stress lead to an alteration of protein metabolism in blood.

The GO-terms associated with the Molecular Function ontology are concentrated in clusters 5; 9, and 12 ("Nucleoside binding"; "Hydrolase activity" and "RNA binding"), that are composed of terms related to nucleic acids, whether ribo-or deoxyribo-, and are related to GO-terms associated with the cell-cycle alteration observed in clusters 6 and 7 ("Cellular response to stress" and "Cell cycle"). Similarly, clusters 10 and 19 ("Microtubules cytoskeleton" and "Spindle organization") are related to centrosome, microtubules and spindle organization and assembly. b. Pathway analysis of the effects of heat-stress on the blood We used the IPA canonical pathway analysis tool to identify pathways enriched in blood DEG, as previously done for the liver. In total, 18 significantly enriched pathways were identified (p ≤ 0.01). The results from this analysis are provided in Figure 6. We divided the pathways into 4 categories:

The amino-acids (1) and energy (2) groups are composed of pathways respectively related to amino-acids or lipids metabolisms and their regulation. The "cell related" pathways (3) encompass functions linked to cell proliferation, survival, differentiation or apoptosis, as well as cell cycle regulation and angiogenesis. These "cell related" pathways make up more than 50% of the list, and all have a number of complex downstream effects, making difficult their precise classification. Finally, the immune response group (4) comprises pathways linked to the immune system.

c. Effects of heat-stress on three phenotypic traits

Following the GO-terms and pathways analyses, we investigated the effect of the heat-stress on the hematocrit, that is, the ratio between the volume of red-blood cells in the blood and the total volume of blood, the Ferric Reducing Ability of Plasma (FRAP), and the uric acid concentration.

FRAP is a measure of the antioxidant power of the plasma, and was proposed by [START_REF] Benzie | The ferric reducing ability of plasma (FRAP) as a measure of "antioxidant power": the FRAP assay[END_REF]. In birds, uric acid is a proxy of protein metabolism, as it is an end product of the purines metabolism, that are synthetized from amino acids [START_REF] Johnson | Lessons from comparative physiology: could uric acid represent a physiologic alarm signal gone awry in western society?[END_REF]. Results of these analysis are presented in Figure 7.

The hematocrit of the HS group is significantly lower than that of the CT group. Similar results

were obtained for the FRAP value as well as for the uric acid concentration.

Discussion

In recent years, several studies have investigated the effect of a HS on the transcriptome of different organs in chicken (for example, [START_REF] Coble | RNA-seq analysis of broiler liver transcriptome reveals novel responses to high ambient temperature[END_REF][START_REF] Zhuo | RNA-seq analysis of abdominal fat reveals differences between modern commercial broiler chickens with high and low feed efficiencies[END_REF]. However, most focused on broilers exposed to an acute HS, and little is known about the transcriptome of laying hens.

Our study is the first to provide RNAseq analysis of liver and blood in laying hens that underwent a chronic HS. Moreover, the numerous phenotypic data measured during the stress enabled a broad the exploration of the effects of the stress on the lines used in this study.

Liver: impact of the heat-stress on gene expression and phenotypic traits

In the liver, we found 229 DEG, of which 105 were related to lipids and amino-acids catabolic functions in mitochondria (Table 1). The majority of these genes was under-expressed, suggesting that HS induces a turndown of lipid and protein metabolism. This is in agreement with previous studies in heat-stressed broilers showing a lower protein synthesis [START_REF] Zuo | Constant heat stress reduces skeletal muscle protein deposition in broilers: Heat Stress Reduces Protein Deposition[END_REF], a reduction in lipid levels [START_REF] Shim | Lipid metabolism and peroxidation in broiler chicks under chronic heat stress[END_REF], and impaired mitochondrial functions [START_REF] Huang | Heat stress impairs mitochondria functions and induces oxidative injury in broiler chickens[END_REF].

Effects of heat-stress on lipid, protein metabolism and mitochondria

The majority of the pathways found by IPA to be altered by the HS was also related to lipids or amino-acids catabolism. In Figure 3, the 8 most significant pathways (from "Ketogenesis" to "Glutaryl-CoA Degradation") share the same 6 genes: ACAT1, ACAT2, HADHA, HADHB, HMGCL and HMGCS1. These genes are all under-expressed in HS compared to the CT group and belong to the same protein-protein interaction cluster, as shown in Figure 2 (group e).

ACAT1, ACAT2, HMGCL and HMGSC1 catalyze reactions that constitute the first steps of the mevalonate pathway, which is itself the first part of cholesterol biosynthesis. The enzymes ACAT1 (mitochondrial and peroxisomal) and ACAT2 (cytoplasmic) catalyze a reaction whose products are used in ketogenesis [START_REF] Mcpherson | The biochemistry of ketogenesis and its role in weight management, neurological disease and oxidative stress[END_REF] or, after another reaction catalyzed by HMGCS1, mevalonate production. In mitochondria and peroxisomes, HMGCL catalyzes a reaction that lead to products used in the β-oxidation of fatty acids and ketogenesis. [START_REF] Mazein | A comprehensive machine-readable view of the mammalian cholesterol biosynthesis pathway[END_REF] provides a comprehensive overview of these pathways. HADHA and HADHB are the two subunits composing the mitochondrial trifunctional protein, which catalyzes the final three steps of long chain fatty acid β-oxidation [START_REF] Eaton | The mitochondrial trifunctional protein: centre of a β-oxidation metabolon?[END_REF]. The consequences of the under-expression of these genes are summarized in Figure 4, in which lipid-related alterations are predicted, which is to be expected considering the key "location" of these genes in the relevant pathways. This is consistent with previous studies showing that thermal manipulation, i.e. the exposure of embryos to high temperature, affects chicken vascularization [START_REF] Loyau | Thermal manipulation of the chicken embryo triggers differential gene expression in response to a later heat challenge[END_REF].

The "EIF4 and p70S6K Signaling", and "EIF2 Signaling" pathways are both linked to translation regulation [START_REF] Shah | Glucocorticoids abate p70S6k and eIF4E function in L6 skeletal myoblasts[END_REF], and form the group related to protein metabolism.

Effect of heat-stress on hematological parameters

The significant difference of the FRAP value between the two groups (Figure 7b) shows a diminution of the anti-oxidant power of plasma, meaning that the ability of the plasma to reduce oxidized elements is reduced in heat-stressed animals.

Similarly, the concentration of uric acid (UA), one of the major antioxidant in blood [START_REF] Sautin | Uric Acid: The Oxidant-Antioxidant Paradox[END_REF]) that contributes to the maintenance of redox balance and accounts for around 60% of the FRAP value [START_REF] Benzie | The ferric reducing ability of plasma (FRAP) as a measure of "antioxidant power": the FRAP assay[END_REF], is significantly lower in the plasma of the HS group (Figure 7c). Interestingly, xanthine dehydrogenase (XDH), which codes for the hepatic enzyme responsible for the last two steps of uric acid synthesis [START_REF] Johnson | Lessons from comparative physiology: could uric acid represent a physiologic alarm signal gone awry in western society?[END_REF] is downregulated in the liver (log2FC = -1.29; p < 0.01), which is one of the primary organs that produces UA [START_REF] Maiuolo | Regulation of uric acid metabolism and excretion[END_REF].

These observations indicate that HS increases the sensitivity toward oxidized elements, thus promoting an oxidative stress, as previously reported [START_REF] Lin | Acute heat stress induces oxidative stress in broiler chickens[END_REF],.

Overall, these results indicate that heat-stress affected numerous cell-related signaling pathways, and induced a diminution of the number of red blood cells and of the anti-oxidant activity of blood.

Conclusion

Together, our results reveal a part of the mechanisms at work in the liver and blood transcriptomes of chickens after a prolonged exposure to heat.

We found a small overlap between DEG from the liver and blood, indicating that these mechanisms are tissue-specific. The reaction in liver tends to lead to a reduction in metabolic activity, which is heat-producing, possibly to maintain normothermia. On the other hand, the blood shows an alteration of "cell-related" functions, a reduction of hematocrit, and an effect on angiogenic-related pathways. This could be explained by considering the blood as a heattransfer fluid: an increase in (i) the total blood-irrigated area and (ii) the plasma-to-cell volume could help to capture and dissipate heat [START_REF] Yahav | Alleviating heat stress in domestic fowl: different strategies[END_REF].

Our results were obtained from experimental chicken lines, representing a valuable model to provide insight into the mechanisms at work during chronic heat-stress in laying hens. They will be useful to identify heat-related markers to exploit in the selection of heat-adapted animals, with the potential to improve both production and animal welfare in hot climates. In this report, we investigate by RNAseq the effects of chronic heat stress (constant 32°C during 4 weeks, HS group) on the liver and blood transcriptomes of laying hens from two experimental lines selected for low and high residual feed intake. We found 229 and 960 differentially expressed genes (DEG) in the liver and blood respectively, when comparing HS and control (CT, 22°C) groups of animals. Analysis of the DEG revealed an under-expression of genes linked to lipid and amino acids metabolism, and mitochondria in the liver and an alteration of genes linked with cell-related functions (cell cycle, differentiation or proliferation) and protein metabolism in the blood. Analysis of phenotypic data collected during the stress exposure showed that the HS group had a significantly lower feed intake, body weight, total mass of laid eggs, hematocrit, uric acid concentration, plasmatic anti-oxidant activity compared to CT group. Our results indicate a turndown of liver's metabolic activity that may aim at decreasing metabolic heat production and an alteration of cell-related functions involved in angiogenesis that may aim at increasing heat dissipation efficiency Mots-clés : stress thermique, poule pondeuse, transcriptome, foie, sang Key Words: heat-stress, laying hen, transcriptome, liver, blood

  Introduction ........................................................................................................................ Methods ...............................................................................................................................

  ................................................................................................................................. 1. Identification of differentially expressed genes in the liver and blood of heatstressed animals .............................................................................................................. 2. Effects of heat-stress on the liver transcriptome .................................................... a.

  -stress on the blood transcriptome ............................................... a. GO-terms analysis of DEG ..................................................................................... b. Pathway analysis of the effects of heat-stress on the blood ................................... c. Effects of heat-stress on three phenotypic traits ..................................................... Discussion ........................................................................................................................ Liver: impact of the heat-stress on genes' expression and phenotypic traits ...........

  line with low RFC R+: Chicken line with high RFC RFC: Residual Feed Consumption RSEM: RNA-Seq by Expectation Maximization STAR: Spliced Transcript Alignment to a Reference STRING: Search Tool for the Retrieval of Interacting Genes/Proteins TMM: Trimmed Mean of M-values UA: Uric Acid UMR: Unité Mixte de Recherche

  was conducted within the PSGEN (Populations, Statistiques et Génome) team of the UMR GABI (Génétique Animale et Biologie Intégrative), at the Institut National de la Recherche Agronomique (INRA) center of Jouy-en-Josas, under the supervision of Tatiana Zerjal and Andrea Rau.

Figure 1 |

 1 Figure 1 | Volcano plots of the adjusted p-values (-log10transformed) and the log2(Fold Change) of the DE in the liver (a) and the blood (b). Genes were colored depending on their mean count value, which was log10transformed to make pattern more visible. The dashed line represents the adjusted p-value cutoff at p = 0.05.

Figure 2 |

 2 Figure 2 | Gene network from DEG in the liver based on known protein-protein interactions. Colored lines between proteins indicate the various type of interaction as noted in the legend. The groups of proteins were manually associated with a representative function: (a) Growth and cell differentiation, (b) Cell cycle, (c) Nuclear communication, (d) Circadian rhythm, (e) Lipid metabolism, (f) General metabolism, and (g) Mitochondrial respiratory chain. Grey lines indicate an unspecified action type. Node colors have no signification here.

Figure 3 |

 3 Figure 3 | Ingenuity Canonical Pathways associated with DEG in liver. The horizontal scale represents -log10(p-values). Pathways with p-values > 0.01 were discarded. Pathways associated with lipids metabolism are in orange, those related to aminoacids metabolism in blue, cell-cycle in red and catecholamine in green

Figure 4 |

 4 Figure 4 | Potential downstream effect of DEG in liver. Genes in red and green are significantly over-and under-expressed, respectively. The shade indicates the magnitude of the differential expression. Blue hexagons represent down-regulated biological functions. Blue, yellow and grey dashed line respectively represent inhibition; findings inconsistent with the state of the downstream molecule and unpredicted effects. Node shapes indicate the type of gene product. Squares: cytokines; rectangles: nuclear receptors; ellipses: transcription regulators; diamonds: enzymes; trapezoid: transporters.

Figure 5 |

 5 Figure 5 | Effect of heat-stress on feed intake, body weight and mass of laid eggs. (a) Evolution of feed intake during the 4 weeks of stress. Feed intake was measured at the end of each week of stress, the end of week 27 corresponds to 1 week of heat-stress (b) relative differences in body weight in each group between the beginning and the end of the stress. Relative difference was computed as (massbeginningmassend) / massbeginning and expressed in percent. Error bars represent 95% confidence interval (c) total mass of laid eggs during the stress, i.e. sum of the masses of all eggs laid during the 4 weeks, in each condition. ANOVA. n.s: non-significant; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001

Figure 6 |Figure 7 |

 67 Figure 6 | Ingenuity Canonical Pathways associated with DEG in blood. Horizontal scale represents -log10(p-value). Pathways with p-values > 0.01 were discarded. Pathways associated with energy are in orange, amino-acids in blue, "cell-related" pathways in red and immunological functions in purple

  Impact du stress thermique sur les transcriptomes hépatique et sanguin de la poule pondeuse Titre anglais : Impact of heat stress on liver and blood transcriptomes of laying hen Résumé (1600 caractères maximum) : Dans ce rapport, nous étudions par RNAseq les effets d'un stress thermique chronique (température constante de 32°C pendant 4 semaines, groupe ST) sur les transcriptomes hépatique et sanguin de deux lignés expérimentales de poules pondeuses sélectionnées de façon divergente sur la consommation alimentaire résiduelle. Nous avons trouvé respectivement 229 et 960 gènes différentiellement exprimés (GDE) dans le foie et le sang des animaux en comparant le groupe ST et le groupe CT (contrôle, 22°C). L'analyse des GDE a révélé une sous-expression de gènes liés aux métabolismes des lipides et des acides-aminés ainsi qu'aux mitochondries dans le foie, une altération de gènes aux fonctions « liées à la cellule » (cycle cellulaire, différentiation, prolifération) et au métabolisme protéique dans le sang. L'analyse de données phénotypiques collectées lors du stress a montré que le groupe ST avait une consommation alimentaire, un poids du corps, une masse totale d'oeufs pondus, un hématocrite, une concentration d'acide urique et une activité antioxydante plasmatique significativement plus faible que le groupe CT. Nos résultats indiquent une diminution de l'activité métabolique hépatique qui pourrait viser à diminuer la production de chaleur métabolique et une altération des fonctions liées à la cellule et à l'angiogenèse qui pourrait viser à augmenter l'efficacité de la dissipation thermique. Abstract (1600 caractères maximum) :

Table 1 |

 1 Functional annotation clusters of DEG in liver.Annotation clusters were obtained and named as described in Methods.In parentheses the percentage of genes that are under-expressed in each cluster is reported. Percentages in bold represent those that differ significantly from the percentage of underexpressed genes in the whole set of DEG(χ²-test, p ≤ 0.05)

	2 Domain associated with the cluster: Biological Process (BP), Cellular Component (CC) or
	Molecular Function (MF)
	3 Number of DEG in each cluster

1

Table 2 |

 2 Functional annotation clusters of DEG in blood.

	Annotation clusters were obtained and named as described in Methods.
	2 Domain associated with the cluster: Biological Process (BP), Cellular Component (CC) or
	Molecular Function (MF)
	3 Number of DEG in each cluster

1

In parentheses the percentage of genes that are under-expressed in each cluster is reported. Percentages in bold represent those that differ significantly from the percentage of underexpressed genes in the whole set of DEG

(χ²-test, p ≤ 0.05)

Remerciements

Effect of the heat-stress on circadian rhythm

In Figure 2, we distinguished a group of genes associated with the circadian rhythm, which consists of endogenous cycles of approximately 24 hours that are shared by plants [START_REF] Mcclung | Plant circadian rhythms[END_REF], bacteria [START_REF] Kondo | Circadian rhythms in prokaryotes: luciferase as a reporter of circadian gene expression in cyanobacteria[END_REF] and animals.

In avian, the circadian rhythm is controlled by the suprachiasmatic nucleus, the pineal gland and the retina [START_REF] Zeman | Ontogeny of circadian oscillations in the heart and liver in chicken[END_REF]. This master clock synchronizes internal clocks of other organs in the body. This internal clock in liver is responsible for the cyclic expression of enzymes and transcription factors [START_REF] Reinke | Circadian Clock Control of Liver Metabolic Functions[END_REF]. Both food [START_REF] Mohawk | Central and Peripheral Circadian Clocks in Mammals[END_REF] and body temperature [START_REF] Buhr | Temperature as a Universal Resetting Cue for Mammalian Circadian Oscillators[END_REF] are cues that drive circadian oscillators. Interestingly, [START_REF] Şahin | A simple way to reduce heat stress in laying hens as judged by egg laying, body weight gain and biochemical parameters[END_REF] showed that darkening the rearing place of hens at hotter times of the day reduces the effects of a heat-stress.

We found 5 genes associated with the GO-term "Circadian rhythm" in our analysis with p-value < 0.05 (ARNTL, HDAC2, NPAS2, NR2F6, PER3), and 3 more (CLOCK, NR1D2, AHR) with p < 0.1. Among them, ARNTL has been shown to affect fatty acids' chain length and saturation in adipose tissues [START_REF] Castro | A metabolomic study of adipose tissue in mice with a disruption of the circadian system[END_REF]. Furthermore, ARNTL-CLOCK heterodimers (whose genes are under-expressed in HS group) stimulates the expression of PER3 (over-expressed), which in turn represses ARNTL and CLOCK expression [START_REF] Yoshimura | Molecular analysis of avian circadian clock genes[END_REF]. Interestingly, PER3 has been shown to have an effect on body mass [START_REF] Dallmann | Altered Body Mass Regulation In Male mPeriod Mutant Mice On High-Fat Diet[END_REF] and composition, by inhibiting PPARγ-mediated transcriptional activity [START_REF] Costa | Circadian Rhythm Gene Period 3 Is an Inhibitor of the Adipocyte Cell Fate[END_REF].

Circadian rhythm alteration may be linked to an adaptive shift toward cooler time of the day.

In the present study, the HS was of constant intensity throughout the whole month, making the interpretation difficult.

Effects of the heat-stress on phenotypic traits

The HS on phenotypic traits (Figure 5) resulted in a significant difference in weight between the control and heat-stressed groups, as well as a significant difference in the total egg mass. These observations may be linked with the significant differences in feed intake observed between the groups. and are consistent with the literature [START_REF] Mashaly | Effect of heat stress on production parameters and immune responses of commercial laying hens[END_REF].

The adaptive goal underlying these metabolic changes may be the reduction of metabolic heat production in order to avoid hyperthermia [START_REF] Renaudeau | Adaptation to hot climate and strategies to alleviate heat stress in livestock production[END_REF]. Group a of Figure 2 and the "Role of JAK2 in Hormone-like Cytokine Signaling" pathway in Figure 3 could be part of the signaling responsible for this phenomenon. JAK2 is central in both growth hormone and PRLR signaling [START_REF] Yamauchi | Growth hormone and prolactin stimulate tyrosine phosphorylation of insulin receptor substrate-1,-2, and-3, their association with p85 phosphatidylinositol 3-kinase (PI3kinase), and concomitantly PI3-kinase activation via JAK2 kinase[END_REF] which are involved in the regulation of lipid metabolism in liver (GH; [START_REF] Wang | Growth Hormone-Regulated mRNAs and miRNAs in Chicken Hepatocytes[END_REF] or in egg production traits (PRLR; [START_REF] Wilkanowska | Prolactin (PRL) and Prolactin Receptor (PRLR) Genes and their Role in Poultry Production Traits[END_REF]. Overall, these results indicate a general turndown of hepatic metabolic activity.

Blood: impact of the heat-stress on genes expression and phenotypic traits

In the blood, we found 960 DEG, and observed an alteration in a variety of signaling pathways (Figure 6), that for the most part affect cell survival or proliferation. Contrary to mammalian blood, avian erythrocytes contain a nucleus and mitochondria [START_REF] Stier | Avian erythrocytes have functional mitochondria, opening novel perspectives for birds as animal models in the study of ageing[END_REF] and are transcriptionally active. There are only a few studies analyzing chicken blood transcriptome. [START_REF] Isitor | Nucleic acid distribution pattern in avian erythrocytes and mammalian lymphocytes: Comparative studies by fluorescence microscopy and digital imaging analytical techniques[END_REF] found no trace of RNA in mature chicken erythrocytes, but [START_REF] Désert | Transcriptomes of whole blood and PBMC in chickens[END_REF] analyzed chicken whole blood (i.e. all circulating cells) and PBMC (Peripheral Blood Mononuclear Cells, which excludes red blood cells) and showed that they had different transcriptomic profiles. In our study, the most abundant genes in blood (hemoglobin subunits) mirrored the results from Désert et al.

We observed a significant reduction in hematocrit (Figure 7a), consistent with previous studies [START_REF] Yahav | Blood system response of chickens to changes in environmental temperature[END_REF], but no differences in immune cell counts (data not shown) were detected. This leads us to suppose that modifications in expression are most likely due to changes in red blood cells. However, red cell counts differences are probably not the only cause. The population of circulating red blood cells in avian blood is composed of cells of different developmental stages, some of which presenting figures of mitosis [START_REF] Martinho | Blood transfusion in birds[END_REF]. Our data seem to indicate that HS has impaired cell development, and both the GO-term analysis and the pathways analysis showed that DEG in blood can be roughly divided into two groups: the cellrelated group and the protein-related group. These two groups are related, as the ubiquitinproteasome system acts at different phases of the cell-cycle, by degrading key proteins [START_REF] Bassermann | The ubiquitin proteasome system-implications for cell cycle control and the targeted treatment of cancer[END_REF], or because both are involved in endoplasmic-reticulum-associated protein degradation [START_REF] Mehnert | ERAD ubiquitin ligases: Multifunctional tools for protein quality control and waste disposal in the endoplasmic reticulum[END_REF].

Effect of heat-stress on cell-related and protein metabolism pathways

Among the "cell-function related" pathways from Figure 6, the PI3K/AKT, 14-3-3, putrescine [START_REF] Pegg | Functions of Polyamines in Mammals[END_REF], JAK/STAT, Platelet-Derived Growth Factor (PDGF), Insulin Receptor and Insulin like Growth Factor 1 (IGF-1) pathways are related to cell proliferation, survival and apoptosis in general, but also to angiogenesis (PI3K/AKT; [START_REF] Hers | Akt signalling in health and disease[END_REF], intracellular protein trafficking (14-3-3; Aghazadeh and Papadopoulos, 2016), blood formation (JAK/STAT; [START_REF] Vainchenker | JAK/STAT signaling in hematological malignancies[END_REF], or metabolism and glucose homeostasis (Insulin and IGF1;[START_REF] Singh | Insulin receptor (IR) and insulin-like growth factor receptor 1 (IGF-1R) signaling systems: novel treatment strategies for cancer[END_REF].

Additionally, VEGF (Vascular Endothelial Growth Factor) is a key player in angiogenesis [START_REF] Arjaans | VEGF pathway targeting agents, vessel normalization and tumor drug uptake: from bench to bedside[END_REF]. Interestingly, angiogenesis is one of the downstream consequence of the activation of these pathways, indicating that the HS has an effect on blood vessel formation.