A interação QTL por ambientes (QE) têm sido relatada como uma das principais causas de insucesso da seleção assistida por marcadores moleculares (SAM). Estudos que visam o melhor entendimento da interação QE podem contribuir para o aumento da eficiência dos programas de SAM. O objetivo deste trabalho foi mapear QTL para produção de grãos (PG), prolificidade (PROL), peso de 500 grãos (P500), comprimento (CE) e diâmetro de espiga (DE), profundidade de grão (PROF), número de fileiras (NFil) e de grãos por fileira (NGFil) em uma população de milho tropical, verificar a importância da interação QE para estes caracteres e avaliar a estabilidade dos efeitos genéticos dos QTL mapeados. Uma população de 256 progênies F2:3 obtida do cruzamento entre duas linhagens de grupos heteróticos distintos e contrastantes para diversos caracteres foi avaliada em 13 ambientes. Os ambientes foram alocados em grupo de ambientes utilizando um método de agrupamento e o modelo AMMI, sendo que ambos os métodos levaram a identificação de três grupos de ambientes. O mapeamento de QTL foi realizado considerando um mapa genético com 177 marcadores microssatélites e mapeamento por intervalo composto expandido para múltiplos ambientes (mCIM). As médias de grupo de ambientes para cada caráter foram utilizadas nas análises. Foram mapeados 87 QTL, sendo 9 para PG, 9 para PROL, 14 para P500, 7 para CE, 9 para DE, 14 para PROF, 17 para NFil e 8 para NGFil. A maioria dos QTL mapeados localizou-se em regiões genômicas que ainda não foram reportados QTL, tanto para germoplasma temperado quanto tropical. A interação QTL por grupo de ambientes foi significativa para PG e não significativa para os componentes de produção. Para PG, as metodologias QQE biplot e AMMI foram utilizadas para estudar a interação QE dos efeitos genéticos dos QTL. As estimativas dos efeitos aditivos e de dominância dos QTL foram influenciadas pela interação QTL por grupo de ambientes, sendo que o padrão de interação foi específico para cada efeito genético. A expressiva interação QTL por grupo de ambientes para PG e o padrão específico de interação dos efeitos genéticos dos QTL impõe desafios adicionais à incorporação da SAM nos programas de melhoramento que visam o desenvolvimento de genótipos produtivos e com estabilidade de produção. / QTL by environment (QE) interaction has been reported as one of the main reasons for the unsuccessful of marker-assisted selection (MAS). Studies aimed to a better understanding of QE interaction could contribute to increase the efficiency of MAS programs. The objectives of this study were to map QTL for grain yield (GY), prolificacy (PROL), 500 Kernels weight (W500), ear length (EL), ear diameter (ED), kernel depth (KD), row number per ear (RN) and kernels per row number (KRN) in a tropical maize population, to assess the importance of QE interaction for these traits and to evaluate the stability of the genetic effects of mapped QTL. A population of two-hundred and fifty-six progenies obtained from the cross between two inbred lines, which belong to different heterotic groups and divergent for different traits, was evaluated in 13 environments. The environments were jointed into groups using a cluster method and an AMMI model. Both methods led to the identification of three groups of environments. The QTL mapping was performed considering a genetic map with 177 microsatellites markers and the multiple-environment composite interval mapping analysis (mCIM). The means from each group of environments of each trait were used in the analyses. Eighty seven QTL were mapped: 9 for GY, 9 for PROL, 14 for W500, 7 for EL, 9 for ED, 14 for KD, 17 for RN and 8 for KRN. Most of the mapped QTL was located in genomic regions that have not been reported QTL in both temperate and tropical germplasm. The QTL by group of environments interaction was significant for GY and not significant for yield components. For GY, QQE biplot and AMMI methodologies were used to study the QE interaction of the genetic effects of the QTL. The estimates of additive and dominance effects of QTL were affected by QTL by group of environments interaction and the interaction pattern was specific for each genetic effect. The large QTL by group of environments interaction for GY and the specific interaction pattern of the genetic effects of QTL impose additional challenges for the incorporation of MAS in breeding programs that aim to develop high yielding genotypes with grain yield stability.

Sélectionner les animaux qui ont le plus haut niveau de production, en tenant peu compte d’autres caractères, a toujours bien fonctionné dans les conditions d’un environnement favorable (i.e. ration riche en nutriments, faible charge pathogène, thermoneutralité). Toutefois, pour de nombreuses raisons (économiques, climatiques, écologiques), les éleveurs auront sans doute de plus en plus de mal à réunir de telles conditions dans l’environnement de leur troupeau, et pourront même délibérément choisir de ne pas le faire. Sélectionner des animaux qui soient adaptés avec les conditions futures des troupeaux devient donc tout aussi important qu’adapter la conduite du troupeau en fonction des génotypes sélectionnés. Pour mieux identifier les contraintes et les opportunités d'appliquer ces deux options, nous proposons, pour la première fois dans cette thèse, un modèle animal intégrant les effets de la sélection génétique et de la conduite du troupeau. Ce modèle intègre des coefficients d’allocation de la ressource alimentaire entre les fonctions biologiques en tant que caractères héritables Il permet de simuler à court-terme les performances zootechniques et à long-terme les réponses à la sélection résultant de la transmission de ces caractères d’allocation entre générations. Le modèle a été appliqué à la chèvre laitière et se focalise sur la conduite en lactation longue (LL) d’une partie des chèvres du troupeau (conduite consistant à préserver des femelles en lactation ayant après une mise bas sans réengagement d’une nouvelle reproduction). Nous sommes partis du principe que la sélection et la conduite du troupeau influencent tous deux la façon dont chaque animal alloue ses ressources entre ses fonctions biologiques. Nous avons cherché à évaluer la portée de ce principe pour mieux comprendre le développement des interactions génotype-environnement (G x E) sur le long terme. Dans un troupeau soumis à des variations du niveau d'alimentation, différentes stratégies de sélection ciblant l’amélioration de la production laitière et de la longévité ont été simulées. En accord avec la théorie de l’allocation, les réponses à la sélection révèlent que l’amélioration de la production et de la survie doit faire face à un compromis entre ces deux caractères. Cependant, ce compromis est atténué lorsque la sélection est combinée avec la conduite en LL d’une partie du troupeau. Un tel effet de synergie entre sélection et conduite résulte d’une interaction complexe entre la dynamique individuelle de performance au cours de la LL et le renouvellement du troupeau. Ainsi, la capacité innée des chèvres à prolonger leur lactation semble pouvoir être valorisée pour améliorer la résilience du troupeau. / Selecting those animals that have the greatest level of production, with little regard for other traits, has historically worked well in a favorable environment (i.e. nutrient-rich diet, low pathogen load, thermo-neutrality). However, for numerous reasons (economic, climatic, ecological) farmers will find it increasingly difficult, and indeed may actively choose not, to provide such favorable conditions in their herd environment. Selecting animals that match the future herd environments thus becomes as important as managing the herd environment to match the selected genotypes. To better identify constraints and opportunities to apply these two options, we propose, for the first time, in this thesis an animal model integrating the effects of selection and management. This model integrates resource allocation between life-functions resource as heritable traits. It enables simulating short-term performance and long-term selection response resulting from the transmission of allocation traits between generations. The model was applied to the dairy goat and focused on the management of extended lactation (EL) for a part of the herd (management practice based on keeping females in lactation without a new reproductive cycle). Both selection and management were assumed to influence the way every animal allocates its resource between functions. We aimed to assess the significance of this assumption for a better understanding of the development of genotype-environment interactions (G × E) over the long-term. In a herd subject to variations in the feeding level, different selection strategies aiming at improving milk production and longevity were simulated. In agreement with the resource allocation theory, the selection responses show improving production and survival has to face a trade-off between these two traits. However, this trade-off is alleviated when selection is combined with some proportion of EL in the herd. Such a synergistic effect between selection and management results from a complex interaction between the individual dynamic performance during EL and the herd turnover. Thereby, the innate capacity of goats to extend their lactation might be promoted to enhance herd resilience.

La France est l’un des premiers producteurs européens d’orge brassicole (Hordeum vulgare L.) et le premier exportateur mondial de malt. La production d’orge brassicole repose actuellement sur une utilisation massive d’intrants de synthèse et entraîne comme d’autres grandes cultures des impacts négatifs sur l’environnement et la santé des consommateurs. Ce travail a pour objectif de concevoir et d’évaluer des variétés et des itinéraires techniques pour cette espèce permettant une production quantitative et qualitative élevée avec un moindre recours aux intrants de synthèse. À partir d’un réseau d’essai multilocal, nous montrons que la teneur en protéines et le rendement calibré (poids des grains >2.5 mm) des orges brassicoles doivent être spécifiquement améliorés pour les conduites techniques en bas niveau d’intrants. Sur cette base, nous avons identifié les caractéristiques variétales favorables à une faible perte de teneur en protéines et de rendement calibré en situation de stress azoté.Puis, après avoir développé un modèle de culture adapté à cette espèce, nous avons identifié des stratégies de fertilisation azotées offrant les meilleurs compromis entre production quantitative et qualitative, tout en minimisant les pertes en azote vers l’environnement. Grâce à une caractérisation précise des environnements de production français, les meilleures stratégies de fertilisation azotée ont été identifiées localement. Enfin, nous avons identifié de nouvelles combinaisons de caractéristiques variétales permettant d’optimiser la production d’orge dans des situations d’intrants réduits. Nous montrons in silico, qu’adapter simultanément les caractéristiques variétales et de l’itinéraire technique permet d’atteindre des performances comparables aux variétés actuelles dans des itinéraires techniques avec recours intensif aux intrants. Nous discutons des méthodes de sélection adaptées pour identifier les variétés les plus performantes dans des situations d’intrant réduit. Enfin, nous revenons sur la démarche de conception mobilisée. / France is the largest European producer of malting barley (Hordeum vulgare L.) and the leading exporter of malt worldwide, accounting for 20% of world trade. French barley production has relied heavily on the use of synthetic inputs and has led, as other arable crops, to considerable environmental damage. The aim of this study is to design and evaluate crop and management ideotype adapted to a lower use of synthetic fertilizer. From a multi-environment trial, we conclude that the grain protein content and the calibrated yield (weight of grains >2.5 mm) have to be specifically improved in low-input management systems. We experimentally identified genotypic characteristics adapted to a low grain protein content loss and calibrated yield loss under N stress. With a crop model we adapted to malting barley, we also identified optimal N fertilization strategies allowing to reach high quantitative and qualitative performances whilst minimizing N losses toward the environment. Based on a precise characterization of environments the French barley belt, the best N fertilization strategies were identified for different regions. Finally, we identified new combinations of genotypic characteristics optimizing quantitative and qualitative performances in low management system. We showed that, in silico, a simultaneous adaptation of genotypic characteristics and optimization of N fertilization management allowed to reach similar performances as current genotypes in high-input management systems. We discuss methods to breed genotypes with high performances in low-input systems and the method used for innovative design of new management and barley malting cultivars adapted to low-input systems.

La France présente une grande diversité de conditions pédoclimatiques et par conséquent des systèmes d'élevage très variés. Pourtant, les schémas de sélection actuels en bovins laitiers considèrent que les meilleurs reproducteurs sont les mêmes quel que soit le type de système d'élevage, c'est-à-dire qu'il n'existe pas d'interactions Génotype*Milieu. L'objectif de cette thèse est de mesurer les interactions Génotype*Milieu en France sur les caractères laitiers et fonctionnels dans les 3 races bovines laitières principales (Normande, Montbéliarde, Holstein).Un point crucial dans ce type d'étude est la façon de définir le milieu. L'innovation de cette thèse est l'utilisation des profils Troupeau-Jour de Contrôle. Ce sont des coproduits du modèle génétique basé sur les contrôles élémentaires. Ils reflètent la production permise par la conduite de troupeau au cours du temps. Ils présentent l'avantage d'être disponibles à partir des bases de données nationales et d'être uniquement le reflet de la conduite, contrairement à d'autres définitions qui mêlent effet génétique et effet d'environnement au sein de la définition du milieu ou qui se focalisent sur certains points précis de la conduite sans prendre en compte son effet global. La description des profils Troupeau-Jour de Contrôle de plus de 15000 élevages normands, montbéliards et holsteins par des méthodes de lissage de séries temporelles, d'analyses factorielles et de classification a permis de créer 2 définitions du milieu en vue de l'étude des interactions Génotype*Milieu : des milieux définis comme des groupes d'élevages aux conduites distinctes ou un milieu défini comme un continuum à travers une ou des variables synthétiques.L'importance des interactions Génotype*Milieu a été estimées à partir de 2 types de modèles : un modèle multicaractères qui valorise la définition du milieu sous forme de groupes d'élevages et un modèle de norme de réaction qui valorise, quant à lui, le milieu défini comme un continuum. Les avancées méthodologiques proposées dans cette thèse concernent les modèles de normes de réaction. Des approches permettant de prendre en compte plusieurs variables d'environnement au sein d'un même modèle et de les résumer au sein d'une matrice génétique de rang réduit sont mises en avant.Aucun reclassement n'a été mis en évidence : les meilleurs reproducteurs sont les mêmes quel que soit le système d'élevage. Les schémas des sélections actuels sont donc performants. Il existe tout de même une interaction Génotype*Milieu significative sous forme d'effet d'échelle : la variabilité des valeurs génétiques des animaux est plus importante dans les systèmes d'élevage plus intensifs. Cet effet d'échelle ne sera pas pris en compte dans les modèles d'évaluation génétique, en revanche, il est possible d'imaginer un indicateur utilisable sur le terrain pour mesurer les écarts de performances, dus à cet effet, auxquels il faut s'attendre. / Because of the diversity of pedoclimatic conditions in France, dairy farms have very diversified herd management systems. For this reason, some breeders question the efficiency of the existing breeding schemes for their own management system. To overcome these concerns, a genotype by environment interaction study at the French national level has been considered necessary. The aim of this thesis is to assess the presence of genotype by environment interactions in Normande, Montbéliarde and Holstein breeds for production and functional traits.A tricky point in genotype by environment interaction studies is the environmentdefinition. The innovation of this thesis deals with the use of Herd-Test Day profiles.They are co-products of the French test day model. They reflect the production dueto herd management over time. They are available in national databases and only reflect herd management effect contrary to other definitions in which there is a confusion between genetic and environmental effects in the environment definition or which focus on specific features of the herd management without taking into account its global effect. Herd Test Day profiles of more than 15,000 herds have been studied through time series smoothing, factor analysis and clustering methods. It led to 2 definitions of the environment for the genotype by environment interaction study : environments defined as herd groups or one to several environmental gradients.Genotype by environment interactions were assessed with 2 models : the multitrait model and the reaction norm model. The first one uses herd groups as definition of the environment whereas reaction norm model considers the environment as a gradient. Several methodological improvements have been suggested for reaction norm models : taking into account several environmental gradients in a reaction norm model and summarizing them through a reduced rank genetic matrix.No reranking has been shown : the best parents are the same whatever the herd management system. Consequently, current breeding schemes are relevant. However, a scale effect exists : the variability of animal breeding values is higher in intensive herds. Genetic models will not account for this scale effect. However, a tool useful for breeders could indicate the deviation between expected performances and actual performances due to this scale effect.

As características genéticas das culturas agrícolas podem ser influenciadas pelo ambiente, interferindo na produtividade. Sendo assim, esta pesquisa visa entender como ocorre a interação entre genótipo e ambiente (IGA) e a interação entre quantitative trait locus (QTL) e ambiente (IQA), a fim de fornecer instrumentos que possam melhorar a produtividade. Em destaque, vemos que o modelo de efeitos principais aditivos e interação multiplicativa (AMMI), que considera como aditivos os efeitos principais de genótipo e ambiente e como multiplicativos os efeitos da interação, é uma importante ferramenta que permite estudar a interação com dados de ensaios multi-ambientais e apresentar boas previsões na detecção de QTL para novos ambientes. Para se levar em considera- ção a heterogeneidade da variância do erro ao longo dos ambientes, uma generalização do modelo AMMI é utilizada, o modelo AMMI ponderado ou W-AMMI. Nesta pesquisa, observando os dados resultantes de um experimento com 9 genótipos de milho conduzidos em 20 ambientes e 4 blocos, foram comparadas as análises da IGA utilizando o modelo AMMI e W-AMMI. Com um segundo conjunto de dados, resultantes do cruzamento das variedades de cevada Harrington e TR306, com 141 genótipos conduzidos em 12 ambientes foram comparados os resultados das análises da IGA e IQA utilizando os modelos AMMI e W-AMMI, sendo que foram propostas ponderações por linha (todos os ambientes para determinado genótipo ficam com o mesmo peso) e coluna (todos os genótipos para determinado ambiente ficam com o mesmo peso). / The genetic characteristics of crops can be influenced by the environment, interfering with productivity. This research intends to understand the genotype-by-environment interaction(IGA) and quantitative trait locus (QTL)-by-environment interection (IQA), in order to provide tools that can improve productivity. That the Additive Main Effects and Multiplicative Interactions (AMMI) model, has been widely used to study and understand these interactions and has shown to provide good interpretations of both IGA and IQA, as well as QTL detection. In order to take into account of the heterogeneity of error variance over the environments, a generalization of the AMMI model is used, the weighted AMMI or W-AMMI. In this study, observing the data resulting from an experiment with 9 maize genotypes conducted in 20 environments and 4 blocks, was used to compare the results between the AMMI and W-AMMI models. A second set of data, resulting a cross between the barley varieties Harrington and TR306, with 141 genotypes conducted in 12 environments, was used to compare the AMMI and two versions of the W-AMMI (equal weighs per row; and equal weights per column) models in terms of IGA, IQA and QTL detection.

Hedi HAMMAMI (2009). Genotype by Environment Interaction for Production Traits of Holsteins Using Two Countries as Model: Luxembourg and Tunisia (Doctoral thesis). Gembloux, Belgium, Gembloux Agricultural University, 170 p., 30 tabl., 16 fig. Summary. Under globalization, breeding organizations are selecting animals and exchanging germplasm across various environments. Ignoring genotype by environment interaction (G x E) may affect the efficiency of breeding strategies and limit outcomes from cooperation between breeding programs. Quantifying the effectiveness of indirect selection and effects of G x E for different breeds is therefore necessary. The objective of this thesis was to evaluate the magnitude of G x E for milk yield using Luxembourg and Tunisian Holstein populations. In fact, these two countries rely considerably on importation of superior genes from diverse origins for their breeding programs. This study needed records on both the genotype and the environment. In the first part of this thesis, genetic ties between the two populations were studied. Additive relationships and genetic similarity were important and genetic links have been strengthened with time which allowed the analysis of the phenotypic expression of daughters of common sires under each of these tow production environments. In the second part, genetic parameters for production traits of Tunisian Holsteins were estimated by a test-day random regression model (RRTD). Heritability estimates for 305-d milk, fat and protein yields were low to moderate (0.12 to 0.18) suspecting difficulties of high-producing cows to express their potential under limiting production conditions. In the third part, G x E for milk yield and persistency were investigated using character state models, where milk yield in each country was considered as a separate trait, and where the country border delimitation was designed as an environmental character state. A RRTD sire model was applied and was extended to a RRTD animal model. Significant G x E was detected for milk yield and persistency by both models. Large differences in genetic and permanent environmental variances between the two countries were observed. Genetic correlations for 305-d milk yield and persistency between Luxembourg and Tunisian Holsteins were 0.50 and 0.43 (sire model) and 0.60 and 0.36 (animal model). Moreover, low rank correlations obtained between estimated breeding values of common sires translate a significant re-ranking between the two environments. At the end of this thesis, a herd management (HM) parameter reflecting feeding and management intensity was defined. Three HM levels were identified in each country and G x E was investigated within- and across-environments. Significant G x E was detected between the Tunisian HM levels, whereas, only heterogeneous genetic variance for milk yield with limited re-ranking of sires across the three Luxembourg environments was observed. Overall, this thesis shows that under constraining environmental effects, selection for adaptive traits among economically valuable traits under their specific conditions is needed for low-input systems. When satisfactory feeding resources, management and husbandry practices are available, high degree environmental sensitivity is desired and the use of a high yielding breed may be encouraged.

As características genéticas das culturas agrícolas podem ser influenciadas pelo ambiente, interferindo na produtividade. Sendo assim, esta pesquisa visa entender como ocorre a interação entre genótipo e ambiente (IGA) e a interação entre quantitative trait locus (QTL) e ambiente (IQA), a fim de fornecer instrumentos que possam melhorar a produtividade. Em destaque, vemos que o modelo de efeitos principais aditivos e interação multiplicativa (AMMI), que considera como aditivos os efeitos principais de genótipo e ambiente e como multiplicativos os efeitos da interação, é uma importante ferramenta que permite estudar a interação com dados de ensaios multi-ambientais e apresentar boas previsões na detecção de QTL para novos ambientes. Para se levar em considera- ção a heterogeneidade da variância do erro ao longo dos ambientes, uma generalização do modelo AMMI é utilizada, o modelo AMMI ponderado ou W-AMMI. Nesta pesquisa, observando os dados resultantes de um experimento com 9 genótipos de milho conduzidos em 20 ambientes e 4 blocos, foram comparadas as análises da IGA utilizando o modelo AMMI e W-AMMI. Com um segundo conjunto de dados, resultantes do cruzamento das variedades de cevada Harrington e TR306, com 141 genótipos conduzidos em 12 ambientes foram comparados os resultados das análises da IGA e IQA utilizando os modelos AMMI e W-AMMI, sendo que foram propostas ponderações por linha (todos os ambientes para determinado genótipo ficam com o mesmo peso) e coluna (todos os genótipos para determinado ambiente ficam com o mesmo peso). / The genetic characteristics of crops can be influenced by the environment, interfering with productivity. This research intends to understand the genotype-by-environment interaction(IGA) and quantitative trait locus (QTL)-by-environment interection (IQA), in order to provide tools that can improve productivity. That the Additive Main Effects and Multiplicative Interactions (AMMI) model, has been widely used to study and understand these interactions and has shown to provide good interpretations of both IGA and IQA, as well as QTL detection. In order to take into account of the heterogeneity of error variance over the environments, a generalization of the AMMI model is used, the weighted AMMI or W-AMMI. In this study, observing the data resulting from an experiment with 9 maize genotypes conducted in 20 environments and 4 blocks, was used to compare the results between the AMMI and W-AMMI models. A second set of data, resulting a cross between the barley varieties Harrington and TR306, with 141 genotypes conducted in 12 environments, was used to compare the AMMI and two versions of the W-AMMI (equal weighs per row; and equal weights per column) models in terms of IGA, IQA and QTL detection.

Abstract Forest ecosystems are likely to shift faster in response to climate change than their maximum natural rate at which they can migrate and establish. This thesis introduces an interdisciplinary approach to develop a proactive management strategy towards climate change through assisted populations’ migration for two pine species; Aleppo pine (Pinus halepensis Mill.) and Black pine (Pinus nigra ssp. salzmannii). The main objectives of this study were to (1) evaluate plantation performance and phenotypic plasticity in the broad context of genotype by environment interaction (GEI) of these pine seed sources out-planted in contrasting trial sites to test a hypothetical northwards migration for further selection under specific conditions, (2) compare the efficiency of joint regression and Additive Main effect and Multiplicative Interaction (AMMI) models in elucidating seed sources adaptation patterns in each site then, (3) explain the basis of the differential response of seed sources to induced drought and cold stresses through the physiological, metabolomic and proteomic analyses. This study reproduced real conditions of reforestation in potential future climatic conditions either in field or under phytotron controlled conditions. The selective use of the intraspecific variability was demonstrated to have a potential contribution to alleviate adverse climate change impacts on forest ecosystems. For both species, certain seed sources were able to cope better with specific climate perturbations than others in response to the northwards shifts; seedlings not belonging to the target site could be selected for facing current climate irregularities in different environments. Abstract Here, provenances moved from slightly different transfer distance metrics were the best performers. The main problem is the high expected seedlings mortality due to freezing events and drought stress mainly for seedlings belonging to warmer provenances. Seed sources phenotypic plasticity was low to moderate for height and diameter growth and the environmental effect had a great influence on their performance variation. The AMMI models demonstrated higher adequacy to analyse complex GEI than the joint regression analysis. An important finding is that specific adaptation to adverse environmental conditions was coupled with low phenotypic plasticity responses. Differences among Aleppo pine seed sources subjected to induced drought conditions were significant for chlorophyll fluorescence, pigments and soluble sugars contents. However, induced cold stress changes transpiration rate, stomatal conductance, pigments and glucose contents. The decrease in photosynthesis under drought, unlike to cold stress, was due to stomatal closure. At the considered metabolomic level, drought tolerance was related to the decrease of glucose and fructose and the increase of sucrose contents in needles. However, the cold tolerance was associated to the decrease of glucose and the increase of sucrose and fructose contents. At the proteomic level, most of the identified proteins were related to the transcriptional machinery and sugar metabolism. The presence of enzyme related to the sulphur amino-acids metabolism could be the limiting factor for drought stress in Aleppo pine. Keywords Assisted population migration, Reforestation, Pinus halepensis, Pinus nigra ssp. salzmannii, Seed Sources, Out-planting performance, Survival, Growth, Phenotypic Plasticity, Genotype by Environment Interaction, Adaptation, Physiology, Metabolomic, Proteomic. / Taïbi, K. (2014). Integrated approach for addressing assisted population migration programs in forest management to climate change: out-planting performance, genotype by environment interactions, physiological and molecular response [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48467 / TESIS

L’étude des rendements en blé a mis en évidence une stagnation apparue dans les années 1990, notamment en France, et principalement lié aux stress hydrique et thermique. Dans ce contexte, améliorer la tolérance du blé européen à ces stress est de première importance. Cette étude avait pour but d’étudier le déterminisme génétique de la tolérance à ces stress chez le blé. Pour ce faire, trois populations de blé tendre du CIMMYT combinant des caractères d’adaptation à ces stress ont été cultivées en conditions irriguée, sèche et stress thermique irriguée plusieurs années. Des caractères physiologiques et agronomiques ont été mesurés sur un réseau de 15 essais. Une méthodologie de caractérisation environnementale a été développée et a permis l’identification de six scenarii de stress au sein du réseau. Une covariable environnementale représentative de chacun a été extraite. L’utilisation des modèles de régression factorielles a permis la décomposition de l’interaction génotype x environnement ainsi que la mise en évidence d’une sensibilité différentielle au stress dans le germplasm. Une recherche de QTL multi-environnementale a conduit à la détection de régions génomiques contrôlant les caractères physiologiques et agronomiques ainsi que leurs interactions avec l’environnement. De la caractérisation environnementale à la détection de QTL, cette étude a abouti au développement d’un outil pour les sélectionneurs permettant l’évaluation du potentiel des génotypes face à une gamme d’environnement, mais aussi à l’identification de régions génomiques impliquées dans le contrôle de la tolérance aux stress hydrique et thermique chez le blé tendre. Ceci pourrait améliorer la tolérance à ces stress au sein du germplasm européen. / A stagnation of wheat yield was reported in France and other countries worldwide since the 1990’s, which incriminated mainly drought and heat stress. Improving the European wheat tolerance to them is of first importance. This study aimed to investigate the genetic determinism of the tolerance to such stresses. Three CIMMYT bread wheat populations combining complementary heat and drought adaptive habits were grown in Northern Mexico under irrigated, drought and heat-irrigated treatments from 2011 to 2013. The trial network comprised 15 trials and both physiological and agronomic traits were scored. First, an environmental characterization methodology was developed and resulted in the identification of six main environmental scenarios in the network. A representative environmental covariate was extracted from each of them. Then, a factorial regression model leaded to the dissection of the genotype-by-environment interaction and highlighted differential stress sensitivity of the germplasm. Finally, a multi-environmental QTL detection resulted in the discovery of genomic regions involved in the control of both physiological and agronomic traits and the study of their sensitivity to the environment. From the environmental characterization to the QTL detection, this study resulted in the development of a tool for breeders which may enable the evaluation of the potential of any genotypes in front of a range of environment, but also the identification of genomic regions involved in the control of the tolerance to drought and heat stress in bread wheat. This may help in improving the tolerance of the European bread wheat germplasm to drought and heat stress.

<p>Breeding for improved animal welfare is paramount for increasing the long-term sustainability of the animal food industry. In this context, the main objectives of this dissertation were to understand the genetic and genomic background of welfare indicators in livestock and evaluate the feasibility of single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) for performing genomic selection in beef cattle. This dissertation includes five studies. First, we aimed to test and identify an optimal ssGBLUP scenario for crossbreeding schemes. We simulated multiple populations differing based on the genetic background of the trait, and then we tested alternative models, such as multiple-trait weighted ssGBLUP. Even though more elaborated scenarios were evaluated, a single-trait ssGBLUP approach was recommended when genetic correlation across populations were higher than 0.70. The goal of the second study was to identify genomic regions controlling behavior traits that are conserved across livestock species. We systematically reviewed genomic regions associated with behavioral indicators in beef and dairy cattle, pigs, and sheep. The genomic regions identified in this study were located in genes previously reported controlling human behavioral, neural, and mental disorders. In the third study we used a large dataset (675,678 records) from North American Angus cattle to investigate the genetic background of temperament, a behavioral indicator, recorded on one-year-old calves, and provide the models and protocols for implementing genomic selection. We reported a heritability estimate equal to 0.38 for yearling temperament, and it was, in general, genetically favorably correlated with other productivity and fertility traits. Candidate genomic regions controlling yearling temperament were also identified. The fourth study was based on temperament recorded on North American Angus cows from 2 to 15 years of age (797,187 records). The goal was to understand the genetic and genomic background of temperament across the animal’s lifetime. By fitting a random regression model, we observed that temperament is highly genetically correlated across time. However, animals have differential learning and behavioral plasticity (LBP; changes of the phenotype overtime), although the LBP heritability is low. In our last study we evaluated foot scores (foot angle, FA; and claw set, CS) in American (US) and Australian (AU) Angus cattle aiming to assess the genetic and genomic background of foot scores and investigate the feasibility of performing an across-country genomic evaluation (~1.15 million animals genotyped). Foot scores are heritable (heritability from 0.22 to 0.27), and genotype-by-environment interaction was observed between US and AU Angus populations (genetic correlation equal to 0.61 for FA and 0.76 for CS). An across-country genomic prediction outperformed within-country evaluations in terms of predictivity ability (bias, dispersion, and validation accuracy) and theoretical accuracies. We have also identified genes associated with FA and CS previously reported in human’s bone structure and repair mechanism. In conclusion, this dissertation presents a comprehensive genetic and genomic characterization of welfare indicators (temperament and foot scores) in (inter)national livestock populations. </p>