Search

Feed efficiency depends on the genetic potential of animals, the characteristics of feed and their interactions. Due to technical constraints, genetic selection and nutritional studies requiring the evaluation of feed efficiency and behavior are carried out under conditions that are not representative of the breeding conditions, on animals placed in individual cages or in small groups. Significant progress can be expected in these two areas thanks to new technologies, allowing the automation of individual body weight measurements and feed consumption of poultry bred in groups on the ground. On the basis of a prototype feeder developed and patented by INRAE, this project has made it possible to develop a functional and reliable tool that can be used in research and development, by associating an automatic animal scale and a high-speed data management system with the feeder. This pre-industrial prototype is now available for the performance of precision experiments in genetics and nutrition, while respecting animal welfare.; L’efficacité alimentaire dépend à la fois du potentiel génétique des animaux, des caractéristiques de l’aliment et de leurs interactions. Du fait de contraintes techniques, la sélection génétique et les études nutritionnelles nécessitant l’évaluation de l’efficacité et du comportement alimentaire sont réalisées dans des conditions non-représentatives des conditions d’élevage, sur des animaux placés en cages individuelles ou en petits groupes. Des progrès importants peuvent être escomptés dans ces deux domaines grâce aux nouvelles technologies, permettant l’automatisation des mesures individuelles de poids corporel et de la consommation alimentaire de volailles élevées en groupe au sol. Sur la base d’un prototype de mangeoire développé et breveté par INRAE, ce projet a permis de mettre au point un outil fonctionnel et fiable, utilisable en recherche et développement, en associant à la mangeoire un peson automatique d’animaux et un système de gestion de données à haut débit. Ce prototype préindustriel est dorénavant disponible pour la réalisation d’expérimentations de précision en génétique et en nutrition, dans le respect du bien-être animal.

International audience; The autonomy for Protein-Rich resources of poultry feed in France is around 40%, due in particular to massive imports of soybean meals, which are economically and nutritionally competitive. The study ofnew French Protein-Rich Feedstuffs (FPRF) within the framework of VOCALIM has shown that technological processes make it possible to better exploit fiber-rich resources (rapeseed and sunflower meals), without affecting the performance or health of the animals. The genetic selection of animals could be a lever to further improve the valuation of these resources. Simulations up to 2023 showed a gain of 17 protein autonomy points in broilers production and a reduction in food costs of 2.8% thanks to these FPRF. Their use allows, according to the scenarios studied, to gain in protein efficiency and to reduce overall environmental impacts.; L’autonomie protéique de l’alimentation des volailles est en France d’environ 40%, en raison notamment d’importations massives de tourteau de soja, très concurrentiel sur le plan économique et nutritionnel. L’étude de nouvelles Matières Premières Riches en Protéines françaises (MPRP) dans le cadre du projet VOCALIM a permis de montrer que des procédés technologiques permettent de mieux valoriser des ressources riches en fibres (tourteaux de colza et tournesol), sans altérer les performances ou la santé des animaux. La sélection génétique des animaux pourrait être un levier pour encore améliorer la valorisation de ces ressources. Des simulations à l’horizon 2023 montrent un gain de 17 points d’autonomie protéique dans la filière poulet de chair et une réduction du coût alimentaire de 2,8% grâce à ces MPRP. Leur utilisation permet, selon les scénarios étudiés, de gagner en efficience protéique et de réduire globalement tous les impacts environnementaux.

Until now, individual measurements of feed efficiency and feeding behavior have been performed on animals raised alone and in cages, but it has several drawbacks, in particular the absence of social interactions and the limitation of movements, which leads to an experimental bias, as conditions are not representative of farming conditions. The electronic feeder BIRD-e (Bird Individual Ration Dispenser-electronic) developed by INRAE and ITAVI allows to overcome these constraints with automatic recording of individual measurements of feed consumption and poultry weight raised on the ground and in groups. BIRD-e has eight feed access points, each equipped with two scales (one for feed, one for birds) and a detection antenna. Each chick is fitted with an electronic identification chip so that each visit to the feeder is recorded. Each station can record data from 100 to 120 animals raised on the ground, without human intervention and without penalizing their growth. Therefore, individualized measurements of weight and feed consumption are obtained continuously. It is also possible to collect information on feeding behavior: time spent to eat, time between two meals, etc. The expected benefits of this technology are at first progress in genetic selection, by integrating criteria of feeding behavior and by being more efficient on feed efficiency. On the nutritional aspect, this innovative tool allows to study the impacts of feed composition and technology on the feeding behavior of birds and their performance. This device is already used in research programs and could be used for partnership research within a year.

National audience

National audience; Chicken meat quality defects are mainly detected on breast muscles. They are frequently associated with heavy chicken strains selected for high growth rate and breast meat yield and often used for cutting and further processing. These defects show similarities with changes observed in some myopathy forms. The following conditions are described: the white striping that corresponds to the inclusion of lipid deposition and connective tissue between the muscle fibres; the wooden breast that affects more or less wide zones of fillets becoming very hard, pale and sometimes covered with a clear and viscous liquid; the “spaghetti fillets” whose muscle fibres are completely deconstructed and break up; the “Oregon disease” that occurs on Pectoralis minor muscle and results in a greenish colour. The aim of this review was to present the current knowledge on the origin of these defects and the strategies to limit them.; Les défauts de qualité de la viande de poulet s'observent essentiellement sur les filets, au stade de la découpe. Ils sont fréquemment associés aux souches lourdes à fort rendement musculaire qui sont très utilisées pour la découpe et la transformation. Ces défauts présentent des similitudes avec des altérations observées dans certaines myopathies. Les phénomènes suivants sont décrits : le «white striping» qui se présente sous la forme de stries blanches sur les filets ; le «wooden breast» qui touche des zones plus ou moins larges des filets, devenant dures, pâles et parfois recouvertes d'un liquide clair et visqueux ; le filet «spaghetti» dont les fibres musculaires sont déstructurées et se dissocient les unes des autres ; l’«Oregon disease» qui apparaît au niveau des aiguillettes et qui prennent une couleur verte. Cette revue a pour objectif de faire le point sur les connaissances actuelles concernant l'origine de ces défauts et les stratégies pour les limiter

International audience; Milk somatic cell count (SCC) is commonly higher in goats than in cattle and sheep. Furthermore, the ability of milk SCC to predict mastitis is considered lower in goats than in cattle and sheep, and the relevance of somatic cell score (SCS)-based selection in this species has been questioned. To address this issue, we created 2 divergent lines of Alpine goats using artificially inseminated bucks with extreme estimated breeding values for SCS. A total of 287 goats, 158 in high- and 129 in low-SCS lines, were scrutinized for mastitis infections. We subjected 2,688 milk samples to conventional bacteriological analyses on agarose and bacterial counts were estimated for positive samples. The SCS, milk yield, fat content, and protein content were recorded every 3 wk. Clinical mastitis was systematically noted. A subset of 40 goats (20 from each line) was subsequently challenged with Haemonchus contortus and monitored for anemia (blood packed cell volume) and fecal egg counts to see if SCS-based selection had an indirect effect on resistance to gastrointestinal nematodes. Milk production traits, including milk quantity, fat content, and protein content, were similar in both goat lines. In contrast, the raw milk SCC almost doubled between the lines, with 1,542,000 versus 855,000 cells/mL in the high- and low-SCS lines, respectively. The difference in breeding value for SCS between lines was 1.65 genetic standard deviation equivalents. The Staphylococcus spp. most frequently isolated from milk were S. xylosus, S. caprae, S. epidermidis, and S. aureus. The frequency of positive bacteriology samples was significantly higher in the high-SCS line (49%) than in the low-SCS line (33%). The highest odds ratio was 3.49 (95% confidence interval: 11.95-6.25) for S. aureus. The distribution of bacterial species in positive samples between lines was comparable. The average quantity of bacteria in positive samples was also significantly higher in high-SCS goats (69 ± 80 growing colonies) than in low-SCS goats (38 ± 62 growing colonies). Clinical cases were rare and equally distributed between high- (n = 4; 2.5%) and low-SCS (n = 3; 2.3%) lines. Furthermore, the larger the amounts of bacteria in milk the higher the SCS level. Conversely, goats with repeatedly culture-negative udders exhibited the lowest SCC levels, with an average of below 300,000 cells/mL. We therefore confirmed that SCS is a relevant predictor of intramammary infection and hygienic quality of milk in goats and can be used for prophylactic purposes. After challenge with H. contortus, goats were anemic with high fecal egg counts but we found no difference between the genetic lines. This result provides initial evidence that resistance to mastitis or to gastrointestinal nematodes infections is under independent genetic regulation. Altogether, this monitoring of the goat lines indicated that SCS-based selection helps to improve udder health by decreasing milk cell counts and reducing the incidence of infection and related bacterial shedding in milk. Selection for low SCC should not affect a goat's ability to cope with gastrointestinal nematodes.

Milk somatic cell count (SCC) is commonly higher in goats than in cattle and sheep. Furthermore, the ability of milk SCC to predict mastitis is considered lower in goats than in cattle and sheep, and the relevance of somatic cell score (SCS)-based selection in this species has been questioned. To address this issue, we created 2 divergent lines of Alpine goats using artificially inseminated bucks with extreme estimated breeding values for SCS. A total of 287 goats, 158 in high- and 129 in low-SCS lines, were scrutinized for mastitis infections. We subjected 2,688 milk samples to conventional bacteriological analyses on agarose and bacterial counts were estimated for positive samples. The SCS, milk yield, fat content, and protein content were recorded every 3 wk. Clinical mastitis was systematically noted. A subset of 40 goats (20 from each line) was subsequently challenged with Haemonchus contortus and monitored for anemia (blood packed cell volume) and fecal egg counts to see if SCS-based selection had an indirect effect on resistance to gastrointestinal nematodes. Milk production traits, including milk quantity, fat content, and protein content, were similar in both goat lines. In contrast, the raw milk SCC almost doubled between the lines, with 1,542,000 versus 855,000 cells/mL in the high- and low-SCS lines, respectively. The difference in breeding value for SCS between lines was 1.65 genetic standard deviation equivalents. The Staphylococcus spp. most frequently isolated from milk were S. xylosus, S. caprae, S. epidermidis, and S. aureus. The frequency of positive bacteriology samples was significantly higher in the high-SCS line (49%) than in the low-SCS line (33%). The highest odds ratio was 3.49 (95% confidence interval: 11.95-6.25) for S. aureus. The distribution of bacterial species in positive samples between lines was comparable. The average quantity of bacteria in positive samples was also significantly higher in high-SCS goats (69 ± 80 growing colonies) than in low-SCS goats (38 ± 62 growing colonies). Clinical cases were rare and equally distributed between high- (n = 4; 2.5%) and low-SCS (n = 3; 2.3%) lines. Furthermore, the larger the amounts of bacteria in milk the higher the SCS level. Conversely, goats with repeatedly culture-negative udders exhibited the lowest SCC levels, with an average of below 300,000 cells/mL. We therefore confirmed that SCS is a relevant predictor of intramammary infection and hygienic quality of milk in goats and can be used for prophylactic purposes. After challenge with H. contortus, goats were anemic with high fecal egg counts but we found no difference between the genetic lines. This result provides initial evidence that resistance to mastitis or to gastrointestinal nematodes infections is under independent genetic regulation. Altogether, this monitoring of the goat lines indicated that SCS-based selection helps to improve udder health by decreasing milk cell counts and reducing the incidence of infection and related bacterial shedding in milk. Selection for low SCC should not affect a goat's ability to cope with gastrointestinal nematodes.

Poultry industry is facing muscular defects that impair chicken meat quality. Genetic and genomic studies were carried out in addition to histological measurements to better understand the etiology of these defects and to contribute to the development of new indicators useful for diagnosis and selection. Studies focused on two complementary genetic models: (i) two divergent chicken lines selected on breast meat ultimate pH and (ii) a line with strong muscular development more severely affected by the defects, which was studied in comparison with a slow-growing strain free from lesions. The thesis helped to describe the metabolic and structural changes induced by long-term selection on growth and breast muscle yield as well as the biological deregulations observed in case of severe myopathies. It also led to the identification of the first QTL regions controlling muscular defects in chicken and to the establishment of a set of genes correlated with histological measurements of myopathies that will serve after validation as tool for selection and breeding., La filière avicole est confrontée à des défauts musculaires qui impactent la qualité de la viande de poulet. Des analyses génétiques et génomiques ont été menées en complément de mesures histologiques afin de mieux comprendre l’étiologie de ces défauts et contribuer au développement de nouveaux indicateurs et biomarqueurs utiles au diagnostic et à la sélection. L’étude a porté sur deux modèles génétiques complémentaires : (1) deux lignées divergentes de poulets sélectionnées sur le pH ultime du filet, et (2) une lignée à fort développement musculaire plus sévèrement affectée comparée avec une souche à croissance lente indemne de lésions. La thèse a permis de décrire les modifications métaboliques et structurales induites par la sélection à long terme sur la croissance et le rendement en filet ainsi que les dérégulations biologiques observées en cas de myopathies sévères. Elle a aussi conduit à l’identification des premières régions QTL contrôlant les défauts chez le poulet et à l’établissement d’un set de marqueurs géniques corrélés aux mesures histologiques des myopathies, qui une fois validé, servira d’outil d’aide à la sélection et à l’élevage.

Ce volume regroupe les textes issus du programme Casdar "Innovation et Partenariat" et "Recherche finalisée et innovation" de 2013. Le colloque de restitution s’est déroulé le 6 février 2019 sous l’égide du GIS Relance Agronomique; National audience; Even though meat is increasingly consumed in elaborated form, consumers are sensitive to naturality of the products. This trend is largely taken into account by agribusiness company seeking to reduce additives (flavor enhancers or texturizing agents) or preservatives (in particular salt). This shows the importance of upstream control of quality of the raw material for elaborated products. This issue particularly affects chicken meat, mostly consumed in cut or processed but whose technological quality is highly variable. The objective of the CASDAR OPTIVIANDE project was to develop new phenotyping tools and biological or genetic markers that could be used for selection or evaluation of the impact of breeding factors. The approaches implemented concerned the use of near-infrared spectrometry (NIRS) as well as high-throughput biological and genomic analyzes. The study was based on an original animal model composed of two chicken lines selected in a divergent manner on the ultimate pH of the filet and whose technological and sensory characteristics of meat were very different. Near-infrared spectrometry is fast to implement and makes it possible to predict several technological quality criteria such as ultimate pH, water loss during storage and hardness after cooking. Transcriptomic and metabolomics analyzes made it possible to develop first prediction models based on a limited number of metabolites (blood and muscle) or muscle transcripts. At the genetic level, analyzes made possible to identify the main regions controlling the ultimate pH of the filet and revealed several genes of interest. In conclusion, the project led to significant advances in understanding the genetic and physiological mechanisms involved in the establishment of quality defects in chicken. It opens perspectives of application thanks to the development of prediction tools for selection whose genericity will have to be validated on other populations and in conditions of production

Even though meat is increasingly consumed in elaborated form, consumers are sensitive to naturality of the products. This trend is largely taken into account by agribusiness company seeking to reduce additives (flavor enhancers or texturizing agents) or preservatives (in particular salt). This shows the importance of upstream control of quality of the raw material for elaborated products. This issue particularly affects chicken meat, mostly consumed in cut or processed but whose technological quality is highly variable. The objective of the CASDAR OPTIVIANDE project was to develop new phenotyping tools and biological or genetic markers that could be used for selection or evaluation of the impact of breeding factors. The approaches implemented concerned the use of near-infrared spectrometry (NIRS) as well as high-throughput biological and genomic analyzes. The study was based on an original animal model composed of two chicken lines selected in a divergent manner on the ultimate pH of the filet and whose technological and sensory characteristics of meat were very different. Near-infrared spectrometry is fast to implement and makes it possible to predict several technological quality criteria such as ultimate pH, water loss during storage and hardness after cooking. Transcriptomic and metabolomics analyzes made it possible to develop first prediction models based on a limited number of metabolites (blood and muscle) or muscle transcripts. At the genetic level, analyzes made possible to identify the main regions controlling the ultimate pH of the filet and revealed several genes of interest. In conclusion, the project led to significant advances in understanding the genetic and physiological mechanisms involved in the establishment of quality defects in chicken. It opens perspectives of application thanks to the development of prediction tools for selection whose genericity will have to be validated on other populations and in conditions of production

Figure S2. Gene environment of the region of interest for WS on GGA1. The first track corresponds to the chromosome 1 where the region of interest is indicated by a red line. The second track corresponds to the genomic axis for the region of interest. The third track corresponds to the gene model based on GalGal5 assembly. The last track corresponds to the Manhattan plot of the region of interest where the orange line represents the chromosome threshold and the most significant SNP for WS is highlighted in red. (PDF 8 kb)

Figure S3. Gene environment of the region of interest for WS and BMY on GGA4. The first track corresponds to the chromosome 4 where the region of interest is indicated by a red box. The second track corresponds to the genomic axis for the region of interest. The third track corresponds to the gene model based on GalGal5 assembly. The two last tracks correspond to the Manhattan plot of BMY and WS respectively, on the region of interest, where the orange line represents the chromosome threshold and the most significant SNP for WS and BMY is highlighted in red. (PDF 10 kb)

Table S1. Significant SNPs for the level of expression of the 16 candidate genes. (DOCX 36 kb)

Figure S7. Gene environment of the pleiotropic region on GGA4. The first track corresponds to the chromosome 4 where the region of interest is indicated by a red box. The second track corresponds to the genomic axis for the region of interest. The third track corresponds to the gene model based on GalGal5 assembly. The last track corresponds to the Manhattan plot of CL, which has the most significant SNP in the pleiotropic region. Orange line represents the chromosome threshold and the most significant SNP is highlighted in red. (PDF 9 kb)

Figure S8. Manhattan plot showing the association of SNPs with MYH1F expression. Black line represents the 5% genome-wide threshold and blue line the 5% GGA18-wide threshold. (DOCX 560 kb)

Figure S9. Manhattan plot showing the association of SNPs with CAV3 expression. Black line represents the 5% genome-wide threshold and green line the 5% GGA12-wide threshold. (DOCX 585 kb)

Figure S6. Gene environment of the region of interest for WS on GGA18. The first track corresponds to the chromosome 18 where the region of interest is indicated by a red box. The second track corresponds to the genomic axis for the region of interest. The third track corresponds to the gene model based on GalGal5 assembly. The last track corresponds to the Manhattan plot of the region of interest where the orange line represents the chromosome threshold and the most significant SNP is highlighted in red. (PDF 10 kb)

Figure S5. Gene environment of the region of interest for WS on GGA17. The first track corresponds to the chromosome 17 where the region of interest is indicated by a red box. The second track corresponds to the genomic axis for the region of interest. The third track corresponds to the gene model based on GalGal5 assembly. The last track corresponds to the Manhattan plot of the region of interest where the orange line represents the chromosome threshold and the most significant SNP is highlighted in red. (PDF 9 kb)

Figure S4. Gene environment of the region of interest for WS on GGA7. The first track corresponds to the chromosome 7 where the region of interest is indicated by a red box. The second track corresponds to the genomic axis for the region of interest. The third track corresponds to the gene model based on GalGal5 assembly. The last track corresponds to the Manhattan plot of the region of interest where the orange line represents the chromosome threshold and the most significant SNP is highlighted in red. (PDF 8 kb)