Mastitis is a serious burden for the milk industry due to the altered quality of milk and increased cost for production. Beside hygienic measures, genetic selection for improved immunity against mammary infections and resistance to mastitis is considered, and implemented in breeding programs of several dairy breeds worldwide. However, resistance to mastitis is a highly complex trait which genetically-determined biological basis is mostly unknown. Based on a genome-wide association study for a mastitis trait, the milk somatic cell count (SCC) in dairy sheep, we identified a point mutation in the SH2 binding domain of SOCS-2, leading to the loss of ligand recognition. The frequency of this mutation was surprisingly high (22%) in the studied population. Additionally, size, weight and milk production were significantly increased in ewes carrying the mutated socs2 allele when compared to wild type sheep. Altogether these results gave strong evidence for a causal mutation controlling mastitis in sheep and highlighted the major role of SOCS-2 as a potential tradeoff factor between host’s inflammatory response to mammary infections, and milk production. The purpose of the REIDSOCS project is to study the role of SOCS-2 in the predisposition to bacterial infections, and explore its pleiotropic effect on both health and production traits. Indeed, SOCS-2 belongs to a protein family that regulates the JAK/STAT signaling pathways originating from several cytokine and hormone receptors. Regulatory mechanisms of inflammatory responses and their impact on the issue of infectious diseases are still not completely resolved. Investigations will be performed at the levels of the sheep population, animal and cells. - At the population levels, a precise description of the allele frequencies and their evolution will be conducted. The genetic association of the Socs2 genotype with various production traits will be investigated in order to hypothesize on the history of the mutation. An insightful strategy for the management of the mutation in the sheep breeding scheme is proposed as a deliverable. More generally, the project will provide means on how to manage known causal mutations with pleiotropic effects on production versus functional traits in bred livestock. - At the animal and systems levels, the role of the point mutation, independently of the genetic background, will be investigated in sheep after genome edition. The objective is to introduce the SOCS-2 mutation in a mastitis-resistant genetic background and to definitively prove the predisposition to bacterial infections. - Furthermore, after non-meiotic introgression of the mutation into the murine genome, the mechanisms associated with impaired SOCS-2 functions will be determined using in vitro and in vivo experiments. These studies also aim at determining the repertoire of genes and pathways leading to abnormal cell functions in various cell types and consequently, to an increased predisposition to bacterial infections. By this way, we will define the SOCS-2-related interactome by identifying the proteins and associated signaling pathways leading to milk production and altered immunity to bacterial infections. This information will be used in return to look for other altered expression or mutations in the repertoire of factors that are protective against mammary infections. Altogether, the project will open up new avenues for the genetic improvement of animal health, but also provide new knowledge on the mechanisms of immune and inflammatory regulation.

European cattle farmers are facing increased demand for pasture-based and environmentally friendly products. Although feeding strategies to reduce Greenhouse Gas (GHG) emissions have been studied intensively, strategies for grazing systems are under-researched. The lack of easy-to-implement technologies for methane measurement with grazing cattle complicates the necessary large-scale studies. GrASTech will develop an animal-mounted sensor platform for methane measurement in grazing cattle and validate using established techniques (Respiration chambers, LaserGun and Greenfeed). Additionally, herd productivity, which has a major impact on GHG emission intensity (per kg product), will be improved using a wide range of precision livestock farming technologies. All strategies will be evaluated using life cycle assessment in order to find net positive effects. GrASTech will provide important advances towards achieving the challenging goals of the climate action plan.

Animal-Future will design strategies for assessing and enhancing the sustainability of animal production systems (APS). Main objectives are (i) Assess the multi-dimensional consequences of innovations on benefits (cash flow, income, jobs, product quality and safety, ecosystem services etc.) and costs (use of scarce natural resources, health and welfare) of APS. (ii) Improve the capacity of European animal sector actors to facilitate sound changes based on a thorough understanding of mechanisms underlying trade-offs between benefits and costs. (iii) Provide guidance co-designed by scientists and animal production actors through which the latter can reinforce their innovation capacity. To achieve these, the project will (i) Develop a indicator-based decision support tool that will be used for assessing and benchmarking European APS according to benefits and costs induced by innovations (from farm to region, nation and EU27). (ii) Bring together multi-disciplinary research teams and animal production actors (farmers, processors, breeders etc.) using a multi-actor approach and starting from a farm network of intensive/extensive APS across Europe. Relevance to research area includes (RA1) Developing and assessing innovations that move farm management closer to the production frontier, while considering fundamental trade-offs with respect to social and environmental dimensions. (RA2) Insights into how animal production sector (from the farm to EU scale) can increase the efficiency of feed utilization, recycle waste and exploit potentials to convert biomass resources not directly edible for humans into high-quality protein sources for human nutrition. (RA3) Transparent and comprehensive accounting for on-farm practices that makes explicit a whole set of benefits and costs, at farm and larger spatial scales, thus raising the awareness of animal sector actors, citizens and policy makers about the often-neglected benefits that animal systems provide to society.

The livestock sector is highly concerned by the global food system, both by an expected increase in the demand for animal products such as milk, and by the ecological footprint of animal production, which must be minimized. Increasing feed efficiency (FE) in dairy cows would reduce some of the direct emissions (methane and ammonia) from livestock production but would also have a substantial positive impact on the induced emissions associated with crop production, due to the better feed conversion. Genetic improvement of FE is a particularly attractive strategy because it would impact most of the dairy farms for a limited cost. The decreased use of feed inputs implied by such an efficiency gain would give a competitive advantage to dairy production, but will also contribute to reducing environmental impacts. Thus, this project is expected to provide the essential elements needed for genetic selection strategies to improve FE in dairy cows. It fits with the fifth of the major societal challenges of ANR and the first research theme of the APIS-GENE consortium on FE and limitation of N pollution and methane emission by ruminants to improve the overall efficiency of ruminants. Selecting for FE is not as straight forwards as it might first seem, there is evidence to suggest that robustness and adaptive capacity, especially for reproductive females, can be adversely affected by short-sighted strategies to improve efficiency. Thus, the choice of indicators used to assess FE is of great important, and it is essential to verify and validate the anticipated benefits of any such strategies to improve efficiency for their long-term consequences. Another key issue is to be able to better exploit new possibilities to target specific characteristics that contribute in part to FE. Such characters have rarely been studied because they have been very difficult to phenotype. The project will use new phenotyping technologies and the newly available information from them to develop selection for efficient use of body reserves whilst limiting the risks of undesirable trade-offs with other life functions that have been associated with high levels of production in dairy cows. DeffiLait aims to elucidate ways by which to improve the FE of dairy cows without decreasing their robustness, to build strategies for doing this, and models to predict the future increases in FE attainable by selection programs, and directly on farm. The project will first involve developing new tools for large-scale phenotyping of the major biological characteristics that are directly involved in FE. The project will produce new tools to better estimate body condition, morphology, and digestive efficiency in large scale studies. These phenotypic measures will also impact on our capabilities for on-farm advising, and monitoring in livestock, which are also levers for improving efficiency at farm level. Then, to study the major determinants of FE, the project will also build an original database of dairy cow lactations with a large set of phenotypes to describe the main sources of energy transformation, thus explaining the observed between-animal variability in FE. This dataset will then be used to quantify the contribution of the different mechanisms to the variability in FE, and to test different indicators and strategies to improve FE. A specific focus will be made on body reserves mobilization in early lactation to assess its genetic components and correlation with other traits with a larger dataset involving commercial farms. The project will then develop simulation tools to predict the short- and long-term consequences of different selection strategies in different environments. The expected results will contribute to the definition of strategies of selection to combine efficiency and robustness. The project will provide a coherent framework to undertake a balanced genetic selection on these traits, and thereby make a significant - and lasting – contribution to improving FE.

Due to a growing world population and changing consumption patterns, demand for animal products is expected to increase. Ruminant-based systems have the potential advantage of using resources non edible by humans and converting these into high quality human food. However, the emergence of intensive ruminant production systems, relying on increasing use of concentrate feeds, with food value, and the related increase in land abandonment in traditional grassland regions, has increased scrutiny in respect of the sustainability of EU livestock productions. Moreover the consumers’ point of view, the social acceptability of cattle products is being questioned with regards to food quality and safety, animal welfare and the competition between feed and food. To face these drawbacks, we hypothesize that cattle farming systems which rely mainly on grasslands and agro-industrial resources non-edible by humans are more or can be designed to be more sustainable than specialized systems which use feedstuffs that could also be directly used as food or that was produced at the detriment of food production. In addition such systems would greatly contribute to circular economy. Our measure of sustainability includes, environmental and social dimensions as well as economic perspectives taking into account the services delivered by these systems. Our proposal focuses on beef production systems as they are increasingly questioned by society. To test this, actual and potential performances of systems representative of Europe will be compared, mobilizing multidisciplinary and multi-actors approaches to co-define 1-beef system types, 2-the set of sustainability indicators to be mobilized, 3-potential scenarios of evolution for more sustainable systems. These scenarios will be evaluated and, furthermore, suitable incentive measures to enhance their implementation will be tested and, when relevant, proposed. The dissemination of results will be facilitated throughout this bottom-up approach.