Animals and their microbiota form a composite organism, called a holobiont, which can be considered the ultimate unit on which evolution and selection act. Host genes and the environment influence the colonization, development, and function of the various microbiota, which in turn help shape the host's phenotypes. The phenotypes of the holobiont thus result from the combined action of the host genes and those of its microbiota, and their determinism can be explored by implementing hologenetic approaches capable of considering host genomes and metagenomes jointly. In agro-ecological livestock systems aiming to reduce environmental footprints (greenhouse gas emissions, water and energy supply, etc.), animals must also cope with changing and complex environments (climate change, diverse non-competitive nutritional resources, less controlled and less protective environment against pathogens, etc.). In this context, it is important, to determine the part of host/microbiota components in the variability of the determinism of phenotypes relevant in an agroecological perspective and to understand how host genetics control the symbiotic microbiota.
The overall objective is to develop integrative hologenetic approaches for animal breeding, using state-of-the-art technologies to generate, process and analyze genetic and genomic datasets of the host and its microbiota as well as the phenotypes and environmental parameters in which the holobionts evolve. To this end, the project aims to develop methods for the analysis of new-generation phenotyping data of the holobiont (mainly high-throughput and continuous), for their modeling and for the analysis of their interrelationships with the microbiota data (WP1). Based on these developments, the aim will be to optimize joint modeling methods of host allelic variability, metagenomic indicators and their interaction in order to better understand the genetic determinism of traits involved in the adaptation of animals to agro-ecological production systems and to improve the accuracy of selection in the various species of interest (WP2). This project includes the production of large reference populations with automated and high throughput generation of new generation phenotypes, microbiota data and high throughput genotyping, in poorly controlled and fluctuating environments and at different physiological stages (WP3). The generation and analysis of multi-omics data at the level of the host and its microbiota will allow to understand the mechanisms that link the microbiota to its host in order to identify the key actors of the dialogue allowing the establishment and the persistence of symbiotic interactions (WP4). These omics data that best describe the functional characteristics of the holobiont will be explored in order to implement predictive models capable of predicting the functional characteristics of the metagenomes in 16S/18S/ITS datasets. These results will help to refine the selection objectives. Finally, all the methods implemented in WP 1&2 will be applied to the datasets generated in WP 3&4 to define diversity management approaches at the holobiont population level for sustainable agriculture systems.

Code: 22-PEAE-0006