Review: The genetic architecture of host-microbiota interactions in livestock: a comprehensive review and critical appraisal

• Host genetics influence the composition and diversity of livestock microbiota. • Genetic associations link microbiota composition to livestock main traits. • Integrating microbiota data may improve breeding prediction and selection. • Amplicon sequencing prevails, but whole-metagenome enables functional insight. • Microbiota data challenges limit reproducibility; meta-analyses enhance robustness. This article reviews host genetics and microbiota interactions in livestock species, emphasizing the key role of microbial communities—especially gut microbiota—in animal health, growth and feed efficiency. The concept of the holobiont, where the host and its microbiota form a single biological unit, is gaining traction in animal breeding. Thanks to advancements in sequencing technologies and bioinformatics analyses, detailed profiling of microbial composition is now available for large groups of animals (one to several hundred). Comparisons between breeds raised under similar conditions, or between lines experimentally selected for specific traits, reveal marked differences in microbial composition. These findings support the idea that the microbiota composition could be partly under genetic control. Recent studies conducted on livestock species have reported high heritability estimates of certain microbial taxa, but the vast majority of taxa did not differ from zero. Moreover, some significant genetic correlations exist between microbial taxa and traits like feed efficiency, methane emissions, and health indicator. Genome wide association studies have identified loci linked to both microbial and economically important traits, suggesting shared genetic control. After demonstrating that it was possible to directly select specific microbial taxa to modify a trait, the integration of microbiota data into genetic prediction models improved the accuracy of traits, particularly those related to digestion and methane emissions across species. Following this review of knowledges regarding genetic and microbiota, the authors discuss the opportunities, challenges and current limitations of using microbiota information in livestock breeding.