| dc.description.abstract | The genetic improvement of feed efficiency is imperative to augment profits and promote sustainable production in aquaculture. The essential role that the gut microbiome plays in digestion and nutrient metabolism implies its significant involvement in the efficient utilization of feed. However, the influence of gut microbiota, and its potential interaction with host genetics, on feed efficiency has not yet been investigated in any aquaculture species. In this study, a hologenomic approach using a series of linear mixed animal models was applied to determine the effects of host genetics and gut microbiota on growth and individual indicator traits for feed conversion ratio (IFCR) and feed efficiency ratio (IFER) based on muscle 13C (AMC) and 15N (AMN) isotope profiles in Atlantic salmon. Using a total of 690 samples, the host genetics was found to affect relative weight gain (RG) and feed efficiency indicator traits explaining 6-26% of the variations for the said traits. The gut microbiota also explained 14% and 32% of variations in RG and AMN-based feed efficiency indicator traits, respectively. On the other hand, the microbes in the gut exhibited zero microbiability on AMC-based indicator traits for feed efficiency. Comparison of heritability and microbiability using full (including both microbial and animal genetic effects) and reduced (including either microbial or animal genetic effects) models revealed almost no change in the estimates indicating independent effects of host genetics and gut microbiome on growth and feed efficiency. Results of microbiome-wide association analyses revealed that Jeotgalibaca were linked to AMN-based feed efficiency implying the potential use of the bacteria for microbiome-assisted improvement of feed efficiency. Among the identified microbes, Lactobacillus was the only bacteria discovered to be heritable. The present study confirmed the combined effects of gut microbiome and host genetics on growth and feed efficiency in Atlantic salmon. However, their influence on the analyzed traits were independent of each other thus a separate management should be implemented. Finally, the research strengthened the importance of adopting a hologenomic framework in analyzing complex traits that are highly relevant for aquaculture production. | |
