Amoebic gill disease (AGD), caused by Neoparamoeba perurans, is one of the major threats to gill health of marine salmonids and hence of major importance in salmon aquaculture. AGD prevention and treatment options are scant, therefore other options such as selective breeding or genetic engineering to increase resilience of Atlantic salmon stock to AGD may present an alternative prevention strategy. A number of studies have addressed AGD resistance in Atlantic salmon using transcriptomic and quantitative genetic approaches. However, another, often overlooked layer can be added to the narrative – namely that of the gill microbiota.
Here we utilised a combined approach of metabarcoding and quantitative genetics to address AGD resistance, by considering the microbiota as an extended resistance phenotype of the salmon. We characterised the gill microbiota of Atlantic salmon subject to an AGD disease challenge, and investigated microbiota composition in relation to common AGD phenotype scoring methods (gill score and amoebic load). We then applied a GWAS approach to investigate SNPs associated with the microbiota and the AGD phenotypic scoring methods.
We found that the overall microbiota composition of gill samples was relatively simple as over 60% of the overall relative abundance of microbial taxa was attributable to two families namely, Simkaniaceae and Arcobacteraceae . Notably, bacteria of the family Simkaniaceae are known to cause epitheliocystis and respiratory distress in Atlantic salmon and may be endosymbionts of the disease causing amoeba. Furthermore, we found significant differences in weighted alpha diversity estimates among samples grouped by amoebic load and significant difference in beta diversity among samples grouped by severity of gill damage. No genome-wide significant QTLs were identified, however four suggestive QTLs were found in relation to gill score, microbiota diversity, and relative abundance of individual bacterial families.
This study highlights the utility of integrating metagenomic and genomic approaches to address the interplay between host genetics, microbiota and disease resistance.