Genome-wide target enriched viral sequencing reveals extensive ‘hidden’ salmonid alphavirus diversity in farmed and wild fish populations

Abstract

Aquaculture plays a crucial role in global food and economic security, though its expansion and sustainability remain under threat from infectious diseases. Salmonid alphavirus (SAV, Togaviridae), the causative agent of pancreas disease and sleeping disease, is responsible for large negative impacts in salmonid aquaculture. Few studies have characterized this virus at a genome-wide level, and the extent of intrahost SAV genetic diversity remains largely unexplored. Pooling tissues from multiple infected animals is a standard method of sampling for molecular diagnostics of pathogens in aquaculture; however the impacts of pooling on detection of viral diversity remain poorly understood. Here we applied a sequence capture strategy to obtain SAV genomes at high coverage from infected fish using both pooled and individual samples. We compared the genetic diversity of SAV in farmed Atlantic salmon and rainbow trout, in addition to two wild flatfish species, sampled from multiple regions in Scottish and Irish waters. Mixed subtype infections were present in three of the four species studied, and in both farmed and wild samples. This involved pairs of SAV subtypes known to previously exist in the sampled geographical locations. Evidence of subtype-level SAV co-infections were also shown in individual fish (i.e. not pooled), including wild fish such as dab. Our findings confirm the circulation of multiple SAV subtypes on the same fish farm and abundant within-subtype genetic diversity in all studied samples. Further, the pooling of samples from different fish clearly underestimates the genetic diversity characterizing infections, and likely limits the power to detect the transmission of novel viral genotypes into different geographic regions or fish farms. We conclude that SAV transmission and evolutionary dynamics are more complex than recognized currently, and should be routinely characterized at a genome-wide level to capture the true diversity associated with disease outbreaks, providing stronger information for decision-making on disease control.