In the ever-evolving world of aquaculture, researchers are continually seeking innovative methods to monitor and manage disease outbreaks, which can devastate fish populations and significantly impact the industry’s economic viability. A recent study published in *Aquaculture Reports* offers a promising approach to pathogen surveillance using existing genotyping data, potentially revolutionizing disease management in barramundi farming.
The study, led by Celestine Terence of the Tropical Futures Institute at James Cook University in Singapore, leverages double digest Restriction-site Associated DNA sequencing (ddRADseq) Genotyping by Sequencing (GBS) data to simultaneously genotype barramundi and monitor the presence of scale-drop disease virus (SDDV). SDDV is a notorious pathogen responsible for causing 40–90% mortality in farmed barramundi, making it a significant concern for aquaculture producers.
Traditionally, GBS has been employed in selective breeding programs to acquire single nucleotide polymorphism (SNP) genotypes for various applications, including pedigree reconstruction and estimating genetic parameters. However, this study demonstrates that the sequencing libraries used in GBS, which encompass all DNA present in fin-clip tissue, can also recover the non-host metagenomic fraction, including pathogens.
By aligning raw reads from 4484 fish of four commercial cohorts to the SDDV reference genome, the researchers found a striking association between SDDV prevalence and load with clinical status. “We observed that 88.9% of moribund fish carried SDDV, while only 0.2% of healthy fish were positive,” Terence explained. “Moreover, the viral load in moribund fish was significantly higher, with an average of 21.8 reads per million (RPM) compared to just 0.002 RPM in healthy fish.”
The study’s findings were further validated through quantitative PCR (qPCR) on a subset of 172 fish, which yielded viral copy numbers strongly correlated with ddRADseq RPM. This correlation underscores the suitability of non-lethal fin tissue for surveillance, as viral loads were consistently higher in fin tissue than in spleen tissue.
The implications of this research for the aquaculture industry are substantial. By repurposing routine ddRADseq datasets, fish farmers can integrate pathogen monitoring into their existing genomic improvement programs. This dual approach not only streamlines the breeding process but also enhances disease management, ultimately leading to more resilient and productive fish populations.
As the aquaculture sector continues to grow, the need for efficient and effective disease surveillance methods becomes increasingly critical. This study’s findings suggest that breeding programs generating large ddRADseq GBS datasets may also serve pathogen surveillance purposes, provided the target pathogen infects the host genotyped tissue. This innovative approach could pave the way for more integrated and proactive disease management strategies in aquaculture, benefiting both producers and consumers alike.
In the words of Terence, “Our findings demonstrate the potential of repurposing existing genotyping data for pathogen surveillance, offering a cost-effective and efficient solution for disease management in aquaculture.” As the industry continues to evolve, such integrated approaches will be crucial in ensuring its sustainability and profitability.