Microbiome and Pathobiome Characterization in Farmed Barramundi (Lates calcarifer) During and Post Scale Drop Disease Outbreaks

Abstract

Large-scale double-digest RAD sequencing (ddRADseq) datasets generated for genotyping are increasingly available in aquaculture, yet their unmapped reads remain largely unexplored for pathogen surveillance. Here, we evaluated the utility and limitations of repurposing unmapped ddRADseq reads to examine pathogen-associated and disease-associated microbiome-pathobiome patterns during scale drop disease (SDD) outbreaks in farmed barramundi (Lates calcarifer). Using fin clips ddRADseq datasets from 4593 barramundi across four commercial sea-cages, we profiled bacterial and viral communities by taxonomic classification of unmapped reads. Fish sampled during active outbreaks consistently exhibited strong enrichment of scale drop disease virus (SDDV-associated signals; 76.3%–80.5%), frequently co-occurrence with infectious spleen and kidney necrosis virus (ISKNV; 0%–13.4%), along with a marked microbial shift towards Vibrio-dominated bacterial communities, particularly reads classified within the Vibrio harveyi clade. In contrast, clinically healthy post-outbreak fish showed consistently low viral signals and were characterized by distinct, more diverse microbial profiles dominated by Alphanudivirus, Cyvirus, Stenotrophomonas and Burkholderia, indicating a comparatively stable microbiome state in the absence of active disease outbreaks. Treating normalized pathogen read counts as proxy traits, exploratory quantitative genetic analyses indicated low overall heritability estimates for SDDV-associated signal (h² = 0.08), with higher cohort-specific estimates (up to 0.23), consistent with strong environmental or co-infection effects and complex co-infection dynamics in open-sea farming systems. While ddRADseq-based pathogen detection is inherently biased by restriction-enzyme site representation, host-DNA dominance and the lack of absolute quantification, consistent patterns observed across thousands of fish tissues across multiple cohorts and outbreak stages provide biological meaningful population-level insights into farm-associated microbiome and pathobiome dynamics. Together, our results support that the use of unmapped ddRADseq reads as a cost-effective, complementary tool for retrospective pathogen screening and hypothesis generation in aquaculture, alongside targeted surveillance and diagnostic approaches.