Microbriome-pathobiome characterization in barramundi (unmapped reads from ddRADseq)
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 feasibility and limitations of repurposing unmapped ddRADseq reads to characterise pathogen presence and disease-associated microbiome-pathobiome patterns during scale drop disease (SDD) outbreaks in farmed barramundi (Lates calcarifer). Using fin clips ddRADseq datasets from 4,593 barramundi across four commercial sea-cages, we profiled bacterial and viral communities by taxonomic classification of unmapped reads. Diseased individuals exhibited strong enrichment of scale drop disease virus (SDDV; 76.3–80.5%), frequently co-occurrence with infectious spleen and kidney necrosis virus (ISKNV; 0–13.4%), along with a marked microbial shift toward Vibrio spp., especially V. harveyi. In contrast, clinically healthy fish showed consistently low viral signals and were characterised by distinct, more diverse microbial profiles dominated by Alphanudivirus, Cyvirus, Stenotrophomonas, and Burkholderia, indicating a comparatively stable microbiome state in the absence of disease outbreaks. Treating normalized 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 in open-sea farming systems. While ddRADseq-based pathogen detection is inherently biased by restriction-enzyme site representation and host-DNA dominance and does not provide absolute pathogen quantification, patterns observed across thousands of sequenced fish tissues from multiple cohorts?spanning healthy conditions and outbreak events?have improved our understanding of the farm-associated microbiome and pathobiome. Together, our results demonstrate that unmapped ddRADseq reads can be repurposed as a cost-effective, population-level tool for retrospective pathogen screening and hypothesis generation in aquaculture, complementing targeted surveillance and diagnostic approaches.