# Mechanistic investigation into the differences in growth performance and resistance to spring viremia of carp virus in common carp

## TL;DR

This study explores how faster-growing carp are more vulnerable to a virus, uncovering genetic and metabolic links between growth and disease resistance.

## Contribution

The study identifies specific genes and metabolites associated with growth and resistance to SVCV in common carp using multi-omics approaches.

## Key findings

- Fast-growing carp showed significantly lower survival rates after SVCV infection compared to slow-growing carp.
- Genes in the Grey module were positively linked to growth but negatively to resistance, with key hub genes gsta4, adh8b, and gimap7.
- Metabolite modules Florawhite and Grey60 were associated with growth and survival, highlighting nutrient and detoxification pathways.

## Abstract

Spring viremia of carp virus (SVCV) is a highly infectious pathogen threatening common carp (Cyprinus carpio). Hence, implementing protective measures is crucial to safeguard aquatic species and minimize economic impacts, including pharmaceuticals, vaccines, and breeding of resistant varieties. Common carp is a major aquaculture species, with breeding programs primarily focused on enhancing growth performance. However, evidence indicates that accelerated growth may compromise disease resistance, suggesting a trade-off between these traits.

We challenged two carp populations with contrasting growth rates using SVCV and performed integrated multi-omics analyses.

Survival analysis showed that fast-growing carp had significantly lower survival than slow-growing carp, with growth negatively correlated with resistance (r = -0.83). RNA-seq analysis of head kidney tissues identified a Grey module gene via Weighted Gene Co-expression Network Analysis (WGCNA), positively linked to growth but negatively to resistance. KEGG enrichment analysis showed that genes within this module were significantly enriched in pathways related to xenobiotic metabolism, nutrient processing, and detoxification. Protein–protein interaction (PPI) network analysis highlighted three hub genes (gsta4, adh8b, and gimap7) potentially regulating both traits. Metabolomic profiling of liver tissues, combined with WGCNA, revealed three metabolite modules: Florawhite, positively associated with body weight and negatively with survival rate; Grey60, negatively associated with body weight and positively with survival rate; and Lightsheelblue, positively associated with survival rate only. These metabolites were predominantly enriched in pathways related to nutrient metabolism, digestion and absorption, and secondary metabolite biosynthesis. Correlation analysis between Grey module genes and metabolites identified 20 genes significantly associated with 159 metabolites. Among these, ss18, arl5a, and hnrnph3 emerged as potentially pivotal. The metabolites highly correlated with these three genes were predominantly enriched in pathways related to nutrient metabolism, energy metabolism, detoxification and antioxidation, and immune regulation.

In summary, our integrated multi-omics analysis suggests that enhanced nutrient absorption and xenobiotic processing may contribute to superior growth performance in the YB population, while elevated detoxification and antioxidant capacity may underlie stronger disease resistance in the CD population. These findings provide insights into the interplay between growth and immunity in carp and offer biomarkers for balanced breeding strategies.