Introduction
The rapid development of aquaculture has positioned it as a vital component of global food systems. Within the Mediterranean basin, gilthead seabream (Sparus aurata) has emerged as a dominant cultured species, reflecting both its commercial importance and adaptability to farming conditions. However, growth variability in gilthead seabream still represents a major challenge for Mediterranean aquaculture, as individuals raised under identical conditions often show large differences in growth rate. This stems from multiple factors, including genetic diversity, where inherent differences in genetic growth potential lead to unequal growth rates. Environmental factors, such as water quality and temperature fluctuations further exacerbate these differences, often favoring certain individuals while suppressing others. This inconsistency reduces overall production efficiency by making synchronized harvesting difficult, as fish reach market size at different times. To address these challenges, in most aquaculture companies periodic grading is commonly practiced, where fish are physically separated based on their size to reduce competition and ensure uniform growth within groups. This method offers a practical short-term solution for managing size variation, but it is still labor-intensive and does not address the underlying molecular factors that influence growth. Moreover, conventional gene expression analyses target only a limited group of candidate genes which may not fully capture the genetic landscape regulating growth.
Materials and Methods
Two independent trials were conducted at EPPO/IPMA facilities, where growth differences were identified at initial sampling with mean weights of 14.0 ± 1,8 g (trial 1) and 14.5 ± 2.6 g (trial 2). Then fish were sorted into slow- and fast-growing based on the average batch weight, with density maintained across all tanks. Fish were maintained at a flow-through system and fed a commercial diet, three times per day, until apparent satiety. Trial 1 lasted 100 summer days, while Trial 2 extended for 284 winter days, reflecting seasonal variations. In the final sampling, liver and intestine (in trial 1 and 2) and muscle (only in trial 2) samples were collected from six fish per condition (fast vs slow) for differential gene expression (DGEs) analysis. Total RNA was extracted with a TRItidy G��� reagent, under manufactures instructions, quantified and quality verified by gel electrophoresis before sending for library construction and mRNA sequencing (Novogene Co., Ltd). To select growth biomarkers in liver and intestine, the DEGs in both trials were compared and only the genes differentially expressed in both trials were selected as hits for validation through RT-qPCR. To select growth biomarkers in muscle, the top 5 up- and down DGEs were selected as hits using data only from trial 2.
Results and Discussion
Results show that fast-growing fish outperformed slow-growing ones, demonstrating better growth potential and physiological performance with mean weights in trial 1 of 139 ± 17 g and 194 ± 16 g and trial 2 of 216 ± 54 g and 591 ± 22 g, for slow and fast-growing, respectively. The combination of both trials' biomarkers selection revealed 11 up (including cacna1d, ccbe1 and hamp) and 4 down-regulated genes (including efna2 and trim21) in liver and 1 up (samd9) and 2 down-regulated genes (dhrs12 and irgc) in intestine, when comparing fast- with slow-growing fish. The top 5 up-regulated genes in muscle were tmprss9, ctxn3, nlrp12, dpy30 and znf608, and top 5 down-regulated genes were mfap4, dhys, mdn1, lgals3 and gpr12. RT-qPCR validation of some genes confirmed the differential expression between fast- and slow-growing fish, concordant with RNA-seq results. These genes play diverse yet interconnected roles in growth regulation, metabolism, immunity, and muscle function. Their differential expression between fast- and slow-growing fish suggests that they could serve as potential biomarkers for growth profiles in Sparus aurata. Differential KEGG pathway enrichment analysis between fast-growing and slow-growing fish revealed tissue-specific metabolic reprogramming associated with growth rate. For liver and intestine, only the pathways that are significant in both trials were analyzed, and in muscle all significant ones. In the liver, fast-growing fish showed significant down-regulation of pathways involved in oxidative phosphorylation, potentially indicating a reduced reliance on hepatic mitochondrial ATP production, and cardiac muscle contraction pathway that reflect a systemic metabolic prioritization away from energetically costly maintenance processes. No up-regulated pathways were observed. In intestine, fast-growing fish showed down-regulation of two metabolic pathways, carbon metabolism and biosynthesis of amino acids. This pattern suggests a reduction in endogenous metabolic processing and amino acid synthesis within the intestinal tissue, potentially reflecting a reliance on dietary nutrient uptake and a more efficient utilization of absorbed nutrients to support rapid growth. In muscle, fast-growing fish exhibited a mixed but overall, metabolically enhanced pathway profile. Several central energy and metabolic pathways were up-regulated, including oxidative phosphorylation, the citrate cycle (TCA cycle), carbon metabolism, peroxisome activity, drug metabolism – cytochrome P450, mitophagy animal, and valine, leucine and isoleucine degradation. Together, these changes indicate increased mitochondrial activity, enhanced energy production, and active cellular remodeling to meet the high energetic demands of fast growth. In contrast, the ribosome pathway was downregulated in muscle of fast-growing fish, suggesting a potential reduction in protein synthesis capacity or a shift toward more selective and efficient translational processes during rapid growth. This coordinated inter-tissue regulation likely enhances energy efficiency, supporting rapid somatic growth.
These results reveal distinct molecular signatures associated with growth capacity in gilthead seabream and that the use of RNA-seq proved to be effective for identifying genes and regulatory networks directly related to growth performance. Future work includes expanding validation efforts and conducting additional trials to further test the predictive value of these biomarkers in a real-life setting.
Acknowledgment
This study was funded by the project NanoPEIXE (ALG-01-0247-FEDER-070032) and with funding from Interface Mission, project cofinanced by PRR - Plano de Recupera����o e Resili��ncia by the European Union (operation code 01/C05-i02/2022.P148).