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Article

Investigating the Impact of six6 Genetic Variation on Morphological Traits in Larvae and Juveniles of European Seabass (Dicentrarchus labrax Linnaeus)

by
Marinina Papamichail
1,
Aristotelis Moulistanos
2,3,
Ioannis Georgatis
1,
Ioustini Vagia
2,
Katerina Tasiouli
2,
Konstantinos Gkagkavouzis
2,3,
Anastasia Laggis
2,
Nikoleta Karaiskou
2,3,
Efthimia Antonopoulou
4,
Alexandros Triantafyllidis
2,3,
Spiros Papakostas
5 and
Ioannis Leonardos
1,*
1
Laboratory of Zoology, Biological Applications and Technology Department, University of Ioannina, 45110 Ioannina, Greece
2
Department of Genetics, Development and Molecular Biology, School of Biology, Faculty of Science, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
3
Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH), 57001 Thessaloniki, Greece
4
Department of Zoology, School of Biology, Faculty of Science, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
5
Department of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Fishes 2025, 10(8), 416; https://doi.org/10.3390/fishes10080416
Submission received: 29 May 2025 / Revised: 15 July 2025 / Accepted: 12 August 2025 / Published: 19 August 2025
(This article belongs to the Section Genetics and Biotechnology)
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Abstract

The European seabass is a key Mediterranean aquaculture species, vital for sustainably meeting rising global protein demands amid declining wild fish stocks. Genetic analyses have identified the six6 gene as a candidate target of domestication and selective breeding, with two SNPs showing significant genotypic differences between wild and farmed European seabass populations. Further analyses revealed differential six6 expression between larval and juvenile stages, suggesting a potential developmental role. This study explores associations between these SNPs and important aquaculture traits across early developmental stages. Seabass samples were examined at 34 days post-hatching (dph, larval stage) and 71 dph (juvenile stage). We examined associations between specific six6 SNPs and morphological traits using traditional morphometrics, analyzing 20 and 26 characteristics in the larval and juvenile stages, respectively. Shape and size differences were examined without allometric correction. The six6 gene was primarily associated with body length, height, and caudal fin morphology. Notably, homozygous six6 genotype combinations at the studied SNPs were associated with increased body length in a developmental stage-specific manner. Variation in this gene also appeared to influence eye development in juveniles. These findings offer phenotypic evidence supporting previous genetic and expression studies in European seabass, highlighting their potential applications in fisheries and aquaculture.
Keywords:
Dicentrarchus labrax; aquaculture; selective breeding; morphometry; six6
Key Contribution: This study provides the first phenotypic evidence linking six6 gene variants to key morphological traits in European seabass, including body length, body height, and eye development, across early developmental stages. These findings support the gene’s role in domestication.

1. Introduction

With wild fish stocks increasingly threatened by overfishing and environmental changes, aquaculture has emerged as an alternative to meet the growing global demand for food [1,2,3], especially as the global population is projected to reach 9.8 billion by 2050 [4]. As a nutrient-dense and environmentally sustainable option [5,6,7,8], fish consumption plays a vital role in meeting global food needs, providing a reliable protein source for the expanding human population [2]. Recognized as a key solution for food security and economic growth, aquaculture aligns with the United Nations’ 2030 Agenda for Sustainable Development, addressing the “Zero Hunger” (Goal 2) and “Ensure Sustainable Consumption and Production Patterns” (Goal 12) goals. In 2022 alone, aquaculture contributed 25% of the EUs finfish supply and generated €4.8 billion in revenue [9,10]. Genetic enhancement through selective breeding and modern technologies, such as marker-assisted and genomic selection, can further boost aquaculture’s productivity, resilience, and sustainability, while reducing reliance on wild stocks [11,12]. By optimizing desirable traits, such as growth rates, disease resistance, and consumer-preferred morphology, genetic advancements can help meet the rising seafood demand while minimizing environmental impacts and ensuring food security and economic stability [1,11,12,13,14].
The morphological appearance of fish plays a pivotal role in aquaculture. Consumer preferences for fish are influenced by traits like body shape, size, skin coloration, and flesh quality [11,15,16,17], whereas aquaculture operations prioritize characteristics such as disease resistance, faster growth rates, and early sexual maturity to enhance efficiency and sustainability [11,15,17]. These traits are often evaluated visually and can significantly impact the perceived quality and market appeal of fish [13,18,19,20,21]. The study of morphological traits plays a pivotal role in selective breeding programs, serving as a key for improving fish stocks in aquaculture [22]. For instance, Beeman et al. [23] highlights the utility of morphogenetic analysis in salmonids as a non-lethal alternative for assessing smoltification [23]. Morphometric traits have consistently proven valuable in fisheries management and stock identification, revealing patterns like isometric growth, in which morphometric characters scale with body length while meristic characters remain constant [24]. Understanding the genetic basis of these traits and their functional effects by linking genotype to phenotype is critical for advancing selective breeding efforts [25,26].
The European seabass (Dicentrarchus labrax, Linnaeus 1758) is a species of high commercial value [17]. In 2022, seabass accounted for 44.6% of the Mediterranean production, amounting to 256,577 tons [9]. Over the past decade, the European seabass aquaculture industry has experienced significant growth. By 2022, seabass represented 14% of the total European aquaculture production value, reaching a 10-year peak [27]. The demand for fresh seabass continues to grow, driven by its nutritional value, taste, flavor, and overall quality as appreciated by consumers [28]. Consequently, seabass is widely farmed across Europe, especially in the Mediterranean Sea, where selective breeding programs have been implemented to enhance desirable traits [17]. Recent research has highlighted a potential role for the six6 (SIX homeobox 6) gene in the domestication of European seabass [29]. Notably, significant differences in genotype and allele frequencies at two intronic SNPs within six6 have been observed between seven farmed and eleven wild populations from Greece [29]. Additionally, gene expression analyses suggest that genetic variation in six6 may be linked to developmental processes in European seabass, with differences in expression variability among six6 genotypes most notably observed during the larval stage [30]. The function of six6 in eye development is well established across taxa [31,32]. As a transcription factor functioning within the hypothalamus-pituitary-gonadal axis, six6 is involved in regulating sexual maturation in salmonids [33,34,35]. Beyond these roles, six6 has been associated with similar life history traits in various species, including both fish and mammals [31,32,33,34,35,36,37,38]. Given its evolutionary conserved functions and its associations with the domestication and development in European seabass, the phenotypic impact of six6 across different developmental stages remains an important open question.
The aim of this study was to evaluate the association of different six6 genotypes on the phenotype of D. labrax at two early developmental stages by using multivariate and univariate morphometric analyses. This research employs a biometric approach in aquaculture to better understand the species’ morphological development and its relationship with biomass growth, thereby contributing to improved efficiency in European seabass farming. Specifically, we examined two intronic SNPs within the six6 gene that have previously been associated with the domestication and developmental process of European seabass [29,30]. By investigating the association between these domestication-related SNP genotypes [29] and the morphological traits of specimens at two developmental stages, we aimed to gain deeper insights into the role of six6 in shaping developmental outcomes. Furthermore, we assessed its potential influence on traits that align with the aquaculture and consumer preferences, including shape, size, and structural changes, which are critical for fitness variation and commercial success.

2. Materials and Methods

2.1. Sampling

In February 2023, we collected farmed specimens of European seabass at two developmental stages. We categorized the sampled individuals based on their different combinations of the two intronic six6 SNP genotypes previously associated with domestication, henceforth called haplogenotypes. We thus obtained four sample groups at the larval stage (34 days post-hatch, dph) and five groups of samples at the juvenile stage (71 dph) (Table 1). The total number of samples analyzed was 109 at 34 dph and 125 at 71 dph. All individuals were reared under identical controlled conditions, which included a temperature of 19 °C, a salinity of 40‰, a pH ranging from 7.6 to 7.8, and dissolved oxygen (O2) saturation levels of 6–7 ppm. At 34 dph, larvae were kept under a 16 h light: 8 h dark photoperiod, with light intensity maintained at approximately 400 lux, and were fed enriched Artemia nauplii. By 71 dph, juveniles were transitioned to natural photoperiod conditions and fed a commercial dry diet formulated for marine species. The collected specimens were anesthetized with clove oil and photographed using a digital camera (Nikon D3300, with image resolution 3872 × 2592 pixels) for subsequent morphological analysis. To ensure standardized imaging, each specimen was placed laterally on a background printed with a millimeter-scale grid, allowing for precise calibration of measurements. The camera was mounted at a fixed distance and angle to maintain consistent magnification across all specimens. Lighting conditions were kept uniform to minimize shadows and distortion, ensuring high-quality images suitable for accurate shape and size comparisons. Following photography, each specimen was preserved in vials of pure ethanol at –20 °C.

2.2. Genotyping of six6

The genomic locations of the two domestication-related SNPs are 12:11591053 and 12:11591093, according to the GCA_000689215.1 genome assembly for D. labrax [29]. Genomic DNA was extracted using the protocol by Hillis et al. (1996) [39] and was stored at –20 °C. For PCR amplification, we used the primers 5′-GGCTACAGGACTTACACCCA-3′ and 5′-AAGTACCACAGCAAGATCGC-3′ [29]. The amplification reaction was conducted in a total volume of 25 μL, containing 100 ng of genomic DNA as the template, 0.05 units of Qiagen Taq polymerase, 2 mM dNTPs, 0.25 μL of each primer (100 μΜ), and 2.5 μL of 10x Reaction Buffer (Qiagen, Hilden, Germany). PCR conditions were as follows: initial denaturation at 94 °C for 2 min; 35 cycles of denaturation at 94 °C for 30 s, annealing at 63 °C for 40 s, and extension at 72 °C for 1 min; followed by a final extension at 72 °C for 10 min. The PCR products were confirmed by electrophoresis in 1.5% (w/v) agarose gels and then entrusted to the company Genewiz (Leipzig, Germany) for enzymatic cleanup and Sanger sequencing. To genotype the SNPs, the resulting sequences were aligned with the reference genome (D. labrax: GCA_000689215.1) using the Geneious program (v.10.2.6; Biomatters Ltd., Auckland, New Zealand; https://www.geneious.com; last accessed 7 February 2025).

2.3. Microsatellites Genotyping and Population Structure Analysis

One multiplex PCR targeting seven microsatellite loci (Lab13, DLA0119, DLA0016, DLA0105, Lab3, DLA0116, and DLA-20) was performed on the samples studied. Amplification and fragment analysis were carried out using an ABI 3500 Genetic Analyzer with the GeneScan 500 LIZ size standard (250 bp peak) (Thermo Fisher Scientific, Waltham, MA, USA) at the Laboratory of Agrobiotechnology and Inspection of Agricultural Products, International Hellenic University. Genotyping was conducted using Geneious software version 10.2.6. Fst values based on microsatellite loci of larvae and juveniles among six6 haplogenotypes were calculated using the Genepop 3.4 software package (Laboratory of Genetics and Environment, Institute of Evolutionary Sciences (UM2–CNRS), University of Montpellier, Montpellier, France) [40].

2.4. Morphometric Analysis

A combination of traditional morphometry [41] and the truss network method [42] was applied for morphometric analysis. Distances between defined anatomical landmarks were measured on digital photos of every individual. To ensure consistency, all morphometric measurements were performed by a single trained observer, eliminating inter-observer variability. Homologous body marks were used to statistically assess biological shape variation [43], thereby creating a truss network. For the larvae stage, distances (D) between 18 homologous landmarks on each fish were measured, yielding a total of 20 morphometric characters (Figure 1a, Table S1). For the juvenile stage, distances between 20 landmarks were measured, yielding a total of 26 morphometric characteristics (Figure 1b, Table S1). A condensed summary of distance codes is provided in Figure 1. Landmark codes were assigned to maintain anatomical consistency across developmental stages, ensuring homologous structures shared the same labels. Using the ImageJ program (v.1.54k; National Institutes of Health, Bethesda, MD, USA, and the Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI, USA), these distances were calculated and recorded in an Excel file (version 16.0.17628.20110). All measurements were expressed in units of 0.01 cm.

2.5. Statistical Analysis

Specimens of both sexes were analyzed together, as sex could not be reliably determined at 34 and 71 days post-hatching without molecular markers, and no morphological differences are expected between sexes at such early developmental stages [44,45]. Measurement values were log10-transformed to satisfy the normality assumption. An allometric adjustment of the morphometric data relative to standard length (SL) was then performed. To remove the effect of body size [46,47], all individual morphometric measurements were standardized according to the formula:
Dadj = logD − b ∗ (logSL − logSLmean)
where Dadj is the standardized measurement, D is the measured character length, SL is the standard length of fish, and SLmean is the overall mean standard length. Coefficient b was estimated as the slope of the regression of log10 Di on log10 SLi using all fish in all groups, while allowing the intercept to vary between groups [47]. According to Reist (1985), this transformation best reflects any shape variation among groups, independently of size [46].
All statistical analyses were performed in SPSS (version 29.0.1.0; IBM Corporation, Chicago, IL, USA), using allometrically corrected data and were implemented using standard settings. Multivariate analyses—principal component analysis (PCA) and discriminant function analysis (DFA)—were employed to identify morphological differences among the haplogenotypes; both of which are effective tools for analyzing intraspecific variations [41,48,49]. This approach is appropriate for developmental stage comparisons in early fish ontogeny, where linear measurements represent distinct morphological traits of interest [43]. Initially, PCA was conducted to detect morphometric differences among biological categories and to determine the contribution of each variable to group differentiation. Components with an eigenvalue greater than one (1) were considered statistically significant, with the first two principal components of utmost importance. The remaining principal components were not discussed further, as they did not contribute meaningfully to group differentiation. Subsequently, DFA was performed on both the entire dataset and on overlapping genotypic classes and characteristics of the two developmental stages for group discrimination and classification.
The morphological differences among the sample groups were further investigated using a univariate Kruskal–Wallis test on the allometrically corrected data. To focus on the most biologically relevant traits, we selected morphometric variables with the highest contributions to variance in PCA (|loading| > 0.5). These morphometric distances are highlighted in bold in the factor loadings table. Kruskal–Wallis tests were performed on both the entire dataset and the overlapping genotypic classes of the two developmental stages to further assess the differences among groups. The null hypothesis (H0) was defined as the medians of each characteristic being equal across groups. To account for multiple comparisons, Bonferroni correction was applied manually by dividing the standard α level (0.05) by the number of independent Kruskal–Wallis tests performed. Specifically, for the larval stage (14 tests), the adjusted significance level was α = 0.0036; for the juvenile stage (14 tests), α = 0.0036; and for the comparison across stages (7 tests), α = 0.007. Only p-values below these corrected thresholds were considered statistically significant.

3. Results

Morphometric data from individuals at two developmental stages (109 larvae and 125 juveniles) of European seabass were analyzed, while the same specimens were genotyped at two intronic SNPs in the six6 gene, previously associated with the domestication process. For the morphometric analysis, we categorized individuals according to the combination of composite genotype from both SNPs (haplogenotypes).

3.1. six6 Haplogenotypes and Population Structure Effect

The genotyping of European seabass individuals at two SNPs within the six6 gene (positions 12:11591053 and 12:11591093 on the GCA_000689215.1 assembly) identified six distinct haplogenotypes across the two developmental stages (34 and 71 days post-hatching, dph). The results of the genotyping analysis are summarized in Table 1. At 34 dph, the most frequent haplogenotypes were TT-TT (n = 30), AT-TT (n = 30), and AA-TT (n = 30), while AT-CT (n = 19) was less represented. At 71 dph, the most common haplogenotypes were TT-TT (n = 32), AT-TT (n = 30), and AT-CT (n = 30), followed by AA-CC (n = 18) and AA-CT (n = 15). The AA-TT haplogenotype was only observed at 34 dph, whereas AA-CC and AA-CT appeared exclusively at 71 dph.
To assess potential genetic differentiation among six6 haplogenotypes, we calculated pairwise FST at two developmental stages. At 34 days post-hatch (dph), the average FST was 0.0460, and at 71 dph, it was 0.0286. These values are considerably lower than the typical FST values reported among European seabass populations (up to 0.12) [29], suggesting minimal population structure within the hatchery cohort used in this study.

3.2. Larval Stage (34 dph)

3.2.1. Principal Component Analysis (PCA) for Larvae at 34 dph

Nineteen principal components were derived, five of which were considered statistically significant (eigenvalue greater than 1), cumulatively accounting for 72.77% of the total morphological variation (Table S2). The first principal component (PC I) explained 28.25% of the variance, while the second principal component (PC II) explained 17.51%. Cumulatively, the first two principal components accounted for 45.76% of the total variance (Figure 2a). The remaining principal components were not discussed further, as they did not contribute meaningfully to group differentiation (Table S2). According to the factor loadings for each morphometric variable (Table 2, Table S3), PC I mainly reflected characters associated with fish length (D3, D4) and caudal fin morphology (D5, D6, D8), whereas PC II was primarily associated with body height measurements (D13, D14, D16, D20).

3.2.2. Discriminant Function Analysis (DFA) for Larvae at 34 dph

A DFA was performed on 106 D. labrax larvae specimens. Group centroids represent the average multivariate profile of each haplogenotype in discriminant space. The relative positions of the group centroids obtained from the DFA are provided in Table 3. The analysis extracted three canonical discriminant functions describing the dataset. Summary statistics indicated that DFA I accounted for 73.60% of the total morphological diversity, DFA II for 15.20%, and DFA III for 11.20%. The DFA achieved an overall correct classification (repositioning) rate of 71.70% (Table 4), with particularly strong separation between AA-TT and TT-TT haplogenotypes, as well as between AT-CT and AT-TT specimens, as seen in the canonical plot (Figure 3a) and group centroid locations (Table 3).

3.2.3. Kruskal–Wallis Test for Larvae at 34 dph

A Kruskal–Wallis test was performed on 14 traits to assess the relations between genotype combinations, including the morphometric distances highlighted in bold in Table 2. Statistically significant differences in morphometric distances related to body length (D3, D17), body height (D16, D20), and caudal fin morphology (D5, D6) were observed between larvae with AT-CT and AT-TT haplogenotypes (Table 5, Figure 4). AT-TT larvae exhibited greater body length (D3, D17) than AT-CT individuals. Specimens with AT-TT and TT-TT haplogenotypes showed greater body height (D16). These results indicate that the CT genotype of the second SNP is associated with smaller length-related differences, while the TT genotype of the same SNP is associated with larger height-related differences (Figure 4).

3.3. Juvenile Stage (71 dph)

3.3.1. Principal Component Analysis (PCA) for Juveniles at 71 dph

In total, 25 principal components were derived, seven of which had an eigenvalue greater than 1, cumulatively accounting for 77.62% of the morphological diversity (Table S4). The first principal component (PC I) explained 23.15% of the total variance, while the second principal component (PC II) explained 17.37%. Together, the first two principal components accounted for 40.53% of the total variance (Figure 2b). The remaining principal components were not discussed further, as they did not contribute meaningfully to group differentiation (Table S4). According to the factor loadings for each morphometric variable (Table 6, Table S5), PC I expressed characters mainly associated with fish length (D3, D4), caudal fin morphology (D5, D6, D8), and body height (D23, D25), whereas PC II represented characters mainly associated with the height measurements (D11, D23, D24, D12, D13, D15).

3.3.2. Discriminant Function Analysis (DFA) for Juveniles at 71 dph

A DFA was performed on 121 juvenile specimens. The relative positions of the group centroids resulting from the DFA are provided in Table 7. The analysis extracted four canonical discriminant functions describing the dataset. Summary statistics indicated that DFA I accounted for 43.60% of the total morphological diversity, DFA II for 25.80%, DFA III for 21.30%, and DFA IV for 9.30%. The DFA yielded a high overall classification accuracy of 73.6% (Table 8), with particularly strong separation between AT-TT and the rest of the haplogenotypes, as seen in the canonical plot (Figure 3b) and group centroid locations (Table 7).

3.3.3. Kruskal–Wallis Test for Juveniles at 71 dph

A Kruskal–Wallis test was conducted on 14 morphometric traits to assess the effect of allometry, including the distances highlighted in bold in Table 6. Significant differences in body length (D3), caudal fin morphology (D6), eye size (D18), and body height (D23) were detected between AA-CC and AT-TT haplogenotypes (Table 9). AT-TT specimens showed smaller body length (D6) and eyes (D18) but greater body height (D23) (Figure 5). Additionally, AA-CC specimens exhibited larger eyes than the AT-CT juveniles, too (Table 9, Figure 5d). These results suggest that the AT genotype of the first SNP is associated with smaller eye size.

3.4. Comparison Between the Two Developmental Stages

3.4.1. Principal Component Analysis (PCA) Comparing Larvae (34 dph) and Juveniles (71 dph)

In total, 19 principal components were derived, 6 of which had an eigenvalue greater than 1, cumulatively accounting for 78.986% of the larvae diversity and 77.370% of the juvenile morphological variance (Table S6). When analyzing the larvae specimens, cumulatively the first two principal components explain 44.612% of the total variance (Figure S1a), while when analyzing the juveniles, they explain 43.367% of the total variance (Figure S1b). The remaining principal components were not discussed further, as they did not contribute meaningfully to group differentiation (Table S6). According to the factor loadings for each morphometric variable (Table S7) for both developmental stages, it can be assumed that PC I expressed characters mainly associated with the fish length (D3, D4) and the caudal fin morphology (D5, D6, D8), whereas PC II expressed variables mainly associated with the body height (D16) and length (D17, D20).

3.4.2. Discriminant Function Analysis (DFA) Comparing Larvae (34 dph) and Juveniles (71 dph)

A DFA was performed on 76 larvae specimens. Group centroids represent the average multivariate profile of each haplogenotype in discriminant space. The relative positions of the group centroids are provided in Table S8. The DFA extracted two canonical discriminant functions describing the dataset. Summary statistics indicated that DFA I accounted for 76.30% of the total morphological diversity, while DFA II accounted for 23.70%. The analysis achieved a correct classification (repositioning) rate of 69.70% (Table S9), with particularly strong separation between AT-CT and TT-TT larvae (Figure 3c).
A DFA was also performed on a total of 92 juveniles. Group centroids represent the average multivariate profile of each haplogenotype in discriminant space. The relative positions of the group centroids are also provided in Table S8. The DFA extracted two canonical discriminant functions describing the data set. Summary statistics indicated that DFA I accounted for 65.40% of the total morphological diversity, while DFA II accounted for 34.60% (Table S9). The analysis achieved a correct classification (repositioning) rate of 75%, with particularly strong separation between AT-CT and AT-TT juveniles (Figure 3d).

3.4.3. Kruskal–Wallis Test Comparing Larvae (34 dph) and Juveniles (71 dph)

A Kruskal–Wallis test was conducted on seven morphometric traits to assess their discriminatory capacity between the two developmental stages, including the common morphometric distances labeled in bold in Table S7. These morphometric traits are primarily associated with fish length (D3, D17), caudal fin morphology (D6), and body height (D16, D20). The haplogenotype pairs with a statistically significant difference are provided in Table S10 and Figure S2.

4. Discussion

Our findings suggest that different six6 genotypes may be associated with the phenotype of European seabass during early development in terms of external morphology. The analysis employed two approaches: multivariate analyses (PCA and DFA) and a univariate Kruskal–Wallis test on raw data, excluding allometric growth effects. The results provided important insights into the role of six6 in growth, showcasing its influence on body length, body height, and caudal fin morphology. In larvae, the correlation of six6 was also observed in the second dorsal and anal fin, while in juveniles, variation in this gene was also associated with differences in eye development. These phenotypic effects likely arise from six6’s role as a transcription factor that regulates the expression of genes involved in hypothalamic development and retinal cell differentiation, as demonstrated by Kurko et al. (2020) [50], providing a molecular mechanism for its impact on growth and eye morphology. To our knowledge, this is the first study to link the genetic variance of the six6 gene with the phenotype in European seabass, extending previous work that explored six6 primarily in the context of age at maturity and spawning ecotypes in Atlantic salmon [33,50,51,52]. This cross-species comparison highlights the evolutionary conservation of six6’s role across distinct teleost lineages and supports its involvement in regulating developmental and morphological differentiation. By unraveling the genetic underpinnings of commercially relevant traits, these findings have the potential to inform selective breeding strategies for more efficient and sustainable European seabass aquaculture.
Physical traits such as body shape, size, and structural features provide valuable insights when integrated with genetic data, facilitating the development of fish strains with enhanced growth, quality, and disease resistance [18,19,20]. This approach accelerates breeding processes, reduces the need for extensive trials, and helps optimize aquaculture practices [21], thereby improving fish quality and profitability [53], while playing a pivotal role in selective breeding programs [22]. By demonstrating a notable effect on morphological traits, our findings highlight the practical benefits of such integration for improving aquaculture production efficiency. Our study focused on the association of six6 during specific early developmental stages (larvae and juveniles), which are crucial for determining growth potential [54,55,56]. The regulation of key genes during these stages, influenced by genetic, environmental, and epigenetic factors, significantly affects body length and metabolic efficiency [57,58,59]. Notably, prior research in Atlantic salmon has identified these developmental windows as particularly relevant for studying six6 expression and function [50,52].
Multivariate PCA revealed that, in larvae (34 dph), the greatest variance was explained by characters associated with fish length and caudal fin morphology (PC I), followed by body height (PC II). In juveniles (71 dph), PC I also reflected body length and fin traits, but PC II captured eye size and vertical body height, indicating a developmental progression in the traits most influenced by six6. DFA further supported these patterns, achieving 71.7% classification accuracy in larvae and 73.6% in juveniles, with particularly strong morphological separation between AA-TT and TT-TT, AT-TT and AT-CT in larvae, and between AT-TT and other haplogenotypes in juveniles. Although different traits and haplogenotypes were assessed at each developmental stage, only 20 overlapping morphometric traits and three shared haplogenotypes enabled direct comparisons. Under these constraints, juveniles showed a higher successful repositioning rate in DFA (75%) compared to larvae (69.70%), indicating greater morphological divergence at the juvenile stage and suggesting that the effects of six6 become more pronounced during later development.
The Kruskal–Wallis tests on allometrically corrected traits reinforced the multivariate findings, revealing significant differences in morphometric features associated with body length, body height, and caudal fin morphology. Body length, a key trait for consumer preference and selective breeding [11,17], shows clear variation across six6 haplogenotypes. Similarly, body height—a critical morphological trait in aquaculture due to its strong correlation with body weight and relevance to both breeding programs and market value [18,60,61]—also displays genotypic differences.
In larvae, traits associated with body length (D3, D17) were significantly greater in AT-TT larvae compared to AT-CT (p < 0.003), indicating that the TT genotype at the second SNP may promote greater longitudinal growth during the larval stage. Morphometric distances related to body height (D16, D20) showed significant differences, with AT-TT and TT-TT larvae exhibiting increased height compared to AT-CT (p < 0.002), reinforcing a height-enhancing effect of homozygous TT genotypes. These results imply that the AT-CT haplogenotype, which carries the heterozygous CT genotype at the second SNP, is associated with reduced size-related traits, whereas homozygosity for the TT genotype is linked to increased length and height—consistent with previous gene expression analysis of six6 showing that larvae with the heterozygous AT genotype (at the first SNP) exhibit greater variability in six6 expression compared to homozygous genotypes (AA and TT) at equivalent developmental stages (34 days post-hatching) [30]; possibly reflecting regulatory instability that contributes to the morphological differences observed among genotypes [62,63]. Complementing these morphological patterns, a previous DNA-based study showed that the TT genotype is most frequent in farmed populations and is associated with the domestication process of European seabass [29]. These findings highlight the potential association of six6 genetic variation and expression variability in shaping commercially relevant and ecologically significant traits, such as growth, in the larvae of European seabass.
In juveniles, the phenotypic influence of six6 genotypes was even more pronounced. The AA-CC haplogenotype was associated with greater body length (p < 0.002) and larger eyes (p < 0.003), traits often linked to fitness and survival in natural settings [64,65,66]. In contrast, the AT-TT haplogenotype was associated with smaller eye size and shorter body length, though AT-TT individuals also displayed increased body height compared to AA-CC (p = 0.002), suggesting genotype-specific developmental trade-offs.
In addition to its role in body length, our results also highlighted the involvement of six6 in eye development, a process well-documented across various species. From vertebrates such as frogs [32,67], fish [31,68], mammals, e.g., mice [69], and humans [70], to more primitive organisms like jellyfish [71], six6 has consistently been shown to play a critical role in the development of the visual organ, underscoring its evolutionary conservation. In our study, larger eye size, an adaptive trait that enhances vision and survival in the wild [64,65,66], was more prominent in AA-CC juveniles. Despite its biological importance, eye size is often overlooked in aquaculture breeding programs [72]. Previous research has shown that domestication can influence eye size in fish [72]. In our study, eye diameter (D18) was significantly smaller in AT-TT juveniles compared to AA-CC (p < 0.001), indicating that homozygous TT genotypes, associated with domestication [29], may drive reduced eye development. These findings further support the proposed role of six6 in the domestication of European seabass, suggesting that genetic variation in the latter key developmental gene may significantly impact eye morphology, an ecologically relevant trait with potential implications for aquaculture selection strategies.
However, the findings of this study should be interpreted considering certain limitations. First, the morphological traits assessed are polygenic, with the six6 gene likely serving as a contributing factor, though their precise role—whether causative or correlative—remains unclear. The six6 SNPs studied are located within intronic regions [29], and while intronic mutations are known to influence gene regulation, their exact phenotypic effects in this context are uncertain [58,73,74]. Intronic variation can modulate gene expression and phenotype by altering splice site activity, regulatory elements, and chromatin architecture [75,76,77,78]. In particular, alternative splicing is a key mechanism driving transcriptional diversity in developmental genes like six6 [78]. Furthermore, the SNPs examined may be in linkage disequilibrium with the actual causative variant. Therefore, further functional studies are needed to determine whether these variants directly influence gene expression or are merely linked to functionally relevant loci. Second, the traditional morphometrics as applied in this study provide a two-dimensional approximation of fish morphology using linear distances between landmarks derived from digital images instead of a 3-D approximation. Finally, all specimens were sourced from a single hatchery in Greece, and the study’s rather small sample size (109 larvae and 125 juveniles) further limits the generalizability of the results.
Future research should aim to clarify the precise role of six6 in shaping polygenic morphological traits, as its specific contribution remains unresolved. Expanding the scope of analysis to include the effects of additional genes could yield a more comprehensive understanding of genotype-phenotype relationships. Investigating additional developmental stages, across an extended days-post-hatching timeline, may offer deeper insights into the influence of six6 genetic variation on early morphological development in European seabass. Future studies should consider advancing beyond traditional two-dimensional morphometrics, for example, by employing three-dimensional imaging techniques, providing a more accurate representation of morphology. The current study analyzed only 109 larvae and 125 juveniles from a single hatchery, which restricts the generalizability of the findings across broader populations and environmental contexts. To improve the robustness and applicability of future results, we recommend increasing the sample size and including individuals from multiple hatcheries across Europe. Additionally, expanding the number of genetic markers assessed at these developmental stages could help uncover more pronounced patterns of variation. Notably, specimens with the AA-CC (juveniles) and AT-TT (larvae) haplogenotypes seem to have characteristics typically preferred by consumers, such as increased body length and height, traits that could also inform selective breeding strategies. Finally, increasing the sample size of each six6 SNP genotype could reinforce the robustness of our findings.

5. Conclusions

In conclusion, this study examined the impact of different six6 haplogenotypes on the morphology of larvae and juvenile European seabass. These findings highlight stage-specific genotype effects on body length, height, caudal fin shape, and eye size. Notably, these results align with existing genotypic and expression data showing the gene’s evolutionary conservation across fish species and its stage-specific roles during development. Significant morphological differentiation was observed among haplogenotypes, with greater differentiation in juveniles compared to larvae. AT-TT haplogenotype showed increased overall size (length and height) in larvae and greater body height in juveniles. Juveniles with homozygous haplogenotypes (AA-CC and TT-TT) showed increased body length. Additionally, the domestication-associated AT-TT haplogenotype was linked to reduced eye size in juveniles. This is the first study to link genetic variants to morphological outcomes in seabass, providing a valuable foundation for future functional genomics and selective breeding strategies in Mediterranean aquaculture. Future research should expand the developmental scope, incorporate three-dimensional imaging, increase sample size, and include additional genetic markers, among others. These efforts will be essential for validating the current findings and deepening our understanding of the genetic mechanisms underlying domesticated phenotypes in cultured fish, ultimately contributing to improved breeding strategies in aquaculture.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/fishes10080416/s1, Figure S1: Plot of the measured variables (for codes and explanations see Table S1), for PC I and PC II by running a principal component analysis (PCA) on the overlapping morphometric characteristics and haplogenotypes between the two developmental stages for (a) the larval stage and (b) the juvenile stage; Figure S2: Box plots of the morphometric characteristics as derived from the Kruskal–Wallis test for the larval (a,b) and juvenile (c,d) European seabass specimens, when analyzing the overlapping morphometric distances and haplogenotypes of the two developmental stages. The box plot presents the median of each fish length and height for every haplogenotype in cm: (a) fork length in larvae (D2), (b) distance from the second dorsal fin anterior limit to the lower limit of gill cover in larvae (D16), (c) fork length in juveniles (D2), and (d) distance from the second dorsal fin anterior limit to the lower limit of gill cover in juveniles (D16). Each haplogenotype pair with a statistically significant difference is marked with asterisks (** p ≤ 0.01). Table S1: The morphometric characteristics analyzed of Dicentrarchus labrax at 34 days post-hatching (dph; larval stage) and 71 dph (juvenile stage); Table S2: Total variance explained of principal component analysis (PCA) on larvae Dicentrarchus labrax specimens for each principal component. The principal components with an eigenvalue greater than one were considered statistically significant; Table S3: Factor loadings of principal component analysis (PCA) on larvae Dicentrarchus labrax specimens for each morphometric variable (for codes and explanations, see Table S1) on the five extracted PCA factors. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers; Table S4: Total variance explained of principal component analysis (PCA) on juvenile Dicentrarchus labrax specimens for each principal component. The principal components with an eigenvalue greater than one were considered statistically significant; Table S5: Factor loadings of principal component analysis (PCA) on juvenile Dicentrarchus labrax specimens for each morphometric variable (for codes and explanations, see Table S1) on the seven extracted PCA factors. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers; Table S6: Total variance explained of principal component analysis (PCA) on larvae and juvenile Dicentrarchus labrax specimens when comparing the two developmental stages. Each principal component with an eigenvalue greater than one was considered statistically significant; Table S7: Factor loadings of principal component analysis (PCA) on larvae (34 dph) and juveniles (71 dph) Dicentrarchus labrax specimens for each morphometric variable (for codes and explanations, see Table S1) on the six extracted PCA factors after analyzing the overlapping morphometric traits and haplogenotypes. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers; Table S8: Position of group centroids in discriminant function analysis (DFA) on larvae (36 dph) and juvenile (71 dph) specimens when investigating the comparable discriminatory capacity between the two developmental stages; Table S9: Classification results from the discriminant function analysis (DFA) on larvae and juvenile Dicentrarchus labrax specimens when analyzing the overlapping morphometric distances and haplogenotypes of the two developmental stages. The DFA yielded a high overall classification accuracy of 69.7% in larvae specimens, while juveniles exhibited a higher repositioning rate of 75%. Particularly strong separation is noted between AT-CT and TT-TT individuals at the larval stage, but between AT-CT and AT-TT at the juvenile stage; Table S10: Significant associations between genotype combinations (haplogenotypes) of six6 SNPs and morphological traits in European seabass larval and juvenile specimens, as derived from the Kruskal–Wallis test when analyzing the overlapping haplogenotypes and characteristics of the two developmental stages. The table presents pairwise comparisons between haplogenotypes (AT-CT, AT-TT, TT–TT) and their corresponding significance levels (p-values). Only statistically significant differences (p < 0.007) are shown, after correcting with multiple hypothesis tests. Morphological trait distance variables correspond to descriptors detailed in Table S1.

Author Contributions

Conceptualization, A.T. and S.P.; methodology, M.P., A.M., I.G., I.V., K.T., K.G., A.L., N.K., E.A., A.T., S.P. and I.L.; software, M.P., I.G.; validation, S.P. and I.L.; formal analysis, M.P., A.M., I.G., I.V.; investigation, M.P., A.M., I.G., A.T., S.P. and I.L.; resources, S.P.; data curation, M.P., A.M., I.G., I.V., S.P. and I.L.; writing—original draft preparation, M.P., A.M., S.P. and I.L.; writing—review and editing, I.G., I.V., K.T., K.G., A.L., N.K., E.A., A.T.; visualization, M.P., A.M., I.G., A.T., S.P. and I.L.; supervision, E.A., A.T., S.P. and I.L.; project administration, K.G., A.T. and S.P.; funding acquisition, A.T. and S.P. All authors have read and agreed to the published version of the manuscript.

Funding

This study was conducted under the project “SEaLIFT: SystEms Biology Modelling of Key LIFe History Traits for Sustainable Aquaculture Production in the Mediterranean Region,” funded by the Hellenic Foundation for Research and Innovation (H.F.R.I.) Grant Number 00414.

Institutional Review Board Statement

The “Principles and Procedures Governing the Operation of the Research Ethics Committee” of the University in which the research was conducted (Aristotle University of Thessaloniki). This regulation is drafted by the provisions of Article 68, Law 4485/2017, and Articles 21–27, Law 4521/2018 of Greece, an EU member country. Article 25 of the regulation (“Research Involving the Use of Animals”) states that the implementation of our experimental protocols did not use endangered species or wildlife animals (i.e., aquaculture-reared fish) and is part of routine practice in aquaculture practice (Article 25, Section 5.d); such procedures do not require approval.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (a) Landmarks taken on Dicentrarchus labrax 34 dph. The code for each morphometric distance between individual landmarks (in parentheses) is as follows: D1 (L1–L2), D2 (L1–L3), D3 (L1–L4), D4 (L1–L5), D5 (L3–L5), D6 (L3–L4), D7 (L6–L8), D8 (L6–L7), D9 (L8–L9), D10 (L10–L11), D11 (L12–L13), D12 (L10–L12), D13 (L10–L13), D14 (L11–L12), D15 (L11–L13), D16 (L10–L18), D17 (L18–L12), D18 (L14–15), D19 (L16–L17), D20 (L1–L18). (b) Landmarks taken on Dicentrarchus labrax 71 dph. The code for each morphometric distance between individual landmarks (in parentheses) is as follows: D1 (L1–L2), D2 (L1–L3), D3 (L1–L4), D4 (L1–L5), D5 (L3–L5), D6 (L3–L4), D7 (L6–L8), D8 (L6–L7), D9 (L8–L9), D10 (L10–L11), D11 (L12–L13), D12 (L10–L12), D13 (L10–L13), D14 (L11–L12), D15 (L11–L13), D16 (L10–L18), D17 (L18–L12), D18 (L14–L15), D19 (L16–L17), D20 (L1–L18), D21 (L19–L20), D22 (L19–L12), D23 (L19–L13), D24 (L20–L12), D25 (L20–L13), D26 (L19–18).
Figure 1. (a) Landmarks taken on Dicentrarchus labrax 34 dph. The code for each morphometric distance between individual landmarks (in parentheses) is as follows: D1 (L1–L2), D2 (L1–L3), D3 (L1–L4), D4 (L1–L5), D5 (L3–L5), D6 (L3–L4), D7 (L6–L8), D8 (L6–L7), D9 (L8–L9), D10 (L10–L11), D11 (L12–L13), D12 (L10–L12), D13 (L10–L13), D14 (L11–L12), D15 (L11–L13), D16 (L10–L18), D17 (L18–L12), D18 (L14–15), D19 (L16–L17), D20 (L1–L18). (b) Landmarks taken on Dicentrarchus labrax 71 dph. The code for each morphometric distance between individual landmarks (in parentheses) is as follows: D1 (L1–L2), D2 (L1–L3), D3 (L1–L4), D4 (L1–L5), D5 (L3–L5), D6 (L3–L4), D7 (L6–L8), D8 (L6–L7), D9 (L8–L9), D10 (L10–L11), D11 (L12–L13), D12 (L10–L12), D13 (L10–L13), D14 (L11–L12), D15 (L11–L13), D16 (L10–L18), D17 (L18–L12), D18 (L14–L15), D19 (L16–L17), D20 (L1–L18), D21 (L19–L20), D22 (L19–L12), D23 (L19–L13), D24 (L20–L12), D25 (L20–L13), D26 (L19–18).
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Figure 2. Plot of the measured variables (for codes and explanations, see Figure 1) for PC I and PC II (a) by analyzing the larvae specimens and (b) by analyzing the juvenile specimens of Dicentrarchus labrax.
Figure 2. Plot of the measured variables (for codes and explanations, see Figure 1) for PC I and PC II (a) by analyzing the larvae specimens and (b) by analyzing the juvenile specimens of Dicentrarchus labrax.
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Figure 3. Scatter plots of discriminant function analysis scores (DFA I and DFA II only) for (a) the larvae specimens, (b) the juvenile specimens, (c) the larvae specimens of Dicentrarchus labrax by running discriminant function analysis (DFA) on the overlapping morphometric characteristics and haplogenotypes between the two developmental stages, and (d) the juvenile specimens by running a DFA on the overlapping morphometric characteristics and haplogenotypes between the two developmental stages. DFA I and II: first and second functions of discriminant analysis; burgundy square (Fishes 10 00416 i001), each group centroid; inverted triangle (Fishes 10 00416 i002), AA-CC haplogenotype; pentagon (Fishes 10 00416 i003), AA-CT haplogenotype; circle (Fishes 10 00416 i004), AA-TT haplogenotype; rhombus (Fishes 10 00416 i005), AT-CT haplogenotype; rectangle (Fishes 10 00416 i006), AT-TT haplogenotype; triangle (Fishes 10 00416 i007), TT-TT haplogenotype.
Figure 3. Scatter plots of discriminant function analysis scores (DFA I and DFA II only) for (a) the larvae specimens, (b) the juvenile specimens, (c) the larvae specimens of Dicentrarchus labrax by running discriminant function analysis (DFA) on the overlapping morphometric characteristics and haplogenotypes between the two developmental stages, and (d) the juvenile specimens by running a DFA on the overlapping morphometric characteristics and haplogenotypes between the two developmental stages. DFA I and II: first and second functions of discriminant analysis; burgundy square (Fishes 10 00416 i001), each group centroid; inverted triangle (Fishes 10 00416 i002), AA-CC haplogenotype; pentagon (Fishes 10 00416 i003), AA-CT haplogenotype; circle (Fishes 10 00416 i004), AA-TT haplogenotype; rhombus (Fishes 10 00416 i005), AT-CT haplogenotype; rectangle (Fishes 10 00416 i006), AT-TT haplogenotype; triangle (Fishes 10 00416 i007), TT-TT haplogenotype.
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Fishes 10 00416 g004
Figure 4. Box plots of the morphometric characteristics (for codes and explanations, see Figure 1) associated with the fish length and height as derived from the Kruskal–Wallis test for the Dicentrarchus labrax larvae specimens. The box plot presents the median of each fish length and height for every haplogenotype in cm: (a) fork length (D3) and (b) distance from the second dorsal fin anterior limit to the lower limit of gill cover (D16). Each haplogenotype pair with a statistically significant difference is marked with asterisks (** p ≤ 0.01, *** p ≤ 0.001). Small circles represent outliers.
Figure 4. Box plots of the morphometric characteristics (for codes and explanations, see Figure 1) associated with the fish length and height as derived from the Kruskal–Wallis test for the Dicentrarchus labrax larvae specimens. The box plot presents the median of each fish length and height for every haplogenotype in cm: (a) fork length (D3) and (b) distance from the second dorsal fin anterior limit to the lower limit of gill cover (D16). Each haplogenotype pair with a statistically significant difference is marked with asterisks (** p ≤ 0.01, *** p ≤ 0.001). Small circles represent outliers.
Fishes 10 00416 g004
Fishes 10 00416 g005aFishes 10 00416 g005b
Figure 5. Box plots of the morphometric characteristics (for codes and explanations, see Figure 1) as derived from the Kruskal–Wallis test for the Dicentrarchus labrax juvenile specimens. The box plot presents the median of each morphometric distance for every haplogenotype in cm: (a) fork length (D3), (b) fork tail length (D6), (c) horizontal eye diameter (D18), and (d) distance from first dorsal fin anterior limit to anal fin posterior limit (D23). Each haplogenotype pair with a statistically significant difference is marked with asterisks (** p ≤ 0.01, *** p ≤ 0.001). Small circles represent outliers.
Figure 5. Box plots of the morphometric characteristics (for codes and explanations, see Figure 1) as derived from the Kruskal–Wallis test for the Dicentrarchus labrax juvenile specimens. The box plot presents the median of each morphometric distance for every haplogenotype in cm: (a) fork length (D3), (b) fork tail length (D6), (c) horizontal eye diameter (D18), and (d) distance from first dorsal fin anterior limit to anal fin posterior limit (D23). Each haplogenotype pair with a statistically significant difference is marked with asterisks (** p ≤ 0.01, *** p ≤ 0.001). Small circles represent outliers.
Fishes 10 00416 g005aFishes 10 00416 g005b
Table 1. Number of the analyzed individuals per haplogenotype of European sea bass. The haplogenotypes are classified according to the two SNPs in the six6 gene (region 12:11591053–12:11591093, based on the GCA_000689215.1 assembly). dph: days post-hatching.
Table 1. Number of the analyzed individuals per haplogenotype of European sea bass. The haplogenotypes are classified according to the two SNPs in the six6 gene (region 12:11591053–12:11591093, based on the GCA_000689215.1 assembly). dph: days post-hatching.
Haplogenotypes34 dph71 dph
AA-CC-18
AA-CT-15
AA-TT30-
AT-CT1930
AT-TT3030
TT-TT3032
Table 2. Factor loadings of principal component analysis (PCA) on Dicentrarchus labrax larvae specimens for each morphometric variable (for codes and explanations, see Figure 1) on the first two extracted PCA factors. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers.
Table 2. Factor loadings of principal component analysis (PCA) on Dicentrarchus labrax larvae specimens for each morphometric variable (for codes and explanations, see Figure 1) on the first two extracted PCA factors. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers.
Distance VariablesPC IPC II
D10.366−0.012
D30.877−0.192
D40.926−0.218
D50.925−0.221
D60.883−0.186
D70.1530.005
D80.554−0.019
D90.5100.033
D100.0570.601
D110.2120.590
D120.4950.240
D130.3070.659
D140.3630.516
D150.4560.084
D160.243−0.804
D170.118−0.728
D180.3880.080
D190.5890.131
D200.2900.696
Table 3. Position of group centroids in discriminant function analysis (DFA) on larvae Dicentrarchus labrax specimens. DFA I, DFA II, and DFA III represent the first, second, and third discriminant functions, respectively.
Table 3. Position of group centroids in discriminant function analysis (DFA) on larvae Dicentrarchus labrax specimens. DFA I, DFA II, and DFA III represent the first, second, and third discriminant functions, respectively.
HaplogenotypeDFA IDFA IIDFA III
AA-TT1.598−0.490−0.132
AT-CT0.9021.2040.105
AT-TT−0.881−0.2030.680
TT-TT−1.2580.004−0.585
Table 4. Classification results from the discriminant function analysis (DFA) on larvae Dicentrarchus labrax specimens. The DFA yielded a high overall classification accuracy of 71.7%. More specifically, AA-TT larvae were correctly classified to the same haplogenotype by 90%, while 10% were repositioned to the TT-TT haplogenotype. AT-CT larvae were correctly classified to the same haplogenotype by 52.9%. AT-TT larvae were correctly classified to the same haplogenotype by 69%, and 20.7% were repositioned to the TT-TT haplogenotype. TT-TT specimens were correctly repositioned by 66.7%, but 20% were classified under the AT-TT haplogenotype.
Table 4. Classification results from the discriminant function analysis (DFA) on larvae Dicentrarchus labrax specimens. The DFA yielded a high overall classification accuracy of 71.7%. More specifically, AA-TT larvae were correctly classified to the same haplogenotype by 90%, while 10% were repositioned to the TT-TT haplogenotype. AT-CT larvae were correctly classified to the same haplogenotype by 52.9%. AT-TT larvae were correctly classified to the same haplogenotype by 69%, and 20.7% were repositioned to the TT-TT haplogenotype. TT-TT specimens were correctly repositioned by 66.7%, but 20% were classified under the AT-TT haplogenotype.
Predicted Group Membership (%)
HaplogenotypeAA-TTAT-CTAT-TTTT-TT
Original Count (%)AA-TT90.00.00.010.0
AT-CT23.552.911.811.8
AT-TT6.93.469.020.7
TT-TT6.96.720.066.7
Table 5. Significant associations between genotype combinations (haplogenotypes) of six6 SNPs and morphological traits in European seabass larval specimens as derived from the Kruskal–Wallis test. The table presents pairwise comparisons between haplogenotypes (AA–TT, AT–CT, AT–TT, TT–TT) and their corresponding significance levels (p-values). Only statistically significant differences (p < 0.0036) are shown, after correcting for multiple hypothesis tests. Morphological trait distance variables correspond to descriptors detailed in Figure 1a. The symbol ☒ indicates a statistically significant difference between the compared haplogenotype pairs.
Table 5. Significant associations between genotype combinations (haplogenotypes) of six6 SNPs and morphological traits in European seabass larval specimens as derived from the Kruskal–Wallis test. The table presents pairwise comparisons between haplogenotypes (AA–TT, AT–CT, AT–TT, TT–TT) and their corresponding significance levels (p-values). Only statistically significant differences (p < 0.0036) are shown, after correcting for multiple hypothesis tests. Morphological trait distance variables correspond to descriptors detailed in Figure 1a. The symbol ☒ indicates a statistically significant difference between the compared haplogenotype pairs.
Distance VariablesAA-TTAT-CTAT-TTTT-TTp-Value
D3 ☒☒ 0.003
D5☒ ☒ 0.003
D6 ☒☒ 0.003
D16 ☒☒ <0.001
☒ ☒0.002
☒ ☒ <0.001
☒ ☒<0.001
D17 ☒☒ <0.001
☒ ☒ <0.001
☒ ☒0.001
D20 ☒☒ 0.002
☒ ☒<0.001
☒ ☒ <0.001
☒ ☒<0.001
Table 6. Factor loadings of principal component analysis (PCA) on Dicentrarchus labrax juvenile specimens for each morphometric variable (for codes and explanations, see Figure 1) on the first two extracted PCA factors. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers.
Table 6. Factor loadings of principal component analysis (PCA) on Dicentrarchus labrax juvenile specimens for each morphometric variable (for codes and explanations, see Figure 1) on the first two extracted PCA factors. The statistically significant values (those with an absolute value greater than 0.50) are shown in bold numbers.
Distance VariablesPC IPC II
D10.4660.204
D30.7330.277
D40.7260.379
D50.7340.379
D60.7380.286
D70.1550.452
D80.5490.403
D90.6550.251
D10−0.4200.319
D11−0.0700.155
D12−0.1800.815
D13−0.4300.672
D14−0.2300.493
D15−0.0900.557
D16−0.3500.032
D17−0.430−0.100
D180.5300.116
D190.4110.437
D200.4730.166
D21−0.3500.673
D220.3230.081
D23−0.5200.548
D24−0.4700.618
D25−0.6900.430
D26−0.1900.247
Table 7. Position of group centroids in discriminant function analysis (DFA) on juvenile Dicentrarchus labrax specimens.
Table 7. Position of group centroids in discriminant function analysis (DFA) on juvenile Dicentrarchus labrax specimens.
HaplogenotypeDFA IDFA IIDFA IIIDFA IV
AA-CC1.4360.5811.3490.448
AA-CT1.525−0.242−0.271−1.063
AT-CT0.4390.146−0.9890.438
AT-TT−1.1960.9070.112−0.245
TT-TT−0.630−1.1530.3090.074
Table 8. Classification results from the discriminant function analysis (DFA) on juvenile Dicentrarchus labrax specimens. The discriminant analysis yielded a high overall classification accuracy of 73.6%, with particularly strong separation between AT-TT and the rest of the haplogenotypes. AA-CC larvae were correctly classified as the same haplogenotype by 73.3%, while 20% were repositioned to the TT-TT haplogenotype. AA-CT larvae were correctly classified to the same haplogenotype by 57.1%. AT-CT specimens were correctly repositioned by 70%, but 10% were classified under AA-CT or AT-TT haplogenotype. TT-TT specimens were correctly repositioned by 71.9%.
Table 8. Classification results from the discriminant function analysis (DFA) on juvenile Dicentrarchus labrax specimens. The discriminant analysis yielded a high overall classification accuracy of 73.6%, with particularly strong separation between AT-TT and the rest of the haplogenotypes. AA-CC larvae were correctly classified as the same haplogenotype by 73.3%, while 20% were repositioned to the TT-TT haplogenotype. AA-CT larvae were correctly classified to the same haplogenotype by 57.1%. AT-CT specimens were correctly repositioned by 70%, but 10% were classified under AA-CT or AT-TT haplogenotype. TT-TT specimens were correctly repositioned by 71.9%.
Predicted Group Membership (%)
HaplogenotypeAA-CCAA-CTAT-CTAT-TTTT-TT
Original Count (%)AA-CC73.30.06.70.020.0
AA-CT21.457.114.37.10.0
AT-CT6.710.070.010.03.3
AT-TT3.33.33.386.76.7
TT-TT3.112.512.56.371.9
Table 9. Significant associations between genotype combinations (haplogenotypes) of six6 SNPs and morphological traits in European seabass juvenile specimens as derived from the Kruskal–Wallis test. The table presents pairwise comparisons between genotypes (AA-CC, AA-CT, AT-CT, AT-TT, TT-TT) and their corresponding significance levels (p-values). Only statistically significant differences (p < 0.0036) are shown, after correcting for multiple hypothesis tests. Morphological trait distance variables correspond to descriptors detailed in Figure 1b. The symbol ☒ indicates a statistically significant difference between the compared haplogenotype pairs.
Table 9. Significant associations between genotype combinations (haplogenotypes) of six6 SNPs and morphological traits in European seabass juvenile specimens as derived from the Kruskal–Wallis test. The table presents pairwise comparisons between genotypes (AA-CC, AA-CT, AT-CT, AT-TT, TT-TT) and their corresponding significance levels (p-values). Only statistically significant differences (p < 0.0036) are shown, after correcting for multiple hypothesis tests. Morphological trait distance variables correspond to descriptors detailed in Figure 1b. The symbol ☒ indicates a statistically significant difference between the compared haplogenotype pairs.
Distance VariablesAA-CCAA-CTAT-CTAT-TTTT-TTp-Value
D3☒ ☒ <0.001
☒ ☒ 0.001
☒☒<0.001
D6☒ ☒ <0.001
☒ ☒ 0.002
☒☒0.001
D18☒ ☒ 0.002
☒ ☒ 0.003
D23☒ ☒ 0.002
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Papamichail, M.; Moulistanos, A.; Georgatis, I.; Vagia, I.; Tasiouli, K.; Gkagkavouzis, K.; Laggis, A.; Karaiskou, N.; Antonopoulou, E.; Triantafyllidis, A.; et al. Investigating the Impact of six6 Genetic Variation on Morphological Traits in Larvae and Juveniles of European Seabass (Dicentrarchus labrax Linnaeus). Fishes 2025, 10, 416. https://doi.org/10.3390/fishes10080416

AMA Style

Papamichail M, Moulistanos A, Georgatis I, Vagia I, Tasiouli K, Gkagkavouzis K, Laggis A, Karaiskou N, Antonopoulou E, Triantafyllidis A, et al. Investigating the Impact of six6 Genetic Variation on Morphological Traits in Larvae and Juveniles of European Seabass (Dicentrarchus labrax Linnaeus). Fishes. 2025; 10(8):416. https://doi.org/10.3390/fishes10080416

Chicago/Turabian Style

Papamichail, Marinina, Aristotelis Moulistanos, Ioannis Georgatis, Ioustini Vagia, Katerina Tasiouli, Konstantinos Gkagkavouzis, Anastasia Laggis, Nikoleta Karaiskou, Efthimia Antonopoulou, Alexandros Triantafyllidis, and et al. 2025. "Investigating the Impact of six6 Genetic Variation on Morphological Traits in Larvae and Juveniles of European Seabass (Dicentrarchus labrax Linnaeus)" Fishes 10, no. 8: 416. https://doi.org/10.3390/fishes10080416

APA Style

Papamichail, M., Moulistanos, A., Georgatis, I., Vagia, I., Tasiouli, K., Gkagkavouzis, K., Laggis, A., Karaiskou, N., Antonopoulou, E., Triantafyllidis, A., Papakostas, S., & Leonardos, I. (2025). Investigating the Impact of six6 Genetic Variation on Morphological Traits in Larvae and Juveniles of European Seabass (Dicentrarchus labrax Linnaeus). Fishes, 10(8), 416. https://doi.org/10.3390/fishes10080416

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