Influences of Size-Selective Harvesting on Growth Characteristics and Associated Gene Expression Patterns in Marine Medaka (Oryzias melastigma)

Influences of Size-Selective Harvesting on Growth Characteristics and Associated Gene Expression Patterns in Marine Medaka (Oryzias melastigma) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Influences of Size-Selective Harvesting on Growth Characteristics and Associated Gene Expression Patterns in Marine Medaka (Oryzias melastigma) Chengcheng Su, Shuo Li, Yunlong Chen, Xianshi Jin, Changwei Shao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7708251/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Jan, 2026 Read the published version in Marine Biotechnology → Version 1 posted 9 You are reading this latest preprint version Abstract Fisheries-induced evolution (FIE) poses a critical threat to global fisheries sustainability, but the molecular mechanisms that translate harvesting pressure into rapid, heritable trait changes remain largely unknown. Here, using a multi-generational experimental evolution approach with the marine medaka ( Oryzias melastigma ), we demonstrate that size-selective harvesting drives profound phenotypic divergence within just two generations. This evolutionary response is directly underpinned by the heritable reprogramming of the core growth hormone/insulin-like growth factor (GH/IGF) axis. Strikingly, selection for large body size led to an upregulation of gh gene expression by several orders of magnitude, cementing this pathway as a primary target of selection. Conversely, intense selection against large size prompted a complex adaptive response involving a shift in body allometry rather than a simple reduction in size, suggesting the influence of underlying physiological constraints. Our findings establish heritable gene expression reprogramming as a key rapid mechanism for FIE, providing a crucial mechanistic foundation for developing evolution-aware strategies for sustainable fisheries management. Size-selective harvesting Oryzias melastigma Growth hormone Growth trait Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Overfishing is a primary driver of ecological imbalance in marine ecosystems, and its evolutionary consequences represent a significant, yet often overlooked, threat (Dulvy et al., 2021 ). Beyond simple population depletion, intense, size-selective harvesting acts as a powerful evolutionary force, inducing rapid genetic changes in targeted stocks — a phenomenon known as Fisheries-Induced Evolution (FIE) (Heino et al., 2015 ; Hollins et al., 2018 ). Decades of field observations and laboratory experiments have provided compelling evidence for FIE across a range of species. For instance, classic experimental harvesting on the Atlantic silverside ( Menidia menidia ) resulted in significant divergence in growth rates and allele frequencies within just a few generations (Conover and Munch, 2002 ; Therkildsen et al., 2019 ). Similar rapid shifts towards smaller body size and earlier maturation have been documented in species from guppies ( Poecilia reticulata ) to zebrafish ( Danio rerio ) (Dunlop et al., 2015 ; Uusi-Heikkilä et al., 2015 ; Uusi-Heikkilä, 2020 ). These evolutionary changes are not benign; they can erode the genetic potential of populations, leading to reduced productivity and compromising their ability to recover, thereby posing a significant threat to fishery sustainability (Jørgensen et al., 2007 ; Dunlop et al., 2009 ; Hutchings and Kuparinen, 2020 ). Despite the well-documented phenotypic consequences of FIE, the underlying molecular mechanisms that translate harvesting pressure into heritable traits remain a critical black box, hindering our ability to predict and mitigate these detrimental evolutionary trajectories (Heino and Dieckmann, 2008 ). To illuminate this black box, we targeted the master regulatory pathway of vertebrate growth. Given that size-selective harvesting directly acts on somatic growth, we hypothesized that FIE is primarily mediated through heritable alterations in the growth hormone (GH) / insulin-like growth factor (IGF) axis (Reindl and Sheridan, 2012 ; Ahti et al., 2020 ). This endocrine system fundamentally links genetic information to an organism's growth trajectory, which is then subject to selection (Pérez-Sánchez, 2000 ; Triantaphyllopoulos et al., 2020 ). GH, synthesized in the pituitary, directly stimulates growth via its receptor (GHR) and indirectly promotes hepatic production of IGF1, a potent mitogen (Baker et al., 1993 ; Liu et al., 1993 ). While previous studies have correlated gene expression in this axis with growth rates (Solberg et al., 2012 ; Zhong et al., 2012 ; Ndandala et al., 2022 ; Qing et al., 2024 ), no study has yet established a causal link between a defined selection pressure and the evolution of this pathway's activity. Here, we employ a rigorous experimental evolution approach using the marine medaka ( Oryzias melastigma ) to mechanistically dissect how size-selective harvesting shapes the GH/IGF axis. The short generation time and genetic tractability of this species make it a powerful system for observing evolution in real-time under controlled laboratory conditions (Chen et al., 2009 ; Inoue and Takei, 2002 ; Kim et al., 2018 ). By subjecting replicate populations to two generations of size-selective harvesting, we directly quantified the resulting phenotypic divergence in growth traits. We then integrated these data with expression analyses of key axis genes ( gh , ghr , and igf1 ) to test our central hypothesis. This integrative approach allows us to forge a direct, mechanistic pathway from selection pressure to molecular response, and ultimately, to phenotypic evolution. Our findings provide the evidence that FIE operates by modulating the heritable expression of the GH/IGF axis, offering a molecular-level explanation for this widespread evolutionary phenomenon and laying the groundwork for more sustainable, evolution-aware fisheries management. 2. Materials and Methods 2.1 Size-selective Harvesting and Fish Collection The marine medaka used in this study originated from a stock population from the Yellow Sea Fisheries Research Institute (YSFRI), Chinese Academy of Fishery Sciences (CAFS), maintained in the laboratory for over three generations. Fish were reared under controlled laboratory conditions following established protocols. The animals were housed in 150 L round fiberglass tanks with seawater maintained at a temperature of 26.0 ± 0.5°C, salinity of 29.0 ± 2.0, pH of 7.8 ± 0.1, and dissolved oxygen of 6.0 ± 1.0 mg/L on a 14:10 h light-dark cycle. Ammonia-nitrogen levels were consistently maintained below 0.15 mg/L. Initially, fish were stocked at a density of 2 fish/L to mitigate density-dependent effects. The fish were fed three times a day with a diet of newly hatched Artemia nauplii and commercial flake food (TetraMin, Tetra GmbH). To initiate the multi-generational selection experiment, fertilized eggs from the stock population were collected and incubated at 28°C for 10 days. The resulting F1 generation of juvenile fish was collected and randomly allocated into four experimental regimes, each with three replicate tanks. Each replicate tank was initially stocked with 300 juveniles. Upon reaching sexual maturity, a specific size-selective harvesting strategy was applied to each regime. Following the selection event, eggs were collected from the remaining broodstock, hatched, and 300 F2 larvae were transferred to a new rearing tank to replace the F1 generation. This selection protocol was repeated for two consecutive generations. The four distinct selection regimes were designed to simulate different fishery management strategies (Fig. 1 ): (1) High-intensity, positive size-selection (HB): The largest 90% of individuals, based on body length, were removed, leaving the smallest 10% to reproduce. This protocol simulates an extreme fishing pressure scenario. (2) Medium-intensity, positive size-selection (MB): The largest 75% of individuals were removed, retaining the smallest 25% for breeding. This intensity was chosen to reflect current fishing pressures and management policies that impose minimum size limits (Uusi-Heikkilä et al., 2015 ) (3) Medium-intensity, negative size-selection (MS): The smallest 75% of individuals were removed, thereby preserving the largest 25% for reproduction. This scenario was designed to test the evolutionary consequences of management measures that aim to protect large individuals, contradicting traditional size-selective pressures. (4) Low-intensity, positive size-selection (LB): The largest 50% of individuals were removed, allowing the remaining 50% to breed. This group serves as another reference for the effect of fishing intensity. 2.2 RNA Extraction and cDNA Synthesis This study selected male marine medaka from the F0 generation on various days (40, 60, 80, 100, 120, 140, 160, and 200 days). Each day, nine fish samples were collected for brain analysis. Furthermore, fish aged 60 and 200 days were selected for the collection of gonads, liver, brain, muscles, gills, intestines, skin, and eyes in the F0 generation. In F1 and F2 generations, adult male fish from the HB, MB, MS, and LB treatment groups were selected, with three fish in each group. Brain tissue samples were collected from each chosen individual. Total RNA was isolated from each sample using TRIzol reagent from Invitrogen (Carlsbad, CA, USA). The RNA concentration was measured with a NanoDrop 2000 spectrophotometer from Thermo (Waltham, MA, USA), and the RNA quality was evaluated using agarose gel electrophoresis. The first-strand cDNA was synthesized from purified total RNA using the PrimeScript™ II 1st Strand cDNA Synthesis Kit from Takara (Kusatsu, Japan). 2.3 Cloning of gh The first strand of cDNA was synthesized from purified total RNA using the PrimeScriptTM II 1st Strand cDNA Synthesis Kit (Takara, Kusatsu, Japan). Primers (Table 1 ) were designed based on predicted sequences in the NCBI database to obtain partial cDNA fragments of gh with PCR. The PCR products were detected by agarose gel electrophoresis, and the corresponding band of interest was purified using a product purification kit (Vazyme, Nanjing, China). Finally, the purified fragments were connected to the pEASY-T1 (TransGen, Beijing, China) vector for Sanger sequencing to verify the sequence fidelity. Table 1 The primers for gh cloning and related genes expression analysis. Primer Name Sequence (5′ – 3′) Target Sequence gh -qF GCCATTAACAGAGCCATCCTT RT-qPCR gh -qR CTTGCTGAGTTGACGTTGCT ghr -qF TGGGTGGAGTTCATCGAAGTG ghr -qR CATTAGGGTGGCGGACAGT igf1 -qF CCCGGGCATAGTCATTCATCC igf1 -qR AGGTAAGGCCACTCCCTCAT igfbp1 -qF ATCTTCCCTGAGCAAGGTCCC igfbp1 -qR TCGCAGTTCGGGAGGTAGAA β-actin-qF TATCATTCGCCTGAAACCGAT β-actin-qR CTTTGCACATGCCAGATCCG gh -pF GATTTCAGAGCAGATCCACG Plasmid construction gh -pR TAAAAAGCTGGGCAGTCATC 2.4 Sequence Analysis and Phylogenetic Tree Construction The open reading frame (ORF) of the marine medaka gh gene were predicted using the NCBI ORF Finder tool. The deduced amino acid sequence of the GH protein was used for all subsequent analyses. Physicochemical properties, including theoretical molecular weight, isoelectric point (pI), and grand average of hydropathicity (GRAVY), were calculated using the ExPASy ProtParam tool. Potential post-translational modification sites were predicted from the GH amino acid sequence. Phosphorylation sites on serine, threonine, and tyrosine residues were predicted. The tertiary (3D) structure of the mature GH protein was predicted by homology modeling using the SWISS-MODEL server. To investigate the evolutionary history of GH, orthologous protein sequences from representative vertebrate species were retrieved from the NCBI GenBank database. The collected sequences were aligned using the NCBI Cobalt web server with its default parameters. Based on the resulting alignment, a phylogenetic tree was constructed using the Fast Minimum Evolution (FastME) method, which is integrated into the Cobalt results page. The tree was calculated using the Kimura (protein) distance model. 2.5 Expression of gh gene in Different Fishery Strategies The relative mRNA expression of the gh gene was quantified by quantitative reverse transcription PCR (RT-qPCR). The analysis aimed to characterize its tissue-specific expression profile in F0 males and to evaluate its differential expression in the brains of F1 and F2 males from the different selection regimes. RT-qPCR was performed on a LightCycler® 480 II system (Roche, Basel, Switzerland) using the QuantiNova SYBR Green PCR Kit (Qiagen, Hilden, Germany). Each 10 µL reaction contained 5 µL of 2× SYBR Green PCR Master Mix, 0.4 µL each of the forward and reverse primers (400 nM final concentration), 1 µL of cDNA template, and 3.2 µL of nuclease-free water. The thermal cycling protocol was an initial activation at 95°C for 2 min, followed by 40 cycles of 95°C for 5 s and 60°C for 10 s. The β-actin gene served as an internal reference for normalization (Table 1 ). All assays were conducted with three biological and three technical replicates. Relative gene expression levels were calculated using the 2 −∆∆Ct method. 2.6 Statistical Analysis All statistical analyses were performed using GraphPad Prism 10. Unless otherwise stated, all results are presented as mean ± standard error of the mean (SEM). Differences were considered statistically significant at a p-value < 0.05. To assess the effects of size-selective harvesting on fish growth, phenotypic traits were compared among the four selection regimes. For each generation, a one-way analysis of variance (ANOVA) was used, followed by Tukey's honestly significant difference (HSD) post-hoc test for pairwise comparisons among all four groups. Relative mRNA expression levels were also analyzed. Within each generation, differences in the relative expression of the gh gene among the four selection regimes were tested using a one-way ANOVA followed by Tukey's HSD post-hoc test. All figures were generated using GraphPad Prism and Origin. Gene expression data are visualized as bar charts showing the mean ± SEM, with individual data points overlaid to show the distribution of the data. 3. Results 3.1 Size-Selective Harvesting Rapidly Induces Heritable Phenotypic Divergence Our multi-generational selection experiment demonstrated that simulated harvesting strategies can act as a powerful evolutionary force, inducing rapid and heritable changes in the growth phenotypes of marine medaka. After a single generation of selection (F1), significant differences in body size were already apparent among the treatment groups (Fig. 2 A). Fish from the negative selection line (MS), which were selected for large size, exhibited the greatest mean standard length and body weight. Specifically, they were significantly longer ( p < 0.01) and heavier ( p < 0.05) than fish from the high-intensity positive selection line (HB), which were selected for small size. This phenotypic divergence was substantially magnified in the second generation (F2) (Fig. 2 A). The MS line became markedly larger than all other groups, showing a highly significant difference in both standard length and body weight ( p < 0.0001 for all pairwise comparisons against HB, MB, and LB). Furthermore, a dose-dependent response to positive selection pressure was evident in the F2 generation's body weight, with the HB line being significantly smaller than the MB line ( p < 0.01). Crucially, intergenerational analysis confirmed that these phenotypic shifts were heritable and uncovered an interesting divergence in evolutionary strategies. As hypothesized, the MS line responded directly to the selection pressure for largeness, with F2 individuals becoming significantly longer ( p < 0.01) and heavier ( p < 0.05) than their F1 predecessors (Fig. 2 B). This demonstrates a classic and successful response to artificial selection. In stark contrast, the intense harvesting pressure in the HB line, which targeted the smallest 10% for breeding, resulted in a counter-intuitive evolutionary trajectory. Instead of evolving towards a smaller body size, F2 fish in the HB line became significantly longer than their F1 counterparts ( p < 0.05), while exhibiting no corresponding change in body weight (Fig. 2 B). This decoupling of length and weight gain strongly suggests a rapid adaptive shift in body allometry—the evolution of a more slender, gaunt phenotype. This finding indicates that under intense pressure to mature at a small size, the fish did not simply shrink but fundamentally altered their growth strategy. 3.2 Cloning and Molecular Characterization of Marine Medaka gh We successfully cloned the full-length cDNA of the marine medaka gh gene. The sequence contains a 633 bp ORF that encodes a 210-amino acid protein. This deduced GH protein has a predicted molecular mass of 23.53 kDa and a theoretical isoelectric point of 6.51. Bioinformatic analysis of the amino acid sequence revealed hallmark features consistent with a secreted peptide hormone. The protein is predicted to be hydrophilic (grand average of hydropathicity: -0.075) and possesses a canonical N-terminal signal peptide with a predicted cleavage site after Serine 23, indicating its entry into the secretory pathway (Fig. 3 ). Furthermore, the sequence contains 26 potential phosphorylation sites for various kinases, suggesting that GH activity is likely regulated by post-translational modifications. The protein was, however, predicted to be unstable in vitro, with an instability index of 51.78. Finally, homology modeling predicted that the marine medaka GH protein adopts the classic four-helix bundle structure characteristic of the vertebrate growth hormone family (Fig. 3 ). This structural conservation, combined with the presence of a signal peptide, confirms the identity of the cloned sequence as a bona fide growth hormone. 3.3 GH Sequence Conservation and Phylogenetic Position To assess the conservation of the newly identified growth hormone, we aligned its protein sequence with orthologs from other teleost fishes. The alignment revealed substantial sequence conservation across these species (Fig. 4 A). Several sequence blocks, particularly in the central and C-terminal portions of the protein, showed near-perfect identity. This high degree of conservation in specific regions suggests they are under strong functional constraint. Phylogenetic analysis was then conducted to resolve the evolutionary placement of the marine medaka GH within the broader vertebrate context. The resulting tree robustly recapitulated the known evolutionary relationships between major vertebrate lineages, showing a clear and deep divergence between the teleost fish and the tetrapod clades (Fig. 4 B). As hypothesized, the marine medaka GH clustered firmly within the teleost fish group. More specifically, it formed a well-supported sister-group relationship with the GH from its close relative, the Japanese medaka ( Oryzias latipes ). This placement, nested within the spiny-rayed fishes, is fully consistent with established species phylogeny and confirms the evolutionary identity of our cloned sequence. 3.4 Spatiotemporal Expression Profile of gh and ghr To determine the spatial expression pattern of gh , we performed RT-qPCR on a panel of tissues from adult male medaka. The analysis revealed that gh expression is highly tissue specific. Its mRNA transcripts were detected at substantially and significantly higher levels in the brain compared to all other tissues examined (gonad, liver, muscle, gills, intestine, skin, and eyes), where expression was negligible ( p < 0.0001) (Fig. 5 A). This brain-specific expression pattern was consistent in fish at both 60- and 200-days post-hatch. We next examined the temporal expression dynamics of gh and its receptor, ghr , in the brain throughout development, uncovering a tightly coordinated expression pattern (Fig. 5 B). Both genes exhibited a distinct bimodal expression profile. The expression of gh showed two significant peaks around day 60 and day 100. Specifically, its expression at day 100 was significantly higher than at the initial 40-day timepoint and the subsequent trough at day 80. A similar peak was observed at day 60. Remarkably, the expression profile of ghr , almost perfectly mirrored that of its ligand. It displayed a major peak at day 60, which was significantly higher than all other time points, and a second prominent peak at day 100. These two peaks were separated by a significant drop in expression at day 80. This highly synchronized expression dynamic, with both genes peaking and troughing at nearly identical developmental stages, strongly suggests a functional co-regulation of the GH/GHR axis during key periods of post-larval development and maturation in marine medaka. 3.5 Selection Regimes Induce Divergent and Heritable Reprogramming of the GH/IGF Axis To uncover the molecular mechanisms driving the observed phenotypic divergence, we quantified the expression of key genes in the GH/IGF axis. Our results reveal that the size-selective harvesting strategies induced a profound, divergent, and heritable reprogramming of this critical growth pathway (Fig. 7 ). A consistent and striking pattern emerged across the axis: selection for large size (MS) robustly upregulated gene expression, while selection for small size (HB) led to its suppression. In the F1 generation, the expression of both gh and its receptor ghr was already significantly higher in the MS compared to the HB. This divergent response was dramatically amplified in the F2 generation, providing powerful evidence of a rapid, heritable evolutionary change at the molecular level. Most notably, the expression of gh in the F2 MS was upregulated by several orders of magnitude compared to the F1 generation, reaching levels thousands of times higher than in the HB. This massive induction was mirrored by other key axis genes. The expression of ghr and the downstream gene igfbp1 were also significantly higher in the F2 MS and MB compared to the low-expression HB and LB. Interestingly, the expression of igf1 showed a more complex pattern, with the MB line exhibiting the highest expression in the F2 generation. Nevertheless, the predominant signal across the entire GH/IGF axis is one of coordinated and heritable reprogramming, directly reflecting the direction and intensity of the applied selection pressure. 4. Discussion Fisheries-induced evolution is widely recognized as a potent force reshaping wild populations, yet the molecular engines driving these rapid phenotypic shifts have remained largely a black box. Our study provides the direct experimental evidence that this evolution is driven by the rapid and heritable reprogramming of the core GH/GHR growth axis. By demonstrating a clear causal chain—from a simulated harvesting pressure to altered gene expression and consequent phenotypic divergence—we fill a critical mechanistic gap at the intersection of evolutionary biology and fisheries science. This work transitions the understanding of FIE from a pattern of observation to a process rooted in predictable molecular physiology. The most direct evidence for this mechanistic link comes from the strong positive correlation we observed between selection for large body size, the upregulation of the GH/GHR axis, and the resulting acceleration in growth. This was most pronounced in our MS group, where two generations of selection favoring the largest individuals resulted in F2 fish that not only exhibited a significant increase in body size, but also displayed the highest transcription levels of both gh and its receptor. The tight coupling of this molecular response to the phenotypic outcome was stark: by the F2 generation, fish from the MS line, with their highly active GH/GHR axis, in which the axis was consistently suppressed. This finding—that selection for larger size preferentially propagates individuals with a more active GH/GHR signaling pathway—is consistent with the well-documented positive correlation between gh expression and growth rates in other teleosts, such as larval Japanese puffer ( Takifugu rubripes ) (Kaneko et al., 2011 ), sideromorphic barbel chub ( Squaliobarbus curriculus ) (Wang et al., 2020 ), and juvenile triploid crucian carp ( Carassius auratus ) (Zhong et al., 2012 ). Our study thus provides powerful experimental confirmation that this fundamental endocrine axis is a primary and predictable target that is rapidly modulated by external selective pressures mimicking fisheries harvesting. Interestingly, the evolutionary response to harvesting was markedly asymmetrical. While selection for larger size in the MS group yielded a strong and direct phenotypic and molecular response, the intense pressure against large size in the HB line revealed a more complex evolutionary trajectory. Contrary to the expectation of evolving a smaller, miniaturized body, F2 individuals in the HB group became significantly longer than their F1 predecessors, yet exhibited no corresponding increase in body weight. This decoupling of length and weight gain is a critical finding, strongly indicating a rapid evolutionary shift in body allometry—a trade-off that produces a more slender or gaunt phenotype rather than a simple, proportional reduction in size. This resistance to downward size selection is not unprecedented and aligns with findings from previous experimental evolution studies in zebrafish (Uusi-Heikkilä et al., 2015 ) and Japanese medaka ( Oryzias latipes ) (Renneville et al., 2020 ), which also reported attenuated responses to selection for smaller sizes. Such a pattern suggests the influence of a powerful physiological or genetic constraint, a potential evolutionary floor below which the viability or reproductive success of an individual is critically compromised. When faced with this lower limit, populations may adopt alternative adaptive strategies, such as the alteration in body shape observed here. Our findings contribute a crucial mechanistic layer to the extensive FIE literature. For decades, experimental evolution studies have convincingly demonstrated rapid phenotypic shifts in response to harvesting. For instance, high-intensity harvesting of Atlantic silverside led to a 22% difference in length after just four generations (Conover and Baumann, 2009 ; Conover and Munch, 2002 ), while similar selection experiments on zebrafish and Japanese medaka also produced significant changes in body size over multiple generations (Uusi-Heikkilä et al., 2015 ; Renneville et al., 2020 ). More recently, genomic studies have begun to link these traits to shifts in allele frequencies, confirming a genetic basis for FIE (Audzijonyte et al., 2013 ; Han et al., 2025 ). However, despite this progress, the regulatory mechanisms that bridge the genotype-phenotype gap—explaining how genetic variation is translated into a rapid organismal response—have remained largely elusive. Our work fills this void. We identify the heritable modulation of gene expression within the GH/GHR axis as a primary and powerful response to selection. This suggests that FIE does not solely depend on the slower process of new allele fixation, but can also proceed swiftly via the epigenetic or regulatory inheritance of expression patterns in key physiological pathways, providing a compelling explanation for the remarkably high rates of evolution observed in exploited fish stocks. While our study establishes a clear mechanistic link between harvesting pressure and the evolution of its underlying molecular machinery, we acknowledge its limitations and the exciting avenues they open for future research. Our experiment was conducted over two generations, capturing the critical initial stages of evolutionary response. Future work should extend this framework over more generations to investigate the long-term stability of these reprogrammed expression patterns and, crucially, to explore their potential for reversal—a topic of intense debate and immense importance for fisheries management. Furthermore, while we focused on the core GH/GHR axis, a holistic view is needed. Applying transcriptomic (RNA-seq) analysis to key tissues like the brain and liver would uncover the broader gene networks responding to selection. This approach could ultimately allow us to pinpoint the specific regulatory elements, such as SNPs in promoter regions, that anchor these heritable changes in gene expression to the underlying genetic architecture. Integrating such multi-generational and multi-omics approaches will be pivotal in developing truly evolutionarily enlightened strategies for sustainable fisheries. Conclusion In conclusion, our research demonstrates that fisheries-induced evolution is not merely a selective sieve acting on existing phenotypes, but a potent force that actively reshapes the underlying molecular machinery of growth. We establish a direct, causal link between size-selective pressure and the heritable reprogramming of the GH/GHR axis, revealing how selection on an organismal trait can rapidly and divergently alter a core endocrine pathway. This highlights that heritable shifts in gene expression can serve as a primary and rapid engine for evolution in response to intense anthropogenic pressures, supplementing the slower process of allele fixation. Ultimately, this mechanistic insight is a critical step towards predicting the evolutionary trajectories of exploited populations and is fundamental for designing sustainable, evolution-aware management strategies to safeguard global fisheries. Declarations Ethics Approval All experimental procedures involving animals were conducted in accordance with the ethical standards and regulations set forth by the Yellow Sea Fisheries Research Institute, CAFS. This approval certifies that the experimental design adhered to the guidelines for the ethical treatment of animals used in research. Competing Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was funded by the State Key Laboratory of Mariculture Biobreeding and Sustainable Goods Basic Research Experimental Support Grants (BRESG-JB202503), the National Key Research and Development Program 2024YFD2400405, the Special Fund of Taishan Scholar Project(tsqn202103135) and the National Natural Science Foundation of China (42206104). Author Contribution Chengcheng Su: Conceptualization, Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review & editing, Visualization. **Shuo Li:** Conceptualization, Methodology, Formal analysis, Validation, Writing-Review & Editing, Supervision. **Yunlong Chen:** Writing - review & editing, Visualization **. Xianshi Jin:** Data collection, Methodology, Formal analysis, Validation, Writing-Review & Editing, Funding acquisition, Supervision. **Changwei Shao:** Conceptualization, Methodology, Formal analysis, Validation, Writing-Review & Editing, Supervision. **Xiujuan Shan:** Conceptualization, Methodology, Formal analysis, Validation, Writing-Review & Editing, Supervision. Data availability The authors are unable or have chosen not to specify which data has been used. References Ahti PA, Kuparinen A, Uusi-Heikkilä S (2020) Size does matter — the eco-evolutionary effects of changing body size in fish. 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Supplementary Files SupplementTable.docx Cite Share Download PDF Status: Published Journal Publication published 09 Jan, 2026 Read the published version in Marine Biotechnology → Version 1 posted Editorial decision: Revision requested 03 Nov, 2025 Reviews received at journal 30 Oct, 2025 Reviews received at journal 28 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers invited by journal 09 Oct, 2025 Editor assigned by journal 01 Oct, 2025 Submission checks completed at journal 01 Oct, 2025 First submitted to journal 24 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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04:33:15","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112676,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/87e3b0dd1168735e27a28621.html"},{"id":94242917,"identity":"b199553e-439b-49d4-b25c-79be8ddfbc66","added_by":"auto","created_at":"2025-10-24 04:33:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of experimental design. The dark parts represent individuals that remain and are used for offspring reproduction\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/2c435931dbb8a73f791bab1d.png"},{"id":94243463,"identity":"9ef1cf1b-4539-47d4-9870-d4f2f63c73d4","added_by":"auto","created_at":"2025-10-24 04:41:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2850168,"visible":true,"origin":"","legend":"\u003cp\u003eIntergenerational differences in standard length and body weight of fish in the same fishing strategy. HB: High-intensity, positive size-selection, MB: Medium-intensity, positive size-selection, MS: Medium-intensity, negative size-selection, LB: Low-intensity, positive size-selection. Standard length and body weight were expressed as mean ± SD, respectively (\u003cem\u003en\u003c/em\u003e=3).\u003cstrong\u003e \u003c/strong\u003eAsterisks (*), (**), (***), and (****) indicate significant differences at \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001 and \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.0001 respectively.\u003c/p\u003e","description":"","filename":"Figure.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/fe1e0e1e8e415776e81cdde1.png"},{"id":94242932,"identity":"da3cfb85-26a1-47fb-80ba-61f43bd255f5","added_by":"auto","created_at":"2025-10-24 04:33:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35809996,"visible":true,"origin":"","legend":"\u003cp\u003eSequence analysis and predicted structure of the marine medaka GH. (A) Nucleotide and deduced amino acid sequence of the \u003cem\u003egh\u003c/em\u003e CDS. Nucleotides are numbered on the left. The stop codon is indicated by an asterisk (*). Predicted phosphorylation sites on serine, threonine, and tyrosine residues are highlighted in red, green, and blue boxes, respectively. (B) Predicted 3D structure of the mature GH protein. The serine residue at position 23 (Ser23), which marks the predicted cleavage site for the N-terminal signal peptide, is highlighted in red.\u003c/p\u003e","description":"","filename":"Figure.3.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/6a36c22019509861853338c0.png"},{"id":94242923,"identity":"563556dd-8f99-4c43-8772-d8f96840a71f","added_by":"auto","created_at":"2025-10-24 04:33:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8782628,"visible":true,"origin":"","legend":"\u003cp\u003eSequence alignment and phylogenetic analysis of \u003cem\u003egh\u003c/em\u003e and its homologous genes. \u003cstrong\u003e(A)\u003c/strong\u003e Multiple sequence alignment of Gh\u003cem\u003e \u003c/em\u003eprotein sequences between marine medaka\u003cem\u003e \u003c/em\u003eand other vertebrates. \u003cstrong\u003e(B)\u003c/strong\u003e Phylogenetic tree of Gh and its orthologs.\u003c/p\u003e","description":"","filename":"Figure.4.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/7eb7398332d263bd4e5e5c7f.png"},{"id":94242921,"identity":"447f2bba-33ef-4a62-8a37-2ae96e1044da","added_by":"auto","created_at":"2025-10-24 04:33:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":547979,"visible":true,"origin":"","legend":"\u003cp\u003eTissue-specific expression of \u003cem\u003egh\u003c/em\u003e gene in marine medaka for 60 and 200 days. Realtime–PCR was used to analyze g\u003cem\u003eh\u003c/em\u003e gene expression, and \u003cem\u003eβ\u003c/em\u003e-actin as a reference housekeeping gene was compared. Data were mean ± SD of three replicates of each tissue, three times per tissue. Asterisks (****) indicate significant differences at \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Figure.5.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/b5db96c27578fd29790c1674.png"},{"id":94242927,"identity":"d94c72ca-71da-4e07-bb49-2d0f0816dfa0","added_by":"auto","created_at":"2025-10-24 04:33:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1062023,"visible":true,"origin":"","legend":"\u003cp\u003eBrain expression of \u003cem\u003egh\u003c/em\u003e and \u003cem\u003eghr\u003c/em\u003e in marine medaka under development stages. Difference letters indicated statistically significant differences (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05), the uppercase letter was \u003cem\u003egh\u003c/em\u003e gene, and the lowercase letter was \u003cem\u003eghr\u003c/em\u003egene expression difference at a different age, respectively.\u003c/p\u003e","description":"","filename":"Figure.6.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/1865c61c08cf1af0c1bab9b0.png"},{"id":94242925,"identity":"31a21c1e-f3bf-45ff-aaf7-a2506ca46e1d","added_by":"auto","created_at":"2025-10-24 04:33:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1073285,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of \u003cem\u003egh\u003c/em\u003e and related genes in the brain of marine medaka. The first row and the second row showed the expression patterns of four genes in different fishing groups in F1 and F2, respectively. Showed the mean ± SD for three independent individuals (\u003cem\u003en\u003c/em\u003e=3). β-actin was used as the internal reference gene. The letter indicated a statistically significant difference (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Figure.7.png","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/dbd880e881b6ffb28c532a64.png"},{"id":100070034,"identity":"bee5a26a-48d6-48bc-8ba6-5641daa772ee","added_by":"auto","created_at":"2026-01-12 16:16:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":49271840,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/0dcb8583-109d-4eb7-82b9-9f2e7e3004e7.pdf"},{"id":94242918,"identity":"e8a2970c-c796-4f97-b296-1725abf9df54","added_by":"auto","created_at":"2025-10-24 04:33:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19001,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-7708251/v1/686e3a4d42936cac6a14f63b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influences of Size-Selective Harvesting on Growth Characteristics and Associated Gene Expression Patterns in Marine Medaka (Oryzias melastigma)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOverfishing is a primary driver of ecological imbalance in marine ecosystems, and its evolutionary consequences represent a significant, yet often overlooked, threat (Dulvy et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Beyond simple population depletion, intense, size-selective harvesting acts as a powerful evolutionary force, inducing rapid genetic changes in targeted stocks \u0026mdash; a phenomenon known as Fisheries-Induced Evolution (FIE) (Heino et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hollins et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Decades of field observations and laboratory experiments have provided compelling evidence for FIE across a range of species. For instance, classic experimental harvesting on the Atlantic silverside (\u003cem\u003eMenidia menidia\u003c/em\u003e) resulted in significant divergence in growth rates and allele frequencies within just a few generations (Conover and Munch, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Therkildsen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similar rapid shifts towards smaller body size and earlier maturation have been documented in species from guppies (\u003cem\u003ePoecilia reticulata\u003c/em\u003e) to zebrafish (\u003cem\u003eDanio rerio\u003c/em\u003e) (Dunlop et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Uusi-Heikkil\u0026auml; et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Uusi-Heikkil\u0026auml;, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These evolutionary changes are not benign; they can erode the genetic potential of populations, leading to reduced productivity and compromising their ability to recover, thereby posing a significant threat to fishery sustainability (J\u0026oslash;rgensen et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Dunlop et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Hutchings and Kuparinen, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Despite the well-documented phenotypic consequences of FIE, the underlying molecular mechanisms that translate harvesting pressure into heritable traits remain a critical black box, hindering our ability to predict and mitigate these detrimental evolutionary trajectories (Heino and Dieckmann, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo illuminate this black box, we targeted the master regulatory pathway of vertebrate growth. Given that size-selective harvesting directly acts on somatic growth, we hypothesized that FIE is primarily mediated through heritable alterations in the growth hormone (GH) / insulin-like growth factor (IGF) axis (Reindl and Sheridan, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ahti et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This endocrine system fundamentally links genetic information to an organism's growth trajectory, which is then subject to selection (P\u0026eacute;rez-S\u0026aacute;nchez, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Triantaphyllopoulos et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). GH, synthesized in the pituitary, directly stimulates growth via its receptor (GHR) and indirectly promotes hepatic production of IGF1, a potent mitogen (Baker et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). While previous studies have correlated gene expression in this axis with growth rates (Solberg et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhong et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ndandala et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Qing et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), no study has yet established a causal link between a defined selection pressure and the evolution of this pathway's activity.\u003c/p\u003e\u003cp\u003eHere, we employ a rigorous experimental evolution approach using the marine medaka (\u003cem\u003eOryzias melastigma\u003c/em\u003e) to mechanistically dissect how size-selective harvesting shapes the GH/IGF axis. The short generation time and genetic tractability of this species make it a powerful system for observing evolution in real-time under controlled laboratory conditions (Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Inoue and Takei, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). By subjecting replicate populations to two generations of size-selective harvesting, we directly quantified the resulting phenotypic divergence in growth traits. We then integrated these data with expression analyses of key axis genes (\u003cem\u003egh\u003c/em\u003e, \u003cem\u003eghr\u003c/em\u003e, and \u003cem\u003eigf1\u003c/em\u003e) to test our central hypothesis. This integrative approach allows us to forge a direct, mechanistic pathway from selection pressure to molecular response, and ultimately, to phenotypic evolution. Our findings provide the evidence that FIE operates by modulating the heritable expression of the GH/IGF axis, offering a molecular-level explanation for this widespread evolutionary phenomenon and laying the groundwork for more sustainable, evolution-aware fisheries management.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Size-selective Harvesting and Fish Collection\u003c/h2\u003e\u003cp\u003eThe marine medaka used in this study originated from a stock population from the Yellow Sea Fisheries Research Institute (YSFRI), Chinese Academy of Fishery Sciences (CAFS), maintained in the laboratory for over three generations. Fish were reared under controlled laboratory conditions following established protocols. The animals were housed in 150 L round fiberglass tanks with seawater maintained at a temperature of 26.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C, salinity of 29.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0, pH of 7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1, and dissolved oxygen of 6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 mg/L on a 14:10 h light-dark cycle. Ammonia-nitrogen levels were consistently maintained below 0.15 mg/L. Initially, fish were stocked at a density of 2 fish/L to mitigate density-dependent effects. The fish were fed three times a day with a diet of newly hatched \u003cem\u003eArtemia nauplii\u003c/em\u003e and commercial flake food (TetraMin, Tetra GmbH).\u003c/p\u003e\u003cp\u003eTo initiate the multi-generational selection experiment, fertilized eggs from the stock population were collected and incubated at 28\u0026deg;C for 10 days. The resulting F1 generation of juvenile fish was collected and randomly allocated into four experimental regimes, each with three replicate tanks. Each replicate tank was initially stocked with 300 juveniles. Upon reaching sexual maturity, a specific size-selective harvesting strategy was applied to each regime. Following the selection event, eggs were collected from the remaining broodstock, hatched, and 300 F2 larvae were transferred to a new rearing tank to replace the F1 generation. This selection protocol was repeated for two consecutive generations. The four distinct selection regimes were designed to simulate different fishery management strategies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e(1) High-intensity, positive size-selection (HB): The largest 90% of individuals, based on body length, were removed, leaving the smallest 10% to reproduce. This protocol simulates an extreme fishing pressure scenario.\u003c/p\u003e\u003cp\u003e(2) Medium-intensity, positive size-selection (MB): The largest 75% of individuals were removed, retaining the smallest 25% for breeding. This intensity was chosen to reflect current fishing pressures and management policies that impose minimum size limits (Uusi-Heikkil\u0026auml; et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e(3) Medium-intensity, negative size-selection (MS): The smallest 75% of individuals were removed, thereby preserving the largest 25% for reproduction. This scenario was designed to test the evolutionary consequences of management measures that aim to protect large individuals, contradicting traditional size-selective pressures.\u003c/p\u003e\u003cp\u003e(4) Low-intensity, positive size-selection (LB): The largest 50% of individuals were removed, allowing the remaining 50% to breed. This group serves as another reference for the effect of fishing intensity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 RNA Extraction and cDNA Synthesis\u003c/h2\u003e\u003cp\u003eThis study selected male marine medaka from the F0 generation on various days (40, 60, 80, 100, 120, 140, 160, and 200 days). Each day, nine fish samples were collected for brain analysis. Furthermore, fish aged 60 and 200 days were selected for the collection of gonads, liver, brain, muscles, gills, intestines, skin, and eyes in the F0 generation. In F1 and F2 generations, adult male fish from the HB, MB, MS, and LB treatment groups were selected, with three fish in each group. Brain tissue samples were collected from each chosen individual. Total RNA was isolated from each sample using TRIzol reagent from Invitrogen (Carlsbad, CA, USA). The RNA concentration was measured with a NanoDrop 2000 spectrophotometer from Thermo (Waltham, MA, USA), and the RNA quality was evaluated using agarose gel electrophoresis. The first-strand cDNA was synthesized from purified total RNA using the PrimeScript\u0026trade; II 1st Strand cDNA Synthesis Kit from Takara (Kusatsu, Japan).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Cloning of \u003cem\u003egh\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eThe first strand of cDNA was synthesized from purified total RNA using the PrimeScriptTM II 1st Strand cDNA Synthesis Kit (Takara, Kusatsu, Japan). Primers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were designed based on predicted sequences in the NCBI database to obtain partial cDNA fragments of \u003cem\u003egh\u003c/em\u003e with PCR. The PCR products were detected by agarose gel electrophoresis, and the corresponding band of interest was purified using a product purification kit (Vazyme, Nanjing, China). Finally, the purified fragments were connected to the pEASY-T1 (TransGen, Beijing, China) vector for Sanger sequencing to verify the sequence fidelity.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe primers for \u003cem\u003egh\u003c/em\u003e cloning and related genes expression analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimer Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSequence (5\u0026prime; \u0026ndash; 3\u0026prime;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTarget Sequence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003egh\u003c/em\u003e-qF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCCATTAACAGAGCCATCCTT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRT-qPCR\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003egh\u003c/em\u003e-qR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCTTGCTGAGTTGACGTTGCT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eghr\u003c/em\u003e-qF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTGGGTGGAGTTCATCGAAGTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eghr\u003c/em\u003e-qR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCATTAGGGTGGCGGACAGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eigf1\u003c/em\u003e-qF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCCCGGGCATAGTCATTCATCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eigf1\u003c/em\u003e-qR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAGGTAAGGCCACTCCCTCAT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eigfbp1\u003c/em\u003e-qF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATCTTCCCTGAGCAAGGTCCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eigfbp1\u003c/em\u003e-qR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTCGCAGTTCGGGAGGTAGAA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-actin-qF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTATCATTCGCCTGAAACCGAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-actin-qR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCTTTGCACATGCCAGATCCG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003egh\u003c/em\u003e-pF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGATTTCAGAGCAGATCCACG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePlasmid construction\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003egh\u003c/em\u003e-pR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTAAAAAGCTGGGCAGTCATC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Sequence Analysis and Phylogenetic Tree Construction\u003c/h2\u003e\u003cp\u003eThe open reading frame (ORF) of the marine medaka \u003cem\u003egh\u003c/em\u003e gene were predicted using the NCBI ORF Finder tool. The deduced amino acid sequence of the GH protein was used for all subsequent analyses. Physicochemical properties, including theoretical molecular weight, isoelectric point (pI), and grand average of hydropathicity (GRAVY), were calculated using the ExPASy ProtParam tool. Potential post-translational modification sites were predicted from the GH amino acid sequence. Phosphorylation sites on serine, threonine, and tyrosine residues were predicted. The tertiary (3D) structure of the mature GH protein was predicted by homology modeling using the SWISS-MODEL server.\u003c/p\u003e\u003cp\u003eTo investigate the evolutionary history of GH, orthologous protein sequences from representative vertebrate species were retrieved from the NCBI GenBank database. The collected sequences were aligned using the NCBI Cobalt web server with its default parameters. Based on the resulting alignment, a phylogenetic tree was constructed using the Fast Minimum Evolution (FastME) method, which is integrated into the Cobalt results page. The tree was calculated using the Kimura (protein) distance model.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Expression of gh gene in Different Fishery Strategies\u003c/h2\u003e\u003cp\u003eThe relative mRNA expression of the \u003cem\u003egh\u003c/em\u003e gene was quantified by quantitative reverse transcription PCR (RT-qPCR). The analysis aimed to characterize its tissue-specific expression profile in F0 males and to evaluate its differential expression in the brains of F1 and F2 males from the different selection regimes.\u003c/p\u003e\u003cp\u003eRT-qPCR was performed on a LightCycler\u0026reg; 480 II system (Roche, Basel, Switzerland) using the QuantiNova SYBR Green PCR Kit (Qiagen, Hilden, Germany). Each 10 \u0026micro;L reaction contained 5 \u0026micro;L of 2\u0026times; SYBR Green PCR Master Mix, 0.4 \u0026micro;L each of the forward and reverse primers (400 nM final concentration), 1 \u0026micro;L of cDNA template, and 3.2 \u0026micro;L of nuclease-free water. The thermal cycling protocol was an initial activation at 95\u0026deg;C for 2 min, followed by 40 cycles of 95\u0026deg;C for 5 s and 60\u0026deg;C for 10 s. The \u003cem\u003eβ-actin\u003c/em\u003e gene served as an internal reference for normalization (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All assays were conducted with three biological and three technical replicates. Relative gene expression levels were calculated using the 2\u003csup\u003e\u0026minus;∆∆Ct\u003c/sup\u003e method.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Statistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses were performed using GraphPad Prism 10. Unless otherwise stated, all results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). Differences were considered statistically significant at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eTo assess the effects of size-selective harvesting on fish growth, phenotypic traits were compared among the four selection regimes. For each generation, a one-way analysis of variance (ANOVA) was used, followed by Tukey's honestly significant difference (HSD) post-hoc test for pairwise comparisons among all four groups.\u003c/p\u003e\u003cp\u003eRelative mRNA expression levels were also analyzed. Within each generation, differences in the relative expression of the \u003cem\u003egh\u003c/em\u003e gene among the four selection regimes were tested using a one-way ANOVA followed by Tukey's HSD post-hoc test.\u003c/p\u003e\u003cp\u003eAll figures were generated using GraphPad Prism and Origin. Gene expression data are visualized as bar charts showing the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM, with individual data points overlaid to show the distribution of the data.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Size-Selective Harvesting Rapidly Induces Heritable Phenotypic Divergence\u003c/h2\u003e\u003cp\u003eOur multi-generational selection experiment demonstrated that simulated harvesting strategies can act as a powerful evolutionary force, inducing rapid and heritable changes in the growth phenotypes of marine medaka.\u003c/p\u003e\u003cp\u003eAfter a single generation of selection (F1), significant differences in body size were already apparent among the treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Fish from the negative selection line (MS), which were selected for large size, exhibited the greatest mean standard length and body weight. Specifically, they were significantly longer (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and heavier (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than fish from the high-intensity positive selection line (HB), which were selected for small size.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis phenotypic divergence was substantially magnified in the second generation (F2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The MS line became markedly larger than all other groups, showing a highly significant difference in both standard length and body weight (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for all pairwise comparisons against HB, MB, and LB). Furthermore, a dose-dependent response to positive selection pressure was evident in the F2 generation's body weight, with the HB line being significantly smaller than the MB line (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003eCrucially, intergenerational analysis confirmed that these phenotypic shifts were heritable and uncovered an interesting divergence in evolutionary strategies. As hypothesized, the MS line responded directly to the selection pressure for largeness, with F2 individuals becoming significantly longer (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and heavier (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than their F1 predecessors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). This demonstrates a classic and successful response to artificial selection.\u003c/p\u003e\u003cp\u003eIn stark contrast, the intense harvesting pressure in the HB line, which targeted the smallest 10% for breeding, resulted in a counter-intuitive evolutionary trajectory. Instead of evolving towards a smaller body size, F2 fish in the HB line became significantly longer than their F1 counterparts (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while exhibiting no corresponding change in body weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). This decoupling of length and weight gain strongly suggests a rapid adaptive shift in body allometry\u0026mdash;the evolution of a more slender, gaunt phenotype. This finding indicates that under intense pressure to mature at a small size, the fish did not simply shrink but fundamentally altered their growth strategy.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Cloning and Molecular Characterization of Marine Medaka \u003cem\u003egh\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eWe successfully cloned the full-length cDNA of the marine medaka \u003cem\u003egh\u003c/em\u003e gene. The sequence contains a 633 bp ORF that encodes a 210-amino acid protein. This deduced GH protein has a predicted molecular mass of 23.53 kDa and a theoretical isoelectric point of 6.51.\u003c/p\u003e\u003cp\u003eBioinformatic analysis of the amino acid sequence revealed hallmark features consistent with a secreted peptide hormone. The protein is predicted to be hydrophilic (grand average of hydropathicity: -0.075) and possesses a canonical N-terminal signal peptide with a predicted cleavage site after Serine 23, indicating its entry into the secretory pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Furthermore, the sequence contains 26 potential phosphorylation sites for various kinases, suggesting that GH activity is likely regulated by post-translational modifications. The protein was, however, predicted to be unstable in vitro, with an instability index of 51.78.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFinally, homology modeling predicted that the marine medaka GH protein adopts the classic four-helix bundle structure characteristic of the vertebrate growth hormone family (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This structural conservation, combined with the presence of a signal peptide, confirms the identity of the cloned sequence as a bona fide growth hormone.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 GH Sequence Conservation and Phylogenetic Position\u003c/h2\u003e\u003cp\u003eTo assess the conservation of the newly identified growth hormone, we aligned its protein sequence with orthologs from other teleost fishes. The alignment revealed substantial sequence conservation across these species (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Several sequence blocks, particularly in the central and C-terminal portions of the protein, showed near-perfect identity. This high degree of conservation in specific regions suggests they are under strong functional constraint.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePhylogenetic analysis was then conducted to resolve the evolutionary placement of the marine medaka GH within the broader vertebrate context. The resulting tree robustly recapitulated the known evolutionary relationships between major vertebrate lineages, showing a clear and deep divergence between the teleost fish and the tetrapod clades (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). As hypothesized, the marine medaka GH clustered firmly within the teleost fish group. More specifically, it formed a well-supported sister-group relationship with the GH from its close relative, the Japanese medaka (\u003cem\u003eOryzias latipes\u003c/em\u003e). This placement, nested within the spiny-rayed fishes, is fully consistent with established species phylogeny and confirms the evolutionary identity of our cloned sequence.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Spatiotemporal Expression Profile of \u003cem\u003egh\u003c/em\u003e and \u003cem\u003eghr\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eTo determine the spatial expression pattern of \u003cem\u003egh\u003c/em\u003e, we performed RT-qPCR on a panel of tissues from adult male medaka. The analysis revealed that \u003cem\u003egh\u003c/em\u003e expression is highly tissue specific. Its mRNA transcripts were detected at substantially and significantly higher levels in the brain compared to all other tissues examined (gonad, liver, muscle, gills, intestine, skin, and eyes), where expression was negligible (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This brain-specific expression pattern was consistent in fish at both 60- and 200-days post-hatch.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next examined the temporal expression dynamics of \u003cem\u003egh\u003c/em\u003e and its receptor, \u003cem\u003eghr\u003c/em\u003e, in the brain throughout development, uncovering a tightly coordinated expression pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Both genes exhibited a distinct bimodal expression profile. The expression of \u003cem\u003egh\u003c/em\u003e showed two significant peaks around day 60 and day 100. Specifically, its expression at day 100 was significantly higher than at the initial 40-day timepoint and the subsequent trough at day 80. A similar peak was observed at day 60.\u003c/p\u003e\u003cp\u003eRemarkably, the expression profile of \u003cem\u003eghr\u003c/em\u003e, almost perfectly mirrored that of its ligand. It displayed a major peak at day 60, which was significantly higher than all other time points, and a second prominent peak at day 100. These two peaks were separated by a significant drop in expression at day 80. This highly synchronized expression dynamic, with both genes peaking and troughing at nearly identical developmental stages, strongly suggests a functional co-regulation of the GH/GHR axis during key periods of post-larval development and maturation in marine medaka.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Selection Regimes Induce Divergent and Heritable Reprogramming of the GH/IGF Axis\u003c/h2\u003e\u003cp\u003eTo uncover the molecular mechanisms driving the observed phenotypic divergence, we quantified the expression of key genes in the GH/IGF axis. Our results reveal that the size-selective harvesting strategies induced a profound, divergent, and heritable reprogramming of this critical growth pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA consistent and striking pattern emerged across the axis: selection for large size (MS) robustly upregulated gene expression, while selection for small size (HB) led to its suppression. In the F1 generation, the expression of both \u003cem\u003egh\u003c/em\u003e and its receptor \u003cem\u003eghr\u003c/em\u003e was already significantly higher in the MS compared to the HB.\u003c/p\u003e\u003cp\u003eThis divergent response was dramatically amplified in the F2 generation, providing powerful evidence of a rapid, heritable evolutionary change at the molecular level. Most notably, the expression of \u003cem\u003egh\u003c/em\u003e in the F2 MS was upregulated by several orders of magnitude compared to the F1 generation, reaching levels thousands of times higher than in the HB. This massive induction was mirrored by other key axis genes. The expression of \u003cem\u003eghr\u003c/em\u003e and the downstream gene \u003cem\u003eigfbp1\u003c/em\u003e were also significantly higher in the F2 MS and MB compared to the low-expression HB and LB.\u003c/p\u003e\u003cp\u003eInterestingly, the expression of \u003cem\u003eigf1\u003c/em\u003e showed a more complex pattern, with the MB line exhibiting the highest expression in the F2 generation. Nevertheless, the predominant signal across the entire GH/IGF axis is one of coordinated and heritable reprogramming, directly reflecting the direction and intensity of the applied selection pressure.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eFisheries-induced evolution is widely recognized as a potent force reshaping wild populations, yet the molecular engines driving these rapid phenotypic shifts have remained largely a black box. Our study provides the direct experimental evidence that this evolution is driven by the rapid and heritable reprogramming of the core GH/GHR growth axis. By demonstrating a clear causal chain\u0026mdash;from a simulated harvesting pressure to altered gene expression and consequent phenotypic divergence\u0026mdash;we fill a critical mechanistic gap at the intersection of evolutionary biology and fisheries science. This work transitions the understanding of FIE from a pattern of observation to a process rooted in predictable molecular physiology.\u003c/p\u003e\u003cp\u003eThe most direct evidence for this mechanistic link comes from the strong positive correlation we observed between selection for large body size, the upregulation of the GH/GHR axis, and the resulting acceleration in growth. This was most pronounced in our MS group, where two generations of selection favoring the largest individuals resulted in F2 fish that not only exhibited a significant increase in body size, but also displayed the highest transcription levels of both \u003cem\u003egh\u003c/em\u003e and its receptor. The tight coupling of this molecular response to the phenotypic outcome was stark: by the F2 generation, fish from the MS line, with their highly active GH/GHR axis, in which the axis was consistently suppressed. This finding\u0026mdash;that selection for larger size preferentially propagates individuals with a more active GH/GHR signaling pathway\u0026mdash;is consistent with the well-documented positive correlation between gh expression and growth rates in other teleosts, such as larval Japanese puffer (\u003cem\u003eTakifugu rubripes\u003c/em\u003e) (Kaneko et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), sideromorphic barbel chub (\u003cem\u003eSqualiobarbus curriculus\u003c/em\u003e) (Wang et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and juvenile triploid crucian carp (\u003cem\u003eCarassius auratus\u003c/em\u003e) (Zhong et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Our study thus provides powerful experimental confirmation that this fundamental endocrine axis is a primary and predictable target that is rapidly modulated by external selective pressures mimicking fisheries harvesting.\u003c/p\u003e\u003cp\u003eInterestingly, the evolutionary response to harvesting was markedly asymmetrical. While selection for larger size in the MS group yielded a strong and direct phenotypic and molecular response, the intense pressure against large size in the HB line revealed a more complex evolutionary trajectory. Contrary to the expectation of evolving a smaller, miniaturized body, F2 individuals in the HB group became significantly longer than their F1 predecessors, yet exhibited no corresponding increase in body weight. This decoupling of length and weight gain is a critical finding, strongly indicating a rapid evolutionary shift in body allometry\u0026mdash;a trade-off that produces a more slender or gaunt phenotype rather than a simple, proportional reduction in size. This resistance to downward size selection is not unprecedented and aligns with findings from previous experimental evolution studies in zebrafish (Uusi-Heikkil\u0026auml; et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Japanese medaka (\u003cem\u003eOryzias latipes\u003c/em\u003e) (Renneville et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which also reported attenuated responses to selection for smaller sizes. Such a pattern suggests the influence of a powerful physiological or genetic constraint, a potential evolutionary floor below which the viability or reproductive success of an individual is critically compromised. When faced with this lower limit, populations may adopt alternative adaptive strategies, such as the alteration in body shape observed here.\u003c/p\u003e\u003cp\u003eOur findings contribute a crucial mechanistic layer to the extensive FIE literature. For decades, experimental evolution studies have convincingly demonstrated rapid phenotypic shifts in response to harvesting. For instance, high-intensity harvesting of Atlantic silverside led to a 22% difference in length after just four generations (Conover and Baumann, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Conover and Munch, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), while similar selection experiments on zebrafish and Japanese medaka also produced significant changes in body size over multiple generations (Uusi-Heikkil\u0026auml; et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Renneville et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). More recently, genomic studies have begun to link these traits to shifts in allele frequencies, confirming a genetic basis for FIE (Audzijonyte et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Han et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, despite this progress, the regulatory mechanisms that bridge the genotype-phenotype gap\u0026mdash;explaining how genetic variation is translated into a rapid organismal response\u0026mdash;have remained largely elusive. Our work fills this void. We identify the heritable modulation of gene expression within the GH/GHR axis as a primary and powerful response to selection. This suggests that FIE does not solely depend on the slower process of new allele fixation, but can also proceed swiftly via the epigenetic or regulatory inheritance of expression patterns in key physiological pathways, providing a compelling explanation for the remarkably high rates of evolution observed in exploited fish stocks.\u003c/p\u003e\u003cp\u003eWhile our study establishes a clear mechanistic link between harvesting pressure and the evolution of its underlying molecular machinery, we acknowledge its limitations and the exciting avenues they open for future research. Our experiment was conducted over two generations, capturing the critical initial stages of evolutionary response. Future work should extend this framework over more generations to investigate the long-term stability of these reprogrammed expression patterns and, crucially, to explore their potential for reversal\u0026mdash;a topic of intense debate and immense importance for fisheries management. Furthermore, while we focused on the core GH/GHR axis, a holistic view is needed. Applying transcriptomic (RNA-seq) analysis to key tissues like the brain and liver would uncover the broader gene networks responding to selection. This approach could ultimately allow us to pinpoint the specific regulatory elements, such as SNPs in promoter regions, that anchor these heritable changes in gene expression to the underlying genetic architecture. Integrating such multi-generational and multi-omics approaches will be pivotal in developing truly evolutionarily enlightened strategies for sustainable fisheries.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our research demonstrates that fisheries-induced evolution is not merely a selective sieve acting on existing phenotypes, but a potent force that actively reshapes the underlying molecular machinery of growth. We establish a direct, causal link between size-selective pressure and the heritable reprogramming of the GH/GHR axis, revealing how selection on an organismal trait can rapidly and divergently alter a core endocrine pathway. This highlights that heritable shifts in gene expression can serve as a primary and rapid engine for evolution in response to intense anthropogenic pressures, supplementing the slower process of allele fixation. Ultimately, this mechanistic insight is a critical step towards predicting the evolutionary trajectories of exploited populations and is fundamental for designing sustainable, evolution-aware management strategies to safeguard global fisheries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003cp\u003e All experimental procedures involving animals were conducted in accordance with the ethical standards and regulations set forth by the Yellow Sea Fisheries Research Institute, CAFS. This approval certifies that the experimental design adhered to the guidelines for the ethical treatment of animals used in research.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was funded by the State Key Laboratory of Mariculture Biobreeding and Sustainable Goods Basic Research Experimental Support Grants (BRESG-JB202503), the National Key Research and Development Program 2024YFD2400405, the Special Fund of Taishan Scholar Project(tsqn202103135) and the National Natural Science Foundation of China (42206104).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eChengcheng Su: Conceptualization, Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review \u0026amp; editing, Visualization. **Shuo Li:** Conceptualization, Methodology, Formal analysis, Validation, Writing-Review \u0026amp; Editing, Supervision. **Yunlong Chen:** Writing - review \u0026amp; editing, Visualization **. Xianshi Jin:** Data collection, Methodology, Formal analysis, Validation, Writing-Review \u0026amp; Editing, Funding acquisition, Supervision. **Changwei Shao:** Conceptualization, Methodology, Formal analysis, Validation, Writing-Review \u0026amp; Editing, Supervision. **Xiujuan Shan:** Conceptualization, Methodology, Formal analysis, Validation, Writing-Review \u0026amp; Editing, Supervision.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe authors are unable or have chosen not to specify which data has been used.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhti PA, Kuparinen A, Uusi-Heikkil\u0026auml; S (2020) Size does matter \u0026mdash; the eco-evolutionary effects of changing body size in fish. 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Endocrinol. 178, 291\u0026ndash;300. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ygcen.2012.06.006\u003c/span\u003e\u003cspan address=\"10.1016/j.ygcen.2012.06.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"marine-biotechnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mbte","sideBox":"Learn more about [Marine Biotechnology](http://link.springer.com/journal/10126)","snPcode":"10126","submissionUrl":"https://submission.nature.com/new-submission/10126/3","title":"Marine Biotechnology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Size-selective harvesting, Oryzias melastigma, Growth hormone, Growth trait","lastPublishedDoi":"10.21203/rs.3.rs-7708251/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7708251/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFisheries-induced evolution (FIE) poses a critical threat to global fisheries sustainability, but the molecular mechanisms that translate harvesting pressure into rapid, heritable trait changes remain largely unknown. Here, using a multi-generational experimental evolution approach with the marine medaka (\u003cem\u003eOryzias melastigma\u003c/em\u003e), we demonstrate that size-selective harvesting drives profound phenotypic divergence within just two generations. This evolutionary response is directly underpinned by the heritable reprogramming of the core growth hormone/insulin-like growth factor (GH/IGF) axis. Strikingly, selection for large body size led to an upregulation of \u003cem\u003egh\u003c/em\u003e gene expression by several orders of magnitude, cementing this pathway as a primary target of selection. Conversely, intense selection against large size prompted a complex adaptive response involving a shift in body allometry rather than a simple reduction in size, suggesting the influence of underlying physiological constraints. Our findings establish heritable gene expression reprogramming as a key rapid mechanism for FIE, providing a crucial mechanistic foundation for developing evolution-aware strategies for sustainable fisheries management.\u003c/p\u003e","manuscriptTitle":"Influences of Size-Selective Harvesting on Growth Characteristics and Associated Gene Expression Patterns in Marine Medaka (Oryzias melastigma)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-24 04:33:09","doi":"10.21203/rs.3.rs-7708251/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-03T22:44:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-30T20:14:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-29T01:39:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224463342332667436691658876180275488713","date":"2025-10-10T01:56:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300080529009942131177303252087574424441","date":"2025-10-09T15:37:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T12:53:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-01T14:22:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-01T14:20:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Marine Biotechnology","date":"2025-09-25T03:23:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"marine-biotechnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mbte","sideBox":"Learn more about [Marine Biotechnology](http://link.springer.com/journal/10126)","snPcode":"10126","submissionUrl":"https://submission.nature.com/new-submission/10126/3","title":"Marine Biotechnology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d82b5a3b-b376-4e9c-ac14-7780cad31ca1","owner":[],"postedDate":"October 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:08:56+00:00","versionOfRecord":{"articleIdentity":"rs-7708251","link":"https://doi.org/10.1007/s10126-025-10566-2","journal":{"identity":"marine-biotechnology","isVorOnly":false,"title":"Marine Biotechnology"},"publishedOn":"2026-01-09 15:58:31","publishedOnDateReadable":"January 9th, 2026"},"versionCreatedAt":"2025-10-24 04:33:09","video":"","vorDoi":"10.1007/s10126-025-10566-2","vorDoiUrl":"https://doi.org/10.1007/s10126-025-10566-2","workflowStages":[]},"version":"v1","identity":"rs-7708251","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7708251","identity":"rs-7708251","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}