Salinity-associated differential gene expression in natural populations of the euryhaline killifish Aphanius iberus

Salinity-associated differential gene expression in natural populations of the euryhaline killifish Aphanius iberus | 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 Salinity-associated differential gene expression in natural populations of the euryhaline killifish Aphanius iberus Alfonso López-Solano, Aida Verdes, Silvia Perea, Elena Andrés, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9115348/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 16 You are reading this latest preprint version Abstract Background Salinity is a major ecological driver in aquatic environments and strongly influences the physiology, distribution, and survival of fish species. While many fishes are restricted to narrow salinity ranges, euryhaline species can tolerate large osmotic fluctuations despite the substantial physiological adjustments required. The Spanish toothcarp, Aphanius iberus , an endemic Mediterranean killifish, is one of such exceptional species capable of inhabiting environments ranging from freshwater to hypersaline systems. However, despite this remarkable resilience, the molecular mechanisms underlying salinity tolerance and osmoregulatory plasticity in this species remain poorly understood. Results We analyzed using RNA sequencing transcriptomes from the gills and gastrointestinal tract of individuals from four wild populations spanning a natural salinity gradient from freshwater (0.75 PSU) to brackish (5-10 PSU) and hypersaline (~50 PSU) habitats. Differential gene expression analyses revealed strong tissue-specific patterns and environment-dependent responses. A substantially higher number of differentially expressed genes was detected in the gills, where genes associated with ion transport, cytoskeletal remodeling, and energetic metabolism varied across salinity conditions, reflecting their central role in osmoregulation. In the gastrointestinal tract, pathways related to lipid and carbohydrate metabolism were enriched, particularly in brackish populations. In addition, several genes associated with osmotic stress responses, including ATPases, histones, and transposable elements, showed significant expression differences across populations. Conclusions These findings offer novel insights into the molecular architecture of salinity tolerance in euryhaline fishes, highlighting coordinated transcriptional responses across tissues involved in ion regulation and metabolic adjustment and improving our understanding of how euryhaline fishes cope with extreme and fluctuating osmotic environments. From a conservation perspective, identifying the molecular basis of this physiological plasticity contributes to the management of this highly threatened endemic species and the dynamic coastal habitats it inhabits. Transcriptomics Aphanius iberus Differential Gene Expression Salinity Osmoregulation Adaptation Figures Figure 1 Figure 2 Figure 3 Background The thermo-physicochemical properties of water are key drivers in the evolution of aquatic life, pressing organisms to adapt to variable habitats [1,2]. In animals, the ancestral metabolic conditions enabling adaptation to seawater underwent modifications with the colonization of new environments, notably the transition from saltwater to freshwater [3]. Fishes in particular, exhibit remarkable plasticity, which facilitates environmental colonization shaping global evolutionary patterns [4]. Euryhalinity , the ability to tolerate a wide range of salinity levels , is considered an ancestral, transitional trait that enables colonization of new adaptive zones, promoting diversification and eventually leading to the origin of stenohaline taxa (i.e., those that only survive in a narrow range of salinity levels). Today, most fishes are stenohaline, restricted to either FW or SW with narrow salinity tolerances, while true euryhaline species are rare [5,6]. Only 3 - 5% of fish species retain their euryhaline capacity, allowing them to withstand broader salinity ranges and to transition between FW and SW environments [7]. Despite its adaptive advantages, euryhalinity is rare, likely due to significant physiological and immunological [8]. It is therefore likely that this trait would have been lost, were it not for strong selection pressures [9]. However, these uncommon euryhaline taxa contribute to evolutionary diversity, as landlocking and FW radiations frequently occur in ancestrally euryhaline lineages [6] . Euryhalinity is a highly demanding process, with estimated energy costs ranging from 20% to 62% of the total energy produced by organisms under elevated salinity stress [10,11]. For instance, gills alone require approximately 7% of the total energy to sustain the osmoregulatory processes necessary under these conditions [10,11]. Despite its high energy demands, euryhalinity provides a significant advantage specially in the current context of global climate change, where rapid environmental shifts towards salinization are increasingly impacting FW ecosystems [12,13]. Aquatic habitats are typically classified by salinity levels, from freshwater (FW) with <0.5 Practical Salinity Units (PSU), to brackish water (BW) with 0.5-30 PSU, and seawater/saltwater (SW) with 30-40 PSU [14]. In natural ecosystems, salinity fluctuations are a key abiotic factor affecting the adaptability and survival of species. Osmoregulation capacity determines an organism's salinity tolerance, as it directly influences biological processes such as growth, survival, lipid metabolism in fish larvae, gonad development, embryo hatchability, feeding and digestion, among others [15,16]. Fishes generally maintain body fluid osmolarity at about one-third of SW [17]. In SW, they lose water through osmosis and gain Na+ and Cl− via diffusion, compensating through seawater ingestion, minimal urine excretion, and active salt excretion via the gills. Conversely, FW fish excrete dilute urine, actively absorb salts across the gills, and may also ingest salts through their diet [17,18,19]. Euryhaline fishes, commonly found in estuaries or as migratory species, endure frequent salinity shifts. Coastal SW salinity fluctuates due to surface runoff, rainfall, floods, and tides, requiring euryhaline fish to exhibit high iono-osmoregulatory plasticity. Their response involves cellular remodeling in osmoregulatory organs, including modulation of transporters, channels, and intercellular structures [18,20]. Under salinity stress, osmosensors trigger molecular cascades that induce cellular remodeling, allowing fish to restore osmotic balance by adjusting or switching between different osmolar environments [18,20]. As research continues to explore independent instances of adaptation to different osmotic environments in fishes, it remains intriguing to determine whether evolution repeatedly employs similar pathways to address the same challenges [19,21]. However, physiological flexibility varies among individuals. For example, in Fundulus heteroclitus , populations exhibit differing abilities to acclimate to extreme osmotic conditions, with interspecific divergence in osmotic plasticity observed even among geographically close groups [22]. FW populations demonstrate greater efficiency in compensating for hypoosmotic challenges than BW or coastal populations, despite long-term rearing in seawater. Additionally, northern coastal populations tolerate hypoosmotic challenges better than their southern counterparts [21,23]. Salinity acclimation in fish involves high plasticity in key osmoregulatory organs such as the gills, kidney, liver, and gastrointestinal tract (GIT), which maintain homeostasis in FW, BW, and SW environments [18,24]. The gills serve as the primary site for osmotic sensing and compensation, uptaking ions in FW and excreting salt in SW [18,19]. The GIT also plays a crucial osmoregulatory role beyond nutrient absorption, especially in SW fishes, which drink seawater and rely on intestinal processes, such as bicarbonate secretion and ion precipitation, to reduce chyme osmolality and facilitate water absorption. In fish species exposed to varying salinities, differences in expression of genes related to ion transport, water and solute channels, as well as immune functions, have been identified particularly in mucosal surfaces such as the gills, skin, and GIT [24,25]. A conserved molecular response to osmotic stress has also been identified, involving regulation of the cell cycle, metabolism, protein synthesis, cytoskeletal organization, and immune responses [26,27]. Studies of fish osmoregulatory processes using RNA-seq have been growing exponentially in recent decades [28,29,30]; most focusing either on model species such as mummichogs, three-spine sticklebacks, medakas and guppys [21,31,32,33,34] or economically important species such as theNile tilapia, Atlantic salmon, rainbow trout and the Asian, European and spotted seabass (9,26,35,36,37,38,39,40,41). However, studies focusing on non-model wild species are scarce, despite their potential to provide insights into salinity adaptation in the current context of global climate change. Here, we used an RNA-seq approach on Aphanius iberus , the Spanish toothcarp,a small endemic fish species belonging to the order Cyprinodontiformes which can be found on the eastern coast of the Iberian Peninsula, and it is currently classified as Endangered by the Libro Rojo de las Especies Españolas [42,43] and by the Spanish Catalogue of Threatened Species (Real Decreto 139/2011, Official State Gazette (BOE-A-2011-3582)). It inhabits a wide range of habitats ranging from groundwater springs (locally known as ullals ) to coastal lagoons, river mouths, and even salt marshes where the salinity level is often greater than the sea (e.g. Marchamalo salt flats). Apart from the mentioned studies conducted on F. heteroclitus [21], there are few studies on this globally distributed and diverse order, which includes over 1,300 species (e.g. Aphanius dispar , [44]; Poecilia reticulata , [34]; Limia perugiae , [45]. A. iberus has been the subject of many genetic and ecological studies [46,47,48,49,50,51,52], but never from a transcriptional perspective. Given the species' natural exposure to a broad salinity range, we hypothesize that A. iberus exhibits a distinctive and complex transcriptional response to salinity stress. This response likely involves differential expressions of key iono-osmoregulatory genes across tissues, comparable on a functional level, but divergent in molecular pathways from those described in classical euryhaline model species. We anticipate that this transcriptomic plasticity reflects a combination of ancestral euryhaline traits and habitat-driven local adaptation. Material & Methods 1. Sample collection and processing We selected four populations of Aphanius iberus living at different salinity levels, all located along the eastern Mediterranean coast of the Iberian Peninsula, within the species’ distribution range (Figure 1A) and collected four individuals from each location (Supp. Table 1). The northernmost population was the Natural Park of Cabanes i Torreblanca in the mediterranean province of Castellón (Séquia del Polo; 40.18500, 0.2063). This population inhabits brackish waters with a salinity of 4.8 PSU. Two additional populations were collected in coastal saline systems: Santa Pola (Los Xiprerets; 38.19778, -0.578633), within the Santa Pola Salt Pans Natural Park (Alicante), with a salinity of 7.4 PSU at the time of sampling; and Marchamalo (37.63536, -0.717281) in Murcia, a hypersaline saltworks where salinity reached 52 PSU, exceeding Mediterranean seawater levels. The southernmost population was sampled in Adra (Almería; 36.7633659, -2.9513865), where individuals were found in irrigation ponds with a salinity of 0.76 PSU, corresponding to near-freshwater conditions. Fish were collected using minnow trap nets and euthanized by immersion in an overdose of buffered tricaine methanesulfonate (MS-222, 0.1%), ensuring rapid loss of consciousness, in accordance with internationally accepted guidelines for the use of fish in research. All procedures were carried out by qualified personnel under the relevant institutional and regional permits (see Ethics approval and consent to participate section). Specimens were then fixed in RNAlater solution (Invitrogen™) and kept at 4 °C until further processing. The gills and gastrointestinal tract (GIT) of four individuals per population were dissected under a binocular stereoscope and stored at −80 °C at the National Museum of Natural Sciences (Madrid, Spain) for subsequent RNA extraction and cDNA library preparation. 2. RNA Extraction, Library Preparation and Sequencing Total RNA was extracted from a set of 32 samples, corresponding to the gills and GIT of four specimens per population (Supp. Table 1), using the Trizol protocol of the Invitrogen™ PureLink™ RNA Mini Kit, following manufacturer’s instructions. Quantity and quality of the extracted RNA were assessed with a Nanodrop spectrophotometer and genomic libraries were constructed using the Illumina Stranded mRNA Prep kit, following the protocol on the Ligation Reference Guide. The quality, insert size and concentration of the libraries were checked with an Agilent TapeStation 4150, verified with Qubit DNA hs assay, and sent to Novogene Europe (Cambridge, UK) for sequencing with Illumina NovaSeq X Plus technology, at 150 base-pairs (bp) paired-end reads. 3. Sequence processing, read mapping and abundance estimation The quality of the raw reads generated from each of the 32 libraries was evaluated with FastQC v0.12.1 [53]. Adapter sequences and low-quality bases and reads (phred score < 30) were removed with Trimmomatic v0.39 [54]. Clean reads were aligned to the reference genome of Aphanius iberus , sequenced and annotated by our research group (GCA_028564705.1 NCBI GenBank; [55]), using Star Aligner v2.7.9a [56]. Read abundance was then estimated with StringTie v2.1.7 [57] following the Simplified Workflow and the prepDE.py script of the StringTie package was used to generate a count matrix with the estimated abundances for each gene. 4. Differential Gene Expression, Gene Ontology and Pathway Analyses All analyses were conducted using Trinity v2.13.2 [58]. Differential Gene Expression (DGE) analysis was performed through pairwise comparisons using edgeR from trinityrnaseq v2.13.2, executed via the run_DE_analysis.pl script, selecting genes with P ≤ 1e-3 and a fold-change of at least 2². Functional annotations and GOTerms from the reference genome were assigned to each overexpressed gene. Heatmaps were created using Pheatmap v1.0.12 [59], while Volcano plots were generated with EnhancedVolcano v1.24 [60], applying a fold-change threshold of ±2 and a p-value cutoff of 10e-3, both analyses conducted in RStudio v2024.12.1.563 [61]. Gene Ontology (GO) analysis was conducted using InterProScan [62] and sma3s [63] annotations from the Aphanius iberus reference genome and DGE data. Finally, annotated genes from each comparison were filtered using InterProScan, classifying them by population overexpression. These results were used for KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis [64], performed in ShinyGO v0.80 [65]. Results 1. Sequencing results and Differential Gene Expression analyses We generated a total of 313,31 GB of data from the 32 sequenced libraries that were used for the DGE analyses. After quality filtering and cleaning the reads, we obtained libraries ranging from 3,146,004 to 31,431,060 high quality reads (Supp. Table 1). We identified a total of 1,428 DEGs in the gills and 504 in the GIT, of which we could functionally annotate 1,081 and 398 respectively (Supp. Table 2). The pairwise comparisons among all samples revealed that the gills exhibited a significantly higher number of differentially expressed genes across populations than the GIT in most cases (Fig. 1B). The populations that exhibited the greatest amount of differentially expressed genes (DEG) for gills were the SW population of Marchamalo (140 DEGs on average) and the FW population of Adra (138 DEGs), which correspond to the highest and lowest salinity levels, respectively (Fig. 1B). Regarding the GIT, the populations that exhibited the greatest number of overexpressed genes were the SW population of Marchamalo (79 DEGs) and the BW population of Cabanes (61 DEGs) (Figure 1B). We performed pairwise comparisons among populations with an increasing level of salinity (Figs. 1C-D) and examined the functions of the genes with the highest expression levels. We found a significant number of DEG related with transcription processes, including ribonucleases, integrases, and ligases including HECT E3 ligase catalytic domain , as well as structural genes like histones ( linker histone H1/H5 ). A considerable number of genes are associated with Repetitive Elements, including the L1 Transposable Element or Reverse Transcriptases. Additionally, immunoglobulins were identified among these top upregulated genes in both tissues, along with other genes associated with apoptosis and phagocytosis, such as interferon alpha-inducible protein IFI6/IFI27-like and adhesion G protein-coupled receptor B1 . Finally, we also found genes associated with salinity regulation processes, including Peptidases, Heat-shock Proteins, Tristetraprolin or Voltage-dependent L-type Calcium Channel Subunit Alpha-1C (Supp. Table 2). A summary of the most relevant upregulated genes identified in all pairwise comparisons across populations can be found in Table 1 (Supp Table 7). Table 1. Candidate genes potentially involved in salinity acclimatation in Aphanius iberus organized in five categories that include genes involved in ion transport, energetic metabolism, signal transduction, immune response, structure organization and repetitive elements. Category Gene Upregulated in population Tissue References Ion transporter Na(+)/K(+) ATPase alpha-1 subunit (ATP1A1) FW Adra Gill Boutet et al. 2006; Whitehead et al. 2012; Norman et al. 2014; Maryoung et al. 2015; Gibbons et al. 2017; Guo et al. 2018; Lee et al. 2020; Lee et al. 2020; Vij et al. 2020; Li et al. 2021; Valenzuela-Muñoz et al. 2021; Taugbøl et al. 2022 Chloride channel protein 2 FW Adra Gill Vij et al. 2020 Solute carrier families FW Adra Gill Lam et al. 2014; Gibbons et al. 2017; Cui et al., 2019 BW Cabanes Gill BW Santa Pola Gill SW Marchamalo Gill Claudin-3 SW Marchamalo Gill Whitehead et al. 2012; Li et al. 2012; Lam et al. 2014; Nguyen et al. 2016 Energetic metabolism G protein-coupled receptor FW Adra Gill Lam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017 Tristetraprolin (MAPK cascade) BW Cabanes GIT Lam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017 P2X purinoreceptor (activation of MAPK activity) BW Cabanes GIT Lam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017 BW Santa Pola GIT Probable ATP-dependent RNA helicase DDX43 BW Santa Pola GIT Lam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017 GTPase IMAP family member 7 SW Marchamalo GIT Lam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017 Stress and Immune Responses Heat-shock 70 kDa protein 12A FW Adra GIT Thanh et al., 2014; Li et al., 2020; Zhang et al., 2020; Valenzuela-Muñoz et al., 2021 BW Santa Pola Gill Structure organization KASH domain BW Cabanes Gill Li et al., 2012; Wong et al., 2014; Nguyen et al., 2016 helically-extended SH3 domain BW Cabanes Gill Li et al., 2012; Wong et al., 2014; Nguyen et al., 2016 BW Santa Pola Gill Histones H1a and H4 FW Adra Gill Whitehead et al., 2011; Whitehead et al., 2012 BW Cabanes Gill Repetitive Elements Tc1 DNA transposon FW Adra Gill Caratti et al. 2022 SW Marchamalo Gill L1 transposable element BW Santa Pola Gill Caratti et al. 2022 PiggyBac transposable element-derived protein BW Cabanes GIT Barney transposase SW Marchamalo GIT The most extreme populations in terms of salinity levels are Adra (with the lowest levels) and Marchamalo (with the highest salinity) and accordingly, we found the highest number of DEGs in the pairwise comparison of both tissues from these populations (Fig. 2, Supp. Table 3). For the gill, we found among the most up-regulated genes in Adra a solute carrier gene ( SLC12A domain ), involved in ion transport, and an arginase domain-containing gene, linked to nitrogen metabolism and osmotic balance. In contrast, the gill of Marchamalo showed upregulation of a cytochrome c domain gene, consistent with an increased energetic demand under hyperosmotic stress. For GIT, we found among the most up-regulated genes in Adra an ATPase domain-containing gene, involved in active ion transport under hypoosmotic conditions (Figs. 2A–D). For the rest of the pairwise comparisons, we found a similar number of DEGs in both gill and GIT with some of the most up-regulated genes related to osmoregulation or immune response among others (Supp. Table 2). Volcano plots and heatmaps with the top 20 annotated DEGs among pairwise comparisons for gill and GIT can be found in the Supplementary Material, Supplementary Figures 1 and 2, respectively. 2. Gene Ontology and KEGG pathway Analyses We conducted Gene Ontology (GO) and KEGG analyses to investigate whether any functions or pathways were overrepresented among the DEGs identified (Fig. 3 and Supp. Table 4). For both analyses, we identified a greater number of overrepresented functions in the gills, with 207 different terms in the category of Molecular Function, 176 terms for Biological Processes, and 40 terms for Cellular Component. For the GIT, 300 different terms were identified for Molecular Function, 354 for Biological Processes and 75 terms for Cellular Component. It is noteworthy to mention again that the comparison of the BW population of Cabanes vs. the SW population of Marchamalo contributed the most genes to almost every term in every category of the GIT. Most overrepresented GO terms in the category of Biological Processes in both tissues were associated with salinity regulation, including transmembrane transport (GO:0055085) and ion transport (GO:0006811) which were present in both tissues and all populations. Additionally for gills, cation transport (GO:0006812), potassium ion transport (GO:0006813), and ion transmembrane transport (GO:0034220) were observed across all populations. In all populations of the GIT, the term calcium ion transmembrane transport (GO:0070588) was identified. In addition, the following terms were identified in the gills: anion transport (GO:0006820), chloride transport (GO:0006821), and sodium ion transport (GO:0006814) (Supp. Table 5). In the comparison of the BW populations (Cabanes and Santa Pola) with the rest, we identified many overrepresented GO terms associated to immune response (GO:0006955) in both tissues (Supp. Table 6). The majority of the identified genes that contributed to this GO term can be grouped in the following categories: interleukins, immunoglobulins, and MHC complex in the gills; and proteins of the membrane attack complex, cell signaling proteins (Helically-extended SH3 domain), and interleukins for the GIT (Supp. Table 6). For the KEGG analysis, we only identified enriched pathways in the comparisons of the FW population of Adra vs all other populations for both tissues, and in the comparison of the SW population of Marchamalo vs the BW population of Santa Pola for the gills (Supp. Table 4). The Cysteine and methionine metabolism (Path:dre00270) pathway was enriched in the pairwise comparisons of the gills from the FW population of Adra versus all other populations. Other enriched pathways in the gill tissue comparisons were Glycine serine and threonine metabolism (Path:dre00260), Selenocompound metabolism (Path:dre00450), Citrate cycle (TCA cycle) (Path:dre00020) and Sulfur metabolism (Path:dre00920). In the case of the GIT, we found a greater variety of enriched pathways including Starch and sucrose metabolism (Path:dre00500), Apoptosis (Path:dre04210), Metabolic pathways (Path:dre01100), RNA degradation (Path:dre03018), One carbon pool by folate (Path:dre00670), Tryptophan metabolism (Path:dre00380), Arachidonic acid metabolism (Path:dre00590), and DNA replication (Path:dre03030) (Supp. Table 4). Discussion Our results indicate strong tissue-specific gene expression patterns in response to salinity variation, with gills exhibiting a higher number of DEGs than the gastrointestinal tract (GIT). This pattern is consistent with previous studies highlighting the central role of the gills in osmoregulation, as they are in direct contact with the external environment and represent the primary boundary for osmotic exchange and regulation. In contrast, the GIT is involved in a multitude of additional functions beyond osmoregulation, which might attenuate or mask salinity-specific transcriptional changes [ 66 , 67 ]. Nevertheless, we found a similar proportion of upregulated genes associated with salinity regulation processes in both tissues (Supp. Tables 1 and 5), in line with previous studies showing that the GIT exhibits a rapid response to changes in environmental salinity [ 17 , 68 ]. Several cyprinodontiform fishes closely related to A. iberus are capable of remodeling the morphology of the gill epithelium through reorganization of cytoskeletal structures, water flux channels, and other cell structures in response to changes in the environment [ 9 , 24 , 69 ]. In hyperosmotic SW habitats, fish must increase water absorption through the GIT and lose ions, while in hypoosmotic FW habitats fish must actively uptake ions to maintain cellular homeostasis [ 9 , 20 ]. Our results are consistent with these physiological patterns, showing DEGs involved in osmoregulatory processes and adaptation to salinity across different functional categories (Table 1 and Supp. Table 7). Among populations, the SW population of Marchamalo exhibited the most pronounced transcriptional response, with the highest number of DEGs, enriched GO terms and KEGG pathways (Fig. 1 , Supp. Tables 1 –5), followed by the FW population of Adra, which also showed strong signals across functional and pathway-level analyses. In the following sections, we focus on the most relevant genes and biological processes underlying the remarkable plasticity and adaptive capacity of A. iberus to live in habitats with widely different salinity levels. Ion transport and solute carrier genes are upregulated in low salinity populations Ion transport and solute carrier genes were consistently upregulated in populations inhabiting low-salinity environments, highlighting the importance of active transport processes in osmotic regulation. Although fishes can passively exchange ions and water, active transport is often essential to maintain cellular homeostasis under fluctuating salinity conditions. Accordingly, a substantial number of DEGs identified in this study are associated with ion transport and solute carrier functions across membrane-processes highly dependent on external environmental conditions [ 24 , 34 , 70 , 71 ]. The magnitude of transcriptional differences closely mirrors the degree of environmental contrast, with comparisons between populations with larger salinity differences showing higher numbers of DEGs, while relatively few differences were found between populations with similar salinity levels, such as the two BW populations. This pattern suggests that the observed expression changes represent adaptive or plastic responses to osmotic conditions rather than background population divergence. In line with this, previous studies have shown significant variation in the abundance of transporters and ion channels in the anterior intestine, contributing to different osmoregulatory mechanisms across the gastrointestinal tract (GIT) [ 35 ]. Among ion transporters, ATPases play a fundamental role by using ATP hydrolysis to drive particle movement across membranes. The Na⁺/K⁺-ATPase alpha-1 subunit ( ATP1A1 ) which actively transport ions into (K⁺) and out (Na⁺) of the cells was significantly upregulated in the gills of the FW population from Adra. This pattern is consistent with numerous studies showing downregulation of various ATPases when FW-adapted fish are transferred to SW reflecting reduced reliance on active ion uptake in hyperosmotic environments [ 9 , 21 , 26 , 31 , 32 , 37 , 72 , 73 , 74 , 75 ]. An inverse expression pattern has been described in Arctic charr ( Salvelinus alpinus ) and chum salmon ( Oncorhynchus keta ), where ATP1α1a was predominant in SW and ATP1α1b is upregulated in SW [ 27 , 74 ] showing strong tissue and environment-dependent expression of this transporter (Supp. Table 2). Solute carriers, membrane transport proteins that facilitate the movement of small solutes along chemiosmotic gradients, were generally upregulated in FW environments due to the lower external solute concentration [ 20 , 24 , 31 ]. We detected significantly higher expression of several solute carrier families in the gills of the FW population of Adra, but also in the BW populations of Cabanes and Santa Pola and, to a lesser extent, in the SW population of Marchamalo. Notably, the chloride channel protein 2 , bumetanide-sensitive sodium-(potassium)-chloride cotransporter 2 , was upregulated across all these populations, reflecting the importance of reabsorbing sodium, potassium and chloride ions, which plays a crucial role in maintaining osmotic gradients [ 76 , 77 ]. Additional genes related to ion transporters and solute carriers identified across population comparisons included solute carrier family 9 member 1 , Na⁺/K⁺/Ca²⁺-exchange protein 3 , ATP-binding cassette sub-family D member , choline transporter-like protein 2 , neurotransmitter-gated ion-channel , and solute carrier family 12 member 9 , sodium channel protein type 4 subunit alpha B and ATP-binding cassette sub-family C member 7 (Supp. Table 2). Particularly interesting were the differential expression of the voltage-dependent L-type calcium channel subunit alpha-1C in BW Cabanes vs BW Santa Pola and BW Santa Pola vs SW Marchamalo, and the Na⁺/K⁺/Ca²⁺-exchange protein 3 in FW Adra vs SW Marchamalo, both of which are known to play key roles in ionic balance, cell volume regulation and salinity sensing [ 24 , 31 , 70 , 71 , 78 , 79 , 80 ]. Previous studies have also reported downregulation of some solute carriers and a reduction of chloride cell numbers in gills upon transfer of FW-acclimated fish to SW [ 9 , 20 , 32 , 33 ] (Supp. Table 2). Tight junction components also contributed to salinity-associated expression patterns. Claudin-3 , a protein related to occludins and involved in regulating cellular permeability, was consistently upregulated in the gills of the SW population of Marchamalo. Although claudins are usually upregulated in FW and downregulated in SW [ 20 , 21 , 25 , 66 ], recent studies have documented increased Claudin-3 levels in SW-maintained and sea-caught fish compared to FW-acclimated individuals [ 26 , 32 ]. In contrast, aquaporins, which are water channel proteins associated with volume regulation and sensing typically upregulated in FW [ 20 , 70 , 80 ], did not show differential expression across populations (Supp. Table 2), suggesting that water balance may be regulated through alternative mechanisms in the Spanish toothcarp. At the functional level, GO analysis revealed multiple terms associated with biological process related to osmoregulation, mostly including ion and transmembrane transport (Fig. 3 , Supp. Table 4). Enriched terms included ion, cation and anion transport, as well as pathways mediating the movement of potassium, chloride, sodium and calcium ions across membranes (Fig. 3 , Supp. Table 4). These processes are key components of osmotic regulation in fishes, with numerous studies reporting differences between FW and SW populations [ 21 , 31 , 34 , 66 , 70 , 71 , 75 , 79 , 81 ]. In our case, we found tissue-specific patterns, with most terms related to ion transport found exclusively in the gills, consistent with their primary role in mediating ion exchange with the external environment, while calcium ion transmembrane transport was exclusive to the GIT, indicating a distinct and complementary role of this tissue in ionic homeostasis. Increased energetic metabolism accompanies osmoregulatory adaptation across salinity gradients Numerous DEGs associated with energy metabolism were identified across population comparisons, particularly in the gills, where transcriptional divergence was highest. These included transporters and enzymes participating in energy-intensive processes, as well as genes involved in protein synthesis and the coding of key metabolic enzymes [ 66 , 69 ]. This pattern reflects the metabolic investment required to maintain homeostasis and osmotic pressure balance under salinity stress [ 24 ], a process known to demand substantial energy to cope with external salinity fluctuations and ensure survival [ 80 ]. Indeed, osmoregulatory processes can account for 20–62% of total energy expenditure under elevated salinity stress, with approximately 7% specifically attributed to gill activity [ 10 , 11 ]. Enrichment analyses further supported this trend. Several KEGG pathways related to energetic metabolism and energy acquisition were significantly overrepresented, including amino acid, lipid, and carbohydrate metabolism, as well as central aerobic pathways such as the citrate cycle (TCA cycle). Similar enrichment of energy-related pathways under seawater conditions has been reported in other teleosts [ 17 , 36 , 39 , 66 , 73 , 75 , 81 ]. In the gills, the Glycine, Serine and Threonine Metabolism pathway was significantly enriched in the comparison between FW Adra and SW Marchamalo. Serine, derived from glycolytic intermediates, and glycine, synthesized from serine, are central to metabolic flexibility under environmental change, as previously reported [ 9 , 70 , 82 ]. The citrate cycle (TCA cycle) was enriched between FW Adra and BW Cabanes, consistent with its fundamental role in aerobic oxidation of carbohydrates and fatty acids and with previous reports of citrate metabolism shifts during salinity acclimation [ 83 ]. The GO term lipid transport was also consistently overrepresented in the gills (Supp. Table 4). In contrast, the GIT showed enrichment of lipid- and carbohydrate-related pathways, including arachidonic acid metabolism (SW Marchamalo vs FW Adra) and starch and sucrose metabolism (BW Cabanes vs FW Adra). The GO term carbohydrate metabolic process was repeatedly overrepresented across comparisons. Additionally, sulfur metabolism was enriched in the comparison between SW Marchamalo and BW Santa Pola, highlighting modulation of sulfate pathways that participate in both assimilatory and dissimilatory energy processes (Fig. 3 , Supp. Table 4). Our analyses also identified DEGs involved in fatty acid and carbohydrate metabolism, which serve as major energy reservoirs or direct substrates [ 17 , 31 , 33 , 39 , 73 , 75 , 81 ]. Among them, mannose-P-dolichol utilization defect 1 was upregulated in the GIT of BW Cabanes and in the gills of BW Santa Pola, indicating enhanced glycosylation processes. The B30.2/SPRY domain superfamily was upregulated in the GIT of SW Marchamalo and is associated with carbohydrate recognition and binding (Supp. Table 2). Collectively, these results indicate that energy production and substrate utilization pathways are tightly modulated across salinity gradients, supporting extensive metabolic reprogramming in response to osmotic stress [ 10 , 11 ]. Signal transduction and transcriptional regulation are overrepresented in extreme salinity populations Signal transduction and transcription-related genes were strongly overrepresented in extreme salinity populations (FW Adra and SW Marchamalo). As primary osmosensory organs, gills detect environmental changes and initiate downstream signaling cascades that increase cellular metabolism and mitochondrial activity, ultimately contributing to pathway enrichment and a higher number of DEGs across populations [ 20 , 72 ]. One of the most prominent internal responses is enhanced ribosome production, which increases translational capacity and protein synthesis; however, this efficiency may become compromised under excessive salinity [ 20 , 36 , 81 ]. Consistent with these patterns, many of the top DEGs identified along the salinity gradient were involved in receptor-mediated signaling, ubiquitination, chromatin remodeling, and transcriptional regulation, a trend further supported by GO enrichment analyses, where over half of the identified terms were associated with signal transduction and transcriptional regulation across all three GO categories. Enriched domains frequently included zinc-binding and nucleic acid-interacting motifs, supporting a role for Zn²⁺-dependent transcriptional modulation under osmotic stress [ 20 ]. Moreover, KEGG analyses indicated that amino acid metabolism is central to transcriptional and signaling responses under salinity stress, in agreement with previous studies [ 9 , 70 , 79 , 81 ]. Extreme salinity populations (FW Adra and SW Marchamalo) exhibited the strongest transcriptional signatures along the salinity gradient, concentrating the highest proportion of signal transduction- and transcription-related responses. In FW Adra gills, several of the top DEGs encoded integrases ( integrase zinc-binding domain ), ubiquitin ligases ( HECT , E3 ligase catalytic domain ), G protein-coupled receptors , NACHT-associated domain, family 2 secretin-like , and ASB-5 (ankyrin repeat and SOCS box protein 5), highlighting activation of receptor-mediated signaling and protein turnover pathways. In the GIT, FW Adra showed differential expression of integrase zinc-binding domain proteins , calpain-5 , Brf1 , TBP-binding domain , and leucine-rich repeat and guanylate kinase domain-containing proteins , reinforcing the prominence of transcriptional and post-transcriptional regulation. At the opposite extreme, SW Marchamalo also displayed a marked enrichment of signaling and regulatory components. In gills, highly expressed genes included cytochrome c , members of the endonuclease/exonuclease/phosphatase superfamily , and several ribonuclease H-like proteins, consistent with intensified transcriptional and DNA/RNA processing activity. In the GIT, domains such as sterile alpha motif, butyrophilin-like, integrase catalytic core, MyHC-beta (XRCC4-like), HECT (E3 ligase catalytic domain), and GTPase IMAP family member 7 were prominent, many of which are implicated in osmoregulatory signaling pathways including GPCR- and MAPK-related cascades [ 20 , 39 , 66 ] (Supp. Table 2). Enrichment analyses reinforced this pattern. Amino acid metabolism emerged as central to transcriptional regulation under salinity stress, consistent with previous studies [ 9 , 70 , 79 , 81 ], with Cysteine and methionine metabolism enriched in FW Adra gills, and Tryptophan metabolism and Selenocompound metabolism enriched in GIT comparisons involving FW Adra vs SW Marchamalo and BW Cabanes, respectively (Fig. 3 , Supp. Table 4). Additional SW Marchamalo-associated pathways included RNA degradation and DNA replication . Consistently, over half of the identified GO terms were linked to signal transduction and transcriptional regulation, with particularly strong representation in FW Adra and SW Marchamalo across all three GO categories. In the gills, Molecular Function terms included nucleic acid, ATP, zinc ion and GTP binding , together with activities such as methyltransferase and 2 -oxoglutarate-dependent dioxygenase . Biological Process terms encompassed DNA integration, proteolysis, transcriptional regulation, lipid transport, GPCR signaling , and transposition . In the GIT, additional enrichment of protein phosphorylation, cell surface receptor signaling , and DNA repair further emphasized the intensity of regulatory remodeling at the salinity extremes. Together, these results position the freshwater and hypersaline populations as the endpoints of the gradient where transcriptional reprogramming and signaling activity are most pronounced (Supp. Table 4). In the two BW populations (Cabanes and Santa Pola), gene expression patterns reflected an intermediate but still pronounced activation of regulatory and signaling machinery. In the gills, domains associated with ubiquitination and protein turnover (e.g., HECT E3 ligase catalytic domain ), DNA repair and polymerase activity, as well as glycosyltransferases such as BGnT-7 , were detected. In the GIT, both populations showed enrichment of transcription- and signaling-related factors, including Piwi-like protein 2 , TATA box-binding protein-like 2 , DnaJ homolog subfamily B member 6 , helically-extended SH3 domains, Tudor domains, and P2X purinoreceptor , alongside proteins involved in RNA processing (e.g., DDX43 ), post-translational modification (F-box proteins, transglutaminase-like), and vesicular trafficking ( PRA1 ). Together, these profiles indicate that brackish populations maintain active regulatory and signaling networks, but with a comparatively moderated transcriptional response relative to the freshwater and hypersaline endpoints of the gradient. Immune response and apoptosis are modulated by salinity gradients Immune-related genes were differentially regulated across the salinity gradient, with both brackish and extreme salinity populations showing distinct immune signatures depending on tissue and comparison. Enrichment analyses revealed multiple GO terms associated with immune system processes, cytokine activity, antigen presentation, and apoptotic regulation, particularly in the gills and GIT (Fig. 3 ; Supp. Table 4). These patterns indicate that salinity shifts are accompanied by coordinated modulation of innate and adaptive immune components, consistent with the well-documented role of environmental salinity as a physiological stressor in fishes [ 34 , 72 ]. Numerous studies have identified genes implicated in salinity-associated immune responses across osmoregulatory organs, enabling the reconstruction of defense mechanisms at the molecular level [ 34 , 39 , 79 ]. Cytokine-mediated signaling emerged as a prominent component of the salinity-associated immune response. Cytokines act as key messengers regulating communication between immune and non-immune cells during early immune activation. GO term analyses revealed enrichment of immune-related genes, particularly in the gills, where an interleukin-8-like chemokine domain was upregulated in BW Cabanes and Santa Pola relative to FW and SW populations. The interleukin gene itself was upregulated in BW Cabanes compared to SW Marchamalo, but downregulated in FW Adra relative to both SW Marchamalo and BW Santa Pola. As central regulators of innate and adaptive immunity, interleukins enable rapid responses to environmental stressors such as fluctuating salinity [ 84 ]. Consistent with this pattern, multifunctional proteins interacting with cytokine pathways were also detected in BW populations, including ATP receptors and Butyrate response factor 1 (Tristetraprolin), a zinc finger protein involved in immune regulation, cell proliferation, and differentiation [ 85 , 86 ]. In the GIT, helically-extended SH3 domain-containing proteins and nuclear factor interleukin-3-regulated protein were upregulated in BW populations relative to SW Marchamalo, further supporting enhanced cytokine-associated signaling under intermediate salinity conditions. Together, these coordinated transcriptional changes suggest an adaptive immune adjustment to fluctuating brackish environments, consistent with previous findings in euryhaline fishes [ 37 , 39 , 75 , 79 , 87 ] (Fig. 3 , Supp. Table 4). Beyond cytokine signaling, additional components of adaptive and stress-associated immunity were differentially regulated across the salinity gradient. MHC class II genes were upregulated in FW Adra and SW Marchamalo relative to BW Santa Pola, suggesting enhanced antigen presentation capacity at the salinity extremes. The major histocompatibility complex class II plays a central role in adaptive immune activation [ 88 ]. In contrast, Immunoglobulin C1-set domain-containing proteins were downregulated in FW Adra compared to BW Cabanes and SW Marchamalo, indicating population-specific modulation of humoral immune components. Heat shock proteins (HSPs), which contribute to both cellular protection and immune regulation under stress, were also differentially expressed. Heat shock 70 kDa protein 12A was upregulated in the GIT of FW Adra and in the gills of BW Santa Pola. HSPs facilitate protein refolding and participate in cell cycle control, and their induction under salinity stress has been widely documented [ 37 , 79 , 82 , 89 ]. However, reduced HSP expression has also been reported under specific stress contexts or combined salinity-temperature challenges [ 32 , 38 ]. Upregulation of HSP family members, including ubiquitin-related proteins, has likewise been described during salinity transfer [ 32 , 41 ]. In addition, immune effector components were differentially modulated along the salinity gradient. The membrane attack complex component/perforin (MAC) , essential for cytotoxic activity in both innate and adaptive immunity, was downregulated in BW Cabanes relative to FW Adra, highlighting variation in terminal immune responses across environmental conditions (Fig. 3 , Supp. Tables 2, 4). While acute salinity shifts can activate immune pathways, prolonged exposure may weaken immune capacity and increase susceptibility to infection [ 90 ], suggesting that sustained osmotic stress can exceed compensatory immune mechanisms. Under such conditions, cumulative cellular damage may activate apoptotic signaling pathways. Although Aphanius iberus is euryhaline, sustained osmotic stress may shift the balance from adaptive plasticity toward programmed cell death. Both KEGG and GO analyses supported this pattern, revealing enrichment of apoptosis-related pathways, particularly in the GIT [ 20 , 21 , 37 , 66 , 91 ]. Notably, the KEGG Apoptosis pathway was enriched in GIT comparisons between BW Cabanes and FW Adra. Regulatory components associated with apoptotic modulation were also detected, including apoptosis inhibitor-2 (c-IAP2) and junctophilin in the GIT of BW Santa Pola. In addition, Butyrate response factor 1 / Tristetraprolin , a regulator of tumor necrosis factor production and inflammatory signaling, was upregulated in the GIT of BW Cabanes (Supp. Table 4). Together, these results indicate that prolonged or extreme salinity exposure not only activates immune and stress-related pathways but may also engage cell death mechanisms, particularly in intestinal tissues, highlighting the physiological limits of osmotic tolerance. Structural organization remodeling under salinity stress Genes associated with cytoskeletal organization and structural remodeling, together with the majority of GO terms within the Cellular Component category, were differentially expressed across the salinity gradient, with a particularly marked signal in BW populations. In the GIT of both BW populations, several DEGs were linked to cytoskeletal structure and cell adhesion, suggesting enhanced structural plasticity under fluctuating salinity conditions. In BW Cabanes, a KASH domain containing protein was detected, a domain typically localized at the outer nuclear membrane and involved in nuclear positioning and force transmission between the nucleoskeleton and the cytoplasmic cytoskeleton. Additionally, the helically-extended SH3 domain was upregulated in both BW populations (Cabanes and Santa Pola). This variant SH3 fold functions as a lipid interaction module capable of binding acidic phospholipids and is associated with integrin complexes, which mediate cell–cell adhesion and mechanotransduction [ 17 , 25 , 66 ]. These patterns indicate that BW populations may require enhanced cytoskeletal flexibility to rapidly adjust cellular architecture and maintain cytoplasmic volume under fluctuating osmotic conditions. Changes in cell volume caused by passive water diffusion necessitate rapid reorganization of cytoskeletal elements to preserve structural integrity and cellular homeostasis. Chromatin-associated structural components were also modulated. Histones, which regulate chromatin condensation and transcriptional accessibility, have previously been implicated in osmotic acclimation [ 23 ]. In our dataset, Histone H1a was upregulated in the gills of FW Adra, while Histone H4 was upregulated in the gills of BW Cabanes. Furthermore, the chromatin-target of PRMT1 (C-terminal) protein was upregulated in the GIT of BW Santa Pola. This protein associates with facultative heterochromatin and participates in transcriptional regulation, suggesting coordinated structural and epigenetic remodeling under salinity stress [ 21 , 23 ] (Supp. Table 2). Within the Cellular Component category, numerous GO terms were associated with structural elements and membrane organization. The most frequent terms across both tissues included integral component of membrane, membrane , and extracellular region. Gill-specific enrichment of plasma membrane and extracellular space further highlights the structural role of this tissue as the primary interface for osmotic exchange, whereas cytoplasm and integral component of plasma membrane were particularly prominent in the GIT (Fig. 3 , Supp. Table 4). Together, these results indicate coordinated remodeling of cytoskeletal, membrane, and chromatin architecture in response to salinity stress. Activation of Repetitive Elements under salinity stress The Tc1 DNA transposon , which mediates the mobilization of DNA transposons to new genomic loci, was upregulated in the gills of both the FW Adra and SW Marchamalo populations, indicating activation of DNA transposons at the salinity extremes [ 92 ]. In addition, the Barney transposase (Tcb1 transposase ) was upregulated in the GIT of SW Marchamalo, and the L1 element , a non-LTR retrotransposon belonging to the Long Interspersed Nuclear Elements (LINEs), which transpose via an RNA intermediate, showed increased expression in the gills of BW Santa Pola [ 93 , 94 ]. These patterns suggest that repetitive elements respond dynamically to osmotic conditions across tissues and environments (Supp. Table 2). Repetitive elements can modulate the expression of genes critical for osmoregulation and facilitate rapid adaptation to saline or fluctuating environments, acting as drivers of plasticity and evolutionary change [ 95 , 96 ], consistent with the activation patterns observed along the salinity gradient. We also detected upregulation of an RRM (RNA recognition motif) domain-containing gene, consistent with altered RNA processing and post-transcriptional regulation under stress [ 97 ]. Furthermore, a PiggyBac transposable element-derived protein was upregulated in the GIT of BW Cabanes and SW Marchamalo. Although PiggyBac -derived proteins are conserved across taxa, their functional roles in stress adaptation remain poorly understood [ 98 , 99 ]. Together, these findings indicate that activation of repetitive elements forms part of the broader transcriptional remodeling observed along the salinity gradient, potentially contributing to regulatory plasticity in A. iberus under osmotic stress. Ecological and conservation implications The pattern observed, with substantially higher numbers of differentially expressed genes in populations inhabiting both hypo- and hyperosmotic environments, suggests that although Aphanius iberus tolerates a broad salinity range, intermediate salinity conditions may represent comparatively less physiologically demanding environments. The elevated transcriptional responses observed at salinity extremes likely reflect the substantial energetic and regulatory costs required to maintain ionic and osmotic homeostasis, consistent with patterns described in other euryhaline fishes [ 20 , 31 , 75 ]. Exposure to salinity extremes triggers coordinated cellular responses aimed at preserving homeostasis, including activation of signaling cascades, cytoskeletal remodeling, modulation of membrane transport processes, immune regulation, apoptotic pathways, and enhanced energetic metabolism [ 20 , 75 , 80 ]. Tissue-specific transcriptional signatures, particularly in the gastrointestinal tract, indicate that spatial physiological specialization within intestinal tissues contributes significantly to overall osmoregulatory capacity [ 35 ]. Collectively, these results demonstrate that A. iberus modulates interconnected osmoregulatory, metabolic, immune, and stress-response pathways under osmotic challenge, revealing substantial transcriptional plasticity across environmental contexts. From a ecological perspective, transitional habitats with intermediate salinity may function as energetically favorable environments and could therefore play a stabilizing role in population persistence. At the same time, the persistence of populations in hypersaline systems, where reduced interspecific competition may offset physiological costs, underscores the ecological flexibility of the species. In a context of accelerating anthropogenic salinization and climate-driven hydrological instability, such plasticity may represent a key component of resilience. By generating a comprehensive reference transcriptome for Aphanius iberus , this study provides a genomic framework for future comparative and evolutionary analyses of euryhalinity in fishes. It also expands the application of environmental transcriptomics to an endemic species currently listed as Endangered in the Spanish National Catalogue of Threatened Species ([ 42 ]; Real Decreto 139/2011 (BOE-A-2011-3582)). More broadly, these findings contribute to understanding whether convergent molecular strategies underlie osmotic tolerance across phylogenetically distant taxa, a question of increasing relevance in the context of global climate change. Conclusions This study provides the first transcriptomic characterization of salinity responses in the endangered Spanish toothcarp, Aphanius iberus . Our results reveal strong tissue-specific transcriptional responses along a natural salinity gradient, with gills showing extensive differential expression related to ion transport, cytoskeletal organization, and energetic metabolism, while the gastrointestinal tract displayed enrichment of metabolic pathways. The increased number of differentially expressed genes detected in populations inhabiting both hypo- and hyperosmotic environments suggests that intermediate salinity conditions may represent comparatively less physiologically demanding habitats for this species. These findings highlight the coordinated molecular mechanisms that enable A. iberus to tolerate extreme and fluctuating osmotic environments and contribute to expanding environmental transcriptomics in non-model and conservation-relevant species. The reference transcriptome generated here provides a valuable genomic resource for future comparative and evolutionary studies of euryhalinity in fishes and may facilitate further research on the molecular basis of salinity tolerance in Mediterranean coastal systems. Nevertheless, because our analyses are based on transcriptomic profiles from wild populations, environmentally induced plastic responses cannot be fully distinguished from potential population-level genetic differentiation. In addition, only two osmoregulatory tissues were analyzed, whereas other organs such as kidney or liver may also contribute to salinity acclimation. Future studies combining experimental approaches, broader tissue sampling, and population genomic analyses will help clarify the regulatory mechanisms underlying osmotic adaptation in this species. Declarations Ethics approval and consent to participate All procedures were reviewed and approved by the Animal Experimentation Ethics Committee of the National Museum of Natural Sciences (CEEA-MNCN; Spanish Animal Experimentation Research Centre no. ES280790000189) and conducted in strict accordance with Spanish law RD53/2013, which transposes the EU Directive 2010/63/EU (art. 2, 5f). Experimental protocols followed relevant guidelines and regulations and are reported in compliance with the ARRIVE guidelines (https://arriveguidelines.org). Humane endpoints were defined a priori: following immersion in the anesthetic solution, fish were monitored for the immediate loss of opercular movement and reflexes to confirm effective euthanasia and safeguard animal welfare. Sampling of Aphanius iberus was conducted under appropriate regional authorizations: ● In Andalusia, sampling in Adra was covered by the Resolución de la Directora General de Medio Natural, Biodiversidad y Espacios Protegidos (25 January 2021), which grants an exception to the general protection regime and authorizes the capture and handling of Aphanius species for scientific purposes, including the inclusion of I. Doadrio and A. López Solano as members of the approved research team. ● In Valencia, the Dirección General de Medio Natural i Animal authorized the collection and euthanasia of eight Aphanius iberus individuals for RNA preservation, under Article 13.1 of Decree 32/2004 regulating the Valencian Catalogue of Threatened Fauna Species. ● In Murcia, sampling in the Salinas de Marchamalo (Mar Menor area) was conducted under research permit AUF/2022/0007, with institutional support from the Universidad de Murcia and collaboration of Dr. Francisco J. Oliva-Paterna, who certified compliance with all regional regulations. Consent for publication Not applicable. Availability of data and materials The raw sequence reads generated during the current study are available in the NCBI Nucleotide Database under the Bioproject (PRJNA1041354), with accession numbers provided in Supp. Table 1. Competing interests The authors declare that they have no competing interests. Funding This project was supported by the Ministerio de Ciencia, Innovación y Universidades, Spain (Project Saltfish; PID2023-146173NB-C22) granted to ID. AL-S is funded by an FPI fellowship from the same governmental institution (PRE2020-092988). EA is supported by a predoctoral fellowship (FPI-UAH 2023, Universidad de Alcalá Programme), Spain. TLN is supported by an FPU fellowship (FPU2020/04500) from the Ministerio de Ciencia, Innovación y Universidades, Spain. Authors' contributions AL-S, AV, SP and ID contributed to the conceptualization and to the research design. AL-S and TLN carried out the field work. AL-S, AV and EA performed the laboratory work. The analyses of the data were led by AL-S and AV with collaboration of SP and EA. The interpretation of the results was performed by all the authors. AL-S wrote the first draft which was revised by all authors. Acknowledgements We would like to thank the Spanish Ministry of Science and Innovation and the State Agency for Research for their financial support through Project Saltfish (PID2023-146173NB-C22) awarded to Ignacio Doadrio. We also acknowledge support from a fellowship from “la Caixa” Foundation (ID 100010434), with fellowship code LCF/BQ/PR24/12050011 and a Ramón y Cajal grant RYC2023-044466-I awarded to Aida Verdes. We are grateful to Sergio García Peña for his help in the sampling. We would also like to thank Antonio Pradillo, Jesús Hernández, and Pilar Risueño from the Centro de Conservación de Especies Dulceacuícolas ("Piscifactoría de El Palmar") for their assistance with sampling and for obtaining the requisite permission granted by the Government of Valencia (Spain). We also thank Francisco Oliva-Paterna from the University of Murcia for his help with sampling and permits in Murcia, and Mariano Paracuellos from the University of Almería for his support with sampling in Adra. We further acknowledge the Universidad Complutense de Madrid for hosting Alfonso López-Solano and Tessa Lynn Nester within the Doctorado en Biología program. We also acknowledge the Universidad de Alcalá for hosting Elena Andrés within the PhD program in Ecology, Biodiversity and Global Change. Finally, we thank CESGA (Centro de Supercomputación de Galicia) for its indispensable contribution to data analysis. References Carpenter SR, Stanley EH, Vander Zanden MJ. State of the world’s freshwater ecosystems: physical, chemical, and biological changes. Annu Rev Environ Resour. 2011;36(1):75-99. doi:10.1146/annurev-environ-021810-094524 Seehausen O, Wagner CE. Speciation in freshwater fishes. Annu Rev Ecol Evol Syst. 2014;45(1):621-651. doi:10.1146/annurev-ecolsys-120213-091818. Lee CE, Bell MA. Causes and consequences of recent freshwater invasions by saltwater animals. Trends Ecol Evol. 1999;14(7):284-288. doi:10.1016/S0169-5347(99)01596-7 Schneider RF, Meyer A. How plasticity, genetic assimilation and cryptic genetic variation may contribute to adaptive radiations. Mol Ecol. 2017;26(1):330-350. doi:10.1111/mec.13880. Hoar WS, Randall DJ, Donaldson EM. Fish physiology. Vol. 10-11. New York: Academic Press; 1983. Schultz ET, McCormick SD. Euryhalinity in an evolutionary context. In: McCormick SD, Farrell AP, Brauner CJ, editors. Fish physiology. Vol. 32. New York: Academic Press; 2012. p. 477-533. McCormick SD, Farrell AP, Brauner CJ, editors. Fish physiology: euryhaline fishes. Vol. 32. New York: Academic Press; 2013. Mauro AA, Velotta JP, Ghalambor CK. A systems approach to homeostasis: what euryhaline fish teach us about organismal stress responses. Integr Comp Biol. 2025;icaf085. doi:10.1093/icb/icaf085 Vij S, Purushothaman K, Sridatta PSR, Jerry DR. Transcriptomic analysis of gill and kidney from Asian seabass ( Lates calcarifer ) acclimated to different salinities reveals pathways involved with euryhalinity. Genes. 2020;11(7):733. doi:10.3390/genes11070733. Hoar WS, Randall DJ, Donaldson EM, editors. Fish physiology. New York: Academic Press; 1983. Bœuf G, Payan P. How should salinity influence fish growth? Comp Biochem Physiol C Toxicol Pharmacol. 2001;130(4):411-423. doi:10.1016/S1532-0456(01)00268-X. Cunillera-Montcusí D, Beklioğlu M, Cañedo-Argüelles M, Jeppesen E, Ptacnik R, Amorim CA, et al. Freshwater salinisation: a research agenda for a saltier world. Trends Ecol Evol. 2022;37(5):440-453. doi:10.1016/j.tree.2021.12.005 Małachowicz M, Krasnov A, Wenne R. Diverse transcriptome responses to salinity change in Atlantic cod subpopulations. Cells. 2023;12(23):2760. doi:10.3390/cells12232760. Kültz D. Physiological mechanisms used by fish to cope with salinity stress. J Exp Biol. 2015;218(12):1907–1914. Shi Z, Huang X, Fu R, Wang H, Luo H, Chen B, et al. Salinity stress on embryos and early larval stages of the pomfret Pampus punctatissimus . Aquaculture. 2008;275(1-4):306-310. doi:10.1016/j.aquaculture.2008.01.030 Yuan XC, He S, Liang XF, Luo X, Li A, Zhou Y. Food conditions and water salinity affect survival and growth of golden mandarin fish, Siniperca scherzeri , larvae through transcriptional regulation of growth and lipometabolic genes. J World Aquac Soc. 2018;49(3):590-600. doi:10.1111/jwas.12450 Wong MKS, Ozaki H, Suzuki Y, Iwasaki W, Takei Y. Discovery of osmotic sensitive transcription factors in fish intestine via a transcriptomic approach. BMC Genomics. 2014;15:947. doi:10.1186/1471-2164-15-1134 Evans DH, Piermarini PM, Choe KP. The multifunctional fish gill: dominant site of gas exchange, osmoregulation, acid-base regulation, and excretion of nitrogenous waste. Physiol Rev. 2005;85(1):97–177. Edwards SL, Marshall WS. Principles and patterns of osmoregulation and euryhalinity in fishes. In: Perry SF, Farrell AP, Brauner CJ, editors. Fish physiology. Vol. 32. New York: Academic Press; 2012. p. 1-44. doi:10.1016/B978-0-12-396951-4.00001-3. Lam SH, Lui EY, Li Z, Cai S, Sung WK, Mathavan S, et al. Differential transcriptomic analyses revealed genes and signaling pathways involved in iono-osmoregulation and cellular remodeling in the gills of euryhaline Mozambique tilapia, Oreochromis mossambicus . BMC Genomics. 2014;15:921. doi:10.1186/1471-2164-15-921. Whitehead A, Roach JL, Zhang S, Galvez F. Salinity- and population-dependent genome regulatory response during osmotic acclimation in the killifish ( Fundulus heteroclitus ) gill. J Exp Biol. 2012;215(8):1293-1305. doi:10.1242/jeb.062075 Rana SB, Zadlock IV FJ, Zhang Z, Murphy WR, Bentivegna CS. Comparison of de novo transcriptome assemblers and k-mer strategies using the killifish, Fundulus heteroclitus . PLoS One. 2016;11(4):e0153104. doi:10.1371/journal.pone.0153104. Whitehead A, Roach JL, Zhang S, Galvez F. Genomic mechanisms of evolved physiological plasticity in killifish distributed along an environmental salinity gradient. Proc Natl Acad Sci U S A. 2011;108(15):6193-6198. doi:10.1073/pnas.1017542108. Cui Q, Qiu L, Yang X, Shang S, Yang B, Chen M, et al. Transcriptome profiling of the low-salinity stress responses in the gills of the juvenile Pseudopleuronectes yokohamae . Comp Biochem Physiol D Genomics Proteomics. 2019;32:100612. doi:10.1016/j.cbd.2019.100612. Li C, Zhang Y, Wang R, Lu J, Nandi S, Mohanty S, et al. RNA-seq analysis of mucosal immune responses reveals signatures of intestinal barrier disruption and pathogen entry following Edwardsiella ictaluri infection in channel catfish, Ictalurus punctatus . Fish Shellfish Immunol. 2012;32(5):816-827. doi:10.1016/j.fsi.2012.02.004 Boutet I, Ky CL, Bonhomme F. A transcriptomic approach of salinity response in the euryhaline teleost Dicentrarchus labrax . Gene. 2006;379:40-50. doi:10.1016/j.gene.2006.04.011 Norman JD, Ferguson MM, Danzmann RG. An integrated transcriptomic and comparative genomic analysis of differential gene expression in Arctic charr ( Salvelinus alpinus ) following seawater exposure. J Exp Biol. 2014;217(22):4029-4042. doi:10.1242/jeb.107441 Mohindra V, Chowdhury LM, Chauhan N, Paul A, Singh RK, Kushwaha B, et al. Transcriptome analysis revealed osmoregulation related regulatory networks and hub genes in the gills of Hilsa shad, Tenualosa ilisha , during the migratory osmotic stress. Mar Biotechnol. 2023;25(1):161-173. doi:10.1007/s10126-022-10190-4 Pan J, Wang M, Zhu J, Huang Y, Zhang F, Li E, et al. Quantitative proteomic and metabolomic profiling reveals different osmoregulation mechanisms of tilapia cells coping with different hyperosmotic stress. J Proteomics. 2024;296:105113. doi:10.1016/j.jprot.2024.105113. Li C, Wang L, Pan M, Wang R, Zhang H, Li W, et al. Comparative transcriptomic analysis reveals osmoregulatory mechanisms of juvenile Lateolabrax maculatus responses to long-term hypotonic and hypertonic acclimation. Aquaculture. 2025;596:741864. doi:10.1016/j.aquaculture.2024.741864 Gibbons TC, Metzger DCH, Healy TM, Schulte PM. Gene expression plasticity in response to salinity acclimation in threespine stickleback ecotypes from different salinity habitats. Mol Ecol. 2017;26(10):2711-2725. doi:10.1111/mec.14065 Taugbøl A, Solbakken MH, Jakobsen KS, Vøllestad LA. Salinity-induced transcriptome profiles in marine and freshwater threespine stickleback after an abrupt 6-hour exposure. Ecol Evol. 2022;12(10):e9395. doi:10.1002/ece3.9395. Lai KP, Li JW, Wang SY, Chiu JMY, Tse A, Lau K, et al. Tissue-specific transcriptome assemblies of the marine medaka Oryzias melastigma and comparative analysis with the freshwater medaka Oryzias latipes . BMC Genomics. 2015;16:135. doi:10.1186/s12864-015-1325-7 Chen X, Gong H, Chi H, Xu B, Zheng Z, Bai Y. Gill transcriptome analysis revealed the difference in gene expression between freshwater and seawater acclimated guppy ( Poecilia reticulata ). Mar Biotechnol. 2021;23(4):615-627. doi:10.1007/s10126-021-10053-4 Ronkin D, Seroussi E, Nitzan T, Doron-Faigenboim A, Cnaani A. Intestinal transcriptome analysis revealed differential salinity adaptation between two tilapiine species. Comp Biochem Physiol D Genomics Proteomics. 2015;13:35-43. doi:10.1016/j.cbd.2015.01.003 Xu Z, Gan L, Li T, Xu C, Chen K, Wang X, et al. Transcriptome profiling and molecular pathway analysis of genes in association with salinity adaptation in Nile tilapia Oreochromis niloticus . PLoS One. 2015;10(8):e0136506. doi:10.1371/journal.pone.0136506. Valenzuela-Muñoz V, Váldes JA, Gallardo-Escárate C. Transcriptome profiling of long non-coding RNAs during the Atlantic salmon smoltification process. Mar Biotechnol. 2021;23:308-320. doi:10.1007/s10126-021-10024-9 Sánchez CC, Weber GM, Gao G, Cleveland BM, Yao J, Rexroad CE. Generation of a reference transcriptome for evaluating rainbow trout responses to various stressors. BMC Genomics. 2011;12:626. doi:10.1186/1471-2164-12-626. Zhang X, Wen H, Wang H, Ren Y, Zhao J, Li Y. RNA-Seq analysis of salinity stress–responsive transcriptome in the liver of spotted sea bass ( Lateolabrax maculatus ). PLoS One. 2017;12(3):e0173238. doi:10.1371/journal.pone.0173238. Shen Y, He Y, Bi Y, Chen J, Zhao Z, Li J, et al. Transcriptome analysis of gill from Lateolabrax maculatus and aqp3 gene expression. Aquac Fish. 2019;4(6):247-254. doi:10.1016/j.aaf.2019.03.004 Li X, Liu S, Wang Y, Lu W, Zhang Q, Cheng J. Genomic and transcriptomic landscape and evolutionary dynamics of heat shock proteins in spotted sea bass ( Lateolabrax maculatus ) under salinity change and alkalinity stress. Biology. 2022;11(3):353. doi:10.3390/biology11030353 Doadrio I, editor. Atlas y Libro Rojo de los Peces Continentales de España. Madrid: Dirección General de Conservación de la Naturaleza - Museo Nacional de Ciencias Naturales; CSIC/MIMAM; 2001. Doadrio I. Ictiofauna continental española: bases para su seguimiento. Madrid: Ministerio de Medio Ambiente y Medio Rural y Marino, Centro de Publicaciones; 2011. Bonzi LC, Poltronieri C, Maradonna F, Gioacchini G, Carnevali O. The time course of molecular acclimation to seawater in a euryhaline fish. Sci Rep. 2021;11:18127. doi:10.1038/s41598-021-97295-3 Wilson EJ, Barts N, Coffin JL, Johnson JB, Rodríguez Peña CM, Kelley JL, et al. Gene expression signatures between Limia perugiae (Poeciliidae) populations from freshwater and hypersaline habitats, with comparisons to other teleosts. PLoS One. 2024;19(12):e0315014. Doi:10.1371/journal.pone.0315014 Alcaraz C, Pou-Rovira Q, García-Berthou E. Use of a flooded salt marsh habitat by an endangered cyprinodontid fish ( Aphanius iberus ). Hydrobiologia. 2008;600(1):177-185. doi:10.1007/s10750-007-9230-y Oliva-Paterna FJ, Ruiz-Navarro A, Torralva M, Fernández-Delgado C. Biology of the endangered cyprinodontid Aphanius iberus in a saline wetland (SE Iberian Peninsula). Ital J Zool. 2009;76(3):316-329. doi:10.1080/11250000802488159 Perdices A, Carmona JA, Fernández-Delgado C, Doadrio I. Nuclear and mitochondrial data reveal high genetic divergence among Atlantic and Mediterranean populations of the Iberian killifish Aphanius iberus (Teleostei: Cyprinodontidae). Heredity. 2001;87(3):314–324. Doadrio I, Carmona JA, Fernández-Delgado C. Morphometric study of the Iberian Aphanius (Actinopterygii, Cyprinodontiformes), with description of a new species. Folia Zool. 2002;51:67–79. González EG, Cunha C, Ghanavi HR, Oliva-Paterna FJ, Torralva M, Doadrio I. Phylogeography and population genetic analyses in the Iberian toothcarp ( Aphanius iberus Valenciennes, 1846) at different time scales. J Hered. 2018;109(3):253–263. doi:10.1093/jhered/esx076. Nester TL, López-Solano A, Perea S, Doadrio I. Genomic population structure and diversity of the endangered Aphanius iberus : strategies for killifish conservation. Conserv Genet. 2025;26(2):263–277. Estarellas M, López-Solano A, Mochales-Riaño G, Perea S, Talavera A, Burriel-Carranza B, et al. Saving the locals: a conservation genomics approach to the endangered Spanish toothcarp, Aphanius iberus (Valenciennes, 1846). Sci Rep. 2025. Andrews S. FastQC: a quality control tool for high throughput sequence data. 2010. http://www.bioinformatics.babraham.ac.uk/projects/fastqc. Accessed Mar 2025. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114-2120. doi:10.1093/bioinformatics/btu170 López-Solano A, Doadrio I, Nester TL, Perea S. De novo genome hybrid assembly and annotation of the endangered and euryhaline fish Aphanius iberus (Valenciennes, 1846) with identification of genes potentially involved in salinity adaptation. BMC Genomics. 2025;26:136. doi:10.1186/s12864-025-11327-0 Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15-21. doi:10.1093/bioinformatics/bts635. Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290-295. doi:10.1038/nbt.3122. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat Biotechnol. 2011;29(7):644-652. doi:10.1038/nbt.1883. Kolde R. pheatmap: Pretty heatmaps. R package version 1.0.12. 2015. https://CRAN.R-project.org/package=pheatmap. Accessed Apr 2025. Blighe K, Rana S, Lewis M. EnhancedVolcano: publication-ready volcano plots with enhanced colouring and labeling. R package version 1.27.0. 2025. doi:10.18129/B9.bioc.EnhancedVolcano Posit Team. RStudio: integrated development environment for R. Boston (MA): Posit Software, PBC; 2025. https://www.posit.co/. Accessed Jan 2025. Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, et al.InterPro‑Scan 5: Genome-scale protein function classification. Bioinformatics. 2014;30(9):1236–40. Casimiro-Soriguer CS, Muñoz-Mérida A, Pérez-Pulido AJ. Sma3s: a universal tool for easy functional annotation of proteomes and transcriptomes. Proteomics. 2017;17(12):1700071. doi:10.1002/pmic.201700071 Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49(D1):D545-D551. doi:10.1093/nar/gkaa970 Ge SX, Jung D, Yao R. ShinyGO: a graphical enrichment tool for animals and plants. Bioinformatics. 2020;36(8):2628-2629. doi:10.1093/bioinformatics/btz931. Nguyen TV, Jung H, Nguyen TM, Hurwood D, Mather P. Evaluation of potential candidate genes involved in salinity tolerance in striped catfish ( Pangasianodon hypophthalmus ) using an RNA-Seq approach. Mar Genomics. 2016;25:75-88. doi:10.1016/j.margen.2015.11.010 Liang P, Saqib HSA, Lin Z, Zheng R, Qiu Y, Xie Y, et al. RNA-seq analyses of marine medaka ( Oryzias melastigma ) reveal salinity responsive transcriptomes in the gills and livers. Aquat Toxicol. 2021;240:105970. doi:10.1016/j.aquatox.2021.105970. Lin G, Li S, Huang J, Gao D, Lu J. Hypoosmotic stress induced functional alternations of intestinal barrier integrity, inflammatory reactions, and neurotransmission along gut-brain axis in the yellowfin seabream ( Acanthopagrus latus ). Fish Physiol Biochem. 2021;47(6):1725-1738. doi:10.1007/s10695-021-01011-x Tine M, De Lorgeril J, D'Cotta H, Pepey E, Bonhomme F, Baroiller JF, et al. Transcriptional responses of the black-chinned tilapia Sarotherodon melanotheron to salinity extremes. Mar Genomics. 2008;1(2):37-46. doi:10.1016/j.margen.2008.06.001 Su H, Ma D, Zhu H, Liu Z, Gao F. Transcriptomic response to three osmotic stresses in gills of hybrid tilapia ( Oreochromis mossambicus female × O. urolepis hornorum male). BMC Genomics. 2020;21:673. doi:10.1186/s12864-020-6512-5 Escobar-Sierra C, Canedo-Argüelles M, Vinyoles D, Lampert KP. Unravelling the molecular mechanisms of fish salinity adaptation in the face of multiple stressors: a comparative multi-tissue transcriptomic study in the Llobregat River, Barcelona, Spain. bioRxiv. 2023. doi:10.1101/2023.11.20.567554 Maryoung LA, Lavado R, Bammler TK, Gallagher EP, Stapleton PL, Beyer RP, et al. Differential gene expression in liver, gill, and olfactory rosettes of coho salmon ( Oncorhynchus kisutch ) after acclimation to salinity. Mar Biotechnol. 2015;17:703-717. doi:10.1007/s10126-015-9654-6. doi:10.1007/s10126-015-9649-5 Guo B, Tang Z, Wu C, Xu K, Qi P. Transcriptomic analysis reveals an efficient osmoregulatory system in Siberian sturgeon Acipenser baeri in response to salinity stress. Sci Rep. 2018;8:14353. doi:10.1038/s41598-018-32771-x Lee SY, Lee HJ, Kim YK. Comparative transcriptome profiling of selected osmotic regulatory proteins in the gill during seawater acclimation of chum salmon ( Oncorhynchus keta ) fry. Sci Rep. 2020;10:1987. doi:10.1038/s41598-020-58915-6. Li Z, Gao T, Han Z. RNA-seq and analysis of Argyrosomus japonicus under different salinities. Front Mar Sci. 2021;8:790065. doi:10.3389/fmars.2021.790065 Tang CH, Lee TH. The effect of environmental salinity on the protein expression of Na⁺/K⁺-ATPase, Na⁺/K⁺/2Cl⁻ cotransporter, cystic fibrosis transmembrane conductance regulator, anion exchanger 1, and chloride channel 3 in gills of a euryhaline teleost, Tetraodon nigroviridis . Comp Biochem Physiol A Mol Integr Physiol. 2007;147(2):521-528. doi:10.1016/j.cbpa.2007.01.679 Ruiz Jarabo de la Rocha I, Barany Ruiz A, Jerez Cepa I, Mancera Romero JM, Fuentes J. Intestinal response to salinity challenge in the Senegalese sole ( Solea senegalensis ). Comp Biochem Physiol A Mol Integr Physiol. 2017;203:66-75. doi:10.1016/j.cbpa.2016.11.009 Jentsch TJ. Molecular physiology of anion channels. Curr Opin Cell Biol. 1994;6(4):600-606. doi:10.1016/0955-0674(94)90082-5 Li J, Xue L, Cao M, Zhang Y, Wang Y, Xu S, et al. Gill transcriptomes reveal expression changes of genes related with immune and ion transport under salinity stress in silvery pomfret ( Pampus argenteus ). Fish Physiol Biochem. 2020;46:1255-1277. doi:10.1007/s10695-020-00786-9 Sun Z, Lou F, Zhang Y, Song N. Gill transcriptome sequencing and de novo annotation of Acanthogobius ommaturus in response to salinity stress. Genes. 2020;11(6):631. doi:10.3390/genes11060631. He Z, Shou C, Han Z. Transcriptome analysis of marbled rockfish Sebastiscus marmoratus under salinity stress. Animals. 2023;13(3):400. doi:10.3390/ani13030400 Thanh NM, Jung H, Lyons RE, Chand V, Tuan NV, Thu VTM, et al. A transcriptomic analysis of striped catfish ( Pangasianodon hypophthalmus ) in response to salinity adaptation: de novo assembly, gene annotation and marker discovery. Comp Biochem Physiol D Genomics Proteomics. 2014;10:52-63. doi:10.1016/j.cbd.2014.04.001 Tseng YC, Hwang PP. Some insights into energy metabolism for osmoregulation in fish. Comp Biochem Physiol C Toxicol Pharmacol. 2008;148(4):419-429. doi:10.1016/j.cbpc.2008.04.009 Fang H, Yang YY, Wu XM, Zheng SY, Song YJ, Zhang J, et al. Effects and molecular regulation mechanisms of salinity stress on the health and disease resistance of grass carp. Front Immunol. 2022;13:917497. doi:10.3389/fimmu.2022.917497 Chen MT, Dong L, Zhang XH, Yin XL, Ning HM, Shen C, et al. ZFP36L1 promotes monocyte/macrophage differentiation by repressing CDK6. Sci Rep. 2015;5:16229. doi:10.1038/srep16229 Cook ME, Bradstreet TR, Webber AM, Kim J, Santeford A, Harris KM, et al. The ZFP36 family of RNA binding proteins regulates homeostatic and autoreactive T cell responses. Sci Immunol. 2022;7(76):eabo0981. doi:10.1126/sciimmunol.abo0981 Wang Z, Du J, Lam SH, Mathavan S, Matsudaira P, Gong Z. Morphological and molecular evidence for functional organization along the rostrocaudal axis of the adult zebrafish intestine. BMC Genomics. 2010;11:392. Roche PA, Furuta K. The ins and outs of MHC class II-mediated antigen processing and presentation. Nat Rev Immunol. 2015;15(4):203-216. doi:10.1038/nri3818 Zhang M, Li L, Liu Y, Gao X. Effects of sudden drop in salinity on osmotic pressure regulation and antioxidant defense mechanism of Scapharca subcrenata . Front Physiol. 2020;11:884. doi:10.3389/fphys.2020.00884. Tort L. Stress and immune modulation in fish. Dev Comp Immunol. 2011;35(12):1366-1375. doi:10.1016/j.dci.2011.07.002. Fulda S, Gorman AM, Hori O, Samali A. Cellular stress responses: cell survival and cell death. Int J Cell Biol. 2010;2010:214074. doi:10.1155/2010/214074. Krasnov A, Koskinen H, Afanasyev S, Mölsä H. Transcribed Tc1-like transposons in salmonid fish. BMC Genomics. 2005;6:107. doi:10.1186/1471-2164-6-107 Wicker T, Sabot F, Hua-Van A, Bennetzen JL, Capy P, Chalhoub B, et al. A unified classification system for eukaryotic transposable elements. Nat Rev Genet. 2007;8(12):973-982. doi:10.1038/nrg2165. Bourque G, Burns KH, Gehring M, Gorbunova V, Seluanov A, Hammell M, et al. Ten things you should know about transposable elements. Genome Biol. 2018;19:199. doi:10.1186/s13059-018-1577-z. Yuan J, Zhang X, Wang M, Sun Y, Liu C, Li S, et al. Simple sequence repeats drive genome plasticity and promote adaptive evolution in penaeid shrimp. Commun Biol. 2021;4(1):186. doi:10.1038/s42003-021-01716-y Carotti E, Carducci F, Greco S, Gerdol M, Di Marino D, Perta N, et al. Transcriptional contribution of transposable elements in relation to salinity conditions in teleosts and silencing mechanisms involved. Int J Mol Sci. 2022;23:5215. doi:10.3390/ijms23095215 Maris C, Dominguez C, Allain FHT. The RNA recognition motif, a plastic RNA-binding platform to regulate post-transcriptional gene expression. FEBS J. 2005;272(9):2118-2131. doi:10.1111/j.1742-4658.2005.04653.x Wilson MH, Coates CJ, George AL. PiggyBac transposon-mediated gene transfer in human cells. Mol Ther. 2007;15(1):139-145. doi:10.1038/sj.mt.6300028 Yusa K. piggyBac transposon. In: Craig NL, Chandler M, Gellert M, Lambowitz AM, Rice PA, Sandmeyer SB, editors. Mobile DNA III. Washington (DC): ASM Press; 2015. p. 873-890. doi:10.1128/9781555819217.ch39 Additional Declarations No competing interests reported. Supplementary Files SuppTable1Reads.xlsx SuppTable2DEGenes.xlsx SuppTable3AdravsMarch.xlsx SuppTable4GOTermsKEGG.xlsx SuppTable5GOSalinity.xlsx SuppTable6GOImmuno.xlsx SuppTable7Table1extended.xlsx AnnotatedGITpopulations.xlsx AnnotatedGillpopulations.xlsx SuppFig1HeatVolGillopt.pdf Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 04 May, 2026 Reviews received at journal 02 May, 2026 Reviews received at journal 01 May, 2026 Reviews received at journal 01 May, 2026 Reviews received at journal 23 Apr, 2026 Reviews received at journal 21 Apr, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviewers invited by journal 26 Mar, 2026 Editor assigned by journal 26 Mar, 2026 Editor invited by journal 23 Mar, 2026 Submission checks completed at journal 21 Mar, 2026 First submitted to journal 21 Mar, 2026 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9115348","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":613294951,"identity":"35083610-9220-4458-bef5-8a15c741340e","order_by":0,"name":"Alfonso López-Solano","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYDACdsYHYJoPTFbAhA3waGFmhsiygckzJGthbCPCXfzNzIyPC/7YMLCx9x58+HPetjz+2Q2MH38U2DHw8x/AqkXiMDOz8cy2NAY2nnPJBpLbbhdL3DnALM1jkMwgOSMBuzWH+Y9J8zYcZmCTyDGTMNx2O3GDRAIbM4PBAQaDG9h1yB9mZpPm+QPWYv4jcQ5EC+MPoBb789gdZgDWwgaxheFgA0QLAw/IFgbsDjME+YW3LY0H5BfJhmO3E2fcSGwG+YVH4gZ2LXLHmxkf8/yxkeMHhtjHHzW3E/tnJAMZf+zk+PuxOwwGeMAIAhgboCIEATFqRsEoGAWjYEQCADdnUXciTqpzAAAAAElFTkSuQmCC","orcid":"","institution":"Museo Nacional de Ciencias Naturales - CSIC","correspondingAuthor":true,"prefix":"","firstName":"Alfonso","middleName":"","lastName":"López-Solano","suffix":""},{"id":613294954,"identity":"367d44ff-9cec-4013-a265-d6b9be3edef3","order_by":1,"name":"Aida Verdes","email":"","orcid":"","institution":"Museo Nacional de Ciencias Naturales - CSIC","correspondingAuthor":false,"prefix":"","firstName":"Aida","middleName":"","lastName":"Verdes","suffix":""},{"id":613294956,"identity":"16e771c6-d9bd-404c-a8e2-fcb9d5ec11fa","order_by":2,"name":"Silvia Perea","email":"","orcid":"","institution":"Museo Nacional de Ciencias Naturales - CSIC","correspondingAuthor":false,"prefix":"","firstName":"Silvia","middleName":"","lastName":"Perea","suffix":""},{"id":613294958,"identity":"49bf3ced-0072-4db8-a8ee-1a3308342b1a","order_by":3,"name":"Elena Andrés","email":"","orcid":"","institution":"Museo Nacional de Ciencias Naturales - CSIC","correspondingAuthor":false,"prefix":"","firstName":"Elena","middleName":"","lastName":"Andrés","suffix":""},{"id":613294960,"identity":"c4efb338-89ea-49ef-afc7-b97809410e27","order_by":4,"name":"Tessa L. Nester","email":"","orcid":"","institution":"Museo Nacional de Ciencias Naturales - CSIC","correspondingAuthor":false,"prefix":"","firstName":"Tessa","middleName":"L.","lastName":"Nester","suffix":""},{"id":613294962,"identity":"708dc534-38ae-4e20-a4a4-096bce336d4c","order_by":5,"name":"Ignacio Doadrio","email":"","orcid":"","institution":"Museo Nacional de Ciencias Naturales - CSIC","correspondingAuthor":false,"prefix":"","firstName":"Ignacio","middleName":"","lastName":"Doadrio","suffix":""}],"badges":[],"createdAt":"2026-03-13 13:39:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9115348/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9115348/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105749017,"identity":"50ca09a0-5ebd-42c9-8409-5b1d54b10326","added_by":"auto","created_at":"2026-03-30 14:58:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":520634,"visible":true,"origin":"","legend":"\u003cp\u003ePatterns of differential gene expression across \u003cem\u003eAphanius iberus\u003c/em\u003e populations; A. Distribution range of the species with colored dots indicating populations sampled in this study; B. Barplot showing number of differentially expressed genes per pairwise population comparison in gills (green) and GIT (pink); C-D. Hierarchically clustered heatmaps of the top 20 DEGs in gills (C) and GIT (D) from pairwise sequential comparisons of populations in order of salinity level.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/57beefe5c1929c34a19c2648.png"},{"id":105749003,"identity":"aa228aec-d9e3-472a-9650-66dc29ed865d","added_by":"auto","created_at":"2026-03-30 14:58:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":499262,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plots and hierarchically clustered heatmaps showing a selection of the most DE annotated genes in the gills (A-B) and GIT (C-D) of \u003cem\u003eAphanius iberus\u003c/em\u003e from the populations with the most extreme salinity levels (i.e., FW population of Adra and SW population of Marchamalo).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/03a960022d1fc24d66fb7133.png"},{"id":105749019,"identity":"b3cc5cd2-7ad0-485e-8757-55ceed4cf31f","added_by":"auto","created_at":"2026-03-30 14:58:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":455278,"visible":true,"origin":"","legend":"\u003cp\u003eCircular bar plots representing enriched GO terms in the categories of Molecular Function (MF), Biological Processes (BP), and Cellular Component (CC) for gills (darker colors) and GIT (lighter colors). Bar plots are shown for each of the populations’ pairwise comparisons, ordered by increasing salinity level (A–D).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/83a0fa026837622fa4981b81.png"},{"id":105904158,"identity":"bebbe6bf-05de-43e1-b92f-c6cf3ccd6262","added_by":"auto","created_at":"2026-04-01 10:05:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1942464,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/02754633-3989-454d-aad9-81786523123b.pdf"},{"id":105749020,"identity":"ff5011a9-72fa-4ba5-9041-31daae78b96f","added_by":"auto","created_at":"2026-03-30 14:58:25","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13155,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable1Reads.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/b8056c4fea5eddba9fdffa8e.xlsx"},{"id":105749037,"identity":"2cdf5254-aaff-470e-83ab-998ab72fe340","added_by":"auto","created_at":"2026-03-30 14:58:35","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":609708,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable2DEGenes.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/7f9532a05a859732efae0650.xlsx"},{"id":105749002,"identity":"b2c628ab-d3ce-4861-a234-bed21231ee4d","added_by":"auto","created_at":"2026-03-30 14:58:17","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":30919,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable3AdravsMarch.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/01a1e14e936d2df3ad3ee766.xlsx"},{"id":105749014,"identity":"94db296a-086f-44f4-99ae-9d51d070eabc","added_by":"auto","created_at":"2026-03-30 14:58:23","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":51339,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable4GOTermsKEGG.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/dff5ad504aa73acd9ab3850f.xlsx"},{"id":105752206,"identity":"2908d3fe-3a6f-43bd-b7a3-088ecc403f2f","added_by":"auto","created_at":"2026-03-30 15:55:50","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":55183,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable5GOSalinity.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/191830588200eccfdf9d6232.xlsx"},{"id":105749007,"identity":"ddc68551-ec42-44f1-8e89-64ff10ad684e","added_by":"auto","created_at":"2026-03-30 14:58:17","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":12777,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable6GOImmuno.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/b3faa9cffecb892c70bf6b48.xlsx"},{"id":105749005,"identity":"6f13fd47-26e2-4dd9-8cd4-56ed9f2b7bab","added_by":"auto","created_at":"2026-03-30 14:58:17","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":14006,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable7Table1extended.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/3cffad6807772c8ec231f62b.xlsx"},{"id":105749006,"identity":"e6c9ad1b-9609-4257-9908-d246e10f1f4e","added_by":"auto","created_at":"2026-03-30 14:58:17","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":55805,"visible":true,"origin":"","legend":"","description":"","filename":"AnnotatedGITpopulations.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/6a860389996935040ff7e379.xlsx"},{"id":105749018,"identity":"8a6dc591-97c8-4273-8d2d-158505656005","added_by":"auto","created_at":"2026-03-30 14:58:25","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":78314,"visible":true,"origin":"","legend":"","description":"","filename":"AnnotatedGillpopulations.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/afd247936451922907048ec4.xlsx"},{"id":105749027,"identity":"ab9bfd6c-e988-4a39-b8b5-b8a8606873bd","added_by":"auto","created_at":"2026-03-30 14:58:26","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":470404,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFig1HeatVolGillopt.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9115348/v1/091a3e86a92bc87dfe0e4a95.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Salinity-associated differential gene expression in natural populations of the euryhaline killifish Aphanius iberus","fulltext":[{"header":"Background","content":"\u003cp\u003eThe thermo-physicochemical properties of water are key drivers in the evolution of aquatic life, pressing organisms to adapt to variable habitats [1,2]. In animals, the ancestral metabolic conditions enabling adaptation to seawater underwent modifications with the colonization of new environments, notably the transition from saltwater to freshwater [3]. Fishes in particular, exhibit remarkable plasticity, which facilitates environmental colonization shaping global evolutionary patterns [4]. Euryhalinity\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003ethe ability to tolerate a wide range of salinity levels\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eis considered an ancestral, transitional trait that enables colonization of new adaptive zones, promoting diversification and eventually leading to the origin of stenohaline taxa (i.e., those that only survive in a narrow range of salinity levels). Today, most fishes are stenohaline, restricted to either FW or SW with narrow salinity tolerances, while true euryhaline species are rare [5,6]. Only 3\u003cstrong\u003e-\u003c/strong\u003e5% of fish species retain their euryhaline capacity, allowing them to withstand broader salinity ranges and to transition between FW and SW environments [7]. Despite its adaptive advantages, euryhalinity is rare, likely due to significant physiological and immunological [8]. It is therefore likely that this trait would have been lost, were it not for strong selection pressures [9]. However, these uncommon euryhaline taxa contribute to evolutionary diversity, as landlocking and FW radiations frequently occur in ancestrally euryhaline lineages [6]\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEuryhalinity is a highly demanding process, with estimated energy costs ranging from 20% to 62% of the total energy produced by organisms under elevated salinity stress [10,11]. For instance, gills alone require approximately 7% of the total energy to sustain the osmoregulatory processes necessary under these conditions [10,11]. Despite its high energy demands, euryhalinity provides a significant advantage specially in the current context of global climate change, where rapid environmental shifts towards salinization are increasingly impacting FW ecosystems [12,13].\u003c/p\u003e\n\u003cp\u003eAquatic habitats are typically classified by salinity levels, from freshwater (FW) with \u0026lt;0.5 Practical Salinity Units (PSU), to brackish water (BW) with 0.5-30 PSU, and seawater/saltwater (SW) with 30-40 PSU [14]. In natural ecosystems, salinity fluctuations are a key abiotic factor affecting the adaptability and survival of species. Osmoregulation capacity determines an organism's salinity tolerance, as it directly influences biological processes such as growth, survival, lipid metabolism in fish larvae, gonad development, embryo hatchability, feeding and digestion, among others [15,16]. Fishes generally maintain body fluid osmolarity at about one-third of SW [17]. In SW, they lose water through osmosis and gain Na+ and Cl− via diffusion, compensating through seawater ingestion, minimal urine excretion, and active salt excretion via the gills. Conversely, FW fish excrete dilute urine, actively absorb salts across the gills, and may also ingest salts through their diet [17,18,19]. Euryhaline fishes, commonly found in estuaries or as migratory species, endure frequent salinity shifts. Coastal SW salinity fluctuates due to surface runoff, rainfall, floods, and tides, requiring euryhaline fish to exhibit high iono-osmoregulatory plasticity. Their response involves cellular remodeling in osmoregulatory organs, including modulation of transporters, channels, and intercellular structures [18,20]. Under salinity stress, osmosensors trigger molecular cascades that induce cellular remodeling, allowing fish to restore osmotic balance by adjusting or switching between different osmolar environments [18,20].\u003c/p\u003e\n\u003cp\u003eAs research continues to explore independent instances of adaptation to different osmotic environments in fishes, it remains intriguing to determine whether evolution repeatedly employs similar pathways to address the same challenges [19,21]. However, physiological flexibility varies among individuals. For example, in \u003cem\u003eFundulus heteroclitus\u003c/em\u003e, populations exhibit differing abilities to acclimate to extreme osmotic conditions, with interspecific divergence in osmotic plasticity observed even among geographically close groups [22]. FW populations demonstrate greater efficiency in compensating for hypoosmotic challenges than BW or coastal populations, despite long-term rearing in seawater. Additionally, northern coastal populations tolerate hypoosmotic challenges better than their southern counterparts [21,23].\u003c/p\u003e\n\u003cp\u003eSalinity acclimation in fish involves high plasticity in key osmoregulatory organs such as the gills, kidney, liver, and gastrointestinal tract (GIT), which maintain homeostasis in FW, BW, and SW environments [18,24]. The gills serve as the primary site for osmotic sensing and compensation, uptaking ions in FW and excreting salt in SW [18,19]. The GIT also plays a crucial osmoregulatory role beyond nutrient absorption, especially in SW fishes, which drink seawater and rely on intestinal processes, such as bicarbonate secretion and ion precipitation, to reduce chyme osmolality and facilitate water absorption. In fish species exposed to varying salinities, differences in expression of genes related to ion transport, water and solute channels, as well as immune functions, have been identified particularly in mucosal surfaces such as the gills, skin, and GIT [24,25]. A conserved molecular response to osmotic stress has also been identified, involving regulation of the cell cycle, metabolism, protein synthesis, cytoskeletal organization, and immune responses [26,27].\u003c/p\u003e\n\u003cp\u003eStudies of fish osmoregulatory processes using RNA-seq have been growing exponentially in recent decades [28,29,30]; most focusing either on model species such as mummichogs, three-spine sticklebacks, medakas and guppys [21,31,32,33,34] or economically important species such as theNile tilapia, Atlantic salmon, rainbow trout and the Asian, European and spotted seabass (9,26,35,36,37,38,39,40,41). However, studies focusing on non-model wild species are scarce, despite their potential to provide insights into salinity adaptation in the current context of global climate change. Here, we used an RNA-seq approach on \u003cem\u003eAphanius iberus\u003c/em\u003e, the Spanish toothcarp,a small endemic fish species belonging to the order Cyprinodontiformes which can be found on the eastern coast of the Iberian Peninsula, and it is currently classified as Endangered by the \u003cem\u003eLibro Rojo de las Especies Españolas\u003c/em\u003e [42,43] and by the \u003cem\u003eSpanish Catalogue of Threatened Species\u003c/em\u003e (Real Decreto 139/2011, Official State Gazette (BOE-A-2011-3582)). It inhabits a wide range of habitats ranging from groundwater springs (locally known as \u003cem\u003eullals\u003c/em\u003e) to coastal lagoons, river mouths, and even salt marshes where the salinity level is often greater than the sea (e.g. Marchamalo salt flats). Apart from the mentioned studies conducted on \u003cem\u003eF. heteroclitus\u0026nbsp;\u003c/em\u003e[21], there are few studies on this globally distributed and diverse order, which includes over 1,300 species (e.g. \u003cem\u003eAphanius dispar\u003c/em\u003e, [44]; \u003cem\u003ePoecilia reticulata\u003c/em\u003e, [34]; \u003cem\u003eLimia perugiae\u003c/em\u003e, [45]. \u003cem\u003eA. iberus\u003c/em\u003e has been the subject of many genetic and ecological studies [46,47,48,49,50,51,52], but never from a transcriptional perspective.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the species' natural exposure to a broad salinity range, we hypothesize that \u003cem\u003eA. iberus\u003c/em\u003e exhibits a distinctive and complex transcriptional response to salinity stress. This response likely involves differential expressions of key iono-osmoregulatory genes across tissues, comparable on a functional level, but divergent in molecular pathways from those described in classical euryhaline model species. We anticipate that this transcriptomic plasticity reflects a combination of ancestral euryhaline traits and habitat-driven local adaptation.\u003c/p\u003e"},{"header":"Material \u0026 Methods ","content":"\u003cp\u003e1.\u0026nbsp; \u0026nbsp;\u0026nbsp;Sample collection and processing\u003c/p\u003e\n\u003cp\u003eWe selected four populations of \u003cem\u003eAphanius iberus\u003c/em\u003e living at different salinity levels, all located along the eastern Mediterranean coast of the Iberian Peninsula, within the species’ distribution range (Figure 1A) and collected four individuals from each location (Supp. Table 1). The northernmost population was the Natural Park of Cabanes i Torreblanca in the mediterranean province of Castellón (Séquia del Polo; 40.18500, 0.2063). This population inhabits brackish waters with a salinity of 4.8 PSU. Two additional populations were collected in coastal saline systems: Santa Pola (Los Xiprerets; 38.19778, -0.578633), within the Santa Pola Salt Pans Natural Park (Alicante), with a salinity of 7.4 PSU at the time of sampling; and Marchamalo (37.63536, -0.717281) in Murcia, a hypersaline saltworks\u0026nbsp;where salinity reached 52 PSU, exceeding Mediterranean seawater levels.\u0026nbsp;The southernmost population was sampled in Adra (Almería; 36.7633659, -2.9513865), where individuals were found in irrigation ponds with a salinity of 0.76 PSU, corresponding to near-freshwater conditions. Fish were collected using minnow trap nets and euthanized by immersion in an overdose of buffered tricaine methanesulfonate (MS-222, 0.1%), ensuring rapid loss of consciousness, in accordance with internationally accepted guidelines for the use of fish in research. All procedures were carried out by qualified personnel under the relevant institutional and regional permits (see Ethics approval and consent to participate section). Specimens were then fixed in RNAlater solution (Invitrogen™) and kept at 4 °C until further processing. The gills and gastrointestinal tract (GIT) of four individuals per population were dissected under a binocular stereoscope and stored at −80 °C at the National Museum of Natural Sciences (Madrid, Spain) for subsequent RNA extraction and cDNA library preparation.\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp;\u0026nbsp;RNA Extraction, Library Preparation and Sequencing\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from a set of 32 samples, corresponding to the gills and GIT of four specimens per population (Supp. Table 1), using the Trizol protocol of the Invitrogen™ PureLink™ RNA Mini Kit, following manufacturer’s instructions. Quantity and quality of the extracted RNA were assessed with a Nanodrop spectrophotometer and genomic libraries were constructed using the Illumina Stranded mRNA Prep kit, following the protocol on the Ligation Reference Guide. The quality, insert size and concentration of the libraries were checked with an Agilent TapeStation 4150, verified with Qubit DNA hs assay, and sent to Novogene Europe (Cambridge, UK) for sequencing with Illumina NovaSeq X Plus technology, at 150 base-pairs (bp) paired-end reads.\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp;\u0026nbsp;Sequence processing, read mapping and abundance estimation\u003c/p\u003e\n\u003cp\u003eThe quality of the raw reads generated from each of the 32 libraries was evaluated with FastQC v0.12.1\u0026nbsp;[53]. Adapter sequences and low-quality bases and reads (phred score \u0026lt; 30) were removed with Trimmomatic v0.39 [54]. Clean reads were aligned to the reference genome of\u0026nbsp;\u003cem\u003eAphanius iberus\u003c/em\u003e, sequenced and annotated by our research group (GCA_028564705.1 NCBI GenBank; [55]), using Star Aligner v2.7.9a [56]. Read abundance was then estimated with StringTie v2.1.7 [57] following the Simplified Workflow and the \u003cem\u003eprepDE.py\u003c/em\u003e script of the StringTie package was used to generate a count matrix with the estimated abundances for each gene.\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp; \u0026nbsp;\u0026nbsp;Differential Gene Expression, Gene Ontology and Pathway Analyses\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted using Trinity v2.13.2 [58]. Differential Gene Expression (DGE) analysis was performed through pairwise comparisons using edgeR from trinityrnaseq v2.13.2, executed via the run_DE_analysis.pl script, selecting genes with P ≤ 1e-3 and a fold-change of at least 2². Functional annotations and GOTerms from the reference genome were assigned to each overexpressed gene. Heatmaps were created using Pheatmap v1.0.12 [59], while Volcano plots were generated with EnhancedVolcano v1.24 [60], applying a fold-change threshold of ±2 and a p-value cutoff of 10e-3, both analyses conducted in RStudio v2024.12.1.563 [61]. Gene Ontology (GO) analysis was conducted using InterProScan [62] and sma3s [63] annotations from the \u003cem\u003eAphanius iberus\u003c/em\u003e reference genome and DGE data. Finally, annotated genes from each comparison were filtered using InterProScan, classifying them by population overexpression. These results were used for KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis [64], performed in ShinyGO v0.80 [65].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e1.\u0026nbsp; \u0026nbsp;\u0026nbsp;Sequencing results and Differential Gene Expression analyses\u003c/p\u003e\n\u003cp\u003eWe generated a total of 313,31 GB of data from the 32 sequenced libraries that were used for the DGE analyses. After quality filtering and cleaning the reads, we obtained libraries ranging from 3,146,004 to 31,431,060 high quality reads (Supp. Table 1). We identified a total of 1,428 DEGs in the gills and 504 in the GIT, of which we could functionally annotate 1,081 and 398 respectively (Supp. Table 2). The pairwise comparisons among all samples revealed that the gills exhibited a significantly higher number of differentially expressed genes across populations than the GIT in most cases (Fig. 1B). The populations that exhibited the greatest amount of differentially expressed genes (DEG) for gills were the SW population of Marchamalo (140 DEGs on average) and the FW population of Adra (138 DEGs), which correspond to the highest and lowest salinity levels, respectively (Fig. 1B). Regarding the GIT, the populations that exhibited the greatest number of overexpressed genes were the SW population of Marchamalo (79 DEGs) and the BW population of Cabanes (61 DEGs) (Figure 1B).\u003c/p\u003e\n\u003cp\u003eWe performed pairwise comparisons among populations with an increasing level of salinity (Figs. 1C-D) and examined the functions of the genes with the highest expression levels. We found a significant number of DEG related with transcription processes, including ribonucleases, integrases, and ligases including \u003cem\u003eHECT E3 ligase catalytic domain\u003c/em\u003e, as well as structural genes like histones (\u003cem\u003elinker histone H1/H5\u003c/em\u003e). A considerable number of genes are associated with Repetitive Elements, including the \u003cem\u003eL1 Transposable Element\u003c/em\u003e or Reverse Transcriptases. Additionally, immunoglobulins were identified among these top upregulated genes in both tissues, along with other genes associated with apoptosis and phagocytosis, such as \u003cem\u003einterferon alpha-inducible protein IFI6/IFI27-like\u003c/em\u003e and \u003cem\u003eadhesion G protein-coupled receptor B1\u003c/em\u003e. Finally, we also found genes associated with salinity regulation processes, including Peptidases, Heat-shock Proteins, \u003cem\u003eTristetraprolin\u003c/em\u003e or \u003cem\u003eVoltage-dependent L-type Calcium Channel Subunit Alpha-1C\u003c/em\u003e (Supp. Table 2). A summary of the most relevant upregulated genes identified in all pairwise comparisons across populations can be found in Table 1 (Supp Table 7).\u003c/p\u003e\n\u003cp\u003eTable 1. Candidate genes potentially involved in salinity acclimatation in\u0026nbsp;\u003cem\u003eAphanius iberus\u003c/em\u003e organized in five categories that include genes involved in ion transport, energetic metabolism, signal transduction, immune response, structure organization and repetitive elements.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"741\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16.5932%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 19.2364%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpregulated in population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11.1601%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"51\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"34\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 16.5932%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIon transporter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eNa(+)/K(+) ATPase alpha-1 subunit (ATP1A1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eBoutet et al. 2006; Whitehead et al. 2012; Norman et al. 2014; Maryoung et al. 2015; Gibbons et al. 2017; Guo et al. 2018; Lee et al. 2020; Lee et al. 2020; Vij et al. 2020; Li et al. 2021; Valenzuela-Mu\u0026ntilde;oz et al. 2021; Taugb\u0026oslash;l et al. 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"216\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eChloride channel protein 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eVij et al. 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"27\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eSolute carrier families\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLam et al. 2014; Gibbons et al. 2017; Cui et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Santa Pola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eSW Marchamalo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"9\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eClaudin-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eSW Marchamalo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eWhitehead et al. 2012; Li et al. 2012; Lam et al. 2014; Nguyen et al. 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"92\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 16.5932%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnergetic metabolism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eG protein-coupled receptor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"37\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eTristetraprolin (MAPK cascade)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"13\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eP2X purinoreceptor (activation of MAPK activity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"56\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Santa Pola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"42\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eProbable ATP-dependent RNA helicase DDX43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Santa Pola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"5\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eGTPase IMAP family member 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eSW Marchamalo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLam et al., 2014; Nguyen et al., 2016; Zhang et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"62\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16.5932%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStress and Immune Responses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eHeat-shock 70 kDa protein 12A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eThanh et al., 2014; Li et al., 2020; Zhang et al., 2020; Valenzuela-Mu\u0026ntilde;oz et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"44\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Santa Pola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"42\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 16.5932%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStructure organization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eKASH domain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLi et al., 2012; Wong et al., 2014; Nguyen et al., 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"17\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003ehelically-extended SH3 domain\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eLi et al., 2012; Wong et al., 2014; Nguyen et al., 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Santa Pola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eHistones H1a and H4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eWhitehead et al., 2011; Whitehead et al., 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 16.5932%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRepetitive Elements\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eTc1 DNA transposon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eFW Adra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eCaratti et al. 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eSW Marchamalo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"7\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eL1 transposable element\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Santa Pola\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003eCaratti et al. 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"11\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003ePiggyBac transposable element-derived protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eBW Cabanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"69\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.4949%;\"\u003e\n \u003cp\u003eBarney transposase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.2364%;\"\u003e\n \u003cp\u003eSW Marchamalo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1601%;\"\u003e\n \u003cp\u003eGIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.6344%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"32\" style=\"width: 0.8811%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe most extreme populations in terms of salinity levels are Adra (with the lowest levels) and Marchamalo (with the highest salinity) and accordingly, we found the highest number of DEGs in the pairwise comparison of both tissues from these populations (Fig. 2, Supp. Table 3). For the gill, we found among the most up-regulated genes in Adra a solute carrier gene (\u003cem\u003eSLC12A domain\u003c/em\u003e), involved in ion transport, and an arginase domain-containing gene, linked to nitrogen metabolism and osmotic balance. In contrast, the gill of Marchamalo showed upregulation of a cytochrome c domain gene, consistent with an increased energetic demand under hyperosmotic stress. For GIT, we found among the most up-regulated genes in Adra an ATPase domain-containing gene, involved in active ion transport under hypoosmotic conditions (Figs. 2A\u0026ndash;D). For the rest of the pairwise comparisons, we found a similar number of DEGs in both gill and GIT with some of the most up-regulated genes related to osmoregulation or immune response among others (Supp. Table 2). Volcano plots and heatmaps with the top 20 annotated DEGs among pairwise comparisons for gill and GIT can be found in the Supplementary Material, Supplementary Figures 1 and 2, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp;\u0026nbsp;Gene Ontology and KEGG pathway Analyses\u003c/p\u003e\n\u003cp\u003eWe conducted Gene Ontology (GO) and KEGG analyses to investigate whether any functions or pathways were overrepresented among the DEGs identified (Fig. 3 and Supp. Table 4). For both analyses, we identified a greater number of overrepresented functions in the gills, with 207 different terms in the category of Molecular Function, 176 terms for Biological Processes, and 40 terms for Cellular Component. For the GIT, 300 different terms were identified for Molecular Function, 354 for Biological Processes and 75 terms for Cellular Component. It is noteworthy to mention again that the comparison of the BW population of Cabanes vs. the SW population of Marchamalo contributed the most genes to almost every term in every category of the GIT. Most overrepresented GO terms in the category of Biological Processes in both tissues were associated with salinity regulation, including transmembrane transport (GO:0055085) and ion transport (GO:0006811) which were present in both tissues and all populations. Additionally for gills, cation transport (GO:0006812), potassium ion transport (GO:0006813), and ion transmembrane transport (GO:0034220) were observed across all populations. In all populations of the GIT, the term calcium ion transmembrane transport (GO:0070588) was identified. In addition, the following terms were identified in the gills: anion transport (GO:0006820), chloride transport (GO:0006821), and sodium ion transport (GO:0006814) (Supp. Table 5). In the comparison of the BW populations (Cabanes and Santa Pola) with the rest, we identified many overrepresented GO terms associated to immune response (GO:0006955) in both tissues (Supp. Table 6). The majority of the identified genes that contributed to this GO term can be grouped in the following categories: interleukins, immunoglobulins, and MHC complex in the gills; and proteins of the membrane attack complex, cell signaling proteins (Helically-extended SH3 domain), and interleukins for the GIT (Supp. Table 6).\u003c/p\u003e\n\u003cp\u003eFor the KEGG analysis, we only identified enriched pathways in the comparisons of the FW population of Adra vs all other populations for both tissues, and in the comparison of the SW population of Marchamalo vs the BW population of Santa Pola for the gills (Supp. Table 4). The Cysteine and methionine metabolism (Path:dre00270) pathway was enriched in the pairwise comparisons of the gills from the FW population of Adra versus all other populations. Other enriched pathways in the gill tissue comparisons were Glycine serine and threonine metabolism (Path:dre00260), Selenocompound metabolism (Path:dre00450), Citrate cycle (TCA cycle) (Path:dre00020) and Sulfur metabolism (Path:dre00920). In the case of the GIT, we found a greater variety of enriched pathways including Starch and sucrose metabolism (Path:dre00500), Apoptosis (Path:dre04210), Metabolic pathways (Path:dre01100), RNA degradation (Path:dre03018), One carbon pool by folate (Path:dre00670), Tryptophan metabolism (Path:dre00380), Arachidonic acid metabolism (Path:dre00590), and DNA replication (Path:dre03030) (Supp. Table 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results indicate strong tissue-specific gene expression patterns in response to salinity variation, with gills exhibiting a higher number of DEGs than the gastrointestinal tract (GIT). This pattern is consistent with previous studies highlighting the central role of the gills in osmoregulation, as they are in direct contact with the external environment and represent the primary boundary for osmotic exchange and regulation. In contrast, the GIT is involved in a multitude of additional functions beyond osmoregulation, which might attenuate or mask salinity-specific transcriptional changes [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Nevertheless, we found a similar proportion of upregulated genes associated with salinity regulation processes in both tissues (Supp. Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and 5), in line with previous studies showing that the GIT exhibits a rapid response to changes in environmental salinity [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral cyprinodontiform fishes closely related to \u003cem\u003eA. iberus\u003c/em\u003e are capable of remodeling the morphology of the gill epithelium through reorganization of cytoskeletal structures, water flux channels, and other cell structures in response to changes in the environment [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. In hyperosmotic SW habitats, fish must increase water absorption through the GIT and lose ions, while in hypoosmotic FW habitats fish must actively uptake ions to maintain cellular homeostasis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our results are consistent with these physiological patterns, showing DEGs involved in osmoregulatory processes and adaptation to salinity across different functional categories (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Supp. Table\u0026nbsp;7). Among populations, the SW population of Marchamalo exhibited the most pronounced transcriptional response, with the highest number of DEGs, enriched GO terms and KEGG pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supp. Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;5), followed by the FW population of Adra, which also showed strong signals across functional and pathway-level analyses. In the following sections, we focus on the most relevant genes and biological processes underlying the remarkable plasticity and adaptive capacity of \u003cem\u003eA. iberus\u003c/em\u003e to live in habitats with widely different salinity levels.\u003c/p\u003e \u003cp\u003eIon transport and solute carrier genes are upregulated in low salinity populations\u003c/p\u003e \u003cp\u003eIon transport and solute carrier genes were consistently upregulated in populations inhabiting low-salinity environments, highlighting the importance of active transport processes in osmotic regulation. Although fishes can passively exchange ions and water, active transport is often essential to maintain cellular homeostasis under fluctuating salinity conditions. Accordingly, a substantial number of DEGs identified in this study are associated with ion transport and solute carrier functions across membrane-processes highly dependent on external environmental conditions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. The magnitude of transcriptional differences closely mirrors the degree of environmental contrast, with comparisons between populations with larger salinity differences showing higher numbers of DEGs, while relatively few differences were found between populations with similar salinity levels, such as the two BW populations. This pattern suggests that the observed expression changes represent adaptive or plastic responses to osmotic conditions rather than background population divergence. In line with this, previous studies have shown significant variation in the abundance of transporters and ion channels in the anterior intestine, contributing to different osmoregulatory mechanisms across the gastrointestinal tract (GIT) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong ion transporters, ATPases play a fundamental role by using ATP hydrolysis to drive particle movement across membranes. The Na⁺/K⁺-ATPase alpha-1 subunit (\u003cem\u003eATP1A1\u003c/em\u003e) which actively transport ions into (K⁺) and out (Na⁺) of the cells was significantly upregulated in the gills of the FW population from Adra. This pattern is consistent with numerous studies showing downregulation of various ATPases when FW-adapted fish are transferred to SW reflecting reduced reliance on active ion uptake in hyperosmotic environments [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. An inverse expression pattern has been described in Arctic charr (\u003cem\u003eSalvelinus alpinus\u003c/em\u003e) and chum salmon (\u003cem\u003eOncorhynchus keta\u003c/em\u003e), where \u003cem\u003eATP1α1a\u003c/em\u003e was predominant in SW and \u003cem\u003eATP1α1b\u003c/em\u003e is upregulated in SW [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] showing strong tissue and environment-dependent expression of this transporter (Supp. Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eSolute carriers, membrane transport proteins that facilitate the movement of small solutes along chemiosmotic gradients, were generally upregulated in FW environments due to the lower external solute concentration [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. We detected significantly higher expression of several \u003cem\u003esolute carrier families\u003c/em\u003e in the gills of the FW population of Adra, but also in the BW populations of Cabanes and Santa Pola and, to a lesser extent, in the SW population of Marchamalo. Notably, the \u003cem\u003echloride channel protein 2\u003c/em\u003e, \u003cem\u003ebumetanide-sensitive sodium-(potassium)-chloride cotransporter 2\u003c/em\u003e, was upregulated across all these populations, reflecting the importance of reabsorbing sodium, potassium and chloride ions, which plays a crucial role in maintaining osmotic gradients [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditional genes related to ion transporters and solute carriers identified across population comparisons included \u003cem\u003esolute carrier family 9 member 1\u003c/em\u003e, \u003cem\u003eNa⁺/K⁺/Ca\u0026sup2;⁺-exchange protein 3\u003c/em\u003e, \u003cem\u003eATP-binding cassette sub-family D member\u003c/em\u003e, \u003cem\u003echoline transporter-like protein 2\u003c/em\u003e, \u003cem\u003eneurotransmitter-gated ion-channel\u003c/em\u003e, and \u003cem\u003esolute carrier family 12 member 9\u003c/em\u003e, \u003cem\u003esodium channel protein type 4 subunit alpha B\u003c/em\u003e and \u003cem\u003eATP-binding cassette sub-family C member 7\u003c/em\u003e (Supp. Table\u0026nbsp;2). Particularly interesting were the differential expression of the \u003cem\u003evoltage-dependent L-type calcium channel subunit alpha-1C\u003c/em\u003e in BW Cabanes vs BW Santa Pola and BW Santa Pola vs SW Marchamalo, and the \u003cem\u003eNa⁺/K⁺/Ca\u0026sup2;⁺-exchange protein 3\u003c/em\u003e in FW Adra vs SW Marchamalo, both of which are known to play key roles in ionic balance, cell volume regulation and salinity sensing [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Previous studies have also reported downregulation of some solute carriers and a reduction of chloride cell numbers in gills upon transfer of FW-acclimated fish to SW [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] (Supp. Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eTight junction components also contributed to salinity-associated expression patterns. \u003cem\u003eClaudin-3\u003c/em\u003e, a protein related to occludins and involved in regulating cellular permeability, was consistently upregulated in the gills of the SW population of Marchamalo. Although claudins are usually upregulated in FW and downregulated in SW [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], recent studies have documented increased \u003cem\u003eClaudin-3\u003c/em\u003e levels in SW-maintained and sea-caught fish compared to FW-acclimated individuals [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In contrast, aquaporins, which are water channel proteins associated with volume regulation and sensing typically upregulated in FW [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e], did not show differential expression across populations (Supp. Table\u0026nbsp;2), suggesting that water balance may be regulated through alternative mechanisms in the Spanish toothcarp.\u003c/p\u003e \u003cp\u003eAt the functional level, GO analysis revealed multiple terms associated with biological process related to osmoregulation, mostly including ion and transmembrane transport (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Table\u0026nbsp;4). Enriched terms included ion, cation and anion transport, as well as pathways mediating the movement of potassium, chloride, sodium and calcium ions across membranes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Table\u0026nbsp;4). These processes are key components of osmotic regulation in fishes, with numerous studies reporting differences between FW and SW populations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. In our case, we found tissue-specific patterns, with most terms related to ion transport found exclusively in the gills, consistent with their primary role in mediating ion exchange with the external environment, while calcium ion transmembrane transport was exclusive to the GIT, indicating a distinct and complementary role of this tissue in ionic homeostasis.\u003c/p\u003e \u003cp\u003eIncreased energetic metabolism accompanies osmoregulatory adaptation across salinity gradients\u003c/p\u003e \u003cp\u003eNumerous DEGs associated with energy metabolism were identified across population comparisons, particularly in the gills, where transcriptional divergence was highest. These included transporters and enzymes participating in energy-intensive processes, as well as genes involved in protein synthesis and the coding of key metabolic enzymes [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. This pattern reflects the metabolic investment required to maintain homeostasis and osmotic pressure balance under salinity stress [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], a process known to demand substantial energy to cope with external salinity fluctuations and ensure survival [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Indeed, osmoregulatory processes can account for 20\u0026ndash;62% of total energy expenditure under elevated salinity stress, with approximately 7% specifically attributed to gill activity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEnrichment analyses further supported this trend. Several KEGG pathways related to energetic metabolism and energy acquisition were significantly overrepresented, including amino acid, lipid, and carbohydrate metabolism, as well as central aerobic pathways such as the citrate cycle (TCA cycle). Similar enrichment of energy-related pathways under seawater conditions has been reported in other teleosts [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the gills, the \u003cem\u003eGlycine, Serine and Threonine Metabolism\u003c/em\u003e pathway was significantly enriched in the comparison between FW Adra and SW Marchamalo. Serine, derived from glycolytic intermediates, and glycine, synthesized from serine, are central to metabolic flexibility under environmental change, as previously reported [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. The \u003cem\u003ecitrate cycle (TCA cycle)\u003c/em\u003e was enriched between FW Adra and BW Cabanes, consistent with its fundamental role in aerobic oxidation of carbohydrates and fatty acids and with previous reports of citrate metabolism shifts during salinity acclimation [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. The GO term \u003cem\u003elipid transport\u003c/em\u003e was also consistently overrepresented in the gills (Supp. Table\u0026nbsp;4). In contrast, the GIT showed enrichment of lipid- and carbohydrate-related pathways, including \u003cem\u003earachidonic acid metabolism\u003c/em\u003e (SW Marchamalo vs FW Adra) and \u003cem\u003estarch and sucrose metabolism\u003c/em\u003e (BW Cabanes vs FW Adra). The GO term \u003cem\u003ecarbohydrate metabolic process\u003c/em\u003e was repeatedly overrepresented across comparisons. Additionally, \u003cem\u003esulfur metabolism\u003c/em\u003e was enriched in the comparison between SW Marchamalo and BW Santa Pola, highlighting modulation of sulfate pathways that participate in both assimilatory and dissimilatory energy processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eOur analyses also identified DEGs involved in fatty acid and carbohydrate metabolism, which serve as major energy reservoirs or direct substrates [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Among them, \u003cem\u003emannose-P-dolichol utilization defect 1\u003c/em\u003e was upregulated in the GIT of BW Cabanes and in the gills of BW Santa Pola, indicating enhanced glycosylation processes. The \u003cem\u003eB30.2/SPRY domain superfamily\u003c/em\u003e was upregulated in the GIT of SW Marchamalo and is associated with carbohydrate recognition and binding (Supp. Table\u0026nbsp;2). Collectively, these results indicate that energy production and substrate utilization pathways are tightly modulated across salinity gradients, supporting extensive metabolic reprogramming in response to osmotic stress [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSignal transduction and transcriptional regulation are overrepresented in extreme salinity populations\u003c/p\u003e \u003cp\u003eSignal transduction and transcription-related genes were strongly overrepresented in extreme salinity populations (FW Adra and SW Marchamalo). As primary osmosensory organs, gills detect environmental changes and initiate downstream signaling cascades that increase cellular metabolism and mitochondrial activity, ultimately contributing to pathway enrichment and a higher number of DEGs across populations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. One of the most prominent internal responses is enhanced ribosome production, which increases translational capacity and protein synthesis; however, this efficiency may become compromised under excessive salinity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Consistent with these patterns, many of the top DEGs identified along the salinity gradient were involved in receptor-mediated signaling, ubiquitination, chromatin remodeling, and transcriptional regulation, a trend further supported by GO enrichment analyses, where over half of the identified terms were associated with signal transduction and transcriptional regulation across all three GO categories. Enriched domains frequently included zinc-binding and nucleic acid-interacting motifs, supporting a role for Zn\u0026sup2;⁺-dependent transcriptional modulation under osmotic stress [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Moreover, KEGG analyses indicated that amino acid metabolism is central to transcriptional and signaling responses under salinity stress, in agreement with previous studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExtreme salinity populations (FW Adra and SW Marchamalo) exhibited the strongest transcriptional signatures along the salinity gradient, concentrating the highest proportion of signal transduction- and transcription-related responses. In FW Adra gills, several of the top DEGs encoded integrases (\u003cem\u003eintegrase zinc-binding domain\u003c/em\u003e), ubiquitin ligases (\u003cem\u003eHECT\u003c/em\u003e, \u003cem\u003eE3 ligase catalytic domain\u003c/em\u003e), \u003cem\u003eG protein-coupled receptors\u003c/em\u003e, \u003cem\u003eNACHT-associated domain, family 2 secretin-like\u003c/em\u003e, and \u003cem\u003eASB-5\u003c/em\u003e (ankyrin repeat and SOCS box protein 5), highlighting activation of receptor-mediated signaling and protein turnover pathways. In the GIT, FW Adra showed differential expression of \u003cem\u003eintegrase zinc-binding domain proteins\u003c/em\u003e, \u003cem\u003ecalpain-5\u003c/em\u003e, \u003cem\u003eBrf1\u003c/em\u003e, \u003cem\u003eTBP-binding domain\u003c/em\u003e, and \u003cem\u003eleucine-rich repeat and guanylate kinase domain-containing proteins\u003c/em\u003e, reinforcing the prominence of transcriptional and post-transcriptional regulation. At the opposite extreme, SW Marchamalo also displayed a marked enrichment of signaling and regulatory components. In gills, highly expressed genes included \u003cem\u003ecytochrome c\u003c/em\u003e, members of the \u003cem\u003eendonuclease/exonuclease/phosphatase superfamily\u003c/em\u003e, and several \u003cem\u003eribonuclease H-like\u003c/em\u003e proteins, consistent with intensified transcriptional and DNA/RNA processing activity. In the GIT, domains such as \u003cem\u003esterile alpha motif, butyrophilin-like, integrase catalytic core, MyHC-beta\u003c/em\u003e (XRCC4-like), \u003cem\u003eHECT\u003c/em\u003e (E3 ligase catalytic domain), and \u003cem\u003eGTPase IMAP family member 7\u003c/em\u003e were prominent, many of which are implicated in osmoregulatory signaling pathways including \u003cem\u003eGPCR-\u003c/em\u003e and \u003cem\u003eMAPK-related cascades\u003c/em\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] (Supp. Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eEnrichment analyses reinforced this pattern. Amino acid metabolism emerged as central to transcriptional regulation under salinity stress, consistent with previous studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e], with \u003cem\u003eCysteine and methionine metabolism\u003c/em\u003e enriched in FW Adra gills, and \u003cem\u003eTryptophan metabolism\u003c/em\u003e and \u003cem\u003eSelenocompound metabolism\u003c/em\u003e enriched in GIT comparisons involving FW Adra vs SW Marchamalo and BW Cabanes, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Table\u0026nbsp;4). Additional SW Marchamalo-associated pathways included \u003cem\u003eRNA degradation\u003c/em\u003e and \u003cem\u003eDNA replication\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eConsistently, over half of the identified GO terms were linked to signal transduction and transcriptional regulation, with particularly strong representation in FW Adra and SW Marchamalo across all three GO categories. In the gills, Molecular Function terms included \u003cem\u003enucleic acid, ATP, zinc ion\u003c/em\u003e and \u003cem\u003eGTP binding\u003c/em\u003e, together with activities such as \u003cem\u003emethyltransferase\u003c/em\u003e and 2\u003cem\u003e-oxoglutarate-dependent dioxygenase\u003c/em\u003e. Biological Process terms encompassed \u003cem\u003eDNA integration, proteolysis, transcriptional regulation, lipid transport, GPCR signaling\u003c/em\u003e, and \u003cem\u003etransposition\u003c/em\u003e. In the GIT, additional enrichment of \u003cem\u003eprotein phosphorylation, cell surface receptor signaling\u003c/em\u003e, and \u003cem\u003eDNA repair\u003c/em\u003e further emphasized the intensity of regulatory remodeling at the salinity extremes. Together, these results position the freshwater and hypersaline populations as the endpoints of the gradient where transcriptional reprogramming and signaling activity are most pronounced (Supp. Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eIn the two BW populations (Cabanes and Santa Pola), gene expression patterns reflected an intermediate but still pronounced activation of regulatory and signaling machinery. In the gills, domains associated with ubiquitination and protein turnover (e.g., \u003cem\u003eHECT E3 ligase catalytic domain\u003c/em\u003e), DNA repair and polymerase activity, as well as glycosyltransferases such as \u003cem\u003eBGnT-7\u003c/em\u003e, were detected. In the GIT, both populations showed enrichment of transcription- and signaling-related factors, including \u003cem\u003ePiwi-like protein 2\u003c/em\u003e, \u003cem\u003eTATA box-binding protein-like 2\u003c/em\u003e, \u003cem\u003eDnaJ homolog subfamily B member 6\u003c/em\u003e, helically-extended SH3 domains, Tudor domains, and \u003cem\u003eP2X purinoreceptor\u003c/em\u003e, alongside proteins involved in RNA processing (e.g., \u003cem\u003eDDX43\u003c/em\u003e), post-translational modification (F-box proteins, transglutaminase-like), and vesicular trafficking (\u003cem\u003ePRA1\u003c/em\u003e). Together, these profiles indicate that brackish populations maintain active regulatory and signaling networks, but with a comparatively moderated transcriptional response relative to the freshwater and hypersaline endpoints of the gradient.\u003c/p\u003e \u003cp\u003eImmune response and apoptosis are modulated by salinity gradients\u003c/p\u003e \u003cp\u003eImmune-related genes were differentially regulated across the salinity gradient, with both brackish and extreme salinity populations showing distinct immune signatures depending on tissue and comparison. Enrichment analyses revealed multiple GO terms associated with immune system processes, cytokine activity, antigen presentation, and apoptotic regulation, particularly in the gills and GIT (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Supp. Table\u0026nbsp;4). These patterns indicate that salinity shifts are accompanied by coordinated modulation of innate and adaptive immune components, consistent with the well-documented role of environmental salinity as a physiological stressor in fishes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Numerous studies have identified genes implicated in salinity-associated immune responses across osmoregulatory organs, enabling the reconstruction of defense mechanisms at the molecular level [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCytokine-mediated signaling emerged as a prominent component of the salinity-associated immune response. Cytokines act as key messengers regulating communication between immune and non-immune cells during early immune activation. GO term analyses revealed enrichment of immune-related genes, particularly in the gills, where an \u003cem\u003einterleukin-8-like chemokine domain\u003c/em\u003e was upregulated in BW Cabanes and Santa Pola relative to FW and SW populations. The interleukin gene itself was upregulated in BW Cabanes compared to SW Marchamalo, but downregulated in FW Adra relative to both SW Marchamalo and BW Santa Pola. As central regulators of innate and adaptive immunity, interleukins enable rapid responses to environmental stressors such as fluctuating salinity [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent with this pattern, multifunctional proteins interacting with cytokine pathways were also detected in BW populations, including ATP receptors and \u003cem\u003eButyrate response factor 1\u003c/em\u003e (Tristetraprolin), a zinc finger protein involved in immune regulation, cell proliferation, and differentiation [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. In the GIT, \u003cem\u003ehelically-extended SH3\u003c/em\u003e domain-containing proteins and \u003cem\u003enuclear factor interleukin-3-regulated protein\u003c/em\u003e were upregulated in BW populations relative to SW Marchamalo, further supporting enhanced cytokine-associated signaling under intermediate salinity conditions. Together, these coordinated transcriptional changes suggest an adaptive immune adjustment to fluctuating brackish environments, consistent with previous findings in euryhaline fishes [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e] (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eBeyond cytokine signaling, additional components of adaptive and stress-associated immunity were differentially regulated across the salinity gradient. \u003cem\u003eMHC class II\u003c/em\u003e genes were upregulated in FW Adra and SW Marchamalo relative to BW Santa Pola, suggesting enhanced antigen presentation capacity at the salinity extremes. The major histocompatibility complex class II plays a central role in adaptive immune activation [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. In contrast, \u003cem\u003eImmunoglobulin C1-set\u003c/em\u003e domain-containing proteins were downregulated in FW Adra compared to BW Cabanes and SW Marchamalo, indicating population-specific modulation of humoral immune components. Heat shock proteins (HSPs), which contribute to both cellular protection and immune regulation under stress, were also differentially expressed. \u003cem\u003eHeat shock 70 kDa protein 12A\u003c/em\u003e was upregulated in the GIT of FW Adra and in the gills of BW Santa Pola. HSPs facilitate protein refolding and participate in cell cycle control, and their induction under salinity stress has been widely documented [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. However, reduced HSP expression has also been reported under specific stress contexts or combined salinity-temperature challenges [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Upregulation of HSP family members, including ubiquitin-related proteins, has likewise been described during salinity transfer [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In addition, immune effector components were differentially modulated along the salinity gradient. The \u003cem\u003emembrane attack complex component/perforin (MAC)\u003c/em\u003e, essential for cytotoxic activity in both innate and adaptive immunity, was downregulated in BW Cabanes relative to FW Adra, highlighting variation in terminal immune responses across environmental conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Tables\u0026nbsp;2, 4).\u003c/p\u003e \u003cp\u003eWhile acute salinity shifts can activate immune pathways, prolonged exposure may weaken immune capacity and increase susceptibility to infection [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e], suggesting that sustained osmotic stress can exceed compensatory immune mechanisms. Under such conditions, cumulative cellular damage may activate apoptotic signaling pathways. Although \u003cem\u003eAphanius iberus\u003c/em\u003e is euryhaline, sustained osmotic stress may shift the balance from adaptive plasticity toward programmed cell death. Both KEGG and GO analyses supported this pattern, revealing enrichment of apoptosis-related pathways, particularly in the GIT [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. Notably, the KEGG Apoptosis pathway was enriched in GIT comparisons between BW Cabanes and FW Adra. Regulatory components associated with apoptotic modulation were also detected, including \u003cem\u003eapoptosis inhibitor-2 (c-IAP2)\u003c/em\u003e and \u003cem\u003ejunctophilin\u003c/em\u003e in the GIT of BW Santa Pola. In addition, \u003cem\u003eButyrate response factor 1 / Tristetraprolin\u003c/em\u003e, a regulator of tumor necrosis factor production and inflammatory signaling, was upregulated in the GIT of BW Cabanes (Supp. Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eTogether, these results indicate that prolonged or extreme salinity exposure not only activates immune and stress-related pathways but may also engage cell death mechanisms, particularly in intestinal tissues, highlighting the physiological limits of osmotic tolerance.\u003c/p\u003e \u003cp\u003eStructural organization remodeling under salinity stress\u003c/p\u003e \u003cp\u003eGenes associated with cytoskeletal organization and structural remodeling, together with the majority of GO terms within the Cellular Component category, were differentially expressed across the salinity gradient, with a particularly marked signal in BW populations. In the GIT of both BW populations, several DEGs were linked to cytoskeletal structure and cell adhesion, suggesting enhanced structural plasticity under fluctuating salinity conditions. In BW Cabanes, a \u003cem\u003eKASH domain\u003c/em\u003e containing protein was detected, a domain typically localized at the outer nuclear membrane and involved in nuclear positioning and force transmission between the nucleoskeleton and the cytoplasmic cytoskeleton. Additionally, \u003cem\u003ethe helically-extended SH3\u003c/em\u003e domain was upregulated in both BW populations (Cabanes and Santa Pola). This variant SH3 fold functions as a lipid interaction module capable of binding acidic phospholipids and is associated with integrin complexes, which mediate cell\u0026ndash;cell adhesion and mechanotransduction [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. These patterns indicate that BW populations may require enhanced cytoskeletal flexibility to rapidly adjust cellular architecture and maintain cytoplasmic volume under fluctuating osmotic conditions. Changes in cell volume caused by passive water diffusion necessitate rapid reorganization of cytoskeletal elements to preserve structural integrity and cellular homeostasis.\u003c/p\u003e \u003cp\u003eChromatin-associated structural components were also modulated. Histones, which regulate chromatin condensation and transcriptional accessibility, have previously been implicated in osmotic acclimation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In our dataset, \u003cem\u003eHistone H1a\u003c/em\u003e was upregulated in the gills of FW Adra, while \u003cem\u003eHistone H4\u003c/em\u003e was upregulated in the gills of BW Cabanes. Furthermore, the \u003cem\u003echromatin-target of PRMT1 (C-terminal)\u003c/em\u003e protein was upregulated in the GIT of BW Santa Pola. This protein associates with facultative heterochromatin and participates in transcriptional regulation, suggesting coordinated structural and epigenetic remodeling under salinity stress [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] (Supp. Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eWithin the Cellular Component category, numerous GO terms were associated with structural elements and membrane organization. The most frequent terms across both tissues included \u003cem\u003eintegral component of membrane, membrane\u003c/em\u003e, and \u003cem\u003eextracellular region.\u003c/em\u003e Gill-specific enrichment of \u003cem\u003eplasma membrane\u003c/em\u003e and \u003cem\u003eextracellular space\u003c/em\u003e further highlights the structural role of this tissue as the primary interface for osmotic exchange, whereas \u003cem\u003ecytoplasm\u003c/em\u003e and \u003cem\u003eintegral component of plasma membrane\u003c/em\u003e were particularly prominent in the GIT (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supp. Table\u0026nbsp;4). Together, these results indicate coordinated remodeling of cytoskeletal, membrane, and chromatin architecture in response to salinity stress.\u003c/p\u003e \u003cp\u003eActivation of Repetitive Elements under salinity stress\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eTc1 DNA transposon\u003c/em\u003e, which mediates the mobilization of DNA transposons to new genomic loci, was upregulated in the gills of both the FW Adra and SW Marchamalo populations, indicating activation of DNA transposons at the salinity extremes [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. In addition, the \u003cem\u003eBarney transposase (Tcb1 transposase\u003c/em\u003e) was upregulated in the GIT of SW Marchamalo, and the \u003cem\u003eL1 element\u003c/em\u003e, a non-LTR retrotransposon belonging to the Long Interspersed Nuclear Elements (LINEs), which transpose via an RNA intermediate, showed increased expression in the gills of BW Santa Pola [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. These patterns suggest that repetitive elements respond dynamically to osmotic conditions across tissues and environments (Supp. Table\u0026nbsp;2). Repetitive elements can modulate the expression of genes critical for osmoregulation and facilitate rapid adaptation to saline or fluctuating environments, acting as drivers of plasticity and evolutionary change [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e], consistent with the activation patterns observed along the salinity gradient.\u003c/p\u003e \u003cp\u003eWe also detected upregulation of an \u003cem\u003eRRM (RNA recognition motif) domain-containing\u003c/em\u003e gene, consistent with altered RNA processing and post-transcriptional regulation under stress [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. Furthermore, a \u003cem\u003ePiggyBac\u003c/em\u003e transposable element-derived protein was upregulated in the GIT of BW Cabanes and SW Marchamalo. Although \u003cem\u003ePiggyBac\u003c/em\u003e-derived proteins are conserved across taxa, their functional roles in stress adaptation remain poorly understood [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. Together, these findings indicate that activation of repetitive elements forms part of the broader transcriptional remodeling observed along the salinity gradient, potentially contributing to regulatory plasticity in A. iberus under osmotic stress.\u003c/p\u003e \u003cp\u003eEcological and conservation implications\u003c/p\u003e \u003cp\u003eThe pattern observed, with substantially higher numbers of differentially expressed genes in populations inhabiting both hypo- and hyperosmotic environments, suggests that although \u003cem\u003eAphanius iberus\u003c/em\u003e tolerates a broad salinity range, intermediate salinity conditions may represent comparatively less physiologically demanding environments. The elevated transcriptional responses observed at salinity extremes likely reflect the substantial energetic and regulatory costs required to maintain ionic and osmotic homeostasis, consistent with patterns described in other euryhaline fishes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExposure to salinity extremes triggers coordinated cellular responses aimed at preserving homeostasis, including activation of signaling cascades, cytoskeletal remodeling, modulation of membrane transport processes, immune regulation, apoptotic pathways, and enhanced energetic metabolism [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Tissue-specific transcriptional signatures, particularly in the gastrointestinal tract, indicate that spatial physiological specialization within intestinal tissues contributes significantly to overall osmoregulatory capacity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Collectively, these results demonstrate that \u003cem\u003eA. iberus\u003c/em\u003e modulates interconnected osmoregulatory, metabolic, immune, and stress-response pathways under osmotic challenge, revealing substantial transcriptional plasticity across environmental contexts.\u003c/p\u003e \u003cp\u003eFrom a ecological perspective, transitional habitats with intermediate salinity may function as energetically favorable environments and could therefore play a stabilizing role in population persistence. At the same time, the persistence of populations in hypersaline systems, where reduced interspecific competition may offset physiological costs, underscores the ecological flexibility of the species. In a context of accelerating anthropogenic salinization and climate-driven hydrological instability, such plasticity may represent a key component of resilience.\u003c/p\u003e \u003cp\u003eBy generating a comprehensive reference transcriptome for \u003cem\u003eAphanius iberus\u003c/em\u003e, this study provides a genomic framework for future comparative and evolutionary analyses of euryhalinity in fishes. It also expands the application of environmental transcriptomics to an endemic species currently listed as Endangered in the Spanish National Catalogue of Threatened Species ([\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]; Real Decreto 139/2011 (BOE-A-2011-3582)). More broadly, these findings contribute to understanding whether convergent molecular strategies underlie osmotic tolerance across phylogenetically distant taxa, a question of increasing relevance in the context of global climate change.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides the first transcriptomic characterization of salinity responses in the endangered Spanish toothcarp, \u003cem\u003eAphanius iberus\u003c/em\u003e. Our results reveal strong tissue-specific transcriptional responses along a natural salinity gradient, with gills showing extensive differential expression related to ion transport, cytoskeletal organization, and energetic metabolism, while the gastrointestinal tract displayed enrichment of metabolic pathways. The increased number of differentially expressed genes detected in populations inhabiting both hypo- and hyperosmotic environments suggests that intermediate salinity conditions may represent comparatively less physiologically demanding habitats for this species.\u003c/p\u003e \u003cp\u003eThese findings highlight the coordinated molecular mechanisms that enable \u003cem\u003eA. iberus\u003c/em\u003e to tolerate extreme and fluctuating osmotic environments and contribute to expanding environmental transcriptomics in non-model and conservation-relevant species. The reference transcriptome generated here provides a valuable genomic resource for future comparative and evolutionary studies of euryhalinity in fishes and may facilitate further research on the molecular basis of salinity tolerance in Mediterranean coastal systems.\u003c/p\u003e \u003cp\u003eNevertheless, because our analyses are based on transcriptomic profiles from wild populations, environmentally induced plastic responses cannot be fully distinguished from potential population-level genetic differentiation. In addition, only two osmoregulatory tissues were analyzed, whereas other organs such as kidney or liver may also contribute to salinity acclimation. Future studies combining experimental approaches, broader tissue sampling, and population genomic analyses will help clarify the regulatory mechanisms underlying osmotic adaptation in this species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eAll procedures were reviewed and approved by the Animal Experimentation Ethics Committee of the National Museum of Natural Sciences (CEEA-MNCN; Spanish Animal Experimentation Research Centre no. ES280790000189) and conducted in strict accordance with Spanish law RD53/2013, which transposes the EU Directive 2010/63/EU (art. 2, 5f). Experimental protocols followed relevant guidelines and regulations and are reported in compliance with the ARRIVE guidelines (https://arriveguidelines.org).\u003c/p\u003e\n\u003cp\u003eHumane endpoints were defined a priori: following immersion in the anesthetic solution, fish were monitored for the immediate loss of opercular movement and reflexes to confirm effective euthanasia and safeguard animal welfare.\u003c/p\u003e\n\u003cp\u003eSampling of \u003cem\u003eAphanius iberus\u003c/em\u003e was conducted under appropriate regional authorizations:\u003c/p\u003e\n\u003cp\u003e● In Andalusia, sampling in Adra was covered by the \u003cem\u003eResolución de la Directora General de Medio Natural, Biodiversidad y Espacios Protegidos\u003c/em\u003e (25 January 2021), which grants an exception to the general protection regime and authorizes the capture and handling of \u003cem\u003eAphanius\u003c/em\u003e species for scientific purposes, including the inclusion of I. Doadrio and A. López Solano as members of the approved research team.\u003c/p\u003e\n\u003cp\u003e● In Valencia, the \u003cem\u003eDirección General de Medio Natural i Animal\u003c/em\u003e authorized the collection and euthanasia of eight \u003cem\u003eAphanius iberus\u003c/em\u003e individuals for RNA preservation, under Article 13.1 of Decree 32/2004 regulating the Valencian Catalogue of Threatened Fauna Species.\u003c/p\u003e\n\u003cp\u003e● In Murcia, sampling in the Salinas de Marchamalo (Mar Menor area) was conducted under research permit AUF/2022/0007, with institutional support from the Universidad de Murcia and collaboration of Dr. Francisco J. Oliva-Paterna, who certified compliance with all regional regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot\u0026nbsp;applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequence reads generated during the current study are available in the NCBI Nucleotide Database under the Bioproject (PRJNA1041354), with accession numbers provided in Supp. Table 1.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis project was supported by the \u003cem\u003eMinisterio de Ciencia, Innovación y Universidades,\u0026nbsp;\u003c/em\u003eSpain (Project Saltfish; PID2023-146173NB-C22) granted to ID. AL-S is funded by an FPI fellowship from the same governmental institution (PRE2020-092988). EA\u0026nbsp;is supported by a predoctoral fellowship (FPI-UAH 2023, Universidad de Alcalá Programme), Spain. TLN is supported by an FPU fellowship (FPU2020/04500) from the \u003cem\u003eMinisterio de Ciencia, Innovación y Universidades,\u0026nbsp;\u003c/em\u003eSpain.\u003c/p\u003e\n\u003cp\u003eAuthors' contributions\u003c/p\u003e\n\u003cp\u003eAL-S, AV, SP and ID contributed to the conceptualization and to the research design. AL-S and TLN carried out the field work. AL-S, AV and EA performed the laboratory work. The analyses of the data were led by AL-S and AV with collaboration of SP and EA. The interpretation of the results was performed by all the authors. AL-S wrote the first draft which was revised by all authors.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe would like to thank the Spanish Ministry of Science and Innovation and the State Agency for Research for their financial support through Project Saltfish (PID2023-146173NB-C22) awarded to Ignacio Doadrio. We also acknowledge support from a fellowship from “la Caixa” Foundation (ID 100010434), with fellowship code LCF/BQ/PR24/12050011 and a Ramón y Cajal grant RYC2023-044466-I awarded to Aida Verdes. We are grateful to Sergio García Peña for his help in the sampling. We would also like to thank Antonio Pradillo, Jesús Hernández, and Pilar Risueño from the Centro de Conservación de Especies Dulceacuícolas (\"Piscifactoría de El Palmar\") for their assistance with sampling and for obtaining the requisite permission granted by the Government of Valencia (Spain). We also thank Francisco Oliva-Paterna from the University of Murcia for his help with sampling and permits in Murcia, and Mariano Paracuellos from the University of Almería for his support with sampling in Adra.\u003c/p\u003e\n\u003cp\u003eWe further acknowledge the Universidad Complutense de Madrid for hosting Alfonso López-Solano and Tessa Lynn Nester within the \u003cem\u003eDoctorado en Biología\u003c/em\u003e program. We also acknowledge the Universidad de Alcalá for hosting Elena Andrés within the PhD program in Ecology, Biodiversity and Global Change. Finally, we thank CESGA (Centro de Supercomputación de Galicia) for its indispensable contribution to data analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCarpenter SR, Stanley EH, Vander Zanden MJ. State of the world\u0026rsquo;s freshwater ecosystems: physical, chemical, and biological changes. Annu Rev Environ Resour. 2011;36(1):75-99. doi:10.1146/annurev-environ-021810-094524 \u003c/li\u003e\n\u003cli\u003eSeehausen O, Wagner CE. Speciation in freshwater fishes. Annu Rev Ecol Evol Syst. 2014;45(1):621-651. doi:10.1146/annurev-ecolsys-120213-091818.\u003c/li\u003e\n\u003cli\u003eLee CE, Bell MA. Causes and consequences of recent freshwater invasions by saltwater animals. Trends Ecol Evol. 1999;14(7):284-288. doi:10.1016/S0169-5347(99)01596-7\u003c/li\u003e\n\u003cli\u003eSchneider RF, Meyer A. How plasticity, genetic assimilation and cryptic genetic variation may contribute to adaptive radiations. Mol Ecol. 2017;26(1):330-350. doi:10.1111/mec.13880.\u003c/li\u003e\n\u003cli\u003eHoar WS, Randall DJ, Donaldson EM. Fish physiology. Vol. 10-11. New York: Academic Press; 1983.\u003c/li\u003e\n\u003cli\u003eSchultz ET, McCormick SD. Euryhalinity in an evolutionary context. In: McCormick SD, Farrell AP, Brauner CJ, editors. Fish physiology. Vol. 32. New York: Academic Press; 2012. p. 477-533.\u003c/li\u003e\n\u003cli\u003eMcCormick SD, Farrell AP, Brauner CJ, editors. Fish physiology: euryhaline fishes. Vol. 32. New York: Academic Press; 2013.\u003c/li\u003e\n\u003cli\u003eMauro AA, Velotta JP, Ghalambor CK. A systems approach to homeostasis: what euryhaline fish teach us about organismal stress responses. Integr Comp Biol. 2025;icaf085. doi:10.1093/icb/icaf085\u003c/li\u003e\n\u003cli\u003eVij S, Purushothaman K, Sridatta PSR, Jerry DR. Transcriptomic analysis of gill and kidney from Asian seabass (\u003cem\u003eLates calcarifer\u003c/em\u003e) acclimated to different salinities reveals pathways involved with euryhalinity. Genes. 2020;11(7):733. doi:10.3390/genes11070733.\u003c/li\u003e\n\u003cli\u003eHoar WS, Randall DJ, Donaldson EM, editors. Fish physiology. New York: Academic Press; 1983.\u003c/li\u003e\n\u003cli\u003eB\u0026oelig;uf G, Payan P. How should salinity influence fish growth? Comp Biochem Physiol C Toxicol Pharmacol. 2001;130(4):411-423. doi:10.1016/S1532-0456(01)00268-X.\u003c/li\u003e\n\u003cli\u003eCunillera-Montcus\u0026iacute; D, Beklioğlu M, Ca\u0026ntilde;edo-Arg\u0026uuml;elles M, Jeppesen E, Ptacnik R, Amorim CA, et al. Freshwater salinisation: a research agenda for a saltier world. Trends Ecol Evol. 2022;37(5):440-453. doi:10.1016/j.tree.2021.12.005\u003c/li\u003e\n\u003cli\u003eMałachowicz M, Krasnov A, Wenne R. Diverse transcriptome responses to salinity change in Atlantic cod subpopulations. Cells. 2023;12(23):2760. doi:10.3390/cells12232760.\u003c/li\u003e\n\u003cli\u003eK\u0026uuml;ltz D. Physiological mechanisms used by fish to cope with salinity stress. J Exp Biol. 2015;218(12):1907\u0026ndash;1914.\u003c/li\u003e\n\u003cli\u003eShi Z, Huang X, Fu R, Wang H, Luo H, Chen B, et al. Salinity stress on embryos and early larval stages of the pomfret \u003cem\u003ePampus punctatissimus\u003c/em\u003e. Aquaculture. 2008;275(1-4):306-310. doi:10.1016/j.aquaculture.2008.01.030\u003c/li\u003e\n\u003cli\u003eYuan XC, He S, Liang XF, Luo X, Li A, Zhou Y. Food conditions and water salinity affect survival and growth of golden mandarin fish, \u003cem\u003eSiniperca scherzeri\u003c/em\u003e, larvae through transcriptional regulation of growth and lipometabolic genes. J World Aquac Soc. 2018;49(3):590-600. doi:10.1111/jwas.12450\u003c/li\u003e\n\u003cli\u003eWong MKS, Ozaki H, Suzuki Y, Iwasaki W, Takei Y. Discovery of osmotic sensitive transcription factors in fish intestine via a transcriptomic approach. BMC Genomics. 2014;15:947. doi:10.1186/1471-2164-15-1134\u003c/li\u003e\n\u003cli\u003eEvans DH, Piermarini PM, Choe KP. The multifunctional fish gill: dominant site of gas exchange, osmoregulation, acid-base regulation, and excretion of nitrogenous waste. Physiol Rev. 2005;85(1):97\u0026ndash;177.\u003c/li\u003e\n\u003cli\u003eEdwards SL, Marshall WS. Principles and patterns of osmoregulation and euryhalinity in fishes. In: Perry SF, Farrell AP, Brauner CJ, editors. Fish physiology. Vol. 32. New York: Academic Press; 2012. p. 1-44. doi:10.1016/B978-0-12-396951-4.00001-3.\u003c/li\u003e\n\u003cli\u003eLam SH, Lui EY, Li Z, Cai S, Sung WK, Mathavan S, et al. Differential transcriptomic analyses revealed genes and signaling pathways involved in iono-osmoregulation and cellular remodeling in the gills of euryhaline Mozambique tilapia, \u003cem\u003eOreochromis mossambicus\u003c/em\u003e. BMC Genomics. 2014;15:921. doi:10.1186/1471-2164-15-921.\u003c/li\u003e\n\u003cli\u003eWhitehead A, Roach JL, Zhang S, Galvez F. Salinity- and population-dependent genome regulatory response during osmotic acclimation in the killifish (\u003cem\u003eFundulus heteroclitus\u003c/em\u003e) gill. J Exp Biol. 2012;215(8):1293-1305. doi:10.1242/jeb.062075\u003c/li\u003e\n\u003cli\u003eRana SB, Zadlock IV FJ, Zhang Z, Murphy WR, Bentivegna CS. Comparison of de novo transcriptome assemblers and k-mer strategies using the killifish, \u003cem\u003eFundulus heteroclitus\u003c/em\u003e. PLoS One. 2016;11(4):e0153104. doi:10.1371/journal.pone.0153104.\u003c/li\u003e\n\u003cli\u003eWhitehead A, Roach JL, Zhang S, Galvez F. Genomic mechanisms of evolved physiological plasticity in killifish distributed along an environmental salinity gradient. Proc Natl Acad Sci U S A. 2011;108(15):6193-6198. doi:10.1073/pnas.1017542108.\u003c/li\u003e\n\u003cli\u003eCui Q, Qiu L, Yang X, Shang S, Yang B, Chen M, et al. Transcriptome profiling of the low-salinity stress responses in the gills of the juvenile \u003cem\u003ePseudopleuronectes yokohamae\u003c/em\u003e. Comp Biochem Physiol D Genomics Proteomics. 2019;32:100612. doi:10.1016/j.cbd.2019.100612.\u003c/li\u003e\n\u003cli\u003eLi C, Zhang Y, Wang R, Lu J, Nandi S, Mohanty S, et al. RNA-seq analysis of mucosal immune responses reveals signatures of intestinal barrier disruption and pathogen entry following \u003cem\u003eEdwardsiella ictaluri\u003c/em\u003e infection in channel catfish, \u003cem\u003eIctalurus punctatus\u003c/em\u003e. Fish Shellfish Immunol. 2012;32(5):816-827. doi:10.1016/j.fsi.2012.02.004\u003c/li\u003e\n\u003cli\u003eBoutet I, Ky CL, Bonhomme F. A transcriptomic approach of salinity response in the euryhaline teleost \u003cem\u003eDicentrarchus labrax\u003c/em\u003e. Gene. 2006;379:40-50. doi:10.1016/j.gene.2006.04.011\u003c/li\u003e\n\u003cli\u003eNorman JD, Ferguson MM, Danzmann RG. An integrated transcriptomic and comparative genomic analysis of differential gene expression in Arctic charr (\u003cem\u003eSalvelinus alpinus\u003c/em\u003e) following seawater exposure. J Exp Biol. 2014;217(22):4029-4042. doi:10.1242/jeb.107441\u003c/li\u003e\n\u003cli\u003eMohindra V, Chowdhury LM, Chauhan N, Paul A, Singh RK, Kushwaha B, et al. Transcriptome analysis revealed osmoregulation related regulatory networks and hub genes in the gills of Hilsa shad, \u003cem\u003eTenualosa ilisha\u003c/em\u003e, during the migratory osmotic stress. Mar Biotechnol. 2023;25(1):161-173. doi:10.1007/s10126-022-10190-4\u003c/li\u003e\n\u003cli\u003ePan J, Wang M, Zhu J, Huang Y, Zhang F, Li E, et al. Quantitative proteomic and metabolomic profiling reveals different osmoregulation mechanisms of tilapia cells coping with different hyperosmotic stress. J Proteomics. 2024;296:105113. doi:10.1016/j.jprot.2024.105113.\u003c/li\u003e\n\u003cli\u003eLi C, Wang L, Pan M, Wang R, Zhang H, Li W, et al. Comparative transcriptomic analysis reveals osmoregulatory mechanisms of juvenile \u003cem\u003eLateolabrax maculatus\u003c/em\u003e responses to long-term hypotonic and hypertonic acclimation. Aquaculture. 2025;596:741864. doi:10.1016/j.aquaculture.2024.741864\u003c/li\u003e\n\u003cli\u003eGibbons TC, Metzger DCH, Healy TM, Schulte PM. Gene expression plasticity in response to salinity acclimation in threespine stickleback ecotypes from different salinity habitats. Mol Ecol. 2017;26(10):2711-2725. doi:10.1111/mec.14065\u003c/li\u003e\n\u003cli\u003eTaugb\u0026oslash;l A, Solbakken MH, Jakobsen KS, V\u0026oslash;llestad LA. Salinity-induced transcriptome profiles in marine and freshwater threespine stickleback after an abrupt 6-hour exposure. Ecol Evol. 2022;12(10):e9395. doi:10.1002/ece3.9395.\u003c/li\u003e\n\u003cli\u003eLai KP, Li JW, Wang SY, Chiu JMY, Tse A, Lau K, et al. Tissue-specific transcriptome assemblies of the marine medaka \u003cem\u003eOryzias melastigma\u003c/em\u003e and comparative analysis with the freshwater medaka \u003cem\u003eOryzias latipes\u003c/em\u003e. BMC Genomics. 2015;16:135. doi:10.1186/s12864-015-1325-7\u003c/li\u003e\n\u003cli\u003eChen X, Gong H, Chi H, Xu B, Zheng Z, Bai Y. Gill transcriptome analysis revealed the difference in gene expression between freshwater and seawater acclimated guppy (\u003cem\u003ePoecilia reticulata\u003c/em\u003e). Mar Biotechnol. 2021;23(4):615-627. doi:10.1007/s10126-021-10053-4\u003c/li\u003e\n\u003cli\u003eRonkin D, Seroussi E, Nitzan T, Doron-Faigenboim A, Cnaani A. Intestinal transcriptome analysis revealed differential salinity adaptation between two tilapiine species. Comp Biochem Physiol D Genomics Proteomics. 2015;13:35-43. doi:10.1016/j.cbd.2015.01.003\u003c/li\u003e\n\u003cli\u003eXu Z, Gan L, Li T, Xu C, Chen K, Wang X, et al. Transcriptome profiling and molecular pathway analysis of genes in association with salinity adaptation in Nile tilapia \u003cem\u003eOreochromis niloticus\u003c/em\u003e. PLoS One. 2015;10(8):e0136506. doi:10.1371/journal.pone.0136506.\u003c/li\u003e\n\u003cli\u003eValenzuela-Mu\u0026ntilde;oz V, V\u0026aacute;ldes JA, Gallardo-Esc\u0026aacute;rate C. Transcriptome profiling of long non-coding RNAs during the Atlantic salmon smoltification process. Mar Biotechnol. 2021;23:308-320. doi:10.1007/s10126-021-10024-9\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez CC, Weber GM, Gao G, Cleveland BM, Yao J, Rexroad CE. Generation of a reference transcriptome for evaluating rainbow trout responses to various stressors. BMC Genomics. 2011;12:626. doi:10.1186/1471-2164-12-626.\u003c/li\u003e\n\u003cli\u003eZhang X, Wen H, Wang H, Ren Y, Zhao J, Li Y. RNA-Seq analysis of salinity stress\u0026ndash;responsive transcriptome in the liver of spotted sea bass (\u003cem\u003eLateolabrax maculatus\u003c/em\u003e). PLoS One. 2017;12(3):e0173238. doi:10.1371/journal.pone.0173238.\u003c/li\u003e\n\u003cli\u003eShen Y, He Y, Bi Y, Chen J, Zhao Z, Li J, et al. Transcriptome analysis of gill from \u003cem\u003eLateolabrax maculatus\u003c/em\u003e and aqp3 gene expression. Aquac Fish. 2019;4(6):247-254. doi:10.1016/j.aaf.2019.03.004\u003c/li\u003e\n\u003cli\u003eLi X, Liu S, Wang Y, Lu W, Zhang Q, Cheng J. Genomic and transcriptomic landscape and evolutionary dynamics of heat shock proteins in spotted sea bass (\u003cem\u003eLateolabrax maculatus\u003c/em\u003e) under salinity change and alkalinity stress. Biology. 2022;11(3):353. doi:10.3390/biology11030353\u003c/li\u003e\n\u003cli\u003eDoadrio I, editor. Atlas y Libro Rojo de los Peces Continentales de Espa\u0026ntilde;a. Madrid: Direcci\u0026oacute;n General de Conservaci\u0026oacute;n de la Naturaleza - Museo Nacional de Ciencias Naturales; CSIC/MIMAM; 2001.\u003c/li\u003e\n\u003cli\u003eDoadrio I. Ictiofauna continental espa\u0026ntilde;ola: bases para su seguimiento. Madrid: Ministerio de Medio Ambiente y Medio Rural y Marino, Centro de Publicaciones; 2011.\u003c/li\u003e\n\u003cli\u003eBonzi LC, Poltronieri C, Maradonna F, Gioacchini G, Carnevali O. The time course of molecular acclimation to seawater in a euryhaline fish. Sci Rep. 2021;11:18127. doi:10.1038/s41598-021-97295-3\u003c/li\u003e\n\u003cli\u003eWilson EJ, Barts N, Coffin JL, Johnson JB, Rodr\u0026iacute;guez Pe\u0026ntilde;a CM, Kelley JL, et al. Gene expression signatures between \u003cem\u003eLimia perugiae\u003c/em\u003e (Poeciliidae) populations from freshwater and hypersaline habitats, with comparisons to other teleosts. PLoS One. 2024;19(12):e0315014. Doi:10.1371/journal.pone.0315014\u003c/li\u003e\n\u003cli\u003eAlcaraz C, Pou-Rovira Q, Garc\u0026iacute;a-Berthou E. Use of a flooded salt marsh habitat by an endangered cyprinodontid fish (\u003cem\u003eAphanius iberus\u003c/em\u003e). Hydrobiologia. 2008;600(1):177-185. doi:10.1007/s10750-007-9230-y\u003c/li\u003e\n\u003cli\u003eOliva-Paterna FJ, Ruiz-Navarro A, Torralva M, Fern\u0026aacute;ndez-Delgado C. Biology of the endangered cyprinodontid \u003cem\u003eAphanius iberus\u003c/em\u003e in a saline wetland (SE Iberian Peninsula). Ital J Zool. 2009;76(3):316-329. doi:10.1080/11250000802488159\u003c/li\u003e\n\u003cli\u003ePerdices A, Carmona JA, Fern\u0026aacute;ndez-Delgado C, Doadrio I. Nuclear and mitochondrial data reveal high genetic divergence among Atlantic and Mediterranean populations of the Iberian killifish \u003cem\u003eAphanius iberus\u003c/em\u003e (Teleostei: Cyprinodontidae). Heredity. 2001;87(3):314\u0026ndash;324.\u003c/li\u003e\n\u003cli\u003eDoadrio I, Carmona JA, Fern\u0026aacute;ndez-Delgado C. Morphometric study of the Iberian \u003cem\u003eAphanius\u003c/em\u003e (Actinopterygii, Cyprinodontiformes), with description of a new species. Folia Zool. 2002;51:67\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eGonz\u0026aacute;lez EG, Cunha C, Ghanavi HR, Oliva-Paterna FJ, Torralva M, Doadrio I. Phylogeography and population genetic analyses in the Iberian toothcarp (\u003cem\u003eAphanius iberus \u003c/em\u003eValenciennes, 1846) at different time scales. J Hered. 2018;109(3):253\u0026ndash;263. doi:10.1093/jhered/esx076.\u003c/li\u003e\n\u003cli\u003eNester TL, L\u0026oacute;pez-Solano A, Perea S, Doadrio I. Genomic population structure and diversity of the endangered \u003cem\u003eAphanius iberus\u003c/em\u003e: strategies for killifish conservation. Conserv Genet. 2025;26(2):263\u0026ndash;277.\u003c/li\u003e\n\u003cli\u003eEstarellas M, L\u0026oacute;pez-Solano A, Mochales-Ria\u0026ntilde;o G, Perea S, Talavera A, Burriel-Carranza B, et al. Saving the locals: a conservation genomics approach to the endangered Spanish toothcarp, \u003cem\u003eAphanius iberus\u003c/em\u003e (Valenciennes, 1846). Sci Rep. 2025.\u003c/li\u003e\n\u003cli\u003eAndrews S. FastQC: a quality control tool for high throughput sequence data. 2010. http://www.bioinformatics.babraham.ac.uk/projects/fastqc. Accessed Mar 2025.\u003c/li\u003e\n\u003cli\u003eBolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114-2120. doi:10.1093/bioinformatics/btu170\u003c/li\u003e\n\u003cli\u003eL\u0026oacute;pez-Solano A, Doadrio I, Nester TL, Perea S. De novo genome hybrid assembly and annotation of the endangered and euryhaline fish \u003cem\u003eAphanius iberus\u003c/em\u003e (Valenciennes, 1846) with identification of genes potentially involved in salinity adaptation. BMC Genomics. 2025;26:136. doi:10.1186/s12864-025-11327-0\u003c/li\u003e\n\u003cli\u003eDobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15-21. doi:10.1093/bioinformatics/bts635.\u003c/li\u003e\n\u003cli\u003ePertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290-295. doi:10.1038/nbt.3122.\u003c/li\u003e\n\u003cli\u003eGrabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat Biotechnol. 2011;29(7):644-652. doi:10.1038/nbt.1883.\u003c/li\u003e\n\u003cli\u003eKolde R. pheatmap: Pretty heatmaps. R package version 1.0.12. 2015. https://CRAN.R-project.org/package=pheatmap. Accessed Apr 2025.\u003c/li\u003e\n\u003cli\u003eBlighe K, Rana S, Lewis M. EnhancedVolcano: publication-ready volcano plots with enhanced colouring and labeling. R package version 1.27.0. 2025. doi:10.18129/B9.bioc.EnhancedVolcano\u003c/li\u003e\n\u003cli\u003ePosit Team. RStudio: integrated development environment for R. Boston (MA): Posit Software, PBC; 2025. https://www.posit.co/. Accessed Jan 2025.\u003c/li\u003e\n\u003cli\u003eJones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, et al.InterPro‑Scan 5: Genome-scale protein function classification. Bioinformatics. 2014;30(9):1236\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eCasimiro-Soriguer CS, Mu\u0026ntilde;oz-M\u0026eacute;rida A, P\u0026eacute;rez-Pulido AJ. Sma3s: a universal tool for easy functional annotation of proteomes and transcriptomes. Proteomics. 2017;17(12):1700071. doi:10.1002/pmic.201700071 \u003c/li\u003e\n\u003cli\u003eKanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49(D1):D545-D551. doi:10.1093/nar/gkaa970\u003c/li\u003e\n\u003cli\u003eGe SX, Jung D, Yao R. ShinyGO: a graphical enrichment tool for animals and plants. Bioinformatics. 2020;36(8):2628-2629. doi:10.1093/bioinformatics/btz931.\u003c/li\u003e\n\u003cli\u003eNguyen TV, Jung H, Nguyen TM, Hurwood D, Mather P. Evaluation of potential candidate genes involved in salinity tolerance in striped catfish (\u003cem\u003ePangasianodon hypophthalmus\u003c/em\u003e) using an RNA-Seq approach. Mar Genomics. 2016;25:75-88. doi:10.1016/j.margen.2015.11.010\u003c/li\u003e\n\u003cli\u003eLiang P, Saqib HSA, Lin Z, Zheng R, Qiu Y, Xie Y, et al. RNA-seq analyses of marine medaka (\u003cem\u003eOryzias melastigma\u003c/em\u003e) reveal salinity responsive transcriptomes in the gills and livers. Aquat Toxicol. 2021;240:105970. doi:10.1016/j.aquatox.2021.105970.\u003c/li\u003e\n\u003cli\u003eLin G, Li S, Huang J, Gao D, Lu J. Hypoosmotic stress induced functional alternations of intestinal barrier integrity, inflammatory reactions, and neurotransmission along gut-brain axis in the yellowfin seabream (\u003cem\u003eAcanthopagrus latus\u003c/em\u003e). Fish Physiol Biochem. 2021;47(6):1725-1738. doi:10.1007/s10695-021-01011-x\u003c/li\u003e\n\u003cli\u003eTine M, De Lorgeril J, D\u0026apos;Cotta H, Pepey E, Bonhomme F, Baroiller JF, et al. Transcriptional responses of the black-chinned tilapia \u003cem\u003eSarotherodon melanotheron\u003c/em\u003e to salinity extremes. Mar Genomics. 2008;1(2):37-46. doi:10.1016/j.margen.2008.06.001\u003c/li\u003e\n\u003cli\u003eSu H, Ma D, Zhu H, Liu Z, Gao F. Transcriptomic response to three osmotic stresses in gills of hybrid tilapia (\u003cem\u003eOreochromis mossambicus\u003c/em\u003e female \u0026times; \u003cem\u003eO. urolepis hornorum\u003c/em\u003e male). BMC Genomics. 2020;21:673. doi:10.1186/s12864-020-6512-5\u003c/li\u003e\n\u003cli\u003eEscobar-Sierra C, Canedo-Arg\u0026uuml;elles M, Vinyoles D, Lampert KP. Unravelling the molecular mechanisms of fish salinity adaptation in the face of multiple stressors: a comparative multi-tissue transcriptomic study in the Llobregat River, Barcelona, Spain. bioRxiv. 2023. doi:10.1101/2023.11.20.567554\u003c/li\u003e\n\u003cli\u003eMaryoung LA, Lavado R, Bammler TK, Gallagher EP, Stapleton PL, Beyer RP, et al. Differential gene expression in liver, gill, and olfactory rosettes of coho salmon (\u003cem\u003eOncorhynchus kisutch\u003c/em\u003e) after acclimation to salinity. Mar Biotechnol. 2015;17:703-717. doi:10.1007/s10126-015-9654-6. doi:10.1007/s10126-015-9649-5\u003c/li\u003e\n\u003cli\u003eGuo B, Tang Z, Wu C, Xu K, Qi P. Transcriptomic analysis reveals an efficient osmoregulatory system in Siberian sturgeon \u003cem\u003eAcipenser baeri\u003c/em\u003e in response to salinity stress. Sci Rep. 2018;8:14353. doi:10.1038/s41598-018-32771-x\u003c/li\u003e\n\u003cli\u003eLee SY, Lee HJ, Kim YK. Comparative transcriptome profiling of selected osmotic regulatory proteins in the gill during seawater acclimation of chum salmon (\u003cem\u003eOncorhynchus keta\u003c/em\u003e) fry. Sci Rep. 2020;10:1987. doi:10.1038/s41598-020-58915-6.\u003c/li\u003e\n\u003cli\u003eLi Z, Gao T, Han Z. RNA-seq and analysis of \u003cem\u003eArgyrosomus japonicus\u003c/em\u003e under different salinities. Front Mar Sci. 2021;8:790065. doi:10.3389/fmars.2021.790065\u003c/li\u003e\n\u003cli\u003eTang CH, Lee TH. The effect of environmental salinity on the protein expression of Na⁺/K⁺-ATPase, Na⁺/K⁺/2Cl⁻ cotransporter, cystic fibrosis transmembrane conductance regulator, anion exchanger 1, and chloride channel 3 in gills of a euryhaline teleost, \u003cem\u003eTetraodon nigroviridis\u003c/em\u003e. Comp Biochem Physiol A Mol Integr Physiol. 2007;147(2):521-528. doi:10.1016/j.cbpa.2007.01.679\u003c/li\u003e\n\u003cli\u003eRuiz Jarabo de la Rocha I, Barany Ruiz A, Jerez Cepa I, Mancera Romero JM, Fuentes J. Intestinal response to salinity challenge in the Senegalese sole (\u003cem\u003eSolea senegalensis\u003c/em\u003e). Comp Biochem Physiol A Mol Integr Physiol. 2017;203:66-75. doi:10.1016/j.cbpa.2016.11.009\u003c/li\u003e\n\u003cli\u003eJentsch TJ. Molecular physiology of anion channels. Curr Opin Cell Biol. 1994;6(4):600-606. doi:10.1016/0955-0674(94)90082-5\u003c/li\u003e\n\u003cli\u003eLi J, Xue L, Cao M, Zhang Y, Wang Y, Xu S, et al. Gill transcriptomes reveal expression changes of genes related with immune and ion transport under salinity stress in silvery pomfret (\u003cem\u003ePampus argenteus\u003c/em\u003e). Fish Physiol Biochem. 2020;46:1255-1277. doi:10.1007/s10695-020-00786-9\u003c/li\u003e\n\u003cli\u003eSun Z, Lou F, Zhang Y, Song N. Gill transcriptome sequencing and de novo annotation of \u003cem\u003eAcanthogobius ommaturus\u003c/em\u003e in response to salinity stress. Genes. 2020;11(6):631. doi:10.3390/genes11060631.\u003c/li\u003e\n\u003cli\u003eHe Z, Shou C, Han Z. Transcriptome analysis of marbled rockfish \u003cem\u003eSebastiscus marmoratus\u003c/em\u003e under salinity stress. Animals. 2023;13(3):400. doi:10.3390/ani13030400\u003c/li\u003e\n\u003cli\u003eThanh NM, Jung H, Lyons RE, Chand V, Tuan NV, Thu VTM, et al. A transcriptomic analysis of striped catfish (\u003cem\u003ePangasianodon hypophthalmus\u003c/em\u003e) in response to salinity adaptation: de novo assembly, gene annotation and marker discovery. Comp Biochem Physiol D Genomics Proteomics. 2014;10:52-63. doi:10.1016/j.cbd.2014.04.001\u003c/li\u003e\n\u003cli\u003eTseng YC, Hwang PP. Some insights into energy metabolism for osmoregulation in fish. Comp Biochem Physiol C Toxicol Pharmacol. 2008;148(4):419-429. doi:10.1016/j.cbpc.2008.04.009\u003c/li\u003e\n\u003cli\u003eFang H, Yang YY, Wu XM, Zheng SY, Song YJ, Zhang J, et al. Effects and molecular regulation mechanisms of salinity stress on the health and disease resistance of grass carp. Front Immunol. 2022;13:917497. doi:10.3389/fimmu.2022.917497\u003c/li\u003e\n\u003cli\u003eChen MT, Dong L, Zhang XH, Yin XL, Ning HM, Shen C, et al. ZFP36L1 promotes monocyte/macrophage differentiation by repressing CDK6. Sci Rep. 2015;5:16229. doi:10.1038/srep16229\u003c/li\u003e\n\u003cli\u003eCook ME, Bradstreet TR, Webber AM, Kim J, Santeford A, Harris KM, et al. The ZFP36 family of RNA binding proteins regulates homeostatic and autoreactive T cell responses. Sci Immunol. 2022;7(76):eabo0981. doi:10.1126/sciimmunol.abo0981\u003c/li\u003e\n\u003cli\u003eWang Z, Du J, Lam SH, Mathavan S, Matsudaira P, Gong Z. Morphological and molecular evidence for functional organization along the rostrocaudal axis of the adult zebrafish intestine. BMC Genomics. 2010;11:392.\u003c/li\u003e\n\u003cli\u003eRoche PA, Furuta K. The ins and outs of MHC class II-mediated antigen processing and presentation. Nat Rev Immunol. 2015;15(4):203-216. doi:10.1038/nri3818\u003c/li\u003e\n\u003cli\u003eZhang M, Li L, Liu Y, Gao X. Effects of sudden drop in salinity on osmotic pressure regulation and antioxidant defense mechanism of \u003cem\u003eScapharca subcrenata\u003c/em\u003e. Front Physiol. 2020;11:884. doi:10.3389/fphys.2020.00884.\u003c/li\u003e\n\u003cli\u003eTort L. Stress and immune modulation in fish. Dev Comp Immunol. 2011;35(12):1366-1375. doi:10.1016/j.dci.2011.07.002.\u003c/li\u003e\n\u003cli\u003eFulda S, Gorman AM, Hori O, Samali A. Cellular stress responses: cell survival and cell death. Int J Cell Biol. 2010;2010:214074. doi:10.1155/2010/214074.\u003c/li\u003e\n\u003cli\u003eKrasnov A, Koskinen H, Afanasyev S, M\u0026ouml;ls\u0026auml; H. Transcribed Tc1-like transposons in salmonid fish. BMC Genomics. 2005;6:107. doi:10.1186/1471-2164-6-107\u003c/li\u003e\n\u003cli\u003eWicker T, Sabot F, Hua-Van A, Bennetzen JL, Capy P, Chalhoub B, et al. A unified classification system for eukaryotic transposable elements. Nat Rev Genet. 2007;8(12):973-982. doi:10.1038/nrg2165.\u003c/li\u003e\n\u003cli\u003eBourque G, Burns KH, Gehring M, Gorbunova V, Seluanov A, Hammell M, et al. Ten things you should know about transposable elements. Genome Biol. 2018;19:199. doi:10.1186/s13059-018-1577-z.\u003c/li\u003e\n\u003cli\u003eYuan J, Zhang X, Wang M, Sun Y, Liu C, Li S, et al. Simple sequence repeats drive genome plasticity and promote adaptive evolution in penaeid shrimp. Commun Biol. 2021;4(1):186. doi:10.1038/s42003-021-01716-y\u003c/li\u003e\n\u003cli\u003eCarotti E, Carducci F, Greco S, Gerdol M, Di Marino D, Perta N, et al. Transcriptional contribution of transposable elements in relation to salinity conditions in teleosts and silencing mechanisms involved. Int J Mol Sci. 2022;23:5215. doi:10.3390/ijms23095215 \u003c/li\u003e\n\u003cli\u003eMaris C, Dominguez C, Allain FHT. The RNA recognition motif, a plastic RNA-binding platform to regulate post-transcriptional gene expression. FEBS J. 2005;272(9):2118-2131. doi:10.1111/j.1742-4658.2005.04653.x\u003c/li\u003e\n\u003cli\u003eWilson MH, Coates CJ, George AL. PiggyBac transposon-mediated gene transfer in human cells. Mol Ther. 2007;15(1):139-145. doi:10.1038/sj.mt.6300028 \u003c/li\u003e\n\u003cli\u003eYusa K. piggyBac transposon. In: Craig NL, Chandler M, Gellert M, Lambowitz AM, Rice PA, Sandmeyer SB, editors. Mobile DNA III. Washington (DC): ASM Press; 2015. p. 873-890. doi:10.1128/9781555819217.ch39\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Transcriptomics, Aphanius iberus, Differential Gene Expression, Salinity, Osmoregulation, Adaptation","lastPublishedDoi":"10.21203/rs.3.rs-9115348/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9115348/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\n\u003cp\u003eSalinity is a major ecological driver in aquatic environments and strongly influences the physiology, distribution, and survival of fish species. While many fishes are restricted to narrow salinity ranges, euryhaline species can tolerate large osmotic fluctuations despite the substantial physiological adjustments required. The Spanish toothcarp, \u003cem\u003eAphanius iberus\u003c/em\u003e, an endemic Mediterranean killifish, is one of such exceptional species capable of inhabiting environments ranging from freshwater to hypersaline systems. However, despite this remarkable resilience, the molecular mechanisms underlying salinity tolerance and osmoregulatory plasticity in this species remain poorly understood.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eWe analyzed using RNA sequencing transcriptomes from the gills and gastrointestinal tract of individuals from four wild populations spanning a natural salinity gradient from freshwater (0.75 PSU) to brackish (5-10 PSU) and hypersaline (~50 PSU) habitats. Differential gene expression analyses revealed strong tissue-specific patterns and environment-dependent responses. A substantially higher number of differentially expressed genes was detected in the gills, where genes associated with ion transport, cytoskeletal remodeling, and energetic metabolism varied across salinity conditions, reflecting their central role in osmoregulation. In the gastrointestinal tract, pathways related to lipid and carbohydrate metabolism were enriched, particularly in brackish populations. In addition, several genes associated with osmotic stress responses, including ATPases, histones, and transposable elements, showed significant expression differences across populations.\u003c/p\u003e\n\u003cp\u003eConclusions\u003c/p\u003e\n\u003cp\u003eThese findings offer novel insights into the molecular architecture of salinity tolerance in euryhaline fishes, highlighting coordinated transcriptional responses across tissues involved in ion regulation and metabolic adjustment and improving our understanding of how euryhaline fishes cope with extreme and fluctuating osmotic environments. From a conservation perspective, identifying the molecular basis of this physiological plasticity contributes to the management of this highly threatened endemic species and the dynamic coastal habitats it inhabits.\u003c/p\u003e","manuscriptTitle":"Salinity-associated differential gene expression in natural populations of the euryhaline killifish Aphanius iberus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-30 14:58:11","doi":"10.21203/rs.3.rs-9115348/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-04T11:49:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T16:47:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T03:10:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T15:12:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T13:25:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-21T13:27:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289052704770276549852356586189499552973","date":"2026-04-12T04:52:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65575275610075580069661938972863790561","date":"2026-04-10T12:06:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330504710736063576399622169298951282904","date":"2026-04-10T08:01:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199218482277669551906231945435462252259","date":"2026-04-10T04:40:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89681896419370042559470520267417420970","date":"2026-04-01T02:44:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-27T03:43:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-27T03:39:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-23T20:22:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-21T08:21:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2026-03-21T08:17:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e647f97-8070-4550-b739-b76fa1c2317a","owner":[],"postedDate":"March 30th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-04T11:49:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T16:47:17+00:00","index":54,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T03:10:09+00:00","index":53,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T15:12:55+00:00","index":52,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T11:55:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-30 14:58:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9115348","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9115348","identity":"rs-9115348","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}