Dynamic expression and functional transformation of microRNA isoforms induced by osmotic stress in invasive Ciona robusta

Dynamic expression and functional transformation of microRNA isoforms induced by osmotic stress in invasive Ciona robusta | 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 Dynamic expression and functional transformation of microRNA isoforms induced by osmotic stress in invasive Ciona robusta Weijie Yan, Ruiying Fu, Xuena Huang, Aibin Zhan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7993353/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Understanding the mechanisms underlying invasion success is crucial for addressing the rapidly increasing frequency of biological invasions and their escalating ecological and economic impacts worldwide. Phenotypic plasticity plays a crucial role in facilitating invasion success by enabling organisms to respond rapidly to environmental fluctuations. Among molecular regulators of such plasticity, microRNAs (miRNAs) mediate stress adaptation through post-transcriptional gene regulation. Increasing evidence suggests that a single miRNA locus can generate multiple variants (isomiRs), which may diversify regulatory functions and enhance environmental resilience. However, their expression dynamics and functional significance under environmental stress remain largely unexplored during biological invasions. Here, using the highly invasive ascidian Ciona robusta as a model, we examined the dynamic expression and functional divergence of miRNA isoforms in response to osmotic stress. Integrative analysis of miRNAome and transcriptome revealed 10 miRNAs that produced 5’ isomiRs with time-dependent and stress-specific expression patterns. Both canonical miRNAs and their isomiRs targeted overlapping yet distinct gene sets, particularly in pathways related to free amino acid metabolism and ion transport. Functional analysis demonstrated that isomiRs underwent neo-functionalization, sub-functionalization, or mixed functional shifts relative to their canonical counterparts, and in some cases exerted opposite regulatory effects on the same target genes. These results reveal that osmotic stress induces rapid diversification and functional transformation of miRNA isoforms, forming a flexible and dynamic regulatory network. Such plasticity in isomiR regulation likely contributes to enhanced stress tolerance and environmental adaptability, thereby promoting invasion success across diverse, harsh, or rapidly changing environments. Biological invasion epigenetics gene expression miRNA isomiR phenotypic plasticity Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Biological invasions have emerged as a prominent feature of global change in the Anthropocene, simultaneously acting as both a consequence of human-induced transformations and a major driver that actively accelerates further global disruptions [ 1 – 3 ]. Mounting evidence reveals that invasions interact with other global change drivers in complex and nonlinear ways, often leading to unexpected ecological and evolutionary consequences [ 4 , 5 ]. Beyond their well-documented ecological disruptions, their economic impacts are more alarming, exceeding at least US $ 423 billion globally and CNY 400 billion annually in China alone [ 1 , 6 ]. The cost is comparable to those of major natural disasters such as earthquakes, floods, and wildfires, but continue to escalate at an even faster rate [ 1 , 2 ]. The growing frequency and magnitude of invasions highlight the urgent need for an integrated theoretical framework and science-based strategies for their monitoring, prediction, and management, particularly in identifying crucial determinants of invasion success. Invasive species must overcome a sequence of environmental challenges to achieve establishment and invasion success in a new region [ 7 , 8 ]. A critical factor underpinning this success is the ability to respond to both abiotic and biotic stresses throughout the invasion process [ 9 , 10 ]. During early stages such as transport, introduction, and establishment, invasive species often encounter rapidly changing, harsh, and repeated abiotic challenges, including temperature extremes, drought, or salinity, as well as biotic stresses such as competition, predation, and novel mutualistic interactions [ 10 – 12 ]. The capacity to acclimate within a single generation through phenotypic plasticity, or to adjust trait distributions rapidly via epigenetic modifications or swift evolutionary changes, mitigates demographic bottlenecks and increases the likelihood of successful establishment [ 9 , 11 , 13 ]. Of various mechanisms contributing to success during the early stages of invasions, phenotypic plasticity allows individuals to maintain performance across variable environments, effectively “buying time” for further adaptive evolution [ 14 – 16 ]. By enabling populations to persist under a broader range of conditions, sustain growth in disturbed habitats, and expand their geographic range more efficiently, these rapid stress-response mechanisms form a crucial bridge between initial exposure to novel environments and long-term invasion success [ 14 , 16 , 18 ]. Among multiple molecular mechanisms contributing to phenotypic plasticity, microRNAs (miRNAs) are crucial epigenetic regulators that influence the response of invasive species by post-transcriptionally modulating gene expression [ 19 – 21 ]. These small, non-coding RNAs can function independently or in concert with other regulatory elements to fine-tune gene activities, thereby enabling rapid and reversible phenotypic changes essential for response to environmental challenges [ 22 , 23 ]. For example, our former study has confirmed that invasive tunicates can utilize miRNAs to mediate a “stress memory” that enhances the ability to cope with recurrent salinity changes, primarily by regulating genes involved in osmotic homeostasis such as free amino acid metabolism and ion transport [ 21 ]. Similarly, in invasive agricultural weeds, a failure to induce certain miRNAs after herbicide exposure can lead to the successful constitutive expression of detoxification enzymes (e.g., Cytochrome P450s), effectively conferring herbicide resistance and ensuring the weed's survival and subsequent invasion success [ 24 ]. Although the importance of miRNAs in stress responses has been well recognized, comprehensive studies are largely needed to advance from descriptive identification of differentially expressed miRNAs to mechanistic understanding of their regulatory dynamics and evolutionary significance. Traditionally, mature miRNAs were regarded as single, invariant sequences. However, accumulating evidence reveals that a single miRNA locus can generate multiple sequence variants, collectively known as microRNA isoforms (isomiRs) [ 25 , 26 ]. These variants arise through several molecular mechanisms. Imprecise cleavage by the RNase III enzymes Drosha and Dicer can process pri-miRNA and pre-miRNA at alternative positions, producing templated isomiRs with variable 5’ or 3’ ends [ 27 ]. Exonucleolytic trimming by exonucleases further contributes to length heterogeneity by removing nucleotides from miRNA termini [ 28 , 29 ]. In addition, non-templated nucleotide additions catalyzed by terminal nucleotidyl transferases (TUTases), such as TUT4 and TUT7, introduce uridine (uridylation) or adenine (adenylation) residues at the 3’ end, thereby influencing miRNA stability and Argonaute (AGO) loading efficiency [ 30 , 31 ]. Less frequently, RNA editing, such as adenosine-to-inosine conversions mediated by Adenosine Deaminases Acting on RNA (ADAR) enzymes, introduces internal nucleotide substitutions that give rise to non-templated isomiRs with potential regulatory divergence [ 32 ]. Collectively, these mechanisms generate diverse classes of isomiRs, including 5’ variants (alterations at the 5’ end), 3’ variants (alterations at the 3’ end), polymorphic variants (nucleotide substitutions without length changes), and mixed-type variants (combining sequence and length variations). Interestingly, multiple lines of evidence have established that isomiRs are functionally active, being selectively incorporated into AGO complexes and capable of regulating both distinct and overlapping target genes relative to their canonical miRNAs [ 33 , 34 ]. Among the various classes, 5’ isomiRs exert particularly strong functional effects, as 5’ diversification alters the seed region (nucleotides 2–8) and thereby reshapes target specificity. For instance, a 5’ isomiR of miR-9-1 gains the ability to inhibit DNMT3B and NCAM2 while losing regulation of CDH1 compared with the canonical sequence [ 35 ]. Some isomiRs, especially those with minor 3’ or internal variations, share many targets with their canonical counterparts, providing functional redundancy and potentially enhancing overall gene repression [ 33 , 36 ]. Nevertheless, experimental evidence demonstrates that distinct isomiRs can possess unique targetomes and biological roles, as observed for miR-411 [ 37 ], miR-34/449 [ 38 ], and miR-183 [ 39 ]. Beyond target recognition, 5’ variations may also influence miRNA stability and half-life due to structural alterations affecting RNA-induced silencing complex (RISC) interactions [ 40 ]. Although the relative rate of 5’ variants was lower than 3’ variants, 5’ isomiRs could directly affect the seed sequence and weigh more in influencing the targetome, 3’ isomiRs were proved to influence the regulation process on targets, but the mechanisms are still unclear [ 41 ]. As for the polymorphic variants, it was observed that the frequency of single-nucleotide polymorphisms (SNPs) was lower than other genomic regions, for instance, the density of miRNA genes’ SNPs among the total SNPs in human genome was less than 1% [ 42 ]. Given the diverse forms and flexible functions of isomiRs, it is plausible that they play crucial roles in mediating rapid environmental responses during biological invasions. By generating a spectrum of regulatory variants from a single miRNA locus, isomiRs can enhance transcriptomic versatility and fine-tune gene expression dynamics, thereby promoting stress tolerance in invasive populations. Accordingly, we hypothesize that the diversification of isomiR variants facilitates rapid gene regulatory adjustments, further supporting stress responses and environmental resilience during biological invasions. To effectively test this hypothesis, it is essential to select a model invasive species that combines high ecological impact with well-characterized biology. Ciona robusta is a highly invasive ascidian presumably native to the Northwest Pacific and has invaded coastal ecosystems globally, including extreme environments such as the Red Sea [ 43 , 44 ]. This species has caused substantial economic losses through biofouling in aquaculture and has strongly affected invaded ecosystems by reducing species richness and overall biodiversity [ 45 , 46 ]. During its invasion process, C. robusta often encounters rapid and severe environmental fluctuations, such as salinity changes of ~ 15‰ [ 46 ]. As a sessile species, it cannot actively escape these challenges and instead rely on a highly resilient physiological system to maintain homeostasis under rapidly changing, harsh conditions [ 46 ]. Its combination of high invasiveness, exceptional stress tolerance, and a compact, well-characterized genome makes C. robusta an ideal model for exploring the mechanisms driving invasion success [ 46 ]. Using C. robusta as a model system here, we aim to (1) characterize the expression patterns of 5’ isomiRs and their corresponding canonical miRNAs under osmotic stress, (2) identify overlapping and specific targets of 5’ isomiRs and canonical miRNAs, and (3) examine functional differences between the targets of canonical miRNAs and their isomiRs. Our results are expected to shed light on how osmotic fluctuations influence isomiR expression and function, thus providing deeper insights into the dynamic roles of miRNAs under varied environmental conditions during biological invasions. Methods Experimental design, sample collection, and sequencing Adult C. robusta specimens were collected from an aquaculture farm in Dalian, Liaoning Province, China (38°49’19’’N, 121°2’28’’E). To imitate the environmental stress that C. robusta experiences during the invasion process, we exposed the C. robusta individuals to hyper-osmotic stress with the salinity of 40‰, which refers to the extreme environmental conditions in the Red Sea that C. robusta has invaded since 2018 [ 43 , 44 ]. The control salinity was set to 30‰ according to the ambient salinity of the sampling site. After acclimation in the laboratory for three days, C. robusta individuals were subjected to the hyper-salinity stress for 48 h and six replicate samples were collected at 0 h, 24 h and 48 h. The somatic muscle tissues of each individual were collected for subsequent analysis. The total RNA was extracted utilizing Trizol reagent (Ambion, Massachusetts, USA) according to the manufacturer’s instructions, we utilized the Agilent 2100 Bioanalyzer, NanoPhotometer, and Qubit 3.0 Fluorometer to measure the integrity, purity, and quantity of RNAs. Subsequently, the RNA molecules between 18 and 30 nt were enriched, 3’ and 5’ adapters were added and then ligation products underwent reverse transcription, and the PCR products from 140 to 160 bp were used for library construction. The constructed library was sequenced on the Illumina Novaseq 6000 platform using the PE150 strategy. The same samples at 0 h, 24 h and 48 h were used for transcriptome sequencing in parallel. Sequencing libraries were prepared according to the instruction of the NEBNext ® Ultra ™ RNA Library Prep Kit (New England Biolabs, Massachusetts, USA) and then sequenced on the Illumina HiSeqX Ten Sequencing System (Illumina, California, USA) with the PE150 strategy. The transcriptome and small RNA sequencing data have been deposited in National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database with the number PRJNA775866, PRJNA1120970, respectively. miRNA/isomiR identification and expression analysis After sequencing, low-quality reads containing more than one base with a Q -value ≤ 20 or any unknown nucleotides (N) were removed. Adapter sequences were trimmed from the raw reads using Cutadapt v4.5 [ 47 ]. The resulting clean reads were then mapped to the C. robusta reference genome (HT version; http://ghost.zool.kyoto-u.ac.jp/default_ht.html ) using Bowtie2 v2.5.1 [ 48 ] with default parameters. miRDeep2 [ 49 ] was employed for miRNA prediction and quantification under default settings, while isomiR-SEA v1.6 [ 50 ] was used for isomiR identification. Sequences matching reference entries in the miRBase database (version 22) were considered canonical miRNAs. Expression levels of miRNAs and their corresponding isomiRs were normalized from raw read counts to transcripts per million (TPM). The relative expression percentages of isomiRs, canonical miRNAs, and different isomiR types were visualized as boxplots using the online OmicShare tools [ 51 ]. In this study, we focused on 5’ isomiRs because modifications at the 5’ end alter the seed region, which is critical for target recognition and thus can fundamentally reshape the regulatory network. Compared with 3’ or internal variants that mainly affect stability or processing efficiency, 5’ variants have the greatest potential to drive functional diversification and adaptive gene regulation under environmental stress. Target prediction and functional analysis The target prediction of miRNAs and their corresponding isomiRs was performed using two algorithms, RNAhybrid and miRanda, with a binding energy threshold of ≤ -20 kcal/mol. The overlapping results from both algorithms were considered true targets to minimize false positives for subsequent analyses [ 52 , 53 ]. To further compare the functional profiles of predicted targets between miRNAs and isomiRs, we focused on genes involved in free amino acid (FAA) metabolism and biogenesis, water transport, and ion transport, based on candidate gene lists compiled from previous studies [ 54 – 57 ]. Only differentially expressed target genes were retained for downstream analyses, with significance thresholds set at padj 1, determined using the DESeq2 package in R [ 58 ]. The expression correlations between miRNAs/isomiRs and their target genes were evaluated using Pearson correlation coefficients, calculated with the psych package in R [ 59 ]. Results Dynamic responsive patterns of miRNAs and corresponding isomiRs We identified 10 miRNAs (isomiRs) exhibiting 5’ end modifications in the C. robusta miRNAome, including four 5’ a1, one 5’ a2, four 5’ d1, and one 5’ d2 (Table 1 ). Both canonical miRNAs and their isomiRs, along with their relative proportions, displayed dynamic expression patterns in response to high salinity stress, independent of isomiR type. Notably, five miRNA loci (miR-11097e-5p, miR-2024c-5p, miR-11953a-3p, miR-2064b, and miR-10507a-3p) were not expressed under control conditions (Fig. 1 A-E) but were induced following 24 or 48 hours of high salinity exposure. Specifically, isomiRs of miR-11953a-3p, miR-2064b, and miR-10507a-3p were upregulated at 24 hours, whereas their canonical counterparts were induced at 48 hours. In contrast, both canonical and isomiR of miR-11097e-5p and miR-2024c-5p were co-expressed at a given time point, but their relative proportions shifted over time. Opposite to these trends, high salinity stress suppressed both canonical and isomiR expression of miR-5605a-3p (Fig. 1 F). Furthermore, three loci (miR-8356a-5p, miR-8840, and miR-5596b-3p) expressed only canonical miRNAs under control conditions, while their isomiRs emerged after stress exposure with varying proportions at 24 and 48 hours (Fig. 1 G-I). For miR-7093-5p, both canonical and isomiR forms were expressed under control conditions, with their relative abundances changing dynamically under high salinity stress (Fig. 1 J). Table 1 Summary of all isomiRs and canonical miRNAs ID sequence miR-11097e-5p guggacauaguggacaugcacu 5’d1 uggacauaguggacaugcacu miR-2024c-5p auguugcuguugggcaaagacu 5’d1 uguugcuguugggcaaagacu miR-8356a-5p uccuuggacucguuugauug 5’d1 ccuuggacucguuugauug miR-11953a-3p guguguggauaaacggaaauga 5’d1 uguguggauaaacggaaauga miR-2064b cuaaccacugugcuacugcacc 5’d2 aaccacugugcuacugcacc miR-7093-5p caggaugacagacaaaacauc 5’a1 gcaggaugacagacaaaacauc miR-10507a-3p cacagucgaucgagcggaugu 5’a1 ucacagucgaucgagcggaugu miR-5605a-3p gugggggaagaugcgacacc 5’a1 ggugggggaagaugcgacacc miR-8840 cauccggugccuugaacucuu 5’a1 acauccggugccuugaacucuu miR-5596b-3p guggggggagaugggacacc 5’a2 caguggggggagaugggacacc Different targets and functional transformation of miRNAs and corresponding isomiRs To assess whether the dynamic expression of miRNAs and isomiRs influences downstream gene regulation and biological functions, we predicted the target genes of each miRNA and its corresponding isomiR. The resulting target gene pools showed partial overlap between canonical miRNAs and their isomiRs, while each also contained distinct sets of unique targets, with proportions varying among different miRNAs (Fig. 2 ). For example, certain miRNA-isomiR pairs (e.g., miR-5605a-3p and miR-5596b-3p) shared most of their predicted targets (Fig. 2 A, B), whereas others, such as miR-10507a-3p and miR-8840, exhibited minimal overlap, with canonical miRNAs possessing a higher proportion of unique targets (Fig. 2 F, G). These results suggest that isomiRs may lose some of the regulatory targets of their canonical counterparts while simultaneously acquiring novel ones, thereby reshaping the overall regulatory landscape. We focused on the functional divergence between canonical miRNAs and their isomiRs in key osmoregulatory processes, including FAA biogenesis/metabolism and ion transport. Their target repertoires diverged substantially, suggesting a rewiring of regulatory networks. We classified these changes into three models: neo-functionalization, where isomiRs acquire new osmoregulatory functions (e.g., miR-2024c, miR-8840, miR-11953a-3p; Fig. 3 A, D, G); sub-functionalization, where they lose ancestral functions of canonical miRNAs (e.g., miR-10507a-3p; Fig. 3 F); and a mixed model, involving both gain and loss of functions (e.g., miR-2064b, miR-5596b-3p, and miR-5605a-3p; Fig. 3 B, C, E). Specifically, miR-2024c-5p regulated nka , while its 5’d1 isomiR retained nka regulation and additionally targeted kcnip1 / kcnip4 , involved in K⁺ transport (neo-functionalization; Fig. 3 A). In contrast, miR-10507a-5p regulated scn5a , a key gene for Na⁺ transport, and phda2 , involved in alanine and aspartate metabolism, but its isomiR lost these functions (sub-functionalization; Fig. 3 F). Finally, the isomiR of miR-5605a-3p exhibited a mixed model, losing regulation of cyp2u1 while gaining control over slc22a15 (Fig. 3 E). Interestingly, beyond differences in their target repertoires, canonical miRNAs and their isomiRs can exert opposing regulatory effects on the same target. For instance, both the canonical miRNA and isomiR of miR-2024c-5p regulate the nka gene, but the canonical form acts as a positive regulator, whereas the isomiR functions as a negative regulator (Fig. 3 A). Dynamic regulatory networks of miRNA and isomiRs By integrating the dynamic expression patterns (Fig. 1 ) with the distinct target gene repertoires of canonical miRNAs and isomiRs (Figs. 2 – 3 ), we constructed a comprehensive overview illustrating functional shifts and regulatory variations between canonical miRNAs and isomiRs at different time points under high salinity stress (Fig. 4 ). Our results revealed that the generation of miRNA isoforms established a complex osmoregulatory network. Notably, three canonical miRNA-isomiR pairs (miR-2024c-5p, miR-2064b, and miR-5596b-3p) played particularly central roles in this network. Under control conditions, neither the canonical miRNA nor the isomiR of miR-2024c-5p was expressed. The canonical form was induced at 24 and 48 hours, positively regulating Na⁺/K⁺ co-transport functions. In contrast, the isomiR appeared specifically at 48 hours, positively regulating K⁺ transport while negatively affecting Na⁺/K⁺ co-transport and FAA biogenesis (Fig. 4 ). For miR-2064b, the isomiR was induced first at 24 hours, positively regulating glutathione and selenoamino acid metabolism. The corresponding canonical miRNA was induced later, at 48 hours, positively regulating K⁺ transport and selenoamino acid metabolism, while negatively affecting tryptophan metabolism. For miR-5596b-3p, the canonical miRNA was expressed only under control conditions, negatively regulating K⁺ transport, organic ion transport, tryptophan metabolism, and glutathione metabolism. Under high salinity stress at 48 hours, regulation shifted to the isomiR, which additionally negatively regulated Cl⁻ transport while positively influencing D-glutamine and D-glutamate metabolism. These dynamic expression patterns and functional shifts between canonical miRNAs and their isomiRs may be crucial for invasive ascidians to rapidly adapt to acute changes in osmotic stress during high salinity exposure. Discussion The success of biological invasions depends on the rapid and effective adjustment to the fluctuating and often harsh conditions of novel environments, particularly during early invasion stages when propagule numbers are low. Using the model invasive ascidian C. robusta in this study, we found that salinity challenges triggered timely and dynamic expression of isomiRs, which often diverged from their canonical miRNA counterparts, with their relative abundances changing in a time-dependent manner under stress (Figs. 1 & 2 ). Importantly, both isomiRs and canonical miRNAs regulated overlapping as well as distinct sets of target genes, indicating that miRNA isoform diversification generated functional variation (Figs. 3 & 4 ). These functional shifts included the loss, gain, modification, or addition of regulatory roles in key osmoregulatory processes, such as free amino acid metabolism and ion transport, which were categorized as neo-functionalization, sub-functionalization, or a mixed model (Fig. 4 ). Interestingly, canonical miRNAs and their corresponding isomiRs can exert opposing regulatory effects on the same target gene (Fig. 3 ). Together, our results provide evidence supporting our hypothesis that 5’ isomiR diversification contributes to adaptive plasticity by enabling dynamic reconfiguration of gene regulatory networks. The observed neo-functionalization, sub-functionalization, and opposing regulatory effects highlight that 5’ end modifications generate functional flexibility essential for stress tolerance during biological invasions. Dynamic responsive expression of miRNA isoforms Whether isomiRs are expressed similarly to their corresponding canonical miRNAs has long been debated [ 33 , 60 ]. Some studies have shown that isomiRs exhibit expression patterns comparable to their canonical counterparts across multiple human tissues [ 33 ]. In contrast, other evidence indicates that isomiRs can display distinct expression profiles. For example, during the developmental stages of Caenorhabditis elegans , several isomiR/canonical miRNA pairs showed divergent temporal patterns: canonical miR-50-5p peaked in embryos, whereas its isomiRs reached maximal expression at the L2/L3 stages and in young adults [ 60 ]. Such temporal variation suggests a connection between isomiR regulation and the organism’s life cycle and has been proposed as a strategy to fine-tune gene expression during development. Similarly, stress conditions can induce differential responses between canonical miRNAs and their isomiRs. For example, in human vascular fibroblasts and venous tissues exposed to acute ischemia, canonical miR-411 expression increased, whereas its 5’ isomiR exhibited a rapid decrease. Notably, the 5’ isomiR targeted different transcripts than the canonical sequence, leading to distinct functional outcomes such as reduced cell migration and impaired wound healing [ 37 ]. In the present study, we observed that almost all isomiRs displayed expression patterns distinct from their canonical sequences, except for the isomiR of miR-5605a-3p, which mirrored the canonical expression at specific hyper-salinity stages or between control and stress groups (Fig. 1 ). The observed functional divergence across different studies underscores the biological significance of differential expression patterns between canonical miRNAs and their isomiRs, further highlighting the diverse and potentially specialized roles of isomiRs in stress responses. Traditionally, 5’ isomiRs are considered to have lower expression than canonical miRNAs, and some analytical algorithms define canonical miRNAs as the most highly expressed sequences [ 60 ]. However, these general trends are not absolute, and notable exceptions have been reported. For instance, the 5’ isomiR of miR-9 was highly expressed in low-grade glioma biopsies [ 61 ], and in C. elegans , certain 5’ isomiRs were equally or more abundant than their canonical counterparts across developmental stages [ 60 ]. Indeed, the classification of sequences as canonical miRNAs or isomiRs represents a technical distinction that, in many contexts, does not substantially affect biological interpretation. The observed differences in abundance between 5’ isomiRs and their canonical miRNAs suggest potential functional relevance. Higher expression of a 5’ isomiR may indicate that it plays a more prominent regulatory role under certain conditions or in specific tissues. Similarly, dynamic changes in abundance across varied scenarios likely reflect context-dependent modulation of miRNA function, highlighting that isomiRs are not merely minor variants but can contribute significantly to gene regulation. The functional significance of 5’ isomiRs arises from their ability to modify the miRNA seed sequence, a critical determinant of target recognition. A single-nucleotide variation or length alteration at the 5’ end shifts the seed sequence, fundamentally changing the target repertoire and enabling the isomiR to regulate distinct metabolic and developmental pathways [ 62 ]. This mechanism provides a plausible explanation for the functional diversification of isomiRs under stress conditions. Stress conditions can modulate this processing machinery. Drosha activity, for instance, is regulated by phosphorylation via the p38/MAPK pathway under heat or oxidative stress, which decreases its binding affinity to DGCR8 and alters pri-miRNA processing efficiency [ 63 ]. This provides a molecular basis for the dynamic changes in isomiR dominance observed under hyper-salinity stress. Consistently, our previous work demonstrated that Drosha expression levels themselves change under salinity stress [ 21 ], supporting that osmotic stress modulates Drosha activity, leading to the observed dynamic cleavage patterns and relative expression levels of isomiRs. Target diversification and functional transformation The shifted seed region fundamentally redefines the microRNA’s target profile, allowing 5'-isomiRs to function across a dual spectrum: acting either as cooperative supporters of the canonical microRNA or as divergent competitors to expand the overall functional repertoire of the regulatory locus. In a cooperative model, canonical microRNAs and their isomiRs work together to reinforce specific biological pathways. This functional redundancy may provide regulatory robustness and reduce off-target effects [ 33 ]. For instance, we found in this study that canonical miR-2064b and its isomiR co-regulating the same target, prmt7 , and miR-2024c-5p and its isomiR co-regulating nka (Fig. 3 ). More complex cooperation involves isomiRs regulating different targets that ultimately converge on the same crucial cellular function. This is exemplified by human miR-142-3p, where co-expressed 5’ isomiRs recognize distinct sets of binding sites, yet both modulate multiple regulators of the actin cytoskeleton (such as p190RhoGap and CFL2 ), essential for megakaryocyte maturation and function [ 64 ]. Similarly, in breast cancer, while the canonical miR-140-3p controls cell stemness, its 5’ isoform focuses on inducing cell cycle arrest and inhibiting migration, demonstrating a collaborative tumor-suppressive strategy [ 65 ]. Conversely, 5’ isomiRs are potent drivers of divergence and neofunctionalization through the acquisition of novel targets and the loss of canonical ones. This functional transformation results from the altered seed sequence giving the isomiR an entirely new targetome. For example, previous studies detected that the 5’ isomiR of miR-9-1, which gained the capacity to repress DNMT3B and NCAM2 while simultaneously losing its ability to inhibit the canonical target CDH1 [ 35 ]. Another 5’ isoform of miR-140-3p gained the ability to inhibit the novel targets including COL4A1 , ITGA6 , and MARCKSL1 [ 65 ]. Furthermore, the relationship can become antagonistic: in human vascular cells subjected to ischemia, the canonical miR-411 is upregulated and regulates the pro-angiogenic TGFB, while the 5’ isomiR-411 level rapidly decreases, controlling exclusive targets (F3 and ANGPT1) and leading to opposite effects on cell migration [ 37 ]. Limitations and future perspectives Although this study provides evidence for the dynamic and functional divergence of isomiRs in stress responses, several limitations warrant further investigations in the future. A major technical constraint is the dependence on computational target prediction algorithms to infer regulatory divergence between canonical miRNAs and their corresponding isomiRs. Despite the fact that this approach is commonly adopted in many studies and these tools provide valuable insights into potential target relationships, their predictions remain inferential rather than experimentally confirmed. Furthermore, while the study reveals significant correlations among hyper-salinity stress, isomiR expression, and the regulation of osmoregulatory genes, these relationships are correlative rather than causal. Demonstrating causality will be essential to confirm that isomiR modulation is not merely a byproduct of stress but a mechanistic driver of phenotypic plasticity. Consequently, future work should integrate experimental validation approaches, such as luciferase reporter assays, RNA immunoprecipitation (RIP) or CLIP-based techniques, and loss- or gain-of-function analyses, to confirm predicted targets and elucidate the mechanistic basis of isomiR-mediated regulatory divergence. Another important direction for future research involves elucidating the molecular mechanisms underlying isomiR biogenesis and decay under stress conditions. The present study captured the downstream outcome (i.e., a shift in the relative abundance of specific isomiRs) but did not address the upstream regulatory processes driving this shift. The potential roles of stress-induced post-transcriptional modifications or altered enzymatic activities (e.g., those of Drosha, Dicer, or nucleotidyl transferases) remain largely unknown. As a result, the mechanistic pathways linking environmental stress cues to isomiR generation and maturation remain unvalidated. Clarifying these pathways will be essential to understanding how cellular stress responses contribute to the structural diversification and functional complexity of miRNA in response to varied stresses. Given that biological invasions are escalating in both scale and frequency globally, understanding the mechanisms underpinning invasion success is crucial for effective ecological and economic management. miRNAs and their diverse isomiRs play a pivotal role in this context, as they provide a rapid and flexible layer of post-transcriptional regulation that underlies (adaptive) phenotypic plasticity and environmental tolerance, traits central to the establishment and persistence of invasive species. Accordingly, future research should aim to integrate emerging molecular insights from isomiR-mediated regulation into a broader ecological framework, advancing from the observation of gene regulatory changes to experimental validation of how these molecular processes directly enhance fitness-related traits such as phenotypic plasticity and transgenerational resilience. Such integration will be critical for bridging the current divide between molecular biology and invasion ecology. Conclusions Using the highly invasive ascidian model species, C. robusta , the current study demonstrates that the flexibility of miRNA-based gene expression regulation is significantly enhanced by the dynamic expression and functional divergence of their isoforms, isomiRs. Exposure to hyper-salinity stress triggered a time-dependent and dynamic expression of isomiRs, which often followed a pattern distinct from their canonical miRNA counterparts. This functional diversification was critical, as isomiRs and canonical miRNAs regulated overlapping and unique sets of target genes, leading to a ‘rewiring’ of the regulatory network. The observed changes in the target repertoire resulted in the functional transformation of the regulatory roles of the miRNA loci, categorized into neo-functionalization (gain of new functions), sub-functionalization (loss of ancestral functions), or a mixed model (both gain and loss) in key osmoregulatory processes such as FAA metabolism and ion transport. Intriguingly, in some cases, a canonical miRNA and its corresponding isomiR were found to exert opposing regulatory effects on the same target gene. This dual capacity for both cooperative and divergent regulation, primarily driven by 5’ isomiRs that alter the critical seed region, establishes a more flexible and intricate regulatory network. This mechanism is highly plausible for enhancing stress tolerance and environmental resilience in invasive populations, thereby promoting their success in novel and fluctuating environments. Declarations Authors’ contributions A.Z. conceived and designed the study; W.Y., R.F., and X.H. performed the experiments and collected the data. W.Y., R.F., and X.H. conducted the bioinformatics analyses. W.Y. interpreted the results with input from all co-authors. W.Y. drafted the manuscript. R.F., X.H., and A.Z. contributed to manuscript revisions and provided critical feedback. A.Z. and X.H. supervised the project and acquired funding. All authors read and approved the final version of the manuscript. Funding This work was funded by the National Natural Science Foundation of China (Nos. 32471740, 32561143021, and 32101352) Data availability All raw high-throughput mRNA and DNA methylation sequencing data were deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under accession number PRJNA775866, and the raw miRNA-seq data was deposited in SRA database under the number PRJNA1120970. Ethics This work did not require ethical approval from a human subject or animal welfare committee. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Declaration of AI use We have not used AI-assisted technologies in creating this article. References Diagne C, Leroy B, Vaissière A-C, Gozlan RE, Roiz D, Jarić I, Salles J-M, Bradshaw CJ, Courchamp F. High and rising economic costs of biological invasions worldwide. 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BMC Genom. 2016; 17: 566. https://doi.org/10.1186/s12864-016-2869-x Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Feb, 2026 Reviews received at journal 10 Feb, 2026 Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 21 Jan, 2026 Reviewers agreed at journal 26 Dec, 2025 Reviewers invited by journal 02 Dec, 2025 Editor invited by journal 03 Nov, 2025 Editor assigned by journal 31 Oct, 2025 Submission checks completed at journal 31 Oct, 2025 First submitted to journal 30 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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09:22:53","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74928,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/eb0fc5b74ff94cbe572f144b.png"},{"id":97665757,"identity":"34d01454-3c45-4df6-b491-c76cfc80abd7","added_by":"auto","created_at":"2025-12-08 09:19:32","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":183048,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/35050bec58f052f417a3bc1c.png"},{"id":97395970,"identity":"ab184946-4a87-459f-82ea-776fb9b99080","added_by":"auto","created_at":"2025-12-04 00:14:24","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":190746,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/572819f9f94d02e87a81ce0d.png"},{"id":97395967,"identity":"f92153bc-f297-4325-950d-bb66cb6400c7","added_by":"auto","created_at":"2025-12-04 00:14:24","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":77655,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/dd8f3e1e26946c06bb30bf4e.png"},{"id":97665438,"identity":"ee38f6f1-eb58-4413-814d-93eb0b2ea9d3","added_by":"auto","created_at":"2025-12-08 09:18:25","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":160045,"visible":true,"origin":"","legend":"","description":"","filename":"46b5934790f44dcd95507f7752a90d7d1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/7e6df63ec68e6a6ed2d64641.xml"},{"id":97395968,"identity":"da47b1e0-70c5-488c-bfeb-39fc0acfcc10","added_by":"auto","created_at":"2025-12-04 00:14:24","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171037,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/68a9e8cacfea1e715db18234.html"},{"id":97665449,"identity":"63bd3ffe-17f0-40df-a572-39216a5d0eb8","added_by":"auto","created_at":"2025-12-08 09:18:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":441353,"visible":true,"origin":"","legend":"\u003cp\u003eExpression patterns and relative percentages of canonical miRNAs and their corresponding 5′ isomiRs. Expression levels were normalized to Transcripts Per Million (TPM), and the proportions of canonical miRNAs and isomiRs are shown in yellow and red, respectively.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/299f4ca85a69d9c72ced9fa7.jpg"},{"id":97395955,"identity":"8613e708-4ba1-4342-965f-62ff94689afb","added_by":"auto","created_at":"2025-12-04 00:14:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":755246,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram of predicted targets for miRNAs and isomiRs. Targets of canonical miRNAs, isomiRs, and their overlap are indicated in red, green, and yellow, respectively.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/15020f407c65963f63e06031.jpg"},{"id":97395957,"identity":"5f132f6c-6dd6-4374-8fcf-cf8035831aa8","added_by":"auto","created_at":"2025-12-04 00:14:24","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1713409,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic canonical miRNA/isomiR-target network during osmotic stress. Canonical miRNAs and isomiRs are labeled in pink and purple, respectively; their targets are represented by pentagrams (canonical miRNAs) and circles (isomiRs). Functions regulated by miRNAs are annotated at the corresponding sampling points.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/93fc0a6cc055b26af742776f.jpg"},{"id":97665385,"identity":"aa5aafc5-6e71-4098-b9e7-29d77b5e525f","added_by":"auto","created_at":"2025-12-08 09:18:10","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":593904,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic patterns of canonical miRNA/isomiR targets involved in free amino acid metabolism/biogenesis (FAA), water transport, and ion transport at different sampling points. Eleven functional pathways related to FAA metabolism/biogenesis and ion transport are color-coded. Targets of canonical miRNAs and isomiRs are represented by pentagrams and circles, with red and blue indicating positive and negative regulation, respectively.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/bdd3f87e2cddd5741573a340.jpg"},{"id":97677425,"identity":"fcf6262f-9697-479d-bad7-783ad47689ad","added_by":"auto","created_at":"2025-12-08 09:53:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4239847,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7993353/v1/6851ec9e-6649-4a37-b81e-d906d9ac13d0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamic expression and functional transformation of microRNA isoforms induced by osmotic stress in invasive Ciona robusta","fulltext":[{"header":"Background","content":"\u003cp\u003eBiological invasions have emerged as a prominent feature of global change in the Anthropocene, simultaneously acting as both a consequence of human-induced transformations and a major driver that actively accelerates further global disruptions [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Mounting evidence reveals that invasions interact with other global change drivers in complex and nonlinear ways, often leading to unexpected ecological and evolutionary consequences [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Beyond their well-documented ecological disruptions, their economic impacts are more alarming, exceeding at least US\u003cspan\u003e$\u003c/span\u003e423\u0026nbsp;billion globally and CNY 400\u0026nbsp;billion annually in China alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The cost is comparable to those of major natural disasters such as earthquakes, floods, and wildfires, but continue to escalate at an even faster rate [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The growing frequency and magnitude of invasions highlight the urgent need for an integrated theoretical framework and science-based strategies for their monitoring, prediction, and management, particularly in identifying crucial determinants of invasion success.\u003c/p\u003e\u003cp\u003eInvasive species must overcome a sequence of environmental challenges to achieve establishment and invasion success in a new region [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A critical factor underpinning this success is the ability to respond to both abiotic and biotic stresses throughout the invasion process [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. During early stages such as transport, introduction, and establishment, invasive species often encounter rapidly changing, harsh, and repeated abiotic challenges, including temperature extremes, drought, or salinity, as well as biotic stresses such as competition, predation, and novel mutualistic interactions [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The capacity to acclimate within a single generation through phenotypic plasticity, or to adjust trait distributions rapidly \u003cem\u003evia\u003c/em\u003e epigenetic modifications or swift evolutionary changes, mitigates demographic bottlenecks and increases the likelihood of successful establishment [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Of various mechanisms contributing to success during the early stages of invasions, phenotypic plasticity allows individuals to maintain performance across variable environments, effectively \u0026ldquo;buying time\u0026rdquo; for further adaptive evolution [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. By enabling populations to persist under a broader range of conditions, sustain growth in disturbed habitats, and expand their geographic range more efficiently, these rapid stress-response mechanisms form a crucial bridge between initial exposure to novel environments and long-term invasion success [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAmong multiple molecular mechanisms contributing to phenotypic plasticity, microRNAs (miRNAs) are crucial epigenetic regulators that influence the response of invasive species by post-transcriptionally modulating gene expression [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These small, non-coding RNAs can function independently or in concert with other regulatory elements to fine-tune gene activities, thereby enabling rapid and reversible phenotypic changes essential for response to environmental challenges [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For example, our former study has confirmed that invasive tunicates can utilize miRNAs to mediate a \u0026ldquo;stress memory\u0026rdquo; that enhances the ability to cope with recurrent salinity changes, primarily by regulating genes involved in osmotic homeostasis such as free amino acid metabolism and ion transport [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similarly, in invasive agricultural weeds, a failure to induce certain miRNAs after herbicide exposure can lead to the successful constitutive expression of detoxification enzymes (e.g., Cytochrome P450s), effectively conferring herbicide resistance and ensuring the weed's survival and subsequent invasion success [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Although the importance of miRNAs in stress responses has been well recognized, comprehensive studies are largely needed to advance from descriptive identification of differentially expressed miRNAs to mechanistic understanding of their regulatory dynamics and evolutionary significance.\u003c/p\u003e\u003cp\u003eTraditionally, mature miRNAs were regarded as single, invariant sequences. However, accumulating evidence reveals that a single miRNA locus can generate multiple sequence variants, collectively known as microRNA isoforms (isomiRs) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These variants arise through several molecular mechanisms. Imprecise cleavage by the RNase III enzymes Drosha and Dicer can process pri-miRNA and pre-miRNA at alternative positions, producing templated isomiRs with variable 5\u0026rsquo; or 3\u0026rsquo; ends [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Exonucleolytic trimming by exonucleases further contributes to length heterogeneity by removing nucleotides from miRNA termini [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In addition, non-templated nucleotide additions catalyzed by terminal nucleotidyl transferases (TUTases), such as TUT4 and TUT7, introduce uridine (uridylation) or adenine (adenylation) residues at the 3\u0026rsquo; end, thereby influencing miRNA stability and Argonaute (AGO) loading efficiency [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Less frequently, RNA editing, such as adenosine-to-inosine conversions mediated by Adenosine Deaminases Acting on RNA (ADAR) enzymes, introduces internal nucleotide substitutions that give rise to non-templated isomiRs with potential regulatory divergence [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Collectively, these mechanisms generate diverse classes of isomiRs, including 5\u0026rsquo; variants (alterations at the 5\u0026rsquo; end), 3\u0026rsquo; variants (alterations at the 3\u0026rsquo; end), polymorphic variants (nucleotide substitutions without length changes), and mixed-type variants (combining sequence and length variations).\u003c/p\u003e\u003cp\u003eInterestingly, multiple lines of evidence have established that isomiRs are functionally active, being selectively incorporated into AGO complexes and capable of regulating both distinct and overlapping target genes relative to their canonical miRNAs [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Among the various classes, 5\u0026rsquo; isomiRs exert particularly strong functional effects, as 5\u0026rsquo; diversification alters the seed region (nucleotides 2\u0026ndash;8) and thereby reshapes target specificity. For instance, a 5\u0026rsquo; isomiR of miR-9-1 gains the ability to inhibit \u003cem\u003eDNMT3B\u003c/em\u003e and \u003cem\u003eNCAM2\u003c/em\u003e while losing regulation of \u003cem\u003eCDH1\u003c/em\u003e compared with the canonical sequence [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Some isomiRs, especially those with minor 3\u0026rsquo; or internal variations, share many targets with their canonical counterparts, providing functional redundancy and potentially enhancing overall gene repression [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Nevertheless, experimental evidence demonstrates that distinct isomiRs can possess unique targetomes and biological roles, as observed for miR-411 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], miR-34/449 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and miR-183 [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Beyond target recognition, 5\u0026rsquo; variations may also influence miRNA stability and half-life due to structural alterations affecting RNA-induced silencing complex (RISC) interactions [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Although the relative rate of 5\u0026rsquo; variants was lower than 3\u0026rsquo; variants, 5\u0026rsquo; isomiRs could directly affect the seed sequence and weigh more in influencing the targetome, 3\u0026rsquo; isomiRs were proved to influence the regulation process on targets, but the mechanisms are still unclear [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. As for the polymorphic variants, it was observed that the frequency of single-nucleotide polymorphisms (SNPs) was lower than other genomic regions, for instance, the density of miRNA genes\u0026rsquo; SNPs among the total SNPs in human genome was less than 1% [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven the diverse forms and flexible functions of isomiRs, it is plausible that they play crucial roles in mediating rapid environmental responses during biological invasions. By generating a spectrum of regulatory variants from a single miRNA locus, isomiRs can enhance transcriptomic versatility and fine-tune gene expression dynamics, thereby promoting stress tolerance in invasive populations. Accordingly, we hypothesize that the diversification of isomiR variants facilitates rapid gene regulatory adjustments, further supporting stress responses and environmental resilience during biological invasions. To effectively test this hypothesis, it is essential to select a model invasive species that combines high ecological impact with well-characterized biology.\u003c/p\u003e\u003cp\u003e\u003cem\u003eCiona robusta\u003c/em\u003e is a highly invasive ascidian presumably native to the Northwest Pacific and has invaded coastal ecosystems globally, including extreme environments such as the Red Sea [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This species has caused substantial economic losses through biofouling in aquaculture and has strongly affected invaded ecosystems by reducing species richness and overall biodiversity [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. During its invasion process, \u003cem\u003eC. robusta\u003c/em\u003e often encounters rapid and severe environmental fluctuations, such as salinity changes of ~\u0026thinsp;15\u0026permil; [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. As a sessile species, it cannot actively escape these challenges and instead rely on a highly resilient physiological system to maintain homeostasis under rapidly changing, harsh conditions [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Its combination of high invasiveness, exceptional stress tolerance, and a compact, well-characterized genome makes \u003cem\u003eC. robusta\u003c/em\u003e an ideal model for exploring the mechanisms driving invasion success [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eUsing \u003cem\u003eC. robusta\u003c/em\u003e as a model system here, we aim to (1) characterize the expression patterns of 5\u0026rsquo; isomiRs and their corresponding canonical miRNAs under osmotic stress, (2) identify overlapping and specific targets of 5\u0026rsquo; isomiRs and canonical miRNAs, and (3) examine functional differences between the targets of canonical miRNAs and their isomiRs. Our results are expected to shed light on how osmotic fluctuations influence isomiR expression and function, thus providing deeper insights into the dynamic roles of miRNAs under varied environmental conditions during biological invasions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExperimental design, sample collection, and sequencing\u003c/h2\u003e\u003cp\u003eAdult \u003cem\u003eC. robusta\u003c/em\u003e specimens were collected from an aquaculture farm in Dalian, Liaoning Province, China (38\u0026deg;49\u0026rsquo;19\u0026rsquo;\u0026rsquo;N, 121\u0026deg;2\u0026rsquo;28\u0026rsquo;\u0026rsquo;E). To imitate the environmental stress that \u003cem\u003eC. robusta\u003c/em\u003e experiences during the invasion process, we exposed the \u003cem\u003eC. robusta\u003c/em\u003e individuals to hyper-osmotic stress with the salinity of 40\u0026permil;, which refers to the extreme environmental conditions in the Red Sea that \u003cem\u003eC. robusta\u003c/em\u003e has invaded since 2018 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The control salinity was set to 30\u0026permil; according to the ambient salinity of the sampling site. After acclimation in the laboratory for three days, \u003cem\u003eC. robusta\u003c/em\u003e individuals were subjected to the hyper-salinity stress for 48 h and six replicate samples were collected at 0 h, 24 h and 48 h. The somatic muscle tissues of each individual were collected for subsequent analysis. The total RNA was extracted utilizing Trizol reagent (Ambion, Massachusetts, USA) according to the manufacturer\u0026rsquo;s instructions, we utilized the Agilent 2100 Bioanalyzer, NanoPhotometer, and Qubit 3.0 Fluorometer to measure the integrity, purity, and quantity of RNAs. Subsequently, the RNA molecules between 18 and 30 nt were enriched, 3\u0026rsquo; and 5\u0026rsquo; adapters were added and then ligation products underwent reverse transcription, and the PCR products from 140 to 160 bp were used for library construction. The constructed library was sequenced on the Illumina Novaseq 6000 platform using the PE150 strategy. The same samples at 0 h, 24 h and 48 h were used for transcriptome sequencing in parallel. Sequencing libraries were prepared according to the instruction of the NEBNext\u003csup\u003e\u0026reg;\u003c/sup\u003e Ultra\u003csup\u003e\u0026trade;\u003c/sup\u003e RNA Library Prep Kit (New England Biolabs, Massachusetts, USA) and then sequenced on the Illumina HiSeqX Ten Sequencing System (Illumina, California, USA) with the PE150 strategy. The transcriptome and small RNA sequencing data have been deposited in National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database with the number PRJNA775866, PRJNA1120970, respectively.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003emiRNA/isomiR identification and expression analysis\u003c/h3\u003e\n\u003cp\u003eAfter sequencing, low-quality reads containing more than one base with a \u003cem\u003eQ\u003c/em\u003e-value\u0026thinsp;\u0026le;\u0026thinsp;20 or any unknown nucleotides (N) were removed. Adapter sequences were trimmed from the raw reads using Cutadapt v4.5 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The resulting clean reads were then mapped to the \u003cem\u003eC. robusta\u003c/em\u003e reference genome (HT version; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghost.zool.kyoto-u.ac.jp/default_ht.html\u003c/span\u003e\u003cspan address=\"http://ghost.zool.kyoto-u.ac.jp/default_ht.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using Bowtie2 v2.5.1 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] with default parameters. miRDeep2 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] was employed for miRNA prediction and quantification under default settings, while isomiR-SEA v1.6 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] was used for isomiR identification. Sequences matching reference entries in the miRBase database (version 22) were considered canonical miRNAs. Expression levels of miRNAs and their corresponding isomiRs were normalized from raw read counts to transcripts per million (TPM). The relative expression percentages of isomiRs, canonical miRNAs, and different isomiR types were visualized as boxplots using the online OmicShare tools [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, we focused on 5\u0026rsquo; isomiRs because modifications at the 5\u0026rsquo; end alter the seed region, which is critical for target recognition and thus can fundamentally reshape the regulatory network. Compared with 3\u0026rsquo; or internal variants that mainly affect stability or processing efficiency, 5\u0026rsquo; variants have the greatest potential to drive functional diversification and adaptive gene regulation under environmental stress.\u003c/p\u003e\n\u003ch3\u003eTarget prediction and functional analysis\u003c/h3\u003e\n\u003cp\u003eThe target prediction of miRNAs and their corresponding isomiRs was performed using two algorithms, RNAhybrid and miRanda, with a binding energy threshold of \u0026le; -20 kcal/mol. The overlapping results from both algorithms were considered true targets to minimize false positives for subsequent analyses [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. To further compare the functional profiles of predicted targets between miRNAs and isomiRs, we focused on genes involved in free amino acid (FAA) metabolism and biogenesis, water transport, and ion transport, based on candidate gene lists compiled from previous studies [\u003cspan additionalcitationids=\"CR55 CR56\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Only differentially expressed target genes were retained for downstream analyses, with significance thresholds set at \u003cem\u003epadj\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log₂ fold change| \u0026gt;1, determined using the DESeq2 package in R [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The expression correlations between miRNAs/isomiRs and their target genes were evaluated using Pearson correlation coefficients, calculated with the psych package in R [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eDynamic responsive patterns of miRNAs and corresponding isomiRs\u003c/h2\u003e\u003cp\u003eWe identified 10 miRNAs (isomiRs) exhibiting 5\u0026rsquo; end modifications in the \u003cem\u003eC. robusta\u003c/em\u003e miRNAome, including four 5\u0026rsquo; a1, one 5\u0026rsquo; a2, four 5\u0026rsquo; d1, and one 5\u0026rsquo; d2 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Both canonical miRNAs and their isomiRs, along with their relative proportions, displayed dynamic expression patterns in response to high salinity stress, independent of isomiR type. Notably, five miRNA loci (miR-11097e-5p, miR-2024c-5p, miR-11953a-3p, miR-2064b, and miR-10507a-3p) were not expressed under control conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-E) but were induced following 24 or 48 hours of high salinity exposure. Specifically, isomiRs of miR-11953a-3p, miR-2064b, and miR-10507a-3p were upregulated at 24 hours, whereas their canonical counterparts were induced at 48 hours. In contrast, both canonical and isomiR of miR-11097e-5p and miR-2024c-5p were co-expressed at a given time point, but their relative proportions shifted over time. Opposite to these trends, high salinity stress suppressed both canonical and isomiR expression of miR-5605a-3p (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Furthermore, three loci (miR-8356a-5p, miR-8840, and miR-5596b-3p) expressed only canonical miRNAs under control conditions, while their isomiRs emerged after stress exposure with varying proportions at 24 and 48 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG-I). For miR-7093-5p, both canonical and isomiR forms were expressed under control conditions, with their relative abundances changing dynamically under high salinity stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of all isomiRs and canonical miRNAs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003esequence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-11097e-5p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eguggacauaguggacaugcacu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;d1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003euggacauaguggacaugcacu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-2024c-5p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eauguugcuguugggcaaagacu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;d1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003euguugcuguugggcaaagacu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-8356a-5p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003euccuuggacucguuugauug\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;d1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eccuuggacucguuugauug\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-11953a-3p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eguguguggauaaacggaaauga\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;d1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003euguguggauaaacggaaauga\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-2064b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecuaaccacugugcuacugcacc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;d2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eaaccacugugcuacugcacc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-7093-5p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecaggaugacagacaaaacauc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;a1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egcaggaugacagacaaaacauc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-10507a-3p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecacagucgaucgagcggaugu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;a1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eucacagucgaucgagcggaugu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-5605a-3p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egugggggaagaugcgacacc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;a1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eggugggggaagaugcgacacc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-8840\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecauccggugccuugaacucuu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;a1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eacauccggugccuugaacucuu\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emiR-5596b-3p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eguggggggagaugggacacc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;a2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecaguggggggagaugggacacc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDifferent targets and functional transformation of miRNAs and corresponding isomiRs\u003c/h2\u003e\u003cp\u003eTo assess whether the dynamic expression of miRNAs and isomiRs influences downstream gene regulation and biological functions, we predicted the target genes of each miRNA and its corresponding isomiR. The resulting target gene pools showed partial overlap between canonical miRNAs and their isomiRs, while each also contained distinct sets of unique targets, with proportions varying among different miRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For example, certain miRNA-isomiR pairs (e.g., miR-5605a-3p and miR-5596b-3p) shared most of their predicted targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B), whereas others, such as miR-10507a-3p and miR-8840, exhibited minimal overlap, with canonical miRNAs possessing a higher proportion of unique targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF, G). These results suggest that isomiRs may lose some of the regulatory targets of their canonical counterparts while simultaneously acquiring novel ones, thereby reshaping the overall regulatory landscape.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe focused on the functional divergence between canonical miRNAs and their isomiRs in key osmoregulatory processes, including FAA biogenesis/metabolism and ion transport. Their target repertoires diverged substantially, suggesting a rewiring of regulatory networks. We classified these changes into three models: neo-functionalization, where isomiRs acquire new osmoregulatory functions (e.g., miR-2024c, miR-8840, miR-11953a-3p; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, D, G); sub-functionalization, where they lose ancestral functions of canonical miRNAs (e.g., miR-10507a-3p; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF); and a mixed model, involving both gain and loss of functions (e.g., miR-2064b, miR-5596b-3p, and miR-5605a-3p; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C, E). Specifically, miR-2024c-5p regulated \u003cem\u003enka\u003c/em\u003e, while its 5\u0026rsquo;d1 isomiR retained \u003cem\u003enka\u003c/em\u003e regulation and additionally targeted \u003cem\u003ekcnip1\u003c/em\u003e/\u003cem\u003ekcnip4\u003c/em\u003e, involved in K⁺ transport (neo-functionalization; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In contrast, miR-10507a-5p regulated \u003cem\u003escn5a\u003c/em\u003e, a key gene for Na⁺ transport, and \u003cem\u003ephda2\u003c/em\u003e, involved in alanine and aspartate metabolism, but its isomiR lost these functions (sub-functionalization; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Finally, the isomiR of miR-5605a-3p exhibited a mixed model, losing regulation of \u003cem\u003ecyp2u1\u003c/em\u003e while gaining control over \u003cem\u003eslc22a15\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eInterestingly, beyond differences in their target repertoires, canonical miRNAs and their isomiRs can exert opposing regulatory effects on the same target. For instance, both the canonical miRNA and isomiR of miR-2024c-5p regulate the \u003cem\u003enka\u003c/em\u003e gene, but the canonical form acts as a positive regulator, whereas the isomiR functions as a negative regulator (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDynamic regulatory networks of miRNA and isomiRs\u003c/h3\u003e\n\u003cp\u003eBy integrating the dynamic expression patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) with the distinct target gene repertoires of canonical miRNAs and isomiRs (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), we constructed a comprehensive overview illustrating functional shifts and regulatory variations between canonical miRNAs and isomiRs at different time points under high salinity stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Our results revealed that the generation of miRNA isoforms established a complex osmoregulatory network. Notably, three canonical miRNA-isomiR pairs (miR-2024c-5p, miR-2064b, and miR-5596b-3p) played particularly central roles in this network.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eUnder control conditions, neither the canonical miRNA nor the isomiR of miR-2024c-5p was expressed. The canonical form was induced at 24 and 48 hours, positively regulating Na⁺/K⁺ co-transport functions. In contrast, the isomiR appeared specifically at 48 hours, positively regulating K⁺ transport while negatively affecting Na⁺/K⁺ co-transport and FAA biogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For miR-2064b, the isomiR was induced first at 24 hours, positively regulating glutathione and selenoamino acid metabolism. The corresponding canonical miRNA was induced later, at 48 hours, positively regulating K⁺ transport and selenoamino acid metabolism, while negatively affecting tryptophan metabolism. For miR-5596b-3p, the canonical miRNA was expressed only under control conditions, negatively regulating K⁺ transport, organic ion transport, tryptophan metabolism, and glutathione metabolism. Under high salinity stress at 48 hours, regulation shifted to the isomiR, which additionally negatively regulated Cl⁻ transport while positively influencing D-glutamine and D-glutamate metabolism. These dynamic expression patterns and functional shifts between canonical miRNAs and their isomiRs may be crucial for invasive ascidians to rapidly adapt to acute changes in osmotic stress during high salinity exposure.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe success of biological invasions depends on the rapid and effective adjustment to the fluctuating and often harsh conditions of novel environments, particularly during early invasion stages when propagule numbers are low. Using the model invasive ascidian \u003cem\u003eC. robusta\u003c/em\u003e in this study, we found that salinity challenges triggered timely and dynamic expression of isomiRs, which often diverged from their canonical miRNA counterparts, with their relative abundances changing in a time-dependent manner under stress (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Importantly, both isomiRs and canonical miRNAs regulated overlapping as well as distinct sets of target genes, indicating that miRNA isoform diversification generated functional variation (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These functional shifts included the loss, gain, modification, or addition of regulatory roles in key osmoregulatory processes, such as free amino acid metabolism and ion transport, which were categorized as neo-functionalization, sub-functionalization, or a mixed model (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Interestingly, canonical miRNAs and their corresponding isomiRs can exert opposing regulatory effects on the same target gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Together, our results provide evidence supporting our hypothesis that 5\u0026rsquo; isomiR diversification contributes to adaptive plasticity by enabling dynamic reconfiguration of gene regulatory networks. The observed neo-functionalization, sub-functionalization, and opposing regulatory effects highlight that 5\u0026rsquo; end modifications generate functional flexibility essential for stress tolerance during biological invasions.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDynamic responsive expression of miRNA isoforms\u003c/h2\u003e\u003cp\u003eWhether isomiRs are expressed similarly to their corresponding canonical miRNAs has long been debated [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Some studies have shown that isomiRs exhibit expression patterns comparable to their canonical counterparts across multiple human tissues [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In contrast, other evidence indicates that isomiRs can display distinct expression profiles. For example, during the developmental stages of \u003cem\u003eCaenorhabditis elegans\u003c/em\u003e, several isomiR/canonical miRNA pairs showed divergent temporal patterns: canonical miR-50-5p peaked in embryos, whereas its isomiRs reached maximal expression at the L2/L3 stages and in young adults [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Such temporal variation suggests a connection between isomiR regulation and the organism\u0026rsquo;s life cycle and has been proposed as a strategy to fine-tune gene expression during development.\u003c/p\u003e\u003cp\u003eSimilarly, stress conditions can induce differential responses between canonical miRNAs and their isomiRs. For example, in human vascular fibroblasts and venous tissues exposed to acute ischemia, canonical miR-411 expression increased, whereas its 5\u0026rsquo; isomiR exhibited a rapid decrease. Notably, the 5\u0026rsquo; isomiR targeted different transcripts than the canonical sequence, leading to distinct functional outcomes such as reduced cell migration and impaired wound healing [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In the present study, we observed that almost all isomiRs displayed expression patterns distinct from their canonical sequences, except for the isomiR of miR-5605a-3p, which mirrored the canonical expression at specific hyper-salinity stages or between control and stress groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The observed functional divergence across different studies underscores the biological significance of differential expression patterns between canonical miRNAs and their isomiRs, further highlighting the diverse and potentially specialized roles of isomiRs in stress responses.\u003c/p\u003e\u003cp\u003eTraditionally, 5\u0026rsquo; isomiRs are considered to have lower expression than canonical miRNAs, and some analytical algorithms define canonical miRNAs as the most highly expressed sequences [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. However, these general trends are not absolute, and notable exceptions have been reported. For instance, the 5\u0026rsquo; isomiR of miR-9 was highly expressed in low-grade glioma biopsies [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], and in \u003cem\u003eC. elegans\u003c/em\u003e, certain 5\u0026rsquo; isomiRs were equally or more abundant than their canonical counterparts across developmental stages [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Indeed, the classification of sequences as canonical miRNAs or isomiRs represents a technical distinction that, in many contexts, does not substantially affect biological interpretation. The observed differences in abundance between 5\u0026rsquo; isomiRs and their canonical miRNAs suggest potential functional relevance. Higher expression of a 5\u0026rsquo; isomiR may indicate that it plays a more prominent regulatory role under certain conditions or in specific tissues. Similarly, dynamic changes in abundance across varied scenarios likely reflect context-dependent modulation of miRNA function, highlighting that isomiRs are not merely minor variants but can contribute significantly to gene regulation.\u003c/p\u003e\u003cp\u003eThe functional significance of 5\u0026rsquo; isomiRs arises from their ability to modify the miRNA seed sequence, a critical determinant of target recognition. A single-nucleotide variation or length alteration at the 5\u0026rsquo; end shifts the seed sequence, fundamentally changing the target repertoire and enabling the isomiR to regulate distinct metabolic and developmental pathways [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. This mechanism provides a plausible explanation for the functional diversification of isomiRs under stress conditions. Stress conditions can modulate this processing machinery. Drosha activity, for instance, is regulated by phosphorylation \u003cem\u003evia\u003c/em\u003e the p38/MAPK pathway under heat or oxidative stress, which decreases its binding affinity to DGCR8 and alters pri-miRNA processing efficiency [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. This provides a molecular basis for the dynamic changes in isomiR dominance observed under hyper-salinity stress. Consistently, our previous work demonstrated that \u003cem\u003eDrosha\u003c/em\u003e expression levels themselves change under salinity stress [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], supporting that osmotic stress modulates \u003cem\u003eDrosha\u003c/em\u003e activity, leading to the observed dynamic cleavage patterns and relative expression levels of isomiRs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eTarget diversification and functional transformation\u003c/h2\u003e\u003cp\u003eThe shifted seed region fundamentally redefines the microRNA\u0026rsquo;s target profile, allowing 5'-isomiRs to function across a dual spectrum: acting either as cooperative supporters of the canonical microRNA or as divergent competitors to expand the overall functional repertoire of the regulatory locus. In a cooperative model, canonical microRNAs and their isomiRs work together to reinforce specific biological pathways. This functional redundancy may provide regulatory robustness and reduce off-target effects [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. For instance, we found in this study that canonical miR-2064b and its isomiR co-regulating the same target, \u003cem\u003eprmt7\u003c/em\u003e, and miR-2024c-5p and its isomiR co-regulating \u003cem\u003enka\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). More complex cooperation involves isomiRs regulating different targets that ultimately converge on the same crucial cellular function. This is exemplified by human miR-142-3p, where co-expressed 5\u0026rsquo; isomiRs recognize distinct sets of binding sites, yet both modulate multiple regulators of the actin cytoskeleton (such as \u003cem\u003ep190RhoGap\u003c/em\u003e and \u003cem\u003eCFL2\u003c/em\u003e), essential for megakaryocyte maturation and function [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Similarly, in breast cancer, while the canonical miR-140-3p controls cell stemness, its 5\u0026rsquo; isoform focuses on inducing cell cycle arrest and inhibiting migration, demonstrating a collaborative tumor-suppressive strategy [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConversely, 5\u0026rsquo; isomiRs are potent drivers of divergence and neofunctionalization through the acquisition of novel targets and the loss of canonical ones. This functional transformation results from the altered seed sequence giving the isomiR an entirely new targetome. For example, previous studies detected that the 5\u0026rsquo; isomiR of miR-9-1, which gained the capacity to repress \u003cem\u003eDNMT3B\u003c/em\u003e and \u003cem\u003eNCAM2\u003c/em\u003e while simultaneously losing its ability to inhibit the canonical target \u003cem\u003eCDH1\u003c/em\u003e [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Another 5\u0026rsquo; isoform of miR-140-3p gained the ability to inhibit the novel targets including \u003cem\u003eCOL4A1\u003c/em\u003e, \u003cem\u003eITGA6\u003c/em\u003e, and \u003cem\u003eMARCKSL1\u003c/em\u003e [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Furthermore, the relationship can become antagonistic: in human vascular cells subjected to ischemia, the canonical miR-411 is upregulated and regulates the pro-angiogenic TGFB, while the 5\u0026rsquo; isomiR-411 level rapidly decreases, controlling exclusive targets (F3 and ANGPT1) and leading to opposite effects on cell migration [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eLimitations and future perspectives\u003c/h2\u003e\u003cp\u003eAlthough this study provides evidence for the dynamic and functional divergence of isomiRs in stress responses, several limitations warrant further investigations in the future. A major technical constraint is the dependence on computational target prediction algorithms to infer regulatory divergence between canonical miRNAs and their corresponding isomiRs. Despite the fact that this approach is commonly adopted in many studies and these tools provide valuable insights into potential target relationships, their predictions remain inferential rather than experimentally confirmed. Furthermore, while the study reveals significant correlations among hyper-salinity stress, isomiR expression, and the regulation of osmoregulatory genes, these relationships are correlative rather than causal. Demonstrating causality will be essential to confirm that isomiR modulation is not merely a byproduct of stress but a mechanistic driver of phenotypic plasticity. Consequently, future work should integrate experimental validation approaches, such as luciferase reporter assays, RNA immunoprecipitation (RIP) or CLIP-based techniques, and loss- or gain-of-function analyses, to confirm predicted targets and elucidate the mechanistic basis of isomiR-mediated regulatory divergence.\u003c/p\u003e\u003cp\u003eAnother important direction for future research involves elucidating the molecular mechanisms underlying isomiR biogenesis and decay under stress conditions. The present study captured the downstream outcome (i.e., a shift in the relative abundance of specific isomiRs) but did not address the upstream regulatory processes driving this shift. The potential roles of stress-induced post-transcriptional modifications or altered enzymatic activities (e.g., those of Drosha, Dicer, or nucleotidyl transferases) remain largely unknown. As a result, the mechanistic pathways linking environmental stress cues to isomiR generation and maturation remain unvalidated. Clarifying these pathways will be essential to understanding how cellular stress responses contribute to the structural diversification and functional complexity of miRNA in response to varied stresses.\u003c/p\u003e\u003cp\u003eGiven that biological invasions are escalating in both scale and frequency globally, understanding the mechanisms underpinning invasion success is crucial for effective ecological and economic management. miRNAs and their diverse isomiRs play a pivotal role in this context, as they provide a rapid and flexible layer of post-transcriptional regulation that underlies (adaptive) phenotypic plasticity and environmental tolerance, traits central to the establishment and persistence of invasive species. Accordingly, future research should aim to integrate emerging molecular insights from isomiR-mediated regulation into a broader ecological framework, advancing from the observation of gene regulatory changes to experimental validation of how these molecular processes directly enhance fitness-related traits such as phenotypic plasticity and transgenerational resilience. Such integration will be critical for bridging the current divide between molecular biology and invasion ecology.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eUsing the highly invasive ascidian model species, \u003cem\u003eC. robusta\u003c/em\u003e, the current study demonstrates that the flexibility of miRNA-based gene expression regulation is significantly enhanced by the dynamic expression and functional divergence of their isoforms, isomiRs. Exposure to hyper-salinity stress triggered a time-dependent and dynamic expression of isomiRs, which often followed a pattern distinct from their canonical miRNA counterparts. This functional diversification was critical, as isomiRs and canonical miRNAs regulated overlapping and unique sets of target genes, leading to a \u0026lsquo;rewiring\u0026rsquo; of the regulatory network. The observed changes in the target repertoire resulted in the functional transformation of the regulatory roles of the miRNA loci, categorized into neo-functionalization (gain of new functions), sub-functionalization (loss of ancestral functions), or a mixed model (both gain and loss) in key osmoregulatory processes such as FAA metabolism and ion transport. Intriguingly, in some cases, a canonical miRNA and its corresponding isomiR were found to exert opposing regulatory effects on the same target gene. This dual capacity for both cooperative and divergent regulation, primarily driven by 5\u0026rsquo; isomiRs that alter the critical seed region, establishes a more flexible and intricate regulatory network. This mechanism is highly plausible for enhancing stress tolerance and environmental resilience in invasive populations, thereby promoting their success in novel and fluctuating environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.Z. conceived and designed the study; W.Y., R.F., and X.H. performed the experiments and collected the data. W.Y., R.F., and X.H. conducted the bioinformatics analyses. W.Y. interpreted the results with input from all co-authors. W.Y. drafted the manuscript. R.F., X.H., and A.Z. contributed to manuscript revisions and provided critical feedback. A.Z. and X.H. supervised the project and acquired funding. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the National Natural Science Foundation of China (Nos. 32471740, 32561143021, and 32101352)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll raw high-throughput mRNA and DNA methylation sequencing data were deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under accession number PRJNA775866, and the raw miRNA-seq data was deposited in SRA database under the number PRJNA1120970.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work did not require ethical approval from a human subject or animal welfare committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of AI use\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have not used AI-assisted technologies in creating this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDiagne C, Leroy B, Vaissi\u0026egrave;re A-C, Gozlan RE, Roiz D, Jarić I, Salles J-M, Bradshaw CJ, Courchamp F. 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BMC Genom. 2016; 17: 566. https://doi.org/10.1186/s12864-016-2869-x\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-ecology-and-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"evob","sideBox":"Learn more about [BMC Ecology and Evolution](http://bmcevolbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/evob/default.aspx","title":"BMC Ecology and Evolution","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Biological invasion, epigenetics, gene expression, miRNA, isomiR, phenotypic plasticity","lastPublishedDoi":"10.21203/rs.3.rs-7993353/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7993353/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding the mechanisms underlying invasion success is crucial for addressing the rapidly increasing frequency of biological invasions and their escalating ecological and economic impacts worldwide. Phenotypic plasticity plays a crucial role in facilitating invasion success by enabling organisms to respond rapidly to environmental fluctuations. Among molecular regulators of such plasticity, microRNAs (miRNAs) mediate stress adaptation through post-transcriptional gene regulation. Increasing evidence suggests that a single miRNA locus can generate multiple variants (isomiRs), which may diversify regulatory functions and enhance environmental resilience. However, their expression dynamics and functional significance under environmental stress remain largely unexplored during biological invasions. Here, using the highly invasive ascidian \u003cem\u003eCiona robusta\u003c/em\u003e as a model, we examined the dynamic expression and functional divergence of miRNA isoforms in response to osmotic stress. Integrative analysis of miRNAome and transcriptome revealed 10 miRNAs that produced 5\u0026rsquo; isomiRs with time-dependent and stress-specific expression patterns. Both canonical miRNAs and their isomiRs targeted overlapping yet distinct gene sets, particularly in pathways related to free amino acid metabolism and ion transport. Functional analysis demonstrated that isomiRs underwent neo-functionalization, sub-functionalization, or mixed functional shifts relative to their canonical counterparts, and in some cases exerted opposite regulatory effects on the same target genes. These results reveal that osmotic stress induces rapid diversification and functional transformation of miRNA isoforms, forming a flexible and dynamic regulatory network. Such plasticity in isomiR regulation likely contributes to enhanced stress tolerance and environmental adaptability, thereby promoting invasion success across diverse, harsh, or rapidly changing environments.\u003c/p\u003e","manuscriptTitle":"Dynamic expression and functional transformation of microRNA isoforms induced by osmotic stress in invasive Ciona robusta","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 00:14:19","doi":"10.21203/rs.3.rs-7993353/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-23T09:39:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-10T18:08:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T16:57:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54858247352457065344378480517116492662","date":"2026-01-21T16:27:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289659504772736545693622121296794364027","date":"2025-12-26T11:07:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-02T06:17:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-03T05:50:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-31T04:24:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-31T04:23:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ecology and Evolution","date":"2025-10-31T01:32:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ecology-and-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"evob","sideBox":"Learn more about [BMC Ecology and Evolution](http://bmcevolbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/evob/default.aspx","title":"BMC Ecology and Evolution","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2aeda388-83b1-4f0f-8f79-909f8ebd4bf3","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-03T08:08:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 00:14:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7993353","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7993353","identity":"rs-7993353","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}