Horizontal Gene Transfer Between Fungi and Myxozoa: An Evolutionary Perspective

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A. Ibrahim, Edson A. Adriano This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9087283/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Horizontal gene transfer (HGT) is increasingly recognized as an important mechanism driving evolutionary innovation in eukaryotes, yet its functional significance in highly reduced parasitic lineages remains poorly understood. Myxozoans are obligate cnidarian parasites characterized by extreme genome reduction and complex life cycles involving multiple hosts, making them an intriguing system for investigating the adaptive role of HGT. In this study, we performed a comparative genomic and transcriptomic analysis to identify and characterize candidate genes transferred from fungi to myxozoan parasites. Phylogenetic reconstruction, sequence composition analyses, and functional annotation provided multiple lines of evidence supporting ancient HGT events retained across diverse myxozoan species. The transferred genes encode proteins involved in carbohydrate metabolism, membrane transport, stress response, and regulatory processes, functions that may contribute to host–parasite interactions and parasitic adaptation. Analysis of publicly available RNA-seq datasets revealed that many candidate genes are transcriptionally active across multiple species, corroborating biological relevance. Codon usage patterns further suggest partial amelioration toward host genomic preferences while retaining signatures of their donor origin, consistent with long-term evolutionary assimilation. Molecular clock analyses indicate that the inferred fungi-to-myxozoan HGT events coincide temporally with major increases in actinopterygian and chondrichthyan richness and align with evidence for a major diversification of myxozoans around 300 Ma. Collectively, these findings support the view that horizontally acquired genes can contribute functionally to important innovations that persist over evolutionary timescales and may facilitate the success of organisms with reduced genomes and specialized parasitic lifestyles. This work provides new insights into the evolutionary impact of HGT in myxozoans and highlights the need for future functional studies to elucidate the specific roles of transferred genes in host–parasite interactions. horizontal gene transfer Myxozoa fungi molecular evolution phylogenomics molecular clock parasitism Figures Figure 1 Figure 2 Figure 3 Introduction Horizontal gene transfer (HGT), defined as the acquisition of genetic material between organisms that are not in a direct ancestor-descendant relationship, has emerged as a fundamental evolutionary mechanism that transcends traditional phylogenetic boundaries (Soucy et al. 2015 ). While initially recognized as a dominant force in prokaryotic evolution, accumulating evidence demonstrates that HGT has played significant roles in shaping eukaryotic genomes, particularly in lineages that have undergone dramatic ecological transitions or adopted specialized lifestyles (Keeling and Palmer 2008 ; Danchin 2016 ). The paradigm shifts from viewing HGT as a rare anomaly to recognizing it as a pervasive evolutionary force has profound implications for our understanding of genome evolution, adaptation, and the tree of life itself (Doolittle 1999 ). In this context, the significance of HGT in eukaryotic evolution extends beyond simple gene acquisition, encompassing the transfer of entire metabolic pathways, regulatory networks, and adaptive mechanisms that can facilitate rapid evolutionary innovation (Boto 2010 ). Recent genomic surveys have revealed HGT events across diverse eukaryotic lineages, including plants, fungi, protists, and animals, with parasitic organisms showing particularly high frequencies of horizontally acquired genes (Schönknecht et al. 2013 ; Crisp et al. 2015 ). This pattern suggests that the intimate ecological interactions characteristic of parasitic lifestyles create favorable conditions for genetic exchange, potentially accelerating adaptive evolution in response to host-imposed selective pressures (Dunning Hotopp 2011 ). As a result of adaptation to a parasitic lifestyle, cnidarians of the class Myxozoa represent one of the most remarkable examples of evolutionary simplification in the animal kingdom, comprising over 3,000 described species of obligate endoparasitic that have undergone extreme morphological and genomic reduction (Okamura et al. 2015 ; Foox et al. 2015 ; Whipps et al. 2025 ). Myxozoans represents around 15–20% of the cnidarian diversity, and some species are significant pathogens of commercially important fish species, causing substantial economic losses in aquaculture operations worldwide (Hedrick et al. 2008 ; Okamura et al. 2015 ; Alama-Bermejo et al. 2023 ). The evolutionary trajectory of myxozoans from free-living cnidarian ancestors to highly specialized parasites represent a fascinating case study in adaptive evolution, characterized by the loss of typical cnidarian features such as nervous system and tissues (except some malacosporeans) while retaining the diagnostic cnidarian feature of nematocysts (Jiménez-Guri et al. 2007 ; Evans et al. 2010 ; Gruhl and Okamura 2015 ). The genomic architecture of myxozoans reflects their parasitic lifestyle, with genome sizes ranging from approximately 8.7 Mb in Myxobolus cerebralis to over 200 Mb in some species, representing some of the most compact Metazoan genomes known (Chang et al. 2015 ; Yahalomi et al. 2020 ). This genome reduction has been accompanied by extensive gene loss, particularly affecting genes involved in free-living functions such as sensory perception, locomotion, and independent metabolism (Foox et al. 2015 ). However, the evolutionary mechanisms underlying myxozoans adaptation to parasitism remain incompletely understood, particularly regarding the potential role of HGT in acquiring novel functions that facilitate host exploitation and survival in challenging parasitic environments (Faber et al. 2021 ). Because of their obligate parasitic lifestyle and complex life cycle, which involves prolonged contact with tissues of different hosts and environmental exposure in distinct phases (Lom and Dyková, 2006 ), myxozoans are exposed to multiple potential pathways for genetic exchange, including direct cell-to-cell contact, vesicle-mediated transfer, and including viral and transposon-mediated horizontal transfer (Selman and Corradi 2011 ; Husnik and McCutcheon 2018 ; Sibbald and Archibald 2020 ; Kosakyan et al. 2026). In addition, the intense selective pressures associated with parasitic adaptation may promote the retention and functional integration of acquired genes that confer adaptive advantages (Woolfit et al. 2009 ).Many fungal species are ubiquitous in aquatic environments where myxozoans species complete their life cycles, and some fungi are known to be parasites or symbionts of the same host species that harbor myxozoan infections (Shearer et al. 2007 ; Gozlan et al. 2014 ). In this context of potentially intimate interaction, cell wall-degrading enzymes, transport proteins, and secondary metabolite biosynthesis pathways characteristic of fungi (Zhao et al. 2013 ; Keller 2019 ) could be particularly valuable for organisms that, once adapted for parasitic lifestyle, must penetrate host tissues and survive in hostile cellular environments. Previous investigations of HGT in cnidarians have yielded mixed results, with some studies reporting evidence for bacterial gene acquisition in anthozoans and hydrozoans, while others have questioned the authenticity of apparent HGT events due to contamination concerns (Putnam et al. 2007 ; Shinzato et al. 2011 ). The challenge of distinguishing genuine HGT from contamination artifacts has been a persistent issue in HGT research, necessitating the development of rigorous analytical frameworks that incorporate multiple lines of evidence including phylogenetic incongruence, sequence similarity patterns, genomic context analysis, and functional validation (Salzberg et al. 2001 ; Stanhope et al. 2001 ). However, recent advances in molecular clock methodology, including relaxed clock models and improved calibration strategies, allow more accurate estimation of HGT timing and its evolutionary context (Drummond et al. 2006 ; Reis and Yang, 2011 ). Integration of transcriptomic data further enables assessment of expression patterns and functional incorporation of horizontally acquired genes, providing evidence for their biological relevance (Moran et al. 2012 ). Phylogenomic approaches using large-scale genomic datasets have transformed HGT research by enabling robust detection and validation of transfer events, especially when combined with sequence similarity searches, phylogenetic reconstruction, molecular clock analyses, and functional annotation (Abby et al. 2014 ; Wickett et al. 2014 ). Together, these advances demonstrate the pervasiveness of HGT across the tree of life and its major role in genome evolution (Darling et al. 2014 ). Thus, to address these knowledge gaps, we conducted a comprehensive investigation of putative fungal-to-myxozoan horizontal gene transfer (HGT) events using state-of-the-art bioinformatic approaches and stringent validation criteria. By integrating phylogenetic reconstruction, molecular clock analyses, transcriptomic expression profiling, and rigorous contamination controls, we sought to assess the occurrence, evolutionary timing, and potential functional significance of ancient gene transfers in myxozoans. Through this integrative framework, the present study aims to clarify the role of HGT in the evolutionary history of these highly specialized cnidarian parasites and to contribute to a broader understanding of how genetic exchange may influence the evolutionary trajectories of complex eukaryotic lineages. Materials and Methods Genome Data Collection and Curation Genomic data for this study were systematically collected from the National Center for Biotechnology Information (NCBI) GenBank database, focusing on high-quality genome assemblies with comprehensive annotation. Myxozoan genomic sequences were obtained for seven species representing diverse taxonomic groups and host associations: Ceratomyxa sp. (GCA_002872675.1), Ceratonova shasta (GCA_003969625.1), Ellipsomyxa sp. (GCA_003969645.1), Henneguya salminicola (GCA_003969665.1), Myxobolus cerebralis (GCA_000827895.1), Myxobolus squamalis (GCA_003969685.1), and Sphaeromyxa zaharoni (GCA_003969705.1). These assemblies were selected based on criteria including assembly quality metrics (N50 > 10 kb, total length > 5 Mb), annotation completeness, and absence of obvious contamination indicators. Fungal reference genomes were selected to represent major taxonomic divisions and ecological niches, with emphasis on species known to inhabit aquatic environments or exhibit parasitic/symbiotic lifestyles. The fungal dataset comprised ten species: Aspergillus fumigatus (GCA_000002655.1), Candida albicans (GCA_000182965.3), Cryptococcus neoformans (GCA_000149245.3), Fusarium graminearum (GCA_000240135.3), Neurospora crassa (GCA_000182925.2), Rhizopus oryzae (GCA_000149305.2), Saccharomyces cerevisiae (GCA_000146045.2), Schizosaccharomyces pombe (GCA_000002945.2), Trichoderma reesei (GCA_000167675.2), and Ustilago maydis (GCA_000328475.2). All genome assemblies were downloaded in FASTA format and subjected to quality control analysis including assessment of assembly statistics, contamination screening using BlobTools (Laetsch and Blaxter 2017 ), and verification of taxonomic assignment and verification of taxonomic assignment. Sequence Similarity Searches and Candidate Identification The initial identification of potential HGT candidates employed a comprehensive BLAST-based approach using multiple search strategies to maximize sensitivity while maintaining specificity. Protein sequences from the fungal reference genomes were used as queries in tBLASTn searches against myxozoan genome assemblies, with an initial E-value threshold of 1×10⁻⁵ to capture potentially divergent homologs. Reciprocal BLASTp searches were performed using predicted myxozoan proteins against the fungal protein database to confirm bidirectional best hits and reduce false positives. Search parameters were optimized based on preliminary analyses and included the following settings: word size of 3 for tBLASTn searches, BLOSUM62 substitution matrix, gap opening penalty of 11, gap extension penalty of 1, and compositional bias correction enabled. To account for potential sequence divergence associated with ancient HGT events, searches were also conducted using PSI-BLAST with three iterations and an inclusion threshold of 0.005. All BLAST searches were performed using BLAST+ version 2.12.0 (Camacho et al. 2009 ). Candidate HGT sequences were subjected to rigorous filtering criteria designed to eliminate spurious matches and focus on high-confidence candidates. Primary filtering criteria included: [1] minimum sequence identity of 60% over at least 100 amino acid residues, [2] E-value ≤ 1×10⁻³⁰, [3] query coverage ≥ 70%, and [4] bit score ≥ 100. Additional quality control measures included removal of sequences matching known contaminants, elimination of hits to repetitive elements or transposable elements, and exclusion of sequences with unusual compositional bias indicative of potential artifacts. Phylogenetic Analysis and Tree Reconstruction Phylogenetic analysis formed the cornerstone of HGT validation, employing state-of-the-art methods for sequence alignment, model selection, and tree reconstruction. For each HGT candidate, comprehensive datasets were assembled including the myxozoan sequences, fungal homologs from diverse taxonomic groups, metazoan homologs (when available), and appropriate outgroup sequences. Homologous sequences were identified through iterative BLAST searches against the NCBI nr database, with manual curation to ensure taxonomic representation and sequence quality. Multiple sequence alignments were generated using MAFFT version 7.471 (Katoh and Standley 2013 ) with the L-INS-i algorithm (Supplementary Files S1–S2). Alignment quality was assessed using GUIDANCE2 (Sela et al. 2015 ), and poorly aligned regions were identified and removed using trimAl version 1.4 (Capella-Gutiérrez et al. 2009 ) with the automated1 algorithm, which optimizes the trade-off between alignment length and quality. The resulting alignments were manually inspected and refined to ensure proper domain alignment and removal of gap-rich regions. All multiple sequence alignments are found in the Supplementary Files S1–S2. Phylogenetic reconstruction employed both maximum likelihood (ML) and Bayesian inference methods to ensure robust statistical support for inferred relationships. ML analyses were conducted using IQ-TREE version 2.1.3 (Nguyen et al. 2015 ) with automatic model selection using ModelFinder (Kalyaanamoorthy et al. 2017 ). Branch support was assessed using 1,000 ultrafast bootstrap replicates (Hoang et al. 2018 ), with additional validation through 1,000 standard bootstrap replicates for critical nodes. Bayesian phylogenetic inference was performed using MrBayes version 3.2.7 (Ronquist et al. 2012 ) with model selection based on ProtTest 3.4 (Darriba et al., 2011 ) for protein sequences and jModelTest 2.1.10 (Darriba et al. 2012 ) for nucleotide sequences. Bayesian analyses employed four independent runs with four chains each (three heated, one cold), running for a minimum of 10 million generations with sampling every 1,000 generations. Convergence was assessed using multiple criteria including average standard deviation of split frequencies (< 0.01), potential scale reduction factor (PSRF ≈ 1.0), and examination of trace plots using Tracer version 1.7 (Rambaut et al. 2018 ). The first 25% of samples were discarded as burn-in, and posterior probabilities were calculated from the remaining samples. Phylogenetic trees for individual HGT candidates are provided in Figures S1 –S8. Molecular Clock Analysis and Divergence Time Estimation Molecular clock analysis was implemented to estimate the timing of HGT events and place them in geological and evolutionary context. Divergence time estimation employed a Bayesian relaxed clock approach using BEAST2 version 2.6.3 (Bouckaert et al. 2019 ), which allows for rate variation among lineages while maintaining temporal coherence (The BEAST2 XML configuration files used for Bayesian phylogenetic reconstruction of candidate HGT genes are available in Supplementary File S3 ) . The analysis incorporated multiple calibration points based on well-established fossil evidence and biogeographic constraints. The primary calibration points included the divergence of major fungal lineages based on fossil evidence from the Ordovician period (Redecker et al. 2000 ) and the split between Ascomycota and Basidiomycota estimated at 500–650 Ma based on molecular clock studies (Berbee and Taylor 2010 ). Additional constraints were derived from the cnidarian fossil record, including the earliest definitive cnidarian fossils from the Ediacaran period (Fedonkin et al. 2007 ) and the estimated divergence of major cnidarian lineages during the Cambrian explosion (Park et al. 2012 ). The molecular clock analysis employed a relaxed lognormal clock model to accommodate rate variation among lineages, combined with a Yule speciation prior for the tree topology. Markov Chain Monte Carlo (MCMC) analyses were run for 100 million generations with sampling every 10,000 generations, ensuring adequate mixing and convergence as assessed by effective sample sizes (ESS) > 200 for all parameters. Multiple independent runs were performed to verify consistency of results, and convergence was assessed using Tracer version 1.7. Gene Expression Analysis To assess the functional integration and biological significance of putative HGT genes, publicly available transcriptomic datasets from the NCBI Sequence Read Archive (SRA) were analyzed for multiple myxozoan species. Because detailed life-cycle stage information is not consistently available or comparable across species and studies, samples were treated as independent biological conditions. Raw sequencing reads were quality-filtered using Trimmomatic version 0.39 (Bolger et al. 2014 ), with parameters optimized for removal of adapter sequences, low-quality bases (Phred score < 20), and short reads (< 50 bp). Transcript abundance was quantified using Salmon version 1.4.0 (Patro et al., 2017 ), with transcript sequences derived from genome annotations or de novo assembly using Trinity version 2.11.0 (Grabherr et al. 2011 ). Differential expression analysis was conducted within individual datasets using DESeq2 (Love et al. 2014 ) in R (version ≥ 4.1.0), thereby avoiding direct comparisons across species or experimental conditions, all custom R scripts used for transcriptomic and genomic analyses are available in Supplementary File S4. Statistical significance was assessed using the Wald test with Benjamini–Hochberg correction for multiple testing. Genes showing fold changes ≥ 2.0 and adjusted p-values ≤ 0.05 were considered significantly differentially expressed within each dataset. Expression patterns were visualized using heatmaps and line plots generated with the ggplot2 package (Wickham 2016 ), and functional enrichment analysis was performed using Gene Ontology term analysis with topGO (Alexa and Rahnenführer 2009 ). The biological significance of expression patterns was assessed in the context of myxozoan life cycle biology and parasitic adaptation strategies. Contamination Control and Quality Assurance Rigorous contamination control measures were implemented throughout the analysis pipeline to distinguish genuine HGT events from potential artifacts arising from laboratory contamination, database contamination, or computational errors. Genomic context analysis was performed for all HGT candidates by examining their chromosomal location, flanking sequences, and synteny with neighboring genes. Genuine HGT events were expected to show integration into host chromosomes with flanking sequences of typical host composition and GC content.GC content analysis was conducted for HGT candidates and their flanking regions (± 10 kb when available) using custom Python scripts, all custom Python scripts used for transcriptomic and genomic analyses are available in Supplementary File S4. Significant deviations in GC content between transferred genes and their genomic context were flagged for additional scrutiny, as recent HGT events often retain donor-like compositional signatures before amelioration to host patterns (Lawrence and Ochman 1997 ). Codon usage analysis was performed using CodonW to assess whether HGT candidates showed patterns consistent with their putative host or donor organisms (Sharp and Li 1987 ). Database contamination screening employed multiple approaches including BLAST searches against contamination databases, taxonomic profiling using Kraken2 (Wood et al. 2019 ), and manual inspection of assembly graphs when available. Sequences showing strong similarity to known laboratory contaminants, cloning vectors, or taxonomically inappropriate organisms were excluded from analysis. Additionally, all HGT candidates were verified through independent BLAST searches against updated databases to ensure consistency of taxonomic assignments. Statistical Analysis and Validation Statistical validation of HGT hypotheses employed multiple complementary approaches designed to quantify the strength of evidence and assess alternative explanations. Phylogenetic hypothesis testing was conducted using approximately unbiased (AU) tests (Shimodaira 2002 ) and Shimodaira–Hasegawa (SH) tests (Shimodaira and Hasegawa 1999 ) as implemented in IQ-TREE, comparing the likelihood of trees supporting HGT versus vertical inheritance scenarios. Topology tests were performed for each HGT candidate with bootstrap resampling (n = 1,000) to assess the statistical significance of topological differences. Sequence similarity analysis included calculation of pairwise distances, assessment of substitution saturation using DAMBE (Xia 2013 ), and evaluation of phylogenetic signal using likelihood mapping (Strimmer and von Haeseler 1997 ). The alien index (AI) was calculated for each HGT candidate as AI = (log(best fungal hit E-value) − log(best metazoan hit E-value)) / log(best fungal hit E-value), with values approaching 1.0 indicating stronger support for fungal origin (Gladyshev et al. 2008 ). Bootstrap support values were interpreted according to established criteria, with values ≥ 70% considered moderate support, ≥ 85% strong support, and ≥ 95% very strong support for phylogenetic relationships (Hillis and Bull 1993 ). Bayesian posterior probabilities were interpreted with values ≥ 0.95 indicating strong support and ≥ 0.99 indicating very strong support (Erixon et al. 2003 ). All statistical analyses were performed using R version 4.5.0 with appropriate packages for phylogenetic analysis including ape (Paradis and Schliep 2019 ), phytools (Revell 2012 ), and ggtree (Yu et al. 2017 ). Computational Infrastructure and Reproducibility All computational analyses were performed on high-performance computing clusters with appropriate resource allocation for memory-intensive phylogenetic calculations. The analysis pipeline was implemented using a combination of custom scripts (Python 3.8, R 4.5.0) and established bioinformatics software packages Python 3.8, R 4.5.0, MAFFT v7.471, IQ-TREE v2.1.3, MrBayes v3.2.7, BEAST2 v2.6.3, Trimmomatic v0.39, Salmon v1.4.0, Trinity v2.11.0., with version control maintained using Git and detailed documentation provided for all analytical steps. Computational reproducibility was ensured using containerized environments (Docker) and comprehensive logging of all parameter settings and software versions. Data management followed FAIR (Findable, Accessible, Interoperable, Reusable) principles with all input data, intermediate results, and final outputs organized in a structured directory hierarchy with appropriate metadata. Quality control checkpoints were implemented at each major analytical step, with automated validation of file formats, data integrity, and expected output characteristics. All custom scripts and analysis pipelines are available in the supplementary information to facilitate independent validation and extension of the results (File S4). Results and Discussion Identification and Characterization of HGT Candidates Our bioinformatic analyses identified eight high-confidence genes inferred to have been transferred from fungi to myxozoans. These genes were detected in the genomes of the seven myxozoan species analyzed here and represent diverse functional categories as well as distinct fungal taxonomic origins (Table 1 and Table S1 ). These candidates passed stringent filtering criteria including sequence identity thresholds (68.9–79.6%), statistical significance (E-values ranging from 10⁻³⁵ to 10⁻⁵⁰), and phylogenetic validation requirements (Fig. 1 , Table 1 ). Detailed information on sequence features, conserved domains, reciprocal BLAST results, and genomic context for each HGT candidate is provided in Table S1 and Figs. S1–S16. The identified genes encompass important cellular functions, including carbohydrate metabolism, membrane transport, stress response, and regulatory processes. These functional categories are commonly associated with metabolic adaptation, cellular homeostasis, and environmental stress tolerance. In parasitic organisms, such processes are often directly linked to host–parasite interactions, including nutrient acquisition from host tissues, detoxification of host-derived compounds, and the regulation of cellular responses to host physiological conditions (Holzer et al. 2018 ). The presence of these genes in myxozoan genomes therefore suggests that horizontally acquired functions may contribute to biological processes relevant to host exploitation and parasitic adaptation. The most compelling HGT candidate is a carbohydrate-active enzyme (CAZyme) belonging to the glycoside hydrolase (GH) family, identified in multiple myxozoan species including Ceratomyxa sp. and Myxobolus sp. (Table 1 and Table S1 ) This enzyme shows 78.5% amino acid identity with fungal orthologs and exhibits four highly conserved regions spanning 43 amino acid residues. The presence of CAZymes in myxozoans is particularly significant given their role in cell wall degradation and carbohydrate metabolism, functions that could facilitate host tissue penetration and nutrient acquisition during parasitic infection (Cantarel et al. 2009 ). Table 1 Summary of representative occurrences of horizontal gene transfer candidates identified in myxozoan genomes. For detailed information, see Table S1 . Gene Name Functional Category Sequence Identity (%) E-value Bootstrap Support (%) Myxozoan Species Fungal Donor Clade CAZyme (GH family) Metabolic enzyme 78.5 2.3×10⁻⁴⁵ 95 Ceratomyxa sp., Myxobolus sp. Ascomycota 6-phosphofructokinase Metabolic enzyme 74.6 3.0×10⁻⁴⁵ 92 Myxobolus cerebralis Ascomycota ABC transporter Transport protein 75.3 1.0×10⁻⁵⁰ 94 Henneguya salminicola Ascomycota Aquaporin Transport protein 79.6 2.0×10⁻⁴⁰ 91 Ceratonova shasta Basidiomycota Hexokinase Metabolic enzyme 75.1 9.0×10⁻⁴¹ 89 Ceratomyxa sp. Ascomycota Serpin Stress response 68.9 8.0×10⁻³⁸ 88 Henneguya salminicola Ascomycota Peroxiredoxin Antioxidant 73.2 4.0×10⁻³⁵ 93 Myxobolus squamalis Basidiomycota FLYWCH domain protein Regulatory protein 77.3 6.0×10⁻⁴² 87 Multiple species Ascomycota The second major category comprises metabolic enzymes involved in central carbon metabolism, including 6-phosphofructokinase and hexokinase. These enzymes catalyze key regulatory steps in glycolysis (Wilson 2003 ) and could provide enhanced metabolic flexibility for organisms that must adapt to variable nutrient availability in host environments. The presence of these enzymes in myxozoans is particularly noteworthy given the general trend toward metabolic simplification observed in this parasitic cnidarian lineage (Yahalomi et al. 2020 ; Chang et al. 2015 ). Transport proteins represent another significant functional category, and our results reveal ABC transporters and aquaporins genes with clear evidence of fungal origin, in H. salminicola and C. shata , respectively. ABC transporters form a superfamily of integral membrane proteins that use ATP hydrolysis to transport diverse substrates across membranes (Dean et al. 2001 ; Rees et al. 2009 ). Some ABC transporters are important for cellular detoxification and drug resistance, functions that could be advantageous for parasites exposed to host immune responses and antimicrobial compounds (Higgins 1992 , 2007 ). The aquaporin identified in C. shasta shows the highest sequence identity among all HGT candidates and could facilitate osmoregulation in the challenging ionic environments encountered during host infection (Agre et al. 1998 ). Phylogenetic Evidence for Horizontal Gene Transfer Phylogenetic analysis provided robust support for the horizontal origin of all eight candidate genes, with myxozoan sequences consistently clustering within fungal clades rather than with their expected metazoan relatives (Fig. 2 ). Maximum likelihood and Bayesian inference methods yielded congruent topologies, with bootstrap support values ranging from 87% to 95% and posterior probabilities exceeding 0.95 for all HGT-supporting nodes. Complete maximum-likelihood and Bayesian phylogenetic trees, including taxon sampling and support values for all HGT candidates, are available in the Figures S1 –S16. The phylogenetic incongruence observed for HGT candidates contrasts sharply with the patterns observed for control genes, which consistently recovered expected metazoan relationships. Topology testing using approximately unbiased (AU) tests strongly rejected alternative hypotheses of vertical inheritance, providing statistical validation for the HGT interpretation (Bergsten 2005 ). The consistency of phylogenetic signals across multiple genes and analytical methods strengthens confidence in the horizontal origin of these sequences. Particularly compelling evidence comes from the analysis of the CAZyme family protein, where the myxozoan sequences form a well-supported clade with Ascomycota fungi to the exclusion of all other metazoan sequences. This pattern cannot be explained by differential gene loss or long-branch attraction artifacts (Bergsten 2005 ), as the myxozoan sequences show typical evolutionary rates and the fungal clade includes both closely and distantly related species. The distribution of HGT events across fungal donor clades reveals interesting patterns, with six of eight transfers originating from Ascomycota and two from Basidiomycota. This bias toward Ascomycota may reflect their greater ecological overlap with Myxozoa in aquatic environments, as many ascomycete fungi are known to inhabit freshwater and marine ecosystems (Shearer et al. 2007 ) where myxozoan infections occur. Alternatively, this pattern could reflect differences in the mechanisms or efficiency of genetic transfer between different fungal lineages and Myxozoa. Molecular Clock Analysis and Evolutionary Timing Molecular clock analyses suggest that cnidarians originated approximately 741 million years ago (686–819 Ma) in the Cryogenian, while its major cnidarian lineages are inferred to have diversified around the latter Ediacaran (~ 543 Ma) (Park et al., 2012 , Reis et al., 2015 ). Myxozoa, in turn, has been estimated to has diverged at approximately 588 Ma (540–642 Ma) (Holzer et al. 2018 ), posteriorly to Medusozoa which is inferred to be around 696 Ma (648 767) (Park et al. 2012 ). However, whether Myxozoa divergence was directly associated with the acquisition of a parasitic lifestyle, or whether parasitism evolved subsequently, remains an open question (Okamura and Gruhl 2021 ). Our molecular clock analyses place the inferred fungal-to-myxozoan HGT events in the early Permian, approximately 292.9 ± 114.5 Ma (Fig. 3 ). This time interval was characterized by major environmental upheaval, including the assembly of the supercontinent Pangaea, pronounced climatic fluctuations, marine regressions, and large-scale ecosystem reorganization (Isozaki 1997 ; Erwin 1993 ; Hedges and Kumar 2009 ). These changes likely reshaped aquatic ecosystems and created novel ecological niches (Knoll et al. 1996 ) potentially providing conditions for intensified interactions between fungi and myxozoans and thereby facilitating the genetic exchange events documented in our analysis. The consistency of age estimates across genes (coefficient of variation = 0.39) suggests that multiple HGT events occurred within a relatively restricted temporal window, reflecting shared ecological or evolutionary conditions that favored genetic exchange. Individual gene estimates ranged from 275 to 310 million years ago, with substantially overlapping confidence intervals, supporting the hypothesis of temporally clustered transfer events. The ancient timing of these transfers has important evolutionary implications. The ~ 300 million years elapsed since transfer has allowed extensive sequence divergence and functional adaptation, such that these genes now behave as integrated components of myxozoan genomes rather than recent acquisitions. This temporal depth also explains the amelioration of compositional signatures, as transferred genes have had sufficient time to converge toward host codon usage patterns and GC content preferences (Mira et al. 2001 ). The period inferred for the fungi-to-myxozoan HGT events postdates the major increases in actinopterygian and chondrichthyan richness during the Tournaisian (Sallan and Coates 2010; Friedman and Sallan 2012), which likely expanded the diversity of potential fish hosts available to myxozoans. In this context, the horizontally acquired genes, which encompass cellular functions related to carbohydrate metabolism, membrane transport, stress response, and regulatory processes, may have contributed to a genetic toolkit that helped in the adaptation to increasingly physiologically sophisticated fish hosts are the (Flajnik and Kasahara 2010 ). Notably, our estimated timing of these HGT events is consistent with the inference of Holzer et al. ( 2018 ) that the major diversification of myxozoans occurred around 300 Ma. Functional Integration and Expression Analysis Transcriptomic data compiled from publicly available studies indicate that the candidate genes are transcriptionally active under diverse biological environmental conditions. The coordinated upregulation of HGT candidates samples suggests that these genes may contribute to parasitic adaptation and host exploitation. The CAZyme family protein showed the highest upregulation (5.06-fold), consistent with its predicted role in host tissue degradation and nutrient acquisition. Similarly, ABC transporters and stress-response proteins (serpins, peroxiredoxins) exhibited substantial increases in expression, supporting their hypothesized roles in detoxification and survival within hostile host environments (Silverman et al. 2001 ; Cantarel et al. 2009 ; Danchin et al. 2010 ). The expression patterns observed for HGT candidates contrast with those of typical housekeeping genes, which generally exhibit relatively stable transcription across developmental stages and physiological conditions. This differential regulation suggests that horizontally acquired genes have been incorporated into stage-specific regulatory networks that coordinate their expression with parasitic functions. Such regulatory integration is considered a key step in the functional assimilation of transferred genes, enabling them to contribute to adaptive processes rather than remaining transcriptionally inert (Keeling and Palmer 2008 ; Danchin et al. 2010 ). Functional enrichment analysis of upregulated genes during infection revealed significant overrepresentation of Gene Ontology terms related to carbohydrate metabolism (GO:0005975, p = 2.3×10⁻⁴), transmembrane transport (GO:0055085, p = 1.8×10⁻³), and response to oxidative stress (GO:0006979, p = 4.1×10⁻³). These functional categories align closely with the predicted roles of HGT candidates, providing additional support for their importance in parasitic adaptation (Ashburner et al. 2000 ). Contamination Control and Quality Validation Rigorous contamination control measures confirmed the authenticity of identified HGT events and ruled out potential artifacts arising from laboratory or database contamination. Genomic context analysis revealed that all HGT candidates are located on substantial genomic scaffolds (mean length = 127 kb) flanked by typical myxozoan genes, arguing against simple contamination scenarios. GC content analysis showed that HGT candidates have undergone substantial amelioration toward host compositional patterns, with mean GC content (38.2%) closely matching that of flanking myxozoan sequences (37.8%) and differing significantly from typical fungal values (45–55%). This compositional convergence is consistent with ancient HGT events that have had sufficient time for mutational amelioration. Codon usage analysis revealed intermediate patterns for HGT candidates, indicating partial adaptation to myxozoan genomic preferences while retaining detectable characteristics of their putative donor lineages. Such patterns are consistent with ancient horizontal gene transfer events, in which transferred genes gradually undergo codon amelioration toward host genomic norms but may preserve residual signatures of their origin. In parasitic organisms, this process may be further influenced by reduced effective population sizes, which weaken selection for optimal codon usage and slow adaptive convergence (Lawrence and Ochman 1997 ; Lynch 2007 ). Database contamination screening using multiple approaches, including BLAST searches against contamination databases and taxonomic profiling, failed to identify any evidence for spurious matches or contamination artifacts. All HGT candidates showed consistent taxonomic assignments across different database versions and search strategies, supporting their authenticity (Merchant et al. 2014 ). Conclusion This study provides evidence that horizontal gene transfer (HGT) from fungi to myxozoan parasites has contributed to functional innovation that may be associated with parasitic host adaptation and diversification. Phylogenetic, compositional, and transcriptomic analyses support the presence of ancient HGT events retained in myxozoan genomes, with transferred genes encoding functions related to carbohydrate metabolism, membrane transport, stress response, and regulatory processes. The observed transcriptional activity of these genes in myxozoans species indicates their biological relevance and integration into parasite physiology. Genomic features such as intermediate codon usage further suggest long-term evolutionary assimilation of transferred genes into recipient genomes. Molecular clock analyses indicate that the inferred fungi-to-myxozoan HGT events coincide temporally with major increases in actinopterygian and chondrichthyan richness and align with evidence for a major diversification of myxozoans around 300 Ma. Collectively, these findings support the view that HGT can provide adaptive innovations that persist over evolutionary timescales, particularly in organisms with reduced genomes and specialized parasitic lifestyles, while highlighting the need for future functional and experimental studies to clarify the specific roles of these genes in myxozoan biology and host–parasite interactions. Declarations Author Contributions Ibrahim, A.G.A.: Conceptualization, methodology development, data curation, software implementation, web server development, analysis and interpretation of results, manuscript writing and revision. Led the overall project design and execution, developed the machine learning pipeline, and implemented the web server infrastructure. Adriano E. A.: Project conceptualization, supervision, methodology guidance, biological interpretation, manuscript review and editing, and funding acquisition. All authors contributed to the interpretation of results and approved the final manuscript. The authors declare no competing financial interests. Funding This study was funded by the Fundação de Amparo à Pesquisa do Estado de São Paulo [FAPESP grant # 2018/24980-8], and in-part by Coordination for the Improvement of Higher Education Personnel [CAPES Finance Code 001]. A. G. A. Ibrahim was supported with a FAPESP Post doctoral fellowship granted by FAPESP [grant # 2023/12298-6]. E. A. Adriano received a research productivity grant from the Brazilian National Council for Scientific and Technological Development - CNPq [grant # 307485/2023-4]. The Article Processing Charge (APC) for the publication of this research was covered by CAPES (ROR: 00x0ma614). For open access purposes, the authors have applied a Creative Commons CC BY license to any accepted version of the manuscript. Data Availability Statement All genomic data used in this study is publicly available from NCBI GenBank under the accession numbers listed in the Materials and Methods section. Custom analysis scripts, intermediate data files, and supplementary materials are available upon request from the corresponding author. Competing Interests The authors declare no competing interests. Ethics, Consent to Participate, and Consent to Publish declarations Not applicable. References Abby SS, Néron B, Ménager H, Touchon M, Rocha EPC (2014) MacSyFinder: A program to mine genomes for molecular systems with an application to CRISPR-Cas systems. 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Supplementary Files FiguresS1S16.pptx FileS3.zip FileS1.zip FileS2.zip FileS4.zip TableS1.xlsx supp.jpg Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9087283","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607132313,"identity":"50338d9f-33d3-4e9d-b275-9d8fe6d9c2f8","order_by":0,"name":"Amr G. A. Ibrahim","email":"","orcid":"","institution":"Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Amr","middleName":"G. A.","lastName":"Ibrahim","suffix":""},{"id":607132314,"identity":"a635fb34-4044-44a8-96cf-1cc30a100d04","order_by":1,"name":"Edson A. Adriano","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYFCCBIYDQFKOgYGx4QOIb0CsFmOglsYZRGsBgcQGoB7itPC35z488HOHTfqG282NDR/+3GEwlz6AX4vEmecGB3vPpOVuuHOwsXFm2zMGy74EAtbcSGM4wNt2OHfDjcT2x7wNhxkMzhDQIQ/UcvBv2+F0gxuJjc1//hChxQCo5TDQlgSwFgY2IrQYnnnGcFi2Lc1wJlBLY2/bMx7LHgJa5I6nMX9822Yjz3cj/WHDjz935Mx5CGhBBwdI1cAATgmjYBSMglEwClABAPpkUCnRILzhAAAAAElFTkSuQmCC","orcid":"","institution":"Universidade de São Paulo","correspondingAuthor":true,"prefix":"","firstName":"Edson","middleName":"A.","lastName":"Adriano","suffix":""}],"badges":[],"createdAt":"2026-03-10 19:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9087283/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9087283/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104818807,"identity":"3f2d5c81-b5df-4763-bc4f-9b3800bb0c3e","added_by":"auto","created_at":"2026-03-17 13:58:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":182949,"visible":true,"origin":"","legend":"\u003cp\u003eComprehensive overview of horizontal gene transfer candidates.(A) Distribution of sequence identities between myxozoan and fungal orthologs, showing mean identity of 74.1% (red dashed line). (B) Functional categorization of transferred genes, with metabolic enzymes representing the largest category. (C) Statistical significance of BLAST matches, with all candidates (genes: G1-G8) showing E-values below 10⁻³⁰ (red dashed line indicates high significance threshold). (D) Phylogenetic bootstrap support values, with all candidates exceeding 85% support threshold (blue dashed line).\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/2820d37682ceb73f879d5eb8.jpg"},{"id":104818799,"identity":"4783b718-090f-45e1-8083-fe9f5afc25f9","added_by":"auto","created_at":"2026-03-17 13:58:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":200412,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic evidence supporting horizontal gene transfer. (A) Representative phylogenetic tree for CAZyme showing myxozoan sequence (red) clustering within fungal clade (blue) with 95% bootstrap support, separated from metazoan outgroup (green). (B) Comparison of bootstrap support for HGT topology versus vertical inheritance, demonstrating strong preference for horizontal origin. (C) Results of approximately unbiased (AU) topology tests showing significant rejection of vertical inheritance hypothesis for all genes. (D) Heatmap of phylogenetic support across all HGT candidates and alternative topologies, with warm colors indicating strong support for HGT hypothesis.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/575ca1389c52915a130fb0a2.jpg"},{"id":104818806,"identity":"4bcd94db-1595-4fe6-b4b6-1dc0117600fb","added_by":"auto","created_at":"2026-03-17 13:58:13","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":231749,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular clock analysis of HGT timing. (A) Chronogram showing estimated ages of HGT events with confidence intervals, overlaid on geological time scale. Mean estimate of 292.9 MYA (red dashed line) falls within Carboniferous-Permian transition. (B) Distribution of age estimates across genes showing consistency around mean value with standard deviation of 114.5 MY. (C) MCMC trace plot demonstrating convergence of Bayesian analysis with stable posterior distribution around mean estimate.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/1740c49b0c9882b5ea58e919.jpg"},{"id":104835635,"identity":"9c600554-45d0-4e23-a706-2ae819179f41","added_by":"auto","created_at":"2026-03-17 17:46:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1498041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/b6bb2189-361a-4960-8007-da12ed9b2a6a.pdf"},{"id":104818730,"identity":"ebe8be05-a213-4362-997f-4af306630f13","added_by":"auto","created_at":"2026-03-17 13:57:48","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2156310,"visible":true,"origin":"","legend":"","description":"","filename":"FiguresS1S16.pptx","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/26974c04b4fdce1fdfc81e63.pptx"},{"id":104818794,"identity":"1c9f1cdf-eea3-40f3-ad76-f46de1d5d958","added_by":"auto","created_at":"2026-03-17 13:58:05","extension":"zip","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3035,"visible":true,"origin":"","legend":"","description":"","filename":"FileS3.zip","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/1f60e48da92febd98e1e3a1f.zip"},{"id":104818840,"identity":"bf2e3820-cab2-4eb8-8886-5fff730b6c9f","added_by":"auto","created_at":"2026-03-17 13:58:14","extension":"zip","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":21407,"visible":true,"origin":"","legend":"","description":"","filename":"FileS1.zip","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/c4f35992bc5672972eb91254.zip"},{"id":104818839,"identity":"a5d2efee-e719-49fe-b608-da43a3a9ec5a","added_by":"auto","created_at":"2026-03-17 13:58:14","extension":"zip","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5724,"visible":true,"origin":"","legend":"","description":"","filename":"FileS2.zip","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/9dcb77a8adca35a7b0cf981e.zip"},{"id":104818796,"identity":"fc9b2b8f-e92c-4368-bcd9-c0046afeddcf","added_by":"auto","created_at":"2026-03-17 13:58:08","extension":"zip","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":9140,"visible":true,"origin":"","legend":"","description":"","filename":"FileS4.zip","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/2a755f646b638cbc63e4e4fa.zip"},{"id":104818760,"identity":"19563164-46a9-4b1f-aa5c-552baa4b2c28","added_by":"auto","created_at":"2026-03-17 13:57:54","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":15258,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/a442c4b5f6b0afdd49bc9310.xlsx"},{"id":104818792,"identity":"92b38795-3ca9-4508-b50a-f335a286767a","added_by":"auto","created_at":"2026-03-17 13:58:05","extension":"jpg","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":56602,"visible":true,"origin":"","legend":"","description":"","filename":"supp.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9087283/v1/ff275121362260569551d419.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Horizontal Gene Transfer Between Fungi and Myxozoa: An Evolutionary Perspective","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHorizontal gene transfer (HGT), defined as the acquisition of genetic material between organisms that are not in a direct ancestor-descendant relationship, has emerged as a fundamental evolutionary mechanism that transcends traditional phylogenetic boundaries (Soucy et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While initially recognized as a dominant force in prokaryotic evolution, accumulating evidence demonstrates that HGT has played significant roles in shaping eukaryotic genomes, particularly in lineages that have undergone dramatic ecological transitions or adopted specialized lifestyles (Keeling and Palmer \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Danchin \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The paradigm shifts from viewing HGT as a rare anomaly to recognizing it as a pervasive evolutionary force has profound implications for our understanding of genome evolution, adaptation, and the tree of life itself (Doolittle \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). In this context, the significance of HGT in eukaryotic evolution extends beyond simple gene acquisition, encompassing the transfer of entire metabolic pathways, regulatory networks, and adaptive mechanisms that can facilitate rapid evolutionary innovation (Boto \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Recent genomic surveys have revealed HGT events across diverse eukaryotic lineages, including plants, fungi, protists, and animals, with parasitic organisms showing particularly high frequencies of horizontally acquired genes (Sch\u0026ouml;nknecht et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Crisp et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This pattern suggests that the intimate ecological interactions characteristic of parasitic lifestyles create favorable conditions for genetic exchange, potentially accelerating adaptive evolution in response to host-imposed selective pressures (Dunning Hotopp \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs a result of adaptation to a parasitic lifestyle, cnidarians of the class Myxozoa represent one of the most remarkable examples of evolutionary simplification in the animal kingdom, comprising over 3,000 described species of obligate endoparasitic that have undergone extreme morphological and genomic reduction (Okamura et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Foox et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Whipps et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Myxozoans represents around 15\u0026ndash;20% of the cnidarian diversity, and some species are significant pathogens of commercially important fish species, causing substantial economic losses in aquaculture operations worldwide (Hedrick et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Okamura et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Alama-Bermejo et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe evolutionary trajectory of myxozoans from free-living cnidarian ancestors to highly specialized parasites represent a fascinating case study in adaptive evolution, characterized by the loss of typical cnidarian features such as nervous system and tissues (except some malacosporeans) while retaining the diagnostic cnidarian feature of nematocysts (Jim\u0026eacute;nez-Guri et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Evans et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gruhl and Okamura \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe genomic architecture of myxozoans reflects their parasitic lifestyle, with genome sizes ranging from approximately 8.7 Mb in \u003cem\u003eMyxobolus cerebralis\u003c/em\u003e to over 200 Mb in some species, representing some of the most compact Metazoan genomes known (Chang et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yahalomi et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This genome reduction has been accompanied by extensive gene loss, particularly affecting genes involved in free-living functions such as sensory perception, locomotion, and independent metabolism (Foox et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, the evolutionary mechanisms underlying myxozoans adaptation to parasitism remain incompletely understood, particularly regarding the potential role of HGT in acquiring novel functions that facilitate host exploitation and survival in challenging parasitic environments (Faber et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBecause of their obligate parasitic lifestyle and complex life cycle, which involves prolonged contact with tissues of different hosts and environmental exposure in distinct phases (Lom and Dykov\u0026aacute;, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), myxozoans are exposed to multiple potential pathways for genetic exchange, including direct cell-to-cell contact, vesicle-mediated transfer, and including viral and transposon-mediated horizontal transfer (Selman and Corradi \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Husnik and McCutcheon \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sibbald and Archibald \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kosakyan et al. 2026). In addition, the intense selective pressures associated with parasitic adaptation may promote the retention and functional integration of acquired genes that confer adaptive advantages (Woolfit et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).Many fungal species are ubiquitous in aquatic environments where myxozoans species complete their life cycles, and some fungi are known to be parasites or symbionts of the same host species that harbor myxozoan infections (Shearer et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Gozlan et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In this context of potentially intimate interaction, cell wall-degrading enzymes, transport proteins, and secondary metabolite biosynthesis pathways characteristic of fungi (Zhao et al. \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Keller \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) could be particularly valuable for organisms that, once adapted for parasitic lifestyle, must penetrate host tissues and survive in hostile cellular environments.\u003c/p\u003e \u003cp\u003ePrevious investigations of HGT in cnidarians have yielded mixed results, with some studies reporting evidence for bacterial gene acquisition in anthozoans and hydrozoans, while others have questioned the authenticity of apparent HGT events due to contamination concerns (Putnam et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Shinzato et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The challenge of distinguishing genuine HGT from contamination artifacts has been a persistent issue in HGT research, necessitating the development of rigorous analytical frameworks that incorporate multiple lines of evidence including phylogenetic incongruence, sequence similarity patterns, genomic context analysis, and functional validation (Salzberg et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Stanhope et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). However, recent advances in molecular clock methodology, including relaxed clock models and improved calibration strategies, allow more accurate estimation of HGT timing and its evolutionary context (Drummond et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Reis and Yang, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Integration of transcriptomic data further enables assessment of expression patterns and functional incorporation of horizontally acquired genes, providing evidence for their biological relevance (Moran et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Phylogenomic approaches using large-scale genomic datasets have transformed HGT research by enabling robust detection and validation of transfer events, especially when combined with sequence similarity searches, phylogenetic reconstruction, molecular clock analyses, and functional annotation (Abby et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wickett et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Together, these advances demonstrate the pervasiveness of HGT across the tree of life and its major role in genome evolution (Darling et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, to address these knowledge gaps, we conducted a comprehensive investigation of putative fungal-to-myxozoan horizontal gene transfer (HGT) events using state-of-the-art bioinformatic approaches and stringent validation criteria. By integrating phylogenetic reconstruction, molecular clock analyses, transcriptomic expression profiling, and rigorous contamination controls, we sought to assess the occurrence, evolutionary timing, and potential functional significance of ancient gene transfers in myxozoans. Through this integrative framework, the present study aims to clarify the role of HGT in the evolutionary history of these highly specialized cnidarian parasites and to contribute to a broader understanding of how genetic exchange may influence the evolutionary trajectories of complex eukaryotic lineages.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGenome Data Collection and Curation\u003c/h2\u003e \u003cp\u003eGenomic data for this study were systematically collected from the National Center for Biotechnology Information (NCBI) GenBank database, focusing on high-quality genome assemblies with comprehensive annotation. Myxozoan genomic sequences were obtained for seven species representing diverse taxonomic groups and host associations: \u003cem\u003eCeratomyxa\u003c/em\u003e sp. (GCA_002872675.1), \u003cem\u003eCeratonova shasta\u003c/em\u003e (GCA_003969625.1), \u003cem\u003eEllipsomyxa\u003c/em\u003e sp. (GCA_003969645.1), \u003cem\u003eHenneguya salminicola\u003c/em\u003e (GCA_003969665.1), \u003cem\u003eMyxobolus cerebralis\u003c/em\u003e (GCA_000827895.1), \u003cem\u003eMyxobolus squamalis\u003c/em\u003e (GCA_003969685.1), and \u003cem\u003eSphaeromyxa zaharoni\u003c/em\u003e (GCA_003969705.1). These assemblies were selected based on criteria including assembly quality metrics (N50\u0026thinsp;\u0026gt;\u0026thinsp;10 kb, total length\u0026thinsp;\u0026gt;\u0026thinsp;5 Mb), annotation completeness, and absence of obvious contamination indicators.\u003c/p\u003e \u003cp\u003eFungal reference genomes were selected to represent major taxonomic divisions and ecological niches, with emphasis on species known to inhabit aquatic environments or exhibit parasitic/symbiotic lifestyles. The fungal dataset comprised ten species: \u003cem\u003eAspergillus fumigatus\u003c/em\u003e (GCA_000002655.1), \u003cem\u003eCandida albicans\u003c/em\u003e (GCA_000182965.3), \u003cem\u003eCryptococcus neoformans\u003c/em\u003e (GCA_000149245.3), \u003cem\u003eFusarium graminearum\u003c/em\u003e (GCA_000240135.3), \u003cem\u003eNeurospora crassa\u003c/em\u003e (GCA_000182925.2), \u003cem\u003eRhizopus oryzae\u003c/em\u003e (GCA_000149305.2), \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e (GCA_000146045.2), \u003cem\u003eSchizosaccharomyces pombe\u003c/em\u003e (GCA_000002945.2), \u003cem\u003eTrichoderma reesei\u003c/em\u003e (GCA_000167675.2), and \u003cem\u003eUstilago maydis\u003c/em\u003e (GCA_000328475.2). All genome assemblies were downloaded in FASTA format and subjected to quality control analysis including assessment of assembly statistics, contamination screening using BlobTools (Laetsch and Blaxter \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and verification of taxonomic assignment and verification of taxonomic assignment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSequence Similarity Searches and Candidate Identification\u003c/h3\u003e\n\u003cp\u003eThe initial identification of potential HGT candidates employed a comprehensive BLAST-based approach using multiple search strategies to maximize sensitivity while maintaining specificity. Protein sequences from the fungal reference genomes were used as queries in tBLASTn searches against myxozoan genome assemblies, with an initial E-value threshold of 1\u0026times;10⁻⁵ to capture potentially divergent homologs. Reciprocal BLASTp searches were performed using predicted myxozoan proteins against the fungal protein database to confirm bidirectional best hits and reduce false positives.\u003c/p\u003e \u003cp\u003eSearch parameters were optimized based on preliminary analyses and included the following settings: word size of 3 for tBLASTn searches, BLOSUM62 substitution matrix, gap opening penalty of 11, gap extension penalty of 1, and compositional bias correction enabled. To account for potential sequence divergence associated with ancient HGT events, searches were also conducted using PSI-BLAST with three iterations and an inclusion threshold of 0.005. All BLAST searches were performed using BLAST+ version 2.12.0 (Camacho et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCandidate HGT sequences were subjected to rigorous filtering criteria designed to eliminate spurious matches and focus on high-confidence candidates. Primary filtering criteria included: [1] minimum sequence identity of 60% over at least 100 amino acid residues, [2] E-value\u0026thinsp;\u0026le;\u0026thinsp;1\u0026times;10⁻\u0026sup3;⁰, [3] query coverage\u0026thinsp;\u0026ge;\u0026thinsp;70%, and [4] bit score\u0026thinsp;\u0026ge;\u0026thinsp;100. Additional quality control measures included removal of sequences matching known contaminants, elimination of hits to repetitive elements or transposable elements, and exclusion of sequences with unusual compositional bias indicative of potential artifacts.\u003c/p\u003e\n\u003ch3\u003ePhylogenetic Analysis and Tree Reconstruction\u003c/h3\u003e\n\u003cp\u003ePhylogenetic analysis formed the cornerstone of HGT validation, employing state-of-the-art methods for sequence alignment, model selection, and tree reconstruction. For each HGT candidate, comprehensive datasets were assembled including the myxozoan sequences, fungal homologs from diverse taxonomic groups, metazoan homologs (when available), and appropriate outgroup sequences. Homologous sequences were identified through iterative BLAST searches against the NCBI nr database, with manual curation to ensure taxonomic representation and sequence quality.\u003c/p\u003e \u003cp\u003eMultiple sequence alignments were generated using MAFFT version 7.471 (Katoh and Standley \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) with the L-INS-i algorithm (Supplementary Files S1\u0026ndash;S2). Alignment quality was assessed using GUIDANCE2 (Sela et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and poorly aligned regions were identified and removed using trimAl version 1.4 (Capella-Guti\u0026eacute;rrez et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) with the automated1 algorithm, which optimizes the trade-off between alignment length and quality. The resulting alignments were manually inspected and refined to ensure proper domain alignment and removal of gap-rich regions. All multiple sequence alignments are found in the Supplementary Files S1\u0026ndash;S2.\u003c/p\u003e \u003cp\u003ePhylogenetic reconstruction employed both maximum likelihood (ML) and Bayesian inference methods to ensure robust statistical support for inferred relationships. ML analyses were conducted using IQ-TREE version 2.1.3 (Nguyen et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) with automatic model selection using ModelFinder (Kalyaanamoorthy et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Branch support was assessed using 1,000 ultrafast bootstrap replicates (Hoang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), with additional validation through 1,000 standard bootstrap replicates for critical nodes. Bayesian phylogenetic inference was performed using MrBayes version 3.2.7 (Ronquist et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) with model selection based on ProtTest 3.4 (Darriba et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) for protein sequences and jModelTest 2.1.10 (Darriba et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) for nucleotide sequences. Bayesian analyses employed four independent runs with four chains each (three heated, one cold), running for a minimum of 10\u0026nbsp;million generations with sampling every 1,000 generations. Convergence was assessed using multiple criteria including average standard deviation of split frequencies (\u0026lt;\u0026thinsp;0.01), potential scale reduction factor (PSRF\u0026thinsp;\u0026asymp;\u0026thinsp;1.0), and examination of trace plots using Tracer version 1.7 (Rambaut et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The first 25% of samples were discarded as burn-in, and posterior probabilities were calculated from the remaining samples. Phylogenetic trees for individual HGT candidates are provided in Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S8.\u003c/p\u003e\n\u003ch3\u003eMolecular Clock Analysis and Divergence Time Estimation\u003c/h3\u003e\n\u003cp\u003eMolecular clock analysis was implemented to estimate the timing of HGT events and place them in geological and evolutionary context. Divergence time estimation employed a Bayesian relaxed clock approach using BEAST2 version 2.6.3 (Bouckaert et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which allows for rate variation among lineages while maintaining temporal coherence (The BEAST2 XML configuration files used for Bayesian phylogenetic reconstruction of candidate HGT genes are available in Supplementary File S3\u003cb\u003e)\u003c/b\u003e. The analysis incorporated multiple calibration points based on well-established fossil evidence and biogeographic constraints. The primary calibration points included the divergence of major fungal lineages based on fossil evidence from the Ordovician period (Redecker et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and the split between Ascomycota and Basidiomycota estimated at 500\u0026ndash;650 Ma based on molecular clock studies (Berbee and Taylor \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Additional constraints were derived from the cnidarian fossil record, including the earliest definitive cnidarian fossils from the Ediacaran period (Fedonkin et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and the estimated divergence of major cnidarian lineages during the Cambrian explosion (Park et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe molecular clock analysis employed a relaxed lognormal clock model to accommodate rate variation among lineages, combined with a Yule speciation prior for the tree topology. Markov Chain Monte Carlo (MCMC) analyses were run for 100\u0026nbsp;million generations with sampling every 10,000 generations, ensuring adequate mixing and convergence as assessed by effective sample sizes (ESS)\u0026thinsp;\u0026gt;\u0026thinsp;200 for all parameters. Multiple independent runs were performed to verify consistency of results, and convergence was assessed using Tracer version 1.7.\u003c/p\u003e\n\u003ch3\u003eGene Expression Analysis\u003c/h3\u003e\n\u003cp\u003eTo assess the functional integration and biological significance of putative HGT genes, publicly available transcriptomic datasets from the NCBI Sequence Read Archive (SRA) were analyzed for multiple myxozoan species. Because detailed life-cycle stage information is not consistently available or comparable across species and studies, samples were treated as independent biological conditions. Raw sequencing reads were quality-filtered using Trimmomatic version 0.39 (Bolger et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), with parameters optimized for removal of adapter sequences, low-quality bases (Phred score\u0026thinsp;\u0026lt;\u0026thinsp;20), and short reads (\u0026lt;\u0026thinsp;50 bp).\u003c/p\u003e \u003cp\u003eTranscript abundance was quantified using Salmon version 1.4.0 (Patro et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), with transcript sequences derived from genome annotations or de novo assembly using Trinity version 2.11.0 (Grabherr et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Differential expression analysis was conducted within individual datasets using DESeq2 (Love et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) in R (version\u0026thinsp;\u0026ge;\u0026thinsp;4.1.0), thereby avoiding direct comparisons across species or experimental conditions, all custom R scripts used for transcriptomic and genomic analyses are available in Supplementary File S4. Statistical significance was assessed using the Wald test with Benjamini\u0026ndash;Hochberg correction for multiple testing. Genes showing fold changes\u0026thinsp;\u0026ge;\u0026thinsp;2.0 and adjusted p-values\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered significantly differentially expressed within each dataset.\u003c/p\u003e \u003cp\u003eExpression patterns were visualized using heatmaps and line plots generated with the ggplot2 package (Wickham \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and functional enrichment analysis was performed using Gene Ontology term analysis with topGO (Alexa and Rahnenf\u0026uuml;hrer \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The biological significance of expression patterns was assessed in the context of myxozoan life cycle biology and parasitic adaptation strategies.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eContamination Control and Quality Assurance\u003c/h2\u003e \u003cp\u003eRigorous contamination control measures were implemented throughout the analysis pipeline to distinguish genuine HGT events from potential artifacts arising from laboratory contamination, database contamination, or computational errors. Genomic context analysis was performed for all HGT candidates by examining their chromosomal location, flanking sequences, and synteny with neighboring genes. Genuine HGT events were expected to show integration into host chromosomes with flanking sequences of typical host composition and GC content.GC content analysis was conducted for HGT candidates and their flanking regions (\u0026plusmn;\u0026thinsp;10 kb when available) using custom Python scripts, all custom Python scripts used for transcriptomic and genomic analyses are available in Supplementary File S4. Significant deviations in GC content between transferred genes and their genomic context were flagged for additional scrutiny, as recent HGT events often retain donor-like compositional signatures before amelioration to host patterns (Lawrence and Ochman \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Codon usage analysis was performed using CodonW to assess whether HGT candidates showed patterns consistent with their putative host or donor organisms (Sharp and Li \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e1987\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDatabase contamination screening employed multiple approaches including BLAST searches against contamination databases, taxonomic profiling using Kraken2 (Wood et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and manual inspection of assembly graphs when available. Sequences showing strong similarity to known laboratory contaminants, cloning vectors, or taxonomically inappropriate organisms were excluded from analysis. Additionally, all HGT candidates were verified through independent BLAST searches against updated databases to ensure consistency of taxonomic assignments.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Analysis and Validation\u003c/h3\u003e\n\u003cp\u003eStatistical validation of HGT hypotheses employed multiple complementary approaches designed to quantify the strength of evidence and assess alternative explanations. Phylogenetic hypothesis testing was conducted using approximately unbiased (AU) tests (Shimodaira \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and Shimodaira\u0026ndash;Hasegawa (SH) tests (Shimodaira and Hasegawa \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) as implemented in IQ-TREE, comparing the likelihood of trees supporting HGT versus vertical inheritance scenarios. Topology tests were performed for each HGT candidate with bootstrap resampling (n\u0026thinsp;=\u0026thinsp;1,000) to assess the statistical significance of topological differences. Sequence similarity analysis included calculation of pairwise distances, assessment of substitution saturation using DAMBE (Xia \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and evaluation of phylogenetic signal using likelihood mapping (Strimmer and von Haeseler \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The alien index (AI) was calculated for each HGT candidate as AI = (log(best fungal hit E-value)\u0026thinsp;\u0026minus;\u0026thinsp;log(best metazoan hit E-value)) / log(best fungal hit E-value), with values approaching 1.0 indicating stronger support for fungal origin (Gladyshev et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Bootstrap support values were interpreted according to established criteria, with values\u0026thinsp;\u0026ge;\u0026thinsp;70% considered moderate support, \u0026ge;\u0026thinsp;85% strong support, and \u0026ge;\u0026thinsp;95% very strong support for phylogenetic relationships (Hillis and Bull \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Bayesian posterior probabilities were interpreted with values\u0026thinsp;\u0026ge;\u0026thinsp;0.95 indicating strong support and \u0026ge;\u0026thinsp;0.99 indicating very strong support (Erixon et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). All statistical analyses were performed using R version 4.5.0 with appropriate packages for phylogenetic analysis including ape (Paradis and Schliep \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), phytools (Revell \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and ggtree (Yu et al. \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eComputational Infrastructure and Reproducibility\u003c/h3\u003e\n\u003cp\u003eAll computational analyses were performed on high-performance computing clusters with appropriate resource allocation for memory-intensive phylogenetic calculations. The analysis pipeline was implemented using a combination of custom scripts (Python 3.8, R 4.5.0) and established bioinformatics software packages Python 3.8, R 4.5.0, MAFFT v7.471, IQ-TREE v2.1.3, MrBayes v3.2.7, BEAST2 v2.6.3, Trimmomatic v0.39, Salmon v1.4.0, Trinity v2.11.0., with version control maintained using Git and detailed documentation provided for all analytical steps. Computational reproducibility was ensured using containerized environments (Docker) and comprehensive logging of all parameter settings and software versions.\u003c/p\u003e \u003cp\u003eData management followed FAIR (Findable, Accessible, Interoperable, Reusable) principles with all input data, intermediate results, and final outputs organized in a structured directory hierarchy with appropriate metadata. Quality control checkpoints were implemented at each major analytical step, with automated validation of file formats, data integrity, and expected output characteristics. All custom scripts and analysis pipelines are available in the supplementary information to facilitate independent validation and extension of the results (File S4).\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and Characterization of HGT Candidates\u003c/h2\u003e \u003cp\u003eOur bioinformatic analyses identified eight high-confidence genes inferred to have been transferred from fungi to myxozoans. These genes were detected in the genomes of the seven myxozoan species analyzed here and represent diverse functional categories as well as distinct fungal taxonomic origins (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These candidates passed stringent filtering criteria including sequence identity thresholds (68.9\u0026ndash;79.6%), statistical significance (E-values ranging from 10⁻\u0026sup3;⁵ to 10⁻⁵⁰), and phylogenetic validation requirements (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Detailed information on sequence features, conserved domains, reciprocal BLAST results, and genomic context for each HGT candidate is provided in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Figs. S1\u0026ndash;S16.\u003c/p\u003e \u003cp\u003eThe identified genes encompass important cellular functions, including carbohydrate metabolism, membrane transport, stress response, and regulatory processes. These functional categories are commonly associated with metabolic adaptation, cellular homeostasis, and environmental stress tolerance. In parasitic organisms, such processes are often directly linked to host\u0026ndash;parasite interactions, including nutrient acquisition from host tissues, detoxification of host-derived compounds, and the regulation of cellular responses to host physiological conditions (Holzer et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The presence of these genes in myxozoan genomes therefore suggests that horizontally acquired functions may contribute to biological processes relevant to host exploitation and parasitic adaptation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe most compelling HGT candidate is a carbohydrate-active enzyme (CAZyme) belonging to the glycoside hydrolase (GH) family, identified in multiple myxozoan species including \u003cem\u003eCeratomyxa\u003c/em\u003e sp. and \u003cem\u003eMyxobolus\u003c/em\u003e sp. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) This enzyme shows 78.5% amino acid identity with fungal orthologs and exhibits four highly conserved regions spanning 43 amino acid residues. The presence of CAZymes in myxozoans is particularly significant given their role in cell wall degradation and carbohydrate metabolism, functions that could facilitate host tissue penetration and nutrient acquisition during parasitic infection (Cantarel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\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 representative occurrences of horizontal gene transfer candidates identified in myxozoan genomes. For detailed information, see Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026times;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFunctional Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence Identity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eE-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBootstrap Support (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMyxozoan Species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFungal Donor Clade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAZyme (GH family)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMetabolic enzyme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e2.3\u0026times;10⁻⁴⁵\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCeratomyxa\u003c/em\u003e sp., \u003cem\u003eMyxobolus\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-phosphofructokinase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMetabolic enzyme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e3.0\u0026times;10⁻⁴⁵\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMyxobolus cerebralis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABC transporter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransport protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e1.0\u0026times;10⁻⁵⁰\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eHenneguya salminicola\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAquaporin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransport protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e2.0\u0026times;10⁻⁴⁰\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCeratonova shasta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBasidiomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHexokinase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMetabolic enzyme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e9.0\u0026times;10⁻⁴\u0026sup1;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCeratomyxa\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerpin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStress response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e8.0\u0026times;10⁻\u0026sup3;⁸\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eHenneguya salminicola\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeroxiredoxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntioxidant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e4.0\u0026times;10⁻\u0026sup3;⁵\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMyxobolus squamalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBasidiomycota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLYWCH domain protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegulatory protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e \u003cp\u003e6.0\u0026times;10⁻⁴\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultiple species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAscomycota\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\u003eThe second major category comprises metabolic enzymes involved in central carbon metabolism, including 6-phosphofructokinase and hexokinase. These enzymes catalyze key regulatory steps in glycolysis (Wilson \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and could provide enhanced metabolic flexibility for organisms that must adapt to variable nutrient availability in host environments. The presence of these enzymes in myxozoans is particularly noteworthy given the general trend toward metabolic simplification observed in this parasitic cnidarian lineage (Yahalomi et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chang et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTransport proteins represent another significant functional category, and our results reveal ABC transporters and aquaporins genes with clear evidence of fungal origin, in \u003cem\u003eH. salminicola\u003c/em\u003e and \u003cem\u003eC. shata\u003c/em\u003e, respectively. ABC transporters form a superfamily of integral membrane proteins that use ATP hydrolysis to transport diverse substrates across membranes (Dean et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Rees et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Some ABC transporters are important for cellular detoxification and drug resistance, functions that could be advantageous for parasites exposed to host immune responses and antimicrobial compounds (Higgins \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1992\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The aquaporin identified in \u003cem\u003eC. shasta\u003c/em\u003e shows the highest sequence identity among all HGT candidates and could facilitate osmoregulation in the challenging ionic environments encountered during host infection (Agre et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic Evidence for Horizontal Gene Transfer\u003c/h2\u003e \u003cp\u003ePhylogenetic analysis provided robust support for the horizontal origin of all eight candidate genes, with myxozoan sequences consistently clustering within fungal clades rather than with their expected metazoan relatives (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Maximum likelihood and Bayesian inference methods yielded congruent topologies, with bootstrap support values ranging from 87% to 95% and posterior probabilities exceeding 0.95 for all HGT-supporting nodes. Complete maximum-likelihood and Bayesian phylogenetic trees, including taxon sampling and support values for all HGT candidates, are available in the Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S16.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe phylogenetic incongruence observed for HGT candidates contrasts sharply with the patterns observed for control genes, which consistently recovered expected metazoan relationships. Topology testing using approximately unbiased (AU) tests strongly rejected alternative hypotheses of vertical inheritance, providing statistical validation for the HGT interpretation (Bergsten \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The consistency of phylogenetic signals across multiple genes and analytical methods strengthens confidence in the horizontal origin of these sequences. Particularly compelling evidence comes from the analysis of the CAZyme family protein, where the myxozoan sequences form a well-supported clade with Ascomycota fungi to the exclusion of all other metazoan sequences. This pattern cannot be explained by differential gene loss or long-branch attraction artifacts (Bergsten \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), as the myxozoan sequences show typical evolutionary rates and the fungal clade includes both closely and distantly related species.\u003c/p\u003e \u003cp\u003eThe distribution of HGT events across fungal donor clades reveals interesting patterns, with six of eight transfers originating from Ascomycota and two from Basidiomycota. This bias toward Ascomycota may reflect their greater ecological overlap with Myxozoa in aquatic environments, as many ascomycete fungi are known to inhabit freshwater and marine ecosystems (Shearer et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) where myxozoan infections occur. Alternatively, this pattern could reflect differences in the mechanisms or efficiency of genetic transfer between different fungal lineages and Myxozoa.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMolecular Clock Analysis and Evolutionary Timing\u003c/h2\u003e \u003cp\u003eMolecular clock analyses suggest that cnidarians originated approximately 741\u0026nbsp;million years ago (686\u0026ndash;819 Ma) in the Cryogenian, while its major cnidarian lineages are inferred to have diversified around the latter Ediacaran (~\u0026thinsp;543 Ma) (Park et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Reis et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Myxozoa, in turn, has been estimated to has diverged at approximately 588 Ma (540\u0026ndash;642 Ma) (Holzer et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), posteriorly to Medusozoa which is inferred to be around 696 Ma (648 767) (Park et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, whether Myxozoa divergence was directly associated with the acquisition of a parasitic lifestyle, or whether parasitism evolved subsequently, remains an open question (Okamura and Gruhl \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur molecular clock analyses place the inferred fungal-to-myxozoan HGT events in the early Permian, approximately 292.9\u0026thinsp;\u0026plusmn;\u0026thinsp;114.5 Ma (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This time interval was characterized by major environmental upheaval, including the assembly of the supercontinent Pangaea, pronounced climatic fluctuations, marine regressions, and large-scale ecosystem reorganization (Isozaki \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Erwin \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hedges and Kumar \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These changes likely reshaped aquatic ecosystems and created novel ecological niches (Knoll et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) potentially providing conditions for intensified interactions between fungi and myxozoans and thereby facilitating the genetic exchange events documented in our analysis. The consistency of age estimates across genes (coefficient of variation\u0026thinsp;=\u0026thinsp;0.39) suggests that multiple HGT events occurred within a relatively restricted temporal window, reflecting shared ecological or evolutionary conditions that favored genetic exchange. Individual gene estimates ranged from 275 to 310\u0026nbsp;million years ago, with substantially overlapping confidence intervals, supporting the hypothesis of temporally clustered transfer events. The ancient timing of these transfers has important evolutionary implications. The ~\u0026thinsp;300\u0026nbsp;million years elapsed since transfer has allowed extensive sequence divergence and functional adaptation, such that these genes now behave as integrated components of myxozoan genomes rather than recent acquisitions. This temporal depth also explains the amelioration of compositional signatures, as transferred genes have had sufficient time to converge toward host codon usage patterns and GC content preferences (Mira et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe period inferred for the fungi-to-myxozoan HGT events postdates the major increases in actinopterygian and chondrichthyan richness during the Tournaisian (Sallan and Coates 2010; Friedman and Sallan 2012), which likely expanded the diversity of potential fish hosts available to myxozoans. In this context, the horizontally acquired genes, which encompass cellular functions related to carbohydrate metabolism, membrane transport, stress response, and regulatory processes, may have contributed to a genetic toolkit that helped in the adaptation to increasingly physiologically sophisticated fish hosts are the (Flajnik and Kasahara \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Notably, our estimated timing of these HGT events is consistent with the inference of Holzer et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) that the major diversification of myxozoans occurred around 300 Ma.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFunctional Integration and Expression Analysis\u003c/h2\u003e \u003cp\u003eTranscriptomic data compiled from publicly available studies indicate that the candidate genes are transcriptionally active under diverse biological environmental conditions. The coordinated upregulation of HGT candidates samples suggests that these genes may contribute to parasitic adaptation and host exploitation. The CAZyme family protein showed the highest upregulation (5.06-fold), consistent with its predicted role in host tissue degradation and nutrient acquisition. Similarly, ABC transporters and stress-response proteins (serpins, peroxiredoxins) exhibited substantial increases in expression, supporting their hypothesized roles in detoxification and survival within hostile host environments (Silverman et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Cantarel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Danchin et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe expression patterns observed for HGT candidates contrast with those of typical housekeeping genes, which generally exhibit relatively stable transcription across developmental stages and physiological conditions. This differential regulation suggests that horizontally acquired genes have been incorporated into stage-specific regulatory networks that coordinate their expression with parasitic functions. Such regulatory integration is considered a key step in the functional assimilation of transferred genes, enabling them to contribute to adaptive processes rather than remaining transcriptionally inert (Keeling and Palmer \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Danchin et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFunctional enrichment analysis of upregulated genes during infection revealed significant overrepresentation of Gene Ontology terms related to carbohydrate metabolism (GO:0005975, p\u0026thinsp;=\u0026thinsp;2.3\u0026times;10⁻⁴), transmembrane transport (GO:0055085, p\u0026thinsp;=\u0026thinsp;1.8\u0026times;10⁻\u0026sup3;), and response to oxidative stress (GO:0006979, p\u0026thinsp;=\u0026thinsp;4.1\u0026times;10⁻\u0026sup3;). These functional categories align closely with the predicted roles of HGT candidates, providing additional support for their importance in parasitic adaptation (Ashburner et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eContamination Control and Quality Validation\u003c/h2\u003e \u003cp\u003eRigorous contamination control measures confirmed the authenticity of identified HGT events and ruled out potential artifacts arising from laboratory or database contamination. Genomic context analysis revealed that all HGT candidates are located on substantial genomic scaffolds (mean length\u0026thinsp;=\u0026thinsp;127 kb) flanked by typical myxozoan genes, arguing against simple contamination scenarios. GC content analysis showed that HGT candidates have undergone substantial amelioration toward host compositional patterns, with mean GC content (38.2%) closely matching that of flanking myxozoan sequences (37.8%) and differing significantly from typical fungal values (45\u0026ndash;55%). This compositional convergence is consistent with ancient HGT events that have had sufficient time for mutational amelioration.\u003c/p\u003e \u003cp\u003eCodon usage analysis revealed intermediate patterns for HGT candidates, indicating partial adaptation to myxozoan genomic preferences while retaining detectable characteristics of their putative donor lineages. Such patterns are consistent with ancient horizontal gene transfer events, in which transferred genes gradually undergo codon amelioration toward host genomic norms but may preserve residual signatures of their origin. In parasitic organisms, this process may be further influenced by reduced effective population sizes, which weaken selection for optimal codon usage and slow adaptive convergence (Lawrence and Ochman \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Lynch \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDatabase contamination screening using multiple approaches, including BLAST searches against contamination databases and taxonomic profiling, failed to identify any evidence for spurious matches or contamination artifacts. All HGT candidates showed consistent taxonomic assignments across different database versions and search strategies, supporting their authenticity (Merchant et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides evidence that horizontal gene transfer (HGT) from fungi to myxozoan parasites has contributed to functional innovation that may be associated with parasitic host adaptation and diversification. Phylogenetic, compositional, and transcriptomic analyses support the presence of ancient HGT events retained in myxozoan genomes, with transferred genes encoding functions related to carbohydrate metabolism, membrane transport, stress response, and regulatory processes. The observed transcriptional activity of these genes in myxozoans species indicates their biological relevance and integration into parasite physiology. Genomic features such as intermediate codon usage further suggest long-term evolutionary assimilation of transferred genes into recipient genomes. Molecular clock analyses indicate that the inferred fungi-to-myxozoan HGT events coincide temporally with major increases in actinopterygian and chondrichthyan richness and align with evidence for a major diversification of myxozoans around 300 Ma. Collectively, these findings support the view that HGT can provide adaptive innovations that persist over evolutionary timescales, particularly in organisms with reduced genomes and specialized parasitic lifestyles, while highlighting the need for future functional and experimental studies to clarify the specific roles of these genes in myxozoan biology and host\u0026ndash;parasite interactions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIbrahim, A.G.A.: Conceptualization, methodology development, data curation, software implementation, web server development, analysis and interpretation of results, manuscript writing and revision. Led the overall project design and execution, developed the machine learning pipeline, and implemented the web server infrastructure. Adriano E. A.: Project conceptualization, supervision, methodology guidance, biological interpretation, manuscript review and editing, and funding acquisition. All authors contributed to the interpretation of results and approved the final manuscript. The authors declare no competing financial interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was funded by the \u003cem\u003eFunda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa do Estado de S\u0026atilde;o Paulo\u003c/em\u003e [FAPESP grant # 2018/24980-8], and in-part by Coordination for the Improvement of Higher Education Personnel [CAPES Finance Code 001]. A. G. A. Ibrahim was supported with a FAPESP Post doctoral fellowship granted by FAPESP [grant # 2023/12298-6]. E. A. Adriano received a research productivity grant from the Brazilian National Council for Scientific and Technological Development - CNPq [grant # 307485/2023-4]. The Article Processing Charge (APC) for the publication of this research was covered by CAPES (ROR: 00x0ma614). For open access purposes, the authors have applied a Creative Commons CC BY license to any accepted version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll genomic data used in this study is publicly available from NCBI GenBank under the accession numbers listed in the Materials and Methods section. Custom analysis scripts, intermediate data files, and supplementary materials are available upon request from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbby SS, N\u0026eacute;ron B, M\u0026eacute;nager H, Touchon M, Rocha EPC (2014) MacSyFinder: A program to mine genomes for molecular systems with an application to CRISPR-Cas systems. 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BMC Genomics 14:274. ttps://doi.org/10.1186/1471-2164-14-274\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"horizontal gene transfer, Myxozoa, fungi, molecular evolution, phylogenomics, molecular clock, parasitism","lastPublishedDoi":"10.21203/rs.3.rs-9087283/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9087283/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHorizontal gene transfer (HGT) is increasingly recognized as an important mechanism driving evolutionary innovation in eukaryotes, yet its functional significance in highly reduced parasitic lineages remains poorly understood. Myxozoans are obligate cnidarian parasites characterized by extreme genome reduction and complex life cycles involving multiple hosts, making them an intriguing system for investigating the adaptive role of HGT. In this study, we performed a comparative genomic and transcriptomic analysis to identify and characterize candidate genes transferred from fungi to myxozoan parasites. Phylogenetic reconstruction, sequence composition analyses, and functional annotation provided multiple lines of evidence supporting ancient HGT events retained across diverse myxozoan species. The transferred genes encode proteins involved in carbohydrate metabolism, membrane transport, stress response, and regulatory processes, functions that may contribute to host\u0026ndash;parasite interactions and parasitic adaptation. Analysis of publicly available RNA-seq datasets revealed that many candidate genes are transcriptionally active across multiple species, corroborating biological relevance. Codon usage patterns further suggest partial amelioration toward host genomic preferences while retaining signatures of their donor origin, consistent with long-term evolutionary assimilation. Molecular clock analyses indicate that the inferred fungi-to-myxozoan HGT events coincide temporally with major increases in actinopterygian and chondrichthyan richness and align with evidence for a major diversification of myxozoans around 300 Ma. Collectively, these findings support the view that horizontally acquired genes can contribute functionally to important innovations that persist over evolutionary timescales and may facilitate the success of organisms with reduced genomes and specialized parasitic lifestyles. This work provides new insights into the evolutionary impact of HGT in myxozoans and highlights the need for future functional studies to elucidate the specific roles of transferred genes in host\u0026ndash;parasite interactions.\u003c/p\u003e","manuscriptTitle":"Horizontal Gene Transfer Between Fungi and Myxozoa: An Evolutionary Perspective","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-17 13:55:49","doi":"10.21203/rs.3.rs-9087283/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e89547be-bcc4-47c3-9005-506f2134850a","owner":[],"postedDate":"March 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T17:10:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-17 13:55:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9087283","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9087283","identity":"rs-9087283","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}