Structural characterization of RLKomes reveals lineage-specific families in oomycetes

Structural characterization of RLKomes reveals lineage-specific families in oomycetes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Structural characterization of RLKomes reveals lineage-specific families in oomycetes Jun Cheng, Xuteng Ye, Yong Pei, Jinding Liu, Zhiyuan Yin, Daolong Dou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9308108/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 Receptor-like kinases (RLKs) are a large family of transmembrane receptors that play central roles in signal perception and transduction in plants. However, their distribution and evolution in oomycetes, which belong to the Stramenopiles lineage, remain largely unexplored. Here, we conducted a systematic proteome-wide survey of RLKomes across 233 stramenopile species, including 179 oomycetes and 54 other stramenopiles. In total, we identified 11357 RLKs (10867 in oomycetes), which are mainly clustered into six core families, with the LRR family accounting for the largest proportion. The remaining five correspond to distinct RLK families present in oomycetes, including the elicitin family, the EGF domain-containing family, and three functionally uncharacterized families. Collectively, our results systematically delineate the distribution patterns and structural diversity of the RLK superfamily in oomycetes. Furthermore, the specialized oomycete RLK database established in this study provides a foundational resource for investigating the evolutionary dynamics and functional mechanisms of these critical signaling molecules. Oomycetes Receptor-like kinases Structural characterization Lineage-specific families Stramenopiles LRR-RLK Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Oomycetes are filamentous microorganisms that include some of the most destructive plant pathogens known to agriculture (Wang et al. 2025 ). Species such as Phytophthora infestans (causal agent of potato late blight), Phytophthora sojae (soybean root rot), and various Pythium and Saprolegnia species pose persistent threats to global food security and aquaculture (Fry. 2008; Judelson et al. 2005). Despite their fungal-like morphology, oomycetes are evolutionarily distinct from true fungi, belonging instead to the Stramenopiles, a diverse supergroup that also includes photosynthetic diatoms and brown algae (Ochrophyta) as well as heterotrophic flagellates (Bigyra) (Jirsova et al. 2024). This phylogenetic placement offers a unique opportunity to investigate how signaling systems have evolved in parallel with pathogenic lifestyles. Receptor-like kinases (RLKs) constitute a major class of signal transduction molecules in plants, characterized by a modular architecture comprising an extracellular ligand-binding domain (ECD), a single transmembrane domain (TM), and an intracellular kinase domain (KD) (Dievart et al. 2020 ). Through ligand-induced activation, RLKs initiate downstream phosphorylation cascades that regulate growth, development, immunity, and environmental adaptation (Ngou et al. 2022 ). Plant RLKs have undergone extensive expansion and diversification, forming one of the largest gene families in plant genomes (Dievart et al. 2020 ). Based on extracellular domain composition, plant RLKs are traditionally classified into multiple subfamilies, including leucine-rich repeat RLKs (LRR-RLKs), lectin RLKs, wall-associated kinases (WAKs), S-domain RLKs, and cysteine-rich RLKs (CRKs), among others (Dievart et al. 2020 ; Ngou et al. 2024 ). This diversification is thought to reflect adaptive pressures associated with terrestrialization, multicellularity, and the need for sophisticated environmental sensing and immune surveillance (Lease et al. 1998 ; Man et al. 2020 ). Among these subfamilies, LRR-RLKs represent the largest and most functionally versatile group (Soltabayeva et al. 2022 ). Their conserved yet structurally flexible LRR motifs enable the perception of chemically diverse ligands (da Silva Dambroz et al. 2023 ), underpinning their central roles in plant innate immunity and developmental signaling (Tang et al. 2017 ; Zipfel et al. 2014). To date, RLK research has been overwhelmingly plant-centric (Brustolini et al. 2017 ). Extensive functional, evolutionary, and genomic analyses have established RLKs as key drivers of terrestrial adaptation (Xu et al. 2024 ), immune surveillance, and symbiotic interactions in land plants, culminating in the construction of comprehensive plant-specific RLK resources such as RLKdb (Yin et al. 2024 -) and metaRLK (Liu et al. 2024 ; Zhang et al. 2026 ). In striking contrast, systematic studies of RLKs in oomycetes remain scarce (Bozkurt et al. 2012 ). Previous studies have shown the presence of LRR-RLKs in oomycetes (Thines. 2018), where they may function as receptors involved in host recognition and pathogenicity (Pei et al. 2024 ; Zhang et al. 2022 ). For other major Stramenopiles lineages, including diatoms and brown algae, RLK repertoires, family classification, and evolutionary origins remain virtually unexplored (Cock et al. 2010 ). Intriguingly, although plant and oomycetes RLKs share similar extracellular architectures, their cytoplasmic kinase domains belong to distinct evolutionary clades, indicative of modular convergent evolution (Diévart et al. 2011 ). This evolutionary decoupling of extracellular sensing and intracellular signaling modules highlights the necessity of lineage-specific RLK classification frameworks. Conventional homology-based approaches, such as BLAST or HMMER, lack sufficient sensitivity to reliably detect distantly related RLKs, resulting in widespread under-annotation or misannotation in oomycete genomes (Denoeud et al. 2024 ; Schulze et al. 2015 ). Recent advances in AI-driven protein structure prediction, including OmegaFold, together with ultra-fast structural comparison tools such as Foldseek, have transformed this landscape (Jumper et al. 2021 ; van Kempen et al. 2024 ). Because protein tertiary structures are substantially more conserved than primary sequences, structure-based strategies offer a powerful avenue for identifying deeply divergent homologs that remain invisible to sequence-based methods (Yu et al. 2025 ). Consequently, a structure-based identification and classification strategy can thus accurately capture divergent yet structurally conserved RLKs in oomycetes. In this study, we integrated large-scale proteomic sampling with structure-based identification to perform a systematic analysis of RLKs across Stramenopiles, with a primary focus on oomycetes. From 233 species, we identified 11357 RLKs and obtained 6 major families via structural clustering (cluster size > 100). Oomycetes harbor significantly expanded RLK repertoires compared to other stramenopiles, driven largely by lineage-specific amplification of LRR-RLKs. Several families, including elicitin-associated RLKs and three families of unknown function, appear oomycete-specific. These findings suggest that oomycete RLKs have undergone independent diversification shaped by pathogenic lifestyles. We further constructed a dedicated oomycetes RLK database integrating sequence, structure, and taxonomic information, providing a foundational resource for evolutionary and functional studies. Results Systematic Identification and Family Classification of RLKs To systematically characterize the repertoire and evolutionary dynamics of receptor-like kinases (RLKs) across Stramenopiles, with a particular emphasis on oomycetes, we implemented a standardized computational workflow integrating multi-source data curation, topology-aware RLK identification, and structure-guided family classification (Fig. 1 ). We first compiled a comprehensive proteome dataset encompassing 233 stramenopile species from NCBI, Ensembl, and CNCB databases, spanning the three major clades Oomycota, Ochrophyta, and Bigyra (Additional file: Table S1 ). For RLK identification, we adopted a topology-aware pipeline that integrates HMMER-based kinase domain annotation with DeepTMHMM-based transmembrane topology prediction as previous reported (Yin et al. 2023 ). Only proteins harboring a single transmembrane domain, an extracellular domain (ECD), and a cytoplasmic kinase domain were retained as bona fide RLKs. This stringent pipeline yielded a total of 11357 RLKs across 232 species, of which 10867 were identified from Oomycota (Fig. 1 ). Taxonomic Distribution of RLKs Across Stramenopiles To contextualize these findings within an evolutionary framework, we reconstructed a species phylogeny using the NCBI Taxonomy Common Tree tool (Fig. 2 A). Our dataset is taxonomically dominated by Oomycota (77%), followed by Ochrophyta (20%) and Bigyra (3%), reflecting broad sampling across stramenopile diversity (Fig. 2 B). At the species level, RLK counts varied substantially, ranging from fewer than 10 to over 100 per genome, with an average of 48 RLKs per species, accounting for ~ 1.2% of the total proteome, a proportion comparable to that reported in plant lineages (Ngou et al. 2024 ). Correlation analysis of log 10 -transformed proteome size and RLK abundance revealed a weak positive association, suggesting that RLK expansion is partially coupled to overall proteome complexity (Fig. 2 C). Inter-clade comparisons further demonstrated that Oomycota species harbored significantly more RLKs (average ~ 67 per species) than Ochrophyta (~ 23 per species) and Bigyra (~ 18 per species), indicative of lineage-specific expansion of RLK families in oomycetes (Fig. 2 D). Within Oomycota, analysis of four core orders, Albuginales, Peronosporales, Pythiales, and Saprolegniales, revealed that Saprolegniales exhibited the highest average RLK count (~ 89 per species), highlighting order-specific patterns in RLK family expansion (Fig. 2 E). Structural Characteristics and Distribution Patterns of Major RLK Families To classify these RLKs into functionally coherent families, we performed structure-guided hierarchical clustering based on ECD structures predicted by OmegaFold. Pairwise structural similarities were quantified via TM-score using Foldseek, followed by two rounds of average-linkage hierarchical clustering. This analysis clustered the 11357 RLKs and designated clusters containing greater than or equal to 100 members as major families. In total, six major families were identified, representing the core RLK groups of Stramenopiles, and these six families collectively account for 87% of all identified RLKs (Fig. 1 and Additional file: Table S2 ). All identified families varied substantially in size and taxonomic breadth, 19 families contained RLKs from only one species, 29 families from 2–5 species, 34 families from 6–10 species, and 51 families from more than 10 species. (Additional file: Table S3 ). To investigate the structural relationships among these six core families, we constructed a protein structural similarity network based on pairwise TM-score comparisons of extracellular domains (ECDs). This analysis revealed that the LRR family (family-1) constitutes the largest and most densely connected cluster, indicative of high sequence conservation within this family. In contrast, the remaining five core families (family-2 to family-6) form smaller, discrete clusters with limited inter-family connectivity, suggesting distinct structural and evolutionary origins (Fig. 3 A). We next examined the three-dimensional folding features of representative ECDs from each core family. Structural analysis revealed distinct spatial architectures among the six families. Family-1 (LRR) adopts a canonical helix-turn-helix repeat fold, a conserved structural hallmark that confers plasticity for diverse ligand recognition; family-4 (elicitin) (Boissy et al. 1999 ; Derevnina et al. 2016 ) and family-6 (EGF) display compact spatial conformations; while family-2, family-3, and family-5 possess unique, previously uncharacterized folding patterns, consistent with their unknown functional roles (Fig. 3 B) (da Silva Dambroz et al. 2023 ; Wang et al. 2025 ). Quantification of family-level abundance across Stramenopiles revealed a highly skewed distribution pattern. The LRR family (family-1) dominates the RLK repertoire, accounting for 50% of all identified RLKs, followed by family-2 (10%), family-3 (9%), family-4 (9%), family-5 (8%), and family-6 (1%) (Fig. 3 C). Together, these six core families comprise 87% of all identified RLKs (Fig. 3 C). To examine the distribution patterns of major RLK families across taxonomic groups, we analyzed the proportional representation of core families across three stramenopile phyla (Oomycota, Ochrophyta, Bigyra) and four oomycete orders (Albuginales, Peronosporales, Pythiales, Saprolegniales) (Fig. 3 D, Additional file: Table S4 ). At the phylum level, the LRR family showed enrichment in Oomycota (54%) compared to Ochrophyta (32%) and Bigyra (28%), while family-2 was overrepresented in Bigyra (19%). The EGF family (family-6) maintained a consistently low proportion across all three phyla (1–2%). Within Oomycota, order-level analysis revealed that the LRR family reached its highest proportion in Peronosporales (56%) and Pythiales (55%), followed by Saprolegniales (48%) and Albuginales (42%). Family-4 (elicitin) was most abundant in Peronosporales (11%) and Pythiales (10%), while family-2 and family-5 showed elevated representation in Saprolegniales (12% and 10%, respectively). Collectively, these six major RLK families exhibited distinct structural features and lineage-specific distribution patterns across Stramenopiles. Construction of a Dedicated Oomycetes RLK Database To facilitate access to the extensive RLK resources generated in this study, we constructed a specialized oomycetes RLK database integrating sequence, structural, and taxonomic information. The database encompasses RLKs from all 233 species and supports hierarchical browsing across five taxonomic levels (phylum to species), enabling comparative analyses across trophic modes and evolutionary lineages (Fig. 4 A). Its cross-trophic coverage characteristic provides dual support of taxonomic and genetic data for studying the association between lifestyle evolution and RLK function. In terms of functional design, the database constructs three core retrieval modules based on "user needs" (Fig. 4 B): (1) Species-specific retrieval supports hierarchical screening of complete RLKome sequences and annotations for specific species; (2) BLASTp-based sequence similarity retrieval enables rapid identification of homologous RLKs and their family affiliation for unknown sequences; (3) Family-specific retrieval supports specialized query and comparative analysis of all identified families, with a primary focus on the six core families. In addition, the database integrates the topological distribution of RLK domains (graphical display) and three-dimensional structural models (predicted by OmegaFold), realizing integrated presentation of "sequence-structure-classification-distribution" data. In terms of tools, we have localized Foldseek, allowing users to perform similarity searches using structure files (PDB); at the same time, we also provide an interactive interface for structural clustering, where users can upload batch protein PDB files to obtain their family classification. This database not only fills the gap of insufficient systematic integration of current Stramenopiles RLK data but also transforms the aforementioned basic research achievements into practical tools, providing key data support for subsequent studies on RLK functional evolution. Discussion RLKs are well-established as central regulators of development, environmental sensing, and immunity in plants. Recent studies reveal that oomycetes, including major pathogens, also possess RLKs that play crucial roles in development, host interaction, and environmental adaptation. In Phytophthora sojae , a comprehensive functional characterization of the LRR-RLK family revealed diverse roles of LRR-RLKs in modulating development, interaction with soybean, and responses to diverse environmental factors (Si et al. 2021 ). Beyond general development, specific RLKs have evolved to sense host-specific cues; for instance, PsIRK1 and PsIRK2 were recently identified as direct chemoreceptors for soybean isoflavones, mediating zoospore chemotaxis via G protein signaling (Ji et al. 2025 ), while SSRK1 functions as a sterol-sensing RLK that cooperates with elicitin to detect host-derived sterols, linking nutrient perception to pathogenic development (Pei et al. 2024 ). Furthermore, PsRLK6 has been shown to play a dual role, acting as both an essential regulator of oospore development and a pathogen-associated molecular pattern (PAMP) that triggers pattern-triggered immunity in plants (Pei et al. 2023 ). Despite this functional significance, a comprehensive, genome-wide inventory of RLKs across the diverse oomycete lineage has been conspicuously absent, largely due to the limitations of sequence-based homology searches in detecting highly divergent members. Here, using a topology-aware identification pipeline combined with structure-guided hierarchical clustering, we analyzed 179 oomycete proteomes and identified 10,867 RLKs. These were systematically classified based on extracellular domain architecture, with six core families predominating. Four of these core families, elicitin-associated RLKs and three families of unknown function (family-2, family-3, and family-5), are oomycete-specific, providing a systematic framework for RLK studies in this lineage. A comparative analysis between oomycete and plant RLK families reveals a striking divergence in their extracellular sensing domains. The major plant RLK families, such as lectin-RLKs, wall-associated kinases (WAKs), and S-domain RLKs, are largely absent from oomycetes (Dievart et al. 2020 ; Ngou et al. 2024 ). Conversely, the four oomycete-specific families we identified have no known counterparts in plant genomes. This profound disparity suggests that the signaling systems of plants and oomycetes have evolved independently, reflecting their distant phylogenetic relationship and distinct ecological niches. The evolutionary decoupling of their extracellular domains, despite the convergent use of an intracellular kinase domain, implies that the molecular dialogues during infection are likely mediated by unique, lineage-specific ligand-receptor pairs (Diévart et al. 2011 ; Yin et al. 2023 ). However, despite this overall divergence, LRR-RLK family stands out as a dominant and conserved component in both lineages. In oomycetes, the LRR family accounts for the largest proportion of RLKs, mirroring its preeminence in plants, where LRR-RLKs are central to both development and immunity (da Silva Dambroz et al. 2023 ; Soltabayeva et al. 2022 ). The shared expansion of LRR-RLKs suggests that the LRR domain architecture, with its remarkable structural plasticity for diverse ligand recognition, offers a powerful evolutionary advantage for organisms requiring complex environmental sensing. This is particularly relevant for host-pathogen interactions, where LRR-RLKs can form intricate regulatory networks. LRR-RLKs in oomycetes can form complex interaction networks to coordinate developmental and pathogenic programs. Notably, P. sojae PsRLK6 can be recognized by the plant LRR-RLP GmRLP30, triggering host immunity and illustrating a potential mechanism for cross-kingdom signaling (Pei et al. 2025 ). This example illustrates that oomycete LRR-RLKs, while primarily functioning in pathogen signaling, can also interface with host receptors, highlighting a potential avenue for cross-kingdom interactions. Among the oomycete-specific families, the elicitin-RLKs (family-4) present a compelling case of adaptation to fundamental metabolic constraints. As sterol auxotrophs, oomycetes are entirely dependent on acquiring host-derived sterols for growth and reproduction (Wang et al. 2021 ). Elicitins are small, secreted proteins known for their high-affinity sterol-binding capacity. The identification of RLKs harboring elicitin-like domains in their extracellular regions provides a direct molecular link between sterol perception and transmembrane signaling. This model is strongly supported by the discovery that the LRR-RLK SSRK1 physically interacts with secreted elicitins to cooperatively sense sterols, a mechanism where elicitins act as ligand-binding subunits that "relay" captured sterols to the SSRK1 signaling complex to bridge the gap between extracellular nutrient acquisition and intracellular pathogenic programming. (Pei et al. 2024 ; Pei et al. 2025 ). Interestingly, plants have evolved a conceptually analogous system involving PATHOGENESIS-RELATED PROTEIN 1 (PR-1) and PR-1 receptor kinases (PR-1-RLK). Like elicitins, PR-1 proteins belong to the CAP superfamily and possess sterol-binding capabilities (Breen et al. 2017 ; Gamir et al. 2017 ). The existence of elicitin-RLKs in oomycetes and PR-1-RLKs in plants represents a remarkable instance of convergent evolution driven by the universal biological importance of sterols (Lu et al. 2017 ; Teixeira et al. 2013 ). However, the functional outcomes differ; while oomycetes likely use elicitin-RLKs to exploit host sterols for pathogenic programs, plants may utilize PR-1-RLKs to monitor sterol status or detect pathogen invasion. The enrichment of elicitin-RLKs in pathogenic oomycetes underscores the adaptive significance of this sensory module, directly linking nutritional acquisition to the regulation of virulence. In summary, this study provides the first comprehensive, structure-based census of the RLKome across the Stramenopiles, identifying 11357 RLKs from 233 species and systematically classifying them based on extracellular domain architecture, with six core families identified as the dominant groups. Our results reveal a striking lineage-specific expansion in oomycetes, where 10867 RLKs are predominantly organized into six core families, including the dominant LRR-RLK family (family-1) and five oomycete-specific groups such as the elicitin-RLKs (family-4) and three families of unknown function (family-2, 3, and 5). We demonstrate that while LRR-RLKs have convergently expanded in both plants and oomycetes to coordinate complex infection and developmental programs, the unique elicitin-RLK family represents a specialized evolutionary adaptation to sterol auxotrophy, potentially functioning as a molecular sensing module for host-derived nutrients. By delineating these distribution patterns and constructing a dedicated oomycetes RLK Database, we provide a foundational resource that integrates sequence, structural, and taxonomic data, offering a powerful platform for future functional studies and the identification of novel targets for disease control. Conclusions This study provides the first comprehensive structure-based characterization of the RLKome across 233 Stramenopile species, with a focus on oomycetes. We identified 11357 RLKs (10867 from oomycetes) and classified them into six core families. The LRR family is the most abundant, while four families (including elicitin-RLKs) are oomycete-specific. Lineage-specific expansion of oomycete RLKs is closely linked to their pathogenic lifestyles and sterol auxotrophy, and the convergent expansion of LRR-RLKs in oomycetes and plants highlights its evolutionary advantage in environmental sensing. We further constructed a dedicated oomycete RLK database as a foundational resource for functional studies. These findings clarify the structural diversity and evolutionary patterns of oomycete RLKs, and provide novel targets for the green control of oomycete diseases. Methods Data Collection and Curation ​​ Genomic data for 233 Stramenopile taxa were collected, with screening criteria requiring complete gene annotations and accompanying proteome sequences. Data were sourced from multiple public databases, including the National Center for Biotechnology Information ( https://www.ncbi.nlm.nih.gov/ ), the China National GeneBank ( https://ngdc.cncb.ac.cn/ ), the Dryad Digital Repository ( https://datadryad.org/ ), and the Ensembl database( https://www.ensembl.org/ ). The taxonomic composition of the dataset was dominated by oomycetes (77%), with the remainder consisting of non-oomycete Stramenopile groups, ensuring coverage of major evolutionary lineages within the clade (Additional file: Table S1 ). RLK identification and Structure-Guided Clustering RLK proteins were identified following the homology search and domain validation pipeline established in previous studies (Yin et al. 2023 ). Initial RLK sequences were filtered to exclude those with an extracellular domain (ECD) length < 50 amino acids and sequences belonging to the IRE1 family, resulting in a final set of 11357 RLK sequences for clustering analysis. Structural modeling of the ECDs (sequences upstream of the transmembrane helix predicted by deepTMHMM)(Hallgren et al. 2022 ) was performed using OmegaFold to generate corresponding PDB structure files. Structural similarity between ECDs was quantified via TM-score (a TM-score greater than or equal to 0.5 typically indicates homologous structures), with all-against-all structural alignments conducted using Foldseek v4.0.0, a tool that balances speed and accuracy through HMM-based fold alignment (Barrio-Hernandez et al. 2023 ). Alignment results were converted into a similarity matrix (values slightly > 1 were truncated to 1), and a distance matrix was constructed as distance = 1 - TM-score (Chen et al. 2025 ). Hierarchical clustering was implemented using the average linkage method, which calculates the average distance between clusters to mitigate biases from extreme values (Huang et al. 2023 ). Two rounds of clustering were performed: (i) The full dataset of 11357 ECDs was clustered, with tree height cutoff thresholds tested from 0.5 to 0.9 (step size = 0.1; lower thresholds produce more clusters, while higher thresholds merge more clusters). (ii) Representative sequences for each first-round cluster were selected via the total similarity method (sequences with the highest average similarity to other cluster members), followed by repeated all-against-all alignments and clustering using the same parameters as the first round. By comparing error rates and false positives across threshold combinations, the (0.7, 0.9) cutoff combination was selected to balance clustering resolution and reliability: the first round yielded 1206 clusters, which were further merged into 133 clusters in the second round. These 133 computational clusters served as the foundational basis for our subsequent RLK family classification and in-depth analyses focusing on core families. (Additional file: Table S2 and S3). Oomycetes RLK Database We constructed a comprehensive oomycetes RLK protein database ( https://biotec2.njau.edu.cn/oomycetes_RLKdb ) to facilitate the retrieval and functional analysis of RLK proteins across stramenopiles, particularly oomycetes. By integrating multi-source RLK protein data derived from our genome-wide identification and structural classification, this database incorporates multi-dimensional retrieval strategies, integrated analytical tool interfaces, and bulk data download functionalities to support evolutionary and functional studies of RLKs. Specifically, it stores detailed information on all identified RLK proteins, enabling users to retrieve target proteins via three core strategies: (i) species-specific query, allowing targeted access to RLK repertoires in individual stramenopile or oomycete species; (ii) sequence homology search using the BLASTp algorithm, facilitating the identification of orthologous RLKs across diverse species; and (iii) family-based classification retrieval, enabling browsing and analysis of RLKs according to their structural hierarchical clustering results. Additionally, the database embeds dedicated analytical tool interfaces, and provides downloadable datasets (including protein sequences, domain annotations, and family classifications) for offline research and downstream bioinformatic analyses. Abbreviations CRKs Cysteine-rich Receptor-like Kinases ECD Extracellular Domain KD Kinase Domain LRR Leucine-rich Repeat PAMP Pathogen-associated Molecular Pattern PR-1 Pathogenesis-Related Protein 1 RLKs Receptor-like Kinases TM Transmembrane Domain TM-score Template Modeling score WAKs Wall-associated Kinases Declarations Author contributions ZY and JL conceived and designed the research plan and computational workflow. JC carried out the structure-guided hierarchical clustering of RLK families and all subsequent bioinformatics analyses. JC and XY co-constructed the oomycetes RLK database website. JC, YP, ZY, and DD wrote the manuscript. All authors participated in data interpretation, manuscript drafting and revision, and approved the final version for publication. Funding This study was supported by the Fundamental Research Funds for the Central Universities (KYCXJC2025005), the National Natural Science Foundation of China (32472502 and 32270208), and the China Agriculture Research System (CARS-21). Data availability The oomycete RLK database established in this study is publicly accessible at https://biotec2.njau.edu.cn/oomycetes_RLKdb. All raw data, including RLK protein sequences, predicted 3D structures, structural clustering results and taxonomic annotation files, are available from the corresponding author upon reasonable request. The proteome datasets used for RLK identification were obtained from public databases (NCBI, Ensembl and CNCB) as described in the Methods section. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. 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Nat Commun. 2024;15:308. https://doi.org/10.1038/s41467-023-44408-3 . Pei Y, Ji P, Miao J, et al. A receptor kinase senses sterol by coupling with elicitins in auxotrophic Phytophthora. Proc Natl Acad Sci U S A. 2024;121:e2408186121. https://doi.org/10.1073/pnas.2408186121 . Pei Y, Ji P, Si J, et al. A Phytophthora receptor-like kinase regulates oospore development and can activate pattern-triggered plant immunity. Nat Commun. 2023;14:4593. https://doi.org/10.1038/s41467-023-40171-7 . Pei Y, Yin Z, Xu T, Dou D. Relay model: bridging ligands and receptors in networks. Trends Plant Sci. 2025;30:702–4. https://doi.org/10.1016/j.tplants.2025.03.018 . Pei Y, Zhao Y, Wang H, et al. Uncovering Convergent Pattern Recognition Receptors Recognising Phytophthora Across Plant Lineages. Plant Biotechnol J. 2025. https://doi.org/10.1111/pbi.70409 . Schulze B, Buhmann MT, Río Bártulos C, Kroth PG. Comprehensive computational analysis of leucine-rich repeat (LRR) proteins encoded in the genome of the diatom Phaeodactylum tricornutum. Mar Genomics. 2015;21:43–51. https://doi.org/10.1016/j.margen.2015.02.007 . Si J, Pei Y, Shen D, et al. Phytophthora sojae leucine-rich repeat receptor-like kinases: diverse and essential roles in development and pathogenicity. iScience. 2021;24:102725. https://doi.org/10.1016/j.isci.2021.102725 . Soltabayeva A, Dauletova N, Serik S, et al. Receptor-like Kinases (LRR-RLKs) in Response of Plants to Biotic and Abiotic Stresses. Plants (Basel). 2022;11:2660. https://doi.org/10.3390/plants11192660 . Tang D, Wang G, Zhou JM. Receptor Kinases in Plant-Pathogen Interactions: More Than Pattern Recognition. Plant Cell. 2017;29:618–37. https://doi.org/10.1105/tpc.16.00891 . Teixeira PJ, Costa GG, Fiorin GL, Pereira GA, Mondego JM. Novel receptor-like kinases in cacao contain PR-1 extracellular domains. Mol Plant Pathol. 2013;14:602–9. https://doi.org/10.1111/mpp.12028 . Thines M, Oomycetes. Curr Biol. 2018;28:R812–3. https://doi.org/10.1016/j.cub.2018.05.062 . van Kempen M, Kim SS, Tumescheit C, et al. Fast and accurate protein structure search with Foldseek. Nat Biotechnol. 2024;42:243–6. https://doi.org/10.1038/s41587-023-01773-0 . Wang W, Liu X, Govers F. The mysterious route of sterols in oomycetes. PLoS Pathog. 2021;17:e1009591. https://doi.org/10.1371/journal.ppat.1009591 . Wang Y, Govers F, Wang Y. Oomycete plant pathogens: biology, pathogenesis and emerging control strategies. Nat Rev Microbiol. 2025. https://doi.org/10.1038/s41579-025-01248-w . Xu F, Wang L, Li Y, et al. Phase separation of GRP7 facilitated by FERONIA-mediated phosphorylation inhibits mRNA translation to modulate plant temperature resilience. Mol Plant. 2024;17:460–77. https://doi.org/10.1016/j.molp.2024.02.001 . Yin Z, Liu J, Dou D, RLKdb. A comprehensively curated database of plant receptor-like kinase families. Mol Plant. 2024;17:513–5. https://doi.org/10.1016/j.molp.2024.02.014 . Yin Z, Shen D, Zhao Y, et al. Cross-kingdom analyses of transmembrane protein kinases show their functional diversity and distinct origins in protists. Comput Struct Biotechnol J. 2023;21:4070–8. https://doi.org/10.1016/j.csbj.2023.08.007 . Yu M, Wu J, Zhao C, Qiu JL. Exploring plant protein functions through structure-based clustering. Trends Plant Sci. 2025;30:1111–8. https://doi.org/10.1016/j.tplants.2025.03.014 . Zhang B, Zhang Z, Yong S, et al. An Oomycete-Specific Leucine-Rich Repeat-Containing Protein Is Involved in Zoospore Flagellum Development in Phytophthora sojae. Phytopathology. 2022;112:2351–9. https://doi.org/10.1094/phyto-12-21-0523-r . Zhang Z, Li X, Li J, et al. metaRLK 2.0: an updated database of plant receptor-like kinases developed with structure- and deep learning-based functional annotation and classification. Plant Commun. 2026;101781. https://doi.org/10.1016/j.xplc.2026.101781 . Zipfel C. Plant pattern-recognition receptors. Trends Immunol. 2014;35:345–51. https://doi.org/10.1016/j.it.2014.05.004 . Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformationlegends.docx TableS1.xlsx TableS2.xlsx TableS3.xlsx TableS4.xlsx 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. 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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-9308108","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627256966,"identity":"7cd1902c-3cd2-47b9-8f18-21499b8b0540","order_by":0,"name":"Jun Cheng","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Cheng","suffix":""},{"id":627256967,"identity":"d4ec1627-12c9-4d88-87a3-d725eab309f0","order_by":1,"name":"Xuteng Ye","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xuteng","middleName":"","lastName":"Ye","suffix":""},{"id":627256968,"identity":"b8ce6a91-961e-4a59-a230-bb69f81997a2","order_by":2,"name":"Yong Pei","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Pei","suffix":""},{"id":627256971,"identity":"91d950e8-8830-45c8-aae4-f0ff4af6759f","order_by":3,"name":"Jinding Liu","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jinding","middleName":"","lastName":"Liu","suffix":""},{"id":627256973,"identity":"a58af1e5-cd7f-48db-9bfe-c7e60b34882c","order_by":4,"name":"Zhiyuan Yin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYFACxgaGDwxsYKYE0VoYZ5CohYGBmQfKIE6L/Izktse2O/jkDQ4wH7zNw2CXR9hZMxLbjXPPsBluOMCWbM3DkFxM2FESiW3SuW1sjBsO8JhJ8zAcSGwgpIUNpMWyjc1+wwH+b8Rp4QFpYWxjSwTawkacFgmeh22SvW1syTMPsxlbzjFIJqxFvj39mcTPtmO2fcebH954U2FHWAuDQAKIPAYMCBBtQFA9EPAfAJE1xCgdBaNgFIyCkQoAFV81mEpsPC0AAAAASUVORK5CYII=","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Zhiyuan","middleName":"","lastName":"Yin","suffix":""},{"id":627256974,"identity":"9451349a-b843-489d-b894-37eb796701c6","order_by":5,"name":"Daolong Dou","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Daolong","middleName":"","lastName":"Dou","suffix":""}],"badges":[],"createdAt":"2026-04-03 02:55:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9308108/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9308108/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107707108,"identity":"20ab4c8a-4c4e-4ea1-827e-b2b79a2e2ccf","added_by":"auto","created_at":"2026-04-24 09:19:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":401498,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification pipeline of 11357 RLKs across 233 Stramenopiles species.\u003cstrong\u003e \u003c/strong\u003eComputational workflow for RLK identification and family classification. Proteome datasets from 233 Stramenopiles species were collected and screened for RLKs using HMMER-based kinase domain detection combined with deepTMHMM for transmembrane topology prediction. Extracellular domains of the 11357 identified RLKs were structurally predicted using OmegaFold, followed by structure-based similarity analysis using Foldseek. Hierarchical clustering, representative protein selection, and secondary structural clustering yielded 133 computational clusters, which were further classified into RLK families. Among these, 6 major families (family-1 (LRR), family-2 (unknown), family-3 (unknown), family-4 (elicitin), family-5 (unknown), family-6 (EGF)) with more than 100 members were retained for downstream analyses.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/c1f96f3bae9824989423dc68.png"},{"id":107623171,"identity":"621852c5-1daa-407f-9ec5-b6f2049da897","added_by":"auto","created_at":"2026-04-23 09:58:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1899213,"visible":true,"origin":"","legend":"\u003cp\u003eRLK evolution and abundance in Stramenopiles. \u003cstrong\u003ea\u003c/strong\u003e Phylogenetic tree of 233 Stramenopiles species. A circular phylogenetic tree of 233 Stramenopiles species, visualized with tips grouped by genus (encompassing 67 genera) to illustrate their evolutionary relationships. The outermost colored strip denotes the three major Stramenopiles lineages: Oomycota (pink), Ochrophyta (green), and Bigyra (yellow), aligned with the phylogenetic placement of each genus. Two concentric rings flank the tree, displaying key metrics per genus: the inner ring (adjacent to the tree) is a blue heatmap showing the log10-transformed (lg) number of identified receptor-like kinase (RLK) genes, with zero RLK counts represented by the lightest shade on the blue color scale; the outer ring is a green bar chart indicating the number of species contained within each genus. These visualizations highlight lineage-specific patterns in RLK gene family evolution and taxonomic diversity across Stramenopiles genera. \u003cstrong\u003eb\u003c/strong\u003eTaxonomic composition of analyzed species. Pie chart showing the proportion of species across three stramenopile phyla: Oomycota (77%), Ochrophyta (20%), and Bigyra (3%), based on the 233 analyzed Stramenopiles species. \u003cstrong\u003ec\u003c/strong\u003eCorrelation between proteome size and RLK abundance. Scatter plot depicting the relationship between proteome size (log10-transformed, x-axis) and RLK number (log10-transformed, y-axis) for each species. Data points are color-coded by phylum, revealing that Oomycota species generally have higher RLK numbers relative to proteome size compared to Ochrophyta and Bigyra. \u003cstrong\u003ed\u003c/strong\u003eComparison of RLK numbers among stramenopile phyla. Box-and-whisker plots with overlaid individual data points showing RLK counts per species in Bigyra, Ochrophyta, and Oomycota, demonstrating a markedly higher RLK abundance in Oomycota species. \u003cstrong\u003ee\u003c/strong\u003e Variation of RLK abundance within Oomycota. Box-and-whisker plots showing RLK counts per species across four oomycete orders (Albuginales, Peronosporales, Pythiales, and Saprolegniales), with Saprolegniales exhibiting the highest median and overall RLK abundance.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/fa21060e64685e5fe477e2d4.png"},{"id":107707424,"identity":"1767b4eb-6eef-4b24-8265-6ad8a7de352b","added_by":"auto","created_at":"2026-04-24 09:20:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":535496,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of six major RLK families in Stramenopiles.\u003cstrong\u003e a\u003c/strong\u003e Protein structural similarity network of major RLK families. Network visualization of intra- and inter-family structural relationships among RLKs, constructed based on pairwise structural similarity comparisons of extracellular domains. Nodes represent individual RLKs, colored by family: orange (family-1, LRR), light blue (family-2, unknown function), yellow (family-3, unknown function), white (family-4, elicitin), dark blue (family-5, unknown function), red (family-6, EGF). Edges indicate structural similarity, highlighting connectivity patterns within and between families. \u003cstrong\u003eb\u003c/strong\u003e Representative extracellular domain structures. Three-dimensional structural models of representative RLKs from each core family, ordered as: family-1 (LRR), family-2 (unknown function), family-3 (unknown function), family-4 (elicitin), family-5 (unknown function), family-6 (EGF). Distinct structural folds are highlighted to illustrate family-specific spatial folding characteristics. \u003cstrong\u003ec\u003c/strong\u003e RLK family composition. Pie chart showing the relative proportions of the six major RLK families and all remaining minor families (total = 11357 RLKs). The LRR family (family-1) is the most abundant, accounting for 50% of all RLKs, followed by family-2 (unknown function, 10%), family-3 (unknown function, 9%), family-4 (elicitin, 9%), family-5 (unknown function, 8%), and family-6 (EGF, 1%); the remaining 127 minor families collectively account for 13% of total RLKs. \u003cstrong\u003ed\u003c/strong\u003e Taxonomic distribution of the six major RLK families. Stacked bar charts show the relative abundance of each major RLK family (excluding minor families, with percentages summing to 100% for each lineage) across three stramenopile phyla (upper panel: Oomycota, Ochrophyta, Bigyra) and four ecologically important oomycete orders (lower panel: Saprolegniales, Pythiales, Peronosporales, Albuginales).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/5047eb6b6d67ae03d11b7ca1.png"},{"id":107623178,"identity":"44a91dfc-6250-4e01-b02d-7aecf2a23695","added_by":"auto","created_at":"2026-04-23 09:58:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":994262,"visible":true,"origin":"","legend":"\u003cp\u003eOverview and functionality of the oomycetes receptor-like kinase database.\u003cstrong\u003e \u003c/strong\u003eFunctional architecture of the RLK database. The oomycetes RLK database integrates 11357 RLK proteins identified from 233 species and supports three primary retrieval modes: species-based search, BLASTp-based sequence similarity search, and family-based classification search. Each RLK entry is linked to detailed annotations, including domain architecture and predicted three-dimensional protein structures, and it simultaneously supports the local search and structural clustering functions of the Foldseek tool, providing users with a user-friendly interactive interface, providing a comprehensive resource for studying the evolution and functional diversification of RLKs in Stramenopiles.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/aa5f3c7d21d9981908887884.png"},{"id":107868830,"identity":"67f1bc3e-f76b-4c4c-8298-0746e655bae0","added_by":"auto","created_at":"2026-04-27 07:34:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4099037,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/47b10d72-91c7-44db-8a39-4251f2176b20.pdf"},{"id":107707355,"identity":"057ecace-5708-4cce-9ccc-6076945a9f9d","added_by":"auto","created_at":"2026-04-24 09:20:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13992,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformationlegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/e8224be4c9832bff026317be.docx"},{"id":107706876,"identity":"9d4d66b0-d855-4af0-9445-3328e0552495","added_by":"auto","created_at":"2026-04-24 09:18:58","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":55496,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/4d38cb04c1de9af108391e2d.xlsx"},{"id":107623173,"identity":"b8a552c8-d4bd-4c2c-93e7-90a73fc464af","added_by":"auto","created_at":"2026-04-23 09:58:40","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1166115,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/97c8c6ff6be1d4a59e021cd4.xlsx"},{"id":107623176,"identity":"fd7f6708-cbfc-4fc8-8f52-a35cf3be1bff","added_by":"auto","created_at":"2026-04-23 09:58:40","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11850,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/2b33d1c771dc05c9cbf83501.xlsx"},{"id":107623175,"identity":"8198f145-6f74-44e6-911f-ee4e2ae86398","added_by":"auto","created_at":"2026-04-23 09:58:40","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":29582,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9308108/v1/bf68c1feb6fa026593b1cc7d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structural characterization of RLKomes reveals lineage-specific families in oomycetes","fulltext":[{"header":"Background","content":"\u003cp\u003eOomycetes are filamentous microorganisms that include some of the most destructive plant pathogens known to agriculture (Wang et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Species such as \u003cem\u003ePhytophthora infestans\u003c/em\u003e (causal agent of potato late blight), \u003cem\u003ePhytophthora sojae\u003c/em\u003e (soybean root rot), and various \u003cem\u003ePythium\u003c/em\u003e and \u003cem\u003eSaprolegnia\u003c/em\u003e species pose persistent threats to global food security and aquaculture (Fry. 2008; Judelson et al. 2005). Despite their fungal-like morphology, oomycetes are evolutionarily distinct from true fungi, belonging instead to the Stramenopiles, a diverse supergroup that also includes photosynthetic diatoms and brown algae (Ochrophyta) as well as heterotrophic flagellates (Bigyra) (Jirsova et al. 2024). This phylogenetic placement offers a unique opportunity to investigate how signaling systems have evolved in parallel with pathogenic lifestyles.\u003c/p\u003e \u003cp\u003eReceptor-like kinases (RLKs) constitute a major class of signal transduction molecules in plants, characterized by a modular architecture comprising an extracellular ligand-binding domain (ECD), a single transmembrane domain (TM), and an intracellular kinase domain (KD) (Dievart et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Through ligand-induced activation, RLKs initiate downstream phosphorylation cascades that regulate growth, development, immunity, and environmental adaptation (Ngou et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Plant RLKs have undergone extensive expansion and diversification, forming one of the largest gene families in plant genomes (Dievart et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Based on extracellular domain composition, plant RLKs are traditionally classified into multiple subfamilies, including leucine-rich repeat RLKs (LRR-RLKs), lectin RLKs, wall-associated kinases (WAKs), S-domain RLKs, and cysteine-rich RLKs (CRKs), among others (Dievart et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ngou et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This diversification is thought to reflect adaptive pressures associated with terrestrialization, multicellularity, and the need for sophisticated environmental sensing and immune surveillance (Lease et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Man et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among these subfamilies, LRR-RLKs represent the largest and most functionally versatile group (Soltabayeva et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Their conserved yet structurally flexible LRR motifs enable the perception of chemically diverse ligands (da Silva Dambroz et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), underpinning their central roles in plant innate immunity and developmental signaling (Tang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zipfel et al. 2014).\u003c/p\u003e \u003cp\u003eTo date, RLK research has been overwhelmingly plant-centric (Brustolini et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Extensive functional, evolutionary, and genomic analyses have established RLKs as key drivers of terrestrial adaptation (Xu et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), immune surveillance, and symbiotic interactions in land plants, culminating in the construction of comprehensive plant-specific RLK resources such as RLKdb (Yin et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e-) and metaRLK (Liu et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). In striking contrast, systematic studies of RLKs in oomycetes remain scarce (Bozkurt et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Previous studies have shown the presence of LRR-RLKs in oomycetes (Thines. 2018), where they may function as receptors involved in host recognition and pathogenicity (Pei et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For other major Stramenopiles lineages, including diatoms and brown algae, RLK repertoires, family classification, and evolutionary origins remain virtually unexplored (Cock et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Intriguingly, although plant and oomycetes RLKs share similar extracellular architectures, their cytoplasmic kinase domains belong to distinct evolutionary clades, indicative of modular convergent evolution (Di\u0026eacute;vart et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This evolutionary decoupling of extracellular sensing and intracellular signaling modules highlights the necessity of lineage-specific RLK classification frameworks.\u003c/p\u003e \u003cp\u003eConventional homology-based approaches, such as BLAST or HMMER, lack sufficient sensitivity to reliably detect distantly related RLKs, resulting in widespread under-annotation or misannotation in oomycete genomes (Denoeud et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Schulze et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Recent advances in AI-driven protein structure prediction, including OmegaFold, together with ultra-fast structural comparison tools such as Foldseek, have transformed this landscape (Jumper et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; van Kempen et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Because protein tertiary structures are substantially more conserved than primary sequences, structure-based strategies offer a powerful avenue for identifying deeply divergent homologs that remain invisible to sequence-based methods (Yu et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Consequently, a structure-based identification and classification strategy can thus accurately capture divergent yet structurally conserved RLKs in oomycetes.\u003c/p\u003e \u003cp\u003eIn this study, we integrated large-scale proteomic sampling with structure-based identification to perform a systematic analysis of RLKs across Stramenopiles, with a primary focus on oomycetes. From 233 species, we identified 11357 RLKs and obtained 6 major families via structural clustering (cluster size\u0026thinsp;\u0026gt;\u0026thinsp;100). Oomycetes harbor significantly expanded RLK repertoires compared to other stramenopiles, driven largely by lineage-specific amplification of LRR-RLKs. Several families, including elicitin-associated RLKs and three families of unknown function, appear oomycete-specific. These findings suggest that oomycete RLKs have undergone independent diversification shaped by pathogenic lifestyles. We further constructed a dedicated oomycetes RLK database integrating sequence, structure, and taxonomic information, providing a foundational resource for evolutionary and functional studies.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSystematic Identification and Family Classification of RLKs\u003c/h2\u003e \u003cp\u003eTo systematically characterize the repertoire and evolutionary dynamics of receptor-like kinases (RLKs) across Stramenopiles, with a particular emphasis on oomycetes, we implemented a standardized computational workflow integrating multi-source data curation, topology-aware RLK identification, and structure-guided family classification (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We first compiled a comprehensive proteome dataset encompassing 233 stramenopile species from NCBI, Ensembl, and CNCB databases, spanning the three major clades Oomycota, Ochrophyta, and Bigyra (Additional file: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). For RLK identification, we adopted a topology-aware pipeline that integrates HMMER-based kinase domain annotation with DeepTMHMM-based transmembrane topology prediction as previous reported (Yin et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Only proteins harboring a single transmembrane domain, an extracellular domain (ECD), and a cytoplasmic kinase domain were retained as bona fide RLKs. This stringent pipeline yielded a total of 11357 RLKs across 232 species, of which 10867 were identified from Oomycota (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTaxonomic Distribution of RLKs Across Stramenopiles\u003c/h3\u003e\n\u003cp\u003eTo contextualize these findings within an evolutionary framework, we reconstructed a species phylogeny using the NCBI Taxonomy Common Tree tool (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Our dataset is taxonomically dominated by Oomycota (77%), followed by Ochrophyta (20%) and Bigyra (3%), reflecting broad sampling across stramenopile diversity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). At the species level, RLK counts varied substantially, ranging from fewer than 10 to over 100 per genome, with an average of 48 RLKs per species, accounting for ~\u0026thinsp;1.2% of the total proteome, a proportion comparable to that reported in plant lineages (Ngou et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Correlation analysis of log\u003csub\u003e10\u003c/sub\u003e-transformed proteome size and RLK abundance revealed a weak positive association, suggesting that RLK expansion is partially coupled to overall proteome complexity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInter-clade comparisons further demonstrated that Oomycota species harbored significantly more RLKs (average\u0026thinsp;~\u0026thinsp;67 per species) than Ochrophyta (~\u0026thinsp;23 per species) and Bigyra (~\u0026thinsp;18 per species), indicative of lineage-specific expansion of RLK families in oomycetes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Within Oomycota, analysis of four core orders, Albuginales, Peronosporales, Pythiales, and Saprolegniales, revealed that Saprolegniales exhibited the highest average RLK count (~\u0026thinsp;89 per species), highlighting order-specific patterns in RLK family expansion (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e\n\u003ch3\u003eStructural Characteristics and Distribution Patterns of Major RLK Families\u003c/h3\u003e\n\u003cp\u003eTo classify these RLKs into functionally coherent families, we performed structure-guided hierarchical clustering based on ECD structures predicted by OmegaFold. Pairwise structural similarities were quantified via TM-score using Foldseek, followed by two rounds of average-linkage hierarchical clustering. This analysis clustered the 11357 RLKs and designated clusters containing greater than or equal to 100 members as major families. In total, six major families were identified, representing the core RLK groups of Stramenopiles, and these six families collectively account for 87% of all identified RLKs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Additional file: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). All identified families varied substantially in size and taxonomic breadth, 19 families contained RLKs from only one species, 29 families from 2\u0026ndash;5 species, 34 families from 6\u0026ndash;10 species, and 51 families from more than 10 species. (Additional file: Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo investigate the structural relationships among these six core families, we constructed a protein structural similarity network based on pairwise TM-score comparisons of extracellular domains (ECDs). This analysis revealed that the LRR family (family-1) constitutes the largest and most densely connected cluster, indicative of high sequence conservation within this family. In contrast, the remaining five core families (family-2 to family-6) form smaller, discrete clusters with limited inter-family connectivity, suggesting distinct structural and evolutionary origins (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next examined the three-dimensional folding features of representative ECDs from each core family. Structural analysis revealed distinct spatial architectures among the six families. Family-1 (LRR) adopts a canonical helix-turn-helix repeat fold, a conserved structural hallmark that confers plasticity for diverse ligand recognition; family-4 (elicitin) (Boissy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Derevnina et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and family-6 (EGF) display compact spatial conformations; while family-2, family-3, and family-5 possess unique, previously uncharacterized folding patterns, consistent with their unknown functional roles (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) (da Silva Dambroz et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eQuantification of family-level abundance across Stramenopiles revealed a highly skewed distribution pattern. The LRR family (family-1) dominates the RLK repertoire, accounting for 50% of all identified RLKs, followed by family-2 (10%), family-3 (9%), family-4 (9%), family-5 (8%), and family-6 (1%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Together, these six core families comprise 87% of all identified RLKs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eTo examine the distribution patterns of major RLK families across taxonomic groups, we analyzed the proportional representation of core families across three stramenopile phyla (Oomycota, Ochrophyta, Bigyra) and four oomycete orders (Albuginales, Peronosporales, Pythiales, Saprolegniales) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, Additional file: Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). At the phylum level, the LRR family showed enrichment in Oomycota (54%) compared to Ochrophyta (32%) and Bigyra (28%), while family-2 was overrepresented in Bigyra (19%). The EGF family (family-6) maintained a consistently low proportion across all three phyla (1\u0026ndash;2%). Within Oomycota, order-level analysis revealed that the LRR family reached its highest proportion in Peronosporales (56%) and Pythiales (55%), followed by Saprolegniales (48%) and Albuginales (42%). Family-4 (elicitin) was most abundant in Peronosporales (11%) and Pythiales (10%), while family-2 and family-5 showed elevated representation in Saprolegniales (12% and 10%, respectively). Collectively, these six major RLK families exhibited distinct structural features and lineage-specific distribution patterns across Stramenopiles.\u003c/p\u003e\u003cdiv class=\"Heading\"\u003e\u003cb\u003eConstruction of a Dedicated Oomycetes RLK Database\u003c/b\u003e\u003c/div\u003e \u003cp\u003eTo facilitate access to the extensive RLK resources generated in this study, we constructed a specialized oomycetes RLK database integrating sequence, structural, and taxonomic information. The database encompasses RLKs from all 233 species and supports hierarchical browsing across five taxonomic levels (phylum to species), enabling comparative analyses across trophic modes and evolutionary lineages (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIts cross-trophic coverage characteristic provides dual support of taxonomic and genetic data for studying the association between lifestyle evolution and RLK function. In terms of functional design, the database constructs three core retrieval modules based on \"user needs\" (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB): (1) Species-specific retrieval supports hierarchical screening of complete RLKome sequences and annotations for specific species; (2) BLASTp-based sequence similarity retrieval enables rapid identification of homologous RLKs and their family affiliation for unknown sequences; (3) Family-specific retrieval supports specialized query and comparative analysis of all identified families, with a primary focus on the six core families. In addition, the database integrates the topological distribution of RLK domains (graphical display) and three-dimensional structural models (predicted by OmegaFold), realizing integrated presentation of \"sequence-structure-classification-distribution\" data. In terms of tools, we have localized Foldseek, allowing users to perform similarity searches using structure files (PDB); at the same time, we also provide an interactive interface for structural clustering, where users can upload batch protein PDB files to obtain their family classification. This database not only fills the gap of insufficient systematic integration of current Stramenopiles RLK data but also transforms the aforementioned basic research achievements into practical tools, providing key data support for subsequent studies on RLK functional evolution.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRLKs are well-established as central regulators of development, environmental sensing, and immunity in plants. Recent studies reveal that oomycetes, including major pathogens, also possess RLKs that play crucial roles in development, host interaction, and environmental adaptation. In \u003cem\u003ePhytophthora sojae\u003c/em\u003e, a comprehensive functional characterization of the LRR-RLK family revealed diverse roles of LRR-RLKs in modulating development, interaction with soybean, and responses to diverse environmental factors (Si et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Beyond general development, specific RLKs have evolved to sense host-specific cues; for instance, PsIRK1 and PsIRK2 were recently identified as direct chemoreceptors for soybean isoflavones, mediating zoospore chemotaxis via G protein signaling (Ji et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), while SSRK1 functions as a sterol-sensing RLK that cooperates with elicitin to detect host-derived sterols, linking nutrient perception to pathogenic development (Pei et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, PsRLK6 has been shown to play a dual role, acting as both an essential regulator of oospore development and a pathogen-associated molecular pattern (PAMP) that triggers pattern-triggered immunity in plants (Pei et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite this functional significance, a comprehensive, genome-wide inventory of RLKs across the diverse oomycete lineage has been conspicuously absent, largely due to the limitations of sequence-based homology searches in detecting highly divergent members. Here, using a topology-aware identification pipeline combined with structure-guided hierarchical clustering, we analyzed 179 oomycete proteomes and identified 10,867 RLKs. These were systematically classified based on extracellular domain architecture, with six core families predominating. Four of these core families, elicitin-associated RLKs and three families of unknown function (family-2, family-3, and family-5), are oomycete-specific, providing a systematic framework for RLK studies in this lineage.\u003c/p\u003e \u003cp\u003eA comparative analysis between oomycete and plant RLK families reveals a striking divergence in their extracellular sensing domains. The major plant RLK families, such as lectin-RLKs, wall-associated kinases (WAKs), and S-domain RLKs, are largely absent from oomycetes (Dievart et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ngou et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Conversely, the four oomycete-specific families we identified have no known counterparts in plant genomes. This profound disparity suggests that the signaling systems of plants and oomycetes have evolved independently, reflecting their distant phylogenetic relationship and distinct ecological niches. The evolutionary decoupling of their extracellular domains, despite the convergent use of an intracellular kinase domain, implies that the molecular dialogues during infection are likely mediated by unique, lineage-specific ligand-receptor pairs (Di\u0026eacute;vart et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yin et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, despite this overall divergence, LRR-RLK family stands out as a dominant and conserved component in both lineages. In oomycetes, the LRR family accounts for the largest proportion of RLKs, mirroring its preeminence in plants, where LRR-RLKs are central to both development and immunity (da Silva Dambroz et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Soltabayeva et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The shared expansion of LRR-RLKs suggests that the LRR domain architecture, with its remarkable structural plasticity for diverse ligand recognition, offers a powerful evolutionary advantage for organisms requiring complex environmental sensing. This is particularly relevant for host-pathogen interactions, where LRR-RLKs can form intricate regulatory networks. LRR-RLKs in oomycetes can form complex interaction networks to coordinate developmental and pathogenic programs. Notably, \u003cem\u003eP. sojae\u003c/em\u003e PsRLK6 can be recognized by the plant LRR-RLP GmRLP30, triggering host immunity and illustrating a potential mechanism for cross-kingdom signaling (Pei et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This example illustrates that oomycete LRR-RLKs, while primarily functioning in pathogen signaling, can also interface with host receptors, highlighting a potential avenue for cross-kingdom interactions.\u003c/p\u003e \u003cp\u003eAmong the oomycete-specific families, the elicitin-RLKs (family-4) present a compelling case of adaptation to fundamental metabolic constraints. As sterol auxotrophs, oomycetes are entirely dependent on acquiring host-derived sterols for growth and reproduction (Wang et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Elicitins are small, secreted proteins known for their high-affinity sterol-binding capacity. The identification of RLKs harboring elicitin-like domains in their extracellular regions provides a direct molecular link between sterol perception and transmembrane signaling. This model is strongly supported by the discovery that the LRR-RLK SSRK1 physically interacts with secreted elicitins to cooperatively sense sterols, a mechanism where elicitins act as ligand-binding subunits that \"relay\" captured sterols to the SSRK1 signaling complex to bridge the gap between extracellular nutrient acquisition and intracellular pathogenic programming. (Pei et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pei et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Interestingly, plants have evolved a conceptually analogous system involving PATHOGENESIS-RELATED PROTEIN 1 (PR-1) and PR-1 receptor kinases (PR-1-RLK). Like elicitins, PR-1 proteins belong to the CAP superfamily and possess sterol-binding capabilities (Breen et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gamir et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The existence of elicitin-RLKs in oomycetes and PR-1-RLKs in plants represents a remarkable instance of convergent evolution driven by the universal biological importance of sterols (Lu et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Teixeira et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, the functional outcomes differ; while oomycetes likely use elicitin-RLKs to exploit host sterols for pathogenic programs, plants may utilize PR-1-RLKs to monitor sterol status or detect pathogen invasion. The enrichment of elicitin-RLKs in pathogenic oomycetes underscores the adaptive significance of this sensory module, directly linking nutritional acquisition to the regulation of virulence.\u003c/p\u003e \u003cp\u003eIn summary, this study provides the first comprehensive, structure-based census of the RLKome across the Stramenopiles, identifying 11357 RLKs from 233 species and systematically classifying them based on extracellular domain architecture, with six core families identified as the dominant groups. Our results reveal a striking lineage-specific expansion in oomycetes, where 10867 RLKs are predominantly organized into six core families, including the dominant LRR-RLK family (family-1) and five oomycete-specific groups such as the elicitin-RLKs (family-4) and three families of unknown function (family-2, 3, and 5). We demonstrate that while LRR-RLKs have convergently expanded in both plants and oomycetes to coordinate complex infection and developmental programs, the unique elicitin-RLK family represents a specialized evolutionary adaptation to sterol auxotrophy, potentially functioning as a molecular sensing module for host-derived nutrients. By delineating these distribution patterns and constructing a dedicated oomycetes RLK Database, we provide a foundational resource that integrates sequence, structural, and taxonomic data, offering a powerful platform for future functional studies and the identification of novel targets for disease control.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides the first comprehensive structure-based characterization of the RLKome across 233 Stramenopile species, with a focus on oomycetes. We identified 11357 RLKs (10867 from oomycetes) and classified them into six core families. The LRR family is the most abundant, while four families (including elicitin-RLKs) are oomycete-specific. Lineage-specific expansion of oomycete RLKs is closely linked to their pathogenic lifestyles and sterol auxotrophy, and the convergent expansion of LRR-RLKs in oomycetes and plants highlights its evolutionary advantage in environmental sensing. We further constructed a dedicated oomycete RLK database as a foundational resource for functional studies. These findings clarify the structural diversity and evolutionary patterns of oomycete RLKs, and provide novel targets for the green control of oomycete diseases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eData Collection and Curation\u003c/b\u003e​​\u003c/p\u003e \u003cp\u003eGenomic data for 233 Stramenopile taxa were collected, with screening criteria requiring complete gene annotations and accompanying proteome sequences. Data were sourced from multiple public databases, including the National Center for Biotechnology Information (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), the China National GeneBank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ngdc.cncb.ac.cn/\u003c/span\u003e\u003cspan address=\"https://ngdc.cncb.ac.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), the Dryad Digital Repository (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://datadryad.org/\u003c/span\u003e\u003cspan address=\"https://datadryad.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and the Ensembl database(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ensembl.org/\u003c/span\u003e\u003cspan address=\"https://www.ensembl.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The taxonomic composition of the dataset was dominated by oomycetes (77%), with the remainder consisting of non-oomycete Stramenopile groups, ensuring coverage of major evolutionary lineages within the clade (Additional file: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eRLK identification and Structure-Guided Clustering\u003c/h3\u003e\n\u003cp\u003eRLK proteins were identified following the homology search and domain validation pipeline established in previous studies (Yin et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Initial RLK sequences were filtered to exclude those with an extracellular domain (ECD) length\u0026thinsp;\u0026lt;\u0026thinsp;50 amino acids and sequences belonging to the IRE1 family, resulting in a final set of 11357 RLK sequences for clustering analysis.\u003c/p\u003e \u003cp\u003eStructural modeling of the ECDs (sequences upstream of the transmembrane helix predicted by deepTMHMM)(Hallgren et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) was performed using OmegaFold to generate corresponding PDB structure files. Structural similarity between ECDs was quantified via TM-score (a TM-score greater than or equal to 0.5 typically indicates homologous structures), with all-against-all structural alignments conducted using Foldseek v4.0.0, a tool that balances speed and accuracy through HMM-based fold alignment (Barrio-Hernandez et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Alignment results were converted into a similarity matrix (values slightly\u0026thinsp;\u0026gt;\u0026thinsp;1 were truncated to 1), and a distance matrix was constructed as distance\u0026thinsp;=\u0026thinsp;1 - TM-score (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHierarchical clustering was implemented using the average linkage method, which calculates the average distance between clusters to mitigate biases from extreme values (Huang et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Two rounds of clustering were performed: (i) The full dataset of 11357 ECDs was clustered, with tree height cutoff thresholds tested from 0.5 to 0.9 (step size\u0026thinsp;=\u0026thinsp;0.1; lower thresholds produce more clusters, while higher thresholds merge more clusters). (ii) Representative sequences for each first-round cluster were selected via the total similarity method (sequences with the highest average similarity to other cluster members), followed by repeated all-against-all alignments and clustering using the same parameters as the first round.\u003c/p\u003e \u003cp\u003eBy comparing error rates and false positives across threshold combinations, the (0.7, 0.9) cutoff combination was selected to balance clustering resolution and reliability: the first round yielded 1206 clusters, which were further merged into 133 clusters in the second round. These 133 computational clusters served as the foundational basis for our subsequent RLK family classification and in-depth analyses focusing on core families. (Additional file: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e and S3).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOomycetes RLK Database\u003c/h2\u003e \u003cp\u003eWe constructed a comprehensive oomycetes RLK protein database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://biotec2.njau.edu.cn/oomycetes_RLKdb\u003c/span\u003e\u003cspan address=\"https://biotec2.njau.edu.cn/oomycetes_RLKdb\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to facilitate the retrieval and functional analysis of RLK proteins across stramenopiles, particularly oomycetes. By integrating multi-source RLK protein data derived from our genome-wide identification and structural classification, this database incorporates multi-dimensional retrieval strategies, integrated analytical tool interfaces, and bulk data download functionalities to support evolutionary and functional studies of RLKs.\u003c/p\u003e \u003cp\u003eSpecifically, it stores detailed information on all identified RLK proteins, enabling users to retrieve target proteins via three core strategies: (i) species-specific query, allowing targeted access to RLK repertoires in individual stramenopile or oomycete species; (ii) sequence homology search using the BLASTp algorithm, facilitating the identification of orthologous RLKs across diverse species; and (iii) family-based classification retrieval, enabling browsing and analysis of RLKs according to their structural hierarchical clustering results.\u003c/p\u003e \u003cp\u003eAdditionally, the database embeds dedicated analytical tool interfaces, and provides downloadable datasets (including protein sequences, domain annotations, and family classifications) for offline research and downstream bioinformatic analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRKs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCysteine-rich Receptor-like Kinases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtracellular Domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKinase Domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLRR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeucine-rich Repeat\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePAMP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePathogen-associated Molecular Pattern\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePR-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePathogenesis-Related Protein 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRLKs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceptor-like Kinases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransmembrane Domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTM-score\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTemplate Modeling score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWAKs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWall-associated Kinases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZY and JL conceived and designed the research plan and computational workflow. JC carried out the structure-guided hierarchical clustering of RLK families and all subsequent bioinformatics analyses. JC and XY co-constructed the oomycetes RLK database website. JC, YP, ZY, and DD wrote the manuscript. All authors participated in data interpretation, manuscript drafting and revision, and approved the final version for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Fundamental Research Funds for the Central Universities (KYCXJC2025005), the National Natural Science Foundation of China (32472502 and 32270208), and the China Agriculture Research System (CARS-21).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe oomycete RLK database established in this study is publicly accessible at https://biotec2.njau.edu.cn/oomycetes_RLKdb. All raw data, including RLK protein sequences, predicted 3D structures, structural clustering results and taxonomic annotation files, are available from the corresponding author upon reasonable request. The proteome datasets used for RLK identification were obtained from public databases (NCBI, Ensembl and CNCB) as described in the Methods section.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBarrio-Hernandez I, Yeo J, Janes J, et al. 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Trends Immunol. 2014;35:345\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.it.2014.05.004\u003c/span\u003e\u003cspan address=\"10.1016/j.it.2014.05.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":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":"Oomycetes, Receptor-like kinases, Structural characterization, Lineage-specific families, Stramenopiles, LRR-RLK","lastPublishedDoi":"10.21203/rs.3.rs-9308108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9308108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReceptor-like kinases (RLKs) are a large family of transmembrane receptors that play central roles in signal perception and transduction in plants. However, their distribution and evolution in oomycetes, which belong to the Stramenopiles lineage, remain largely unexplored. Here, we conducted a systematic proteome-wide survey of RLKomes across 233 stramenopile species, including 179 oomycetes and 54 other stramenopiles. In total, we identified 11357 RLKs (10867 in oomycetes), which are mainly clustered into six core families, with the LRR family accounting for the largest proportion. The remaining five correspond to distinct RLK families present in oomycetes, including the elicitin family, the EGF domain-containing family, and three functionally uncharacterized families. Collectively, our results systematically delineate the distribution patterns and structural diversity of the RLK superfamily in oomycetes. Furthermore, the specialized oomycete RLK database established in this study provides a foundational resource for investigating the evolutionary dynamics and functional mechanisms of these critical signaling molecules.\u003c/p\u003e","manuscriptTitle":"Structural characterization of RLKomes reveals lineage-specific families in oomycetes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 09:58:30","doi":"10.21203/rs.3.rs-9308108/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":"dd7deba8-ed62-431a-8c2e-22d5a28819f6","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T06:06:14+00:00","index":23,"fulltext":""},{"type":"reviewerAgreed","content":"155330994783934058929130161291422868092","date":"2026-05-07T10:45:49+00:00","index":19,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T09:58:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 09:58:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9308108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9308108","identity":"rs-9308108","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}