Pan-genomic insights into RLK family evolution and adaptation in Dioscorea alata

Pan-genomic insights into RLK family evolution and adaptation in Dioscorea alata | 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 Pan-genomic insights into RLK family evolution and adaptation in Dioscorea alata Zhi-Yan Wei, Sai-Xi Li, Ming-Han Li, Jie Tang, Yu-Qian Jiang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7198655/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Oct, 2025 Read the published version in Plant Molecular Biology → Version 1 posted 7 You are reading this latest preprint version Abstract Dioscorea alata (greater yam) is a vital tuber crop underpinning global food security, while this crop suffers great reduction due to diseases like anthracnose, yam mosaic virus, and tuber rot. Receptor-like kinases (RLKs) play pivotal role in plant disease resistance, transducing plant immune signal. Yet the evolutionary dynamics of RLKs remain underexplored in D. alata . Here, we leveraged seven chromosome-level D. alata genomes to characterize the pan-RLKome of D. alata , identifying 4,119 RLK genes across 48 subfamilies. Our analysis revealed moderate variation in total RLK numbers but striking subfamily-specific expansions on several chromosome hotspots driven primarily by whole-genome/segmental duplication. Phylogenomic reconstruction uncovered pervasive extracellular domain swaps, fusions, and losses, contributing to diversified RLK architectures. Selection pressure analyses showed that purifying selection has maintained core RLK functions, while positive selection drove adaptive evolution in stress-associated subfamilies. Our study uncovers the pan-genomic basis of RLK evolution in D. alata , highlighting how duplication mechanisms and domain plasticity underpin functional innovation and environmental adaptation in this vital crop. Dioscorea alata pan-RLKome duplication subfamiliy evolution adaptation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Key Message Dioscorea alata's pan-RLKome reveals subfamily-specific expansions and domain plasticity driven by duplications, with purifying and positive selection shaping immune receptor evolution for disease adaptation. Introduction Greater yam ( Dioscorea alata ), also called water yam or winged yam, is cultivated worldwide, serving as an important food crop for millions of people especially in tropical and subtropical regions 1 , 2 . D. alata stands out in a number of cultivated yams ( Dioscorea spp.) for its high production, ease of storage, and strong disease resistance 3 , 4 . The tubers of D. alata are rich in a variety of nutrients, including carbohydrates, proteins, fats, and vitamins 5 . The unique bioactive molecule relating to the antioxidant system, i.e. diosgenin, also provide D. alata particular properties as herb medicine 6 . As the world’s fourth most important tuber crop (right behind cassava, potato, and sweet potato), D. alata has gained more and more attention for providing food diversity and security 1 . Signal perception and processing via cell-surface localized receptors is vital for all living organisms. In plants, receptor-like kinases (RLKs) function as receptors at the cell surface and represent one of the largest gene families 7 , 8 . Plant RLKs share a monophyletic origin with animal interleukin-1 receptor-associated kinase and Pelle kinases 9 . During plant evolution, the RLK family has experienced dramatic expansion and diversification, which is thought to be crucial for plant adaptation to changeable environments 10 . The domain architecture of RLKs is represented by the presence of a cytosolic kinase domain (KD), a transmembrane domain (TMD), and an extracellular domain (ECD) 7 . RLKs perceive both self- and non-self-derived signals through diverse ECDs and transduces the signals downstream via their KDs 7 . Dozens of RLK subfamilies have been established based on the phylogenetic relationships of KD and the identity of ECD, with leucine-rich repeat (LRR)-RLK being the predominant subfamily 9 , 10 , 11 . It has been widely reported that RLKs can play roles in a diverse range of biological processes, including growth and development, reproduction, interaction with microbes, as well as biotic and abiotic responses 7 , 8 . For example, two well characterized LRR-RLKs brassinosteroid insensitive 1 ( BRI1 ) and flagellin sensing 2 ( FLS2 ) participate in brassinosteroid-mediated growth responses and bacterial flagellin perception, respectively 12 , 13 , 14 , 15 . In light of the recent publication of sequenced genome of D. alata 16 , genome-wide identification and analysis of its RLK gene family has been conducted, providing useful insights into the evolutionary history and potential functional mechanism of RLK genes in D. alata 17 . However, with the great advancements in sequencing technology, more and more evidence show that a single “reference” genome is far from sufficient for fully depicting the genome content of one species 18 . Therefore, the concept of pan-genome has been proposed, meaning the whole non-redundant collection of genomic sequences of a species 18 . Pan-genome consists of the core genes, shared by all individuals, and the variable genes or dispensable genes, which are present only in some but not all individuals 19 , 20 . Dissecting the pan-genome is of great necessity for providing the information of genetically structural variants (SVs), including single-nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy-number variants (CNVs), and presence/absence variants (PAVs). These SVs have been proven to be the contributor to many important phenotypic variations 19 , 20 . However, the elaborate profile of D. alata RLK gene family in the context of pan-genome remains to be explored, impeding the comprehensive understanding on the evolutionary dynamics of RLK genes in D. alata . In this study, with the aid of seven high-quality chromosome-level genomes of D. alata 21 , we aimed to dissect the evolutionary dynamics of the RLK gene family at the pan-genome scale. By integrating genome-wide identification, phylogenetic reconstruction, and selection pressure analysis, we systematically explored the variation in RLK gene content, chromosomal distribution, duplication mechanisms, and domain architecture diversification across diverse accessions. Our work not only provides the first comprehensive characterization of the D. alata pan-RLKome but also unravels how specific RLK subfamilies have been shaped by both purifying and positive selection, reflecting their roles in balancing functional conservation and adaptive innovation. This pan-genome perspective bridges the gap between structural variation and functional evolution, offering a foundation for understanding RLK-mediated adaptability in D. alata and informing strategies for enhancing stress resilience in this vital crop species. Methods Genomes used in this study Genomes of seven D. alata accessions were included in this study, which are ZSDa006 (guangzhougaotie) 21 , ZSDa005 (suyu6hao), ZSDa015(ziyushanyao), ZSDa018 (S10 zisejiaobanshu), ZSDa019 (S22 jiaobanshu), ZSDa022 (S36 tangbeijiaobanshu), and ZSDa046 (nanyuanshenshu). The RLK sequences of the seven accessions are available at the China National GeneBank DataBase (CNGB) under accession number CNP0007639. Identification of RLK genes The primary transcripts of the annotated proteomes across seven D. alata accessions were filtered for downstream analysis. First, the hmmsearch programme in HMMER (v.3.3) 26 was used to search the KD (Pkinase, Pfam: PF00069.28) (e-value: 1 × 10 − 1 ). Second, we scanned all domains presented in the obtained kinase candidates through the hmmscan programme in HMMER (v.3.3) 26 (e-value: 1 × 10 − 1 ). Third, TMD and potential signal peptide were identified by adopting TMbed, a protein language model-based method in predicting the transmembrane helix or sheet domain 22 . Proteins with N-terminal ECD, intermediate TMD and C-terminal KD were identified as RLKs. Classification of RLK genes Dozens of RLK subfamilies have been established based on the phylogenetic relationships of KD and the identity of ECD 11 . The hidden Markov models (HMMs) built in a previous landmark study 11 were used to assign RLK members into different subfamilies and subgroups through hmmsearch (e-value: 1 × 10 − 10 ). Duplication events and collinearity analysis On the basis of copy number and genomic distribution, genes within a single genome can be classified as one of the five types: singleton, dispersed duplicate, proximal duplicate, tandem duplicate and segmental/WGD duplicate 27 . We initially conducted all-against-all blast analysis for protein sequences of each seven D. alata accession via DIAMOND (v.2.0.14) 28 (e-value: 1 × 10 − 5 ). Next, the obtained blast result files and genome annotation files were used to determine duplication type and collinearity relationship of all annotated proteins through MCScanX 23 . The “advanced circus” module of TBtools-II 27 was adopted to visualize the synteny blocks of RLK genes. Sequence alignment and phylogenetic analysis Depending on the hmmscan results (e-value: 1 × 10 − 1), we extracted the protein sequences of KDs from RLKs. Then, we adopted MAFFT (v.7) 29 to align the KD sequences. FastTree (v.2.1.11) 30 was used to conduct the phylogenetic analyses with default parameters. The R package ggtree (v.3.16) 31 was used to visualize the phylogenetic trees. Orthogroup determination and selection pressure analysis Clades were defined as OGs if all descendant leaves had cumulative branch lengths ≤ 0.05 and represented ≥ four accessions. Non-overlapping clusters were prioritized by size, with remaining genes classified as non_OG. We performed the selection pressure analysis on each determined OG through ParaAT (v.2) 32 and KaKs_Calculator 2.0 (ref. 33 ). Results Construction of D. alata pan-RLKome based on genomes from seven accessions Seven D. alata accessions with chromosome-level genomes were collected in this study, one of which was assembled to near telomere-to-telomere (T2T) standard 21 . By utilizing the language-model-based RLK detection method 17 , 22 , we identified and classified the RLK gene family in each D. alata accession. A total of 4,119 RLK genes were retrieved, with 3,552 RLKs possessing both ECDs and TMDs, and 568 RLKs having only TMDs but lacking definite ECDs (Fig. 1 A; Supplementary Table 1; Supplementary Data 1). Considering that the annotated ECDs were not deemed as the indispensable criterion for identifying RLKs in recent researches, we retained those RLKs without ECDs to maximize the prediction of transmembrane receptors. The average RLK gene number of seven D. alata accessions was 588. ZSDa018 and ZSDa019 had the most and fewest RLK genes among them, with number of 603 and 577, respectively (Fig. 1 A). This indicated that the variation degree of D. alata RLK gene number was moderate. We grouped RLK genes into 48 subfamilies by interrogating plant kinase Hidden Markov Models (HMMs) established by phytogenic relationships in a previous landmark study 11 . The largest subfamily was LRR-RLK as expected, with its number ranging from 230 in ZSDa019 to 243 in ZSDa015, followed by DLSV (DUF26, SD-1, LRR-VIII, and VWA), L-LEC, SD-2b, and LRK10L-2 (Fig. 1 B). On the basis of HMMs, LRR-RLK were further classified into 23 subgroups, among which LRR-XI-1, LRR-III, and LRR-XII-1 being the first three abundant subgroups (Fig. 1 C). Subfamilies not mentioned above, with or without LRR, tended to have comparatively smaller but more constant gene number (Fig. 1 C-D). To determine the variation degree of D. alata RLK subfamily gene number, we calculated the standard deviation of each subfamily. Our results showed that LRK10L-2, LRR-XI-1, DLSV, LRR-III, and SD-2b exhibited the highest dispersion degree (Supplementary Fig. 1). Interestingly, they represented the biggest subfamilies at the same time (Fig. 1 B-D). By comparison, the small subfamilies were often more constant and conserved since their values of standard deviation were lower and some even reached 0 (Supplementary Fig. 1). Since the large RLK subfamilies are often reported to be versatile, their flexibility might reflect the capability of plant adaptation throughout evolution. Through scrutinizing of our data, we observed a remarkable increase of the LRK10L-2 gene number in ZSDa018, with at least 20 more than others, which could be the cause of the larger RLK gene number in ZSDa018 as well as the higher dispersion degree in LRK10L-2 (Fig. 1 D; Supplementary Table 1). D. alata pan-RLKome localization dynamics underscores the chromosomal hotspots To explore the chromosomal distribution pattern of D. alata RLK genes, we retrieved their physical locations from each D. alata accession. Our results showed that RLK genes were distributed in all 20 D. alata chromosomes, among which chromosome (Chr) 15 (Chr15) contained the most RLK genes (range from 82 to 93), whereas only two RLK genes were distributed on Chr6 (Fig. 2 A). Interestingly, RLK gene number among seven D. alata accessions maintained constant only on two chromosomes (Chr6 and Chr11), but showed more or less variable on other chromosomes (Fig. 2 A; Supplementary Fig. 2). We found the largest value of standard deviation on Chr16, where ZSDa018 owned a substantially increase of RLK (Fig. 2 A; Supplementary Fig. 2). Collectively, these results suggested that both the inter- and intra-chromosomal distributions of RLK genes were uneven and swiftly fine-tuned throughout evolution. Considering the complex composition of RLK gene family, we inquired the arrangement of each RLK subfamily on D. alata chromosomes and analyzed their inter-accession differences. The results showed that Chr5 had the most diversified RLK subfamilies (23 subfamilies), while Chr6 had only two RLK subfamilies (LRR-III and RLCK-V) (Fig. 2 B). Interestingly, although the most widely distributed subfamily, LRR-III, could be detected on 18 chromosomes, a total of 10 subfamilies were localized on merely one chromosome (Fig. 2 B). Furthermore, the value of standard deviation of LRK10L-2 on Chr16, LRR-XI-1 on Chr2, and DLSV on Chr15 ranked at the top three, which exactly coincided with the most variable subfamilies as well as chromosomes (Fig. 1 C-D; Fig. 2 B; Supplementary Figs. 1–2). Taken together, our resulted indicated that the variation of pan-RLKome in D. alata was not unlimited and could be attributed to differences caused by members from specific RLK subfamilies and on specific chromosomes. Diverse duplication mechanisms shaped the expansion history of D. alata pan-RLKome In view of the large size of RLK gene family, we delved into its expansion history in D. alata under the background of pan-genome. The duplication types of RLK genes from seven D. alata accessions were analyzed by adopting MCScanX package 23 (Supplementary Table 2). Approximately a quarter of RLK genes were generated by tandem duplication, and another quarter were resulted from whole genome duplication (WGD) and/or segmental duplication (SD) (Fig. 3 A). In addition, less than 20% RLK genes were resulted from proximal duplication (Fig. 3 A). It was noteworthy that no singleton RLK gene was detected in all seven D. alata accessions (Fig. 3 A), indicating that RLK repertoires were largely shaped by the recurrent and ubiquitous duplication events. We further investigated the duplication types of each RLK subfamily and found that the majority of RLK subfamilies have experienced dispersed duplication (44/48) and WGD/SD (30/48) (Fig. 3 B). By comparison, tandem duplication (15/48) and proximal duplication (14/48) contributed to the expansion of only one third of RLK subfamilies, respectively (Fig. 3 B). Interestingly, RLK genes duplicated via WGD/SD were more abundant in ZSDa018 and ZSDa046 (Fig. 3 A). Compared to other accessions, ZSDa018 and ZSDa046 contained remarkably elevated amount of WGD/SD-derived LRK10L-2 and LRR-XI-1 genes, respectively, and both of them also possessed larger number of WGD/SD-derived DLSV genes (Fig. 3 B; Supplementary Fig. 3). To dissect the expansion dynamics of RLK subfamilies in D. alata , we conducted the synteny analysis and delineated the specific gene loci that were produced by WGD/SD. Our analysis revealed extensive blocks of collinearity within the genomes of seven accessions, pinpointing numerous duplicated regions derived from ancient polyploidization and/or large-scale segmental duplication events (Supplementary Fig. 4A-G). Specifically, in ZSDa018, clusters of WGD/SD-derived LRK10L-2 genes were predominantly localized within collinear blocks on Chr16 (Supplementary Fig. 4D), indicating their origin from shared ancestral duplication events. Similarly, ZSDa046 exhibited dense clusters of LRR-XI-1 genes within syntenic regions on Chr2 (Supplementary Fig. 4G). Furthermore, the enrichment of DLSV genes via WGD/SD in both accessions was corroborated by their frequent occurrence within these identified collinear blocks across Chr5 (Supplementary Fig. 4A-G). These intra-specific synteny patterns provide strong genomic evidence supporting the significant role of WGD/SD events in driving the lineage-specific expansion of key RLK subfamilies. Evolutionary trajectory and domain architecture diversification of D. alata pan-RLKome The intricate evolutionary trajectory of RLK gene family has long been mysterious due to its large size and numerous subfamily composition. Several dedicated researches have been conducted for model plants 9 , 10 , 11 , 17 , but the pan-genome-based analysis still remains scarce. To provide a panoramic evolutionary history of D. alata RLK gene family, we reconstructed the phylogeny of the pan-RLKome in seven D. alata accessions (Supplementary Fig. 5; Supplementary Data 2). Interestingly, we found that one same clade in the phylogenetic tree could often accommodate RLKs derived from different subfamilies and/or located on different chromosomes, indicating the frequent ECD changes and chromosome-translocations of RLKs (Fig. 4 A). For example, as the largest RLK subfamily, LRR-RLK did not form a monophyletic group but rather belonged to several different clades (Fig. 4 A). Similarly, subfamilies of receptor-like cytosolic kinases (RLCKs) were also distributed on a couple of clades (Fig. 4 A). A wide variety of types of domains are integrated into the RLK gene family to serve as ECDs. Therefore, we probed into the evolutionary roadmap of RLK domain architectures by determining the ECD types. Totally, eight classes of ECD type were identified, including cysteine-rich repeat (CRR), lectin, LRR, lysin motif (LysM), malectin, regulator of chromosome condensation repeat (RCC), similar protein to arbuscular receptor-like kinase (SPARK), and wall-associated kinase (WAK) (Fig. 4 B; Supplementary Figs. 6–7; Supplementary Table 3). CRR, LysM and RCC domains were specifically adopted as ECDs in DLSV, LysM-RLK and CR4L subfamilies, respectively (Fig. 4 B; Supplementary Figs. 6–7). Among the subfamilies with lectin as ECD, C-LEC, L-LEC, and SD-2b/DLSV held the C-type, L-type, and B-type lectin domains, respectively (Fig. 4 B; Supplementary Figs. 6–7). LRR, malectin, SPARK, WAK domains were integrated into more than one RLK subfamilies, underscoring the versatility of these ECDs (Fig. 4 B; Supplementary Figs. 6–7). Despite the various ECD types, no ECD was found at all in 13 RLK subfamilies, which implied their intrinsic role in intercellular signal transduction but not perceiving extracellular stimuli (Fig. 4 B; Supplementary Fig. 6–7). The phylogeny of RLK subfamilies mapped with ECD types showed the swift and frequent ECD domain change events (Fig. 4 B). The inositol-requiring enzyme 1 (IRE1) clade that contained TMD but no ECD was the sister group to all other RLK subfamilies (Fig. 4 B). Homologs of IRE1 have been found in human, suggesting the ancient origin of this transmembrane kinase receptors 24 . Notably, LRR domains were predominant in many clades (Fig. 4 B), which raised the possibility that other domains could be recruited into the RLK through ECD swap mediated by LRR. Intriguingly, 14 subfamilies that comprised mostly of RLKs with ECD simultaneously contained RLKs without ECD (Supplementary Figs. 6–7). The pervasive distribution of subfamilies with no specific ECDs were across the phylogenetic tree of RLKs highlighted the universality of the ECD loss (Fig. 4 B). In a nutshell, the prevailing ECD fusion, swap, and loss events shaped the domain architectures of the RLK gene family throughout the evolution. Purifying and positive selection jointly shaped functional specialization of RLK subfamilies in D. alata To analyse the evolutionary dynamics of the D. alata pan-RLKome, we determined orthologous groups (OGs) of RLK genes using a post-order traversal strategy through systematically scanning internal nodes of the phylogenetic tree (detailed in Methods) (Supplementary Fig. 5; Supplementary Data 2). We identified 493 OGs containing totally 3,900 RLK genes, accounting for more than 94% of the D. alata pan-RLKome (Fig. 5 A; Supplementary Fig. 8; Supplementary Table 3). Most of the OGs (432/493, 87.6%) contained genes from all seven accessions (Fig. 5 A; Supplementary Table 3). Conserved OGs that possessed no more than two genes per accession accounts for the vast majority (475/493, 96.3%) (Fig. 5 A; Supplementary Table 3). This indicated that our approach allowed identification of evolutionarily conserved gene groups while maintaining accession-specific resolution. To elucidate the evolutionary forces acting on the D. alata pan-RLKome, we calculated the ratio of nonsynonymous substitution rates (Ka) to synonymous substitution rates (Ks) (Ka/Ks) for orthologous RLK genes across seven accessions. Among the 493 OGs, 240 highly conserved OGs (48.6%) exhibited Ka = 0 and Ks = 0, indicating strong purifying selection and no detectable changes of the nucleotide sequences (Fig. 5 B; Supplementary Table 4). For the remaining OGs, a pronounced proportion of them showed Ka/Ks values around 1, which meant that neutral selection and genetic drift served as the major contributor (Fig. 5 B; Supplementary Table 4). Notably, many subfamilies harboured OGs under positive selection alongside those under purifying selection, such as SD-2b, L-Lec and DLSV, suggesting their versatility (Fig. 5 C). By comparison, RLK subfamilies involved in conserved biological processes (e.g., LRR-V, WAK) showed remarkably lower Ka/Ks values (Fig. 5 C). Further subgroup analysis revealed that RLKs derived from proximal duplication events possessed more OGs with Ka/Ks < 1 values compared to those from dispersed, tandem or WGD/SD duplications (Fig. 5 D). Collectively, these results underscore the heterogeneous evolutionary pressures across RLK subfamilies, shaped by their functional specialization and duplication mechanisms. Discussion This study represents the first comprehensive dissection of the RLK gene family at a pan-genome scale in D. alata , leveraging seven high-quality chromosome-level assemblies. Our analysis revealed a pan-RLKome of 4,119 genes, extending beyond previous single-reference genome analyses which identified ~ 500 RLKs 17 . In addition, pan-genomic analysis reveals richer structural variations (e.g., copy number variations and presence-absence variations) that likely drive RLK functional diversification. The moderate variation in total RLK numbers across accessions (577–603 genes) contrasts with striking subfamily-specific expansions, notably in LRK10L-2, LRR-XI-1, DLSV, and SD-2b. Synteny and duplication analyses demonstrate that WGD/SD serve as the primary drivers of these expansions, particularly on chromosomal hotspots, such as LRK10L-2 on Chr16 in ZSDa018 and LRR-XI-1 on Chr2 in ZSDa046 (Supplementary Fig. 4). This aligns with findings in other plants, where WGD/SD events facilitate rapid neofunctionalization and adaptation gene families 25 . Tandem and proximal duplications contributed to a smaller fraction of RLKs (15–25%), underscoring the dominant role of large-scale genomic reconfigurations in shaping RLK diversity (Fig. 3 ). Phylogenomic reconstruction revealed pervasive ECD swaps, fusions, and losses across RLK clades. Subfamilies historically defined by conserved ECDs, such as LRR-RLKs, were polyphyletic, with domains like lectin, malectin, and LysM frequently exchanged or lost (Fig. 4 A). This architectural fluidity suggests evolutionary flexibility in ligand perception strategies, potentially enabling novel environmental sensing capabilities. Notably, 13 subfamilies lacked identifiable ECDs, implying roles in intracellular signaling or co-receptor functions. OG analysis identified 493 conserved RLK groups, 87.6% of which were shared across all accessions, highlighting a core RLKome stabilized by purifying selection. Strikingly, 48.6% of OGs showed no detectable sequence divergence (Ka = Ks = 0), indicating intense functional conservation (Fig. 5 ). Conversely, RLK subfamilies associated with stress responses (e.g., SD-2b, L-LEC, and DLSV) exhibited signatures of positive selection (Ka/Ks > 1), suggesting adaptive evolution to biotic/abiotic challenges. This dichotomy aligns with dual roles of RLKs: conserved kinases maintain developmental integrity, while stress-linked clades diversify under environmental pressures 10 . Subfamilies derived from proximal duplications showed stronger purifying selection than those from WGD/SD, implying tighter functional constraints in localized genomic contexts. The pan-RLKome landscape provides insights into D. alata adaptive evolution, particularly its stress resilience. The expansion of stress-related RLK subfamilies (e.g., LRK10L-2, DLSV) and the plasticity of ECDs likely contribute to its strong resistance traits, a key agronomic advantage. These findings offer targets for molecular breeding. For example, leveraging natural variation in RLK copy numbers or domain architectures to enhance disease resistance or abiotic stress tolerance. Future studies could functionalize specific RLKs via gene editing to validate their roles in stress responses, or expand pan-genomic analyses to include wild Dioscorea species to uncover ancestral RLK functions. In summary, our pan-genomic analysis reveals how duplication-driven expansion and domain plasticity have shaped the D. alata RLK repertoire, balancing functional conservation with adaptive innovation. This framework not only advances our understanding of plant receptor evolution but also provides a foundation for leveraging RLK diversity in crop improvement strategies. Declarations Author Contributions Statement J.Y.X. and Y.M.Z. conceived and designed the research. Z.Y.W., S.X.L. and M.H.L. obtained and analyzed the data; S.X.L., M.H.L. and Z.Y.W. drafted the manuscript; J.T., Y.Q.J. and X.Y.L. participated in data analyses; J.Y.X. and Y.M.Z. revised the manuscript. All the authors read and approved the final manuscript. Competing Interests Statement The authors declare no conflict of interests. Author Contribution J.Y.X. and Y.M.Z. conceived and designed the research. Z.Y.W., S.X.L. and M.H.L. obtained and analyzed the data; S.X.L., M.H.L. and Z.Y.W. drafted the manuscript; J.T., Y.Q.J. and X.Y.L. participated in data analyses; J.Y.X. and Y.M.Z. revised the manuscript. All the authors read and approved the final manuscript. Acknowledgements This work was supported by the National Natural Science Foundation of China (32172089), Scientific Fund of Nanjing Botanical Garden Mem. Sun Yat-Sen (JSPKLB202503). 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Supplementary Files figS18.pdf tableS140702.xlsx Cite Share Download PDF Status: Published Journal Publication published 20 Oct, 2025 Read the published version in Plant Molecular Biology → Version 1 posted Editorial decision: Revision requested 19 Aug, 2025 Reviews received at journal 17 Aug, 2025 Reviewers agreed at journal 28 Jul, 2025 Reviewers invited by journal 27 Jul, 2025 Editor assigned by journal 24 Jul, 2025 Submission checks completed at journal 24 Jul, 2025 First submitted to journal 23 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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-7198655","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491854837,"identity":"d8604c48-dffe-4647-94d6-3f4ce7c9b330","order_by":0,"name":"Zhi-Yan Wei","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Yan","middleName":"","lastName":"Wei","suffix":""},{"id":491854840,"identity":"6ac11d86-940d-4866-9a59-24e0178c8bc5","order_by":1,"name":"Sai-Xi Li","email":"","orcid":"","institution":"Nanjing University","correspondingAuthor":false,"prefix":"","firstName":"Sai-Xi","middleName":"","lastName":"Li","suffix":""},{"id":491854842,"identity":"420154b0-ac60-492e-9d15-a7b4f89eb364","order_by":2,"name":"Ming-Han Li","email":"","orcid":"","institution":"Jiangsu Province and Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ming-Han","middleName":"","lastName":"Li","suffix":""},{"id":491854844,"identity":"4fad44ed-90e5-4837-aa64-56fb92192940","order_by":3,"name":"Jie Tang","email":"","orcid":"","institution":"Crop Research Institute of Jiangxi Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Tang","suffix":""},{"id":491854845,"identity":"bfb33c03-eef5-45d9-b777-ce5c32c5a416","order_by":4,"name":"Yu-Qian Jiang","email":"","orcid":"","institution":"Nanjing University","correspondingAuthor":false,"prefix":"","firstName":"Yu-Qian","middleName":"","lastName":"Jiang","suffix":""},{"id":491854846,"identity":"0574311c-a631-4f7e-87d3-77ca8720eb6d","order_by":5,"name":"Xin-Yu Lu","email":"","orcid":"","institution":"Jiangsu Province and Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xin-Yu","middleName":"","lastName":"Lu","suffix":""},{"id":491854847,"identity":"9cd058ac-aeaa-45a7-8bfe-55477bb31377","order_by":6,"name":"Yan-Mei Zhang","email":"","orcid":"","institution":"Jiangsu Province and Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yan-Mei","middleName":"","lastName":"Zhang","suffix":""},{"id":491854848,"identity":"a02e5264-8e90-4ec5-ac1b-76defc508959","order_by":7,"name":"Jia-Yu Xue","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYJACA4YKBmYwi4d4LWdI1cLA2AZlEKXF4EbygWLeeXfY+WckMD5428Ygb05Ii+SMtARj3m3PmCVuJDAbzm1jMNzZQEALv0SOAVDLYWaGGwls0rxtDAkGBwhoYZPI/2DMO+cws/yNBPbfRGkB2sJgzNtwmNkAaAszUVoke54ZGM45dpjZ8MzDZsk55yQMNxDSYnA8+ZnBm5rDyXLHkw9+eFNmI0/QFpB3jIDRkQyMnQYgR4KweiBgfviDgcGOKKWjYBSMglEwMgEAfvQ7zA9BFcMAAAAASUVORK5CYII=","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Jia-Yu","middleName":"","lastName":"Xue","suffix":""}],"badges":[],"createdAt":"2025-07-23 16:53:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7198655/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7198655/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11103-025-01647-w","type":"published","date":"2025-10-20T16:16:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87859813,"identity":"57cf1a1f-a993-441e-8b50-14a860863657","added_by":"auto","created_at":"2025-07-29 17:55:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":418207,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eD. alata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e pan-RLKome constructed on seven accession genomes. A\u003c/strong\u003e Distribution of the RLK gene numbers across seven \u003cem\u003eD. alata\u003c/em\u003eaccession genomes. The RLK gene numbers are presented as bar plots. RLK with ECD is indicated in red, while RLK without ECD is indicated in cyan. \u003cstrong\u003eB\u003c/strong\u003eProportions of the RLK subfamilies in \u003cem\u003eD. alata\u003c/em\u003e pan-RLKome. The proportions are presented as bar plots. LRR, DLSV, L-LEC, SD-2b, LRK10L-2, and other subfamilies are indicated in different colours. \u003cstrong\u003eC\u003c/strong\u003e Distribution of the RLK gene numbers across subgroups of LRR-RLKs. The RLK gene numbers are presented as boxplots, with points representing each accession in different colours (centre line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range; points, each accession). \u003cstrong\u003eD\u003c/strong\u003e Distribution of the RLK gene number across non-LRR-RLK subfamilies. The RLK gene numbers are presented as boxplots, with points representing each accession in different colours (centre line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range; points, each accession).\u003c/p\u003e","description":"","filename":"fig151.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/c03b8f2b09ea08cb38ab770d.jpg"},{"id":87859905,"identity":"d53dc9ac-6298-49ca-acab-6f7d7ca78430","added_by":"auto","created_at":"2025-07-29 18:03:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":467295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChromosomal distribution of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eD. alata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e pan-RLKome. A \u003c/strong\u003eDistribution of the RLK gene numbers across 20 \u003cem\u003eD. alata\u003c/em\u003e chromosomes. The RLK gene numbers are presented as boxplots, with points representing each accession in different colours (centre line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range; points, each accession). \u003cstrong\u003eB\u003c/strong\u003eDistribution of the 46 RLK gene subfamilies across 20 D. alata chromosomes. The RLK gene numbers are presented as a bubble diagram, with the colour and size key shown at the right. Brown point indicates that only one accession possessed RLK gene on corresponding chromosome.\u003c/p\u003e","description":"","filename":"fig152.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/ecd0bad70d98167f36e45446.jpg"},{"id":87859907,"identity":"d4522251-e5f8-4de4-9163-3e68cee27377","added_by":"auto","created_at":"2025-07-29 18:03:35","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":362428,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiverse duplication mechanisms of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eD. alata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e pan-RLKome. A \u003c/strong\u003eNumber and proportion of the duplication events on RLK genes from seven \u003cem\u003eD. alata \u003c/em\u003eaccessions. The RLK gene numbers are presented as a heat map, with the colour key shown at the right. \u003cstrong\u003eB\u003c/strong\u003e Distribution of the duplication events on 46 RLK subfamilies from seven \u003cem\u003eD. alata\u003c/em\u003e accessions. The RLK gene numbers are presented as stacked bar charts. Seven \u003cem\u003eD. alata\u003c/em\u003e accessions are indicated in different colours.\u003c/p\u003e","description":"","filename":"fig153.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/e90bb8d0d369a88bb89a54c9.jpg"},{"id":87859814,"identity":"28110b39-a8fc-4f63-9b06-6da6bcedd83c","added_by":"auto","created_at":"2025-07-29 17:55:35","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":508751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolutionary trajectory of RLK gene family in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eD. alata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. A \u003c/strong\u003ePhylogenetic tree of \u003cem\u003eD. alata\u003c/em\u003e pan-RLKome. Points on the leaf tip represent the accessions in different colours. The outlier ring indicates the RLK subfamilies in different colour. \u003cstrong\u003eB\u003c/strong\u003e Phylogenetic relationship of RLK subfamilies. The RLK gene numbers are presented as bar plots. RLK with different ECD types are shown in different colours.\u003c/p\u003e","description":"","filename":"fig154.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/357a06e9ed621b39962c373d.jpg"},{"id":87859906,"identity":"36b4027e-3205-4e21-a571-c517c90bb680","added_by":"auto","created_at":"2025-07-29 18:03:35","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":403972,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelection pressure analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eD. alata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e pan-RLKome. A\u003c/strong\u003e Composition of \u003cem\u003eD. alata\u003c/em\u003e RLK OGs. The left section of the Sankey diagram classifies accessions into two groups: “7 accessions” and “\u0026lt; 7 accessions”. The middle section presents different RLK OG subfamilies, including LRR, DLSV, L - LEC, SD - 2b, and others. The right section shows the classification of gene copy numbers per OG: “1 gene”, “1–2 genes”, and “\u0026gt; 2 genes”. \u003cstrong\u003eB\u003c/strong\u003e Frequency distribution of Ka, Ks, and Ka/Ks of \u003cem\u003eD. alata\u003c/em\u003e RLK OGs. The values of Ka (red), Ks (green), and Ka/Ks (blue) are presented as a histogram. \u003cstrong\u003eC\u003c/strong\u003eDistribution of Ka/Ks of \u003cem\u003eD. alata\u003c/em\u003e RLK OGs in 46 RLK subfamilies. The values of Ka/Ks are presented as boxplots, with points representing each OG (centre line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range; points, each OG). Points with Ka/Ks \u0026gt; 1 are indicated in red, while points with Ka/Ks \u0026lt; 1 are indicated in blue. \u003cstrong\u003eD\u003c/strong\u003eDistribution of Ka/Ks of D. alata RLK OGs in four duplication types. The values of Ka/Ks are presented as boxplots and violin plots, with points representing each OG (centre line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range; points, each OG). Red dots indicate mean values. Pairwise significance of differences was determined using two-sided Mann-Whitney U-test, and only significant groups are shown.\u003c/p\u003e","description":"","filename":"fig155.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/a5548588b1f36ff6cf3c230b.jpg"},{"id":94490570,"identity":"285c9647-46d6-49cb-b250-1dcf20943640","added_by":"auto","created_at":"2025-10-27 17:12:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3028802,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/8c457eb0-3dff-43f1-bc2d-75166d80075c.pdf"},{"id":87859862,"identity":"a8670b48-1221-4617-a9e6-0b991d47a583","added_by":"auto","created_at":"2025-07-29 17:55:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":46978332,"visible":true,"origin":"","legend":"","description":"","filename":"figS18.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/c736fbde2558909ffff4b511.pdf"},{"id":87859818,"identity":"a6e5f8e7-b856-4d32-a433-2c5045aabfd3","added_by":"auto","created_at":"2025-07-29 17:55:35","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":376460,"visible":true,"origin":"","legend":"","description":"","filename":"tableS140702.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7198655/v1/58566683af4c1ab211ec02c0.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pan-genomic insights into RLK family evolution and adaptation in Dioscorea alata","fulltext":[{"header":"Key Message","content":"\u003cp\u003e\u003cem\u003eDioscorea alata's\u0026nbsp;\u003c/em\u003epan-RLKome reveals subfamily-specific expansions and domain plasticity driven by duplications, with purifying and positive selection shaping immune receptor evolution for disease adaptation.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eGreater yam (\u003cem\u003eDioscorea alata\u003c/em\u003e), also called water yam or winged yam, is cultivated worldwide, serving as an important food crop for millions of people especially in tropical and subtropical regions\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eD. alata\u003c/em\u003e stands out in a number of cultivated yams (\u003cem\u003eDioscorea\u003c/em\u003e spp.) for its high production, ease of storage, and strong disease resistance\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The tubers of \u003cem\u003eD. alata\u003c/em\u003e are rich in a variety of nutrients, including carbohydrates, proteins, fats, and vitamins\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The unique bioactive molecule relating to the antioxidant system, i.e. diosgenin, also provide \u003cem\u003eD. alata\u003c/em\u003e particular properties as herb medicine\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. As the world\u0026rsquo;s fourth most important tuber crop (right behind cassava, potato, and sweet potato), \u003cem\u003eD. alata\u003c/em\u003e has gained more and more attention for providing food diversity and security\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSignal perception and processing via cell-surface localized receptors is vital for all living organisms. In plants, receptor-like kinases (RLKs) function as receptors at the cell surface and represent one of the largest gene families\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Plant RLKs share a monophyletic origin with animal interleukin-1 receptor-associated kinase and Pelle kinases\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. During plant evolution, the RLK family has experienced dramatic expansion and diversification, which is thought to be crucial for plant adaptation to changeable environments\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The domain architecture of RLKs is represented by the presence of a cytosolic kinase domain (KD), a transmembrane domain (TMD), and an extracellular domain (ECD)\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. RLKs perceive both self- and non-self-derived signals through diverse ECDs and transduces the signals downstream via their KDs\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Dozens of RLK subfamilies have been established based on the phylogenetic relationships of KD and the identity of ECD, with leucine-rich repeat (LRR)-RLK being the predominant subfamily\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. It has been widely reported that RLKs can play roles in a diverse range of biological processes, including growth and development, reproduction, interaction with microbes, as well as biotic and abiotic responses\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. For example, two well characterized LRR-RLKs \u003cem\u003ebrassinosteroid insensitive 1\u003c/em\u003e (\u003cem\u003eBRI1\u003c/em\u003e) and \u003cem\u003eflagellin sensing 2\u003c/em\u003e (\u003cem\u003eFLS2\u003c/em\u003e) participate in brassinosteroid-mediated growth responses and bacterial flagellin perception, respectively\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn light of the recent publication of sequenced genome of \u003cem\u003eD. alata\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, genome-wide identification and analysis of its RLK gene family has been conducted, providing useful insights into the evolutionary history and potential functional mechanism of RLK genes in \u003cem\u003eD. alata\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, with the great advancements in sequencing technology, more and more evidence show that a single \u0026ldquo;reference\u0026rdquo; genome is far from sufficient for fully depicting the genome content of one species\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Therefore, the concept of pan-genome has been proposed, meaning the whole non-redundant collection of genomic sequences of a species\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Pan-genome consists of the core genes, shared by all individuals, and the variable genes or dispensable genes, which are present only in some but not all individuals\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Dissecting the pan-genome is of great necessity for providing the information of genetically structural variants (SVs), including single-nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy-number variants (CNVs), and presence/absence variants (PAVs). These SVs have been proven to be the contributor to many important phenotypic variations\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. However, the elaborate profile of \u003cem\u003eD. alata\u003c/em\u003e RLK gene family in the context of pan-genome remains to be explored, impeding the comprehensive understanding on the evolutionary dynamics of RLK genes in \u003cem\u003eD. alata\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eIn this study, with the aid of seven high-quality chromosome-level genomes of \u003cem\u003eD. alata\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, we aimed to dissect the evolutionary dynamics of the RLK gene family at the pan-genome scale. By integrating genome-wide identification, phylogenetic reconstruction, and selection pressure analysis, we systematically explored the variation in RLK gene content, chromosomal distribution, duplication mechanisms, and domain architecture diversification across diverse accessions. Our work not only provides the first comprehensive characterization of the \u003cem\u003eD. alata\u003c/em\u003e pan-RLKome but also unravels how specific RLK subfamilies have been shaped by both purifying and positive selection, reflecting their roles in balancing functional conservation and adaptive innovation. This pan-genome perspective bridges the gap between structural variation and functional evolution, offering a foundation for understanding RLK-mediated adaptability in \u003cem\u003eD. alata\u003c/em\u003e and informing strategies for enhancing stress resilience in this vital crop species.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eGenomes used in this study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGenomes of seven \u003cem\u003eD. alata\u003c/em\u003e accessions were included in this study, which are ZSDa006 (guangzhougaotie)\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, ZSDa005 (suyu6hao), ZSDa015(ziyushanyao), ZSDa018 (S10 zisejiaobanshu), ZSDa019 (S22 jiaobanshu), ZSDa022 (S36 tangbeijiaobanshu), and ZSDa046 (nanyuanshenshu). The RLK sequences of the seven accessions are available at the China National GeneBank DataBase (CNGB) under accession number CNP0007639.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIdentification of RLK genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe primary transcripts of the annotated proteomes across seven \u003cem\u003eD. alata\u003c/em\u003e accessions were filtered for downstream analysis. First, the hmmsearch programme in HMMER (v.3.3)\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e was used to search the KD (Pkinase, Pfam: PF00069.28) (e-value: 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Second, we scanned all domains presented in the obtained kinase candidates through the hmmscan programme in HMMER (v.3.3)\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e (e-value: 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Third, TMD and potential signal peptide were identified by adopting TMbed, a protein language model-based method in predicting the transmembrane helix or sheet domain\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Proteins with N-terminal ECD, intermediate TMD and C-terminal KD were identified as RLKs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eClassification of RLK genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDozens of RLK subfamilies have been established based on the phylogenetic relationships of KD and the identity of ECD\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The hidden Markov models (HMMs) built in a previous landmark study\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e were used to assign RLK members into different subfamilies and subgroups through hmmsearch (e-value: 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;10\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDuplication events and collinearity analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOn the basis of copy number and genomic distribution, genes within a single genome can be classified as one of the five types: singleton, dispersed duplicate, proximal duplicate, tandem duplicate and segmental/WGD duplicate\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. We initially conducted all-against-all blast analysis for protein sequences of each seven \u003cem\u003eD. alata\u003c/em\u003e accession via DIAMOND (v.2.0.14)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e (e-value: 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e). Next, the obtained blast result files and genome annotation files were used to determine duplication type and collinearity relationship of all annotated proteins through MCScanX\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The \u0026ldquo;advanced circus\u0026rdquo; module of TBtools-II\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e was adopted to visualize the synteny blocks of RLK genes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSequence alignment and phylogenetic analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDepending on the hmmscan results (e-value: 1 \u0026times; 10\u0026thinsp;\u0026minus;\u0026thinsp;1), we extracted the protein sequences of KDs from RLKs. Then, we adopted MAFFT (v.7)\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e to align the KD sequences. FastTree (v.2.1.11)\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e was used to conduct the phylogenetic analyses with default parameters. The R package ggtree (v.3.16)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e was used to visualize the phylogenetic trees.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOrthogroup determination and selection pressure analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eClades were defined as OGs if all descendant leaves had cumulative branch lengths\u0026thinsp;\u0026le;\u0026thinsp;0.05 and represented\u0026thinsp;\u0026ge;\u0026thinsp;four accessions. Non-overlapping clusters were prioritized by size, with remaining genes classified as non_OG. We performed the selection pressure analysis on each determined OG through ParaAT (v.2)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and KaKs_Calculator 2.0 (ref.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eConstruction of\u003c/b\u003e \u003cb\u003eD. alata\u003c/b\u003e \u003cb\u003epan-RLKome based on genomes from seven accessions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSeven \u003cem\u003eD. alata\u003c/em\u003e accessions with chromosome-level genomes were collected in this study, one of which was assembled to near telomere-to-telomere (T2T) standard\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. By utilizing the language-model-based RLK detection method\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, we identified and classified the RLK gene family in each \u003cem\u003eD. alata\u003c/em\u003e accession. A total of 4,119 RLK genes were retrieved, with 3,552 RLKs possessing both ECDs and TMDs, and 568 RLKs having only TMDs but lacking definite ECDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; Supplementary Table\u0026nbsp;1; Supplementary Data 1). Considering that the annotated ECDs were not deemed as the indispensable criterion for identifying RLKs in recent researches, we retained those RLKs without ECDs to maximize the prediction of transmembrane receptors. The average RLK gene number of seven \u003cem\u003eD. alata\u003c/em\u003e accessions was 588. ZSDa018 and ZSDa019 had the most and fewest RLK genes among them, with number of 603 and 577, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). This indicated that the variation degree of \u003cem\u003eD. alata\u003c/em\u003e RLK gene number was moderate.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe grouped RLK genes into 48 subfamilies by interrogating plant kinase Hidden Markov Models (HMMs) established by phytogenic relationships in a previous landmark study\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The largest subfamily was LRR-RLK as expected, with its number ranging from 230 in ZSDa019 to 243 in ZSDa015, followed by DLSV (DUF26, SD-1, LRR-VIII, and VWA), L-LEC, SD-2b, and LRK10L-2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). On the basis of HMMs, LRR-RLK were further classified into 23 subgroups, among which LRR-XI-1, LRR-III, and LRR-XII-1 being the first three abundant subgroups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Subfamilies not mentioned above, with or without LRR, tended to have comparatively smaller but more constant gene number (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D).\u003c/p\u003e\u003cp\u003eTo determine the variation degree of \u003cem\u003eD. alata\u003c/em\u003e RLK subfamily gene number, we calculated the standard deviation of each subfamily. Our results showed that LRK10L-2, LRR-XI-1, DLSV, LRR-III, and SD-2b exhibited the highest dispersion degree (Supplementary Fig.\u0026nbsp;1). Interestingly, they represented the biggest subfamilies at the same time (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-D). By comparison, the small subfamilies were often more constant and conserved since their values of standard deviation were lower and some even reached 0 (Supplementary Fig.\u0026nbsp;1). Since the large RLK subfamilies are often reported to be versatile, their flexibility might reflect the capability of plant adaptation throughout evolution. Through scrutinizing of our data, we observed a remarkable increase of the LRK10L-2 gene number in ZSDa018, with at least 20 more than others, which could be the cause of the larger RLK gene number in ZSDa018 as well as the higher dispersion degree in LRK10L-2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD; Supplementary Table\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003cb\u003eD. alata\u003c/b\u003e \u003cb\u003epan-RLKome localization dynamics underscores the chromosomal hotspots\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore the chromosomal distribution pattern of \u003cem\u003eD. alata\u003c/em\u003e RLK genes, we retrieved their physical locations from each \u003cem\u003eD. alata\u003c/em\u003e accession. Our results showed that RLK genes were distributed in all 20 \u003cem\u003eD. alata\u003c/em\u003e chromosomes, among which chromosome (Chr) 15 (Chr15) contained the most RLK genes (range from 82 to 93), whereas only two RLK genes were distributed on Chr6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Interestingly, RLK gene number among seven \u003cem\u003eD. alata\u003c/em\u003e accessions maintained constant only on two chromosomes (Chr6 and Chr11), but showed more or less variable on other chromosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; Supplementary Fig.\u0026nbsp;2). We found the largest value of standard deviation on Chr16, where ZSDa018 owned a substantially increase of RLK (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; Supplementary Fig.\u0026nbsp;2). Collectively, these results suggested that both the inter- and intra-chromosomal distributions of RLK genes were uneven and swiftly fine-tuned throughout evolution.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eConsidering the complex composition of RLK gene family, we inquired the arrangement of each RLK subfamily on \u003cem\u003eD. alata\u003c/em\u003e chromosomes and analyzed their inter-accession differences. The results showed that Chr5 had the most diversified RLK subfamilies (23 subfamilies), while Chr6 had only two RLK subfamilies (LRR-III and RLCK-V) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Interestingly, although the most widely distributed subfamily, LRR-III, could be detected on 18 chromosomes, a total of 10 subfamilies were localized on merely one chromosome (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Furthermore, the value of standard deviation of LRK10L-2 on Chr16, LRR-XI-1 on Chr2, and DLSV on Chr15 ranked at the top three, which exactly coincided with the most variable subfamilies as well as chromosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB; Supplementary Figs.\u0026nbsp;1\u0026ndash;2). Taken together, our resulted indicated that the variation of pan-RLKome in \u003cem\u003eD. alata\u003c/em\u003e was not unlimited and could be attributed to differences caused by members from specific RLK subfamilies and on specific chromosomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDiverse duplication mechanisms shaped the expansion history of\u003c/b\u003e \u003cb\u003eD. alata\u003c/b\u003e \u003cb\u003epan-RLKome\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn view of the large size of RLK gene family, we delved into its expansion history in \u003cem\u003eD. alata\u003c/em\u003e under the background of pan-genome. The duplication types of RLK genes from seven \u003cem\u003eD. alata\u003c/em\u003e accessions were analyzed by adopting MCScanX package\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e (Supplementary Table\u0026nbsp;2). Approximately a quarter of RLK genes were generated by tandem duplication, and another quarter were resulted from whole genome duplication (WGD) and/or segmental duplication (SD) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In addition, less than 20% RLK genes were resulted from proximal duplication (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). It was noteworthy that no singleton RLK gene was detected in all seven \u003cem\u003eD. alata\u003c/em\u003e accessions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), indicating that RLK repertoires were largely shaped by the recurrent and ubiquitous duplication events.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe further investigated the duplication types of each RLK subfamily and found that the majority of RLK subfamilies have experienced dispersed duplication (44/48) and WGD/SD (30/48) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). By comparison, tandem duplication (15/48) and proximal duplication (14/48) contributed to the expansion of only one third of RLK subfamilies, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Interestingly, RLK genes duplicated via WGD/SD were more abundant in ZSDa018 and ZSDa046 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Compared to other accessions, ZSDa018 and ZSDa046 contained remarkably elevated amount of WGD/SD-derived LRK10L-2 and LRR-XI-1 genes, respectively, and both of them also possessed larger number of WGD/SD-derived DLSV genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB; Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e\u003cp\u003eTo dissect the expansion dynamics of RLK subfamilies in \u003cem\u003eD. alata\u003c/em\u003e, we conducted the synteny analysis and delineated the specific gene loci that were produced by WGD/SD. Our analysis revealed extensive blocks of collinearity within the genomes of seven accessions, pinpointing numerous duplicated regions derived from ancient polyploidization and/or large-scale segmental duplication events (Supplementary Fig.\u0026nbsp;4A-G). Specifically, in ZSDa018, clusters of WGD/SD-derived LRK10L-2 genes were predominantly localized within collinear blocks on Chr16 (Supplementary Fig.\u0026nbsp;4D), indicating their origin from shared ancestral duplication events. Similarly, ZSDa046 exhibited dense clusters of LRR-XI-1 genes within syntenic regions on Chr2 (Supplementary Fig.\u0026nbsp;4G). Furthermore, the enrichment of DLSV genes via WGD/SD in both accessions was corroborated by their frequent occurrence within these identified collinear blocks across Chr5 (Supplementary Fig.\u0026nbsp;4A-G). These intra-specific synteny patterns provide strong genomic evidence supporting the significant role of WGD/SD events in driving the lineage-specific expansion of key RLK subfamilies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEvolutionary trajectory and domain architecture diversification of\u003c/b\u003e \u003cb\u003eD. alata\u003c/b\u003e \u003cb\u003epan-RLKome\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe intricate evolutionary trajectory of RLK gene family has long been mysterious due to its large size and numerous subfamily composition. Several dedicated researches have been conducted for model plants\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, but the pan-genome-based analysis still remains scarce. To provide a panoramic evolutionary history of \u003cem\u003eD. alata\u003c/em\u003e RLK gene family, we reconstructed the phylogeny of the pan-RLKome in seven \u003cem\u003eD. alata\u003c/em\u003e accessions (Supplementary Fig.\u0026nbsp;5; Supplementary Data 2). Interestingly, we found that one same clade in the phylogenetic tree could often accommodate RLKs derived from different subfamilies and/or located on different chromosomes, indicating the frequent ECD changes and chromosome-translocations of RLKs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). For example, as the largest RLK subfamily, LRR-RLK did not form a monophyletic group but rather belonged to several different clades (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Similarly, subfamilies of receptor-like cytosolic kinases (RLCKs) were also distributed on a couple of clades (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA wide variety of types of domains are integrated into the RLK gene family to serve as ECDs. Therefore, we probed into the evolutionary roadmap of RLK domain architectures by determining the ECD types. Totally, eight classes of ECD type were identified, including cysteine-rich repeat (CRR), lectin, LRR, lysin motif (LysM), malectin, regulator of chromosome condensation repeat (RCC), similar protein to arbuscular receptor-like kinase (SPARK), and wall-associated kinase (WAK) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Supplementary Figs.\u0026nbsp;6\u0026ndash;7; Supplementary Table\u0026nbsp;3). CRR, LysM and RCC domains were specifically adopted as ECDs in DLSV, LysM-RLK and CR4L subfamilies, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Supplementary Figs.\u0026nbsp;6\u0026ndash;7). Among the subfamilies with lectin as ECD, C-LEC, L-LEC, and SD-2b/DLSV held the C-type, L-type, and B-type lectin domains, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Supplementary Figs.\u0026nbsp;6\u0026ndash;7). LRR, malectin, SPARK, WAK domains were integrated into more than one RLK subfamilies, underscoring the versatility of these ECDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Supplementary Figs.\u0026nbsp;6\u0026ndash;7). Despite the various ECD types, no ECD was found at all in 13 RLK subfamilies, which implied their intrinsic role in intercellular signal transduction but not perceiving extracellular stimuli (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Supplementary Fig.\u0026nbsp;6\u0026ndash;7).\u003c/p\u003e\u003cp\u003eThe phylogeny of RLK subfamilies mapped with ECD types showed the swift and frequent ECD domain change events (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The inositol-requiring enzyme 1 (IRE1) clade that contained TMD but no ECD was the sister group to all other RLK subfamilies (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Homologs of IRE1 have been found in human, suggesting the ancient origin of this transmembrane kinase receptors\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Notably, LRR domains were predominant in many clades (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), which raised the possibility that other domains could be recruited into the RLK through ECD swap mediated by LRR. Intriguingly, 14 subfamilies that comprised mostly of RLKs with ECD simultaneously contained RLKs without ECD (Supplementary Figs.\u0026nbsp;6\u0026ndash;7). The pervasive distribution of subfamilies with no specific ECDs were across the phylogenetic tree of RLKs highlighted the universality of the ECD loss (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In a nutshell, the prevailing ECD fusion, swap, and loss events shaped the domain architectures of the RLK gene family throughout the evolution.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePurifying and positive selection jointly shaped functional specialization of RLK subfamilies in\u003c/b\u003e \u003cb\u003eD. alata\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo analyse the evolutionary dynamics of the \u003cem\u003eD. alata\u003c/em\u003e pan-RLKome, we determined orthologous groups (OGs) of RLK genes using a post-order traversal strategy through systematically scanning internal nodes of the phylogenetic tree (detailed in Methods) (Supplementary Fig.\u0026nbsp;5; Supplementary Data 2). We identified 493 OGs containing totally 3,900 RLK genes, accounting for more than 94% of the \u003cem\u003eD. alata\u003c/em\u003e pan-RLKome (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; Supplementary Fig.\u0026nbsp;8; Supplementary Table\u0026nbsp;3). Most of the OGs (432/493, 87.6%) contained genes from all seven accessions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; Supplementary Table\u0026nbsp;3). Conserved OGs that possessed no more than two genes per accession accounts for the vast majority (475/493, 96.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; Supplementary Table\u0026nbsp;3). This indicated that our approach allowed identification of evolutionarily conserved gene groups while maintaining accession-specific resolution.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo elucidate the evolutionary forces acting on the \u003cem\u003eD. alata\u003c/em\u003e pan-RLKome, we calculated the ratio of nonsynonymous substitution rates (Ka) to synonymous substitution rates (Ks) (Ka/Ks) for orthologous RLK genes across seven accessions. Among the 493 OGs, 240 highly conserved OGs (48.6%) exhibited Ka\u0026thinsp;=\u0026thinsp;0 and Ks\u0026thinsp;=\u0026thinsp;0, indicating strong purifying selection and no detectable changes of the nucleotide sequences (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB; Supplementary Table\u0026nbsp;4). For the remaining OGs, a pronounced proportion of them showed Ka/Ks values around 1, which meant that neutral selection and genetic drift served as the major contributor (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB; Supplementary Table\u0026nbsp;4). Notably, many subfamilies harboured OGs under positive selection alongside those under purifying selection, such as SD-2b, L-Lec and DLSV, suggesting their versatility (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). By comparison, RLK subfamilies involved in conserved biological processes (e.g., LRR-V, WAK) showed remarkably lower Ka/Ks values (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Further subgroup analysis revealed that RLKs derived from proximal duplication events possessed more OGs with Ka/Ks\u0026thinsp;\u0026lt;\u0026thinsp;1 values compared to those from dispersed, tandem or WGD/SD duplications (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Collectively, these results underscore the heterogeneous evolutionary pressures across RLK subfamilies, shaped by their functional specialization and duplication mechanisms.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study represents the first comprehensive dissection of the RLK gene family at a pan-genome scale in \u003cem\u003eD. alata\u003c/em\u003e, leveraging seven high-quality chromosome-level assemblies. Our analysis revealed a pan-RLKome of 4,119 genes, extending beyond previous single-reference genome analyses which identified\u0026thinsp;~\u0026thinsp;500 RLKs\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In addition, pan-genomic analysis reveals richer structural variations (e.g., copy number variations and presence-absence variations) that likely drive RLK functional diversification.\u003c/p\u003e\u003cp\u003eThe moderate variation in total RLK numbers across accessions (577\u0026ndash;603 genes) contrasts with striking subfamily-specific expansions, notably in LRK10L-2, LRR-XI-1, DLSV, and SD-2b. Synteny and duplication analyses demonstrate that WGD/SD serve as the primary drivers of these expansions, particularly on chromosomal hotspots, such as LRK10L-2 on Chr16 in ZSDa018 and LRR-XI-1 on Chr2 in ZSDa046 (Supplementary Fig.\u0026nbsp;4). This aligns with findings in other plants, where WGD/SD events facilitate rapid neofunctionalization and adaptation gene families\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Tandem and proximal duplications contributed to a smaller fraction of RLKs (15\u0026ndash;25%), underscoring the dominant role of large-scale genomic reconfigurations in shaping RLK diversity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePhylogenomic reconstruction revealed pervasive ECD swaps, fusions, and losses across RLK clades. Subfamilies historically defined by conserved ECDs, such as LRR-RLKs, were polyphyletic, with domains like lectin, malectin, and LysM frequently exchanged or lost (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). This architectural fluidity suggests evolutionary flexibility in ligand perception strategies, potentially enabling novel environmental sensing capabilities. Notably, 13 subfamilies lacked identifiable ECDs, implying roles in intracellular signaling or co-receptor functions.\u003c/p\u003e\u003cp\u003eOG analysis identified 493 conserved RLK groups, 87.6% of which were shared across all accessions, highlighting a core RLKome stabilized by purifying selection. Strikingly, 48.6% of OGs showed no detectable sequence divergence (Ka\u0026thinsp;=\u0026thinsp;Ks\u0026thinsp;=\u0026thinsp;0), indicating intense functional conservation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Conversely, RLK subfamilies associated with stress responses (e.g., SD-2b, L-LEC, and DLSV) exhibited signatures of positive selection (Ka/Ks\u0026thinsp;\u0026gt;\u0026thinsp;1), suggesting adaptive evolution to biotic/abiotic challenges. This dichotomy aligns with dual roles of RLKs: conserved kinases maintain developmental integrity, while stress-linked clades diversify under environmental pressures\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Subfamilies derived from proximal duplications showed stronger purifying selection than those from WGD/SD, implying tighter functional constraints in localized genomic contexts.\u003c/p\u003e\u003cp\u003eThe pan-RLKome landscape provides insights into \u003cem\u003eD. alata\u003c/em\u003e adaptive evolution, particularly its stress resilience. The expansion of stress-related RLK subfamilies (e.g., LRK10L-2, DLSV) and the plasticity of ECDs likely contribute to its strong resistance traits, a key agronomic advantage. These findings offer targets for molecular breeding. For example, leveraging natural variation in RLK copy numbers or domain architectures to enhance disease resistance or abiotic stress tolerance. Future studies could functionalize specific RLKs via gene editing to validate their roles in stress responses, or expand pan-genomic analyses to include wild Dioscorea species to uncover ancestral RLK functions.\u003c/p\u003e\u003cp\u003eIn summary, our pan-genomic analysis reveals how duplication-driven expansion and domain plasticity have shaped the \u003cem\u003eD. alata\u003c/em\u003e RLK repertoire, balancing functional conservation with adaptive innovation. This framework not only advances our understanding of plant receptor evolution but also provides a foundation for leveraging RLK diversity in crop improvement strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contributions Statement\u003c/h2\u003e\n\u003cp\u003eJ.Y.X. and Y.M.Z. conceived and designed the research. Z.Y.W., S.X.L. and M.H.L. obtained and analyzed the data; S.X.L., M.H.L. and Z.Y.W. drafted the manuscript; J.T., Y.Q.J. and X.Y.L. participated in data analyses; J.Y.X. and Y.M.Z. revised the manuscript. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests Statement\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflict of interests.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eJ.Y.X. and Y.M.Z. conceived and designed the research. Z.Y.W., S.X.L. and M.H.L. obtained and analyzed the data; S.X.L., M.H.L. and Z.Y.W. drafted the manuscript; J.T., Y.Q.J. and X.Y.L. participated in data analyses; J.Y.X. and Y.M.Z. revised the manuscript. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (32172089), Scientific Fund of Nanjing Botanical Garden Mem. Sun Yat-Sen (JSPKLB202503).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLebot V, Lawac F, Legendre L (2023) The greater yam (Dioscorea alata L.): A review of its phytochemical content and potential for processed products and biofortification. J Food Compos Anal 115\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAsiedu R, Sartie A (2010) Crops that feed the World 1. Yams Food Secur 2:305\u0026ndash;315\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalehi B et al (2019) Dioscorea Plants: A Genus Rich in Vital Nutra-pharmaceuticals-A Review. 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Genomics Proteom Bioinf 8:77\u0026ndash;80\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-molecular-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plan","sideBox":"Learn more about [Plant Molecular Biology](https://www.springer.com/journal/11103)","snPcode":"11103","submissionUrl":"https://submission.nature.com/new-submission/11103/3","title":"Plant Molecular Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Dioscorea alata, pan-RLKome, duplication, subfamiliy, evolution, adaptation","lastPublishedDoi":"10.21203/rs.3.rs-7198655/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7198655/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eDioscorea alata\u003c/em\u003e (greater yam) is a vital tuber crop underpinning global food security, while this crop suffers great reduction due to diseases like anthracnose, yam mosaic virus, and tuber rot. Receptor-like kinases (RLKs) play pivotal role in plant disease resistance, transducing plant immune signal. Yet the evolutionary dynamics of RLKs remain underexplored in \u003cem\u003eD. alata\u003c/em\u003e. Here, we leveraged seven chromosome-level \u003cem\u003eD. alata\u003c/em\u003e genomes to characterize the pan-RLKome of \u003cem\u003eD. alata\u003c/em\u003e, identifying 4,119 RLK genes across 48 subfamilies. Our analysis revealed moderate variation in total RLK numbers but striking subfamily-specific expansions on several chromosome hotspots driven primarily by whole-genome/segmental duplication. Phylogenomic reconstruction uncovered pervasive extracellular domain swaps, fusions, and losses, contributing to diversified RLK architectures. Selection pressure analyses showed that purifying selection has maintained core RLK functions, while positive selection drove adaptive evolution in stress-associated subfamilies. Our study uncovers the pan-genomic basis of RLK evolution in \u003cem\u003eD. alata\u003c/em\u003e, highlighting how duplication mechanisms and domain plasticity underpin functional innovation and environmental adaptation in this vital crop.\u003c/p\u003e","manuscriptTitle":"Pan-genomic insights into RLK family evolution and adaptation in Dioscorea alata","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 17:55:30","doi":"10.21203/rs.3.rs-7198655/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-19T23:24:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-17T06:20:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115943288710921407785683478169477269514","date":"2025-07-28T06:16:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-27T23:43:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-24T12:14:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-24T12:10:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant Molecular Biology","date":"2025-07-23T16:43:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-molecular-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plan","sideBox":"Learn more about [Plant Molecular Biology](https://www.springer.com/journal/11103)","snPcode":"11103","submissionUrl":"https://submission.nature.com/new-submission/11103/3","title":"Plant Molecular Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5efaf150-843d-4165-81a4-15b3e4a037cc","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:39:21+00:00","versionOfRecord":{"articleIdentity":"rs-7198655","link":"https://doi.org/10.1007/s11103-025-01647-w","journal":{"identity":"plant-molecular-biology","isVorOnly":false,"title":"Plant Molecular Biology"},"publishedOn":"2025-10-20 16:16:18","publishedOnDateReadable":"October 20th, 2025"},"versionCreatedAt":"2025-07-29 17:55:30","video":"","vorDoi":"10.1007/s11103-025-01647-w","vorDoiUrl":"https://doi.org/10.1007/s11103-025-01647-w","workflowStages":[]},"version":"v1","identity":"rs-7198655","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7198655","identity":"rs-7198655","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}