The Reference Genome Sequence of the Scarlet Follicle, Sterculia lanceolata, reveals a paleo-polyploidization and its impact on fruit quality and fruit dehiscence

The Reference Genome Sequence of the Scarlet Follicle, Sterculia lanceolata, reveals a paleo-polyploidization and its impact on fruit quality and fruit dehiscence | 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 The Reference Genome Sequence of the Scarlet Follicle, Sterculia lanceolata, reveals a paleo-polyploidization and its impact on fruit quality and fruit dehiscence Youtao Hu, Youpeng Zhang, Hongbin Zhang, Jiahao Zhang, Guilian Guo, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7559915/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Feb, 2026 Read the published version in Functional & Integrative Genomics → Version 1 posted 8 You are reading this latest preprint version Abstract Sterculia lanceolata , a tree species of the Malvaceae family with notable ornamental and medicinal value, has long been constrained in genetic research and breeding applications due to the lack of genomic resources. In this study, we report for the first time a high-quality, chromosome-level genome assembly of this species, aimed at elucidating its evolutionary history and the genetic basis of key traits. We constructed the genome using PacBio HiFi sequencing and further assembled it into 20 chromosomes with the aid of Hi-C technology, yielding a final genome assembly size of 610.4 Mb with a contig N50 of 29.3 Mb and a BUSCO completeness of 98.7%. The assembly includes the identification of 20 chromosomes and the annotation of 35,873 protein-coding genes, with an annotation rate of 96.4%. By integrating genomic data from other Malvaceae species, we analyzed the karyotype evolution of S. lanceolata and revealed the basal ploidy level of the family. Comparative genomic analyses uncovered significant syntenic relationships and whole-genome duplication (WGD) events among Malvaceae species, thereby clarifying the trajectory of karyotype evolution. Moreover, the study identified key regulatory gene families associated with fruit dehiscence (homologs of SHP1/2 , FUL , IND , and ALC ) that have undergone extensive expansion in S. lanceolata as a consequence of ancient polyploidy events. The reference genome provided in this study not only serves as a critical resource for evolutionary research in Malvaceae but also establishes a foundational framework for molecular breeding, genetic improvement, and conservation of S. lanceolata and related species. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Sterculia lanceolata , an important member of the genus Sterculia within the family Malvaceae, is a striking subtropical evergreen tree (Guymer 1988 ). It is renowned for its distinctive economic value and long-standing traditional medicinal uses (Prasad et al. 2022 ), with a broad geographic distribution primarily across subtropical regions of Asia, spanning southern China, Vietnam, Thailand, India, and beyond (Bawri et al. 2024 ). The species exhibits remarkable adaptability to the humid and variable climatic conditions characteristic of these regions. In addition to serving as a major regional source of timber, its roots, leaves, and seeds have been widely utilized in traditional medicine. For instance, according to the theory of traditional Chinese medicine, its leaves are pungent and warm in nature, associated with the liver meridian, and function to disperse blood stasis and alleviate pain. They have been commonly applied to treat symptoms such as pain, swelling, and bruising caused by trauma or blood stasis. Previous studies have shown that plants of the genus Sterculia are generally rich in flavonoids and their derivatives, compounds that have been demonstrated to possess diverse biological activities, including antibacterial, anti-inflammatory, antioxidant, and anticancer properties (L. Wang et al. 2024 ). Within forest ecosystems, S. lanceolata also plays an essential role in providing both food sources and habitats for a variety of organisms. Despite its pronounced ecological and economic importance, our understanding of its genetics remains extremely limited. To date, the NCBI public database contains only a single transcriptome dataset derived from its leaves (PRJNA435648), and no complete nuclear genome has yet been reported for any member of the genus Sterculia (Eum et al. 2019 ). This knowledge gap has posed a significant barrier to uncovering the complex molecular mechanisms underlying its physiological characteristics, medicinal value, and ecological adaptability (Ganie et al. 2015 ). This knowledge gap highlights the urgency of conducting in-depth genetic studies on S. lanceolata , as such research is essential to deciphering the genetic codes underlying its remarkable adaptability and economically important traits. The Malvaceae family also encompasses globally significant crops such as cotton ( Gossypium raimondii ) and durian ( Durio zibethinus ), and important ornamental plant species such as Hibiscus (Cvetković et al. 2021 ). Although the genomes of multiple cotton and durian species have been decoded, providing profound insights into key traits such as fiber development and flavor compound biosynthesis, investigations into the evolutionary origins and genetic foundations of its important sister genus, Sterculia , remain in their infancy. Given the unique medicinal value and strong environmental adaptability of S. lanceolata , obtaining its complete genome and identifying genes associated with its desirable traits hold great significance for advancing both evolutionary studies within Malvaceae and the genetic improvement of the species itself. More importantly, for certain lineage-specific biological traits within Malvaceae—such as the molecular mechanisms regulating precise fruit dehiscence following maturation—there is still a lack of in-depth cross-species comparative research (Pabón-Mora et al. 2014 ). Therefore, this study aims to construct a high-quality, chromosome-level reference genome of S. lanceolata . By conducting an in-depth analysis of its genomic background and evolutionary history, we seek to identify the key gene families that determine its unique fruit morphology. Compared with existing studies on the genus Sterculia , which have been largely limited to morphological descriptions and transcriptome sequencing (Eom and Na 2019 ), this research provides, for the first time, a complete nuclear genome assembly, representing a major advancement. This will enable a deeper understanding of the molecular mechanisms underlying its ecological adaptability and valuable economic traits. In addition, our findings bear direct significance for research across the entire Malvaceae family. Given the phylogenetic position of S. lanceolata within Malvaceae, our analysis of whole-genome duplication events and identification of key gene family expansions provide a valuable resource for comparative genomics. Specifically, the identification of critical genes associated with fruit dehiscence in S. lanceolata may offer novel genetic targets for the improvement of other related crops. Building on these insights, our study not only deepens the understanding of this economically important forest species but also provides essential scientific evidence for the evolution, genetic improvement, and conservation of Malvaceae. Materials and methods Experimental materials and sequencing technologies Samples for sequencing of S. lanceolata were collected in the vicinity of the Innovation Research and Education Valley teaching area, Yazhou District, Sanya City, Hainan Province, China. DNA was extracted from young leaves, while samples for transcriptome analysis were obtained from various tissues of S. lanceolata , including roots, stems, functional leaves, and seeds. Samples were immediately flash-frozen in liquid nitrogen after collection and stored at − 80°C in an ultra-low temperature freezer for subsequent nucleic acid extraction. Genomic DNA was randomly sheared, and short-read libraries of S. lanceolata were constructed following the TruSeq DNA sample preparation protocol. These libraries were then subjected to paired-end sequencing (150 bp read length) on the NovaSeq 6000 platform. In addition, a PacBio HiFi library was constructed. The library was prepared for sequencing using the PacBio Binding Kit (Wenger et al. 2019 ), in which primers and polymerases were ligated to the library. The final reaction products were purified with AMPure PB Beads and subsequently sequenced on the Revio sequencing system. Furthermore, Hi-C libraries were sequenced on the Illumina NovaSeq platform with paired-end reads of 150 bp. All transcriptome libraries were sequenced on the Illumina platform (Quail et al. 2008 ), generating paired-end reads of 150 bp. All sequencing data were processed using fastp v0.23.4 (S. Chen et al. 2018 ) to filter out low-quality reads and obtain clean data for downstream analyses. Genome size estimation based on k-mer analysis A k-mer analysis was performed for genome survey. To obtain clean reads, the raw data were filtered by removing low-quality reads, short reads, adapter sequences, and polyG tails. Subsequently, KMC v3.2.4 (Kokot et al. 2017 ) was employed to conduct k-mer frequency distribution analysis with k = 19. Genome size, heterozygosity, and repeat content were estimated using GenomeScope v2.0 (Ranallo-Benavidez et al. 2020 ). The genome size of S. lanceolata was estimated to be 465.5 Mb, with a heterozygosity of 0.321%. Chromosome-level genome assembly First, the raw HiFi data were converted into FASTQ format using samtools v1.21 (Li et al. 2009 ). To obtain clean HiFi and Hi-C data, fastp v0.23.4 (S. Chen et al. 2018 ) was applied to filter out low-quality reads, short reads, adapter sequences, and polyG tails from the raw datasets. The filtered HiFi data were then assembled into contigs using hifiasm 0.19.9 (Cheng et al. 2021 ) with default parameters. Hi-C data processing was performed with ALLHiC v0.9.13 (Zhang et al. 2019 ), in which the clean Hi-C reads were aligned to the assembled contigs to generate an interaction matrix. Subsequently, the contigs were ordered and anchored using 3D de novo Assembly v180114 (Dudchenko et al. 2017 ). Finally, the assembled Hi-C contact maps were manually inspected using Juicebox v1.11.08 (Durand et al. 2016 ). To assess assembly quality, we conducted a comprehensive evaluation using BUSCO v5.1 (Seppey et al. 2019 ) with the eudicots_odb10 database to examine the presence and completeness of single-copy orthologs. Ultimately, we obtained a high-quality, well-assembled S. lanceolata genome sequence, providing a solid foundation for future functional studies. Gene prediction and annotation We utilized RepeatModeler v2.0.3 (Flynn et al. 2020 ) to construct a de novo repeat library for the classification of repetitive sequences, and employed RepeatMasker v4.1.2 (N. Chen 2004 ) to identify them. In total, 376.7 Mb of repetitive elements were identified, constituting 59.6% of the S. lanceolata genome. All transcriptomic data were aligned to the genome using HISAT2 v2.2.1 (Kim et al. 2019 ). Subsequently, BRAKER v3.0.3 (Gabriel et al. 2024 ) was used to automatically train a species-specific parameter model and annotate gene structures, leveraging alignment evidence from both transcriptomic data and proteins. For functional annotation, the predicted protein-coding genes were aligned against the eggNOG database (Hernández-Plaza et al. 2023 ). Assembly and annotation of the chloroplast and Mitochondrion genome To assemble the chloroplast genome, we used the GetOrganelle v1.7.7.1 (Jin et al. 2020 ) software to assemble the Illumina paired-end sequencing data, specifying the -k option with values set to 21, 45, 65, 85, and 105, respectively. For mitochondrial genome assembly, we utilized the Oatk v1.0 (Zhou et al. 2025 ) toolkit for de novo assembly from PacBio HiFi sequencing reads, invoking the syncasm module within Oatk to filter specific k-mer sequences from the raw HiFi reads. We applied -k 1001 to set the minimum k-mer length and used -c 150 to set the minimum coverage threshold. The resulting FASTA file was used as the input for annotation on the OGDRAW platform (Lohse et al. 2007 ) ( https://chlorobox.mpimp-golm.mpg.de/OGDraw.html ). Following the platform's guidelines, we annotated the organellar genomes and chose the GenBank (GB) format for the output. To visualize the annotated genome, we accessed the "Upload" section of the OGDRAW online tool and submitted the GB file containing the S. lanceolata genome sequence. After selecting the appropriate options, we submitted the file for processing. OGDRAW then generated and displayed the annotated organellar genome in a graphical format, thus providing a clear representation of the organellar genetic structure. Synteny and whole-genome duplication analysis We selected the protein sequence data of H. littoralis , F. kwangsiensis , F. hainanensis , and S. lanceolata as the basis for our collinearity analysis. To ensure the reliability of the results, we performed both intra- and inter-genomic self- and cross-comparisons using the BLASTP v2.12.0 tool, with an E-value threshold set to 1e-5. Subsequently, we utilized MCScanX v1.0.0 (Y. Wang et al. 2012 ) to identify high-confidence collinear blocks. For the visualization of collinearity information, we used JCVI v1.5.1 (Tang et al. 2024 ), which effectively displays inter-chromosomal collinear regions. For the analysis of whole-genome duplication (WGD) events, we applied WGD v1.1.054 (Schranz et al. 2012 ) to calculate the WGD incidence rate and used the WGDI v0.6.5 (Sun et al. 2022 ) software to plot the Ks value distribution, thereby estimating the timing and frequency of WGD events. Polyploidy and karyotype analysis We pre-processed the protein data for S. lanceolata , D. zibethinus , G. raimondii , and H. schizopetalus using BLAST v2.9.0–2 (Altschul et al. 1997 ), selecting the output file format "-outfmt 6" and "-num_alignment 2". Subsequently, we constructed the ancestral Malvaceae karyotype (AMK) using WGDI v0.6.5 (Sun et al. 2022 ) with the "-km" option. Based on the protein sequence information, we inferred the modern karyotypes of the studied species. To quantify the fission and fusion events that occurred in the evolutionary history of these species, we enumerated all homologous segments and calculated the corresponding fission and fusion counts. Identification and Functional Enrichment Analysis of WGD Genes To identify genes in the S. lanceolata genome derived from whole-genome duplication (WGD), we first performed an all-versus-all BLASTP v2.12.0 (Lavigne et al. 2008 ) search of all protein sequences, setting an E-value threshold of 1e-5. Using these alignment results and gene location data, we detected collinear blocks and classified gene duplication types with the MCScanX v1.0.0 (Y. Wang et al. 2012 ) toolkit. Subsequently, we conducted a Gene Ontology (GO) enrichment analysis on the identified set of WGD genes. We used the web-based tool agriGO v2.0 (Tian et al. 2017 ) ( https://systemsbiology.cau.edu.cn/agriGOv2/ ) for the enrichment analysis. agriGO v2.0 performs gene enrichment using the Singular Enrichment Analysis (SEA) method, with the SEA parameters set as follows: Fisher's exact test, Yekutieli correction (FDR under dependency), a significance level of 0.05, a minimum of 5 mapped genes, and analysis of the complete GO and molecular function. Phylogenetic analysis and divergence time estimation We collected protein data for 39 species from public databases such as TropiCODB (Dai et al. 2025 ) ( https://bioinformatics.hainanu.edu.cn/tropdb/ ) and PLAZA 5.0 (Van Bel et al. 2022 ) ( https://bioinformatics.psb.ugent.be/plaza/versions/plaza_v5_dicots/ ), focusing on plants from the Malvaceae family and the model plant Arabidopsis thaliana . Using OrthoFinder v2.5.5 (Emms and Kelly 2019 ), a tree-based method, we identified high-quality orthogroups among these species. The OrthoFinder output was optimized with TRIMAL (Capella-Gutiérrez et al. 2009 ), applying the -gt 0.6 option to remove short sequences within each orthogroup and using a -cons 60 threshold to retain only the most conserved sites. Subsequently, we performed a Maximum Likelihood (ML) analysis on the concatenated protein sequences of these species using the parallel version of RAxML v8.2.13 (Stamatakis 2014 ) (raxmlHPC-PTHREADS). This analysis aimed to infer the phylogenetic relationships in the context of S. lanceolata , thereby providing a clearer understanding of its evolutionary position relative to other plant species. To estimate the divergence times among closely related species, including H. littoralis , F. kwangsiensis , F. hainanensis , T. cacao , D. zibethinus , B. ceiba , G. hirsutum , and S. lanceolata , we utilized the protein sequences of single-copy genes from Malvaceae plants. The divergence time estimation was conducted using the mcmctree v4.9 (Puttick 2019 ) tool in the PAML package. Following the analysis, the estimated divergence times were integrated into a phylogenetic tree reconstructed with IQTREE v2.4.0 (Minh et al. 2020 ), thereby providing a comprehensive understanding of the evolutionary relationships among the species. Identification and Phylogeny of Key Fruit Dehiscence Genes To elucidate the molecular regulatory mechanism of follicle dehiscence along the ventral suture in S. lanceolata , we first selected five known key regulatory genes from the model plant Arabidopsis thaliana : SHP1 (AT3G58780), SHP2 (AT2G42830), FUL (AT5G60910), IND (AT4G00120), and ALC (AT5G67110). The proteome data used in this study included those of S. lanceolata , Gossypium hirsutum (upland cotton), Durio zibethinus (durian), and Arabidopsis thaliana . Based on the conserved protein domain features of the target genes in A. thaliana , we downloaded the Hidden Markov Model (HMM) file for the MADS-box domain from the Pfam database v35.0 (Mistry et al. 2021 ). Using the hmmsearch program within the HMMER package v3.3.2 (Finn et al. 2011 ) with default parameters, a search was conducted against the combined proteomes of the four aforementioned species. To elucidate the evolutionary relationships among the members of each gene family, we constructed phylogenetic trees for each family separately. First, a multiple sequence alignment of the homologous protein sequences for each family was performed using MAFFT v7.525 (Katoh and Standley 2013 ). Subsequently, based on the alignment results, phylogenetic trees were constructed using FastTree v2.1.11 (Price et al. 2010 ) with the WAG amino acid substitution model and the approximate maximum-likelihood method. Branch reliability was assessed based on Shimodaira-Hasegawa-like (SH-like) local support values. Finally, the resulting tree files were imported into the iTOL v6 (Letunic and Bork 2024 ) online platform for visualization and annotation. Results Chromosome-level genome assembly To gain a deeper understanding of the genetic characteristics and evolutionary history of S. lanceolata , we employed advanced sequencing technologies to successfully construct a high-quality, chromosome-level reference genome. The final assembly yielded a genome size of 602.8 Mb with a contig N50 of 29.3 Mb, indicating excellent continuity. Using high-throughput chromosome conformation capture (Hi-C) technology, the vast majority of sequences were successfully anchored to 20 pseudochromosomes (Fig. 1 a). The Hi-C interaction heatmap clearly displayed strong diagonal signals and very weak inter-chromosomal interactions, strongly supporting the high accuracy and completeness of our genome assembly at the chromosome level (Fig. 1 a). To evaluate the overall quality of the genome, k-mer analysis was performed. The results indicated that the S. lanceolata genome exhibits a low heterozygosity rate estimated at 0.321% (Fig. 1 b), While this characteristic makes the assembly of a haplotype-resolved genome both difficult and less critical, it provides a solid foundation for subsequent high-quality genome assembly and annotation. Genome completeness is a core metric for evaluating its quality. We assessed the completeness of the genome using BUSCO v5.1 (Seppey et al. 2019 ). The results showed that the BUSCO completeness of the genome assembly reached 98.7% (Fig. 1 c), indicating that nearly all core conserved genes were fully represented. This high score demonstrates that the S. lanceolata genome we obtained is a high-quality, highly complete reference genome, sufficient to support downstream analyses such as comparative genomics, evolutionary studies, and functional gene mining. In addition, we successfully assembled the complete chloroplast (160,400 bp) and mitochondrial (161,707 bp) genomes (Figs. 1 e, 1 f), providing additional layers of genetic information for species identification and phylogenetic research. Table 1 Genome features of S. lanceolata . Genome S. lanceolata Ploidy 2n = 40 Assembled genome size (Mb) 602.8 Genomic heterozygosity (%) 0.321 Contig N50 (Mb) 29.3 Number of contigs 188 Number of pseudochromosomes 20 Repeat sequence content (%) 59.59 GC content (%) 32.71 Number of gene models 35,873 Genome BUSCOs (%) 98.7 Gene BUSCO (%) 96.4 Repeat sequence characterization and genome annotation Following repeat annotation using both de novo prediction and homology-based approaches, we found that S. lanceolata contains a substantial proportion of repetitive sequences, accounting for 59.59% of the genome. Among these, 42.46% are retrotransposons and 3.59% are DNA transposons, with long terminal repeats (LTRs) comprising 40.94% of the genome. The overall genomic GC content reached 32.71% (Fig. 1 d). By integrating de novo prediction, homology-based alignment, and transcriptome annotation, we identified a total of 35,873 protein-coding genes, with a BUSCO v5.1 completeness of 96.4% for the genome (Table 1 ). Notably, the number of genes in S. lanceolata exceeds that of closely related Malvaceae subfamily species, including H. littoralis (29,154 genes) (He et al. 2022 )d hainanensis (34,388 genes) (Dong et al. 2025 ), suggesting that S. lanceolata may encode a broader repertoire of stress-resistance and developmental genes. This provides a valuable genetic resource for horticultural breeding research, with the potential to introduce novel genes to enhance resistance and growth-related traits. Ancient Whole-Genome Duplications Shaping Evolutionary Dynamics Whole-genome duplication (WGD) or polyploidy events are key drivers of plant evolution, providing abundant genetic material that facilitates adaptation and species diversification. To investigate the evolutionary history of S. lanceolata and related species, we constructed a phylogenetic tree encompassing multiple subfamilies within Malvaceae (Fig. 2 d). The tree clearly places S. lanceolata within the subfamily Sterculioideae and reveals well-defined phylogenetic relationships with other Malvaceae species. Notably, we identified several ancient polyploidy events at key nodes of the phylogenetic tree. For example, on the branch of Helicteroideae, which includes durian ( Durio zibethinus ), we detected a pronounced whole-genome triplication (WGT) event (Fig. 2 d). This finding is consistent with previous studies and helps explain the large genome size and complex genetic background of durian. To elucidate the polyploidy history and chromosomal evolution of Malvaceae plants, we conducted a comparative genomics analysis of S. lanceolata and its closely related species. Within the S. lanceolata genome, the distribution of synonymous substitution rates (Ks) for paralogous gene pairs exhibits a pronounced peak at approximately 1.6, providing clear evidence for an ancient whole-genome duplication (WGD) event (Fig. 2 a). More importantly, analysis of Ks distributions of paralogous genes offers critical evidence for the evolutionary history of S. lanceolata itself. The Ks distribution shows a distinct peak at around 0.3 for S. lanceolata (Fig. 2 a, red solid line), which is a characteristic molecular signature of a recent polyploidy event. In combination with the WGD events annotated on the phylogenetic tree (Fig. 2 d) along the branch of S. lanceolata , we confirmed that this species underwent an independent whole-genome duplication during its evolutionary history. This WGD event provided S. lanceolata with a substantial number of novel genes, which are likely associated with the formation of its unique biological traits, such as seed development and fruit dehiscence mechanisms. In contrast, an older Ks peak (approximately 1.5–2.0) is shared among multiple species, which may correspond to ancient polyploidy events in the Malvaceae family or even earlier. Inter-species synteny analysis (Fig. 2 b) further corroborates the chromosomal conservation and rearrangement patterns among these species, providing cross-validation for the inference of polyploidy events. Chromosomal rearrangements shaped the unique 20 chromosomes of S. lanceolata Our reconstruction of karyotype evolution (Fig. 3 ) indicates that a common ancestor of Malvaceae possessed a karyotype with 11 chromosomes (n = 11). Following this ancestral stage, a major divergence occurred. The lineage leading to Malvoideae (including Gossypium raimondii and Hibiscus schizopetalus ) underwent an ancient whole-genome pentaplication (WGM) event. In contrast, the lineage leading to S. lanceolata within Sterculioideae experienced an independent whole-genome duplication (WGD) event. Following this WGD, the S. lanceolata genome underwent extensive chromosomal rearrangements, including reciprocal translocations (RTA), end-to-end joining (EEJ), fissions, and losses, ultimately stabilizing into its current karyotype of 20 chromosome pairs (n = 20, 2n = 40). For comparison, its close relative durian ( Durio zibethinus , subfamily Helicteroideae) appears to have undergone another independent whole-genome triplication (WGT) event, followed by a series of complex fissions, nested chromosome fusions (NCFs), and other rearrangements, resulting in its modern karyotype of 2n = 56. Gossypium raimondii has maintained a relatively stable karyotype (2n = 26) with few subsequent changes, whereas Hibiscus schizopetalus experienced at least two additional WGD events, followed by extensive chromosomal fissions and fusions, culminating in its current karyotype of 2n = 42. These diverse evolutionary trajectories vividly illustrate the substantial differences in genome structural evolution among lineages following WGD events, and it is precisely these differences that have shaped the rich and varied biological characteristics of Malvaceae species. Dynamic changes in seed nutrient composition and gene accumulation driven by polyploidy The seeds of S. lanceolata have attracted considerable attention due to their rich nutritional content and unique flavor. We conducted a systematic study of the morphology and nutritional composition of S. lanceolata seeds during their development from immature to mature stages (Fig. 4 ). Morphologically, both the fruit (follicle) and seeds undergo significant color changes throughout development (Figs. 4 e–g). To characterize the molecular mechanisms underlying these phenotypic changes, we conducted metabolite profiling and transcriptomic analyses on seeds at different developmental stages. We first accurately identified the set of paralogous genes retained from the WGD event. This specific gene set was then subjected to Gene Ontology (GO) enrichment analysis to determine the biological processes predominantly associated with these expanded gene families. The results provided compelling evidence: among the WGD-retained genes, GO terms related to “Seed development” and “Starch metabolic process” were significantly enriched (Fig. 5 a). This finding directly indicates that the WGD event in S. lanceolata did not randomly increase gene copy numbers, but rather led to a directed, large-scale expansion of gene repertoires associated with the synthesis and accumulation of seed nutrients. These expanded gene sets provide abundant raw material for the complex regulatory networks governing seed metabolism. The metabolite profiling results provided direct evidence supporting this conclusion. We found that, as the seeds matured, the contents of several key mineral elements, including magnesium (Mg), phosphorus (P), and potassium (K), increased significantly (Fig. 5 b), which is critical for energy storage in seeds and subsequent germination. Total starch content peaked during the mid-developmental stage and slightly declined at maturity, while amylose content also exhibited dynamic changes throughout seed development (Figs. 5 f, 5 g). Interestingly, we observed that flavonoid content was very high during the early stages of seed development but decreased sharply upon maturation (Fig. 5 h). Flavonoids are generally associated with plant defense and bitterness, and their reduction is considered an evolutionary strategy to enhance seed palatability, attract animals for consumption, and facilitate dispersal (Cipollini and Levey 1997 ). Therefore, the observed changes in flavonoid content in S. lanceolata seeds likely reflect an evolutionary compromise balancing the dual demands of “self-protection” and “attracting dispersers” during co-evolution. Expansion and mechanistic study of gene families related to fruit dehiscence The fruits of S. lanceolata undergo dehiscence along the ventral suture upon maturation, representing a critical biological process for the propagation of the species. This process is regulated by a precise gene regulatory network. We focused on the well-characterized core pathway controlling fruit dehiscence, including the MADS-box family genes FUL and SHP1/2 , as well as the bHLH transcription factor family genes IND and ALC . According to the classical regulatory model (Fig. 6 e), FUL is primarily expressed in the fruit valves, suppressing the formation of the dehiscence zone, whereas SHP1/2 , IND , and ALC act synergistically to promote the differentiation and lignification of the dehiscence zone, ultimately leading to fruit opening. To validate this model and investigate the unique dehiscence mechanism in S. lanceolata , we conducted a systematic phylogenetic analysis of these key gene families (Fig. 6 a–d). In the analyses of the SHP1/2 , IND , FUL , and ALC gene families, we observed that, compared with the model plant Arabidopsis thaliana , S. lanceolata (denoted as "Slan" in the figures) exhibits a notable expansion in gene copy numbers across most of these families (Figs. 6 a–c). For instance, in the phylogenetic tree of the SHP1/2 gene family, multiple "Slan" genes cluster together, forming species-specific gene clusters (Fig. 6 a). Fruit dehiscence is a critical developmental process governed by a finely tuned gene regulatory network that ensures a clear boundary between the valve and the dehiscence zone (Fig. 6 e). Within this regulatory network, the MADS-box transcription factors SHP1/2 act upstream, activating the downstream bHLH factors IND and ALC . IND primarily orchestrates the specialization of the separation layer and lignified layer, working in concert with ALC to complete the formation of the separation layer, whereas loss of ALC typically results in dehiscence defects. In contrast, the MADS-box gene FUL plays a dominant role in valve growth and development, restricting differentiation of the dehiscence zone by antagonizing the SHP1/2–IND/ALC pathway. Through the activation by SHP1/2 and the antagonistic action of FUL , this regulatory network collectively establishes the spatial boundary between the valve and valve margin, thereby enabling controlled dehiscence of mature fruits along a predetermined interface. Discussion This study reports the first high-quality, chromosome-level reference genome for S. lanceolata , filling a critical gap in the genomics of the Sterculia genus within the Malvaceae family. This achievement not only establishes a solid genetic foundation for dissecting the species' unique economic and medicinal traits but also provides a new and crucial phylogenetic node for resolving the complex evolutionary history of the entire Malvaceae family. The assembled genome exhibits excellent continuity (Contig N50 = 29.3 Mb) and high completeness (BUSCO = 98.7%), with a quality sufficient to support sophisticated comparative genomics and functional gene discovery. Furthermore, the genome’s low heterozygosity offers critical insights into the species' reproductive biology, population history, and provides a crucial baseline for future conservation genetics. This research marks a pivotal transition for the study of the Sterculia genus, advancing it from traditional morphology and limited transcriptomics into the whole-genome era. The whole-genome duplication (WGD) events revealed in our study are a core driving force in the evolution of S. lanceolata and the entire Malvaceae family. Through Ks distribution analysis, we clearly identified two pivotal polyploidization events: an ancient WGD (Ks ≈ 1.6) shared among Malvaceae species and a more recent, lineage-specific WGD (Ks ≈ 0.3) within the S. lanceolata lineage. This recent WGD event is key to understanding the unique biological traits of S. lanceolata . Polyploidization provides abundant raw genetic material, enabling organisms to adapt to environmental changes and evolve novel functions. Compared to the whole-genome triplication (WGT) experienced by durian ( Durio zibethinus ) (Teh et al. 2017 ) and the pentaploidy (WGM) event in the cotton lineage (Wendel and Cronn 2002 ), the WGD in S. lanceolata demonstrates the diversity and complexity of polyploidization history within Malvaceae. Following a WGD, the genome typically undergoes drastic rearrangement and a process of diploidization. Our karyotype analysis reconstructed the evolutionary trajectory of S. lanceolata from a putative ancestral Malvaceae karyotype of n = 11. This pathway involved a WGD event (theoretically forming n = 22), followed by a series of complex chromosomal rearrangements including reciprocal translocations (RTA), fissions, and losses, which ultimately stabilized to form its characteristic n = 20 (2n = 40) karyotype. This model not only perfectly explains the origin of its modern chromosome number but also vividly illustrates the universal mechanisms of dynamic genome evolution post-polyploidization (Soltis et al. 2015 ). One of the primary breakthroughs of this study is the direct link established between a macro-evolutionary WGD event and the species' key economic traits. We innovatively identified the set of genes that originated from the recent WGD and were subsequently retained, then performed a functional enrichment analysis on this specific gene set. The analysis revealed significant enrichment in the categories of 'seed development' and 'starch metabolic process.' This finding provides strong evidence that gene retention post-WGD was non-random, instead favoring the selective expansion and preservation of genes related to nutrient accumulation in seeds. We then corroborated these genetic findings with metabolomic data, which demonstrated that as seeds mature, key mineral elements and total starch content increase significantly, while flavonoid compounds associated with astringency decrease sharply. This forms a complete evidentiary chain—from a genomic evolutionary event to functional gene set expansion, and ultimately to the formation of a desirable economic trait—profoundly uncovering the evolutionary underpinnings of the high nutritional value of S. lanceolata seeds. This research paradigm, which tightly integrates WGD with economic traits, remains relatively rare in plant genomics and is analogous to research on the expansion of starch-related genes in potato (Van Harsselaar et al. 2017 ). Similarly, the WGD event provides clues for elucidating another key biological trait in S. lanceolata : fruit dehiscence. The ability of a fruit to dehisce at the appropriate time is crucial for plant seed dispersal and propagation. Our study revealed that the core gene families regulating fruit dehiscence, including SHP1/2, FUL, IND, and ALC, all exhibit significant copy number expansion in the S. lanceolata genome. It is plausible that this WGD-driven increase in gene dosage led to a more complex and finely-tuned regulatory network. For instance, the expanded gene copies, potentially through subfunctionalization or neofunctionalization, may have enabled more precise control over the dehiscence zone and valve margins, thereby ensuring that the follicle dehisces efficiently and accurately along the ventral suture upon maturation. This discovery not only clarifies the developmental mechanisms in S. lanceolata but also offers potential homologous gene targets for the genetic improvement of other crops, such as preventing yield loss from pod shattering in rapeseed ( Brassica napus ) (Raman et al. 2014 ). Conclusions This study reports the first successful construction of a high-quality, chromosome-level reference genome for S. lanceolata , revealing its genomic structure, gene composition, and evolutionary features. Through in-depth comparative genomic analysis, we elucidated that S. lanceolata underwent an independent, recent whole-genome duplication (WGD) event and have reconstructed in detail its evolutionary trajectory, which led to the formation of its current n = 20 karyotype via large-scale chromosomal rearrangements post-WGD. Crucially, this study establishes a direct link between this macro-scale genomic evolutionary event and the species' key agronomic traits. We demonstrate that the WGD-driven expansion of gene families directly resulted in the large-scale duplication and retention of key genes associated with 'seed development,' 'starch metabolism,' and 'pod dehiscence.' These changes at the genetic level are ultimately manifested at the phenotypic level as the rich accumulation of seed nutrients and a precise fruit dehiscence mechanism. In conclusion, this research not only provides an invaluable resource for evolutionary and comparative genomics of the Malvaceae family but also establishes a solid molecular foundation for the genetic improvement, germplasm conservation, and exploitation of the medicinal value of S. lanceolata . Declarations Conflict of Interest The authors declare they have no conflict of interest. Funding This study was supported by the Startup Funding for the Double First-Class Discipline of Crop Science at Hainan University (RZ2100003362). Author Contribution The authors confirm their contributions to the manuscript as follows: Conceptualization and project supervision: Wang W, Chen F, R. Henry; Plant material collection: Hu Y, Guo G, Zhang Y; Data analysis: Hu Y, Zhang Y, Guo G, Zhang H, Zhang J, Shao B, Xue J; Draft manuscript preparation: Hu Y, Zhang J, Yang K. All authors reviewed the results and approved the final version of the manuscript. Acknowledgement We gratefully acknowledge the valuable comments and suggestions provided by the editor and anonymous reviewers. Data availability The raw genomic sequencing data and transcriptomic reads have been deposited in the National Genomics Data Center under accession number PRJCA028606. References Guymer GP (1988) A taxonomic revision of Brachychiton (Sterculiaceae). Aust Syst Bot 1(3):199–323. https://doi.org/10.1071/SB9880199 Prasad N, Thombare N, Sharma SC, Kumar S (2022) Production, processing, properties and applications of karaya (Sterculia species) gum. Ind Crops Prod 177:114467. https://doi.org/10.1016/j.indcrop.2021.114467 Bawri A, Baro D, Sarma K, Teron R, Tanti B (2024) Sterculia lanceolata Cav. var. lanceolata (Malvaceae): an addition to flora of India. Vegetos 37(6):2642–2646. https://doi.org/10.1007/s42535-023-00745-8 Wang L, Yan YC, Hao YM, Zhuo XX, Duan HT, Zhang Q et al (2024) A Review on the Phytochemistry and Pharmacology of the Genus Sterculia. Chem Biodivers 21(8):e202400963. http://dx.doi.org/10.1002/cbdv.202400963 Eum SM, Kim S-Y, Hong JS, Roy NS, Choi S, Paik J et al (2019) Transcriptome analysis and development of SSR markers of ethnobotanical plant Sterculia lanceolata. Tree Genet Genomes 15(3):37. https://doi.org/10.1007/s11295-019-1348-3 Ganie SH, Upadhyay P, Das S, Sharma MP (2015) Authentication of medicinal plants by DNA markers. Plant gene 4:83–99. http://dx.doi.org/10.1016/j.plgene.2015.10.002 Cvetković T, Areces-Berazain F, Hinsinger DD, Thomas DC, Wieringa JJ, Ganesan SK et al (2021) Phylogenomics resolves deep subfamilial relationships in Malvaceae sl. G3(7):jkab136. https://doi.org/10.1093/g3journal/jkab136 . 11 Pabón-Mora N, Wong GK-S, Ambrose BA (2014) Evolution of fruit development genes in flowering plants. Front Plant Sci 5:300. http://dx.doi.org/10.3389/fpls.2014.00300 Eom SH, Na J-K (2019) Leaf transcriptome data of two tropical medicinal plants: Sterculia lanceolata and Clausena excavata. Data brief 25:104297. http://dx.doi.org/10.1016/j.dib.2019.104297 Wenger AM, Peluso P, Rowell WJ, Chang P-C, Hall RJ, Concepcion GT et al (2019) Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat Biotechnol 37(10):1155–1162. http://dx.doi.org/10.1038/s41587-019-0217-9 Quail MA, Kozarewa I, Smith F, Scally A, Stephens PJ, Durbin R et al (2008) A large genome center's improvements to the Illumina sequencing system. Nat Methods 5(12):1005–1010. http://dx.doi.org/10.1038/nmeth.1270 Chen S, Zhou Y, Chen Y, Gu J (2018) fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34:i884–i890. https://doi.org/10.1093/bioinformatics/bty560 Kokot M, Długosz M, Deorowicz S (2017) KMC 3: counting and manipulating k-mer statistics. Bioinformatics 33(17):2759–2761. http://dx.doi.org/10.1093/bioinformatics/btx304 Ranallo-Benavidez TR, Jaron KS, Schatz MC (2020) GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nat Commun 11(1):1432. http://dx.doi.org/10.1038/s41467-020-14998-3 Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079. http://dx.doi.org/10.1093/bioinformatics/btp352 Cheng H, Concepcion GT, Feng X, Zhang H, Li H (2021) Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat Methods 18(2):170–175. http://dx.doi.org/10.1038/s41592-020-01056-5 Zhang X, Zhang S, Zhao Q, Ming R, Tang H (2019) Assembly of allele-aware, chromosomal-scale autopolyploid genomes based on Hi-C data. Nat plants 5(8):833–845. http://dx.doi.org/10.1038/s41477-019-0487-8 Dudchenko O, Batra SS, Omer AD, Nyquist SK, Hoeger M, Durand NC et al (2017) De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356(6333):92–95. http://dx.doi.org/10.1126/science.aal3327 Durand NC, Robinson JT, Shamim MS, Machol I, Mesirov JP, Lander ES et al (2016) Juicebox provides a visualization system for Hi-C contact maps with unlimited zoom. Cell Syst 3(1):99–101. http://dx.doi.org/10.1016/j.cels.2015.07.012 Seppey M, Manni M, Zdobnov EM (2019) BUSCO: assessing genome assembly and annotation completeness. Gene prediction: methods and protocols. Springer, pp 227–245. https://doi.org/10.1093/bioinformatics/btv351 Flynn JM, Hubley R, Goubert C, Rosen J, Clark AG, Feschotte C et al (2020) RepeatModeler2 for automated genomic discovery of transposable element families. Proceedings of the National Academy of Sciences, 117 (17), 9451–9457. http://dx.doi.org/10.1073/pnas.1921046117 Chen N (2004) Using Repeat Masker to identify repetitive elements in genomic sequences. Current protocols in bioinformatics, 5 (1), 4.10. 11-14.10. 14. http://dx.doi.org/10.1002/0471250953.bi0410s25 Kim D, Paggi JM, Park C, Bennett C, Salzberg SL (2019) Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol 37(8):907–915. http://dx.doi.org/10.1038/s41587-019-0201-4 Gabriel L, Brůna T, Hoff KJ, Ebel M, Lomsadze A, Borodovsky M et al (2024) BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS, and TSEBRA. Genome Res 34(5):769–777. http://dx.doi.org/10.1101/gr.278090.123 Hernández-Plaza A, Szklarczyk D, Botas J, Cantalapiedra CP, Giner-Lamia J, Mende DR et al (2023) eggNOG 6.0: enabling comparative genomics across 12 535 organisms. Nucleic Acids Res 51(D1):D389–D394. http://dx.doi.org/10.1093/nar/gkac1022 Jin J-J, Yu W-B, Yang J-B, Song Y, DePamphilis CW, Yi T-S et al (2020) GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes. Genome Biol 21(1):241. http://dx.doi.org/10.1186/s13059-020-02154-5 Zhou C, Brown M, Blaxter M, Consortium DT, o. LP, McCarthy SA, Durbin R (2025) Oatk: a de novo assembly tool for complex plant organelle genomes. Genome Biol 26(1):235. http://dx.doi.org/10.1186/s13059-025-03676-6 Lohse M, Drechsel O, Bock R (2007) OrganellarGenomeDRAW (OGDRAW): a tool for the easy generation of high-quality custom graphical maps of plastid and mitochondrial genomes. Curr Genet 52(5):267–274. http://dx.doi.org/10.1007/s00294-007-0161-y Wang Y, Tang H, DeBarry JD, Tan X, Li J, Wang X et al (2012) MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res 40(7):e49–e49. http://dx.doi.org/10.1093/nar/gkr1293 Tang H, Krishnakumar V, Zeng X, Xu Z, Taranto A, Lomas JS et al (2024) JCVI: A versatile toolkit for comparative genomics analysis. Imeta 3(4):e211. http://dx.doi.org/10.1002/imt2.211 Schranz ME, Mohammadin S, Edger PP (2012) Ancient whole genome duplications, novelty and diversification: the WGD Radiation Lag-Time Model. Curr Opin Plant Biol 15(2):147–153. http://dx.doi.org/10.1016/j.pbi.2012.03.011 Sun P, Jiao B, Yang Y, Shan L, Li T, Li X et al (2022) WGDI: a user-friendly toolkit for evolutionary analyses of whole-genome duplications and ancestral karyotypes. Mol Plant 15(12):1841–1851. http://dx.doi.org/10.1016/j.molp.2022.10.018 Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389–3402. https://doi.org/10.1093/nar/25.17.3389 Lavigne R, Seto D, Mahadevan P, Ackermann H-W, Kropinski AM (2008) Unifying classical and molecular taxonomic classification: analysis of the Podoviridae using BLASTP-based tools. Res Microbiol 159(5):406–414. http://dx.doi.org/10.1016/j.resmic.2008.03.005 Tian T, Liu Y, Yan H, You Q, Yi X, Du Z et al (2017) agriGO v2. 0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res 45(W1):W122–W129. http://dx.doi.org/10.1093/nar/gkx382 Dai W, He S, Luo Y, Zhao C, Yang Z, Zhang J et al (2025) TropiCODB: A multi-omics resource for supporting biodesign in tropical crops. BioDesign Res 7(1):100003. https://doi.org/10.1016/j.bidere.2025.100003 Van Bel M, Silvestri F, Weitz EM, Kreft L, Botzki A, Coppens F et al (2022) PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants. Nucleic Acids Res 50(D1):D1468–D1474. http://dx.doi.org/10.1093/nar/gkab1024 Emms DM, Kelly S (2019) OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 20(1):238. http://dx.doi.org/10.1186/s13059-019-1832-y Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T (2009) trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25(15):1972–1973. http://dx.doi.org/10.1093/bioinformatics/btp348 Stamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30(9):1312–1313. http://dx.doi.org/10.1093/bioinformatics/btu033 Puttick MN (2019) MCMCtreeR: functions to prepare MCMCtree analyses and visualize posterior ages on trees. Bioinformatics 35(24):5321–5322. http://dx.doi.org/10.1093/bioinformatics/btz554 Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, Von Haeseler A et al (2020) IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 37(5):1530–1534. https://doi.org/10.1093/molbev/msaa015 Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer EL et al (2021) Pfam: The protein families database in 2021. Nucleic Acids Res 49(D1):D412–D419. http://dx.doi.org/10.1093/nar/gkaa913 Finn RD, Clements J, Eddy SR (2011) HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 39(suppl2):W29–W37. http://dx.doi.org/10.1093/nar/gkr367 Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30(4):772–780. http://dx.doi.org/10.1093/molbev/mst010 Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5(3):e9490. http://dx.doi.org/10.1371/journal.pone.0009490 Letunic I, Bork P (2024) Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res 52(W1):W78–W82. http://dx.doi.org/10.1093/nar/gkae268 He Z, Feng X, Chen Q, Li L, Li S, Han K et al (2022) Evolution of coastal forests based on a full set of mangrove genomes. Nat Ecol Evol 6(6):738–749. http://dx.doi.org/10.1038/s41559-022-01744-9 Dong Z, Jin S, Fan R, Sun P, Shao L, Zhao T et al (2025) High-quality genome of Firmiana hainanensis provides insights into the evolution of Malvaceae subfamilies and the mechanism of their wood density formation. J Genet Genomics 52(6):812–825. http://dx.doi.org/10.1016/j.jgg.2024.12.009 Cipollini ML, Levey DJ (1997) Secondary metabolites of fleshy vertebrate-dispersed fruits: adaptive hypotheses and implications for seed dispersal. Am Nat 150(3):346–372. http://dx.doi.org/10.1086/286069 Teh BT, Lim K, Yong CH, Ng CCY, Rao SR, Rajasegaran V et al (2017) The draft genome of tropical fruit durian (Durio zibethinus). Nat Genet 49(11):1633–1641. http://dx.doi.org/10.1038/ng.3972 Wendel JF, Cronn RC (2002) Polyploidy and the evolutionary history of cotton. Adv Agron 87:139–186 Soltis PS, Marchant DB, Van de Peer Y, Soltis DE (2015) Polyploidy and genome evolution in plants. Curr Opin Genet Dev 35:119–125. http://dx.doi.org/10.1016/j.gde.2015.11.003 Van Harsselaar JK, Lorenz J, Senning M, Sonnewald U, Sonnewald S (2017) Genome-wide analysis of starch metabolism genes in potato (Solanum tuberosum L). BMC Genomics 18(1):37. http://dx.doi.org/10.1186/s12864-016-3381-z Raman H, Raman R, Kilian A, Detering F, Carling J, Coombes N et al (2014) Genome-wide delineation of natural variation for pod shatter resistance in Brassica napus. PLoS ONE 9(7):e101673. http://dx.doi.org/10.1371/journal.pone.0101673 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Feb, 2026 Read the published version in Functional & Integrative Genomics → Version 1 posted Editorial decision: Revision requested 28 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers agreed at journal 22 Oct, 2025 Reviewers invited by journal 18 Sep, 2025 Editor assigned by journal 18 Sep, 2025 Submission checks completed at journal 15 Sep, 2025 First submitted to journal 08 Sep, 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7559915","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":521814524,"identity":"ea833bfd-0e20-4fb3-b833-5ebab7283b9c","order_by":0,"name":"Youtao Hu","email":"","orcid":"","institution":"Hainan University","correspondingAuthor":false,"prefix":"","firstName":"Youtao","middleName":"","lastName":"Hu","suffix":""},{"id":521814525,"identity":"ec6bf53a-f46d-4851-b6d8-655ad1957796","order_by":1,"name":"Youpeng Zhang","email":"","orcid":"","institution":"Hainan University","correspondingAuthor":false,"prefix":"","firstName":"Youpeng","middleName":"","lastName":"Zhang","suffix":""},{"id":521814526,"identity":"eb477495-f42e-48fa-ad48-41b461c6567c","order_by":2,"name":"Hongbin Zhang","email":"","orcid":"","institution":"Hainan University","correspondingAuthor":false,"prefix":"","firstName":"Hongbin","middleName":"","lastName":"Zhang","suffix":""},{"id":521814527,"identity":"eb693f77-b015-4498-b649-e9b381467295","order_by":3,"name":"Jiahao Zhang","email":"","orcid":"","institution":"Hainan University","correspondingAuthor":false,"prefix":"","firstName":"Jiahao","middleName":"","lastName":"Zhang","suffix":""},{"id":521814528,"identity":"49006972-d700-44dc-a354-270b73484579","order_by":4,"name":"Guilian Guo","email":"","orcid":"","institution":"Hainan University","correspondingAuthor":false,"prefix":"","firstName":"Guilian","middleName":"","lastName":"Guo","suffix":""},{"id":521814529,"identity":"949248dc-54e4-4e22-b0c1-5e814aa9e4b2","order_by":5,"name":"Kejing Yang","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Kejing","middleName":"","lastName":"Yang","suffix":""},{"id":521814530,"identity":"f0850cac-8602-427e-ad55-6fa523b21113","order_by":6,"name":"Bing-Yan Shao","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Bing-Yan","middleName":"","lastName":"Shao","suffix":""},{"id":521814531,"identity":"accb95f8-ecb8-4a09-a7f9-e13ffde86890","order_by":7,"name":"Jia-yu Xue","email":"","orcid":"","institution":"Nanjing Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jia-yu","middleName":"","lastName":"Xue","suffix":""},{"id":521814532,"identity":"d9a5dc59-8068-46dc-9725-bb5434dbdf65","order_by":8,"name":"Robert Henry","email":"","orcid":"","institution":"University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Henry","suffix":""},{"id":521814533,"identity":"65e1313f-180c-47dc-95c0-b01b74c61cd9","order_by":9,"name":"Wenquan Wang","email":"","orcid":"","institution":"Hainan University","correspondingAuthor":false,"prefix":"","firstName":"Wenquan","middleName":"","lastName":"Wang","suffix":""},{"id":521814534,"identity":"a9cbe612-a4dd-4cbb-9468-d72462acc07f","order_by":10,"name":"Fei Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBAC9gbGBmYgLWfAwNgAFUvAr4XnAESLMSlaGBhAWhI3IMQIaWFvbvxcUHEnfTv74bYHP3ccZuBnzzFg+LkDjxaeg83SM848y93Zk9hu2HvmMINkzxsDxt4zuLXYSyS2MfO2Hc7dcCCxTQLIYDC4kWPAzNiGxxb5h0At/w6nG5x/2Cb5F6jFnqAWCUaglobDCQY3EtukwbZIENLCk9gszXPssOGGGw/bpGXb0nkkzjwrONiLTwv78YefeWoOyxucT38m+bbNWo6/PXnjg594tGCaASIOkKBhFIyCUTAKRgEWAAAHr1Hd5Bw3QwAAAABJRU5ErkJggg==","orcid":"","institution":"Hainan University","correspondingAuthor":true,"prefix":"","firstName":"Fei","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-09-08 04:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7559915/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7559915/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10142-026-01829-9","type":"published","date":"2026-02-16T15:58:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":92545787,"identity":"a141ff93-9c4f-4658-9fcc-b91af09a4e5b","added_by":"auto","created_at":"2025-09-30 20:28:14","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":142812863,"visible":true,"origin":"","legend":"","description":"","filename":"MS.docx","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/80ff34eb83ca5e77db44f14a.docx"},{"id":92545765,"identity":"63c38d11-ecc1-49ad-a1aa-7a76062c663a","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11334,"visible":true,"origin":"","legend":"","description":"","filename":"dadfe7905c6d4805acf9b4069a3a18c7.json","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/6d30e1c8f70f76488f5947b1.json"},{"id":92545772,"identity":"32e0ffdb-be8d-435a-9a4d-4ecbffb89b7f","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":142733,"visible":true,"origin":"","legend":"","description":"","filename":"dadfe7905c6d4805acf9b4069a3a18c71enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/a29cabf9b6fa4237e90594ba.xml"},{"id":92545783,"identity":"3df4d5e2-91c8-45e7-a281-a3cf15f942b0","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40582704,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/c49fd40795a3d60f268ffbdc.jpeg"},{"id":92545778,"identity":"cd644237-89ca-41d5-b9c0-0360143d0a28","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18967586,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/eebd892f2975e82a7dbe77e2.jpeg"},{"id":92545774,"identity":"64b350c7-bf9d-48a0-aacd-b9da06e3541e","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"jpeg","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2227488,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/900b5e460a66b46f45d85670.jpeg"},{"id":92545785,"identity":"e89a7ee0-4185-4b72-90ce-22f096450a86","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":49112232,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/dea5a19d1b3873794137f2db.jpeg"},{"id":92545773,"identity":"122d207b-9d71-447c-88c7-44f2a95be7ef","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"jpeg","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6240072,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/18119ef01fb5b1a3d2c31175.jpeg"},{"id":92545943,"identity":"c9d578ea-f3c9-4890-b423-44e0b2196838","added_by":"auto","created_at":"2025-09-30 20:36:13","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":25572752,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/6fb53463ead5e5b3b32739c3.jpeg"},{"id":92545941,"identity":"5f274944-ff79-4bb8-bb93-0fa665b707ea","added_by":"auto","created_at":"2025-09-30 20:36:13","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":417858,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/f0362f39ebcdc24e4c0b3c03.png"},{"id":92545782,"identity":"12dcb94c-e16b-4a0d-b9fb-bc078a118fed","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9189066,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/a72b2d5d5f15d64e6a246e76.png"},{"id":92545781,"identity":"fc5a585c-1f4a-45dc-98cd-ad005426f61e","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105042,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/d77b65c11c22d9ba6facd9c1.png"},{"id":92545784,"identity":"9af70e41-01b7-437c-a23b-f62a65252d52","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20906043,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/b74e34724385d81a88d3d49e.png"},{"id":92546333,"identity":"8b6483c5-07e2-4251-a21e-9953f7ee7d91","added_by":"auto","created_at":"2025-09-30 20:44:13","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2651252,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/108dfb1ca9e1aa38ce73d108.png"},{"id":92545940,"identity":"e3e9970e-73a1-4c81-85c6-82eb9a3d1d91","added_by":"auto","created_at":"2025-09-30 20:36:13","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1847097,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/f295a9f907f67ff9b04f194a.png"},{"id":92545775,"identity":"7b8173e2-2609-44fa-acf9-8344d3844971","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":142404,"visible":true,"origin":"","legend":"","description":"","filename":"dadfe7905c6d4805acf9b4069a3a18c71structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/141389838745f6b911478622.xml"},{"id":92545777,"identity":"2cc02ec1-97c5-4098-908a-a209dcc05b72","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152586,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/deb51b527d0c0ddb561ebb9f.html"},{"id":92545936,"identity":"a3e8add8-cab1-427c-b933-d624a0cfcc9b","added_by":"auto","created_at":"2025-09-30 20:36:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2880748,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMorphological and genomic features of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. lanceolata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(a) Hi-C heatmap of the genome assembly. (b) Distribution of 19-bp short reads. (c) Assessment of completeness for the genome assembly and gene set annotation. (d) Genomic features of \u003cem\u003eS. lanceolata\u003c/em\u003e (chromosome karyotype; gene density; GC content per Mb; repeat content per Mb; long terminal repeat (LTR) distribution; identification of syntenic regions among different chromosomes). (e) Chloroplast genome of \u003cem\u003eS. lanceolata\u003c/em\u003e. (f) Mitochondrial genome of \u003cem\u003eS. lanceolata\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/f9bdd23cdf7784b92819296b.png"},{"id":92545937,"identity":"8c75d332-6847-4836-b16c-c1d7d8f07e90","added_by":"auto","created_at":"2025-09-30 20:36:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4259246,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGenome evolution and phylogenetic analysis of representative Malvaceae species.\u003c/strong\u003e (a) Distribution of synonymous substitution rates (Ks) for paralogous genes within the genomes of three Malvaceae species. (b) Synteny between \u003cem\u003eS. lanceolata\u003c/em\u003e and \u003cem\u003eH. littoralis\u003c/em\u003e, \u003cem\u003eF. kwangsiensis\u003c/em\u003e, and \u003cem\u003eF. hainanensis\u003c/em\u003e. (c) Images of six Malvaceae species. (d) Phylogeny and divergence time estimation of 39 plant species.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/da2566d31f85e74250d27900.png"},{"id":92545767,"identity":"e23d0ceb-63f5-46aa-b2ba-15ac2b7b6ae8","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1032068,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaryotype analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. lanceolata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand three other Malvaceae species.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/bf09978cf20ab522225c0438.png"},{"id":92545769,"identity":"897bd4f6-dd98-4299-9d6f-461adae48f05","added_by":"auto","created_at":"2025-09-30 20:28:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3815923,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMorphological features of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. lanceolata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(a) Morphology of a mature plant. (b–d) Follicles (fruits) at different developmental stages. (e–g) Seeds at different developmental stages. (h–j) Longitudinal sections of seeds at various developmental stages.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/b9fccaa90a72decfbedcc850.png"},{"id":92545938,"identity":"cab65bd3-954a-4461-aec9-6aba393cf334","added_by":"auto","created_at":"2025-09-30 20:36:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2162266,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGO functional annotation and physiological–biochemical changes during seed development in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. lanceolata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e(a) GO functional annotation of \u003cem\u003eS. lanceolata\u003c/em\u003e, with seed development and starch metabolism highlighted within the red box. (b–e) Changes in mineral element contents in seeds at different developmental stages. (f) Changes in total starch content in seeds at various developmental stages. (g) Changes in amylose content in seeds at different developmental stages. (h) Changes in flavonoid content in seeds at different developmental stages.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/cf574735e9da2953e6cf0171.png"},{"id":92546332,"identity":"b7e048b0-de00-40dd-a163-f3102b21ac2c","added_by":"auto","created_at":"2025-09-30 20:44:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1986514,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenetic relationships and regulatory pathway model of fruit dehiscence genes in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. lanceolata\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e(a–d) Maximum likelihood phylogenetic trees of the \u003cem\u003eSHP1/2\u003c/em\u003e, \u003cem\u003eIND\u003c/em\u003e, \u003cem\u003eFUL\u003c/em\u003e, and \u003cem\u003eALC\u003c/em\u003e gene families. (e) Simplified model of the regulatory pathway controlling fruit dehiscence in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/9c192ad1d05a4d3b8730aaa4.png"},{"id":103251286,"identity":"b53a5bec-1f7f-48e9-9e13-0b99531c2fed","added_by":"auto","created_at":"2026-02-23 16:08:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17360880,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7559915/v1/ac4830da-19f8-468d-9c6d-0d4be305ac60.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Reference Genome Sequence of the Scarlet Follicle, Sterculia lanceolata, reveals a paleo-polyploidization and its impact on fruit quality and fruit dehiscence","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eSterculia lanceolata\u003c/em\u003e, an important member of the genus \u003cem\u003eSterculia\u003c/em\u003e within the family Malvaceae, is a striking subtropical evergreen tree (Guymer \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). It is renowned for its distinctive economic value and long-standing traditional medicinal uses (Prasad et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), with a broad geographic distribution primarily across subtropical regions of Asia, spanning southern China, Vietnam, Thailand, India, and beyond (Bawri et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The species exhibits remarkable adaptability to the humid and variable climatic conditions characteristic of these regions. In addition to serving as a major regional source of timber, its roots, leaves, and seeds have been widely utilized in traditional medicine. For instance, according to the theory of traditional Chinese medicine, its leaves are pungent and warm in nature, associated with the liver meridian, and function to disperse blood stasis and alleviate pain. They have been commonly applied to treat symptoms such as pain, swelling, and bruising caused by trauma or blood stasis. Previous studies have shown that plants of the genus \u003cem\u003eSterculia\u003c/em\u003e are generally rich in flavonoids and their derivatives, compounds that have been demonstrated to possess diverse biological activities, including antibacterial, anti-inflammatory, antioxidant, and anticancer properties (L. Wang et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Within forest ecosystems, \u003cem\u003eS. lanceolata\u003c/em\u003e also plays an essential role in providing both food sources and habitats for a variety of organisms. Despite its pronounced ecological and economic importance, our understanding of its genetics remains extremely limited. To date, the NCBI public database contains only a single transcriptome dataset derived from its leaves (PRJNA435648), and no complete nuclear genome has yet been reported for any member of the genus \u003cem\u003eSterculia\u003c/em\u003e (Eum et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This knowledge gap has posed a significant barrier to uncovering the complex molecular mechanisms underlying its physiological characteristics, medicinal value, and ecological adaptability (Ganie et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis knowledge gap highlights the urgency of conducting in-depth genetic studies on \u003cem\u003eS. lanceolata\u003c/em\u003e, as such research is essential to deciphering the genetic codes underlying its remarkable adaptability and economically important traits. The Malvaceae family also encompasses globally significant crops such as cotton (\u003cem\u003eGossypium raimondii\u003c/em\u003e) and durian (\u003cem\u003eDurio zibethinus\u003c/em\u003e), and important ornamental plant species such as \u003cem\u003eHibiscus\u003c/em\u003e (Cvetković et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although the genomes of multiple cotton and durian species have been decoded, providing profound insights into key traits such as fiber development and flavor compound biosynthesis, investigations into the evolutionary origins and genetic foundations of its important sister genus, \u003cem\u003eSterculia\u003c/em\u003e, remain in their infancy. Given the unique medicinal value and strong environmental adaptability of \u003cem\u003eS. lanceolata\u003c/em\u003e, obtaining its complete genome and identifying genes associated with its desirable traits hold great significance for advancing both evolutionary studies within Malvaceae and the genetic improvement of the species itself. More importantly, for certain lineage-specific biological traits within Malvaceae\u0026mdash;such as the molecular mechanisms regulating precise fruit dehiscence following maturation\u0026mdash;there is still a lack of in-depth cross-species comparative research (Pab\u0026oacute;n-Mora et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTherefore, this study aims to construct a high-quality, chromosome-level reference genome of \u003cem\u003eS. lanceolata\u003c/em\u003e. By conducting an in-depth analysis of its genomic background and evolutionary history, we seek to identify the key gene families that determine its unique fruit morphology. Compared with existing studies on the genus \u003cem\u003eSterculia\u003c/em\u003e, which have been largely limited to morphological descriptions and transcriptome sequencing (Eom and Na \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), this research provides, for the first time, a complete nuclear genome assembly, representing a major advancement. This will enable a deeper understanding of the molecular mechanisms underlying its ecological adaptability and valuable economic traits.\u003c/p\u003e\u003cp\u003eIn addition, our findings bear direct significance for research across the entire Malvaceae family. Given the phylogenetic position of \u003cem\u003eS. lanceolata\u003c/em\u003e within Malvaceae, our analysis of whole-genome duplication events and identification of key gene family expansions provide a valuable resource for comparative genomics. Specifically, the identification of critical genes associated with fruit dehiscence in \u003cem\u003eS. lanceolata\u003c/em\u003e may offer novel genetic targets for the improvement of other related crops. Building on these insights, our study not only deepens the understanding of this economically important forest species but also provides essential scientific evidence for the evolution, genetic improvement, and conservation of Malvaceae.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExperimental materials and sequencing technologies\u003c/h2\u003e\u003cp\u003eSamples for sequencing of \u003cem\u003eS. lanceolata\u003c/em\u003e were collected in the vicinity of the Innovation Research and Education Valley teaching area, Yazhou District, Sanya City, Hainan Province, China. DNA was extracted from young leaves, while samples for transcriptome analysis were obtained from various tissues of \u003cem\u003eS. lanceolata\u003c/em\u003e, including roots, stems, functional leaves, and seeds. Samples were immediately flash-frozen in liquid nitrogen after collection and stored at \u0026minus;\u0026thinsp;80\u0026deg;C in an ultra-low temperature freezer for subsequent nucleic acid extraction. Genomic DNA was randomly sheared, and short-read libraries of \u003cem\u003eS. lanceolata\u003c/em\u003e were constructed following the TruSeq DNA sample preparation protocol. These libraries were then subjected to paired-end sequencing (150 bp read length) on the NovaSeq 6000 platform. In addition, a PacBio HiFi library was constructed. The library was prepared for sequencing using the PacBio Binding Kit (Wenger et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), in which primers and polymerases were ligated to the library. The final reaction products were purified with AMPure PB Beads and subsequently sequenced on the Revio sequencing system. Furthermore, Hi-C libraries were sequenced on the Illumina NovaSeq platform with paired-end reads of 150 bp. All transcriptome libraries were sequenced on the Illumina platform (Quail et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), generating paired-end reads of 150 bp. All sequencing data were processed using fastp v0.23.4 (S. Chen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) to filter out low-quality reads and obtain clean data for downstream analyses.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGenome size estimation based on k-mer analysis\u003c/h3\u003e\n\u003cp\u003eA k-mer analysis was performed for genome survey. To obtain clean reads, the raw data were filtered by removing low-quality reads, short reads, adapter sequences, and polyG tails. Subsequently, KMC v3.2.4 (Kokot et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) was employed to conduct k-mer frequency distribution analysis with \u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;19. Genome size, heterozygosity, and repeat content were estimated using GenomeScope v2.0 (Ranallo-Benavidez et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The genome size of \u003cem\u003eS. lanceolata\u003c/em\u003e was estimated to be 465.5 Mb, with a heterozygosity of 0.321%.\u003c/p\u003e\n\u003ch3\u003eChromosome-level genome assembly\u003c/h3\u003e\n\u003cp\u003eFirst, the raw HiFi data were converted into FASTQ format using samtools v1.21 (Li et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). To obtain clean HiFi and Hi-C data, fastp v0.23.4 (S. Chen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) was applied to filter out low-quality reads, short reads, adapter sequences, and polyG tails from the raw datasets. The filtered HiFi data were then assembled into contigs using hifiasm 0.19.9 (Cheng et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) with default parameters. Hi-C data processing was performed with ALLHiC v0.9.13 (Zhang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), in which the clean Hi-C reads were aligned to the assembled contigs to generate an interaction matrix. Subsequently, the contigs were ordered and anchored using 3D de novo Assembly v180114 (Dudchenko et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Finally, the assembled Hi-C contact maps were manually inspected using Juicebox v1.11.08 (Durand et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). To assess assembly quality, we conducted a comprehensive evaluation using BUSCO v5.1 (Seppey et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) with the eudicots_odb10 database to examine the presence and completeness of single-copy orthologs. Ultimately, we obtained a high-quality, well-assembled \u003cem\u003eS. lanceolata\u003c/em\u003e genome sequence, providing a solid foundation for future functional studies.\u003c/p\u003e\n\u003ch3\u003eGene prediction and annotation\u003c/h3\u003e\n\u003cp\u003eWe utilized RepeatModeler v2.0.3 (Flynn et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to construct a \u003cem\u003ede novo\u003c/em\u003e repeat library for the classification of repetitive sequences, and employed RepeatMasker v4.1.2 (N. Chen \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) to identify them. In total, 376.7 Mb of repetitive elements were identified, constituting 59.6% of the \u003cem\u003eS. lanceolata\u003c/em\u003e genome. All transcriptomic data were aligned to the genome using HISAT2 v2.2.1 (Kim et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Subsequently, BRAKER v3.0.3 (Gabriel et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) was used to automatically train a species-specific parameter model and annotate gene structures, leveraging alignment evidence from both transcriptomic data and proteins. For functional annotation, the predicted protein-coding genes were aligned against the eggNOG database (Hern\u0026aacute;ndez-Plaza et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eAssembly and annotation of the chloroplast and Mitochondrion genome\u003c/h3\u003e\n\u003cp\u003eTo assemble the chloroplast genome, we used the GetOrganelle v1.7.7.1 (Jin et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) software to assemble the Illumina paired-end sequencing data, specifying the -k option with values set to 21, 45, 65, 85, and 105, respectively. For mitochondrial genome assembly, we utilized the Oatk v1.0 (Zhou et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) toolkit for \u003cem\u003ede novo\u003c/em\u003e assembly from PacBio HiFi sequencing reads, invoking the syncasm module within Oatk to filter specific k-mer sequences from the raw HiFi reads. We applied -k 1001 to set the minimum k-mer length and used -c 150 to set the minimum coverage threshold.\u003c/p\u003e\u003cp\u003eThe resulting FASTA file was used as the input for annotation on the OGDRAW platform (Lohse et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chlorobox.mpimp-golm.mpg.de/OGDraw.html\u003c/span\u003e\u003cspan address=\"https://chlorobox.mpimp-golm.mpg.de/OGDraw.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Following the platform's guidelines, we annotated the organellar genomes and chose the GenBank (GB) format for the output. To visualize the annotated genome, we accessed the \"Upload\" section of the OGDRAW online tool and submitted the GB file containing the \u003cem\u003eS. lanceolata\u003c/em\u003e genome sequence. After selecting the appropriate options, we submitted the file for processing. OGDRAW then generated and displayed the annotated organellar genome in a graphical format, thus providing a clear representation of the organellar genetic structure.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSynteny and whole-genome duplication analysis\u003c/h2\u003e\u003cp\u003eWe selected the protein sequence data of \u003cem\u003eH. littoralis\u003c/em\u003e, \u003cem\u003eF. kwangsiensis\u003c/em\u003e, \u003cem\u003eF. hainanensis\u003c/em\u003e, and \u003cem\u003eS. lanceolata\u003c/em\u003e as the basis for our collinearity analysis. To ensure the reliability of the results, we performed both intra- and inter-genomic self- and cross-comparisons using the BLASTP v2.12.0 tool, with an E-value threshold set to 1e-5. Subsequently, we utilized MCScanX v1.0.0 (Y. Wang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) to identify high-confidence collinear blocks. For the visualization of collinearity information, we used JCVI v1.5.1 (Tang et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which effectively displays inter-chromosomal collinear regions. For the analysis of whole-genome duplication (WGD) events, we applied WGD v1.1.054 (Schranz et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) to calculate the WGD incidence rate and used the WGDI v0.6.5 (Sun et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) software to plot the Ks value distribution, thereby estimating the timing and frequency of WGD events.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePolyploidy and karyotype analysis\u003c/h3\u003e\n\u003cp\u003eWe pre-processed the protein data for \u003cem\u003eS. lanceolata\u003c/em\u003e, \u003cem\u003eD. zibethinus\u003c/em\u003e, \u003cem\u003eG. raimondii\u003c/em\u003e, and \u003cem\u003eH. schizopetalus\u003c/em\u003e using BLAST v2.9.0\u0026ndash;2 (Altschul et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), selecting the output file format \"-outfmt 6\" and \"-num_alignment 2\". Subsequently, we constructed the ancestral Malvaceae karyotype (AMK) using WGDI v0.6.5 (Sun et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) with the \"-km\" option. Based on the protein sequence information, we inferred the modern karyotypes of the studied species. To quantify the fission and fusion events that occurred in the evolutionary history of these species, we enumerated all homologous segments and calculated the corresponding fission and fusion counts.\u003c/p\u003e\n\u003ch3\u003eIdentification and Functional Enrichment Analysis of WGD Genes\u003c/h3\u003e\n\u003cp\u003eTo identify genes in the \u003cem\u003eS. lanceolata\u003c/em\u003e genome derived from whole-genome duplication (WGD), we first performed an all-versus-all BLASTP v2.12.0 (Lavigne et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) search of all protein sequences, setting an E-value threshold of 1e-5. Using these alignment results and gene location data, we detected collinear blocks and classified gene duplication types with the MCScanX v1.0.0 (Y. Wang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) toolkit. Subsequently, we conducted a Gene Ontology (GO) enrichment analysis on the identified set of WGD genes. We used the web-based tool agriGO v2.0 (Tian et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://systemsbiology.cau.edu.cn/agriGOv2/\u003c/span\u003e\u003cspan address=\"https://systemsbiology.cau.edu.cn/agriGOv2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for the enrichment analysis. agriGO v2.0 performs gene enrichment using the Singular Enrichment Analysis (SEA) method, with the SEA parameters set as follows: Fisher's exact test, Yekutieli correction (FDR under dependency), a significance level of 0.05, a minimum of 5 mapped genes, and analysis of the complete GO and molecular function.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePhylogenetic analysis and divergence time estimation\u003c/h2\u003e\u003cp\u003eWe collected protein data for 39 species from public databases such as TropiCODB (Dai et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinformatics.hainanu.edu.cn/tropdb/\u003c/span\u003e\u003cspan address=\"https://bioinformatics.hainanu.edu.cn/tropdb/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and PLAZA 5.0 (Van Bel et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinformatics.psb.ugent.be/plaza/versions/plaza_v5_dicots/\u003c/span\u003e\u003cspan address=\"https://bioinformatics.psb.ugent.be/plaza/versions/plaza_v5_dicots/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), focusing on plants from the Malvaceae family and the model plant \u003cem\u003eArabidopsis thaliana\u003c/em\u003e. Using OrthoFinder v2.5.5 (Emms and Kelly \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), a tree-based method, we identified high-quality orthogroups among these species. The OrthoFinder output was optimized with TRIMAL (Capella-Guti\u0026eacute;rrez et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), applying the -gt 0.6 option to remove short sequences within each orthogroup and using a -cons 60 threshold to retain only the most conserved sites. Subsequently, we performed a Maximum Likelihood (ML) analysis on the concatenated protein sequences of these species using the parallel version of RAxML v8.2.13 (Stamatakis \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) (raxmlHPC-PTHREADS). This analysis aimed to infer the phylogenetic relationships in the context of \u003cem\u003eS. lanceolata\u003c/em\u003e, thereby providing a clearer understanding of its evolutionary position relative to other plant species.\u003c/p\u003e\u003cp\u003eTo estimate the divergence times among closely related species, including \u003cem\u003eH. littoralis\u003c/em\u003e, \u003cem\u003eF. kwangsiensis\u003c/em\u003e, \u003cem\u003eF. hainanensis\u003c/em\u003e, \u003cem\u003eT. cacao\u003c/em\u003e, \u003cem\u003eD. zibethinus\u003c/em\u003e, \u003cem\u003eB. ceiba\u003c/em\u003e, \u003cem\u003eG. hirsutum\u003c/em\u003e, and \u003cem\u003eS. lanceolata\u003c/em\u003e, we utilized the protein sequences of single-copy genes from Malvaceae plants. The divergence time estimation was conducted using the mcmctree v4.9 (Puttick \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) tool in the PAML package. Following the analysis, the estimated divergence times were integrated into a phylogenetic tree reconstructed with IQTREE v2.4.0 (Minh et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), thereby providing a comprehensive understanding of the evolutionary relationships among the species.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eIdentification and Phylogeny of Key Fruit Dehiscence Genes\u003c/h2\u003e\u003cp\u003eTo elucidate the molecular regulatory mechanism of follicle dehiscence along the ventral suture in \u003cem\u003eS. lanceolata\u003c/em\u003e, we first selected five known key regulatory genes from the model plant \u003cem\u003eArabidopsis thaliana\u003c/em\u003e: SHP1 (AT3G58780), SHP2 (AT2G42830), FUL (AT5G60910), IND (AT4G00120), and ALC (AT5G67110). The proteome data used in this study included those of \u003cem\u003eS. lanceolata\u003c/em\u003e, \u003cem\u003eGossypium hirsutum\u003c/em\u003e (upland cotton), \u003cem\u003eDurio zibethinus\u003c/em\u003e (durian), and \u003cem\u003eArabidopsis thaliana\u003c/em\u003e. Based on the conserved protein domain features of the target genes in \u003cem\u003eA. thaliana\u003c/em\u003e, we downloaded the Hidden Markov Model (HMM) file for the MADS-box domain from the Pfam database v35.0 (Mistry et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Using the hmmsearch program within the HMMER package v3.3.2 (Finn et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) with default parameters, a search was conducted against the combined proteomes of the four aforementioned species.\u003c/p\u003e\u003cp\u003eTo elucidate the evolutionary relationships among the members of each gene family, we constructed phylogenetic trees for each family separately. First, a multiple sequence alignment of the homologous protein sequences for each family was performed using MAFFT v7.525 (Katoh and Standley \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Subsequently, based on the alignment results, phylogenetic trees were constructed using FastTree v2.1.11 (Price et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) with the WAG amino acid substitution model and the approximate maximum-likelihood method. Branch reliability was assessed based on Shimodaira-Hasegawa-like (SH-like) local support values. Finally, the resulting tree files were imported into the iTOL v6 (Letunic and Bork \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) online platform for visualization and annotation.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eChromosome-level genome assembly\u003c/h2\u003e\u003cp\u003eTo gain a deeper understanding of the genetic characteristics and evolutionary history of \u003cem\u003eS. lanceolata\u003c/em\u003e, we employed advanced sequencing technologies to successfully construct a high-quality, chromosome-level reference genome. The final assembly yielded a genome size of 602.8 Mb with a contig N50 of 29.3 Mb, indicating excellent continuity. Using high-throughput chromosome conformation capture (Hi-C) technology, the vast majority of sequences were successfully anchored to 20 pseudochromosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The Hi-C interaction heatmap clearly displayed strong diagonal signals and very weak inter-chromosomal interactions, strongly supporting the high accuracy and completeness of our genome assembly at the chromosome level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). To evaluate the overall quality of the genome, k-mer analysis was performed. The results indicated that the \u003cem\u003eS. lanceolata\u003c/em\u003e genome exhibits a low heterozygosity rate estimated at 0.321% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), While this characteristic makes the assembly of a haplotype-resolved genome both difficult and less critical, it provides a solid foundation for subsequent high-quality genome assembly and annotation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGenome completeness is a core metric for evaluating its quality. We assessed the completeness of the genome using BUSCO v5.1 (Seppey et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The results showed that the BUSCO completeness of the genome assembly reached 98.7% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec), indicating that nearly all core conserved genes were fully represented. This high score demonstrates that the \u003cem\u003eS. lanceolata\u003c/em\u003e genome we obtained is a high-quality, highly complete reference genome, sufficient to support downstream analyses such as comparative genomics, evolutionary studies, and functional gene mining. In addition, we successfully assembled the complete chloroplast (160,400 bp) and mitochondrial (161,707 bp) genomes (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef), providing additional layers of genetic information for species identification and phylogenetic research.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenome features of \u003cem\u003eS. lanceolata\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eS. lanceolata\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePloidy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2n\u0026thinsp;=\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssembled genome size (Mb)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e602.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenomic heterozygosity (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContig N50 (Mb)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of contigs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e188\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of pseudochromosomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepeat sequence content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGC content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of gene models\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35,873\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenome BUSCOs (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene BUSCO (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e96.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eRepeat sequence characterization and genome annotation\u003c/h2\u003e\u003cp\u003eFollowing repeat annotation using both \u003cem\u003ede novo\u003c/em\u003e prediction and homology-based approaches, we found that \u003cem\u003eS. lanceolata\u003c/em\u003e contains a substantial proportion of repetitive sequences, accounting for 59.59% of the genome. Among these, 42.46% are retrotransposons and 3.59% are DNA transposons, with long terminal repeats (LTRs) comprising 40.94% of the genome. The overall genomic GC content reached 32.71% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). By integrating \u003cem\u003ede novo\u003c/em\u003e prediction, homology-based alignment, and transcriptome annotation, we identified a total of 35,873 protein-coding genes, with a BUSCO v5.1 completeness of 96.4% for the genome (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Notably, the number of genes in \u003cem\u003eS. lanceolata\u003c/em\u003e exceeds that of closely related Malvaceae subfamily species, including \u003cem\u003eH. littoralis\u003c/em\u003e (29,154 genes) (He et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)d \u003cem\u003ehainanensis\u003c/em\u003e (34,388 genes) (Dong et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), suggesting that \u003cem\u003eS. lanceolata\u003c/em\u003e may encode a broader repertoire of stress-resistance and developmental genes. This provides a valuable genetic resource for horticultural breeding research, with the potential to introduce novel genes to enhance resistance and growth-related traits.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAncient Whole-Genome Duplications Shaping Evolutionary Dynamics\u003c/h2\u003e\u003cp\u003eWhole-genome duplication (WGD) or polyploidy events are key drivers of plant evolution, providing abundant genetic material that facilitates adaptation and species diversification. To investigate the evolutionary history of \u003cem\u003eS. lanceolata\u003c/em\u003e and related species, we constructed a phylogenetic tree encompassing multiple subfamilies within Malvaceae (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). The tree clearly places \u003cem\u003eS. lanceolata\u003c/em\u003e within the subfamily Sterculioideae and reveals well-defined phylogenetic relationships with other Malvaceae species.\u003c/p\u003e\u003cp\u003eNotably, we identified several ancient polyploidy events at key nodes of the phylogenetic tree. For example, on the branch of Helicteroideae, which includes durian (\u003cem\u003eDurio zibethinus\u003c/em\u003e), we detected a pronounced whole-genome triplication (WGT) event (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). This finding is consistent with previous studies and helps explain the large genome size and complex genetic background of durian.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo elucidate the polyploidy history and chromosomal evolution of Malvaceae plants, we conducted a comparative genomics analysis of \u003cem\u003eS. lanceolata\u003c/em\u003e and its closely related species. Within the \u003cem\u003eS. lanceolata\u003c/em\u003e genome, the distribution of synonymous substitution rates (Ks) for paralogous gene pairs exhibits a pronounced peak at approximately 1.6, providing clear evidence for an ancient whole-genome duplication (WGD) event (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eMore importantly, analysis of Ks distributions of paralogous genes offers critical evidence for the evolutionary history of \u003cem\u003eS. lanceolata\u003c/em\u003e itself. The Ks distribution shows a distinct peak at around 0.3 for \u003cem\u003eS. lanceolata\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, red solid line), which is a characteristic molecular signature of a recent polyploidy event. In combination with the WGD events annotated on the phylogenetic tree (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) along the branch of \u003cem\u003eS. lanceolata\u003c/em\u003e, we confirmed that this species underwent an independent whole-genome duplication during its evolutionary history. This WGD event provided \u003cem\u003eS. lanceolata\u003c/em\u003e with a substantial number of novel genes, which are likely associated with the formation of its unique biological traits, such as seed development and fruit dehiscence mechanisms. In contrast, an older Ks peak (approximately 1.5\u0026ndash;2.0) is shared among multiple species, which may correspond to ancient polyploidy events in the Malvaceae family or even earlier. Inter-species synteny analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) further corroborates the chromosomal conservation and rearrangement patterns among these species, providing cross-validation for the inference of polyploidy events.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChromosomal rearrangements shaped the unique 20 chromosomes of\u003c/b\u003e \u003cb\u003eS. lanceolata\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur reconstruction of karyotype evolution (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicates that a common ancestor of Malvaceae possessed a karyotype with 11 chromosomes (n\u0026thinsp;=\u0026thinsp;11). Following this ancestral stage, a major divergence occurred. The lineage leading to Malvoideae (including \u003cem\u003eGossypium raimondii\u003c/em\u003e and \u003cem\u003eHibiscus schizopetalus\u003c/em\u003e) underwent an ancient whole-genome pentaplication (WGM) event. In contrast, the lineage leading to \u003cem\u003eS. lanceolata\u003c/em\u003e within Sterculioideae experienced an independent whole-genome duplication (WGD) event. Following this WGD, the \u003cem\u003eS. lanceolata\u003c/em\u003e genome underwent extensive chromosomal rearrangements, including reciprocal translocations (RTA), end-to-end joining (EEJ), fissions, and losses, ultimately stabilizing into its current karyotype of 20 chromosome pairs (n\u0026thinsp;=\u0026thinsp;20, 2n\u0026thinsp;=\u0026thinsp;40).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor comparison, its close relative durian (\u003cem\u003eDurio zibethinus\u003c/em\u003e, subfamily Helicteroideae) appears to have undergone another independent whole-genome triplication (WGT) event, followed by a series of complex fissions, nested chromosome fusions (NCFs), and other rearrangements, resulting in its modern karyotype of 2n\u0026thinsp;=\u0026thinsp;56. \u003cem\u003eGossypium raimondii\u003c/em\u003e has maintained a relatively stable karyotype (2n\u0026thinsp;=\u0026thinsp;26) with few subsequent changes, whereas \u003cem\u003eHibiscus schizopetalus\u003c/em\u003e experienced at least two additional WGD events, followed by extensive chromosomal fissions and fusions, culminating in its current karyotype of 2n\u0026thinsp;=\u0026thinsp;42. These diverse evolutionary trajectories vividly illustrate the substantial differences in genome structural evolution among lineages following WGD events, and it is precisely these differences that have shaped the rich and varied biological characteristics of Malvaceae species.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eDynamic changes in seed nutrient composition and gene accumulation driven by polyploidy\u003c/h2\u003e\u003cp\u003eThe seeds of \u003cem\u003eS. lanceolata\u003c/em\u003e have attracted considerable attention due to their rich nutritional content and unique flavor. We conducted a systematic study of the morphology and nutritional composition of \u003cem\u003eS. lanceolata\u003c/em\u003e seeds during their development from immature to mature stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Morphologically, both the fruit (follicle) and seeds undergo significant color changes throughout development (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee\u0026ndash;g).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo characterize the molecular mechanisms underlying these phenotypic changes, we conducted metabolite profiling and transcriptomic analyses on seeds at different developmental stages. We first accurately identified the set of paralogous genes retained from the WGD event. This specific gene set was then subjected to Gene Ontology (GO) enrichment analysis to determine the biological processes predominantly associated with these expanded gene families. The results provided compelling evidence: among the WGD-retained genes, GO terms related to \u0026ldquo;Seed development\u0026rdquo; and \u0026ldquo;Starch metabolic process\u0026rdquo; were significantly enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). This finding directly indicates that the WGD event in \u003cem\u003eS. lanceolata\u003c/em\u003e did not randomly increase gene copy numbers, but rather led to a directed, large-scale expansion of gene repertoires associated with the synthesis and accumulation of seed nutrients. These expanded gene sets provide abundant raw material for the complex regulatory networks governing seed metabolism.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe metabolite profiling results provided direct evidence supporting this conclusion. We found that, as the seeds matured, the contents of several key mineral elements, including magnesium (Mg), phosphorus (P), and potassium (K), increased significantly (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), which is critical for energy storage in seeds and subsequent germination. Total starch content peaked during the mid-developmental stage and slightly declined at maturity, while amylose content also exhibited dynamic changes throughout seed development (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg). Interestingly, we observed that flavonoid content was very high during the early stages of seed development but decreased sharply upon maturation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh). Flavonoids are generally associated with plant defense and bitterness, and their reduction is considered an evolutionary strategy to enhance seed palatability, attract animals for consumption, and facilitate dispersal (Cipollini and Levey \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Therefore, the observed changes in flavonoid content in \u003cem\u003eS. lanceolata\u003c/em\u003e seeds likely reflect an evolutionary compromise balancing the dual demands of \u0026ldquo;self-protection\u0026rdquo; and \u0026ldquo;attracting dispersers\u0026rdquo; during co-evolution.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eExpansion and mechanistic study of gene families related to fruit dehiscence\u003c/h2\u003e\u003cp\u003eThe fruits of \u003cem\u003eS. lanceolata\u003c/em\u003e undergo dehiscence along the ventral suture upon maturation, representing a critical biological process for the propagation of the species. This process is regulated by a precise gene regulatory network. We focused on the well-characterized core pathway controlling fruit dehiscence, including the MADS-box family genes \u003cem\u003eFUL\u003c/em\u003e and \u003cem\u003eSHP1/2\u003c/em\u003e, as well as the bHLH transcription factor family genes \u003cem\u003eIND\u003c/em\u003e and \u003cem\u003eALC\u003c/em\u003e. According to the classical regulatory model (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee), \u003cem\u003eFUL\u003c/em\u003e is primarily expressed in the fruit valves, suppressing the formation of the dehiscence zone, whereas \u003cem\u003eSHP1/2\u003c/em\u003e, \u003cem\u003eIND\u003c/em\u003e, and \u003cem\u003eALC\u003c/em\u003e act synergistically to promote the differentiation and lignification of the dehiscence zone, ultimately leading to fruit opening.\u003c/p\u003e\u003cp\u003eTo validate this model and investigate the unique dehiscence mechanism in \u003cem\u003eS. lanceolata\u003c/em\u003e, we conducted a systematic phylogenetic analysis of these key gene families (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea\u0026ndash;d). In the analyses of the \u003cem\u003eSHP1/2\u003c/em\u003e, \u003cem\u003eIND\u003c/em\u003e, \u003cem\u003eFUL\u003c/em\u003e, and \u003cem\u003eALC\u003c/em\u003e gene families, we observed that, compared with the model plant \u003cem\u003eArabidopsis thaliana\u003c/em\u003e, \u003cem\u003eS. lanceolata\u003c/em\u003e (denoted as \"Slan\" in the figures) exhibits a notable expansion in gene copy numbers across most of these families (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea\u0026ndash;c). For instance, in the phylogenetic tree of the \u003cem\u003eSHP1/2\u003c/em\u003e gene family, multiple \"Slan\" genes cluster together, forming species-specific gene clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFruit dehiscence is a critical developmental process governed by a finely tuned gene regulatory network that ensures a clear boundary between the valve and the dehiscence zone (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee). Within this regulatory network, the MADS-box transcription factors \u003cem\u003eSHP1/2\u003c/em\u003e act upstream, activating the downstream bHLH factors \u003cem\u003eIND\u003c/em\u003e and \u003cem\u003eALC\u003c/em\u003e. \u003cem\u003eIND\u003c/em\u003e primarily orchestrates the specialization of the separation layer and lignified layer, working in concert with \u003cem\u003eALC\u003c/em\u003e to complete the formation of the separation layer, whereas loss of \u003cem\u003eALC\u003c/em\u003e typically results in dehiscence defects. In contrast, the MADS-box gene \u003cem\u003eFUL\u003c/em\u003e plays a dominant role in valve growth and development, restricting differentiation of the dehiscence zone by antagonizing the \u003cem\u003eSHP1/2\u0026ndash;IND/ALC\u003c/em\u003e pathway. Through the activation by \u003cem\u003eSHP1/2\u003c/em\u003e and the antagonistic action of \u003cem\u003eFUL\u003c/em\u003e, this regulatory network collectively establishes the spatial boundary between the valve and valve margin, thereby enabling controlled dehiscence of mature fruits along a predetermined interface.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study reports the first high-quality, chromosome-level reference genome for \u003cem\u003eS. lanceolata\u003c/em\u003e, filling a critical gap in the genomics of the \u003cem\u003eSterculia\u003c/em\u003e genus within the Malvaceae family. This achievement not only establishes a solid genetic foundation for dissecting the species' unique economic and medicinal traits but also provides a new and crucial phylogenetic node for resolving the complex evolutionary history of the entire Malvaceae family. The assembled genome exhibits excellent continuity (Contig N50\u0026thinsp;=\u0026thinsp;29.3 Mb) and high completeness (BUSCO\u0026thinsp;=\u0026thinsp;98.7%), with a quality sufficient to support sophisticated comparative genomics and functional gene discovery. Furthermore, the genome\u0026rsquo;s low heterozygosity offers critical insights into the species' reproductive biology, population history, and provides a crucial baseline for future conservation genetics. This research marks a pivotal transition for the study of the \u003cem\u003eSterculia\u003c/em\u003e genus, advancing it from traditional morphology and limited transcriptomics into the whole-genome era.\u003c/p\u003e\u003cp\u003eThe whole-genome duplication (WGD) events revealed in our study are a core driving force in the evolution of \u003cem\u003eS. lanceolata\u003c/em\u003e and the entire Malvaceae family. Through Ks distribution analysis, we clearly identified two pivotal polyploidization events: an ancient WGD (Ks\u0026thinsp;\u0026asymp;\u0026thinsp;1.6) shared among Malvaceae species and a more recent, lineage-specific WGD (Ks\u0026thinsp;\u0026asymp;\u0026thinsp;0.3) within the \u003cem\u003eS. lanceolata\u003c/em\u003e lineage. This recent WGD event is key to understanding the unique biological traits of \u003cem\u003eS. lanceolata\u003c/em\u003e. Polyploidization provides abundant raw genetic material, enabling organisms to adapt to environmental changes and evolve novel functions.\u003c/p\u003e\u003cp\u003eCompared to the whole-genome triplication (WGT) experienced by durian (\u003cem\u003eDurio zibethinus\u003c/em\u003e) (Teh et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and the pentaploidy (WGM) event in the cotton lineage (Wendel and Cronn \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), the WGD in \u003cem\u003eS. lanceolata\u003c/em\u003e demonstrates the diversity and complexity of polyploidization history within Malvaceae. Following a WGD, the genome typically undergoes drastic rearrangement and a process of diploidization. Our karyotype analysis reconstructed the evolutionary trajectory of \u003cem\u003eS. lanceolata\u003c/em\u003e from a putative ancestral Malvaceae karyotype of n\u0026thinsp;=\u0026thinsp;11. This pathway involved a WGD event (theoretically forming n\u0026thinsp;=\u0026thinsp;22), followed by a series of complex chromosomal rearrangements including reciprocal translocations (RTA), fissions, and losses, which ultimately stabilized to form its characteristic n\u0026thinsp;=\u0026thinsp;20 (2n\u0026thinsp;=\u0026thinsp;40) karyotype. This model not only perfectly explains the origin of its modern chromosome number but also vividly illustrates the universal mechanisms of dynamic genome evolution post-polyploidization (Soltis et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOne of the primary breakthroughs of this study is the direct link established between a macro-evolutionary WGD event and the species' key economic traits. We innovatively identified the set of genes that originated from the recent WGD and were subsequently retained, then performed a functional enrichment analysis on this specific gene set. The analysis revealed significant enrichment in the categories of 'seed development' and 'starch metabolic process.'\u003c/p\u003e\u003cp\u003eThis finding provides strong evidence that gene retention post-WGD was non-random, instead favoring the selective expansion and preservation of genes related to nutrient accumulation in seeds. We then corroborated these genetic findings with metabolomic data, which demonstrated that as seeds mature, key mineral elements and total starch content increase significantly, while flavonoid compounds associated with astringency decrease sharply. This forms a complete evidentiary chain\u0026mdash;from a genomic evolutionary event to functional gene set expansion, and ultimately to the formation of a desirable economic trait\u0026mdash;profoundly uncovering the evolutionary underpinnings of the high nutritional value of \u003cem\u003eS. lanceolata\u003c/em\u003e seeds. This research paradigm, which tightly integrates WGD with economic traits, remains relatively rare in plant genomics and is analogous to research on the expansion of starch-related genes in potato (Van Harsselaar et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSimilarly, the WGD event provides clues for elucidating another key biological trait in \u003cem\u003eS. lanceolata\u003c/em\u003e: fruit dehiscence. The ability of a fruit to dehisce at the appropriate time is crucial for plant seed dispersal and propagation. Our study revealed that the core gene families regulating fruit dehiscence, including SHP1/2, FUL, IND, and ALC, all exhibit significant copy number expansion in the \u003cem\u003eS. lanceolata\u003c/em\u003e genome. It is plausible that this WGD-driven increase in gene dosage led to a more complex and finely-tuned regulatory network. For instance, the expanded gene copies, potentially through subfunctionalization or neofunctionalization, may have enabled more precise control over the dehiscence zone and valve margins, thereby ensuring that the follicle dehisces efficiently and accurately along the ventral suture upon maturation. This discovery not only clarifies the developmental mechanisms in \u003cem\u003eS. lanceolata\u003c/em\u003e but also offers potential homologous gene targets for the genetic improvement of other crops, such as preventing yield loss from pod shattering in rapeseed (\u003cem\u003eBrassica napus\u003c/em\u003e) (Raman et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study reports the first successful construction of a high-quality, chromosome-level reference genome for \u003cem\u003eS. lanceolata\u003c/em\u003e, revealing its genomic structure, gene composition, and evolutionary features. Through in-depth comparative genomic analysis, we elucidated that \u003cem\u003eS. lanceolata\u003c/em\u003e underwent an independent, recent whole-genome duplication (WGD) event and have reconstructed in detail its evolutionary trajectory, which led to the formation of its current n\u0026thinsp;=\u0026thinsp;20 karyotype via large-scale chromosomal rearrangements post-WGD.\u003c/p\u003e\u003cp\u003eCrucially, this study establishes a direct link between this macro-scale genomic evolutionary event and the species' key agronomic traits. We demonstrate that the WGD-driven expansion of gene families directly resulted in the large-scale duplication and retention of key genes associated with 'seed development,' 'starch metabolism,' and 'pod dehiscence.' These changes at the genetic level are ultimately manifested at the phenotypic level as the rich accumulation of seed nutrients and a precise fruit dehiscence mechanism.\u003c/p\u003e\u003cp\u003eIn conclusion, this research not only provides an invaluable resource for evolutionary and comparative genomics of the Malvaceae family but also establishes a solid molecular foundation for the genetic improvement, germplasm conservation, and exploitation of the medicinal value of \u003cem\u003eS. lanceolata\u003c/em\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of Interest\u003c/h2\u003e\u003cp\u003eThe authors declare they have no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study was supported by the Startup Funding for the Double First-Class Discipline of Crop Science at Hainan University (RZ2100003362).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe authors confirm their contributions to the manuscript as follows: Conceptualization and project supervision: Wang W, Chen F, R. Henry; Plant material collection: Hu Y, Guo G, Zhang Y; Data analysis: Hu Y, Zhang Y, Guo G, Zhang H, Zhang J, Shao B, Xue J; Draft manuscript preparation: Hu Y, Zhang J, Yang K. All authors reviewed the results and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe gratefully acknowledge the valuable comments and suggestions provided by the editor and anonymous reviewers.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe raw genomic sequencing data and transcriptomic reads have been deposited in the National Genomics Data Center under accession number PRJCA028606.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGuymer GP (1988) A taxonomic revision of Brachychiton (Sterculiaceae). Aust Syst Bot 1(3):199\u0026ndash;323. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SB9880199\u003c/span\u003e\u003cspan address=\"10.1071/SB9880199\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrasad N, Thombare N, Sharma SC, Kumar S (2022) Production, processing, properties and applications of karaya (Sterculia species) gum. Ind Crops Prod 177:114467. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.indcrop.2021.114467\u003c/span\u003e\u003cspan address=\"10.1016/j.indcrop.2021.114467\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBawri A, Baro D, Sarma K, Teron R, Tanti B (2024) Sterculia lanceolata Cav. var. lanceolata (Malvaceae): an addition to flora of India. Vegetos 37(6):2642\u0026ndash;2646. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s42535-023-00745-8\u003c/span\u003e\u003cspan address=\"10.1007/s42535-023-00745-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang L, Yan YC, Hao YM, Zhuo XX, Duan HT, Zhang Q et al (2024) A Review on the Phytochemistry and Pharmacology of the Genus Sterculia. Chem Biodivers 21(8):e202400963. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1002/cbdv.202400963\u003c/span\u003e\u003cspan address=\"10.1002/cbdv.202400963\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEum SM, Kim S-Y, Hong JS, Roy NS, Choi S, Paik J et al (2019) Transcriptome analysis and development of SSR markers of ethnobotanical plant Sterculia lanceolata. Tree Genet Genomes 15(3):37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11295-019-1348-3\u003c/span\u003e\u003cspan address=\"10.1007/s11295-019-1348-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGanie SH, Upadhyay P, Das S, Sharma MP (2015) Authentication of medicinal plants by DNA markers. Plant gene 4:83\u0026ndash;99. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.plgene.2015.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.plgene.2015.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCvetković T, Areces-Berazain F, Hinsinger DD, Thomas DC, Wieringa JJ, Ganesan SK et al (2021) Phylogenomics resolves deep subfamilial relationships in Malvaceae sl. G3(7):jkab136. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/g3journal/jkab136\u003c/span\u003e\u003cspan address=\"10.1093/g3journal/jkab136\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. \u003cem\u003e11\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePab\u0026oacute;n-Mora N, Wong GK-S, Ambrose BA (2014) Evolution of fruit development genes in flowering plants. Front Plant Sci 5:300. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.3389/fpls.2014.00300\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2014.00300\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEom SH, Na J-K (2019) Leaf transcriptome data of two tropical medicinal plants: Sterculia lanceolata and Clausena excavata. Data brief 25:104297. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.dib.2019.104297\u003c/span\u003e\u003cspan address=\"10.1016/j.dib.2019.104297\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWenger AM, Peluso P, Rowell WJ, Chang P-C, Hall RJ, Concepcion GT et al (2019) Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat Biotechnol 37(10):1155\u0026ndash;1162. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41587-019-0217-9\u003c/span\u003e\u003cspan address=\"10.1038/s41587-019-0217-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuail MA, Kozarewa I, Smith F, Scally A, Stephens PJ, Durbin R et al (2008) A large genome center's improvements to the Illumina sequencing system. Nat Methods 5(12):1005\u0026ndash;1010. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/nmeth.1270\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.1270\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen S, Zhou Y, Chen Y, Gu J (2018) fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34:i884\u0026ndash;i890. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/bty560\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/bty560\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKokot M, Długosz M, Deorowicz S (2017) KMC 3: counting and manipulating k-mer statistics. Bioinformatics 33(17):2759\u0026ndash;2761. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/bioinformatics/btx304\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btx304\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRanallo-Benavidez TR, Jaron KS, Schatz MC (2020) GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nat Commun 11(1):1432. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41467-020-14998-3\u003c/span\u003e\u003cspan address=\"10.1038/s41467-020-14998-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078\u0026ndash;2079. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/bioinformatics/btp352\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btp352\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng H, Concepcion GT, Feng X, Zhang H, Li H (2021) Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat Methods 18(2):170\u0026ndash;175. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41592-020-01056-5\u003c/span\u003e\u003cspan address=\"10.1038/s41592-020-01056-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Zhang S, Zhao Q, Ming R, Tang H (2019) Assembly of allele-aware, chromosomal-scale autopolyploid genomes based on Hi-C data. Nat plants 5(8):833\u0026ndash;845. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41477-019-0487-8\u003c/span\u003e\u003cspan address=\"10.1038/s41477-019-0487-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDudchenko O, Batra SS, Omer AD, Nyquist SK, Hoeger M, Durand NC et al (2017) De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356(6333):92\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1126/science.aal3327\u003c/span\u003e\u003cspan address=\"10.1126/science.aal3327\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDurand NC, Robinson JT, Shamim MS, Machol I, Mesirov JP, Lander ES et al (2016) Juicebox provides a visualization system for Hi-C contact maps with unlimited zoom. Cell Syst 3(1):99\u0026ndash;101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.cels.2015.07.012\u003c/span\u003e\u003cspan address=\"10.1016/j.cels.2015.07.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeppey M, Manni M, Zdobnov EM (2019) BUSCO: assessing genome assembly and annotation completeness. Gene prediction: methods and protocols. Springer, pp 227\u0026ndash;245. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btv351\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btv351\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFlynn JM, Hubley R, Goubert C, Rosen J, Clark AG, Feschotte C et al (2020) RepeatModeler2 for automated genomic discovery of transposable element families. \u003cem\u003eProceedings of the National Academy of Sciences, 117\u003c/em\u003e(17), 9451\u0026ndash;9457. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1073/pnas.1921046117\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1921046117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen N (2004) Using Repeat Masker to identify repetitive elements in genomic sequences. \u003cem\u003eCurrent protocols in bioinformatics, 5\u003c/em\u003e(1), 4.10. 11-14.10. 14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1002/0471250953.bi0410s25\u003c/span\u003e\u003cspan address=\"10.1002/0471250953.bi0410s25\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim D, Paggi JM, Park C, Bennett C, Salzberg SL (2019) Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol 37(8):907\u0026ndash;915. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41587-019-0201-4\u003c/span\u003e\u003cspan address=\"10.1038/s41587-019-0201-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGabriel L, Brůna T, Hoff KJ, Ebel M, Lomsadze A, Borodovsky M et al (2024) BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS, and TSEBRA. Genome Res 34(5):769\u0026ndash;777. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1101/gr.278090.123\u003c/span\u003e\u003cspan address=\"10.1101/gr.278090.123\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHern\u0026aacute;ndez-Plaza A, Szklarczyk D, Botas J, Cantalapiedra CP, Giner-Lamia J, Mende DR et al (2023) eggNOG 6.0: enabling comparative genomics across 12 535 organisms. Nucleic Acids Res 51(D1):D389\u0026ndash;D394. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkac1022\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkac1022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJin J-J, Yu W-B, Yang J-B, Song Y, DePamphilis CW, Yi T-S et al (2020) GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes. Genome Biol 21(1):241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1186/s13059-020-02154-5\u003c/span\u003e\u003cspan address=\"10.1186/s13059-020-02154-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou C, Brown M, Blaxter M, Consortium DT, o. LP, McCarthy SA, Durbin R (2025) Oatk: a de novo assembly tool for complex plant organelle genomes. Genome Biol 26(1):235. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1186/s13059-025-03676-6\u003c/span\u003e\u003cspan address=\"10.1186/s13059-025-03676-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLohse M, Drechsel O, Bock R (2007) OrganellarGenomeDRAW (OGDRAW): a tool for the easy generation of high-quality custom graphical maps of plastid and mitochondrial genomes. Curr Genet 52(5):267\u0026ndash;274. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1007/s00294-007-0161-y\u003c/span\u003e\u003cspan address=\"10.1007/s00294-007-0161-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Tang H, DeBarry JD, Tan X, Li J, Wang X et al (2012) MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res 40(7):e49\u0026ndash;e49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkr1293\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkr1293\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang H, Krishnakumar V, Zeng X, Xu Z, Taranto A, Lomas JS et al (2024) JCVI: A versatile toolkit for comparative genomics analysis. Imeta 3(4):e211. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1002/imt2.211\u003c/span\u003e\u003cspan address=\"10.1002/imt2.211\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchranz ME, Mohammadin S, Edger PP (2012) Ancient whole genome duplications, novelty and diversification: the WGD Radiation Lag-Time Model. Curr Opin Plant Biol 15(2):147\u0026ndash;153. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.pbi.2012.03.011\u003c/span\u003e\u003cspan address=\"10.1016/j.pbi.2012.03.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun P, Jiao B, Yang Y, Shan L, Li T, Li X et al (2022) WGDI: a user-friendly toolkit for evolutionary analyses of whole-genome duplications and ancestral karyotypes. Mol Plant 15(12):1841\u0026ndash;1851. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.molp.2022.10.018\u003c/span\u003e\u003cspan address=\"10.1016/j.molp.2022.10.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAltschul SF, Madden TL, Sch\u0026auml;ffer AA, Zhang J, Zhang Z, Miller W et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389\u0026ndash;3402. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/25.17.3389\u003c/span\u003e\u003cspan address=\"10.1093/nar/25.17.3389\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLavigne R, Seto D, Mahadevan P, Ackermann H-W, Kropinski AM (2008) Unifying classical and molecular taxonomic classification: analysis of the Podoviridae using BLASTP-based tools. Res Microbiol 159(5):406\u0026ndash;414. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.resmic.2008.03.005\u003c/span\u003e\u003cspan address=\"10.1016/j.resmic.2008.03.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTian T, Liu Y, Yan H, You Q, Yi X, Du Z et al (2017) agriGO v2. 0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res 45(W1):W122\u0026ndash;W129. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkx382\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkx382\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDai W, He S, Luo Y, Zhao C, Yang Z, Zhang J et al (2025) TropiCODB: A multi-omics resource for supporting biodesign in tropical crops. BioDesign Res 7(1):100003. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bidere.2025.100003\u003c/span\u003e\u003cspan address=\"10.1016/j.bidere.2025.100003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Bel M, Silvestri F, Weitz EM, Kreft L, Botzki A, Coppens F et al (2022) PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants. Nucleic Acids Res 50(D1):D1468\u0026ndash;D1474. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkab1024\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkab1024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEmms DM, Kelly S (2019) OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 20(1):238. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1186/s13059-019-1832-y\u003c/span\u003e\u003cspan address=\"10.1186/s13059-019-1832-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCapella-Guti\u0026eacute;rrez S, Silla-Mart\u0026iacute;nez JM, Gabald\u0026oacute;n T (2009) trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25(15):1972\u0026ndash;1973. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/bioinformatics/btp348\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btp348\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30(9):1312\u0026ndash;1313. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/bioinformatics/btu033\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btu033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePuttick MN (2019) MCMCtreeR: functions to prepare MCMCtree analyses and visualize posterior ages on trees. Bioinformatics 35(24):5321\u0026ndash;5322. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/bioinformatics/btz554\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btz554\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMinh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, Von Haeseler A et al (2020) IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 37(5):1530\u0026ndash;1534. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/msaa015\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msaa015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer EL et al (2021) Pfam: The protein families database in 2021. Nucleic Acids Res 49(D1):D412\u0026ndash;D419. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkaa913\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkaa913\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFinn RD, Clements J, Eddy SR (2011) HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 39(suppl2):W29\u0026ndash;W37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkr367\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkr367\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKatoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30(4):772\u0026ndash;780. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/molbev/mst010\u003c/span\u003e\u003cspan address=\"10.1093/molbev/mst010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrice MN, Dehal PS, Arkin AP (2010) FastTree 2\u0026ndash;approximately maximum-likelihood trees for large alignments. PLoS ONE 5(3):e9490. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1371/journal.pone.0009490\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0009490\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLetunic I, Bork P (2024) Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res 52(W1):W78\u0026ndash;W82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/nar/gkae268\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkae268\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHe Z, Feng X, Chen Q, Li L, Li S, Han K et al (2022) Evolution of coastal forests based on a full set of mangrove genomes. Nat Ecol Evol 6(6):738\u0026ndash;749. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41559-022-01744-9\u003c/span\u003e\u003cspan address=\"10.1038/s41559-022-01744-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDong Z, Jin S, Fan R, Sun P, Shao L, Zhao T et al (2025) High-quality genome of Firmiana hainanensis provides insights into the evolution of Malvaceae subfamilies and the mechanism of their wood density formation. J Genet Genomics 52(6):812\u0026ndash;825. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.jgg.2024.12.009\u003c/span\u003e\u003cspan address=\"10.1016/j.jgg.2024.12.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCipollini ML, Levey DJ (1997) Secondary metabolites of fleshy vertebrate-dispersed fruits: adaptive hypotheses and implications for seed dispersal. Am Nat 150(3):346\u0026ndash;372. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1086/286069\u003c/span\u003e\u003cspan address=\"10.1086/286069\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTeh BT, Lim K, Yong CH, Ng CCY, Rao SR, Rajasegaran V et al (2017) The draft genome of tropical fruit durian (Durio zibethinus). Nat Genet 49(11):1633\u0026ndash;1641. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/ng.3972\u003c/span\u003e\u003cspan address=\"10.1038/ng.3972\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWendel JF, Cronn RC (2002) Polyploidy and the evolutionary history of cotton. Adv Agron 87:139\u0026ndash;186\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSoltis PS, Marchant DB, Van de Peer Y, Soltis DE (2015) Polyploidy and genome evolution in plants. Curr Opin Genet Dev 35:119\u0026ndash;125. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.gde.2015.11.003\u003c/span\u003e\u003cspan address=\"10.1016/j.gde.2015.11.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Harsselaar JK, Lorenz J, Senning M, Sonnewald U, Sonnewald S (2017) Genome-wide analysis of starch metabolism genes in potato (Solanum tuberosum L). BMC Genomics 18(1):37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1186/s12864-016-3381-z\u003c/span\u003e\u003cspan address=\"10.1186/s12864-016-3381-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRaman H, Raman R, Kilian A, Detering F, Carling J, Coombes N et al (2014) Genome-wide delineation of natural variation for pod shatter resistance in Brassica napus. PLoS ONE 9(7):e101673. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1371/journal.pone.0101673\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0101673\" 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":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":"functional-and-integrative-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fige","sideBox":"Learn more about [Functional \u0026 Integrative Genomics](http://link.springer.com/journal/10142)","snPcode":"10142","submissionUrl":"https://submission.nature.com/new-submission/10142/3","title":"Functional \u0026 Integrative Genomics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7559915/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7559915/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eSterculia lanceolata\u003c/em\u003e, a tree species of the Malvaceae family with notable ornamental and medicinal value, has long been constrained in genetic research and breeding applications due to the lack of genomic resources. In this study, we report for the first time a high-quality, chromosome-level genome assembly of this species, aimed at elucidating its evolutionary history and the genetic basis of key traits. We constructed the genome using PacBio HiFi sequencing and further assembled it into 20 chromosomes with the aid of Hi-C technology, yielding a final genome assembly size of 610.4 Mb with a contig N50 of 29.3 Mb and a BUSCO completeness of 98.7%. The assembly includes the identification of 20 chromosomes and the annotation of 35,873 protein-coding genes, with an annotation rate of 96.4%. By integrating genomic data from other Malvaceae species, we analyzed the karyotype evolution of \u003cem\u003eS. lanceolata\u003c/em\u003e and revealed the basal ploidy level of the family. Comparative genomic analyses uncovered significant syntenic relationships and whole-genome duplication (WGD) events among Malvaceae species, thereby clarifying the trajectory of karyotype evolution. Moreover, the study identified key regulatory gene families associated with fruit dehiscence (homologs of \u003cem\u003eSHP1/2\u003c/em\u003e, \u003cem\u003eFUL\u003c/em\u003e, \u003cem\u003eIND\u003c/em\u003e, and \u003cem\u003eALC\u003c/em\u003e) that have undergone extensive expansion in \u003cem\u003eS. lanceolata\u003c/em\u003e as a consequence of ancient polyploidy events. The reference genome provided in this study not only serves as a critical resource for evolutionary research in Malvaceae but also establishes a foundational framework for molecular breeding, genetic improvement, and conservation of \u003cem\u003eS. lanceolata\u003c/em\u003e and related species.\u003c/p\u003e","manuscriptTitle":"The Reference Genome Sequence of the Scarlet Follicle, Sterculia lanceolata, reveals a paleo-polyploidization and its impact on fruit quality and fruit dehiscence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 20:28:08","doi":"10.21203/rs.3.rs-7559915/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-28T12:32:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T12:44:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40639582608866816035504866385103662486","date":"2025-10-27T18:05:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122365371629800883546112030201607841744","date":"2025-10-22T13:11:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T17:14:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-18T17:07:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T10:48:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Functional \u0026 Integrative Genomics","date":"2025-09-08T04:34:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"functional-and-integrative-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fige","sideBox":"Learn more about [Functional \u0026 Integrative Genomics](http://link.springer.com/journal/10142)","snPcode":"10142","submissionUrl":"https://submission.nature.com/new-submission/10142/3","title":"Functional \u0026 Integrative Genomics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c26b2dfb-500f-4e13-b3f3-fa071eb2b774","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:04:51+00:00","versionOfRecord":{"articleIdentity":"rs-7559915","link":"https://doi.org/10.1007/s10142-026-01829-9","journal":{"identity":"functional-and-integrative-genomics","isVorOnly":false,"title":"Functional \u0026 Integrative Genomics"},"publishedOn":"2026-02-16 15:58:32","publishedOnDateReadable":"February 16th, 2026"},"versionCreatedAt":"2025-09-30 20:28:08","video":"","vorDoi":"10.1007/s10142-026-01829-9","vorDoiUrl":"https://doi.org/10.1007/s10142-026-01829-9","workflowStages":[]},"version":"v1","identity":"rs-7559915","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7559915","identity":"rs-7559915","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}