Abstract
The rhizome of Drynaria roosii (Drynariae Rhizoma) holds significant medicinal and economic value. It is traditionally used to promote blood circulation, remove blood stasis, and strengthen the kidneys and bones. However, the distribution and biosynthetic pathways of medicinal compounds in different tissues of D. roosii remain unclear. In this study, non-targeted metabolomics and transcriptomics analyses were conducted on leaves, stems, and tubers of D. roosii, and a high-quality reference transcriptome was obtained using Pacific BioSciences (PacBio) single-molecule real-time (SMRT) sequencing. A total of 1,151 metabolites were identified, including 203 flavonoid-related compounds. Among them, 31 flavonoids-such as quercetin 7-glucoside, tamarixetin, and naringenin 7-rutinoside—were found to be relatively abundant in the tuber. PacBio SMRT sequencing yielded 151,192 consensus reads. A total of 5,581 intron retention (IR) events were identified through alternative splicing analysis, and 56,773 non-redundant transcripts were obtained after transcript redundancy removal. Comparative transcriptome analysis revealed that metabolic pathways such as steroid biosynthesis (ko00100) and phenylpropanoid biosynthesis were enriched in the tuber and leaf. Correlation network analysis identified key genes, including Glycosyltransferase, 4CL, DELLA and others, to be significantly associated with the biosynthesis of naringin 6’'-rhamnoside and naringenin 7-rutinoside. This study provides a foundation for the resource utilization, medicinal compound biosynthesis, and molecular breeding of D. roosii.
Data availability
The raw bam file from PacBio SMRT sequencing has been deposited in the NCBI SRA database (BioProject acc. PRJNA1291835). The raw reads generated from Illumina sequencing have been deposited in the NCBI SRA database (BioProject acc. PRJNA1291623).
References
Chang, H.-C. et al. In vitro culture of Drynaria fortunei, a fern species source of Chinese medicine “Gu-Sui-Bu”. In Vitro Cellular Dev. Biol. Plant 43, 133–139 (2007).
Chang, N. et al. Epiphytic patterns impacting metabolite diversity of Drynaria roosii rhizomes based on widely targeted metabolomics. Metabolites 14, 409 (2024).
Sun, M., Li, J., Li, D. & Shi, L. Complete chloroplast genome sequence of the medical fern Drynaria roosii and its phylogenetic analysis. Mitochondrial Dna Part B 2, 7–8 (2017).
Han, F. et al. Action mechanism and clinical research progress of gusuibu (Rhizoma Drynariae) fighting against osteoporosis. Acta Chin. Med. 40, 812–819. https://doi.org/10.16368/j.issn.1674-8999.2025.04.131 (2025).
Yu, X. et al. Research progress on the clinical efficacy mechanism of total flavonoids of Rhizoma drynariae in the treatment of osteoporotic fracture. Chin. J. Osteoporosis 31, 149–156 (2025).
Dong, Y. et al. Metabolite profiling of Drynariae Rhizoma using 1H NMR and HPLC coupled with multivariate statistical analysis. J. Nat. Med. 77, 839–857 (2023).
Chen, R., Qi, Q.-L., Wang, M.-T. & Li, Q.-Y. Therapeutic potential of naringin: an overview. Pharm. Biol. 54, 3203–3210 (2016).
Song, S.-H. et al. Effects of total flavonoids from Drynariae Rhizoma prevent bone loss in vivo and in vitro. Bone Rep. 5, 262–273 (2016).
Song, S. et al. Total flavonoids of Drynariae Rhizoma prevent bone loss induced by Hindlimb unloading in rats. Molecules 22, 1033 (2017).
Zhang, Y. et al 2017. Total flavonoids from Rhizoma Drynariae (Gusuibu) for treating osteoporotic fractures: implication in clinical practice. Drug Design, Development and Therapy, 1881–1890 (2017).
Li, W. et al. Effects of total flavonoids of Rhizoma Drynariae on biochemical indicators of bone metabolism: a systematic review and meta-analysis. Front. Pharmacol. 15, 1443235 (2024).
Zhang, F. et al. Total flavonoids of Drynariae rhizoma improve glucocorticoid-induced osteoporosis of rats: UHPLC-MS-based qualitative analysis, network pharmacology strategy and pharmacodynamic validation. Front. Endocrinol. 13, 920931 (2022).
Qiu, D., Luo, Y., Li, C., Du, C. & Yuan, X. Comparative analysis of broad-targeted metabolomics between greenhouse cultivated and wild collected Drynaria fortune. Guangdong Agric. Sci. 51, 30–43. https://doi.org/10.16768/j.issn.1004-874X.2024.05.003 (2024).
Rhoads, A. & Au, K. F. PacBio sequencing and its applications. Genom. Proteom. Bioinform. 13, 278–289 (2015).
Liao, T. et al. Full-length transcriptome characterization of Platycladus orientalis based on the PacBio platform. Front. Genet. 15, 1345039 (2024).
Li, Z. et al. Comprehensive analysis of Metacrinus rotundus full length transcriptome. Sci. Rep. 15, 6723 (2025).
Sun, M.-Y. et al. Full-length transcriptome sequencing and modular organization analysis of the naringin/neoeriocitrin-related gene expression pattern in Drynaria roosii. Plant Cell Physiol. 59, 1398–1414 (2018).
Mirdita, M., Steinegger, M., Breitwieser, F., Söding, J. & Levy Karin, E. Fast and sensitive taxonomic assignment to metagenomic contigs. Bioinformatics 37, 3029–3031 (2021).
Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).
Buchfink, B., Reuter, K. & Drost, H.-G. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat. Methods 18, 366–368 (2021).
Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).
Jensen, L. J. et al. eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic Acids Res. 36, D250–D254 (2007).
Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890. https://doi.org/10.1093/bioinformatics/bty560 (2018).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 1–16 (2011).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21 (2014).
Wu, T. et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The innovation 2 (2021).
Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008).
Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods 25, 402–408 (2001).
Sun, M., Li, J., Li, D. & Shi, L. Complete chloroplast genome sequence of the medical fern Drynaria roosii and its phylogenetic analysis. Mitochondrial DNA Part B https://doi.org/10.1080/23802359.2016.1275835 (2017).
Dong, N. Q. & Lin, H. X. Contribution of phenylpropanoid metabolism to plant development and plant–environment interactions. J. Integr. Plant Biol. 63, 180–209 (2021).
Tanaka, Y., Sasaki, N. & Ohmiya, A. Biosynthesis of plant pigments: anthocyanins, betalains and carotenoids. Plant J. 54, 733–749 (2008).
Sasaki, N. & Nakayama, T. Achievements and perspectives in biochemistry concerning anthocyanin modification for blue flower coloration. Plant Cell Physiol. 56, 28–40 (2015).
Xie, N. et al. Integrated transcriptomic and WGCNA analyses reveal candidate genes regulating mainly flavonoid biosynthesis in Litsea coreana var. sinensis. BMC Plant Biol. 24, 231 (2024).
Jiang, W., Xia, Y., Su, X. & Pang, Y. ARF2 positively regulates flavonols and proanthocyanidins biosynthesis in Arabidopsis thaliana. Planta 256, 44 (2022).
Funding
This research was funded by Guizhou Provincial Science and Technology Plan Project (QKH Support [2023] General 003; Talent Base Project of Guizhou Provincial Committee Organization Department (RCJD2020-21); Guangzhou Science and Technology Plan Project (2023B03J1292); Bijie Science and Technology Innovation Platform and Talent Team (BKH [2023] No. 66); Scientific Research Team Project of Bijie Medical College (BJYZXT202401).
Author information
Authors and Affiliations
Contributions
Conceptualization, Z.X. and C.X.; methodology, Z.X. and C.X..; software, Z.X..; validation, W.Y, W.C. and Z.T.; formal analysis, Z.X. and C.X.; investigation, Z.X. and C.X.; resources, W.Y, L.M., W.C. and Z.T.; data curation, Z.X.; writing—original draft preparation, Z.X. and C.X.; writing—review and editing, Z.X. and C.X..; visualization, Z.X.; supervision, Z.X.; project administration, Z.X.; funding acquisition, Z.X. All authors have read and agreed to the published version of the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Zhang, X., Chen, X., Wang, Y. et al. Integrative transcriptomic and metabolomic analysis of Drynaria roosii reveals genes involved in the biosynthesis of medicinal compounds. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39037-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-39037-x