From folklore to explore: integrating genomic and multiomics data for Clinacanthus nutans provides insights into the evolution and organ-specific therapeutic basis

Abstract

Clinacanthus nutans is a traditional medicinal plant widely used in Southeast Asia for treating inflammation, viral infections, and cancer. However, its molecular basis remains poorly understood. In this study, the first chromosome-scale genome of C. nutans (731.61 Mbp) was assembled, with 93.76% anchored to 18 pseudochromosomes. Repetitive elements constituted 69.05% of the genome, predominantly long terminal repeat retrotransposons. Phylogenomic and synonymous substitution rate analyses revealed a Lamiales-wide whole-genome duplication event, followed by extensive chromosomal rearrange- ments. Gene family expansion analysis showed that segmental and dispersed duplications were the primary drivers of enzyme-coding genes (EGs) expansion involved in the flavonoid and triterpenoid pathways. Integrated transcriptomic and metabolomic analyses across five organs revealed distinct organ-specific expression and metabolite profiles. Genes exhibited pronounced differential expression between leaves and roots, with enrichment in flavonoid and triterpenoid biosynthetic pathways, highlighting functional divergence and metabolic specialization. Flavonoids were enriched in aerial tissues, whereas triterpenoids accumulated in roots. Weighted gene co-expression network analysis identified key EGs (e.g. CHS, CHI, OSC) and core transcription factors (e.g. MYB, bHLH, WRKY) potentially involved in organ-specific metabolic regulation. These findings suggest a coordinated transcriptional-metabolic regulatory framework underlying the specialized functions of different tissues. This work provides valuable genomic resources and mechanistic insights into the biosynthesis and regulation of bioactive compounds in C. nutans , thereby facilitating future research and molecular breeding of this important ethnomedicinal plant.

Acknowledgments

We would like to express our sincere gratitude to the reviewers for their valuable comments and suggestions, which greatly improved the quality of our manuscript. We also thank Chief Physician Zhuhou Huang and Dr. Kangzhuo Ye for their assistance in sample collection. In addition, we are grateful to various open educational platforms and bioinformatics communities for providing high-quality tutorials and datasets that supported the development of data-analysis skills essential to this study. This work was supported by the National Key R&D Program of China (2023YFA0913500) and the National Natural Science Foundation of China (32270366 and 32460062).

Author contributions

Chang An: resources, data curation, formal analysis, conceptualization, writing-original draft. Bingrui Wang: supervision. Denglin Li: software, Junzhang Li: software, formal analysis. Yongbin Lu: software, formal analysis. Yixin Yao: supervision. Yanxiang Lin: supervision. Lin Lu: data curation. Yan Cheng: conceptualization, supervision. Chongrong Ke: supervision. Zongshen Zhang: supervision. Ping Zheng: data curation, supervision. Yuan Qin: funding acquisition, conceptualization, project administration, writing-review & editing.

Data availability

The genome sequences and raw RNA-seq data described in this study have been deposited in CNGBdb under the accession number CNP0008755. The metabolomic datasets and related project reports are available from the corresponding author upon reasonable request.

Conflicts of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary material

Supplementary material is available at Horticulture Research online.

References

[1] Miranda JJM . Medicinal plants and their traditional uses in different locations. In: Farid A (ed.), Phytomedicine. Amsterdam, The Netherlands: Elsevier, 2021, 207-23.

[2] Zheng H, Fu X, Shao J et al. Transcriptional regulatory network of high-value active ingredients in medicinal plants. Trends Plant Sci . 2023; 28: 429-46.

[3] Hostettmann K, Marston A . Twenty years of research into medicinal plants: results and perspectives. Phytochem Rev. 2002; 1: 275-85.

[4] Yang L, Yang Y, Huang L et al. From single-to multi-omics: future research trends in medicinal plants. Brief Bioinform. 2023; 24: bbac485.

[5] Guo L, Yao H, Chen W et al. Natural products of medicinal plants: biosynthesis and bioengineering in post-genomic era. Hortic Res . 2022; 9: uhac223.

[6] Zhang Y, Shen Q, Leng L et al. Incipient diploidization of the medicinal plant Perilla within 10,000 years. Nat Commun. 2021; 12: 5508.

[7] Nie B, Chen X, Hou Z et al. Haplotype-phased genome unveils the butylphthalide biosynthesis and homoploid hybrid origin of Ligusticum chuanxiong . Sci Adv. 2024; 10: eadj6547.

[8] Kim NH, Jayakodi M, Lee SC et al. Genome and evolution of the shade-requiring medicinal herb Panax ginseng. Plant Biotechnol J. 2018; 16: 1904-17.

[9] Meng F, Tang Q, Chu T et al. TCMPG: an integrative database for traditional Chinese medicine plant genomes. Hortic Res. 2022; 9: uhac060.

[10] Cheng L, Wang Z, Zhu Q et al. A long road ahead to reliable and complete medicinal plant genomes. Nat Commun. 2025; 16: 2150.

[11] Al-Shami AMA, Khalid KA, Hadi H . Pharmacological effects of Clinacanthus nutans Lindau and its potential cosmeceutical values: A comprehensive review . Journal of Pharmaceutical Sciences and Research. 2020; 12: 10-9.

[12] Mustapa AN, Martin Á, Mato RB et al. Extraction of phytocompounds from the medicinal plant Clinacanthus nutans Lindau by microwave-assisted extraction and supercritical carbon dioxide extraction . Ind Crop Prod. 2015; 74: 83-94.

[13] An C, Lin L, Kangzhuo Y et al. Comprehensive review on research of Ezuihua (Clinacanthus nutans) and predictive analysis on quality marker (Q-marker) . Chin Arch Tradit Chin Med. 2023; 41: 25-35.

[14] Yun-Jie L , Jia-Yi Z , Xiao-Die Z et al. Integrative multi-omics profiling of geographical and organ-specific variations of bioactive constituents in Andrographis paniculata: UHPLC-QTOF-MS, MALDI-MSI and antioxidant activity. Ind Crop Prod. 2025; 233: 121369.

[15] Chang A, Denghang W, Ningwei L et al. The basic helix-loop-helix (bHLH) gene family in Clinacanthus nutans: insights into tissue-specific expression, stress responses, and methyl jasmonate (MeJA) responsiveness . Medicinal Plant Biology. 2025; 4: e032.

[16] The Angiosperm Phylogeny Group, Chase MW, Christenhusz MJM et al. An update of the angiosperm phylogeny group classification for the orders and families of flowering plants: APG IV. Bot J Linn Soc . 2016; 181: 1-20.

[17] Renne PR, Deino AL, Hilgen FJ et al. Time scales of critical events around the cretaceous-Paleogene boundary, Time scales of critical events around the cretaceous-Paleogene boundary. Science. 2013; 339: 684-7.

[18] Sun Y, Shang L, Zhu QH et al. Twenty years of plant genome sequencing: achievements and challenges. Trends Plant Sci. 2022; 27: 391-401.

[19] Xu W, Zhang L, Cunningham AB et al. Blue genome: chromosome-scale genome reveals the evolutionary and molecular basis of indigo biosynthesis in Strobilanthes cusia . Plant J. 2020; 104: 864-79.

[20] Liang Y, Chen S, Wei K et al. Chromosome level genome assembly of Andrographis paniculata . Front Genet. 2020; 11: 701.

[21] Wang J, Song B, Yang M et al. Deciphering recursive polyploidization in Lamiales and reconstructing their chromosome evolutionary trajectories. Plant Physiol. 2024; 195: 2143-57.

[22] Wendel JF . The wondrous cycles of polyploidy in plants. Am J Bot . 2015; 102: 1753-6.

[23] Anjum N, Dash CK, Sultana SS . Karyological diversity among six medicinally important species of Acanthaceae with three new chromosome counts. Nucleus. 2024; 67: 341-9.

[24] Flagel LE, Wendel JF . Gene duplication and evolutionary novelty in plants. New Phytol. 2009; 183: 557-64.

[25] Rensing SA . Gene duplication as a driver of plant morphogenetic evolution. Curr Opin Plant Biol. 2014; 17: 43-8.

[26] Panchy N, Lehti-Shiu M, Shiu SH . Evolution of gene duplication in plants. Plant Physiol . 2016; 171: 2294-316.

[27] Andersson DI, Jerlström-Hultqvist J, Näsvall J . Evolution of new functions de novo and from preexisting genes. Cold Spring Harb Perspect Biol. 2015; 7: a017996.

[28] Weng JK . The evolutionary paths towards complexity: a metabolic perspective. New Phytol. 2014; 201: 1141-9.

[29] Guo Y, Peng X, Liu F et al. Potential of natural products in inflammation: biological activities, structure-activity relationships, and mechanistic targets. Arch Pharm Res. 2024; 47: 377-409.

[30] Dong H, Qi X . Biosynthesis of triterpenoids in plants: pathways, regulation, and biological functions. Curr Opin Plant Biol. 2025; 85: 102701.

[31] Huong-Giang L , Hao HT , Bo-Rong P et al. Investigating the therapeutic potential of terpene metabolites in hot-natured herbal medicines and their mechanistic impact on circulatory disorders. Phytochem Rev. 2025; 1-48.

[32] Shen N, Wang T, Gan Q et al. Plant flavonoids: classification, distribution, biosynthesis, and antioxidant activity. Food Chem . 2022; 383: 132531.

[33] Tang Q, Li Z, Chen N et al. Natural pigments derived from plants and microorganisms: classification, biosynthesis, and applications. Plant Biotechnol J . 2025; 23: 592-614.

[34] Ferreyra MLF, Serra P, Casati P . Recent advances on the roles of flavonoids as plant protective molecules after UV and high light exposure. Physiol Plant. 2021; 173: 736-49.

[35] Puente-Garza CA, Meza-Miranda C, Ochoa-Martínez D et al. Effect of in vitro drought stress on phenolic acids, flavonols, saponins, and antioxidant activity in Agave salmiana. Plant Physiol Biochem. 2017; 115: 400-7.

[36] Nabavi SM, Samec D, Tomczyk M et al. Flavonoid biosynthetic pathways in plants: versatile targets for metabolic engineering. Biotechnol Adv . 2020; 38: 107316.

[37] Vogt T . Phenylpropanoid biosynthesis. Mol Plant. 2010; 3: 2-20.

[38] Zhao L, Shan CM, Shan TY et al. Comparative transcriptomic analysis reveals the regulatory mechanisms of catechins synthesis in different cultivars of Camellia sinensis . Food Res Int. 2022; 157: 111375.

[39] Dai Y, He M, Liu H et al. The chromosome-scale assembly of the Salvia plebeia genome provides insight into the biosynthesis and regulation of rosmarinic acid . Plant Biotechnol J. 2025; 23: 1507-20.

[40] Martin VJ , Pitera DJ , Withers ST et al. Engineering a mevalonate pathway in Escherichia coli for production of terpenoids . Nat Biotechnol. 2003; 21: 796-802.

[41] Cheng H, Concepcion GT, Feng X et al. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat Methods. 2021; 18: 170-5.

[42] Zeng X, Chen G . Achieving de novo scaffolding of chromosome-level haplotypes using hi-C data. Nat Plants. 2024; 10: 1157-8.

[43] Simão FA, Waterhouse RM, Ioannidis P et al. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015; 31: 3210-2.

[44] Gurevich A, Saveliev V, Vyahhi N et al. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013; 29: 1072-5.

[45] Xia E, Li F, Tong W et al. The tea plant reference genome and improved gene annotation using long-read and paired-end sequencing data. Sci Data . 2019; 6: 122.

[46] Hoff KJ, Stanke M . Current methods for automated annotation of protein-coding genes. Current Opinion in Insect Science . 2015; 7: 8-14.

[47] Nishimura D . RepeatMasker. Biotech Software & Internet Report . 2000; 1: 36-9.

[48] Flynn JM, Hubley R , Goubert C et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proc Natl Acad Sci. 2020; 117: 9451-7.

[49] Cantalapiedra CP, Hernández-Plaza A, Letunic I et al. eggNOG-mapper v2: functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Mol Biol Evol. 2021; 38: 5825-9.

[50] Li M, Zhang D, Gao Q et al. Genome structure and evolution of Antirrhinum majus L. Nat Plants. 2019; 5: 174-83.

[51] Huang H, Wang C, Pei S et al. A chromosome-level reference genome of an aromatic medicinal plant Adenosma buchneroides . Sci Data. 2023; 10: 660.

[52] Ma Y, Wariss HM, Liao RL et al. Genome-wide analysis of butterfly bush (Buddleja alternifolia) in three uplands provides insights into biogeography, demography and speciation . New Phytol. 2021; 232: 1463-76.

[53] Wang L, Yu S, Tong C et al. Genome sequencing of the high oil crop sesame provides insight into oil biosynthesis. Genome Biol. 2014; 15: R39.

[54] Silva-Junior OB, Grattapaglia D, Novaes E et al. Genome assembly of the pink Ipê (Handroanthus impetiginosus, Bignoniaceae), a highly valued, ecologically keystone Neotropical timber forest tree . GigaScience. 2018; 7: gix125.

[55] Hamilton JP, Godden GT, Lanier E et al. Generation of a chromosome-scale genome assembly of the insect-repellent terpenoid-producing Lamiaceae species, Callicarpa americana . GigaScience. 2020; 9: giaa093.

[56] Zheng X, Chen D, Chen B et al. Insights into salvianolic acid B biosynthesis from chromosome-scale assembly of the Salvia bowleyana genome . J Integr Plant Biol. 2021; 63: 1309-23.

[57] Edger PP, Smith R, McKain M et al. Subgenome dominance in an interspecific hybrid, synthetic allopolyploid, and a 140-year-old naturally established neo-allopolyploid monkeyflower. Plant Cell. 2017; 29: 2150-67.

[58] Cao Y, Sun G, Zhai X et al. Genomic insights into the fast growth of paulownias and the formation of paulownia witches’ broom. Mol Plant. 2021; 14: 1668-82.

[59] Xu Y, Zhang J, Ma C et al. Comparative genomics of orobanchaceous species with different parasitic lifestyles reveals the origin and stepwise evolution of plant parasitism. Mol Plant. 2022; 15: 1384-99.

[60] Buchfink B, Reuter K, Drost HG . Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat Methods . 2021; 18: 366-8.

[61] Emms DM, Kelly S . OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019; 20: 1-14.

[62] Katoh K, Misawa K, Kuma KI et al. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002; 30: 3059-66.

[63] Minh BQ , Schmidt HA , Chernomor O et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020; 37: 1530-4.

[64] Puttick MN . MCMCtreeR: functions to prepare MCMCtree analyses and visualize posterior ages on trees. Bioinformatics. 2019; 35: 5321-2.

[65] De Bie T, Cristianini N, Demuth JP et al. CAFE: a computational tool for the study of gene family evolution. Bioinformatics. 2006; 22: 1269-71.

[66] Chen H, Zwaenepoel A, Van de Peer Y . Wgd v2: a suite of tools to uncover and date ancient polyploidy and whole-genome duplication. Bioinformatics. 2024; 40: btae272.

[67] Tang H, Krishnakumar V, Zeng X et al. JCVI: A versatile toolkit for comparative genomics analysis. iMeta . 2024; 3: e211.

[68] Kim D, Paggi JM, Park C et al. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019; 37: 907-15.

[69] Robinson MD, McCarthy DJ, Smyth GK . edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010; 26: 139-40.

[70] Wold S, Sjöström M, Eriksson L . PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst. 2001; 58: 109-30.

[71] Marchler-Bauer A, Derbyshire MK, Gonzales NR et al. CDD: NCBI’s conserved domain database. Nucleic Acids Res. 2015; 43: D222-6.

[72] Letunic I, Copley RR, Schmidt S et al. SMART 4.0: towards genomic data integration. Nucleic Acids Res. 2004; 32: 142D-144.

[73] Bailey TL, Boden M, Buske FA et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009; 37: W202-8.

[74] Yang H, Zhong S, Chen C et al. Expression profiling and putative biosynthetic network of flavonoids by global analysis with simplified omics data elucidating the large potential of Akebia trifoliata as an herbal industrial plant . Ind Crop Prod. 2024; 212: 118360.

[75] Zheng Y, Jiao C, Sun H et al. iTAK: a program for genome-wide prediction and classification of plant transcription factors, transcriptional regulators, and protein kinases. Mol Plant. 2016; 9: 1667-70.

[76] Shannon P, Markiel A, Ozier O et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003; 13: 2498-504.