Telomere-to-telomere genome assembly and 3D chromatin architecture of Centella asiatica insight into evolution and genetic basis of triterpenoid saponin biosynthesis

Abstract

Centella asiatica is renowned for its medicinal properties, particularly due to its triterpenoid saponins, such as asiaticoside and madecassoside, which are in excess demand for the cosmetic industry. However, comprehensive genomic resources for this species are lacking, which impedes the understanding of its biosynthetic pathways. Here, we report a telomere-to-telomere (T2T) C. asiatica genome. The genome size is 438.12 Mb with a contig N50 length of 54.12 Mb. The genome comprises 258.87 Mb of repetitive sequences and 25 200 protein-coding genes. Comparative genomic analyses revealed C. asiatica as an early-diverging genus within the Apiaceae family with a single whole-genome duplication (WGD, Apiaceae-ω) event following the ancient γ-triplication, contrasting with Apiaceae species that exhibit two WGD events (Apiaceae-α and Apiaceae-ω). We further constructed 3D chromatin structures, A/B compartments, and topologically associated domains (TADs) in C. asiatica leaves, elucidating the influence of chromatin organization on expression WGD-derived genes. Additionally, gene family and functional characterization analysis highlight the key role of CasiOSC03 in α-amyrin production while also revealing significant expansion and high expression of CYP716, CYP714, and UGT73 families involved in asiaticoside biosynthesis compared to other Apiaceae species. Notably, a unique and large UGT73 gene cluster, located within the same TAD, is potentially pivotal for enhancing triterpenoid saponin. Weighted gene coexpression network analysis (WGCNA) further highlighted the pathways modulated in response to methyl jasmonate (MeJA), offering insights into the regulatory networks governing saponin biosynthesis. This work not only provides a valuable genomic resource for C. asiatica but also sheds light on the molecular mechanisms driving the biosynthesis of pharmacologically important metabolites.

Acknowledgements

This work was supported by the Yunnan Characteristic Plant Extraction Laboratory (2022YKZY001) and Yunnan Seed Laboratory (202305AR340004). Additionally, we thank Mr. Fuyan Liu and Mr. Guisheng Xiang for providing assistance and valuable advice.

Author contributions

S.Y., Y.D., and G.Z. designed and led this project. W.S., B.C., and H.B. wrote the manuscript. W.S., G.C., L.F., and S.H. assembled and annotated the genome. W.S. performed the experiment and analyzed the transcriptomic data. All the authors have read and approved the final version of the paper.

Data availability

The raw genome sequencing and transcriptome data reported in this study are accessible through NCBI under the accession number PRJNA1121499 (https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRP512688&o=acc_s%3Aa). The genome assembly and annotation data can be found in the Figshare database at https://doi.org/10.6084/m9.figshare.28022099.v1 and the National Genomics Data Center (NGDC) at https://ngdc.cncb.ac.cn/gsa/, with the BioProject identifier PRJCA033632.

Conflict of interest statement

The authors declare that they have no conflict of interest.

Supplementary Data

References

[1] Asakawa Y, Matsuda R, Takemoto T. Mono- and sesquiter-penoids from Hydrocotyle and Centella species. Phytochemistry. 1982;21:2590-2

[2] Bandara MS, Lee EL, Thomas JE. Gotu Kola (Centella asiatica L.): an under-utilized herb. Am J Plant Sci Biotechnol. 2011;5: 20-31

[3] Leung Albert Y. Chinese medicinals. In: Advances in New Crops. OR, Timber Press: Portland, 1990,499-510

[4] Bailey E. Treatment of leprosy. Nature. 1945;155:601

[5] Brinkhaus B, Lindner M, Schuppan D. et al. Chemical, pharma-cological and clinical profile of the East Asian medical plant Centella aslatica. Phytomedicine. 2000;7:427-48

[6] Gregory J, Vengalasetti YV, Bredesen DE. et al. Neuroprotective herbs for the management of Alzheimer’s disease. Biomol Ther. 2021;11:543

[7] Saini S, Dhiman A, Nanda S.Traditional Indian medicinal plants with potential wound healing activity: a review. Int J Pharm Sci Res. 2016;7:1809

[8] Teerapattarakan N, Benya-Aphikul H, Tansawat R. et al. Neuro-protective effect of a standardized extract of Centella asiatica ECa233 in rotenone-induced parkinsonism rats. Phytomedicine. 2018;44:65-73

[9] James JT, Dubery IA. Pentacyclic triterpenoids from the medici-nal herb, Centella asiatica (L.) Urban. Molecules. 2009;14:3922-41

[10] Kim OT, Kim MY, Huh SM. et al. Cloning of a cDNA probably encoding oxidosqualene cyclase associated with asiaticoside biosynthesis from Centella asiatica (L.) Urban. Plant Cell Rep. 2005;24:304-11

[11] Miettinen K, Pollier J, Buyst D. et al. The ancient CYP716 family is a major contributor to the diversification of eudicot triterpenoid biosynthesis. Nat Commun. 2017;8:14153

[12] Moses T, Pollier J, Shen Q. et al. OSC2 and CYP716A14v2 catalyze the biosynthesis of triterpenoids for the cuticle of aerial organs of Artemisia annua. Plant Cell. 2015;27:286-301

[13] Sun R, Gao J, Chen H. et al. CbCYP716A261, a new β-amyrin 28-hydroxylase involved in conyzasaponin biosynthesis from Conyza blinii. Mol Biol. 2020;54:719-29

[14] Yasumoto S, Seki H, Shimizu Y. et al. Functional characterization of CYP716 family P450 enzymes in triterpenoid biosynthesis in tomato. Front Plant Sci. 2017;8:21

[15] Alcalde MA, Cusido RM, Moyano E. et al. Metabolic gene expres-sion and centelloside production in elicited Centella asiatica hairy root cultures. IndCropProd. 2022;184:114988

[16] Kim OT, Um Y, Jin ML. et al. A novel multifunctional C-23 oxidase, CYP714E19, is involved in asiaticoside biosynthesis. Plant Cell Physiol. 2018;59:1200-13

[17] De Costa F, Barber CJ, Kim Y-b. et al. Molecular cloning of an ester-forming triterpenoid: UDP-glucose 28-O-glucosyltransferase involved in saponin biosynthesis from the medicinal plant Cen-tella asiatica. Plant Sci. 2017;262:9-17

[18] Kim OT, Jin ML, Lee DY. et al. Characterization of the asiatic acid glucosyltransferase, UGT73AH1, involved in asiaticoside biosyn-thesis in Centella asiatica (L.) Urban. Int J Mol Sci. 2017;18:2630

[19] Xiaoyang H, Jingyi Z, Hong Z. et al. The biosynthesis of asiatico-side and madecassoside reveals a tandem duplication-directed evolution of glycoside glycosyltransferases in the Apiales. Plant Commun. 2024;5:101005

[20] Zhao X, Wei W, Li S. et al. Elucidation of the biosynthesis of asiaticoside and its reconstitution in yeast. ACS Sustain Chem Eng. 2024;12:4028-40

[21] Han X, Zhao J, Chang X. et al. Revisiting the transcriptome data of Centella asiatica identified an ester-forming triterpenoid: UDP-glucose 28-O-glucosyltransferase. Tetrahedron. 2022;129:133136

[22] Zeng W, Li D, Zhang H. et al. Multi-strategy integration improves 28-O-glucosylation of asiatic acid into asiatic acid monogluco-side. Food Biosci. 2024;61:104832

[23] He S, Weng D, Zhang Y. et al. A telomere-to-telomere ref-erence genome provides genetic insight into the pentacyclic triterpenoid biosynthesis in Chaenomeles speciosa. Hortic. Res.. 2023;10:uhad183

[24] Song Y, Zhang Y, Wang X. et al. Telomere-to-telomere reference genome for Panax ginseng highlights the evolution of saponin biosynthesis. Hortic Res. 2024;11:uhae107

[25] Yun L, Zhang C, Liang T. et al. Insights into dammarane-type triterpenoid saponin biosynthesis from the telomere-to-telomere genome of Gynostemma pentaphyllum. Plant Commun. 2024;5:100932

[26] Pootakham W, Naktang C, Kongkachana W. et al. De novo chromosome-level assembly of the Centella asiatica genome. Genomics. 2021;113:2221-8

[27] Wang M, Wang P, Lin M. et al. Evolutionary dynamics of 3D genome architecture following polyploidization in cotton. Nature Plants. 2018;4:90-7

[28] Ouyang W, Xiong D, Li G. et al. Unraveling the 3D genome architecture in plants: present and future. Mol Plant. 2020;13: 1676-93

[29] Emms DM, Kelly S.OrthoFinder: phylogenetic orthology infer-ence for comparative genomics. Genome Biol. 2019;20:238

[30] Zhang R-G, Shang H-Y, Milne RI. et al. SOI: robust identifi-cation of orthologous synteny with the Orthology Index and broad applications in evolutionary genomics. bioRxiv. 2024; 2024. 08.22.609065

[31] Yang Z, Li X, Yang L. et al. Comparative genomics reveals the diversification of triterpenoid biosynthesis and origin of ocotillol-type triterpenes in Panax. Plant Commun. 2023;258: 100591

[32] Zhang Y, Pan X, Shi T. et al. P450Rdb: a manually curated database of reactions catalyzed by cytochrome P450 enzymes. J Adv Res. 2024;63:35-42

[33] Li Y, Zhao J, Chen H. et al. Transcriptome level reveals the triter-penoid saponin biosynthesis pathway of Bupleurum falcatum L. Genes. 2022;13:2237

[34] Zhang Q, Li M, Chen X. et al. Chromosome-level genome assem-bly of Bupleurum chinense DC provides insights into the saikos-aponin biosynthesis. Front Genet. 2022;13:878431

[35] Wang Y-H, Liu P-Z, Liu H. et al. Telomere-to-telomere carrot (Dau-cus carota) genome assembly reveals carotenoid characteristics. Hortic Res. 2023;10:uhad103

[36] Zhang C, Zhang T, Luebert F. et al. Asterid phylogenomics/phylotranscriptomics uncover morphological evolutionary his-tories and support phylogenetic placement for numerous whole-genome duplications. Mol Biol Evol. 2020;37:3188-210

[37] Leebens-Mack JH, Barker MS, Carpenter EJ. et al. One thousand plant transcriptomes and the phylogenomics of green plants. Nature. 2019;574:679-85

[38] Li Q, Dai Y, Huang X-C. et al. The chromosome-scale assembly of the Notopterygium incisum genome provides insight into the structural diversity of coumarins. Acta Pharm Sin B. 2024;14: 3760-73

[39] Han X, Li C, Sun S. et al. The chromosome-level genome of female ginseng (Angelica sinensis) provides insights into molecular mechanisms and evolution of coumarin biosynthesis. Plant J. 2022;112:1224-37

[40] Liao Y, Wang J, Zhu Z. et al. The 3D architecture of the pepper genome and its relationship to function and evolution. Nat Commun. 2022;13:3479

[41] Haralampidis K, Trojanowska M, Osbourn AE. Biosynthesis of triterpenoid saponins in plants. Adv Biochem Eng Biotechnol. 2002;75:31-49

[42] Kim OT, Um Y, Jin ML. et al. Analysis of expressed sequence tags from Centella asiatica (L.) Urban hairy roots elicited by methyl jasmonate to discover genes related to cytochrome P450s and glucosyltransferases. Plant Biotechnol Rep. 2014;8:211-20

[43] Kim OT, Lee JW, Bang KH. et al. Characterization of a dammarenediol synthase in Centella asiatica (L.) Urban. Plant Physiol Biochem. 2009;47:998-1002

[44] Liu Y, Wang B, Shu S. et al. Analysis of the Coptis chinensis genome reveals the diversification of protoberberine-type alka-loids. Nat Commun. 2021;12:3276

[45] Buraphaka H, Putalun W. Stimulation of health-promoting triterpenoids accumulation in Centella asiatica (L.) Urban leaves triggered by postharvest application of methyl jasmonate and salicylic acid elicitors. IndCropProd. 2020;146:112171

[46] James JT, Tugizimana F, Steenkamp PA. et al. Metabolomic analy-sis of methyl jasmonate-induced triterpenoid production in the medicinal herb Centella asiatica (L.) urban. Molecules. 2013;18: 4267-81

[47] Baek S, Ho T-T, Lee H. et al. Enhanced biosynthesis of triter-penoids in Centella asiatica hairy root culture by precursor feeding and elicitation. Plant Biotechnol Rep. 2020;14:45-53

[48] Qi T, Wang J, Huang H. et al. Regulation of jasmonate-induced leaf senescence by antagonism between bHLH subgroup IIIe and IIId factors in Arabidopsis. Plant Cell. 2015;27:1634-49

[49] Song S, Qi T, Fan M. et al. The bHLH subgroup IIId factors nega-tively regulate jasmonate-mediated plant defense and develop-ment. PLoS Genet. 2013;9:e1003653

[50] Belton J-M, McCord RP, Gibcus JH. et al. Hi-C: a comprehensive technique to capture the conformation of genomes. Methods. 2012;58:268-76

[51] Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114-20

[52] Liu B, Shi Y, Yuan J. et al. Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects arXiv preprint arXiv:1308.2012. 2013;

[53] Ranallo-Benavidez TR, Jaron KS, Schatz MC. GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nat Commun. 2020;11:1432

[54] 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

[55] Wick RR, Schultz MB, Zobel J. et al. Bandage: interactive visu-alization of de novo genome assemblies. Bioinformatics. 2015;31: 3350-2

[56] Zhou C, McCarthy SA, Durbin R. YaHS: yet another Hi-C scaf-folding tool. Bioinformatics. 2023;39:btac808

[57] Durand NC, Shamim MS, Machol I. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 2016;3:95-8

[58] Lin Y, Ye C, Li X. et al.quarTeT: a telomere-to-telomere toolkit for gap-free genome assembly and centromeric repeat identifi-cation. Hortic Res. 2023;10:uhad127

[59] Vollger MR, Kerpedjiev P, Phillippy AM. et al. StainedGlass: inter-active visualization of massive tandem repeat structures with identity heatmaps. Bioinformatics. 2022;38:2049-51

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

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

[62] Rhie A, Walenz BP, Koren S. et al. Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies. Genome Biol. 2020;21:1-27

[63] Ou S, Chen J, Jiang N. Assessing genome assembly quality using the LTR Assembly Index (LAI). Nucleic Acids Res. 2018;46: e126-6

[64] Ou S, Su W, Liao Y. et al. Benchmarking transposable element annotation methods for creation of a streamlined, comprehen-sive pipeline. Genome Biol. 2019;20:1-18

[65] Chan PP, Lin BY, Mak AJ. et al. tRNAscan-SE 2.0: improved detection and functional classification of transfer RNA genes. Nucleic Acids Res. 2021;49:9077-96

[66] Stanke M, Keller O, Gunduz I. et al. AUGUSTUS: ab initio predic-tion of alternative transcripts. Nucleic Acids Res. 2006;34:W435-9

[67] Majoros WH, Pertea M, Salzberg SL. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics. 2004;20:2878-9

[68] Brůna T, Lomsadze A, Borodovsky M.GeneMark-EP+: eukaryotic gene prediction with self-training in the space of genes and proteins. NAR Genomics Bioinf. 2020;2:lqaa026

[69] Brůna T, Hoff KJ, Lomsadze A. et al. BRAKER2:automatic eukary-otic genome annotation with GeneMark-EP+ and AUGUSTUS supported by a protein database. NAR Genomics Bioinf. 2021;3: lqaa108

[70] Keilwagen J, Hartung F, Paulini M. et al. Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi. BMC Bioinf. 2018;19:1-12

[71] 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

[72] Grabherr MG, Haas BJ, Yassour M. et al. Full-length transcrip-tome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29:644-52

[73] Avram O, Kigel A, Vaisman-Mentesh A. et al. PASA: proteomic analysis of serum antibodies web server. PLoS Comput Biol. 2021; 17:e1008607

[74] Meleshko D.Novel Synthetic Long-Read Methods for Structural Vari-ant Discovery and Transcriptomic Assembly. Vol. 2024. Weill Medical College of Cornell University

[75] Jones P, Binns D, Chang H-Y. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics. 2014;30:1236-40

[76] Aramaki T, Blanc-Mathieu R, Endo H. et al. KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics. 2020;36:2251-2

[77] Katoh K, Asimenos G, Toh H. Multiple alignment of DNA sequences with MAFFT. Methods Mol Biol. 2009;537:39-64

[78] Talavera G, Castresana J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from pro-tein sequence alignments. Syst Biol. 2007;56:564-77

[79] Kalyaanamoorthy S, Minh BQ, Wong TKF. et al. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14:587-9

[80] Nguyen LT, Schmidt HA, von Haeseler A. et al. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268-74

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

[82] Yang Z. PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci. 1997;13:555-6

[83] Han MV, Thomas GW, Lugo-Martinez J. et al. Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3. MolBiolEvol. 2013;30:1987-97

[84] Wang Y, Tang H, DeBarry JD. et al. MCScanX: a toolkit for detec-tion and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012;40:e49-9

[85] Sun P, Jiao B, Yang Y. et al. WGDI: a user-friendly toolkit for evo-lutionary analyses of whole-genome duplications and ancestral karyotypes. Mol Plant. 2022;15:1841-51

[86] Sensalari C, Maere S, Lohaus R. Ksrates: positioning whole-genome duplications relative to speciation events in KS distri-butions. Bioinformatics. 2021;38:530-2

[87] Yu G, Wang LG, Han Y. et al. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284-7

[88] Servant N, Varoquaux N, Lajoie BR. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 2015;16:1-11

[89] Wolff J, Backofen R, Grüning B. Loop detection using Hi-C data with HiCExplorer. GigaScience. 2022;11:giac061

[90] Altschul SF, Gish W, Miller W. et al. Basic local alignment search tool. J Mol Biol. 1990;215:403-10

[91] Finn RD, Clements J, Eddy SR. HMMER web server: interac-tive sequence similarity searching. Nucleic Acids Res. 2011;39: W29-37

[92] Kumar S, Stecher G, Li M. et al. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35:1547-9

[93] Pertea M, Pertea GM, Antonescu CM. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33:290-5

[94] Cline MS, Smoot M, Cerami E. et al. Integration of biological networks and gene expression data using Cytoscape. Nat Protoc. 2007;2:2366-82

[95] Gietz RD, Woods RA. Transformation of yeast by lithium acetate/single-stranded carrier DNA/polyethylene glycol method. Meth-ods Enzymol. 2002;350:87-96