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Brief Report

Chromosome-Scale Genome Assembly and Triterpenoid Saponin Biosynthesis in Korean Bellflower (Platycodon grandiflorum)

by
Dong-Jun Lee
1,
Ji-Weon Choi
2,
Ji-Nam Kang
1,
Si-Myung Lee
1,
Gyu-Hwang Park
1 and
Chang-Kug Kim
1,*
1
Genomics Division, National Institute of Agricultural Sciences, Jeonju 54874, Republic of Korea
2
Postharvest Technology Division, National Institute of Horticultural and Herbal Science, Wanju 55365, Republic of Korea
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2023, 24(7), 6534; https://doi.org/10.3390/ijms24076534
Submission received: 2 March 2023 / Revised: 24 March 2023 / Accepted: 29 March 2023 / Published: 31 March 2023
(This article belongs to the Special Issue Genome Assembly)
Browse Figures
Review Reports Versions Notes

Abstract

:
Platycodon grandiflorum belongs to the Campanulaceae family and is an important medicinal and food plant in East Asia. However, on the whole, the genome evolution of P. grandiflorum and the molecular basis of its major biochemical pathways are poorly understood. We reported a chromosome-scale genome assembly of P. grandiflorum based on a hybrid method using Oxford Nanopore Technologies, Illumina sequences, and high-throughput chromosome conformation capture (Hi-C) analysis. The assembled genome was finalized as 574 Mb, containing 41,355 protein-coding genes, and the genome completeness was assessed as 97.6% using a Benchmarking Universal Single-Copy Orthologs analysis. The P. grandiflorum genome comprises nine pseudo-chromosomes with 56.9% repeat sequences, and the transcriptome analysis revealed an expansion of the 14 beta-amylin genes related to triterpenoid saponin biosynthesis. Our findings provide an understanding of P. grandiflorum genome evolution and enable genomic-assisted breeding for the mass production of important components such as triterpenoid saponins.

1. Introduction

The Korean bellflower (Platycodon grandiflorum), a herbaceous, perennial, bell-shaped flower, belongs to the Campanulaceae family. Bellflower is used in traditional medicines and food additives due to its therapeutic effects on bronchitis, sore throats, and asthma [1]. Bellflower root is an oriental herbal medicine used in East Asia, and the flowers are used for ornamental purposes in the USA and Europe [2,3,4]. The applications of P. grandiflorum have increased in oriental medicine, food fields, herbal teas, ornamental flowers, and health products [5,6].
In the Campanulaceae family, Platycodon grandiflorus A. De Candolle (P. grandiflorus A. DC) is the sole species in the Platycodon genus [7]. However, some papers have described Platycodon grandiflorum A. De Candolle (P. grandiflorum A. DC) as the only species in the Platycodon genus [8,9,10]. In many cases, both scientific names have been used for the same plant, without distinguishing between P. grandiflorum and P. grandiflorus [11,12]. In the Platycodon genus, the taxonomic delimitation of some species is difficult because historical descriptions are not detailed and the morphological characteristics are similar. The scientific names of P. grandiflorus and P. grandiflorum are often confused because of an orthographic change in the epithets, which has led to misinterpretations [13]. In this study, P. grandiflorum is defined as a variety of P. grandiflorus species, because this orthographic error has made it impossible to search databases for information about a single species.
In the P. grandiflorus species, two genome sequence assemblies using Chinese balloon flower [14] and Korean balloon flower [15] were reported. Genomic information on these species is available to guide breeding strategies for crop improvement [16]; however, the molecular basis of P. grandiflorum remains uncharacterized. The recent development of high-throughput sequencing technologies has reduced the difficulty of genomic research, and next-generation sequencing (NGS) technologies such as Oxford Nanopore Technologies (ONT) have enabled accurate genome assembly [17].
Triterpenoid saponins are the most important bioactive components of P. grandiflorum [18,19] and have pharmacological activities such as anti-inflammatory, anti-obesity, and hepatotoxic effects [20,21]. Triterpenoid saponins are surface-active glycosides of triterpenes that possess a wide, biologically active group of terpenoids. The triterpenoid saponin of P. grandiflorum has a typical oleanane backbone with glucose at the C-30 position and an ester linkage between C-28 and arabinose [22]. The major components are synthesized via mevalonic acid (MVA) and methylerythritol 4-phosphate (MEP) pathways, and the first diversifying step in triterpenoid biosynthesis is the cyclization of 2,3-oxidosqualene, catalyzed by an oxidosqualene cyclase (OSC) [15,23]. In particular, CYP716 and bAS gene families indicate the species-specific selection of key player genes towards the triterpenoid saponin biosynthesis and their functions [15]. Triterpenoid saponins include a large chemical diversity of secondary metabolites with carbon skeletons which undergo various modifications, such as oxidation, hydroxylation, or glycosylation, mediated by cytochrome P450 monooxygenases (CYP450s), glycosyltransferases (UGTs), and other enzymes [24]. Various biochemical pathways have been studied in the Campanulaceae family, including the triterpenoid and flavonoid components [25].
Here, we report a chromosome-scale reference genome sequence for P. grandiflorum obtained by combining ONT, Illumina sequence, and high-throughput chromosome conformation capture (Hi-C) technology. Comparative genome analyses illuminated the genome evolution, and the genome-wide analysis revealed the evolutionary adaptation of P. grandiflorum which has evolved specifically towards triterpenoid saponins. The present study provides insights into genomic resources that will enable further research into this medicinal plant and expand our understanding of the Campanulaceae family.

2. Results and Discussion

2.1. Genome Assembly

For the chromosome-scale reference genome of P. grandiflorum, 574.7 Mb genome sequences were completed with nine pseudo-chromosomes (Table 1 and Figure 1A). To produce a high-quality genome sequence, we generated approximately 52.7 Gb trimmed Nanopore long-read sequences with an average read length of 4911 base pairs (bp). In addition, 100.5 Gb Illumina short-read length sequences were produced using three insert sizes (Supplementary Table S1). The P. grandiflorum genome size was estimated to be approximately 634 Mb based on a k-mer analysis using Illumina short reads (Supplementary Figure S1).
To assemble P. grandiflorum, firstly, trimmed Nanopore long reads were used to produce the draft assembly after base correction using trimmed Illumina short reads (Supplementary Table S1). Secondly, two assemblers were used to compare the accuracy of the draft assembly. Two contig sets were identified by polishing Illumina short-read data (Supplementary Table S2). Thirdly, one contig set was selected due to scaffolding efficiency, which was subjected to preliminary scaffolding with Hi-C data (Supplementary Figure S2). Finally, the contig sequences were scaffolded into nine pseudo-chromosomes using a manual polishing process in the Hi-C analysis (Figure 1B).
The P. grandiflorum genome was completed at 574.7 Mb (90.6% of the estimated genome size), being composed of 429 sequence sets (chromosome and contigs) with an N50 value of 64.5 Mb (Table 1). The comprising nine pseudo-chromosomes ranged from 43.5 to 93.4 Mb, and the Hi-C interaction heatmap shows the interaction signals on the nine chromosomes (Figure 1B and Supplementary Figure S2). The quality of the assembled genome was evaluated using a Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis, which captured 97.6% of the 1614 conserved orthologous angiosperm genes (Table 1). The assembled genome was validated by mapping paired-end (PE) sequences based on three categories. Trimmed PE reads from 95.3% to 96.8% were mapped to the assembled genome sequences, and a maximum of 94.5% of the genome was covered by the mapped reads (Supplementary Table S3).

2.2. Genome Annotation

A total of 41,355 protein-coding genes were predicted using an evidence-based annotation pipeline (Supplementary Figure S3) based on transcriptome data (Supplementary Table S4) and protein sequences. The genome annotation identified 327.5 Mb repeat sequences in P. grandiflorum, accounting for 56.9% of the genome (Table 1). The most repetitive category was long terminal repeat (LTR) retrotransposons, including Gypsy (13.0%) and Copia (11.8%) (Supplementary Table S5). The total length of the protein-coding genes was 40.6 Mb, with an average gene length of 982 bp and a GC content of 44.5%. Among 41,355 protein-coding genes, 80.5% were functionally annotated by comparing their homology against libraries of known proteins, such as NCBI GenBank, protein domains, gene ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In total, 79.8% of the genes showed high similarity with known protein sequences deposited in NCBI GenBank, and 61.2% of the genes had known conserved protein domains. A total of 41.8% of the genes were assigned to at least one GO term, and 27.6% were assigned to a pathway registered in the KEGG database (Supplementary Table S6). For the functional classification of annotated genes, 17,286 GO term genes were classified into functional categories. Within the three categories at level three, the most enriched genes were assigned to organic substance processes, organic cyclic compounds, and membrane processes (Figure 2A).

2.3. Genome Comparison

To evaluate genome completeness and annotation accuracy, we compared P. grandiflorum and two other Platycodon grandiflorus genomes [14,23], all of which belong to the Campanulaceae family. For genome completeness, the BUSCO value was 96.7–98.3% (Supplementary Table S7) and the metrics of the annotation gene set were similar to those previously reported for the two Platycodon grandiflorus genomes (Supplementary Table S8). Therefore, whole-genome sequencing and an annotation comparison indirectly showed that the P. grandiflorum genome was well-assembled.
To determine the the evolutionary relationship between P. grandiflorum and four other whole genomes (Panax ginseng, Helianthus annuus, Solanum lycopersicum, and Arabidopsis thaliana) (Supplementary Table S9), we performed a similarity-based gene clustering analysis. A total of 10,282 genes were shared among the five genomes, and 1422 genes were unique to P. grandiflorum (Figure 2B). To identify enriched functional categories, we performed GO enrichment analysis using shared and unique genes. In the GO term groups, shared genes were clustered in the regulation of transcription, oxidoreductase activity, and DNA binding. Unique genes were clustered in relation to post-embryonic development (Supplementary Table S10), and this GO term is controlled by multiple transcription factors during post-embryonic development [26].
In addition, a GO enrichment analysis was performed using P. grandiflorum and two Platycodon grandiflorus genomes. Gene clustering revealed that 16,116 genes were shared among the three genomes and 866 genes were unique (Supplementary Figure S4 and Supplementary Table S11).

2.4. Identification of Genes Involved in Triterpenoid Saponin Biosynthesis

To reveal the expression profile of P. grandiflorum, RNA-Seq data identified a gene expressed in at least one of eight different tissues and one of three methyl jasmonate (MJ) treatments. To identify the genes related to triterpenoid saponins in P. grandiflorum, 46 candidate genes were identified to be involved in the triterpenoid biosynthesis pathway using the KEGG database (Figure 3). Triterpenoids are generated by OSCs that catalyze the production of diverse triterpene skeletons [24], and β-amyrin synthases are important OSCs for triterpenoid saponin biosynthesis [27]. Therefore, the existence of 14 beta-amyrin (β-amyrin) synthases is evidence of their major contribution to triterpenoid saponin modifications in P. grandiflorum. Most β-amyrin genes were strongly expressed in roots and seeds (Figure 3). Among the fourteen β-amyrin genes, three genes (Pg_chr02_56820T, Pg_chr04_41420T, and Pg_chr04_41430T) showed significantly higher expression in root tissues under normal conditions (Supplementary Table S12), suggesting they are key genes associated with the production of triterpenoid saponins in the roots of P. grandiflorum. However, two β-amyrin genes (Pg_chr04_41450T and Pg_chr04_41400T) significantly expressed in roots were not selected as key genes because of their relatively low expression in roots with the absence of expression in other tissues.
In addition, the expression of Pg_chr02_56820T increased at 12–48 h after exposure after exogenous hormone MJ treatment, indicating its potential association with the induction of triterpenoid saponins [28]. This expression pattern was supported by a previous report [29] related to the efficient induction of ginsenoside biosynthesis in Panax species. Considering the high expression of this gene in roots, it may be involved in the accumulation of triterpenoid saponins in roots.

3. Materials and Methods

3.1. Plant Materials and Genome Sequencing

The whole plant body of P. grandiflorum cultivar doraji was collected from the National Institute of Agricultural Sciences research field in Jeonju, Republic of Korea, and was registered at the National Agrobiodiversity Center (http://genebank.rda.go.kr/, accessed on 17 January 2022) under voucher number IT209935. Genomic DNA was extracted from young leaves using the GeneAll Exgene Plant SV kit (GeneAll, Seoul, Republic of Korea) and purified using 0.7x AMPure XP beads (Beckman Coulter, Brea, CA, USA). Nanopore sequencing libraries were constructed using an ONT 1D ligation sequencing kit and sequenced using 1D flow cells (Oxford Nanopore Technologies, Oxford, UK). Nanopore sequencing data (Q > 7) and Illumina PE data (Phred score > 20) were trimmed using Trimmomatic (version 0.38) with the default parameters [30]. During Hi-C sequencing, chromatin conformation capture data were produced by Phase Genomics (Phase Genomics, Seattle, WA, USA) using the Proximo Hi-C Plant Kit (Phase Genomics, Seattle, WA, USA) following the manufacturer’s instructions. The molecules were pulled down with streptavidin beads and used for the construction of an Illumina-compatible sequencing library and sequencing using the HiSeq X platform (Illumina, San Diego, CA, USA).

3.2. Genome Size Estimation

The genome size of P. grandiflorum was estimated via k-mer frequency analyses of high-quality Illumina PE data using Jellyfish (version 2.0) [31] and the GenomeScope tool (version 2.0) [32]. PE data were analyzed using Jellyfish to obtain k-mer frequency data using an optimal k-mer value of 17. Then, the genome size was estimated using GenomeScope based on the 17 k-mer frequency value.

3.3. Genome Assembly

First, the trimmed nanopore sequencing data were self-corrected using the Canu assembler (version 1.71) [33] with default parameters to generate the corrected nanopore sequences. The corrected nanopore sequences were de novo assembled using SMARTdenovo [34] and the Canu assembler. The parameters of both assemblers were set with a minimum read length of 1000 bp and the remaining parameters were set to default settings. The assembled contig sequences were polished twice using Pilon (version 1.23) [35] with the trimmed PE data. To improve the quality of genome assembly, additional polishing was performed by mapping the trimmed PE data and generating a consensus sequence, as described in [36]. Haplotigs were removed from the contig sequences using Purge haplotigs [37] with default parameters. In the Hi-C data, scaffolding was performed using Phase Genomics (Phase Genomics, Seattle, WA, USA), and read pairs were aligned using BWA-MEM (version 0.7.17) [38]. The Proximo Hi-C genome scaffolding platform was used to create chromosome-scale scaffolds [39]. The completeness of the gene set predicted in the genome sequence was validated via an analysis using BUSCO (version 5.0.0) [40] with the Embryophyta _odb10 lineage dataset. In addition, genome assembly was further validated by mapping the PE data using BWA-MEM with the default parameters.

3.4. Gene Annotation

Protein-coding regions were predicted in genome sequence using an evidence-based annotation pipeline (Supplementary Figure S3). For transcriptome evidence, RNA-Seq data produced in [23] were downloaded from the NCBI Sequence Rad Archive (SRA) database (https://www.ncbi.nlm.nih.gov/bioproject/526590, accessed on 12 December 2022) and de novo assembled using Trinity [41]. A total of 180,652 transcripts were prepared, with a total length of 184.4 Mb. Protein sequences were compared from three published genome assemblies: sunflower (Helianthus annuus, version 1.2), Korean ginseng (Panax ginseng, version 1.1), and Arabidopsis thaliana (Araport11).
Consensus repeat sequences in the genome sequence were identified and characterized using RepeatModeler (version 1.0.11, http://www.repeatmasker.org/, accessed on 12 September 2022), then combined with known repeat sequences in RepBase (version 28.04, https://www.girinst.org/, accessed on 19 September 2022). The combined sequences were referenced using RepeatMasker (version 4.0.9, http://www.repeatmasker.org/, accessed on 12 September 2022) to identify repeat sequences in the genome. The genome sequences were masked with repeat sequences using an annotation pipeline composed of MAKER3, SNAP, AUGUSTUS, GeneMark-ES, and EvidenceModeler (Supplementary Figure S3). The final gene set was selected as the gene sequence with an annotation evidence distance (AED) score of <1.

3.5. Genome Comparative and Functional Annotation

For a comparative analysis, P. grandiflorum and four plant genomes were used: P. ginseng (Korean ginseng), H. annuus (sunflower), S. lycopersicum (tomato), and Arabidopsis thaliana. In addition, P. grandiflorum and two Platycodon species, Korean and Chinese balloon flowers, all belonging to the Campanulaceae family, were compared (Supplementary Table S7). Genome sequences of P. grandiflorum and other genomes were identified by gene clustering using the OrthoVenn2 web tool [42] with an E-value cutoff of 1 × 10−5. Functional annotation of the predicted protein-coding genes was performed using sequence similarities in the NCBI non-redundant protein database using DIAMOND (version 0.9.30.131) [43] with an E-value cutoff of 1 × 10−5. Based on these similarity search results, gene ontology (GO) terms were assigned to genes using the Blast2GO Command Line (version 1.4.4) [44] with default parameters. Conserved domains within protein-coding genes were determined using InterProScan (version 5.34) [45] with the default parameters.

3.6. Genome Comparative and Functional Annotation

For the gene expression profiling of protein-coding genes, 60 total RNA sequencing data were downloaded from the SRA database (https://www.ncbi.nlm.nih.gov/bioproject/526590), 24 RNA data were derived from eight different tissues (leaves, stems, roots, petals, sepals, pistils, stamens, and seeds) with three replications, and 36 RNA data were derived from methyl jasmonate treatments for control, 12, 24, and 48 h with three replications and three repetitions [23].
The RNA-Seq data were trimmed using Trimmomatic [29] with a Phred score > 20 as a parameter. In addition, contaminated sequences from bacteria and viruses were removed using the BBDuk program (https://jgi.doe.gov/, accessed on 29 September 2022) with the k-mer 31 parameter. Expression profiles were determined from trimmed RNA reads using HISAT2 (version 2.2.0) [46] with spliced alignment options. The RNA reads were mapped to protein-coding sequences using HTSeq-count (version 0.12.4) [47]. Fragments per kilobase of transcript per million mapped reads (FPKM) were calculated based on the number of mapped RNA reads, and a heatmap was generated using the R package pheatmap [48]. To investigate triterpenoid saponin biosynthesis, candidate genes were identified by searching for genes assigned to the triterpenoid biosynthesis pathway. A metabolic pathway was assigned to genes using the KAAS server [49] on eukaryote gene sets using the single-directional best hit method.

4. Conclusions

P. grandiflorum is a popular medicinal and health food resource with potential therapeutic effects used throughout East Asia. In this study, we report the chromosome-scale genome assembly and genomic characterization of P. grandiflorum. Additionally, transcriptomic analyses were performed to explore the formation of triterpenoid saponins. Our findings provide insights into P. grandiflorum genome evolution and enable the future genomic-aided breeding of important traits in the Campanulaceae family. These genomic resources represent important first steps towards the genetic improvement of P. grandiflorum for the utilization of plant pharmaceutical resources and will accelerate improvements in agricultural traits, such as the production of triterpenoid saponins, which is the most important bioactive component of P. grandiflorum.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24076534/s1.

Author Contributions

Conceptualization, D.-J.L. and J.-W.C.; methodology, D.-J.L. and J.-N.K.; formal analysis, G.-H.P.; investigation, C.-K.K.; writing—original draft preparation, C.-K.K.; writing—review and editing, S.-M.L.; project administration, C.-K.K.; funding acquisition, C.-K.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the Research Program for Agricultural Science and Technology Development (project nos. PJ015713 and PJ014276) of the Rural Development Administration, Republic of Korea.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All raw sequencing data produced in this study were deposited into the NCBI Sequence Rad Archive (SRA) under BioProject number PRJNA656905 and BioSample SAMN15806942. This Whole Genome Shotgun project has been deposited in GenBank under accession number JACONP000000000 under BioProject number PRJNA656905. In addition, files for the annotated gene sequences and functional annotations were uploaded to Figshare (https://doi.org/10.6084/m9.figshare.21511020).

Acknowledgments

We would like to thank the Bioinformatics and Sales team at Phyzen for their technical assistance and contribution to the management of this study.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Zhang, L.L.; Huang, M.Y.; Yang, Y.; Huang, M.Q.; Shi, J.J.; Zou, L.; Lu, J.J. Bioactive platycodins from Platycodonis Radix: Phytochemistry, pharmacological activities, toxicology and pharmacokinetics. Food Chem. 2020, 327, 127029. [Google Scholar] [CrossRef] [PubMed]
  2. Lee, H.O.; Choi, J.W.; Baek, J.H.; Oh, J.H.; Lee, S.C.; Kim, C.K. Assembly of the mitochondrial genome in the Campanulaceae Family using Illumina low-coverage sequencing. Genes 2018, 9, 383. [Google Scholar] [CrossRef] [Green Version]
  3. Chang, A.; Pei, W.; Li, S.; Wang, T.; Song, H.; Kang, T.; Zhang, H. Integrated metabolomic and transcriptomic analysis reveals variation in the metabolites and genes of Platycodon grandiflorus roots from different regions. Phytochem. Anal. 2022, 33, 982–994. [Google Scholar] [CrossRef]
  4. Kondo, T.; Hagihara, S.; Takaya, Y.; Yoshida, K. Polyacylated anthocyanins in bluish-purple petals of Chinese bellflower. Platycodon grandiflorum. Int. J. Mol. Sci. 2021, 22, 4044. [Google Scholar] [CrossRef] [PubMed]
  5. Ji, M.Y.; Bo, A.; Yang, M.; Xu, J.F.; Jiang, L.L.; Zhou, B.C.; Li, M.H. The pharmacological effects and health benefits of Platycodon grandiflorus-A medicine food homology species. Foods 2020, 9, 142. [Google Scholar] [CrossRef] [Green Version]
  6. Kim, G.; Rim, Y.; Cho, H.; Hyun, T.K. Identification and functional characterization of FLOWERING LOCUS T in Platycodon grandiflorus. Plants 2022, 11, 325. [Google Scholar] [CrossRef]
  7. Zhang, L.; Wang, Y.L.; Yang, D.W.; Zhang, C.H.; Zhang, N.; Li, M.H.; Liu, Y.Z. Platycodon grandiflorus—An Ethnopharmacological, phytochemical and pharmacological review. J. Ethnopharm. 2015, 164, 147–161. [Google Scholar] [CrossRef] [PubMed]
  8. Ma, C.H.; Gao, Z.J.; Zhang, J.J.; Zhang, W.; Shao, J.H.; Hai, M.R.; Chen, J.W.; Yang, S.C.; Zhang, G.H. Candidate genes involved in the biosynthesis of triterpenoid saponins in Platycodon grandiflorum identified by transcriptome analysis. Front. Plant Sci. 2016, 7, 673. [Google Scholar] [CrossRef] [Green Version]
  9. Zhang, S.; Chai, X.; Hou, G.; Zhao, F.; Meng, Q. Platycodon grandiflorum (Jacq.) A. DC.: A review of phytochemistry, pharmacology, toxicology and traditional use. Phytomedicine 2022, 106, 154422. [Google Scholar] [CrossRef]
  10. Kim, H.J.; Jung, J.; Kim, M.-S.; Lee, J.M.; Choi, D.; Yeam, I. Molecular marker development and genetic diversity exploration by RNA-seq in Platycodon grandiflorum. Genome 2015, 58, 441–451. [Google Scholar] [CrossRef]
  11. Su, X.; Liu, Y.; Han, L.; Wang, Z.; Cao, M.; Wu, L.; Jiang, W.; Meng, F.; Guo, X.; Yu, N.; et al. A candidate gene identified in converting platycoside E to platycodin D from Platycodon grandiflorus by transcriptome and main metabolites analysis. Sci. Rep. 2021, 11, 9810. [Google Scholar] [CrossRef]
  12. Wang, F.; Dong, Q.; Gao, Z.; Zhou, B.; Bao, X. Characterisation of a novel alphaendornavirus isolated from balloon flower (Platycodon grandiflorus). Arch. Virol. 2020, 165, 1023–1026. [Google Scholar] [CrossRef]
  13. Bennett, B.C.; Balick, M.J. Phytomedicine 101: Plant taxonomy for preclinical and clinical medicinal plant researchers. J. Soc. Integr. Oncol. 2008, 6, 150–157. [Google Scholar] [PubMed]
  14. Jia, Y.; Chen, S.; Chen, W.; Zhang, P.; Su, Z.; Zhang, L.; Xu, M.; Guo, L. A chromosome-level reference genome of Chinese balloon flower (Platycodon grandiflorus). Front. Genet. 2022, 13, 869784. [Google Scholar] [CrossRef] [PubMed]
  15. Kim, J.; Kang, S.H.; Park, S.G.; Yang, T.J.; Lee, Y.; Kim, O.T.; Chung, O.; Lee, J.; Choi, J.P.; Kwon, S.J.; et al. Whole-genome, transcriptome, and methylome analyses provide insights into the evolution of Platycoside biosynthesis in Platycodon grandiflorus, a medicinal plant. Hortic. Res. 2020, 7, 112. [Google Scholar] [CrossRef]
  16. Yu, H.; Liu, M.; Yin, M.; Shan, T.; Peng, H.; Wang, J.; Chang, X.; Peng, D.; Zha, L.; Gui, S. Transcriptome analysis identifies putative genes involved in triterpenoid biosynthesis in Platycodon grandiflorus. Planta 2021, 254, 34. [Google Scholar] [CrossRef] [PubMed]
  17. Dumschott, K.; Schmidt, M.H.; Chawla, H.S.; Snowdon, R.; Usadel, B. Oxford Nanopore Sequencing: New opportunities for plant genomics? J. Exp. Bot. 2020, 71, 5313–5322. [Google Scholar] [CrossRef]
  18. Tamura, K.; Teranishi, Y.; Ueda, S.; Suzuki, H.; Kawano, N.; Yoshimatsu, K.; Saito, K.; Kawahara, N.; Muranaka, T.; Seki, H. Cytochrome P450 monooxygenase CYP716A141 is a unique β-amyrin C-16β oxidase involved in triterpenoid saponin biosynthesis in Platycodon grandiflorus. Plant Cell Physiol. 2017, 58, 1119. [Google Scholar] [CrossRef] [Green Version]
  19. Nyakudya, E.; Jeong, J.H.; Lee, N.K.; Jeong, Y.S. Platycosides from the roots of Platycodon grandiflorum and their health benefits. Prev. Nutr. Food Sci. 2014, 19, 59–68. [Google Scholar] [CrossRef]
  20. Li, T.; Chen, X.; Chen, X.; Ma, D.L.; Leung, C.H.; Lu, J.J. Platycodin D potentiates proliferation inhibition and apoptosis induction upon AKT inhibition via feedback blockade in non-small cell lung cancer cells. Sci. Rep. 2016, 6, 37997. [Google Scholar] [CrossRef] [Green Version]
  21. Khan, M.; Maryam, A.; Zhang, H.; Mehmood, T.; Ma, T. Killing cancer with platycodin D through multiple mechanisms. J. Cell. Mol. Med. 2016, 20, 389–402. [Google Scholar] [CrossRef] [PubMed]
  22. Zhang, D.; Li, W.; Xia, E.H.; Zhang, Q.J.; Liu, Y.; Zhang, Y.; Tong, Y.; Zhao, Y.; Niu, Y.C.; Xu, J.H.; et al. The Medicinal herb Panax notoginseng genome provides insights into ginsenoside biosynthesis and genome evolution. Mol. Plant 2017, 10, 903–907. [Google Scholar] [CrossRef] [Green Version]
  23. Busta, L.; Serra, O.; Kim, O.T.; Molinas, M.; Peré-Fossoul, I.; Figueras, M.; Jetter, R. Oxidosqualene cyclases involved in the biosynthesis of triterpenoids in Quercus suber cork. Sci. Rep. 2020, 10, 8011. [Google Scholar] [CrossRef]
  24. Seki, H.; Tamura, K.; Muranaka, T. P450s and UGTs: Key Players in the Structural Diversity of Triterpenoid Saponins. Plant Cell Physiol. 2015, 56, 1463–1471. [Google Scholar] [CrossRef] [Green Version]
  25. Ashour, A.S.; El Aziz, M.M.A.; Gomha Melad, A.S. A review on saponins from medicinal plants: Chemistry, isolation, and determination. J. Nanomed. Res. 2019, 7, 282–288. [Google Scholar] [CrossRef] [Green Version]
  26. Kumar, G.; Gupta, K.; Pathania, S.; Swarnkar, M.K.; Rattan, U.K.; Singh, G.; Sharma, R.K.; Singh, A.K. Chilling Affects Phytohormone and Post-Embryonic Development Pathways during Bud Break and Fruit Set in Apple (Malus domestica Borkh.). Sci. Rep. 2017, 7, 42593. [Google Scholar] [CrossRef] [Green Version]
  27. Choi, H.S.; Han, J.Y.; Choi, Y.E. Identification of triterpenes and functional characterization of oxidosqualene cyclases involved in triterpene biosynthesis in lettuce (Lactuca sativa). Plant Sci. 2020, 301, 110656. [Google Scholar] [CrossRef]
  28. Na, Y.C.; Ha, Y.W.; Kim, Y.S.; Kim, K.J. Structural analysis of platycosides in Platycodi Radix by liquid chromatography/electrospray ionization-tandem mass spectrometry. J. Chromatogr. 2008, 1189, 467–475. [Google Scholar] [CrossRef] [PubMed]
  29. Wang, W.; Zhao, Z.J.; Xu, Y.; Qian, X.; Zhong, J.J. Efficient induction of ginsenoside biosynthesis and alteration of ginsenoside heterogeneity in cell cultures of Panax notoginseng by using chemically synthesized 2-hydroxyethyl jasmonate. Appl. Microbiol. Biotechnol. 2006, 70, 298–307. [Google Scholar] [CrossRef] [PubMed]
  30. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [Green Version]
  31. Marçais, G.; Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 2011, 27, 764–770. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Ranallo-Benavidez, T.R.; Jaron, K.S.; Schatz, M.C. GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nat. Commun. 2020, 11, 1432. [Google Scholar] [CrossRef] [Green Version]
  33. Koren, S.; Walenz, B.P.; Berlin, K.; Miller, J.R.; Bergman, N.H.; Phillippy, A.M. Canu: Scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 2017, 27, 722–736. [Google Scholar] [CrossRef] [Green Version]
  34. Liu, H.; Wu, S.; Li, A.; Ruan, J. SMARTdenovo: A De Novo Assembler Using Long Noisy Reads. Gigabyte 2021, 1–9. [Google Scholar] [CrossRef]
  35. Walker, B.J.; Abeel, T.; Shea, T.; Priest, M.; Abouelliel, A.; Sakthikumar, S.; Cuomo, C.A.; Zeng, Q.; Wortman, J.; Young, S.K.; et al. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 2014, 9, e112963. [Google Scholar] [CrossRef]
  36. Kang, S.H.; Kim, B.; Choi, B.S.; Lee, H.O.; Kim, N.H.; Lee, S.J.; Kim, H.S.; Shin, M.J.; Kim, H.W.; Nam, K.; et al. Genome Assembly and Annotation of Soft-Shelled Adlay (Coix Lacryma-jobi Variety ma-yuen), a Cereal and Medicinal Crop in the Poaceae Family. Front. Plant Sci. 2020, 11, 630. [Google Scholar] [CrossRef] [PubMed]
  37. Roach, M.J.; Schmidt, S.A.; Borneman, A.R. Purge Haplotigs: Allelic contig reassignment for third-gen diploid genome assemblies. BMC Bioinform. 2018, 19, 460. [Google Scholar] [CrossRef]
  38. Li, H.; Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 2010, 26, 589–595. [Google Scholar] [CrossRef] [Green Version]
  39. Bickhart, D.M.; Rosen, B.D.; Koren, S.; Sayre, B.L.; Hastie, A.R.; Chan, S.; Lee, J.; Lam, E.T.; Liachko, I.; Sullivan, S.T.; et al. Single-molecule sequencing and chromatin conformation capture enable de novo reference assembly of the domestic goat genome. Nat. Genet. 2017, 49, 643–650. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. 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 2015, 31, 3210–3212. [Google Scholar] [CrossRef] [Green Version]
  41. Grabherr, M.G.; Haas, B.J.; Yassour, M.; Levin, J.Z.; Thompson, D.A.; Amit, I.; Adiconis, X.; Fan, L.; Raychowdhury, R.; Zeng, Q.; et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 2011, 29, 644–652. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Xu, L.; Dong, Z.; Fang, L.; Luo, Y.; Wei, Z.; Guo, H.; Zhang, G.; Gu, Y.Q.; Coleman-Derr, D.; Xia, Q.; et al. OrthoVenn2: A web server for whole-genome comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res. 2019, 47, W52–W58. [Google Scholar] [CrossRef] [Green Version]
  43. Buchfink, B.; Xie, C.; Huson, D.H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 2015, 12, 59–60. [Google Scholar] [CrossRef]
  44. Götz, S.; García-Gómez, J.M.; Terol, J.; Williams, T.D.; Nagaraj, S.H.; Nueda, M.J.; Robles, M.; Talón, M.; Dopazo, J.; Conesa, A. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008, 36, 3420–3435. [Google Scholar] [CrossRef] [PubMed]
  45. Jones, P.; Binns, D.; Chang, H.Y.; Fraser, M.; Li, W.; McAnulla, C.; McWilliam, H.; Maslen, J.; Mitchell, A.; Nuka, G.; et al. InterProScan 5: Genome-scale protein function classification. Bioinformatics 2014, 30, 1236–1240. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Kim, D.; Langmead, B.; Salzberg, S.L. HISAT: A fast spliced aligner with low memory requirements. Nat. Methods 2015, 12, 357–360. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Anders, S.; Pyl, P.T.; Huber, W. HTSeq—A Python framework to work with high-throughput sequencing data. Bioinformatics 2015, 31, 166–169. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Kolde, R. Package ‘pheatmap’. Bioconductor 2018, 1, 1–6. [Google Scholar]
  49. Moriya, Y.; Itoh, M.; Okuda, S.; Yoshizawa, A.C.; Kanehisa, M. KAAS: An automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007, 35, W182–W185. [Google Scholar] [CrossRef] [Green Version]
Ijms 24 06534 g001 550
Figure 1. Overview of chromosome scale in P. grandiflorum. (A) Circos plot of the nine pseudo-chromosomes. The outermost track (light blue) indicates nine pseudo-chromosomes. The a–d track shows the distribution of genes (a, orange), repeat distribution (b, green), GC contents (c, gray), and GC skew (d, blue) in non-overlapping 100 kb sliding windows. The innermost lines (red) indicate collinear blocks identified within the pseudo-chromosomes. (B) Heatmap of Hi-C assisted assembly. Blue box indicates higher contact probability.
Figure 1. Overview of chromosome scale in P. grandiflorum. (A) Circos plot of the nine pseudo-chromosomes. The outermost track (light blue) indicates nine pseudo-chromosomes. The a–d track shows the distribution of genes (a, orange), repeat distribution (b, green), GC contents (c, gray), and GC skew (d, blue) in non-overlapping 100 kb sliding windows. The innermost lines (red) indicate collinear blocks identified within the pseudo-chromosomes. (B) Heatmap of Hi-C assisted assembly. Blue box indicates higher contact probability.
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Figure 2. Gene distribution of P. grandiflorum. (A) Gene ontology (GO) classification of genes. The 17,286 genes assigned to GO terms were classified in functional categories based on GO terms at level 3. The Y-axis is the number of genes. (B) Shared and unique gene clusters in P. grandiflorum and four related species. Venn diagram illustrating the number of shared and unique gene clusters among P. grandiflorum (Korean bellflower), P. ginseng (Korean ginseng), H. annuus (sunflower), S. lycopersicum (tomato), and Arabidopsis thaliana.
Figure 2. Gene distribution of P. grandiflorum. (A) Gene ontology (GO) classification of genes. The 17,286 genes assigned to GO terms were classified in functional categories based on GO terms at level 3. The Y-axis is the number of genes. (B) Shared and unique gene clusters in P. grandiflorum and four related species. Venn diagram illustrating the number of shared and unique gene clusters among P. grandiflorum (Korean bellflower), P. ginseng (Korean ginseng), H. annuus (sunflower), S. lycopersicum (tomato), and Arabidopsis thaliana.
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Figure 3. Expression patterns of candidate genes involved in the triterpenoid biosynthesis pathway in eight different tissues and three methyl jasmonate (MJ) treatments. Expression values were scaled per row (i.e., per gene) to visualize gene expression peaks among the different samples. Sample names and gene symbols are shown at the bottom and on the right of the heatmap, respectively. RNA sequencing data taken from the SRA database (https://www.ncbi.nlm.nih.gov/bioproject/526590, accessed on 12 December 2022). AFS1: alpha-farnesene synthase, FDFT: farnesyl-diphosphate farnesyltransferase, NADPH: NAD+-dependent farnesol dehydrogenase.
Figure 3. Expression patterns of candidate genes involved in the triterpenoid biosynthesis pathway in eight different tissues and three methyl jasmonate (MJ) treatments. Expression values were scaled per row (i.e., per gene) to visualize gene expression peaks among the different samples. Sample names and gene symbols are shown at the bottom and on the right of the heatmap, respectively. RNA sequencing data taken from the SRA database (https://www.ncbi.nlm.nih.gov/bioproject/526590, accessed on 12 December 2022). AFS1: alpha-farnesene synthase, FDFT: farnesyl-diphosphate farnesyltransferase, NADPH: NAD+-dependent farnesol dehydrogenase.
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Table
Table 1. Genome assembly and gene annotation of P. grandiflorum.
Table 1. Genome assembly and gene annotation of P. grandiflorum.
ParametersValue
Genome assembly
 Number of sequences429 *
 Total length of sequences574,706,410 bp
 N50 length 64,545,416 bp
 Average length1,339,642 bp
 Smallest sequence1071 bp
 Longest sequences93,483,513 bp
 Complete BUSCO97.6%
Gene annotation
 Number of protein-coding genes41,355
 Total length of protein-coding genes40,602,816 bp
 Average gene length982 bp
 Smallest gene length102 bp
 Longest gene length15,303 bp
 Repeat content56.9%
 GC content44.5%
 Functionally annotated80.5%
 Complete BUSCO86.5%
* Nine pseudo-chromosomes and 420 contigs.
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Lee, D.-J.; Choi, J.-W.; Kang, J.-N.; Lee, S.-M.; Park, G.-H.; Kim, C.-K. Chromosome-Scale Genome Assembly and Triterpenoid Saponin Biosynthesis in Korean Bellflower (Platycodon grandiflorum). Int. J. Mol. Sci. 2023, 24, 6534. https://doi.org/10.3390/ijms24076534

AMA Style

Lee D-J, Choi J-W, Kang J-N, Lee S-M, Park G-H, Kim C-K. Chromosome-Scale Genome Assembly and Triterpenoid Saponin Biosynthesis in Korean Bellflower (Platycodon grandiflorum). International Journal of Molecular Sciences. 2023; 24(7):6534. https://doi.org/10.3390/ijms24076534

Chicago/Turabian Style

Lee, Dong-Jun, Ji-Weon Choi, Ji-Nam Kang, Si-Myung Lee, Gyu-Hwang Park, and Chang-Kug Kim. 2023. "Chromosome-Scale Genome Assembly and Triterpenoid Saponin Biosynthesis in Korean Bellflower (Platycodon grandiflorum)" International Journal of Molecular Sciences 24, no. 7: 6534. https://doi.org/10.3390/ijms24076534

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