Search
2024 Volume 4
Article Contents
ARTICLE   Open Access    

Insights into Aquilaria phylogenetics through comparative plastomic resources

  • # Authors contributed equally: Junhu Kan, Liyun Nie, Zenglu Mi

More Information
  • Received: 06 May 2024
    Revised: 06 August 2024
    Accepted: 19 August 2024
    Published online: 04 September 2024
    Forestry Research  4 Article number: e030 (2024)  |  Cite this article
  • The plastid is an essential organelle for its role in photosynthesis and energy production and its genomic information is always employed as important evolutionary markers to explore the relationship among species. Agarwood (Aquilaria), prized for its aromatic blend, finds extensive use in various cultures as incense and perfume. Despite its high economic importance, the phylogenetic status among Aquilaria based on plastomes remains ambiguous due to the lack of available plastomic resources. To bridge this knowledge gap, 22 Aquilaria plastomes were newly sequenced, similar variation patterns in this genus were determined, including a shared 16 bp extension of the rps19 gene and seven highly variable regions. The analysis highlighted the highest prevalence of the A/T motif among simple sequence repeats in these plastomes. Further phylogenetic analysis revealed Aquilaria's phylogenetic implications with an expanded dataset. This comprehensive plastomic resource not only enhances our understanding of Aquilaria evolution but also presents potential molecular markers for DNA barcoding.
  • 加载中
  • Supplemental Table S1 Structural feactures of Aquilaria plastomes.
    Supplemental Fig. S1 Mauve alignment of the 22 Aquilaria samples alliance plastomes, illustrating colliner blocks rearrangement of the accessible gene at the junction of inverted repeat and small-single copy regions. White blocks represent protein-coding gene, black blocks represent transfer RNA (tRNA) genes, and red blocks represent ribosomal RNA (rRNA).
    Supplemental Fig. S2 Comparison of the large single-copy (LSC), small single-copy (SSC), and inverted repeat (IR) region borders of Aquilaria plastomes. The LSC, IR, and SSC regions are depicted with blue, orange, and green blocks, respectively. Gene boxes above the block are transcribed counterclockwise while those below the block are transcribed clockwise.
    Supplemental Fig. S3 Structural comparisons of 37 Aquilaria plastomes with the mVISTA program. X-axis represents the gene position and the y-axis means the con-sistency of the sequences with the numbers ranged from 50% to 100%.
  • [1]

    Eurlings MCM, Gravendeel B. 2005. TrnL-trnF sequence data imply paraphyly of Aquilaria and Gyrinops (Thymelaeaceae) and provide new perspectives for agarwood identification. Plant Systematics and Evolution 254:1−12

    doi: 10.1007/s00606-005-0312-x

    CrossRef   Google Scholar

    [2]

    Hashim YZHY, Kerr PG, Abbas P, Mohd Salleh H. 2016. Aquilaria spp. (agarwood) as source of health beneficial compounds: a review of traditional use, phytochemistry and pharmacology. Journal of Ethnopharmacology 189:331−60

    doi: 10.1016/j.jep.2016.06.055

    CrossRef   Google Scholar

    [3]

    Takamatsu S, Ito M. 2020. Agarotetrol in agarwood: its use in evaluation of agarwood quality. Journal of Natural Medicines 74:98−105

    doi: 10.1007/s11418-019-01349-w

    CrossRef   Google Scholar

    [4]

    López-Sampson A, Page T. 2018. History of use and trade of agarwood. Economic Botany 72:107−29

    doi: 10.1007/s12231-018-9408-4

    CrossRef   Google Scholar

    [5]

    Adam AZ, Lee SY, Mohamed R. 2017. Pharmacological properties of agarwood tea derived from Aquilaria (Thymelaeaceae) leaves: an emerging contemporary herbal drink. Journal of Herbal Medicine 10:37−44

    doi: 10.1016/j.hermed.2017.06.002

    CrossRef   Google Scholar

    [6]

    Liu Y, Chen H, Yang Y, Zhang Z, Wei J, et al. 2013. Whole-tree agarwood-inducing technique: an efficient novel technique for producing high-quality agarwood in cultivated Aquilaria sinensis trees. Molecules 183:3086−106

    doi: 10.3390/molecules18033086

    CrossRef   Google Scholar

    [7]

    Ahmad Mokhtar AM, Mohd Zain HH, Mohammed Muayad TA. 2021. Overview of medicinal properties and toxicities of agarwood species. Educatum Journal of Science, Mathematics and Technology 8:1−16

    doi: 10.37134/ejsmt.vol8.2.1.2021

    CrossRef   Google Scholar

    [8]

    Tsuyuki H, Roberts E. 1965. Zone electrophoretic comparison of muscle myogens and blood proteins of artificial hybrids of Salmonidae with their parental species. Journal of the Fisheries Board of Canada 22:767−73

    doi: 10.1139/f65-067

    CrossRef   Google Scholar

    [9]

    Yin Y, Jiao L, Dong M, Jiang X, Zhang S. 2016. Wood resources, identification, and utilization of agarwood in China. In Agarwood, ed. Mohamed R. Singapore: Springer. pp. 21–38. doi:10.1007/978-981-10-0833-7_2

    [10]

    Wyn L, Anak N. 2010. Wood for the trees: a review of the agarwood (Gaharu) trade in Malaysia. Malaysia: Traffic Southeast Asia. 108 pp.

    [11]

    Uddin MS, Mukul SA, Khan MASA, Alamgir M, Harun MY, et al. 2008. Small-scale agar (Aquilaria agallocha Roxb.) based cottage enterprises in Maulvibazar district of Bangladesh: production, marketing and potential contribution to rural development. Small-scale Forestry 7:139−49

    doi: 10.1007/s11842-008-9046-2

    CrossRef   Google Scholar

    [12]

    Sy EY, Melgar AGB. 2024. The online agarwood trade and seizure analysis in the philippines. Journal of Nature Studies 22(2):12−26

    Google Scholar

    [13]

    Eurlings MCM, van Beek HH, Gravendeel B. 2010. Polymorphic microsatellites for forensic identification of agarwood (Aquilaria crassna). Forensic Science International 197:30−34

    doi: 10.1016/j.forsciint.2009.12.017

    CrossRef   Google Scholar

    [14]

    Naef R. 2011. The volatile and semi-volatile constituents of agarwood, the infected heartwood of Aquilaria species: a review. Flavour and Fragrance Journal 26:73−87

    doi: 10.1002/ffj.2034

    CrossRef   Google Scholar

    [15]

    Dahham SS, Hassan LEA, Ahamed MBK, Majid ASA, Majid AMSA, et al. 2016. In vivo toxicity and antitumor activity of essential oils extract from agarwood (Aquilaria crassna). BMC Complementary and Alternative Medicine 16:236

    doi: 10.1186/s12906-016-1210-1

    CrossRef   Google Scholar

    [16]

    Wu Z, Gu C, Tembrock LR, Zhang D, Ge S. 2017. Characterization of the whole chloroplast genome of Chikusichloa mutica and its comparison with other rice tribe (Oryzeae) species. PLoS One 12:e0177553

    doi: 10.1371/journal.pone.0177553

    CrossRef   Google Scholar

    [17]

    Takamatsu T, Baslam M, Inomata T, Oikawa K, Itoh K, et al. 2018. Optimized method of extracting rice chloroplast DNA for high-quality plastome resequencing and de novo assembly. Frontiers in Plant Science 9:266

    doi: 10.3389/fpls.2018.00266

    CrossRef   Google Scholar

    [18]

    Zhao J, Zhang X, Hong Y, Liu Y. 2016. Chloroplast in plant-virus interaction. Frontiers in Microbiology 7:1565

    doi: 10.3389/fmicb.2016.01565

    CrossRef   Google Scholar

    [19]

    Ding H, Han S, Ye Y, Bi D, Zhang S, et al. 2022. Ten plastomes of Crassula (Crassulaceae) and phylogenetic implications. Biology 11:1779

    doi: 10.3390/biology11121779

    CrossRef   Google Scholar

    [20]

    Zheng S, Poczai P, Hyvönen J, Tang J, Amiryousefi A. 2020. Chloroplot: an online program for the versatile plotting of organelle genomes. Frontiers in Genetics 11:576124

    doi: 10.3389/fgene.2020.576124

    CrossRef   Google Scholar

    [21]

    Sheng J, Yan M, Wang J, Zhao L, Zhou F, et al. 2021. The complete chloroplast genome sequences of five Miscanthus species, and comparative analyses with other grass plastomes. Industrial Crops and Products 162:113248

    doi: 10.1016/j.indcrop.2021.113248

    CrossRef   Google Scholar

    [22]

    Xie C, An W, Liu S, Huang Y, Yang Z, et al. 2021. Comparative genomic study on the complete plastomes of four officinal Ardisia species in China. Scientific Reports 11:22239

    doi: 10.1038/s41598-021-01561-3

    CrossRef   Google Scholar

    [23]

    Yan XL, Kan SL, Wang MX, Li YY, Tembrock LR, et al. 2024. Genetic diversity and evolution of the plastome in allotetraploid cotton (Gossypium spp.). Journal of Systematics and Evolution 00:Early View

    doi: 10.1111/jse.13070

    CrossRef   Google Scholar

    [24]

    Zhang S, Han S, Bi D, Yang J, Ge W, et al. 2024. Intraspecific and intrageneric genomic variation across three Sedum species (Crassulaceae): a plastomic perspective. Genes 15:444

    doi: 10.3390/genes15040444

    CrossRef   Google Scholar

    [25]

    Kan J, Zhang S, Wu Z, Bi D. 2024. Exploring plastomic resources in Sempervivum (Crassulaceae): implications for phylogenetics. Genes 15:441

    doi: 10.3390/genes15040441

    CrossRef   Google Scholar

    [26]

    Wang J, Liao X, Li Y, Ye Y, Xing G, et al. 2023. Comparative plastomes of Curcuma alismatifolia (Zingiberaceae) reveal diversified patterns among 56 different cut-flower cultivars. Genes 14:1743

    doi: 10.3390/genes14091743

    CrossRef   Google Scholar

    [27]

    Wang J, Kan S, Liao X, Zhou J, Tembrock LR, et al. 2024. Plant organellar genomes: much done, much more to do. Trends in Plant Science 29:754−69

    doi: 10.1016/j.tplants.2023.12.014

    CrossRef   Google Scholar

    [28]

    Farah AH, Lee SY, Gao Z, Yao TL, Madon M, et al. 2018. Genome size, molecular phylogeny, and evolutionary history of the tribe Aquilarieae (Thymelaeaceae), the natural source of agarwood. Frontiers in Plant Science 9:712

    doi: 10.3389/fpls.2018.00712

    CrossRef   Google Scholar

    [29]

    Lee SY, Turjaman M, Chaveerach A, Subasinghe S, Fan Q, et al. 2022. Phylogenetic relationships of Aquilaria and Gyrinops (Thymelaeaceae) revisited: evidence from complete plastid genomes. Botanical Journal of the Linnean Society 200:344−59

    doi: 10.1093/botlinnean/boac014

    CrossRef   Google Scholar

    [30]

    Porebski S, Bailey LG, Baum BR. 1997. Modification of a CTAB DNA extraction protocol for plants containing high polysaccharide and polyphenol components. Plant Molecular Biology Reporter 15:8−15

    doi: 10.1007/BF02772108

    CrossRef   Google Scholar

    [31]

    Jin JJ, Yu WB, Yang JB, Song Y, DePamphilis CW, et al. 2020. GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes. Genome Biology 21:241

    doi: 10.1186/s13059-020-02154-5

    CrossRef   Google Scholar

    [32]

    Shi L, Chen H, Jiang M, Wang L, Wu X, et al. 2019. CPGAVAS2, an integrated plastome sequence annotator and analyzer. Nucleic Acids Research 47:W65−W73

    doi: 10.1093/nar/gkz345

    CrossRef   Google Scholar

    [33]

    Greiner S, Lehwark P, Bock R. 2019. OrganellarGenomeDRAW (OGDRAW) version 1.3. 1: expanded toolkit for the graphical visualization of organellar genomes. Nucleic Acids Research 47:W59−W64

    doi: 10.1093/nar/gkz238

    CrossRef   Google Scholar

    [34]

    Li H, Guo Q, Xu L, Gao H, Liu L, et al. 2023. CPJSdraw: analysis and visualization of junction sites of chloroplast genomes. PeerJ 11:e15326

    doi: 10.7717/peerj.15326

    CrossRef   Google Scholar

    [35]

    Darling ACE, Mau B, Blattner FR, Perna NT. 2004. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Research 14:1394−403

    doi: 10.1101/gr.2289704

    CrossRef   Google Scholar

    [36]

    Frazer KA, Pachter L, Poliakov A, Rubin EM, Dubchak I. 2004. VISTA: computational tools for comparative genomics. Nucleic Acids Research 32:W273−W279

    doi: 10.1093/nar/gkh458

    CrossRef   Google Scholar

    [37]

    Rozas J, Ferrer-Mata A, Sánchez-DelBarrio JC, Guirao-Rico S, Librado P, et al. 2017. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Molecular Biology and Evolution 34:3299−302

    doi: 10.1093/molbev/msx248

    CrossRef   Google Scholar

    [38]

    Kurtz S, Choudhuri JV, Ohlebusch E, Schleiermacher C, Stoye J, et al. 2001. REPuter: the manifold applications of repeat analysis on a genomic scale. Nucleic Acids Research 29:4633−42

    doi: 10.1093/nar/29.22.4633

    CrossRef   Google Scholar

    [39]

    Beier S, Thiel T, Münch T, Scholz U, Mascher M. 2017. MISA-web: a web server for microsatellite prediction. Bioinformatics 33:2583−85

    doi: 10.1093/bioinformatics/btx198

    CrossRef   Google Scholar

    [40]

    Xia X. 2017. DAMBE6: new tools for microbial genomics, phylogenetics, and molecular evolution. Journal of Heredity 108:431−37

    doi: 10.1093/jhered/esx033

    CrossRef   Google Scholar

    [41]

    Katoh K, Standley DM. 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular Biology and Evolution 30:772−80

    doi: 10.1093/molbev/mst010

    CrossRef   Google Scholar

    [42]

    Yang Z. 2007. PAML 4: phylogenetic analysis by maximum likelihood. Molecular Biology and Evolution 24:1586−91

    doi: 10.1093/molbev/msm088

    CrossRef   Google Scholar

    [43]

    Stamatakis A. 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312−13

    doi: 10.1093/bioinformatics/btu033

    CrossRef   Google Scholar

    [44]

    Ronquist F, Teslenko M, Van Der Mark P, Ayres DL, Darling A, et al. 2012. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic Biology 61:539−42

    doi: 10.1093/sysbio/sys029

    CrossRef   Google Scholar

    [45]

    Darriba D, Posada D, Kozlov AM, Stamatakis A, Morel B, et al. 2020. ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models. Molecular Biology and Evolution 37:291−94

    doi: 10.1093/molbev/msz189

    CrossRef   Google Scholar

    [46]

    Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. 2018. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Systematic Biology 67:901−04

    doi: 10.1093/sysbio/syy032

    CrossRef   Google Scholar

    [47]

    Hishamuddin MS, Lee SY, Ng WL, Ramlee SI, Lamasudin DU, et al. 2020. Comparison of eight complete chloroplast genomes of the endangered Aquilaria tree species (Thymelaeaceae) and their phylogenetic relationships. Scientific Reports 10:13034

    doi: 10.1038/s41598-020-70030-0

    CrossRef   Google Scholar

    [48]

    Zheng G, Wei L, Ma L, Wu Z, Gu C, et al. 2020. Comparative analyses of chloroplast genomes from 13 Lagerstroemia (Lythraceae) species: identification of highly divergent regions and inference of phylogenetic relationships. Plant Molecular Biology 102:659−76

    doi: 10.1007/s11103-020-00972-6

    CrossRef   Google Scholar

    [49]

    Abdullah, Mehmood F, Shahzadi I, Waseem S, Mirza B, et al. 2020. Chloroplast genome of Hibiscus rosa-sinensis (Malvaceae): comparative analyses and identification of mutational hotspots. Genomics 112:581−91

    doi: 10.1016/j.ygeno.2019.04.010

    CrossRef   Google Scholar

    [50]

    Wang J, Fu GF, Tembrock LR, Liao XZ, Ge S, et al. 2023. Mutational meltdown or controlled chain reaction: The dynamics of rapid plastome evolution in the hyperdiversity of Poaceae. Journal of Systematics and Evolution 61:328−44

    doi: 10.1111/jse.12854

    CrossRef   Google Scholar

    [51]

    Zhou J, Zhang S, Wang J, Shen H, Ai B, et al. 2021. Chloroplast genomes in Populus (Salicaceae): comparisons from an intensively sampled genus reveal dynamic patterns of evolution. Scientific Reports 11:9471

    doi: 10.1038/s41598-021-88160-4

    CrossRef   Google Scholar

    [52]

    He L, Zhang Y, Lee SY. 2021. Complete plastomes of six species of Wikstroemia (Thymelaeaceae) reveal paraphyly with the monotypic genus Stellera. Scientific Reports 11:13608

    doi: 10.1038/s41598-021-93057-3

    CrossRef   Google Scholar

    [53]

    Qian S, Zhang Y, Lee SY. 2021. Comparative analysis of complete chloroplast genome sequences in Edgeworthia (Thymelaeaceae) and new insights into phylogenetic relationships. Frontiers in Genetics 12:643552

    doi: 10.3389/fgene.2021.643552

    CrossRef   Google Scholar

    [54]

    Bakewell MA, Shi P, Zhang J. 2007. More genes underwent positive selection in chimpanzee evolution than in human evolution. Proceedings of the National Academy of Sciences of the United States of America 104:7489−94

    doi: 10.1073/pnas.0701705104

    CrossRef   Google Scholar

    [55]

    Ai B, Gao Y, Zhang X, Tao J, Kang M, et al. 2015. Comparative transcriptome resources of eleven Primulina species, a group of 'stone plants' from a biodiversity hot spot. Molecular Ecology Resources 15:619−32

    doi: 10.1111/1755-0998.12333

    CrossRef   Google Scholar

    [56]

    Hurst LD. 2002. The Ka/Ks ratio: diagnosing the form of sequence evolution. Trends in Genetics 18:486−87

    doi: 10.1016/S0168-9525(02)02722-1

    CrossRef   Google Scholar

    [57]

    Zhang YH, Huang Y, Li ZM, Zhang SD. 2019. Characterization of the complete chloroplast genome of the vulnerable agarwood tree, Aquilaria yunnanensis (Thymelaeaceae). Conservation Genetics Resources 11:161−64

    doi: 10.1007/s12686-018-0989-0

    CrossRef   Google Scholar

    [58]

    Guo L, Guo S, Xu J, He L, Carlson JE, et al. 2020. Phylogenetic analysis based on chloroplast genome uncover evolutionary relationship of all the nine species and six cultivars of tree peony. Industrial Crops and Products 153:112567

    doi: 10.1016/j.indcrop.2020.112567

    CrossRef   Google Scholar

    [59]

    Sun J, Wang Y, Liu Y, Xu C, Yuan Q, et al. 2020. Evolutionary and phylogenetic aspects of the chloroplast genome of Chaenomeles species. Scientific Reports 10:11466

    doi: 10.1038/s41598-020-67943-1

    CrossRef   Google Scholar

    [60]

    Li E, Liu K, Deng R, Gao Y, Liu X, et al. 2023. Insights into the phylogeny and chloroplast genome evolution of Eriocaulon (Eriocaulaceae). BMC Plant Biology 23:32

    doi: 10.1186/s12870-023-04034-z

    CrossRef   Google Scholar

    [61]

    Liang H, Zhang Y, Deng J, Gao G, Ding C, et al. 2020. The complete chloroplast genome sequences of 14 Curcuma species: insights into genome evolution and phylogenetic relationships within Zingiberales. Frontiers in Genetics 11:802

    doi: 10.3389/fgene.2020.00802

    CrossRef   Google Scholar

    [62]

    Dong WL, Wang RN, Zhang NY, Fan WB, Fang MF, et al. 2018. Molecular evolution of chloroplast genomes of orchid species: insights into phylogenetic relationship and adaptive evolution. International Journal of Molecular Sciences 19:716

    doi: 10.3390/ijms19030716

    CrossRef   Google Scholar

    [63]

    Du F, Li Y, Xu K. 2023. Phylogeny and evolution of Cocconeiopsis (Cocconeidaceae) as revealed by complete chloroplast and mitochondrial genomes. International Journal of Molecular Sciences 25:266

    doi: 10.3390/ijms25010266

    CrossRef   Google Scholar

    [64]

    Ahmad S, Kaul T, Chitkara P, Raza K. 2023. Comparative insight into rice chloroplasts genome: mutational phylogenomics reveals Echinochloa oryzicola as the ongoing progenitor of rice. Genetic Resources and Crop Evolution 70:869−85

    doi: 10.1007/s10722-022-01471-x

    CrossRef   Google Scholar

    [65]

    Tomitani A, Okada K, Miyashita H, Matthijs HCP, Ohno T, et al. 1999. Chlorophyll b and phycobilins in the common ancestor of cyanobacteria and chloroplasts. Nature 400:159−62

    doi: 10.1038/22101

    CrossRef   Google Scholar

    [66]

    Li S, Duan W, Zhao J, Jing Y, Feng M, et al. 2022. Comparative analysis of chloroplast genome in Saccharum spp. and related members of 'Saccharum Complex'. International Journal of Molecular Sciences 23:7661

    doi: 10.3390/ijms23147661

    CrossRef   Google Scholar

    [67]

    Yan L, Wang H, Huang X, Li Y, Yue Y, et al. 2022. Chloroplast genomes of genus Tilia: comparative genomics and molecular evolution. Frontiers in Genetics 13:925726

    doi: 10.3389/fgene.2022.925726

    CrossRef   Google Scholar

  • Cite this article

    Kan J, Nie L, Mi Z, Liu X, Xu D, et al. 2024. Insights into Aquilaria phylogenetics through comparative plastomic resources. Forestry Research 4: e030 doi: 10.48130/forres-0024-0028
    Kan J, Nie L, Mi Z, Liu X, Xu D, et al. 2024. Insights into Aquilaria phylogenetics through comparative plastomic resources. Forestry Research 4: e030 doi: 10.48130/forres-0024-0028

Figures(6)  /  Tables(1)

Article Metrics

Article views(959) PDF downloads(200)

ARTICLE   Open Access    

Insights into Aquilaria phylogenetics through comparative plastomic resources

Forestry Research  4 Article number: e030  (2024)  |  Cite this article

Abstract: The plastid is an essential organelle for its role in photosynthesis and energy production and its genomic information is always employed as important evolutionary markers to explore the relationship among species. Agarwood (Aquilaria), prized for its aromatic blend, finds extensive use in various cultures as incense and perfume. Despite its high economic importance, the phylogenetic status among Aquilaria based on plastomes remains ambiguous due to the lack of available plastomic resources. To bridge this knowledge gap, 22 Aquilaria plastomes were newly sequenced, similar variation patterns in this genus were determined, including a shared 16 bp extension of the rps19 gene and seven highly variable regions. The analysis highlighted the highest prevalence of the A/T motif among simple sequence repeats in these plastomes. Further phylogenetic analysis revealed Aquilaria's phylogenetic implications with an expanded dataset. This comprehensive plastomic resource not only enhances our understanding of Aquilaria evolution but also presents potential molecular markers for DNA barcoding.

    • Agarwood, a precious aromatic blend, is produced through natural or induced injury to plants within the Aquilaria or Gyrinops genus of the Thymelaeaceae family[1]. As sap seeps from tree wounds mixed with the white wood, a gradual transformation occurs, leading to the development of a distinctive yellow-brown or black-brown wood–oil mixture, thus giving rise to agarwood[2]. Renowned for its extraordinary fragrance, agarwood is widely utilized as both incense and perfume across numerous cultures[3,4]. Agarwood from various varieties exhibits distinct medicinal properties, boasting significant pharmacological effects, clinical efficacy, and health benefits[58]. Its exorbitant value has spurred numerous international trades, with annual trading volumes reaching hundreds of tons and trading scales exceeding millions of dollars[911]. However, its heightened demand has fueled illegal logging and non-selective felling, exacerbated by the scarcity of naturally occurring agarwood trees in the wild[12,13]. At present, Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITS) lists 23 species of Aquilaria plants and eight species of Gyrinops plants, distributed across countries such as China, Indonesia, Malaysia, India, the Philippines, Cambodia, Vietnam, Laos, Thailand, Papua New Guinea, and Singapore[14]. Currently, the agarwood circulating in the market is primarily sourced from several agarwood plants, notably A. sinensis, A. malaccensis, and A. crassna[15].

      When the morphological differences are evident, utilizing such markers offer advantages in terms of easy recognition and understanding, as well as simplicity and intuitiveness. However, since commercially traded agarwood primarily exists in the form of traditional Chinese patent medicines, simple preparations, and wood, often devoid of key morphological components (especially flowers and fruits), there arises a need for an effective method to distinguish between different agarwood species. Plastids, organelles within plant cells, play important roles in photosynthesis and energy generation[1618]. Typically, the plastome presents a conserved quadripartite circular structure, consisting of two single-copy (SC) regions [large single-copy (LSC) and small single-copy (SSC) regions] and two inverted repeat (IR) regions[1922]. Plastomes serve as effective tools for unveiling phylogenetic relationships among plants[2327]. Despite the rapid advancement of high-throughput sequencing technologies, which has resulted in the release of thousands of plastomes in public databases, the number of plastomes from the Aquilaria genus remains limited. This scarcity of plastomic data has impeded progress in understanding the evolutionary status of Aquilaria.

      Although many previous studies have attempted to determine the phylogenetic status of Aquilaria, the lack of comprehensive genetic data has limited their efficacy. For instance, Farah et al.[28] utilized five chloroplast loci (matK, rbcL, trnL intron, trnL-trnF, and psbC-trnS), along with the internal transcribed spacer (ITS) region, in their analysis of Aquilaria. However, discrepancies emerged between the phylogenetic trees constructed from these two datasets. Notably, while A. agallocha was identified as the sister species to A. sinensis based on chloroplast loci, the ITS data revealed a different scenario, with A. sinensis clustering together with A. yunnanensis. A recent study[29] further revealed a distinct phylogenetic relationship among Aquilaria species, which expanded the analysis by including the plastome of A. rugosa, resulting in notable changes to the relationships among A. sinensis, A. yunnanensis, and A. agallocha. Additionally, the phylogenetic status of A. crassna appeared ambiguous, as different varieties of this species did not cluster together. Specifically, A. crassna (MK779998) exhibited a closer phylogenetic relationship with A. subintegra (MN147871) than to A. crassna (MN125348) varieties. Given these debates and uncertainties, there is a pressing need for a more comprehensive phylogenetic study to provide novel insights into the evolutionary relationships within the Aquilaria genus.

      In this study, novel sequencing of 22 complete plastomes of Aquilaria was conducted, which were combined with 15 published Aquilaria plastomes. Subsequently, this dataset was utilized to conduct comparative genomic and phylogenetic analyses, aiming to achieve three primary objectives: (1) addressing the gap of insufficient plastomic resources within the Aquilaria genus and gain deeper insights into its evolutionary patterns; (2) identification of highly variable regions (HVRs) suitable for DNA barcode-based identification; and (3) performing a phylogenetic analysis to infer the relationships among Aquilaria species using an expanded dataset.

    • Fresh leaves from five A. sinensis samples were collected from the Xishuangbanna Tropical Botanical Garden of the Chinese Academy of Sciences (21°55'55" N, 101°15' 40" E). Additionally, eight A. sinensis samples were collected from Jianfeng, Hainan, China (19°47'48" N, 109°48'37" E), while three samples of A. sinensis were collected from the Guangdong Academy of Forestry (23°11'38" N, 113°22'52" E). Moreover, four A. crassna and two A. rugosa samples were obtained from the Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences (22°32'44" N, 114°03'10" E). Genomic DNA extraction from plant samples was conducted using the cetyl trimethylammonium bromide (CTAB) method[30], followed by the sequencing process by BGI Genomics. For library construction, the Illumina TruSeq DNA PCR-Free Library Prep Kit was utilized, with subsequent sequencing carried out using Illumina HiSeq X Ten system.

    • For the de novo assembly of the 22 newly sequenced plastomes, GetOrganelle v.1.6.4 was utilized[31], with a complete plastome of A. sinensis (MN720647) serving as the reference. Genome annotation was conducted using CPGAVAS2[32], and the annotation results were subsequently verified manually. The annotation files were uploaded in Figshare (doi:10.6084/m9.figshare.25713024). Finally, the circular maps of the Aquilaria plastomes were generated using Chloroplot[20], with visualization facilitated by OGDRAW[33].

    • The analysis of the SC and IR borders among the 22 Aquilaria plastomes was conducted using CPJSdraw v1.0[34] to visualize the expansion and contraction of IRs. Gene rearrangement within these plastomes was examined using Mauve v.2.4.0[35]. To facilitate comparative analyses, 15 complete Aquilaria plastomes were downloaded from GenBank and reannotated (Supplemental Table S1). Subsequently, the mVISTA[36] tool was employed to visualize the similarity among the 37 Aquilaria plastomes. Default parameters were utilized for plastome alignment in Shuffle-LAGAN mode. The number of polymorphic sites and nucleotide variability (π) were further evaluated using DnaSP v.6.12[37], employing a step size of 200 bp and a window length of 600 bp.

    • REPuter (https://bibiserv.cebitec.uni-bielefeld.de/reputer) online program was employed[38] to detect large sequence repeats (LSRs), including forward (F), reverse (R), complement (C), and palindrome (P) sequence repeats. Parameters were set for sequences of n ≥ 30 bp, a sequence identity of ≥ 90%, and a Hamming distance of 3. Additionally, simple sequence repeats (SSRs) were identified using the MISA-web (https://webblast.ipk-gatersleben.de/misa/) online program[39]. Thresholds of seven for mononucleotide repeats, four for dinucleotide repeats, and three for tri-, tetra-, and penta-nucleotide repeats were utilized.

    • In DAMABE v7.3.11[40], 79 protein-coding genes (PCGs) were extracted from 37 plastomes, followed by alignment using MAFFT software (v.7.487)[41]. Subsequently, the CodeML in PAML v.4.9[42] was employed to estimate rates of synonymous (Ks) and non-synonymous (Ka) substitution, along with their ratio (Ka/Ks), utilizing a one-ratio model.

      Phylogenetic relationships among 37 Aquilaria samples were inferred based on complete plastomes with maximum likelihood (ML) and Bayesian inference (BI) methods. To root the trees, three samples from the Daphne genus were selected as outgroups. For the ML analysis, RAxML v.8.2.12[43] with the GTRCAT model was employed, performing 1,000 bootstrap replicates to assess node support. Convergence was evaluated using the '-I autoMRE' parameter. For the BI analysis, MrBayes 3.2.7a[44] was utilized. The best models for nucleotide substitutions were selected using ModelTest-NG[45] based on the Bayesian information criterion (BIC). Two trials with four independent Markov chains were run for 10 million generations each, and convergence was verified using Tracer v.1.7.1[46].

    • In this study, the structural features and plastome organizations of 22 newly sequenced Aquilaria plastomes were investigated (Fig. 1, Supplemental Table S1). The length of these plastomes ranged from 174,804 to 175,046 bp, with an overall GC content ranging between 36.70% and 36.71%. Each plastome exhibited a typical quadripartite structure, comprising IRs ranging from 42,095 to 42,172 bp, an SSC region ranging from 3,344 to 3,347 bp and an LSC region ranging from 87,270 to 87,355 bp in size.

      Figure 1. 

      Annotation map of the Aquilaria plastome. Genes listed inside and outside the circle are transcribed clockwise and counterclockwise, respectively, with genes color-coded based on functional classification.

      The plastomes of these Aquilaria samples encoded an identical set of 142 genes (Table 1), comprising 96 PCGs, 38 transfer RNA (tRNA) genes, and eight ribosomal RNA (rRNA) genes. Among them, 64 single-copy PCGs were identified, with 16 PCGs located in the IR regions. Additionally, four rRNA genes (rrn4.5, rrn23, rrn5, and rrn16) and eight tRNA genes (trnA-UGC, trnI-CAU, trnI-GAU, trnL-CAA, trnL-UAG, trnN-GUU, trnR-ACG, and trnV-GAC) were found to have two copies in IR regions. Introns were detected in 10 PCGs and six tRNA genes. Notably, two PCGs, ycf3, and trans-spliced rps12 (characterized by the first exon located in the LSC region and the other two in the IR regions) contained two introns. These findings underscore a highly conserved genome structure and gene content across Aquilaria plastomes.

      Table 1.  Genes present within Aquilaria plastomes.

      Category Group of genes Names of genes
      Photosynthesis Subunits of photosystem I psaA, psaB, psaC(2), psaI, psaJ
      Subunits of photosystem II psbA, psbB, psbC, psbD, psbE, psbF, psbH, psbI, psbJ, psbK, psbL, psbM, psbN, psbT, psbZ
      Subunits of NADH dehydrogenase ndhA*(2), ndhB*(2), ndhC, ndhD(2), ndhE(2), ndhF, ndhG(2), ndhH(2), ndhI(2), ndhJ, ndhK
      Subunits of cytochrome b/f complex petA, petB*, petD*, petG, petL, petN
      Subunits of ATP synthase atpA, atpB, atpE, atpF*, atpH, atpI
      Large subunit of rubisco rbcL
      Subunits photochlorophyllide reductase
      Self-replication Proteins of large ribosomal subunit rpl14, rpl16, rpl2*(2), rpl20, rpl22, rpl23(2), rpl32, rpl33, rpl36
      Proteins of small ribosomal subunit rps11, rps12**(2), rps14, rps15(2), rps16*, rps18, rps19, rps2, rps3, rps4, rps7(2), rps8
      Subunits of RNA polymerase rpoA, rpoB, rpoC1*, rpoC2
      Ribosomal RNAs rrn16(2), rrn23(2), rrn4.5(2), rrn5(2)
      Transfer RNAs trnA-UGC*(2), trnC-GCA, trnD-GUC, trnE-UUC, trnF-GAA, trnG-GCC, trnG-UCC*, trnH-GUG, trnI-CAU(2), trnI-GAU*(2), trnK-UUU*, trnL-CAA(2), trnL-UAA*, trnL-UAG(2), trnM-CAU, trnN-GUU(2), trnP-UGG, trnQ-UUG, trnR-ACG(2), trnR-UCU, trnS-GCU, trnS-GGA, trnS-UGA, trnT-GGU, trnT-UGU, trnV-GAC(2), trnV-UAC*,
      trnW-CCA, trnY-GUA, trnfM-CAU
      Other genes Maturase matK
      Protease clpP
      Envelope membrane protein cemA
      Acetyl-CoA carboxylase accD
      c-type cytochrome synthesis gene ccsA
      Translation initiation factor
      other
      Genes of unknown function Conserved hypothetical chloroplast ORF ycf1(2), ycf15(2), ycf2(2), ycf3**, ycf4
      Gene*: Gene with one intron; Gene**: Gene with two introns; Gene(2): Number of copies of multi-copy genes.
    • The Mauve alignment results (Supplemental Fig. S1) revealed no gene rearrangements in these newly sequenced plastomes, with the plastome of A. malaccensis serving as the reference. To further explore structure variations within the Aquilaria genus, 15 Aquilaria plastomes were downloaded from GenBank for comparative analysis. The junction sites on the boundaries of genomic regions in Aquilaria species, namely LSC/IRb, SSC/IRb, SSC/IRa, and LSC/IRa, are pivotal in chloroplast genome evolution. These junctions were determined using CPJSdraw. As depicted in Fig. 2 (or Supplemental Fig. S2), the boundaries of genomic regions in Aquilaria samples are highly conserved, with only minor variations observed in the junctions and adjacent genes. The rps19 gene was found across both the LSC and IRb regions, with most of its sequence situated in the LSC region. Furthermore, a 16 bp extension of this gene was consistently observed in the IRb region across all Aquilaria plastomes. This 16 bp extension could potentially serve as a genus-special marker for Aquilaria. Moreover, it was observed that the IRb/SSC junction was located within the ndhF gene. Notably, no genes were found spanning the SSC/IRa and IRa/LSC junctions.

      Figure 2. 

      Comparison of the large single-copy (LSC), small single-copy (SSC), and inverted repeat (IR) region borders of Aquilaria plastomes. The LSC, IR, and SSC regions are depicted with blue, orange, and green blocks, respectively. Gene boxes above the block are transcribed counterclockwise while those below the block are transcribed clockwise. (Representative plastomes from Supplemental Fig. S2).

      The overall organization of the plastomes was analyzed using mVISTA, revealing a high degree of conservation among these Aquilaria plastomes (Supplemental Fig. S3). Interestingly, the SC regions exhibited higher divergence compared to the IR regions. Furthermore, it was observed that PCGs displayed a lower level of variation when compared to non-coding regions.

      Furthermore, we identified some variant hotspot regions, primarily comprising intergenic regions and a few gene coding regions such as rps16 and rpoC1. The nucleotide variability (π) values across the analyzed coding and intergenic sequences of the 37 chloroplast genomes ranged from 0 to 0.03037 (Fig. 3). Notably, variation in the SSC region was higher than that in the IR region, consistent with the mVISTA results. Seven regions with π values higher than 0.005, including rps16, rpoC1, psbM-trnD-GUC, ndhC-trnV-UAC, psbJ-petA, ndhF-rpl32, and rpl32-trnL-UAG, were detected. These regions were identified as HVRs in this study. Among them, the coding region of the rps16 gene exhibited a π value exceeding 0.04, while the rpl32-trnL-UAG inter-region possessed the most informative sites. These HVRs have the potential to serve as barcodes for identifying Aquilaria species.

      Figure 3. 

      Comparison of nucleotide variability values among 37 plastomes using window sliding analysis. The x-axis indicates the position of the midpoint of the window, while the y-axis indicates the nucleotide diversity of each window.

    • Nucleotide repeats within chloroplast genomes play a crucial role in plant typing and are widely used as genetic molecular markers in population genetics. Large sequence repeats (LSRs) were identified as repeats with a length of ≥ 30 bp each. A total of 4,765 LSRs were detected across the 37 plastomes, encompassing palindromic repeats (P), forward repeats (F), reverse repeats (R) and complementary repeats (C) (Fig. 4a). Among these, forward repeats were the most prevalent type, with 2,533 occurrences, while complementary repeats were the least common, totaling 46 occurrences.

      Figure 4. 

      (a) Distribution of different types of large sequences repeat (LSRs) in Aquilaria plastomes, including complementary (C), forward (F), palindromic (P), and reverse (R) type repeats. (b) Distribution of distinct types of simple sequence repeats (SSRs) in Aquilaria plastomes.

      In the MISA-web analysis, five types of simple sequence repeats (SSRs) were identified, with mononucleotide repeats comprising the majority (1,775, 59.91%), followed by dinucleotide repeats (477, 16.1%), trinucleotide repeats (294, 9.92%), tetranucleotide repeats (409, 13.80%), and pentanucleotide repeats (8, 0.27%) (Fig. 4b). Among these SSRs, repeat units of A/T, AT/AT, AAAT/ATTT, AAAAT/ATTTT, and AAATT/AATTT accounted for 87.55% of the total, indicating a bias towards A/T bases in SSR composition.

    • Ka/Ks is a valuable metric for evaluating whether PCGs have undergone adaptive evolution. Typically, synonymous nucleotide substitutions occur more frequently than non-synonymous substitutions in most genes of organisms, resulting in Ka/Ks values typically being less than 1. In this study, the Ka/Ks values for the PCGs of these plastomes were calculated. Most of the PCGs exhibited Ka/Ks values of less than 1, indicating that these species were subjected to strong purifying selection during the long-term evolutionary process (Fig. 5). Notably, the expression-related accD gene displayed the highest Ka/Ks value (1.54). This finding suggests that the accD gene may have been influenced by positive selection during the evolutionary process.

      Figure 5. 

      Values of synonymous (Ks) and non-synonymous (Ka) substitution rates for 79 protein-coding genes in Aquilaria.

      To elucidate the phylogenetic relationships within the Aquilaria genus, 22 newly sequenced Aquilaria plastomes were utilized in conjunction with an additional 15 Aquilaria plastomes to reconstruct the phylogenetic tree using ML and BI methods. Additionally, three Daphne samples were selected as outgroups (Fig. 6). The results revealed the formation of five clades within Aquilaria. The newly sequenced A. sinensis plastomes clustered together with published A. sinensis plastomes, forming a monophyletic clade designated as clade 1 (C1). Clade 2 (C2) comprised three A. rugosa plastomes, which clustered together and formed a sister group to A. yunnanensis with high confidence. Clade 3 (C3) consisted of only one species, identified as A. agallocha.

      Figure 6. 

      Phylogenetic tree depicting relationships among Aquilaria species. Red circles indicates bootstrap support (BS) values greater than 80% and posterior probability (PP) values exceeding 1. Yellow circles indicates BS values ranging from 40% to 80%, and PP values ranging from 0.7 to 0.9. Grey circles indicates BS values below 40% and PP values less than 0.7.

      In clade 4 (C4), it was observed that A. crassna (NC043844) clustered together with A. subintegra (MN147871), which aligns with previous research[47]. The newly sequenced A. crassna plastomes also clustered together, demonstrating high consistency. This finding suggests the possibility of hybridization events or misidentification of the published plastome sample (NC043844). It is conceivable that hybridization occurred among these species, with plastomes likely following maternal inheritance, leading to significant disturbance in DNA information within the plastomes. Alternatively, the high similarity in morphology between these species may have contributed to misidentification. Lastly, clade 5 (C5) encompassed five species, mirroring the phylogenetic findings of a previous study[29,47].

    • In this study, the complete plastome sequences of 22 Aquilaria taxa were presented. By integrating these newly sequenced plastomes with an additional 15 Aquilaria published plastomes, a series of comparative analyses within this genus were conducted. The investigation into the location of the SC/IR boundaries offers novel insights into evolutionary studies. The expansion and contraction of IR regions are often associated with various evolutionary events, including gene duplication, loss of gene copies, and the emergence of pseudogenes (such as the ycf1 pseudogene observed in many plants)[48,49]. The substantial variation observed among these boundaries may harbor potential markers for genus/species identification[50,51]. The present research has unveiled a consistent structural feature at the IR/SC boundary in Aquilaria species. Intriguingly, all Aquilaria plastomes analyzed in this study exhibited a 16 bp extension of the rps19 gene in the IRb region. This phenomenon is rarely observed in other species within the Thymelaeaceae family, as it has only been detected in a few species across certain genera[52,53]. In Aquilaria, a consistent 16 bp extension was observed across all examined species, suggesting its potential as a genus-specific marker. Such markers have been utilized for identification previously; for example, the 110 bp expansion of the rps19 gene in the Crassulaceae family serves as a specific family marker[19]. Future studies employing extensive datasets of Thymelaeaceae species may identify additional family-specific identification markers. Furthermore, discrepancies were noted in the plastomes of A. malaccensis (NC041117) and other Aquilaria species, particularly in the positions and transcriptional directions of ndhF and rpl32; their transcribed directions were reversed. These anomalies were primarily attributed to assembly errors. Notably, the same misassembly was found in A. sinensis (NC029243). The loss of rps32 and the incorrect positioning of trnN, ndhF, and ycf1 genes further underscored the erroneous assembly of the plastome. To elucidate the authentic structural patterns of the plastome genome, these inaccurate annotations were substituted with normal data, thereby eliminating potential sources of misinterpretation.

      Furthermore, accD displayed the highest Ka/Ks value of 1.54. Previous research has suggested that adaptive evolution may occur at the molecular level, as evidenced by an elevated Ka/Ks value[54]. Numerous studies have corroborated that a higher Ka/Ks ratio correlates with a more robust positive selection[26,55,56]. Thus, the elevated Ka/Ks ratio observed in accD implies its significant contribution in the adaptation and evolutionary processes within Aquilaria species.

      While previous research has attempted to elucidate the phylogenetic status of the Aquilaria genus, the limited availability of plastomic resources for Aquilaria has left certain issues unresolved. One such point of interest pertains to the relationship among A. sinensis, A. agallocha, and A. yunnanensis. Farah et al.[28] utilized two types of datasets (chloroplast loci and ITS regions) and reported conflicting patterns among these three species. The chloroplast loci data clustered these species into the same clade, with A. agallocha being closer to A. sinensis. Conversely, the evolutionary tree based on ITS regions separated A. sinensis to another clade. Another study[29] also examined these species for phylogenetic analysis, yielding different results. In that study, these species were clustered in the same clade, with A. yunnanensis exhibiting a closer relationship to A. sinensis. Additionally, several studies[1,47,57] have explored phylogenetic relationships in Aquilaria; however, not all of them included all three species of interest. The phylogenetic tree reconstructed in this study mirrored the results of the study conducted by Lee et al.[29] with high confidence. The structure of the phylogenetic tree appeared to be highly influenced by the volume of the dataset; as the number of Aquilaria plastomes were increased, it was anticipated that this result would better elucidate the true relationship among these species.

      Furthermore, of interest was a previous study[47] which revealed that different varieties of A. crassna did not form a monophyletic clade, as A. subintetegra (MN147870) clustered with A. crassna (MK779998, also coded as NC043844). To explore the underlying reason for this discrepancy, four A. crassna plastomes were sequenced. The phylogenetic results unveiled that the newly sequenced A. crassna plastomes in this study clustered together. However, the published A. crassna (NC043844) also clustered with A. subintegra (MN147871), aligning with the findings of the earlier research conducted by Hishamuddin et al.[47]. Chloroplasts, organelles present in plants and some protist cells, possess their own DNA distinct from the nuclear genome. The similarity of the chloroplast genome sequences can unveil phylogenetic relationships and evolutionary history among species[5862], suggesting inheritance from a common ancestor in many cases[6365], as chloroplasts are typically maternally inherited in plants[66,67]. Conversely, similar plastomes may also result from convergent evolution, where analogous chloroplast genome sequences evolve independently on distinct evolutionary trajectories. In the case of A. crassna (NC043844), there is a possibility of incorrect assembly, or even misidentification of the specimen as either A. crassna (NC043844) or A. subintegra (MN147871). Moreover, conducting a pan-plastome study involving A. subintegra and A. crassna could offer a more comprehensive understanding of the relationship between these two species.

      With the augmented dataset of plastomes in this study, a more distinct phylogenetic pattern was unveiled compared to previous research. Besides, although plastomes can provide valuable insights into phylogenetic relationships, the limitations imposed by frequent artificial hybridization are recognized[8]. It is anticipated that future studies integrating data from nuclear genomes, mitogenomes, and plastomes will undoubtedly provide a deeper understanding of the phylogenetic implications within the Aquilaria genus. This study can serve as a valuable example for species identification in trees, highlighting the significance of understanding evolutionary relationships between species or subspecies, given the high similarity among tree species.

    • This study presents the sequencing of 22 Aquilaria plastomes, revealing no gene rearrangements among them. Comparative genomics unveiled a consistent genome size (174,804–175,046 bp) and GC content (36.70%–36.75%) across Aquilaria plastomes. Additionally, seven HVRs were identified, spanning rps16, rpoC1, psbM-trnD-GUC, ndhC-trnV-UAC, psbJ-petA, ndhF-rpl32, and rpl32-trnL-UAG. In examining the IR junction pattern, it was noted that the rps19 gene spans both the LSC and IRb regions, with a 16 bp expansion of the rps19 gene in IRb, potentially serving as a genus-specific marker for Aquilaria. Furthermore, the present analysis identified four types of LSRs and five types of SSRs with a notable A/T bias. The ndhD gene displayed the highest Ka/Ks value of 1.54, indicative of its significant contribution to the adaptation and evolution of Aquilaria species. Finally, the present study elucidated the phylogenetic relationships within Aquilaria and addressed several issues within the genus through an expanded dataset, providing valuable insights into its evolutionary dynamics.

    • The authors confirm contribution to the paper as follows: study conception and design: Wu Z, Hong Z; data collection: Liu X, Xu D, Tembrock LR; analysis and interpretation of results: Kan J, Mi Z, Nie L; draft manuscript preparation: Kan J, Mi Z; organizing and supervising the whole project: Wu Z, Hong Z. All authors reviewed the results and approved the final version of the manuscript.

    • The annotation files of newly assembled Aquilaria plastomes are uploaded to the Figshare website (https://figshare.com/, doi:10.6084/m9.figshare.25713024).

      • This study was funded by Forestry Science and Technology Innovation Project of Guangdong Province (Grant No. 2023KJCX009) and Fundamental Research Funds for the Central Non-profit Research Institution of Chinese Academy of Forestry (Grant No. CAFYBB2021QD003-03). It was also funded by the Science Technology and Innovation Commission of Shenzhen Municipality (Grant No. RCYX20200714114538196) and the Shenzhen Fundamental Research Program (Grant No. JCYJ20220818103212025). This work was also funded by the Guangdong Pearl River Talent Program (Grant No. 2021QN02N792) and the Innovation Program of Chinese Academy of Agricultural Sciences.

      • The authors declare that they have no conflict of interest.

      • # Authors contributed equally: Junhu Kan, Liyun Nie, Zenglu Mi

      • Supplemental Table S1 Structural feactures of Aquilaria plastomes.
      • Supplemental Fig. S1 Mauve alignment of the 22 Aquilaria samples alliance plastomes, illustrating colliner blocks rearrangement of the accessible gene at the junction of inverted repeat and small-single copy regions. White blocks represent protein-coding gene, black blocks represent transfer RNA (tRNA) genes, and red blocks represent ribosomal RNA (rRNA).
      • Supplemental Fig. S2 Comparison of the large single-copy (LSC), small single-copy (SSC), and inverted repeat (IR) region borders of Aquilaria plastomes. The LSC, IR, and SSC regions are depicted with blue, orange, and green blocks, respectively. Gene boxes above the block are transcribed counterclockwise while those below the block are transcribed clockwise.
      • Supplemental Fig. S3 Structural comparisons of 37 Aquilaria plastomes with the mVISTA program. X-axis represents the gene position and the y-axis means the con-sistency of the sequences with the numbers ranged from 50% to 100%.
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (6)  Table (1) References (67)
  • About this article
    Cite this article
    Kan J, Nie L, Mi Z, Liu X, Xu D, et al. 2024. Insights into Aquilaria phylogenetics through comparative plastomic resources. Forestry Research 4: e030 doi: 10.48130/forres-0024-0028
    Kan J, Nie L, Mi Z, Liu X, Xu D, et al. 2024. Insights into Aquilaria phylogenetics through comparative plastomic resources. Forestry Research 4: e030 doi: 10.48130/forres-0024-0028

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return