Plastid genome and composition analysis of two medical ferns: Dryopteris crassirhizoma Nakai and Osmunda japonica Thunb. View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Liang Xu, Yanping Xing, Bing Wang, Chunsheng Liu, Wenquan Wang, Tingguo Kang

ABSTRACT

Background: Dryopteris crassirhizoma Nakai and Osmunda japonica Thunb. are ferns that are popularly used for medicine, as recorded by the Chinese pharmacopoeia, and are distributed in different regions of China. However, O. japonica is not record in the Standards of Chinese Herbal Medicines in Hong Kong. Research on identification methods of D. crassirhizoma and O. japonica is necessary and the phylogenetic position of the two species should be identified. The plastid genome is structurally highly conserved, providing valuable sources of genetic markers for phylogenetic analyses and development of molecule makers for identification. Methods: The plastid genome DNA was extracted from both fern species and then sequenced on the Illumina Hiseq 4000. Sequences were assembled into contigs by SOAPdenovo2.04, aligned to the reference genome using BLAST, and then manually corrected. Genome annotation was performed by the online DOGMA tool. General characteristics of the plastid genomes of the two species were analyzed and compared with closely related species. Additionally, phylogenetical trees were reconstructed by maximum likelihood methods. The content of dryocrassin of the two species were determined according to the Standards of Chinese Herbal Medicines in Hong Kong. Results: The genome structures of D. crassirhizoma and O. japonica have different characteristics including the genome size, the size of each area, gene location, and types. Moreover, the (simple sequence repeats) SSRs of the plastid genomes were more similar to other species in the same genera. Compared with D. fragrans, D. crassirhizoma shows an inversion (approximately 1.6 kb), and O. japonica shows two inversions (1.9 kb and 216 bp). The nucleotide diversity (polymorphism information, Pi) analysis showed that the psbK gene and rpl14-rpl16 region have the highest Pi value in Dryopteris, and the ycf2-CDS3 and rpl14-rpl16 regions show the highest Pi vale in O. japonica. Phylogenetic analyses showed that the two species were grouped in two separate clades from each other, with both individually located with other members of their genus. The marker content of dryocrassin is not found in O. japonica. Conclusions: The study is the first to identify plastid genome features of D. crassirhizoma and O. japonica. The results may provide a theoretical basis for the identification and the application of the two medically important fern species. More... »

PAGES

9

References to SciGraph publications

  • 2007-12. Comparative chloroplast genomics: analyses including new sequences from the angiosperms Nuphar advena and Ranunculus macranthus in BMC GENOMICS
  • 2000-05. Gene Ontology: tool for the unification of biology in NATURE GENETICS
  • 2009-12. Complete chloroplast genome sequence of a tree fern Alsophila spinulosa: insights into evolutionary changes in fern chloroplast genomes in BMC EVOLUTIONARY BIOLOGY
  • 2018-12. Chloroplast genome analyses and genomic resource development for epilithic sister genera Oresitrophe and Mukdenia (Saxifragaceae), using genome skimming data in BMC GENOMICS
  • 2003-12. The COG database: an updated version includes eukaryotes in BMC BIOINFORMATICS
  • 2013-12. Capturing chloroplast variation for molecular ecology studies: a simple next generation sequencing approach applied to a rainforest tree in BMC ECOLOGY
  • 2015-10. Comparative Analysis of Asteraceae Chloroplast Genomes: Structural Organization, RNA Editing and Evolution in PLANT MOLECULAR BIOLOGY REPORTER
  • 2005-03. Chloroplast SSR polymorphisms in the Compositae and the mode of organellar inheritance in Helianthus annuus in THEORETICAL AND APPLIED GENETICS
  • 2017-12. Comparative analysis of inverted repeats of polypod fern (Polypodiales) plastomes reveals two hypervariable regions in BMC PLANT BIOLOGY
  • 2009-12. Patent applications for using DNA technologies to authenticate medicinal herbal material in CHINESE MEDICINE
  • 2012-12. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler in GIGASCIENCE
  • 2008-03. An update on chloroplast genomes in PLANT SYSTEMATICS AND EVOLUTION
  • 2014-12. A chloroplast genomic strategy for designing taxon specific DNA mini-barcodes: a case study on ginsengs in BMC GENETICS
  • 2015-08. Use of chloroplast DNA barcodes to identify Osmunda japonica and its adulterants in PLANT SYSTEMATICS AND EVOLUTION
  • 2013-12. Complete plastid genomes from Ophioglossum californicum, Psilotum nudum, and Equisetum hyemale reveal an ancestral land plant genome structure and resolve the position of Equisetales among monilophytes in BMC EVOLUTIONARY BIOLOGY
  • 2016-12. Chloroplast genomes: diversity, evolution, and applications in genetic engineering in GENOME BIOLOGY
  • 2018-12. Complete chloroplast genome of the medicinal plant Amomum compactum: gene organization, comparative analysis, and phylogenetic relationships within Zingiberales in CHINESE MEDICINE
  • 2001-02. Horsetails and ferns are a monophyletic group and the closest living relatives to seed plants in NATURE
  • 2010-12. Genome-wide analysis of tandem repeats in Daphnia pulex - a comparative approach in BMC GENOMICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13020-019-0230-4

    DOI

    http://dx.doi.org/10.1186/s13020-019-0230-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112767236

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30911328


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Liaoning University of Traditional Chinese Medicine", 
              "id": "https://www.grid.ac/institutes/grid.411464.2", 
              "name": [
                "School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China", 
                "School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Xu", 
            "givenName": "Liang", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Liaoning University of Traditional Chinese Medicine", 
              "id": "https://www.grid.ac/institutes/grid.411464.2", 
              "name": [
                "School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Xing", 
            "givenName": "Yanping", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Liaoning University of Traditional Chinese Medicine", 
              "id": "https://www.grid.ac/institutes/grid.411464.2", 
              "name": [
                "School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wang", 
            "givenName": "Bing", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Beijing University of Chinese Medicine", 
              "id": "https://www.grid.ac/institutes/grid.24695.3c", 
              "name": [
                "School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Liu", 
            "givenName": "Chunsheng", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Tsinghua University", 
              "id": "https://www.grid.ac/institutes/grid.12527.33", 
              "name": [
                "School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China", 
                "Institute of Medicinal Plant Development, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wang", 
            "givenName": "Wenquan", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Liaoning University of Traditional Chinese Medicine", 
              "id": "https://www.grid.ac/institutes/grid.411464.2", 
              "name": [
                "School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kang", 
            "givenName": "Tingguo", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.14348/molcells.2014.2296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000252395"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/database/bar009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002484367"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/dnares/10.2.59", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003499143"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-11-277", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004318568", 
              "https://doi.org/10.1186/1471-2164-11-277"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.arplant.51.1.111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004835401"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1749-8546-4-21", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005119475", 
              "https://doi.org/10.1186/1749-8546-4-21"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2148-13-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006039492", 
              "https://doi.org/10.1186/1471-2148-13-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1640/0002-8444(2007)97[95:tcpgso]2.0.co;2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006115360"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/molbev/msi174", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008885890"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/molbev/msi174", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008885890"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0019119", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011161078"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gene.2015.07.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012222260"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0035071", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012980256"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12863-014-0138-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013030567", 
              "https://doi.org/10.1186/s12863-014-0138-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12863-014-0138-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013030567", 
              "https://doi.org/10.1186/s12863-014-0138-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-4-41", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013163036", 
              "https://doi.org/10.1186/1471-2105-4-41"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0022-2836(05)80360-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013618994"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0012762", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016440387"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2047-217x-1-18", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016521225", 
              "https://doi.org/10.1186/2047-217x-1-18"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkh063", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017271040"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2148-9-130", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020104454", 
              "https://doi.org/10.1186/1471-2148-9-130"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1472-6785-13-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020768419", 
              "https://doi.org/10.1186/1472-6785-13-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp187", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021484173"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3109/19401736.2015.1063131", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021555788"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-9525(97)01223-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022738563"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0169-5347(00)02097-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026229109"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/16.11.1046", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026953484"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkj102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028128110"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-1004-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028676039", 
              "https://doi.org/10.1186/s13059-016-1004-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-1004-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028676039", 
              "https://doi.org/10.1186/s13059-016-1004-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/gbe/evu087", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028892049"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0073053", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029190478"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-8-174", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029379402", 
              "https://doi.org/10.1186/1471-2164-8-174"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00606-007-0608-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029614971", 
              "https://doi.org/10.1007/s00606-007-0608-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00606-007-0608-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029614971", 
              "https://doi.org/10.1007/s00606-007-0608-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.bse.2010.12.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036410108"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkn502", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037164940"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00606-015-1197-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038151245", 
              "https://doi.org/10.1007/s00606-015-1197-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/35054555", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038499798", 
              "https://doi.org/10.1038/35054555"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/35054555", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038499798", 
              "https://doi.org/10.1038/35054555"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.278.5338.631", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039646901"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/genes7120115", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039695896"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11105-015-0853-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041029695", 
              "https://doi.org/10.1007/s11105-015-0853-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/nph.14135", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041145635"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/75556", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044135237", 
              "https://doi.org/10.1038/75556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/75556", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044135237", 
              "https://doi.org/10.1038/75556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/sysbio/syq010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046004748"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/29.22.4633", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046065243"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0000508", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046302972"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/gbe/evt099", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046472038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bth352", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050086076"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3732/ajb.94.3.275", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050985240"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00122-004-1914-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053101193", 
              "https://doi.org/10.1007/s00122-004-1914-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/376817", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058670030"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.12677/bp.2011.12003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064602173"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/molecules22020249", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083696481"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/molecules22020249", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083696481"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/acs.jafc.7b00925", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085615448"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/gbe/evx107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1086005951"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4268/cjcmm20162216", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1087168018"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0184257", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091408573"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12870-017-1195-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100102273", 
              "https://doi.org/10.1186/s12870-017-1195-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13020-018-0164-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100995401", 
              "https://doi.org/10.1186/s13020-018-0164-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-018-4633-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103128552", 
              "https://doi.org/10.1186/s12864-018-4633-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-018-4633-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103128552", 
              "https://doi.org/10.1186/s12864-018-4633-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-018-4633-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103128552", 
              "https://doi.org/10.1186/s12864-018-4633-x"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-12", 
        "datePublishedReg": "2019-12-01", 
        "description": "Background: Dryopteris crassirhizoma Nakai and Osmunda japonica Thunb. are ferns that are popularly used for medicine, as recorded by the Chinese pharmacopoeia, and are distributed in different regions of China. However, O. japonica is not record in the Standards of Chinese Herbal Medicines in Hong Kong. Research on identification methods of D. crassirhizoma and O. japonica is necessary and the phylogenetic position of the two species should be identified. The plastid genome is structurally highly conserved, providing valuable sources of genetic markers for phylogenetic analyses and development of molecule makers for identification.\nMethods: The plastid genome DNA was extracted from both fern species and then sequenced on the Illumina Hiseq 4000. Sequences were assembled into contigs by SOAPdenovo2.04, aligned to the reference genome using BLAST, and then manually corrected. Genome annotation was performed by the online DOGMA tool. General characteristics of the plastid genomes of the two species were analyzed and compared with closely related species. Additionally, phylogenetical trees were reconstructed by maximum likelihood methods. The content of dryocrassin of the two species were determined according to the Standards of Chinese Herbal Medicines in Hong Kong.\nResults: The genome structures of D. crassirhizoma and O. japonica have different characteristics including the genome size, the size of each area, gene location, and types. Moreover, the (simple sequence repeats) SSRs of the plastid genomes were more similar to other species in the same genera. Compared with D. fragrans, D. crassirhizoma shows an inversion (approximately 1.6\u00a0kb), and O. japonica shows two inversions (1.9\u00a0kb and 216\u00a0bp). The nucleotide diversity (polymorphism information, Pi) analysis showed that the psbK gene and rpl14-rpl16 region have the highest Pi value in Dryopteris, and the ycf2-CDS3 and rpl14-rpl16 regions show the highest Pi vale in O. japonica. Phylogenetic analyses showed that the two species were grouped in two separate clades from each other, with both individually located with other members of their genus. The marker content of dryocrassin is not found in O. japonica.\nConclusions: The study is the first to identify plastid genome features of D. crassirhizoma and O. japonica. The results may provide a theoretical basis for the identification and the application of the two medically important fern species.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s13020-019-0230-4", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1313369", 
            "issn": [
              "1991-0150", 
              "1749-8546"
            ], 
            "name": "Chinese Medicine", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "14"
          }
        ], 
        "name": "Plastid genome and composition analysis of two medical ferns: Dryopteris crassirhizoma Nakai and Osmunda japonica Thunb.", 
        "pagination": "9", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "d2c448700a399cec06b8a0671761a2d60ec7a7906985158e24242c0d888536ba"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "30911328"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101265109"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s13020-019-0230-4"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1112767236"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s13020-019-0230-4", 
          "https://app.dimensions.ai/details/publication/pub.1112767236"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T14:00", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000371_0000000371/records_130826_00000006.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1186%2Fs13020-019-0230-4"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13020-019-0230-4'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13020-019-0230-4'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13020-019-0230-4'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13020-019-0230-4'


     

    This table displays all metadata directly associated to this object as RDF triples.

    296 TRIPLES      21 PREDICATES      86 URIs      21 LITERALS      9 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s13020-019-0230-4 schema:about anzsrc-for:06
    2 anzsrc-for:0604
    3 schema:author N688e31c6de084c3483637b44ea1ab559
    4 schema:citation sg:pub.10.1007/s00122-004-1914-3
    5 sg:pub.10.1007/s00606-007-0608-0
    6 sg:pub.10.1007/s00606-015-1197-y
    7 sg:pub.10.1007/s11105-015-0853-2
    8 sg:pub.10.1038/35054555
    9 sg:pub.10.1038/75556
    10 sg:pub.10.1186/1471-2105-4-41
    11 sg:pub.10.1186/1471-2148-13-8
    12 sg:pub.10.1186/1471-2148-9-130
    13 sg:pub.10.1186/1471-2164-11-277
    14 sg:pub.10.1186/1471-2164-8-174
    15 sg:pub.10.1186/1472-6785-13-8
    16 sg:pub.10.1186/1749-8546-4-21
    17 sg:pub.10.1186/2047-217x-1-18
    18 sg:pub.10.1186/s12863-014-0138-z
    19 sg:pub.10.1186/s12864-018-4633-x
    20 sg:pub.10.1186/s12870-017-1195-z
    21 sg:pub.10.1186/s13020-018-0164-2
    22 sg:pub.10.1186/s13059-016-1004-2
    23 https://doi.org/10.1016/j.bse.2010.12.011
    24 https://doi.org/10.1016/j.gene.2015.07.020
    25 https://doi.org/10.1016/s0022-2836(05)80360-2
    26 https://doi.org/10.1016/s0168-9525(97)01223-7
    27 https://doi.org/10.1016/s0169-5347(00)02097-8
    28 https://doi.org/10.1021/acs.jafc.7b00925
    29 https://doi.org/10.1086/376817
    30 https://doi.org/10.1093/bioinformatics/16.11.1046
    31 https://doi.org/10.1093/bioinformatics/bth352
    32 https://doi.org/10.1093/bioinformatics/btp187
    33 https://doi.org/10.1093/database/bar009
    34 https://doi.org/10.1093/dnares/10.2.59
    35 https://doi.org/10.1093/gbe/evt099
    36 https://doi.org/10.1093/gbe/evu087
    37 https://doi.org/10.1093/gbe/evx107
    38 https://doi.org/10.1093/molbev/msi174
    39 https://doi.org/10.1093/nar/29.22.4633
    40 https://doi.org/10.1093/nar/gkh063
    41 https://doi.org/10.1093/nar/gkj102
    42 https://doi.org/10.1093/nar/gkn502
    43 https://doi.org/10.1093/sysbio/syq010
    44 https://doi.org/10.1111/nph.14135
    45 https://doi.org/10.1126/science.278.5338.631
    46 https://doi.org/10.1146/annurev.arplant.51.1.111
    47 https://doi.org/10.12677/bp.2011.12003
    48 https://doi.org/10.1371/journal.pone.0000508
    49 https://doi.org/10.1371/journal.pone.0012762
    50 https://doi.org/10.1371/journal.pone.0019119
    51 https://doi.org/10.1371/journal.pone.0035071
    52 https://doi.org/10.1371/journal.pone.0073053
    53 https://doi.org/10.1371/journal.pone.0184257
    54 https://doi.org/10.14348/molcells.2014.2296
    55 https://doi.org/10.1640/0002-8444(2007)97[95:tcpgso]2.0.co;2
    56 https://doi.org/10.3109/19401736.2015.1063131
    57 https://doi.org/10.3390/genes7120115
    58 https://doi.org/10.3390/molecules22020249
    59 https://doi.org/10.3732/ajb.94.3.275
    60 https://doi.org/10.4268/cjcmm20162216
    61 schema:datePublished 2019-12
    62 schema:datePublishedReg 2019-12-01
    63 schema:description Background: Dryopteris crassirhizoma Nakai and Osmunda japonica Thunb. are ferns that are popularly used for medicine, as recorded by the Chinese pharmacopoeia, and are distributed in different regions of China. However, O. japonica is not record in the Standards of Chinese Herbal Medicines in Hong Kong. Research on identification methods of D. crassirhizoma and O. japonica is necessary and the phylogenetic position of the two species should be identified. The plastid genome is structurally highly conserved, providing valuable sources of genetic markers for phylogenetic analyses and development of molecule makers for identification. Methods: The plastid genome DNA was extracted from both fern species and then sequenced on the Illumina Hiseq 4000. Sequences were assembled into contigs by SOAPdenovo2.04, aligned to the reference genome using BLAST, and then manually corrected. Genome annotation was performed by the online DOGMA tool. General characteristics of the plastid genomes of the two species were analyzed and compared with closely related species. Additionally, phylogenetical trees were reconstructed by maximum likelihood methods. The content of dryocrassin of the two species were determined according to the Standards of Chinese Herbal Medicines in Hong Kong. Results: The genome structures of D. crassirhizoma and O. japonica have different characteristics including the genome size, the size of each area, gene location, and types. Moreover, the (simple sequence repeats) SSRs of the plastid genomes were more similar to other species in the same genera. Compared with D. fragrans, D. crassirhizoma shows an inversion (approximately 1.6 kb), and O. japonica shows two inversions (1.9 kb and 216 bp). The nucleotide diversity (polymorphism information, Pi) analysis showed that the psbK gene and rpl14-rpl16 region have the highest Pi value in Dryopteris, and the ycf2-CDS3 and rpl14-rpl16 regions show the highest Pi vale in O. japonica. Phylogenetic analyses showed that the two species were grouped in two separate clades from each other, with both individually located with other members of their genus. The marker content of dryocrassin is not found in O. japonica. Conclusions: The study is the first to identify plastid genome features of D. crassirhizoma and O. japonica. The results may provide a theoretical basis for the identification and the application of the two medically important fern species.
    64 schema:genre research_article
    65 schema:inLanguage en
    66 schema:isAccessibleForFree true
    67 schema:isPartOf N08c3639f12d74b70a4c18c0aacf5d71c
    68 N27ec17feb59f4b6882981f323a4f8dbf
    69 sg:journal.1313369
    70 schema:name Plastid genome and composition analysis of two medical ferns: Dryopteris crassirhizoma Nakai and Osmunda japonica Thunb.
    71 schema:pagination 9
    72 schema:productId N2326a344e09b4f9a8c5ae796eb183d67
    73 N50082f14ff824f48a50381c613d3d937
    74 N787ab55eebcd432b9c4fe0604a3a7a2e
    75 N98dd924cfecf456c879057b53f03e6f3
    76 Nc13768527ada4486919eefc5e0ac09bf
    77 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112767236
    78 https://doi.org/10.1186/s13020-019-0230-4
    79 schema:sdDatePublished 2019-04-11T14:00
    80 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    81 schema:sdPublisher Na74217cf4cfc42149a523a6393205f71
    82 schema:url https://link.springer.com/10.1186%2Fs13020-019-0230-4
    83 sgo:license sg:explorer/license/
    84 sgo:sdDataset articles
    85 rdf:type schema:ScholarlyArticle
    86 N08c3639f12d74b70a4c18c0aacf5d71c schema:volumeNumber 14
    87 rdf:type schema:PublicationVolume
    88 N0e6b77e64ba04fb7a5762dab03d091f5 schema:affiliation https://www.grid.ac/institutes/grid.411464.2
    89 schema:familyName Xing
    90 schema:givenName Yanping
    91 rdf:type schema:Person
    92 N2326a344e09b4f9a8c5ae796eb183d67 schema:name pubmed_id
    93 schema:value 30911328
    94 rdf:type schema:PropertyValue
    95 N27ec17feb59f4b6882981f323a4f8dbf schema:issueNumber 1
    96 rdf:type schema:PublicationIssue
    97 N30ca96ca4843460889a15b81d75109db schema:affiliation https://www.grid.ac/institutes/grid.411464.2
    98 schema:familyName Kang
    99 schema:givenName Tingguo
    100 rdf:type schema:Person
    101 N4ef49619ceb047979a51196b1006409c schema:affiliation https://www.grid.ac/institutes/grid.411464.2
    102 schema:familyName Xu
    103 schema:givenName Liang
    104 rdf:type schema:Person
    105 N50082f14ff824f48a50381c613d3d937 schema:name doi
    106 schema:value 10.1186/s13020-019-0230-4
    107 rdf:type schema:PropertyValue
    108 N688e31c6de084c3483637b44ea1ab559 rdf:first N4ef49619ceb047979a51196b1006409c
    109 rdf:rest N922a7eee0ed24df4a32313138d064818
    110 N6c20103991b74b0397f083e0c11aa784 rdf:first N6d23b5412ce0438ab6f522bede4f3196
    111 rdf:rest Ne9a6c60745d4438a90e3a3242233cfcb
    112 N6d23b5412ce0438ab6f522bede4f3196 schema:affiliation https://www.grid.ac/institutes/grid.411464.2
    113 schema:familyName Wang
    114 schema:givenName Bing
    115 rdf:type schema:Person
    116 N787ab55eebcd432b9c4fe0604a3a7a2e schema:name dimensions_id
    117 schema:value pub.1112767236
    118 rdf:type schema:PropertyValue
    119 N7b9e62fa4adc4ac5a2de8a4ecd6b7e0c rdf:first N30ca96ca4843460889a15b81d75109db
    120 rdf:rest rdf:nil
    121 N7f4cbe9289a24a37a3f6939e5ce6bc74 schema:affiliation https://www.grid.ac/institutes/grid.24695.3c
    122 schema:familyName Liu
    123 schema:givenName Chunsheng
    124 rdf:type schema:Person
    125 N922a7eee0ed24df4a32313138d064818 rdf:first N0e6b77e64ba04fb7a5762dab03d091f5
    126 rdf:rest N6c20103991b74b0397f083e0c11aa784
    127 N98dd924cfecf456c879057b53f03e6f3 schema:name readcube_id
    128 schema:value d2c448700a399cec06b8a0671761a2d60ec7a7906985158e24242c0d888536ba
    129 rdf:type schema:PropertyValue
    130 N9e9004d8f09149a296efce6fe17e7a9c schema:affiliation https://www.grid.ac/institutes/grid.12527.33
    131 schema:familyName Wang
    132 schema:givenName Wenquan
    133 rdf:type schema:Person
    134 Na74217cf4cfc42149a523a6393205f71 schema:name Springer Nature - SN SciGraph project
    135 rdf:type schema:Organization
    136 Nc13768527ada4486919eefc5e0ac09bf schema:name nlm_unique_id
    137 schema:value 101265109
    138 rdf:type schema:PropertyValue
    139 Ne9a6c60745d4438a90e3a3242233cfcb rdf:first N7f4cbe9289a24a37a3f6939e5ce6bc74
    140 rdf:rest Nee4dd6c2a5b148258acefb3b91c5ca23
    141 Nee4dd6c2a5b148258acefb3b91c5ca23 rdf:first N9e9004d8f09149a296efce6fe17e7a9c
    142 rdf:rest N7b9e62fa4adc4ac5a2de8a4ecd6b7e0c
    143 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    144 schema:name Biological Sciences
    145 rdf:type schema:DefinedTerm
    146 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    147 schema:name Genetics
    148 rdf:type schema:DefinedTerm
    149 sg:journal.1313369 schema:issn 1749-8546
    150 1991-0150
    151 schema:name Chinese Medicine
    152 rdf:type schema:Periodical
    153 sg:pub.10.1007/s00122-004-1914-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053101193
    154 https://doi.org/10.1007/s00122-004-1914-3
    155 rdf:type schema:CreativeWork
    156 sg:pub.10.1007/s00606-007-0608-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029614971
    157 https://doi.org/10.1007/s00606-007-0608-0
    158 rdf:type schema:CreativeWork
    159 sg:pub.10.1007/s00606-015-1197-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1038151245
    160 https://doi.org/10.1007/s00606-015-1197-y
    161 rdf:type schema:CreativeWork
    162 sg:pub.10.1007/s11105-015-0853-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041029695
    163 https://doi.org/10.1007/s11105-015-0853-2
    164 rdf:type schema:CreativeWork
    165 sg:pub.10.1038/35054555 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038499798
    166 https://doi.org/10.1038/35054555
    167 rdf:type schema:CreativeWork
    168 sg:pub.10.1038/75556 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044135237
    169 https://doi.org/10.1038/75556
    170 rdf:type schema:CreativeWork
    171 sg:pub.10.1186/1471-2105-4-41 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013163036
    172 https://doi.org/10.1186/1471-2105-4-41
    173 rdf:type schema:CreativeWork
    174 sg:pub.10.1186/1471-2148-13-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006039492
    175 https://doi.org/10.1186/1471-2148-13-8
    176 rdf:type schema:CreativeWork
    177 sg:pub.10.1186/1471-2148-9-130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020104454
    178 https://doi.org/10.1186/1471-2148-9-130
    179 rdf:type schema:CreativeWork
    180 sg:pub.10.1186/1471-2164-11-277 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004318568
    181 https://doi.org/10.1186/1471-2164-11-277
    182 rdf:type schema:CreativeWork
    183 sg:pub.10.1186/1471-2164-8-174 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029379402
    184 https://doi.org/10.1186/1471-2164-8-174
    185 rdf:type schema:CreativeWork
    186 sg:pub.10.1186/1472-6785-13-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020768419
    187 https://doi.org/10.1186/1472-6785-13-8
    188 rdf:type schema:CreativeWork
    189 sg:pub.10.1186/1749-8546-4-21 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005119475
    190 https://doi.org/10.1186/1749-8546-4-21
    191 rdf:type schema:CreativeWork
    192 sg:pub.10.1186/2047-217x-1-18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016521225
    193 https://doi.org/10.1186/2047-217x-1-18
    194 rdf:type schema:CreativeWork
    195 sg:pub.10.1186/s12863-014-0138-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1013030567
    196 https://doi.org/10.1186/s12863-014-0138-z
    197 rdf:type schema:CreativeWork
    198 sg:pub.10.1186/s12864-018-4633-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1103128552
    199 https://doi.org/10.1186/s12864-018-4633-x
    200 rdf:type schema:CreativeWork
    201 sg:pub.10.1186/s12870-017-1195-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1100102273
    202 https://doi.org/10.1186/s12870-017-1195-z
    203 rdf:type schema:CreativeWork
    204 sg:pub.10.1186/s13020-018-0164-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100995401
    205 https://doi.org/10.1186/s13020-018-0164-2
    206 rdf:type schema:CreativeWork
    207 sg:pub.10.1186/s13059-016-1004-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028676039
    208 https://doi.org/10.1186/s13059-016-1004-2
    209 rdf:type schema:CreativeWork
    210 https://doi.org/10.1016/j.bse.2010.12.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036410108
    211 rdf:type schema:CreativeWork
    212 https://doi.org/10.1016/j.gene.2015.07.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012222260
    213 rdf:type schema:CreativeWork
    214 https://doi.org/10.1016/s0022-2836(05)80360-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013618994
    215 rdf:type schema:CreativeWork
    216 https://doi.org/10.1016/s0168-9525(97)01223-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022738563
    217 rdf:type schema:CreativeWork
    218 https://doi.org/10.1016/s0169-5347(00)02097-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026229109
    219 rdf:type schema:CreativeWork
    220 https://doi.org/10.1021/acs.jafc.7b00925 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085615448
    221 rdf:type schema:CreativeWork
    222 https://doi.org/10.1086/376817 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058670030
    223 rdf:type schema:CreativeWork
    224 https://doi.org/10.1093/bioinformatics/16.11.1046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026953484
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1093/bioinformatics/bth352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050086076
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.1093/bioinformatics/btp187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021484173
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.1093/database/bar009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002484367
    231 rdf:type schema:CreativeWork
    232 https://doi.org/10.1093/dnares/10.2.59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003499143
    233 rdf:type schema:CreativeWork
    234 https://doi.org/10.1093/gbe/evt099 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046472038
    235 rdf:type schema:CreativeWork
    236 https://doi.org/10.1093/gbe/evu087 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028892049
    237 rdf:type schema:CreativeWork
    238 https://doi.org/10.1093/gbe/evx107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086005951
    239 rdf:type schema:CreativeWork
    240 https://doi.org/10.1093/molbev/msi174 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008885890
    241 rdf:type schema:CreativeWork
    242 https://doi.org/10.1093/nar/29.22.4633 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046065243
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1093/nar/gkh063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017271040
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1093/nar/gkj102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028128110
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1093/nar/gkn502 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037164940
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1093/sysbio/syq010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046004748
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1111/nph.14135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041145635
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1126/science.278.5338.631 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039646901
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1146/annurev.arplant.51.1.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004835401
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.12677/bp.2011.12003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064602173
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1371/journal.pone.0000508 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046302972
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1371/journal.pone.0012762 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016440387
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1371/journal.pone.0019119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011161078
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1371/journal.pone.0035071 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012980256
    267 rdf:type schema:CreativeWork
    268 https://doi.org/10.1371/journal.pone.0073053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029190478
    269 rdf:type schema:CreativeWork
    270 https://doi.org/10.1371/journal.pone.0184257 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091408573
    271 rdf:type schema:CreativeWork
    272 https://doi.org/10.14348/molcells.2014.2296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000252395
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.1640/0002-8444(2007)97[95:tcpgso]2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006115360
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.3109/19401736.2015.1063131 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021555788
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.3390/genes7120115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039695896
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.3390/molecules22020249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083696481
    281 rdf:type schema:CreativeWork
    282 https://doi.org/10.3732/ajb.94.3.275 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050985240
    283 rdf:type schema:CreativeWork
    284 https://doi.org/10.4268/cjcmm20162216 schema:sameAs https://app.dimensions.ai/details/publication/pub.1087168018
    285 rdf:type schema:CreativeWork
    286 https://www.grid.ac/institutes/grid.12527.33 schema:alternateName Tsinghua University
    287 schema:name Institute of Medicinal Plant Development, Beijing, China
    288 School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
    289 rdf:type schema:Organization
    290 https://www.grid.ac/institutes/grid.24695.3c schema:alternateName Beijing University of Chinese Medicine
    291 schema:name School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
    292 rdf:type schema:Organization
    293 https://www.grid.ac/institutes/grid.411464.2 schema:alternateName Liaoning University of Traditional Chinese Medicine
    294 schema:name School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
    295 School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian, China
    296 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...