Yang Lu, Lichao Jiao, Shoujia Liu, Tuo He, Xiaomei Jiang, Yafang Yin
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The five highest variable regions (Pi>0.009; <jats:italic>psbA-trnH, psbJ, psbJ-petA, rpl32-trnL,</jats:italic> and <jats:italic>ycf</jats:italic> <jats:italic>1</jats:italic>) were identified, and three nuclear regions (ITS, <jats:italic>LEAFY,</jats:italic> and <jats:italic>RPB2</jats:italic>) were compared. Among single DNA fragments, the nuclear DNA region <jats:italic>LEAFY</jats:italic> proved optimal for identifying Nanmu species, while <jats:italic>psbA-trnH</jats:italic>+<jats:italic>psbJ</jats:italic>+<jats:italic>ycf1</jats:italic> was the optimal plastid combination locus. Compared with distance-based (TaxonDNA) and machine-learning analyses, the tree-based method had a lower success rate for species identification. Four labelled Nanmu samples were selected to validate the method and clustered with <jats:italic>P. zhennan</jats:italic> and <jats:italic>P. sheareri</jats:italic> data based on the <jats:italic>LEAFY</jats:italic> region and plastid combination locus. These findings will contribute to the conservation, classification, architecture maintenance, and trade monitoring of Nanmu natural resources.","PeriodicalId":13083,"journal":{"name":"Holzforschung","volume":"32 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wood discrimination of six commonly traded Phoebe and Machilus species using high-resolution plastid and nuclear DNA barcodes\",\"authors\":\"Yang Lu, Lichao Jiao, Shoujia Liu, Tuo He, Xiaomei Jiang, Yafang Yin\",\"doi\":\"10.1515/hf-2024-0012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<jats:italic>Phoebe</jats:italic> and <jats:italic>Machilus</jats:italic> trees, whose wood is known as Nanmu in China, face endangerment owing to long-term manmade destruction and climate change. Therefore, effective and accurate forensic tools to identify Nanmu species are required. This study developed a method for DNA identification of woods from six commonly traded <jats:italic>Phoebe</jats:italic> and <jats:italic>Machilus</jats:italic> species. DNA was efficiently extracted from oil cell-rich wood tissues, DNA barcodes were screened, species were compared, and a Nanmu DNA database was constructed. Comparison and analysis involved 26 sets of plastid genomes of <jats:italic>Phoebe</jats:italic> and <jats:italic>Machilus</jats:italic>. The five highest variable regions (Pi>0.009; <jats:italic>psbA-trnH, psbJ, psbJ-petA, rpl32-trnL,</jats:italic> and <jats:italic>ycf</jats:italic> <jats:italic>1</jats:italic>) were identified, and three nuclear regions (ITS, <jats:italic>LEAFY,</jats:italic> and <jats:italic>RPB2</jats:italic>) were compared. Among single DNA fragments, the nuclear DNA region <jats:italic>LEAFY</jats:italic> proved optimal for identifying Nanmu species, while <jats:italic>psbA-trnH</jats:italic>+<jats:italic>psbJ</jats:italic>+<jats:italic>ycf1</jats:italic> was the optimal plastid combination locus. Compared with distance-based (TaxonDNA) and machine-learning analyses, the tree-based method had a lower success rate for species identification. Four labelled Nanmu samples were selected to validate the method and clustered with <jats:italic>P. zhennan</jats:italic> and <jats:italic>P. sheareri</jats:italic> data based on the <jats:italic>LEAFY</jats:italic> region and plastid combination locus. 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引用次数: 0
摘要
由于长期的人为破坏和气候变化,其木材在中国被称为楠木的凤凰木和楠木面临濒危。因此,需要有效、准确的法医工具来鉴定楠木树种。本研究开发了一种对六种常见楠木品种进行 DNA 鉴定的方法。从富含油细胞的木材组织中有效提取 DNA,筛选 DNA 条形码,比较物种,并构建楠木 DNA 数据库。比较和分析涉及 26 套 Phoebe 和 Machilus 的质体基因组。确定了五个最高可变区(Pi>0.009; psbA-trnH、psbJ、psbJ-petA、rpl32-trnL 和 ycf 1),并比较了三个核区(ITS、LEAFY 和 RPB2)。在单个 DNA 片段中,核 DNA 区域 LEAFY 被证明是鉴定楠木物种的最佳区域,而 psbA-trnH+psbJ+ycf1 则是最佳的质体组合位点。与基于距离(TaxonDNA)和机器学习的分析方法相比,基于树的方法鉴定物种的成功率较低。研究人员选取了四个楠木标本对该方法进行了验证,并根据叶绿体区域和质体组合位点与浙南楠木和剪股颖楠木数据进行了聚类。这些发现将有助于楠木自然资源的保护、分类、结构维护和贸易监测。
Wood discrimination of six commonly traded Phoebe and Machilus species using high-resolution plastid and nuclear DNA barcodes
Phoebe and Machilus trees, whose wood is known as Nanmu in China, face endangerment owing to long-term manmade destruction and climate change. Therefore, effective and accurate forensic tools to identify Nanmu species are required. This study developed a method for DNA identification of woods from six commonly traded Phoebe and Machilus species. DNA was efficiently extracted from oil cell-rich wood tissues, DNA barcodes were screened, species were compared, and a Nanmu DNA database was constructed. Comparison and analysis involved 26 sets of plastid genomes of Phoebe and Machilus. The five highest variable regions (Pi>0.009; psbA-trnH, psbJ, psbJ-petA, rpl32-trnL, and ycf1) were identified, and three nuclear regions (ITS, LEAFY, and RPB2) were compared. Among single DNA fragments, the nuclear DNA region LEAFY proved optimal for identifying Nanmu species, while psbA-trnH+psbJ+ycf1 was the optimal plastid combination locus. Compared with distance-based (TaxonDNA) and machine-learning analyses, the tree-based method had a lower success rate for species identification. Four labelled Nanmu samples were selected to validate the method and clustered with P. zhennan and P. sheareri data based on the LEAFY region and plastid combination locus. These findings will contribute to the conservation, classification, architecture maintenance, and trade monitoring of Nanmu natural resources.
期刊介绍:
Holzforschung is an international scholarly journal that publishes cutting-edge research on the biology, chemistry, physics and technology of wood and wood components. High quality papers about biotechnology and tree genetics are also welcome. Rated year after year as one of the top scientific journals in the category of Pulp and Paper (ISI Journal Citation Index), Holzforschung represents innovative, high quality basic and applied research. The German title reflects the journal''s origins in a long scientific tradition, but all articles are published in English to stimulate and promote cooperation between experts all over the world. Ahead-of-print publishing ensures fastest possible knowledge transfer.