Integrating DNA Barcoding and Traditional Taxonomy for the Identification of Dipterocarps in Remnant Lowland Forests of Sumatra

Moura, Carina Carneiro de Melo; Brambach, Fabian; Bado, Kevin Jair Hernandez; Krutovsky, Konstantin V.; Kreft, Holger; Tjitrosoedirdjo, S.; Siregar, Iskandar Z.; Gailing, Oliver

doi:10.3390/plants8110461

Cited by 31 publications

(22 citation statements)

References 41 publications

(83 reference statements)

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“…Similarly, morphological markers have been studied in combination with molecular markers as an efficient method of species classification ( Carneiro de Melo Moura et al, 2019 ; Xie et al, 2019 ; Martínez-Arce et al, 2020 ). Morphological data always play a key role in plant species classification based on phylogeny ( Scotland et al, 2003 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of Vicia Species Native to South Korea Using Molecular and Morphological Characteristics

et al. 2021

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Recently, within the Fabaceae family, the Vicia genus has been recognized for its vital role in sustainable agriculture. Vicia species are economically important grain and forage crops. However, the presence of complex morphological characteristics makes identification and recognition of native species difficult. In this study, the possibility of using DNA barcoding regions (ITS2, matK, and rbcL) to distinguish among 19 Vicia taxa (59 accessions) found in South Korea was evaluated. The sequence alignment analysis revealed considerable nucleotide diversity (π) between the loci, in which ITS2 showed the highest mean interspecific distance, whereas there was no intraspecific variability among the barcode regions in 12 of the 19 taxa. Phylogenetic analysis of combined barcoding regions revealed well-resolved phylogeny with the highest species level discrimination. Combinations of barcode loci were also used in classification at the subgenera and section levels. The results revealed that the combined barcoding regions can be used effectively to differentiate the following species: Vicia angustifolia var. segetilis, Vicia bungei, Vicia villosa, Vicia cracca, Vicia dasycarpa, Vicia hirsuta, Vicia tetrasperma, Vicia amurensis, Vicia hirticalycina, and Vicia chosenensis. However, it is difficult to differentiate the species of Vicia unijuga, Vicia unijuga var. kaussanensis, Vicia linearifolia, Vicia unijuga f. angustifolia, Vicia nipponica, Vicia amoena, Vicia venosa var. cuspidata, Vicia pseudo-orobus, and Vicia japonica with the tested barcode regions. These species come under sect. Vicilla and are found to be closely related or species that have recently undergone speciation; thus, it has limitation to distinguish with recommended barcodes. Hence, to differentiate the unclassified species, 39 morphological characteristics were investigated, in which 16 useful characteristics were selected for efficient classification. Finally, the 16 selected morphological useful traits efficiently differentiated all the Vicia species. In conclusion, a combination of barcoding loci together with morphological characteristics of this study efficiently discriminated all the Korean Vicia species.

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Section: Introductionmentioning

confidence: 99%

Identification of Vicia Species Native to South Korea Using Molecular and Morphological Characteristics

et al. 2021

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“…Moreover, the skewed rate of identification in matK could be primarily due gaps or missing data; secondly, it could also be due to the higher evolutionary rate is about 2-3 times higher than rbcL [69], giving high discriminatory power and su reliability. Similar studies on plant barcodes have validated the efficacy of the marker for species discrimination [70][71][72].…”

Section: Discussionmentioning

confidence: 65%

Evaluation of Arabian Vascular Plant Barcodes (rbcL and matK): Precision of Unsupervised and Supervised Learning Methods towards Accurate Identification

Jamdade¹,

Upadhyay²,

Shaer³

et al. 2021

Plants

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Arabia is the largest peninsula in the world, with >3000 species of vascular plants. Not much effort has been made to generate a multi-locus marker barcode library to identify and discriminate the recorded plant species. This study aimed to determine the reliability of the available Arabian plant barcodes (>1500; rbcL and matK) at the public repository (NCBI GenBank) using the unsupervised and supervised methods. Comparative analysis was carried out with the standard dataset (FINBOL) to assess the methods and markers’ reliability. Our analysis suggests that from the unsupervised method, TaxonDNA’s All Species Barcode criterion (ASB) exhibits the highest accuracy for rbcL barcodes, followed by the matK barcodes using the aligned dataset (FINBOL). However, for the Arabian plant barcode dataset (GBMA), the supervised method performed better than the unsupervised method, where the Random Forest and K-Nearest Neighbor (gappy kernel) classifiers were robust enough. These classifiers successfully recognized true species from both barcode markers belonging to the aligned and alignment-free datasets, respectively. The multi-class classifier showed high species resolution following the two classifiers, though its performance declined when employed to recognize true species. Similar results were observed for the FINBOL dataset through the supervised learning approach; overall, matK marker showed higher accuracy than rbcL. However, the lower rate of species identification in matK in GBMA data could be due to the higher evolutionary rate or gaps and missing data, as observed for the ASB criterion in the FINBOL dataset. Further, a lower number of sequences and singletons could also affect the rate of species resolution, as observed in the GBMA dataset. The GBMA dataset lacks sufficient species membership. We would encourage the taxonomists from the Arabian Peninsula to join our campaign on the Arabian Barcode of Life at the Barcode of Life Data (BOLD) systems. Our efforts together could help improve the rate of species identification for the Arabian Vascular plants.

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“…The nucleotide divergence was estimated based on the multiple sequence alignment of ITS, matK, rbcL and the concatenated sequences by MEGA X (Ver.10.1.7) using the Kimura-2-parameter (K2P) model 38 . A uniform distribution was set as rate variation among sites.…”

Section: Methodsmentioning

confidence: 99%

Phylogenetic relationship of Paramignya trimera and its relatives: an evidence for the wide sexual compatibility

Phi

Chu

et al. 2020

Sci Rep

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The genus Paramignya (Rutaceae) comprises about 30 species typically distributing in tropical Asia. Like other genera of the family Rutaceae, the significant variation in the morphology of Paramignya species makes the taxonomic study and accurate identification become difficult. In Vietnam, Paramignya species have been mostly found in Khanh Hoa and Lam Dong provinces and used as traditional medicines. Recently, Paramignya trimera, a species of the genus Paramignya with local name “Xao tam phan” has been drawn attention and intensively exploited to treat liver diseases and cancers. However, the significant variations in the morphology and different local names of P. trimera have caused confusion and difficulty in the accurate identification and application of this plant for medicine. In this study, the combination of both morphological and DNA sequence data has effectively supported the taxonomic identification of P. trimera and some relatives collected in Khanh Hoa and Lam Dong provinces. The comparison of the morphology and analysis of the phylogenetic trees suggested that there was a significant variation of P. trimera. In addition, some accessions of P. trimera with morphological characteristics similar and Atalantia buxifolia were likely the intergeneric hybrids between the two species. Analysis of genetic variation, interspecific and intraspecific distances using ITS, matK and rbcL sequences shown that P. trimera was closely related to A. buxifolia, Severinia monophylla and Luvunga scandens. In addition, matK sequences represented as the effective candidate DNA barcode to identify and distinguish Paramignya species from others of the family Rutaceae.

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Integrating DNA Barcoding and Traditional Taxonomy for the Identification of Dipterocarps in Remnant Lowland Forests of Sumatra

Cited by 31 publications

References 41 publications

Identification of Vicia Species Native to South Korea Using Molecular and Morphological Characteristics

Identification of Vicia Species Native to South Korea Using Molecular and Morphological Characteristics

Evaluation of Arabian Vascular Plant Barcodes (rbcL and matK): Precision of Unsupervised and Supervised Learning Methods towards Accurate Identification

Phylogenetic relationship of Paramignya trimera and its relatives: an evidence for the wide sexual compatibility

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