Figures
Abstract
Piper is one of two large genera in the Piperaceae, and with ca. 2600 species, is one of the largest plant genera in the world. Species delimitation and evaluation of genetic diversity among populations are important requisites for conservation and adequate exploitation of economically important species. DNA barcoding has been used as a powerful tool and a practical method for species characterization and delimitation. The present work aims to evaluate molecular markers for barcoding three Piper species native to Brazil: P. gaudichaudianum (“jaborandi” or “pariparoba”), P. malacophyllum (“pariparoba-murta”) and P. regnellii (“caapeba” or “pariparoba”). A reference DNA barcode library was developed using sequences of three candidate regions: ITS2, trnH-psbA and rbcL. Transferability of the microsatellite (SSR) primers Psol 3, Psol 6 and Psol 10, designed originally for Piper solmsianum, to the three Piper species was also evaluated. The discriminatory power of the markers was based on the determination of inter- and intraspecific distances, phylogenetic reconstruction, and clustering analysis, as well as BLASTn comparison. Sequences of ITS2 enabled efficient species identification by means of the BLASTn procedure. Based on these sequences, intraspecific divergence was lower than interspecific variation. Maximum Parsimony analyses based on ITS2 sequences provided three resolved clades, each corresponding to one of the three analysed species. Sequences of trnH-psbA and rbcL had lower discriminatory value. Analyses combining sequences of these regions were less effective toward the attainment of resolved and strongly supported clades of all species. In summary, robustly supported clades of P. regnellii were obtained in most of the analyses, based either on isolated or combined sequences. The SSRs primers Psol 3, Psol 6 and Psol 10 were shown to be transferable to P. gaudichaudianum and P. regnellii, but not to P. malacophyllum. Preliminary cluster analyses based on the polymorphism of the amplified products suggested that Psol 3 has lower potential than Psol 6 and Psol 10 for discrimination of Piper species.
Citation: Egydio Brandão APM, Yamaguchi LF, Tepe EJ, Salatino A, Kato MJ (2020) Evaluation of DNA markers for molecular identification of three Piper species from Brazilian Atlantic Rainforest. PLoS ONE 15(10): e0239056. https://doi.org/10.1371/journal.pone.0239056
Editor: Branislav T. Šiler, Institute for Biological Research "S. Stanković", University of Belgrade, SERBIA
Received: January 28, 2020; Accepted: August 28, 2020; Published: October 19, 2020
Copyright: © 2020 Egydio Brandão et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: the data are held or will be held in a public repositor - https://www.ncbi.nlm.nih.gov/genbank/ All DNA sequences were deposited in NCBI/Genebank.
Funding: MJK - 2009/51850-9; 2014/50316-7 - FAPESP APMEB - 2013/19398-4 - FAPESP FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) - www.fapesp.br CNPq (Conselho Nacional do Desenvolvimento Científico e Tecnológico) and FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo; grants 2009/51850-9, 2013/19398-4 and 2014/50316-7) US National Science Foundation (DEB-1442075).
Competing interests: The authors have declared that no competing interests exist.
Introduction
Family Piperaceae is one of the largest groups of basal angiosperms, with species widely distributed in tropical and subtropical regions of both New and Old worlds. Peperomia Ruiz & Pav. and Piper L. are the genera in the Piperaceae with the highest number of species, with ca. 2,000 and 2,600 taxa, respectively [1–3]. Several species of Piper are frequently used as spices, as medicines or as ornamentals. Piper nigrum L. (black pepper) is one the most consumed spices in the world, and P. methysticum G. Forst. (“kava-kava”) is widely used to treat anxiety disorders [4].
Piper malacophyllum (C.Presl) C.DC. and P. regnellii (Miq.) C.DC. are native to Brazil and P. gaudichaudianum Kunth occurs more widely in Latin America. No genomic data have been published for either P. regnellii or P. malacophyllum. The three species are used in popular medicine for treatment of many diseases. For example, P. regnellii is used as anesthetic and anti-inflammatory and P. gaudichaudianum, is used to treat toothaches [5]. Extracts of these species have revealed activity against human and plant fungal pathogens [6–8]. On the other hand, frauds, misuses, and misidentifications of plant names are common in the market of medicinal plants. In addition, vernacular names are often used to refer to several species, due to similarities in the morphology of these plants and their traditional uses. Thus, “pariparoba” may apply to P. regnellii, P. gaudichaudianum, P. malacophyllum, P. umbellatum L. and other species. The development of molecular tools may contribute to the correct identification of these useful species.
DNA barcoding is a rapid and reliable procedures aimed at the accurate identification and delimitation of species [9]. As part of the DNA barcoding protocol, sequences of unidentified samples are compared against a database of know-DNA sequences [10–11]. Certain properties of DNA markers are essential for barcoding purposes: a) high interspecific polymorphism, b) low or non-existing intraspecific divergence, c) existence of conserved flanking regions, allowing for the design of universal primers [12–14]. The mitochondrial gene Cox I (or COI) has been universally employed for barcoding animal species [15]; however, a single marker that is useful across all plants has not yet been identified. Nevertheless, a comprehensive review [16] revealed multiple markers that could be used as DNA barcodes within a given plant group. The CBOL-Consortium for the Barcode of Life has recommended the plastid gene ribulose-bisphosphate carboxylase (rbcL) [17], because of its universality, sequence quality and differentiation power [14,18]. Although rbcL has been useful for distinction between species [19], its usefulness is usually restricted to the levels of family and genus. For this reason, markers with high degree of variation have been recommended [10], such as the nuclear Internal Transcribed Spacer (ITS) and the plastid trnH-psbA intergenic spacer [12]. The plastid DNA regions rbcL, matK and trnH-psbA have been used for DNA barcode of Pteridophytes [20], Cycadales [21], Fabaceae [22], in addition to several other taxa.
Previous attempts at barcoding Old World Piper species included the use of chloroplast regions matK, rbcL, rpoC1 and trnH-psbA, as well as the nuclear ITS2 markers [23–24]. The barcoding analysis of thirty-six Piper species from Thailand was carried out using matK, rbcL and trnH-psbA [25]. In these studies, most species could be accurately identified using the DNA barcodes.
Microsatellites, also known as SSRs (Simple Sequence Repeats), are simple and short DNA sequences, consisting of two to six nucleotides repeated in tandem. Their polymorphism results from variation of the number of sequence repeats [26]. Due to their specificity, codominant inheritance, high abundance in all eukaryotic genomes, high polymorphism, good reproducibility, versatility and ease of use, SSRs have become valuable markers for a wide range of applications, including barcoding, mapping, marker-assisted breeding [27], and evaluation of plant genetic variability [28]. Arguments have been put forward regarding the value of SSRs for authentication and identification of medicinal plants [29], spices and other food plants [30–31]. For instance, nine SSR markers were used for the identification of Chinese samples of ginseng [31]. The use of sixty SSR markers showed high polymorphic levels among 192 Capsicum lines, allowing the assembling of five groups [30]. Additionally, integrated SSRs and sequences of chloroplast rpoC1, aimed at the identification of the ’Eglouvi’ lentil variety was also carried out [32]; the combination of molecular markers was used to detect adulterants at low cost, suggesting its use could be a valuable tool in forensic sciences and determination of food safety. Within Piper, SSRs were used to assess the genetic diversity among commercial genotypes of P. nigrum in Southern India [33], as well as the infraspecific genetic variation of P. methysticum [34] and P. solmsianum C. DC. [35]. Finally, information from SSR amplification profiles, along with morphological characters traditionally used in Piper taxonomy were used to identify the most efficient data set for species distinction [36].
In spite of the cost and time-consuming development of specific SSR primers [37], several works have shown that primers developed for one species can be used to amplify SSRs of phylogenetically related species. Primer transferability among species demonstrated that the regions flanking of microsatellites can be highly conserved [38–39], thus making it possible for primers developed for one species to produce useful data in other closely related species. Transferability of SSR primers, for example, have been verified for Secale cereale L., Triticum aestivum L. [37], Ficus [40], Betula, Corylus [39], Lolium [41], Arachis [42], many other species. Previous investigation about transferability of SSR markers to Piper revealed that markers designed for P. solmsianum provided the highest transferability rate among Piper species [36].
The present study aims to evaluate sequences of DNA regions toward barcoding of three Piper species native from Brazil: P. gaudichaudianum (“jaborandi”), P. malacophyllum (“pariparoba-murta”) and P. regnellii (“caapeba” or “pariparoba”). In addition, it is intended to evaluate the transferability of SSR primers, previously designed for P. solmsianum [35], to the three mentioned species and evaluate their efficacy for barcoding purposes.
Material and methods
Plant material
Fresh leaves from 20 specimens of P. gaudichaudianum, 20 of P. regnellii and 20 of P. malacophyllum were collected. Plant material was obtained from specimens cultivated at the garden of the Laboratory of Natural Product Chemistry, Institute of Chemistry, University of São Paulo (LQPN-USP), and from specimens growing in the Intervales State Park (State of São Paulo, Southeast Brazil) (Table 1). All plant material was identified by Dr. Elsie F. Guimarães, and voucher specimens were deposited in the Herbarium of the Research Institute of the Botanical Garden of Rio de Janeiro, Brazil (RB).
DNA extraction
Genomic DNA was extracted using either the NucleoSpin Plant II kit (Macherey-Nagel-MN) or the Dneasy Plant Mini (Qiagen) kits, following the manufacturers’ protocols. The quality of the DNA obtained was evaluated by electrophoresis using TAE 1X buffer and 2% agarose gel containing GelRed (Amersham).
Amplification and sequencing of DNA regions
Primers used for amplification of DNA regions are shown on Table 2. Polymerase chain reactions (PCRs) were performed with 50 μL reaction mixtures, containing 10X Taq reaction buffer, dNTPs in the final concentration of 0.2 mM, each primer at 10 μM, 1.25 U Taq Polymerase (Promega, USA), 10 μL of 1% PVP (polyvinylpolypyrrolidone), 20–50 ng of total DNA template and milliQ water to make up the volume of 50 μL. Thermal cycling conditions for ITS2 were: 1 min at 97°C, 40 cycles of 1 min at 97°C, 1 min at 48°C, 45 sec at 72°C and 7 min at 72°C. For rbcL, the following protocol was used: 5 min at 94°C, 30 cycles of 1 min at 94°C, 30 sec at 50°C, 1 min at 72°C and a final extension of 7 min at 72°C. The following protocol was used for trnH-psbA: 5 min at 94°C, 30 cycles of 30 sec at 94°C, 30 sec at 48°C, 30 sec at 72°C and a final extension of 5 min at 72°C.
Amplification was performed in a MyCycler Thermal Cycler (BioRad). Purification of the amplified products was performed by combining two enzymes: shrimp alkaline phosphatase (SAP) and exonuclease I (EXO). For each reaction, 8 μL of the amplified product and 2 μL of the ExoSAP-IT enzyme kit were used. The reaction was incubated in thermocycler for 1 h at 37°C and 15 min at 80°C.
Reactions for sequencing were prepared in 96-well plates with the BigDye® Terminator kit version 3.1 (Applied Biosystems), according to the manufacturer’s protocol. Each reaction contained 3 μL of the amplified product, 4.7 μL of milliQ water, 0.30 μL of the primer and 2 μL of BigDye® Terminator. The labeled products were precipitated with 60 μL of 70% isopropanol and centrifuged at 4000 rpm for 45 min. After discarding the supernatant, 170 μL of 70% ethanol was added. Centrifugation was done at 4000 rpm for 10 min, the supernatants were discarded, and the pellets dried in incubator at 37°C. The DNA was resuspended following standard procedures, and was denatured at 94°C for 2 min, followed by immediate cooling on ice. Sequencing was performed using an ABI Prism 3100 (Perkin Elmer) Genetic Analyzer. The forward and reverse sequences of the same sample were complemented, assembled, and aligned with ClustalW [43], followed by manual optimization with BioEdit. Sequences of each plant sample were organized into matrices for phylogenetic analysis.
Amplification and analysis of SSR fragments
Development of the SSR primers (Table 3), Psol 3, Psol 6, and Psol 10 was described elsewhere [35]. Polymerase chain reactions (PCRs) were performed in 20 μL reaction mixtures, containing 10 mM Tris-HCl and 50 mM KCl buffer, 20–50 ng of total DNA template, 2 mM MgCl2, dNTPs at 0.25 μM, bovine serum albumin (BSA) at 0.5 μg.μL−1, forward primer (F) at 0.16 μM, reverse primer (R) at 0.2 μM, M13 primer IR700 or IR800 at 0.3 μM, and 1 U of Taq DNA polymerase. One of the primers of each of the six pairs contained a fluorophore (IRDye-700 or IRDye-800) for capillary electrophoretic detection. For PCR amplification, the following program of temperatures was used: 5 min at 94°C, 10 cycles of 1 min at 94°C, 1 min at 58°C, decreasing 1°C at each following cycle, 1 min at 72°C, 30 cycles of 40 sec at 94°C, 40 sec at 48°C, 1 min at 72°C, and a final extension of 10 min at 72°C [31].
PCR products were analyzed using a 4300 DNA Analyzer (LI-COR, Lincoln, Nebraska, USA). Allele sizes were obtained by comparison with 50–700 bp standards (IRDye 700). Banding pattern analyses were performed using the GeneMapper software (Applied Biosystems) [26].
Data analysis
Sequence quality evaluation.
Sequence alignment was performed with the MUSCLE program [45], using default parameters and further manual optimization.
Identification test using local BLAST.
A local BLAST search was used as a test of species identification ability [46]. A reference library was constructed using the "makeblastDB" command in BLAST for each region (ITS2, trnH-psbA and rbcL) and the combination ITS2+trnH-psbA. The BLASTn search method was used to test the species identification capacity, as previously described. This method was applied to the three markers and combinations between markers. A species sequence representing the genus was used as a query sequence in BLASTn searches. Species identification was based on sequences from the database with the highest index of identity, highest score, and lowest e-value.
Distance analysis.
Intra and interspecific divergence patterns were estimated for the genomic regions ITS2, trnH-psbA, rbcL and combinations among them, based on the Kimura method 2 parameters (K2P), using the MEGA 6 software [47]. Wilcoxon signed rank tests were performed to compare interspecific variability for every barcode pair [10]. Barcoding gaps between interspecific and intraspecific distances were evaluated using frequency histograms based on the paired p-distances obtained with the Mega 6 software package [48].
Phylogenetic inference and cluster analysis.
Phylogenetic inference based on DNA sequences and the Maximum Parsimony (MP) method was analyzed with MEGA 6 [48]. For analysis of each DNA region, the Subtree-Pruning-Regrafting (SPR) algorithm was chosen, saving the first 100 more parsimonious trees. Values of clade consistencies were obtained with the bootstrap (BS) method [49] with 1000 replicates. The reliability intervals of consistency of BS values were assumed as follows: 50–74—weak; 75–84—moderate; 85–100—strong [50]. For each analysis, the number of informative characters, consistency indexes (CI) and retention indexes (RI) were determined. As out groups, sequences from NCBI/Genebank of the following species were used: rbcL—Piper longum L. (KF432059.1); trnH-psbA—P. betle L. (JQ248053.1); ITS2 –P. imperiale (Miq.) C.DC. (EF056264). Distinct outgroups were used, because sequences of all three DNA regions for the same Piper species are not available in Genbank.
Results
Amplification for DNA sequencing was successful for all individuals of P. regnellii and P. gaudichaudianum. However, only four individuals of P. malacophyllum provided amplified products (S1 Fig). Considering all Piper populations and the three DNA regions, a total of 96 sequences were obtained. All sequences generated in this study has been submitted to GenBank (S1 Table). Amplification products were obtained with SSR primers Psol 3, Psol 6 and Psol 10 for P. gaudichaudianum and P. regnellii, but not for P. malacophyllum.
Success rates of PCR amplification, sequencing, and detection of SSR segments
The amplification rates were high regarding ITS2 (100%) and rbcL (90%) and moderate regarding trnH-psbA (70%). Sequencing success rates were high for rbcL and ITS2 (100% and 95%, respectively) and moderate for trnH-psbA (86%).
Capillary electrophoresis analysis detected SSR segments from 72% of the samples. The amplification of Psol 3, Psol 6 and Psol 10 was successful for P. gaudichaudianum and P. regnellii (97% rate), but not for P. malacophyllum. While amplification was successful for all populations of P. gaudichaudianum using primers of the three SSR markers, amplification failed for samples of P. regnellii from the USP populations using Psol 3 and Psol 6 primers. Table 3 contains data regarding length polymorphism of the observed microsatellite fragment sizes.
Local BLASTn
The sequences of regions ITS2 and the sequence combination ITS2+trnH-psbA provided high identity (I) and score (S) values, as well as null e-values (Table 4).
Molecular divergence between and within species
Means of interspecific genetic diversity varied from 0.02 (rbcL; P. gaudichaudianum x P. malacophyllum) to 0.21 (ITS2; P. regnellii x P. malacophyllum), while the diversity mean within population showed values from 0.0035 (rbcL) to 0.013 (ITS2+trnH-psbA) (Fig 1). Sequences of all three genomic regions showed levels of intraspecific genetic divergence lower than interspecific variation (Fig 1).
Wilcoxon signed rank tests confirmed that the internal transcribed spacer 2 (ITS2) provided the highest interspecific divergence, which was significantly higher than those of other regions. The second highest interspecific divergence corresponded to the trnH-psbA intergenic spacer, ITS2+trnH-psbA and ITS2+trnH-psbA+rbcL combined data, whereas rbcL showed the lowest divergence (Table 5).
Barcodes should generally demonstrate a “barcoding gap” between intra- and interspecific distances. To evaluate the gaps, we distributed the divergences in classes of 0.01 distance units for all species (Fig 2) and each species (S2 and S3 Figs).
A: ITS2; B: trnH-psbA; C: rbcL; D: ITS2+trnH-psbA; E: ITS2+trnH-psbA+rbcL.
Phylogenetic analyses
Strict consensus trees from phylogenetic analyses of Piper populations, based on Maximum Parsimony analysis of sequences from the three DNA regions, are shown on Figs 3 and 4, S4–S7 Figs. Matrix parameters and details of the phylogenetic analyses are given in Table 6.
Bootstrap support values above 50% are shown above branches. USP, Int: population of Piper species from University of São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
Bootstrap support values above 50% are shown above branches. USP, Int: population of Piper species from University o0066 São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
The tree based on ITS2 sequences (Fig 3) provided three clades: 1) P. malacophyllum, with high BootStrap value (100); 2) P. gaudichaudianum, weakly supported (BS 72); 3) P. regnellii, with robust BS (100). Sequences of trnH-psbA are useful for characterizing P. regnellii (BS 100), but not P. gaudichaudianum which was resolved as paraphyletic (S4 Fig). The DNA marker trnH-psbA might also be useful for P. malacophyllum, but the sample size was too small for a robust test. Sequences of rbcL are useful for characterization of P. regnellii, which claded with strong BS (100) (S5 Fig). However, no separation was possible between samples of P. gaudichaudianum and P. malacophyllum. A strongly supported clade (BS 100) comprising three individuals of P. malacophyllum is nested within populations of P. gaudichaudianum. The P. gaudichaudianum/P. malacophyllum clade is moderately supported (BS 80; S5 Fig).
Results resembling those obtained with sequences of rbcL were achieved with the combination ITS2+trnH-psbA, namely two strongly supported clades with one corresponding to P. gaudichaudianum/P. malacophyllum and the other P. regnellii (Fig 4). The combination trnH-psbA+rbcL was not able to successfully characterize of any of the three Piper species. Populations of P. malacophyllum emerged as a grade at the base of the tree, the clade joining all populations of P. regnellii has no BS support and P. gaudichaudianum is polyphyletic (S6 Fig). The combination ITS2+trnH-psbA+rbcL provided two polytomous clades: a strongly supported clade P. gaudichaudianum/P. malacophyllum (BS 100) and a moderately supported clade P. regnellii (BS 75) (S7 Fig).
Cladograms obtained with data from Psol 3 and Psol 6, derived from the same populations, have distinct topologies (Fig 5a and 5b). Analysis based on Psol 3 failed to cluster the two samples of P. gaudichaudianum (Fig 5a). On the contrary, the same samples comprise a cluster on the cladogram based on Psol 6 (Fig 5b). The cladogram based on Psol 10 contains a cluster with the two samples of P. regnellii. On the other hand, the samples of P. gaudichaudianum do not cluster, but form a basal grade.
USP, Int: population of Piper species from University of São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
Discussion
Efficiency of PCR amplification and sequencing is vital for evaluating molecular markers in DNA barcoding [18]. In this respect, the data presented in Table 3 are encouraging regarding the SSR markers and the three DNA regions evaluated here.
As a first evaluation of the sequences of ITS2, rbcL and trnH-psbA for barcoding within the genus Piper, the tests of local BLASTn provided promising results using both ITS2 alone, and the combination of ITS2+trnH-psbA (Table 4).
High variation between species and low variation within species is a fundamental requisite for genomic makers used for barcoding that are aimed a species identification and delimitation [15, 22]. Variation within all the DNA regions examined in this study were higher between species than within species (Fig 1). When individual and combined loci were analyzed, ITS2 presented the best barcode gap performance, with 40% of pairwise interspecific p-distances greater than 0.09 and 33% of pairwise intraspecific p-distances lower than 0.007. The second highest barcode gap performance resulted from the combination of ITS2+trnH-psbA and ITS2+trnH-psbA+rbcL. Conversely, trnH-psbA and rbcL showed the worst performance, with an overlap of intra- and interspecific variation (Fig 2). Analyses of the DNA barcoding gap and Wilcoxon two-sample tests support the notion that the mean interspecific divergence of the ITS2 is significantly higher than its mean intraspecific variation (Table 5).
The capacity of DNA sequences to clade populations of Piper species in phylogenetic analyses varied from one genomic region to another (Figs 3 and 4, S4–S7 Figs). ITS2 sequences enabled the delimitations of the three species, although the P. gaudichaudianum clade was weakly supported. Analyses based on the DNA regions trnH-psbA and rbcL were successful at grouping populations of P. regnellii into strongly supported clades, but not P. gaudichaudianum (S4 and S5 Figs). ITS was previously used in a large phylogenetic analysis including Piper species from around the world [51], but none of the three species examined here were included in that analysis. In this global phylogeny, ten major clades were recognized, and a morphological description was included for each. Some of these clades correspond to previously recognized sections, such as Radula and Schilleria [51]. A recent phylogenetic analysis including many species native to Brazil places P. gaudichaudianum and P. malacophyllum in section Radula, while P. regnellii belongs to section Schilleria (unpublished results). The close relationship between P. gaudichaudianum and P. malacophyllum may account for the difficulty at attaining separate and strongly supported clades for these two species using sequences of some genomic regions, such as rbcL (S5 Fig). The phylogeny based on trnH-psbA suggests the possibility that this marker might be a useful barcode for P. malacophyllum (S4 Fig); however, only a small subset of the samples included in this study amplified and sequenced successfully so the sample size presented here is too small to draw a definite conclusion. Although the combination of sequences from several genomic regions often improves resolution and clade support in phylogenetic analysis [52], our results indicate that no gain of resolution or BS support is attained with the combination of sequences of the DNA regions used in this study (Fig 4 and S7 Fig).
Transferability of the SSR markers using Psol primers were successful for P. gaudichaudianum and P. regnellii, but no amplified SSR segments were obtained from P. malacophyllum. SSR markers have been useful for evaluation of genetic diversity and establishment of affinity relationships among species of Piper, including P. solmsianum [35], P. nigrum [53] and P. polysyphonum C. DC. [54]. Results of preliminary cluster analysis based on polymorphisms of amplified products obtained with transferred SSR markers are shown on Fig 5a–5c. The number of polymorphic characters obtained is still too small to be confidently used as barcodes, which precludes any conclusion about the possibility of distinguishing the three species based on the transferred SSR markers. However, comparing the topologies of the dendrograms obtained, it appears that Psol 6 and Psol 10 (Fig 5b and 5c, respectively) may hold more promise for distinguishing Piper species than Psol 3 (Fig 5a). Further study is necessary to thorough evaluate Psol primers for delimiting and distinguishing among Piper species.
The phytochemistry of species P. gaudichaudianum, P. malacophyllum and P. regnellii have been investigated. While P. gaudichaudianum was characterized by the presence of prenylated benzoic acids such as gaudichaudianic acid [55] and taboganic acid [56], P. malacophyllum was shown to contain piperolides, a specific type of polyketide [6]. The chemistry of P. regnellii was shown to contain dihydrobenzofuran neolignans exemplified as conocarpan, eupomatenoids and phenylpropanoids [57–58]. The close phylogenetic relationship between P. gaudichaudianum and P. malacophyllum is not reflected in the secondary chemical profiles of these species.
The molecular markers used in the present study may be useful for a variety of biological and economic applications, such as species identification, even in the absence of flowers and fruits, which are necessary for accurate identification of many Piper species [59–60], authentication and quality control of medicinal plants [14], as well as quality control in analyses of food safety [32], as support for studies of chemical variability and for accurate understanding of ecological relationships [61]. Thus, the development of tools to accurately identify species in the large, complicated, and economically important genus Piper is of great interest.
Conclusions
Sequences of ITS2 enabled delimitation of the three Piper species and provided a high degree of intraspecific stability. Analyses based on trnH-psbA, rbcL and combination of both sequences were successful at grouping populations of P. regnellii, but not of P. gaudichaudianum. Transferability of SSR Psol primers is feasible for P. gaudichaudianum and P. regnellii. Preliminary analysis suggests that barcoding of Piper species based on polymorphisms of Psol microsatellites holds promise.
Supporting information
S1 Fig. Raw gel electrophoresis photograph of DNA and PCR products in the ITS2, trnH-psbA and rbcL region detected by 2% agarose.
LaneM: 1Kb Plus DNA Ladder; Lane1-19: representative samples of P. gaudichaudianum, P. malacophyllum and P. regnellii.
https://doi.org/10.1371/journal.pone.0239056.s001
(TIF)
S2 Fig. Histograms of frequencies (y-axes) of pairwise intraspecific (grey bars) and interspecific (black bars) divergences based on p-distances (x-axes) for individual and combined ITS2, trnH-psbA, and rbcL markers for P. regnellii.
A: ITS2; B: trnH-psbA; C: rbcL; D: ITS2+trnH-psbA; E: ITS2+trnH-psbA+rbcL.
https://doi.org/10.1371/journal.pone.0239056.s002
(TIF)
S3 Fig. Histograms of frequencies (y-axes) of pairwise intraspecific (grey bars) and interspecific (black bars) divergences based on p-distances (x-axes) for individual and combined ITS2, trnH-psbA, and rbcL markers for P. gaudichaudianum.
A: ITS2; B: trnH-psbA; C: rbcL; D: ITS2+trnH-psbA; E: ITS2+trnH-psbA+rbcL.
https://doi.org/10.1371/journal.pone.0239056.s003
(TIF)
S4 Fig. Strict consensus tree based on sequences of trnH-psbA of Piper species, based on maximum parsimony.
Bootstrap support values above 50% are shown above branches. USP, Int: population of Piper species from University of São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
https://doi.org/10.1371/journal.pone.0239056.s004
(TIF)
S5 Fig. Strict consensus tree based on sequences of rbcL of Piper species, based on maximum parsimony.
Bootstrap support values above 50% are shown above branches. USP, Int: population of Piper species from University of São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
https://doi.org/10.1371/journal.pone.0239056.s005
(TIF)
S6 Fig. Strict consensus trees based on combined sequences of trnH-psbA+rbcL of Piper species, based on maximum parsimony.
Bootstrap support values above 50% are shown above branches. USP, Int: population of Piper species from University of São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
https://doi.org/10.1371/journal.pone.0239056.s006
(TIF)
S7 Fig. Strict consensus trees based on combined sequences of ITS2+trnH-psbA+rbcL of Piper species, based on maximum parsimony.
Bootstrap support values above 50% are shown above branches. USP, Int: population of Piper species from University of São Paulo and Intervales State Park (Ribeirão Grande, São Paulo State), respectively.
https://doi.org/10.1371/journal.pone.0239056.s007
(TIF)
S1 Table. International nucleotide sequence database collaboration GenBank.
(-) Indicates no sequence obtained.
https://doi.org/10.1371/journal.pone.0239056.s008
(DOCX)
References
- 1.
Callejas Posada R. Piperaceae. In: Davidse G, Ulloa Ulloa C, Hernández Macías HM, Knapp S. (Eds.) Flora Mesoamericana. St. Louis: Missouri Botanical Garden Press. 2020; 2 (2): pp. i–xix; 1–590.
- 2. Quijano-April MA, Callejas-Posada R, Miranda-Esquivel DR. Areas of endemism and distribution patterns for Neotropical Piper species (Piperaceae). J Biogeogr. 2006; 33:1266–1278.
- 3. Wanke S, Samain MS, Vanderschaeve L, Mathieu G, Goetghebeur P, Neinhuis C. Phylogeny of the genus Peperomia (Piperaceae) inferred from the trnK/matK region (cpDNA). Plant Biol. 2006; 8:93–102. pmid:16435273
- 4. Ooi SL, Henderson P, Pak SC. Kava for generalized anxiety disorder: a review of current evidence. J Altern Compl Med. 2018; 24(8):770–780.
- 5.
Di Stasi LC, Hiruma-Lima CA. Plantas medicinais na Amazônia e na Mata Atlântica. 2st ed. São Paulo: Editora UNESP; 2002.
- 6. Lago JHG, Tanizaki TM, Young MCM, Guimaraes EF, Kato MJ. Antifungal piperolides from Piper malacophyllum (Prels) C.DC. J Braz Chem Soc. 2005; 16:153–156.
- 7. Morandim-Giannetti AA, Pin AR, Santo Pietro NA, Oliveira HC, Mendes-Gianni MJ, et al. Composition and antifungal activity against Candida albicans, Candida parapsilosis, Candida kruzei and Cryptococcus neoformans of essential oils from leaves of Piper and Peperomia species. J Med Pl Res. 2011; 4:1810–4
- 8. Pessini GL, Dias Filho BP, Nakamura CV, Cortez DA. Antifungal activity of the extracts and neolignans from Piper regnellii (Miq.) D.DC. var. pallescens (C.DC.) Yunck. J Braz Chem Soc. 2005; 16:1130–3
- 9. Hebert PDN, Gregory TR. The promise of DNA barcoding for taxonomy. Syst Biol. 2005; 54:852–859. pmid:16243770
- 10. Kress WJ, Erickson DL. A two-locus global DNA barcode for land plants: the coding rbcL gene complements the non-coding trnH-psbA spacer region. PLoS ONE. 2007; 2(6):e508. https://doi.org/10.1371/journal.pone.0000508 pmid:17551588
- 11. Ratnasingham S, Hebert PDN. BOLD: The Barcode of Life Data System (www.barcodinglife.org). Mol Ecol Notes. 2007; 7:355–364. pmid:18784790
- 12. Kress WJ, Wurdack KJ, Zimmer EA, Weigt LA, Janzen DH. Use of DNA barcodes to identify flowering plants. Proc Natl Acad Sci USA. 2005; 102(23):8369–8374. pmid:15928076
- 13. Vijayan K, Tsou CH. DNA barcoding in plants: taxonomy in a new perspective. Curr Sci. 2010; 99(11):1530–1541.
- 14. Li M, Cao H, But PPH, Shaw PC. Identification of herbal medicinal materials using DNA barcodes. J Syst Evol. 2011; 49(3):271–283.
- 15. Hebert PDN, Cywinska NA, Ball SL, Waard JR. Biological identifications through DNA barcodes. Proc Roy Soc Lond B Biol Sci. 2003; 270:313–321.
- 16. Kress WJ. Plant DNA barcodes: Applications today and in the future. J Syst Evol. 2017; 55(4):291–307.
- 17. Bafeel SO, Arif IA, Bakir MA, Al Homaidan AA, Al Farhan AH, Khan HA. DNA barcoding of arid wild plants using rbcL gene sequences. Genet Mol Res. 2012; 11:1934–41. pmid:22869548
- 18. CBOL—Plant Working Group. A DNA barcode for land plants. Proc Natl Acad Sci. 2009; 106(31):12794–12797. pmid:19666622
- 19. Hollingsworth ML, Andra Clark A, Forrest LL, Richardson J, Pennington R, Long DG, et al. Selecting barcoding loci for plants: evaluation of seven candidate loci with species-level sampling in three divergent groups of land plants. Mol Ecol Res. 2009; 9:439–457.
- 20. Ma XY, Xie CX, Liu C, Song JY, Yao H, Luo K, et al. Species identification of medicinal pteridophytes by a DNA barcode marker, the chloroplast trnH-psbA intergenic region. Biol Pharm Bull. 2010; 33(11):1919–1924. pmid:21048323
- 21. Sass C, Little DP, Stevensonm DW, Specht CD. DNA Barcoding in the Cycadales: Testing the potential of proposed barcoding markers for species identification of cycads. PLoS ONE. 2007; 2(11): e1154. https://doi.org/10.1371/journal.pone.0001154 pmid:17987130
- 22. Gao T, Yao H, Song JY, Liu C, Zhu YJ, Zhu Y, et al. Identification of medicinal plants in the family Fabaceae using a potential DNA barcode ITS2. J Ethnopharmacol. 2010; 130:116–121. pmid:20435122
- 23. Yu N, Gu H, Wei Y, Zhu N, Wang Y, Zhang H, et al. Suitable DNA barcoding for identification and supervision of Piper kadsura in Chinese medicine markets. Molecules. 2016; 21(9): 1221. https://doi.org/10.3390/molecules21091221
- 24. Parvathy VA, Swetha VP, Sheeja TE, Sasikumar B. A two locus barcode for discriminating Piper nigrum from its related adulterant species. Indian J Biotechnol. 2018; 17(2):346–350.
- 25. Chaveerach A, Tanee T, Sanubol A, Monkheang P, Sudmoon R. Efficient DNA barcode regions for classifying Piper species (Piperaceae). PhytoKeys. 2016; 70:1–10.
- 26. Akkaya MS, Bhagwat AA, Cregan PB. Length polymorphisms of simple sequence repeat DNA in soybean. Genet. 1992; 132(4):113–39.
- 27. Hayashi K, Hashimoto N, Daigen M, Ashikawa I. Development of PCR-based SNP markers for rice. Theor Appl Genet. 2004; 108(7):1212–1220 pmid:14740086
- 28. Ghebru B, Schmidt RJ, Bennetzen JL. Genetic diversity of Eritrean sorghum landraces assessed with simple sequence repeats (SSR) markers. Theor Appl Genet. 2002; 105:229–236. pmid:12582524
- 29. Ganie SH, Upadhyay P, Das S, Sharma MP. Authentication of medicinal plants by DNA markers. Plant Gene. 2015; 4:83–99 pmid:32289060
- 30. Shirasawa K, Ishii K, Kim C, Ban T, Suzuki M, Ito T, et al. Development of Capsicum EST–SSR markers for species identification and in silico mapping onto the tomato genome sequence. Mol Breed. 2013; 31:101–110. pmid:23316112
- 31. Hon CC, Chow YC, Zeng FY, Leung FC. Genetic authentication of ginseng and other traditional Chinese medicine. Acta Pharm Sin. 2003; 24:841–846.
- 32. Bosmali I, Ganopoulos I, Madesis P, Tsaftaris A. Microsatellite and DNA-barcode regions typing combined with high resolution melting (HRM) analysis for food forensic uses: a case study on lentils (Lens culinaris). Food Res Int. 2012; 46(1):141–147.
- 33. Joy N, Prasanth VP, Soniya EV. Microsatellite based analysis of genetic diversity of popular black pepper genotypes in South India. Genet. 2011;139(8):1033–43. pmid:21874534
- 34. Vandenbroucke H, Mournet P, Malapa R, Glaszmann JC, Chaïr H, Lebot V. Comparative analysis of genetic variation in kava (Piper methysticum) assessed by SSR and DArT reveals zygotic foundation and clonal diversification. Genome. 2015; 58(1):1–11. pmid:25973616
- 35. Yoshida NC, Lima PF, Priolli RH, Kato M, Colombo CA. Isolation and characterization of nine polymorphic microsatellite loci in Piper solmsianum (Piperaceae). Appl Plant Sci. 2014; 2(4). https://doi.org/10.3732/apps.1300092
- 36. Christ JA, Hollunder RK, Carvalho MS, Ferreira MFDS, Garbin ML, Carrijo TT. DNA fingerprinting based on SSR amplification profiles for Piper species identification (Piperaceae). Acta Bot Bras. 2018; 32(4):511–520.
- 37. Kuleung C, Baenziger PS, Dweikat I. Transferability of SSR markers among wheat, rye, and triticale. Theor Appl Genet. 2004; 108(6):1147–1150. pmid:15067402
- 38. Matsuoka Y, Mitchell SE, Kresovich S, Goodman M, Doebley J. Microsatellites in Zea–variability, patterns of mutations, and use for evolutionary studies. Theor Appl Genet. 2002; 104(2–3):436–450. pmid:12582717
- 39. Gürcan K, Mehlenbacher SA. Transferability of microsatellite markers in the Betulaceae. J Am Soc Horticult Sci. 2010; 135(2):159–173.
- 40. Nazareno AG, Pereira RAS, Feres JM, Mestriner MA, Alzate-Marin AL. Transferability and characterization of microsatellite markers in two Neotropical Ficus species. Gen Mol Biol. 2009; 32(3):568–571.
- 41. Guo ZH, Fu KX, Zhang XQ, Zhang CL, Sun M, Huang T, et al. SSRs transferability and genetic diversity of three allogamous ryegrass species. C R Biol. 2016; 339(2):60–67. pmid:26874459
- 42. Huang L, Wu B, Zhao J, Li H, Chen W, Zheng Y, et al. Characterization and transferable utility of microsatellite markers in the wild and cultivated Arachis species. PLoS ONE. 2016; 11(5): e0156633. https://doi.org/10.1371/journal.pone.015663 pmid:27243460
- 43. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res.1994; 22:4673–4680. pmid:7984417
- 44.
Fazekas AJ, Kuzmina ML, Newmaster SG, Hollingsworth PM. DNA barcoding methods for land plants. In: Kress W, Erickson D. DNA Barcodes. Methods in Molecular Biology (Methods and Protocols). Totowa: Humana Press; 2012. pp. 223–252.
- 45. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004; 32(5):1792–97. pmid:15034147
- 46. Ebihara A, Nitta JH, Ito M. Molecular species identification with rich floristic sampling: DNA Barcoding the Pteridophyte flora of Japan. PLoS ONE. 2010; 5(12): e15136. https://doi.org/10.1371/journal.pone.0015136 pmid:21170336
- 47. Tamura K, Peterson D, Peterson N, Stecher G, Nei M. MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Mol Biol Evol. 2011; 28(10):2731–9. pmid:21546353
- 48.
Hall BG. Phylogenetic trees made easy: A how-to manual. 4st ed. Sunderland, Massachusetts: Sinauer Associates; 2011.
- 49. Felsenstein J. Confidence-limits on phylogenies—an approach using the bootstrap. Evol. 1985; 39:783–791.
- 50. Pirie MD, Chatrou LW, Mols JB, Erkens RJ, Oosterhof J. Andean-centred’ genera in the shor-branch clade of Annonaceae: testing biogeographical hypotheses using phylogeny reconstruction and molecular dating. J Biogeogr. 2006; 33(1):31–46.
- 51. Jaramillo MA, Callejas R, Davidson C, Smith JF, Stevens AC, Tepe EJ. A phylogeny of the Tropica genus Piper using ITS and the chloroplast intron psbJ-petA. Syst Bot. 2008; 33(4):647–660.
- 52. Kang Y, Deng Z, Zang R, Long W. DNA barcoding analysis and phylogenetic relationships of tree species in tropical cloud forest. Sci Rep. 2017; (7):12564.
- 53. Menezes IC, Cidade FW, Souza AP, Sampaio IC. Isolation and characterization of microsatellite loci in the black pepper, Piper nigrum L. (Piperaceae). Conserv Genet Resour. 2009; (1):209–212.
- 54. Liao PC, Gong X, Shih HC, Chiang YC. Isolation and characterization of eleven polymorphic microsatellite loci from an endemic species, Piper polysyphonum (Piperaceae). Conserv Genet. 2009; 10(6):1911.
- 55. Lago JHG, Ramos CS, Casanova DCC, Morandim AD, Bergamo DCB, et al. Benzoic acid derivatives from Piper species and their fungitoxic activity against Cladosporium cladosporioides and C. sphaerospermum. J Nat Prod. 2004; 67:1783–1788. pmid:15568762
- 56. Ramos CS, Vanin SA, Kato MJ. Sequestration of prenylated benzoic acid and chromenes by Naupactus bipes (Coleoptera: Curculionidae) feeding on Piper gaudichaudianum (Piperaceae). Chemoecology. 2009; 19:73–80.
- 57. Benevides PJC, Sartorelli P, Kato MJ. Phenylpropanoids and neolignans from Piper regnellii. Phytochemistry. 1999; 52:339–343.
- 58. Garcia FP, Lazarin-Bidóia D, Ueda-Nakamura T, Silva SDO, Nakamura CV. Eupomatenoid-5 isolated from leaves of Piper regnellii induces apoptosis in Leishmania amazonensis. Evid Based Complement Alternat Med. 2013; 940531. pmid:23573160
- 59. Asif MJ, Cannon CH. DNA extraction from processed wood: a case study for the identification of an endangered timber species (Gonystylus bancanus). Plant Mol Biol Rep. 2005; 23(2):185–192.
- 60. Aubriot X, Lowry PP, Cruaud C, Couloux A, Haevermans T. DNA barcoding in a biodiversity hot spot: potential value for the identification of Malagasy Euphorbia L. listed in CITES Appendices I and II. Mol Ecology Resour. 2013; 13(1):57–65.
- 61. Tepe EJ, Rodríguez-Castañeda G, Glassmire AE, Dyer LA. Piper kelleyi, a hotspot of ecological interactions and a new species from Ecuador and Peru. Phytokeys. 2014; 34:19–32.