Illegal trade is considered one of the greatest threats to the loss of biodiversity of endangered plants. Some of these plant species are often trafficked in processed forms, making it extremely difficult for taxonomic experts to identify them. In the past, illegal traders of endangered species have been arrested and prosecuted but eventually cleared due to a lack of conclusive evidence. DNA barcoding is a veritable tool to protect these endangered species from illegal trade. It identifies all stages of the species’ life forms including processed products (milled or powdered animal and plant parts). The study util
ised the rbcL gene as a single barcode region in the identification/authentication of 19 Nigeria’s endangered forest species legislated under the CITES and other endangered species of national interest. The generated sequence barcodes were used to query NCBI-GenBank and BOLD databases. 57.89% of the samples were identified down to species level and 42.11% to genus level. Amongst the 19 samples, sample (S7) yielded a high-quality sequence for a single sequencing read (forward), sufficient to identify the sample with a 99.81% identity match on NCBI-GenBank and BOLD. The results reveal that the
rbcL single barcode efficiently identified most of the sampled plants; this supports the potential utilisation of DNA barcoding in the accurate detection and conservation of CITES-listed plants in Nigeria. The study documented the CITES-listed plants and other essential plants endangered or threatened plants in Nigeria and provided the first chloroplast DNA reference dataset to support the utilisation of DNA barcoding to identify CITES-listed plant species in Nigeria, which is significant for future studies.
Annonaceae Apocynaceae BOLD CITES DNA Barcoding NCBI <i>rbcL</i>1. Introduction
Land plants make up a large percentage of life diversity on earth, consisting of seed plants (angiosperms and gymnosperms), bryophytes, ferns and lilies, estimated at over 380,000 species [1] [2] [3]. It has been estimated that there are 352,000 species of angiosperms, 1300 species of gymnosperms and 13,000 species of bryophytes. During the last century, decreases in biodiversity have been increasingly observed. The Food and Agriculture Organization of the United Nations [4] reported the loss of 75% of the genetic diversity of crops, and according to Royal Botanic Gardens Kew [5], about one-fifth of known plant species are threatened with extinction. Nigeria is rich in bioresources and the distribution of biodiversity. This is shown by a broad range of habitats, starting from the Gulf of Guinea along the Atlantic coast, consisting of aquatic and non-aquatic organisms found in different ecological areas [6]. However, the country’s biodiversity are being threatened by various factors, which include but are not limited to anthropogenic activities and climate change effects.
As reported in the 2013 IUCN’s Red List, Nigeria’s threatened species are 309. The taxonomic categories include twenty-six mammals, nineteen birds, eight reptiles, thirteen amphibians, sixty fishes, a mollusc, fourteen other invertebrates and one hundred and sixty-eight plants [7]. Also, Nigeria Federal Environmental Protection Agency [8] reported that Nigeria has over 5000 recorded species of plants. It is estimated that 0.4% of the plant species are threatened, and 8.5% are endangered and close to becoming extinct due to poaching, climate change, urbanisation and industrialisation. According to Borokini [9], 91 species of Nigerian plants are endemic, and they belong to 44 families, with Rubiaceae attributing to the majority. Conservation scientists opine that serious consideration should be aimed at rescuing the remnants of the significant zones for biodiversity in the nation. Furthermore, there is a common agreement on where the outstanding node of biodiversity exists in Nigeria. The first level of feat is proper identification and documentation (Federal Ministry of Environment [10]). How fast this can be achieved will depend on the county’s capability, capacity and willpower to apply and deploy scientific advances such as DNA barcoding.
According to Convention on Biological Diversity [11], the global conservation strategy deems genes, species and ecosystem as prospective tools for sustaining biodiversity ecosystems conservation. Species identification is essential in assessing the level of biodiversity that appraises species diversity for conservation and management efforts [12] [13]. Fast and accurate plant species identification is vital in almost all plant-based research, including biodiversity studies. To protect global biodiversity from poaching and international trade abuse, countries of the world signed a treaty on March 3 1973, known as the Convention on International Trade on Endangered Species of Wild Fauna and Flora (CITES), for regulating trade in endangered species across the border. Protected species are classified in CITES Appendices I, II, and III, in accordance with how a particular populace is being threatened by extinction (Convention on the International Trade in Endangered Species of Wild Fauna and Flora [14]). Species listed in CITES Appendix I are illegal for international trade except for research. However, foreign trade could be approved by appropriate agencies of the nations affected by the import and export. Species listed in Appendix II of CITES are not yet threatened by extinction but may soon become unless their trade is checked [6].
Nigeria has over two hundred plants and animal species listed in the CITES, almost half of which are plants and most of which belong to Orchidaceae, Fabaceae, Euphorbiaceae families and Cycadaceae [15]. Most of the endangered land plants are located in the country’s various hard-to-reach protected forest reserves, from where some of the samples used in this study were collected. For adequate protection from illegal trade/over-exploitation for conservation purposes, there is a need for proper identification of the plants and authentication of same using DNA barcoding technique. The technique has been extensively utilised for several purposes and documented as a resurgence for taxonomy (Kress, 2017; Yu et al., 2021). DNA barcoding has also been applied in disease and pest control, market fraud detection and protection of endangered species from poachers and illegal international trade [16] [17]. Globally, there are ongoing initiatives to produce DNA barcodes for all assemblages of living organisms and the public availability of these information to comprehend, conserve, and use the world’s biodiversity [18]. For instance, Pathak et al. [19] reported using DNA barcoding in identifying 29 medicinal plants in the kingdom of Bahrain, while Lv et al. [20] identified herbal plants in the Apocynaceae family using DNA barcodes.
A DNA barcode is a genetic signature occurring naturally within every living species’ genome [21]. Mitochondrial cytochrome oxidase 1 gene (CO1) has been found effective in identifying animal groups, including birds, flies, butterflies and fish [22]; however, CO1 is ineffective for land plants. In the plastid region of land plants, the regions commonly used are two gene regions in the chloroplast, matK and Ribulose-1,5-bisphosphate carboxylase large subunit (rbcL), with two additional regions,trnH-psbA and internal transcribed spacer (ITS) or (ITS2) [23]. Jamdade et al. [24] assessed the ability of ITS2, rbcL and matK in classifying 20 key plant species of Caryophyllales and found that ITS2 was more effective in distinguishing between studied species. Lone et al. [25] investigated the use of ITS,rbcL, trnH-psbA and matK markers in identifying Epimedium elatum, a rare medicinal plant in the Himalayas, India and revealed highest polymorphic sites in ITS and matK. However, Negi et al. [26] identified rbcL as a potential marker to curb illicit trade of medicinal plants, Aconitum heterophyllum and Aconitum balfourii. Also, Ho et al. [27], in comparing the effectiveness of rbcL and matK DNA barcodes in the classification of Jewel orchid in Vietnam, disclosed rbcL gene has higher characteristic potential than matK.
This paper presents the first report of Nigeria’s Barcode of Wildlife—Plant Working Group (BWP-PWG) to protect the endangered flora species listed under CITES from poaching and illegal trading using DNA barcoding.
2. Materials and Methods2.1. Sample Collection
Tools and materials used for the sample collection include Pair of secateurs, silica gel, machete and knife, polythene bag, hand lenses, a hardcover waterproof notebook, transparent rulers, plant presses, FluidX tubes, personal protective wear and a GPS device. Samples were collected as fresh as possible from the field and not touched with bare hands to avoid contamination. Young, fresh, flexible and non-waxy leaves, about 5 to 10 cm2 in size, were chosen and stored in paper envelopes under relatively dry climatic conditions. The envelopes were assigned the same number as the plant specimen from which the leaves were collected, and the general rule is one plant per number. The number given to each plant is unique, written on a tag tied to the collected plant, and the replicates bear the same number. The samples were later transferred into FluidX tubes with unique barcodes containing silica gel. The ratio of the silica gel to leaf tissue was 5 - 10:1. Information, such as the GPS location, plant’s taxonomic name, tissue barcode number and habitat, was recorded and presented in Table 1.
2.2. DNA Extraction
According to the manufacturer’s protocol, the extraction of genomic DNA from the samples was done using a modified DNA extraction kit (DNeasy plant mini kit, QIAGEN). Geno-grinder (2000, SPEX Inc.) was utilised to grind the lyophilised plant tissues, after which 20 mg of each plant tissue was put into distinctly labelled micro-centrifuge tubes. Approximately 400 µl of Buffer AP1 and 4 µl of RNase A stock solution (100 mg/ml) were added to each tube containing the powdered tissue. The mixtures were incubated in a water bath for 10 min at 65˚C. The tubes were homogenised 2 - 3 times by inverting tubes while incubating. Additionally, 130 µl of Buffer AP2 was added to the lysates, stirred, and incubated on ice for 5 min. Centrifuging of the lysates for 5 min at 14,000 rpm was made, and the supernatants were transferred to QIAshredder spin columns sitting in 2 ml collection tubes and centrifuged for 2 min at 14,000 rpm. The flow-through was moved to well-labelled micro-centrifuge tubes. About 1.5 volume of Buffer AP3/E was put into the cleared lysates and homogenised by pipetting.
Consequently, pipetting of 650 µl of the mixture into DNeasy mini spin columns sitting in 2 ml collection tubes was executed and centrifuged for 1 min at ≥6000 × g. Then, the filtrate was removed, and the spin columns returned to the
Samples field collection data
Sample ID
Taxonomic ID
Family
Tissue barcode
States collected
Locality
Decimal latitude
Decimal longitude
S1
Funtumia elastica
Apocynaceae
FR04499552
Ogun
Omo Biosphere Reserve, Etemi
6.975361
4.366111
S2
Ficus exasperata
Moraceae
FR04499555
Ogun
Omo Biosphere Reserve, Etemi
6.979333
4.371944
S3
Kigelia Africana
Bignoniaceae
FR04499557
Osun
Sasa
7.089556
4.350306
S4
Diospyros mespiliformis
Ebenaceae
FR04499559
Oyo
Ebuya, Old Oyo National Park
8.485583
3.758833
S5
Lophira lanceolata
Ochnaceae
FR04499560
Oyo
Ebuya, Old Oyo National Park
8.486889
3.758
S6
Aframomum sceptrum
Zingiberaceae
FR04499565
Oyo
Ebuya, Old Oyo National Park
8.486167
3.7565
S7
Afzelia Africana
Fabaceae
FR04499569
Oyo
Ebuya, Old Oyo National Park
8.487222
3.757444
S8
Annona senegalensis
Annonaceae
FR04499570
Oyo
Ebuya, Old Oyo National Park
8.487113
3.757417
S9
Annona muricata
Annonaceae
FR04499573
Oyo
Sepeteri
8.623306
3.645861
S10
Albizia zygia
Fabaceae
FR04499578
Osun
Abataju village, Oke-Odo, Ikire
7.383444
4.230056
S11
Gongronema latifolium
Apocynaceae
FR04499581
Osun
Abataju village, Oke-Odo
7.384222
4.230389
S12
Funtumia africana
Apocynaceae
FR04499582
Osun
Abataju village, Oke-Odo
7.384417
4.230528
S13
Garcinia kola
Clusiaceae
FR04499583
Osun
Abataju village, Oke-Odo
7.387944
4.229056
S14
Lophira alata
Ochnaceae
FR04499588
Edo
Arakwan, Okomu National Park
6.34225
5.361028
S15
Khaya ivorensis
Meliaceae
FR04499589
Edo
Arakwan, Okomu National Park
6.343
5.360167
S16
Diospyros piscatoria
Ebenaceae
FR04499595
Edo
Arakwan, Okomu National Park
6.349417
5.343083
S17
Monodora tenuifolia
Annonaceae
FR04499597
Oyo
Microbiology dept, University of Ibadan
7.442778
3.897139
S18
Momordica charantia
Cucurbitaceae
FR04499542
Oyo
FRIN arboretum
7.391694
3.85775
S19
Entandrophragma angolense
Meliaceae
FR04499544
Oyo
FRIN premises, opposite FHI
7.39175
3.863028
collection tubes. A repeat of this phase was made for the residual. About 500 µl of Buffer AW was put into the DNeasy columns, inserted in new 2 ml collection tubes and centrifuged for 1 min at ≥6000 × g (≥8000 rpm). Then, the filtrate was thrown away, and 500 µl of Buffer AW was put into the DNeasy columns and centrifuged for 2 minutes at the highest rate for drying the membrane. Transfer of the DNeasy columns was made to 1.5 ml micro-centrifuge tubes, and 200 µl of preheated (65˚C) Buffer AE was put into the DNeasy membrane directly. They were incubated for 5 minutes at room temperature, after which centrifugation was done at ≥6000 × g (≥8000 rpm) for 1 minute for elution. The quality and concentration of DNA were determined using 2 µl of the diluted DNA sample on 1% agarose gel. DNA’s quantity was measured with a Nanodrop spectrophotometer (2000/2000c, Thermo Scientific Inc.).
PCR was evaluated using a 25 µl cocktail made up of genomic DNA—100 ng, 10× PCR buffer—2.5 µl, 50 mM MgCl2—1 µl, 2.5 mM dNTPs—2 µl, Taq polymerase—0.1 µl, DMSO—1 µl, forward and reverse primer—1 µl each and H2O—11.3 µl. The gene region targeted and primer sequenced used are shown in Table 2. Amplification was performed using touch-down PCR as follows: an initial denaturation step of 5 mins at 94˚C, followed by nine cycles, each consisting of a denaturation step of 20 sec at 94˚C, an annealing step of 30 sec at 65˚C, and an extension step of 72˚C for 45 sec, this is followed by another 30 cycles each consisting of a denaturation step of 20 sec at 94˚C, annealing step of 30 sec at 55˚C, and an extension step of 72˚C for 45 sec. All amplification reactions were conducted in a GeneAmp PCR (Applied Biosystems). PCR amplicons were loaded on 1.5% agarose gel and ran at 100 volts for 2 hours.
2.4. Sequencing
The amplified products were used to select the amplicons with a single band and were purified according to the company’s protocol (Cat. No.28106, QIAquick PCR Purification Kit). Afterwards, sequencing was executed using a sequencing kit (BigDye terminator cycle, Applied BioSystems). With ethanol EDTA solution,
Gene region targeted and primer sequences used
Gene and Region
Name of Primer
Primer Sequence 5' - 3'
Direction
Reference
Expected band size (bp)
rbcL
rbcLaf
ATGTCACCACAAACAGAGACTAAAGC
F
Levin et al. [28] modified from
750
Soltis et al. [29]
rbcLarev
GTAAAATCAAGTCCACCRCG
R
Kress and Erickson [30] modified from
Fofana et al. [31]
unincorporated dye terminators were cleaned and precipitated. Furthermore, the pellets were dissolved in HiDi formaldehyde buffer (Cat No. 4311320, Applied Biosystems). Finally, a Genetic Analyser (3130xl, Applied Biosystems) was used to complete the sequencing, and the obtained sequence trace files were uploaded to the open-access DNA Subway software, following the guidelines reported by Goff et al. [32] and Merchant et al. [33]. The DNA sequences were analysed on the Blue Line of the DNA Subway.
The sequences were trimmed and viewed, and the forward and reverse sequences were manually edited and then paired to construct a consensus sequence. In case(s) where the forward and reverse sequence could not be merged to generate a consensus sequence, only the readable barcode sequence was utilised in the subsequent analysis due to the poor quality. The consensus sequences were exported for downstream analysis on NCBI-GenBank [34] and BOLD [35]. The samples were recognised based on the maximum percentage identity score. In cases where NCBI GenBank and BOLD searches returned identical identifications, the samples were considered at least to the genus level. The generated sequence barcodes were translated to amino acid sequences using the EMBOSS Transeq web tool of the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) to determine their suitable open reading frame. The sequences were later tendered to NCBI-GenBank, and their accession numbers were obtained, as shown in Table 3.
3. Results
This study tested the effectiveness of DNA barcoding to authenticate sampled CITES-listed land plants in Nigeria. Following the Nigerian plants CITES list created by the Barcode of Wildlife Nigeria-Plant Working Group in 2014, nineteen (19) plants in twelve (12) families belonging to Annonaceae and Apocynaceae families were sampled (Table 1). Extraction of DNA from all the samples was followed by PCR amplification of the rbcL barcode region. All the samples were successfully amplified. The PCR products, which were bidirectionally sequenced, produced a good sequence of at least 500 bp in length for both directions, with fewer nucleotide ambiguities. However, sample (S7) yielded a high-quality sequence for a single sequencing read (forward), sufficient to identify the sample with a 99.81% identity match on NCBI-GenBank and BOLD.
GenBank and BOLD comparison authenticated the identity of all the plant samples. Although DNA Subway’s local nucleotide database allows a rapid search, it has limitations [36]. Based on this fact, GenBank and BOLD were employed in identifying the samples, of which 57.89% were identified at the species level, and 42.11% were identified only at the genus level. The top BLAST result was evaluated with the highest percent identity score for all sequences. In the case of a tie between two identity scores, the lowest e-value was used as a deciding factor. If there were identical e-values and identity scores for multiple species, the individuals were only identified to the genus level to avoid taxonomic misidentification.
Blast output of the generated rbcL sequences of the sampled species
Sample number
Taxonomic ID
GenBank ID
Percentage identity
BOLD ID
Percentage Identity
Accession number
S1
Funtumia elastica
Funtumia elastic
99.82
Funtumia elastica
100
MT385762
S2
Ficus exasperate
Ficus hirta
99.83
Ficus carica
99.83
MT385771
S3
Kigelia Africana
Kigelia africana
99.46
Kigelia africana
99.47
MT385758
S4
Diospyros mespiliformis
Diospyros mespiliformis
100
Diospyros melanoxylon
100
MT385755
S5
Lophira lanceolata
Lophira lanceolata
100
Lophira lanceolata
100
MT385763
S6
Aframomum septrum
Aframomum angustifolium
99.09
Aframomum sp.
99.63
MT385764
S7
Afzelia Africana
Afzelia africana
99.81
Afzelia africana
99.81
MT385760
S8
Annona senegalensis
Annona senegalensis
99.47
Annona senegalensis
99.46
MT385759
S9
Annona muricate
Annona muricata
99.24
Annona muricata
99.81
MT385765
S10
Albizia zygia
Albizia chevalieri
100
Albizia lebbeck
98.67
MT385766
S11
Gongronema latifolium
Gongronema latifolium
100
Gongronema latifolium
100
MF162300
S12
Funtumia africana
Funtumia elastica
99.44
Funtumia elastica
99.63
MT385760
S13
Garcinia kola
Garcinia sp
99.5
Garcinia sp
100
MT385770
S14
Lophira alata
Lophira lanceolata
100
Lophira lanceolata
100
MT385756
S15
Khaya ivorensis
Khaya madagascariensis
99.53
Khaya nyasica
99.35
MT385766
S16
Diospyros piscatoria
Diospyros gabunensis
98.99
Diospyros gabunensis
98.99
MT385757
S17
Monodora tenuifolia
Monodora tenuifolia
99.82
Monodora tenuifolia
99.82
MT385768
S18
Momordica charantia
Momordica charantia
100
Momordica charantia
100
MT385772
S19
Entandrophragma angolense
Entandrophragma caudatum
99.83
Swietenia macrophylla
98.5
MT385769
4. Discussion
Although no single barcode region has been reported to be suitable for accurate discrimination of all plant taxa [37], the results of this study found the rbcL single barcode as an adequate estimation of species’ identification of most of the sampled tree plants. However, these findings would have to be tested with a much more extensive sample collection. According to Yu et al. [17], although there have been remarkable developments in standardized genetic markers, DNA barcode markers are merged with other biotechnologies, such as spectrum technologies, to achieve improved characterisation outcomes.
One of the complicating factors and limitations in applying DNA barcoding in the fight against the illegal trade of CITES-listed plants is that most of the products are trafficked in parts (like timber) or processed forms, such as traditional herbal medicines composed of more than one ingredient. Such products may contain multiple plant species that can only be analysed accurately if several DNA barcode templates can be sequenced concurrently. Concurrent sequencing is presently effectively achieved by next-generation sequencing (NGS) technology. Coghlan et al. [38] highlighted the effectiveness of metabarcoding in their study of the CITES-listed species contained in diverse traditional Chinese medicine (TCM) samples formulated in capsules, powders, herbal tea and tablets. Their study revealed that some of the TCM products contained CITES-listed species, including Saiga antelope (Saiga tatarica) and the Asian black bear (Ursus thibetanus), as well as some non-listed ingredients and potentially harmful and allergic plants [39].
In conclusion, this study documented the CITES-listed plants and other essential plants endangered or threatened plants in Nigeria. rbcL gene was employed as a single barcode region in the identification/authentication of some of Nigeria’s endangered forest species legislated under CITES. In addition, the study provided the first chloroplast DNA reference dataset to support the utilisation of DNA barcoding to identify CITES-listed plant species in Nigeria, which is significant for future studies.
Acknowledgements
We thank the Consortium for Barcode of Life (CBOL) for supporting Nigeria’s Barcode of Wildlife Project; specifically, Dr David Schindel for effective coordination of the CITES project globally.
Data Accessibility Statement
All data generated during this study are contained in this article. Raw sequence reads are deposited in NCBI GenBank with the following accession numbers; MT385762, MT385771, MT385758, MT385755, MT385763, MT385764, MT385760, MT385759, MT385765, MT385766, MF162300, MT385760, MT385770, MT385756, MT385766, MT385757, MT385768, MT385772, MT385769.
Author Contributions
Christie Oby Onyia: Conceptualization and Principal investigator; Christie Oby Onyia and Obianuju Patience Ilo: Writing—original draft; Chosen Ekene Obih: Investigation and Data analysis; Omokafe Ugbogu and Emmanuel Chukwudi Chukwuma: Fieldwork and Curation; Beatrice Onyinye Ojiego and Paschaleen Soromtochukwu Onyemachi: Research design and methodology; Sunkanmi Saheed Rufai: Fieldwork. All authors read and approved the final manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
Cite this paper
Onyia, C.O., Ilo, O.P., Obih, C.E., Ugbogu, O., Ojiego, B.O., Rufai, S.S., Onyemaechi, P.S. and Chukwuma, E.C. (2022) DNA Barcoding of Nigeria’s Forest Species Listed in CITES and Other Endangered Plant Species of National Interest. American Journal of Plant Sciences, 13, 1335-1346. https://doi.org/10.4236/ajps.2022.1311090
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